Assessing climate change impacts, benefits of mitigation, and uncertainties on major global forest regions under multiple socioeconomic and emissions scenarios

Treesearch

John B Kim; Erwan Monier; Brent Sohngen; G Stephen Pitts; Ray Drapek; James McFarland; Sara Ohrel; Jefferson Cole

2016-01-01

We analyze a set of simulations to assess the impact of climate change on global forests where MC2 dynamic global vegetation model (DGVM) was run with climate simulations from the MIT Integrated Global System Model-Community Atmosphere Model (IGSM-CAM) modeling framework. The core study relies on an ensemble of climate simulations under two emissions scenarios: a...

Integrating Climate Science, Marine Ecology, and Fisheries Economics to Predict the Effects of Climate Change on New England lobster Fisheries

NASA Astrophysics Data System (ADS)

Le Bris, A.; Pershing, A. J.; Holland, D. S.; Mills, K.; Sun, C. H. J.

2016-02-01

The Gulf of Maine and the northwest Atlantic shelf have experienced one of the fastest warming rates of the global ocean over the past decade, and concerns are growing about the long-term sustainability of the fishing industries in the region. The lucrative American lobster fishery occurs over a steep temperature gradient, providing a unique opportunity to evaluate the consequences of climate change and variability on marine socio-ecological systems. This study aims at developing an integrated climate, population dynamics, and fishery economics model to predict consequences of climate change on the American lobster fishery. In this talk, we first describe a mechanistic model that combines life-history theory and a size-spectrum approach to simulate the dynamics of the population. Results show that as temperature increases, early growth rate and predation on small individuals increases, while size-at-maturity, maximum length and predation on large individuals decreases, resulting in a lower recruitment in the southern New-England and higher recruitment in the northern Gulf of Maine. Second, we present an integrated fishery and economic module that links temperature to landings and price through its influence on catchability and abundance. Preliminary results show that temperature is positively correlated with landings and negatively correlated with price in the Gulf of Maine. Finally, we discuss how model simulations under various fishing effort, market and climate scenarios can be used to identify adaptation opportunities to improve the resilience of the fishery to climate change.

Alternative future analysis for assessing the potential impact of climate change on urban landscape dynamics.

PubMed

He, Chunyang; Zhao, Yuanyuan; Huang, Qingxu; Zhang, Qiaofeng; Zhang, Da

2015-11-01

Assessing the impact of climate change on urban landscape dynamics (ULD) is the foundation for adapting to climate change and maintaining urban landscape sustainability. This paper demonstrates an alternative future analysis by coupling a system dynamics (SD) and a cellular automata (CA) model. The potential impact of different climate change scenarios on ULD from 2009 to 2030 was simulated and evaluated in the Beijing-Tianjin-Tangshan megalopolis cluster area (BTT-MCA). The results suggested that the integrated model, which combines the advantages of the SD and CA model, has the strengths of spatial quantification and flexibility. Meanwhile, the results showed that the influence of climate change would become more severe over time. In 2030, the potential urban area affected by climate change will be 343.60-1260.66 km(2) (5.55 -20.37 % of the total urban area, projected by the no-climate-change-effect scenario). Therefore, the effects of climate change should not be neglected when designing and managing urban landscape. Copyright © 2015 Elsevier B.V. All rights reserved.

Climate Sensitivity of the Community Climate System Model, Version 4

DOE PAGES

Bitz, Cecilia M.; Shell, K. M.; Gent, P. R.; ...

2012-05-01

Equilibrium climate sensitivity of the Community Climate System Model Version 4 (CCSM4) is 3.20°C for 1° horizontal resolution in each component. This is about a half degree Celsius higher than in the previous version (CCSM3). The transient climate sensitivity of CCSM4 at 1° resolution is 1.72°C, which is about 0.2°C higher than in CCSM3. These higher climate sensitivities in CCSM4 cannot be explained by the change to a preindustrial baseline climate. We use the radiative kernel technique to show that from CCSM3 to CCSM4, the global mean lapse-rate feedback declines in magnitude, and the shortwave cloud feedback increases. These twomore » warming effects are partially canceled by cooling due to slight decreases in the global mean water-vapor feedback and longwave cloud feedback from CCSM3 to CCSM4. A new formulation of the mixed-layer, slab ocean model in CCSM4 attempts to reproduce the SST and sea ice climatology from an integration with a full-depth ocean, and it is integrated with a dynamic sea ice model. These new features allow an isolation of the influence of ocean dynamical changes on the climate response when comparing integrations with the slab ocean and full-depth ocean. The transient climate response of the full-depth ocean version is 0.54 of the equilibrium climate sensitivity when estimated with the new slab ocean model version for both CCSM3 and CCSM4. We argue the ratio is the same in both versions because they have about the same zonal mean pattern of change in ocean surface heat flux, which broadly resembles the zonal mean pattern of net feedback strength.« less

Recent range expansion of a terrestrial orchid corresponds with climate-driven variation in its population dynamics.

PubMed

van der Meer, Sascha; Jacquemyn, Hans; Carey, Peter D; Jongejans, Eelke

2016-06-01

The population dynamics and distribution limits of plant species are predicted to change as the climate changes. However, it remains unclear to what extent climate variables affect population dynamics, which vital rates are most sensitive to climate change, and whether the same vital rates drive population dynamics in different populations. In this study, we used long-term demographic data from two populations of the terrestrial orchid Himantoglossum hircinum growing at the northern edge of their geographic range to quantify the influence of climate change on demographic vital rates. Integral projection models were constructed to study how climate conditions between 1991 and 2006 affected population dynamics and to assess how projected future climate change will affect the long-term viability of this species. Based on the parameterised vital rate functions and the observed climatic conditions, one of the studied populations had an average population growth rate above 1 (λ = 1.04), while the other was declining at ca. 3 % year(-1) (λ = 0.97). Variation in temperature and precipitation mainly affected population growth through their effect on survival and fecundity. Based on UK Climate Projection 2009 estimates of future climate conditions for three greenhouse gas emission scenarios, population growth rates are expected to increase in one of the studied populations. Overall, our results indicate that the observed changes in climatic conditions appeared to be beneficial to the long-term survival of the species in the UK and suggest that they may have been the driving force behind the current range expansion of H. hircinum in England.

Implementation of malaria dynamic models in municipality level early warning systems in Colombia. Part I: description of study sites.

PubMed

Ruiz, Daniel; Cerón, Viviana; Molina, Adriana M; Quiñónes, Martha L; Jiménez, Mónica M; Ahumada, Martha; Gutiérrez, Patricia; Osorio, Salua; Mantilla, Gilma; Connor, Stephen J; Thomson, Madeleine C

2014-07-01

As part of the Integrated National Adaptation Pilot project and the Integrated Surveillance and Control System, the Colombian National Institute of Health is working on the design and implementation of a Malaria Early Warning System framework, supported by seasonal climate forecasting capabilities, weather and environmental monitoring, and malaria statistical and dynamic models. In this report, we provide an overview of the local ecoepidemiologic settings where four malaria process-based mathematical models are currently being implemented at a municipal level. The description includes general characteristics, malaria situation (predominant type of infection, malaria-positive cases data, malaria incidence, and seasonality), entomologic conditions (primary and secondary vectors, mosquito densities, and feeding frequencies), climatic conditions (climatology and long-term trends), key drivers of epidemic outbreaks, and non-climatic factors (populations at risk, control campaigns, and socioeconomic conditions). Selected pilot sites exhibit different ecoepidemiologic settings that must be taken into account in the development of the integrated surveillance and control system. © The American Society of Tropical Medicine and Hygiene.

Accelerating Time Integration for the Shallow Water Equations on the Sphere Using GPUs

DOE PAGES

Archibald, R.; Evans, K. J.; Salinger, A.

2015-06-01

The push towards larger and larger computational platforms has made it possible for climate simulations to resolve climate dynamics across multiple spatial and temporal scales. This direction in climate simulation has created a strong need to develop scalable timestepping methods capable of accelerating throughput on high performance computing. This study details the recent advances in the implementation of implicit time stepping of the spectral element dynamical core within the United States Department of Energy (DOE) Accelerated Climate Model for Energy (ACME) on graphical processing units (GPU) based machines. We demonstrate how solvers in the Trilinos project are interfaced with ACMEmore » and GPU kernels to increase computational speed of the residual calculations in the implicit time stepping method for the atmosphere dynamics. We demonstrate the optimization gains and data structure reorganization that facilitates the performance improvements.« less

Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models.

PubMed

Keith, David A; Akçakaya, H Resit; Thuiller, Wilfried; Midgley, Guy F; Pearson, Richard G; Phillips, Steven J; Regan, Helen M; Araújo, Miguel B; Rebelo, Tony G

2008-10-23

Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.

Land Cover Applications, Landscape Dynamics, and Global Change

USGS Publications Warehouse

Tieszen, Larry L.

2007-01-01

The Land Cover Applications, Landscape Dynamics, and Global Change project at U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) seeks to integrate remote sensing and simulation models to better understand and seek solutions to national and global issues. Modeling processes related to population impacts, natural resource management, climate change, invasive species, land use changes, energy development, and climate mitigation all pose significant scientific opportunities. The project activities use remotely sensed data to support spatial monitoring, provide sensitivity analyses across landscapes and large regions, and make the data and results available on the Internet with data access and distribution, decision support systems, and on-line modeling. Applications support sustainable natural resource use, carbon cycle science, biodiversity conservation, climate change mitigation, and robust simulation modeling approaches that evaluate ecosystem and landscape dynamics.

Stringent Mitigation Policy Implied By Temperature Impacts on Economic Growth

NASA Astrophysics Data System (ADS)

Moore, F.; Turner, D.

2014-12-01

Integrated assessment models (IAMs) compare the costs of greenhouse gas mitigation with damages from climate change in order to evaluate the social welfare implications of climate policy proposals and inform optimal emissions reduction trajectories. However, these models have been criticized for lacking a strong empirical basis for their damage functions, which do little to alter assumptions of sustained GDP growth, even under extreme temperature scenarios. We implement empirical estimates of temperature effects on GDP growth-rates in the Dynamic Integrated Climate and Economy (DICE) model via two pathways, total factor productivity (TFP) growth and capital depreciation. Even under optimistic adaptation assumptions, this damage specification implies that optimal climate policy involves the elimination of emissions in the near future, the stabilization of global temperature change below 2°C, and a social cost of carbon (SCC) an order of magnitude larger than previous estimates. A sensitivity analysis shows that the magnitude of growth effects, the rate of adaptation, and the dynamic interaction between damages from warming and GDP are three critical uncertainties and an important focus for future research.

Ecology and the ratchet of events: climate variability, niche dimensions, and species distributions

USGS Publications Warehouse

Jackson, Stephen T.; Betancourt, Julio L.; Booth, Robert K.; Gray, Stephen T.

2009-01-01

Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and more-fundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics.

Ecology and the ratchet of events: Climate variability, niche dimensions, and species distributions

USGS Publications Warehouse

Jackson, S.T.; Betancourt, J.L.; Booth, R.K.; Gray, S.T.

2009-01-01

Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and morefundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics.

Project Summary (2012-2015) – Carbon Dynamics of the Greater Everglades Watershed and Implications of Climate Change

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

Hinkle, Ross; Benscoter, Brian; Comas, Xavier

2015-04-07

Carbon Dynamics of the Greater Everglades Watershed and Implications of Climate Change The objectives of this project are to: 1) quantify above- and below-ground carbon stocks of terrestrial ecosystems along a seasonal hydrologic gradient in the headwaters region of the Greater Everglades watershed; 2) develop budgets of ecosystem gaseous carbon exchange (carbon dioxide and methane) across the seasonal hydrologic gradient; 3) assess the impact of climate drivers on ecosystem carbon exchange in the Greater Everglades headwater region; and 4) integrate research findings with climate-driven terrestrial ecosystem carbon models to examine the potential influence of projected future climate change on regionalmore » carbon cycling. Note: this project receives a one-year extension past the original performance period - David Sumner (USGS) is not included in this extension.« less

Ecology and the ratchet of events: Climate variability, niche dimensions, and species distributions

PubMed Central

Jackson, Stephen T.; Betancourt, Julio L.; Booth, Robert K.; Gray, Stephen T.

2009-01-01

Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and more-fundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics. PMID:19805104

Population dynamics and climate change: what are the links?

PubMed

Stephenson, Judith; Newman, Karen; Mayhew, Susannah

2010-06-01

Climate change has been described as the biggest global health threat of the 21(st) century. World population is projected to reach 9.1 billion by 2050, with most of this growth in developing countries. While the principal cause of climate change is high consumption in the developed countries, its impact will be greatest on people in the developing world. Climate change and population can be linked through adaptation (reducing vulnerability to the adverse effects of climate change) and, more controversially, through mitigation (reducing the greenhouse gases that cause climate change). The contribution of low-income, high-fertility countries to global carbon emissions has been negligible to date, but is increasing with the economic development that they need to reduce poverty. Rapid population growth endangers human development, provision of basic services and poverty eradication and weakens the capacity of poor communities to adapt to climate change. Significant mass migration is likely to occur in response to climate change and should be regarded as a legitimate response to the effects of climate change. Linking population dynamics with climate change is a sensitive issue, but family planning programmes that respect and protect human rights can bring a remarkable range of benefits. Population dynamics have not been integrated systematically into climate change science. The contribution of population growth, migration, urbanization, ageing and household composition to mitigation and adaptation programmes needs urgent investigation.

Integrating research tools to support the management of social-ecological systems under climate change

USGS Publications Warehouse

Miller, Brian W.; Morisette, Jeffrey T.

2014-01-01

Developing resource management strategies in the face of climate change is complicated by the considerable uncertainty associated with projections of climate and its impacts and by the complex interactions between social and ecological variables. The broad, interconnected nature of this challenge has resulted in calls for analytical frameworks that integrate research tools and can support natural resource management decision making in the face of uncertainty and complex interactions. We respond to this call by first reviewing three methods that have proven useful for climate change research, but whose application and development have been largely isolated: species distribution modeling, scenario planning, and simulation modeling. Species distribution models provide data-driven estimates of the future distributions of species of interest, but they face several limitations and their output alone is not sufficient to guide complex decisions for how best to manage resources given social and economic considerations along with dynamic and uncertain future conditions. Researchers and managers are increasingly exploring potential futures of social-ecological systems through scenario planning, but this process often lacks quantitative response modeling and validation procedures. Simulation models are well placed to provide added rigor to scenario planning because of their ability to reproduce complex system dynamics, but the scenarios and management options explored in simulations are often not developed by stakeholders, and there is not a clear consensus on how to include climate model outputs. We see these strengths and weaknesses as complementarities and offer an analytical framework for integrating these three tools. We then describe the ways in which this framework can help shift climate change research from useful to usable.

Forest production dynamics along a wood density spectrum in eastern US forests

Treesearch

C.W. Woodall; M.B. Russell; B.F. Walters; A.W. D' Amato; K. Zhu; S.S. Saatchi

2015-01-01

Emerging plant economics spectrum theories were confirmed across temperate forest systems of the eastern US where the use of a forest stand's mean wood density elucidated forest volume and biomass production dynamics integrating aspects of climate, tree mortality/growth, and rates of site occupancy.

Integrating legacy data to understand agroecosystem regional dynamics to catastrophic events

USDA-ARS?s Scientific Manuscript database

Multi-year extreme drought events are part of the history of the Earth system. Legacy data on the climate drivers, geomorphic features, and agroecosystem responses across a dynamically changing landscape throughout a region can provide important insights to a future where large-scale catastrophic ev...

Variable effects of climate on forest growth in relation to climate extremes, disturbance, and forest dynamics.

PubMed

Itter, Malcolm S; Finley, Andrew O; D'Amato, Anthony W; Foster, Jane R; Bradford, John B

2017-06-01

Changes in the frequency, duration, and severity of climate extremes are forecast to occur under global climate change. The impacts of climate extremes on forest productivity and health remain difficult to predict due to potential interactions with disturbance events and forest dynamics-changes in forest stand composition, density, size and age structure over time. Such interactions may lead to non-linear forest growth responses to climate involving thresholds and lag effects. Understanding how forest dynamics influence growth responses to climate is particularly important given stand structure and composition can be modified through management to increase forest resistance and resilience to climate change. To inform such adaptive management, we develop a hierarchical Bayesian state space model in which climate effects on tree growth are allowed to vary over time and in relation to past climate extremes, disturbance events, and forest dynamics. The model is an important step toward integrating disturbance and forest dynamics into predictions of forest growth responses to climate extremes. We apply the model to a dendrochronology data set from forest stands of varying composition, structure, and development stage in northeastern Minnesota that have experienced extreme climate years and forest tent caterpillar defoliation events. Mean forest growth was most sensitive to water balance variables representing climatic water deficit. Forest growth responses to water deficit were partitioned into responses driven by climatic threshold exceedances and interactions with insect defoliation. Forest growth was both resistant and resilient to climate extremes with the majority of forest growth responses occurring after multiple climatic threshold exceedances across seasons and years. Interactions between climate and disturbance were observed in a subset of years with insect defoliation increasing forest growth sensitivity to water availability. Forest growth was particularly sensitive to climate extremes during periods of high stem density following major regeneration events when average inter-tree competition was high. Results suggest the resistance and resilience of forest growth to climate extremes can be increased through management steps such as thinning to reduce competition during early stages of stand development and small-group selection harvests to maintain forest structures characteristic of older, mature stands. © 2017 by the Ecological Society of America.

More reliable forecasts with less precise computations: a fast-track route to cloud-resolved weather and climate simulators?

PubMed Central

Palmer, T. N.

2014-01-01

This paper sets out a new methodological approach to solving the equations for simulating and predicting weather and climate. In this approach, the conventionally hard boundary between the dynamical core and the sub-grid parametrizations is blurred. This approach is motivated by the relatively shallow power-law spectrum for atmospheric energy on scales of hundreds of kilometres and less. It is first argued that, because of this, the closure schemes for weather and climate simulators should be based on stochastic–dynamic systems rather than deterministic formulae. Second, as high-wavenumber elements of the dynamical core will necessarily inherit this stochasticity during time integration, it is argued that the dynamical core will be significantly over-engineered if all computations, regardless of scale, are performed completely deterministically and if all variables are represented with maximum numerical precision (in practice using double-precision floating-point numbers). As the era of exascale computing is approached, an energy- and computationally efficient approach to cloud-resolved weather and climate simulation is described where determinism and numerical precision are focused on the largest scales only. PMID:24842038

More reliable forecasts with less precise computations: a fast-track route to cloud-resolved weather and climate simulators?

PubMed

Palmer, T N

2014-06-28

This paper sets out a new methodological approach to solving the equations for simulating and predicting weather and climate. In this approach, the conventionally hard boundary between the dynamical core and the sub-grid parametrizations is blurred. This approach is motivated by the relatively shallow power-law spectrum for atmospheric energy on scales of hundreds of kilometres and less. It is first argued that, because of this, the closure schemes for weather and climate simulators should be based on stochastic-dynamic systems rather than deterministic formulae. Second, as high-wavenumber elements of the dynamical core will necessarily inherit this stochasticity during time integration, it is argued that the dynamical core will be significantly over-engineered if all computations, regardless of scale, are performed completely deterministically and if all variables are represented with maximum numerical precision (in practice using double-precision floating-point numbers). As the era of exascale computing is approached, an energy- and computationally efficient approach to cloud-resolved weather and climate simulation is described where determinism and numerical precision are focused on the largest scales only.

Agent-based Model for the Coupled Human-Climate System

NASA Astrophysics Data System (ADS)

Zvoleff, A.; Werner, B.

2006-12-01

Integrated assessment models have been used to predict the outcome of coupled economic growth, resource use, greenhouse gas emissions and climate change, both for scientific and policy purposes. These models generally have employed significant simplifications that suppress nonlinearities and the possibility of multiple equilibria in both their economic (DeCanio, 2005) and climate (Schneider and Kuntz-Duriseti, 2002) components. As one step toward exploring general features of the nonlinear dynamics of the coupled system, we have developed a series of variations on the well studied RICE and DICE models, which employ different forms of agent-based market dynamics and "climate surprises." Markets are introduced through the replacement of the production function of the DICE/RICE models with an agent-based market modeling the interactions of producers, policymakers, and consumer agents. Technological change and population growth are treated endogenously. Climate surprises are representations of positive (for example, ice sheet collapse) or negative (for example, increased aerosols from desertification) feedbacks that are turned on with probability depending on warming. Initial results point toward the possibility of large amplitude instabilities in the coupled human-climate system owing to the mismatch between short outlook market dynamics and long term climate responses. Implications for predictability of future climate will be discussed. Supported by the Andrew W Mellon Foundation and the UC Academic Senate.

Tax authorities' interaction with taxpayers: A conception of compliance in social dilemmas by power and trust

PubMed Central

Gangl, Katharina; Hofmann, Eva; Kirchler, Erich

2015-01-01

Tax compliance represents a social dilemma in which the short-term self-interest to minimize tax payments is at odds with the collective long-term interest to provide sufficient tax funds for public goods. According to the Slippery Slope Framework, the social dilemma can be solved and tax compliance can be guaranteed by power of tax authorities and trust in tax authorities. The framework, however, remains silent on the dynamics between power and trust. The aim of the present theoretical paper is to conceptualize the dynamics between power and trust by differentiating coercive and legitimate power and reason-based and implicit trust. Insights into this dynamic are derived from an integration of a wide range of literature such as on organizational behavior and social influence. Conclusions on the effect of the dynamics between power and trust on the interaction climate between authorities and individuals and subsequent individual motivation of cooperation in social dilemmas such as tax contributions are drawn. Practically, the assumptions on the dynamics can be utilized by authorities to increase cooperation and to change the interaction climate from an antagonistic climate to a service and confidence climate. PMID:25859096

Tax authorities' interaction with taxpayers: A conception of compliance in social dilemmas by power and trust.

PubMed

Gangl, Katharina; Hofmann, Eva; Kirchler, Erich

2015-02-01

Tax compliance represents a social dilemma in which the short-term self-interest to minimize tax payments is at odds with the collective long-term interest to provide sufficient tax funds for public goods. According to the Slippery Slope Framework, the social dilemma can be solved and tax compliance can be guaranteed by power of tax authorities and trust in tax authorities. The framework, however, remains silent on the dynamics between power and trust. The aim of the present theoretical paper is to conceptualize the dynamics between power and trust by differentiating coercive and legitimate power and reason-based and implicit trust. Insights into this dynamic are derived from an integration of a wide range of literature such as on organizational behavior and social influence. Conclusions on the effect of the dynamics between power and trust on the interaction climate between authorities and individuals and subsequent individual motivation of cooperation in social dilemmas such as tax contributions are drawn. Practically, the assumptions on the dynamics can be utilized by authorities to increase cooperation and to change the interaction climate from an antagonistic climate to a service and confidence climate.

Safety climate and culture: Integrating psychological and systems perspectives.

PubMed

Casey, Tristan; Griffin, Mark A; Flatau Harrison, Huw; Neal, Andrew

2017-07-01

Safety climate research has reached a mature stage of development, with a number of meta-analyses demonstrating the link between safety climate and safety outcomes. More recently, there has been interest from systems theorists in integrating the concept of safety culture and to a lesser extent, safety climate into systems-based models of organizational safety. Such models represent a theoretical and practical development of the safety climate concept by positioning climate as part of a dynamic work system in which perceptions of safety act to constrain and shape employee behavior. We propose safety climate and safety culture constitute part of the enabling capitals through which organizations build safety capability. We discuss how organizations can deploy different configurations of enabling capital to exert control over work systems and maintain safe and productive performance. We outline 4 key strategies through which organizations to reconcile the system control problems of promotion versus prevention, and stability versus flexibility. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Understanding Water-Energy-Ecology Nexus from an Integrated Earth-Human System Perspective

NASA Astrophysics Data System (ADS)

Li, H. Y.; Zhang, X.; Wan, W.; Zhuang, Y.; Hejazi, M. I.; Leung, L. R.

2017-12-01

Both Earth and human systems exert notable controls on streamflow and stream temperature that influence energy production and ecosystem health. An integrated water model representing river processes and reservoir regulations has been developed and coupled to a land surface model and an integrated assessment model of energy, land, water, and socioeconomics to investigate the energy-water-ecology nexus in the context of climate change and water management. Simulations driven by two climate change projections following the RCP 4.5 and RCP 8.5 radiative forcing scenarios, with and without water management, are analyzed to evaluate the individual and combined effects of climate change and water management on streamflow and stream temperature in the U.S. The simulations revealed important impacts of climate change and water management on hydrological droughts. The simulations also revealed the dynamics of competition between changes in water demand and water availability in the RCP 4.5 and RCP 8.5 scenarios that influence streamflow and stream temperature, with important consequences to thermoelectricity production and future survival of juvenile Salmon. The integrated water model is being implemented to the Accelerated Climate Modeling for Energy (ACME), a coupled Earth System Model, to enable future investigations of the energy-water-ecology nexus in the integrated Earth-Human system.

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.

Climate Dynamics and Experimental Prediction (CDEP) and Regional Integrated Science Assessments (RISA) Programs at NOAA Office of Global Programs

NASA Astrophysics Data System (ADS)

Bamzai, A.

2003-04-01

This talk will highlight science and application activities of the CDEP and RISA programs at NOAA OGP. CDEP, through a set of Applied Research Centers (ARCs), supports NOAA's program of quantitative assessments and predictions of global climate variability and its regional implications on time scales of seasons to centuries. The RISA program consolidates results from ongoing disciplinary process research under an integrative framework. Examples of joint CDEP-RISA activities will be presented. Future directions and programmatic challenges will also be discussed.

Integrating seasonal climate prediction and agricultural models for insights into agricultural practice

PubMed Central

Hansen, James W

2005-01-01

Interest in integrating crop simulation models with dynamic seasonal climate forecast models is expanding in response to a perceived opportunity to add value to seasonal climate forecasts for agriculture. Integrated modelling may help to address some obstacles to effective agricultural use of climate information. First, modelling can address the mismatch between farmers' needs and available operational forecasts. Probabilistic crop yield forecasts are directly relevant to farmers' livelihood decisions and, at a different scale, to early warning and market applications. Second, credible ex ante evidence of livelihood benefits, using integrated climate–crop–economic modelling in a value-of-information framework, may assist in the challenge of obtaining institutional, financial and political support; and inform targeting for greatest benefit. Third, integrated modelling can reduce the risk and learning time associated with adaptation and adoption, and related uncertainty on the part of advisors and advocates. It can provide insights to advisors, and enhance site-specific interpretation of recommendations when driven by spatial data. Model-based ‘discussion support systems’ contribute to learning and farmer–researcher dialogue. Integrated climate–crop modelling may play a genuine, but limited role in efforts to support climate risk management in agriculture, but only if they are used appropriately, with understanding of their capabilities and limitations, and with cautious evaluation of model predictions and of the insights that arises from model-based decision analysis. PMID:16433092

Challenges and Opportunities for Integrating Social Science Perspectives into Climate and Global Change Assessments

NASA Astrophysics Data System (ADS)

Larson, E. K.; Li, J.; Zycherman, A.

2017-12-01

Integration of social science into climate and global change assessments is fundamental for improving understanding of the drivers, impacts and vulnerability of climate change, and the social, cultural and behavioral challenges related to climate change responses. This requires disciplinary and interdisciplinary knowledge as well as integrational and translational tools for linking this knowledge with the natural and physical sciences. The USGCRP's Social Science Coordinating Committee (SSCC) is tasked with this challenge and is working to integrate relevant social, economic and behavioral knowledge into processes like sustained assessments. This presentation will discuss outcomes from a recent SSCC workshop, "Social Science Perspectives on Climate Change" and their applications to sustained assessments. The workshop brought academic social scientists from four disciplines - anthropology, sociology, geography and archaeology - together with federal scientists and program managers to discuss three major research areas relevant to the USGCRP and climate assessments: (1) innovative tools, methods, and analyses to clarify the interactions of human and natural systems under climate change, (2) understanding of factors contributing to differences in social vulnerability between and within communities under climate change, and (3) social science perspectives on drivers of global climate change. These disciplines, collectively, emphasize the need to consider socio-cultural, political, economic, geographic, and historic factors, and their dynamic interactions, to understand climate change drivers, social vulnerability, and mitigation and adaptation responses. They also highlight the importance of mixed quantitative and qualitative methods to explain impacts, vulnerability, and responses at different time and spatial scales. This presentation will focus on major contributions of the social sciences to climate and global change research. We will discuss future directions for sustained assessments that integrate and reflect the social science understanding of the complex relationships between social and natural worlds in a changing climate, and factors that impact effective mitigation and adaptation strategies that address risks and vulnerabilities of climate change.

The impact of 850,000 years of climate changes on the structure and dynamics of mammal food webs.

PubMed

Nenzén, Hedvig K; Montoya, Daniel; Varela, Sara

2014-01-01

Most evidence of climate change impacts on food webs comes from modern studies and little is known about how ancient food webs have responded to climate changes in the past. Here, we integrate fossil evidence from 71 fossil sites, body-size relationships and actualism to reconstruct food webs for six large mammal communities that inhabited the Iberian Peninsula at different times during the Quaternary. We quantify the long-term dynamics of these food webs and study how their structure changed across the Quaternary, a period for which fossil data and climate changes are well known. Extinction, immigration and turnover rates were correlated with climate changes in the last 850 kyr. Yet, we find differences in the dynamics and structural properties of Pleistocene versus Holocene mammal communities that are not associated with glacial-interglacial cycles. Although all Quaternary mammal food webs were highly nested and robust to secondary extinctions, general food web properties changed in the Holocene. These results highlight the ability of communities to re-organize with the arrival of phylogenetically similar species without major structural changes, and the impact of climate change and super-generalist species (humans) on Iberian Holocene mammal communities.

The Impact of 850,000 Years of Climate Changes on the Structure and Dynamics of Mammal Food Webs

PubMed Central

Nenzén, Hedvig K.; Montoya, Daniel; Varela, Sara

2014-01-01

Most evidence of climate change impacts on food webs comes from modern studies and little is known about how ancient food webs have responded to climate changes in the past. Here, we integrate fossil evidence from 71 fossil sites, body-size relationships and actualism to reconstruct food webs for six large mammal communities that inhabited the Iberian Peninsula at different times during the Quaternary. We quantify the long-term dynamics of these food webs and study how their structure changed across the Quaternary, a period for which fossil data and climate changes are well known. Extinction, immigration and turnover rates were correlated with climate changes in the last 850 kyr. Yet, we find differences in the dynamics and structural properties of Pleistocene versus Holocene mammal communities that are not associated with glacial-interglacial cycles. Although all Quaternary mammal food webs were highly nested and robust to secondary extinctions, general food web properties changed in the Holocene. These results highlight the ability of communities to re-organize with the arrival of phylogenetically similar species without major structural changes, and the impact of climate change and super-generalist species (humans) on Iberian Holocene mammal communities. PMID:25207754

Advancing coupled human-earth system models: The integrated Earth System Model Project

NASA Astrophysics Data System (ADS)

Thomson, A. M.; Edmonds, J. A.; Collins, W.; Thornton, P. E.; Hurtt, G. C.; Janetos, A. C.; Jones, A.; Mao, J.; Chini, L. P.; Calvin, K. V.; Bond-Lamberty, B. P.; Shi, X.

2012-12-01

As human and biogeophysical models develop, opportunities for connections between them evolve and can be used to advance our understanding of human-earth systems interaction in the context of a changing climate. One such integration is taking place with the Community Earth System Model (CESM) and the Global Change Assessment Model (GCAM). A multi-disciplinary, multi-institution team has succeeded in integrating the GCAM integrated assessment model of human activity into CESM to dynamically represent the feedbacks between changing climate and human decision making, in the context of greenhouse gas mitigation policies. The first applications of this capability have focused on the feedbacks between climate change impacts on terrestrial ecosystem productivity and human decisions affecting future land use change, which are in turn connected to human decisions about energy systems and bioenergy production. These experiments have been conducted in the context of the RCP4.5 scenario, one of four pathways of future radiative forcing being used in CMIP5, which constrains future human-induced greenhouse gas emissions from energy and land activities to stabilize radiative forcing at 4.5 W/m2 (~650 ppm CO2 -eq) by 2100. When this pathway is run in GCAM with the climate feedback on terrestrial productivity from CESM, there are implications for both the land use and energy system changes required for stabilization. Early findings indicate that traditional definitions of radiative forcing used in scenario development are missing a critical component of the biogeophysical consequences of land use change and their contribution to effective radiative forcing. Initial full coupling of the two global models has important implications for how climate impacts on terrestrial ecosystems changes the dynamics of future land use change for agriculture and forestry, particularly in the context of a climate mitigation policy designed to reduce emissions from land use as well as energy systems. While these initial experiments have relied on offline coupling methodologies, current and future experiments are utilizing a single model code developed to integrate GCAM into CESM as a component of the land model. This unique capability facilitates many new applications to scientific questions arising from human and biogeophysical systems interaction. Future developments will further integrate the energy system decisions and greenhouse gas emissions as simulated in GCAM with the appropriate climate and land system components of CESM.

Quantifying Hydro-biogeochemical Model Sensitivity in Assessment of Climate Change Effect on Hyporheic Zone Processes

NASA Astrophysics Data System (ADS)

Song, X.; Chen, X.; Dai, H.; Hammond, G. E.; Song, H. S.; Stegen, J.

2016-12-01

The hyporheic zone is an active region for biogeochemical processes such as carbon and nitrogen cycling, where the groundwater and surface water mix and interact with each other with distinct biogeochemical and thermal properties. The biogeochemical dynamics within the hyporheic zone are driven by both river water and groundwater hydraulic dynamics, which are directly affected by climate change scenarios. Besides that, the hydraulic and thermal properties of local sediments and microbial and chemical processes also play important roles in biogeochemical dynamics. Thus for a comprehensive understanding of the biogeochemical processes in the hyporheic zone, a coupled thermo-hydro-biogeochemical model is needed. As multiple uncertainty sources are involved in the integrated model, it is important to identify its key modules/parameters through sensitivity analysis. In this study, we develop a 2D cross-section model in the hyporheic zone at the DOE Hanford site adjacent to Columbia River and use this model to quantify module and parametric sensitivity on assessment of climate change. To achieve this purpose, We 1) develop a facies-based groundwater flow and heat transfer model that incorporates facies geometry and heterogeneity characterized from a field data set, 2) derive multiple reaction networks/pathways from batch experiments with in-situ samples and integrate temperate dependent reactive transport modules to the flow model, 3) assign multiple climate change scenarios to the coupled model by analyzing historical river stage data, 4) apply a variance-based global sensitivity analysis to quantify scenario/module/parameter uncertainty in hierarchy level. The objectives of the research include: 1) identifing the key control factors of the coupled thermo-hydro-biogeochemical model in the assessment of climate change, and 2) quantify the carbon consumption in different climate change scenarios in the hyporheic zone.

Insights on the energy-water nexus through modeling of the integrated water cycle

NASA Astrophysics Data System (ADS)

Leung, L. R.; Li, H. Y.; Zhang, X.; Wan, W.; Voisin, N.; Leng, G.

2016-12-01

For sustainable energy planning, understanding the impacts of climate change, land use change, and water management is essential as they all exert notable controls on streamflow and stream temperature that influence energy production. An integrated water model representing river processes, irrigation water use and water management has been developed and coupled to a land surface model to investigate the energy-water nexus. Simulations driven by two climate change projections with the RCP 4.5 and RCP 8.5 emissions scenarios, with and without water management, are analyzed to evaluate the individual and combined effects of climate change and water management on streamflow and stream temperature. The simulations revealed important impacts of climate change and water management on both floods and droughts. The simulations also revealed the dynamics of competition between changes in water demand and water availability in the climate mitigation (RCP 4.5) and business as usual (RCP 8.5) scenarios that influence streamflow and stream temperature, with important consequences to energy production. The integrated water model is being implemented to the Accelerated Climate Modeling for Energy (ACME) to enable investigation of the energy-water nexus in the fully coupled Earth system.

A crucial step toward realism: responses to climate change from an evolving metacommunity perspective.

PubMed

Urban, Mark C; De Meester, Luc; Vellend, Mark; Stoks, Robby; Vanoverbeke, Joost

2012-02-01

We need to understand joint ecological and evolutionary responses to climate change to predict future threats to biological diversity. The 'evolving metacommunity' framework emphasizes that interactions between ecological and evolutionary mechanisms at both local and regional scales will drive community dynamics during climate change. Theory suggests that ecological and evolutionary dynamics often interact to produce outcomes different from those predicted based on either mechanism alone. We highlight two of these dynamics: (i) species interactions prevent adaptation of nonresident species to new niches and (ii) resident species adapt to changing climates and thereby prevent colonization by nonresident species. The rate of environmental change, level of genetic variation, source-sink structure, and dispersal rates mediate between these potential outcomes. Future models should evaluate multiple species, species interactions other than competition, and multiple traits. Future experiments should manipulate factors such as genetic variation and dispersal to determine their joint effects on responses to climate change. Currently, we know much more about how climates will change across the globe than about how species will respond to these changes despite the profound effects these changes will have on global biological diversity. Integrating evolving metacommunity perspectives into climate change biology should produce more accurate predictions about future changes to species distributions and extinction threats.

A crucial step toward realism: responses to climate change from an evolving metacommunity perspective

PubMed Central

Urban, Mark C; De Meester, Luc; Vellend, Mark; Stoks, Robby; Vanoverbeke, Joost

2012-01-01

We need to understand joint ecological and evolutionary responses to climate change to predict future threats to biological diversity. The ‘evolving metacommunity’ framework emphasizes that interactions between ecological and evolutionary mechanisms at both local and regional scales will drive community dynamics during climate change. Theory suggests that ecological and evolutionary dynamics often interact to produce outcomes different from those predicted based on either mechanism alone. We highlight two of these dynamics: (i) species interactions prevent adaptation of nonresident species to new niches and (ii) resident species adapt to changing climates and thereby prevent colonization by nonresident species. The rate of environmental change, level of genetic variation, source-sink structure, and dispersal rates mediate between these potential outcomes. Future models should evaluate multiple species, species interactions other than competition, and multiple traits. Future experiments should manipulate factors such as genetic variation and dispersal to determine their joint effects on responses to climate change. Currently, we know much more about how climates will change across the globe than about how species will respond to these changes despite the profound effects these changes will have on global biological diversity. Integrating evolving metacommunity perspectives into climate change biology should produce more accurate predictions about future changes to species distributions and extinction threats. PMID:25568038

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.

Integrating vegetation index time series and meteorological data to understand the effect of the land use/land cover (LULC) in the climatic seasonality of the Brazilian Cerrado

NASA Astrophysics Data System (ADS)

Lins, D. B.; Zullo, J.; Friedel, M. J.

2013-12-01

The Cerrado (savanna ecosystem) of São Paulo state (Brazil) represent a complex mosaic of different typologies of uses, actors and biophysical and social restrictions. Originally, 14% of the state of São Paulo area was covered by the diversity of Cerrado phytophysiognomies. Currently, only 1% of this original composition remains fragmented into numerous relicts of biodiversity, mainly concentrated in the central-eastern of the state. A relevant part of the fragments are found in areas of intense coverage change by human activities, whereas the greatest pressure comes from sugar cane cultivation, either by direct replacement of Cerrado vegetation or occupying pasture areas in the fragments edges. As a result, new local level dynamics has been introduced, directly or indirectly, affecting the established of processes in climate systems. In this study, the main goal is analyzing the relationship between the Cerrado landscape changing and the climate dynamics in regional and local areas. The multi-temporal MODIS 250 m Vegetation Index (VI) datasets (period of 2000 to 2012) are integrated with precipitation data of the correspondent period (http://www.agritempo.gov.br/),one of the most important variable of the spatial phytophysiognomies distribution. The integration of meteorological data enable the development of an integrated approach to understand the relationship between climatic seasonality and the changes in the spatial patterns. A procedure to congregated diverse dynamics information is the Self Organizing Map (SOM, Kohonen, 2001), a technique that relies on unsupervised competitive learning (Kohonen and Somervuo 2002) to recognize patterns. In this approach, high-dimensional data are represented on two dimensions, making possible to obtain patterns that takes into account information from different natures. Observed advances will contribute to bring machine-learning techniques as a valid tool to provide improve in land use/land cover (LULC) analyzes at different hierarchical scales to support numerous science and policy applications.

A multiscale, hierarchical model of pulse dynamics in arid-land ecosystems

USGS Publications Warehouse

Collins, Scott L.; Belnap, Jayne; Grimm, N. B.; Rudgers, J. A.; Dahm, Clifford N.; D'Odorico, P.; Litvak, M.; Natvig, D. O.; Peters, Douglas C.; Pockman, W. T.; Sinsabaugh, R. L.; Wolf, B. O.

2014-01-01

Ecological processes in arid lands are often described by the pulse-reserve paradigm, in which rain events drive biological activity until moisture is depleted, leaving a reserve. This paradigm is frequently applied to processes stimulated by one or a few precipitation events within a growing season. Here we expand the original framework in time and space and include other pulses that interact with rainfall. This new hierarchical pulse-dynamics framework integrates space and time through pulse-driven exchanges, interactions, transitions, and transfers that occur across individual to multiple pulses extending from micro to watershed scales. Climate change will likely alter the size, frequency, and intensity of precipitation pulses in the future, and arid-land ecosystems are known to be highly sensitive to climate variability. Thus, a more comprehensive understanding of arid-land pulse dynamics is needed to determine how these ecosystems will respond to, and be shaped by, increased climate variability.

On climate prediction: how much can we expect from climate memory?

NASA Astrophysics Data System (ADS)

Yuan, Naiming; Huang, Yan; Duan, Jianping; Zhu, Congwen; Xoplaki, Elena; Luterbacher, Jürg

2018-03-01

Slowing variability in climate system is an important source of climate predictability. However, it is still challenging for current dynamical models to fully capture the variability as well as its impacts on future climate. In this study, instead of simulating the internal multi-scale oscillations in dynamical models, we discussed the effects of internal variability in terms of climate memory. By decomposing climate state x(t) at a certain time point t into memory part M(t) and non-memory part ɛ (t) , climate memory effects from the past 30 years on climate prediction are quantified. For variables with strong climate memory, high variance (over 20% ) in x(t) is explained by the memory part M(t), and the effects of climate memory are non-negligible for most climate variables, but the precipitation. Regarding of multi-steps climate prediction, a power law decay of the explained variance was found, indicating long-lasting climate memory effects. The explained variances by climate memory can remain to be higher than 10% for more than 10 time steps. Accordingly, past climate conditions can affect both short (monthly) and long-term (interannual, decadal, or even multidecadal) climate predictions. With the memory part M(t) precisely calculated from Fractional Integral Statistical Model, one only needs to focus on the non-memory part ɛ (t) , which is an important quantity that determines climate predictive skills.

Evolving Views on a Dynamic Greenhouse Earth

NASA Astrophysics Data System (ADS)

Hollis, Chris; Huber, Matthew

2009-06-01

Climatic and Biotic Events of the Paleogene (CBEP 2009) Conference; Wellington, New Zealand, 12-15 January 2009; The Paleogene (65-24 million years ago) was a dynamic period in Earth's history in which major mammal groups became established and diversified, rapid and repeated extreme global warming events occurred, and climate began its stuttering progression from a greenhouse to an icehouse climate state. With atmospheric carbon dioxide concentrations in the range projected to occur over the next several centuries (>1000 parts per million), the Paleogene is also a window into our future (see J. C. Zachos et al., Nature, 451, 279-283, 2008). Long-standing interest in understanding the causes and consequences of global change in the Paleogene and the current timeliness of greenhouse climate research explain why conferences are periodically devoted to the climatic and biotic events of the Paleogene. The 2009 conference, held in New Zealand, attracted 130 participants from 20 countries. Presentations demonstrated substantial progress in new climate proxy development, new multiproxy approaches, and closer integration of paleoclimate records with climate models, consolidating around three main issues.

integrated Earth System Model

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

Jones, Andew; Di Vittorio, Alan; Collins, William

The integrated Earth system model (iESM) has been developed as a new tool for projecting the joint human/climate system. The iESM is based upon coupling an integrated assessment model (IAM) and an Earth system model (ESM) into a common modeling infrastructure. IAMs are the primary tool for describing the human-Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species (SLS), land use and land cover change (LULCC), and other resource-related drivers of anthropogenic climate change. ESMs are the primary scientific tools for examining the physical, chemical, and biogeochemical impacts of human-induced changes to the climate system. Themore » iESM project integrates the economic and human-dimension modeling of an IAM and a fully coupled ESM within a single simulation system while maintaining the separability of each model if needed. Both IAM and ESM codes are developed and used by large communities and have been extensively applied in recent national and international climate assessments. By introducing heretofore-omitted feedbacks between natural and societal drivers, we can improve scientific understanding of the human-Earth system dynamics. Potential applications include studies of the interactions and feedbacks leading to the timing, scale, and geographic distribution of emissions trajectories and other human influences, corresponding climate effects, and the subsequent impacts of a changing climate on human and natural systems.« less

Toward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity

Treesearch

Mercedes M. C. Bustamante; Iris Roitman; T. Mitchell Aide; Ane Alencar; Liana O. Anderson; Luiz Aragao; Gregory P. Asner; Jos Barlow; Erika Berenguer; Jeffrey Chambers; Marcos H. Costa; Thierry Fanin; Laerte G. Ferreira; Joice Ferreira; Michael Keller; William E. Magnusson; Lucia Morales-Barquero; Douglas Morton; Jean P. H. B. Ometto; Michael Palace; Carlos A. Peres; Divino Silverio; Susan Trumbore; Ima C. G. Vieira

2015-01-01

Tropical forests harbor a significant portion of global biodiversity and are a critical component of the climate system. Reducing deforestation and forest degradation contributes to global climate-change mitigation efforts, yet emissions and removals from forest dynamics are still poorly quantified. We reviewed the main challenges to estimate changes in carbon stocks...

Development and application of dynamic hybrid multi-region inventory analysis for macro-level environmental policy analysis: a case study on climate policy in Taiwan.

PubMed

Chao, Chia-Wei; Heijungs, Reinout; Ma, Hwong-wen

2013-03-19

We develop a novel inventory method called Dynamic Hybrid Multi-Region Inventory analysis (DHMRI), which integrates the EEMRIOA and Integrated Hybrid LCA and applies time-dependent environmental intervention information for inventory analysis. Consequently, DHMRI is able to quantify the change in the environmental footprint caused by a specific policy while taking structural changes and technological dynamics into consideration. DHMRI is applied to assess the change in the total CO2 emissions associated with the total final demand caused by the climate policy in Taiwan to demonstrate the practicality of this novel method. The evaluation reveals that the implementation of mitigation measures included in the existing climate policy, such as an enhancement in energy efficiency, promotion of renewable energy, and limitation of the growth of energy-intensive industries, will lead to a 28% increase in the total CO2 emissions and that the main driver is the export-oriented electronics industry. Moreover, a major increase in the total emissions is predicted to occur in Southeast Asia and China. The observations from the case study reveal that DHMRI is capable of overcoming the limitations of existing assessment tools at macro-level evaluation of environmental policies.

Variable effects of climate on forest growth in relation to climate extremes, disturbance, and forest dynamics

USGS Publications Warehouse

Itter, Malcolm S.; Finley, Andrew O.; D'Amato, Anthony W.; Foster, Jane R.; Bradford, John B.

2017-01-01

Changes in the frequency, duration, and severity of climate extremes are forecast to occur under global climate change. The impacts of climate extremes on forest productivity and health remain difficult to predict due to potential interactions with disturbance events and forest dynamics—changes in forest stand composition, density, size and age structure over time. Such interactions may lead to non-linear forest growth responses to climate involving thresholds and lag effects. Understanding how forest dynamics influence growth responses to climate is particularly important given stand structure and composition can be modified through management to increase forest resistance and resilience to climate change. To inform such adaptive management, we develop a hierarchical Bayesian state space model in which climate effects on tree growth are allowed to vary over time and in relation to past climate extremes, disturbance events, and forest dynamics. The model is an important step toward integrating disturbance and forest dynamics into predictions of forest growth responses to climate extremes. We apply the model to a dendrochronology data set from forest stands of varying composition, structure, and development stage in northeastern Minnesota that have experienced extreme climate years and forest tent caterpillar defoliation events. Mean forest growth was most sensitive to water balance variables representing climatic water deficit. Forest growth responses to water deficit were partitioned into responses driven by climatic threshold exceedances and interactions with insect defoliation. Forest growth was both resistant and resilient to climate extremes with the majority of forest growth responses occurring after multiple climatic threshold exceedances across seasons and years. Interactions between climate and disturbance were observed in a subset of years with insect defoliation increasing forest growth sensitivity to water availability. Forest growth was particularly sensitive to climate extremes during periods of high stem density following major regeneration events when average inter-tree competition was high. Results suggest the resistance and resilience of forest growth to climate extremes can be increased through management steps such as thinning to reduce competition during early stages of stand development and small-group selection harvests to maintain forest structures characteristic of older, mature stands.

Detecting changes in water limitation in the West using integrated ecosystem modeling approaches

NASA Astrophysics Data System (ADS)

Poulter, B.; Hoy, J.; Emmett, K.; Cross, M.; Maneta, M. P.; Al-Chokhachy, R.

2016-12-01

Water in the western United States is the critical currency for determining a range of ecosystem services, such as wildlife habitat, carbon sequestration, and timber and water resources for an expanding human population. The current generation of catchment models trades a detailed representation of hydrologic processes for a generalization of vegetation processes and thus ignores many land-surface feedbacks that are driven by physiological responses to atmospheric CO2 and changes in vegetation structure following disturbance and climate change. Here we demonstrate how catchment scale modeling can better couple vegetation dynamics and disturbance processes to reconstruct historic streamflow, stream temperature and vegetation greening for the Greater Yellowstone Ecosystem. Using a new catchment routing model coupled to the LPJ-GUESS dynamic global vegetation model, simulations are made at 1 km spatial resolution using two different climate products. Decreased winter snowpack has led to increasing spring runoff and declines in summertime slow, and increasing the likelihood that stream temperature exceeds thresholds for cold-water fish growth. Since the mid-1980s, vegetation greening is projected by both the model and detected from space-borne normalized difference vegetation index observations. These greening trends are superimposed on a landscape matrix defined by frequent disturbance and intensive land management, making the climate and CO2 fingerprint difficult to discern. Integrating dynamical vegetation models with in-situ and spaceborne measurements to understand and interpret catchment-scale trends in water availability has potential to better disentangle historical climate, CO2, and human drivers and their ecosystem consequences.

Integrated assessment in the Mediterranean: the CIRCE case studies

NASA Astrophysics Data System (ADS)

Goodess, C. M.; Agnew, M. D.; Hemming, D.; Giannakopoulos, C.

2012-04-01

The heterogeneous nature of the Mediterranean environment, combined with a wide diversity of economic, social and cultural identities, make this region particularly amenable to integrated research on climate change impacts, vulnerabilities, and adaptive response. Within the framework of the EU FP7 CIRCE project, eleven case-study locations were selected to reflect three generic environments (urban, rural and coastal), to quantify current and future climate change and to assess the potential consequences to human communities and ecosystems at the regional to local scale. The case studies (Athens, Beirut, Alexandria, Tuscany, Apulia, Tel Hadya, Judean Foothills, Gulf of Valencia, Gulf of Oran, Gulf of Gabes, West Nile Delta) were chosen to reflect the east-west and north-south contrasts across the Mediterranean, using common selection criteria. A rigorous common framework, referred to as the CIRCE Case studies Integrating Framework was developed to facilitate a structured and systematic basis for identifying and selecting indicators. Within this framework, climate dynamics is viewed as a key driver of changes in social and biogeophysical systems and is modulated by the inherent dynamics of these systems. The top-down, indicator-based approach was complemented by a bottom-up approach involving local and regional stakeholders. A participatory level of involvement was aimed for, with stakeholder dialogue on an informal basis throughout the project, culminating in a series of more formal regional stakeholder workshops. Identification and construction of physical and socio-economic indicators was the most challenging and time-consuming aspect of the case-study work. A detailed set of selection criteria was defined and the process of reviewing and refining indicators was iterative. Nonetheless, a number of data and methodological challenges were encountered. Despite these issues, indicator linkages diagrams provided a useful preparatory stage for structuring the integrated assessment for each case study. In the first and major assessment stage, impacts and vulnerability due to exposure to hazards associated with current and recent climate variability and change were explored using observed data. This then provided the context for considering future changes. The latter work was based on climate projections derived from the CIRCE global and regional climate model simulations which have the main novel characteristic of incorporating coupling between the Mediterranean Sea and atmosphere. Natural and human systems in all eleven case studies were found to be vulnerable to current climate variability and change as well as to social dynamics or drivers. The climate projections of increases in mean and extreme high temperature and decreases in precipitation are considered to be robust, although there is uncertainty with regards to the magnitude of change. They indicate that all case studies will experience continuing and increasing vulnerability to climate change in the absence of mitigation or adaptation. Projections for other extreme weather events, such as heavy precipitation and flooding, are highly uncertain, but any increase in such events would further increase vulnerability. At the same time, social dynamics and drivers such as population growth (at least in the short term and in the southern Mediterranean) are likely to further increase vulnerability.

Evaluating CO2 and CH4 dynamics of Alaskan ecosystems during the Holocene Thermal Maximum

USGS Publications Warehouse

He, Yujie; Jones, Miriam C.; Zhuang, Qianlai; Bochicchio, Christopher; Felzer, B. S.; Mason, Erik; Yu, Zicheng

2014-01-01

The Arctic has experienced much greater warming than the global average in recent decades due to polar amplification. Warming has induced ecological changes that have impacted climate carbon-cycle feedbacks, making it important to understand the climate and vegetation controls on carbon (C) dynamics. Here we used the Holocene Thermal Maximum (HTM, 11–9 ka BP, 1 ka BP = 1000 cal yr before present) in Alaska as a case study to examine how ecosystem Cdynamics responded to the past warming climate using an integrated approach of combining paleoecological reconstructions and ecosystem modeling. Our paleoecological synthesis showed expansion of deciduous broadleaf forest (dominated by Populus) into tundra and the establishment of boreal evergreen needleleaf and mixed forest during the second half of the HTM under a warmer- and wetter-than-before climate, coincident with the occurrence of the highest net primary productivity, cumulative net ecosystem productivity, soil C accumulation and CH4 emissions. These series of ecological and biogeochemical shifts mirrored the solar insolation and subsequent temperature and precipitation patterns during HTM, indicating the importance of climate controls on C dynamics. Our simulated regional estimate of CH4 emission rates from Alaska during the HTM ranged from 3.5 to 6.4 Tg CH4 yr−1 and highest annual NPP of 470 Tg C yr−1, significantly higher than previously reported modern estimates. Our results show that the differences in static vegetation distribution maps used in simulations of different time slices have greater influence on modeled C dynamics than climatic fields within each time slice, highlighting the importance of incorporating vegetation community dynamics and their responses to climatic conditions in long-term biogeochemical modeling.

Integrating physiology, population dynamics and climate to make multi-scale predictions for the spread of an invasive insect: the Argentine ant at Haleakala National Park, Hawaii

USGS Publications Warehouse

Hartley, Stephen; Krushelnycky, Paul D.; Lester, Philip J.

2010-01-01

Mechanistic models for predicting species’ distribution patterns present particular advantages and challenges relative to models developed from statistical correlations between distribution and climate. They can be especially useful for predicting the range of invasive species whose distribution has not yet reached equilibrium. Here, we illustrate how a physiological model of development for the invasive Argentine ant can be connected to differences in micro-site suitability, population dynamics and climatic gradients; processes operating at quite different spatial scales. Our study is located in the subalpine shrubland of Haleakala National Park, Hawaii, where the spread of Argentine ants Linepithema humile has been documented for the past twenty-five years. We report four main results. First, at a microsite level, the accumulation of degree-days recorded in potential ant nest sites under bare ground or rocks was significantly greater than under a groundcover of grassy vegetation. Second, annual degree-days measured where population boundaries have not expanded (456-521 degree-days), were just above the developmental requirements identified from earlier laboratory studies (445 degree-days above 15.98C). Third, rates of population expansion showed a strong linear relationship with annual degree-days. Finally, an empirical relationship between soil degree-days and climate variables mapped at a broader scale predicts the potential for future range expansion of Argentine ants at Haleakala, particularly to the west of the lower colony and the east of the upper colony. Variation in the availability of suitable microsites, driven by changes in vegetation cover and ultimately climate, provide a hierarchical understanding of the distribution of Argentine ants close to their cold-wet limit of climatic tolerances. We conclude that the integration of physiology, population dynamics and climate mapping holds much promise for making more robust predictions about the potential spread of invasive species.

Climate change amplifies the interactions between wind and bark beetle disturbances in forest landscapes.

PubMed

Seidl, Rupert; Rammer, Werner

2017-07-01

Growing evidence suggests that climate change could substantially alter forest disturbances. Interactions between individual disturbance agents are a major component of disturbance regimes, yet how interactions contribute to their climate sensitivity remains largely unknown. Here, our aim was to assess the climate sensitivity of disturbance interactions, focusing on wind and bark beetle disturbances. We developed a process-based model of bark beetle disturbance, integrated into the dynamic forest landscape model iLand (already including a detailed model of wind disturbance). We evaluated the integrated model against observations from three wind events and a subsequent bark beetle outbreak, affecting 530.2 ha (3.8 %) of a mountain forest landscape in Austria between 2007 and 2014. Subsequently, we conducted a factorial experiment determining the effect of changes in climate variables on the area disturbed by wind and bark beetles separately and in combination. iLand was well able to reproduce observations with regard to area, temporal sequence, and spatial pattern of disturbance. The observed disturbance dynamics was strongly driven by interactions, with 64.3 % of the area disturbed attributed to interaction effects. A +4 °C warming increased the disturbed area by +264.7 % and the area-weighted mean patch size by +1794.3 %. Interactions were found to have a ten times higher sensitivity to temperature changes than main effects, considerably amplifying the climate sensitivity of the disturbance regime. Disturbance interactions are a key component of the forest disturbance regime. Neglecting interaction effects can lead to a substantial underestimation of the climate change sensitivity of disturbance regimes.

Integration of climatic water deficit and fine-scale physiography in process-based modeling of forest landscape resilience to large-scale tree mortality

NASA Astrophysics Data System (ADS)

Yang, J.; Weisberg, P.; Dilts, T.

2016-12-01

Climate warming can lead to large-scale drought-induced tree mortality events and greatly affect forest landscape resilience. Climatic water deficit (CWD) and its physiographic variations provide a key mechanism in driving landscape dynamics in response to climate change. Although CWD has been successfully applied in niche-based species distribution models, its application in process-based forest landscape models is still scarce. Here we present a framework incorporating fine-scale influence of terrain on ecohydrology in modeling forest landscape dynamics. We integrated CWD with a forest landscape succession and disturbance model (LANDIS-II) to evaluate how tree species distribution might shift in response to different climate-fire scenarios across an elevation-aspect gradient in a semi-arid montane landscape of northeastern Nevada, USA. Our simulations indicated that drought-intolerant tree species such as quaking aspen could experience greatly reduced distributions in the more arid portions of their existing ranges due to water stress limitations under future climate warming scenarios. However, even at the most xeric portions of its range, aspen is likely to persist in certain environmental settings due to unique and often fine-scale combinations of resource availability, species interactions and disturbance regime. The modeling approach presented here allowed identification of these refugia. In addition, this approach helped quantify how the direction and magnitude of fire influences on species distribution would vary across topoclimatic gradients, as well as furthers our understanding on the role of environmental conditions, fire, and inter-specific competition in shaping potential responses of landscape resilience to climate change.

Climate variability and human impact in South America during the last 2000 years: synthesis and perspectives from pollen records

NASA Astrophysics Data System (ADS)

Flantua, S. G. A.; Hooghiemstra, H.; Vuille, M.; Behling, H.; Carson, J. F.; Gosling, W. D.; Hoyos, I.; Ledru, M. P.; Montoya, E.; Mayle, F.; Maldonado, A.; Rull, V.; Tonello, M. S.; Whitney, B. S.; González-Arango, C.

2016-02-01

An improved understanding of present-day climate variability and change relies on high-quality data sets from the past 2 millennia. Global efforts to model regional climate modes are in the process of being validated against, and integrated with, records of past vegetation change. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to an absence of information on the spatial and temporal coverage of study sites. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last 2 millennia. We identify 60 vegetation (pollen) records from across South America which satisfy geochronological requirements set out for climate modelling, and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local-scale responses to climate modes; thus, it is necessary to understand how vegetation-climate interactions might diverge under variable settings. We provide a qualitative translation from pollen metrics to climate variables. Additionally, pollen is an excellent indicator of human impact through time. We discuss evidence for human land use in pollen records and provide an overview considered useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. This manuscript forms part of the wider LOng-Term multi-proxy climate REconstructions and Dynamics in South America - 2k initiative that provides the ideal framework for the integration of the various palaeoclimatic subdisciplines and palaeo-science, thereby jump-starting and fostering multidisciplinary research into environmental change on centennial and millennial timescales.

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

USGS Publications Warehouse

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

2008-01-01

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

One carbon cycle: Impacts of model integration, ecosystem process detail, model resolution, and initialization data, on projections of future climate mitigation strategies

NASA Astrophysics Data System (ADS)

Fisk, J.; Hurtt, G. C.; le page, Y.; Patel, P. L.; Chini, L. P.; Sahajpal, R.; Dubayah, R.; Thomson, A. M.; Edmonds, J.; Janetos, A. C.

2013-12-01

Integrated assessment models (IAMs) simulate the interactions between human and natural systems at a global scale, representing a broad suite of phenomena across the global economy, energy system, land-use, and carbon cycling. Most proposed climate mitigation strategies rely on maintaining or enhancing the terrestrial carbon sink as a substantial contribution to restrain the concentration of greenhouse gases in the atmosphere, however most IAMs rely on simplified regional representations of terrestrial carbon dynamics. Our research aims to reduce uncertainties associated with forest modeling within integrated assessments, and to quantify the impacts of climate change on forest growth and productivity for integrated assessments of terrestrial carbon management. We developed the new Integrated Ecosystem Demography (iED) to increase terrestrial ecosystem process detail, resolution, and the utilization of remote sensing in integrated assessments. iED brings together state-of-the-art models of human society (GCAM), spatial land-use patterns (GLM) and terrestrial ecosystems (ED) in a fully coupled framework. The major innovative feature of iED is a consistent, process-based representation of ecosystem dynamics and carbon cycle throughout the human, terrestrial, land-use, and atmospheric components. One of the most challenging aspects of ecosystem modeling is to provide accurate initialization of land surface conditions to reflect non-equilibrium conditions, i.e., the actual successional state of the forest. As all plants in ED have an explicit height, it is one of the few ecosystem models that can be initialized directly with vegetation height data. Previous work has demonstrated that ecosystem model resolution and initialization data quality have a large effect on flux predictions at continental scales. Here we use a factorial modeling experiment to quantify the impacts of model integration, process detail, model resolution, and initialization data on projections of future climate mitigation strategies. We find substantial effects on key integrated assessment projections including the magnitude of emissions to mitigate, the economic value of ecosystem carbon storage, future land-use patterns, food prices and energy technology.

Integrated Assessment of Carbon Dioxide Removal

NASA Astrophysics Data System (ADS)

Rickels, W.; Reith, F.; Keller, D.; Oschlies, A.; Quaas, M. F.

2018-03-01

To maintain the chance of keeping the average global temperature increase below 2°C and to limit long-term climate change, removing carbon dioxide from the atmosphere (carbon dioxide removal, CDR) is becoming increasingly necessary. We analyze optimal and cost-effective climate policies in the dynamic integrated assessment model (IAM) of climate and the economy (DICE2016R) and investigate (1) the utilization of (ocean) CDR under different climate objectives, (2) the sensitivity of policies with respect to carbon cycle feedbacks, and (3) how well carbon cycle feedbacks are captured in the carbon cycle models used in state-of-the-art IAMs. Overall, the carbon cycle model in DICE2016R shows clear improvements compared to its predecessor, DICE2013R, capturing much better long-term dynamics and also oceanic carbon outgassing due to excess oceanic storage of carbon from CDR. However, this comes at the cost of a (too) tight short-term remaining emission budget, limiting the model suitability to analyze low-emission scenarios accurately. With DICE2016R, the compliance with the 2°C goal is no longer feasible without negative emissions via CDR. Overall, the optimal amount of CDR has to take into account (1) the emission substitution effect and (2) compensation for carbon cycle feedbacks.

Coupled impacts of climate and land use change across a river-lake continuum: insights from an integrated assessment model of Lake Champlain’s Missisquoi Basin, 2000-2040

NASA Astrophysics Data System (ADS)

Zia, Asim; Bomblies, Arne; Schroth, Andrew W.; Koliba, Christopher; Isles, Peter D. F.; Tsai, Yushiou; Mohammed, Ibrahim N.; Bucini, Gabriela; Clemins, Patrick J.; Turnbull, Scott; Rodgers, Morgan; Hamed, Ahmed; Beckage, Brian; Winter, Jonathan; Adair, Carol; Galford, Gillian L.; Rizzo, Donna; Van Houten, Judith

2016-11-01

Global climate change (GCC) is projected to bring higher-intensity precipitation and higher-variability temperature regimes to the Northeastern United States. The interactive effects of GCC with anthropogenic land use and land cover changes (LULCCs) are unknown for watershed level hydrological dynamics and nutrient fluxes to freshwater lakes. Increased nutrient fluxes can promote harmful algal blooms, also exacerbated by warmer water temperatures due to GCC. To address the complex interactions of climate, land and humans, we developed a cascading integrated assessment model to test the impacts of GCC and LULCC on the hydrological regime, water temperature, water quality, bloom duration and severity through 2040 in transnational Lake Champlain’s Missisquoi Bay. Temperature and precipitation inputs were statistically downscaled from four global circulation models (GCMs) for three Representative Concentration Pathways. An agent-based model was used to generate four LULCC scenarios. Combined climate and LULCC scenarios drove a distributed hydrological model to estimate river discharge and nutrient input to the lake. Lake nutrient dynamics were simulated with a 3D hydrodynamic-biogeochemical model. We find accelerated GCC could drastically limit land management options to maintain water quality, but the nature and severity of this impact varies dramatically by GCM and GCC scenario.

Participatory Climate Research in a Dynamic Urban Context: Activities of the Consortium for Climate Risk in the Urban Northeast (CCRUN)

NASA Technical Reports Server (NTRS)

Horton, Radley M.; Bader, Daniel A.; Montalto, Franco; Solecki, William

2016-01-01

The Consortium for Climate Risk in the Urban Northeast (CCRUN), one of ten NOAA-RISAs, supports resilience efforts in the urban corridor stretching from Philadelphia to Boston. Challenges and opportunities include the diverse set of needs in broad urban contexts, as well as the integration of interdisciplinary perspectives. CCRUN is addressing these challenges through strategies including: 1) the development of an integrated project framework, 2) stakeholder surveys, 3) leveraging extreme weather events as focusing opportunities, and 4) a seminar series that enables scientists and stakeholders to partner. While recognizing that the most extreme weather events will always lead to surprises (even with sound planning), CCRUN endeavors to remain flexible by facilitating place-based research in an interdisciplinary context.

National housing and impervious surface scenarios for integrated climate impact assessments

PubMed Central

Bierwagen, Britta G.; Theobald, David M.; Pyke, Christopher R.; Choate, Anne; Groth, Philip; Thomas, John V.; Morefield, Philip

2010-01-01

Understanding the impacts of climate change on people and the environment requires an understanding of the dynamics of both climate and land use/land cover changes. A range of future climate scenarios is available for the conterminous United States that have been developed based on widely used international greenhouse gas emissions storylines. Climate scenarios derived from these emissions storylines have not been matched with logically consistent land use/cover maps for the United States. This gap is a critical barrier to conducting effective integrated assessments. This study develops novel national scenarios of housing density and impervious surface cover that are logically consistent with emissions storylines. Analysis of these scenarios suggests that combinations of climate and land use/cover can be important in determining environmental conditions regulated under the Clean Air and Clean Water Acts. We found significant differences in patterns of habitat loss and the distribution of potentially impaired watersheds among scenarios, indicating that compact development patterns can reduce habitat loss and the number of impaired watersheds. These scenarios are also associated with lower global greenhouse gas emissions and, consequently, the potential to reduce both the drivers of anthropogenic climate change and the impacts of changing conditions. The residential housing and impervious surface datasets provide a substantial first step toward comprehensive national land use/land cover scenarios, which have broad applicability for integrated assessments as these data and tools are publicly available. PMID:21078956

Carbon-climate-human interactions in an integrated human-Earth system model

NASA Astrophysics Data System (ADS)

Calvin, K. V.; Bond-Lamberty, B. P.; Jones, A. D.; Shi, X.

2016-12-01

The C4MIP and CMIP5 results highlighted large uncertainties in climate projections, driven to a large extent by limited understanding of the interactions between terrestrial carbon-cycle and climate feedbacks, and their associated uncertainties. These feedbacks are dominated by uncertainties in soil processes, disturbance dynamics, ecosystem response to climate change, and agricultural productivity, and land-use change. This research addresses three questions: (1) how do terrestrial feedbacks vary across different levels of climate change, (2) what is the relative contribution of CO2 fertilization and climate change, and (3) how robust are the results across different models and methods? We used a coupled modeling framework that integrates an Integrated Assessment Model (modeling economic and energy activity) with an Earth System Model (modeling the natural earth system) to examine how business-as-usual (RCP 8.5) climate change will affect ecosystem productivity, cropland extent, and other aspects of the human-Earth system. We find that higher levels of radiative forcing result in higher productivity growth, that increases in CO2 concentrations are the dominant contributors to that growth, and that our productivity increases fall in the middle of the range when compared to other CMIP5 models and the AgMIP models. These results emphasize the importance of examining both the anthropogenic and natural components of the earth system, and their long-term interactive feedbacks.

Time-varying Concurrent Risk of Extreme Droughts and Heatwaves in California

NASA Astrophysics Data System (ADS)

Sarhadi, A.; Diffenbaugh, N. S.; Ausin, M. C.

2016-12-01

Anthropogenic global warming has changed the nature and the risk of extreme climate phenomena such as droughts and heatwaves. The concurrent of these nature-changing climatic extremes may result in intensifying undesirable consequences in terms of human health and destructive effects in water resources. The present study assesses the risk of concurrent extreme droughts and heatwaves under dynamic nonstationary conditions arising from climate change in California. For doing so, a generalized fully Bayesian time-varying multivariate risk framework is proposed evolving through time under dynamic human-induced environment. In this methodology, an extreme, Bayesian, dynamic copula (Gumbel) is developed to model the time-varying dependence structure between the two different climate extremes. The time-varying extreme marginals are previously modeled using a Generalized Extreme Value (GEV) distribution. Bayesian Markov Chain Monte Carlo (MCMC) inference is integrated to estimate parameters of the nonstationary marginals and copula using a Gibbs sampling method. Modelled marginals and copula are then used to develop a fully Bayesian, time-varying joint return period concept for the estimation of concurrent risk. Here we argue that climate change has increased the chance of concurrent droughts and heatwaves over decades in California. It is also demonstrated that a time-varying multivariate perspective should be incorporated to assess realistic concurrent risk of the extremes for water resources planning and management in a changing climate in this area. The proposed generalized methodology can be applied for other stochastic nature-changing compound climate extremes that are under the influence of climate change.

Carbon sequestration in managed temperate coniferous forests under climate change

NASA Astrophysics Data System (ADS)

Dymond, Caren C.; Beukema, Sarah; Nitschke, Craig R.; Coates, K. David; Scheller, Robert M.

2016-03-01

Management of temperate forests has the potential to increase carbon sinks and mitigate climate change. However, those opportunities may be confounded by negative climate change impacts. We therefore need a better understanding of climate change alterations to temperate forest carbon dynamics before developing mitigation strategies. The purpose of this project was to investigate the interactions of species composition, fire, management, and climate change in the Copper-Pine Creek valley, a temperate coniferous forest with a wide range of growing conditions. To do so, we used the LANDIS-II modelling framework including the new Forest Carbon Succession extension to simulate forest ecosystems under four different productivity scenarios, with and without climate change effects, until 2050. Significantly, the new extension allowed us to calculate the net sector productivity, a carbon accounting metric that integrates aboveground and belowground carbon dynamics, disturbances, and the eventual fate of forest products. The model output was validated against literature values. The results implied that the species optimum growing conditions relative to current and future conditions strongly influenced future carbon dynamics. Warmer growing conditions led to increased carbon sinks and storage in the colder and wetter ecoregions but not necessarily in the others. Climate change impacts varied among species and site conditions, and this indicates that both of these components need to be taken into account when considering climate change mitigation activities and adaptive management. The introduction of a new carbon indicator, net sector productivity, promises to be useful in assessing management effectiveness and mitigation activities.

The integrated Earth system model version 1: formulation and functionality

DOE PAGES

Collins, W. D.; Craig, A. P.; Truesdale, J. E.; ...

2015-07-23

The integrated Earth system model (iESM) has been developed as a new tool for projecting the joint human/climate system. The iESM is based upon coupling an integrated assessment model (IAM) and an Earth system model (ESM) into a common modeling infrastructure. IAMs are the primary tool for describing the human–Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species (SLS), land use and land cover change (LULCC), and other resource-related drivers of anthropogenic climate change. ESMs are the primary scientific tools for examining the physical, chemical, and biogeochemical impacts of human-induced changes to the climate system. Themore » iESM project integrates the economic and human-dimension modeling of an IAM and a fully coupled ESM within a single simulation system while maintaining the separability of each model if needed. Both IAM and ESM codes are developed and used by large communities and have been extensively applied in recent national and international climate assessments. By introducing heretofore-omitted feedbacks between natural and societal drivers, we can improve scientific understanding of the human–Earth system dynamics. Potential applications include studies of the interactions and feedbacks leading to the timing, scale, and geographic distribution of emissions trajectories and other human influences, corresponding climate effects, and the subsequent impacts of a changing climate on human and natural systems. This paper describes the formulation, requirements, implementation, testing, and resulting functionality of the first version of the iESM released to the global climate community.« less

Holistic view to integrated climate change assessment and extreme weather adaptation in the Lake Victoria Basin East Africa

NASA Astrophysics Data System (ADS)

Mutua, F.; Koike, T.

2013-12-01

Extreme weather events have been the leading cause of disasters and damage all over the world.The primary ingredient to these disasters especially floods is rainfall which over the years, despite advances in modeling, computing power and use of new data and technologies, has proven to be difficult to predict. Also, recent climate projections showed a pattern consistent with increase in the intensity and frequency of extreme events in the East African region.We propose a holistic integrated approach to climate change assessment and extreme event adaptation through coupling of analysis techniques, tools and data. The Lake Victoria Basin (LVB) in East Africa supports over three million livelihoods and is a valuable resource to five East African countries as a source of water and means of transport. However, with a Mesoscale weather regime driven by land and lake dynamics,extreme Mesoscale events have been prevalent and the region has been on the receiving end during anomalously wet years in the region. This has resulted in loss of lives, displacements, and food insecurity. In the LVB, the effects of climate change are increasingly being recognized as a significant contributor to poverty, by its linkage to agriculture, food security and water resources. Of particular importance are the likely impacts of climate change in frequency and intensity of extreme events. To tackle this aspect, this study adopted an integrated regional, mesoscale and basin scale approach to climate change assessment. We investigated the projected changes in mean climate over East Africa, diagnosed the signals of climate change in the atmosphere, and transferred this understanding to mesoscale and basin scale. Changes in rainfall were analyzed and similar to the IPCC AR4 report; the selected three General Circulation Models (GCMs) project a wetter East Africa with intermittent dry periods in June-August. Extreme events in the region are projected to increase; with the number of wet days exceeding the 90% percentile of 1981-2000 likely to increase by 20-40% in the whole region. We also focused on short-term weather forecasting as a step towards adapting to a changing climate. This involved dynamic downscaling of global weather forecasts to high resolution with a special focus on extreme events. By utilizing complex model dynamics, the system was able to reproduce the Mesoscale dynamics well, simulated the land/lake breeze and diurnal pattern but was inadequate in some aspects. The quantitative prediction of rainfall was inaccurate with overestimation and misplacement but with reasonable occurrence. To address these shortcomings we investigated the value added by assimilating Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperature during the event. By assimilating 23GHz (sensitive to water) and 89GHz (sensitive to cloud) frequency brightness temperature; the predictability of an extreme rain weather event was investigated. The assimilation through a Cloud Microphysics Data Assimilation (CMDAS) into the weather prediction model considerably improved the spatial distribution of this event.

Participatory Climate Research in a Dynamic Urban Context

NASA Astrophysics Data System (ADS)

Horton, R. M.

2016-12-01

The Consortium for Climate Risk in the Urban Northeast (CCRUN), one of ten NOAA-RISA's, supports resilience efforts in the urban corridor stretching from Philadelphia to Boston. Challenges and opportunities include the diverse set of needs in broad urban contexts, as well as the integration of interdisciplinary perspectives. CCRUN is addressing these challenges through 1) stakeholder surveys, 2) webinar series that enable scientists to engage with stakeholders, 3) leveraging extreme events as focusing opportunities, and 4) the development of an integrated project framework. Moving forward, increasing extreme events can lead to unexpected detours, and further effort is needed around facilitating place-based research in an interdisciplinary context.

Managing living marine resources in a dynamic environment: The role of seasonal to decadal climate forecasts

NASA Astrophysics Data System (ADS)

Tommasi, Desiree; Stock, Charles A.; Hobday, Alistair J.; Methot, Rick; Kaplan, Isaac C.; Eveson, J. Paige; Holsman, Kirstin; Miller, Timothy J.; Gaichas, Sarah; Gehlen, Marion; Pershing, Andrew; Vecchi, Gabriel A.; Msadek, Rym; Delworth, Tom; Eakin, C. Mark; Haltuch, Melissa A.; Séférian, Roland; Spillman, Claire M.; Hartog, Jason R.; Siedlecki, Samantha; Samhouri, Jameal F.; Muhling, Barbara; Asch, Rebecca G.; Pinsky, Malin L.; Saba, Vincent S.; Kapnick, Sarah B.; Gaitan, Carlos F.; Rykaczewski, Ryan R.; Alexander, Michael A.; Xue, Yan; Pegion, Kathleen V.; Lynch, Patrick; Payne, Mark R.; Kristiansen, Trond; Lehodey, Patrick; Werner, Francisco E.

2017-03-01

Recent developments in global dynamical climate prediction systems have allowed for skillful predictions of climate variables relevant to living marine resources (LMRs) at a scale useful to understanding and managing LMRs. Such predictions present opportunities for improved LMR management and industry operations, as well as new research avenues in fisheries science. LMRs respond to climate variability via changes in physiology and behavior. For species and systems where climate-fisheries links are well established, forecasted LMR responses can lead to anticipatory and more effective decisions, benefitting both managers and stakeholders. Here, we provide an overview of climate prediction systems and advances in seasonal to decadal prediction of marine-resource relevant environmental variables. We then describe a range of climate-sensitive LMR decisions that can be taken at lead-times of months to decades, before highlighting a range of pioneering case studies using climate predictions to inform LMR decisions. The success of these case studies suggests that many additional applications are possible. Progress, however, is limited by observational and modeling challenges. Priority developments include strengthening of the mechanistic linkages between climate and marine resource responses, development of LMR models able to explicitly represent such responses, integration of climate driven LMR dynamics in the multi-driver context within which marine resources exist, and improved prediction of ecosystem-relevant variables at the fine regional scales at which most marine resource decisions are made. While there are fundamental limits to predictability, continued advances in these areas have considerable potential to make LMR managers and industry decision more resilient to climate variability and help sustain valuable resources. Concerted dialog between scientists, LMR managers and industry is essential to realizing this potential.

Using Copernicus earth observation services to monitor climate change impacts and adaptations

NASA Astrophysics Data System (ADS)

Becker, Daniel; Zebisch, Marc; Sonnenschein, Ruth; Schönthaler, Konstanze; von Andrian-Werburg, Stefan

2016-04-01

In the last years, earth observation made a big leap towards an operational monitoring of the state of environment. Remote sensing provides for instance information on the dynamics, trends and anomalies of snow and glaciers, vegetation, soil moisture or water temperature. In particular, the European Copernicus initiative offers new opportunities through new satellites with a higher temporal and spatial resolution, operational services for environmental monitoring and an open data access policy. With the Copernicus climate change service and the ESA climate change initiative, specific earth observation programs are in place to address the impacts of climate change. However, such products and services are until now rarely picked up in the field of policy or decision making oriented climate impact or climate risk assessments. In this talk, we will present results of a study, which focus on the question, if and how remote sensing approaches could be integrated into operational monitoring activities of climate impacts and response measures on a national and subnational scale. We assessed all existing and planned Copernicus services regarding their relevance for climate impact monitoring by comparing them against the indication fields from an indicator system for climate impact and response monitoring in Germany, which has lately been developed in the framework of the German national adaptation strategy. For several climate impact or response indicators, an immediate integration of remote sensing data could be identified and been recommended. For these cases, we will show practical examples on the benefit of remote sensing data. For other indication fields, promising approaches were found, which need further development. We argue that remote sensing is a very valuable complement to the existing indicator schemes by contributing with spatial explicit, timely information but not always easy to integrate with classical approaches, which are oriented towards consistent long term monitoring. Furthermore, we provide specific recommendations for the Copernicus services to ensure a consistent climate change monitoring in future and we indicate options and limitations for integrating service products into practical assessment and monitoring activities.

Regional Approach for Linking Ecosystem Services and Livelihood Strategies Under Climate Change of Pastoral Communities in the Mongolian Steppe Ecosystem

NASA Astrophysics Data System (ADS)

Ojima, D. S.; Galvin, K.; Togtohyn, C.

2012-12-01

Dramatic changes due to climate and land use dynamics in the Mongolian Plateau affecting ecosystem services and agro-pastoral systems in Mongolia. Recently, market forces and development strategies are affecting land and water resources of the pastoral communities which are being further stressed due to climatic changes. Evaluation of pastoral systems, where humans depend on livestock and grassland ecosystem services, have demonstrated the vulnerability of the social-ecological system to climate change. Current social-ecological changes in ecosystem services are affecting land productivity and carrying capacity, land-atmosphere interactions, water resources, and livelihood strategies. The general trend involves greater intensification of resource exploitation at the expense of traditional patterns of extensive range utilization. Thus we expect climate-land use-land cover relationships to be crucially modified by the social-economic forces. The analysis incorporates information about the social-economic transitions taking place in the region which affect land-use, food security, and ecosystem dynamics. The region of study extends from the Mongolian plateau in Mongolia. Our research indicate that sustainability of pastoral systems in the region needs to integrate the impact of climate change on ecosystem services with socio-economic changes shaping the livelihood strategies of pastoral systems in the region. Adaptation strategies which incorporate integrated analysis of landscape management and livelihood strategies provides a framework which links ecosystem services to critical resource assets. Analysis of the available livelihood assets provides insights to the adaptive capacity of various agents in a region or in a community. Sustainable development pathways which enable the development of these adaptive capacity elements will lead to more effective adaptive management strategies for pastoral land use and herder's living standards. Pastoralists will have the opportunity to utilize seasonal resources and enhance their ability to process and manufacture products from the available ecosystem services in these dynamic social-ecological systems.

GRACE storage-runoff hystereses reveal the dynamics of ...

EPA Pesticide Factsheets

Watersheds function as integrated systems where climate and geology govern the movement of water. In situ instrumentation can provide local-scale insights into the non-linear relationship between streamflow and water stored in a watershed as snow, soil moisture, and groundwater. However, there is a poor understanding of these processes at the regional scale—primarily because of our inability to measure water stores and fluxes in the subsurface. Now NASA’s Gravity Recovery and Climate Experiment (GRACE) satellites quantify changes in the amount of water stored across and through the Earth, providing measurements of regional hydrologic behavior. Here we apply GRACE data to characterize for the first time how regional watersheds function as simple, dynamic systems through a series of hysteresis loops. While the physical processes underlying the loops are inherently complex, the vertical integration of terrestrial water in the GRACE signal provides process-based insights into the dynamic and non-linear function of regional-scale watersheds. We use this process-based understanding with GRACE data to effectively forecast seasonal runoff (mean R2 of 0.91) and monthly runoff (mean R2 of 0.77) in three regional-scale watersheds (>150,000 km2) of the Columbia River Basin, USA. Data from the Gravity Recovery and Climate Experiment (GRACE) satellites provide a novel dataset for understanding changes in the amount of water stored across and through the surface of the Ear

Improved National Response to Climate Change: Aligning USGCRP reports and the U.S. Climate Resilience Toolkit

NASA Astrophysics Data System (ADS)

Lipschultz, F.; Dahlman, L. E.; Herring, D.; Fox, J. F.

2017-12-01

As part of an effort to coordinate production and distribution of scientific climate information across the U.S. Government, and to spur adaptation actions across the nation, the U.S. Global Change Research Program (USGCRP) has worked to better integrate the U.S. Climate Resilience Toolkit (CRT) and its Climate Explorer (CE) tool into USGCRP activities and products. Much of the initial CRT content was based on the Third National Climate Assessment (NCA3). The opportunity to integrate current development of NCA4—scheduled for release in late 2018—with CRT and CE can enhance all three projects and result in a useable and "living" NCA that is part of USGCRP's approach to sustained climate assessment. To coordinate this work, a USGCRP-led science team worked with CRT staff and CE developers to update the set of climate projections displayed in the CE tool. In concert with the USGCRP scenarios effort, the combined team selected the Localized Constructed Analogs (LOCA) dataset for the updated version of CE, based on its capabilities for capturing climate extremes and local climate variations. The team identified 28 variables from the LOCA dataset for display in the CE; many of these variables will also be used in USGCRP reports. In CRT engagements, communities with vulnerable assets have expressed a high value for the ability to integrate climate data available through the CE with data related to non-climate stressors in their locations. Moving forward, the teams intend to serve climate information needs at additional spatial scales by making NCA4 content available via CE's capability for dynamic interaction with climate-relevant datasets. This will permit users to customize the extent of data they access for decision-making, starting with the static NCA4 report. Additionally, NCA4 case studies and other content can be linked to more in-depth content within the CRT site. This capability will enable more frequent content updates than can be managed with quadrennial NCA reports. Overall, enhanced integration between USGCRP and CRT will provide consistent information for communities that are assessing their climate vulnerabilities or considering adaptation options.

The Equations of Oceanic Motions

NASA Astrophysics Data System (ADS)

Müller, Peter

2006-10-01

Modeling and prediction of oceanographic phenomena and climate is based on the integration of dynamic equations. The Equations of Oceanic Motions derives and systematically classifies the most common dynamic equations used in physical oceanography, from large scale thermohaline circulations to those governing small scale motions and turbulence. After establishing the basic dynamical equations that describe all oceanic motions, M|ller then derives approximate equations, emphasizing the assumptions made and physical processes eliminated. He distinguishes between geometric, thermodynamic and dynamic approximations and between the acoustic, gravity, vortical and temperature-salinity modes of motion. Basic concepts and formulae of equilibrium thermodynamics, vector and tensor calculus, curvilinear coordinate systems, and the kinematics of fluid motion and wave propagation are covered in appendices. Providing the basic theoretical background for graduate students and researchers of physical oceanography and climate science, this book will serve as both a comprehensive text and an essential reference.

A platform to integrate climate information and rural telemedicine in Malawi

NASA Astrophysics Data System (ADS)

Lowe, R.; Chadza, T.; Chirombo, J.; Fonda, C.; Muyepa, A.; Nkoloma, M.; Pietrosemoli, E.; Radicella, S. M.; Tompkins, A. M.; Zennaro, M.

2012-04-01

It is commonly accepted that climate plays a role in the transmission of many infectious diseases, particularly those transmitted by mosquitoes such as malaria, which is one of the most important causes of mortality and morbidity in developing countries. Due to time lags involved in the climate-disease transmission system, lagged observed climate variables could provide some predictive lead for forecasting disease epidemics. This lead time could be extended by using forecasts of the climate in disease prediction models. This project aims to implement a platform for the dissemination of climate-driven disease risk forecasts, using a telemedicine approach. A pilot project has been established in Malawi, where a 162 km wireless link has been installed, spanning from Blantyre City to remote health facilities in the district of Mangochi in the Southern region, bordering Lake Malawi. This long Wi-Fi technology allows rural health facilities to upload real-time disease cases as they occur to an online health information system (DHIS2); a national medical database repository administered by the Ministry of Health. This technology provides a real-time data logging system for disease incidence monitoring and facilitates the flow of information between local and national levels. This platform allows statistical and dynamical disease prediction models to be rapidly updated with real-time climate and epidemiological information. This permits health authorities to target timely interventions ahead of an imminent increase in malaria incidence. By integrating meteorological and health information systems in a statistical-dynamical prediction model, we show that a long-distance Wi-Fi link is a practical and inexpensive means to enable the rapid analysis of real-time information in order to target disease prevention and control measures and mobilise resources at the local level.

From terrestrial to aquatic fluxes: Integrating stream dynamics within a dynamic global vegetation modeling framework

NASA Astrophysics Data System (ADS)

Hoy, Jerad; Poulter, Benjamin; Emmett, Kristen; Cross, Molly; Al-Chokhachy, Robert; Maneta, Marco

2016-04-01

Integrated terrestrial ecosystem models simulate the dynamics and feedbacks between climate, vegetation, disturbance, and hydrology and are used to better understand biogeography and biogeochemical cycles. Extending dynamic vegetation models to the aquatic interface requires coupling surface and sub-surface runoff to catchment routing schemes and has the potential to enhance how researchers and managers investigate how changes in the environment might impact the availability of water resources for human and natural systems. In an effort towards creating such a coupled model, we developed catchment-based hydrologic routing and stream temperature model to pair with LPJ-GUESS, a dynamic global vegetation model. LPJ-GUESS simulates detailed stand-level vegetation dynamics such as growth, carbon allocation, and mortality, as well as various physical and hydrologic processes such as canopy interception and through-fall, and can be applied at small spatial scales, i.e., 1 km. We demonstrate how the coupled model can be used to investigate the effects of transient vegetation dynamics and CO2 on seasonal and annual stream discharge and temperature regimes. As a direct management application, we extend the modeling framework to predict habitat suitability for fish habitat within the Greater Yellowstone Ecosystem, a 200,000 km2 region that provides critical habitat for a range of aquatic species. The model is used to evaluate, quantitatively, the effects of management practices aimed to enhance hydrologic resilience to climate change, and benefits for water storage and fish habitat in the coming century.

Integrated surface/subsurface permafrost thermal hydrology: Model formulation and proof-of-concept simulations

DOE PAGES

Painter, Scott L.; Coon, Ethan T.; Atchley, Adam L.; ...

2016-08-11

The need to understand potential climate impacts and feedbacks in Arctic regions has prompted recent interest in modeling of permafrost dynamics in a warming climate. A new fine-scale integrated surface/subsurface thermal hydrology modeling capability is described and demonstrated in proof-of-concept simulations. The new modeling capability combines a surface energy balance model with recently developed three-dimensional subsurface thermal hydrology models and new models for nonisothermal surface water flows and snow distribution in the microtopography. Surface water flows are modeled using the diffusion wave equation extended to include energy transport and phase change of ponded water. Variation of snow depth in themore » microtopography, physically the result of wind scour, is also modeled heuristically with a diffusion wave equation. The multiple surface and subsurface processes are implemented by leveraging highly parallel community software. Fully integrated thermal hydrology simulations on the tilted open book catchment, an important test case for integrated surface/subsurface flow modeling, are presented. Fine-scale 100-year projections of the integrated permafrost thermal hydrological system on an ice wedge polygon at Barrow Alaska in a warming climate are also presented. Finally, these simulations demonstrate the feasibility of microtopography-resolving, process-rich simulations as a tool to help understand possible future evolution of the carbon-rich Arctic tundra in a warming climate.« less

GRACE storage-runoff hystereses reveal the dynamics of regional watersheds

EPA Science Inventory

Watersheds function as integrated systems where climate and geology govern the movement of water. In situ instrumentation can provide local-scale insights into the non-linear relationship between streamflow and water stored in a watershed as snow, soil moisture, and groundwater. ...

US FRESHWATER RESOURCES IN THE COMING DECADES: AN INTEGRATED CLIMATE-HYDROLOGIC MODELING STUDY

EPA Science Inventory

The outcome is a dynamically and nationally consistent assessment of the range of potential changes in the hydrologic states (snow, soil moisture, groundwater level, river flow, wetland extent) and fluxes (precipitation, evapotranspiration, surface runoff, water table recha...

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.

Young students, satellites aid understanding of climate-biosphere link

NASA Astrophysics Data System (ADS)

White, Michael A.; Schwartz, Mark D.; Running, Steven W.

Data collected by young students from kindergarten through high school are being combined with satellite data to develop a more consistent understanding of the intimate connection between climate dynamics and the terrestrial biosphere. Comparison of the two sets of data involving the onset of budburst among trees and other vegetation has been extremely encouraging.Surface-atmosphere interactions involving exchanges of carbon, water, and energy are strongly affected by interannual variability in the timing and length of the vegetation growing season, and satellite remote sensing has the unique ability to consistently monitor global spatiotemporal variability in growing season dynamics. But without a clear picture of how satellite information (Figure 1) relates to ground conditions, the application of satellite growing season estimates for monitoring of climate-vegetation interactions, calculation of energy budgets, and large-scale ecological modeling is extremely limited.The integrated phenological analysis of field data, satellite observations, and climate advocated by Schwartz [1998], for example, has been primarily limited by the lack of geographically extensive and consistently measured phenology databases.

Ecological dynamics across the Arctic associated with recent climate change.

PubMed

Post, Eric; Forchhammer, Mads C; Bret-Harte, M Syndonia; Callaghan, Terry V; Christensen, Torben R; Elberling, Bo; Fox, Anthony D; Gilg, Olivier; Hik, David S; Høye, Toke T; Ims, Rolf A; Jeppesen, Erik; Klein, David R; Madsen, Jesper; McGuire, A David; Rysgaard, Søren; Schindler, Daniel E; Stirling, Ian; Tamstorf, Mikkel P; Tyler, Nicholas J C; van der Wal, Rene; Welker, Jeffrey; Wookey, Philip A; Schmidt, Niels Martin; Aastrup, Peter

2009-09-11

At the close of the Fourth International Polar Year, we take stock of the ecological consequences of recent climate change in the Arctic, focusing on effects at population, community, and ecosystem scales. Despite the buffering effect of landscape heterogeneity, Arctic ecosystems and the trophic relationships that structure them have been severely perturbed. These rapid changes may be a bellwether of changes to come at lower latitudes and have the potential to affect ecosystem services related to natural resources, food production, climate regulation, and cultural integrity. We highlight areas of ecological research that deserve priority as the Arctic continues to warm.

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

Collins, William D.; Craig, Anthony P.; Truesdale, John E.

The integrated Earth System Model (iESM) has been developed as a new tool for pro- jecting the joint human/climate system. The iESM is based upon coupling an Integrated Assessment Model (IAM) and an Earth System Model (ESM) into a common modeling in- frastructure. IAMs are the primary tool for describing the human–Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species, land use and land cover change, and other resource-related drivers of anthropogenic climate change. ESMs are the primary scientific tools for examining the physical, chemical, and biogeochemical impacts of human-induced changes to the climate system. Themore » iESM project integrates the economic and human dimension modeling of an IAM and a fully coupled ESM within a sin- gle simulation system while maintaining the separability of each model if needed. Both IAM and ESM codes are developed and used by large communities and have been extensively applied in recent national and international climate assessments. By introducing heretofore- omitted feedbacks between natural and societal drivers, we can improve scientific under- standing of the human–Earth system dynamics. Potential applications include studies of the interactions and feedbacks leading to the timing, scale, and geographic distribution of emissions trajectories and other human influences, corresponding climate effects, and the subsequent impacts of a changing climate on human and natural systems. This paper de- scribes the formulation, requirements, implementation, testing, and resulting functionality of the first version of the iESM released to the global climate community.« less

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

Collins, W. D.; Craig, A. P.; Truesdale, J. E.

The integrated Earth system model (iESM) has been developed as a new tool for projecting the joint human/climate system. The iESM is based upon coupling an integrated assessment model (IAM) and an Earth system model (ESM) into a common modeling infrastructure. IAMs are the primary tool for describing the human–Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species (SLS), land use and land cover change (LULCC), and other resource-related drivers of anthropogenic climate change. ESMs are the primary scientific tools for examining the physical, chemical, and biogeochemical impacts of human-induced changes to the climate system. Themore » iESM project integrates the economic and human-dimension modeling of an IAM and a fully coupled ESM within a single simulation system while maintaining the separability of each model if needed. Both IAM and ESM codes are developed and used by large communities and have been extensively applied in recent national and international climate assessments. By introducing heretofore-omitted feedbacks between natural and societal drivers, we can improve scientific understanding of the human–Earth system dynamics. Potential applications include studies of the interactions and feedbacks leading to the timing, scale, and geographic distribution of emissions trajectories and other human influences, corresponding climate effects, and the subsequent impacts of a changing climate on human and natural systems. This paper describes the formulation, requirements, implementation, testing, and resulting functionality of the first version of the iESM released to the global climate community.« less

Integrated Assessment of Climate Change, Agricultural Land Use, and Regional Carbon Changes

NASA Astrophysics Data System (ADS)

MU, J.

2014-12-01

Changes in land use have caused a net release of carbon to the atmosphere over the last centuries and decades1. On one hand, agriculture accounts for 52% and 84% of global anthropogenic methane and nitrous oxide emissions, respectively. On the other hand, many agricultural practices can potentially mitigate greenhouse gas (GHG) emissions, the most prominent of which are improved cropland and grazing land management2. From this perspective, land use change that reduces emissions and/or increases carbon sequestration can play an important role in climate change mitigation. As shown in Figure 1, this paper is an integrated study of climate impacts, land uses, and regional carbon changes to examine, link and assess climate impacts on regional carbon changes via impacts on land uses. This study will contribute to previous research in two aspects: impacts of climate change on future land uses under an uncertain future world and projections of regional carbon dynamics due to changes in future land use. Specifically, we will examine how land use change under historical climate change using observed data and then project changes in land use under future climate projections from 14 Global Climate Models (GCMs) for two emission scenarios (i.e., RCP4.5 and RCP8.5). More importantly, we will investigate future land use under uncertainties with changes in agricultural development and social-economic conditions along with a changing climate. By doing this, we then could integrate with existing efforts by USGS land-change scientists developing and parameterizing models capable of projecting changes across a full spectrum of land use and land cover changes and track the consequences on ecosystem carbon to provide better information for land managers and policy makers when informing climate change adaptation and mitigation policies.

Climate forcing and infectious disease transmission in urban landscapes: integrating demographic and socioeconomic heterogeneity.

PubMed

Santos-Vega, Mauricio; Martinez, Pamela P; Pascual, Mercedes

2016-10-01

Urbanization and climate change are the two major environmental challenges of the 21st century. The dramatic expansion of cities around the world creates new conditions for the spread, surveillance, and control of infectious diseases. In particular, urban growth generates pronounced spatial heterogeneity within cities, which can modulate the effect of climate factors at local spatial scales in large urban environments. Importantly, the interaction between environmental forcing and socioeconomic heterogeneity at local scales remains an open area in infectious disease dynamics, especially for urban landscapes of the developing world. A quantitative and conceptual framework on urban health with a focus on infectious diseases would benefit from integrating aspects of climate forcing, population density, and level of wealth. In this paper, we review what is known about these drivers acting independently and jointly on urban infectious diseases; we then outline elements that are missing and would contribute to building such a framework. © 2016 New York Academy of Sciences.

Assessing the Problem Formulation in an Integrated Assessment Model: Implications for Climate Policy Decision-Support

NASA Astrophysics Data System (ADS)

Garner, G. G.; Reed, P. M.; Keller, K.

2014-12-01

Integrated assessment models (IAMs) are often used with the intent to aid in climate change decisionmaking. Numerous studies have analyzed the effects of parametric and/or structural uncertainties in IAMs, but uncertainties regarding the problem formulation are often overlooked. Here we use the Dynamic Integrated model of Climate and the Economy (DICE) to analyze the effects of uncertainty surrounding the problem formulation. The standard DICE model adopts a single objective to maximize a weighted sum of utilities of per-capita consumption. Decisionmakers, however, may be concerned with a broader range of values and preferences that are not captured by this a priori definition of utility. We reformulate the problem by introducing three additional objectives that represent values such as (i) reliably limiting global average warming to two degrees Celsius and minimizing both (ii) the costs of abatement and (iii) the damages due to climate change. We derive a set of Pareto-optimal solutions over which decisionmakers can trade-off and assess performance criteria a posteriori. We illustrate the potential for myopia in the traditional problem formulation and discuss the capability of this multiobjective formulation to provide decision support.

Towards the Goal of Modular Climate Data Services: An Overview of NCPP Applications and Software

NASA Astrophysics Data System (ADS)

Koziol, B. W.; Cinquini, L.; Treshansky, A.; Murphy, S.; DeLuca, C.

2013-12-01

In August 2013, the National Climate Predictions and Projections Platform (NCPP) organized a workshop focusing on the quantitative evaluation of downscaled climate data products (QED-2013). The QED-2013 workshop focused on real-world application problems drawn from several sectors (e.g. hydrology, ecology, environmental health, agriculture), and required that downscaled downscaled data products be dynamically accessed, generated, manipulated, annotated, and evaluated. The cyberinfrastructure elements that were integrated to support the workshop included (1) a wiki-based project hosting environment (Earth System CoG) with an interface to data services provided by an Earth System Grid Federation (ESGF) data node; (2) metadata tools provided by the Earth System Documentation (ES-DOC) collaboration; and (3) a Python-based library OpenClimateGIS (OCGIS) for subsetting and converting NetCDF-based climate data to GIS and tabular formats. Collectively, this toolset represents a first deployment of a 'ClimateTranslator' that enables users to access, interpret, and apply climate information at local and regional scales. This presentation will provide an overview of these components above, how they were used in the workshop, and discussion of current and potential integration. The long-term strategy for this software stack is to offer the suite of services described on a customizable, per-project basis. Additional detail on the three components is below. (1) Earth System CoG is a web-based collaboration environment that integrates data discovery and access services with tools for supporting governance and the organization of information. QED-2013 utilized these capabilities to share with workshop participants a suite of downscaled datasets, associated images derived from those datasets, and metadata files describing the downscaling techniques involved. The collaboration side of CoG was used for workshop organization, discussion, and results. (2) The ES-DOC Questionnaire, Viewer, and Comparator are web-based tools for the creation and use of model and experiment documentation. Workshop participants used the Questionnaire to generate metadata on regional downscaling models and statistical downscaling methods, and the Viewer to display the results. A prototype Comparator was available to compare properties across dynamically downscaled models. (3) OCGIS is a Python (v2.7) package designed for geospatial manipulation, subsetting, computation, and translation of Climate and Forecasting (CF)-compliant climate datasets - either stored in local NetCDF files, or files served through THREDDS data servers.

The climate4impact platform: Providing, tailoring and facilitating climate model data access

NASA Astrophysics Data System (ADS)

Pagé, Christian; Pagani, Andrea; Plieger, Maarten; Som de Cerff, Wim; Mihajlovski, Andrej; de Vreede, Ernst; Spinuso, Alessandro; Hutjes, Ronald; de Jong, Fokke; Bärring, Lars; Vega, Manuel; Cofiño, Antonio; d'Anca, Alessandro; Fiore, Sandro; Kolax, Michael

2017-04-01

One of the main objectives of climate4impact is to provide standardized web services and tools that are reusable in other portals. These services include web processing services, web coverage services and web mapping services (WPS, WCS and WMS). Tailored portals can be targeted to specific communities and/or countries/regions while making use of those services. Easier access to climate data is very important for the climate change impact communities. To fulfill this objective, the climate4impact (http://climate4impact.eu/) web portal and services has been developed, targeting climate change impact modellers, impact and adaptation consultants, as well as other experts using climate change data. It provides to users harmonized access to climate model data through tailored services. It features static and dynamic documentation, Use Cases and best practice examples, an advanced search interface, an integrated authentication and authorization system with the Earth System Grid Federation (ESGF), a visualization interface with ADAGUC web mapping tools. In the latest version, statistical downscaling services, provided by the Santander Meteorology Group Downscaling Portal, were integrated. An innovative interface to integrate statistical downscaling services will be released in the upcoming version. The latter will be a big step in bridging the gap between climate scientists and the climate change impact communities. The climate4impact portal builds on the infrastructure of an international distributed database that has been set to disseminate the results from the global climate model results of the Coupled Model Intercomparison project Phase 5 (CMIP5). This database, the ESGF, is an international collaboration that develops, deploys and maintains software infrastructure for the management, dissemination, and analysis of climate model data. The European FP7 project IS-ENES, Infrastructure for the European Network for Earth System modelling, supports the European contribution to ESGF and contributes to the ESGF open source effort, notably through the development of search, monitoring, quality control, and metadata services. In its second phase, IS-ENES2 supports the implementation of regional climate model results from the international Coordinated Regional Downscaling Experiments (CORDEX). These services were extended within the European FP7 Climate Information Portal for Copernicus (CLIPC) project, and some could be later integrated into the European Copernicus platform.

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.

Dynamic integration of land use changes in a hydrologic assessment of a rapidly developing Indian catchment.

PubMed

Wagner, Paul D; Bhallamudi, S Murty; Narasimhan, Balaji; Kantakumar, Lakshmi N; Sudheer, K P; Kumar, Shamita; Schneider, Karl; Fiener, Peter

2016-01-01

Rapid land use and land-cover changes strongly affect water resources. Particularly in regions that experience seasonal water scarcity, land use scenario assessments provide a valuable basis for the evaluation of possible future water shortages. The objective of this study is to dynamically integrate land use model projections with a hydrologic model to analyze potential future impacts of land use change on the water resources of a rapidly developing catchment upstream of Pune, India. For the first time projections from the urban growth and land use change model SLEUTH are employed as a dynamic input to the hydrologic model SWAT. By this means, impacts of land use changes on the water balance components are assessed for the near future (2009-2028) employing four different climate conditions (baseline, IPCC A1B, dry, wet). The land use change modeling results in an increase of urban area by +23.1% at the fringes of Pune and by +12.2% in the upper catchment, whereas agricultural land (-14.0% and -0.3%, respectively) and semi-natural area (-9.1% and -11.9%, respectively) decrease between 2009 and 2028. Under baseline climate conditions, these land use changes induce seasonal changes in the water balance components. Water yield particularly increases at the onset of monsoon (up to +11.0mm per month) due to increased impervious area, whereas evapotranspiration decreases in the dry season (up to -15.1mm per month) as a result of the loss of irrigated agricultural area. As the projections are made for the near future (2009-2028) land use change impacts are similar under IPCC A1B climate conditions. Only if more extreme dry years occur, an exacerbation of the land use change impacts can be expected. Particularly in rapidly changing environments an implementation of both dynamic land use change and climate change seems favorable to assess seasonal and gradual changes in the water balance. Copyright © 2015 Elsevier B.V. All rights reserved.

Integrated population modeling reveals the impact of climate on the survival of juvenile emperor penguins.

PubMed

Abadi, Fitsum; Barbraud, Christophe; Gimenez, Olivier

2017-03-01

Early-life demographic traits are poorly known, impeding our understanding of population processes and sensitivity to climate change. Survival of immature individuals is a critical component of population dynamics and recruitment in particular. However, obtaining reliable estimates of juvenile survival (i.e., from independence to first year) remains challenging, as immatures are often difficult to observe and to monitor individually in the field. This is particularly acute for seabirds, in which juveniles stay at sea and remain undetectable for several years. In this work, we developed a Bayesian integrated population model to estimate the juvenile survival of emperor penguins (Aptenodytes forsteri), and other demographic parameters including adult survival and fecundity of the species. Using this statistical method, we simultaneously analyzed capture-recapture data of adults, the annual number of breeding females, and the number of fledglings of emperor penguins collected at Dumont d'Urville, Antarctica, for the period 1971-1998. We also assessed how climate covariates known to affect the species foraging habitats and prey [southern annular mode (SAM), sea ice concentration (SIC)] affect juvenile survival. Our analyses revealed that there was a strong evidence for the positive effect of SAM during the rearing period (SAMR) on juvenile survival. Our findings suggest that this large-scale climate index affects juvenile emperor penguins body condition and survival through its influence on wind patterns, fast ice extent, and distance to open water. Estimating the influence of environmental covariates on juvenile survival is of major importance to understand the impacts of climate variability and change on the population dynamics of emperor penguins and seabirds in general and to make robust predictions on the impact of climate change on marine predators. © 2016 John Wiley & Sons Ltd.

Dispersive models describing mosquitoes’ population dynamics

NASA Astrophysics Data System (ADS)

Yamashita, W. M. S.; Takahashi, L. T.; Chapiro, G.

2016-08-01

The global incidences of dengue and, more recently, zica virus have increased the interest in studying and understanding the mosquito population dynamics. Understanding this dynamics is important for public health in countries where climatic and environmental conditions are favorable for the propagation of these diseases. This work is based on the study of nonlinear mathematical models dealing with the life cycle of the dengue mosquito using partial differential equations. We investigate the existence of traveling wave solutions using semi-analytical method combining dynamical systems techniques and numerical integration. Obtained solutions are validated through numerical simulations using finite difference schemes.

Combined effects of climate and land management on watershed vegetation dynamics in an arid environment.

PubMed

Liu, Peilong; Hao, Lu; Pan, Cen; Zhou, Decheng; Liu, Yongqiang; Sun, Ge

2017-07-01

Leaf area index (LAI) is a key parameter to characterize vegetation dynamics and ecosystem structure that determines the ecosystem functions and services such as clean water supply and carbon sequestration in a watershed. However, linking LAI dynamics and environmental controls (i.e., coupling biosphere, atmosphere, and anthroposphere) remains challenging and such type of studies have rarely been done at a watershed scale due to data availability. The present study examined the spatial and temporal variations of LAI for five ecosystem types within a watershed with a complex topography in the Upper Heihe River Basin, a major inland river in the arid and semi-arid western China. We integrated remote sensing-based GLASS (Global Land Surface Satellite) LAI products, interpolated climate data, watershed characteristics, and land management records for the period of 2001-2012. We determined the relationships among LAI, topography, air temperature and precipitation, and grazing history by five ecosystem types using several advanced statistical methods. We show that long-term mean LAI distribution had an obvious vertical pattern as controlled by precipitation and temperature in a hilly watershed. Overall, watershed-wide mean LAI had an increasing trend overtime for all ecosystem types during 2001-2012, presumably as a result of global warming and a wetting climate. However, the fluctuations of observed LAI at a pixel scale (1km) varied greatly across the watershed. We classified the vegetation changes within the watershed as 'Improved', 'Stabilized', and 'Degraded' according their respective LAI changes. We found that climate was not the only driver for temporal vegetation changes for all land cover types. Grazing partially contributed to the decline of LAI in some areas and masked the positive climate warming effects in other areas. Extreme weathers such as cold spells and droughts could substantially affect inter-annual variability of LAI dynamics. We concluded that temporal and spatial LAI dynamics were rather complex and were affected by both climate variations and human disturbances in the study basin. Future monitoring studies should focus on the functional interactions among vegetation dynamics, climate variations, land management, and human disturbances. Published by Elsevier B.V.

Synthesizing late Holocene paleoclimate reconstructions: Lessons learned, common challenges, and implications for future research

NASA Astrophysics Data System (ADS)

Rodysill, J. R.

2017-12-01

Proxy-based reconstructions provide vital information for developing histories of environmental and climate changes. Networks of spatiotemporal paleoclimate information are powerful tools for understanding dynamical processes within the global climate system and improving model-based predictions of the patterns and magnitudes of climate changes at local- to global-scales. Compiling individual paleoclimate records and integrating reconstructed climate information in the context of an ensemble of multi-proxy records, which are fundamental for developing a spatiotemporal climate data network, are hindered by challenges related to data and information accessibility, chronological uncertainty, sampling resolution, climate proxy type, and differences between depositional environments. The U.S. Geological Survey (USGS) North American Holocene Climate Synthesis Working Group has been compiling and integrating multi-proxy paleoclimate data as part of an ongoing effort to synthesize Holocene climate records from North America. The USGS North American Holocene Climate Synthesis Working Group recently completed a late Holocene hydroclimate synthesis for the North American continent using several proxy types from a range of depositional environments, including lakes, wetlands, coastal marine, and cave speleothems. Using new age-depth relationships derived from the Bacon software package, we identified century-scale patterns of wetness and dryness for the past 2000 years with an age uncertainty-based confidence rating for each proxy record. Additionally, for highly-resolved North American lake sediment records, we computed average late Holocene sediment deposition rates and identified temporal trends in age uncertainty that are common to multiple lakes. This presentation addresses strengths and challenges of compiling and integrating data from different paleoclimate archives, with a particular focus on lake sediments, which may inform and guide future paleolimnological studies.

Implicit-Explicit Time Integration Methods for Non-hydrostatic Atmospheric Models

NASA Astrophysics Data System (ADS)

Gardner, D. J.; Guerra, J. E.; Hamon, F. P.; Reynolds, D. R.; Ullrich, P. A.; Woodward, C. S.

2016-12-01

The Accelerated Climate Modeling for Energy (ACME) project is developing a non-hydrostatic atmospheric dynamical core for high-resolution coupled climate simulations on Department of Energy leadership class supercomputers. An important factor in computational efficiency is avoiding the overly restrictive time step size limitations of fully explicit time integration methods due to the stiffest modes present in the model (acoustic waves). In this work we compare the accuracy and performance of different Implicit-Explicit (IMEX) splittings of the non-hydrostatic equations and various Additive Runge-Kutta (ARK) time integration methods. Results utilizing the Tempest non-hydrostatic atmospheric model and the ARKode package show that the choice of IMEX splitting and ARK scheme has a significant impact on the maximum stable time step size as well as solution quality. Horizontally Explicit Vertically Implicit (HEVI) approaches paired with certain ARK methods lead to greatly improved runtimes. With effective preconditioning IMEX splittings that incorporate some implicit horizontal dynamics can be competitive with HEVI results. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-699187

Summer drought predictability over Europe: empirical versus dynamical forecasts

NASA Astrophysics Data System (ADS)

Turco, Marco; Ceglar, Andrej; Prodhomme, Chloé; Soret, Albert; Toreti, Andrea; Doblas-Reyes Francisco, J.

2017-08-01

Seasonal climate forecasts could be an important planning tool for farmers, government and insurance companies that can lead to better and timely management of seasonal climate risks. However, climate seasonal forecasts are often under-used, because potential users are not well aware of the capabilities and limitations of these products. This study aims at assessing the merits and caveats of a statistical empirical method, the ensemble streamflow prediction system (ESP, an ensemble based on reordering historical data) and an operational dynamical forecast system, the European Centre for Medium-Range Weather Forecasts—System 4 (S4) in predicting summer drought in Europe. Droughts are defined using the Standardized Precipitation Evapotranspiration Index for the month of August integrated over 6 months. Both systems show useful and mostly comparable deterministic skill. We argue that this source of predictability is mostly attributable to the observed initial conditions. S4 shows only higher skill in terms of ability to probabilistically identify drought occurrence. Thus, currently, both approaches provide useful information and ESP represents a computationally fast alternative to dynamical prediction applications for drought prediction.

Integrating SPOT-VEGETATION 13-yr time series and land-surface modelling to forecast the terrestrial carbon dynamics in a changing climate - The VEGECLIM project: achievements and lessons learned

NASA Astrophysics Data System (ADS)

Defourny, Pierre; Verbeeck, Hans; Moreau, Inès; De Weirdt, Marjolein; Verhegghen, Astrid; Kibambe-Lubamba, Jean-Paul; Jungers, Quentin; Maignan, Fabienne; Najdovski, Nicolas; Poulter, Benjamin; MacBean, Natasha; Peylin, Philippe

2014-05-01

Vegetation is a major carbon sink and is as such a key component of the international response to climate change caused by the build-up of greenhouse gases in the atmosphere. However, anthropogenic disturbances like deforestation are the primary mechanism that changes ecosystems from carbon sinks to sources, and are hardly included in the current carbon modelling approaches. Moreover, in tropical regions, the seasonal/interannual variability of carbon fluxes is still uncertain and a weak or even no seasonality is taken into account in global vegetation models. In the context of climate change and mitigation policies like "Reducing Emissions from Deforestation and Forest Degradation in Developing Countries" (REDD), it is particularly important to be able to quantify and forecast the vegetation dynamics and carbon fluxes in these regions. The overall objective of the VEGECLIM project is to increase our knowledge on the terrestrial carbon cycle in tropical regions and to improve the forecast of the vegetation dynamics and carbon stocks and fluxes under different climate-change and deforestation scenarios. Such an approach aims to determine whether the African terrestrial carbon balance will remain a net sink or could become a carbon source by the end of the century, according to different climate-change and deforestation scenarios. The research strategy is to integrate the information of the land surface characterizations obtained from 13 years of consistent SPOT-VEGETATION time series (land cover, vegetation phenology through vegetation indices such as the Enhanced Vegetation Index (EVI)) as well as in-situ carbon flux data into the process based ORCHIDEE global vegetation model, capable of simulating vegetation dynamics and carbon balance. Key challenge of this project was to bridge the gap between the land cover and the land surface model teams. Several improvements of the ORCHIDEE model have been realized such as a new seasonal leaf dynamics for tropical evergreen forests, the introduction of spatial soil phosphorus to improve the spatial distribution of simulated woody biomass and an assimilation of smoothed seasonal pattern of satellite-based EVI used as a proxy to vegetation productivity. The outputs of the ORCHIDEE simulations over both Amazon and Congo Basins are discussed with regards to the observed phenology by remote sensing.

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.

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

Understanding the Dynamics of Socio-Hydrological Environment: a Conceptual Framework

NASA Astrophysics Data System (ADS)

Woyessa, Y.; Welderufael, W.; Edossa, D.

2011-12-01

Human actions affect ecological systems and the services they provide through various activities, such as land use, water use, pollution and climate change. Climate change is perhaps one of the most important sustainable development challenges that threaten to undo many of the development efforts being made to reach the targets set for the Millennium Development Goals. Understanding the change of ecosystems under different scenarios of climate and biophysical conditions could assist in bringing the issue of ecosystem services into decision making process. Similarly, the impacts of land use change on ecosystems and biodiversity have received considerable attention from ecologists and hydrologists alike. Land use change in a catchment can impact on water supply by altering hydrological processes, such as infiltration, groundwater recharge, base flow and direct runoff. In the past a variety of models were used for predicting land-use changes. Recently the focus has shifted away from using mathematically oriented models to agent-based modelling (ABM) approach to simulate land use scenarios. A conceptual framework is being developed which integrates climate change scenarios and the human dimension of land use decision into a hydrological model in order to assess its impacts on the socio-hydrological dynamics of a river basin. The following figures present the framework for the analysis and modelling of the socio-hydrological dynamics. Keywords: climate change, land use, river basin

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...

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.

Examining Dynamical Processes of Tropical Mountain Hydroclimate, Particularly During the Wet Season, Through Integration of Autonomous Sensor Observations and Climate Modeling

NASA Astrophysics Data System (ADS)

Hellstrom, R. A.; Fernandez, A.; Mark, B. G.; Covert, J. M.

2016-12-01

Peru is facing imminent water resource issues as glaciers retreat and demand increases, yet limited observations and model resolution hamper understanding of hydrometerological processes on local to regional scales. Much of current global and regional climate studies neglect the meteorological forcing of lapse rates (LRs) and valley and slope wind dynamics on critical components of the Peruvian Andes' water-cycle, and herein we emphasize the wet season. In 2004 and 2005 we installed an autonomous sensor network (ASN) within the glacierized Llanganuco Valley, Cordillera Blanca (9°S), consisting of discrete, cost-effective, automatic temperature loggers located along the valley axis and anchored by two automatic weather stations. Comparisons of these embedded hydrometeorological measurements from the ASN and climate modeling by dynamical downscaling using the Weather Research and Forecasting model (WRF) elucidate distinct diurnal and seasonal characteristics of the mountain wind regime and LRs. Wind, temperature, humidity, and cloud simulations suggest that thermally driven up-valley and slope winds converging with easterly flow aloft enhance late afternoon and evening cloud development which helps explain nocturnal wet season precipitation maxima measured by the ASN. Furthermore, the extreme diurnal variability of along-valley-axis LR, and valley wind detected from ground observations and confirmed by dynamical downscaling demonstrate the importance of realistic scale parameterizations of the atmospheric boundary layer to improve regional climate model projections in mountainous regions. We are currently considering to use intermediate climate models such as ICAR to reduce computing cost and we continue to maintain the ASN in the Cordillera Blanca.

A regional-scale, high resolution dynamical malaria model that accounts for population density, climate and surface hydrology.

PubMed

Tompkins, Adrian M; Ermert, Volker

2013-02-18

The relative roles of climate variability and population related effects in malaria transmission could be better understood if regional-scale dynamical malaria models could account for these factors. A new dynamical community malaria model is introduced that accounts for the temperature and rainfall influences on the parasite and vector life cycles which are finely resolved in order to correctly represent the delay between the rains and the malaria season. The rainfall drives a simple but physically based representation of the surface hydrology. The model accounts for the population density in the calculation of daily biting rates. Model simulations of entomological inoculation rate and circumsporozoite protein rate compare well to data from field studies from a wide range of locations in West Africa that encompass both seasonal endemic and epidemic fringe areas. A focus on Bobo-Dioulasso shows the ability of the model to represent the differences in transmission rates between rural and peri-urban areas in addition to the seasonality of malaria. Fine spatial resolution regional integrations for Eastern Africa reproduce the malaria atlas project (MAP) spatial distribution of the parasite ratio, and integrations for West and Eastern Africa show that the model grossly reproduces the reduction in parasite ratio as a function of population density observed in a large number of field surveys, although it underestimates malaria prevalence at high densities probably due to the neglect of population migration. A new dynamical community malaria model is publicly available that accounts for climate and population density to simulate malaria transmission on a regional scale. The model structure facilitates future development to incorporate migration, immunity and interventions.

A regional-scale, high resolution dynamical malaria model that accounts for population density, climate and surface hydrology

PubMed Central

2013-01-01

Background The relative roles of climate variability and population related effects in malaria transmission could be better understood if regional-scale dynamical malaria models could account for these factors. Methods A new dynamical community malaria model is introduced that accounts for the temperature and rainfall influences on the parasite and vector life cycles which are finely resolved in order to correctly represent the delay between the rains and the malaria season. The rainfall drives a simple but physically based representation of the surface hydrology. The model accounts for the population density in the calculation of daily biting rates. Results Model simulations of entomological inoculation rate and circumsporozoite protein rate compare well to data from field studies from a wide range of locations in West Africa that encompass both seasonal endemic and epidemic fringe areas. A focus on Bobo-Dioulasso shows the ability of the model to represent the differences in transmission rates between rural and peri-urban areas in addition to the seasonality of malaria. Fine spatial resolution regional integrations for Eastern Africa reproduce the malaria atlas project (MAP) spatial distribution of the parasite ratio, and integrations for West and Eastern Africa show that the model grossly reproduces the reduction in parasite ratio as a function of population density observed in a large number of field surveys, although it underestimates malaria prevalence at high densities probably due to the neglect of population migration. Conclusions A new dynamical community malaria model is publicly available that accounts for climate and population density to simulate malaria transmission on a regional scale. The model structure facilitates future development to incorporate migration, immunity and interventions. PMID:23419192

CLIMATIC EFFECTS ON TUNDRA CARBON STORAGE INFERRED FROM EXPERIMENTAL DATA AND A MODEL

EPA Science Inventory

We used a process-based model of ecosystem carbon (C) and nitrogen (N)dynamics, MBL-GEM (Marine Biological Laboratory General Ecosystem Model), to integrated and analyze the results of several experiments that examined the response of arctic tussock tundra to manipulations of CO2...

Design for and efficient dynamic climate model with realistic geography

NASA Technical Reports Server (NTRS)

Suarez, M. J.; Abeles, J.

1984-01-01

The long term climate sensitivity which include realistic atmospheric dynamics are severely restricted by the expense of integrating atmospheric general circulation models are discussed. Taking as an example models used at GSFC for this dynamic model is an alternative which is of much lower horizontal or vertical resolution. The model of Heid and Suarez uses only two levels in the vertical and, although it has conventional grid resolution in the meridional direction, horizontal resolution is reduced by keeping only a few degrees of freedom in the zonal wavenumber spectrum. Without zonally asymmetric forcing this model simulates a day in roughly 1/2 second on a CRAY. The model under discussion is a fully finite differenced, zonally asymmetric version of the Heid-Suarez model. It is anticipated that speeds can be obtained a few seconds a day roughly 50 times faster than moderate resolution, multilayer GCM's.

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.

Adapting agriculture to climate change.

PubMed

Howden, S Mark; Soussana, Jean-François; Tubiello, Francesco N; Chhetri, Netra; Dunlop, Michael; Meinke, Holger

2007-12-11

The strong trends in climate change already evident, the likelihood of further changes occurring, and the increasing scale of potential climate impacts give urgency to addressing agricultural adaptation more coherently. There are many potential adaptation options available for marginal change of existing agricultural systems, often variations of existing climate risk management. We show that implementation of these options is likely to have substantial benefits under moderate climate change for some cropping systems. However, there are limits to their effectiveness under more severe climate changes. Hence, more systemic changes in resource allocation need to be considered, such as targeted diversification of production systems and livelihoods. We argue that achieving increased adaptation action will necessitate integration of climate change-related issues with other risk factors, such as climate variability and market risk, and with other policy domains, such as sustainable development. Dealing with the many barriers to effective adaptation will require a comprehensive and dynamic policy approach covering a range of scales and issues, for example, from the understanding by farmers of change in risk profiles to the establishment of efficient markets that facilitate response strategies. Science, too, has to adapt. Multidisciplinary problems require multidisciplinary solutions, i.e., a focus on integrated rather than disciplinary science and a strengthening of the interface with decision makers. A crucial component of this approach is the implementation of adaptation assessment frameworks that are relevant, robust, and easily operated by all stakeholders, practitioners, policymakers, and scientists.

The effects of increased stream temperatures on juvenile steelhead growth in the Yakima River Basin based on projected climate change scenarios

USGS Publications Warehouse

Hardiman, Jill M.; Mesa, Matthew G.

2013-01-01

Stakeholders within the Yakima River Basin expressed concern over impacts of climate change on mid-Columbia River steelhead (Oncorhynchus mykiss), listed under the Endangered Species Act. We used a bioenergetics model to assess the impacts of changing stream temperatures—resulting from different climate change scenarios—on growth of juvenile steelhead in the Yakima River Basin. We used diet and fish size data from fieldwork in a bioenergetics model and integrated baseline and projected stream temperatures from down-scaled air temperature climate modeling into our analysis. The stream temperature models predicted that daily mean temperatures of salmonid-rearing streams in the basin could increase by 1–2°C and our bioenergetics simulations indicated that such increases could enhance the growth of steelhead in the spring, but reduce it during the summer. However, differences in growth rates of fish living under different climate change scenarios were minor, ranging from about 1–5%. Because our analysis focused mostly on the growth responses of steelhead to changes in stream temperatures, further work is needed to fully understand the potential impacts of climate change. Studies should include evaluating changing stream flows on fish activity and energy budgets, responses of aquatic insects to climate change, and integration of bioenergetics, population dynamics, and habitat responses to climate change.

Quantifying the effects of overgrazing on mountainous watershed vegetation dynamics under a changing climate.

PubMed

Hao, Lu; Pan, Cen; Fang, Di; Zhang, Xiaoyu; Zhou, Decheng; Liu, Peilong; Liu, Yongqiang; Sun, Ge

2018-10-15

Grazing is a major ecosystem disturbance in arid regions that are increasingly threatened by climate change. Understanding the long-term impacts of grazing on rangeland vegetation dynamics in a complex terrain in mountainous regions is important for quantifying dry land ecosystem services for integrated watershed management and climate change adaptation. However, data on the detailed long-term spatial distribution of grazing activities are rare, which prevents trend detection and environmental impact assessments of grazing. This study quantified the impacts of grazing on vegetation dynamics for the period of 1983-2010 in the Upper Heihe River basin, a complex multiple-use watershed in northwestern China. We also examined the relative contributions of grazing and climate to vegetation change using a dynamic grazing pressure method. Spatial grazing patterns and temporal dynamics were mapped at a 1 km × 1 km pixel scale using satellite-derived leaf area index (LAI) data. We found that overgrazing was a dominant driver for LAI reduction in alpine grasslands and shrubs, especially for the periods of 1985-1991 and 1997-2004. Although the recent decade-long active grazing management contributed to the improvement of LAI and partially offset the negative effects of increased livestock, overgrazing has posed significant challenges to shrub-grassland ecosystem recovery in the eastern part of the study basin. We conclude that the positive effects of a warming and wetting climate on vegetation could be underestimated if the negative long-term grazing effects are not considered. Findings from the present case study show that assessing long-term climate change impacts on watersheds must include the influences of human activities. Our study provides important guidance for ecological restoration efforts in locating vulnerable areas and designing effective management practices in the study watershed. Such information is essential for natural resource management that aims at meeting multiple demands of watershed ecosystem services in arid and semiarid rangelands. Copyright © 2018 Elsevier B.V. All rights reserved.

The Beringian coevolution project: Holistic collections of mammals and associated parasites reveal novel perspectives on evolutionary and environmental change in the North

USGS Publications Warehouse

Cook, Joseph A.; Galbreath, Kurt E.; Campbell, Mariel; Carrière, Susanne; Colella, Jocelyn P.; Dawson, Natalie G.; Dunnum, Jonathan L.; Eckerlin, Ralph P.; Greiman, Stephen E.; Fedorov, Vadim B.; Haas, Genevieve M. S.; Haukisalmi, Voitto; Henttonen, Heikki; Hope, Andrew G.; Jackson, Donavan; Jung, Tom; Koehler, Anson V.; Kinsella, John M.; Krejsa, Dianna; Kutz, Susan J.; Liphardt, Schuyler; MacDonald, Stephen O.; Malaney, Jason L.; Makarikov, Arseny; Martin, Jon; McLean, Bryan S.; Mulders, Robert; Nyamsuren, Batsaikhan; Talbot, Sandra L.; Tkach, Vasyl V.; Tsvetkova, Albina; Toman, Heather M.; Waltari, Eric C.; Whitman, Jackson S.; Hoberg, Eric P.

2017-01-01

The Beringian Coevolution Project (BCP), a field program underway in the high northern latitudes since 1999, has focused on building key scientific infrastructure for integrated specimen-based studies on mammals and their associated parasites. BCP has contributed new insights across temporal and spatial scales into how ancient climate and environmental change have shaped faunas, emphasizing processes of assembly, persistence, and diversification across the vast Beringian region. BCP collections also represent baseline records of biotic diversity from across the northern high latitudes at a time of accelerated environmental change. These specimens and associated data form an unmatched resource for identifying hidden diversity, interpreting past responses to climate oscillations, documenting contemporary conditions, and anticipating outcomes for complex biological systems in a regime of ecological perturbation. Because of its dual focus on hosts and parasites, the BCP record also provides a foundation for comparative analyses that can document the effects of dynamic change on the geographic distribution, transmission dynamics, and emergence of pathogens. By using specific examples from carnivores, shrews, lagomorphs, rodents and their associated parasites, we demonstrate how broad, integrated field collections provide permanent infrastructure that informs policy decisions regarding human impact and the effect of climate change on natural populations.

Spatial Selection and Local Adaptation Jointly Shape Life-History Evolution during Range Expansion.

PubMed

Van Petegem, Katrien H P; Boeye, Jeroen; Stoks, Robby; Bonte, Dries

2016-11-01

In the context of climate change and species invasions, range shifts increasingly gain attention because the rates at which they occur in the Anthropocene induce rapid changes in biological assemblages. During range shifts, species experience multiple selection pressures. For poleward expansions in particular, it is difficult to interpret observed evolutionary dynamics because of the joint action of evolutionary processes related to spatial selection and to adaptation toward local climatic conditions. To disentangle the effects of these two processes, we integrated stochastic modeling and data from a common garden experiment, using the spider mite Tetranychus urticae as a model species. By linking the empirical data with those derived form a highly parameterized individual-based model, we infer that both spatial selection and local adaptation contributed to the observed latitudinal life-history divergence. Spatial selection best described variation in dispersal behavior, while variation in development was best explained by adaptation to the local climate. Divergence in life-history traits in species shifting poleward could consequently be jointly determined by contemporary evolutionary dynamics resulting from adaptation to the environmental gradient and from spatial selection. The integration of modeling with common garden experiments provides a powerful tool to study the contribution of these evolutionary processes on life-history evolution during range expansion.

Phenology of mixed woody-herbaceous ecosystems following extreme events: net and differential responses.

PubMed

Rich, Paul M; Breshears, David D; White, Amanda B

2008-02-01

Ecosystem responses to key climate drivers are reflected in phenological dynamics such as the timing and degree of "green-up" that integrate responses over spatial scales from individual plants to ecosystems. This integration is clearest in ecosystems dominated by a single species or life form, such as seasonally dynamic grasslands or more temporally constant evergreen forests. Yet many ecosystems have substantial contribution of cover from both herbaceous and woody evergreen plants. Responses of mixed woody-herbaceous ecosystems to climate are of increasing concern due to their extensive nature, the potential for such systems to yield more complex responses than those dominated by a single life form, and projections that extreme climate and weather events will increase in frequency and intensity with global warming. We present responses of a mixed woody-herbaceous ecosystem type to an extreme event: regional-scale piñon pine mortality following an extended drought and the subsequent herbaceous green-up following the first wet period after the drought. This example highlights how reductions in greenness of the slower, more stable evergreen woody component can rapidly be offset by increases associated with resources made available to the relatively more responsive herbaceous component. We hypothesize that such two-phase phenological responses to extreme events are characteristic of many mixed woody-herbaceous ecosystems.

A multi-year comparison of IPCI scores for prairie pothole wetlands: implications of temporal and spatial variation

USGS Publications Warehouse

Euliss, Ned H.; Mushet, David M.

2011-01-01

In the prairie pothole region of North America, development of Indices of Biotic Integrity (IBIs) to detect anthropogenic impacts on wetlands has been hampered by naturally dynamic inter-annual climate fluctuations. Of multiple efforts to develop IBIs for prairie pothole wetlands, only one, the Index of Plant Community Integrity (IPCI), has reported success. We evaluated the IPCI and its ability to distinguish between natural and anthropogenic variation using plant community data collected from 16 wetlands over a 4-year-period. We found that under constant anthropogenic influence, IPCI metric scores and condition ratings varied annually in response to environmental variation driven primarily by natural climate variation. Artificially forcing wetlands that occur along continuous hydrologic gradients into a limited number of discrete classes (e.g., temporary, seasonal, and semi-permanent) further confounded the utility of IPCI metrics. Because IPCI scores vary significantly due to natural climate dynamics as well as human impacts, methodology must be developed that adequately partitions natural and anthropogenically induced variation along continuous hydrologic gradients. Until such methodology is developed, the use of the IPCI to evaluate prairie pothole wetlands creates potential for misdirected corrective or regulatory actions, impairment of natural wetland functional processes, and erosion of public confidence in the wetland sciences.

Essays on agricultural adaptation to climate change and ethanol market integration in the U.S

NASA Astrophysics Data System (ADS)

Aisabokhae, Ruth Ada

Climate factors like precipitation and temperature, being closely intertwined with agriculture, make a changing climate a big concern for the entire human race and its basic survival. Adaptation to climate is a long-running characteristic of agriculture evidenced by the varying types and forms of agricultural enterprises associated with differing climatic conditions. Nevertheless climate change poses a substantial, additional adaptation challenge for agriculture. Mitigation encompasses efforts to reduce the current and future extent of climate change. Biofuels production, for instance, expands agriculture's role in climate change mitigation. This dissertation encompasses adaptation and mitigation strategies as a response to climate change in the U.S. by examining comprehensively scientific findings on agricultural adaptation to climate change; developing information on the costs and benefits of select adaptations to examine what adaptations are most desirable, for which society can further devote its resources; and studying how ethanol prices are interrelated across, and transmitted within the U.S., and the markets that play an important role in these dynamics. Quantitative analysis using the Forestry and Agricultural Sector Optimization Model (FASOM) shows adaptation to be highly beneficial to agriculture. On-farm varietal and other adaptations contributions outweigh a mix shift northwards significantly, implying progressive technical change and significant returns to adaptation research and investment focused on farm management and varietal adaptations could be quite beneficial over time. Northward shift of corn-acre weighted centroids observed indicates that substantial production potential may shift across regions with the possibility of less production in the South, and more in the North, and thereby, potential redistribution of income. Time series techniques employed to study ethanol price dynamics show that the markets studied are co-integrated and strongly related, with the observable high levels of interaction between all nine cities. Information is transmitted rapidly between these markets. Price seems to be discovered (where shocks originate from) in regions of high demand and perhaps shortages, like Los Angeles and Chicago (metropolitan population centers). The Maximum Likelihood approach following Spiller and Huang's model however shows cities may not belong to the same economic market and the possibility of arbitrage does not exist between all markets.

A vertically integrated snow/ice model over land/sea for climate models. I - Development. II - Impact on orbital change experiments

NASA Technical Reports Server (NTRS)

Neeman, Binyamin U.; Ohring, George; Joseph, Joachim H.

1988-01-01

A vertically integrated formulation (VIF) model for sea ice/snow and land snow is discussed which can simulate the nonlinear effects of heat storage and transfer through the layers of snow and ice. The VIF demonstates the accuracy of the multilayer formulation, while benefitting from the computational flexibility of linear formulations. In the second part, the model is implemented in a seasonal dynamic zonally averaged climate model. It is found that, in response to a change between extreme high and low summer insolation orbits, the winter orbital change dominates over the opposite summer change for sea ice. For snow over land the shorter but more pronounced summer orbital change is shown to dominate.

Sensitivity of the carbon cycle in the Arctic to climate change

USGS Publications Warehouse

McGuire, A. David; Anderson, Leif G.; Christensen, Torben R.; Dallimore, Scott; Guo, Laodong; Hayes, Daniel J.; Heimann, Martin; Lorenson, T.D.; Macdonald, Robie W.; Roulet, Nigel

2009-01-01

The recent warming in the Arctic is affecting a broad spectrum of physical, ecological, and human/cultural systems that may be irreversible on century time scales and have the potential to cause rapid changes in the earth system. The response of the carbon cycle of the Arctic to changes in climate is a major issue of global concern, yet there has not been a comprehensive review of the status of the contemporary carbon cycle of the Arctic and its response to climate change. This review is designed to clarify key uncertainties and vulnerabilities in the response of the carbon cycle of the Arctic to ongoing climatic change. While it is clear that there are substantial stocks of carbon in the Arctic, there are also significant uncertainties associated with the magnitude of organic matter stocks contained in permafrost and the storage of methane hydrates beneath both subterranean and submerged permafrost of the Arctic. In the context of the global carbon cycle, this review demonstrates that the Arctic plays an important role in the global dynamics of both CO2 and CH4. Studies suggest that the Arctic has been a sink for atmospheric CO2 of between 0 and 0.8 Pg C/yr in recent decades, which is between 0% and 25% of the global net land/ocean flux during the 1990s. The Arctic is a substantial source of CH4 to the atmosphere (between 32 and 112 Tg CH4/yr), primarily because of the large area of wetlands throughout the region. Analyses to date indicate that the sensitivity of the carbon cycle of the Arctic during the remainder of the 21st century is highly uncertain. To improve the capability to assess the sensitivity of the carbon cycle of the Arctic to projected climate change, we recommend that (1) integrated regional studies be conducted to link observations of carbon dynamics to the processes that are likely to influence those dynamics, and (2) the understanding gained from these integrated studies be incorporated into both uncoupled and fully coupled carbon–climate modeling efforts.

Corporate funding and ideological polarization about climate change

PubMed Central

Farrell, Justin

2016-01-01

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

Corporate funding and ideological polarization about climate change.

PubMed

Farrell, Justin

2016-01-05

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

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.

Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models

NASA Technical Reports Server (NTRS)

Cess, R. D.; Potter, G. L.; Blanchet, J. P.; Boer, G. J.; Del Genio, A. D.

1990-01-01

The present study provides an intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. This intercomparison uses sea surface temperature change as a surrogate for climate change. The interpretation of cloud-climate interactions is given special attention. A roughly threefold variation in one measure of global climate sensitivity is found among the 19 models. The important conclusion is that most of this variation is attributable to differences in the models' depiction of cloud feedback, a result that emphasizes the need for improvements in the treatment of clouds in these models if they are ultimately to be used as reliable climate predictors. It is further emphazied that cloud feedback is the consequence of all interacting physical and dynamical processes in a general circulation model. The result of these processes is to produce changes in temperature, moisture distribution, and clouds which are integrated into the radiative response termed cloud feedback.

Dynamic hydro-climatic networks in pristine and regulated rivers

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Toward an Improved Representation of Middle Atmospheric Dynamics Thanks to the ARISE Project

NASA Astrophysics Data System (ADS)

Blanc, E.; Ceranna, L.; Hauchecorne, A.; Charlton-Perez, A.; Marchetti, E.; Evers, L. G.; Kvaerna, T.; Lastovicka, J.; Eliasson, L.; Crosby, N. B.; Blanc-Benon, P.; Le Pichon, A.; Brachet, N.; Pilger, C.; Keckhut, P.; Assink, J. D.; Smets, P. S. M.; Lee, C. F.; Kero, J.; Sindelarova, T.; Kämpfer, N.; Rüfenacht, R.; Farges, T.; Millet, C.; Näsholm, S. P.; Gibbons, S. J.; Espy, P. J.; Hibbins, R. E.; Heinrich, P.; Ripepe, M.; Khaykin, S.; Mze, N.; Chum, J.

2018-03-01

This paper reviews recent progress toward understanding the dynamics of the middle atmosphere in the framework of the Atmospheric Dynamics Research InfraStructure in Europe (ARISE) initiative. The middle atmosphere, integrating the stratosphere and mesosphere, is a crucial region which influences tropospheric weather and climate. Enhancing the understanding of middle atmosphere dynamics requires improved measurement of the propagation and breaking of planetary and gravity waves originating in the lowest levels of the atmosphere. Inter-comparison studies have shown large discrepancies between observations and models, especially during unresolved disturbances such as sudden stratospheric warmings for which model accuracy is poorer due to a lack of observational constraints. Correctly predicting the variability of the middle atmosphere can lead to improvements in tropospheric weather forecasts on timescales of weeks to season. The ARISE project integrates different station networks providing observations from ground to the lower thermosphere, including the infrasound system developed for the Comprehensive Nuclear-Test-Ban Treaty verification, the Lidar Network for the Detection of Atmospheric Composition Change, complementary meteor radars, wind radiometers, ionospheric sounders and satellites. This paper presents several examples which show how multi-instrument observations can provide a better description of the vertical dynamics structure of the middle atmosphere, especially during large disturbances such as gravity waves activity and stratospheric warming events. The paper then demonstrates the interest of ARISE data in data assimilation for weather forecasting and re-analyzes the determination of dynamics evolution with climate change and the monitoring of atmospheric extreme events which have an atmospheric signature, such as thunderstorms or volcanic eruptions.

A spatial socio-ecosystem approach to analyse human-environment interactions on climate change adaptation for water resources management

NASA Astrophysics Data System (ADS)

Giupponi, Carlo; Mojtahed, Vahid

2017-04-01

Global climate and socio-economic drivers determine the future patterns of the allocation and the trade of resources and commodities in all markets. The agricultural sector is an emblematic case in which natural (e.g. climate), social (e.g. demography) and economic (e.g. the market) drivers of change interact, determining the evolution of social and ecological systems (or simply socio-ecosystems; SES) over time. In order to analyse the dynamics and possible future evolutions of SES, the combination of local complex systems and global drivers and trends require the development of multiscale approaches. At global level, climatic general circulation models (CGM) and computable general equilibrium or partial equilibrium models have been used for many years to explore the effects of global trends and generate future climate and socio-economic scenarios. Al local level, the inherent complexity of SESs and their spatial and temporal variabilities require different modelling approaches of physical/environmental sub-systems (e.g. field scale crop modelling, GIS-based models, etc.) and of human agency decision makers (e.g. agent based models). Global and local models have different assumption, limitations, constrains, etc., but in some cases integration is possible and several attempts are in progress to couple different models within the so-called Integrated Assessment Models. This work explores an innovative proposal to integrate the global and local approaches, where agent-based models (ABM) are used to simulate spatial (i.e. grid-based) and temporal dynamics of land and water resource use spatial and temporal dynamics, under the effect of global drivers. We focus in particular on how global change may affect land-use allocation at the local to regional level, under the influence of limited natural resources, land and water in particular. We specifically explore how constrains and competition for natural resources may induce non-linearities and discontinuities in socio-ecosystems behaviour. Our general ambition is to explore the feasibility of an approach that could be implemented worldwide through the identification of representative cases described by means of spatially explicit integrated simulations in communication with global modelling. Our specific objective is to test how ABMs can support scenario analysis at regional scale, and in particular how this can facilitate understanding of the role of human agency and its behavioural characteristics in local to global dynamics. The SES of interest is the agro-ecosystem with its relationships with other land uses. In order to test the feasibility of application at global level, all the information about land uses, natural resources, local climate, crop potential productions, etc. were derived from freely available spatial data sets covering the whole planet, which provided the ABM model with spatial information as matrices of pixels. Input maps were extracted from the Global Agro-Ecological Zone (GAEZ) web site of the Food and Agriculture Organization of the United Nations and compiled in the local GIS from where they were then converted in a format compatible with Matlab. In this initial application, an ABM prototype was developed in three test areas around the Mediterranean Basin, in agricultural regions of Tunisia, Italy and Spain.

Analysing Surface Exposure to Climate Dynamics in the Himalayas to Adopt a Planning Framework for Landslide Risk Reduction

NASA Astrophysics Data System (ADS)

Tiwari, A.

2017-12-01

Himalayas rank first in the inventory of most densely populated and congested high altitude mountain regions of the planet. The region is mostly characterized by inadequate infrastructure, lack of mitigation tools along with constraints of terrain undermining the carrying capacity and resilience of urban ecosystems. Moreover, climate change has increased vulnerability of poor and marginalized population living in rapidly urbanizing mountain towns to increased frequency and severity of risks from extreme weather events. Such events pose multifold threat by easily translating to hazards, without the ability to respond and mitigate. Additionally, the recent extreme climate dynamics such as rainfall patterns have influenced the natural rate of surface/slope processes in the Himalaya. The aim of the study was to analyze the extent of interaction between climate dynamics and upland surface to develop participatory planning framework for landslide risk reduction using Integral Geographic Information System (integral GIS). At this stage, the study is limited to only rainfall triggered landslides (RTL). The study region lies in the middle Himalayan range (Himachal). Research utilized terrain analysis tools in integral GIS and identified risk susceptible surface without: 1.adding to its (often) complex fragmentation, and 2. Interference in surface/slope processes. Analysis covered most of the relevant surface factors including geology, slope instability, infrastructure development, natural and urban drainage system, land-cover and land-use as well. The outcome included an exposure-reduced model of existing terrain and the surface-process accommodated by it, with the use of local technical tools available among the poor and fragile mountain community. The final participatory planning framework successfully harmonized people's perception and adaptation knowledge, and incorporated priorities of local authorities. This research is significant as it rises above the fundamental challenges arising during management of the (often) conflicting perspectives, interests, and approaches of multiplicity of stakeholders thereby having vast potential to replicate/upscale in mountains beyond the study region as it ensures barrier free risk-communication through the most affordable and innovative tools.

Climate Variability and Ponderosa Pine Colonizations in Central Wyoming: Integrating Dendroecology and Dendroclimatology

NASA Astrophysics Data System (ADS)

Lesser, M.; Wentzel, C.; Gray, S.; Jackson, S.

2007-12-01

Many tree species are predicted to expand into new territory over the coming decades in response to changing climate. By studying tree expansions over the last several centuries we can begin to understand the mechanisms underlying these changes and anticipate their consequences for forest management. Woody-plant demographics and decadal to multidecadal climate variability are often closely linked in semi-arid regions. Integrated tree-ring analysis, combining dendroecology and dendroclimatology to document, respectively, the demographic history of the population and the climatic history of the region, can reveal ecological dynamics in response to climate variability. We studied four small, disjunct populations of Pinus ponderosa in the Bighorn Basin of north-central Wyoming. These populations are located 30 to 100 kilometers from the nearest core populations of ponderosa pine in the western Bighorn Mountains. Packrat midden studies have shown that ponderosa pine colonized the western slopes of the Bighorn Range 1500 years ago, so the disjunct populations in the basin must be younger. All trees (living and dead) at each of the four disjunct populations were mapped, cored, and then aged using tree-ring based techniques. We obtained records of hydroclimatic variability from the Bighorn Basin using four tree-ring series from Pinus flexilis (3 sites) and Pseudotsuga menziesii (1 site). The four disjunct populations were all established within the past 500 years. Initially, the populations grew slowly with low recruitment rates until the early 19th century, when they experienced one or more large recruitment pulses. These pulses coincided with extended wet periods in the climate reconstruction. However, similar wet periods before the 19th Century were not accompanied by recruitment pulses, indicating that other factors (e.g., population density, genetic variability) are also important in colonization and expansion. We are currently obtaining genetic data and carrying out population modeling to differentiate the effects of population dynamics, genetic variability, and climate variability on recruitment and expansion of these populations.

Between Earth and Sky - Climate Change on the Last Frontier

NASA Astrophysics Data System (ADS)

Weindorf, David; Hunton, Paul

2017-04-01

Globally, Gelisols comprise 11.26 million km2; 8.6% of earth's surface. These soils effectively sequester 25% of global soil organic carbon. Global climate change has disproportionately affected arctic regions of the world, accelerating warming, erosion events, and altering soils and ecosystems. While many documentary films have touched on global climate change, this film is the first to consider the critical role soils play in the biogeochemical carbon cycle. Between Earth and Sky is a feature length documentary filmed in 4K which presents both the science of soil/climate dynamics whilst integrating the perspective of native Alaskans and respected elders of the community who provide personal accounts of changes observed over the past decades in Alaska. More than 40 scientists from universities, governmental research units, and consultancies deconstruct this complex topic to explain how soils form an integral part of the carbon cycle in arctic environments. This presentation will cover the development of the film from initial concepts, writing, fundraising, and project development, through filming on-site, post-production, marketing, and outreach plans.

Ongoing climatic extreme dynamics in Siberia

NASA Astrophysics Data System (ADS)

Gordov, E. P.; Shulgina, T. M.; Okladnikov, I. G.; Titov, A. G.

2013-12-01

Ongoing global climate changes accompanied by the restructuring of global processes in the atmosphere and biosphere are strongly pronounced in the Northern Eurasia regions, especially in Siberia. Recent investigations indicate not only large changes in averaged climatic characteristics (Kabanov and Lykosov, 2006, IPCC, 2007; Groisman and Gutman, 2012), but more frequent occurrence and stronger impacts of climatic extremes are reported as well (Bulygina et al., 2007; IPCC, 2012: Climate Extremes, 2012; Oldenborh et al., 2013). This paper provides the results of daily temperature and precipitation extreme dynamics in Siberia for the last three decades (1979 - 2012). Their seasonal dynamics is assessed using 10th and 90th percentile-based threshold indices that characterize frequency, intensity and duration of climatic extremes. To obtain the geographical pattern of these variations with high spatial resolution, the sub-daily temperature data from ECMWF ERA-Interim reanalysis and daily precipitation amounts from APHRODITE JMA dataset were used. All extreme indices and linear trend coefficients have been calculated using web-GIS information-computational platform Climate (http://climate.scert.ru/) developed to support collaborative multidisciplinary investigations of regional climatic changes and their impacts (Gordov et al., 2012). Obtained results show that seasonal dynamics of daily temperature extremes is asymmetric for tails of cold and warm temperature extreme distributions. Namely, the intensity of warming during cold nights is higher than during warm nights, especially at high latitudes of Siberia. The similar dynamics is observed for cold and warm day-time temperatures. Slight summer cooling was observed in the central part of Siberia. It is associated with decrease in warm temperature extremes. In the southern Siberia in winter, we also observe some cooling mostly due to strengthening of the cold temperature extremes. Changes in daily precipitation extremes are spatially inhomogeneous. The largest increase in frequency and intensity of heavy precipitation is observed in the north of East Siberia. Negative trends related to precipitation amount decrease are found in the central West Siberia and in the south of East Siberia. The authors acknowledge partial financial support for this research from the Russian Foundation for Basic Research projects (11-05-01190 and 13-05-12034), SB RAS Integration project 131 and project VIII.80.2.1., the Ministry of Education and Science of the Russian Federation contract 8345 and grant of the President of Russian Federation (decree 181).

DYNAMICO, an atmospheric dynamical core for high-performance climate modeling

NASA Astrophysics Data System (ADS)

Dubos, Thomas; Meurdesoif, Yann; Spiga, Aymeric; Millour, Ehouarn; Fita, Lluis; Hourdin, Frédéric; Kageyama, Masa; Traore, Abdoul-Khadre; Guerlet, Sandrine; Polcher, Jan

2017-04-01

Institut Pierre Simon Laplace has developed a very scalable atmospheric dynamical core, DYNAMICO, based on energy-conserving finite-difference/finite volume numerics on a quasi-uniform icosahedral-hexagonal mesh. Scalability is achieved by combining hybrid MPI/OpenMP parallelism to asynchronous I/O. This dynamical core has been coupled to radiative transfer physics tailored to the atmosphere of Saturn, allowing unprecedented simulations of the climate of this giant planet. For terrestrial climate studies DYNAMICO is being integrated into the IPSL Earth System Model IPSL-CM. Preliminary aquaplanet and AMIP-style simulations yield reasonable results when compared to outputs from IPSL-CM5. The observed performance suggests that an order of magnitude may be gained with respect to IPSL-CM CMIP5 simulations either on the duration of simulations or on their resolution. Longer simulations would be of interest for the study of paleoclimate, while higher resolution could improve certain aspects of the modeled climate such as extreme events, as will be explored in the HighResMIP project. Following IPSL's strategic vision of building a unified global-regional modelling system, a fully-compressible, non-hydrostatic prototype of DYNAMICO has been developed, enabling future convection-resolving simulations. Work supported by ANR project "HEAT", grant number CE23_2014_HEAT Dubos, T., Dubey, S., Tort, M., Mittal, R., Meurdesoif, Y., and Hourdin, F.: DYNAMICO-1.0, an icosahedral hydrostatic dynamical core designed for consistency and versatility, Geosci. Model Dev., 8, 3131-3150, doi:10.5194/gmd-8-3131-2015, 2015.

Improved Analysis of Earth System Models and Observations using Simple Climate Models

NASA Astrophysics Data System (ADS)

Nadiga, B. T.; Urban, N. M.

2016-12-01

Earth system models (ESM) are the most comprehensive tools we have to study climate change and develop climate projections. However, the computational infrastructure required and the cost incurred in running such ESMs precludes direct use of such models in conjunction with a wide variety of tools that can further our understanding of climate. Here we are referring to tools that range from dynamical systems tools that give insight into underlying flow structure and topology to tools that come from various applied mathematical and statistical techniques and are central to quantifying stability, sensitivity, uncertainty and predictability to machine learning tools that are now being rapidly developed or improved. Our approach to facilitate the use of such models is to analyze output of ESM experiments (cf. CMIP) using a range of simpler models that consider integral balances of important quantities such as mass and/or energy in a Bayesian framework.We highlight the use of this approach in the context of the uptake of heat by the world oceans in the ongoing global warming. Indeed, since in excess of 90% of the anomalous radiative forcing due greenhouse gas emissions is sequestered in the world oceans, the nature of ocean heat uptake crucially determines the surface warming that is realized (cf. climate sensitivity). Nevertheless, ESMs themselves are never run long enough to directly assess climate sensitivity. So, we consider a range of models based on integral balances--balances that have to be realized in all first-principles based models of the climate system including the most detailed state-of-the art climate simulations. The models range from simple models of energy balance to those that consider dynamically important ocean processes such as the conveyor-belt circulation (Meridional Overturning Circulation, MOC), North Atlantic Deep Water (NADW) formation, Antarctic Circumpolar Current (ACC) and eddy mixing. Results from Bayesian analysis of such models using both ESM experiments and actual observations are presented. One such result points to the importance of direct sequestration of heat below 700 m, a process that is not allowed for in the simple models that have been traditionally used to deduce climate sensitivity.

Influence of feedbacks from simulated crop growth on integrated regional hydrologic simulations under climate scenarios

NASA Astrophysics Data System (ADS)

van Walsum, P. E. V.

2011-11-01

Climate change impact modelling of hydrologic responses is hampered by climate-dependent model parameterizations. Reducing this dependency was one of the goals of extending the regional hydrologic modelling system SIMGRO with a two-way coupling to the crop growth simulation model WOFOST. The coupling includes feedbacks to the hydrologic model in terms of the root zone depth, soil cover, leaf area index, interception storage capacity, crop height and crop factor. For investigating whether such feedbacks lead to significantly different simulation results, two versions of the model coupling were set up for a test region: one with exogenous vegetation parameters, the "static" model, and one with endogenous simulation of the crop growth, the "dynamic" model WOFOST. The used parameterization methods of the static/dynamic vegetation models ensure that for the current climate the simulated long-term average of the actual evapotranspiration is the same for both models. Simulations were made for two climate scenarios. Owing to the higher temperatures in combination with a higher CO2-concentration of the atmosphere, a forward time shift of the crop development is simulated in the dynamic model; the used arable land crop, potatoes, also shows a shortening of the growing season. For this crop, a significant reduction of the potential transpiration is simulated compared to the static model, in the example by 15% in a warm, dry year. In consequence, the simulated crop water stress (the unit minus the relative transpiration) is lower when the dynamic model is used; also the simulated increase of crop water stress due to climate change is lower; in the example, the simulated increase is 15 percentage points less (of 55) than when a static model is used. The static/dynamic models also simulate different absolute values of the transpiration. The difference is most pronounced for potatoes at locations with ample moisture supply; this supply can either come from storage release of a good soil or from capillary rise. With good supply of moisture, the dynamic model simulates up to 10% less actual evapotranspiration than the static one in the example. This can lead to cases where the dynamic model predicts a slight increase of the recharge in a climate scenario, where the static model predicts a decrease. The use of a dynamic model also affects the simulated demand for surface water from external sources; especially the timing is affected. The proposed modelling approach uses postulated relationships that require validation with controlled field trials. In the Netherlands there is a lack of experimental facilities for performing such validations.

Climate impacts of energy technologies depend on emissions timing

NASA Astrophysics Data System (ADS)

Edwards, Morgan R.; Trancik, Jessika E.

2014-05-01

Energy technologies emit greenhouse gases with differing radiative efficiencies and atmospheric lifetimes. Standard practice for evaluating technologies, which uses the global warming potential (GWP) to compare the integrated radiative forcing of emitted gases over a fixed time horizon, does not acknowledge the importance of a changing background climate relative to climate change mitigation targets. Here we demonstrate that the GWP misvalues the impact of CH4-emitting technologies as mid-century approaches, and we propose a new class of metrics to evaluate technologies based on their time of use. The instantaneous climate impact (ICI) compares gases in an expected radiative forcing stabilization year, and the cumulative climate impact (CCI) compares their time-integrated radiative forcing up to a stabilization year. Using these dynamic metrics, we quantify the climate impacts of technologies and show that high-CH4-emitting energy sources become less advantageous over time. The impact of natural gas for transportation, with CH4 leakage, exceeds that of gasoline within 1-2 decades for a commonly cited 3 W m-2 stabilization target. The impact of algae biodiesel overtakes that of corn ethanol within 2-3 decades, where algae co-products are used to produce biogas and corn co-products are used for animal feed. The proposed metrics capture the changing importance of CH4 emissions as a climate threshold is approached, thereby addressing a major shortcoming of the GWP for technology evaluation.

Climate Discovery: Integrating Research With Exhibit, Public Tours, K-12, and Web-based EPO Resources

NASA Astrophysics Data System (ADS)

Foster, S. Q.; Carbone, L.; Gardiner, L.; Johnson, R.; Russell, R.; Advisory Committee, S.; Ammann, C.; Lu, G.; Richmond, A.; Maute, A.; Haller, D.; Conery, C.; Bintner, G.

2005-12-01

The Climate Discovery Exhibit at the National Center for Atmospheric Research (NCAR) Mesa Lab provides an exciting conceptual outline for the integration of several EPO activities with other well-established NCAR educational resources and programs. The exhibit is organized into four topic areas intended to build understanding among NCAR's 80,000 annual visitors, including 10,000 school children, about Earth system processes and scientific methods contributing to a growing body of knowledge about climate and global change. These topics include: 'Sun-Earth Connections,' 'Climate Now,' 'Climate Past,' and 'Climate Future.' Exhibit text, graphics, film and electronic media, and interactives are developed and updated through collaborations between NCAR's climate research scientists and staff in the Office of Education and Outreach (EO) at the University Corporation for Atmospheric Research (UCAR). With funding from NCAR, paleoclimatologists have contributed data and ideas for a new exhibit Teachers' Guide unit about 'Climate Past.' This collection of middle-school level, standards-aligned lessons are intended to help students gain understanding about how scientists use proxy data and direct observations to describe past climates. Two NASA EPO's have funded the development of 'Sun-Earth Connection' lessons, visual media, and tips for scientists and teachers. Integrated with related content and activities from the NASA-funded Windows to the Universe web site, these products have been adapted to form a second unit in the Climate Discovery Teachers' Guide about the Sun's influence on Earth's climate. Other lesson plans, previously developed by on-going efforts of EO staff and NSF's previously-funded Project Learn program are providing content for a third Teachers' Guide unit on 'Climate Now' - the dynamic atmospheric and geological processes that regulate Earth's climate. EO has plans to collaborate with NCAR climatologists and computer modelers in the next year to develop lessons and ancillary exhibit interactives and visualizations for the final Teachers' Guide unit about 'Climate Future.' Units developed so far are available in downloadable format on the NCAR EO and Windows to the Universe web sites for dissemination to educators and the general public public. Those web sites are, respectively, (http://eo.ucar.edu/educators/ClimateDiscovery) and (http://www.windows.ucar.edu). Encouragement from funding agencies to integrate and relate resources and growing pressure to implement efficiencies in educational programs have created excellent opportunities which will be described from the viewpoints of EO staff and scientists'. Challenges related to public and student perceptions about climate and global change, the scientific endeavor, and how to establish successful dialogues between educators and scientists will also be discussed.

A comparative gradient approach as a tool for understanding and managing urban ecosystems

Treesearch

Christopher G. Boone; Elizabeth Cook; Sharon J. Hall; Marcia L. Nation; Nancy B. Grimm; Carol B. Raish; Deborah M. Finch; Abigail M. York

2012-01-01

To meet the grand challenges of the urban century - such as climate change, biodiversity loss, and persistent poverty - urban and ecological theory must contribute to integrated frameworks that treat social and ecological dynamics as interdependent. A socioecological framework that encapsulates theory from the social and ecological sciences will improve understanding...

Teaching and Learning for Intercultural Sensitivity: A Cross-Cultural Examination of American Domestic Students and Japanese Exchange Students

ERIC Educational Resources Information Center

Sakurauchi, Yoko Hwang

2014-01-01

Global student mobility has become a dynamic force in American higher education. Integrating international students into diverse campus environments provides domestic as well as foreign students with enriched learning opportunities. However, a diverse campus climate itself will not make college students interculturally competent. Intentional…

Ecosystem dynamics and disturbance in mountain wildernesses: assessing vulnerability of natural resources to change

Treesearch

Daniel B. Fagre; David L. Peterson

2000-01-01

An integrated program of ecosystem modeling and extensive field studies at Glacier and Olympic National Parks has quantified many of the ecological processes affected by climatic variability and disturbance. Models have successfully estimated snow distribution, annual watershed discharge, and stream temperature variation based on seven years of monitoring. Various...

Climate impacts on environmental risks evaluated from space: a contribution to social benefits within the GEOSS Health Area: The case of Rift Valley Fever in Senegal

NASA Astrophysics Data System (ADS)

Tourre, Y. M.

2009-12-01

Climate and environment vary on many spatio-temporal scales, including climate change, with impacts on ecosystems, vector-borne diseases and public health worldwide. This study is to enable societal benefits from a conceptual approach by mapping climatic and environmental conditions from space and understanding the mechanisms within the Health Social Benefit GEOSS area. The case study is for Rift Valley Fever (RVF) epidemics in Senegal is presented. Ponds contributing to mosquitoes’ thriving, were identified from remote sensing using high-resolution SPOT-5 satellite images. Additional data on ponds’ dynamics and rainfall events (obtained from the Tropical Rainfall Measuring Mission) were combined with hydrological in-situ data. Localization of vulnerable hosts such as parked cattle (from QuickBird satellite) are also used. Dynamic spatio-temporal distribution of Aedes vexans density (one of the main RVF vectors) is based on the total rainfall amount and ponds’ dynamics. While Zones Potentially Occupied by Mosquitoes (ZPOM) are mapped, detailed risks areas, i.e. zones where hazards and vulnerability occur, are expressed in percentages of parks where cattle is potentially exposed to mosquitoes’ bites. This new conceptual approach, using remote-sensing techniques belonging to GEOSS, simply relies upon rainfall distribution also evaluated from space. It is meant to contribute to the implementation of integrated operational early warning system within the health application communities since climatic and environmental conditions (both natural and anthropogenic) are changing rapidly.

Assessing and Mitigating Hurricane Storm Surge Risk in a Changing Environment

NASA Astrophysics Data System (ADS)

Lin, N.; Shullman, E.; Xian, S.; Feng, K.

2017-12-01

Hurricanes have induced devastating storm surge flooding worldwide. The impacts of these storms may worsen in the coming decades because of rapid coastal development coupled with sea-level rise and possibly increasing storm activity due to climate change. Major advances in coastal flood risk management are urgently needed. We present an integrated dynamic risk analysis for flooding task (iDraft) framework to assess and manage coastal flood risk at the city or regional scale, considering integrated dynamic effects of storm climatology change, sea-level rise, and coastal development. We apply the framework to New York City. First, we combine climate-model projected storm surge climatology and sea-level rise with engineering- and social/economic-model projected coastal exposure and vulnerability to estimate the flood damage risk for the city over the 21st century. We derive temporally-varying risk measures such as the annual expected damage as well as temporally-integrated measures such as the present value of future losses. We also examine the individual and joint contributions to the changing risk of the three dynamic factors (i.e., sea-level rise, storm change, and coastal development). Then, we perform probabilistic cost-benefit analysis for various coastal flood risk mitigation strategies for the city. Specifically, we evaluate previously proposed mitigation measures, including elevating houses on the floodplain and constructing flood barriers at the coast, by comparing their estimated cost and probability distribution of the benefit (i.e., present value of avoided future losses). We also propose new design strategies, including optimal design (e.g., optimal house elevation) and adaptive design (e.g., flood protection levels that are designed to be modified over time in a dynamic and uncertain environment).

Impact of Atmospheric Aerosols on Solar Photovoltaic Electricity Generation in China

NASA Astrophysics Data System (ADS)

Li, X.; Mauzerall, D. L.; Wagner, F.; Peng, W.; Yang, J.

2016-12-01

Hurricanes have induced devastating storm surge flooding worldwide. The impacts of these storms may worsen in the coming decades because of rapid coastal development coupled with sea-level rise and possibly increasing storm activity due to climate change. Major advances in coastal flood risk management are urgently needed. We present an integrated dynamic risk analysis for flooding task (iDraft) framework to assess and manage coastal flood risk at the city or regional scale, considering integrated dynamic effects of storm climatology change, sea-level rise, and coastal development. We apply the framework to New York City. First, we combine climate-model projected storm surge climatology and sea-level rise with engineering- and social/economic-model projected coastal exposure and vulnerability to estimate the flood damage risk for the city over the 21st century. We derive temporally-varying risk measures such as the annual expected damage as well as temporally-integrated measures such as the present value of future losses. We also examine the individual and joint contributions to the changing risk of the three dynamic factors (i.e., sea-level rise, storm change, and coastal development). Then, we perform probabilistic cost-benefit analysis for various coastal flood risk mitigation strategies for the city. Specifically, we evaluate previously proposed mitigation measures, including elevating houses on the floodplain and constructing flood barriers at the coast, by comparing their estimated cost and probability distribution of the benefit (i.e., present value of avoided future losses). We also propose new design strategies, including optimal design (e.g., optimal house elevation) and adaptive design (e.g., flood protection levels that are designed to be modified over time in a dynamic and uncertain environment).

Towards a high resolution, integrated hydrology model of North America.

NASA Astrophysics Data System (ADS)

Maxwell, R. M.; Condon, L. E.

2015-12-01

Recent studies demonstrate feedbacks between groundwater dynamics, overland flow, land surface and vegetation processes, and atmospheric boundary layer development that significantly affect local and regional climate across a range of climatic conditions. Furthermore, the type and distribution of vegetation cover alters land-atmosphere water and energy fluxes, as well as runoff generation and overland flow processes. These interactions can result in significant feedbacks on local and regional climate. In mountainous regions, recent research has shown that spatial and temporal variability in annual evapotranspiration, and thus water budgets, is strongly dependent on lateral groundwater flow; however, the full effects of these feedbacks across varied terrain (e.g. from plains to mountains) are not well understood. Here, we present a high-resolution, integrated hydrology model that covers much of continental North America and encompasses the Mississippi and Colorado watersheds. The model is run in a fully-transient manner at hourly temporal resolution incorporating fully-coupled land energy states and fluxes with integrated surface and subsurface hydrology. Connections are seen between hydrologic variables (such as water table depth) and land energy fluxes (such as latent heat) and spatial and temporal scaling is shown to span many orders of magnitude. Using these transient simulations as a proof of concept, we present a vision for future integrated simulation capabilities.

A data-driven emulation framework for representing water-food nexus in a changing cold region

NASA Astrophysics Data System (ADS)

Nazemi, A.; Zandmoghaddam, S.; Hatami, S.

2017-12-01

Water resource systems are under increasing pressure globally. Growing population along with competition between water demands and emerging effects of climate change have caused enormous vulnerabilities in water resource management across many regions. Diagnosing such vulnerabilities and provision of effective adaptation strategies requires the availability of simulation tools that can adequately represent the interactions between competing water demands for limiting water resources and inform decision makers about the critical vulnerability thresholds under a range of potential natural and anthropogenic conditions. Despite a significant progress in integrated modeling of water resource systems, regional models are often unable to fully represent the contemplating dynamics within the key elements of water resource systems locally. Here we propose a data-driven approach to emulate a complex regional water resource system model developed for Oldman River Basin in southern Alberta, Canada. The aim of the emulation is to provide a detailed understanding of the trade-offs and interaction at the Oldman Reservoir, which is the key to flood control and irrigated agriculture in this over-allocated semi-arid cold region. Different surrogate models are developed to represent the dynamic of irrigation demand and withdrawal as well as reservoir evaporation and release individually. The nan-falsified offline models are then integrated through the water balance equation at the reservoir location to provide a coupled model for representing the dynamic of reservoir operation and water allocation at the local scale. The performance of individual and integrated models are rigorously examined and sources of uncertainty are highlighted. To demonstrate the practical utility of such surrogate modeling approach, we use the integrated data-driven model for examining the trade-off in irrigation water supply, reservoir storage and release under a range of changing climate, upstream streamflow and local irrigation conditions.

An Integrated Modeling System for Water Resource Management Under Climate Change, Socio-Economic Development and Irrigation Management

NASA Astrophysics Data System (ADS)

SU, Q.; Karthikeyan, R.; Lin, Y.

2017-12-01

Water resources across the world have been increasingly stressed in the past few decades due to the population and economic growth and climate change. Consequently, the competing use of water among agricultural, domestic and industrial sectors is expected to be increasing. In this study, the water stresses under various climate change, socio-economic development and irrigation management scenarios are predicted over the period of 2015-2050 using an integrated model, in which the changes in water supply and demand induced by climate change, socio-economic development and irrigation management are dynamically parameterized. Simulations on the case of Texas, Southwest U.S. were performed using the newly developed integrated model, showing that the water stress is projected to be elevated in 2050 over most areas of Texas, particularly at Northern and Southern Plain and metropolitan areas. Climate change represents the most pronounce factor affecting the water supply and irrigation water demand in Texas. The water supply over East Texas is largely reduced in future because of the less precipitation and higher temperature under the climate change scenario, resulting in an elevated irrigation water demand and thus a higher water stress in this region. In contrast, the severity of water shortage in West Texas would be alleviated in future because of climate change. The water shortage index over metropolitan areas would increase by 50-90% under 1.0% migration scenario, suggesting that the population growth in future could also greatly stress the water supply, especially megacities like Dallas, Houston, Austin and San Antonio. The projected increase in manufacturing water demand shows little effects on the water stress. Increasing irrigation rate exacerbates the water stress over irrigated agricultural areas of Texas.

Combining surface reanalysis and remote sensing data for monitoring evapotranspiration

USGS Publications Warehouse

Marshall, M.; Tu, K.; Funk, C.; Michaelsen, J.; Williams, Pat; Williams, C.; Ardö, J.; Marie, B.; Cappelaere, B.; Grandcourt, A.; Nickless, A.; Noubellon, Y.; Scholes, R.; Kutsch, W.

2012-01-01

Climate change is expected to have the greatest impact on the world's poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled actual evapotranspiration (AET), a key input in continental-scale hydrologic models. In this study, a model driven by dynamic canopy AET was combined with the Global Land Data Assimilation System realization of the NOAH Land Surface Model (GNOAH) wet canopy and soil AET for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against AET from the GNOAH model and dynamic model using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance are at humid sites with dense vegetation, while performance at semi-arid sites is poor, but better than individual models. The reduction in errors using the hybrid model can be attributed to the integration of a dynamic vegetation component with land surface model estimates, improved model parameterization, and reduction of multiplicative effects of uncertain data.

Climate Change and Future U.S. Electricity Infrastructure: the Nexus between Water Availability, Land Suitability, and Low-Carbon Technologies

NASA Astrophysics Data System (ADS)

Rice, J.; Halter, T.; Hejazi, M. I.; Jensen, E.; Liu, L.; Olson, J.; Patel, P.; Vernon, C. R.; Voisin, N.; Zuljevic, N.

2014-12-01

Integrated assessment models project the future electricity generation mix under different policy, technology, and socioeconomic scenarios, but they do not directly address site-specific factors such as interconnection costs, population density, land use restrictions, air quality, NIMBY concerns, or water availability that might affect the feasibility of achieving the technology mix. Moreover, since these factors can change over time due to climate, policy, socioeconomics, and so on, it is important to examine the dynamic feasibility of integrated assessment scenarios "on the ground." This paper explores insights from coupling an integrated assessment model (GCAM-USA) with a geospatial power plant siting model (the Capacity Expansion Regional Feasibility model, CERF) within a larger multi-model framework that includes regional climate, hydrologic, and water management modeling. GCAM-USA is a dynamic-recursive market equilibrium model simulating the impact of carbon policies on global and national markets for energy commodities and other goods; one of its outputs is the electricity generation mix and expansion at the state-level. It also simulates water demands from all sectors that are downscaled as input to the water management modeling. CERF simulates siting decisions by dynamically representing suitable areas for different generation technologies with geospatial analyses (informed by technology-specific siting criteria, such as required mean streamflow per the Clean Water Act), and then choosing siting locations to minimize interconnection costs (to electric transmission and gas pipelines). CERF results are compared across three scenarios simulated by GCAM-USA: 1) a non-mitigation scenario (RCP8.5) in which conventional fossil-fueled technologies prevail, 2) a mitigation scenario (RCP4.5) in which the carbon price causes a shift toward nuclear, carbon capture and sequestration (CCS), and renewables, and 3) a repeat of scenario (2) in which CCS technologies are made unavailable—resulting in a large increase in the nuclear fraction of the mix.

Sensitivity study of heavy precipitation in Limited Area Model climate simulations: influence of the size of the domain and the use of the spectral nudging technique

NASA Astrophysics Data System (ADS)

Colin, Jeanne; Déqué, Michel; Radu, Raluca; Somot, Samuel

2010-10-01

We assess the impact of two sources of uncertainties in a limited area model (LAM) on the representation of intense precipitation: the size of the domain of integration and the use of the spectral nudging technique (driving of the large-scale within the domain of integration). We work in a perfect-model approach where the LAM is driven by a general circulation model (GCM) run at the same resolution and sharing the same physics and dynamics as the LAM. A set of three 50 km resolution simulations run over Western Europe with the LAM ALADIN-Climate and the GCM ARPEGE-Climate are performed to address this issue. Results are consistent with previous studies regarding the seasonal-mean fields. Furthermore, they show that neither the use of the spectral nudging nor the choice of a small domain are detrimental to the modelling of heavy precipitation in the present experiment.

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

Ecological Assimilation of Land and Climate Observations - the EALCO model

NASA Astrophysics Data System (ADS)

Wang, S.; Zhang, Y.; Trishchenko, A.

2004-05-01

Ecosystems are intrinsically dynamic and interact with climate at a highly integrated level. Climate variables are the main driving factors in controlling the ecosystem physical, physiological, and biogeochemical processes including energy balance, water balance, photosynthesis, respiration, and nutrient cycling. On the other hand, ecosystems function as an integrity and feedback on the climate system through their control on surface radiation balance, energy partitioning, and greenhouse gases exchange. To improve our capability in climate change impact assessment, a comprehensive ecosystem model is required to address the many interactions between climate change and ecosystems. In addition, different ecosystems can have very different responses to the climate change and its variation. To provide more scientific support for ecosystem impact assessment at national scale, it is imperative that ecosystem models have the capability of assimilating the large scale geospatial information including satellite observations, GIS datasets, and climate model outputs or reanalysis. The EALCO model (Ecological Assimilation of Land and Climate Observations) is developed for such purposes. EALCO includes the comprehensive interactions among ecosystem processes and climate, and assimilates a variety of remote sensing products and GIS database. It provides both national and local scale model outputs for ecosystem responses to climate change including radiation and energy balances, water conditions and hydrological cycles, carbon sequestration and greenhouse gas exchange, and nutrient (N) cycling. These results form the foundation for the assessment of climate change impact on ecosystems, their services, and adaptation options. In this poster, the main algorithms for the radiation, energy, water, carbon, and nitrogen simulations were diagrammed. Sample input data layers at Canada national scale were illustrated. Model outputs including the Canada wide spatial distributions of net radiation, evapotranspiration, gross primary production, net primary production, and net ecosystem production were discussed.

Heinrich Events as an integral part of glacial-interglacial climate dynamics

NASA Astrophysics Data System (ADS)

Barker, S.; Knorr, G.; Zhang, X.; Gong, X.; Lohmann, G.; Bazin, L.

2017-12-01

Since their discovery in the 1980s Heinrich Events have provided a playground for climate scientists trying to understand the interactions between ice sheets and the ocean. Subsequently it has become clear that these interactions extend to almost all parts of the global climate system, from temperature, winds and rainfall to deep ocean currents and atmospheric CO2. Furthermore it remains unclear as to whether these dramatic events are a cause or consequence (or both) of regional to global perturbations in a range of parameters, including meridional overturning circulation within the Atlantic. Here we will discuss some of these aspects to highlight ongoing and future research related to Heinrich events and abrupt change more generally. We will discuss some of the possible triggers for H-events, including abrupt versus more gradual forcing mechanisms and conversely the potential influence of such events on the wider climate system, including deglacial climate change.

Ecosystem vulnerability to climate change in the southeastern United States

USGS Publications Warehouse

Cartwright, Jennifer M.; Costanza, Jennifer

2016-08-11

Two recent investigations of climate-change vulnerability for 19 terrestrial, aquatic, riparian, and coastal ecosystems of the southeastern United States have identified a number of important considerations, including potential for changes in hydrology, disturbance regimes, and interspecies interactions. Complementary approaches using geospatial analysis and literature synthesis integrated information on ecosystem biogeography and biodiversity, climate projections, vegetation dynamics, soil and water characteristics, anthropogenic threats, conservation status, sea-level rise, and coastal flooding impacts. Across a diverse set of ecosystems—ranging in size from dozens of square meters to thousands of square kilometers—quantitative and qualitative assessments identified types of climate-change exposure, evaluated sensitivity, and explored potential adaptive capacity. These analyses highlighted key gaps in scientific understanding and suggested priorities for future research. Together, these studies help create a foundation for ecosystem-level analysis of climate-change vulnerability to support effective biodiversity conservation in the southeastern United States.

The role of organic soil layer on the fate of Siberian larch forest and near-surface permafrost under changing climate: A simulation study

NASA Astrophysics Data System (ADS)

SATO, H.; Iwahana, G.; Ohta, T.

2013-12-01

Siberian larch forest is the largest coniferous forest region in the world. In this vast region, larch often forms nearly pure stands, regenerated by recurrent fire. This region is characterized by a short and dry growing season; the annual mean precipitation for Yakutsk was only about 240 mm. To maintain forest ecosystem under such small precipitation, underlying permafrost and seasonal soil freezing-thawing-cycle have been supposed to play important roles; (1) frozen ground inhibits percolation of soil water into deep soil layers, and (2) excess soil water at the end of growing season can be carried over until the next growing season as ice, and larch trees can use the melt water. As a proof for this explanation, geographical distribution of Siberian larch region highly coincides with continuous and discontinuous permafrost zone. Recent observations and simulation studies suggests that existences of larch forest and permafrost in subsurface layer are co-dependent; permafrost maintains the larch forest by enhancing water use efficiency of trees, while larch forest maintains permafrost by inhibiting solar radiation and preventing heat exchanges between soil and atmosphere. Owing to such complexity and absence of enough ecosystem data available, current-generation Earth System Models significantly diverse in their prediction of structure and key ecosystem functions in Siberian larch forest under changing climate. Such uncertainty should in turn expand uncertainty over predictions of climate, because Siberian larch forest should have major role in the global carbon balance with its huge area and vast potential carbon pool within the biomass and soil, and changes in boreal forest albedo can have a considerable effect on Northern Hemisphere climate. In this study, we developed an integrated ecosystem model, which treats interactions between plant-dynamics and freeze-thaw cycles. This integrated model contains a dynamic global vegetation model SEIB-DGVM, which simulates plant and carbon dynamics. It also contains a one-dimensional land surface model NOAH 2.7.1, which simulates soil moisture (both liquid and frozen), soil temperature, snowpack depth and density, canopy water content, and the energy and water fluxes. This integrated model quantitatively reconstructs post-fire development of forest structure (i.e. LAI and biomass) and organic soil layer, which dampens heat exchanges between soil and atmosphere. With the post-fire development of LAI and the soil organic layer, the integrated model also quantitatively reconstructs changes in seasonal maximum of active layer depth. The integrated model is then driven by the IPCC A1B scenario of rising atmospheric CO2, and by climate changes during the twenty-first century resulting from the change in CO2. This simulation suggests that forecasted global warming would causes decay of Siberian larch ecosystem, but such responses could be delayed by "memory effect" of the soil organic layer for hundreds of years.

The evolution of climatic niches in squamate reptiles.

PubMed

Pie, Marcio R; Campos, Leonardo L F; Meyer, Andreas L S; Duran, Andressa

2017-07-12

Despite the remarkable diversity found in squamate reptiles, most of their species tend to be found in warm/dry environments, suggesting that climatic requirements played a crucial role in their diversification, yet little is known about the evolution of their climatic niches. In this study, we integrate climatic information associated with the geographical distribution of 1882 squamate species and their phylogenetic relationships to investigate the tempo and mode of climatic niche evolution in squamates, both over time and among lineages. We found that changes in climatic niche dynamics were pronounced over their recent squamate evolutionary history, and we identified extensive evidence for rate heterogeneity in squamate climatic niche evolution. Most rate shifts involved accelerations, particularly over the past 50 Myr. Most squamates occupy similar regions of the climatic niche space, with only a few lineages diversifying into colder and humid climatic conditions. The changes from arid to mesic conditions in some regions of the globe may have provided opportunities for climatic niche evolution, although most lineages tended to remain near their ancestral niche. Variation in rates of climatic niche evolution seems common, particularly in response to the availability of new climatic conditions over evolutionary time. © 2017 The Author(s).

Improving the Projections of Vegetation Biogeography by Integrating Climate Envelope Models and Dynamic Global Vegetation Models

NASA Astrophysics Data System (ADS)

Case, M. J.; Kim, J. B.

2015-12-01

Assessing changes in vegetation is increasingly important for conservation planning in the face of climate change. Dynamic global vegetation models (DGVMs) are important tools for assessing such changes. DGVMs have been applied at regional scales to create projections of range expansions and contractions of plant functional types. Many DGVMs use a number of algorithms to determine the biogeography of plant functional types. One such DGVM, MC2, uses a series of decision trees based on bioclimatic thresholds while others, such as LPJ, use constraining emergent properties with a limited set of bioclimatic threshold-based rules. Although both approaches have been used widely, we demonstrate that these biogeography outputs perform poorly at continental scales when compared to existing potential vegetation maps. Specifically, we found that with MC2, the algorithm for determining leaf physiognomy is too simplistic to capture arid and semi-arid vegetation in much of the western U.S., as well as is the algorithm for determining the broadleaf and needleleaf mix in the Southeast. With LPJ, we found that the bioclimatic thresholds used to allow seedling establishment are too broad and fail to capture regional-scale biogeography of the plant functional types. In response, we demonstrate a new approach to determining the biogeography of plant functional types by integrating the climatic thresholds produced for individual tree species by a series of climate envelope models with the biogeography algorithms of MC2 and LPJ. Using this approach, we find that MC2 and LPJ perform considerably better when compared to potential vegetation maps.

El Niño/Southern Oscillation response to global warming

PubMed Central

Latif, M.; Keenlyside, N. S.

2009-01-01

The El Niño/Southern Oscillation (ENSO) phenomenon, originating in the Tropical Pacific, is the strongest natural interannual climate signal and has widespread effects on the global climate system and the ecology of the Tropical Pacific. Any strong change in ENSO statistics will therefore have serious climatic and ecological consequences. Most global climate models do simulate ENSO, although large biases exist with respect to its characteristics. The ENSO response to global warming differs strongly from model to model and is thus highly uncertain. Some models simulate an increase in ENSO amplitude, others a decrease, and others virtually no change. Extremely strong changes constituting tipping point behavior are not simulated by any of the models. Nevertheless, some interesting changes in ENSO dynamics can be inferred from observations and model integrations. Although no tipping point behavior is envisaged in the physical climate system, smooth transitions in it may give rise to tipping point behavior in the biological, chemical, and even socioeconomic systems. For example, the simulated weakening of the Pacific zonal sea surface temperature gradient in the Hadley Centre model (with dynamic vegetation included) caused rapid Amazon forest die-back in the mid-twenty-first century, which in turn drove a nonlinear increase in atmospheric CO2, accelerating global warming. PMID:19060210

El Nino/Southern Oscillation response to global warming.

PubMed

Latif, M; Keenlyside, N S

2009-12-08

The El Niño/Southern Oscillation (ENSO) phenomenon, originating in the Tropical Pacific, is the strongest natural interannual climate signal and has widespread effects on the global climate system and the ecology of the Tropical Pacific. Any strong change in ENSO statistics will therefore have serious climatic and ecological consequences. Most global climate models do simulate ENSO, although large biases exist with respect to its characteristics. The ENSO response to global warming differs strongly from model to model and is thus highly uncertain. Some models simulate an increase in ENSO amplitude, others a decrease, and others virtually no change. Extremely strong changes constituting tipping point behavior are not simulated by any of the models. Nevertheless, some interesting changes in ENSO dynamics can be inferred from observations and model integrations. Although no tipping point behavior is envisaged in the physical climate system, smooth transitions in it may give rise to tipping point behavior in the biological, chemical, and even socioeconomic systems. For example, the simulated weakening of the Pacific zonal sea surface temperature gradient in the Hadley Centre model (with dynamic vegetation included) caused rapid Amazon forest die-back in the mid-twenty-first century, which in turn drove a nonlinear increase in atmospheric CO(2), accelerating global warming.

Investigating the Sensitivity of Streamflow and Water Quality to Climate Change and Urbanization in 20 U.S. Watersheds

NASA Astrophysics Data System (ADS)

Johnson, T. E.; Weaver, C. P.; Butcher, J.; Parker, A.

2011-12-01

Watershed modeling was conducted in 20 large (15,000-60,000 km2), U.S. watersheds to address gaps in our knowledge of the sensitivity of U.S. streamflow, nutrient (N and P) and sediment loading to potential future climate change, and methodological challenges associated with integrating existing tools (e.g., climate models, watershed models) and datasets to address these questions. Climate change scenarios are based on dynamically downscaled (50x50 km2) output from four of the GCMs used in the Intergovernmental Panel on Climate Change (IPCC) 4th Assessment Report for the period 2041-2070 archived by the North American Regional Climate Change Assessment Program (NARCCAP). To explore the potential interaction of climate change and urbanization, model simulations also include urban and residential development scenarios for each of the 20 study watersheds. Urban and residential development scenarios were acquired from EPA's national-scale Integrated Climate and Land Use Scenarios (ICLUS) project. Watershed modeling was conducted using the Hydrologic Simulation Program-FORTRAN (HSPF) and Soil and Water Assessment Tool (SWAT) models. Here we present a summary of results for 5 of the study watersheds; the Minnesota River, the Susquehanna River, the Apalachicola-Chattahoochee-Flint, the Salt/Verde/San Pedro, and the Willamette River Basins. This set of results provide an overview of the response to climate change in different regions of the U.S., the different sensitivities of different streamflow and water quality endpoints, and illustrate a number of methodological issues including the sensitivities and uncertainties associated with use of different watershed models, approaches for downscaling climate change projections, and interaction between climate change and other forcing factors, specifically urbanization and changes in atmospheric CO2 concentration.

Global Air Quality and Climate Impacts of Mitigating Short-lived Climate Pollution in China

NASA Astrophysics Data System (ADS)

Harper, K.; Unger, N.; Heyes, C.; Kiesewetter, G.; Klimont, Z.; Schoepp, W.; Wagner, F.

2014-12-01

China is a major emitter of harmful air pollutants, including the short-lived climate pollutants (SLCPs) and their precursors. Implementation of pollution control technologies provides a mechanism for simultaneously protecting human and ecosystem health and achieving near-term climate co-benefits; however, predicting the outcomes of technical and policy interventions is challenging because the SLCPs participate in both climate warming and cooling and share many common emission sources. Here, we present the results of a combined regional integrated assessment and global climate modeling study aimed at quantifying the near-term climate and air quality co-benefits of selective control of Chinese air pollution emissions. Results from IIASA's Greenhouse Gas - Air Pollution Interactions and Synergies (GAINS) integrated assessment model indicate that methane emission reductions make up > 75% of possible CO2-equivalent emission reductions of the SLCPs and their precursors in China in 2030. A multi-pollutant emission reduction scenario incorporating the 2030 Chinese pollution control measures with the highest potential for future climate impact is applied to the NASA ModelE2 - Yale Interactive Terrestrial Biosphere (NASA ModelE2-YIBs) global carbon - chemistry - climate model to assess the regional and long-range impacts of Chinese SLCP mitigation measures. Using model simulations that incorporate dynamic methane emissions and photosynthesis-dependent isoprene emissions, we quantify the impacts of Chinese reductions of the short-lived air pollutants on radiative forcing and on surface ozone and particulate air pollution. Present-day modeled methane mole fractions are evaluated against SCIAMACHY methane columns and NOAA ESRL/GMD surface flask measurements.

Integrating ecophysiology and forest landscape models to improve projections of drought effects under climate change

Treesearch

Eric J. Gustafson; Arjan M.G. De Bruijn; Robert E. Pangle; Jean-Marc Limousin; Nate G. McDowell; William T. Pockman; Brian R. Sturtevant; Jordan D. Muss; Mark E. Kubiske

2015-01-01

Fundamental drivers of ecosystem processes such as temperature and precipitation are rapidly changing and creating novel environmental conditions. Forest landscape models (FLM) are used by managers and policy-makers to make projections of future ecosystem dynamics under alternative management or policy options, but the links between the fundamental drivers and...

Strategizing for the Future: Evolving Cultural Resource Centers in Higher Education

ERIC Educational Resources Information Center

Shek, Yen Ling

2013-01-01

Cultural resource centers have been an ongoing and integral component to creating a more welcoming campus climate for Students of Color since its establishment in the 1960s. While the racial dynamics may have changed, many of the challenges Students of Color faced on predominantly White campuses have not. Interestingly, cultural resource centers…

Nitrogen attenuation of terrestrial carbon cycle response to global environmental factors

Treesearch

Atul Jain; Xiaojuan Yang; Haroon Kheshgi; A. David McGuire; Wilfred Post; David Kicklighter

2009-01-01

Nitrogen cycle dynamics have the capacity to attenuate the magnitude of global terrestrial carbon sinks and sources driven by CO2 fertilization and changes in climate. In this study, two versions of the terrestrial carbon and nitrogen cycle components of the Integrated Science Assessment Model (ISAM) are used to evaluate how variation in nitrogen...

Answering a Call to Action: Engaging University Faculty on the Common Core State Standards

ERIC Educational Resources Information Center

Alvarado-Santos, Angelita; Case, Jennifer M.; Thompson, Ashleigh; Chertoff, Natalie

2017-01-01

Using various strategies, the City University of New York--a large, public, urban university system--engaged hundreds of faculty across 15 colleges in integrating the Common Core state standards (CCSS) in college coursework. Against the backdrop of a dynamic political climate, this CCSS initiative is described along with findings from a…

Integration of remote sensing based surface information into a three-dimensional microclimate model

NASA Astrophysics Data System (ADS)

Heldens, Wieke; Heiden, Uta; Esch, Thomas; Mueller, Andreas; Dech, Stefan

2017-03-01

Climate change urges cities to consider the urban climate as part of sustainable planning. Urban microclimate models can provide knowledge on the climate at building block level. However, very detailed information on the area of interest is required. Most microclimate studies therefore make use of assumptions and generalizations to describe the model area. Remote sensing data with area wide coverage provides a means to derive many parameters at the detailed spatial and thematic scale required by urban climate models. This study shows how microclimate simulations for a series of real world urban areas can be supported by using remote sensing data. In an automated process, surface materials, albedo, LAI/LAD and object height have been derived and integrated into the urban microclimate model ENVI-met. Multiple microclimate simulations have been carried out both with the dynamic remote sensing based input data as well as with manual and static input data to analyze the impact of the RS-based surface information and the suitability of the applied data and techniques. A valuable support of the integration of the remote sensing based input data for ENVI-met is the use of an automated processing chain. This saves tedious manual editing and allows for fast and area wide generation of simulation areas. The analysis of the different modes shows the importance of high quality height data, detailed surface material information and albedo.

Assessing the potential impact and uncertainty of climate, land use change and demographic trends on malaria transmission in Africa by 2050.

NASA Astrophysics Data System (ADS)

Tompkins, Adrian; Caporaso, Luca; Colon-Gonzalez, Felipe

2014-05-01

Previous analyses of data has shown that in addition to variability and longer term trends in climate variables, both land use change (LUC) and population mobility and urbanisation trends can impact malaria transmission intensities and socio-economic burden. With the new regional VECTRI dynamical malaria model it is now possible to examine these in an integrated modelling framework. Using 5 global climate models which were bias corrected using the WATCH data for the recent ISIMIP project, the four Representative Concentration Pathways (RCP), population projections disaggregated from the Shared Socioeconomic Pathways (SSP) and Land use change from the HYDE model output used in the CMIP5 process, we construct a multi-member ensemble of malaria transmission intensity projections for 2050. The ensemble integrations indicate that climate has the leading impact on malaria changes, but that population growth and urbanisation can offset the effect of climate locally. LUC impacts can also be significant on the local scale but their assessment is highly uncertain and only indicative in this study. It is argued that the study should be repeated with a range of malaria models or VECTRI configurations in order to assess the additional uncertainty due to the malaria model assumptions.

Mesoscale weather and climate modeling with the global non-hydrostatic Goddard Earth Observing System Model (GEOS-5) at cloud-permitting resolutions

NASA Astrophysics Data System (ADS)

Putman, W. M.; Suarez, M.

2009-12-01

The Goddard Earth Observing System Model (GEOS-5), an earth system model developed in the NASA Global Modeling and Assimilation Office (GMAO), has integrated the non-hydrostatic finite-volume dynamical core on the cubed-sphere grid. The extension to a non-hydrostatic dynamical framework and the quasi-uniform cubed-sphere geometry permits the efficient exploration of global weather and climate modeling at cloud permitting resolutions of 10- to 4-km on today's high performance computing platforms. We have explored a series of incremental increases in global resolution with GEOS-5 from it's standard 72-level 27-km resolution (~5.5 million cells covering the globe from the surface to 0.1 hPa) down to 3.5-km (~3.6 billion cells). We will present results from a series of forecast experiments exploring the impact of the non-hydrostatic dynamics at transition resolutions of 14- to 7-km, and the influence of increased horizontal/vertical resolution on convection and physical parameterizations within GEOS-5. Regional and mesoscale features of 5- to 10-day weather forecasts will be presented and compared with satellite observations. Our results will highlight the impact of resolution on the structure of cloud features including tropical convection and tropical cyclone predicability, cloud streets, von Karman vortices, and the marine stratocumulus cloud layer. We will also present experiment design and early results from climate impact experiments for global non-hydrostatic models using GEOS-5. Our climate experiments will focus on support for the Year of Tropical Convection (YOTC). We will also discuss a seasonal climate time-slice experiment design for downscaling coarse resolution century scale climate simulations to global non-hydrostatic resolutions of 14- to 7-km with GEOS-5.

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.

Local control on precipitation in a fully coupled climate-hydrology model.

PubMed

Larsen, Morten A D; Christensen, Jens H; Drews, Martin; Butts, Michael B; Refsgaard, Jens C

2016-03-10

The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies.

Advances in risk assessment for climate change adaptation policy.

PubMed

Adger, W Neil; Brown, Iain; Surminski, Swenja

2018-06-13

Climate change risk assessment involves formal analysis of the consequences, likelihoods and responses to the impacts of climate change and the options for addressing these under societal constraints. Conventional approaches to risk assessment are challenged by the significant temporal and spatial dynamics of climate change; by the amplification of risks through societal preferences and values; and through the interaction of multiple risk factors. This paper introduces the theme issue by reviewing the current practice and frontiers of climate change risk assessment, with specific emphasis on the development of adaptation policy that aims to manage those risks. These frontiers include integrated assessments, dealing with climate risks across borders and scales, addressing systemic risks, and innovative co-production methods to prioritize solutions to climate challenges with decision-makers. By reviewing recent developments in the use of large-scale risk assessment for adaptation policy-making, we suggest a forward-looking research agenda to meet ongoing strategic policy requirements in local, national and international contexts.This article is part of the theme issue 'Advances in risk assessment for climate change adaptation policy'. © 2018 The Author(s).

Advances in risk assessment for climate change adaptation policy

NASA Astrophysics Data System (ADS)

Adger, W. Neil; Brown, Iain; Surminski, Swenja

2018-06-01

Climate change risk assessment involves formal analysis of the consequences, likelihoods and responses to the impacts of climate change and the options for addressing these under societal constraints. Conventional approaches to risk assessment are challenged by the significant temporal and spatial dynamics of climate change; by the amplification of risks through societal preferences and values; and through the interaction of multiple risk factors. This paper introduces the theme issue by reviewing the current practice and frontiers of climate change risk assessment, with specific emphasis on the development of adaptation policy that aims to manage those risks. These frontiers include integrated assessments, dealing with climate risks across borders and scales, addressing systemic risks, and innovative co-production methods to prioritize solutions to climate challenges with decision-makers. By reviewing recent developments in the use of large-scale risk assessment for adaptation policy-making, we suggest a forward-looking research agenda to meet ongoing strategic policy requirements in local, national and international contexts. This article is part of the theme issue `Advances in risk assessment for climate change adaptation policy'.

Advances in risk assessment for climate change adaptation policy

PubMed Central

Adger, W. Neil; Brown, Iain; Surminski, Swenja

2018-01-01

Climate change risk assessment involves formal analysis of the consequences, likelihoods and responses to the impacts of climate change and the options for addressing these under societal constraints. Conventional approaches to risk assessment are challenged by the significant temporal and spatial dynamics of climate change; by the amplification of risks through societal preferences and values; and through the interaction of multiple risk factors. This paper introduces the theme issue by reviewing the current practice and frontiers of climate change risk assessment, with specific emphasis on the development of adaptation policy that aims to manage those risks. These frontiers include integrated assessments, dealing with climate risks across borders and scales, addressing systemic risks, and innovative co-production methods to prioritize solutions to climate challenges with decision-makers. By reviewing recent developments in the use of large-scale risk assessment for adaptation policy-making, we suggest a forward-looking research agenda to meet ongoing strategic policy requirements in local, national and international contexts. This article is part of the theme issue ‘Advances in risk assessment for climate change adaptation policy’. PMID:29712800

Local control on precipitation in a fully coupled climate-hydrology model

PubMed Central

Larsen, Morten A. D.; Christensen, Jens H.; Drews, Martin; Butts, Michael B.; Refsgaard, Jens C.

2016-01-01

The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies. PMID:26960564

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.

Rise of interdisciplinary research on climate

PubMed Central

Weart, Spencer

2013-01-01

Until the middle of the 20th century, the discipline of climatology was a stagnant field preoccupied with regional statistics. It had little to do with meteorology, which itself was predominantly a craft that paid scant attention to physical theory. The Second World War and Cold War promoted a rapid growth of meteorology, which some practitioners increasingly combined with physical science in hopes of understanding global climate dynamics. However, the dozen or so scientific disciplines that had something to say about climate were largely isolated from one another. In the 1960s and 1970s, worries about climate change helped to push the diverse fields into contact. Scientists interested in climate change kept their identification with different disciplines but developed ways to communicate across the boundaries (for example, in large international projects). Around the turn of the 21st century, the Intergovernmental Panel on Climate Change institutionalized an unprecedented process of exchanges; its reports relied especially on computer modeling, which became a center of fully integrated interdisciplinary cooperation. PMID:22778431

Online coupled regional meteorology-chemistry models in Europe: current status and prospects

NASA Astrophysics Data System (ADS)

Baklanov, A.; Schluenzen, K. H.; Suppan, P.; Baldasano, J.; Brunner, D.; Aksoyoglu, S.; Carmichael, G.; Douros, J.; Flemming, J.; Forkel, R.; Galmarini, S.; Gauss, M.; Grell, G.; Hirtl, M.; Joffre, S.; Jorba, O.; Kaas, E.; Kaasik, M.; Kallos, G.; Kong, X.; Korsholm, U.; Kurganskiy, A.; Kushta, J.; Lohmann, U.; Mahura, A.; Manders-Groot, A.; Maurizi, A.; Moussiopoulos, N.; Rao, S. T.; Savage, N.; Seigneur, C.; Sokhi, R.; Solazzo, E.; Solomos, S.; Sørensen, B.; Tsegas, G.; Vignati, E.; Vogel, B.; Zhang, Y.

2013-05-01

The simulation of the coupled evolution of atmospheric dynamics, pollutant transport, chemical reactions and atmospheric composition is one of the most challenging tasks in environmental modelling, climate change studies, and weather forecasting for the next decades as they all involve strongly integrated processes. Weather strongly influences air quality (AQ) and atmospheric transport of hazardous materials, while atmospheric composition can influence both weather and climate by directly modifying the atmospheric radiation budget or indirectly affecting cloud formation. Until recently, however, due to the scientific complexities and lack of computational power, atmospheric chemistry and weather forecasting have developed as separate disciplines, leading to the development of separate modelling systems that are only loosely coupled. The continuous increase in computer power has now reached a stage that enables us to perform online coupling of regional meteorological models with atmospheric chemical transport models. The focus on integrated systems is timely, since recent research has shown that meteorology and chemistry feedbacks are important in the context of many research areas and applications, including numerical weather prediction (NWP), AQ forecasting as well as climate and Earth system modelling. However, the relative importance of online integration and its priorities, requirements and levels of detail necessary for representing different processes and feedbacks can greatly vary for these related communities: (i) NWP, (ii) AQ forecasting and assessments, (iii) climate and earth system modelling. Additional applications are likely to benefit from online modelling, e.g.: simulation of volcanic ash or forest fire plumes, pollen warnings, dust storms, oil/gas fires, geo-engineering tests involving changes in the radiation balance. The COST Action ES1004 - European framework for online integrated air quality and meteorology modelling (EuMetChem) - aims at paving the way towards a new generation of online integrated atmospheric chemical transport and meteorology modelling with two-way interactions between different atmospheric processes including dynamics, chemistry, clouds, radiation, boundary layer and emissions. As its first task, we summarise the current status of European modelling practices and experience with online coupled modelling of meteorology with atmospheric chemistry including feedback mechanisms and attempt reviewing the various issues connected to the different modules of such online coupled models but also providing recommendations for coping with them for the benefit of the modelling community at large.

Coupled Climate-Economy-Biosphere (CoCEB) model - Part 1: Abatement share and investment in low-carbon technologies

NASA Astrophysics Data System (ADS)

Ogutu, K. B. Z.; D'Andrea, F.; Ghil, M.; Nyandwi, C.; Manene, M. M.; Muthama, J. N.

2015-04-01

The Coupled Climate-Economy-Biosphere (CoCEB) model described herein takes an integrated assessment approach to simulating global change. By using an endogenous economic growth module with physical and human capital accumulation, this paper considers the sustainability of economic growth, as economic activity intensifies greenhouse gas emissions that in turn cause economic damage due to climate change. Different types of fossil fuels and different technologies produce different volumes of carbon dioxide in combustion. The shares of different fuels and their future evolution are not known. We assume that the dynamics of hydrocarbon-based energy share and their replacement with renewable energy sources in the global energy balance can be modeled into the 21st century by use of logistic functions. Various climate change mitigation policy measures are considered. While many integrated assessment models treat abatement costs merely as an unproductive loss of income, we consider abatement activities also as an investment in overall energy efficiency of the economy and decrease of overall carbon intensity of the energy system. The paper shows that these efforts help to reduce the volume of industrial carbon dioxide emissions, lower temperature deviations, and lead to positive effects in economic growth.

An analysis of relationships among climate forcing and time-integrated NDVI of grasslands over the U.S. northern and central Great Plains

USGS Publications Warehouse

Yang, Limin; Wylie, Bruce K.; Tieszen, Larry L.; Reed, Bradley C.

1998-01-01

Time-integrated normalized difference vegetation index (TI NDVI) derived from the multitemporal satellite imagery (1989–1993) was used as a surrogate for primary production to investigate climate impacts on grassland performance for central and northern Great Plains grasslands. Results suggest that spatial and temporal variability in growing season precipitation, potential evapotranspiration, and growing degree days are the most important controls on grassland performance and productivity. When TI NDVI and climate data of all grassland land cover classes were examined as a whole, a statistical model showed significant positive correlation between the TI NDVI and accumulated spring and summer precipitation, and a negative correlation between TI NDVI and spring potential evapotranspiration. The coefficient of determination (R2) of the general model was 0.45. When the TI NDVI-climate relationship was examined by individual land cover type, the relationship was generally better defined in terms of the variance accounted for by class-specific models . The photosynthetic pathway is an important determinant of grassland performance with northern mixed prairie (mixture of C3 and C4 grassland) TI NDVI affected by both thermal and moisture conditions during the growing season while southern plains grasslands (primarily C4grassland) were predominantly influenced by spring and summer precipitation. Grassland land cover classes associated with sandy soils also demonstrated a strong relationship between TI NDVI and growing season rainfall. Significant impact of interannual climate variability on the TI NDVI–climate relationship was also observed. The study suggests an integrated approach involving numerical models, satellite remote sensing, and field observations to monitor grassland ecosystem dynamics on a regional scale.

Improved methods for estimating local terrestrial water dynamics from GRACE in the Northern High Plains

NASA Astrophysics Data System (ADS)

Seyoum, Wondwosen M.; Milewski, Adam M.

2017-12-01

Investigating terrestrial water cycle dynamics is vital for understanding the recent climatic variability and human impacts in the hydrologic cycle. In this study, a downscaling approach was developed and tested, to improve the applicability of terrestrial water storage (TWS) anomaly data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission for understanding local terrestrial water cycle dynamics in the Northern High Plains region. A non-parametric, artificial neural network (ANN)-based model, was utilized to downscale GRACE data by integrating it with hydrological variables (e.g. soil moisture) derived from satellite and land surface model data. The downscaling model, constructed through calibration and sensitivity analysis, was used to estimate TWS anomaly for watersheds ranging from 5000 to 20,000 km2 in the study area. The downscaled water storage anomaly data were evaluated using water storage data derived from an (1) integrated hydrologic model, (2) land surface model (e.g. Noah), and (3) storage anomalies calculated from in-situ groundwater level measurements. Results demonstrate the ANN predicts monthly TWS anomaly within the uncertainty (conservative error estimate = 34 mm) for most of the watersheds. Seasonal derived groundwater storage anomaly (GWSA) from the ANN correlated well (r = ∼0.85) with GWSAs calculated from in-situ groundwater level measurements for a watershed size as small as 6000 km2. ANN downscaled TWSA matches closely with Noah-based TWSA compared to standard GRACE extracted TWSA at a local scale. Moreover, the ANN-downscaled change in TWS replicated the water storage variability resulting from the combined effect of climatic and human impacts (e.g. abstraction). The implications of utilizing finer resolution GRACE data for improving local and regional water resources management decisions and applications are clear, particularly in areas lacking in-situ hydrologic monitoring networks.

Revisiting the social cost of carbon.

PubMed

Nordhaus, William D

2017-02-14

The social cost of carbon (SCC) is a central concept for understanding and implementing climate change policies. This term represents the economic cost caused by an additional ton of carbon dioxide emissions or its equivalent. The present study presents updated estimates based on a revised DICE model (Dynamic Integrated model of Climate and the Economy). The study estimates that the SCC is $31 per ton of CO 2 in 2010 US$ for the current period (2015). For the central case, the real SCC grows at 3% per year over the period to 2050. The paper also compares the estimates with those from other sources.

Revisiting the social cost of carbon

NASA Astrophysics Data System (ADS)

Nordhaus, William D.

2017-02-01

The social cost of carbon (SCC) is a central concept for understanding and implementing climate change policies. This term represents the economic cost caused by an additional ton of carbon dioxide emissions or its equivalent. The present study presents updated estimates based on a revised DICE model (Dynamic Integrated model of Climate and the Economy). The study estimates that the SCC is 31 per ton of CO2 in 2010 US for the current period (2015). For the central case, the real SCC grows at 3% per year over the period to 2050. The paper also compares the estimates with those from other sources.

Thermal energy and economic analysis of a PCM-enhanced household envelope considering different climate zones in Morocco

NASA Astrophysics Data System (ADS)

Kharbouch, Yassine; Mimet, Abdelaziz; El Ganaoui, Mohammed; Ouhsaine, Lahoucine

2018-07-01

This study investigates the thermal energy potentials and economic feasibility of an air-conditioned family household-integrated phase change material (PCM) considering different climate zones in Morocco. A simulation-based optimisation was carried out in order to define the optimal design of a PCM-enhanced household envelope for thermal energy effectiveness and cost-effectiveness of predefined candidate solutions. The optimisation methodology is based on coupling Energyplus® as a dynamic simulation tool and GenOpt® as an optimisation tool. Considering the obtained optimum design strategies, a thermal energy and economic analysis are carried out to investigate PCMs' integration feasibility in the Moroccan constructions. The results show that the PCM-integrated household envelope allows minimising the cooling/heating thermal energy demand vs. a reference household without PCM. While for the cost-effectiveness optimisation, it has been deduced that the economic feasibility is stilling insufficient under the actual PCM market conditions. The optimal design parameters results are also analysed.

Projecting Future Water Levels of the Laurentian Great Lakes

NASA Astrophysics Data System (ADS)

Bennington, V.; Notaro, M.; Holman, K.

2013-12-01

The Laurentian Great Lakes are the largest freshwater system on Earth, containing 84% of North America's freshwater. The lakes are a valuable economic and recreational resource, valued at over 62 billion in annual wages and supporting a 7 billion fishery. Shipping, recreation, and coastal property values are significantly impacted by water level variability, with large economic consequences. Great Lakes water levels fluctuate both seasonally and long-term, responding to natural and anthropogenic climate changes. Due to the integrated nature of water levels, a prolonged small change in any one of the net basin supply components: over-lake precipitation, watershed runoff, or evaporation from the lake surface, may result in important trends in water levels. We utilize the Abdus Salam International Centre for Theoretical Physics's Regional Climate Model Version 4.5.6 to dynamically downscale three global global climate models that represent a spread of potential future climate change for the region to determine whether the climate models suggest a robust response of the Laurentian Great Lakes to anthropogenic climate change. The Model for Interdisciplinary Research on Climate Version 5 (MIROC5), the National Centre for Meteorological Research Earth system model (CNRM-CM5), and the Community Climate System Model Version 4 (CCSM4) project different regional temperature increases and precipitation change over the next century and are used as lateral boundary conditions. We simulate the historical (1980-2000) and late-century periods (2080-2100). Upon model evaluation we will present dynamically downscaled projections of net basin supply changes for each of the Laurentian Great Lakes.

Methodology to assess and map the potential development of forest ecosystems exposed to climate change and atmospheric nitrogen deposition: A pilot study in Germany.

PubMed

Schröder, Winfried; Nickel, Stefan; Jenssen, Martin; Riediger, Jan

2015-07-15

A methodology for mapping ecosystems and their potential development under climate change and atmospheric nitrogen deposition was developed using examples from Germany. The methodology integrated data on vegetation, soil, climate change and atmospheric nitrogen deposition. These data were used to classify ecosystem types regarding six ecological functions and interrelated structures. Respective data covering 1961-1990 were used for reference. The assessment of functional and structural integrity relies on comparing a current or future state with an ecosystem type-specific reference. While current functions and structures of ecosystems were quantified by measurements, potential future developments were projected by geochemical soil modelling and data from a regional climate change model. The ecosystem types referenced the potential natural vegetation and were mapped using data on current tree species coverage and land use. In this manner, current ecosystem types were derived, which were related to data on elevation, soil texture, and climate for the years 1961-1990. These relations were quantified by Classification and Regression Trees, which were used to map the spatial patterns of ecosystem type clusters for 1961-1990. The climate data for these years were subsequently replaced by the results of a regional climate model for 1991-2010, 2011-2040, and 2041-2070. For each of these periods, one map of ecosystem type clusters was produced and evaluated with regard to the development of areal coverage of ecosystem type clusters over time. This evaluation of the structural aspects of ecological integrity at the national level was added by projecting potential future values of indicators for ecological functions at the site level by using the Very Simple Dynamic soil modelling technique based on climate data and two scenarios of nitrogen deposition as input. The results were compared to the reference and enabled an evaluation of site-specific ecosystem changes over time which proved to be both, positive and negative. Copyright © 2015 Elsevier B.V. All rights reserved.

Climate variability and human impact on the environment in South America during the last 2000 years: synthesis and perspectives

NASA Astrophysics Data System (ADS)

Flantua, S. G. A.; Hooghiemstra, H.; Vuille, M.; Behling, H.; Carson, J. F.; Gosling, W. D.; Hoyos, I.; Ledru, M. P.; Montoya, E.; Mayle, F.; Maldonado, A.; Rull, V.; Tonello, M. S.; Whitney, B. S.; González-Arango, C.

2015-07-01

An improved understanding of present-day climate variability and change relies on high-quality data sets from the past two millennia. Global efforts to reconstruct regional climate modes are in the process of validating and integrating paleo-proxies. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to its unknown spatial and temporal coverage. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last two millennia. We identify the pollen records with the required temporal characteristics for PAGES-2 ka climate modelling and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local scale responses to climate modes, thus it is necessary to understand how vegetation-climate interactions might diverge under variable settings. Additionally, pollen is an excellent indicator of human impact through time. Evidence for human land use in pollen records is useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. The LOTRED-SA-2 k initiative provides the ideal framework for the integration of the various paleoclimatic sub-disciplines and paleo-science, thereby jumpstarting and fostering multi-disciplinary research into environmental change on centennial and millennial time scales.

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.

Socio-economic and climate change impacts on agriculture: an integrated assessment, 1990–2080

PubMed Central

Fischer, Günther; Shah, Mahendra; N. Tubiello, Francesco; van Velhuizen, Harrij

2005-01-01

A comprehensive assessment of the impacts of climate change on agro-ecosystems over this century is developed, up to 2080 and at a global level, albeit with significant regional detail. To this end an integrated ecological–economic modelling framework is employed, encompassing climate scenarios, agro-ecological zoning information, socio-economic drivers, as well as world food trade dynamics. Specifically, global simulations are performed using the FAO/IIASA agro-ecological zone model, in conjunction with IIASAs global food system model, using climate variables from five different general circulation models, under four different socio-economic scenarios from the intergovernmental panel on climate change. First, impacts of different scenarios of climate change on bio-physical soil and crop growth determinants of yield are evaluated on a 5′×5′ latitude/longitude global grid; second, the extent of potential agricultural land and related potential crop production is computed. The detailed bio-physical results are then fed into an economic analysis, to assess how climate impacts may interact with alternative development pathways, and key trends expected over this century for food demand and production, and trade, as well as key composite indices such as risk of hunger and malnutrition, are computed. This modelling approach connects the relevant bio-physical and socio-economic variables within a unified and coherent framework to produce a global assessment of food production and security under climate change. The results from the study suggest that critical impact asymmetries due to both climate and socio-economic structures may deepen current production and consumption gaps between developed and developing world; it is suggested that adaptation of agricultural techniques will be central to limit potential damages under climate change. PMID:16433094

An Integrated Hydro-Economic Model for Economy-Wide Climate Change Impact Assessment for Zambia

NASA Astrophysics Data System (ADS)

Zhu, T.; Thurlow, J.; Diao, X.

2008-12-01

Zambia is a landlocked country in Southern Africa, with a total population of about 11 million and a total area of about 752 thousand square kilometers. Agriculture in the country depends heavily on rainfall as the majority of cultivated land is rain-fed. Significant rainfall variability has been a huge challenge for the country to keep a sustainable agricultural growth, which is an important condition for the country to meet the United Nations Millennium Development Goals. The situation is expected to become even more complex as climate change would impose additional impacts on rainwater availability and crop water requirements, among other changes. To understand the impacts of climate variability and change on agricultural production and national economy, a soil hydrology model and a crop water production model are developed to simulate actual crop water uses and yield losses under water stress which provide annual shocks for a recursive dynamic computational general equilibrium (CGE) model developed for Zambia. Observed meteorological data of the past three decades are used in the integrated hydro-economic model for climate variability impact analysis, and as baseline climatology for climate change impact assessment together with several GCM-based climate change scenarios that cover a broad range of climate projections. We found that climate variability can explain a significant portion of the annual variations of agricultural production and GDP of Zambia in the past. Hidden beneath climate variability, climate change is found to have modest impacts on agriculture and national economy of Zambia around 2025 but the impacts would be pronounced in the far future if appropriate adaptations are not implemented. Policy recommendations are provided based on scenario analysis.

Pyrenean Erosion fluxes over the Neoglacial period: From local meteorological climate dynamics to global ones

NASA Astrophysics Data System (ADS)

Simonneau, Anaëlle; Galop, Didier; Chapron, Emmanuel; Guyard, Hervé; Tachikawa, Kazuyo; Mazier, Florence; Bard, Edouard

2016-04-01

Enhanced erosive phases reconstructed from lake sediments from the Eastern Pyrenees (Ariege, France) have been related to past meteorological to climate variations over the Neoglacial period, and more particularly to the impact of snowmelt processes enhancing erosion of mountainous drainage basins (1, 2, 3). The distinctive feature of this study is to perform integrative source to sink approaches, classically developed for diachronic climate reconstructions, on five lacustrine sedimentary infills, both sensitive to extreme meteorological events and located within a radius of only 20 km, in order to distinguish local meteorological from global climatic dynamics, and further discuss the influence of westerlies and North Atlantic Oscillation on clastic supply in contrasted lake basins. For each site, age-depth models are based on radionuclides and radiocarbon dating, and the minerogenic properties of the sediment have been characterized combining X-ray imaging, magnetic susceptibility, grain size, X-ray microfluorescence and laser ICP-MS, in order to document clastic sediment source areas. For instance, titanium and potassium are particularly relevant to track metamorphic rocks erosion, whereas rubidium is specific of the granite one. Combined with the grain texture results, such characterization allowed us to order different types of deposits over the Neoglacial period, interpreted as reflecting enhanced local hydrological events, and more particularly the impact of local snowmelt processes. 13 main phases of enhanced erosion associated with climate deterioration phases have been identified and dated to 4715, 4455, 3875, 2620, 1670, 1380, 1035, 845 (AD1105), 620 (AD1330), 430 (AD1520), 215 (AD1735) et 105 (AD1845) cal BP, and to AD1955 et AD1985. Beyond local meteorological fluctuations, the inter-sites comparison of the five lacustrine sequences studied makes the discussion of global climate dynamics possible, performing wavelets analysis, and identifying characteristic frequencies. We therefore demonstrated that the regional Pyrenean meteorological signal is contemporaneous to Alpine deterioration phases, and remarkably matches negative North Atlantic Oscillation phases and solar minima over the Mid-Late Holocene (4, 5). (1) Simonneau et al., 2013, Climate of the Past, 9: 825-840. (2) Simonneau et al., 2013, The Holocene, 23: 1764-1777. (3) Vannière et al ;, 2013, Climate of the Past, 9: 1193-1209. (4) Olsen et al., 2012, Nature Geoscience, 5 : 808-812. (5) Delaygue and Bard, 2011, Climate Dynamic, 36: 2201-2218.

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

PubMed

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

2012-11-01

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

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD

PubMed Central

Lorenz, David J.; Nieto-Lugilde, Diego; Blois, Jessica L.; Fitzpatrick, Matthew C.; Williams, John W.

2016-01-01

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950–2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850–2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity. PMID:27377537

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD.

PubMed

Lorenz, David J; Nieto-Lugilde, Diego; Blois, Jessica L; Fitzpatrick, Matthew C; Williams, John W

2016-07-05

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950-2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850-2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity.

Creating Dynamically Downscaled Seasonal Climate Forecast and Climate Change Projection Information for the North American Monsoon Region Suitable for Decision Making Purposes

NASA Astrophysics Data System (ADS)

Castro, C. L.; Dominguez, F.; Chang, H.

2010-12-01

Current seasonal climate forecasts and climate change projections of the North American monsoon are based on the use of course-scale information from a general circulation model. The global models, however, have substantial difficulty in resolving the regional scale forcing mechanisms of precipitation. This is especially true during the period of the North American Monsoon in the warm season. Precipitation is driven primarily due to the diurnal cycle of convection, and this process cannot be resolve in coarse-resolution global models that have a relatively poor representation of terrain. Though statistical downscaling may offer a relatively expedient method to generate information more appropriate for the regional scale, and is already being used in the resource decision making processes in the Southwest U.S., its main drawback is that it cannot account for a non-stationary climate. Here we demonstrate the use of a regional climate model, specifically the Weather Research and Forecast (WRF) model, for dynamical downscaling of the North American Monsoon. To drive the WRF simulations, we use retrospective reforecasts from the Climate Forecast System (CFS) model, the operational model used at the U.S. National Center for Environmental Prediction, and three select “well performing” IPCC AR 4 models for the A2 emission scenario. Though relatively computationally expensive, the use of WRF as a regional climate model in this way adds substantial value in the representation of the North American Monsoon. In both cases, the regional climate model captures a fairly realistic and reasonable monsoon, where none exists in the driving global model, and captures the dominant modes of precipitation anomalies associated with ENSO and the Pacific Decadal Oscillation (PDO). Long-term precipitation variability and trends in these simulations is considered via the standardized precipitation index (SPI), a commonly used metric to characterize long-term drought. Dynamically downscaled climate projection data will be integrated into future water resource projections in the state of Arizona, through a cooperative effort involving numerous water resource stakeholders.

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.

Soils evolution and treeline fluctuations under late Holocene climatic changes: an integrated approach from Valle d'Aosta (Western European Alps, Italy)

NASA Astrophysics Data System (ADS)

Masseroli, Anna; Leonelli, Giovanni; Verrecchia, Eric P.; Sebag, David; Pozzi, Emanuele D.; Pelfini, Manuela; Maggi, Valter; Trombino, Luca

2017-04-01

The treeline ecotone, defined as the transition belt in mountain vegetation between the closed forest (timberline) and the alpine grasslands, is one of the most distinctive features of mountain environments and it is widely considered as a climatic boundary. Treeline altitudinal fluctuations may be considered to assess past and ongoing climatic and environmental changes. Although the ecological dynamics of the alpine treeline ecotone is mainly influenced by climate, especially by soil temperature, climatic parameters are not the only factors that influence the treeline position. In fact, the treeline altitude may be locally influenced by environmental factors, geomorphological processes, soil development, and human activities. This study aims at the reconstruction of late Holocene soil evolution and environmental changes at the treeline on the SW slope of the Becca di Viou Mountain in Valle d'Aosta (Western Italian Alps). First, we performed a detailed reconstruction of the treeline altitudinal dynamics. In addition, field (including air and soil temperatures) and laboratory (of both mineral and organic compounds) characterizations have been performed along two transects of seven soil profiles developing at an altitude ranging from 2100 m a.s.l. (closed forest) to 2400 m a.s.l. (treeline ecotone), in order to understand the relationships between colonization by trees and soil development under the ongoing climate change. The upward shift of the treeline was assessed analyzing tree age distribution along the slope by means of a tree-ring based approach. The reconstruction of the treeline altitudinal dynamics (based on years at which the trees reached 2 m in height) at the study site reveals an upward shift of 115 m over the period 1901-2000, reaching the altitude of 2515 m a.s.l. in 2008. The recent treeline shift and the acceleration of tree colonization rates in the alpine belt can be mainly attributed to a climatic input, and particularly to an increasing temperature. The investigated soils show a decreasing development with increasing altitude. Indeed, in the forest area (about 2100 m a.s.l.) soils are well developed (i.e. Podzol), but at higher altitude, they are less developed (i.e. Ranker). In the treeline ecotone, possible traces of Paleosols are also observed. However, future treeline upward shifts in the study area might be severely limited by the geomorphic processes: even if temperature will continue to increase, at higher altitudes, the treeline will meet harsher geomorphic environments characterized by high-energy gravity processes and rock faces that impede soil evolution and tree colonization. The integrated analysis of geopedological, dendrochronological and climate data will provide high resolution information about the responses of high-altitude biological and abiological systems through the Holocene and to the ongoing climate change.

Effects of dynamic agricultural decision making in an ecohydrological model

NASA Astrophysics Data System (ADS)

Reichenau, T. G.; Krimly, T.; Schneider, K.

2012-04-01

Due to various interdependencies between the cycles of water, carbon, nitrogen, and energy the impacts of climate change on ecohydrological systems can only be investigated in an integrative way. Furthermore, the human intervention in the environmental processes makes the system even more complex. On the one hand human impact affects natural systems. On the other hand the changing natural systems have a feedback on human decision making. One of the most important examples for this kind of interaction can be found in the agricultural sector. Management dates (planting, fertilization, harvesting) are chosen based on meteorological conditions and yield expectations. A faster development of crops under a warmer climate causes shorter cropping seasons. The choice of crops depends on their profitability, which is mainly determined by market prizes, the agro-political framework, and the (climate dependent) crop yield. This study investigates these relations for the district Günzburg located in the Upper Danube catchment in southern Germany. The modeling system DANUBIA was used to perform dynamically coupled simulations of plant growth, surface and soil hydrological processes, soil nitrogen transformations, and agricultural decision making. The agro-economic model simulates decisions on management dates (based on meteorological conditions and the crops' development state), on fertilization intensities (based on yield expectations), and on choice of crops (based on profitability). The environmental models included in DANUBIA are to a great extent process based to enable its use in a climate change scenario context. Scenario model runs until 2058 were performed using an IPCC A1B forcing. In consecutive runs, dynamic crop management, dynamic crop selection, and a changing agro-political framework were activated. Effects of these model features on hydrological and ecological variables were analyzed separately by comparing the results to a model run with constant crop distribution and constant management. Results show that the influence of the modeled dynamic management adaptation on variables like transpiration, carbon uptake, or nitrate leaching from the vadose zone is stronger than the influence of a dynamic choice of crops. Climate change was found to have a stronger impact on this modeled choice of crops than the agro-political framework. These results suggest that scenario studies in areas with a large share of arable land should take into account management adaptations to changing climate.

Incorporating climate change into ecosystem service assessments and decisions: a review.

PubMed

Runting, Rebecca K; Bryan, Brett A; Dee, Laura E; Maseyk, Fleur J F; Mandle, Lisa; Hamel, Perrine; Wilson, Kerrie A; Yetka, Kathleen; Possingham, Hugh P; Rhodes, Jonathan R

2017-01-01

Climate change is having a significant impact on ecosystem services and is likely to become increasingly important as this phenomenon intensifies. Future impacts can be difficult to assess as they often involve long timescales, dynamic systems with high uncertainties, and are typically confounded by other drivers of change. Despite a growing literature on climate change impacts on ecosystem services, no quantitative syntheses exist. Hence, we lack an overarching understanding of the impacts of climate change, how they are being assessed, and the extent to which other drivers, uncertainties, and decision making are incorporated. To address this, we systematically reviewed the peer-reviewed literature that assesses climate change impacts on ecosystem services at subglobal scales. We found that the impact of climate change on most types of services was predominantly negative (59% negative, 24% mixed, 4% neutral, 13% positive), but varied across services, drivers, and assessment methods. Although uncertainty was usually incorporated, there were substantial gaps in the sources of uncertainty included, along with the methods used to incorporate them. We found that relatively few studies integrated decision making, and even fewer studies aimed to identify solutions that were robust to uncertainty. For management or policy to ensure the delivery of ecosystem services, integrated approaches that incorporate multiple drivers of change and account for multiple sources of uncertainty are needed. This is undoubtedly a challenging task, but ignoring these complexities can result in misleading assessments of the impacts of climate change, suboptimal management outcomes, and the inefficient allocation of resources for climate adaptation. © 2016 John Wiley & Sons Ltd.

Participatory Scenario Planning for Climate Change Adaptation: the Maui Groundwater Project

NASA Astrophysics Data System (ADS)

Keener, V. W.; Brewington, L.; Finucane, M.

2015-12-01

For the last century, the island of Maui in Hawai'i has been the center of environmental, agricultural, and legal conflict with respect to both surface and groundwater allocation. Planning for sustainable future freshwater supply in Hawai'i requires adaptive policies and decision-making that emphasizes private and public partnerships and knowledge transfer between scientists and non-scientists. We have downscaled dynamical climate models to 1 km resolution in Maui and coupled them with a USGS Water Budget model and a participatory scenario building process to quantify future changes in island-scale climate and groundwater recharge under different land uses. Although these projections are uncertain, the integrated nature of the Pacific RISA research program has allowed us to take a multi-pronged approach to facilitate the uptake of climate information into policy and management. This presentation details the ongoing work to support the development of Hawai'i's first island-wide water use plan under the new climate adaptation directive. Participatory scenario planning began in 2012 to bring together a diverse group of ~100 decision-makers in state and local government, watershed restoration, agriculture, and conservation to 1) determine the type of information (climate variables, land use and development, agricultural practices) they would find helpful in planning for climate change, and 2) develop a set of nested scenarios that represent alternative climate and management futures. This integration of knowledge is an iterative process, resulting in flexible and transparent narratives of complex futures comprised of information at multiple scales. We will present an overview of the downscaling, scenario building, hydrological modeling processes, and stakeholder response.

The treatment of climate science in Integrated Assessment Modelling: integration of climate step function response in an energy system integrated assessment model.

NASA Astrophysics Data System (ADS)

Dessens, Olivier

2016-04-01

Integrated Assessment Models (IAMs) are used as crucial inputs to policy-making on climate change. These models simulate aspect of the economy and climate system to deliver future projections and to explore the impact of mitigation and adaptation policies. The IAMs' climate representation is extremely important as it can have great influence on future political action. The step-function-response is a simple climate model recently developed by the UK Met Office and is an alternate method of estimating the climate response to an emission trajectory directly from global climate model step simulations. Good et al., (2013) have formulated a method of reconstructing general circulation models (GCMs) climate response to emission trajectories through an idealized experiment. This method is called the "step-response approach" after and is based on an idealized abrupt CO2 step experiment results. TIAM-UCL is a technology-rich model that belongs to the family of, partial-equilibrium, bottom-up models, developed at University College London to represent a wide spectrum of energy systems in 16 regions of the globe (Anandarajah et al. 2011). The model uses optimisation functions to obtain cost-efficient solutions, in meeting an exogenously defined set of energy-service demands, given certain technological and environmental constraints. Furthermore, it employs linear programming techniques making the step function representation of the climate change response adapted to the model mathematical formulation. For the first time, we have introduced the "step-response approach" method developed at the UK Met Office in an IAM, the TIAM-UCL energy system, and we investigate the main consequences of this modification on the results of the model in term of climate and energy system responses. The main advantage of this approach (apart from the low computational cost it entails) is that its results are directly traceable to the GCM involved and closely connected to well-known methods of analysing GCMs with the step-experiments. Acknowledgments: This work is supported by the FP7 HELIX project (www.helixclimate.eu) References: Anandarajah, G., Pye, S., Usher, W., Kesicki, F., & Mcglade, C. (2011). TIAM-UCL Global model documentation. https://www.ucl.ac.uk/energy-models/models/tiam-ucl/tiam-ucl-manual Good, P., Gregory, J. M., Lowe, J. A., & Andrews, T. (2013). Abrupt CO2 experiments as tools for predicting and understanding CMIP5 representative concentration pathway projections. Climate Dynamics, 40(3-4), 1041-1053.

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.

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.

Physically-Derived Dynamical Cores in Atmospheric General Circulation Models

NASA Technical Reports Server (NTRS)

Rood, Richard B.; Lin, Shian-Jiann

1999-01-01

The algorithm chosen to represent the advection in atmospheric models is often used as the primary attribute to classify the model. Meteorological models are generally classified as spectral or grid point, with the term grid point implying discretization using finite differences. These traditional approaches have a number of shortcomings that render them non-physical. That is, they provide approximate solutions to the conservation equations that do not obey the fundamental laws of physics. The most commonly discussed shortcomings are overshoots and undershoots which manifest themselves most overtly in the constituent continuity equation. For this reason many climate models have special algorithms to model water vapor advection. This talk focuses on the development of an atmospheric general circulation model which uses a consistent physically-based advection algorithm in all aspects of the model formulation. The shallow-water model is generalized to three dimensions and combined with the physics parameterizations of NCAR's Community Climate Model. The scientific motivation for the development is to increase the integrity of the underlying fluid dynamics so that the physics terms can be more effectively isolated, examined, and improved. The expected benefits of the new model are discussed and results from the initial integrations will be presented.

Physically-Derived Dynamical Cores in Atmospheric General Circulation Models

NASA Technical Reports Server (NTRS)

Rood, Richard B.; Lin, Shian-Kiann

1999-01-01

The algorithm chosen to represent the advection in atmospheric models is often used as the primary attribute to classify the model. Meteorological models are generally classified as spectral or grid point, with the term grid point implying discretization using finite differences. These traditional approaches have a number of shortcomings that render them non-physical. That is, they provide approximate solutions to the conservation equations that do not obey the fundamental laws of physics. The most commonly discussed shortcomings are overshoots and undershoots which manifest themselves most overtly in the constituent continuity equation. For this reason many climate models have special algorithms to model water vapor advection. This talk focuses on the development of an atmospheric general circulation model which uses a consistent physically-based advection algorithm in all aspects of the model formulation. The shallow-water model of Lin and Rood (QJRMS, 1997) is generalized to three dimensions and combined with the physics parameterizations of NCAR's Community Climate Model. The scientific motivation for the development is to increase the integrity of the underlying fluid dynamics so that the physics terms can be more effectively isolated, examined, and improved. The expected benefits of the new model are discussed and results from the initial integrations will be presented.

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.

Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk.

PubMed

MacLeod, D A; Morse, A P

2014-12-02

Around $1.6 billion per year is spent financing anti-malaria initiatives, and though malaria morbidity is falling, the impact of annual epidemics remains significant. Whilst malaria risk may increase with climate change, projections are highly uncertain and to sidestep this intractable uncertainty, adaptation efforts should improve societal ability to anticipate and mitigate individual events. Anticipation of climate-related events is made possible by seasonal climate forecasting, from which warnings of anomalous seasonal average temperature and rainfall, months in advance are possible. Seasonal climate hindcasts have been used to drive climate-based models for malaria, showing significant skill for observed malaria incidence. However, the relationship between seasonal average climate and malaria risk remains unquantified. Here we explore this relationship, using a dynamic weather-driven malaria model. We also quantify key uncertainty in the malaria model, by introducing variability in one of the first order uncertainties in model formulation. Results are visualized as location-specific impact surfaces: easily integrated with ensemble seasonal climate forecasts, and intuitively communicating quantified uncertainty. Methods are demonstrated for two epidemic regions, and are not limited to malaria modeling; the visualization method could be applied to any climate impact.

Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk

NASA Astrophysics Data System (ADS)

MacLeod, D. A.; Morse, A. P.

2014-12-01

Around $1.6 billion per year is spent financing anti-malaria initiatives, and though malaria morbidity is falling, the impact of annual epidemics remains significant. Whilst malaria risk may increase with climate change, projections are highly uncertain and to sidestep this intractable uncertainty, adaptation efforts should improve societal ability to anticipate and mitigate individual events. Anticipation of climate-related events is made possible by seasonal climate forecasting, from which warnings of anomalous seasonal average temperature and rainfall, months in advance are possible. Seasonal climate hindcasts have been used to drive climate-based models for malaria, showing significant skill for observed malaria incidence. However, the relationship between seasonal average climate and malaria risk remains unquantified. Here we explore this relationship, using a dynamic weather-driven malaria model. We also quantify key uncertainty in the malaria model, by introducing variability in one of the first order uncertainties in model formulation. Results are visualized as location-specific impact surfaces: easily integrated with ensemble seasonal climate forecasts, and intuitively communicating quantified uncertainty. Methods are demonstrated for two epidemic regions, and are not limited to malaria modeling; the visualization method could be applied to any climate impact.

Land-use and carbon cycle responses to moderate climate change: implications for land-based mitigation?

PubMed

Humpenöder, Florian; Popp, Alexander; Stevanovic, Miodrag; Müller, Christoph; Bodirsky, Benjamin Leon; Bonsch, Markus; Dietrich, Jan Philipp; Lotze-Campen, Hermann; Weindl, Isabelle; Biewald, Anne; Rolinski, Susanne

2015-06-02

Climate change has impacts on agricultural yields, which could alter cropland requirements and hence deforestation rates. Thus, land-use responses to climate change might influence terrestrial carbon stocks. Moreover, climate change could alter the carbon storage capacity of the terrestrial biosphere and hence the land-based mitigation potential. We use a global spatially explicit economic land-use optimization model to (a) estimate the mitigation potential of a climate policy that provides economic incentives for carbon stock conservation and enhancement, (b) simulate land-use and carbon cycle responses to moderate climate change (RCP2.6), and (c) investigate the combined effects throughout the 21st century. The climate policy immediately stops deforestation and strongly increases afforestation, resulting in a global mitigation potential of 191 GtC in 2100. Climate change increases terrestrial carbon stocks not only directly through enhanced carbon sequestration (62 GtC by 2100) but also indirectly through less deforestation due to higher crop yields (16 GtC by 2100). However, such beneficial climate impacts increase the potential of the climate policy only marginally, as the potential is already large under static climatic conditions. In the broader picture, this study highlights the importance of land-use dynamics for modeling carbon cycle responses to climate change in integrated assessment modeling.

Critical Watersheds: Climate Change, Tipping Points, and Energy-Water Impacts

NASA Astrophysics Data System (ADS)

Middleton, R. S.; Brown, M.; Coon, E.; Linn, R.; McDowell, N. G.; Painter, S. L.; Xu, C.

2014-12-01

Climate change, extreme climate events, and climate-induced disturbances will have a substantial and detrimental impact on terrestrial ecosystems. How ecosystems respond to these impacts will, in turn, have a significant effect on the quantity, quality, and timing of water supply for energy security, agriculture, industry, and municipal use. As a community, we lack sufficient quantitative and mechanistic understanding of the complex interplay between climate extremes (e.g., drought, floods), ecosystem dynamics (e.g., vegetation succession), and disruptive events (e.g., wildfire) to assess ecosystem vulnerabilities and to design mitigation strategies that minimize or prevent catastrophic ecosystem impacts. Through a combination of experimental and observational science and modeling, we are developing a unique multi-physics ecohydrologic framework for understanding and quantifying feedbacks between novel climate and extremes, surface and subsurface hydrology, ecosystem dynamics, and disruptive events in critical watersheds. The simulation capability integrates and advances coupled surface-subsurface hydrology from the Advanced Terrestrial Simulator (ATS), dynamic vegetation succession from the Ecosystem Demography (ED) model, and QUICFIRE, a novel wildfire behavior model developed from the FIRETEC platform. These advances are expected to make extensive contributions to the literature and to earth system modeling. The framework is designed to predict, quantify, and mitigate the impacts of climate change on vulnerable watersheds, with a focus on the US Mountain West and the energy-water nexus. This emerging capability is used to identify tipping points in watershed ecosystems, quantify impacts on downstream users, and formally evaluate mitigation efforts including forest (e.g., thinning, prescribed burns) and watershed (e.g., slope stabilization). The framework is being trained, validated, and demonstrated using field observations and remote data collections in the Valles Caldera National Preserve, including pre- and post-wildfire and infestation observations. Ultimately, the framework will be applied to the upper Colorado River basin. Here, we present an overview of the framework development strategy and latest field and modeling results.

Integration and Typologies of Vulnerability to Climate Change: A Case Study from Australian Wheat Sheep Zones.

PubMed

Huai, Jianjun

2016-09-27

Although the integrated indicator methods have become popular for assessing vulnerability to climate change, their proliferation has introduced a confusing array of scales and indicators that cause a science-policy gap. I argue for a clear adaptation pathway in an "integrative typology" of regional vulnerability that matches appropriate scales, optimal measurements and adaptive strategies in a six-dimensional and multi-level analysis framework of integration and typology inspired by the "5W1H" questions: "Who is concerned about how to adapt to the vulnerability of what to what in some place (where) at some time (when)?" Using the case of the vulnerability of wheat, barley and oats to drought in Australian wheat sheep zones during 1978-1999, I answer the "5W1H" questions through establishing the "six typologies" framework. I then optimize the measurement of vulnerability through contrasting twelve kinds of vulnerability scores with the divergence of crops yields from their regional mean. Through identifying the socioeconomic constraints, I propose seven generic types of crop-drought vulnerability and local adaptive strategy. Our results illustrate that the process of assessing vulnerability and selecting adaptations can be enhanced using a combination of integration, optimization and typology, which emphasize dynamic transitions and transformations between integration and typology.

A GRASS GIS module to obtain an estimation of glacier behavior under climate change: A pilot study on Italian glacier

NASA Astrophysics Data System (ADS)

Strigaro, Daniele; Moretti, Massimiliano; Mattavelli, Matteo; Frigerio, Ivan; Amicis, Mattia De; Maggi, Valter

2016-09-01

The aim of this work is to integrate the Minimal Glacier Model in a Geographic Information System Python module in order to obtain spatial simulations of glacier retreat and to assess the future scenarios with a spatial representation. The Minimal Glacier Models are a simple yet effective way of estimating glacier response to climate fluctuations. This module can be useful for the scientific and glaciological community in order to evaluate glacier behavior, driven by climate forcing. The module, called r.glacio.model, is developed in a GRASS GIS (GRASS Development Team, 2016) environment using Python programming language combined with different libraries as GDAL, OGR, CSV, math, etc. The module is applied and validated on the Rutor glacier, a glacier in the south-western region of the Italian Alps. This glacier is very large in size and features rather regular and lively dynamics. The simulation is calibrated by reconstructing the 3-dimensional dynamics flow line and analyzing the difference between the simulated flow line length variations and the observed glacier fronts coming from ortophotos and DEMs. These simulations are driven by the past mass balance record. Afterwards, the future assessment is estimated by using climatic drivers provided by a set of General Circulation Models participating in the Climate Model Inter-comparison Project 5 effort. The approach devised in r.glacio.model can be applied to most alpine glaciers to obtain a first-order spatial representation of glacier behavior under climate change.

Climatic and biotic drivers of tropical evergreen forest photosynthesis: integrating field, eddy flux, remote sensing and modelling

NASA Astrophysics Data System (ADS)

Wu, J.; Serbin, S.; Xu, X.; Guan, K.; Albert, L.; Hayek, M.; Restrepo-Coupe, N.; Lopes, A. P.; Wiedemann, K. T.; Christoffersen, B. O.; Meng, R.; De Araujo, A. C.; Oliveira Junior, R. C.; Camargo, P. B. D.; Silva, R. D.; Nelson, B. W.; Huete, A. R.; Rogers, A.; Saleska, S. R.

2016-12-01

Tropical evergreen forest photosynthetic metabolism is an important driver of large-scale carbon, water, and energy cycles, generating various climate feedbacks. However, considerable uncertainties remain regarding how best to represent evergreen forest photosynthesis in current terrestrial biosphere models (TBMs), especially its sensitivity to climatic vs. biotic variation. Here, we develop a new approach to partition climatic and biotic controls on tropical forest photosynthesis from hourly to inter-annual timescales. Our results show that climatic factors dominate photosynthesis dynamics at shorter-time scale (i.e. hourly), while biotic factors dominate longer-timescale (i.e. monthly and longer) photosynthetic dynamics. Focusing on seasonal timescales, we combine camera and ecosystem carbon flux observations of forests across a rainfall gradient in Amazonia to show that high dry season leaf turnover shifts canopy composition towards younger more efficient leaves. This seasonal variation in leaf quality (per-area leaf photosynthetic capacity) thus can explain the high photosynthetic seasonality observed in the tropics. Finally, we evaluated the performance of models with different phenological schemes (i.e. leaf quantity versus leaf quality; with and without leaf phenological variation alone the vertical canopy profile). We found that models which represented the phenology of leaf quality and its within-canopy variation performed best in simulating photosynthetic seasonality in tropical evergreen forests. This work highlights the importance of incorporating improved understanding of climatic and biotic controls in next generation TBMs to project future carbon and water cycles in the tropics.

Modeling vector-borne disease risk in migratory animals under climate change.

PubMed

Hall, Richard J; Brown, Leone M; Altizer, Sonia

2016-08-01

Recent theory suggests that animals that migrate to breed at higher latitudes may benefit from reduced pressure from natural enemies, including pathogens ("migratory escape"), and that migration itself weeds out infected individuals and lowers infection prevalence ("migratory culling"). The distribution and activity period of arthropod disease vectors in temperate regions is expected to respond rapidly to climate change, which could reduce the potential for migratory escape. However, climate change could have the opposite effect of reducing transmission if differential responses in the phenology and distribution of migrants and disease vectors reduce their overlap in space and time. Here we outline a simple modeling framework for exploring the influence of climate change on vector-borne disease dynamics in a migratory host. We investigate two scenarios under which pathogen transmission dynamics might be mediated by climate change: (1) vectors respond more rapidly than migrants to advancing phenology at temperate breeding sites, causing peak susceptible host density and vector emergence to diverge ("migratory mismatch") and (2) reduced migratory propensity allows increased nonbreeding survival of infected hosts and larger breeding-site epidemics (loss of migratory culling, here referred to as "sedentary amplification"). Our results highlight the need for continued surveillance of climate-induced changes to migratory behavior and vector activity to predict pathogen prevalence and its impacts on migratory animals. © The Author 2016. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

An Interdisciplinary Module on Regulating Carbon Emissions to Mitigate Climate Change

NASA Astrophysics Data System (ADS)

Penny, S.; Sethi, G.; Smyth, R.; Leibensperger, E. M.; Gervich, C.; Batur, P.

2016-12-01

The dynamics of the unfolding carbon regulatory process presents a unique and timely opportunity to teach students about the grand challenge brought by climate change and the importance of systems thinking and interdisciplinary problem solving. In this poster, we summarize our recently developed 4-week activity-based class module "Regulating Carbon Emissions to Mitigate Climate Change," which we have developed as part of the InTeGrate ("Interdisciplinary Teaching about Earth for a Sustainable Future") program. These materials are suitable for introductory non-majors, environmental sciences majors, and political science majors, and we have formally piloted in each of these settings. This module is truly interdisciplinary and spans topics such as the Supreme Court ruling in Massachusetts v. EPA, costs and benefits of carbon abatement, and climate sensitivity. We discuss the unique challenges (and rewards!) that we experienced teaching materials entirely outside one's expertise.

Modeling the spatial-temporal dynamics of net primary production in Yangtze River Basin using IBIS model

USGS Publications Warehouse

Zhang, Z.; Jiang, H.; Liu, J.; Zhu, Q.; Wei, X.; Jiang, Z.; Zhou, G.; Zhang, X.; Han, J.

2011-01-01

The climate change has significantly affected the carbon cycling in Yangtze River Basin. To better understand the alternation pattern for the relationship between carbon cycling and climate change, the net primary production (NPP) were simulated in the study area from 1956 to 2006 by using the Integrated Biosphere Simulator (IBIS). The results showed that the average annual NPP per square meter was about 0.518 kg C in Yangtze River Basin. The high NPP levels were mainly distributed in the southeast area of Sichuan, and the highest value reached 1.05 kg C/m2. The NPP increased based on the simulated temporal trends. The spatiotemporal variability of the NPP in the vegetation types was obvious, and it was depended on the climate and soil condition. We found the drought climate was one of critical factor that impacts the alterations of the NPP in the area by the simulation. ?? 2011 IEEE.

Global Warming and Northern Hemisphere Sea Ice Extent.

PubMed

Vinnikov; Robock; Stouffer; Walsh; Parkinson; Cavalieri; Mitchell; Garrett; Zakharov

1999-12-03

Surface and satellite-based observations show a decrease in Northern Hemisphere sea ice extent during the past 46 years. A comparison of these trends to control and transient integrations (forced by observed greenhouse gases and tropospheric sulfate aerosols) from the Geophysical Fluid Dynamics Laboratory and Hadley Centre climate models reveals that the observed decrease in Northern Hemisphere sea ice extent agrees with the transient simulations, and both trends are much larger than would be expected from natural climate variations. From long-term control runs of climate models, it was found that the probability of the observed trends resulting from natural climate variability, assuming that the models' natural variability is similar to that found in nature, is less than 2 percent for the 1978-98 sea ice trends and less than 0.1 percent for the 1953-98 sea ice trends. Both models used here project continued decreases in sea ice thickness and extent throughout the next century.

A spatial analysis of population dynamics and climate change in Africa: potential vulnerability hot spots emerge where precipitation declines and demographic pressures coincide

USGS Publications Warehouse

López-Carr, David; Pricope, Narcisa G.; Aukema, Juliann E.; Jankowska, Marta M.; Funk, Christopher C.; Husak, Gregory J.; Michaelsen, Joel C.

2014-01-01

We present an integrative measure of exposure and sensitivity components of vulnerability to climatic and demographic change for the African continent in order to identify “hot spots” of high potential population vulnerability. Getis-Ord Gi* spatial clustering analyses reveal statistically significant locations of spatio-temporal precipitation decline coinciding with high population density and increase. Statistically significant areas are evident, particularly across central, southern, and eastern Africa. The highly populated Lake Victoria basin emerges as a particularly salient hot spot. People located in the regions highlighted in this analysis suffer exceptionally high exposure to negative climate change impacts (as populations increase on lands with decreasing rainfall). Results may help inform further hot spot mapping and related research on demographic vulnerabilities to climate change. Results may also inform more suitable geographical targeting of policy interventions across the continent.

Hydrology: The interdisciplinary science of water

NASA Astrophysics Data System (ADS)

Vogel, Richard M.; Lall, Upmanu; Cai, Ximing; Rajagopalan, Balaji; Weiskel, Peter K.; Hooper, Richard P.; Matalas, Nicholas C.

2015-06-01

We live in a world where biophysical and social processes are tightly coupled. Hydrologic systems change in response to a variety of natural and human forces such as climate variability and change, water use and water infrastructure, and land cover change. In turn, changes in hydrologic systems impact socioeconomic, ecological, and climate systems at a number of scales, leading to a coevolution of these interlinked systems. The Harvard Water Program, Hydrosociology, Integrated Water Resources Management, Ecohydrology, Hydromorphology, and Sociohydrology were all introduced to provide distinct, interdisciplinary perspectives on water problems to address the contemporary dynamics of human interaction with the hydrosphere and the evolution of the Earth's hydrologic systems. Each of them addresses scientific, social, and engineering challenges related to how humans influence water systems and vice versa. There are now numerous examples in the literature of how holistic approaches can provide a structure and vision of the future of hydrology. We review selected examples, which taken together, describe the type of theoretical and applied integrated hydrologic analyses and associated curricular content required to address the societal issue of water resources sustainability. We describe a modern interdisciplinary science of hydrology needed to develop an in-depth understanding of the dynamics of the connectedness between human and natural systems and to determine effective solutions to resolve the complex water problems that the world faces today. Nearly, every theoretical hydrologic model introduced previously is in need of revision to accommodate how climate, land, vegetation, and socioeconomic factors interact, change, and evolve over time.

Hydrology: The interdisciplinary science of water

USGS Publications Warehouse

Vogel, Richard M.; Lall, Upmanu; Cai, Ximing; Rajagopalan, Balaji; Weiskel, Peter K.; Hooper, Richard P.; Matalas, Nicholas C.

2015-01-01

We live in a world where biophysical and social processes are tightly coupled. Hydrologic systems change in response to a variety of natural and human forces such as climate variability and change, water use and water infrastructure, and land cover change. In turn, changes in hydrologic systems impact socioeconomic, ecological, and climate systems at a number of scales, leading to a coevolution of these interlinked systems. The Harvard Water Program, Hydrosociology, Integrated Water Resources Management, Ecohydrology, Hydromorphology, and Sociohydrology were all introduced to provide distinct, interdisciplinary perspectives on water problems to address the contemporary dynamics of human interaction with the hydrosphere and the evolution of the Earth’s hydrologic systems. Each of them addresses scientific, social, and engineering challenges related to how humans influence water systems and vice versa. There are now numerous examples in the literature of how holistic approaches can provide a structure and vision of the future of hydrology. We review selected examples, which taken together, describe the type of theoretical and applied integrated hydrologic analyses and associated curricular content required to address the societal issue of water resources sustainability. We describe a modern interdisciplinary science of hydrology needed to develop an in-depth understanding of the dynamics of the connectedness between human and natural systems and to determine effective solutions to resolve the complex water problems that the world faces today. Nearly, every theoretical hydrologic model introduced previously is in need of revision to accommodate how climate, land, vegetation, and socioeconomic factors interact, change, and evolve over time.

Linking Environmental Research and Practice: Lessons From The Integration of Climate Science and Water Management in the Western United States

NASA Astrophysics Data System (ADS)

Ferguson, D. B.; Rice, J.; Woodhouse, C. A.

2015-12-01

Efforts to better connect scientific research with people and organizations involved in environmental decision making are receiving increased interest and attention. Some of the challenges we currently face, however—including complex questions associated with climate change—present unique challenges because of their scale and scope. Focused research on the intersections between environment and society has provided substantial insight into dynamics of large-scale environmental change and the related impacts on people, natural resources, and ecosystems, yet our ability to connect this research to real-world decision making remains limited. Addressing these complex environmental problems requires broad cooperation between scientists and those who may apply research results in decision making, but there are few templates for guiding the growing number of scientists and practitioners now engaging in this kind of cooperative work. This presentation will offer a set of heuristics for carrying out collaborative work between scientists and practitioners. These heuristics were derived from research that examined the direct experiences of water resources professionals and climate researchers who have been working to integrate science and practice.

A systematic approach to community resilience that reduces the federal fiscal exposure to climate change

NASA Astrophysics Data System (ADS)

Stwertka, C.; Albert, M. R.; White, K. D.

2016-12-01

Despite widely available information about the adverse impacts of climate change to the public, including both private sector and federal fiscal exposure, there remain opportunities to effectively translate this knowledge into action. Further delay of climate preparedness and resilience actions imposes a growing toll on American communities and the United States fiscal budget. We hypothesize that a set of four criteria must be met before a community can translate climate disturbances into preparedness action. We examine four case studies to review these proposed criteria, we discuss the critical success factors that can build community resilience, and we define an operational strategy that could support community resilience while reducing the federal fiscal exposure to climate change. This operational strategy defines a community response system that integrates social science research, builds on the strengths of different sectors, values existing resources, and reduces the planning-to-action time. Our next steps are to apply this solution in the field, and to study the dynamics of community engagement and the circular economy.

Development of virtual research environment for regional climatic and ecological studies and continuous education support

NASA Astrophysics Data System (ADS)

Gordov, Evgeny; Lykosov, Vasily; Krupchatnikov, Vladimir; Bogomolov, Vasily; Gordova, Yulia; Martynova, Yulia; Okladnikov, Igor; Titov, Alexander; Shulgina, Tamara

2014-05-01

Volumes of environmental data archives are growing immensely due to recent models, high performance computers and sensors development. It makes impossible their comprehensive analysis in conventional manner on workplace using in house computing facilities, data storage and processing software at hands. One of possible answers to this challenge is creation of virtual research environment (VRE), which should provide a researcher with an integrated access to huge data resources, tools and services across disciplines and user communities and enable researchers to process structured and qualitative data in virtual workspaces. VRE should integrate data, network and computing resources providing interdisciplinary climatic research community with opportunity to get profound understanding of ongoing and possible future climatic changes and their consequences. Presented are first steps and plans for development of VRE prototype element aimed at regional climatic and ecological monitoring and modeling as well as at continuous education and training support. Recently developed experimental software and hardware platform aimed at integrated analysis of heterogeneous georeferenced data "Climate" (http://climate.scert.ru/, Gordov et al., 2013; Shulgina et al., 2013; Okladnikov et al., 2013) is used as a VRE element prototype and approach test bench. VRE under development will integrate on the base of geoportal distributed thematic data storage, processing and analysis systems and set of models of complex climatic and environmental processes run on supercomputers. VRE specific tools are aimed at high resolution rendering on-going climatic processes occurring in Northern Eurasia and reliable and found prognoses of their dynamics for selected sets of future mankind activity scenaria. Currently the VRE element is accessible via developed geoportal at the same link (http://climate.scert.ru/) and integrates the WRF and «Planet Simulator» models, basic reanalysis and instrumental measurements data and support profound statistical analysis of storaged and modeled on demand data. In particular, one can run the integrated models, preprocess modeling results data, using dedicated modules for numerical processing perform analysys and visualize obtained results. New functionality recently has been added to the statistical analysis tools set aimed at detailed studies of climatic extremes occurring in Northern Asia. The VRE element is also supporting thematic educational courses for students and post-graduate students of the Tomsk State University. In particular, it allow students to perform on-line thematic laboratory work cycles on the basics of analysis of current and potential future regional climate change using Siberia territory as an example (Gordova et al, 2013). We plan to expand the integrated models set and add comprehensive surface and Arctic Ocean description. Developed VRE element "Climate" provides specialists involved into multidisciplinary research projects with reliable and practical instruments for integrated research of climate and ecosystems changes on global and regional scales. With its help even a user without programming skills can process and visualize multidimensional observational and model data through unified web-interface using a common graphical web-browser. This work is partially supported by SB RAS project VIII.80.2.1, RFBR grant 13-05-12034, grant 14-05-00502, and integrated project SB RAS 131. References 1. Gordov E.P., Lykosov V.N., Krupchatnikov V.N., Okladnikov I.G., Titov A.G., Shulgina T.M. Computationaland information technologies for monitoring and modeling of climate changes and their consequences. Novosibirsk: Nauka, Siberian branch, 2013. - 195 p. (in Russian) 2. T.M. Shulgina, E.P. Gordov, I.G. Okladnikov, A.G., Titov, E.Yu. Genina, N.P. Gorbatenko, I.V. Kuzhevskaya,A.S. Akhmetshina. Software complex for a regional climate change analysis. // Vestnik NGU. Series: Information technologies. 2013. Vol. 11. Issue 1. P. 124-131. (in Russian) 3. I.G. Okladnikov, A.G. Titov, T.M. Shulgina, E.P. Gordov, V.Yu. Bogomolov, Yu.V. Martynova, S.P. Suschenko,A.V. Skvortsov. Software for analysis and visualization of climate change monitoring and forecasting data //Numerical methods and programming, 2013. Vol. 14. P. 123-131.(in Russian) 4. Yu.E. Gordova, E.Yu. Genina, V.P. Gorbatenko, E.P. Gordov, I.V. Kuzhevskaya, Yu.V. Martynova , I.G. Okladnikov, A.G. Titov, T.M. Shulgina, N.K. Barashkova Support of the educational process in modern climatology within the web-gis platform «Climate». Open and Distant Education. 2013, No 1(49)., P. 14-19.(in Russian)

Vulnerability of carbon storage in North American boreal forests to wildfires during the 21st century

USGS Publications Warehouse

Balshi, M. S.; McGuire, Anthony David; Duffy, P.; Flannigan, M.; Kicklighter, David W.; Melillo, J.

2009-01-01

The boreal forest contains large reserves of carbon. Across this region, wildfires influence the temporal and spatial dynamics of carbon storage. In this study, we estimate fire emissions and changes in carbon storage for boreal North America over the 21st century. We use a gridded data set developed with a multivariate adaptive regression spline approach to determine how area burned varies each year with changing climatic and fuel moisture conditions. We apply the process-based Terrestrial Ecosystem Model to evaluate the role of future fire on the carbon dynamics of boreal North America in the context of changing atmospheric carbon dioxide (CO2) concentration and climate in the A2 and B2 emissions scenarios of the CGCM2 global climate model. Relative to the last decade of the 20th century, decadal total carbon emissions from fire increase by 2.5–4.4 times by 2091–2100, depending on the climate scenario and assumptions about CO2fertilization. Larger fire emissions occur with warmer climates or if CO2 fertilization is assumed to occur. Despite the increases in fire emissions, our simulations indicate that boreal North America will be a carbon sink over the 21st century if CO2 fertilization is assumed to occur in the future. In contrast, simulations excluding CO2 fertilization over the same period indicate that the region will change to a carbon source to the atmosphere, with the source being 2.1 times greater under the warmer A2 scenario than the B2 scenario. To improve estimates of wildfire on terrestrial carbon dynamics in boreal North America, future studies should incorporate the role of dynamic vegetation to represent more accurately post-fire successional processes, incorporate fire severity parameters that change in time and space, account for human influences through increased fire suppression, and integrate the role of other disturbances and their interactions with future fire regime.

Reconstruction of fire regimes through integrated paleoecological proxy data and ecological modeling.

PubMed

Iglesias, Virginia; Yospin, Gabriel I; Whitlock, Cathy

2014-01-01

Fire is a key ecological process affecting vegetation dynamics and land cover. The characteristic frequency, size, and intensity of fire are driven by interactions between top-down climate-driven and bottom-up fuel-related processes. Disentangling climatic from non-climatic drivers of past fire regimes is a grand challenge in Earth systems science, and a topic where both paleoecology and ecological modeling have made substantial contributions. In this manuscript, we (1) review the use of sedimentary charcoal as a fire proxy and the methods used in charcoal-based fire history reconstructions; (2) identify existing techniques for paleoecological modeling; and (3) evaluate opportunities for coupling of paleoecological and ecological modeling approaches to better understand the causes and consequences of past, present, and future fire activity.

Reconstruction of fire regimes through integrated paleoecological proxy data and ecological modeling

PubMed Central

Iglesias, Virginia; Yospin, Gabriel I.; Whitlock, Cathy

2015-01-01

Fire is a key ecological process affecting vegetation dynamics and land cover. The characteristic frequency, size, and intensity of fire are driven by interactions between top-down climate-driven and bottom-up fuel-related processes. Disentangling climatic from non-climatic drivers of past fire regimes is a grand challenge in Earth systems science, and a topic where both paleoecology and ecological modeling have made substantial contributions. In this manuscript, we (1) review the use of sedimentary charcoal as a fire proxy and the methods used in charcoal-based fire history reconstructions; (2) identify existing techniques for paleoecological modeling; and (3) evaluate opportunities for coupling of paleoecological and ecological modeling approaches to better understand the causes and consequences of past, present, and future fire activity. PMID:25657652

Future Wildfire and Managed Fire Interactions in the Lake Tahoe Basin

NASA Astrophysics Data System (ADS)

Scheller, R.; Kretchun, A.

2017-12-01

Managing large forested landscape in the context of a changing climate and altered disturbance regimes presents new challenges and require integrated assessments of forest disturbance, management, succession, and the carbon cycle. Successful management under these circumstances will require information about trade-offs among multiple objectives and opportunities for spatially optimized landscape-scale management. Improved information about the effects of climate on forest communities, disturbance feedbacks, and the effectiveness of mitigation strategies enables actionable options for landscape managers. We evaluated the effects of fire suppression, wildfires, and forest fuel (thinning) treatments on the long-term carbon storage potential for Lake Tahoe Basin (LTB) forests under various climate futures. We simulated management scenarios that encompass fuel treatments across the larger landscape, beyond the Wildland Urban Interface. We improved upon current fire modeling under climate change via an integrated fire modeling module that, a) explicitly captures the influence of climate, fuels, topography, active fire management (e.g., fire suppression), and fuel treatments, and b) can be parameterized from available data, e.g., remote sensing, field reporting, fire databases, expert opinion. These improvements increase geographic flexibility and decrease reliance on broad historical fire regime statistics - imperfect targets for a no analog future and require minimal parameterization and calibration. We assessed the interactions among fuel treatments, prescribe fire, fire suppression, and stochastically recurring wildfires. Predicted changes in climate and ignition patterns in response to future climatic conditions, vegetation dynamics, and fuel treatments indicate larger potential long-term effects on C emissions, forest structure, and forest composition than prior studies.

Computer simulation of the coffee leaf miner using sexual Penna aging model

NASA Astrophysics Data System (ADS)

de Oliveira, A. C. S.; Martins, S. G. F.; Zacarias, M. S.

2008-01-01

Forecast models based on climatic conditions are of great interest in Integrated Pest Management (IPM) programs. The success of these models depends, among other factors, on the knowledge of the temperature effect on the pests’ population dynamics. In this direction, a computer simulation was made for the population dynamics of the coffee leaf miner, L. coffeella, at different temperatures, considering experimental data relative to the pest. The age structure was inserted into the dynamics through sexual Penna Model. The results obtained, such as life expectancy, growth rate and annual generations’ number, in agreement to those in laboratory and field conditions, show that the simulation can be used as a forecast model for controlling L. coffeella.

Revisiting the social cost of carbon

PubMed Central

Nordhaus, William D.

2017-01-01

The social cost of carbon (SCC) is a central concept for understanding and implementing climate change policies. This term represents the economic cost caused by an additional ton of carbon dioxide emissions or its equivalent. The present study presents updated estimates based on a revised DICE model (Dynamic Integrated model of Climate and the Economy). The study estimates that the SCC is $31 per ton of CO2 in 2010 US$ for the current period (2015). For the central case, the real SCC grows at 3% per year over the period to 2050. The paper also compares the estimates with those from other sources. PMID:28143934

Energy Performance and Optimal Control of Air-conditioned Buildings Integrated with Phase Change Materials

NASA Astrophysics Data System (ADS)

Zhu, Na

This thesis presents an overview of the previous research work on dynamic characteristics and energy performance of buildings due to the integration of PCMs. The research work on dynamic characteristics and energy performance of buildings using PCMs both with and without air-conditioning is reviewed. Since the particular interest in using PCMs for free cooling and peak load shifting, specific research efforts on both subjects are reviewed separately. A simplified physical dynamic model of building structures integrated with SSPCM (shaped-stabilized phase change material) is developed and validated in this study. The simplified physical model represents the wall by 3 resistances and 2 capacitances and the PCM layer by 4 resistances and 2 capacitances respectively while the key issue is the parameter identification of the model. This thesis also presents the studies on the thermodynamic characteristics of buildings enhanced by PCM and on the investigation of the impacts of PCM on the building cooling load and peak cooling demand at different climates and seasons as well as the optimal operation and control strategies to reduce the energy consumption and energy cost by reducing the air-conditioning energy consumption and peak load. An office building floor with typical variable air volume (VAV) air-conditioning system is used and simulated as the reference building in the comparison study. The envelopes of the studied building are further enhanced by integrating the PCM layers. The building system is tested in two selected cities of typical climates in China including Hong Kong and Beijing. The cold charge and discharge processes, the operation and control strategies of night ventilation and the air temperature set-point reset strategy for minimizing the energy consumption and electricity cost are studied. This thesis presents the simulation test platform, the test results on the cold storage and discharge processes, the air-conditioning energy consumption and demand reduction potentials in typical air-conditioning seasons in typical China cites as well as the impacts of operation and control strategies.

VALUE - Validating and Integrating Downscaling Methods for Climate Change Research

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Widmann, Martin; Benestad, Rasmus; Kotlarski, Sven; Huth, Radan; Hertig, Elke; Wibig, Joanna; Gutierrez, Jose

2013-04-01

Our understanding of global climate change is mainly based on General Circulation Models (GCMs) with a relatively coarse resolution. Since climate change impacts are mainly experienced on regional scales, high-resolution climate change scenarios need to be derived from GCM simulations by downscaling. Several projects have been carried out over the last years to validate the performance of statistical and dynamical downscaling, yet several aspects have not been systematically addressed: variability on sub-daily, decadal and longer time-scales, extreme events, spatial variability and inter-variable relationships. Different downscaling approaches such as dynamical downscaling, statistical downscaling and bias correction approaches have not been systematically compared. Furthermore, collaboration between different communities, in particular regional climate modellers, statistical downscalers and statisticians has been limited. To address these gaps, the EU Cooperation in Science and Technology (COST) action VALUE (www.value-cost.eu) has been brought into life. VALUE is a research network with participants from currently 23 European countries running from 2012 to 2015. Its main aim is to systematically validate and develop downscaling methods for climate change research in order to improve regional climate change scenarios for use in climate impact studies. Inspired by the co-design idea of the international research initiative "future earth", stakeholders of climate change information have been involved in the definition of research questions to be addressed and are actively participating in the network. The key idea of VALUE is to identify the relevant weather and climate characteristics required as input for a wide range of impact models and to define an open framework to systematically validate these characteristics. Based on a range of benchmark data sets, in principle every downscaling method can be validated and compared with competing methods. The results of this exercise will directly provide end users with important information about the uncertainty of regional climate scenarios, and will furthermore provide the basis for further developing downscaling methods. This presentation will provide background information on VALUE and discuss the identified characteristics and the validation framework.

Estimating Rates of Permafrost Degradation and their Impact on Ecosystems across Alaska and Northwest Canada using the Process-based Permafrost Dynamics Model GIPL as a Component of the Integrated Ecosystem Model (IEM)

NASA Astrophysics Data System (ADS)

Marchenko, S. S.; Genet, H.; Euskirchen, E. S.; Breen, A. L.; McGuire, A. D.; Rupp, S. T.; Romanovsky, V. E.; Bolton, W. R.; Walsh, J. E.

2016-12-01

The impact of climate warming on permafrost and the potential of climate feedbacks resulting from permafrost thawing have recently received a great deal of attention. Permafrost temperature has increased in most locations in the Arctic and Sub-Arctic during the past 30-40 years. The typical increase in permafrost temperature is 1-3°C. The process-based permafrost dynamics model GIPL developed in the Geophysical Institute Permafrost Lab, and which is the permafrost module of the Integrated Ecosystem Model (IEM) has been using to quantify the nature and rate of permafrost degradation and its impact on ecosystems, infrastructure, CO2 and CH4fluxes and net C storage following permafrost thaw across Alaska and Northwest Canada. The IEM project is a multi-institutional and multi-disciplinary effort aimed at understanding potential landscape, habitat and ecosystem change across the IEM domain. The IEM project also aims to tie three scientific models together Terrestrial Ecosystem Model (TEM), the ALFRESCO (ALaska FRame-based EcoSystem Code) and GIPL so that they exchange data at run-time. The models produce forecasts of future fire, vegetation, organic matter, permafrost and hydrology regimes. The climate forcing data are based on the historical CRU3.1 data set for the retrospective analysis period (1901-2009) and the CMIP3 CCCMA-CGCM3.1 and MPI-ECHAM5/MPI-OM climate models for the future period (2009-2100). All data sets were downscaled to a 1 km resolution, using a differencing methodology (i.e., a delta method) and the Parameter-elevation Regressions on Independent Slopes Model (PRISM) climatology. We estimated the dynamics of permafrost temperature, active layer thickness, area occupied by permafrost, and volume of thawed soils across the IEM domain. The modeling results indicate how different types of ecosystems affect the thermal state of permafrost and its stability. Although the rate of soil warming and permafrost degradation in peatland areas are slower than other areas, a considerable volume of peat will be thawed by the end of the current century. The release of carbon and the net effect of this thawing depends on the balance between increased productivity and respiration, which depend, in part, on soil moisture dynamics.

Climate change hampers endangered species through intensified moisture-related plant stresses (Invited)

NASA Astrophysics Data System (ADS)

Bartholomeus, R.; Witte, J.; van Bodegom, P.; Dam, J. V.; Aerts, R.

2010-12-01

With recent climate change, extremes in meteorological conditions are forecast and observed to increase globally, and to affect vegetation composition. More prolonged dry periods will alternate with more intensive rainfall events, both within and between years, which will change soil moisture dynamics. In temperate climates, soil moisture, in concert with nutrient availability and soil acidity, is the most important environmental filter in determining local plant species composition, as it determines the availability of both oxygen and water to plant roots. These resources are indispensable for meeting the physiological demands of plants. The consequences of climate change for our natural environment are among the most pressing issues of our time. The international research community is beginning to realise that climate extremes may be more powerful drivers of vegetation change and species extinctions than slow-and-steady climatic changes, but the causal mechanisms of such changes are presently unknown. The roles of amplitudes in water availability as drivers of vegetation change have been particularly elusive owing to the lack of integration of the key variables involved. Here we show that the combined effect of increased rainfall variability, temperature and atmospheric CO2-concentration will lead to an increased variability in both wet and dry extremes in stresses faced by plants (oxygen and water stress, respectively). We simulated these plant stresses with a novel, process-based approach, incorporating in detail the interacting processes in the soil-plant-atmosphere interface. In order to quantify oxygen and water stress with causal measures, we focused on interacting meteorological, soil physical, microbial, and plant physiological processes in the soil-plant-atmosphere system. As both the supply and demand of oxygen and water depend strongly on the prevailing meteorological conditions, both oxygen and water stress were calculated dynamically in time to capture climate change effects. We demonstrate that increased rainfall variability in interaction with predicted changes in temperature and CO2, affects soil moisture conditions and plant oxygen and water demands such, that both oxygen stress and water stress will intensify due to climate change. Moreover, these stresses will increasingly coincide, causing variable stress conditions. These variable stress conditions were found to decrease future habitat suitability, especially for plant species that are presently endangered. The future existence of such species is thus at risk by climate change, which has direct implications for policies to maintain endangered species, as applied by international nature management organisations (e.g. IUCN). Our integrated mechanistic analysis of two stresses combined, which has never been done so far, reveals large impacts of climate change on species extinctions and thereby on biodiversity.

Biologically Based Methods for Pest Management in Agriculture under Changing Climates: Challenges and Future Directions.

PubMed

Chidawanyika, Frank; Mudavanhu, Pride; Nyamukondiwa, Casper

2012-11-09

The current changes in global climatic regimes present a significant societal challenge, affecting in all likelihood insect physiology, biochemistry, biogeography and population dynamics. With the increasing resistance of many insect pest species to chemical insecticides and an increasing organic food market, pest control strategies are slowly shifting towards more sustainable, ecologically sound and economically viable options. Biologically based pest management strategies present such opportunities through predation or parasitism of pests and plant direct or indirect defense mechanisms that can all be important components of sustainable integrated pest management programs. Inevitably, the efficacy of biological control systems is highly dependent on natural enemy-prey interactions, which will likely be modified by changing climates. Therefore, knowledge of how insect pests and their natural enemies respond to climate variation is of fundamental importance in understanding biological insect pest management under global climate change. Here, we discuss biological control, its challenges under climate change scenarios and how increased global temperatures will require adaptive management strategies to cope with changing status of insects and their natural enemies.

Representation of the Great Lakes in the Coupled Model Intercomparison Project Version 5

NASA Astrophysics Data System (ADS)

Briley, L.; Rood, R. B.

2017-12-01

The U.S. Great Lakes play a significant role in modifying regional temperatures and precipitation, and as the lakes change in response to a warming climate (i.e., warmer surface water temperatures, decreased ice cover, etc) lake-land-atmosphere dynamics are affected. Because the lakes modify regional weather and are a driver of regional climate change, understanding how they are represented in climate models is important to the reliability of model based information for the region. As part of the Great Lakes Integrated Sciences + Assessments (GLISA) Ensemble project, a major effort is underway to evaluate the Coupled Model Intercomparison Project version (CMIP) 5 global climate models for how well they physically represent the Great Lakes and lake-effects. The CMIP models were chosen because they are a primary source of information in many products developed for decision making (i.e., National Climate Assessment, downscaled future climate projections, etc.), yet there is very little description of how well they represent the lakes. This presentation will describe the results of our investigation of if and how the Great Lakes are represented in the CMIP5 models.

Using a Pareto-optimal solution set to characterize trade-offs between a broad range of values and preferences in climate risk management

NASA Astrophysics Data System (ADS)

Garner, Gregory; Reed, Patrick; Keller, Klaus

2015-04-01

Integrated assessment models (IAMs) are often used to inform the design of climate risk management strategies. Previous IAM studies have broken important new ground on analyzing the effects of parametric uncertainties, but they are often silent on the implications of uncertainties regarding the problem formulation. Here we use the Dynamic Integrated model of Climate and the Economy (DICE) to analyze the effects of uncertainty surrounding the definition of the objective(s). The standard DICE model adopts a single objective to maximize a weighted sum of utilities of per-capita consumption. Decision makers, however, are often concerned with a broader range of values and preferences that may be poorly captured by this a priori definition of utility. We reformulate the problem by introducing three additional objectives that represent values such as (i) reliably limiting global average warming to two degrees Celsius and minimizing (ii) the costs of abatement and (iii) the climate change damages. We use advanced multi-objective optimization methods to derive a set of Pareto-optimal solutions over which decision makers can trade-off and assess performance criteria a posteriori. We illustrate the potential for myopia in the traditional problem formulation and discuss the capability of this multiobjective formulation to provide decision support.

Forecasting effects of climate change on Great Lakes fisheries: models that link habitat supply to population dynamics can help

USGS Publications Warehouse

Jones, Michael L.; Shuter, Brian J.; Zhao, Yingming; Stockwell, Jason D.

2006-01-01

Future changes to climate in the Great Lakes may have important consequences for fisheries. Evidence suggests that Great Lakes air and water temperatures have risen and the duration of ice cover has lessened during the past century. Global circulation models (GCMs) suggest future warming and increases in precipitation in the region. We present new evidence that water temperatures have risen in Lake Erie, particularly during summer and winter in the period 1965–2000. GCM forecasts coupled with physical models suggest lower annual runoff, less ice cover, and lower lake levels in the future, but the certainty of these forecasts is low. Assessment of the likely effects of climate change on fish stocks will require an integrative approach that considers several components of habitat rather than water temperature alone. We recommend using mechanistic models that couple habitat conditions to population demographics to explore integrated effects of climate-caused habitat change and illustrate this approach with a model for Lake Erie walleye (Sander vitreum). We show that the combined effect on walleye populations of plausible changes in temperature, river hydrology, lake levels, and light penetration can be quite different from that which would be expected based on consideration of only a single factor.

Climate Change: Integrating Science and Economics

NASA Astrophysics Data System (ADS)

Prinn, R. G.

2008-12-01

The world is facing an ever-growing conflict between environment and development. Climate change is a century-scale threat requiring a century-long effort in science, technology and policy analysis, and institutions that can sustain this effort over generations. To inform policy development and implementation there is urgent need for better integration of the diverse components of the problem. Motivated by this challenge, we have developed the Integrated Global System Model (IGSM) at MIT. It comprises coupled sub- models of economic development, atmospheric chemistry, climate dynamics and ecosystems. The results of a recent uncertainty analysis involving hundreds of runs of the IGSM imply that, without mitigation policies, the global average surface temperature may rise much faster than previously estimated. Polar temperatures are projected to rise even faster than the average rate with obvious great risks for high latitude ecosystems and ice sheets at the high end of this range. Analysis of policies for climate mitigation, show that the greatest effect of these policies is to lower the probability of extreme changes as opposed to lowering the medians. Faced with the above estimated impacts, the long lifetimes of most greenhouse gases in the atmosphere, the long delay in ultimate warming due to ocean heat uptake, and the capital-intensive global energy infrastructure, the case is strong for concerted action now. Results of runs of the IGSM indicate the need for transformation of the global energy industry on a very large scale to mitigate climate change. Carbon sequestration, renewable energy sources, and nuclear present new economic, technological, and environmental challenges when implemented at the needed scales. Economic analyses using the IGSM indicate that global implementation of efficient policies could allow the needed transformations at bearable costs.

Climatic conditions produce contrasting influences on demographic traits in a long-distance Arctic migrant.

PubMed

Cleasby, Ian R; Bodey, Thomas W; Vigfusdottir, Freydis; McDonald, Jenni L; McElwaine, Graham; Mackie, Kerry; Colhoun, Kendrew; Bearhop, Stuart

2017-03-01

The manner in which patterns of variation and interactions among demographic rates contribute to population growth rate (λ) is key to understanding how animal populations will respond to changing climatic conditions. Migratory species are likely to be particularly sensitive to climatic conditions as they experience a range of different environments throughout their annual cycle. However, few studies have provided fully integrated demographic analyses of migratory populations in response to changing climatic conditions. Here, we employed integrated population models to demonstrate that the environmental conditions experienced during a short but critical period play a central role in the demography of a long-distance migrant, the light-bellied Brent goose (Branta bernicla hrota). Female survival was positively associated with June North Atlantic Oscillation (NAO) values, whereas male survival was not. In contrast, breeding productivity was negatively associated with June NAO, suggesting a trade-off between female survival and reproductive success. Both adult female and adult male survival showed low temporal variation, whereas there was high temporal variation in recruitment and breeding productivity. In addition, while annual population growth was positively correlated with annual breeding productivity, a sensitivity analysis revealed that population growth was most sensitive to changes in adult survival. Our results demonstrate that the environmental conditions experienced during a relatively short-time window at the start of the breeding season play a critical role in shaping the demography of a long-distant Arctic migrant. Crucially, different demographic rates responded in opposing directions to climatic variation, emphasising the need for integrated analysis of multiple demographic traits when understanding population dynamics. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

Response of Debris-Covered and Clean-Ice Glaciers to Climate Change from Observations and Modeling

NASA Astrophysics Data System (ADS)

Rupper, S.; Maurer, J. M.; Schaefer, J. M.; Roe, G.; Huybers, K. M.

2017-12-01

Debris-covered glaciers form a significant percentage of the glacier area and volume in many mountainous regions of the world, and respond differently to climatic forcings as compared to clean-ice glaciers. In particular, debris-covered glaciers tend to downwaste with very little retreat, while clean-ice glaciers simultaneously thin and retreat. This difference has posed a significant challenge to quantifying glacier sensitivity to climate change, modeling glacier response to future climate change, and assessing the impacts of recent and future glacier changes on mountain environments and downstream populations. In this study, we evaluate observations of the geodetic mass balance and thinning profiles of 1000 glaciers across the Himalayas from 1975 to 2016. We use this large sampling of glacier changes over multiple decades to provide a robust statistical comparison of mass loss for clean-ice versus debris-covered glaciers over a period relevant to glacier dynamics. In addition, we force a glacier model with a series of climate change scenarios, and compare the modeled results to the observations. We essentially ask the question, "Are our theoretical expectations consistent with the observations?" Our observations show both clean-ice and debris-covered glaciers, regionally averaged, thinned in a similar pattern for the first 25-year observation period. For the more recent 15-year period, clean ice glaciers show significantly steepened thinning gradients across the surface, while debris-covered glaciers have continued to thin more uniformaly across the surface. Our preliminary model results generally agree with these observations, and suggest that both glacier types are expected to have a thinning phase followed by a retreat phase, but that the timing of the retreat phase is much later for debris-covered glaciers. Thus, these early results suggest these two glacier types are dynamically very similar, but are currently in different phases of response to recent climate change. This difference in phase of response will be carefully evaluated by integrating the modeling and observational components of this work. In addition, we will use this integrated framework to assess the expected impacts of differing glacier response on glacier-related resources in the Himalayas over the coming century.

Towards a high resolution, integrated hydrology model of North America: Diagnosis of feedbacks between groundwater and land energy fluxes at continental scales.

NASA Astrophysics Data System (ADS)

Maxwell, Reed; Condon, Laura

2016-04-01

Recent studies demonstrate feedbacks between groundwater dynamics, overland flow, land surface and vegetation processes, and atmospheric boundary layer development that significantly affect local and regional climate across a range of climatic conditions. Furthermore, the type and distribution of vegetation cover alters land-atmosphere water and energy fluxes, as well as runoff generation and overland flow processes. These interactions can result in significant feedbacks on local and regional climate. In mountainous regions, recent research has shown that spatial and temporal variability in annual evapotranspiration, and thus water budgets, is strongly dependent on lateral groundwater flow; however, the full effects of these feedbacks across varied terrain (e.g. from plains to mountains) are not well understood. Here, we present a high-resolution, integrated hydrology model that covers much of continental North America and encompasses the Mississippi and Colorado watersheds. The model is run in a fully-transient manner at hourly temporal resolution incorporating fully-coupled land energy states and fluxes with integrated surface and subsurface hydrology. Connections are seen between hydrologic variables (such as water table depth) and land energy fluxes (such as latent heat) and spatial and temporal scaling is shown to span many orders of magnitude. Model results suggest that partitioning of plant transpiration to bare soil evaporation is a function of water table depth and later groundwater flow. Using these transient simulations as a proof of concept, we present a vision for future integrated simulation capabilities.

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

PubMed

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

2016-03-31

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

Spatially distributed potential evapotranspiration modeling and climate projections.

PubMed

Gharbia, Salem S; Smullen, Trevor; Gill, Laurence; Johnston, Paul; Pilla, Francesco

2018-08-15

Evapotranspiration integrates energy and mass transfer between the Earth's surface and atmosphere and is the most active mechanism linking the atmosphere, hydrosphsophere, lithosphere and biosphere. This study focuses on the fine resolution modeling and projection of spatially distributed potential evapotranspiration on the large catchment scale as response to climate change. Six potential evapotranspiration designed algorithms, systematically selected based on a structured criteria and data availability, have been applied and then validated to long-term mean monthly data for the Shannon River catchment with a 50m 2 cell size. The best validated algorithm was therefore applied to evaluate the possible effect of future climate change on potential evapotranspiration rates. Spatially distributed potential evapotranspiration projections have been modeled based on climate change projections from multi-GCM ensembles for three future time intervals (2020, 2050 and 2080) using a range of different Representative Concentration Pathways producing four scenarios for each time interval. Finally, seasonal results have been compared to baseline results to evaluate the impact of climate change on the potential evapotranspiration and therefor on the catchment dynamical water balance. The results present evidence that the modeled climate change scenarios would have a significant impact on the future potential evapotranspiration rates. All the simulated scenarios predicted an increase in potential evapotranspiration for each modeled future time interval, which would significantly affect the dynamical catchment water balance. This study addresses the gap in the literature of using GIS-based algorithms to model fine-scale spatially distributed potential evapotranspiration on the large catchment systems based on climatological observations and simulations in different climatological zones. Providing fine-scale potential evapotranspiration data is very crucial to assess the dynamical catchment water balance to setup management scenarios for the water abstractions. This study illustrates a transferable systematic method to design GIS-based algorithms to simulate spatially distributed potential evapotranspiration on the large catchment systems. Copyright © 2018 Elsevier B.V. All rights reserved.

Coupled Crop/Hydrology Model to Estimate Expanded Irrigation Impact on Water Resources

NASA Astrophysics Data System (ADS)

Handyside, C. T.; Cruise, J.

2017-12-01

A coupled agricultural and hydrologic systems model is used to examine the environmental impact of irrigation in the Southeast. A gridded crop model for the Southeast is used to determine regional irrigation demand. This irrigation demand is used in a regional hydrologic model to determine the hydrologic impact of irrigation. For the Southeast to maintain/expand irrigated agricultural production and provide adaptation to climate change and climate variability it will require integrated agricultural and hydrologic system models that can calculate irrigation demand and the impact of the this demand on the river hydrology. These integrated models can be used as (1) historical tools to examine vulnerability of expanded irrigation to past climate extremes (2) future tools to examine the sustainability of expanded irrigation under future climate scenarios and (3) a real-time tool to allow dynamic water resource management. Such tools are necessary to assure stakeholders and the public that irrigation can be carried out in a sustainable manner. The system tools to be discussed include a gridded version of the crop modeling system (DSSAT). The gridded model is referred to as GriDSSAT. The irrigation demand from GriDSSAT is coupled to a regional hydrologic model developed by the Eastern Forest Environmental Threat Assessment Center of the USDA Forest Service) (WaSSI). The crop model provides the dynamic irrigation demand which is a function of the weather. The hydrologic model includes all other competing uses of water. Examples of use the crop model coupled with the hydrologic model include historical analyses which show the change in hydrology as additional acres of irrigated land are added to water sheds. The first order change in hydrology is computed in terms of changes in the Water Availability Stress Index (WASSI) which is the ratio of water demand (irrigation, public water supply, industrial use, etc.) and water availability from the hydrologic model. Also, statistics such as the number of times certain WASSI thresholds are exceeded are calculated to show the impact of expanded irrigation during times of hydrologic drought and the coincident use of water by other sectors. Also, integrated downstream impacts of irrigation are also calculated through changes in flows through the whole river systems.

Developing Flexible, Integrated Hydrologic Modeling Systems for Multiscale Analysis in the Midwest and Great Lakes Region

NASA Astrophysics Data System (ADS)

Hamlet, A. F.; Chiu, C. M.; Sharma, A.; Byun, K.; Hanson, Z.

2016-12-01

Physically based hydrologic modeling of surface and groundwater resources that can be flexibly and efficiently applied to support water resources policy/planning/management decisions at a wide range of spatial and temporal scales are greatly needed in the Midwest, where stakeholder access to such tools is currently a fundamental barrier to basic climate change assessment and adaptation efforts, and also the co-production of useful products to support detailed decision making. Based on earlier pilot studies in the Pacific Northwest Region, we are currently assembling a suite of end-to-end tools and resources to support various kinds of water resources planning and management applications across the region. One of the key aspects of these integrated tools is that the user community can access gridded products at any point along the end-to-end chain of models, looking backwards in time about 100 years (1915-2015), and forwards in time about 85 years using CMIP5 climate model projections. The integrated model is composed of historical and projected future meteorological data based on station observations and statistical and dynamically downscaled climate model output respectively. These gridded meteorological data sets serve as forcing data for the macro-scale VIC hydrologic model implemented over the Midwest at 1/16 degree resolution. High-resolution climate model (4km WRF) output provides inputs for the analyses of urban impacts, hydrologic extremes, agricultural impacts, and impacts to the Great Lakes. Groundwater recharge estimated by the surface water model provides input data for fine-scale and macro-scale groundwater models needed for specific applications. To highlight the multi-scale use of the integrated models in support of co-production of scientific information for decision making, we briefly describe three current case studies addressing different spatial scales of analysis: 1) Effects of climate change on the water balance of the Great Lakes, 2) Future hydropower resources in the St. Joseph River basin, 3) Effects of climate change on carbon cycling in small lakes in the Northern Highland Lakes District.

Spatiotemporal causal modeling for the management of Dengue Fever

NASA Astrophysics Data System (ADS)

Yu, Hwa-Lung; Huang, Tailin; Lee, Chieh-Han

2015-04-01

Increasing climatic extremes have caused growing concerns about the health effects and disease outbreaks. The association between climate variation and the occurrence of epidemic diseases play an important role on a country's public health systems. Part of the impacts are direct casualties associated with the increasing frequency and intensity of typhoons, the proliferation of disease vectors and the short-term increase of clinic visits on gastro-intestinal discomforts, diarrhea, dermatosis, or psychological trauma. Other impacts come indirectly from the influence of disasters on the ecological and socio-economic systems, including the changes of air/water quality, living environment and employment condition. Previous risk assessment studies on dengue fever focus mostly on climatic and non-climatic factors and their association with vectors' reproducing pattern. The public-health implication may appear simple. Considering the seasonal changes and regional differences, however, the causality of the impacts is full of uncertainties. Without further investigation, the underlying dengue fever risk dynamics may not be assessed accurately. The objective of this study is to develop an epistemic framework for assessing dynamic dengue fever risk across space and time. The proposed framework integrates cross-departmental data, including public-health databases, precipitation data over time and various socio-economic data. We explore public-health issues induced by typhoon through literature review and spatiotemporal analytic techniques on public health databases. From those data, we identify relevant variables and possible causal relationships, and their spatiotemporal patterns derived from our proposed spatiotemporal techniques. Eventually, we create a spatiotemporal causal network and a framework for modeling dynamic dengue fever risk.

Addressing spatial scales and new mechanisms in climate impact ecosystem modeling

NASA Astrophysics Data System (ADS)

Poulter, B.; Joetzjer, E.; Renwick, K.; Ogunkoya, G.; Emmett, K.

2015-12-01

Climate change impacts on vegetation distributions are typically addressed using either an empirical approach, such as a species distribution model (SDM), or with process-based methods, for example, dynamic global vegetation models (DGVMs). Each approach has its own benefits and disadvantages. For example, an SDM is constrained by data and few parameters, but does not include adaptation or acclimation processes or other ecosystem feedbacks that may act to mitigate or enhance climate effects. Alternatively, a DGVM model includes many mechanisms relating plant growth and disturbance to climate, but simulations are costly to perform at high-spatial resolution and there remains large uncertainty on a variety of fundamental physical processes. To address these issues, here, we present two DGVM-based case studies where i) high-resolution (1 km) simulations are being performed for vegetation in the Greater Yellowstone Ecosystem using a biogeochemical, forest gap model, LPJ-GUESS, and ii) where new mechanisms for simulating tropical tree-mortality are being introduced. High-resolution DGVM model simulations require not only computing and reorganizing code but also a consideration of scaling issues on vegetation dynamics and stochasticity and also on disturbance and migration. New mechanisms for simulating forest mortality must consider hydraulic limitations and carbon reserves and their interactions on source-sink dynamics and in controlling water potentials. Improving DGVM approaches by addressing spatial scale challenges and integrating new approaches for estimating forest mortality will provide new insights more relevant for land management and possibly reduce uncertainty by physical processes more directly comparable to experimental and observational evidence.

Report from the workshop on climate downscaling and its application in high Hawaiian Islands, September 16–17, 2015

USGS Publications Warehouse

Helweg, David A.; Keener, Victoria; Burgett, Jeff M.

2016-07-14

In the subtropical and tropical Pacific islands, changing climate is predicted to influence precipitation and freshwater availability, and thus is predicted to impact ecosystems goods and services available to ecosystems and human communities. The small size of high Hawaiian Islands, plus their complex microlandscapes, require downscaling of global climate models to provide future projections of greater skill and spatial resolution. Two different climate modeling approaches (physics-based dynamical downscaling and statistics-based downscaling) have produced dissimilar projections. Because of these disparities, natural resource managers and decision makers have low confidence in using the modeling results and are therefore are unwilling to include climate-related projections in their decisions. In September 2015, the Pacific Islands Climate Science Center (PICSC), the Pacific Islands Climate Change Cooperative (PICCC), and the Pacific Regional Integrated Sciences and Assessments (Pacific RISA) program convened a 2-day facilitated workshop in which the two modeling teams, plus key model users and resource managers, were brought together for a comparison of the two approaches, culminating with a discussion of how to provide predictions that are useable by resource managers. The proceedings, discussions, and outcomes of this Workshop are summarized in this Open-File Report.

On the use of finite difference matrix-vector products in Newton-Krylov solvers for implicit climate dynamics with spectral elements

DOE PAGES

Woodward, Carol S.; Gardner, David J.; Evans, Katherine J.

2015-01-01

Efficient solutions of global climate models require effectively handling disparate length and time scales. Implicit solution approaches allow time integration of the physical system with a step size governed by accuracy of the processes of interest rather than by stability of the fastest time scales present. Implicit approaches, however, require the solution of nonlinear systems within each time step. Usually, a Newton's method is applied to solve these systems. Each iteration of the Newton's method, in turn, requires the solution of a linear model of the nonlinear system. This model employs the Jacobian of the problem-defining nonlinear residual, but thismore » Jacobian can be costly to form. If a Krylov linear solver is used for the solution of the linear system, the action of the Jacobian matrix on a given vector is required. In the case of spectral element methods, the Jacobian is not calculated but only implemented through matrix-vector products. The matrix-vector multiply can also be approximated by a finite difference approximation which may introduce inaccuracy in the overall nonlinear solver. In this paper, we review the advantages and disadvantages of finite difference approximations of these matrix-vector products for climate dynamics within the spectral element shallow water dynamical core of the Community Atmosphere Model.« less

Biodiversity matters in feedbacks between climate change and air quality: a study using an individual-based model.

PubMed

Wang, Bin; Shuman, Jacquelyn; Shugart, Herman H; Lerdau, Manuel T

2018-03-30

Air quality is closely associated with climate change via the biosphere because plants release large quantities of volatile organic compounds (VOC) that mediate both gaseous pollutants and aerosol dynamics. Earlier studies, which considered only leaf physiology and simply scale up from leaf-level enhancements of emissions, suggest that climate warming enhances whole forest VOC emissions, and these increased VOC emissions aggravate ozone pollution and secondary organic aerosol formation. Using an individual-based forest VOC emissions model, UVAFME-VOC, that simulates system-level emissions by explicitly simulating forest community dynamics to the individual tree level, ecological competition among the individuals of differing size and age, and radiative transfer and leaf function through the canopy, we find that climate warming only sometimes stimulates isoprene emissions (the single largest source of non-methane hydrocarbon) in a southeastern U.S. forest. These complex patterns result from the combination of higher temperatures' stimulating emissions at the leaf level but decreasing the abundance of isoprene-emitting taxa at the community level by causing a decline in the abundance of isoprene-emitting species (Quercus spp.). This ecological effect eventually outweighs the physiological one, thus reducing overall emissions. Such reduced emissions have far-reaching implications for the climate-air-quality relationships that have been established on the paradigm of warming-enhancement VOC emissions from vegetation. This local scale modeling study suggests that community ecology rather than only individual physiology should be integrated into future studies of biosphere-climate-chemistry interactions. © 2018 by the Ecological Society of America.

Carbon dynamics and land-use choices: building a regional-scale multidisciplinary model

USGS Publications Warehouse

Kerr, Suzi; Liu, Shu-Guang; Pfaff, Alexander S.P.; Hughes, R. Flint

2003-01-01

Policy enabling tropical forests to approach their potential contribution to global-climate-change mitigation requires forecasts of land use and carbon storage on a large scale over long periods. In this paper, we present an integrated modeling methodology that addresses these needs. We model the dynamics of the human land-use system and of C pools contained in each ecosystem, as well as their interactions. The model is national scale, and is currently applied in a preliminary way to Costa Rica using data spanning a period of over 50 years. It combines an ecological process model, parameterized using field and other data, with an economic model, estimated using historical data to ensure a close link to actual behavior. These two models are linked so that ecological conditions affect land-use choices and vice versa. The integrated model predicts land use and its consequences for C storage for policy scenarios. These predictions can be used to create baselines, reward sequestration, and estimate the value in both environmental and economic terms of including C sequestration in tropical forests as part of the efforts to mitigate global climate change. The model can also be used to assess the benefits from costly activities to increase accuracy and thus reduce errors and their societal costs.

Integrating Climate Information and Decision Processes for Regional Climate Resilience

NASA Astrophysics Data System (ADS)

Buizer, James; Goddard, Lisa; Guido, Zackry

2015-04-01

An integrated multi-disciplinary team of researchers from the University of Arizona and the International Research Institute for Climate and Society at Columbia University have joined forces with communities and institutions in the Caribbean, South Asia and West Africa to develop relevant, usable climate information and connect it to real decisions and development challenges. The overall objective of the "Integrating Climate Information and Decision Processes for Regional Climate Resilience" program is to build community resilience to negative impacts of climate variability and change. We produce and provide science-based climate tools and information to vulnerable peoples and the public, private, and civil society organizations that serve them. We face significant institutional challenges because of the geographical and cultural distance between the locale of climate tool-makers and the locale of climate tool-users and because of the complicated, often-inefficient networks that link them. To use an accepted metaphor, there is great institutional difficulty in coordinating the supply of and the demand for useful climate products that can be put to the task of building local resilience and reducing climate vulnerability. Our program is designed to reduce the information constraint and to initiate a linkage that is more demand driven, and which provides a set of priorities for further climate tool generation. A demand-driven approach to the co-production of appropriate and relevant climate tools seeks to meet the direct needs of vulnerable peoples as these needs have been canvassed empirically and as the benefits of application have been adequately evaluated. We first investigate how climate variability and climate change affect the livelihoods of vulnerable peoples. In so doing we assess the complex institutional web within which these peoples live -- the public agencies that serve them, their forms of access to necessary information, the structural constraints under which they make their decisions, and the non-public institutions of support that are available to them. We then interpret this complex reality in terms of the demand for science-based climate products and analyze the channels through which such climate support must pass, thus linking demand assessment with the scientific capacity to create appropriate decision support tools. In summary, the approach we employ is: 1) Demand-driven, beginning with a knowledge of the impacts of climate variability and change upon targeted populations, 2) Focused on vulnerability and resilience, which requires an understanding of broader networks of institutional actors who contribute to the adaptive capacity of vulnerable peoples, 3) Needs-based in that the climate needs matrix set priorities for the assessment of relevant climate products, 4) Dynamic in that the producers of climate products are involved at the point of demand assessment and can respond directly to stated needs, 5) Reflective in that the impacts of climate product interventions are subject to monitoring and evaluation throughout the process. Methods, approaches and preliminary results of our work in the Caribbean will be presented.

Integration and Typologies of Vulnerability to Climate Change: A Case Study from Australian Wheat Sheep Zones

PubMed Central

Huai, Jianjun

2016-01-01

Although the integrated indicator methods have become popular for assessing vulnerability to climate change, their proliferation has introduced a confusing array of scales and indicators that cause a science-policy gap. I argue for a clear adaptation pathway in an “integrative typology” of regional vulnerability that matches appropriate scales, optimal measurements and adaptive strategies in a six-dimensional and multi-level analysis framework of integration and typology inspired by the “5W1H” questions: “Who is concerned about how to adapt to the vulnerability of what to what in some place (where) at some time (when)?” Using the case of the vulnerability of wheat, barley and oats to drought in Australian wheat sheep zones during 1978–1999, I answer the “5W1H” questions through establishing the “six typologies” framework. I then optimize the measurement of vulnerability through contrasting twelve kinds of vulnerability scores with the divergence of crops yields from their regional mean. Through identifying the socioeconomic constraints, I propose seven generic types of crop-drought vulnerability and local adaptive strategy. Our results illustrate that the process of assessing vulnerability and selecting adaptations can be enhanced using a combination of integration, optimization and typology, which emphasize dynamic transitions and transformations between integration and typology. PMID:27670975

Building the Capacity for Climate Services: Thoughts on Training Next Generation Climate Science Integrators

NASA Astrophysics Data System (ADS)

Garfin, G. M.; Brugger, J.; Gordon, E. S.; Barsugli, J. J.; Rangwala, I.; Travis, W.

2015-12-01

For more than a decade, stakeholder needs assessments and reports, including the recent National Climate Assessment, have pointed out the need for climate "science translators" or "science integrators" who can help bridge the gap between the cultures and contexts of researchers and decision-makers. Integration is important for exchanging and enhancing knowledge, building capacity to use climate information in decision making, and fostering more robust planning for decision-making in the context of climate change. This talk will report on the characteristics of successful climate science integrators, and a variety of models for training the upcoming generation of climate science integrators. Science integration characteristics identified by an experienced vanguard in the U.S. include maintaining credibility in both the scientific and stakeholder communities, a basic respect for stakeholders demonstrated through active listening, and a deep understanding of the decision-making context. Drawing upon the lessons of training programs for Cooperative Extension, public health professionals, and natural resource managers, we offer ideas about training next generation climate science integrators. Our model combines training and development of skills in interpersonal relations, communication of science, project implementation, education techniques and practices - integrated with a strong foundation in disciplinary knowledge.

A new dynamical downscaling approach with GCM bias corrections and spectral nudging

NASA Astrophysics Data System (ADS)

Xu, Zhongfeng; Yang, Zong-Liang

2015-04-01

To improve confidence in regional projections of future climate, a new dynamical downscaling (NDD) approach with both general circulation model (GCM) bias corrections and spectral nudging is developed and assessed over North America. GCM biases are corrected by adjusting GCM climatological means and variances based on reanalysis data before the GCM output is used to drive a regional climate model (RCM). Spectral nudging is also applied to constrain RCM-based biases. Three sets of RCM experiments are integrated over a 31 year period. In the first set of experiments, the model configurations are identical except that the initial and lateral boundary conditions are derived from either the original GCM output, the bias-corrected GCM output, or the reanalysis data. The second set of experiments is the same as the first set except spectral nudging is applied. The third set of experiments includes two sensitivity runs with both GCM bias corrections and nudging where the nudging strength is progressively reduced. All RCM simulations are assessed against North American Regional Reanalysis. The results show that NDD significantly improves the downscaled mean climate and climate variability relative to other GCM-driven RCM downscaling approach in terms of climatological mean air temperature, geopotential height, wind vectors, and surface air temperature variability. In the NDD approach, spectral nudging introduces the effects of GCM bias corrections throughout the RCM domain rather than just limiting them to the initial and lateral boundary conditions, thereby minimizing climate drifts resulting from both the GCM and RCM biases.

Climate simulation of the twenty-first century with interactive land-use changes

NASA Astrophysics Data System (ADS)

Voldoire, Aurore; Eickhout, Bas; Schaeffer, Michiel; Royer, Jean-François; Chauvin, Fabrice

2007-08-01

To include land-use dynamics in a general circulation model (GCM), the physical system has to be linked to a system that represents socio-economy. This issue is addressed by coupling an integrated assessment model, IMAGE2.2, to an ocean atmosphere GCM, CNRM-CM3. In the new system, IMAGE2.2 provides CNRM-CM3 with all the external forcings that are scenario dependent: greenhouse gas (GHGs) concentrations, sulfate aerosols charge and land cover. Conversely, the GCM gives IMAGE changes in mean temperature and precipitation. With this new system, we have run an adapted scenario of the IPCC SRES scenario family. We have chosen a single scenario with maximum land-use changes (SRES A2), to illustrate some important feedback issues. Even in this two-way coupled model set-up, land use in this scenario is mainly driven by demographic and agricultural practices, which overpowers a potential influence of climate feedbacks on land-use patterns. This suggests that for scenarios in which socio-economically driven land-use change is very large, land-use changes can be incorporated in GCM simulations as a one-way driving force, without taking into account climate feedbacks. The dynamics of natural vegetation is more closely linked to climate but the time-scale of changes is of the order of a century. Thus, the coupling between natural vegetation and climate could generate important feedbacks but these effects are relevant mainly for multi-centennial simulations.

Modelling carbon responses of tundra ecosystems to historical and projected climate: Sensitivity of pan-Arctic carbon storage to temporal and spatial variation in climate

USGS Publications Warehouse

McGuire, A.D.; Clein, Joy S.; Melillo, J.M.; Kicklighter, D.W.; Meier, R.A.; Vorosmarty, C.J.; Serreze, Mark C.

2000-01-01

Historical and projected climate trends for high latitudes show substantial temporal and spatial variability. To identify uncertainties in simulating carbon (C) dynamics for pan-Arctic tundra, we compare the historical and projected responses of tundra C storage from 1921 to 2100 between simulations by the Terrestrial Ecosystem Model (TEM) for the pan-Arctic and the Kuparuk River Basin, which was the focus of an integrated study of C dynamics from 1994 to 1996. In the historical period from 1921 to 1994, the responses of net primary production (NPP) and heterotrophic respiration (RH) simulated for the Kuparuk River Basin and the pan-Arctic are correlated with the same factors; NPP is positively correlated with net nitrogen mineralization (NMIN) and RH is negatively correlated with mean annual soil moisture. In comparison to the historical period, the spatially aggregated responses of NPP and RH for the Kuparuk River Basin and the pan-Arctic in our simulations for the projected period have different sensitivities to temperature, soil moisture and NMIN. In addition to being sensitive to soil moisture during the projected period, RH is also sensitive to temperature and there is a significant correlation between RH and NMIN. We interpret the increases in NPP during the projected period as being driven primarily by increases in NMIN, and that the correlation between NPP and temperature in the projected period is a result primarily of the causal linkage between temperature, RH, and NMIN. Although similar factors appear to be controlling simulated regional-and biome-scale C dynamics, simulated C dynamics at the two scales differ in magnitude with higher increases in C storage simulated for the Kuparuk River Basin than for the pan-Arctic at the end of the historical period and throughout the projected period. Also, the results of the simulations indicate that responses of C storage show different climate sensitivities at regional and pan-Arctic spatial scales and that these sensitivities change across the temporal scope of the simulations. The results of the TEM simulations indicate that the scaling of C dynamics to a region of arctic tundra may not represent C dynamics of pan-Arctic tundra because of the limited spatial variation in climate and vegetation within a region relative to the pan-Arctic. For reducing uncertainties, our analyses highlight the importance of incorporating the understanding gained from process-level studies of C dynamics in a region of arctic tundra into process-based models that simulate C dynamics in a spatially explicit fashion across the spatial domain of pan-Arctic tundra. Also, efforts to improve gridded datasets of historical climate for the pan-Arctic would advance the ability to assess the responses of C dynamics for pan-Arctic tundra in a more realistic fashion. A major challenge will be to incorporate topographic controls over soil moisture in assessing the response of C storage for pan-Arctic tundra.

Towards an integrated forecasting system for fisheries on habitat-bound stocks

NASA Astrophysics Data System (ADS)

Christensen, A.; Butenschön, M.; Gürkan, Z.; Allen, I. J.

2013-03-01

First results of a coupled modelling and forecasting system for fisheries on habitat-bound stocks are being presented. The system consists currently of three mathematically, fundamentally different model subsystems coupled offline: POLCOMS providing the physical environment implemented in the domain of the north-west European shelf, the SPAM model which describes sandeel stocks in the North Sea, and the third component, the SLAM model, which connects POLCOMS and SPAM by computing the physical-biological interaction. Our major experience by the coupling model subsystems is that well-defined and generic model interfaces are very important for a successful and extendable coupled model framework. The integrated approach, simulating ecosystem dynamics from physics to fish, allows for analysis of the pathways in the ecosystem to investigate the propagation of changes in the ocean climate and to quantify the impacts on the higher trophic level, in this case the sandeel population, demonstrated here on the basis of hindcast data. The coupled forecasting system is tested for some typical scientific questions appearing in spatial fish stock management and marine spatial planning, including determination of local and basin-scale maximum sustainable yield, stock connectivity and source/sink structure. Our presented simulations indicate that sandeel stocks are currently exploited close to the maximum sustainable yield, even though periodic overfishing seems to have occurred, but large uncertainty is associated with determining stock maximum sustainable yield due to stock inherent dynamics and climatic variability. Our statistical ensemble simulations indicates that the predictive horizon set by climate interannual variability is 2-6 yr, after which only an asymptotic probability distribution of stock properties, like biomass, are predictable.

CIM-EARTH: Community Integrated Model of Economic and Resource Trajectories for Humankind

NASA Astrophysics Data System (ADS)

Foster, I.; Elliott, J.; Munson, T.; Judd, K.; Moyer, E. J.; Sanstad, A. H.

2010-12-01

We report here on the development of an open source software framework termed CIM-EARTH that is intended to aid decision-making in climate and energy policy. Numerical modeling in support of evaluating policies to address climate change is difficult not only because of inherent uncertainties but because of the differences in scale and modeling approach required for various subcomponents of the system. Economic and climate models are structured quite differently, and while climate forcing can be assumed to be roughly global, climate impacts and the human response to them occur on small spatial scales. Mitigation policies likewise can be applied on scales ranging from the better part of a continent (e.g. a carbon cap-and-trade program for the entire U.S.) to a few hundred km (e.g. statewide renewable portfolio standards and local gasoline taxes). Both spatial and time resolution requirements can be challenging for global economic models. CIM-EARTH is a modular framework based around dynamic general equilibrium models. It is designed as a community tool that will enable study of the environmental benefits, transition costs, capitalization effects, and other consequences of both mitigation policies and unchecked climate change. Modularity enables both integration of highly resolved component sub-models for energy and other key systems and also user-directed choice of tradeoffs between e.g. spatial, sectoral, and time resolution. This poster describes the framework architecture, the current realized version, and plans for future releases. As with other open-source models familiar to the climate community (e.g. CCSM), deliverables will be made publicly available on a regular schedule, and community input is solicited for development of new features and modules.

Incorporating geodiversity into conservation decisions.

PubMed

Comer, Patrick J; Pressey, Robert L; Hunter, Malcolm L; Schloss, Carrie A; Buttrick, Steven C; Heller, Nicole E; Tirpak, John M; Faith, Daniel P; Cross, Molly S; Shaffer, Mark L

2015-06-01

In a rapidly changing climate, conservation practitioners could better use geodiversity in a broad range of conservation decisions. We explored selected avenues through which this integration might improve decision making and organized them within the adaptive management cycle of assessment, planning, implementation, and monitoring. Geodiversity is seldom referenced in predominant environmental law and policy. With most natural resource agencies mandated to conserve certain categories of species, agency personnel are challenged to find ways to practically implement new directives aimed at coping with climate change while retaining their species-centered mandate. Ecoregions and ecological classifications provide clear mechanisms to consider geodiversity in plans or decisions, the inclusion of which will help foster the resilience of conservation to climate change. Methods for biodiversity assessment, such as gap analysis, climate change vulnerability analysis, and ecological process modeling, can readily accommodate inclusion of a geophysical component. We adapted others' approaches for characterizing landscapes along a continuum of climate change vulnerability for the biota they support from resistant, to resilient, to susceptible, and to sensitive and then summarized options for integrating geodiversity into planning in each landscape type. In landscapes that are relatively resistant to climate change, options exist to fully represent geodiversity while ensuring that dynamic ecological processes can change over time. In more susceptible landscapes, strategies aiming to maintain or restore ecosystem resilience and connectivity are paramount. Implementing actions on the ground requires understanding of geophysical constraints on species and an increasingly nimble approach to establishing management and restoration goals. Because decisions that are implemented today will be revisited and amended into the future, increasingly sophisticated forms of monitoring and adaptation will be required to ensure that conservation efforts fully consider the value of geodiversity for supporting biodiversity in the face of a changing climate. © 2015 Society for Conservation Biology.

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

Health risk in the context of climate change and adaptation - Concept and mapping as an integrated approach

NASA Astrophysics Data System (ADS)

Kienberger, S.; Notenbaert, A.; Zeil, P.; Bett, B.; Hagenlocher, M.; Omolo, A.

2012-04-01

Climate change has been stated as being one of the greatest challenges to global health in the current century. Climate change impacts on human health and the socio-economic and related poverty consequences are however still poorly understood. While epidemiological issues are strongly coupled with environmental and climatic parameters, the social and economic circumstances of populations might be of equal or even greater importance when trying to identify vulnerable populations and design appropriate and well-targeted adaptation measures. The inter-linkage between climate change, human health risk and socio-economic impacts remains an important - but largely outstanding - research field. We present an overview on how risk is traditionally being conceptualised in the human health domain and reflect critically on integrated approaches as being currently used in the climate change context. The presentation will also review existing approaches, and how they can be integrated towards adaptation tools. Following this review, an integrated risk concept is being presented, which has been currently adapted under the EC FP7 research project (HEALTHY FUTURES; http://www.healthyfutures.eu/). In this approach, health risk is not only defined through the disease itself (as hazard) but also by the inherent vulnerability of the system, population or region under study. It is in fact the interaction of environment and society that leads to the development of diseases and the subsequent risk of being negatively affected by it. In this conceptual framework vulnerability is being attributed to domains of lack of resilience as well as underlying preconditions determining susceptibilities. To fulfil a holistic picture vulnerability can be associated to social, economic, environmental, institutional, cultural and physical dimensions. The proposed framework also establishes the important nexus to adaptation and how different measures can be related to avoid disease outbreaks, reduce vulnerability in order to lower health risks and disease impacts. The proposed framework explains the generic concepts of disease hazard, vulnerability, risk and its connections. It can be applied to many different diseases and implemented in different ways. Statistical or dynamic disease models integrating future climate projections can - for example - be combined with forecast models. These can be evaluated against different socio-economic development pathways and feed into decisions support systems with an ultimate aim of designing the most appropriate risk reduction strategies. The paper will present first preliminary results on the mapping of vulnerability for the Eastern African region, including diseases such as Malaria, Schistosomiasis and Rift Valley Fever and conclude with current research challenges and how they will be addressed within the HEALTHY FUTURES project.

Climate Change Impacts and Adaptation on Southwestern DoD Facilities

DTIC Science & Technology

2017-03-03

integrating climate change risks into decision priorities. 15. SUBJECT TERMS adaptation, baseline sensitivity, climate change, climate exposure...four bases we found that integrating climate change risks into the current decision matrix, by linking projected risks to current or past impacts...data and decision tools and methods. Bases have some capacity to integrate climate-related information, but they have limited resources to undertake

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

NASA Astrophysics Data System (ADS)

Cai, X.; Yang, Z.-L.; Fisher, J. B.; Zhang, X.; Barlage, M.; Chen, F.

2016-01-01

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. In this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soil and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station - a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.

Spiders: water-driven erosive structures in the southern hemisphere of Mars.

PubMed

Prieto-Ballesteros, Olga; Fernández-Remolar, David C; Rodríguez-Manfredi, José Antonio; Selsis, Franck; Manrubia, Susanna C

2006-08-01

Recent data from space missions reveal that there are ongoing climatic changes and erosive processes that continuously modify surface features of Mars. We have investigated the seasonal dynamics of a number of morphological features located at Inca City, a representative area at high southern latitude that has undergone seasonal processes. By integrating visual information from the Mars Orbiter Camera on board the Mars Global Surveyor and climatic cycles from a Mars' General Circulation Model, and considering the recently reported evidence for the presence of water-ice and aqueous precipitates on Mars, we propose that a number of the erosive features identified in Inca City, among them spiders, result from the seasonal melting of aqueous salty solutions.

Climate and atmosphere simulator for experiments on ecological systems in changing environments.

PubMed

Verdier, Bruno; Jouanneau, Isabelle; Simonnet, Benoit; Rabin, Christian; Van Dooren, Tom J M; Delpierre, Nicolas; Clobert, Jean; Abbadie, Luc; Ferrière, Régis; Le Galliard, Jean-François

2014-01-01

Grand challenges in global change research and environmental science raise the need for replicated experiments on ecosystems subjected to controlled changes in multiple environmental factors. We designed and developed the Ecolab as a variable climate and atmosphere simulator for multifactor experimentation on natural or artificial ecosystems. The Ecolab integrates atmosphere conditioning technology optimized for accuracy and reliability. The centerpiece is a highly contained, 13-m(3) chamber to host communities of aquatic and terrestrial species and control climate (temperature, humidity, rainfall, irradiance) and atmosphere conditions (O2 and CO2 concentrations). Temperature in the atmosphere and in the water or soil column can be controlled independently of each other. All climatic and atmospheric variables can be programmed to follow dynamical trajectories and simulate gradual as well as step changes. We demonstrate the Ecolab's capacity to simulate a broad range of atmospheric and climatic conditions, their diurnal and seasonal variations, and to support the growth of a model terrestrial plant in two contrasting climate scenarios. The adaptability of the Ecolab design makes it possible to study interactions between variable climate-atmosphere factors and biotic disturbances. Developed as an open-access, multichamber platform, this equipment is available to the international scientific community for exploring interactions and feedbacks between ecological and climate systems.

Analysis and prediction of agricultural pest dynamics with Tiko'n, a generic tool to develop agroecological food web models

NASA Astrophysics Data System (ADS)

Malard, J. J.; Rojas, M.; Adamowski, J. F.; Anandaraja, N.; Tuy, H.; Melgar-Quiñonez, H.

2016-12-01

While several well-validated crop growth models are currently widely used, very few crop pest models of the same caliber have been developed or applied, and pest models that take trophic interactions into account are even rarer. This may be due to several factors, including 1) the difficulty of representing complex agroecological food webs in a quantifiable model, and 2) the general belief that pesticides effectively remove insect pests from immediate concern. However, pests currently claim a substantial amount of harvests every year (and account for additional control costs), and the impact of insects and of their trophic interactions on agricultural crops cannot be ignored, especially in the context of changing climates and increasing pressures on crops across the globe. Unfortunately, most integrated pest management frameworks rely on very simple models (if at all), and most examples of successful agroecological management remain more anecdotal than scientifically replicable. In light of this, there is a need for validated and robust agroecological food web models that allow users to predict the response of these webs to changes in management, crops or climate, both in order to predict future pest problems under a changing climate as well as to develop effective integrated management plans. Here we present Tiko'n, a Python-based software whose API allows users to rapidly build and validate trophic web agroecological models that predict pest dynamics in the field. The programme uses a Bayesian inference approach to calibrate the models according to field data, allowing for the reuse of literature data from various sources and reducing the need for extensive field data collection. We apply the model to the cononut black-headed caterpillar (Opisina arenosella) and associated parasitoid data from Sri Lanka, showing how the modeling framework can be used to rapidly develop, calibrate and validate models that elucidate how the internal structures of food webs determine their behaviour and allow users to evaluate different integrated management options.

Dynamic data analysis of climate and recharge conditions over time in the Edwards Aquifer, Texas

NASA Astrophysics Data System (ADS)

Pierce, S. A.; Collins, J.; Banner, J.

2017-12-01

Understanding the temporal patterns in datasets related to climate, recharge, and water resource conditions is important for informing water management and policy decisions. Data analysis and pipelines for evaluating these disparate sources of information are challenging to set up and rely on emerging informatics tools to complete. This project gathers data from both historical and recent sources for the Edwards Aquifer of central Texas. The Edwards faces a unique array of challenges, as it is composed of karst limestone, is susceptible to contaminants and climate change, and is expected to supply water for a rapidly growing population. Given these challenges, new approaches to integrating data will be particularly important. Case study data from the Edwards is used to evaluate aquifer and hydrologic system conditions over time as well as to discover patterns and possible relationships across the information sources. Prior research that evaluated trends in discharge and recharge of the aquifer is revisited by considering new data from 1992-2015, and the sustainability of the Edwards as a water resource within the more recent time period is addressed. Reusable and shareable analytical data pipelines are constructed using Jupyter Notebooks and Python libraries, and an interactive visualization is implemented with the information. In addition to the data sources that are utilized for the water balance analyses, the Global Surface Water Monitoring System from the University of Minnesota, a tool that integrates a wide number of satellite datasets with known surface water dynamics and machine learning, is used to evaluate water body persistence and change over time at regional scales. Preliminary results indicate that surface water body over the Edwards with differing aerial extents are declining, excepting some dam-controlled lakes in the region. Other existing tools and machine learning applications are also considered. Results are useful to the Texas Water Research Network and provide a reproducible geoinformatics approach to integrated data analysis for water resources at regional scales.

Hydrofutures and Hydromorphology

NASA Astrophysics Data System (ADS)

Lall, U.

2006-12-01

Hydromorphology refers to the science of hydrologic evolution. It represents a synthesis of planetary and social sciences that collectively determine the spatial and temporal evolution of planetary water. At present human actions directly or indirectly play a major role in determining hydrofutures. Man's role in changing water trajectories is now clear at both local and planetary scales. Changing climate leads to changing ecology and changing water patterns. Changing water conditions may in turn regulate (limit anthropogenic climate change) or adversely impact (e.g., runaway greenhouse) climate, as well as human habitation and water use patterns. This talk will address the problem of the prediction of future hydrologic conditions in the different media and reservoirs of the planet, from the integrated perspective indicated above. Key examples of the mechanisms of hydrologic change, that relate to climate and ecological dyanmics, and to human activity are identified as well. A theoretical framework for researching this multi-attribute dynamical system from a water centric perspective is advocated as a critical need for planetary science and human welfare.

Southern high-latitude terrestrial climate change during the Paleocene-Eocene derived from a marine pollen record (ODP Site 1172, East Tasman Plateau)

NASA Astrophysics Data System (ADS)

Contreras, L.; Pross, J.; Bijl, P. K.; O'Hara, R. B.; Raine, J. I.; Sluijs, A.; Brinkhuis, H.

2014-01-01

Reconstructing the early Paleogene climate dynamics of terrestrial settings in the high southern latitudes is important to assess the role of high-latitude physical and biogeochemical processes in the global climate system. However, whereas a number of high-quality Paleogene climate records has become available for the marine realm of the high southern latitudes over the recent past, the long-term evolution of coeval terrestrial climates and ecosystems is yet poorly known. We here explore the climate and vegetation dynamics on Tasmania from the middle Paleocene to the early Eocene (60.7-54.2 Ma) based on a sporomorph record from Ocean Drilling Program (ODP) Site 1172 on the East Tasman Plateau. Our results show that three distinctly different vegetation types thrived on Tasmania under a high-precipitation regime during the middle Paleocene to early Eocene, with each type representing different temperature conditions: (i) warm-temperate forests dominated by gymnosperms that were dominant during the middle and late Paleocene; (ii) cool-temperate forests dominated by southern beech (Nothofagus) and araucarians across the middle/late Paleocene transition interval (~59.5 to ~59.0 Ma); and (iii) paratropical forests rich in ferns that were established during and in the wake of the Paleocene-Eocene Thermal Maximum (PETM). The transient establishment of cool-temperate forests lacking any frost-sensitive elements (i.e., palms and cycads) across the middle/late Paleocene transition interval indicates markedly cooler conditions, with the occurrence of frosts in winter, on Tasmania during that time. The integration of our sporomorph data with previously published TEX86-based sea-surface temperatures from ODP Site 1172 documents that the vegetation dynamics on Tasmania were closely linked with the temperature evolution in the Tasman sector of the Southwest Pacific region. Moreover, the comparison of our season-specific climate estimates for the sporomorph assemblages from ODP Site 1172 with the TEX86L- and TEX86H-based temperature data suggests a warm-season bias of both calibrations for the early Paleogene of the high southern latitudes.

Southern high-latitude terrestrial climate change during the Palaeocene-Eocene derived from a marine pollen record (ODP Site 1172, East Tasman Plateau)

NASA Astrophysics Data System (ADS)

Contreras, L.; Pross, J.; Bijl, P. K.; O'Hara, R. B.; Raine, J. I.; Sluijs, A.; Brinkhuis, H.

2014-07-01

Reconstructing the early Palaeogene climate dynamics of terrestrial settings in the high southern latitudes is important to assess the role of high-latitude physical and biogeochemical processes in the global climate system. However, whereas a number of high-quality Palaeogene climate records has become available for the marine realm of the high southern latitudes over the recent past, the long-term evolution of coeval terrestrial climates and ecosystems is yet poorly known. We here explore the climate and vegetation dynamics on Tasmania from the middle Palaeocene to the early Eocene (60.7-54.2 Ma) based on a sporomorph record from Ocean Drilling Program (ODP) Site 1172 on the East Tasman Plateau. Our results show that three distinctly different vegetation types thrived on Tasmania under a high-precipitation regime during the middle Palaeocene to early Eocene, with each type representing different temperature conditions: (i) warm-temperate forests dominated by gymnosperms that were dominant during the middle and late Palaeocene (excluding the middle/late Palaeocene transition); (ii) cool-temperate forests dominated by southern beech (Nothofagus) and araucarians that transiently prevailed across the middle/late Palaeocene transition interval (~ 59.5 to ~ 59.0 Ma); and (iii) paratropical forests rich in ferns that were established during and in the wake of the Palaeocene-Eocene Thermal Maximum (PETM). The transient establishment of cool-temperate forests lacking any frost-sensitive elements (i.e. palms and cycads) across the middle/late Palaeocene transition interval indicates markedly cooler conditions, with the occurrence of frosts in winter, on Tasmania during that time. The integration of our sporomorph data with previously published TEX86-based sea-surface temperatures from ODP Site 1172 documents that the vegetation dynamics on Tasmania were closely linked with the temperature evolution in the Tasman sector of the Southwest Pacific region. Moreover, the comparison of our season-specific climate estimates for the sporomorph assemblages from ODP Site 1172 with the TEX86L- and TEX86H-based temperature data suggests a warm bias of both calibrations for the early Palaeogene of the high southern latitudes.

Uncertainty analysis of vegetation distribution in the northern high latitudes during the 21st century with a dynamic vegetation model.

PubMed

Jiang, Yueyang; Zhuang, Qianlai; Schaphoff, Sibyll; Sitch, Stephen; Sokolov, Andrei; Kicklighter, David; Melillo, Jerry

2012-03-01

This study aims to assess how high-latitude vegetation may respond under various climate scenarios during the 21st century with a focus on analyzing model parameters induced uncertainty and how this uncertainty compares to the uncertainty induced by various climates. The analysis was based on a set of 10,000 Monte Carlo ensemble Lund-Potsdam-Jena (LPJ) simulations for the northern high latitudes (45(o)N and polewards) for the period 1900-2100. The LPJ Dynamic Global Vegetation Model (LPJ-DGVM) was run under contemporary and future climates from four Special Report Emission Scenarios (SRES), A1FI, A2, B1, and B2, based on the Hadley Centre General Circulation Model (GCM), and six climate scenarios, X901M, X902L, X903H, X904M, X905L, and X906H from the Integrated Global System Model (IGSM) at the Massachusetts Institute of Technology (MIT). In the current dynamic vegetation model, some parameters are more important than others in determining the vegetation distribution. Parameters that control plant carbon uptake and light-use efficiency have the predominant influence on the vegetation distribution of both woody and herbaceous plant functional types. The relative importance of different parameters varies temporally and spatially and is influenced by climate inputs. In addition to climate, these parameters play an important role in determining the vegetation distribution in the region. The parameter-based uncertainties contribute most to the total uncertainty. The current warming conditions lead to a complexity of vegetation responses in the region. Temperate trees will be more sensitive to climate variability, compared with boreal forest trees and C3 perennial grasses. This sensitivity would result in a unanimous northward greenness migration due to anomalous warming in the northern high latitudes. Temporally, boreal needleleaved evergreen plants are projected to decline considerably, and a large portion of C3 perennial grass is projected to disappear by the end of the 21st century. In contrast, the area of temperate trees would increase, especially under the most extreme A1FI scenario. As the warming continues, the northward greenness expansion in the Arctic region could continue.

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.

Progress in fast, accurate multi-scale climate simulations

DOE PAGES

Collins, W. D.; Johansen, H.; Evans, K. J.; ...

2015-06-01

We present a survey of physical and computational techniques that have the potential to contribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth with these computational improvements include the capture of remote forcings of localized hydrological extreme events, an accurate representation of cloud features over a range of spatial and temporal scales, and parallel, large ensembles of simulations to more effectively explore model sensitivities and uncertainties. Numerical techniques, such as adaptive mesh refinement, implicit time integration, and separate treatment of fast physical time scales are enablingmore » improved accuracy and fidelity in simulation of dynamics and allowing more complete representations of climate features at the global scale. At the same time, partnerships with computer science teams have focused on taking advantage of evolving computer architectures such as many-core processors and GPUs. As a result, approaches which were previously considered prohibitively costly have become both more efficient and scalable. In combination, progress in these three critical areas is poised to transform climate modeling in the coming decades.« less

From biota to chemistry and climate: towards a comprehensive description of trace gas exchange between the biosphere and atmosphere

NASA Astrophysics Data System (ADS)

Arneth, A.; Sitch, S.; Bondeau, A.; Butterbach-Bahl, K.; Foster, P.; Gedney, N.; de Noblet-Ducoudré, N.; Prentice, I. C.; Sanderson, M.; Thonicke, K.; Wania, R.; Zaehle, S.

2010-01-01

Exchange of non-CO2 trace gases between the land surface and the atmosphere plays an important role in atmospheric chemistry and climate. Recent studies have highlighted its importance for interpretation of glacial-interglacial ice-core records, the simulation of the pre-industrial and present atmosphere, and the potential for large climate-chemistry and climate-aerosol feedbacks in the coming century. However, spatial and temporal variations in trace gas emissions and the magnitude of future feedbacks are a major source of uncertainty in atmospheric chemistry, air quality and climate science. To reduce such uncertainties Dynamic Global Vegetation Models (DGVMs) are currently being expanded to mechanistically represent processes relevant to non-CO2 trace gas exchange between land biota and the atmosphere. In this paper we present a review of important non-CO2 trace gas emissions, the state-of-the-art in DGVM modelling of processes regulating these emissions, identify key uncertainties for global scale model applications, and discuss a methodology for model integration and evaluation.

From biota to chemistry and climate: towards a comprehensive description of trace gas exchange between the biosphere and atmosphere

NASA Astrophysics Data System (ADS)

Arneth, A.; Sitch, S.; Bondeau, A.; Butterbach-Bahl, K.; Foster, P.; Gedney, N.; de Noblet-Ducoudré, N.; Prentice, I. C.; Sanderson, M.; Thonicke, K.; Wania, R.; Zaehle, S.

2009-07-01

Exchange of non-CO2 trace gases between the land surface and the atmosphere plays an important role in atmospheric chemistry and climate. Recent studies have highlighted its importance for interpretation of glacial-interglacial ice-core records, the simulation of the pre-industrial and present atmosphere, and the potential for large climate-chemistry and climate-aerosol feedbacks in the coming century. However, spatial and temporal variations in trace gas emissions and the magnitude of future feedbacks are a major source of uncertainty in atmospheric chemistry, air quality and climate science. To reduce such uncertainties Dynamic Global Vegetation Models (DGVMs) are currently being expanded to mechanistically represent processes relevant to non-CO2 trace gas exchange between land biota and the atmosphere. In this paper we present a review of important non-CO2 trace gas emissions, the state-of-the-art in DGVM modelling of processes regulating these emissions, identify key uncertainties for global scale model applications, and discuss a methodology for model integration and evaluation.

Assessing Impacts of Climate Change on Forests: The State of Biological Modeling

DOE R&D Accomplishments Database

Dale, V. H.; Rauscher, H. M.

1993-04-06

Models that address the impacts to forests of climate change are reviewed by four levels of biological organization: global, regional or landscape, community, and tree. The models are compared as to their ability to assess changes in greenhouse gas flux, land use, maps of forest type or species composition, forest resource productivity, forest health, biodiversity, and wildlife habitat. No one model can address all of these impacts, but landscape transition models and regional vegetation and land-use models consider the largest number of impacts. Developing landscape vegetation dynamics models of functional groups is suggested as a means to integrate the theory of both landscape ecology and individual tree responses to climate change. Risk assessment methodologies can be adapted to deal with the impacts of climate change at various spatial and temporal scales. Four areas of research development are identified: (1) linking socioeconomic and ecologic models, (2) interfacing forest models at different scales, (3) obtaining data on susceptibility of trees and forest to changes in climate and disturbance regimes, and (4) relating information from different scales.

Diel growth dynamics in tree stems: linking anatomy and ecophysiology.

PubMed

Steppe, Kathy; Sterck, Frank; Deslauriers, Annie

2015-06-01

Impacts of climate on stem growth in trees are studied in anatomical, ecophysiological, and ecological disciplines, but an integrative framework to assess those impacts remains lacking. In this opinion article, we argue that three research efforts are required to provide that integration. First, we need to identify the missing links in diel patterns in stem diameter and stem growth and relate those patterns to the underlying mechanisms that control water and carbon balance. Second, we should focus on the understudied mechanisms responsible for seasonal impacts on such diel patterns. Third, information on stem anatomy and ecophysiology should be integrated in the same experiments and mechanistic plant growth models to capture both diel and seasonal scales. Copyright © 2015 Elsevier Ltd. All rights reserved.

(Model) Peatlands in late Quaternary interglacials

NASA Astrophysics Data System (ADS)

Kleinen, Thomas; Brovkin, Victor

2016-04-01

Peatlands have accumulated a substantial amount of carbon, roughly 600 PgC, during the Holocene. Prior to the Holocene, there is relatively little direct evidence of peatlands, though coal deposits bear witness to a long history of peat-forming ecosystems going back to the Carboniferous. We therefore need to rely on models to investigate peatlands in times prior to the Holocene. We have developed a dynamical model of wetland extent and peat accumulation, integrated in the coupled climate carbon cycle model of intermediate complexity CLIMBER2-LPJ, in order to mechanistically model interglacial carbon cycle dynamics. This model consists of the climate model of intermediate complexity CLIMBER2 and the dynamic global vegetation model LPJ, which we have extended with modules to determine peatland extent and carbon accumulation. The model compares reasonably well to Holocene peat data. We have used this model to investigate the dynamics of atmospheric CO2 in the Holocene and two other late Quaternary interglacials, namely the Eemian, which is interesting due to its warmth, and Marine Isotope Stage 11 (MIS11), which is the longest interglacial during the last 500ka. We will also present model results of peatland extent and carbon accumulation for these interglacials. We will discuss model shortcomings and knowledge gaps currently preventing an application of the model to full glacial-interglacial cycles.

Long-term boreal forest dynamics and disturbances: a multi-proxy approach

NASA Astrophysics Data System (ADS)

Stivrins, Normunds; Aakala, Tuomas; Kuuluvainen, Timo; Pasanen, Leena; Ilvonen, Liisa; Holmström, Lasse; Seppä, Heikki

2017-04-01

The boreal forest provides a variety of ecosystem services that are threatened under the ongoing climate warming. Along with the climate, there are several factors (fire, human-impact, pathogens), which influence boreal forest dynamics. Combination of short and long-term studies allowing complex assessment of forest response to natural abiotic and biotic stress factors is necessary for sustainable management of the boreal forest now and in the future. The ongoing EBOR (Ecological history and long-term dynamics of the boreal forest ecosystem) project integrates forest ecological and palaeoecological approaches to study boreal forest dynamics and disturbances. Using pollen, non-pollen palynomorphs, micro- and macrocharcoal, tree rings and fire scars, we analysed forest dynamics at stand-scale by sampling small forest hollows (small paludified depressions) and the surrounding forest stands in Finland and western Russia. Using charcoal data, we estimated a fire return interval of 320 years for the Russian sites, and, based on the fungi Neurospora that can grow on charred tree bark after a low-intensity fire, we were able to distinguish low- and high-intensity fire-events. In addition to the influence of fire events and/or fire regime changes, we further assessed potential relationships between tree species and herbivore presence and pathogens. As an example of such a relationship, our preliminary findings indicated a negative relationship between Picea and fungi Lasiosphaeria (caudata), which occurred during times of Picea decline.

System Dynamics based Dengue modeling environment to simulate evolution of Dengue infection under different climate scenarios

NASA Astrophysics Data System (ADS)

Anwar, R.; Khan, R.; Usmani, M.; Colwell, R. R.; Jutla, A.

2017-12-01

Vector borne infectious diseases such as Dengue, Zika and Chikungunya remain a public health threat. An estimate of the World Health Organization (WHO) suggests that about 2.5 billion people, representing ca. 40% of human population,are at increased risk of dengue; with more than 100 million infection cases every year. Vector-borne infections cannot be eradicated since disease causing pathogens survive in the environment. Over the last few decades dengue infection has been reported in more than 100 countries and is expanding geographically. Female Ae. Aegypti mosquito, the daytime active and a major vector for dengue virus, is associated with urban population density and regional climatic processes. However, mathematical quantification of relationships on abundance of vectors and climatic processes remain a challenge, particularly in regions where such data are not routinely collected. Here, using system dynamics based feedback mechanism, an algorithm integrating knowledge from entomological, meteorological and epidemiological processes is developed that has potential to provide ensemble simulations on risk of occurrence of dengue infection in human population. Using dataset from satellite remote sensing, the algorithm was calibrated and validated using actual dengue case data of Iquitos, Peru. We will show results on model capabilities in capturing initiation and peak in the observed time series. In addition, results from several simulation scenarios under different climatic conditions will be discussed.

An Overview of SASSCAL Activities Supporting Interdisciplinary Water Research in Southern Africa

NASA Astrophysics Data System (ADS)

Helmschrot, J.; Jürgens, N.

2013-12-01

Climate change will affect current water resources in sub-Saharan Africa. Considering projected climate scenarios, the overall challenge in the southern African region is to secure water at sufficient quality and quantity for both, the stability of ecosystems with their functions and services as well as for human well-being (potable water, irrigation water, and water for industrial use). Thus, improved understanding of the linkages between hydrological (including hydro-geological) components of ecosystems and society is needed as a precondition to develop sustainable management strategies for integrated water resources management in this data scarce region. Funded by the German Ministry of Education and Research (BMBF), 87 research projects of the SASSCAL Initiative (Southern African Science Service Centre for Climate Change and Adaptive Land Management) focus on providing information and services allowing for a better understanding and assessment of the impact of climate and land management changes in five thematic areas, namely climate, water, agriculture, forestry and biodiversity. Water-related research activities in SASSCAL aim to improve our knowledge on the complex interactions and feedbacks between surface and groundwater dynamics and resources as well as land surface processes in selected regions of the participating countries (Angola, Botswana, Namibia, South Africa and Zambia). The main objective of this joint and integrated research effort is to develop reliable hydrological and hydro-geological baseline data along with a set of analytical methods to strengthen the research capacity of the water sector of the Southern African region. Thereby, SASSCAL contributes to the implemention of integrated water resources management strategies for improved trans-boundary river management and resources usage in the perspective of global climate and land management changes. Here, we present an overview and first results of ongoing studies conducted by various SASSCAL research teams. Specifically addressed is the installation of 30 Automatic Weather Stations in Angola, Botswana and Zambia which will notably improve regional data availability. We further introduce case studies on flood monitoring using remote sensing products, hydrological risks assessments and early warning systems for floods, integrated hydrological modeling efforts, groundwater-surface water interactions and various hydrological process studies in different ecosystems, all at various spatial (local, regional, national and international) and temporal (short-term, long-term, climate projection) scales. With this variety of examples we demonstrate our interdisciplinary research approach as the prerequisite to address the complexity of interacting drivers and processes affecting our land and water resources. The integration of these joint research efforts with findings from other thematic areas, e.g. in the field of optimized land management, deforestation and restoration, ecosystem stability and resilience, climate projections, food production and security, will allow for a better understanding and assessment of global change related environmental threats and resulting societal challenges in the Southern African region.

From vision to action: roadmapping as a strategic method and tool to implement climate change adaptation - the example of the roadmap 'water sensitive urban design 2020'.

PubMed

Hasse, J U; Weingaertner, D E

2016-01-01

As the central product of the BMBF-KLIMZUG-funded Joint Network and Research Project (JNRP) 'dynaklim - Dynamic adaptation of regional planning and development processes to the effects of climate change in the Emscher-Lippe region (North Rhine Westphalia, Germany)', the Roadmap 2020 'Regional Climate Adaptation' has been developed by the various regional stakeholders and institutions containing specific regional scenarios, strategies and adaptation measures applicable throughout the region. This paper presents the method, elements and main results of this regional roadmap process by using the example of the thematic sub-roadmap 'Water Sensitive Urban Design 2020'. With a focus on the process support tool 'KlimaFLEX', one of the main adaptation measures of the WSUD 2020 roadmap, typical challenges for integrated climate change adaptation like scattered knowledge, knowledge gaps and divided responsibilities but also potential solutions and promising chances for urban development and urban water management are discussed. With the roadmap and the related tool, the relevant stakeholders of the Emscher-Lippe region have jointly developed important prerequisites to integrate their knowledge, to clarify vulnerabilities, adaptation goals, responsibilities and interests, and to foresightedly coordinate measures, resources, priorities and schedules for an efficient joint urban planning, well-grounded decision-making in times of continued uncertainties and step-by-step implementation of adaptation measures from now on.

Modeling Joint Climate and Bioenergy Policies: Challenges of integrating economic and environmental data. (Invited)

NASA Astrophysics Data System (ADS)

Hellwinckel, C. M.; West, T. O.; de La Torre Ugarte, D.; Perlack, R.

2010-12-01

In the coming decades agriculture will be asked to play a significant role in reducing carbon emissions and reducing our use of foreign oil. The Renewable Fuels Standard combined with possible climate legislation will alter the economic landscape effecting agricultural land use decisions. The joint implementation of these two policies could potentially work against one another. We have integrated biogeophysical data into the POLYSYS economic model to analyze the effects of climate change and bioenergy legislation upon regional land-use change, soil carbon, carbon emissions, biofuel production, and agricultural income. The purpose of the analysis was to use the integrated model to identify carbon and bioenergy policies that could act synergistically to meet Renewable Fuel Standard goals, reduce net emissions of carbon, and increase agricultural incomes. The heterogeneous nature of soils, crop yields, and management practices presented challenges to the modeling process. Regional variation in physical data can significantly affect economic land use decisions and patterns. For this reason, we disaggregated the economic component of the model to the county level, with sub-county soils and land-use data informing the county level decisions. Modeling carbon offset dynamics presented unique challenges, as the physical responses of local soils impact the economic incentives offered, and conversely, the resulting land-use changes impact characteristics of local soils. Additionally, using data from different resolution levels led to questions of appropriate scale of analysis. This presentation will describe the integrated model, present some significant results from our analysis, and discuss appropriate steps forward given what we learned.

Dynamic Agroecological Zones for the Inland Pacific Northwest, USA

NASA Astrophysics Data System (ADS)

Huggins, D. R.; Rupp, R.; Gessler, P.; Pan, W.; Brown, D. J.; Machado, S.; Walden, V. P.; Eigenbrode, S.; Abatzoglou, J. T.

2011-12-01

Agroecological zones (AEZ's) have traditionally been defined by integrating multiple layers of biophysical (e.g. climate, soil, terrain) and occasionally socioeconomic data to create unique zones with specific ranges of land use constraints and potentials. Our approach to defining AEZ's assumes that current agricultural land uses have emerged as a consequence of biophysical and socioeconomic drivers. Therefore, we explore the concept that AEZ's can be derived from classifying the geographic distribution of current agricultural systems (e.g. the wheat-fallow cropping system zone) based on spatially geo-referenced annual cropland use data that is currently available through the National Agricultural Statistical Service (NASS). By defining AEZ's in this way, we expect to: (1) provide baseline information that geographically delineates the boundaries of current AEZ's and subzones and therefore the capacity to evaluate shifts in AEZ boundaries over time; (2) assess the biophysical (e.g. climate, soils, terrain) and socioeconomic factors (e.g. commodity prices) that are most useful for predicting and correctly classifying current AEZ's, subzones or future shifts in AEZ boundaries; (3) identify and develop AEZ-relevant climate mitigation and adaptation strategies; and (4) integrate biophysical and socioeconomic data sources to pursue a transdisciplinary examination of climate-driven AEZ futures. Achieving these goals will aid in realizing major objectives for a USDA National Institute of Food and Agriculture, Agriculture and Food Research Initiative, Cooperative Agricultural Project entitled "Regional Approaches to Climate Change (REACCH) for Pacific Northwest Agriculture". REACCH is a research, education and extension project under the leadership of the University of Idaho with significant collaboration from Washington State University, Oregon State University and the USDA Agricultural Research Service that is working towards increasing the capacity of Inland Pacific Northwest cereal production systems to adapt to and mitigate climate change. The AEZ concept is central to project-wide integration that will enable researchers, stakeholders, students, the public, and policymakers to acquire a more holistic understanding of the interrelationships of agriculture, climate change and the development of mitigation and adaptation strategies. Therefore AEZ's are part of a prescription for land management, given climate change that will enable the incorporation of information from climate models, economic models, crop models, pest disease and weed vulnerabilities, and other data sources. Specific to this presentation, we address the AEZ-related objective of developing methodology for defining major AEZ's within the Inland Pacific Northwest REACCH study area based on annual NASS cropland data.

Decarbonizing the Global Economy - An Integrated Assessment of Low Carbon Emission Scenarios proposed in Climate Policy

NASA Astrophysics Data System (ADS)

Hokamp, Sascha; Khabbazan, Mohammad Mohammadi

2017-04-01

In 2015, the Conference of the Parties (COP 21) reaffirmed to targeting the global mean temperature rise below 2 °C in 2100 while finding no consent on decarbonizing the global economy, and instead, the final agreement called for enhanced scientific investigation of low carbon emission scenarios (UNFCC, 2015). In addition, the Climate Action Network International (CAN) proposes Special Reports to address decarbonization and low carbon development including 1.5 °C scenarios (IPCC, 2016). In response to these developments, we investigate whether the carbon emission cuts, in accordance with the recent climate policy proposals, may reach the climate target. To tackle this research question, we employ the coupled climate-energy-economy integrated assessment Model of INvestment and endogenous technological Development (MIND, cf. Edenhofer et al., 2005, Neubersch et al. 2014). Extending MIND's climate module to the two-box version used in the Dynamic Integrated model of Climate and the Economy (DICE, cf. Nordhaus and Sztorc, 2013, Nordhaus 2014), we perform a cost-effectiveness analysis with constraints on anthropogenic carbon emissions. We show that a climate policy scenario with early decarbonization complies with the 2° C climate target, even without Carbon Capturing and Storage (CCS) or negative emissions (see van Vuuren et al., 2013, for negative emissions). However, using emission inertia of 3.7 percent annually, reflecting the inflexibility on transforming the energy sector, we find a climate policy with moderately low emissions from 2100 onwards at a cost in terms of Balanced Growth Equivalents (BGE, cf. Anthoff and Tol, 2009) of 0.764 % that requires an early (2035 vs. 2120) peak of investments in renewable energy production compared to a business-as-usual scenario. Hence, decarbonizing the global economy and achieving the 2 °C target might still be possible before 2100, but the window of opportunity is beginning to close. References: Anthoff, D., and Tol, R. S. J. (2009), "The Impact of Climate Change on the Balanced Growth Equivalent: An Application to FUND", Environmental and Resource Economics, 43 (3), 351-367. Edenhofer, O., Bauer, N., and Kriegler, E. (2005), "The Impact of Technological Change on Climate Protection and Welfare: Insights from the Model MIND", Ecological Economics, 54, 277-292. Neubersch, D., Held, H., and Otto, A., (2014), "Operationalizing Climate Targets under Learning: An Application of Cost-Risk Analysis", Climatic Change, 126, 305-318. Nordhaus, W. D., and Sztorc, P., (2013), DICE2013R: Introduction and User's Manual Nordhaus, W. D. (2014), "Estimates of the Social Cost of Carbon: Concepts and Results from the DICE-2013R Model and Alternative Approaches", Journal of the Association of Environmental and Resource Economists, 1 (1/2, Spring/Summer, 2014), 273-312. IPCC (2016), Sixth Assessment Report (AR6) Products, IPCC-XLIII/INF.7. UNFCCC (2015), Adoption of the Paris Agreement van Vuuren, D. P., Deetman, S., van Vliet, J., van den Berg, M. , van Ruijven, B.J., and Koelbl, B. (2013): "The Role of Negative CO2 Emissions for Reaching 2 °C - Insights from Integrated Assessment Modelling", Climatic Change, 118, 15-27.

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

PubMed

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

2015-09-04

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

Directed International Technological Change and Climate Policy: New Methods for Identifying Robust Policies Under Conditions of Deep Uncertainty

NASA Astrophysics Data System (ADS)

Molina-Perez, Edmundo

It is widely recognized that international environmental technological change is key to reduce the rapidly rising greenhouse gas emissions of emerging nations. In 2010, the United Nations Framework Convention on Climate Change (UNFCCC) Conference of the Parties (COP) agreed to the creation of the Green Climate Fund (GCF). This new multilateral organization has been created with the collective contributions of COP members, and has been tasked with directing over USD 100 billion per year towards investments that can enhance the development and diffusion of clean energy technologies in both advanced and emerging nations (Helm and Pichler, 2015). The landmark agreement arrived at the COP 21 has reaffirmed the key role that the GCF plays in enabling climate mitigation as it is now necessary to align large scale climate financing efforts with the long-term goals agreed at Paris 2015. This study argues that because of the incomplete understanding of the mechanics of international technological change, the multiplicity of policy options and ultimately the presence of climate and technological change deep uncertainty, climate financing institutions such as the GCF, require new analytical methods for designing long-term robust investment plans. Motivated by these challenges, this dissertation shows that the application of new analytical methods, such as Robust Decision Making (RDM) and Exploratory Modeling (Lempert, Popper and Bankes, 2003) to the study of international technological change and climate policy provides useful insights that can be used for designing a robust architecture of international technological cooperation for climate change mitigation. For this study I developed an exploratory dynamic integrated assessment model (EDIAM) which is used as the scenario generator in a large computational experiment. The scope of the experimental design considers an ample set of climate and technological scenarios. These scenarios combine five sources of uncertainty: climate change, elasticity of substitution between renewable and fossil energy and three different sources of technological uncertainty (i.e. R&D returns, innovation propensity and technological transferability). The performance of eight different GCF and non-GCF based policy regimes is evaluated in light of various end-of-century climate policy targets. Then I combine traditional scenario discovery data mining methods (Bryant and Lempert, 2010) with high dimensional stacking methods (Suzuki, Stem and Manzocchi, 2015; Taylor et al., 2006; LeBlanc, Ward and Wittels, 1990) to quantitatively characterize the conditions under which it is possible to stabilize greenhouse gas emissions and keep temperature rise below 2°C before the end of the century. Finally, I describe a method by which it is possible to combine the results of scenario discovery with high-dimensional stacking to construct a dynamic architecture of low cost technological cooperation. This dynamic architecture consists of adaptive pathways (Kwakkel, Haasnoot and Walker, 2014; Haasnoot et al., 2013) which begin with carbon taxation across both regions as a critical near term action. Then in subsequent phases different forms of cooperation are triggered depending on the unfolding climate and technological conditions. I show that there is no single policy regime that dominates over the entire uncertainty space. Instead I find that it is possible to combine these different architectures into a dynamic framework for technological cooperation across regions that can be adapted to unfolding climate and technological conditions which can lead to a greater rate of success and to lower costs in meeting the end-of-century climate change objectives agreed at the 2015 Paris Conference of the Parties. Keywords: international technological change, emerging nations, climate change, technological uncertainties, Green Climate Fund.

Integration of a Physically based Distributed Hydrological Model with a Model of Carbon and Nitrogen Cycling: A Case Study at the Luquillo Critical Zone Observatory, Puerto Rico

NASA Astrophysics Data System (ADS)

Bastola, S.; Dialynas, Y. G.; Bras, R. L.; Arnone, E.; Noto, L. V.

2015-12-01

The dynamics of carbon and nitrogen cycles, increasingly influenced by human activities, are the key to the functioning of ecosystems. These cycles are influenced by the composition of the substrate, availability of nitrogen, the population of microorganisms, and by environmental factors. Therefore, land management and use, climate change, and nitrogen deposition patterns influence the dynamics of these macronutrients at the landscape scale. In this work a physically based distributed hydrological model, the tRIBS model, is coupled with a process-based multi-compartment model of the biogeochemical cycle to simulate the dynamics of carbon and nitrogen (CN) in the Mameyes River basin, Puerto Rico. The model includes a wide range of processes that influence the movement, production, alteration of nutrients in the landscape and factors that affect the CN cycling. The tRIBS integrates geomorphological and climatic factors that influence the cycling of CN in soil. Implementing the decomposition module into tRIBS makes the model a powerful complement to a biogeochemical observation system and a forecast tool able to analyze the influences of future changes on ecosystem services. The soil hydrologic parameters of the model were obtained using ranges of published parameters and observed streamflow data at the outlet. The parameters of the decomposition module are based on previously published data from studies conducted in the Luquillio CZO (budgets of soil organic matter and CN ratio for each of the dominant vegetation types across the landscape). Hydrological fluxes, wet depositon of nitrogen, litter fall and its corresponding CN ratio drive the decomposition model. The simulation results demonstrate a strong influence of soil moisture dynamics on the spatiotemporal distribution of nutrients at the landscape level. The carbon in the litter pool and the nitrate and ammonia pool respond quickly to soil moisture content. Moreover, the CN ratios of the plant litter have significant influence in the dynamics of CN cycling.

Forecasting daily meteorological time series using ARIMA and regression models

NASA Astrophysics Data System (ADS)

Murat, Małgorzata; Malinowska, Iwona; Gos, Magdalena; Krzyszczak, Jaromir

2018-04-01

The daily air temperature and precipitation time series recorded between January 1, 1980 and December 31, 2010 in four European sites (Jokioinen, Dikopshof, Lleida and Lublin) from different climatic zones were modeled and forecasted. In our forecasting we used the methods of the Box-Jenkins and Holt- Winters seasonal auto regressive integrated moving-average, the autoregressive integrated moving-average with external regressors in the form of Fourier terms and the time series regression, including trend and seasonality components methodology with R software. It was demonstrated that obtained models are able to capture the dynamics of the time series data and to produce sensible forecasts.

Evaluation of Offline Models Used to Simulate Components of the Permafrost Carbon Feedback: Experience from the Permafrost Carbon Network Model Integration Group

NASA Astrophysics Data System (ADS)

McGuire, A. D.

2016-12-01

The Model Integration Group of the Permafrost Carbon Network (see http://www.permafrostcarbon.org/) has conducted studies to evaluate the sensitivity of offline terrestrial permafrost and carbon models to both historical and projected climate change. These studies indicate that there is a wide range of (1) initial states permafrost extend and carbon stocks simulated by these models and (2) responses of permafrost extent and carbon stocks to both historical and projected climate change. In this study, we synthesize what has been learned about the variability in initial states among models and the driving factors that contribute to variability in the sensitivity of responses. We conclude the talk with a discussion of efforts needed by (1) the modeling community to standardize structural representation of permafrost and carbon dynamics among models that are used to evaluate the permafrost carbon feedback and (2) the modeling and observational communities to jointly develop data sets and methodologies to more effectively benchmark models.

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.

Interactions of forest disturbance-recovery dynamics with a changing climate

NASA Astrophysics Data System (ADS)

Anderson-Teixeira, K. J.; Miller, A. D.; Tepley, A. J.; Bennett, A. C.; Wang, M.

2015-12-01

As the climate changes, altered disturbance-recovery dynamics in forests worldwide are likely to result in significant biogeochemical and biophysical feedbacks to the climate system. Climate shapes forest disturbance events including tree mortality and fire, with consequent climate feedbacks. For instance, in forests globally, drought increases tree mortality rates, having a stronger impact on larger trees and resulting in greater feedbacks to climate change than would occur if drought sensitivities were equal across tree size classes. Forest regeneration and associated biogeochemical and biophysical feedbacks are also shaped by climate: across the tropics the rate of biomass accumulation is faster in everwet than in seasonally dry climates, and in the Klamath region (N California / S Oregon), post-fire vegetation dynamics and microclimate are shaped by aridity. Forest recovery dynamics will be affected by elevated CO2 and climate change; for instance, models predict that forest regeneration rate, successional dynamics, and climate feedbacks will all be altered under elevated CO2. In combination, climatic impacts on disturbance and recovery can result in dramatic shifts in forest cover on the landscape level. For instance, in fire-prone forested landscapes, forest cover decreases with increasing frequency of high-severity fire and decreasing forest recovery rate, both of which could be altered by climate change, producing rapid loss of forest on the landscape level. Such effects may be amplified by the existence of alternative stable states, which can cause systems to experience non-reversible changes in cover type. Critical transitions in landscape-level forest cover would have significant biogeochemical and biophysical feedbacks. Thus, altered disturbance-recovery dynamics under a changing climate may have sudden and dramatic impacts on forest-climate interactions.

Forecasting wildlife response to rapid warming in the Alaskan Arctic

USGS Publications Warehouse

Van Hemert, Caroline R.; Flint, Paul L.; Udevitz, Mark S.; Koch, Joshua C.; Atwood, Todd C.; Oakley, Karen L.; Pearce, John M.

2015-01-01

Arctic wildlife species face a dynamic and increasingly novel environment because of climate warming and the associated increase in human activity. Both marine and terrestrial environments are undergoing rapid environmental shifts, including loss of sea ice, permafrost degradation, and altered biogeochemical fluxes. Forecasting wildlife responses to climate change can facilitate proactive decisions that balance stewardship with resource development. In this article, we discuss the primary and secondary responses to physical climate-related drivers in the Arctic, associated wildlife responses, and additional sources of complexity in forecasting wildlife population outcomes. Although the effects of warming on wildlife populations are becoming increasingly well documented in the scientific literature, clear mechanistic links are often difficult to establish. An integrated science approach and robust modeling tools are necessary to make predictions and determine resiliency to change. We provide a conceptual framework and introduce examples relevant for developing wildlife forecasts useful to management decisions.

Santa Ana Winds of Southern California: Their climatology, extremes, and behavior spanning six and a half decades

NASA Astrophysics Data System (ADS)

Guzman-Morales, Janin; Gershunov, Alexander; Theiss, Jurgen; Li, Haiqin; Cayan, Daniel

2016-03-01

Santa Ana Winds (SAWs) are an integral feature of the regional climate of Southern California/Northern Baja California region, but their climate-scale behavior is poorly understood. In the present work, we identify SAWs in mesoscale dynamical downscaling of a global reanalysis from 1948 to 2012. Model winds are validated with anemometer observations. SAWs exhibit an organized pattern with strongest easterly winds on westward facing downwind slopes and muted magnitudes at sea and over desert lowlands. We construct hourly local and regional SAW indices and analyze elements of their behavior on daily, annual, and multidecadal timescales. SAWs occurrences peak in winter, but some of the strongest winds have occurred in fall. Finally, we observe that SAW intensity is influenced by prominent large-scale low-frequency modes of climate variability rooted in the tropical and north Pacific ocean-atmosphere system.

Reference aquaplanet climate in the Community Atmosphere Model, Version 5

DOE PAGES

Medeiros, Brian; Williamson, David L.; Olson, Jerry G.

2016-03-18

In this study, fundamental characteristics of the aquaplanet climate simulated by the Community Atmosphere Model, Version 5.3 (CAM5.3) are presented. The assumptions and simplifications of the configuration are described. A 16 year long, perpetual equinox integration with prescribed SST using the model’s standard 18 grid spacing is presented as a reference simulation. Statistical analysis is presented that shows similar aquaplanet configurations can be run for about 2 years to obtain robust climatological structures, including global and zonal means, eddy statistics, and precipitation distributions. Such a simulation can be compared to the reference simulation to discern differences in the climate, includingmore » an assessment of confidence in the differences. To aid such comparisons, the reference simulation has been made available via earthsystemgrid.org. Examples are shown comparing the reference simulation with simulations from the CAM5 series that make different microphysical assumptions and use a different dynamical core.« less

Technical Report Series on Global Modeling and Data Assimilation. Volume 20; The Climate of the FVCCM-3 Model

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); Chang, Yehui; Schubert, Siegfried D.; Lin, Shian-Jiann; Nebuda, Sharon; Shen, Bo-Wen

2001-01-01

This document describes the climate of version 1 of the NASA-NCAR model developed at the Data Assimilation Office (DAO). The model consists of a new finite-volume dynamical core and an implementation of the NCAR climate community model (CCM-3) physical parameterizations. The version of the model examined here was integrated at a resolution of 2 degrees latitude by 2.5 degrees longitude and 32 levels. The results are based on assimilation that was forced with observed sea surface temperature and sea ice for the period 1979-1995, and are compared with NCEP/NCAR reanalyses and various other observational data sets. The results include an assessment of seasonal means, subseasonal transients including the Madden Julian Oscillation, and interannual variability. The quantities include zonal and meridional winds, temperature, specific humidity, geopotential height, stream function, velocity potential, precipitation, sea level pressure, and cloud radiative forcing.

Modeling the role of environmental variables on the population dynamics of the malaria vector Anopheles gambiae sensu stricto

PubMed Central

2012-01-01

Background The impact of weather and climate on malaria transmission has attracted considerable attention in recent years, yet uncertainties around future disease trends under climate change remain. Mathematical models provide powerful tools for addressing such questions and understanding the implications for interventions and eradication strategies, but these require realistic modeling of the vector population dynamics and its response to environmental variables. Methods Published and unpublished field and experimental data are used to develop new formulations for modeling the relationships between key aspects of vector ecology and environmental variables. These relationships are integrated within a validated deterministic model of Anopheles gambiae s.s. population dynamics to provide a valuable tool for understanding vector response to biotic and abiotic variables. Results A novel, parsimonious framework for assessing the effects of rainfall, cloudiness, wind speed, desiccation, temperature, relative humidity and density-dependence on vector abundance is developed, allowing ease of construction, analysis, and integration into malaria transmission models. Model validation shows good agreement with longitudinal vector abundance data from Tanzania, suggesting that recent malaria reductions in certain areas of Africa could be due to changing environmental conditions affecting vector populations. Conclusions Mathematical models provide a powerful, explanatory means of understanding the role of environmental variables on mosquito populations and hence for predicting future malaria transmission under global change. The framework developed provides a valuable advance in this respect, but also highlights key research gaps that need to be resolved if we are to better understand future malaria risk in vulnerable communities. PMID:22877154

Regional Approach for Managing for Resilience Linking Ecosystem Services and Livelihood Strategies for Agro-Pastoral Communities in the Mongolian Steppe Ecosystem

NASA Astrophysics Data System (ADS)

Ojima, D. S.; Togtohyn, C.; Qi, J.; Galvin, K.

2011-12-01

Dramatic changes due to climate and land use dynamics in the Mongolian Plateau are affecting ecosystem services and agro-pastoral livelihoods in Mongolia and China. Recently, evaluation of pastoral systems, where humans depend on livestock and grassland ecosystem services, have demonstrated the vulnerability of the social-ecological system to climate change. Current social-ecological changes in ecosystem services are affecting land productivity and carrying capacity, land-atmosphere interactions, water resources, and livelihood strategies. Regional dust events, changes in hydrological cycle, and land use changes contribute to changing interactions between ecosystem and landscape processes which then affect social-ecological systems. The general trend involves greater intensification of resource exploitation at the expense of traditional patterns of extensive range utilization. Thus we expect climate-land use-land cover relationships to be crucially modified by the socio-economic forces. The analysis incorporates information of the socio-economic transitions taking place in the region which affect land-use, food security, and ecosystem dynamics. The region of study extends from the Mongolian plateau in Mongolia and China to the fertile northeast China plain. Sustainability of agro-pastoral systems in the region needs to integrate the impact of climate change on ecosystem services with socio-economic changes shaping the livelihood strategies of pastoral systems in the region. Adaptation strategies which incorporate landscape management provides a potential framework to link ecosystem services across space and time more effectively to meet the needs of agro-pastoral land use, herd quality, and herder's living standards. Under appropriate adaptation strategies agro-pastoralists will have the opportunity to utilize seasonal resources and enhance their ability to process and manufacture products from the available ecosystem services in these dynamic social-ecological systems.

Dynamical variability in the modelling of chemistry-climate interactions.

PubMed

Pyle, J A; Braesicke, P; Zeng, G

2005-01-01

We have used a version of the Met Office's climate model, into which we have introduced schemes for atmospheric chemistry, to study chemistry-dynamics-climate interactions. We have considered the variability of the stratospheric polar vortex, whose behaviour influences stratospheric ozone loss and will affect ozone recovery. In particular, we analyse the dynamical control of high latitude ozone in a model version which includes an assimilation of the equatorial quasi-biennial oscillation (QBO), demonstrating the stability of the linear relation between vortex strength and high latitude ozone. We discuss the effect of interactive model ozone on polar stratospheric cloud (PSC) area/volume and winter-spring stratospheric ozone loss in the northern hemisphere. In general we find larger polar ozone losses calculated in those model integrations in which modelled ozone is used interactively in the radiation scheme, even though we underestimate the slope of the ozone loss per PSC volume relation derived from observations. We have also looked at the influence of changing stratosphere-to-troposphere exchange on the tropospheric oxidizing capacity and, in particular, have considered the variability of tropospheric composition under different climate regimes (El Niño/La Niña, etc.). Focusing on the UT/LS, we show the response of ozone to El Niño in two different model set-ups (tropospheric/ stratospheric). In the stratospheric model set-up we find a distinct signal in the lower tropical stratosphere, which shows an anti-correlation between the Niño 3 index and the ozone column amount. In contrast ozone generally increases in the upper troposphere of the tropospheric model set-up after an El Niño. Understanding future trends in stratospheric ozone and tropospheric oxidizing capacity requires an understanding of natural variability, which we explore here.

Toward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity.

PubMed

Bustamante, Mercedes M C; Roitman, Iris; Aide, T Mitchell; Alencar, Ane; Anderson, Liana O; Aragão, Luiz; Asner, Gregory P; Barlow, Jos; Berenguer, Erika; Chambers, Jeffrey; Costa, Marcos H; Fanin, Thierry; Ferreira, Laerte G; Ferreira, Joice; Keller, Michael; Magnusson, William E; Morales-Barquero, Lucia; Morton, Douglas; Ometto, Jean P H B; Palace, Michael; Peres, Carlos A; Silvério, Divino; Trumbore, Susan; Vieira, Ima C G

2016-01-01

Tropical forests harbor a significant portion of global biodiversity and are a critical component of the climate system. Reducing deforestation and forest degradation contributes to global climate-change mitigation efforts, yet emissions and removals from forest dynamics are still poorly quantified. We reviewed the main challenges to estimate changes in carbon stocks and biodiversity due to degradation and recovery of tropical forests, focusing on three main areas: (1) the combination of field surveys and remote sensing; (2) evaluation of biodiversity and carbon values under a unified strategy; and (3) research efforts needed to understand and quantify forest degradation and recovery. The improvement of models and estimates of changes of forest carbon can foster process-oriented monitoring of forest dynamics, including different variables and using spatially explicit algorithms that account for regional and local differences, such as variation in climate, soil, nutrient content, topography, biodiversity, disturbance history, recovery pathways, and socioeconomic factors. Generating the data for these models requires affordable large-scale remote-sensing tools associated with a robust network of field plots that can generate spatially explicit information on a range of variables through time. By combining ecosystem models, multiscale remote sensing, and networks of field plots, we will be able to evaluate forest degradation and recovery and their interactions with biodiversity and carbon cycling. Improving monitoring strategies will allow a better understanding of the role of forest dynamics in climate-change mitigation, adaptation, and carbon cycle feedbacks, thereby reducing uncertainties in models of the key processes in the carbon cycle, including their impacts on biodiversity, which are fundamental to support forest governance policies, such as Reducing Emissions from Deforestation and Forest Degradation. © 2015 John Wiley & Sons Ltd.

Interactions Between Mineral Surfaces, Substrates, Enzymes, and Microbes Result in Hysteretic Temperature Sensitivities and Microbial Carbon Use Efficiencies and Weaker Predicted Carbon-Climate Feedbacks

NASA Astrophysics Data System (ADS)

Riley, W. J.; Tang, J.

2014-12-01

We hypothesize that the large observed variability in decomposition temperature sensitivity and carbon use efficiency arises from interactions between temperature, microbial biogeochemistry, and mineral surface sorptive reactions. To test this hypothesis, we developed a numerical model that integrates the Dynamic Energy Budget concept for microbial physiology, microbial trait-based community structure and competition, process-specific thermodynamically ­­based temperature sensitivity, a non-linear mineral sorption isotherm, and enzyme dynamics. We show, because mineral surfaces interact with substrates, enzymes, and microbes, both temperature sensitivity and microbial carbon use efficiency are hysteretic and highly variable. Further, by mimicking the traditional approach to interpreting soil incubation observations, we demonstrate that the conventional labile and recalcitrant substrate characterization for temperature sensitivity is flawed. In a 4 K temperature perturbation experiment, our fully dynamic model predicted more variable but weaker carbon-climate feedbacks than did the static temperature sensitivity and carbon use efficiency model when forced with yearly, daily, and hourly variable temperatures. These results imply that current earth system models likely over-estimate the response of soil carbon stocks to global warming.

Soil mapping and processes models to support climate change mitigation and adaptation strategies: a review

NASA Astrophysics Data System (ADS)

Muñoz-Rojas, Miriam; Pereira, Paulo; Brevik, Eric; Cerda, Artemi; Jordan, Antonio

2017-04-01

As agreed in Paris in December 2015, global average temperature is to be limited to "well below 2 °C above pre-industrial levels" and efforts will be made to "limit the temperature increase to 1.5 °C above pre-industrial levels. Thus, reducing greenhouse gas emissions (GHG) in all sectors becomes critical and appropriate sustainable land management practices need to be taken (Pereira et al., 2017). Mitigation strategies focus on reducing the rate and magnitude of climate change by reducing its causes. Complementary to mitigation, adaptation strategies aim to minimise impacts and maximize the benefits of new opportunities. The adoption of both practices will require developing system models to integrate and extrapolate anticipated climate changes such as global climate models (GCMs) and regional climate models (RCMs). Furthermore, integrating climate models driven by socio-economic scenarios in soil process models has allowed the investigation of potential changes and threats in soil characteristics and functions in future climate scenarios. One of the options with largest potential for climate change mitigation is sequestering carbon in soils. Therefore, the development of new methods and the use of existing tools for soil carbon monitoring and accounting have therefore become critical in a global change context. For example, soil C maps can help identify potential areas where management practices that promote C sequestration will be productive and guide the formulation of policies for climate change mitigation and adaptation strategies. Despite extensive efforts to compile soil information and map soil C, many uncertainties remain in the determination of soil C stocks, and the reliability of these estimates depends upon the quality and resolution of the spatial datasets used for its calculation. Thus, better estimates of soil C pools and dynamics are needed to advance understanding of the C balance and the potential of soils for climate change mitigation. Here, we discuss the most recent advances on the application of soil mapping and modeling to support climate change mitigation and adaptation strategies; and These strategies are a key component of the implementation of sustainable land management policies need to be integrated are critical to. The objective of this work is to present a review about the advantages of soil mapping and process modeling for sustainable land management. Muñoz-Rojas, M., Pereira, P., Brevic, E., Cerda, A., Jordan, A. (2017) Soil mapping and processes models for sustainable land management applied to modern challenges. In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B. (Eds.) Soil mapping and process modelling for sustainable land use management (Elsevier Publishing House) ISBN: 9780128052006

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.

Mesoscale Climate Evaluation Using Grid Computing

NASA Astrophysics Data System (ADS)

Campos Velho, H. F.; Freitas, S. R.; Souto, R. P.; Charao, A. S.; Ferraz, S.; Roberti, D. R.; Streck, N.; Navaux, P. O.; Maillard, N.; Collischonn, W.; Diniz, G.; Radin, B.

2012-04-01

The CLIMARS project is focused to establish an operational environment for seasonal climate prediction for the Rio Grande do Sul state, Brazil. The dynamical downscaling will be performed with the use of several software platforms and hardware infrastructure to carry out the investigation on mesoscale of the global change impact. The grid computing takes advantage of geographically spread out computer systems, connected by the internet, for enhancing the power of computation. The ensemble climate prediction is an appropriated application for processing on grid computing, because the integration of each ensemble member does not have a dependency on information from another ensemble members. The grid processing is employed to compute the 20-year climatology and the long range simulations under ensemble methodology. BRAMS (Brazilian Regional Atmospheric Model) is a mesoscale model developed from a version of the RAMS (from the Colorado State University - CSU, USA). BRAMS model is the tool for carrying out the dynamical downscaling from the IPCC scenarios. Long range BRAMS simulations will provide data for some climate (data) analysis, and supply data for numerical integration of different models: (a) Regime of the extreme events for temperature and precipitation fields: statistical analysis will be applied on the BRAMS data, (b) CCATT-BRAMS (Coupled Chemistry Aerosol Tracer Transport - BRAMS) is an environmental prediction system that will be used to evaluate if the new standards of temperature, rain regime, and wind field have a significant impact on the pollutant dispersion in the analyzed regions, (c) MGB-IPH (Portuguese acronym for the Large Basin Model (MGB), developed by the Hydraulic Research Institute, (IPH) from the Federal University of Rio Grande do Sul (UFRGS), Brazil) will be employed to simulate the alteration of the river flux under new climate patterns. Important meteorological input variables for the MGB-IPH are the precipitation (most relevant), temperature, and wind field, all provided by BRAMS. The Uruguay river basin will be analyzed in the scope of this proposal, (d) INFOCROP: this crop model has been calibrated for Southern Brazil, three agriculture cropswill be analyzed: rice, soybean and corn.

Accounting for Landscape Heterogeneity Improves Spatial Predictions of Tree Vulnerability to Drought

NASA Astrophysics Data System (ADS)

Schwantes, A. M.; Parolari, A.; Swenson, J. J.; Johnson, D. M.; Domec, J. C.; Jackson, R. B.; Pelak, N. F., III; Porporato, A. M.

2017-12-01

Globally, as climate change continues, forest vulnerability to droughts and heatwaves is increasing, but vulnerability differs regionally and locally depending on landscape position. However, most models used in forecasting forest responses to heatwaves and droughts do not incorporate relevant spatial processes. To improve predictions of spatial tree vulnerability, we employed a non-linear stochastic model of soil moisture dynamics across a landscape, accounting for spatial differences in aspect, topography, and soils. Our unique approach integrated plant hydraulics and landscape processes, incorporating effects from lateral redistribution of water using a topographic index and radiation and temperature differences attributable to aspect. Across a watershed in central Texas we modeled dynamic water stress for a dominant tree species, Juniperus ashei. We compared our results to a detailed spatial dataset of drought-impacted areas (>25% canopy loss) derived from remote sensing during the severe 2011 drought. We then projected future dynamic water stress through the 21st century using climate projections from 10 global climate models under two scenarios, and compared models with and without landscape heterogeneity. Within this watershed, 42% of J. ashei dominated systems were impacted by the 2011 drought. Modeled dynamic water stress tracked these spatial patterns of observed drought-impacted areas. Total accuracy increased from 59%, when accounting only for soil variability, to 73% when including lateral redistribution of water and radiation and temperature effects. Dynamic water stress was projected to increase through the 21st century, with only minimal buffering from the landscape. During the hotter and more severe droughts projected in the 21st century, up to 90% of the watershed crossed a dynamic water stress threshold associated with canopy loss in 2011. Favorable microsites may exist across a landscape where trees can persist; however, if future droughts are too severe, the buffering capacity of a heterogenous landscape could be overwhelmed. Incorporating spatial data will improve projections of future tree water stress and identification of potential resilient refugia.

Vulnerability of Forests in India: A National Scale Assessment.

PubMed

Sharma, Jagmohan; Upgupta, Sujata; Jayaraman, Mathangi; Chaturvedi, Rajiv Kumar; Bala, Govindswamy; Ravindranath, N H

2017-09-01

Forests are subjected to stress from climatic and non-climatic sources. In this study, we have reported the results of inherent, as well as climate change driven vulnerability assessments for Indian forests. To assess inherent vulnerability of forests under current climate, we have used four indicators, namely biological richness, disturbance index, canopy cover, and slope. The assessment is presented as spatial profile of inherent vulnerability in low, medium, high and very high vulnerability classes. Fourty percent forest grid points in India show high or very high inherent vulnerability. Plantation forests show higher inherent vulnerability than natural forests. We assess the climate change driven vulnerability by combining the results of inherent vulnerability assessment with the climate change impact projections simulated by the Integrated Biosphere Simulator dynamic global vegetation model. While 46% forest grid points show high, very high, or extremely high vulnerability under future climate in the short term (2030s) under both representative concentration pathways 4.5 and 8.5, such grid points are 49 and 54%, respectively, in the long term (2080s). Generally, forests in the higher rainfall zones show lower vulnerability as compared to drier forests under future climate. Minimizing anthropogenic disturbance and conserving biodiversity can potentially reduce forest vulnerability under climate change. For disturbed forests and plantations, adaptive management aimed at forest restoration is necessary to build long-term resilience.

Vulnerability of Forests in India: A National Scale Assessment

NASA Astrophysics Data System (ADS)

Sharma, Jagmohan; Upgupta, Sujata; Jayaraman, Mathangi; Chaturvedi, Rajiv Kumar; Bala, Govindswamy; Ravindranath, N. H.

2017-09-01

Forests are subjected to stress from climatic and non-climatic sources. In this study, we have reported the results of inherent, as well as climate change driven vulnerability assessments for Indian forests. To assess inherent vulnerability of forests under current climate, we have used four indicators, namely biological richness, disturbance index, canopy cover, and slope. The assessment is presented as spatial profile of inherent vulnerability in low, medium, high and very high vulnerability classes. Fourty percent forest grid points in India show high or very high inherent vulnerability. Plantation forests show higher inherent vulnerability than natural forests. We assess the climate change driven vulnerability by combining the results of inherent vulnerability assessment with the climate change impact projections simulated by the Integrated Biosphere Simulator dynamic global vegetation model. While 46% forest grid points show high, very high, or extremely high vulnerability under future climate in the short term (2030s) under both representative concentration pathways 4.5 and 8.5, such grid points are 49 and 54%, respectively, in the long term (2080s). Generally, forests in the higher rainfall zones show lower vulnerability as compared to drier forests under future climate. Minimizing anthropogenic disturbance and conserving biodiversity can potentially reduce forest vulnerability under climate change. For disturbed forests and plantations, adaptive management aimed at forest restoration is necessary to build long-term resilience.

Somatic growth dynamics of West Atlantic hawksbill sea turtles: a spatio-temporal perspective

USGS Publications Warehouse

Bjorndal, Karen A.; Chaloupka, Milani; Saba, Vincent S.; Diez, Carlos E.; van Dam, Robert P.; Krueger, Barry H.; Horrocks, Julia A.; Santos, Armando J.B.; Bellini, Cláudio; Marcovaldi, Maria A.G.; Nava, Mabel; Willis, Sue; Godley, Brendan J.; Gore, Shannon; Hawkes, Lucy A.; McGowan, Andrew; Witt, Matthew J.; Stringell, Thomas B.; Sanghera, Amdeep; Richardson, Peter B.; Broderick, Annette C.; Phillips, Quinton; Calosso, Marta C.; Claydon, John A.B.; Blumenthal, Janice; Moncada, Felix; Nodarse, Gonzalo; Medina, Yosvani; Dunbar, Stephen G.; Wood, Lawrence D.; Lagueux, Cynthia J.; Campbell, Cathi L.; Meylan, Anne B.; Meylan, Peter A.; Burns Perez, Virginia R.; Coleman, Robin A.; Strindberg, Samantha; Guzmán-H, Vicente; Hart, Kristen M.; Cherkiss, Michael S.; Hillis-Starr, Zandy; Lundgren, Ian; Boulon, Ralf H.; Connett, Stephen; Outerbridge, Mark E.; Bolten, Alan B.

2016-01-01

Somatic growth dynamics are an integrated response to environmental conditions. Hawksbill sea turtles (Eretmochelys imbricata) are long-lived, major consumers in coral reef habitats that move over broad geographic areas (hundreds to thousands of kilometers). We evaluated spatio-temporal effects on hawksbill growth dynamics over a 33-yr period and 24 study sites throughout the West Atlantic and explored relationships between growth dynamics and climate indices. We compiled the largest ever data set on somatic growth rates for hawksbills – 3541 growth increments from 1980 to 2013. Using generalized additive mixed model analyses, we evaluated 10 covariates, including spatial and temporal variation, that could affect growth rates. Growth rates throughout the region responded similarly over space and time. The lack of a spatial effect or spatio-temporal interaction and the very strong temporal effect reveal that growth rates in West Atlantic hawksbills are likely driven by region-wide forces. Between 1997 and 2013, mean growth rates declined significantly and steadily by 18%. Regional climate indices have significant relationships with annual growth rates with 0- or 1-yr lags: positive with the Multivariate El Niño Southern Oscillation Index (correlation = 0.99) and negative with Caribbean sea surface temperature (correlation = −0.85). Declines in growth rates between 1997 and 2013 throughout the West Atlantic most likely resulted from warming waters through indirect negative effects on foraging resources of hawksbills. These climatic influences are complex. With increasing temperatures, trajectories of decline of coral cover and availability in reef habitats of major prey species of hawksbills are not parallel. Knowledge of how choice of foraging habitats, prey selection, and prey abundance are affected by warming water temperatures is needed to understand how climate change will affect productivity of consumers that live in association with coral reefs. Main conclusions The decadal declines in growth rates between 1997 and 2013 throughout the West Atlantic most likely resulted from warming waters through indirect negative effects on the foraging resources of hawksbills. These climatic influences are complex. With increasing temperatures, the trajectories of decline of coral cover and availability in reef habitats of major prey species of hawksbills are not parallel. Knowledge of how choice of foraging habitats, prey selection, and prey abundance are affected by warming water temperatures is needed to understand how climate change will affect productivity of consumers that live in association with coral reefs.

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.

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

Fort Collins Science Center Ecosystem Dynamics Branch

USGS Publications Warehouse

Wilson, Jim; Melcher, C.; Bowen, Z.

2009-01-01

Complex natural resource issues require understanding a web of interactions among ecosystem components that are (1) interdisciplinary, encompassing physical, chemical, and biological processes; (2) spatially complex, involving movements of animals, water, and airborne materials across a range of landscapes and jurisdictions; and (3) temporally complex, occurring over days, weeks, or years, sometimes involving response lags to alteration or exhibiting large natural variation. Scientists in the Ecosystem Dynamics Branch of the U.S. Geological Survey, Fort Collins Science Center, investigate a diversity of these complex natural resource questions at the landscape and systems levels. This Fact Sheet describes the work of the Ecosystems Dynamics Branch, which is focused on energy and land use, climate change and long-term integrated assessments, herbivore-ecosystem interactions, fire and post-fire restoration, and environmental flows and river restoration.

Choice of baseline climate data impacts projected species' responses to climate change.

PubMed

Baker, David J; Hartley, Andrew J; Butchart, Stuart H M; Willis, Stephen G

2016-07-01

Climate data created from historic climate observations are integral to most assessments of potential climate change impacts, and frequently comprise the baseline period used to infer species-climate relationships. They are often also central to downscaling coarse resolution climate simulations from General Circulation Models (GCMs) to project future climate scenarios at ecologically relevant spatial scales. Uncertainty in these baseline data can be large, particularly where weather observations are sparse and climate dynamics are complex (e.g. over mountainous or coastal regions). Yet, importantly, this uncertainty is almost universally overlooked when assessing potential responses of species to climate change. Here, we assessed the importance of historic baseline climate uncertainty for projections of species' responses to future climate change. We built species distribution models (SDMs) for 895 African bird species of conservation concern, using six different climate baselines. We projected these models to two future periods (2040-2069, 2070-2099), using downscaled climate projections, and calculated species turnover and changes in species-specific climate suitability. We found that the choice of baseline climate data constituted an important source of uncertainty in projections of both species turnover and species-specific climate suitability, often comparable with, or more important than, uncertainty arising from the choice of GCM. Importantly, the relative contribution of these factors to projection uncertainty varied spatially. Moreover, when projecting SDMs to sites of biodiversity importance (Important Bird and Biodiversity Areas), these uncertainties altered site-level impacts, which could affect conservation prioritization. Our results highlight that projections of species' responses to climate change are sensitive to uncertainty in the baseline climatology. We recommend that this should be considered routinely in such analyses. © 2016 John Wiley & Sons Ltd.

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.

Tracing society in climate change: Societal negotiations and physical dynamics of water under climate change conditions in the Cordillera Blanca region, Peru

NASA Astrophysics Data System (ADS)

Neuburger, Martina; Gurgiser, Wolfgang; Maussion, Fabien; Singer, Katrin; Kaser, Georg

2017-04-01

Natural scientists observe and project changes in precipitation and temperature at different spatio-temporal scales and investigate impacts on glaciers and hydrological regimes. Simultaneously, social groups experience ecological phenomena as linked to climate change and integrate them into their understanding of nature and their logics of action, while political actors refer to scientific results as legitimization to focus on adaptation and mitigation strategies on global, national and regional/local level. However, natural and socio-political changes on various scales (regarding time and space) are not directly interlinked, but are communicated by energy and material flows, by discourses, power relations and institutional regulations. In this context, it remains still unclear how natural dynamics are (dis)entangled with societal processes in their historical dimensions and in their interrelations from global via national to regional and local scales. Considering the Cordillera Blanca region in Peru as an example, we analyze the intertwining of scales (global, national, regional, local) and spheres (natural, political, societal) to detect entanglements and disconnections of observed processes. Using the methodology of a time line, we present precipitation variability and glacier recession at different scales, estimate qualitative water availability and investigate the links to the implementation of international and national political programs on climate change adaptation in the Cordillera Blanca region focusing on water and agrarian programs. Finally, we include supposedly contradictory reports of rural population on climate change and related impacts on water availability and agricultural production to analyze the (dis)entanglement due to changing power relations and dominant discourses.

Modelling Holocene peatland and permafrost dynamics with the LPJ-GUESS dynamic vegetation model

NASA Astrophysics Data System (ADS)

Chaudhary, Nitin; Miller, Paul A.; Smith, Benjamin

2016-04-01

Dynamic global vegetation models (DGVMs) are an important platform to study past, present and future vegetation patterns together with associated biogeochemical cycles and climate feedbacks (e.g. Sitch et al. 2008, Smith et al. 2001). However, very few attempts have been made to simulate peatlands using DGVMs (Kleinen et al. 2012, Tang et al. 2015, Wania et al. 2009a). In the present study, we have improved the peatland dynamics in the state-of-the-art dynamic vegetation model (LPJ-GUESS) in order to understand the long-term evolution of northern peatland ecosystems and to assess the effect of changing climate on peatland carbon balance. We combined a dynamic multi-layer approach (Frolking et al. 2010, Hilbert et al. 2000) with soil freezing-thawing functionality (Ekici et al. 2015, Wania et al. 2009a) in LPJ-GUESS. The new model is named LPJ-GUESS Peatland (LPJ-GUESS-P) (Chaudhary et al. in prep). The model was calibrated and tested at the sub-arctic mire in Stordalen, Sweden, and the model was able to capture the reported long-term vegetation dynamics and peat accumulation patterns in the mire (Kokfelt et al. 2010). For evaluation, the model was run at 13 grid points across a north to south transect in Europe. The modelled peat accumulation values were found to be consistent with the published data for each grid point (Loisel et al. 2014). Finally, a series of additional experiments were carried out to investigate the vulnerability of high-latitude peatlands to climate change. We find that the Stordalen mire will sequester more carbon in the future due to milder and wetter climate conditions, longer growing seasons, and the carbon fertilization effect. References: - Chaudhary et al. (in prep.). Modelling Holocene peatland and permafrost dynamics with the LPJ-GUESS dynamic vegetation model - Ekici A, et al. 2015. Site-level model intercomparison of high latitude and high altitude soil thermal dynamics in tundra and barren landscapes. The Cryosphere 9: 1343-1361. - Frolking S, Roulet NT, Tuittila E, Bubier JL, Quillet A, Talbot J, Richard PJH. 2010. A new model of Holocene peatland net primary production, decomposition, water balance, and peat accumulation. Earth Syst. Dynam., 1, 1-21, doi:10.5194/esd-1-1-2010, 2010. - Hilbert DW, Roulet N, Moore T. 2000. Modelling and analysis of peatlands as dynamical systems. Journal of Ecology 88: 230-242. - Kleinen T, Brovkin V, Schuldt RJ. 2012. A dynamic model of wetland extent and peat accumulation: results for the Holocene. Biogeosciences 9: 235-248. - Kokfelt U, Reuss N, Struyf E, Sonesson M, Rundgren M, Skog G, Rosen P, Hammarlund D. 2010. Wetland development, permafrost history and nutrient cycling inferred from late Holocene peat and lake sediment records in subarctic Sweden. Journal of Paleolimnology 44: 327-342. - Loisel J, et al. 2014. A database and synthesis of northern peatland soil properties and Holocene carbon and nitrogen accumulation. Holocene 24: 1028-1042. - Sitch S, et al. 2008. Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs). Global Change Biology 14: 2015-2039. - Smith B, Prentice IC, Sykes MT. 2001. Representation of vegetation dynamics in the modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space. Global Ecology and Biogeography 10: 621-637. - Tang J, et al. 2015. Carbon budget estimation of a subarctic catchment using a dynamic ecosystem model at high spatial resolution. Biogeosciences 12: 2791-2808. - Wania R, Ross I, Prentice IC. 2009a. Integrating peatlands and permafrost into a dynamic global vegetation model: 1. Evaluation and sensitivity of physical land surface processes. Global Biogeochemical Cycles 23.

High-resolution integration of water, energy, and climate models to assess electricity grid vulnerabilities to climate change

NASA Astrophysics Data System (ADS)

Meng, M.; Macknick, J.; Tidwell, V. C.; Zagona, E. A.; Magee, T. M.; Bennett, K.; Middleton, R. S.

2017-12-01

The U.S. electricity sector depends on large amounts of water for hydropower generation and cooling thermoelectric power plants. Variability in water quantity and temperature due to climate change could reduce the performance and reliability of individual power plants and of the electric grid as a system. While studies have modeled water usage in power systems planning, few have linked grid operations with physical water constraints or with climate-induced changes in water resources to capture the role of the energy-water nexus in power systems flexibility and adequacy. In addition, many hydrologic and hydropower models have a limited representation of power sector water demands and grid interaction opportunities of demand response and ancillary services. A multi-model framework was developed to integrate and harmonize electricity, water, and climate models, allowing for high-resolution simulation of the spatial, temporal, and physical dynamics of these interacting systems. The San Juan River basin in the Southwestern U.S., which contains thermoelectric power plants, hydropower facilities, and multiple non-energy water demands, was chosen as a case study. Downscaled data from three global climate models and predicted regional water demand changes were implemented in the simulations. The Variable Infiltration Capacity hydrologic model was used to project inflows, ambient air temperature, and humidity in the San Juan River Basin. Resulting river operations, water deliveries, water shortage sharing agreements, new water demands, and hydroelectricity generation at the basin-scale were estimated with RiverWare. The impacts of water availability and temperature on electric grid dispatch, curtailment, cooling water usage, and electricity generation cost were modeled in PLEXOS. Lack of water availability resulting from climate, new water demands, and shortage sharing agreements will require thermoelectric generators to drastically decrease power production, as much as 50% during intensifying drought scenarios, which can have broader electricity sector system implications. Results relevant to stakeholder and power provider interests highlight the vulnerabilities in grid operations driven by water shortage agreements and changes in the climate.

Adaptive Regulation of the Northern California Reservoir System for Water, Energy, and Environmental Management

NASA Astrophysics Data System (ADS)

Georgakakos, A. P.; Kistenmacher, M.; Yao, H.; Georgakakos, K. P.

2014-12-01

The 2014 National Climate Assessment of the US Global Change Research Program emphasizes that water resources managers and planners in most US regions will have to cope with new risks, vulnerabilities, and opportunities, and recommends the development of adaptive capacity to effectively respond to the new water resources planning and management challenges. In the face of these challenges, adaptive reservoir regulation is becoming all the more ncessary. Water resources management in Northern California relies on the coordinated operation of several multi-objective reservoirs on the Trinity, Sacramento, American, Feather, and San Joaquin Rivers. To be effective, reservoir regulation must be able to (a) account for forecast uncertainty; (b) assess changing tradeoffs among water uses and regions; and (c) adjust management policies as conditions change; and (d) evaluate the socio-economic and environmental benefits and risks of forecasts and policies for each region and for the system as a whole. The Integrated Forecast and Reservoir Management (INFORM) prototype demonstration project operated in Northern California through the collaboration of several forecast and management agencies has shown that decision support systems (DSS) with these attributes add value to stakeholder decision processes compared to current, less flexible management practices. Key features of the INFORM DSS include: (a) dynamically downscaled operational forecasts and climate projections that maintain the spatio-temporal coherence of the downscaled land surface forcing fields within synoptic scales; (b) use of ensemble forecast methodologies for reservoir inflows; (c) assessment of relevant tradeoffs among water uses on regional and local scales; (d) development and evaluation of dynamic reservoir policies with explicit consideration of hydro-climatic forecast uncertainties; and (e) focus on stakeholder information needs.This article discusses the INFORM integrated design concept, underlying methodologies, and selected applications with the California water resources system.

Siberia Integrated Regional Study megaproject: approaches, first results and challenges

NASA Astrophysics Data System (ADS)

Gordov, E. P.; Vaganov, E. A.

2010-12-01

Siberia Integrated Regional Study (SIRS, http://sirs.scert.ru/en/) is a NEESPI megaproject coordinating national and international activity in the region in line with Earth System Science Program approach whose overall objectives are to understand impact of Global change on on-going regional climate and ecosystems dynamics; to study future potential changes in both, and to estimate possible influence of those processes on the whole Earth System dynamics. Needs for SIRS are caused by accelerated warming occurring in Siberia, complexity of on-going and potential land-surface processes sharpened by inherent hydrology pattern and permafrost presence, and lack of reliable high-resolution meteorological and climatic modeling data. The SIRS approaches include coordination of different scale national and international projects, capacity building targeted to early career researchers thematic education and training, and development of distributed information-computational infrastructure required in support of multidisciplinary teams of specialists performing cooperative work with tools for sharing of data, models and knowledge. Coordination within SIRS projects is devoted to major regional and global risks rising with regional environment changes and currently is concentrated on three interrelated problems, whose solution has strong regional environmental and socio-economical impacts and is very important for understanding potential change of the whole Earth System dynamics: Permafrost border shift, which seriously threatens the oil and gas transporting infrastructure and leads to additional carbon release; Desert - steppe- forest-tundra ecosystems changes, which might vary region input into global carbon cycle as well as provoke serious socio-economical consequences for local population; and Temperature/precipitation/hydrology regime changes, which might increase risks of forest and peat fires, thus causing significant carbon release from the region under study. Some findings of those projects will be presented in the report. The information-computational infrastructure is aimed to manage multidisciplinary environmental data and to generate high resolution data sets on demand. One of its key elements, optimizing the usage of information-computational resources, services and applications is the climatic web portal under development. The prototype (http://climate.risks.scert.ru/) is now providing an access to an interactive web- GIS system for climate change assessment on the base of available meteorological data archives in the selected region. SIRS education and training program is run via annual organization in the region either international multidisciplinary conference with elements of young scientists school ENVIROMIS or young scientists school and collocated international conference CITES (http://www.scert.ru/en/conferences/). All the listed above activities have an international dimension whose enlargement might significantly assist in profound understanding of regional and global consequences in on-going Siberia processes.

Dynamics of global vegetation biomass simulated by the integrated Earth System Model

NASA Astrophysics Data System (ADS)

Mao, J.; Shi, X.; Di Vittorio, A. V.; Thornton, P. E.; Piao, S.; Yang, X.; Truesdale, J. E.; Bond-Lamberty, B. P.; Chini, L. P.; Thomson, A. M.; Hurtt, G. C.; Collins, W.; Edmonds, J.

2014-12-01

The global vegetation biomass stores huge amounts of carbon and is thus important to the global carbon budget (Pan et al., 2010). For the past few decades, different observation-based estimates and modeling of biomass in the above- and below-ground vegetation compartments have been comprehensively conducted (Saatchi et al., 2011; Baccini et al., 2012). However, uncertainties still exist, in particular for the simulation of biomass magnitude, tendency, and the response of biomass to climatic conditions and natural and human disturbances. The recently successful coupling of the integrated Earth System Model (iESM) (Di Vittorio et al., 2014; Bond-Lamberty et al., 2014), which links the Global Change Assessment Model (GCAM), Global Land-use Model (GLM), and Community Earth System Model (CESM), offers a great opportunity to understand the biomass-related dynamics in a fully-coupled natural and human modeling system. In this study, we focus on the systematic analysis and evaluation of the iESM simulated historical (1850-2005) and future (2006-2100) biomass changes and the response of the biomass dynamics to various impact factors, in particular the human-induced Land Use/Land Cover Change (LULCC). By analyzing the iESM simulations with and without the interactive LULCC feedbacks, we further study how and where the climate feedbacks affect socioeconomic decisions and LULCC, such as to alter vegetation carbon storage. References Pan Y et. al: A large and persistent carbon sink in the World's forests. Science 2011, 333:988-993. Saatchi SS et al: Benchmark map of forest carbon stocks in tropical regions across three continents. Proc Natl Acad Sci 2011, 108:9899-9904. Baccini A et al: Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nature Clim Change 2012, 2:182-185. Di Vittorio AV et al: From land use to land cover: restoring the afforestation signal in a coupled integrated assessment-earth system model and the implications for CMIP5 RCP simulations. Biogeosciences Discuss 2014, 11:7151-7188. Bond-Lamberty, B et al: Coupling earth system and integrated assessment models: The problem of steady state. Geosci. Model Dev. Discuss 2014, 7: 1499-1524, doi:10.5194/gmdd-7-1499-2014.

Integrated Decision Support for Global Environmental Change Adaptation

NASA Astrophysics Data System (ADS)

Kumar, S.; Cantrell, S.; Higgins, G. J.; Marshall, J.; VanWijngaarden, F.

2011-12-01

Environmental changes are happening now that has caused concern in many parts of the world; particularly vulnerable are the countries and communities with limited resources and with natural environments that are more susceptible to climate change impacts. Global leaders are concerned about the observed phenomena and events such as Amazon deforestation, shifting monsoon patterns affecting agriculture in the mountain slopes of Peru, floods in Pakistan, water shortages in Middle East, droughts impacting water supplies and wildlife migration in Africa, and sea level rise impacts on low lying coastal communities in Bangladesh. These environmental changes are likely to get exacerbated as the temperatures rise, the weather and climate patterns change, and sea level rise continues. Large populations and billions of dollars of infrastructure could be affected. At Northrop Grumman, we have developed an integrated decision support framework for providing necessary information to stakeholders and planners to adapt to the impacts of climate variability and change at the regional and local levels. This integrated approach takes into account assimilation and exploitation of large and disparate weather and climate data sets, regional downscaling (dynamic and statistical), uncertainty quantification and reduction, and a synthesis of scientific data with demographic and economic data to generate actionable information for the stakeholders and decision makers. Utilizing a flexible service oriented architecture and state-of-the-art visualization techniques, this information can be delivered via tailored GIS portals to meet diverse set of user needs and expectations. This integrated approach can be applied to regional and local risk assessments, predictions and decadal projections, and proactive adaptation planning for vulnerable communities. In this paper we will describe this comprehensive decision support approach with selected applications and case studies to illustrate how this system of systems approach could help the local governments and concerned institutions worldwide to adapt to gradually changing environmental conditions as well as manage impacts of extreme events such as droughts, floods, heat waves, wildfires, hurricanes, and storm surges.

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.

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.

Quantifying wetland–aquifer interactions in a humid subtropical climate region: An integrated approach

USGS Publications Warehouse

Mendoza-Sanchez, Itza; Phanikumar, Mantha S.; Niu, Jie; Masoner, Jason R.; Cozzarelli, Isabelle M.; McGuire, Jennifer T.

2013-01-01

Wetlands are widely recognized as sentinels of global climate change. Long-term monitoring data combined with process-based modeling has the potential to shed light on key processes and how they change over time. This paper reports the development and application of a simple water balance model based on long-term climate, soil, vegetation and hydrological dynamics to quantify groundwater–surface water (GW–SW) interactions at the Norman landfill research site in Oklahoma, USA. Our integrated approach involved model evaluation by means of the following independent measurements: (a) groundwater inflow calculation using stable isotopes of oxygen and hydrogen (16O, 18O, 1H, 2H); (b) seepage flux measurements in the wetland hyporheic sediment; and (c) pan evaporation measurements on land and in the wetland. The integrated approach was useful for identifying the dominant hydrological processes at the site, including recharge and subsurface flows. Simulated recharge compared well with estimates obtained using isotope methods from previous studies and allowed us to identify specific annual signatures of this important process during the period of study (1997–2007). Similarly, observations of groundwater inflow and outflow rates to and from the wetland using seepage meters and isotope methods were found to be in good agreement with simulation results. Results indicate that subsurface flow components in the system are seasonal and readily respond to rainfall events. The wetland water balance is dominated by local groundwater inputs and regional groundwater flow contributes little to the overall water balance.

Distributed data discovery, access and visualization services to Improve Data Interoperability across different data holdings

NASA Astrophysics Data System (ADS)

Palanisamy, G.; Krassovski, M.; Devarakonda, R.; Santhana Vannan, S.

2012-12-01

The current climate debate is highlighting the importance of free, open, and authoritative sources of high quality climate data that are available for peer review and for collaborative purposes. It is increasingly important to allow various organizations around the world to share climate data in an open manner, and to enable them to perform dynamic processing of climate data. This advanced access to data can be enabled via Web-based services, using common "community agreed" standards without having to change their internal structure used to describe the data. The modern scientific community has become diverse and increasingly complex in nature. To meet the demands of such diverse user community, the modern data supplier has to provide data and other related information through searchable, data and process oriented tool. This can be accomplished by setting up on-line, Web-based system with a relational database as a back end. The following common features of the web data access/search systems will be outlined in the proposed presentation: - A flexible data discovery - Data in commonly used format (e.g., CSV, NetCDF) - Preparing metadata in standard formats (FGDC, ISO19115, EML, DIF etc.) - Data subseting capabilities and ability to narrow down to individual data elements - Standards based data access protocols and mechanisms (SOAP, REST, OpenDAP, OGC etc.) - Integration of services across different data systems (discovery to access, visualizations and subseting) This presentation will also include specific examples of integration of various data systems that are developed by Oak Ridge National Laboratory's - Climate Change Science Institute, their ability to communicate between each other to enable better data interoperability and data integration. References: [1] Devarakonda, Ranjeet, and Harold Shanafield. "Drupal: Collaborative framework for science research." Collaboration Technologies and Systems (CTS), 2011 International Conference on. IEEE, 2011. [2]Devarakonda, R., Shrestha, B., Palanisamy, G., Hook, L. A., Killeffer, T. S., Boden, T. A., ... & Lazer, K. (2014). THE NEW ONLINE METADATA EDITOR FOR GENERATING STRUCTURED METADATA. Oak Ridge National Laboratory (ORNL).

Sensitivity analysis of a sediment dynamics model applied in a Mediterranean river basin: global change and management implications.

PubMed

Sánchez-Canales, M; López-Benito, A; Acuña, V; Ziv, G; Hamel, P; Chaplin-Kramer, R; Elorza, F J

2015-01-01

Climate change and land-use change are major factors influencing sediment dynamics. Models can be used to better understand sediment production and retention by the landscape, although their interpretation is limited by large uncertainties, including model parameter uncertainties. The uncertainties related to parameter selection may be significant and need to be quantified to improve model interpretation for watershed management. In this study, we performed a sensitivity analysis of the InVEST (Integrated Valuation of Environmental Services and Tradeoffs) sediment retention model in order to determine which model parameters had the greatest influence on model outputs, and therefore require special attention during calibration. The estimation of the sediment loads in this model is based on the Universal Soil Loss Equation (USLE). The sensitivity analysis was performed in the Llobregat basin (NE Iberian Peninsula) for exported and retained sediment, which support two different ecosystem service benefits (avoided reservoir sedimentation and improved water quality). Our analysis identified the model parameters related to the natural environment as the most influential for sediment export and retention. Accordingly, small changes in variables such as the magnitude and frequency of extreme rainfall events could cause major changes in sediment dynamics, demonstrating the sensitivity of these dynamics to climate change in Mediterranean basins. Parameters directly related to human activities and decisions (such as cover management factor, C) were also influential, especially for sediment exported. The importance of these human-related parameters in the sediment export process suggests that mitigation measures have the potential to at least partially ameliorate climate-change driven changes in sediment exportation. Copyright © 2014 Elsevier B.V. All rights reserved.

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

DOE PAGES

Cai, X.; Yang, Z. -L.; Fisher, J. B.; ...

2016-01-15

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. Here in this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soilmore » and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.« less

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

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

Cai, X.; Yang, Z. -L.; Fisher, J. B.

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. Here in this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soilmore » and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.« less

Dynamically downscaled climate simulations over North America: Methods, evaluation, and supporting documentation for users

USGS Publications Warehouse

Hostetler, S.W.; Alder, J.R.; Allan, A.M.

2011-01-01

We have completed an array of high-resolution simulations of present and future climate over Western North America (WNA) and Eastern North America (ENA) by dynamically downscaling global climate simulations using a regional climate model, RegCM3. The simulations are intended to provide long time series of internally consistent surface and atmospheric variables for use in climate-related research. In addition to providing high-resolution weather and climate data for the past, present, and future, we have developed an integrated data flow and methodology for processing, summarizing, viewing, and delivering the climate datasets to a wide range of potential users. Our simulations were run over 50- and 15-kilometer model grids in an attempt to capture more of the climatic detail associated with processes such as topographic forcing than can be captured by general circulation models (GCMs). The simulations were run using output from four GCMs. All simulations span the present (for example, 1968-1999), common periods of the future (2040-2069), and two simulations continuously cover 2010-2099. The trace gas concentrations in our simulations were the same as those of the GCMs: the IPCC 20th century time series for 1968-1999 and the A2 time series for simulations of the future. We demonstrate that RegCM3 is capable of producing present day annual and seasonal climatologies of air temperature and precipitation that are in good agreement with observations. Important features of the high-resolution climatology of temperature, precipitation, snow water equivalent (SWE), and soil moisture are consistently reproduced in all model runs over WNA and ENA. The simulations provide a potential range of future climate change for selected decades and display common patterns of the direction and magnitude of changes. As expected, there are some model to model differences that limit interpretability and give rise to uncertainties. Here, we provide background information about the GCMs and the RegCM3, a basic evaluation of the model output and examples of simulated future climate. We also provide information needed to access the web applications for visualizing and downloading the data, and give complete metadata that describe the variables in the datasets.

Designing the Bridge: Perceptions and Use of Downscaled Climate Data by Climate Modelers and Resource Managers in Hawaii

NASA Astrophysics Data System (ADS)

Keener, V. W.; Brewington, L.; Jaspers, K.

2016-12-01

To build an effective bridge from the climate modeling community to natural resource managers, we assessed the existing landscape to see where different groups diverge in their perceptions of climate data and needs. An understanding of a given community's shared knowledge and differences can help design more actionable science. Resource managers in Hawaii are eager to have future climate projections at spatial scales relevant to the islands. National initiatives to downscale climate data often exclude US insular regions, so researchers in Hawaii have generated regional dynamically and statistically downscaled projections. Projections of precipitation diverge, however, leading to difficulties in communication and use. Recently, a two day workshop was held with scientists and managers to evaluate available models and determine a set of best practices for moving forward with decision-relevant downscaling in Hawaii. To seed the discussion, the Pacific Regional Integrated Sciences and Assessments (RISA) program conducted a pre-workshop survey (N=65) of climate modelers and freshwater, ecosystem, and wildfire managers working in Hawaii. Scientists reported spending less than half of their time on operational research, although the majority was eager to partner with managers on specific projects. Resource managers had varying levels of familiarity with downscaled climate projections, but reported needing more information about uncertainty for decision making, and were less interested in the technical model details. There were large differences between groups of managers, with 41.7% of freshwater managers reporting that they used climate projections regularly, while a majority of ecosystem and wildfire managers reported having "no familiarity". Scientists and managers rated which spatial and temporal scales were most relevant to decision making. Finally, when asked to compare how confident they were in projections of specific climate variables between the dynamical and statistical data, 80-90% of managers responded that they had no opinion. Workshop attendees were very interested in the survey results, adding to evidence of a need for sustained engagement between modeler and user groups, as well as different strategies for working with different types of resource managers.

Forecasting carbon budget under climate change and CO2 fertilization for subtropical region in China using integrated biosphere simulator (IBIS) model

USGS Publications Warehouse

Zhu, Q.; Jiang, H.; Liu, J.; Peng, C.; Fang, X.; Yu, S.; Zhou, G.; Wei, X.; Ju, W.

2011-01-01

The regional carbon budget of the climatic transition zone may be very sensitive to climate change and increasing atmospheric CO2 concentrations. This study simulated the carbon cycles under these changes using process-based ecosystem models. The Integrated Biosphere Simulator (IBIS), a Dynamic Global Vegetation Model (DGVM), was used to evaluate the impacts of climate change and CO2 fertilization on net primary production (NPP), net ecosystem production (NEP), and the vegetation structure of terrestrial ecosystems in Zhejiang province (area 101,800 km2, mainly covered by subtropical evergreen forest and warm-temperate evergreen broadleaf forest) which is located in the subtropical climate area of China. Two general circulation models (HADCM3 and CGCM3) representing four IPCC climate change scenarios (HC3AA, HC3GG, CGCM-sresa2, and CGCM-sresb1) were used as climate inputs for IBIS. Results show that simulated historical biomass and NPP are consistent with field and other modelled data, which makes the analysis of future carbon budget reliable. The results indicate that NPP over the entire Zhejiang province was about 55 Mt C yr-1 during the last half of the 21st century. An NPP increase of about 24 Mt C by the end of the 21st century was estimated with the combined effects of increasing CO2 and climate change. A slight NPP increase of about 5 Mt C was estimated under the climate change alone scenario. Forests in Zhejiang are currently acting as a carbon sink with an average NEP of about 2.5 Mt C yr-1. NEP will increase to about 5 Mt C yr-1 by the end of the 21st century with the increasing atmospheric CO2 concentration and climate change. However, climate change alone will reduce the forest carbon sequestration of Zhejiang's forests. Future climate warming will substantially change the vegetation cover types; warm-temperate evergreen broadleaf forest will be gradually substituted by subtropical evergreen forest. An increasing CO2 concentration will have little contribution to vegetation changes. Simulated NPP shows geographic patterns consistent with temperature to a certain extent, and precipitation is not the limiting factor for forest NPP in the subtropical climate conditions. There is no close relationship between the spatial pattern of NEP and climate condition.

Forecasting carbon budget under climate change and CO 2 fertilization for subtropical region in China using integrated biosphere simulator (IBIS) model

USGS Publications Warehouse

Zhu, Q.; Jiang, H.; Liu, J.; Peng, C.; Fang, X.; Yu, S.; Zhou, G.; Wei, X.; Ju, W.

2011-01-01

The regional carbon budget of the climatic transition zone may be very sensitive to climate change and increasing atmospheric CO 2 concentrations. This study simulated the carbon cycles under these changes using process-based ecosystem models. The Integrated Biosphere Simulator (IBIS), a Dynamic Global Vegetation Model (DGVM), was used to evaluate the impacts of climate change and CO 2 fertilization on net primary production (NPP), net ecosystem production (NEP), and the vegetation structure of terrestrial ecosystems in Zhejiang province (area 101,800 km 2, mainly covered by subtropical evergreen forest and warm-temperate evergreen broadleaf forest) which is located in the subtropical climate area of China. Two general circulation models (HADCM3 and CGCM3) representing four IPCC climate change scenarios (HC3AA, HC3GG, CGCM-sresa2, and CGCM-sresb1) were used as climate inputs for IBIS. Results show that simulated historical biomass and NPP are consistent with field and other modelled data, which makes the analysis of future carbon budget reliable. The results indicate that NPP over the entire Zhejiang province was about 55 Mt C yr -1 during the last half of the 21 st century. An NPP increase of about 24 Mt C by the end of the 21 st century was estimated with the combined effects of increasing CO 2 and climate change. A slight NPP increase of about 5 Mt C was estimated under the climate change alone scenario. Forests in Zhejiang are currently acting as a carbon sink with an average NEP of about 2.5 Mt C yr -1. NEP will increase to about 5 Mt C yr -1 by the end of the 21 st century with the increasing atmospheric CO 2 concentration and climate change. However, climate change alone will reduce the forest carbon sequestration of Zhejiang's forests. Future climate warming will substantially change the vegetation cover types; warm-temperate evergreen broadleaf forest will be gradually substituted by subtropical evergreen forest. An increasing CO 2 concentration will have little contribution to vegetation changes. Simulated NPP shows geographic patterns consistent with temperature to a certain extent, and precipitation is not the limiting factor for forest NPP in the subtropical climate conditions. There is no close relationship between the spatial pattern of NEP and climate condition.

An integrated modelling methodology to study the impacts of nutrients on coastal aquatic ecosystems in the context of climate change

NASA Astrophysics Data System (ADS)

Pesce, Marco; Critto, Andrea; Torresan, Silvia; Santini, Monia; Giubilato, Elisa; Pizzol, Lisa; Mercogliano, Paola; Zirino, Alberto; Wei, Ouyang; Marcomini, Antonio

2017-04-01

It has been recognized that the increase of atmospheric greenhouse gases (GHG) due to anthropogenic activities is causing changes in Earth's climate. Global mean temperatures are expected to rise by 0.3 to 4.8 °C by the end of the 21st century, and the water cycle to alter because of changes in global atmospheric moisture. Coastal waterbodies such as estuaries, bays and lagoons together with the ecological and socio-economic services they provide, could be among those most affected by the ongoing changes on climate. Because of their position at the land-sea interface, they are subjected to the combined changes in the physico-chemical processes of atmosphere, upstream land and coastal waters. Particularly, climate change is expected to alter phytoplankton communities by changing their climate and environmental drivers, such as temperature, precipitation, wind, solar radiation and nutrient loadings, and to exacerbate the symptoms of eutrophication events, such as hypoxia, harmful algal blooms (HAB) and loss of habitat. A better understanding of the links between climate-related drivers and phytoplankton is therefore necessary for predicting climate change impacts on aquatic ecosystems. In this context, the integration of climate scenarios and environmental models can become a valuable tool for the investigation and prediction of phytoplankton ecosystem dynamics under climate change conditions. In the last decade, the effects of climate change on the environmental distribution of nutrients and the resulting effects on aquatic ecosystems encouraged the conduction of modeling studies at a catchment scale, even though mainly are related to lake ecosystem. The further development of integrated modeling approaches and their application to other types of waterbodies such as coastal waters can be a useful contribution to increase the availability of management tools for ecological conservation and adaptation policies. Here we present the case study of the Zero river basin in Italy, one of the main contributors of freshwater and nutrients loadings to the salt-marsh Palude di Cona, a waterbody belonging to the lagoon of Venice. To predict the effects of climate change on nutrient loadings and their effects on the phytoplankton community of the receiving waterbody, we applied a methodology integrating an ensemble of GCM-RCM climate projections, the hydrological model SWAT and the ecological model AQUATOX. Climate scenarios for the study area revealed an increase of precipitations in the winter period and a decrease in the summer months, while temperature shows a significant increase over the whole year. The hydrological model SWAT predicted changes the Zero river's waterflow and nutrients' loadings. Both parameters show a tendency to increase in the winter period, and a reduction during the summer months. Simulations with AQUATOX predicted changes in the concentration of nutrients in the salt-marsh Palude di Cona, and variations in the biomass and species of the phytoplankton community. The simulation shows changes are highly species-dependent. Major changes are observed in the spring-summer period, where the abundance of warm-adapted species increase noticeably.

Erosion under climate and human pressures: An alpine lake sediment perspective

NASA Astrophysics Data System (ADS)

Arnaud, Fabien; Poulenard, Jérôme; Giguet-Covex, Charline; Wilhelm, Bruno; Révillon, Sidonie; Jenny, Jean-Philippe; Revel, Marie; Enters, Dirk; Bajard, Manon; Fouinat, Laurent; Doyen, Elise; Simonneau, Anaëlle; Pignol, Cécile; Chapron, Emmanuel; Vannière, Boris; Sabatier, Pierre

2016-11-01

We review the scientific efforts over the last decades to reconstruct erosion from continuous alpine lake sediment records. We focused both on methodological issues, showing the growing importance of non-destructive high resolution approaches (XRF core-scanner) as well as progresses in the understanding of processes leading to the creation of an "erosion signal" in lakes. We distinguish "continuous records" from "event-records". Both provide complementary information but need to be studied with different approaches. Continuous regionally-relevant records proved to be particularly pertinent to document regional erosion patterns throughout the Holocene, in particular applying the source to sink approach. Event-based approaches demonstrated and took advantage of the strong non-linearity of sediment transport in high altitude catchment areas. This led to flood frequency and intensity reconstructions, highlighting the influence of climate change upon flood dynamics in the mountain. The combination of different record types, both in terms of location (high vs. low elevation), sedimentology (high vs. low terrigenous contribution) and significance (local vs. regional) is one of the main outputs of this paper. It allows the establishment of comprehensive histories of NW French Alps erosion, but also and consequently, soil dynamics and hydrological patterns throughout the Holocene. We also discuss the influence of glacier dynamics, one of the major agents of erosion in the Alps. A major feature is the growing human influence upon erosion at a local scale since at least the middle of the Bronze Age (3500 cal. BP). However and according to the regional record from Lake Bourget, only few periods of rising erosion at local scales generated a regional record that can be discriminated from wetter climatic periods. Among them, the period between 200 BCE and 400 AD appeared to be marked by a generalised rise in human-triggered erosion at local scales in the northern French Alps. This review highlights the importance of modern high-resolution and interdisciplinary studies of lake sediments, in order to better understand the complex relationships between humans, climate and the Earth system in general. We strongly argue that regional integration of data is now required to move a step further. Such an integration is easier with cost- and time-effective methods as well as after a better definition of approaches and their limits. This should lead to a stronger collaboration between paleo-data producers and modellers in the near future.

On the global limits of bioenergy and land use for climate change mitigation

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

Strapasson, Alexandre; Woods, Jeremy; Chum, Helena

Across energy, agricultural and forestry landscapes, the production of biomass for energy has emerged as a controversial driver of land-use change. We present a novel, simple methodology, to probe the potential global sustainability limits of bioenergy over time for energy provision and climate change mitigation using a complex-systems approach for assessing land-use dynamics. Primary biomass that could provide between 70 EJ year -1 and 360 EJ year -1, globally, by 2050 was simulated in the context of different land-use futures, food diet patterns and climate change mitigation efforts. Our simulations also show ranges of potential greenhouse gas emissions for agriculture,more » forestry and other land uses by 2050, including not only above-ground biomass-related emissions, but also from changes in soil carbon, from as high as 24 GtCO 2eq year-1 to as low as minus 21 GtCO 2eq year -1, which would represent a significant source of negative emissions. Based on the modelling simulations, the discussions offer novel insights about bioenergy as part of a broader integrated system. As a result, there are sustainability limits to the scale of bioenergy provision, they are dynamic over time, being responsive to land management options deployed worldwide.« less

On the global limits of bioenergy and land use for climate change mitigation

DOE PAGES

Strapasson, Alexandre; Woods, Jeremy; Chum, Helena; ...

2017-05-24

Across energy, agricultural and forestry landscapes, the production of biomass for energy has emerged as a controversial driver of land-use change. We present a novel, simple methodology, to probe the potential global sustainability limits of bioenergy over time for energy provision and climate change mitigation using a complex-systems approach for assessing land-use dynamics. Primary biomass that could provide between 70 EJ year -1 and 360 EJ year -1, globally, by 2050 was simulated in the context of different land-use futures, food diet patterns and climate change mitigation efforts. Our simulations also show ranges of potential greenhouse gas emissions for agriculture,more » forestry and other land uses by 2050, including not only above-ground biomass-related emissions, but also from changes in soil carbon, from as high as 24 GtCO 2eq year-1 to as low as minus 21 GtCO 2eq year -1, which would represent a significant source of negative emissions. Based on the modelling simulations, the discussions offer novel insights about bioenergy as part of a broader integrated system. As a result, there are sustainability limits to the scale of bioenergy provision, they are dynamic over time, being responsive to land management options deployed worldwide.« less

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.

Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

NASA Astrophysics Data System (ADS)

Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

2015-12-01

Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we contend that creating believable soil carbon predictions requires a robust, transparent, and community-available benchmarking framework. I will present an ILAMB evaluation of several of the above-mentioned approaches in ACME, and attempt to motivate community adoption of this evaluation approach.

The fossil record of phenotypic integration and modularity: A deep-time perspective on developmental and evolutionary dynamics.

PubMed

Goswami, Anjali; Binder, Wendy J; Meachen, Julie; O'Keefe, F Robin

2015-04-21

Variation is the raw material for natural selection, but the factors shaping variation are still poorly understood. Genetic and developmental interactions can direct variation, but there has been little synthesis of these effects with the extrinsic factors that can shape biodiversity over large scales. The study of phenotypic integration and modularity has the capacity to unify these aspects of evolutionary study by estimating genetic and developmental interactions through the quantitative analysis of morphology, allowing for combined assessment of intrinsic and extrinsic effects. Data from the fossil record in particular are central to our understanding of phenotypic integration and modularity because they provide the only information on deep-time developmental and evolutionary dynamics, including trends in trait relationships and their role in shaping organismal diversity. Here, we demonstrate the important perspective on phenotypic integration provided by the fossil record with a study of Smilodon fatalis (saber-toothed cats) and Canis dirus (dire wolves). We quantified temporal trends in size, variance, phenotypic integration, and direct developmental integration (fluctuating asymmetry) through 27,000 y of Late Pleistocene climate change. Both S. fatalis and C. dirus showed a gradual decrease in magnitude of phenotypic integration and an increase in variance and the correlation between fluctuating asymmetry and overall integration through time, suggesting that developmental integration mediated morphological response to environmental change in the later populations of these species. These results are consistent with experimental studies and represent, to our knowledge, the first deep-time validation of the importance of developmental integration in stabilizing morphological evolution through periods of environmental change.

The fossil record of phenotypic integration and modularity: A deep-time perspective on developmental and evolutionary dynamics

PubMed Central

Goswami, Anjali; Binder, Wendy J.; Meachen, Julie; O’Keefe, F. Robin

2015-01-01

Variation is the raw material for natural selection, but the factors shaping variation are still poorly understood. Genetic and developmental interactions can direct variation, but there has been little synthesis of these effects with the extrinsic factors that can shape biodiversity over large scales. The study of phenotypic integration and modularity has the capacity to unify these aspects of evolutionary study by estimating genetic and developmental interactions through the quantitative analysis of morphology, allowing for combined assessment of intrinsic and extrinsic effects. Data from the fossil record in particular are central to our understanding of phenotypic integration and modularity because they provide the only information on deep-time developmental and evolutionary dynamics, including trends in trait relationships and their role in shaping organismal diversity. Here, we demonstrate the important perspective on phenotypic integration provided by the fossil record with a study of Smilodon fatalis (saber-toothed cats) and Canis dirus (dire wolves). We quantified temporal trends in size, variance, phenotypic integration, and direct developmental integration (fluctuating asymmetry) through 27,000 y of Late Pleistocene climate change. Both S. fatalis and C. dirus showed a gradual decrease in magnitude of phenotypic integration and an increase in variance and the correlation between fluctuating asymmetry and overall integration through time, suggesting that developmental integration mediated morphological response to environmental change in the later populations of these species. These results are consistent with experimental studies and represent, to our knowledge, the first deep-time validation of the importance of developmental integration in stabilizing morphological evolution through periods of environmental change. PMID:25901310

Integrated Modeling and Participatory Scenario Planning for Climate Adaptation: the Maui Groundwater Project

NASA Astrophysics Data System (ADS)

Keener, V. W.; Finucane, M.; Brewington, L.

2014-12-01

For the last century, the island of Maui, Hawaii, has been the center of environmental, agricultural, and legal conflict with respect to surface and groundwater allocation. Planning for adequate future freshwater resources requires flexible and adaptive policies that emphasize partnerships and knowledge transfer between scientists and non-scientists. In 2012 the Hawai'i state legislature passed the Climate Change Adaptation Priority Guidelines (Act 286) law requiring county and state policy makers to include island-wide climate change scenarios in their planning processes. This research details the ongoing work by researchers in the NOAA funded Pacific RISA to support the development of Hawaii's first island-wide water use plan under the new climate adaptation directive. This integrated project combines several models with participatory future scenario planning. The dynamically downscaled triply nested Hawaii Regional Climate Model (HRCM) was modified from the WRF community model and calibrated to simulate the many microclimates on the Hawaiian archipelago. For the island of Maui, the HRCM was validated using 20 years of hindcast data, and daily projections were created at a 1 km scale to capture the steep topography and diverse rainfall regimes. Downscaled climate data are input into a USGS hydrological model to quantify groundwater recharge. This model was previously used for groundwater management, and is being expanded utilizing future climate projections, current land use maps and future scenario maps informed by stakeholder input. Participatory scenario planning began in 2012 to bring together a diverse group of over 50 decision-makers in government, conservation, and agriculture to 1) determine the type of information they would find helpful in planning for climate change, and 2) develop a set of scenarios that represent alternative climate/management futures. This is an iterative process, resulting in flexible and transparent narratives at multiple scales. The resulting climate, land use, and groundwater recharge maps give stakeholders a common set of future scenarios that they understand through the participatory scenario process, and identify the vulnerabilities, trade-offs, and adaptive priorities for different groundwater management and land uses in an uncertain future.

Santa Ana Winds of Southern California: Their Climatology and Variability Spanning 6.5 Decades from Regional Dynamical Modelling

NASA Astrophysics Data System (ADS)

Guzman-Morales, J.; Gershunov, A.

2015-12-01

Santa Ana Winds (SAWs) are an integral feature of the regional climate of Southern California/Northern Baja California region. In spite of their tremendous episodic impacts on the health, economy and mood of the region, climate-scale behavior of SAW is poorly understood. In the present work, we identify SAWs in mesoscale dynamical downscaling of a global reanalysis product and construct an hourly SAW catalogue spanning 65 years. We describe the long-term SAW climatology at relevant time-space resolutions, i.e, we developed local and regional SAW indices and analyse their variability on hourly, daily, annual, and multi-decadal timescales. Local and regional SAW indices are validated with available anemometer observations. Characteristic behaviors are revealed, e.g. the SAW intensity-duration relationship. At interdecadal time scales, we find that seasonal SAW activity is sensitive to prominent large-scale low-frequency modes of climate variability rooted in the tropical and north Pacific ocean-atmosphere system that are also known to affect the hydroclimate of this region. Lastly, we do not find any long-term trend in SAW frequency and intensity as previously reported. Instead, we identify a significant long-term trend in SAW behavior whereby contribution of extreme SAW events to total seasonal SAW activity has been increasing at the expense of moderate events. These findings motivate further investigation on SAW evolution in future climate and its impact on wildfires.

Relevance of improved epidemiological knowledge to sustainable control of Haemonchus contortus in Nigeria.

PubMed

Bolajoko, M B; Morgan, E R

2012-12-01

Nigeria experiences losses in small ruminant production as a result of a high prevalence of infection with Haemonchus contortus, but there have been very few investigative studies into the epidemiology of H. contortus in Nigeria, particularly in the south and western parts of the country. For successful planning and execution of control of hemonchosis in Nigeria, there is a need for insight into the epidemiology of free-living stages under the prevailing local conditions and models for climatic and environmental factors that control the risk of hemonchosis and distribution of H. contortus. In this review, we assess previous studies on the epidemiology of H. contortus in Nigeria, evaluate the present climatic and epidemiological situation, and highlight areas that require further investigative studies. The goal is to identify factors that underpin better control strategies and holistic integrated farm-management practice. Previous studies on H. contortus provided important information for formulation of control strategies and development toward integrated parasite management. However, this review has revealed the need for holistic evaluation of the current epidemiology and prevalence of H. contortus in Nigeria, particularly in relation to climate change. Accurate information is needed to build useful predictive models of the population dynamics of all free-living stages, particularly the L3.

A dynamic ocean management tool to reduce bycatch and support sustainable fisheries.

PubMed

Hazen, Elliott L; Scales, Kylie L; Maxwell, Sara M; Briscoe, Dana K; Welch, Heather; Bograd, Steven J; Bailey, Helen; Benson, Scott R; Eguchi, Tomo; Dewar, Heidi; Kohin, Suzy; Costa, Daniel P; Crowder, Larry B; Lewison, Rebecca L

2018-05-01

Seafood is an essential source of protein for more than 3 billion people worldwide, yet bycatch of threatened species in capture fisheries remains a major impediment to fisheries sustainability. Management measures designed to reduce bycatch often result in significant economic losses and even fisheries closures. Static spatial management approaches can also be rendered ineffective by environmental variability and climate change, as productive habitats shift and introduce new interactions between human activities and protected species. We introduce a new multispecies and dynamic approach that uses daily satellite data to track ocean features and aligns scales of management, species movement, and fisheries. To accomplish this, we create species distribution models for one target species and three bycatch-sensitive species using both satellite telemetry and fisheries observer data. We then integrate species-specific probabilities of occurrence into a single predictive surface, weighing the contribution of each species by management concern. We find that dynamic closures could be 2 to 10 times smaller than existing static closures while still providing adequate protection of endangered nontarget species. Our results highlight the opportunity to implement near real-time management strategies that would both support economically viable fisheries and meet mandated conservation objectives in the face of changing ocean conditions. With recent advances in eco-informatics, dynamic management provides a new climate-ready approach to support sustainable fisheries.

Mandate for the Nursing Profession to Address Climate Change Through Nursing Education.

PubMed

Leffers, Jeanne; Levy, Ruth McDermott; Nicholas, Patrice K; Sweeney, Casey F

2017-11-01

The adverse health effects from climate change demand action from the nursing profession. This article examines the calls to action, the status of climate change in nursing education, and challenges and recommendations for nursing education related to climate change and human health. Discussion paper. The integration of climate change into nursing education is essential so that knowledge, skills, and insights critical for clinical practice in our climate-changing world are incorporated in curricula, practice, research, and policy. Our Ecological Planetary Health Model offers a framework for nursing to integrate relevant climate change education into nursing curricula and professional nursing education. Nursing education can offer a leadership role to address the mitigation, adaptation, and resilience strategies for climate change. An ecological framework is valuable for nursing education regarding climate change through its consideration of political, cultural, economic, and environmental interrelationships on human health and the health of the planet. Knowledge of climate change is important for integration into basic and advanced nursing education, as well as professional education for nurses to address adverse health impacts, climate change responses policy, and advocacy roles. For current and future nurses to provide care within a climate-changing environment, nursing education has a mandate to integrate knowledge about climate change issues across all levels of nursing education. Competence in nursing practice follows from knowledge and skill acquisition gained from integration of climate change content into nursing education. © 2017 Sigma Theta Tau International.

Physiological-based modelling of marine fish early life stages provides process knowledge on climate impacts

NASA Astrophysics Data System (ADS)

Peck, M. A.

2016-02-01

Gaining a cause-and-effect understanding of climate-driven changes in marine fish populations at appropriate spatial scales is important for providing robust advice for ecosystem-based fisheries management. Coupling long-term, retrospective analyses and 3-d biophysical, individual-based models (IBMs) shows great potential to reveal mechanism underlying historical changes and to project future changes in marine fishes. IBMs created for marine fish early life stages integrate organismal-level physiological responses and climate-driven changes in marine habitats (from ocean physics to lower trophic level productivity) to test and reveal processes affecting marine fish recruitment. Case studies are provided for hindcasts and future (A1 and B2 projection) simulations performed on some of the most ecologically- and commercially-important pelagic and demersal fishes in the North Sea including European anchovy, Atlantic herring, European sprat and Atlantic cod. We discuss the utility of coupling biophysical IBMs to size-spectrum models to better project indirect (trophodynamic) pathways of climate influence on the early life stages of these and other fishes. Opportunities and challenges are discussed regarding the ability of these physiological-based tools to capture climate-driven changes in living marine resources and food web dynamics of shelf seas.

The New APS Topical Group on the Physics of Climate: History, Objectives and Panel Discussion

NASA Astrophysics Data System (ADS)

Brasseur, James; Behringer, Robert

2013-03-01

The GPC Chair will introduce the new APS Topical Group on the Physics of Climate (GPC), describe its history and objectives, and introduce the current GPC leadership before opening the floor to a panel discussion. The GPC resulted from two petitions that emerged from the controversy that followed the APS Statement on Climate Change (see APS website). The two proposals were merged and an organization committee formed by the APS leadership. After a long organizational period in 2011, the GPC bylaws were finalized with the following key objective: The objective of the GPC shall be to promote the advancement and diffusion of knowledge concerning the physics, measurement, and modeling of climate processes, within the domain of natural science and outside the domains of societal impact and policy, legislation and broader societal issues. The objective includes the integration of scientific knowledge and analysis methods across disciplines to address the dynamical complexities and uncertainties of climate physics. The GPC Invited and Focus Sessions at this March meeting are the inaugural GPC events. The Program Committee Chair will moderate a panel between the attending GPC leadership and audience to solicit suggestions for potential future GPC events that advance the GPC objectives.

Climate change jeopardizes the persistence of freshwater zooplankton by reducing both habitat suitability and demographic resilience.

PubMed

Pinceel, Tom; Buschke, Falko; Weckx, Margo; Brendonck, Luc; Vanschoenwinkel, Bram

2018-01-24

Higher temperatures and increased environmental variability under climate change could jeopardize the persistence of species. Organisms that rely on short windows of rainfall to complete their life-cycles, like desert annual plants or temporary pool animals, may be particularly at risk. Although some could tolerate environmental changes by building-up banks of propagules (seeds or eggs) that buffer against catastrophes, climate change will threaten this resilience mechanism if higher temperatures reduce propagule survival. Using a crustacean model species from temporary waters, we quantified experimentally the survival and dormancy of propagules under anticipated climate change and used these demographic parameters to simulate long term population dynamics. By exposing propagules to present-day and projected daily temperature cycles in an 8 month laboratory experiment, we showed how increased temperatures reduce survival rates in the propagule bank. Integrating these reduced survival rates into population models demonstrated the inability of the bank to maintain populations; thereby exacerbating extinction risk caused by shortened growing seasons. Overall, our study demonstrates that climate change could threaten the persistence of populations by both reducing habitat suitability and eroding life-history strategies that support demographic resilience.

Middle Miocene environmental and climatic evolution at the Wilkes Land margin, East Antarctica

NASA Astrophysics Data System (ADS)

Sangiorgi, Francesca; Bijl, Peter; Passchier, Sandra; Salzmann, Ulrich; Schouten, Stefan; Pross, Jörg; Escutia, Carlota; Brinkhuis, Henk

2015-04-01

Integrated Ocean Drilling Program (IODP) Expedition 318 successfully drilled a Middle Miocene (~ 17 - 12.5 Ma) record from the Wilkes Land Margin at Site U1356A (63°18.6138'S, 135°59.9376'E), located at the transition between the continental rise and the abyssal plain at 4003 mbsl. We present a multiproxy palynological (dinoflagellate cyst, pollen and spores), sedimentological and organic geochemical (TEX86, MBT/CBT) study, which unravels the environmental and climate variability across the Miocene Climatic Optimum (MCO, ~17-15 Ma) and the Mid Miocene Climate Transition (MMCT). Several independent lines of evidence suggest a relatively warm climate during the MCO. Dinocyst and pollen assemblage diversity at the MCO is unprecedented for a Neogene Antarctic record and indicates a temperate, sea ice-free marine environment, with woody sub-antarctic vegetation with elements of forest/shrub tundra and peat lands along the coast. These results are further confirmed by relatively warm TEX86-derived Sea Surface Temperatures and mild MBT-derived continental temperatures, and by the absence of glacially derived deposits and very few ice-rafted clasts. A generally colder but highly dynamic environment is suggested for the interval 15-12.5 Ma.

The value of superpower-submitted INDCs in cooperative and non-cooperative action scenarios: economic impact, dynamic risk, and temperature rise

NASA Astrophysics Data System (ADS)

Augustin, C. M.

2015-12-01

As the 2015 Paris climate talks near, policy discussions are focused on "intended nationally determined contributions" (INDCs) submitted in advance of the discussions. As the major global emitters - specifically the United States and China - have already submitted their INDCs, we have a point of comparison for evaluating the relative potential impacts of the proposed targets. By applying integrated assessment models to robust, publicly available data sets,we aim to evaluate the interplay between climate change and economic development, comment on emissions reduction scenarios in cooperative and non-cooperative situations, and assess the dynamic risks of multiple regional emissions scenarios. We use both the RICE model and the C-ROADS model to examine alternative regional outcomes for emissions, climate change, and damages,under different reduction scenarios, including a scenario where geo-engineering plays a prominent role. These simulators allow us to vary emissions, population, and economic levels in China and the United States specifically to comment on the international climate risk impact of actors working jointly - or not - toward a global climate goal. In a complementary piece of analysis we seek to understand the value judgments, trade-offs, and regional policies that would lead to favorable climate finance flows. To reach an international sample of industry decision-makers, we propose a novel application of a standard discrete-choice survey methodology. A conjoint analysis requires a participant to chose between combinations of attributes and identify trade-offs while allowing the researcher to determine the relative importance of each individual attribute by mathematically assessing the impact each attribute could have on total item utility. As climate policy negotiations will consist of allocation of scarce resources and rejection of certain attributes, a conjoint analysis is an ideal tool for evaluating policy outcomes. This research program seeks to provide a commentary useful to policy makers on the most desirable outcomes of the negotiations and other international cooperation.

Predicting future US water yield and ecosystem productivity by linking an ecohydrological model to WRF dynamically downscaled climate projections

NASA Astrophysics Data System (ADS)

Sun, S.; Sun, G.; Cohen, E.; McNulty, S. G.; Caldwell, P.; Duan, K.; Zhang, Y.

2015-12-01

Quantifying the potential impacts of climate change on water yield and ecosystem productivity (i.e., carbon balances) is essential to developing sound watershed restoration plans, and climate change adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model) dynamically downscaled climate projections of the HadCM3 model under the IPCC SRES A2 emission scenario. We evaluated the future (2031-2060) changes in evapotranspiration (ET), water yield (Q) and gross primary productivity (GPP) from the baseline period of 1979-2007 across the 82 773 watersheds (12 digit Hydrologic Unit Code level) in the conterminous US (CONUS), and evaluated the future annual and monthly changes of hydrology and ecosystem productivity for the 18 Water Resource Regions (WRRs) or 2-digit HUCs. Across the CONUS, the future multi-year means show increases in annual precipitation (P) of 45 mm yr-1 (6 %), 1.8 °C increase in temperature (T), 37 mm yr-1 (7 %) increase in ET, 9 mm yr-1 (3 %) increase in Q, and 106 g C m-2 yr-1 (9 %) increase in GPP. Response to climate change was highly variable across the 82, 773 watersheds, but in general, the majority would see consistent increases in all variables evaluated. Over half of the 82 773 watersheds, mostly found in the northeast and the southern part of the southwest would have an increase in annual Q (>100 mm yr-1 or 20 %). This study provides an integrated method and example for comprehensive assessment of the potential impacts of climate change on watershed water balances and ecosystem productivity at high spatial and temporal resolutions. Results will be useful for policy-makers and land managers in formulating appropriate watershed-specific strategies for sustaining water and carbon sources in the face of climate change.

Changes of Mediterranean cyclones in the future climate employing high resolution climate simulations

NASA Astrophysics Data System (ADS)

Hatzaki, M.; Flocas, H. A.; Kouroutzoglou, J.; Keay, K.; Simmonds, I.; Giannakopoulos, C. A.; Brikolas, V.

2011-12-01

A number of studies suggest that cyclone activity over both hemispheres has changed over the second half of the 20th century. The assessment of the future changes of the cyclonic activity as imposed by global warming conditions is very important since these cyclones can be associated with extreme precipitation conditions, severe storms and floods. This is more important for the Mediterranean that has been found to be more vulnerable to climate change. The main objective of the current study is to better understand and assess future changes in the main characteristics of Mediterranean cyclones, including temporal and spatial variations of frequency of cyclonic tracks, and dynamic and kinematic parameters, such as intensity, size, propagation velocity, as well as trend analysis. For this purpose, the MPI-HH regional coupled climate model of the Max Planck Institute for Meteorology is employed consisting of the REgional atmosphere MOdel (REMO), the Max-Planck-Institute for Meteorology ocean model (MPI-OM) and the Hydrological Discharge Model (HD Model). A 25 km resolution domain is established on a rotated latitude-longitude coordinate system, while the physical parameterizations are taken from the global climate model ECHAM-4. These model data became available through the EU Project CIRCE which aims to perform, for the first time, climate change projections with a realistic representation of the Mediterranean Sea. The model results for the present climate are evaluated against ERA-40 Reanalysis (available through ECMWF), for the period 1962-2001. The identification and tracking of cyclones is performed with the aid of the Melbourne University algorithm (MS algorithm), according to the Lagrangian perspective. MS algorithm characterizes a cyclone only if a vorticity maximum could be connected with a local pressure minimum. According to the results, a decrease of the storm number and a tendency towards deeper cyclones is expected in the future, in general agreement with the results of previous studies. However, new findings reveal with respect to the dynamic/kinematic characteristics of the cyclonic tracks. The model experiments verify that considerable inter-monthly variations of track density occur in the Mediterranean region. The study of the kinematic and dynamic parameters of the cyclonic tracks according to their origin domain show that the vast majority originate within the examined area itself. ACKNOWLEDGMENTS: M. Hatzaki would like to thank the Greek State Scholarships Foundation for financial support through the program of postdoctoral research. The support of EU-FP6 project CIRCE Integrated Project-Climate Change and Impact Research: the Mediterranean Environment (http://www.circeproject.eu) for climate model data provision is also greatly acknowledged.

Remote Sensing Approach to Drought Monitoring to Inform Range Management at the Hopi Tribe and Navajo Nation

NASA Astrophysics Data System (ADS)

El Vilaly, M. M.; Van Leeuwen, W. J.; Didan, K.; Marsh, S. E.; Crimmins, , M. A.

2012-12-01

The Hopi Tribe and Navajo Nation are situated in the Northeastern corner of Arizona in the Colorado River Plateau. For more than a decade, the area has faced extensive and persistent drought conditions that have impacted vegetation communities and local water resources while exacerbating soil erosion. Moreover, these persistent droughts threaten ecosystem services, agriculture, and livestock production activities, and make this region sensitive to inter-annual climate variability and change. The limited hydroclimatic observations, bolstered by numerous anecdotal drought impact reports, indicate that the region has been suffering through an almost 15-year long drought which is threatening its socio-economic development. The objective of this research is to employ remote sensing data to monitor the ongoing drought and inform management and decision-making. The overall goals of this study are to develop a common understanding of the current status of drought across the area in order to understand the existing seasonal and inter-annual relationships between climate variability and vegetation dynamics. To analyze and investigate vegetation responses to climate variability, land use practices, and environmental factors in Hopi and Navajo nation during the last 22 years, a drought assessment framework was developed that integrates climate and topographical data with land surface remote sensing time series data. Multi-sensor Normalized Difference Vegetation Index time series data were acquired from the vegetation index and phenology project (vip.arizona.edu) from 1989 to 2010 at 5.6 km, were analyzed to characterize the intra-annual changes of vegetation, seasonal phenology and inter-annual vegetation response to climate variability and environmental factors. Due to the low number of retrieval obtained from TIMESAT software, we developed a new framework that can maximize the number of retrieval. Four vegetation development stages, annual integrated NDVI (Net Primary Production (NPP)), minimum annual NDVI, maximum annual NDVI, and annual amplitude, were extracted using that new framework. A multi-linear regression has been applied to these vegetation phenology metrics as well as to the relationship between pheno-metrics and environmental variables, to detect potential vegetation changes and to examine the existing relationship between vegetation dynamics and rainfall and elevation gradients. The results suggest that vegetation behavior is foremost governed by rainfall gradients (R-square =0.74). Trend analyses confirmed that around 80 percent of pixels showed a general decline of greenness with confidence level of 95% (p< 0.05), while 4 percent showed a general greening up. Vegetation in the area showed a significant and strong relationship with elevation and precipitation gradients. This correlation was more prominent at mid-elevations, which could be explained by the snowmelt dynamics and hydrological redistribution of water at that elevation. These tools, methods and results can be used to aid in monitoring and understanding climate change and variability impacts on vegetation productivity, ecosystem services, and water resources of the region, and to inform decision-makers and range managers at Hopi Tribe and Navajo nation. Keywords: drought, remote sensing, time series, vegetation dynamics, Hopi Tribe and Navajo Nations

Stoichiometry of hydrological C, N, and P losses across climate and geology: An environmental matrix approach across New Zealand primary forests

NASA Astrophysics Data System (ADS)

McGroddy, M. E.; Baisden, W. T.; Hedin, L. O.

2008-03-01

Hydrologic losses can play a key role in regulating ecosystem nutrient balances, particularly in regions where baseline nutrient cycles are not augmented by industrial deposition. We used first-order streams to integrate hydrologic losses at the watershed scale across unpolluted old-growth forests in New Zealand. We employed a matrix approach to resolve how stream water concentrations of dissolved organic carbon (DOC), organic and inorganic nitrogen (DON and DIN), and organic and inorganic phosphorus (DOP and DIP) varied as a function of landscape differences in climate and geology. We found stream water total dissolved nitrogen (TDN) to be dominated by organic forms (medians for DON, 81.3%, nitrate-N, 12.6%, and ammonium-N, 3.9%). The median stream water DOC:TDN:TDP molar ratio of 1050:21:1 favored C slightly over N and P when compared to typical temperate forest foliage ratios. Using the full set of variables in a multiple regression approach explained approximately half of the variability in DON, DOC, and TDP concentrations. Building on this approach we combined a simplified set of variables with a simple water balance model in a regression designed to predict DON export at larger spatial scales. Incorporating the effects of climate and geologic variables on nutrient exports will greatly aid the development of integrated Earth-climate biogeochemical models which are able to take into account multiple element dynamics and complex natural landscapes.

Estimating global distribution of boreal, temperate, and tropical tree plant functional types using clustering techniques

NASA Astrophysics Data System (ADS)

Wang, Audrey; Price, David T.

2007-03-01

A simple integrated algorithm was developed to relate global climatology to distributions of tree plant functional types (PFT). Multivariate cluster analysis was performed to analyze the statistical homogeneity of the climate space occupied by individual tree PFTs. Forested regions identified from the satellite-based GLC2000 classification were separated into tropical, temperate, and boreal sub-PFTs for use in the Canadian Terrestrial Ecosystem Model (CTEM). Global data sets of monthly minimum temperature, growing degree days, an index of climatic moisture, and estimated PFT cover fractions were then used as variables in the cluster analysis. The statistical results for individual PFT clusters were found consistent with other global-scale classifications of dominant vegetation. As an improvement of the quantification of the climatic limitations on PFT distributions, the results also demonstrated overlapping of PFT cluster boundaries that reflected vegetation transitions, for example, between tropical and temperate biomes. The resulting global database should provide a better basis for simulating the interaction of climate change and terrestrial ecosystem dynamics using global vegetation models.

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

Collins, William D; Johansen, Hans; Evans, Katherine J

We present a survey of physical and computational techniques that have the potential to con- tribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth include the capture of remote forcings of localized hydrological extreme events, an accurate representation of cloud features over a range of spatial and temporal scales, and parallel, large ensembles of simulations to more effectively explore model sensitivities and uncertainties. Numerical techniques, such as adaptive mesh refinement, implicit time integration, and separate treatment of fast physical time scales are enabling improved accuracy andmore » fidelity in simulation of dynamics and allow more complete representations of climate features at the global scale. At the same time, part- nerships with computer science teams have focused on taking advantage of evolving computer architectures, such as many-core processors and GPUs, so that these approaches which were previously considered prohibitively costly have become both more efficient and scalable. In combination, progress in these three critical areas is poised to transform climate modeling in the coming decades.« less

The Impact Snow Albedo Feedback over Mountain Regions as Examined through High-Resolution Regional Climate Change Experiments over the Rocky Mountains

NASA Astrophysics Data System (ADS)

Letcher, Theodore

As the climate warms, the snow albedo feedback (SAF) will play a substantial role in shaping the climate response of mid-latitude mountain regions with transient snow cover. One such region is the Rocky Mountains of the western United States where large snow packs accumulate during the winter and persist throughout the spring. In this dissertation, the Weather Research and Forecast model (WRF) configured as a regional climate model is used to investigate the role of the SAF in determining the regional climate response to forced anthropogenic climate change. The regional effects of climate change are investigated by using the pseudo global warming (PGW) framework, which is an experimental configuration in a which a mean climate perturbation is added to the boundary forcing of a regional model, thus preserving the large-scale circulation entering the region through the model boundaries and isolating the mesoscale climate response. Using this framework, the impact of the SAF on the regional energetics and atmospheric dynamics is examined and quantified. Linear feedback analysis is used to quantify the strength of the SAF over the Headwaters region of the Colorado Rockies for a series of high-resolution PGW experiments. This technique is used to test sensitivity of the feedback strength to model resolution and land surface model. Over the Colorado Rockies, and integrated over the entire spring season, the SAF strength is largely insensitive to model resolution, however there are more substantial differences on the sub-seasonal (monthly) timescale. In contrast, the SAF strength over this region is very sensitive to choice of land surface model. These simulations are also used to investigate how spatial and diurnal variability in warming caused by the SAF influences the dynamics of thermally driven mountain-breeze circulations. It is shown that, the SAF causes stronger daytime mountain-breeze circulations by increasing the warming on the mountains slopes thus enhancing the thermal contrast between the mountain slopes and the surrounding lowlands which drives these wind systems. This analysis is extended to investigate the impacts that the SAF has on the large-scale mountain-plain circulation that develops east of the Rockies over the Great Plains. To help isolate the SAF, a more idealized regional climate experiment which isolates the SAF is performed. It was found that SAF may influence thermally driven atmospheric dynamics up-to 200km east of the Mountains where the SAF originates, suggesting broader regional impacts of the SAF which may not be well resolved by coarser resolution global climate models. The implications of these changes on pollution transport and moist convection are also explored using these simulations.

Environmental tipping points significantly affect the cost-benefit assessment of climate policies.

PubMed

Cai, Yongyang; Judd, Kenneth L; Lenton, Timothy M; Lontzek, Thomas S; Narita, Daiju

2015-04-14

Most current cost-benefit analyses of climate change policies suggest an optimal global climate policy that is significantly less stringent than the level required to meet the internationally agreed 2 °C target. This is partly because the sum of estimated economic damage of climate change across various sectors, such as energy use and changes in agricultural production, results in only a small economic loss or even a small economic gain in the gross world product under predicted levels of climate change. However, those cost-benefit analyses rarely take account of environmental tipping points leading to abrupt and irreversible impacts on market and nonmarket goods and services, including those provided by the climate and by ecosystems. Here we show that including environmental tipping point impacts in a stochastic dynamic integrated assessment model profoundly alters cost-benefit assessment of global climate policy. The risk of a tipping point, even if it only has nonmarket impacts, could substantially increase the present optimal carbon tax. For example, a risk of only 5% loss in nonmarket goods that occurs with a 5% annual probability at 4 °C increase of the global surface temperature causes an immediate two-thirds increase in optimal carbon tax. If the tipping point also has a 5% impact on market goods, the optimal carbon tax increases by more than a factor of 3. Hence existing cost-benefit assessments of global climate policy may be significantly underestimating the needs for controlling climate change.

Environmental tipping points significantly affect the cost−benefit assessment of climate policies

PubMed Central

Cai, Yongyang; Judd, Kenneth L.; Lenton, Timothy M.; Lontzek, Thomas S.; Narita, Daiju

2015-01-01

Most current cost−benefit analyses of climate change policies suggest an optimal global climate policy that is significantly less stringent than the level required to meet the internationally agreed 2 °C target. This is partly because the sum of estimated economic damage of climate change across various sectors, such as energy use and changes in agricultural production, results in only a small economic loss or even a small economic gain in the gross world product under predicted levels of climate change. However, those cost−benefit analyses rarely take account of environmental tipping points leading to abrupt and irreversible impacts on market and nonmarket goods and services, including those provided by the climate and by ecosystems. Here we show that including environmental tipping point impacts in a stochastic dynamic integrated assessment model profoundly alters cost−benefit assessment of global climate policy. The risk of a tipping point, even if it only has nonmarket impacts, could substantially increase the present optimal carbon tax. For example, a risk of only 5% loss in nonmarket goods that occurs with a 5% annual probability at 4 °C increase of the global surface temperature causes an immediate two-thirds increase in optimal carbon tax. If the tipping point also has a 5% impact on market goods, the optimal carbon tax increases by more than a factor of 3. Hence existing cost−benefit assessments of global climate policy may be significantly underestimating the needs for controlling climate change. PMID:25825719

Remote sensing of ecosystem vulnerability: Assessing climate-vegetation-livestock interactions in Mongolia

NASA Astrophysics Data System (ADS)

Kang, S.; Hong, S. Y.

2015-12-01

Stock breeding is a major economic sector of Mongolia, supporting unique cultural and social identity. In spite of its long history, contemporary pastoralism increases interventions on climate-vegetation interactions substantially, which results in negative feedbacks to livestock sector. This presentation draws an attention how natural processes of climate and vegetation interact with livestock dynamics. Massive loss of livestock and wildlife animal during winter seasons (dzud) is an endemic climatic disaster in the Central Asia grasslands but the mechanisms are not well understood yet. Recent national-wide sever Dzud occurred during 2009-2010 winter in Mongolia. The dzud mechanisms were investigated by developing a schematic mechanism model on climate-vegetation-livestock interactions and applying it for quantitative statistical analysis. Various remote sensing products were integrated to prepare the status and process variables of the schematic model, including daily temperature, precipitation, evapotranspiration, and primary production and biomass for a period from 2003 to 2010. At a lower level of administration (i.e., 'soum' generally larger than 1000 km2), stepwise multiple regression analysis was conducted to find significant factors of inter-annual livestock change. As results, linear regression models were successfully produced at 70% of soums. Summer and winter variables appeared equally important in controlling livestock dynamics. The primary factor of each soum showed certain regional patterns incident well with climate severity and foraging resource availability (e.g. temperature in north, dryness in south, and NDVI in middle). Regional pattern of herbaceous biodiversity depends on both climate and disturbance (i.e. fire and grazing) gradients but the livestock grazing effect appeared localized normally within 1.5 km from livestock shelter or wells. At a local-scale (i.e. family level smaller than 100 km2), species composition seems to provide useful indicator of grazing pressure, while climate and fire disturbance determined regional pattern of vegetation biodiversity. The results provide a useful premise to devise a satellite-based assessment tool for foraging resource availability and biological regime shift by grazing and climate change in future study.

Alternating high and low climate variability: The context of natural selection and speciation in Plio-Pleistocene hominin evolution.

PubMed

Potts, Richard; Faith, J Tyler

2015-10-01

Interaction of orbital insolation cycles defines a predictive model of alternating phases of high- and low-climate variability for tropical East Africa over the past 5 million years. This model, which is described in terms of climate variability stages, implies repeated increases in landscape/resource instability and intervening periods of stability in East Africa. It predicts eight prolonged (>192 kyr) eras of intensified habitat instability (high variability stages) in which hominin evolutionary innovations are likely to have occurred, potentially by variability selection. The prediction that repeated shifts toward high climate variability affected paleoenvironments and evolution is tested in three ways. In the first test, deep-sea records of northeast African terrigenous dust flux (Sites 721/722) and eastern Mediterranean sapropels (Site 967A) show increased and decreased variability in concert with predicted shifts in climate variability. These regional measurements of climate dynamics are complemented by stratigraphic observations in five basins with lengthy stratigraphic and paleoenvironmental records: the mid-Pleistocene Olorgesailie Basin, the Plio-Pleistocene Turkana and Olduvai Basins, and the Pliocene Tugen Hills sequence and Hadar Basin--all of which show that highly variable landscapes inhabited by hominin populations were indeed concentrated in predicted stages of prolonged high climate variability. Second, stringent null-model tests demonstrate a significant association of currently known first and last appearance datums (FADs and LADs) of the major hominin lineages, suites of technological behaviors, and dispersal events with the predicted intervals of prolonged high climate variability. Palynological study in the Nihewan Basin, China, provides a third test, which shows the occupation of highly diverse habitats in eastern Asia, consistent with the predicted increase in adaptability in dispersing Oldowan hominins. Integration of fossil, archeological, sedimentary, and paleolandscape evidence illustrates the potential influence of prolonged high variability on the origin and spread of critical adaptations and lineages in the evolution of Homo. The growing body of data concerning environmental dynamics supports the idea that the evolution of adaptability in response to climate and overall ecological instability represents a unifying theme in hominin evolutionary history. Published by Elsevier Ltd.

Climate Induced Spillover and Implications for U.S. Security.

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

Tidwell, Vincent C.; Naugle, Asmeret Bier; Backus, George A.

Developing nations incur a greater risk to climate change than the developed world due to poorly managed human/natural resources, unreliable infrastructure and brittle governing/economic institutions. These vulnerabilities often give rise to a climate induced “domino effect” of reduced natural resource production-leading to economic hardship, social unrest, and humanitarian crises. Integral to this cascading set of events is increased human migration, leading to the “spillover” of impacts to adjoining areas with even broader impact on global markets and security. Given the complexity of factors influencing human migration and the resultant spill-over effect, quantitative tools are needed to aid policy analysis. Towardmore » this need, a series of migration models were developed along with a system dynamics model of the spillover effect. The migration decision models were structured according to two interacting paths, one that captured long-term “chronic” impacts related to protracted deteriorating quality of life and a second focused on short-term “acute” impacts of disaster and/or conflict. Chronic migration dynamics were modeled for two different cases; one that looked only at emigration but at a national level for the entire world; and a second that looked at both emigration and immigration but focused on a single nation. Model parameterization for each of the migration models was accomplished through regression analysis using decadal data spanning the period 1960-2010. A similar approach was taken with acute migration dynamics except regression analysis utilized annual data sets limited to a shorter time horizon (2001-2013). The system dynamics spillover model was organized around two broad modules, one simulating the decision dynamics of migration and a second module that treats the changing environmental conditions that influence the migration decision. The environmental module informs the migration decision, endogenously simulating interactions/changes in the economy, labor, population, conflict, water, and food. A regional model focused on Mali in western Africa was used as a test case to demonstrate the efficacy of the model.« less

Vegetation Fires in the Coupled Human-Earth System Under Future Environmental and Policy Perspectives

NASA Astrophysics Data System (ADS)

le page, Y.; Morton, D. C.; Hurtt, G. C.

2013-12-01

Fires play a major role in terrestrial ecosystems dynamics and the carbon cycle. Potential changes in fire regimes due to climate change, land use change, or human management could have substantial ecological, climatic and socio-economic impacts, and have recently been emphasized as a source of uncertainty for policy-makers and climate mitigation cost estimates. Anticipating these interactions thus entails interdisciplinary models. Here we describe the development of a new fire modeling framework, which features the essential integration of climatic, vegetation and anthropogenic drivers. The model is an attempt to realistically account for ignition, spread and termination processes, on a 12-hour time step and at 1 degree spatial resolution globally. Because the quantitative influence of fire drivers on these processes are often poorly constrained, the framework includes an optimization procedure whereby key parameters (e.g. influence of moisture on fire spread, probability of cloud-to-ground lightning flashes to actually ignite a fire, human ignition frequency as a function of land use density) are determined to maximize the agreement between modeled and observed burned area over the past decade. The model performs surprisingly well across all biomes, and shows good agreement on non-optimized features, such as seasonality and fire size, which suggests some potential for robust projections. We couple the model to an integrated assessment model and explore the consequences of mitigation policies, land use decisions and climate change on future fire regimes with a focus on the Amazon basin. The coupled model future projections show that business-as-usual land use expansion would increase the frequency of escaped fires in the remaining forest, especially when combined with models projecting a drier climate. Inversely, climate mitigation policies as projected in the IPCC RCP4.5 scenario achieve synergistic benefits, with increased forest extent, less fire ignitions, and higher moisture levels.

Integrating Biodiversity into Biosphere-Atmosphere Interactions Using Individual-Based Models (IBM)

NASA Astrophysics Data System (ADS)

Wang, B.; Shugart, H. H., Jr.; Lerdau, M.

2017-12-01

A key component regulating complex, nonlinear, and dynamic biosphere-atmosphere interactions is the inherent diversity of biological systems. The model frameworks currently widely used, i.e., Plant Functional Type models) do not even begin to capture the metabolic and taxonomic diversity found in many terrestrial systems. We propose that a transition from PFT-based to individual-based modeling approaches (hereafter referred to as IBM) is essential for integrating biodiversity into research on biosphere-atmosphere interactions. The proposal emerges from our studying the interactions of forests with atmospheric processes in the context of climate change using an individual-based forest volatile organic compounds model, UVAFME-VOC. This individual-based model can explicitly simulate VOC emissions based on an explicit modelling of forest dynamics by computing the growth, death, and regeneration of each individual tree of different species and their competition for light, moisture, and nutrient, from which system-level VOC emissions are simulated by explicitly computing and summing up each individual's emissions. We found that elevated O3 significantly altered the forest dynamics by favoring species that are O3-resistant, which, meanwhile, are producers of isoprene. Such compositional changes, on the one hand, resulted in unsuppressed forest productivity and carbon stock because of the compensation by O3-resistant species. On the other hand, with more isoprene produced arising from increased producers, a possible positive feedback loop between tropospheric O3 and forest thereby emerged. We also found that climate warming will not always stimulate isoprene emissions because warming simultaneously reduces isoprene emissions by causing a decline in the abundance of isoprene-emitting species. These results suggest that species diversity is of great significance and that individual-based modelling strategies should be applied in studying biosphere-atmosphere interactions.

Integration of environmental simulation models with satellite remote sensing and geographic information systems technologies: case studies

USGS Publications Warehouse

Steyaert, Louis T.; Loveland, Thomas R.; Brown, Jesslyn F.; Reed, Bradley C.

1993-01-01

Environmental modelers are testing and evaluating a prototype land cover characteristics database for the conterminous United States developed by the EROS Data Center of the U.S. Geological Survey and the University of Nebraska Center for Advanced Land Management Information Technologies. This database was developed from multi temporal, 1-kilometer advanced very high resolution radiometer (AVHRR) data for 1990 and various ancillary data sets such as elevation, ecological regions, and selected climatic normals. Several case studies using this database were analyzed to illustrate the integration of satellite remote sensing and geographic information systems technologies with land-atmosphere interactions models at a variety of spatial and temporal scales. The case studies are representative of contemporary environmental simulation modeling at local to regional levels in global change research, land and water resource management, and environmental simulation modeling at local to regional levels in global change research, land and water resource management and environmental risk assessment. The case studies feature land surface parameterizations for atmospheric mesoscale and global climate models; biogenic-hydrocarbons emissions models; distributed parameter watershed and other hydrological models; and various ecological models such as ecosystem, dynamics, biogeochemical cycles, ecotone variability, and equilibrium vegetation models. The case studies demonstrate the important of multi temporal AVHRR data to develop to develop and maintain a flexible, near-realtime land cover characteristics database. Moreover, such a flexible database is needed to derive various vegetation classification schemes, to aggregate data for nested models, to develop remote sensing algorithms, and to provide data on dynamic landscape characteristics. The case studies illustrate how such a database supports research on spatial heterogeneity, land use, sensitivity analysis, and scaling issues involving regional extrapolations and parameterizations of dynamic land processes within simulation models.

Universal Inverse Power-Law Distribution for Fractal Fluctuations in Dynamical Systems: Applications for Predictability of Inter-Annual Variability of Indian and USA Region Rainfall

NASA Astrophysics Data System (ADS)

Selvam, A. M.

2017-01-01

Dynamical systems in nature exhibit self-similar fractal space-time fluctuations on all scales indicating long-range correlations and, therefore, the statistical normal distribution with implicit assumption of independence, fixed mean and standard deviation cannot be used for description and quantification of fractal data sets. The author has developed a general systems theory based on classical statistical physics for fractal fluctuations which predicts the following. (1) The fractal fluctuations signify an underlying eddy continuum, the larger eddies being the integrated mean of enclosed smaller-scale fluctuations. (2) The probability distribution of eddy amplitudes and the variance (square of eddy amplitude) spectrum of fractal fluctuations follow the universal Boltzmann inverse power law expressed as a function of the golden mean. (3) Fractal fluctuations are signatures of quantum-like chaos since the additive amplitudes of eddies when squared represent probability densities analogous to the sub-atomic dynamics of quantum systems such as the photon or electron. (4) The model predicted distribution is very close to statistical normal distribution for moderate events within two standard deviations from the mean but exhibits a fat long tail that are associated with hazardous extreme events. Continuous periodogram power spectral analyses of available GHCN annual total rainfall time series for the period 1900-2008 for Indian and USA stations show that the power spectra and the corresponding probability distributions follow model predicted universal inverse power law form signifying an eddy continuum structure underlying the observed inter-annual variability of rainfall. On a global scale, man-made greenhouse gas related atmospheric warming would result in intensification of natural climate variability, seen immediately in high frequency fluctuations such as QBO and ENSO and even shorter timescales. Model concepts and results of analyses are discussed with reference to possible prediction of climate change. Model concepts, if correct, rule out unambiguously, linear trends in climate. Climate change will only be manifested as increase or decrease in the natural variability. However, more stringent tests of model concepts and predictions are required before applications to such an important issue as climate change. Observations and simulations with climate models show that precipitation extremes intensify in response to a warming climate (O'Gorman in Curr Clim Change Rep 1:49-59, 2015).

Uncertainty analysis of vegetation distribution in the northern high latitudes during the 21st century with a dynamic vegetation model

PubMed Central

Jiang, Yueyang; Zhuang, Qianlai; Schaphoff, Sibyll; Sitch, Stephen; Sokolov, Andrei; Kicklighter, David; Melillo, Jerry

2012-01-01

This study aims to assess how high-latitude vegetation may respond under various climate scenarios during the 21st century with a focus on analyzing model parameters induced uncertainty and how this uncertainty compares to the uncertainty induced by various climates. The analysis was based on a set of 10,000 Monte Carlo ensemble Lund-Potsdam-Jena (LPJ) simulations for the northern high latitudes (45oN and polewards) for the period 1900–2100. The LPJ Dynamic Global Vegetation Model (LPJ-DGVM) was run under contemporary and future climates from four Special Report Emission Scenarios (SRES), A1FI, A2, B1, and B2, based on the Hadley Centre General Circulation Model (GCM), and six climate scenarios, X901M, X902L, X903H, X904M, X905L, and X906H from the Integrated Global System Model (IGSM) at the Massachusetts Institute of Technology (MIT). In the current dynamic vegetation model, some parameters are more important than others in determining the vegetation distribution. Parameters that control plant carbon uptake and light-use efficiency have the predominant influence on the vegetation distribution of both woody and herbaceous plant functional types. The relative importance of different parameters varies temporally and spatially and is influenced by climate inputs. In addition to climate, these parameters play an important role in determining the vegetation distribution in the region. The parameter-based uncertainties contribute most to the total uncertainty. The current warming conditions lead to a complexity of vegetation responses in the region. Temperate trees will be more sensitive to climate variability, compared with boreal forest trees and C3 perennial grasses. This sensitivity would result in a unanimous northward greenness migration due to anomalous warming in the northern high latitudes. Temporally, boreal needleleaved evergreen plants are projected to decline considerably, and a large portion of C3 perennial grass is projected to disappear by the end of the 21st century. In contrast, the area of temperate trees would increase, especially under the most extreme A1FI scenario. As the warming continues, the northward greenness expansion in the Arctic region could continue. PMID:22822437

Technology-Driven and Innovative Training for Sustainable Agriculture in The Face of Climate Change

NASA Astrophysics Data System (ADS)

Wishart, D. N.

2015-12-01

Innovative training in 'Sustainable Agriculture' for an increasingly STEM-dependent agricultural sector will require a combination of approaches and technologies for global agricultural production to increase while offsetting climate change. Climate change impacts the water resources of nations as normal global weather patterns are altered during El Nino events. Agricultural curricula must incorporate awareness of 'climate change' in order to find novel ways to (1) assure global food security; (2) improve soil productivity and conservation; (3) improve crop yields and irrigation; (4) inexpensively develop site specific principles of crop management based on variable soil and associated hydrological properties; and (5) improve precision farming. In February 2015, Central State University (CSU), Ohio became an 1890 Land-Grant institution vital to the sustainability of Ohio's agricultural sector. Besides agricultural extension, the agriculture curriculum at CSU integrates multidisciplinary courses in science, technology engineering, agriculture, and mathematics (STEAM). The agriculture program could benefit from a technology-driven, interdisciplinary soil science course that promotes climate change education and climate literacy while being offered in both a blended and collaborative learning environment. The course will focus on the dynamics of microscale to mesoscale processes occurring in farming systems, those of which impact climate change or could be impacted by climate change. Elements of this course will include: climate change webinars; soil-climate interactions; carbon cycling; the balance of carbon fluxes between soil storage and atmosphere; microorganisms and soil carbon storage; paleoclimate and soil forming processes; geophysical techniques used in the characterization of soil horizons; impact of climate change on soil fertility; experiments; and demonstrations.

Designing water demand management schemes using a socio-technical modelling approach.

PubMed

Baki, Sotiria; Rozos, Evangelos; Makropoulos, Christos

2018-05-01

Although it is now widely acknowledged that urban water systems (UWSs) are complex socio-technical systems and that a shift towards a socio-technical approach is critical in achieving sustainable urban water management, still, more often than not, UWSs are designed using a segmented modelling approach. As such, either the analysis focuses on the description of the purely technical sub-system, without explicitly taking into account the system's dynamic socio-economic processes, or a more interdisciplinary approach is followed, but delivered through relatively coarse models, which often fail to provide a thorough representation of the urban water cycle and hence cannot deliver accurate estimations of the hydrosystem's responses. In this work we propose an integrated modelling approach for the study of the complete socio-technical UWS that also takes into account socio-economic and climatic variability. We have developed an integrated model, which is used to investigate the diffusion of household water conservation technologies and its effects on the UWS, under different socio-economic and climatic scenarios. The integrated model is formed by coupling a System Dynamics model that simulates the water technology adoption process, and the Urban Water Optioneering Tool (UWOT) for the detailed simulation of the urban water cycle. The model and approach are tested and demonstrated in an urban redevelopment area in Athens, Greece under different socio-economic scenarios and policy interventions. It is suggested that the proposed approach can establish quantifiable links between socio-economic change and UWS responses and therefore assist decision makers in designing more effective and resilient long-term strategies for water conservation. Copyright © 2017 Elsevier B.V. All rights reserved.

Land-Use Impacts on the Terrestrial Carbon Cycle: An Integrative Tool for Resource Assessment and Planning

NASA Astrophysics Data System (ADS)

Sleeter, B. M.; Liu, J.; Zhu, Z.; Hawbaker, T. J.

2014-12-01

Human land use and natural processes contribute to the ability of ecosystems to store and sequester carbon and offset greenhouse gas emissions. Changes in land use (e.g. agricultural cultivation, timber harvest, urban development, and other land management strategies) and natural processes (e.g. climate, wildfire, disease, storm, and insect outbreak) drive the dynamics of ecosystem carbon pools. These carbon dynamics operate at different spatial and temporal scales, making it challenging to track the changes in a single integrative framework. Landowners, managers, and policy makers require data, information, and tools on the relative contributions of these drivers of ecosystem carbon stocks and fluxes in order to evaluate alternative policies and management strategies designed to increase carbon storage and sequestration. In this paper we explore preliminary results from efforts to simulate changes in ecosystem carbon at ecoregional scales, resulting from anthropogenic land use, wildfire, natural vegetation change, and climate variability under a range of future conditions coherent with a range of global change scenarios. Simulations track the fate of carbon across several pools, including living biomass, deadwood, litter, soil, and wood products. Carbon fluxes are estimated based on simulations from the Integrated Biosphere Simulator model (IBIS). Downscaled land-use projections from the Special Report on Emission Scenarios and Representative Concentration Pathways drive changes in land use, along with extrapolations based on local-scale data. We discuss the sensitivity of the model to individual drivers, and the overall uncertainty associated with the wide range of scenario projections, as well as explore alternative policy and management outcomes and their ability to increase carbon storage in terrestrial ecosystems.

Energy Balance Models and Planetary Dynamics

NASA Technical Reports Server (NTRS)

Domagal-Goldman, Shawn

2012-01-01

We know that planetary dynamics can have a significant affect on the climate of planets. Planetary dynamics dominate the glacial-interglacial periods on Earth, leaving a significant imprint on the geological record. They have also been demonstrated to have a driving influence on the climates of other planets in our solar system. We should therefore expect th.ere to be similar relationships on extrasolar planets. Here we describe a simple energy balance model that can predict the growth and thickness of glaciers, and their feedbacks on climate. We will also describe model changes that we have made to include planetary dynamics effects. This is the model we will use at the start of our collaboration to handle the influence of dynamics on climate.

Climate-induced change of environmentally defined floristic domains: A conservation based vulnerability framework

Treesearch

Debbie Jewitt; Barend F.N. Erasmus; Peter S. Goodman; Timothy G. O' Connor; William W. Hargrove; Damian M. Maddalena; Ed. T.F. Witkowski

2015-01-01

Global climate change is having marked influences on species distributions, phenology and ecosystem composition and raises questions as to the effectiveness of current conservation strategies. Conservation planning has only recently begun to adequately account for dynamic threats such as climate change. We propose a method to incorporate climate-dynamic environmental...

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.

Towards a better understanding of the sensitivity of permafrost and soil carbon to climate and disturbance-induced change in Alaska

NASA Astrophysics Data System (ADS)

Pastick, N. J.; Jorgenson, T.; Wylie, B. K.; Minsley, B. J.; Brown, D. N.; Genet, H.; Johnson, K. D.; McGuire, A. D.; Kass, A.; Knight, J. F.

2015-12-01

Recent increases in air temperature and disturbance activity have led to amplified rates of permafrost degradation and carbon remobilization across portions of Alaska. Further warming, coupled with increases in disturbance frequency and severity (i.e. wildfire, thermokarst), may exacerbate permafrost thaw and disappearance, which would have a profound effect on high-latitude ecological and socio-economic systems. Here we present research aimed at characterizing the sensitivity of different permafrost landscapes to climate and disturbance-induced change through a compilation of in-situ observations, remote sensing and geophysical data, time series analyses, and spatio-temporal modeling. Our data-driven approach allowed for the development of a quantitative assessment of permafrost's potential response to climate change. This analysis also identified indicators of permafrost's susceptibility to disturbances in Alaska. Initial results suggest that further climate-induced permafrost degradation is most likely to occur in regions characterized by discontinuous permafrost and transition zones between tundra, boreal, and temperate forest ecosystems. Permafrost-affected soils, underlying upland ecosystems, are typically more prone to climate and fire-induced change than lowland ecosystems with relatively thicker organic soil layers. However, field and geophysical data indicate that carbon rich silty lowlands are also prone to deep permafrost thaw (> 5 m) following severe disturbance. Because a substantial amount of frozen soil carbon will become susceptible to decomposition upon permafrost thaw, we combined recently developed permafrost carbon maps and future projections of permafrost distribution to highlight areas that may become potential emission hotspots under warmer temperatures. Despite advances in understanding of the drivers of ecological change, more work is needed to integrate studies that link observations of permafrost dynamics to factors that drive those dynamics.

Hydrological changes of DOM composition and biodegradability of rivers in temperate monsoon climates

NASA Astrophysics Data System (ADS)

Shin, Yera; Lee, Eun-Ju; Jeon, Young-Joon; Hur, Jin; Oh, Neung-Hwan

2016-09-01

The spatial and hydrological dynamics of dissolved organic matter (DOM) composition and biodegradability were investigated for the five largest rivers in the Republic of Korea (South Korea) during the years 2012-2013 using incubation experiments and spectroscopic measurements, which included parallel factor analysis (PARAFAC). The lower reaches of the five rivers were selected as windows showing the integrated effects of basin biogeochemistry of different land use under Asian monsoon climates, providing an insight on consistency of DOM dynamics across multiple sites which could be difficult to obtain from a study on an individual river. The mean dissolved organic carbon (DOC) concentrations of the five rivers were relatively low, ranging from 1.4 to 3.4 mg L-1, due to the high slope and low percentage of wetland cover in the basin. Terrestrial humic- and fulvic-like components were dominant in all the rivers except for one, where protein-like compounds were up to ∼80%. However, terrestrial components became dominant in all five of the rivers after high precipitation during the summer monsoon season, indicating the strong role of hydrology on riverine DOM compositions for the basins under Asian monsoon climates. Considering that 64% of South Korea is forested, our results suggest that the forests could be a large source of riverine DOM, elevating the DOM loads during monsoon rainfall. Although more DOM was degraded when DOM input increased, regardless of its sources, the percent biodegradability was reduced with increased proportions of terrestrially derived aromatic compounds. The shift in DOM quality towards higher percentages of aromatic terrestrial compounds may alter the balance of the carbon cycle of coastal ecosystems by changing microbial metabolic processes if climate extremes such as heavy storms and typhoons become more frequent due to climate change.

Integrating ecophysiology and forest landscape models to improve projections of drought effects under climate change.

PubMed

Gustafson, Eric J; De Bruijn, Arjan M G; Pangle, Robert E; Limousin, Jean-Marc; McDowell, Nate G; Pockman, William T; Sturtevant, Brian R; Muss, Jordan D; Kubiske, Mark E

2015-02-01

Fundamental drivers of ecosystem processes such as temperature and precipitation are rapidly changing and creating novel environmental conditions. Forest landscape models (FLM) are used by managers and policy-makers to make projections of future ecosystem dynamics under alternative management or policy options, but the links between the fundamental drivers and projected responses are weak and indirect, limiting their reliability for projecting the impacts of climate change. We developed and tested a relatively mechanistic method to simulate the effects of changing precipitation on species competition within the LANDIS-II FLM. Using data from a field precipitation manipulation experiment in a piñon pine (Pinus edulis) and juniper (Juniperus monosperma) ecosystem in New Mexico (USA), we calibrated our model to measurements from ambient control plots and tested predictions under the drought and irrigation treatments against empirical measurements. The model successfully predicted behavior of physiological variables under the treatments. Discrepancies between model output and empirical data occurred when the monthly time step of the model failed to capture the short-term dynamics of the ecosystem as recorded by instantaneous field measurements. We applied the model to heuristically assess the effect of alternative climate scenarios on the piñon-juniper ecosystem and found that warmer and drier climate reduced productivity and increased the risk of drought-induced mortality, especially for piñon. We concluded that the direct links between fundamental drivers and growth rates in our model hold great promise to improve our understanding of ecosystem processes under climate change and improve management decisions because of its greater reliance on first principles. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Surveying shrimp aquaculture pond activity using multitemporal VHSR satellite images - case study from the Perancak estuary, Bali, Indonesia.

PubMed

Gusmawati, Niken; Soulard, Benoît; Selmaoui-Folcher, Nazha; Proisy, Christophe; Mustafa, Akhmad; Le Gendre, Romain; Laugier, Thierry; Lemonnier, Hugues

2018-06-01

From the 1980's, Indonesian shrimp production has continuously increased through a large expansion of cultured areas and an intensification of the production. As consequences of diseases and environmental degradations linked to this development, there are currently 250,000ha of abandoned ponds in Indonesia. To implement effective procedure to undertake appropriate aquaculture ecosystem assessment and monitoring, an integrated indicator based on four criteria using very high spatial optical satellite images, has been developed to discriminate active from abandoned ponds. These criteria were: presence of water, aerator, feeding bridge and vegetation. This indicator has then been applied to the Perancak estuary, a production area in decline, to highlight the abandonment dynamic between 2001 and 2015. Two risk factors that could contribute to explain dynamics of abandonment were identified: climate conditions and pond locations within the estuary, suggesting that a spatial approach should be integrated in planning processes to operationalize pond rehabilitation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Academic and social integration on campus among sexual minority students: the impacts of psychological and experiential campus climate.

PubMed

Woodford, Michael R; Kulick, Alex

2015-03-01

A heterosexist campus climate can increase risk for mental health problems for sexual minority students; however, the relationship between campus climate for sexual minorities and academic outcomes remains understudied. Using a sample of sexual minority respondents extracted from a campus climate survey conducted at a large university in the Midwest, we examine relationships between multiple dimensions of psychological and experiential campus climate for sexual minorities with academic integration (academic disengagement, grade-point average [GPA]) and social integration (institutional satisfaction, acceptance on campus). We also investigate the protective role of engagement with informal academic and peer-group systems. Findings suggest campus climate affects sexual minority students' integration. In multivariate analyses, perceptions of whether lesbian, gay, and bisexual (LGB) people could be open about their sexual identity was positively associated with acceptance on campus; personal heterosexist harassment was positively associated with academic disengagement and negatively with GPA. Students' informal academic integration (instructor relations) and informal social integration (LGB friends) demonstrated influential main effects but did not moderate any of the climate-outcome relationships. Researchers should further explore the relationships between climate and academic outcomes among sexual minority students, both collectively and among specific sub-groups, and address the role of other protective factors.

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.

Downscaling Future Climate Change Projections for Water Resource Applications: A Case Study for Mesoamerica (Invited)

NASA Astrophysics Data System (ADS)

Oglesby, R. J.; Rowe, C. M.; Munoz-Arriola, F.

2013-12-01

Mesoamerica is a region that is potentially at severe risk due to future climate change. This is especially true for the water resources required for agriculture, human consumption, and hydroelectric power generation. Yet global climate models cannot properly resolve surface climate in the region, due to it's complex topography and nearness to oceans. Precipitation in particular is poorly handled. Further, Mesoamerica is hardly the only region worldwide for which these issues exist. To address this deficiency, a series of high-resolution (4-12 km) dynamical downscaling simulations of future climate change between now and 2060 have been made for Mesoamerica and the Caribbean. We used the Weather Research and Forecasting (WRF) regional climate model to downscale results from the NCAR CCSM4 CMIP5 RCP8.5 global simulation. The entire region is covered at 12 km horizontal spatial resolution, with as much as possible (especially in mountainous regions) at 4 km. We compare a control period (2006-2010) with 50 years into the future (2056-2060). Basic results for surface climate will be presented, as well as a developing strategy for explicitly employing these results in projecting the implications for water resources in the region. Connections will also be made to other regions around the globe that could benefit from this type of integrated modeling and analysis.

Added value of dynamical downscaling of winter seasonal forecasts over North America

NASA Astrophysics Data System (ADS)

Tefera Diro, Gulilat; Sushama, Laxmi

2017-04-01

Skillful seasonal forecasts have enormous potential benefits for socio-economic sectors that are sensitive to weather and climate conditions, as the early warning routines could reduce the vulnerability of such sectors. In this study, individual ensemble members of the ECMWF global ensemble seasonal forecasts are dynamically downscaled to produce ensemble of regional seasonal forecasts over North America using the fifth generation Canadian Regional Climate Model (CRCM5). CRCM5 forecasts are initialized on November 1st of each year and are integrated for four months for the 1991-2001 period at 0.22 degree resolution to produce a one-month lead-time forecast. The initial conditions for atmospheric variables are obtained from ERA-Interim reanalysis, whereas the initial conditions for land surface are obtained from a separate ERA-interim driven CRCM5 simulation with spectral nudging applied to the interior domain. The global and regional ensemble forecasts were then verified to investigate the skill and economic benefits of dynamical downscaling. Results indicate that both the global and regional climate models produce skillful precipitation forecast over the southern Great Plains and eastern coasts of the U.S and skillful temperature forecasts over the northern U.S. and most of Canada. In comparison to ECMWF forecasts, CRCM5 forecasts improved the temperature forecast skill over most part of the domain, but the improvements for precipitation is limited to regions with complex topography, where it improves the frequency of intense daily precipitation. CRCM5 forecast also yields a better economic value compared to ECMWF precipitation forecasts, for users whose cost to loss ratio is smaller than 0.5.

Two-way against one-way nesting for climate downscaling in Europe and the Mediterranean region using LMDZ4

NASA Astrophysics Data System (ADS)

Li, Shan; Li, Laurent; Le Treut, Hervé

2016-04-01

In the 21st century, the estimated surface temperature warming projected by General Circulation Models (GCMs) is between 0.3 and 4.8 °C, depending on the scenario considered. GCMs exhibit a good representation of climate on a global scale, but they are not able to reproduce regional climate processes with the same level of accuracy. Society and policymakers need model projections to define climate change adaptation and mitigation policies on a global, regional and local scale. Climate downscaling is mostly conducted with a regional model nested into the outputs of a global model. This one-way nesting approach is generally used in the climate community without feedbacks from Regional Climate Models (RCMs) to GCMs. This lack of interaction between the two models may affect regional modes of variability, in particular those with a boundary conflict. The objective of this study is to evaluate a two-way nesting configuration that makes an interactive coupling between the RCM and the GCM, an approach against the traditional configuration of one-way nesting system. An additional aim of this work is to examine if the two-way nesting system can improve the RCM performance. The atmospheric component of the IPSL integrated climate model (LMDZ) is configured at both regional (LMDZ-regional) and global (LMDZ-global) scales. The two models have the same configuration for the dynamical framework and the physical forcings. The climatology values of sea surface temperature (SST) are prescribed for the two models. The stretched-grid of LMDZ-global is applied to a region defined by Europe, the Mediterranean, North Africa and Western North Atlantic. To ensure a good statistical significance of results, all simulations last at least 80 years. The nesting process of models is performed by a relaxation procedure of a time scale of 90 minutes. In the case of two-way nesting, the exchange between the two models is every two hours. The relaxation procedure induces a boundary conflict, particularly in the eastern boundary for temperature and geopotential height. A correlation analysis on the synoptic scale evaluates the relationship between the GCM and the RCM. The beginning of the simulations shows a great consistency of the two models. When dominant dynamics apply, RCM inherits most of the GCM signal with a consistent spatial structure. On the contrary, when the atmospheric circulation is weak, there are not that many effects transferred from the GCM to the RCM. When the RCM has its own dynamics, the boundary conflict is more pronounced. Winter season is chosen for the two-way nesting test due to the predominant role of the atmospheric dynamics in winter. The new approach of a two-way nesting system reduces boundary bias, having a influence in some cases in climate model projections. The effect of two-way nesting is enhanced when using a finer grid.

Characterization of the Dynamics of Climate Systems and Identification of Missing Mechanisms Impacting the Long Term Predictive Capabilities of Global Climate Models Utilizing Dynamical Systems Approaches to the Analysis of Observed and Modeled Climate

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

Bhatt, Uma S.; Wackerbauer, Renate; Polyakov, Igor V.

The goal of this research was to apply fractional and non-linear analysis techniques in order to develop a more complete characterization of climate change and variability for the oceanic, sea ice and atmospheric components of the Earth System. This research applied two measures of dynamical characteristics of time series, the R/S method of calculating the Hurst exponent and Renyi entropy, to observational and modeled climate data in order to evaluate how well climate models capture the long-term dynamics evident in observations. Fractional diffusion analysis was applied to ARGO ocean buoy data to quantify ocean transport. Self organized maps were appliedmore » to North Pacific sea level pressure and analyzed in ways to improve seasonal predictability for Alaska fire weather. This body of research shows that these methods can be used to evaluate climate models and shed light on climate mechanisms (i.e., understanding why something happens). With further research, these methods show promise for improving seasonal to longer time scale forecasts of climate.« less

Integrating Climate and Ecosystem-Response Sciences in Temperate Western North American Mountains: The CIRMOUNT Initiative

NASA Astrophysics Data System (ADS)

Millar, C. I.; Fagre, D. B.

2004-12-01

Mountain regions are uniquely sensitive to changes in climate, vulnerable to climate effects on biotic and physical factors of intense social concern, and serve as critical early-warning systems of climate impacts. Escalating demands on western North American (WNA) mountain ecosystems increasingly stress both natural resources and rural community capacities; changes in mountain systems cascade to issues of national concern. Although WNA has long been a focus for climate- and climate-related environmental research, these efforts remain disciplinary and poorly integrated, hindering interpretation into policy and management. Knowledge is further hampered by lack of standardized climate monitoring stations at high-elevations in WNA. An initiative is emerging as the Consortium for Integrated Climate Research in Western Mountains (CIRMOUNT) whose primary goal is to improve knowledge of high-elevation climate systems and to better integrate physical, ecological, and social sciences relevant to climate change, ecosystem response, and natural-resource policy in WNA. CIRMOUNT seeks to focus research on climate variability and ecosystem response (progress in understanding synoptic scale processes) that improves interpretation of linkages between ecosystem functions and human processing (progress in understanding human-environment integration), which in turn would yield applicable information and understanding on key societal issues such as mountains as water towers, biodiversity, carbon forest sinks, and wildland hazards such as fire and forest dieback (progress in understanding ecosystem services and key thresholds). Achieving such integration depends first on implementing a network of high-elevation climate-monitoring stations, and linking these with integrated ecosystem-response studies. Achievements since 2003 include convening the 2004 Mountain Climate Sciences Symposium (1, 2) and several special sessions at technical conferences; initiating a biennial mountain climate research symposium (MTNCLIM), the first to be held in spring 2005; developing a strategy for climate-monitoring in WNA; installing and networking high-elevation (>3000m) climate-monitoring stations; and completing three target regions (Glacier National Park, MT; Sierra Nevada and White Mountains, CA) of the international GLORIA (Global Observation Research Initiative in Alpine Environments) plant-monitoring project, the first in WNA. CIRMOUNT emphasizes integration at the regional scale in WNA, collaborating with and complementing projects such as the Western Mountain Initiative, whose mandate is more targeted than CIRMOUNT's, and global programs such as GLORIA and the international Mountain Research Initiative. Achievement of continuing success in WNA hinges on the capacity to secure long-term funding and institutional investment. (1) See associated URL for paper and poster pdfs (2) Discussing the future of western U.S. mountains, climate change, and ecosystems. EOS 31 August 2004, 85(35), p. 329

Short ensembles: An Efficient Method for Discerning Climate-relevant Sensitivities in Atmospheric General Circulation Models

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

Wan, Hui; Rasch, Philip J.; Zhang, Kai

2014-09-08

This paper explores the feasibility of an experimentation strategy for investigating sensitivities in fast components of atmospheric general circulation models. The basic idea is to replace the traditional serial-in-time long-term climate integrations by representative ensembles of shorter simulations. The key advantage of the proposed method lies in its efficiency: since fewer days of simulation are needed, the computational cost is less, and because individual realizations are independent and can be integrated simultaneously, the new dimension of parallelism can dramatically reduce the turnaround time in benchmark tests, sensitivities studies, and model tuning exercises. The strategy is not appropriate for exploring sensitivitymore » of all model features, but it is very effective in many situations. Two examples are presented using the Community Atmosphere Model version 5. The first example demonstrates that the method is capable of characterizing the model cloud and precipitation sensitivity to time step length. A nudging technique is also applied to an additional set of simulations to help understand the contribution of physics-dynamics interaction to the detected time step sensitivity. In the second example, multiple empirical parameters related to cloud microphysics and aerosol lifecycle are perturbed simultaneously in order to explore which parameters have the largest impact on the simulated global mean top-of-atmosphere radiation balance. Results show that in both examples, short ensembles are able to correctly reproduce the main signals of model sensitivities revealed by traditional long-term climate simulations for fast processes in the climate system. The efficiency of the ensemble method makes it particularly useful for the development of high-resolution, costly and complex climate models.« less

Why geodiversity matters in valuing nature's stage.

PubMed

Hjort, Jan; Gordon, John E; Gray, Murray; Hunter, Malcolm L

2015-06-01

Geodiversity--the variability of Earth's surface materials, forms, and physical processes-is an integral part of nature and crucial for sustaining ecosystems and their services. It provides the substrates, landform mosaics, and dynamic physical processes for habitat development and maintenance. By determining the heterogeneity of the physical environment in conjunction with climate interactions, geodiversity has a crucial influence on biodiversity across a wide range of scales. From a literature review, we identified the diverse values of geodiversity; examined examples of the dependencies of biodiversity on geodiversity at a site-specific scale (for geosites <1 km(2) in area); and evaluated various human-induced threats to geosites and geodiversity. We found that geosites are important to biodiversity because they often support rare or unique biota adapted to distinctive environmental conditions or create a diversity of microenvironments that enhance species richness. Conservation of geodiversity in the face of a range of threats is critical both for effective management of nature's stage and for its own particular values. This requires approaches to nature conservation that integrate climate, biodiversity, and geodiversity at all spatial scales. © 2015 Society for Conservation Biology.

Translating Knowledge: The role of Shared Learning in Bridging the Science-Application Divide

NASA Astrophysics Data System (ADS)

Moench, M.

2014-12-01

As the organizers of this session state: "Understanding and managing our future relation with the Earth requires research and knowledge spanning diverse fields, and integrated, societally-relevant science that is geared toward solutions." In most cases, however, integration is weak and scientific outputs do not match decision maker requirements. As a result, while scientific results may be highly relevant to society that relevance is operationally far from clear. This paper explores the use of shared learning processes to bridge the gap between the evolving body of scientific information on climate change and its relevance for resilience planning in cities across Asia. Examples related to understanding uncertainty, the evolution of scientific knowledge from different sources, and data extraction and presentation are given using experiences generated over five years of work as part of the Rockefeller Foundation supported Asian Cities Climate Change Resilience Network and other programs. Results suggest that processes supporting effective translation of knowledge between different sources and different applications are essential for the identification of solutions that respond to the dynamics and uncertainties inherent in global change processes.

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.

Variance decomposition shows the importance of human-climate feedbacks in the Earth system

NASA Astrophysics Data System (ADS)

Calvin, K. V.; Bond-Lamberty, B. P.; Jones, A. D.; Shi, X.; Di Vittorio, A. V.; Thornton, P. E.

2017-12-01

The human and Earth systems are intricately linked: climate influences agricultural production, renewable energy potential, and water availability, for example, while anthropogenic emissions from industry and land use change alter temperature and precipitation. Such feedbacks have the potential to significantly alter future climate change. Current climate change projections contain significant uncertainties, however, and because Earth System Models do not generally include dynamic human (demography, economy, energy, water, land use) components, little is known about how climate feedbacks contribute to that uncertainty. Here we use variance decomposition of a novel coupled human-earth system model to show that the influence of human-climate feedbacks can be as large as 17% of the total variance in the near term for global mean temperature rise, and 11% in the long term for cropland area. The near-term contribution of energy and land use feedbacks to the climate on global mean temperature rise is as large as that from model internal variability, a factor typically considered in modeling studies. Conversely, the contribution of climate feedbacks to cropland extent, while non-negligible, is less than that from socioeconomics, policy, or model. Previous assessments have largely excluded these feedbacks, with the climate community focusing on uncertainty due to internal variability, scenario, and model and the integrated assessment community focusing on uncertainty due to socioeconomics, technology, policy, and model. Our results set the stage for a new generation of models and hypothesis testing to determine when and how bidirectional feedbacks between human and Earth systems should be considered in future assessments of climate change.

The changing spatio-temporal dynamics of thaw lake development, Seward Peninsula, Alaska.

NASA Astrophysics Data System (ADS)

Cooper, Michael; Rees, Gareth; Bartsch, Annett

2014-05-01

Contemporary anthropogenic climatic warming is having an accelerated, and more pronounced effect upon Arctic regions than any other environment on Earth. Increased surface temperatures have led to widespread permafrost degradation and a shift in dynamics. One landscape manifestation of localised permafrost decay, seen to be ubiquitous across low-lying tundra regions of Alaska, Canada and Siberia, is the thermokarst lake - or 'thaw' lake. These features are seen to be truly dynamic, with a relatively rapid evolution and decay. The exact impacts of climatic perturbation on thaw lake development are in contention; however, recent studies have suggested an increased vulnerability of these features, owing to the susceptibility of the fundamental processes of initiation, expansion and drainage to climatic variation. It is often hypothesised that with current trends, thaw lakes will see a net increase in expansion rate, and areal extent, with a potential for increased drainage events. Increased permafrost thaw and thermokarst activity has also led to shifts in biogeochemical cycles, leading to an amplified release from large carbon reservoirs currently sequestered within permafrost. An example of carbon release exhibited from thaw lakes is that of methane ebullition (gas bubble formation); this has been theorised to have the potential to initiate a major positive climatic feedback leading to a continued rise in global temperatures. Due to the remote nature and large area over which these landforms occur, remotely sensed data has been widely used in order to both accurately classify features and measure change over spatially large and great temporal extents. As well as studies interpreting data collected in the visible and near-infrared spectra, studies have recently made use of radar or microwave products in order to capture imagery avoiding adverse atmospheric conditions, most notably cloud cover. Data from Envisat ASAR operating in Wide Swath Mode was acquired for this study region; however, the core of this research relied upon the analysis of the changing lake morphology using visible and near-infrared spectra from MODIS and Landsat products. This research explored: (1) intra-annual variability of freeze-thaw cycles and resultant effects on thaw lake development; and (2) the spatio-temporal trends and changing dynamism of thaw lake activity. Research presented here within suggests that although climatic trends do indeed influence widespread changes within thaw lake characteristics, site-specific phenomena of sediment type and ice-content and fluvial activity also play integral roles. Understanding and observing changing spatio-temporal dynamics, particularly on an intra-annual basis, has helped to gather more information concerning complex lake processes, and increase the understanding of permafrost decay and thaw lake development.

The Development in modeling Tibetan Plateau Land/Climate Interaction

NASA Astrophysics Data System (ADS)

Xue, Yongkang; Liu, Ye; li, qian; Maheswor Shrestha, Maheswor; Ma, Hsi-Yen; Cox, Peter; Sun, shufen; Koike, Toshio

2015-04-01

Tibetan Plateau (TP) plays an important role in influencing the continental and planetary scale climate, including East Asian and South Asian monsoon, circulation and precipitation over West Pacific and Indian Oceans. The numerical study has identified TP as the area with strongest land/atmosphere interactions over the midlatitude land. The land degradation there has also affected the monsoon precipitation in TP along the monsoon pathway. The water cycle there affects water sources for major Asian river systems, which include the Tarim, Amu Darya, Indus, Ganges, Brahmaputra, Irrawaddy, Salween, Mekong, Yellow, and Yangtze Rivers. Despite the importance of TP land process in the climate system, the TP land surface processes are poorly modeled due to lack of data available for model validation. To better understand, simulate, and project the role of Tibetan Plateau land surface processes, better parameterization of the Tibetan Land surface processes have been developed and evaluated. The recently available field measurement there and satellite observation have greatly helped this development. This paper presents these new developments and preliminary results using the newly developed biophysical/dynamic vegetation model, frozen soil model, and glacier model. In recent CMIP5 simulation, the CMIP5 models with dynamic vegetation model show poor performance in simulating the TP vegetation and climate. To better simulate the TP vegetation condition and its interaction with climate, we have developed biophysical/dynamic vegetation model, the Simplified Simple Biosphere Model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID), based on water, carbon, and energy balance. The simulated vegetation variables are updates, driven by carbon assimilation, allocation, and accumulation, as well as competition between plant functional types. The model has been validated with the station data, including those measured over the TP. The offline SSiB4/TRIFFID is integrated using the observed precipitation and reanalysis-based meteorological forcing from 1948 to 2008 with 1 degree horizontal resolution. The simulated vegetation conditions and surface hydrology are compared well with observational data with some bias, and shows strong decadal and interannual variabilities with a linear trend associated with the global warming. The TP region is covered by both discontinuous and sporadic permafrost with irregular snow layers above. A frozen soil model is developed to take the coupling effect of mass and heat transport into consideration and includes a detailed description of mass balances of volumetric liquid water, ice, as well as vapor content. It also considers contributions' of heat conduction to the energy balance. The model has been extensively tested using a number of TP station data, which included soil temperature and soil water measurements. The results suggest that it is important to include the frozen sol process to adequately simulate the surface energy balance during the freezing and thawing periods and surface temperature variability, including its diurnal variation. Issues in simulating permafrost process will also be addressed. To better understand the glacier variations under climate change scenarios, an integrated modeling system with an energy budget-based multilayer scheme for clean glaciers, a single-layer scheme for debris-covered glaciers and multilayer scheme for seasonal snow over glacier, soil and forest are developed within a distributed biosphere hydrological modeling framework (WEB-DHM-S model). Discharge simulations using this model show good agreement with observations for Hunza River Basin (13,733 km2) in the Karakoram region of Pakistan for three hydrologic years (2002-2004). Flow composition analysis reveals that the runoff regime is strongly controlled by the snow and glacier melt runoff (50% snowmelt and 33% glacier melt) and suggests that both topography and glacier hypsometry play key roles in glacier mass balance. This study provides a basis for potential application of such an integrated model to the entire Hindu-Kush-Karakoram-Himalaya region.

Effect of Integrated Feedback on Classroom Climate of Secondary School Teachers

ERIC Educational Resources Information Center

Patel, Nilesh Kumar

2018-01-01

This study aimed at finding out the effect of Integrated feedback on Classroom climate of secondary school teachers. This research is experimental in nature. Non-equivalent control group design suggested by Stanley and Campbell (1963) was used for the experiment. Integrated feedback was treatment and independent variable, Classroom climate was…

A walk on the wild side: Disturbance dynamics and the conservation and management of European mountain forest ecosystems☆

PubMed Central

Kulakowski, Dominik; Seidl, Rupert; Holeksa, Jan; Kuuluvainen, Timo; Nagel, Thomas A.; Panayotov, Momchil; Svoboda, Miroslav; Thorn, Simon; Vacchiano, Giorgio; Whitlock, Cathy; Wohlgemuth, Thomas; Bebi, Peter

2017-01-01

Mountain forests are among the most important ecosystems in Europe as they support numerous ecological, hydrological, climatic, social, and economic functions. They are unique relatively natural ecosystems consisting of long-lived species in an otherwise densely populated human landscape. Despite this, centuries of intensive forest management in many of these forests have eclipsed evidence of natural processes, especially the role of disturbances in long-term forest dynamics. Recent trends of land abandonment and establishment of protected forests have coincided with a growing interest in managing forests in more natural states. At the same time, the importance of past disturbances highlighted in an emerging body of literature, and recent increasing disturbances due to climate change are challenging long-held views of dynamics in these ecosystems. Here, we synthesize aspects of this Special Issue on the ecology of mountain forest ecosystems in Europe in the context of broader discussions in the field, to present a new perspective on these ecosystems and their natural disturbance regimes. Most mountain forests in Europe, for which long-term data are available, show a strong and long-term effect of not only human land use but also of natural disturbances that vary by orders of magnitude in size and frequency. Although these disturbances may kill many trees, the forests themselves have not been threatened. The relative importance of natural disturbances, land use, and climate change for ecosystem dynamics varies across space and time. Across the continent, changing climate and land use are altering forest cover, forest structure, tree demography, and natural disturbances, including fires, insect outbreaks, avalanches, and wind disturbances. Projected continued increases in forest area and biomass along with continued warming are likely to further promote forest disturbances. Episodic disturbances may foster ecosystem adaptation to the effects of ongoing and future climatic change. Increasing disturbances, along with trends of less intense land use, will promote further increases in coarse woody debris, with cascading positive effects on biodiversity, edaphic conditions, biogeochemical cycles, and increased heterogeneity across a range of spatial scales. Together, this may translate to disturbance-mediated resilience of forest landscapes and increased biodiversity, as long as climate and disturbance regimes remain within the tolerance of relevant species. Understanding ecological variability, even imperfectly, is integral to anticipating vulnerabilities and promoting ecological resilience, especially under growing uncertainty. Allowing some forests to be shaped by natural processes may be congruent with multiple goals of forest management, even in densely settled and developed countries. PMID:28860677

A walk on the wild side: Disturbance dynamics and the conservation and management of European mountain forest ecosystems.

PubMed

Kulakowski, Dominik; Seidl, Rupert; Holeksa, Jan; Kuuluvainen, Timo; Nagel, Thomas A; Panayotov, Momchil; Svoboda, Miroslav; Thorn, Simon; Vacchiano, Giorgio; Whitlock, Cathy; Wohlgemuth, Thomas; Bebi, Peter

2017-03-15

Mountain forests are among the most important ecosystems in Europe as they support numerous ecological, hydrological, climatic, social, and economic functions. They are unique relatively natural ecosystems consisting of long-lived species in an otherwise densely populated human landscape. Despite this, centuries of intensive forest management in many of these forests have eclipsed evidence of natural processes, especially the role of disturbances in long-term forest dynamics. Recent trends of land abandonment and establishment of protected forests have coincided with a growing interest in managing forests in more natural states. At the same time, the importance of past disturbances highlighted in an emerging body of literature, and recent increasing disturbances due to climate change are challenging long-held views of dynamics in these ecosystems. Here, we synthesize aspects of this Special Issue on the ecology of mountain forest ecosystems in Europe in the context of broader discussions in the field, to present a new perspective on these ecosystems and their natural disturbance regimes. Most mountain forests in Europe, for which long-term data are available, show a strong and long-term effect of not only human land use but also of natural disturbances that vary by orders of magnitude in size and frequency. Although these disturbances may kill many trees, the forests themselves have not been threatened. The relative importance of natural disturbances, land use, and climate change for ecosystem dynamics varies across space and time. Across the continent, changing climate and land use are altering forest cover, forest structure, tree demography, and natural disturbances, including fires, insect outbreaks, avalanches, and wind disturbances. Projected continued increases in forest area and biomass along with continued warming are likely to further promote forest disturbances. Episodic disturbances may foster ecosystem adaptation to the effects of ongoing and future climatic change. Increasing disturbances, along with trends of less intense land use, will promote further increases in coarse woody debris, with cascading positive effects on biodiversity, edaphic conditions, biogeochemical cycles, and increased heterogeneity across a range of spatial scales. Together, this may translate to disturbance-mediated resilience of forest landscapes and increased biodiversity, as long as climate and disturbance regimes remain within the tolerance of relevant species. Understanding ecological variability, even imperfectly, is integral to anticipating vulnerabilities and promoting ecological resilience, especially under growing uncertainty. Allowing some forests to be shaped by natural processes may be congruent with multiple goals of forest management, even in densely settled and developed countries.

Bridging the divide: a model-data approach to Polar and Alpine microbiology.

PubMed

Bradley, James A; Anesio, Alexandre M; Arndt, Sandra

2016-03-01

Advances in microbial ecology in the cryosphere continue to be driven by empirical approaches including field sampling and laboratory-based analyses. Although mathematical models are commonly used to investigate the physical dynamics of Polar and Alpine regions, they are rarely applied in microbial studies. Yet integrating modelling approaches with ongoing observational and laboratory-based work is ideally suited to Polar and Alpine microbial ecosystems given their harsh environmental and biogeochemical characteristics, simple trophic structures, distinct seasonality, often difficult accessibility, geographical expansiveness and susceptibility to accelerated climate changes. In this opinion paper, we explain how mathematical modelling ideally complements field and laboratory-based analyses. We thus argue that mathematical modelling is a powerful tool for the investigation of these extreme environments and that fully integrated, interdisciplinary model-data approaches could help the Polar and Alpine microbiology community address some of the great research challenges of the 21st century (e.g. assessing global significance and response to climate change). However, a better integration of field and laboratory work with model design and calibration/validation, as well as a stronger focus on quantitative information is required to advance models that can be used to make predictions and upscale processes and fluxes beyond what can be captured by observations alone. © FEMS 2016.

Bridging the divide: a model-data approach to Polar and Alpine microbiology

PubMed Central

Bradley, James A.; Anesio, Alexandre M.; Arndt, Sandra

2016-01-01

Advances in microbial ecology in the cryosphere continue to be driven by empirical approaches including field sampling and laboratory-based analyses. Although mathematical models are commonly used to investigate the physical dynamics of Polar and Alpine regions, they are rarely applied in microbial studies. Yet integrating modelling approaches with ongoing observational and laboratory-based work is ideally suited to Polar and Alpine microbial ecosystems given their harsh environmental and biogeochemical characteristics, simple trophic structures, distinct seasonality, often difficult accessibility, geographical expansiveness and susceptibility to accelerated climate changes. In this opinion paper, we explain how mathematical modelling ideally complements field and laboratory-based analyses. We thus argue that mathematical modelling is a powerful tool for the investigation of these extreme environments and that fully integrated, interdisciplinary model-data approaches could help the Polar and Alpine microbiology community address some of the great research challenges of the 21st century (e.g. assessing global significance and response to climate change). However, a better integration of field and laboratory work with model design and calibration/validation, as well as a stronger focus on quantitative information is required to advance models that can be used to make predictions and upscale processes and fluxes beyond what can be captured by observations alone. PMID:26832206

IDESSA: An Integrative Decision Support System for Sustainable Rangeland Management in Southern African Savannas

NASA Astrophysics Data System (ADS)

Meyer, Hanna; Authmann, Christian; Dreber, Niels; Hess, Bastian; Kellner, Klaus; Morgenthal, Theunis; Nauss, Thomas; Seeger, Bernhard; Tsvuura, Zivanai; Wiegand, Kerstin

2017-04-01

Bush encroachment is a syndrome of land degradation that occurs in many savannas including those of southern Africa. The increase in density, cover or biomass of woody vegetation often has negative effects on a range of ecosystem functions and services, which are hardly reversible. However, despite its importance, neither the causes of bush encroachment, nor the consequences of different resource management strategies to combat or mitigate related shifts in savanna states are fully understood. The project "IDESSA" (An Integrative Decision Support System for Sustainable Rangeland Management in Southern African Savannas) aims to improve the understanding of the complex interplays between land use, climate patterns and vegetation dynamics and to implement an integrative monitoring and decision-support system for the sustainable management of different savanna types. For this purpose, IDESSA follows an innovative approach that integrates local knowledge, botanical surveys, remote-sensing and machine-learning based time-series of atmospheric and land-cover dynamics, spatially explicit simulation modeling and analytical database management. The integration of the heterogeneous data will be implemented in a user oriented database infrastructure and scientific workflow system. Accessible via web-based interfaces, this database and analysis system will allow scientists to manage and analyze monitoring data and scenario computations, as well as allow stakeholders (e. g. land users, policy makers) to retrieve current ecosystem information and seasonal outlooks. We present the concept of the project and show preliminary results of the realization steps towards the integrative savanna management and decision-support system.

Impact evaluation of green-grey infrastructure interaction on built-space integrity: an emerging perspective to urban ecosystem service.

PubMed

Tiwary, Abhishek; Kumar, Prashant

2014-07-15

This paper evaluates the role of urban green infrastructure (GI) in maintaining integrity of built-space. The latter is considered as a lateral ecosystem function, worth including in future assessments of integrated ecosystem services. The basic tenet is that integrated green-grey infrastructures (GGIs) would have three influences on built-spaces: (i) reduced wind withering from flow deviation; (ii) reduced material corrosion/degeneration from pollution removal; and (iii) act as a biophysical buffer in altering the micro-climate. A case study is presented, combining the features of computational fluid dynamics (CFD) in micro-environmental modelling with the emerging science on interactions of GGIs. The coupled seasonal dynamics of the above three effects are assessed for two building materials (limestone and steel) using the following three scenarios: (i) business as usual (BAU), (ii) summer (REGEN-S), and (iii) winter (REGEN-W). Apparently, integrated ecosystem service from green-grey interaction, as scoped in this paper, has strong seasonal dependence. Compared to BAU our results suggest that REGEN-S leads to slight increment in limestone recession (<10%), mainly from exacerbation in ozone damage, while large reduction in steel recession (up to 37%) is observed. The selection of vegetation species, especially their bVOC emission potential and seasonal foliage profile, appears to play a vital role in determining the impact GI has on the integrity of the neighbouring built-up environment. Copyright © 2014 Elsevier B.V. All rights reserved.

Influence of late Quaternary climate change on present patterns of genetic variation in valley oak, Quercus lobata Née.

PubMed

Gugger, Paul F; Ikegami, Makihiko; Sork, Victoria L

2013-07-01

Phylogeography and ecological niche models (ENMs) suggest that late Quaternary glacial cycles have played a prominent role in shaping present population genetic structure and diversity, but have not applied quantitative methods to dissect the relative contribution of past and present climate vs. other forces. We integrate multilocus phylogeography, climate-based ENMs and multivariate statistical approaches to infer the effects of late Quaternary climate change on contemporary genetic variation of valley oak (Quercus lobata Née). ENMs indicated that valley oak maintained a stable distribution with local migration from the last interglacial period (~120 ka) to the Last Glacial Maximum (~21 ka, LGM) to the present compared with large-scale range shifts for an eastern North American white oak (Quercus alba L.). Coast Range and Sierra Nevada foothill populations diverged in the late Pleistocene before the LGM [104 ka (28-1622)] and have occupied somewhat distinct climate niches, according to ENMs and coalescent analyses of divergence time. In accordance with neutral expectations for stable populations, nuclear microsatellite diversity positively correlated with niche stability from the LGM to present. Most strikingly, nuclear and chloroplast microsatellite variation significantly correlated with LGM climate, even after controlling for associations with geographic location and present climate using partial redundancy analyses. Variance partitioning showed that LGM climate uniquely explains a similar proportion of genetic variance as present climate (16% vs. 11-18%), and together, past and present climate explains more than geography (19%). Climate can influence local expansion-contraction dynamics, flowering phenology and thus gene flow, and/or impose selective pressures. These results highlight the lingering effect of past climate on genetic variation in species with stable distributions. © 2013 John Wiley & Sons Ltd.

An integrated soil-crop system model for water and nitrogen management in North China

PubMed Central

Liang, Hao; Hu, Kelin; Batchelor, William D.; Qi, Zhiming; Li, Baoguo

2016-01-01

An integrated model WHCNS (soil Water Heat Carbon Nitrogen Simulator) was developed to assess water and nitrogen (N) management in North China. It included five main modules: soil water, soil temperature, soil carbon (C), soil N, and crop growth. The model integrated some features of several widely used crop and soil models, and some modifications were made in order to apply the WHCNS model under the complex conditions of intensive cropping systems in North China. The WHCNS model was evaluated using an open access dataset from the European International Conference on Modeling Soil Water and N Dynamics. WHCNS gave better estimations of soil water and N dynamics, dry matter accumulation and N uptake than 14 other models. The model was tested against data from four experimental sites in North China under various soil, crop, climate, and management practices. Simulated soil water content, soil nitrate concentrations, crop dry matter, leaf area index and grain yields all agreed well with measured values. This study indicates that the WHCNS model can be used to analyze and evaluate the effects of various field management practices on crop yield, fate of N, and water and N use efficiencies in North China. PMID:27181364

WIFIRE: A Scalable Data-Driven Monitoring, Dynamic Prediction and Resilience Cyberinfrastructure for Wildfires

NASA Astrophysics Data System (ADS)

Altintas, I.; Block, J.; Braun, H.; de Callafon, R. A.; Gollner, M. J.; Smarr, L.; Trouve, A.

2013-12-01

Recent studies confirm that climate change will cause wildfires to increase in frequency and severity in the coming decades especially for California and in much of the North American West. The most critical sustainability issue in the midst of these ever-changing dynamics is how to achieve a new social-ecological equilibrium of this fire ecology. Wildfire wind speeds and directions change in an instant, and first responders can only be effective when they take action as quickly as the conditions change. To deliver information needed for sustainable policy and management in this dynamically changing fire regime, we must capture these details to understand the environmental processes. We are building an end-to-end cyberinfrastructure (CI), called WIFIRE, for real-time and data-driven simulation, prediction and visualization of wildfire behavior. The WIFIRE integrated CI system supports social-ecological resilience to the changing fire ecology regime in the face of urban dynamics and climate change. Networked observations, e.g., heterogeneous satellite data and real-time remote sensor data is integrated with computational techniques in signal processing, visualization, modeling and data assimilation to provide a scalable, technological, and educational solution to monitor weather patterns to predict a wildfire's Rate of Spread. Our collaborative WIFIRE team of scientists, engineers, technologists, government policy managers, private industry, and firefighters architects implement CI pathways that enable joint innovation for wildfire management. Scientific workflows are used as an integrative distributed programming model and simplify the implementation of engineering modules for data-driven simulation, prediction and visualization while allowing integration with large-scale computing facilities. WIFIRE will be scalable to users with different skill-levels via specialized web interfaces and user-specified alerts for environmental events broadcasted to receivers before, during and after a wildfire. Scalability of the WIFIRE approach allows many sensors to be subjected to user-specified data processing algorithms to generate threshold alerts within seconds. Integration of this sensor data into both rapidly available fire image data and models will better enable situational awareness, responses and decision support at local, state, national, and international levels. The products of WIFIRE will be initially disseminated to our collaborators (SDG&E, CAL FIRE, USFS), covering academic, private, and government laboratories while generating values to emergency officials, and consequently to the general public. WIFIRE may be used by government agencies in the future to save lives and property during wildfire events, test the effectiveness of response and evacuation scenarios before they occur and assess the effectiveness of high-density sensor networks in improving fire and weather predictions. WIFIRE's high-density network, therefore, will serve as a testbed for future applications worldwide.

The mediating role of integration of safety by activity versus operator between organizational culture and safety climate.

PubMed

Auzoult, Laurent; Gangloff, Bernard

2018-04-20

In this study, we analyse the impact of the organizational culture and introduce a new variable, the integration of safety, which relates to the modalities for the implementation and adoption of safety in the work process, either through the activity or by the operator. One hundred and eighty employees replied to a questionnaire measuring the organizational climate, the safety climate and the integration of safety. We expected that implementation centred on the activity or on the operator would mediate the relationship between the organizational culture and the safety climate. The results support our assumptions. A regression analysis highlights the positive impact on the safety climate of organizational values of the 'rule' and 'support' type, as well as of integration by the operator and activity. Moreover, integration mediates the relation between these variables. The results suggest to take into account organizational culture and to introduce different implementation modalities to improve the safety climate.

Detecting changes in forced climate attractors with Wasserstein distance

NASA Astrophysics Data System (ADS)

Robin, Yoann; Yiou, Pascal; Naveau, Philippe

2017-07-01

The climate system can been described by a dynamical system and its associated attractor. The dynamics of this attractor depends on the external forcings that influence the climate. Such forcings can affect the mean values or variances, but regions of the attractor that are seldom visited can also be affected. It is an important challenge to measure how the climate attractor responds to different forcings. Currently, the Euclidean distance or similar measures like the Mahalanobis distance have been favored to measure discrepancies between two climatic situations. Those distances do not have a natural building mechanism to take into account the attractor dynamics. In this paper, we argue that a Wasserstein distance, stemming from optimal transport theory, offers an efficient and practical way to discriminate between dynamical systems. After treating a toy example, we explore how the Wasserstein distance can be applied and interpreted to detect non-autonomous dynamics from a Lorenz system driven by seasonal cycles and a warming trend.

Linking crop yield anomalies to large-scale atmospheric circulation in Europe.

PubMed

Ceglar, Andrej; Turco, Marco; Toreti, Andrea; Doblas-Reyes, Francisco J

2017-06-15

Understanding the effects of climate variability and extremes on crop growth and development represents a necessary step to assess the resilience of agricultural systems to changing climate conditions. This study investigates the links between the large-scale atmospheric circulation and crop yields in Europe, providing the basis to develop seasonal crop yield forecasting and thus enabling a more effective and dynamic adaptation to climate variability and change. Four dominant modes of large-scale atmospheric variability have been used: North Atlantic Oscillation, Eastern Atlantic, Scandinavian and Eastern Atlantic-Western Russia patterns. Large-scale atmospheric circulation explains on average 43% of inter-annual winter wheat yield variability, ranging between 20% and 70% across countries. As for grain maize, the average explained variability is 38%, ranging between 20% and 58%. Spatially, the skill of the developed statistical models strongly depends on the large-scale atmospheric variability impact on weather at the regional level, especially during the most sensitive growth stages of flowering and grain filling. Our results also suggest that preceding atmospheric conditions might provide an important source of predictability especially for maize yields in south-eastern Europe. Since the seasonal predictability of large-scale atmospheric patterns is generally higher than the one of surface weather variables (e.g. precipitation) in Europe, seasonal crop yield prediction could benefit from the integration of derived statistical models exploiting the dynamical seasonal forecast of large-scale atmospheric circulation.

Toward A Science of Sustainable Water Management

NASA Astrophysics Data System (ADS)

Brown, C.

2016-12-01

Societal need for improved water management and concerns for the long-term sustainability of water resources systems are prominent around the world. The continued susceptibility of society to the harmful effects of hydrologic variability, pervasive concerns related to climate change and the emergent awareness of devastating effects of current practice on aquatic ecosystems all illustrate our limited understanding of how water ought to be managed in a dynamic world. The related challenges of resolving the competition for freshwater among competing uses (so called "nexus" issues) and adapting water resources systems to climate change are prominent examples of the of sustainable water management challenges. In addition, largely untested concepts such as "integrated water resources management" have surfaced as Sustainable Development Goals. In this presentation, we argue that for research to improve water management, and for practice to inspire better research, a new focus is required, one that bridges disciplinary barriers between the water resources research focus on infrastructure planning and management, and the role of human actors, and geophysical sciences community focus on physical processes in the absence of dynamical human response. Examples drawn from climate change adaptation for water resource systems and groundwater management policy provide evidence of initial progress towards a science of sustainable water management that links improved physical understanding of the hydrological cycle with the socioeconomic and ecological understanding of water and societal interactions.

Development of a Permafrost Modeling Cyberinfrastructure

NASA Astrophysics Data System (ADS)

Overeem, I.; Jafarov, E. E.; Piper, M.; Schaefer, K. M.

2016-12-01

Permafrost is seen as an essential Arctic climate indicator, and feedback of thawing permafrost to the global climate system through the impacts on the global carbon cycle remain an important research topic. Observations can assess the current state of permafrost, but models are eventually essential to make predictions of future permafrost extent. The purpose of our project, which we call PermaModel, is to develop an easy-to-access and comprehensive cyberinfrastructure aimed at promoting and improving permafrost modeling. The PermaModel Integrated Modeling Toolbox (IMT) includes three permafrost models of increasing complexity. The IMT will be housed within the existing cyberinfrastructure of the Community Surface Dynamics Modeling System (CSDMS), and made publically accessible through the CSDMS Web Modeling Tool (WMT). The WMT will provide easy online access to students, scientists, and stakeholders who want to use permafrost models, but lack the expertise. We plan to include multiple sets of sample inputs, representing a variety of conditions and locations, to enable immediate use of the IMT. We present here the first permafrost model, which is envisioned to be the most suitable for teaching purposes. The model promotes understanding of a 1D heat equation and permafrost active layer dynamics under monthly temperature/climate drivers in an online environment. Modeling labs are presented through the CSDMS Educational Repository and we solicit feedback from faculty for further design of these resources.

Application of a coupled vegetation competition and groundwater simulation model to study effects of sea level rise and storm surges on coastal vegetation

USGS Publications Warehouse

Teh, Su Yean; Turtora, Michael; DeAngelis, Donald L.; Jiang Jiang,; Pearlstine, Leonard G.; Smith, Thomas; Koh, Hock Lye

2015-01-01

Global climate change poses challenges to areas such as low-lying coastal zones, where sea level rise (SLR) and storm-surge overwash events can have long-term effects on vegetation and on soil and groundwater salinities, posing risks of habitat loss critical to native species. An early warning system is urgently needed to predict and prepare for the consequences of these climate-related impacts on both the short-term dynamics of salinity in the soil and groundwater and the long-term effects on vegetation. For this purpose, the U.S. Geological Survey’s spatially explicit model of vegetation community dynamics along coastal salinity gradients (MANHAM) is integrated into the USGS groundwater model (SUTRA) to create a coupled hydrology–salinity–vegetation model, MANTRA. In MANTRA, the uptake of water by plants is modeled as a fluid mass sink term. Groundwater salinity, water saturation and vegetation biomass determine the water available for plant transpiration. Formulations and assumptions used in the coupled model are presented. MANTRA is calibrated with salinity data and vegetation pattern for a coastal area of Florida Everglades vulnerable to storm surges. A possible regime shift at that site is investigated by simulating the vegetation responses to climate variability and disturbances, including SLR and storm surges based on empirical information.

Modeling ecohydrological impacts of land management and water use in the Silver Creek basin, Idaho

NASA Astrophysics Data System (ADS)

Loinaz, Maria C.; Gross, Dayna; Unnasch, Robert; Butts, Michael; Bauer-Gottwein, Peter

2014-03-01

A number of anthropogenic stressors, including land use change and intensive water use, have caused stream habitat deterioration in arid and semiarid climates throughout the western U.S. These often contribute to high stream temperatures, a widespread water quality problem. Stream temperature is an important indicator of stream ecosystem health and is affected by catchment-scale climate and hydrological processes, morphology, and riparian vegetation. To properly manage affected systems and achieve ecosystem sustainability, it is important to understand the relative impact of these factors. In this study, we predict relative impacts of different stressors using an integrated catchment-scale ecohydrological model that simulates hydrological processes, stream temperature, and fish growth. This type of model offers a suitable measure of ecosystem services because it provides information about the reproductive capability of fish under different conditions. We applied the model to Silver Creek, Idaho, a stream highly valued for its world-renowned trout fishery. The simulations indicated that intensive water use by agriculture and climate change are both major contributors to habitat degradation in the study area. Agricultural practices that increase water use efficiency and mitigate drainage runoff are feasible and can have positive impacts on the ecosystem. All of the mitigation strategies simulated reduced stream temperatures to varying degrees; however, not all resulted in increases in fish growth. The results indicate that temperature dynamics, rather than point statistics, determine optimal growth conditions for fish. Temperature dynamics are influenced by surface water-groundwater interactions. Combined restoration strategies that can achieve ecosystem stability under climate change should be further explored.

Changing Amazon biomass and the role of atmospheric CO2 concentration, climate, and land use

NASA Astrophysics Data System (ADS)

Almeida Castanho, Andrea D.; Galbraith, David; Zhang, Ke; Coe, Michael T.; Costa, Marcos H.; Moorcroft, Paul

2016-01-01

The Amazon tropical evergreen forest is an important component of the global carbon budget. Its forest floristic composition, structure, and function are sensitive to changes in climate, atmospheric composition, and land use. In this study biomass and productivity simulated by three dynamic global vegetation models (Integrated Biosphere Simulator, Ecosystem Demography Biosphere Model, and Joint UK Land Environment Simulator) for the period 1970-2008 are compared with observations from forest plots (Rede Amazónica de Inventarios Forestales). The spatial variability in biomass and productivity simulated by the DGVMs is low in comparison to the field observations in part because of poor representation of the heterogeneity of vegetation traits within the models. We find that over the last four decades the CO2 fertilization effect dominates a long-term increase in simulated biomass in undisturbed Amazonian forests, while land use change in the south and southeastern Amazonia dominates a reduction in Amazon aboveground biomass, of similar magnitude to the CO2 biomass gain. Climate extremes exert a strong effect on the observed biomass on short time scales, but the models are incapable of reproducing the observed impacts of extreme drought on forest biomass. We find that future improvements in the accuracy of DGVM predictions will require improved representation of four key elements: (1) spatially variable plant traits, (2) soil and nutrients mediated processes, (3) extreme event mortality, and (4) sensitivity to climatic variability. Finally, continued long-term observations and ecosystem-scale experiments (e.g. Free-Air CO2 Enrichment experiments) are essential for a better understanding of the changing dynamics of tropical forests.

Predicting Changes in Arctic Tundra Vegetation: Towards an Understanding of Plant Trait Uncertainty

NASA Astrophysics Data System (ADS)

Euskirchen, E. S.; Serbin, S.; Carman, T.; Iversen, C. M.; Salmon, V.; Helene, G.; McGuire, A. D.

2017-12-01

Arctic tundra plant communities are currently undergoing unprecedented changes in both composition and distribution under a warming climate. Predicting how these dynamics may play out in the future is important since these vegetation shifts impact both biogeochemical and biogeophysical processes. More precise estimates of these future vegetation shifts is a key challenge due to both a scarcity of data with which to parameterize vegetation models, particularly in the Arctic, as well as a limited understanding of the importance of each of the model parameters and how they may vary over space and time. Here, we incorporate newly available field data from arctic Alaska into a dynamic vegetation model specifically developed to take into account a particularly wide array of plant species as well as the permafrost soils of the arctic tundra (the Terrestrial Ecosystem Model with Dynamic Vegetation and Dynamic Organic Soil, Terrestrial Ecosystem Model; DVM-DOS-TEM). We integrate the model within the Predicative Ecosystem Analyzer (PEcAn), an open-source integrated ecological bioinformatics toolbox that facilitates the flows of information into and out of process models and model-data integration. We use PEcAn to evaluate the plant functional traits that contribute most to model variability based on a sensitivity analysis. We perform this analysis for the dominant types of tundra in arctic Alaska, including heath, shrub, tussock and wet sedge tundra. The results from this analysis will help inform future data collection in arctic tundra and reduce model uncertainty, thereby improving our ability to simulate Arctic vegetation structure and function in response to global change.

An integrated model for assessing both crop productivity and agricultural water resources at a large scale

NASA Astrophysics Data System (ADS)

Okada, M.; Sakurai, G.; Iizumi, T.; Yokozawa, M.

2012-12-01

Agricultural production utilizes regional resources (e.g. river water and ground water) as well as local resources (e.g. temperature, rainfall, solar energy). Future climate changes and increasing demand due to population increases and economic developments would intensively affect the availability of water resources for agricultural production. While many studies assessed the impacts of climate change on agriculture, there are few studies that dynamically account for changes in water resources and crop production. This study proposes an integrated model for assessing both crop productivity and agricultural water resources at a large scale. Also, the irrigation management to subseasonal variability in weather and crop response varies for each region and each crop. To deal with such variations, we used the Markov Chain Monte Carlo technique to quantify regional-specific parameters associated with crop growth and irrigation water estimations. We coupled a large-scale crop model (Sakurai et al. 2012), with a global water resources model, H08 (Hanasaki et al. 2008). The integrated model was consisting of five sub-models for the following processes: land surface, crop growth, river routing, reservoir operation, and anthropogenic water withdrawal. The land surface sub-model was based on a watershed hydrology model, SWAT (Neitsch et al. 2009). Surface and subsurface runoffs simulated by the land surface sub-model were input to the river routing sub-model of the H08 model. A part of regional water resources available for agriculture, simulated by the H08 model, was input as irrigation water to the land surface sub-model. The timing and amount of irrigation water was simulated at a daily step. The integrated model reproduced the observed streamflow in an individual watershed. Additionally, the model accurately reproduced the trends and interannual variations of crop yields. To demonstrate the usefulness of the integrated model, we compared two types of impact assessment of climate change on crop productivity in a watershed. The first was carried out by the large-scale crop model alone. The second was carried out by the integrated model of the large-scale crop model and the H08 model. The former projected that changes in temperature and precipitation due to future climate change would give rise to increasing the water stress in crops. Nevertheless, the latter projected that the increasing amount of agricultural water resources in the watershed would supply sufficient amount of water for irrigation, consequently reduce the water stress. The integrated model demonstrated the importance of taking into account the water circulation in watershed when predicting the regional crop production.

The Consortium for Integrated Climate Research in Western Mountains (CIRMOUNT)

Treesearch

Constance I. Millar

2004-01-01

I represent a nascent effort in western North America that is committed to improving integration of climate-related research and its societal implications. We go under the name of CIRMOUNT, that is, Consortium for Integrated Climate-Related Research in Western North American Mountains. In a sense, CIRMOUNT is a North American answer (in the affirmative) to Thomas...

Local and cross-seasonal associations of climate and land use with abundance of monarch butterflies Danaus plexippus

USGS Publications Warehouse

Saunders, Sarah P.; Ries, Leslie; Oberhasuer, Karen S.; Thogmartin, Wayne E.; Zipkin, Elise F.

2017-01-01

Quantifying how climate and land use factors drive population dynamics at regional scales is complex because it depends on the extent of spatial and temporal synchrony among local populations, and the integration of population processes throughout a species’ annual cycle. We modeled weekly, site-specific summer abundance (1994–2013) of monarch butterflies Danaus plexippus at sites across Illinois, USA to assess relative associations of monarch abundance with climate and land use variables during the winter, spring, and summer stages of their annual cycle. We developed negative binomial regression models to estimate monarch abundance during recruitment in Illinois as a function of local climate, site-specific crop cover, and county-level herbicide (glyphosate) application. We also incorporated cross-seasonal covariates, including annual abundance of wintering monarchs in Mexico and climate conditions during spring migration and breeding in Texas, USA. We provide the first empirical evidence of a negative association between county-level glyphosate application and local abundance of adult monarchs, particularly in areas of concentrated agriculture. However, this association was only evident during the initial years of the adoption of herbicide-resistant crops (1994–2003). We also found that wetter and, to a lesser degree, cooler springs in Texas were associated with higher summer abundances in Illinois, as were relatively cool local summer temperatures in Illinois. Site-specific abundance of monarchs averaged approximately one fewer per site from 2004–2013 than during the previous decade, suggesting a recent decline in local abundance of monarch butterflies on their summer breeding grounds in Illinois. Our results demonstrate that seasonal climate and land use are associated with trends in adult monarch abundance, and our approach highlights the value of considering fine-resolution temporal fluctuations in population-level responses to environmental conditions when inferring the dynamics of migratory species.

Projecting water yield and ecosystem productivity across the United States by linking an ecohydrological model to WRF dynamically downscaled climate data

NASA Astrophysics Data System (ADS)

Sun, Shanlei; Sun, Ge; Cohen, Erika; McNulty, Steven G.; Caldwell, Peter V.; Duan, Kai; Zhang, Yang

2016-03-01

Quantifying the potential impacts of climate change on water yield and ecosystem productivity is essential to developing sound watershed restoration plans, and ecosystem adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model) using dynamically downscaled climate data of the HadCM3 model under the IPCC SRES A2 emission scenario. We evaluated the future (2031-2060) changes in evapotranspiration (ET), water yield (Q) and gross primary productivity (GPP) from the baseline period of 1979-2007 across the 82 773 watersheds (12-digit Hydrologic Unit Code level) in the coterminous US (CONUS). Across the CONUS, the future multi-year means show increases in annual precipitation (P) of 45 mm yr-1 (6 %), 1.8° C increase in temperature (T), 37 mm yr-1 (7 %) increase in ET, 9 mm yr-1 (3 %) increase in Q, and 106 gC m-2 yr-1 (9 %) increase in GPP. We found a large spatial variability in response to climate change across the CONUS 12-digit HUC watersheds, but in general, the majority would see consistent increases all variables evaluated. Over half of the watersheds, mostly found in the northeast and the southern part of the southwest, would see an increase in annual Q (> 100 mm yr-1 or 20 %). In addition, we also evaluated the future annual and monthly changes of hydrology and ecosystem productivity for the 18 Water Resource Regions (WRRs) or two-digit HUCs. The study provides an integrated method and example for comprehensive assessment of the potential impacts of climate change on watershed water balances and ecosystem productivity at high spatial and temporal resolutions. Results may be useful for policy-makers and land managers to formulate appropriate watershed-specific strategies for sustaining water and carbon sources in the face of climate change.

A dynamic viticultural zoning to explore the resilience of terroir concept under climate change.

PubMed

Bonfante, A; Monaco, E; Langella, G; Mercogliano, P; Bucchignani, E; Manna, P; Terribile, F

2018-05-15

Climate change (CC) directly influences agricultural sectors, presenting the need to identify both adaptation and mitigation actions that can make local farming communities and crop production more resilient. In this context, the viticultural sector is one of those most challenged by CC due to the need to combine grape quality, grapevine cultivar adaptation and therefore farmers' future incomes. Thus, understanding how suitability for viticulture is changing under CC is of primary interest in the development of adaptation strategies in traditional wine-growing regions. Considering that climate is an essential part of the terroir system, the expected variability in climate change could have a marked influence on terroir resilience with important effects on local farming communities in viticultural regions. From this perspective, the aim of this paper is to define a new dynamic viticultural zoning procedure that is able to integrate the effects of CC on grape quality responses and evaluate terroir resilience, providing a support tool for stakeholders involved in viticultural planning (winegrowers, winegrower consortiums, policy makers etc.). To achieve these aims, a Hybrid Land Evaluation System, combining qualitative (standard Land Evaluation) and quantitative (simulation model) approaches, was applied within a traditional region devoted to high quality wine production in Southern Italy (Valle Telesina, BN), for a specific grapevine cultivar (Aglianico). The work employed high resolution climate projections that were derived under two different IPCC scenarios, namely RCP 4.5 and RCP 8.5. The results obtained indicate that: (i) only 2% of the suitable area of Valle Telesina expresses the concept of terroir resilience orientated towards Aglianico ultra quality grape production; (ii) within 2010-2040, it is expected that 41% of the area suitable for Aglianico cultivation will need irrigation to achieve quality grape production; (iii) by 2100, climate change benefits for the cultivation of Aglianico will decrease, as well as the suitable areas. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed

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

2018-03-01

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

Using Virtualization to Integrate Weather, Climate, and Coastal Science Education

NASA Astrophysics Data System (ADS)

Davis, J. R.; Paramygin, V. A.; Figueiredo, R.; Sheng, Y.

2012-12-01

To better understand and communicate the important roles of weather and climate on the coastal environment, a unique publically available tool is being developed to support research, education, and outreach activities. This tool uses virtualization technologies to facilitate an interactive, hands-on environment in which students, researchers, and general public can perform their own numerical modeling experiments. While prior efforts have focused solely on the study of the coastal and estuary environments, this effort incorporates the community supported weather and climate model (WRF-ARW) into the Coastal Science Educational Virtual Appliance (CSEVA), an education tool used to assist in the learning of coastal transport processes; storm surge and inundation; and evacuation modeling. The Weather Research and Forecasting (WRF) Model is a next-generation, community developed and supported, mesoscale numerical weather prediction system designed to be used internationally for research, operations, and teaching. It includes two dynamical solvers (ARW - Advanced Research WRF and NMM - Nonhydrostatic Mesoscale Model) as well as a data assimilation system. WRF-ARW is the ARW dynamics solver combined with other components of the WRF system which was developed primarily at NCAR, community support provided by the Mesoscale and Microscale Meteorology (MMM) division of National Center for Atmospheric Research (NCAR). Included with WRF is the WRF Pre-processing System (WPS) which is a set of programs to prepare input for real-data simulations. The CSEVA is based on the Grid Appliance (GA) framework and is built using virtual machine (VM) and virtual networking technologies. Virtualization supports integration of an operating system, libraries (e.g. Fortran, C, Perl, NetCDF, etc. necessary to build WRF), web server, numerical models/grids/inputs, pre-/post-processing tools (e.g. WPS / RIP4 or UPS), graphical user interfaces, "Cloud"-computing infrastructure and other tools into a single ready-to-use package. Thus, the previous ornery task of setting up and compiling these tools becomes obsolete and the research, educator or student can focus on using the tools to study the interactions between weather, climate and the coastal environment. The incorporation of WRF into the CSEVA has been designed to be synergistic with the extensive online tutorials and biannual tutorials hosted by NCAR. Included are working examples of the idealized test simulations provided with WRF (2D sea breeze and squalls, a large eddy simulation, a Held and Suarez simulation, etc.) To demonstrate the integration of weather, coastal and coastal science education, example applications are being developed to demonstrate how the system can be used to couple a coastal and estuarine circulation, transport and storm surge model with downscale reanalysis weather and future climate predictions. Documentation, tutorials and the enhanced CSEVA itself will be found on the web at: http://cseva.coastal.ufl.edu.

Improved Rainfall Estimates and Predictions for 21st Century Drought Early Warning

NASA Technical Reports Server (NTRS)

Funk, Chris; Peterson, Pete; Shukla, Shraddhanand; Husak, Gregory; Landsfeld, Marty; Hoell, Andrew; Pedreros, Diego; Roberts, J. B.; Robertson, F. R.; Tadesse, Tsegae;

Probabilistic Integrated Assessment of ``Dangerous'' Climate Change

NASA Astrophysics Data System (ADS)

Mastrandrea, Michael D.; Schneider, Stephen H.

2004-04-01

Climate policy decisions are being made despite layers of uncertainty. Such decisions directly influence the potential for ``dangerous anthropogenic interference with the climate system.'' We mapped a metric for this concept, based on Intergovernmental Panel on Climate Change assessment of climate impacts, onto probability distributions of future climate change produced from uncertainty in key parameters of the coupled social-natural system-climate sensitivity, climate damages, and discount rate. Analyses with a simple integrated assessment model found that, under midrange assumptions, endogenously calculated, optimal climate policy controls can reduce the probability of dangerous anthropogenic interference from ~45% under minimal controls to near zero.

Novel approaches to reducing uncertainty in regional climate predictions (Invited)

NASA Astrophysics Data System (ADS)

Ammann, C. M.

2009-12-01

Regional planning in preparation for future climate changes is rapidly gaining importance. However, compared to the global mean projections, correctly anticipating regional climate is often much more difficult, particularly with regard to hydrologic changes. The reason for the high, inherent uncertainty in location specific forecasts arises on one hand from the superposition of large internal variability in the atmosphere-ocean system on the more gradual changes. On the other hand, this problem is confounded by the fact that regional climate records are often short and therefore offer little guidance as to how an underlying trend can be identified within the noise. The use of indirect climate information (proxy records) from a host of natural archives has made significant progress recently. Based on an extended record, process studies can help reveal the regional response to changes in large scale climate that likely have to be expected. But in order to come up with robust, season and parameter specific (temperature versus moisture) climate reconstructions, comprehensive data compilations are needed that integrate proxy records of different characteristics, temporal representations, and different systematic and sampling uncertainties. Based on understanding of physical processes, and making explicit use of that knowledge, new dynamical and statistical techniques in paleoclimatology are being developed and explored. In addition to improved estimates of the past climate, the cascade of uncertainties is directly taken into account so that errors can more comprehensively be assessed. A brief overview of the problems and its potential implications for regional planning is followed by an application that demonstrates how collaboration between paleoclimatologists, climate modelers and statisticians can advance our understanding of the climate system and how agencies, businesses and individuals might be able to make better informed decisions in preparation for future climate.

Empirical evidence that metabolic theory describes the temperature dependency of within-host parasite dynamics.

PubMed

Kirk, Devin; Jones, Natalie; Peacock, Stephanie; Phillips, Jessica; Molnár, Péter K; Krkošek, Martin; Luijckx, Pepijn

2018-02-01

The complexity of host-parasite interactions makes it difficult to predict how host-parasite systems will respond to climate change. In particular, host and parasite traits such as survival and virulence may have distinct temperature dependencies that must be integrated into models of disease dynamics. Using experimental data from Daphnia magna and a microsporidian parasite, we fitted a mechanistic model of the within-host parasite population dynamics. Model parameters comprising host aging and mortality, as well as parasite growth, virulence, and equilibrium abundance, were specified by relationships arising from the metabolic theory of ecology. The model effectively predicts host survival, parasite growth, and the cost of infection across temperature while using less than half the parameters compared to modeling temperatures discretely. Our results serve as a proof of concept that linking simple metabolic models with a mechanistic host-parasite framework can be used to predict temperature responses of parasite population dynamics at the within-host level.

Empirical evidence that metabolic theory describes the temperature dependency of within-host parasite dynamics

PubMed Central

Jones, Natalie; Peacock, Stephanie; Phillips, Jessica; Molnár, Péter K.; Krkošek, Martin; Luijckx, Pepijn

2018-01-01

The complexity of host–parasite interactions makes it difficult to predict how host–parasite systems will respond to climate change. In particular, host and parasite traits such as survival and virulence may have distinct temperature dependencies that must be integrated into models of disease dynamics. Using experimental data from Daphnia magna and a microsporidian parasite, we fitted a mechanistic model of the within-host parasite population dynamics. Model parameters comprising host aging and mortality, as well as parasite growth, virulence, and equilibrium abundance, were specified by relationships arising from the metabolic theory of ecology. The model effectively predicts host survival, parasite growth, and the cost of infection across temperature while using less than half the parameters compared to modeling temperatures discretely. Our results serve as a proof of concept that linking simple metabolic models with a mechanistic host–parasite framework can be used to predict temperature responses of parasite population dynamics at the within-host level. PMID:29415043

Understanding the plume dynamics of explosive super-eruptions.

PubMed

Costa, Antonio; J Suzuki, Yujiro; Koyaguchi, Takehiro

2018-02-13

Explosive super-eruptions can erupt up to thousands of km 3 of magma with extremely high mass flow rates (MFR). The plume dynamics of these super-eruptions are still poorly understood. To understand the processes operating in these plumes we used a fluid-dynamical model to simulate what happens at a range of MFR, from values generating intense Plinian columns, as did the 1991 Pinatubo eruption, to upper end-members resulting in co-ignimbrite plumes like Toba super-eruption. Here, we show that simple extrapolations of integral models for Plinian columns to those of super-eruption plumes are not valid and their dynamics diverge from current ideas of how volcanic plumes operate. The different regimes of air entrainment lead to different shaped plumes. For the upper end-members can generate local up-lifts above the main plume (over-plumes). These over-plumes can extend up to the mesosphere. Injecting volatiles into such heights would amplify their impact on Earth climate and ecosystems.

FATE-HD: A spatially and temporally explicit integrated model for predicting vegetation structure and diversity at regional scale

PubMed Central

Isabelle, Boulangeat; Damien, Georges; Wilfried, Thuiller

2014-01-01

During the last decade, despite strenuous efforts to develop new models and compare different approaches, few conclusions have been drawn on their ability to provide robust biodiversity projections in an environmental change context. The recurring suggestions are that models should explicitly (i) include spatiotemporal dynamics; (ii) consider multiple species in interactions; and (iii) account for the processes shaping biodiversity distribution. This paper presents a biodiversity model (FATE-HD) that meets this challenge at regional scale by combining phenomenological and process-based approaches and using well-defined plant functional groups. FATE-HD has been tested and validated in a French National Park, demonstrating its ability to simulate vegetation dynamics, structure and diversity in response to disturbances and climate change. The analysis demonstrated the importance of considering biotic interactions, spatio-temporal dynamics, and disturbances in addition to abiotic drivers to simulate vegetation dynamics. The distribution of pioneer trees was particularly improved, as were all undergrowth functional groups. PMID:24214499

Assessment of the impact of climate shifts on malaria transmission in the Sahel.

PubMed

Bomblies, Arne; Eltahir, Elfatih A B

2009-09-01

Climate affects malaria transmission through a complex network of causative pathways. We seek to evaluate the impact of hypothetical climate change scenarios on malaria transmission in the Sahel by using a novel mechanistic, high spatial- and temporal-resolution coupled hydrology and agent-based entomology model. The hydrology model component resolves individual precipitation events and individual breeding pools. The impact of future potential climate shifts on the representative Sahel village of Banizoumbou, Niger, is estimated by forcing the model of Banizoumbou environment with meteorological data from two locations along the north-south climatological gradient observed in the Sahel--both for warmer, drier scenarios from the north and cooler, wetter scenarios from the south. These shifts in climate represent hypothetical but historically realistic climate change scenarios. For Banizoumbou climatic conditions (latitude 13.54 N), a shift toward cooler, wetter conditions may dramatically increase mosquito abundance; however, our modeling results indicate that the increased malaria transmissibility is not simply proportional to the precipitation increase. The cooler, wetter conditions increase the length of the sporogonic cycle, dampening a large vectorial capacity increase otherwise brought about by increased mosquito survival and greater overall abundance. Furthermore, simulations varying rainfall event frequency demonstrate the importance of precipitation patterns, rather than simply average or time-integrated precipitation, as a controlling factor of these dynamics. Modeling results suggest that in addition to changes in temperature and total precipitation, changes in rainfall patterns are very important to predict changes in disease susceptibility resulting from climate shifts. The combined effect of these climate-shift-induced perturbations can be represented with the aid of a detailed mechanistic model.

Fire modulates climate change response of simulated aspen distribution across topoclimatic gradients in a semi-arid montane landscape

USGS Publications Warehouse

Yang, Jian; Weisberg, Peter J.; Shinneman, Douglas; Dilts, Thomas E.; Earnst, Susan L.; Scheller, Robert M

2015-01-01

Content Changing aspen distribution in response to climate change and fire is a major focus of biodiversity conservation, yet little is known about the potential response of aspen to these two driving forces along topoclimatic gradients. Objective This study is set to evaluate how aspen distribution might shift in response to different climate-fire scenarios in a semi-arid montane landscape, and quantify the influence of fire regime along topoclimatic gradients. Methods We used a novel integration of a forest landscape succession and disturbance model (LANDIS-II) with a fine-scale climatic water deficit approach to simulate dynamics of aspen and associated conifer and shrub species over the next 150 years under various climate-fire scenarios. Results Simulations suggest that many aspen stands could persist without fire for centuries under current climate conditions. However, a simulated 2–5 °C increase in temperature caused a substantial reduction of aspen coverage at lower elevations and a modest increase at upper elevations, leading to an overall reduction of aspen range at the landscape level. Increasing fire activity may favor aspen increase at its upper elevation limits adjacent to coniferous forest, but may also favor reduction of aspen at lower elevation limits adjacent to xeric shrubland. Conclusions Our study highlights the importance of incorporating fine-scale terrain effects on climatic water deficit and ecohydrology when modeling species distribution response to climate change. This modeling study suggests that climate mitigation and adaptation strategies that use fire would benefit from consideration of spatial context at landscape scales.

Earth System Chemistry integrated Modelling (ESCiMo) with the Modular Earth Submodel System (MESSy) version 2.51

NASA Astrophysics Data System (ADS)

Jöckel, Patrick; Tost, Holger; Pozzer, Andrea; Kunze, Markus; Kirner, Oliver; Brenninkmeijer, Carl A. M.; Brinkop, Sabine; Cai, Duy S.; Dyroff, Christoph; Eckstein, Johannes; Frank, Franziska; Garny, Hella; Gottschaldt, Klaus-Dirk; Graf, Phoebe; Grewe, Volker; Kerkweg, Astrid; Kern, Bastian; Matthes, Sigrun; Mertens, Mariano; Meul, Stefanie; Neumaier, Marco; Nützel, Matthias; Oberländer-Hayn, Sophie; Ruhnke, Roland; Runde, Theresa; Sander, Rolf; Scharffe, Dieter; Zahn, Andreas

2016-03-01

Three types of reference simulations, as recommended by the Chemistry-Climate Model Initiative (CCMI), have been performed with version 2.51 of the European Centre for Medium-Range Weather Forecasts - Hamburg (ECHAM)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model: hindcast simulations (1950-2011), hindcast simulations with specified dynamics (1979-2013), i.e. nudged towards ERA-Interim reanalysis data, and combined hindcast and projection simulations (1950-2100). The manuscript summarizes the updates of the model system and details the different model set-ups used, including the on-line calculated diagnostics. Simulations have been performed with two different nudging set-ups, with and without interactive tropospheric aerosol, and with and without a coupled ocean model. Two different vertical resolutions have been applied. The on-line calculated sources and sinks of reactive species are quantified and a first evaluation of the simulation results from a global perspective is provided as a quality check of the data. The focus is on the intercomparison of the different model set-ups. The simulation data will become publicly available via CCMI and the Climate and Environmental Retrieval and Archive (CERA) database of the German Climate Computing Centre (DKRZ). This manuscript is intended to serve as an extensive reference for further analyses of the Earth System Chemistry integrated Modelling (ESCiMo) simulations.

Audio-visual assistance in co-creating transition knowledge

NASA Astrophysics Data System (ADS)

Hezel, Bernd; Broschkowski, Ephraim; Kropp, Jürgen P.

2013-04-01

Earth system and climate impact research results point to the tremendous ecologic, economic and societal implications of climate change. Specifically people will have to adopt lifestyles that are very different from those they currently strive for in order to mitigate severe changes of our known environment. It will most likely not suffice to transfer the scientific findings into international agreements and appropriate legislation. A transition is rather reliant on pioneers that define new role models, on change agents that mainstream the concept of sufficiency and on narratives that make different futures appealing. In order for the research community to be able to provide sustainable transition pathways that are viable, an integration of the physical constraints and the societal dynamics is needed. Hence the necessary transition knowledge is to be co-created by social and natural science and society. To this end, the Climate Media Factory - in itself a massively transdisciplinary venture - strives to provide an audio-visual connection between the different scientific cultures and a bi-directional link to stake holders and society. Since methodology, particular language and knowledge level of the involved is not the same, we develop new entertaining formats on the basis of a "complexity on demand" approach. They present scientific information in an integrated and entertaining way with different levels of detail that provide entry points to users with different requirements. Two examples shall illustrate the advantages and restrictions of the approach.

Changes in seasonal climate outpace compensatory density-dependence in eastern brook trout

USGS Publications Warehouse

Bassar, Ronald D.; Letcher, Benjamin H.; Nislow, Keith H.; Whiteley, Andrew R.

2016-01-01

Understanding how multiple extrinsic (density-independent) factors and intrinsic (density-dependent) mechanisms influence population dynamics has become increasingly urgent in the face of rapidly changing climates. It is particularly unclear how multiple extrinsic factors with contrasting effects among seasons are related to declines in population numbers and changes in mean body size and whether there is a strong role for density-dependence. The primary goal of this study was to identify the roles of seasonal variation in climate driven environmental direct effects (mean stream flow and temperature) versus density-dependence on population size and mean body size in eastern brook trout (Salvelinus fontinalis). We use data from a 10-year capture-mark-recapture study of eastern brook trout in four streams in Western Massachusetts, USA to parameterize a discrete-time population projection model. The model integrates matrix modeling techniques used to characterize discrete population structures (age, habitat type and season) with integral projection models (IPMs) that characterize demographic rates as continuous functions of organismal traits (in this case body size). Using both stochastic and deterministic analyses we show that decreases in population size are due to changes in stream flow and temperature and that these changes are larger than what can be compensated for through density-dependent responses. We also show that the declines are due mostly to increasing mean stream temperatures decreasing the survival of the youngest age class. In contrast, increases in mean body size over the same period are the result of indirect changes in density with a lesser direct role of climate-driven environmental change.

Lagged processes and critical timescales in boreal forest response to climate

NASA Astrophysics Data System (ADS)

Wofsy, S. C.; Dunn, A. L.; Amiro, B. D.; Barr, A.; Rocha, A. V.; Goulden, M. L.

2006-12-01

Long-term eddy covariance datasets have recorded the response of boreal ecosystems to climate on timescales up to decadal (Dunn et al. 2006, Barr et al. 2006). Carbon balances in these forests are very dynamic, responding to climatic anomalies on timescales of months to years. A boreal black spruce forest in central Manitoba, Canada, was a source of carbon to the atmosphere in the mid-1990s (55 g C m^{- 2} y-1, 1995-1997), but switched to a sink in recent years (-25 g C m-2 y-1, 2003-2005). The short-term carbon exchange at this site was strongly controlled by temperature, but on long timescales the water balance was more important (Dunn et al. 2006). In a boreal aspen forest in central Saskatchewan, Canada, temperature was the main driver of phenology and canopy duration, but drought status, and especially the persistence of drought over multiple years, was a critical control on ecosystem respiration and resultant carbon balance (Barr et al. 2006). Lagged processes are especially important in the boreal forest: Dunn et al. (2006) found that carbon balances, and especially ecosystem respiration, were strongly controlled by the integrated water balance over preceding years, suggesting that the effects of climatic anomalies are expressed slowly in these forests. Rocha et al. (2006) found similar evidence in tree-ring cores from the NOBS site, which showed a strong correlation with lagged water balances, suggesting that wood growth in these forests is a process integrating over prior years. In a tree-ring analysis across aspen stands in western Canada, Hogg et al. (2005) found that current and lagged (up to four years) moisture status were critical factors regulating ecosystem carbon balance. These results from long-term boreal datasets suggest that the vulnerability of these forests to climate change will be strongly dependent on the future balance between precipitation and temperature. Persistent perturbations to the local climate will likely shift overall biome carbon balance.

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.

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

PubMed

van Klinken, R D; Pichancourt, J B

2015-12-01

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

Temperature impacts on economic growth warrant stringent mitigation policy

NASA Astrophysics Data System (ADS)

Moore, Frances C.; Diaz, Delavane B.

2015-02-01

Integrated assessment models compare the costs of greenhouse gas mitigation with damages from climate change to evaluate the social welfare implications of climate policy proposals and inform optimal emissions reduction trajectories. However, these models have been criticized for lacking a strong empirical basis for their damage functions, which do little to alter assumptions of sustained gross domestic product (GDP) growth, even under extreme temperature scenarios. We implement empirical estimates of temperature effects on GDP growth rates in the DICE model through two pathways, total factor productivity growth and capital depreciation. This damage specification, even under optimistic adaptation assumptions, substantially slows GDP growth in poor regions but has more modest effects in rich countries. Optimal climate policy in this model stabilizes global temperature change below 2 °C by eliminating emissions in the near future and implies a social cost of carbon several times larger than previous estimates. A sensitivity analysis shows that the magnitude of climate change impacts on economic growth, the rate of adaptation, and the dynamic interaction between damages and GDP are three critical uncertainties requiring further research. In particular, optimal mitigation rates are much lower if countries become less sensitive to climate change impacts as they develop, making this a major source of uncertainty and an important subject for future research.

Climate influences on the cost-effectiveness of vector-based interventions against malaria in elimination scenarios

PubMed Central

Parham, Paul E.; Hughes, Dyfrig A.

2015-01-01

Despite the dependence of mosquito population dynamics on environmental conditions, the associated impact of climate and climate change on present and future malaria remains an area of ongoing debate and uncertainty. Here, we develop a novel integration of mosquito, transmission and economic modelling to assess whether the cost-effectiveness of indoor residual spraying (IRS) and long-lasting insecticidal nets (LLINs) against Plasmodium falciparum transmission by Anopheles gambiae s.s. mosquitoes depends on climatic conditions in low endemicity scenarios. We find that although temperature and rainfall affect the cost-effectiveness of IRS and/or LLIN scale-up, whether this is sufficient to influence policy depends on local endemicity, existing interventions, host immune response to infection and the emergence rate of insecticide resistance. For the scenarios considered, IRS is found to be more cost-effective than LLINs for the same level of scale-up, and both are more cost-effective at lower mean precipitation and higher variability in precipitation and temperature. We also find that the dependence of peak transmission on mean temperature translates into optimal temperatures for vector-based intervention cost-effectiveness. Further cost-effectiveness analysis that accounts for country-specific epidemiological and environmental heterogeneities is required to assess optimal intervention scale-up for elimination and better understand future transmission trends under climate change. PMID:25688017

Combined effects of climate, predation, and density dependence on Greater and Lesser Scaup population dynamics

USGS Publications Warehouse

Ross, Beth E.; Hooten, Mevin B.; DeVink, Jean-Michel; Koons, David N.

2015-01-01

An understanding of species relationships is critical in the management and conservation of populations facing climate change, yet few studies address how climate alters species interactions and other population drivers. We use a long-term, broad-scale data set of relative abundance to examine the influence of climate, predators, and density dependence on the population dynamics of declining scaup (Aythya) species within the core of their breeding range. The state-space modeling approach we use applies to a wide range of wildlife species, especially populations monitored over broad spatiotemporal extents. Using this approach, we found that immediate snow cover extent in the preceding winter and spring had the strongest effects, with increases in mean snow cover extent having a positive effect on the local surveyed abundance of scaup. The direct effects of mesopredator abundance on scaup population dynamics were weaker, but the results still indicated a potential interactive process between climate and food web dynamics (mesopredators, alternative prey, and scaup). By considering climate variables and other potential effects on population dynamics, and using a rigorous estimation framework, we provide insight into complex ecological processes for guiding conservation and policy actions aimed at mitigating and reversing the decline of scaup.

Increased wind risk from sting-jet windstorms with climate change

NASA Astrophysics Data System (ADS)

Martínez-Alvarado, Oscar; Gray, Suzanne L.; Hart, Neil C. G.; Clark, Peter A.; Hodges, Kevin; Roberts, Malcolm J.

2018-04-01

Extra-tropical cyclones dominate autumn and winter weather over western Europe. The strongest cyclones, often termed windstorms, have a large socio-economic impact on landfall due to strong surface winds and coastal storm surges. Climate model integrations have predicted a future increase in the frequency of, and potential damage from, European windstorms and yet these integrations cannot properly represent localised jets, such as sting jets, that may significantly enhance damage. Here we present the first prediction of how the climatology of sting-jet-containing cyclones will change in a future warmer climate, considering the North Atlantic and Europe. A proven sting-jet precursor diagnostic is applied to 13 year present-day and future (~2100) climate integrations from the Met Office Unified Model in its Global Atmosphere 3.0 configuration. The present-day climate results are consistent with previously-published results from a reanalysis dataset (with around 32% of cyclones exhibiting the sing-jet precursor), lending credibility to the analysis of the future-climate integration. The proportion of cyclones exhibiting the sting-jet precursor in the future-climate integration increases to 45%. Furthermore, while the proportion of explosively-deepening storms increases only slightly in the future climate, the proportion of those storms with the sting-jet precursor increases by 60%. The European resolved-wind risk associated with explosively-deepening storms containing a sting-jet precursor increases substantially in the future climate; in reality this wind risk is likely to be further enhanced by the release of localised moist instability, unresolved by typical climate models.

U.S. Department of the Interior South Central Climate Science Center

USGS Publications Warehouse

Shipp, Allison A.

2012-01-01

On September 14, 2009, the Secretary of the Interior signed a Secretarial Order (No. 3289) entitled, "Addressing the Impacts of Climate Change on America's Water, Land, and Other Natural and Cultural Resources." The Order effectively established the U.S. Department of the Interior (DOI) Climate Science Centers (CSCs) for the purpose of integrating DOI science and management expertise with similar contributions from our partners to provide information to support strategic adaptation and mitigation efforts on public and private lands across the United States and internationally. The South Central Climate Science Center (SC CSC) is supported by a consortium of partners that include The University of Oklahoma, Texas Tech University, Louisiana State University, The Chickasaw Nation, The Choctaw Nation of Oklahoma, Oklahoma State University, and the National Oceanic and Atmospheric Administration's Geophysical Fluid Dynamics Laboratory. Additionally, the SC CSC will collaborate with a number of other universities, State and federal agencies, and nongovernmental organizations (NGOs) with interests and expertise in climate science. The primary partners of the SC CSC are the Landscape Conservation Cooperatives (LCCs), which include the Desert, Eastern Tallgrass Prairie and Big Rivers, Great Plains, Gulf Coast Prairie, Gulf Coastal Plains and Ozarks, and Southern Rockies. CSC collaborations are focused on common science priorities that address priority partner needs, eliminate redundancies in science, share scientific information and findings, and expand understanding of climate change impacts in the south-central United States and Mexico.

Pacific Decadal Variability and Central Pacific Warming El Niño in a Changing Climate

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

Di Lorenzo, Emanuele

This research aimed at understanding the dynamics controlling decadal variability in the Pacific Ocean and its interactions with global-scale climate change. The first goal was to assess how the dynamics and statistics of the El Niño Southern Oscillation and the modes of Pacific decadal variability are represented in global climate models used in the IPCC. The second goal was to quantify how decadal dynamics are projected to change under continued greenhouse forcing, and determine their significance in the context of paleo-proxy reconstruction of long-term climate.

Climate change: Conflict of observational science, theory, and politics

USGS Publications Warehouse

Gerhard, L.C.

2004-01-01

Debate over whether human activity causes Earth climate change obscures the immensity of the dynamic systems that create and maintain climate on the planet. Anthropocentric debate leads people to believe that they can alter these planetary dynamic systems to prevent that they perceive as negative climate impacts on human civilization. Although politicians offer simplistic remedies, such as the Kyoto Protocol, global climate continues to change naturally. Better planning for the inevitable dislocations that have followed natural global climate changes throughout human history requires us to accept the fact that climate will change, and that human society must adapt to the changes. Over the last decade, the scientific literature reported a shift in emphasis from attempting to build theoretical models of putative human impacts on climate to understanding the planetwide dynamic processes that are the natural climate drivers. The current scientific literature is beginning to report the history of past climate change, the extent of natural climate variability, natural system drivers, and the episodicity of many climate changes. The scientific arguments have broadened from focus upon human effects on climate to include the array of natural phenomena that have driven global climate change for eons. However, significant political issues with long-term social consequences continue their advance. This paper summarizes recent scientific progress in climate science and arguments about human influence on climate. ?? 2004. The American Association of Petroleum Geologists. All rights reserved.

Temperature drives abundance fluctuations, but spatial dynamics is constrained by landscape configuration: Implications for climate-driven range shift in a butterfly.

PubMed

Fourcade, Yoan; Ranius, Thomas; Öckinger, Erik

2017-10-01

Prediction of species distributions in an altered climate requires knowledge on how global- and local-scale factors interact to limit their current distributions. Such knowledge can be gained through studies of spatial population dynamics at climatic range margins. Here, using a butterfly (Pyrgus armoricanus) as model species, we first predicted based on species distribution modelling that its climatically suitable habitats currently extend north of its realized range. Projecting the model into scenarios of future climate, we showed that the distribution of climatically suitable habitats may shift northward by an additional 400 km in the future. Second, we used a 13-year monitoring dataset including the majority of all habitat patches at the species northern range margin to assess the synergetic impact of temperature fluctuations and spatial distribution of habitat, microclimatic conditions and habitat quality, on abundance and colonization-extinction dynamics. The fluctuation in abundance between years was almost entirely determined by the variation in temperature during the species larval development. In contrast, colonization and extinction dynamics were better explained by patch area, between-patch connectivity and host plant density. This suggests that the response of the species to future climate change may be limited by future land use and how its host plants respond to climate change. It is, thus, probable that dispersal limitation will prevent P. armoricanus from reaching its potential future distribution. We argue that models of range dynamics should consider the factors influencing metapopulation dynamics, especially at the range edges, and not only broad-scale climate. It includes factors acting at the scale of habitat patches such as habitat quality and microclimate and landscape-scale factors such as the spatial configuration of potentially suitable patches. Knowledge of population dynamics under various environmental conditions, and the incorporation of realistic scenarios of future land use, appears essential to provide predictions useful for actions mitigating the negative effects of climate change. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Linking Science and Management in an Interactive Geospatial, Mutli-Criterion, Structured Decision Support Framework: Use Case Studies of the "Future Forests Geo-visualization and Decision Support Tool

NASA Astrophysics Data System (ADS)

Pontius, J.; Duncan, J.

2017-12-01

Land managers are often faced with balancing management activities to accomplish a diversity of management objectives, in systems faced with many stress agents. Advances in ecosystem modeling provide a rich source of information to inform management. Coupled with advances in decision support techniques and computing capabilities, interactive tools are now accessible for a broad audience of stakeholders. Here we present one such tool designed to capture information on how climate change may impact forested ecosystems, and how that impact varies spatially across the landscape. This tool integrates empirical models of current and future forest structure and function in a structured decision framework that allows users to customize weights for multiple management objectives and visualize suitability outcomes across the landscape. Combined with climate projections, the resulting products allow stakeholders to compare the relative success of various management objectives on a pixel by pixel basis and identify locations where management outcomes are most likely to be met. Here we demonstrate this approach with the integration of several of the preliminary models developed to map species distributions, sugar maple health, forest fragmentation risk and hemlock vulnerability to hemlock woolly adelgid under current and future climate scenarios. We compare three use case studies with objective weightings designed to: 1) Identify key parcels for sugarbush conservation and management, 2) Target state lands that may serve as hemlock refugia from hemlock woolly adelgid induced mortality, and 3) Examine how climate change may alter the success of managing for both sugarbush and hemlock across privately owned lands. This tool highlights the value of flexible models that can be easily run with customized weightings in a dynamic, integrated assessment that allows users to hone in on their potentially complex management objectives, and to visualize and prioritize locations across the landscape. It also demonstrates the importance of including climate considerations for long-term management. This merging of scientific knowledge with the diversity of stakeholder needs is an important step towards using science to inform management and policy decisions.

The influence of historical climate on the population dynamics of three dominant sagebrush steppe plants.

USDA-ARS?s Scientific Manuscript database

Climate change could alter the population growth of dominant species, leading to profound effects on community structure and ecosystem dynamics. Understanding the links between historical variation in climate and population vital rates (survival, growth, recruitment) is one way to predict the impact...

Microbial oceanography and the Hawaii Ocean Time-series programme.

PubMed

Karl, David M; Church, Matthew J

2014-10-01

The Hawaii Ocean Time-series (HOT) programme has been tracking microbial and biogeochemical processes in the North Pacific Subtropical Gyre since October 1988. The near-monthly time series observations have revealed previously undocumented phenomena within a temporally dynamic ecosystem that is vulnerable to climate change. Novel microorganisms, genes and unexpected metabolic pathways have been discovered and are being integrated into our evolving ecological paradigms. Continued research, including higher-frequency observations and at-sea experimentation, will help to provide a comprehensive scientific understanding of microbial processes in the largest biome on Earth.

GFDL's ESM2 global coupled climate-carbon Earth System Models. Part I: physical formulation and baseline simulation characteristics

USGS Publications Warehouse

Dunne, John P.; John, Jasmin G.; Adcroft, Alistair J.; Griffies, Stephen M.; Hallberg, Robert W.; Shevalikova, Elena; Stouffer, Ronald J.; Cooke, William; Dunne, Krista A.; Harrison, Matthew J.; Krasting, John P.; Malyshev, Sergey L.; Milly, P.C.D.; Phillipps, Peter J.; Sentman, Lori A.; Samuels, Bonita L.; Spelman, Michael J.; Winton, Michael; Wittenberg, Andrew T.; Zadeh, Niki

2012-01-01

We describe the physical climate formulation and simulation characteristics of two new global coupled carbon-climate Earth System Models, ESM2M and ESM2G. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory's previous CM2.1 climate model while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4.1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in the El Niño-Southern Oscillation being overly strong in ESM2M and overly weak ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to: total heat content variability given its lack of long term drift, gyre circulation and ventilation in the North Pacific, tropical Atlantic and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to: surface circulation given its superior surface temperature, salinity and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. Our overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords us the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon-climate models.

Science initiative for international development

NASA Astrophysics Data System (ADS)

Showstack, Randy

2011-07-01

A new initiative to use science to address global development challenges was launched by the U.S. National Science Foundation (NSF) and the U.S. Agency for International Development (USAID) on 7 July. Partnerships for Enhanced Engagement in Research (PEER) will capitalize on competitively awarded investments to support and build scientific and technical capacity in the developing world, according to the agencies. USAID has allocated $7 million for PEER, which the agencies indicate could leverage an additional $25-50 million in NSFfunded research at U.S. institutions to focus on issues including climate change, disaster mitigation, water, renewable energy, and food security. The program is beginning with six pilot programs in Asia and Africa, including fostering a Bangladeshi seismological community, studying the impacts of land use on biodiversity dynamics in Burkina Faso, and examining climate change and integrated resource management around Agougou Natural Pond in Mali.

Efficient Computation of Atmospheric Flows with Tempest: Validation of Next-Generation Climate and Weather Prediction Algorithms at Non-Hydrostatic Scales

NASA Astrophysics Data System (ADS)

Guerra, Jorge; Ullrich, Paul

2016-04-01

Tempest is a next-generation global climate and weather simulation platform designed to allow experimentation with numerical methods for a wide range of spatial resolutions. The atmospheric fluid equations are discretized by continuous / discontinuous finite elements in the horizontal and by a staggered nodal finite element method (SNFEM) in the vertical, coupled with implicit/explicit time integration. At horizontal resolutions below 10km, many important questions remain on optimal techniques for solving the fluid equations. We present results from a suite of idealized test cases to validate the performance of the SNFEM applied in the vertical with an emphasis on flow features and dynamic behavior. Internal gravity wave, mountain wave, convective bubble, and Cartesian baroclinic instability tests will be shown at various vertical orders of accuracy and compared with known results.

Hurricane Sandy and Adaptation Pathways in New York: Lessons from a First-Responder City

NASA Technical Reports Server (NTRS)

Rosenzweig, Cynthia; Solecki, William

2014-01-01

Two central issues of climate change have become increasingly evident: Climate change will significantly affect cities; and rapid global urbanization will increase dramatically the number of individuals, amount of critical infrastructure, and means of economic production that are exposed and vulnerable to dynamic climate risks. Simultaneously, cities in many settings have begun to emerge as early adopters of climate change action strategies including greenhouse gas mitigation and adaptation. The objective of this paper is to examine and analyze how officials of one city - the City of New York - have integrated a flexible adaptation pathways approach into the municipality's climate action strategy. This approach has been connected with the City's ongoing response to Hurricane Sandy, which struck in the October 2012 and resulted in damages worth more than US$19 billion. A case study narrative methodology utilizing the Wise et al. conceptual framework (see this volume) is used to evaluate the effectiveness of the flexible adaptation pathways approach in New York City. The paper finds that Hurricane Sandy serves as a ''tipping point'' leading to transformative adaptation due to the explicit inclusion of increasing climate change risks in the rebuilding effort. The potential for transferability of the approach to cities varying in size and development stage is discussed, with elements useful across cities including the overall concept of flexible adaptation pathways, the inclusion of the full metropolitan region in the planning process, and the co-generation of climate-risk information by stakeholders and scientists.

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

Decadal-Scale Forecasting of Climate Drivers for Marine Applications.

PubMed

Salinger, J; Hobday, A J; Matear, R J; O'Kane, T J; Risbey, J S; Dunstan, P; Eveson, J P; Fulton, E A; Feng, M; Plagányi, É E; Poloczanska, E S; Marshall, A G; Thompson, P A

Climate influences marine ecosystems on a range of time scales, from weather-scale (days) through to climate-scale (hundreds of years). Understanding of interannual to decadal climate variability and impacts on marine industries has received less attention. Predictability up to 10 years ahead may come from large-scale climate modes in the ocean that can persist over these time scales. In Australia the key drivers of climate variability affecting the marine environment are the Southern Annular Mode, the Indian Ocean Dipole, the El Niño/Southern Oscillation, and the Interdecadal Pacific Oscillation, each has phases that are associated with different ocean circulation patterns and regional environmental variables. The roles of these drivers are illustrated with three case studies of extreme events-a marine heatwave in Western Australia, a coral bleaching of the Great Barrier Reef, and flooding in Queensland. Statistical and dynamical approaches are described to generate forecasts of climate drivers that can subsequently be translated to useful information for marine end users making decisions at these time scales. Considerable investment is still needed to support decadal forecasting including improvement of ocean-atmosphere models, enhancement of observing systems on all scales to support initiation of forecasting models, collection of important biological data, and integration of forecasts into decision support tools. Collaboration between forecast developers and marine resource sectors-fisheries, aquaculture, tourism, biodiversity management, infrastructure-is needed to support forecast-based tactical and strategic decisions that reduce environmental risk over annual to decadal time scales. © 2016 Elsevier Ltd. All rights reserved.

CO2 and fire influence tropical ecosystem stability in response to climate change.

PubMed

Shanahan, Timothy M; Hughen, Konrad A; McKay, Nicholas P; Overpeck, Jonathan T; Scholz, Christopher A; Gosling, William D; Miller, Charlotte S; Peck, John A; King, John W; Heil, Clifford W

2016-07-18

Interactions between climate, fire and CO2 are believed to play a crucial role in controlling the distributions of tropical woodlands and savannas, but our understanding of these processes is limited by the paucity of data from undisturbed tropical ecosystems. Here we use a 28,000-year integrated record of vegetation, climate and fire from West Africa to examine the role of these interactions on tropical ecosystem stability. We find that increased aridity between 28-15 kyr B.P. led to the widespread expansion of tropical grasslands, but that frequent fires and low CO2 played a crucial role in stabilizing these ecosystems, even as humidity changed. This resulted in an unstable ecosystem state, which transitioned abruptly from grassland to woodlands as gradual changes in CO2 and fire shifted the balance in favor of woody plants. Since then, high atmospheric CO2 has stabilized tropical forests by promoting woody plant growth, despite increased aridity. Our results indicate that the interactions between climate, CO2 and fire can make tropical ecosystems more resilient to change, but that these systems are dynamically unstable and potentially susceptible to abrupt shifts between woodland and grassland dominated states in the future.

CO2 and fire influence tropical ecosystem stability in response to climate change

NASA Astrophysics Data System (ADS)

Shanahan, Timothy M.; Hughen, Konrad A.; McKay, Nicholas P.; Overpeck, Jonathan T.; Scholz, Christopher A.; Gosling, William D.; Miller, Charlotte S.; Peck, John A.; King, John W.; Heil, Clifford W.

2016-07-01

Interactions between climate, fire and CO2 are believed to play a crucial role in controlling the distributions of tropical woodlands and savannas, but our understanding of these processes is limited by the paucity of data from undisturbed tropical ecosystems. Here we use a 28,000-year integrated record of vegetation, climate and fire from West Africa to examine the role of these interactions on tropical ecosystem stability. We find that increased aridity between 28-15 kyr B.P. led to the widespread expansion of tropical grasslands, but that frequent fires and low CO2 played a crucial role in stabilizing these ecosystems, even as humidity changed. This resulted in an unstable ecosystem state, which transitioned abruptly from grassland to woodlands as gradual changes in CO2 and fire shifted the balance in favor of woody plants. Since then, high atmospheric CO2 has stabilized tropical forests by promoting woody plant growth, despite increased aridity. Our results indicate that the interactions between climate, CO2 and fire can make tropical ecosystems more resilient to change, but that these systems are dynamically unstable and potentially susceptible to abrupt shifts between woodland and grassland dominated states in the future.

Modelling the effects of climate and land-use change on the hydrochemistry and ecology of the River Wye (Wales).

PubMed

Bussi, Gianbattista; Whitehead, Paul G; Gutiérrez-Cánovas, Cayetano; Ledesma, José L J; Ormerod, Steve J; Couture, Raoul-Marie

2018-06-15

Interactions between climate change and land use change might have substantial effects on aquatic ecosystems, but are still poorly understood. Using the Welsh River Wye as a case study, we linked models of water quality (Integrated Catchment - INCA) and climate (GFDL - Geophysical Fluid Dynamics Laboratory and IPSL - Institut Pierre Simon Laplace) under greenhouse gas scenarios (RCP4.5 and RCP8.5) to drive a bespoke ecosystem model that simulated the responses of aquatic organisms. The potential effects of economic and social development were also investigated using scenarios from the EU MARS project (Managing Aquatic Ecosystems and Water Resources under Multiple Stress). Longitudinal position along the river mediated response to increasing anthropogenic pressures. Upland locations appeared particularly sensitive to nutrient enrichment or potential re-acidification compared to lowland environments which are already eutrophic. These results can guide attempts to mitigate future impacts and reiterate the need for sensitive land management in upland, temperate environments which are likely to become increasingly important to water supply and biodiversity conservation as the effects of climate change intensify. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

Simulating dissolved organic carbon dynamics at the swedish integrated monitoring sites with the integrated catchments model for carbon, INCA-C.

PubMed

Futter, M N; Löfgren, S; Köhler, S J; Lundin, L; Moldan, F; Bringmark, L

2011-12-01

Surface water concentrations of dissolved organic carbon ([DOC]) are changing throughout the northern hemisphere due to changes in climate, land use and acid deposition. However, the relative importance of these drivers is unclear. Here, we use the Integrated Catchments model for Carbon (INCA-C) to simulate long-term (1996-2008) streamwater [DOC] at the four Swedish integrated monitoring (IM) sites. These are unmanaged headwater catchments with old-growth forests and no major changes in land use. Daily, seasonal and long-term variations in streamwater [DOC] driven by runoff, seasonal temperature and atmospheric sulfate (SO₄(2-)) deposition were observed at all sites. Using INCA-C, it was possible to reproduce observed patterns of variability in streamwater [DOC] at the four IM sites. Runoff was found to be the main short-term control on [DOC]. Seasonal patterns in [DOC] were controlled primarily by soil temperature. Measured SO₄(2-) deposition explained some of the long-term [DOC] variability at all sites.

Integrating Climate Change Science and Sustainability in Environmental Science, Sociology, Philosophy and Business Courses.

NASA Astrophysics Data System (ADS)

Boudrias, M. A.; Cantzler, J.; Croom, S.; Huston, C.; Woods, M.

2015-12-01

Courses on sustainability can be taught from multiple perspectives with some focused on specific areas (environmental, socio-cultural, economic, ethics) and others taking a more integrated approach across areas of sustainability and academic disciplines. In conjunction with the Climate Change Education Program efforts to enhance climate change literacy with innovative approaches, resources and communication strategies developed by Climate Education Partners were used in two distinct ways to integrate climate change science and impacts into undergraduate and graduate level courses. At the graduate level, the first lecture in the MBA program in Sustainable Supply Chain Management is entirely dedicated to climate change science, local and global impacts and discussions about key messages to communicate to the business community. Basic science concepts are integrated with discussions about mitigation and adaptation focused on business leaders. The concepts learned are then applied to the semester-long business plan project for the students. At the undergraduate level, a new model of comprehensive integration across disciplines was implemented in Spring 2015 across three courses on Sustainability each with a specific lens: Natural Science, Sociology and Philosophy. All three courses used climate change as the 'big picture' framing concept and had similar learning objectives creating a framework where lens-specific topics, focusing on depth in a discipline, were balanced with integrated exercises across disciplines providing breadth and possibilities for integration. The comprehensive integration project was the creation of the climate action plan for the university with each team focused on key areas of action (water, energy, transportation, etc.) and each team built with at least one member from each class ensuring a natural science, sociological and philosophical perspective. The final project was presented orally to all three classes and an integrated paper included all three perspectives. The best projects are being compiled so they can be shared with the University of San Diego's planning committee.

Underlying mechanisms leading to El Niño-to-La Niña transition are unchanged under global warming

NASA Astrophysics Data System (ADS)

Yun, Kyung-Sook; Yeh, Sang-Wook; Ha, Kyung-Ja

2018-05-01

El Niño's transitions play critical roles in modulating severe weather and climate events. Therefore, understanding the dynamic factors leading to El Niño's transitions and its future projection is a great challenge in predicting the diverse socioeconomic influences of El Niño over the globe. This study focuses on two dynamic factors controlling the El Niño-to-La Niña transition from the present climate and to future climate, using the observation, the historical and the RCP8.5 simulations of Coupled Model Intercomparison phase 5 climate models. The first is the inter-basin coupling between the Indian Ocean and the western North Pacific through the subtropical high variability. The second is the enhanced sensitivity between sea surface temperature and a deep tropical convection in the central tropical Pacific during the El Niño's developing phase. We show that the dynamic factors leading to El Niño-to-La Niña transition in the present climate are unchanged in spite of the increase of greenhouse gas concentrations. We argue that the two dynamic factors are strongly constrained by the climatological precipitation distribution over the central tropical Pacific and western North Pacific as little changed from the present climate to future climate. This implies that two dynamical processes leading to El Niño-to-La Niña transitions in the present climate will also play a robust role in global warming.

Dynamics of the middle atmosphere as observed by the ARISE project

NASA Astrophysics Data System (ADS)

Blanc, E.

2015-12-01

It has been strongly demonstrated that variations in the circulation of the middle atmosphere influence weather and climate all the way to the Earth's surface. A key part of this coupling occurs through the propagation and breaking of planetary and gravity waves. However, limited observations prevent to faithfully reproduce the dynamics of the middle atmosphere in numerical weather prediction and climate models. The main challenge of the ARISE (Atmospheric dynamics InfraStructure in Europe) project is to combine existing national and international observation networks including: the International infrasound monitoring system developed for the CTBT (Comprehensive nuclear-Test-Ban Treaty) verification, the NDACC (Network for the Detection of Atmospheric Composition Changes) lidar network, European observation infrastructures at mid latitudes (OHP observatory), tropics (Maïdo observatory), high latitudes (ALOMAR and EISCAT), infrasound stations which form a dense European network and satellites. The ARISE network is unique by its coverage (polar to equatorial regions in the European longitude sector), its altitude range (from troposphere to mesosphere and ionosphere) and the involved scales both in time (from seconds to tens of years) and space (from tens of meters to thousands of kilometers). Advanced data products are produced with the scope to assimilate data in the Weather Prediction models to improve future forecasts over weeks and seasonal time scales. ARISE observations are especially relevant for the monitoring of extreme events such as thunderstorms, volcanoes, meteors and at larger scales, deep convection and stratospheric warming events for physical processes description and study of long term evolution with climate change. Among the applications, ARISE fosters integration of innovative methods for remote detection of non-instrumented volcanoes including distant eruption characterization to provide notifications with reliable confidence indices to the civil aviation.

Comprehensive Representation of Hydrologic and Geomorphic Process Coupling in Numerical Models: Internal Dynamics and Basin Evolution

NASA Astrophysics Data System (ADS)

Istanbulluoglu, E.; Vivoni, E. R.; Ivanov, V. Y.; Bras, R. L.

2005-12-01

Landscape morphology has an important control on the spatial and temporal organization of basin hydrologic response to climate forcing, affecting soil moisture redistribution as well as vegetation function. On the other hand, erosion, driven by hydrology and modulated by vegetation, produces landforms over geologic time scales that reflect characteristic signatures of the dominant land forming process. Responding to extreme climate events or anthropogenic disturbances of the land surface, infrequent but rapid forms of erosion (e.g., arroyo development, landsliding) can modify topography such that basin hydrology is significantly influenced. Despite significant advances in both hydrologic and geomorphic modeling over the past two decades, the dynamic interactions between basin hydrology, geomorphology and terrestrial ecology are not adequately captured in current model frameworks. In order to investigate hydrologic-geomorphic-ecologic interactions at the basin scale we present initial efforts in integrating the CHILD landscape evolution model (Tucker et al. 2001) with the tRIBS hydrology model (Ivanov et al. 2004), both developed in a common software environment. In this talk, we present preliminary results of the numerical modeling of the coupled evolution of basin hydro-geomorphic response and resulting landscape morphology in two sets of examples. First, we discuss the long-term evolution of both the hydrologic response and the resulting basin morphology from an initially uplifted plateau. In the second set of modeling experiments, we implement changes in climate and land-use to an existing topography and compare basin hydrologic response to the model results when landscape form is fixed (e.g. no coupling between hydrology and geomorphology). Model results stress the importance of internal basin dynamics, including runoff generation mechanisms and hydrologic states, in shaping hydrologic response as well as the importance of employing comprehensive conceptualizations of hydrology in modeling landscape evolution.

Process-based modeling of species' responses to climate change - a proof of concept using western North American trees

NASA Astrophysics Data System (ADS)

Evans, M. E.; Merow, C.; Record, S.; Menlove, J.; Gray, A.; Cundiff, J.; McMahon, S.; Enquist, B. J.

2013-12-01

Current attempts to forecast how species' distributions will change in response to climate change suffer under a fundamental trade-off: between modeling many species superficially vs. few species in detail (between correlative vs. mechanistic models). The goals of this talk are two-fold: first, we present a Bayesian multilevel modeling framework, dynamic range modeling (DRM), for building process-based forecasts of many species' distributions at a time, designed to address the trade-off between detail and number of distribution forecasts. In contrast to 'species distribution modeling' or 'niche modeling', which uses only species' occurrence data and environmental data, DRMs draw upon demographic data, abundance data, trait data, occurrence data, and GIS layers of climate in a single framework to account for two processes known to influence range dynamics - demography and dispersal. The vision is to use extensive databases on plant demography, distributions, and traits - in the Botanical Information and Ecology Network, the Forest Inventory and Analysis database (FIA), and the International Tree Ring Data Bank - to develop DRMs for North American trees. Second, we present preliminary results from building the core submodel of a DRM - an integral projection model (IPM) - for a sample of dominant tree species in western North America. IPMs are used to infer demographic niches - i.e., the set of environmental conditions under which population growth rate is positive - and project population dynamics through time. Based on >550,000 data points derived from FIA for nine tree species in western North America, we show IPM-based models of their current and future distributions, and discuss how IPMs can be used to forecast future forest productivity, mortality patterns, and inform efforts at assisted migration.

Analyzing and modelling the effect of long-term fertilizer management on crop yield and soil organic carbon in China.

PubMed

Zhang, Jie; Balkovič, Juraj; Azevedo, Ligia B; Skalský, Rastislav; Bouwman, Alexander F; Xu, Guang; Wang, Jinzhou; Xu, Minggang; Yu, Chaoqing

2018-06-15

This study analyzes the influence of various fertilizer management practices on crop yield and soil organic carbon (SOC) based on the long-term field observations and modelling. Data covering 11 years from 8 long-term field trials were included, representing a range of typical soil, climate, and agro-ecosystems in China. The process-based model EPIC (Environmental Policy Integrated Climate model) was used to simulate the response of crop yield and SOC to various fertilization regimes. The results showed that the yield and SOC under additional manure application treatment were the highest while the yield under control treatment was the lowest (30%-50% of NPK yield) at all sites. The SOC in northern sites appeared more dynamic than that in southern sites. The variance partitioning analysis (VPA) showed more variance of crop yield could be explained by the fertilization factor (42%), including synthetic nitrogen (N), phosphorus (P), potassium (K) fertilizers, and fertilizer NPK combined with manure. The interactive influence of soil (total N, P, K, and available N, P, K) and climate factors (mean annual temperature and precipitation) determine the largest part of the SOC variance (32%). EPIC performs well in simulating both the dynamics of crop yield (NRMSE = 32% and 31% for yield calibration and validation) and SOC (NRMSE = 13% and 19% for SOC calibration and validation) under diverse fertilization practices in China. EPIC can assist in predicting the impacts of different fertilization regimes on crop growth and soil carbon dynamics, and contribute to the optimization of fertilizer management for different areas in China. Copyright © 2018. Published by Elsevier B.V.

A dynamic bioenergetic model for coral-Symbiodinium symbioses and coral bleaching as an alternate stable state.

PubMed

Cunning, Ross; Muller, Erik B; Gates, Ruth D; Nisbet, Roger M

2017-10-27

Coral reef ecosystems owe their ecological success - and vulnerability to climate change - to the symbiotic metabolism of corals and Symbiodinium spp. The urgency to understand and predict the stability and breakdown of these symbioses (i.e., coral 'bleaching') demands the development and application of theoretical tools. Here, we develop a dynamic bioenergetic model of coral-Symbiodinium symbioses that demonstrates realistic steady-state patterns in coral growth and symbiont abundance across gradients of light, nutrients, and feeding. Furthermore, by including a mechanistic treatment of photo-oxidative stress, the model displays dynamics of bleaching and recovery that can be explained as transitions between alternate stable states. These dynamics reveal that "healthy" and "bleached" states correspond broadly to nitrogen- and carbon-limitation in the system, with transitions between them occurring as integrated responses to multiple environmental factors. Indeed, a suite of complex emergent behaviors reproduced by the model (e.g., bleaching is exacerbated by nutrients and attenuated by feeding) suggests it captures many important attributes of the system; meanwhile, its modular framework and open source R code are designed to facilitate further problem-specific development. We see significant potential for this modeling framework to generate testable hypotheses and predict integrated, mechanistic responses of corals to environmental change, with important implications for understanding the performance and maintenance of symbiotic systems. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Integrating U.S. climate, energy, and transportation policies : RAND workshops address challenges and potential solutions

DOT National Transportation Integrated Search

2009-01-01

There is growing consensus among policymakers that bold government action is needed : to mitigate climate change, particularly through integrated climate, energy, and transportation : policy initiatives. In an effort to share different perspectives o...

Plant physiological models of heat, water and photoinhibition stress for climate change modelling and agricultural prediction

NASA Astrophysics Data System (ADS)

Nicolas, B.; Gilbert, M. E.; Paw U, K. T.

2015-12-01

Soil-Vegetation-Atmosphere Transfer (SVAT) models are based upon well understood steady state photosynthetic physiology - the Farquhar-von Caemmerer-Berry model (FvCB). However, representations of physiological stress and damage have not been successfully integrated into SVAT models. Generally, it has been assumed that plants will strive to conserve water at higher temperatures by reducing stomatal conductance or adjusting osmotic balance, until potentially damaging temperatures and the need for evaporative cooling become more important than water conservation. A key point is that damage is the result of combined stresses: drought leads to stomatal closure, less evaporative cooling, high leaf temperature, less photosynthetic dissipation of absorbed energy, all coupled with high light (photosynthetic photon flux density; PPFD). This leads to excess absorbed energy by Photosystem II (PSII) and results in photoinhibition and damage, neither are included in SVAT models. Current representations of photoinhibition are treated as a function of PPFD, not as a function of constrained photosynthesis under heat or water. Thus, it seems unlikely that current models can predict responses of vegetation to climate variability and change. We propose a dynamic model of damage to Rubisco and RuBP-regeneration that accounts, mechanistically, for the interactions between high temperature, light, and constrained photosynthesis under drought. Further, these predictions are illustrated by key experiments allowing model validation. We also integrated this new framework within the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA). Preliminary results show that our approach can be used to predict reasonable photosynthetic dynamics. For instances, a leaf undergoing one day of drought stress will quickly decrease its maximum quantum yield of PSII (Fv/Fm), but it won't recover to unstressed levels for several days. Consequently, cumulative effect of photoinhibition on photosynthesis can cause a decrease of about 35% of CO2 uptake. As a result, the incorporation of stress and damage into SVAT models could considerably improve our ability to predict global responses to climate change.

Modelling Hydrology and Erosion in a Changing Socio-Economic Environment

NASA Astrophysics Data System (ADS)

Kirkby, M. J.; van Delden, H.; Hahn, B. M.; Irvine, B. J.

2009-12-01

Although forecasting systems have a limited time horizon due to the impact of unforeseen events, a rationally based model is able to provide some insights into likely short term behaviour, taking account of the dynamic interactions between climate, physical processes and land use decisions. The biophysical model (PESERA) takes land use decisions as inputs, together with climatic data or scenarios, topography and soils, to generate estimates of runoff, soil erosion, crop or natural vegetation growth and physical suitability, primarily based on crop yields. Estimates are made at a spatial resolution of 100 - 1000 m according to the area involved, the former for a catchment of say 1000 km2, the latter for a continental region. The generic dynamic land-use (change) model (METRONAMICA) has been fully integrated with PESERA to create the ‘Integrated Assessment Model’ (IAM) within the DESURVEY European project. The IAM takes biophysical performance and other spatial characteristics as an input and combines them with socio-economic data to determine potential suitability for each possible residential, commercial, agricultural etc use. The model then allocates each land use type and detailed agricultural class to the locations with the highest potential, based on neighbouring and historic choices as well as short-term economic advantage to estimate probabilities of change to alternative uses. Suitability, accessibility and zoning regulations are included in the decision process to provide the locational characteristics. Change of land use over time is thus determined within a cellular automaton model that generates rational spatial patterns of land use choice. The IAM is being applied at country scale in southern Europe and to smaller regions in North Africa. Although, in the long term, climate change is likely to dominate physical and economic impacts, in the shorter term over which this type of model can most reliably be used, the significance of land use change is much stronger.

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.

Solving the Global Climate Monitoring Problem in the Atmosphere: Towards SI-tied Climate Records with Integrated Uncertainty Propagation

NASA Astrophysics Data System (ADS)

Kirchengast, G.; Schwaerz, M.; Fritzer, J.; Schwarz, J.; Scherllin-Pirscher, B.; Steiner, A. K.

2013-12-01

Monitoring the atmosphere to gain accurate and long-term stable records of essential climate variables (ECVs) such as temperature and greenhouse gases is the backbone of contemporary atmospheric and climate science. Earth observation from space is the key to obtain such data globally in the atmosphere. Currently, however, not any existing satellite-based atmospheric ECV record can serve as authoritative benchmark over months to decades so that climate variability and change in the atmosphere are not yet reliably monitored. Radio occultation (RO) using Global Navigation Satellite System (GNSS) signals provides a unique opportunity to solve this problem in the free atmosphere (from ~1-2 km altitude upwards) for core ECVs: the thermodynamic variables temperature and pressure, and to some degree water vapor, which are key parameters for tracking climate change. On top of RO we have recently conceived next-generation methods, microwave and infrared-laser occultation and nadir-looking infrared-laser reflectometry. These can monitor a full set of thermo-dynamic ECVs (incl. wind) as well as the greenhouse gases such as carbon dioxide and methane as main drivers of climate change; for the latter we also target the boundary layer for tracking carbon sources and sinks. We briefly introduce to why the atmospheric climate monitoring challenge is unsolved so far and why just the above methods have the capabilities to break through. We then focus on RO, which already provided more than a decade of observations. RO accurately measures time delays from refraction of GNSS signals during atmospheric occultation events. This enables to tie RO-derived ECVs and their uncertainty to fundamental time standards, effectively the SI second, and to their unique long-term stability and narrow uncertainty. However, despite impressive advances since the pioneering RO mission GPS/Met in the mid-1990ties no rigorous trace from fundamental time to the ECVs (duly accounting also for relevant side influences) exists so far. Establishing such a trace first-time in form of the Reference Occultation Processing System rOPS, providing reference RO data for climate science and applications, is therefore a current cornerstone endeavor at the Wegener Center over 2011 to 2015, supported also by colleagues from other key groups at EUMETSAT Darmstadt, UCAR Boulder, DMI Copenhagen, ECMWF Reading, IAP Moscow, AIUB Berne, and RMIT Melbourne. With the rOPS we undertake to process the full chain from the SI-tied raw data to the atmospheric ECVs with integrated uncertainty propagation. We summarize where we currently stand in quantifying RO accuracy and long-term stability and then discuss the concept, development status and initial results from the rOPS, with emphasis on its novel capability to provide SI-tied reference data with integrated uncertainty estimation. We comment how these data can provide ground-breaking support to challenges such as climate model evaluation, anthropogenic change detection and attribution, and calibration of complementary climate observing systems.

A climate robust integrated modelling framework for regional impact assessment of climate change

NASA Astrophysics Data System (ADS)

Janssen, Gijs; Bakker, Alexander; van Ek, Remco; Groot, Annemarie; Kroes, Joop; Kuiper, Marijn; Schipper, Peter; van Walsum, Paul; Wamelink, Wieger; Mol, Janet

2013-04-01

Decision making towards climate proofing the water management of regional catchments can benefit greatly from the availability of a climate robust integrated modelling framework, capable of a consistent assessment of climate change impacts on the various interests present in the catchments. In the Netherlands, much effort has been devoted to developing state-of-the-art regional dynamic groundwater models with a very high spatial resolution (25x25 m2). Still, these models are not completely satisfactory to decision makers because the modelling concepts do not take into account feedbacks between meteorology, vegetation/crop growth, and hydrology. This introduces uncertainties in forecasting the effects of climate change on groundwater, surface water, agricultural yields, and development of groundwater dependent terrestrial ecosystems. These uncertainties add to the uncertainties about the predictions on climate change itself. In order to create an integrated, climate robust modelling framework, we coupled existing model codes on hydrology, agriculture and nature that are currently in use at the different research institutes in the Netherlands. The modelling framework consists of the model codes MODFLOW (groundwater flow), MetaSWAP (vadose zone), WOFOST (crop growth), SMART2-SUMO2 (soil-vegetation) and NTM3 (nature valuation). MODFLOW, MetaSWAP and WOFOST are coupled online (i.e. exchange information on time step basis). Thus, changes in meteorology and CO2-concentrations affect crop growth and feedbacks between crop growth, vadose zone water movement and groundwater recharge are accounted for. The model chain WOFOST-MetaSWAP-MODFLOW generates hydrological input for the ecological prediction model combination SMART2-SUMO2-NTM3. The modelling framework was used to support the regional water management decision making process in the 267 km2 Baakse Beek-Veengoot catchment in the east of the Netherlands. Computations were performed for regionalized 30-year climate change scenarios developed by KNMI for precipitation and reference evapotranspiration according to Penman-Monteith. Special focus in the project was on the role of uncertainty. How valid is the information that is generated by this modelling framework? What are the most important uncertainties of the input data, how do they affect the results of the model chain and how can the uncertainties of the data, results, and model concepts be quantified and communicated? Besides these technical issues, an important part of the study was devoted to the perception of stakeholders. Stakeholder analysis and additional working sessions yielded insight into how the models, their results and the uncertainties are perceived, how the modelling framework and results connect to the stakeholders' information demands and what kind of additional information is needed for adequate support on decision making.

The water-energy nexus at water supply and its implications on the integrated water and energy management.

PubMed

Khalkhali, Masoumeh; Westphal, Kirk; Mo, Weiwei

2018-09-15

Water and energy are highly interdependent in the modern world, and hence, it is important to understand their constantly changing and nonlinear interconnections to inform the integrated management of water and energy. In this study, a hydrologic model, a water systems model, and an energy model were developed and integrated into a system dynamics modeling framework. This framework was then applied to a water supply system in the northeast US to capture its water-energy interactions under a set of future population, climate, and system operation scenarios. A hydrologic model was first used to simulate the system's hydrologic inflows and outflows under temperature and precipitation changes on a weekly-basis. A water systems model that combines the hydrologic model and management rules (e.g., water release and transfer) was then developed to dynamically simulate the system's water storage and water head. Outputs from the water systems model were used in the energy model to estimate hydropower generation. It was found that critical water-energy synergies and tradeoffs exist, and there is a possibility for integrated water and energy management to achieve better outcomes. This analysis also shows the importance of a holistic understanding of the systems as a whole, which would allow utility managers to make proactive long-term management decisions. The modeling framework is generalizable to other water supply systems with hydropower generation capacities to inform the integrated management of water and energy resources. Copyright © 2018 Elsevier B.V. All rights reserved.

Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis

PubMed Central

Botai, Joel O.; Rautenbach, Hannes; Ncongwane, Katlego P.; Botai, Christina M.

2017-01-01

The north-eastern parts of South Africa, comprising the Limpopo Province, have recorded a sudden rise in the rate of malaria morbidity and mortality in the 2017 malaria season. The epidemiological profiles of malaria, as well as other vector-borne diseases, are strongly associated with climate and environmental conditions. A retrospective understanding of the relationship between climate and the occurrence of malaria may provide insight into the dynamics of the disease’s transmission and its persistence in the north-eastern region. In this paper, the association between climatic variables and the occurrence of malaria was studied in the Mutale local municipality in South Africa over a period of 19-year. Time series analysis was conducted on monthly climatic variables and monthly malaria cases in the Mutale municipality for the period of 1998–2017. Spearman correlation analysis was performed and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was developed. Microsoft Excel was used for data cleaning, and statistical software R was used to analyse the data and develop the model. Results show that both climatic variables’ and malaria cases’ time series exhibited seasonal patterns, showing a number of peaks and fluctuations. Spearman correlation analysis indicated that monthly total rainfall, mean minimum temperature, mean maximum temperature, mean average temperature, and mean relative humidity were significantly and positively correlated with monthly malaria cases in the study area. Regression analysis showed that monthly total rainfall and monthly mean minimum temperature (R2 = 0.65), at a two-month lagged effect, are the most significant climatic predictors of malaria transmission in Mutale local municipality. A SARIMA (2,1,2) (1,1,1) model fitted with only malaria cases has a prediction performance of about 51%, and the SARIMAX (2,1,2) (1,1,1) model with climatic variables as exogenous factors has a prediction performance of about 72% in malaria cases. The model gives a close comparison between the predicted and observed number of malaria cases, hence indicating that the model provides an acceptable fit to predict the number of malaria cases in the municipality. To sum up, the association between the climatic variables and malaria cases provides clues to better understand the dynamics of malaria transmission. The lagged effect detected in this study can help in adequate planning for malaria intervention. PMID:29117114

Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis.

PubMed

Adeola, Abiodun M; Botai, Joel O; Rautenbach, Hannes; Adisa, Omolola M; Ncongwane, Katlego P; Botai, Christina M; Adebayo-Ojo, Temitope C

2017-11-08

The north-eastern parts of South Africa, comprising the Limpopo Province, have recorded a sudden rise in the rate of malaria morbidity and mortality in the 2017 malaria season. The epidemiological profiles of malaria, as well as other vector-borne diseases, are strongly associated with climate and environmental conditions. A retrospective understanding of the relationship between climate and the occurrence of malaria may provide insight into the dynamics of the disease's transmission and its persistence in the north-eastern region. In this paper, the association between climatic variables and the occurrence of malaria was studied in the Mutale local municipality in South Africa over a period of 19-year. Time series analysis was conducted on monthly climatic variables and monthly malaria cases in the Mutale municipality for the period of 1998-2017. Spearman correlation analysis was performed and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was developed. Microsoft Excel was used for data cleaning, and statistical software R was used to analyse the data and develop the model. Results show that both climatic variables' and malaria cases' time series exhibited seasonal patterns, showing a number of peaks and fluctuations. Spearman correlation analysis indicated that monthly total rainfall, mean minimum temperature, mean maximum temperature, mean average temperature, and mean relative humidity were significantly and positively correlated with monthly malaria cases in the study area. Regression analysis showed that monthly total rainfall and monthly mean minimum temperature ( R ² = 0.65), at a two-month lagged effect, are the most significant climatic predictors of malaria transmission in Mutale local municipality. A SARIMA (2,1,2) (1,1,1) model fitted with only malaria cases has a prediction performance of about 51%, and the SARIMAX (2,1,2) (1,1,1) model with climatic variables as exogenous factors has a prediction performance of about 72% in malaria cases. The model gives a close comparison between the predicted and observed number of malaria cases, hence indicating that the model provides an acceptable fit to predict the number of malaria cases in the municipality. To sum up, the association between the climatic variables and malaria cases provides clues to better understand the dynamics of malaria transmission. The lagged effect detected in this study can help in adequate planning for malaria intervention.

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.

Simulating Pacific Northwest Forest Response to Climate Change: How We Made Model Results Useful for Vulnerability Assessments

NASA Astrophysics Data System (ADS)

Kim, J. B.; Kerns, B. K.; Halofsky, J.

2014-12-01

GCM-based climate projections and downscaled climate data proliferate, and there are many climate-aware vegetation models in use by researchers. Yet application of fine-scale DGVM based simulation output in national forest vulnerability assessments is not common, because there are technical, administrative and social barriers for their use by managers and policy makers. As part of a science-management climate change adaptation partnership, we performed simulations of vegetation response to climate change for four national forests in the Blue Mountains of Oregon using the MC2 dynamic global vegetation model (DGVM) for use in vulnerability assessments. Our simulation results under business-as-usual scenarios suggest a starkly different future forest conditions for three out of the four national forests in the study area, making their adoption by forest managers a potential challenge. However, using DGVM output to structure discussion of potential vegetation changes provides a suitable framework to discuss the dynamic nature of vegetation change compared to using more commonly available model output (e.g. species distribution models). From the onset, we planned and coordinated our work with national forest managers to maximize the utility and the consideration of the simulation results in planning. Key lessons from this collaboration were: (1) structured and strategic selection of a small number climate change scenarios that capture the range of variability in future conditions simplified results; (2) collecting and integrating data from managers for use in simulations increased support and interest in applying output; (3) a structured, regionally focused, and hierarchical calibration of the DGVM produced well-validated results; (4) simple approaches to quantifying uncertainty in simulation results facilitated communication; and (5) interpretation of model results in a holistic context in relation to multiple lines of evidence produced balanced guidance. This latest point demonstrates the importance of using model out as a forum for discussion along with other information, rather than using model output in an inappropriately predictive sense. These lessons are being applied currently to other national forests in the Pacific Northwest to contribute in vulnerability assessments.

Exploring Air-Climate-Energy Impacts with GCAM-USA

EPA Science Inventory

The Global Climate Assessment Model (GCAM) is a global integrated assessment model used for exploring future scenarios and examining strategies that address air pollution, climate change and energy (ACE) goals. My research focuseson integration of impact factors in GCAM-USA and a...

Multiannual forecasting of seasonal influenza dynamics reveals climatic and evolutionary drivers.

PubMed

Axelsen, Jacob Bock; Yaari, Rami; Grenfell, Bryan T; Stone, Lewi

2014-07-01

Human influenza occurs annually in most temperate climatic zones of the world, with epidemics peaking in the cold winter months. Considerable debate surrounds the relative role of epidemic dynamics, viral evolution, and climatic drivers in driving year-to-year variability of outbreaks. The ultimate test of understanding is prediction; however, existing influenza models rarely forecast beyond a single year at best. Here, we use a simple epidemiological model to reveal multiannual predictability based on high-quality influenza surveillance data for Israel; the model fit is corroborated by simple metapopulation comparisons within Israel. Successful forecasts are driven by temperature, humidity, antigenic drift, and immunity loss. Essentially, influenza dynamics are a balance between large perturbations following significant antigenic jumps, interspersed with nonlinear epidemic dynamics tuned by climatic forcing.

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.

Towards a paradigm shift in the modeling of soil organic carbon decomposition for earth system models

NASA Astrophysics Data System (ADS)

He, Yujie

Soils are the largest terrestrial carbon pools and contain approximately 2200 Pg of carbon. Thus, the dynamics of soil carbon plays an important role in the global carbon cycle and climate system. Earth System Models are used to project future interactions between terrestrial ecosystem carbon dynamics and climate. However, these models often predict a wide range of soil carbon responses and their formulations have lagged behind recent soil science advances, omitting key biogeochemical mechanisms. In contrast, recent mechanistically-based biogeochemical models that explicitly account for microbial biomass pools and enzyme kinetics that catalyze soil carbon decomposition produce notably different results and provide a closer match to recent observations. However, a systematic evaluation of the advantages and disadvantages of the microbial models and how they differ from empirical, first-order formulations in soil decomposition models for soil organic carbon is still needed. This dissertation consists of a series of model sensitivity and uncertainty analyses and identifies dominant decomposition processes in determining soil organic carbon dynamics. Poorly constrained processes or parameters that require more experimental data integration are also identified. This dissertation also demonstrates the critical role of microbial life-history traits (e.g. microbial dormancy) in the modeling of microbial activity in soil organic matter decomposition models. Finally, this study surveys and synthesizes a number of recently published microbial models and provides suggestions for future microbial model developments.

Satellite-Enhanced Dynamical Downscaling of Extreme Events

NASA Astrophysics Data System (ADS)

Nunes, A.

2015-12-01

Severe weather events can be the triggers of environmental disasters in regions particularly susceptible to changes in hydrometeorological conditions. In that regard, the reconstruction of past extreme weather events can help in the assessment of vulnerability and risk mitigation actions. Using novel modeling approaches, dynamical downscaling of long-term integrations from global circulation models can be useful for risk analysis, providing more accurate climate information at regional scales. Originally developed at the National Centers for Environmental Prediction (NCEP), the Regional Spectral Model (RSM) is being used in the dynamical downscaling of global reanalysis, within the South American Hydroclimate Reconstruction Project. Here, RSM combines scale-selective bias correction with assimilation of satellite-based precipitation estimates to downscale extreme weather occurrences. Scale-selective bias correction is a method employed in the downscaling, similar to the spectral nudging technique, in which the downscaled solution develops in agreement with its coarse boundaries. Precipitation assimilation acts on modeled deep-convection, drives the land-surface variables, and therefore the hydrological cycle. During the downscaling of extreme events that took place in Brazil in recent years, RSM continuously assimilated NCEP Climate Prediction Center morphing technique precipitation rates. As a result, RSM performed better than its global (reanalysis) forcing, showing more consistent hydrometeorological fields compared with more sophisticated global reanalyses. Ultimately, RSM analyses might provide better-quality initial conditions for high-resolution numerical predictions in metropolitan areas, leading to more reliable short-term forecasting of severe local storms.

Integrated climate and land change research to improve decision-making and resource management in Southern Africa: The SASSCAL approach

NASA Astrophysics Data System (ADS)

Helmschrot, J.; Olwoch, J. M.

2017-12-01

The ability of countries in southern Africa to jointly respond to climate challenges with scientifically informed and evidence-based actions and policy decisions remains low due to limited scientific research capacity and infrastructure. The Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL; www.sasscal.org) addresses this gap by implementing a high-level framework to guide research and innovation investments in climate change and adaptive land management interventions in Southern Africa. With a strong climate service component as cross-cutting topic, SASSCAL's focus is to improve the understanding of climate and land management change impacts on the natural and socio-economic environment in Southern Africa. The paper presents a variety of SASSCAL driven activities which contribute to better understand climate and long-term environmental change dynamics at various temporal and spatial scales in Southern Afrika and how these activities are linked to support research and decision-making to optimize agricultural practices as well as sustainable environmental and water resources management. To provide consistent and reliable climate information for Southern Africa, SASSCAL offers various climate services ranging from real-time climate observation across the region utilizing the SASSCAL WeatherNet to regional climate change analysis and modelling efforts at seasonal-to-decadal timescales using climate data from various sources. SASSCAL also offers the current state of the environment in terms of recent data on changes in the environment that are necessary for setting appropriate adaptation strategies . The paper will further demonstrate how these services are utilized for interdisciplinary research on the impact of climate change on natural resources and socio-economic development in the SASSCAL countries and how this knowledge can be effectively used to mitigate and adapt to climate change by informed decision-making from farm to regional level.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors.

PubMed

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H; Gambhir, Manoj; Fu, Joshua S; Liu, Yang; Remais, Justin V

2013-09-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis , the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001-2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057-2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses-including altered phenology-of disease vectors to altered climate.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors

PubMed Central

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H.; Gambhir, Manoj; Fu, Joshua S.; Liu, Yang; Remais, Justin V.

2014-01-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001–2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057–2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses—including altered phenology—of disease vectors to altered climate. PMID:24772388

Monitoring Spatial Patterns of Vegetation Phenology in AN Australian Tropical Transect Using Modis Evi

NASA Astrophysics Data System (ADS)

Ma, X.; Huete, A.; Yu, Q.; Davies, K.; Coupe, N. R.

2012-07-01

Phenology is receiving increasing interest in the area of climate change and vegetation adaptation to climate. The phenology of a landscape can be used as a key parameter in land surface models and dynamic global vegetation models to more accurately simulate carbon, water and energy exchanges between land cover and atmosphere. However, the characterisation of phenology is lacking in tropical savannas which cover more than 30% of global land area, and are highly vulnerable to climate change. The objective of this study is to investigate the spatial pattern of vegetation phenology along the Northern Australia Tropical Transect (NATT) where the major biomes are wet and dry tropical savannas. For this analysis we used more than 11 years Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) product from 2000 to 2011. Eight phenological metrics were derived: Start of Season (SOS), End of Season (EOS), Length of Season (LOS), Maximum EVI (MaxG), Minimum EVI (MinG), annual amplitude (AMP), large integral (LIG), and small integral (SIG) were generated for each year and each pixel. Our results showed there are significant spatial patterns and considerable interannual variations of vegetation phenology along the NATT study area. Generally speaking, vegetation growing season started and ended earlier in the north, and started and ended later in the south, resulting in a southward decrease of growing season length (LOS). Vegetation productivity, which was represented by annual integral EVI (LIG), showed a significant descending trend from the northern part of NATT to the southern part. Segmented regression analysis showed that there exists a distinguishable breakpoint along the latitudinal gradient, at least in terms of annual minimum EVI (EVI), which is located between 18.84°S to 20.04°S.

A systematic review of dynamics in climate risk and vulnerability assessments

NASA Astrophysics Data System (ADS)

Jurgilevich, Alexandra; Räsänen, Aleksi; Groundstroem, Fanny; Juhola, Sirkku

2017-01-01

Understanding climate risk is crucial for effective adaptation action, and a number of assessment methodologies have emerged. We argue that the dynamics of the individual components in climate risk and vulnerability assessments has received little attention. In order to highlight this, we systematically reviewed 42 sub-national climate risk and vulnerability assessments. We analysed the assessments using an analytical framework with which we evaluated (1) the conceptual approaches to vulnerability and exposure used, (2) if current or future risks were assessed, and (3) if and how changes over time (i.e. dynamics) were considered. Of the reviewed assessments, over half addressed future risks or vulnerability; and of these future-oriented studies, less than 1/3 considered both vulnerability and exposure dynamics. While the number of studies that include dynamics is growing, and while all studies included socio-economic aspects, often only biophysical dynamics was taken into account. We discuss the challenges of assessing socio-economic and spatial dynamics, particularly the poor availability of data and methods. We suggest that future-oriented studies assessing risk dynamics would benefit from larger stakeholder involvement, discussion of the assessment purpose, the use of multiple methods, inclusion of uncertainty/sensitivity analyses and pathway approaches.

Supporting students' knowledge integration with technology-enhanced inquiry curricula

NASA Astrophysics Data System (ADS)

Chiu, Jennifer Lopseen

Dynamic visualizations of scientific phenomena have the potential to transform how students learn and understand science. Dynamic visualizations enable interaction and experimentation with unobservable atomic-level phenomena. A series of studies clarify the conditions under which embedding dynamic visualizations in technology-enhanced inquiry instruction can help students develop robust and durable chemistry knowledge. Using the knowledge integration perspective, I designed Chemical Reactions, a technology-enhanced curriculum unit, with a partnership of teachers, educational researchers, and chemists. This unit guides students in an exploration of how energy and chemical reactions relate to climate change. It uses powerful dynamic visualizations to connect atomic level interactions to the accumulation of greenhouse gases. The series of studies were conducted in typical classrooms in eleven high schools across the country. This dissertation describes four studies that contribute to understanding of how visualizations can be used to transform chemistry learning. The efficacy study investigated the impact of the Chemical Reactions unit compared to traditional instruction using pre-, post- and delayed posttest assessments. The self-monitoring study used self-ratings in combination with embedded assessments to explore how explanation prompts help students learn from dynamic visualizations. The self-regulation study used log files of students' interactions with the learning environment to investigate how external feedback and explanation prompts influence students' exploration of dynamic visualizations. The explanation study compared specific and general explanation prompts to explore the processes by which explanations benefit learning with dynamic visualizations. These studies delineate the conditions under which dynamic visualizations embedded in inquiry instruction can enhance student outcomes. The studies reveal that visualizations can be deceptively clear, deterring learners from exploring details. Asking students to generate explanations helps them realize what they don't understand and can spur students to revisit visualizations to remedy gaps in their knowledge. The studies demonstrate that science instruction focused on complex topics can succeed by combining visualizations with generative activities to encourage knowledge integration. Students are more successful at monitoring their progress and remedying gaps in knowledge when required to distinguish among alternative explanations. The results inform the design of technology-enhanced science instruction for typical classrooms.

Reconstruction of the dynamics of the climatic system from time-series data

PubMed Central

Nicolis, C.; Nicolis, G.

1986-01-01

The oxygen isotope record of the last million years, as provided by a deep sea core sediment, is analyzed by a method recently developed in the theory of dynamical systems. The analysis suggests that climatic variability is the manifestation of a chaotic dynamics described by an attractor of fractal dimensionality. A quantitative measure of the limited predictability of the climatic system is provided by the evaluation of the time-correlation function and the largest positive Lyapounov exponent of the system. PMID:16593650