Dynamical organization towards consensus in the Axelrod model on complex networks

NASA Astrophysics Data System (ADS)

Guerra, Beniamino; Poncela, Julia; Gómez-Gardeñes, Jesús; Latora, Vito; Moreno, Yamir

2010-05-01

We analyze the dynamics toward cultural consensus in the Axelrod model on scale-free networks. By looking at the microscopic dynamics of the model, we are able to show how culture traits spread across different cultural features. We compare the diffusion at the level of cultural features to the growth of cultural consensus at the global level, finding important differences between these two processes. In particular, we show that even when most of the cultural features have reached macroscopic consensus, there are still no signals of globalization. Finally, we analyze the topology of consensus clusters both for global culture and at the feature level of representation.

The effects of global awareness on the spreading of epidemics in multiplex networks

NASA Astrophysics Data System (ADS)

Zang, Haijuan

2018-02-01

It is increasingly recognized that understanding the complex interplay patterns between epidemic spreading and human behavioral is a key component of successful infection control efforts. In particular, individuals can obtain the information about epidemics and respond by altering their behaviors, which can affect the spreading dynamics as well. Besides, because the existence of herd-like behaviors, individuals are very easy to be influenced by the global awareness information. Here, in this paper, we propose a global awareness controlled spreading model (GACS) to explore the interplay between the coupled dynamical processes. Using the global microscopic Markov chain approach, we obtain the analytical results for the epidemic thresholds, which shows a high accuracy by comparison with lots of Monte Carlo simulations. Furthermore, considering other classical models used to describe the coupled dynamical processes, including the local awareness controlled contagion spreading (LACS) model, Susceptible-Infected-Susceptible-Unaware-Aware-Unaware (SIS-UAU) model and the single layer occasion, we make a detailed comparisons between the GACS with them. Although the comparisons and results depend on the parameters each model has, the GACS model always shows a strong restrain effects on epidemic spreading process. Our results give us a better understanding of the coupled dynamical processes and highlights the importance of considering the spreading of global awareness in the control of epidemics.

Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model

NASA Astrophysics Data System (ADS)

Smith, B.; Wårlind, D.; Arneth, A.; Hickler, T.; Leadley, P.; Siltberg, J.; Zaehle, S.

2013-11-01

The LPJ-GUESS dynamic vegetation model uniquely combines an individual- and patch-based representation of vegetation dynamics with ecosystem biogeochemical cycling from regional to global scales. We present an updated version that includes plant and soil N dynamics, analysing the implications of accounting for C-N interactions on predictions and performance of the model. Stand structural dynamics and allometric scaling of tree growth suggested by global databases of forest stand structure and development were well-reproduced by the model in comparison to an earlier multi-model study. Accounting for N cycle dynamics improved the goodness-of-fit for broadleaved forests. N limitation associated with low N mineralisation rates reduces productivity of cold-climate and dry-climate ecosystems relative to mesic temperate and tropical ecosystems. In a model experiment emulating free-air CO2 enrichment (FACE) treatment for forests globally, N-limitation associated with low N mineralisation rates of colder soils reduces CO2-enhancement of NPP for boreal forests, while some temperate and tropical forests exhibit increased NPP enhancement. Under a business-as-usual future climate and emissions scenario, ecosystem C storage globally was projected to increase by c. 10%; additional N requirements to match this increasing ecosystem C were within the high N supply limit estimated on stoichiometric grounds in an earlier study. Our results highlight the importance of accounting for C-N interactions not only in studies of global terrestrial C cycling, but to understand underlying mechanisms on local scales and in different regional contexts.

Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model

NASA Astrophysics Data System (ADS)

Smith, B.; Wårlind, D.; Arneth, A.; Hickler, T.; Leadley, P.; Siltberg, J.; Zaehle, S.

2014-04-01

The LPJ-GUESS dynamic vegetation model uniquely combines an individual- and patch-based representation of vegetation dynamics with ecosystem biogeochemical cycling from regional to global scales. We present an updated version that includes plant and soil N dynamics, analysing the implications of accounting for C-N interactions on predictions and performance of the model. Stand structural dynamics and allometric scaling of tree growth suggested by global databases of forest stand structure and development were well reproduced by the model in comparison to an earlier multi-model study. Accounting for N cycle dynamics improved the goodness of fit for broadleaved forests. N limitation associated with low N-mineralisation rates reduces productivity of cold-climate and dry-climate ecosystems relative to mesic temperate and tropical ecosystems. In a model experiment emulating free-air CO2 enrichment (FACE) treatment for forests globally, N limitation associated with low N-mineralisation rates of colder soils reduces CO2 enhancement of net primary production (NPP) for boreal forests, while some temperate and tropical forests exhibit increased NPP enhancement. Under a business-as-usual future climate and emissions scenario, ecosystem C storage globally was projected to increase by ca. 10%; additional N requirements to match this increasing ecosystem C were within the high N supply limit estimated on stoichiometric grounds in an earlier study. Our results highlight the importance of accounting for C-N interactions in studies of global terrestrial N cycling, and as a basis for understanding mechanisms on local scales and in different regional contexts.

Global dynamics of a delay differential equation with spatial non-locality in an unbounded domain

NASA Astrophysics Data System (ADS)

Yi, Taishan; Zou, Xingfu

In this paper, we study the global dynamics of a class of differential equations with temporal delay and spatial non-locality in an unbounded domain. Adopting the compact open topology, we describe the delicate asymptotic properties of the nonlocal delayed effect and establish some a priori estimate for nontrivial solutions which enables us to show the permanence of the equation. Combining these results with a dynamical systems approach, we determine the global dynamics of the equation under appropriate conditions. Applying the main results to the model with Ricker's birth function and Mackey-Glass's hematopoiesis function, we obtain threshold results for the global dynamics of these two models. We explain why our results on the global attractivity of the positive equilibrium in C∖{0} under the compact open topology becomes invalid in C∖{0} with respect to the usual supremum norm, and we identify a subset of C∖{0} in which the positive equilibrium remains attractive with respect to the supremum norm.

Global Scale Atmospheric Processes Research Program Review

NASA Technical Reports Server (NTRS)

Worley, B. A. (Editor); Peslen, C. A. (Editor)

1984-01-01

Global modeling; satellite data assimilation and initialization; simulation of future observing systems; model and observed energetics; dynamics of planetary waves; First Global Atmospheric Research Program Global Experiment (FGGE) diagnosis studies; and National Research Council Research Associateship Program are discussed.

[Review of dynamic global vegetation models (DGVMs)].

PubMed

Che, Ming-Liang; Chen, Bao-Zhang; Wang, Ying; Guo, Xiang-Yun

2014-01-01

Dynamic global vegetation model (DGVM) is an important and efficient tool for study on the terrestrial carbon circle processes and vegetation dynamics. This paper reviewed the development history of DGVMs, introduced the basic structure of DGVMs, and the outlines of several world-widely used DGVMs, including CLM-DGVM, LPJ, IBIS and SEIB. The shortages of the description of dynamic vegetation mechanisms in the current DGVMs were proposed, including plant functional types (PFT) scheme, vegetation competition, disturbance, and phenology. Then the future research directions of DGVMs were pointed out, i. e. improving the PFT scheme, refining the vegetation dynamic mechanism, and implementing a model inter-comparison project.

Swarming UAS II

DTIC Science & Technology

2010-05-05

employed biomimicry to model a swarm of UAS as a colony of ants, where each UAS dynamically updates a global memory map, allowing pheromone-like...matter of design, DSE-R-0808 employed biomimicry to model a swarm of UAS as a colony of ants, where each UAS dynamically updates a global memory map

On dynamical systems approaches and methods in f ( R ) cosmology

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

Alho, Artur; Carloni, Sante; Uggla, Claes, E-mail: aalho@math.ist.utl.pt, E-mail: sante.carloni@tecnico.ulisboa.pt, E-mail: claes.uggla@kau.se

We discuss dynamical systems approaches and methods applied to flat Robertson-Walker models in f ( R )-gravity. We argue that a complete description of the solution space of a model requires a global state space analysis that motivates globally covering state space adapted variables. This is shown explicitly by an illustrative example, f ( R ) = R + α R {sup 2}, α > 0, for which we introduce new regular dynamical systems on global compactly extended state spaces for the Jordan and Einstein frames. This example also allows us to illustrate several local and global dynamical systems techniquesmore » involving, e.g., blow ups of nilpotent fixed points, center manifold analysis, averaging, and use of monotone functions. As a result of applying dynamical systems methods to globally state space adapted dynamical systems formulations, we obtain pictures of the entire solution spaces in both the Jordan and the Einstein frames. This shows, e.g., that due to the domain of the conformal transformation between the Jordan and Einstein frames, not all the solutions in the Jordan frame are completely contained in the Einstein frame. We also make comparisons with previous dynamical systems approaches to f ( R ) cosmology and discuss their advantages and disadvantages.« less

Global warming description using Daisyworld model with greenhouse gases.

PubMed

Paiva, Susana L D; Savi, Marcelo A; Viola, Flavio M; Leiroz, Albino J K

2014-11-01

Daisyworld is an archetypal model of the earth that is able to describe the global regulation that can emerge from the interaction between life and environment. This article proposes a model based on the original Daisyworld considering greenhouse gases emission and absorption, allowing the description of the global warming phenomenon. Global and local analyses are discussed evaluating the influence of greenhouse gases in the planet dynamics. Numerical simulations are carried out showing the general qualitative behavior of the Daisyworld for different scenarios that includes solar luminosity variations and greenhouse gases effect. Nonlinear dynamics perspective is of concern discussing a way that helps the comprehension of the global warming phenomenon. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Using Models to Inform Policy: Insights from Modeling the Complexities of Global Polio Eradication

NASA Astrophysics Data System (ADS)

Thompson, Kimberly M.

Drawing on over 20 years of experience modeling risks in complex systems, this talk will challenge SBP participants to develop models that provide timely and useful answers to critical policy questions when decision makers need them. The talk will include reflections on the opportunities and challenges associated with developing integrated models for complex problems and communicating their results effectively. Dr. Thompson will focus the talk largely on collaborative modeling related to global polio eradication and the application of system dynamics tools. After successful global eradication of wild polioviruses, live polioviruses will still present risks that could potentially lead to paralytic polio cases. This talk will present the insights of efforts to use integrated dynamic, probabilistic risk, decision, and economic models to address critical policy questions related to managing global polio risks. Using a dynamic disease transmission model combined with probabilistic model inputs that characterize uncertainty for a stratified world to account for variability, we find that global health leaders will face some difficult choices, but that they can take actions that will manage the risks effectively. The talk will emphasize the need for true collaboration between modelers and subject matter experts, and the importance of working with decision makers as partners to ensure the development of useful models that actually get used.

An integrated model of soil, hydrology, and vegetation for carbon dynamics in wetland ecosystems

Treesearch

Yu Zhang; Changsheng Li; Carl C. Trettin; Harbin Li; Ge Sun

2002-01-01

Wetland ecosystems are an important component in global carbon (C) cycles and may exert a large influence on global clinlate change. Predictions of C dynamics require us to consider interactions among many critical factors of soil, hydrology, and vegetation. However, few such integrated C models exist for wetland ecosystems. In this paper, we report a simulation model...

Study of atmospheric dynamics

NASA Technical Reports Server (NTRS)

Mcnider, Richard T.; Christy, John R.; Cox, Gregory N.

1993-01-01

In order to better understand the dynamics of the global atmosphere, a data set of precision temperature measurements was developed using the NASA built Microwave Sounding Unit. Modeling research was carried out to validate global model outputs using various satellite data. Idealized flows in a rotating annulus were studied and applied to the general circulation of the atmosphere. Dynamic stratospheric ozone fluctuations were investigated. An extensive bibliography and several reprints are appended.

An improved empirical dynamic control system model of global mean sea level rise and surface temperature change

NASA Astrophysics Data System (ADS)

Wu, Qing; Luu, Quang-Hung; Tkalich, Pavel; Chen, Ge

2018-04-01

Having great impacts on human lives, global warming and associated sea level rise are believed to be strongly linked to anthropogenic causes. Statistical approach offers a simple and yet conceptually verifiable combination of remotely connected climate variables and indices, including sea level and surface temperature. We propose an improved statistical reconstruction model based on the empirical dynamic control system by taking into account the climate variability and deriving parameters from Monte Carlo cross-validation random experiments. For the historic data from 1880 to 2001, we yielded higher correlation results compared to those from other dynamic empirical models. The averaged root mean square errors are reduced in both reconstructed fields, namely, the global mean surface temperature (by 24-37%) and the global mean sea level (by 5-25%). Our model is also more robust as it notably diminished the unstable problem associated with varying initial values. Such results suggest that the model not only enhances significantly the global mean reconstructions of temperature and sea level but also may have a potential to improve future projections.

Global dynamic modeling of a transmission system

NASA Technical Reports Server (NTRS)

Choy, F. K.; Qian, W.

1993-01-01

The work performed on global dynamic simulation and noise correlation of gear transmission systems at the University of Akron is outlined. The objective is to develop a comprehensive procedure to simulate the dynamics of the gear transmission system coupled with the effects of gear box vibrations. The developed numerical model is benchmarked with results from experimental tests at NASA Lewis Research Center. The modal synthesis approach is used to develop the global transient vibration analysis procedure used in the model. Modal dynamic characteristics of the rotor-gear-bearing system are calculated by the matrix transfer method while those of the gear box are evaluated by the finite element method (NASTRAN). A three-dimensional, axial-lateral coupled bearing model is used to couple the rotor vibrations with the gear box motion. The vibrations between the individual rotor systems are coupled through the nonlinear gear mesh interactions. The global equations of motion are solved in modal coordinates and the transient vibration of the system is evaluated by a variable time-stepping integration scheme. The relationship between housing vibration and resulting noise of the gear transmission system is generated by linear transfer functions using experimental data. A nonlinear relationship of the noise components to the fundamental mesh frequency is developed using the hypercoherence function. The numerically simulated vibrations and predicted noise of the gear transmission system are compared with the experimental results from the gear noise test rig at NASA Lewis Research Center. Results of the comparison indicate that the global dynamic model developed can accurately simulate the dynamics of a gear transmission system.

Neocortical dynamics due to axon propagation delays in cortico-cortical fibers: EEG traveling and standing waves with implications for top-down influences on local networks and white matter disease

PubMed Central

Nunez, Paul L.; Srinivasan, Ramesh

2013-01-01

The brain is treated as a nested hierarchical complex system with substantial interactions across spatial scales. Local networks are pictured as embedded within global fields of synaptic action and action potentials. Global fields may act top-down on multiple networks, acting to bind remote networks. Because of scale-dependent properties, experimental electrophysiology requires both local and global models that match observational scales. Multiple local alpha rhythms are embedded in a global alpha rhythm. Global models are outlined in which cm-scale dynamic behaviors result largely from propagation delays in cortico-cortical axons and cortical background excitation level, controlled by neuromodulators on long time scales. The idealized global models ignore the bottom-up influences of local networks on global fields so as to employ relatively simple mathematics. The resulting models are transparently related to several EEG and steady state visually evoked potentials correlated with cognitive states, including estimates of neocortical coherence structure, traveling waves, and standing waves. The global models suggest that global oscillatory behavior of self-sustained (limit-cycle) modes lower than about 20 Hz may easily occur in neocortical/white matter systems provided: Background cortical excitability is sufficiently high; the strength of long cortico-cortical axon systems is sufficiently high; and the bottom-up influence of local networks on the global dynamic field is sufficiently weak. The global models provide "entry points" to more detailed studies of global top-down influences, including binding of weakly connected networks, modulation of gamma oscillations by theta or alpha rhythms, and the effects of white matter deficits. PMID:24505628

Top-down constraints on disturbance dynamics in the terrestrial carbon cycle: effects at global and regional scales

NASA Astrophysics Data System (ADS)

Bloom, A. A.; Exbrayat, J. F.; van der Velde, I.; Peters, W.; Williams, M.

2014-12-01

Large uncertainties preside over terrestrial carbon flux estimates on a global scale. In particular, the strongly coupled dynamics between net ecosystem productivity and disturbance C losses are poorly constrained. To gain an improved understanding of ecosystem C dynamics from regional to global scale, we apply a Markov Chain Monte Carlo based model-data-fusion approach into the CArbon DAta-MOdel fraMework (CARDAMOM). We assimilate MODIS LAI and burned area, plant-trait data, and use the Harmonized World Soil Database (HWSD) and maps of above ground biomass as prior knowledge for initial conditions. We optimize model parameters based on (a) globally spanning observations and (b) ecological and dynamic constraints that force single parameter values and parameter inter-dependencies to be representative of real world processes. We determine the spatial and temporal dynamics of major terrestrial C fluxes and model parameter values on a global scale (GPP = 123 +/- 8 Pg C yr-1 & NEE = -1.8 +/- 2.7 Pg C yr-1). We further show that the incorporation of disturbance fluxes, and accounting for their instantaneous or delayed effect, is of critical importance in constraining global C cycle dynamics, particularly in the tropics. In a higher resolution case study centred on the Amazon Basin we show how fires not only trigger large instantaneous emissions of burned matter, but also how they are responsible for a sustained reduction of up to 50% in plant uptake following the depletion of biomass stocks. The combination of these two fire-induced effects leads to a 1 g C m-2 d-1reduction in the strength of the net terrestrial carbon sink. Through our simulations at regional and global scale, we advocate the need to assimilate disturbance metrics in global terrestrial carbon cycle models to bridge the gap between globally spanning terrestrial carbon cycle data and the full dynamics of the ecosystem C cycle. Disturbances are especially important because their quick occurrence may have long-term effects on ecosystems. Our synthetic simulations show that while tropical ecosystems uptake may reach pre-disturbance level after a decade, biomass stocks would most likely need more than a century to recover from a single extreme disturbance event.

Global dynamics of a network-based SIQRS epidemic model with demographics and vaccination

NASA Astrophysics Data System (ADS)

Huang, Shouying; Chen, Fengde; Chen, Lijuan

2017-02-01

This paper investigates a new SIQRS epidemic model with demographics and vaccination on complex heterogeneous networks. We analytically derive the basic reproduction number R0, which determines not only the existence of endemic equilibrium but also the global dynamics of the model. The permanence of the disease and the globally asymptotical stability of disease-free equilibrium are proved in detail. By using a monotone iterative technique, we show that the unique endemic equilibrium is globally attractive under certain conditions. Our results really improve and enrich the results in Li et al (2014) [14]. Interestingly, the basic reproduction number R0 bears no relation to the degree-dependent birth, but our simulations indicate that the degree-dependent birth does affect the epidemic dynamics. Furthermore, we find that quarantine plays a more active role than vaccination in controlling the disease.

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.

The topology of non-linear global carbon dynamics: from tipping points to planetary boundaries

NASA Astrophysics Data System (ADS)

Anderies, J. M.; Carpenter, S. R.; Steffen, Will; Rockström, Johan

2013-12-01

We present a minimal model of land use and carbon cycle dynamics and use it to explore the relationship between non-linear dynamics and planetary boundaries. Only the most basic interactions between land cover and terrestrial, atmospheric, and marine carbon stocks are considered in the model. Our goal is not to predict global carbon dynamics as it occurs in the actual Earth System. Rather, we construct a conceptually reasonable heuristic model of a feedback system between different carbon stocks that captures the qualitative features of the actual Earth System and use it to explore the topology of the boundaries of what can be called a ‘safe operating space’ for humans. The model analysis illustrates the existence of dynamic, non-linear tipping points in carbon cycle dynamics and the potential complexity of planetary boundaries. Finally, we use the model to illustrate some challenges associated with navigating planetary boundaries.

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.

A Coupled Ocean General Circulation, Biogeochemical, and Radiative Model of the Global Oceans: Seasonal Distributions of Ocean Chlorophyll and Nutrients

NASA Technical Reports Server (NTRS)

Gregg, Watson W.; Busalacchi, Antonio (Technical Monitor)

2000-01-01

A coupled ocean general circulation, biogeochemical, and radiative model was constructed to evaluate and understand the nature of seasonal variability of chlorophyll and nutrients in the global oceans. Biogeochemical processes in the model are determined from the influences of circulation and turbulence dynamics, irradiance availability. and the interactions among three functional phytoplankton groups (diatoms. chlorophytes, and picoplankton) and three nutrients (nitrate, ammonium, and silicate). Basin scale (greater than 1000 km) model chlorophyll results are in overall agreement with CZCS pigments in many global regions. Seasonal variability observed in the CZCS is also represented in the model. Synoptic scale (100-1000 km) comparisons of imagery are generally in conformance although occasional departures are apparent. Model nitrate distributions agree with in situ data, including seasonal dynamics, except for the equatorial Atlantic. The overall agreement of the model with satellite and in situ data sources indicates that the model dynamics offer a reasonably realistic simulation of phytoplankton and nutrient dynamics on synoptic scales. This is especially true given that initial conditions are homogenous chlorophyll fields. The success of the model in producing a reasonable representation of chlorophyll and nutrient distributions and seasonal variability in the global oceans is attributed to the application of a generalized, processes-driven approach as opposed to regional parameterization and the existence of multiple phytoplankton groups with different physiological and physical properties. These factors enable the model to simultaneously represent many aspects of the great diversity of physical, biological, chemical, and radiative environments encountered in the global oceans.

Global simulation of interactions between groundwater and terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Braakhekke, M. C.; Rebel, K.; Dekker, S. C.; Smith, B.; Van Beek, L. P.; Sutanudjaja, E.; van Kampenhout, L.; Wassen, M. J.

2016-12-01

In many places in the world ecosystems are influenced by the presence of a shallow groundwater table. In these regions upward water flux due to capillary rise increases soil moisture availability in the root zone, which has strong positive effect on evapotranspiration. Additionally it has important consequences for vegetation dynamics and fluxes of carbon and nitrogen. Under water limited conditions shallow groundwater stimulates vegetation productivity, and soil organic matter decomposition while under saturated conditions groundwater may have a negative effect on these processes due to lack of oxygen. Furthermore, since plant species differ with respect to their root distribution, preference for moisture conditions, and resistance to oxygen stress, shallow groundwater also influences vegetation type. Finally, processes such as denitrification and methane production occur under strictly anaerobic conditions and are thus strongly influenced by moisture availability. Most global hydrological models and several land surface models simulate groundwater table dynamics and their effects on land surface processes. However, these models typically have relatively simplistic representation of vegetation and do not consider changes in vegetation type and structure and are therefore less suitable to represent effects of groundwater on biogeochemical fluxes. Dynamic global vegetation models (DGVMs), describe land surface from an ecological perspective, combining detailed description of vegetation dynamics and structure and biogeochemical processes. These models are thus more appropriate to simulate the ecological and biogeochemical effects of groundwater interactions. However, currently virtually all DGVMs ignore these effects, assuming that water tables are too deep to affect soil moisture in the root zone. We have implemented a tight coupling between the dynamic global ecosystem model LPJ-GUESS and the global hydrological model PCR-GLOBWB. Using this coupled model we aim to study the influence of shallow groundwater on terrestrial ecosystem processes. We will present results of global simulations to demonstrate the effects on C, N, and water fluxes.

Global dynamics in a stoichiometric food chain model with two limiting nutrients.

PubMed

Chen, Ming; Fan, Meng; Kuang, Yang

2017-07-01

Ecological stoichiometry studies the balance of energy and multiple chemical elements in ecological interactions to establish how the nutrient content affect food-web dynamics and nutrient cycling in ecosystems. In this study, we formulate a food chain with two limiting nutrients in the form of a stoichiometric population model. A comprehensive global analysis of the rich dynamics of the targeted model is explored both analytically and numerically. Chaotic dynamic is observed in this simple stoichiometric food chain model and is compared with traditional model without stoichiometry. The detailed comparison reveals that stoichiometry can reduce the parameter space for chaotic dynamics. Our findings also show that decreasing producer production efficiency may have only a small effect on the consumer growth but a more profound impact on the top predator growth. Copyright © 2017 Elsevier Inc. All rights reserved.

Dynamic Analysis of the Melanoma Model: From Cancer Persistence to Its Eradication

NASA Astrophysics Data System (ADS)

Starkov, Konstantin E.; Jimenez Beristain, Laura

In this paper, we study the global dynamics of the five-dimensional melanoma model developed by Kronik et al. This model describes interactions of tumor cells with cytotoxic T cells and respective cytokines under cellular immunotherapy. We get the ultimate upper and lower bounds for variables of this model, provide formulas for equilibrium points and present local asymptotic stability/hyperbolic instability conditions. Next, we prove the existence of the attracting set. Based on these results we come to global asymptotic melanoma eradication conditions via global stability analysis. Finally, we provide bounds for a locus of the melanoma persistence equilibrium point, study the case of melanoma persistence and describe conditions under which we observe global attractivity to the unique melanoma persistence equilibrium point.

Global modeling of soil evaporation efficiency for a chosen soil type

NASA Astrophysics Data System (ADS)

Georgiana Stefan, Vivien; Mangiarotti, Sylvain; Merlin, Olivier; Chanzy, André

2016-04-01

One way of reproducing the dynamics of a system is by deriving a set of differential, difference or discrete equations directly from observational time series. A method for obtaining such a system is the global modeling technique [1]. The approach is here applied to the dynamics of soil evaporative efficiency (SEE), defined as the ratio of actual to potential evaporation. SEE is an interesting variable to study since it is directly linked to soil evaporation (LE) which plays an important role in the water cycle and since it can be easily derived from satellite measurements. One goal of the present work is to get a semi-empirical parameter that could account for the variety of the SEE dynamical behaviors resulting from different soil properties. Before trying to obtain such a semi-empirical parameter with the global modeling technique, it is first necessary to prove that this technique can be applied to the dynamics of SEE without any a priori information. The global modeling technique is thus applied here to a synthetic series of SEE, reconstructed from the TEC (Transfert Eau Chaleur) model [2]. It is found that an autonomous chaotic model can be retrieved for the dynamics of SEE. The obtained model is four-dimensional and exhibits a complex behavior. The comparison of the original and the model phase portraits shows a very good consistency that proves that the original dynamical behavior is well described by the model. To evaluate the model accuracy, the forecasting error growth is estimated. To get a robust estimate of this error growth, the forecasting error is computed for prediction horizons of 0 to 9 hours, starting from different initial conditions and statistics of the error growth are thus performed. Results show that, for a maximum error level of 40% of the signal variance, the horizon of predictability is close to 3 hours, approximately one third of the diurnal part of day. These results are interesting for various reasons. To the best of our knowledge, it is the very first time that a chaotic model is obtained for the SEE. It also shows that the SEE dynamics can be approximated by a low-dimensional autonomous model. From a theoretical point of view, it is also interesting to note that only very few low-dimensional models could be directly obtained for environmental dynamics, and that four-dimensional models are even rarer. Since a model could be obtained for the SEE, it can be expected, now, to adapt the global modeling technique and to apply it to a range of different soil conditions in order to get a global model that would account for the variability of soil properties. [1] MANGIAROTTI S., COUDRET R., DRAPEAU L., JARLAN L. Polynomial search and global modeling: two algorithms for modeling chaos. Physical Review E, 86(4), 046205, 2012. [2] CHANZY A., MUMEN M., RICHARD G. Accuracy of the top soil moisture simulation using a mechanistic model with limited soil characterization. Water Resources Research, 44, W03432, 2008.

Scaling law analysis of paraffin thin films on different surfaces

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

Dotto, M. E. R.; Camargo, S. S. Jr.

2010-01-15

The dynamics of paraffin deposit formation on different surfaces was analyzed based on scaling laws. Carbon-based films were deposited onto silicon (Si) and stainless steel substrates from methane (CH{sub 4}) gas using radio frequency plasma enhanced chemical vapor deposition. The different substrates were characterized with respect to their surface energy by contact angle measurements, surface roughness, and morphology. Paraffin thin films were obtained by the casting technique and were subsequently characterized by an atomic force microscope in noncontact mode. The results indicate that the morphology of paraffin deposits is strongly influenced by substrates used. Scaling laws analysis for coated substratesmore » present two distinct dynamics: a local roughness exponent ({alpha}{sub local}) associated to short-range surface correlations and a global roughness exponent ({alpha}{sub global}) associated to long-range surface correlations. The local dynamics is described by the Wolf-Villain model, and a global dynamics is described by the Kardar-Parisi-Zhang model. A local correlation length (L{sub local}) defines the transition between the local and global dynamics with L{sub local} approximately 700 nm in accordance with the spacing of planes measured from atomic force micrographs. For uncoated substrates, the growth dynamics is related to Edwards-Wilkinson model.« less

Observations & modeling of solar-wind/magnetospheric interactions

NASA Astrophysics Data System (ADS)

Hoilijoki, Sanni; Von Alfthan, Sebastian; Pfau-Kempf, Yann; Palmroth, Minna; Ganse, Urs

2016-07-01

The majority of the global magnetospheric dynamics is driven by magnetic reconnection, indicating the need to understand and predict reconnection processes and their global consequences. So far, global magnetospheric dynamics has been simulated using mainly magnetohydrodynamic (MHD) models, which are approximate but fast enough to be executed in real time or near-real time. Due to their fast computation times, MHD models are currently the only possible frameworks for space weather predictions. However, in MHD models reconnection is not treated kinetically. In this presentation we will compare the results from global kinetic (hybrid-Vlasov) and global MHD simulations. Both simulations are compared with in-situ measurements. We will show that the kinetic processes at the bow shock, in the magnetosheath and at the magnetopause affect global dynamics even during steady solar wind conditions. Foreshock processes cause an asymmetry in the magnetosheath plasma, indicating that the plasma entering the magnetosphere is not symmetrical on different sides of the magnetosphere. Behind the bow shock in the magnetosheath kinetic wave modes appear. Some of these waves propagate to the magnetopause and have an effect on the magnetopause reconnection. Therefore we find that kinetic phenomena have a significant role in the interaction between the solar wind and the magnetosphere. While kinetic models cannot be executed in real time currently, they could be used to extract heuristics to be added in the faster MHD models.

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...

Seasonal Distributions of Global Ocean Chlorophyll and Nutrients: Analysis with a Coupled Ocean General Circulation Biogeochemical, and Radiative Model

NASA Technical Reports Server (NTRS)

Gregg, Watson W.

1999-01-01

A coupled general ocean circulation, biogeochemical, and radiative model was constructed to evaluate and understand the nature of seasonal variability of chlorophyll and nutrients in the global oceans. The model is driven by climatological meteorological conditions, cloud cover, and sea surface temperature. Biogeochemical processes in the model are determined from the influences of circulation and turbulence dynamics, irradiance availability, and the interactions among three functional phytoplankton groups (diatoms, chorophytes, and picoplankton) and three nutrient groups (nitrate, ammonium, and silicate). Phytoplankton groups are initialized as homogeneous fields horizontally and vertically, and allowed to distribute themselves according to the prevailing conditions. Basin-scale model chlorophyll results are in very good agreement with CZCS pigments in virtually every global region. Seasonal variability observed in the CZCS is also well represented in the model. Synoptic scale (100-1000 km) comparisons of imagery are also in good conformance, although occasional departures are apparent. Agreement of nitrate distributions with in situ data is even better, including seasonal dynamics, except for the equatorial Atlantic. The good agreement of the model with satellite and in situ data sources indicates that the model dynamics realistically simulate phytoplankton and nutrient dynamics on synoptic scales. This is especially true given that initial conditions are homogenous chlorophyll fields. The success of the model in producing a reasonable representation of chlorophyll and nutrient distributions and seasonal variability in the global oceans is attributed to the application of a generalized, processes-driven approach as opposed to regional parameterization, and the existence of multiple phytoplankton groups with different physiological and physical properties. These factors enable the model to simultaneously represent the great diversity of physical, biological, chemical, and radiative environments encountered in the global oceans.

Next Generation Community Based Unified Global Modeling System Development and Operational Implementation Strategies at NCEP

NASA Astrophysics Data System (ADS)

Tallapragada, V.

2017-12-01

NOAA's Next Generation Global Prediction System (NGGPS) has provided the unique opportunity to develop and implement a non-hydrostatic global model based on Geophysical Fluid Dynamics Laboratory (GFDL) Finite Volume Cubed Sphere (FV3) Dynamic Core at National Centers for Environmental Prediction (NCEP), making a leap-step advancement in seamless prediction capabilities across all spatial and temporal scales. Model development efforts are centralized with unified model development in the NOAA Environmental Modeling System (NEMS) infrastructure based on Earth System Modeling Framework (ESMF). A more sophisticated coupling among various earth system components is being enabled within NEMS following National Unified Operational Prediction Capability (NUOPC) standards. The eventual goal of unifying global and regional models will enable operational global models operating at convective resolving scales. Apart from the advanced non-hydrostatic dynamic core and coupling to various earth system components, advanced physics and data assimilation techniques are essential for improved forecast skill. NGGPS is spearheading ambitious physics and data assimilation strategies, concentrating on creation of a Common Community Physics Package (CCPP) and Joint Effort for Data Assimilation Integration (JEDI). Both initiatives are expected to be community developed, with emphasis on research transitioning to operations (R2O). The unified modeling system is being built to support the needs of both operations and research. Different layers of community partners are also established with specific roles/responsibilities for researchers, core development partners, trusted super-users, and operations. Stakeholders are engaged at all stages to help drive the direction of development, resources allocations and prioritization. This talk presents the current and future plans of unified model development at NCEP for weather, sub-seasonal, and seasonal climate prediction applications with special emphasis on implementation of NCEP FV3 Global Forecast System (GFS) and Global Ensemble Forecast System (GEFS) into operations by 2019.

Stability of a general delayed virus dynamics model with humoral immunity and cellular infection

NASA Astrophysics Data System (ADS)

Elaiw, A. M.; Raezah, A. A.; Alofi, A. S.

2017-06-01

In this paper, we investigate the dynamical behavior of a general nonlinear model for virus dynamics with virus-target and infected-target incidences. The model incorporates humoral immune response and distributed time delays. The model is a four dimensional system of delay differential equations where the production and removal rates of the virus and cells are given by general nonlinear functions. We derive the basic reproduction parameter R˜0 G and the humoral immune response activation number R˜1 G and establish a set of conditions on the general functions which are sufficient to determine the global dynamics of the models. We use suitable Lyapunov functionals and apply LaSalle's invariance principle to prove the global asymptotic stability of the all equilibria of the model. We confirm the theoretical results by numerical simulations.

The Representation of Tropical Cyclones Within the Global William Putman Non-Hydrostatic Goddard Earth Observing System Model (GEOS-5) at Cloud-Permitting Resolutions

NASA Technical Reports Server (NTRS)

Putman, William M.

2010-01-01

The Goddard Earth Observing System Model (GEOS-S), 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-S from irs standard 72-level 27-km resolution (approx.5.5 million cells covering the globe from the surface to 0.1 hPa) down to 3.5-km (approx. 3.6 billion cells).

Observations of geographically correlated orbit errors for TOPEX/Poseidon using the global positioning system

NASA Technical Reports Server (NTRS)

Christensen, E. J.; Haines, B. J.; Mccoll, K. C.; Nerem, R. S.

1994-01-01

We have compared Global Positioning System (GPS)-based dynamic and reduced-dynamic TOPEX/Poseidon orbits over three 10-day repeat cycles of the ground-track. The results suggest that the prelaunch joint gravity model (JGM-1) introduces geographically correlated errors (GCEs) which have a strong meridional dependence. The global distribution and magnitude of these GCEs are consistent with a prelaunch covariance analysis, with estimated and predicted global rms error statistics of 2.3 and 2.4 cm rms, respectively. Repeating the analysis with the post-launch joint gravity model (JGM-2) suggests that a portion of the meridional dependence observed in JGM-1 still remains, with global rms error of 1.2 cm.

The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations

NASA Astrophysics Data System (ADS)

Walters, David; Boutle, Ian; Brooks, Malcolm; Melvin, Thomas; Stratton, Rachel; Vosper, Simon; Wells, Helen; Williams, Keith; Wood, Nigel; Allen, Thomas; Bushell, Andrew; Copsey, Dan; Earnshaw, Paul; Edwards, John; Gross, Markus; Hardiman, Steven; Harris, Chris; Heming, Julian; Klingaman, Nicholas; Levine, Richard; Manners, James; Martin, Gill; Milton, Sean; Mittermaier, Marion; Morcrette, Cyril; Riddick, Thomas; Roberts, Malcolm; Sanchez, Claudio; Selwood, Paul; Stirling, Alison; Smith, Chris; Suri, Dan; Tennant, Warren; Vidale, Pier Luigi; Wilkinson, Jonathan; Willett, Martin; Woolnough, Steve; Xavier, Prince

2017-04-01

We describe Global Atmosphere 6.0 and Global Land 6.0 (GA6.0/GL6.0): the latest science configurations of the Met Office Unified Model and JULES (Joint UK Land Environment Simulator) land surface model developed for use across all timescales. Global Atmosphere 6.0 includes the ENDGame (Even Newer Dynamics for General atmospheric modelling of the environment) dynamical core, which significantly increases mid-latitude variability improving a known model bias. Alongside developments of the model's physical parametrisations, ENDGame also increases variability in the tropics, which leads to an improved representation of tropical cyclones and other tropical phenomena. Further developments of the atmospheric and land surface parametrisations improve other aspects of model performance, including the forecasting of surface weather phenomena. We also describe GA6.1/GL6.1, which includes a small number of long-standing differences from our main trunk configurations that we continue to require for operational global weather prediction. Since July 2014, GA6.1/GL6.1 has been used by the Met Office for operational global numerical weather prediction, whilst GA6.0/GL6.0 was implemented in its remaining global prediction systems over the following year.

A model for oscillations and pattern formation in protoplasmic droplets of Physarum polycephalum

NASA Astrophysics Data System (ADS)

Radszuweit, M.; Engel, H.; Bär, M.

2010-12-01

A mechano-chemical model for the spatiotemporal dynamics of free calcium and the thickness in protoplasmic droplets of the true slime mold Physarum polycephalum is derived starting from a physiologically detailed description of intracellular calcium oscillations proposed by Smith and Saldana (Biopys. J. 61, 368 (1992)). First, we have modified the Smith-Saldana model for the temporal calcium dynamics in order to reproduce the experimentally observed phase relation between calcium and mechanical tension oscillations. Then, we formulate a model for spatiotemporal dynamics by adding spatial coupling in the form of calcium diffusion and advection due to calcium-dependent mechanical contraction. In another step, the resulting reaction-diffusion model with mechanical coupling is simplified to a reaction-diffusion model with global coupling that approximates the mechanical part. We perform a bifurcation analysis of the local dynamics and observe a Hopf bifurcation upon increase of a biochemical activity parameter. The corresponding reaction-diffusion model with global coupling shows regular and chaotic spatiotemporal behaviour for parameters with oscillatory dynamics. In addition, we show that the global coupling leads to a long-wavelength instability even for parameters where the local dynamics possesses a stable spatially homogeneous steady state. This instability causes standing waves with a wavelength of twice the system size in one dimension. Simulations of the model in two dimensions are found to exhibit defect-mediated turbulence as well as various types of spiral wave patterns in qualitative agreement with earlier experimental observation by Takagi and Ueda (Physica D, 237, 420 (2008)).

Linking models and data on vegetation structure

NASA Astrophysics Data System (ADS)

Hurtt, G. C.; Fisk, J.; Thomas, R. Q.; Dubayah, R.; Moorcroft, P. R.; Shugart, H. H.

2010-06-01

For more than a century, scientists have recognized the importance of vegetation structure in understanding forest dynamics. Now future satellite missions such as Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI) hold the potential to provide unprecedented global data on vegetation structure needed to reduce uncertainties in terrestrial carbon dynamics. Here, we briefly review the uses of data on vegetation structure in ecosystem models, develop and analyze theoretical models to quantify model-data requirements, and describe recent progress using a mechanistic modeling approach utilizing a formal scaling method and data on vegetation structure to improve model predictions. Generally, both limited sampling and coarse resolution averaging lead to model initialization error, which in turn is propagated in subsequent model prediction uncertainty and error. In cases with representative sampling, sufficient resolution, and linear dynamics, errors in initialization tend to compensate at larger spatial scales. However, with inadequate sampling, overly coarse resolution data or models, and nonlinear dynamics, errors in initialization lead to prediction error. A robust model-data framework will require both models and data on vegetation structure sufficient to resolve important environmental gradients and tree-level heterogeneity in forest structure globally.

Persistence of Soil Organic Carbon can be Explained as an Emergent Property of Microbial Ecology and Population Dynamics

NASA Astrophysics Data System (ADS)

Woolf, D.; Lehmann, J.

2016-12-01

The exchange of carbon between soils and the atmosphere represents an important uncertainty in climate predictions. Current Earth system models apply soil organic matter (SOM) models based on independent carbon pools with 1st order decomposition dynamics. It has been widely argued over the last decade that such models do not accurately describe soil processes and mechanisms. For example, the long term persistence of soil organic carbon (SOC) is only adequately described by such models by the post hoc assumption of passive or inert carbon pools. Further, such 1st order models also fail to account for microbially-mediated dynamics such as priming interactions. These shortcomings may limit their applicability to long term predictions under conditions of global environmental change. In addition to incorporating recent conceptual advances in the mechanisms of SOM decomposition and protection, next-generation SOM models intended for use in Earth system models need to meet further quality criteria. Namely, that they should (a) accurately describe historical data from long term trials and the current global distribution of soil organic carbon, (b) be computationally efficient for large number of iterations involved in climate modeling, and (c) have sufficiently simple parameterization that they can be run on spatially-explicit data available at global scale under varying conditions of global change over long time scales. Here we show that linking fundamental ecological principles and microbial population dynamics to SOC turnover rates results in a dynamic model that meets all of these quality criteria. This approach simultaneously eliminates the need to postulate biogeochemically-implausible passive or inert pools, instead showing how SOM persistence emerges from ecological principles, while also reproducing observed priming interactions.

Mathematical Modelling of Plankton-Oxygen Dynamics Under the Climate Change.

PubMed

Sekerci, Yadigar; Petrovskii, Sergei

2015-12-01

Ocean dynamics is known to have a strong effect on the global climate change and on the composition of the atmosphere. In particular, it is estimated that about 70% of the atmospheric oxygen is produced in the oceans due to the photosynthetic activity of phytoplankton. However, the rate of oxygen production depends on water temperature and hence can be affected by the global warming. In this paper, we address this issue theoretically by considering a model of a coupled plankton-oxygen dynamics where the rate of oxygen production slowly changes with time to account for the ocean warming. We show that a sustainable oxygen production is only possible in an intermediate range of the production rate. If, in the course of time, the oxygen production rate becomes too low or too high, the system's dynamics changes abruptly, resulting in the oxygen depletion and plankton extinction. Our results indicate that the depletion of atmospheric oxygen on global scale (which, if happens, obviously can kill most of life on Earth) is another possible catastrophic consequence of the global warming, a global ecological disaster that has been overlooked.

Global change and terrestrial plant community dynamics

DOE PAGES

Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.; ...

2016-02-29

Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this article, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on amore » literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Lastly, monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change.« less

Global change and terrestrial plant community dynamics

PubMed Central

Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.; Regan, Helen M.

2016-01-01

Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this paper, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on a literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change. PMID:26929338

The Earth's Population Can Reach 14 Billion in the 23rd Century without Significant Adverse Effects on Survivability.

PubMed

Krapivin, Vladimir F; Varotsos, Costas A; Soldatov, Vladimir Yu

2017-08-07

This paper presents the results obtained from the study of the sustainable state between nature and human society on a global scale, focusing on the most critical interactions between the natural and anthropogenic processes. Apart from the conventional global models, the basic tool employed herein is the newly proposed complex model entitled "nature-society system (NSS) model", through which a reliable modeling of the processes taking place in the global climate-nature-society system (CNSS) is achieved. This universal tool is mainly based on the information technology that allows the adaptive conformance of the parametric and functional space of this model. The structure of this model includes the global biogeochemical cycles, the hydrological cycle, the demographic processes and a simple climate model. In this model, the survivability indicator is used as a criterion for the survival of humanity, which defines a trend in the dynamics of the total biomass of the biosphere, taking into account the trends of the biocomplexity dynamics of the land and hydrosphere ecosystems. It should be stressed that there are no other complex global models comparable to those of the CNSS model developed here. The potential of this global model is demonstrated through specific examples in which the classification of the terrestrial ecosystem is accomplished by separating 30 soil-plant formations for geographic pixels 4° × 5°. In addition, humanity is considered to be represented by three groups of economic development status (high, transition, developing) and the World Ocean is parameterized by three latitude zones (low, middle, high). The modelling results obtained show the dynamics of the CNSS at the beginning of the 23rd century, according to which the world population can reach the level of 14 billion without the occurrence of major negative impacts.

Assessing global vegetation activity using spatio-temporal Bayesian modelling

NASA Astrophysics Data System (ADS)

Mulder, Vera L.; van Eck, Christel M.; Friedlingstein, Pierre; Regnier, Pierre A. G.

2016-04-01

This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support our hypothesis. That is, the change of vegetation in space and time may be better understood when modelling vegetation change as both a dynamic and multivariate process. Therefore, future research will focus on a multivariate dynamical spatio-temporal modelling approach. This ongoing research is performed within the context of the project "Global impacts of hydrological and climatic extremes on vegetation" (project acronym: SAT-EX) which is part of the Belgian research programme for Earth Observation Stereo III.

The status and challenge of global fire modelling

DOE PAGES

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; ...

2016-06-09

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less

The status and challenge of global fire modelling

NASA Astrophysics Data System (ADS)

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; Kelley, Douglas I.; Prentice, I. Colin; Rabin, Sam S.; Archibald, Sally; Mouillot, Florent; Arnold, Steve R.; Artaxo, Paulo; Bachelet, Dominique; Ciais, Philippe; Forrest, Matthew; Friedlingstein, Pierre; Hickler, Thomas; Kaplan, Jed O.; Kloster, Silvia; Knorr, Wolfgang; Lasslop, Gitta; Li, Fang; Mangeon, Stephane; Melton, Joe R.; Meyn, Andrea; Sitch, Stephen; Spessa, Allan; van der Werf, Guido R.; Voulgarakis, Apostolos; Yue, Chao

2016-06-01

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.

The status and challenge of global fire modelling

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

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less

Predictive Multiple Model Switching Control with the Self-Organizing Map

NASA Technical Reports Server (NTRS)

Motter, Mark A.

2000-01-01

A predictive, multiple model control strategy is developed by extension of self-organizing map (SOM) local dynamic modeling of nonlinear autonomous systems to a control framework. Multiple SOMs collectively model the global response of a nonautonomous system to a finite set of representative prototype controls. Each SOM provides a codebook representation of the dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the global minimization of a similarity metric. The SOM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme that selects the best available model for the applied control. SOM based linear models are used to predict the response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal.

Dynamic model updating based on strain mode shape and natural frequency using hybrid pattern search technique

NASA Astrophysics Data System (ADS)

Guo, Ning; Yang, Zhichun; Wang, Le; Ouyang, Yan; Zhang, Xinping

2018-05-01

Aiming at providing a precise dynamic structural finite element (FE) model for dynamic strength evaluation in addition to dynamic analysis. A dynamic FE model updating method is presented to correct the uncertain parameters of the FE model of a structure using strain mode shapes and natural frequencies. The strain mode shape, which is sensitive to local changes in structure, is used instead of the displacement mode for enhancing model updating. The coordinate strain modal assurance criterion is developed to evaluate the correlation level at each coordinate over the experimental and the analytical strain mode shapes. Moreover, the natural frequencies which provide the global information of the structure are used to guarantee the accuracy of modal properties of the global model. Then, the weighted summation of the natural frequency residual and the coordinate strain modal assurance criterion residual is used as the objective function in the proposed dynamic FE model updating procedure. The hybrid genetic/pattern-search optimization algorithm is adopted to perform the dynamic FE model updating procedure. Numerical simulation and model updating experiment for a clamped-clamped beam are performed to validate the feasibility and effectiveness of the present method. The results show that the proposed method can be used to update the uncertain parameters with good robustness. And the updated dynamic FE model of the beam structure, which can correctly predict both the natural frequencies and the local dynamic strains, is reliable for the following dynamic analysis and dynamic strength evaluation.

A variable resolution nonhydrostatic global atmospheric semi-implicit semi-Lagrangian model

NASA Astrophysics Data System (ADS)

Pouliot, George Antoine

2000-10-01

The objective of this project is to develop a variable-resolution finite difference adiabatic global nonhydrostatic semi-implicit semi-Lagrangian (SISL) model based on the fully compressible nonhydrostatic atmospheric equations. To achieve this goal, a three-dimensional variable resolution dynamical core was developed and tested. The main characteristics of the dynamical core can be summarized as follows: Spherical coordinates were used in a global domain. A hydrostatic/nonhydrostatic switch was incorporated into the dynamical equations to use the fully compressible atmospheric equations. A generalized horizontal variable resolution grid was developed and incorporated into the model. For a variable resolution grid, in contrast to a uniform resolution grid, the order of accuracy of finite difference approximations is formally lost but remains close to the order of accuracy associated with the uniform resolution grid provided the grid stretching is not too significant. The SISL numerical scheme was implemented for the fully compressible set of equations. In addition, the generalized minimum residual (GMRES) method with restart and preconditioner was used to solve the three-dimensional elliptic equation derived from the discretized system of equations. The three-dimensional momentum equation was integrated in vector-form to incorporate the metric terms in the calculations of the trajectories. Using global re-analysis data for a specific test case, the model was compared to similar SISL models previously developed. Reasonable agreement between the model and the other independently developed models was obtained. The Held-Suarez test for dynamical cores was used for a long integration and the model was successfully integrated for up to 1200 days. Idealized topography was used to test the variable resolution component of the model. Nonhydrostatic effects were simulated at grid spacings of 400 meters with idealized topography and uniform flow. Using a high-resolution topographic data set and the variable resolution grid, sets of experiments with increasing resolution were performed over specific regions of interest. Using realistic initial conditions derived from re-analysis fields, nonhydrostatic effects were significant for grid spacings on the order of 0.1 degrees with orographic forcing. If the model code was adapted for use in a message passing interface (MPI) on a parallel supercomputer today, it was estimated that a global grid spacing of 0.1 degrees would be achievable for a global model. In this case, nonhydrostatic effects would be significant for most areas. A variable resolution grid in a global model provides a unified and flexible approach to many climate and numerical weather prediction problems. The ability to configure the model from very fine to very coarse resolutions allows for the simulation of atmospheric phenomena at different scales using the same code. We have developed a dynamical core illustrating the feasibility of using a variable resolution in a global model.

Temperature-driven regime shifts in the dynamics of size-structured populations.

PubMed

Ohlberger, Jan; Edeline, Eric; Vøllestad, Leif Asbjørn; Stenseth, Nils C; Claessen, David

2011-02-01

Global warming impacts virtually all biota and ecosystems. Many of these impacts are mediated through direct effects of temperature on individual vital rates. Yet how this translates from the individual to the population level is still poorly understood, hampering the assessment of global warming impacts on population structure and dynamics. Here, we study the effects of temperature on intraspecific competition and cannibalism and the population dynamical consequences in a size-structured fish population. We use a physiologically structured consumer-resource model in which we explicitly model the temperature dependencies of the consumer vital rates and the resource population growth rate. Our model predicts that increased temperature decreases resource density despite higher resource growth rates, reflecting stronger intraspecific competition among consumers. At a critical temperature, the consumer population dynamics destabilize and shift from a stable equilibrium to competition-driven generation cycles that are dominated by recruits. As a consequence, maximum age decreases and the proportion of younger and smaller-sized fish increases. These model predictions support the hypothesis of decreasing mean body sizes due to increased temperatures. We conclude that in size-structured fish populations, global warming may increase competition, favor smaller size classes, and induce regime shifts that destabilize population and community dynamics.

The synergistic use of models and observations: understanding the mechanisms behind observed biomass dynamics at 14 Amazonian field sites and the implications for future biomass change

NASA Astrophysics Data System (ADS)

Levine, N. M.; Galbraith, D.; Christoffersen, B. J.; Imbuzeiro, H. A.; Restrepo-Coupe, N.; Malhi, Y.; Saleska, S. R.; Costa, M. H.; Phillips, O.; Andrade, A.; Moorcroft, P. R.

2011-12-01

The Amazonian rainforests play a vital role in global water, energy and carbon cycling. The sensitivity of this system to natural and anthropogenic disturbances therefore has important implications for the global climate. Some global models have predicted large-scale forest dieback and the savannization of Amazonia over the next century [Meehl et al., 2007]. While several studies have demonstrated the sensitivity of dynamic global vegetation models to changes in temperature, precipitation, and dry season length [e.g. Galbraith et al., 2010; Good et al., 2011], the ability of these models to accurately reproduce ecosystem dynamics of present-day transitional or low biomass tropical forests has not been demonstrated. A model-data intercomparison was conducted with four state-of-the-art terrestrial ecosystem models to evaluate the ability of these models to accurately represent structure, function, and long-term biomass dynamics over a range of Amazonian ecosystems. Each modeling group conducted a series of simulations for 14 sites including mature forest, transitional forest, savannah, and agricultural/pasture sites. All models were run using standard physical parameters and the same initialization procedure. Model results were compared against forest inventory and dendrometer data in addition to flux tower measurements. While the models compared well against field observations for the mature forest sites, significant differences were observed between predicted and measured ecosystem structure and dynamics for the transitional forest and savannah sites. The length of the dry season and soil sand content were good predictors of model performance. In addition, for the big leaf models, model performance was highest for sites dominated by late successional trees and lowest for sites with predominantly early and mid-successional trees. This study provides insight into tropical forest function and sensitivity to environmental conditions that will aid in predictions of the response of the Amazonian rainforest to future anthropogenically induced changes.

Modeling Climate Dynamically

ERIC Educational Resources Information Center

Walsh, Jim; McGehee, Richard

2013-01-01

A dynamical systems approach to energy balance models of climate is presented, focusing on low order, or conceptual, models. Included are global average and latitude-dependent, surface temperature models. The development and analysis of the differential equations and corresponding bifurcation diagrams provides a host of appropriate material for…

Vision-based navigation in a dynamic environment for virtual human

NASA Astrophysics Data System (ADS)

Liu, Yan; Sun, Ji-Zhou; Zhang, Jia-Wan; Li, Ming-Chu

2004-06-01

Intelligent virtual human is widely required in computer games, ergonomics software, virtual environment and so on. We present a vision-based behavior modeling method to realize smart navigation in a dynamic environment. This behavior model can be divided into three modules: vision, global planning and local planning. Vision is the only channel for smart virtual actor to get information from the outside world. Then, the global and local planning module use A* and D* algorithm to find a way for virtual human in a dynamic environment. Finally, the experiments on our test platform (Smart Human System) verify the feasibility of this behavior model.

Application of TOPEX/Poseidon altimetry to ocean dynamics and geophysics

NASA Technical Reports Server (NTRS)

Douglas, Bruce; Cheney, R.; Miller, L.; Mcadoo, D.; Leetmaa, A.; Schopf, P.; Schwiderski, E. W.

1991-01-01

We will analyze the TOPEX/POSEIDON data using techniques developed for Geosat, although the more accurate TOPEX/POSEIDON data will enable a wider range of problems to be addressed. Our proposed investigations will have five distinct areas: (1) a description of global sea level variability; (2) tropical ocean dynamics; (3) coupled models for El Nino prediction; (4) structure of the lithosphere; and (5) global tide model improvement.

Nitrogen and Phosphorus Plant Uptake During Periods with no Photosynthesis Accounts for About Half of Global Annual Uptake

NASA Astrophysics Data System (ADS)

Riley, W. J.; Zhu, Q.; Tang, J.

2017-12-01

Uncertainties in current Earth System Model (ESM) predictions of terrestrial carbon-climate feedbacks over the 21st century are as large as, or larger than, any other reported natural system uncertainties. Soil Organic Matter (SOM) decomposition and photosynthesis, the dominant fluxes in this regard, are tightly linked through nutrient availability, and the recent Coupled Model Inter-comparison Project 5 (CMIP5) used for climate change assessment had no credible representations of these constraints. In response, many ESM land models (ESMLMs) have developed dynamic and coupled soil and plant nutrient cycles. Here we quantify terrestrial carbon cycle impacts from well-known observed plant nutrient uptake mechanisms ignored in most current ESMLMs. In particular, we estimate the global role of plant root nutrient competition with microbes and abiotic process at night and during the non-growing season using the ACME land model (ALMv1-ECA-CNP) that explicitly represents these dynamics. We first demonstrate that short-term nutrient uptake dynamics and competition between plants and microbes are accurately predicted by the model compared to 15N and 33P isotopic tracer measurements from more than 20 sites. We then show that global nighttime and non-growing season nitrogen and phosphorus uptake accounts for 46 and 45%, respectively, of annual uptake, with large latitudinal variation. Model experiments show that ignoring these plant uptake periods leads to large positive biases in annual N leaching (globally 58%) and N2O emissions (globally 68%). Biases these large will affect modeled carbon cycle dynamics over time, and lead to predictions of ecosystems that have overly open nutrient cycles and therefore lower capacity to sequester carbon.

The Dynamical Core Model Intercomparison Project (DCMIP-2016): Results of the Supercell Test Case

NASA Astrophysics Data System (ADS)

Zarzycki, C. M.; Reed, K. A.; Jablonowski, C.; Ullrich, P. A.; Kent, J.; Lauritzen, P. H.; Nair, R. D.

2016-12-01

The 2016 Dynamical Core Model Intercomparison Project (DCMIP-2016) assesses the modeling techniques for global climate and weather models and was recently held at the National Center for Atmospheric Research (NCAR) in conjunction with a two-week summer school. Over 12 different international modeling groups participated in DCMIP-2016 and focused on the evaluation of the newest non-hydrostatic dynamical core designs for future high-resolution weather and climate models. The paper highlights the results of the third DCMIP-2016 test case, which is an idealized supercell storm on a reduced-radius Earth. The supercell storm test permits the study of a non-hydrostatic moist flow field with strong vertical velocities and associated precipitation. This test assesses the behavior of global modeling systems at extremely high spatial resolution and is used in the development of next-generation numerical weather prediction capabilities. In this regime the effective grid spacing is very similar to the horizontal scale of convective plumes, emphasizing resolved non-hydrostatic dynamics. The supercell test case sheds light on the physics-dynamics interplay and highlights the impact of diffusion on model solutions.

The Virtual Brain: Modeling Biological Correlates of Recovery after Chronic Stroke

PubMed Central

Falcon, Maria Inez; Riley, Jeffrey D.; Jirsa, Viktor; McIntosh, Anthony R.; Shereen, Ahmed D.; Chen, E. Elinor; Solodkin, Ana

2015-01-01

There currently remains considerable variability in stroke survivor recovery. To address this, developing individualized treatment has become an important goal in stroke treatment. As a first step, it is necessary to determine brain dynamics associated with stroke and recovery. While recent methods have made strides in this direction, we still lack physiological biomarkers. The Virtual Brain (TVB) is a novel application for modeling brain dynamics that simulates an individual’s brain activity by integrating their own neuroimaging data with local biophysical models. Here, we give a detailed description of the TVB modeling process and explore model parameters associated with stroke. In order to establish a parallel between this new type of modeling and those currently in use, in this work we establish an association between a specific TVB parameter (long-range coupling) that increases after stroke with metrics derived from graph analysis. We used TVB to simulate the individual BOLD signals for 20 patients with stroke and 10 healthy controls. We performed graph analysis on their structural connectivity matrices calculating degree centrality, betweenness centrality, and global efficiency. Linear regression analysis demonstrated that long-range coupling is negatively correlated with global efficiency (P = 0.038), but is not correlated with degree centrality or betweenness centrality. Our results suggest that the larger influence of local dynamics seen through the long-range coupling parameter is closely associated with a decreased efficiency of the system. We thus propose that the increase in the long-range parameter in TVB (indicating a bias toward local over global dynamics) is deleterious because it reduces communication as suggested by the decrease in efficiency. The new model platform TVB hence provides a novel perspective to understanding biophysical parameters responsible for global brain dynamics after stroke, allowing the design of focused therapeutic interventions. PMID:26579071

State estimation improves prospects for ocean research

NASA Astrophysics Data System (ADS)

Stammer, Detlef; Wunsch, C.; Fukumori, I.; Marshall, J.

Rigorous global ocean state estimation methods can now be used to produce dynamically consistent time-varying model/data syntheses, the results of which are being used to study a variety of important scientific problems. Figure 1 shows a schematic of a complete ocean observing and synthesis system that includes global observations and state-of-the-art ocean general circulation models (OGCM) run on modern computer platforms. A global observing system is described in detail in Smith and Koblinsky [2001],and the present status of ocean modeling and anticipated improvements are addressed by Griffies et al. [2001]. Here, the focus is on the third component of state estimation: the synthesis of the observations and a model into a unified, dynamically consistent estimate.

Modeling spatial-temporal dynamics of global wetlands: Comprehensive evaluation of a new sub-grid TOPMODEL parameterization and uncertainties

NASA Astrophysics Data System (ADS)

Zhang, Z.; Zimmermann, N. E.; Poulter, B.

2015-12-01

Simulations of the spatial-temporal dynamics of wetlands is key to understanding the role of wetland biogeochemistry under past and future climate variability. Hydrologic inundation models, such as TOPMODEL, are based on a fundamental parameter known as the compound topographic index (CTI) and provide a computationally cost-efficient approach to simulate global wetland dynamics. However, there remains large discrepancy in the implementations of TOPMODEL in land-surface models (LSMs) and thus their performance against observations. This study describes new improvements to TOPMODEL implementation and estimates of global wetland dynamics using the LPJ-wsl DGVM, and quantifies uncertainties by comparing three digital elevation model products (HYDRO1k, GMTED, and HydroSHEDS) at different spatial resolution and accuracy on simulated inundation dynamics. We found that calibrating TOPMODEL with a benchmark dataset can help to successfully predict the seasonal and interannual variations of wetlands, as well as improve the spatial distribution of wetlands to be consistent with inventories. The HydroSHEDS DEM, using a river-basin scheme for aggregating the CTI, shows best accuracy for capturing the spatio-temporal dynamics of wetland among three DEM products. This study demonstrates the feasibility to capture spatial heterogeneity of inundation and to estimate seasonal and interannual variations in wetland by coupling a hydrological module in LSMs with appropriate benchmark datasets. It additionally highlight the importance of an adequate understanding of topographic indices for simulating global wetlands and show the opportunity to converge wetland estimations in LSMs by identifying the uncertainty associated with existing wetland products.

Attitude control with realization of linear error dynamics

NASA Technical Reports Server (NTRS)

Paielli, Russell A.; Bach, Ralph E.

1993-01-01

An attitude control law is derived to realize linear unforced error dynamics with the attitude error defined in terms of rotation group algebra (rather than vector algebra). Euler parameters are used in the rotational dynamics model because they are globally nonsingular, but only the minimal three Euler parameters are used in the error dynamics model because they have no nonlinear mathematical constraints to prevent the realization of linear error dynamics. The control law is singular only when the attitude error angle is exactly pi rad about any eigenaxis, and a simple intuitive modification at the singularity allows the control law to be used globally. The forced error dynamics are nonlinear but stable. Numerical simulation tests show that the control law performs robustly for both initial attitude acquisition and attitude control.

Projected continent-wide declines of the emperor penguin under climate change

NASA Astrophysics Data System (ADS)

Jenouvrier, Stéphanie; Holland, Marika; Stroeve, Julienne; Serreze, Mark; Barbraud, Christophe; Weimerskirch, Henri; Caswell, Hal

2014-08-01

Climate change has been projected to affect species distribution and future trends of local populations, but projections of global population trends are rare. We analyse global population trends of the emperor penguin (Aptenodytes forsteri), an iconic Antarctic top predator, under the influence of sea ice conditions projected by coupled climate models assessed in the Intergovernmental Panel on Climate Change (IPCC) effort. We project the dynamics of all 45 known emperor penguin colonies by forcing a sea-ice-dependent demographic model with local, colony-specific, sea ice conditions projected through to the end of the twenty-first century. Dynamics differ among colonies, but by 2100 all populations are projected to be declining. At least two-thirds are projected to have declined by >50% from their current size. The global population is projected to have declined by at least 19%. Because criteria to classify species by their extinction risk are based on the global population dynamics, global analyses are critical for conservation. We discuss uncertainties arising in such global projections and the problems of defining conservation criteria for species endangered by future climate change.

Tropical Tree Trait Diversity Enhances Forest Biomass Resilience in a Dynamic Global Vegetation Model

NASA Astrophysics Data System (ADS)

Sakschewski, B.; Kirsten, T.; von Bloh, W.; Poorter, L.; Pena-Claros, M.; Boit, A.

2016-12-01

Functional diversity of ecosystems has been found to increase ecosystem functions and therefore enhance ecosystem resilience against environmental stressors. However, global carbon-cycle and biosphere models still classify the global vegetation into a relatively small number of distinct plant functional types (PFT) with constant features over space and time. Therefore, those models might underestimate the resilience and adaptive capacity of natural vegetation under climate change by ignoring positive effects that functional diversity might bring about. We diversified a set a of selected tree traits in a dynamic global vegetation model (LPJmL). In the new subversion, called LPJmL-FIT, Amazon region biomass stocks and forest structure appear significantly more resilient against climate change. Enhanced tree trait diversity enables the simulated rainforests to adjust to new environmental conditions via ecological sorting. These results may stimulate a new debate on the value of biodiversity for climate change mitigation.

Research Review, 1983

NASA Technical Reports Server (NTRS)

1984-01-01

The Global Modeling and Simulation Branch (GMSB) of the Laboratory for Atmospheric Sciences (GLAS) is engaged in general circulation modeling studies related to global atmospheric and oceanographic research. The research activities discussed are organized into two disciplines: Global Weather/Observing Systems and Climate/Ocean-Air Interactions. The Global Weather activities are grouped in four areas: (1) Analysis and Forecast Studies, (2) Satellite Observing Systems, (3) Analysis and Model Development, (4) Atmospheric Dynamics and Diagnostic Studies. The GLAS Analysis/Forecast/Retrieval System was applied to both FGGE and post FGGE periods. The resulting analyses have already been used in a large number of theoretical studies of atmospheric dynamics, forecast impact studies and development of new or improved algorithms for the utilization of satellite data. Ocean studies have focused on the analysis of long-term global sea surface temperature data, for use in the study of the response of the atmosphere to sea surface temperature anomalies. Climate research has concentrated on the simulation of global cloudiness, and on the sensitivities of the climate to sea surface temperature and ground wetness anomalies.

Langevin Equation for DNA Dynamics

NASA Astrophysics Data System (ADS)

Grych, David; Copperman, Jeremy; Guenza, Marina

Under physiological conditions, DNA oligomers can contain well-ordered helical regions and also flexible single-stranded regions. We describe the site-specific motion of DNA with a modified Rouse-Zimm Langevin equation formalism that describes DNA as a coarse-grained polymeric chain with global structure and local flexibility. The approach has successfully described the protein dynamics in solution and has been extended to nucleic acids. Our approach provides diffusive mode analytical solutions for the dynamics of global rotational diffusion and internal motion. The internal DNA dynamics present a rich energy landscape that accounts for an interior where hydrogen bonds and base-stacking determine structure and experience limited solvent exposure. We have implemented several models incorporating different coarse-grained sites with anisotropic rotation, energy barrier crossing, and local friction coefficients that include a unique internal viscosity and our models reproduce dynamics predicted by atomistic simulations. The models reproduce bond autocorrelation along the sequence as compared to that directly calculated from atomistic molecular dynamics simulations. The Langevin equation approach captures the essence of DNA dynamics without a cumbersome atomistic representation.

Simulating PACE Global Ocean Radiances

NASA Technical Reports Server (NTRS)

Gregg, Watson W.; Rousseaux, Cecile S.

2017-01-01

The NASA PACE mission is a hyper-spectral radiometer planned for launch in the next decade. It is intended to provide new information on ocean biogeochemical constituents by parsing the details of high resolution spectral absorption and scattering. It is the first of its kind for global applications and as such, poses challenges for design and operation. To support pre-launch mission development and assess on-orbit capabilities, the NASA Global Modeling and Assimilation Office has developed a dynamic simulation of global water-leaving radiances, using an ocean model containing multiple ocean phytoplankton groups, particulate detritus, particulate inorganic carbon (PIC), and chromophoric dissolved organic carbon (CDOC) along with optical absorption and scattering processes at 1 nm spectral resolution. The purpose here is to assess the skill of the dynamic model and derived global radiances. Global bias, uncertainty, and correlation are derived using available modern satellite radiances at moderate spectral resolution. Total chlorophyll, PIC, and the absorption coefficient of CDOC (aCDOC), are simultaneously assimilated to improve the fidelity of the optical constituent fields. A 5-year simulation showed statistically significant (P < 0.05) comparisons of chlorophyll (r = 0.869), PIC (r = 0.868), and a CDOC (r =0.890) with satellite data. Additionally, diatoms (r = 0.890), cyanobacteria (r = 0.732), and coccolithophores (r = 0.716) were significantly correlated with in situ data. Global assimilated distributions of optical constituents were coupled with a radiative transfer model (Ocean-Atmosphere Spectral Irradiance Model, OASIM) to estimate normalized water-leaving radiances at 1 nm for the spectral range 250-800 nm. These unassimilated radiances were within 0.074 mW/sq cm/micron/sr of MODIS-Aqua radiances at 412, 443, 488, 531, 547, and 667 nm. This difference represented a bias of 10.4% (model low). A mean correlation of 0.706 (P < 0.05) was found with global distributions of MODIS radiances. These results suggest skill in the global assimilated model and resulting radiances. The reported error characterization suggests that the global dynamical simulation can support some aspects of mission design and analysis. For example, the high spectral resolution of the simulation supports investigations of band selection. The global nature of the radiance representations supports investigations of satellite observing scenarios. Global radiances at bands not available in current and past missions support investigations of mission capability. PACE, ocean color, water-leaving radiances, biogeochemical model, radiative transfer model

An Intercomparison of the Dynamical Cores of Global Atmospheric Circulation Models for Mars

NASA Technical Reports Server (NTRS)

Hollingsworth, Jeffery L.; Bridger, Alison F. C.; Haberle, Robert M.

1998-01-01

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. The focus of this JRI has been to evaluate the dynamical 'cores' of two global atmospheric circulation models for Mars that are in operation at the NASA Ames Research Center. The two global circulation models in use are fundamentally different: one uses spherical harmonics in its horizontal representation of field variables; the other uses finite differences on a uniform longitude-latitude grid. Several simulations have been conducted to assess how the dynamical processors of each of these circulation models perform using identical 'simple physics' parameterizations. A variety of climate statistics (e.g., time-mean flows and eddy fields) have been compared for realistic solstitial mean basic states. Results of this research have demonstrated that the two Mars circulation models with completely different spatial representations and discretizations produce rather similar circulation statistics for first-order meteorological fields, suggestive of a tendency for convergence of numerical solutions. Second and higher-order fields can, however, vary significantly between the two models.

An Intercomparison of the Dynamical Cores of Global Atmospheric Circulation Models for Mars

NASA Technical Reports Server (NTRS)

Hollingsworth, Jeffery L.; Bridger, Alison F. C.; Haberle, Robert M.

1998-01-01

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Cen- ter and San Jose State University, Department of Meteorology. The focus of this JRI has been to evaluate the dynamical "cores" of two global atmospheric circulation models for Mars that are in operation at the NASA Ames Research Center. ne two global circulation models in use are fundamentally different: one uses spherical harmonics in its horizontal representation of field variables; the other uses finite differences on a uniform longitude-latitude grid. Several simulations have been conducted to assess how the dynamical processors of each of these circulation models perform using identical "simple physics" parameterizations. A variety of climate statistics (e.g., time-mean flows and eddy fields) have been compared for realistic solstitial mean basic states. Results of this research have demonstrated that the two Mars circulation models with completely different spatial representations and discretizations produce rather similar circulation statistics for first-order meteorological fields, suggestive of a tendency for convergence of numerical solutions. Second and higher-order fields can, however, vary significantly between the two models.

Learning Human Actions by Combining Global Dynamics and Local Appearance.

PubMed

Luo, Guan; Yang, Shuang; Tian, Guodong; Yuan, Chunfeng; Hu, Weiming; Maybank, Stephen J

2014-12-01

In this paper, we address the problem of human action recognition through combining global temporal dynamics and local visual spatio-temporal appearance features. For this purpose, in the global temporal dimension, we propose to model the motion dynamics with robust linear dynamical systems (LDSs) and use the model parameters as motion descriptors. Since LDSs live in a non-Euclidean space and the descriptors are in non-vector form, we propose a shift invariant subspace angles based distance to measure the similarity between LDSs. In the local visual dimension, we construct curved spatio-temporal cuboids along the trajectories of densely sampled feature points and describe them using histograms of oriented gradients (HOG). The distance between motion sequences is computed with the Chi-Squared histogram distance in the bag-of-words framework. Finally we perform classification using the maximum margin distance learning method by combining the global dynamic distances and the local visual distances. We evaluate our approach for action recognition on five short clips data sets, namely Weizmann, KTH, UCF sports, Hollywood2 and UCF50, as well as three long continuous data sets, namely VIRAT, ADL and CRIM13. We show competitive results as compared with current state-of-the-art methods.

Global culture: A noise-induced transition in finite systems

NASA Astrophysics Data System (ADS)

Klemm, Konstantin; Eguíluz, Víctor M.; Toral, Raúl; Miguel, Maxi San

2003-04-01

We analyze the effect of cultural drift, modeled as noise, in Axelrod’s model for the dissemination of culture. The disordered multicultural frozen configurations are found not to be stable. This general result is proven rigorously in d=1, where the dynamics is described in terms of a Lyapunov potential. In d=2, the dynamics is governed by the average relaxation time T of perturbations. Noise at a rate r≲T-1 induces monocultural configurations, whereas r≳T-1 sustains disorder. In the thermodynamic limit, the relaxation time diverges and global polarization persists in spite of a dynamics of local convergence.

Nonlinear dynamics of global atmospheric and Earth-system processes

NASA Technical Reports Server (NTRS)

Saltzman, Barry; Ebisuzaki, Wesley; Maasch, Kirk A.; Oglesby, Robert; Pandolfo, Lionel

1990-01-01

Researchers are continuing their studies of the nonlinear dynamics of global weather systems. Sensitivity analyses of large-scale dynamical models of the atmosphere (i.e., general circulation models i.e., GCM's) were performed to establish the role of satellite-signatures of soil moisture, sea surface temperature, snow cover, and sea ice as crucial boundary conditions determining global weather variability. To complete their study of the bimodality of the planetary wave states, they are using the dynamical systems approach to construct a low-order theoretical explanation of this phenomenon. This work should have important implications for extended range forecasting of low-frequency oscillations, elucidating the mechanisms for the transitions between the two wave modes. Researchers are using the methods of jump analysis and attractor dimension analysis to examine the long-term satellite records of significant variables (e.g., long wave radiation, and cloud amount), to explore the nature of mode transitions in the atmosphere, and to determine the minimum number of equations needed to describe the main weather variations with a low-order dynamical system. Where feasible they will continue to explore the applicability of the methods of complex dynamical systems analysis to the study of the global earth-system from an integrative viewpoint involving the roles of geochemical cycling and the interactive behavior of the atmosphere, hydrosphere, and biosphere.

Dynamics of Bacterial Gene Regulatory Networks.

PubMed

Shis, David L; Bennett, Matthew R; Igoshin, Oleg A

2018-05-20

The ability of bacterial cells to adjust their gene expression program in response to environmental perturbation is often critical for their survival. Recent experimental advances allowing us to quantitatively record gene expression dynamics in single cells and in populations coupled with mathematical modeling enable mechanistic understanding on how these responses are shaped by the underlying regulatory networks. Here, we review how the combination of local and global factors affect dynamical responses of gene regulatory networks. Our goal is to discuss the general principles that allow extrapolation from a few model bacteria to less understood microbes. We emphasize that, in addition to well-studied effects of network architecture, network dynamics are shaped by global pleiotropic effects and cell physiology.

Understanding system dynamics of an adaptive enzyme network from globally profiled kinetic parameters.

PubMed

Chiang, Austin W T; Liu, Wei-Chung; Charusanti, Pep; Hwang, Ming-Jing

2014-01-15

A major challenge in mathematical modeling of biological systems is to determine how model parameters contribute to systems dynamics. As biological processes are often complex in nature, it is desirable to address this issue using a systematic approach. Here, we propose a simple methodology that first performs an enrichment test to find patterns in the values of globally profiled kinetic parameters with which a model can produce the required system dynamics; this is then followed by a statistical test to elucidate the association between individual parameters and different parts of the system's dynamics. We demonstrate our methodology on a prototype biological system of perfect adaptation dynamics, namely the chemotaxis model for Escherichia coli. Our results agreed well with those derived from experimental data and theoretical studies in the literature. Using this model system, we showed that there are motifs in kinetic parameters and that these motifs are governed by constraints of the specified system dynamics. A systematic approach based on enrichment statistical tests has been developed to elucidate the relationships between model parameters and the roles they play in affecting system dynamics of a prototype biological network. The proposed approach is generally applicable and therefore can find wide use in systems biology modeling research.

From Dynamic Global Vegetation Modelling to Real-World regional and local Application

NASA Astrophysics Data System (ADS)

Steinkamp, J.; Forrest, M.; Kamm, K.; Leiblein-Wild, M.; Pachzelt, A.; Werner, C.; Hickler, T.

2015-12-01

Dynamic (global) vegetation models (DGVM) can be applied to any spatial resolution on the local, national, continental and global scale given suitable climatic and geographic input forcing data. LPJ-GUESS, the main DGVM applied in our research group, uses the plant functional type (PFT) concept in the global setup with typically about 10-20 tree PFTs (subdivided into tropical, temperate and boreal) and two herbaceous PFTs by default. When modelling smaller spatial extents, such as continental (e.g. Europe/North America) national domains, or individual sites (e.g. Frankfurt, Germany), i.e. the scale of decision making, it becomes necessary to refine the PFT representation, the model initialization and validation and, in some case, to include additional processes. I will present examples of LPJ-GUESS applications at the continental to local scale performed by our working group including i.) a European simulation representing the main tree species and Mediterranean shrubs, ii.) a climate impact study for Turkey, iii.) coupled dynamic large grazer-vegetation modelling across Africa and, iv.) modelling an allergenic and in Europe invasive shrub (Ambrosia artemisiifolia), iv.) simulating water usage by an oak-pine forest stand near Frankfurt, and v.) stand specific differences in modelling at the FACE sites. Finally, I will present some thoughts on how to advance the models in terms of more detailed and realistic PFT or species parameterizations accounting for adaptive functional trait responses also within species.

Estimating European soil organic carbon mitigation potential in a global integrated land use model

NASA Astrophysics Data System (ADS)

Frank, Stefan; Böttcher, Hannes; Schneider, Uwe; Schmid, Erwin; Havlík, Petr

2013-04-01

Several studies have shown the dynamic interaction between soil organic carbon (SOC) sequestration rates, soil management decisions and SOC levels. Management practices such as reduced and no-tillage, improved residue management and crop rotations as well as the conversion of marginal cropland to native vegetation or conversion of cultivated land to permanent grassland offer the potential to increase SOC content. Even though dynamic interactions are widely acknowledged in literature, they have not been implemented in most existing land use decision models. A major obstacle is the high data and computing requirements for an explicit representation of alternative land use sequences since a model has to be able to track all different management decision paths. To our knowledge no study accounted so far for SOC dynamics explicitly in a global integrated land use model. To overcome these conceptual difficulties described above we apply an approach capable of accounting for SOC dynamics in GLOBIOM (Global Biosphere Management Model), a global recursive dynamic partial equilibrium bottom-up model integrating the agricultural, bioenergy and forestry sectors. GLOBIOM represents all major land based sectors and therefore is able to account for direct and indirect effects of land use change as well as leakage effects (e.g. through trade) implicitly. Together with the detailed representation of technologies (e.g. tillage and fertilizer management systems), these characteristics make the model a highly valuable tool for assessing European SOC emissions and mitigation potential. Demand and international trade are represented in this version of the model at the level of 27 EU member states and 23 aggregated world regions outside Europe. Changes in the demand on the one side, and profitability of the different land based activities on the other side, are the major determinants of land use change in GLOBIOM. In this paper we estimate SOC emissions from cropland for the EU until 2050 explicitly considering SOC dynamics due to land use and land management in a global integrated land use model. Moreover, we calculate the EU SOC mitigation potential taking into account leakage effects outside Europe as well as related feed backs from other sectors. In sensitivity analysis, we disaggregate the SOC mitigation potential i.e. we quantify the impact of different management systems and crop rotations to identify most promising mitigation strategies.

Advances in global sensitivity analyses of demographic-based species distribution models to address uncertainties in dynamic landscapes.

PubMed

Naujokaitis-Lewis, Ilona; Curtis, Janelle M R

2016-01-01

Developing a rigorous understanding of multiple global threats to species persistence requires the use of integrated modeling methods that capture processes which influence species distributions. Species distribution models (SDMs) coupled with population dynamics models can incorporate relationships between changing environments and demographics and are increasingly used to quantify relative extinction risks associated with climate and land-use changes. Despite their appeal, uncertainties associated with complex models can undermine their usefulness for advancing predictive ecology and informing conservation management decisions. We developed a computationally-efficient and freely available tool (GRIP 2.0) that implements and automates a global sensitivity analysis of coupled SDM-population dynamics models for comparing the relative influence of demographic parameters and habitat attributes on predicted extinction risk. Advances over previous global sensitivity analyses include the ability to vary habitat suitability across gradients, as well as habitat amount and configuration of spatially-explicit suitability maps of real and simulated landscapes. Using GRIP 2.0, we carried out a multi-model global sensitivity analysis of a coupled SDM-population dynamics model of whitebark pine (Pinus albicaulis) in Mount Rainier National Park as a case study and quantified the relative influence of input parameters and their interactions on model predictions. Our results differed from the one-at-time analyses used in the original study, and we found that the most influential parameters included the total amount of suitable habitat within the landscape, survival rates, and effects of a prevalent disease, white pine blister rust. Strong interactions between habitat amount and survival rates of older trees suggests the importance of habitat in mediating the negative influences of white pine blister rust. Our results underscore the importance of considering habitat attributes along with demographic parameters in sensitivity routines. GRIP 2.0 is an important decision-support tool that can be used to prioritize research, identify habitat-based thresholds and management intervention points to improve probability of species persistence, and evaluate trade-offs of alternative management options.

Advances in global sensitivity analyses of demographic-based species distribution models to address uncertainties in dynamic landscapes

PubMed Central

Curtis, Janelle M.R.

2016-01-01

Developing a rigorous understanding of multiple global threats to species persistence requires the use of integrated modeling methods that capture processes which influence species distributions. Species distribution models (SDMs) coupled with population dynamics models can incorporate relationships between changing environments and demographics and are increasingly used to quantify relative extinction risks associated with climate and land-use changes. Despite their appeal, uncertainties associated with complex models can undermine their usefulness for advancing predictive ecology and informing conservation management decisions. We developed a computationally-efficient and freely available tool (GRIP 2.0) that implements and automates a global sensitivity analysis of coupled SDM-population dynamics models for comparing the relative influence of demographic parameters and habitat attributes on predicted extinction risk. Advances over previous global sensitivity analyses include the ability to vary habitat suitability across gradients, as well as habitat amount and configuration of spatially-explicit suitability maps of real and simulated landscapes. Using GRIP 2.0, we carried out a multi-model global sensitivity analysis of a coupled SDM-population dynamics model of whitebark pine (Pinus albicaulis) in Mount Rainier National Park as a case study and quantified the relative influence of input parameters and their interactions on model predictions. Our results differed from the one-at-time analyses used in the original study, and we found that the most influential parameters included the total amount of suitable habitat within the landscape, survival rates, and effects of a prevalent disease, white pine blister rust. Strong interactions between habitat amount and survival rates of older trees suggests the importance of habitat in mediating the negative influences of white pine blister rust. Our results underscore the importance of considering habitat attributes along with demographic parameters in sensitivity routines. GRIP 2.0 is an important decision-support tool that can be used to prioritize research, identify habitat-based thresholds and management intervention points to improve probability of species persistence, and evaluate trade-offs of alternative management options. PMID:27547529

Effect of antibodies on pathogen dynamics with delays and two routes of infection

NASA Astrophysics Data System (ADS)

Elaiw, A. M.; Almatrafi, A. A.; Hobiny, A. D.

2018-06-01

We study the global stability of pathogen dynamics models with saturated pathogen-susceptible and infected-susceptible incidence. The models incorporate antibody immune response and three types of discrete or distributed time delays. We first show that the solutions of the model are nonnegative and ultimately bounded. We determine two threshold parameters, the basic reproduction number and antibody response activation number. We establish the existence and stability of the steady states. We study the global stability analysis of models using Lyapunov method. The numerical simulations have shown that antibodies can reduce the pathogen progression.

State-and-transition model archetypes: a global taxonomy of rangeland change

USDA-ARS?s Scientific Manuscript database

State and transition models (STMs) synthesize science-based and local knowledge to formally represent the dynamics of rangeland and other ecosystems. Mental models or concepts of ecosystem dynamics implicitly underlie all management decisions in rangelands and thus how people influence rangeland sus...

Global changes in biogeochemical cycles in response to human activities

NASA Technical Reports Server (NTRS)

Moore, Berrien, III; Melillo, Jerry

1994-01-01

The main objective of our research was to characterize biogeochemical cycles at continental and global scales in both terrestrial and aquatic ecosystems. This characterization applied to both natural ecosystems and those disturbed by human activity. The primary elements of interest were carbon and nitrogen and the analysis sought to quantify standing stocks and dynamic cycling processes. The translocation of major nutrients from the terrestrial landscape to the atmosphere (via trace gases) and to fluvial systems (via leaching, erosional losses, and point source pollution) were of particular importance to this study. Our aim was to develop the first generation of Earth System Models. Our research was organized around the construction and testing of component biogeochemical models which treated terrestrial ecosystem processes, aquatic nutrient transport through drainage basins, and trace gas exchanges at the continental and global scale. A suite of three complementary models were defined within this construct. The models were organized to operate at a 1/2 degree latitude by longitude level of spatial resolution and to execute at a monthly time step. This discretization afforded us the opportunity to understand the dynamics of the biosphere down to subregional scales, while simultaneously placing these dynamics into a global context.

Indices and Dynamics of Global Hydroclimate Over the Past Millennium from Data Assimilation

NASA Astrophysics Data System (ADS)

Steiger, N. J.; Smerdon, J. E.

2017-12-01

Reconstructions based on data assimilation (DA) are at the forefront of model-data syntheses in that such reconstructions optimally fuse proxy data with climate models. DA-based paleoclimate reconstructions have the benefit of being physically-consistent across the reconstructed climate variables and are capable of providing dynamical information about past climate phenomena. Here we use a new implementation of DA, that includes updated proxy system models and climate model bias correction procedures, to reconstruct global hydroclimate on seasonal and annual timescales over the last millennium. This new global hydroclimate product includes reconstructions of the Palmer Drought Severity Index, the Standardized Precipitation Evapotranspiration Index, and global surface temperature along with dynamical variables including the Nino 3.4 index, the latitudinal location of the intertropical convergence zone, and an index of the Atlantic Multidecadal Oscillation. Here we present a validation of the reconstruction product and also elucidate the causes of severe drought in North America and in equatorial Africa. Specifically, we explore the connection between droughts in North America and modes of ocean variability in the Pacific and Atlantic oceans. We also link drought over equatorial Africa to shifts of the intertropical convergence zone and modes of ocean variability.

Exploring the role of fire, succession, climate, and weather on landscape dynamics using comparative modeling

Treesearch

Robert E. Keane; Geoffrey J. Cary; Mike D. Flannigan; Russell A. Parsons; Ian D. Davies; Karen J. King; Chao Li; Ross A. Bradstock; Malcolm Gill

2013-01-01

An assessment of the relative importance of vegetation change and disturbance as agents of landscape change under current and future climates would (1) provide insight into the controls of landscape dynamics, (2) help inform the design and development of coarse scale spatially explicit ecosystem models such as Dynamic Global Vegetation Models (DGVMs), and (3) guide...

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.

Time-varying correlations in global real estate markets: A multivariate GARCH with spatial effects approach

NASA Astrophysics Data System (ADS)

Gu, Huaying; Liu, Zhixue; Weng, Yingliang

2017-04-01

The present study applies the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) with spatial effects approach for the analysis of the time-varying conditional correlations and contagion effects among global real estate markets. A distinguishing feature of the proposed model is that it can simultaneously capture the spatial interactions and the dynamic conditional correlations compared with the traditional MGARCH models. Results reveal that the estimated dynamic conditional correlations have exhibited significant increases during the global financial crisis from 2007 to 2009, thereby suggesting contagion effects among global real estate markets. The analysis further indicates that the returns of the regional real estate markets that are in close geographic and economic proximities exhibit strong co-movement. In addition, evidence of significantly positive leverage effects in global real estate markets is also determined. The findings have significant implications on global portfolio diversification opportunities and risk management practices.

The role of deep Earth dynamics in driving the flooding and emergence of New Guinea since the Jurassic

NASA Astrophysics Data System (ADS)

Harrington, Lauren; Zahirovic, Sabin; Flament, Nicolas; Müller, R. Dietmar

2017-12-01

The paleogeography of New Guinea indicates fluctuating periods of flooding and emergence since the Jurassic, which are inconsistent with estimates of global sea level change since the Eocene. The role of deep Earth dynamics in explaining these discrepancies has not been explored, despite the strongly time-dependent geodynamic setting within which New Guinea has evolved. We aim to investigate the role of subduction-driven mantle flow in controlling long-wavelength dynamic topography and its manifestation in the regional sedimentary record, within a tectonically complex region leading to orogeny. We couple regionally refined global plate reconstructions with forward geodynamic models to compare trends of dynamic topography with estimates of eustasy and regional paleogeography. Qualitative corroboration of modelled mantle structure with equivalent tomographic profiles allows us to ground-truth the models. We show that predicted dynamic topography correlates with the paleogeographic record of New Guinea from the Jurassic to the present. We find that subduction at the East Gondwana margin locally enhanced the high eustatic sea levels from the Early Cretaceous (∼145 Ma) to generate long-term regional flooding. During the Miocene, however, dynamic subsidence associated with subduction of the Maramuni Arc played a fundamental role in causing long-term inundation of New Guinea during a period of global sea level fall.

On the dynamics of the world demographic transition and financial-economic crises forecasts

NASA Astrophysics Data System (ADS)

Akaev, A.; Sadovnichy, V.; Korotayev, A.

2012-05-01

The article considers dynamic processes involving non-linear power-law behavior in such apparently diverse spheres, as demographic dynamics and dynamics of prices of highly liquid commodities such as oil and gold. All the respective variables exhibit features of explosive growth containing precursors indicating approaching phase transitions/catastrophes/crises. The first part of the article analyzes mathematical models of demographic dynamics that describe various scenarios of demographic development in the post-phase-transition period, including a model that takes the limitedness of the Earth carrying capacity into account. This model points to a critical point in the early 2050s, when the world population, after reaching its maximum value may decrease afterward stabilizing then at a certain stationary level. The article presents an analysis of the influence of the demographic transition (directly connected with the hyperexponential growth of the world population) on the global socioeconomic and geopolitical development. The second part deals with the phenomenon of explosive growth of prices of such highly liquid commodities as oil and gold. It is demonstrated that at present the respective processes could be regarded as precursors of waves of the global financial-economic crisis that will demand the change of the current global economic and political system. It is also shown that the moments of the start of the first and second waves of the current global crisis could have been forecasted with a model of accelerating log-periodic fluctuations superimposed over a power-law trend with a finite singularity developed by Didier Sornette and collaborators. With respect to the oil prices, it is shown that it was possible to forecast the 2008 crisis with a precision up to a month already in 2007. The gold price dynamics was used to calculate the possible time of the start of the second wave of the global crisis (July-August 2011); note that this forecast has turned out to be quite correct.

Global attractors and extinction dynamics of cyclically competing species.

PubMed

Rulands, Steffen; Zielinski, Alejandro; Frey, Erwin

2013-05-01

Transitions to absorbing states are of fundamental importance in nonequilibrium physics as well as ecology. In ecology, absorbing states correspond to the extinction of species. We here study the spatial population dynamics of three cyclically interacting species. The interaction scheme comprises both direct competition between species as in the cyclic Lotka-Volterra model, and separated selection and reproduction processes as in the May-Leonard model. We show that the dynamic processes leading to the transient maintenance of biodiversity are closely linked to attractors of the nonlinear dynamics for the overall species' concentrations. The characteristics of these global attractors change qualitatively at certain threshold values of the mobility and depend on the relative strength of the different types of competition between species. They give information about the scaling of extinction times with the system size and thereby the stability of biodiversity. We define an effective free energy as the negative logarithm of the probability to find the system in a specific global state before reaching one of the absorbing states. The global attractors then correspond to minima of this effective energy landscape and determine the most probable values for the species' global concentrations. As in equilibrium thermodynamics, qualitative changes in the effective free energy landscape indicate and characterize the underlying nonequilibrium phase transitions. We provide the complete phase diagrams for the population dynamics and give a comprehensive analysis of the spatio-temporal dynamics and routes to extinction in the respective phases.

Global fast dynamic terminal sliding mode control for a quadrotor UAV.

PubMed

Xiong, Jing-Jing; Zhang, Guo-Bao

2017-01-01

A control method based on global fast dynamic terminal sliding mode control (TSMC) technique is proposed to design the flight controller for performing the finite-time position and attitude tracking control of a small quadrotor UAV. Firstly, the dynamic model of the quadrotor is divided into two subsystems, i.e., a fully actuated subsystem and an underactuated subsystem. Secondly, the dynamic flight controllers of the quadrotor are formulated based on global fast dynamic TSMC, which is able to guarantee that the position and velocity tracking errors of all system state variables converge to zero in finite-time. Moreover, the global fast dynamic TSMC is also able to eliminate the chattering phenomenon caused by the switching control action and realize the high precision performance. In addition, the stabilities of two subsystems are demonstrated by Lyapunov theory, respectively. Lastly, the simulation results are given to illustrate the effectiveness and robustness of the proposed control method in the presence of external disturbances. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Modeling vegetation and carbon dynamics of managed grasslands at the global scale with LPJmL 3.6

NASA Astrophysics Data System (ADS)

Rolinski, Susanne; Müller, Christoph; Heinke, Jens; Weindl, Isabelle; Biewald, Anne; Bodirsky, Benjamin Leon; Bondeau, Alberte; Boons-Prins, Eltje R.; Bouwman, Alexander F.; Leffelaar, Peter A.; te Roller, Johnny A.; Schaphoff, Sibyll; Thonicke, Kirsten

2018-02-01

Grassland management affects the carbon fluxes of one-third of the global land area and is thus an important factor for the global carbon budget. Nonetheless, this aspect has been largely neglected or underrepresented in global carbon cycle models. We investigate four harvesting schemes for the managed grassland implementation of the dynamic global vegetation model (DGVM) Lund-Potsdam-Jena managed Land (LPJmL) that facilitate a better representation of actual management systems globally. We describe the model implementation and analyze simulation results with respect to harvest, net primary productivity and soil carbon content and by evaluating them against reported grass yields in Europe. We demonstrate the importance of accounting for differences in grassland management by assessing potential livestock grazing densities as well as the impacts of grazing, grazing intensities and mowing systems on soil carbon stocks. Grazing leads to soil carbon losses in polar or arid regions even at moderate livestock densities (< 0.4 livestock units per hectare - LSU ha-1) but not in temperate regions even at much higher densities (0.4 to 1.2 LSU ha-1). Applying LPJmL with the new grassland management options enables assessments of the global grassland production and its impact on the terrestrial biogeochemical cycles but requires a global data set on current grassland management.

A toy terrestrial carbon flow model

NASA Technical Reports Server (NTRS)

Parton, William J.; Running, Steven W.; Walker, Brian

1992-01-01

A generalized carbon flow model for the major terrestrial ecosystems of the world is reported. The model is a simplification of the Century model and the Forest-Biogeochemical model. Topics covered include plant production, decomposition and nutrient cycling, biomes, the utility of the carbon flow model for predicting carbon dynamics under global change, and possible applications to state-and-transition models and environmentally driven global vegetation models.

Progress in the Development of a Global Quasi-3-D Multiscale Modeling Framework

NASA Astrophysics Data System (ADS)

Jung, J.; Konor, C. S.; Randall, D. A.

2017-12-01

The Quasi-3-D Multiscale Modeling Framework (Q3D MMF) is a second-generation MMF, which has following advances over the first-generation MMF: 1) The cloud-resolving models (CRMs) that replace conventional parameterizations are not confined to the large-scale dynamical-core grid cells, and are seamlessly connected to each other, 2) The CRMs sense the three-dimensional large- and cloud-scale environment, 3) Two perpendicular sets of CRM channels are used, and 4) The CRMs can resolve the steep surface topography along the channel direction. The basic design of the Q3D MMF has been developed and successfully tested in a limited-area modeling framework. Currently, global versions of the Q3D MMF are being developed for both weather and climate applications. The dynamical cores governing the large-scale circulation in the global Q3D MMF are selected from two cube-based global atmospheric models. The CRM used in the model is the 3-D nonhydrostatic anelastic Vector-Vorticity Model (VVM), which has been tested with the limited-area version for its suitability for this framework. As a first step of the development, the VVM has been reconstructed on the cubed-sphere grid so that it can be applied to global channel domains and also easily fitted to the large-scale dynamical cores. We have successfully tested the new VVM by advecting a bell-shaped passive tracer and simulating the evolutions of waves resulted from idealized barotropic and baroclinic instabilities. For improvement of the model, we also modified the tracer advection scheme to yield positive-definite results and plan to implement a new physics package that includes a double-moment microphysics and an aerosol physics. The interface for coupling the large-scale dynamical core and the VVM is under development. In this presentation, we shall describe the recent progress in the development and show some test results.

Maximum Lyapunov exponents as predictors of global gait stability: a modelling approach.

PubMed

Bruijn, Sjoerd M; Bregman, Daan J J; Meijer, Onno G; Beek, Peter J; van Dieën, Jaap H

2012-05-01

To examine the stability of human walking, methods such as local dynamic stability have been adopted from dynamical systems theory. Local dynamic stability is calculated by estimating maximal finite time Lyapunov exponents (λ(S) and λ(L)), which quantify how a system responds continuously to very small (i.e. "local") perturbations. However, it is unknown if, and to what extent, these measures are correlated to global stability, defined operationally as the probability of falling. We studied whether changes in probability of falling of a simple model of human walking (a so-called dynamic walker) could be predicted from maximum finite time Lyapunov exponents. We used an extended version of the simplest walking model with arced feet and a hip spring. This allowed us to change the probability of falling of the model by changing either the foot radius, the slope at which the model walks, the stiffness of the hip spring, or a combination of these factors. Results showed that λ(S) correlated fairly well with global stability, although this relationship was dependent upon differences in the distance between initial nearest neighbours on the divergence curve. A measure independent of such changes (the log(distance between initially nearest neighbours after 50 samples)) correlated better with global stability, and, more importantly, showed a more consistent relationship across conditions. In contrast, λ(L) showed either weak correlations, or correlations opposite to expected, thus casting doubt on the use of this measure as a predictor of global gait stability. Our findings support the use of λ(S), but not of λ(L), as measure of human gait stability. Copyright © 2011 IPEM. Published by Elsevier Ltd. All rights reserved.

A conceptual model of oceanic heat transport in the Snowball Earth scenario

NASA Astrophysics Data System (ADS)

Comeau, Darin; Kurtze, Douglas A.; Restrepo, Juan M.

2016-12-01

Geologic evidence suggests that the Earth may have been completely covered in ice in the distant past, a state known as Snowball Earth. This is still the subject of controversy, and has been the focus of modeling work from low-dimensional models up to state-of-the-art general circulation models. In our present global climate, the ocean plays a large role in redistributing heat from the equatorial regions to high latitudes, and as an important part of the global heat budget, its role in the initiation a Snowball Earth, and the subsequent climate, is of great interest. To better understand the role of oceanic heat transport in the initiation of Snowball Earth, and the resulting global ice covered climate state, the goal of this inquiry is twofold: we wish to propose the least complex model that can capture the Snowball Earth scenario as well as the present-day climate with partial ice cover, and we want to determine the relative importance of oceanic heat transport. To do this, we develop a simple model, incorporating thermohaline dynamics from traditional box ocean models, a radiative balance from energy balance models, and the more contemporary "sea glacier" model to account for viscous flow effects of extremely thick sea ice. The resulting model, consisting of dynamic ocean and ice components, is able to reproduce both Snowball Earth and present-day conditions through reasonable changes in forcing parameters. We find that including or neglecting oceanic heat transport may lead to vastly different global climate states, and also that the parameterization of under-ice heat transfer in the ice-ocean coupling plays a key role in the resulting global climate state, demonstrating the regulatory effect of dynamic ocean heat transport.

Global identifiability of linear compartmental models--a computer algebra algorithm.

PubMed

Audoly, S; D'Angiò, L; Saccomani, M P; Cobelli, C

1998-01-01

A priori global identifiability deals with the uniqueness of the solution for the unknown parameters of a model and is, thus, a prerequisite for parameter estimation of biological dynamic models. Global identifiability is however difficult to test, since it requires solving a system of algebraic nonlinear equations which increases both in nonlinearity degree and number of terms and unknowns with increasing model order. In this paper, a computer algebra tool, GLOBI (GLOBal Identifiability) is presented, which combines the topological transfer function method with the Buchberger algorithm, to test global identifiability of linear compartmental models. GLOBI allows for the automatic testing of a priori global identifiability of general structure compartmental models from general multi input-multi output experiments. Examples of usage of GLOBI to analyze a priori global identifiability of some complex biological compartmental models are provided.

Ionospheric Outflow in the Magnetosphere: Circulation and Consequences

NASA Astrophysics Data System (ADS)

Welling, D. T.; Liemohn, M. W.

2017-12-01

Including ionospheric outflow in global magnetohydrodynamic models of near-Earth outer space has become an important step towards understanding the role of this plasma source in the magnetosphere. Such simulations have revealed the importance of outflow in populating the plasma sheet and inner magnetosphere as a function of outflow source characteristics. More importantly, these experiments have shown how outflow can control global dynamics, including tail dynamics and dayside reconnection rate. The broad impact of light and heavy ion outflow can create non-linear feedback loops between outflow and the magnetosphere. This paper reviews some of the most important revelations from global magnetospheric modeling that includes ionospheric outflow of light and heavy ions. It also introduces new advances in outflow modeling and coupling outflow to the magnetosphere.

Exploring tropical forest vegetation dynamics using the FATES model

NASA Astrophysics Data System (ADS)

Koven, C. D.; Fisher, R.; Knox, R. G.; Chambers, J.; Kueppers, L. M.; Christoffersen, B. O.; Davies, S. J.; Dietze, M.; Holm, J.; Massoud, E. C.; Muller-Landau, H. C.; Powell, T.; Serbin, S.; Shuman, J. K.; Walker, A. P.; Wright, S. J.; Xu, C.

2017-12-01

Tropical forest vegetation dynamics represent a critical climate feedback in the Earth system, which is poorly represented in current global modeling approaches. We discuss recent progress on exploring these dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a demographic vegetation model for the CESM and ACME ESMs. We will discuss benchmarks of FATES predictions for forest structure against inventory sites, sensitivity of FATES predictions of size and age structure to model parameter uncertainty, and experiments using the FATES model to explore PFT competitive dynamics and the dynamics of size and age distributions in responses to changing climate and CO2.

Dynamic analysis of a hepatitis B model with three-age-classes

NASA Astrophysics Data System (ADS)

Zhang, Suxia; Zhou, Yicang

2014-07-01

Based on the fact that the likelihood of becoming chronically infected is dependent on age at primary infection Kane (1995) [2], Edmunds et al. (1993) [3], Medley et al. (2001) [4], and Ganem and Prince (2004) [6], we formulate a hepatitis B transmission model with three age classes. The reproduction number, R0 is defined and the dynamical behavior of the model is analyzed. It is proved that the disease-free equilibrium is globally stable if R0<1, and there exists at least one endemic equilibrium and that the disease is uniformly persistent if R0>1. The unique endemic equilibrium and its global stability is obtained in a special case. Simulations are also conducted to compare the dynamical behavior of the model with and without age classes.

The Earth’s Population Can Reach 14 Billion in the 23rd Century without Significant Adverse Effects on Survivability

PubMed Central

Krapivin, Vladimir F.; Varotsos, Costas A.; Soldatov, Vladimir Yu.

2017-01-01

This paper presents the results obtained from the study of the sustainable state between nature and human society on a global scale, focusing on the most critical interactions between the natural and anthropogenic processes. Apart from the conventional global models, the basic tool employed herein is the newly proposed complex model entitled “nature-society system (NSS) model”, through which a reliable modeling of the processes taking place in the global climate-nature-society system (CNSS) is achieved. This universal tool is mainly based on the information technology that allows the adaptive conformance of the parametric and functional space of this model. The structure of this model includes the global biogeochemical cycles, the hydrological cycle, the demographic processes and a simple climate model. In this model, the survivability indicator is used as a criterion for the survival of humanity, which defines a trend in the dynamics of the total biomass of the biosphere, taking into account the trends of the biocomplexity dynamics of the land and hydrosphere ecosystems. It should be stressed that there are no other complex global models comparable to those of the CNSS model developed here. The potential of this global model is demonstrated through specific examples in which the classification of the terrestrial ecosystem is accomplished by separating 30 soil-plant formations for geographic pixels 4° × 5°. In addition, humanity is considered to be represented by three groups of economic development status (high, transition, developing) and the World Ocean is parameterized by three latitude zones (low, middle, high). The modelling results obtained show the dynamics of the CNSS at the beginning of the 23rd century, according to which the world population can reach the level of 14 billion without the occurrence of major negative impacts. PMID:28783136

Simulating PACE Global Ocean Radiances

PubMed Central

Gregg, Watson W.; Rousseaux, Cécile S.

2017-01-01

The NASA PACE mission is a hyper-spectral radiometer planned for launch in the next decade. It is intended to provide new information on ocean biogeochemical constituents by parsing the details of high resolution spectral absorption and scattering. It is the first of its kind for global applications and as such, poses challenges for design and operation. To support pre-launch mission development and assess on-orbit capabilities, the NASA Global Modeling and Assimilation Office has developed a dynamic simulation of global water-leaving radiances, using an ocean model containing multiple ocean phytoplankton groups, particulate detritus, particulate inorganic carbon (PIC), and chromophoric dissolved organic carbon (CDOC) along with optical absorption and scattering processes at 1 nm spectral resolution. The purpose here is to assess the skill of the dynamic model and derived global radiances. Global bias, uncertainty, and correlation are derived using available modern satellite radiances at moderate spectral resolution. Total chlorophyll, PIC, and the absorption coefficient of CDOC (aCDOC), are simultaneously assimilated to improve the fidelity of the optical constituent fields. A 5-year simulation showed statistically significant (P <0.05) comparisons of chlorophyll (r = 0.869), PIC (r = 0.868), and aCDOC (r = 0.890) with satellite data. Additionally, diatoms (r = 0.890), cyanobacteria (r = 0.732), and coccolithophores (r = 0.716) were significantly correlated with in situ data. Global assimilated distributions of optical constituents were coupled with a radiative transfer model (Ocean-Atmosphere Spectral Irradiance Model, OASIM) to estimate normalized water-leaving radiances at 1 nm for the spectral range 250–800 nm. These unassimilated radiances were within −0.074 mW cm−2 μm1 sr−1 of MODIS-Aqua radiances at 412, 443, 488, 531, 547, and 667 nm. This difference represented a bias of −10.4% (model low). A mean correlation of 0.706 (P < 0.05) was found with global distributions of MODIS radiances. These results suggest skill in the global assimilated model and resulting radiances. The reported error characterization suggests that the global dynamical simulation can support some aspects of mission design and analysis. For example, the high spectral resolution of the simulation supports investigations of band selection. The global nature of the radiance representations supports investigations of satellite observing scenarios. Global radiances at bands not available in current and past missions support investigations of mission capability. PMID:29292403

Three-pattern decomposition of global atmospheric circulation: part II—dynamical equations of horizontal, meridional and zonal circulations

NASA Astrophysics Data System (ADS)

Hu, Shujuan; Cheng, Jianbo; Xu, Ming; Chou, Jifan

2018-04-01

The three-pattern decomposition of global atmospheric circulation (TPDGAC) partitions three-dimensional (3D) atmospheric circulation into horizontal, meridional and zonal components to study the 3D structures of global atmospheric circulation. This paper incorporates the three-pattern decomposition model (TPDM) into primitive equations of atmospheric dynamics and establishes a new set of dynamical equations of the horizontal, meridional and zonal circulations in which the operator properties are studied and energy conservation laws are preserved, as in the primitive equations. The physical significance of the newly established equations is demonstrated. Our findings reveal that the new equations are essentially the 3D vorticity equations of atmosphere and that the time evolution rules of the horizontal, meridional and zonal circulations can be described from the perspective of 3D vorticity evolution. The new set of dynamical equations includes decomposed expressions that can be used to explore the source terms of large-scale atmospheric circulation variations. A simplified model is presented to demonstrate the potential applications of the new equations for studying the dynamics of the Rossby, Hadley and Walker circulations. The model shows that the horizontal air temperature anomaly gradient (ATAG) induces changes in meridional and zonal circulations and promotes the baroclinic evolution of the horizontal circulation. The simplified model also indicates that the absolute vorticity of the horizontal circulation is not conserved, and its changes can be described by changes in the vertical vorticities of the meridional and zonal circulations. Moreover, the thermodynamic equation shows that the induced meridional and zonal circulations and advection transport by the horizontal circulation in turn cause a redistribution of the air temperature. The simplified model reveals the fundamental rules between the evolution of the air temperature and the horizontal, meridional and zonal components of global atmospheric circulation.

Modelling machine ensembles with discrete event dynamical system theory

NASA Technical Reports Server (NTRS)

Hunter, Dan

1990-01-01

Discrete Event Dynamical System (DEDS) theory can be utilized as a control strategy for future complex machine ensembles that will be required for in-space construction. The control strategy involves orchestrating a set of interactive submachines to perform a set of tasks for a given set of constraints such as minimum time, minimum energy, or maximum machine utilization. Machine ensembles can be hierarchically modeled as a global model that combines the operations of the individual submachines. These submachines are represented in the global model as local models. Local models, from the perspective of DEDS theory , are described by the following: a set of system and transition states, an event alphabet that portrays actions that takes a submachine from one state to another, an initial system state, a partial function that maps the current state and event alphabet to the next state, and the time required for the event to occur. Each submachine in the machine ensemble is presented by a unique local model. The global model combines the local models such that the local models can operate in parallel under the additional logistic and physical constraints due to submachine interactions. The global model is constructed from the states, events, event functions, and timing requirements of the local models. Supervisory control can be implemented in the global model by various methods such as task scheduling (open-loop control) or implementing a feedback DEDS controller (closed-loop control).

Global threshold dynamics of an SIVS model with waning vaccine-induced immunity and nonlinear incidence.

PubMed

Yang, Junyuan; Martcheva, Maia; Wang, Lin

2015-10-01

Vaccination is the most effective method of preventing the spread of infectious diseases. For many diseases, vaccine-induced immunity is not life long and the duration of immunity is not always fixed. In this paper, we propose an SIVS model taking the waning of vaccine-induced immunity and general nonlinear incidence into consideration. Our analysis shows that the model exhibits global threshold dynamics in the sense that if the basic reproduction number is less than 1, then the disease-free equilibrium is globally asymptotically stable implying the disease dies out; while if the basic reproduction number is larger than 1, then the endemic equilibrium is globally asymptotically stable indicating that the disease persists. This global threshold result indicates that if the vaccination coverage rate is below a critical value, then the disease always persists and only if the vaccination coverage rate is above the critical value, the disease can be eradicated. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Simulation of Drought-induced Tree Mortality Using a New Individual and Hydraulic Trait-based Model (S-TEDy)

NASA Astrophysics Data System (ADS)

Sinha, T.; Gangodagamage, C.; Ale, S.; Frazier, A. G.; Giambelluca, T. W.; Kumagai, T.; Nakai, T.; Sato, H.

2017-12-01

Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs.

Principal process analysis of biological models.

PubMed

Casagranda, Stefano; Touzeau, Suzanne; Ropers, Delphine; Gouzé, Jean-Luc

2018-06-14

Understanding the dynamical behaviour of biological systems is challenged by their large number of components and interactions. While efforts have been made in this direction to reduce model complexity, they often prove insufficient to grasp which and when model processes play a crucial role. Answering these questions is fundamental to unravel the functioning of living organisms. We design a method for dealing with model complexity, based on the analysis of dynamical models by means of Principal Process Analysis. We apply the method to a well-known model of circadian rhythms in mammals. The knowledge of the system trajectories allows us to decompose the system dynamics into processes that are active or inactive with respect to a certain threshold value. Process activities are graphically represented by Boolean and Dynamical Process Maps. We detect model processes that are always inactive, or inactive on some time interval. Eliminating these processes reduces the complex dynamics of the original model to the much simpler dynamics of the core processes, in a succession of sub-models that are easier to analyse. We quantify by means of global relative errors the extent to which the simplified models reproduce the main features of the original system dynamics and apply global sensitivity analysis to test the influence of model parameters on the errors. The results obtained prove the robustness of the method. The analysis of the sub-model dynamics allows us to identify the source of circadian oscillations. We find that the negative feedback loop involving proteins PER, CRY, CLOCK-BMAL1 is the main oscillator, in agreement with previous modelling and experimental studies. In conclusion, Principal Process Analysis is a simple-to-use method, which constitutes an additional and useful tool for analysing the complex dynamical behaviour of biological systems.

Diffusion models for innovation: s-curves, networks, power laws, catastrophes, and entropy.

PubMed

Jacobsen, Joseph J; Guastello, Stephen J

2011-04-01

This article considers models for the diffusion of innovation would be most relevant to the dynamics of early 21st century technologies. The article presents an overview of diffusion models and examines the adoption S-curve, network theories, difference models, influence models, geographical models, a cusp catastrophe model, and self-organizing dynamics that emanate from principles of network configuration and principles of heat diffusion. The diffusion dynamics that are relevant to information technologies and energy-efficient technologies are compared. Finally, principles of nonlinear dynamics for innovation diffusion that could be used to rehabilitate the global economic situation are discussed.

Three-pattern decomposition of global atmospheric circulation: part I—decomposition model and theorems

NASA Astrophysics Data System (ADS)

Hu, Shujuan; Chou, Jifan; Cheng, Jianbo

2018-04-01

In order to study the interactions between the atmospheric circulations at the middle-high and low latitudes from the global perspective, the authors proposed the mathematical definition of three-pattern circulations, i.e., horizontal, meridional and zonal circulations with which the actual atmospheric circulation is expanded. This novel decomposition method is proved to accurately describe the actual atmospheric circulation dynamics. The authors used the NCEP/NCAR reanalysis data to calculate the climate characteristics of those three-pattern circulations, and found that the decomposition model agreed with the observed results. Further dynamical analysis indicates that the decomposition model is more accurate to capture the major features of global three dimensional atmospheric motions, compared to the traditional definitions of Rossby wave, Hadley circulation and Walker circulation. The decomposition model for the first time realized the decomposition of global atmospheric circulation using three orthogonal circulations within the horizontal, meridional and zonal planes, offering new opportunities to study the large-scale interactions between the middle-high latitudes and low latitudes circulations.

Oceanic biogeochemical controls on global dynamics of persistent organic pollutants.

PubMed

Dachs, Jordi; Lohmann, Rainer; Ockenden, Wendy A; Méjanelle, Laurence; Eisenreich, Steven J; Jones, Kevin C

2002-10-15

Understanding and quantifying the global dynamics and sinks of persistent organic pollutants (POPs) is important to assess their environmental impact and fate. Air-surface exchange processes, where temperature plays a central role in controlling volatilization and deposition, are of key importance in controlling global POP dynamics. The present study is an assessment of the role of oceanic biogeochemical processes, notably phytoplankton uptake and vertical fluxes of particles, on the global dynamics of POPs. Field measurements of atmospheric polychlorinated biphenyls (PCBs), polychlorinated dibenzodioxins (PCDDs), and furans (PCDFs) are combined with remote sensing estimations of oceanic temperature, wind speed, and chlorophyll, to model the interactions between air-water exchange, phytoplankton uptake, and export of organic matter and POPs out of the mixed surface ocean layer. Deposition is enhanced in the mid-high latitudes and is driven by sinking marine particulate matter, rather than by a cold condensation effect. However, the relative contribution of the biological pump is a function of the physical-chemical properties of POPs. It is concluded that oceanic biogeochemical processes play a critical role in controlling the global dynamics and the ultimate sink of POPs.

Global Environmental Multiscale model - a platform for integrated environmental predictions

NASA Astrophysics Data System (ADS)

Kaminski, Jacek W.; Struzewska, Joanna; Neary, Lori; Dearden, Frank

2017-04-01

The Global Environmental Multiscale model was developed by the Government of Canada as an operational weather prediction model in the mid-1990s. Subsequently, it was used as the host meteorological model for an on-line implementation of air quality chemistry and aerosols from global to the meso-gamma scale. Further model developments led to the vertical extension of the modelling domain to include stratospheric chemistry, aerosols, and formation of polar stratospheric clouds. In parallel, the modelling platform was used for planetary applications where dynamical, radiative transfer and chemical processes in the atmosphere of Mars were successfully simulated. Undoubtedly, the developed modelling platform can be classified as an example capable of the seamless and coupled modelling of the dynamics and chemistry of planetary atmospheres. We will present modelling results for global, regional, and local air quality episodes and the long-term air quality trends. Upper troposphere and lower stratosphere modelling results will be presented in terms of climate change and subsonic aviation emissions modelling. Model results for the atmosphere of Mars will be presented in the context of the 2016 ExoMars mission and the anticipated observations from the NOMAD instrument. Also, we will present plans and the design to extend the GEM model to the F region with further coupling with a magnetospheric model that extends to 15 Re.

On the global dynamics of a chronic myelogenous leukemia model

NASA Astrophysics Data System (ADS)

Krishchenko, Alexander P.; Starkov, Konstantin E.

2016-04-01

In this paper we analyze some features of global dynamics of a three-dimensional chronic myelogenous leukemia (CML) model with the help of the stability analysis and the localization method of compact invariant sets. The behavior of CML model is defined by concentrations of three cellpopulations circulating in the blood: naive T cells, effector T cells specific to CML and CML cancer cells. We prove that the dynamics of the CML system around the tumor-free equilibrium point is unstable. Further, we compute ultimate upper bounds for all three cell populations and provide the existence conditions of the positively invariant polytope. One ultimate lower bound is obtained as well. Moreover, we describe the iterative localization procedure for refining localization bounds; this procedure is based on cyclic using of localizing functions. Applying this procedure we obtain conditions under which the internal tumor equilibrium point is globally asymptotically stable. Our theoretical analyses are supplied by results of the numerical simulation.

Rebased Global Mean Temperature comparisons between Global Climate Models and observed Global Mean Temperature: constraints and implications

NASA Astrophysics Data System (ADS)

Chapman, S. C.; Stainforth, D. A.; Watkins, N. W.

2017-12-01

One of the benchmarks of global climate models (GCMs) is that their slow, decadal or longer timescale variations in past changes in Global Mean Temperature (GMT) track each other [1] and the observed GMT reasonably closely. However, the different GCMs tend to generate GMT time-series which have absolute values that are offset with respect to each other by as much as 3 degrees [2]. Subtracting these offsets, or rebasing, is an integral part of comparisons between observed past GMT and the GMT anomalies generated by ensembles of GCMs. We will formalize how rebasing introduces constraints in how the GCMs are related to each other. The GMT of a given GCM is a macroscopic reduced variable that tracks a subset of the full information contained in the time evolving solution of that GCM. If the GMT slow timescale dynamics of different GCMs is to a good approximation the same subject to a linear translation, then the phenomenology captured by this dynamics is essentially linear. Feedbacks in the different models when expressed through GMT are then to leading order linear. It then follows that a linear energy balance evolution equation for GMT is sufficient to reproduce the slow timescale GMT dynamics, given the appropriate effective heat capacity and feedback parameters. As a consequence, the GMT timeseries future projections generated by the GCMs may underestimate the impact of, and uncertainty in, the outcomes of future forcing scenarios. The offset subtraction procedure identifies a slow time-scale dynamics in model generated GMT. Fluctuations on much faster timescales do not typically track each other from one GCM to another, with the exception of major forcing events such as volcanic eruptions. This suggests that the GMT time-series can be decomposed into a slow and fast timescale which naturally leads to stochastic reduced energy balance models for GMT. [1] IPCC Chapter 9 P743 and fig 9.8, IPCC TS.1 [2] see e.g. [Mauritsen et al., Tuning the Climate of a Global Model, Journal of Advances in Modelling Earth Systems, 2012]4, IPCC SPM.6

Nitrogen feedbacks increase future terrestrial ecosystem carbon uptake in an individual-based dynamic vegetation model

NASA Astrophysics Data System (ADS)

Wårlind, D.; Smith, B.; Hickler, T.; Arneth, A.

2014-11-01

Recently a considerable amount of effort has been put into quantifying how interactions of the carbon and nitrogen cycle affect future terrestrial carbon sinks. Dynamic vegetation models, representing the nitrogen cycle with varying degree of complexity, have shown diverging constraints of nitrogen dynamics on future carbon sequestration. In this study, we use LPJ-GUESS, a dynamic vegetation model employing a detailed individual- and patch-based representation of vegetation dynamics, to evaluate how population dynamics and resource competition between plant functional types, combined with nitrogen dynamics, have influenced the terrestrial carbon storage in the past and to investigate how terrestrial carbon and nitrogen dynamics might change in the future (1850 to 2100; one representative "business-as-usual" climate scenario). Single-factor model experiments of CO2 fertilisation and climate change show generally similar directions of the responses of C-N interactions, compared to the C-only version of the model as documented in previous studies using other global models. Under an RCP 8.5 scenario, nitrogen limitation suppresses potential CO2 fertilisation, reducing the cumulative net ecosystem carbon uptake between 1850 and 2100 by 61%, and soil warming-induced increase in nitrogen mineralisation reduces terrestrial carbon loss by 31%. When environmental changes are considered conjointly, carbon sequestration is limited by nitrogen dynamics up to the present. However, during the 21st century, nitrogen dynamics induce a net increase in carbon sequestration, resulting in an overall larger carbon uptake of 17% over the full period. This contrasts with previous results with other global models that have shown an 8 to 37% decrease in carbon uptake relative to modern baseline conditions. Implications for the plausibility of earlier projections of future terrestrial C dynamics based on C-only models are discussed.

Microbial models with data-driven parameters predict stronger soil carbon responses to climate change.

PubMed

Hararuk, Oleksandra; Smith, Matthew J; Luo, Yiqi

2015-06-01

Long-term carbon (C) cycle feedbacks to climate depend on the future dynamics of soil organic carbon (SOC). Current models show low predictive accuracy at simulating contemporary SOC pools, which can be improved through parameter estimation. However, major uncertainty remains in global soil responses to climate change, particularly uncertainty in how the activity of soil microbial communities will respond. To date, the role of microbes in SOC dynamics has been implicitly described by decay rate constants in most conventional global carbon cycle models. Explicitly including microbial biomass dynamics into C cycle model formulations has shown potential to improve model predictive performance when assessed against global SOC databases. This study aimed to data-constrained parameters of two soil microbial models, evaluate the improvements in performance of those calibrated models in predicting contemporary carbon stocks, and compare the SOC responses to climate change and their uncertainties between microbial and conventional models. Microbial models with calibrated parameters explained 51% of variability in the observed total SOC, whereas a calibrated conventional model explained 41%. The microbial models, when forced with climate and soil carbon input predictions from the 5th Coupled Model Intercomparison Project (CMIP5), produced stronger soil C responses to 95 years of climate change than any of the 11 CMIP5 models. The calibrated microbial models predicted between 8% (2-pool model) and 11% (4-pool model) soil C losses compared with CMIP5 model projections which ranged from a 7% loss to a 22.6% gain. Lastly, we observed unrealistic oscillatory SOC dynamics in the 2-pool microbial model. The 4-pool model also produced oscillations, but they were less prominent and could be avoided, depending on the parameter values. © 2014 John Wiley & Sons Ltd.

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.

Modelling carbon fluxes of forest and grassland ecosystems in Western Europe using the CARAIB dynamic vegetation model: evaluation against eddy covariance data.

NASA Astrophysics Data System (ADS)

Henrot, Alexandra-Jane; François, Louis; Dury, Marie; Hambuckers, Alain; Jacquemin, Ingrid; Minet, Julien; Tychon, Bernard; Heinesch, Bernard; Horemans, Joanna; Deckmyn, Gaby

2015-04-01

Eddy covariance measurements are an essential resource to understand how ecosystem carbon fluxes react in response to climate change, and to help to evaluate and validate the performance of land surface and vegetation models at regional and global scale. In the framework of the MASC project (« Modelling and Assessing Surface Change impacts on Belgian and Western European climate »), vegetation dynamics and carbon fluxes of forest and grassland ecosystems simulated by the CARAIB dynamic vegetation model (Dury et al., iForest - Biogeosciences and Forestry, 4:82-99, 2011) are evaluated and validated by comparison of the model predictions with eddy covariance data. Here carbon fluxes (e.g. net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (RECO)) and evapotranspiration (ET) simulated with the CARAIB model are compared with the fluxes measured at several eddy covariance flux tower sites in Belgium and Western Europe, chosen from the FLUXNET global network (http://fluxnet.ornl.gov/). CARAIB is forced either with surface atmospheric variables derived from the global CRU climatology, or with in situ meteorological data. Several tree (e.g. Pinus sylvestris, Fagus sylvatica, Picea abies) and grass species (e.g. Poaceae, Asteraceae) are simulated, depending on the species encountered on the studied sites. The aim of our work is to assess the model ability to reproduce the daily, seasonal and interannual variablility of carbon fluxes and the carbon dynamics of forest and grassland ecosystems in Belgium and Western Europe.

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.

Forest forming process and dynamic vegetation models under global change

Treesearch

A. Shvidenko; E. Gustafson

2009-01-01

The paper analyzes mathematical models that are used to project the dynamics of forest ecosystems on different spatial and temporal scales. Landscape disturbance and succession models (LDSMs) are of a particular interest for studying the forest forming process in Northern Eurasia. They have a solid empirical background and are able to model ecological processes under...

The Interaction of Global Biochemical Cycles

NASA Technical Reports Server (NTRS)

Moore, B., III; Dastoor, M. N.

1984-01-01

The global biosphere in an exceedingly complex system. To gain an understanding of its structure and dynamic features, it is necessary not only to increase the knowledge about the detailed processes but also to develop models of how global interactions take place. Attempts to analyze the detailed physical, chemical and biological processes in this context need to be guided by an advancement of understanding of the latter. It is necessary to develop a strategy of data gathering that severs both these purposes simultaneously. The following papers deal with critical aspects in the global cycles of carbon, nitrogen, phosphorus and sulfur in details as well as the cycle of water and the flow of energy in the Earth's environment. The objective is to set partly the foundation for the development of mathematical models that allow exploration of the coupled dynamics of the global cycles of carbon, nitrogen, phosphorus, sulfur, as well as energy and water flux.

Multiscale Cloud System Modeling

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Moncrieff, Mitchell W.

2009-01-01

The central theme of this paper is to describe how cloud system resolving models (CRMs) of grid spacing approximately 1 km have been applied to various important problems in atmospheric science across a wide range of spatial and temporal scales and how these applications relate to other modeling approaches. A long-standing problem concerns the representation of organized precipitating convective cloud systems in weather and climate models. Since CRMs resolve the mesoscale to large scales of motion (i.e., 10 km to global) they explicitly address the cloud system problem. By explicitly representing organized convection, CRMs bypass restrictive assumptions associated with convective parameterization such as the scale gap between cumulus and large-scale motion. Dynamical models provide insight into the physical mechanisms involved with scale interaction and convective organization. Multiscale CRMs simulate convective cloud systems in computational domains up to global and have been applied in place of contemporary convective parameterizations in global models. Multiscale CRMs pose a new challenge for model validation, which is met in an integrated approach involving CRMs, operational prediction systems, observational measurements, and dynamical models in a new international project: the Year of Tropical Convection, which has an emphasis on organized tropical convection and its global effects.

A Multiscale Simulation Framework to Investigate Hydrobiogeochemical Processes in the Groundwater-Surface Water Interaction Zone

NASA Astrophysics Data System (ADS)

Scheibe, T. D.; Yang, X.; Song, X.; Chen, X.; Hammond, G. E.; Song, H. S.; Hou, Z.; Murray, C. J.; Tartakovsky, A. M.; Tartakovsky, G.; Yang, X.; Zachara, J. M.

2016-12-01

Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs.

Detection of a dynamic topography signal in last interglacial sea-level records

PubMed Central

Austermann, Jacqueline; Mitrovica, Jerry X.; Huybers, Peter; Rovere, Alessio

2017-01-01

Estimating minimum ice volume during the last interglacial based on local sea-level indicators requires that these indicators are corrected for processes that alter local sea level relative to the global average. Although glacial isostatic adjustment is generally accounted for, global scale dynamic changes in topography driven by convective mantle flow are generally not considered. We use numerical models of mantle flow to quantify vertical deflections caused by dynamic topography and compare predictions at passive margins to a globally distributed set of last interglacial sea-level markers. The deflections predicted as a result of dynamic topography are significantly correlated with marker elevations (>95% probability) and are consistent with construction and preservation attributes across marker types. We conclude that a dynamic topography signal is present in the elevation of last interglacial sea-level records and that the signal must be accounted for in any effort to determine peak global mean sea level during the last interglacial to within an accuracy of several meters. PMID:28695210

Characterizing Middle Atmospheric Dynamical Variability and its Impact on the Thermosphere/Ionosphere System During Recent Stratospheric Sudden Warmings

NASA Astrophysics Data System (ADS)

McCormack, J. P.; Sassi, F.; Hoppel, K.; Ma, J.; Eckermann, S. D.

2015-12-01

We investigate the evolution of neutral atmospheric dynamics in the 10-100 km altitude range before, during, and after recent stratospheric sudden warmings (SSWs) using a prototype high-altitude version of the Navy Global Environmental Model (NAVGEM), which combines a 4-dimensional variational (4DVAR) data assimilation system with a 3-time-level semi-Lagrangian semi-implicit global forecast model. In addition to assimilating conventional meteorological observations, NAVGEM also assimilates middle atmospheric temperature and constituent observations from both operational and research satellite platforms to provide global synoptic meteorological analyses of winds, temperatures, ozone, and water vapor from the surface to ~90 km. In this study, NAVGEM analyses are used to diagnose the spatial and temporal evolution of the main dynamical drivers in the mesosphere and lower thermosphere (MLT) before, during, and after specific SSW events during the 2009-2013 period when large disturbances were observed in the thermosphere/ionosphere (TI) region. Preliminary findings show strong modulation of the semidiurnal tide in the MLT during the onset of an SSW. To assess the impact of the neutral atmosphere dynamical variability on the TI system, NAVGEM analyses are used to constrain simulations of select SSW events using the specified dynamics (SD) configuration of the extended Whole Atmosphere Community Climate Model (WACCM-X).

Utilization of UARS Data in Validation of Photochemical and Dynamical Mechanisms in Stratospheric Models

NASA Technical Reports Server (NTRS)

Ko, M. K. W.; Rodriquez, J. M.; Hu, W.; Danilin, M. Y.; Shia, R.-L.

1998-01-01

The proposed work utilized Upper Atmosphere Research Satellite (UARS) measurements of short-lived and long-lived species, in conjunction with existing photochemical "box" models, trajectory models, and two-dimensional global models, to elucidate outstanding questions in our understanding of photochemical and dynamical mechanisms in the stratosphere. Particular emphasis was given to arriving at the best possible understanding of the chemical and dynamical contributions to the stratospheric ozone budget. Such understanding will increase confidence in the simulations carried out by assessment models.

Utilization of UARS Data in Validation of Photochemical and Dynamical Mechanisms in Stratospheric Models

NASA Technical Reports Server (NTRS)

Ko, Malcolm K. W.; Rodriquez, Jose M.; Hu, Wenjie; Danilin, Michael Y.; Shia, Run-Li

1998-01-01

The proposed work utilized Upper Atmosphere Research Satellite (UARS) measurements of short-lived and long-lived species, in conjunction with existing photochemical "box" models, trajectory models, and two-dimensional global models, to elucidate outstanding questions in our understanding of photochemical and dynamical mechanisms in the stratosphere. Particular emphasis was given to arriving at the best possible understanding of the chemical and dynamical contribution to the stratospheric ozone budget. Such understanding will increase confidence in the simulations carried out by assessment models.

Predictability analysis and validation of a low-dimensional model - an application to the dynamics of cereal crops observed from satellite

NASA Astrophysics Data System (ADS)

Mangiarotti, Sylvain; Drapeau, Laurent

2013-04-01

The global modeling approach aims to obtain parsimonious models of observed dynamics from few or single time series (Letellier et al. 2009). Specific algorithms were developed and validated for this purpose (Mangiarotti et al. 2012a). This approach was applied to the dynamics of cereal crops in semi-arid region using the vegetation index derived from satellite data as a proxy of the dynamics. A low-dimensional autonomous model could be obtained. The corresponding attractor is characteristic of weakly dissipative chaos and exhibits a toroidal-like structure. At present, only few theoretical cases of such chaos are known, and none was obtained from real world observations. Under smooth conditions, a robust validation of three-dimensional chaotic models can be usually performed based on the topological approach (Gilmore 1998). Such approach becomes more difficult for weakly dissipative systems, and almost impossible under noisy observational conditions. For this reason, another validation approach is developed which consists in comparing the forecasting skill of the model to other forecasts for which no dynamical model is required. A data assimilation process is associated to the model to estimate the model's skill; several schemes are tested (simple re-initialization, Extended and Ensemble Kalman Filters and Back and Forth Nudging). Forecasts without model are performed based on the search of analogous states in the phase space (Mangiarotti et al. 2012b). The comparison reveals the quality of the model's forecasts at short to moderate horizons and contributes to validate the model. These results suggest that the dynamics of cereal crops can be reasonably approximated by low-dimensional chaotic models, and also bring out powerful arguments for chaos. Chaotic models have often been used as benchmark to test data assimilation schemes; the present work shows that such tests may not only have a theoretical interest, but also almost direct applicative potential. Moreover, other global models could be obtained for other regions. The model considered here is not a particular case which highlights the usefulness to investigate and to widen this field of modeling and research. References: Letellier, C., Aguirre, L.A., Freitas, U.S., 2009. Frequently asked questions about global modeling. Chaos, 19, doi:10.1063/1.3125705. Gilmore R., 1998. Topological analysis of chaotic dynamical systems. Review of Modern Physics, 70, 1455-1530. Mangiarotti, S., Coudret, R., Drapreau, L., Jarlan, L., 2012a. Polynomial Search and Global Modeling - two algorithms for modelling chaos. Physical Review E, 86(4), 046205. Mangiarotti, S., Mazzega, P., Mougin, E., Hiernaux, P., 2012b. Predictability of vegetation cycles over the semi-arid region of Gourma (Mali) from forecasts of AVHRR-NDVI signals. Remote Sensing of Environment, 123, 246-257.

Bias correction in Global Mean Temperature comparisons between Global Climate Models and implications for the deterministic and stochastic dynamics

NASA Astrophysics Data System (ADS)

Chapman, Sandra; Stainforth, David; Watkins, Nicholas

2017-04-01

Global mean temperature (GMT) provides a simple means of benchmarking a broad ensemble of global climate models (GCMs) against past observed GMT which in turn provide headline assessments of the consequences of possible future forcing scenarios. The slow variations of past changes in GMT seen in different GCMs track each other [1] and the observed GMT reasonably closely. However, the different GCMs tend to generate GMT time-series which have absolute values that are offset with respect to each other [2]. Subtracting these offsets is an integral part of comparisons between ensembles of GCMs and observed past GMT. We will discuss how this constrains how the GCMs are related to each other. The GMT of a given GCM is a macroscopic reduced variable that tracks a subset of the full information contained in the time evolving solution of that GCM. If the GMT slow timescale dynamics of different GCMs is to a good approximation the same, subject to a linear translation, then the phenomenology captured by this dynamics is essentially linear; any feedback is to leading order linear in GMT. It then follows that a linear energy balance evolution equation for GMT is sufficient to reproduce the slow timescale GMT dynamics, provided that the appropriate effective heat capacity and feedback parameters are known. As a consequence, the GCM's GMT timeseries may underestimate the impact of, and uncertainty in, the outcomes of future forcing scenarios. The offset subtraction procedure identifies a slow time-scale dynamics in model generated GMT. Fluctuations on much faster timescales do not typically track each other from one GCM to another, with the exception of major forcing events such as volcanic eruptions. This suggests that the GMT time-series can be decomposed into a slow and fast timescale which naturally leads to stochastic reduced energy balance models for GMT. [1] IPCC Chapter 9 P743 and fig 9.8,IPCC TS.1 [2] see e.g. [Mauritsen et al., Tuning the Climate of a Global Model, Journal of Advances in Modelling Earth Systems, 2012] 4, IPCC SPM.6

ALM-FATES: Using dynamic vegetation and demography to capture changes in forest carbon cycling and competition at the global scale

NASA Astrophysics Data System (ADS)

Holm, J. A.; Knox, R. G.; Koven, C.; Riley, W. J.; Bisht, G.; Fisher, R.; Christoffersen, B. O.; Dietze, M.; Chambers, J. Q.

2017-12-01

The inclusion of dynamic vegetation demography in Earth System Models (ESMs) has been identified as a critical step in moving ESMs towards more realistic representations of plant ecology and the processes that govern climatically important fluxes of carbon, energy, and water. Successful application of dynamic vegetation models, and process-based approaches to simulate plant demography, succession, and response to disturbances without climate envelopes at the global scale is a challenging endeavor. We integrated demographic processes using the Functionally-Assembled Terrestrial Ecosystem Simulator (FATES) in the newly developed ACME Land Model (ALM). We then use an ALM-FATES globally gridded simulation for the first time to investigate plant functional type (PFT) distributions and dynamic turnover rates. Initial global simulations successfully include six interacting and competing PFTs (ranging from tropical to boreal, evergreen, deciduous, needleleaf and broadleaf); including more PFTs is planned. Global maps of net primary productivity, leaf area index, and total vegetation biomass by ALM-FATES matched patterns and values when compared to CLM4.5-BGC and MODIS estimates. We also present techniques for PFT parameterization based on the Predictive Ecosystem Analyzer (PEcAn), field based turnover rates, improved PFT groupings based on trait-tradeoffs, and improved representation of multiple canopy positions. Finally, we applied the improved ALM-FATES model at a central Amazon tropical and western U.S. temperate sites and demonstrate improvements in predicted PFT size- and age-structure and regional distribution. Results from the Amazon tropical site investigate the ability and magnitude of a tropical forest to act as a carbon sink by 2100 with a doubling of CO2, while results from the temperate sites investigate the response of forest mortality with increasing droughts.

Hydroclimatic Controls over Global Variations in Phenology and Carbon Flux

NASA Technical Reports Server (NTRS)

Koster, Randal; Walker, G.; Thornton, Patti; Collatz, G. J.

2012-01-01

The connection between phenological and hydroclimatological variations are quantified through joint analyses of global NDVI, LAI, and precipitation datasets. The global distributions of both NDVI and LAI in the warm season are strongly controlled by three quantities: mean annual precipitation, the standard deviation of annual precipitation, and Budyko's index of dryness. Upon demonstrating that these same basic (if biased) relationships are produced by a dynamic vegetation model (the dynamic vegetation and carbon storage components of the NCAR Community Land Model version 4 combined with the water and energy balance framework of the Catchment Land Surface Model of the NASA Global Modeling and Assimilation Office), we use the model to perform a sensitivity study focusing on how phenology and carbon flux might respond to climatic change. The offline (decoupled from the atmosphere) simulations show us, for example, where on the globe a given small increment in precipitation mean or variability would have the greatest impact on carbon uptake. The analysis framework allows us in addition to quantify the degree to which climatic biases in a free-running GCM are manifested as biases in simulated phenology.

Hydroclimatic Controls over Global Variations in Phenology and Carbon Flux

NASA Astrophysics Data System (ADS)

Koster, R. D.; Walker, G.; Thornton, P. E.; Collatz, G. J.

2012-12-01

The connection between phenological and hydroclimatological variations are quantified through joint analyses of global NDVI, LAI, and precipitation datasets. The global distributions of both NDVI and LAI in the warm season are strongly controlled by three quantities: mean annual precipitation, the standard deviation of annual precipitation, and Budyko's index of dryness. Upon demonstrating that these same basic (if somewhat biased) relationships are produced by a dynamic vegetation model (the dynamic vegetation and carbon storage components of the NCAR Community Land Model version 4 combined with the water and energy balance framework of the Catchment Land Surface Model of the NASA Global Modeling and Assimilation Office), we use the model to perform a sensitivity study focusing on how phenology and carbon flux might respond to climatic change. The offline (decoupled from the atmosphere) simulations show us, for example, where on the globe a given small increment in precipitation mean or variability would have the greatest impact on carbon uptake. The analysis framework allows us in addition to quantify the degree to which climatic biases in a free-running GCM are manifested as biases in simulated phenology.

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

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

Vertical resolution of baroclinic modes in global ocean models

NASA Astrophysics Data System (ADS)

Stewart, K. D.; Hogg, A. McC.; Griffies, S. M.; Heerdegen, A. P.; Ward, M. L.; Spence, P.; England, M. H.

2017-05-01

Improvements in the horizontal resolution of global ocean models, motivated by the horizontal resolution requirements for specific flow features, has advanced modelling capabilities into the dynamical regime dominated by mesoscale variability. In contrast, the choice of the vertical grid remains a subjective choice, and it is not clear that efforts to improve vertical resolution adequately support their horizontal counterparts. Indeed, considering that the bulk of the vertical ocean dynamics (including convection) are parameterized, it is not immediately obvious what the vertical grid is supposed to resolve. Here, we propose that the primary purpose of the vertical grid in a hydrostatic ocean model is to resolve the vertical structure of horizontal flows, rather than to resolve vertical motion. With this principle we construct vertical grids based on their abilities to represent baroclinic modal structures commensurate with the theoretical capabilities of a given horizontal grid. This approach is designed to ensure that the vertical grids of global ocean models complement (and, importantly, to not undermine) the resolution capabilities of the horizontal grid. We find that for z-coordinate global ocean models, at least 50 well-positioned vertical levels are required to resolve the first baroclinic mode, with an additional 25 levels per subsequent mode. High-resolution ocean-sea ice simulations are used to illustrate some of the dynamical enhancements gained by improving the vertical resolution of a 1/10° global ocean model. These enhancements include substantial increases in the sea surface height variance (∼30% increase south of 40°S), the barotropic and baroclinic eddy kinetic energies (up to 200% increase on and surrounding the Antarctic continental shelf and slopes), and the overturning streamfunction in potential density space (near-tripling of the Antarctic Bottom Water cell at 65°S).

Integration of Extended MHD and Kinetic Effects in Global Magnetosphere Models

NASA Astrophysics Data System (ADS)

Germaschewski, K.; Wang, L.; Maynard, K. R. M.; Raeder, J.; Bhattacharjee, A.

2015-12-01

Computational models of Earth's geospace environment are an important tool to investigate the science of the coupled solar-wind -- magnetosphere -- ionosphere system, complementing satellite and ground observations with a global perspective. They are also crucial in understanding and predicting space weather, in particular under extreme conditions. Traditionally, global models have employed the one-fluid MHD approximation, which captures large-scale dynamics quite well. However, in Earth's nearly collisionless plasma environment it breaks down on small scales, where ion and electron dynamics and kinetic effects become important, and greatly change the reconnection dynamics. A number of approaches have recently been taken to advance global modeling, e.g., including multiple ion species, adding Hall physics in a Generalized Ohm's Law, embedding local PIC simulations into a larger fluid domain and also some work on simulating the entire system with hybrid or fully kinetic models, the latter however being to computationally expensive to be run at realistic parameters. We will present an alternate approach, ie., a multi-fluid moment model that is derived rigorously from the Vlasov-Maxwell system. The advantage is that the computational cost remains managable, as we are still solving fluid equations. While the evolution equation for each moment is exact, it depends on the next higher-order moment, so that truncating the hiearchy and closing the system to capture the essential kinetic physics is crucial. We implement 5-moment (density, momentum, scalar pressure) and 10-moment (includes pressure tensor) versions of the model, and use local approximations for the heat flux to close the system. We test these closures by local simulations where we can compare directly to PIC / hybrid codes, and employ them in global simulations using the next-generation OpenGGCM to contrast them to MHD / Hall-MHD results and compare with observations.

Global dynamics of zooplankton and harmful algae in flowing habitats

NASA Astrophysics Data System (ADS)

Hsu, Sze-Bi; Wang, Feng-Bin; Zhao, Xiao-Qiang

This paper is devoted to the study of two advection-dispersion-reaction models arising from the dynamics of harmful algae and zooplankton in flowing-water habitats where a main channel is coupled to a hydraulic storage zone, representing an ensemble of fringing coves on the shoreline. For the system modeling the dynamics of algae and their toxin that contains little limiting nutrient, we establish a threshold type result on the global attractivity in terms of the basic reproduction ratio for algae. For the model with zooplankton that eat the algae and are inhibited by the toxin produced by algae, we show that there exists a coexistence steady state and the zooplankton is uniformly persistent provided that two basic reproduction ratios for algae and zooplankton are greater than unity.

Research activities of the Geodynamics Branch

NASA Technical Reports Server (NTRS)

Kahn, W. D. (Editor); Cohen, S. C. (Editor)

1984-01-01

A broad spectrum of geoscience disciplines including space geodesy, geopotential field modeling, tectonophysics, and dynamic oceanography are discussed. The NASA programs, include the Geodynamics and Ocean Programs, the Crustal Dynamics Project, the proposed Ocean Topography Experiment (TOPEX), and the Geopotential Research Mission (GRM). The papers are grouped into chapters on Crustal Movements, Global Earth Dynamics, Gravity Field Model Development, Sea Surface Topography, and Advanced Studies.

Examining Extreme Events Using Dynamically Downscaled 12-km WRF Simulations

EPA Science Inventory

Continued improvements in the speed and availability of computational resources have allowed dynamical downscaling of global climate model (GCM) projections to be conducted at increasingly finer grid scales and over extended time periods. The implementation of dynamical downscal...

Coldspots and hotspots - Global tectonics and mantle dynamics of Venus

NASA Technical Reports Server (NTRS)

Bindschadler, Duane L.; Schubert, Gerald; Kaula, William M.

1992-01-01

Based on geologic observations provided by Magellan's first cycle of data collection and recent models of mantle convection in spherical shells and crustal deformation, the major topographic and geologic features of Venus are incorporated into a model of global mantle dynamics. Consideration is given to volcanic rises, such as Beta Regio and Atla Regio, plateau-shaped highlands dominated by complex ridged terrain (e.g., Ovda Regio and Alpha Regio), and circular lowland regions, such as Atalanta Planitia. Each of these features is related to either mantle plumes (hotspots) or mantle downwellings (coldspots).

Mechanisms controlling primary and new production in a global ecosystem model - Part I: Validation of the biological simulation

NASA Astrophysics Data System (ADS)

Popova, E. E.; Coward, A. C.; Nurser, G. A.; de Cuevas, B.; Fasham, M. J. R.; Anderson, T. R.

2006-12-01

A global general circulation model coupled to a simple six-compartment ecosystem model is used to study the extent to which global variability in primary and export production can be realistically predicted on the basis of advanced parameterizations of upper mixed layer physics, without recourse to introducing extra complexity in model biology. The "K profile parameterization" (KPP) scheme employed, combined with 6-hourly external forcing, is able to capture short-term periodic and episodic events such as diurnal cycling and storm-induced deepening. The model realistically reproduces various features of global ecosystem dynamics that have been problematic in previous global modelling studies, using a single generic parameter set. The realistic simulation of deep convection in the North Atlantic, and lack of it in the North Pacific and Southern Oceans, leads to good predictions of chlorophyll and primary production in these contrasting areas. Realistic levels of primary production are predicted in the oligotrophic gyres due to high frequency external forcing of the upper mixed layer (accompanying paper Popova et al., 2006) and novel parameterizations of zooplankton excretion. Good agreement is shown between model and observations at various JGOFS time series sites: BATS, KERFIX, Papa and HOT. One exception is the northern North Atlantic where lower grazing rates are needed, perhaps related to the dominance of mesozooplankton there. The model is therefore not globally robust in the sense that additional parameterizations are needed to realistically simulate ecosystem dynamics in the North Atlantic. Nevertheless, the work emphasises the need to pay particular attention to the parameterization of mixed layer physics in global ocean ecosystem modelling as a prerequisite to increasing the complexity of ecosystem models.

The Magnetospheric Constellation Mission. Dynamic Response and Coupling Observatory (DRACO): Understanding the Global Dynamics of the Structured Magnetotail

NASA Technical Reports Server (NTRS)

2001-01-01

Magnetospheric Constellation Dynamic Response and Coupling Observatory (DRACO) is the Solar Terrestrial Probe (STP) designed to understand the nonlinear dynamics, responses, and connections within the Earth's structured magnetotail, using a constellation of approximately 50 to 100 distributed vector measurement spacecraft. DRACO will reveal magnetotail processes operating within a domain extending 20 Earth radii (R(sub E)) across the tail and 40 R(sub E)down the tail, on spatial and time scales accessible to global circulation models, i.e., approximately 2 R(sub E) and 10 seconds.

A dynamic model of functioning of a bank

NASA Astrophysics Data System (ADS)

Malafeyev, Oleg; Awasthi, Achal; Zaitseva, Irina; Rezenkov, Denis; Bogdanova, Svetlana

2018-04-01

In this paper, we analyze dynamic programming as a novel approach to solve the problem of maximizing the profits of a bank. The mathematical model of the problem and the description of bank's work is described in this paper. The problem is then approached using the method of dynamic programming. Dynamic programming makes sure that the solutions obtained are globally optimal and numerically stable. The optimization process is set up as a discrete multi-stage decision process and solved with the help of dynamic programming.

Quantifying spatially and temporally explicit CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics

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

Liu, Shaoqing; Zhuang, Qianlai; Chen, Min

Current terrestrial ecosystem models are usually driven with global average annual atmospheric carbon dioxide (CO 2) concentration data at the global scale. However, high-precision CO 2 measurement from eddy flux towers showed that seasonal, spatial surface atmospheric CO 2 concentration differences were as large as 35 ppmv and the site-level tests indicated that the CO 2 variation exhibited different effects on plant photosynthesis. Here we used a process-based ecosystem model driven with two spatially and temporally explicit CO 2 data sets to analyze the atmospheric CO 2 fertilization effects on the global carbon dynamics of terrestrial ecosystems from 2003 tomore » 2010. Our results demonstrated that CO 2 seasonal variation had a negative effect on plant carbon assimilation, while CO2 spatial variation exhibited a positive impact. When both CO 2 seasonal and spatial effects were considered, global gross primary production and net ecosystem production were 1.7 Pg C•yr –1 and 0.08 Pg C•yr –1 higher than the simulation using uniformly distributed CO 2 data set and the difference was significant in tropical and temperate evergreen broadleaf forest regions. Moreover, this study suggests that the CO 2 observation network should be expanded so that the realistic CO 2 variation can be incorporated into the land surface models to adequately account for CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics.« less

Quantifying spatially and temporally explicit CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics

DOE PAGES

Liu, Shaoqing; Zhuang, Qianlai; Chen, Min; ...

2016-07-25

Current terrestrial ecosystem models are usually driven with global average annual atmospheric carbon dioxide (CO 2) concentration data at the global scale. However, high-precision CO 2 measurement from eddy flux towers showed that seasonal, spatial surface atmospheric CO 2 concentration differences were as large as 35 ppmv and the site-level tests indicated that the CO 2 variation exhibited different effects on plant photosynthesis. Here we used a process-based ecosystem model driven with two spatially and temporally explicit CO 2 data sets to analyze the atmospheric CO 2 fertilization effects on the global carbon dynamics of terrestrial ecosystems from 2003 tomore » 2010. Our results demonstrated that CO 2 seasonal variation had a negative effect on plant carbon assimilation, while CO2 spatial variation exhibited a positive impact. When both CO 2 seasonal and spatial effects were considered, global gross primary production and net ecosystem production were 1.7 Pg C•yr –1 and 0.08 Pg C•yr –1 higher than the simulation using uniformly distributed CO 2 data set and the difference was significant in tropical and temperate evergreen broadleaf forest regions. Moreover, this study suggests that the CO 2 observation network should be expanded so that the realistic CO 2 variation can be incorporated into the land surface models to adequately account for CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics.« less

GFDL's unified regional-global weather-climate modeling system with variable resolution capability for severe weather predictions and regional climate simulations

NASA Astrophysics Data System (ADS)

Lin, S. J.

2015-12-01

The NOAA/Geophysical Fluid Dynamics Laboratory has been developing a unified regional-global modeling system with variable resolution capabilities that can be used for severe weather predictions (e.g., tornado outbreak events and cat-5 hurricanes) and ultra-high-resolution (1-km) regional climate simulations within a consistent global modeling framework. The fundation of this flexible regional-global modeling system is the non-hydrostatic extension of the vertically Lagrangian dynamical core (Lin 2004, Monthly Weather Review) known in the community as FV3 (finite-volume on the cubed-sphere). Because of its flexability and computational efficiency, the FV3 is one of the final candidates of NOAA's Next Generation Global Prediction System (NGGPS). We have built into the modeling system a stretched (single) grid capability, a two-way (regional-global) multiple nested grid capability, and the combination of the stretched and two-way nests, so as to make convection-resolving regional climate simulation within a consistent global modeling system feasible using today's High Performance Computing System. One of our main scientific goals is to enable simulations of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously regarded as impossible. In this presentation I will demonstrate that it is computationally feasible to simulate not only super-cell thunderstorms, but also the subsequent genesis of tornadoes using a global model that was originally designed for century long climate simulations. As a unified weather-climate modeling system, we evaluated the performance of the model with horizontal resolution ranging from 1 km to as low as 200 km. In particular, for downscaling studies, we have developed various tests to ensure that the large-scale circulation within the global varaible resolution system is well simulated while at the same time the small-scale can be accurately captured within the targeted high resolution region.

Global Langevin model of multidimensional biomolecular dynamics.

PubMed

Schaudinnus, Norbert; Lickert, Benjamin; Biswas, Mithun; Stock, Gerhard

2016-11-14

Molecular dynamics simulations of biomolecular processes are often discussed in terms of diffusive motion on a low-dimensional free energy landscape F(). To provide a theoretical basis for this interpretation, one may invoke the system-bath ansatz á la Zwanzig. That is, by assuming a time scale separation between the slow motion along the system coordinate x and the fast fluctuations of the bath, a memory-free Langevin equation can be derived that describes the system's motion on the free energy landscape F(), which is damped by a friction field and driven by a stochastic force that is related to the friction via the fluctuation-dissipation theorem. While the theoretical formulation of Zwanzig typically assumes a highly idealized form of the bath Hamiltonian and the system-bath coupling, one would like to extend the approach to realistic data-based biomolecular systems. Here a practical method is proposed to construct an analytically defined global model of structural dynamics. Given a molecular dynamics simulation and adequate collective coordinates, the approach employs an "empirical valence bond"-type model which is suitable to represent multidimensional free energy landscapes as well as an approximate description of the friction field. Adopting alanine dipeptide and a three-dimensional model of heptaalanine as simple examples, the resulting Langevin model is shown to reproduce the results of the underlying all-atom simulations. Because the Langevin equation can also be shown to satisfy the underlying assumptions of the theory (such as a delta-correlated Gaussian-distributed noise), the global model provides a correct, albeit empirical, realization of Zwanzig's formulation. As an application, the model can be used to investigate the dependence of the system on parameter changes and to predict the effect of site-selective mutations on the dynamics.

Global Langevin model of multidimensional biomolecular dynamics

NASA Astrophysics Data System (ADS)

Schaudinnus, Norbert; Lickert, Benjamin; Biswas, Mithun; Stock, Gerhard

2016-11-01

Molecular dynamics simulations of biomolecular processes are often discussed in terms of diffusive motion on a low-dimensional free energy landscape F ( 𝒙 ) . To provide a theoretical basis for this interpretation, one may invoke the system-bath ansatz á la Zwanzig. That is, by assuming a time scale separation between the slow motion along the system coordinate x and the fast fluctuations of the bath, a memory-free Langevin equation can be derived that describes the system's motion on the free energy landscape F ( 𝒙 ) , which is damped by a friction field and driven by a stochastic force that is related to the friction via the fluctuation-dissipation theorem. While the theoretical formulation of Zwanzig typically assumes a highly idealized form of the bath Hamiltonian and the system-bath coupling, one would like to extend the approach to realistic data-based biomolecular systems. Here a practical method is proposed to construct an analytically defined global model of structural dynamics. Given a molecular dynamics simulation and adequate collective coordinates, the approach employs an "empirical valence bond"-type model which is suitable to represent multidimensional free energy landscapes as well as an approximate description of the friction field. Adopting alanine dipeptide and a three-dimensional model of heptaalanine as simple examples, the resulting Langevin model is shown to reproduce the results of the underlying all-atom simulations. Because the Langevin equation can also be shown to satisfy the underlying assumptions of the theory (such as a delta-correlated Gaussian-distributed noise), the global model provides a correct, albeit empirical, realization of Zwanzig's formulation. As an application, the model can be used to investigate the dependence of the system on parameter changes and to predict the effect of site-selective mutations on the dynamics.

Boundedness and global stability of the two-predator and one-prey models with nonlinear prey-taxis

NASA Astrophysics Data System (ADS)

Wang, Jianping; Wang, Mingxin

2018-06-01

This paper concerns the reaction-diffusion systems modeling the population dynamics of two predators and one prey with nonlinear prey-taxis. We first investigate the global existence and boundedness of the unique classical solution for the general model. Then, we study the global stabilities of nonnegative spatially homogeneous equilibria for an explicit system with type I functional responses and density-dependent death rates for the predators and logistic growth for the prey. Moreover, the convergence rates are also established.

Dynamic Price Vector Formation Model-Based Automatic Demand Response Strategy for PV-Assisted EV Charging Stations

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

Chen, Qifang; Wang, Fei; Hodge, Bri-Mathias

A real-time price (RTP)-based automatic demand response (ADR) strategy for PV-assisted electric vehicle (EV) Charging Station (PVCS) without vehicle to grid is proposed. The charging process is modeled as a dynamic linear program instead of the normal day-ahead and real-time regulation strategy, to capture the advantages of both global and real-time optimization. Different from conventional price forecasting algorithms, a dynamic price vector formation model is proposed based on a clustering algorithm to form an RTP vector for a particular day. A dynamic feasible energy demand region (DFEDR) model considering grid voltage profiles is designed to calculate the lower and uppermore » bounds. A deduction method is proposed to deal with the unknown information of future intervals, such as the actual stochastic arrival and departure times of EVs, which make the DFEDR model suitable for global optimization. Finally, both the comparative cases articulate the advantages of the developed methods and the validity in reducing electricity costs, mitigating peak charging demand, and improving PV self-consumption of the proposed strategy are verified through simulation scenarios.« less

LOW MACH NUMBER MODELING OF CONVECTION IN HELIUM SHELLS ON SUB-CHANDRASEKHAR WHITE DWARFS. II. BULK PROPERTIES OF SIMPLE MODELS

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

Jacobs, A. M.; Zingale, M.; Nonaka, A.

2016-08-10

The dynamics of helium shell convection driven by nuclear burning establish the conditions for runaway in the sub-Chandrasekhar-mass, double-detonation model for SNe Ia, as well as for a variety of other explosive phenomena. We explore these convection dynamics for a range of white dwarf core and helium shell masses in three dimensions using the low Mach number hydrodynamics code MAESTRO. We present calculations of the bulk properties of this evolution, including time-series evolution of global diagnostics, lateral averages of the 3D state, and the global 3D state. We find a variety of outcomes, including quasi-equilibrium, localized runaway, and convective runaway.more » Our results suggest that the double-detonation progenitor model is promising and that 3D dynamic convection plays a key role.« less

Low Mach Number Modeling of Convection in Helium Shells on Sub-Chandrasekhar White Dwarfs. II. Bulk Properties of Simple Models

DOE PAGES

Jacobs, A. M.; Zingale, M.; Nonaka, A.; ...

2016-08-10

The dynamics of helium shell convection driven by nuclear burning establish the conditions for runaway in the sub-Chandrasekhar-mass, double-detonation model for SNe Ia, as well as for a variety of other explosive phenomena. In this paper, we explore these convection dynamics for a range of white dwarf core and helium shell masses in three dimensions using the low Mach number hydrodynamics code MAESTRO. We present calculations of the bulk properties of this evolution, including time-series evolution of global diagnostics, lateral averages of the 3D state, and the global 3D state. We find a variety of outcomes, including quasi-equilibrium, localized runaway,more » and convective runaway. Finally, our results suggest that the double-detonation progenitor model is promising and that 3D dynamic convection plays a key role.« less

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

Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.

Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this article, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on amore » literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Lastly, monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change.« less

Fractional dynamics of globally slow transcription and its impact on deterministic genetic oscillation.

PubMed

Wei, Kun; Gao, Shilong; Zhong, Suchuan; Ma, Hong

2012-01-01

In dynamical systems theory, a system which can be described by differential equations is called a continuous dynamical system. In studies on genetic oscillation, most deterministic models at early stage are usually built on ordinary differential equations (ODE). Therefore, gene transcription which is a vital part in genetic oscillation is presupposed to be a continuous dynamical system by default. However, recent studies argued that discontinuous transcription might be more common than continuous transcription. In this paper, by appending the inserted silent interval lying between two neighboring transcriptional events to the end of the preceding event, we established that the running time for an intact transcriptional event increases and gene transcription thus shows slow dynamics. By globally replacing the original time increment for each state increment by a larger one, we introduced fractional differential equations (FDE) to describe such globally slow transcription. The impact of fractionization on genetic oscillation was then studied in two early stage models--the Goodwin oscillator and the Rössler oscillator. By constructing a "dual memory" oscillator--the fractional delay Goodwin oscillator, we suggested that four general requirements for generating genetic oscillation should be revised to be negative feedback, sufficient nonlinearity, sufficient memory and proper balancing of timescale. The numerical study of the fractional Rössler oscillator implied that the globally slow transcription tends to lower the chance of a coupled or more complex nonlinear genetic oscillatory system behaving chaotically.

The changing global carbon cycle: linking local plant-soil carbon dynamics to global consequences

Treesearch

F. Stuart Chapin; Jack McFarland; A. David McGuire; Eugenie S. Euskirchen; Roger W. Ruess; Knut Kielland

2009-01-01

Most current climate-carbon cycle models that include the terrestrial carbon (C) cycle are based on a model developed 40 years ago by Woodwell & Whittaker (1968) and omit advances in biogeochemical understanding since that time. Their model treats net C emissions from ecosystems as the balance between net primary production (NPP) and heterotrophic respiration (HR,...

How well do terrestrial biosphere models simulate coarse-scale runoff in the contiguous United States?

Treesearch

C.R. Schwalm; D.N. Huntzinger; R.B. Cook; Y. Wei; I.T. Baker; R.P. Neilson; B. Poulter; Peter Caldwell; G. Sun; H.Q. Tian; N. Zeng

2015-01-01

Significant changes in the water cycle are expected under current global environmental change. Robust assessment of present-day water cycle dynamics at continental to global scales is confounded by shortcomings in the observed record. Modeled assessments also yield conflicting results which are linked to differences in model structure and simulation protocol. Here we...

Failure dynamics of the global risk network.

PubMed

Szymanski, Boleslaw K; Lin, Xin; Asztalos, Andrea; Sreenivasan, Sameet

2015-06-18

Risks threatening modern societies form an intricately interconnected network that often underlies crisis situations. Yet, little is known about how risk materializations in distinct domains influence each other. Here we present an approach in which expert assessments of likelihoods and influence of risks underlie a quantitative model of the global risk network dynamics. The modeled risks range from environmental to economic and technological, and include difficult to quantify risks, such as geo-political and social. Using the maximum likelihood estimation, we find the optimal model parameters and demonstrate that the model including network effects significantly outperforms the others, uncovering full value of the expert collected data. We analyze the model dynamics and study its resilience and stability. Our findings include such risk properties as contagion potential, persistence, roles in cascades of failures and the identity of risks most detrimental to system stability. The model provides quantitative means for measuring the adverse effects of risk interdependencies and the materialization of risks in the network.

Trust Model for Protection of Personal Health Data in a Global Environment.

PubMed

Ruotsalainen, Pekka; Blobel, Bernd

2017-01-01

Successful health care, eHealth, digital health, and personal health systems increasingly take place in cross-jurisdictional, dynamic and risk-encumbered information space. They require rich amount of personal health information (PHI). Trust is and will be the cornerstone and prerequisite for successful health services. In global environments, trust cannot be expected as granted. In this paper, health service in the global environment is perceived as a meta-system, and a trust management model is developed to support it. The predefined trusting belief currently used in health care is not transferable to global environments. In the authors' model, the level of trust is dynamically calculated from measurable attributes. These attributes describe trust features of the service provider and its environment. The calculated trust value or profile can be used in defining the risk service user has to accept when disclosing PHI, and in definition of additional privacy and security safeguards before disclosing PHI and/or using services.

Potential role of vegetation dynamics on recent extreme droughts over tropical South America

NASA Astrophysics Data System (ADS)

Wang, G.; Erfanian, A.; Fomenko, L.

2017-12-01

Tropical South America is a drought hot spot. In slightly over a decade (2005-2016), the region encountered three extreme droughts (2005, 2010, and 2016). Recurrent extreme droughts not only impact the region's eco-hydrology and socio-economy, but are also globally important as they can transform the planet's largest rainforest, the Amazon, from a carbon sink to a carbon source. Understanding drought drivers and mechanisms underlying extreme droughts in tropical South America can help better project the fate of the Amazon rainforest in a changing climate. In this study we use a regional climate model (RegCM4.3.4) coupled with a comprehensive land-surface model (CLM4.5) to study the present-day hydroclimate of the region, focusing specifically on what might have caused the frequent recurrence of extreme droughts. In the context of observation natural variability of the global oceanic forcing, we tackle the role of land-atmosphere interactions and ran the model with and without dynamic vegetation to study how vegetation dynamics and carbon-nitrogen cycles may have influenced the drought characteristics. Our results demonstrate skillful simulation of the South American climate in the model, and indicate substantial sensitivity of the region's hydroclimatology to vegetation dynamics. This presentation will compare the role of global oceanic forcing versus regional land surface feedback in the recent recurrent droughts, and will characterize the effects of vegetation dynamics in enhancing the drought severity. Preliminary results on future projections of the regional ecosystem and droughts perspective will be also presented.

Earthquake nucleation in a stochastic fault model of globally coupled units with interaction delays

NASA Astrophysics Data System (ADS)

Vasović, Nebojša; Kostić, Srđan; Franović, Igor; Todorović, Kristina

2016-09-01

In present paper we analyze dynamics of fault motion by considering delayed interaction of 100 all-to-all coupled blocks with rate-dependent friction law in presence of random seismic noise. Such a model sufficiently well describes a real fault motion, whose prevailing stochastic nature is implied by surrogate data analysis of available GPS measurements of active fault movement. Interaction of blocks in an analyzed model is studied as a function of time delay, observed both for dynamics of individual faults and phenomenological models. Analyzed model is examined as a system of all-to-all coupled blocks according to typical assumption of compound faults as complex of globally coupled segments. We apply numerical methods to show that there are local bifurcations from equilibrium state to periodic oscillations, with an occurrence of irregular aperiodic behavior when initial conditions are set away from the equilibrium point. Such a behavior indicates a possible existence of a bi-stable dynamical regime, due to effect of the introduced seismic noise or the existence of global attractor. The latter assumption is additionally confirmed by analyzing the corresponding mean-field approximated model. In this bi-stable regime, distribution of event magnitudes follows Gutenberg-Richter power law with satisfying statistical accuracy, including the b-value within the real observed range.

Global Sensitivity Applied to Dynamic Combined Finite Discrete Element Methods for Fracture Simulation

NASA Astrophysics Data System (ADS)

Godinez, H. C.; Rougier, E.; Osthus, D.; Srinivasan, G.

2017-12-01

Fracture propagation play a key role for a number of application of interest to the scientific community. From dynamic fracture processes like spall and fragmentation in metals and detection of gas flow in static fractures in rock and the subsurface, the dynamics of fracture propagation is important to various engineering and scientific disciplines. In this work we implement a global sensitivity analysis test to the Hybrid Optimization Software Suite (HOSS), a multi-physics software tool based on the combined finite-discrete element method, that is used to describe material deformation and failure (i.e., fracture and fragmentation) under a number of user-prescribed boundary conditions. We explore the sensitivity of HOSS for various model parameters that influence how fracture are propagated through a material of interest. The parameters control the softening curve that the model relies to determine fractures within each element in the mesh, as well a other internal parameters which influence fracture behavior. The sensitivity method we apply is the Fourier Amplitude Sensitivity Test (FAST), which is a global sensitivity method to explore how each parameter influence the model fracture and to determine the key model parameters that have the most impact on the model. We present several sensitivity experiments for different combination of model parameters and compare against experimental data for verification.

Modelling carbon responses of tundra ecosystems to historical and projected climate: A comparison of a plot- and a global-scale ecosystem model to identify process-based uncertainties

USGS Publications Warehouse

Clein, Joy S.; Kwiatkowski, B.L.; McGuire, A.D.; Hobbie, J.E.; Rastetter, E.B.; Melillo, J.M.; Kicklighter, D.W.

2000-01-01

We are developing a process-based modelling approach to investigate how carbon (C) storage of tundra across the entire Arctic will respond to projected climate change. To implement the approach, the processes that are least understood, and thus have the most uncertainty, need to be identified and studied. In this paper, we identified a key uncertainty by comparing the responses of C storage in tussock tundra at one site between the simulations of two models - one a global-scale ecosystem model (Terrestrial Ecosystem Model, TEM) and one a plot-scale ecosystem model (General Ecosystem Model, GEM). The simulations spanned the historical period (1921-94) and the projected period (1995-2100). In the historical period, the model simulations of net primary production (NPP) differed in their sensitivity to variability in climate. However, the long-term changes in C storage were similar in both simulations, because the dynamics of heterotrophic respiration (RH) were similar in both models. In contrast, the responses of C storage in the two model simulations diverged during the projected period. In the GEM simulation for this period, increases in RH tracked increases in NPP, whereas in the TEM simulation increases in RH lagged increases in NPP. We were able to make the long-term C dynamics of the two simulations agree by parameterizing TEM to the fast soil C pools of GEM. We concluded that the differences between the long-term C dynamics of the two simulations lay in modelling the role of the recalcitrant soil C. These differences, which reflect an incomplete understanding of soil processes, lead to quite different projections of the response of pan-Arctic C storage to global change. For example, the reference parameterization of TEM resulted in an estimate of cumulative C storage of 2032 g C m-2 for moist tundra north of 50??N, which was substantially higher than the 463 g C m-2 estimated for a parameterization of fast soil C dynamics. This uncertainty in the depiction of the role of recalcitrant soil C in long-term ecosystem C dynamics resulted from our incomplete understanding of controls over C and N transformations in Arctic soils. Mechanistic studies of these issues are needed to improve our ability to model the response of Arctic ecosystems to global change.

Rich Global Dynamics in a Prey-Predator Model with Allee Effect and Density Dependent Death Rate of Predator

NASA Astrophysics Data System (ADS)

Sen, Moitri; Banerjee, Malay

In this work we have considered a prey-predator model with strong Allee effect in the prey growth function, Holling type-II functional response and density dependent death rate for predators. It presents a comprehensive study of the complete global dynamics for the considered system. Especially to see the effect of the density dependent death rate of predator on the system behavior, we have presented the two parametric bifurcation diagrams taking it as one of the bifurcation parameters. In course of that we have explored all possible local and global bifurcations that the system could undergo, namely the existence of transcritical bifurcation, saddle node bifurcation, cusp bifurcation, Hopf-bifurcation, Bogdanov-Takens bifurcation and Bautin bifurcation respectively.

Simulating the Agulhas system in global ocean models - nesting vs. multi-resolution unstructured meshes

NASA Astrophysics Data System (ADS)

Biastoch, Arne; Sein, Dmitry; Durgadoo, Jonathan V.; Wang, Qiang; Danilov, Sergey

2018-01-01

Many questions in ocean and climate modelling require the combined use of high resolution, global coverage and multi-decadal integration length. For this combination, even modern resources limit the use of traditional structured-mesh grids. Here we compare two approaches: A high-resolution grid nested into a global model at coarser resolution (NEMO with AGRIF) and an unstructured-mesh grid (FESOM) which allows to variably enhance resolution where desired. The Agulhas system around South Africa is used as a testcase, providing an energetic interplay of a strong western boundary current and mesoscale dynamics. Its open setting into the horizontal and global overturning circulations also requires global coverage. Both model configurations simulate a reasonable large-scale circulation. Distribution and temporal variability of the wind-driven circulation are quite comparable due to the same atmospheric forcing. However, the overturning circulation differs, owing each model's ability to represent formation and spreading of deep water masses. In terms of regional, high-resolution dynamics, all elements of the Agulhas system are well represented. Owing to the strong nonlinearity in the system, Agulhas Current transports of both configurations and in comparison with observations differ in strength and temporal variability. Similar decadal trends in Agulhas Current transport and Agulhas leakage are linked to the trends in wind forcing.

Further development of a global pollution model for CO, CH4, and CH2 O

NASA Technical Reports Server (NTRS)

Peters, L. K.

1975-01-01

Global tropospheric pollution models are developed that describe the transport and the physical and chemical processes occurring between the principal sources and sinks of CH4 and CO. Results are given of long term static chemical kinetic computer simulations and preliminary short term dynamic simulations.

Mapping Global Ocean Surface Albedo from Satellite Observations: Models, Algorithms, and Datasets

NASA Astrophysics Data System (ADS)

Li, X.; Fan, X.; Yan, H.; Li, A.; Wang, M.; Qu, Y.

2018-04-01

Ocean surface albedo (OSA) is one of the important parameters in surface radiation budget (SRB). It is usually considered as a controlling factor of the heat exchange among the atmosphere and ocean. The temporal and spatial dynamics of OSA determine the energy absorption of upper level ocean water, and have influences on the oceanic currents, atmospheric circulations, and transportation of material and energy of hydrosphere. Therefore, various parameterizations and models have been developed for describing the dynamics of OSA. However, it has been demonstrated that the currently available OSA datasets cannot full fill the requirement of global climate change studies. In this study, we present a literature review on mapping global OSA from satellite observations. The models (parameterizations, the coupled ocean-atmosphere radiative transfer (COART), and the three component ocean water albedo (TCOWA)), algorithms (the estimation method based on reanalysis data, and the direct-estimation algorithm), and datasets (the cloud, albedo and radiation (CLARA) surface albedo product, dataset derived by the TCOWA model, and the global land surface satellite (GLASS) phase-2 surface broadband albedo product) of OSA have been discussed, separately.

Evaluation of atmospheric aerosol and tropospheric ozone effects on global terrestrial ecosystem carbon dynamics

NASA Astrophysics Data System (ADS)

Chen, Min

The increasing human activities have produced large amounts of air pollutants ejected into the atmosphere, in which atmospheric aerosols and tropospheric ozone are considered to be especially important because of their negative impacts on human health and their impacts on global climate through either their direct radiative effect or indirect effect on land-atmosphere CO2 exchange. This dissertation dedicates to quantifying and evaluating the aerosol and tropospheric ozone effects on global terrestrial ecosystem dynamics using a modeling approach. An ecosystem model, the integrated Terrestrial Ecosystem Model (iTem), is developed to simulate biophysical and biogeochemical processes in terrestrial ecosystems. A two-broad-band atmospheric radiative transfer model together with the Moderate-Resolution Imaging Spectroradiometer (MODIS) measured atmospheric parameters are used to well estimate global downward solar radiation and the direct and diffuse components in comparison with observations. The atmospheric radiative transfer modeling framework were used to quantify the aerosol direct radiative effect, showing that aerosol loadings cause 18.7 and 12.8 W m -2 decrease of direct-beam Photosynthetic Active Radiation (PAR) and Near Infrared Radiation (NIR) respectively, and 5.2 and 4.4 W m -2 increase of diffuse PAR and NIR, respectively, leading to a total 21.9 W m-2 decrease of total downward solar radiation over the global land surface during the period of 2003-2010. The results also suggested that the aerosol effect may be overwhelmed by clouds because of the stronger extinction and scattering ability of clouds. Applications of the iTem with solar radiation data and with or without considering the aerosol loadings shows that aerosol loading enhances the terrestrial productions [Gross Primary Production (GPP), Net Primary Production (NPP) and Net Ecosystem Production (NEP)] and carbon emissions through plant respiration (RA) in global terrestrial ecosystems over the period of 2003-2010. Ecosystem heterotrophic respiration (RH) was negatively affected by the aerosol loading. These results support previous conclusions of the advantage of aerosol light scattering effect on plant productions in other studies but suggest there is strong spatial variation. This study finds indirect aerosol effects on terrestrial ecosystem carbon dynamics through affecting plant phenology, thermal and hydrological environments. All these evidences suggested that the aerosol direct radiative effect on global terrestrial ecosystem carbon dynamics should be considered to better understand the global carbon cycle and climate change. An ozone sub-model is developed in this dissertation and fully coupled with iTem. The coupled model, named iTemO3 considers the processes of ozone stomatal deposition, plant defense to ozone influx, ozone damage and plant repairing mechanism. By using a global atmospheric chemical transport model (GACTM) estimated ground-level ozone concentration data, the model estimated global annual stomatal ozone deposition is 234.0 Tg O3 yr-1 and indicates which regions have high ozone damage risk. Different plant functional types, sunlit and shaded leaves are shown to have different responses to ozone. The model predictions suggest that ozone has caused considerable change on global terrestrial ecosystem carbon storage and carbon exchanges over the study period 2004-2008. The study suggests that uncertainty of the key parameters in iTemO3 could result in large errors in model predictions. Thus more experimental data for better model parameterization is highly needed.

Structure and conformational dynamics of scaffolded DNA origami nanoparticles

DTIC Science & Technology

2017-05-08

all-atom molecular dynamics and coarse-grained finite element modeling to DX-based nanoparticles to elucidate their fine-scale and global conforma... finite element (FE) modeling approach CanDo is also routinely used to predict the 3D equilibrium conformation of programmed DNA assemblies based on a...model with both experimental cryo-electron microscopy (cryo-EM) data and all-atom modeling. MATERIALS AND METHODS Lattice-free finite element model

Final Report from The University of Texas at Austin for DEGAS: Dynamic Global Address Space programming environments

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

Erez, Mattan; Yelick, Katherine; Sarkar, Vivek

The Dynamic, Exascale Global Address Space programming environment (DEGAS) project will develop the next generation of programming models and runtime systems to meet the challenges of Exascale computing. Our approach is to provide an efficient and scalable programming model that can be adapted to application needs through the use of dynamic runtime features and domain-specific languages for computational kernels. We address the following technical challenges: Programmability: Rich set of programming constructs based on a Hierarchical Partitioned Global Address Space (HPGAS) model, demonstrated in UPC++. Scalability: Hierarchical locality control, lightweight communication (extended GASNet), and ef- ficient synchronization mechanisms (Phasers). Performance Portability:more » Just-in-time specialization (SEJITS) for generating hardware-specific code and scheduling libraries for domain-specific adaptive runtimes (Habanero). Energy Efficiency: Communication-optimal code generation to optimize energy efficiency by re- ducing data movement. Resilience: Containment Domains for flexible, domain-specific resilience, using state capture mechanisms and lightweight, asynchronous recovery mechanisms. Interoperability: Runtime and language interoperability with MPI and OpenMP to encourage broad adoption.« less

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.

Nondynamic Tracking Using The Global Positioning System

NASA Technical Reports Server (NTRS)

Yunck, T. P.; Wu, Sien-Chong

1988-01-01

Report describes technique for using Global Positioning System (GPS) to determine position of low Earth orbiter without need for dynamic models. Differential observing strategy requires GPS receiver on user vehicle and network of six ground receivers. Computationally efficient technique delivers decimeter accuracy on orbits down to lowest altitudes. New technique nondynamic long-arc strategy having potential for accuracy of best dynamic techniques while retaining much of computational simplicity of geometric techniques.

Efficient Global Aerodynamic Modeling from Flight Data

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2012-01-01

A method for identifying global aerodynamic models from flight data in an efficient manner is explained and demonstrated. A novel experiment design technique was used to obtain dynamic flight data over a range of flight conditions with a single flight maneuver. Multivariate polynomials and polynomial splines were used with orthogonalization techniques and statistical modeling metrics to synthesize global nonlinear aerodynamic models directly and completely from flight data alone. Simulation data and flight data from a subscale twin-engine jet transport aircraft were used to demonstrate the techniques. Results showed that global multivariate nonlinear aerodynamic dependencies could be accurately identified using flight data from a single maneuver. Flight-derived global aerodynamic model structures, model parameter estimates, and associated uncertainties were provided for all six nondimensional force and moment coefficients for the test aircraft. These models were combined with a propulsion model identified from engine ground test data to produce a high-fidelity nonlinear flight simulation very efficiently. Prediction testing using a multi-axis maneuver showed that the identified global model accurately predicted aircraft responses.

Dynamic Modeling of the Human Coagulation Cascade Using Reduced Order Effective Kinetic Models (Open Access)

DTIC Science & Technology

2015-03-16

shaded region around each total sensitivity value was the maximum uncertainty in that value estimated by the Sobol method. 2.4. Global Sensitivity...Performance We conducted a global sensitivity analysis, using the variance-based method of Sobol , to estimate which parameters controlled the...Hunter, J.D. Matplotlib: A 2D Graphics Environment. Comput. Sci. Eng. 2007, 9, 90–95. 69. Sobol , I. Global sensitivity indices for nonlinear

Development and application of a technique for reducing airframe finite element models for dynamics analysis

NASA Technical Reports Server (NTRS)

Hashemi-Kia, Mostafa; Toossi, Mostafa

1990-01-01

A computational procedure for the reduction of large finite element models was developed. This procedure is used to obtain a significantly reduced model while retaining the essential global dynamic characteristics of the full-size model. This reduction procedure is applied to the airframe finite element model of AH-64A Attack Helicopter. The resulting reduced model is then validated by application to a vibration reduction study.

Spatially explicit modeling of particulate nutrient flux in Large global rivers

NASA Astrophysics Data System (ADS)

Cohen, S.; Kettner, A.; Mayorga, E.; Harrison, J. A.

2017-12-01

Water, sediment, nutrient and carbon fluxes along river networks have undergone considerable alterations in response to anthropogenic and climatic changes, with significant consequences to infrastructure, agriculture, water security, ecology and geomorphology worldwide. However, in a global setting, these changes in fluvial fluxes and their spatial and temporal characteristics are poorly constrained, due to the limited availability of continuous and long-term observations. We present results from a new global-scale particulate modeling framework (WBMsedNEWS) that combines the Global NEWS watershed nutrient export model with the spatially distributed WBMsed water and sediment model. We compare the model predictions against multiple observational datasets. The results indicate that the model is able to accurately predict particulate nutrient (Nitrogen, Phosphorus and Organic Carbon) fluxes on an annual time scale. Analysis of intra-basin nutrient dynamics and fluxes to global oceans is presented.

Three-Dimensional Water and Carbon Cycle Modeling at High Spatial-Temporal Resolutions

NASA Astrophysics Data System (ADS)

Liao, C.; Zhuang, Q.

2017-12-01

Terrestrial ecosystems in cryosphere are very sensitive to the global climate change due to the presence of snow covers, mountain glaciers and permafrost, especially when the increase in near surface air temperature is almost twice as large as the global average. However, few studies have investigated the water and carbon cycle dynamics using process-based hydrological and biogeochemistry modeling approach. In this study, we used three-dimensional modeling approach at high spatial-temporal resolutions to investigate the water and carbon cycle dynamics for the Tanana Flats Basin in interior Alaska with emphases on dissolved organic carbon (DOC) dynamics. The results have shown that: (1) lateral flow plays an important role in water and carbon cycle, especially in dissolved organic carbon (DOC) dynamics. (2) approximately 2.0 × 104 kg C yr-1 DOC is exported to the hydrological networks and it compromises 1% and 0.01% of total annual gross primary production (GPP) and total organic carbon stored in soil, respectively. This study has established an operational and flexible framework to investigate and predict the water and carbon cycle dynamics under the changing climate.

Groundwater development stress: Global-scale indices compared to regional modeling

USGS Publications Warehouse

Alley, William; Clark, Brian R.; Ely, Matt; Faunt, Claudia

2018-01-01

The increased availability of global datasets and technologies such as global hydrologic models and the Gravity Recovery and Climate Experiment (GRACE) satellites have resulted in a growing number of global-scale assessments of water availability using simple indices of water stress. Developed initially for surface water, such indices are increasingly used to evaluate global groundwater resources. We compare indices of groundwater development stress for three major agricultural areas of the United States to information available from regional water budgets developed from detailed groundwater modeling. These comparisons illustrate the potential value of regional-scale analyses to supplement global hydrological models and GRACE analyses of groundwater depletion. Regional-scale analyses allow assessments of water stress that better account for scale effects, the dynamics of groundwater flow systems, the complexities of irrigated agricultural systems, and the laws, regulations, engineering, and socioeconomic factors that govern groundwater use. Strategic use of regional-scale models with global-scale analyses would greatly enhance knowledge of the global groundwater depletion problem.

Importance of vegetation dynamics for future terrestrial carbon cycling

NASA Astrophysics Data System (ADS)

Ahlström, Anders; Xia, Jianyang; Arneth, Almut; Luo, Yiqi; Smith, Benjamin

2015-05-01

Terrestrial ecosystems currently sequester about one third of anthropogenic CO2 emissions each year, an important ecosystem service that dampens climate change. The future fate of this net uptake of CO2 by land based ecosystems is highly uncertain. Most ecosystem models used to predict the future terrestrial carbon cycle share a common architecture, whereby carbon that enters the system as net primary production (NPP) is distributed to plant compartments, transferred to litter and soil through vegetation turnover and then re-emitted to the atmosphere in conjunction with soil decomposition. However, while all models represent the processes of NPP and soil decomposition, they vary greatly in their representations of vegetation turnover and the associated processes governing mortality, disturbance and biome shifts. Here we used a detailed second generation dynamic global vegetation model with advanced representation of vegetation growth and mortality, and the associated turnover. We apply an emulator that describes the carbon flows and pools exactly as in simulations with the full model. The emulator simulates ecosystem dynamics in response to 13 different climate or Earth system model simulations from the Coupled Model Intercomparison Project Phase 5 ensemble under RCP8.5 radiative forcing. By exchanging carbon cycle processes between these 13 simulations we quantified the relative roles of three main driving processes of the carbon cycle; (I) NPP, (II) vegetation dynamics and turnover and (III) soil decomposition, in terms of their contribution to future carbon (C) uptake uncertainties among the ensemble of climate change scenarios. We found that NPP, vegetation turnover (including structural shifts, wild fires and mortality) and soil decomposition rates explained 49%, 17% and 33%, respectively, of uncertainties in modelled global C-uptake. Uncertainty due to vegetation turnover was further partitioned into stand-clearing disturbances (16%), wild fires (0%), stand dynamics (7%), reproduction (10%) and biome shifts (67%) globally. We conclude that while NPP and soil decomposition rates jointly account for 83% of future climate induced C-uptake uncertainties, vegetation turnover and structure, dominated by biome shifts, represent a significant fraction globally and regionally (tropical forests: 40%), strongly motivating their representation and analysis in future C-cycle studies.

A globally calibrated scheme for generating daily meteorology from monthly statistics: Global-WGEN (GWGEN) v1.0

NASA Astrophysics Data System (ADS)

Sommer, Philipp S.; Kaplan, Jed O.

2017-10-01

While a wide range of Earth system processes occur at daily and even subdaily timescales, many global vegetation and other terrestrial dynamics models historically used monthly meteorological forcing both to reduce computational demand and because global datasets were lacking. Recently, dynamic land surface modeling has moved towards resolving daily and subdaily processes, and global datasets containing daily and subdaily meteorology have become available. These meteorological datasets, however, cover only the instrumental era of the last approximately 120 years at best, are subject to considerable uncertainty, and represent extremely large data files with associated computational costs of data input/output and file transfer. For periods before the recent past or in the future, global meteorological forcing can be provided by climate model output, but the quality of these data at high temporal resolution is low, particularly for daily precipitation frequency and amount. Here, we present GWGEN, a globally applicable statistical weather generator for the temporal downscaling of monthly climatology to daily meteorology. Our weather generator is parameterized using a global meteorological database and simulates daily values of five common variables: minimum and maximum temperature, precipitation, cloud cover, and wind speed. GWGEN is lightweight, modular, and requires a minimal set of monthly mean variables as input. The weather generator may be used in a range of applications, for example, in global vegetation, crop, soil erosion, or hydrological models. While GWGEN does not currently perform spatially autocorrelated multi-point downscaling of daily weather, this additional functionality could be implemented in future versions.

Optimization of a hydrodynamic separator using a multiscale computational fluid dynamics approach.

PubMed

Schmitt, Vivien; Dufresne, Matthieu; Vazquez, Jose; Fischer, Martin; Morin, Antoine

2013-01-01

This article deals with the optimization of a hydrodynamic separator working on the tangential separation mechanism along a screen. The aim of this study is to optimize the shape of the device to avoid clogging. A multiscale approach is used. This methodology combines measurements and computational fluid dynamics (CFD). A local model enables us to observe the different phenomena occurring at the orifice scale, which shows the potential of expanded metal screens. A global model is used to simulate the flow within the device using a conceptual model of the screen (porous wall). After validation against the experimental measurements, the global model was used to investigate the influence of deflectors and disk plates in the structure.

Increased future ice discharge from Antarctica owing to higher snowfall.

PubMed

Winkelmann, R; Levermann, A; Martin, M A; Frieler, K

2012-12-13

Anthropogenic climate change is likely to cause continuing global sea level rise, but some processes within the Earth system may mitigate the magnitude of the projected effect. Regional and global climate models simulate enhanced snowfall over Antarctica, which would provide a direct offset of the future contribution to global sea level rise from cryospheric mass loss and ocean expansion. Uncertainties exist in modelled snowfall, but even larger uncertainties exist in the potential changes of dynamic ice discharge from Antarctica and thus in the ultimate fate of the precipitation-deposited ice mass. Here we show that snowfall and discharge are not independent, but that future ice discharge will increase by up to three times as a result of additional snowfall under global warming. Our results, based on an ice-sheet model forced by climate simulations through to the end of 2500 (ref. 8), show that the enhanced discharge effect exceeds the effect of surface warming as well as that of basal ice-shelf melting, and is due to the difference in surface elevation change caused by snowfall on grounded versus floating ice. Although different underlying forcings drive ice loss from basal melting versus increased snowfall, similar ice dynamical processes are nonetheless at work in both; therefore results are relatively independent of the specific representation of the transition zone. In an ensemble of simulations designed to capture ice-physics uncertainty, the additional dynamic ice loss along the coastline compensates between 30 and 65 per cent of the ice gain due to enhanced snowfall over the entire continent. This results in a dynamic ice loss of up to 1.25 metres in the year 2500 for the strongest warming scenario. The reported effect thus strongly counters a potential negative contribution to global sea level by the Antarctic Ice Sheet.

Investigation of Structural Dynamics in a 2-Meter Square Solar Sail Model Including Axial Load Effects

NASA Technical Reports Server (NTRS)

Holland, D. B.; Virgin, L. N.; Belvin, W. K.

2003-01-01

This paper presents a parameter study of the effect of boom axial loading on the global dynamics of a 2-meter solar sail scale model. The experimental model used is meant for building expertise in finite element analysis and experimental execution, not as a predecessor to any planned flight mission or particular design concept. The results here are to demonstrate the ability to predict and measure structural dynamics and mode shapes in the presence of axial loading.

Local conformity induced global oscillation

NASA Astrophysics Data System (ADS)

Li, Dong; Li, Wei; Hu, Gang; Zheng, Zhigang

2009-04-01

The game ‘rock-paper-scissors’ model, with the consideration of the effect of the psychology of conformity, is investigated. The interaction between each two agents is global, but the strategy of the conformity is local for individuals. In the statistical opinion, the probability of the appearance of each strategy is uniform. The dynamical analysis of this model indicates that the equilibrium state may lose its stability at a threshold and is replaced by a globally oscillating state. The global oscillation is induced by the local conformity, which is originated from the synchronization of individual strategies.

DCMIP2016: a review of non-hydrostatic dynamical core design and intercomparison of participating models

NASA Astrophysics Data System (ADS)

Ullrich, Paul A.; Jablonowski, Christiane; Kent, James; Lauritzen, Peter H.; Nair, Ramachandran; Reed, Kevin A.; Zarzycki, Colin M.; Hall, David M.; Dazlich, Don; Heikes, Ross; Konor, Celal; Randall, David; Dubos, Thomas; Meurdesoif, Yann; Chen, Xi; Harris, Lucas; Kühnlein, Christian; Lee, Vivian; Qaddouri, Abdessamad; Girard, Claude; Giorgetta, Marco; Reinert, Daniel; Klemp, Joseph; Park, Sang-Hun; Skamarock, William; Miura, Hiroaki; Ohno, Tomoki; Yoshida, Ryuji; Walko, Robert; Reinecke, Alex; Viner, Kevin

2017-12-01

Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems and are responsible for capturing the dynamical behavior of the Earth's atmosphere via numerical integration of the Navier-Stokes equations. These systems have existed in one form or another for over half of a century, with the earliest discretizations having now evolved into a complex ecosystem of algorithms and computational strategies. In essence, no two dynamical cores are alike, and their individual successes suggest that no perfect model exists. To better understand modern dynamical cores, this paper aims to provide a comprehensive review of 11 non-hydrostatic dynamical cores, drawn from modeling centers and groups that participated in the 2016 Dynamical Core Model Intercomparison Project (DCMIP) workshop and summer school. This review includes a choice of model grid, variable placement, vertical coordinate, prognostic equations, temporal discretization, and the diffusion, stabilization, filters, and fixers employed by each system.

CADLIVE toolbox for MATLAB: automatic dynamic modeling of biochemical networks with comprehensive system analysis.

PubMed

Inoue, Kentaro; Maeda, Kazuhiro; Miyabe, Takaaki; Matsuoka, Yu; Kurata, Hiroyuki

2014-09-01

Mathematical modeling has become a standard technique to understand the dynamics of complex biochemical systems. To promote the modeling, we had developed the CADLIVE dynamic simulator that automatically converted a biochemical map into its associated mathematical model, simulated its dynamic behaviors and analyzed its robustness. To enhance the feasibility by CADLIVE and extend its functions, we propose the CADLIVE toolbox available for MATLAB, which implements not only the existing functions of the CADLIVE dynamic simulator, but also the latest tools including global parameter search methods with robustness analysis. The seamless, bottom-up processes consisting of biochemical network construction, automatic construction of its dynamic model, simulation, optimization, and S-system analysis greatly facilitate dynamic modeling, contributing to the research of systems biology and synthetic biology. This application can be freely downloaded from http://www.cadlive.jp/CADLIVE_MATLAB/ together with an instruction.

Dynamic Modeling of Cell-Free Biochemical Networks Using Effective Kinetic Models

DTIC Science & Technology

2015-03-16

sensitivity value was the maximum uncertainty in that value estimated by the Sobol method. 2.4. Global Sensitivity Analysis of the Reduced Order Coagulation...sensitivity analysis, using the variance-based method of Sobol , to estimate which parameters controlled the performance of the reduced order model [69]. We...Environment. Comput. Sci. Eng. 2007, 9, 90–95. 69. Sobol , I. Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates

Rényi information flow in the Ising model with single-spin dynamics.

PubMed

Deng, Zehui; Wu, Jinshan; Guo, Wenan

2014-12-01

The n-index Rényi mutual information and transfer entropies for the two-dimensional kinetic Ising model with arbitrary single-spin dynamics in the thermodynamic limit are derived as functions of ensemble averages of observables and spin-flip probabilities. Cluster Monte Carlo algorithms with different dynamics from the single-spin dynamics are thus applicable to estimate the transfer entropies. By means of Monte Carlo simulations with the Wolff algorithm, we calculate the information flows in the Ising model with the Metropolis dynamics and the Glauber dynamics, respectively. We find that not only the global Rényi transfer entropy, but also the pairwise Rényi transfer entropy, peaks in the disorder phase.

Dynamic sea surface topography, gravity and improved orbit accuracies from the direct evaluation of SEASAT altimeter data

NASA Technical Reports Server (NTRS)

Marsh, J. G.; Lerch, F.; Koblinsky, C. J.; Klosko, S. M.; Robbins, J. W.; Williamson, R. G.; Patel, G. B.

1989-01-01

A method for the simultaneous solution of dynamic ocean topography, gravity and orbits using satellite altimeter data is described. A GEM-T1 based gravitational model called PGS-3337 that incorporates Seasat altimetry, surface gravimetry and satellite tracking data has been determined complete to degree and order 50. The altimeter data is utilized as a dynamic observation of the satellite's height above the sea surface with a degree 10 model of dynamic topography being recovered simultaneously with the orbit parameters, gravity and tidal terms in this model. PGS-3337 has a geoid uncertainty of 60 cm root-mean-square (RMS) globally, with the uncertainty over the altimeter tracked ocean being in the 25 cm range. Doppler determined orbits for Seasat, show large improvements, with the sub-30 cm radial accuracies being achieved. When altimeter data is used in orbit determination, radial orbital accuracies of 20 cm are achieved. The RMS of fit to the altimeter data directly gives 30 cm fits for Seasat when using PGS-3337 and its geoid and dynamic topography model. This performance level is two to three times better than that achieved with earlier Goddard earth models (GEM) using the dynamic topography from long-term oceanographic averages. The recovered dynamic topography reveals the global long wavelength circulation of the oceans with a resolution of 1500 km. The power in the dynamic topography recovery is now found to be closer to that of oceanographic studies than for previous satellite solutions. This is attributed primarily to the improved modeling of the geoid which has occurred. Study of the altimeter residuals reveals regions where tidal models are poor and sea state effects are major limitations.

Global dynamics of a mathematical model for the possible re-emergence of polio.

PubMed

Dénes, Attila; Székely, László

2017-11-01

Motivated by studies warning about a possible re-emergence of poliomyelitis in Europe, we analyse a compartmental model for the transmission of polio describing the possible effect of unvaccinated people arriving to a region with low vaccination coverage. We calculate the basic reproduction number, and determine the global dynamics of the system: we show that, depending on the parameters, one of the two equilibria is globally asymptotically stable. The main tools applied are Lyapunov functions and persistence theory. We illustrate the analytic results by numerical examples, which also suggest that in order to avoid the risk of polio re-emergence, vaccinating the immigrant population might result insufficient, and also the vaccination coverage of countries with low rates should be increased. Copyright © 2017 Elsevier Inc. All rights reserved.

Global robust output regulation control for cascaded nonlinear systems using the internal model principle

NASA Astrophysics Data System (ADS)

Yu, Jiang-Bo; Zhao, Yan; Wu, Yu-Qiang

2014-04-01

This article considers the global robust output regulation problem via output feedback for a class of cascaded nonlinear systems with input-to-state stable inverse dynamics. The system uncertainties depend not only on the measured output but also all the unmeasurable states. By introducing an internal model, the output regulation problem is converted into a stabilisation problem for an appropriately augmented system. The designed dynamic controller could achieve the global asymptotic tracking control for a class of time-varying reference signals for the system output while keeping all other closed-loop signals bounded. It is of interest to note that the developed control approach can be applied to the speed tracking control of the fan speed control system. The simulation results demonstrate its effectiveness.

Global spatiotemporal distribution of soil respiration modeled using a global database

NASA Astrophysics Data System (ADS)

Hashimoto, S.; Carvalhais, N.; Ito, A.; Migliavacca, M.; Nishina, K.; Reichstein, M.

2015-07-01

The flux of carbon dioxide from the soil to the atmosphere (soil respiration) is one of the major fluxes in the global carbon cycle. At present, the accumulated field observation data cover a wide range of geographical locations and climate conditions. However, there are still large uncertainties in the magnitude and spatiotemporal variation of global soil respiration. Using a global soil respiration data set, we developed a climate-driven model of soil respiration by modifying and updating Raich's model, and the global spatiotemporal distribution of soil respiration was examined using this model. The model was applied at a spatial resolution of 0.5°and a monthly time step. Soil respiration was divided into the heterotrophic and autotrophic components of respiration using an empirical model. The estimated mean annual global soil respiration was 91 Pg C yr-1 (between 1965 and 2012; Monte Carlo 95 % confidence interval: 87-95 Pg C yr-1) and increased at the rate of 0.09 Pg C yr-2. The contribution of soil respiration from boreal regions to the total increase in global soil respiration was on the same order of magnitude as that of tropical and temperate regions, despite a lower absolute magnitude of soil respiration in boreal regions. The estimated annual global heterotrophic respiration and global autotrophic respiration were 51 and 40 Pg C yr-1, respectively. The global soil respiration responded to the increase in air temperature at the rate of 3.3 Pg C yr-1 °C-1, and Q10 = 1.4. Our study scaled up observed soil respiration values from field measurements to estimate global soil respiration and provide a data-oriented estimate of global soil respiration. The estimates are based on a semi-empirical model parameterized with over one thousand data points. Our analysis indicates that the climate controls on soil respiration may translate into an increasing trend in global soil respiration and our analysis emphasizes the relevance of the soil carbon flux from soil to the atmosphere in response to climate change. Further approaches should additionally focus on climate controls in soil respiration in combination with changes in vegetation dynamics and soil carbon stocks, along with their effects on the long temporal dynamics of soil respiration. We expect that these spatiotemporal estimates will provide a benchmark for future studies and also help to constrain process-oriented models.

A review on vegetation models and applicability to climate simulations at regional scale

NASA Astrophysics Data System (ADS)

Myoung, Boksoon; Choi, Yong-Sang; Park, Seon Ki

2011-11-01

The lack of accurate representations of biospheric components and their biophysical and biogeochemical processes is a great source of uncertainty in current climate models. The interactions between terrestrial ecosystems and the climate include exchanges not only of energy, water and momentum, but also of carbon and nitrogen. Reliable simulations of these interactions are crucial for predicting the potential impacts of future climate change and anthropogenic intervention on terrestrial ecosystems. In this paper, two biogeographical (Neilson's rule-based model and BIOME), two biogeochemical (BIOME-BGC and PnET-BGC), and three dynamic global vegetation models (Hybrid, LPJ, and MC1) were reviewed and compared in terms of their biophysical and physiological processes. The advantages and limitations of the models were also addressed. Lastly, the applications of the dynamic global vegetation models to regional climate simulations have been discussed.

Global Migration Dynamics Underlie Evolution and Persistence of Human Influenza A (H3N2)

PubMed Central

Bedford, Trevor; Cobey, Sarah; Beerli, Peter; Pascual, Mercedes

2010-01-01

The global migration patterns of influenza viruses have profound implications for the evolutionary and epidemiological dynamics of the disease. We developed a novel approach to reconstruct the genetic history of human influenza A (H3N2) collected worldwide over 1998 to 2009 and used it to infer the global network of influenza transmission. Consistent with previous models, we find that China and Southeast Asia lie at the center of this global network. However, we also find that strains of influenza circulate outside of Asia for multiple seasons, persisting through dynamic migration between northern and southern regions. The USA acts as the primary hub of temperate transmission and, together with China and Southeast Asia, forms the trunk of influenza's evolutionary tree. These findings suggest that antiviral use outside of China and Southeast Asia may lead to the evolution of long-term local and potentially global antiviral resistance. Our results might also aid the design of surveillance efforts and of vaccines better tailored to different geographic regions. PMID:20523898

Three-dimensional discrete-time Lotka-Volterra models with an application to industrial clusters

NASA Astrophysics Data System (ADS)

Bischi, G. I.; Tramontana, F.

2010-10-01

We consider a three-dimensional discrete dynamical system that describes an application to economics of a generalization of the Lotka-Volterra prey-predator model. The dynamic model proposed is used to describe the interactions among industrial clusters (or districts), following a suggestion given by [23]. After studying some local and global properties and bifurcations in bidimensional Lotka-Volterra maps, by numerical explorations we show how some of them can be extended to their three-dimensional counterparts, even if their analytic and geometric characterization becomes much more difficult and challenging. We also show a global bifurcation of the three-dimensional system that has no two-dimensional analogue. Besides the particular economic application considered, the study of the discrete version of Lotka-Volterra dynamical systems turns out to be a quite rich and interesting topic by itself, i.e. from a purely mathematical point of view.

Dynamical analysis of a fractional SIR model with birth and death on heterogeneous complex networks

NASA Astrophysics Data System (ADS)

Huo, Jingjing; Zhao, Hongyong

2016-04-01

In this paper, a fractional SIR model with birth and death rates on heterogeneous complex networks is proposed. Firstly, we obtain a threshold value R0 based on the existence of endemic equilibrium point E∗, which completely determines the dynamics of the model. Secondly, by using Lyapunov function and Kirchhoff's matrix tree theorem, the globally asymptotical stability of the disease-free equilibrium point E0 and the endemic equilibrium point E∗ of the model are investigated. That is, when R0 < 1, the disease-free equilibrium point E0 is globally asymptotically stable and the disease always dies out; when R0 > 1, the disease-free equilibrium point E0 becomes unstable and in the meantime there exists a unique endemic equilibrium point E∗, which is globally asymptotically stable and the disease is uniformly persistent. Finally, the effects of various immunization schemes are studied and compared. Numerical simulations are given to demonstrate the main results.

On the characteristics of aerosol indirect effect based on dynamic regimes in global climate models

DOE PAGES

Zhang, Shipeng; Wang, Minghuai; Ghan, Steven J.; ...

2016-03-04

Aerosol–cloud interactions continue to constitute a major source of uncertainty for the estimate of climate radiative forcing. The variation of aerosol indirect effects (AIE) in climate models is investigated across different dynamical regimes, determined by monthly mean 500 hPa vertical pressure velocity ( ω 500), lower-tropospheric stability (LTS) and large-scale surface precipitation rate derived from several global climate models (GCMs), with a focus on liquid water path (LWP) response to cloud condensation nuclei (CCN) concentrations. The LWP sensitivity to aerosol perturbation within dynamic regimes is found to exhibit a large spread among these GCMs. It is in regimes of strongmore » large-scale ascent ( ω 500  <  −25 hPa day −1) and low clouds (stratocumulus and trade wind cumulus) where the models differ most. Shortwave aerosol indirect forcing is also found to differ significantly among different regimes. Shortwave aerosol indirect forcing in ascending regimes is close to that in subsidence regimes, which indicates that regimes with strong large-scale ascent are as important as stratocumulus regimes in studying AIE. It is further shown that shortwave aerosol indirect forcing over regions with high monthly large-scale surface precipitation rate (> 0.1 mm day −1) contributes the most to the total aerosol indirect forcing (from 64 to nearly 100 %). Results show that the uncertainty in AIE is even larger within specific dynamical regimes compared to the uncertainty in its global mean values, pointing to the need to reduce the uncertainty in AIE in different dynamical regimes.« less

Global sensitivity analysis of a filtration model for submerged anaerobic membrane bioreactors (AnMBR).

PubMed

Robles, A; Ruano, M V; Ribes, J; Seco, A; Ferrer, J

2014-04-01

The results of a global sensitivity analysis of a filtration model for submerged anaerobic MBRs (AnMBRs) are assessed in this paper. This study aimed to (1) identify the less- (or non-) influential factors of the model in order to facilitate model calibration and (2) validate the modelling approach (i.e. to determine the need for each of the proposed factors to be included in the model). The sensitivity analysis was conducted using a revised version of the Morris screening method. The dynamic simulations were conducted using long-term data obtained from an AnMBR plant fitted with industrial-scale hollow-fibre membranes. Of the 14 factors in the model, six were identified as influential, i.e. those calibrated using off-line protocols. A dynamic calibration (based on optimisation algorithms) of these influential factors was conducted. The resulting estimated model factors accurately predicted membrane performance. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modeling Study of the Geospace System Response to the Solar Wind Dynamic Pressure Enhancement on 17 March 2015

NASA Astrophysics Data System (ADS)

Ozturk, D. S.; Zou, S.; Ridley, A. J.; Slavin, J. A.

2018-04-01

The global magnetosphere-ionosphere-thermosphere system is intrinsically coupled and susceptible to external drivers such as solar wind dynamic pressure enhancements. In order to understand the large-scale dynamic processes in the magnetosphere-ionosphere-thermosphere system due to the compression from the solar wind, the 17 March 2015 sudden commencement was studied in detail using global numerical models. This storm was one of the most geoeffective events of the solar cycle 24 with a minimum Dst of -222 nT. The Wind spacecraft recorded a 10-nPa increment in the solar wind dynamic pressure, while the interplanetary magnetic field BZ became further northward. The University of Michigan Block-Adaptive-Tree Solar wind Roe-type Upwind Scheme global magnetohydrodynamic code was utilized to study the generation and propagation of perturbations associated with the compression of the magnetosphere system. In addition, the high-resolution electric potential and auroral power output from the magnetohydrodynamic model was used to drive the global ionosphere-thermosphere model to investigate the ionosphere-thermosphere system response to pressure enhancement. During the compression, the electric potentials and convection patterns in the polar ionosphere were significantly altered when the preliminary impulse and main impulse field-aligned currents moved from dayside to nightside. As a result of enhanced frictional heating, plasma and neutral temperatures increased at the locations where the flow speeds were enhanced, whereas the electron density dropped at these locations. In particular, the region between the preliminary impulse and main impulse field-aligned currents experienced the most significant heating with 1000-K ion temperature increase and 20-K neutral temperature increase within 2 min. Comparison of the simulation results with the Poker Flat Incoherent Scatter Radar observations showed reasonable agreements despite underestimated magnitudes.

A model for cross-cultural reciprocal interactions through mass media.

PubMed

González-Avella, Juan Carlos; Cosenza, Mario G; San Miguel, Maxi

2012-01-01

We investigate the problem of cross-cultural interactions through mass media in a model where two populations of social agents, each with its own internal dynamics, get information about each other through reciprocal global interactions. As the agent dynamics, we employ Axelrod's model for social influence. The global interaction fields correspond to the statistical mode of the states of the agents and represent mass media messages on the cultural trend originating in each population. Several phases are found in the collective behavior of either population depending on parameter values: two homogeneous phases, one having the state of the global field acting on that population, and the other consisting of a state different from that reached by the applied global field; and a disordered phase. In addition, the system displays nontrivial effects: (i) the emergence of a largest minority group of appreciable size sharing a state different from that of the applied global field; (ii) the appearance of localized ordered states for some values of parameters when the entire system is observed, consisting of one population in a homogeneous state and the other in a disordered state. This last situation can be considered as a social analogue to a chimera state arising in globally coupled populations of oscillators.

Dynamical clockwork axions

NASA Astrophysics Data System (ADS)

Coy, Rupert; Frigerio, Michele; Ibe, Masahiro

2017-10-01

The clockwork mechanism is a novel method for generating a large separation between the dynamical scale and interaction scale of a theory. We demonstrate how the mechanism can arise from a sequence of strongly-coupled sectors. This framework avoids elementary scalar fields as well as ad hoc continuous global symmetries, both of which are subject to serious stability issues. The clockwork factor, q, is determined by the consistency of the strong dynamics. The preserved global U(1) of the clockwork appears as an accidental symmetry, resulting from discrete or U(1) gauge symmetries, and it is spontaneously broken by the chiral condensates. We apply such a dynamical clockwork to construct models with an effectively invisible QCD axion from TeV-scale strong dynamics. The axion couplings are determined by the localisation of the Standard Model interactions along the clockwork sequence. The TeV spectrum includes either coloured hadrons or vector-like quarks. Dark matter can be accounted for by the axion or the lightest neutral baryons, which are accidentally stable.

Unifying viral genetics and human transportation data to predict the global transmission dynamics of human influenza H3N2.

PubMed

Lemey, Philippe; Rambaut, Andrew; Bedford, Trevor; Faria, Nuno; Bielejec, Filip; Baele, Guy; Russell, Colin A; Smith, Derek J; Pybus, Oliver G; Brockmann, Dirk; Suchard, Marc A

2014-02-01

Information on global human movement patterns is central to spatial epidemiological models used to predict the behavior of influenza and other infectious diseases. Yet it remains difficult to test which modes of dispersal drive pathogen spread at various geographic scales using standard epidemiological data alone. Evolutionary analyses of pathogen genome sequences increasingly provide insights into the spatial dynamics of influenza viruses, but to date they have largely neglected the wealth of information on human mobility, mainly because no statistical framework exists within which viral gene sequences and empirical data on host movement can be combined. Here, we address this problem by applying a phylogeographic approach to elucidate the global spread of human influenza subtype H3N2 and assess its ability to predict the spatial spread of human influenza A viruses worldwide. Using a framework that estimates the migration history of human influenza while simultaneously testing and quantifying a range of potential predictive variables of spatial spread, we show that the global dynamics of influenza H3N2 are driven by air passenger flows, whereas at more local scales spread is also determined by processes that correlate with geographic distance. Our analyses further confirm a central role for mainland China and Southeast Asia in maintaining a source population for global influenza diversity. By comparing model output with the known pandemic expansion of H1N1 during 2009, we demonstrate that predictions of influenza spatial spread are most accurate when data on human mobility and viral evolution are integrated. In conclusion, the global dynamics of influenza viruses are best explained by combining human mobility data with the spatial information inherent in sampled viral genomes. The integrated approach introduced here offers great potential for epidemiological surveillance through phylogeographic reconstructions and for improving predictive models of disease control.

Robust Dynamic Multi-objective Vehicle Routing Optimization Method.

PubMed

Guo, Yi-Nan; Cheng, Jian; Luo, Sha; Gong, Dun-Wei

2017-03-21

For dynamic multi-objective vehicle routing problems, the waiting time of vehicle, the number of serving vehicles, the total distance of routes were normally considered as the optimization objectives. Except for above objectives, fuel consumption that leads to the environmental pollution and energy consumption was focused on in this paper. Considering the vehicles' load and the driving distance, corresponding carbon emission model was built and set as an optimization objective. Dynamic multi-objective vehicle routing problems with hard time windows and randomly appeared dynamic customers, subsequently, were modeled. In existing planning methods, when the new service demand came up, global vehicle routing optimization method was triggered to find the optimal routes for non-served customers, which was time-consuming. Therefore, robust dynamic multi-objective vehicle routing method with two-phase is proposed. Three highlights of the novel method are: (i) After finding optimal robust virtual routes for all customers by adopting multi-objective particle swarm optimization in the first phase, static vehicle routes for static customers are formed by removing all dynamic customers from robust virtual routes in next phase. (ii)The dynamically appeared customers append to be served according to their service time and the vehicles' statues. Global vehicle routing optimization is triggered only when no suitable locations can be found for dynamic customers. (iii)A metric measuring the algorithms' robustness is given. The statistical results indicated that the routes obtained by the proposed method have better stability and robustness, but may be sub-optimum. Moreover, time-consuming global vehicle routing optimization is avoided as dynamic customers appear.

Significant Findings: Seasonal Distributions of Global Ocean Chlorophyll and Nutrients With a Coupled Ocean General Circulation, Biogeochemical, and Radiative Model. 2; Comparisons With Satellite and In Situ Data

NASA Technical Reports Server (NTRS)

Gregg, Watson W.; Busalacchi, Antonio (Technical Monitor)

2000-01-01

A coupled ocean general circulation, biogeochemical, and radiative model was constructed to evaluate and understand the nature of seasonal variability of chlorophyll and nutrients in the global oceans. Biogeochemical processes in the model were determined from the influences of circulation and turbulence dynamics, irradiance availability, and the interactions among three functional phytoplankton groups (diatoms, chlorophytes, and picoplankton) and three nutrients (nitrate, ammonium, and silicate). Basin scale (>1000 km) model chlorophyll seasonal distributions were statistically positively correlated with CZCS chlorophyll in 10 of 12 major oceanographic regions, and with SeaWiFS in all 12. Notable disparities in magnitudes occurred, however, in the tropical Pacific, the spring/summer bloom in the Antarctic, autumn in the northern high latitudes, and during the southwest monsoon in the North Indian Ocean. Synoptic scale (100-1000 km) comparisons of satellite and in situ data exhibited broad agreement, although occasional departures were apparent. Model nitrate distributions agreed with in situ data, including seasonal dynamics, except for the equatorial Atlantic. The overall agreement of the model with satellite and in situ data sources indicated that the model dynamics offer a reasonably realistic simulation of phytoplankton and nutrient dynamics on basin and synoptic scales.

Low historical nitrogen deposition effect on carbon sequestration in the boreal zone

NASA Astrophysics Data System (ADS)

Fleischer, K.; Wârlind, D.; van der Molen, M. K.; Rebel, K. T.; Arneth, A.; Erisman, J. W.; Wassen, M. J.; Smith, B.; Gough, C. M.; Margolis, H. A.; Cescatti, A.; Montagnani, L.; Arain, A.; Dolman, A. J.

2015-12-01

Nitrogen (N) cycle dynamics and N deposition play an important role in determining the terrestrial biosphere's carbon (C) balance. We assess global and biome-specific N deposition effects on C sequestration rates with the dynamic global vegetation model LPJ-GUESS. Modeled CN interactions are evaluated by comparing predictions of the C and CN version of the model with direct observations of C fluxes from 68 forest FLUXNET sites. N limitation on C uptake reduced overestimation of gross primary productivity for boreal evergreen needleleaf forests from 56% to 18%, presenting the greatest improvement among forest types. Relative N deposition effects on C sequestration (dC/dN) in boreal, temperate, and tropical sites ranged from 17 to 26 kg C kg N-1 when modeled at site scale and were reduced to 12-22 kg C kg N-1 at global scale. We find that 19% of the recent (1990-2007) and 24% of the historical global C sink (1900-2006) was driven by N deposition effects. While boreal forests exhibit highest dC/dN, their N deposition-induced C sink was relatively low and is suspected to stay low in the future as no major changes in N deposition rates are expected in the boreal zone. N deposition induced a greater C sink in temperate and tropical forests, while predicted C fluxes and N-induced C sink response in tropical forests were associated with greatest uncertainties. Future work should be directed at improving the ability of LPJ-GUESS and other process-based ecosystem models to reproduce C cycle dynamics in the tropics, facilitated by more benchmarking data sets. Furthermore, efforts should aim to improve understanding and model representations of N availability (e.g., N fixation and organic N uptake), N limitation, P cycle dynamics, and effects of anthropogenic land use and land cover changes.

Precise tracking of remote sensing satellites with the Global Positioning System

NASA Technical Reports Server (NTRS)

Yunck, Thomas P.; Wu, Sien-Chong; Wu, Jiun-Tsong; Thornton, Catherine L.

1990-01-01

The Global Positioning System (GPS) can be applied in a number of ways to track remote sensing satellites at altitudes below 3000 km with accuracies of better than 10 cm. All techniques use a precise global network of GPS ground receivers operating in concert with a receiver aboard the user satellite, and all estimate the user orbit, GPS orbits, and selected ground locations simultaneously. The GPS orbit solutions are always dynamic, relying on the laws of motion, while the user orbit solution can range from purely dynamic to purely kinematic (geometric). Two variations show considerable promise. The first one features an optimal synthesis of dynamics and kinematics in the user solution, while the second introduces a novel gravity model adjustment technique to exploit data from repeat ground tracks. These techniques, to be demonstrated on the Topex/Poseidon mission in 1992, will offer subdecimeter tracking accuracy for dynamically unpredictable satellites down to the lowest orbital altitudes.

Global Dynamics of Proteins: Bridging Between Structure and Function

PubMed Central

Bahar, Ivet; Lezon, Timothy R.; Yang, Lee-Wei; Eyal, Eran

2010-01-01

Biomolecular systems possess unique, structure-encoded dynamic properties that underlie their biological functions. Recent studies indicate that these dynamic properties are determined to a large extent by the topology of native contacts. In recent years, elastic network models used in conjunction with normal mode analyses have proven to be useful for elucidating the collective dynamics intrinsically accessible under native state conditions, including in particular the global modes of motions that are robustly defined by the overall architecture. With increasing availability of structural data for well-studied proteins in different forms (liganded, complexed, or free), there is increasing evidence in support of the correspondence between functional changes in structures observed in experiments and the global motions predicted by these coarse-grained analyses. These observed correlations suggest that computational methods may be advantageously employed for assessing functional changes in structure and allosteric mechanisms intrinsically favored by the native fold. PMID:20192781

Global dynamics of proteins: bridging between structure and function.

PubMed

Bahar, Ivet; Lezon, Timothy R; Yang, Lee-Wei; Eyal, Eran

2010-01-01

Biomolecular systems possess unique, structure-encoded dynamic properties that underlie their biological functions. Recent studies indicate that these dynamic properties are determined to a large extent by the topology of native contacts. In recent years, elastic network models used in conjunction with normal mode analyses have proven to be useful for elucidating the collective dynamics intrinsically accessible under native state conditions, including in particular the global modes of motions that are robustly defined by the overall architecture. With increasing availability of structural data for well-studied proteins in different forms (liganded, complexed, or free), there is increasing evidence in support of the correspondence between functional changes in structures observed in experiments and the global motions predicted by these coarse-grained analyses. These observed correlations suggest that computational methods may be advantageously employed for assessing functional changes in structure and allosteric mechanisms intrinsically favored by the native fold.

Global mean dynamic topography based on GOCE data and Wiener filters

NASA Astrophysics Data System (ADS)

Gilardoni, Maddalena; Reguzzoni, Mirko; Albertella, Alberta

2015-04-01

A mean dynamic ocean topography (MDT) has been computed by using a GOCE-only gravity model and a given mean sea surface (MSS) obtained from satellite altimetry. Since the used gravity model, i.e. the fifth release of the time-wise solution covering the full mission lifetime, is truncated at a maximum harmonic degree of 280, the obtained MDT has to be consistently filtered. This has been done globally by using the spherical harmonic representation and following a Wiener minimization principle. This global filtering approach is convenient from the computational point of view but requires to have MDT values all over the Earth surface and therefore to fill the continents with fictitious data. The main improvements with respect to the already presented results are in the MDT filling procedure (to guarantee that the global signal has the same covariance of the one over the oceans), in the error modelling of the input MSS and in the error estimation of the filtered MDT and of the corresponding geostrophic velocities. The impact of GOCE data in the ocean circulation global modelling has been assessed by comparing the pattern of the obtained geostrophic currents with those computed by using EGM2008. Comparisons with independent circulation data based on drifters and other MDT models have been also performed with the aim of evaluating the accuracy of the obtained results.

Neocortical dynamics at multiple scales: EEG standing waves, statistical mechanics, and physical analogs.

PubMed

Ingber, Lester; Nunez, Paul L

2011-02-01

The dynamic behavior of scalp potentials (EEG) is apparently due to some combination of global and local processes with important top-down and bottom-up interactions across spatial scales. In treating global mechanisms, we stress the importance of myelinated axon propagation delays and periodic boundary conditions in the cortical-white matter system, which is topologically close to a spherical shell. By contrast, the proposed local mechanisms are multiscale interactions between cortical columns via short-ranged non-myelinated fibers. A mechanical model consisting of a stretched string with attached nonlinear springs demonstrates the general idea. The string produces standing waves analogous to large-scale coherent EEG observed in some brain states. The attached springs are analogous to the smaller (mesoscopic) scale columnar dynamics. Generally, we expect string displacement and EEG at all scales to result from both global and local phenomena. A statistical mechanics of neocortical interactions (SMNI) calculates oscillatory behavior consistent with typical EEG, within columns, between neighboring columns via short-ranged non-myelinated fibers, across cortical regions via myelinated fibers, and also derives a string equation consistent with the global EEG model. Copyright © 2010 Elsevier Inc. All rights reserved.

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.

Cross - Scale Intercomparison of Climate Change Impacts Simulated by Regional and Global Hydrological Models in Eleven Large River Basins

NASA Technical Reports Server (NTRS)

Hattermann, F. F.; Krysanova, V.; Gosling, S. N.; Dankers, R.; Daggupati, P.; Donnelly, C.; Florke, M.; Huang, S.; Motovilov, Y.; Buda, S.;

Cross-scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

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

Hattermann, F. F.; Krysanova, V.; Gosling, S. N.

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity of impact models designed for either scale to climate variability and change is comparable. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climatemore » change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a much better reproduction of reference conditions. However, the sensitivity of two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases with distinct differences in others, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability, but whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models validated against observed discharge should be used.« less

An Automatic Medium to High Fidelity Low-Thrust Global Trajectory Toolchain; EMTG-GMAT

NASA Technical Reports Server (NTRS)

Beeson, Ryne T.; Englander, Jacob A.; Hughes, Steven P.; Schadegg, Maximillian

2015-01-01

Solving the global optimization, low-thrust, multiple-flyby interplanetary trajectory problem with high-fidelity dynamical models requires an unreasonable amount of computational resources. A better approach, and one that is demonstrated in this paper, is a multi-step process whereby the solution of the aforementioned problem is solved at a lower-fidelity and this solution is used as an initial guess for a higher-fidelity solver. The framework presented in this work uses two tools developed by NASA Goddard Space Flight Center: the Evolutionary Mission Trajectory Generator (EMTG) and the General Mission Analysis Tool (GMAT). EMTG is a medium to medium-high fidelity low-thrust interplanetary global optimization solver, which now has the capability to automatically generate GMAT script files for seeding a high-fidelity solution using GMAT's local optimization capabilities. A discussion of the dynamical models as well as thruster and power modeling for both EMTG and GMAT are given in this paper. Current capabilities are demonstrated with examples that highlight the toolchains ability to efficiently solve the difficult low-thrust global optimization problem with little human intervention.

Parameter Selection Methods in Inverse Problem Formulation

DTIC Science & Technology

2010-11-03

clinical data and used for prediction and a model for the reaction of the cardiovascular system to an ergometric workload. Key Words: Parameter selection...model for HIV dynamics which has been successfully validated with clinical data and used for prediction and a model for the reaction of the...recently developed in-host model for HIV dynamics which has been successfully validated with clinical data and used for prediction [4, 8]; b) a global

Experimental weekly to seasonal U.S. forecasts with the Regional Spectral Model

Treesearch

J. Roads

2004-01-01

As described previously Roads et al. 2001a, hereafter RCF), the Scripps Experimental Climate Prediction Center (ECPC) has been making routine, near-real-time, long-range experimental global and regional dynamical forecasts since 27 September 1997. The global spectral model (GSM) used for these forecasts is that of National Centers for Environmental Prediction’s (NCEP;...

Earth survey applications division: Research leading to the effective use of space technology in applications relating to the Earth's surface and interior

NASA Technical Reports Server (NTRS)

Carpenter, L. (Editor)

1980-01-01

Accomplishments and future plans are described for the following areas: (1) geology - geobotanical indicators and geopotential data; (2) modeling magnetic fields; (3) modeling the structure, composition, and evolution of the Earth's crust; (4) global and regional motions of the Earth's crust and earthquake occurrence; (5) modeling geopotential from satellite tracking data; (6) modeling the Earth's gravity field; (7) global Earth dynamics; (8) sea surface topography, ocean dynamics; and geophysical interpretation; (9) land cover and land use; (10) physical and remote sensing attributes important in detecting, measuring, and monitoring agricultural crops; (11) prelaunch studies using LANDSAT D; (12) the multispectral linear array; (13) the aircraft linear array pushbroom radiometer; and (14) the spaceborne laser ranging system.

Stable configurations in social networks

NASA Astrophysics Data System (ADS)

Bronski, Jared C.; DeVille, Lee; Ferguson, Timothy; Livesay, Michael

2018-06-01

We present and analyze a model of opinion formation on an arbitrary network whose dynamics comes from a global energy function. We study the global and local minimizers of this energy, which we call stable opinion configurations, and describe the global minimizers under certain assumptions on the friendship graph. We show a surprising result that the number of stable configurations is not necessarily monotone in the strength of connection in the social network, i.e. the model sometimes supports more stable configurations when the interpersonal connections are made stronger.

The READY program: Building a global potential energy surface and reactive dynamic simulations for the hydrogen combustion.

PubMed

Mogo, César; Brandão, João

2014-06-30

READY (REActive DYnamics) is a program for studying reactive dynamic systems using a global potential energy surface (PES) built from previously existing PESs corresponding to each of the most important elementary reactions present in the system. We present an application to the combustion dynamics of a mixture of hydrogen and oxygen using accurate PESs for all the systems involving up to four oxygen and hydrogen atoms. Results at the temperature of 4000 K and pressure of 2 atm are presented and compared with model based on rate constants. Drawbacks and advantages of this approach are discussed and future directions of research are pointed out. Copyright © 2014 Wiley Periodicals, Inc.

The Cycles of Snow Cover in Pyrenees Mountain and Mont Lebanon Analyzed Using the Global Modeling Technique.

NASA Astrophysics Data System (ADS)

Drapeau, L.; Mangiarotti, S.; Le Jean, F.; Gascoin, S.; Jarlan, L.

2014-12-01

The global modeling technique provides a way to obtain ordinary differential equations from single time series1. This technique, initiated in the 1990s, could be applied successfully to numerous theoretic and experimental systems. More recently it could be applied to environmental systems2,3. Here this technique is applied to seasonal snow cover area in the Pyrenees mountain (Europe) and Mont Lebanon (Mediterranean region). The snowpack evolution is complex because it results from combination of processes driven by physiography (elevation, slope, land cover...) and meteorological variables (precipitation, temperature, wind speed...), which are highly heterogeneous in such regions. Satellite observations in visible bands offer a powerful tool to monitor snow cover areas at global scale, with large resolutions range. Although this observable does not directly inform about snow water equivalent, its dynamical behavior strongly relies on it. Therefore, snow cover area is likely to be a good proxy of the global dynamics and global modeling technique a well adapted approach. The MOD10A2 product (500m) generated from MODIS by the NASA is used after a pretreatment is applied to minimize clouds effect. The global modeling technique is then applied using two packages4,5. The analysis is performed with two time series for the whole period (2000-2012) and year by year. Low-dimensional chaotic models are obtained in many cases. Such models provide a strong argument for chaos since involving the two necessary conditions in a synthetic way: determinism and strong sensitivity to initial conditions. The models comparison suggests important non-stationnarities at interannual scale which prevent from detecting long term changes. 1: Letellier et al 2009. Frequently asked questions about global modeling, Chaos, 19, 023103. 2: Maquet et al 2007. Global models from the Canadian lynx cycles as a direct evidence for chaos in real ecosystems. J. of Mathematical Biology, 55 (1), 21-39 3: Mangiarotti et al 2014. Two chaotic global models for cereal crops cycles observed from satellite in Northern Morocco. Chaos, 24, 023130. 4 : Mangiarotti et al 2012. Polynomial search and Global modelling: two algorithms for modeling chaos. Physical Review E, 86(4), 046205. 5: http://cran.r-project.org/web/packages/PoMoS/index.html.

Contribution of energy values to the analysis of global searching molecular dynamics simulations of transmembrane helical bundles.

PubMed Central

Torres, Jaume; Briggs, John A G; Arkin, Isaiah T

2002-01-01

Molecular interactions between transmembrane alpha-helices can be explored using global searching molecular dynamics simulations (GSMDS), a method that produces a group of probable low energy structures. We have shown previously that the correct model in various homooligomers is always located at the bottom of one of various possible energy basins. Unfortunately, the correct model is not necessarily the one with the lowest energy according to the computational protocol, which has resulted in overlooking of this parameter in favor of experimental data. In an attempt to use energetic considerations in the aforementioned analysis, we used global searching molecular dynamics simulations on three homooligomers of different sizes, the structures of which are known. As expected, our results show that even when the conformational space searched includes the correct structure, taking together simulations using both left and right handedness, the correct model does not necessarily have the lowest energy. However, for the models derived from the simulation that uses the correct handedness, the lowest energy model is always at, or very close to, the correct orientation. We hypothesize that this should also be true when simulations are performed using homologous sequences, and consequently lowest energy models with the right handedness should produce a cluster around a certain orientation. In contrast, using the wrong handedness the lowest energy structures for each sequence should appear at many different orientations. The rationale behind this is that, although more than one energy basin may exist, basins that do not contain the correct model will shift or disappear because they will be destabilized by at least one conservative (i.e. silent) mutation, whereas the basin containing the correct model will remain. This not only allows one to point to the possible handedness of the bundle, but can be used to overcome ambiguities arising from the use of homologous sequences in the analysis of global searching molecular dynamics simulations. In addition, because clustering of lowest energy models arising from homologous sequences only happens when the estimation of the helix tilt is correct, it may provide a validation for the helix tilt estimate. PMID:12023229

Increased future ice discharge from Antarctica owing to higher snowfall

NASA Astrophysics Data System (ADS)

Winkelmann, Ricarda; Levermann, Anders; Martin, Maria A.; Frieler, Katja

2013-04-01

Anthropogenic climate change is likely to cause continuing global sea-level rise, but some processes within the Earth system may mitigate the magnitude of the projected effect. Regional and global climate models simulate enhanced snowfall over Antarctica, which would provide a direct offset of the future contribution to global sea level rise from cryospheric mass loss and ocean expansion. Uncertainties exist in modelled snowfall, but even larger uncertainties exist in the potential changes of dynamic ice discharge from Antarctica. Here we show that snowfall and discharge are not independent, but that future ice discharge will increase by up to three times as a result of additional snowfall under global warming. Our results, based on an ice-sheet model forced by climate simulations through to the end of 2500, show that the enhanced discharge effect exceeds the effect of surface warming as well as that of basal ice-shelf melting, and is due to the difference in surface elevation change caused by snowfall on grounded versus floating ice. Although different underlying forcings drive ice loss from basal melting versus increased snowfall, similar ice dynamical processes are nonetheless at work in both; therefore results are relatively independent of the specific representation of the transition zone. In an ensemble of simulations designed to capture ice-physics uncertainty, the additional dynamic ice loss along the coastline compensates between 30 and 65 per cent of the ice gain due to enhanced snowfall over the entire continent. This results in a dynamic ice loss of up to 1.25 metres in the year 2500 for the strongest warming scenario.

Global stability and pattern formation in a nonlocal diffusive Lotka-Volterra competition model

NASA Astrophysics Data System (ADS)

Ni, Wenjie; Shi, Junping; Wang, Mingxin

2018-06-01

A diffusive Lotka-Volterra competition model with nonlocal intraspecific and interspecific competition between species is formulated and analyzed. The nonlocal competition strength is assumed to be determined by a diffusion kernel function to model the movement pattern of the biological species. It is shown that when there is no nonlocal intraspecific competition, the dynamics properties of nonlocal diffusive competition problem are similar to those of classical diffusive Lotka-Volterra competition model regardless of the strength of nonlocal interspecific competition. Global stability of nonnegative constant equilibria are proved using Lyapunov or upper-lower solution methods. On the other hand, strong nonlocal intraspecific competition increases the system spatiotemporal dynamic complexity. For the weak competition case, the nonlocal diffusive competition model may possess nonconstant positive equilibria for some suitably large nonlocal intraspecific competition coefficients.

The land-ice contribution to 21st-century dynamic sea level rise

NASA Astrophysics Data System (ADS)

Howard, T.; Ridley, J.; Pardaens, A. K.; Hurkmans, R. T. W. L.; Payne, A. J.; Giesen, R. H.; Lowe, J. A.; Bamber, J. L.; Edwards, T. L.; Oerlemans, J.

2014-06-01

Climate change has the potential to influence global mean sea level through a number of processes including (but not limited to) thermal expansion of the oceans and enhanced land ice melt. In addition to their contribution to global mean sea level change, these two processes (among others) lead to local departures from the global mean sea level change, through a number of mechanisms including the effect on spatial variations in the change of water density and transport, usually termed dynamic sea level changes. In this study, we focus on the component of dynamic sea level change that might be given by additional freshwater inflow to the ocean under scenarios of 21st-century land-based ice melt. We present regional patterns of dynamic sea level change given by a global-coupled atmosphere-ocean climate model forced by spatially and temporally varying projected ice-melt fluxes from three sources: the Antarctic ice sheet, the Greenland Ice Sheet and small glaciers and ice caps. The largest ice melt flux we consider is equivalent to almost 0.7 m of global mean sea level rise over the 21st century. The temporal evolution of the dynamic sea level changes, in the presence of considerable variations in the ice melt flux, is also analysed. We find that the dynamic sea level change associated with the ice melt is small, with the largest changes occurring in the North Atlantic amounting to 3 cm above the global mean rise. Furthermore, the dynamic sea level change associated with the ice melt is similar regardless of whether the simulated ice fluxes are applied to a simulation with fixed CO2 or under a business-as-usual greenhouse gas warming scenario of increasing CO2.

The Rise of China in the International Trade Network: A Community Core Detection Approach

PubMed Central

Zhu, Zhen; Cerina, Federica; Chessa, Alessandro; Caldarelli, Guido; Riccaboni, Massimo

2014-01-01

Theory of complex networks proved successful in the description of a variety of complex systems ranging from biology to computer science and to economics and finance. Here we use network models to describe the evolution of a particular economic system, namely the International Trade Network (ITN). Previous studies often assume that globalization and regionalization in international trade are contradictory to each other. We re-examine the relationship between globalization and regionalization by viewing the international trade system as an interdependent complex network. We use the modularity optimization method to detect communities and community cores in the ITN during the years 1995–2011. We find rich dynamics over time both inter- and intra-communities. In particular, the Asia-Oceania community disappeared and reemerged over time along with a switch in leadership from Japan to China. We provide a multilevel description of the evolution of the network where the global dynamics (i.e., communities disappear or reemerge) and the regional dynamics (i.e., community core changes between community members) are related. Moreover, simulation results show that the global dynamics can be generated by a simple dynamic-edge-weight mechanism. PMID:25136895

The rise of China in the International Trade Network: a community core detection approach.

PubMed

Zhu, Zhen; Cerina, Federica; Chessa, Alessandro; Caldarelli, Guido; Riccaboni, Massimo

2014-01-01

Theory of complex networks proved successful in the description of a variety of complex systems ranging from biology to computer science and to economics and finance. Here we use network models to describe the evolution of a particular economic system, namely the International Trade Network (ITN). Previous studies often assume that globalization and regionalization in international trade are contradictory to each other. We re-examine the relationship between globalization and regionalization by viewing the international trade system as an interdependent complex network. We use the modularity optimization method to detect communities and community cores in the ITN during the years 1995-2011. We find rich dynamics over time both inter- and intra-communities. In particular, the Asia-Oceania community disappeared and reemerged over time along with a switch in leadership from Japan to China. We provide a multilevel description of the evolution of the network where the global dynamics (i.e., communities disappear or reemerge) and the regional dynamics (i.e., community core changes between community members) are related. Moreover, simulation results show that the global dynamics can be generated by a simple dynamic-edge-weight mechanism.

The evolution of global disaster risk assessments: from hazard to global change

NASA Astrophysics Data System (ADS)

Peduzzi, Pascal

2013-04-01

The perception of disaster risk as a dynamic process interlinked with global change is a fairly recent concept. It gradually emerged as an evolution from new scientific theories, currents of thinking and lessons learned from large disasters since the 1970s. The interest was further heighten, in the mid-1980s, by the Chernobyl nuclear accident and the discovery of the ozone layer hole, both bringing awareness that dangerous hazards can generate global impacts. The creation of the UN International Decade for Natural Disaster Reduction (IDNDR) and the publication of the first IPCC report in 1990 reinforced the interest for global risk assessment. First global risk models including hazard, exposure and vulnerability components were available since mid-2000s. Since then increased computation power and more refined datasets resolution, led to more numerous and sophisticated global risk models. This article presents a recent history of global disaster risk models, the current status of researches for the Global Assessment Report on Disaster Risk Reduction (GAR 2013) and future challenges and limitations for the development of next generation global disaster risk models.

3D Global Braginskii Simulations of Plasma Dynamics and Turbulence in LAPD

NASA Astrophysics Data System (ADS)

Fisher, Dustin; Rogers, Barrett

2013-10-01

3D global two-fluid simulations are presented in an ongoing effort to identify and understand the plasma dynamics in the Large Plasma Device (LAPD) at UCLA's Basic Science Facility. Modeling is done using a modified version of the Global Braginskii Solver (GBS) that models the plasma from source to edge region on a field-aligned grid using a finite difference method and 4th order Runge-Kutta time stepping. Progress has been made to account for the thermionic cathode emission of fast electrons at the source, the axial dependence of the plasma source, and biasing the front and side walls. Along with trying to understand the effect sheath's and neutrals have in setting the plasma potential, work is being done to model the biasable limiter recently used by colleagues at UCLA to better understand flow shear and particle transport in the LAPD. Comparisons of the zero bias case are presented along with analysis of the growth and dynamics of turbulent structures (such as drift waves) seen in the simulations. Supported through CICART under the auspices of the DOE's EPSCoR Grant No. DE-FG02-10ER46372.

A Program for Solving the Brain Ischemia Problem

PubMed Central

DeGracia, Donald J.

2013-01-01

Our recently described nonlinear dynamical model of cell injury is here applied to the problems of brain ischemia and neuroprotection. We discuss measurement of global brain ischemia injury dynamics by time course analysis. Solutions to proposed experiments are simulated using hypothetical values for the model parameters. The solutions solve the global brain ischemia problem in terms of “master bifurcation diagrams” that show all possible outcomes for arbitrary durations of all lethal cerebral blood flow (CBF) decrements. The global ischemia master bifurcation diagrams: (1) can map to a single focal ischemia insult, and (2) reveal all CBF decrements susceptible to neuroprotection. We simulate measuring a neuroprotectant by time course analysis, which revealed emergent nonlinear effects that set dynamical limits on neuroprotection. Using over-simplified stroke geometry, we calculate a theoretical maximum protection of approximately 50% recovery. We also calculate what is likely to be obtained in practice and obtain 38% recovery; a number close to that often reported in the literature. The hypothetical examples studied here illustrate the use of the nonlinear cell injury model as a fresh avenue of approach that has the potential, not only to solve the brain ischemia problem, but also to advance the technology of neuroprotection. PMID:24961411

Final report for DOE Award # DE- SC0010039*: Carbon dynamics of forest recovery under a changing climate: Forcings, feedbacks, and implications for earth system modeling

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

Anderson-Teixeira, Kristina J.; DeLucia, Evan H.; Duval, Benjamin D.

2015-10-29

To advance understanding of C dynamics of forests globally, we compiled a new database, the Forest C database (ForC-db), which contains data on ground-based measurements of ecosystem-level C stocks and annual fluxes along with disturbance history. This database currently contains 18,791 records from 2009 sites, making it the largest and most comprehensive database of C stocks and flows in forest ecosystems globally. The tropical component of the database will be published in conjunction with a manuscript that is currently under review (Anderson-Teixeira et al., in review). Database development continues, and we hope to maintain a dynamic instance of the entiremore » (global) database.« less

Century long observation constrained global dynamic downscaling and hydrologic implication

NASA Astrophysics Data System (ADS)

Kim, H.; Yoshimura, K.; Chang, E.; Famiglietti, J. S.; Oki, T.

2012-12-01

It has been suggested that greenhouse gas induced warming climate causes the acceleration of large scale hydrologic cycles, and, indeed, many regions on the Earth have been suffered by hydrologic extremes getting more frequent. However, historical observations are not able to provide enough information in comprehensive manner to understand their long-term variability and/or global distributions. In this study, a century long high resolution global climate data is developed in order to break through existing limitations. 20th Century Reanalysis (20CR) which has relatively low spatial resolution (~2.0°) and longer term availability (140 years) is dynamically downscaled into global T248 (~0.5°) resolution using Experimental Climate Prediction Center (ECPC) Global Spectral Model (GSM) by spectral nudging data assimilation technique. Also, Global Precipitation Climatology Centre (GPCC) and Climate Research Unit (CRU) observational data are adopted to reduce model dependent uncertainty. Downscaled product successfully represents realistic geographical detail keeping low frequency signal in mean state and spatiotemporal variability, while previous bias correction method fails to reproduce high frequency variability. Newly developed data is used to investigate how long-term large scale terrestrial hydrologic cycles have been changed globally and how they have been interacted with various climate modes, such as El-Niño Southern Oscillation (ENSO) and Atlantic Multidecadal Oscillation (AMO). As a further application, it will be used to provide atmospheric boundary condition of multiple land surface models in the Global Soil Wetness Project Phase 3 (GSWP3).

Changes in Concurrent Risk of Warm and Dry Years under Impact of Climate Change

NASA Astrophysics Data System (ADS)

Sarhadi, A.; Wiper, M.; Touma, D. E.; Ausín, M. C.; Diffenbaugh, N. S.

2017-12-01

Anthropogenic global warming has changed the nature and the risk of extreme climate phenomena. The changing concurrence of multiple climatic extremes (warm and dry years) may result in intensification of undesirable consequences for water resources, human and ecosystem health, and environmental equity. The present study assesses how global warming influences the probability that warm and dry years co-occur in a global scale. In the first step of the study a designed multivariate Mann-Kendall trend analysis is used to detect the areas in which the concurrence of warm and dry years has increased in the historical climate records and also climate models in the global scale. The next step investigates the concurrent risk of the extremes under dynamic nonstationary conditions. A fully generalized multivariate risk framework is designed to evolve through time under dynamic nonstationary conditions. In this methodology, Bayesian, dynamic copulas are developed to model the time-varying dependence structure between the two different climate extremes (warm and dry years). The results reveal an increasing trend in the concurrence risk of warm and dry years, which are in agreement with the multivariate trend analysis from historical and climate models. In addition to providing a novel quantification of the changing probability of compound extreme events, the results of this study can help decision makers develop short- and long-term strategies to prepare for climate stresses now and in the future.

User Selection Criteria of Airspace Designs in Flexible Airspace Management

NASA Technical Reports Server (NTRS)

Lee, Hwasoo E.; Lee, Paul U.; Jung, Jaewoo; Lai, Chok Fung

2011-01-01

A method for identifying global aerodynamic models from flight data in an efficient manner is explained and demonstrated. A novel experiment design technique was used to obtain dynamic flight data over a range of flight conditions with a single flight maneuver. Multivariate polynomials and polynomial splines were used with orthogonalization techniques and statistical modeling metrics to synthesize global nonlinear aerodynamic models directly and completely from flight data alone. Simulation data and flight data from a subscale twin-engine jet transport aircraft were used to demonstrate the techniques. Results showed that global multivariate nonlinear aerodynamic dependencies could be accurately identified using flight data from a single maneuver. Flight-derived global aerodynamic model structures, model parameter estimates, and associated uncertainties were provided for all six nondimensional force and moment coefficients for the test aircraft. These models were combined with a propulsion model identified from engine ground test data to produce a high-fidelity nonlinear flight simulation very efficiently. Prediction testing using a multi-axis maneuver showed that the identified global model accurately predicted aircraft responses.

A Thermodynamic Approach to Soil-Plant-Atmosphere Modeling: From Metabolic Biochemical Processes to Water-Carbon-Nitrogen Balance

NASA Astrophysics Data System (ADS)

Clavijo, H. W.

2016-12-01

Modeling the soil-plant-atmosphere continuum has been central part of understanding interrelationships among biogeochemical and hydrological processes. Theory behind of couplings Land Surface Models (LSM) and Dynamical Global Vegetation Models (DGVM) are based on physical and physiological processes connected by input-output interactions mainly. This modeling framework could be improved by the application of non-equilibrium thermodynamic basis that could encompass the majority of biophysical processes in a standard fashion. This study presents an alternative model for plant-water-atmosphere based on energy-mass thermodynamics. The system of dynamic equations derived is based on the total entropy, the total energy balance for the plant, the biomass dynamics at metabolic level and the water-carbon-nitrogen fluxes and balances. One advantage of this formulation is the capability to describe adaptation and evolution of dynamics of plant as a bio-system coupled to the environment. Second, it opens a window for applications on specific conditions from individual plant scale, to watershed scale, to global scale. Third, it enhances the possibility of analyzing anthropogenic impacts on the system, benefiting from the mathematical formulation and its non-linearity. This non-linear model formulation is analyzed under the concepts of qualitative system dynamics theory, for different state-space phase portraits. The attractors and sources are pointed out with its stability analysis. Possibility of bifurcations are explored and reported. Simulations for the system dynamics under different conditions are presented. These results show strong consistency and applicability that validates the use of the non-equilibrium thermodynamic theory.

Differential equation models for sharp threshold dynamics.

PubMed

Schramm, Harrison C; Dimitrov, Nedialko B

2014-01-01

We develop an extension to differential equation models of dynamical systems to allow us to analyze probabilistic threshold dynamics that fundamentally and globally change system behavior. We apply our novel modeling approach to two cases of interest: a model of infectious disease modified for malware where a detection event drastically changes dynamics by introducing a new class in competition with the original infection; and the Lanchester model of armed conflict, where the loss of a key capability drastically changes the effectiveness of one of the sides. We derive and demonstrate a step-by-step, repeatable method for applying our novel modeling approach to an arbitrary system, and we compare the resulting differential equations to simulations of the system's random progression. Our work leads to a simple and easily implemented method for analyzing probabilistic threshold dynamics using differential equations. Published by Elsevier Inc.

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.

Applied Dynamic Analysis of the Global Economy (ADAGE)

EPA Science Inventory

ADAGE is a dynamic computable general equilibrium (CGE) model capable of examining many types of economic, energy, environmental, climate change mitigation, and trade policies at the international, national, U.S. regional, and U.S. state levels. To investigate proposed policy eff...

Compound simulation of fluvial floods and storm surges in a global coupled river-coast flood model: Model development and its application to 2007 Cyclone Sidr in Bangladesh

NASA Astrophysics Data System (ADS)

Ikeuchi, Hiroaki; Hirabayashi, Yukiko; Yamazaki, Dai; Muis, Sanne; Ward, Philip J.; Winsemius, Hessel C.; Verlaan, Martin; Kanae, Shinjiro

2017-08-01

Water-related disasters, such as fluvial floods and cyclonic storm surges, are a major concern in the world's mega-delta regions. Furthermore, the simultaneous occurrence of extreme discharges from rivers and storm surges could exacerbate flood risk, compared to when they occur separately. Hence, it is of great importance to assess the compound risks of fluvial and coastal floods at a large scale, including mega-deltas. However, most studies on compound fluvial and coastal flooding have been limited to relatively small scales, and global-scale or large-scale studies have not yet addressed both of them. The objectives of this study are twofold: to develop a global coupled river-coast flood model; and to conduct a simulation of compound fluvial flooding and storm surges in Asian mega-delta regions. A state-of-the-art global river routing model was modified to represent the influence of dynamic sea surface levels on river discharges and water levels. We conducted the experiments by coupling a river model with a global tide and surge reanalysis data set. Results show that water levels in deltas and estuaries are greatly affected by the interaction between river discharge, ocean tides and storm surges. The effects of storm surges on fluvial flooding are further examined from a regional perspective, focusing on the case of Cyclone Sidr in the Ganges-Brahmaputra-Meghna Delta in 2007. Modeled results demonstrate that a >3 m storm surge propagated more than 200 km inland along rivers. We show that the performance of global river routing models can be improved by including sea level dynamics.

Geodynamics Branch research report, 1982

NASA Technical Reports Server (NTRS)

Kahn, W. D. (Editor); Cohen, S. C. (Editor)

1983-01-01

The research program of the Geodynamics Branch is summarized. The research activities cover a broad spectrum of geoscience disciplines including space geodesy, geopotential field modeling, tectonophysics, and dynamic oceanography. The NASA programs which are supported by the work described include the Geodynamics and Ocean Programs, the Crustal Dynamics Project, the proposed Ocean Topography Experiment (TOPEX) and Geopotential Research Mission. The individual papers are grouped into chapters on Crustal Movements, Global Earth Dynamics, Gravity Field Model Development, Sea Surface Topography, and Advanced Studies.

Magnetospheric Substorm Evolution in the Magnetotail: Challenge to Global MHD Modeling.

NASA Astrophysics Data System (ADS)

Kuznetsova, M. M.; Hesse, M.; Dorelli, J.; Rastaetter, L.

2003-12-01

Testing the ability of global MHD models to describe magnetotail evolution during substroms is one of the elements of science based validation efforts at CCMC. We perform simulations of magnetotail dynamics using global MHD models residing at CCMC. We select solar wind conditions which drive the accumulation of magnetic field in the tail lobes and subsequent magnetic reconnection and energy release. We will analyze the effects of spatial resolution in the plasma sheet on modeled expansion phase evolution, maximum energy stored in the tail, and details of magnetotail reconnection. We will pay special attention to current sheet thinning and multiple plasmoid formation.

Multi-water-bag models of ion temperature gradient instability in cylindrical geometry

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

Coulette, David; Besse, Nicolas

2013-05-15

Ion temperature gradient instabilities play a major role in the understanding of anomalous transport in core fusion plasmas. In the considered cylindrical geometry, ion dynamics is described using a drift-kinetic multi-water-bag model for the parallel velocity dependency of the ion distribution function. In a first stage, global linear stability analysis is performed. From the obtained normal modes, parametric dependencies of the main spectral characteristics of the instability are then examined. Comparison of the multi-water-bag results with a reference continuous Maxwellian case allows us to evaluate the effects of discrete parallel velocity sampling induced by the Multi-Water-Bag model. Differences between themore » global model and local models considered in previous works are discussed. Using results from linear, quasilinear, and nonlinear numerical simulations, an analysis of the first stage saturation dynamics of the instability is proposed, where the divergence between the three models is examined.« less

Sensitivity of burned area in Europe to climate change, atmospheric CO2 levels, and demography: A comparison of two fire-vegetation models

NASA Astrophysics Data System (ADS)

Wu, Minchao; Knorr, Wolfgang; Thonicke, Kirsten; Schurgers, Guy; Camia, Andrea; Arneth, Almut

2015-11-01

Global environmental changes and human activity influence wildland fires worldwide, but the relative importance of the individual factors varies regionally and their interplay can be difficult to disentangle. Here we evaluate projected future changes in burned area at the European and sub-European scale, and we investigate uncertainties in the relative importance of the determining factors. We simulated future burned area with LPJ-GUESS-SIMFIRE, a patch-dynamic global vegetation model with a semiempirical fire model, and LPJmL-SPITFIRE, a dynamic global vegetation model with a process-based fire model. Applying a range of future projections that combine different scenarios for climate changes, enhanced CO2 concentrations, and population growth, we investigated the individual and combined effects of these drivers on the total area and regions affected by fire in the 21st century. The two models differed notably with respect to the dominating drivers and underlying processes. Fire-vegetation interactions and socioeconomic effects emerged as important uncertainties for future burned area in some European regions. Burned area of eastern Europe increased in both models, pointing at an emerging new fire-prone region that should gain further attention for future fire management.

Deconstructing spatiotemporal chaos using local symbolic dynamics.

PubMed

Pethel, Shawn D; Corron, Ned J; Bollt, Erik

2007-11-23

We find that the global symbolic dynamics of a diffusively coupled map lattice is well approximated by a very small local model for weak to moderate coupling strengths. A local symbolic model is a truncation of the full symbolic model to one that considers only a single element and a few neighbors. Using interval analysis, we give rigorous results for a range of coupling strengths and different local model widths. Examples are presented of extracting a local symbolic model from data and of controlling spatiotemporal chaos.

Inferring Dynamics from the Wavenumber Spectra of an Eddying Global Ocean Model with Embedded Tides

DTIC Science & Technology

2012-12-12

MODEL WAVENUMBER SPECTRA (12(112 Ocean Model (HYCOM) [Chassignet et al., 2007 ; Metzger et al., 2010] with 1/12.5° (approximately 9 km) equatorial...Chassignet, E. P., H. E. Ilurlburt. O. M. Smedstad, G. R. Halliwcll, P. J. Hogan, A. J. Wallcraft, R. Baraille. and R. Bleck ( 2007 ), The HYCOM (HYbrid...tide models, J. Geophys. Res., 102, 25,173 25,194, doi:10.1029/97JC00445. Stammer , D. (1997), Global characteristics of ocean variability estimated

Investigating EMIC Wave Dynamics with RAM-SCB-E

NASA Astrophysics Data System (ADS)

Jordanova, V. K.; Fu, X.; Henderson, M. G.; Morley, S.; Welling, D. T.; Yu, Y.

2017-12-01

The distribution of ring current ions and electrons in the inner magnetosphere depends strongly on their transport in realistic electric (E) and magnetic (B) fields and concurrent energization or loss. To investigate the high variability of energetic particle (H+, He+, O+, and electron) fluxes during storms selected by the GEM Surface Charging Challenge, we use our kinetic ring current model (RAM) two-way coupled with a 3-D magnetic field code (SCB). This model was just extended to include electric field calculations, making it a unique, fully self-consistent, anisotropic ring current-atmosphere interactions model, RAM-SCB-E. Recently we investigated electromagnetic ion cyclotron (EMIC) instability in a local plasma using both linear theory and nonlinear hybrid simulations and derived a scaling formula that relates the saturation EMIC wave amplitude to initial plasma conditions. Global dynamic EMIC wave maps obtained with our RAM-SCB-E model using this scaling will be presented and compared with statistical models. These plasma waves can affect significantly both ion and electron precipitation into the atmosphere and the subsequent patterns of ionospheric conductance, as well as the global ring current dynamics.

A Global Picture of the Gamma-Ricker Map: A Flexible Discrete-Time Model with Factors of Positive and Negative Density Dependence.

PubMed

Liz, Eduardo

2018-02-01

The gamma-Ricker model is one of the more flexible and general discrete-time population models. It is defined on the basis of the Ricker model, introducing an additional parameter [Formula: see text]. For some values of this parameter ([Formula: see text], population is overcompensatory, and the introduction of an additional parameter gives more flexibility to fit the stock-recruitment curve to field data. For other parameter values ([Formula: see text]), the gamma-Ricker model represents populations whose per-capita growth rate combines both negative density dependence and positive density dependence. The former can lead to overcompensation and dynamic instability, and the latter can lead to a strong Allee effect. We study the impact of the cooperation factor in the dynamics and provide rigorous conditions under which increasing the Allee effect strength stabilizes or destabilizes population dynamics, promotes or prevents population extinction, and increases or decreases population size. Our theoretical results also include new global stability criteria and a description of the possible bifurcations.

Technical report series on global modeling and data assimilation. Volume 5: Documentation of the AIRES/GEOS dynamical core, version 2

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); Takacs, Lawrence L.

1995-01-01

A detailed description of the numerical formulation of Version 2 of the ARIES/GEOS 'dynamical core' is presented. This code is a nearly 'plug-compatible' dynamics for use in atmospheric general circulation models (GCMs). It is a finite difference model on a staggered latitude-longitude C-grid. It uses second-order differences for all terms except the advection of vorticity by the rotation part of the flow, which is done at fourth-order accuracy. This dynamical core is currently being used in the climate (ARIES) and data assimilation (GEOS) GCMs at Goddard.

Modeling Dissolved Organic Carbon (DOC) Dynamics in Flooded Wetlands

EPA Science Inventory

Wetlands play an important role in the global carbon cycle and are recognized for their considerable potential to sequester carbon. Wetlands contain the largest component (18-30%) of the terrestrial carbon pool and are responsible for about a quarter of the global methane emissi...

Situation Model Updating in Young and Older Adults: Global versus Incremental Mechanisms

PubMed Central

Bailey, Heather R.; Zacks, Jeffrey M.

2015-01-01

Readers construct mental models of situations described by text. Activity in narrative text is dynamic, so readers must frequently update their situation models when dimensions of the situation change. Updating can be incremental, such that a change leads to updating just the dimension that changed, or global, such that the entire model is updated. Here, we asked whether older and young adults make differential use of incremental and global updating. Participants read narratives containing changes in characters and spatial location and responded to recognition probes throughout the texts. Responses were slower when probes followed a change, suggesting that situation models were updated at changes. When either dimension changed, responses to probes for both dimensions were slowed; this provides evidence for global updating. Moreover, older adults showed stronger evidence of global updating than did young adults. One possibility is that older adults perform more global updating to offset reduced ability to manipulate information in working memory. PMID:25938248

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

NASA Astrophysics Data System (ADS)

He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, Anthony D.; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong

2015-12-01

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr-1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil RH with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

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

He, Yujie; Yang, Jinyan; Zhuang, Qianlai

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here in this study we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbialmore » dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO 2 efflux (R H) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil R H (7.5 ± 2.4 PgCyr -1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil R H with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.« less

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

USGS Publications Warehouse

He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, A. David; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong

2015-01-01

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr−1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4–0.6) in the simulated spatial pattern of soil RHwith both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = −0.43 to −0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

Modeling of Global BEAM Structure for Evaluation of MMOD Impacts to Support Development of a Health Monitoring System

NASA Technical Reports Server (NTRS)

Lyle, Karen H.; Vassilakos, Gregory J.

2015-01-01

This report summarizes the initial modeling of the global response of the Bigelow Expandable Activity Module (BEAM) to micrometeorite and orbital debris(MMOD) impacts using a structural, nonlinear, transient dynamic, finite element code. These models complement the on-orbit deployment of the Distributed Impact Detection System (DIDS) to support structural health monitoring studies. Two global models were developed. The first focused exclusively on impacts on the soft-goods (fabric-envelop) portion of BEAM. The second incorporates the bulkhead to support understanding of bulkhead impacts. These models were exercised for random impact locations and responses monitored at the on-orbit sensor locations. The report concludes with areas for future study.

Chaos in plasma simulation and experiment

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

Watts, C.; Newman, D.E.; Sprott, J.C.

1993-09-01

We investigate the possibility that chaos and simple determinism are governing the dynamics of reversed field pinch (RFP) plasmas using data from both numerical simulations and experiment. A large repertoire of nonlinear analysis techniques is used to identify low dimensional chaos. These tools include phase portraits and Poincard sections, correlation dimension, the spectrum of Lyapunov exponents and short term predictability. In addition, nonlinear noise reduction techniques are applied to the experimental data in an attempt to extract any underlying deterministic dynamics. Two model systems are used to simulate the plasma dynamics. These are -the DEBS code, which models global RFPmore » dynamics, and the dissipative trapped electron mode (DTEM) model, which models drift wave turbulence. Data from both simulations show strong indications of low,dimensional chaos and simple determinism. Experimental data were obtained from the Madison Symmetric Torus RFP and consist of a wide array of both global and local diagnostic signals. None of the signals shows any indication of low dimensional chaos or other simple determinism. Moreover, most of the analysis tools indicate the experimental system is very high dimensional with properties similar to noise. Nonlinear noise reduction is unsuccessful at extracting an underlying deterministic system.« less

Can Dynamic Global Vegetation Models Reproduce Satellite Observed Extreme Browning and Greening Events in Vegetation Productivity?

NASA Astrophysics Data System (ADS)

van Eck, C. M.; Morfopoulos, C.; Betts, R. A.; Chang, J.; Ciais, P.; Friedlingstein, P.; Regnier, P. A. G.

2016-12-01

The frequency and severity of extreme climate events such as droughts, extreme precipitation and heatwaves are expected to increase in our changing climate. These extreme climate events will have an effect on vegetation either by enhanced or reduced productivity. Subsequently, this can have a substantial impact on the terrestrial carbon sink and thus the global carbon cycle, especially as extreme climate events are expected to increase in frequency and severity. Connecting observational datasets with modelling studies provides new insights into these climate-vegetation interactions. This study aims to compare extremes in vegetation productivity as derived from observations with that of Dynamic Global Vegetation Models (DGVMs). In this case GIMMS-NDVI 3g is selected as the observational dataset and both JULES (Joint UK Land Environment Simulator) and ORCHIDEE (Organising Carbon and Hydrology In Dynamic Ecosystems) as the DGVMs. Both models are forced with PGFv2 Global Meteorological Forcing Dataset according to the ISI-MIP2 protocol for historical runs. Extremes in vegetation productivity are the focal point, which are identified as NDVI anomalies below the 10th percentile or above the 90th percentile during the growing season, referred to as browning or greening events respectively. The monthly NDVI dataset GIMMS-NDVI 3g is used to obtain the location in time and space of the vegetation extremes. The global GIMMS-NDVI 3g dataset has been subdivided into IPCC's SREX-regions for which the NDVI anomalies are calculated and the extreme thresholds are determined. With this information we can identify the location in time and space of the browning and greening events in remotely-sensed vegetation productivity. The same procedure is applied to the modelled Gross Primary Productivity (GPP) allowing a comparison between the spatial and temporal occurrence of the browning and greening events in the observational dataset and the models' output. The capacity of the models to catch observed extremes in vegetation productivity is assessed and compared. Factors contributing to observed and modelled vegetation browning/greening extremes are analysed. The results of this study provide a stepping stone to modelling future extremes in vegetation productivity.

Dynamics of the stochastic low concentration trimolecular oscillatory chemical system with jumps

NASA Astrophysics Data System (ADS)

Wei, Yongchang; Yang, Qigui

2018-06-01

This paper is devoted to discern long time dynamics through the stochastic low concentration trimolecular oscillatory chemical system with jumps. By Lyapunov technique, this system is proved to have a unique global positive solution, and the asymptotic stability in mean square of such model is further established. Moreover, the existence of random attractor and Lyapunov exponents are obtained for the stochastic homeomorphism flow generated by the corresponding global positive solution. And some numerical simulations are given to illustrate the presented results.

Terminator field-aligned current system: A new finding from model-assimilated data set (MADS)

NASA Astrophysics Data System (ADS)

Zhu, L.; Schunk, R. W.; Scherliess, L.; Sojka, J. J.; Gardner, L. C.; Eccles, J. V.; Rice, D.

2013-12-01

Physics-based data assimilation models have been recognized by the space science community as the most accurate approach to specify and forecast the space weather of the solar-terrestrial environment. The model-assimilated data sets (MADS) produced by these models constitute an internally consistent time series of global three-dimensional fields whose accuracy can be estimated. Because of its internal consistency of physics and completeness of descriptions on the status of global systems, the MADS has also been a powerful tool to identify the systematic errors in measurements, reveal the missing physics in physical models, and discover the important dynamical physical processes that are inadequately observed or missed by measurements due to observational limitations. In the past years, we developed a data assimilation model for the high-latitude ionospheric plasma dynamics and electrodynamics. With a set of physical models, an ensemble Kalman filter, and the ingestion of data from multiple observations, the data assimilation model can produce a self-consistent time-series of the complete descriptions of the global high-latitude ionosphere, which includes the convection electric field, horizontal and field-aligned currents, conductivity, as well as 3-D plasma densities and temperatures, In this presentation, we will show a new field-aligned current system discovered from the analysis of the MADS produced by our data assimilation model. This new current system appears and develops near the ionospheric terminator. The dynamical features of this current system will be described and its connection to the active role of the ionosphere in the M-I coupling will be discussed.

Switch of Sensitivity Dynamics Revealed with DyGloSA Toolbox for Dynamical Global Sensitivity Analysis as an Early Warning for System's Critical Transition

PubMed Central

Baumuratova, Tatiana; Dobre, Simona; Bastogne, Thierry; Sauter, Thomas

2013-01-01

Systems with bifurcations may experience abrupt irreversible and often unwanted shifts in their performance, called critical transitions. For many systems like climate, economy, ecosystems it is highly desirable to identify indicators serving as early warnings of such regime shifts. Several statistical measures were recently proposed as early warnings of critical transitions including increased variance, autocorrelation and skewness of experimental or model-generated data. The lack of automatized tool for model-based prediction of critical transitions led to designing DyGloSA – a MATLAB toolbox for dynamical global parameter sensitivity analysis (GPSA) of ordinary differential equations models. We suggest that the switch in dynamics of parameter sensitivities revealed by our toolbox is an early warning that a system is approaching a critical transition. We illustrate the efficiency of our toolbox by analyzing several models with bifurcations and predicting the time periods when systems can still avoid going to a critical transition by manipulating certain parameter values, which is not detectable with the existing SA techniques. DyGloSA is based on the SBToolbox2 and contains functions, which compute dynamically the global sensitivity indices of the system by applying four main GPSA methods: eFAST, Sobol's ANOVA, PRCC and WALS. It includes parallelized versions of the functions enabling significant reduction of the computational time (up to 12 times). DyGloSA is freely available as a set of MATLAB scripts at http://bio.uni.lu/systems_biology/software/dyglosa. It requires installation of MATLAB (versions R2008b or later) and the Systems Biology Toolbox2 available at www.sbtoolbox2.org. DyGloSA can be run on Windows and Linux systems, -32 and -64 bits. PMID:24367574

Switch of sensitivity dynamics revealed with DyGloSA toolbox for dynamical global sensitivity analysis as an early warning for system's critical transition.

PubMed

Baumuratova, Tatiana; Dobre, Simona; Bastogne, Thierry; Sauter, Thomas

2013-01-01

Systems with bifurcations may experience abrupt irreversible and often unwanted shifts in their performance, called critical transitions. For many systems like climate, economy, ecosystems it is highly desirable to identify indicators serving as early warnings of such regime shifts. Several statistical measures were recently proposed as early warnings of critical transitions including increased variance, autocorrelation and skewness of experimental or model-generated data. The lack of automatized tool for model-based prediction of critical transitions led to designing DyGloSA - a MATLAB toolbox for dynamical global parameter sensitivity analysis (GPSA) of ordinary differential equations models. We suggest that the switch in dynamics of parameter sensitivities revealed by our toolbox is an early warning that a system is approaching a critical transition. We illustrate the efficiency of our toolbox by analyzing several models with bifurcations and predicting the time periods when systems can still avoid going to a critical transition by manipulating certain parameter values, which is not detectable with the existing SA techniques. DyGloSA is based on the SBToolbox2 and contains functions, which compute dynamically the global sensitivity indices of the system by applying four main GPSA methods: eFAST, Sobol's ANOVA, PRCC and WALS. It includes parallelized versions of the functions enabling significant reduction of the computational time (up to 12 times). DyGloSA is freely available as a set of MATLAB scripts at http://bio.uni.lu/systems_biology/software/dyglosa. It requires installation of MATLAB (versions R2008b or later) and the Systems Biology Toolbox2 available at www.sbtoolbox2.org. DyGloSA can be run on Windows and Linux systems, -32 and -64 bits.

Chapman Conference on the Hydrologic Aspects of Global Climate Change, Lake Chelan, WA, June 12-14, 1990, Selected Papers

NASA Technical Reports Server (NTRS)

Lettenmaier, Dennis P. (Editor); Rind, D. (Editor)

1992-01-01

The present conference on the hydrological aspects of global climate change discusses land-surface schemes for future climate models, modeling of the land-surface boundary in climate models as a composite of independent vegetation, a land-surface hydrology parameterizaton with subgrid variability for general circulation models, and conceptual aspects of a statistical-dynamical approach to represent landscape subgrid-scale heterogeneities in atmospheric models. Attention is given to the impact of global warming on river runoff, the influence of atmospheric moisture transport on the fresh water balance of the Atlantic drainage basin, a comparison of observations and model simulations of tropospheric water vapor, and the use of weather types to disaggregate the prediction of general circulation models. Topics addressed include the potential response of an Arctic watershed during a period of global warming and the sensitivity of groundwater recharge estimates to climate variability and change.

Using a Coupled Lake Model with WRF for Dynamical Downscaling

EPA Science Inventory

The Weather Research and Forecasting (WRF) model is used to downscale a coarse reanalysis (National Centers for Environmental Prediction–Department of Energy Atmospheric Model Intercomparison Project reanalysis, hereafter R2) as a proxy for a global climate model (GCM) to examine...

Effect of global climate on termites population. Effect of termites population on global climate

NASA Astrophysics Data System (ADS)

Sapunov, Valentin

2010-05-01

The global climate is under control of factors having both earth and space origin. Global warming took place from XVII century till 1997. Then global cold snap began. This dynamics had effect on global distribution of some animals including termites. Direct human effect on climate is not significant. At the same time man plays role of trigger switching on significant biosphere processes controlling climate. The transformation of marginal lands, development of industry and building, stimulated increase of termite niche and population. Termite role in green house gases production increases too. It may have regular effect on world climate. The dry wood is substrate for metabolism of termites living under symbiosis with bacteria Hypermastigina (Flagellata). The use of dry wood by humanity increased from 18 *108 ton in XVIII to 9*109 to the middle of XX century. Then use of wood decreased because of a new technology development. Hence termite population is controlled by microevolution depending on dry wood and climate dynamics. Producing by them green house gases had reciprocal effect on world climate. It is possible to describe and predict dynamic of termite population using methods of mathematical ecology and analogs with other well studied insects (Colorado potatoes beetle, Chrisomelid beetle Zygogramma and so on). Reclamation of new ecological niche for such insects as termites needs 70 - 75 years. That is delay of population dynamics in relation to dynamics of dry wood production. General principles of population growth were described by G.Gause (1934) and some authors of the end of XX century. This works and analogs with other insects suggest model of termite distribution during XXI century. The extremum of population and its green house gases production would be gotten during 8 - 10 years. Then the number of specimens and sum biological mass would be stabilized and decreased. Termite gas production is not priority for climate regulation, but it has importance as fine regulator of global temperature and climate stability. Key words: termites, green house gases, mathematical modeling. Union symposia Biogeoscience BG2.1

DREAM: An Integrated Space Radiation Nowcast System for Natural and Nuclear Radiation Belts

DTIC Science & Technology

2011-09-01

requires a model of the global geomagnetic field which is represented by the red module in figure 1. The simplest assumption of a tilted dipole field...is grossly inadequate to describe the distorted, dynamic geomagnetic field. Stretching and compression of the field changes the both the local field... geomagnetic field ranging from static models like [Olsen and Pfitzer, 1974] to global MHD models. We believe the best results can be obtained with a

Topographic asymmetry of the South Atlantic from global models of mantle flow and lithospheric stretching

NASA Astrophysics Data System (ADS)

Flament, Nicolas; Gurnis, Michael; Williams, Simon; Seton, Maria; Skogseid, Jakob; Heine, Christian; Dietmar Müller, R.

2014-02-01

The relief of the South Atlantic is characterized by elevated passive continental margins along southern Africa and eastern Brazil, and by the bathymetric asymmetry of the southern oceanic basin where the western flank is much deeper than the eastern flank. We investigate the origin of these topographic features in the present and over time since the Jurassic with a model of global mantle flow and lithospheric deformation. The model progressively assimilates plate kinematics, plate boundaries and lithospheric age derived from global tectonic reconstructions with deforming plates, and predicts the evolution of mantle temperature, continental crustal thickness, long-wavelength dynamic topography, and isostatic topography. Mantle viscosity and the kinematics of the opening of the South Atlantic are adjustable parameters in thirteen model cases. Model predictions are compared to observables both for the present-day and in the past. Present-day predictions are compared to topography, mantle tomography, and an estimate of residual topography. Predictions for the past are compared to tectonic subsidence from backstripped borehole data along the South American passive margin, and to dynamic uplift as constrained by thermochronology in southern Africa. Comparison between model predictions and observations suggests that the first-order features of the topography of the South Atlantic are due to long-wavelength dynamic topography, rather than to asthenospheric processes. The uplift of southern Africa is best reproduced with a lower mantle that is at least 40 times more viscous than the upper mantle.

Topographic asymmetry of the South Atlantic from global models of mantle flow and lithospheric stretching

NASA Astrophysics Data System (ADS)

Flament, Nicolas; Gurnis, Michael; Williams, Simon; Seton, Maria; Skogseid, Jakob; Heine, Christian; Müller, Dietmar

2014-05-01

The relief of the South Atlantic is characterized by elevated passive continental margins along southern Africa and eastern Brazil, and by the bathymetric asymmetry of the southern oceanic basin where the western flank is much deeper than the eastern flank. We investigate the origin of these topographic features in the present and over time since the Jurassic with a model of global mantle flow and lithospheric deformation. The model progressively assimilates plate kinematics, plate boundaries and lithospheric age derived from global tectonic reconstructions with deforming plates, and predicts the evolution of mantle temperature, continental crustal thickness, long-wavelength dynamic topography, and isostatic topography. Mantle viscosity and the kinematics of the opening of the South Atlantic are adjustable parameters in multiple model cases. Model predictions are compared to observables both for the present-day and in the past. Present-day predictions are compared to topography, mantle tomography, and an estimate of residual topography. Predictions for the past are compared to tectonic subsidence from backstripped borehole data along the South American passive margin, and to dynamic uplift as constrained by thermochronology in southern Africa. Comparison between model predictions and observations suggests that the first-order features of the topography of the South Atlantic are due to long-wavelength dynamic topography, rather than to asthenospheric processes. We find the uplift of southern Africa to be best reproduced with a lower mantle that is at least 40 times more viscous than the upper mantle.

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.

Symmetry analysis for hyperbolic equilibria using a TB/dengue fever model

NASA Astrophysics Data System (ADS)

Massoukou, R. Y. M.'Pika; Govinder, K. S.

2016-08-01

We investigate the interplay between Lie symmetry analysis and dynamical systems analysis. As an example, we take a toy model describing the spread of TB and dengue fever. We first undertake a comprehensive dynamical systems analysis including a discussion about local stability. For those regions in which such analyzes cannot be translated to global behavior, we undertake a Lie symmetry analysis. It is shown that the Lie analysis can be useful in providing information for systems where the (local) dynamical systems analysis breaks down.

Improving global paleogeographic reconstructions since the Devonian using paleobiology

NASA Astrophysics Data System (ADS)

Cao, Wenchao; Zahirovic, Sabin; Williams, Simon; Flament, Nicolas; Müller, Dietmar

2017-04-01

Paleogeographic reconstructions are important to understand past eustatic and regional sea level change, the tectonic evolution of the planet, hydrocarbon genesis, and to constrain and interpret the dynamic topography predicted by time-dependent global mantle convection models. Several global paleogeographic compilations have been published, generally presented as static snapshots with varying temporal resolution and fixed spatial resolution. Published paleogeographic compilations are tied to a particular plate motion model, making it difficult to link them to alternative digital plate tectonic reconstructions. In order to address this issue, we developed a workflow to reverse-engineer reconstructed paleogeographies to their present-day coordinates and link them to any reconstruction model. Published paleogeographic compilations are also tied to a given dataset. We used fossil data from the Paleobiology Database to identify inconsistencies between fossils paleoenvironments and paleogeographic reconstructions, and to improve reconstructed terrestrial-marine boundaries by resolving these inconsistencies. We used the improved reconstructed paleogeographies to estimate the surface areas of global paleogeographic features (shallow marine environments, landmasses, mountains and ice sheets), to investigate the global continental flooding history since the late Paleozoic, which has inherent links to global eustasy as well as dynamic topography. Finally, we discuss the relationships between our modeled emerged land area and total continental area through time, continental growth models, and strontium isotope (87Sr/86Sr) signatures in ocean water. Our study highlights the flexibility of digital paleogeographic models linked to state-of-the-art plate tectonic reconstructions in order to better understand the interplay of continental growth and eustasy, with wider implications for understanding Earth's paleotopography, ocean circulation, and the role of mantle convection in shaping long-wavelength topography.

Backward Bifurcation in a Cholera Model: A Case Study of Outbreak in Zimbabwe and Haiti

NASA Astrophysics Data System (ADS)

Sharma, Sandeep; Kumari, Nitu

In this paper, a nonlinear deterministic model is proposed with a saturated treatment function. The expression of the basic reproduction number for the proposed model was obtained. The global dynamics of the proposed model was studied using the basic reproduction number and theory of dynamical systems. It is observed that proposed model exhibits backward bifurcation as multiple endemic equilibrium points exist when R0 < 1. The existence of backward bifurcation implies that making R0 < 1 is not enough for disease eradication. This, in turn, makes it difficult to control the spread of cholera in the community. We also obtain a unique endemic equilibria when R0 > 1. The global stability of unique endemic equilibria is performed using the geometric approach. An extensive numerical study is performed to support our analytical results. Finally, we investigate two major cholera outbreaks, Zimbabwe (2008-09) and Haiti (2010), with the help of the present study.

Long-term dynamic modeling of tethered spacecraft using nodal position finite element method and symplectic integration

NASA Astrophysics Data System (ADS)

Li, G. Q.; Zhu, Z. H.

2015-12-01

Dynamic modeling of tethered spacecraft with the consideration of elasticity of tether is prone to the numerical instability and error accumulation over long-term numerical integration. This paper addresses the challenges by proposing a globally stable numerical approach with the nodal position finite element method (NPFEM) and the implicit, symplectic, 2-stage and 4th order Gaussian-Legendre Runge-Kutta time integration. The NPFEM eliminates the numerical error accumulation by using the position instead of displacement of tether as the state variable, while the symplectic integration enforces the energy and momentum conservation of the discretized finite element model to ensure the global stability of numerical solution. The effectiveness and robustness of the proposed approach is assessed by an elastic pendulum problem, whose dynamic response resembles that of tethered spacecraft, in comparison with the commonly used time integrators such as the classical 4th order Runge-Kutta schemes and other families of non-symplectic Runge-Kutta schemes. Numerical results show that the proposed approach is accurate and the energy of the corresponding numerical model is conservative over the long-term numerical integration. Finally, the proposed approach is applied to the dynamic modeling of deorbiting process of tethered spacecraft over a long period.

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.

Crossfit analysis: a novel method to characterize the dynamics of induced plant responses.

PubMed

Jansen, Jeroen J; van Dam, Nicole M; Hoefsloot, Huub C J; Smilde, Age K

2009-12-16

Many plant species show induced responses that protect them against exogenous attacks. These responses involve the production of many different bioactive compounds. Plant species belonging to the Brassicaceae family produce defensive glucosinolates, which may greatly influence their favorable nutritional properties for humans. Each responding compound may have its own dynamic profile and metabolic relationships with other compounds. The chemical background of the induced response is therefore highly complex and may therefore not reveal all the properties of the response in any single model. This study therefore aims to describe the dynamics of the glucosinolate response, measured at three time points after induction in a feral Brassica, by a three-faceted approach, based on Principal Component Analysis. First the large-scale aspects of the response are described in a 'global model' and then each time-point in the experiment is individually described in 'local models' that focus on phenomena that occur at specific moments in time. Although each local model describes the variation among the plants at one time-point as well as possible, the response dynamics are lost. Therefore a novel method called the 'Crossfit' is described that links the local models of different time-points to each other. Each element of the described analysis approach reveals different aspects of the response. The crossfit shows that smaller dynamic changes may occur in the response that are overlooked by global models, as illustrated by the analysis of a metabolic profiling dataset of the same samples.

Crossfit analysis: a novel method to characterize the dynamics of induced plant responses

PubMed Central

2009-01-01

Background Many plant species show induced responses that protect them against exogenous attacks. These responses involve the production of many different bioactive compounds. Plant species belonging to the Brassicaceae family produce defensive glucosinolates, which may greatly influence their favorable nutritional properties for humans. Each responding compound may have its own dynamic profile and metabolic relationships with other compounds. The chemical background of the induced response is therefore highly complex and may therefore not reveal all the properties of the response in any single model. Results This study therefore aims to describe the dynamics of the glucosinolate response, measured at three time points after induction in a feral Brassica, by a three-faceted approach, based on Principal Component Analysis. First the large-scale aspects of the response are described in a 'global model' and then each time-point in the experiment is individually described in 'local models' that focus on phenomena that occur at specific moments in time. Although each local model describes the variation among the plants at one time-point as well as possible, the response dynamics are lost. Therefore a novel method called the 'Crossfit' is described that links the local models of different time-points to each other. Conclusions Each element of the described analysis approach reveals different aspects of the response. The crossfit shows that smaller dynamic changes may occur in the response that are overlooked by global models, as illustrated by the analysis of a metabolic profiling dataset of the same samples. PMID:20015363

Magnetosphere Modeling: From Cartoons to Simulations

NASA Astrophysics Data System (ADS)

Gombosi, T. I.

2017-12-01

Over the last half a century physics-based global computer simulations became a bridge between experiment and basic theory and now it represents the "third pillar" of geospace research. Today, many of our scientific publications utilize large-scale simulations to interpret observations, test new ideas, plan campaigns, or design new instruments. Realistic simulations of the complex Sun-Earth system have been made possible by the dramatically increased power of both computing hardware and numerical algorithms. Early magnetosphere models were based on simple E&M concepts (like the Chapman-Ferraro cavity) and hydrodynamic analogies (bow shock). At the beginning of the space age current system models were developed culminating in the sophisticated Tsyganenko-type description of the magnetic configuration. The first 3D MHD simulations of the magnetosphere were published in the early 1980s. A decade later there were several competing global models that were able to reproduce many fundamental properties of the magnetosphere. The leading models included the impact of the ionosphere by using a height-integrated electric potential description. Dynamic coupling of global and regional models started in the early 2000s by integrating a ring current and a global magnetosphere model. It has been recognized for quite some time that plasma kinetic effects play an important role. Presently, global hybrid simulations of the dynamic magnetosphere are expected to be possible on exascale supercomputers, while fully kinetic simulations with realistic mass ratios are still decades away. In the 2010s several groups started to experiment with PIC simulations embedded in large-scale 3D MHD models. Presently this integrated MHD-PIC approach is at the forefront of magnetosphere simulations and this technique is expected to lead to some important advances in our understanding of magnetosheric physics. This talk will review the evolution of magnetosphere modeling from cartoons to current systems, to global MHD to MHD-PIC and discuss the role of state-of-the-art models in forecasting space weather.

Nonlinear dynamics of the magnetosphere and space weather

NASA Technical Reports Server (NTRS)

Sharma, A. Surjalal

1996-01-01

The solar wind-magnetosphere system exhibits coherence on the global scale and such behavior can arise from nonlinearity on the dynamics. The observational time series data were used together with phase space reconstruction techniques to analyze the magnetospheric dynamics. Analysis of the solar wind, auroral electrojet and Dst indices showed low dimensionality of the dynamics and accurate prediction can be made with an input/output model. The predictability of the magnetosphere in spite of the apparent complexity arises from its dynamical synchronism with the solar wind. The electrodynamic coupling between different regions of the magnetosphere yields its coherent, low dimensional behavior. The data from multiple satellites and ground stations can be used to develop a spatio-temporal model that identifies the coupling between different regions. These nonlinear dynamical models provide space weather forecasting capabilities.

Application of dynamical systems theory to global weather phenomena revealed by satellite imagery

NASA Technical Reports Server (NTRS)

Saltzman, Barry; Ebisuzaki, Wesley; Maasch, Kirk A.; Oglesby, Robert; Pandolfo, Lionel; Tang, Chung-Muh

1989-01-01

Theoretical studies of low frequency and seasonal weather variability; dynamical properties of observational and general circulation model (GCM)-generated records; effects of the hydrologic cycle and latent heat release on extratropical weather; and Earth-system science studies are summarized.

Precise orbit determination for NASA's earth observing system using GPS (Global Positioning System)

NASA Technical Reports Server (NTRS)

Williams, B. G.

1988-01-01

An application of a precision orbit determination technique for NASA's Earth Observing System (EOS) using the Global Positioning System (GPS) is described. This technique allows the geometric information from measurements of GPS carrier phase and P-code pseudo-range to be exploited while minimizing requirements for precision dynamical modeling. The method combines geometric and dynamic information to determine the spacecraft trajectory; the weight on the dynamic information is controlled by adjusting fictitious spacecraft accelerations in three dimensions which are treated as first order exponentially time correlated stochastic processes. By varying the time correlation and uncertainty of the stochastic accelerations, the technique can range from purely geometric to purely dynamic. Performance estimates for this technique as applied to the orbit geometry planned for the EOS platforms indicate that decimeter accuracies for EOS orbit position may be obtainable. The sensitivity of the predicted orbit uncertainties to model errors for station locations, nongravitational platform accelerations, and Earth gravity is also presented.

Further Studies on Oceanic Biogeochemistry and Carbon Cycling

NASA Technical Reports Server (NTRS)

Signorini, S. R.; McClain, C. R.

2003-01-01

This TM consists of two chapters. Chapter I describes the development of a coupled, one-dimensional biogeochemical model using turbulence closure mixed layer (TCMLM) dynamics. The model is applied to the Sargasso Sea at the BATS (Bermuda Atlantic Time Series) site and the results are compared with a previous model study in the same region described in NASNTP-2001-209991. The use of the TCMLM contributed to some improvements in the model simulation of chlorophyll, PAR, nitrate, phosphate, and oxygen, but most importantly, the current model achieved good agreement with the data with much more realistic background eddy diffusivity. However, off-line calculations of horizontal transport of biogeochemical properties revealed that one-dimensional dynamics can only provide a limited assessment of the nutrient and carbon balances at BATS. Future studies in the BATS region will require comprehensive three-dimensional field studies, combined with three-dimensional eddy resolving numerical experiments, to adequately quantify the impact of the local and remote forcing on ecosystem dynamics and carbon cycling. Chapter II addresses the sensitivity of global sea-air CO, flux estimates to wind speed, temperature, and salinity. Sensitivity analyses of sea-air CO, flux to wind speed climatologies, gas transfer algorithms, SSS and SST were conducted for the global oceans and regional domains. Large uncertainties in the global sea-air flux are identified, primarily due to the different gas transfer algorithms used. The sensitivity of the sea-air flux to SST and SSS is similar in magnitude to the effect of using different wind climatologies. Globally, the mean ocean uptake of CO, changes by 5 to 16%, depending upon the combination of SST and SSS used.

Power-law Growth and Punctuated Equilibrium Dynamics in Water Resources Systems

NASA Astrophysics Data System (ADS)

Parolari, A.; Katul, G. G.; Porporato, A. M.

2015-12-01

The global rise in population-driven water scarcity and recent appreciation of strong dynamic coupling between human and natural systems has called for new approaches to predict the future sustainability of regional and global water resources systems. The dynamics of coupled human-water systems are driven by a complex set of social, environmental, and technological factors. Present projections of water resources systems range from a finite carrying capacity regulated by accessible freshwater, or `peak renewable water,' to punctuated evolution with new supplied and improved efficiency gained from technological and social innovation. However, these projections have yet to be quantified from observations or in a comprehensive theoretical framework. Using data on global water withdrawals and storage capacity of regional water supply systems, non-trivial dynamics are identified in water resources systems development over time, including power-law growth and punctuated equilibria. Two models are introduced to explain this behavior: (1) a delay differential equation and (2) a power-law with log-periodic oscillations, both of which rely on past conditions (or system memory) to describe the present rate of growth in the system. In addition, extension of the first model demonstrates how system delays and punctuated equilibria can emerge from coupling between human population growth and associated resource demands. Lastly, anecdotal evidence is used to demonstrate the likelihood of power-law growth in global water use from the agricultural revolution 3000 BC to the present. In a practical sense, the presence of these patterns in models with delayed oscillations suggests that current decision-making related to water resources development results from the historical accumulation of resource use decisions, technological and social changes, and their consequences.

Driven Bose-Hubbard model with a parametrically modulated harmonic trap

NASA Astrophysics Data System (ADS)

Mann, N.; Bakhtiari, M. Reza; Massel, F.; Pelster, A.; Thorwart, M.

2017-04-01

We investigate a one-dimensional Bose-Hubbard model in a parametrically driven global harmonic trap. The delicate interplay of both the local interaction of the atoms in the lattice and the driving of the global trap allows us to control the dynamical stability of the trapped quantum many-body state. The impact of the atomic interaction on the dynamical stability of the driven quantum many-body state is revealed in the regime of weak interaction by analyzing a discretized Gross-Pitaevskii equation within a Gaussian variational ansatz, yielding a Mathieu equation for the condensate width. The parametric resonance condition is shown to be modified by the atom interaction strength. In particular, the effective eigenfrequency is reduced for growing interaction in the mean-field regime. For a stronger interaction, the impact of the global parametric drive is determined by the numerically exact time-evolving block decimation scheme. When the trapped bosons in the lattice are in a Mott insulating state, the absorption of energy from the driving field is suppressed due to the strongly reduced local compressibility of the quantum many-body state. In particular, we find that the width of the local Mott region shows a breathing dynamics. Finally, we observe that the global modulation also induces an effective time-independent inhomogeneous hopping strength for the atoms.

Rumor Diffusion in an Interests-Based Dynamic Social Network

PubMed Central

Mao, Xinjun; Guessoum, Zahia; Zhou, Huiping

2013-01-01

To research rumor diffusion in social friend network, based on interests, a dynamic friend network is proposed, which has the characteristics of clustering and community, and a diffusion model is also proposed. With this friend network and rumor diffusion model, based on the zombie-city model, some simulation experiments to analyze the characteristics of rumor diffusion in social friend networks have been conducted. The results show some interesting observations: (1) positive information may evolve to become a rumor through the diffusion process that people may modify the information by word of mouth; (2) with the same average degree, a random social network has a smaller clustering coefficient and is more beneficial for rumor diffusion than the dynamic friend network; (3) a rumor is spread more widely in a social network with a smaller global clustering coefficient than in a social network with a larger global clustering coefficient; and (4) a network with a smaller clustering coefficient has a larger efficiency. PMID:24453911

Rumor diffusion in an interests-based dynamic social network.

PubMed

Tang, Mingsheng; Mao, Xinjun; Guessoum, Zahia; Zhou, Huiping

2013-01-01

To research rumor diffusion in social friend network, based on interests, a dynamic friend network is proposed, which has the characteristics of clustering and community, and a diffusion model is also proposed. With this friend network and rumor diffusion model, based on the zombie-city model, some simulation experiments to analyze the characteristics of rumor diffusion in social friend networks have been conducted. The results show some interesting observations: (1) positive information may evolve to become a rumor through the diffusion process that people may modify the information by word of mouth; (2) with the same average degree, a random social network has a smaller clustering coefficient and is more beneficial for rumor diffusion than the dynamic friend network; (3) a rumor is spread more widely in a social network with a smaller global clustering coefficient than in a social network with a larger global clustering coefficient; and (4) a network with a smaller clustering coefficient has a larger efficiency.

Emergence of universal scaling in financial markets from mean-field dynamics

NASA Astrophysics Data System (ADS)

Vikram, S. V.; Sinha, Sitabhra

2011-01-01

Collective phenomena with universal properties have been observed in many complex systems with a large number of components. Here we present a microscopic model of the emergence of scaling behavior in such systems, where the interaction dynamics between individual components is mediated by a global variable making the mean-field description exact. Using the example of financial markets, we show that asset price can be such a global variable with the critical role of coordinating the actions of agents who are otherwise independent. The resulting model accurately reproduces empirical properties such as the universal scaling of the price fluctuation and volume distributions, long-range correlations in volatility, and multiscaling.

Ring Current Ion Coupling with Electromagnetic Ion Cyclotron Waves

NASA Technical Reports Server (NTRS)

Khazanov. G. V.; Gamayunov, K. V.; Jordanova, V. K.; Six, N. Frank (Technical Monitor)

2002-01-01

A new ring current global model has been developed that couples the system of two kinetic equations: one equation describes the ring current (RC) ion dynamic, and another equation describes wave evolution of electromagnetic ion cyclotron waves (EMIC). The coupled model is able to simulate, for the first time self-consistently calculated RC ion kinetic and evolution of EMIC waves that propagate along geomagnetic field lines and reflect from the ionosphere. Ionospheric properties affect the reflection index through the integral Pedersen and Hall conductivities. The structure and dynamics of the ring current proton precipitating flux regions, intensities of EMIC global RC energy balance, and some other parameters will be studied in detail for the selected geomagnetic storms.

Human and climate impact on global riverine water and sediment fluxes - a distributed analysis

NASA Astrophysics Data System (ADS)

Cohen, S.; Kettner, A.; Syvitski, J. P.

2013-05-01

Understanding riverine water and sediment dynamics is an important undertaking for both socially-relevant issues such as agriculture, water security and infrastructure management and for scientific analysis of climate, landscapes, river ecology, oceanography and other disciplines. Providing good quantitative and predictive tools in therefore timely particularly in light of predicted climate and landuse changes. The intensity and dynamics between man-made and climatic factors vary widely across the globe and are therefore hard to predict. Using sophisticated numerical models is therefore warranted. Here we use a distributed global riverine sediment and water discharge model (WBMsed) to simulate human and climate effect on our planet's large rivers.

Double symbolic joint entropy in nonlinear dynamic complexity analysis

NASA Astrophysics Data System (ADS)

Yao, Wenpo; Wang, Jun

2017-07-01

Symbolizations, the base of symbolic dynamic analysis, are classified as global static and local dynamic approaches which are combined by joint entropy in our works for nonlinear dynamic complexity analysis. Two global static methods, symbolic transformations of Wessel N. symbolic entropy and base-scale entropy, and two local ones, namely symbolizations of permutation and differential entropy, constitute four double symbolic joint entropies that have accurate complexity detections in chaotic models, logistic and Henon map series. In nonlinear dynamical analysis of different kinds of heart rate variability, heartbeats of healthy young have higher complexity than those of the healthy elderly, and congestive heart failure (CHF) patients are lowest in heartbeats' joint entropy values. Each individual symbolic entropy is improved by double symbolic joint entropy among which the combination of base-scale and differential symbolizations have best complexity analysis. Test results prove that double symbolic joint entropy is feasible in nonlinear dynamic complexity analysis.

Challenges in understanding past and present eolian dust dynamics

NASA Astrophysics Data System (ADS)

Stuut, Jan-Berend; Merkel, Ute; Rousseau, Denis-Didier

2012-05-01

Dust Workshop 2011: Processes and Quaternary History of Dust Dynamics; Bremen, Germany, 31 October to 3 November 2011 Mineral dust is now generally recognized as a key element in global climate. However, many open questions need to be addressed to reduce the large uncertainties that still exist regarding the global dust cycle. The Atmospheric Dust During the Last Glacial Cycle: Observations and Modeling initiative (ADOM; see http://www.pages-igbp.org/workinggroups/adom) of the Past Global Changes (PAGES) tackles these questions from both modern and paleo perspectives. A 3-day workshop funded by PAGES and the Center for Marine Environmental Sciences (MARUM) in Germany brought together 50 international experts on marine, terrestrial, and polar dust archives; meteorology; remote sensing; and climate modeling. The workshop aimed to bridge gaps between disciplines and to cover all temporal and spatial scales involved in dust processes.

Modeling infectious disease dynamics in the complex landscape of global health.

PubMed

Heesterbeek, Hans; Anderson, Roy M; Andreasen, Viggo; Bansal, Shweta; De Angelis, Daniela; Dye, Chris; Eames, Ken T D; Edmunds, W John; Frost, Simon D W; Funk, Sebastian; Hollingsworth, T Deirdre; House, Thomas; Isham, Valerie; Klepac, Petra; Lessler, Justin; Lloyd-Smith, James O; Metcalf, C Jessica E; Mollison, Denis; Pellis, Lorenzo; Pulliam, Juliet R C; Roberts, Mick G; Viboud, Cecile

2015-03-13

Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity and changeable human behavior, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for decision-making in global health. Copyright © 2015, American Association for the Advancement of Science.

Modeling Zika plasma viral dynamics in non-human primates: insights into viral pathogenesis and antiviral strategies

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

Best, Katharine; Guedj, Jeremie; Madelain, Vincent

2016-10-24

The recent outbreak of Zika virus (ZIKV) has been associated with fetal abnormalities and neurological complications, prompting global concern. Here we present the first mathematical analysis of the within-host dynamics of plasma ZiKV burden in a non-human primate model, allowing for characterization of the growth and clearance of ZIKV within an individual macaque.

Dynamics of Markets

NASA Astrophysics Data System (ADS)

McCauley, Joseph L.

2009-09-01

Preface; 1. Econophysics: why and what; 2. Neo-classical economic theory; 3. Probability and stochastic processes; 4. Introduction to financial economics; 5. Introduction to portfolio selection theory; 6. Scaling, pair correlations, and conditional densities; 7. Statistical ensembles: deducing dynamics from time series; 8. Martingale option pricing; 9. FX market globalization: evolution of the dollar to worldwide reserve currency; 10. Macroeconomics and econometrics: regression models vs. empirically based modeling; 11. Complexity; Index.

Simulating the impacts of disturbances on forest carbon cycling in North America: processes, data, models, and challenges

Treesearch

Shuguang Liu; Ben Bond-Lamberty; Jeffrey A. Hicke; Rodrigo Vargas; Shuqing Zhao; Jing Chen; Steven L. Edburg; Yueming Hu; Jinxun Liu; A. David McGuire; Jingfeng Xiao; Robert Keane; Wenping Yuan; Jianwu Tang; Yiqi Luo; Christopher Potter; Jennifer Oeding

2011-01-01

Forest disturbances greatly alter the carbon cycle at various spatial and temporal scales. It is critical to understand disturbance regimes and their impacts to better quantify regional and global carbon dynamics. This review of the status and major challenges in representing the impacts of disturbances in modeling the carbon dynamics across North America revealed some...

Utilization of UARS Data in Validation of Photochemical and Dynamical Mechanism in Stratospheric Models

NASA Technical Reports Server (NTRS)

Rodriquez, Jose M.; Hu, Wenjie; Ko, Malcolm K.W.

1996-01-01

The global three-dimensional measurement of long- and short-lived species from Upper Atmospheric Research Satellite (UARS) provides a unique opportunity to validate chemistry and dynamics mechanisms in the middle atmosphere. During the past three months, we focused on expanding our study of data-model comparisons to whole time periods when Cryogenic Limb Array Etalon Spectrometer (CLAES) instrument were operating.

Stochastic hybrid delay population dynamics: well-posed models and extinction.

PubMed

Yuan, Chenggui; Mao, Xuerong; Lygeros, John

2009-01-01

Nonlinear differential equations have been used for decades for studying fluctuations in the populations of species, interactions of species with the environment, and competition and symbiosis between species. Over the years, the original non-linear models have been embellished with delay terms, stochastic terms and more recently discrete dynamics. In this paper, we investigate stochastic hybrid delay population dynamics (SHDPD), a very general class of population dynamics that comprises all of these phenomena. For this class of systems, we provide sufficient conditions to ensure that SHDPD have global positive, ultimately bounded solutions, a minimum requirement for a realistic, well-posed model. We then study the question of extinction and establish conditions under which an ecosystem modelled by SHDPD is doomed.

Simulations of Tornadoes, Tropical Cyclones, MJOs, and QBOs, using GFDL's multi-scale global climate modeling system

NASA Astrophysics Data System (ADS)

Lin, Shian-Jiann; Harris, Lucas; Chen, Jan-Huey; Zhao, Ming

2014-05-01

A multi-scale High-Resolution Atmosphere Model (HiRAM) is being developed at NOAA/Geophysical Fluid Dynamics Laboratory. The model's dynamical framework is the non-hydrostatic extension of the vertically Lagrangian finite-volume dynamical core (Lin 2004, Monthly Wea. Rev.) constructed on a stretchable (via Schmidt transformation) cubed-sphere grid. Physical parametrizations originally designed for IPCC-type climate predictions are in the process of being modified and made more "scale-aware", in an effort to make the model suitable for multi-scale weather-climate applications, with horizontal resolution ranging from 1 km (near the target high-resolution region) to as low as 400 km (near the antipodal point). One of the main goals of this development is to enable simulation of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously thought impossible. We will present preliminary results, covering a very wide spectrum of temporal-spatial scales, ranging from simulation of tornado genesis (hours), Madden-Julian Oscillations (intra-seasonal), topical cyclones (seasonal), to Quasi Biennial Oscillations (intra-decadal), using the same global multi-scale modeling system.

Transmission dynamics of cholera: Mathematical modeling and control strategies

NASA Astrophysics Data System (ADS)

Sun, Gui-Quan; Xie, Jun-Hui; Huang, Sheng-He; Jin, Zhen; Li, Ming-Tao; Liu, Liqun

2017-04-01

Cholera, as an endemic disease around the world, has generated great threat to human society and caused enormous morbidity and mortality with weak surveillance system. In this paper, we propose a mathematical model to describe the transmission of Cholera. Moreover, basic reproduction number and the global dynamics of the dynamical model are obtained. Then we apply our model to characterize the transmission process of Cholera in China. It was found that, in order to avoid its outbreak in China, it may be better to increase immunization coverage rate and make effort to improve environmental management especially for drinking water. Our results may provide some new insights for elimination of Cholera.

Integrating Unified Gravity Wave Physics into the NOAA Next Generation Global Prediction System

NASA Astrophysics Data System (ADS)

Alpert, J. C.; Yudin, V.; Fuller-Rowell, T. J.; Akmaev, R. A.

2017-12-01

The Unified Gravity Wave Physics (UGWP) project for the Next Generation Global Prediction System (NGGPS) is a NOAA collaborative effort between the National Centers for Environmental Prediction (NCEP), Environemntal Modeling Center (EMC) and the University of Colorado, Cooperative Institute for Research in Environmental Sciences (CU-CIRES) to support upgrades and improvements of GW dynamics (resolved scales) and physics (sub-grid scales) in the NOAA Environmental Modeling System (NEMS)†. As envisioned the global climate, weather and space weather models of NEMS will substantially improve their predictions and forecasts with the resolution-sensitive (scale-aware) formulations planned under the UGWP framework for both orographic and non-stationary waves. In particular, the planned improvements for the Global Forecast System (GFS) model of NEMS are: calibration of model physics for higher vertical and horizontal resolution and an extended vertical range of simulations, upgrades to GW schemes, including the turbulent heating and eddy mixing due to wave dissipation and breaking, and representation of the internally-generated QBO. The main priority of the UGWP project is unified parameterization of orographic and non-orographic GW effects including momentum deposition in the middle atmosphere and turbulent heating and eddies due to wave dissipation and breaking. The latter effects are not currently represented in NOAA atmosphere models. The team has tested and evaluated four candidate GW solvers integrating the selected GW schemes into the NGGPS model. Our current work and planned activity is to implement the UGWP schemes in the first available GFS/FV3 (open FV3) configuration including adapted GFDL modification for sub-grid orography in GFS. Initial global model results will be shown for the operational and research GFS configuration for spectral and FV3 dynamical cores. †http://www.emc.ncep.noaa.gov/index.php?branch=NEMS

International Management: Creating a More Realistic Global Planning Environment.

ERIC Educational Resources Information Center

Waldron, Darryl G.

2000-01-01

Discusses the need for realistic global planning environments in international business education, introducing a strategic planning model that has teams interacting with teams to strategically analyze a selected multinational company. This dynamic process must result in a single integrated written analysis that specifies an optimal strategy for…

The Influence of Information Acquisition on the Complex Dynamics of Market Competition

NASA Astrophysics Data System (ADS)

Guo, Zhanbing; Ma, Junhai

In this paper, we build a dynamical game model with three bounded rational players (firms) to study the influence of information on the complex dynamics of market competition, where useful information is about rival’s real decision. In this dynamical game model, one information-sharing team is composed of two firms, they acquire and share the information about their common competitor, however, they make their own decisions separately, where the amount of information acquired by this information-sharing team will determine the estimation accuracy about the rival’s real decision. Based on this dynamical game model and some creative 3D diagrams, the influence of the amount of information on the complex dynamics of market competition such as local dynamics, global dynamics and profits is studied. These results have significant theoretical and practical values to realize the influence of information.

Exploring the Role of Social Media and Individual Behaviors in Flood Evacuation Processes: An Agent-Based Modeling Approach

NASA Astrophysics Data System (ADS)

Du, Erhu; Cai, Ximing; Sun, Zhiyong; Minsker, Barbara

2017-11-01

Flood warnings from various information sources are important for individuals to make evacuation decisions during a flood event. In this study, we develop a general opinion dynamics model to simulate how individuals update their flood hazard awareness when exposed to multiple information sources, including global broadcast, social media, and observations of neighbors' actions. The opinion dynamics model is coupled with a traffic model to simulate the evacuation processes of a residential community with a given transportation network. Through various scenarios, we investigate how social media affect the opinion dynamics and evacuation processes. We find that stronger social media can make evacuation processes more sensitive to the change of global broadcast and neighbor observations, and thus, impose larger uncertainty on evacuation rates (i.e., a large range of evacuation rates corresponding to sources of information). For instance, evacuation rates are lower when social media become more influential and individuals have less trust in global broadcast. Stubborn individuals can significantly affect the opinion dynamics and reduce evacuation rates. In addition, evacuation rates respond to the percentage of stubborn agents in a nonlinear manner, i.e., above a threshold, the impact of stubborn agents will be intensified by stronger social media. These results highlight the role of social media in flood evacuation processes and the need to monitor social media so that misinformation can be corrected in a timely manner. The joint impacts of social media, quality of flood warnings, and transportation capacity on evacuation rates are also discussed.

An agent-based modelling framework to explore the role of social media and stubborn people on evacuation rates during flooding events

NASA Astrophysics Data System (ADS)

Du, E.; Cai, X.; Minsker, B. S.; Sun, Z.

2017-12-01

Flood warnings from various information sources are important for individuals to make evacuation decisions during a flood event. In this study, we develop a general opinion dynamics model to simulate how individuals update their flood hazard awareness when exposed to multiple information sources, including global broadcast, social media, and observations of neighbors' actions. The opinion dynamics model is coupled with a traffic model to simulate the evacuation processes of a residential community with a given transportation network. Through various scenarios, we investigate how social media affect the opinion dynamics and evacuation processes. We find that stronger social media can make evacuation processes more sensitive to the change of global broadcast and neighbor observations, and thus, impose larger uncertainty on evacuation rates (i.e., a large range of evacuation rates corresponding to sources of information). For instance, evacuation rates are lower when social media become more influential and individuals have less trust in global broadcast. Stubborn individuals can significantly affect the opinion dynamics and reduce evacuation rates. In addition, evacuation rates respond to the percentage of stubborn agents in a non-linear manner, i.e., above a threshold, the impact of stubborn agents will be intensified by stronger social media. These results highlight the role of social media in flood evacuation processes and the need to monitor social media so that misinformation can be corrected in a timely manner. The joint impacts of social media, quality of flood warnings and transportation capacity on evacuation rates are also discussed.

Outlook on a worldwide forest transition.

PubMed

Pagnutti, Chris; Bauch, Chris T; Anand, Madhur

2013-01-01

It is not clear whether a worldwide "forest transition" to net reforestation will ever occur, and the need to address the main driver--agriculture--is compelling. We present a mathematical model of land use dynamics based on the world food equation that explains historical trends in global land use on the millennial scale. The model predicts that a global forest transition only occurs under a small and very specific range of parameter values (and hence seems unlikely) but if it does occur, it would have to occur within the next 70 years. In our baseline scenario, global forest cover continues to decline until it stabilizes within the next two centuries at 22% of global land cover, and wild pasture at 1.4%. Under other scenarios the model predicts unanticipated dynamics wherein a forest transition may relapse, heralding a second era of deforestation; this brings into question national-level forest transitions observed in recent decades, and suggests we need to expand our lexicon of possibilities beyond the simple "forest transition/no forest transition" dichotomy. This research also underscores that the challenge of feeding a growing population while conserving natural habitat will likely continue for decades to come.

Model of ballistic targets' dynamics used for trajectory tracking algorithms

NASA Astrophysics Data System (ADS)

Okoń-FÄ fara, Marta; Kawalec, Adam; Witczak, Andrzej

2017-04-01

There are known only few ballistic object tracking algorithms. To develop such algorithms and to its further testing, it is necessary to implement possibly simple and reliable objects' dynamics model. The article presents the dynamics' model of a tactical ballistic missile (TBM) including the three stages of flight: the boost stage and two passive stages - the ascending one and the descending one. Additionally, the procedure of transformation from the local coordinate system to the polar-radar oriented and the global is presented. The prepared theoretical data may be used to determine the tracking algorithm parameters and to its further verification.

ORCHIMIC (v1.0), a microbe-mediated model for soil organic matter decomposition

NASA Astrophysics Data System (ADS)

Huang, Ye; Guenet, Bertrand; Ciais, Philippe; Janssens, Ivan A.; Soong, Jennifer L.; Wang, Yilong; Goll, Daniel; Blagodatskaya, Evgenia; Huang, Yuanyuan

2018-06-01

The role of soil microorganisms in regulating soil organic matter (SOM) decomposition is of primary importance in the carbon cycle, in particular in the context of global change. Modeling soil microbial community dynamics to simulate its impact on soil gaseous carbon (C) emissions and nitrogen (N) mineralization at large spatial scales is a recent research field with the potential to improve predictions of SOM responses to global climate change. In this study we present a SOM model called ORCHIMIC, which utilizes input data that are consistent with those of global vegetation models. ORCHIMIC simulates the decomposition of SOM by explicitly accounting for enzyme production and distinguishing three different microbial functional groups: fresh organic matter (FOM) specialists, SOM specialists, and generalists, while also implicitly accounting for microbes that do not produce extracellular enzymes, i.e., cheaters. ORCHIMIC and two other organic matter decomposition models, CENTURY (based on first-order kinetics and representative of the structure of most current global soil carbon models) and PRIM (with FOM accelerating the decomposition rate of SOM), were calibrated to reproduce the observed respiration fluxes of FOM and SOM from the incubation experiments of Blagodatskaya et al. (2014). Among the three models, ORCHIMIC was the only one that effectively captured both the temporal dynamics of the respiratory fluxes and the magnitude of the priming effect observed during the incubation experiment. ORCHIMIC also effectively reproduced the temporal dynamics of microbial biomass. We then applied different idealized changes to the model input data, i.e., a 5 K stepwise increase of temperature and/or a doubling of plant litter inputs. Under 5 K warming conditions, ORCHIMIC predicted a 0.002 K-1 decrease in the C use efficiency (defined as the ratio of C allocated to microbial growth to the sum of C allocated to growth and respiration) and a 3 % loss of SOC. Under the double litter input scenario, ORCHIMIC predicted a doubling of microbial biomass, while SOC stock increased by less than 1 % due to the priming effect. This limited increase in SOC stock contrasted with the proportional increase in SOC stock as modeled by the conventional SOC decomposition model (CENTURY), which can not reproduce the priming effect. If temperature increased by 5 K and litter input was doubled, ORCHIMIC predicted almost the same loss of SOC as when only temperature was increased. These tests suggest that the responses of SOC stock to warming and increasing input may differ considerably from those simulated by conventional SOC decomposition models when microbial dynamics are included. The next step is to incorporate the ORCHIMIC model into a global vegetation model to perform simulations for representative sites and future scenarios.

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.

Sundaland Peat Carbon Dynamics and Its Contribution to the Holocene Atmospheric CO2 Concentration

NASA Astrophysics Data System (ADS)

Abrams, Jesse F.; Hohn, Sönke; Rixen, Tim; Merico, Agostino

2018-04-01

The Sunda Shelf is a large submerged extension of the continental shelf of mainland Asia, joining the islands of Borneo, Java, and Sumatra and forming the shallow seabed of the South China Sea. Recent studies identified present-day peatlands in Southeast Asia as a globally important carbon reservoir. However, little is known about Sundaland paleopeatlands and their role in the global carbon cycle since the Last Glacial Maximum. Using a topography-based, sea level-driven model, we estimate the potential spatial extent of peatlands during the late Pleistocene and early Holocene across the low-lying Sundaland plains. We then use the estimated peatland area together with data on carbon accumulation rates to calculate the total peat carbon pool on the Sunda Shelf. Finally, using a global biogeochemical model, we analyze the relative influence of the predicted Sundaland peat dynamics and other carbon change mechanisms, specifically high-latitude forest growth and peat formation, shallow sea carbonate deposition, ocean warming, and combinations of them, on the global carbon cycle of the Holocene. We identify a feedback mechanism between sea level and peatland carbon sequestration in Sundaland that reduced atmospheric CO2 concentration by about 4-5 ppm and increased δ13C by 0.05‰ during the Holocene. We also show that a concurrence of mechanisms that includes Sundaland peat dynamics produces model results that are consistent with proxy records, especially with respect to δ13C.

A theory for protein dynamics: Global anisotropy and a normal mode approach to local complexity

NASA Astrophysics Data System (ADS)

Copperman, Jeremy; Romano, Pablo; Guenza, Marina

2014-03-01

We propose a novel Langevin equation description for the dynamics of biological macromolecules by projecting the solvent and all atomic degrees of freedom onto a set of coarse-grained sites at the single residue level. We utilize a multi-scale approach where molecular dynamic simulations are performed to obtain equilibrium structural correlations input to a modified Rouse-Zimm description which can be solved analytically. The normal mode solution provides a minimal basis set to account for important properties of biological polymers such as the anisotropic global structure, and internal motion on a complex free-energy surface. This multi-scale modeling method predicts the dynamics of both global rotational diffusion and constrained internal motion from the picosecond to the nanosecond regime, and is quantitative when compared to both simulation trajectory and NMR relaxation times. Utilizing non-equilibrium sampling techniques and an explicit treatment of the free-energy barriers in the mode coordinates, the model is extended to include biologically important fluctuations in the microsecond regime, such as bubble and fork formation in nucleic acids, and protein domain motion. This work supported by the NSF under the Graduate STEM Fellows in K-12 Education (GK-12) program, grant DGE-0742540 and NSF grant DMR-0804145, computational support from XSEDE and ACISS.

Improving representation of nitrogen uptake, allocation, and carbon assimilation in the Community Land Model

NASA Astrophysics Data System (ADS)

Ghimire, B.; Riley, W. J.; Koven, C.

2013-12-01

Nitrogen is the most important nutrient limiting plant carbon assimilation and growth, and is required for production of photosynthetic enzymes, growth and maintenance respiration, and maintaining cell structure. The forecasted rise in plant available nitrogen through atmospheric nitrogen deposition and the release of locked soil nitrogen by permafrost thaw in high latitude ecosystems is likely to result in an increase in plant productivity. However a mechanistic representation of plant nitrogen dynamics is lacking in earth system models. Most earth system models ignore the dynamic nature of plant nutrient uptake and allocation, and further lack tight coupling of below- and above-ground processes. In these models, the increase in nitrogen uptake does not translate to a corresponding increase in photosynthesis parameters, such as maximum Rubisco capacity and electron transfer rate. We present an improved modeling framework implemented in the Community Land Model version 4.5 (CLM4.5) for dynamic plant nutrient uptake, and allocation to different plant parts, including leaf enzymes. This modeling framework relies on imposing a more realistic flexible carbon to nitrogen stoichiometric ratio for different plant parts. The model mechanistically responds to plant nitrogen uptake and leaf allocation though changes in photosynthesis parameters. We produce global simulations, and examine the impacts of the improved nitrogen cycling. The improved model is evaluated against multiple observations including TRY database of global plant traits, nitrogen fertilization observations and 15N tracer studies. Global simulations with this new version of CLM4.5 showed better agreement with the observations than the default CLM4.5-CN model, and captured the underlying mechanisms associated with plant nitrogen cycle.

Priority in Process Algebras

NASA Technical Reports Server (NTRS)

Cleaveland, Rance; Luettgen, Gerald; Natarajan, V.

1999-01-01

This paper surveys the semantic ramifications of extending traditional process algebras with notions of priority that allow for some transitions to be given precedence over others. These enriched formalisms allow one to model system features such as interrupts, prioritized choice, or real-time behavior. Approaches to priority in process algebras can be classified according to whether the induced notion of preemption on transitions is global or local and whether priorities are static or dynamic. Early work in the area concentrated on global pre-emption and static priorities and led to formalisms for modeling interrupts and aspects of real-time, such as maximal progress, in centralized computing environments. More recent research has investigated localized notions of pre-emption in which the distribution of systems is taken into account, as well as dynamic priority approaches, i.e., those where priority values may change as systems evolve. The latter allows one to model behavioral phenomena such as scheduling algorithms and also enables the efficient encoding of real-time semantics. Technically, this paper studies the different models of priorities by presenting extensions of Milner's Calculus of Communicating Systems (CCS) with static and dynamic priority as well as with notions of global and local pre- emption. In each case the operational semantics of CCS is modified appropriately, behavioral theories based on strong and weak bisimulation are given, and related approaches for different process-algebraic settings are discussed.

Implementation of sediment dynamics in a global integrated assessment model for an improved simulation of nutrient retention and transfers in surface freshwaters

NASA Astrophysics Data System (ADS)

Vilmin, L.; Beusen, A.; Mogollón, J.; Bouwman, L.

2017-12-01

Sediment dynamics play a significant role in river biogeochemical functioning. They notably control the transfer of particle-bound nutrients, have a direct influence on light availability for primary production, and particle accumulation can affect oxic conditions of river beds. In the perspective of improving our current understanding of large scale nutrient fluxes in rivers, it is hence necessary to include these dynamics in global models. In this scope, we implement particle accumulation and remobilization in a coupled global hydrology-nutrient model (IMAGE-GNM), at a spatial resolution of 0.5°. The transfer of soil loss from natural and agricultural lands is simulated mechanistically, from headwater streams to estuaries. First tests of the model are performed in the Mississippi river basin. At a yearly time step for the period 1978-2000, the average difference between simulated and measured suspended sediment concentrations at the most downstream monitoring station is 25%. Sediment retention is estimated in the different Strahler stream orders, in lakes and reservoirs. We discuss: 1) the distribution of sediment loads to small streams, which has a significant effect on transfers through watersheds and larger scale river fluxes and 2) the potential effect of damming on the fate of particle-bound nutrients. These new developments are crucial for future assessments of large scale nutrient and carbon fluxes in river systems.

Effects of Kinetic Processes in Shaping Io's Global Plasma Environment: A 3D Hybrid Model

NASA Technical Reports Server (NTRS)

Lipatov, Alexander S.; Combi, Michael R.

2004-01-01

The global dynamics of the ionized and neutral components in the environment of Io plays an important role in the interaction of Jupiter's corotating magnetospheric plasma with Io. The stationary simulation of this problem was done in the MHD and the electrodynamics approaches. One of the main significant results from the simplified two-fluid model simulations was a production of the structure of the double-peak in the magnetic field signature of the I0 flyby that could not be explained by standard MHD models. In this paper, we develop a method of kinetic ion simulation. This method employs the fluid description for electrons and neutrals whereas for ions multilevel, drift-kinetic and particle, approaches are used. We also take into account charge-exchange and photoionization processes. Our model provides much more accurate description for ion dynamics and allows us to take into account the realistic anisotropic ion distribution that cannot be done in fluid simulations. The first results of such simulation of the dynamics of ions in the Io's environment are discussed in this paper.

Balancing building and maintenance costs in growing transport networks

NASA Astrophysics Data System (ADS)

Bottinelli, Arianna; Louf, Rémi; Gherardi, Marco

2017-09-01

The costs associated to the length of links impose unavoidable constraints to the growth of natural and artificial transport networks. When future network developments cannot be predicted, the costs of building and maintaining connections cannot be minimized simultaneously, requiring competing optimization mechanisms. Here, we study a one-parameter nonequilibrium model driven by an optimization functional, defined as the convex combination of building cost and maintenance cost. By varying the coefficient of the combination, the model interpolates between global and local length minimization, i.e., between minimum spanning trees and a local version known as dynamical minimum spanning trees. We show that cost balance within this ensemble of dynamical networks is a sufficient ingredient for the emergence of tradeoffs between the network's total length and transport efficiency, and of optimal strategies of construction. At the transition between two qualitatively different regimes, the dynamics builds up power-law distributed waiting times between global rearrangements, indicating a point of nonoptimality. Finally, we use our model as a framework to analyze empirical ant trail networks, showing its relevance as a null model for cost-constrained network formation.

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.

Modelling MIZ dynamics in a global model

NASA Astrophysics Data System (ADS)

Rynders, Stefanie; Aksenov, Yevgeny; Feltham, Daniel; Nurser, George; Naveira Garabato, Alberto

2016-04-01

Exposure of large, previously ice-covered areas of the Arctic Ocean to the wind and surface ocean waves results in the Arctic pack ice cover becoming more fragmented and mobile, with large regions of ice cover evolving into the Marginal Ice Zone (MIZ). The need for better climate predictions, along with growing economic activity in the Polar Oceans, necessitates climate and forecasting models that can simulate fragmented sea ice with a greater fidelity. Current models are not fully fit for the purpose, since they neither model surface ocean waves in the MIZ, nor account for the effect of floe fragmentation on drag, nor include sea ice rheology that represents both the now thinner pack ice and MIZ ice dynamics. All these processes affect the momentum transfer to the ocean. We present initial results from a global ocean model NEMO (Nucleus for European Modelling of the Ocean) coupled to the Los Alamos sea ice model CICE. The model setup implements a novel rheological formulation for sea ice dynamics, accounting for ice floe collisions, thus offering a seamless framework for pack ice and MIZ simulations. The effect of surface waves on ice motion is included through wave pressure and the turbulent kinetic energy of ice floes. In the multidecadal model integrations we examine MIZ and basin scale sea ice and oceanic responses to the changes in ice dynamics. We analyse model sensitivities and attribute them to key sea ice and ocean dynamical mechanisms. The results suggest that the effect of the new ice rheology is confined to the MIZ. However with the current increase in summer MIZ area, which is projected to continue and may become the dominant type of sea ice in the Arctic, we argue that the effects of the combined sea ice rheology will be noticeable in large areas of the Arctic Ocean, affecting sea ice and ocean. With this study we assert that to make more accurate sea ice predictions in the changing Arctic, models need to include MIZ dynamics and physics.

A Framework of Multi Objectives Negotiation for Dynamic Supply Chain Model

NASA Astrophysics Data System (ADS)

Chai, Jia Yee; Sakaguchi, Tatsuhiko; Shirase, Keiichi

Trends of globalization and advances in Information Technology (IT) have created opportunity in collaborative manufacturing across national borders. A dynamic supply chain utilizes these advances to enable more flexibility in business cooperation. This research proposes a concurrent decision making framework for a three echelons dynamic supply chain model. The dynamic supply chain is formed by autonomous negotiation among agents based on multi agents approach. Instead of generating negotiation aspects (such as amount, price and due date) arbitrary, this framework proposes to utilize the information available at operational level of an organization in order to generate realistic negotiation aspect. The effectiveness of the proposed model is demonstrated by various case studies.

A dynamical model for bark beetle outbreaks

Treesearch

Vlastimil Krivan; Mark Lewis; Barbara J. Bentz; Sharon Bewick; Suzanne M. Lenhart; Andrew Liebhold

2016-01-01

Tree-killing bark beetles are major disturbance agents affecting coniferous forest ecosystems. The role of environmental conditions on driving beetle outbreaks is becoming increasingly important as global climatic change alters environmental factors, such as drought stress, that, in turn, govern tree resistance. Furthermore, dynamics between beetles and trees...

The Australian Computational Earth Systems Simulator

NASA Astrophysics Data System (ADS)

Mora, P.; Muhlhaus, H.; Lister, G.; Dyskin, A.; Place, D.; Appelbe, B.; Nimmervoll, N.; Abramson, D.

2001-12-01

Numerical simulation of the physics and dynamics of the entire earth system offers an outstanding opportunity for advancing earth system science and technology but represents a major challenge due to the range of scales and physical processes involved, as well as the magnitude of the software engineering effort required. However, new simulation and computer technologies are bringing this objective within reach. Under a special competitive national funding scheme to establish new Major National Research Facilities (MNRF), the Australian government together with a consortium of Universities and research institutions have funded construction of the Australian Computational Earth Systems Simulator (ACcESS). The Simulator or computational virtual earth will provide the research infrastructure to the Australian earth systems science community required for simulations of dynamical earth processes at scales ranging from microscopic to global. It will consist of thematic supercomputer infrastructure and an earth systems simulation software system. The Simulator models and software will be constructed over a five year period by a multi-disciplinary team of computational scientists, mathematicians, earth scientists, civil engineers and software engineers. The construction team will integrate numerical simulation models (3D discrete elements/lattice solid model, particle-in-cell large deformation finite-element method, stress reconstruction models, multi-scale continuum models etc) with geophysical, geological and tectonic models, through advanced software engineering and visualization technologies. When fully constructed, the Simulator aims to provide the software and hardware infrastructure needed to model solid earth phenomena including global scale dynamics and mineralisation processes, crustal scale processes including plate tectonics, mountain building, interacting fault system dynamics, and micro-scale processes that control the geological, physical and dynamic behaviour of earth systems. ACcESS represents a part of Australia's contribution to the APEC Cooperation for Earthquake Simulation (ACES) international initiative. Together with other national earth systems science initiatives including the Japanese Earth Simulator and US General Earthquake Model projects, ACcESS aims to provide a driver for scientific advancement and technological breakthroughs including: quantum leaps in understanding of earth evolution at global, crustal, regional and microscopic scales; new knowledge of the physics of crustal fault systems required to underpin the grand challenge of earthquake prediction; new understanding and predictive capabilities of geological processes such as tectonics and mineralisation.

Structural uncertainty of downscaled climate model output in a difficult-to-resolve environment: data sparseness and parameterization error contribution to statistical and dynamical downscaling output in the U.S. Caribbean region

NASA Astrophysics Data System (ADS)

Terando, A. J.; Grade, S.; Bowden, J.; Henareh Khalyani, A.; Wootten, A.; Misra, V.; Collazo, J.; Gould, W. A.; Boyles, R.

2016-12-01

Sub-tropical island nations may be particularly vulnerable to anthropogenic climate change because of predicted changes in the hydrologic cycle that would lead to significant drying in the future. However, decision makers in these regions have seen their adaptation planning efforts frustrated by the lack of island-resolving climate model information. Recently, two investigations have used statistical and dynamical downscaling techniques to develop climate change projections for the U.S. Caribbean region (Puerto Rico and U.S. Virgin Islands). We compare the results from these two studies with respect to three commonly downscaled CMIP5 global climate models (GCMs). The GCMs were dynamically downscaled at a convective-permitting scale using two different regional climate models. The statistical downscaling approach was conducted at locations with long-term climate observations and then further post-processed using climatologically aided interpolation (yielding two sets of projections). Overall, both approaches face unique challenges. The statistical approach suffers from a lack of observations necessary to constrain the model, particularly at the land-ocean boundary and in complex terrain. The dynamically downscaled model output has a systematic dry bias over the island despite ample availability of moisture in the atmospheric column. Notwithstanding these differences, both approaches are consistent in projecting a drier climate that is driven by the strong global-scale anthropogenic forcing.

The Open Global Glacier Model

NASA Astrophysics Data System (ADS)

Marzeion, B.; Maussion, F.

2017-12-01

Mountain glaciers are one of the few remaining sub-systems of the global climate system for which no globally applicable, open source, community-driven model exists. Notable examples from the ice sheet community include the Parallel Ice Sheet Model or Elmer/Ice. While the atmospheric modeling community has a long tradition of sharing models (e.g. the Weather Research and Forecasting model) or comparing them (e.g. the Coupled Model Intercomparison Project or CMIP), recent initiatives originating from the glaciological community show a new willingness to better coordinate global research efforts following the CMIP example (e.g. the Glacier Model Intercomparison Project or the Glacier Ice Thickness Estimation Working Group). In the recent past, great advances have been made in the global availability of data and methods relevant for glacier modeling, spanning glacier outlines, automatized glacier centerline identification, bed rock inversion methods, and global topographic data sets. Taken together, these advances now allow the ice dynamics of glaciers to be modeled on a global scale, provided that adequate modeling platforms are available. Here, we present the Open Global Glacier Model (OGGM), developed to provide a global scale, modular, and open source numerical model framework for consistently simulating past and future global scale glacier change. Global not only in the sense of leading to meaningful results for all glaciers combined, but also for any small ensemble of glaciers, e.g. at the headwater catchment scale. Modular to allow combinations of different approaches to the representation of ice flow and surface mass balance, enabling a new kind of model intercomparison. Open source so that the code can be read and used by anyone and so that new modules can be added and discussed by the community, following the principles of open governance. Consistent in order to provide uncertainty measures at all realizable scales.

Model projections of rapid sea-level rise on the northeast coast of the United States

NASA Astrophysics Data System (ADS)

Yin, Jianjun; Schlesinger, Michael E.; Stouffer, Ronald J.

2009-04-01

Human-induced climate change could cause global sea-level rise. Through the dynamic adjustment of the sea surface in response to a possible slowdown of the Atlantic meridional overturning circulation, a warming climate could also affect regional sea levels, especially in the North Atlantic region, leading to high vulnerability for low-lying Florida and western Europe. Here we analyse climate projections from a set of state-of-the-art climate models for such regional changes, and find a rapid dynamical rise in sea level on the northeast coast of the United States during the twenty-first century. For New York City, the rise due to ocean circulation changes amounts to 15, 20 and 21cm for scenarios with low, medium and high rates of emissions respectively, at a similar magnitude to expected global thermal expansion. Analysing one of the climate models in detail, we find that a dynamic, regional rise in sea level is induced by a weakening meridional overturning circulation in the Atlantic Ocean, and superimposed on the global mean sea-level rise. We conclude that together, future changes in sea level and ocean circulation will have a greater effect on the heavily populated northeastern United States than estimated previously.

Model Projections of Rapid Sea-Level Rise on the Northeast Coast of the United States

NASA Astrophysics Data System (ADS)

Yin, J.; Schlesinger, M.; Stouffer, R. J.

2009-12-01

Human-induced climate change could cause global sea-level rise. Through the dynamic adjustment of the sea surface in response to a possible slowdown of the Atlantic meridional overturning circulation, a warming climate could also affect regional sea levels, especially in the North Atlantic region, leading to high vulnerability for low-lying Florida and western Europe. In the present study, we analyse climate projections from a set of state-of-the-art climate models for such regional changes, and find a rapid dynamical rise in sea level on the northeast coast of the United States during the twenty-first century. For New York City, the rise due to ocean circulation changes amounts to 15, 20 and 21 cm for scenarios with low, medium and high rates of emissions respectively, at a similar magnitude to expected global thermal expansion. Analysing one of the climate models in detail, we find that a dynamic, regional rise in sea level is induced by a weakening meridional overturning circulation in the Atlantic Ocean, and superimposed on the global mean sea level rise. We conclude that together, future changes in sea level and ocean circulation will have a greater effect on the heavily populated northeastern United States than estimated previously.

ORCHIDEE-SOM: modeling soil organic carbon (SOC) and dissolved organic carbon (DOC) dynamics along vertical soil profiles in Europe

NASA Astrophysics Data System (ADS)

Camino-Serrano, Marta; Guenet, Bertrand; Luyssaert, Sebastiaan; Ciais, Philippe; Bastrikov, Vladislav; De Vos, Bruno; Gielen, Bert; Gleixner, Gerd; Jornet-Puig, Albert; Kaiser, Klaus; Kothawala, Dolly; Lauerwald, Ronny; Peñuelas, Josep; Schrumpf, Marion; Vicca, Sara; Vuichard, Nicolas; Walmsley, David; Janssens, Ivan A.

2018-03-01

Current land surface models (LSMs) typically represent soils in a very simplistic way, assuming soil organic carbon (SOC) as a bulk, and thus impeding a correct representation of deep soil carbon dynamics. Moreover, LSMs generally neglect the production and export of dissolved organic carbon (DOC) from soils to rivers, leading to overestimations of the potential carbon sequestration on land. This common oversimplified processing of SOC in LSMs is partly responsible for the large uncertainty in the predictions of the soil carbon response to climate change. In this study, we present a new soil carbon module called ORCHIDEE-SOM, embedded within the land surface model ORCHIDEE, which is able to reproduce the DOC and SOC dynamics in a vertically discretized soil to 2 m. The model includes processes of biological production and consumption of SOC and DOC, DOC adsorption on and desorption from soil minerals, diffusion of SOC and DOC, and DOC transport with water through and out of the soils to rivers. We evaluated ORCHIDEE-SOM against observations of DOC concentrations and SOC stocks from four European sites with different vegetation covers: a coniferous forest, a deciduous forest, a grassland, and a cropland. The model was able to reproduce the SOC stocks along their vertical profiles at the four sites and the DOC concentrations within the range of measurements, with the exception of the DOC concentrations in the upper soil horizon at the coniferous forest. However, the model was not able to fully capture the temporal dynamics of DOC concentrations. Further model improvements should focus on a plant- and depth-dependent parameterization of the new input model parameters, such as the turnover times of DOC and the microbial carbon use efficiency. We suggest that this new soil module, when parameterized for global simulations, will improve the representation of the global carbon cycle in LSMs, thus helping to constrain the predictions of the future SOC response to global warming.

Dynamics of global supply chain and electric power networks: Models, pricing analysis, and computations

NASA Astrophysics Data System (ADS)

Matsypura, Dmytro

In this dissertation, I develop a new theoretical framework for the modeling, pricing analysis, and computation of solutions to electric power supply chains with power generators, suppliers, transmission service providers, and the inclusion of consumer demands. In particular, I advocate the application of finite-dimensional variational inequality theory, projected dynamical systems theory, game theory, network theory, and other tools that have been recently proposed for the modeling and analysis of supply chain networks (cf. Nagurney (2006)) to electric power markets. This dissertation contributes to the extant literature on the modeling, analysis, and solution of supply chain networks, including global supply chains, in general, and electric power supply chains, in particular, in the following ways. It develops a theoretical framework for modeling, pricing analysis, and computation of electric power flows/transactions in electric power systems using the rationale for supply chain analysis. The models developed include both static and dynamic ones. The dissertation also adds a new dimension to the methodology of the theory of projected dynamical systems by proving that, irrespective of the speeds of adjustment, the equilibrium of the system remains the same. Finally, I include alternative fuel suppliers, along with their behavior into the supply chain modeling and analysis framework. This dissertation has strong practical implications. In an era in which technology and globalization, coupled with increasing risk and uncertainty, complicate electricity demand and supply within and between nations, the successful management of electric power systems and pricing become increasingly pressing topics with relevance not only for economic prosperity but also national security. This dissertation addresses such related topics by providing models, pricing tools, and algorithms for decentralized electric power supply chains. This dissertation is based heavily on the following coauthored papers: Nagurney, Cruz, and Matsypura (2003), Nagurney and Matsypura (2004, 2005, 2006), Matsypura and Nagurney (2005), Matsypura, Nagurney, and Liu (2006).

Towards a unified Global Weather-Climate Prediction System

NASA Astrophysics Data System (ADS)

Lin, S. J.

2016-12-01

The Geophysical Fluid Dynamics Laboratory has been developing a unified regional-global modeling system with variable resolution capabilities that can be used for severe weather predictions and kilometer scale regional climate simulations within a unified global modeling system. The foundation of this flexible modeling system is the nonhydrostatic Finite-Volume Dynamical Core on the Cubed-Sphere (FV3). A unique aspect of FV3 is that it is "vertically Lagrangian" (Lin 2004), essentially reducing the equation sets to two dimensions, and is the single most important reason why FV3 outperforms other non-hydrostatic cores. Owning to its accuracy, adaptability, and computational efficiency, the FV3 has been selected as the "engine" for NOAA's Next Generation Global Prediction System (NGGPS). We have built into the modeling system a stretched grid, a two-way regional-global nested grid, and an optimal combination of the stretched and two-way nests capability, making kilometer-scale regional simulations within a global modeling system feasible. Our main scientific goal is to enable simulations of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously regarded as impossible. In this presentation I will demonstrate that, with the FV3, it is computationally feasible to simulate not only super-cell thunderstorms, but also the subsequent genesis of tornado-like vortices using a global model that was originally designed for climate simulations. The development and tuning strategy between traditional weather and climate models are fundamentally different due to different metrics. We were able to adapt and use traditional "climate" metrics or standards, such as angular momentum conservation, energy conservation, and flux balance at top of the atmosphere, and gain insight into problems of traditional weather prediction model for medium-range weather prediction, and vice versa. Therefore, the unification in weather and climate models can happen not just at the algorithm or parameterization level, but also in the metric and tuning strategy used for both applications, and ultimately, with benefits to both weather and climate applications.

A global assessment of gross and net land change dynamics for current conditions and future scenarios

NASA Astrophysics Data System (ADS)

Fuchs, Richard; Prestele, Reinhard; Verburg, Peter H.

2018-05-01

The consideration of gross land changes, meaning all area gains and losses within a pixel or administrative unit (e.g. country), plays an essential role in the estimation of total land changes. Gross land changes affect the magnitude of total land changes, which feeds back to the attribution of biogeochemical and biophysical processes related to climate change in Earth system models. Global empirical studies on gross land changes are currently lacking. Whilst the relevance of gross changes for global change has been indicated in the literature, it is not accounted for in future land change scenarios. In this study, we extract gross and net land change dynamics from large-scale and high-resolution (30-100 m) remote sensing products to create a new global gross and net change dataset. Subsequently, we developed an approach to integrate our empirically derived gross and net changes with the results of future simulation models by accounting for the gross and net change addressed by the land use model and the gross and net change that is below the resolution of modelling. Based on our empirical data, we found that gross land change within 0.5° grid cells was substantially larger than net changes in all parts of the world. As 0.5° grid cells are a standard resolution of Earth system models, this leads to an underestimation of the amount of change. This finding contradicts earlier studies, which assumed gross land changes to appear in shifting cultivation areas only. Applied in a future scenario, the consideration of gross land changes led to approximately 50 % more land changes globally compared to a net land change representation. Gross land changes were most important in heterogeneous land systems with multiple land uses (e.g. shifting cultivation, smallholder farming, and agro-forestry systems). Moreover, the importance of gross changes decreased over time due to further polarization and intensification of land use. Our results serve as an empirical database for land change dynamics that can be applied in Earth system models and integrated assessment models.

Modeling infectious disease dynamics in the complex landscape of global health

PubMed Central

Heesterbeek, Hans; Anderson, Roy; Andreasen, Viggo; Bansal, Shweta; De Angelis, Daniela; Dye, Chris; Eames, Ken; Edmunds, John; Frost, Simon; Funk, Sebastian; Hollingsworth, Deirdre; House, Thomas; Isham, Valerie; Klepac, Petra; Lessler, Justin; Lloyd-Smith, James; Metcalf, Jessica; Mollison, Denis; Pellis, Lorenzo; Pulliam, Juliet; Roberts, Mick; Viboud, Cecile

2015-01-01

Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational and spatial scales, which even within a single pathogen often span hours to months, cellular to ecosystem levels, and local to pandemic spread. Some pathogens are directly transmitted between individuals of a single species, while others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity, and dynamic human behavior, raise prevention and control from formerly national to international issues. In the face of this complexity, mathematical models offer essential tools for synthesizing information to understand epidemiological patterns, and for developing the quantitative evidence base for decision-making in global health. PMID:25766240

Agreement dynamics on interaction networks with diverse topologies

NASA Astrophysics Data System (ADS)

Barrat, Alain; Baronchelli, Andrea; Dall'Asta, Luca; Loreto, Vittorio

2007-06-01

We review the behavior of a recently introduced model of agreement dynamics, called the "Naming Game." This model describes the self-organized emergence of linguistic conventions and the establishment of simple communication systems in a population of agents with pairwise local interactions. The mechanisms of convergence towards agreement strongly depend on the network of possible interactions between the agents. In particular, the mean-field case in which all agents communicate with all the others is not efficient, since a large temporary memory is requested for the agents. On the other hand, regular lattice topologies lead to a fast local convergence but to a slow global dynamics similar to coarsening phenomena. The embedding of the agents in a small-world network represents an interesting tradeoff: a local consensus is easily reached, while the long-range links allow to bypass coarsening-like convergence. We also consider alternative adaptive strategies which can lead to faster global convergence.

Dynamic Constraint Satisfaction with Reasonable Global Constraints

NASA Technical Reports Server (NTRS)

Frank, Jeremy

2003-01-01

Previously studied theoretical frameworks for dynamic constraint satisfaction problems (DCSPs) employ a small set of primitive operators to modify a problem instance. They do not address the desire to model problems using sophisticated global constraints, and do not address efficiency questions related to incremental constraint enforcement. In this paper, we extend a DCSP framework to incorporate global constraints with flexible scope. A simple approach to incremental propagation after scope modification can be inefficient under some circumstances. We characterize the cases when this inefficiency can occur, and discuss two ways to alleviate this problem: adding rejection variables to the scope of flexible constraints, and adding new features to constraints that permit increased control over incremental propagation.

Disease-induced mortality in density-dependent discrete-time S-I-S epidemic models.

PubMed

Franke, John E; Yakubu, Abdul-Aziz

2008-12-01

The dynamics of simple discrete-time epidemic models without disease-induced mortality are typically characterized by global transcritical bifurcation. We prove that in corresponding models with disease-induced mortality a tiny number of infectious individuals can drive an otherwise persistent population to extinction. Our model with disease-induced mortality supports multiple attractors. In addition, we use a Ricker recruitment function in an SIS model and obtained a three component discrete Hopf (Neimark-Sacker) cycle attractor coexisting with a fixed point attractor. The basin boundaries of the coexisting attractors are fractal in nature, and the example exhibits sensitive dependence of the long-term disease dynamics on initial conditions. Furthermore, we show that in contrast to corresponding models without disease-induced mortality, the disease-free state dynamics do not drive the disease dynamics.

Estimating forest carbon dynamics in South Korea from 1954 to 2050 - coupling global forestry model and forest soil carbon model

NASA Astrophysics Data System (ADS)

Lee, Jongyeol; Kim, Moonil; Lakyda, Ivan; Pietsch, Stephan; Shvidenko, Anatoly; Kraxner, Florian; Forsell, Nicklas; Son, Yowhan

2016-04-01

There have been demands on reporting national forest carbon (C) inventories to mitigate global climate change. Global forestry models estimate growth of stem volume and C at various spatial and temporal scales but they do not consider dead organic matter (DOM) C. In this study, we simulated national forest C dynamics in South Korea with a calibrated global forestry model (G4M model) and a module of DOM C dynamics in Korean forest C model (FBDC model). 3890 simulation units (1-16 km2) were established in entire South Korea. Growth functions of stem for major tree species (Pinus densiflora, P. rigida, Larix kaempferi, Quercus variabilis, Q. mongolica, and Q. acutissima) were estimated by internal mechanism of G4M model and Korean yield tables. C dynamics in DOMs were determined by balance between input and output (decomposition) of DOMs in the FBDC model. Annual input of DOM was estimated by multiplying C stock of biomass compartment with turnover rate. Decomposition of DOM was estimated by C stock of DOM, mean air temperature, and decay rate. C stock in each C pool was initialized by spin-up process with consideration of severe deforestation by Japanese exploitation and Korean War. No disturbance was included in the simulation process. Total forest C stock (Tg C) and mean C density (Mg C ha-1) decreased from 657.9 and 112.1 in 1954 to 607.2 and 103.4 in 1973. Especially, C stock in mineral soil decreased at a rate of 0.5 Mg C ha-1 yr-1 during the period due to suppression of regeneration. However, total forest C stock (Tg C) and mean C density (Mg C ha-1) gradually increased from 607.0 and 103.4 in 1974 to 1240.7 and 211.3 in 2015 due to the national reforestation program since 1973. After the reforestation program, Korean forests became C sinks. Model estimates were also verified by comparison of these estimates and national forest inventory data (2006-2010). High similarity between the model estimates and the inventory data showed a reliability of down-scaled global forestry model and integration of DOM C module. Finally, total C stock gradually increased to 1749.8 Tg C in 2050 at a rate of 2.5 Tg C yr-1 and it might be attributed to mature of forest. However, total forest C stock might be overestimated in the future due to the exclusion of disturbance in simulation. This study was supported by Korea Forest Service (S111315L100120) and Korean Ministry of Environment (2014001310008).

Global Analysis, Interpretation and Modelling: An Earth Systems Modelling Program

NASA Technical Reports Server (NTRS)

Moore, Berrien, III; Sahagian, Dork

1997-01-01

The Goal of the GAIM is: To advance the study of the coupled dynamics of the Earth system using as tools both data and models; to develop a strategy for the rapid development, evaluation, and application of comprehensive prognostic models of the Global Biogeochemical Subsystem which could eventually be linked with models of the Physical-Climate Subsystem; to propose, promote, and facilitate experiments with existing models or by linking subcomponent models, especially those associated with IGBP Core Projects and with WCRP efforts. Such experiments would be focused upon resolving interface issues and questions associated with developing an understanding of the prognostic behavior of key processes; to clarify key scientific issues facing the development of Global Biogeochemical Models and the coupling of these models to General Circulation Models; to assist the Intergovernmental Panel on Climate Change (IPCC) process by conducting timely studies that focus upon elucidating important unresolved scientific issues associated with the changing biogeochemical cycles of the planet and upon the role of the biosphere in the physical-climate subsystem, particularly its role in the global hydrological cycle; and to advise the SC-IGBP on progress in developing comprehensive Global Biogeochemical Models and to maintain scientific liaison with the WCRP Steering Group on Global Climate Modelling.

Nitrogen attenuation of terrestrial carbon cycle response to global environmental factors

USGS Publications Warehouse

Jain, A.A.; Yang, Xiaojuan; Kheshgi, H.; McGuire, A. David; Post, W.; Kicklighter, David W.

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 availability influences terrestrial carbon sinks and sources in response to changes over the 20th century in global environmental factors including atmospheric CO2 concentration, nitrogen inputs, temperature, precipitation and land use. The two versions of ISAM vary in their treatment of nitrogen availability: ISAM-NC has a terrestrial carbon cycle model coupled to a fully dynamic nitrogen cycle while ISAM-C has an identical carbon cycle model but nitrogen availability is always in sufficient supply. Overall, the two versions of the model estimate approximately the same amount of global mean carbon uptake over the 20th century. However, comparisons of results of ISAM-NC relative to ISAM-C reveal that nitrogen dynamics: (1) reduced the 1990s carbon sink associated with increasing atmospheric CO2 by 0.53 PgC yr−1 (1 Pg = 1015g), (2) reduced the 1990s carbon source associated with changes in temperature and precipitation of 0.34 PgC yr−1 in the 1990s, (3) an enhanced sink associated with nitrogen inputs by 0.26 PgC yr−1, and (4) enhanced the 1990s carbon source associated with changes in land use by 0.08 PgC yr−1 in the 1990s. These effects of nitrogen limitation influenced the spatial distribution of the estimated exchange of CO2 with greater sink activity in high latitudes associated with climate effects and a smaller sink of CO2 in the southeastern United States caused by N limitation associated with both CO2 fertilization and forest regrowth. These results indicate that the dynamics of nitrogen availability are important to consider in assessing the spatial distribution and temporal dynamics of terrestrial carbon sources and sinks.

The importance of vertical resolution in the free troposphere for modeling intercontinental plumes

NASA Astrophysics Data System (ADS)

Zhuang, Jiawei; Jacob, Daniel J.; Eastham, Sebastian D.

2018-05-01

Chemical plumes in the free troposphere can preserve their identity for more than a week as they are transported on intercontinental scales. Current global models cannot reproduce this transport. The plumes dilute far too rapidly due to numerical diffusion in sheared flow. We show how model accuracy can be limited by either horizontal resolution (Δx) or vertical resolution (Δz). Balancing horizontal and vertical numerical diffusion, and weighing computational cost, implies an optimal grid resolution ratio (Δx / Δz)opt ˜ 1000 for simulating the plumes. This is considerably higher than current global models (Δx / Δz ˜ 20) and explains the rapid plume dilution in the models as caused by insufficient vertical resolution. Plume simulations with the Geophysical Fluid Dynamics Laboratory Finite-Volume Cubed-Sphere Dynamical Core (GFDL-FV3) over a range of horizontal and vertical grid resolutions confirm this limiting behavior. Our highest-resolution simulation (Δx ≈ 25 km, Δz ≈ 80 m) preserves the maximum mixing ratio in the plume to within 35 % after 8 days in strongly sheared flow, a drastic improvement over current models. Adding free tropospheric vertical levels in global models is computationally inexpensive and would also improve the simulation of water vapor.

Effects of deterministic and random refuge in a prey-predator model with parasite infection.

PubMed

Mukhopadhyay, B; Bhattacharyya, R

2012-09-01

Most natural ecosystem populations suffer from various infectious diseases and the resulting host-pathogen dynamics is dependent on host's characteristics. On the other hand, empirical evidences show that for most host pathogen systems, a part of the host population always forms a refuge. To study the role of refuge on the host-pathogen interaction, we study a predator-prey-pathogen model where the susceptible and the infected prey can undergo refugia of constant size to evade predator attack. The stability aspects of the model system is investigated from a local and global perspective. The study reveals that the refuge sizes for the susceptible and the infected prey are the key parameters that control possible predator extinction as well as species co-existence. Next we perform a global study of the model system using Lyapunov functions and show the existence of a global attractor. Finally we perform a stochastic extension of the basic model to study the phenomenon of random refuge arising from various intrinsic, habitat-related and environmental factors. The stochastic model is analyzed for exponential mean square stability. Numerical study of the stochastic model shows that increasing the refuge rates has a stabilizing effect on the stochastic dynamics. Copyright © 2012 Elsevier Inc. All rights reserved.

Towards a physical understanding of stratospheric cooling under global warming through a process-based decomposition method

NASA Astrophysics Data System (ADS)

Yang, Yang; Ren, R.-C.; Cai, Ming

2016-12-01

The stratosphere has been cooling under global warming, the causes of which are not yet well understood. This study applied a process-based decomposition method (CFRAM; Coupled Surface-Atmosphere Climate Feedback Response Analysis Method) to the simulation results of a Coupled Model Intercomparison Project, phase 5 (CMIP5) model (CCSM4; Community Climate System Model, version 4), to demonstrate the responsible radiative and non-radiative processes involved in the stratospheric cooling. By focusing on the long-term stratospheric temperature changes between the "historical run" and the 8.5 W m-2 Representative Concentration Pathway (RCP8.5) scenario, this study demonstrates that the changes of radiative radiation due to CO2, ozone and water vapor are the main divers of stratospheric cooling in both winter and summer. They contribute to the cooling changes by reducing the net radiative energy (mainly downward radiation) received by the stratospheric layer. In terms of the global average, their contributions are around -5, -1.5, and -1 K, respectively. However, the observed stratospheric cooling is much weaker than the cooling by radiative processes. It is because changes in atmospheric dynamic processes act to strongly mitigate the radiative cooling by yielding a roughly 4 K warming on the global average base. In particular, the much stronger/weaker dynamic warming in the northern/southern winter extratropics is associated with an increase of the planetary-wave activity in the northern winter, but a slight decrease in the southern winter hemisphere, under global warming. More importantly, although radiative processes dominate the stratospheric cooling, the spatial patterns are largely determined by the non-radiative effects of dynamic processes.

Propagation, cascades, and agreement dynamics in complex communication and social networks

NASA Astrophysics Data System (ADS)

Lu, Qiming

Many modern and important technological, social, information and infrastructure systems can be viewed as complex systems with a large number of interacting components. Models of complex networks and dynamical interactions, as well as their applications are of fundamental interests in many aspects. Here, several stylized models of multiplex propagation and opinion dynamics are investigated on complex and empirical social networks. We first investigate cascade dynamics in threshold-controlled (multiplex) propagation on random geometric networks. We find that such local dynamics can serve as an efficient, robust, and reliable prototypical activation protocol in sensor networks in responding to various alarm scenarios. We also consider the same dynamics on a modified network by adding a few long-range communication links, resulting in a small-world network. We find that such construction can further enhance and optimize the speed of the network's response, while keeping energy consumption at a manageable level. We also investigate a prototypical agent-based model, the Naming Game, on two-dimensional random geometric networks. The Naming Game [A. Baronchelli et al., J. Stat. Mech.: Theory Exp. (2006) P06014.] is a minimal model, employing local communications that captures the emergence of shared communication schemes (languages) in a population of autonomous semiotic agents. Implementing the Naming Games with local broadcasts on random geometric graphs, serves as a model for agreement dynamics in large-scale, autonomously operating wireless sensor networks. Further, it captures essential features of the scaling properties of the agreement process for spatially-embedded autonomous agents. Among the relevant observables capturing the temporal properties of the agreement process, we investigate the cluster-size distribution and the distribution of the agreement times, both exhibiting dynamic scaling. We also present results for the case when a small density of long-range communication links are added on top of the random geometric graph, resulting in a "small-world"-like network and yielding a significantly reduced time to reach global agreement. We construct a finite-size scaling analysis for the agreement times in this case. When applying the model of Naming Game on empirical social networks, this stylized agent-based model captures essential features of agreement dynamics in a network of autonomous agents, corresponding to the development of shared classification schemes in a network of artificial agents or opinion spreading and social dynamics in social networks. Our study focuses on the impact that communities in the underlying social graphs have on the outcome of the agreement process. We find that networks with strong community structure hinder the system from reaching global agreement; the evolution of the Naming Game in these networks maintains clusters of coexisting opinions indefinitely. Further, we investigate agent-based network strategies to facilitate convergence to global consensus.

Middle Atmosphere Dynamics with Gravity Wave Interactions in the Numerical Spectral Model: Tides and Planetary Waves

NASA Technical Reports Server (NTRS)

Mayr, Hans G.; Mengel, J. G.; Chan, K. L.; Huang, F. T.

2010-01-01

As Lindzen (1981) had shown, small-scale gravity waves (GW) produce the observed reversals of the zonal-mean circulation and temperature variations in the upper mesosphere. The waves also play a major role in modulating and amplifying the diurnal tides (DT) (e.g., Waltersheid, 1981; Fritts and Vincent, 1987; Fritts, 1995a). We summarize here the modeling studies with the mechanistic numerical spectral model (NSM) with Doppler spread parameterization for GW (Hines, 1997a, b), which describes in the middle atmosphere: (a) migrating and non-migrating DT, (b) planetary waves (PW), and (c) global-scale inertio gravity waves. Numerical experiments are discussed that illuminate the influence of GW filtering and nonlinear interactions between DT, PW, and zonal mean variations. Keywords: Theoretical modeling, Middle atmosphere dynamics, Gravity wave interactions, Migrating and non-migrating tides, Planetary waves, Global-scale inertio gravity waves.

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

Franović, Igor, E-mail: franovic@ipb.ac.rs; Todorović, Kristina; Burić, Nikola

We use the mean-field approach to analyze the collective dynamics in macroscopic networks of stochastic Fitzhugh-Nagumo units with delayed couplings. The conditions for validity of the two main approximations behind the model, called the Gaussian approximation and the Quasi-independence approximation, are examined. It is shown that the dynamics of the mean-field model may indicate in a self-consistent fashion the parameter domains where the Quasi-independence approximation fails. Apart from a network of globally coupled units, we also consider the paradigmatic setup of two interacting assemblies to demonstrate how our framework may be extended to hierarchical and modular networks. In both cases,more » the mean-field model can be used to qualitatively analyze the stability of the system, as well as the scenarios for the onset and the suppression of the collective mode. In quantitative terms, the mean-field model is capable of predicting the average oscillation frequency corresponding to the global variables of the exact system.« less

An enhanced model of land water and energy for global hydrologic and earth-system studies

USGS Publications Warehouse

Milly, Paul C.D.; Malyshev, Sergey L.; Shevliakova, Elena; Dunne, Krista A.; Findell, Kirsten L.; Gleeson, Tom; Liang, Zhi; Phillips, Peter; Stouffer, Ronald J.; Swenson, Sean

2014-01-01

LM3 is a new model of terrestrial water, energy, and carbon, intended for use in global hydrologic analyses and as a component of earth-system and physical-climate models. It is designed to improve upon the performance and to extend the scope of the predecessor Land Dynamics (LaD) and LM3V models by better quantifying the physical controls of climate and biogeochemistry and by relating more directly to components of the global water system that touch human concerns. LM3 includes multilayer representations of temperature, liquid water content, and ice content of both snowpack and macroporous soil–bedrock; topography-based description of saturated area and groundwater discharge; and transport of runoff to the ocean via a global river and lake network. Sensible heat transport by water mass is accounted throughout for a complete energy balance. Carbon and vegetation dynamics and biophysics are represented as in LM3V. In numerical experiments, LM3 avoids some of the limitations of the LaD model and provides qualitatively (though not always quantitatively) reasonable estimates, from a global perspective, of observed spatial and/or temporal variations of vegetation density, albedo, streamflow, water-table depth, permafrost, and lake levels. Amplitude and phase of annual cycle of total water storage are simulated well. Realism of modeled lake levels varies widely. The water table tends to be consistently too shallow in humid regions. Biophysical properties have an artificial stepwise spatial structure, and equilibrium vegetation is sensitive to initial conditions. Explicit resolution of thick (>100 m) unsaturated zones and permafrost is possible, but only at the cost of long (≫300 yr) model spinup times.

Non-dynamic decimeter tracking of earth satellites using the Global Positioning System

NASA Technical Reports Server (NTRS)

Yunck, T. P.; Wu, S. C.

1986-01-01

A technique is described for employing the Global Positioning System (GPS) to determine the position of a low earth orbiter with decimeter accuracy without the need for user dynamic models. A differential observing strategy is used requiring a GPS receiver on the user vehicle and a network of six ground receivers. The technique uses the continuous record of position change obtained from GPS carrier phase to smooth position measurements made with pseudo-range. The result is a computationally efficient technique that can deliver decimeter accuracy down to the lowest altitude orbits.

Complex dynamics of an SEIR epidemic model with saturated incidence rate and treatment

NASA Astrophysics Data System (ADS)

Khan, Muhammad Altaf; Khan, Yasir; Islam, Saeed

2018-03-01

In this paper, we describe the dynamics of an SEIR epidemic model with saturated incidence, treatment function, and optimal control. Rigorous mathematical results have been established for the model. The stability analysis of the model is investigated and found that the model is locally asymptotically stable when R0 < 1. The model is locally as well as globally asymptotically stable at endemic equilibrium when R0 > 1. The proposed model may possess a backward bifurcation. The optimal control problem is designed and obtained their necessary results. Numerical results have been presented for justification of theoretical results.

The role of sea ice dynamics in global climate change

NASA Technical Reports Server (NTRS)

Hibler, William D., III

1992-01-01

The topics covered include the following: general characteristics of sea ice drift; sea ice rheology; ice thickness distribution; sea ice thermodynamic models; equilibrium thermodynamic models; effect of internal brine pockets and snow cover; model simulations of Arctic Sea ice; and sensitivity of sea ice models to climate change.

Spatiotemporal splitting of global eigenmodes due to cross-field coupling via vortex dynamics in drift wave turbulence.

PubMed

Brandt, C; Thakur, S C; Light, A D; Negrete, J; Tynan, G R

2014-12-31

Spatiotemporal splitting events of drift wave (DW) eigenmodes due to nonlinear coupling are investigated in a cylindrical helicon plasma device. DW eigenmodes in the radial-azimuthal cross section have been experimentally observed to split at radial locations and recombine into the global eigenmode with a time shorter than the typical DW period (t≪fDW(-1)). The number of splits correlates with the increase of turbulence. The observed dynamics can be theoretically reproduced by a Kuramoto-type model of a network of radially coupled azimuthal eigenmodes. Coupling by E×B-vortex convection cell dynamics and ion gyro radii motion leads to cross-field synchronization and occasional mode splitting events.

Fluctuations of global energy release and crackling in nominally brittle heterogeneous fracture.

PubMed

Barés, J; Hattali, M L; Dalmas, D; Bonamy, D

2014-12-31

The temporal evolution of mechanical energy and spatially averaged crack speed are both monitored in slowly fracturing artificial rocks. Both signals display an irregular burstlike dynamics, with power-law distributed fluctuations spanning a broad range of scales. Yet, the elastic power released at each time step is proportional to the global velocity all along the process, which enables defining a material-constant fracture energy. We characterize the intermittent dynamics by computing the burst statistics. This latter displays the scale-free features signature of crackling dynamics, in qualitative but not quantitative agreement with the depinning interface models derived for fracture problems. The possible sources of discrepancies are pointed out and discussed.

The physics of interstellar shock waves

NASA Technical Reports Server (NTRS)

Shull, J. Michael; Draine, Bruce T.

1987-01-01

This review discusses the observations and theoretical models of interstellar shock waves, in both diffuse cloud and molecular cloud environments. It summarizes the relevant gas dynamics, atomic, molecular and grain processes, radiative transfer, and physics of radiative and magnetic precursors in shock models. It then describes the importance of shocks for observations, diagnostics, and global interstellar dynamics. It concludes with current research problems and data needs for atomic, molecular and grain physics.

Evolutionary optimization with data collocation for reverse engineering of biological networks.

PubMed

Tsai, Kuan-Yao; Wang, Feng-Sheng

2005-04-01

Modern experimental biology is moving away from analyses of single elements to whole-organism measurements. Such measured time-course data contain a wealth of information about the structure and dynamic of the pathway or network. The dynamic modeling of the whole systems is formulated as a reverse problem that requires a well-suited mathematical model and a very efficient computational method to identify the model structure and parameters. Numerical integration for differential equations and finding global parameter values are still two major challenges in this field of the parameter estimation of nonlinear dynamic biological systems. We compare three techniques of parameter estimation for nonlinear dynamic biological systems. In the proposed scheme, the modified collocation method is applied to convert the differential equations to the system of algebraic equations. The observed time-course data are then substituted into the algebraic system equations to decouple system interactions in order to obtain the approximate model profiles. Hybrid differential evolution (HDE) with population size of five is able to find a global solution. The method is not only suited for parameter estimation but also can be applied for structure identification. The solution obtained by HDE is then used as the starting point for a local search method to yield the refined estimates.

Chaos and simple determinism in reversed field pinch plasmas: Nonlinear analysis of numerical simulation and experimental data

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

Watts, Christopher A.

In this dissertation the possibility that chaos and simple determinism are governing the dynamics of reversed field pinch (RFP) plasmas is investigated. To properly assess this possibility, data from both numerical simulations and experiment are analyzed. A large repertoire of nonlinear analysis techniques is used to identify low dimensional chaos in the data. These tools include phase portraits and Poincare sections, correlation dimension, the spectrum of Lyapunov exponents and short term predictability. In addition, nonlinear noise reduction techniques are applied to the experimental data in an attempt to extract any underlying deterministic dynamics. Two model systems are used to simulatemore » the plasma dynamics. These are the DEBS code, which models global RFP dynamics, and the dissipative trapped electron mode (DTEM) model, which models drift wave turbulence. Data from both simulations show strong indications of low dimensional chaos and simple determinism. Experimental date were obtained from the Madison Symmetric Torus RFP and consist of a wide array of both global and local diagnostic signals. None of the signals shows any indication of low dimensional chaos or low simple determinism. Moreover, most of the analysis tools indicate the experimental system is very high dimensional with properties similar to noise. Nonlinear noise reduction is unsuccessful at extracting an underlying deterministic system.« less

Self-Consistent Ring Current Modeling with Propagating Electromagnetic Ion Cyclotron Waves in the Presence of Heavy Ions

NASA Technical Reports Server (NTRS)

Khazanov, G. V.; Gamayunov, K. V.; Gallagher, D. L.; Kozyra, J. U.; Liemohn, M. W.

2006-01-01

The self-consistent treatment of the RC ion dynamics and EMlC waves, which are thought to exert important influences on the ion dynamical evolution, is an important missing element in our understanding of the storm-and recovery-time ring current evolution. Under certain conditions, relativistic electrons, with energies greater than or equal to 1 MeV, can be removed from the outer radiation belt by EMlC wave scattering during a magnetic storm (Summers and Thorne, 2003; Albert, 2003). That is why the modeling of EMlC waves is critical and timely issue in magnetospheric physics. This study will generalize the self-consistent theoretical description of RC ions and EMlC waves that has been developed by Khazanov et al. [2002, 2003] and include the heavy ions and propagation effects of EMlC waves in the global dynamic of self-consistent RC - EMlC waves coupling. The results of our newly developed model that will be presented at Huntsville 2006 meeting, focusing mainly on the dynamic of EMlC waves and comparison of these results with the previous global RC modeling studies devoted to EMlC waves formation. We also discuss RC ion precipitations and wave induced thermal electron fluxes into the ionosphere.

Analysis of the Effects of Surface Pitting and Wear on the Vibrations of a Gear Transmission System

NASA Technical Reports Server (NTRS)

Choy, F. K.; Polyshchuk, V.; Zakrajsek, J. J.; Handschuh, R. F.; Townsend, D. P.

1994-01-01

A comprehensive procedure to simulate and analyze the vibrations in a gear transmission system with surface pitting, 'wear' and partial tooth fracture of the gear teeth is presented. An analytical model was developed where the effects of surface pitting and wear of the gear tooth were simulated by phase and magnitude changes in the gear mesh stiffness. Changes in the gear mesh stiffness were incorporated into each gear-shaft model during the global dynamic simulation of the system. The overall dynamics of the system were evaluated by solving for the transient dynamics of each shaft system simultaneously with the vibration of the gearbox structure. In order to reduce the number of degrees-of-freedom in the system, a modal synthesis procedure was used in the global transient dynamic analysis of the overall transmission system. An FFT procedure was used to transform the averaged time signal into the frequency domain for signature analysis. In addition, the Wigner-Ville distribution was also introduced to examine the gear vibration in the joint time frequency domain for vibration pattern recognition. Experimental results obtained from a gear fatigue test rig at NASA Lewis Research Center were used to evaluate the analytical model.

Global identification of stochastic dynamical systems under different pseudo-static operating conditions: The functionally pooled ARMAX case

NASA Astrophysics Data System (ADS)

Sakellariou, J. S.; Fassois, S. D.

2017-01-01

The identification of a single global model for a stochastic dynamical system operating under various conditions is considered. Each operating condition is assumed to have a pseudo-static effect on the dynamics and be characterized by a single measurable scheduling variable. Identification is accomplished within a recently introduced Functionally Pooled (FP) framework, which offers a number of advantages over Linear Parameter Varying (LPV) identification techniques. The focus of the work is on the extension of the framework to include the important FP-ARMAX model case. Compared to their simpler FP-ARX counterparts, FP-ARMAX models are much more general and offer improved flexibility in describing various types of stochastic noise, but at the same time lead to a more complicated, non-quadratic, estimation problem. Prediction Error (PE), Maximum Likelihood (ML), and multi-stage estimation methods are postulated, and the PE estimator optimality, in terms of consistency and asymptotic efficiency, is analytically established. The postulated estimators are numerically assessed via Monte Carlo experiments, while the effectiveness of the approach and its superiority over its FP-ARX counterpart are demonstrated via an application case study pertaining to simulated railway vehicle suspension dynamics under various mass loading conditions.

WHO WOULD EAT IN A WORLD WITHOUT PHOSPHORUS? A GLOBAL DYNAMIC MODEL

NASA Astrophysics Data System (ADS)

Dumas, M.

2009-12-01

Phosphorus is an indispensable and non-substitutable resource, as agriculture is impossible if soils do not hold adequate amounts of this nutrient. Phosphorus is also considered to be a non-renewable and increasingly scarce resource, as phosphate rock reserves - as one measure of availability amongst others - are estimated to last for 50 to 100 years at current rates of consumption. How would food production decline in different parts of the world in the scenario of a sudden shortage in phosphorus? To answer this question and explore management scenarios, I present a probabilistic model of the structure and dynamics of the global P cycle in the world’s agro-ecosystems. The model proposes an original solution to the challenge of capturing the large-scale aggregate dynamics of multiple micro-scale soil cycling processes. Furthermore, it integrates the essential natural processes with a model of human-managed flows, thereby bringing together several decades of research and measurements from soil science, plant nutrition and long-term agricultural experiments from around the globe. In this paper, I present the model, the first simulation results and the implications for long-term sustainable management of phosphorus and soil fertility.

Challenges in global modeling of wetland extent and wetland methane dynamics

NASA Astrophysics Data System (ADS)

Spahni, R.; Melton, J. R.; Wania, R.; Stocker, B. D.; Zürcher, S.; Joos, F.

2012-12-01

Global wetlands are known to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. Modelling of global wetland extent and wetland CH4 dynamics remains a challenge. Here we present results from the Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) that investigated our present ability to simulate large scale wetland characteristics (e.g. wetland type, water table, carbon cycling, gas transport, etc.) and corresponding CH4 emissions. Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The WETCHIMP experiments showed that while models disagree in spatial and temporal patterns of simulated CH4 emissions and wetland areal extent, they all do agree on a strong positive response to increased carbon dioxide concentrations. WETCHIMP made clear that we currently lack observation data sets that are adequate to evaluate model CH4 soil-atmosphere fluxes at a spatial scale comparable to model grid cells. Thus there are substantial parameter and structural uncertainties in large-scale CH4 emission models. As an illustration of the implications of CH4 emissions on climate we show results of the LPX-Bern model, as one of the models participating in WETCHIMP. LPX-Bern is forced with observed 20th century climate and climate output from an ensemble of five comprehensive climate models for a low and a high emission scenario till 2100 AD. In the high emission scenario increased substrate availability for methanogenesis due to a strong stimulation of net primary productivity, and faster soil turnover leads to an amplification of CH4 emissions with the sharpest increase in peatlands (+180% compared to present). Combined with prescribed anthropogenic CH4 emissions, simulated atmospheric CH4 concentration reaches ~4500 ppbv by 2100 AD, about 800 ppbv more than in standard IPCC scenarios. This represents a significant contribution to radiative forcing of global climate.

Event-chain algorithm for the Heisenberg model: Evidence for z≃1 dynamic scaling.

PubMed

Nishikawa, Yoshihiko; Michel, Manon; Krauth, Werner; Hukushima, Koji

2015-12-01

We apply the event-chain Monte Carlo algorithm to the three-dimensional ferromagnetic Heisenberg model. The algorithm is rejection-free and also realizes an irreversible Markov chain that satisfies global balance. The autocorrelation functions of the magnetic susceptibility and the energy indicate a dynamical critical exponent z≈1 at the critical temperature, while that of the magnetization does not measure the performance of the algorithm. We show that the event-chain Monte Carlo algorithm substantially reduces the dynamical critical exponent from the conventional value of z≃2.

Identity Formation of American Indian Adolescents: Local, National, and Global Considerations

ERIC Educational Resources Information Center

Markstrom, Carol A.

2011-01-01

A conceptual model is presented that approaches identity formation of American Indian adolescents according to 3 levels of social contextual influence--local, national, and global--relative to types of identity, dynamics of identity, and sources of influence. Ethnic identity of American Indians is embedded within the local cultural milieu and…

Dynamics of epidemic spreading model with drug-resistant variation on scale-free networks

NASA Astrophysics Data System (ADS)

Wan, Chen; Li, Tao; Zhang, Wu; Dong, Jing

2018-03-01

Considering the influence of the virus' drug-resistant variation, a novel SIVRS (susceptible-infected-variant-recovered-susceptible) epidemic spreading model with variation characteristic on scale-free networks is proposed in this paper. By using the mean-field theory, the spreading dynamics of the model is analyzed in detail. Then, the basic reproductive number R0 and equilibriums are derived. Studies show that the existence of disease-free equilibrium is determined by the basic reproductive number R0. The relationships between the basic reproductive number R0, the variation characteristic and the topology of the underlying networks are studied in detail. Furthermore, our studies prove the global stability of the disease-free equilibrium, the permanence of epidemic and the global attractivity of endemic equilibrium. Numerical simulations are performed to confirm the analytical results.

Ring Current Ion Coupling with Electromagnetic Ion Cyclotron Waves

NASA Technical Reports Server (NTRS)

Khazanov, George V.

2002-01-01

A new ring current global model has been developed for the first time that couples the system of two kinetic equations: one equation describes the ring current (RC) ion dynamic, and another equation describes wave evolution of electromagnetic ion cyclotron waves (EMIC). The coupled model is able to simulate, for the first time self-consistently calculated RC ion kinetic and evolution of EMIC waves that propagate along geomagnetic field lines and reflect from the ionosphere. Ionospheric properties affect the reflection index through the integral Pedersen and Hall coductivities. The structure and dynamics of the ring current proton precipitating flux regions, intensities of EMIC, global RC energy balance, and some other parameters will be studied in detail for the selected geomagnetic storms. The space whether aspects of RC modelling and comparison with the data will also be discussed.

Improved treatment of optics in the Lindquist-Wheeler models

NASA Astrophysics Data System (ADS)

Clifton, Timothy; Ferreira, Pedro G.; O'Donnell, Kane

2012-01-01

We consider the optical properties of Lindquist-Wheeler (LW) models of the Universe. These models consist of lattices constructed from regularly arranged discrete masses. They are akin to the Wigner-Seitz construction of solid state physics, and result in a dynamical description of the large-scale Universe in which the global expansion is given by a Friedmann-like equation. We show that if these models are constructed in a particular way then the redshifts of distant objects, as well as the dynamics of the global space-time, can be made to be in good agreement with the homogeneous and isotropic Friedmann-Lemaître-Robertson-Walker (FLRW) solutions of Einstein’s equations, at the level of ≲3% out to z≃2. Angular diameter and luminosity distances, on the other hand, differ from those found in the corresponding FLRW models, while being consistent with the “empty beam” approximation, together with the shearing effects due to the nearest masses. This can be compared with the large deviations found from the corresponding FLRW values obtained in a previous study that considered LW models constructed in a different way. We therefore advocate the improved LW models we consider here as useful constructions that appear to faithfully reproduce both the dynamical and observational properties of space-times containing discrete masses.

Evaluations of high-resolution dynamically downscaled ensembles over the contiguous United States Climate Dynamics

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

Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.

This study uses Weather Research and Forecast (WRF) model to evaluate the performance of six dynamical downscaled decadal historical simulations with 12-km resolution for a large domain (7200 x 6180 km) that covers most of North America. The initial and boundary conditions are from three global climate models (GCMs) and one reanalysis data. The GCMs employed in this study are the Geophysical Fluid Dynamics Laboratory Earth System Model with Generalized Ocean Layer Dynamics component, Community Climate System Model, version 4, and the Hadley Centre Global Environment Model, version 2-Earth System. The reanalysis data is from the National Centers for Environmentalmore » Prediction-US. Department of Energy Reanalysis II. We analyze the effects of bias correcting, the lateral boundary conditions and the effects of spectral nudging. We evaluate the model performance for seven surface variables and four upper atmospheric variables based on their climatology and extremes for seven subregions across the United States. The results indicate that the simulation’s performance depends on both location and the features/variable being tested. We find that the use of bias correction and/or nudging is beneficial in many situations, but employing these when running the RCM is not always an improvement when compared to the reference data. The use of an ensemble mean and median leads to a better performance in measuring the climatology, while it is significantly biased for the extremes, showing much larger differences than individual GCM driven model simulations from the reference data. This study provides a comprehensive evaluation of these historical model runs in order to make informed decisions when making future projections.« less

Dynamic Model for Life History of Scyphozoa

PubMed Central

Xie, Congbo; Fan, Meng; Wang, Xin; Chen, Ming

2015-01-01

A two-state life history model governed by ODEs is formulated to elucidate the population dynamics of jellyfish and to illuminate the triggering mechanism of its blooms. The polyp-medusa model admits trichotomous global dynamic scenarios: extinction, polyps survival only, and both survival. The population dynamics sensitively depend on several biotic and abiotic limiting factors such as substrate, temperature, and predation. The combination of temperature increase, substrate expansion, and predator diminishment acts synergistically to create a habitat that is more favorable for jellyfishes. Reducing artificial marine constructions, aiding predator populations, and directly controlling the jellyfish population would help to manage the jellyfish blooms. The theoretical analyses and numerical experiments yield several insights into the nature underlying the model and shed some new light on the general control strategy for jellyfish. PMID:26114642

Dynamic Model for Life History of Scyphozoa.

PubMed

Xie, Congbo; Fan, Meng; Wang, Xin; Chen, Ming

2015-01-01

A two-state life history model governed by ODEs is formulated to elucidate the population dynamics of jellyfish and to illuminate the triggering mechanism of its blooms. The polyp-medusa model admits trichotomous global dynamic scenarios: extinction, polyps survival only, and both survival. The population dynamics sensitively depend on several biotic and abiotic limiting factors such as substrate, temperature, and predation. The combination of temperature increase, substrate expansion, and predator diminishment acts synergistically to create a habitat that is more favorable for jellyfishes. Reducing artificial marine constructions, aiding predator populations, and directly controlling the jellyfish population would help to manage the jellyfish blooms. The theoretical analyses and numerical experiments yield several insights into the nature underlying the model and shed some new light on the general control strategy for jellyfish.

Spatio-temporal patterns and climate variables controlling of biomass carbon stock of global grassland ecosystems from 1982 to 2006

USGS Publications Warehouse

Xia, Jiangzhou; Liu, Shuguang; Liang, Shunlin; Chen, Yang; Xu, Wenfang; Yuan, Wenping

2014-01-01

Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, Normalized Difference Vegetation Index (NDVI) time series from satellite data, climate reanalysis data, and a satellite-based statistical model. Results showed that the NDVI-based biomass carbon model developed from this study explained 60% of the variance across 38 sites globally. The global carbon stock in grassland aboveground live biomass was 1.05 Pg·C, averaged from 1982 to 2006, and increased at a rate of 2.43 Tg·C·y−1 during this period. Temporal change of the global biomass was significantly and positively correlated with temperature and precipitation. The distribution of biomass carbon density followed the precipitation gradient. The dynamics of regional grassland biomass showed various trends largely determined by regional climate variability, disturbances, and management practices (such as grazing for meat production). The methods and results from this study can be used to monitor the dynamics of grassland aboveground biomass and evaluate grassland susceptibility to climate variability and change, disturbances, and management.

Exploring the Common Dynamics of Homologous Proteins. Application to the Globin Family

PubMed Central

Maguid, Sandra; Fernandez-Alberti, Sebastian; Ferrelli, Leticia; Echave, Julian

2005-01-01

We present a procedure to explore the global dynamics shared between members of the same protein family. The method allows the comparison of patterns of vibrational motion obtained by Gaussian network model analysis. After the identification of collective coordinates that were conserved during evolution, we quantify the common dynamics within a family. Representative vectors that describe these dynamics are defined using a singular value decomposition approach. As a test case, the globin heme-binding family is considered. The two lowest normal modes are shown to be conserved within this family. Our results encourage the development of models for protein evolution that take into account the conservation of dynamical features. PMID:15749782

Spreading dynamics of an e-commerce preferential information model on scale-free networks

NASA Astrophysics Data System (ADS)

Wan, Chen; Li, Tao; Guan, Zhi-Hong; Wang, Yuanmei; Liu, Xiongding

2017-02-01

In order to study the influence of the preferential degree and the heterogeneity of underlying networks on the spread of preferential e-commerce information, we propose a novel susceptible-infected-beneficial model based on scale-free networks. The spreading dynamics of the preferential information are analyzed in detail using the mean-field theory. We determine the basic reproductive number and equilibria. The theoretical analysis indicates that the basic reproductive number depends mainly on the preferential degree and the topology of the underlying networks. We prove the global stability of the information-elimination equilibrium. The permanence of preferential information and the global attractivity of the information-prevailing equilibrium are also studied in detail. Some numerical simulations are presented to verify the theoretical results.

MODELING DYNAMIC VEGETATION RESPONSE TO RAPID CLIMATE CHANGE USING BIOCLIMATIC CLASSIFICATION

EPA Science Inventory

Modeling potential global redistribution of terrestrial vegetation frequently is based on bioclimatic classifications which relate static regional vegetation zones (biomes) to a set of static climate parameters. The equilibrium character of the relationships limits our confidence...

A methodology for global-sensitivity analysis of time-dependent outputs in systems biology modelling.

PubMed

Sumner, T; Shephard, E; Bogle, I D L

2012-09-07

One of the main challenges in the development of mathematical and computational models of biological systems is the precise estimation of parameter values. Understanding the effects of uncertainties in parameter values on model behaviour is crucial to the successful use of these models. Global sensitivity analysis (SA) can be used to quantify the variability in model predictions resulting from the uncertainty in multiple parameters and to shed light on the biological mechanisms driving system behaviour. We present a new methodology for global SA in systems biology which is computationally efficient and can be used to identify the key parameters and their interactions which drive the dynamic behaviour of a complex biological model. The approach combines functional principal component analysis with established global SA techniques. The methodology is applied to a model of the insulin signalling pathway, defects of which are a major cause of type 2 diabetes and a number of key features of the system are identified.

Multiscale System for Environmentally-Driven Infectious Disease with Threshold Control Strategy

NASA Astrophysics Data System (ADS)

Sun, Xiaodan; Xiao, Yanni

A multiscale system for environmentally-driven infectious disease is proposed, in which control measures at three different scales are implemented when the number of infected hosts exceeds a certain threshold. Our coupled model successfully describes the feedback mechanisms of between-host dynamics on within-host dynamics by employing one-scale variable guided enhancement of interventions on other scales. The modeling approach provides a novel idea of how to link the large-scale dynamics to small-scale dynamics. The dynamic behaviors of the multiscale system on two time-scales, i.e. fast system and slow system, are investigated. The slow system is further simplified to a two-dimensional Filippov system. For the Filippov system, we study the dynamics of its two subsystems (i.e. free-system and control-system), the sliding mode dynamics, the boundary equilibrium bifurcations, as well as the global behaviors. We prove that both subsystems may undergo backward bifurcations and the sliding domain exists. Meanwhile, it is possible that the pseudo-equilibrium exists and is globally stable, or the pseudo-equilibrium, the disease-free equilibrium and the real equilibrium are tri-stable, or the pseudo-equilibrium and the real equilibrium are bi-stable, or the pseudo-equilibrium and disease-free equilibrium are bi-stable, which depends on the threshold value and other parameter values. The global stability of the pseudo-equilibrium reveals that we may maintain the number of infected hosts at a previously given value. Moreover, the bi-stability and tri-stability indicate that whether the number of infected individuals tends to zero or a previously given value or other positive values depends on the parameter values and the initial states of the system. These results highlight the challenges in the control of environmentally-driven infectious disease.

Global solutions to a class of multi-species reaction-diffusion systems with cross-diffusions arising in population dynamics

NASA Astrophysics Data System (ADS)

Wen, Zijuan; Fu, Shengmao

2009-08-01

In this paper, an n-species strongly coupled cooperating diffusive system is considered in a bounded smooth domain, subject to homogeneous Neumann boundary conditions. Employing the method of energy estimates, we obtain some conditions on the diffusion matrix and inter-specific cooperatives to ensure the global existence and uniform boundedness of a nonnegative solution. The globally asymptotical stability of the constant positive steady state is also discussed. As a consequence, all the results hold true for multi-species Lotka-Volterra type competition model and prey-predator model.

Future U.S. ozone projections dependence on regional emissions, climate change, long-range transport and differences in modeling design

NASA Astrophysics Data System (ADS)

He, Hao; Liang, Xin-Zhong; Lei, Hang; Wuebbles, Donald J.

2016-03-01

A consistent modeling framework with nested global and regional chemical transport models (CTMs) is used to separate and quantitatively assess the relative contributions to projections of future U.S. ozone pollution from the effects of emissions changes, climate change, long-range transport (LRT) of pollutants, and differences in modeling design. After incorporating dynamic lateral boundary conditions (LBCs) from a global CTM, a regional CTM's representation of present-day U.S. ozone pollution is notably improved, especially relative to results from the regional CTM with fixed LBCs or from the global CTM alone. This nested system of global and regional CTMs projects substantial surface ozone trends for the 2050's: 6-10 ppb decreases under the 'clean' A1B scenario and ∼15 ppb increases under the 'dirty' A1Fi scenario. Among the total trends of future ozone, regional emissions changes dominate, contributing negative 25-60% in A1B and positive 30-45% in A1Fi. Comparatively, climate change contributes positive 10-30%, while LRT effects through changing chemical LBCs account for positive 15-20% in both scenarios, suggesting introducing dynamic LBCs could influence projections of the U.S. future ozone pollution with a magnitude comparable to effects of climate change alone. The contribution to future ozone projections due to differences in modeling design, including model formulations, emissions treatments, and other factors between the global and the nested regional CTMs, is regionally dependent, ranging from negative 20% to positive 25%. It is shown that the model discrepancies for present-day simulations between global and regional CTMs can propagate into future U.S. ozone projections systematically but nonlinearly, especially in California and the Southeast. Therefore in addition to representations of emissions change and climate change, accurate treatment of LBCs for the regional CTM is essential for projecting the future U.S. ozone pollution.

Modelling carbon cycle in boreal wetlands with the Earth System Model ECHAM6/MPIOM

NASA Astrophysics Data System (ADS)

Getzieh, Robert J.; Brovkin, Victor; Kleinen, Thomas; Raivonen, Maarit; Sevanto, Sanna

2010-05-01

Wetlands of the northern high latitudes provide excellent conditions for peat accumulation and methanogenesis. High moisture and low O2 content in the soils lead to effective preservation of soil organic matter and methane emissions. Boreal Wetlands contain about 450 PgC and currently constitute a significant natural source of methane (CH4) even though they cover only 3% of the global land surface. While storing carbon and removing CO2 from the atmosphere, boreal wetlands have contributed to global cooling on millennial timescales. Undisturbed boreal wetlands are likely to continue functioning as a net carbon sink. On the other hand these carbon pools might be destabilised in future since they are sensitive to climate change. Given that processes of peat accumulation and decay are closely dependent on hydrology and temperature, this balance may be altered significantly in the future. As a result, northern wetlands could have a large impact on carbon cycle-climate feedback mechanisms and therefore play an important role in global carbon cycle dynamics. However global biogeochemistry models used for simulations of CO2 dynamics in past and future climates usually neglect carbon cycle in wetlands. We investigate the potential for positive or negative feedbacks to the climate system through fluxes of greenhouse gases (CO2 and CH4) with the general circulation model ECHAM6/MPIOM. A generic model of peat accumulation and decay has been developed and implemented into the land surface module JSBACH. We consider anaerobic biogeochemical processes which lead to formation of thick organic soils. Furthermore we consider specific wetland plant functional types (PFTs) in our model such as vascular plants (sedges) which impact methane transport and oxidation processes and non vascular plants (sphagnum mosses) which are promoting peat growth. As prototypes we use the modelling approaches by Frolking et al. (2001) as well as Walter & Heimann (2001) for the peat dynamics, and the wetland model by Wania (2008) for vegetation cover and methane emissions. An initial distribution of wetlands follows the GLWD-3 map by Lehner and Döll (2004). A dynamical wetlands hydrology scheme (T. Stacke) and a methane transport and emission model (M. Raivonen) are at the moment also under development at the MPI for Meteorology respectively in close cooperation with the University of Helsinki. First results of our modelling approach will be presented. REFERENCES S. Frolking et al., Ecosystems 4, 479-498 (2001). B. Lehner et al., Journal of Hydrology 296, 1-22 (2004). B. P. Walter et al., J. Geophys. Res. 106, D24, 34189-34206 and 34207-34219 (2001). R. Wania et al., Global Biogeochem. Cycles 23, GB3014 and GB3015 (2009).

Leaf and stem economics spectra drive diversity of functional plant traits in a dynamic global vegetation model.

PubMed

Sakschewski, Boris; von Bloh, Werner; Boit, Alice; Rammig, Anja; Kattge, Jens; Poorter, Lourens; Peñuelas, Josep; Thonicke, Kirsten

2015-01-22

Functional diversity is critical for ecosystem dynamics, stability and productivity. However, dynamic global vegetation models (DGVMs) which are increasingly used to simulate ecosystem functions under global change, condense functional diversity to plant functional types (PFTs) with constant parameters. Here, we develop an individual- and trait-based version of the DGVM LPJmL (Lund-Potsdam-Jena managed Land) called LPJmL- flexible individual traits (LPJmL-FIT) with flexible individual traits) which we apply to generate plant trait maps for the Amazon basin. LPJmL-FIT incorporates empirical ranges of five traits of tropical trees extracted from the TRY global plant trait database, namely specific leaf area (SLA), leaf longevity (LL), leaf nitrogen content (N area ), the maximum carboxylation rate of Rubisco per leaf area (vcmaxarea), and wood density (WD). To scale the individual growth performance of trees, the leaf traits are linked by trade-offs based on the leaf economics spectrum, whereas wood density is linked to tree mortality. No preselection of growth strategies is taking place, because individuals with unique trait combinations are uniformly distributed at tree establishment. We validate the modeled trait distributions by empirical trait data and the modeled biomass by a remote sensing product along a climatic gradient. Including trait variability and trade-offs successfully predicts natural trait distributions and achieves a more realistic representation of functional diversity at the local to regional scale. As sites of high climatic variability, the fringes of the Amazon promote trait divergence and the coexistence of multiple tree growth strategies, while lower plant trait diversity is found in the species-rich center of the region with relatively low climatic variability. LPJmL-FIT enables to test hypotheses on the effects of functional biodiversity on ecosystem functioning and to apply the DGVM to current challenges in ecosystem management from local to global scales, that is, deforestation and climate change effects. © 2015 John Wiley & Sons Ltd.

LPJmL4 - a dynamic global vegetation model with managed land - Part 1: Model description

NASA Astrophysics Data System (ADS)

Schaphoff, Sibyll; von Bloh, Werner; Rammig, Anja; Thonicke, Kirsten; Biemans, Hester; Forkel, Matthias; Gerten, Dieter; Heinke, Jens; Jägermeyr, Jonas; Knauer, Jürgen; Langerwisch, Fanny; Lucht, Wolfgang; Müller, Christoph; Rolinski, Susanne; Waha, Katharina

2018-04-01

This paper provides a comprehensive description of the newest version of the Dynamic Global Vegetation Model with managed Land, LPJmL4. This model simulates - internally consistently - the growth and productivity of both natural and agricultural vegetation as coherently linked through their water, carbon, and energy fluxes. These features render LPJmL4 suitable for assessing a broad range of feedbacks within and impacts upon the terrestrial biosphere as increasingly shaped by human activities such as climate change and land use change. Here we describe the core model structure, including recently developed modules now unified in LPJmL4. Thereby, we also review LPJmL model developments and evaluations in the field of permafrost, human and ecological water demand, and improved representation of crop types. We summarize and discuss LPJmL model applications dealing with the impacts of historical and future environmental change on the terrestrial biosphere at regional and global scale and provide a comprehensive overview of LPJmL publications since the first model description in 2007. To demonstrate the main features of the LPJmL4 model, we display reference simulation results for key processes such as the current global distribution of natural and managed ecosystems, their productivities, and associated water fluxes. A thorough evaluation of the model is provided in a companion paper. By making the model source code freely available at https://gitlab.pik-potsdam.de/lpjml/LPJmL, we hope to stimulate the application and further development of LPJmL4 across scientific communities in support of major activities such as the IPCC and SDG process.

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.

Estimating indices of range shifts in birds using dynamic models when detection is imperfect

USGS Publications Warehouse

Clement, Matthew J.; Hines, James E.; Nichols, James D.; Pardieck, Keith L.; Ziolkowski, David J.

2016-01-01

There is intense interest in basic and applied ecology about the effect of global change on current and future species distributions. Projections based on widely used static modeling methods implicitly assume that species are in equilibrium with the environment and that detection during surveys is perfect. We used multiseason correlated detection occupancy models, which avoid these assumptions, to relate climate data to distributional shifts of Louisiana Waterthrush in the North American Breeding Bird Survey (BBS) data. We summarized these shifts with indices of range size and position and compared them to the same indices obtained using more basic modeling approaches. Detection rates during point counts in BBS surveys were low, and models that ignored imperfect detection severely underestimated the proportion of area occupied and slightly overestimated mean latitude. Static models indicated Louisiana Waterthrush distribution was most closely associated with moderate temperatures, while dynamic occupancy models indicated that initial occupancy was associated with diurnal temperature ranges and colonization of sites was associated with moderate precipitation. Overall, the proportion of area occupied and mean latitude changed little during the 1997–2013 study period. Near-term forecasts of species distribution generated by dynamic models were more similar to subsequently observed distributions than forecasts from static models. Occupancy models incorporating a finite mixture model on detection – a new extension to correlated detection occupancy models – were better supported and may reduce bias associated with detection heterogeneity. We argue that replacing phenomenological static models with more mechanistic dynamic models can improve projections of future species distributions. In turn, better projections can improve biodiversity forecasts, management decisions, and understanding of global change biology.

(A)biotic processes control soil carbon dynamics: quantitative assessment of model complexity, stability and response to perturbations for improving ESMs

NASA Astrophysics Data System (ADS)

Georgiou, K.; Abramoff, R. Z.; Harte, J.; Riley, W. J.; Torn, M. S.

2016-12-01

As global temperatures and atmospheric CO2 concentrations continue to increase, soil microbial activity and decomposition of soil organic matter (SOM) are expected to follow suit, potentially limiting soil carbon storage. Traditional global- and ecosystem-scale models simulate SOM decomposition using linear kinetics, which are inherently unable to reproduce carbon-concentration feedbacks, such as priming of native SOM at elevated CO2 concentrations. Recent studies using nonlinear microbial models of SOM decomposition seek to capture these interactions, and several groups are currently integrating these microbial models into Earth System Models (ESMs). However, despite their widespread ability to exhibit nonlinear responses, these models vary tremendously in complexity and, consequently, dynamics. In this study, we explore, both analytically and numerically, the emergent oscillatory behavior and insensitivity of SOM stocks to carbon inputs that have been deemed `unrealistic' in recent microbial models. We discuss the sources of instability in four models of varying complexity, by sequentially reducing complexity of a detailed model that includes microbial physiology, a mineral sorption isotherm, and enzyme dynamics. We also present an alternative representation of microbial turnover that limits population sizes and, thus, reduces oscillations. We compare these models to several long-term carbon input manipulations, including the Detritus Input and Removal Treatment (DIRT) experiments, to show that there are clear metrics that can be used to distinguish and validate the inherent dynamics of each model structure. We find that traditional linear and nonlinear models cannot readily capture the range of long-term responses observed across the DIRT experiments as a direct consequence of their model structures, and that modifying microbial turnover results in more realistic predictions. Finally, we discuss our findings in the context of improving microbial model behavior for inclusion in ESMs.

Integrating global socio-economic influences into a regional land use change model for China

NASA Astrophysics Data System (ADS)

Xu, Xia; Gao, Qiong; Peng, Changhui; Cui, Xuefeng; Liu, Yinghui; Jiang, Li

2014-03-01

With rapid economic development and urbanization, land use in China has experienced huge changes in recent years; and this will probably continue in the future. Land use problems in China are urgent and need further study. Rapid land-use change and economic development make China an ideal region for integrated land use change studies, particularly the examination of multiple factors and global-regional interactions in the context of global economic integration. This paper presents an integrated modeling approach to examine the impact of global socio-economic processes on land use changes at a regional scale. We develop an integrated model system by coupling a simple global socio-economic model (GLOBFOOD) and regional spatial allocation model (CLUE). The model system is illustrated with an application to land use in China. For a given climate change, population growth, and various socio-economic situations, a global socio-economic model simulates the impact of global market and economy on land use, and quantifies changes of different land use types. The land use spatial distribution model decides the type of land use most appropriate in each spatial grid by employing a weighted suitability index, derived from expert knowledge about the ecosystem state and site conditions. A series of model simulations will be conducted and analyzed to demonstrate the ability of the integrated model to link global socioeconomic factors with regional land use changes in China. The results allow an exploration of the future dynamics of land use and landscapes in China.

Global modeling of withdrawal, allocation and consumptive use of surface water and groundwater resources

NASA Astrophysics Data System (ADS)

Wada, Y.; Wisser, D.; Bierkens, M. F. P.

2014-01-01

To sustain growing food demand and increasing standard of living, global water withdrawal and consumptive water use have been increasing rapidly. To analyze the human perturbation on water resources consistently over large scales, a number of macro-scale hydrological models (MHMs) have been developed in recent decades. However, few models consider the interaction between terrestrial water fluxes, and human activities and associated water use, and even fewer models distinguish water use from surface water and groundwater resources. Here, we couple a global water demand model with a global hydrological model and dynamically simulate daily water withdrawal and consumptive water use over the period 1979-2010, using two re-analysis products: ERA-Interim and MERRA. We explicitly take into account the mutual feedback between supply and demand, and implement a newly developed water allocation scheme to distinguish surface water and groundwater use. Moreover, we include a new irrigation scheme, which works dynamically with a daily surface and soil water balance, and incorporate the newly available extensive Global Reservoir and Dams data set (GRanD). Simulated surface water and groundwater withdrawals generally show good agreement with reported national and subnational statistics. The results show a consistent increase in both surface water and groundwater use worldwide, with a more rapid increase in groundwater use since the 1990s. Human impacts on terrestrial water storage (TWS) signals are evident, altering the seasonal and interannual variability. This alteration is particularly large over heavily regulated basins such as the Colorado and the Columbia, and over the major irrigated basins such as the Mississippi, the Indus, and the Ganges. Including human water use and associated reservoir operations generally improves the correlation of simulated TWS anomalies with those of the GRACE observations.

Global Modeling of Withdrawal, Allocation and Consumptive Use of Surface Water and Groundwater Resources

NASA Astrophysics Data System (ADS)

Wada, Y.; Wisser, D.; Bierkens, M. F.

2014-12-01

To sustain growing food demand and increasing standard of living, global water withdrawal and consumptive water use have been increasing rapidly. To analyze the human perturbation on water resources consistently over large scales, a number of macro-scale hydrological models (MHMs) have been developed in recent decades. However, few models consider the interaction between terrestrial water fluxes, and human activities and associated water use, and even fewer models distinguish water use from surface water and groundwater resources. Here, we couple a global water demand model with a global hydrological model and dynamically simulate daily water withdrawal and consumptive water use over the period 1979-2010, using two re-analysis products: ERA-Interim and MERRA. We explicitly take into account the mutual feedback between supply and demand, and implement a newly developed water allocation scheme to distinguish surface water and groundwater use. Moreover, we include a new irrigation scheme, which works dynamically with a daily surface and soil water balance, and incorporate the newly available extensive global reservoir data set (GRanD). Simulated surface water and groundwater withdrawals generally show good agreement with reported national and sub-national statistics. The results show a consistent increase in both surface water and groundwater use worldwide, with a more rapid increase in groundwater use since the 1990s. Human impacts on terrestrial water storage (TWS) signals are evident, altering the seasonal and inter-annual variability. This alteration is particularly large over heavily regulated basins such as the Colorado and the Columbia, and over the major irrigated basins such as the Mississippi, the Indus, and the Ganges. Including human water use and associated reservoir operations generally improves the correlation of simulated TWS anomalies with those of the GRACE observations.

Dynamics of financial crises in the world trade network

NASA Astrophysics Data System (ADS)

Askari, Marziyeh; Shirazi, Homayoun; Aghababaei Samani, Keivan

2018-07-01

A simple dynamical model is introduced to simulate the spreading of financial crises in the world trade network. In this model a directed network is constructed in which a weighted and directed link indicates the export value between two countries. The weights are subject to the change by a simple dynamical rule. The process begins with a crisis, i.e. a sudden decrease in the export value of a certain country and spreads throughout the whole network. We compare our results with the real values corresponding to the global financial crisis of 2008 and show that the results of our model are in good agreement with reality.

Modeling and Managing the Risks of Measles and Rubella: A Global Perspective, Part I.

PubMed

Thompson, Kimberly M; Cochi, Stephen L

2016-07-01

Over the past 50 years, the use of vaccines led to significant decreases in the global burdens of measles and rubella, motivated at least in part by the successive development of global control and elimination targets. The Global Vaccine Action Plan (GVAP) includes specific targets for regional elimination of measles and rubella in five of six regions of the World Health Organization by 2020. Achieving the GVAP measles and rubella goals will require significant immunization efforts and associated financial investments and political commitments. Planning and budgeting for these efforts can benefit from learning some important lessons from the Global Polio Eradication Initiative (GPEI). Following an overview of the global context of measles and rubella risks and discussion of lessons learned from the GPEI, we introduce the contents of the special issue on modeling and managing the risks of measles and rubella. This introduction describes the synthesis of the literature available to support evidence-based model inputs to support the development of an integrated economic and dynamic disease transmission model to support global efforts to optimally manage these diseases globally using vaccines. © 2016 Society for Risk Analysis.

Global dynamics and diffusion in triaxial galactic models

NASA Astrophysics Data System (ADS)

Papaphilippou, Y.

We apply the Frequency Map Analysis method to the 3--dimensional logarithmic galactic potential in order to clarify the dynamical behaviour of triaxial power--law galactic models. All the fine dynamical details are displayed in the complete frequency map, a direct representation of the system's Arnol'd web. The influence of resonant lines and the extent of the chaotic zones are directly associated with the physical space of the system. Some new results related with the diffusion of galactic orbits are also discussed. This approach reveals many unknown dynamical features of triaxial galactic potentials and provides strong indications that chaos should be an innate characteristic of triaxial configurations.

Combination of synoptical-analogous and dynamical methods to increase skill score of monthly air temperature forecasts over Northern Eurasia

NASA Astrophysics Data System (ADS)

Khan, Valentina; Tscepelev, Valery; Vilfand, Roman; Kulikova, Irina; Kruglova, Ekaterina; Tischenko, Vladimir

2016-04-01

Long-range forecasts at monthly-seasonal time scale are in great demand of socio-economic sectors for exploiting climate-related risks and opportunities. At the same time, the quality of long-range forecasts is not fully responding to user application necessities. Different approaches, including combination of different prognostic models, are used in forecast centers to increase the prediction skill for specific regions and globally. In the present study, two forecasting methods are considered which are exploited in operational practice of Hydrometeorological Center of Russia. One of them is synoptical-analogous method of forecasting of surface air temperature at monthly scale. Another one is dynamical system based on the global semi-Lagrangian model SL-AV, developed in collaboration of Institute of Numerical Mathematics and Hydrometeorological Centre of Russia. The seasonal version of this model has been used to issue global and regional forecasts at monthly-seasonal time scales. This study presents results of the evaluation of surface air temperature forecasts generated with using above mentioned synoptical-statistical and dynamical models, and their combination to potentially increase skill score over Northern Eurasia. The test sample of operational forecasts is encompassing period from 2010 through 2015. The seasonal and interannual variability of skill scores of these methods has been discussed. It was noticed that the quality of all forecasts is highly dependent on the inertia of macro-circulation processes. The skill scores of forecasts are decreasing during significant alterations of synoptical fields for both dynamical and empirical schemes. Procedure of combination of forecasts from different methods, in some cases, has demonstrated its effectiveness. For this study the support has been provided by Grant of Russian Science Foundation (№14-37-00053).

Reconstructing the regulatory circuit of cell fate determination in yeast mating response.

PubMed

Shao, Bin; Yuan, Haiyu; Zhang, Rongfei; Wang, Xuan; Zhang, Shuwen; Ouyang, Qi; Hao, Nan; Luo, Chunxiong

2017-07-01

Massive technological advances enabled high-throughput measurements of proteomic changes in biological processes. However, retrieving biological insights from large-scale protein dynamics data remains a challenging task. Here we used the mating differentiation in yeast Saccharomyces cerevisiae as a model and developed integrated experimental and computational approaches to analyze the proteomic dynamics during the process of cell fate determination. When exposed to a high dose of mating pheromone, the yeast cell undergoes growth arrest and forms a shmoo-like morphology; however, at intermediate doses, chemotropic elongated growth is initialized. To understand the gene regulatory networks that control this differentiation switch, we employed a high-throughput microfluidic imaging system that allows real-time and simultaneous measurements of cell growth and protein expression. Using kinetic modeling of protein dynamics, we classified the stimulus-dependent changes in protein abundance into two sources: global changes due to physiological alterations and gene-specific changes. A quantitative framework was proposed to decouple gene-specific regulatory modes from the growth-dependent global modulation of protein abundance. Based on the temporal patterns of gene-specific regulation, we established the network architectures underlying distinct cell fates using a reverse engineering method and uncovered the dose-dependent rewiring of gene regulatory network during mating differentiation. Furthermore, our results suggested a potential crosstalk between the pheromone response pathway and the target of rapamycin (TOR)-regulated ribosomal biogenesis pathway, which might underlie a cell differentiation switch in yeast mating response. In summary, our modeling approach addresses the distinct impacts of the global and gene-specific regulation on the control of protein dynamics and provides new insights into the mechanisms of cell fate determination. We anticipate that our integrated experimental and modeling strategies could be widely applicable to other biological systems.

Changes of the Oceanic Long-term and seasonal variation in a Global-warming Climate

NASA Astrophysics Data System (ADS)

Xia, Q.; He, Y.; Dong, C.

2015-12-01

Abstract: Gridded absolute dynamic topography (ADT) from AVISO and outputs of sea surface height above geoid from a series of climate models run for CMIP5 are used to analysis global sea level variation. Variance has been calculated to determine the magnitude of change in sea level variation over two decades. Increasing trend of variance of ADT suggests an enhanced fluctuation as well as geostrophic shear of global ocean. To further determine on what scale does the increasing fluctuation dominate, the global absolute dynamic topography (ADT) has been separated into two distinguished parts: the global five-year mean sea surface (MSS) and the residual absolute dynamic topography (RADT). Increased variance of MSS can be ascribed to the nonuniform rising of global sea level and an enhancement of ocean gyres in the Pacific Ocean. While trend in the variance of RADT is found to be close to zero which suggests an unchanged ocean mesoscale variability. The Gaussian-like distribution of global ADT are used to study the change in extreme sea levels. Information entropy has also been adapted in our study. Increasing trend of information entropy which measures the degree of dispersion of a probability distribution suggests more appearance of extreme sea levels. Extreme high sea levels are increasing with a higher growing rate than the mean sea level rise.

Multi-scale predictions of massive conifer mortality due to chronic temperature rise

NASA Astrophysics Data System (ADS)

McDowell, N. G.; Williams, A. P.; Xu, C.; Pockman, W. T.; Dickman, L. T.; Sevanto, S.; Pangle, R.; Limousin, J.; Plaut, J.; Mackay, D. S.; Ogee, J.; Domec, J. C.; Allen, C. D.; Fisher, R. A.; Jiang, X.; Muss, J. D.; Breshears, D. D.; Rauscher, S. A.; Koven, C.

2016-03-01

Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April-August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted >=50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.

Multi-scale predictions of massive conifer mortality due to chronic temperature rise

USGS Publications Warehouse

McDowell, Nathan G.; Williams, A.P.; Xu, C.; Pockman, W. T.; Dickman, L. T.; Sevanto, Sanna; Pangle, R.; Limousin, J.; Plaut, J.J.; Mackay, D.S.; Ogee, J.; Domec, Jean-Christophe; Allen, Craig D.; Fisher, Rosie A.; Jiang, X.; Muss, J.D.; Breshears, D.D.; Rauscher, Sara A.; Koven, C.

2016-01-01

Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April–August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted ≥50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.

The dynamics behind Titan's methane clouds.

PubMed

Mitchell, Jonathan L; Pierrehumbert, Raymond T; Frierson, Dargan M W; Caballero, Rodrigo

2006-12-05

We present results of an axisymmetric global circulation model of Titan with a simplified suite of atmospheric physics forced by seasonally varying insolation. The recent discovery of midlatitude tropospheric clouds on Titan has caused much excitement about the roles of surface sources of methane and the global circulation in forming clouds. Although localized surface sources, such as methane geysers or "cryovolcanoes," have been invoked to explain these clouds, we find in this work that clouds appear in regions of convergence by the mean meridional circulation and over the poles during solstices, where the solar forcing reaches its seasonal maximum. Other regions are inhibited from forming clouds because of dynamical transports of methane and strong subsidence. We find that for a variety of moist regimes, i.e., with the effect of methane thermodynamics included, the observed cloud features can be explained by the large-scale dynamics of the atmosphere. Clouds at the solsticial pole are found to be a robust feature of Titan's dynamics, whereas isolated midlatitude clouds are present exclusively in a variety of moist dynamical regimes. In all cases, even without including methane thermodynamics, our model ceases to produce polar clouds approximately 4-6 terrestrial years after solstices.

Pronounced differences between observed and CMIP5-simulated multidecadal climate variability in the twentieth century

NASA Astrophysics Data System (ADS)

Kravtsov, Sergey

2017-06-01

Identification and dynamical attribution of multidecadal climate undulations to either variations in external forcings or to internal sources is one of the most important topics of modern climate science, especially in conjunction with the issue of human-induced global warming. Here we utilize ensembles of twentieth century climate simulations to isolate the forced signal and residual internal variability in a network of observed and modeled climate indices. The observed internal variability so estimated exhibits a pronounced multidecadal mode with a distinctive spatiotemporal signature, which is altogether absent in model simulations. This single mode explains a major fraction of model-data differences over the entire climate index network considered; it may reflect either biases in the models' forced response or models' lack of requisite internal dynamics, or a combination of both.