Free energy landscapes of small peptides in an implicit solvent model determined by force-biased multicanonical molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Watanabe, Yukihisa S.; Kim, Jae Gil; Fukunishi, Yoshifumi; Nakamura, Haruki

2004-12-01

In order to investigate whether the implicit solvent (GB/SA) model could reproduce the free energy landscapes of peptides, the potential of mean forces (PMFs) of eight tripeptides was examined and compared with the PMFs of the explicit water model. The force-biased multicanonical molecular dynamics method was used for the enhanced conformational sampling. Consequently, the GB/SA model reproduced almost all the global and local minima in the PMFs observed with the explicit water model. However, the GB/SA model overestimated frequencies of the structures that are stabilized by intra-peptide hydrogen bonds.

Separating direct and indirect effects of global change: a population dynamic modeling approach using readily available field data.

PubMed

Farrer, Emily C; Ashton, Isabel W; Knape, Jonas; Suding, Katharine N

2014-04-01

Two sources of complexity make predicting plant community response to global change particularly challenging. First, realistic global change scenarios involve multiple drivers of environmental change that can interact with one another to produce non-additive effects. Second, in addition to these direct effects, global change drivers can indirectly affect plants by modifying species interactions. In order to tackle both of these challenges, we propose a novel population modeling approach, requiring only measurements of abundance and climate over time. To demonstrate the applicability of this approach, we model population dynamics of eight abundant plant species in a multifactorial global change experiment in alpine tundra where we manipulated nitrogen, precipitation, and temperature over 7 years. We test whether indirect and interactive effects are important to population dynamics and whether explicitly incorporating species interactions can change predictions when models are forecast under future climate change scenarios. For three of the eight species, population dynamics were best explained by direct effect models, for one species neither direct nor indirect effects were important, and for the other four species indirect effects mattered. Overall, global change had negative effects on species population growth, although species responded to different global change drivers, and single-factor effects were slightly more common than interactive direct effects. When the fitted population dynamic models were extrapolated under changing climatic conditions to the end of the century, forecasts of community dynamics and diversity loss were largely similar using direct effect models that do not explicitly incorporate species interactions or best-fit models; however, inclusion of species interactions was important in refining the predictions for two of the species. The modeling approach proposed here is a powerful way of analyzing readily available datasets which should be added to our toolbox to tease apart complex drivers of global change. © 2013 John Wiley & Sons Ltd.

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.

Influence of spatial temperature estimation method in ecohydrologic modeling in the western Oregon Cascades

Treesearch

E. Garcia; C.L. Tague; J. Choate

2013-01-01

Most spatially explicit hydrologic models require estimates of air temperature patterns. For these models, empirical relationships between elevation and air temperature are frequently used to upscale point measurements or downscale regional and global climate model estimates of air temperature. Mountainous environments are particularly sensitive to air temperature...

Implicit–explicit (IMEX) Runge–Kutta methods for non-hydrostatic atmospheric models

DOE PAGES

Gardner, David J.; Guerra, Jorge E.; Hamon, François P.; ...

2018-04-17

The efficient simulation of non-hydrostatic atmospheric dynamics requires time integration methods capable of overcoming the explicit stability constraints on time step size arising from acoustic waves. In this work, we investigate various implicit–explicit (IMEX) additive Runge–Kutta (ARK) methods for evolving acoustic waves implicitly to enable larger time step sizes in a global non-hydrostatic atmospheric model. The IMEX formulations considered include horizontally explicit – vertically implicit (HEVI) approaches as well as splittings that treat some horizontal dynamics implicitly. In each case, the impact of solving nonlinear systems in each implicit ARK stage in a linearly implicit fashion is also explored.The accuracymore » and efficiency of the IMEX splittings, ARK methods, and solver options are evaluated on a gravity wave and baroclinic wave test case. HEVI splittings that treat some vertical dynamics explicitly do not show a benefit in solution quality or run time over the most implicit HEVI formulation. While splittings that implicitly evolve some horizontal dynamics increase the maximum stable step size of a method, the gains are insufficient to overcome the additional cost of solving a globally coupled system. Solving implicit stage systems in a linearly implicit manner limits the solver cost but this is offset by a reduction in step size to achieve the desired accuracy for some methods. Overall, the third-order ARS343 and ARK324 methods performed the best, followed by the second-order ARS232 and ARK232 methods.« less

Implicit-explicit (IMEX) Runge-Kutta methods for non-hydrostatic atmospheric models

NASA Astrophysics Data System (ADS)

Gardner, David J.; Guerra, Jorge E.; Hamon, François P.; Reynolds, Daniel R.; Ullrich, Paul A.; Woodward, Carol S.

2018-04-01

The efficient simulation of non-hydrostatic atmospheric dynamics requires time integration methods capable of overcoming the explicit stability constraints on time step size arising from acoustic waves. In this work, we investigate various implicit-explicit (IMEX) additive Runge-Kutta (ARK) methods for evolving acoustic waves implicitly to enable larger time step sizes in a global non-hydrostatic atmospheric model. The IMEX formulations considered include horizontally explicit - vertically implicit (HEVI) approaches as well as splittings that treat some horizontal dynamics implicitly. In each case, the impact of solving nonlinear systems in each implicit ARK stage in a linearly implicit fashion is also explored. The accuracy and efficiency of the IMEX splittings, ARK methods, and solver options are evaluated on a gravity wave and baroclinic wave test case. HEVI splittings that treat some vertical dynamics explicitly do not show a benefit in solution quality or run time over the most implicit HEVI formulation. While splittings that implicitly evolve some horizontal dynamics increase the maximum stable step size of a method, the gains are insufficient to overcome the additional cost of solving a globally coupled system. Solving implicit stage systems in a linearly implicit manner limits the solver cost but this is offset by a reduction in step size to achieve the desired accuracy for some methods. Overall, the third-order ARS343 and ARK324 methods performed the best, followed by the second-order ARS232 and ARK232 methods.

Implicit–explicit (IMEX) Runge–Kutta methods for non-hydrostatic atmospheric models

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

Gardner, David J.; Guerra, Jorge E.; Hamon, François P.

The efficient simulation of non-hydrostatic atmospheric dynamics requires time integration methods capable of overcoming the explicit stability constraints on time step size arising from acoustic waves. In this work, we investigate various implicit–explicit (IMEX) additive Runge–Kutta (ARK) methods for evolving acoustic waves implicitly to enable larger time step sizes in a global non-hydrostatic atmospheric model. The IMEX formulations considered include horizontally explicit – vertically implicit (HEVI) approaches as well as splittings that treat some horizontal dynamics implicitly. In each case, the impact of solving nonlinear systems in each implicit ARK stage in a linearly implicit fashion is also explored.The accuracymore » and efficiency of the IMEX splittings, ARK methods, and solver options are evaluated on a gravity wave and baroclinic wave test case. HEVI splittings that treat some vertical dynamics explicitly do not show a benefit in solution quality or run time over the most implicit HEVI formulation. While splittings that implicitly evolve some horizontal dynamics increase the maximum stable step size of a method, the gains are insufficient to overcome the additional cost of solving a globally coupled system. Solving implicit stage systems in a linearly implicit manner limits the solver cost but this is offset by a reduction in step size to achieve the desired accuracy for some methods. Overall, the third-order ARS343 and ARK324 methods performed the best, followed by the second-order ARS232 and ARK232 methods.« less

On the Nexus of the Spatial Dynamics of Global Urbanization and the Age of the City

PubMed Central

Scheuer, Sebastian; Haase, Dagmar; Volk, Martin

2016-01-01

A number of concepts exist regarding how urbanization can be described as a process. Understanding this process that affects billions of people and its future development in a spatial manner is imperative to address related issues such as human quality of life. In the focus of spatially explicit studies on urbanization is typically a city, a particular urban region, an agglomeration. However, gaps remain in spatially explicit global models. This paper addresses that issue by examining the spatial dynamics of urban areas over time, for a full coverage of the world. The presented model identifies past, present and potential future hotspots of urbanization as a function of an urban area's spatial variation and age, whose relation could be depicted both as a proxy and as a path of urban development. PMID:27490199

On the Nexus of the Spatial Dynamics of Global Urbanization and the Age of the City.

PubMed

Scheuer, Sebastian; Haase, Dagmar; Volk, Martin

2016-01-01

A number of concepts exist regarding how urbanization can be described as a process. Understanding this process that affects billions of people and its future development in a spatial manner is imperative to address related issues such as human quality of life. In the focus of spatially explicit studies on urbanization is typically a city, a particular urban region, an agglomeration. However, gaps remain in spatially explicit global models. This paper addresses that issue by examining the spatial dynamics of urban areas over time, for a full coverage of the world. The presented model identifies past, present and potential future hotspots of urbanization as a function of an urban area's spatial variation and age, whose relation could be depicted both as a proxy and as a path of urban development.

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.

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

Isoprene derived secondary organic aerosol in a global aerosol chemistry climate model

NASA Astrophysics Data System (ADS)

Stadtler, Scarlet; Kühn, Thomas; Taraborrelli, Domenico; Kokkola, Harri; Schultz, Martin

2017-04-01

Secondary organic aerosol (SOA) impacts earth's climate and human health. Since its precursor chemistry and its formation are not fully understood, climate models cannot catch its direct and indirect effects. Global isoprene emissions are higher than any other non-methane hydrocarbons. Therefore, SOA from isoprene-derived, low volatile species (iSOA) is simulated using a global aerosol chemistry climate model ECHAM6-HAM-SALSA-MOZ. Isoprene oxidation in the chemistry model MOZ is following a novel semi-explicit scheme, embedded in a detailed atmospheric chemical mechanism. For iSOA formation four low volatile isoprene oxidation products were identified. The group method by Nanoonlal et al. 2008 was used to estimate their evaporation enthalpies ΔHvap. To calculate the saturation concentration C∗(T) the sectional aerosol model SALSA uses the gas phase concentrations simulated by MOZ and their corresponding ΔHvap to obtain the saturation vapor pressure p∗(T) from the Clausius Clapeyron equation. Subsequently, the saturation concentration is used to calculate the explicit kinetic partitioning of these compounds forming iSOA. Furthermore, the irreversible heterogeneous reactions of IEPOX and glyoxal from isoprene were included. The possibility of reversible heterogeneous uptake was ignored at this stage, leading to an upper estimate of the contribution of glyoxal to iSOA mass.

Cloud Modeling

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Moncrieff, Mitchell; Einaud, Franco (Technical Monitor)

2001-01-01

Numerical cloud models have been developed and applied extensively to study cloud-scale and mesoscale processes during the past four decades. The distinctive aspect of these cloud models is their ability to treat explicitly (or resolve) cloud-scale dynamics. This requires the cloud models to be formulated from the non-hydrostatic equations of motion that explicitly include the vertical acceleration terms since the vertical and horizontal scales of convection are similar. Such models are also necessary in order to allow gravity waves, such as those triggered by clouds, to be resolved explicitly. In contrast, the hydrostatic approximation, usually applied in global or regional models, does allow the presence of gravity waves. In addition, the availability of exponentially increasing computer capabilities has resulted in time integrations increasing from hours to days, domain grids boxes (points) increasing from less than 2000 to more than 2,500,000 grid points with 500 to 1000 m resolution, and 3-D models becoming increasingly prevalent. The cloud resolving model is now at a stage where it can provide reasonably accurate statistical information of the sub-grid, cloud-resolving processes poorly parameterized in climate models and numerical prediction models.

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.

Multi-scale Modeling of Arctic Clouds

NASA Astrophysics Data System (ADS)

Hillman, B. R.; Roesler, E. L.; Dexheimer, D.

2017-12-01

The presence and properties of clouds are critically important to the radiative budget in the Arctic, but clouds are notoriously difficult to represent in global climate models (GCMs). The challenge stems partly from a disconnect in the scales at which these models are formulated and the scale of the physical processes important to the formation of clouds (e.g., convection and turbulence). Because of this, these processes are parameterized in large-scale models. Over the past decades, new approaches have been explored in which a cloud system resolving model (CSRM), or in the extreme a large eddy simulation (LES), is embedded into each gridcell of a traditional GCM to replace the cloud and convective parameterizations to explicitly simulate more of these important processes. This approach is attractive in that it allows for more explicit simulation of small-scale processes while also allowing for interaction between the small and large-scale processes. The goal of this study is to quantify the performance of this framework in simulating Arctic clouds relative to a traditional global model, and to explore the limitations of such a framework using coordinated high-resolution (eddy-resolving) simulations. Simulations from the global model are compared with satellite retrievals of cloud fraction partioned by cloud phase from CALIPSO, and limited-area LES simulations are compared with ground-based and tethered-balloon measurements from the ARM Barrow and Oliktok Point measurement facilities.

A New Global Regression Analysis Method for the Prediction of Wind Tunnel Model Weight Corrections

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred; Bridge, Thomas M.; Amaya, Max A.

2014-01-01

A new global regression analysis method is discussed that predicts wind tunnel model weight corrections for strain-gage balance loads during a wind tunnel test. The method determines corrections by combining "wind-on" model attitude measurements with least squares estimates of the model weight and center of gravity coordinates that are obtained from "wind-off" data points. The method treats the least squares fit of the model weight separate from the fit of the center of gravity coordinates. Therefore, it performs two fits of "wind- off" data points and uses the least squares estimator of the model weight as an input for the fit of the center of gravity coordinates. Explicit equations for the least squares estimators of the weight and center of gravity coordinates are derived that simplify the implementation of the method in the data system software of a wind tunnel. In addition, recommendations for sets of "wind-off" data points are made that take typical model support system constraints into account. Explicit equations of the confidence intervals on the model weight and center of gravity coordinates and two different error analyses of the model weight prediction are also discussed in the appendices of the paper.

Optimal harvesting of a stochastic delay logistic model with Lévy jumps

NASA Astrophysics Data System (ADS)

Qiu, Hong; Deng, Wenmin

2016-10-01

The optimal harvesting problem of a stochastic time delay logistic model with Lévy jumps is considered in this article. We first show that the model has a unique global positive solution and discuss the uniform boundedness of its pth moment with harvesting. Then we prove that the system is globally attractive and asymptotically stable in distribution under our assumptions. Furthermore, we obtain the existence of the optimal harvesting effort by the ergodic method, and then we give the explicit expression of the optimal harvesting policy and maximum yield.

Global spatially explicit CO2 emission metrics at 0.25° horizontal resolution for forest bioenergy

NASA Astrophysics Data System (ADS)

Cherubini, F.

2015-12-01

Bioenergy is the most important renewable energy option in studies designed to align with future RCP projections, reaching approximately 250 EJ/yr in RCP2.6, 145 EJ/yr in RCP4.5 and 180 EJ/yr in RCP8.5 by the end of the 21st century. However, many questions enveloping the direct carbon cycle and climate response to bioenergy remain partially unexplored. Bioenergy systems are largely assessed under the default climate neutrality assumption and the time lag between CO2 emissions from biomass combustion and CO2 uptake by vegetation is usually ignored. Emission metrics of CO2 from forest bioenergy are only available on a case-specific basis and their quantification requires processing of a wide spectrum of modelled or observed local climate and forest conditions. On the other hand, emission metrics are widely used to aggregate climate impacts of greenhouse gases to common units such as CO2-equivalents (CO2-eq.), but a spatially explicit analysis of emission metrics with global forest coverage is today lacking. Examples of emission metrics include the global warming potential (GWP), the global temperature change potential (GTP) and the absolute sustained emission temperature (aSET). Here, we couple a global forest model, a heterotrophic respiration model, and a global climate model to produce global spatially explicit emission metrics for CO2 emissions from forest bioenergy. We show their applications to global emissions in 2015 and until 2100 under the different RCP scenarios. We obtain global average values of 0.49 ± 0.03 kgCO2-eq. kgCO2-1 (mean ± standard deviation), 0.05 ± 0.05 kgCO2-eq. kgCO2-1, and 2.14·10-14 ± 0.11·10-14 °C (kg yr-1)-1, and 2.14·10-14 ± 0.11·10-14 °C (kg yr-1)-1 for GWP, GTP and aSET, respectively. We also present results aggregated at a grid, national and continental level. The metrics are found to correlate with the site-specific turnover times and local climate variables like annual mean temperature and precipitation. Simplified equations are derived to infer metric values from the turnover time of the biomass feedstock and the fraction of forest residues left on site after harvest. Our results provide a basis for assessing CO2 emissions from forest bioenergy under different indicators and across various spatial and temporal scales.

Challenges and needs in fire management: A landscape simulation modeling perspective [chapter 4

Treesearch

Robert E. Keane; Geoffrey J. Cary; Mike D. Flannigan

2011-01-01

Fire management will face many challenges in the future from global climate change to protecting people, communities, and values at risk. Simulation modeling will be a vital tool for addressing these challenges but the next generation of simulation models must be spatially explicit to address critical landscape ecology relationships and they must use mechanistic...

Global conservation model for a mushy region over a moving substrate

NASA Astrophysics Data System (ADS)

Kyselica, J.; Šimkanin, J.

2018-03-01

We study solidification over a cool substrate moving with a relative velocity with respect to the rest of the fluid. A mathematical model based on global conservation of solute is presented. The explicit solutions of the governing equations are found and analysed via the asymptotic methods. The assessment of how the boundary-layer flow influences the physical characteristics of the mushy region is given, together with the discussion of a possible connection with the solidification at the inner core boundary.

Spatiotemporal dynamics of soil phosphorus and crop uptake in global cropland during the 20th century

NASA Astrophysics Data System (ADS)

Zhang, Jie; Beusen, Arthur H. W.; Van Apeldoorn, Dirk F.; Mogollón, José M.; Yu, Chaoqing; Bouwman, Alexander F.

2017-04-01

Phosphorus (P) plays a vital role in global crop production and food security. In this study, we investigate the changes in soil P pool inventories calibrated from historical countrywide crop P uptake, using a 0.5-by-0.5° spatially explicit model for the period 1900-2010. Globally, the total P pool per hectare increased rapidly between 1900 and 2010 in soils of Europe (+31 %), South America (+2 %), North America (+15 %), Asia (+17 %), and Oceania (+17 %), while it has been stable in Africa. Simulated crop P uptake is influenced by both soil properties (available P and the P retention potential) and crop characteristics (maximum uptake). Until 1950, P fertilizer application had a negligible influence on crop uptake, but recently it has become a driving factor for food production in industrialized countries and a number of transition countries like Brazil, Korea, and China. This comprehensive and spatially explicit model can be used to assess how long surplus P fertilization is needed or how long depletions of built-up surplus P can continue without affecting crop yield.

River export of triclosan from land to sea: A global modelling approach.

PubMed

van Wijnen, Jikke; Ragas, Ad M J; Kroeze, Carolien

2018-04-15

Triclosan (TCS) is an antibacterial agent that is added to commonly used personal care products. Emitted to the aquatic environment in large quantities, it poses a potential threat to aquatic organisms. Triclosan enters the aquatic environment mainly through sewage effluent. We developed a global, spatially explicit model, the Global TCS model, to simulate triclosan transport by rivers to coastal areas. With this model we analysed annual, basin-wide triclosan export for the year 2000 and two future scenarios for the year 2050. Our analyses for 2000 indicate that triclosan export to coastal areas in Western Europe, Southeast Asia and the East Coast of the USA is higher than in the rest of the world. For future scenarios, the Global TCS model predicts an increase in river export of triclosan in Southeast Asia and a small decrease in Europe. The number of rivers with an annual average triclosan concentration at the river mouth that exceeds a PNEC of 26.2ng/L is projected to double between 2000 and 2050. This increase is most prominent in Southeast Asia, as a result of fast population growth, increasing urbanisation and increasing numbers of people connected to sewerage systems with poor wastewater treatment. Predicted triclosan loads correspond reasonably well with measured values. However, basin-specific predictions have considerable uncertainty due to lacking knowledge and location-specific data on the processes determining the fate of triclosan in river water, e.g. sorption, degradation and sedimentation. Additional research on the fate of triclosan in river systems is therefore recommended. We developed a global spatially explicit model to simulate triclosan export by rivers to coastal seas. For two future scenarios this Global TCS model projects an increase in river export of triclosan to several seas around the world. Copyright © 2017 Elsevier B.V. All rights reserved.

Academic Work from a Comparative Perspective: A Survey of Faculty Working Time across 13 Countries

ERIC Educational Resources Information Center

Bentley, Peter James; Kyvik, Svein

2012-01-01

Sociological institutional theory views universities as model driven organizations. The world's stratification system promotes conformity, imitation and isomorphism towards the "best" university models. Accordingly, academic roles may be locally shaped in minor ways, but are defined and measured explicitly in global terms. We test this proposition…

Representing climate, disturbance, and vegetation interactions in landscape models

Treesearch

Robert E. Keane; Donald McKenzie; Donald A. Falk; Erica A.H. Smithwick; Carol Miller; Lara-Karena B. Kellogg

2015-01-01

The prospect of rapidly changing climates over the next century calls for methods to predict their effects on myriad, interactive ecosystem processes. Spatially explicit models that simulate ecosystem dynamics at fine (plant, stand) to coarse (regional, global) scales are indispensable tools for meeting this challenge under a variety of possible futures. A special...

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...

Awakening the Scientist Inside: Global Climate Change and the Nature of Science in an Elementary Science Methods Course

ERIC Educational Resources Information Center

Matkins, Juanita Jo; Bell, Randy L.

2007-01-01

This investigation assessed the impact of situating explicit nature of science (NOS) instruction within the issues surrounding global climate change and global warming (GCC/GW). Participants in the study were 15 preservice elementary teachers enrolled in a science methods course. The instructional intervention included explicit NOS instruction…

Seamless atmospheric modeling across the hydrostatic-nonhydrostatic scales - preliminary results using an unstructured-Voronoi mesh for weather prediction.

NASA Astrophysics Data System (ADS)

Skamarock, W. C.

2015-12-01

One of the major problems in atmospheric model applications is the representation of deep convection within the models; explicit simulation of deep convection on fine meshes performs much better than sub-grid parameterized deep convection on coarse meshes. Unfortunately, the high cost of explicit convective simulation has meant it has only been used to down-scale global simulations in weather prediction and regional climate applications, typically using traditional one-way interactive nesting technology. We have been performing real-time weather forecast tests using a global non-hydrostatic atmospheric model (the Model for Prediction Across Scales, MPAS) that employs a variable-resolution unstructured Voronoi horizontal mesh (nominally hexagons) to span hydrostatic to nonhydrostatic scales. The smoothly varying Voronoi mesh eliminates many downscaling problems encountered using traditional one- or two-way grid nesting. Our test weather forecasts cover two periods - the 2015 Spring Forecast Experiment conducted at the NOAA Storm Prediction Center during the month of May in which we used a 50-3 km mesh, and the PECAN field program examining nocturnal convection over the US during the months of June and July in which we used a 15-3 km mesh. An important aspect of this modeling system is that the model physics be scale-aware, particularly the deep convection parameterization. These MPAS simulations employ the Grell-Freitas scale-aware convection scheme. Our test forecasts show that the scheme produces a gradual transition in the deep convection, from the deep unstable convection being handled entirely by the convection scheme on the coarse mesh regions (dx > 15 km), to the deep convection being almost entirely explicit on the 3 km NA region of the meshes. We will present results illustrating the performance of critical aspects of the MPAS model in these tests.

Commentary: Explicit Attention to Age and Gender Disparities is Key to Understanding Adolescent Experiences and Outcomes

ERIC Educational Resources Information Center

Blanc, Ann K.; Bruce, Judith

2013-01-01

This special issue addresses an ambitious set of concerns around the experience of adolescents in the majority world: expanded models of development, successful models of intervention, and the impact of globalization. The papers, which vary widely in both substance and methodology, make a substantial contribution to pushing forward the boundaries…

Not explicit but implicit memory is influenced by individual perception style

PubMed Central

Tsushima, Yoshiaki

2018-01-01

Not only explicit but also implicit memory has considerable influence on our daily life. However, it is still unclear whether explicit and implicit memories are sensitive to individual differences. Here, we investigated how individual perception style (global or local) correlates with implicit and explicit memory. As a result, we found that not explicit but implicit memory was affected by the perception style: local perception style people more greatly used implicit memory than global perception style people. These results help us to make the new effective application adapting to individual perception style and understand some clinical symptoms such as autistic spectrum disorder. Furthermore, this finding might give us new insight of memory involving consciousness and unconsciousness as well as relationship between implicit/explicit memory and individual perception style. PMID:29370212

Not explicit but implicit memory is influenced by individual perception style.

PubMed

Hine, Kyoko; Tsushima, Yoshiaki

2018-01-01

Not only explicit but also implicit memory has considerable influence on our daily life. However, it is still unclear whether explicit and implicit memories are sensitive to individual differences. Here, we investigated how individual perception style (global or local) correlates with implicit and explicit memory. As a result, we found that not explicit but implicit memory was affected by the perception style: local perception style people more greatly used implicit memory than global perception style people. These results help us to make the new effective application adapting to individual perception style and understand some clinical symptoms such as autistic spectrum disorder. Furthermore, this finding might give us new insight of memory involving consciousness and unconsciousness as well as relationship between implicit/explicit memory and individual perception style.

Oil Dependence, Climate Change and Energy Security: Will Constraints on Oil Shape our Climate Future or Vice Versa?

NASA Astrophysics Data System (ADS)

Mignone, B. K.

2008-12-01

Threats to US and global energy security take several forms. First, the overwhelming dependence on oil in the transport sector leaves the US economy (and others) vulnerable to supply shocks and price volatility. Secondly, the global dependence on oil inflates prices and enhances the transfer of wealth to authoritarian regimes. Finally, the global reliance on fossil fuels more generally jeopardizes the stability of the climate system. These three threats - economic, strategic and environmental - can only be mitigated through a gradual substitution away from fossil fuels (both coal and oil) on a global scale. Such large-scale substitution could occur in response to potential resource constraints or in response to coordinated government policies in which these externalities are explicitly internalized. Here, I make use of a well-known integrated assessment model (MERGE) to examine both possibilities. When resource limits are considered alone, global fuel use tends to shift toward even more carbon-intensive resources, like oil shale or liquids derived from coal. On the other hand, when explicit carbon constraints are imposed, the fuel sector response is more complex. Generally, less stringent climate targets can be satisfied entirely through reductions in global coal consumption, while more stringent targets require simultaneous reductions in both coal and oil consumption. Taken together, these model results suggest that resource constraints alone will only exacerbate the climate problem, while a subset of policy-driven carbon constraints may yield tangible security benefits (in the form of reduced global oil consumption) in addition to the intended environmental outcome.

Modeling trends from North American Breeding Bird Survey data: a spatially explicit approach

USGS Publications Warehouse

Bled, Florent; Sauer, John R.; Pardieck, Keith L.; Doherty, Paul; Royle, J. Andy

2013-01-01

Population trends, defined as interval-specific proportional changes in population size, are often used to help identify species of conservation interest. Efficient modeling of such trends depends on the consideration of the correlation of population changes with key spatial and environmental covariates. This can provide insights into causal mechanisms and allow spatially explicit summaries at scales that are of interest to management agencies. We expand the hierarchical modeling framework used in the North American Breeding Bird Survey (BBS) by developing a spatially explicit model of temporal trend using a conditional autoregressive (CAR) model. By adopting a formal spatial model for abundance, we produce spatially explicit abundance and trend estimates. Analyses based on large-scale geographic strata such as Bird Conservation Regions (BCR) can suffer from basic imbalances in spatial sampling. Our approach addresses this issue by providing an explicit weighting based on the fundamental sample allocation unit of the BBS. We applied the spatial model to three species from the BBS. Species have been chosen based upon their well-known population change patterns, which allows us to evaluate the quality of our model and the biological meaning of our estimates. We also compare our results with the ones obtained for BCRs using a nonspatial hierarchical model (Sauer and Link 2011). Globally, estimates for mean trends are consistent between the two approaches but spatial estimates provide much more precise trend estimates in regions on the edges of species ranges that were poorly estimated in non-spatial analyses. Incorporating a spatial component in the analysis not only allows us to obtain relevant and biologically meaningful estimates for population trends, but also enables us to provide a flexible framework in order to obtain trend estimates for any area.

Spatially explicit global population scenarios consistent with the Shared Socioeconomic Pathways

DOE PAGES

Jones, B.; O’Neill, B. C.

2016-07-29

Here we report that the projected size and spatial distribution of the future population are important drivers of global change and key determinants of exposure and vulnerability to hazards. Spatial demographic projections are widely used as inputs to spatial projections of land use, energy use, and emissions, as well as to assessments of the impacts of extreme events, sea level rise, and other climate-related outcomes. To date, however, there are very few global-scale, spatially explicit population projections, and those that do exist are often based on simple scaling or trend extrapolation. Here we present a new set of global, spatiallymore » explicit population scenarios that are consistent with the new Shared Socioeconomic Pathways (SSPs) developed to facilitate global change research. We use a parameterized gravity-based downscaling model to produce projections of spatial population change that are quantitatively consistent with national population and urbanization projections for the SSPs and qualitatively consistent with assumptions in the SSP narratives regarding spatial development patterns. We show that the five SSPs lead to substantially different spatial population outcomes at the continental, national, and sub-national scale. In general, grid cell-level outcomes are most influenced by national-level population change, second by urbanization rate, and third by assumptions about the spatial style of development. However, the relative importance of these factors is a function of the magnitude of the projected change in total population and urbanization for each country and across SSPs. We also demonstrate variation in outcomes considering the example of population existing in a low-elevation coastal zone under alternative scenarios.« less

Spatially explicit global population scenarios consistent with the Shared Socioeconomic Pathways

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

Jones, B.; O’Neill, B. C.

Here we report that the projected size and spatial distribution of the future population are important drivers of global change and key determinants of exposure and vulnerability to hazards. Spatial demographic projections are widely used as inputs to spatial projections of land use, energy use, and emissions, as well as to assessments of the impacts of extreme events, sea level rise, and other climate-related outcomes. To date, however, there are very few global-scale, spatially explicit population projections, and those that do exist are often based on simple scaling or trend extrapolation. Here we present a new set of global, spatiallymore » explicit population scenarios that are consistent with the new Shared Socioeconomic Pathways (SSPs) developed to facilitate global change research. We use a parameterized gravity-based downscaling model to produce projections of spatial population change that are quantitatively consistent with national population and urbanization projections for the SSPs and qualitatively consistent with assumptions in the SSP narratives regarding spatial development patterns. We show that the five SSPs lead to substantially different spatial population outcomes at the continental, national, and sub-national scale. In general, grid cell-level outcomes are most influenced by national-level population change, second by urbanization rate, and third by assumptions about the spatial style of development. However, the relative importance of these factors is a function of the magnitude of the projected change in total population and urbanization for each country and across SSPs. We also demonstrate variation in outcomes considering the example of population existing in a low-elevation coastal zone under alternative scenarios.« less

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.

2013-02-01

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 a large scale, a number of macro-scale hydrological models (MHMs) have been developed over the recent decades. However, few models consider the feedback between water availability and water demand, and even fewer models explicitly incorporate water allocation from surface water and groundwater resources. Here, we integrate a global water demand model into a global water balance model, and simulate water withdrawal and consumptive water use over the period 1979-2010, considering water allocation from surface water and groundwater resources and explicitly taking into account feedbacks between supply and demand, using two re-analysis products: ERA-Interim and MERRA. We implement an irrigation water scheme, which works dynamically with daily surface and soil water balance, and include a newly available extensive reservoir data set. Simulated surface water and groundwater withdrawal show generally good agreement with available reported national and sub-national statistics. The results show a consistent increase in both surface water and groundwater use worldwide, but groundwater use has been increasing more rapidly than surface water use since the 1990s. Human impacts on terrestrial water storage (TWS) signals are evident, altering the seasonal and inter-annual variability. The alteration is particularly large over the 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 generally improves the correlation of simulated TWS anomalies with those of the GRACE observations.

Integrating remote sensing and spatially explicit epidemiological modeling

NASA Astrophysics Data System (ADS)

Finger, Flavio; Knox, Allyn; Bertuzzo, Enrico; Mari, Lorenzo; Bompangue, Didier; Gatto, Marino; Rinaldo, Andrea

2015-04-01

Spatially explicit epidemiological models are a crucial tool for the prediction of epidemiological patterns in time and space as well as for the allocation of health care resources. In addition they can provide valuable information about epidemiological processes and allow for the identification of environmental drivers of the disease spread. Most epidemiological models rely on environmental data as inputs. They can either be measured in the field by the means of conventional instruments or using remote sensing techniques to measure suitable proxies of the variables of interest. The later benefit from several advantages over conventional methods, including data availability, which can be an issue especially in developing, and spatial as well as temporal resolution of the data, which is particularly crucial for spatially explicit models. Here we present the case study of a spatially explicit, semi-mechanistic model applied to recurring cholera outbreaks in the Lake Kivu area (Democratic Republic of the Congo). The model describes the cholera incidence in eight health zones on the shore of the lake. Remotely sensed datasets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers. Human mobility and its effect on the disease spread is also taken into account. Several model configurations are tested on a data set of reported cases. The best models, accounting for different environmental drivers, and selected using the Akaike information criterion, are formally compared via cross validation. The best performing model accounts for seasonality, El Niño Southern Oscillation, precipitation and human mobility.

Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison

PubMed Central

Rosenzweig, Cynthia; Elliott, Joshua; Deryng, Delphine; Ruane, Alex C.; Müller, Christoph; Arneth, Almut; Boote, Kenneth J.; Folberth, Christian; Glotter, Michael; Khabarov, Nikolay; Neumann, Kathleen; Piontek, Franziska; Pugh, Thomas A. M.; Schmid, Erwin; Stehfest, Elke; Yang, Hong; Jones, James W.

2014-01-01

Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies. PMID:24344314

Assessing Agricultural Risks of Climate Change in the 21st Century in a Global Gridded Crop Model Intercomparison

NASA Technical Reports Server (NTRS)

Rosenzweig, Cynthia E.; Elliott, Joshua; Deryng, Delphine; Ruane, Alex C.; Mueller, Christoph; Arneth, Almut; Boote, Kenneth J.; Folberth, Christian; Glotter, Michael; Khabarov, Nikolay

2014-01-01

Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies.

Fully implicit Particle-in-cell algorithms for multiscale plasma simulation

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

Chacon, Luis

The outline of the paper is as follows: Particle-in-cell (PIC) methods for fully ionized collisionless plasmas, explicit vs. implicit PIC, 1D ES implicit PIC (charge and energy conservation, moment-based acceleration), and generalization to Multi-D EM PIC: Vlasov-Darwin model (review and motivation for Darwin model, conservation properties (energy, charge, and canonical momenta), and numerical benchmarks). The author demonstrates a fully implicit, fully nonlinear, multidimensional PIC formulation that features exact local charge conservation (via a novel particle mover strategy), exact global energy conservation (no particle self-heating or self-cooling), adaptive particle orbit integrator to control errors in momentum conservation, and canonical momenta (EM-PICmore » only, reduced dimensionality). The approach is free of numerical instabilities: ω peΔt >> 1, and Δx >> λ D. It requires many fewer dofs (vs. explicit PIC) for comparable accuracy in challenging problems. Significant CPU gains (vs explicit PIC) have been demonstrated. The method has much potential for efficiency gains vs. explicit in long-time-scale applications. Moment-based acceleration is effective in minimizing N FE, leading to an optimal algorithm.« less

The development of an explicit thermochemical nonequilibrium algorithm and its application to compute three dimensional AFE flowfields

NASA Technical Reports Server (NTRS)

Palmer, Grant

1989-01-01

This study presents a three-dimensional explicit, finite-difference, shock-capturing numerical algorithm applied to viscous hypersonic flows in thermochemical nonequilibrium. The algorithm employs a two-temperature physical model. Equations governing the finite-rate chemical reactions are fully-coupled to the gas dynamic equations using a novel coupling technique. The new coupling method maintains stability in the explicit, finite-rate formulation while allowing relatively large global time steps. The code uses flux-vector accuracy. Comparisons with experimental data and other numerical computations verify the accuracy of the present method. The code is used to compute the three-dimensional flowfield over the Aeroassist Flight Experiment (AFE) vehicle at one of its trajectory points.

Formulation of an explicit-multiple-time-step time integration method for use in a global primitive equation grid model

NASA Technical Reports Server (NTRS)

Chao, W. C.

1982-01-01

With appropriate modifications, a recently proposed explicit-multiple-time-step scheme (EMTSS) is incorporated into the UCLA model. In this scheme, the linearized terms in the governing equations that generate the gravity waves are split into different vertical modes. Each mode is integrated with an optimal time step, and at periodic intervals these modes are recombined. The other terms are integrated with a time step dictated by the CFL condition for low-frequency waves. This large time step requires a special modification of the advective terms in the polar region to maintain stability. Test runs for 72 h show that EMTSS is a stable, efficient and accurate scheme.

PATTERNS AND CONTROLS OF DISSOLVED ORGANIC MATTER EXPORT BY MAJOR RIVERS: A NEW SEASONAL, SPATIALLY EXPLICIT, GLOBAL MODEL

EPA Science Inventory

River-derived dissolved organic matter (DOM) influences metabolism, light attenuation, and bioavailability of metals and nutrients in coastal ecosystems. Recent work suggests that DOM concentrations in surface waters vary seasonally because different organic matter pools are mobi...

Higher climatological temperature sensitivity of soil carbon in cold than warm climates

NASA Astrophysics Data System (ADS)

Koven, Charles D.; Hugelius, Gustaf; Lawrence, David M.; Wieder, William R.

2017-11-01

The projected loss of soil carbon to the atmosphere resulting from climate change is a potentially large but highly uncertain feedback to warming. The magnitude of this feedback is poorly constrained by observations and theory, and is disparately represented in Earth system models (ESMs). To assess the climatological temperature sensitivity of soil carbon, we calculate apparent soil carbon turnover times that reflect long-term and broad-scale rates of decomposition. Here, we show that the climatological temperature control on carbon turnover in the top metre of global soils is more sensitive in cold climates than in warm climates and argue that it is critical to capture this emergent ecosystem property in global-scale models. We present a simplified model that explains the observed high cold-climate sensitivity using only the physical scaling of soil freeze-thaw state across climate gradients. Current ESMs fail to capture this pattern, except in an ESM that explicitly resolves vertical gradients in soil climate and carbon turnover. An observed weak tropical temperature sensitivity emerges in a different model that explicitly resolves mineralogical control on decomposition. These results support projections of strong carbon-climate feedbacks from northern soils and demonstrate a method for ESMs to capture this emergent behaviour.

Towards an Understanding of Atmospheric Balance

NASA Technical Reports Server (NTRS)

Errico, Ronald M.

2015-01-01

During a 35 year period I published 30+ pear-reviewed papers and technical reports concerning, in part or whole, the topic of atmospheric balance. Most used normal modes, either implicitly or explicitly, as the appropriate diagnostic tool. This included examination of nonlinear balance in several different global and regional models using a variety of novel metrics as well as development of nonlinear normal mode initialization schemes for particular global and regional models. Recent studies also included the use of adjoint models and OSSEs to answer some questions regarding balance. lwill summarize what I learned through those many works, but also present what l see as remaining issues to be considered or investigated.

Non-hydrostatic general circulation model of the Venus atmosphere

NASA Astrophysics Data System (ADS)

Rodin, Alexander V.; Mingalev, Igor; Orlov, Konstantin; Ignatiev, Nikolay

We present the first non-hydrostatic global circulation model of the Venus atmosphere based on the complete set of gas dynamics equations. The model employs a spatially uniform triangular mesh that allows to avoid artificial damping of the dynamical processes in the polar regions, with altitude as a vertical coordinate. Energy conversion from the solar flux into atmospheric motion is described via explicitly specified heating and cooling rates or, alternatively, with help of the radiation block based on comprehensive treatment of the Venus atmosphere spectroscopy, including line mixing effects in CO2 far wing absorption. Momentum equations are integrated using the semi-Lagrangian explicit scheme that provides high accuracy of mass and energy conservation. Due to high vertical grid resolution required by gas dynamics calculations, the model is integrated on the short time step less than one second. The model reliably repro-duces zonal superrotation, smoothly extending far below the cloud layer, tidal patterns at the cloud level and above, and non-rotating, sun-synchronous global convective cell in the upper atmosphere. One of the most interesting features of the model is the development of the polar vortices resembling those observed by Venus Express' VIRTIS instrument. Initial analysis of the simulation results confirms the hypothesis that it is thermal tides that provides main driver for the superrotation.

Modelling the nonlinear behaviour of an underplatform damper test rig for turbine applications

NASA Astrophysics Data System (ADS)

Pesaresi, L.; Salles, L.; Jones, A.; Green, J. S.; Schwingshackl, C. W.

2017-02-01

Underplatform dampers (UPD) are commonly used in aircraft engines to mitigate the risk of high-cycle fatigue failure of turbine blades. The energy dissipated at the friction contact interface of the damper reduces the vibration amplitude significantly, and the couplings of the blades can also lead to significant shifts of the resonance frequencies of the bladed disk. The highly nonlinear behaviour of bladed discs constrained by UPDs requires an advanced modelling approach to ensure that the correct damper geometry is selected during the design of the turbine, and that no unexpected resonance frequencies and amplitudes will occur in operation. Approaches based on an explicit model of the damper in combination with multi-harmonic balance solvers have emerged as a promising way to predict the nonlinear behaviour of UPDs correctly, however rigorous experimental validations are required before approaches of this type can be used with confidence. In this study, a nonlinear analysis based on an updated explicit damper model having different levels of detail is performed, and the results are evaluated against a newly-developed UPD test rig. Detailed linear finite element models are used as input for the nonlinear analysis, allowing the inclusion of damper flexibility and inertia effects. The nonlinear friction interface between the blades and the damper is described with a dense grid of 3D friction contact elements which allow accurate capturing of the underlying nonlinear mechanism that drives the global nonlinear behaviour. The introduced explicit damper model showed a great dependence on the correct contact pressure distribution. The use of an accurate, measurement based, distribution, better matched the nonlinear dynamic behaviour of the test rig. Good agreement with the measured frequency response data could only be reached when the zero harmonic term (constant term) was included in the multi-harmonic expansion of the nonlinear problem, highlighting its importance when the contact interface experiences large normal load variation. The resulting numerical damper kinematics with strong translational and rotational motion, and the global blades frequency response were fully validated experimentally, showing the accuracy of the suggested high detailed explicit UPD modelling approach.

Factors influencing export of dissolved inorganic nitrogen by major rivers: A new seasonal, spatially explicit, global model - 2012

EPA Science Inventory

Background/Question/Methods Substantial effort has focused on understanding spatial variation in dissolved inorganic nitrogen (DIN) export to the coastal zone and specific basins have been studied in some depth. Much less is known, however, about seasonal patterns and zone and ...

Factors influencing export of dissolved inorganic nitrogen by major rivers: a new seasonal, spatially explicit, global model

EPA Science Inventory

Background/Question/Methods Substantial effort has focused on understanding spatial variation in dissolved inorganic nitrogen (DIN) export to the coastal zone and specific basins have been studied in some depth. Much less is known, however, about seasonal patterns and controls ...

Spatially-explicit and spectral soil carbon modeling in Florida

USDA-ARS?s Scientific Manuscript database

Profound shifts have occurred over the last three centuries in which human actions have become the main driver to global environmental change. In this new epoch, the Anthropocene, human-driven changes such as population growth, climate and land use change, are pushing the Earth system well outside i...

Factors influencing export of dissolved inorganic nitrogen by major rivers: A new, seasonal, spatially explicit, global model

EPA Science Inventory

Substantial effort has focused on understanding spatial variation in dissolved inorganic nitrogen (DIN) export to the coastal zone and specific basins have been studied in depth. Much less is known, however, about seasonal patterns and controls of coastal DIN delivery across larg...

Revisiting the global surface energy budgets with maximum-entropy-production model of surface heat fluxes

NASA Astrophysics Data System (ADS)

Huang, Shih-Yu; Deng, Yi; Wang, Jingfeng

2017-09-01

The maximum-entropy-production (MEP) model of surface heat fluxes, based on contemporary non-equilibrium thermodynamics, information theory, and atmospheric turbulence theory, is used to re-estimate the global surface heat fluxes. The MEP model predicted surface fluxes automatically balance the surface energy budgets at all time and space scales without the explicit use of near-surface temperature and moisture gradient, wind speed and surface roughness data. The new MEP-based global annual mean fluxes over the land surface, using input data of surface radiation, temperature data from National Aeronautics and Space Administration-Clouds and the Earth's Radiant Energy System (NASA CERES) supplemented by surface specific humidity data from the Modern-Era Retrospective Analysis for Research and Applications (MERRA), agree closely with previous estimates. The new estimate of ocean evaporation, not using the MERRA reanalysis data as model inputs, is lower than previous estimates, while the new estimate of ocean sensible heat flux is higher than previously reported. The MEP model also produces the first global map of ocean surface heat flux that is not available from existing global reanalysis products.

LES with and without explicit filtering: comparison and assessment of various models

NASA Astrophysics Data System (ADS)

Winckelmans, Gregoire S.; Jeanmart, Herve; Wray, Alan A.; Carati, Daniele

2000-11-01

The proper mathematical formalism for large eddy simulation (LES) of turbulent flows assumes that a regular ``explicit" filter (i.e., a filter with a well-defined second moment, such as the gaussian, the top hat, etc.) is applied to the equations of fluid motion. This filter is then responsible for a ``filtered-scale" stress. Because of the discretization of the filtered equations, using the LES grid, there is also a ``subgrid-scale" stress. The global effective stress is found to be the discretization of a filtered-scale stress plus a subgrid-scale stress. The former can be partially reconstructed from an exact, infinite, series, the first term of which is the ``tensor-diffusivity" model of Leonard and is found, in practice, to be sufficient for modeling. Alternatively, sufficient reconstruction can also be achieved using the ``scale-similarity" model of Bardina. The latter corresponds to loss of information: it cannot be reconstructed; its effect (essentially dissipation) must be modeled using ad hoc modeling strategies (such as the dynamic version of the ``effective viscosity" model of Smagorinsky). Practitionners also often assume LES without explicit filtering: the effective stress is then only a subgrid-scale stress. We here compare the performance of various LES models for both approaches (with and without explicit filtering), and for cases without solid boundaries: (1) decay of isotropic turbulence; (2) decay of aircraft wake vortices in a turbulent atmosphere. One main conclusion is that better subgrid-scale models are still needed, the effective viscosity models being too active at the large scales.

Visual crowding illustrates the inadequacy of local vs. global and feedforward vs. feedback distinctions in modeling visual perception

PubMed Central

Clarke, Aaron M.; Herzog, Michael H.; Francis, Gregory

2014-01-01

Experimentalists tend to classify models of visual perception as being either local or global, and involving either feedforward or feedback processing. We argue that these distinctions are not as helpful as they might appear, and we illustrate these issues by analyzing models of visual crowding as an example. Recent studies have argued that crowding cannot be explained by purely local processing, but that instead, global factors such as perceptual grouping are crucial. Theories of perceptual grouping, in turn, often invoke feedback connections as a way to account for their global properties. We examined three types of crowding models that are representative of global processing models, and two of which employ feedback processing: a model based on Fourier filtering, a feedback neural network, and a specific feedback neural architecture that explicitly models perceptual grouping. Simulations demonstrate that crucial empirical findings are not accounted for by any of the models. We conclude that empirical investigations that reject a local or feedforward architecture offer almost no constraints for model construction, as there are an uncountable number of global and feedback systems. We propose that the identification of a system as being local or global and feedforward or feedback is less important than the identification of a system's computational details. Only the latter information can provide constraints on model development and promote quantitative explanations of complex phenomena. PMID:25374554

Harnessing Big Data to Represent 30-meter Spatial Heterogeneity in Earth System Models

NASA Astrophysics Data System (ADS)

Chaney, N.; Shevliakova, E.; Malyshev, S.; Van Huijgevoort, M.; Milly, C.; Sulman, B. N.

2016-12-01

Terrestrial land surface processes play a critical role in the Earth system; they have a profound impact on the global climate, food and energy production, freshwater resources, and biodiversity. One of the most fascinating yet challenging aspects of characterizing terrestrial ecosystems is their field-scale (˜30 m) spatial heterogeneity. It has been observed repeatedly that the water, energy, and biogeochemical cycles at multiple temporal and spatial scales have deep ties to an ecosystem's spatial structure. Current Earth system models largely disregard this important relationship leading to an inadequate representation of ecosystem dynamics. In this presentation, we will show how existing global environmental datasets can be harnessed to explicitly represent field-scale spatial heterogeneity in Earth system models. For each macroscale grid cell, these environmental data are clustered according to their field-scale soil and topographic attributes to define unique sub-grid tiles. The state-of-the-art Geophysical Fluid Dynamics Laboratory (GFDL) land model is then used to simulate these tiles and their spatial interactions via the exchange of water, energy, and nutrients along explicit topographic gradients. Using historical simulations over the contiguous United States, we will show how a robust representation of field-scale spatial heterogeneity impacts modeled ecosystem dynamics including the water, energy, and biogeochemical cycles as well as vegetation composition and distribution.

High potential for weathering and climate effects of non-vascular vegetation in the Late Ordovician

NASA Astrophysics Data System (ADS)

Porada, Philipp; Lenton, Tim; Pohl, Alexandre; Weber, Bettina; Mander, Luke; Donnadieu, Yannick; Beer, Christian; Pöschl, Ulrich; Kleidon, Axel

2017-04-01

Early non-vascular vegetation in the Late Ordovician may have strongly increased chemical weathering rates of surface rocks at the global scale. This could have led to a drawdown of atmospheric CO2 and, consequently, a decrease in global temperature and an interval of glaciations. Under current climatic conditions, usually field or laboratory experiments are used to quantify enhancement of chemical weathering rates by non-vascular vegetation. However, these experiments are constrained to a small spatial scale and a limited number of species. This complicates the extrapolation to the global scale, even more so for the geological past, where physiological properties of non-vascular vegetation may have differed from current species. Here we present a spatially explicit modelling approach to simulate large-scale chemical weathering by non-vascular vegetation in the Late Ordovician. For this purpose, we use a process-based model of lichens and bryophytes, since these organisms are probably the closest living analogue to Late Ordovician vegetation. The model explicitly represents multiple physiological strategies, which enables the simulated vegetation to adapt to Ordovician climatic conditions. We estimate productivity of Ordovician vegetation with the model, and relate it to chemical weathering by assuming that the organisms dissolve rocks to extract phosphorus for the production of new biomass. Thereby we account for limits on weathering due to reduced supply of unweathered rock material in shallow regions, as well as decreased transport capacity of runoff for dissolved weathered material in dry areas. We simulate a potential global weathering flux of 2.8 km3 (rock) per year, which we define as volume of primary minerals affected by chemical transformation. Our estimate is around 3 times larger than today's global chemical weathering flux. Furthermore, chemical weathering rates simulated by our model are highly sensitive to atmospheric CO2 concentration, which implies a strong negative feedback between weathering by non-vascular vegetation and Ordovician climate.

A comparison of the performance of 1st order and 2nd order turbulence models when solving the RANS equations in reproducing the liquid film length unsteady response to momentum flux ratio in Gas-Centered Swirl-Coaxial Injectors in Rocket Engine Applications

DTIC Science & Technology

2012-06-07

scheme for the VOF requires the use of the explicit solver to advance the solution in time. The drawback of using the explicit solver is that such ap...proach required much smaller time steps to guarantee that a converged and stable solution is obtained during each fractional time step (Global...Comparable results were obtained for the solutions with the RSM model. 50x 25x 100x25x 25x200x 0.000 0.002 0.004 0.006 0.008 0.010 0 100 200 300

Global models for synthetic fuels planning

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

Lamontagne, J.

1983-10-01

This study was performed to identify the set of existing global models with the best potential for use in the US Synthetic Fuels Corporation's strategic planning process, and to recommend the most appropriate model. The study was limited to global models with representations that encompass time horizons beyond the year 2000, multiple fuel forms, and significant regional detail. Potential accessibility to the Synthetic Fuels Corporation and adequate documentation were also required. Four existing models (LORENDAS, WIM, IIASA, and IEA/ORAU) were judged to be the best candidates for the SFC's use at this time; none of the models appears to bemore » ideal for the SFC's purposes. On the basis of currently available information, the most promising short-term option open to the SFC is the use of LORENDAS, with careful attention to definition of alternative energy demand scenarios. Longer-term options which deserve further study are coupling LORENDAS with an explicit model of energy demand, and modification of the IEA/ORAU model to include finer time-period definition and additional technological detail.« less

Parameterization of dust emissions in the global atmospheric chemistry-climate model EMAC: impact of nudging and soil properties

NASA Astrophysics Data System (ADS)

Astitha, M.; Lelieveld, J.; Abdel Kader, M.; Pozzer, A.; de Meij, A.

2012-11-01

Airborne desert dust influences radiative transfer, atmospheric chemistry and dynamics, as well as nutrient transport and deposition. It directly and indirectly affects climate on regional and global scales. Two versions of a parameterization scheme to compute desert dust emissions are incorporated into the atmospheric chemistry general circulation model EMAC (ECHAM5/MESSy2.41 Atmospheric Chemistry). One uses a globally uniform soil particle size distribution, whereas the other explicitly accounts for different soil textures worldwide. We have tested these two versions and investigated the sensitivity to input parameters, using remote sensing data from the Aerosol Robotic Network (AERONET) and dust concentrations and deposition measurements from the AeroCom dust benchmark database (and others). The two versions are shown to produce similar atmospheric dust loads in the N-African region, while they deviate in the Asian, Middle Eastern and S-American regions. The dust outflow from Africa over the Atlantic Ocean is accurately simulated by both schemes, in magnitude, location and seasonality. Approximately 70% of the modelled annual deposition data and 70-75% of the modelled monthly aerosol optical depth (AOD) in the Atlantic Ocean stations lay in the range 0.5 to 2 times the observations for all simulations. The two versions have similar performance, even though the total annual source differs by ~50%, which underscores the importance of transport and deposition processes (being the same for both versions). Even though the explicit soil particle size distribution is considered more realistic, the simpler scheme appears to perform better in several locations. This paper discusses the differences between the two versions of the dust emission scheme, focusing on their limitations and strengths in describing the global dust cycle and suggests possible future improvements.

Long-run evolution of the global economy: 2. Hindcasts of innovation and growth

NASA Astrophysics Data System (ADS)

Garrett, T. J.

2015-03-01

Long-range climate forecasts rely upon integrated assessment models that link the global economy to greenhouse gas emissions. This paper evaluates an alternative economic framework, outlined in Part 1, that is based on physical principles rather than explicitly resolved societal dynamics. Relative to a reference model of persistence in trends, model hindcasts that are initialized with data from 1950 to 1960 reproduce trends in global economic production and energy consumption between 2000 and 2010 with a skill score greater than 90%. In part, such high skill appears to be because civilization has responded to an impulse of fossil fuel discovery in the mid-twentieth century. Forecasting the coming century will be more of a challenge because the effect of the impulse appears to have nearly run its course. Nonetheless, the model offers physically constrained futures for the coupled evolution of civilization and climate during the Anthropocene.

Why Is Rainfall Error Analysis Requisite for Data Assimilation and Climate Modeling?

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.

2004-01-01

Given the large temporal and spatial variability of precipitation processes, errors in rainfall observations are difficult to quantify yet crucial to making effective use of rainfall data for improving atmospheric analysis, weather forecasting, and climate modeling. We highlight the need for developing a quantitative understanding of systematic and random errors in precipitation observations by examining explicit examples of how each type of errors can affect forecasts and analyses in global data assimilation. We characterize the error information needed from the precipitation measurement community and how it may be used to improve data usage within the general framework of analysis techniques, as well as accuracy requirements from the perspective of climate modeling and global data assimilation.

An integrated conceptual framework for long-term social-ecological research

Treesearch

S.L. Collins; S.R. Carpenter; S.M. Swinton; D.E. Orenstein; D.L. Childers; T.L. Gragson; N.B. Grimm; J.M. Grove; S.L. Harlan; J.P. Kaye; A.K. Knapp; G.P. Kofinas; J.J. Magnuson; W.H. McDowell; J.M. Melack; L.A. Ogden; G.P. Robertson; M.D. Smith; A.C. Whitmer

2010-01-01

The global reach of human activities affects all natural ecosystems, so that the environment is best viewed as a social-ecological system. Consequently, a more integrative approach to environmental science, one that bridges the biophysical and social domains, is sorely needed. Although models and frameworks for social-ecological systems exist, few are explicitly...

Global Simulation of Bioenergy Crop Productivity: Analytical Framework and Case Study for Switchgrass

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

Kang, Shujiang; Kline, Keith L; Nair, S. Surendran

A global energy crop productivity model that provides geospatially explicit quantitative details on biomass potential and factors affecting sustainability would be useful, but does not exist now. This study describes a modeling platform capable of meeting many challenges associated with global-scale agro-ecosystem modeling. We designed an analytical framework for bioenergy crops consisting of six major components: (i) standardized natural resources datasets, (ii) global field-trial data and crop management practices, (iii) simulation units and management scenarios, (iv) model calibration and validation, (v) high-performance computing (HPC) simulation, and (vi) simulation output processing and analysis. The HPC-Environmental Policy Integrated Climate (HPC-EPIC) model simulatedmore » a perennial bioenergy crop, switchgrass (Panicum virgatum L.), estimating feedstock production potentials and effects across the globe. This modeling platform can assess soil C sequestration, net greenhouse gas (GHG) emissions, nonpoint source pollution (e.g., nutrient and pesticide loss), and energy exchange with the atmosphere. It can be expanded to include additional bioenergy crops (e.g., miscanthus, energy cane, and agave) and food crops under different management scenarios. The platform and switchgrass field-trial dataset are available to support global analysis of biomass feedstock production potential and corresponding metrics of sustainability.« less

How a new funding model will shift allocations from the Global Fund to Fight AIDS, tuberculosis, and malaria.

PubMed

Fan, Victoria Y; Glassman, Amanda; Silverman, Rachel L

2014-12-01

Policy makers deciding how to fund global health programs in low- and middle-income countries face important but difficult questions about how to allocate resources across countries. In this article we present a typology of three allocation methodologies to align allocations with priorities. We then apply our typology to the Global Fund to Fight AIDS, Tuberculosis, and Malaria. We examined the Global Fund's historical HIV allocations and its predicted allocations under a new funding model that creates an explicit allocation methodology. We found that under the new funding model, substantial shifts in the Global Fund's portfolio are likely to result from concentrating resources in countries with more HIV cases and lower per capita incomes. For example, South Africa, which had 15.8 percent of global HIV cases in 2009, could see its Global Fund HIV funding more than triple, from historic levels that averaged 3.0 percent to 9.7 percent of total Global Fund allocations. The new funding model methodology is expected, but not guaranteed, to improve the efficiency of Global Fund allocations in comparison to historical practice. We conclude with recommendations for the Global Fund and other global health donors to further develop their allocation methodologies and processes to improve efficiency and transparency. Project HOPE—The People-to-People Health Foundation, Inc.

Influence of explicit Phaeocystis parameterizations on the global distribution of marine dimethyl sulfide

DOE PAGES

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

2015-10-07

Dimethyl sulfide (DMS) is a biogenic organosulfur compound which contributes strongly to marine aerosol mass and the determination of cloud condensation nuclei over the remote oceans. Since uncertainties in DMS flux to the atmosphere lead to large variations in climate forcing, the global DMS distribution has been the subject of increasingly complex dynamic simulations. DMS concentrations are directly controlled by marine ecosystems. Phaeocystis is a major DMS producer but is often omitted from global reduced sulfur mechanisms. Here we incorporate this phytoplankton group into the marine ecosystem-biogeochemical module of the Community Earth System Model. To examine its role in themore » ocean sulfur cycle, an earlier DMS model has been enhanced to include new knowledge gained over the last few years. Results from the baseline run show that simulated Phaeocystis biomass generally agrees with observations, with high concentrations near the Antarctic continent and between 50° and 60° north. Given the new explicit Phaeocystis representation, the DMS distribution shows significant improvements, especially regarding the amplitude and location of high-latitude peaks. The simulated global mean surface DMS value is 2.26 nM, comparable to an estimate of 2.34 nM from the latest climatology extrapolated based on observations. The total oceanic DMS source to the atmosphere is 20.4 Tg S/yr, on the low side of previous estimates. Comparisons with and without Phaeocystis show that the group dominates DMS distributions in temperate and cold waters, contributing 13% of the global flux. The proportion may increase as sea ice declines and should be considered in climate projections.« less

Scaling a Convection-Resolving RCM to Near-Global Scales

NASA Astrophysics Data System (ADS)

Leutwyler, D.; Fuhrer, O.; Chadha, T.; Kwasniewski, G.; Hoefler, T.; Lapillonne, X.; Lüthi, D.; Osuna, C.; Schar, C.; Schulthess, T. C.; Vogt, H.

2017-12-01

In the recent years, first decade-long kilometer-scale resolution RCM simulations have been performed on continental-scale computational domains. However, the size of the planet Earth is still an order of magnitude larger and thus the computational implications of performing global climate simulations at this resolution are challenging. We explore the gap between the currently established RCM simulations and global simulations by scaling the GPU accelerated version of the COSMO model to a near-global computational domain. To this end, the evolution of an idealized moist baroclinic wave has been simulated over the course of 10 days with a grid spacing of up to 930 m. The computational mesh employs 36'000 x 16'001 x 60 grid points and covers 98.4% of the planet's surface. The code shows perfect weak scaling up to 4'888 Nodes of the Piz Daint supercomputer and yields 0.043 simulated years per day (SYPD) which is approximately one seventh of the 0.2-0.3 SYPD required to conduct AMIP-type simulations. However, at half the resolution (1.9 km) we've observed 0.23 SYPD. Besides formation of frontal precipitating systems containing embedded explicitly-resolved convective motions, the simulations reveal a secondary instability that leads to cut-off warm-core cyclonic vortices in the cyclone's core, once the grid spacing is refined to the kilometer scale. The explicit representation of embedded moist convection and the representation of the previously unresolved instabilities exhibit a physically different behavior in comparison to coarser-resolution simulations. The study demonstrates that global climate simulations using kilometer-scale resolution are imminent and serves as a baseline benchmark for global climate model applications and future exascale supercomputing systems.

Evaluating the effects of climate change on US agricultural systems: sensitivity to regional impact and trade expansion scenarios

NASA Astrophysics Data System (ADS)

Baker, Justin S.; Havlík, Petr; Beach, Robert; Leclère, David; Schmid, Erwin; Valin, Hugo; Cole, Jefferson; Creason, Jared; Ohrel, Sara; McFarland, James

2018-06-01

Agriculture is one of the sectors that is expected to be most significantly impacted by climate change. There has been considerable interest in assessing these impacts and many recent studies investigating agricultural impacts for individual countries and regions using an array of models. However, the great majority of existing studies explore impacts on a country or region of interest without explicitly accounting for impacts on the rest of the world. This approach can bias the results of impact assessments for agriculture given the importance of global trade in this sector. Due to potential impacts on relative competitiveness, international trade, global supply, and prices, the net impacts of climate change on the agricultural sector in each region depend not only on productivity impacts within that region, but on how climate change impacts agricultural productivity throughout the world. In this study, we apply a global model of agriculture and forestry to evaluate climate change impacts on US agriculture with and without accounting for climate change impacts in the rest of the world. In addition, we examine scenarios where trade is expanded to explore the implications for regional allocation of production, trade volumes, and prices. To our knowledge, this is one of the only attempts to explicitly quantify the relative importance of accounting for global climate change when conducting regional assessments of climate change impacts. The results of our analyses reveal substantial differences in estimated impacts on the US agricultural sector when accounting for global impacts vs. US-only impacts, particularly for commodities where the United States has a smaller share of global production. In addition, we find that freer trade can play an important role in helping to buffer regional productivity shocks.

Spatial-explicit modeling of social vulnerability to malaria in East Africa

PubMed Central

2014-01-01

Background Despite efforts in eradication and control, malaria remains a global challenge, particularly affecting vulnerable groups. Despite the recession in malaria cases, previously malaria free areas are increasingly confronted with epidemics as a result of changing environmental and socioeconomic conditions. Next to modeling transmission intensities and probabilities, integrated spatial methods targeting the complex interplay of factors that contribute to social vulnerability are required to effectively reduce malaria burden. We propose an integrative method for mapping relative levels of social vulnerability in a spatially explicit manner to support the identification of intervention measures. Methods Based on a literature review, a holistic risk and vulnerability framework has been developed to guide the assessment of social vulnerability to water-related vector-borne diseases (VBDs) in the context of changing environmental and societal conditions. Building on the framework, this paper applies spatially explicit modeling for delineating homogeneous regions of social vulnerability to malaria in eastern Africa, while taking into account expert knowledge for weighting the single vulnerability indicators. To assess the influence of the selected indicators on the final index a local sensitivity analysis is carried out. Results Results indicate that high levels of malaria vulnerability are concentrated in the highlands, where immunity within the population is currently low. Additionally, regions with a lack of access to education and health services aggravate vulnerability. Lower values can be found in regions with relatively low poverty, low population pressure, low conflict density and reduced contributions from the biological susceptibility domain. Overall, the factors characterizing vulnerability vary spatially in the region. The vulnerability index reveals a high level of robustness in regard to the final choice of input datasets, with the exception of the immunity indicator which has a marked impact on the composite vulnerability index. Conclusions We introduce a conceptual framework for modeling risk and vulnerability to VBDs. Drawing on the framework we modeled social vulnerability to malaria in the context of global change using a spatially explicit approach. The results provide decision makers with place-specific options for targeting interventions that aim at reducing the burden of the disease amongst the different vulnerable population groups. PMID:25127688

Implicit-Explicit Formulations of a Three-Dimensional Nonhydrostatic Unified Model of the Atmosphere (NUMA)

DTIC Science & Technology

2013-01-01

Gravity Wave. A slice of the potential temperature perturbation (at y=50 km) after 700 s for 30× 30× 5 elements with 4th-order polynomials . The contour...CONSTANTINESCU ‡ Key words. cloud-resolving model; compressible flow; element-based Galerkin methods; Euler; global model; IMEX; Lagrange; Legendre ...methods in terms of accuracy and efficiency for two types of geophysical fluid dynamics problems: buoyant convection and inertia- gravity waves. These

The Coastal Dynamics of Heterogeneous Sedimentary Environments: Numerical Modeling of Nearshore Hydrodynamics and Sediment Transport

DTIC Science & Technology

2010-05-10

supplied boundary data for Hurricane Katrina (Keen, Furukawa et al. 2006; Keen, Slingerland et al. 2010). The numerical models discussed in this report...explicitly. NCOM can be nested to a coarse-grid model to supply boundary conditions at the open boundary of the domain. NCOM has been validated at global...circulation study of Mississippi Sound (Keen 2002), which supplied steady currents for the nearshore erosion problem discussed in this report

Improved data for integrated modeling of global environmental change

NASA Astrophysics Data System (ADS)

Lotze-Campen, Hermann

2011-12-01

The assessment of global environmental changes, their impact on human societies, and possible management options requires large-scale, integrated modeling efforts. These models have to link biophysical with socio-economic processes, and they have to take spatial heterogeneity of environmental conditions into account. Land use change and freshwater use are two key research areas where spatial aggregation and the use of regional average numbers may lead to biased results. Useful insights can only be obtained if processes like economic globalization can be consistently linked to local environmental conditions and resource constraints (Lambin and Meyfroidt 2011). Spatially explicit modeling of environmental changes at the global scale has a long tradition in the natural sciences (Woodward et al 1995, Alcamo et al 1996, Leemans et al 1996). Socio-economic models with comparable spatial detail, e.g. on grid-based land use change, are much less common (Heistermann et al 2006), but are increasingly being developed (Popp et al 2011, Schneider et al 2011). Spatially explicit models require spatially explicit input data, which often constrains their development and application at the global scale. The amount and quality of available data on environmental conditions is growing fast—primarily due to improved earth observation methods. Moreover, systematic efforts for collecting and linking these data across sectors are on the way (www.earthobservations.org). This has, among others, also helped to provide consistent databases on different land cover and land use types (Erb et al 2007). However, spatially explicit data on specific anthropogenic driving forces of global environmental change are still scarce—also because these cannot be collected with satellites or other devices. The basic data on socio-economic driving forces, i.e. population density and wealth (measured as gross domestic product per capita), have been prepared for spatially explicit analyses (CIESIN, IFPRI and WRI 2000, Nordhaus 2006) and there is also some information on road networks and the travel time to the nearest cities (Nelson 2008). However, this information has not so far been integrated to facilitate analyses of market access and market influence, which has hampered many socio-economic analyses to date. The analysis by Verburg et al (2011) provides an important improvement in this respect. They developed a consistent global dataset on various market accessibility indicators on a 1 km2 spatial resolution. Their analysis shows that market access is distinctly different from population patterns in some regions, which may help us to understand the prevalence of current economic conditions there. These are mostly areas with high population density, but little access to markets and, hence, a large share of subsistence farming and local economic activities. Measures of market access and market influence can improve our understanding about the drivers of environmental change, as they link regional and global economic activity to local environmental conditions. They can also help to assess, design and implement targeted measures to reduce environmental pressure and improve ecosystem services. The analysis and dataset provided by Verburg et al demonstrates the kind of valuable insights that can be generated by an integration of earth observation data, local case studies and modeling efforts at different spatial scales. This integration can improve monitoring, modeling and management of various global environmental changes, which will contribute to more sustainable economic development (Lotze-Campen et al 2008). Moreover, local market access is an important factor for economic development, poverty and food security. Aggregate, national figures, such as the human development index, do not provide sufficient detail. In many developing countries, certain rural areas lack market access and related options for development, as shown by Verburg et al for e.g. Nigeria and Ethiopia. Together with data from household studies, the new dataset could provide the basis for improved assessments of targeted infrastructure investment, which could help to reduce environmental degradation, promote economic development and alleviate poverty. References Alcamo J et al 1996 Baseline scenarios of global environmental change Glob. Environ. Change—Human Policy Dimens. 6 261-303 CIESIN, IFPRI and WRI 2000 Gridded Population of the World (GPW), Version 2 (available at http://sedac.ciesin.columbia.edu/plue/gpw, accessed March 2004) Erb K-H et al 2007 A comprehensive global 5 min resolution land-use data set for the year 2000 consistent with national census data J. Land Use Sci. 2 191-224 Heistermann M, Müller C and Ronneberger K 2006 Land in sight? Achievements, deficits and potentials of global land-use modeling Agric. Ecosyst. Environ. 114 141-58 Lambin E F and Meyfroidt P 2011 Global land use change, economic globalization, and the looming land scarcity Proc. Natl Acad. Sci. USA 108 3465-72 Leemans R et al 1996 The land cover and carbon cycle consequences of large-scale utilizations of biomass as an energy source Glob. Environ. Change 6 335-57 Lotze-Campen H, Reusswig F and Stoll-Kleemann S 2008 Socio-ecological monitoring of biodiversity change: building upon the world network of biosphere reserves GAIA—Ecological Perspectives for Science and Society 17 (Suppl. 1) 107-15 Nelson A 2008 Estimated travel time to the nearest city of 50,000 or more people in year 2000 (Ispra: Global Environment Monitoring Unit, Joint Research Centre of the European Commission) (available at http://bioval.jrc.ec.europa.eu/products/gam/download.htm, accessed August 2011) Nordhaus W D 2006 Geography and macroeconomics: new data and new findings Proc. Natl Acad. Sci. USA 103 3510-7 Popp A et al 2011 The economic potential of bioenergy for climate change mitigation with special attention given to implications for the land system Environ. Res. Lett. 6 034017 Schneider U A et al 2011 Impacts of population growth, economic development, and technical change on global food production and consumption Agricult. Syst. 104 204-15 Verburg P H, Ellis E C and Letourneau A 2011 A global assessment of market accessibility and market influence for global environmental change studies Environ. Res. Lett. 6 034019 Woodward F I, Smith T M and Emanuel W R 1995 A global land primary productivity and phytogeography model Glob. Biogeochem. Cycles 9 471-90

Global Similarity Predicts Dissociation of Classification and Recognition: Evidence Questioning the Implicit-Explicit Learning Distinction in Amnesia

ERIC Educational Resources Information Center

Jamieson, Randall K.; Holmes, Signy; Mewhort, D. J. K.

2010-01-01

Dissociation of classification and recognition in amnesia is widely taken to imply 2 functional systems: an implicit procedural-learning system that is spared in amnesia and an explicit episodic-learning system that is compromised. We argue that both tasks reflect the global similarity of probes to memory. In classification, subjects sort…

Downscaling CMIP5 climate models shows increased tropical cyclone activity over the 21st century

PubMed Central

Emanuel, Kerry A.

2013-01-01

A recently developed technique for simulating large [O(104)] numbers of tropical cyclones in climate states described by global gridded data is applied to simulations of historical and future climate states simulated by six Coupled Model Intercomparison Project 5 (CMIP5) global climate models. Tropical cyclones downscaled from the climate of the period 1950–2005 are compared with those of the 21st century in simulations that stipulate that the radiative forcing from greenhouse gases increases by over preindustrial values. In contrast to storms that appear explicitly in most global models, the frequency of downscaled tropical cyclones increases during the 21st century in most locations. The intensity of such storms, as measured by their maximum wind speeds, also increases, in agreement with previous results. Increases in tropical cyclone activity are most prominent in the western North Pacific, but are evident in other regions except for the southwestern Pacific. The increased frequency of events is consistent with increases in a genesis potential index based on monthly mean global model output. These results are compared and contrasted with other inferences concerning the effect of global warming on tropical cyclones. PMID:23836646

Global Symmetries of Six Dimensional Superconformal Field Theories

NASA Astrophysics Data System (ADS)

Merkx, Peter R.

In this work we investigate the global symmetries of six-dimensional superconformal field theories (6D SCFTs) via their description in F-theory. We provide computer algebra system routines determining global symmetry maxima for all known 6D SCFTs while tracking the singularity types of the associated elliptic fibrations. We tabulate these bounds for many CFTs including every 0-link based theory. The approach we take provides explicit tracking of geometric information which has remained implicit in the classifications of 6D SCFTs to date. We derive a variety of new geometric restrictions on collections of singularity collisions in elliptically fibered Calabi-Yau varieties and collect data from local model analyses of these collisions. The resulting restrictions are sufficient to match the known gauge enhancement structure constraints for all 6D SCFTs without appeal to anomaly cancellation and enable our global symmetry computations for F-theory SCFT models to proceed similarly.

Locally adaptive, spatially explicit projection of US population for 2030 and 2050.

PubMed

McKee, Jacob J; Rose, Amy N; Bright, Edward A; Huynh, Timmy; Bhaduri, Budhendra L

2015-02-03

Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Building on the spatial interpolation technique previously developed for high-resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically informed spatial distribution of projected population of the contiguous United States for 2030 and 2050, depicting one of many possible population futures. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection model departs from these by accounting for multiple components that affect population distribution. Modeled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the US Census's projection methodology, with the US Census's official projection as the benchmark. Applications of our model include incorporating multiple various scenario-driven events to produce a range of spatially explicit population futures for suitability modeling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.

Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence

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

Parishani, Hossein; Pritchard, Michael S.; Bretherton, Christopher S.

Systematic biases in the representation of boundary layer (BL) clouds are a leading source of uncertainty in climate projections. A variation on superparameterization (SP) called “ultraparameterization” (UP) is developed, in which the grid spacing of the cloud-resolving models (CRMs) is fine enough (250 × 20 m) to explicitly capture the BL turbulence, associated clouds, and entrainment in a global climate model capable of multiyear simulations. UP is implemented within the Community Atmosphere Model using 2° resolution (~14,000 embedded CRMs) with one-moment microphysics. By using a small domain and mean-state acceleration, UP is computationally feasible today and promising for exascale computers.more » Short-duration global UP hindcasts are compared with SP and satellite observations of top-of-atmosphere radiation and cloud vertical structure. The most encouraging improvement is a deeper BL and more realistic vertical structure of subtropical stratocumulus (Sc) clouds, due to stronger vertical eddy motions that promote entrainment. Results from 90 day integrations show climatological errors that are competitive with SP, with a significant improvement in the diurnal cycle of offshore Sc liquid water. Ongoing concerns with the current UP implementation include a dim bias for near-coastal Sc that also occurs less prominently in SP and a bright bias over tropical continental deep convection zones. Nevertheless, UP makes global eddy-permitting simulation a feasible and interesting alternative to conventionally parameterized GCMs or SP-GCMs with turbulence parameterizations for studying BL cloud-climate and cloud-aerosol feedback.« less

Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence

DOE PAGES

Parishani, Hossein; Pritchard, Michael S.; Bretherton, Christopher S.; ...

2017-06-19

Systematic biases in the representation of boundary layer (BL) clouds are a leading source of uncertainty in climate projections. A variation on superparameterization (SP) called “ultraparameterization” (UP) is developed, in which the grid spacing of the cloud-resolving models (CRMs) is fine enough (250 × 20 m) to explicitly capture the BL turbulence, associated clouds, and entrainment in a global climate model capable of multiyear simulations. UP is implemented within the Community Atmosphere Model using 2° resolution (~14,000 embedded CRMs) with one-moment microphysics. By using a small domain and mean-state acceleration, UP is computationally feasible today and promising for exascale computers.more » Short-duration global UP hindcasts are compared with SP and satellite observations of top-of-atmosphere radiation and cloud vertical structure. The most encouraging improvement is a deeper BL and more realistic vertical structure of subtropical stratocumulus (Sc) clouds, due to stronger vertical eddy motions that promote entrainment. Results from 90 day integrations show climatological errors that are competitive with SP, with a significant improvement in the diurnal cycle of offshore Sc liquid water. Ongoing concerns with the current UP implementation include a dim bias for near-coastal Sc that also occurs less prominently in SP and a bright bias over tropical continental deep convection zones. Nevertheless, UP makes global eddy-permitting simulation a feasible and interesting alternative to conventionally parameterized GCMs or SP-GCMs with turbulence parameterizations for studying BL cloud-climate and cloud-aerosol feedback.« less

Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence

NASA Astrophysics Data System (ADS)

Parishani, Hossein; Pritchard, Michael S.; Bretherton, Christopher S.; Wyant, Matthew C.; Khairoutdinov, Marat

2017-07-01

Systematic biases in the representation of boundary layer (BL) clouds are a leading source of uncertainty in climate projections. A variation on superparameterization (SP) called "ultraparameterization" (UP) is developed, in which the grid spacing of the cloud-resolving models (CRMs) is fine enough (250 × 20 m) to explicitly capture the BL turbulence, associated clouds, and entrainment in a global climate model capable of multiyear simulations. UP is implemented within the Community Atmosphere Model using 2° resolution (˜14,000 embedded CRMs) with one-moment microphysics. By using a small domain and mean-state acceleration, UP is computationally feasible today and promising for exascale computers. Short-duration global UP hindcasts are compared with SP and satellite observations of top-of-atmosphere radiation and cloud vertical structure. The most encouraging improvement is a deeper BL and more realistic vertical structure of subtropical stratocumulus (Sc) clouds, due to stronger vertical eddy motions that promote entrainment. Results from 90 day integrations show climatological errors that are competitive with SP, with a significant improvement in the diurnal cycle of offshore Sc liquid water. Ongoing concerns with the current UP implementation include a dim bias for near-coastal Sc that also occurs less prominently in SP and a bright bias over tropical continental deep convection zones. Nevertheless, UP makes global eddy-permitting simulation a feasible and interesting alternative to conventionally parameterized GCMs or SP-GCMs with turbulence parameterizations for studying BL cloud-climate and cloud-aerosol feedback.

Spatially explicit estimates of N2 O emissions from croplands suggest climate mitigation opportunities from improved fertilizer management.

PubMed

Gerber, James S; Carlson, Kimberly M; Makowski, David; Mueller, Nathaniel D; Garcia de Cortazar-Atauri, Iñaki; Havlík, Petr; Herrero, Mario; Launay, Marie; O'Connell, Christine S; Smith, Pete; West, Paul C

2016-10-01

With increasing nitrogen (N) application to croplands required to support growing food demand, mitigating N2 O emissions from agricultural soils is a global challenge. National greenhouse gas emissions accounting typically estimates N2 O emissions at the country scale by aggregating all crops, under the assumption that N2 O emissions are linearly related to N application. However, field studies and meta-analyses indicate a nonlinear relationship, in which N2 O emissions are relatively greater at higher N application rates. Here, we apply a super-linear emissions response model to crop-specific, spatially explicit synthetic N fertilizer and manure N inputs to provide subnational accounting of global N2 O emissions from croplands. We estimate 0.66 Tg of N2 O-N direct global emissions circa 2000, with 50% of emissions concentrated in 13% of harvested area. Compared to estimates from the IPCC Tier 1 linear model, our updated N2 O emissions range from 20% to 40% lower throughout sub-Saharan Africa and Eastern Europe, to >120% greater in some Western European countries. At low N application rates, the weak nonlinear response of N2 O emissions suggests that relatively large increases in N fertilizer application would generate relatively small increases in N2 O emissions. As aggregated fertilizer data generate underestimation bias in nonlinear models, high-resolution N application data are critical to support accurate N2 O emissions estimates. © 2016 John Wiley & Sons Ltd.

Global F-theory GUTs

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

Blumenhagen, Ralph; /Munich, Max Planck Inst.; Grimm, Thomas W.

2010-08-26

We construct global F-theory GUT models on del Pezzo surfaces in compact Calabi-Yau fourfolds realized as complete intersections of two hypersurface constraints. The intersections of the GUT brane and the flavour branes as well as the gauge flux are described by the spectral cover construction. We consider a split S[U(4) x U(1){sub X}] spectral cover, which allows for the phenomenologically relevant Yukawa couplings and GUT breaking to the MSSM via hypercharge flux while preventing dimension-4 proton decay. General expressions for the massless spectrum, consistency conditions and a new method for the computation of curvature-induced tadpoles are presented. We also providemore » a geometric toolkit for further model searches in the framework of toric geometry. Finally, an explicit global model with three chiral generations and all required Yukawa couplings is defined on a Calabi-Yau fourfold which is fibered over the del Pezzo transition of the Fano threefold P{sup 4}.« less

Blue water scarcity and the economic impacts of future agricultural trade and demand

NASA Astrophysics Data System (ADS)

Schmitz, Christoph; Lotze-Campen, Hermann; Gerten, Dieter; Dietrich, Jan Philipp; Bodirsky, Benjamin; Biewald, Anne; Popp, Alexander

2013-06-01

An increasing demand for agricultural goods affects the pressure on global water resources over the coming decades. In order to quantify these effects, we have developed a new agroeconomic water scarcity indicator, considering explicitly economic processes in the agricultural system. The indicator is based on the water shadow price generated by an economic land use model linked to a global vegetation-hydrology model. Irrigation efficiency is implemented as a dynamic input depending on the level of economic development. We are able to simulate the heterogeneous distribution of water supply and agricultural water demand for irrigation through the spatially explicit representation of agricultural production. This allows in identifying regional hot spots of blue water scarcity and explicit shadow prices for water. We generate scenarios based on moderate policies regarding future trade liberalization and the control of livestock-based consumption, dependent on different population and gross domestic product (GDP) projections. Results indicate increased water scarcity in the future, especially in South Asia, the Middle East, and north Africa. In general, water shadow prices decrease with increasing liberalization, foremost in South Asia, Southeast Asia, and the Middle East. Policies to reduce livestock consumption in developed countries not only lower the domestic pressure on water but also alleviate water scarcity to a large extent in developing countries. It is shown that one of the two policy options would be insufficient for most regions to retain water scarcity in 2045 on levels comparable to 2005.

Sensitivity of a model projection of near-surface permafrost degradation to soil column depth and representation of soil organic matter.

Treesearch

David M. Lawrence; Andrew G. Slater; Vladimir E. Romanovsky; Dmitry J. Nicolsky

2008-01-01

The sensitivity of a global land-surface model projection of near-surface permafrost degradation is assessed with respect to explicit accounting of the thermal and hydrologic properties of soil organic matter and to a deepening of the soil column from 3.5 to 50 or more m. Together these modifications result in substantial improvements in the simulation of near-surface...

Global marine bacterial diversity peaks at high latitudes in winter

PubMed Central

Ladau, Joshua; Sharpton, Thomas J; Finucane, Mariel M; Jospin, Guillaume; Kembel, Steven W; O'Dwyer, James; Koeppel, Alexander F; Green, Jessica L; Pollard, Katherine S

2013-01-01

Genomic approaches to characterizing bacterial communities are revealing significant differences in diversity and composition between environments. But bacterial distributions have not been mapped at a global scale. Although current community surveys are way too sparse to map global diversity patterns directly, there is now sufficient data to fit accurate models of how bacterial distributions vary across different environments and to make global scale maps from these models. We apply this approach to map the global distributions of bacteria in marine surface waters. Our spatially and temporally explicit predictions suggest that bacterial diversity peaks in temperate latitudes across the world's oceans. These global peaks are seasonal, occurring 6 months apart in the two hemispheres, in the boreal and austral winters. This pattern is quite different from the tropical, seasonally consistent diversity patterns observed for most macroorganisms. However, like other marine organisms, surface water bacteria are particularly diverse in regions of high human environmental impacts on the oceans. Our maps provide the first picture of bacterial distributions at a global scale and suggest important differences between the diversity patterns of bacteria compared with other organisms. PMID:23514781

Nearly scale invariant spectrum of gravitational radiation from global phase transitions.

PubMed

Jones-Smith, Katherine; Krauss, Lawrence M; Mathur, Harsh

2008-04-04

Using a large N sigma model approximation we explicitly calculate the power spectrum of gravitational waves arising from a global phase transition in the early Universe and we confirm that it is scale invariant, implying an observation of such a spectrum may not be a unique feature of inflation. Moreover, the predicted amplitude can be over 3 orders of magnitude larger than the naive dimensional estimate, implying that even a transition that occurs after inflation may dominate in cosmic microwave background polarization or other gravity wave signals.

Fermionic vacuum polarization in a higher-dimensional global monopole spacetime

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

Bezerra de Mello, E. R.

2007-12-15

In this paper we analyze the vacuum polarization effects associated with a massless fermionic field in a higher-dimensional global monopole spacetime in the 'braneworld' scenario. In this context we admit that our Universe, the bulk, is represented by a flat (n-1)-dimensional brane having a global monopole in an extra transverse three-dimensional submanifold. We explicitly calculate the renormalized vacuum average of the energy-momentum tensor, {sub Ren}, admitting the global monopole as being a pointlike object. We observe that this quantity depends crucially on the value of n, and provide explicit expressions to it for specific values attributed to n.

Persistence of Rift Valley fever virus in East Africa

NASA Astrophysics Data System (ADS)

Gachohi, J.; Hansen, F.; Bett, B.; Kitala, P.

2012-04-01

Rift Valley fever virus (RVFv) is a mosquito-borne pathogen of livestock, wildlife and humans that causes severe outbreaks in intervals of several years. One of the open questions is how the virus persists between outbreaks. We developed a spatially-explicit, individual-based simulation model of the RVFv transmission dynamics to investigate this question. The model, is based on livestock and mosquito population dynamics. Spatial aspects are explicitly represented by a set of grid cells that represent mosquito breeding sites. A grid cell measures 500 by 500m and the model considers a grid of 100 by 100 grid cells; the model thus operates on the regional scale of 2500km2. Livestock herds move between grid cells, and provide connectivity between the cells. The model is used to explore the spatio-temporal dynamics of RVFv persistence in absence of a wildlife reservoir in an east African semi-arid context. Specifically, the model assesses the importance of local virus persistence in mosquito breeding sites relative to global virus persistence mitigated by movement of hosts. Local persistence is determined by the length of time the virus remains in a mosquito breeding site once introduced. In the model, this is a function of the number of mosquitoes that emerge infected and their lifespan. Global persistence is determined by the level of connectivity between isolated grid cells. Our work gives insights into the ecological and epidemiological conditions under which RVFv persists. The implication for disease surveillance and management are discussed.

Long-run evolution of the global economy - Part 2: Hindcasts of innovation and growth

NASA Astrophysics Data System (ADS)

Garrett, T. J.

2015-10-01

Long-range climate forecasts use integrated assessment models to link the global economy to greenhouse gas emissions. This paper evaluates an alternative economic framework outlined in part 1 of this study (Garrett, 2014) that approaches the global economy using purely physical principles rather than explicitly resolved societal dynamics. If this model is initialized with economic data from the 1950s, it yields hindcasts for how fast global economic production and energy consumption grew between 2000 and 2010 with skill scores > 90 % relative to a model of persistence in trends. The model appears to attain high skill partly because there was a strong impulse of discovery of fossil fuel energy reserves in the mid-twentieth century that helped civilization to grow rapidly as a deterministic physical response. Forecasting the coming century may prove more of a challenge because the effect of the energy impulse appears to have nearly run its course. Nonetheless, an understanding of the external forces that drive civilization may help development of constrained futures for the coupled evolution of civilization and climate during the Anthropocene.

Awakening the Scientist Inside: Global Climate Change and the Nature of Science in an Elementary Science Methods Course

NASA Astrophysics Data System (ADS)

Matkins, Juanita Jo; Bell, Randy L.

2007-04-01

This investigation assessed the impact of situating explicit nature of science (NOS) instruction within the issues surrounding global climate change and global warming (GCC/GW). Participants in the study were 15 preservice elementary teachers enrolled in a science methods course. The instructional intervention included explicit NOS instruction combined with explicit GCC/GW instruction situated within the normal elementary science methods curriculum. Participants’ conceptions of NOS and GCC/GW were assessed with pre- and postadministrations of open-ended questionnaires and interviews. Results indicated that participants’ conceptions of NOS and GCC/GW improved over the course of the semester. Furthermore, participants were able to apply their conceptions to decision making about socioscientific issues. The results provide support for context-based NOS instruction in an elementary science methods course.

Confronting Future Risks of Global Water Stress and Sustainability: Avoided Changes Versus Adaptive Actions

NASA Astrophysics Data System (ADS)

Schlosser, C. A.; Strzepek, K. M.; Gao, X.; Fant, C.; Paltsev, S.; Monier, E.; Sokolov, A. P.; Winchester, N.; Chen, H.; Kicklighter, D. W.; Ejaz, Q.

2016-12-01

We examine the fate of global water resources under a range of self-consistent socio-economic projections using the MIT Integrated Global System Model (IGSM) under a range of plausible mitigation and adaptation scenarios of development to the water-energy-land systems and against an assessment of the results from the UN COP-21 meeting. We assess the trends of an index of managed water stress as well as unmet water demands as simulated by the Water Resource System within the IGSM framework (IGSM-WRS). The WRS is forced by the simulations of the global climate response, variations in regional climate pattern changes, as well as the socio-economic drivers from the IGSM scenarios. We focus on the changes in water-stress metrics in the coming decades and going into the latter half of this century brought about by our projected climate and socio-economic changes, as well as the total (additional) populations affected by increased stress. We highlight selected basins to demonstrate sensitivities and interplay between supply and demand, the uncertainties in global climate sensitivity as well as regional climate change, and their implications to assessing and reducing water risks and the populations affected by water scarcity. We also evaluate the impact of explicitly representing irrigated land and water scarcity in an economy-wide model on food prices, bioenergy production and deforestation both with and without a global carbon policy. We highlight the importance of adaptive measures that will be required, worldwide, to meet surface-water shortfalls even under more aggressive and certainly under intermediate climate mitigation pathways - and further analyses is presented in this context quantifying risks averted and their associated costs. In addition, we also demonstrate that the explicit representation of irrigated land within this intergrated modeling frameowork has a small impact on food, bioenergy and deforestation outcomes within the scenarios considered. Nevertheless, globally speaking the scenarios indicate that going into the latter half of the twentieth century, approximately one-and-a-half billion additional people will experience at least moderately stressed water conditions worldwide and of that 1 billion will be at least will be living within regions under heavily stressed water conditions.

Tracing global supply chains to air pollution hotspots

NASA Astrophysics Data System (ADS)

Moran, Daniel; Kanemoto, Keiichiro

2016-09-01

While high-income countries have made significant strides since the 1970s in improving air quality, air pollution continues to rise in many developing countries and the world as a whole. A significant share of the pollution burden in developing countries can be attributed to production for export to consumers in high-income nations. However, it remains a challenge to quantify individual actors’ share of responsibility for pollution, and to involve parties other than primary emitters in cleanup efforts. Here we present a new spatially explicit modeling approach to link SO2, NO x , and PM10 severe emissions hotspots to final consumers via global supply chains. These maps show developed countries reducing their emissions domestically but driving new pollution hotspots in developing countries. This is also the first time a spatially explicit footprint inventory has been established. Linking consumers and supply chains to emissions hotspots creates opportunities for other parties to participate alongside primary emitters and local regulators in pollution abatement efforts.

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.

Improving Secondary Organic Aerosol (SOA) Models using Global Sensitivity Analysis and by Comparison to Chamber Data.

NASA Astrophysics Data System (ADS)

Miller, D. O.; Brune, W. H.

2017-12-01

Accurate estimates of secondary organic aerosol (SOA) from atmospheric models is a major research challenge due to the complexity of the chemical and physical processes involved in the SOA formation and continuous aging. The primary uncertainties of SOA models include those associated with the formation of gas-phase products, the conversion between gas phase and particle phase, the aging mechanisms of SOA, and other processes related to the heterogeneous and particle-phase reactions. To address this challenge, we us a modular modeling framework that combines both simple and near-explicit gas-phase reactions and a two-dimensional volatility basis set (2D-VBS) to simulate the formation and evolution of SOA. Global sensitivity analysis is used to assess the relative importance of the model input parameters. In addition, the model is compared to the measurements from the Focused Isoprene eXperiment at the California Institute of Technology (FIXCIT).

Tradeoffs in Acceleration and Initialization of Superparameterized Global Atmospheric Models for MJO and Climate Science

NASA Astrophysics Data System (ADS)

Pritchard, M. S.; Bretherton, C. S.; DeMott, C. A.

2014-12-01

New trade-offs are discussed in the cloud superparameterization approach to explicitly representing deep convection in global climate models. Intrinsic predictability tests show that the memory of cloud-resolving-scale organization is not critical for producing desired modes of organized convection such as the Madden-Julian Oscillation (MJO). This has implications for the feasibility of data assimilation and real-world initialization for superparameterized weather forecasting. Climate simulation sensitivity tests demonstrate that 400% acceleration of cloud superparameterization is possible by restricting the 32-128 km scale regime without deteriorating the realism of the simulated MJO but the number of cloud resolving model grid columns is discovered to constrain the efficiency of vertical mixing, with consequences for the simulated liquid cloud climatology. Tuning opportunities for next generation accelerated superparameterized climate models are discussed.

Effects of explicit convection on global land-atmosphere coupling in the superparameterized CAM

DOE PAGES

Sun, Jian; Pritchard, Michael S.

2016-07-25

Here, conventional global climate models are prone to producing unrealistic land-atmosphere coupling signals. Cumulus and convection parameterizations are natural culprits but the effect of bypassing them with explicitly resolved convection on global land-atmosphere coupling dynamics has not been explored systematically. We apply a suite of modern land-atmosphere coupling diagnostics to isolate the effect of cloud Superparameterization in the Community Atmosphere Model (SPCAM) v3.5, focusing on both the terrestrial segment (i.e., soil moisture and surface turbulent fluxes interaction) and atmospheric segment (i.e., surface turbulent fluxes and precipitation interaction) in the water pathway of the landatmosphere feedback loop. At daily timescales, SPCAMmore » produces stronger uncoupled terrestrial signals (negative sign) over tropical rainforests in wet seasons, reduces the terrestrial coupling strength in the Central Great Plain in American, and reverses the coupling sign (from negative to positive) over India in the boreal summer season—all favorable improvements relative to reanalysis-forced land modeling. Analysis of the triggering feedback strength (TFS) and amplification feedback strength (AFS) shows that SPCAM favorably reproduces the observed geographic patterns of these indices over North America, with the probability of afternoon precipitation enhanced by high evaporative fraction along the eastern United States and Mexico, while conventional CAM does not capture this signal. We introduce a new diagnostic called the Planetary Boundary Layer (PBL) Feedback Strength (PFS), which reveals that SPCAM exhibits a tight connection between the responses of the lifting condensation level, the PBL height, and the rainfall triggering to surface turbulent fluxes; a triggering disconnect is found in CAM.« less

Effects of explicit convection on global land-atmosphere coupling in the superparameterized CAM

NASA Astrophysics Data System (ADS)

Sun, Jian; Pritchard, Michael S.

2016-09-01

Conventional global climate models are prone to producing unrealistic land-atmosphere coupling signals. Cumulus and convection parameterizations are natural culprits but the effect of bypassing them with explicitly resolved convection on global land-atmosphere coupling dynamics has not been explored systematically. We apply a suite of modern land-atmosphere coupling diagnostics to isolate the effect of cloud Superparameterization in the Community Atmosphere Model (SPCAM) v3.5, focusing on both the terrestrial segment (i.e., soil moisture and surface turbulent fluxes interaction) and atmospheric segment (i.e., surface turbulent fluxes and precipitation interaction) in the water pathway of the land-atmosphere feedback loop. At daily timescales, SPCAM produces stronger uncoupled terrestrial signals (negative sign) over tropical rainforests in wet seasons, reduces the terrestrial coupling strength in the Central Great Plain in American, and reverses the coupling sign (from negative to positive) over India in the boreal summer season—all favorable improvements relative to reanalysis-forced land modeling. Analysis of the triggering feedback strength (TFS) and amplification feedback strength (AFS) shows that SPCAM favorably reproduces the observed geographic patterns of these indices over North America, with the probability of afternoon precipitation enhanced by high evaporative fraction along the eastern United States and Mexico, while conventional CAM does not capture this signal. We introduce a new diagnostic called the Planetary Boundary Layer (PBL) Feedback Strength (PFS), which reveals that SPCAM exhibits a tight connection between the responses of the lifting condensation level, the PBL height, and the rainfall triggering to surface turbulent fluxes; a triggering disconnect is found in CAM.

Effects of explicit convection on global land-atmosphere coupling in the superparameterized CAM

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

Sun, Jian; Pritchard, Michael S.

Here, conventional global climate models are prone to producing unrealistic land-atmosphere coupling signals. Cumulus and convection parameterizations are natural culprits but the effect of bypassing them with explicitly resolved convection on global land-atmosphere coupling dynamics has not been explored systematically. We apply a suite of modern land-atmosphere coupling diagnostics to isolate the effect of cloud Superparameterization in the Community Atmosphere Model (SPCAM) v3.5, focusing on both the terrestrial segment (i.e., soil moisture and surface turbulent fluxes interaction) and atmospheric segment (i.e., surface turbulent fluxes and precipitation interaction) in the water pathway of the landatmosphere feedback loop. At daily timescales, SPCAMmore » produces stronger uncoupled terrestrial signals (negative sign) over tropical rainforests in wet seasons, reduces the terrestrial coupling strength in the Central Great Plain in American, and reverses the coupling sign (from negative to positive) over India in the boreal summer season—all favorable improvements relative to reanalysis-forced land modeling. Analysis of the triggering feedback strength (TFS) and amplification feedback strength (AFS) shows that SPCAM favorably reproduces the observed geographic patterns of these indices over North America, with the probability of afternoon precipitation enhanced by high evaporative fraction along the eastern United States and Mexico, while conventional CAM does not capture this signal. We introduce a new diagnostic called the Planetary Boundary Layer (PBL) Feedback Strength (PFS), which reveals that SPCAM exhibits a tight connection between the responses of the lifting condensation level, the PBL height, and the rainfall triggering to surface turbulent fluxes; a triggering disconnect is found in CAM.« less

Aerosol-cloud interactions in a multi-scale modeling framework

NASA Astrophysics Data System (ADS)

Lin, G.; Ghan, S. J.

2017-12-01

Atmospheric aerosols play an important role in changing the Earth's climate through scattering/absorbing solar and terrestrial radiation and interacting with clouds. However, quantification of the aerosol effects remains one of the most uncertain aspects of current and future climate projection. Much of the uncertainty results from the multi-scale nature of aerosol-cloud interactions, which is very challenging to represent in traditional global climate models (GCMs). In contrast, the multi-scale modeling framework (MMF) provides a viable solution, which explicitly resolves the cloud/precipitation in the cloud resolved model (CRM) embedded in the GCM grid column. In the MMF version of community atmospheric model version 5 (CAM5), aerosol processes are treated with a parameterization, called the Explicit Clouds Parameterized Pollutants (ECPP). It uses the cloud/precipitation statistics derived from the CRM to treat the cloud processing of aerosols on the GCM grid. However, this treatment treats clouds on the CRM grid but aerosols on the GCM grid, which is inconsistent with the reality that cloud-aerosol interactions occur on the cloud scale. To overcome the limitation, here, we propose a new aerosol treatment in the MMF: Explicit Clouds Explicit Aerosols (ECEP), in which we resolve both clouds and aerosols explicitly on the CRM grid. We first applied the MMF with ECPP to the Accelerated Climate Modeling for Energy (ACME) model to have an MMF version of ACME. Further, we also developed an alternative version of ACME-MMF with ECEP. Based on these two models, we have conducted two simulations: one with the ECPP and the other with ECEP. Preliminary results showed that the ECEP simulations tend to predict higher aerosol concentrations than ECPP simulations, because of the more efficient vertical transport from the surface to the higher atmosphere but the less efficient wet removal. We also found that the cloud droplet number concentrations are also different between the two simulations due to the difference in the cloud droplet lifetime. Next, we will explore how the ECEP treatment affects the anthropogenic aerosol forcing, particularly the aerosol indirect forcing, by comparing present-day and pre-industrial simulations.

Late time neutrino masses, the LSND experiment, and the cosmic microwave background.

PubMed

Chacko, Z; Hall, Lawrence J; Oliver, Steven J; Perelstein, Maxim

2005-03-25

Models with low-scale breaking of global symmetries in the neutrino sector provide an alternative to the seesaw mechanism for understanding why neutrinos are light. Such models can easily incorporate light sterile neutrinos required by the Liquid Scintillator Neutrino Detector experiment. Furthermore, the constraints on the sterile neutrino properties from nucleosynthesis and large-scale structure can be removed due to the nonconventional cosmological evolution of neutrino masses and densities. We present explicit, fully realistic supersymmetric models, and discuss the characteristic signatures predicted in the angular distributions of the cosmic microwave background.

An efficient, explicit finite-rate algorithm to compute flows in chemical nonequilibrium

NASA Technical Reports Server (NTRS)

Palmer, Grant

1989-01-01

An explicit finite-rate code was developed to compute hypersonic viscous chemically reacting flows about three-dimensional bodies. Equations describing the finite-rate chemical reactions were fully coupled to the gas dynamic equations using a new coupling technique. The new technique maintains stability in the explicit finite-rate formulation while permitting relatively large global time steps.

Our Changing Planet: The FY 1993 US Global Change Research Program. A report by the Committee on Earth and Environmental Sciences, a supplement to the US President's fiscal year 1993 budget

NASA Technical Reports Server (NTRS)

1992-01-01

The U.S. Global Change Reasearch Program (USGCRP) was established as a Presidential initiative in the FY-1990 Budget to help develop sound national and international policies related to global environmental issues, particularly global climate change. The USGCRP is implemented through a priority-driven scientific research agenda that is designed to be integrated, comprehensive, and multidisciplinary. It is designed explicitly to address scientific uncertainties in such areas as climate change, ozone depletion, changes in terrestrial and marine productivity, global water and energy cycles, sea level changes, the impact of global changes on human health and activities, and the impact of anthropogenic activities on the Earth system. The USGCRP addresses three parallel but interconnected streams of activity: documenting global change (observations); enhancing understanding of key processes (process research); and predicting global and regional environmental change (integrated modeling and prediction).

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.

Scalable Computing of the Mesh Size Effect on Modeling Damage Mechanics in Woven Armor Composites

DTIC Science & Technology

2008-12-01

manner of a user defined material subroutine to provide overall stress increments to, the parallel LS-DYNA3D a Lagrangian explicit code used in...finite element code, as a user defined material subroutine . The ability of this subroutine to model the effect of the progressions of a select number...is added as a user defined material subroutine to parallel LS-DYNA3D. The computations of the global mesh are handled by LS-DYNA3D and are spread

A high-resolution global flood hazard model

NASA Astrophysics Data System (ADS)

Sampson, Christopher C.; Smith, Andrew M.; Bates, Paul B.; Neal, Jeffrey C.; Alfieri, Lorenzo; Freer, Jim E.

2015-09-01

Floods are a natural hazard that affect communities worldwide, but to date the vast majority of flood hazard research and mapping has been undertaken by wealthy developed nations. As populations and economies have grown across the developing world, so too has demand from governments, businesses, and NGOs for modeled flood hazard data in these data-scarce regions. We identify six key challenges faced when developing a flood hazard model that can be applied globally and present a framework methodology that leverages recent cross-disciplinary advances to tackle each challenge. The model produces return period flood hazard maps at ˜90 m resolution for the whole terrestrial land surface between 56°S and 60°N, and results are validated against high-resolution government flood hazard data sets from the UK and Canada. The global model is shown to capture between two thirds and three quarters of the area determined to be at risk in the benchmark data without generating excessive false positive predictions. When aggregated to ˜1 km, mean absolute error in flooded fraction falls to ˜5%. The full complexity global model contains an automatically parameterized subgrid channel network, and comparison to both a simplified 2-D only variant and an independently developed pan-European model shows the explicit inclusion of channels to be a critical contributor to improved model performance. While careful processing of existing global terrain data sets enables reasonable model performance in urban areas, adoption of forthcoming next-generation global terrain data sets will offer the best prospect for a step-change improvement in model performance.

Iron control on global productivity: an efficient inverse model of the ocean's coupled phosphate and iron cycles.

NASA Astrophysics Data System (ADS)

Pasquier, B.; Holzer, M.; Frants, M.

2016-02-01

We construct a data-constrained mechanistic inverse model of the ocean's coupled phosphorus and iron cycles. The nutrient cycling is embedded in a data-assimilated steady global circulation. Biological nutrient uptake is parameterized in terms of nutrient, light, and temperature limitations on growth for two classes of phytoplankton that are not transported explicitly. A matrix formulation of the discretized nutrient tracer equations allows for efficient numerical solutions, which facilitates the objective optimization of the key biogeochemical parameters. The optimization minimizes the misfit between the modelled and observed nutrient fields of the current climate. We systematically assess the nonlinear response of the biological pump to changes in the aeolian iron supply for a variety of scenarios. Specifically, Green-function techniques are employed to quantify in detail the pathways and timescales with which those perturbations are propagated throughout the world oceans, determining the global teleconnections that mediate the response of the global ocean ecosystem. We confirm previous findings from idealized studies that increased iron fertilization decreases biological production in the subtropical gyres and we quantify the counterintuitive and asymmetric response of global productivity to increases and decreases in the aeolian iron supply.

Estimate of changes in agricultural terrestrial nitrogen pathways and ammonia emissions from 1850 to present in the Community Earth System Model

NASA Astrophysics Data System (ADS)

Riddick, Stuart; Ward, Daniel; Hess, Peter; Mahowald, Natalie; Massad, Raia; Holland, Elisabeth

2016-06-01

Nitrogen applied to the surface of the land for agricultural purposes represents a significant source of reactive nitrogen (Nr) that can be emitted as a gaseous Nr species, be denitrified to atmospheric nitrogen (N2), run off during rain events or form plant-useable nitrogen in the soil. To investigate the magnitude, temporal variability and spatial heterogeneity of nitrogen pathways on a global scale from sources of animal manure and synthetic fertilizer, we developed a mechanistic parameterization of these pathways within a global terrestrial land model, the Community Land Model (CLM). In this first model version the parameterization emphasizes an explicit climate-dependent approach while using highly simplified representations of agricultural practices, including manure management and fertilizer application. The climate-dependent approach explicitly simulates the relationship between meteorological variables and biogeochemical processes to calculate the volatilization of ammonia (NH3), nitrification and runoff of Nr following manure or synthetic fertilizer application. For the year 2000, approximately 125 Tg N yr-1 is applied as manure and 62 Tg N yr-1 is applied as synthetic fertilizer. We estimate the resulting global NH3 emissions are 21 Tg N yr-1 from manure (17 % of manure production) and 12 Tg N yr-1 from fertilizer (19 % of fertilizer application); reactive nitrogen runoff during rain events is calculated as 11 Tg N yr-1 from manure and 5 Tg N yr-1 from fertilizer. The remaining nitrogen from manure (93 Tg N yr-1) and synthetic fertilizer (45 Tg N yr-1) is captured by the canopy or transferred to the soil nitrogen pools. The parameterization was implemented in the CLM from 1850 to 2000 using a transient simulation which predicted that, even though absolute values of all nitrogen pathways are increasing with increased manure and synthetic fertilizer application, partitioning of nitrogen to NH3 emissions from manure is increasing on a percentage basis, from 14 % of nitrogen applied in 1850 (3 Tg NH3 yr-1) to 17 % of nitrogen applied in 2000 (21 Tg NH3 yr-1). Under current manure and synthetic fertilizer application rates we find a global sensitivity of an additional 1 Tg NH3 (approximately 3 % of manure and fertilizer) emitted per year per °C of warming. While the model confirms earlier estimates of nitrogen fluxes made in a range of studies, its key purpose is to provide a theoretical framework that can be employed within a biogeochemical model, that can explicitly respond to climate and that can evolve and improve with further observation.

A Global Magnetohydrodynamic Model of Jovian Magnetosphere

NASA Technical Reports Server (NTRS)

Walker, Raymond J.; Sharber, James (Technical Monitor)

2001-01-01

The goal of this project was to develop a new global magnetohydrodynamic model of the interaction of the Jovian magnetosphere with the solar wind. Observations from 28 orbits of Jupiter by Galileo along with those from previous spacecraft at Jupiter, Pioneer 10 and 11, Voyager I and 2 and Ulysses, have revealed that the Jovian magnetosphere is a vast, complicated system. The Jovian aurora also has been monitored for several years. Like auroral observations at Earth, these measurements provide us with a global picture of magnetospheric dynamics. Despite this wide range of observations, we have limited quantitative understanding of the Jovian magnetosphere and how it interacts with the solar wind. For the past several years we have been working toward a quantitative understanding of the Jovian magnetosphere and its interaction with the solar wind by employing global magnetohydrodynamic simulations to model the magnetosphere. Our model has been an explicit MHD code (previously used to model the Earth's magnetosphere) to study Jupiter's magnetosphere. We continue to obtain important insights with this code, but it suffers from some severe limitations. In particular with this code we are limited to considering the region outside of 15RJ, with cell sizes of about 1.5R(sub J). The problem arises because of the presence of widely separated time scales throughout the magnetosphere. The numerical stability criterion for explicit MHD codes is the CFL limit and is given by C(sub max)(Delta)t/(Delta)x less than 1 where C(sub max) is the maximum group velocity in a given cell, (Delta)x is the grid spacing and (Delta)t is the time step. If the maximum wave velocity is C(sub w) and the flow speed is C(sub f), C(sub max) = C(sub w) + C(sub f). Near Jupiter the Alfven wave speed becomes very large (it approaches the speed of light at one Jovian radius). Operating with this time step makes the calculation essentially intractable. Therefore under this funding we have been designing a new MHD model that will be able to compute solutions in the wide parameter regime of the Jovian magnetosphere.

Synthesis of a control model for a liquid nitrogen cooled, closed circuit, cryogenic nitrogen wind tunnel and its validation

NASA Technical Reports Server (NTRS)

Balakrishna, S.; Goglia, G. L.

1979-01-01

The details of the efforts to synthesize a control-compatible multivariable model of a liquid nitrogen cooled, gaseous nitrogen operated, closed circuit, cryogenic pressure tunnel are presented. The synthesized model was transformed into a real-time cryogenic tunnel simulator, and this model is validated by comparing the model responses to the actual tunnel responses of the 0.3 m transonic cryogenic tunnel, using the quasi-steady-state and the transient responses of the model and the tunnel. The global nature of the simple, explicit, lumped multivariable model of a closed circuit cryogenic tunnel is demonstrated.

Explicit simulation of a midlatitude Mesoscale Convective System

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

Alexander, G.D.; Cotton, W.R.

1996-04-01

We have explicitly simulated the mesoscale convective system (MCS) observed on 23-24 June 1985 during PRE-STORM, the Preliminary Regional Experiment for the Stormscale Operational and Research and Meterology Program. Stensrud and Maddox (1988), Johnson and Bartels (1992), and Bernstein and Johnson (1994) are among the researchers who have investigated various aspects of this MCS event. We have performed this MCS simulation (and a similar one of a tropical MCS; Alexander and Cotton 1994) in the spirit of the Global Energy and Water Cycle Experiment Cloud Systems Study (GCSS), in which cloud-resolving models are used to assist in the formulation andmore » testing of cloud parameterization schemes for larger-scale models. In this paper, we describe (1) the nature of our 23-24 June MCS dimulation and (2) our efforts to date in using our explicit MCS simulations to assist in the development of a GCM parameterization for mesoscale flow branches. The paper is organized as follows. First, we discuss the synoptic situation surrounding the 23-24 June PRE-STORM MCS followed by a discussion of the model setup and results of our simulation. We then discuss the use of our MCS simulation. We then discuss the use of our MCS simulations in developing a GCM parameterization for mesoscale flow branches and summarize our results.« less

A high‐resolution global flood hazard model†

PubMed Central

Smith, Andrew M.; Bates, Paul D.; Neal, Jeffrey C.; Alfieri, Lorenzo; Freer, Jim E.

2015-01-01

Abstract Floods are a natural hazard that affect communities worldwide, but to date the vast majority of flood hazard research and mapping has been undertaken by wealthy developed nations. As populations and economies have grown across the developing world, so too has demand from governments, businesses, and NGOs for modeled flood hazard data in these data‐scarce regions. We identify six key challenges faced when developing a flood hazard model that can be applied globally and present a framework methodology that leverages recent cross‐disciplinary advances to tackle each challenge. The model produces return period flood hazard maps at ∼90 m resolution for the whole terrestrial land surface between 56°S and 60°N, and results are validated against high‐resolution government flood hazard data sets from the UK and Canada. The global model is shown to capture between two thirds and three quarters of the area determined to be at risk in the benchmark data without generating excessive false positive predictions. When aggregated to ∼1 km, mean absolute error in flooded fraction falls to ∼5%. The full complexity global model contains an automatically parameterized subgrid channel network, and comparison to both a simplified 2‐D only variant and an independently developed pan‐European model shows the explicit inclusion of channels to be a critical contributor to improved model performance. While careful processing of existing global terrain data sets enables reasonable model performance in urban areas, adoption of forthcoming next‐generation global terrain data sets will offer the best prospect for a step‐change improvement in model performance. PMID:27594719

High-resolution assessment of land use impacts on biodiversity in life cycle assessment using species habitat suitability models.

PubMed

de Baan, Laura; Curran, Michael; Rondinini, Carlo; Visconti, Piero; Hellweg, Stefanie; Koellner, Thomas

2015-02-17

Agricultural land use is a main driver of global biodiversity loss. The assessment of land use impacts in decision-support tools such as life cycle assessment (LCA) requires spatially explicit models, but existing approaches are either not spatially differentiated or modeled at very coarse scales (e.g., biomes or ecoregions). In this paper, we develop a high-resolution (900 m) assessment method for land use impacts on biodiversity based on habitat suitability models (HSM) of mammal species. This method considers potential land use effects on individual species, and impacts are weighted by the species' conservation status and global rarity. We illustrate the method using a case study of crop production in East Africa, but the underlying HSMs developed by the Global Mammals Assessment are available globally. We calculate impacts of three major export crops and compare the results to two previously developed methods (focusing on local and regional impacts, respectively) to assess the relevance of the methodological innovations proposed in this paper. The results highlight hotspots of product-related biodiversity impacts that help characterize the links among agricultural production, consumption, and biodiversity loss.

Development of a Navier-Stokes algorithm for parallel-processing supercomputers. Ph.D. Thesis - Colorado State Univ., Dec. 1988

NASA Technical Reports Server (NTRS)

Swisshelm, Julie M.

1989-01-01

An explicit flow solver, applicable to the hierarchy of model equations ranging from Euler to full Navier-Stokes, is combined with several techniques designed to reduce computational expense. The computational domain consists of local grid refinements embedded in a global coarse mesh, where the locations of these refinements are defined by the physics of the flow. Flow characteristics are also used to determine which set of model equations is appropriate for solution in each region, thereby reducing not only the number of grid points at which the solution must be obtained, but also the computational effort required to get that solution. Acceleration to steady-state is achieved by applying multigrid on each of the subgrids, regardless of the particular model equations being solved. Since each of these components is explicit, advantage can readily be taken of the vector- and parallel-processing capabilities of machines such as the Cray X-MP and Cray-2.

Modeling lakes and reservoirs in the climate system

USGS Publications Warehouse

MacKay, M.D.; Neale, P.J.; Arp, C.D.; De Senerpont Domis, L. N.; Fang, X.; Gal, G.; Jo, K.D.; Kirillin, G.; Lenters, J.D.; Litchman, E.; MacIntyre, S.; Marsh, P.; Melack, J.; Mooij, W.M.; Peeters, F.; Quesada, A.; Schladow, S.G.; Schmid, M.; Spence, C.; Stokes, S.L.

2009-01-01

Modeling studies examining the effect of lakes on regional and global climate, as well as studies on the influence of climate variability and change on aquatic ecosystems, are surveyed. Fully coupled atmosphere-land surface-lake climate models that could be used for both of these types of study simultaneously do not presently exist, though there are many applications that would benefit from such models. It is argued here that current understanding of physical and biogeochemical processes in freshwater systems is sufficient to begin to construct such models, and a path forward is proposed. The largest impediment to fully representing lakes in the climate system lies in the handling of lakes that are too small to be explicitly resolved by the climate model, and that make up the majority of the lake-covered area at the resolutions currently used by global and regional climate models. Ongoing development within the hydrological sciences community and continual improvements in model resolution should help ameliorate this issue.

Spatiotemporal variability of urban growth factors: A global and local perspective on the megacity of Mumbai

NASA Astrophysics Data System (ADS)

Shafizadeh-Moghadam, Hossein; Helbich, Marco

2015-03-01

The rapid growth of megacities requires special attention among urban planners worldwide, and particularly in Mumbai, India, where growth is very pronounced. To cope with the planning challenges this will bring, developing a retrospective understanding of urban land-use dynamics and the underlying driving-forces behind urban growth is a key prerequisite. This research uses regression-based land-use change models - and in particular non-spatial logistic regression models (LR) and auto-logistic regression models (ALR) - for the Mumbai region over the period 1973-2010, in order to determine the drivers behind spatiotemporal urban expansion. Both global models are complemented by a local, spatial model, the so-called geographically weighted logistic regression (GWLR) model, one that explicitly permits variations in driving-forces across space. The study comes to two main conclusions. First, both global models suggest similar driving-forces behind urban growth over time, revealing that LRs and ALRs result in estimated coefficients with comparable magnitudes. Second, all the local coefficients show distinctive temporal and spatial variations. It is therefore concluded that GWLR aids our understanding of urban growth processes, and so can assist context-related planning and policymaking activities when seeking to secure a sustainable urban future.

Medial-based deformable models in nonconvex shape-spaces for medical image segmentation.

PubMed

McIntosh, Chris; Hamarneh, Ghassan

2012-01-01

We explore the application of genetic algorithms (GA) to deformable models through the proposition of a novel method for medical image segmentation that combines GA with nonconvex, localized, medial-based shape statistics. We replace the more typical gradient descent optimizer used in deformable models with GA, and the convex, implicit, global shape statistics with nonconvex, explicit, localized ones. Specifically, we propose GA to reduce typical deformable model weaknesses pertaining to model initialization, pose estimation and local minima, through the simultaneous evolution of a large number of models. Furthermore, we constrain the evolution, and thus reduce the size of the search-space, by using statistically-based deformable models whose deformations are intuitive (stretch, bulge, bend) and are driven in terms of localized principal modes of variation, instead of modes of variation across the entire shape that often fail to capture localized shape changes. Although GA are not guaranteed to achieve the global optima, our method compares favorably to the prevalent optimization techniques, convex/nonconvex gradient-based optimizers and to globally optimal graph-theoretic combinatorial optimization techniques, when applied to the task of corpus callosum segmentation in 50 mid-sagittal brain magnetic resonance images.

Estimation of wetland methane emissions in a biogeochemical model integrated in CESM: sensitivity analysis and comparison against surface and atmospheric measurements

NASA Astrophysics Data System (ADS)

Meng, L.; Mahowald, N. M.; Hess, P. G.; Yavitt, J. B.; Riley, W. J.; Subin, Z. M.; Lawrence, D. M.; Swenson, S. C.; Jauhiainen, J.; Fuka, D. R.

2012-12-01

Methane emissions from natural wetlands and rice paddies constitute a large proportion of atmospheric methane, but the magnitude and year-to-year variation of these methane sources is still unpredictable. Here we describe and evaluate the integration of a methane biogeochemical model (CLM4Me; Riley et al. 2011) into the Community Land Model 4.0 (CLM4CN) in order to better explain spatial and temporal variations in methane emissions. We test new functions for soil pH and redox potential that impact microbial methane production in soils. We also constrain aerenchyma in plants in always-inundated areas in order to better represent wetland vegetation. Satellite inundated fraction is explicitly prescribed in the model because there are large differences between simulated fractional inundation and satellite observations and thus we do not use CLM4 simulated inundated area. The model is evaluated at the site level with vegetation cover and water table prescribed from measurements. Explicit site level evaluations of simulated methane emissions are quite different than evaluating the grid cell averaged emissions against available measurements. Using a baseline set of parameter values, our model-estimated average global wetland emissions for the period 1993-2004 were 256 Tg CH4 y-1 (including the soil sink). Tropical wetlands contributed 201 Tg CH4 y-1, or 78% of the global wetland flux. Northern latitude (>50N) systems contributed 12 Tg CH4 y-1. Our sensitivity studies show a large range (150-346 Tg CH4 y-1) in predicted global methane emissions. In order to evaluate our methane emissions on the regional and global scales against atmospheric measurements, we conducted simulations with the Community Atmospheric Model with chemistry (CAM-chem) forced with our baseline simulation of wetland and rice paddy emissions along with other methane sources (e.g. anthropogenic, fire, and termite emissions) and compared model simulations against measured atmospheric concentrations obtained from the World Data Centre for Greenhouse Gases (WDCGG) at http://ds.data.jma.go.jp/gmd/wdcgg/. Overall, using our estimated wetland and rice paddy emissions, CAM-chem model can produce seasonal and interannual variations of observed atmospheric concentration performs well. Thus, within the current level of uncertainty, our emissions appear to be reasonable.

A Neuronal Model of Classical Conditioning.

DTIC Science & Technology

1987-10-01

animal’s nervous system. This assunption might not hold up well at hiyher, cognitive levels of function but the assumption appears reasonabie as a starting...complex, cognitive phenomena may begin to emerge. To support the process of drive acquisition or learning dt the network level, global centers that...intelligence at higher, cognitive levels. At such levels, explicit teachers play an important role. However, I suggest that this has misled neural

All is not loss: plant biodiversity in the anthropocene.

PubMed

Ellis, Erle C; Antill, Erica C; Kreft, Holger

2012-01-01

Anthropogenic global changes in biodiversity are generally portrayed in terms of massive native species losses or invasions caused by recent human disturbance. Yet these biodiversity changes and others caused directly by human populations and their use of land tend to co-occur as long-term biodiversity change processes in the Anthropocene. Here we explore contemporary anthropogenic global patterns in vascular plant species richness at regional landscape scales by combining spatially explicit models and estimates for native species loss together with gains in exotics caused by species invasions and the introduction of agricultural domesticates and ornamental exotic plants. The patterns thus derived confirm that while native losses are likely significant across at least half of Earth's ice-free land, model predictions indicate that plant species richness has increased overall in most regional landscapes, mostly because species invasions tend to exceed native losses. While global observing systems and models that integrate anthropogenic species loss, introduction and invasion at regional landscape scales remain at an early stage of development, integrating predictions from existing models within a single assessment confirms their vast global extent and significance while revealing novel patterns and their potential drivers. Effective global stewardship of plant biodiversity in the Anthropocene will require integrated frameworks for observing, modeling and forecasting the different forms of anthropogenic biodiversity change processes at regional landscape scales, towards conserving biodiversity within the novel plant communities created and sustained by human systems.

All Is Not Loss: Plant Biodiversity in the Anthropocene

PubMed Central

Ellis, Erle C.; Antill, Erica C.; Kreft, Holger

2012-01-01

Anthropogenic global changes in biodiversity are generally portrayed in terms of massive native species losses or invasions caused by recent human disturbance. Yet these biodiversity changes and others caused directly by human populations and their use of land tend to co-occur as long-term biodiversity change processes in the Anthropocene. Here we explore contemporary anthropogenic global patterns in vascular plant species richness at regional landscape scales by combining spatially explicit models and estimates for native species loss together with gains in exotics caused by species invasions and the introduction of agricultural domesticates and ornamental exotic plants. The patterns thus derived confirm that while native losses are likely significant across at least half of Earth's ice-free land, model predictions indicate that plant species richness has increased overall in most regional landscapes, mostly because species invasions tend to exceed native losses. While global observing systems and models that integrate anthropogenic species loss, introduction and invasion at regional landscape scales remain at an early stage of development, integrating predictions from existing models within a single assessment confirms their vast global extent and significance while revealing novel patterns and their potential drivers. Effective global stewardship of plant biodiversity in the Anthropocene will require integrated frameworks for observing, modeling and forecasting the different forms of anthropogenic biodiversity change processes at regional landscape scales, towards conserving biodiversity within the novel plant communities created and sustained by human systems. PMID:22272360

On Spatially Explicit Models of Epidemic and Endemic Cholera: The Haiti and Lake Kivu Case Studies.

NASA Astrophysics Data System (ADS)

Rinaldo, A.; Bertuzzo, E.; Mari, L.; Finger, F.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.

2014-12-01

The first part of the Lecture deals with the predictive ability of mechanistic models for the Haitian cholera epidemic. Predictive models of epidemic cholera need to resolve at suitable aggregation levels spatial data pertaining to local communities, epidemiological records, hydrologic drivers, waterways, patterns of human mobility and proxies of exposure rates. A formal model comparison framework provides a quantitative assessment of the explanatory and predictive abilities of various model settings with different spatial aggregation levels. Intensive computations and objective model comparisons show that parsimonious spatially explicit models accounting for spatial connections have superior explanatory power than spatially disconnected ones for short-to intermediate calibration windows. In general, spatially connected models show better predictive ability than disconnected ones. We suggest limits and validity of the various approaches and discuss the pathway towards the development of case-specific predictive tools in the context of emergency management. The second part deals with approaches suitable to describe patterns of endemic cholera. Cholera outbreaks have been reported in the Democratic Republic of the Congo since the 1970s. Here we employ a spatially explicit, inhomogeneous Markov chain model to describe cholera incidence in eight health zones on the shore of lake Kivu. Remotely sensed datasets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers in addition to baseline seasonality. The effect of human mobility is also modelled mechanistically. We test several models on a multi-year dataset of reported cholera cases. Fourteen models, accounting for different environmental drivers, are selected in calibration. Among these, the one accounting for seasonality, El Nino Southern Oscillation, precipitation and human mobility outperforms the others in cross-validation.

Modeling Wood Encroachment in Abandoned Grasslands in the Eifel National Park – Model Description and Testing

PubMed Central

Hudjetz, Silvana; Lennartz, Gottfried; Krämer, Klara; Roß-Nickoll, Martina; Gergs, André; Preuss, Thomas G.

2014-01-01

The degradation of natural and semi-natural landscapes has become a matter of global concern. In Germany, semi-natural grasslands belong to the most species-rich habitat types but have suffered heavily from changes in land use. After abandonment, the course of succession at a specific site is often difficult to predict because many processes interact. In order to support decision making when managing semi-natural grasslands in the Eifel National Park, we built the WoodS-Model (Woodland Succession Model). A multimodeling approach was used to integrate vegetation dynamics in both the herbaceous and shrub/tree layer. The cover of grasses and herbs was simulated in a compartment model, whereas bushes and trees were modelled in an individual-based manner. Both models worked and interacted in a spatially explicit, raster-based landscape. We present here the model description, parameterization and testing. We show highly detailed projections of the succession of a semi-natural grassland including the influence of initial vegetation composition, neighborhood interactions and ungulate browsing. We carefully weighted the single processes against each other and their relevance for landscape development under different scenarios, while explicitly considering specific site conditions. Model evaluation revealed that the model is able to emulate successional patterns as observed in the field as well as plausible results for different population densities of red deer. Important neighborhood interactions such as seed dispersal, the protection of seedlings from browsing ungulates by thorny bushes, and the inhibition of wood encroachment by the herbaceous layer, have been successfully reproduced. Therefore, not only a detailed model but also detailed initialization turned out to be important for spatially explicit projections of a given site. The advantage of the WoodS-Model is that it integrates these many mutually interacting processes of succession. PMID:25494057

Spatially Explicit Models of Carbon and Alkalinity Cycling in the Coastal Oceans

NASA Astrophysics Data System (ADS)

O'Mara, N. A.; Dunne, J. P.

2016-12-01

Calcium carbonate (CaCO3) production, dissolution, and preservation are strongly influenced by seawater temperature and carbon chemistry and thus play a key role in the global carbon cycle and are highly susceptible to influence by climate change. Coastal and continental shelf (neritic) environments have been estimated to account for more than half of all CaCO3 accumulation in ocean sediment globally. Unfortunately, current neritic CaCO3 budgets are muddled with assumptions of the spatial extent of various communities, rely on long term averages rather than deterministic relationships for production rates, and therefore have little predictive power for quantifying the impact of climate change on this system. Current biogeochemical components of globally coupled earth system models include open ocean pelagic CaCO3 production and deep sea preservation (0.130 PgC yr-1), but do not resolve nearshore pelagic or benthic production. Here, a 1° spatially explicit model for determining CaCO3 accumulation in neritic sediments is developed. Globally gridded observational, satellite, and benthic community area data are used to calculate rates of benthic and pelagic community CaCO3 production and preservation using a set of equations sensitive to temperature, carbonate saturation state, light availability, and nutrients. Accumulation rates (PgC yr-1) of four neritic zone environments are calculated: coral reefs and banks (0.075), seagrass dominated embayments (0.043), carbonate rich shelves (0.042), and carbonate poor shelves (0.0007). This analysis corroborates previous budget predictions of total neritic CaCO3 accumulation (0.160) and additionally supports the hypothesis that benthic CaCO3 production (0.151) in coastal water greatly exceeds pelagic production (0.009). However, results additionally suggest that erroneous assumptions about spatial extent of neritic communities have led to overestimations of coral reef and under estimations of embayment accumulation rates in the past.

Global-scale high-resolution ( 1 km) modelling of mean, maximum and minimum annual streamflow

NASA Astrophysics Data System (ADS)

Barbarossa, Valerio; Huijbregts, Mark; Hendriks, Jan; Beusen, Arthur; Clavreul, Julie; King, Henry; Schipper, Aafke

2017-04-01

Quantifying mean, maximum and minimum annual flow (AF) of rivers at ungauged sites is essential for a number of applications, including assessments of global water supply, ecosystem integrity and water footprints. AF metrics can be quantified with spatially explicit process-based models, which might be overly time-consuming and data-intensive for this purpose, or with empirical regression models that predict AF metrics based on climate and catchment characteristics. Yet, so far, regression models have mostly been developed at a regional scale and the extent to which they can be extrapolated to other regions is not known. We developed global-scale regression models that quantify mean, maximum and minimum AF as function of catchment area and catchment-averaged slope, elevation, and mean, maximum and minimum annual precipitation and air temperature. We then used these models to obtain global 30 arc-seconds (˜ 1 km) maps of mean, maximum and minimum AF for each year from 1960 through 2015, based on a newly developed hydrologically conditioned digital elevation model. We calibrated our regression models based on observations of discharge and catchment characteristics from about 4,000 catchments worldwide, ranging from 100 to 106 km2 in size, and validated them against independent measurements as well as the output of a number of process-based global hydrological models (GHMs). The variance explained by our regression models ranged up to 90% and the performance of the models compared well with the performance of existing GHMs. Yet, our AF maps provide a level of spatial detail that cannot yet be achieved by current GHMs.

A modified impulse-response representation of the global near-surface air temperature and atmospheric concentration response to carbon dioxide emissions

NASA Astrophysics Data System (ADS)

Millar, Richard J.; Nicholls, Zebedee R.; Friedlingstein, Pierre; Allen, Myles R.

2017-06-01

Projections of the response to anthropogenic emission scenarios, evaluation of some greenhouse gas metrics, and estimates of the social cost of carbon often require a simple model that links emissions of carbon dioxide (CO2) to atmospheric concentrations and global temperature changes. An essential requirement of such a model is to reproduce typical global surface temperature and atmospheric CO2 responses displayed by more complex Earth system models (ESMs) under a range of emission scenarios, as well as an ability to sample the range of ESM response in a transparent, accessible and reproducible form. Here we adapt the simple model of the Intergovernmental Panel on Climate Change 5th Assessment Report (IPCC AR5) to explicitly represent the state dependence of the CO2 airborne fraction. Our adapted model (FAIR) reproduces the range of behaviour shown in full and intermediate complexity ESMs under several idealised carbon pulse and exponential concentration increase experiments. We find that the inclusion of a linear increase in 100-year integrated airborne fraction with cumulative carbon uptake and global temperature change substantially improves the representation of the response of the climate system to CO2 on a range of timescales and under a range of experimental designs.

Regional impacts of iron-light colimitation in a global biogeochemical model

NASA Astrophysics Data System (ADS)

Galbraith, E. D.; Gnanadesikan, A.; Dunne, J. P.; Hiscock, M. R.

2009-07-01

Laboratory and field studies have revealed that iron has multiple roles in phytoplankton physiology, with particular importance for light-harvesting cellular machinery. However, although iron-limitation is explicitly included in numerous biogeochemical/ecosystem models, its implementation varies, and its effect on the efficiency of light harvesting is often ignored. Given the complexity of the ocean environment, it is difficult to predict the consequences of applying different iron limitation schemes. Here we explore the interaction of iron and nutrient cycles using a new, streamlined model of ocean biogeochemistry. Building on previously published parameterizations of photoadaptation and export production, the Biogeochemistry with Light Iron Nutrients and Gasses (BLING) model is constructed with only three explicit tracers but including macronutrient and micronutrient limitation, light limitation, and an implicit treatment of community structure. The structural simplicity of this computationally inexpensive model allows us to clearly isolate the global effects of iron availability on maximum light-saturated photosynthesis rates from those of photosynthetic efficiency. We find that the effect on light-saturated photosynthesis rates is dominant, negating the importance of photosynthetic efficiency in most regions, especially the cold waters of the Southern Ocean. The primary exceptions to this occur in iron-rich regions of the Northern Hemisphere, where high light-saturated photosynthesis rates cause photosynthetic efficiency to play a more important role. Additionally, we speculate that the small phytoplankton dominating iron-limited regions tend to have relatively high photosynthetic efficiency, such that iron-limitation has less of a deleterious effect on growth rates than would be expected from short-term iron addition experiments.

Stability and bifurcation analysis on a ratio-dependent predator-prey model with time delay

NASA Astrophysics Data System (ADS)

Xu, Rui; Gan, Qintao; Ma, Zhien

2009-08-01

A ratio-dependent predator-prey model with time delay due to the gestation of the predator is investigated. By analyzing the corresponding characteristic equations, the local stability of a positive equilibrium and a semi-trivial boundary equilibrium is discussed, respectively. Further, it is proved that the system undergoes a Hopf bifurcation at the positive equilibrium. Using the normal form theory and the center manifold reduction, explicit formulae are derived to determine the direction of bifurcations and the stability and other properties of bifurcating periodic solutions. By means of an iteration technique, sufficient conditions are obtained for the global attractiveness of the positive equilibrium. By comparison arguments, the global stability of the semi-trivial equilibrium is also addressed. Numerical simulations are carried out to illustrate the main results.

Towards Better Simulation of US Maize Yield Responses to Climate in the Community Earth System Model

NASA Astrophysics Data System (ADS)

Peng, B.; Guan, K.; Chen, M.; Lawrence, D. M.; Jin, Z.; Bernacchi, C.; Ainsworth, E. A.; DeLucia, E. H.; Lombardozzi, D. L.; Lu, Y.

2017-12-01

Global food security is undergoing continuing pressure from increased population and climate change despites the potential advancement in breeding and management technologies. Earth system models (ESMs) are essential tools to study the impacts of historical and future climate on regional and global food production, as well as to assess the effectiveness of possible adaptations and their potential feedback to climate. Here we developed an improved maize representation within the Community Earth System Model (CESM) by combining the strengths of both the Community Land Model version 4.5 (CLM4.5) and the Agricultural Production Systems sIMulator (APSIM) models. Specifically, we modified the maize planting scheme, incorporated the phenology scheme adopted from the APSIM model, added a new carbon allocation scheme into CLM4.5, and improved the estimation of canopy structure parameters including leaf area index (LAI) and canopy height. Unique features of the new model (CLM-APSIM) include more detailed phenology stages, an explicit implementation of the impacts of various abiotic environmental stresses (including nitrogen, water, temperature and heat stresses) on maize phenology and carbon allocation, as well as an explicit simulation of grain number and grain size. We conducted a regional simulation of this new model over the US Corn Belt during 1990 to 2010. The simulated maize yield as well as its responses to climate (growing season mean temperature and precipitation) are benchmarked with data from UADA NASS statistics. Our results show that the CLM-APSIM model outperforms the CLM4.5 in simulating county-level maize yield production and reproduces more realistic yield responses to climate variations than CLM4.5. However, some critical processes (such as crop failure due to frost and inundation and suboptimal growth condition due to biotic stresses) are still missing in both CLM-APSIM and CLM4.5, making the simulated yield responses to climate slightly deviate from the reality. Our results demonstrate that with improved paramterization of crop growth, the ESMs can be powerful tools for realistically simulating agricultural production, which is gaining increasing interests and critical to study of global food security and food-energy-water nexus.

Citizenship, Identity and Education: Examining the Public Purposes of Schools in an Age of Globalization

ERIC Educational Resources Information Center

Reimers, Fernando

2006-01-01

One of the purposes of educational institutions is to develop citizenship. In the 21st century, citizenship includes global citizenship. Addressing the challenges of globalization will require making citizenship education and the development of global values an explicit objective of efforts to improve quality throughout the world, critically…

Preservice Teachers' Views on the Global Dimensions of Education

ERIC Educational Resources Information Center

Oikonomidoy, Eleni

2008-01-01

The impact of globalization on many aspects of current social life has not left the field of multicultural education unaffected. Yet the theoretical call for the creation of global multicultural frameworks has not translated into teacher education practice. In one multicultural education class, I attempted to explicitly infuse global insights and…

Remedying excessive numerical diapycnal mixing in a global 0.25° NEMO configuration

NASA Astrophysics Data System (ADS)

Megann, Alex; Nurser, George; Storkey, Dave

2016-04-01

If numerical ocean models are to simulate faithfully the upwelling branches of the global overturning circulation, they need to have a good representation of the diapycnal mixing processes which contribute to conversion of the bottom and deep waters produced in high latitudes into less dense watermasses. It is known that the default class of depth-coordinate ocean models such as NEMO and MOM5, as used in many state-of-the art coupled climate models and Earth System Models, have excessive numerical diapycnal mixing, resulting from irreversible advection across coordinate surfaces. The GO5.0 configuration of the NEMO ocean model, on an "eddy-permitting" 0.25° global grid, is used in the current UK GC1 and GC2 coupled models. Megann and Nurser (2016) have shown, using the isopycnal watermass analysis of Lee et al (2002), that spurious numerical mixing is substantially larger than the explicit mixing prescribed by the mixing scheme used by the model. It will be shown that increasing the biharmonic viscosity by a factor of three tends to suppress small-scale noise in the vertical velocity in the model. This significantly reduces the numerical mixing in GO5.0, and we shall show that it also leads to large-scale improvements in model biases.

Carbon cycle confidence and uncertainty: Exploring variation among soil biogeochemical models

DOE PAGES

Wieder, William R.; Hartman, Melannie D.; Sulman, Benjamin N.; ...

2017-11-09

Emerging insights into factors responsible for soil organic matter stabilization and decomposition are being applied in a variety of contexts, but new tools are needed to facilitate the understanding, evaluation, and improvement of soil biogeochemical theory and models at regional to global scales. To isolate the effects of model structural uncertainty on the global distribution of soil carbon stocks and turnover times we developed a soil biogeochemical testbed that forces three different soil models with consistent climate and plant productivity inputs. The models tested here include a first-order, microbial implicit approach (CASA-CNP), and two recently developed microbially explicit models thatmore » can be run at global scales (MIMICS and CORPSE). When forced with common environmental drivers, the soil models generated similar estimates of initial soil carbon stocks (roughly 1,400 Pg C globally, 0–100 cm), but each model shows a different functional relationship between mean annual temperature and inferred turnover times. Subsequently, the models made divergent projections about the fate of these soil carbon stocks over the 20th century, with models either gaining or losing over 20 Pg C globally between 1901 and 2010. Single-forcing experiments with changed inputs, tem- perature, and moisture suggest that uncertainty associated with freeze-thaw processes as well as soil textural effects on soil carbon stabilization were larger than direct temper- ature uncertainties among models. Finally, the models generated distinct projections about the timing and magnitude of seasonal heterotrophic respiration rates, again reflecting structural uncertainties that were related to environmental sensitivities and assumptions about physicochemical stabilization of soil organic matter. Here, by providing a computationally tractable and numerically consistent framework to evaluate models we aim to better understand uncertainties among models and generate insights about fac- tors regulating the turnover of soil organic matter.« less

Carbon cycle confidence and uncertainty: Exploring variation among soil biogeochemical models

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

Wieder, William R.; Hartman, Melannie D.; Sulman, Benjamin N.

Emerging insights into factors responsible for soil organic matter stabilization and decomposition are being applied in a variety of contexts, but new tools are needed to facilitate the understanding, evaluation, and improvement of soil biogeochemical theory and models at regional to global scales. To isolate the effects of model structural uncertainty on the global distribution of soil carbon stocks and turnover times we developed a soil biogeochemical testbed that forces three different soil models with consistent climate and plant productivity inputs. The models tested here include a first-order, microbial implicit approach (CASA-CNP), and two recently developed microbially explicit models thatmore » can be run at global scales (MIMICS and CORPSE). When forced with common environmental drivers, the soil models generated similar estimates of initial soil carbon stocks (roughly 1,400 Pg C globally, 0–100 cm), but each model shows a different functional relationship between mean annual temperature and inferred turnover times. Subsequently, the models made divergent projections about the fate of these soil carbon stocks over the 20th century, with models either gaining or losing over 20 Pg C globally between 1901 and 2010. Single-forcing experiments with changed inputs, tem- perature, and moisture suggest that uncertainty associated with freeze-thaw processes as well as soil textural effects on soil carbon stabilization were larger than direct temper- ature uncertainties among models. Finally, the models generated distinct projections about the timing and magnitude of seasonal heterotrophic respiration rates, again reflecting structural uncertainties that were related to environmental sensitivities and assumptions about physicochemical stabilization of soil organic matter. Here, by providing a computationally tractable and numerically consistent framework to evaluate models we aim to better understand uncertainties among models and generate insights about fac- tors regulating the turnover of soil organic matter.« less

Phylogeographical footprint of colonial history in the global dispersal of human immunodeficiency virus type 2 group A

PubMed Central

Hodges-Mameletzis, Ioannis; Silva, Joana C.; Rodés, Berta; Erasmus, Smit; Paolucci, Stefania; Ruelle, Jean; Pieniazek, Danuta; Taveira, Nuno; Treviño, Ana; Gonçalves, Maria F.; Jallow, Sabelle; Xu, Li; Camacho, Ricardo J.; Soriano, Vincent; Goubau, Patrick; de Sousa, João D.; Vandamme, Anne-Mieke; Suchard, Marc A.; Lemey, Philippe

2012-01-01

Human immunodeficiency virus type 2 (HIV-2) emerged in West Africa and has spread further to countries that share socio-historical ties with this region. However, viral origins and dispersal patterns at a global scale remain poorly understood. Here, we adopt a Bayesian phylogeographic approach to investigate the spatial dynamics of HIV-2 group A (HIV-2A) using a collection of 320 partial pol and 248 partial env sequences sampled throughout 19 countries worldwide. We extend phylogenetic diffusion models that simultaneously draw information from multiple loci to estimate location states throughout distinct phylogenies and explicitly attempt to incorporate human migratory fluxes. Our study highlights that Guinea-Bissau, together with Côte d’Ivoire and Senegal, have acted as the main viral sources in the early stages of the epidemic. We show that convenience sampling can obfuscate the estimation of the spatial root of HIV-2A. We explicitly attempt to circumvent this by incorporating rate priors that reflect the ratio of human flow from and to West Africa. We recover four main routes of HIV-2A dispersal that are laid out along colonial ties: Guinea-Bissau and Cape Verde to Portugal, Côte d’Ivoire and Senegal to France. Within Europe, we find strong support for epidemiological linkage from Portugal to Luxembourg and to the UK. We demonstrate that probabilistic models can uncover global patterns of HIV-2A dispersal providing sampling bias is taken into account and we provide a scenario for the international spread of this virus. PMID:22190015

Informing Species Conservation at Multiple Scales Using Data Collected for Marine Mammal Stock Assessments

PubMed Central

Grech, Alana; Sheppard, James; Marsh, Helene

2011-01-01

Background Conservation planning and the design of marine protected areas (MPAs) requires spatially explicit information on the distribution of ecological features. Most species of marine mammals range over large areas and across multiple planning regions. The spatial distributions of marine mammals are difficult to predict using habitat modelling at ecological scales because of insufficient understanding of their habitat needs, however, relevant information may be available from surveys conducted to inform mandatory stock assessments. Methodology and Results We use a 20-year time series of systematic aerial surveys of dugong (Dugong dugong) abundance to create spatially-explicit models of dugong distribution and relative density at the scale of the coastal waters of northeast Australia (∼136,000 km2). We interpolated the corrected data at the scale of 2 km * 2 km planning units using geostatistics. Planning units were classified as low, medium, high and very high dugong density on the basis of the relative density of dugongs estimated from the models and a frequency analysis. Torres Strait was identified as the most significant dugong habitat in northeast Australia and the most globally significant habitat known for any member of the Order Sirenia. The models are used by local, State and Federal agencies to inform management decisions related to the Indigenous harvest of dugongs, gill-net fisheries and Australia's National Representative System of Marine Protected Areas. Conclusion/Significance In this paper we demonstrate that spatially-explicit population models add value to data collected for stock assessments, provide a robust alternative to predictive habitat distribution models, and inform species conservation at multiple scales. PMID:21464933

Analysis on Patterns of Globally Coupled Phase Oscillators with Attractive and Repulsive Interactions

NASA Astrophysics Data System (ADS)

Wang, Peng-Fei; Ruan, Xiao-Dong; Xu, Zhong-Bin; Fu, Xin

2015-11-01

The Hong-Strogatz (HS) model of globally coupled phase oscillators with attractive and repulsive interactions reflects the fact that each individual (oscillator) has its own attitude (attractive or repulsive) to the same environment (mean field). Previous studies on HS model focused mainly on the stable states on Ott-Antonsen (OA) manifold. In this paper, the eigenvalues of the Jacobi matrix of each fixed point in HS model are explicitly derived, with the aim to understand the local dynamics around each fixed point. Phase transitions are described according to relative population and coupling strength. Besides, the dynamics off OA manifold is studied. Supported by the National Basic Research Program of China under Grant No. 2015CB057301, the Applied Research Project of Public Welfare Technology of Zhejiang Province under Grant No. 201SC31109 and China Postdoctoral Science Foundation under Grant No. 2014M560483

Regional disparities in the beneficial effects of rising CO2 concentrations on crop water productivity

NASA Astrophysics Data System (ADS)

Deryng, Delphine; Elliott, Joshua; Folberth, Christian; Müller, Christoph; Pugh, Thomas A. M.; Boote, Kenneth J.; Conway, Declan; Ruane, Alex C.; Gerten, Dieter; Jones, James W.; Khabarov, Nikolay; Olin, Stefan; Schaphoff, Sibyll; Schmid, Erwin; Yang, Hong; Rosenzweig, Cynthia

2016-08-01

Rising atmospheric CO2 concentrations ([CO2]) are expected to enhance photosynthesis and reduce crop water use. However, there is high uncertainty about the global implications of these effects for future crop production and agricultural water requirements under climate change. Here we combine results from networks of field experiments and global crop models to present a spatially explicit global perspective on crop water productivity (CWP, the ratio of crop yield to evapotranspiration) for wheat, maize, rice and soybean under elevated [CO2] and associated climate change projected for a high-end greenhouse gas emissions scenario. We find CO2 effects increase global CWP by 10[047]%-27[737]% (median[interquartile range] across the model ensemble) by the 2080s depending on crop types, with particularly large increases in arid regions (by up to 48[25;56]% for rainfed wheat). If realized in the fields, the effects of elevated [CO2] could considerably mitigate global yield losses whilst reducing agricultural consumptive water use (4-17%). We identify regional disparities driven by differences in growing conditions across agro-ecosystems that could have implications for increasing food production without compromising water security. Finally, our results demonstrate the need to expand field experiments and encourage greater consistency in modelling the effects of rising [CO2] across crop and hydrological modelling communities.

Regional Disparities in the Beneficial Effects of Rising CO2 Emissions on Crop Water Productivity

NASA Technical Reports Server (NTRS)

Deryng, Delphine; Elliott, Joshua; Folberth, Christian; Meuller, Christoph; Pugh, Thomas A. M.; Boote, Kenneth J.; Conway, Declan; Ruane, Alex C.; Gerten, Dieter; Jones, James W.;

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

Explicit Simulation of Networks of Outlet Glaciers to Constrain Greenland's Sea Level Contribution

NASA Astrophysics Data System (ADS)

Ultee, E.; Bassis, J. N.

2017-12-01

Ice from the Greenland Ice Sheet drains to the ocean through hundreds of outlet glaciers, many of which are too small to be accurately resolved in continental-scale ice sheet models. Moreover, despite the fact that dynamic changes in Greenland outlet glaciers are currently responsible for about half of the ice sheet's contribution to global sea level, all but the largest are often excluded from major sea level assessments. We have previously developed and validated a simple model that simulates advance and retreat of networks of marine-terminating glaciers based on the perfect plastic approximation. Here we apply this model to a selection of forcing scenarios, representing both climate persistence and extreme scenarios, to constrain changes in calving flux from the most significant Greenland outlet glaciers. Our model can be implemented in standalone mode or as the calving module in a more sophisticated large-scale model, providing constraints on Greenland's future contribution to global sea level rise under a range of scenarios.

Towards Global Simulation of Irrigation in a Land Surface Model: Multiple Cropping and Rice Paddy in Southeast Asia

NASA Technical Reports Server (NTRS)

Beaudoing, Hiroko Kato; Rodell, Matthew; Ozdogan, Mutlu

2010-01-01

Agricultural land use significantly influences the surface water and energy balances. Effects of irrigation on land surface states and fluxes include repartitioning of latent and sensible heat fluxes, an increase in net radiation, and an increase in soil moisture and runoff. We are working on representing irrigation practices in continental- to global-scale land surface simulation in NASA's Global Land Data Assimilation System (GLDAS). Because agricultural practices across the nations are diverse, and complex, we are attempting to capture the first-order reality of the regional practices before achieving a global implementation. This study focuses on two issues in Southeast Asia: multiple cropping and rice paddy irrigation systems. We first characterize agricultural practices in the region (i.e., crop types, growing seasons, and irrigation) using the Global data set of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000) dataset. Rice paddy extent is identified using remote sensing products. Whether irrigated or rainfed, flooded fields need to be represented and treated explicitly. By incorporating these properties and processes into a physically based land surface model, we are able to quantify the impacts on the simulated states and fluxes.

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

Ocean-Atmosphere Coupled Model Simulations of Precipitation in the Central Andes

NASA Technical Reports Server (NTRS)

Nicholls, Stephen D.; Mohr, Karen I.

2015-01-01

The meridional extent and complex orography of the South American continent contributes to a wide diversity of climate regimes ranging from hyper-arid deserts to tropical rainforests to sub-polar highland regions. In addition, South American meteorology and climate are also made further complicated by ENSO, a powerful coupled ocean-atmosphere phenomenon. Modelling studies in this region have typically resorted to either atmospheric mesoscale or atmosphere-ocean coupled global climate models. The latter offers full physics and high spatial resolution, but it is computationally inefficient typically lack an interactive ocean, whereas the former offers high computational efficiency and ocean-atmosphere coupling, but it lacks adequate spatial and temporal resolution to adequate resolve the complex orography and explicitly simulate precipitation. Explicit simulation of precipitation is vital in the Central Andes where rainfall rates are light (0.5-5 mm hr-1), there is strong seasonality, and most precipitation is associated with weak mesoscale-organized convection. Recent increases in both computational power and model development have led to the advent of coupled ocean-atmosphere mesoscale models for both weather and climate study applications. These modelling systems, while computationally expensive, include two-way ocean-atmosphere coupling, high resolution, and explicit simulation of precipitation. In this study, we use the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST), a fully-coupled mesoscale atmosphere-ocean modeling system. Previous work has shown COAWST to reasonably simulate the entire 2003-2004 wet season (Dec-Feb) as validated against both satellite and model analysis data when ECMWF interim analysis data were used for boundary conditions on a 27-9-km grid configuration (Outer grid extent: 60.4S to 17.7N and 118.6W to 17.4W).

Constraints on natural global atmospheric CO2 fluxes from 1860 to 2010 using a simplified explicit forward model

PubMed Central

Hellevang, Helge; Aagaard, Per

2015-01-01

Land-use changes until the beginning of the 20th century made the terrestrial biosphere a net source of atmospheric carbon. Later, burning of fossil fuel surpassed land use changes as the major anthropogenic source of carbon. The terrestrial biosphere is at present suggested to be a carbon sink, but the distribution of excess anthropogenic carbon to the ocean and biosphere sinks is highly uncertain. Our modeling suggest that land-use changes can be tracked quite well by the carbon isotopes until mid-20th century, whereas burning of fossil fuel dominates the present-day observed changes in the isotope signature. The modeling indicates that the global carbon isotope fractionation has not changed significantly during the last 150 years. Furthermore, increased uptake of carbon by the ocean and increasing temperatures does not yet appear to have resulted in increasing the global gross ocean-to-atmosphere carbon fluxes. This may however change in the future when the excess carbon will emerge in the ocean upwelling zones, possibly reducing the net-uptake of carbon compared to the present-day ocean. PMID:26611741

Global Mittag-Leffler stability and synchronization analysis of fractional-order quaternion-valued neural networks with linear threshold neurons.

PubMed

Yang, Xujun; Li, Chuandong; Song, Qiankun; Chen, Jiyang; Huang, Junjian

2018-05-04

This paper talks about the stability and synchronization problems of fractional-order quaternion-valued neural networks (FQVNNs) with linear threshold neurons. On account of the non-commutativity of quaternion multiplication resulting from Hamilton rules, the FQVNN models are separated into four real-valued neural network (RVNN) models. Consequently, the dynamic analysis of FQVNNs can be realized by investigating the real-valued ones. Based on the method of M-matrix, the existence and uniqueness of the equilibrium point of the FQVNNs are obtained without detailed proof. Afterwards, several sufficient criteria ensuring the global Mittag-Leffler stability for the unique equilibrium point of the FQVNNs are derived by applying the Lyapunov direct method, the theory of fractional differential equation, the theory of matrix eigenvalue, and some inequality techniques. In the meanwhile, global Mittag-Leffler synchronization for the drive-response models of the addressed FQVNNs are investigated explicitly. Finally, simulation examples are designed to verify the feasibility and availability of the theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.

Global-scale Joint Body and Surface Wave Tomography with Vertical Transverse Isotropy for Seismic Monitoring Applications

NASA Astrophysics Data System (ADS)

Simmons, Nathan; Myers, Steve

2017-04-01

We continue to develop more advanced models of Earth's global seismic structure with specific focus on improving predictive capabilities for future seismic events. Our most recent version of the model combines high-quality P and S wave body wave travel times and surface-wave group and phase velocities into a joint (simultaneous) inversion process to tomographically image Earth's crust and mantle. The new model adds anisotropy (known as vertical transverse isotropy) to the model, which is necessitated by the addition of surface waves to the tomographic data set. Like previous versions of the model the new model consists of 59 surfaces and 1.6 million model nodes from the surface to the core-mantle boundary, overlaying a 1-D outer and inner core model. The model architecture is aspherical and we directly incorporate Earth's expected hydrostatic shape (ellipticity and mantle stretching). We also explicitly honor surface undulations including the Moho, several internal crustal units, and the upper mantle transition zone undulations as predicated by previous studies. The explicit Earth model design allows for accurate travel time computation using our unique 3-D ray tracing algorithms, capable of 3-D ray tracing more than 20 distinct seismic phases including crustal, regional, teleseismic, and core phases. Thus, we can now incorporate certain secondary (and sometimes exotic) phases into source location determination and other analyses. New work on model uncertainty quantification assesses the error covariance of the model, which when completed will enable calculation of path-specific estimates of uncertainty for travel times computed using our previous model (LLNL-G3D-JPS) which is available to the monitoring and broader research community and we encourage external evaluation and validation. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Load Balancing Using Time Series Analysis for Soft Real Time Systems with Statistically Periodic Loads

NASA Technical Reports Server (NTRS)

Hailperin, Max

1993-01-01

This thesis provides design and analysis of techniques for global load balancing on ensemble architectures running soft-real-time object-oriented applications with statistically periodic loads. It focuses on estimating the instantaneous average load over all the processing elements. The major contribution is the use of explicit stochastic process models for both the loading and the averaging itself. These models are exploited via statistical time-series analysis and Bayesian inference to provide improved average load estimates, and thus to facilitate global load balancing. This thesis explains the distributed algorithms used and provides some optimality results. It also describes the algorithms' implementation and gives performance results from simulation. These results show that our techniques allow more accurate estimation of the global system load ing, resulting in fewer object migration than local methods. Our method is shown to provide superior performance, relative not only to static load-balancing schemes but also to many adaptive methods.

Teaching Children about the Global Economy: Integrating Inquiry with Human Rights

ERIC Educational Resources Information Center

McCall, Ava L.

2017-01-01

Although children are already part of the global economy, they often have little understanding of its influence without explicit instruction. The article focuses on recommendations for teaching elementary students in grades three through five about the global economy utilizing the pedagogical recommendations from the National Council for the…

Using an Explicit Emission Tagging Method in Global Modeling of Source-Receptor Relationships for Black Carbon in the Arctic: Variations, Sources and Transport Pathways

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

Wang, Hailong; Rasch, Philip J.; Easter, Richard C.

2014-11-27

We introduce an explicit emission tagging technique in the Community Atmosphere Model to quantify source-region-resolved characteristics of black carbon (BC), focusing on the Arctic. Explicit tagging of BC source regions without perturbing the emissions makes it straightforward to establish source-receptor relationships and transport pathways, providing a physically consistent and computationally efficient approach to produce a detailed characterization of the destiny of regional BC emissions and the potential for mitigation actions. Our analysis shows that the contributions of major source regions to the global BC burden are not proportional to the respective emissions due to strong region-dependent removal rates and lifetimes,more » while the contributions to BC direct radiative forcing show a near-linear dependence on their respective contributions to the burden. Distant sources contribute to BC in remote regions mostly in the mid- and upper troposphere, having much less impact on lower-level concentrations (and deposition) than on burden. Arctic BC concentrations, deposition and source contributions all have strong seasonal variations. Eastern Asia contributes the most to the wintertime Arctic burden. Northern Europe emissions are more important to both surface concentration and deposition in winter than in summer. The largest contribution to Arctic BC in the summer is from Northern Asia. Although local emissions contribute less than 10% to the annual mean BC burden and deposition within the Arctic, the per-emission efficiency is much higher than for major non-Arctic sources. The interannual variability (1996-2005) due to meteorology is small in annual mean BC burden and radiative forcing but is significant in yearly seasonal means over the Arctic. When a slow aging treatment of BC is introduced, the increase of BC lifetime and burden is source-dependent. Global BC forcing-per-burden efficiency also increases primarily due to changes in BC vertical distributions. The relative contribution from major non-Arctic sources to the Arctic BC burden increases only slightly, although the contribution of Arctic local sources is reduced by a factor of 2 due to the slow aging treatment.« less

Spatializing 6,000 years of global urbanization from 3700 BC to AD 2000

NASA Astrophysics Data System (ADS)

Reba, Meredith; Reitsma, Femke; Seto, Karen C.

2016-06-01

How were cities distributed globally in the past? How many people lived in these cities? How did cities influence their local and regional environments? In order to understand the current era of urbanization, we must understand long-term historical urbanization trends and patterns. However, to date there is no comprehensive record of spatially explicit, historic, city-level population data at the global scale. Here, we developed the first spatially explicit dataset of urban settlements from 3700 BC to AD 2000, by digitizing, transcribing, and geocoding historical, archaeological, and census-based urban population data previously published in tabular form by Chandler and Modelski. The dataset creation process also required data cleaning and harmonization procedures to make the data internally consistent. Additionally, we created a reliability ranking for each geocoded location to assess the geographic uncertainty of each data point. The dataset provides the first spatially explicit archive of the location and size of urban populations over the last 6,000 years and can contribute to an improved understanding of contemporary and historical urbanization trends.

Spatializing 6,000 years of global urbanization from 3700 BC to AD 2000

PubMed Central

Reba, Meredith; Reitsma, Femke; Seto, Karen C.

2016-01-01

How were cities distributed globally in the past? How many people lived in these cities? How did cities influence their local and regional environments? In order to understand the current era of urbanization, we must understand long-term historical urbanization trends and patterns. However, to date there is no comprehensive record of spatially explicit, historic, city-level population data at the global scale. Here, we developed the first spatially explicit dataset of urban settlements from 3700 BC to AD 2000, by digitizing, transcribing, and geocoding historical, archaeological, and census-based urban population data previously published in tabular form by Chandler and Modelski. The dataset creation process also required data cleaning and harmonization procedures to make the data internally consistent. Additionally, we created a reliability ranking for each geocoded location to assess the geographic uncertainty of each data point. The dataset provides the first spatially explicit archive of the location and size of urban populations over the last 6,000 years and can contribute to an improved understanding of contemporary and historical urbanization trends. PMID:27271481

High potential for weathering and climate effects of non-vascular vegetation in the Late Ordovician

PubMed Central

Porada, P.; Lenton, T. M.; Pohl, A.; Weber, B.; Mander, L.; Donnadieu, Y.; Beer, C.; Pöschl, U.; Kleidon, A.

2016-01-01

It has been hypothesized that predecessors of today's bryophytes significantly increased global chemical weathering in the Late Ordovician, thus reducing atmospheric CO2 concentration and contributing to climate cooling and an interval of glaciations. Studies that try to quantify the enhancement of weathering by non-vascular vegetation, however, are usually limited to small areas and low numbers of species, which hampers extrapolating to the global scale and to past climatic conditions. Here we present a spatially explicit modelling approach to simulate global weathering by non-vascular vegetation in the Late Ordovician. We estimate a potential global weathering flux of 2.8 (km3 rock) yr−1, defined here as volume of primary minerals affected by chemical transformation. This is around three times larger than today's global chemical weathering flux. Moreover, we find that simulated weathering is highly sensitive to atmospheric CO2 concentration. This implies a strong negative feedback between weathering by non-vascular vegetation and Ordovician climate. PMID:27385026

Incorporating microbes into large-scale biogeochemical models

NASA Astrophysics Data System (ADS)

Allison, S. D.; Martiny, J. B.

2008-12-01

Micro-organisms, including Bacteria, Archaea, and Fungi, control major processes throughout the Earth system. Recent advances in microbial ecology and microbiology have revealed an astounding level of genetic and metabolic diversity in microbial communities. However, a framework for interpreting the meaning of this diversity has lagged behind the initial discoveries. Microbial communities have yet to be included explicitly in any major biogeochemical models in terrestrial ecosystems, and have only recently broken into ocean models. Although simplification of microbial communities is essential in complex systems, omission of community parameters may seriously compromise model predictions of biogeochemical processes. Two key questions arise from this tradeoff: 1) When and where must microbial community parameters be included in biogeochemical models? 2) If microbial communities are important, how should they be simplified, aggregated, and parameterized in models? To address these questions, we conducted a meta-analysis to determine if microbial communities are sensitive to four environmental disturbances that are associated with global change. In all cases, we found that community composition changed significantly following disturbance. However, the implications for ecosystem function were unclear in most of the published studies. Therefore, we developed a simple model framework to illustrate the situations in which microbial community changes would affect rates of biogeochemical processes. We found that these scenarios could be quite common, but powerful predictive models cannot be developed without much more information on the functions and disturbance responses of microbial taxa. Small-scale models that explicitly incorporate microbial communities also suggest that process rates strongly depend on microbial interactions and disturbance responses. The challenge is to scale up these models to make predictions at the ecosystem and global scales based on measurable parameters. We argue that meeting this challenge will require a coordinated effort to develop a series of nested models at scales ranging from the micron to the globe in order to optimize the tradeoff between model realism and feasibility.

Explicitly Accounting for Protected Lands within the GCAM 3.0

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

Dooley, James J.; Zhou, Yuyu

2012-05-01

The Global Change Assessment Model Version 3.0 defines three different levels of “Protected Lands” within the agricultural and landuse component. These three different scenarios effectively cordon off 3.5% (5.0 million km2) of the Earth’s terrestrial lands in the de minimus Protected Land Scenario, 5.0% (7.20 million km2) in the Core Protected Land Scenario, and 8.2% (11.8 million km2) in the Expanded Protected Land Scenario. None of these scenarios represents the “right” level of Protected Lands for the planet today or tomorrow. Rather, the goal is to create a range of scenarios that can be used in modeling human responses tomore » climate change and the impact those would have on managed and unmanaged terrestrial lands. These scenarios harness the wealth of information in the United Nations Environment Programme World Conservation Monitoring Centre’s World Database on Protected Areas and its categories of explicit degrees of protection.« less

Optimal implicit 2-D finite differences to model wave propagation in poroelastic media

NASA Astrophysics Data System (ADS)

Itzá, Reymundo; Iturrarán-Viveros, Ursula; Parra, Jorge O.

2016-08-01

Numerical modeling of seismic waves in heterogeneous porous reservoir rocks is an important tool for the interpretation of seismic surveys in reservoir engineering. We apply globally optimal implicit staggered-grid finite differences (FD) to model 2-D wave propagation in heterogeneous poroelastic media at a low-frequency range (<10 kHz). We validate the numerical solution by comparing it to an analytical-transient solution obtaining clear seismic wavefields including fast P and slow P and S waves (for a porous media saturated with fluid). The numerical dispersion and stability conditions are derived using von Neumann analysis, showing that over a wide range of porous materials the Courant condition governs the stability and this optimal implicit scheme improves the stability of explicit schemes. High-order explicit FD can be replaced by some lower order optimal implicit FD so computational cost will not be as expensive while maintaining the accuracy. Here, we compute weights for the optimal implicit FD scheme to attain an accuracy of γ = 10-8. The implicit spatial differentiation involves solving tridiagonal linear systems of equations through Thomas' algorithm.

Aeras: A next generation global atmosphere model

DOE PAGES

Spotz, William F.; Smith, Thomas M.; Demeshko, Irina P.; ...

2015-06-01

Sandia National Laboratories is developing a new global atmosphere model named Aeras that is performance portable and supports the quantification of uncertainties. These next-generation capabilities are enabled by building Aeras on top of Albany, a code base that supports the rapid development of scientific application codes while leveraging Sandia's foundational mathematics and computer science packages in Trilinos and Dakota. Embedded uncertainty quantification (UQ) is an original design capability of Albany, and performance portability is a recent upgrade. Other required features, such as shell-type elements, spectral elements, efficient explicit and semi-implicit time-stepping, transient sensitivity analysis, and concurrent ensembles, were not componentsmore » of Albany as the project began, and have been (or are being) added by the Aeras team. We present early UQ and performance portability results for the shallow water equations.« less

Global asymptotic stability and hopf bifurcation for a blood cell production model.

PubMed

Crauste, Fabien

2006-04-01

We analyze the asymptotic stability of a nonlinear system of two differential equations with delay, describing the dynamics of blood cell produc- tion. This process takes place in the bone marrow, where stem cells differen- tiate throughout division in blood cells. Taking into account an explicit role of the total population of hematopoietic stem cells in the introduction of cells in cycle, we are led to study a characteristic equation with delay-dependent coefficients. We determine a necessary and sufficient condition for the global stability of the first steady state of our model, which describes the popula- tion's dying out, and we obtain the existence of a Hopf bifurcation for the only nontrivial positive steady state, leading to the existence of periodic solutions. These latter are related to dynamical diseases affecting blood cells known for their cyclic nature.

Computing approximate solutions of the protein structure determination problem using global constraints on discrete crystal lattices.

PubMed

Dal Palù, Alessandro; Dovier, Agostino; Pontelli, Enrico

2010-01-01

Crystal lattices are discrete models of the three-dimensional space that have been effectively employed to facilitate the task of determining proteins' natural conformation. This paper investigates alternative global constraints that can be introduced in a constraint solver over discrete crystal lattices. The objective is to enhance the efficiency of lattice solvers in dealing with the construction of approximate solutions of the protein structure determination problem. Some of them (e.g., self-avoiding-walk) have been explicitly or implicitly already used in previous approaches, while others (e.g., the density constraint) are new. The intrinsic complexities of all of them are studied and preliminary experimental results are discussed.

From water use to water scarcity footprinting in environmentally extended input-output analysis.

PubMed

Ridoutt, Bradley George; Hadjikakou, Michalis; Nolan, Martin; Bryan, Brett A

2018-05-18

Environmentally extended input-output analysis (EEIOA) supports environmental policy by quantifying how demand for goods and services leads to resource use and emissions across the economy. However, some types of resource use and emissions require spatially-explicit impact assessment for meaningful interpretation, which is not possible in conventional EEIOA. For example, water use in locations of scarcity and abundance is not environmentally equivalent. Opportunities for spatially-explicit impact assessment in conventional EEIOA are limited because official input-output tables tend to be produced at the scale of political units which are not usually well aligned with environmentally relevant spatial units. In this study, spatially-explicit water scarcity factors and a spatially disaggregated Australian water use account were used to develop water scarcity extensions that were coupled with a multi-regional input-output model (MRIO). The results link demand for agricultural commodities to the problem of water scarcity in Australia and globally. Important differences were observed between the water use and water scarcity footprint results, as well as the relative importance of direct and indirect water use, with significant implications for sustainable production and consumption-related policies. The approach presented here is suggested as a feasible general approach for incorporating spatially-explicit impact assessment in EEIOA.

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

Aartsen, M.G.; Abraham, K.; Ackermann, M.

We present an improved event-level likelihood formalism for including neutrino telescope data in global fits to new physics. We derive limits on spin-dependent dark matter-proton scattering by employing the new formalism in a re-analysis of data from the 79-string IceCube search for dark matter annihilation in the Sun, including explicit energy information for each event. The new analysis excludes a number of models in the weak-scale minimal supersymmetric standard model (MSSM) for the first time. This work is accompanied by the public release of the 79-string IceCube data, as well as an associated computer code for applying the new likelihoodmore » to arbitrary dark matter models.« less

Carbon mapping of Argentine savannas: Using fractional tree cover to scale from field to region

NASA Astrophysics Data System (ADS)

González-Roglich, M.; Swenson, J. J.

2015-12-01

Programs which intend to maintain or enhance carbon (C) stocks in natural ecosystems are promising, but require detailed and spatially explicit C distribution models to monitor the effectiveness of management interventions. Savanna ecosystems are significant components of the global C cycle, covering about one fifth of the global land mass, but they have received less attention in C monitoring protocols. Our goal was to estimate C storage across a broad savanna ecosystem using field surveys and freely available satellite images. We first mapped tree canopies at 2.5 m resolution with a spatial subset of high resolution panchromatic images to then predict regional wall-to-wall tree percent cover using 30-m Landsat imagery and the Random Forests algorithms. We found that a model with summer and winter spectral indices from Landsat, climate and topography performed best. Using a linear relationship between C and % tree cover, we then predicted tree C stocks across the gradient of tree cover, explaining 87 % of the variability. The spatially explicit validation of the tree C model with field-measured C-stocks revealed an RMSE of 8.2 tC/ha which represented ~30% of the mean C stock for areas with tree cover, comparable to studies based on more advanced remote sensing methods, such as LiDAR and RADAR. Sample spatial distribution highly affected the performance of the RF models in predicting tree cover, raising concerns regarding the predictive capabilities of the model in areas for which training data is not present. The 50,000 km2 has ~41 Tg C, which could be released to the atmosphere if agricultural pressure intensifies in this semiarid savanna.

Estimating the numerical diapycnal mixing in an eddy-permitting ocean model

NASA Astrophysics Data System (ADS)

Megann, Alex

2018-01-01

Constant-depth (or "z-coordinate") ocean models such as MOM4 and NEMO have become the de facto workhorse in climate applications, having attained a mature stage in their development and are well understood. A generic shortcoming of this model type, however, is a tendency for the advection scheme to produce unphysical numerical diapycnal mixing, which in some cases may exceed the explicitly parameterised mixing based on observed physical processes, and this is likely to have effects on the long-timescale evolution of the simulated climate system. Despite this, few quantitative estimates have been made of the typical magnitude of the effective diapycnal diffusivity due to numerical mixing in these models. GO5.0 is a recent ocean model configuration developed jointly by the UK Met Office and the National Oceanography Centre. It forms the ocean component of the GC2 climate model, and is closely related to the ocean component of the UKESM1 Earth System Model, the UK's contribution to the CMIP6 model intercomparison. GO5.0 uses version 3.4 of the NEMO model, on the ORCA025 global tripolar grid. An approach to quantifying the numerical diapycnal mixing in this model, based on the isopycnal watermass analysis of Lee et al. (2002), is described, and the estimates thereby obtained of the effective diapycnal diffusivity in GO5.0 are compared with the values of the explicit diffusivity used by the model. It is shown that the effective mixing in this model configuration is up to an order of magnitude higher than the explicit mixing in much of the ocean interior, implying that mixing in the model below the mixed layer is largely dominated by numerical mixing. This is likely to have adverse consequences for the representation of heat uptake in climate models intended for decadal climate projections, and in particular is highly relevant to the interpretation of the CMIP6 class of climate models, many of which use constant-depth ocean models at ¼° resolution

Multiscale Failure Analysis of Laminated Composite Panels Subjected to Blast Loading Using FEAMAC/Explicit

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Waas, Anthony M.; Berdnarcyk, Brett A.; Arnold, Steven M.; Collier, Craig S.

2009-01-01

This preliminary report demonstrates the capabilities of the recently developed software implementation that links the Generalized Method of Cells to explicit finite element analysis by extending a previous development which tied the generalized method of cells to implicit finite elements. The multiscale framework, which uses explicit finite elements at the global-scale and the generalized method of cells at the microscale is detailed. This implementation is suitable for both dynamic mechanics problems and static problems exhibiting drastic and sudden changes in material properties, which often encounter convergence issues with commercial implicit solvers. Progressive failure analysis of stiffened and un-stiffened fiber-reinforced laminates subjected to normal blast pressure loads was performed and is used to demonstrate the capabilities of this framework. The focus of this report is to document the development of the software implementation; thus, no comparison between the results of the models and experimental data is drawn. However, the validity of the results are assessed qualitatively through the observation of failure paths, stress contours, and the distribution of system energies.

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 accuracy of climate models' simulated season lengths and the effectiveness of grid scale correction factors

DOE PAGES

Winterhalter, Wade E.

2011-09-01

Global climate change is expected to impact biological populations through a variety of mechanisms including increases in the length of their growing season. Climate models are useful tools for predicting how season length might change in the future. However, the accuracy of these models tends to be rather low at regional geographic scales. Here, I determined the ability of several atmosphere and ocean general circulating models (AOGCMs) to accurately simulate historical season lengths for a temperate ectotherm across the continental United States. I also evaluated the effectiveness of regional-scale correction factors to improve the accuracy of these models. I foundmore » that both the accuracy of simulated season lengths and the effectiveness of the correction factors to improve the model's accuracy varied geographically and across models. These results suggest that regional specific correction factors do not always adequately remove potential discrepancies between simulated and historically observed environmental parameters. As such, an explicit evaluation of the correction factors' effectiveness should be included in future studies of global climate change's impact on biological populations.« less

Terrestrial nitrogen cycling in Earth system models revisited

USGS Publications Warehouse

Stocker, Benjamin D; Prentice, I. Colin; Cornell, Sarah; Davies-Barnard, T; Finzi, Adrien; Franklin, Oskar; Janssens, Ivan; Larmola, Tuula; Manzoni, Stefano; Näsholm, Torgny; Raven, John; Rebel, Karin; Reed, Sasha C.; Vicca, Sara; Wiltshire, Andy; Zaehle, Sönke

2016-01-01

Understanding the degree to which nitrogen (N) availability limits land carbon (C) uptake under global environmental change represents an unresolved challenge. First-generation ‘C-only’vegetation models, lacking explicit representations of N cycling,projected a substantial and increasing land C sink under rising atmospheric CO2 concentrations. This prediction was questioned for not taking into account the potentially limiting effect of N availability, which is necessary for plant growth (Hungate et al.,2003). More recent global models include coupled C and N cycles in land ecosystems (C–N models) and are widely assumed to be more realistic. However, inclusion of more processes has not consistently improved their performance in capturing observed responses of the global C cycle (e.g. Wenzel et al., 2014). With the advent of a new generation of global models, including coupled C, N, and phosphorus (P) cycling, model complexity is sure to increase; but model reliability may not, unless greater attention is paid to the correspondence of model process representations ande mpirical evidence. It was in this context that the ‘Nitrogen Cycle Workshop’ at Dartington Hall, Devon, UK was held on 1–5 February 2016. Organized by I. Colin Prentice and Benjamin D. Stocker (Imperial College London, UK), the workshop was funded by the European Research Council,project ‘Earth system Model Bias Reduction and assessing Abrupt Climate change’ (EMBRACE). We gathered empirical ecologists and ecosystem modellers to identify key uncertainties in terrestrial C–N cycling, and to discuss processes that are missing or poorly represented in current models.

AgMIP Coordinated Global and Regional Assessments for 1.5°C and 2.0°C

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2017-12-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study performs a proof-of-concept of the CGRA to demonstrate advantages and challenges of the framework. This effort responds to the request by UNFCCC for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), HAPPI and CMIP5 ensemble scenarios, global gridded crop models, global agricultural economic models, site-based crop models, and within-country regional economic models. CGRA results show that at the global scale, mixed areas of positive and negative simulated yield changes, with declines in some breadbasket regions led to overall declines in productivity at both 1.5°C and 2.0°C. These projected global yield changes resulted in increases in prices of major commodities in a global economic model. Simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on region and crop, but with more negative effects on productivity at 2.0°C than at 1.5°C for the most part. In conjunction with price changes from the global economics models, these productivity declines resulted generally in small positive effects on regional farm livelihoods, showing that farming systems should continue to be viable under high mitigation scenarios. CGRA protocols focus on how mitigation actions and effects differ across scales, with main mechanisms studied in the integrated assessment models being policies and technologies that reduce direct non-CO2 emissions from agriculture, reduce CO2 emissions from land use change and forest sink enhancement, and utilize biomass for energy production. At regional scales, increasing soil organic carbon (SOC) is of active interest.

Regional impacts of iron-light colimitation in a global biogeochemical model

NASA Astrophysics Data System (ADS)

Galbraith, E. D.; Gnanadesikan, A.; Dunne, J. P.; Hiscock, M. R.

2010-03-01

Laboratory and field studies have revealed that iron has multiple roles in phytoplankton physiology, with particular importance for light-harvesting cellular machinery. However, although iron-limitation is explicitly included in numerous biogeochemical/ecosystem models, its implementation varies, and its effect on the efficiency of light harvesting is often ignored. Given the complexity of the ocean environment, it is difficult to predict the consequences of applying different iron limitation schemes. Here we explore the interaction of iron and nutrient cycles in an ocean general circulation model using a new, streamlined model of ocean biogeochemistry. Building on previously published parameterizations of photoadaptation and export production, the Biogeochemistry with Light Iron Nutrients and Gasses (BLING) model is constructed with only four explicit tracers but including macronutrient and micronutrient limitation, light limitation, and an implicit treatment of community structure. The structural simplicity of this computationally-inexpensive model allows us to clearly isolate the global effect that iron availability has on maximum light-saturated photosynthesis rates vs. the effect iron has on photosynthetic efficiency. We find that the effect on light-saturated photosynthesis rates is dominant, negating the importance of photosynthetic efficiency in most regions, especially the cold waters of the Southern Ocean. The primary exceptions to this occur in iron-rich regions of the Northern Hemisphere, where high light-saturated photosynthesis rates allow photosynthetic efficiency to play a more important role. In other words, the ability to efficiently harvest photons has little effect in regions where light-saturated growth rates are low. Additionally, we speculate that the phytoplankton cells dominating iron-limited regions tend to have relatively high photosynthetic efficiency, due to reduced packaging effects. If this speculation is correct, it would imply that natural communities of iron-stressed phytoplankton may tend to harvest photons more efficiently than would be inferred from iron-limitation experiments with other phytoplankton. We suggest that iron limitation of photosynthetic efficiency has a relatively small impact on global biogeochemistry, though it is expected to impact the seasonal cycle of plankton as well as the vertical structure of primary production.

Scattering from Colloid-Polymer Conjugates with Excluded Volume Effect

DOE PAGES

Li, Xin; Sanchez-Diaz, Luis E.; Smith, Gregory Scott; ...

2015-01-13

This work presents scattering functions of conjugates consisting of a colloid particle and a self-avoiding polymer chain as a model for protein-polymer conjugates and nanoparticle-polymer conjugates in solution. The model is directly derived from the two-point correlation function with the inclusion of excluded volume effects. The dependence of the calculated scattering function on the geometric shape of the colloid and polymer stiffness is investigated. The model is able to describe the experimental scattering signature of the solutions of suspending hard particle-polymer conjugates and provide additional conformational information. This model explicitly elucidates the link between the global conformation of a conjugatemore » and the microstructure of its constituent components.« less

A scattering function of star polymers including excluded volume effects

DOE PAGES

Li, Xin; Do, Changwoo; Liu, Yun; ...

2014-11-04

In this work we present a new model for the form factor of a star polymer consisting of self-avoiding branches. This new model incorporates excluded volume effects and is derived from the two point correlation function for a star polymer.. We compare this model to small angle neutron scattering (SANS) measurements from polystyrene (PS) stars immersed in a good solvent, tetrahydrofuran (THF). It is shown that this model provides a good description of the scattering signature originating from the excluded volume effect and it explicitly elucidates the connection between the global conformation of a star polymer and the local stiffnessmore » of its constituent branch.« less

Superstatistical model of bacterial DNA architecture

NASA Astrophysics Data System (ADS)

Bogachev, Mikhail I.; Markelov, Oleg A.; Kayumov, Airat R.; Bunde, Armin

2017-02-01

Understanding the physical principles that govern the complex DNA structural organization as well as its mechanical and thermodynamical properties is essential for the advancement in both life sciences and genetic engineering. Recently we have discovered that the complex DNA organization is explicitly reflected in the arrangement of nucleotides depicted by the universal power law tailed internucleotide interval distribution that is valid for complete genomes of various prokaryotic and eukaryotic organisms. Here we suggest a superstatistical model that represents a long DNA molecule by a series of consecutive ~150 bp DNA segments with the alternation of the local nucleotide composition between segments exhibiting long-range correlations. We show that the superstatistical model and the corresponding DNA generation algorithm explicitly reproduce the laws governing the empirical nucleotide arrangement properties of the DNA sequences for various global GC contents and optimal living temperatures. Finally, we discuss the relevance of our model in terms of the DNA mechanical properties. As an outlook, we focus on finding the DNA sequences that encode a given protein while simultaneously reproducing the nucleotide arrangement laws observed from empirical genomes, that may be of interest in the optimization of genetic engineering of long DNA molecules.

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

A spatially explicit representation of conservation agriculture for application in global change studies.

PubMed

Prestele, Reinhard; Hirsch, Annette L; Davin, Edouard L; Seneviratne, Sonia I; Verburg, Peter H

2018-05-10

Conservation agriculture (CA) is widely promoted as a sustainable agricultural management strategy with the potential to alleviate some of the adverse effects of modern, industrial agriculture such as large-scale soil erosion, nutrient leaching and overexploitation of water resources. Moreover, agricultural land managed under CA is proposed to contribute to climate change mitigation and adaptation through reduced emission of greenhouse gases, increased solar radiation reflection, and the sustainable use of soil and water resources. Due to the lack of official reporting schemes, the amount of agricultural land managed under CA systems is uncertain and spatially explicit information about the distribution of CA required for various modeling studies is missing. Here, we present an approach to downscale present-day national-level estimates of CA to a 5 arcminute regular grid, based on multicriteria analysis. We provide a best estimate of CA distribution and an uncertainty range in the form of a low and high estimate of CA distribution, reflecting the inconsistency in CA definitions. We also design two scenarios of the potential future development of CA combining present-day data and an assessment of the potential for implementation using biophysical and socioeconomic factors. By our estimates, 122-215 Mha or 9%-15% of global arable land is currently managed under CA systems. The lower end of the range represents CA as an integrated system of permanent no-tillage, crop residue management and crop rotations, while the high estimate includes a wider range of areas primarily devoted to temporary no-tillage or reduced tillage operations. Our scenario analysis suggests a future potential of CA in the range of 533-1130 Mha (38%-81% of global arable land). Our estimates can be used in various ecosystem modeling applications and are expected to help identifying more realistic climate mitigation and adaptation potentials of agricultural practices. © 2018 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

On isometry anomalies in minimal 𝒩 = (0,1) and 𝒩 = (0,2) sigma models

NASA Astrophysics Data System (ADS)

Chen, Jin; Cui, Xiaoyi; Shifman, Mikhail; Vainshtein, Arkady

2016-09-01

The two-dimensional minimal supersymmetric sigma models with homogeneous target spaces G/H and chiral fermions of the same chirality are revisited. In particular, we look into the isometry anomalies in O(N) and CP(N - 1) models. These anomalies are generated by fermion loop diagrams which we explicitly calculate. In the case of O(N) sigma models the first Pontryagin class vanishes, so there is no global obstruction for the minimal 𝒩 = (0, 1) supersymmetrization of these models. We show that at the local level isometries in these models can be made anomaly free by specifying the counterterms explicitly. Thus, there are no obstructions to quantizing the minimal 𝒩 = (0, 1) models with the SN-1 = SO(N)/SO(N - 1) target space while preserving the isometries. This also includes CP(1) (equivalent to S2) which is an exceptional case from the CP(N - 1) series. For other CP(N - 1) models, the isometry anomalies cannot be rescued even locally, this leads us to a discussion on the relation between the geometric and gauged formulations of the CP(N - 1) models to compare the original of different anomalies. A dual formalism of O(N) model is also given, in order to show the consistency of our isometry anomaly analysis in different formalisms. The concrete counterterms to be added, however, will be formalism dependent.

Intercomparison and Evaluation of Global Aerosol Microphysical Properties Among Aerocom Models of a Range of Complexity

NASA Technical Reports Server (NTRS)

Mann, G. W.; Carslaw, K. S.; Reddington, C. L.; Pringle, K. J.; Schulz, M.; Asmi, A.; Spracklen, D. V.; Ridley, D. A.; Woodhouse, M. T.; Lee, L. A.;

Global Pyrogeography: the Current and Future Distribution of Wildfire

PubMed Central

Krawchuk, Meg A.; Moritz, Max A.; Parisien, Marc-André; Van Dorn, Jeff; Hayhoe, Katharine

2009-01-01

Climate change is expected to alter the geographic distribution of wildfire, a complex abiotic process that responds to a variety of spatial and environmental gradients. How future climate change may alter global wildfire activity, however, is still largely unknown. As a first step to quantifying potential change in global wildfire, we present a multivariate quantification of environmental drivers for the observed, current distribution of vegetation fires using statistical models of the relationship between fire activity and resources to burn, climate conditions, human influence, and lightning flash rates at a coarse spatiotemporal resolution (100 km, over one decade). We then demonstrate how these statistical models can be used to project future changes in global fire patterns, highlighting regional hotspots of change in fire probabilities under future climate conditions as simulated by a global climate model. Based on current conditions, our results illustrate how the availability of resources to burn and climate conditions conducive to combustion jointly determine why some parts of the world are fire-prone and others are fire-free. In contrast to any expectation that global warming should necessarily result in more fire, we find that regional increases in fire probabilities may be counter-balanced by decreases at other locations, due to the interplay of temperature and precipitation variables. Despite this net balance, our models predict substantial invasion and retreat of fire across large portions of the globe. These changes could have important effects on terrestrial ecosystems since alteration in fire activity may occur quite rapidly, generating ever more complex environmental challenges for species dispersing and adjusting to new climate conditions. Our findings highlight the potential for widespread impacts of climate change on wildfire, suggesting severely altered fire regimes and the need for more explicit inclusion of fire in research on global vegetation-climate change dynamics and conservation planning. PMID:19352494

The impact of ARM on climate modeling

DOE PAGES

Randall, David A.; Del Genio, Anthony D.; Donner, Lee J.; ...

2016-07-15

Climate models are among humanity’s most ambitious and elaborate creations. They are designed to simulate the interactions of the atmosphere, ocean, land surface, and cryosphere on time scales far beyond the limits of deterministic predictability and including the effects of time-dependent external forcings. The processes involved include radiative transfer, fluid dynamics, microphysics, and some aspects of geochemistry, biology, and ecology. The models explicitly simulate processes on spatial scales ranging from the circumference of Earth down to 100 km or smaller and implicitly include the effects of processes on even smaller scales down to a micron or so. In addition, themore » atmospheric component of a climate model can be called an atmospheric global circulation model (AGCM).« less

Soil Biogeochemistry in the Ent DGVM

NASA Astrophysics Data System (ADS)

Kharecha, P. A.; Kiang, N. Y.; Aleinov, I.; Moorcroft, P.; Koster, R.

2007-12-01

As the global climate continues to warm in the 21st century, it will be vital to assess the degree of carbon cycle feedbacks from the terrestrial biosphere, particularly the soil. Global soil carbon stocks, which amount to approximately double the carbon stored in vegetation, could provide either positive or negative climate feedbacks, depending on a given ecosystem's response to warming. To predict changes in net terrestrial CO2 fluxes and belowground organic carbon storage, we have developed and evaluated a soil biogeochemistry submodel for the Ent dynamic global vegetation model currently being tested within the GISS GCM. It is a modified version of the soil submodel in the CASA biosphere model (Potter et al., Glob. Biogeoch. Cyc. 7, 1993). We have enhanced it to allow for explicit depth structure (2 soil layers, 0-30 cm and 30-100 cm), first-order inter-layer (vertical) soil organic carbon transport, and a variable-Q10 temperature dependence for soil microbial respiration. We have tested the soil model in numerous offline runs. To spin up the simulated carbon pools offline, we conducted multi-century runs using meteorological and ecological data from various FLUXNET field sites that represent 7 of the 8 GISS GCM plant functional types: tundra, grassland, shrubland, savanna, deciduous forest, evergreen needleleaf forest, and tropical rainforest (the eighth, cropland, will be dealt with in a separate study). We then compare the magnitudes of the simulated spun-up soil pools to soil carbon stock data from these field sites as well as the biome-aggregated data from Post et al. (Nature 317, 1985). Net ecosystem CO2 fluxes and soil respiration are also compared to site-specific measurements where available. Preliminary results suggest that simulated fluxes are reasonably close to measured values, but simulated carbon storage tends to be lower than the measurements. In addition to site-specific comparisons, we discuss the broader implications of our results, e.g., the effects of including explicit depth structure and inter-layer soil carbon transport on simulated soil respiration, carbon storage, and estimation of the global carbon budget.

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

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

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

2012-01-01

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

A Multi-scale Modeling System: Developments, Applications and Critical Issues

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chern, Jiundar; Atlas, Robert; Randall, David; Lin, Xin; Khairoutdinov, Marat; Li, Jui-Lin; Waliser, Duane E.; Hou, Arthur; Peters-Lidard, Christa;

Alternative Food in the Global South: Reflections on a Direct Marketing Initiative in Kenya

ERIC Educational Resources Information Center

Freidberg, Susanne; Goldstein, Lissa

2011-01-01

Amidst booming scholarship on alternative food networks (AFNs) in the global North, research on AFN in the global South remains scarce. Partly this is because explicitly alternative initiatives are themselves scarce, except for those focused on export markets. Yet in countries such as Kenya, urban consumers and rural smallholders have good reason…

Evaluating the Impact of Role-Playing Simulations on Global Competency in an Online Transnational Engineering Course

ERIC Educational Resources Information Center

Wold, Kari

2013-01-01

Successfully interacting with those from different cultures is essential to excel in any field, particularly when global, transnational collaborations in the workplace are increasingly common. However, many higher education students in engineering are not explicitly taught how to display the global competency skills desired by future employers. To…

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.

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.

Explicit formulation of an anisotropic Allman/DKT 3-node thin triangular flat shell elements

NASA Astrophysics Data System (ADS)

Ertas, A.; Krafcik, J. T.; Ekwaro-Osire, S.

A simple, explicit formulation of the stiffness matrix for an anisotropic, 3-node, thin triangular, flat shell element in global coordinates is presented. An Allman triangle is used for membrane stiffness. The membrane stiffness matrix is explicitly derived by applying an Allman transformation to a Felippa 6-node linear strain triangle (LST). Bending stiffness is incorporated by the use of a discrete Kirchhoff triangle (DKT) bending triangle. Stiffness terms resulting from anisotropic membrane-bending coupling are included by integrating, in area coordinates, membrane and bending strain-displacement matrices.

Global Asymptotic Behavior of Iterative Implicit Schemes

NASA Technical Reports Server (NTRS)

Yee, H. C.; Sweby, P. K.

1994-01-01

The global asymptotic nonlinear behavior of some standard iterative procedures in solving nonlinear systems of algebraic equations arising from four implicit linear multistep methods (LMMs) in discretizing three models of 2 x 2 systems of first-order autonomous nonlinear ordinary differential equations (ODEs) is analyzed using the theory of dynamical systems. The iterative procedures include simple iteration and full and modified Newton iterations. The results are compared with standard Runge-Kutta explicit methods, a noniterative implicit procedure, and the Newton method of solving the steady part of the ODEs. Studies showed that aside from exhibiting spurious asymptotes, all of the four implicit LMMs can change the type and stability of the steady states of the differential equations (DEs). They also exhibit a drastic distortion but less shrinkage of the basin of attraction of the true solution than standard nonLMM explicit methods. The simple iteration procedure exhibits behavior which is similar to standard nonLMM explicit methods except that spurious steady-state numerical solutions cannot occur. The numerical basins of attraction of the noniterative implicit procedure mimic more closely the basins of attraction of the DEs and are more efficient than the three iterative implicit procedures for the four implicit LMMs. Contrary to popular belief, the initial data using the Newton method of solving the steady part of the DEs may not have to be close to the exact steady state for convergence. These results can be used as an explanation for possible causes and cures of slow convergence and nonconvergence of steady-state numerical solutions when using an implicit LMM time-dependent approach in computational fluid dynamics.

Coevolution of Cooperation and Partner Rewiring Range in Spatial Social Networks

NASA Astrophysics Data System (ADS)

Khoo, Tommy; Fu, Feng; Pauls, Scott

2016-11-01

In recent years, there has been growing interest in the study of coevolutionary games on networks. Despite much progress, little attention has been paid to spatially embedded networks, where the underlying geographic distance, rather than the graph distance, is an important and relevant aspect of the partner rewiring process. It thus remains largely unclear how individual partner rewiring range preference, local vs. global, emerges and affects cooperation. Here we explicitly address this issue using a coevolutionary model of cooperation and partner rewiring range preference in spatially embedded social networks. In contrast to local rewiring, global rewiring has no distance restriction but incurs a one-time cost upon establishing any long range link. We find that under a wide range of model parameters, global partner switching preference can coevolve with cooperation. Moreover, the resulting partner network is highly degree-heterogeneous with small average shortest path length while maintaining high clustering, thereby possessing small-world properties. We also discover an optimum availability of reputation information for the emergence of global cooperators, who form distant partnerships at a cost to themselves. From the coevolutionary perspective, our work may help explain the ubiquity of small-world topologies arising alongside cooperation in the real world.

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

PubMed

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

2016-01-01

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

A new solution method for wheel/rail rolling contact.

PubMed

Yang, Jian; Song, Hua; Fu, Lihua; Wang, Meng; Li, Wei

2016-01-01

To solve the problem of wheel/rail rolling contact of nonlinear steady-state curving, a three-dimensional transient finite element (FE) model is developed by the explicit software ANSYS/LS-DYNA. To improve the solving speed and efficiency, an explicit-explicit order solution method is put forward based on analysis of the features of implicit and explicit algorithm. The solution method was first applied to calculate the pre-loading of wheel/rail rolling contact with explicit algorithm, and then the results became the initial conditions in solving the dynamic process of wheel/rail rolling contact with explicit algorithm as well. Simultaneously, the common implicit-explicit order solution method is used to solve the FE model. Results show that the explicit-explicit order solution method has faster operation speed and higher efficiency than the implicit-explicit order solution method while the solution accuracy is almost the same. Hence, the explicit-explicit order solution method is more suitable for the wheel/rail rolling contact model with large scale and high nonlinearity.

Solving the Sea-Level Equation in an Explicit Time Differencing Scheme

NASA Astrophysics Data System (ADS)

Klemann, V.; Hagedoorn, J. M.; Thomas, M.

2016-12-01

In preparation of coupling the solid-earth to an ice-sheet compartment in an earth-system model, the dependency of initial topography on the ice-sheet history and viscosity structure has to be analysed. In this study, we discuss this dependency and how it influences the reconstruction of former sea level during a glacial cycle. The modelling is based on the VILMA code in which the field equations are solved in the time domain applying an explicit time-differencing scheme. The sea-level equation is solved simultaneously in the same explicit scheme as the viscoleastic field equations (Hagedoorn et al., 2007). With the assumption of only small changes, we neglect the iterative solution at each time step as suggested by e.g. Kendall et al. (2005). Nevertheless, the prediction of the initial paleo topography in case of moving coastlines remains to be iterated by repeated integration of the whole load history. The sensitivity study sketched at the beginning is accordingly motivated by the question if the iteration of the paleo topography can be replaced by a predefined one. This study is part of the German paleoclimate modelling initiative PalMod. Lit:Hagedoorn JM, Wolf D, Martinec Z, 2007. An estimate of global mean sea-level rise inferred from tide-gauge measurements using glacial-isostatic models consistent with the relative sea-level record. Pure appl. Geophys. 164: 791-818, doi:10.1007/s00024-007-0186-7Kendall RA, Mitrovica JX, Milne GA, 2005. On post-glacial sea level - II. Numerical formulation and comparative reesults on spherically symmetric models. Geophys. J. Int., 161: 679-706, doi:10.1111/j.365-246.X.2005.02553.x

Climatological temperature senstivity of soil carbon turnover: Observations, simple scaling models, and ESMs

NASA Astrophysics Data System (ADS)

Koven, C. D.; Hugelius, G.; Lawrence, D. M.; Wieder, W. R.

2016-12-01

The projected loss of soil carbon to the atmosphere resulting from climate change is a potentially large but highly uncertain feedback to warming. The magnitude of this feedback is poorly constrained by observations and theory, and is disparately represented in Earth system models. To assess the likely long-term response of soils to climate change, spatial gradients in soil carbon turnover times can identify broad-scale and long-term controls on the rate of carbon cycling as a function of climate and other factors. Here we show that the climatological temperature control on carbon turnover in the top meter of global soils is more sensitive in cold climates than in warm ones. We present a simplified model that explains the high cold-climate sensitivity using only the physical scaling of soil freeze-thaw state across climate gradients. Critically, current Earth system models (ESMs) fail to capture this pattern, however it emerges from an ESM that explicitly resolves vertical gradients in soil climate and turnover. The weak tropical temperature sensitivity emerges from a different model that explicitly resolves mineralogical control on decomposition. These results support projections of strong future carbon-climate feedbacks from northern soils and demonstrate a method for ESMs to capture this emergent behavior.

Representing Plant Hydraulics in a Global Model: Updates to the Community Land Model

NASA Astrophysics Data System (ADS)

Kennedy, D.; Swenson, S. C.; Oleson, K. W.; Lawrence, D. M.; Fisher, R.; Gentine, P.

2017-12-01

In previous versions, the Community Land Model has used soil moisture to stand in for plant water status, with transpiration and photosynthesis driven directly by soil water potential. This eschews significant literature demonstrating the importance of plant hydraulic traits in the dynamics of water flow through the soil-plant-atmosphere continuum and in the regulation of stomatal aperture. In this study we install a simplified hydraulic framework to represent vegetation water potential and to regulate root water uptake and turbulent fluxes. Plant hydraulics allow for a more explicit representation of plant water status, which improves the physical basis for many processes represented in CLM. This includes root water uptake and the attenuation of photosynthesis and transpiration with drought. Model description is accompanied by results from a point simulation based at the Caxiuanã flux tower site in Eastern Amazonia, covering a throughfall exclusion experiment from 2001-2003. Including plant hydraulics improves the response to drought forcing compared to previous versions of CLM. Parameter sensitivity is examined at the same site and presented in the context of estimating hydraulic parameters in a global model.

A novel approach to modeling atmospheric convection

NASA Astrophysics Data System (ADS)

Goodman, A.

2016-12-01

The inadequate representation of clouds continues to be a large source of uncertainty in the projections from global climate models (GCMs). With continuous advances in computational power, however, the ability for GCMs to explicitly resolve cumulus convection will soon be realized. For this purpose, Jung and Arakawa (2008) proposed the Vector Vorticity Model (VVM), in which vorticity is the predicted variable instead of momentum. This has the advantage of eliminating the pressure gradient force within the framework of an anelastic system. However, the VVM was designed for use on a planar quadrilateral grid, making it unsuitable for implementation in global models discretized on the sphere. Here we have proposed a modification to the VVM where instead the curl of the horizontal vorticity is the primary predicted variable. This allows us to maintain the benefits of the original VVM while working within the constraints of a non-quadrilateral mesh. We found that our proposed model produced results from a warm bubble simulation that were consistent with the VVM. Further improvements that can be made to the VVM are also discussed.

Spontaneous Centralization of Control in a Network of Company Ownerships

PubMed Central

Krause, Sebastian M.; Peixoto, Tiago P.; Bornholdt, Stefan

2013-01-01

We introduce a model for the adaptive evolution of a network of company ownerships. In a recent work it has been shown that the empirical global network of corporate control is marked by a central, tightly connected “core” made of a small number of large companies which control a significant part of the global economy. Here we show how a simple, adaptive “rich get richer” dynamics can account for this characteristic, which incorporates the increased buying power of more influential companies, and in turn results in even higher control. We conclude that this kind of centralized structure can emerge without it being an explicit goal of these companies, or as a result of a well-organized strategy. PMID:24324594

Benchmarking carbon-nitrogen interactions in Earth System Models to observations: An inter-comparison of nitrogen limitation in global land surface models with carbon and nitrogen cycles (CLM-CN and O-CN)

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Zaehle, S.; Templer, P. H.; Goodale, C. L.

2011-12-01

Predictions of climate change depend on accurately modeling the feedbacks among the carbon cycle, nitrogen cycle, and climate system. Several global land surface models have shown that nitrogen limitation determines how land carbon fluxes respond to rising CO2, nitrogen deposition, and climate change, thereby influencing predictions of climate change. However, the magnitude of the carbon-nitrogen-climate feedbacks varies considerably by model, leading to critical and timely questions of why they differ and how they compare to field observations. To address these questions, we initiated a model inter-comparison of spatial patterns and drivers of nitrogen limitation. The experiment assessed the regional consequences of sustained nitrogen additions in a set of 25-year global nitrogen fertilization simulations. The model experiments were designed to cover effects from small changes in nitrogen inputs associated with plausible increases in nitrogen deposition to large changes associated with field-based nitrogen fertilization experiments. The analyses of model simulations included assessing the geographically varying degree of nitrogen limitation on plant and soil carbon cycling and the mechanisms underlying model differences. Here, we present results from two global land-surface models (CLM-CN and O-CN) with differing approaches to modeling carbon-nitrogen interactions. The predictions from each model were compared to a set of globally distributed observational data that includes nitrogen fertilization experiments, 15N tracer studies, small catchment nitrogen input-output studies, and syntheses across nitrogen deposition gradients. Together these datasets test many aspects of carbon-nitrogen coupling and are able to differentiate between the two models. Overall, this study is the first to explicitly benchmark carbon and nitrogen interactions in Earth System Models using a range of observations and is a foundation for future inter-comparisons.

For how long can we predict the weather? - Insights into atmospheric predictability from global convection-allowing simulations

NASA Astrophysics Data System (ADS)

Judt, Falko

2017-04-01

A tremendous increase in computing power has facilitated the advent of global convection-resolving numerical weather prediction (NWP) models. Although this technological breakthrough allows for the seamless prediction of weather from local to global scales, the predictability of multiscale weather phenomena in these models is not very well known. To address this issue, we conducted a global high-resolution (4-km) predictability experiment using the Model for Prediction Across Scales (MPAS), a state-of-the-art global NWP model developed at the National Center for Atmospheric Research. The goals of this experiment are to investigate error growth from convective to planetary scales and to quantify the intrinsic, scale-dependent predictability limits of atmospheric motions. The globally uniform resolution of 4 km allows for the explicit treatment of organized deep moist convection, alleviating grave limitations of previous predictability studies that either used high-resolution limited-area models or global simulations with coarser grids and cumulus parameterization. Error growth is analyzed within the context of an "identical twin" experiment setup: the error is defined as the difference between a 20-day long "nature run" and a simulation that was perturbed with small-amplitude noise, but is otherwise identical. It is found that in convectively active regions, errors grow by several orders of magnitude within the first 24 h ("super-exponential growth"). The errors then spread to larger scales and begin a phase of exponential growth after 2-3 days when contaminating the baroclinic zones. After 16 days, the globally averaged error saturates—suggesting that the intrinsic limit of atmospheric predictability (in a general sense) is about two weeks, which is in line with earlier estimates. However, error growth rates differ between the tropics and mid-latitudes as well as between the troposphere and stratosphere, highlighting that atmospheric predictability is a complex problem. The comparatively slower error growth in the tropics and in the stratosphere indicates that certain weather phenomena could potentially have longer predictability than currently thought.

[Proposal for a Nationwide Johann-Peter Frank Cooperation Model under the National Leopoldina Initiative for Public Health and Global Health].

PubMed

Teichert, U; Kaufhold, C; Rissland, J; Tinnemann, P; Wildner, M

2016-07-01

The discussion on the development of public health affairs was invigorated anew by the report on public health in Germany of Leopoldina/Acatech/Union of the German Academies of Sciences and Humanities of the year 2015. The report urges strengthening of public health and global health in Germany and addresses explicitly the Public Health Service (PHS). This indispensable inclusion of the PHS in further strategic planning offers for the first time an opportunity for a comprehensive and sustainable practice/policy transfer on the federal, state and community level, and also a chance for a sustainable network with modern academic public health institutions together with representation of medical specialization in public health at universities, that has been absent so far. A Johann-Peter Frank model for cooperation and stepwise modelling of this transition with the inclusion of the Academies for Public Health Service is presented. © Georg Thieme Verlag KG Stuttgart · New York.

Modeled climate-induced glacier change in Glacier National Park, 1850-2100

USGS Publications Warehouse

Hall, M.H.P.; Fagre, D.B.

2003-01-01

The glaciers in the Blackfoot-Jackson Glacier Basin of Glacier National Park, Montana, decreased in area from 21.6 square kilometers (km2) in 1850 to 7.4 km2 in 1979. Over this same period global temperatures increased by 0.45??C (?? 0. 15??C). We analyzed the climatic causes and ecological consequences of glacier retreat by creating spatially explicit models of the creation and ablation of glaciers and of the response of vegetation to climate change. We determined the melt rate and spatial distribution of glaciers under two possible future climate scenarios, one based on carbon dioxide-induced global warming and the other on a linear temperature extrapolation. Under the former scenario, all glaciers in the basin will disappear by the year 2030, despite predicted increases in precipitation; under the latter, melting is slower. Using a second model, we analyzed vegetation responses to variations in soil moisture and increasing temperature in a complex alpine landscape and predicted where plant communities are likely to be located as conditions change.

Growth-rate dependent global effects on gene expression in bacteria

PubMed Central

Klumpp, Stefan; Zhang, Zhongge; Hwa, Terence

2010-01-01

Summary Bacterial gene expression depends not only on specific regulations but also directly on bacterial growth, because important global parameters such as the abundance of RNA polymerases and ribosomes are all growth-rate dependent. Understanding these global effects is necessary for a quantitative understanding of gene regulation and for the robust design of synthetic genetic circuits. The observed growth-rate dependence of constitutive gene expression can be explained by a simple model using the measured growth-rate dependence of the relevant cellular parameters. More complex growth dependences for genetic circuits involving activators, repressors and feedback control were analyzed, and salient features were verified experimentally using synthetic circuits. The results suggest a novel feedback mechanism mediated by general growth-dependent effects and not requiring explicit gene regulation, if the expressed protein affects cell growth. This mechanism can lead to growth bistability and promote the acquisition of important physiological functions such as antibiotic resistance and tolerance (persistence). PMID:20064380

UPC++ Programmer’s Guide (v1.0 2017.9)

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

Bachan, J.; Baden, S.; Bonachea, D.

UPC++ is a C++11 library that provides Asynchronous Partitioned Global Address Space (APGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The APGAS model is single program, multiple-data (SPMD), with each separate thread of execution (referred to as a rank, a term borrowed from MPI) having access to local memory as it would in C++. However, APGAS also provides access to a global address space, which is allocated in shared segments that are distributed over the ranks. UPC++ provides numerous methods for accessing and using global memory. In UPC++, allmore » operations that access remote memory are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all remote-memory access operations are by default asynchronous, to enable programmers to write code that scales well even on hundreds of thousands of cores.« less

UPC++ Programmer’s Guide, v1.0-2018.3.0

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

Bachan, J.; Baden, S.; Bonachea, Dan

UPC++ is a C++11 library that provides Partitioned Global Address Space (PGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The PGAS model is single program, multiple-data (SPMD), with each separate thread of execution (referred to as a rank, a term borrowed from MPI) having access to local memory as it would in C++. However, PGAS also provides access to a global address space, which is allocated in shared segments that are distributed over the ranks. UPC++ provides numerous methods for accessing and using global memory. In UPC++, all operationsmore » that access remote memory are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all remote-memory access operations are by default asynchronous, to enable programmers to write code that scales well even on hundreds of thousands of cores.« less

Explicit Global Simulation of Gravity Waves up to the Lower Thermosphere

NASA Astrophysics Data System (ADS)

Becker, E.

2016-12-01

At least for short-term simulations, middle atmosphere general circulation models (GCMs) can be run with sufficiently high resolution in order to describe a good part of the gravity wave spectrum explicitly. Nevertheless, the parameterization of unresolved dynamical scales remains an issue, especially when the scales of parameterized gravity waves (GWs) and resolved GWs become comparable. In addition, turbulent diffusion must always be parameterized along with other subgrid-scale dynamics. A practical solution to the combined closure problem for GWs and turbulent diffusion is to dispense with a parameterization of GWs, apply a high spatial resolution, and to represent the unresolved scales by a macro-turbulent diffusion scheme that gives rise to wave damping in a self-consistent fashion. This is the approach of a few GCMs that extend from the surface to the lower thermosphere and simulate a realistic GW drag and summer-to-winter-pole residual circulation in the upper mesosphere. In this study we describe a new version of the Kuehlungsborn Mechanistic general Circulation Model (KMCM), which includes explicit (though idealized) computations of radiative transfer and the tropospheric moisture cycle. Particular emphasis is spent on 1) the turbulent diffusion scheme, 2) the attenuation of resolved GWs at critical levels, 3) the generation of GWs in the middle atmosphere from body forces, and 4) GW-tidal interactions (including the energy deposition of GWs and tides).

Current Status and Challenges of Atmospheric Data Assimilation

NASA Astrophysics Data System (ADS)

Atlas, R. M.; Gelaro, R.

2016-12-01

The issues of modern atmospheric data assimilation are fairly simple to comprehend but difficult to address, involving the combination of literally billions of model variables and tens of millions of observations daily. In addition to traditional meteorological variables such as wind, temperature pressure and humidity, model state vectors are being expanded to include explicit representation of precipitation, clouds, aerosols and atmospheric trace gases. At the same time, model resolutions are approaching single-kilometer scales globally and new observation types have error characteristics that are increasingly non-Gaussian. This talk describes the current status and challenges of atmospheric data assimilation, including an overview of current methodologies, the difficulty of estimating error statistics, and progress toward coupled earth system analyses.

Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments

NASA Astrophysics Data System (ADS)

Rosenzweig, Cynthia; Ruane, Alex C.; Antle, John; Elliott, Joshua; Ashfaq, Muhammad; Chatta, Ashfaq Ahmad; Ewert, Frank; Folberth, Christian; Hathie, Ibrahima; Havlik, Petr; Hoogenboom, Gerrit; Lotze-Campen, Hermann; MacCarthy, Dilys S.; Mason-D'Croz, Daniel; Contreras, Erik Mencos; Müller, Christoph; Perez-Dominguez, Ignacio; Phillips, Meridel; Porter, Cheryl; Raymundo, Rubi M.; Sands, Ronald D.; Schleussner, Carl-Friedrich; Valdivia, Roberto O.; Valin, Hugo; Wiebe, Keith

2018-05-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study aims to perform a proof of concept of the CGRA to demonstrate advantages and challenges of the proposed framework. This effort responds to the request by the UN Framework Convention on Climate Change (UNFCCC) for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) and Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble scenarios, global gridded crop models, global agricultural economics models, site-based crop models and within-country regional economics models. The CGRA consistently links disciplines, models and scales in order to track the complex chain of climate impacts and identify key vulnerabilities, feedbacks and uncertainties in managing future risk. CGRA proof-of-concept results show that, at the global scale, there are mixed areas of positive and negative simulated wheat and maize yield changes, with declines in some breadbasket regions, at both 1.5°C and 2.0°C. Declines are especially evident in simulations that do not take into account direct CO2 effects on crops. These projected global yield changes mostly resulted in increases in prices and areas of wheat and maize in two global economics models. Regional simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on the region and the crop. In conjunction with price changes from the global economics models, productivity declines in the Punjab, Pakistan, resulted in an increase in vulnerable households and the poverty rate. This article is part of the theme issue `The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.

Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments.

PubMed

Rosenzweig, Cynthia; Ruane, Alex C; Antle, John; Elliott, Joshua; Ashfaq, Muhammad; Chatta, Ashfaq Ahmad; Ewert, Frank; Folberth, Christian; Hathie, Ibrahima; Havlik, Petr; Hoogenboom, Gerrit; Lotze-Campen, Hermann; MacCarthy, Dilys S; Mason-D'Croz, Daniel; Contreras, Erik Mencos; Müller, Christoph; Perez-Dominguez, Ignacio; Phillips, Meridel; Porter, Cheryl; Raymundo, Rubi M; Sands, Ronald D; Schleussner, Carl-Friedrich; Valdivia, Roberto O; Valin, Hugo; Wiebe, Keith

2018-05-13

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study aims to perform a proof of concept of the CGRA to demonstrate advantages and challenges of the proposed framework. This effort responds to the request by the UN Framework Convention on Climate Change (UNFCCC) for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) and Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble scenarios, global gridded crop models, global agricultural economics models, site-based crop models and within-country regional economics models. The CGRA consistently links disciplines, models and scales in order to track the complex chain of climate impacts and identify key vulnerabilities, feedbacks and uncertainties in managing future risk. CGRA proof-of-concept results show that, at the global scale, there are mixed areas of positive and negative simulated wheat and maize yield changes, with declines in some breadbasket regions, at both 1.5°C and 2.0°C. Declines are especially evident in simulations that do not take into account direct CO 2 effects on crops. These projected global yield changes mostly resulted in increases in prices and areas of wheat and maize in two global economics models. Regional simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on the region and the crop. In conjunction with price changes from the global economics models, productivity declines in the Punjab, Pakistan, resulted in an increase in vulnerable households and the poverty rate.This article is part of the theme issue 'The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'. © 2018 The Authors.

Development of the Semi-implicit Time Integration in KIM-SH

NASA Astrophysics Data System (ADS)

NAM, H.

2015-12-01

The Korea Institute of Atmospheric Prediction Systems (KIAPS) was founded in 2011 by the Korea Meteorological Administration (KMA) to develop Korea's own global Numerical Weather Prediction (NWP) system as nine year (2011-2019) project. The KIM-SH is a KIAPS integrated model-spectral element based in the HOMME. In KIM-SH, the explicit schemes are employed. We introduce the three- and two-time-level semi-implicit scheme in KIM-SH as the time integration. Explicit schemes however have a tendancy to be unstable and require very small timesteps while semi-implicit schemes are very stable and can have much larger timesteps.We define the linear and reference values, then by definition of semi-implicit scheme, we apply the linear solver as GMRES. The numerical results from experiments will be introduced with the current development status of the time integration in KIM-SH. Several numerical examples are shown to confirm the efficiency and reliability of the proposed schemes.

Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence

USDA-ARS?s Scientific Manuscript database

Global monitoring of agricultural productivity is critical in a world under a continuous increase of food demand. Here we have used new spaceborne retrievals of chlorophyll fluorescence, an emission quantity intrinsically linked to photosynthesis, to derive spatially explicit photosynthetic uptake r...

A global, spatially-explicit assessment of irrigated croplands influenced by urban wastewater flows

NASA Astrophysics Data System (ADS)

Thebo, A. L.; Drechsel, P.; Lambin, E. F.; Nelson, K. L.

2017-07-01

When urban areas expand without concomitant increases in wastewater treatment capacity, vast quantities of wastewater are released to surface waters with little or no treatment. Downstream of many urban areas are large areas of irrigated croplands reliant on these same surface water sources. Case studies document the widespread use of untreated wastewater in irrigated agriculture, but due to the practical and political challenges of conducting a true census of this practice, its global extent is not well known except where reuse has been planned. This study used GIS-based modeling methods to develop the first spatially-explicit estimate of the global extent of irrigated croplands influenced by urban wastewater flows, including indirect wastewater use. These croplands were further classified by their likelihood of using poor quality water based on the spatial proximity of croplands to urban areas, urban wastewater return flow ratios, and proportion of wastewater treated. This study found that 65% (35.9 Mha) of downstream irrigated croplands were located in catchments with high levels of dependence on urban wastewater flows. These same catchments were home to 1.37 billion urban residents. Of these croplands, 29.3 Mha were located in countries with low levels of wastewater treatment and home to 885 million urban residents. These figures provide insight into the key role that water reuse plays in meeting the water and food needs of people around the world, and the need to invest in wastewater treatment to protect public health.

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.

Load Balancing Using Time Series Analysis for Soft Real Time Systems with Statistically Periodic Loads

NASA Technical Reports Server (NTRS)

Hailperin, M.

1993-01-01

This thesis provides design and analysis of techniques for global load balancing on ensemble architectures running soft-real-time object-oriented applications with statistically periodic loads. It focuses on estimating the instantaneous average load over all the processing elements. The major contribution is the use of explicit stochastic process models for both the loading and the averaging itself. These models are exploited via statistical time-series analysis and Bayesian inference to provide improved average load estimates, and thus to facilitate global load balancing. This thesis explains the distributed algorithms used and provides some optimality results. It also describes the algorithms' implementation and gives performance results from simulation. These results show that the authors' techniques allow more accurate estimation of the global system loading, resulting in fewer object migrations than local methods. The authors' method is shown to provide superior performance, relative not only to static load-balancing schemes but also to many adaptive load-balancing methods. Results from a preliminary analysis of another system and from simulation with a synthetic load provide some evidence of more general applicability.

A test of the hierarchical model of litter decomposition.

PubMed

Bradford, Mark A; Veen, G F Ciska; Bonis, Anne; Bradford, Ella M; Classen, Aimee T; Cornelissen, J Hans C; Crowther, Thomas W; De Long, Jonathan R; Freschet, Gregoire T; Kardol, Paul; Manrubia-Freixa, Marta; Maynard, Daniel S; Newman, Gregory S; Logtestijn, Richard S P; Viketoft, Maria; Wardle, David A; Wieder, William R; Wood, Stephen A; van der Putten, Wim H

2017-12-01

Our basic understanding of plant litter decomposition informs the assumptions underlying widely applied soil biogeochemical models, including those embedded in Earth system models. Confidence in projected carbon cycle-climate feedbacks therefore depends on accurate knowledge about the controls regulating the rate at which plant biomass is decomposed into products such as CO 2 . Here we test underlying assumptions of the dominant conceptual model of litter decomposition. The model posits that a primary control on the rate of decomposition at regional to global scales is climate (temperature and moisture), with the controlling effects of decomposers negligible at such broad spatial scales. Using a regional-scale litter decomposition experiment at six sites spanning from northern Sweden to southern France-and capturing both within and among site variation in putative controls-we find that contrary to predictions from the hierarchical model, decomposer (microbial) biomass strongly regulates decomposition at regional scales. Furthermore, the size of the microbial biomass dictates the absolute change in decomposition rates with changing climate variables. Our findings suggest the need for revision of the hierarchical model, with decomposers acting as both local- and broad-scale controls on litter decomposition rates, necessitating their explicit consideration in global biogeochemical models.

Explicit Context Matching in Content-Based Publish/Subscribe Systems

PubMed Central

Vavassori, Sergio; Soriano, Javier; Lizcano, David; Jiménez, Miguel

2013-01-01

Although context could be exploited to improve performance, elasticity and adaptation in most distributed systems that adopt the publish/subscribe (P/S) communication model, only a few researchers have focused on the area of context-aware matching in P/S systems and have explored its implications in domains with highly dynamic context like wireless sensor networks (WSNs) and IoT-enabled applications. Most adopted P/S models are context agnostic or do not differentiate context from the other application data. In this article, we present a novel context-aware P/S model. SilboPS manages context explicitly, focusing on the minimization of network overhead in domains with recurrent context changes related, for example, to mobile ad hoc networks (MANETs). Our approach represents a solution that helps to efficiently share and use sensor data coming from ubiquitous WSNs across a plethora of applications intent on using these data to build context awareness. Specifically, we empirically demonstrate that decoupling a subscription from the changing context in which it is produced and leveraging contextual scoping in the filtering process notably reduces (un)subscription cost per node, while improving the global performance/throughput of the network of brokers without altering the cost of SIENA-like topology changes. PMID:23529118

Compilation of 3D global conductivity model of the Earth for space weather applications

NASA Astrophysics Data System (ADS)

Alekseev, Dmitry; Kuvshinov, Alexey; Palshin, Nikolay

2015-07-01

We have compiled a global three-dimensional (3D) conductivity model of the Earth with an ultimate goal to be used for realistic simulation of geomagnetically induced currents (GIC), posing a potential threat to man-made electric systems. Bearing in mind the intrinsic frequency range of the most intense disturbances (magnetospheric substorms) with typical periods ranging from a few minutes to a few hours, the compiled 3D model represents the structure in depth range of 0-100 km, including seawater, sediments, earth crust, and partly the lithosphere/asthenosphere. More explicitly, the model consists of a series of spherical layers, whose vertical and lateral boundaries are established based on available data. To compile a model, global maps of bathymetry, sediment thickness, and upper and lower crust thicknesses as well as lithosphere thickness are utilized. All maps are re-interpolated on a common grid of 0.25×0.25 degree lateral spacing. Once the geometry of different structures is specified, each element of the structure is assigned either a certain conductivity value or conductivity versus depth distribution, according to available laboratory data and conversion laws. A numerical formalism developed for compilation of the model, allows for its further refinement by incorporation of regional 3D conductivity distributions inferred from the real electromagnetic data. So far we included into our model four regional conductivity models, available from recent publications, namely, surface conductance model of Russia, and 3D conductivity models of Fennoscandia, Australia, and northwest of the United States.

Model criticism based on likelihood-free inference, with an application to protein network evolution.

PubMed

Ratmann, Oliver; Andrieu, Christophe; Wiuf, Carsten; Richardson, Sylvia

2009-06-30

Mathematical models are an important tool to explain and comprehend complex phenomena, and unparalleled computational advances enable us to easily explore them without any or little understanding of their global properties. In fact, the likelihood of the data under complex stochastic models is often analytically or numerically intractable in many areas of sciences. This makes it even more important to simultaneously investigate the adequacy of these models-in absolute terms, against the data, rather than relative to the performance of other models-but no such procedure has been formally discussed when the likelihood is intractable. We provide a statistical interpretation to current developments in likelihood-free Bayesian inference that explicitly accounts for discrepancies between the model and the data, termed Approximate Bayesian Computation under model uncertainty (ABCmicro). We augment the likelihood of the data with unknown error terms that correspond to freely chosen checking functions, and provide Monte Carlo strategies for sampling from the associated joint posterior distribution without the need of evaluating the likelihood. We discuss the benefit of incorporating model diagnostics within an ABC framework, and demonstrate how this method diagnoses model mismatch and guides model refinement by contrasting three qualitative models of protein network evolution to the protein interaction datasets of Helicobacter pylori and Treponema pallidum. Our results make a number of model deficiencies explicit, and suggest that the T. pallidum network topology is inconsistent with evolution dominated by link turnover or lateral gene transfer alone.

A Verification System for Distributed Objects with Asynchronous Method Calls

NASA Astrophysics Data System (ADS)

Ahrendt, Wolfgang; Dylla, Maximilian

We present a verification system for Creol, an object-oriented modeling language for concurrent distributed applications. The system is an instance of KeY, a framework for object-oriented software verification, which has so far been applied foremost to sequential Java. Building on KeY characteristic concepts, like dynamic logic, sequent calculus, explicit substitutions, and the taclet rule language, the system presented in this paper addresses functional correctness of Creol models featuring local cooperative thread parallelism and global communication via asynchronous method calls. The calculus heavily operates on communication histories which describe the interfaces of Creol units. Two example scenarios demonstrate the usage of the system.

Leveraging human decision making through the optimal management of centralized resources

NASA Astrophysics Data System (ADS)

Hyden, Paul; McGrath, Richard G.

2016-05-01

Combining results from mixed integer optimization, stochastic modeling and queuing theory, we will advance the interdisciplinary problem of efficiently and effectively allocating centrally managed resources. Academia currently fails to address this, as the esoteric demands of each of these large research areas limits work across traditional boundaries. The commercial space does not currently address these challenges due to the absence of a profit metric. By constructing algorithms that explicitly use inputs across boundaries, we are able to incorporate the advantages of using human decision makers. Key improvements in the underlying algorithms are made possible by aligning decision maker goals with the feedback loops introduced between the core optimization step and the modeling of the overall stochastic process of supply and demand. A key observation is that human decision-makers must be explicitly included in the analysis for these approaches to be ultimately successful. Transformative access gives warfighters and mission owners greater understanding of global needs and allows for relationships to guide optimal resource allocation decisions. Mastery of demand processes and optimization bottlenecks reveals long term maximum marginal utility gaps in capabilities.

The Global Fund to Fight AIDS, Tuberculosis and Malaria's investments in harm reduction through the rounds-based funding model (2002-2014).

PubMed

Bridge, Jamie; Hunter, Benjamin M; Albers, Eliot; Cook, Catherine; Guarinieri, Mauro; Lazarus, Jeffrey V; MacAllister, Jack; McLean, Susie; Wolfe, Daniel

2016-01-01

Harm reduction is an evidence-based, effective response to HIV transmission and other harms faced by people who inject drugs, and is explicitly supported by the Global Fund to Fight AIDS, Tuberculosis and Malaria. In spite of this, people who inject drugs continue to have poor and inequitable access to these services and face widespread stigma and discrimination. In 2013, the Global Fund launched a new funding model-signalling the end of the previous rounds-based model that had operated since its founding in 2002. This study updates previous analyses to assess Global Fund investments in harm reduction interventions for the duration of the rounds-based model, from 2002 to 2014. Global Fund HIV and TB/HIV grant documents from 2002 to 2014 were reviewed to identify grants that contained activities for people who inject drugs. Data were collected from detailed grant budgets, and relevant budget lines were recorded and analysed to determine the resources allocated to different interventions that were specifically targeted at people who inject drugs. 151 grants for 58 countries, plus one regional proposal, contained activities targeting people who inject drugs-for a total investment of US$ 620 million. Two-thirds of this budgeted amount was for interventions in the "comprehensive package" defined by the United Nations. 91% of the identified amount was for Eastern Europe and Asia. This study represents an updated, comprehensive assessment of Global Fund investments in harm reduction from its founding (2002) until the start of the new funding model (2014). It also highlights the overall shortfall of harm reduction funding, with the estimated global need being US$ 2.3 billion for harm reduction in 2015 alone. Using this baseline, the Global Fund must carefully monitor its new funding model and ensure that investments in harm reduction are maintained or scaled-up. There are widespread concerns regarding the withdrawal from middle-income countries where harm reduction remains essential and unfunded through other sources: for example, 15% of the identified investments were for countries which are now ineligible for Global Fund support. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Attribution of Large-Scale Climate Patterns to Seasonal Peak-Flow and Prospects for Prediction Globally

NASA Astrophysics Data System (ADS)

Lee, Donghoon; Ward, Philip; Block, Paul

2018-02-01

Flood-related fatalities and impacts on society surpass those from all other natural disasters globally. While the inclusion of large-scale climate drivers in streamflow (or high-flow) prediction has been widely studied, an explicit link to global-scale long-lead prediction is lacking, which can lead to an improved understanding of potential flood propensity. Here we attribute seasonal peak-flow to large-scale climate patterns, including the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO), using streamflow station observations and simulations from PCR-GLOBWB, a global-scale hydrologic model. Statistically significantly correlated climate patterns and streamflow autocorrelation are subsequently applied as predictors to build a global-scale season-ahead prediction model, with prediction performance evaluated by the mean squared error skill score (MSESS) and the categorical Gerrity skill score (GSS). Globally, fair-to-good prediction skill (20% ≤ MSESS and 0.2 ≤ GSS) is evident for a number of locations (28% of stations and 29% of land area), most notably in data-poor regions (e.g., West and Central Africa). The persistence of such relevant climate patterns can improve understanding of the propensity for floods at the seasonal scale. The prediction approach developed here lays the groundwork for further improving local-scale seasonal peak-flow prediction by identifying relevant global-scale climate patterns. This is especially attractive for regions with limited observations and or little capacity to develop flood early warning systems.

Developing a global crop model for maize, wheat, and soybean production

NASA Astrophysics Data System (ADS)

Deryng, D.; Ramankutty, N.; Sacks, W. J.

2008-12-01

Recently, the world food supply has faced a crisis due to increasing food prices driven by rising food demand, increasing fuel prices, poor harvests due to climate factors, and the use of crops such as maize and soybean to produce biofuel. In order to assess the future of global food availability, there is a need for understanding the factors underlying food production. Farmer management practices along with climatic conditions are the main elements directly influencing crop yield. As a consequence, estimations of future world food production require the use of a global crop model that simulates reasonably the effect of both climate and management practices on yield. Only a few global crop models have been developed to date, and currently none of them represent management factors adequately, principally due to the lack of spatially explicit datasets at the global scale. In this study, we present a global crop model designed for maize, wheat, and soybean production that incorporates planting and harvest decisions, along with irrigation options based on newly available data. The crop model is built on a simple water-balance algorithm based on the Penman- Monteith equation combined with a light use efficiency approach that calculates biomass production under non-nutrient-limiting conditions. We used a world crop calendar dataset to develop statistical relationships between climate variables and planting dates for different regions of the world. Development stages are defined based on total growing degree days required to reach the beginning of each phase. Irrigation options are considered in regions where water stress occurs and irrigation infrastructures exist. We use a global dataset on irrigated areas for each crop type. The quantity of water applied is then calculated in order to avoid water stress but with an upper threshold derived from total irrigation withdrawal quantity estimated by the global water use model WaterGAP 2. Our analysis will present the model sensitivity to different scenarios of management practices, e.g. planting date and water supply, under non-nutrient limited conditions. With this study, we hope to clarify the importance of planting date and irrigation versus climate for crop yield.

Spatial modeling of agricultural land use change at global scale

NASA Astrophysics Data System (ADS)

Meiyappan, P.; Dalton, M.; O'Neill, B. C.; Jain, A. K.

2014-11-01

Long-term modeling of agricultural land use is central in global scale assessments of climate change, food security, biodiversity, and climate adaptation and mitigation policies. We present a global-scale dynamic land use allocation model and show that it can reproduce the broad spatial features of the past 100 years of evolution of cropland and pastureland patterns. The modeling approach integrates economic theory, observed land use history, and data on both socioeconomic and biophysical determinants of land use change, and estimates relationships using long-term historical data, thereby making it suitable for long-term projections. The underlying economic motivation is maximization of expected profits by hypothesized landowners within each grid cell. The model predicts fractional land use for cropland and pastureland within each grid cell based on socioeconomic and biophysical driving factors that change with time. The model explicitly incorporates the following key features: (1) land use competition, (2) spatial heterogeneity in the nature of driving factors across geographic regions, (3) spatial heterogeneity in the relative importance of driving factors and previous land use patterns in determining land use allocation, and (4) spatial and temporal autocorrelation in land use patterns. We show that land use allocation approaches based solely on previous land use history (but disregarding the impact of driving factors), or those accounting for both land use history and driving factors by mechanistically fitting models for the spatial processes of land use change do not reproduce well long-term historical land use patterns. With an example application to the terrestrial carbon cycle, we show that such inaccuracies in land use allocation can translate into significant implications for global environmental assessments. The modeling approach and its evaluation provide an example that can be useful to the land use, Integrated Assessment, and the Earth system modeling communities.

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.

Self-Consistent Model of Magnetospheric Ring Current and Propagating Electromagnetic Ion Cyclotron Waves: Waves in Multi-Ion Magnetosphere

NASA Technical Reports Server (NTRS)

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

2006-01-01

The further development of a self-consistent theoretical model of interacting ring current ions and electromagnetic ion cyclotron waves (Khazanov et al., 2003) is presented In order to adequately take into account wave propagation and refraction in a multi-ion magnetosphere, we explicitly include the ray tracing equations in our previous self-consistent model and use the general form of the wave kinetic equation. This is a major new feature of the present model and, to the best of our knowledge, the ray tracing equations for the first time are explicitly employed on a global magnetospheric scale in order to self-consistently simulate the spatial, temporal, and spectral evolution of the ring current and of electromagnetic ion cyclotron waves To demonstrate the effects of EMIC wave propagation and refraction on the wave energy distribution and evolution, we simulate the May 1998 storm. The main findings of our simulation can be summarized as follows. First, owing to the density gradient at the plasmapause, the net wave refraction is suppressed, and He+-mode grows preferably at the plasmapause. This result is in total agreement with previous ray tracing studies and is very clearly found in presented B field spectrograms. Second, comparison of global wave distributions with the results from another ring current model (Kozyra et al., 1997) reveals that this new model provides more intense and more highly plasmapause-organized wave distributions during the May 1998 storm period Finally, it is found that He(+)-mode energy distributions are not Gaussian distributions and most important that wave energy can occupy not only the region of generation, i.e., the region of small wave normal angles, but all wave normal angles, including those to near 90 . The latter is extremely crucial for energy transfer to thermal plasmaspheric electrons by resonant Landau damping and subsequent downward heat transport and excitation of stable auroral red arcs.

Self-Consistent Model of Magnetospheric Ring Current and Propagating Electromagnetic Ion Cyclotron Waves. 1; Waves in Multi Ion Magnetosphere

NASA Technical Reports Server (NTRS)

Khazanov, G. V.; Gumayunov, K. V.; Gallagher, D. L.; Kozyra, J. U.

2006-01-01

The further development of a self-consistent theoretical model of interacting ring current ions and electromagnetic ion cyclotron waves [Khazanov et al., 2003] is presented. In order to adequately take into account the wave propagation and refraction in a multi-ion plasmasphere, we explicitly include the ray tracing equations in our previous self-consistent model and use the general form of the wave kinetic equation. This is a major new feature of the present model and, to the best of our knowledge, the ray tracing equations for the first time are explicitly employed on a global magnetospheric scale in order to self-consistently simulate spatial, temporal, and spectral evolutions of the ring current and electromagnetic ion cyclotron waves. To demonstrate the effects of EMIC wave propagation and refraction on the EMIC wave energy distributions and evolution we simulate the May 1998 storm. The main findings of our simulation can be summarized as follows. First, due to the density gradient at the plasmapause, the net wave refraction is suppressed, and He(+)-mode grows preferably at plasmapause. This result is in a total agreement with the previous ray tracing studies, and very clear observed in presented B-field spectrograms. Second, comparison the global wave distributions with the results from other ring current model [Kozyra et al., 1997] reveals that our model provides more intense and higher plasmapause organized distributions during the May, 1998 storm period. Finally, the found He(+)-mode energy distributions are not Gaussian distributions, and most important that wave energy can occupy not only the region of generation, i. e. the region of small wave normal angles, but the entire wave normal angle region and even only the region near 90 degrees. The latter is extremely crucial for energy transfer to thermal plasmaspheric electrons by resonant Landau damping, and subsequent downward heat transport and excitation of stable auroral red arcs.

Study of the stability of a SEIRS model for computer worm propagation

NASA Astrophysics Data System (ADS)

Hernández Guillén, J. D.; Martín del Rey, A.; Hernández Encinas, L.

2017-08-01

Nowadays, malware is the most important threat to information security. In this sense, several mathematical models to simulate malware spreading have appeared. They are compartmental models where the population of devices is classified into different compartments: susceptible, exposed, infectious, recovered, etc. The main goal of this work is to propose an improved SEIRS (Susceptible-Exposed-Infectious-Recovered-Susceptible) mathematical model to simulate computer worm propagation. It is a continuous model whose dynamic is ruled by means of a system of ordinary differential equations. It considers more realistic parameters related to the propagation; in fact, a modified incidence rate has been used. Moreover, the equilibrium points are computed and their local and global stability analyses are studied. From the explicit expression of the basic reproductive number, efficient control measures are also obtained.

Developing a Toolkit for Model Evaluation Using Speleothem Isotope Data

NASA Astrophysics Data System (ADS)

Comas-Bru, L.; Deininger, M.; Harrison, S.

2017-12-01

Speleothems can provide high-resolution records of changes in both climate and atmospheric composition. These records have the potential to be used to document regional changes in mean climate and climate variability on annual to centennial timescales. They can also be used to refine our understanding of regional changes in climate forcings, such as dust and volcanic aerosols, through time. Many climate models now explicitly include isotopic tracers, and thus the isotopic records from speleothems can be used for model evaluation. Previous attempts to compile speleothem data have not provided a globally-comprehensive synthesis, nor have they provided assessments of measurement, chronological or interpretation uncertainties. SISAL (Speleothem Isotopes Synthesis and Analysis) is a new community-based working groupsponsored by Past Global Changes (PAGES) to synthesise the 500+speleothem isotopic records available globallyand develop a public-accessdatabase, that can be used both to explore past climate changes and in model evaluation. This presentation will showcase preliminary syntheses for the Last Glacial Maximum (21 ka), the mid-Holocene (6 ka) and the Last Millennium (850-1850 CE).

Relaxation of the composite Higgs little hierarchy

NASA Astrophysics Data System (ADS)

Batell, Brian; Fedderke, Michael A.; Wang, Lian-Tao

2017-12-01

We describe a composite Higgs scenario in which a cosmological relaxation mechanism naturally gives rise to a hierarchy between the weak scale and the scale of spontaneous global symmetry breaking. This is achieved through the scanning of sources of explicit global symmetry breaking by a relaxion field during an exponentially long period of inflation in the early universe. We explore this mechanism in detail in a specific composite Higgs scenario with QCD-like dynamics, based on an ultraviolet SU( N )TC `technicolor' confining gauge theory with three Dirac technifermion flavors. We find that we can successfully generate a hierarchy of scales ξ≡〈 h〉2/ F π 2 ≳ 1.2 × 10- 4 (i.e., compositeness scales F π ˜ 20 TeV) without tuning. This evades all current electroweak precision bounds on our (custodial violating) model. While directly observing the heavy composite states in this model will be challenging, a future electroweak precision measurement program can probe most of the natural parameter space for the model. We also highlight signatures of more general composite Higgs models in the cosmological relaxation framework, including some implications for flavor and dark matter.

Modeling and Assimilating Ocean Color Radiances

NASA Technical Reports Server (NTRS)

Gregg, Watson

2012-01-01

Radiances are the source of information from ocean color sensors to produce estimates of biological and geochemical constituents. They potentially provide information on various other aspects of global biological and chemical systems, and there is considerable work involved in deriving new information from these signals. Each derived product, however, contains errors that are derived from the application of the radiances, above and beyond the radiance errors. A global biogeochemical model with an explicit spectral radiative transfer model is used to investigate the potential of assimilating radiances. The results indicate gaps in our understanding of radiative processes in the oceans and their relationships with biogeochemical variables. Most important, detritus optical properties are not well characterized and produce important effects of the simulated radiances. Specifically, there does not appear to be a relationship between detrital biomass and its optical properties, as there is for chlorophyll. Approximations are necessary to get beyond this problem. In this reprt we will discuss the challenges in modeling and assimilation water-leaving radiances and the prospects for improving our understanding of biogeochemical process by utilizing these signals.

An open and extensible framework for spatially explicit land use change modelling in R: the lulccR package (0.1.0)

NASA Astrophysics Data System (ADS)

Moulds, S.; Buytaert, W.; Mijic, A.

2015-04-01

Land use change has important consequences for biodiversity and the sustainability of ecosystem services, as well as for global environmental change. Spatially explicit land use change models improve our understanding of the processes driving change and make predictions about the quantity and location of future and past change. Here we present the lulccR package, an object-oriented framework for land use change modelling written in the R programming language. The contribution of the work is to resolve the following limitations associated with the current land use change modelling paradigm: (1) the source code for model implementations is frequently unavailable, severely compromising the reproducibility of scientific results and making it impossible for members of the community to improve or adapt models for their own purposes; (2) ensemble experiments to capture model structural uncertainty are difficult because of fundamental differences between implementations of different models; (3) different aspects of the modelling procedure must be performed in different environments because existing applications usually only perform the spatial allocation of change. The package includes a stochastic ordered allocation procedure as well as an implementation of the widely used CLUE-S algorithm. We demonstrate its functionality by simulating land use change at the Plum Island Ecosystems site, using a dataset included with the package. It is envisaged that lulccR will enable future model development and comparison within an open environment.

An explicit closed-form analytical solution for European options under the CGMY model

NASA Astrophysics Data System (ADS)

Chen, Wenting; Du, Meiyu; Xu, Xiang

2017-01-01

In this paper, we consider the analytical pricing of European path-independent options under the CGMY model, which is a particular type of pure jump Le´vy process, and agrees well with many observed properties of the real market data by allowing the diffusions and jumps to have both finite and infinite activity and variation. It is shown that, under this model, the option price is governed by a fractional partial differential equation (FPDE) with both the left-side and right-side spatial-fractional derivatives. In comparison to derivatives of integer order, fractional derivatives at a point not only involve properties of the function at that particular point, but also the information of the function in a certain subset of the entire domain of definition. This ;globalness; of the fractional derivatives has added an additional degree of difficulty when either analytical methods or numerical solutions are attempted. Albeit difficult, we still have managed to derive an explicit closed-form analytical solution for European options under the CGMY model. Based on our solution, the asymptotic behaviors of the option price and the put-call parity under the CGMY model are further discussed. Practically, a reliable numerical evaluation technique for the current formula is proposed. With the numerical results, some analyses of impacts of four key parameters of the CGMY model on European option prices are also provided.

The UNESCO Global Network of National Geoparks

NASA Astrophysics Data System (ADS)

Mc Keever1, P.; Zouros, N.; Patzak, M.; Missotten, R.

2009-12-01

The UNESCO Global Network of National Geoparks was founded in 2004, following the model successfully established by the European Geoparks Network in 2000. It now comprises 63 members in 19 nations across the world. A Global Geopark is an area with geological heritage of international value but where that heritage is being used for the sustainable economic benefit if the local inhabitants, primarily through education and tourism. Supported by IUGS and IUCN, the aim of the Global Geoparks Network is to facilitate exchange and sharing between members to assist in the protection and conservation of the geological heritage of our planet but to do so in way where local communities can take ownership of these special places and where they can get some sustainable economic benefit from them. While allowing for the sustainable economic development of geoparks, the network explicitly forbids the destruction or sale of the geological value of a geopark. This paper outlines the ethos of the Global Geoparks Network and describes the typical activities of geoparks and how the network functions. Using two examples it also illustrates how members of the Global Geoparks Network provide good examples as tools not only for holistic nature conservation but also for economic development.

Climate change risk analysis framework (CCRAF) a probabilistic tool for analyzing climate change uncertainties

NASA Astrophysics Data System (ADS)

Legget, J.; Pepper, W.; Sankovski, A.; Smith, J.; Tol, R.; Wigley, T.

2003-04-01

Potential risks of human-induced climate change are subject to a three-fold uncertainty associated with: the extent of future anthropogenic and natural GHG emissions; global and regional climatic responses to emissions; and impacts of climatic changes on economies and the biosphere. Long-term analyses are also subject to uncertainty regarding how humans will respond to actual or perceived changes, through adaptation or mitigation efforts. Explicitly addressing these uncertainties is a high priority in the scientific and policy communities Probabilistic modeling is gaining momentum as a technique to quantify uncertainties explicitly and use decision analysis techniques that take advantage of improved risk information. The Climate Change Risk Assessment Framework (CCRAF) presented here a new integrative tool that combines the probabilistic approaches developed in population, energy and economic sciences with empirical data and probabilistic results of climate and impact models. The main CCRAF objective is to assess global climate change as a risk management challenge and to provide insights regarding robust policies that address the risks, by mitigating greenhouse gas emissions and by adapting to climate change consequences. The CCRAF endogenously simulates to 2100 or beyond annual region-specific changes in population; GDP; primary (by fuel) and final energy (by type) use; a wide set of associated GHG emissions; GHG concentrations; global temperature change and sea level rise; economic, health, and biospheric impacts; costs of mitigation and adaptation measures and residual costs or benefits of climate change. Atmospheric and climate components of CCRAF are formulated based on the latest version of Wigley's and Raper's MAGICC model and impacts are simulated based on a modified version of Tol's FUND model. The CCRAF is based on series of log-linear equations with deterministic and random components and is implemented using a Monte-Carlo method with up to 5000 variants per set of fixed input parameters. The shape and coefficients of CCRAF equations are derived from regression analyses of historic data and expert assessments. There are two types of random components in CCRAF - one reflects a year-to-year fluctuations around the expected value of a given variable (e.g., standard error of the annual GDP growth) and another is fixed within each CCRAF variant and represents some essential constants within a "world" represented by that variant (e.g., the value of climate sensitivity). Both types of random components are drawn from pre-defined probability distributions functions developed based on historic data or expert assessments. Preliminary CCRAF results emphasize the relative importance of uncertainties associated with the conversion of GHG and particulate emissions into radiative forcing and quantifying climate change effects at the regional level. A separates analysis involves an "adaptive decision-making", which optimizes the expected future policy effects given the estimated probabilistic uncertainties. As uncertainty for some variables evolve over the time steps, the decisions also adapt. This modeling approach is feasible only with explicit modeling of uncertainties.

An ensemble-based dynamic Bayesian averaging approach for discharge simulations using multiple global precipitation products and hydrological models

NASA Astrophysics Data System (ADS)

Qi, Wei; Liu, Junguo; Yang, Hong; Sweetapple, Chris

2018-03-01

Global precipitation products are very important datasets in flow simulations, especially in poorly gauged regions. Uncertainties resulting from precipitation products, hydrological models and their combinations vary with time and data magnitude, and undermine their application to flow simulations. However, previous studies have not quantified these uncertainties individually and explicitly. This study developed an ensemble-based dynamic Bayesian averaging approach (e-Bay) for deterministic discharge simulations using multiple global precipitation products and hydrological models. In this approach, the joint probability of precipitation products and hydrological models being correct is quantified based on uncertainties in maximum and mean estimation, posterior probability is quantified as functions of the magnitude and timing of discharges, and the law of total probability is implemented to calculate expected discharges. Six global fine-resolution precipitation products and two hydrological models of different complexities are included in an illustrative application. e-Bay can effectively quantify uncertainties and therefore generate better deterministic discharges than traditional approaches (weighted average methods with equal and varying weights and maximum likelihood approach). The mean Nash-Sutcliffe Efficiency values of e-Bay are up to 0.97 and 0.85 in training and validation periods respectively, which are at least 0.06 and 0.13 higher than traditional approaches. In addition, with increased training data, assessment criteria values of e-Bay show smaller fluctuations than traditional approaches and its performance becomes outstanding. The proposed e-Bay approach bridges the gap between global precipitation products and their pragmatic applications to discharge simulations, and is beneficial to water resources management in ungauged or poorly gauged regions across the world.

Potential Increasing Dominance of Heterotrophy in the Global Ocean

NASA Astrophysics Data System (ADS)

Kvale, K.; Meissner, K. J.; Keller, D. P.

2016-02-01

Autotrophs are largely limited by resources in the modern ocean. However, standard metabolic theory suggests continued ocean warming could globally benefit heterotrophs, thereby reducing autotrophic nutrient limitation. The paleo record as well as modern observations offer evidence this has happened in the past and could happen again. Increasing dominance of heterotrophs would result in strong nutrient recycling in the upper ocean and high rates of net primary production (NPP), yet low carbon export to the deep ocean and sediments. We describe the transition towards such a state in the early 22nd century as a response to business-as-usual Representative Concentration Pathway forcing (RCP8.5) in an intermediate complexity Earth system model in three configurations: with and without an explicit calcifier phytoplankton class and calcite ballast model. In all models nutrient regeneration in the near surface becomes an increasingly important driver of primary production. The near-linear relationship between changes in NPP and global sea surface temperature (SST) found over the 21st century becomes exponential above a 2-4 °C global mean SST change. This transition to a more heterotrophic ocean agrees roughly with metabolic theory. Inclusion of small phytoplankton and calcifiers increase the model NPP:SST sensitivity because of their relatively higher nutrient affinity than general phytoplankton. Accounting for organic carbon "protected" from remineralization by carbonate ballast mitigates the exponential increase in NPP and provides an increasingly important pathway for deep carbon export with higher SST changes, despite simultaneous increasing carbonate dissolution rates due to ocean acidification.

Constraints on global oceanic emissions of N2O from observations and models

NASA Astrophysics Data System (ADS)

Buitenhuis, Erik T.; Suntharalingam, Parvadha; Le Quéré, Corinne

2018-04-01

We estimate the global ocean N2O flux to the atmosphere and its confidence interval using a statistical method based on model perturbation simulations and their fit to a database of ΔpN2O (n = 6136). We evaluate two submodels of N2O production. The first submodel splits N2O production into oxic and hypoxic pathways following previous publications. The second submodel explicitly represents the redox transformations of N that lead to N2O production (nitrification and hypoxic denitrification) and N2O consumption (suboxic denitrification), and is presented here for the first time. We perturb both submodels by modifying the key parameters of the N2O cycling pathways (nitrification rates; NH4+ uptake; N2O yields under oxic, hypoxic and suboxic conditions) and determine a set of optimal model parameters by minimisation of a cost function against four databases of N cycle observations. Our estimate of the global oceanic N2O flux resulting from this cost function minimisation derived from observed and model ΔpN2O concentrations is 2.4 ± 0.8 and 2.5 ± 0.8 Tg N yr-1 for the two N2O submodels. These estimates suggest that the currently available observational data of surface ΔpN2O constrain the global N2O flux to a narrower range relative to the large range of results presented in the latest IPCC report.

Combined simulation of carbon and water isotopes in a global ocean model

NASA Astrophysics Data System (ADS)

Paul, André; Krandick, Annegret; Gebbie, Jake; Marchal, Olivier; Dutkiewicz, Stephanie; Losch, Martin; Kurahashi-Nakamura, Takasumi; Tharammal, Thejna

2013-04-01

Carbon and water isotopes are included as passive tracers in the MIT general circulation model (MITgcm). The implementation of the carbon isotopes is based on the existing MITgcm carbon cycle component and involves the fractionation processes during photosynthesis and air-sea gas exchange. Special care is given to the use of a real freshwater flux boundary condition in conjunction with the nonlinear free surface of the ocean model. The isotopic content of precipitation and water vapor is obtained from an atmospheric GCM (the NCAR CAM3) and mapped onto the MITgcm grid system, but the kinetic fractionation during evaporation is treated explicitly in the ocean model. In a number of simulations, we test the sensitivity of the carbon isotope distributions to the formulation of fractionation during photosynthesis and compare the results to modern observations of δ13C and Δ14C from GEOSECS, WOCE and CLIVAR. Similarly, we compare the resulting distribution of oxygen isotopes to modern δ18O data from the NASA GISS Global Seawater Oxygen-18 Database. The overall agreement is good, but there are discrepancies in the carbon isotope composition of the surface water and the oxygen isotope composition of the intermediate and deep waters. The combined simulation of carbon and water isotopes in a global ocean model will provide a framework for studying present and past states of ocean circulation such as postulated from deep-sea sediment records.

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

Spatially explicit simulation of hydrologically controlled carbon and nitrogen cycles and associated feedback mechanisms in a boreal ecosystem in Eastern Canada.

NASA Astrophysics Data System (ADS)

Govind, A.; Chen, J. M.; Margolis, H.

2007-12-01

Current estimates of terrestrial carbon overlook the effects of topographically-driven lateral flow of soil water. We hypothesize that this component, which occur at a landscape or watershed scale have significant influences on the spatial distribution of carbon, due to its large contribution to the local water balance. To this end, we further developed a spatially explicit ecohydrological model, BEPS-TerrainLab V2.0. We simulated the coupled hydrological and carbon cycle processes in a black spruce-moss ecosystem in central Quebec, Canada. The carbon stocks were initialized using a long term carbon cycling model, InTEC, under a climate change and disturbance scenario, the accuracy of which was determined with inventory plot measurements. Further, we simulated and validated several ecosystem indicators such as ET, GPP, NEP, water table, snow depth and soil temperature, using the measurements for two years, 2004 and 2005. After gaining confidence in the model's ability to simulate ecohydrological processes, we tested the influence of lateral water flow on the carbon cycle. We made three hydrological modeling scenarios 1) Explicit, were realistic lateral water routing was considered 2) Implicit where calculations were based on a bucket modeling approach 3) NoFlow, where the lateral water flow was turned off in the model. The results showed that pronounced anomalies exist among the scenarios for the simulated GPP, ET and NEP. In general, Implicit calculation overestimated GPP and underestimated NEP, as opposed to Explicit simulation. NoFlow underestimated GPP and overestimated NEP. The key processes controlling GPP were manifested through stomatal conductance which reduces under conditions of rapid soil saturation ( NoFlow ) or increases in the Implicit case, and, nitrogen availability which affects Vcmax, the maximum carboxylation rate. However, for NEP, the anomalies were attributed to differences in soil carbon pool decomposition, which determine the heterotrophic respiration and the resultant nitrogen mineralization which affects GPP and several other feedback mechanisms. These results suggest that lateral water flow does play a significant role in the terrestrial carbon distribution. Therefore, regional or global scale terrestrial carbon estimates could have significant errors if proper hydrological constrains are not considered for modeling ecological processes due to large topographic variations on the Earth's surface. For more info please visit: http://ajit.govind.googlepages.com/agu2007

Methane emissions from floodplains in the Amazon Basin: challenges in developing a process-based model for global applications

NASA Astrophysics Data System (ADS)

Ringeval, B.; Houweling, S.; van Bodegom, P. M.; Spahni, R.; van Beek, R.; Joos, F.; Röckmann, T.

2014-03-01

Tropical wetlands are estimated to represent about 50% of the natural wetland methane (CH4) emissions and explain a large fraction of the observed CH4 variability on timescales ranging from glacial-interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This publication documents a first step in the development of a process-based model of CH4 emissions from tropical floodplains for global applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was slightly modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially explicit hydrology model PCR-GLOBWB. We introduced new plant functional types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote-sensing data sets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX reproduces the average magnitude of observed net CH4 flux densities for the Amazon Basin. However, the model does not reproduce the variability between sites or between years within a site. Unfortunately, site information is too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. Sensitivity analyses gave insights into the main drivers of floodplain CH4 emission and their associated uncertainties. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr-1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin, modulated emissions by about 20%. Correcting the LPX-simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the full dynamics in CH4 emissions but we proposed solutions to this issue. The interannual variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is accounted for, but still remains lower than in most of the WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results helped identify and prioritize directions towards more accurate estimates of tropical CH4 emissions, and they stress the need for more research to constrain floodplain CH4 emissions and their temporal variability, even before including other fundamental mechanisms such as floating macrophytes or lateral water fluxes.

Improved limits on dark matter annihilation in the Sun with the 79-string IceCube detector and implications for supersymmetry

NASA Astrophysics Data System (ADS)

Aartsen, M. G.; Abraham, K.; Ackermann, M.; Adams, J.; Aguilar, J. A.; Ahlers, M.; Ahrens, M.; Altmann, D.; Anderson, T.; Ansseau, I.; Anton, G.; Archinger, M.; Arguelles, C.; Arlen, T. C.; Auffenberg, J.; Bai, X.; Barwick, S. W.; Baum, V.; Bay, R.; Beatty, J. J.; Becker Tjus, J.; Becker, K.-H.; Beiser, E.; BenZvi, S.; Berghaus, P.; Berley, D.; Bernardini, E.; Bernhard, A.; Besson, D. Z.; Binder, G.; Bindig, D.; Bissok, M.; Blaufuss, E.; Blumenthal, J.; Boersma, D. J.; Bohm, C.; Börner, M.; Bos, F.; Bose, D.; Böser, S.; Botner, O.; Braun, J.; Brayeur, L.; Bretz, H.-P.; Buzinsky, N.; Casey, J.; Casier, M.; Cheung, E.; Chirkin, D.; Christov, A.; Clark, K.; Classen, L.; Coenders, S.; Collin, G. H.; Conrad, J. M.; Cowen, D. F.; Cruz Silva, A. H.; Danninger, M.; Daughhetee, J.; Davis, J. C.; Day, M.; de André, J. P. A. M.; De Clercq, C.; del Pino Rosendo, E.; Dembinski, H.; De Ridder, S.; Desiati, P.; de Vries, K. D.; de Wasseige, G.; de With, M.; DeYoung, T.; Díaz-Vélez, J. C.; di Lorenzo, V.; Dumm, J. P.; Dunkman, M.; Eberhardt, B.; Edsjö, J.; Ehrhardt, T.; Eichmann, B.; Euler, S.; Evenson, P. A.; Fahey, S.; Fazely, A. R.; Feintzeig, J.; Felde, J.; Filimonov, K.; Finley, C.; Flis, S.; Fösig, C.-C.; Fuchs, T.; Gaisser, T. K.; Gaior, R.; Gallagher, J.; Gerhardt, L.; Ghorbani, K.; Gier, D.; Gladstone, L.; Glagla, M.; Glüsenkamp, T.; Goldschmidt, A.; Golup, G.; Gonzalez, J. G.; Góra, D.; Grant, D.; Griffith, Z.; Groß, A.; Ha, C.; Haack, C.; Haj Ismail, A.; Hallgren, A.; Halzen, F.; Hansen, E.; Hansmann, B.; Hanson, K.; Hebecker, D.; Heereman, D.; Helbing, K.; Hellauer, R.; Hickford, S.; Hignight, J.; Hill, G. C.; Hoffman, K. D.; Hoffmann, R.; Holzapfel, K.; Homeier, A.; Hoshina, K.; Huang, F.; Huber, M.; Huelsnitz, W.; Hulth, P. O.; Hultqvist, K.; In, S.; Ishihara, A.; Jacobi, E.; Japaridze, G. S.; Jeong, M.; Jero, K.; Jones, B. J. P.; Jurkovic, M.; Kappes, A.; Karg, T.; Karle, A.; Katz, U.; Kauer, M.; Keivani, A.; Kelley, J. L.; Kemp, J.; Kheirandish, A.; Kiryluk, J.; Klein, S. R.; Kohnen, G.; Koirala, R.; Kolanoski, H.; Konietz, R.; Köpke, L.; Kopper, C.; Kopper, S.; Koskinen, D. J.; Kowalski, M.; Krings, K.; Kroll, G.; Kroll, M.; Krückl, G.; Kunnen, J.; Kurahashi, N.; Kuwabara, T.; Labare, M.; Lanfranchi, J. L.; Larson, M. J.; Lesiak-Bzdak, M.; Leuermann, M.; Leuner, J.; Lu, L.; Lünemann, J.; Madsen, J.; Maggi, G.; Mahn, K. B. M.; Mandelartz, M.; Maruyama, R.; Mase, K.; Matis, H. S.; Maunu, R.; McNally, F.; Meagher, K.; Medici, M.; Meier, M.; Meli, A.; Menne, T.; Merino, G.; Meures, T.; Miarecki, S.; Middell, E.; Mohrmann, L.; Montaruli, T.; Morse, R.; Nahnhauer, R.; Naumann, U.; Neer, G.; Niederhausen, H.; Nowicki, S. C.; Nygren, D. R.; Obertacke Pollmann, A.; Olivas, A.; Omairat, A.; O'Murchadha, A.; Palczewski, T.; Pandya, H.; Pankova, D. V.; Paul, L.; Pepper, J. A.; Pérez de los Heros, C.; Pfendner, C.; Pieloth, D.; Pinat, E.; Posselt, J.; Price, P. B.; Przybylski, G. T.; Quinnan, M.; Raab, C.; Rädel, L.; Rameez, M.; Rawlins, K.; Reimann, R.; Relich, M.; Resconi, E.; Rhode, W.; Richman, M.; Richter, S.; Riedel, B.; Robertson, S.; Rongen, M.; Rott, C.; Ruhe, T.; Ryckbosch, D.; Sabbatini, L.; Sander, H.-G.; Sandrock, A.; Sandroos, J.; Sarkar, S.; Savage, C.; Schatto, K.; Schimp, M.; Schlunder, P.; Schmidt, T.; Schoenen, S.; Schöneberg, S.; Schönwald, A.; Schulte, L.; Schumacher, L.; Scott, P.; Seckel, D.; Seunarine, S.; Silverwood, H.; Soldin, D.; Song, M.; Spiczak, G. M.; Spiering, C.; Stahlberg, M.; Stamatikos, M.; Stanev, T.; Stasik, A.; Steuer, A.; Stezelberger, T.; Stokstad, R. G.; Stößl, A.; Ström, R.; Strotjohann, N. L.; Sullivan, G. W.; Sutherland, M.; Taavola, H.; Taboada, I.; Tatar, J.; Ter-Antonyan, S.; Terliuk, A.; Te{š}ić, G.; Tilav, S.; Toale, P. A.; Tobin, M. N.; Toscano, S.; Tosi, D.; Tselengidou, M.; Turcati, A.; Unger, E.; Usner, M.; Vallecorsa, S.; Vandenbroucke, J.; van Eijndhoven, N.; Vanheule, S.; van Santen, J.; Veenkamp, J.; Vehring, M.; Voge, M.; Vraeghe, M.; Walck, C.; Wallace, A.; Wallraff, M.; Wandkowsky, N.; Weaver, Ch.; Wendt, C.; Westerhoff, S.; Whelan, B. J.; Wiebe, K.; Wiebusch, C. H.; Wille, L.; Williams, D. R.; Wills, L.; Wissing, H.; Wolf, M.; Wood, T. R.; Woschnagg, K.; Xu, D. L.; Xu, X. W.; Xu, Y.; Yanez, J. P.; Yodh, G.; Yoshida, S.; Zoll, M.

2016-04-01

We present an improved event-level likelihood formalism for including neutrino telescope data in global fits to new physics. We derive limits on spin-dependent dark matter-proton scattering by employing the new formalism in a re-analysis of data from the 79-string IceCube search for dark matter annihilation in the Sun, including explicit energy information for each event. The new analysis excludes a number of models in the weak-scale minimal supersymmetric standard model (MSSM) for the first time. This work is accompanied by the public release of the 79-string IceCube data, as well as an associated computer code for applying the new likelihood to arbitrary dark matter models.

The dynamics of architectural complexity on coral reefs under climate change.

PubMed

Bozec, Yves-Marie; Alvarez-Filip, Lorenzo; Mumby, Peter J

2015-01-01

One striking feature of coral reef ecosystems is the complex benthic architecture which supports diverse and abundant fauna, particularly of reef fish. Reef-building corals are in decline worldwide, with a corresponding loss of live coral cover resulting in a loss of architectural complexity. Understanding the dynamics of the reef architecture is therefore important to envision the ability of corals to maintain functional habitats in an era of climate change. Here, we develop a mechanistic model of reef topographical complexity for contemporary Caribbean reefs. The model describes the dynamics of corals and other benthic taxa under climate-driven disturbances (hurricanes and coral bleaching). Corals have a simplified shape with explicit diameter and height, allowing species-specific calculation of their colony surface and volume. Growth and the mechanical (hurricanes) and biological erosion (parrotfish) of carbonate skeletons are important in driving the pace of extension/reduction in the upper reef surface, the net outcome being quantified by a simple surface roughness index (reef rugosity). The model accurately simulated the decadal changes of coral cover observed in Cozumel (Mexico) between 1984 and 2008, and provided a realistic hindcast of coral colony-scale (1-10 m) changing rugosity over the same period. We then projected future changes of Caribbean reef rugosity in response to global warming. Under severe and frequent thermal stress, the model predicted a dramatic loss of rugosity over the next two or three decades. Critically, reefs with managed parrotfish populations were able to delay the general loss of architectural complexity, as the benefits of grazing in maintaining living coral outweighed the bioerosion of dead coral skeletons. Overall, this model provides the first explicit projections of reef rugosity in a warming climate, and highlights the need of combining local (protecting and restoring high grazing) to global (mitigation of greenhouse gas emissions) interventions for the persistence of functional reef habitats. © 2014 John Wiley & Sons Ltd.

Solvable Hydrodynamics of Quantum Integrable Systems

NASA Astrophysics Data System (ADS)

Bulchandani, Vir B.; Vasseur, Romain; Karrasch, Christoph; Moore, Joel E.

2017-12-01

The conventional theory of hydrodynamics describes the evolution in time of chaotic many-particle systems from local to global equilibrium. In a quantum integrable system, local equilibrium is characterized by a local generalized Gibbs ensemble or equivalently a local distribution of pseudomomenta. We study time evolution from local equilibria in such models by solving a certain kinetic equation, the "Bethe-Boltzmann" equation satisfied by the local pseudomomentum density. Explicit comparison with density matrix renormalization group time evolution of a thermal expansion in the XXZ model shows that hydrodynamical predictions from smooth initial conditions can be remarkably accurate, even for small system sizes. Solutions are also obtained in the Lieb-Liniger model for free expansion into vacuum and collisions between clouds of particles, which model experiments on ultracold one-dimensional Bose gases.

Global scale modeling of riverine sediment loads: tropical rivers in a global context

NASA Astrophysics Data System (ADS)

Cohen, Sagy; Syvitski, James; Kettner, Albert

2015-04-01

A global scale riverine sediment flux model (termed WBMsed) is introduced. The model predicts spatially and temporally explicit water, suspended sediment and nutrients flux in relatively high resolutions (6 arc-min and daily). Modeled riverine suspended sediment flux through global catchments is used in conjunction with observational data for 35 tropical basins to highlight key basin scaling relationships. A 50 year, daily model simulation illuminates how precipitation, relief, lithology and drainage basin area affect sediment load, yield and concentration. Tropical river systems, wherein much of a drainage basin experiences tropical climate are strongly influenced by the annual and inter-annual variations of the Inter-tropical Convergence Zone (ITCZ) and its derivative monsoonal winds, have comparatively low inter-annual variation in sediment yield. Rivers draining rainforests and those subjected to tropical monsoons typically demonstrate high runoff, but with notable exceptions. High rainfall intensities from burst weather events are common in the tropics. The release of rain-forming aerosols also appears to uniquely increase regional rainfall, but its geomorphic manifestation is hard to detect. Compared to other more temperate river systems, climate-driven tropical rivers do not appear to transport a disproportionate amount of particulate load to the world's oceans, and their warmer, less viscous waters are less competent. Multiple-year hydrographs reveal that seasonality is a dominant feature of most tropical rivers, but the rivers of Papua New Guinea are somewhat unique being less seasonally modulated. Local sediment yield within the Amazon is highest near the Andes, but decreases towards the ocean as the river's discharge is diluted by water influxes from sediment-deprived rainforest tributaries

Estimation of Fractional Plant Lifeform Cover Using Landsat and Airborne LiDAR/hyperspectral Data

NASA Astrophysics Data System (ADS)

Parra, A. S.; Xu, Q.; Dilts, T.; Weisberg, P.; Greenberg, J. A.

2017-12-01

Land-cover change has generally been understood as the result of local, landscape or regional-scale processes with most studies focusing on case-study landscapes or smaller regions. However, as we observe similar types of land-cover change occurring across different biomes worldwide, it becomes clear that global-scale processes such as climate change and CO2 fertilization, in interaction with local influences, are underlying drivers in land-cover change patterns. Prior studies on global land-cover change may not have had a suitable spatial, temporal and thematic resolution for allowing the identification of such patterns. Furthermore, the lack of globally consistent spatial data products also constitutes a limiting factor in evaluating both proximate and ultimate causes of land-cover change. In this study, we derived a global model for broadleaf tree, needleleaf tree, shrub, herbaceous, and "other" fractional cover using Landsat imagery. Combined LiDAR/hyperspectral data sets were used for calibration and validation of the Landsat-derived products. Spatially explicit uncertainties were also created as part of the data products. Our results highlight the potential for large-scale studies that model local and global influences on land-cover transition types and rates at fine thematic, spatial, and temporal resolutions. These spatial data products are relevant for identifying patterns in land-cover change due to underlying global-scale processes and can provide valuable insights into climatic and land-use factors determining vegetation distributions.

Explicitly represented polygon wall boundary model for the explicit MPS method

NASA Astrophysics Data System (ADS)

Mitsume, Naoto; Yoshimura, Shinobu; Murotani, Kohei; Yamada, Tomonori

2015-05-01

This study presents an accurate and robust boundary model, the explicitly represented polygon (ERP) wall boundary model, to treat arbitrarily shaped wall boundaries in the explicit moving particle simulation (E-MPS) method, which is a mesh-free particle method for strong form partial differential equations. The ERP model expresses wall boundaries as polygons, which are explicitly represented without using the distance function. These are derived so that for viscous fluids, and with less computational cost, they satisfy the Neumann boundary condition for the pressure and the slip/no-slip condition on the wall surface. The proposed model is verified and validated by comparing computed results with the theoretical solution, results obtained by other models, and experimental results. Two simulations with complex boundary movements are conducted to demonstrate the applicability of the E-MPS method to the ERP model.

The global abundance and size distribution of lakes, ponds, and impoundments

USGS Publications Warehouse

Downing, J.A.; Prairie, Y.T.; Cole, J.J.; Duarte, C.M.; Tranvik, L.J.; Striegl, Robert G.; McDowell, W.H.; Kortelainen, Pirkko; Caraco, N.F.; Melack, J.M.; Middelburg, J.J.

2006-01-01

One of the major impediments to the integration of lentic ecosystems into global environmental analyses has been fragmentary data on the extent and size distribution of lakes, ponds, and impoundments. We use new data sources, enhanced spatial resolution, and new analytical approaches to provide new estimates of the global abundance of surface-water bodies. A global model based on the Pareto distribution shows that the global extent of natural lakes is twice as large as previously known (304 million lakes; 4.2 million km 2 in area) and is dominated in area by millions of water bodies smaller than 1 km2. Similar analyses of impoundments based on inventories of large, engineered dams show that impounded waters cover approximately 0.26 million km2. However, construction of low-tech farm impoundments is estimated to be between 0.1 % and 6% of farm area worldwide, dependent upon precipitation, and represents >77,000 km 2 globally, at present. Overall, about 4.6 million km2 of the earth's continental "land" surface (>3%) is covered by water. These analyses underscore the importance of explicitly considering lakes, ponds, and impoundments, especially small ones, in global analyses of rates and processes. ?? 2006, by the American Society of Limnology and Oceanography, Inc.

Evaluating L2 Readers' Previewing Strategies Using Eye Tracking

ERIC Educational Resources Information Center

Prichard, Caleb; Atkins, Andrew

2016-01-01

Previewing a text is a key global reading strategy. Previewing may increase comprehension as it can activate schema, increase global awareness of the text, and enhance the use of other reading strategies. Despite its importance, an explicit focus on previewing skills has been lacking and previous research on the reading strategies of second…

Researching Absences and Silences in Higher Education: Data for Democratisation

ERIC Educational Resources Information Center

Morley, Louise

2012-01-01

Knowledge, power and democracy are being more explicitly related to higher education globally. Increasingly there are calls for cognitive justice and the development of a sociology of absences, particularly in relation to structures of inequalities and knowledge production from the Global South. The university of the future will need to be…

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.

Solvent induced conformational fluctuation of alanine dipeptide studied by using vibrational probes

NASA Astrophysics Data System (ADS)

Cai, Kaicong; Du, Fenfen; Liu, Jia; Su, Tingting

2015-02-01

The solvation effect on the three dimensional structure and the vibrational feature of alanine dipeptide (ALAD) was evaluated by applying the implicit solvents from polarizable continuum solvent model (PCM) through ab initio calculations, by using molecular dynamic (MD) simulations with explicit solvents, and by combining these two approaches. The implicit solvent induced potential energy fluctuations of ALAD in CHCl3, DMSO and H2O are revealed by means of ab initio calculations, and a global view of conformational and solvation environmental dependence of amide I frequencies is achieved. The results from MD simulations with explicit solvents show that ALAD trends to form PPII, αL, αR, and C5 in water, PPII and C5 in DMSO, and C5 in CHCl3, ordered by population, and the demonstration of the solvated structure, the solute-solvent interaction and hydrogen bonding is therefore enhanced. Representative ALAD-solvent clusters were sampled from MD trajectories and undergone ab initio calculations. The explicit solvents reveal the hydrogen bonding between ALAD and solvents, and the correlation between amide I frequencies and the Cdbnd O bond length is built. The implicit solvents applied to the ALAD-solvent clusters further compensate the solvation effect from the bulk, and thus enlarge the degree of structural distortion and the amide I frequency red shift. The combination of explicit solvent in the first hydration shell and implicit solvent in the bulk is helpful for our understanding about the conformational fluctuation of solvated polypeptides through vibrational probes.

Application and Evaluation of an Explicit Prognostic Cloud-Cover Scheme in GRAPES Global Forecast System

NASA Astrophysics Data System (ADS)

Ma, Zhanshan; Liu, Qijun; Zhao, Chuanfeng; Shen, Xueshun; Wang, Yuan; Jiang, Jonathan H.; Li, Zhe; Yung, Yuk

2018-03-01

An explicit prognostic cloud-cover scheme (PROGCS) is implemented into the Global/Regional Assimilation and Prediction System (GRAPES) for global middle-range numerical weather predication system (GRAPES_GFS) to improve the model performance in simulating cloud cover and radiation. Unlike the previous diagnostic cloud-cover scheme (DIAGCS), PROGCS considers the formation and dissipation of cloud cover by physically connecting it to the cumulus convection and large-scale stratiform condensation processes. Our simulation results show that clouds in mid-high latitudes arise mainly from large-scale stratiform condensation processes, while cumulus convection and large-scale condensation processes jointly determine cloud cover in low latitudes. Compared with DIAGCS, PROGCS captures more consistent vertical distributions of cloud cover with the observations from Atmospheric Radiation Measurements (ARM) program at the Southern Great Plains (SGP) site and simulates more realistic diurnal cycle of marine stratocumulus with the ERA-Interim reanalysis data. The low, high, and total cloud covers that are determined via PROGCS appear to be more realistic than those simulated via DIAGCS when both are compared with satellite retrievals though the former maintains slight negative biases. In addition, the simulations of outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) from PROGCS runs have been considerably improved as well, resulting in less biases in radiative heating rates at heights below 850 hPa and above 400 hPa of GRAPES_GFS. Our results indicate that a prognostic method of cloud-cover calculation has significant advantage over the conventional diagnostic one, and it should be adopted in both weather and climate simulation and forecast.

A collision probability analysis of the double-heterogeneity problem

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

Hebert, A.

1993-10-01

A practical collision probability model is presented for the description of geometries with many levels of heterogeneity. Regular regions of the macrogeometry are assumed to contain a stochastic mixture of spherical grains or cylindrical tubes. Simple expressions for the collision probabilities in the global geometry are obtained as a function of the collision probabilities in the macro- and microgeometries. This model was successfully implemented in the collision probability kernel of the APOLLO-1, APOLLO-2, and DRAGON lattice codes for the description of a broad range of reactor physics problems. Resonance self-shielding and depletion calculations in the microgeometries are possible because eachmore » microregion is explicitly represented.« less

Methane emissions from floodplains in the Amazon Basin: towards a process-based model for global applications

NASA Astrophysics Data System (ADS)

Ringeval, B.; Houweling, S.; van Bodegom, P. M.; Spahni, R.; van Beek, R.; Joos, F.; Röckmann, T.

2013-10-01

Tropical wetlands are estimated to represent about 50% of the natural wetland emissions and explain a large fraction of the observed CH4 variability on time scales ranging from glacial-interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This study documents the first regional-scale, process-based model of CH4 emissions from tropical floodplains. The LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially-explicit hydrology model PCR-GLOBWB. We introduced new Plant Functional Types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote sensing datasets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX simulated CH4 flux densities are in reasonable agreement with observations at the field scale but with a~tendency to overestimate the flux observed at specific sites. In addition, the model did not reproduce between-site variations or between-year variations within a site. Unfortunately, site informations are too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr-1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin modulated emissions by about 20%. Correcting the LPX simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the seasonality in CH4 emissions. The Inter Annual Variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is account for, but still remains lower than in most of WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results stress the need for more research to constrain floodplain CH4 emissions and their temporal variability.

Oceanic signals in rapid polar motion: results from a barotropic forward model with explicit consideration of self-attraction and loading effects

NASA Astrophysics Data System (ADS)

Schindelegger, Michael; Quinn, Katherine J.; Ponte, Rui M.

2017-04-01

Numerical modeling of non-tidal variations in ocean currents and bottom pressure has played a key role in closing the excitation budget of Earth's polar motion for a wide range of periodicities. Non-negligible discrepancies between observations and model accounts of pole position changes prevail, however, on sub-monthly time scales and call for examination of hydrodynamic effects usually omitted in general circulation models. Specifically, complete hydrodynamic cores must incorporate self-attraction and loading (SAL) feedbacks on redistributed water masses, effects that produces ocean bottom pressure perturbations of typically about 10% relative to the computed mass variations. Here, we report on a benchmark simulation with a near-global, barotropic forward model forced by wind stress, atmospheric pressure, and a properly calculated SAL term. The latter is obtained by decomposing ocean mass anomalies on a 30-minute grid into spherical harmonics at each time step and applying Love numbers to account for seafloor deformation and changed gravitational attraction. The increase in computational time at each time step is on the order of 50%. Preliminary results indicate that the explicit consideration of SAL in the forward runs increases the fidelity of modeled polar motion excitations, in particular on time scales shorter than 5 days as evident from cross spectral comparisons with geodetic excitation. Definite conclusions regarding the relevance of SAL in simulating rapid polar motion are, however, still hampered by the model's incomplete domain representation that excludes parts of the highly energetic Arctic Ocean.

Cholera in the Lake Kivu region (DRC): Integrating remote sensing and spatially explicit epidemiological modeling

NASA Astrophysics Data System (ADS)

Finger, Flavio; Knox, Allyn; Bertuzzo, Enrico; Mari, Lorenzo; Bompangue, Didier; Gatto, Marino; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

2014-07-01

Mathematical models of cholera dynamics can not only help in identifying environmental drivers and processes that influence disease transmission, but may also represent valuable tools for the prediction of the epidemiological patterns in time and space as well as for the allocation of health care resources. Cholera outbreaks have been reported in the Democratic Republic of the Congo since the 1970s. They have been ravaging the shore of Lake Kivu in the east of the country repeatedly during the last decades. Here we employ a spatially explicit, inhomogeneous Markov chain model to describe cholera incidence in eight health zones on the shore of the lake. Remotely sensed data sets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers in addition to baseline seasonality. The effect of human mobility is also modelled mechanistically. We test several models on a multiyear data set of reported cholera cases. The best fourteen models, accounting for different environmental drivers, and selected using the Akaike information criterion, are formally compared via proper cross validation. Among these, the one accounting for seasonality, El Niño Southern Oscillation, precipitation and human mobility outperforms the others in cross validation. Some drivers (such as human mobility and rainfall) are retained only by a few models, possibly indicating that the mechanisms through which they influence cholera dynamics in the area will have to be investigated further.

Environmental risk of leptospirosis infections in the Netherlands: Spatial modelling of environmental risk factors of leptospirosis in the Netherlands.

PubMed

Rood, Ente J J; Goris, Marga G A; Pijnacker, Roan; Bakker, Mirjam I; Hartskeerl, Rudy A

2017-01-01

Leptospirosis is a globally emerging zoonotic disease, associated with various climatic, biotic and abiotic factors. Mapping and quantifying geographical variations in the occurrence of leptospirosis and the surrounding environment offer innovative methods to study disease transmission and to identify associations between the disease and the environment. This study aims to investigate geographic variations in leptospirosis incidence in the Netherlands and to identify associations with environmental factors driving the emergence of the disease. Individual case data derived over the period 1995-2012 in the Netherlands were geocoded and aggregated by municipality. Environmental covariate data were extracted for each municipality and stored in a spatial database. Spatial clusters were identified using kernel density estimations and quantified using local autocorrelation statistics. Associations between the incidence of leptospirosis and the local environment were determined using Simultaneous Autoregressive Models (SAR) explicitly modelling spatial dependence of the model residuals. Leptospirosis incidence rates were found to be spatially clustered, showing a marked spatial pattern. Fitting a spatial autoregressive model significantly improved model fit and revealed significant association between leptospirosis and the coverage of arable land, built up area, grassland and sabulous clay soils. The incidence of leptospirosis in the Netherlands could effectively be modelled using a combination of soil and land-use variables accounting for spatial dependence of incidence rates per municipality. The resulting spatially explicit risk predictions provide an important source of information which will benefit clinical awareness on potential leptospirosis infections in endemic areas.

Environmental risk of leptospirosis infections in the Netherlands: Spatial modelling of environmental risk factors of leptospirosis in the Netherlands

PubMed Central

Goris, Marga G. A.; Pijnacker, Roan; Bakker, Mirjam I.; Hartskeerl, Rudy A.

2017-01-01

Leptospirosis is a globally emerging zoonotic disease, associated with various climatic, biotic and abiotic factors. Mapping and quantifying geographical variations in the occurrence of leptospirosis and the surrounding environment offer innovative methods to study disease transmission and to identify associations between the disease and the environment. This study aims to investigate geographic variations in leptospirosis incidence in the Netherlands and to identify associations with environmental factors driving the emergence of the disease. Individual case data derived over the period 1995–2012 in the Netherlands were geocoded and aggregated by municipality. Environmental covariate data were extracted for each municipality and stored in a spatial database. Spatial clusters were identified using kernel density estimations and quantified using local autocorrelation statistics. Associations between the incidence of leptospirosis and the local environment were determined using Simultaneous Autoregressive Models (SAR) explicitly modelling spatial dependence of the model residuals. Leptospirosis incidence rates were found to be spatially clustered, showing a marked spatial pattern. Fitting a spatial autoregressive model significantly improved model fit and revealed significant association between leptospirosis and the coverage of arable land, built up area, grassland and sabulous clay soils. The incidence of leptospirosis in the Netherlands could effectively be modelled using a combination of soil and land-use variables accounting for spatial dependence of incidence rates per municipality. The resulting spatially explicit risk predictions provide an important source of information which will benefit clinical awareness on potential leptospirosis infections in endemic areas. PMID:29065186

A reaction-diffusion within-host HIV model with cell-to-cell transmission.

PubMed

Ren, Xinzhi; Tian, Yanni; Liu, Lili; Liu, Xianning

2018-06-01

In this paper, a reaction-diffusion within-host HIV model is proposed. It incorporates cell mobility, spatial heterogeneity and cell-to-cell transmission, which depends on the diffusion ability of the infected cells. In the case of a bounded domain, the basic reproduction number [Formula: see text] is established and shown as a threshold: the virus-free steady state is globally asymptotically stable if [Formula: see text] and the virus is uniformly persistent if [Formula: see text]. The explicit formula for [Formula: see text] and the global asymptotic stability of the constant positive steady state are obtained for the case of homogeneous space. In the case of an unbounded domain and [Formula: see text], the existence of the traveling wave solutions is proved and the minimum wave speed [Formula: see text] is obtained, providing the mobility of infected cells does not exceed that of the virus. These results are obtained by using Schauder fixed point theorem, limiting argument, LaSalle's invariance principle and one-side Laplace transform. It is found that the asymptotic spreading speed may be larger than the minimum wave speed via numerical simulations. However, our simulations show that it is possible either to underestimate or overestimate the spread risk [Formula: see text] if the spatial averaged system is used rather than one that is spatially explicit. The spread risk may also be overestimated if we ignore the mobility of the cells. It turns out that the minimum wave speed could be either underestimated or overestimated as long as the mobility of infected cells is ignored.

Using the CARDAMOM framework to retrieve global terrestrial ecosystem functioning properties

NASA Astrophysics Data System (ADS)

Exbrayat, Jean-François; Bloom, A. Anthony; Smallman, T. Luke; van der Velde, Ivar R.; Feng, Liang; Williams, Mathew

2016-04-01

Terrestrial ecosystems act as a sink for anthropogenic emissions of fossil-fuel and thereby partially offset the ongoing global warming. However, recent model benchmarking and intercomparison studies have highlighted the non-trivial uncertainties that exist in our understanding of key ecosystem properties like plant carbon allocation and residence times. It leads to worrisome differences in terrestrial carbon stocks simulated by Earth system models, and their evolution in a warming future. In this presentation we attempt to provide global insights on these properties by merging an ecosystem model with remotely-sensed global observations of leaf area and biomass through a data-assimilation system: the CARbon Data MOdel fraMework (CARDAMOM). CARDAMOM relies on a Markov Chain Monte Carlo algorithm to retrieve confidence intervals of model parameters that regulate ecosystem properties independently of any prior land-cover information. The MCMC method thereby enables an explicit representation of the uncertainty in land-atmosphere fluxes and the evolution of terrestrial carbon stocks through time. Global experiments are performed for the first decade of the 21st century using a 1°×1° spatial resolution. Relationships emerge globally between key ecosystem properties. For example, our analyses indicate that leaf lifespan and leaf mass per area are highly correlated. Furthermore, there exists a latitudinal gradient in allocation patterns: high latitude ecosystems allocate more carbon to photosynthetic carbon (leaves) while plants invest more carbon in their structural parts (wood and root) in the wet tropics. Overall, the spatial distribution of these ecosystem properties does not correspond to usual land-cover maps and are also partially correlated with disturbance regimes. For example, fire-prone ecosystems present statistically significant higher values of carbon use efficiency than less disturbed ecosystems experiencing similar climatic conditions. These results raise concerns on the suitability of the plant functional type paradigm for terrestrial carbon cycling.

Simulation of multi-pulse coaxial helicity injection in the Sustained Spheromak Physics Experiment

NASA Astrophysics Data System (ADS)

O'Bryan, J. B.; Romero-Talamás, C. A.; Woodruff, S.

2018-03-01

Nonlinear, numerical computation with the NIMROD code is used to explore magnetic self-organization during multi-pulse coaxial helicity injection in the Sustained Spheromak Physics eXperiment. We describe multiple distinct phases of spheromak evolution, starting from vacuum magnetic fields and the formation of the initial magnetic flux bubble through multiple refluxing pulses and the eventual onset of the column mode instability. Experimental and computational magnetic diagnostics agree on the onset of the column mode instability, which first occurs during the second refluxing pulse of the simulated discharge. Our computations also reproduce the injector voltage traces, despite only specifying the injector current and not explicitly modeling the external capacitor bank circuit. The computations demonstrate that global magnetic evolution is fairly robust to different transport models and, therefore, that a single fluid-temperature model is sufficient for a broader, qualitative assessment of spheromak performance. Although discharges with similar traces of normalized injector current produce similar global spheromak evolution, details of the current distribution during the column mode instability impact the relative degree of poloidal flux amplification and magnetic helicity content.

A seawater desalination scheme for global hydrological models

NASA Astrophysics Data System (ADS)

Hanasaki, Naota; Yoshikawa, Sayaka; Kakinuma, Kaoru; Kanae, Shinjiro

2016-10-01

Seawater desalination is a practical technology for providing fresh water to coastal arid regions. Indeed, the use of desalination is rapidly increasing due to growing water demand in these areas and decreases in production costs due to technological advances. In this study, we developed a model to estimate the areas where seawater desalination is likely to be used as a major water source and the likely volume of production. The model was designed to be incorporated into global hydrological models (GHMs) that explicitly include human water usage. The model requires spatially detailed information on climate, income levels, and industrial and municipal water use, which represent standard input/output data in GHMs. The model was applied to a specific historical year (2005) and showed fairly good reproduction of the present geographical distribution and national production of desalinated water in the world. The model was applied globally to two periods in the future (2011-2040 and 2041-2070) under three distinct socioeconomic conditions, i.e., SSP (shared socioeconomic pathway) 1, SSP2, and SSP3. The results indicate that the usage of seawater desalination will have expanded considerably in geographical extent, and that production will have increased by 1.4-2.1-fold in 2011-2040 compared to the present (from 2.8 × 109 m3 yr-1 in 2005 to 4.0-6.0 × 109 m3 yr-1), and 6.7-17.3-fold in 2041-2070 (from 18.7 to 48.6 × 109 m3 yr-1). The estimated global costs for production for each period are USD 1.1-10.6 × 109 (0.002-0.019 % of the total global GDP), USD 1.6-22.8 × 109 (0.001-0.020 %), and USD 7.5-183.9 × 109 (0.002-0.100 %), respectively. The large spreads in these projections are primarily attributable to variations within the socioeconomic scenarios.

Global continental and ocean basin reconstructions since 200 Ma

NASA Astrophysics Data System (ADS)

Seton, M.; Müller, R. D.; Zahirovic, S.; Gaina, C.; Torsvik, T.; Shephard, G.; Talsma, A.; Gurnis, M.; Turner, M.; Maus, S.; Chandler, M.

2012-07-01

Global plate motion models provide a spatial and temporal framework for geological data and have been effective tools for exploring processes occurring at the earth's surface. However, published models either have insufficient temporal coverage or fail to treat tectonic plates in a self-consistent manner. They usually consider the motions of selected features attached to tectonic plates, such as continents, but generally do not explicitly account for the continuous evolution of plate boundaries through time. In order to explore the coupling between the surface and mantle, plate models are required that extend over at least a few hundred million years and treat plates as dynamic features with dynamically evolving plate boundaries. We have constructed a new type of global plate motion model consisting of a set of continuously-closing topological plate polygons with associated plate boundaries and plate velocities since the break-up of the supercontinent Pangea. Our model is underpinned by plate motions derived from reconstructing the seafloor-spreading history of the ocean basins and motions of the continents and utilizes a hybrid absolute reference frame, based on a moving hotspot model for the last 100 Ma, and a true-polar wander corrected paleomagnetic model for 200 to 100 Ma. Detailed regional geological and geophysical observations constrain plate boundary inception or cessation, and time-dependent geometry. Although our plate model is primarily designed as a reference model for a new generation of geodynamic studies by providing the surface boundary conditions for the deep earth, it is also useful for studies in disparate fields when a framework is needed for analyzing and interpreting spatio-temporal data.

Nonglobal correlations in collider physics

DOE PAGES

Moult, Ian; Larkoski, Andrew J.

2016-01-13

Despite their importance for precision QCD calculations, correlations between in- and out-of-jet regions of phase space have never directly been observed. These so-called non-global effects are present generically whenever a collider physics measurement is not explicitly dependent on radiation throughout the entire phase space. In this paper, we introduce a novel procedure based on mutual information, which allows us to isolate these non-global correlations between measurements made in different regions of phase space. We study this procedure both analytically and in Monte Carlo simulations in the context of observables measured on hadronic final states produced in e+e- collisions, though itmore » is more widely applicable.The procedure exploits the sensitivity of soft radiation at large angles to non-global correlations, and we calculate these correlations through next-to-leading logarithmic accuracy. The bulk of these non-global correlations are found to be described in Monte Carlo simulation. They increase by the inclusion of non-perturbative effects, which we show can be incorporated in our calculation through the use of a model shape function. As a result, this procedure illuminates the source of non-global correlations and has connections more broadly to fundamental quantities in quantum field theory.« less

Reviewing Biosphere Reserves globally: effective conservation action or bureaucratic label?

PubMed

Coetzer, Kaera L; Witkowski, Edward T F; Erasmus, Barend F N

2014-02-01

The Biosphere Reserve (BR) model of UNESCO's Man and the Biosphere Programme reflects a shift towards more accountable conservation. Biosphere Reserves attempt to reconcile environmental protection with sustainable development; they explicitly acknowledge humans, and human interests in the conservation landscape while still maintaining the ecological values of existing protected areas. Conceptually, this model is attractive, with 610 sites currently designated globally. Yet the practical reality of implementing dual 'conservation' and 'development' goals is challenging, with few examples successfully conforming to the model's full criteria. Here, we review the history of Biosphere Reserves from first inception in 1974 to the current status quo, and examine the suitability of the designation as an effective conservation model. We track the spatial expansion of Biosphere Reserves globally, assessing the influence of the Statutory Framework of the World Network of Biosphere Reserves and Seville strategy in 1995, when the BR concept refocused its core objectives on sustainable development. We use a comprehensive range of case studies to discuss conformity to the Programme, the social and ecological consequences associated with implementation of the designation, and challenges in aligning conservation and development. Given that the 'Biosphere Reserve' label is a relatively unknown designation in the public arena, this review also provides details on popularising the Biosphere Reserve brand, as well as prospects for further research, currently unexploited, but implicit in the designation. © 2013 The Authors. Biological Reviews © 2013 Cambridge Philosophical Society.

Global Gauge Anomalies in Two-Dimensional Bosonic Sigma Models

NASA Astrophysics Data System (ADS)

Gawȩdzki, Krzysztof; Suszek, Rafał R.; Waldorf, Konrad

2011-03-01

We revisit the gauging of rigid symmetries in two-dimensional bosonic sigma models with a Wess-Zumino term in the action. Such a term is related to a background closed 3-form H on the target space. More exactly, the sigma-model Feynman amplitudes of classical fields are associated to a bundle gerbe with connection of curvature H over the target space. Under conditions that were unraveled more than twenty years ago, the classical amplitudes may be coupled to the topologically trivial gauge fields of the symmetry group in a way which assures infinitesimal gauge invariance. We show that the resulting gauged Wess-Zumino amplitudes may, nevertheless, exhibit global gauge anomalies that we fully classify. The general results are illustrated on the example of the WZW and the coset models of conformal field theory. The latter are shown to be inconsistent in the presence of global anomalies. We introduce a notion of equivariant gerbes that allow an anomaly-free coupling of the Wess-Zumino amplitudes to all gauge fields, including the ones in non-trivial principal bundles. Obstructions to the existence of equivariant gerbes and their classification are discussed. The choice of different equivariant structures on the same bundle gerbe gives rise to a new type of discrete-torsion ambiguities in the gauged amplitudes. An explicit construction of gerbes equivariant with respect to the adjoint symmetries over compact simply connected simple Lie groups is given.

Estimation of height-dependent solar irradiation and application to the solar climate of Iran

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

Samimi, J.

1994-05-01

An explicitly height-dependent model has been used to estimate the solar irradiation over Iran which has a vast range of altitudes. The parameters of the model have been chosen on general grounds and not by parameters best fitting to any of the available measured irradiation data in Iran. The estimated global solar irradiation on the horizontal surface shows a very good agreement (4.1% deviation) with the 17-year long pyranometric measurements in Tehran, and also, is in good agreement with other, shorter available measured data. The entire data base of the Iranian meteorological stations have been used to establish a simplemore » relation between the sunshine duration records and the cloud cover reports which can be utilized in solar energy estimations for sites with no sunshine duration recorders. Clear sky maps of Iran for direct solar irradiation on tracking, horizontal, and south-facing vertical planes are presented. The global solar irradiation map for horizontal surface with cloudiness is zoned into four irradiation zones. In about four-fifths of the land in Iran, the annual-mean daily global solar irradiation on horizontal surface ranges from 4.5 to 5.4 kWh/m[sup 2].« less

Global Cryptosporidium Loads from Livestock Manure.

PubMed

Vermeulen, Lucie C; Benders, Jorien; Medema, Gertjan; Hofstra, Nynke

2017-08-01

Understanding the environmental pathways of Cryptosporidium is essential for effective management of human and animal cryptosporidiosis. In this paper we aim to quantify livestock Cryptosporidium spp. loads to land on a global scale using spatially explicit process-based modeling, and to explore the effect of manure storage and treatment on oocyst loads using scenario analysis. Our model GloWPa-Crypto L1 calculates a total global Cryptosporidium spp. load from livestock manure of 3.2 × 10 23 oocysts per year. Cattle, especially calves, are the largest contributors, followed by chickens and pigs. Spatial differences are linked to animal spatial distributions. North America, Europe, and Oceania together account for nearly a quarter of the total oocyst load, meaning that the developing world accounts for the largest share. GloWPa-Crypto L1 is most sensitive to oocyst excretion rates, due to large variation reported in literature. We compared the current situation to four alternative management scenarios. We find that although manure storage halves oocyst loads, manure treatment, especially of cattle manure and particularly at elevated temperatures, has a larger load reduction potential than manure storage (up to 4.6 log units). Regions with high reduction potential include India, Bangladesh, western Europe, China, several countries in Africa, and New Zealand.

An optical potential for the statically deformed actinide nuclei derived from a global spherical potential

NASA Astrophysics Data System (ADS)

Al-Rawashdeh, S. M.; Jaghoub, M. I.

2018-04-01

In this work we test the hypothesis that a properly deformed spherical optical potential, used within a channel-coupling scheme, provides a good description for the scattering data corresponding to neutron induced reactions on the heavy, statically deformed actinides and other lighter deformed nuclei. To accomplish our goal, we have deformed the Koning-Delaroche spherical global potential and then used it in a channel-coupling scheme. The ground-state is coupled to a sufficient number of inelastic rotational channels belonging to the ground-state band to ensure convergence. The predicted total cross sections, elastic and inelastic angular distributions are in good agreement with the experimental data. As a further test, we compare our results to those obtained by a global channel-coupled optical model whose parameters were obtained by fitting elastic and inelastic angular distributions in addition to total cross sections. Our results compare quite well with those obtained by the fitted, channel-coupled optical model. Below neutron incident energies of about 1MeV, our results show that scattering into the rotational excited states of the ground-state band plays a significant role in the scattering process and must be explicitly accounted for using a channel-coupling scheme.

Shrinking of fishes exacerbates impacts of global ocean changes on marine ecosystems

NASA Astrophysics Data System (ADS)

Cheung, William W. L.; Sarmiento, Jorge L.; Dunne, John; Frölicher, Thomas L.; Lam, Vicky W. Y.; Deng Palomares, M. L.; Watson, Reg; Pauly, Daniel

2013-03-01

Changes in temperature, oxygen content and other ocean biogeochemical properties directly affect the ecophysiology of marine water-breathing organisms. Previous studies suggest that the most prominent biological responses are changes in distribution, phenology and productivity. Both theory and empirical observations also support the hypothesis that warming and reduced oxygen will reduce body size of marine fishes. However, the extent to which such changes would exacerbate the impacts of climate and ocean changes on global marine ecosystems remains unexplored. Here, we employ a model to examine the integrated biological responses of over 600 species of marine fishes due to changes in distribution, abundance and body size. The model has an explicit representation of ecophysiology, dispersal, distribution, and population dynamics. We show that assemblage-averaged maximum body weight is expected to shrink by 14-24% globally from 2000 to 2050 under a high-emission scenario. About half of this shrinkage is due to change in distribution and abundance, the remainder to changes in physiology. The tropical and intermediate latitudinal areas will be heavily impacted, with an average reduction of more than 20%. Our results provide a new dimension to understanding the integrated impacts of climate change on marine ecosystems.

Exploring global carbon turnover and radiocarbon cycling in terrestrial biosphere models

NASA Astrophysics Data System (ADS)

Graven, H. D.; Warren, H.

2017-12-01

The uptake of carbon into terrestrial ecosystems through net primary productivity (NPP) and the turnover of that carbon through various pathways are the fundamental drivers of changing carbon stocks on land, in addition to human-induced and natural disturbances. Terrestrial biosphere models use different formulations for carbon uptake and release, resulting in a range of values in NPP of 40-70 PgC/yr and biomass turnover times of about 25-40 years for the preindustrial period in current-generation models from CMIP5. Biases in carbon uptake and turnover impact simulated carbon uptake and storage in the historical period and later in the century under changing climate and CO2 concentration, however evaluating global-scale NPP and carbon turnover is challenging. Scaling up of plot-scale measurements involves uncertainty due to the large heterogeneity across ecosystems and biomass types, some of which are not well-observed. We are developing the modelling of radiocarbon in terrestrial biosphere models, with a particular focus on decadal 14C dynamics after the nuclear weapons testing in the 1950s-60s, including the impact of carbon flux trends and variability on 14C cycling. We use an estimate of the total inventory of excess 14C in the biosphere constructed by Naegler and Levin (2009) using a 14C budget approach incorporating estimates of total 14C produced by the weapons tests and atmospheric and oceanic 14C observations. By simulating radiocarbon in simple biosphere box models using carbon fluxes from the CMIP5 models, we find that carbon turnover is too rapid in many of the simple models - the models appear to take up too much 14C and release it too quickly. Therefore many CMIP5 models may also simulate carbon turnover that is too rapid. A caveat is that the simple box models we use may not adequately represent carbon dynamics in the full-scale models. Explicit simulation of radiocarbon in terrestrial biosphere models would allow more robust evaluation of biosphere models and the investigation of climate-carbon cycle feedbacks on various timescales. Explicit simulation of radiocarbon and carbon-13 in terrestrial biosphere models of Earth System Models, as well as in ocean models, is recommended by CMIP6 and supported by CMIP6 protocols and forcing datasets.

The global distribution of leaf chlorophyll content and seasonal controls on carbon uptake

NASA Astrophysics Data System (ADS)

Croft, H.; Chen, J. M.; Luo, X.; Bartlett, P. A.; Staebler, R. M.; He, L.; Mo, G.; Luo, S.; Simic, A.; Arabian, J.; He, Y.; Zhang, Y.; Beringer, J.; Hutley, L. B.; Noland, T. L.; Arellano, P.; Stahl, C.; Homolová, L.; Bonal, D.; Malenovský, Z.; Yi, Q.; Amiri, R.

2017-12-01

Leaf chlorophyll (ChlLeaf) is crucial to biosphere-atmosphere exchanges of carbon and water, and the functioning of terrestrial ecosystems. Improving the accuracy of modelled photosynthetic carbon uptake is a central priority for understanding ecosystem response to a changing climate. A source of uncertainty within gross primary productivity (GPP) estimates is the failure to explicitly consider seasonal controls on leaf photosynthetic potential. Whilst the inclusion of ChlLeafinto carbon models has shown potential to provide a physiological constraint, progress has been hampered by the absence of a spatially-gridded, global chlorophyll product. Here, we present the first spatially-continuous, global view of terrestrial ChlLeaf, at weekly intervals. Satellite-derived ChlLeaf was modelled using a physically-based radiative transfer modelling approach, with a two stage model inversion method. 4-Scale and SAIL canopy models were first used to model leaf-level reflectance from ENIVSAT MERIS 300m satellite data. The PROSPECT leaf model was then used to derive ChlLeaf from the modelled leaf reflectance. This algorithm was validated using measured ChlLeaf data from 248 measurements within 26 field locations, covering six plant functional types (PFTs). Modelled results show very good relationships with measured data, particularly for deciduous broadleaf forests (R2 = 0.67; p<0.001) and croplands (R2 = 0.42; p<000.1). With all PFTs considered together, the overall validation against measured data was strong (R2 = 0.50; p<0.001). The incorporation of chlorophyll within a light-use efficiency GPP modelling approach and a Terrestrial Biosphere Model demonstrated that neglecting to account for seasonality in leaf physiology resulted in over-estimations in GPP at the start/end of a deciduous growing season, due to a divergence in canopy structure and leaf function. Across nine PFTs, Fluxnet eddy-covariance data was used to validate TBM GPP estimates using ChlLeaf-constrained Vcmax; reducing the seasonal bias and explaining 13%-49% of daily variations in GPP. This work demonstrates the importance of considering leaf pigment status in modelling photosynthetic carbon uptake. We anticipate that the global ChlLeaf product will make an important step towards improving the accuracy of global carbon budgets.

Updating the lake-atmosphere gas transfer velocity with impacts on the role of lake ecosystems in global carbon cycling

NASA Astrophysics Data System (ADS)

Heiskanen, J. J.; Mammarella, I.; Haapanala, S.; Vesala, T.; Pumpanen, J. S.; Ojala, A.

2013-12-01

Currently, the global estimate for the amount of carbon bound in terrestrial ecosystems is 3.0 × 0.9 Pg C y-1 [Le Quéré et al., 2009]. Lakes are not explicitly included in currently used global carbon models [Randall et al., 2007] but it has been estimated that the global net CO2 flux from lakes to the atmosphere range from 0.07 to 0.15 Pg C y-1 [Cole et al., 2007], corresponding to 2.3-5.0% of the total average terrestrial net uptake of carbon. These lake flux estimates may be considerably biased [MacIntyre et al., 2010], since although the data pertain to about 5000 lakes throughout the world [Sobek and Tranvik, 2005], the estimates are not from direct flux measurements. Instead, they are based on surface-water CO2 partial pressure in combination with the gas transfer velocity, k. The uncertainty in the global net CO2 flux is mostly due to the uncertainties in k, which can vary considerably. Cole and Caraco (1998) measured a range of 1.4 to 4.8 cm h-1 for k, but again, these values are not based on direct flux measurements of CO2. The most widely used empirical models of k have wind speed as the only explaining variable. However, the gas transfer velocity is also known to depend on turbulence in the surface water [MacIntyre et al., 2010], which in turn depends mostly on penetrative water convection at low wind conditions [MacIntyre et al., 2010; MacIntyre et al., 2001] - the conditions often prevailing in lakes [Schladow et al., 2002]. We formulated an improved model for k with heat flux parameterization in addition to a wind-speed parameter, determined from an analysis of 4 months (August - November 2011) of continuous high-frequency data in a typical small boreal lake in southern Finland. The CO2 flux from the lake to the atmosphere, atmospheric partial pressure of CO2, and latent and sensible heat were measured with the EC technique installed on a platform. Ancillary measurements included surface-water CO2 concentration and temperature, and net longwave and shortwave radiation. The modeled average k for the whole period, 9.5 cm h-1, was near to the measured average, 8.7 cm h-1. We used 24-hour averages when comparing the results. The new model for k had an R2 value of 0.66 when its performance was compared to the measured gas transfer velocity. Even though this is a lot higher value than when comparing the measured k with a widely used model for k (Cole and Caraco 1998, R2=0.29), the new model could not predict all the sudden changes in k and still roughly one third of the variation was left unexplained. This might be due to the environmental factors omitted by the model, e.g. surfactants. As a result, we showed that the current estimate of the global net CO2 flux from lakes to the atmosphere triples from 0.07-0.15 Pg C y-1 to 0.23-0.48 Pg C y-1 when the average k by Cole and Caraco (1998) is replaced with the new k. This corresponds to 7.5-16.0% of the total CO2 bound in terrestrial ecosystems compared with the current estimates of 2.3-5.0%. The new parameterization of k, assuming that it represents lakes in general, thus shows that the role of lakes in the global carbon cycle has been heavily underestimated and emphasizes the explicit inclusion of lakes in global carbon models.

The world's biomes and primary production as a triple tragedy of the commons foraging game played among plants

PubMed Central

Gonzalez-Meler, Miquel A.; Lynch, Douglas J.; Baltzer, Jennifer L.

2016-01-01

Plants appear to produce an excess of leaves, stems and roots beyond what would provide the most efficient harvest of available resources. One way to understand this overproduction of tissues is that excess tissue production provides a competitive advantage. Game theoretic models predict overproduction of all tissues compared with non-game theoretic models because they explicitly account for this indirect competitive benefit. Here, we present a simple game theoretic model of plants simultaneously competing to harvest carbon and nitrogen. In the model, a plant's fitness is influenced by its own leaf, stem and root production, and the tissue production of others, which produces a triple tragedy of the commons. Our model predicts (i) absolute net primary production when compared with two independent global datasets; (ii) the allocation relationships to leaf, stem and root tissues in one dataset; (iii) the global distribution of biome types and the plant functional types found within each biome; and (iv) ecosystem responses to nitrogen or carbon fertilization. Our game theoretic approach removes the need to define allocation or vegetation type a priori but instead lets these emerge from the model as evolutionarily stable strategies. We believe this to be the simplest possible model that can describe plant production. PMID:28120794

The world's biomes and primary production as a triple tragedy of the commons foraging game played among plants.

PubMed

McNickle, Gordon G; Gonzalez-Meler, Miquel A; Lynch, Douglas J; Baltzer, Jennifer L; Brown, Joel S

2016-11-16

Plants appear to produce an excess of leaves, stems and roots beyond what would provide the most efficient harvest of available resources. One way to understand this overproduction of tissues is that excess tissue production provides a competitive advantage. Game theoretic models predict overproduction of all tissues compared with non-game theoretic models because they explicitly account for this indirect competitive benefit. Here, we present a simple game theoretic model of plants simultaneously competing to harvest carbon and nitrogen. In the model, a plant's fitness is influenced by its own leaf, stem and root production, and the tissue production of others, which produces a triple tragedy of the commons. Our model predicts (i) absolute net primary production when compared with two independent global datasets; (ii) the allocation relationships to leaf, stem and root tissues in one dataset; (iii) the global distribution of biome types and the plant functional types found within each biome; and (iv) ecosystem responses to nitrogen or carbon fertilization. Our game theoretic approach removes the need to define allocation or vegetation type a priori but instead lets these emerge from the model as evolutionarily stable strategies. We believe this to be the simplest possible model that can describe plant production. © 2016 The Author(s).

Fostering Global Competence through Internationalization at American Research Universities. SERU Consortium Research Paper. Research & Occasional Paper Series: CSHE.10.17

ERIC Educational Resources Information Center

Shcheglova, Irina A.; Thomson, Gregg E.; Merrill, Martha C.

2017-01-01

American research universities have recently joined the march for internationalization and now are putting explicit efforts into finding ways to create an international focus. Within a short number of years, their missions have been transformed, incorporating elements of globalization. Universities now declare the importance of preparing students…

Infants of the Knowledge Economy: The Ambition of the Australian Government's Early Years Learning Framework

ERIC Educational Resources Information Center

Cheeseman, Sandra; Sumsion, Jennifer; Press, Frances

2014-01-01

Shifts in global education policy to formalise curricula and make explicit learning outcomes for ever younger children have become popular for a number of countries responding to changes in global market economics. Human capital discourses, broadly aimed at shaping national prosperity, have entered the early childhood education and care policy…

Land Use Management in the Panama Canal Watershed to Maximize Hydrologic Ecosystem Services Benefits: Explicit Simulation of Preferential Flow Paths in an HPC Environment

NASA Astrophysics Data System (ADS)

Regina, J. A.; Ogden, F. L.; Steinke, R. C.; Frazier, N.; Cheng, Y.; Zhu, J.

2017-12-01

Preferential flow paths (PFP) resulting from biotic and abiotic factors contribute significantly to the generation of runoff in moist lowland tropical watersheds. Flow through PFPs represents the dominant mechanism by which land use choices affect hydrological behavior. The relative influence of PFP varies depending upon land-use management practices. Assessing the possible effects of land-use and landcover change on flows, and other ecosystem services, in the humid tropics partially depends on adequate simulation of PFP across different land-uses. Currently, 5% of global trade passes through the Panama Canal, which is supplied with fresh water from the Panama Canal Watershed. A third set of locks, recently constructed, are expected to double the capacity of the Canal. We incorporated explicit simulation of PFPs in to the ADHydro HPC distributed hydrological model to simulate the effects of land-use and landcover change due to land management incentives on water resources availability in the Panama Canal Watershed. These simulations help to test hypotheses related to the effectiveness of various proposed payments for ecosystem services schemes. This presentation will focus on hydrological model formulation and performance in an HPC environment.

Cloud Condensation Nuclei Prediction Error from Application of Kohler Theory: Importance for the Aerosol Indirect Effect

NASA Technical Reports Server (NTRS)

Sotiropoulou, Rafaella-Eleni P.; Nenes, Athanasios; Adams, Peter J.; Seinfeld, John H.

2007-01-01

In situ observations of aerosol and cloud condensation nuclei (CCN) and the GISS GCM Model II' with an online aerosol simulation and explicit aerosol-cloud interactions are used to quantify the uncertainty in radiative forcing and autoconversion rate from application of Kohler theory. Simulations suggest that application of Koehler theory introduces a 10-20% uncertainty in global average indirect forcing and 2-11% uncertainty in autoconversion. Regionally, the uncertainty in indirect forcing ranges between 10-20%, and 5-50% for autoconversion. These results are insensitive to the range of updraft velocity and water vapor uptake coefficient considered. This study suggests that Koehler theory (as implemented in climate models) is not a significant source of uncertainty for aerosol indirect forcing but can be substantial for assessments of aerosol effects on the hydrological cycle in climatically sensitive regions of the globe. This implies that improvements in the representation of GCM subgrid processes and aerosol size distribution will mostly benefit indirect forcing assessments. Predictions of autoconversion, by nature, will be subject to considerable uncertainty; its reduction may require explicit representation of size-resolved aerosol composition and mixing state.

CDPOP: A spatially explicit cost distance population genetics program

Treesearch

Erin L. Landguth; S. A. Cushman

2010-01-01

Spatially explicit simulation of gene flow in complex landscapes is essential to explain observed population responses and provide a foundation for landscape genetics. To address this need, we wrote a spatially explicit, individual-based population genetics model (CDPOP). The model implements individual-based population modelling with Mendelian inheritance and k-allele...

Gene-centric approach to integrating environmental genomics and biogeochemical models.

PubMed

Reed, Daniel C; Algar, Christopher K; Huber, Julie A; Dick, Gregory J

2014-02-04

Rapid advances in molecular microbial ecology have yielded an unprecedented amount of data about the evolutionary relationships and functional traits of microbial communities that regulate global geochemical cycles. Biogeochemical models, however, are trailing in the wake of the environmental genomics revolution, and such models rarely incorporate explicit representations of bacteria and archaea, nor are they compatible with nucleic acid or protein sequence data. Here, we present a functional gene-based framework for describing microbial communities in biogeochemical models by incorporating genomics data to provide predictions that are readily testable. To demonstrate the approach in practice, nitrogen cycling in the Arabian Sea oxygen minimum zone (OMZ) was modeled to examine key questions about cryptic sulfur cycling and dinitrogen production pathways in OMZs. Simulations support previous assertions that denitrification dominates over anammox in the central Arabian Sea, which has important implications for the loss of fixed nitrogen from the oceans. Furthermore, cryptic sulfur cycling was shown to attenuate the secondary nitrite maximum often observed in OMZs owing to changes in the composition of the chemolithoautotrophic community and dominant metabolic pathways. Results underscore the need to explicitly integrate microbes into biogeochemical models rather than just the metabolisms they mediate. By directly linking geochemical dynamics to the genetic composition of microbial communities, the method provides a framework for achieving mechanistic insights into patterns and biogeochemical consequences of marine microbes. Such an approach is critical for informing our understanding of the key role microbes play in modulating Earth's biogeochemistry.

Theory of a microfluidic serial dilution bioreactor for growth of planktonic and biofilm populations.

PubMed

Hsu, Sze-Bi; Yang, Ya-Tang

2016-04-01

We present the theory of a microfluidic bioreactor with a two-compartment growth chamber and periodic serial dilution. In the model, coexisting planktonic and biofilm populations exchange by adsorption and detachment. The criteria for coexistence and global extinction are determined by stability analysis of the global extinction state. Stability analysis yields the operating diagram in terms of the dilution and removal ratios, constrained by the plumbing action of the bioreactor. The special case of equal uptake function and logistic growth is analytically solved and explicit growth curves are plotted. The presented theory is applicable to generic microfluidic bioreactors with discrete growth chambers and periodic dilution at discrete time points. Therefore, the theory is expected to assist the design of microfluidic devices for investigating microbial competition and microbial biofilm growth under serial dilution conditions.

A new climate dataset for systematic assessments of climate change impacts as a function of global warming

NASA Astrophysics Data System (ADS)

Heinke, J.; Ostberg, S.; Schaphoff, S.; Frieler, K.; Müller, C.; Gerten, D.; Meinshausen, M.; Lucht, W.

2013-10-01

In the ongoing political debate on climate change, global mean temperature change (ΔTglob) has become the yardstick by which mitigation costs, impacts from unavoided climate change, and adaptation requirements are discussed. For a scientifically informed discourse along these lines, systematic assessments of climate change impacts as a function of ΔTglob are required. The current availability of climate change scenarios constrains this type of assessment to a narrow range of temperature change and/or a reduced ensemble of climate models. Here, a newly composed dataset of climate change scenarios is presented that addresses the specific requirements for global assessments of climate change impacts as a function of ΔTglob. A pattern-scaling approach is applied to extract generalised patterns of spatially explicit change in temperature, precipitation and cloudiness from 19 Atmosphere-Ocean General Circulation Models (AOGCMs). The patterns are combined with scenarios of global mean temperature increase obtained from the reduced-complexity climate model MAGICC6 to create climate scenarios covering warming levels from 1.5 to 5 degrees above pre-industrial levels around the year 2100. The patterns are shown to sufficiently maintain the original AOGCMs' climate change properties, even though they, necessarily, utilise a simplified relationships between ΔTglob and changes in local climate properties. The dataset (made available online upon final publication of this paper) facilitates systematic analyses of climate change impacts as it covers a wider and finer-spaced range of climate change scenarios than the original AOGCM simulations.

Locally-Adaptive, Spatially-Explicit Projection of U.S. Population for 2030 and 2050

DOE PAGES

McKee, Jacob J.; Rose, Amy N.; Bright, Eddie A.; ...

2015-02-03

Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Moreover, knowing the spatial distribution of future population allows for increased preparation in the event of an emergency. Building on the spatial interpolation technique previously developed for high resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically-informed spatial distribution of the projected population of the contiguous U.S. for 2030 and 2050. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection modelmore » departs from these by accounting for multiple components that affect population distribution. Modelled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the U.S. Census s projection methodology with the U.S. Census s official projection as the benchmark. Applications of our model include, but are not limited to, suitability modelling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.« less

Locally-Adaptive, Spatially-Explicit Projection of U.S. Population for 2030 and 2050

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

McKee, Jacob J.; Rose, Amy N.; Bright, Eddie A.

Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Moreover, knowing the spatial distribution of future population allows for increased preparation in the event of an emergency. Building on the spatial interpolation technique previously developed for high resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically-informed spatial distribution of the projected population of the contiguous U.S. for 2030 and 2050. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection modelmore » departs from these by accounting for multiple components that affect population distribution. Modelled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the U.S. Census s projection methodology with the U.S. Census s official projection as the benchmark. Applications of our model include, but are not limited to, suitability modelling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.« less

Towards an purely data driven view on the global carbon cycle and its spatiotemporal variability

NASA Astrophysics Data System (ADS)

Zscheischler, Jakob; Mahecha, Miguel; Reichstein, Markus; Avitabile, Valerio; Carvalhais, Nuno; Ciais, Philippe; Gans, Fabian; Gruber, Nicolas; Hartmann, Jens; Herold, Martin; Jung, Martin; Landschützer, Peter; Laruelle, Goulven; Lauerwald, Ronny; Papale, Dario; Peylin, Philippe; Regnier, Pierre; Rödenbeck, Christian; Cuesta, Rosa Maria Roman; Valentini, Ricardo

2015-04-01

Constraining carbon (C) fluxes between the Earth's surface and the atmosphere at regional scale via observations is essential for understanding the Earth's carbon budget and predicting future atmospheric C concentrations. Carbon budgets have often been derived based on merging observations, statistical models and process-based models, for example in the Global Carbon Project (GCP). However, it would be helpful to derive global C budgets and fluxes at global scale as independent as possible from model assumptions to obtain an independent reference. Long-term in-situ measurements of land and ocean C stocks and fluxes have enabled the derivation of a new generation of data driven upscaled data products. Here, we combine a wide range of in-situ derived estimates of terrestrial and aquatic C fluxes for one decade. The data were produced and/or collected during the FP7 project GEOCARBON and include surface-atmosphere C fluxes from the terrestrial biosphere, fossil fuels, fires, land use change, rivers, lakes, estuaries and open ocean. By including spatially explicit uncertainties in each dataset we are able to identify regions that are well constrained by observations and areas where more measurements are required. Although the budget cannot be closed at the global scale, we provide, for the first time, global time-varying maps of the most important C fluxes, which are all directly derived from observations. The resulting spatiotemporal patterns of C fluxes and their uncertainties inform us about the needs for intensifying global C observation activities. Likewise, we provide priors for inversion exercises or to identify regions of high (and low) uncertainty of integrated C fluxes. We discuss the reasons for regions of high observational uncertainties, and for biases in the budget. Our data synthesis might also be used as empirical reference for other local and global C budgeting exercises.

a Heavy Higgs Boson from Flavor and Electroweak Symmetry Unification

NASA Astrophysics Data System (ADS)

Fabbrichesi, Marco

2005-08-01

We present a unified picture of flavor and electroweak symmetry breaking based on a nonlinear sigma model spontaneously broken at the TeV scale. Flavor and Higgs bosons arise as pseudo-Goldstone modes. Explicit collective symmetry breaking yields stable vacuum expectation values and masses protected at one loop by the little-Higgs mechanism. The coupling to the fermions generates well-definite mass textures--according to a U(1) global flavor symmetry--that correctly reproduce the mass hierarchies and mixings of quarks and leptons. The model is more constrained than usual little-Higgs models because of bounds on weak and flavor physics. The main experimental signatures testable at the LHC are a rather large mass mh0 = 317 ± 80 GeV for the (lightest) Higgs boson.

A New Method of Comparing Forcing Agents in Climate Models

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

Kravitz, Benjamin S.; MacMartin, Douglas; Rasch, Philip J.

We describe a new method of comparing different climate forcing agents (e.g., CO2, CH4, and solar irradiance) that avoids many of the ambiguities introduced by temperature-related climate feedbacks. This is achieved by introducing an explicit feedback loop external to the climate model that adjusts one forcing agent to balance another while keeping global mean surface temperature constant. Compared to current approaches, this method has two main advantages: (i) the need to define radiative forcing is bypassed and (ii) by maintaining roughly constant global mean temperature, the effects of state dependence on internal feedback strengths are minimized. We demonstrate this approachmore » for several different forcing agents and derive the relationships between these forcing agents in two climate models; comparisons between forcing agents are highly linear in concordance with predicted functional forms. Transitivity of the relationships between the forcing agents appears to hold within a wide range of forcing. The relationships between the forcing agents obtained from this method are consistent across both models but differ from relationships that would be obtained from calculations of radiative forcing, highlighting the importance of controlling for surface temperature feedback effects when separating radiative forcing and climate response.« less

A Dynamic Competition Simulation for Worldwide Big-size TV Market Using Lotka-Volterra Model

NASA Astrophysics Data System (ADS)

Chen, Wu-Tung Terry; Li, Yiming; Hung, Chih-Young

2009-08-01

Technological innovation is characterized by the substitution of new technologies for full-fledged ones in the development of new products, processes and techniques. Global TV market is seeing a price down-spiral for FPD(Flat Panel Display)-TVs, replacement of CRT by LCD, and consumer's defection to larger screen. The LCD-TV market started in Japan from 2003 and took off globally from 2005. LCD panel production is moving toward larger sizes. In the 35″-39″ size market, the price/performance ratio of LCD-TV is better than that of PDP. The purpose of this paper is to estimate the demand function of worldwide big-size (35″-39″) TVs including LCD and PDP with an explicit consideration of market competition. The demand function was estimated using Lotka-Volterra model, a famous competitive diffusion model. The results exhibit a kind of predator-prey relationship, in which the PDP market was hunted by LCD product. In addition, the coefficients of difference equations of Lotka-Volterra model in this analysis are also used to forecast the future market of the big-size LCD and PDP.

Effect of Damping and Yielding on the Seismic Response of 3D Steel Buildings with PMRF

PubMed Central

Haldar, Achintya; Rodelo-López, Ramon Eduardo; Bojórquez, Eden

2014-01-01

The effect of viscous damping and yielding, on the reduction of the seismic responses of steel buildings modeled as three-dimensional (3D) complex multidegree of freedom (MDOF) systems, is studied. The reduction produced by damping may be larger or smaller than that of yielding. This reduction can significantly vary from one structural idealization to another and is smaller for global than for local response parameters, which in turn depends on the particular local response parameter. The uncertainty in the estimation is significantly larger for local response parameter and decreases as damping increases. The results show the limitations of the commonly used static equivalent lateral force procedure where local and global response parameters are reduced in the same proportion. It is concluded that estimating the effect of damping and yielding on the seismic response of steel buildings by using simplified models may be a very crude approximation. Moreover, the effect of yielding should be explicitly calculated by using complex 3D MDOF models instead of estimating it in terms of equivalent viscous damping. The findings of this paper are for the particular models used in the study. Much more research is needed to reach more general conclusions. PMID:25097892

Effect of damping and yielding on the seismic response of 3D steel buildings with PMRF.

PubMed

Reyes-Salazar, Alfredo; Haldar, Achintya; Rodelo-López, Ramon Eduardo; Bojórquez, Eden

2014-01-01

The effect of viscous damping and yielding, on the reduction of the seismic responses of steel buildings modeled as three-dimensional (3D) complex multidegree of freedom (MDOF) systems, is studied. The reduction produced by damping may be larger or smaller than that of yielding. This reduction can significantly vary from one structural idealization to another and is smaller for global than for local response parameters, which in turn depends on the particular local response parameter. The uncertainty in the estimation is significantly larger for local response parameter and decreases as damping increases. The results show the limitations of the commonly used static equivalent lateral force procedure where local and global response parameters are reduced in the same proportion. It is concluded that estimating the effect of damping and yielding on the seismic response of steel buildings by using simplified models may be a very crude approximation. Moreover, the effect of yielding should be explicitly calculated by using complex 3D MDOF models instead of estimating it in terms of equivalent viscous damping. The findings of this paper are for the particular models used in the study. Much more research is needed to reach more general conclusions.

Cold light dark matter in extended seesaw models

NASA Astrophysics Data System (ADS)

Boulebnane, Sami; Heeck, Julian; Nguyen, Anne; Teresi, Daniele

2018-04-01

We present a thorough discussion of light dark matter produced via freeze-in in two-body decays A→ B DM . If A and B are quasi-degenerate, the dark matter particle has a cold spectrum even for keV masses. We show this explicitly by calculating the transfer function that encodes the impact on structure formation. As examples for this setup we study extended seesaw mechanisms with a spontaneously broken global U(1) symmetry, such as the inverse seesaw. The keV-scale pseudo-Goldstone dark matter particle is then naturally produced cold by the decays of the quasi-degenerate right-handed neutrinos.

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

Tan, Zeli; Zhuang, Qianlai; Shurpali, Narasinha J.

Recent studies indicated that Arctic lakes play an important role in receiving, processing, and storing organic carbon exported from terrestrial ecosystems. To quantify the contribution of Arctic lakes to the global carbon cycle, we developed a one-dimensional process-based Arctic Lake Biogeochemistry Model (ALBM) that explicitly simulates the dynamics of organic and inorganic carbon in Arctic lakes. By realistically modeling water mixing, carbon biogeochemistry, and permafrost carbon loading, the model can reproduce the seasonal variability of CO 2 fluxes from the study Arctic lakes. The simulated area-weighted CO 2 fluxes from yedoma thermokarst lakes, nonyedoma thermokarst lakes, and glacial lakes aremore » 29.5, 13.0, and 21.4 g C m -2 yr -1, respectively, close to the observed values (31.2, 17.2, and 16.5 ± 7.7 g C m -2 yr -1, respectively). The simulations show that the high CO 2 fluxes from yedoma thermokarst lakes are stimulated by the biomineralization of mobilized labile organic carbon from thawing yedoma permafrost. The simulations also imply that the relative contribution of glacial lakes to the global carbon cycle could be the largest because of their much larger surface area and high biomineralization and carbon loading. According to the model, sunlight-induced organic carbon degradation is more important for shallow nonyedoma thermokarst lakes but its overall contribution to the global carbon cycle could be limited. Overall, the ALBM can simulate the whole-lake carbon balance of Arctic lakes, a difficult task for field and laboratory experiments and other biogeochemistry models.« less

A fire model with distinct crop, pasture, and non-agricultural burning: use of new data and a model-fitting algorithm for FINAL.1

NASA Astrophysics Data System (ADS)

Rabin, Sam S.; Ward, Daniel S.; Malyshev, Sergey L.; Magi, Brian I.; Shevliakova, Elena; Pacala, Stephen W.

2018-03-01

This study describes and evaluates the Fire Including Natural & Agricultural Lands model (FINAL) which, for the first time, explicitly simulates cropland and pasture management fires separately from non-agricultural fires. The non-agricultural fire module uses empirical relationships to simulate burned area in a quasi-mechanistic framework, similar to past fire modeling efforts, but with a novel optimization method that improves the fidelity of simulated fire patterns to new observational estimates of non-agricultural burning. The agricultural fire components are forced with estimates of cropland and pasture fire seasonality and frequency derived from observational land cover and satellite fire datasets. FINAL accurately simulates the amount, distribution, and seasonal timing of burned cropland and pasture over 2001-2009 (global totals: 0.434×106 and 2.02×106 km2 yr-1 modeled, 0.454×106 and 2.04×106 km2 yr-1 observed), but carbon emissions for cropland and pasture fire are overestimated (global totals: 0.295 and 0.706 PgC yr-1 modeled, 0.194 and 0.538 PgC yr-1 observed). The non-agricultural fire module underestimates global burned area (1.91×106 km2 yr-1 modeled, 2.44×106 km2 yr-1 observed) and carbon emissions (1.14 PgC yr-1 modeled, 1.84 PgC yr-1 observed). The spatial pattern of total burned area and carbon emissions is generally well reproduced across much of sub-Saharan Africa, Brazil, Central Asia, and Australia, whereas the boreal zone sees underestimates. FINAL represents an important step in the development of global fire models, and offers a strategy for fire models to consider human-driven fire regimes on cultivated lands. At the regional scale, simulations would benefit from refinements in the parameterizations and improved optimization datasets. We include an in-depth discussion of the lessons learned from using the Levenberg-Marquardt algorithm in an interactive optimization for a dynamic global vegetation model.

Microphysics in Multi-scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2012-01-01

Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Exploring a microbial ecosystem approach to modeling deep ocean biogeochemical cycles

NASA Astrophysics Data System (ADS)

Zakem, E.; Follows, M. J.

2014-12-01

Though microbial respiration of organic matter in the deep ocean governs ocean and atmosphere biogeochemistry, it is not represented mechanistically in current global biogeochemical models. We seek approaches that are feasible for a global resolution, yet still reflect the enormous biodiversity of the deep microbial community and its associated metabolic pathways. We present a modeling framework grounded in thermodynamics and redox reaction stoichiometry that represents diverse microbial metabolisms explicitly. We describe a bacterial/archaeal functional type with two parameters: a growth efficiency representing the chemistry underlying a bacterial metabolism, and a rate limitation given by the rate of uptake of each of the necessary substrates for that metabolism. We then apply this approach to answer questions about microbial ecology. As a start, we resolve two dominant heterotrophic respiratory pathways- reduction of oxygen and nitrate- and associated microbial functional types. We combine these into an ecological model and a two-dimensional ocean circulation model to explore the organization, biogeochemistry, and ecology of oxygen minimum zones. Intensified upwelling and lateral transport conspire to produce an oxygen minimum at mid-depth, populated by anaerobic denitrifiers. This modeling approach should ultimately allow for the emergence of bacterial biogeography from competition of metabolisms and for the incorporation of microbial feedbacks to the climate system.

Biogeochemical Trends and Their Ecosystem Impacts in Atlantic Canada

NASA Astrophysics Data System (ADS)

Fennel, Katja; Rutherford, Krysten; Kuhn, Angela; Zhang, Wenxia; Brennan, Katie; Zhang, Rui

2017-04-01

The representation of coastal oceans in global biogeochemical models is a challenge, yet the ecosystems in these regions are most vulnerable to the combined stressors of ocean warming, deoxygenation, acidification, eutrophication and fishing. Coastal regions also have large air-sea fluxes of CO2, making them an important but poorly quantified component of the global carbon cycle, and are the most relevant for human activities. Regional model applications that are nested within large-scale or global models are necessary for detailed studies of coastal regions. We present results from such a regional biogeochemical model for the northwestern North Atlantic shelves and adjacent deep ocean of Atlantic Canada. The model is an implementation of the Regional Ocean Modeling System (ROMS) and includes an NPZD-type nitrogen cycle model with explicit representation of dissolved oxygen and inorganic carbon. The region is at the confluence of the Gulf Stream and Labrador Current making it highly dynamic, a challenge for analysis and prediction, and prone to large changes. Historically a rich fishing ground, coastal ecosystems in Atlantic Canada have undergone dramatic changes including the collapse of several economically important fish stocks and the listing of many species as threatened or endangered. Furthermore it is unclear whether the region is a net source or sink of atmospheric CO2 with estimates of the size and direction of the net air-sea CO2 flux remaining controversial. We will discuss simulated patterns of primary production, inorganic carbon fluxes and oxygen trends in the context of circulation features and shelf residence times for the present ocean state and present future projections.

Modeling CO 2 emissions from Arctic lakes: Model development and site-level study

DOE PAGES

Tan, Zeli; Zhuang, Qianlai; Shurpali, Narasinha J.; ...

2017-09-14

Recent studies indicated that Arctic lakes play an important role in receiving, processing, and storing organic carbon exported from terrestrial ecosystems. To quantify the contribution of Arctic lakes to the global carbon cycle, we developed a one-dimensional process-based Arctic Lake Biogeochemistry Model (ALBM) that explicitly simulates the dynamics of organic and inorganic carbon in Arctic lakes. By realistically modeling water mixing, carbon biogeochemistry, and permafrost carbon loading, the model can reproduce the seasonal variability of CO 2 fluxes from the study Arctic lakes. The simulated area-weighted CO 2 fluxes from yedoma thermokarst lakes, nonyedoma thermokarst lakes, and glacial lakes aremore » 29.5, 13.0, and 21.4 g C m -2 yr -1, respectively, close to the observed values (31.2, 17.2, and 16.5 ± 7.7 g C m -2 yr -1, respectively). The simulations show that the high CO 2 fluxes from yedoma thermokarst lakes are stimulated by the biomineralization of mobilized labile organic carbon from thawing yedoma permafrost. The simulations also imply that the relative contribution of glacial lakes to the global carbon cycle could be the largest because of their much larger surface area and high biomineralization and carbon loading. According to the model, sunlight-induced organic carbon degradation is more important for shallow nonyedoma thermokarst lakes but its overall contribution to the global carbon cycle could be limited. Overall, the ALBM can simulate the whole-lake carbon balance of Arctic lakes, a difficult task for field and laboratory experiments and other biogeochemistry models.« less

Domain size sensitivities of landfalling eastern Pacific atmospheric rivers

NASA Astrophysics Data System (ADS)

McClenny, E. E.; Ullrich, P. A.; Grotjahn, R.; Guan, B.; Waliser, D. E.

2017-12-01

Atmospheric rivers (ARs) concentrate a majority of mid-latitude latent heat transport into narrow bands. ARs making landfall along the North American coast typically originate in the waters surrounding Hawaii. We explore here the effects of explicitly simulating this "genesis region" on AR characteristics. We do this using two models and three domains centered on the North American coast. The Weather Research and Forecast (WRF) model, forced by National Center for Environmental Prediction Final Reanalysis data, provides a representative regional model. The simulation domains include: 1. Just off the coastline (100-130W), 2. The coastline to the Pacific just east of Hawaii (100-155W), and 3. The coastline to the Pacific west of Hawaii (100-180W). The Variable Resolution Community Earth System Model simulates ARs while preserving global interactions. In this global model, "domain" refers to the mesh refinement region, each of which corresponds to one of the three previously described WRF domains. We compare ARs from the wet season (October-April) for water years 2009-2017 in the test models against those found in the Modern Era Retrospective Reanalysis 2 (MERRA2). We objectively detect events with the global AR detection algorithm introduced in Guan and Waliser (2015). Comparisons between all model configurations and the reference MERRA2 data will be assessed by characteristics including landfall location (meridional distributions, including quartile ranges and standard deviations of landfalls across the coast), as well as vapor flux and precipitation (in terms of both the contribution of ARs to the larger regional climatology and any differences in the intensity of individual AR events across runs).

Global Distribution of Cloud Droplet Number Concentration, Autoconversion Rate, and Aerosol Indirect Effect Under Diabatic Droplet Activation

NASA Technical Reports Server (NTRS)

Barahona, Donifan; Sotiropoulou, Rafaella; Nenes, Athanasios

2011-01-01

This study presents a global assessment of the sensitivity of droplet number to diabatic activation (i.e., including effects from entrainment of dry air) and its first-order tendency on indirect forcing and autoconversion. Simulations were carried out with the NASA Global Modeling Initiative (GMI) atmospheric and transport model using climatological metereorological fields derived from the former NASA Data Assimilation Office (DAO), the NASA Finite volume GCM (FVGCM) and the Goddard Institute for Space Studies version II (GISS) GCM. Cloud droplet number concentration (CDNC) is calculated using a physically based prognostic parameterization that explicitly includes entrainment effects on droplet formation. Diabatic activation results in lower CDNC, compared to adiabatic treatment of the process. The largest decrease in CDNC (by up to 75 percent) was found in the tropics and in zones of moderate CCN concentration. This leads to a global mean effective radius increase between 0.2-0.5 micrometers (up to 3.5 micrometers over the tropics), a global mean autoconversion rate increase by a factor of 1.1 to 1.7 (up to a factor of 4 in the tropics), and a 0.2-0.4 W m(exp -2) decrease in indirect forcing. The spatial patterns of entrainment effects on droplet activation tend to reduce biases in effective radius (particularly in the tropics) when compared to satellite retrievals. Considering the diabatic nature of ambient clouds, entrainment effects on CDNC need to be considered in GCM studies of the aerosol indirect effect.

Skills for a Changing World: National Perspectives and the Global Movement

ERIC Educational Resources Information Center

Care, Esther; Kim, Helyn; Anderson, Kate; Gustafsson-Wright, Emily

2017-01-01

The Skills for a Changing World project presents evidence of a movement of education systems globally toward a more explicit focus on a broad range of skills that our 21st century society needs and demands. This movement can be seen in the vision and mission statements of education systems as well as through their curricula. Although clearly…

How universal is the relationship between remotely sensed vegetation indices and crop leaf area index? A global assessment

USDA-ARS?s Scientific Manuscript database

This study aims to assess the relationship between Leaf Area Index (LAI) and remotely sensed Vegetation Indices (VIs) for major crops, based on a globally explicit dataset of in situ LAI measurements over a significant set of locations. We used a total of 1394 LAI measurements from 29 sites spannin...

Global Auroral Energy Deposition Compared with Magnetic Indices

NASA Technical Reports Server (NTRS)

Brittnacher, M. J.; Fillingim, M. O.; Elsen, R.; Parks, G. K.; Germany, G. A.; Spann, J. F., Jr.

1997-01-01

Measurement of the global rate of energy deposition in the ionosphere via auroral particle precipitation is one of the primary goals of the Polar UVI program and is an important component of the ISTP program. The instantaneous rate of energy deposition for the entire month of January 1997 has been calculated by applying models to the UVI images and is presented by Fillingim et al. in this session. Magnetic indices, such as Kp, AE, and Dst, which are sensitive to variations in magnetospheric current systems have been constructed from ground magnetometer measurements and employed as measures of activity. The systematic study of global energy deposition raises the possibility of constructing a global magnetospheric activity index explicitly based on particle precipitation to supplement magnetic indices derived from ground magnetometer measurements. The relationship between global magnetic activity as measured by these indices and the rate of total global energy loss due to precipitation is not known at present. We study the correlation of the traditional magnetic index of Kp for the month of January 1997 with the energy deposition derived from the UVI images. We address the question of whether the energy deposition through particle precipitation generally matches the Kp and AE indices, or the more exciting, but distinct, possibility that this particle-derived index may provide an somewhat independent measure of global magnetospheric activity that could supplement traditional magnetically-based activity indices.

Integrated earth system dynamic modeling for life cycle impact assessment of ecosystem services.

PubMed

Arbault, Damien; Rivière, Mylène; Rugani, Benedetto; Benetto, Enrico; Tiruta-Barna, Ligia

2014-02-15

Despite the increasing awareness of our dependence on Ecosystem Services (ES), Life Cycle Impact Assessment (LCIA) does not explicitly and fully assess the damages caused by human activities on ES generation. Recent improvements in LCIA focus on specific cause-effect chains, mainly related to land use changes, leading to Characterization Factors (CFs) at the midpoint assessment level. However, despite the complexity and temporal dynamics of ES, current LCIA approaches consider the environmental mechanisms underneath ES to be independent from each other and devoid of dynamic character, leading to constant CFs whose representativeness is debatable. This paper takes a step forward and is aimed at demonstrating the feasibility of using an integrated earth system dynamic modeling perspective to retrieve time- and scenario-dependent CFs that consider the complex interlinkages between natural processes delivering ES. The GUMBO (Global Unified Metamodel of the Biosphere) model is used to quantify changes in ES production in physical terms - leading to midpoint CFs - and changes in human welfare indicators, which are considered here as endpoint CFs. The interpretation of the obtained results highlights the key methodological challenges to be solved to consider this approach as a robust alternative to the mainstream rationale currently adopted in LCIA. Further research should focus on increasing the granularity of environmental interventions in the modeling tools to match current standards in LCA and on adapting the conceptual approach to a spatially-explicit integrated model. Copyright © 2013 Elsevier B.V. All rights reserved.

The regional and global significance of nitrogen removal in lakes and reservoirs

USGS Publications Warehouse

Harrison, J.A.; Maranger, R.J.; Alexander, Richard B.; Giblin, A.E.; Jacinthe, P.-A.; Mayorga, Emilio; Seitzinger, S.P.; Sobota, D.J.; Wollheim, W.M.

2009-01-01

Human activities have greatly increased the transport of biologically available nitrogen (N) through watersheds to potentially sensitive coastal ecosystems. Lentic water bodies (lakes and reservoirs) have the potential to act as important sinks for this reactive N as it is transported across the landscape because they offer ideal conditions for N burial in sediments or permanent loss via denitrification. However, the patterns and controls on lentic N removal have not been explored in great detail at large regional to global scales. In this paper we describe, evaluate, and apply a new, spatially explicit, annual-scale, global model of lentic N removal called NiRReLa (Nitrogen Retention in Reservoirs and Lakes). The NiRReLa model incorporates small lakes and reservoirs than have been included in previous global analyses, and also allows for separate treatment and analysis of reservoirs and natural lakes. Model runs for the mid-1990s indicate that lentic systems are indeed important sinks for N and are conservatively estimated to remove 19.7 Tg N year-1 from watersheds globally. Small lakes (<50 km2) were critical in the analysis, retaining almost half (9.3 Tg N year -1) of the global total. In model runs, capacity of lakes and reservoirs to remove watershed N varied substantially at the half-degree scale (0-100%) both as a function of climate and the density of lentic systems. Although reservoirs occupy just 6% of the global lentic surface area, we estimate they retain ~33% of the total N removed by lentic systems, due to a combination of higher drainage ratios (catchment surface area:lake or reservoir surface area), higher apparent settling velocities for N, and greater average N loading rates in reservoirs than in lakes. Finally, a sensitivity analysis of NiRReLa suggests that, on-average, N removal within lentic systems will respond more strongly to changes in land use and N loading than to changes in climate at the global scale. ?? 2008 Springer Science+Business Media B.V.

Enhancing the water management schemes of H08 global hydrological model to attribute human water use to six major water sources

NASA Astrophysics Data System (ADS)

Hanasaki, N.; Yoshikawa, S.; Pokhrel, Y. N.; Kanae, S.

2017-12-01

Humans abstract water from various sources to sustain their livelihood and society. Some global hydrological models (GHMs) include explicit schemes of human water management, but the representation and performance of these schemes remain limited. We substantially enhanced the human water management schemes of the H08 GHM by incorporating the latest data and techniques. The model enables us to estimate water abstraction from six major water sources, namely, river flow regulated by global reservoirs (i.e., reservoirs regulating the flow of the world's major rivers), aqueduct water transfer, local reservoirs, seawater desalination, renewable groundwater, and nonrenewable groundwater. All the interactions were simulated in a single computer program and the water balance was always strictly closed at any place and time during the simulation period. Using this model, we first conducted a historical global hydrological simulation at a spatial resolution of 0.5 x 0.5 degree to specify the sources of water for humanity. The results indicated that, in 2000, of the 3628 km3yr-1 global freshwater requirement, 2839 km3yr-1 was taken from surface water and 789 km3yr-1 from groundwater. Streamflow, aqueduct water transfer, local reservoirs, and seawater desalination accounted for 1786, 199, 106, and 1.8 km3yr-1 of the surface water, respectively. The remaining 747 km3yr-1 freshwater requirement was unmet, or surface water was not available when and where it was needed in our simulation. Renewable and nonrenewable groundwater accounted for 607 and 182 km3yr-1 of the groundwater total, respectively. Second, we evaluated the water stress using our simulations and contrasted it with earlier global assessments based on empirical water scarcity indicators, namely, the Withdrawal to Availability ratio and the Falkenmark index (annual renewable water resources per capita). We found that inclusion of water infrastructures in our model diminished water stress in some parts of the world, on the other hand, daily evaluation of water supply and demand highlighted the temporal/seasonal water deficit due to their variations. The enhanced model is potentially useful for quantitative understanding of the global hydrological cycles including human activities and advancement of global water resources assessment.

Optimized Unlike-Pair Interactions for Water-Carbon Dioxide Mixtures described by the SPC/E and EPM2 Models

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

Vlcek, Lukas; Chialvo, Ariel A; Cole, David

The unlike- pair interaction parameters for the SPC/E- EPM2 models have been optimized to reproduce the mutual solubility of water and carbon dioxide at the conditions of liquid- supercritical fluid phase equilibria. An efficient global optimization of the parameters is achieved through an implementation of the coupling parameter approach, adapted to phase equilibria calculations in the Gibbs ensemble, that explicitly corrects for the over- polarization of the SPC/E water molecule in the non- polar CO2 environments. The resulting H2O- CO2 force field reproduces accurately the available experimental solubilities at the two fluid phases in equilibria as well as the correspondingmore » species tracer diffusion coefficients.« less

Towards a new paleotemperature proxy from reef coral occurrences.

PubMed

Lauchstedt, Andreas; Pandolfi, John M; Kiessling, Wolfgang

2017-09-05

Global mean temperature is thought to have exceeded that of today during the last interglacial episode (LIG, ~ 125,000 yrs b.p.) but robust paleoclimate data are still rare in low latitudes. Occurrence data of tropical reef corals may provide new proxies of low latitude sea-surface temperatures. Using modern reef coral distributions we developed a geographically explicit model of sea surface temperatures. Applying this model to coral occurrence data of the LIG provides a latitudinal U-shaped pattern of temperature anomalies with cooler than modern temperatures around the equator and warmer subtropical climes. Our results agree with previously published estimates of LIG temperatures and suggest a poleward broadening of the habitable zone for reef corals during the LIG.

Supersymmetric dS/CFT

NASA Astrophysics Data System (ADS)

Hertog, Thomas; Tartaglino-Mazzucchelli, Gabriele; Van Riet, Thomas; Venken, Gerben

2018-02-01

We put forward new explicit realisations of dS/CFT that relate N = 2 supersymmetric Euclidean vector models with reversed spin-statistics in three dimensions to specific supersymmetric Vasiliev theories in four-dimensional de Sitter space. The partition function of the free supersymmetric vector model deformed by a range of low spin deformations that preserve supersymmetry appears to specify a well-defined wave function with asymptotic de Sitter boundary conditions in the bulk. In particular we find the wave function is globally peaked at undeformed de Sitter space, with a low amplitude for strong deformations. This suggests that supersymmetric de Sitter space is stable in higher-spin gravity and in particular free from ghosts. We speculate this is a limiting case of the de Sitter realizations in exotic string theories.

Effects of cumulus entrainment and multiple cloud types on a January global climate model simulation

NASA Technical Reports Server (NTRS)

Yao, Mao-Sung; Del Genio, Anthony D.

1989-01-01

An improved version of the GISS Model II cumulus parameterization designed for long-term climate integrations is used to study the effects of entrainment and multiple cloud types on the January climate simulation. Instead of prescribing convective mass as a fixed fraction of the cloud base grid-box mass, it is calculated based on the closure assumption that the cumulus convection restores the atmosphere to a neutral moist convective state at cloud base. This change alone significantly improves the distribution of precipitation, convective mass exchanges, and frequencies in the January climate. The vertical structure of the tropical atmosphere exhibits quasi-equilibrium behavior when this closure is used, even though there is no explicit constraint applied above cloud base.

Epidemic spreading on random surfer networks with optimal interaction radius

NASA Astrophysics Data System (ADS)

Feng, Yun; Ding, Li; Hu, Ping

2018-03-01

In this paper, the optimal control problem of epidemic spreading on random surfer heterogeneous networks is considered. An epidemic spreading model is established according to the classification of individual's initial interaction radii. Then, a control strategy is proposed based on adjusting individual's interaction radii. The global stability of the disease free and endemic equilibrium of the model is investigated. We prove that an optimal solution exists for the optimal control problem and the explicit form of which is presented. Numerical simulations are conducted to verify the correctness of the theoretical results. It is proved that the optimal control strategy is effective to minimize the density of infected individuals and the cost associated with the adjustment of interaction radii.

Global off-line evaluation of the ISBA-TRIP continental hydrological system used in the CNRM-CM6 climate model for the next CMIP6 exercise

NASA Astrophysics Data System (ADS)

Decharme, Bertrand; Vergnes, Jean-Pierre; Minvielle, Marie; Colin, Jeanne; Delire, Christine

2016-04-01

The land surface hydrology represents an active component of the climate system. It is likely to influence the water and energy exchanges at the land surface, the ocean salinity and temperature at the mouth of the largest rivers, and the climate at least at the regional scale. In climate models, the continental hydrology is simulated via Land Surface Models (LSM), which compute water and energy budgets at the surface, coupled to River Routing Model (RRM), which convert the runoff simulated by the LSMs into river discharge in order to transfer the continental fresh water into the oceans and then to close the global hydrological cycle. Validating these Continental Hydrological Systems (CHS) at the global scale is therefore a crucial task, which requires off-line simulations driven by realistic atmospheric fluxes to avoid the systematic biases commonly found in the atmospheric models. In the CNRM-CM6 climate model of Météo-France, that will be used for the next Coupled Climate Intercomparison Project phase 6 (CMIP6) exercise, the land surface hydrology is simulated using the ISBA-TRIP CHS coupled via the OASIS-MCT coupler. The ISBA LSM solves explicitly the one dimensional Fourier law for soil temperature and the mixed form of the Richards equation for soil moisture using a 14-layers discretization over 12m depths. For the snowpack, a discretization using 12 layers allows the explicit representation of some snow key processes as its viscosity, its compaction due to wind, its age and its albedo on the visible and near infrared spectra. The TRIP RRM uses a global river channel network at 0.5° resolution. It is based on a three prognostic equations for the surface stream water, the seasonal floodplains, and the groundwater. The streamflow velocity is computed using the Maning's formula. The floodplain reservoir fills when the river height exceeds the river bankfull height and vice-versa. The flood interacts with the ISBA soil hydrology through infiltration and with the overlying atmosphere through precipitation interception and free water surface evaporation. Finally, the groundwater scheme is based on the two-dimensional groundwater flow equation for the piezometric head. Its coupling with ISBA permits to account for the presence of a water table under the soil moisture column allowing upward capillarity fluxes into the soil. In this study, we will present the off-line evaluation at the global scale of the ISBA-TRIP CHS over a recent period (1979-2010). The system will be compared to observations such as GRACE (Gravity Recovery and Climate Experiment) terrestrial water storage data, snow and permafrost extents from NSIDC (National Snow and Ice Data Center), or in-situ river discharge measurements from several sources. In addition we will also explore the impacts on the simulated water budget to account for some processes such as upward capillarity fluxes from groundwaters or seasonal floodplains. At last, it is envisaged to discuss some results about land/atmosphere interactions induced by these processes in the CNRM-CM6 climate model.

A Machine Learning Approach to Predicted Bathymetry

NASA Astrophysics Data System (ADS)

Wood, W. T.; Elmore, P. A.; Petry, F.

2017-12-01

Recent and on-going efforts have shown how machine learning (ML) techniques, incorporating more, and more disparate data than can be interpreted manually, can predict seafloor properties, with uncertainty, where they have not been measured directly. We examine here a ML approach to predicted bathymetry. Our approach employs a paradigm of global bathymetry as an integral component of global geology. From a marine geology and geophysics perspective the bathymetry is the thickness of one layer in an ensemble of layers that inter-relate to varying extents vertically and geospatially. The nature of the multidimensional relationships in these layers between bathymetry, gravity, magnetic field, age, and many other global measures is typically geospatially dependent and non-linear. The advantage of using ML is that these relationships need not be stated explicitly, nor do they need to be approximated with a transfer function - the machine learns them via the data. Fundamentally, ML operates by brute-force searching for multidimensional correlations between desired, but sparsely known data values (in this case water depth), and a multitude of (geologic) predictors. Predictors include quantities known extensively such as remotely sensed measurements (i.e. gravity and magnetics), distance from spreading ridge, trench etc., (and spatial statistics based on these quantities). Estimating bathymetry from an approximate transfer function is inherently model, as well as data limited - complex relationships are explicitly ruled out. The ML is a purely data-driven approach, so only the extent and quality of the available observations limit prediction accuracy. This allows for a system in which new data, of a wide variety of types, can be quickly and easily assimilated into updated bathymetry predictions with quantitative posterior uncertainties.

Creating a spatially-explicit index: a method for assessing the global wildfire-water risk

NASA Astrophysics Data System (ADS)

Robinne, François-Nicolas; Parisien, Marc-André; Flannigan, Mike; Miller, Carol; Bladon, Kevin D.

2017-04-01

The wildfire-water risk (WWR) has been defined as the potential for wildfires to adversely affect water resources that are important for downstream ecosystems and human water needs for adequate water quantity and quality, therefore compromising the security of their water supply. While tools and methods are numerous for watershed-scale risk analysis, the development of a toolbox for the large-scale evaluation of the wildfire risk to water security has only started recently. In order to provide managers and policy-makers with an adequate tool, we implemented a method for the spatial analysis of the global WWR based on the Driving forces-Pressures-States-Impacts-Responses (DPSIR) framework. This framework relies on the cause-and-effect relationships existing between the five categories of the DPSIR chain. As this approach heavily relies on data, we gathered an extensive set of spatial indicators relevant to fire-induced hydrological hazards and water consumption patterns by human and natural communities. When appropriate, we applied a hydrological routing function to our indicators in order to simulate downstream accumulation of potentially harmful material. Each indicator was then assigned a DPSIR category. We collapsed the information in each category using a principal component analysis in order to extract the most relevant pixel-based information provided by each spatial indicator. Finally, we compiled our five categories using an additive indexation process to produce a spatially-explicit index of the WWR. A thorough sensitivity analysis has been performed in order to understand the relationship between the final risk values and the spatial pattern of each category used during the indexation. For comparison purposes, we aggregated index scores by global hydrological regions, or hydrobelts, to get a sense of regional DPSIR specificities. This rather simple method does not necessitate the use of complex physical models and provides a scalable and efficient tool for the analysis of global water security issues.

Fate of global symmetries in the Universe: QCD axion, quintessential axion and trans-Planckian inflaton decay constant

NASA Astrophysics Data System (ADS)

Kim, Jihn E.; Nam, Soonkeon; Semetzidis, Yannis K.

2018-01-01

Pseudoscalars appearing in particle physics are reviewed systematically. From the fundamental point of view at an ultraviolet completed theory, they can be light if they are realized as pseudo-Goldstone bosons of some spontaneously broken global symmetries. The spontaneous breaking scale is parametrized by the decay constant f. The global symmetry is defined by the lowest order terms allowed in the effective theory consistent with the gauge symmetry in question. Since any global symmetry is known to be broken at least by quantum gravitational effects, all pseudoscalars should be massive. The mass scale is determined by f and the explicit breaking terms ΔV in the effective potential and also anomaly terms ΔΛG4 for some non-Abelian gauge groups G. The well-known example by non-Abelian gauge group breaking is the potential for the “invisible” QCD axion, via the Peccei-Quinn symmetry, which constitutes a major part of this review. Even if there is no breaking terms from gauge anomalies, there can be explicit breaking terms ΔV in the potential in which case the leading term suppressed by f determines the pseudoscalar mass scale. If the breaking term is extremely small and the decay constant is trans-Planckian, the corresponding pseudoscalar can be a candidate for a “quintessential axion.” In general, (ΔV )1/4 is considered to be smaller than f, and hence the pseudo-Goldstone boson mass scales are considered to be smaller than the decay constants. In such a case, the potential of the pseudo-Goldstone boson at the grand unification scale is sufficiently flat near the top of the potential that it can be a good candidate for an inflationary model, which is known as “natural inflation.” We review all these ideas in the bosonic collective motion framework.

Effects of Explicit Instructions, Metacognition, and Motivation on Creative Performance

ERIC Educational Resources Information Center

Hong, Eunsook; O'Neil, Harold F.; Peng, Yun

2016-01-01

Effects of explicit instructions, metacognition, and intrinsic motivation on creative homework performance were examined in 303 Chinese 10th-grade students. Models that represent hypothesized relations among these constructs and trait covariates were tested using structural equation modelling. Explicit instructions geared to originality were…

The distribution of soil phosphorus for global biogeochemical modeling

DOE PAGES

Yang, Xiaojuan; Post, Wilfred M.; Thornton, Peter E.; ...

2013-04-16

We discuss that phosphorus (P) is a major element required for biological activity in terrestrial ecosystems. Although the total P content in most soils can be large, only a small fraction is available or in an organic form for biological utilization because it is bound either in incompletely weathered mineral particles, adsorbed on mineral surfaces, or, over the time of soil formation, made unavailable by secondary mineral formation (occluded). In order to adequately represent phosphorus availability in global biogeochemistry–climate models, a representation of the amount and form of P in soils globally is required. We develop an approach that buildsmore » on existing knowledge of soil P processes and databases of parent material and soil P measurements to provide spatially explicit estimates of different forms of naturally occurring soil P on the global scale. We assembled data on the various forms of phosphorus in soils globally, chronosequence information, and several global spatial databases to develop a map of total soil P and the distribution among mineral bound, labile, organic, occluded, and secondary P forms in soils globally. The amount of P, to 50cm soil depth, in soil labile, organic, occluded, and secondary pools is 3.6 ± 3, 8.6 ± 6, 12.2 ± 8, and 3.2 ± 2 Pg P (Petagrams of P, 1 Pg = 1 × 10 15g) respectively. The amount in soil mineral particles to the same depth is estimated at 13.0 ± 8 Pg P for a global soil total of 40.6 ± 18 Pg P. The large uncertainty in our estimates reflects our limited understanding of the processes controlling soil P transformations during pedogenesis and a deficiency in the number of soil P measurements. In spite of the large uncertainty, the estimated global spatial variation and distribution of different soil P forms presented in this study will be useful for global biogeochemistry models that include P as a limiting element in biological production by providing initial estimates of the available soil P for plant uptake and microbial utilization.« less

Assessment of parametric uncertainty for groundwater reactive transport modeling,

USGS Publications Warehouse

Shi, Xiaoqing; Ye, Ming; Curtis, Gary P.; Miller, Geoffery L.; Meyer, Philip D.; Kohler, Matthias; Yabusaki, Steve; Wu, Jichun

2014-01-01

The validity of using Gaussian assumptions for model residuals in uncertainty quantification of a groundwater reactive transport model was evaluated in this study. Least squares regression methods explicitly assume Gaussian residuals, and the assumption leads to Gaussian likelihood functions, model parameters, and model predictions. While the Bayesian methods do not explicitly require the Gaussian assumption, Gaussian residuals are widely used. This paper shows that the residuals of the reactive transport model are non-Gaussian, heteroscedastic, and correlated in time; characterizing them requires using a generalized likelihood function such as the formal generalized likelihood function developed by Schoups and Vrugt (2010). For the surface complexation model considered in this study for simulating uranium reactive transport in groundwater, parametric uncertainty is quantified using the least squares regression methods and Bayesian methods with both Gaussian and formal generalized likelihood functions. While the least squares methods and Bayesian methods with Gaussian likelihood function produce similar Gaussian parameter distributions, the parameter distributions of Bayesian uncertainty quantification using the formal generalized likelihood function are non-Gaussian. In addition, predictive performance of formal generalized likelihood function is superior to that of least squares regression and Bayesian methods with Gaussian likelihood function. The Bayesian uncertainty quantification is conducted using the differential evolution adaptive metropolis (DREAM(zs)) algorithm; as a Markov chain Monte Carlo (MCMC) method, it is a robust tool for quantifying uncertainty in groundwater reactive transport models. For the surface complexation model, the regression-based local sensitivity analysis and Morris- and DREAM(ZS)-based global sensitivity analysis yield almost identical ranking of parameter importance. The uncertainty analysis may help select appropriate likelihood functions, improve model calibration, and reduce predictive uncertainty in other groundwater reactive transport and environmental modeling.

Microbial processes in marine ecosystem models: state of the art and future prospective

NASA Astrophysics Data System (ADS)

Polimene, L.; Butenschon, M.; Blackford, J.; Allen, I.

2012-12-01

Heterotrophic bacteria play a key role in the marine biogeochemistry being the main consumer of dissolved organic matter (DOM) and the main producer of carbon dioxide (CO2) by respiration. Quantifying the carbon and energy fluxes within bacteria (i.e. production, respiration, overflow metabolism etc.) is therefore crucial for the assessment of the global ocean carbon and nutrient cycles. Consequently, the description of bacteria dynamic in ecosystem models is a key (although challenging) issue which cannot be overlooked if we want to properly simulate the marine environment. We present an overview of the microbial processes described in the European Sea Regional Ecosystem Model (ERSEM), a state of the art biogeochemical model resolving carbon and nutrient cycles (N, P, Si and Fe) within the low trophic levels (up to mesozooplankton) of the marine ecosystem. The description of the theoretical assumptions and philosophy underpinning the ERSEM bacteria sub-model will be followed by the presentation of some case studies highlighting the relevance of resolving microbial processes in the simulation of ecosystem dynamics at a local scale. Recent results concerning the implementation of ERSEM on a global ocean domain will be also presented. This latter exercise includes a comparison between simulations carried out with the full bacteria sub-model and simulations carried out with an implicit parameterization of bacterial activity. The results strongly underline the importance of explicitly resolved bacteria in the simulation of global carbon fluxes. Finally, a summary of the future developments along with issues still open on the topic will be presented and discussed.

Development of a global aerosol model using a two-dimensional sectional method: 1. Model design

NASA Astrophysics Data System (ADS)

Matsui, H.

2017-08-01

This study develops an aerosol module, the Aerosol Two-dimensional bin module for foRmation and Aging Simulation version 2 (ATRAS2), and implements the module into a global climate model, Community Atmosphere Model. The ATRAS2 module uses a two-dimensional (2-D) sectional representation with 12 size bins for particles from 1 nm to 10 μm in dry diameter and 8 black carbon (BC) mixing state bins. The module can explicitly calculate the enhancement of absorption and cloud condensation nuclei activity of BC-containing particles by aging processes. The ATRAS2 module is an extension of a 2-D sectional aerosol module ATRAS used in our previous studies within a framework of a regional three-dimensional model. Compared with ATRAS, the computational cost of the aerosol module is reduced by more than a factor of 10 by simplifying the treatment of aerosol processes and 2-D sectional representation, while maintaining good accuracy of aerosol parameters in the simulations. Aerosol processes are simplified for condensation of sulfate, ammonium, and nitrate, organic aerosol formation, coagulation, and new particle formation processes, and box model simulations show that these simplifications do not substantially change the predicted aerosol number and mass concentrations and their mixing states. The 2-D sectional representation is simplified (the number of advected species is reduced) primarily by the treatment of chemical compositions using two interactive bin representations. The simplifications do not change the accuracy of global aerosol simulations. In part 2, comparisons with measurements and the results focused on aerosol processes such as BC aging processes are shown.

Drivers And Uncertainties Of Increasing Global Water Scarcity

NASA Astrophysics Data System (ADS)

Scherer, L.; Pfister, S.

2015-12-01

Water scarcity threatens ecosystems and human health and hampers economic development. It generally depends on the ratio of water consumption to availability. We calculated global, spatially explicit water stress indices (WSIs) which describe the vulnerability to additional water consumption on a scale from 0 (low) to 1 (high) and compare them for the decades 1981-1990 and 2001-2010. Input data are obtained from a multi-model ensemble at a resolution of 0.5 degrees. The variability among the models was used to run 1000 Monte Carlo simulations (latin hypercube sampling) and to subsequently estimate uncertainties of the WSIs. Globally, a trend of increasing water scarcity can be observed, however, uncertainties are large. The probability that this trend is actually occurring is as low as 53%. The increase in WSIs is rather driven by higher water use than lower water availability. Water availability is only 40% likely to decrease whereas water consumption is 67% likely to increase. Independent from the trend, we are already living under water scarce conditions, which is reflected in a consumption-weighted average of monthly WSIs of 0.51 in the recent decade. Its coefficient of variation points with 0.8 to the high uncertainties entailed, which might still hide poor model performance where all models consistently over- or underestimate water availability or use. Especially in arid areas, models generally overestimate availability. Although we do not traverse the planetary boundary of freshwater use as global water availability is sufficient, local water scarcity might be high. Therefore the regionalized assessment of WSIs under uncertainty helps to focus on specific regions to optimise water consumption. These global results can also help to raise awareness of water scarcity, and to suggest relevant measures such as more water efficient technologies to international companies, which have to deal with complex and distributed supply chains (e.g. in food production).

The Critical Role of the Routing Scheme in Simulating Peak River Discharge in Global Hydrological Models

NASA Technical Reports Server (NTRS)

Zhao, Fang; Veldkamp, Ted I. E.; Frieler, Katja; Schewe, Jacob; Ostberg, Sebastian; Willner, Sven; Schauberger, Bernhard; Gosling, Simon N.; Schmied, Hannes Muller; Portmann, Felix T.;

Transdimensional Bayesian tomography of the lowermost mantle from shear waves

NASA Astrophysics Data System (ADS)

Richardson, C.; Mousavi, S. S.; Tkalcic, H.; Masters, G.

2017-12-01

The lowermost layer of the mantle, known as D'', is a complex region that contains significant heterogeneities on different spatial scales and a wide range of physical and chemical features such as partial melting, seismic anisotropy, and variations in thermal and chemical composition. The most powerful tools we have to probe this region are seismic waves and corresponding imaging techniques such as tomography. Recently, we developed compressional velocity tomograms of D'' using a transdimensional Bayesian inversion, where the model parameterization is not explicit and regularization is not required. This has produced a far more nuanced P-wave velocity model of D'' than that from traditional S-wave tomography. We also note that P-wave models of D'' vary much more significantly among various research groups than the corresponding S-wave models. This study therefore seeks to develop a new S-wave velocity model of D'' underneath Australia by using predominantly ScS-S differential travel times measured through waveform correlation and Bayesian transdimensional inversion to further understand and characterize heterogeneities in D''. We used events at epicentral distances between 45 and 75 degrees from stations in Australia at depths of over 200 km and with magnitudes between 6.0 and 6.7. Because of globally incomplete coverage of station and earthquake locations, a major limitation of deep earth tomography has been the explicit parameterization of the region of interest. Explicit parameterization has been foundational in most studies, but faces inherent problems of either over-smoothing the data, or allowing for too much noise. To avoid this, we use spherical Voronoi polygons, which allow for a high level of flexibility as the polygons can grow, shrink, or be altogether deleted throughout a sequence of iterations. Our technique also yields highly desired model parameter uncertainties. While there is little doubt that D'' is heterogeneous, there is still much that is unclear about the extent and spatial distribution of different heterogeneous domains, as there are open questions about their dynamics and chemical interactions in the context of the surrounding mantle and outer core. In this context, our goal is also to quantify and understand the differences between S-wave and P-wave velocity tomographic models.

Spectral Analysis of Forecast Error Investigated with an Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Prive, N. C.; Errico, Ronald M.

2015-01-01

The spectra of analysis and forecast error are examined using the observing system simulation experiment (OSSE) framework developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASAGMAO). A global numerical weather prediction model, the Global Earth Observing System version 5 (GEOS-5) with Gridpoint Statistical Interpolation (GSI) data assimilation, is cycled for two months with once-daily forecasts to 336 hours to generate a control case. Verification of forecast errors using the Nature Run as truth is compared with verification of forecast errors using self-analysis; significant underestimation of forecast errors is seen using self-analysis verification for up to 48 hours. Likewise, self analysis verification significantly overestimates the error growth rates of the early forecast, as well as mischaracterizing the spatial scales at which the strongest growth occurs. The Nature Run-verified error variances exhibit a complicated progression of growth, particularly for low wave number errors. In a second experiment, cycling of the model and data assimilation over the same period is repeated, but using synthetic observations with different explicitly added observation errors having the same error variances as the control experiment, thus creating a different realization of the control. The forecast errors of the two experiments become more correlated during the early forecast period, with correlations increasing for up to 72 hours before beginning to decrease.

GLOFRIM - A globally applicable framework for integrated hydrologic-hydrodynamic inundation modelling

NASA Astrophysics Data System (ADS)

Hoch, J. M.; Neal, J. C.; Baart, F.; Van Beek, L. P.; Winsemius, H.; Bates, P. D.; Bierkens, M. F.

2017-12-01

Currently, many approaches to provide detailed flood hazard and risk estimates are built upon specific hydrologic or hydrodynamic model routines. By applying these routines in stand-alone mode important processes can however not accurately be described. For instance, global hydrologic models run at coarse spatial resolution, not supporting the detailed simulation of flood hazard. Hydrodynamic models excel in the computations of open water flow dynamics, but dependent on specific runoff or observed discharge as input. In most cases hydrodynamic models are forced at the boundaries and thus cannot account for water sources within the model domain, limiting the simulation of inundation dynamics to reaches fed by upstream boundaries. Recently, Hoch et al. (HESS, 2017) coupled PCR-GLOBWB (PCR) with the hydrodynamic model Delft3D Flexible Mesh (DFM). By means of the Basic Model Interface both models were connected on a cell-by-cell basis, allowing for spatially explicit coupling. Model results showed that discharge simulations can profit from model coupling compared to stand-alone runs. As model results of a coupled simulation depend on the quality of the models, it would be worthwhile to allow a suite of models to be coupled. To facilitate this, we present GLOFRIM, a globally applicable framework for integrated hydrologic-hydrodynamic inundation modelling. In the current version coupling between PCR and both DFM and LISFLOOD-FP (LFP) can be established (Hoch et al., GMDD, 2017). First results show that differences between both hydrodynamic models are present in the timing of peak discharge which is most likely due to differences in channel-floodplain interactions and bathymetry processing. Having benchmarked inundation extent, LFP and DFM agree for around half of the inundated area which is attributable to variations in grid size. Results also indicate that, despite using identical boundary conditions and forcing, the schematization itself as well as internal processes can still greatly influence results. In general, the application of GLOFRIM brings several advantages. For example, with PCR being a global model, it is possible to reduce the dependency of observation data for discharge boundaries, and benchmarking of hydrodynamic models is greatly facilitated by employing identical hydrologic forcing.

Modeling the Space-Time Destiny of Pan-Arctic Permafrost DOC in a Global Land Surface Model: Feedback Implications

NASA Astrophysics Data System (ADS)

Bowring, S.; Lauerwald, R.; Guenet, B.; Zhu, D.; Ciais, P.

2017-12-01

Most global climate models do not represent the unique permafrost soil environment and its respective processes. This significantly contributes to uncertainty in estimating their responses, and that of the planet at large, to warming. Here, the production, transport and atmospheric release of dissolved organic carbon (DOC) from high-latitude permafrost soils into inland waters and the ocean is explicitly represented for the first time in the land surface component (ORCHIDEE-MICT) of a CMIP6 global climate model (IPSL). This work merges two models that are able to mechanistically simulate complex processes for 1) snow, ice and soil phenomena in high latitude environments, and 2) DOC production and lateral transport through soils and the river network, respectively, at 0.5° to 2° resolution. The resulting model is subjected to a wide range of input forcing data, parameter testing and contentious feedback phenomena, including microbial heat generation as the active layer deepens. We present results for the present and future Pan-Arctic and Eurasia, with a focus on the Lena and Mackenzie River basins, and show that soil DOC concentrations, their riverine transport and atmospheric evasion are reasonably well represented as compared to observed stocks, fluxes and seasonality. We show that most basins exhibit large increases in DOC transport and riverine CO2 evasion across the suite of RCP scenarios to 2100. We also show that model output is strongly influenced by choice of input forcing data. The riverine component of what is known as the `boundless carbon cycle' is little-recognized in global climate modeling. Hydrological mobilization to the river network results either in sedimentary settling or atmospheric `evasion', presently amounting to 0.5-1.8 PgC yr-1. Our work aims at filling in these knowledge gaps, and the response of these DOC-related processes to thermal forcing. Potential feedbacks owing to such a response are of particular relevance, given the magnitude of the permafrost carbon pool.

The ecological module of BOATS-1.0: a bioenergetically-constrained model of marine upper trophic levels suitable for studies of fisheries and ocean biogeochemistry

NASA Astrophysics Data System (ADS)

Carozza, D. A.; Bianchi, D.; Galbraith, E. D.

2015-12-01

Environmental change and the exploitation of marine resources have had profound impacts on marine communities, with potential implications for ocean biogeochemistry and food security. In order to study such global-scale problems, it is helpful to have computationally efficient numerical models that predict the first-order features of fish biomass production as a function of the environment, based on empirical and mechanistic understandings of marine ecosystems. Here we describe the ecological module of the BiOeconomic mArine Trophic Size-spectrum (BOATS) model, which takes an Earth-system approach to modeling fish biomass at the global scale. The ecological model is designed to be used on an Earth System model grid, and determines size spectra of fish biomass by explicitly resolving life history as a function of local temperature and net primary production. Biomass production is limited by the availability of photosynthetic energy to upper trophic levels, following empirical trophic efficiency scalings, and by well-established empirical temperature-dependent growth rates. Natural mortality is calculated using an empirical size-based relationship, while reproduction and recruitment depend on both the food availability to larvae from net primary production and the production of eggs by mature adult fish. We describe predicted biomass spectra and compare them to observations, and conduct a sensitivity study to determine how the change as a function of net primary production and temperature. The model relies on a limited number of parameters compared to similar modeling efforts, while retaining realistic representations of biological and ecological processes, and is computationally efficient, allowing extensive parameter-space analyses even when implemented globally. As such, it enables the exploration of the linkages between ocean biogeochemistry, climate, and upper trophic levels at the global scale, as well as a representation of fish biomass for idealized studies of fisheries.

The global aerosol-climate model ECHAM-HAM, version 2: sensitivity to improvements in process representations

NASA Astrophysics Data System (ADS)

Zhang, K.; O'Donnell, D.; Kazil, J.; Stier, P.; Kinne, S.; Lohmann, U.; Ferrachat, S.; Croft, B.; Quaas, J.; Wan, H.; Rast, S.; Feichter, J.

2012-03-01

This paper introduces and evaluates the second version of the global aerosol-climate model ECHAM-HAM. Major changes have been brought into the model, including new parameterizations for aerosol nucleation and water uptake, an explicit treatment of secondary organic aerosols, modified emission calculations for sea salt and mineral dust, the coupling of aerosol microphysics to a two-moment stratiform cloud microphysics scheme, and alternative wet scavenging parameterizations. These revisions extend the model's capability to represent details of the aerosol lifecycle and its interaction with climate. Sensitivity experiments are carried out to analyse the effects of these improvements in the process representation on the simulated aerosol properties and global distribution. The new parameterizations that have largest impact on the global mean aerosol optical depth and radiative effects turn out to be the water uptake scheme and cloud microphysics. The former leads to a significant decrease of aerosol water contents in the lower troposphere, and consequently smaller optical depth; the latter results in higher aerosol loading and longer lifetime due to weaker in-cloud scavenging. The combined effects of the new/updated parameterizations are demonstrated by comparing the new model results with those from the earlier version, and against observations. Model simulations are evaluated in terms of aerosol number concentrations against measurements collected from twenty field campaigns as well as from fixed measurement sites, and in terms of optical properties against the AERONET measurements. Results indicate a general improvement with respect to the earlier version. The aerosol size distribution and spatial-temporal variance simulated by HAM2 are in better agreement with the observations. Biases in the earlier model version in aerosol optical depth and in the Ångström parameter have been reduced. The paper also points out the remaining model deficiencies that need to be addressed in the future.

The ecological module of BOATS-1.0: a bioenergetically constrained model of marine upper trophic levels suitable for studies of fisheries and ocean biogeochemistry

NASA Astrophysics Data System (ADS)

Carozza, David Anthony; Bianchi, Daniele; Galbraith, Eric Douglas

2016-04-01

Environmental change and the exploitation of marine resources have had profound impacts on marine communities, with potential implications for ocean biogeochemistry and food security. In order to study such global-scale problems, it is helpful to have computationally efficient numerical models that predict the first-order features of fish biomass production as a function of the environment, based on empirical and mechanistic understandings of marine ecosystems. Here we describe the ecological module of the BiOeconomic mArine Trophic Size-spectrum (BOATS) model, which takes an Earth-system approach to modelling fish biomass at the global scale. The ecological model is designed to be used on an Earth-system model grid, and determines size spectra of fish biomass by explicitly resolving life history as a function of local temperature and net primary production. Biomass production is limited by the availability of photosynthetic energy to upper trophic levels, following empirical trophic efficiency scalings, and by well-established empirical temperature-dependent growth rates. Natural mortality is calculated using an empirical size-based relationship, while reproduction and recruitment depend on both the food availability to larvae from net primary production and the production of eggs by mature adult fish. We describe predicted biomass spectra and compare them to observations, and conduct a sensitivity study to determine how they change as a function of net primary production and temperature. The model relies on a limited number of parameters compared to similar modelling efforts, while retaining reasonably realistic representations of biological and ecological processes, and is computationally efficient, allowing extensive parameter-space analyses even when implemented globally. As such, it enables the exploration of the linkages between ocean biogeochemistry, climate, and upper trophic levels at the global scale, as well as a representation of fish biomass for idealized studies of fisheries.

Social justice and the global economy: new challenges for social work in the 21st century.

PubMed

Polack, Robert J

2004-04-01

The globalization of the economy creates new challenges for social work in the arenas of social and economic justice. This article outlines social justice issues related to the debt crisis of the Global South and sweatshops. A presentation of colonial precursors is followed by a detailed examination of these global institutions with an emphasis on the vulnerability, disempowered status, and exploitation of poor people of the Global South. Connections with global inequities in wealth, income, and the distribution of resources are made explicit. The article explores domestic social justice problems as possible points of connection with these issues. Finally, the authors give recommendations for social work education, advocacy, and activism.

Climate Modeling and Analysis with Decision Makers in Mind

NASA Astrophysics Data System (ADS)

Jones, A. D.; Jagannathan, K.; Calvin, K. V.; Lamarque, J. F.; Ullrich, P. A.

2016-12-01

There is a growing need for information about future climate conditions to support adaptation planning across a wide range of sectors and stakeholder communities. However, our principal tools for understanding future climate - global Earth system models - were not developed with these user needs in mind, nor have we developed transparent methods for evaluating and communicating the credibility of various climate information products with respect to the climate characteristics that matter most to decision-makers. Several recent community engagements have identified a need for "co-production" of knowledge among stakeholders and scientists. Here we highlight some of the barriers to communication and collaboration that must be overcome to improve the dialogue among researchers and climate adaptation practitioners in a meaningful way. Solutions to this challenge are two-fold: 1) new institutional arrangements and collaborative mechanisms designed to improve coordination and understanding among communities, and 2) a research agenda that explicitly incorporates stakeholder needs into model evaluation, development, and experimental design. We contrast the information content in global-scale model evaluation exercises with that required for in specific decision contexts, such as long-term agricultural management decisions. Finally, we present a vision for advancing the science of model evaluation in the context of predicting decision-relevant hydroclimate regime shifts in North America.

Rhizosphere Processes Are Quantitatively Important Components of Terrestrial Biogeochemical Cycles: Data & Models

NASA Astrophysics Data System (ADS)

Finzi, A.

2016-12-01

The rhizosphere is a hot spot and hot moment for biogeochemical cycles. Microbial activity, extracellular enzyme activity and element cycles are greatly enhanced by root derived carbon inputs. As such the rhizosphere may be an important driver of ecosystem responses to global changes such as rising temperatures and atmospheric CO2 concentrations. Empirical research on the rhizosphere is extensive but extrapolation of rhizosphere processes to large spatial and temporal scales is largely uninterrogated. Using a combination of field studies, meta-analysis and numerical models we have found good reason to think that scaling is possible. In this talk I discuss the results of this research and focus on the results of a new modeling effort that explicitly links root distribution and architecture with a model of microbial physiology to assess the extent to which rhizosphere processes may affect ecosystem responses to global change. Results to date suggest that root inputs of C and possibly nutrients (ie, nitrogen) impact the fate of new C inputs to the soil (ie, accumulation or loss) in response to warming and enhanced productivity at elevated CO2. The model also provides qualitative guidance on incorporating the known effects of ectomycorrhizal fungi on decomposition and rates of soil C and N cycling.

Impact of capturing rainfall scavenging intermittency using cloud superparameterization on simulated continental scale wildfire smoke transport

NASA Astrophysics Data System (ADS)

Pritchard, M. S.; Kooperman, G. J.; Zhao, Z.; Wang, M.; Russell, L. M.; Somerville, R. C.; Ghan, S. J.

2011-12-01

Evaluating the fidelity of new aerosol physics in climate models is confounded by uncertainties in source emissions, systematic error in cloud parameterizations, and inadequate sampling of long-range plume concentrations. To explore the degree to which cloud parameterizations distort aerosol processing and scavenging, the Pacific Northwest National Laboratory (PNNL) Aerosol-Enabled Multi-Scale Modeling Framework (AE-MMF), a superparameterized branch of the Community Atmosphere Model Version 5 (CAM5), is applied to represent the unusually active and well sampled North American wildfire season in 2004. In the AE-MMF approach, the evolution of double moment aerosols in the exterior global resolved scale is linked explicitly to convective statistics harvested from an interior cloud resolving scale. The model is configured in retroactive nudged mode to observationally constrain synoptic meteorology, and Arctic wildfire activity is prescribed at high space/time resolution using data from the Global Fire Emissions Database. Comparisons against standard CAM5 bracket the effect of superparameterization to isolate the role of capturing rainfall intermittency on the bulk characteristics of 2004 Arctic plume transport. Ground based lidar and in situ aircraft wildfire plume constraints from the International Consortium for Atmospheric Research on Transport and Transformation field campaign are used as a baseline for model evaluation.

An agent-based approach to modelling the effects of extreme events on global food prices

NASA Astrophysics Data System (ADS)

Schewe, Jacob; Otto, Christian; Frieler, Katja

2015-04-01

Extreme climate events such as droughts or heat waves affect agricultural production in major food producing regions and therefore can influence the price of staple foods on the world market. There is evidence that recent dramatic spikes in grain prices were at least partly triggered by actual and/or expected supply shortages. The reaction of the market to supply changes is however highly nonlinear and depends on complex and interlinked processes such as warehousing, speculation, and export restrictions. Here we present for the first time an agent-based modelling framework that accounts, in simplified terms, for these processes and allows to estimate the reaction of world food prices to supply shocks on a short (monthly) timescale. We test the basic model using observed historical supply, demand, and price data of wheat as a major food grain. Further, we illustrate how the model can be used in conjunction with biophysical crop models to assess the effect of future changes in extreme event regimes on the volatility of food prices. In particular, the explicit representation of storage dynamics makes it possible to investigate the potentially nonlinear interaction between simultaneous extreme events in different food producing regions, or between several consecutive events in the same region, which may both occur more frequently under future global warming.

Global agriculture and carbon trade-offs

PubMed Central

Johnson, Justin Andrew; Runge, Carlisle Ford; Senauer, Benjamin; Foley, Jonathan; Polasky, Stephen

2014-01-01

Feeding a growing and increasingly affluent world will require expanded agricultural production, which may require converting grasslands and forests into cropland. Such conversions can reduce carbon storage, habitat provision, and other ecosystem services, presenting difficult societal trade-offs. In this paper, we use spatially explicit data on agricultural productivity and carbon storage in a global analysis to find where agricultural extensification should occur to meet growing demand while minimizing carbon emissions from land use change. Selective extensification saves ∼6 billion metric tons of carbon compared with a business-as-usual approach, with a value of approximately $1 trillion (2012 US dollars) using recent estimates of the social cost of carbon. This type of spatially explicit geospatial analysis can be expanded to include other ecosystem services and other industries to analyze how to minimize conflicts between economic development and environmental sustainability. PMID:25114254

Global agriculture and carbon trade-offs.

PubMed

Johnson, Justin Andrew; Runge, Carlisle Ford; Senauer, Benjamin; Foley, Jonathan; Polasky, Stephen

2014-08-26

Feeding a growing and increasingly affluent world will require expanded agricultural production, which may require converting grasslands and forests into cropland. Such conversions can reduce carbon storage, habitat provision, and other ecosystem services, presenting difficult societal trade-offs. In this paper, we use spatially explicit data on agricultural productivity and carbon storage in a global analysis to find where agricultural extensification should occur to meet growing demand while minimizing carbon emissions from land use change. Selective extensification saves ∼ 6 billion metric tons of carbon compared with a business-as-usual approach, with a value of approximately $1 trillion (2012 US dollars) using recent estimates of the social cost of carbon. This type of spatially explicit geospatial analysis can be expanded to include other ecosystem services and other industries to analyze how to minimize conflicts between economic development and environmental sustainability.

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

Whicker, Jeffrey J; Field, Jason P; Belnap, Jayne

Emission and redistribution of dust due to wind erosion in drylands drives major biogeochemical dynamics and provides important aeolian environmental connectivity at scales from individual plants up to the global scale. Yet, perhaps because most relevant research on aeolian processes has been presented in a geosciences rather than ecological context, most ecological studies do not explicitly consider dust-driven processes. To bridge this disciplinary gap, we provide a general overview of the ecological importance of dust, examine complex interactions between wind erosion and ecosystem dynamics from the plant-interspace scale to regional and global scales, and highlight specific examples of how disturbancemore » affects these interactions and their consequences. Changes in climate and intensification of land use will both likely lead to increased dust production. To address these challenges, environmental scientists, land managers and policy makers need to more explicitly consider dust in resource management decisions.« less

Improvement, Verification, and Refinement of Spatially-Explicit Exposure Models in Risk Assessment - FishRand Spatially-Explicit Bioaccumulation Model Demonstration

DTIC Science & Technology

2015-08-01

21  Figure 4. Data-based proportion of DDD , DDE and DDT in total DDx in fish and sediment by... DDD dichlorodiphenyldichloroethane DDE dichlorodiphenyldichloroethylene DDT dichlorodiphenyltrichloroethane DoD Department of Defense ERM... DDD ) at the other site. The spatially-explicit model consistently predicts tissue concentrations that closely match both the average and the

Early action on HFCs mitigates future atmospheric change

NASA Astrophysics Data System (ADS)

Hurwitz, Margaret M.; Fleming, Eric L.; Newman, Paul A.; Li, Feng; Liang, Qing

2016-11-01

As countries take action to mitigate global warming, both by ratifying the UNFCCC Paris Agreement and enacting the Kigali Amendment to the Montreal Protocol to manage hydrofluorocarbons (HFCs), it is important to consider the relative importance of the pertinent greenhouse gases and the distinct structure of their atmospheric impacts, and how the timing of potential greenhouse gas regulations would affect future changes in atmospheric temperature and ozone. HFCs should be explicitly considered in upcoming climate and ozone assessments, since chemistry-climate model simulations demonstrate that HFCs could contribute substantially to anthropogenic climate change by the mid-21st century, particularly in the upper troposphere and lower stratosphere i.e., global average warming up to 0.19 K at 80 hPa. The HFC mitigation scenarios described in this study demonstrate the benefits of taking early action in avoiding future atmospheric change: more than 90% of the climate change impacts of HFCs can be avoided if emissions stop by 2030.

Including eddies in global ocean models

NASA Astrophysics Data System (ADS)

Semtner, Albert J.; Chervin, Robert M.

The ocean is a turbulent fluid that is driven by winds and by surface exchanges of heat and moisture. It is as important as the atmosphere in governing climate through heat distribution, but so little is known about the ocean that it remains a “final frontier” on the face of the Earth. Many ocean currents are truly global in extent, such as the Antarctic Circumpolar Current and the “conveyor belt” that connects the North Atlantic and North Pacific oceans by flows around the southern tips of Africa and South America. It has long been a dream of some oceanographers to supplement the very limited observational knowledge by reconstructing the currents of the world ocean from the first principles of physics on a computer. However, until very recently, the prospect of doing this was thwarted by the fact that fluctuating currents known as “mesoscale eddies” could not be explicitly included in the calculation.

Early Action on Hfcs Mitigates Future Atmospheric Change

NASA Technical Reports Server (NTRS)

Hurwitz, Margaret M.; Fleming, Eric L.; Newman, Paul A.; Li, Feng; Liang, Qing

2016-01-01

As countries take action to mitigate global warming, both by ratifying theUNFCCCParis Agreement and enacting the Kigali Amendment to the Montreal Protocol to manage hydrofluorocarbons (HFCs), it is important to consider the relative importance of the pertinent greenhouse gases and the distinct structure of their atmospheric impacts, and how the timing of potential greenhouse gas regulations would affect future changes in atmospheric temperature and ozone. HFCs should be explicitly considered in upcoming climate and ozone assessments, since chemistry-climate model simulations demonstrate that HFCs could contribute substantially to anthropogenic climate change by the mid- 21st century, particularly in the upper troposphere and lower stratosphere i.e., global average warming up to 0.19 Kat 80 hPa. The HFCmitigation scenarios described in this study demonstrate the benefits of taking early action in avoiding future atmospheric change: more than 90% of the climate change impacts of HFCs can be avoided if emissions stop by 2030.

Carbon stock and carbon turnover in boreal and temperate forests - Integration of remote sensing data and global vegetation models

NASA Astrophysics Data System (ADS)

Thurner, Martin; Beer, Christian; Carvalhais, Nuno; Forkel, Matthias; Tito Rademacher, Tim; Santoro, Maurizio; Tum, Markus; Schmullius, Christiane

2016-04-01

Long-term vegetation dynamics are one of the key uncertainties of the carbon cycle. There are large differences in simulated vegetation carbon stocks and fluxes including productivity, respiration and carbon turnover between global vegetation models. Especially the implementation of climate-related mortality processes, for instance drought, fire, frost or insect effects, is often lacking or insufficient in current models and their importance at global scale is highly uncertain. These shortcomings have been due to the lack of spatially extensive information on vegetation carbon stocks, which cannot be provided by inventory data alone. Instead, we recently have been able to estimate northern boreal and temperate forest carbon stocks based on radar remote sensing data. Our spatially explicit product (0.01° resolution) shows strong agreement to inventory-based estimates at a regional scale and allows for a spatial evaluation of carbon stocks and dynamics simulated by global vegetation models. By combining this state-of-the-art biomass product and NPP datasets originating from remote sensing, we are able to study the relation between carbon turnover rate and a set of climate indices in northern boreal and temperate forests along spatial gradients. We observe an increasing turnover rate with colder winter temperatures and longer winters in boreal forests, suggesting frost damage and the trade-off between frost adaptation and growth being important mortality processes in this ecosystem. In contrast, turnover rate increases with climatic conditions favouring drought and insect outbreaks in temperate forests. Investigated global vegetation models from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, and VISIT, are able to reproduce observation-based spatial climate - turnover rate relationships only to a limited extent. While most of the models compare relatively well in terms of NPP, simulated vegetation carbon stocks are severely biased compared to our biomass dataset. Current limitations lead to considerable uncertainties in the estimated vegetation carbon turnover, contributing substantially to the forest feedback to climate change. Our results are the basis for improving mortality concepts in models and estimating their impact on the land carbon balance.

A stochastic global identification framework for aerospace structures operating under varying flight states

NASA Astrophysics Data System (ADS)

Kopsaftopoulos, Fotis; Nardari, Raphael; Li, Yu-Hung; Chang, Fu-Kuo

2018-01-01

In this work, a novel data-based stochastic "global" identification framework is introduced for aerospace structures operating under varying flight states and uncertainty. In this context, the term "global" refers to the identification of a model that is capable of representing the structure under any admissible flight state based on data recorded from a sample of these states. The proposed framework is based on stochastic time-series models for representing the structural dynamics and aeroelastic response under multiple flight states, with each state characterized by several variables, such as the airspeed, angle of attack, altitude and temperature, forming a flight state vector. The method's cornerstone lies in the new class of Vector-dependent Functionally Pooled (VFP) models which allow the explicit analytical inclusion of the flight state vector into the model parameters and, hence, system dynamics. This is achieved via the use of functional data pooling techniques for optimally treating - as a single entity - the data records corresponding to the various flight states. In this proof-of-concept study the flight state vector is defined by two variables, namely the airspeed and angle of attack of the vehicle. The experimental evaluation and assessment is based on a prototype bio-inspired self-sensing composite wing that is subjected to a series of wind tunnel experiments under multiple flight states. Distributed micro-sensors in the form of stretchable sensor networks are embedded in the composite layup of the wing in order to provide the sensing capabilities. Experimental data collected from piezoelectric sensors are employed for the identification of a stochastic global VFP model via appropriate parameter estimation and model structure selection methods. The estimated VFP model parameters constitute two-dimensional functions of the flight state vector defined by the airspeed and angle of attack. The identified model is able to successfully represent the wing's aeroelastic response under the admissible flight states via a minimum number of estimated parameters compared to standard identification approaches. The obtained results demonstrate the high accuracy and effectiveness of the proposed global identification framework, thus constituting a first step towards the next generation of "fly-by-feel" aerospace vehicles with state awareness capabilities.

Prediction of Complex Aerodynamic Flows with Explicit Algebraic Stress Models

NASA Technical Reports Server (NTRS)

Abid, Ridha; Morrison, Joseph H.; Gatski, Thomas B.; Speziale, Charles G.

1996-01-01

An explicit algebraic stress equation, developed by Gatski and Speziale, is used in the framework of K-epsilon formulation to predict complex aerodynamic turbulent flows. The nonequilibrium effects are modeled through coefficients that depend nonlinearly on both rotational and irrotational strains. The proposed model was implemented in the ISAAC Navier-Stokes code. Comparisons with the experimental data are presented which clearly demonstrate that explicit algebraic stress models can predict the correct response to nonequilibrium flow.

Global assessment of nitrogen losses and trade-offs with yields from major crop cultivations.

PubMed

Liu, Wenfeng; Yang, Hong; Liu, Junguo; Azevedo, Ligia B; Wang, Xiuying; Xu, Zongxue; Abbaspour, Karim C; Schulin, Rainer

2016-12-01

Agricultural application of reactive nitrogen (N) for fertilization is a cause of massive negative environmental problems on a global scale. However, spatially explicit and crop-specific information on global N losses into the environment and knowledge of trade-offs between N losses and crop yields are largely lacking. We use a crop growth model, Python-based Environmental Policy Integrated Climate (PEPIC), to determine global N losses from three major food crops: maize, rice, and wheat. Simulated total N losses into the environment (including water and atmosphere) are 44TgNyr -1 . Two thirds of these, or 29TgNyr -1 , are losses to water alone. Rice accounts for the highest N losses, followed by wheat and maize. The N loss intensity (NLI), defined as N losses per unit of yield, is used to address trade-offs between N losses and crop yields. The NLI presents high variation among different countries, indicating diverse N losses to produce the same amount of yields. Simulations of mitigation scenarios indicate that redistributing global N inputs and improving N management could significantly abate N losses and at the same time even increase yields without any additional total N inputs. Copyright © 2016 Elsevier B.V. All rights reserved.

Robust global ocean cooling trend for the pre-industrial Common Era

NASA Astrophysics Data System (ADS)

McGregor, Helen V.; Evans, Michael N.; Goosse, Hugues; Leduc, Guillaume; Martrat, Belen; Addison, Jason A.; Mortyn, P. Graham; Oppo, Delia W.; Seidenkrantz, Marit-Solveig; Sicre, Marie-Alexandrine; Phipps, Steven J.; Selvaraj, Kandasamy; Thirumalai, Kaustubh; Filipsson, Helena L.; Ersek, Vasile

2015-09-01

The oceans mediate the response of global climate to natural and anthropogenic forcings. Yet for the past 2,000 years -- a key interval for understanding the present and future climate response to these forcings -- global sea surface temperature changes and the underlying driving mechanisms are poorly constrained. Here we present a global synthesis of sea surface temperatures for the Common Era (CE) derived from 57 individual marine reconstructions that meet strict quality control criteria. We observe a cooling trend from 1 to 1800 CE that is robust against explicit tests for potential biases in the reconstructions. Between 801 and 1800 CE, the surface cooling trend is qualitatively consistent with an independent synthesis of terrestrial temperature reconstructions, and with a sea surface temperature composite derived from an ensemble of climate model simulations using best estimates of past external radiative forcings. Climate simulations using single and cumulative forcings suggest that the ocean surface cooling trend from 801 to 1800 CE is not primarily a response to orbital forcing but arises from a high frequency of explosive volcanism. Our results show that repeated clusters of volcanic eruptions can induce a net negative radiative forcing that results in a centennial and global scale cooling trend via a decline in mixed-layer oceanic heat content.

Robust global ocean cooling trend for the pre-industrial Common Era

USGS Publications Warehouse

McGregor, Helen V.; Evans, Michael N.; Goosse, Hugues; Leduc, Guillaume; Martrat, Belen; Addison, Jason A.; Mortyn, P. Graham; Oppo, Delia W.; Seidenkrantz, Marit-Solveig; Sicre, Marie-Alexandrine; Phipps, Steven J.; Selvaraj, Kandasamy; Thirumalai, Kaustubh; Filipsson, Helena L.; Ersek, Vasile

2015-01-01

The oceans mediate the response of global climate to natural and anthropogenic forcings. Yet for the past 2,000 years — a key interval for understanding the present and future climate response to these forcings — global sea surface temperature changes and the underlying driving mechanisms are poorly constrained. Here we present a global synthesis of sea surface temperatures for the Common Era (CE) derived from 57 individual marine reconstructions that meet strict quality control criteria. We observe a cooling trend from 1 to 1800 CEthat is robust against explicit tests for potential biases in the reconstructions. Between 801 and 1800 CE, the surface cooling trend is qualitatively consistent with an independent synthesis of terrestrial temperature reconstructions, and with a sea surface temperature composite derived from an ensemble of climate model simulations using best estimates of past external radiative forcings. Climate simulations using single and cumulative forcings suggest that the ocean surface cooling trend from 801 to 1800 CE is not primarily a response to orbital forcing but arises from a high frequency of explosive volcanism. Our results show that repeated clusters of volcanic eruptions can induce a net negative radiative forcing that results in a centennial and global scale cooling trend via a decline in mixed-layer oceanic heat content.

Program SPACECAP: software for estimating animal density using spatially explicit capture-recapture models

USGS Publications Warehouse

Gopalaswamy, Arjun M.; Royle, J. Andrew; Hines, James E.; Singh, Pallavi; Jathanna, Devcharan; Kumar, N. Samba; Karanth, K. Ullas

2012-01-01

1. The advent of spatially explicit capture-recapture models is changing the way ecologists analyse capture-recapture data. However, the advantages offered by these new models are not fully exploited because they can be difficult to implement. 2. To address this need, we developed a user-friendly software package, created within the R programming environment, called SPACECAP. This package implements Bayesian spatially explicit hierarchical models to analyse spatial capture-recapture data. 3. Given that a large number of field biologists prefer software with graphical user interfaces for analysing their data, SPACECAP is particularly useful as a tool to increase the adoption of Bayesian spatially explicit capture-recapture methods in practice.

Patterns and Trends of Primary Production, Inorganic Carbon and Oxygen and Their Ecosystem Impacts in a Regional Biogeochemical Ocean Model for Atlantic Canada

NASA Astrophysics Data System (ADS)

Fennel, K.; Rutherford, K. E.; Kuhn, A. M.; Zhang, W.; Brennan, C. E.; Zhang, R.

2016-12-01

Representing coastal oceans in global biogeochemical models is a challenge, yet the ecosystems in these regions are most vulnerable to the combined stressors of ocean warming, deoxygenation, acidification, eutrophication and fishing. Coastal regions also have large air-sea fluxes of CO2, making them an important but poorly quantified component of the global carbon cycle, and are the most relevant for human activities. Regional model applications that are nested within large-scale or global models are necessary for detailed studies of coastal regions. We present results from such a regional biogeochemical model for the northwestern North Atlantic shelves and adjacent deep ocean of Atlantic Canada. The model is an implementation of the Regional Ocean Modeling System (ROMS) and includes an NPZD-type nitrogen cycle model with explicit representation of dissolved oxygen and inorganic carbon. The region is at the confluence of the Gulf Stream and Labrador Current making it highly dynamic, a challenge for analysis and prediction, and prone to large changes. Historically a rich fishing ground, coastal ecosystems in Atlantic Canada have undergone dramatic changes including the collapse of several economically important fish stocks and the listing of many species as threatened or endangered. Furthermore it is unclear whether the region is a net source or sink of atmospheric CO2 with estimates of the size and direction of the net air-sea CO2 flux remaining controversial. We will discuss simulated patterns of primary production, inorganic carbon fluxes and oxygen trends in the context of circulation features and shelf residence times for the present ocean state and present future projections.

Connecting Free Energy Surfaces in Implicit and Explicit Solvent: an Efficient Method to Compute Conformational and Solvation Free Energies

PubMed Central

Deng, Nanjie; Zhang, Bin W.; Levy, Ronald M.

2015-01-01

The ability to accurately model solvent effects on free energy surfaces is important for understanding many biophysical processes including protein folding and misfolding, allosteric transitions and protein-ligand binding. Although all-atom simulations in explicit solvent can provide an accurate model for biomolecules in solution, explicit solvent simulations are hampered by the slow equilibration on rugged landscapes containing multiple basins separated by barriers. In many cases, implicit solvent models can be used to significantly speed up the conformational sampling; however, implicit solvent simulations do not fully capture the effects of a molecular solvent, and this can lead to loss of accuracy in the estimated free energies. Here we introduce a new approach to compute free energy changes in which the molecular details of explicit solvent simulations are retained while also taking advantage of the speed of the implicit solvent simulations. In this approach, the slow equilibration in explicit solvent, due to the long waiting times before barrier crossing, is avoided by using a thermodynamic cycle which connects the free energy basins in implicit solvent and explicit solvent using a localized decoupling scheme. We test this method by computing conformational free energy differences and solvation free energies of the model system alanine dipeptide in water. The free energy changes between basins in explicit solvent calculated using fully explicit solvent paths agree with the corresponding free energy differences obtained using the implicit/explicit thermodynamic cycle to within 0.3 kcal/mol out of ~3 kcal/mol at only ~8 % of the computational cost. We note that WHAM methods can be used to further improve the efficiency and accuracy of the explicit/implicit thermodynamic cycle. PMID:26236174

Connecting free energy surfaces in implicit and explicit solvent: an efficient method to compute conformational and solvation free energies.

PubMed

Deng, Nanjie; Zhang, Bin W; Levy, Ronald M

2015-06-09

The ability to accurately model solvent effects on free energy surfaces is important for understanding many biophysical processes including protein folding and misfolding, allosteric transitions, and protein–ligand binding. Although all-atom simulations in explicit solvent can provide an accurate model for biomolecules in solution, explicit solvent simulations are hampered by the slow equilibration on rugged landscapes containing multiple basins separated by barriers. In many cases, implicit solvent models can be used to significantly speed up the conformational sampling; however, implicit solvent simulations do not fully capture the effects of a molecular solvent, and this can lead to loss of accuracy in the estimated free energies. Here we introduce a new approach to compute free energy changes in which the molecular details of explicit solvent simulations are retained while also taking advantage of the speed of the implicit solvent simulations. In this approach, the slow equilibration in explicit solvent, due to the long waiting times before barrier crossing, is avoided by using a thermodynamic cycle which connects the free energy basins in implicit solvent and explicit solvent using a localized decoupling scheme. We test this method by computing conformational free energy differences and solvation free energies of the model system alanine dipeptide in water. The free energy changes between basins in explicit solvent calculated using fully explicit solvent paths agree with the corresponding free energy differences obtained using the implicit/explicit thermodynamic cycle to within 0.3 kcal/mol out of ∼3 kcal/mol at only ∼8% of the computational cost. We note that WHAM methods can be used to further improve the efficiency and accuracy of the implicit/explicit thermodynamic cycle.

The mass media destabilizes the cultural homogenous regime in Axelrod's model

NASA Astrophysics Data System (ADS)

Peres, Lucas R.; Fontanari, José F.

2010-02-01

An important feature of Axelrod's model for culture dissemination or social influence is the emergence of many multicultural absorbing states, despite the fact that the local rules that specify the agents interactions are explicitly designed to decrease the cultural differences between agents. Here we re-examine the problem of introducing an external, global interaction—the mass media—in the rules of Axelrod's model: in addition to their nearest neighbors, each agent has a certain probability p to interact with a virtual neighbor whose cultural features are fixed from the outset. Most surprisingly, this apparently homogenizing effect actually increases the cultural diversity of the population. We show that, contrary to previous claims in the literature, even a vanishingly small value of p is sufficient to destabilize the homogeneous regime for very large lattice sizes.

Numerical study of supersonic combustion using a finite rate chemistry model

NASA Technical Reports Server (NTRS)

Chitsomboon, T.; Tiwari, S. N.; Kumar, A.; Drummond, J. P.

1986-01-01

The governing equations of two-dimensional chemically reacting flows are presented together with a global two-step chemistry model for H2-air combustion. The explicit unsplit MacCormack finite difference algorithm is used to advance the discrete system of the governing equations in time until convergence is attained. The source terms in the species equations are evaluated implicitly to alleviate stiffness associated with fast reactions. With implicit source terms, the species equations give rise to a block-diagonal system which can be solved very efficiently on vector-processing computers. A supersonic reacting flow in an inlet-combustor configuration is calculated for the case where H2 is injected into the flow from the side walls and the strut. Results of the calculation are compared against the results obtained by using a complete reaction model.

Toward a Unified Representation of Atmospheric Convection in Variable-Resolution Climate Models

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

Walko, Robert

2016-11-07

The purpose of this project was to improve the representation of convection in atmospheric weather and climate models that employ computational grids with spatially-variable resolution. Specifically, our work targeted models whose grids are fine enough over selected regions that convection is resolved explicitly, while over other regions the grid is coarser and convection is represented as a subgrid-scale process. The working criterion for a successful scheme for representing convection over this range of grid resolution was that identical convective environments must produce very similar convective responses (i.e., the same precipitation amount, rate, and timing, and the same modification of themore » atmospheric profile) regardless of grid scale. The need for such a convective scheme has increased in recent years as more global weather and climate models have adopted variable resolution meshes that are often extended into the range of resolving convection in selected locations.« less

Replumbing of the Biological Pump caused by Millennial Climate Variability

NASA Astrophysics Data System (ADS)

Galbraith, E.; Sarmiento, J.

2008-12-01

It has been hypothesized that millennial-timescale variability in the biological pump was a critical instigator of glacial-interglacial cycles. However, even in the absence of changes in ecosystem function (e.g. due to iron fertilization), determining the mechanisms by which physical climate variability alters the biological pump is not simple. Changes in upper ocean circulation and deep water formation have previously been shown to alter both the downward flux of organic matter and the mass of respired carbon in the ocean interior, often in non- intuitive ways. For example, a reduced upward flux of nutrients at the global scale will decrease the global rate of export production, but it could either increase or decrease the respired carbon content of the ocean interior, depending on where the reduced upward flux of nutrients occurs. Furthermore, viable candidates for physical climate forcing are numerous, including changes in the westerly winds, changes in the depth of the thermocline, and changes in the formation rate of North Atlantic Deep Water, among others. We use a simple, prognostic, light-and temperature-dependent model of biogeochemical cycling within a state-of-the- art global coupled ocean-atmosphere model to examine the response of the biological pump to changes in the coupled Earth system over multiple centuries. The biogeochemical model explicitly distinguishes respired carbon from preformed and saturation carbon, allowing the activity of the biological pump to be clearly quantified. Changes are forced in the model by altering the background climate state, and by manipulating the flux of freshwater to the North Atlantic region. We show how these changes in the physical state of the coupled ocean-atmosphere system impact the distribution and mass of respired carbon in the ocean interior, and the relationship these changes bear to global patterns of export production via the redistribution of nutrients.

The critical role of the routing scheme in simulating peak river discharge in global hydrological models

NASA Astrophysics Data System (ADS)

Zhao, F.; Veldkamp, T.; Frieler, K.; Schewe, J.; Ostberg, S.; Willner, S. N.; Schauberger, B.; Gosling, S.; Mueller Schmied, H.; Portmann, F. T.; Leng, G.; Huang, M.; Liu, X.; Tang, Q.; Hanasaki, N.; Biemans, H.; Gerten, D.; Satoh, Y.; Pokhrel, Y. N.; Stacke, T.; Ciais, P.; Chang, J.; Ducharne, A.; Guimberteau, M.; Wada, Y.; Kim, H.; Yamazaki, D.

2017-12-01

Global hydrological models (GHMs) have been applied to assess global flood hazards, but their capacity to capture the timing and amplitude of peak river discharge—which is crucial in flood simulations—has traditionally not been the focus of examination. Here we evaluate to what degree the choice of river routing scheme affects simulations of peak discharge and may help to provide better agreement with observations. To this end we use runoff and discharge simulations of nine GHMs forced by observational climate data (1971-2010) within the ISIMIP2a project. The runoff simulations were used as input for the global river routing model CaMa-Flood. The simulated daily discharge was compared to the discharge generated by each GHM using its native river routing scheme. For each GHM both versions of simulated discharge were compared to monthly and daily discharge observations from 1701 GRDC stations as a benchmark. CaMa-Flood routing shows a general reduction of peak river discharge and a delay of about two to three weeks in its occurrence, likely induced by the buffering capacity of floodplain reservoirs. For a majority of river basins, discharge produced by CaMa-Flood resulted in a better agreement with observations. In particular, maximum daily discharge was adjusted, with a multi-model averaged reduction in bias over about 2/3 of the analysed basin area. The increase in agreement was obtained in both managed and near-natural basins. Overall, this study demonstrates the importance of routing scheme choice in peak discharge simulation, where CaMa-Flood routing accounts for floodplain storage and backwater effects that are not represented in most GHMs. Our study provides important hints that an explicit parameterisation of these processes may be essential in future impact studies.

Climate variability and change scenarios for a marine commodity: Modelling small pelagic fish, fisheries and fishmeal in a globalized market

NASA Astrophysics Data System (ADS)

Merino, Gorka; Barange, Manuel; Mullon, Christian

2010-04-01

The world's small pelagic fish populations, their fisheries, fishmeal and fish oil production industries and markets are part of a globalised production and consumption system. The potential for climate variability and change to alter the balance in this system is explored by means of bioeconomic models at two different temporal scales, with the objective of investigating the interactive nature of environmental and human-induced changes on this globalised system. Short-term (interannual) environmental impacts on fishmeal production are considered by including an annual variable production rate on individual small pelagic fish stocks over a 10-year simulation period. These impacts on the resources are perceived by the fishmeal markets, where they are confronted by two aquaculture expansion hypotheses. Long-term (2080) environmental impacts on the same stocks are estimated using long-term primary production predictions as proxies for the species' carrying capacities, rather than using variable production rates, and are confronted on the market side by two alternative fishmeal management scenarios consistent with IPCC-type storylines. The two scenarios, World Markets and Global Commons, are parameterized through classic equilibrium solutions for a global surplus production bioeconomic model, namely maximum sustainable yield and open access, respectively. The fisheries explicitly modelled in this paper represent 70% of total fishmeal production, thus encapsulating the expected dynamics of the global production and consumption system. Both short and long-term simulations suggest that the sustainability of the small pelagic resources, in the face of climate variability and change, depends more on how society responds to climate impacts than on the magnitude of climate alterations per se.

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.

Challenges in the global-scale quantification of permafrost changes

NASA Astrophysics Data System (ADS)

Gruber, S.

2012-12-01

Permafrost underlies much of Earth's surface and interacts with climate, land-surface phenomena and human systems. This presentation highlights heterogeneity and near-isothermal ground, two simple and well-known phenomena, as important challenges for investigating current and future states of permafrost. Heterogeneity, which can be introduced by e.g., topography, vegetation or subsurface material, is shown to be important for large parts of the global permafrost areas based on two proxies calculated from a global model of permafrost distribution. The model is based on a 1km DEM and NCEP-NCAR as well as CRU TS 2.0 air temperature data. Near-isothermal ground occurs when heat flow into a volume of ground material is accompanied by only a minute temperature change due to the dominance of latent heat transfer near 0°C. This causes our monitoring systems, which are to a large part based on temperature measurements, to lose much of their sensitivity as an instrument to measure permafrost changes. The importance of this is argued for based on (a) the long duration that soil columns are usually exposed to this effect, (b) the abundance of boreholes with temperatures close to 0°C based on the IPY-TSP data set, and (c) the global abundance and relative importance of ground near 0°C. The results presented indicated that systems and methods of gathering permafrost evidence and monitoring data need to better account for heterogeneity and isothermal ground in order to maintain long-term relevance, and that in large-area models sub-grid heterogeneity needs explicit attention.

Green Revolution research saved an estimated 18 to 27 million hectares from being brought into agricultural production

PubMed Central

Stevenson, James R.; Villoria, Nelson; Byerlee, Derek; Kelley, Timothy; Maredia, Mywish

2013-01-01

New estimates of the impacts of germplasm improvement in the major staple crops between 1965 and 2004 on global land-cover change are presented, based on simulations carried out using a global economic model (Global Trade Analysis Project Agro-Ecological Zone), a multicommodity, multiregional computable general equilibrium model linked to a global spatially explicit database on land use. We estimate the impact of removing the gains in cereal productivity attributed to the widespread adoption of improved varieties in developing countries. Here, several different effects—higher yields, lower prices, higher land rents, and trade effects—have been incorporated in a single model of the impact of Green Revolution research (and subsequent advances in yields from crop germplasm improvement) on land-cover change. Our results generally support the Borlaug hypothesis that increases in cereal yields as a result of widespread adoption of improved crop germplasm have saved natural ecosystems from being converted to agriculture. However, this relationship is complex, and the net effect is of a much smaller magnitude than Borlaug proposed. We estimate that the total crop area in 2004 would have been between 17.9 and 26.7 million hectares larger in a world that had not benefited from crop germplasm improvement since 1965. Of these hectares, 12.0–17.7 million would have been in developing countries, displacing pastures and resulting in an estimated 2 million hectares of additional deforestation. However, the negative impacts of higher food prices on poverty and hunger under this scenario would likely have dwarfed the welfare effects of agricultural expansion. PMID:23671086

Green Revolution research saved an estimated 18 to 27 million hectares from being brought into agricultural production.

PubMed

Stevenson, James R; Villoria, Nelson; Byerlee, Derek; Kelley, Timothy; Maredia, Mywish

2013-05-21

New estimates of the impacts of germplasm improvement in the major staple crops between 1965 and 2004 on global land-cover change are presented, based on simulations carried out using a global economic model (Global Trade Analysis Project Agro-Ecological Zone), a multicommodity, multiregional computable general equilibrium model linked to a global spatially explicit database on land use. We estimate the impact of removing the gains in cereal productivity attributed to the widespread adoption of improved varieties in developing countries. Here, several different effects--higher yields, lower prices, higher land rents, and trade effects--have been incorporated in a single model of the impact of Green Revolution research (and subsequent advances in yields from crop germplasm improvement) on land-cover change. Our results generally support the Borlaug hypothesis that increases in cereal yields as a result of widespread adoption of improved crop germplasm have saved natural ecosystems from being converted to agriculture. However, this relationship is complex, and the net effect is of a much smaller magnitude than Borlaug proposed. We estimate that the total crop area in 2004 would have been between 17.9 and 26.7 million hectares larger in a world that had not benefited from crop germplasm improvement since 1965. Of these hectares, 12.0-17.7 million would have been in developing countries, displacing pastures and resulting in an estimated 2 million hectares of additional deforestation. However, the negative impacts of higher food prices on poverty and hunger under this scenario would likely have dwarfed the welfare effects of agricultural expansion.

Global Cryptosporidium Loads from Livestock Manure

PubMed Central

2017-01-01

Understanding the environmental pathways of Cryptosporidium is essential for effective management of human and animal cryptosporidiosis. In this paper we aim to quantify livestock Cryptosporidium spp. loads to land on a global scale using spatially explicit process-based modeling, and to explore the effect of manure storage and treatment on oocyst loads using scenario analysis. Our model GloWPa-Crypto L1 calculates a total global Cryptosporidium spp. load from livestock manure of 3.2 × 1023 oocysts per year. Cattle, especially calves, are the largest contributors, followed by chickens and pigs. Spatial differences are linked to animal spatial distributions. North America, Europe, and Oceania together account for nearly a quarter of the total oocyst load, meaning that the developing world accounts for the largest share. GloWPa-Crypto L1 is most sensitive to oocyst excretion rates, due to large variation reported in literature. We compared the current situation to four alternative management scenarios. We find that although manure storage halves oocyst loads, manure treatment, especially of cattle manure and particularly at elevated temperatures, has a larger load reduction potential than manure storage (up to 4.6 log units). Regions with high reduction potential include India, Bangladesh, western Europe, China, several countries in Africa, and New Zealand. PMID:28654242

Increasing atmospheric CO2 overrides the historical legacy of multiple stable biome states in Africa.

PubMed

Moncrieff, Glenn R; Scheiter, Simon; Bond, William J; Higgins, Steven I

2014-02-01

The dominant vegetation over much of the global land surface is not predetermined by contemporary climate, but also influenced by past environmental conditions. This confounds attempts to predict current and future biome distributions, because even a perfect model would project multiple possible biomes without knowledge of the historical vegetation state. Here we compare the distribution of tree- and grass-dominated biomes across Africa simulated using a dynamic global vegetation model (DGVM). We explicitly evaluate where and under what conditions multiple stable biome states are possible for current and projected future climates. Our simulation results show that multiple stable biomes states are possible for vast areas of tropical and subtropical Africa under current conditions. Widespread loss of the potential for multiple stable biomes states is projected in the 21st Century, driven by increasing atmospheric CO2 . Many sites where currently both tree-dominated and grass-dominated biomes are possible become deterministically tree-dominated. Regions with multiple stable biome states are widespread and require consideration when attempting to predict future vegetation changes. Testing for behaviour characteristic of systems with multiple stable equilibria, such as hysteresis and dependence on historical conditions, and the resulting uncertainty in simulated vegetation, will lead to improved projections of global change impacts. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Dynamic Non-Rigid Objects Reconstruction with a Single RGB-D Sensor

PubMed Central

Zuo, Xinxin; Du, Chao; Wang, Runxiao; Zheng, Jiangbin; Yang, Ruigang

2018-01-01

This paper deals with the 3D reconstruction problem for dynamic non-rigid objects with a single RGB-D sensor. It is a challenging task as we consider the almost inevitable accumulation error issue in some previous sequential fusion methods and also the possible failure of surface tracking in a long sequence. Therefore, we propose a global non-rigid registration framework and tackle the drifting problem via an explicit loop closure. Our novel scheme starts with a fusion step to get multiple partial scans from the input sequence, followed by a pairwise non-rigid registration and loop detection step to obtain correspondences between neighboring partial pieces and those pieces that form a loop. Then, we perform a global registration procedure to align all those pieces together into a consistent canonical space as guided by those matches that we have established. Finally, our proposed model-update step helps fixing potential misalignments that still exist after the global registration. Both geometric and appearance constraints are enforced during our alignment; therefore, we are able to get the recovered model with accurate geometry as well as high fidelity color maps for the mesh. Experiments on both synthetic and various real datasets have demonstrated the capability of our approach to reconstruct complete and watertight deformable objects. PMID:29547562

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.

Continuous Long-Term Modeling of Shallow Groundwater-Surface Water Interaction: Implications for a Wet Prairie Restoration

NASA Astrophysics Data System (ADS)

Wijayarathne, D. B.; Gomezdelcampo, E.

2017-12-01

The existence of wet prairies is wholly dependent on the groundwater and surface water interaction. Any process that alters this interaction has a significant impact on the eco-hydrology of wet prairies. The Oak Openings Region (OOR) in Northwest Ohio supports globally rare wet prairie habitats and the precious few remaining have been drained by ditches, altering their natural flow and making them an unusually variable and artificial system. The Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model from the US Army Engineer Research and Development Center was used to assess the long-term impacts of land-use change on wet prairie restoration. This study is the first spatially explicit, continuous, long-term modeling approach for understanding the response of the shallow groundwater system of the OOR to human intervention, both positive and negative. The GSSHA model was calibrated using a 2-year weekly time series of water table elevations collected with an array of piezometers in the field. Basic statistical analysis indicates a good fit between observed and simulated water table elevations on a weekly level, though the model was run on an hourly time step and a pixel size of 10 m. Spatially-explicit results show that removal of a local ditch may not drastically change the amount of ponding in the area during spring storms, but large flooding over the entire area would occur if two other ditches are removed. This model is being used by The Nature Conservancy and Toledo Metroparks to develop different scenarios for prairie restoration that minimize its effect on local homeowners.

From wrinkling to global buckling of a ring on a curved substrate

NASA Astrophysics Data System (ADS)

Lagrange, R.; López Jiménez, F.; Terwagne, D.; Brojan, M.; Reis, P. M.

2016-04-01

We present a combined analytical approach and numerical study on the stability of a ring bound to an annular elastic substrate, which contains a circular cavity. The system is loaded by depressurizing the inner cavity. The ring is modeled as an Euler-Bernoulli beam and its equilibrium equations are derived from the mechanical energy which takes into account both stretching and bending contributions. The curvature of the substrate is considered explicitly to model the work done by its reaction force on the ring. We distinguish two different instabilities: periodic wrinkling of the ring or global buckling of the structure. Our model provides an expression for the critical pressure, as well as a phase diagram that rationalizes the transition between instability modes. Towards assessing the role of curvature, we compare our results for the critical stress and the wrinkling wavelength to their planar counterparts. We show that the critical stress is insensitive to the curvature of the substrate, while the wavelength is only affected due to the permissible discrete values of the azimuthal wavenumber imposed by the geometry of the problem. Throughout, we contrast our analytical predictions against finite element simulations.

Multiresolution image registration in digital x-ray angiography with intensity variation modeling.

PubMed

Nejati, Mansour; Pourghassem, Hossein

2014-02-01

Digital subtraction angiography (DSA) is a widely used technique for visualization of vessel anatomy in diagnosis and treatment. However, due to unavoidable patient motions, both externally and internally, the subtracted angiography images often suffer from motion artifacts that adversely affect the quality of the medical diagnosis. To cope with this problem and improve the quality of DSA images, registration algorithms are often employed before subtraction. In this paper, a novel elastic registration algorithm for registration of digital X-ray angiography images, particularly for the coronary location, is proposed. This algorithm includes a multiresolution search strategy in which a global transformation is calculated iteratively based on local search in coarse and fine sub-image blocks. The local searches are accomplished in a differential multiscale framework which allows us to capture both large and small scale transformations. The local registration transformation also explicitly accounts for local variations in the image intensities which incorporated into our model as a change of local contrast and brightness. These local transformations are then smoothly interpolated using thin-plate spline interpolation function to obtain the global model. Experimental results with several clinical datasets demonstrate the effectiveness of our algorithm in motion artifact reduction.

Validation of A Global Hydrological Model

NASA Astrophysics Data System (ADS)

Doell, P.; Lehner, B.; Kaspar, F.; Vassolo, S.

Freshwater availability has been recognized as a global issue, and its consistent quan- tification not only in individual river basins but also at the global scale is required to support the sustainable use of water. The Global Hydrology Model WGHM, which is a submodel of the global water use and availability model WaterGAP 2, computes sur- face runoff, groundwater recharge and river discharge at a spatial resolution of 0.5. WGHM is based on the best global data sets currently available, including a newly developed drainage direction map and a data set of wetlands, lakes and reservoirs. It calculates both natural and actual discharge by simulating the reduction of river discharge by human water consumption (as computed by the water use submodel of WaterGAP 2). WGHM is calibrated against observed discharge at 724 gauging sta- tions (representing about 50% of the global land area) by adjusting a parameter of the soil water balance. It not only computes the long-term average water resources but also water availability indicators that take into account the interannual and seasonal variability of runoff and discharge. The reliability of the model results is assessed by comparing observed and simulated discharges at the calibration stations and at se- lected other stations. We conclude that reliable results can be obtained for basins of more than 20,000 km2. In particular, the 90% reliable monthly discharge is simu- lated well. However, there is the tendency that semi-arid and arid basins are modeled less satisfactorily than humid ones, which is partially due to neglecting river channel losses and evaporation of runoff from small ephemeral ponds in the model. Also, the hydrology of highly developed basins with large artificial storages, basin transfers and irrigation schemes cannot be simulated well. The seasonality of discharge in snow- dominated basins is overestimated by WGHM, and if the snow-dominated basin is uncalibrated, discharge is likely to be underestimated due to the precipitation mea- surement errors. Even though the explicit modeling of wetlands and lakes leads to a much improved modeling of both the vertical water balance and the lateral transport of water, not enough information is included in WGHM to accurately capture the hy- drology of these water bodies. Certainly, the reliability of model results is highest at the locations at which WGHM was calibrated. The validation indicates that reliability for cells inside calibrated basins is satisfactory if the basin is relatively homogeneous. Analyses of the few available stations outside of calibrated basins indicate a reason- ably high model reliability, particularly in humid regions.

A Goddard Multi-Scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, W.K.; Anderson, D.; Atlas, R.; Chern, J.; Houser, P.; Hou, A.; Lang, S.; Lau, W.; Peters-Lidard, C.; Kakar, R.;

Conformal standard model with an extended scalar sector

NASA Astrophysics Data System (ADS)

Latosinski, Adam; Lewandowski, Adrian; Meissner, Krzysztof A.; Nicolai, Hermann

2015-10-01

We present an extended version of the Conformal Standard Model (characterized by the absence of any new intermediate scales between the electroweak scale and the Planck scale) with an enlarged scalar sector coupling to right-chiral neutrinos. The scalar potential and the Yukawa couplings involving only right-chiral neutrinos are invariant under a new global symmetry SU(3) N that complements the standard U(1) B-L symmetry, and is broken explicitly only by the Yukawa interaction, of order O (10-6), coupling right-chiral neutrinos and the electroweak lepton doublets. We point out four main advantages of this enlargement, namely: (1) the economy of the (non-supersymmetric) Standard Model, and thus its observational success, is preserved; (2) thanks to the enlarged scalar sector the RG improved one-loop effective potential is everywhere positive with a stable global minimum, thereby avoiding the notorious instability of the Standard Model vacuum; (3) the pseudo-Goldstone bosons resulting from spontaneous breaking of the SU(3) N symmetry are natural Dark Matter candidates with calculable small masses and couplings; and (4) the Majorana Yukawa coupling matrix acquires a form naturally adapted to leptogenesis. The model is made perturbatively consistent up to the Planck scale by imposing the vanishing of quadratic divergences at the Planck scale (`softly broken conformal symmetry'). Observable consequences of the model occur mainly via the mixing of the new scalars and the standard model Higgs boson.

Impacts of global warming on boreal larch forest in East Siberia: simulations with a coupled carbon cycle and fire regime model

NASA Astrophysics Data System (ADS)

Ito, A.

2005-12-01

Boreal forest is one of the focal areas in the study of global warming and carbon cycle. In this study, a coupled carbon cycle and fire regime model was developed and applied to a larch forest in East Siberia, near Yakutsk. Fire regime is simulated with a cellular automaton (20 km x 20 km), in which fire ignition, propagation, and extinction are parameterized in a stochastic manner, including the effects of fuel accumulation and weather condition. For each grid, carbon cycle is simulated with a 10-box scheme, in which net biome production by photosynthesis, respiration, decomposition, and biomass burning are calculated explicitly. Model parameters were calibrated with field data of biomass, litter stock, and fire statistics; the carbon cycle scheme was examined with flux measurement data. As a result, the model successfully captured average carbon stocks, productivity, fire frequency, and biomass burning. To assess the effects of global warming, a series of simulations were performed using climatic projections based on the IPCC-SRES emission scenarios from 1990 to 2100. The range of uncertainty among the different climate models and emission scenarios was assessed by using multi-model projection data by CCCma, CCSR/NIES, GFDL, and HCCPR corresponding to the SRES A2 and B2 scenarios. The model simulations showed that global warming in the 21st century would considerably enhance the fire regime (e.g., cumulative burnt area increased by 80 to 120 percent), leading to larger carbon emission by biomass burning. The effect was so strong that growth enhancement by elevated atmospheric CO2 concentration and elongated growing period was cancelled out at landscape scale. In many cases, the larch forest was estimated to act as net carbon sources of 2 to 5 kg C m_|2 by the end of the 21st century, underscoring the importance of forest fire monitoring and management in this region.

LLNL-G3Dv3: Global P wave tomography model for improved regional and teleseismic travel time prediction: LLNL-G3DV3---GLOBAL P WAVE TOMOGRAPHY

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

Simmons, N. A.; Myers, S. C.; Johannesson, G.

[1] We develop a global-scale P wave velocity model (LLNL-G3Dv3) designed to accurately predict seismic travel times at regional and teleseismic distances simultaneously. The model provides a new image of Earth's interior, but the underlying practical purpose of the model is to provide enhanced seismic event location capabilities. The LLNL-G3Dv3 model is based on ∼2.8 millionP and Pnarrivals that are re-processed using our global multiple-event locator called Bayesloc. We construct LLNL-G3Dv3 within a spherical tessellation based framework, allowing for explicit representation of undulating and discontinuous layers including the crust and transition zone layers. Using a multiscale inversion technique, regional trendsmore » as well as fine details are captured where the data allow. LLNL-G3Dv3 exhibits large-scale structures including cratons and superplumes as well numerous complex details in the upper mantle including within the transition zone. Particularly, the model reveals new details of a vast network of subducted slabs trapped within the transition beneath much of Eurasia, including beneath the Tibetan Plateau. We demonstrate the impact of Bayesloc multiple-event location on the resulting tomographic images through comparison with images produced without the benefit of multiple-event constraints (single-event locations). We find that the multiple-event locations allow for better reconciliation of the large set of direct P phases recorded at 0–97° distance and yield a smoother and more continuous image relative to the single-event locations. Travel times predicted from a 3-D model are also found to be strongly influenced by the initial locations of the input data, even when an iterative inversion/relocation technique is employed.« less

Evaluation of simulated biospheric carbon dioxide fluxes and atmospheric concentrations using global in situ observations

NASA Astrophysics Data System (ADS)

Philip, S.; Johnson, M. S.; Potter, C. S.; Genovese, V. B.

2016-12-01

Atmospheric mixing ratios of carbon dioxide (CO2) are largely controlled by anthropogenic emission sources and biospheric sources/sinks. Global biospheric fluxes of CO2 are controlled by complex processes facilitating the exchange of carbon between terrestrial ecosystems and the atmosphere. These processes which play a key role in these terrestrial ecosystem-atmosphere carbon exchanges are currently not fully understood, resulting in large uncertainties in the quantification of biospheric CO2 fluxes. Current models with these inherent deficiencies have difficulties simulating the global carbon cycle with high accuracy. We are developing a new modeling platform, GEOS-Chem-CASA by integrating the year-specific NASA-CASA (National Aeronautics and Space Administration - Carnegie Ames Stanford Approach) biosphere model with the GEOS-Chem (Goddard Earth Observation System-Chemistry) chemical transport model to improve the simulation of atmosphere-terrestrial ecosystem carbon exchange. We use NASA-CASA to explicitly represent the exchange of CO2 between terrestrial ecosystem and atmosphere by replacing the baseline GEOS-Chem land net CO2 flux and forest biomass burning CO2 emissions. We will present the estimation and evaluation of these "bottom-up" land CO2 fluxes, simulated atmospheric mixing ratios, and forest disturbance changes over the last decade. In addition, we will present our initial comparison of atmospheric column-mean dry air mole fraction of CO2 predicted by the model and those retrieved from NASA's OCO-2 (Orbiting Carbon Observatory-2) satellite instrument and model-predicted surface CO2 mixing ratios with global in situ observations. This evaluation is the first step necessary for our future work planned to constrain the estimates of biospheric carbon fluxes through "top-down" inverse modeling, which will improve our understanding of the processes controlling atmosphere-terrestrial ecosystem greenhouse gas exchanges, especially over regions which lack in situ observations.

B33C-0612: Evaluation of Simulated Biospheric Carbon Dioxide Fluxes and Atmospheric Concentrations Using Global in Situ Observations

NASA Technical Reports Server (NTRS)

Philip, Sajeev; Johnson, Matthew S.; Potter, Christopher S.; Genovese, Vanessa

2016-01-01

Atmospheric mixing ratios of carbon dioxide (CO2) are largely controlled by anthropogenic emission sources and biospheric sources/sinks. Global biospheric fluxes of CO2 are controlled by complex processes facilitating the exchange of carbon between terrestrial ecosystems and the atmosphere. These processes which play a key role in these terrestrial ecosystem-atmosphere carbon exchanges are currently not fully understood, resulting in large uncertainties in the quantification of biospheric CO2 fluxes. Current models with these inherent deficiencies have difficulties simulating the global carbon cycle with high accuracy. We are developing a new modeling platform, GEOS-Chem-CASA by integrating the year-specific NASA-CASA (National Aeronautics and Space Administration - Carnegie Ames Stanford Approach) biosphere model with the GEOS-Chem (Goddard Earth Observation System-Chemistry) chemical transport model to improve the simulation of atmosphere-terrestrial ecosystem carbon exchange. We use NASA-CASA to explicitly represent the exchange of CO2 between terrestrial ecosystem and atmosphere by replacing the baseline GEOS-Chem land net CO2 flux and forest biomass burning CO2 emissions. We will present the estimation and evaluation of these "bottom-up" land CO2 fluxes, simulated atmospheric mixing ratios, and forest disturbance changes over the last decade. In addition, we will present our initial comparison of atmospheric column-mean dry air mole fraction of CO2 predicted by the model and those retrieved from NASA's OCO-2 (Orbiting Carbon Observatory-2) satellite instrument and model-predicted surface CO2 mixing ratios with global in situ observations. This evaluation is the first step necessary for our future work planned to constrain the estimates of biospheric carbon fluxes through "top-down" inverse modeling, which will improve our understanding of the processes controlling atmosphere-terrestrial ecosystem greenhouse gas exchanges, especially over regions which lack in situ observations.

Spatially explicit modelling of forest structure and function using airborne lidar and hyperspectral remote sensing data combined with micrometeorological measurements

NASA Astrophysics Data System (ADS)

Thomas, Valerie Anne

This research models canopy-scale photosynthesis at the Groundhog River Flux Site through the integration of high-resolution airborne remote sensing data and micrometeorological measurements collected from a flux tower. Light detection and ranging (lidar) data are analysed to derive models of tree structure, including: canopy height, basal area, crown closure, and average aboveground biomass. Lidar and hyperspectral remote sensing data are used to model canopy chlorophyll (Chl) and carotenoid concentrations (known to be good indicators of photosynthesis). The integration of lidar and hyperspectral data is applied to derive spatially explicit models of the fraction of photosynthetically active radiation (fPAR) absorbed by the canopy as well as a species classification for the site. These products are integrated with flux tower meteorological measurements (i.e., air temperature and global solar radiation) collected on a continuous basis over 2004 to apply the C-Fix model of carbon exchange to the site. Results demonstrate that high resolution lidar and lidar-hyperspectral integration techniques perform well in the boreal mixedwood environment. Lidar models are well correlated with forest structure, despite the complexities introduced in the mixedwood case (e.g., r2=0.84, 0.89, 0.60, and 0.91, for mean dominant height, basal area, crown closure, and average aboveground biomass). Strong relationships are also shown for canopy scale chlorophyll/carotenoid concentration analysis using integrated lidar-hyperspectral techniques (e.g., r2=0.84, 0.84, and 0.82 for Chl(a), Chl(a+b), and Chl(b)). Examination of the spatially explicit models of fPAR reveal distinct spatial patterns which become increasingly apparent throughout the season due to the variation in species groupings (and canopy chlorophyll concentration) within the 1 km radius surrounding the flux tower. Comparison of results from the modified local-scale version of the C-Fix model to tower gross ecosystem productivity (GEP) demonstrate a good correlation to flux tower measured GEP (r2=0.70 for 10 day averages), with the largest deviations occurring in June-July. This research has direct benefits for forest inventory mapping and management practices; mapping of canopy physiology and biochemical constituents related to forest health; and scaling and direct comparison to large resolution satellite models to help bridge the gap between the local-scale measurements at flux towers and predictions derived from continental-scale carbon models.

How does soil erosion influence the terrestrial carbon cycle and the impacts of land use and land cover change?

NASA Astrophysics Data System (ADS)

Naipal, V.; Wang, Y.; Ciais, P.; Guenet, B.; Lauerwald, R.

2017-12-01

The onset of agriculture has accelerated soil erosion rates significantly, mobilizing vast quantities of soil organic carbon (SOC) globally. Studies show that at timescales of decennia to millennia this mobilized SOC can significantly alter previously estimated carbon emissions from land use and land cover change (LULCC). However, a full understanding of the impact of soil erosion on land-atmosphere carbon exchange is still missing. The aim of our study is to better constrain the terrestrial carbon fluxes by developing methods, which are compatible with earth system models (ESMs), and explicitly represent the links between soil erosion and carbon dynamics. For this we use an emulator that represents the carbon cycle of ORCHIDEE, which is the land component of the IPSL ESM, in combination with an adjusted version of the Revised Universal Soil Loss Equation (RUSLE) model. We applied this modeling framework at the global scale to evaluate how soil erosion influenced the terrestrial carbon cycle in the presence of elevated CO2, regional climate change and land use change. Here, we focus on the effects of soil detachment by erosion only and do not consider sediment transport and deposition. We found that including soil erosion in the SOC dynamics-scheme resulted in two times more SOC being lost during the historical period (1850-2005 AD). LULCC is the main contributor to this SOC loss, whose impact on the SOC stocks is significantly amplified by erosion. Regionally, the influence of soil erosion varies significantly, depending on the magnitude of the perturbations to the carbon cycle and the effects of LULCC and climate change on soil erosion rates. We conclude that it is necessary to include soil erosion in assessments of LULCC, and to explicitly consider the effects of elevated CO2 and climate change on the carbon cycle and on soil erosion, for better quantification of past, present, and future LULCC carbon emissions.

Potential impacts of climate change on the ecology of dengue and its mosquito vector the Asian tiger mosquito (Aedes albopictus)

NASA Astrophysics Data System (ADS)

Erickson, R. A.; Hayhoe, K.; Presley, S. M.; Allen, L. J. S.; Long, K. R.; Cox, S. B.

2012-09-01

Shifts in temperature and precipitation patterns caused by global climate change may have profound impacts on the ecology of certain infectious diseases. We examine the potential impacts of climate change on the transmission and maintenance dynamics of dengue, a resurging mosquito-vectored infectious disease. In particular, we project changes in dengue season length for three cities: Atlanta, GA; Chicago, IL and Lubbock, TX. These cities are located on the edges of the range of the Asian tiger mosquito within the United States of America and were chosen as test cases. We use a disease model that explicitly incorporates mosquito population dynamics and high-resolution climate projections. Based on projected changes under the Special Report on Emissions Scenarios (SRES) A1fi (higher) and B1 (lower) emission scenarios as simulated by four global climate models, we found that the projected warming shortened mosquito lifespan, which in turn decreased the potential dengue season. These results illustrate the difficulty in predicting how climate change may alter complex systems.

On the global well-posedness of BV weak solutions to the Kuramoto-Sakaguchi equation

NASA Astrophysics Data System (ADS)

Amadori, Debora; Ha, Seung-Yeal; Park, Jinyeong

2017-01-01

The Kuramoto model is a prototype phase model describing the synchronous behavior of weakly coupled limit-cycle oscillators. When the number of oscillators is sufficiently large, the dynamics of Kuramoto ensemble can be effectively approximated by the corresponding mean-field equation, namely "the Kuramoto-Sakaguchi (KS) equation". This KS equation is a kind of scalar conservation law with a nonlocal flux function due to the mean-field interactions among oscillators. In this paper, we provide a unique global solvability of bounded variation (BV) weak solutions to the kinetic KS equation for identical oscillators using the method of front-tracking in hyperbolic conservation laws. Moreover, we also show that our BV weak solutions satisfy local-in-time L1-stability with respect to BV-initial data. For the ensemble of identical Kuramoto oscillators, we explicitly construct an exponentially growing BV weak solution generated from BV perturbation of incoherent state for any positive coupling strength. This implies the nonlinear instability of incoherent state in a positive coupling strength regime. We provide several numerical examples and compare them with our analytical results.

The limited and localized flow of fresh groundwater to the world's oceans

NASA Astrophysics Data System (ADS)

Luijendijk, E.; Gleeson, T. P.; Moosdorf, N.

2017-12-01

Submarine groundwater discharge, the flow of fresh or saline groundwater to oceans [Burnett et al., 2003], may be a significant contributor to the water and chemical budgets of the world's oceans [Taniguchi et al., 2002] potentially buffering ocean acidification with groundwater alkalinity and is arguably the most uncertain component of the global groundwater budget [Alley et al., 2002]. The fresh component of submarine groundwater discharge is critical due to its high solute and nutrient load, and has been quantified locally and but only roughly estimated globally using significant assumptions. Here we show that that fresh submarine groundwater discharge is an insignificant water contributor to global oceans (0.05% of the total input) but that the freshwater discharge may still be an important chemical and nutrient contributor especially around distinct hotspots. The first spatially-explicit, physically-based global estimate of fresh submarine groundwater discharge was derived by combining density-dependent numerical groundwater models and a geospatial analysis of global coastal watersheds to robustly simulate the partitioning of onshore and offshore groundwater discharge. Although fresh submarine groundwater discharge is an insignificant part of fresh coastal groundwater discharge, results are consistent with previous estimates of significant recirculated seawater discharging as groundwater as well as quantifying the significant near-shore terrestrial discharge, a flux that has so far been overlooked in global hydrological studies and that affects coastal water budgets, evapotranspiration and ecosystems.

Modeling the Impact of Spatial Structure on Growth Dynamics of Invasive Plant Species

NASA Astrophysics Data System (ADS)

Murphy, James T.; Johnson, Mark P.; Walshe, Ray

2013-07-01

Invasive nonindigenous plant species can have potentially serious detrimental effects on local ecosystems and, as a result, costly control efforts often have to be put in place to protect habitats. An example of an invasive problem on a global scale involves the salt marsh grass species from the genus Spartina. The spread of Spartina anglica in Europe and Asia has drawn much concern due to its ability to convert coastal habitats into cord-grass monocultures and to alter the native food webs. However, the patterns of invasion of Spartina species are amenable to spatially-explicit modeling strategies that take into account both temporal and spatio-temporal processes. In this study, an agent-based model of Spartina growth on a simulated mud flat environment was developed in order to study the effects of spatial pattern and initial seedling placement on the invasion dynamics of the population. The spatial pattern of an invasion plays a key role in the rate of spread of the species and understanding this can lead to significant cost savings when designing efficient control strategies. We present here a model framework that can be used to explicitly represent complex spatial and temporal patterns of invasion in order to be able to predict quantitatively the impact of these factors on invasion dynamics. This would be a useful tool for assessing eradication strategies and choosing optimal control solutions in order to be able to minimize future control costs.

Spatially Explicit Life Cycle Analysis of Cellulosic Ethanol Production Scenarios in Southwestern Michigan

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

Cronin, Keith R.; Runge, Troy M.; Zhang, Xuesong

By modeling the life cycle of fuel pathways for cellulosic ethanol (CE) it can help identify logistical barriers and anticipated impacts for the emerging commercial CE industry. Such models contain high amounts of variability, primarily due to the varying nature of agricultural production but also because of limitations in the availability of data at the local scale, resulting in the typical practice of using average values. In this study, 12 spatially explicit, cradle-to-refinery gate CE pathways were developed that vary by feedstock (corn stover, switchgrass, and Miscanthus), nitrogen application rate (higher, lower), pretreatment method (ammonia fiber expansion [AFEX], dilute acid),more » and co-product treatment method (mass allocation, sub-division), in which feedstock production was modeled at the watershed scale over a nine-county area in Southwestern Michigan. When comparing feedstocks, the model showed that corn stover yielded higher global warming potential (GWP), acidification potential (AP), and eutrophication potential (EP) than the perennial feedstocks of switchgrass and Miscanthus, on an average per area basis. Full life cycle results per MJ of produced ethanol demonstrated more mixed results, with corn stover-derived CE scenarios that use sub-division as a co-product treatment method yielding similarly favorable outcomes as switchgrass- and Miscanthus-derived CE scenarios. Variability was found to be greater between feedstocks than watersheds. Additionally, scenarios using dilute acid pretreatment had more favorable results than those using AFEX pretreatment.« less

Spatially Explicit Life Cycle Analysis of Cellulosic Ethanol Production Scenarios in Southwestern Michigan

DOE PAGES

Cronin, Keith R.; Runge, Troy M.; Zhang, Xuesong; ...

2016-07-13

By modeling the life cycle of fuel pathways for cellulosic ethanol (CE) it can help identify logistical barriers and anticipated impacts for the emerging commercial CE industry. Such models contain high amounts of variability, primarily due to the varying nature of agricultural production but also because of limitations in the availability of data at the local scale, resulting in the typical practice of using average values. In this study, 12 spatially explicit, cradle-to-refinery gate CE pathways were developed that vary by feedstock (corn stover, switchgrass, and Miscanthus), nitrogen application rate (higher, lower), pretreatment method (ammonia fiber expansion [AFEX], dilute acid),more » and co-product treatment method (mass allocation, sub-division), in which feedstock production was modeled at the watershed scale over a nine-county area in Southwestern Michigan. When comparing feedstocks, the model showed that corn stover yielded higher global warming potential (GWP), acidification potential (AP), and eutrophication potential (EP) than the perennial feedstocks of switchgrass and Miscanthus, on an average per area basis. Full life cycle results per MJ of produced ethanol demonstrated more mixed results, with corn stover-derived CE scenarios that use sub-division as a co-product treatment method yielding similarly favorable outcomes as switchgrass- and Miscanthus-derived CE scenarios. Variability was found to be greater between feedstocks than watersheds. Additionally, scenarios using dilute acid pretreatment had more favorable results than those using AFEX pretreatment.« less

Deconstructing the core dynamics from a complex time-lagged regulatory biological circuit.

PubMed

Eriksson, O; Brinne, B; Zhou, Y; Björkegren, J; Tegnér, J

2009-03-01

Complex regulatory dynamics is ubiquitous in molecular networks composed of genes and proteins. Recent progress in computational biology and its application to molecular data generate a growing number of complex networks. Yet, it has been difficult to understand the governing principles of these networks beyond graphical analysis or extensive numerical simulations. Here the authors exploit several simplifying biological circumstances which thereby enable to directly detect the underlying dynamical regularities driving periodic oscillations in a dynamical nonlinear computational model of a protein-protein network. System analysis is performed using the cell cycle, a mathematically well-described complex regulatory circuit driven by external signals. By introducing an explicit time delay and using a 'tearing-and-zooming' approach the authors reduce the system to a piecewise linear system with two variables that capture the dynamics of this complex network. A key step in the analysis is the identification of functional subsystems by identifying the relations between state-variables within the model. These functional subsystems are referred to as dynamical modules operating as sensitive switches in the original complex model. By using reduced mathematical representations of the subsystems the authors derive explicit conditions on how the cell cycle dynamics depends on system parameters, and can, for the first time, analyse and prove global conditions for system stability. The approach which includes utilising biological simplifying conditions, identification of dynamical modules and mathematical reduction of the model complexity may be applicable to other well-characterised biological regulatory circuits. [Includes supplementary material].

Electric power and the global economy: Advances in database construction and sector representation

NASA Astrophysics Data System (ADS)

Peters, Jeffrey C.

The electricity sector plays a crucial role in the global economy. The sector is a major consumer of fossil fuel resources, producer of greenhouse gas emissions, and an important indicator and correlate of economic development. As such, the sector is a primary target for policy-makers seeking to address these issues. The sector is also experiencing rapid technological change in generation (e.g. renewables), primary inputs (e.g. horizontal drilling and hydraulic fracturing), and end-use efficiency. This dissertation seeks to further our understanding of the role of the electricity sector as part of the dynamic global energy-economy, which requires significant research advances in both database construction and modeling techniques. Chapter 2 identifies useful engineering-level data and presents a novel matrix balancing method for integrating these data in global economic databases. Chapter 3 demonstrates the relationship between matrix balancing method and modeling results, and Chapter 4 presents the full construction methodology for GTAP-Power, the foremost, publicly-available global computable general equilibrium database. Chapter 5 presents an electricity-detailed computational equilibrium model that explicitly and endogenously captures capacity utilization, capacity expansion, and their interdependency - important aspects of technological substitution in the electricity sector. The individual, but interrelated, research contributions to database construction and electricity modeling in computational equilibrium are placed in the context of analyzing the US EPA Clean Power Plan (CPP) CO 2 target of 32 percent reduction of CO2 emissions in the US electricity sector from a 2005 baseline by 2030. Assuming current fuel prices, the model predicts an almost 28 percent CO2 reduction without further policy intervention. Next, a carbon tax and investment subsidies for renewable technologies to meet the CPP full targets are imposed and compared (Chapter 6). The carbon tax achieves the target via both utilization and expansion, while the renewable investment subsidies lead to over-expansion and compromises some of the possibilities via utilization. In doing so, this dissertation furthers our understanding of the role of the electricity sector as part of the dynamic global energy-economy.

Flexible language constructs for large parallel programs

NASA Technical Reports Server (NTRS)

Rosing, Matthew; Schnabel, Robert

1993-01-01

The goal of the research described is to develop flexible language constructs for writing large data parallel numerical programs for distributed memory (MIMD) multiprocessors. Previously, several models have been developed to support synchronization and communication. Models for global synchronization include SIMD (Single Instruction Multiple Data), SPMD (Single Program Multiple Data), and sequential programs annotated with data distribution statements. The two primary models for communication include implicit communication based on shared memory and explicit communication based on messages. None of these models by themselves seem sufficient to permit the natural and efficient expression of the variety of algorithms that occur in large scientific computations. An overview of a new language that combines many of these programming models in a clean manner is given. This is done in a modular fashion such that different models can be combined to support large programs. Within a module, the selection of a model depends on the algorithm and its efficiency requirements. An overview of the language and discussion of some of the critical implementation details is given.

Multidimensional, fully implicit, exactly conserving electromagnetic particle-in-cell simulations

NASA Astrophysics Data System (ADS)

Chacon, Luis

2015-09-01

We discuss a new, conservative, fully implicit 2D-3V particle-in-cell algorithm for non-radiative, electromagnetic kinetic plasma simulations, based on the Vlasov-Darwin model. Unlike earlier linearly implicit PIC schemes and standard explicit PIC schemes, fully implicit PIC algorithms are unconditionally stable and allow exact discrete energy and charge conservation. This has been demonstrated in 1D electrostatic and electromagnetic contexts. In this study, we build on these recent algorithms to develop an implicit, orbit-averaged, time-space-centered finite difference scheme for the Darwin field and particle orbit equations for multiple species in multiple dimensions. The Vlasov-Darwin model is very attractive for PIC simulations because it avoids radiative noise issues in non-radiative electromagnetic regimes. The algorithm conserves global energy, local charge, and particle canonical-momentum exactly, even with grid packing. The nonlinear iteration is effectively accelerated with a fluid preconditioner, which allows efficient use of large timesteps, O(√{mi/me}c/veT) larger than the explicit CFL. In this presentation, we will introduce the main algorithmic components of the approach, and demonstrate the accuracy and efficiency properties of the algorithm with various numerical experiments in 1D and 2D. Support from the LANL LDRD program and the DOE-SC ASCR office.

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

Mendonça, João M.; Grimm, Simon L.; Grosheintz, Luc

We have designed and developed, from scratch, a global circulation model (GCM) named THOR that solves the three-dimensional nonhydrostatic Euler equations. Our general approach lifts the commonly used assumptions of a shallow atmosphere and hydrostatic equilibrium. We solve the “pole problem” (where converging meridians on a sphere lead to increasingly smaller time steps near the poles) by implementing an icosahedral grid. Irregularities in the grid, which lead to grid imprinting, are smoothed using the “spring dynamics” technique. We validate our implementation of spring dynamics by examining calculations of the divergence and gradient of test functions. To prevent the computational timemore » step from being bottlenecked by having to resolve sound waves, we implement a split-explicit method together with a horizontally explicit and vertically implicit integration. We validate our GCM by reproducing the Earth and hot-Jupiter-like benchmark tests. THOR was designed to run on graphics processing units (GPUs), which allows for physics modules (radiative transfer, clouds, chemistry) to be added in the future, and is part of the open-source Exoclimes Simulation Platform (www.exoclime.org).« less

The Role of Model and Initial Condition Error in Numerical Weather Forecasting Investigated with an Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Prive, Nikki C.; Errico, Ronald M.

2013-01-01

A series of experiments that explore the roles of model and initial condition error in numerical weather prediction are performed using an observing system simulation experiment (OSSE) framework developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO). The use of an OSSE allows the analysis and forecast errors to be explicitly calculated, and different hypothetical observing networks can be tested with ease. In these experiments, both a full global OSSE framework and an 'identical twin' OSSE setup are utilized to compare the behavior of the data assimilation system and evolution of forecast skill with and without model error. The initial condition error is manipulated by varying the distribution and quality of the observing network and the magnitude of observation errors. The results show that model error has a strong impact on both the quality of the analysis field and the evolution of forecast skill, including both systematic and unsystematic model error components. With a realistic observing network, the analysis state retains a significant quantity of error due to systematic model error. If errors of the analysis state are minimized, model error acts to rapidly degrade forecast skill during the first 24-48 hours of forward integration. In the presence of model error, the impact of observation errors on forecast skill is small, but in the absence of model error, observation errors cause a substantial degradation of the skill of medium range forecasts.

The effect of road network patterns on pedestrian safety: A zone-based Bayesian spatial modeling approach.

PubMed

Guo, Qiang; Xu, Pengpeng; Pei, Xin; Wong, S C; Yao, Danya

2017-02-01

Pedestrian safety is increasingly recognized as a major public health concern. Extensive safety studies have been conducted to examine the influence of multiple variables on the occurrence of pedestrian-vehicle crashes. However, the explicit relationship between pedestrian safety and road network characteristics remains unknown. This study particularly focused on the role of different road network patterns on the occurrence of crashes involving pedestrians. A global integration index via space syntax was introduced to quantify the topological structures of road networks. The Bayesian Poisson-lognormal (PLN) models with conditional autoregressive (CAR) prior were then developed via three different proximity structures: contiguity, geometry-centroid distance, and road network connectivity. The models were also compared with the PLN counterpart without spatial correlation effects. The analysis was based on a comprehensive crash dataset from 131 selected traffic analysis zones in Hong Kong. The results indicated that higher global integration was associated with more pedestrian-vehicle crashes; the irregular pattern network was proved to be safest in terms of pedestrian crash occurrences, whereas the grid pattern was the least safe; the CAR model with a neighborhood structure based on road network connectivity was found to outperform in model goodness-of-fit, implying the importance of accurately accounting for spatial correlation when modeling spatially aggregated crash data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Will high-resolution global ocean models benefit coupled predictions on short-range to climate timescales?

NASA Astrophysics Data System (ADS)

Hewitt, Helene T.; Bell, Michael J.; Chassignet, Eric P.; Czaja, Arnaud; Ferreira, David; Griffies, Stephen M.; Hyder, Pat; McClean, Julie L.; New, Adrian L.; Roberts, Malcolm J.

2017-12-01

As the importance of the ocean in the weather and climate system is increasingly recognised, operational systems are now moving towards coupled prediction not only for seasonal to climate timescales but also for short-range forecasts. A three-way tension exists between the allocation of computing resources to refine model resolution, the expansion of model complexity/capability, and the increase of ensemble size. Here we review evidence for the benefits of increased ocean resolution in global coupled models, where the ocean component explicitly represents transient mesoscale eddies and narrow boundary currents. We consider lessons learned from forced ocean/sea-ice simulations; from studies concerning the SST resolution required to impact atmospheric simulations; and from coupled predictions. Impacts of the mesoscale ocean in western boundary current regions on the large-scale atmospheric state have been identified. Understanding of air-sea feedback in western boundary currents is modifying our view of the dynamics in these key regions. It remains unclear whether variability associated with open ocean mesoscale eddies is equally important to the large-scale atmospheric state. We include a discussion of what processes can presently be parameterised in coupled models with coarse resolution non-eddying ocean models, and where parameterizations may fall short. We discuss the benefits of resolution and identify gaps in the current literature that leave important questions unanswered.

A model for global diversity in response to temperature change over geological time scales, with reference to planktic organisms.

PubMed

De Blasio, Fabio Vittorio; Liow, Lee Hsiang; Schweder, Tore; De Blasio, Birgitte Freiesleben

2015-01-21

There are strong propositions in the literature that abiotic factors override biotic drivers of diversity on time scales of the fossil record. In order to study the interaction of biotic and abiotic forces on long term changes, we devise a spatio-temporal discrete-time Markov process model of macroevolution featuring population formation, speciation, migration and extinction, where populations are free to migrate. In our model, the extinction probability of these populations is controlled by latitudinally and temporally varying environment (temperature) and competition. Although our model is general enough to be applicable to disparate taxa, we explicitly address planktic organisms, which are assumed to disperse freely without barriers over the Earth's oceans. While rapid and drastic environmental changes tend to eliminate many species, generalists preferentially survive and hence leave generalist descendants. In other words, environmental fluctuations result in generalist descendants which are resilient to future environmental changes. Periods of stable or slow environmental changes lead to more specialist species and higher population numbers. Simulating Cenozoic diversity dynamics with both competition and the environmental component of our model produces diversity curves that reflect current empirical knowledge, which cannot be obtained with just one component. Our model predicts that the average temperature optimum at which planktic species thrive best has declined over the Neogene, following the trend of global average temperatures. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cosmological constraints on pseudo-Nambu-Goldstone bosons

NASA Technical Reports Server (NTRS)

Frieman, Joshua A.; Jaffe, Andrew H.

1991-01-01

Particle physics models with pseudo-Nambu-Goldstone bosons (PNGBs) are characterized by two mass scales: a global spontaneous symmetry breaking scale, f, and a soft (explicit) symmetry breaking scale, Lambda. General model insensitive constraints were studied on this 2-D parameter space arising from the cosmological and astrophysical effects of PNGBs. In particular, constraints were studied arising from vacuum misalignment and thermal production of PNGBs, topological defects, and the cosmological effects of PNGB decay products, as well as astrophysical constraints from stellar PNGB emission. Bounds on the Peccei-Quinn axion scale, 10(exp 10) GeV approx. = or less than f sub pq approx. = or less than 10(exp 10) to 10(exp 12) GeV, emerge as a special case, where the soft breaking scale is fixed at Lambda sub QCD approx. = 100 MeV.

On the Interpretation and Use of Mediation: Multiple Perspectives on Mediation Analysis.

PubMed

Agler, Robert; De Boeck, Paul

2017-01-01

Mediation analysis has become a very popular approach in psychology, and it is one that is associated with multiple perspectives that are often at odds, often implicitly. Explicitly discussing these perspectives and their motivations, advantages, and disadvantages can help to provide clarity to conversations and research regarding the use and refinement of mediation models. We discuss five such pairs of perspectives on mediation analysis, their associated advantages and disadvantages, and their implications: with vs. without a mediation hypothesis, specific effects vs. a global model, directness vs. indirectness of causation, effect size vs. null hypothesis testing, and hypothesized vs. alternative explanations. Discussion of the perspectives is facilitated by a small simulation study. Some philosophical and linguistic considerations are briefly discussed, as well as some other perspectives we do not develop here.

A spanner in the works? anti-politics in global health policy: Comment on "A ghost in the machine? politics in global health policy".

PubMed

McCoy, David; Singh, Guddi

2014-08-01

The formulation of global health policy is political; and all institutions operating in the global health landscape are political. This is because policies and institutions inevitably represent certain values, reflect particular ideologies, and preferentially serve some interests over others. This may be expressed explicitly and consciously; or implicitly and unconsciously. But it's important to recognise the social and political dimension of global health policy. In some instances however, the politics of global health policy may be actively denied or obscured. This has been described in the development studies literature as a form of 'anti-politics'. In this article we describe four forms of anti-politics and consider their application to the global health sector.

THOR: an open-source exo-GCM

NASA Astrophysics Data System (ADS)

Grosheintz, Luc; Mendonça, João; Käppeli, Roger; Lukas Grimm, Simon; Mishra, Siddhartha; Heng, Kevin

2015-12-01

In this talk, I will present THOR, the first fully conservative, GPU-accelerated exo-GCM (general circulation model) on a nearly uniform, global grid that treats shocks and is non-hydrostatic. THOR will be freely available to the community as a standard tool.Unlike most GCMs THOR solves the full, non-hydrostatic Euler equations instead of the primitive equations. The equations are solved on a global three-dimensional icosahedral grid by a second order Finite Volume Method (FVM). Icosahedral grids are nearly uniform refinements of an icosahedron. We've implemented three different versions of this grid. FVM conserves the prognostic variables (density, momentum and energy) exactly and doesn't require a diffusion term (artificial viscosity) in the Euler equations to stabilize our solver. Historically FVM was designed to treat discontinuities correctly. Hence it excels at resolving shocks, including those present in hot exoplanetary atmospheres.Atmospheres are generally in near hydrostatic equilibrium. We therefore implement a well-balancing technique recently developed at the ETH Zurich. This well-balancing ensures that our FVM maintains hydrostatic equilibrium to machine precision. Better yet, it is able to resolve pressure perturbations from this equilibrium as small as one part in 100'000. It is important to realize that these perturbations are significantly smaller than the truncation error of the same scheme without well-balancing. If during the course of the simulation (due to forcing) the atmosphere becomes non-hydrostatic, our solver continues to function correctly.THOR just passed an important mile stone. We've implemented the explicit part of the solver. The explicit solver is useful to study instabilities or local problems on relatively short time scales. I'll show some nice properties of the explicit THOR. An explicit solver is not appropriate for climate study because the time step is limited by the sound speed. Therefore, we are working on the first fully implicit GCM. By ESS3, I hope to present results for the advection equation.THOR is part of the Exoclimes Simulation Platform (ESP), a set of open-source community codes for simulating and understanding the atmospheres of exoplanets. The ESP also includes tools for radiative transfer and retrieval (HELIOS), an opacity calculator (HELIOS-K), and a chemical kinetics solver (VULCAN). We expect to publicly release an initial version of THOR in 2016 on www.exoclime.org.

Implicit and explicit self-esteem and their reciprocal relationship with symptoms of depression and social anxiety: a longitudinal study in adolescents.

PubMed

van Tuijl, Lonneke A; de Jong, Peter J; Sportel, B Esther; de Hullu, Eva; Nauta, Maaike H

2014-03-01

A negative self-view is a prominent factor in most cognitive vulnerability models of depression and anxiety. Recently, there has been increased attention to differentiate between the implicit (automatic) and the explicit (reflective) processing of self-related evaluations. This longitudinal study aimed to test the association between implicit and explicit self-esteem and symptoms of adolescent depression and social anxiety disorder. Two complementary models were tested: the vulnerability model and the scarring effect model. Participants were 1641 first and second year pupils of secondary schools in the Netherlands. The Rosenberg Self-Esteem Scale, self-esteem Implicit Association Test and Revised Child Anxiety and Depression Scale were completed to measure explicit self-esteem, implicit self-esteem and symptoms of social anxiety disorder (SAD) and major depressive disorder (MDD), respectively, at baseline and two-year follow-up. Explicit self-esteem at baseline was associated with symptoms of MDD and SAD at follow-up. Symptomatology at baseline was not associated with explicit self-esteem at follow-up. Implicit self-esteem was not associated with symptoms of MDD or SAD in either direction. We relied on self-report measures of MDD and SAD symptomatology. Also, findings are based on a non-clinical sample. Our findings support the vulnerability model, and not the scarring effect model. The implications of these findings suggest support of an explicit self-esteem intervention to prevent increases in MDD and SAD symptomatology in non-clinical adolescents. Copyright © 2013 Elsevier Ltd. All rights reserved.

A methodological approach for deriving regional crop rotations as basis for the assessment of the impact of agricultural strategies using soil erosion as example.

PubMed

Lorenz, Marco; Fürst, Christine; Thiel, Enrico

2013-09-01

Regarding increasing pressures by global societal and climate change, the assessment of the impact of land use and land management practices on land degradation and the related decrease in sustainable provision of ecosystem services gains increasing interest. Existing approaches to assess agricultural practices focus on the assessment of single crops or statistical data because spatially explicit information on practically applied crop rotations is mostly not available. This provokes considerable uncertainties in crop production models as regional specifics have to be neglected or cannot be considered in an appropriate way. In a case study in Saxony, we developed an approach to (i) derive representative regional crop rotations by combining different data sources and expert knowledge. This includes the integration of innovative crop sequences related to bio-energy production or organic farming and different soil tillage, soil management and soil protection techniques. Furthermore, (ii) we developed a regionalization approach for transferring crop rotations and related soil management strategies on the basis of statistical data and spatially explicit data taken from so called field blocks. These field blocks are the smallest spatial entity for which agricultural practices must be reported to apply for agricultural funding within the frame of the European Agricultural Fund for Rural Development (EAFRD) program. The information was finally integrated into the spatial decision support tool GISCAME to assess and visualize in spatially explicit manner the impact of alternative agricultural land use strategies on soil erosion risk and ecosystem services provision. Objective of this paper is to present the approach how to create spatially explicit information on agricultural management practices for a study area around Dresden, the capital of the German Federal State Saxony. Copyright © 2013 Elsevier Ltd. All rights reserved.

Are mixed explicit/implicit solvation models reliable for studying phosphate hydrolysis? A comparative study of continuum, explicit and mixed solvation models.

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

Kamerlin, Shina C. L.; Haranczyk, Maciej; Warshel, Arieh

2009-05-01

Phosphate hydrolysis is ubiquitous in biology. However, despite intensive research on this class of reactions, the precise nature of the reaction mechanism remains controversial. In this work, we have examined the hydrolysis of three homologous phosphate diesters. The solvation free energy was simulated by means of either an implicit solvation model (COSMO), hybrid quantum mechanical / molecular mechanical free energy perturbation (QM/MM-FEP) or a mixed solvation model in which N water molecules were explicitly included in the ab initio description of the reacting system (where N=1-3), with the remainder of the solvent being implicitly modelled as a continuum. Here, bothmore » COSMO and QM/MM-FEP reproduce Delta Gobs within an error of about 2kcal/mol. However, we demonstrate that in order to obtain any form of reliable results from a mixed model, it is essential to carefully select the explicit water molecules from short QM/MM runs that act as a model for the true infinite system. Additionally, the mixed models tend to be increasingly inaccurate the more explicit water molecules are placed into the system. Thus, our analysis indicates that this approach provides an unreliable way for modelling phosphate hydrolysis in solution.« less

Explicit filtering in large eddy simulation using a discontinuous Galerkin method

NASA Astrophysics Data System (ADS)

Brazell, Matthew J.

The discontinuous Galerkin (DG) method is a formulation of the finite element method (FEM). DG provides the ability for a high order of accuracy in complex geometries, and allows for highly efficient parallelization algorithms. These attributes make the DG method attractive for solving the Navier-Stokes equations for large eddy simulation (LES). The main goal of this work is to investigate the feasibility of adopting an explicit filter in the numerical solution of the Navier-Stokes equations with DG. Explicit filtering has been shown to increase the numerical stability of under-resolved simulations and is needed for LES with dynamic sub-grid scale (SGS) models. The explicit filter takes advantage of DG's framework where the solution is approximated using a polyno- mial basis where the higher modes of the solution correspond to a higher order polynomial basis. By removing high order modes, the filtered solution contains low order frequency content much like an explicit low pass filter. The explicit filter implementation is tested on a simple 1-D solver with an initial condi- tion that has some similarity to turbulent flows. The explicit filter does restrict the resolution as well as remove accumulated energy in the higher modes from aliasing. However, the ex- plicit filter is unable to remove numerical errors causing numerical dissipation. A second test case solves the 3-D Navier-Stokes equations of the Taylor-Green vortex flow (TGV). The TGV is useful for SGS model testing because it is initially laminar and transitions into a fully turbulent flow. The SGS models investigated include the constant coefficient Smagorinsky model, dynamic Smagorinsky model, and dynamic Heinz model. The constant coefficient Smagorinsky model is over dissipative, this is generally not desirable however it does add stability. The dynamic Smagorinsky model generally performs better, especially during the laminar-turbulent transition region as expected. The dynamic Heinz model which is based on an improved model, handles the laminar-turbulent transition region well while also showing additional robustness.

Adaptable Information Models in the Global Change Information System

NASA Astrophysics Data System (ADS)

Duggan, B.; Buddenberg, A.; Aulenbach, S.; Wolfe, R.; Goldstein, J.

2014-12-01

The US Global Change Research Program has sponsored the creation of the Global Change Information System () to provide a web based source of accessible, usable, and timely information about climate and global change for use by scientists, decision makers, and the public. The GCIS played multiple roles during the assembly and release of the Third National Climate Assessment. It provided human and programmable interfaces, relational and semantic representations of information, and discrete identifiers for various types of resources, which could then be manipulated by a distributed team with a wide range of specialties. The GCIS also served as a scalable backend for the web based version of the report. In this talk, we discuss the infrastructure decisions made during the design and deployment of the GCIS, as well as ongoing work to adapt to new types of information. Both a constrained relational database and an open ended triple store are used to ensure data integrity while maintaining fluidity. Using natural primary keys allows identifiers to propagate through both models. Changing identifiers are accomodated through fine grained auditing and explicit mappings to external lexicons. A practical RESTful API is used whose endpoints are also URIs in an ontology. Both the relational schema and the ontology are maleable, and stability is ensured through test driven development and continuous integration testing using modern open source techniques. Content is also validated through continuous testing techniques. A high degres of scalability is achieved through caching.

A new dataset for systematic assessments of climate change impacts as a function of global warming

NASA Astrophysics Data System (ADS)

Heinke, J.; Ostberg, S.; Schaphoff, S.; Frieler, K.; M{ü}ller, C.; Gerten, D.; Meinshausen, M.; Lucht, W.

2012-11-01

In the ongoing political debate on climate change, global mean temperature change (ΔTglob) has become the yardstick by which mitigation costs, impacts from unavoided climate change, and adaptation requirements are discussed. For a scientifically informed discourse along these lines systematic assessments of climate change impacts as a function of ΔTglob are required. The current availability of climate change scenarios constrains this type of assessment to a~narrow range of temperature change and/or a reduced ensemble of climate models. Here, a newly composed dataset of climate change scenarios is presented that addresses the specific requirements for global assessments of climate change impacts as a function of ΔTglob. A pattern-scaling approach is applied to extract generalized patterns of spatially explicit change in temperature, precipitation and cloudiness from 19 AOGCMs. The patterns are combined with scenarios of global mean temperature increase obtained from the reduced-complexity climate model MAGICC6 to create climate scenarios covering warming levels from 1.5 to 5 degrees above pre-industrial levels around the year 2100. The patterns are shown to sufficiently maintain the original AOGCMs' climate change properties, even though they, necessarily, utilize a simplified relationships betweenΔTglob and changes in local climate properties. The dataset (made available online upon final publication of this paper) facilitates systematic analyses of climate change impacts as it covers a wider and finer-spaced range of climate change scenarios than the original AOGCM simulations.

High resolution modeling of reservoir storage and extent dynamics at the continental scale

NASA Astrophysics Data System (ADS)

Shin, S.; Pokhrel, Y. N.

2017-12-01

Over the past decade, significant progress has been made in developing reservoir schemes in large scale hydrological models to better simulate hydrological fluxes and storages in highly managed river basins. These schemes have been successfully used to study the impact of reservoir operation on global river basins. However, improvements in the existing schemes are needed for hydrological fluxes and storages, especially at the spatial resolution to be used in hyper-resolution hydrological modeling. In this study, we developed a reservoir routing scheme with explicit representation of reservoir storage and extent at the grid scale of 5km or less. Instead of setting reservoir area to a fixed value or diagnosing it using the area-storage equation, which is a commonly used approach in the existing reservoir schemes, we explicitly simulate the inundated storage and area for all grid cells that are within the reservoir extent. This approach enables a better simulation of river-floodplain-reservoir storage by considering both the natural flood and man-made reservoir storage. Results of the seasonal dynamics of reservoir storage, river discharge at the downstream of dams, and the reservoir inundation extent are evaluated with various datasets from ground-observations and satellite measurements. The new model captures the dynamics of these variables with a good accuracy for most of the large reservoirs in the western United States. It is expected that the incorporation of the newly developed reservoir scheme in large-scale land surface models (LSMs) will lead to improved simulation of river flow and terrestrial water storage in highly managed river basins.

Embedded-explicit emergent literacy intervention I: Background and description of approach.

PubMed

Justice, Laura M; Kaderavek, Joan N

2004-07-01

This article, the first of a two-part series, provides background information and a general description of an emergent literacy intervention model for at-risk preschoolers and kindergartners. The embedded-explicit intervention model emphasizes the dual importance of providing young children with socially embedded opportunities for meaningful, naturalistic literacy experiences throughout the day, in addition to regular structured therapeutic interactions that explicitly target critical emergent literacy goals. The role of the speech-language pathologist (SLP) in the embedded-explicit model encompasses both indirect and direct service delivery: The SLP consults and collaborates with teachers and parents to ensure the highest quality and quantity of socially embedded literacy-focused experiences and serves as a direct provider of explicit interventions using structured curricula and/or lesson plans. The goal of this integrated model is to provide comprehensive emergent literacy interventions across a spectrum of early literacy skills to ensure the successful transition of at-risk children from prereaders to readers.

Developing Spatially Explicit Habitat Models for Grassland Bird Conservation Planning in the Prairie Pothole Region of North Dakota

Treesearch

Neal D. Niemuth; Michael E. Estey; Charles R. Loesch

2005-01-01

Conservation planning for birds is increasingly focused on landscapes. However, little spatially explicit information is available to guide landscape-level conservation planning for many species of birds. We used georeferenced 1995 Breeding Bird Survey (BBS) data in conjunction with land-cover information to develop a spatially explicit habitat model predicting the...

Explicit robust schemes for implementation of general principal value-based constitutive models

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Saleeb, A. F.; Tan, H. Q.; Zhang, Y.

1993-01-01

The issue of developing effective and robust schemes to implement general hyperelastic constitutive models is addressed. To this end, special purpose functions are used to symbolically derive, evaluate, and automatically generate the associated FORTRAN code for the explicit forms of the corresponding stress function and material tangent stiffness tensors. These explicit forms are valid for the entire deformation range. The analytical form of these explicit expressions is given here for the case in which the strain-energy potential is taken as a nonseparable polynomial function of the principle stretches.

Explicit validation of a surface shortwave radiation balance model over snow-covered complex terrain

NASA Astrophysics Data System (ADS)

Helbig, N.; Löwe, H.; Mayer, B.; Lehning, M.

2010-09-01

A model that computes the surface radiation balance for all sky conditions in complex terrain is presented. The spatial distribution of direct and diffuse sky radiation is determined from observations of incident global radiation, air temperature, and relative humidity at a single measurement location. Incident radiation under cloudless sky is spatially derived from a parameterization of the atmospheric transmittance. Direct and diffuse sky radiation for all sky conditions are obtained by decomposing the measured global radiation value. Spatial incident radiation values under all atmospheric conditions are computed by adjusting the spatial radiation values obtained from the parametric model with the radiation components obtained from the decomposition model at the measurement site. Topographic influences such as shading are accounted for. The radiosity approach is used to compute anisotropic terrain reflected radiation. Validations of the shortwave radiation balance model are presented in detail for a day with cloudless sky. For a day with overcast sky a first validation is presented. Validation of a section of the horizon line as well as of individual radiation components is performed with high-quality measurements. A new measurement setup was designed to determine terrain reflected radiation. There is good agreement between the measurements and the modeled terrain reflected radiation values as well as with incident radiation values. A comparison of the model with a fully three-dimensional radiative transfer Monte Carlo model is presented. That validation reveals a good agreement between modeled radiation values.

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

Tan, Zeli; Zhuang, Qianlai; Shurpali, Narasinha J.

Recent studies indicated that Arctic lakes play an important role in receiving, processing, and storing organic carbon exported from terrestrial ecosystems. To quantify the contribution of Arctic lakes to the global carbon cycle, we developed a one-dimensional process-based Arctic Lake Biogeochemistry Model (ALBM) that explicitly simulates the dynamics of organic and inorganic carbon in Arctic lakes. By realistically modeling water mixing, carbon biogeochemistry, and permafrost carbon loading, the model can reproduce the seasonal variability of CO2 fluxes from the study Arctic lakes. The simulated area-weighted CO2 fluxes from yedoma thermokarst lakes, non-yedoma thermokarst lakes and glacial lakes are 29.5 gmore » C m-2 yr-1, 13.0 g C m-2 yr-1 and 21.4 g C m-2 yr-1, respectively, close to the observed values (31.2 g C m-2 yr-1, 17.2 g C m-2 yr-1 and 16.5±7.7 g C m-2 yr-1, respectively). The simulations show that the high CO2 fluxes from yedoma thermokarst lakes are stimulated by the biomineralization of mobilized labile organic carbon from thawing yedoma permafrost. The simulations also imply that the relative contribution of glacial lakes to the global carbon cycle could be the largest because of their much larger surface area and high biomineralization and carbon loading. According to the model, sunlight-induced organic carbon degradation is more important for shallow non-yedoma thermokarst lakes but its overall contribution to the global carbon cycle could be limited. Overall, the ALBM model can simulate the whole-lake carbon balance of Arctic lakes, a difficult task for field and laboratory experiments and other biogeochemistry models.« less

Lower Psychological Well-Being and Excessive Sexual Interest Predict Symptoms of Compulsive Use of Sexually Explicit Internet Material Among Adolescent Boys.

PubMed

Doornwaard, Suzan M; van den Eijnden, Regina J J M; Baams, Laura; Vanwesenbeeck, Ine; ter Bogt, Tom F M

2016-01-01

Although a growing body of literature addresses the effects of young people's use of sexually explicit Internet material, research on the compulsive use of this type of online content among adolescents and its associated factors is largely lacking. This study investigated whether factors from three distinct psychosocial domains (i.e., psychological well-being, sexual interests/behaviors, and impulsive-psychopathic personality) predicted symptoms of compulsive use of sexually explicit Internet material among adolescent boys. Links between psychosocial factors and boys' compulsive use symptoms were analyzed both cross-sectionally and longitudinally with compulsive use symptoms measured 6 months later (T2). Data were used from 331 Dutch boys (M age = 15.16 years, range 11-17) who indicated that they used sexually explicit Internet material. The results from negative binomial regression analyses indicated that lower levels of global self-esteem and higher levels of excessive sexual interest concurrently predicted boys' symptoms of compulsive use of sexually explicit Internet material. Longitudinally, higher levels of depressive feelings and, again, excessive sexual interest predicted relative increases in compulsive use symptoms 6 months later. Impulsive and psychopathic personality traits were not uniquely related to boys' symptoms of compulsive use of sexually explicit Internet material. Our findings, while preliminary, suggest that both psychological well-being factors and sexual interests/behaviors are involved in the development of compulsive use of sexually explicit Internet material among adolescent boys. Such knowledge is important for prevention and intervention efforts that target the needs of specific problematic users of sexually explicit Internet material.

Uncertainty in spatially explicit animal dispersal models

USGS Publications Warehouse

Mooij, Wolf M.; DeAngelis, Donald L.

2003-01-01

Uncertainty in estimates of survival of dispersing animals is a vexing difficulty in conservation biology. The current notion is that this uncertainty decreases the usefulness of spatially explicit population models in particular. We examined this problem by comparing dispersal models of three levels of complexity: (1) an event-based binomial model that considers only the occurrence of mortality or arrival, (2) a temporally explicit exponential model that employs mortality and arrival rates, and (3) a spatially explicit grid-walk model that simulates the movement of animals through an artificial landscape. Each model was fitted to the same set of field data. A first objective of the paper is to illustrate how the maximum-likelihood method can be used in all three cases to estimate the means and confidence limits for the relevant model parameters, given a particular set of data on dispersal survival. Using this framework we show that the structure of the uncertainty for all three models is strikingly similar. In fact, the results of our unified approach imply that spatially explicit dispersal models, which take advantage of information on landscape details, suffer less from uncertainly than do simpler models. Moreover, we show that the proposed strategy of model development safeguards one from error propagation in these more complex models. Finally, our approach shows that all models related to animal dispersal, ranging from simple to complex, can be related in a hierarchical fashion, so that the various approaches to modeling such dispersal can be viewed from a unified perspective.

A Coupled GCM-Cloud Resolving Modeling System, and a Regional Scale Model to Study Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2007-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a superparameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (2ICE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generatio11 regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

A Coupled GCM-Cloud Resolving Modeling System, and A Regional Scale Model to Study Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2006-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (21CE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generation regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

Consistent global responses of marine ecosystems to future climate change across the IPCC AR5 earth system models

NASA Astrophysics Data System (ADS)

Cabré, Anna; Marinov, Irina; Leung, Shirley

2015-09-01

We analyze for the first time all 16 Coupled Model Intercomparison Project Phase 5 models with explicit marine ecological modules to identify the common mechanisms involved in projected phytoplankton biomass, productivity, and organic carbon export changes over the twenty-first century in the RCP8.5 scenario (years 2080-2099) compared to the historical scenario (years 1980-1999). All models predict decreases in primary and export production globally of up to 30 % of the historical value. We divide the ocean into biomes using upwelling velocities, sea-ice coverage, and maximum mixed layer depths. Models generally show expansion of subtropical, oligotrophic biomes and contraction of marginal sea-ice biomes. The equatorial and subtropical biomes account for 77 % of the total modern oceanic primary production (PP), but contribute 117 % to the global drop in PP, slightly compensated by an increase in PP in high latitudes. The phytoplankton productivity response to climate is surprisingly similar across models in low latitude biomes, indicating a common set of modeled processes controlling productivity changes. Ecological responses are less consistent across models in the subpolar and sea-ice biomes. Inter-hemispheric asymmetries in physical drivers result in stronger climate-driven relative decreases in biomass, productivity, and export of organic matter in the northern compared to the southern hemisphere low latitudes. The export ratio, a measure of the efficiency of carbon export to the deep ocean, decreases across low and mid-latitude biomes and models with more than one phytoplankton type, particularly in the northern hemisphere. Inter-model variability is much higher for biogeochemical than physical variables in the historical period, but is very similar among predicted 100-year biogeochemical and physical changes. We include detailed biome-by-biome analyses, discuss the decoupling between biomass, productivity and export across biomes and models, and present statistical significance and consistency across models using a novel technique based on bootstrapping combined with a weighting scheme based on similarity across models.

Influence of isoprene chemical mechanism on modelled changes in tropospheric ozone due to climate and land use over the 21st century

NASA Astrophysics Data System (ADS)

Squire, O. J.; Archibald, A. T.; Griffiths, P. T.; Jenkin, M. E.; Pyle, J. A.

2014-09-01

Isoprene is a precursor to tropospheric ozone, a key pollutant and greenhouse gas. Anthropogenic activity over the coming century is likely to cause large changes in atmospheric CO2 levels, climate and land use, all of which will alter the global vegetation distribution leading to changes in isoprene emissions. Previous studies have used global chemistry-climate models to assess how possible changes in climate and land use could affect isoprene emissions and hence tropospheric ozone. The chemistry of isoprene oxidation, which can alter the concentration of ozone, is highly complex, therefore it must be parameterised in these models. In this work we compare the effect of four different reduced isoprene chemical mechanisms, all currently used in Earth-system models, on tropospheric ozone. Using a box model we compare ozone in these reduced schemes to that in a more explicit scheme (the MCM) over a range of NOx and isoprene emissions, through the use of O3 isopleths. We find that there is some variability, especially at high isoprene emissions, caused by differences in isoprene-derived NOx reservoir species. A global model is then used to examine how the different reduced schemes respond to potential future changes in climate, isoprene emissions, anthropogenic emissions and land use change. We find that, particularly in isoprene rich regions, the response of the schemes varies considerably. The wide ranging response is due to differences in the types of peroxy radicals produced by isoprene oxidation, and their relative rates of reaction towards NO, leading to ozone formation, or HO2, leading to termination. Also important is the yield of isoprene-nitrates and peroxyacyl nitrate precursors from isoprene oxidation. Those schemes that produce less of these NOx reservoir species, tend to produce more ozone locally and less away from the source region. Additionally, by combining the emissions and O3 data from all of the global model integrations, we are able to construct isopleth plots comparable to those from the box model analysis. We find that the global and box model isopleths show good qualitative agreement, suggesting that comparing chemical mechanisms with a box model in this framework is a useful tool for assessing mechanistic performance in complex global models. We conclude that as the choice of reduced isoprene mechanism may alter both the magnitude and sign of the ozone response, how isoprene chemistry is parameterised in perturbation experiments such as these is a crucially important consideration. More measurements are needed to validate these reduced mechanisms especially in high-VOC, low-NOx environments.

Effective Reading and Writing Instruction: A Focus on Modeling

ERIC Educational Resources Information Center

Regan, Kelley; Berkeley, Sheri

2012-01-01

When providing effective reading and writing instruction, teachers need to provide explicit modeling. Modeling is particularly important when teaching students to use cognitive learning strategies. Examples of how teachers can provide specific, explicit, and flexible instructional modeling is presented in the context of two evidence-based…

Inter- and intra- observer reliability of risk assessment of repetitive work without an explicit method.

PubMed

Eliasson, Kristina; Palm, Peter; Nyman, Teresia; Forsman, Mikael

2017-07-01

A common way to conduct practical risk assessments is to observe a job and report the observed long term risks for musculoskeletal disorders. The aim of this study was to evaluate the inter- and intra-observer reliability of ergonomists' risk assessments without the support of an explicit risk assessment method. Twenty-one experienced ergonomists assessed the risk level (low, moderate, high risk) of eight upper body regions, as well as the global risk of 10 video recorded work tasks. Intra-observer reliability was assessed by having nine of the ergonomists repeat the procedure at least three weeks after the first assessment. The ergonomists made their risk assessment based on his/her experience and knowledge. The statistical parameters of reliability included agreement in %, kappa, linearly weighted kappa, intraclass correlation and Kendall's coefficient of concordance. The average inter-observer agreement of the global risk was 53% and the corresponding weighted kappa (K w ) was 0.32, indicating fair reliability. The intra-observer agreement was 61% and 0.41 (K w ). This study indicates that risk assessments of the upper body, without the use of an explicit observational method, have non-acceptable reliability. It is therefore recommended to use systematic risk assessment methods to a higher degree. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Quantifying the Interannual Variability in Global Carbon Fluxes from Heterotrophic Respiration using a Testbed and Pulse Response Modeling Approach.

NASA Astrophysics Data System (ADS)

Basile, S.; Wieder, W. R.; Hartman, M. D.; Keppel-Aleks, G.

2017-12-01

The atmospheric growth rate of carbon dioxide (CO2) varies interannually and is strongly correlated with climate factors, including temperature and drought. These climate drivers affect vegetation productivity and the rate of respiration of organic matter to CO2 (heterotrophic respiration). Here we quantified the interannual variability in global carbon fluxes from heterotrophic respiration and their relationship to climate drivers. We used a novel testbed approach to simulate respiration, then simulated the imprint that these modeled heterotrophic fluxes have on atmospheric CO2 using an idealized pulse response model. Two of the testbed formulations (MIMICS and CORPSE) are microbially explicit by incorporation of microbial physiological tradeoffs and microbial activity in soil near fine roots (rhizosphere soils), respectively, while the third model (CASA) uses a CENTURY-like microbially implicit framework. Modeled respiration exhibited subtle differences, with MIMICS showing the largest seasonal amplitude in the Northern Hemisphere and the strongest correlation with global temperature variations. At Mauna Loa (MLO) the simulated seasonal CO2 amplitude in response to global heterotrophic respiration ranged by a factor of 1.5 across the models with the MIMICS and CASA models producing the higher amplitude responses between 1987 and 2006. The seasonal CO2 amplitude at MLO varied by about 5% interannually, with the largest variation in the MIMICS model. In the Northern Hemisphere there was a similar response range in average peak-to-trough seasonal CO2 but all models showed slightly higher amplitude values. Comparatively in the Northern Hemisphere, the average seasonal CO2 amplitude in response to respiration ranged between 30%-41% of the seasonal CO2 amplitude in response to net primary productivity. We expect that exploring the imprint of heterotrophic respiration on atmospheric CO2 from these three different models will improve our understanding of the imprint that heterotrophic respiration imparts on atmospheric data. The aim of this work is to ultimately yield an approach for combining CO2 observations with remote sensing-based observations of terrestrial productivity to produce regional constraints on heterotrophic respiration.

Computer aided weld defect delineation using statistical parametric active contours in radiographic inspection.

PubMed

Goumeidane, Aicha Baya; Nacereddine, Nafaa; Khamadja, Mohammed

2015-01-01

A perfect knowledge of a defect shape is determinant for the analysis step in automatic radiographic inspection. Image segmentation is carried out on radiographic images and extract defects indications. This paper deals with weld defect delineation in radiographic images. The proposed method is based on a new statistics-based explicit active contour. An association of local and global modeling of the image pixels intensities is used to push the model to the desired boundaries. Furthermore, other strategies are proposed to accelerate its evolution and make the convergence speed depending only on the defect size as selecting a band around the active contour curve. The experimental results are very promising, since experiments on synthetic and radiographic images show the ability of the proposed model to extract a piece-wise homogenous object from very inhomogeneous background, even in a bad quality image.

Scale-up of ecological experiments: Density variation in the mobile bivalve Macomona liliana

USGS Publications Warehouse

Schneider, Davod C.; Walters, R.; Thrush, S.; Dayton, P.

1997-01-01

At present the problem of scaling up from controlled experiments (necessarily at a small spatial scale) to questions of regional or global importance is perhaps the most pressing issue in ecology. Most of the proposed techniques recommend iterative cycling between theory and experiment. We present a graphical technique that facilitates this cycling by allowing the scope of experiments, surveys, and natural history observations to be compared to the scope of models and theory. We apply the scope analysis to the problem of understanding the population dynamics of a bivalve exposed to environmental stress at the scale of a harbour. Previous lab and field experiments were found not to be 1:1 scale models of harbour-wide processes. Scope analysis allowed small scale experiments to be linked to larger scale surveys and to a spatially explicit model of population dynamics.

Do People Use the Shortest Path? An Empirical Test of Wardrop’s First Principle

PubMed Central

Zhu, Shanjiang; Levinson, David

2015-01-01

Most recent route choice models, following either the random utility maximization or rule-based paradigm, require explicit enumeration of feasible routes. The quality of model estimation and prediction is sensitive to the appropriateness of the consideration set. However, few empirical studies of revealed route characteristics have been reported in the literature. This study evaluates the widely applied shortest path assumption by evaluating routes followed by residents of the Minneapolis—St. Paul metropolitan area. Accurate Global Positioning System (GPS) and Geographic Information System (GIS) data were employed to reveal routes people used over an eight to thirteen week period. Most people did not choose the shortest path. Using three weeks of that data, we find that current route choice set generation algorithms do not reveal the majority of paths that individuals took. Findings from this study may guide future efforts in building better route choice models. PMID:26267756

Functional Nonlinear Mixed Effects Models For Longitudinal Image Data

PubMed Central

Luo, Xinchao; Zhu, Lixing; Kong, Linglong; Zhu, Hongtu

2015-01-01

Motivated by studying large-scale longitudinal image data, we propose a novel functional nonlinear mixed effects modeling (FN-MEM) framework to model the nonlinear spatial-temporal growth patterns of brain structure and function and their association with covariates of interest (e.g., time or diagnostic status). Our FNMEM explicitly quantifies a random nonlinear association map of individual trajectories. We develop an efficient estimation method to estimate the nonlinear growth function and the covariance operator of the spatial-temporal process. We propose a global test and a simultaneous confidence band for some specific growth patterns. We conduct Monte Carlo simulation to examine the finite-sample performance of the proposed procedures. We apply FNMEM to investigate the spatial-temporal dynamics of white-matter fiber skeletons in a national database for autism research. Our FNMEM may provide a valuable tool for charting the developmental trajectories of various neuropsychiatric and neurodegenerative disorders. PMID:26213453

Geometric Metamorphosis

PubMed Central

Niethammer, Marc; Hart, Gabriel L.; Pace, Danielle F.; Vespa, Paul M.; Irimia, Andrei; Van Horn, John D.; Aylward, Stephen R.

2013-01-01

Standard image registration methods do not account for changes in image appearance. Hence, metamorphosis approaches have been developed which jointly estimate a space deformation and a change in image appearance to construct a spatio-temporal trajectory smoothly transforming a source to a target image. For standard metamorphosis, geometric changes are not explicitly modeled. We propose a geometric metamorphosis formulation, which explains changes in image appearance by a global deformation, a deformation of a geometric model, and an image composition model. This work is motivated by the clinical challenge of predicting the long-term effects of traumatic brain injuries based on time-series images. This work is also applicable to the quantification of tumor progression (e.g., estimating its infiltrating and displacing components) and predicting chronic blood perfusion changes after stroke. We demonstrate the utility of the method using simulated data as well as scans from a clinical traumatic brain injury patient. PMID:21995083

Decomposing task-switching costs with the diffusion model.

PubMed

Schmitz, Florian; Voss, Andreas

2012-02-01

In four experiments, task-switching processes were investigated with variants of the alternating runs paradigm and the explicit cueing paradigm. The classical diffusion model for binary decisions (Ratcliff, 1978) was used to dissociate different components of task-switching costs. Findings can be reconciled with the view that task-switching processes take place in successive phases as postulated by multiple-components models of task switching (e.g., Mayr & Kliegl, 2003; Ruthruff, Remington, & Johnston, 2001). At an earlier phase, task-set reconfiguration (Rogers & Monsell, 1995) or cue-encoding (Schneider & Logan, 2005) takes place, at a later phase, the response is selected in accord with constraints set in the first phase. Inertia effects (Allport, Styles, & Hsieh, 1994; Allport & Wylie, 2000) were shown to affect this later stage. Additionally, findings support the notion that response caution contributes to both global as well as to local switching costs when task switches are predictable.

Sampling schemes and parameter estimation for nonlinear Bernoulli-Gaussian sparse models

NASA Astrophysics Data System (ADS)

Boudineau, Mégane; Carfantan, Hervé; Bourguignon, Sébastien; Bazot, Michael

2016-06-01

We address the sparse approximation problem in the case where the data are approximated by the linear combination of a small number of elementary signals, each of these signals depending non-linearly on additional parameters. Sparsity is explicitly expressed through a Bernoulli-Gaussian hierarchical model in a Bayesian framework. Posterior mean estimates are computed using Markov Chain Monte-Carlo algorithms. We generalize the partially marginalized Gibbs sampler proposed in the linear case in [1], and build an hybrid Hastings-within-Gibbs algorithm in order to account for the nonlinear parameters. All model parameters are then estimated in an unsupervised procedure. The resulting method is evaluated on a sparse spectral analysis problem. It is shown to converge more efficiently than the classical joint estimation procedure, with only a slight increase of the computational cost per iteration, consequently reducing the global cost of the estimation procedure.

A local time stepping algorithm for GPU-accelerated 2D shallow water models

NASA Astrophysics Data System (ADS)

Dazzi, Susanna; Vacondio, Renato; Dal Palù, Alessandro; Mignosa, Paolo

2018-01-01

In the simulation of flooding events, mesh refinement is often required to capture local bathymetric features and/or to detail areas of interest; however, if an explicit finite volume scheme is adopted, the presence of small cells in the domain can restrict the allowable time step due to the stability condition, thus reducing the computational efficiency. With the aim of overcoming this problem, the paper proposes the application of a Local Time Stepping (LTS) strategy to a GPU-accelerated 2D shallow water numerical model able to handle non-uniform structured meshes. The algorithm is specifically designed to exploit the computational capability of GPUs, minimizing the overheads associated with the LTS implementation. The results of theoretical and field-scale test cases show that the LTS model guarantees appreciable reductions in the execution time compared to the traditional Global Time Stepping strategy, without compromising the solution accuracy.

A global assessment of market accessibility and market influence for global environmental change studies

NASA Astrophysics Data System (ADS)

Verburg, Peter H.; Ellis, Erle C.; Letourneau, Aurelien

2011-07-01

Markets influence the global patterns of urbanization, deforestation, agriculture and other land use systems. Yet market influence is rarely incorporated into spatially explicit global studies of environmental change, largely because consistent global data are lacking below the national level. Here we present the first high spatial resolution gridded data depicting market influence globally. The data jointly represent variations in both market strength and accessibility based on three market influence indices derived from an index of accessibility to market locations and national level gross domestic product (purchasing power parity). These indices show strong correspondence with human population density while also revealing several distinct and useful relationships with other global environmental patterns. As market influence grows, the need for high resolution global data on market influence and its dynamics will become increasingly important to understanding and forecasting global environmental change.

On the Effect of Dust Particles on Global Cloud Condensation Nuclei and Cloud Droplet Number

NASA Technical Reports Server (NTRS)

Karydis, V. A.; Kumar, P.; Barahona, D.; Sokolik, I. N.; Nenes, A.

2011-01-01

Aerosol-cloud interaction studies to date consider aerosol with a substantial fraction of soluble material as the sole source of cloud condensation nuclei (CCN). Emerging evidence suggests that mineral dust can act as good CCN through water adsorption onto the surface of particles. This study provides a first assessment of the contribution of insoluble dust to global CCN and cloud droplet number concentration (CDNC). Simulations are carried out with the NASA Global Modeling Initiative chemical transport model with an online aerosol simulation, considering emissions from fossil fuel, biomass burning, marine, and dust sources. CDNC is calculated online and explicitly considers the competition of soluble and insoluble CCN for water vapor. The predicted annual average contribution of insoluble mineral dust to CCN and CDNC in cloud-forming areas is up to 40 and 23.8%, respectively. Sensitivity tests suggest that uncertainties in dust size distribution and water adsorption parameters modulate the contribution of mineral dust to CDNC by 23 and 56%, respectively. Coating of dust by hygroscopic salts during the atmospheric aging causes a twofold enhancement of the dust contribution to CCN; the aged dust, however, can substantially deplete in-cloud supersaturation during the initial stages of cloud formation and can eventually reduce CDNC. Considering the hydrophilicity from adsorption and hygroscopicity from solute is required to comprehensively capture the dust-warm cloud interactions. The framework presented here addresses this need and can be easily integrated in atmospheric models.

Explicit continuous charge-based compact model for long channel heavily doped surrounding-gate MOSFETs incorporating interface traps and quantum effects

NASA Astrophysics Data System (ADS)

Hamzah, Afiq; Hamid, Fatimah A.; Ismail, Razali

2016-12-01

An explicit solution for long-channel surrounding-gate (SRG) MOSFETs is presented from intrinsic to heavily doped body including the effects of interface traps and fixed oxide charges. The solution is based on the core SRGMOSFETs model of the Unified Charge Control Model (UCCM) for heavily doped conditions. The UCCM model of highly doped SRGMOSFETs is derived to obtain the exact equivalent expression as in the undoped case. Taking advantage of the undoped explicit charge-based expression, the asymptotic limits for below threshold and above threshold have been redefined to include the effect of trap states for heavily doped cases. After solving the asymptotic limits, an explicit mobile charge expression is obtained which includes the trap state effects. The explicit mobile charge model shows very good agreement with respect to numerical simulation over practical terminal voltages, doping concentration, geometry effects, and trap state effects due to the fixed oxide charges and interface traps. Then, the drain current is obtained using the Pao-Sah's dual integral, which is expressed as a function of inversion charge densities at the source/drain ends. The drain current agreed well with the implicit solution and numerical simulation for all regions of operation without employing any empirical parameters. A comparison with previous explicit models has been conducted to verify the competency of the proposed model with the doping concentration of 1× {10}19 {{cm}}-3, as the proposed model has better advantages in terms of its simplicity and accuracy at a higher doping concentration.

From Cycle Rooted Spanning Forests to the Critical Ising Model: an Explicit Construction

NASA Astrophysics Data System (ADS)

de Tilière, Béatrice

2013-04-01

Fisher established an explicit correspondence between the 2-dimensional Ising model defined on a graph G and the dimer model defined on a decorated version {{G}} of this graph (Fisher in J Math Phys 7:1776-1781, 1966). In this paper we explicitly relate the dimer model associated to the critical Ising model and critical cycle rooted spanning forests (CRSFs). This relation is established through characteristic polynomials, whose definition only depends on the respective fundamental domains, and which encode the combinatorics of the model. We first show a matrix-tree type theorem establishing that the dimer characteristic polynomial counts CRSFs of the decorated fundamental domain {{G}_1}. Our main result consists in explicitly constructing CRSFs of {{G}_1} counted by the dimer characteristic polynomial, from CRSFs of G 1, where edges are assigned Kenyon's critical weight function (Kenyon in Invent Math 150(2):409-439, 2002); thus proving a relation on the level of configurations between two well known 2-dimensional critical models.

Atmosphere-Wave-Ocean Coupling from Regional to Global Earth System Models for High-Impact Extreme Weather Prediction

NASA Astrophysics Data System (ADS)

Chen, S. S.; Curcic, M.

2017-12-01

The need for acurrate and integrated impact forecasts of extreme wind, rain, waves, and storm surge is growing as coastal population and built environment expand worldwide. A key limiting factor in forecasting impacts of extreme weather events associated with tropical cycle and winter storms is fully coupled atmosphere-wave-ocean model interface with explicit momentum and energy exchange. It is not only critical for accurate prediction of storm intensity, but also provides coherent wind, rian, ocean waves and currents forecasts for forcing for storm surge. The Unified Wave INterface (UWIN) has been developed for coupling of the atmosphere-wave-ocean models. UWIN couples the atmosphere, wave, and ocean models using the Earth System Modeling Framework (ESMF). It is a physically based and computationally efficient coupling sytem that is flexible to use in a multi-model system and portable for transition to the next generation global Earth system prediction mdoels. This standardized coupling framework allows researchers to develop and test air-sea coupling parameterizations and coupled data assimilation, and to better facilitate research-to-operation activities. It has been used and extensively tested and verified in regional coupled model forecasts of tropical cycles and winter storms (Chen and Curcic 2016, Curcic et al. 2016, and Judt et al. 2016). We will present 1) an overview of UWIN and its applications in fully coupled atmosphere-wave-ocean model predictions of hurricanes and coastal winter storms, and 2) implenmentation of UWIN in the NASA GMAO GEOS-5.

Protein structure modeling and refinement by global optimization in CASP12.

PubMed

Hong, Seung Hwan; Joung, InSuk; Flores-Canales, Jose C; Manavalan, Balachandran; Cheng, Qianyi; Heo, Seungryong; Kim, Jong Yun; Lee, Sun Young; Nam, Mikyung; Joo, Keehyoung; Lee, In-Ho; Lee, Sung Jong; Lee, Jooyoung

2018-03-01

For protein structure modeling in the CASP12 experiment, we have developed a new protocol based on our previous CASP11 approach. The global optimization method of conformational space annealing (CSA) was applied to 3 stages of modeling: multiple sequence-structure alignment, three-dimensional (3D) chain building, and side-chain re-modeling. For better template selection and model selection, we updated our model quality assessment (QA) method with the newly developed SVMQA (support vector machine for quality assessment). For 3D chain building, we updated our energy function by including restraints generated from predicted residue-residue contacts. New energy terms for the predicted secondary structure and predicted solvent accessible surface area were also introduced. For difficult targets, we proposed a new method, LEEab, where the template term played a less significant role than it did in LEE, complemented by increased contributions from other terms such as the predicted contact term. For TBM (template-based modeling) targets, LEE performed better than LEEab, but for FM targets, LEEab was better. For model refinement, we modified our CASP11 molecular dynamics (MD) based protocol by using explicit solvents and tuning down restraint weights. Refinement results from MD simulations that used a new augmented statistical energy term in the force field were quite promising. Finally, when using inaccurate information (such as the predicted contacts), it was important to use the Lorentzian function for which the maximal penalty arising from wrong information is always bounded. © 2017 Wiley Periodicals, Inc.

Individuals with 22q11.2 Deletion Syndrome Are Impaired at Explicit, but Not Implicit, Discrimination of Local Forms Embedded in Global Structures

ERIC Educational Resources Information Center

Giersch, Anne; Glaser, Bronwyn; Pasca, Catherine; Chabloz, Mélanie; Debbané, Martin; Eliez, Stephan

2014-01-01

Individuals with 22q11.2 deletion syndrome (22q11.2DS) are impaired at exploring visual information in space; however, not much is known about visual form discrimination in the syndrome. Thirty-five individuals with 22q11.2DS and 41 controls completed a form discrimination task with global forms made up of local elements. Affected individuals…

An explicit microphysics thunderstorm model.

Treesearch

R. Solomon; C.M. Medaglia; C. Adamo; S. Dietrick; A. Mugnai; U. Biader Ceipidor

2005-01-01

The authors present a brief description of a 1.5-dimensional thunderstorm model with a lightning parameterization that utilizes an explicit microphysical scheme to model lightning-producing clouds. The main intent of this work is to describe the basic microphysical and electrical properties of the model, with a small illustrative section to show how the model may be...

Graph-based analysis of connectivity in spatially-explicit population models: HexSim and the Connectivity Analysis Toolkit

EPA Science Inventory

Background / Question / Methods Planning for the recovery of threatened species is increasingly informed by spatially-explicit population models. However, using simulation model results to guide land management decisions can be difficult due to the volume and complexity of model...

Sensitivity analysis of the GEMS soil organic carbon model to land cover land use classification uncertainties under different climate scenarios in Senegal

USGS Publications Warehouse

Dieye, A.M.; Roy, David P.; Hanan, N.P.; Liu, S.; Hansen, M.; Toure, A.

2012-01-01

Spatially explicit land cover land use (LCLU) change information is needed to drive biogeochemical models that simulate soil organic carbon (SOC) dynamics. Such information is increasingly being mapped using remotely sensed satellite data with classification schemes and uncertainties constrained by the sensing system, classification algorithms and land cover schemes. In this study, automated LCLU classification of multi-temporal Landsat satellite data were used to assess the sensitivity of SOC modeled by the Global Ensemble Biogeochemical Modeling System (GEMS). The GEMS was run for an area of 1560 km2 in Senegal under three climate change scenarios with LCLU maps generated using different Landsat classification approaches. This research provides a method to estimate the variability of SOC, specifically the SOC uncertainty due to satellite classification errors, which we show is dependent not only on the LCLU classification errors but also on where the LCLU classes occur relative to the other GEMS model inputs.

Integrating Environmental Genomics and Biogeochemical Models: a Gene-centric Approach

NASA Astrophysics Data System (ADS)

Reed, D. C.; Algar, C. K.; Huber, J. A.; Dick, G.

2013-12-01

Rapid advances in molecular microbial ecology have yielded an unprecedented amount of data about the evolutionary relationships and functional traits of microbial communities that regulate global geochemical cycles. Biogeochemical models, however, are trailing in the wake of the environmental genomics revolution and such models rarely incorporate explicit representations of bacteria and archaea, nor are they compatible with nucleic acid or protein sequence data. Here, we present a functional gene-based framework for describing microbial communities in biogeochemical models that uses genomics data and provides predictions that are readily testable using cutting-edge molecular tools. To demonstrate the approach in practice, nitrogen cycling in the Arabian Sea oxygen minimum zone (OMZ) was modelled to examine key questions about cryptic sulphur cycling and dinitrogen production pathways in OMZs. By directly linking geochemical dynamics to the genetic composition of microbial communities, the method provides mechanistic insights into patterns and biogeochemical consequences of marine microbes. Such an approach is critical for informing our understanding of the key role microbes play in modulating Earth's biogeochemistry.

Using Model-Based Reasoning for Autonomous Instrument Operation - Lessons Learned From IMAGE/LENA

NASA Technical Reports Server (NTRS)

Johnson, Michael A.; Rilee, Michael L.; Truszkowski, Walt; Bailin, Sidney C.

2001-01-01

Model-based reasoning has been applied as an autonomous control strategy on the Low Energy Neutral Atom (LENA) instrument currently flying on board the Imager for Magnetosphere-to-Aurora Global Exploration (IMAGE) spacecraft. Explicit models of instrument subsystem responses have been constructed and are used to dynamically adapt the instrument to the spacecraft's environment. These functions are cast as part of a Virtual Principal Investigator (VPI) that autonomously monitors and controls the instrument. In the VPI's current implementation, LENA's command uplink volume has been decreased significantly from its previous volume; typically, no uplinks are required for operations. This work demonstrates that a model-based approach can be used to enhance science instrument effectiveness. The components of LENA are common in space science instrumentation, and lessons learned by modeling this system may be applied to other instruments. Future work involves the extension of these methods to cover more aspects of LENA operation and the generalization to other space science instrumentation.

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

PubMed

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

2008-10-23

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

The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and Pilot Studies

NASA Technical Reports Server (NTRS)

Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P.; Antle, J. M.; Nelson, G. C.; Porter, C.; Janssen, S.;

CONSTRUCTING, PERTURBATION ANALYSIIS AND TESTING OF A MULTI-HABITAT PERIODIC MATRIX POPULATION MODEL

EPA Science Inventory

We present a matrix model that explicitly incorporates spatial habitat structure and seasonality and discuss preliminary results from a landscape level experimental test. Ecological risk to populations is often modeled without explicit treatment of spatially or temporally distri...

Ensemble superparameterization versus stochastic parameterization: A comparison of model uncertainty representation in tropical weather prediction

NASA Astrophysics Data System (ADS)

Subramanian, Aneesh C.; Palmer, Tim N.

2017-06-01

Stochastic schemes to represent model uncertainty in the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system has helped improve its probabilistic forecast skill over the past decade by both improving its reliability and reducing the ensemble mean error. The largest uncertainties in the model arise from the model physics parameterizations. In the tropics, the parameterization of moist convection presents a major challenge for the accurate prediction of weather and climate. Superparameterization is a promising alternative strategy for including the effects of moist convection through explicit turbulent fluxes calculated from a cloud-resolving model (CRM) embedded within a global climate model (GCM). In this paper, we compare the impact of initial random perturbations in embedded CRMs, within the ECMWF ensemble prediction system, with stochastically perturbed physical tendency (SPPT) scheme as a way to represent model uncertainty in medium-range tropical weather forecasts. We especially focus on forecasts of tropical convection and dynamics during MJO events in October-November 2011. These are well-studied events for MJO dynamics as they were also heavily observed during the DYNAMO field campaign. We show that a multiscale ensemble modeling approach helps improve forecasts of certain aspects of tropical convection during the MJO events, while it also tends to deteriorate certain large-scale dynamic fields with respect to stochastically perturbed physical tendencies approach that is used operationally at ECMWF.