Can We Use Regression Modeling to Quantify Mean Annual Streamflow at a Global-Scale?

Science.gov (United States)

Barbarossa, V.; Huijbregts, M. A. J.; Hendriks, J. A.; Beusen, A.; Clavreul, J.; King, H.; Schipper, A.

2016-12-01

Quantifying mean annual flow of rivers (MAF) at ungauged sites is essential for a number of applications, including assessments of global water supply, ecosystem integrity and water footprints. MAF 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 MAF based on climate and catchment characteristics. Yet, 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. In this study, we developed a global-scale regression model for MAF using observations of discharge and catchment characteristics from 1,885 catchments worldwide, ranging from 2 to 106 km2 in size. In addition, we compared the performance of the regression model with the predictive ability of the spatially explicit global hydrological model PCR-GLOBWB [van Beek et al., 2011] by comparing results from both models to independent measurements. We obtained a regression model explaining 89% of the variance in MAF based on catchment area, mean annual precipitation and air temperature, average slope and elevation. The regression model performed better than PCR-GLOBWB for the prediction of MAF, as root-mean-square error values were lower (0.29 - 0.38 compared to 0.49 - 0.57) and the modified index of agreement was higher (0.80 - 0.83 compared to 0.72 - 0.75). Our regression model can be applied globally at any point of the river network, provided that the input parameters are within the range of values employed in the calibration of the model. The performance is reduced for water scarce regions and further research should focus on improving such an aspect for regression-based global hydrological models.

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

Science.gov (United States)

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.

Orographic precipitation at global and regional scales: Observational uncertainty and evaluation of 25-km global model simulations

Science.gov (United States)

Schiemann, Reinhard; Roberts, Charles J.; Bush, Stephanie; Demory, Marie-Estelle; Strachan, Jane; Vidale, Pier Luigi; Mizielinski, Matthew S.; Roberts, Malcolm J.

2015-04-01

Precipitation over land exhibits a high degree of variability due to the complex interaction of the precipitation generating atmospheric processes with coastlines, the heterogeneous land surface, and orography. Global general circulation models (GCMs) have traditionally had very limited ability to capture this variability on the mesoscale (here ~50-500 km) due to their low resolution. This has changed with recent investments in resolution and ensembles of multidecadal climate simulations of atmospheric GCMs (AGCMs) with ~25 km grid spacing are becoming increasingly available. Here, we evaluate the mesoscale precipitation distribution in one such set of simulations obtained in the UPSCALE (UK on PrACE - weather-resolving Simulations of Climate for globAL Environmental risk) modelling campaign with the HadGEM-GA3 AGCM. Increased model resolution also poses new challenges to the observational datasets used to evaluate models. Global gridded data products such as those provided by the Global Precipitation Climatology Project (GPCP) are invaluable for assessing large-scale features of the precipitation distribution but may not sufficiently resolve mesoscale structures. In the absence of independent estimates, the intercomparison of different observational datasets may be the only way to get some insight into the uncertainties associated with these observations. Here, we focus on mid-latitude continental regions where observations based on higher-density gauge networks are available in addition to the global data sets: Europe/the Alps, South and East Asia, and the continental US. The ability of GCMs to represent mesoscale variability is of interest in its own right, as climate information on this scale is required by impact studies. An additional motivation for the research proposed here arises from continuing efforts to quantify the components of the global radiation budget and water cycle. Recent estimates based on radiation measurements suggest that the global mean

From global circulation to flood loss: Coupling models across the scales

Science.gov (United States)

Felder, Guido; Gomez-Navarro, Juan Jose; Bozhinova, Denica; Zischg, Andreas; Raible, Christoph C.; Ole, Roessler; Martius, Olivia; Weingartner, Rolf

2017-04-01

The prediction and the prevention of flood losses requires an extensive understanding of underlying meteorological, hydrological, hydraulic and damage processes. Coupled models help to improve the understanding of such underlying processes and therefore contribute the understanding of flood risk. Using such a modelling approach to determine potentially flood-affected areas and damages requires a complex coupling between several models operating at different spatial and temporal scales. Although the isolated parts of the single modelling components are well established and commonly used in the literature, a full coupling including a mesoscale meteorological model driven by a global circulation one, a hydrologic model, a hydrodynamic model and a flood impact and loss model has not been reported so far. In the present study, we tackle the application of such a coupled model chain in terms of computational resources, scale effects, and model performance. From a technical point of view, results show the general applicability of such a coupled model, as well as good model performance. From a practical point of view, such an approach enables the prediction of flood-induced damages, although some future challenges have been identified.

MODELING THE SUN’S SMALL-SCALE GLOBAL PHOTOSPHERIC MAGNETIC FIELD

Energy Technology Data Exchange (ETDEWEB)

Meyer, K. A. [Division of Computing and Mathematics, Abertay University, Kydd Building, Dundee, Bell Street, DD1 1HG, Scotland (United Kingdom); Mackay, D. H., E-mail: k.meyer@abertay.ac.uk [School of Mathematics and Statistics, University of St Andrews, North Haugh, St Andrews, KY16 9SS, Scotland (United Kingdom)

2016-10-20

We present a new model for the Sun’s global photospheric magnetic field during a deep minimum of activity, in which no active regions emerge. The emergence and subsequent evolution of small-scale magnetic features across the full solar surface is simulated, subject to the influence of a global supergranular flow pattern. Visually, the resulting simulated magnetograms reproduce the typical structure and scale observed in quiet Sun magnetograms. Quantitatively, the simulation quickly reaches a steady state, resulting in a mean field and flux distribution that are in good agreement with those determined from observations. A potential coronal magnetic field is extrapolated from the simulated full Sun magnetograms to consider the implications of such a quiet photospheric magnetic field on the corona and inner heliosphere. The bulk of the coronal magnetic field closes very low down, in short connections between small-scale features in the simulated magnetic network. Just 0.1% of the photospheric magnetic flux is found to be open at 2.5 R {sub ⊙}, around 10–100 times less than that determined for typical Helioseismic and Magnetic Imager synoptic map observations. If such conditions were to exist on the Sun, this would lead to a significantly weaker interplanetary magnetic field than is currently observed, and hence a much higher cosmic ray flux at Earth.

Modeling urbanization patterns at a global scale with generative adversarial networks

Science.gov (United States)

Albert, A. T.; Strano, E.; Gonzalez, M.

2017-12-01

Current demographic projections show that, in the next 30 years, global population growth will mostly take place in developing countries. Coupled with a decrease in density, such population growth could potentially double the land occupied by settlements by 2050. The lack of reliable and globally consistent socio-demographic data, coupled with the limited predictive performance underlying traditional urban spatial explicit models, call for developing better predictive methods, calibrated using a globally-consistent dataset. Thus, richer models of the spatial interplay between the urban built-up land, population distribution and energy use are central to the discussion around the expansion and development of cities, and their impact on the environment in the context of a changing climate. In this talk we discuss methods for, and present an analysis of, urban form, defined as the spatial distribution of macroeconomic quantities that characterize a city, using modern machine learning methods and best-available remote-sensing data for the world's largest 25,000 cities. We first show that these cities may be described by a small set of patterns in radial building density, nighttime luminosity, and population density, which highlight, to first order, differences in development and land use across the world. We observe significant, spatially-dependent variance around these typical patterns, which would be difficult to model using traditional statistical methods. We take a first step in addressing this challenge by developing CityGAN, a conditional generative adversarial network model for simulating realistic urban forms. To guide learning and measure the quality of the simulated synthetic cities, we develop a specialized loss function for GAN optimization that incorporates standard spatial statistics used by urban analysis experts. Our framework is a stark departure from both the standard physics-based approaches in the literature (that view urban forms as fractals with a

Large-scale groundwater modeling using global datasets: a test case for the Rhine-Meuse basin

Directory of Open Access Journals (Sweden)

E. H. Sutanudjaja

2011-09-01

Full Text Available The current generation of large-scale hydrological models does not include a groundwater flow component. Large-scale groundwater models, involving aquifers and basins of multiple countries, are still rare mainly due to a lack of hydro-geological data which are usually only available in developed countries. In this study, we propose a novel approach to construct large-scale groundwater models by using global datasets that are readily available. As the test-bed, we use the combined Rhine-Meuse basin that contains groundwater head data used to verify the model output. We start by building a distributed land surface model (30 arc-second resolution to estimate groundwater recharge and river discharge. Subsequently, a MODFLOW transient groundwater model is built and forced by the recharge and surface water levels calculated by the land surface model. Results are promising despite the fact that we still use an offline procedure to couple the land surface and MODFLOW groundwater models (i.e. the simulations of both models are separately performed. The simulated river discharges compare well to the observations. Moreover, based on our sensitivity analysis, in which we run several groundwater model scenarios with various hydro-geological parameter settings, we observe that the model can reasonably well reproduce the observed groundwater head time series. However, we note that there are still some limitations in the current approach, specifically because the offline-coupling technique simplifies the dynamic feedbacks between surface water levels and groundwater heads, and between soil moisture states and groundwater heads. Also the current sensitivity analysis ignores the uncertainty of the land surface model output. Despite these limitations, we argue that the results of the current model show a promise for large-scale groundwater modeling practices, including for data-poor environments and at the global scale.

Globalizing Lessons Learned from Regional-scale Observatories

Science.gov (United States)

Glenn, S. M.

2016-02-01

The Mid Atlantic Regional Association Coastal Ocean Observing System (MARACOOS) has accumulated a decade of experience designing, building and operating a Regional Coastal Ocean Observing System for the U.S. Integrated Ocean Observing System (IOOS). MARACOOS serves societal goals and supports scientific discovery at the scale of a Large Marine Ecosystem (LME). Societal themes include maritime safety, ecosystem decision support, coastal inundation, water quality and offshore energy. Scientific results that feed back on societal goals with better products include improved understanding of seasonal transport pathways and their impact on phytoplankton blooms and hypoxia, seasonal evolution of the subsurface Mid Atlantic Cold Pool and its impact on fisheries, biogeochemical transformations in coastal plumes, coastal ocean evolution and impact on hurricane intensities, and storm sediment transport pathways. As the global ocean observing requirements grow to support additional societal needs for information on fisheries and aquaculture, ocean acidification and deoxygenation, water quality and offshore development, global observing will necessarily evolve to include more coastal observations and forecast models at the scale of the world's many LMEs. Here we describe our efforts to share lessons learned between the observatory operators at the regional-scale of the LMEs. Current collaborators are spread across Europe, and also include Korea, Indonesia, Australia, Brazil and South Africa. Specific examples include the development of a world standard QA/QC approach for HF Radar data that will foster the sharing of data between countries, basin-scale underwater glider missions between internationally-distributed glider ports to developed a shared understanding of operations and an ongoing evaluation of the global ocean models in which the regional models for the LME will be nested, and joint training programs to develop the distributed teams of scientists and technicians

The carbon cycle in a land surface model: modelling, validation and implementation at a global scale; Cycle du carbone dans un modele de surface continentale: modelisation, validation et mise en oeuvre a l'echelle globale

Energy Technology Data Exchange (ETDEWEB)

Gibelin, A L

2007-05-15

ISBA-A-gs is an option of the CNRM land surface model ISBA which allows for the simulation of carbon exchanges between the terrestrial biosphere and the atmosphere. The model was implemented for the first time at the global scale as a stand-alone model. Several global simulations were performed to assess the sensitivity of the turbulent fluxes and Leaf Area Index to a doubling of the CO{sub 2} atmospheric concentration, and to the climate change simulated by the end of the 21. century. In addition, a new option of ISBA, referred to as ISBA-CC, was developed in order to simulate a more detailed ecosystem respiration by separating the autotrophic respiration and the heterotrophic respiration. The vegetation dynamics and the carbon fluxes were validated at a global scale using satellite datasets, and at a local scale using data from 26 sites of the FLUXNET network. All these results show that the model is sufficiently realistic to be coupled with a general circulation model, in order to account for interactions between the terrestrial biosphere, the atmosphere and the carbon cycle. (author)

Modelling Groundwater Depletion at Regional and Global Scales: Present State and Future Prospects.

Science.gov (United States)

Wada, Yoshihide

2015-01-01

Except for frozen water in ice and glaciers, groundwater is the world's largest distributed store of freshwater and has strategic importance to global food and water security. In this paper, the most recent advances quantifying groundwater depletion (GWD) are comprehensively reviewed. This paper critically evaluates the recently advanced modeling approaches estimating GWD at regional and global scales, and the evidence of feedbacks to the Earth system including sea-level rise associated with GWD. Finally, critical challenges and opportunities in the use of groundwater are identified for the adaption to growing food demand and uncertain climate.

Regionalizing global climate models

NARCIS (Netherlands)

Pitman, A.J.; Arneth, A.; Ganzeveld, L.N.

2012-01-01

Global climate models simulate the Earth's climate impressively at scales of continents and greater. At these scales, large-scale dynamics and physics largely define the climate. At spatial scales relevant to policy makers, and to impacts and adaptation, many other processes may affect regional and

The carbon cycle in a land surface model: modelling, validation and implementation at a global scale; Cycle du carbone dans un modele de surface continentale: modelisation, validation et mise en oeuvre a l'echelle globale

Energy Technology Data Exchange (ETDEWEB)

Gibelin, A.L

2007-05-15

ISBA-A-gs is an option of the CNRM land surface model ISBA which allows for the simulation of carbon exchanges between the terrestrial biosphere and the atmosphere. The model was implemented for the first time at the global scale as a stand-alone model. Several global simulations were performed to assess the sensitivity of the turbulent fluxes and Leaf Area Index to a doubling of the CO{sub 2} atmospheric concentration, and to the climate change simulated by the end of the 21. century. In addition, a new option of ISBA, referred to as ISBA-CC, was developed in order to simulate a more detailed ecosystem respiration by separating the autotrophic respiration and the heterotrophic respiration. The vegetation dynamics and the carbon fluxes were validated at a global scale using satellite datasets, and at a local scale using data from 26 sites of the FLUXNET network. All these results show that the model is sufficiently realistic to be coupled with a general circulation model, in order to account for interactions between the terrestrial biosphere, the atmosphere and the carbon cycle. (author)

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

Energy Technology Data Exchange (ETDEWEB)

Hattermann, F. F.; Krysanova, V.; Gosling, S. N.; Dankers, R.; Daggupati, P.; Donnelly, C.; Flörke, M.; Huang, S.; Motovilov, Y.; Buda, S.; Yang, T.; Müller, C.; Leng, G.; Tang, Q.; Portmann, F. T.; Hagemann, S.; Gerten, D.; Wada, Y.; Masaki, Y.; Alemayehu, T.; Satoh, Y.; Samaniego, L.

2017-01-04

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

Sources of uncertainties in modelling black carbon at the global scale

Directory of Open Access Journals (Sweden)

E. Vignati

2010-03-01

Full Text Available Our understanding of the global black carbon (BC cycle is essentially qualitative due to uncertainties in our knowledge of its properties. This work investigates two source of uncertainties in modelling black carbon: those due to the use of different schemes for BC ageing and its removal rate in the global Transport-Chemistry model TM5 and those due to the uncertainties in the definition and quantification of the observations, which propagate through to both the emission inventories, and the measurements used for the model evaluation.

The schemes for the atmospheric processing of black carbon that have been tested with the model are (i a simple approach considering BC as bulk aerosol and a simple treatment of the removal with fixed 70% of in-cloud black carbon concentrations scavenged by clouds and removed when rain is present and (ii a more complete description of microphysical ageing within an aerosol dynamics model, where removal is coupled to the microphysical properties of the aerosol, which results in a global average of 40% in-cloud black carbon that is scavenged in clouds and subsequently removed by rain, thus resulting in a longer atmospheric lifetime. This difference is reflected in comparisons between both sets of modelled results and the measurements. Close to the sources, both anthropogenic and vegetation fire source regions, the model results do not differ significantly, indicating that the emissions are the prevailing mechanism determining the concentrations and the choice of the aerosol scheme does not influence the levels. In more remote areas such as oceanic and polar regions the differences can be orders of magnitude, due to the differences between the two schemes. The more complete description reproduces the seasonal trend of the black carbon observations in those areas, although not always the magnitude of the signal, while the more simplified approach underestimates black carbon concentrations by orders of

Integrated modelling of anthropogenic land-use and land-cover change on the global scale

Science.gov (United States)

Schaldach, R.; Koch, J.; Alcamo, J.

2009-04-01

In many cases land-use activities go hand in hand with substantial modifications of the physical and biological cover of the Earth's surface, resulting in direct effects on energy and matter fluxes between terrestrial ecosystems and the atmosphere. For instance, the conversion of forest to cropland is changing climate relevant surface parameters (e.g. albedo) as well as evapotranspiration processes and carbon flows. In turn, human land-use decisions are also influenced by environmental processes. Changing temperature and precipitation patterns for example are important determinants for location and intensity of agriculture. Due to these close linkages, processes of land-use and related land-cover change should be considered as important components in the construction of Earth System models. A major challenge in modelling land-use change on the global scale is the integration of socio-economic aspects and human decision making with environmental processes. One of the few global approaches that integrates functional components to represent both anthropogenic and environmental aspects of land-use change, is the LandSHIFT model. It simulates the spatial and temporal dynamics of the human land-use activities settlement, cultivation of food crops and grazing management, which compete for the available land resources. The rational of the model is to regionalize the demands for area intensive commodities (e.g. crop production) and services (e.g. space for housing) from the country-level to a global grid with the spatial resolution of 5 arc-minutes. The modelled land-use decisions within the agricultural sector are influenced by changing climate and the resulting effects on biomass productivity. Currently, this causal chain is modelled by integrating results from the process-based vegetation model LPJmL model for changing crop yields and net primary productivity of grazing land. Model output of LandSHIFT is a time series of grid maps with land-use/land-cover information

Spatial scale separation in regional climate modelling

Energy Technology Data Exchange (ETDEWEB)

Feser, F.

2005-07-01

In this thesis the concept of scale separation is introduced as a tool for first improving regional climate model simulations and, secondly, to explicitly detect and describe the added value obtained by regional modelling. The basic idea behind this is that global and regional climate models have their best performance at different spatial scales. Therefore the regional model should not alter the global model's results at large scales. The for this purpose designed concept of nudging of large scales controls the large scales within the regional model domain and keeps them close to the global forcing model whereby the regional scales are left unchanged. For ensemble simulations nudging of large scales strongly reduces the divergence of the different simulations compared to the standard approach ensemble that occasionally shows large differences for the individual realisations. For climate hindcasts this method leads to results which are on average closer to observed states than the standard approach. Also the analysis of the regional climate model simulation can be improved by separating the results into different spatial domains. This was done by developing and applying digital filters that perform the scale separation effectively without great computational effort. The separation of the results into different spatial scales simplifies model validation and process studies. The search for 'added value' can be conducted on the spatial scales the regional climate model was designed for giving clearer results than by analysing unfiltered meteorological fields. To examine the skill of the different simulations pattern correlation coefficients were calculated between the global reanalyses, the regional climate model simulation and, as a reference, of an operational regional weather analysis. The regional climate model simulation driven with large-scale constraints achieved a high increase in similarity to the operational analyses for medium-scale 2 meter

A suite of global, cross-scale topographic variables for environmental and biodiversity modeling

Science.gov (United States)

Amatulli, Giuseppe; Domisch, Sami; Tuanmu, Mao-Ning; Parmentier, Benoit; Ranipeta, Ajay; Malczyk, Jeremy; Jetz, Walter

2018-03-01

Topographic variation underpins a myriad of patterns and processes in hydrology, climatology, geography and ecology and is key to understanding the variation of life on the planet. A fully standardized and global multivariate product of different terrain features has the potential to support many large-scale research applications, however to date, such datasets are unavailable. Here we used the digital elevation model products of global 250 m GMTED2010 and near-global 90 m SRTM4.1dev to derive a suite of topographic variables: elevation, slope, aspect, eastness, northness, roughness, terrain roughness index, topographic position index, vector ruggedness measure, profile/tangential curvature, first/second order partial derivative, and 10 geomorphological landform classes. We aggregated each variable to 1, 5, 10, 50 and 100 km spatial grains using several aggregation approaches. While a cross-correlation underlines the high similarity of many variables, a more detailed view in four mountain regions reveals local differences, as well as scale variations in the aggregated variables at different spatial grains. All newly-developed variables are available for download at Data Citation 1 and for download and visualization at http://www.earthenv.org/topography.

Multi-scale spatial modeling of human exposure from local sources to global intake

DEFF Research Database (Denmark)

Wannaz, Cedric; Fantke, Peter; Jolliet, Olivier

2018-01-01

Exposure studies, used in human health risk and impact assessments of chemicals are largely performed locally or regionally. It is usually not known how global impacts resulting from exposure to point source emissions compare to local impacts. To address this problem, we introduce Pangea......, an innovative multi-scale, spatial multimedia fate and exposure assessment model. We study local to global population exposure associated with emissions from 126 point sources matching locations of waste-to-energy plants across France. Results for three chemicals with distinct physicochemical properties...... occur within a 100 km radius from the source. This suggests that, by neglecting distant low-level exposure, local assessments might only account for fractions of global cumulative intakes. We also study ~10,000 emission locations covering France more densely to determine per chemical and exposure route...

Global fits of GUT-scale SUSY models with GAMBIT

Science.gov (United States)

Athron, Peter; Balázs, Csaba; Bringmann, Torsten; Buckley, Andy; Chrząszcz, Marcin; Conrad, Jan; Cornell, Jonathan M.; Dal, Lars A.; Edsjö, Joakim; Farmer, Ben; Jackson, Paul; Krislock, Abram; Kvellestad, Anders; Mahmoudi, Farvah; Martinez, Gregory D.; Putze, Antje; Raklev, Are; Rogan, Christopher; de Austri, Roberto Ruiz; Saavedra, Aldo; Savage, Christopher; Scott, Pat; Serra, Nicola; Weniger, Christoph; White, Martin

2017-12-01

We present the most comprehensive global fits to date of three supersymmetric models motivated by grand unification: the constrained minimal supersymmetric standard model (CMSSM), and its Non-Universal Higgs Mass generalisations NUHM1 and NUHM2. We include likelihoods from a number of direct and indirect dark matter searches, a large collection of electroweak precision and flavour observables, direct searches for supersymmetry at LEP and Runs I and II of the LHC, and constraints from Higgs observables. Our analysis improves on existing results not only in terms of the number of included observables, but also in the level of detail with which we treat them, our sampling techniques for scanning the parameter space, and our treatment of nuisance parameters. We show that stau co-annihilation is now ruled out in the CMSSM at more than 95% confidence. Stop co-annihilation turns out to be one of the most promising mechanisms for achieving an appropriate relic density of dark matter in all three models, whilst avoiding all other constraints. We find high-likelihood regions of parameter space featuring light stops and charginos, making them potentially detectable in the near future at the LHC. We also show that tonne-scale direct detection will play a largely complementary role, probing large parts of the remaining viable parameter space, including essentially all models with multi-TeV neutralinos.

Global fits of GUT-scale SUSY models with GAMBIT

Energy Technology Data Exchange (ETDEWEB)

Athron, Peter [Monash University, School of Physics and Astronomy, Melbourne, VIC (Australia); Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); Balazs, Csaba [Monash University, School of Physics and Astronomy, Melbourne, VIC (Australia); Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); Bringmann, Torsten; Dal, Lars A.; Krislock, Abram; Raklev, Are [University of Oslo, Department of Physics, Oslo (Norway); Buckley, Andy [University of Glasgow, SUPA, School of Physics and Astronomy, Glasgow (United Kingdom); Chrzaszcz, Marcin [Universitaet Zuerich, Physik-Institut, Zurich (Switzerland); H. Niewodniczanski Institute of Nuclear Physics, Polish Academy of Sciences, Krakow (Poland); Conrad, Jan; Edsjoe, Joakim; Farmer, Ben [AlbaNova University Centre, Oskar Klein Centre for Cosmoparticle Physics, Stockholm (Sweden); Stockholm University, Department of Physics, Stockholm (Sweden); Cornell, Jonathan M. [McGill University, Department of Physics, Montreal, QC (Canada); Jackson, Paul; White, Martin [Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); University of Adelaide, Department of Physics, Adelaide, SA (Australia); Kvellestad, Anders; Savage, Christopher [NORDITA, Stockholm (Sweden); Mahmoudi, Farvah [Univ Lyon, Univ Lyon 1, CNRS, ENS de Lyon, Centre de Recherche Astrophysique de Lyon UMR5574, Saint-Genis-Laval (France); Theoretical Physics Department, CERN, Geneva (Switzerland); Martinez, Gregory D. [University of California, Physics and Astronomy Department, Los Angeles, CA (United States); Putze, Antje [LAPTh, Universite de Savoie, CNRS, Annecy-le-Vieux (France); Rogan, Christopher [Harvard University, Department of Physics, Cambridge, MA (United States); Ruiz de Austri, Roberto [IFIC-UV/CSIC, Instituto de Fisica Corpuscular, Valencia (Spain); Saavedra, Aldo [Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); The University of Sydney, Faculty of Engineering and Information Technologies, Centre for Translational Data Science, School of Physics, Camperdown, NSW (Australia); Scott, Pat [Imperial College London, Department of Physics, Blackett Laboratory, London (United Kingdom); Serra, Nicola [Universitaet Zuerich, Physik-Institut, Zurich (Switzerland); Weniger, Christoph [University of Amsterdam, GRAPPA, Institute of Physics, Amsterdam (Netherlands); Collaboration: The GAMBIT Collaboration

2017-12-15

We present the most comprehensive global fits to date of three supersymmetric models motivated by grand unification: the constrained minimal supersymmetric standard model (CMSSM), and its Non-Universal Higgs Mass generalisations NUHM1 and NUHM2. We include likelihoods from a number of direct and indirect dark matter searches, a large collection of electroweak precision and flavour observables, direct searches for supersymmetry at LEP and Runs I and II of the LHC, and constraints from Higgs observables. Our analysis improves on existing results not only in terms of the number of included observables, but also in the level of detail with which we treat them, our sampling techniques for scanning the parameter space, and our treatment of nuisance parameters. We show that stau co-annihilation is now ruled out in the CMSSM at more than 95% confidence. Stop co-annihilation turns out to be one of the most promising mechanisms for achieving an appropriate relic density of dark matter in all three models, whilst avoiding all other constraints. We find high-likelihood regions of parameter space featuring light stops and charginos, making them potentially detectable in the near future at the LHC. We also show that tonne-scale direct detection will play a largely complementary role, probing large parts of the remaining viable parameter space, including essentially all models with multi-TeV neutralinos. (orig.)

Modeling Global Biogenic Emission of Isoprene: Exploration of Model Drivers

Science.gov (United States)

Alexander, Susan E.; Potter, Christopher S.; Coughlan, Joseph C.; Klooster, Steven A.; Lerdau, Manuel T.; Chatfield, Robert B.; Peterson, David L. (Technical Monitor)

1996-01-01

Vegetation provides the major source of isoprene emission to the atmosphere. We present a modeling approach to estimate global biogenic isoprene emission. The isoprene flux model is linked to a process-based computer simulation model of biogenic trace-gas fluxes that operates on scales that link regional and global data sets and ecosystem nutrient transformations Isoprene emission estimates are determined from estimates of ecosystem specific biomass, emission factors, and algorithms based on light and temperature. Our approach differs from an existing modeling framework by including the process-based global model for terrestrial ecosystem production, satellite derived ecosystem classification, and isoprene emission measurements from a tropical deciduous forest. We explore the sensitivity of model estimates to input parameters. The resulting emission products from the global 1 degree x 1 degree coverage provided by the satellite datasets and the process model allow flux estimations across large spatial scales and enable direct linkage to atmospheric models of trace-gas transport and transformation.

Continental and global scale flood forecasting systems

NARCIS (Netherlands)

Emerton, Rebecca E.; Stephens, Elisabeth M.; Pappenberger, Florian; Pagano, Thomas P.; Weerts, A.H.; Wood, A.; Salamon, Peter; Brown, James D.; Hjerdt, Niclas; Donnelly, Chantal; Baugh, Calum A.; Cloke, Hannah L.

2016-01-01

Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not

High-Resolution Global Modeling of the Effects of Subgrid-Scale Clouds and Turbulence on Precipitating Cloud Systems

Energy Technology Data Exchange (ETDEWEB)

Bogenschutz, Peter [National Center for Atmospheric Research, Boulder, CO (United States); Moeng, Chin-Hoh [National Center for Atmospheric Research, Boulder, CO (United States)

2015-10-13

The PI’s at the National Center for Atmospheric Research (NCAR), Chin-Hoh Moeng and Peter Bogenschutz, have primarily focused their time on the implementation of the Simplified-Higher Order Turbulence Closure (SHOC; Bogenschutz and Krueger 2013) to the Multi-scale Modeling Framework (MMF) global model and testing of SHOC on deep convective cloud regimes.

A new synoptic scale resolving global climate simulation using the Community Earth System Model

Science.gov (United States)

Small, R. Justin; Bacmeister, Julio; Bailey, David; Baker, Allison; Bishop, Stuart; Bryan, Frank; Caron, Julie; Dennis, John; Gent, Peter; Hsu, Hsiao-ming; Jochum, Markus; Lawrence, David; Muñoz, Ernesto; diNezio, Pedro; Scheitlin, Tim; Tomas, Robert; Tribbia, Joseph; Tseng, Yu-heng; Vertenstein, Mariana

2014-12-01

High-resolution global climate modeling holds the promise of capturing planetary-scale climate modes and small-scale (regional and sometimes extreme) features simultaneously, including their mutual interaction. This paper discusses a new state-of-the-art high-resolution Community Earth System Model (CESM) simulation that was performed with these goals in mind. The atmospheric component was at 0.25° grid spacing, and ocean component at 0.1°. One hundred years of "present-day" simulation were completed. Major results were that annual mean sea surface temperature (SST) in the equatorial Pacific and El-Niño Southern Oscillation variability were well simulated compared to standard resolution models. Tropical and southern Atlantic SST also had much reduced bias compared to previous versions of the model. In addition, the high resolution of the model enabled small-scale features of the climate system to be represented, such as air-sea interaction over ocean frontal zones, mesoscale systems generated by the Rockies, and Tropical Cyclones. Associated single component runs and standard resolution coupled runs are used to help attribute the strengths and weaknesses of the fully coupled run. The high-resolution run employed 23,404 cores, costing 250 thousand processor-hours per simulated year and made about two simulated years per day on the NCAR-Wyoming supercomputer "Yellowstone."

Global Energy and Water Cycle Experiment (GEWEX) and the Continental-scale International Project (GCIP)

Science.gov (United States)

Vane, Deborah

1993-01-01

A discussion of the objectives of the Global Energy and Water Cycle Experiment (GEWEX) and the Continental-scale International Project (GCIP) is presented in vugraph form. The objectives of GEWEX are as follows: determine the hydrological cycle by global measurements; model the global hydrological cycle; improve observations and data assimilation; and predict response to environmental change. The objectives of GCIP are as follows: determine the time/space variability of the hydrological cycle over a continental-scale region; develop macro-scale hydrologic models that are coupled to atmospheric models; develop information retrieval schemes; and support regional climate change impact assessment.

Effects of climate variability on global scale flood risk

Science.gov (United States)

Ward, P.; Dettinger, M. D.; Kummu, M.; Jongman, B.; Sperna Weiland, F.; Winsemius, H.

2013-12-01

research. We carried out the research by simulating daily river discharge using a global hydrological model (PCR-GLOBWB), forced with gridded climate reanalysis time-series. From this, we derived peak annual flood volumes for large-scale river basins globally. These were used to force a global inundation model (dynRout) to map inundation extent and depth for return periods between 2 and 1000 years, under El Niño conditions, neutral conditions, and La Niña conditions. Theses flood hazard maps were combined with global datasets on socioeconomic variables such as population and income to represent the socioeconomic exposure to flooding, and depth-damage curves to represent vulnerability.

Global terrestrial biogeochemistry: Perturbations, interactions, and time scales

Energy Technology Data Exchange (ETDEWEB)

Braswell, B.H. Jr.

1996-12-01

Global biogeochemical processes are being perturbed by human activity, principally that which is associated with industrial activity and expansion of urban and agricultural complexes. Perturbations have manifested themselves at least since the beginning of the 19th Century, and include emissions of CO{sub 2} and other pollutants from fossil fuel combustion, agricultural emissions of reactive nitrogen, and direct disruption of ecosystem function through land conversion. These perturbations yield local impacts, but there are also global consequences that are the sum of local-scale influences. Several approaches to understanding the global-scale implications of chemical perturbations to the Earth system are discussed. The lifetime of anthropogenic CO{sub 2} in the atmosphere is an important concept for understanding the current and future commitment to an altered atmospheric heat budget. The importance of the terrestrial biogeochemistry relative to the lifetime of excess CO{sub 2} is demonstrated using dynamic, aggregated models of the global carbon cycle.

Global scale ionospheric irregularities associated with thunderstorm activity

CERN Document Server

Pulinets, S A

2002-01-01

The potential difference near 280 kV exists between ground and ionosphere. This potential difference is generated by thunderstorm discharges all over the world, and return current closes the circuit in the areas of fair weather (so-called fair weather current). The model calculations and experimental measurements clearly demonstrate non-uniform latitude-longitude distribution of electric field within the atmosphere. The recent calculations show that the strong large scale vertical atmospheric electric field can penetrate into the ionosphere and create large scale irregularities of the electron concentration. To check this the global distributions of thunderstorm activity obtained with the satellite monitoring for different seasons were compared with the global distributions of ionosphere critical frequency (which is equivalent to peak electron concentration) obtained with the help of satellite topside sounding. The similarity of the obtained global distributions clearly demonstrates the effects of thunderstor...

The scaling structure of the global road network.

Science.gov (United States)

Strano, Emanuele; Giometto, Andrea; Shai, Saray; Bertuzzo, Enrico; Mucha, Peter J; Rinaldo, Andrea

2017-10-01

Because of increasing global urbanization and its immediate consequences, including changes in patterns of food demand, circulation and land use, the next century will witness a major increase in the extent of paved roads built worldwide. To model the effects of this increase, it is crucial to understand whether possible self-organized patterns are inherent in the global road network structure. Here, we use the largest updated database comprising all major roads on the Earth, together with global urban and cropland inventories, to suggest that road length distributions within croplands are indistinguishable from urban ones, once rescaled to account for the difference in mean road length. Such similarity extends to road length distributions within urban or agricultural domains of a given area. We find two distinct regimes for the scaling of the mean road length with the associated area, holding in general at small and at large values of the latter. In suitably large urban and cropland domains, we find that mean and total road lengths increase linearly with their domain area, differently from earlier suggestions. Scaling regimes suggest that simple and universal mechanisms regulate urban and cropland road expansion at the global scale. As such, our findings bear implications for global road infrastructure growth based on land-use change and for planning policies sustaining urban expansions.

Using Scaling to Understand, Model and Predict Global Scale Anthropogenic and Natural Climate Change

Science.gov (United States)

Lovejoy, S.; del Rio Amador, L.

2014-12-01

The atmosphere is variable over twenty orders of magnitude in time (≈10-3 to 1017 s) and almost all of the variance is in the spectral "background" which we show can be divided into five scaling regimes: weather, macroweather, climate, macroclimate and megaclimate. We illustrate this with instrumental and paleo data. Based the signs of the fluctuation exponent H, we argue that while the weather is "what you get" (H>0: fluctuations increasing with scale), that it is macroweather (Hdecreasing with scale) - not climate - "that you expect". The conventional framework that treats the background as close to white noise and focuses on quasi-periodic variability assumes a spectrum that is in error by a factor of a quadrillion (≈ 1015). Using this scaling framework, we can quantify the natural variability, distinguish it from anthropogenic variability, test various statistical hypotheses and make stochastic climate forecasts. For example, we estimate the probability that the warming is simply a giant century long natural fluctuation is less than 1%, most likely less than 0.1% and estimate return periods for natural warming events of different strengths and durations, including the slow down ("pause") in the warming since 1998. The return period for the pause was found to be 20-50 years i.e. not very unusual; however it immediately follows a 6 year "pre-pause" warming event of almost the same magnitude with a similar return period (30 - 40 years). To improve on these unconditional estimates, we can use scaling models to exploit the long range memory of the climate process to make accurate stochastic forecasts of the climate including the pause. We illustrate stochastic forecasts on monthly and annual scale series of global and northern hemisphere surface temperatures. We obtain forecast skill nearly as high as the theoretical (scaling) predictability limits allow: for example, using hindcasts we find that at 10 year forecast horizons we can still explain ≈ 15% of the

Scaling behaviour of the global tropopause

Directory of Open Access Journals (Sweden)

C. Varotsos

2009-01-01

Full Text Available Detrended fluctuation analysis is applied to the time series of the global tropopause height derived from the 1980–2004 daily radiosonde data, in order to detect long-range correlations in its time evolution.

Global tropopause height fluctuations in small time-intervals are found to be positively correlated to those in larger time intervals in a power-law fashion. The exponent of this dependence is larger in the tropics than in the middle and high latitudes in both hemispheres. Greater persistence is observed in the tropopause of the Northern than in the Southern Hemisphere. A plausible physical explanation of the fact that long-range correlations in tropopause variability decreases with increasing latitude is that the column ozone fluctuations (that are closely related with the tropopause ones exhibit long range correlations, which are larger in tropics than in the middle and high latitudes at long time scales.

This finding for the tropopause height variability should reduce the existing uncertainties in assessing the climatic characteristics. More specifically the reliably modelled values of a climatic variable (i.e. past and future simulations must exhibit the same scaling behaviour with that possibly existing in the real observations of the variable under consideration. An effort has been made to this end by applying the detrended fluctuation analysis to the global mean monthly land and sea surface temperature anomalies during the period January 1850–August 2008. The result obtained supports the findings presented above, notably: the correlations between the fluctuations in the global mean monthly land and sea surface temperature display scaling behaviour which must characterizes any projection.

Preparing for Exascale: Towards convection-permitting, global atmospheric simulations with the Model for Prediction Across Scales (MPAS)

Science.gov (United States)

Heinzeller, Dominikus; Duda, Michael G.; Kunstmann, Harald

2017-04-01

With strong financial and political support from national and international initiatives, exascale computing is projected for the end of this decade. Energy requirements and physical limitations imply the use of accelerators and the scaling out to orders of magnitudes larger numbers of cores then today to achieve this milestone. In order to fully exploit the capabilities of these Exascale computing systems, existing applications need to undergo significant development. The Model for Prediction Across Scales (MPAS) is a novel set of Earth system simulation components and consists of an atmospheric core, an ocean core, a land-ice core and a sea-ice core. Its distinct features are the use of unstructured Voronoi meshes and C-grid discretisation to address shortcomings of global models on regular grids and the use of limited area models nested in a forcing data set, with respect to parallel scalability, numerical accuracy and physical consistency. Here, we present work towards the application of the atmospheric core (MPAS-A) on current and future high performance computing systems for problems at extreme scale. In particular, we address the issue of massively parallel I/O by extending the model to support the highly scalable SIONlib library. Using global uniform meshes with a convection-permitting resolution of 2-3km, we demonstrate the ability of MPAS-A to scale out to half a million cores while maintaining a high parallel efficiency. We also demonstrate the potential benefit of a hybrid parallelisation of the code (MPI/OpenMP) on the latest generation of Intel's Many Integrated Core Architecture, the Intel Xeon Phi Knights Landing.

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

Science.gov (United States)

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

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

Science.gov (United States)

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

Global scale ionospheric irregularities associated with thunderstorm activity

International Nuclear Information System (INIS)

Pulinets, Sergey A.; Depuev, Victor H.

2003-01-01

The potential difference near 280 kV exists between ground and ionosphere. This potential difference is generated by thunderstorm discharges all over the world, and return current closes the circuit in the areas of fair weather (so-called fair weather current). The model calculations and experimental measurements clearly demonstrate non-uniform latitude-longitude distribution of electric field within the atmosphere. The recent calculations show that the strong large scale vertical atmospheric electric field can penetrate into the ionosphere and create large scale irregularities of the electron concentration. To check this the global distributions of thunderstorm activity obtained with the satellite monitoring for different seasons were compared with the global distributions of ionosphere critical frequency (which is equivalent to peak electron concentration) obtained with the help of satellite topside sounding. The similarity of the obtained global distributions clearly demonstrates the effects of thunderstorm electric fields onto the Earth's ionosphere. (author)

The Global Tsunami Model (GTM)

Science.gov (United States)

Lorito, S.; Basili, R.; Harbitz, C. B.; Løvholt, F.; Polet, J.; Thio, H. K.

2017-12-01

The tsunamis occurred worldwide in the last two decades have highlighted the need for a thorough understanding of the risk posed by relatively infrequent but often disastrous tsunamis and the importance of a comprehensive and consistent methodology for quantifying the hazard. In the last few years, several methods for probabilistic tsunami hazard analysis have been developed and applied to different parts of the world. In an effort to coordinate and streamline these activities and make progress towards implementing the Sendai Framework of Disaster Risk Reduction (SFDRR) we have initiated a Global Tsunami Model (GTM) working group with the aim of i) enhancing our understanding of tsunami hazard and risk on a global scale and developing standards and guidelines for it, ii) providing a portfolio of validated tools for probabilistic tsunami hazard and risk assessment at a range of scales, and iii) developing a global tsunami hazard reference model. This GTM initiative has grown out of the tsunami component of the Global Assessment of Risk (GAR15), which has resulted in an initial global model of probabilistic tsunami hazard and risk. Started as an informal gathering of scientists interested in advancing tsunami hazard analysis, the GTM is currently in the process of being formalized through letters of interest from participating institutions. The initiative has now been endorsed by the United Nations International Strategy for Disaster Reduction (UNISDR) and the World Bank's Global Facility for Disaster Reduction and Recovery (GFDRR). We will provide an update on the state of the project and the overall technical framework, and discuss the technical issues that are currently being addressed, including earthquake source recurrence models, the use of aleatory variability and epistemic uncertainty, and preliminary results for a probabilistic global hazard assessment, which is an update of the model included in UNISDR GAR15.

The Spatial Scaling of Global Rainfall Extremes

Science.gov (United States)

Devineni, N.; Xi, C.; Lall, U.; Rahill-Marier, B.

2013-12-01

Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (upto 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. A clear understanding of the space-time rainfall patterns for events or for a season will enable in assessing the spatial distribution of areas likely to have a high/low inundation potential for each type of rainfall forcing. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances. We also investigate the connection of persistent rainfall events at different latitudinal bands to large-scale climate phenomena such as ENSO. Finally, we present the scaling phenomena of contiguous flooded areas as a result of large scale organization of long duration rainfall events. This can be used for spatially distributed flood risk assessment conditional on a particular rainfall scenario. Statistical models for spatio-temporal loss simulation including model uncertainty to support regional and portfolio analysis can be developed.

Multi-scale Modeling of Arctic Clouds

Science.gov (United States)

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.

Cloud Geospatial Analysis Tools for Global-Scale Comparisons of Population Models for Decision Making

Science.gov (United States)

Hancher, M.; Lieber, A.; Scott, L.

2017-12-01

The volume of satellite and other Earth data is growing rapidly. Combined with information about where people are, these data can inform decisions in a range of areas including food and water security, disease and disaster risk management, biodiversity, and climate adaptation. Google's platform for planetary-scale geospatial data analysis, Earth Engine, grants access to petabytes of continually updating Earth data, programming interfaces for analyzing the data without the need to download and manage it, and mechanisms for sharing the analyses and publishing results for data-driven decision making. In addition to data about the planet, data about the human planet - population, settlement and urban models - are now available for global scale analysis. The Earth Engine APIs enable these data to be joined, combined or visualized with economic or environmental indicators such as nighttime lights trends, global surface water, or climate projections, in the browser without the need to download anything. We will present our newly developed application intended to serve as a resource for government agencies, disaster response and public health programs, or other consumers of these data to quickly visualize the different population models, and compare them to ground truth tabular data to determine which model suits their immediate needs. Users can further tap into the power of Earth Engine and other Google technologies to perform a range of analysis from simple statistics in custom regions to more complex machine learning models. We will highlight case studies in which organizations around the world have used Earth Engine to combine population data with multiple other sources of data, such as water resources and roads data, over deep stacks of temporal imagery to model disease risk and accessibility to inform decisions.

The Nature of Global Large-scale Sea Level Variability in Relation to Atmospheric Forcing: A Modeling Study

Science.gov (United States)

Fukumori, I.; Raghunath, R.; Fu, L. L.

1996-01-01

The relation between large-scale sea level variability and ocean circulation is studied using a numerical model. A global primitive equaiton model of the ocean is forced by daily winds and climatological heat fluxes corresponding to the period from January 1992 to February 1996. The physical nature of the temporal variability from periods of days to a year, are examined based on spectral analyses of model results and comparisons with satellite altimetry and tide gauge measurements.

Regional-Scale Forcing and Feedbacks from Alternative Scenarios of Global-Scale Land Use Change

Science.gov (United States)

Jones, A. D.; Chini, L. P.; Collins, W.; Janetos, A. C.; Mao, J.; Shi, X.; Thomson, A. M.; Torn, M. S.

2011-12-01

Future patterns of land use change depend critically on the degree to which terrestrial carbon management strategies, such as biological carbon sequestration and biofuels, are utilized in order to mitigate global climate change. Furthermore, land use change associated with terrestrial carbon management induces biogeophysical changes to surface energy budgets that perturb climate at regional and possibly global scales, activating different feedback processes depending on the nature and location of the land use change. As a first step in a broader effort to create an integrated earth system model, we examine two scenarios of future anthropogenic activity generated by the Global Change Assessment Model (GCAM) within the full-coupled Community Earth System Model (CESM). Each scenario stabilizes radiative forcing from greenhouse gases and aerosols at 4.5 W/m^2. In the first, stabilization is achieved through a universal carbon tax that values terrestrial carbon equally with fossil carbon, leading to modest afforestation globally and low biofuel utilization. In the second scenario, stabilization is achieved with a tax on fossil fuel and industrial carbon alone. In this case, biofuel utilization increases dramatically and crop area expands to claim approximately 50% of forest cover globally. By design, these scenarios exhibit identical climate forcing from atmospheric constituents. Thus, differences among them can be attributed to the biogeophysical effects of land use change. In addition, we utilize offline radiative transfer and offline land model simulations to identify forcing and feedback mechanisms operating in different regions. We find that boreal deforestation has a strong climatic signature due to significant albedo change coupled with a regional-scale water vapor feedback. Tropical deforestation, on the other hand, has more subtle effects on climate. Globally, the two scenarios yield warming trends over the 21st century that differ by 0.5 degrees Celsius. This

Global Atmosphere Watch Workshop on Measurement-Model ...

Science.gov (United States)

The World Meteorological Organization’s (WMO) Global Atmosphere Watch (GAW) Programme coordinates high-quality observations of atmospheric composition from global to local scales with the aim to drive high-quality and high-impact science while co-producing a new generation of products and services. In line with this vision, GAW’s Scientific Advisory Group for Total Atmospheric Deposition (SAG-TAD) has a mandate to produce global maps of wet, dry and total atmospheric deposition for important atmospheric chemicals to enable research into biogeochemical cycles and assessments of ecosystem and human health effects. The most suitable scientific approach for this activity is the emerging technique of measurement-model fusion for total atmospheric deposition. This technique requires global-scale measurements of atmospheric trace gases, particles, precipitation composition and precipitation depth, as well as predictions of the same from global/regional chemical transport models. The fusion of measurement and model results requires data assimilation and mapping techniques. The objective of the GAW Workshop on Measurement-Model Fusion for Global Total Atmospheric Deposition (MMF-GTAD), an initiative of the SAG-TAD, was to review the state-of-the-science and explore the feasibility and methodology of producing, on a routine retrospective basis, global maps of atmospheric gas and aerosol concentrations as well as wet, dry and total deposition via measurement-model

Value of river discharge data for global-scale hydrological modeling

Directory of Open Access Journals (Sweden)

M. Hunger

2008-05-01

Full Text Available This paper investigates the value of observed river discharge data for global-scale hydrological modeling of a number of flow characteristics that are e.g. required for assessing water resources, flood risk and habitat alteration of aquatic ecosystems. An improved version of the WaterGAP Global Hydrology Model (WGHM was tuned against measured discharge using either the 724-station dataset (V1 against which former model versions were tuned or an extended dataset (V2 of 1235 stations. WGHM is tuned by adjusting one model parameter (γ that affects runoff generation from land areas in order to fit simulated and observed long-term average discharge at tuning stations. In basins where γ does not suffice to tune the model, two correction factors are applied successively: the areal correction factor corrects local runoff in a basin and the station correction factor adjusts discharge directly the gauge. Using station correction is unfavorable, as it makes discharge discontinuous at the gauge and inconsistent with runoff in the upstream basin. The study results are as follows. (1 Comparing V2 to V1, the global land area covered by tuning basins increases by 5% and the area where the model can be tuned by only adjusting γ increases by 8%. However, the area where a station correction factor (and not only an areal correction factor has to be applied more than doubles. (2 The value of additional discharge information for representing the spatial distribution of long-term average discharge (and thus renewable water resources with WGHM is high, particularly for river basins outside of the V1 tuning area and in regions where the refined dataset provides a significant subdivision of formerly extended tuning basins (average V2 basin size less than half the V1 basin size. If the additional discharge information were not used for tuning, simulated long-term average discharge would differ from the observed one by a factor of, on average, 1.8 in the formerly

Does a General Temperature-Dependent Q10 Model of Soil Respiration Exist at Biome and Global Scale?

Institute of Scientific and Technical Information of China (English)

Hua CHEN; Han-Qin TIAN

2005-01-01

Soil respiration (SR) is commonly modeled by a Q10 (an indicator of temperature sensitivity)function in ecosystem models. Q10is usually treated as a constant of 2 in these models, although Q10 value of SR often decreases with increasing temperatures. It remains unclear whether a general temperaturedependent Q10 model of SR exists at biome and global scale. In this paper, we have compiled the long-term Q10 data of 38 SR studies ranging from the Boreal, Temperate, to Tropical/Subtropical biome on four continents.Our analysis indicated that the general temperature-dependent biome Q10 models of SR existed, especially in the Boreal and Temperate biomes. A single-exponential model was better than a simple linear model in fitting the average Q10 values at the biome scale. Average soil temperature is a better predictor of Q10 value than average air temperature in these models, especially in the Boreal biome. Soil temperature alone could explain about 50% of the Q10 variations in both the Boreal and Temperate biome single-exponential Q10 model. Q10 value of SR decreased with increasing soil temperature but at quite different rates among the three biome Q10 models. The k values (Q10 decay rate constants) were 0.09, 0.07, and 0.02/℃ in the Boreal, Temperate, and Tropical/Subtropical biome, respectively, suggesting that Q10 value is the most sensitive to soil temperature change in the Boreal biome, the second in the Temperate biome, and the least sensitive in the Tropical/Subtropical biome. This also indirectly confirms that acclimation of SR in many soil warming experiments probably occurs. The k value in the "global" single-exponential Q10 model which combined both the Boreal and Temperate biome data set was 0.08/℃. However, the global general temperature-dependent Q10model developed using the data sets of the three biomes is not adequate for predicting Q10 values of SR globally.The existence of the general temperature-dependent Q10 models of SR in the Boreal and

Multi-Scale Models for the Scale Interaction of Organized Tropical Convection

Science.gov (United States)

Yang, Qiu

Assessing the upscale impact of organized tropical convection from small spatial and temporal scales is a research imperative, not only for having a better understanding of the multi-scale structures of dynamical and convective fields in the tropics, but also for eventually helping in the design of new parameterization strategies to improve the next-generation global climate models. Here self-consistent multi-scale models are derived systematically by following the multi-scale asymptotic methods and used to describe the hierarchical structures of tropical atmospheric flows. The advantages of using these multi-scale models lie in isolating the essential components of multi-scale interaction and providing assessment of the upscale impact of the small-scale fluctuations onto the large-scale mean flow through eddy flux divergences of momentum and temperature in a transparent fashion. Specifically, this thesis includes three research projects about multi-scale interaction of organized tropical convection, involving tropical flows at different scaling regimes and utilizing different multi-scale models correspondingly. Inspired by the observed variability of tropical convection on multiple temporal scales, including daily and intraseasonal time scales, the goal of the first project is to assess the intraseasonal impact of the diurnal cycle on the planetary-scale circulation such as the Hadley cell. As an extension of the first project, the goal of the second project is to assess the intraseasonal impact of the diurnal cycle over the Maritime Continent on the Madden-Julian Oscillation. In the third project, the goals are to simulate the baroclinic aspects of the ITCZ breakdown and assess its upscale impact on the planetary-scale circulation over the eastern Pacific. These simple multi-scale models should be useful to understand the scale interaction of organized tropical convection and help improve the parameterization of unresolved processes in global climate models.

Sensitivities in global scale modeling of isoprene

Directory of Open Access Journals (Sweden)

R. von Kuhlmann

2004-01-01

Full Text Available A sensitivity study of the treatment of isoprene and related parameters in 3D atmospheric models was conducted using the global model of tropospheric chemistry MATCH-MPIC. A total of twelve sensitivity scenarios which can be grouped into four thematic categories were performed. These four categories consist of simulations with different chemical mechanisms, different assumptions concerning the deposition characteristics of intermediate products, assumptions concerning the nitrates from the oxidation of isoprene and variations of the source strengths. The largest differences in ozone compared to the reference simulation occured when a different isoprene oxidation scheme was used (up to 30-60% or about 10 nmol/mol. The largest differences in the abundance of peroxyacetylnitrate (PAN were found when the isoprene emission strength was reduced by 50% and in tests with increased or decreased efficiency of the deposition of intermediates. The deposition assumptions were also found to have a significant effect on the upper tropospheric HOx production. Different implicit assumptions about the loss of intermediate products were identified as a major reason for the deviations among the tested isoprene oxidation schemes. The total tropospheric burden of O3 calculated in the sensitivity runs is increased compared to the background methane chemistry by 26±9  Tg( O3 from 273 to an average from the sensitivity runs of 299 Tg(O3. % revised Thus, there is a spread of ± 35% of the overall effect of isoprene in the model among the tested scenarios. This range of uncertainty and the much larger local deviations found in the test runs suggest that the treatment of isoprene in global models can only be seen as a first order estimate at present, and points towards specific processes in need of focused future work.

Bringing the Global Scale to Education in Natural Resources Management

Science.gov (United States)

Turner, D. P.

2017-12-01

Given the ominous trajectory of rapid global environmental change, environmental managers must grapple with global scale structures, processes, and concepts. The concept of the Anthropocene Epoch, albeit contested, is highly integrative across disciplines and temporal scales, and thus potentially helpful in the context of educating environmental managers. It can be framed temporally in terms of the geologic history of the global environment, the initiation and acceleration of anthropogenic impacts on the environment, and a future global environment that is highly dependent on human decisions. A key lesson from Earth's pre-human geologic history is that global climate has generally been linked to greenhouse gas concentrations, and many mass extinction events were associated with high greenhouse gas concentrations. The pervasive impacts of the contemporary technosphere on the biosphere point especially to the need to conserve biosphere capital. Scenarios of Earth's future environment, based on Earth system models, suggest that business-as-usual technologies and economic practices will set the stage for a biophysical environment that is hostile (if not inimical) to a high technology global civilization. These lessons can inform and inspire sub-global management efforts to mitigate and adapt to global environmental change.

Modeling Root Exudation, Priming and Protection in Soil Carbon Responses to Elevated CO2 from Ecosystem to Global Scales

Science.gov (United States)

Sulman, B. N.; Phillips, R.; Shevliakova, E.; Oishi, A. C.; Pacala, S. W.

2014-12-01

The sensitivity of soil organic carbon (SOC) to changing environmental conditions represents a critical uncertainty in coupled carbon cycle-climate models. Much of this uncertainty arises from our limited understanding of the extent to which plants induce SOC losses (through accelerated decomposition or "priming") or promote SOC gains (via stabilization through physico-chemical protection). We developed a new SOC model, "Carbon, Organisms, Rhizosphere and Protection in the Soil Environment" (CORPSE), to examine the net effect of priming and protection in response to rising atmospheric CO2, and conducted simulations of rhizosphere priming effects at both ecosystem and global scales. At the ecosystem scale, the model successfully captured and explained disparate SOC responses at the Duke and Oak Ridge free-air CO2 enrichment (FACE) experiments. We show that stabilization of "new" carbon in protected SOC pools may equal or exceed microbial priming of "old" SOC in ecosystems with readily decomposable litter (e.g. Oak Ridge). In contrast, carbon losses owing to priming dominate the net SOC response in ecosystems with more resistant litters (e.g. Duke). For global simulations, the model was fully integrated into the Geophysical Fluid Dynamics Laboratory (GFDL) land model LM3. Globally, priming effects driven by enhanced root exudation and expansion of the rhizosphere reduced SOC storage in the majority of terrestrial areas, partially counterbalancing SOC gains from the enhanced ecosystem productivity driven by CO2 fertilization. Collectively, our results suggest that SOC stocks globally depend not only on temperature and moisture, but also on vegetation responses to environmental changes, and that protected C may provide an important constraint on priming effects.

Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balance

Science.gov (United States)

Tang, G.; Bartlein, P. J.

2012-01-01

Water balance models of simple structure are easier to grasp and more clearly connect cause and effect than models of complex structure. Such models are essential for studying large spatial scale land surface water balance in the context of climate and land cover change, both natural and anthropogenic. This study aims to (i) develop a large spatial scale water balance model by modifying a dynamic global vegetation model (DGVM), and (ii) test the model's performance in simulating actual evapotranspiration (ET), soil moisture and surface runoff for the coterminous United States (US). Toward these ends, we first introduced development of the "LPJ-Hydrology" (LH) model by incorporating satellite-based land covers into the Lund-Potsdam-Jena (LPJ) DGVM instead of dynamically simulating them. We then ran LH using historical (1982-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells. The simulated ET, soil moisture and surface runoff were compared to existing sets of observed or simulated data for the US. The results indicated that LH captures well the variation of monthly actual ET (R2 = 0.61, p 0.46, p 0.52) with observed values over the years 1982-2006, respectively. The modeled spatial patterns of annual ET and surface runoff are in accordance with previously published data. Compared to its predecessor, LH simulates better monthly stream flow in winter and early spring by incorporating effects of solar radiation on snowmelt. Overall, this study proves the feasibility of incorporating satellite-based land-covers into a DGVM for simulating large spatial scale land surface water balance. LH developed in this study should be a useful tool for studying effects of climate and land cover change on land surface hydrology at large spatial scales.

Carbon budgets of biological soil crusts at micro-, meso-, and global scales

Science.gov (United States)

Sancho, Leopoldo G; Belnap, Jayne; Colesie, Claudia; Raggio, Jose; Weber, Bettina

2016-01-01

The importance of biocrusts in the ecology of arid lands across all continents is widely recognized. In spite of this broad distribution, contributions of biocrusts to the global biogeochemical cycles have only recently been considered. While these studies opened a new view on the global role of biocrusts, they also clearly revealed the lack of data for many habitats and of overall standards for measurements and analysis. In order to understand carbon cycling in biocrusts and the progress which has been made during the last 15 years, we offer a multi-scale approach covering different climatic regions. We also include a discussion on available measurement techniques at each scale: A micro-scale section focuses on the individual organism level, including modeling based on the combination of field and lab data. The meso-scale section addresses the CO2 exchange of a complete ecosystem or at the community level. Finally, we consider the contribution of biocrusts at a global scale, giving a general perspective of the most relevant findings regarding the role of biological soil crusts in the global terrestrial carbon cycle.

Constraining the global carbon budget from global to regional scales - The measurement challenge

International Nuclear Information System (INIS)

Francey, R.J.; Rayner, P.J.; Allison, C.E.

2002-01-01

The Global Carbon Cycle can be modelled by a Bayesian synthesis inversion technique, where measured atmospheric CO 2 concentrations and isotopic compositions are analysed by use of an atmospheric transport model and estimates of regional sources and sinks of atmospheric carbon. The uncertainty associated to carbon flux estimates even on a regional scale can be improved considerably using the inversion technique. In this approach, besides the necessary control on the precision of atmospheric transport models and on the constraints for surface fluxes, an important component is the calibration of atmospheric CO 2 concentration and isotope measurements. The recent improved situation in respect to data comparability is discussed using results of conducted interlaboratory comparison exercises and larger scale calibration programs are proposed for the future to further improve the comparability of analytical data. (author)

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

Science.gov (United States)

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.

Modeling Aircraft Emissions for Regional-scale Air Quality: Adapting a New Global Aircraft Emissions Database for the U.S

Science.gov (United States)

Arunachalam, S.; Baek, B. H.; Vennam, P. L.; Woody, M. C.; Omary, M.; Binkowski, F.; Fleming, G.

2012-12-01

Commercial aircraft emit substantial amounts of pollutants during their complete activity cycle that ranges from landing-and-takeoff (LTO) at airports to cruising in upper elevations of the atmosphere, and affect both air quality and climate. Since these emissions are not uniformly emitted over the earth, and have substantial temporal and spatial variability, it is vital to accurately evaluate and quantify the relative impacts of aviation emissions on ambient air quality. Regional-scale air quality modeling applications do not routinely include these aircraft emissions from all cycles. Federal Aviation Administration (FAA) has developed the Aviation Environmental Design Tool (AEDT), a software system that dynamically models aircraft performance in space and time to calculate fuel burn and emissions from gate-to-gate for all commercial aviation activity from all airports globally. To process in-flight aircraft emissions and to provide a realistic representation of these for treatment in grid-based air quality models, we have developed an interface processor called AEDTproc that accurately distributes full-flight chorded emissions in time and space to create gridded, hourly model-ready emissions input data. Unlike the traditional emissions modeling approach of treating aviation emissions as ground-level sources or processing emissions only from the LTO cycles in regional-scale air quality studies, AEDTproc distributes chorded inventories of aircraft emissions during LTO cycles and cruise activities into a time-variant 3-D gridded structure. We will present results of processed 2006 global emissions from AEDT over a continental U.S. modeling domain to support a national-scale air quality assessment of the incremental impacts of aircraft emissions on surface air quality. This includes about 13.6 million flights within the U.S. out of 31.2 million flights globally. We will focus on assessing spatio-temporal variability of these commercial aircraft emissions, and

Water dependency and water exploitation at global scale as indicators of water security

Science.gov (United States)

De Roo, A. P. J.; Beck, H.; Burek, P.; Bernard, B.

2015-12-01

A water dependency index has been developed indicating the dependency of water consumption from upstream sources of water, sometimes across (multiple) national border. This index is calculated at global scale using the 0.1 global LISFLOOD hydrological modelling system forced by WFDEI meteorological data for the timeframe 1979-2012. The global LISFLOOD model simulates the most important hydrological processes, as well as water abstraction and consumption from various sectors, and flood routing, at daily scale, with sub-timesteps for routing and subgrid parameterization related to elevation and landuse. The model contains also options for water allocation, to allow preferences of water use for particular sectors in water scarce periods. LISFLOOD is also used for the Global Flood Awareness System (GloFAS), the European Flood Awareness System (EFAS), continental scale climate change impact studies on floods and droughts. The water dependency indicator is calculated on a monthly basis, and various annual and multiannual indicators are derived from it. In this study, the indicator will be compared against water security areas known from other studies. Other indicators calculated are the Water Exploitation Index (WEI+), which is a commonly use water security indicator in Europe, and freshwater resources per capita indicators at regional, national and river basin scale. Several climate scnearios are run to indicate future trends in water security.

Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison.

Science.gov (United States)

Prestele, Reinhard; Alexander, Peter; Rounsevell, Mark D A; Arneth, Almut; Calvin, Katherine; Doelman, Jonathan; Eitelberg, David A; Engström, Kerstin; Fujimori, Shinichiro; Hasegawa, Tomoko; Havlik, Petr; Humpenöder, Florian; Jain, Atul K; Krisztin, Tamás; Kyle, Page; Meiyappan, Prasanth; Popp, Alexander; Sands, Ronald D; Schaldach, Rüdiger; Schüngel, Jan; Stehfest, Elke; Tabeau, Andrzej; Van Meijl, Hans; Van Vliet, Jasper; Verburg, Peter H

2016-12-01

Model-based global projections of future land-use and land-cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC

Modeling lightning-NOx chemistry on a sub-grid scale in a global chemical transport model

Directory of Open Access Journals (Sweden)

A. Gressent

2016-05-01

Full Text Available For the first time, a plume-in-grid approach is implemented in a chemical transport model (CTM to parameterize the effects of the nonlinear reactions occurring within high concentrated NOx plumes from lightning NOx emissions (LNOx in the upper troposphere. It is characterized by a set of parameters including the plume lifetime, the effective reaction rate constant related to NOx–O3 chemical interactions, and the fractions of NOx conversion into HNO3 within the plume. Parameter estimates were made using the Dynamical Simple Model of Atmospheric Chemical Complexity (DSMACC box model, simple plume dispersion simulations, and the 3-D Meso-NH (non-hydrostatic mesoscale atmospheric model. In order to assess the impact of the LNOx plume approach on the NOx and O3 distributions on a large scale, simulations for the year 2006 were performed using the GEOS-Chem global model with a horizontal resolution of 2° × 2.5°. The implementation of the LNOx parameterization implies an NOx and O3 decrease on a large scale over the region characterized by a strong lightning activity (up to 25 and 8 %, respectively, over central Africa in July and a relative increase downwind of LNOx emissions (up to 18 and 2 % for NOx and O3, respectively, in July. The calculated variability in NOx and O3 mixing ratios around the mean value according to the known uncertainties in the parameter estimates is at a maximum over continental tropical regions with ΔNOx [−33.1, +29.7] ppt and ΔO3 [−1.56, +2.16] ppb, in January, and ΔNOx [−14.3, +21] ppt and ΔO3 [−1.18, +1.93] ppb, in July, mainly depending on the determination of the diffusion properties of the atmosphere and the initial NO mixing ratio injected by lightning. This approach allows us (i to reproduce a more realistic lightning NOx chemistry leading to better NOx and O3 distributions on the large scale and (ii to focus on other improvements to reduce remaining uncertainties from processes

Spatiotemporal models of global soil organic carbon stock to support land degradation assessments at regional and global scales: limitations, challenges and opportunities

Science.gov (United States)

Hengl, Tomislav; Heuvelink, Gerard; Sanderman, Jonathan; MacMillan, Robert

2017-04-01

There is an increasing interest in fitting and applying spatiotemporal models that can be used to assess and monitor soil organic carbon stocks (SOCS), for example, in support of the '4 pourmille' initiative aiming at soil carbon sequestration towards climate change adaptation and mitigation and UN's Land Degradation Neutrality indicators and similar degradation assessment projects at regional and global scales. The land cover mapping community has already produced several spatiotemporal data sets with global coverage and at relatively fine resolution e.g. USGS MODIS land cover annual maps for period 2000-2014; European Space Agency land cover maps at 300 m resolution for the year 2000, 2005 and 2010; Chinese GlobeLand30 dataset available for years 2000 and 2010; Columbia University's WRI GlobalForestWatch with deforestation maps at 30 m resolution for the period 2000-2016 (Hansen et al. 2013). These data sets can be used for land degradation assessment and scenario testing at global and regional scales (Wei et al 2014). Currently, however, no compatible global spatiotemporal data sets exist on status of soil quality and/or soil health (Powlson et al. 2013). This paper describes an initial effort to devise and evaluate a procedure for mapping spatio-temporal changes in SOC stocks using a complete stack of soil forming factors (climate, relief, land cover, land use, lithology and living organisms) represented mainly through remote sensing based time series of Earth images. For model building we used some 75,000 geo-referenced soil profiles and a stacks space-time covariates (land cover, land use, biomass, climate) at two standard resolutions: (1) 10 km resolution with data available for period 1920-2014 and (2) 1000 m resolution with data available for period 2000-2014. The initial results show that, although it is technically feasible to produce space time estimates of SOCS that demonstrate the procedure, the estimates are relatively uncertain (<45% of variation

An integrated model to simulate sown area changes for major crops at a global scale

Institute of Scientific and Technical Information of China (English)

SHIBASAKI; Ryosuke

2008-01-01

Dynamics of land use systems have attracted much attention from scientists around the world due to their ecological and socio-economic implications. An integrated model to dynamically simulate future changes in sown areas of four major crops (rice, maize, wheat and soybean) on a global scale is pre- sented. To do so, a crop choice model was developed on the basis of Multinomial Logit (Logit) model to model land users’ decisions on crop choices among a set of available alternatives with using a crop utility function. A GIS-based Environmental Policy Integrated Climate (EPIC) model was adopted to simulate the crop yields under a given geophysical environment and farming management conditions, while the International Food Policy and Agricultural Simulation (IFPSIM) model was utilized to estimate crop price in the international market. The crop choice model was linked with the GIS-based EPIC model and the IFPSIM model through data exchange. This integrated model was then validated against the FAO statistical data in 2001-2003 and the Moderate Resolution Imaging Spectroradiometer (MODIS) global land cover product in 2001. Both validation approaches indicated reliability of the model for ad- dressing the dynamics in agricultural land use and its capability for long-term scenario analysis. Finally, the model application was designed to run over a time period of 30 a, taking the year 2000 as baseline. The model outcomes can help understand and explain the causes, locations and consequences of land use changes, and provide support for land use planning and policy making.

An integrated model to simulate sown area changes for major crops at a global scale

Institute of Scientific and Technical Information of China (English)

WU WenBin; YANG Peng; MENG ChaoYing; SHIBASAKI Ryosuke; ZHOU QingBo; TANG HuaJun; SHI Yun

2008-01-01

Dynamics of land use systems have attracted much attention from scientists around the world due to their ecological and socio-economic implications. An integrated model to dynamically simulate future changes in sown areas of four major crops (rice, maize, wheat and soybean) on a global scale is presented. To do so, a crop choice model was developed on the basis of Multinomial Logit (Logit) model to model land users' decisions on crop choices among a set of available alternatives with using a crop utility function. A GIS-based Environmental Policy Integrated Climate (EPIC) model was adopted to simulate the crop yields under a given geophysical environment and farming management conditions,while the International Food Policy and Agricultural Simulation (IFPSIM) model was utilized to estimate crop price in the international market. The crop choice model was linked with the GIS-based EPIC model and the IFPSIM model through data exchange. This integrated model was then validated against the FAO statistical data in 2001-2003 and the Moderate Resolution Imaging Spectroradiometer (MODIS)global land cover product in 2001. Both validation approaches indicated reliability of the model for addressing the dynamics in agricultural land use and its capability for long-term scenario analysis. Finally,the model application was designed to run over a time period of 30 a, taking the year 2000 as baseline.The model outcomes can help understand and explain the causes, locations and consequences of land use changes, and provide support for land use planning and policy making.

A comparison of changes in river runoff from multiple global and catchment-scale hydrological models under global warming scenarios of 1 °C, 2 °C and 3 °C

NARCIS (Netherlands)

Gosling, S.N.; Zaherpour, J.J.; Mount, N.J.; Hattermann, F.F.; Dankers, R.; Arheimer, B.; Breuer, L.; Ding, J.; Haddeland, I.; Kumar, R.; Kundu, D.; Liu, J.; van Griensven, A.; Veldkamp, T.I.E.; Vetter, T.; Wang, X.; Zhang, X.

2017-01-01

We present one of the first climate change impact assessments on river runoff that utilises an ensemble of global hydrological models (Glob-HMs) and an ensemble of catchment-scale hydrological models (Cat-HMs), across multiple catchments: the upper Amazon, Darling, Ganges, Lena, upper Mississippi,

The sensitivity of soil respiration to soil temperature, moisture, and carbon supply at the global scale.

Science.gov (United States)

Hursh, Andrew; Ballantyne, Ashley; Cooper, Leila; Maneta, Marco; Kimball, John; Watts, Jennifer

2017-05-01

Soil respiration (Rs) is a major pathway by which fixed carbon in the biosphere is returned to the atmosphere, yet there are limits to our ability to predict respiration rates using environmental drivers at the global scale. While temperature, moisture, carbon supply, and other site characteristics are known to regulate soil respiration rates at plot scales within certain biomes, quantitative frameworks for evaluating the relative importance of these factors across different biomes and at the global scale require tests of the relationships between field estimates and global climatic data. This study evaluates the factors driving Rs at the global scale by linking global datasets of soil moisture, soil temperature, primary productivity, and soil carbon estimates with observations of annual Rs from the Global Soil Respiration Database (SRDB). We find that calibrating models with parabolic soil moisture functions can improve predictive power over similar models with asymptotic functions of mean annual precipitation. Soil temperature is comparable with previously reported air temperature observations used in predicting Rs and is the dominant driver of Rs in global models; however, within certain biomes soil moisture and soil carbon emerge as dominant predictors of Rs. We identify regions where typical temperature-driven responses are further mediated by soil moisture, precipitation, and carbon supply and regions in which environmental controls on high Rs values are difficult to ascertain due to limited field data. Because soil moisture integrates temperature and precipitation dynamics, it can more directly constrain the heterotrophic component of Rs, but global-scale models tend to smooth its spatial heterogeneity by aggregating factors that increase moisture variability within and across biomes. We compare statistical and mechanistic models that provide independent estimates of global Rs ranging from 83 to 108 Pg yr -1 , but also highlight regions of uncertainty

Climate Controls AM Fungal Distributions from Global to Local Scales

Science.gov (United States)

Kivlin, S. N.; Hawkes, C.; Muscarella, R.; Treseder, K. K.; Kazenel, M.; Lynn, J.; Rudgers, J.

2016-12-01

Arbuscular mycorrhizal (AM) fungi have key functions in terrestrial biogeochemical processes; thus, determining the relative importance of climate, edaphic factors, and plant community composition on their geographic distributions can improve predictions of their sensitivity to global change. Local adaptation by AM fungi to plant hosts, soil nutrients, and climate suggests that all of these factors may control fungal geographic distributions, but their relative importance is unknown. We created species distribution models for 142 AM fungal taxa at the global scale with data from GenBank. We compared climate variables (BioClim and soil moisture), edaphic variables (phosphorus, carbon, pH, and clay content), and plant variables using model selection on models with (1) all variables, (2) climatic variables only (including soil moisture) and (3) resource-related variables only (all other soil parameters and NPP) using the MaxEnt algorithm evaluated with ENMEval. We also evaluated whether drivers of AM fungal distributions were phylogenetically conserved. To test whether global correlates of AM fungal distributions were reflected at local scales, we then surveyed AM fungi in nine plant hosts along three elevation gradients in the Upper Gunnison Basin, Colorado, USA. At the global scale, the distributions of 55% of AM fungal taxa were affected by both climate and soil resources, whereas 16% were only affected by climate and 29% were only affected by soil resources. Even for AM fungi that were affected by both climate and resources, the effects of climatic variables nearly always outweighed those of resources. Soil moisture and isothermality were the main climatic and NPP and soil carbon the main resource related factors influencing AM fungal distributions. Distributions of closely related AM fungal taxa were similarly affected by climate, but not by resources. Local scale surveys of AM fungi across elevations confirmed that climate was a key driver of AM fungal

Spatial Scaling of Global Rainfall and Flood Extremes

Science.gov (United States)

Devineni, Naresh; Lall, Upmanu; Xi, Chen; Ward, Philip

2014-05-01

Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration and spatial extent of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (up to 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances and floods. We present the first ever results on a global analysis of the scaling characteristics of extreme rainfall and flood event duration, volumes and contiguous flooded areas as a result of large scale organization of long duration rainfall events. Results are organized by latitude and with reference to the phases of ENSO, and reveal surprising invariance across latitude. Speculation as to the potential relation to the dynamical factors is presented

Global Hail Model

Science.gov (United States)

Werner, A.; Sanderson, M.; Hand, W.; Blyth, A.; Groenemeijer, P.; Kunz, M.; Puskeiler, M.; Saville, G.; Michel, G.

2012-04-01

Hail risk models are rare for the insurance industry. This is opposed to the fact that average annual hail losses can be large and hail dominates losses for many motor portfolios worldwide. Insufficient observational data, high spatio-temporal variability and data inhomogenity have hindered creation of credible models so far. In January 2012, a selected group of hail experts met at Willis in London in order to discuss ways to model hail risk at various scales. Discussions aimed at improving our understanding of hail occurrence and severity, and covered recent progress in the understanding of microphysical processes and climatological behaviour and hail vulnerability. The final outcome of the meeting was the formation of a global hail risk model initiative and the launch of a realistic global hail model in order to assess hail loss occurrence and severities for the globe. The following projects will be tackled: Microphysics of Hail and hail severity measures: Understand the physical drivers of hail and hailstone size development in different regions on the globe. Proposed factors include updraft and supercooled liquid water content in the troposphere. What are the thresholds drivers of hail formation around the globe? Hail Climatology: Consider ways to build a realistic global climatological set of hail events based on physical parameters including spatial variations in total availability of moisture, aerosols, among others, and using neural networks. Vulnerability, Exposure, and financial model: Use historical losses and event footprints available in the insurance market to approximate fragility distributions and damage potential for various hail sizes for property, motor, and agricultural business. Propagate uncertainty distributions and consider effects of policy conditions along with aggregating and disaggregating exposure and losses. This presentation provides an overview of ideas and tasks that lead towards a comprehensive global understanding of hail risk for

Nonstandard scaling law of fluctuations in finite-size systems of globally coupled oscillators.

Science.gov (United States)

Nishikawa, Isao; Tanaka, Gouhei; Aihara, Kazuyuki

2013-08-01

Universal scaling laws form one of the central issues in physics. A nonstandard scaling law or a breakdown of a standard scaling law, on the other hand, can often lead to the finding of a new universality class in physical systems. Recently, we found that a statistical quantity related to fluctuations follows a nonstandard scaling law with respect to the system size in a synchronized state of globally coupled nonidentical phase oscillators [I. Nishikawa et al., Chaos 22, 013133 (2012)]. However, it is still unclear how widely this nonstandard scaling law is observed. In the present paper, we discuss the conditions required for the unusual scaling law in globally coupled oscillator systems and validate the conditions by numerical simulations of several different models.

Biodiversity and Climate Modeling Workshop Series: Identifying gaps and needs for improving large-scale biodiversity models

Science.gov (United States)

Weiskopf, S. R.; Myers, B.; Beard, T. D.; Jackson, S. T.; Tittensor, D.; Harfoot, M.; Senay, G. B.

2017-12-01

At the global scale, well-accepted global circulation models and agreed-upon scenarios for future climate from the Intergovernmental Panel on Climate Change (IPCC) are available. In contrast, biodiversity modeling at the global scale lacks analogous tools. While there is great interest in development of similar bodies and efforts for international monitoring and modelling of biodiversity at the global scale, equivalent modelling tools are in their infancy. This lack of global biodiversity models compared to the extensive array of general circulation models provides a unique opportunity to bring together climate, ecosystem, and biodiversity modeling experts to promote development of integrated approaches in modeling global biodiversity. Improved models are needed to understand how we are progressing towards the Aichi Biodiversity Targets, many of which are not on track to meet the 2020 goal, threatening global biodiversity conservation, monitoring, and sustainable use. We brought together biodiversity, climate, and remote sensing experts to try to 1) identify lessons learned from the climate community that can be used to improve global biodiversity models; 2) explore how NASA and other remote sensing products could be better integrated into global biodiversity models and 3) advance global biodiversity modeling, prediction, and forecasting to inform the Aichi Biodiversity Targets, the 2030 Sustainable Development Goals, and the Intergovernmental Platform on Biodiversity and Ecosystem Services Global Assessment of Biodiversity and Ecosystem Services. The 1st In-Person meeting focused on determining a roadmap for effective assessment of biodiversity model projections and forecasts by 2030 while integrating and assimilating remote sensing data and applying lessons learned, when appropriate, from climate modeling. Here, we present the outcomes and lessons learned from our first E-discussion and in-person meeting and discuss the next steps for future meetings.

Global-scale hydrological response to future glacier mass loss

Science.gov (United States)

Huss, Matthias; Hock, Regine

2018-01-01

Worldwide glacier retreat and associated future runoff changes raise major concerns over the sustainability of global water resources1-4, but global-scale assessments of glacier decline and the resulting hydrological consequences are scarce5,6. Here we compute global glacier runoff changes for 56 large-scale glacierized drainage basins to 2100 and analyse the glacial impact on streamflow. In roughly half of the investigated basins, the modelled annual glacier runoff continues to rise until a maximum (`peak water') is reached, beyond which runoff steadily declines. In the remaining basins, this tipping point has already been passed. Peak water occurs later in basins with larger glaciers and higher ice-cover fractions. Typically, future glacier runoff increases in early summer but decreases in late summer. Although most of the 56 basins have less than 2% ice coverage, by 2100 one-third of them might experience runoff decreases greater than 10% due to glacier mass loss in at least one month of the melt season, with the largest reductions in central Asia and the Andes. We conclude that, even in large-scale basins with minimal ice-cover fraction, the downstream hydrological effects of continued glacier wastage can be substantial, but the magnitudes vary greatly among basins and throughout the melt season.

Landslide susceptibility mapping on a global scale using the method of logistic regression

Directory of Open Access Journals (Sweden)

L. Lin

2017-08-01

Full Text Available This paper proposes a statistical model for mapping global landslide susceptibility based on logistic regression. After investigating explanatory factors for landslides in the existing literature, five factors were selected for model landslide susceptibility: relative relief, extreme precipitation, lithology, ground motion and soil moisture. When building the model, 70 % of landslide and nonlandslide points were randomly selected for logistic regression, and the others were used for model validation. To evaluate the accuracy of predictive models, this paper adopts several criteria including a receiver operating characteristic (ROC curve method. Logistic regression experiments found all five factors to be significant in explaining landslide occurrence on a global scale. During the modeling process, percentage correct in confusion matrix of landslide classification was approximately 80 % and the area under the curve (AUC was nearly 0.87. During the validation process, the above statistics were about 81 % and 0.88, respectively. Such a result indicates that the model has strong robustness and stable performance. This model found that at a global scale, soil moisture can be dominant in the occurrence of landslides and topographic factor may be secondary.

Current and future levels of mercury atmospheric pollution on a global scale

Science.gov (United States)

Pacyna, Jozef M.; Travnikov, Oleg; De Simone, Francesco; Hedgecock, Ian M.; Sundseth, Kyrre; Pacyna, Elisabeth G.; Steenhuisen, Frits; Pirrone, Nicola; Munthe, John; Kindbom, Karin

2016-10-01

An assessment of current and future emissions, air concentrations, and atmospheric deposition of mercury worldwide is presented on the basis of results obtained during the performance of the EU GMOS (Global Mercury Observation System) project. Emission estimates for mercury were prepared with the main goal of applying them in models to assess current (2013) and future (2035) air concentrations and atmospheric deposition of this contaminant. The combustion of fossil fuels (mainly coal) for energy and heat production in power plants and in industrial and residential boilers, as well as artisanal and small-scale gold mining, is one of the major anthropogenic sources of Hg emissions to the atmosphere at present. These sources account for about 37 and 25 % of the total anthropogenic Hg emissions globally, estimated to be about 2000 t. Emissions in Asian countries, particularly in China and India, dominate the total emissions of Hg. The current estimates of mercury emissions from natural processes (primary mercury emissions and re-emissions), including mercury depletion events, were estimated to be 5207 t year-1, which represents nearly 70 % of the global mercury emission budget. Oceans are the most important sources (36 %), followed by biomass burning (9 %). A comparison of the 2035 anthropogenic emissions estimated for three different scenarios with current anthropogenic emissions indicates a reduction of these emissions in 2035 up to 85 % for the best-case scenario. Two global chemical transport models (GLEMOS and ECHMERIT) have been used for the evaluation of future mercury pollution levels considering future emission scenarios. Projections of future changes in mercury deposition on a global scale simulated by these models for three anthropogenic emissions scenarios of 2035 indicate a decrease in up to 50 % deposition in the Northern Hemisphere and up to 35 % in Southern Hemisphere for the best-case scenario. The EU GMOS project has proved to be a very important

Current and future levels of mercury atmospheric pollution on a global scale

Directory of Open Access Journals (Sweden)

J. M. Pacyna

2016-10-01

Full Text Available An assessment of current and future emissions, air concentrations, and atmospheric deposition of mercury worldwide is presented on the basis of results obtained during the performance of the EU GMOS (Global Mercury Observation System project. Emission estimates for mercury were prepared with the main goal of applying them in models to assess current (2013 and future (2035 air concentrations and atmospheric deposition of this contaminant. The combustion of fossil fuels (mainly coal for energy and heat production in power plants and in industrial and residential boilers, as well as artisanal and small-scale gold mining, is one of the major anthropogenic sources of Hg emissions to the atmosphere at present. These sources account for about 37 and 25 % of the total anthropogenic Hg emissions globally, estimated to be about 2000 t. Emissions in Asian countries, particularly in China and India, dominate the total emissions of Hg. The current estimates of mercury emissions from natural processes (primary mercury emissions and re-emissions, including mercury depletion events, were estimated to be 5207 t year−1, which represents nearly 70 % of the global mercury emission budget. Oceans are the most important sources (36 %, followed by biomass burning (9 %. A comparison of the 2035 anthropogenic emissions estimated for three different scenarios with current anthropogenic emissions indicates a reduction of these emissions in 2035 up to 85 % for the best-case scenario. Two global chemical transport models (GLEMOS and ECHMERIT have been used for the evaluation of future mercury pollution levels considering future emission scenarios. Projections of future changes in mercury deposition on a global scale simulated by these models for three anthropogenic emissions scenarios of 2035 indicate a decrease in up to 50 % deposition in the Northern Hemisphere and up to 35 % in Southern Hemisphere for the best-case scenario. The EU GMOS project has

Global river flood hazard maps: hydraulic modelling methods and appropriate uses

Science.gov (United States)

Townend, Samuel; Smith, Helen; Molloy, James

2014-05-01

Flood hazard is not well understood or documented in many parts of the world. Consequently, the (re-)insurance sector now needs to better understand where the potential for considerable river flooding aligns with significant exposure. For example, international manufacturing companies are often attracted to countries with emerging economies, meaning that events such as the 2011 Thailand floods have resulted in many multinational businesses with assets in these regions incurring large, unexpected losses. This contribution addresses and critically evaluates the hydraulic methods employed to develop a consistent global scale set of river flood hazard maps, used to fill the knowledge gap outlined above. The basis of the modelling approach is an innovative, bespoke 1D/2D hydraulic model (RFlow) which has been used to model a global river network of over 5.3 million kilometres. Estimated flood peaks at each of these model nodes are determined using an empirically based rainfall-runoff approach linking design rainfall to design river flood magnitudes. The hydraulic model is used to determine extents and depths of floodplain inundation following river bank overflow. From this, deterministic flood hazard maps are calculated for several design return periods between 20-years and 1,500-years. Firstly, we will discuss the rationale behind the appropriate hydraulic modelling methods and inputs chosen to produce a consistent global scaled river flood hazard map. This will highlight how a model designed to work with global datasets can be more favourable for hydraulic modelling at the global scale and why using innovative techniques customised for broad scale use are preferable to modifying existing hydraulic models. Similarly, the advantages and disadvantages of both 1D and 2D modelling will be explored and balanced against the time, computer and human resources available, particularly when using a Digital Surface Model at 30m resolution. Finally, we will suggest some

Aerosol-cloud interactions from urban, regional to global scales

International Nuclear Information System (INIS)

Wang, Yuan

2015-01-01

The studies in this dissertation aim at advancing our scientific understandings about physical processes involved in the aerosol-cloud-precipitation interaction and quantitatively assessing the impacts of aerosols on the cloud systems with diverse scales over the globe on the basis of the observational data analysis and various modeling studies. As recognized in the Fifth Assessment Report by the Inter-government Panel on Climate Change, the magnitude of radiative forcing by atmospheric aerosols is highly uncertain, representing the largest uncertainty in projections of future climate by anthropogenic activities. By using a newly implemented cloud microphysical scheme in the cloud-resolving model, the thesis assesses aerosol-cloud interaction for distinct weather systems, ranging from individual cumulus to mesoscale convective systems. This thesis also introduces a novel hierarchical modeling approach that solves a long outstanding mismatch between simulations by regional weather models and global climate models in the climate modeling community. More importantly, the thesis provides key scientific solutions to several challenging questions in climate science, including the global impacts of the Asian pollution. As scientists wrestle with the complexities of climate change in response to varied anthropogenic forcing, perhaps no problem is more challenging than the understanding of the impacts of atmospheric aerosols from air pollution on clouds and the global circulation.

Aerosol-cloud interactions from urban, regional to global scales

Energy Technology Data Exchange (ETDEWEB)

Wang, Yuan [California Institute of Technology, Pasadena, CA (United States). Seismological Lab.

2015-10-01

The studies in this dissertation aim at advancing our scientific understandings about physical processes involved in the aerosol-cloud-precipitation interaction and quantitatively assessing the impacts of aerosols on the cloud systems with diverse scales over the globe on the basis of the observational data analysis and various modeling studies. As recognized in the Fifth Assessment Report by the Inter-government Panel on Climate Change, the magnitude of radiative forcing by atmospheric aerosols is highly uncertain, representing the largest uncertainty in projections of future climate by anthropogenic activities. By using a newly implemented cloud microphysical scheme in the cloud-resolving model, the thesis assesses aerosol-cloud interaction for distinct weather systems, ranging from individual cumulus to mesoscale convective systems. This thesis also introduces a novel hierarchical modeling approach that solves a long outstanding mismatch between simulations by regional weather models and global climate models in the climate modeling community. More importantly, the thesis provides key scientific solutions to several challenging questions in climate science, including the global impacts of the Asian pollution. As scientists wrestle with the complexities of climate change in response to varied anthropogenic forcing, perhaps no problem is more challenging than the understanding of the impacts of atmospheric aerosols from air pollution on clouds and the global circulation.

Prospects for improving the representation of coastal and shelf seas in global ocean models

Science.gov (United States)

Holt, Jason; Hyder, Patrick; Ashworth, Mike; Harle, James; Hewitt, Helene T.; Liu, Hedong; New, Adrian L.; Pickles, Stephen; Porter, Andrew; Popova, Ekaterina; Icarus Allen, J.; Siddorn, John; Wood, Richard

2017-02-01

Accurately representing coastal and shelf seas in global ocean models represents one of the grand challenges of Earth system science. They are regions of immense societal importance through the goods and services they provide, hazards they pose and their role in global-scale processes and cycles, e.g. carbon fluxes and dense water formation. However, they are poorly represented in the current generation of global ocean models. In this contribution, we aim to briefly characterise the problem, and then to identify the important physical processes, and their scales, needed to address this issue in the context of the options available to resolve these scales globally and the evolving computational landscape.We find barotropic and topographic scales are well resolved by the current state-of-the-art model resolutions, e.g. nominal 1/12°, and still reasonably well resolved at 1/4°; here, the focus is on process representation. We identify tides, vertical coordinates, river inflows and mixing schemes as four areas where modelling approaches can readily be transferred from regional to global modelling with substantial benefit. In terms of finer-scale processes, we find that a 1/12° global model resolves the first baroclinic Rossby radius for only ˜ 8 % of regions benefit of improved resolution and process representation using 1/12° global- and basin-scale northern North Atlantic nucleus for a European model of the ocean (NEMO) simulations; the latter includes tides and a k-ɛ vertical mixing scheme. These are compared with global stratification observations and 19 models from CMIP5. In terms of correlation and basin-wide rms error, the high-resolution models outperform all these CMIP5 models. The model with tides shows improved seasonal cycles compared to the high-resolution model without tides. The benefits of resolution are particularly apparent in eastern boundary upwelling zones.To explore the balance between the size of a globally refined model and that of

Large-Scale and Global Hydrology. Chapter 92

Science.gov (United States)

Rodell, Matthew; Beaudoing, Hiroko Kato; Koster, Randal; Peters-Lidard, Christa D.; Famiglietti, James S.; Lakshmi, Venkat

2016-01-01

Powered by the sun, water moves continuously between and through Earths oceanic, atmospheric, and terrestrial reservoirs. It enables life, shapes Earths surface, and responds to and influences climate change. Scientists measure various features of the water cycle using a combination of ground, airborne, and space-based observations, and seek to characterize it at multiple scales with the aid of numerical models. Over time our understanding of the water cycle and ability to quantify it have improved, owing to advances in observational capabilities, the extension of the data record, and increases in computing power and storage. Here we present some of the most recent estimates of global and continental ocean basin scale water cycle stocks and fluxes and provide examples of modern numerical modeling systems and reanalyses.Further, we discuss prospects for predicting water cycle variability at seasonal and longer scales, which is complicated by a changing climate and direct human impacts related to water management and agriculture. Changes to the water cycle will be among the most obvious and important facets of climate change, thus it is crucial that we continue to invest in our ability to monitor it.

Seismic waves and earthquakes in a global monolithic model

Science.gov (United States)

Roubíček, Tomáš

2018-03-01

The philosophy that a single "monolithic" model can "asymptotically" replace and couple in a simple elegant way several specialized models relevant on various Earth layers is presented and, in special situations, also rigorously justified. In particular, global seismicity and tectonics is coupled to capture, e.g., (here by a simplified model) ruptures of lithospheric faults generating seismic waves which then propagate through the solid-like mantle and inner core both as shear (S) or pressure (P) waves, while S-waves are suppressed in the fluidic outer core and also in the oceans. The "monolithic-type" models have the capacity to describe all the mentioned features globally in a unified way together with corresponding interfacial conditions implicitly involved, only when scaling its parameters appropriately in different Earth's layers. Coupling of seismic waves with seismic sources due to tectonic events is thus an automatic side effect. The global ansatz is here based, rather for an illustration, only on a relatively simple Jeffreys' viscoelastic damageable material at small strains whose various scaling (limits) can lead to Boger's viscoelastic fluid or even to purely elastic (inviscid) fluid. Self-induced gravity field, Coriolis, centrifugal, and tidal forces are counted in our global model, as well. The rigorous mathematical analysis as far as the existence of solutions, convergence of the mentioned scalings, and energy conservation is briefly presented.

A global high-resolution model experiment on the predictability of the atmosphere

Science.gov (United States)

Judt, F.

2016-12-01

Forecasting high-impact weather phenomena is one of the most important aspects of numerical weather prediction (NWP). Over the last couple of years, a tremendous increase in computing power has facilitated the advent of global convection-resolving NWP models, which allow for the seamless prediction of weather from local to planetary scales. Unfortunately, the predictability of specific meteorological phenomena in these models is not very well known. This raises questions about which forecast problems are potentially tractable, and what is the value of global convection-resolving model predictions for the end user. To address this issue, we use the Yellowstone supercomputer to conduct a global high-resolution predictability experiment with the recently developed Model for Prediction Across Scales (MPAS). The computing power of Yellowstone enables the model to run at a globally uniform resolution of 4 km with 55 vertical levels (>2 billion grid cells). These simulations, which require 3 million core-hours for the entire experiment, allow for the explicit treatment of organized deep moist convection (i.e., thunderstorm systems). Resolving organized deep moist convection alleviates grave limitations of previous predictability studies, which either used high-resolution limited-area models or global simulations with coarser grids and cumulus parameterization. By computing the error growth characteristics in a set of "identical twin" model runs, the experiment will clarify the intrinsic predictability limits of atmospheric phenomena on a wide range of scales, from severe thunderstorms to global-scale wind patterns that affect the distribution of tropical rainfall. Although a major task by itself, this study is intended to be exploratory work for a future predictability experiment going beyond of what has so far been feasible. We hope to use CISL's new Cheyenne supercomputer to conduct a similar predictability experiments on a global mesh with 1-2 km resolution. This

Matérn-based nonstationary cross-covariance models for global processes

KAUST Repository

Jun, Mikyoung

2014-07-01

Many spatial processes in environmental applications, such as climate variables and climate model errors on a global scale, exhibit complex nonstationary dependence structure, in not only their marginal covariance but also their cross-covariance. Flexible cross-covariance models for processes on a global scale are critical for an accurate description of each spatial process as well as the cross-dependences between them and also for improved predictions. We propose various ways to produce cross-covariance models, based on the Matérn covariance model class, that are suitable for describing prominent nonstationary characteristics of the global processes. In particular, we seek nonstationary versions of Matérn covariance models whose smoothness parameters vary over space, coupled with a differential operators approach for modeling large-scale nonstationarity. We compare their performance to the performance of some existing models in terms of the aic and spatial predictions in two applications: joint modeling of surface temperature and precipitation, and joint modeling of errors in climate model ensembles. © 2014 Elsevier Inc.

Spatially explicit modeling of particulate nutrient flux in Large global rivers

Science.gov (United States)

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.

Using friends as sensors to detect global-scale contagious outbreaks.

Directory of Open Access Journals (Sweden)

Manuel Garcia-Herranz

Full Text Available Recent research has focused on the monitoring of global-scale online data for improved detection of epidemics, mood patterns, movements in the stock market political revolutions, box-office revenues, consumer behaviour and many other important phenomena. However, privacy considerations and the sheer scale of data available online are quickly making global monitoring infeasible, and existing methods do not take full advantage of local network structure to identify key nodes for monitoring. Here, we develop a model of the contagious spread of information in a global-scale, publicly-articulated social network and show that a simple method can yield not just early detection, but advance warning of contagious outbreaks. In this method, we randomly choose a small fraction of nodes in the network and then we randomly choose a friend of each node to include in a group for local monitoring. Using six months of data from most of the full Twittersphere, we show that this friend group is more central in the network and it helps us to detect viral outbreaks of the use of novel hashtags about 7 days earlier than we could with an equal-sized randomly chosen group. Moreover, the method actually works better than expected due to network structure alone because highly central actors are both more active and exhibit increased diversity in the information they transmit to others. These results suggest that local monitoring is not just more efficient, but also more effective, and it may be applied to monitor contagious processes in global-scale networks.

Challenges in Modeling of the Global Atmosphere

Science.gov (United States)

Janjic, Zavisa; Djurdjevic, Vladimir; Vasic, Ratko; Black, Tom

2015-04-01

") with significant amplitudes can develop. Due to their large scales, that are comparable to the scales of the dominant Rossby waves, such fictitious solutions are hard to identify and remove. Another new challenge on the global scale is that the limit of validity of the hydrostatic approximation is rapidly being approached. Having in mind the sensitivity of extended deterministic forecasts to small disturbances, we may need global non-hydrostatic models sooner than we think. The unified Non-hydrostatic Multi-scale Model (NMMB) that is being developed at the National Centers for Environmental Prediction (NCEP) as a part of the new NOAA Environmental Modeling System (NEMS) will be discussed as an example. The non-hydrostatic dynamics were designed in such a way as to avoid over-specification. The global version is run on the latitude-longitude grid, and the polar filter selectively slows down the waves that would otherwise be unstable. The model formulation has been successfully tested on various scales. A global forecasting system based on the NMMB has been run in order to test and tune the model. The skill of the medium range forecasts produced by the NMMB is comparable to that of other major medium range models. The computational efficiency of the global NMMB on parallel computers is good.

Teach for All: Storytelling "Shared Solutions" and Scaling Global Reform

Science.gov (United States)

Ahmann, Chloe

2015-01-01

"Teach For All" is a global network of state-based organizations that translate "Teach For America's" market model of school reform into moral projects of nation-building abroad. Referring to this challenge as one of "scaling" the organization, its leaders elaborate a theory of change that hinges on replicability: in…

Assessing global vegetation activity using spatio-temporal Bayesian modelling

Science.gov (United States)

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

2016-04-01

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

The AgMIP GRIDded Crop Modeling Initiative (AgGRID) and the Global Gridded Crop Model Intercomparison (GGCMI)

Science.gov (United States)

Elliott, Joshua; Muller, Christoff

2015-01-01

Climate change is a significant risk for agricultural production. Even under optimistic scenarios for climate mitigation action, present-day agricultural areas are likely to face significant increases in temperatures in the coming decades, in addition to changes in precipitation, cloud cover, and the frequency and duration of extreme heat, drought, and flood events (IPCC, 2013). These factors will affect the agricultural system at the global scale by impacting cultivation regimes, prices, trade, and food security (Nelson et al., 2014a). Global-scale evaluation of crop productivity is a major challenge for climate impact and adaptation assessment. Rigorous global assessments that are able to inform planning and policy will benefit from consistent use of models, input data, and assumptions across regions and time that use mutually agreed protocols designed by the modeling community. To ensure this consistency, large-scale assessments are typically performed on uniform spatial grids, with spatial resolution of typically 10 to 50 km, over specified time-periods. Many distinct crop models and model types have been applied on the global scale to assess productivity and climate impacts, often with very different results (Rosenzweig et al., 2014). These models are based to a large extent on field-scale crop process or ecosystems models and they typically require resolved data on weather, environmental, and farm management conditions that are lacking in many regions (Bondeau et al., 2007; Drewniak et al., 2013; Elliott et al., 2014b; Gueneau et al., 2012; Jones et al., 2003; Liu et al., 2007; M¨uller and Robertson, 2014; Van den Hoof et al., 2011;Waha et al., 2012; Xiong et al., 2014). Due to data limitations, the requirements of consistency, and the computational and practical limitations of running models on a large scale, a variety of simplifying assumptions must generally be made regarding prevailing management strategies on the grid scale in both the baseline and

Calibration of a surface mass balance model for global-scale applications

NARCIS (Netherlands)

Giesen, R. H.; Oerlemans, J.

2012-01-01

Global applications of surface mass balance models have large uncertainties, as a result of poor climate input data and limited availability of mass balance measurements. This study addresses several possible consequences of these limitations for the modelled mass balance. This is done by applying a

GEM - The Global Earthquake Model

Science.gov (United States)

Smolka, A.

2009-04-01

Over 500,000 people died in the last decade due to earthquakes and tsunamis, mostly in the developing world, where the risk is increasing due to rapid population growth. In many seismic regions, no hazard and risk models exist, and even where models do exist, they are intelligible only by experts, or available only for commercial purposes. The Global Earthquake Model (GEM) answers the need for an openly accessible risk management tool. GEM is an internationally sanctioned public private partnership initiated by the Organisation for Economic Cooperation and Development (OECD) which will establish an authoritative standard for calculating and communicating earthquake hazard and risk, and will be designed to serve as the critical instrument to support decisions and actions that reduce earthquake losses worldwide. GEM will integrate developments on the forefront of scientific and engineering knowledge of earthquakes, at global, regional and local scale. The work is organized in three modules: hazard, risk, and socio-economic impact. The hazard module calculates probabilities of earthquake occurrence and resulting shaking at any given location. The risk module calculates fatalities, injuries, and damage based on expected shaking, building vulnerability, and the distribution of population and of exposed values and facilities. The socio-economic impact module delivers tools for making educated decisions to mitigate and manage risk. GEM will be a versatile online tool, with open source code and a map-based graphical interface. The underlying data will be open wherever possible, and its modular input and output will be adapted to multiple user groups: scientists and engineers, risk managers and decision makers in the public and private sectors, and the public-at- large. GEM will be the first global model for seismic risk assessment at a national and regional scale, and aims to achieve broad scientific participation and independence. Its development will occur in a

Cross-scale modelling of the climate-change mitigation potential of biochar systems: Global implications of nano-scale processes

Science.gov (United States)

Woolf, Dominic; Lehmann, Johannes

2014-05-01

With CO2 emissions still tracking the upper bounds of projected emissions scenarios, it is becoming increasingly urgent to reduce net greenhouse gas (GHG) emissions, and increasingly likely that restricting future atmospheric GHG concentrations to within safe limits will require an eventual transition towards net negative GHG emissions. Few measures capable of providing negative emissions at a globally-significant scale are currently known. Two that are most often considered include carbon sequestration in biomass and soil, and biomass energy with carbon capture and storage (BECCS). In common with these two approaches, biochar also relies on the use of photosynthetically-bound carbon in biomass. But, because biomass and land are limited, it is critical that these resources are efficiently allocated between biomass/soil sequestration, bioenergy, BECCS, biochar, and other competing uses such as food, fiber and biodiversity. In many situations, biochar can offer advantages that may make it the preferred use of a limited biomass supply. These advantages include that: 1) Biochar can provide valuable benefits to agriculture by improving soil fertility and crop production, and reducing fertlizer and irrigation requirements. 2) Biochar is significantly more stable than biomass or other forms of soil carbon, thus lowering the risk of future losses compared to sequestration in biomass or soil organic carbon. 3) Gases and volatiles produced by pyrolysis can be combusted for energy (which may offset fossil fuel emissions). 4) Biochar can further lower GHG emissions by reducing nitrous oxide emissions from soil and by enhancing net primary production. Determining the optimal use of biomass requires that we are able to model not only the climate-change mitigation impact of each option, but also their economic and wider environmental impacts. Thus, what is required is a systems modelling approach that integrates components representing soil biogeochemistry, hydrology, crop

The benefits of global scaling in multi-criteria decision analysis

Directory of Open Access Journals (Sweden)

Jamie P. Monat

2009-10-01

Full Text Available When there are multiple competing objectives in a decision-making process, Multi-Attribute Choice scoring models are excellent tools, permitting the incorporation of both subjective and objective attributes. However, their accuracy depends upon the subjective techniques used to construct the attribute scales and their concomitant weights. Conventional techniques using local scales tend to overemphasize small differences in attribute measures, which may yield erroneous conclusions. The Range Sensitivity Principle (RSP is often invoked to adjust attribute weights when local scales are used. In practice, however, decision makers often do not follow the prescriptions of the Range Sensitivity Principle and under-adjust the weights, resulting in potentially poor decisions. Examples are discussed as is a proposed solution: the use of global scales instead of local scales.

A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

Science.gov (United States)

Gosling, S. N.; Taylor, R. G.; Arnell, N. W.; Todd, M. C.

2011-01-01

We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and developmental conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangxi (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs include SLURP v. 12.2 (Liard), SLURP v. 12.7 (Mekong), Pitman (Okavango), MGB-IPH (Rio Grande), AV-SWAT-X 2005 (Xiangxi) and Cat-PDM (Harper's Brook). The CHMs typically simulate water resource impacts based on a more explicit representation of catchment water resources than that available from the GHM and the CHMs include river routing, whereas the GHM does not. Simulations of mean annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline (1961-1990) and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in global-mean air temperature of 1.0, 2.0, 3.0, 4.0, 5.0 and 6.0 °C relative to baseline from the UKMO HadCM3 Global Climate Model (GCM) to explore response to different amounts of climate forcing, and (2) a prescribed increase in global-mean air temperature of 2.0 °C relative to baseline for seven GCMs to explore response to climate model structural uncertainty. We find that the differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM (e.g. an absolute GHM-CHM difference in mean annual runoff percentage change for UKMO HadCM3 2 °C warming of up to 25%), and they are generally larger for indicators of high and low monthly runoff. However

A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

Directory of Open Access Journals (Sweden)

S. N. Gosling

2011-01-01

Full Text Available We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM and catchment-scale hydrological models (CHM. Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and developmental conditions. These include the Liard (Canada, Mekong (SE Asia, Okavango (SW Africa, Rio Grande (Brazil, Xiangxi (China and Harper's Brook (UK. A single GHM (Mac-PDM.09 is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs include SLURP v. 12.2 (Liard, SLURP v. 12.7 (Mekong, Pitman (Okavango, MGB-IPH (Rio Grande, AV-SWAT-X 2005 (Xiangxi and Cat-PDM (Harper's Brook. The CHMs typically simulate water resource impacts based on a more explicit representation of catchment water resources than that available from the GHM and the CHMs include river routing, whereas the GHM does not. Simulations of mean annual runoff, mean monthly runoff and high (Q5 and low (Q95 monthly runoff under baseline (1961–1990 and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1 prescribed increases in global-mean air temperature of 1.0, 2.0, 3.0, 4.0, 5.0 and 6.0 °C relative to baseline from the UKMO HadCM3 Global Climate Model (GCM to explore response to different amounts of climate forcing, and (2 a prescribed increase in global-mean air temperature of 2.0 °C relative to baseline for seven GCMs to explore response to climate model structural uncertainty.

We find that the differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM (e.g. an absolute GHM-CHM difference in mean annual runoff percentage change for UKMO HadCM3 2 °C warming of up to 25%, and they are generally larger for indicators of high and low monthly runoff

Drought Persistence Errors in Global Climate Models

Science.gov (United States)

Moon, H.; Gudmundsson, L.; Seneviratne, S. I.

2018-04-01

The persistence of drought events largely determines the severity of socioeconomic and ecological impacts, but the capability of current global climate models (GCMs) to simulate such events is subject to large uncertainties. In this study, the representation of drought persistence in GCMs is assessed by comparing state-of-the-art GCM model simulations to observation-based data sets. For doing so, we consider dry-to-dry transition probabilities at monthly and annual scales as estimates for drought persistence, where a dry status is defined as negative precipitation anomaly. Though there is a substantial spread in the drought persistence bias, most of the simulations show systematic underestimation of drought persistence at global scale. Subsequently, we analyzed to which degree (i) inaccurate observations, (ii) differences among models, (iii) internal climate variability, and (iv) uncertainty of the employed statistical methods contribute to the spread in drought persistence errors using an analysis of variance approach. The results show that at monthly scale, model uncertainty and observational uncertainty dominate, while the contribution from internal variability is small in most cases. At annual scale, the spread of the drought persistence error is dominated by the statistical estimation error of drought persistence, indicating that the partitioning of the error is impaired by the limited number of considered time steps. These findings reveal systematic errors in the representation of drought persistence in current GCMs and suggest directions for further model improvement.

Towards understanding resprouting at the global scale

Science.gov (United States)

Pausas, Juli G.; Pratt, R. Brandon; Keeley, Jon E.; Jacobsen, Anna L.; Ramirez, Aaron R.; Vilagrosa, Alberto; Paula, Susana; Kanekua-Pia, Iolana N.; Davis, Stephen D.

2016-01-01

Understanding and predicting plant response to disturbance is of paramount importance in our changing world. Resprouting ability is often considered a simple qualitative trait and used in many ecological studies. Our aim is to show some of the complexities of resprouting while highlighting cautions that need be taken in using resprouting ability to predict vegetation responses across disturbance types and biomes. There are marked differences in resprouting depending on the disturbance type, and fire is often the most severe disturbance because it includes both defoliation and lethal temperatures. In the Mediterranean biome, there are differences in functional strategies to cope with water deficit between resprouters (dehydration avoiders) and nonresprouters (dehydration tolerators); however, there is little research to unambiguously extrapolate these results to other biomes. Furthermore, predictions of vegetation responses to changes in disturbance regimes require consideration not only of resprouting, but also other relevant traits (e.g. seeding, bark thickness) and the different correlations among traits observed in different biomes; models lacking these details would behave poorly at the global scale. Overall, the lessons learned from a given disturbance regime and biome (e.g. crown-fire Mediterranean ecosystems) can guide research in other ecosystems but should not be extrapolated at the global scale.

Globalization: Ecological consequences of global-scale connectivity in people, resources and information

Science.gov (United States)

Globalization is a phenomenon affecting all facets of the Earth System. Within the context of ecological systems, it is becoming increasingly apparent that global connectivity among terrestrial systems, the atmosphere, and oceans is driving many ecological dynamics at finer scales and pushing thresh...

Global Scale Periodic Responses in Saturn’s Magnetosphere

Science.gov (United States)

Jia, Xianzhe; Kivelson, Margaret G.

2017-10-01

Despite having an axisymmetric internal magnetic field, Saturn’s magnetosphere exhibits periodic modulations in a variety of properties at periods close to the planetary rotation period. While the source of the periodicity remains unidentified, it is evident from Cassini observations that much of Saturn’s magnetospheric structure and dynamics is dominated by global-scale responses to the driving source of the periodicity. We have developed a global MHD model in which a rotating field-aligned current system is introduced by imposing vortical flows in the high-latitude ionosphere in order to simulate the magnetospheric periodicities. The model has been utilized to quantitatively characterize various periodic responses in the magnetosphere, such as the displacement of the magnetopause and bow shock and flapping of the tail plasma sheet, all of which show quantitative agreement with Cassini observations. One of our model predictions is periodic release of plasmoids in the tail that occurs preferentially in the midnight-to-dawn local time sector during each rotation cycle. Here we present detailed analysis of the periodic responses seen in our simulations focusing on the properties of plasmoids predicted by the model, including their spatial distribution, occurrence frequency, and mass loss rate. We will compare these modeled parameters with published Cassini observations, and discuss their implications for interpreting in-situ measurements.

ENSO impacts on flood risk at the global scale

Science.gov (United States)

Ward, Philip; Dettinger, Michael; Jongman, Brenden; Kummu, Matti; Winsemius, Hessel

2014-05-01

We present the impacts of El Niño Southern Oscillation (ENSO) on society and the economy, via relationships between ENSO and the hydrological cycle. We also discuss ways in which this knowledge can be used in disaster risk management and risk reduction. This contribution provides the most recent results of an ongoing 4-year collaborative research initiative to assess and map the impacts of large scale interannual climate variability on flood hazard and risk at the global scale. We have examined anomalies in flood risk between ENSO phases, whereby flood risk is expressed in terms of indicators such as: annual expected damage; annual expected affected population; annual expected affected Gross Domestic Product (GDP). We show that large anomalies in flood risk occur during El Niño or La Niña years in basins covering large parts of the Earth's surface. These anomalies reach statistical significance river basins covering almost two-thirds of the Earth's surface. Particularly strong anomalies exist in southern Africa, parts of western Africa, Australia, parts of Central Eurasia (especially for El Niño), the western USA (especially La Niña anomalies), and parts of South America. We relate these anomalies to possible causal relationships between ENSO and flood hazard, using both modelled and observed data on flood occurrence and extremity. The implications for flood risk management are many-fold. In those regions where disaster risk is strongly influenced by ENSO, the potential predictably of ENSO could be used to develop probabilistic flood risk projections with lead times up to several seasons. Such data could be used by the insurance industry in managing risk portfolios and by multinational companies for assessing the robustness of their supply chains to potential flood-related interruptions. Seasonal forecasts of ENSO influence of peak flows could also allow for improved flood early warning and regulation by dam operators, which could also reduce overall risks

Global spatiotemporal distribution of soil respiration modeled using a global database

Science.gov (United States)

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

2015-07-01

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

Scale-dependency of the global mean surface temperature trend and its implication for the recent hiatus of global warming.

Science.gov (United States)

Lin, Yong; Franzke, Christian L E

2015-08-11

Studies of the global mean surface temperature trend are typically conducted at a single (usually annual or decadal) time scale. The used scale does not necessarily correspond to the intrinsic scales of the natural temperature variability. This scale mismatch complicates the separation of externally forced temperature trends from natural temperature fluctuations. The hiatus of global warming since 1999 has been claimed to show that human activities play only a minor role in global warming. Most likely this claim is wrong due to the inadequate consideration of the scale-dependency in the global surface temperature (GST) evolution. Here we show that the variability and trend of the global mean surface temperature anomalies (GSTA) from January 1850 to December 2013, which incorporate both land and sea surface data, is scale-dependent and that the recent hiatus of global warming is mainly related to natural long-term oscillations. These results provide a possible explanation of the recent hiatus of global warming and suggest that the hiatus is only temporary.

Statistical models of global Langmuir mixing

Science.gov (United States)

Li, Qing; Fox-Kemper, Baylor; Breivik, Øyvind; Webb, Adrean

2017-05-01

The effects of Langmuir mixing on the surface ocean mixing may be parameterized by applying an enhancement factor which depends on wave, wind, and ocean state to the turbulent velocity scale in the K-Profile Parameterization. Diagnosing the appropriate enhancement factor online in global climate simulations is readily achieved by coupling with a prognostic wave model, but with significant computational and code development expenses. In this paper, two alternatives that do not require a prognostic wave model, (i) a monthly mean enhancement factor climatology, and (ii) an approximation to the enhancement factor based on the empirical wave spectra, are explored and tested in a global climate model. Both appear to reproduce the Langmuir mixing effects as estimated using a prognostic wave model, with nearly identical and substantial improvements in the simulated mixed layer depth and intermediate water ventilation over control simulations, but significantly less computational cost. Simpler approaches, such as ignoring Langmuir mixing altogether or setting a globally constant Langmuir number, are found to be deficient. Thus, the consequences of Stokes depth and misaligned wind and waves are important.

Black Carbon Absorption at the Global Scale Is Affected by Particle-Scale Diversity in Composition

Science.gov (United States)

Fierce, Laura; Bond, Tami C.; Bauer, Susanne E.; Mena, Francisco; Riemer, Nicole

2016-01-01

Atmospheric black carbon (BC) exerts a strong, but uncertain, warming effect on the climate. BC that is coated with non-absorbing material absorbs more strongly than the same amount of BC in an uncoated particle, but the magnitude of this absorption enhancement (E(sub abs)) is not well constrained. Modelling studies and laboratory measurements have found stronger absorption enhancement than has been observed in the atmosphere. Here, using a particle-resolved aerosol model to simulate diverse BC populations, we show that absorption is overestimated by as much as a factor of two if diversity is neglected and population-averaged composition is assumed across all BC-containing particles. If, instead, composition diversity is resolved, we find E(sub abs) = 1 - 1.5 at low relative humidity, consistent with ambient observations. This study offers not only an explanation for the discrepancy between modelled and observed absorption enhancement, but also demonstrates how particle-scale simulations can be used to develop relationships for global-scale models.

Description and Evaluation of IAP-AACM: A Global-regional Aerosol Chemistry Model for the Earth System Model CAS-ESM

Science.gov (United States)

Wei, Y.; Chen, X.

2017-12-01

We present a first description and evaluation of the IAP Atmospheric Aerosol Chemistry Model (IAP-AACM) which has been integrated into the earth system model CAS-ESM. In this way it is possible to research into interaction of clouds and aerosol by its two-way coupling with the IAP Atmospheric General Circulation Model (IAP-AGCM). The model has a nested global-regional grid based on the Global Environmental Atmospheric Transport Model (GEATM) and the Nested Air Quality Prediction Modeling System (NAQPMS). The AACM provides two optional gas chemistry schemes, the CBM-Z gas chemistry as well as a sulfur oxidize box designed specifically for the CAS-ESM. Now the model driven by AGCM has been applied to a 1-year simulation of tropospheric chemistry both on global and regional scales for 2014, and been evaluated against various observation datasets, including aerosol precursor gas concentration, aerosol mass and number concentrations. Furthermore, global budgets in AACM are compared with other global aerosol models. Generally, the AACM simulations are within the range of other global aerosol model predictions, and the model has a reasonable agreement with observations of gases and particles concentration both on global and regional scales.

Global MHD Modelling of the ISM - From large towards small scale turbulence

Science.gov (United States)

de Avillez, M.; Breitschwerdt, D.

2005-06-01

Dealing numerically with the turbulent nature and non-linearity of the physical processes involved in the ISM requires the use of sophisticated numerical schemes coupled to HD and MHD mathematical models. SNe are the main drivers of the interstellar turbulence by transferring kinetic energy into the system. This energy is dissipated by shocks (which is more efficient) and by molecular viscosity. We carried out adaptive mesh refinement simulations (with a finest resolution of 0.625 pc) of the turbulent ISM embedded in a magnetic field with mean field components of 2 and 3 μG. The time scale of our run was 400 Myr, sufficiently long to avoid memory effects of the initial setup, and to allow for a global dynamical equilibrium to be reached in case of a constant energy input rate. It is found that the longitudinal and transverse turbulent length scales have a time averaged (over a period of 50 Myr) ratio of 0.52-0.6, almost similar to the one expected for isotropic homogeneous turbulence. The mean characteristic size of the larger eddies is found to be ˜ 75 pc in both runs. In order to check the simulations against observations, we monitored the OVI and HI column densities within a superbubble created by the explosions of 19 SNe having masses and velocities of the stars that exploded in vicinity of the Sun generating the Local Bubble. The model reproduces the FUSE absorption measurements towards 25 white dwarfs of the OVI column density as function of distance and of N(HI). In particular for lines of sight with lengths smaller than 120 pc it is found that there is no correlation between N(OVI) and N(HI).

On global and regional spectral evaluation of global geopotential models

International Nuclear Information System (INIS)

Ustun, A; Abbak, R A

2010-01-01

Spectral evaluation of global geopotential models (GGMs) is necessary to recognize the behaviour of gravity signal and its error recorded in spherical harmonic coefficients and associated standard deviations. Results put forward in this wise explain the whole contribution of gravity data in different kinds that represent various sections of the gravity spectrum. This method is more informative than accuracy assessment methods, which use external data such as GPS-levelling. Comparative spectral evaluation for more than one model can be performed both in global and local sense using many spectral tools. The number of GGMs has grown with the increasing number of data collected by the dedicated satellite gravity missions, CHAMP, GRACE and GOCE. This fact makes it necessary to measure the differences between models and to monitor the improvements in the gravity field recovery. In this paper, some of the satellite-only and combined models are examined in different scales, globally and regionally, in order to observe the advances in the modelling of GGMs and their strengths at various expansion degrees for geodetic and geophysical applications. The validation of the published errors of model coefficients is a part of this evaluation. All spectral tools explicitly reveal the superiority of the GRACE-based models when compared against the models that comprise the conventional satellite tracking data. The disagreement between models is large in local/regional areas if data sets are different, as seen from the example of the Turkish territory

From Global to Cloud Resolving Scale: Experiments with a Scale- and Aerosol-Aware Physics Package and Impact on Tracer Transport

Science.gov (United States)

Grell, G. A.; Freitas, S. R.; Olson, J.; Bela, M.

2017-12-01

We will start by providing a summary of the latest cumulus parameterization modeling efforts at NOAA's Earth System Research Laboratory (ESRL) will be presented on both regional and global scales. The physics package includes a scale-aware parameterization of subgrid cloudiness feedback to radiation (coupled PBL, microphysics, radiation, shallow and congestus type convection), the stochastic Grell-Freitas (GF) scale- and aerosol-aware convective parameterization, and an aerosol aware microphysics package. GF is based on a stochastic approach originally implemented by Grell and Devenyi (2002) and described in more detail in Grell and Freitas (2014, ACP). It was expanded to include PDF's for vertical mass flux, as well as modifications to improve the diurnal cycle. This physics package will be used on different scales, spanning global to cloud resolving, to look at the impact on scalar transport and numerical weather prediction.

Deriving Scaling Factors Using a Global Hydrological Model to Restore GRACE Total Water Storage Changes for China's Yangtze River Basin

Science.gov (United States)

Long, Di; Yang, Yuting; Yoshihide, Wada; Hong, Yang; Liang, Wei; Chen, Yaning; Yong, Bin; Hou, Aizhong; Wei, Jiangfeng; Chen, Lu

2015-01-01

This study used a global hydrological model (GHM), PCR-GLOBWB, which simulates surface water storage changes, natural and human induced groundwater storage changes, and the interactions between surface water and subsurface water, to generate scaling factors by mimicking low-pass filtering of GRACE signals. Signal losses in GRACE data were subsequently restored by the scaling factors from PCR-GLOBWB. Results indicate greater spatial heterogeneity in scaling factor from PCR-GLOBWB and CLM4.0 than that from GLDAS-1 Noah due to comprehensive simulation of surface and subsurface water storage changes for PCR-GLOBWB and CLM4.0. Filtered GRACE total water storage (TWS) changes applied with PCR-GLOBWB scaling factors show closer agreement with water budget estimates of TWS changes than those with scaling factors from other land surface models (LSMs) in China's Yangtze River basin. Results of this study develop a further understanding of the behavior of scaling factors from different LSMs or GHMs over hydrologically complex basins, and could be valuable in providing more accurate TWS changes for hydrological applications (e.g., monitoring drought and groundwater storage depletion) over regions where human-induced interactions between surface water and subsurface water are intensive.

GloFAS-Seasonal: Operational Seasonal Ensemble River Flow Forecasts at the Global Scale

Science.gov (United States)

Emerton, Rebecca; Zsoter, Ervin; Smith, Paul; Salamon, Peter

2017-04-01

Seasonal hydrological forecasting has potential benefits for many sectors, including agriculture, water resources management and humanitarian aid. At present, no global scale seasonal hydrological forecasting system exists operationally; although smaller scale systems have begun to emerge around the globe over the past decade, a system providing consistent global scale seasonal forecasts would be of great benefit in regions where no other forecasting system exists, and to organisations operating at the global scale, such as disaster relief. We present here a new operational global ensemble seasonal hydrological forecast, currently under development at ECMWF as part of the Global Flood Awareness System (GloFAS). The proposed system, which builds upon the current version of GloFAS, takes the long-range forecasts from the ECMWF System4 ensemble seasonal forecast system (which incorporates the HTESSEL land surface scheme) and uses this runoff as input to the Lisflood routing model, producing a seasonal river flow forecast out to 4 months lead time, for the global river network. The seasonal forecasts will be evaluated using the global river discharge reanalysis, and observations where available, to determine the potential value of the forecasts across the globe. The seasonal forecasts will be presented as a new layer in the GloFAS interface, which will provide a global map of river catchments, indicating whether the catchment-averaged discharge forecast is showing abnormally high or low flows during the 4-month lead time. Each catchment will display the corresponding forecast as an ensemble hydrograph of the weekly-averaged discharge forecast out to 4 months, with percentile thresholds shown for comparison with the discharge climatology. The forecast visualisation is based on a combination of the current medium-range GloFAS forecasts and the operational EFAS (European Flood Awareness System) seasonal outlook, and aims to effectively communicate the nature of a seasonal

The status and challenge of global fire modelling

Science.gov (United States)

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

2016-06-01

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

Toward GEOS-6, A Global Cloud System Resolving Atmospheric Model

Science.gov (United States)

Putman, William M.

2010-01-01

NASA is committed to observing and understanding the weather and climate of our home planet through the use of multi-scale modeling systems and space-based observations. Global climate models have evolved to take advantage of the influx of multi- and many-core computing technologies and the availability of large clusters of multi-core microprocessors. GEOS-6 is a next-generation cloud system resolving atmospheric model that will place NASA at the forefront of scientific exploration of our atmosphere and climate. Model simulations with GEOS-6 will produce a realistic representation of our atmosphere on the scale of typical satellite observations, bringing a visual comprehension of model results to a new level among the climate enthusiasts. In preparation for GEOS-6, the agency's flagship Earth System Modeling Framework [JDl] has been enhanced to support cutting-edge high-resolution global climate and weather simulations. Improvements include a cubed-sphere grid that exposes parallelism; a non-hydrostatic finite volume dynamical core, and algorithm designed for co-processor technologies, among others. GEOS-6 represents a fundamental advancement in the capability of global Earth system models. The ability to directly compare global simulations at the resolution of spaceborne satellite images will lead to algorithm improvements and better utilization of space-based observations within the GOES data assimilation system

Global warming precipitation accumulation increases above the current-climate cutoff scale.

Science.gov (United States)

Neelin, J David; Sahany, Sandeep; Stechmann, Samuel N; Bernstein, Diana N

2017-02-07

Precipitation accumulations, integrated over rainfall events, can be affected by both intensity and duration of the storm event. Thus, although precipitation intensity is widely projected to increase under global warming, a clear framework for predicting accumulation changes has been lacking, despite the importance of accumulations for societal impacts. Theory for changes in the probability density function (pdf) of precipitation accumulations is presented with an evaluation of these changes in global climate model simulations. We show that a simple set of conditions implies roughly exponential increases in the frequency of the very largest accumulations above a physical cutoff scale, increasing with event size. The pdf exhibits an approximately power-law range where probability density drops slowly with each order of magnitude size increase, up to a cutoff at large accumulations that limits the largest events experienced in current climate. The theory predicts that the cutoff scale, controlled by the interplay of moisture convergence variance and precipitation loss, tends to increase under global warming. Thus, precisely the large accumulations above the cutoff that are currently rare will exhibit increases in the warmer climate as this cutoff is extended. This indeed occurs in the full climate model, with a 3 °C end-of-century global-average warming yielding regional increases of hundreds of percent to >1,000% in the probability density of the largest accumulations that have historical precedents. The probabilities of unprecedented accumulations are also consistent with the extension of the cutoff.

Global warming precipitation accumulation increases above the current-climate cutoff scale

Science.gov (United States)

Sahany, Sandeep; Stechmann, Samuel N.; Bernstein, Diana N.

2017-01-01

Precipitation accumulations, integrated over rainfall events, can be affected by both intensity and duration of the storm event. Thus, although precipitation intensity is widely projected to increase under global warming, a clear framework for predicting accumulation changes has been lacking, despite the importance of accumulations for societal impacts. Theory for changes in the probability density function (pdf) of precipitation accumulations is presented with an evaluation of these changes in global climate model simulations. We show that a simple set of conditions implies roughly exponential increases in the frequency of the very largest accumulations above a physical cutoff scale, increasing with event size. The pdf exhibits an approximately power-law range where probability density drops slowly with each order of magnitude size increase, up to a cutoff at large accumulations that limits the largest events experienced in current climate. The theory predicts that the cutoff scale, controlled by the interplay of moisture convergence variance and precipitation loss, tends to increase under global warming. Thus, precisely the large accumulations above the cutoff that are currently rare will exhibit increases in the warmer climate as this cutoff is extended. This indeed occurs in the full climate model, with a 3 °C end-of-century global-average warming yielding regional increases of hundreds of percent to >1,000% in the probability density of the largest accumulations that have historical precedents. The probabilities of unprecedented accumulations are also consistent with the extension of the cutoff. PMID:28115693

Atmospheric Dust Modeling from Meso to Global Scales with the Online NMMB/BSC-Dust Model Part 2: Experimental Campaigns in Northern Africa

Science.gov (United States)

Haustein, K.; Perez, C.; Baldasano, J. M.; Jorba, O.; Basart, S.; Miller, R. L.; Janjic, Z.; Black, T.; Nickovic, S.; Todd, M. C.;

Scale-dependency of the global mean surface temperature trend and its implication for the recent hiatus of global warming

Science.gov (United States)

Lin, Yong; Franzke, Christian L. E.

2015-01-01

Studies of the global mean surface temperature trend are typically conducted at a single (usually annual or decadal) time scale. The used scale does not necessarily correspond to the intrinsic scales of the natural temperature variability. This scale mismatch complicates the separation of externally forced temperature trends from natural temperature fluctuations. The hiatus of global warming since 1999 has been claimed to show that human activities play only a minor role in global warming. Most likely this claim is wrong due to the inadequate consideration of the scale-dependency in the global surface temperature (GST) evolution. Here we show that the variability and trend of the global mean surface temperature anomalies (GSTA) from January 1850 to December 2013, which incorporate both land and sea surface data, is scale-dependent and that the recent hiatus of global warming is mainly related to natural long-term oscillations. These results provide a possible explanation of the recent hiatus of global warming and suggest that the hiatus is only temporary. PMID:26259555

Global-scale combustion sources of organic aerosols: sensitivity to formation and removal mechanisms

Science.gov (United States)

Tsimpidi, Alexandra P.; Karydis, Vlassis A.; Pandis, Spyros N.; Lelieveld, Jos

2017-06-01

Organic compounds from combustion sources such as biomass burning and fossil fuel use are major contributors to the global atmospheric load of aerosols. We analyzed the sensitivity of model-predicted global-scale organic aerosols (OA) to parameters that control primary emissions, photochemical aging, and the scavenging efficiency of organic vapors. We used a computationally efficient module for the description of OA composition and evolution in the atmosphere (ORACLE) of the global chemistry-climate model EMAC (ECHAM/MESSy Atmospheric Chemistry). A global dataset of aerosol mass spectrometer (AMS) measurements was used to evaluate simulated primary (POA) and secondary (SOA) OA concentrations. Model results are sensitive to the emission rates of intermediate-volatility organic compounds (IVOCs) and POA. Assuming enhanced reactivity of semi-volatile organic compounds (SVOCs) and IVOCs with OH substantially improved the model performance for SOA. The use of a hybrid approach for the parameterization of the aging of IVOCs had a small effect on predicted SOA levels. The model performance improved by assuming that freshly emitted organic compounds are relatively hydrophobic and become increasingly hygroscopic due to oxidation.

On global H-mode scaling laws for JET

International Nuclear Information System (INIS)

Kardaun, O.; Lackner, K.; Thomsen, K.; Christiansen, J.; Cordey, J.; Gottardi, N.; Keilhacker, M.; Smeulders, P.

1989-01-01

Investigation of the scaling of the energy confinement time τ E with various plasma parameters has since long been an interesting, albeit not uncontroversial topic in plasma physics. Various global scaling laws have been derived for ohmic as well as (NBI and/or RF heated) L-mode discharges. Due to the scarce availability of computerised, extensive and validated H-mode datasets, systematic statistical analysis of H-mode scaling behaviour has hitherto been limited. A common approach is to fit the available H-mode data by an L-mode scaling law (e.g., Kaye-Goldston, Rebut-Lallia) with one or two adjustable constant terms. In this contribution we will consider the alternative approach of fitting all free parameters of various simple scaling models to two recently compiled datasets consisting of about 140 ELM-free and 40 ELMy H-mode discharges, measured at JET in the period 1986-1988. From this period, approximately all known H-mode shots have been included that satisfy the following criteria: D-injected D + discharges with no RF heating, a sufficiently long (≥300 ms) and regular P NBI flat-top, and validated main diagnostics. (author) 13 refs., 1 tab

Large-Scale Variation in Forest Carbon Turnover Rate and its Relation to Climate - Remote Sensing vs. Global Vegetation Models

Science.gov (United States)

Carvalhais, N.; Thurner, M.; Beer, C.; Forkel, M.; Rademacher, T. T.; Santoro, M.; Tum, M.; Schmullius, C.

2015-12-01

While vegetation productivity is known to be strongly correlated to climate, there is a need for an improved understanding of the underlying processes of vegetation carbon turnover and their importance at a global scale. This shortcoming has been due to the lack of spatially extensive information on vegetation carbon stocks, which we recently have been able to overcome by a biomass dataset covering northern boreal and temperate forests originating from radar remote sensing. Based on state-of-the-art products on biomass and NPP, we are for the first time able to study the relation between carbon turnover rate and a set of climate indices in northern boreal and temperate forests. The implementation of climate-related mortality processes, for instance drought, fire, frost or insect effects, is often lacking or insufficient in current global vegetation models. In contrast to our observation-based findings, investigated models from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, and VISIT, are able to reproduce spatial climate - turnover rate relationships only to a limited extent. While most of the models compare relatively well to observation-based 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 global vegetation models and estimating their impact on the land carbon balance.

Optimal Stomatal Behaviour Around the World: Synthesis of a Global Stomatal Conductance Database and Scaling from Leaf to Ecosystem

Science.gov (United States)

Lin, Y. S.; Medlyn, B. E.; Duursma, R.; Prentice, I. C.; Wang, H.

2014-12-01

Stomatal conductance (gs) is a key land surface attribute as it links transpiration, the dominant component of global land evapotranspiration and a key element of the global water cycle, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of gs in predictions of global water and carbon cycles, a global scale database and an associated globally applicable model of gs that allow predictions of stomatal behaviour are lacking. We present a unique database of globally distributed gs obtained in the field for a wide range of plant functional types (PFTs) and biomes. We employed a model of optimal stomatal conductance to assess differences in stomatal behaviour, and estimated the model slope coefficient, g1, which is directly related to the marginal carbon cost of water, for each dataset. We found that g1 varies considerably among PFTs, with evergreen savanna trees having the largest g1 (least conservative water use), followed by C3 grasses and crops, angiosperm trees, gymnosperm trees, and C4 grasses. Amongst angiosperm trees, species with higher wood density had a higher marginal carbon cost of water, as predicted by the theory underpinning the optimal stomatal model. There was an interactive effect between temperature and moisture availability on g1: for wet environments, g1 was largest in high temperature environments, indicated by high mean annual temperature during the period when temperature above 0oC (Tm), but it did not vary with Tm across dry environments. We examine whether these differences in leaf-scale behaviour are reflected in ecosystem-scale differences in water-use efficiency. These findings provide a robust theoretical framework for understanding and predicting the behaviour of stomatal conductance across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of productivity and ecohydrological processes in a future changing climate.

A dynamic globalization model for large eddy simulation of complex turbulent flow

Energy Technology Data Exchange (ETDEWEB)

Choi, Hae Cheon; Park, No Ma; Kim, Jin Seok [Seoul National Univ., Seoul (Korea, Republic of)

2005-07-01

A dynamic subgrid-scale model is proposed for large eddy simulation of turbulent flows in complex geometry. The eddy viscosity model by Vreman [Phys. Fluids, 16, 3670 (2004)] is considered as a base model. A priori tests with the original Vreman model show that it predicts the correct profile of subgrid-scale dissipation in turbulent channel flow but the optimal model coefficient is far from universal. Dynamic procedures of determining the model coefficient are proposed based on the 'global equilibrium' between the subgrid-scale dissipation and viscous dissipation. An important feature of the proposed procedures is that the model coefficient determined is globally constant in space but varies only in time. Large eddy simulations with the present dynamic model are conducted for forced isotropic turbulence, turbulent channel flow and flow over a sphere, showing excellent agreements with previous results.

Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balances

Science.gov (United States)

Tang, G.; Bartlein, P. J.

2012-08-01

Satellite-based data, such as vegetation type and fractional vegetation cover, are widely used in hydrologic models to prescribe the vegetation state in a study region. Dynamic global vegetation models (DGVM) simulate land surface hydrology. Incorporation of satellite-based data into a DGVM may enhance a model's ability to simulate land surface hydrology by reducing the task of model parameterization and providing distributed information on land characteristics. The objectives of this study are to (i) modify a DGVM for simulating land surface water balances; (ii) evaluate the modified model in simulating actual evapotranspiration (ET), soil moisture, and surface runoff at regional or watershed scales; and (iii) gain insight into the ability of both the original and modified model to simulate large spatial scale land surface hydrology. To achieve these objectives, we introduce the "LPJ-hydrology" (LH) model which incorporates satellite-based data into the Lund-Potsdam-Jena (LPJ) DGVM. To evaluate the model we ran LH using historical (1981-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells for the conterminous US and for the entire world using coarser climate and land cover data. We evaluated the simulated ET, soil moisture, and surface runoff using a set of observed or simulated data at different spatial scales. Our results demonstrate that spatial patterns of LH-simulated annual ET and surface runoff are in accordance with previously published data for the US; LH-modeled monthly stream flow for 12 major rivers in the US was consistent with observed values respectively during the years 1981-2006 (R2 > 0.46, p 0.52). The modeled mean annual discharges for 10 major rivers worldwide also agreed well (differences day method for snowmelt computation, the addition of the solar radiation effect on snowmelt enabled LH to better simulate monthly stream flow in winter and early spring for rivers located at mid-to-high latitudes. In addition, LH-modeled

Sub-seasonal predictability of water scarcity at global and local scale

Science.gov (United States)

Wanders, N.; Wada, Y.; Wood, E. F.

2016-12-01

Forecasting the water demand and availability for agriculture and energy production has been neglected in previous research, partly due to the fact that most large-scale hydrological models lack the skill to forecast human water demands at sub-seasonal time scale. We study the potential of a sub-seasonal water scarcity forecasting system for improved water management decision making and improved estimates of water demand and availability. We have generated 32 years of global sub-seasonal multi-model water availability, demand and scarcity forecasts. The quality of the forecasts is compared to a reference forecast derived from resampling historic weather observations. The newly developed system has been evaluated for both the global scale and in a real-time local application in the Sacramento valley for the Trinity, Shasta and Oroville reservoirs, where the water demand for agriculture and hydropower is high. On the global scale we find that the reference forecast shows high initial forecast skill (up to 8 months) for water scarcity in the eastern US, Central Asia and Sub-Saharan Africa. Adding dynamical sub-seasonal forecasts results in a clear improvement for most regions in the world, increasing the forecasts' lead time by 2 or more months on average. The strongest improvements are found in the US, Brazil, Central Asia and Australia. For the Sacramento valley we can accurately predict anomalies in the reservoir inflow, hydropower potential and the downstream irrigation water demand 6 months in advance. This allow us to forecast potential water scarcity in the Sacramento valley and adjust the reservoir management to prevent deficits in energy or irrigation water availability. The newly developed forecast system shows that it is possible to reduce the vulnerability to upcoming water scarcity events and allows optimization of the distribution of the available water between the agricultural and energy sector half a year in advance.

Global scale analysis and evaluation of an improved mechanistic representation of plant nitrogen and carbon dynamics in the Community Land Model (CLM)

Science.gov (United States)

Ghimire, B.; Riley, W. J.; Koven, C. D.; Randerson, J. T.; Mu, M.; Kattge, J.; Rogers, A.; Reich, P. B.

2014-12-01

In many ecosystems, nitrogen is the most limiting nutrient for plant growth and productivity. However mechanistic representation of nitrogen uptake linked to root traits, and functional nitrogen allocation among different leaf enzymes involved in respiration and photosynthesis is currently lacking in Earth System models. The linkage between nitrogen availability and plant productivity is simplistically represented by potential photosynthesis rates, and is subsequently downregulated depending on nitrogen supply and other nitrogen consumers in the model (e.g., nitrification). This type of potential photosynthesis rate calculation is problematic for several reasons. Firstly, plants do not photosynthesize at potential rates and then downregulate. Secondly, there is considerable subjectivity on the meaning of potential photosynthesis rates. Thirdly, there exists lack of understanding on modeling these potential photosynthesis rates in a changing climate. In addition to model structural issues in representing photosynthesis rates, the role of plant roots in nutrient acquisition have been largely ignored in Earth System models. For example, in CLM4.5, nitrogen uptake is linked to leaf level processes (e.g., primarily productivity) rather than root scale process involved in nitrogen uptake. We present a new plant model for CLM with an improved mechanistic presentation of plant nitrogen uptake based on root scale Michaelis Menten kinetics, and stronger linkages between leaf nitrogen and plant productivity by inferring relationships observed in global databases of plant traits (including the TRY database and several individual studies). We also incorporate improved representation of plant nitrogen leaf allocation, especially in tropical regions where significant over-prediction of plant growth and productivity in CLM4.5 simulations exist. We evaluate our improved global model simulations using the International Land Model Benchmarking (ILAMB) framework. We conclude that

Microphysics in Multi-scale Modeling System with Unified Physics

Science.gov (United States)

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.

Challenges and Opportunities in Modeling of the Global Atmosphere

Science.gov (United States)

Janjic, Zavisa; Djurdjevic, Vladimir; Vasic, Ratko

2016-04-01

Modeling paradigms on global scales may need to be reconsidered in order to better utilize the power of massively parallel processing. For high computational efficiency with distributed memory, each core should work on a small subdomain of the full integration domain, and exchange only few rows of halo data with the neighbouring cores. Note that the described scenario strongly favors horizontally local discretizations. This is relatively easy to achieve in regional models. However, the spherical geometry complicates the problem. The latitude-longitude grid with local in space and explicit in time differencing has been an early choice and remained in use ever since. The problem with this method is that the grid size in the longitudinal direction tends to zero as the poles are approached. So, in addition to having unnecessarily high resolution near the poles, polar filtering has to be applied in order to use a time step of a reasonable size. However, the polar filtering requires transpositions involving extra communications as well as more computations. The spectral transform method and the semi-implicit semi-Lagrangian schemes opened the way for application of spectral representation. With some variations, such techniques are currently dominating in global models. Unfortunately, the horizontal non-locality is inherent to the spectral representation and implicit time differencing, which inhibits scaling on a large number of cores. In this respect the lat-lon grid with polar filtering is a step in the right direction, particularly at high resolutions where the Legendre transforms become increasingly expensive. Other grids with reduced variability of grid distances, such as various versions of the cubed sphere and the hexagonal/pentagonal ("soccer ball") grids, were proposed almost fifty years ago. However, on these grids, large-scale (wavenumber 4 and 5) fictitious solutions ("grid imprinting") with significant amplitudes can develop. Due to their large scales, that

Impact of transport model errors on the global and regional methane emissions estimated by inverse modelling

Directory of Open Access Journals (Sweden)

R. Locatelli

2013-10-01

Full Text Available A modelling experiment has been conceived to assess the impact of transport model errors on methane emissions estimated in an atmospheric inversion system. Synthetic methane observations, obtained from 10 different model outputs from the international TransCom-CH4 model inter-comparison exercise, are combined with a prior scenario of methane emissions and sinks, and integrated into the three-component PYVAR-LMDZ-SACS (PYthon VARiational-Laboratoire de Météorologie Dynamique model with Zooming capability-Simplified Atmospheric Chemistry System inversion system to produce 10 different methane emission estimates at the global scale for the year 2005. The same methane sinks, emissions and initial conditions have been applied to produce the 10 synthetic observation datasets. The same inversion set-up (statistical errors, prior emissions, inverse procedure is then applied to derive flux estimates by inverse modelling. Consequently, only differences in the modelling of atmospheric transport may cause differences in the estimated fluxes. In our framework, we show that transport model errors lead to a discrepancy of 27 Tg yr−1 at the global scale, representing 5% of total methane emissions. At continental and annual scales, transport model errors are proportionally larger than at the global scale, with errors ranging from 36 Tg yr−1 in North America to 7 Tg yr−1 in Boreal Eurasia (from 23 to 48%, respectively. At the model grid-scale, the spread of inverse estimates can reach 150% of the prior flux. Therefore, transport model errors contribute significantly to overall uncertainties in emission estimates by inverse modelling, especially when small spatial scales are examined. Sensitivity tests have been carried out to estimate the impact of the measurement network and the advantage of higher horizontal resolution in transport models. The large differences found between methane flux estimates inferred in these different configurations highly

Terrestrial nitrogen-carbon cycle interactions at the global scale.

Science.gov (United States)

Zaehle, S

2013-07-05

Interactions between the terrestrial nitrogen (N) and carbon (C) cycles shape the response of ecosystems to global change. However, the global distribution of nitrogen availability and its importance in global biogeochemistry and biogeochemical interactions with the climate system remain uncertain. Based on projections of a terrestrial biosphere model scaling ecological understanding of nitrogen-carbon cycle interactions to global scales, anthropogenic nitrogen additions since 1860 are estimated to have enriched the terrestrial biosphere by 1.3 Pg N, supporting the sequestration of 11.2 Pg C. Over the same time period, CO2 fertilization has increased terrestrial carbon storage by 134.0 Pg C, increasing the terrestrial nitrogen stock by 1.2 Pg N. In 2001-2010, terrestrial ecosystems sequestered an estimated total of 27 Tg N yr(-1) (1.9 Pg C yr(-1)), of which 10 Tg N yr(-1) (0.2 Pg C yr(-1)) are due to anthropogenic nitrogen deposition. Nitrogen availability already limits terrestrial carbon sequestration in the boreal and temperate zone, and will constrain future carbon sequestration in response to CO2 fertilization (regionally by up to 70% compared with an estimate without considering nitrogen-carbon interactions). This reduced terrestrial carbon uptake will probably dominate the role of the terrestrial nitrogen cycle in the climate system, as it accelerates the accumulation of anthropogenic CO2 in the atmosphere. However, increases of N2O emissions owing to anthropogenic nitrogen and climate change (at a rate of approx. 0.5 Tg N yr(-1) per 1°C degree climate warming) will add an important long-term climate forcing.

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

Science.gov (United States)

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

2014-12-01

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

NASA/MSFC FY88 Global Scale Atmospheric Processes Research Program Review

Science.gov (United States)

Wilson, Greg S. (Editor); Leslie, Fred W. (Editor); Arnold, J. E. (Editor)

1989-01-01

Interest in environmental issues and the magnitude of the environmental changes continues. One way to gain more understanding of the atmosphere is to make measurements on a global scale from space. The Earth Observation System is a series of new sensors to measure globally atmospheric parameters. Analysis of satellite data by developing algorithms to interpret the radiance information improves the understanding and also defines requirements for these sensors. One measure of knowledge of the atmosphere lies in the ability to predict its behavior. Use of numerical and experimental models provides a better understanding of these processes. These efforts are described in the context of satellite data analysis and fundamental studies of atmospheric dynamics which examine selected processes important to the global circulation.

Atmospheric dust modeling from meso to global scales with the online NMMB/BSC-Dust model – Part 2: Experimental campaigns in Northern Africa

Directory of Open Access Journals (Sweden)

K. Haustein

2012-03-01

Full Text Available The new NMMB/BSC-Dust model is intended to provide short to medium-range weather and dust forecasts from regional to global scales. It is an online model in which the dust aerosol dynamics and physics are solved at each model time step. The companion paper (Pérez et al., 2011 develops the dust model parameterizations and provides daily to annual evaluations of the model for its global and regional configurations. Modeled aerosol optical depth (AOD was evaluated against AERONET Sun photometers over Northern Africa, Middle East and Europe with correlations around 0.6–0.7 on average without dust data assimilation. In this paper we analyze in detail the behavior of the model using data from the Saharan Mineral dUst experiment (SAMUM-1 in 2006 and the Bodélé Dust Experiment (BoDEx in 2005. AOD from satellites and Sun photometers, vertically resolved extinction coefficients from lidars and particle size distributions at the ground and in the troposphere are used, complemented by wind profile data and surface meteorological measurements. All simulations were performed at the regional scale for the Northern African domain at the expected operational horizontal resolution of 25 km. Model results for SAMUM-1 generally show good agreement with satellite data over the most active Saharan dust sources. The model reproduces the AOD from Sun photometers close to sources and after long-range transport, and the dust size spectra at different height levels. At this resolution, the model is not able to reproduce a large haboob that occurred during the campaign. Some deficiencies are found concerning the vertical dust distribution related to the representation of the mixing height in the atmospheric part of the model. For the BoDEx episode, we found the diurnal temperature cycle to be strongly dependant on the soil moisture, which is underestimated in the NCEP analysis used for model initialization. The low level jet (LLJ and the dust AOD over the Bodélé are

Global tropospheric ozone modeling: Quantifying errors due to grid resolution

OpenAIRE

Wild, Oliver; Prather, Michael J

2006-01-01

Ozone production in global chemical models is dependent on model resolution because ozone chemistry is inherently nonlinear, the timescales for chemical production are short, and precursors are artificially distributed over the spatial scale of the model grid. In this study we examine the sensitivity of ozone, its precursors, and its production to resolution by running a global chemical transport model at four different resolutions between T21 (5.6° × 5.6°) and T106 (1.1° × 1.1°) and by quant...

Modeling Fire Occurrence at the City Scale: A Comparison between Geographically Weighted Regression and Global Linear Regression.

Science.gov (United States)

Song, Chao; Kwan, Mei-Po; Zhu, Jiping

2017-04-08

An increasing number of fires are occurring with the rapid development of cities, resulting in increased risk for human beings and the environment. This study compares geographically weighted regression-based models, including geographically weighted regression (GWR) and geographically and temporally weighted regression (GTWR), which integrates spatial and temporal effects and global linear regression models (LM) for modeling fire risk at the city scale. The results show that the road density and the spatial distribution of enterprises have the strongest influences on fire risk, which implies that we should focus on areas where roads and enterprises are densely clustered. In addition, locations with a large number of enterprises have fewer fire ignition records, probably because of strict management and prevention measures. A changing number of significant variables across space indicate that heterogeneity mainly exists in the northern and eastern rural and suburban areas of Hefei city, where human-related facilities or road construction are only clustered in the city sub-centers. GTWR can capture small changes in the spatiotemporal heterogeneity of the variables while GWR and LM cannot. An approach that integrates space and time enables us to better understand the dynamic changes in fire risk. Thus governments can use the results to manage fire safety at the city scale.

Global and Regional Ecosystem Modeling: Databases of Model Drivers and Validation Measurements

Energy Technology Data Exchange (ETDEWEB)

Olson, R.J.

2002-03-19

Understanding global-scale ecosystem responses to changing environmental conditions is important both as a scientific question and as the basis for making policy decisions. The confidence in regional models depends on how well the field data used to develop the model represent the region of interest, how well the environmental model driving variables (e.g., vegetation type, climate, and soils associated with a site used to parameterize ecosystem models) represent the region of interest, and how well regional model predictions agree with observed data for the region. To assess the accuracy of global model forecasts of terrestrial carbon cycling, two Ecosystem Model-Data Intercomparison (EMDI) workshops were held (December 1999 and April 2001). The workshops included 17 biogeochemical, satellite-driven, detailed process, and dynamic vegetation global model types. The approach was to run regional or global versions of the models for sites with net primary productivity (NPP) measurements (i.e., not fine-tuned for specific site conditions) and analyze the model-data differences. Extensive worldwide NPP data were assembled with model driver data, including vegetation, climate, and soils data, to perform the intercomparison. This report describes the compilation of NPP estimates for 2,523 sites and 5,164 0.5{sup o}-grid cells under the Global Primary Production Data Initiative (GPPDI) and the results of the EMDI review and outlier analysis that produced a refined set of NPP estimates and model driver data. The EMDI process resulted in 81 Class A sites, 933 Class B sites, and 3,855 Class C cells derived from the original synthesis of NPP measurements and associated driver data. Class A sites represent well-documented study sites that have complete aboveground and below ground NPP measurements. Class B sites represent more numerous ''extensive'' sites with less documentation and site-specific information available. Class C cells represent estimates of

Development and Psychometric Evaluation of a Clinical Global Impression for Schizoaffective Disorder Scale

OpenAIRE

Allen, Michael H; Daniel, David G; Revicki, Dennis A; Canuso, Carla M; Turkoz, Ibrahim; Fu, Dong-Jing; Alphs, Larry; Ishak, K. Jack; Bartko, John J; Lindenmayer, Jean-Pierre

2012-01-01

Objective: The Clinical Global Impression for Schizoaffective Disorder scale is a new rating scale adapted from the Clinical Global Impression scale for use in patients with schizoaffective disorder. The psychometric characteristics of the Clinical Global Impression for Schizoaffective Disorder are described.

Sources of uncertainties in modelling black carbon at the global scale

NARCIS (Netherlands)

Vignati, E.; Karl, M.; Krol, M.C.; Wilson, J.; Stier, P.; Cavalli, F.

2010-01-01

Our understanding of the global black carbon (BC) cycle is essentially qualitative due to uncertainties in our knowledge of its properties. This work investigates two source of uncertainties in modelling black carbon: those due to the use of different schemes for BC ageing and its removal rate in

Modeling the contributions of global air temperature, synoptic-scale phenomena and soil moisture to near-surface static energy variability using artificial neural networks

Science.gov (United States)

Pryor, Sara C.; Sullivan, Ryan C.; Schoof, Justin T.

2017-12-01

The static energy content of the atmosphere is increasing on a global scale, but exhibits important subglobal and subregional scales of variability and is a useful parameter for integrating the net effect of changes in the partitioning of energy at the surface and for improving understanding of the causes of so-called warming holes (i.e., locations with decreasing daily maximum air temperatures (T) or increasing trends of lower magnitude than the global mean). Further, measures of the static energy content (herein the equivalent potential temperature, θe) are more strongly linked to excess human mortality and morbidity than air temperature alone, and have great relevance in understanding causes of past heat-related excess mortality and making projections of possible future events that are likely to be associated with negative human health and economic consequences. New nonlinear statistical models for summertime daily maximum and minimum θe are developed and used to advance understanding of drivers of historical change and variability over the eastern USA. The predictor variables are an index of the daily global mean temperature, daily indices of the synoptic-scale meteorology derived from T and specific humidity (Q) at 850 and 500 hPa geopotential heights (Z), and spatiotemporally averaged soil moisture (text">SM). text">SM is particularly important in determining the magnitude of θe over regions that have previously been identified as exhibiting warming holes, confirming the key importance of text">SM in dictating the partitioning of net radiation into sensible and latent heat and dictating trends in near-surface T and θe. Consistent with our a priori expectations, models built using artificial neural networks (ANNs) out-perform linear models that do not permit interaction of the predictor variables (global T, synoptic-scale meteorological conditions and text">SM). This is particularly marked in regions with high variability in minimum and maximum θe, where

Development and psychometric evaluation of a clinical global impression for schizoaffective disorder scale.

Science.gov (United States)

Allen, Michael H; Daniel, David G; Revicki, Dennis A; Canuso, Carla M; Turkoz, Ibrahim; Fu, Dong-Jing; Alphs, Larry; Ishak, K Jack; Bartko, John J; Lindenmayer, Jean-Pierre

2012-01-01

The Clinical Global Impression for Schizoaffective Disorder scale is a new rating scale adapted from the Clinical Global Impression scale for use in patients with schizoaffective disorder. The psychometric characteristics of the Clinical Global Impression for Schizoaffective Disorder are described. Content validity was assessed using an investigator questionnaire. Inter-rater reliability was determined with 12 sets of videotaped interviews rated independently by two trained individuals. Test-retest reliability was assessed using 30 randomly selected raters from clinical trials who evaluated the same videos on separate occasions two weeks apart. Convergent and divergent validity and effect size were evaluated by comparing scores between the Clinical Global Impression for Schizoaffective Disorder and the Positive and Negative Syndrome Scale, 21-item Hamilton Rating Scale for Depression, and Young Mania Rating Scale scales using pooled patient data from two clinical trials. Clinical Global Impression for Schizoaffective Disorder scores were then linked to corresponding Positive and Negative Syndrome Scale scores. Content validity was strong. Inter-rater agreement was good to excellent for most scales and subscales (intra-class correlation coefficient ≥ 0.50). Test-retest showed good reproducibility, with intraclass correlation coefficients ranging from 0.444 to 0.898. Spearman correlations between Clinical Global Impression for Schizoaffective Disorder domains and corresponding symptom scales were 0.60 or greater, and effect sizes for Clinical Global Impression for Schizoaffective Disorder overall and domain scores were similar to Positive and Negative Syndrome Scale Young Mania Rating Scale, and 21-item Hamilton Rating Scale for Depression scores. Raters anticipated that the scale might be less effective in distinguishing negative from depressive symptoms, and, in fact, the results here may reflect that clinical reality. Multiple lines of evidence support the

Scale and Scope Economies in the Global Advertising and Marketing Services Business

OpenAIRE

Alvin J. Silk; Ernst R. Berndt

2003-01-01

We assess size and scope-related economies in the global advertising and marketing services business. A translog cost function is employed wherein a firm's costs vary according to its scale and two dimensions of the scope of its operations. Parameters of the model are estimated via three stage least squares using annual data for 1989-2001 for an unbalanced panel consisting of the eight largest firms in this industry. A firm's total variable costs are affected by its scale, scope (mix of servi...

Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balances

Directory of Open Access Journals (Sweden)

G. Tang

2012-08-01

Full Text Available Satellite-based data, such as vegetation type and fractional vegetation cover, are widely used in hydrologic models to prescribe the vegetation state in a study region. Dynamic global vegetation models (DGVM simulate land surface hydrology. Incorporation of satellite-based data into a DGVM may enhance a model's ability to simulate land surface hydrology by reducing the task of model parameterization and providing distributed information on land characteristics. The objectives of this study are to (i modify a DGVM for simulating land surface water balances; (ii evaluate the modified model in simulating actual evapotranspiration (ET, soil moisture, and surface runoff at regional or watershed scales; and (iii gain insight into the ability of both the original and modified model to simulate large spatial scale land surface hydrology. To achieve these objectives, we introduce the "LPJ-hydrology" (LH model which incorporates satellite-based data into the Lund-Potsdam-Jena (LPJ DGVM. To evaluate the model we ran LH using historical (1981–2006 climate data and satellite-based land covers at 2.5 arc-min grid cells for the conterminous US and for the entire world using coarser climate and land cover data. We evaluated the simulated ET, soil moisture, and surface runoff using a set of observed or simulated data at different spatial scales. Our results demonstrate that spatial patterns of LH-simulated annual ET and surface runoff are in accordance with previously published data for the US; LH-modeled monthly stream flow for 12 major rivers in the US was consistent with observed values respectively during the years 1981–2006 (R² > 0.46, p < 0.01; Nash-Sutcliffe Coefficient > 0.52. The modeled mean annual discharges for 10 major rivers worldwide also agreed well (differences < 15% with observed values for these rivers. Compared to a degree-day method for snowmelt computation, the addition of the solar radiation effect on snowmelt

Spherical Process Models for Global Spatial Statistics

KAUST Repository

Jeong, Jaehong

2017-11-28

Statistical models used in geophysical, environmental, and climate science applications must reflect the curvature of the spatial domain in global data. Over the past few decades, statisticians have developed covariance models that capture the spatial and temporal behavior of these global data sets. Though the geodesic distance is the most natural metric for measuring distance on the surface of a sphere, mathematical limitations have compelled statisticians to use the chordal distance to compute the covariance matrix in many applications instead, which may cause physically unrealistic distortions. Therefore, covariance functions directly defined on a sphere using the geodesic distance are needed. We discuss the issues that arise when dealing with spherical data sets on a global scale and provide references to recent literature. We review the current approaches to building process models on spheres, including the differential operator, the stochastic partial differential equation, the kernel convolution, and the deformation approaches. We illustrate realizations obtained from Gaussian processes with different covariance structures and the use of isotropic and nonstationary covariance models through deformations and geographical indicators for global surface temperature data. To assess the suitability of each method, we compare their log-likelihood values and prediction scores, and we end with a discussion of related research problems.

Log-Normal Turbulence Dissipation in Global Ocean Models

Science.gov (United States)

Pearson, Brodie; Fox-Kemper, Baylor

2018-03-01

Data from turbulent numerical simulations of the global ocean demonstrate that the dissipation of kinetic energy obeys a nearly log-normal distribution even at large horizontal scales O (10 km ) . As the horizontal scales of resolved turbulence are larger than the ocean is deep, the Kolmogorov-Yaglom theory for intermittency in 3D homogeneous, isotropic turbulence cannot apply; instead, the down-scale potential enstrophy cascade of quasigeostrophic turbulence should. Yet, energy dissipation obeys approximate log-normality—robustly across depths, seasons, regions, and subgrid schemes. The distribution parameters, skewness and kurtosis, show small systematic departures from log-normality with depth and subgrid friction schemes. Log-normality suggests that a few high-dissipation locations dominate the integrated energy and enstrophy budgets, which should be taken into account when making inferences from simplified models and inferring global energy budgets from sparse observations.

Improved convergence of gradient-based reconstruction using multi-scale models

International Nuclear Information System (INIS)

Cunningham, G.S.; Hanson, K.M.; Koyfman, I.

1996-01-01

Geometric models have received increasing attention in medical imaging for tasks such as segmentation, reconstruction, restoration, and registration. In order to determine the best configuration of the geometric model in the context of any of these tasks, one needs to perform a difficult global optimization of an energy function that may have many local minima. Explicit models of geometry, also called deformable models, snakes, or active contours, have been used extensively to solve image segmentation problems in a non-Bayesian framework. Researchers have seen empirically that multi-scale analysis is useful for convergence to a configuration that is near the global minimum. In this type of analysis, the image data are convolved with blur functions of increasing resolution, and an optimal configuration of the snake is found for each blurred image. The configuration obtained using the highest resolution blur is used as the solution to the global optimization problem. In this article, the authors use explicit models of geometry for a variety of Bayesian estimation problems, including image segmentation, reconstruction and restoration. The authors introduce a multi-scale approach that blurs the geometric model, rather than the image data, and show that this approach turns a global, highly nonquadratic optimization into a sequence of local, approximately quadratic problems that converge to the global minimum. The result is a deterministic, robust, and efficient optimization strategy applicable to a wide variety of Bayesian estimation problems in which geometric models of images are an important component

How important is biological ice nucleation in clouds on a global scale?

International Nuclear Information System (INIS)

Hoose, C; Kristjansson, J E; Burrows, S M

2010-01-01

The high ice nucleating ability of some biological particles has led to speculations about living and dead organisms being involved in cloud ice and precipitation formation, exerting a possibly significant influence on weather and climate. In the present study, the role of primary biological aerosol particles (PBAPs) as heterogeneous ice nuclei is investigated with a global model. Emission parametrizations for bacteria, fungal spores and pollen based on recent literature are introduced, as well as an immersion freezing parametrization based on classical nucleation theory and laboratory measurements. The simulated contribution of PBAPs to the global average ice nucleation rate is only 10 -5 %, with an uppermost estimate of 0.6%. At the same time, observed PBAP concentrations in air and biological ice nucleus concentrations in snow are reasonably well captured by the model. This implies that 'bioprecipitation' processes (snow and rain initiated by PBAPs) are of minor importance on the global scale.

Modeling the recovery and degradation of mangroves at the global scale

Science.gov (United States)

Lagomasino, D.; Fatoyinbo, T.; Lee, S. K.; Feliciano, E. A.; Trettin, C.

2017-12-01

Forest growth and reforestation rates are crucial information for sustainable forest management practices and decision-making for restoration projects. There has been a recent increase in mangrove blue carbon restoration projects because of their extremely high carbon density, globally can reach over 1000 Mg ha-1 of carbon. If ecosystem projects do plan to facilitate mangrove restoration or deter land cover changes as a climate change mitigation strategy or in other carbon inventory strategies, unbiased field inventories need to become the norm. It is known that mangrove carbon can be extremely high in certain geographic settings, but that is not the case for many other regions. Remotely sensed canopy height has recently been incorporated into mangrove field inventories which provides an unbiased, readily accessible, and spatially-explicit model that was used to stratify the inventory design into discrete height classes. Combining the forest canopy height distribution captured from space and the field inventory data, biomass and carbon density were determined for each height class. Here, we present mangrove vertical growth rates and global carbon stock changes modeled through the combination of remotely sensed land cover change and canopy height class models using Landsat-derived vegetation index anomalies and synthetic aperture radar interferometry, respectively. Average growth rates ( 1-1.5m yr-1) were determined for four mangrove forests in the Zambezi, Rufiji, Ganges, and Mekong Deltas. An average global net productivity (9-10 Mg C ha-1 yr-1) was then derived using the four sites which represent young, fast-growing mangrove forests. Global mangrove carbon change was calculated using the average productivity estimates and land cover change from 2000 to 2015. Losses were categorized based on canopy height derived biomass classes in 2000 using Shuttle Radar Topography Mission data, while gained carbon stocks were assessed by using the study-derived mean

Global thermal models of the lithosphere

Science.gov (United States)

Cammarano, F.; Guerri, M.

2017-12-01

Unraveling the thermal structure of the outermost shell of our planet is key for understanding its evolution. We obtain temperatures from interpretation of global shear-velocity (VS) models. Long-wavelength thermal structure is well determined by seismic models and only slightly affected by compositional effects and uncertainties in mineral-physics properties. Absolute temperatures and gradients with depth, however, are not well constrained. Adding constraints from petrology, heat-flow observations and thermal evolution of oceanic lithosphere help to better estimate absolute temperatures in the top part of the lithosphere. We produce global thermal models of the lithosphere at different spatial resolution, up to spherical-harmonics degree 24, and provide estimated standard deviations. We provide purely seismic thermal (TS) model and hybrid models where temperatures are corrected with steady-state conductive geotherms on continents and cooling model temperatures on oceanic regions. All relevant physical properties, with the exception of thermal conductivity, are based on a self-consistent thermodynamical modelling approach. Our global thermal models also include density and compressional-wave velocities (VP) as obtained either assuming no lateral variations in composition or a simple reference 3-D compositional structure, which takes into account a chemically depleted continental lithosphere. We found that seismically-derived temperatures in continental lithosphere fit well, overall, with continental geotherms, but a large variation in radiogenic heat is required to reconcile them with heat flow (long wavelength) observations. Oceanic shallow lithosphere below mid-oceanic ridges and young oceans is colder than expected, confirming the possible presence of a dehydration boundary around 80 km depth already suggested in previous studies. The global thermal models should serve as the basis to move at a smaller spatial scale, where additional thermo-chemical variations

Tropospheric Ozone Assessment Report: Assessment of global-scale model performance for global and regional ozone distributions, variability, and trends

Directory of Open Access Journals (Sweden)

P. J. Young

2018-01-01

Full Text Available The goal of the Tropospheric Ozone Assessment Report (TOAR is to provide the research community with an up-to-date scientific assessment of tropospheric ozone, from the surface to the tropopause. While a suite of observations provides significant information on the spatial and temporal distribution of tropospheric ozone, observational gaps make it necessary to use global atmospheric chemistry models to synthesize our understanding of the processes and variables that control tropospheric ozone abundance and its variability. Models facilitate the interpretation of the observations and allow us to make projections of future tropospheric ozone and trace gas distributions for different anthropogenic or natural perturbations. This paper assesses the skill of current-generation global atmospheric chemistry models in simulating the observed present-day tropospheric ozone distribution, variability, and trends. Drawing upon the results of recent international multi-model intercomparisons and using a range of model evaluation techniques, we demonstrate that global chemistry models are broadly skillful in capturing the spatio-temporal variations of tropospheric ozone over the seasonal cycle, for extreme pollution episodes, and changes over interannual to decadal periods. However, models are consistently biased high in the northern hemisphere and biased low in the southern hemisphere, throughout the depth of the troposphere, and are unable to replicate particular metrics that define the longer term trends in tropospheric ozone as derived from some background sites. When the models compare unfavorably against observations, we discuss the potential causes of model biases and propose directions for future developments, including improved evaluations that may be able to better diagnose the root cause of the model-observation disparity. Overall, model results should be approached critically, including determining whether the model performance is acceptable for

Potentials of satellite derived SIF products to constrain GPP simulated by the new ORCHIDEE-FluOR terrestrial model at the global scale

Science.gov (United States)

Bacour, C.; Maignan, F.; Porcar-Castell, A.; MacBean, N.; Goulas, Y.; Flexas, J.; Guanter, L.; Joiner, J.; Peylin, P.

2016-12-01

A new era for improving our knowledge of the terrestrial carbon cycle at the global scale has begun with recent studies on the relationships between remotely sensed Sun Induce Fluorescence (SIF) and plant photosynthetic activity (GPP), and the availability of such satellite-derived products now "routinely" produced from GOSAT, GOME-2, or OCO-2 observations. Assimilating SIF data into terrestrial ecosystem models (TEMs) represents a novel opportunity to reduce the uncertainty of their prediction with respect to carbon-climate feedbacks, in particular the uncertainties resulting from inaccurate parameter values. A prerequisite is a correct representation in TEMs of the several drivers of plant fluorescence from the leaf to the canopy scale, and in particular the competing processes of photochemistry and non photochemical quenching (NPQ).In this study, we present the first results of a global scale assimilation of GOME-2 SIF products within a new version of the ORCHIDEE land surface model including a physical module of plant fluorescence. At the leaf level, the regulation of fluorescence yield is simulated both by the photosynthesis module of ORCHIDEE to calculate the photochemical yield and by a parametric model to estimate NPQ. The latter has been calibrated on leaf fluorescence measurements performed for boreal coniferous and Mediterranean vegetation species. A parametric representation of the SCOPE radiative transfer model is used to model the plant fluorescence fluxes for PSI and PSII and the scaling up to the canopy level. The ORCHIDEE-FluOR model is firstly evaluated with respect to in situ measurements of plant fluorescence flux and photochemical yield for scots pine and wheat. The potentials of SIF data to constrain the modelled GPP are evaluated by assimilating one year of GOME-2-SIF products within ORCHIDEE-FluOR. We investigate in particular the changes in the spatial patterns of GPP following the optimization of the photosynthesis and phenology parameters

Homogenized global nonlinear constitutive model for RC panels under cyclic loadings

International Nuclear Information System (INIS)

Huguet, Miquel; Voldoire, Francois; Kotronis, Panagiotis; Erlicher, Silvano

2014-01-01

A new nonlinear stress resultant global constitutive model for RC panels is presented. Concrete damage, concrete stress transfer at cracks and bond-slip stress are the main nonlinear effects identified at the local scale that constitute the basis for the construction of the stress resultant global model through an analytical homogenization technique. The closed form solution is obtained using general functions for the previous phenomena. (authors)

The community Noah land surface model with multiparameterization options (Noah-MP): 2. Evaluation over global river basins

KAUST Repository

Yang, Zong-Liang

2011-06-24

The augmented Noah land surface model described in the first part of the two-part series was evaluated here over global river basins. Across various climate zones, global-scale tests can reveal a model\\'s weaknesses and strengths that a local-scale testing cannot. In addition, global-scale tests are more challenging than local- and catchment-scale tests. Given constant model parameters (e. g., runoff parameters) across global river basins, global-scale tests are more stringent. We assessed model performance against various satellite and ground-based observations over global river basins through six experiments that mimic a transition from the original Noah LSM to the fully augmented version. The model shows transitional improvements in modeling runoff, soil moisture, snow, and skin temperature, despite considerable increase in computational time by the fully augmented Noah-MP version compared to the original Noah LSM. The dynamic vegetation model favorably captures seasonal and spatial variability of leaf area index and green vegetation fraction. We also conducted 36 ensemble experiments with 36 combinations of optional schemes for runoff, leaf dynamics, stomatal resistance, and the β factor. Runoff schemes play a dominant and different role in controlling soil moisture and its relationship with evapotranspiration compared to ecological processes such as β the factor, vegetation dynamics, and stomatal resistance. The 36-member ensemble mean of runoff performs better than any single member over the world\\'s 50 largest river basins, suggesting a great potential of land-based ensemble simulations for climate prediction. Copyright © 2011 by the American Geophysical Union.

Technical Report Series on Global Modeling and Data Assimilation. Volume 31; Global Surface Ocean Carbon Estimates in a Model Forced by MERRA

Science.gov (United States)

Gregg, Watson W.; Casey, Nancy W.; Rousseaux, Cecile S.

2013-01-01

MERRA products were used to force an established ocean biogeochemical model to estimate surface carbon inventories and fluxes in the global oceans. The results were compared to public archives of in situ carbon data and estimates. The model exhibited skill for ocean dissolved inorganic carbon (DIC), partial pressure of ocean CO2 (pCO2) and air-sea fluxes (FCO2). The MERRA-forced model produced global mean differences of 0.02% (approximately 0.3 microns) for DIC, -0.3% (about -1.2 (micro) atm; model lower) for pCO2, and -2.3% (-0.003 mol C/sq m/y) for FCO2 compared to in situ estimates. Basin-scale distributions were significantly correlated with observations for all three variables (r=0.97, 0.76, and 0.73, P<0.05, respectively for DIC, pCO2, and FCO2). All major oceanographic basins were represented as sources to the atmosphere or sinks in agreement with in situ estimates. However, there were substantial basin-scale and local departures.

a Model Study of Small-Scale World Map Generalization

Science.gov (United States)

Cheng, Y.; Yin, Y.; Li, C. M.; Wu, W.; Guo, P. P.; Ma, X. L.; Hu, F. M.

2018-04-01

With the globalization and rapid development every filed is taking an increasing interest in physical geography and human economics. There is a surging demand for small scale world map in large formats all over the world. Further study of automated mapping technology, especially the realization of small scale production on a large scale global map, is the key of the cartographic field need to solve. In light of this, this paper adopts the improved model (with the map and data separated) in the field of the mapmaking generalization, which can separate geographic data from mapping data from maps, mainly including cross-platform symbols and automatic map-making knowledge engine. With respect to the cross-platform symbol library, the symbol and the physical symbol in the geographic information are configured at all scale levels. With respect to automatic map-making knowledge engine consists 97 types, 1086 subtypes, 21845 basic algorithm and over 2500 relevant functional modules.In order to evaluate the accuracy and visual effect of our model towards topographic maps and thematic maps, we take the world map generalization in small scale as an example. After mapping generalization process, combining and simplifying the scattered islands make the map more explicit at 1 : 2.1 billion scale, and the map features more complete and accurate. Not only it enhance the map generalization of various scales significantly, but achieve the integration among map-makings of various scales, suggesting that this model provide a reference in cartographic generalization for various scales.

Emergence of global scaling behaviour in the coupled Earth-atmosphere interaction

OpenAIRE

Fallah, Bijan; Saberi, Abbas Ali; Sodoudi, Sahar

2016-01-01

Scale invariance property in the global geometry of Earth may lead to a coupled interactive behaviour between various components of the climate system. One of the most interesting correlations exists between spatial statistics of the global topography and the temperature on Earth. Here we show that the power-law behaviour observed in the Earth topography via different approaches, resembles a scaling law in the global spatial distribution of independent atmospheric parameters. We report on obs...

A comprehensive set of benchmark tests for a land surface model of simultaneous fluxes of water and carbon at both the global and seasonal scale

Directory of Open Access Journals (Sweden)

E. Blyth

2011-04-01

Full Text Available Evaluating the models we use in prediction is important as it allows us to identify uncertainties in prediction as well as guiding the priorities for model development. This paper describes a set of benchmark tests that is designed to quantify the performance of the land surface model that is used in the UK Hadley Centre General Circulation Model (JULES: Joint UK Land Environment Simulator. The tests are designed to assess the ability of the model to reproduce the observed fluxes of water and carbon at the global and regional spatial scale, and on a seasonal basis. Five datasets are used to test the model: water and carbon dioxide fluxes from ten FLUXNET sites covering the major global biomes, atmospheric carbon dioxide concentrations at four representative stations from the global network, river flow from seven catchments, the seasonal mean NDVI over the seven catchments and the potential land cover of the globe (after the estimated anthropogenic changes have been removed. The model is run in various configurations and results are compared with the data.

A few examples are chosen to demonstrate the importance of using combined use of observations of carbon and water fluxes in essential in order to understand the causes of model errors. The benchmarking approach is suitable for application to other global models.

How to scale SaaS business  from local to global markets? : Case of ad servers

OpenAIRE

PANDERS, TOMS

2014-01-01

This thesis will describe SaaS (Software as a Service) business in a global environment. The prior focus will be to give suggestions of models and good examples of how to scale local business into global markets. The necessary theoretical framework on software product and scalability issues is given. Qualitative research is carried out to find out how the suggested models are adopted among selected ad serving companies. The results from three different companies were analyzed to find similari...

Assessing the influence of watershed characteristics on chlorophyll a in waterbodies at global and regional scales

Science.gov (United States)

Woelmer, Whitney; Kao, Yu-Chun; Bunnell, David B.; Deines, Andrew M.; Bennion, David; Rogers, Mark W.; Brooks, Colin N.; Sayers, Michael J.; Banach, David M.; Grimm, Amanda G.; Shuchman, Robert A.

2016-01-01

Prediction of primary production of lentic water bodies (i.e., lakes and reservoirs) is valuable to researchers and resource managers alike, but is very rarely done at the global scale. With the development of remote sensing technologies, it is now feasible to gather large amounts of data across the world, including understudied and remote regions. To determine which factors were most important in explaining the variation of chlorophyll a (Chl-a), an indicator of primary production in water bodies, at global and regional scales, we first developed a geospatial database of 227 water bodies and watersheds with corresponding Chl-a, nutrient, hydrogeomorphic, and climate data. Then we used a generalized additive modeling approach and developed model selection criteria to select models that most parsimoniously related Chl-a to predictor variables for all 227 water bodies and for 51 lakes in the Laurentian Great Lakes region in the data set. Our best global model contained two hydrogeomorphic variables (water body surface area and the ratio of watershed to water body surface area) and a climate variable (average temperature in the warmest model selection criteria to select models that most parsimoniously related Chl-a to predictor variables quarter) and explained ~ 30% of variation in Chl-a. Our regional model contained one hydrogeomorphic variable (flow accumulation) and the same climate variable, but explained substantially more variation (58%). Our results indicate that a regional approach to watershed modeling may be more informative to predicting Chl-a, and that nearly a third of global variability in Chl-a may be explained using hydrogeomorphic and climate variables.

Simplifiying global biogeochemistry models to evaluate methane emissions

Science.gov (United States)

Gerber, S.; Alonso-Contes, C.

2017-12-01

Process-based models are important tools to quantify wetland methane emissions, particularly also under climate change scenarios, evaluating these models is often cumbersome as they are embedded in larger land-surface models where fluctuating water table and the carbon cycle (including new readily decomposable plant material) are predicted variables. Here, we build on these large scale models but instead of modeling water table and plant productivity we provide values as boundary conditions. In contrast, aerobic and anaerobic decomposition, as well as soil column transport of oxygen and methane are predicted by the model. Because of these simplifications, the model has the potential to be more readily adaptable to the analysis of field-scale data. Here we determine the sensitivity of the model to specific setups, parameter choices, and to boundary conditions in order to determine set-up needs and inform what critical auxiliary variables need to be measured in order to better predict field-scale methane emissions from wetland soils. To that end we performed a global sensitivity analysis that also considers non-linear interactions between processes. The global sensitivity analysis revealed, not surprisingly, that water table dynamics (both mean level and amplitude of fluctuations), and the rate of the carbon cycle (i.e. net primary productivity) are critical determinants of methane emissions. The depth-scale where most of the potential decomposition occurs also affects methane emissions. Different transport mechanisms are compensating each other to some degree: If plant conduits are constrained, methane emissions by diffusive flux and ebullition compensate to some degree, however annual emissions are higher when plants help to bypass methanotrophs in temporally unsaturated upper layers. Finally, while oxygen consumption by plant roots help creating anoxic conditions it has little effect on overall methane emission. Our initial sensitivity analysis helps guiding

Global scaling analysis for the pebble bed advanced high temperature reactor

International Nuclear Information System (INIS)

Blandford, E.D.; Peterson, P.F.

2009-01-01

Scaled Integral Effects Test (IET) facilities play a critical role in the design certification process of innovative reactor designs. Best-estimate system analysis codes, which minimize deliberate conservatism, require confirmatory data during the validation process to ensure an acceptable level of accuracy as defined by the regulator. The modular Pebble Bed Advanced High Temperature Reactor (PB-AHTR), with a nominal power output of 900 MWth, is the most recent UC Berkeley design for a liquid fluoride salt cooled, solid fuel reactor. The PB-AHTR takes advantage of technologies developed for gas-cooled high temperature thermal and fast reactors, sodium fast reactors, and molten salt reactors. In this paper, non-dimensional scaling groups and similarity criteria are presented at the global system level for a loss of forced circulation transient, where single-phase natural circulation is the primary mechanism for decay heat removal following a primary pump trip. Due to very large margin to fuel damage temperatures, the peak metal temperature of primary-loop components was identified as the key safety parameter of interest. Fractional Scaling Analysis (FSA) methods were used to quantify the intensity of each transfer process during the transient and subsequently rank them by their relative importance while identifying key sources of distortion between the prototype and model. The results show that the development of a scaling hierarchy at the global system level informs the bottom-up scaling analysis. (author)

Continent-scale global change attribution in European birds - combining annual and decadal time scales

DEFF Research Database (Denmark)

Jørgensen, Peter Søgaard; Böhning-Gaese, Katrin; Thorup, Kasper

2016-01-01

foundation for attributing species responses to global change may be achieved by complementing an attributes-based approach by one estimating the relationship between repeated measures of organismal and environmental changes over short time scales. To assess the benefit of this multiscale perspective, we...... on or in the peak of the breeding season with the largest effect sizes observed in cooler parts of species' climatic ranges. Our results document the potential of combining time scales and integrating both species attributes and environmental variables for global change attribution. We suggest such an approach......Species attributes are commonly used to infer impacts of environmental change on multiyear species trends, e.g. decadal changes in population size. However, by themselves attributes are of limited value in global change attribution since they do not measure the changing environment. A broader...

Interannual Variation in Phytoplankton Primary Production at a Global Scale

Science.gov (United States)

Rousseaux, Cecile Severine; Gregg, Watson W.

2013-01-01

We used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of four phytoplankton groups to the total primary production. First, we assessed the contribution of each phytoplankton groups to the total primary production at a global scale for the period 1998-2011. Globally, diatoms contributed the most to the total phytoplankton production ((is)approximately 50%, the equivalent of 20 PgC·y1). Coccolithophores and chlorophytes each contributed approximately 20% ((is) approximately 7 PgC·y1) of the total primary production and cyanobacteria represented about 10% ((is) approximately 4 PgC·y1) of the total primary production. Primary production by diatoms was highest in the high latitudes ((is) greater than 40 deg) and in major upwelling systems (Equatorial Pacific and Benguela system). We then assessed interannual variability of this group-specific primary production over the period 1998-2011. Globally the annual relative contribution of each phytoplankton groups to the total primary production varied by maximum 4% (1-2 PgC·y1). We assessed the effects of climate variability on group-specific primary production using global (i.e., Multivariate El Niño Index, MEI) and "regional" climate indices (e.g., Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability as indicated by significant correlation (p (is) less than 0.05) between the MEI and the group-specific primary production from all groups except coccolithophores. In the Atlantic, climate variability as indicated by NAO was significantly correlated to the primary production of 2 out of the 4 groups in the North Central Atlantic (diatoms/cyanobacteria) and in the North Atlantic (chlorophytes and coccolithophores). We found that climate variability as indicated by SAM had only a limited effect

The GEWEX LandFlux project: evaluation of model evaporation using tower-based and globally gridded forcing data

Science.gov (United States)

McCabe, M. F.; Ershadi, A.; Jimenez, C.; Miralles, D. G.; Michel, D.; Wood, E. F.

2016-01-01

Determining the spatial distribution and temporal development of evaporation at regional and global scales is required to improve our understanding of the coupled water and energy cycles and to better monitor any changes in observed trends and variability of linked hydrological processes. With recent international efforts guiding the development of long-term and globally distributed flux estimates, continued product assessments are required to inform upon the selection of suitable model structures and also to establish the appropriateness of these multi-model simulations for global application. In support of the objectives of the Global Energy and Water Cycle Exchanges (GEWEX) LandFlux project, four commonly used evaporation models are evaluated against data from tower-based eddy-covariance observations, distributed across a range of biomes and climate zones. The selected schemes include the Surface Energy Balance System (SEBS) approach, the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model, the Penman-Monteith-based Mu model (PM-Mu) and the Global Land Evaporation Amsterdam Model (GLEAM). Here we seek to examine the fidelity of global evaporation simulations by examining the multi-model response to varying sources of forcing data. To do this, we perform parallel and collocated model simulations using tower-based data together with a global-scale grid-based forcing product. Through quantifying the multi-model response to high-quality tower data, a better understanding of the subsequent model response to the coarse-scale globally gridded data that underlies the LandFlux product can be obtained, while also providing a relative evaluation and assessment of model performance. Using surface flux observations from 45 globally distributed eddy-covariance stations as independent metrics of performance, the tower-based analysis indicated that PT-JPL provided the highest overall statistical performance (0.72; 61 W m-2; 0.65), followed closely by GLEAM (0.68; 64 W m-2

Multi-scale inference of interaction rules in animal groups using Bayesian model selection.

Directory of Open Access Journals (Sweden)

Richard P Mann

2012-01-01

Full Text Available Inference of interaction rules of animals moving in groups usually relies on an analysis of large scale system behaviour. Models are tuned through repeated simulation until they match the observed behaviour. More recent work has used the fine scale motions of animals to validate and fit the rules of interaction of animals in groups. Here, we use a Bayesian methodology to compare a variety of models to the collective motion of glass prawns (Paratya australiensis. We show that these exhibit a stereotypical 'phase transition', whereby an increase in density leads to the onset of collective motion in one direction. We fit models to this data, which range from: a mean-field model where all prawns interact globally; to a spatial Markovian model where prawns are self-propelled particles influenced only by the current positions and directions of their neighbours; up to non-Markovian models where prawns have 'memory' of previous interactions, integrating their experiences over time when deciding to change behaviour. We show that the mean-field model fits the large scale behaviour of the system, but does not capture fine scale rules of interaction, which are primarily mediated by physical contact. Conversely, the Markovian self-propelled particle model captures the fine scale rules of interaction but fails to reproduce global dynamics. The most sophisticated model, the non-Markovian model, provides a good match to the data at both the fine scale and in terms of reproducing global dynamics. We conclude that prawns' movements are influenced by not just the current direction of nearby conspecifics, but also those encountered in the recent past. Given the simplicity of prawns as a study system our research suggests that self-propelled particle models of collective motion should, if they are to be realistic at multiple biological scales, include memory of previous interactions and other non-Markovian effects.

Toward a global multi-scale heliophysics observatory

Science.gov (United States)

Semeter, J. L.

2017-12-01

We live within the only known stellar-planetary system that supports life. What we learn about this system is not only relevant to human society and its expanding reach beyond Earth's surface, but also to our understanding of the origins and evolution of life in the universe. Heliophysics is focused on solar-terrestrial interactions mediated by the magnetic and plasma environment surrounding the planet. A defining feature of energy flow through this environment is interaction across physical scales. A solar disturbance aimed at Earth can excite geospace variability on scales ranging from thousands of kilometers (e.g., global convection, region 1 and 2 currents, electrojet intensifications) to 10's of meters (e.g., equatorial spread-F, dispersive Alfven waves, plasma instabilities). Most "geospace observatory" concepts are focused on a single modality (e.g., HF/UHF radar, magnetometer, optical) providing a limited parameter set over a particular spatiotemporal resolution. Data assimilation methods have been developed to couple heterogeneous and distributed observations, but resolution has typically been prescribed a-priori and according to physical assumptions. This paper develops a conceptual framework for the next generation multi-scale heliophysics observatory, capable of revealing and quantifying the complete spectrum of cross-scale interactions occurring globally within the geospace system. The envisioned concept leverages existing assets, enlists citizen scientists, and exploits low-cost access to the geospace environment. Examples are presented where distributed multi-scale observations have resulted in substantial new insight into the inner workings of our stellar-planetary system.

AgMIP 1.5°C Assessment: Mitigation and Adaptation at Coordinated Global and Regional Scales

Science.gov (United States)

Rosenzweig, C.

2016-12-01

The AgMIP 1.5°C Coordinated Global and Regional Integrated Assessments of Climate Change and Food Security (AgMIP 1.5 CGRA) is linking site-based crop and livestock models with similar models run on global grids, and then links these biophysical components with economics models and nutrition metrics at regional and global scales. The AgMIP 1.5 CGRA assessment brings together experts in climate, crop, livestock, economics, nutrition, and food security to define the 1.5°C Protocols and guide the process throughout the assessment. Scenarios are designed to consistently combine elements of intertwined storylines of future society including socioeconomic development (Shared Socioeconomic Pathways), greenhouse gas concentrations (Representative Concentration Pathways), and specific pathways of agricultural sector development (Representative Agricultural Pathways). Shared Climate Policy Assumptions will be extended to provide additional agricultural detail on mitigation and adaptation strategies. The multi-model, multi-disciplinary, multi-scale integrated assessment framework is using scenarios of economic development, adaptation, mitigation, food policy, and food security. These coordinated assessments are grounded in the expertise of AgMIP partners around the world, leading to more consistent results and messages for stakeholders, policymakers, and the scientific community. The early inclusion of nutrition and food security experts has helped to ensure that assessment outputs include important metrics upon which investment and policy decisions may be based. The CGRA builds upon existing AgMIP research groups (e.g., the AgMIP Wheat Team and the AgMIP Global Gridded Crop Modeling Initiative; GGCMI) and regional programs (e.g., AgMIP Regional Teams in Sub-Saharan Africa and South Asia), with new protocols for cross-scale and cross-disciplinary linkages to ensure the propagation of expert judgment and consistent assumptions.

Global change impact on water resources at the regional scale - a reflection on participatory modeling

Science.gov (United States)

Barthel, Roland; Büttner, Hannah; Nickel, Darla; Seidl, Roman

2015-04-01

discussion we therefore focus on the following three questions: • Can a stakeholder dialogue be successfully used to support the development of new, complex modelling systems, in particular at the regional scale? • What is the right timing for stakeholder interaction in the case of unclear problem definition - i.e. global (climate) change impact on regions where climate is not (yet) a threat to water or land use related demands and activities? • To what degree can scientists be motivated to carry out participatory research at all? We conclude that the PM process in GD was only partly successful because the project set overambitious goals, including the application of fundamentally new approaches to interdisciplinary science, the use of new modelling technologies, the focus upon and evaluation of potential and therefore characteristically uncertain future problems, including stakeholder demands, and the development of a ready-to-use, user-friendly tool. Furthermore, GD also showed that an externally and professionally moderated stakeholder dialogue is an absolute necessity to achieve successful participation of stakeholders in model development. The modelers themselves neither had the time, the skills and the ambitions to do this. Furthermore, there is a lack of incentives for scientists, particularly natural scientists, to commit to PM activities. Given the fact that the outcomes of PM are supposed to be relevant for societal decision making, this issue needs further attention.

Global assessment of ocean carbon export by combining satellite observations and food-web models

Science.gov (United States)

Siegel, D. A.; Buesseler, K. O.; Doney, S. C.; Sailley, S. F.; Behrenfeld, M. J.; Boyd, P. W.

2014-03-01

The export of organic carbon from the surface ocean by sinking particles is an important, yet highly uncertain, component of the global carbon cycle. Here we introduce a mechanistic assessment of the global ocean carbon export using satellite observations, including determinations of net primary production and the slope of the particle size spectrum, to drive a food-web model that estimates the production of sinking zooplankton feces and algal aggregates comprising the sinking particle flux at the base of the euphotic zone. The synthesis of observations and models reveals fundamentally different and ecologically consistent regional-scale patterns in export and export efficiency not found in previous global carbon export assessments. The model reproduces regional-scale particle export field observations and predicts a climatological mean global carbon export from the euphotic zone of 6 Pg C yr-1. Global export estimates show small variation (typically model parameter values. The model is also robust to the choices of the satellite data products used and enables interannual changes to be quantified. The present synthesis of observations and models provides a path for quantifying the ocean's biological pump.

Optimizing rice yields while minimizing yield-scaled global warming potential.

Science.gov (United States)

Pittelkow, Cameron M; Adviento-Borbe, Maria A; van Kessel, Chris; Hill, James E; Linquist, Bruce A

2014-05-01

To meet growing global food demand with limited land and reduced environmental impact, agricultural greenhouse gas (GHG) emissions are increasingly evaluated with respect to crop productivity, i.e., on a yield-scaled as opposed to area basis. Here, we compiled available field data on CH4 and N2 O emissions from rice production systems to test the hypothesis that in response to fertilizer nitrogen (N) addition, yield-scaled global warming potential (GWP) will be minimized at N rates that maximize yields. Within each study, yield N surplus was calculated to estimate deficit or excess N application rates with respect to the optimal N rate (defined as the N rate at which maximum yield was achieved). Relationships between yield N surplus and GHG emissions were assessed using linear and nonlinear mixed-effects models. Results indicate that yields increased in response to increasing N surplus when moving from deficit to optimal N rates. At N rates contributing to a yield N surplus, N2 O and yield-scaled N2 O emissions increased exponentially. In contrast, CH4 emissions were not impacted by N inputs. Accordingly, yield-scaled CH4 emissions decreased with N addition. Overall, yield-scaled GWP was minimized at optimal N rates, decreasing by 21% compared to treatments without N addition. These results are unique compared to aerobic cropping systems in which N2 O emissions are the primary contributor to GWP, meaning yield-scaled GWP may not necessarily decrease for aerobic crops when yields are optimized by N fertilizer addition. Balancing gains in agricultural productivity with climate change concerns, this work supports the concept that high rice yields can be achieved with minimal yield-scaled GWP through optimal N application rates. Moreover, additional improvements in N use efficiency may further reduce yield-scaled GWP, thereby strengthening the economic and environmental sustainability of rice systems. © 2013 John Wiley & Sons Ltd.

Global Wildfire Forecasts Using Large Scale Climate Indices

Science.gov (United States)

Shen, Huizhong; Tao, Shu

2016-04-01

Using weather readings, fire early warning can provided forecast 4-6 hour in advance to minimize fire loss. The benefit would be dramatically enhanced if relatively accurate long-term projection can be also provided. Here we present a novel method for predicting global fire season severity (FSS) at least three months in advance using multiple large-scale climate indices (CIs). The predictive ability is proven effective for various geographic locations and resolution. Globally, as well as in most continents, the El Niño Southern Oscillation (ENSO) is the dominant driving force controlling interannual FSS variability, whereas other CIs also play indispensable roles. We found that a moderate El Niño event is responsible for 465 (272-658 as interquartile range) Tg carbon release and an annual increase of 29,500 (24,500-34,800) deaths from inhalation exposure to air pollutants. Southeast Asia accounts for half of the deaths. Both intercorrelation and interaction of WPs and CIs are revealed, suggesting possible climate-induced modification of fire responses to weather conditions. Our models can benefit fire management in response to climate change.

Global Carbon-and-Conservation Models, Global Eco-States? Ecuador’s Yasuní-ITT Initiative and Governance Implications

Directory of Open Access Journals (Sweden)

Conny Davidsen

2013-05-01

Full Text Available The “global carbon age” marks a structural change far beyond the economic realms of implementing carbon trade, affecting the fabric of global environmental governance and its actors. Carbon trade and conservation in the Global South have taken on various forms, and climate change mitigation efforts in light of continued rainforest deforestation are scrambling to establish effective approaches. Ecuador’s Yasuní-ITT Initiative proposes a new global carbon-and-conservation model in the Ecuadorian Amazon that leaves oil reserves of the Yasuní Ishpingo Tambococha Tiputini (ITT oil fields underground, in exchange for international compensation payments that would be based on voluntary contributions of governments and nongovernmental actors in an international conservation partnership and trust fund under the auspices of the United Nations Development Programme. This model suggests far-reaching consequences, as it introduces new global scales for the sharing and management of environmental costs within a framework of neoliberal cost internalization. The analysis in this paper uses the concept of the “ecological state” (Duit, 2008 as a theoretical point of departure to examine the trans-scalar implications of such a carbon-and-conservation model on global governance structures toward a “global ecological state” (or global eco-state.

A Process-based Model of Global Lichen Productivity

Science.gov (United States)

Porada, P.; Kleidon, A.

2012-04-01

Lichens and biotic crusts are abundant in most ecosystems of the world. They are the main autotrophic organisms in many deserts and at high altitudes and they can also be found in large amounts as epiphytes in some forests, especially in the boreal zone. They are characterised by a great variety of physiological properties, such as growth form, productivity or color. Due to the vast land surface areas covered by lichens, they may contribute significantly to the global terrestrial net carbon uptake. Furthermore, they potentially play an important role with respect to nutrient cycles in some ecosystems and they have the ability to enhance weathering at the surface on which they grow. A possible way to quantify these processes at the global scale is presented here in form of a process-based lichen model. This approach is based on the concepts used in many dynamical vegetation models and extends these methods to account for the specific properties of lichens. Hence, processes such as photosynthesis, respiration and water exchange are implemented as well as important trade-offs like photosynthetic capacity versus respiratory load and water content versus CO2 conductivity. The great physiological variability of lichens is incorporated directly into the model through ranges of possible parameter values, which are randomly sampled. In this way, many artificial lichen "species" are created and climate then acts as a filter to determine the species which are able to survive permanently. By averaging over the surviving "species", the model predicts lichen productivity as a function of climate input data such as temperature, radiation and precipitation at the global scale. Consequently, the contribution of lichens to the global carbon balance can be quantified. Moreover, global patterns of lichen biodiversity and other properties can be illustrated. The model can be extended to account for the nutrient dynamics of lichens, such as nitrogen fixation and the acquisition and

The ecology of dust: local- to global-scale perspectives

Energy Technology Data Exchange (ETDEWEB)

Whicker, Jeffrey J [Los Alamos National Laboratory; Field, Jason P [UA; Belnap, Jayne [NON LANL; Breshears, David D [UA; Neff, Jason [CU; Okin, Gregory S [UCLA; Painter, Thomas H [UNIV OF ARIZONA; Ravi, Sujith [UNIV OF ARIZONA; Reheis, Marith C [UCLA; Reynolds, Richard L [NON LANL

2009-01-01

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 disturbance 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.

A Coupled GCM-Cloud Resolving Modeling System, and a Regional Scale Model to Study Precipitation Processes

Science.gov (United States)

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).

Combined discriminative global and generative local models for visual tracking

Science.gov (United States)

Zhao, Liujun; Zhao, Qingjie; Chen, Yanming; Lv, Peng

2016-03-01

It is a challenging task to develop an effective visual tracking algorithm due to factors such as pose variation, rotation, and so on. Combined discriminative global and generative local appearance models are proposed to address this problem. Specifically, we develop a compact global object representation by extracting the low-frequency coefficients of the color and texture of the object based on two-dimensional discrete cosine transform. Then, with the global appearance representation, we learn a discriminative metric classifier in an online fashion to differentiate the target object from its background, which is very important to robustly indicate the changes in appearance. Second, we develop a new generative local model that exploits the scale invariant feature transform and its spatial geometric information. To make use of the advantages of the global discriminative model and the generative local model, we incorporate them into Bayesian inference framework. In this framework, the complementary models help the tracker locate the target more accurately. Furthermore, we use different mechanisms to update global and local templates to capture appearance changes. The experimental results demonstrate that the proposed approach performs favorably against state-of-the-art methods in terms of accuracy.

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

Science.gov (United States)

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

2018-02-01

Grassland management affects the carbon fluxes of one-third of the global land area and is thus an important factor for the global carbon budget. Nonetheless, this aspect has been largely neglected or underrepresented in global carbon cycle models. We investigate four harvesting schemes for the managed grassland implementation of the dynamic global vegetation model (DGVM) Lund-Potsdam-Jena managed Land (LPJmL) that facilitate a better representation of actual management systems globally. We describe the model implementation and analyze simulation results with respect to harvest, net primary productivity and soil carbon content and by evaluating them against reported grass yields in Europe. We demonstrate the importance of accounting for differences in grassland management by assessing potential livestock grazing densities as well as the impacts of grazing, grazing intensities and mowing systems on soil carbon stocks. Grazing leads to soil carbon losses in polar or arid regions even at moderate livestock densities (management options enables assessments of the global grassland production and its impact on the terrestrial biogeochemical cycles but requires a global data set on current grassland management.

Spatial patterns and temporal dynamics of global scale climate-groundwater interactions

Science.gov (United States)

Cuthbert, M. O.; Gleeson, T. P.; Moosdorf, N.; Schneider, A. C.; Hartmann, J.; Befus, K. M.; Lehner, B.

2017-12-01

The interactions between groundwater and climate are important to resolve in both space and time as they influence mass and energy transfers at Earth's land surface. Despite the significance of these processes, little is known about the spatio-temporal distribution of such interactions globally, and many large-scale climate, hydrological and land surface models oversimplify groundwater or exclude it completely. In this study we bring together diverse global geomatic data sets to map spatial patterns in the sensitivity and degree of connectedness between the water table and the land surface, and use the output from a global groundwater model to assess the locations where the lateral import or export of groundwater is significant. We also quantify the groundwater response time, the characteristic time for groundwater systems to respond to a change in boundary conditions, and map its distribution globally to assess the likely dynamics of groundwater's interaction with climate. We find that more than half of the global land surface significantly exports or imports groundwater laterally. Nearly 40% of Earth's landmass has water tables that are strongly coupled to topography with water tables shallow enough to enable a bi-directional exchange of moisture with the climate system. However, only a small proportion (around 12%) of such regions have groundwater response times of 100 years or less and have groundwater fluxes that would significantly respond to rapid environmental changes over this timescale. We last explore fundamental relationships between aridity, groundwater response times and groundwater turnover times. Our results have wide ranging implications for understanding and modelling changes in Earth's water and energy balance and for informing robust future water management and security decisions.

The Tunneling Method for Global Optimization in Multidimensional Scaling.

Science.gov (United States)

Groenen, Patrick J. F.; Heiser, Willem J.

1996-01-01

A tunneling method for global minimization in multidimensional scaling is introduced and adjusted for multidimensional scaling with general Minkowski distances. The method alternates a local search step with a tunneling step in which a different configuration is sought with the same STRESS implementation. (SLD)

The GEWEX LandFlux project: evaluation of model evaporation using tower-based and globally-gridded forcing data

Science.gov (United States)

McCabe, M. F.; Ershadi, A.; Jimenez, C.; Miralles, D. G.; Michel, D.; Wood, E. F.

2015-08-01

Determining the spatial distribution and temporal development of evaporation at regional and global scales is required to improve our understanding of the coupled water and energy cycles and to better monitor any changes in observed trends and variability of linked hydrological processes. With recent international efforts guiding the development of long-term and globally distributed flux estimates, continued product assessments are required to inform upon the selection of suitable model structures and also to establish the appropriateness of these multi-model simulations for global application. In support of the objectives of the GEWEX LandFlux project, four commonly used evaporation models are evaluated against data from tower-based eddy-covariance observations, distributed across a range of biomes and climate zones. The selected schemes include the Surface Energy Balance System (SEBS) approach, the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model, the Penman-Monteith based Mu model (PM-Mu) and the Global Land Evaporation: the Amsterdam Methodology (GLEAM). Here we seek to examine the fidelity of global evaporation simulations by examining the multi-model response to varying sources of forcing data. To do this, we perform parallel and collocated model simulations using tower-based data together with a global-scale grid-based forcing product. Through quantifying the multi-model response to high-quality tower data, a better understanding of the subsequent model response to coarse-scale globally gridded data that underlies the LandFlux product can be obtained, while also providing a relative evaluation and assessment of model performance. Using surface flux observations from forty-five globally distributed eddy-covariance stations as independent metrics of performance, the tower-based analysis indicated that PT-JPL provided the highest overally statistical performance (0.72; 61 W m-2; 0.65), followed closely by GLEAM (0.68; 64 W m-2; 0.62), with values in

Combining observations and models to reduce uncertainty in the cloud response to global warming

Science.gov (United States)

Norris, J. R.; Myers, T.; Chellappan, S.

2017-12-01

Currently there is large uncertainty on how subtropical low-level clouds will respond to global warming and whether they will act as a positive feedback or negative feedback. Global climate models substantially agree on what changes in atmospheric structure and circulation will occur with global warming but greatly disagree over how clouds will respond to these changes in structure and circulation. An examination of models with the most realistic simulations of low-level cloudiness indicates that the model cloud response to atmospheric changes associated with global warming is quantitatively similar to the model cloud response to atmospheric changes at interannual time scales. For these models, the cloud response to global warming predicted by multilinear regression using coefficients derived from interannual time scales is quantitatively similar to the cloud response to global warming directly simulated by the model. Since there is a large spread among cloud response coefficients even among models with the most realistic cloud simulations, substitution of coefficients derived from satellite observations reduces the uncertainty range of the low-level cloud feedback. Increased sea surface temperature associated with global warming acts to reduce low-level cloudiness, which is partially offset by increased lower tropospheric stratification that acts to enhance low-level cloudiness. Changes in free-tropospheric relative humidity, subsidence, and horizontal advection have only a small impact on low-level cloud. The net reduction in subtropical low-level cloudiness increases absorption of solar radiation by the climate system, thus resulting in a weak positive feedback.

A Coupled fcGCM-GCE Modeling System: A 3D Cloud Resolving Model and a Regional Scale Model

Science.gov (United States)

Tao, Wei-Kuo

2005-01-01

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 ore 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 explicity 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), (3) A discussion on the Goddard WRF version (its developments and applications), and (4) The characteristics of the four-dimensional cloud data

Workshop on Human Activity at Scale in Earth System Models

Energy Technology Data Exchange (ETDEWEB)

Allen, Melissa R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Aziz, H. M. Abdul [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Coletti, Mark A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Kennedy, Joseph H. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Nair, Sujithkumar S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Omitaomu, Olufemi A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2017-01-26

Changing human activity within a geographical location may have significant influence on the global climate, but that activity must be parameterized in such a way as to allow these high-resolution sub-grid processes to affect global climate within that modeling framework. Additionally, we must have tools that provide decision support and inform local and regional policies regarding mitigation of and adaptation to climate change. The development of next-generation earth system models, that can produce actionable results with minimum uncertainties, depends on understanding global climate change and human activity interactions at policy implementation scales. Unfortunately, at best we currently have only limited schemes for relating high-resolution sectoral emissions to real-time weather, ultimately to become part of larger regions and well-mixed atmosphere. Moreover, even our understanding of meteorological processes at these scales is imperfect. This workshop addresses these shortcomings by providing a forum for discussion of what we know about these processes, what we can model, where we have gaps in these areas and how we can rise to the challenge to fill these gaps.

The GEWEX LandFlux project: evaluation of model evaporation using tower-based and globally gridded forcing data

KAUST Repository

McCabe, Matthew; Ershadi, Ali; Jimenez, C.; Miralles, Diego G.; Michel, D.; Wood, E. F.

2016-01-01

Determining the spatial distribution and temporal development of evaporation at regional and global scales is required to improve our understanding of the coupled water and energy cycles and to better monitor any changes in observed trends and variability of linked hydrological processes. With recent international efforts guiding the development of long-term and globally distributed flux estimates, continued product assessments are required to inform upon the selection of suitable model structures and also to establish the appropriateness of these multi-model simulations for global application. In support of the objectives of the Global Energy and Water Cycle Exchanges (GEWEX) LandFlux project, four commonly used evaporation models are evaluated against data from tower-based eddy-covariance observations, distributed across a range of biomes and climate zones. The selected schemes include the Surface Energy Balance System (SEBS) approach, the Priestley–Taylor Jet Propulsion Laboratory (PT-JPL) model, the Penman–Monteith-based Mu model (PM-Mu) and the Global Land Evaporation Amsterdam Model (GLEAM). Here we seek to examine the fidelity of global evaporation simulations by examining the multi-model response to varying sources of forcing data. To do this, we perform parallel and collocated model simulations using tower-based data together with a global-scale grid-based forcing product. Through quantifying the multi-model response to high-quality tower data, a better understanding of the subsequent model response to the coarse-scale globally gridded data that underlies the LandFlux product can be obtained, while also providing a relative evaluation and assessment of model performance.

Using surface flux observations from 45 globally distributed eddy-covariance stations as independent metrics of performance, the tower-based analysis indicated that PT-JPL provided the highest overall statistical performance (0.72; 61 W m⁻²; 0.65), followed

The GEWEX LandFlux project: evaluation of model evaporation using tower-based and globally gridded forcing data

KAUST Repository

McCabe, Matthew

2016-01-26

Determining the spatial distribution and temporal development of evaporation at regional and global scales is required to improve our understanding of the coupled water and energy cycles and to better monitor any changes in observed trends and variability of linked hydrological processes. With recent international efforts guiding the development of long-term and globally distributed flux estimates, continued product assessments are required to inform upon the selection of suitable model structures and also to establish the appropriateness of these multi-model simulations for global application. In support of the objectives of the Global Energy and Water Cycle Exchanges (GEWEX) LandFlux project, four commonly used evaporation models are evaluated against data from tower-based eddy-covariance observations, distributed across a range of biomes and climate zones. The selected schemes include the Surface Energy Balance System (SEBS) approach, the Priestley–Taylor Jet Propulsion Laboratory (PT-JPL) model, the Penman–Monteith-based Mu model (PM-Mu) and the Global Land Evaporation Amsterdam Model (GLEAM). Here we seek to examine the fidelity of global evaporation simulations by examining the multi-model response to varying sources of forcing data. To do this, we perform parallel and collocated model simulations using tower-based data together with a global-scale grid-based forcing product. Through quantifying the multi-model response to high-quality tower data, a better understanding of the subsequent model response to the coarse-scale globally gridded data that underlies the LandFlux product can be obtained, while also providing a relative evaluation and assessment of model performance.

Using surface flux observations from 45 globally distributed eddy-covariance stations as independent metrics of performance, the tower-based analysis indicated that PT-JPL provided the highest overall statistical performance (0.72; 61 W m⁻²; 0.65), followed

Nature of global large-scale sea level variability in relation to atmospheric forcing: A modeling study

Science.gov (United States)

Fukumori, Ichiro; Raghunath, Ramanujam; Fu, Lee-Lueng

1998-03-01

The relation between large-scale sea level variability and ocean circulation is studied using a numerical model. A global primitive equation model of the ocean is forced by daily winds and climatological heat fluxes corresponding to the period from January 1992 to January 1994. The physical nature of sea level's temporal variability from periods of days to a year is examined on the basis of spectral analyses of model results and comparisons with satellite altimetry and tide gauge measurements. The study elucidates and diagnoses the inhomogeneous physics of sea level change in space and frequency domain. At midlatitudes, large-scale sea level variability is primarily due to steric changes associated with the seasonal heating and cooling cycle of the surface layer. In comparison, changes in the tropics and high latitudes are mainly wind driven. Wind-driven variability exhibits a strong latitudinal dependence in itself. Wind-driven changes are largely baroclinic in the tropics but barotropic at higher latitudes. Baroclinic changes are dominated by the annual harmonic of the first baroclinic mode and is largest off the equator; variabilities associated with equatorial waves are smaller in comparison. Wind-driven barotropic changes exhibit a notable enhancement over several abyssal plains in the Southern Ocean, which is likely due to resonant planetary wave modes in basins semienclosed by discontinuities in potential vorticity. Otherwise, barotropic sea level changes are typically dominated by high frequencies with as much as half the total variance in periods shorter than 20 days, reflecting the frequency spectra of wind stress curl. Implications of the findings with regards to analyzing observations and data assimilation are discussed.

Terrestrial Feedbacks Incorporated in Global Vegetation Models through Observed Trait-Environment Responses

Science.gov (United States)

Bodegom, P. V.

2015-12-01

Most global vegetation models used to evaluate climate change impacts rely on plant functional types to describe vegetation responses to environmental stresses. In a traditional set-up in which vegetation characteristics are considered constant within a vegetation type, the possibility to implement and infer feedback mechanisms are limited as feedback mechanisms will likely involve a changing expression of community trait values. Based on community assembly concepts, we implemented functional trait-environment relationships into a global dynamic vegetation model to quantitatively assess this feature. For the current climate, a different global vegetation distribution was calculated with and without the inclusion of trait variation, emphasizing the importance of feedbacks -in interaction with competitive processes- for the prevailing global patterns. These trait-environmental responses do, however, not necessarily imply adaptive responses of vegetation to changing conditions and may locally lead to a faster turnover in vegetation upon climate change. Indeed, when running climate projections, simulations with trait variation did not yield a more stable or resilient vegetation than those without. Through the different feedback expressions, global and regional carbon and water fluxes were -however- strongly altered. At a global scale, model projections suggest an increased productivity and hence an increased carbon sink in the next decades to come, when including trait variation. However, by the end of the century, a reduced carbon sink is projected. This effect is due to a downregulation of photosynthesis rates, particularly in the tropical regions, even when accounting for CO2-fertilization effects. Altogether, the various global model simulations suggest the critical importance of including vegetation functional responses to changing environmental conditions to grasp terrestrial feedback mechanisms at global scales in the light of climate change.

GLEAM version 3: Global Land Evaporation Datasets and Model

Science.gov (United States)

Martens, B.; Miralles, D. G.; Lievens, H.; van der Schalie, R.; de Jeu, R.; Fernandez-Prieto, D.; Verhoest, N.

2015-12-01

Terrestrial evaporation links energy, water and carbon cycles over land and is therefore a key variable of the climate system. However, the global-scale magnitude and variability of the flux, and the sensitivity of the underlying physical process to changes in environmental factors, are still poorly understood due to limitations in in situ measurements. As a result, several methods have risen to estimate global patterns of land evaporation from satellite observations. However, these algorithms generally differ in their approach to model evaporation, resulting in large differences in their estimates. One of these methods is GLEAM, the Global Land Evaporation: the Amsterdam Methodology. GLEAM estimates terrestrial evaporation based on daily satellite observations of meteorological variables, vegetation characteristics and soil moisture. Since the publication of the first version of the algorithm (2011), the model has been widely applied to analyse trends in the water cycle and land-atmospheric feedbacks during extreme hydrometeorological events. A third version of the GLEAM global datasets is foreseen by the end of 2015. Given the relevance of having a continuous and reliable record of global-scale evaporation estimates for climate and hydrological research, the establishment of an online data portal to host these data to the public is also foreseen. In this new release of the GLEAM datasets, different components of the model have been updated, with the most significant change being the revision of the data assimilation algorithm. In this presentation, we will highlight the most important changes of the methodology and present three new GLEAM datasets and their validation against in situ observations and an alternative dataset of terrestrial evaporation (ERA-Land). Results of the validation exercise indicate that the magnitude and the spatiotemporal variability of the modelled evaporation agree reasonably well with the estimates of ERA-Land and the in situ

MEGAPOLI: concept of multi-scale modelling of megacity impact on air quality and climate

Science.gov (United States)

Baklanov, A.; Lawrence, M.; Pandis, S.; Mahura, A.; Finardi, S.; Moussiopoulos, N.; Beekmann, M.; Laj, P.; Gomes, L.; Jaffrezo, J.-L.; Borbon, A.; Coll, I.; Gros, V.; Sciare, J.; Kukkonen, J.; Galmarini, S.; Giorgi, F.; Grimmond, S.; Esau, I.; Stohl, A.; Denby, B.; Wagner, T.; Butler, T.; Baltensperger, U.; Builtjes, P.; van den Hout, D.; van der Gon, H. D.; Collins, B.; Schluenzen, H.; Kulmala, M.; Zilitinkevich, S.; Sokhi, R.; Friedrich, R.; Theloke, J.; Kummer, U.; Jalkinen, L.; Halenka, T.; Wiedensholer, A.; Pyle, J.; Rossow, W. B.

2010-11-01

The EU FP7 Project MEGAPOLI: "Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation" (http://megapoli.info) brings together leading European research groups, state-of-the-art scientific tools and key players from non-European countries to investigate the interactions among megacities, air quality and climate. MEGAPOLI bridges the spatial and temporal scales that connect local emissions, air quality and weather with global atmospheric chemistry and climate. The suggested concept of multi-scale integrated modelling of megacity impact on air quality and climate and vice versa is discussed in the paper. It requires considering different spatial and temporal dimensions: time scales from seconds and hours (to understand the interaction mechanisms) up to years and decades (to consider the climate effects); spatial resolutions: with model down- and up-scaling from street- to global-scale; and two-way interactions between meteorological and chemical processes.

Evaluation of global continental hydrology as simulated by the Land-surface Processes and eXchanges Dynamic Global Vegetation Model

Directory of Open Access Journals (Sweden)

S. J. Murray

2011-01-01

Full Text Available Global freshwater resources are sensitive to changes in climate, land cover and population density and distribution. The Land-surface Processes and eXchanges Dynamic Global Vegetation Model is a recent development of the Lund-Potsdam-Jena model with improved representation of fire-vegetation interactions. It allows simultaneous consideration of the effects of changes in climate, CO₂ concentration, natural vegetation and fire regime shifts on the continental hydrological cycle. Here the model is assessed for its ability to simulate large-scale spatial and temporal runoff patterns, in order to test its suitability for modelling future global water resources. Comparisons are made against observations of streamflow and a composite dataset of modelled and observed runoff (1986–1995 and are also evaluated against soil moisture data and the Palmer Drought Severity Index. The model captures the main features of the geographical distribution of global runoff, but tends to overestimate runoff in much of the Northern Hemisphere (where this can be somewhat accounted for by freshwater consumption and the unrealistic accumulation of the simulated winter snowpack in permafrost regions and the southern tropics. Interannual variability is represented reasonably well at the large catchment scale, as are seasonal flow timings and monthly high and low flow events. Further improvements to the simulation of intra-annual runoff might be achieved via the addition of river flow routing. Overestimates of runoff in some basins could likely be corrected by the inclusion of transmission losses and direct-channel evaporation.

Validation of A Global Hydrological Model

Science.gov (United States)

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

The Copernicus Atmosphere Monitoring Service: facilitating the prediction of air quality from global to local scales

Science.gov (United States)

Engelen, R. J.; Peuch, V. H.

2017-12-01

The European Copernicus Atmosphere Monitoring Service (CAMS) operationally provides daily forecasts of global atmospheric composition and regional air quality. The global forecasting system is using ECMWF's Integrated Forecasting System (IFS), which is used for numerical weather prediction and which has been extended with modules for atmospheric chemistry, aerosols and greenhouse gases. The regional forecasts are produced by an ensemble of seven operational European air quality models that take their boundary conditions from the global system and provide an ensemble median with ensemble spread as their main output. Both the global and regional forecasting systems are feeding their output into air quality models on a variety of scales in various parts of the world. We will introduce the CAMS service chain and provide illustrations of its use in downstream applications. Both the usage of the daily forecasts and the usage of global and regional reanalyses will be addressed.

Globalization of Brewing and Economies of Scale

DEFF Research Database (Denmark)

Madsen, Erik Strøjer; Wu, Yanqing

The globalization of the brewing industry after the turn of the century through a large wave of mergers and acquisitions has changed the structure of the world beer markets. The paper tracks the development in industry concentrations from 2002 to 2012 and points to high transportation costs...... for beers and economies of scale in advertising and sales efforts as the main factors behind the wave of cross-country mergers and acquisitions. Using firm-level data from the largest breweries, the estimations verify significant economies of scale in marketing and distribution costs. Based on information...

Global forward-predicting dynamic routing for traffic concurrency space stereo multi-layer scale-free network

International Nuclear Information System (INIS)

Xie Wei-Hao; Zhou Bin; Liu En-Xiao; Lu Wei-Dang; Zhou Ting

2015-01-01

Many real communication networks, such as oceanic monitoring network and land environment observation network, can be described as space stereo multi-layer structure, and the traffic in these networks is concurrent. Understanding how traffic dynamics depend on these real communication networks and finding an effective routing strategy that can fit the circumstance of traffic concurrency and enhance the network performance are necessary. In this light, we propose a traffic model for space stereo multi-layer complex network and introduce two kinds of global forward-predicting dynamic routing strategies, global forward-predicting hybrid minimum queue (HMQ) routing strategy and global forward-predicting hybrid minimum degree and queue (HMDQ) routing strategy, for traffic concurrency space stereo multi-layer scale-free networks. By applying forward-predicting strategy, the proposed routing strategies achieve better performances in traffic concurrency space stereo multi-layer scale-free networks. Compared with the efficient routing strategy and global dynamic routing strategy, HMDQ and HMQ routing strategies can optimize the traffic distribution, alleviate the number of congested packets effectively and reach much higher network capacity. (paper)

The GEWEX LandFlux project: evaluation of model evaporation using tower-based and globally-gridded forcing data

KAUST Repository

McCabe, Matthew

2015-08-24

Determining the spatial distribution and temporal development of evaporation at regional and global scales is required to improve our understanding of the coupled water and energy cycles and to better monitor any changes in observed trends and variability of linked hydrological processes. With recent international efforts guiding the development of long-term and globally distributed flux estimates, continued product assessments are required to inform upon the selection of suitable model structures and also to establish the appropriateness of these multi-model simulations for global application. In support of the objectives of the GEWEX LandFlux project, four commonly used evaporation models are evaluated against data from tower-based eddy-covariance observations, distributed across a range of biomes and climate zones. The selected schemes include the Surface Energy Balance System (SEBS) approach, the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model, the Penman-Monteith based Mu model (PM-Mu) and the Global Land Evaporation: the Amsterdam Methodology (GLEAM). Here we seek to examine the fidelity of global evaporation simulations by examining the multi-model response to varying sources of forcing data. To do this, we perform parallel and collocated model simulations using tower-based data together with a global-scale grid-based forcing product. Through quantifying the multi-model response to high-quality tower data, a better understanding of the subsequent model response to coarse-scale globally gridded data that underlies the LandFlux product can be obtained, while also providing a relative evaluation and assessment of model performance.

Using surface flux observations from forty-five globally distributed eddy-covariance stations as independent metrics of performance, the tower-based analysis indicated that PT-JPL provided the highest overally statistical performance (0.72; 61 W m⁻²; 0.65), followed closely by GLEAM (0.68; 64 W m

Interannual Variation in Phytoplankton Class-Specific Primary Production at a Global Scale

Science.gov (United States)

Rousseaux, Cecile Severine; Gregg, Watson W.

2014-01-01

We used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of 4 phytoplankton groups to the total primary production. First we assessed the contribution of each phytoplankton groups to the total primary production at a global scale for the period 1998-2011. Globally, diatoms were the group that contributed the most to the total phytoplankton production (50, the equivalent of 20 PgC y-1. Coccolithophores and chlorophytes each contributed to 20 (7 PgC y-1 of the total primary production and cyanobacteria represented about 10 (4 PgC y(sub-1) of the total primary production. Primary production by diatoms was highest in high latitude (45) and in major upwelling systems (Equatorial Pacific and Benguela system). We then assessed interannual variability of this group-specific primary production over the period 1998-2011. Globally the annual relative contribution of each phytoplankton groups to the total primary production varied by maximum 4 (1-2 PgC y-1. We assessed the effects of climate variability on the class-specific primary production using global (i.e. Multivariate El Nio Index, MEI) and regional climate indices (e.g. Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability as indicated by significant correlation (p 0.05) between the MEI and the class-specific primary production from all groups except coccolithophores. In the Atlantic, climate variability as indicated by NAO was significantly correlated to the primary production of 2 out of the 4 groups in the North Central Atlantic (diatomscyanobacteria) and in the North Atlantic (chlorophytes and coccolithophores). We found that climate variability as indicated by SAM had only a limited effect on the class-specific primary production in the Southern Ocean. These results provide a modeling and

Numerical Simulation of Hydrogen Combustion: Global Reaction Model and Validation

Energy Technology Data Exchange (ETDEWEB)

Zhang, Yun [School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an (China); Department of Mechanical, Aerospace and Nuclear Engineering, Rensselaer Polytechnic Institute, Troy, NY (United States); Liu, Yinhe, E-mail: yinheliu@mail.xjtu.edu.cn [School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an (China)

2017-11-20

Due to the complexity of modeling the combustion process in nuclear power plants, the global mechanisms are preferred for numerical simulation. To quickly perform the highly resolved simulations with limited processing resources of large-scale hydrogen combustion, a method based on thermal theory was developed to obtain kinetic parameters of global reaction mechanism of hydrogen–air combustion in a wide range. The calculated kinetic parameters at lower hydrogen concentration (C{sub hydrogen} < 20%) were validated against the results obtained from experimental measurements in a container and combustion test facility. In addition, the numerical data by the global mechanism (C{sub hydrogen} > 20%) were compared with the results by detailed mechanism. Good agreement between the model prediction and the experimental data was achieved, and the comparison between simulation results by the detailed mechanism and the global reaction mechanism show that the present calculated global mechanism has excellent predictable capabilities for a wide range of hydrogen–air mixtures.

Numerical Simulation of Hydrogen Combustion: Global Reaction Model and Validation

International Nuclear Information System (INIS)

Zhang, Yun; Liu, Yinhe

2017-01-01

Due to the complexity of modeling the combustion process in nuclear power plants, the global mechanisms are preferred for numerical simulation. To quickly perform the highly resolved simulations with limited processing resources of large-scale hydrogen combustion, a method based on thermal theory was developed to obtain kinetic parameters of global reaction mechanism of hydrogen–air combustion in a wide range. The calculated kinetic parameters at lower hydrogen concentration (C hydrogen < 20%) were validated against the results obtained from experimental measurements in a container and combustion test facility. In addition, the numerical data by the global mechanism (C hydrogen > 20%) were compared with the results by detailed mechanism. Good agreement between the model prediction and the experimental data was achieved, and the comparison between simulation results by the detailed mechanism and the global reaction mechanism show that the present calculated global mechanism has excellent predictable capabilities for a wide range of hydrogen–air mixtures.

Hydrologic Derivatives for Modeling and Analysis—A new global high-resolution database

Science.gov (United States)

Verdin, Kristine L.

2017-07-17

The U.S. Geological Survey has developed a new global high-resolution hydrologic derivative database. Loosely modeled on the HYDRO1k database, this new database, entitled Hydrologic Derivatives for Modeling and Analysis, provides comprehensive and consistent global coverage of topographically derived raster layers (digital elevation model data, flow direction, flow accumulation, slope, and compound topographic index) and vector layers (streams and catchment boundaries). The coverage of the data is global, and the underlying digital elevation model is a hybrid of three datasets: HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales), GMTED2010 (Global Multi-resolution Terrain Elevation Data 2010), and the SRTM (Shuttle Radar Topography Mission). For most of the globe south of 60°N., the raster resolution of the data is 3 arc-seconds, corresponding to the resolution of the SRTM. For the areas north of 60°N., the resolution is 7.5 arc-seconds (the highest resolution of the GMTED2010 dataset) except for Greenland, where the resolution is 30 arc-seconds. The streams and catchments are attributed with Pfafstetter codes, based on a hierarchical numbering system, that carry important topological information. This database is appropriate for use in continental-scale modeling efforts. The work described in this report was conducted by the U.S. Geological Survey in cooperation with the National Aeronautics and Space Administration Goddard Space Flight Center.

Globally covering a-priori regional gravity covariance models

Directory of Open Access Journals (Sweden)

D. Arabelos

2003-01-01

Full Text Available Gravity anomaly data generated using Wenzel’s GPM98A model complete to degree 1800, from which OSU91A has been subtracted, have been used to estimate covariance functions for a set of globally covering equal-area blocks of size 22.5° × 22.5° at Equator, having a 2.5° overlap. For each block an analytic covariance function model was determined. The models are based on 4 parameters: the depth to the Bjerhammar sphere (determines correlation, the free-air gravity anomaly variance, a scale factor of the OSU91A error degree-variances and a maximal summation index, N, of the error degree-variances. The depth of Bjerhammar-sphere varies from -134km to nearly zero, N varies from 360 to 40, the scale factor from 0.03 to 38.0 and the gravity variance from 1081 to 24(10µms-22. The parameters are interpreted in terms of the quality of the data used to construct OSU91A and GPM98A and general conditions such as the occurrence of mountain chains. The variation of the parameters show that it is necessary to use regional covariance models in order to obtain a realistic signal to noise ratio in global applications.Key words. GOCE mission, Covariance function, Spacewise approach`

Global and local level density models

International Nuclear Information System (INIS)

Koning, A.J.; Hilaire, S.; Goriely, S.

2008-01-01

Four different level density models, three phenomenological and one microscopic, are consistently parameterized using the same set of experimental observables. For each of the phenomenological models, the Constant Temperature Model, the Back-shifted Fermi gas Model and the Generalized Superfluid Model, a version without and with explicit collective enhancement is considered. Moreover, a recently published microscopic combinatorial model is compared with the phenomenological approaches and with the same set of experimental data. For each nuclide for which sufficient experimental data exists, a local level density parameterization is constructed for each model. Next, these local models have helped to construct global level density prescriptions, to be used for cases for which no experimental data exists. Altogether, this yields a collection of level density formulae and parameters that can be used with confidence in nuclear model calculations. To demonstrate this, a large-scale validation with experimental discrete level schemes and experimental cross sections and neutron emission spectra for various different reaction channels has been performed

Looking back to move forward on model validation: insights from a global model of agricultural land use

International Nuclear Information System (INIS)

Baldos, Uris Lantz C; Hertel, Thomas W

2013-01-01

Global agricultural models are becoming indispensable in the debate over climate change impacts and mitigation policies. Therefore, it is becoming increasingly important to validate these models and identify critical areas for improvement. In this letter, we illustrate both the opportunities and the challenges in undertaking such model validation, using the SIMPLE model of global agriculture. We look back at the long run historical period 1961–2006 and, using a few key historical drivers—population, incomes and total factor productivity—we find that SIMPLE is able to accurately reproduce historical changes in cropland use, crop price, crop production and average crop yields at the global scale. Equally important is our investigation into how the specific assumptions embedded in many agricultural models will likely influence these results. We find that those global models which are largely biophysical—thereby ignoring the price responsiveness of demand and supply—are likely to understate changes in crop production, while failing to capture the changes in cropland use and crop price. Likewise, global models which incorporate economic responses, but do so based on limited time series estimates of these responses, are likely to understate land use change and overstate price changes. (letter)

Improved data for integrated modeling of global environmental change

Science.gov (United States)

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

Transforming Global Health by Improving the Science of Scale-Up.

Directory of Open Access Journals (Sweden)

Margaret E Kruk

2016-03-01

Full Text Available In its report Global Health 2035, the Commission on Investing in Health proposed that health investments can reduce mortality in nearly all low- and middle-income countries to very low levels, thereby averting 10 million deaths per year from 2035 onward. Many of these gains could be achieved through scale-up of existing technologies and health services. A key instrument to close this gap is policy and implementation research (PIR that aims to produce generalizable evidence on what works to implement successful interventions at scale. Rigorously designed PIR promotes global learning and local accountability. Much greater national and global investments in PIR capacity will be required to enable the scaling of effective approaches and to prevent the recycling of failed ideas. Sample questions for the PIR research agenda include how to close the gap in the delivery of essential services to the poor, which population interventions for non-communicable diseases are most applicable in different contexts, and how to engage non-state actors in equitable provision of health services in the context of universal health coverage.

What can('t) we do with global flood risk models?

Science.gov (United States)

Ward, Philip; Jongman, Brenden; Salamon, Peter; Simpson, Alanna; Winsemius, Hessel

2015-04-01

In recent years, several global scale flood risk models have become available. Within the scientific community these have been, and are being, used to assess and map the current levels of risk faced by countries and societies. Increasingly, they are also being used to assess how that level of risk may change in the future, under scenarios of climate change and/or socioeconomic development. More and more, these 'quick and not so dirty' methods are also being used in practice, for a large range of uses and applications, and by an increasing range of practitioners and decision makers. For example, assessments can be used by: International Financing Institutes for prioritising investments in the most promising natural disaster risk reduction measures and strategies; intra-national institutes in the monitoring of progress on risk reduction activities; the (re-)insurance industry in assessing their risk portfolios and potential changes in those portfolios under climate change; by multinational companies in assessing risks to their regional investments and supply chains; and by international aid organisations for improved resource planning. However, global scale flood risk models clearly have their limits, and therefore both modellers and users need to critically address the question 'What can('t) we do with global flood risk models?'. This contribution is intended to start a dialogue between model developers, users, and decision makers to better answer this question. We will provide a number of examples of how the GLOFRIS global flood risk model has recently been used in several practical applications, and share both the positive and negative insights gained through these experiences. We wish to discuss similar experiences with other groups of modelers, users, and decision-makers, in order to better understand and harness the potential of this new generation of models, understand the differences in model approaches followed and their impacts on applicability, and develop

Moduli stabilisation for chiral global models

International Nuclear Information System (INIS)

Cicoli, Michele; Mayrhofer, Christoph; Valandro, Roberto

2011-10-01

We combine moduli stabilisation and (chiral) model building in a fully consistent global set-up in Type IIB/F-theory. We consider compactifications on Calabi-Yau orientifolds which admit an explicit description in terms of toric geometry. We build globally consistent compactifications with tadpole and Freed-Witten anomaly cancellation by choosing appropriate brane set-ups and world-volume fluxes which also give rise to SU(5)- or MSSM-like chiral models. We fix all the Kaehler moduli within the Kaehler cone and the regime of validity of the 4D effective field theory. This is achieved in a way compatible with the local presence of chirality. The hidden sector generating the non-perturbative effects is placed on a del Pezzo divisor that does not have any chiral intersections with any other brane. In general, the vanishing D-term condition implies the shrinking of the rigid divisor supporting the visible sector. However, we avoid this problem by generating r< n D-term conditions on a set of n intersecting divisors. The remaining (n-r) flat directions are fixed by perturbative corrections to the Kaehler potential. We illustrate our general claims in an explicit example. We consider a K3-fibred Calabi-Yau with four Kaehler moduli, that is an hypersurface in a toric ambient space and admits a simple F-theory up-lift. We present explicit choices of brane set-ups and fluxes which lead to three different phenomenological scenarios: the first with GUT-scale strings and TeV-scale SUSY by fine-tuning the background fluxes; the second with an exponentially large value of the volume and TeV-scale SUSY without fine-tuning the background fluxes; and the third with a very anisotropic configuration that leads to TeV-scale strings and two micron-sized extra dimensions. The K3 fibration structure of the Calabi-Yau three-fold is also particularly suitable for cosmological purposes. (orig.)

Moduli stabilisation for chiral global models

Energy Technology Data Exchange (ETDEWEB)

Cicoli, Michele [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Abdus Salam International Centre for Theoretical Physics, Trieste (Italy); Mayrhofer, Christoph [Heidelberg Univ. (Germany). Inst. fuer Theoretische Physik; Valandro, Roberto [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik

2011-10-15

We combine moduli stabilisation and (chiral) model building in a fully consistent global set-up in Type IIB/F-theory. We consider compactifications on Calabi-Yau orientifolds which admit an explicit description in terms of toric geometry. We build globally consistent compactifications with tadpole and Freed-Witten anomaly cancellation by choosing appropriate brane set-ups and world-volume fluxes which also give rise to SU(5)- or MSSM-like chiral models. We fix all the Kaehler moduli within the Kaehler cone and the regime of validity of the 4D effective field theory. This is achieved in a way compatible with the local presence of chirality. The hidden sector generating the non-perturbative effects is placed on a del Pezzo divisor that does not have any chiral intersections with any other brane. In general, the vanishing D-term condition implies the shrinking of the rigid divisor supporting the visible sector. However, we avoid this problem by generating rscale strings and TeV-scale SUSY by fine-tuning the background fluxes; the second with an exponentially large value of the volume and TeV-scale SUSY without fine-tuning the background fluxes; and the third with a very anisotropic configuration that leads to TeV-scale strings and two micron-sized extra dimensions. The K3 fibration structure of the Calabi-Yau three-fold is also particularly suitable for cosmological purposes. (orig.)

Global and local confinement scaling laws of NBI-heated gas-puffing plasmas on LHD

International Nuclear Information System (INIS)

Yamazaki, K.; Miyazawa, J.; Sakakibara, S.; Yamada, H.; Narihara, K.; Tanaka, K.; Osakabe, M.

2003-01-01

The relation between global confinement scaling laws and local transport characteristics is evaluated on the Large Helical Device (LHD). Previous 'new LHD' global scaling laws are revised using the precise plasma edge definition and the recent LHD data of 4th, 5th and 6th experimental campaigns. Strong Gyro-Bohm-like feature of global confinement is reconfirmed. The magnetic field dependence and geometrical scale dependence are stronger than the conventional scaling laws. Using same database of LHD data, the radial profiles of transport coefficients are evaluated, and it is reconfirmed that the local transport in the core is Gyro-Bohm-like, and that near the boundary is strong Gyro-Bohm-like. The global confinement property is consistent with effective transport coefficient near the edge. (author)

Leaf optical properties shed light on foliar trait variability at individual to global scales

Science.gov (United States)

Shiklomanov, A. N.; Serbin, S.; Dietze, M.

2017-12-01

Recent syntheses of large trait databases have contributed immensely to our understanding of drivers of plant function at the global scale. However, the global trade-offs revealed by such syntheses, such as the trade-off between leaf productivity and resilience (i.e. "leaf economics spectrum"), are often absent at smaller scales and fail to correlate with actual functional limitations. An improved understanding of how traits vary among communities, species, and individuals is critical to accurate representations of vegetation ecophysiology and ecological dynamics in ecosystem models. Spectral data from both field observations and remote sensing platforms present a rich and widely available source of information on plant traits. Here, we apply Bayesian inversion of the PROSPECT leaf radiative transfer model to a large global database of over 60,000 field spectra and plant traits to (1) comprehensively assess the accuracy of leaf trait estimation using PROSPECT spectral inversion; (2) investigate the correlations between optical traits estimable from PROSPECT and other important foliar traits such as nitrogen and lignin concentrations; and (3) identify dominant sources of variability and characterize trade-offs in optical and non-optical foliar traits. Our work provides a key methodological contribution by validating physically-based retrieval of plant traits from remote sensing observations, and provides insights about trait trade-offs related to plant acclimation, adaptation, and community assembly.

Modelling the Evolution of Sea Spray Droplets on a Global Scale

Science.gov (United States)

Staniec, A.; Vlahos, P.; Monahan, E. C.

2017-12-01

Sea spray droplets are an important mechanism for the transport of moisture, heat, and organic material between the ocean and the atmosphere. Spume droplets are the largest of the size spectrum and as such have the potential to transport significant amounts of energy and gases despite their generally short residence time in the atmosphere. A model is developed based on the physical parameterizations from Andreas et al. (1995, 2005)and a range of spume generation functions, coupled with a biogeochemical exchange model for gases developed here to examine the equilibrium temperature and gas exchange of spume droplets under representative open ocean conditions. The modelling approach uses micro-physics to simulate the expected changes to the droplet as it equilibrates with the atmospheric temperature and relative humidity. The effect of temperature differentials and relative humidity variations is explored. A global approach is simulated by using average summer and winter values for SST, salinity, and air temperature throughout the various ocean basins.

Modeling global scene factors in attention

Science.gov (United States)

Torralba, Antonio

2003-07-01

Models of visual attention have focused predominantly on bottom-up approaches that ignored structured contextual and scene information. I propose a model of contextual cueing for attention guidance based on the global scene configuration. It is shown that the statistics of low-level features across the whole image can be used to prime the presence or absence of objects in the scene and to predict their location, scale, and appearance before exploring the image. In this scheme, visual context information can become available early in the visual processing chain, which allows modulation of the saliency of image regions and provides an efficient shortcut for object detection and recognition. 2003 Optical Society of America

Large-scale groundwater modeling using global datasets: a test case for the Rhine-Meuse basin

NARCIS (Netherlands)

Sutanudjaja, E.H.; Beek, L.P.H. van; Jong, S.M. de; Geer, F.C. van; Bierkens, M.F.P.

2011-01-01

The current generation of large-scale hydrological models does not include a groundwater flow component. Large-scale groundwater models, involving aquifers and basins of multiple countries, are still rare mainly due to a lack of hydro-geological data which are usually only available in

Large-scale groundwater modeling using global datasets: A test case for the Rhine-Meuse basin

NARCIS (Netherlands)

Sutanudjaja, E.H.; Beek, L.P.H. van; Jong, S.M. de; Geer, F.C. van; Bierkens, M.F.P.

2011-01-01

The current generation of large-scale hydrological models does not include a groundwater flow component. Large-scale groundwater models, involving aquifers and basins of multiple countries, are still rare mainly due to a lack of hydro-geological data which are usually only available in developed

The community Noah land surface model with multiparameterization options (Noah-MP): 2. Evaluation over global river basins

KAUST Repository

Yang, Zong-Liang; Niu, Guo-Yue; Mitchell, Kenneth E.; Chen, Fei; Ek, Michael B.; Barlage, Michael; Longuevergne, Laurent; Manning, Kevin; Niyogi, Dev; Tewari, Mukul; Xia, Youlong

2011-01-01

The augmented Noah land surface model described in the first part of the two-part series was evaluated here over global river basins. Across various climate zones, global-scale tests can reveal a model's weaknesses and strengths that a local

Urban ecosystem modeling and global change: Potential for rational urban management and emissions mitigation

International Nuclear Information System (INIS)

Chen, Shaoqing; Chen, Bin; Fath, Brian D.

2014-01-01

Urbanization is a strong and extensive driver that causes environmental pollution and climate change from local to global scale. Modeling cities as ecosystems has been initiated by a wide range of scientists as a key to addressing challenging problems concomitant with urbanization. In this paper, ‘urban ecosystem modeling (UEM)’ is defined in an inter-disciplinary context to acquire a broad perception of urban ecological properties and their interactions with global change. Furthermore, state-of-the-art models of urban ecosystems are reviewed, categorized as top-down models (including materials/energy-oriented models and structure-oriented models), bottom-up models (including land use-oriented models and infrastructure-oriented models), or hybrid models thereof. Based on the review of UEM studies, a future framework for explicit UEM is proposed based the integration of UEM approaches of different scales, guiding more rational urban management and efficient emissions mitigation. - Highlights: • Urban ecosystems modeling (UEM) is defined in an interdisciplinary context. • State-of-the-art models for UEM are critically reviewed and compared. • An integrated framework for explicit UEM is proposed under global change. - State-of-the-art models of urban ecosystem modeling (UEM) are reviewed for rational urban management and emissions mitigation

Development OF A Multi-Scale Framework for Mapping Global Evapotranspiration

Science.gov (United States)

Hain, Christopher R.; Anderson, Martha C.; Schull, Mitchell; Neale, Christopher; Zhan, Xiwu

2017-01-01

As the worlds water resources come under increasing tension due to dual stressors of climate change and population growth, accurate knowledge of water consumption through evapotranspiration (ET) over a range in spatial scales will be critical in developing adaptation strategies. Remote sensing methods for monitoring consumptive water use (e.g, ET) are becoming increasingly important, especially in areas of significant water and food insecurity. One method to estimate ET from satellite-based methods, the Atmosphere Land Exchange Inverse (ALEXI) model uses the change in mid-morning land surface temperature to estimate the partitioning of sensible and latent heat fluxes which are then used to estimate daily ET. This presentation will outline several recent enhancements to the ALEXI modeling system, with a focus on global ET and drought monitoring.

Scale-dependent performances of CMIP5 earth system models in simulating terrestrial vegetation carbon

Science.gov (United States)

Jiang, L.; Luo, Y.; Yan, Y.; Hararuk, O.

2013-12-01

Mitigation of global changes will depend on reliable projection for the future situation. As the major tools to predict future climate, Earth System Models (ESMs) used in Coupled Model Intercomparison Project Phase 5 (CMIP5) for the IPCC Fifth Assessment Report have incorporated carbon cycle components, which account for the important fluxes of carbon between the ocean, atmosphere, and terrestrial biosphere carbon reservoirs; and therefore are expected to provide more detailed and more certain projections. However, ESMs are never perfect; and evaluating the ESMs can help us to identify uncertainties in prediction and give the priorities for model development. In this study, we benchmarked carbon in live vegetation in the terrestrial ecosystems simulated by 19 ESMs models from CMIP5 with an observationally estimated data set of global carbon vegetation pool 'Olson's Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation: An Updated Database Using the GLC2000 Land Cover Product' by Gibbs (2006). Our aim is to evaluate the ability of ESMs to reproduce the global vegetation carbon pool at different scales and what are the possible causes for the bias. We found that the performance CMIP5 ESMs is very scale-dependent. While CESM1-BGC, CESM1-CAM5, CESM1-FASTCHEM and CESM1-WACCM, and NorESM1-M and NorESM1-ME (they share the same model structure) have very similar global sums with the observation data but they usually perform poorly at grid cell and biome scale. In contrast, MIROC-ESM and MIROC-ESM-CHEM simulate the best on at grid cell and biome scale but have larger differences in global sums than others. Our results will help improve CMIP5 ESMs for more reliable prediction.

Scaling future tropical cyclone damage with global mean temperature

Science.gov (United States)

Geiger, T.; Bresch, D.; Frieler, K.

2017-12-01

Tropical cyclones (TC) are one of the most damaging natural hazards and severely affectmany countries around the globe each year. Their nominal impact is projected to increasesubstantially as the exposed coastal population grows, per capita income increases, andanthropogenic climate change manifests. The magnitude of this increase, however, variesacross regions and is obscured by the stochastic behaviour of TCs, so far impeding arigorous quantification of trends in TC damage with global mean temperature (GMT) rise. Here, we build on the large sample of spatially explicit TCs simulations generated withinISIMIP(2b) for 1) pre-industrial conditions, 2) the historical period, and 3) future projectionsunder RCP2.6 and RCP6.0 to estimate future TC damage assuming fixed present-daysocio-economic conditions or SSP-based future projections of population patterns andincome. Damage estimates will be based on region-specific empirical damage modelsderived from reported damages and accounting for regional characteristics of vulnerability.Different combinations of 1) socio-economic drivers with pre-industrial climate or 2) changingclimate with fixed socio-economic conditions will be used to derive functional relationshipsbetween regionally aggregated changes in damages on one hand and global meantemperature and socio-economic predictors on the other hand. The obtained region-specific scaling of future TC damage with GMT provides valuable inputfor IPCC's special report on the impacts of global warming of 1.5°C by quantifying theincremental changes in impact with global warming. The approach allows for an update ofdamage functions used in integrated assessment models, and contributes to assessing theadequateness of climate mitigation and adaptation strategies.

Introduction to the Special Issue: Across the horizon: scale effects in global change research.

Science.gov (United States)

Gornish, Elise S; Leuzinger, Sebastian

2015-01-01

As a result of the increasing speed and magnitude in which habitats worldwide are experiencing environmental change, making accurate predictions of the effects of global change on ecosystems and the organisms that inhabit them have become an important goal for ecologists. Experimental and modelling approaches aimed at understanding the linkages between factors of global change and biotic responses have become numerous and increasingly complex in order to adequately capture the multifarious dynamics associated with these relationships. However, constrained by resources, experiments are often conducted at small spatiotemporal scales (e.g. looking at a plot of a few square metres over a few years) and at low organizational levels (looking at organisms rather than ecosystems) in spite of both theoretical and experimental work that suggests ecological dynamics across scales can be dissimilar. This phenomenon has been hypothesized to occur because the mechanisms that drive dynamics across scales differ. A good example is the effect of elevated CO2 on transpiration. While at the leaf level, transpiration can be reduced, at the stand level, transpiration can increase because leaf area per unit ground area increases. The reported net effect is then highly dependent on the spatiotemporal scale. This special issue considers the biological relevancy inherent in the patterns associated with the magnitude and type of response to changing environmental conditions, across scales. This collection of papers attempts to provide a comprehensive treatment of this phenomenon in order to help develop an understanding of the extent of, and mechanisms involved with, ecological response to global change. Published by Oxford University Press on behalf of the Annals of Botany Company.

Large-scale hydrological modeling for calculating water stress indices: implications of improved spatiotemporal resolution, surface-groundwater differentiation, and uncertainty characterization.

Science.gov (United States)

Scherer, Laura; Venkatesh, Aranya; Karuppiah, Ramkumar; Pfister, Stephan

2015-04-21

Physical water scarcities can be described by water stress indices. These are often determined at an annual scale and a watershed level; however, such scales mask seasonal fluctuations and spatial heterogeneity within a watershed. In order to account for this level of detail, first and foremost, water availability estimates must be improved and refined. State-of-the-art global hydrological models such as WaterGAP and UNH/GRDC have previously been unable to reliably reflect water availability at the subbasin scale. In this study, the Soil and Water Assessment Tool (SWAT) was tested as an alternative to global models, using the case study of the Mississippi watershed. While SWAT clearly outperformed the global models at the scale of a large watershed, it was judged to be unsuitable for global scale simulations due to the high calibration efforts required. The results obtained in this study show that global assessments miss out on key aspects related to upstream/downstream relations and monthly fluctuations, which are important both for the characterization of water scarcity in the Mississippi watershed and for water footprints. Especially in arid regions, where scarcity is high, these models provide unsatisfying results.

Global characteristics of geomagnetic excursions as seen in global empirical models and a numerical geodynamo simulation

Science.gov (United States)

Korte, M. C.; Wardinski, I.; Brown, M. C.

2016-12-01

Paleomagnetic results from sediments and lava flows provide observational evidence of numerous geomagnetic excursions throughout Earth's history. Two new spherical harmonic geomagnetic field models covering 50-30 ka, including the Laschamp ( 41ka) and Mono Lake ( 32-35 ka) excursions allow us to characterize the global behaviour of these events, both at Earth's surface and the core-mantle boundary. We investigate the evolution of dipole and large-scale non-dipole power throughout the duration of the model and the morphology of the large-scale radial field at the core-mantle boundary. The models suggest clear differences in both the decrease in axial dipole strength and dipole tilt between the two excursions and unlike the previously published model by Leonhardt et al. (2009), they suggest some increase of non-dipole power during the early and late stages of the Laschamp excursion. Global characteristics from the models can be directly compared with results from numerical simulations. We do so for several excursions generated by a numerical simulation driven by purely compositional convection, which appears Earth-like in terms of excursion and reversal occurrence frequency. Excursions from this simulation show differing characteristics, including differences in spectral power evolution. Some cases show similarities to the Laschamp and Mono Lake excursions in the spherical harmonic models. In particular they all indicate that excursions are mainly governed by the axial dipole term and equatorial dipole terms play a minor role.

Quantification of effective plant rooting depth: advancing global hydrological modelling

Science.gov (United States)

Yang, Y.; Donohue, R. J.; McVicar, T.

2017-12-01

Plant rooting depth (Zr) is a key parameter in hydrological and biogeochemical models, yet the global spatial distribution of Zr is largely unknown due to the difficulties in its direct measurement. Moreover, Zr observations are usually only representative of a single plant or several plants, which can differ greatly from the effective Zr over a modelling unit (e.g., catchment or grid-box). Here, we provide a global parameterization of an analytical Zr model that balances the marginal carbon cost and benefit of deeper roots, and produce a climatological (i.e., 1982-2010 average) global Zr map. To test the Zr estimates, we apply the estimated Zr in a highly transparent hydrological model (i.e., the Budyko-Choudhury-Porporato (BCP) model) to estimate mean annual actual evapotranspiration (E) across the globe. We then compare the estimated E with both water balance-based E observations at 32 major catchments and satellite grid-box retrievals across the globe. Our results show that the BCP model, when implemented with Zr estimated herein, optimally reproduced the spatial pattern of E at both scales and provides improved model outputs when compared to BCP model results from two already existing global Zr datasets. These results suggest that our Zr estimates can be effectively used in state-of-the-art hydrological models, and potentially biogeochemical models, where the determination of Zr currently largely relies on biome type-based look-up tables.

Classically scale-invariant B–L model and conformal gravity

International Nuclear Information System (INIS)

Oda, Ichiro

2013-01-01

We consider a coupling of conformal gravity to the classically scale-invariant B–L extended standard model which has been recently proposed as a phenomenologically viable model realizing the Coleman–Weinberg mechanism of breakdown of the electroweak symmetry. As in a globally scale-invariant dilaton gravity, it is also shown in a locally scale-invariant conformal gravity that without recourse to the Coleman–Weinberg mechanism, the B–L gauge symmetry is broken in the process of spontaneous symmetry breakdown of the local scale invariance (Weyl invariance) at the tree level and as a result the B–L gauge field becomes massive via the Higgs mechanism. As a bonus of conformal gravity, the massless dilaton field does not appear and the parameters in front of the non-minimal coupling of gravity are completely fixed in the present model. This observation clearly shows that the conformal gravity has a practical application even if the scalar field does not possess any dynamical degree of freedom owing to the local scale symmetry

Clouds in ECMWF's 30 KM Resolution Global Atmospheric Forecast Model (TL639)

Science.gov (United States)

Cahalan, R. F.; Morcrette, J. J.

1999-01-01

Global models of the general circulation of the atmosphere resolve a wide range of length scales, and in particular cloud structures extend from planetary scales to the smallest scales resolvable, now down to 30 km in state-of-the-art models. Even the highest resolution models do not resolve small-scale cloud phenomena seen, for example, in Landsat and other high-resolution satellite images of clouds. Unresolved small-scale disturbances often grow into larger ones through non-linear processes that transfer energy upscale. Understanding upscale cascades is of crucial importance in predicting current weather, and in parameterizing cloud-radiative processes that control long term climate. Several movie animations provide examples of the temporal and spatial variation of cloud fields produced in 4-day runs of the forecast model at the European Centre for Medium-Range Weather Forecasts (ECMWF) in Reading, England, at particular times and locations of simultaneous measurement field campaigns. model resolution is approximately 30 km horizontally (triangular truncation TL639) with 31 vertical levels from surface to stratosphere. Timestep of the model is about 10 minutes, but animation frames are 3 hours apart, at timesteps when the radiation is computed. The animations were prepared from an archive of several 4-day runs at the highest available model resolution, and archived at ECMWF. Cloud, wind and temperature fields in an approximately 1000 km X 1000 km box were retrieved from the archive, then approximately 60 Mb Vis5d files were prepared with the help of Graeme Kelly of ECMWF, and were compressed into MPEG files each less than 3 Mb. We discuss the interaction of clouds and radiation in the model, and compare the variability of cloud liquid as a function of scale to that seen in cloud observations made in intensive field campaigns. Comparison of high-resolution global runs to cloud-resolving models, and to lower resolution climate models is leading to better

Global Delivery Models

DEFF Research Database (Denmark)

Manning, Stephan; Larsen, Marcus M.; Bharati, Pratyush

2013-01-01

This article examines antecedents and performance implications of global delivery models (GDMs) in global business services. GDMs require geographically distributed operations to exploit both proximity to clients and time-zone spread for efficient service delivery. We propose and empirically show...

Irrational Delay Revisited: Examining Five Procrastination Scales in a Global Sample

OpenAIRE

Frode Svartdal; Piers Steel

2017-01-01

Source at http://dx.doi.org/10.3389/fpsyg.2017.01927 Scales attempting to measure procrastination focus on different facets of the phenomenon, yet they share a common understanding of procrastination as an unnecessary, unwanted, and disadvantageous delay. The present paper examines in a global sample (N = 4,169) five different procrastination scales – Decisional Procrastination Scale (DPS), Irrational Procrastination Scale (IPS), Pure Procrastination Scale (PPS), Adult Inventory of Procr...

Global modeling of withdrawal, allocation and consumptive use of surface water and groundwater resources

NARCIS (Netherlands)

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

Disinformative data in large-scale hydrological modelling

Directory of Open Access Journals (Sweden)

A. Kauffeldt

2013-07-01

Full Text Available Large-scale hydrological modelling has become an important tool for the study of global and regional water resources, climate impacts, and water-resources management. However, modelling efforts over large spatial domains are fraught with problems of data scarcity, uncertainties and inconsistencies between model forcing and evaluation data. Model-independent methods to screen and analyse data for such problems are needed. This study aimed at identifying data inconsistencies in global datasets using a pre-modelling analysis, inconsistencies that can be disinformative for subsequent modelling. The consistency between (i basin areas for different hydrographic datasets, and (ii between climate data (precipitation and potential evaporation and discharge data, was examined in terms of how well basin areas were represented in the flow networks and the possibility of water-balance closure. It was found that (i most basins could be well represented in both gridded basin delineations and polygon-based ones, but some basins exhibited large area discrepancies between flow-network datasets and archived basin areas, (ii basins exhibiting too-high runoff coefficients were abundant in areas where precipitation data were likely affected by snow undercatch, and (iii the occurrence of basins exhibiting losses exceeding the potential-evaporation limit was strongly dependent on the potential-evaporation data, both in terms of numbers and geographical distribution. Some inconsistencies may be resolved by considering sub-grid variability in climate data, surface-dependent potential-evaporation estimates, etc., but further studies are needed to determine the reasons for the inconsistencies found. Our results emphasise the need for pre-modelling data analysis to identify dataset inconsistencies as an important first step in any large-scale study. Applying data-screening methods before modelling should also increase our chances to draw robust conclusions from subsequent

A One-Dimensional Global-Scaling Erosive Burning Model Informed by Blowing Wall Turbulence

Science.gov (United States)

Kibbey, Timothy P.

2014-01-01

A derivation of turbulent flow parameters, combined with data from erosive burning test motors and blowing wall tests results in erosive burning model candidates useful in one-dimensional internal ballistics analysis capable of scaling across wide ranges of motor size. The real-time burn rate data comes from three test campaigns of subscale segmented solid rocket motors tested at two facilities. The flow theory admits the important effect of the blowing wall on the turbulent friction coefficient by using blowing wall data to determine the blowing wall friction coefficient. The erosive burning behavior of full-scale motors is now predicted more closely than with other recent models.

Kinetics programs for simulation of tropospheric photochemistry on the global scale

International Nuclear Information System (INIS)

Elliott, S.; Kao, C.Y.J.; Turco, R.P.; Zhao, X.P.

1993-08-01

The study of tropospheric kinetics underlies global change because key greenhouse gases are photochemically active. Modeling of tropospheric chemistry on a global scale is essential because some indirect greenhouse gases are short-lived and interact in a non-linear fashion. It is also extremely challenging, however; the global change grid is extensive in both the physical and temporal domains, and critical lower atmospheric species include the organics and their oxidized derivatives, which are numerous. Several types of optimization may be incorporated into kinetics modules to enhance their ability to simulate the complete lower atmospheric gas phase chemical system. (1) The photochemical integrator can be accelerated by avoiding matrix and iterative solutions and by establishing families. Accuracy and mass conservation are sacrificed in the absence of iteration, but atom balancing is restorable post hoc. (2) Chemistry can be arranged upon the massive grid to exploit parallel processing, and solutions to its continuity equations can be automated to permit experimentation with species and reaction lists or family definitions. Costs in programming effort will be incurred in these cases. (3) Complex hydrocarbon decay sequences can be streamlined either through structural lumping methods descended from smog investigations, which require considerable calibration, or by defining surrogates for classes of compounds, with a loss in constituent detail. From among the available options, the most advantageous permutations will vary with the specific nature of any eventual global scale study, and there is likely to be demand for many approaches. Tracer transport codes serve as a foundation upon which tropospheric chemistry packages will be tested. Encroachment of the NO x sphere of influence upon tropical rain forests and the upper free troposphere are two examples of specific problems to which full three-dimensional chemical simulations might be applied

Empirical scaling law connecting persistence and severity of global terrorism

Science.gov (United States)

Gao, Jianbo; Fang, Peng; Liu, Feiyan

2017-09-01

Terrorism and counterterrorism have both been evolving rapidly. From time to time, there have been debates on whether the new terrorism is evolutionary or revolutionary. Such debate often becomes more heated after major terrorist activities, such as the terrorist attacks on September 11, 2001 and the November 13, 2015 coordinated Paris terror attack. Using country-wide terrorism data since 1970, we show that there exist scaling laws governing the continuity and persistence of world-wide terrorism, with the long-term scaling parameter for each country closely related to its yearly global terrorism index. This suggests that the new terrorism is more accurately considered evolutionary. It is further shown that the imbalance in the seesaw of terrorism and counterterrorism is not only responsible for the scaling behavior found here, but also provides new means of quantifying the severity of the global terrorism.

Integration of Extended MHD and Kinetic Effects in Global Magnetosphere Models

Science.gov (United States)

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

2015-12-01

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

Improving Water Resources Management on Global and Region Scales - Evaluating Strategies for Water Futures with the IIASA's Community Water Model

Science.gov (United States)

Burek, P.; Kahil, T.; Satoh, Y.; Greve, P.; Byers, E.; Langan, S.; Wada, Y.

2017-12-01

Half of the planet's population is severely impacted by severe water issues including absent or unreliable water supply, sanitation, poor water quality, unmitigated floods and droughts, and degraded water environments. In recent years, global water security has been highlighted not only by the science community but also by business leaders as one of the greatest threats to sustainable human development for different generations. How can we ensure the well-being of people and ecosystems with limited water, technology and financial resources? To evaluate this, IIASA's Water Futures and Solutions Initiative (WFaS) is identifying a portfolios of robust and cost-effective options across different economic sectors including agriculture, energy, manufacturing, households, and environment and ecosystems. Options to increase water supply and accessibility are evaluated together with water demand management and water governance options. To test these solution-portfolios in order to obtain a clear picture of the opportunities but also of the risks and the trade-offs we have developed the Community Water Model (CWATM) which joins IIASA's integrated assessment modeling framework, coupling hydrology with hydro-economics (ECHO model), energy (MESSAGE model) and land use (GLOBIOM model). CWATM has been developed to work flexibly with varying spatial resolutions from global to regional levels. The model is open source and community-driven to promote our work amongst the wider water and other science community worldwide, with flexibility to link to other models and integrate newly developed modules such as water quality. In order to identify the solution portfolios, we present a global hotspots assessment of water-related risks with the ability to zoom in at regional scale using the example of the Lake Victoria basin in E. Africa. We show how socio-economic and climate change will alter spatial patterns of the hydrological cycle and have regional impacts on water availability. At

Representation of fine scale atmospheric variability in a nudged limited area quasi-geostrophic model: application to regional climate modelling

Science.gov (United States)

Omrani, H.; Drobinski, P.; Dubos, T.

2009-09-01

In this work, we consider the effect of indiscriminate nudging time on the large and small scales of an idealized limited area model simulation. The limited area model is a two layer quasi-geostrophic model on the beta-plane driven at its boundaries by its « global » version with periodic boundary condition. This setup mimics the configuration used for regional climate modelling. Compared to a previous study by Salameh et al. (2009) who investigated the existence of an optimal nudging time minimizing the error on both large and small scale in a linear model, we here use a fully non-linear model which allows us to represent the chaotic nature of the atmosphere: given the perfect quasi-geostrophic model, errors in the initial conditions, concentrated mainly in the smaller scales of motion, amplify and cascade into the larger scales, eventually resulting in a prediction with low skill. To quantify the predictability of our quasi-geostrophic model, we measure the rate of divergence of the system trajectories in phase space (Lyapunov exponent) from a set of simulations initiated with a perturbation of a reference initial state. Predictability of the "global", periodic model is mostly controlled by the beta effect. In the LAM, predictability decreases as the domain size increases. Then, the effect of large-scale nudging is studied by using the "perfect model” approach. Two sets of experiments were performed: (1) the effect of nudging is investigated with a « global » high resolution two layer quasi-geostrophic model driven by a low resolution two layer quasi-geostrophic model. (2) similar simulations are conducted with the two layer quasi-geostrophic LAM where the size of the LAM domain comes into play in addition to the first set of simulations. In the two sets of experiments, the best spatial correlation between the nudge simulation and the reference is observed with a nudging time close to the predictability time.

The Lifespan Self-Esteem Scale: Initial Validation of a New Measure of Global Self-Esteem.

Science.gov (United States)

Harris, Michelle A; Donnellan, M Brent; Trzesniewski, Kali H

2018-01-01

This article introduces the Lifespan Self-Esteem Scale (LSE), a short measure of global self-esteem suitable for populations drawn from across the lifespan. Many existing measures of global self-esteem cannot be used across multiple developmental periods due to changes in item content, response formats, and other scale characteristics. This creates a need for a new lifespan scale so that changes in global self-esteem over time can be studied without confounding maturational changes with alterations in the measure. The LSE is a 4-item measure with a 5-point response format using items inspired by established self-esteem scales. The scale is essentially unidimensional and internally consistent, and it converges with existing self-esteem measures across ages 5 to 93 (N = 2,714). Thus, the LSE appears to be a useful measure of global self-esteem suitable for use across the lifespan as well as contexts where a short measure is desirable, such as populations with short attention spans or large projects assessing multiple constructs. Moreover, the LSE is one of the first global self-esteem scales to be validated for children younger than age 8, which provides the opportunity to broaden the field to include research on early formation and development of global self-esteem, an area that has previously been limited.

Global modeling of withdrawal, allocation and consumptive use of surface water and groundwater resources

NARCIS (Netherlands)

Wada, Y.; Wisser, D.; Bierkens, M.F.P.

2013-01-01

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 a large scale, a number of macro-scale hydrological models (MHMs) have been

Use of a hybrid code for global-scale plasma simulation

International Nuclear Information System (INIS)

Swift, D.W.

1996-01-01

This paper presents a demonstration of the use of a hybrid code to model the Earth's magnetosphere on a global scale. The typical hybrid code calculates the interaction of fully kinetic ions and a massless electron fluid with the magnetic field. This code also includes a fluid ion component to approximate the cold ionospheric plasma that spatially overlaps with the discrete particle component. Other innovative features of the code include a numerically generated curvilinear coordinate system and subcycling of the magnetic field update to the particle push. These innovations allow the code to accommodate disparate time and distance scales. The demonstration is a simulation of the noon meridian plane of the magnetosphere. The code exhibits the formation of fast and slow-mode shocks and tearing reconnection at the magnetopause. New results include particle acceleration in the cusp and nearly field aligned currents linking the cusp and polar ionosphere. The paper also describes a density depletion instability and measures to avoid it. 27 refs., 4 figs

Global ice sheet modeling

International Nuclear Information System (INIS)

Hughes, T.J.; Fastook, J.L.

1994-05-01

The University of Maine conducted this study for Pacific Northwest Laboratory (PNL) as part of a global climate modeling task for site characterization of the potential nuclear waste respository site at Yucca Mountain, NV. The purpose of the study was to develop a global ice sheet dynamics model that will forecast the three-dimensional configuration of global ice sheets for specific climate change scenarios. The objective of the third (final) year of the work was to produce ice sheet data for glaciation scenarios covering the next 100,000 years. This was accomplished using both the map-plane and flowband solutions of our time-dependent, finite-element gridpoint model. The theory and equations used to develop the ice sheet models are presented. Three future scenarios were simulated by the model and results are discussed

Evaluating the effects of terrestrial ecosystems, climate and carbon dioxide on weathering over geological time: a global-scale process-based approach

Science.gov (United States)

Taylor, Lyla L.; Banwart, Steve A.; Valdes, Paul J.; Leake, Jonathan R.; Beerling, David J.

2012-01-01

Global weathering of calcium and magnesium silicate rocks provides the long-term sink for atmospheric carbon dioxide (CO2) on a timescale of millions of years by causing precipitation of calcium carbonates on the seafloor. Catchment-scale field studies consistently indicate that vegetation increases silicate rock weathering, but incorporating the effects of trees and fungal symbionts into geochemical carbon cycle models has relied upon simple empirical scaling functions. Here, we describe the development and application of a process-based approach to deriving quantitative estimates of weathering by plant roots, associated symbiotic mycorrhizal fungi and climate. Our approach accounts for the influence of terrestrial primary productivity via nutrient uptake on soil chemistry and mineral weathering, driven by simulations using a dynamic global vegetation model coupled to an ocean–atmosphere general circulation model of the Earth's climate. The strategy is successfully validated against observations of weathering in watersheds around the world, indicating that it may have some utility when extrapolated into the past. When applied to a suite of six global simulations from 215 to 50 Ma, we find significantly larger effects over the past 220 Myr relative to the present day. Vegetation and mycorrhizal fungi enhanced climate-driven weathering by a factor of up to 2. Overall, we demonstrate a more realistic process-based treatment of plant fungal–geosphere interactions at the global scale, which constitutes a first step towards developing ‘next-generation’ geochemical models. PMID:22232768

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

Science.gov (United States)

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

2015-01-01

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

Parallel processing and non-uniform grids in global air quality modeling

NARCIS (Netherlands)

Berkvens, P.J.F.; Bochev, Mikhail A.

2002-01-01

A large-scale global air quality model, running efficiently on a single vector processor, is enhanced to make more realistic and more long-term simulations feasible. Two strategies are combined: non-uniform grids and parallel processing. The communication through the hierarchy of non-uniform grids

Spatiotemporal exploratory models for broad-scale survey data.

Science.gov (United States)

Fink, Daniel; Hochachka, Wesley M; Zuckerberg, Benjamin; Winkler, David W; Shaby, Ben; Munson, M Arthur; Hooker, Giles; Riedewald, Mirek; Sheldon, Daniel; Kelling, Steve

2010-12-01

The distributions of animal populations change and evolve through time. Migratory species exploit different habitats at different times of the year. Biotic and abiotic features that determine where a species lives vary due to natural and anthropogenic factors. This spatiotemporal variation needs to be accounted for in any modeling of species' distributions. In this paper we introduce a semiparametric model that provides a flexible framework for analyzing dynamic patterns of species occurrence and abundance from broad-scale survey data. The spatiotemporal exploratory model (STEM) adds essential spatiotemporal structure to existing techniques for developing species distribution models through a simple parametric structure without requiring a detailed understanding of the underlying dynamic processes. STEMs use a multi-scale strategy to differentiate between local and global-scale spatiotemporal structure. A user-specified species distribution model accounts for spatial and temporal patterning at the local level. These local patterns are then allowed to "scale up" via ensemble averaging to larger scales. This makes STEMs especially well suited for exploring distributional dynamics arising from a variety of processes. Using data from eBird, an online citizen science bird-monitoring project, we demonstrate that monthly changes in distribution of a migratory species, the Tree Swallow (Tachycineta bicolor), can be more accurately described with a STEM than a conventional bagged decision tree model in which spatiotemporal structure has not been imposed. We also demonstrate that there is no loss of model predictive power when a STEM is used to describe a spatiotemporal distribution with very little spatiotemporal variation; the distribution of a nonmigratory species, the Northern Cardinal (Cardinalis cardinalis).

Very small glaciers under climate change: from the local to the global scale

Science.gov (United States)

Huss, M.; Fischer, M.

2015-12-01

Very small glaciers (climate archive. Very small glaciers have generally shorter response times than valley glaciers and their mass balance is strongly dependent on snow redistribution processes. Worldwide glacier monitoring has focused on medium-sized to large glaciers leaving us with a relatively limited understanding of the behavior of very small glaciers. With warming climate there is an increasing concern that very small glaciers might be the first to disappear. Already in the next decades this might result in the complete deglaciation of mountain ranges with glacier equilibrium lines close to the highest peaks, such as in the Rocky Mountains, the European Alps, the Andes or parts of High Mountain Asia. In this contribution, we present a comprehensive modelling framework to assess past and future changes in very small glaciers at the mountain-range scale. Among other processes our model accounts for snow redistribution, changes in glacier geometry and dynamic changes in debris-coverage, and computes e.g. distributed mass balance, englacial temperature and proglacial runoff. Detailed glacier projections until 2060 are shown for the Swiss Alps based on new data sets, and the 21st century contribution of all very small glaciers worldwide to sea-level rise is quantified using a global model. Grid-based modelling of surface mass balance and retreat for 1133 very small glaciers in Switzerland indicates that 70% of them will completely vanish within the next 25 years. However, a few avalanche-fed glaciers at low elevation might be able to survive even substantial atmospheric warming. We find relatively high static and dynamic sensitivities for gently-sloping glaciers. At the global scale, glaciers presently smaller than 1 km2 make up for only 0.7% of total ice volume but account for 6.7% of sea-level rise contribution during the period 2015-2025. This indicates that very small glaciers are a non-negligible component of global glacier change, at least in the near

Bioremediation at a global scale: from the test tube to planet Earth.

Science.gov (United States)

de Lorenzo, Víctor; Marlière, Philippe; Solé, Ricard

2016-09-01

Planet Earth's biosphere has evolved over billions of years as a balanced bio-geological system ultimately sustained by sunpower and the large-scale cycling of elements largely run by the global environmental microbiome. Humans have been part of this picture for much of their existence. But the industrial revolution started in the XIX century and the subsequent advances in medicine, chemistry, agriculture and communications have impacted such balances to an unprecedented degree - and the problem has nothing but exacerbated in the last 20 years. Human overpopulation, industrial growth along with unsustainable use of natural resources have driven many sites and perhaps the planetary ecosystem as a whole, beyond recovery by spontaneous natural means, even if the immediate causes could be stopped. The most conspicuous indications of such a state of affairs include the massive change in land use, the accelerated increase in the levels of greenhouse gases, the frequent natural disasters associated to climate change and the growing non-recyclable waste (e.g. plastics and recalcitrant chemicals) that we release to the Environment. While the whole planet is afflicted at a global scale by chemical pollution and anthropogenic emissions, the ongoing development of systems and synthetic biology, metagenomics, modern chemistry and some key concepts from ecological theory allow us to tackle this phenomenal challenge and propose large-scale interventions aimed at reversing and even improving the situation. This involves (i) identification of key reactions or processes that need to be re-established (or altogether created) for ecosystem reinstallation, (ii) implementation of such reactions in natural or designer hosts able to self-replicate and deliver the corresponding activities when/where needed in a fashion guided by sound ecological modelling, (iii) dispersal of niche-creating agents at a global scale and (iv) containment, monitoring and risk assessment of the whole process

Global-Scale Hydrology: Simple Characterization of Complex Simulation

Science.gov (United States)

Koster, Randal D.

1999-01-01

Atmospheric general circulation models (AGCMS) are unique and valuable tools for the analysis of large-scale hydrology. AGCM simulations of climate provide tremendous amounts of hydrological data with a spatial and temporal coverage unmatched by observation systems. To the extent that the AGCM behaves realistically, these data can shed light on the nature of the real world's hydrological cycle. In the first part of the seminar, I will describe the hydrological cycle in a typical AGCM, with some emphasis on the validation of simulated precipitation against observations. The second part of the seminar will focus on a key goal in large-scale hydrology studies, namely the identification of simple, overarching controls on hydrological behavior hidden amidst the tremendous amounts of data produced by the highly complex AGCM parameterizations. In particular, I will show that a simple 50-year-old climatological relation (and a recent extension we made to it) successfully predicts, to first order, both the annual mean and the interannual variability of simulated evaporation and runoff fluxes. The seminar will conclude with an example of a practical application of global hydrology studies. The accurate prediction of weather statistics several months in advance would have tremendous societal benefits, and conventional wisdom today points at the use of coupled ocean-atmosphere-land models for such seasonal-to-interannual prediction. Understanding the hydrological cycle in AGCMs is critical to establishing the potential for such prediction. Our own studies show, among other things, that soil moisture retention can lead to significant precipitation predictability in many midlatitude and tropical regions.

Open source large-scale high-resolution environmental modelling with GEMS

NARCIS (Netherlands)

Baarsma, R.J.; Alberti, K.; Marra, W.A.; Karssenberg, D.J.

2016-01-01

Many environmental, topographic and climate data sets are freely available at a global scale, creating the opportunities to run environmental models for every location on Earth. Collection of the data necessary to do this and the consequent conversion into a useful format is very demanding however,

Accelerating the Global Nested Air Quality Prediction Modeling System (GNAQPMS) model on Intel Xeon Phi processors

OpenAIRE

Wang, Hui; Chen, Huansheng; Wu, Qizhong; Lin, Junming; Chen, Xueshun; Xie, Xinwei; Wang, Rongrong; Tang, Xiao; Wang, Zifa

2017-01-01

The GNAQPMS model is the global version of the Nested Air Quality Prediction Modelling System (NAQPMS), which is a multi-scale chemical transport model used for air quality forecast and atmospheric environmental research. In this study, we present our work of porting and optimizing the GNAQPMS model on the second generation Intel Xeon Phi processor codename “Knights Landing” (KNL). Compared with the first generation Xeon Phi coprocessor, KNL introduced many new hardware features such as a boo...

Modeling Global Urbanization Supported by Nighttime Light Remote Sensing

Science.gov (United States)

Zhou, Y.

2015-12-01

Urbanization, a major driver of global change, profoundly impacts our physical and social world, for example, altering carbon cycling and climate. Understanding these consequences for better scientific insights and effective decision-making unarguably requires accurate information on urban extent and its spatial distributions. In this study, we developed a cluster-based method to estimate the optimal thresholds and map urban extents from the nighttime light remote sensing data, extended this method to the global domain by developing a computational method (parameterization) to estimate the key parameters in the cluster-based method, and built a consistent 20-year global urban map series to evaluate the time-reactive nature of global urbanization (e.g. 2000 in Fig. 1). Supported by urban maps derived from nightlights remote sensing data and socio-economic drivers, we developed an integrated modeling framework to project future urban expansion by integrating a top-down macro-scale statistical model with a bottom-up urban growth model. With the models calibrated and validated using historical data, we explored urban growth at the grid level (1-km) over the next two decades under a number of socio-economic scenarios. The derived spatiotemporal information of historical and potential future urbanization will be of great value with practical implications for developing adaptation and risk management measures for urban infrastructure, transportation, energy, and water systems when considered together with other factors such as climate variability and change, and high impact weather events.

Traveling-wave reactors: A truly sustainable and full-scale resource for global energy needs

International Nuclear Information System (INIS)

Ellis, T.; Petroski, R.; Hejzlar, P.; Zimmerman, G.; McAlees, D.; Whitmer, C.; Touran, N.; Hejzlar, J.; Weave, K.; Walter, J. C.; McWhirter, J.; Ahlfeld, C.; Burke, T.; Odedra, A.; Hyde, R.; Gilleland, J.; Ishikawa, Y.; Wood, L.; Myhrvold, N.; Gates Iii, W. H.

2010-01-01

mankind's anticipated energy needs for as long as the sun shines and the rain falls. Moreover, TWRs can naturally retain their efficiently-expended fuel for century length time-scales, so that they intrinsically pose minimal safety and security transportation hazards in addition to being full-scale carbon-free energy sources. This paper describes how TWRs could help move the global energy economy to a more sustainable footing. An economic case and potential impacts on the global energy system are explored. The paper also provides an overview of the practical engineering embodiment of the TWR, new computational tools we have developed for modeling TWRs, the degradation of the plutonium vector in used fuel from TWRs and advanced technological options for re-purposing fuel to extract more of its potential energy. (authors)

Multi-scale inference of interaction rules in animal groups using Bayesian model selection.

Directory of Open Access Journals (Sweden)

Richard P Mann

Full Text Available Inference of interaction rules of animals moving in groups usually relies on an analysis of large scale system behaviour. Models are tuned through repeated simulation until they match the observed behaviour. More recent work has used the fine scale motions of animals to validate and fit the rules of interaction of animals in groups. Here, we use a Bayesian methodology to compare a variety of models to the collective motion of glass prawns (Paratya australiensis. We show that these exhibit a stereotypical 'phase transition', whereby an increase in density leads to the onset of collective motion in one direction. We fit models to this data, which range from: a mean-field model where all prawns interact globally; to a spatial Markovian model where prawns are self-propelled particles influenced only by the current positions and directions of their neighbours; up to non-Markovian models where prawns have 'memory' of previous interactions, integrating their experiences over time when deciding to change behaviour. We show that the mean-field model fits the large scale behaviour of the system, but does not capture the observed locality of interactions. Traditional self-propelled particle models fail to capture the fine scale dynamics of the system. The most sophisticated model, the non-Markovian model, provides a good match to the data at both the fine scale and in terms of reproducing global dynamics, while maintaining a biologically plausible perceptual range. We conclude that prawns' movements are influenced by not just the current direction of nearby conspecifics, but also those encountered in the recent past. Given the simplicity of prawns as a study system our research suggests that self-propelled particle models of collective motion should, if they are to be realistic at multiple biological scales, include memory of previous interactions and other non-Markovian effects.

Century-scale variability in global annual runoff examined using a water balance model

Science.gov (United States)

McCabe, G.J.; Wolock, D.M.

2011-01-01

A monthly water balance model (WB model) is used with CRUTS2.1 monthly temperature and precipitation data to generate time series of monthly runoff for all land areas of the globe for the period 1905 through 2002. Even though annual precipitation accounts for most of the temporal and spatial variability in annual runoff, increases in temperature have had an increasingly negative effect on annual runoff after 1980. Although the effects of increasing temperature on runoff became more apparent after 1980, the relative magnitude of these effects are small compared to the effects of precipitation on global runoff. ?? 2010 Royal Meteorological Society.

An Efficient Upscaling Process Based on a Unified Fine-scale Multi-Physics Model for Flow Simulation in Naturally Fracture Carbonate Karst Reservoirs

KAUST Repository

Bi, Linfeng

2009-01-01

The main challenges in modeling fluid flow through naturally-fractured carbonate karst reservoirs are how to address various flow physics in complex geological architectures due to the presence of vugs and caves which are connected via fracture networks at multiple scales. In this paper, we present a unified multi-physics model that adapts to the complex flow regime through naturally-fractured carbonate karst reservoirs. This approach generalizes Stokes-Brinkman model (Popov et al. 2007). The fracture networks provide the essential connection between the caves in carbonate karst reservoirs. It is thus very important to resolve the flow in fracture network and the interaction between fractures and caves to better understand the complex flow behavior. The idea is to use Stokes-Brinkman model to represent flow through rock matrix, void caves as well as intermediate flows in very high permeability regions and to use an idea similar to discrete fracture network model to represent flow in fracture network. Consequently, various numerical solution strategies can be efficiently applied to greatly improve the computational efficiency in flow simulations. We have applied this unified multi-physics model as a fine-scale flow solver in scale-up computations. Both local and global scale-up are considered. It is found that global scale-up has much more accurate than local scale-up. Global scale-up requires the solution of global flow problems on fine grid, which generally is computationally expensive. The proposed model has the ability to deal with large number of fractures and caves, which facilitate the application of Stokes-Brinkman model in global scale-up computation. The proposed model flexibly adapts to the different flow physics in naturally-fractured carbonate karst reservoirs in a simple and effective way. It certainly extends modeling and predicting capability in efficient development of this important type of reservoir.

Dissonance and harmony between global and regional-scale seismic anisotropy and mantle dynamics

Science.gov (United States)

Becker, T. W.

2017-12-01

Huge numbers of SKS splitting observations and improved surface-wave based models of azimuthal anisotropy have advanced our understanding of how convection is recorded in mantle fabrics in the upper mantle. However, we are still debating the relative importance of frozen to actively forming olivine fabrics, subduction zone anisotropy lacks a clear reference model, and regional marine studies yield conflicting evidence as to what exactly is going on at the base of the plates and below. Here, I review the degree of agreement between regional and global observations of seismic anisotropy and how well those may be matched by first-order mantle convection models. Updated bean counting can help contextualize the spatial scales of alignment, and I discuss several examples of the relative roles of plate shear to mantle density anomalies and frozen-in structure for oceanic and continental plates. Resolution of seismological models is globally uneven, but there are some locales where such exercises may yield information on the relative strength of asthenosphere and mantle. Another long-standing question is how olivine fabrics record flow under different stress and volatile conditions. I illustrate how different petrological assumptions might be used to reconcile observations of azimuthal dependency of wave speeds for both Love and Rayleigh waves, and how this could improve our models of the upper mantle, much in the spirit of Montagner's vectorial tomography. This is but one approach to improve the regional realism of global geodynamic background models to understand where in space and time dissonance arises, and if a harmonious model may yet be constructed given our assumptions about the workings of the mantle.

Regional scaling of annual mean precipitation and water availability with global temperature change

Science.gov (United States)

Greve, Peter; Gudmundsson, Lukas; Seneviratne, Sonia I.

2018-03-01

Changes in regional water availability belong to the most crucial potential impacts of anthropogenic climate change, but are highly uncertain. It is thus of key importance for stakeholders to assess the possible implications of different global temperature thresholds on these quantities. Using a subset of climate model simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), we derive here the sensitivity of regional changes in precipitation and in precipitation minus evapotranspiration to global temperature changes. The simulations span the full range of available emission scenarios, and the sensitivities are derived using a modified pattern scaling approach. The applied approach assumes linear relationships on global temperature changes while thoroughly addressing associated uncertainties via resampling methods. This allows us to assess the full distribution of the simulations in a probabilistic sense. Northern high-latitude regions display robust responses towards wetting, while subtropical regions display a tendency towards drying but with a large range of responses. Even though both internal variability and the scenario choice play an important role in the overall spread of the simulations, the uncertainty stemming from the climate model choice usually accounts for about half of the total uncertainty in most regions. We additionally assess the implications of limiting global mean temperature warming to values below (i) 2 K or (ii) 1.5 K (as stated within the 2015 Paris Agreement). We show that opting for the 1.5 K target might just slightly influence the mean response, but could substantially reduce the risk of experiencing extreme changes in regional water availability.

Deep-sea benthic megafaunal habitat suitability modelling: A global-scale maximum entropy model for xenophyophores

Science.gov (United States)

Ashford, Oliver S.; Davies, Andrew J.; Jones, Daniel O. B.

2014-12-01

Xenophyophores are a group of exclusively deep-sea agglutinating rhizarian protozoans, at least some of which are foraminifera. They are an important constituent of the deep-sea megafauna that are sometimes found in sufficient abundance to act as a significant source of habitat structure for meiofaunal and macrofaunal organisms. This study utilised maximum entropy modelling (Maxent) and a high-resolution environmental database to explore the environmental factors controlling the presence of Xenophyophorea and two frequently sampled xenophyophore species that are taxonomically stable: Syringammina fragilissima and Stannophyllum zonarium. These factors were also used to predict the global distribution of each taxon. Areas of high habitat suitability for xenophyophores were highlighted throughout the world's oceans, including in a large number of areas yet to be suitably sampled, but the Northeast and Southeast Atlantic Ocean, Gulf of Mexico and Caribbean Sea, the Red Sea and deep-water regions of the Malay Archipelago represented particular hotspots. The two species investigated showed more specific habitat requirements when compared to the model encompassing all xenophyophore records, perhaps in part due to the smaller number and relatively more clustered nature of the presence records available for modelling at present. The environmental variables depth, oxygen parameters, nitrate concentration, carbon-chemistry parameters and temperature were of greatest importance in determining xenophyophore distributions, but, somewhat surprisingly, hydrodynamic parameters were consistently shown to have low importance, possibly due to the paucity of well-resolved global hydrodynamic datasets. The results of this study (and others of a similar type) have the potential to guide further sample collection, environmental policy, and spatial planning of marine protected areas and industrial activities that impact the seafloor, particularly those that overlap with aggregations of

Impact of changes in river fluxes of silica on the global marine silicon cycle: a model comparison

Directory of Open Access Journals (Sweden)

C. Y. Bernard

2010-02-01

Full Text Available The availability of dissolved silica (Si in the ocean provides a major control on the growth of siliceous phytoplankton. Diatoms in particular account for a large proportion of oceanic primary production. The original source of the silica is rock weathering, followed by transport of dissolved and biogenic silica to the coastal zone. This model study aims at assessing the sensitivity of the global marine silicon cycle to variations in the river input of silica on timescales ranging from several centuries to millennia. We compare the performance of a box model for the marine silicon cycle to that of a global biogeochemical ocean general circulation model (HAMOCC2 and 5. Results indicate that the average global ocean response to changes in river input of silica is comparable in the models on time scales up to 150 kyrs. While the trends in export production and opal burial are the same, the box model shows a delayed response to the imposed perturbations compared to the general circulation model. Results of both models confirm the important role of the continental margins as a sink for silica at the global scale. Our work also demonstrates that the effects of changes in riverine dissolved silica on ocean biogeochemistry depend on the availability of the other nutrients such as nitrogen, phosphorus and iron. The model results suggest that the effects of reduced silica inputs due to river damming are particularly pronounced in the Gulf of Bengal, Gulf of Mexico and the Amazon plume where they negatively affect opal production. While general circulation models are indispensable when assessing the spatial variation in opal export production and biogenic Si burial in the ocean, this study demonstrates that box models provide a good alternative when studying the average global ocean response to perturbations of the oceanic silica cycle (especially on longer time scales.

TRICYCLE: a new mathematical model for tritium at the global scale

International Nuclear Information System (INIS)

Killough, G.G.; Kocher, D.C.

1987-01-01

TRICYCLE (for TRItium CYCLE) is a new linear dynamic compartment model that has been successful in reproducing environmental time-series data that show levels of tritium from nuclear weapons testing. Based on the global hydrologic cycle and other geophysical data, TRICYCLE includes (1) separate stratosphere compartments for the northern and southern hemispheres, (2) disaggregation of the troposphere and ocean surface waters into eight latitude zones each, (3) consideration of the different concentrations of tritium in atmospheric water vapor over land and over the ocean (the concentration over land exceeds that over the ocean by a factor of 3-4), and (4) a box-diffusion model for vertical transport in the ocean. The authors have used the model to simulate tritium in precipitation, ocean surface waters, and surface fresh waters (rivers and lakes). When they assume that 50% of the tritium from atmospheric weapons testing was injected directly into the northern stratosphere, the model gives good representations of tritium in the ocean surface waters and the rivers and lakes of the northern hemisphere; moreover, it estimates reasonable approximations to time-series measurements of tritium in marine precipitation taken at specific latitudes; and over the full range of latitudes, its representation of the high-to-low latitude gradient of tritium in marine precipitation is remarkable. Apart from their intrinsic geophysical interest, such models are useful in assessing the collective radiation dose to populations from tritium that is reeased at a particular latitude

A Canonical Response in Rainfall Characteristics to Global Warming: Projections by IPCC CMIP5 Models

Science.gov (United States)

Lau, William K. M.; Wu, H. T.; Kim, K. M.

2012-01-01

Changes in rainfall characteristics induced by global warming are examined based on probability distribution function (PDF) analysis, from outputs of 14 IPCC (Intergovernmental Panel on Climate Change), CMIP (5th Coupled Model Intercomparison Project) models under various scenarios of increased CO2 emissions. Results show that collectively CMIP5 models project a robust and consistent global and regional rainfall response to CO2 warming. Globally, the models show a 1-3% increase in rainfall per degree rise in temperature, with a canonical response featuring large increase (100-250 %) in frequency of occurrence of very heavy rain, a reduction (5-10%) of moderate rain, and an increase (10-15%) of light rain events. Regionally, even though details vary among models, a majority of the models (>10 out of 14) project a consistent large scale response with more heavy rain events in climatologically wet regions, most pronounced in the Pacific ITCZ and the Asian monsoon. Moderate rain events are found to decrease over extensive regions of the subtropical and extratropical oceans, but increases over the extratropical land regions, and the Southern Oceans. The spatial distribution of light rain resembles that of moderate rain, but mostly with opposite polarity. The majority of the models also show increase in the number of dry events (absence or only trace amount of rain) over subtropical and tropical land regions in both hemispheres. These results suggest that rainfall characteristics are changing and that increased extreme rainfall events and droughts occurrences are connected, as a consequent of a global adjustment of the large scale circulation to global warming.

The Stanford Microsurgery and Resident Training (SMaRT) Scale: validation of an on-line global rating scale for technical assessment.

Science.gov (United States)

Satterwhite, Thomas; Son, Ji; Carey, Joseph; Echo, Anthony; Spurling, Terry; Paro, John; Gurtner, Geoffrey; Chang, James; Lee, Gordon K

2014-05-01

We previously reported results of our on-line microsurgery training program, showing that residents who had access to our website significantly improved their cognitive and technical skills. In this study, we report an objective means for expert evaluators to reliably rate trainees' technical skills under the microscope, with the use of our novel global rating scale. "Microsurgery Essentials" (http://smartmicrosurgery.com) is our on-line training curriculum. Residents were randomly divided into 2 groups: 1 group reviewed this online resource and the other did not. Pre- and post-tests consisted of videotaped microsurgical sessions in which the trainee performed "microsurgery" on 3 different models: latex glove, penrose drain, and the dorsal vessel of a chicken foot. The SMaRT (Stanford Microsurgery and Resident Training) scale, consisting of 9 categories graded on a 5-point Likert scale, was used to assess the trainees. Results were analyzed with ANOVA and Student t test, with P less than 0.05 indicating statistical significance. Seventeen residents participated in the study. The SMaRT scale adequately differentiated the performance of more experienced senior residents (PGY-4 to PGY-6, total average score=3.43) from less experienced junior residents (PGY-1 to PGY-3, total average score=2.10, P0.05). Additionally, junior residents who had access to our website showed a significant increase in their graded technical performance by 0.7 points when compared to residents who did not have access to the website who showed an improvement of only 0.2 points (P=0.01). Our SMaRT scale is valid and reliable in assessing the microsurgical skills of residents and other trainees. Current trainees are more likely to use self-directed on-line education because of its easy accessibility and interactive format. Our global rating scale can help ensure residents are achieving appropriate technical milestones.

Interannual Variation in Phytoplankton Class-specific Primary Production at a Global Scale

Science.gov (United States)

Rousseaux, Cecile; Gregg, Watson

2014-01-01

Phytoplankton is responsible for over half of the net primary production on earth. The knowledge on the contribution of various phytoplankton groups to the total primary production is still poorly understood. Data from satellite observations suggest that for upwelling regions, photosynthetic rates by microplankton is higher than that of nanoplankton but that when the spatial extent is considered, the production by nanoplankton is comparable or even larger than microplankton. Here, we used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of 4 phytoplankton groups to the total primary production. Globally, diatoms were the group that contributed the most to the total phytoplankton production (approx. 50%) followed by coccolithophores and chlorophytes. Primary production by diatoms was highest in high latitude (>45 deg) and in major upwelling systems (Equatorial Pacific and Benguela system). We assessed the effects of climate variability on the class-specific primary production using global (i.e. Multivariate El Nino Index, MEI) and 'regional' climate indices (e.g. Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability. These results provide a modeling and data assimilation perspective to phytoplankton partitioning of primary production and contribute to our understanding of the dynamics of the carbon cycle in the oceans at a global scale.

Testing the performance of a Dynamic Global Ecosystem Model: Water balance, carbon balance, and vegetation structure

Science.gov (United States)

Kucharik, Christopher J.; Foley, Jonathan A.; Delire, Christine; Fisher, Veronica A.; Coe, Michael T.; Lenters, John D.; Young-Molling, Christine; Ramankutty, Navin; Norman, John M.; Gower, Stith T.

2000-09-01

While a new class of Dynamic Global Ecosystem Models (DGEMs) has emerged in the past few years as an important tool for describing global biogeochemical cycles and atmosphere-biosphere interactions, these models are still largely untested. Here we analyze the behavior of a new DGEM and compare the results to global-scale observations of water balance, carbon balance, and vegetation structure. In this study, we use version 2 of the Integrated Biosphere Simulator (IBIS), which includes several major improvements and additions to the prototype model developed by Foley et al. [1996]. IBIS is designed to be a comprehensive model of the terrestrial biosphere; the model represents a wide range of processes, including land surface physics, canopy physiology, plant phenology, vegetation dynamics and competition, and carbon and nutrient cycling. The model generates global simulations of the surface water balance (e.g., runoff), the terrestrial carbon balance (e.g., net primary production, net ecosystem exchange, soil carbon, aboveground and belowground litter, and soil CO2 fluxes), and vegetation structure (e.g., biomass, leaf area index, and vegetation composition). In order to test the performance of the model, we have assembled a wide range of continental and global-scale data, including measurements of river discharge, net primary production, vegetation structure, root biomass, soil carbon, litter carbon, and soil CO2 flux. Using these field data and model results for the contemporary biosphere (1965-1994), our evaluation shows that simulated patterns of runoff, NPP, biomass, leaf area index, soil carbon, and total soil CO2 flux agree reasonably well with measurements that have been compiled from numerous ecosystems. These results also compare favorably to other global model results.

Probabilistic, meso-scale flood loss modelling

Science.gov (United States)

Kreibich, Heidi; Botto, Anna; Schröter, Kai; Merz, Bruno

2016-04-01

Flood risk analyses are an important basis for decisions on flood risk management and adaptation. However, such analyses are associated with significant uncertainty, even more if changes in risk due to global change are expected. Although uncertainty analysis and probabilistic approaches have received increased attention during the last years, they are still not standard practice for flood risk assessments and even more for flood loss modelling. State of the art in flood loss modelling is still the use of simple, deterministic approaches like stage-damage functions. Novel probabilistic, multi-variate flood loss models have been developed and validated on the micro-scale using a data-mining approach, namely bagging decision trees (Merz et al. 2013). In this presentation we demonstrate and evaluate the upscaling of the approach to the meso-scale, namely on the basis of land-use units. The model is applied in 19 municipalities which were affected during the 2002 flood by the River Mulde in Saxony, Germany (Botto et al. submitted). The application of bagging decision tree based loss models provide a probability distribution of estimated loss per municipality. Validation is undertaken on the one hand via a comparison with eight deterministic loss models including stage-damage functions as well as multi-variate models. On the other hand the results are compared with official loss data provided by the Saxon Relief Bank (SAB). The results show, that uncertainties of loss estimation remain high. Thus, the significant advantage of this probabilistic flood loss estimation approach is that it inherently provides quantitative information about the uncertainty of the prediction. References: Merz, B.; Kreibich, H.; Lall, U. (2013): Multi-variate flood damage assessment: a tree-based data-mining approach. NHESS, 13(1), 53-64. Botto A, Kreibich H, Merz B, Schröter K (submitted) Probabilistic, multi-variable flood loss modelling on the meso-scale with BT-FLEMO. Risk Analysis.

Towards forecasting volcanic eruptions on a global scale

Science.gov (United States)

Hooper, A. J.; Heimisson, E. R.; Gaddes, M.; Bagnardi, M.; Sigmundsson, F.; Spaans, K.; Parks, M.; Gudmundsson, M. T.; Ebmeier, S. K.; Holohan, E. P.; Wright, T. J.; Jonsdottir, K.; Hreinsdottir, S.; Dumont, S.; Ofeigsson, B.; Vogfjord, K. S.

2016-12-01

Volcanic eruptions can cause loss of life, damage health, and have huge economic impacts, providing strong societal motivation for predicting eruptive behavior prior to and during eruptions. I will present here recent progress we have made in mechanical modelling with a predictive capacity, and how we are expanding volcano monitoring to a global scale. The eruption of Bardarbunga volcano, Iceland, in 2014-2015 was the largest eruption there for more than 200 years, producing 1.6 km3of lava. Prior to eruption, magma propagated almost 50 km beneath the surface, over a period of two weeks. Key questions to answer in advance of such eruptions are: will it erupt, where, how much and for how long? We developed a model based on magma taking a path that maximizes energy release, which aligns well with the actual direction taken. Our model also predicts eruption in a topographic low, as actually occurred. As magma was withdrawn, the volcano surface sagged downwards. A coupled model of magma flow and piston-like collapse predicts a declining magma flow rate and ground subsidence rate, in accordance with that observed. With such a model, observations can be used to predict the timescale and rates of eruption, even before one starts. The primary data needed to constrain these predictive models are measurements of surface deformation. In Iceland, this is achieved using high accuracy GPS, however, most volcanoes have no ground instrumentation. A recent ESA mission, Sentinel-1, can potentially image deformation at almost all subaerial volcanoes every 6 days, using a technique called interferometric synthetic aperture radar (InSAR). This will allow us to detect early stages of magma migration at any volcano, then task other satellites to acquire data at a higher rate. We are working on a system to process all Sentinel-1 data in near-real time, which is a big data challenge. We have also developed new algorithms that maximize signal extraction from each new acquisition and

High resolution global flood hazard map from physically-based hydrologic and hydraulic models.

Science.gov (United States)

Begnudelli, L.; Kaheil, Y.; McCollum, J.

2017-12-01

The global flood map published online at http://www.fmglobal.com/research-and-resources/global-flood-map at 90m resolution is being used worldwide to understand flood risk exposure, exercise certain measures of mitigation, and/or transfer the residual risk financially through flood insurance programs. The modeling system is based on a physically-based hydrologic model to simulate river discharges, and 2D shallow-water hydrodynamic model to simulate inundation. The model can be applied to large-scale flood hazard mapping thanks to several solutions that maximize its efficiency and the use of parallel computing. The hydrologic component of the modeling system is the Hillslope River Routing (HRR) hydrologic model. HRR simulates hydrological processes using a Green-Ampt parameterization, and is calibrated against observed discharge data from several publicly-available datasets. For inundation mapping, we use a 2D Finite-Volume Shallow-Water model with wetting/drying. We introduce here a grid Up-Scaling Technique (UST) for hydraulic modeling to perform simulations at higher resolution at global scale with relatively short computational times. A 30m SRTM is now available worldwide along with higher accuracy and/or resolution local Digital Elevation Models (DEMs) in many countries and regions. UST consists of aggregating computational cells, thus forming a coarser grid, while retaining the topographic information from the original full-resolution mesh. The full-resolution topography is used for building relationships between volume and free surface elevation inside cells and computing inter-cell fluxes. This approach almost achieves computational speed typical of the coarse grids while preserving, to a significant extent, the accuracy offered by the much higher resolution available DEM. The simulations are carried out along each river of the network by forcing the hydraulic model with the streamflow hydrographs generated by HRR. Hydrographs are scaled so that the peak

Global ocean tide models on the eve of Topex/Poseidon

Science.gov (United States)

Ray, Richard D.

1993-01-01

Some existing global ocean tide models that can provide tide corrections to Topex/Poseidon altimeter data are described. Emphasis is given to the Schwiderski and Cartwright-Ray models, as these are the most comprehensive, highest resolution models, but other models that will soon appear are mentioned. Differences between models for M2 often exceed 10 cm over vast stretches of the ocean. Comparisons to 80 selected pelagic and island gauge measurements indicate the Schwiderski model is more accurate for the major solar tides, Cartwright-Ray for the major lunar tides. The adequacy of available tide models for studying basin-scale motions is probably marginal at best.

Strong constraint on modelled global carbon uptake using solar-induced chlorophyll fluorescence data.

Science.gov (United States)

MacBean, Natasha; Maignan, Fabienne; Bacour, Cédric; Lewis, Philip; Peylin, Philippe; Guanter, Luis; Köhler, Philipp; Gómez-Dans, Jose; Disney, Mathias

2018-01-31

Accurate terrestrial biosphere model (TBM) simulations of gross carbon uptake (gross primary productivity - GPP) are essential for reliable future terrestrial carbon sink projections. However, uncertainties in TBM GPP estimates remain. Newly-available satellite-derived sun-induced chlorophyll fluorescence (SIF) data offer a promising direction for addressing this issue by constraining regional-to-global scale modelled GPP. Here, we use monthly 0.5° GOME-2 SIF data from 2007 to 2011 to optimise GPP parameters of the ORCHIDEE TBM. The optimisation reduces GPP magnitude across all vegetation types except C4 plants. Global mean annual GPP therefore decreases from 194 ± 57 PgCyr -1 to 166 ± 10 PgCyr -1 , bringing the model more in line with an up-scaled flux tower estimate of 133 PgCyr -1 . Strongest reductions in GPP are seen in boreal forests: the result is a shift in global GPP distribution, with a ~50% increase in the tropical to boreal productivity ratio. The optimisation resulted in a greater reduction in GPP than similar ORCHIDEE parameter optimisation studies using satellite-derived NDVI from MODIS and eddy covariance measurements of net CO 2 fluxes from the FLUXNET network. Our study shows that SIF data will be instrumental in constraining TBM GPP estimates, with a consequent improvement in global carbon cycle projections.

Leaf optical properties shed light on foliar trait variability at individual to global scales

Science.gov (United States)

Shiklomanov, A. N.; Serbin, S.; Dietze, M.

2016-12-01

Recent syntheses of large trait databases have contributed immensely to our understanding of drivers of plant function at the global scale. However, the global trade-offs revealed by such syntheses, such as the trade-off between leaf productivity and resilience (i.e. "leaf economics spectrum"), are often absent at smaller scales and fail to correlate with actual functional limitations. An improved understanding of how traits vary within communities, species, and individuals is critical to accurate representations of vegetation ecophysiology and ecological dynamics in ecosystem models. Spectral data from both field observations and remote sensing platforms present a potentially rich and widely available source of information on plant traits. In particular, the inversion of physically-based radiative transfer models (RTMs) is an effective and general method for estimating plant traits from spectral measurements. Here, we apply Bayesian inversion of the PROSPECT leaf RTM to a large database of field spectra and plant traits spanning tropical, temperate, and boreal forests, agricultural plots, arid shrublands, and tundra to identify dominant sources of variability and characterize trade-offs in plant functional traits. By leveraging such a large and diverse dataset, we re-calibrate the empirical absorption coefficients underlying the PROSPECT model and expand its scope to include additional leaf biochemical components, namely leaf nitrogen content. Our work provides a key methodological contribution as a physically-based retrieval of leaf nitrogen from remote sensing observations, and provides substantial insights about trait trade-offs related to plant acclimation, adaptation, and community assembly.

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

Science.gov (United States)

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

2017-08-01

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

Global hydrobelts: improved reporting scale for water-related issues?

Science.gov (United States)

Meybeck, M.; Kummu, M.; Dürr, H. H.

2012-08-01

Questions related to water such as its availability, water needs or stress, or management, are mapped at various resolutions at the global scale. They are reported at many scales, mostly along political or continental boundaries. As such, they ignore the fundamental heterogeneity of the hydroclimate and the natural boundaries of the river basins. Here, we describe the continental landmasses according to eight global-scale hydrobelts strictly limited by river basins, defined at a 30' (0.5°) resolution. The belts were defined and delineated, based primarily on the annual average temperature (T) and runoff (q), to maximise interbelt differences and minimise intrabelt variability. The belts were further divided into 29 hydroregions based on continental limits. This new global puzzle defines homogeneous and near-contiguous entities with similar hydrological and thermal regimes, glacial and postglacial basin histories, endorheism distribution and sensitivity to climate variations. The Mid-Latitude, Dry and Subtropical belts have northern and southern analogues and a general symmetry can be observed for T and q between them. The Boreal and Equatorial belts are unique. The hydroregions (median size 4.7 Mkm2) contrast strongly, with the average q ranging between 6 and 1393 mm yr-1 and the average T between -9.7 and +26.3 °C. Unlike the hydroclimate, the population density between the North and South belts and between the continents varies greatly, resulting in pronounced differences between the belts with analogues in both hemispheres. The population density ranges from 0.7 to 0.8 p km-2 for the North American Boreal and some Australian hydroregions to 280 p km-2 for the Asian part of the Northern Mid-Latitude belt. The combination of population densities and hydroclimate features results in very specific expressions of water-related characteristics in each of the 29 hydroregions. Our initial tests suggest that hydrobelt and hydroregion divisions are often more

Global nuclear material control model

International Nuclear Information System (INIS)

Dreicer, J.S.; Rutherford, D.A.

1996-01-01

The nuclear danger can be reduced by a system for global management, protection, control, and accounting as part of a disposition program for special nuclear materials. The development of an international fissile material management and control regime requires conceptual research supported by an analytical and modeling tool that treats the nuclear fuel cycle as a complete system. Such a tool must represent the fundamental data, information, and capabilities of the fuel cycle including an assessment of the global distribution of military and civilian fissile material inventories, a representation of the proliferation pertinent physical processes, and a framework supportive of national or international perspective. They have developed a prototype global nuclear material management and control systems analysis capability, the Global Nuclear Material Control (GNMC) model. The GNMC model establishes the framework for evaluating the global production, disposition, and safeguards and security requirements for fissile nuclear material

A new approach to inventorying bodies of water, from local to global scale

Directory of Open Access Journals (Sweden)

Bartout, Pascal

2015-12-01

Full Text Available Having reliable estimates of the number of water bodies on different geographical scales is of great importance to better understand biogeochemical cycles and to tackle the social issues related to the economic and cultural use of water bodies. However, limnological research suffers from a lack of reliable inventories; the available scientific references are predominately based on water bodies of natural origin, large in size and preferentially located in previously glaciated areas. Artificial, small and randomly distributed water bodies, especially ponds, are usually not inventoried. Following Wetzel’s theory (1990, some authors included them in global inventories by using remote sensing or mathematical extrapolation, but fieldwork on the ground has been done on a very limited amount of territory. These studies have resulted in an explosive increase in the estimated number of water bodies, going from 8.44 million lakes (Meybeck 1995 to 3.5 billion water bodies (Downing 2010. These numbers raise several questions, especially about the methodology used for counting small-sized water bodies and the methodological treatment of spatial variables. In this study, we use inventories of water bodies for Sweden, Finland, Estonia and France to show incoherencies generated by the “global to local” approach. We demonstrate that one universal relationship does not suffice for generating the regional or global inventories of water bodies because local conditions vary greatly from one region to another and cannot be offset adequately by each other. The current paradigm for global estimates of water bodies in limnology, which is based on one representative model applied to different territories, does not produce sufficiently exact global inventories. The step-wise progression from the local to the global scale requires the development of many regional equations based on fieldwork; a specific equation that adequately reflects the actual relationship

Integrating global socio-economic influences into a regional land use change model for China

Science.gov (United States)

Xu, Xia; Gao, Qiong; Peng, Changhui; Cui, Xuefeng; Liu, Yinghui; Jiang, Li

2014-03-01

With rapid economic development and urbanization, land use in China has experienced huge changes in recent years; and this will probably continue in the future. Land use problems in China are urgent and need further study. Rapid land-use change and economic development make China an ideal region for integrated land use change studies, particularly the examination of multiple factors and global-regional interactions in the context of global economic integration. This paper presents an integrated modeling approach to examine the impact of global socio-economic processes on land use changes at a regional scale. We develop an integrated model system by coupling a simple global socio-economic model (GLOBFOOD) and regional spatial allocation model (CLUE). The model system is illustrated with an application to land use in China. For a given climate change, population growth, and various socio-economic situations, a global socio-economic model simulates the impact of global market and economy on land use, and quantifies changes of different land use types. The land use spatial distribution model decides the type of land use most appropriate in each spatial grid by employing a weighted suitability index, derived from expert knowledge about the ecosystem state and site conditions. A series of model simulations will be conducted and analyzed to demonstrate the ability of the integrated model to link global socioeconomic factors with regional land use changes in China. The results allow an exploration of the future dynamics of land use and landscapes in China.

Global tropospheric ozone modeling: Quantifying errors due to grid resolution

Science.gov (United States)

Wild, Oliver; Prather, Michael J.

2006-06-01

Ozone production in global chemical models is dependent on model resolution because ozone chemistry is inherently nonlinear, the timescales for chemical production are short, and precursors are artificially distributed over the spatial scale of the model grid. In this study we examine the sensitivity of ozone, its precursors, and its production to resolution by running a global chemical transport model at four different resolutions between T21 (5.6° × 5.6°) and T106 (1.1° × 1.1°) and by quantifying the errors in regional and global budgets. The sensitivity to vertical mixing through the parameterization of boundary layer turbulence is also examined. We find less ozone production in the boundary layer at higher resolution, consistent with slower chemical production in polluted emission regions and greater export of precursors. Agreement with ozonesonde and aircraft measurements made during the NASA TRACE-P campaign over the western Pacific in spring 2001 is consistently better at higher resolution. We demonstrate that the numerical errors in transport processes on a given resolution converge geometrically for a tracer at successively higher resolutions. The convergence in ozone production on progressing from T21 to T42, T63, and T106 resolution is likewise monotonic but indicates that there are still large errors at 120 km scales, suggesting that T106 resolution is too coarse to resolve regional ozone production. Diagnosing the ozone production and precursor transport that follow a short pulse of emissions over east Asia in springtime allows us to quantify the impacts of resolution on both regional and global ozone. Production close to continental emission regions is overestimated by 27% at T21 resolution, by 13% at T42 resolution, and by 5% at T106 resolution. However, subsequent ozone production in the free troposphere is not greatly affected. We find that the export of short-lived precursors such as NOx by convection is overestimated at coarse resolution.

Hydrodynamic modelling and global datasets: Flow connectivity and SRTM data, a Bangkok case study.

Science.gov (United States)

Trigg, M. A.; Bates, P. B.; Michaelides, K.

2012-04-01

The rise in the global interconnected manufacturing supply chains requires an understanding and consistent quantification of flood risk at a global scale. Flood risk is often better quantified (or at least more precisely defined) in regions where there has been an investment in comprehensive topographical data collection such as LiDAR coupled with detailed hydrodynamic modelling. Yet in regions where these data and modelling are unavailable, the implications of flooding and the knock on effects for global industries can be dramatic, as evidenced by the recent floods in Bangkok, Thailand. There is a growing momentum in terms of global modelling initiatives to address this lack of a consistent understanding of flood risk and they will rely heavily on the application of available global datasets relevant to hydrodynamic modelling, such as Shuttle Radar Topography Mission (SRTM) data and its derivatives. These global datasets bring opportunities to apply consistent methodologies on an automated basis in all regions, while the use of coarser scale datasets also brings many challenges such as sub-grid process representation and downscaled hydrology data from global climate models. There are significant opportunities for hydrological science in helping define new, realistic and physically based methodologies that can be applied globally as well as the possibility of gaining new insights into flood risk through analysis of the many large datasets that will be derived from this work. We use Bangkok as a case study to explore some of the issues related to using these available global datasets for hydrodynamic modelling, with particular focus on using SRTM data to represent topography. Research has shown that flow connectivity on the floodplain is an important component in the dynamics of flood flows on to and off the floodplain, and indeed within different areas of the floodplain. A lack of representation of flow connectivity, often due to data resolution limitations, means

Geoscience Meets Social Science: A Flexible Data Driven Approach for Developing High Resolution Population Datasets at Global Scale

Science.gov (United States)

Rose, A.; McKee, J.; Weber, E.; Bhaduri, B. L.

2017-12-01

Leveraging decades of expertise in population modeling, and in response to growing demand for higher resolution population data, Oak Ridge National Laboratory is now generating LandScan HD at global scale. LandScan HD is conceived as a 90m resolution population distribution where modeling is tailored to the unique geography and data conditions of individual countries or regions by combining social, cultural, physiographic, and other information with novel geocomputation methods. Similarities among these areas are exploited in order to leverage existing training data and machine learning algorithms to rapidly scale development. Drawing on ORNL's unique set of capabilities, LandScan HD adapts highly mature population modeling methods developed for LandScan Global and LandScan USA, settlement mapping research and production in high-performance computing (HPC) environments, land use and neighborhood mapping through image segmentation, and facility-specific population density models. Adopting a flexible methodology to accommodate different geographic areas, LandScan HD accounts for the availability, completeness, and level of detail of relevant ancillary data. Beyond core population and mapped settlement inputs, these factors determine the model complexity for an area, requiring that for any given area, a data-driven model could support either a simple top-down approach, a more detailed bottom-up approach, or a hybrid approach.

A Global Model of Meteoric Sodium

Science.gov (United States)

Marsh, Daniel R.; Janches, Diego; Feng, Wuhu; Plane, John M. C.

2013-01-01

A global model of sodium in the mesosphere and lower thermosphere has been developed within the framework of the National Center for Atmospheric Research's Whole Atmosphere Community Climate Model (WACCM). The standard fully interactive WACCM chemistry module has been augmented with a chemistry scheme that includes nine neutral and ionized sodium species. Meteoric ablation provides the source of sodium in the model and is represented as a combination of a meteoroid input function (MIF) and a parameterized ablation model. The MIF provides the seasonally and latitudinally varying meteoric flux which is modeled taking into consideration the astronomical origins of sporadic meteors and considers variations in particle entry angle, velocity, mass, and the differential ablation of the chemical constituents. WACCM simulations show large variations in the sodium constituents over time scales from days to months. Seasonality of sodium constituents is strongly affected by variations in the MIF and transport via the mean meridional wind. In particular, the summer to winter hemisphere flow leads to the highest sodium species concentrations and loss rates occurring over the winter pole. In the Northern Hemisphere, this winter maximum can be dramatically affected by stratospheric sudden warmings. Simulations of the January 2009 major warming event show that it caused a short-term decrease in the sodium column over the polar cap that was followed by a factor of 3 increase in the following weeks. Overall, the modeled distribution of atomic sodium in WACCM agrees well with both ground-based and satellite observations. Given the strong sensitivity of the sodium layer to dynamical motions, reproducing its variability provides a stringent test of global models and should help to constrain key atmospheric variables in this poorly sampled region of the atmosphere.

Diversification and intensification of agricultural adaptation from global to local scales.

Directory of Open Access Journals (Sweden)

Minjie Chen

Full Text Available Smallholder farming systems are vulnerable to a number of challenges, including continued population growth, urbanization, income disparities, land degradation, decreasing farm size and productivity, all of which are compounded by uncertainty of climatic patterns. Understanding determinants of smallholder farming practices is critical for designing and implementing successful interventions, including climate change adaptation programs. We examine two dimensions wherein smallholder farmers may adapt agricultural practices; through intensification (i.e., adopt more practices or diversification (i.e. adopt different practices. We use data on 5314 randomly sampled households located in 38 sites in 15 countries across four regions (East and West Africa, South Asia, and Central America. We estimate empirical models designed to assess determinants of both intensification and diversification of adaptation activities at global scales. Aspects of adaptive capacity that are found to increase intensification of adaptation globally include variables associated with access to information and human capital, financial considerations, assets, household infrastructure and experience. In contrast, there are few global drivers of adaptive diversification, with a notable exception being access to weather information, which also increases adaptive intensification. Investigating reasons for adaptation indicate that conditions present in underdeveloped markets provide the primary impetus for adaptation, even in the context of climate change. We also compare determinants across spatial scales, which reveals a variety of local avenues through which policy interventions can relax economic constraints and boost agricultural adaptation for both intensification and diversification. For example, access to weather information does not affect intensification adaptation in Africa, but is significant at several sites in Bangladesh and India. Moreover, this information leads to

Diversification and intensification of agricultural adaptation from global to local scales

Science.gov (United States)

Chen, Minjie; Wichmann, Bruno; Luckert, Marty; Winowiecki, Leigh; Förch, Wiebke

2018-01-01

Smallholder farming systems are vulnerable to a number of challenges, including continued population growth, urbanization, income disparities, land degradation, decreasing farm size and productivity, all of which are compounded by uncertainty of climatic patterns. Understanding determinants of smallholder farming practices is critical for designing and implementing successful interventions, including climate change adaptation programs. We examine two dimensions wherein smallholder farmers may adapt agricultural practices; through intensification (i.e., adopt more practices) or diversification (i.e. adopt different practices). We use data on 5314 randomly sampled households located in 38 sites in 15 countries across four regions (East and West Africa, South Asia, and Central America). We estimate empirical models designed to assess determinants of both intensification and diversification of adaptation activities at global scales. Aspects of adaptive capacity that are found to increase intensification of adaptation globally include variables associated with access to information and human capital, financial considerations, assets, household infrastructure and experience. In contrast, there are few global drivers of adaptive diversification, with a notable exception being access to weather information, which also increases adaptive intensification. Investigating reasons for adaptation indicate that conditions present in underdeveloped markets provide the primary impetus for adaptation, even in the context of climate change. We also compare determinants across spatial scales, which reveals a variety of local avenues through which policy interventions can relax economic constraints and boost agricultural adaptation for both intensification and diversification. For example, access to weather information does not affect intensification adaptation in Africa, but is significant at several sites in Bangladesh and India. Moreover, this information leads to diversification of

A model for global diversity in response to temperature change over geological time scales, with reference to planktic organisms.

Science.gov (United States)

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.

GLOBATO: An enhanced global relief model at 30 arc-seconds resolution

Science.gov (United States)

O'Leary, V.; Amante, C.

2017-12-01

The National Centers for Environmental Information (NCEI), an office of the National Oceanic and Atmospheric Administration (NOAA), first developed a digital bathymetric and elevation model, ETOPO5, from publicly available data in 1993. For nearly 25 years, NCEI's ETOPO family of global relief models have supported research at a planetary scale, including tsunami forecasting, ocean circulation modeling, visualization of the seafloor, understanding geological phenomena, and aiding the development of other global and regional elevation models. GLOBATO (GLObal BAThymetry and TOpography) is now the most detailed version released by NCEI with a horizontal resolution of 30 arc-seconds and succeeds ETOPO1 with the inclusion of several new or updated data-sets for the seafloor as well as land areas. GLOBATO is a compilation of data derived from models of satellite measurements, ship depth soundings, and multibeam surveys, as well as regional models developed for Greenland and Antarctica. These data were converted from different formats, resolutions, spatial distributions, and projections into a single global model using GDAL v2.2 and MB-System v5.5. As with previous NCEI models, GLOBATO is available in two formats, "bedrock elevation" (measured as the base of major ice sheets) and "ice surface elevation" (measured as the surface of major ice sheets) which provides comprehensive topographic and bathymetric coverage between +- 90 degrees latitude and +- 180 degrees longitude. Adhering to best practices, GLOBATO, all related digital products, and any supporting documentation are available online through the NCEI data portal. These new, high resolution models will better support the variety of research ETOPO1 has made possible.

Large Scale Skill in Regional Climate Modeling and the Lateral Boundary Condition Scheme

Science.gov (United States)

Veljović, K.; Rajković, B.; Mesinger, F.

2009-04-01

Several points are made concerning the somewhat controversial issue of regional climate modeling: should a regional climate model (RCM) be expected to maintain the large scale skill of the driver global model that is supplying its lateral boundary condition (LBC)? Given that this is normally desired, is it able to do so without help via the fairly popular large scale nudging? Specifically, without such nudging, will the RCM kinetic energy necessarily decrease with time compared to that of the driver model or analysis data as suggested by a study using the Regional Atmospheric Modeling System (RAMS)? Finally, can the lateral boundary condition scheme make a difference: is the almost universally used but somewhat costly relaxation scheme necessary for a desirable RCM performance? Experiments are made to explore these questions running the Eta model in two versions differing in the lateral boundary scheme used. One of these schemes is the traditional relaxation scheme, and the other the Eta model scheme in which information is used at the outermost boundary only, and not all variables are prescribed at the outflow boundary. Forecast lateral boundary conditions are used, and results are verified against the analyses. Thus, skill of the two RCM forecasts can be and is compared not only against each other but also against that of the driver global forecast. A novel verification method is used in the manner of customary precipitation verification in that forecast spatial wind speed distribution is verified against analyses by calculating bias adjusted equitable threat scores and bias scores for wind speeds greater than chosen wind speed thresholds. In this way, focusing on a high wind speed value in the upper troposphere, verification of large scale features we suggest can be done in a manner that may be more physically meaningful than verifications via spectral decomposition that are a standard RCM verification method. The results we have at this point are somewhat

Utilization of Large Scale Surface Models for Detailed Visibility Analyses

Science.gov (United States)

Caha, J.; Kačmařík, M.

2017-11-01

This article demonstrates utilization of large scale surface models with small spatial resolution and high accuracy, acquired from Unmanned Aerial Vehicle scanning, for visibility analyses. The importance of large scale data for visibility analyses on the local scale, where the detail of the surface model is the most defining factor, is described. The focus is not only the classic Boolean visibility, that is usually determined within GIS, but also on so called extended viewsheds that aims to provide more information about visibility. The case study with examples of visibility analyses was performed on river Opava, near the Ostrava city (Czech Republic). The multiple Boolean viewshed analysis and global horizon viewshed were calculated to determine most prominent features and visibility barriers of the surface. Besides that, the extended viewshed showing angle difference above the local horizon, which describes angular height of the target area above the barrier, is shown. The case study proved that large scale models are appropriate data source for visibility analyses on local level. The discussion summarizes possible future applications and further development directions of visibility analyses.

Modeling large-scale human alteration of land surface hydrology and climate

Science.gov (United States)

Pokhrel, Yadu N.; Felfelani, Farshid; Shin, Sanghoon; Yamada, Tomohito J.; Satoh, Yusuke

2017-12-01

Rapidly expanding human activities have profoundly affected various biophysical and biogeochemical processes of the Earth system over a broad range of scales, and freshwater systems are now amongst the most extensively altered ecosystems. In this study, we examine the human-induced changes in land surface water and energy balances and the associated climate impacts using a coupled hydrological-climate model framework which also simulates the impacts of human activities on the water cycle. We present three sets of analyses using the results from two model versions—one with and the other without considering human activities; both versions are run in offline and coupled mode resulting in a series of four experiments in total. First, we examine climate and human-induced changes in regional water balance focusing on the widely debated issue of the desiccation of the Aral Sea in central Asia. Then, we discuss the changes in surface temperature as a result of changes in land surface energy balance due to irrigation over global and regional scales. Finally, we examine the global and regional climate impacts of increased atmospheric water vapor content due to irrigation. Results indicate that the direct anthropogenic alteration of river flow in the Aral Sea basin resulted in the loss of 510 km3 of water during the latter half of the twentieth century which explains about half of the total loss of water from the sea. Results of irrigation-induced changes in surface energy balance suggest a significant surface cooling of up to 3.3 K over 1° grids in highly irrigated areas but a negligible change in land surface temperature when averaged over sufficiently large global regions. Results from the coupled model indicate a substantial change in 2 m air temperature and outgoing longwave radiation due to irrigation, highlighting the non-local (regional and global) implications of irrigation. These results provide important insights on the direct human alteration of land surface

Optimization Model for Mitigating Global Warming at the Farm Scale: An Application to Japanese Rice Farms

Directory of Open Access Journals (Sweden)

Kiyotaka Masuda

2016-06-01

Full Text Available In Japan, greenhouse gas emissions from rice production, especially CH4 emissions in rice paddy fields, are the primary contributors to global warming from agriculture. When prolonged midseason drainage for mitigating CH4 emissions from rice paddy fields is practiced with environmentally friendly rice production based on reduced use of synthetic pesticides and chemical fertilizers, Japanese rice farmers can receive an agri-environmental direct payment. This paper examines the economic and environmental effects of the agri-environmental direct payment on the adoption of a measure to mitigate global warming in Japanese rice farms using a combined application of linear programming and life cycle assessment at the farm scale. Eco-efficiency, which is defined as net farm income divided by global warming potential, is used as an integrated indicator for assessing the economic and environmental feasibilities. The results show that under the current direct payment level, the prolonged midseason drainage technique does not improve the eco-efficiency of Japanese rice farms because the practice of this technique in environmentally friendly rice production causes large economic disadvantages in exchange for small environmental advantages. The direct payment rates for agri-environmental measures should be determined based on the condition that environmentally friendly agricultural practices improve eco-efficiency compared with conventional agriculture.

A global central banker competency model

Directory of Open Access Journals (Sweden)

David W. Brits

2014-07-01

Full Text Available Orientation: No comprehensive, integrated competency model exists for central bankers. Due to the importance of central banks in the context of the ongoing global financial crisis, it was deemed necessary to design and validate such a model. Research purpose: To craft and validate a comprehensive, integrated global central banker competency model (GCBCM and to assess whether central banks using the GCBCM for training have a higher global influence. Motivation for the study: Limited consensus exists globally about what constitutes a ‘competent’ central banker. A quantitatively validated GCBCM would make a significant contribution to enhancing central banker effectiveness, and also provide a solid foundation for effective people management. Research approach, design and method: A blended quantitative and qualitative research approach was taken. Two sets of hypotheses were tested regarding the relationships between the GCBCM and the training offered, using the model on the one hand, and a central bank’s global influence on the other. Main findings: The GCBCM was generally accepted across all participating central banks globally, although some differences were found between central banks with higher and lower global influence. The actual training offered by central banks in terms of the model, however, is generally limited to technical-functional skills. The GCBCM is therefore at present predominantly aspirational. Significant differences were found regarding the training offered. Practical/managerial implications: By adopting the GCBCM, central banks would be able to develop organisation-specific competency models in order to enhance their organisational capabilities and play their increasingly important global role more effectively. Contribution: A generic conceptual framework for the crafting of a competency model with evaluation criteria was developed. A GCBCM was quantitatively validated.

Global off-line evaluation of the ISBA-TRIP flood model

Energy Technology Data Exchange (ETDEWEB)

Decharme, B.; Alkama, R.; Faroux, S.; Douville, H. [GAME-CNRM/CNRS - Meteo-France, Toulouse (France); Papa, F. [NOAA-CREST, City College of New York, New York, NY (United States); Institut de Recherche pour le Developpement IRD-LEGOS, Toulouse (France); Prigent, C. [CNRS/Laboratoire d' Etudes du Rayonnement et de la Matiere en Astrophysique, Observatoire de Paris, Paris (France)

2012-04-15

This study presents an off-line global evaluation of the ISBA-TRIP hydrological model including a two-way flood scheme. The flood dynamics is indeed described through the daily coupling between the ISBA land surface model and the TRIP river routing model including a prognostic flood reservoir. This reservoir fills when the river height exceeds the critical river bankfull height and vice versa. The flood interacts with the soil hydrology through infiltration and with the overlying atmosphere through precipitation interception and free water surface evaporation. The model is evaluated over a relatively long period (1986-2006) at 1 resolution using the Princeton University 3-hourly atmospheric forcing. Four simulations are performed in order to assess the model sensitivity to the river bankfull height. The evaluation is made against satellite-derived global inundation estimates as well as in situ river discharge observations at 122 gauging stations. First, the results show a reasonable simulation of the global distribution of simulated floodplains when compared to satellite-derived estimates. At basin scale, the comparison reveals some discrepancies, both in terms of climatology and interannual variability, but the results remain acceptable for a simple large-scale model. In addition, the simulated river discharges are improved in term of efficiency scores for more than 50% of the 122 stations and deteriorated for 4% only. Two mechanisms mainly explain this positive impact: an increase in evapotranspiration that limits the annual discharge overestimation found when flooding is not taking into account and a smoothed river peak flow when the floodplain storage is significant. Finally, the sensitivity experiments suggest that the river bankfull depth is potentially tunable according to the river discharge scores to control the accuracy of the simulated flooded areas and its related increase in land surface evaporation. Such a tuning could be relevant at least for climate

Dry deposition velocities in the global multi-scale CTM MOCAGE

Science.gov (United States)

Michou, M.; Peuch, V.-H.

2003-04-01

Surface exchanges considered in the MOCAGE multiscale Chemistry and Transport Model (CTM) of Météo-France include dry deposition of gaseous species. To compute realistic time-dependent fluxes at the surface, a 2D interface between MOCAGE and ARPEGE, the French operational numerical weather prediction model, has been developed. Dry deposition of species including ozone, sulfur dioxide, nitrogen-containing compounds, long-lived and short-lived intermediates organic compounds, have been parameterised according to the [Wesely, 1989] scheme. A number of modifications has been made, for instance concerning the deposition against wet surfaces. The formulation of the aerodynamic resistance follows [Louis, 1979], and that of the stomatal resistance, the Interaction Soil Biosphere Atmosphere (ISBA) Météo-France scheme. Resistances are computed using the surface meteorological fields obtained from the analyses or forecasts of ARPEGE. Vegetation fields such as the Leaf Area Index are prescribed with a one-degree spatial resolution at the global scale, and a five-minute resolution over Europe. Calculated dry deposition velocities of ozone, sulfur dioxide and nitric acid have been evaluated against field experimental data at various locations around the world, from tropical regions, rain forest or savannah over Central Africa and Amazonia (EXPRESSO and LBA campaigns), to Mediterranean regions, including forested and crop sites (ESCOMPTE campaign), and temperate areas (deciduous and evergreen forests). Hourly values, monthly and seasonal means have been examined, as well as the impact of the model resolution, from 2 degrees over the globe to 0.08 degrees over regional domains. The contributions to the global budget of ozone of the deposition fluxes in these different regions of the globe will be also presented.

Characterizing the utility of the TMPA real-time product for hydrologic predictions over global river basins across scales

Science.gov (United States)

Gao, H.; Zhang, S.; Nijssen, B.; Zhou, T.; Voisin, N.; Sheffield, J.; Lee, K.; Shukla, S.; Lettenmaier, D. P.

2017-12-01

Despite its errors and uncertainties, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis real-time product (TMPA-RT) has been widely used for hydrological monitoring and forecasting due to its timely availability for real-time applications. To evaluate the utility of TMPA-RT in hydrologic predictions, many studies have compared modeled streamflows driven by TMPA-RT against gauge data. However, because of the limited availability of streamflow observations in data sparse regions, there is still a lack of comprehensive comparisons for TMPA-RT based hydrologic predictions at the global scale. Furthermore, it is expected that its skill is less optimal at the subbasin scale than the basin scale. In this study, we evaluate and characterize the utility of the TMPA-RT product over selected global river basins during the period of 1998 to 2015 using the TMPA research product (TMPA-RP) as a reference. The Variable Infiltration Capacity (VIC) model, which was calibrated and validated previously, is adopted to simulate streamflows driven by TMPA-RT and TMPA-RP, respectively. The objective of this study is to analyze the spatial and temporal characteristics of the hydrologic predictions by answering the following questions: (1) How do the precipitation errors associated with the TMPA-RT product transform into streamflow errors with respect to geographical and climatological characteristics? (2) How do streamflow errors vary across scales within a basin?

Spatial Variability in Column CO2 Inferred from High Resolution GEOS-5 Global Model Simulations: Implications for Remote Sensing and Inversions

Science.gov (United States)

Ott, L.; Putman, B.; Collatz, J.; Gregg, W.

2012-01-01

Column CO2 observations from current and future remote sensing missions represent a major advancement in our understanding of the carbon cycle and are expected to help constrain source and sink distributions. However, data assimilation and inversion methods are challenged by the difference in scale of models and observations. OCO-2 footprints represent an area of several square kilometers while NASA s future ASCENDS lidar mission is likely to have an even smaller footprint. In contrast, the resolution of models used in global inversions are typically hundreds of kilometers wide and often cover areas that include combinations of land, ocean and coastal areas and areas of significant topographic, land cover, and population density variations. To improve understanding of scales of atmospheric CO2 variability and representativeness of satellite observations, we will present results from a global, 10-km simulation of meteorology and atmospheric CO2 distributions performed using NASA s GEOS-5 general circulation model. This resolution, typical of mesoscale atmospheric models, represents an order of magnitude increase in resolution over typical global simulations of atmospheric composition allowing new insight into small scale CO2 variations across a wide range of surface flux and meteorological conditions. The simulation includes high resolution flux datasets provided by NASA s Carbon Monitoring System Flux Pilot Project at half degree resolution that have been down-scaled to 10-km using remote sensing datasets. Probability distribution functions are calculated over larger areas more typical of global models (100-400 km) to characterize subgrid-scale variability in these models. Particular emphasis is placed on coastal regions and regions containing megacities and fires to evaluate the ability of coarse resolution models to represent these small scale features. Additionally, model output are sampled using averaging kernels characteristic of OCO-2 and ASCENDS measurement

Evaluation of drought propagation in an ensemble mean of large-scale hydrological models

Directory of Open Access Journals (Sweden)

A. F. Van Loon

2012-11-01

Full Text Available Hydrological drought is increasingly studied using large-scale models. It is, however, not sure whether large-scale models reproduce the development of hydrological drought correctly. The pressing question is how well do large-scale models simulate the propagation from meteorological to hydrological drought? To answer this question, we evaluated the simulation of drought propagation in an ensemble mean of ten large-scale models, both land-surface models and global hydrological models, that participated in the model intercomparison project of WATCH (WaterMIP. For a selection of case study areas, we studied drought characteristics (number of droughts, duration, severity, drought propagation features (pooling, attenuation, lag, lengthening, and hydrological drought typology (classical rainfall deficit drought, rain-to-snow-season drought, wet-to-dry-season drought, cold snow season drought, warm snow season drought, composite drought.

Drought characteristics simulated by large-scale models clearly reflected drought propagation; i.e. drought events became fewer and longer when moving through the hydrological cycle. However, more differentiation was expected between fast and slowly responding systems, with slowly responding systems having fewer and longer droughts in runoff than fast responding systems. This was not found using large-scale models. Drought propagation features were poorly reproduced by the large-scale models, because runoff reacted immediately to precipitation, in all case study areas. This fast reaction to precipitation, even in cold climates in winter and in semi-arid climates in summer, also greatly influenced the hydrological drought typology as identified by the large-scale models. In general, the large-scale models had the correct representation of drought types, but the percentages of occurrence had some important mismatches, e.g. an overestimation of classical rainfall deficit droughts, and an

Ozone Production in Global Tropospheric Models: Quantifying Errors due to Grid Resolution

Science.gov (United States)

Wild, O.; Prather, M. J.

2005-12-01

Ozone production in global chemical models is dependent on model resolution because ozone chemistry is inherently nonlinear, the timescales for chemical production are short, and precursors are artificially distributed over the spatial scale of the model grid. In this study we examine the sensitivity of ozone, its precursors, and its production to resolution by running a global chemical transport model at four different resolutions between T21 (5.6° × 5.6°) and T106 (1.1° × 1.1°) and by quantifying the errors in regional and global budgets. The sensitivity to vertical mixing through the parameterization of boundary layer turbulence is also examined. We find less ozone production in the boundary layer at higher resolution, consistent with slower chemical production in polluted emission regions and greater export of precursors. Agreement with ozonesonde and aircraft measurements made during the NASA TRACE-P campaign over the Western Pacific in spring 2001 is consistently better at higher resolution. We demonstrate that the numerical errors in transport processes at a given resolution converge geometrically for a tracer at successively higher resolutions. The convergence in ozone production on progressing from T21 to T42, T63 and T106 resolution is likewise monotonic but still indicates large errors at 120~km scales, suggesting that T106 resolution is still too coarse to resolve regional ozone production. Diagnosing the ozone production and precursor transport that follow a short pulse of emissions over East Asia in springtime allows us to quantify the impacts of resolution on both regional and global ozone. Production close to continental emission regions is overestimated by 27% at T21 resolution, by 13% at T42 resolution, and by 5% at T106 resolution, but subsequent ozone production in the free troposphere is less significantly affected.

The (in)effectiveness of Global Land Policies on Large-Scale Land Acquisition

NARCIS (Netherlands)

Verhoog, S.M.

2014-01-01

Due to current crises, large-scale land acquisition (LSLA) is becoming a topic of growing concern. Public data from the ‘Land Matrix Global Observatory’ project (Land Matrix 2014a) demonstrates that since 2000, 1,664 large-scale land transactions in low- and middle-income countries were reported,

Global model structures for ∗-modules

DEFF Research Database (Denmark)

Böhme, Benjamin

2018-01-01

We extend Schwede's work on the unstable global homotopy theory of orthogonal spaces and L-spaces to the category of ∗-modules (i.e., unstable S-modules). We prove a theorem which transports model structures and their properties from L-spaces to ∗-modules and show that the resulting global model...... structure for ∗-modules is monoidally Quillen equivalent to that of orthogonal spaces. As a consequence, there are induced Quillen equivalences between the associated model categories of monoids, which identify equivalent models for the global homotopy theory of A∞-spaces....

The sensitivity of the atmospheric branch of the global water cycle to temperature fluctuations at synoptic to decadal time-scales in different satellite- and model-based products

Science.gov (United States)

Nogueira, Miguel

2018-02-01

Spectral analysis of global-mean precipitation, P, evaporation, E, precipitable water, W, and surface temperature, Ts, revealed significant variability from sub-daily to multi-decadal time-scales, superposed on high-amplitude diurnal and yearly peaks. Two distinct regimes emerged from a transition in the spectral exponents, β. The weather regime covering time-scales 1-2 years, while at time-scales global-ocean and full-globe averages, ρDCCA showed large spread of the C-C importance for P and E variability amongst different datasets at multi-year time-scales, ranging from negligible (governing mechanisms.

The magnitude and causes of uncertainty in global model simulations of cloud condensation nuclei

Directory of Open Access Journals (Sweden)

L. A. Lee

2013-09-01

Full Text Available Aerosol–cloud interaction effects are a major source of uncertainty in climate models so it is important to quantify the sources of uncertainty and thereby direct research efforts. However, the computational expense of global aerosol models has prevented a full statistical analysis of their outputs. Here we perform a variance-based analysis of a global 3-D aerosol microphysics model to quantify the magnitude and leading causes of parametric uncertainty in model-estimated present-day concentrations of cloud condensation nuclei (CCN. Twenty-eight model parameters covering essentially all important aerosol processes, emissions and representation of aerosol size distributions were defined based on expert elicitation. An uncertainty analysis was then performed based on a Monte Carlo-type sampling of an emulator built for each model grid cell. The standard deviation around the mean CCN varies globally between about ±30% over some marine regions to ±40–100% over most land areas and high latitudes, implying that aerosol processes and emissions are likely to be a significant source of uncertainty in model simulations of aerosol–cloud effects on climate. Among the most important contributors to CCN uncertainty are the sizes of emitted primary particles, including carbonaceous combustion particles from wildfires, biomass burning and fossil fuel use, as well as sulfate particles formed on sub-grid scales. Emissions of carbonaceous combustion particles affect CCN uncertainty more than sulfur emissions. Aerosol emission-related parameters dominate the uncertainty close to sources, while uncertainty in aerosol microphysical processes becomes increasingly important in remote regions, being dominated by deposition and aerosol sulfate formation during cloud-processing. The results lead to several recommendations for research that would result in improved modelling of cloud–active aerosol on a global scale.

Improved simulation of tropospheric ozone by a global-multi-regional two-way coupling model system

Directory of Open Access Journals (Sweden)

Y. Yan

2016-02-01

Full Text Available Small-scale nonlinear chemical and physical processes over pollution source regions affect the tropospheric ozone (O3, but these processes are not captured by current global chemical transport models (CTMs and chemistry–climate models that are limited by coarse horizontal resolutions (100–500 km, typically 200 km. These models tend to contain large (and mostly positive tropospheric O3 biases in the Northern Hemisphere. Here we use the recently built two-way coupling system of the GEOS-Chem CTM to simulate the regional and global tropospheric O3 in 2009. The system couples the global model (at 2.5° long.  ×  2° lat. and its three nested models (at 0.667° long.  ×  0.5° lat. covering Asia, North America and Europe, respectively. Specifically, the nested models take lateral boundary conditions (LBCs from the global model, better capture small-scale processes and feed back to modify the global model simulation within the nested domains, with a subsequent effect on their LBCs. Compared to the global model alone, the two-way coupled system better simulates the tropospheric O3 both within and outside the nested domains, as found by evaluation against a suite of ground (1420 sites from the World Data Centre for Greenhouse Gases (WDCGG, the United States National Oceanic and Atmospheric Administration (NOAA Earth System Research Laboratory Global Monitoring Division (GMD, the Chemical Coordination Centre of European Monitoring and Evaluation Programme (EMEP, and the United States Environmental Protection Agency Air Quality System (AQS, aircraft (the High-performance Instrumented Airborne Platform for Environmental Research (HIAPER Pole-to-Pole Observations (HIPPO and Measurement of Ozone and Water Vapor by Airbus In- Service Aircraft (MOZAIC and satellite measurements (two Ozone Monitoring Instrument (OMI products. The two-way coupled simulation enhances the correlation in day-to-day variation of afternoon mean surface O3

GLOBOX : A spatially differentiated global fate, intake and effect model for toxicity assessment in LCA

NARCIS (Netherlands)

Wegener Sleeswijk, Anneke; Heijungs, Reinout

GLOBOX is a model for the calculation of spatially differentiated LCA toxicity characterisation factors on a global scale. It can also be used for human and environmental risk assessment. The GLOBOX model contains equations for the calculation of fate, intake and effect factors, and equations for

A mesoscale chemical transport model (MEDIUM) nested in a global chemical transport model (MEDIANTE)

Energy Technology Data Exchange (ETDEWEB)

Claveau, J; Ramaroson, R [Office National d` Etudes et de Recherches Aerospatiales (ONERA), 92 - Chatillon (France)

1998-12-31

The lower stratosphere and upper troposphere (UT-LS) are frequently subject to mesoscale or local scale exchange of air masses occurring along discontinuities. This exchange (e.g. downward) can constitute one of the most important source of ozone from the stratosphere down to the middle troposphere where strong mixing dilutes the air mass and competing the non-linear chemistry. The distribution of the chemical species in the troposphere and the lower stratosphere depends upon various source emissions, e.g. from polluted boundary layer or from aircraft emissions. Global models, as well as chemical transport models describe the climatological state of the atmosphere and are not able to describe correctly the stratosphere and troposphere exchange. Mesoscale models go further in the description of smaller scales and can reasonably include a rather detailed chemistry. They can be used to assess the budget of NO{sub x} from aircraft emissions in a mesoscale domain. (author) 4 refs.

A mesoscale chemical transport model (MEDIUM) nested in a global chemical transport model (MEDIANTE)

Energy Technology Data Exchange (ETDEWEB)

Claveau, J.; Ramaroson, R. [Office National d`Etudes et de Recherches Aerospatiales (ONERA), 92 - Chatillon (France)

1997-12-31

The lower stratosphere and upper troposphere (UT-LS) are frequently subject to mesoscale or local scale exchange of air masses occurring along discontinuities. This exchange (e.g. downward) can constitute one of the most important source of ozone from the stratosphere down to the middle troposphere where strong mixing dilutes the air mass and competing the non-linear chemistry. The distribution of the chemical species in the troposphere and the lower stratosphere depends upon various source emissions, e.g. from polluted boundary layer or from aircraft emissions. Global models, as well as chemical transport models describe the climatological state of the atmosphere and are not able to describe correctly the stratosphere and troposphere exchange. Mesoscale models go further in the description of smaller scales and can reasonably include a rather detailed chemistry. They can be used to assess the budget of NO{sub x} from aircraft emissions in a mesoscale domain. (author) 4 refs.

Should Global Items on Student Rating Scales Be Used for Summative Decisions?

Science.gov (United States)

Berk, Ronald A.

2013-01-01

One of the simplest indicators of teaching or course effectiveness is student ratings on one or more global items from the entire rating scale. That approach seems intuitively sound and easy to use. Global items have even been recommended by a few researchers to get a quick-read, at-a-glance summary for summative decisions about faculty. The…

Phosphorus in agricultural soils: drivers of its distribution at the global scale

Energy Technology Data Exchange (ETDEWEB)

Ringeval, Bruno [ISPA, Villenave d' Ornon (France); Augusto, Laurent [ISPA, Villenave d' Ornon (France); Monod, Herve [Univ. Paris-Saclay, Jouy-en-Josas (France); van Apeldoorn, Dirk [Utrecht Univ., Utrecht (The Netherlands); Bouwman, Lex [Utrecht Univ., Utrecht (The Netherlands); Yang, Xiaojuan [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Achat, David L. [ISPA, Villenave d' Ornon (France); Chini, Louise P. [Univ. of Maryland, College Park, MD (United States); Van Oost, Kristof [Univ. Catholique de Louvain, Louvain-la-Neuve (Belgium); Guenet, Bertrand [Univ. Paris-Saclay, Gif-sur-Yvette (France); Wang, Rong [Univ. Paris-Saclay, Gif-sur-Yvette (France); Peking Univ., Beijing (China); Decharme, Bertrand [CNRS/Meteo-France, Toulouse (France); Nesme, Thomas [ISPA, Villenave d' Ornon (France); Pellerin, Sylvain [ISPA, Villenave d' Ornon (France)

2017-01-09

Phosphorus (P) availability in soils limits crop yields in many regions of the world, while excess of soil P triggers aquatic eutrophication in other regions. Numerous processes drive the global spatial distribution of P in agricultural soils, but their relative roles remain unclear. Here, we combined several global datasets describing these drivers with a soil P dynamics model to simulate the distribution of P in agricultural soils and to assess the contributions of the different drivers at the global scale. We analyzed both the labile inorganic P (P_ILAB), a proxy of the pool involved in plant nutrition and the total soil P (P_TOT). We found that the soil biogeochemical background (BIOG) and farming practices (FARM) were the main drivers of the spatial variability in cropland soil P content but that their contribution varied between P_TOT vs P_ILAB. Indeed, 97% of the P_TOT spatial variability could be explained by BIOG, while BIOG and FARM explained 41% and 58% of P_ILAB spatial variability, respectively. Other drivers such as climate, soil erosion, atmospheric P deposition and soil buffering capacity made only very small contribution. Lastly, our study is a promising approach to investigate the potential effect of P as a limiting factor for agricultural ecosystems and for global food production. Additionally, we quantified the anthropogenic perturbation of P cycle and demonstrated how the different drivers are combined to explain the global distribution of agricultural soil P.

Incorporating nitrogen fixing cyanobacteria in the global biogeochemical model HAMOCC

Science.gov (United States)

Paulsen, Hanna; Ilyina, Tatiana; Six, Katharina

2015-04-01

Nitrogen fixation by marine diazotrophs plays a fundamental role in the oceanic nitrogen and carbon cycle as it provides a major source of 'new' nitrogen to the euphotic zone that supports biological carbon export and sequestration. Since most global biogeochemical models include nitrogen fixation only diagnostically, they are not able to capture its spatial pattern sufficiently. Here we present the incorporation of an explicit, dynamic representation of diazotrophic cyanobacteria and the corresponding nitrogen fixation in the global ocean biogeochemical model HAMOCC (Hamburg Ocean Carbon Cycle model), which is part of the Max Planck Institute for Meteorology Earth system model (MPI-ESM). The parameterization of the diazotrophic growth is thereby based on available knowledge about the cyanobacterium Trichodesmium spp., which is considered as the most significant pelagic nitrogen fixer. Evaluation against observations shows that the model successfully reproduces the main spatial distribution of cyanobacteria and nitrogen fixation, covering large parts of the tropical and subtropical oceans. Besides the role of cyanobacteria in marine biogeochemical cycles, their capacity to form extensive surface blooms induces a number of bio-physical feedback mechanisms in the Earth system. The processes driving these interactions, which are related to the alteration of heat absorption, surface albedo and momentum input by wind, are incorporated in the biogeochemical and physical model of the MPI-ESM in order to investigate their impacts on a global scale. First preliminary results will be shown.

Regional and urban down scaling of global climate scenarios for health impact assessments

Energy Technology Data Exchange (ETDEWEB)

San Jose, R.; Perez, J. L.; Perez, L.; Gonzalez, R. M.; Pecci, J.; Garzon, A.; Palacios, M.

2015-07-01

In this contribution we have used global climate RCP IPCC scenarios to produce climate and air pollution maps at regional (25 km resolution) and urban scale with 200 m spatial resolution over Europe and five European cities in order to investigate the impact on meteorological variables and pollutant concentrations . We have used the very well known mesoscale meteorological model WRF-Chem (NOAA, US). We have used 2011 as control past year and two RCP scenarios from CCSM global climate model with 4.5 W/m2 and 8.5 W/m2 for 2030, 2050 and 2100 years. After running WRF-Chem model, using the boundary conditions provided by RCP scenarios with the emissions of 2011, we have performed a detailed down scaling process using CALMET diagnostic model to obtain a full 200 m spatial resolution map of five European cities (London, Antwerp, Madrid, Milan, and Helsinki). We will show the results and the health impacts for future RCP IPCC climate scenarios in comparison with the 2011 control year information for climate and health indicators. Finally, we have also investigated the impact of the aerosol effects in the short wave radiation mean value. Two simulations with the WRF-Chem model have been performed over Europe in 2010. A baseline simulation without any feedback effects and a second simulation including the direct effects affecting the solar radiation reaching the surface as well as the indirect aerosol effect with potential impacts on increasing or decreasing the precipitation rates. Aerosol effects produce an increase of incoming radiation over Atlantic Ocean (up to 70%) because the prescribed aerosol concentrations in the WRF-Chem without feedbacks is substantially higher than the aerosol concentrations produced when we activate the feedback effects. The decrease in solar radiation in the Sahara area (10%) is found to be produced because the prescribed aerosol concentration in the no feedback simulation is lower than when we activate the feedback effects. (Author)

Global Stability of Complex-Valued Genetic Regulatory Networks with Delays on Time Scales

Directory of Open Access Journals (Sweden)

Wang Yajing

2016-01-01

Full Text Available In this paper, the global exponential stability of complex-valued genetic regulatory networks with delays is investigated. Besides presenting conditions guaranteeing the existence of a unique equilibrium pattern, its global exponential stability is discussed. Some numerical examples for different time scales.

Multiresolution comparison of precipitation datasets for large-scale models

Science.gov (United States)

Chun, K. P.; Sapriza Azuri, G.; Davison, B.; DeBeer, C. M.; Wheater, H. S.

2014-12-01

Gridded precipitation datasets are crucial for driving large-scale models which are related to weather forecast and climate research. However, the quality of precipitation products is usually validated individually. Comparisons between gridded precipitation products along with ground observations provide another avenue for investigating how the precipitation uncertainty would affect the performance of large-scale models. In this study, using data from a set of precipitation gauges over British Columbia and Alberta, we evaluate several widely used North America gridded products including the Canadian Gridded Precipitation Anomalies (CANGRD), the National Center for Environmental Prediction (NCEP) reanalysis, the Water and Global Change (WATCH) project, the thin plate spline smoothing algorithms (ANUSPLIN) and Canadian Precipitation Analysis (CaPA). Based on verification criteria for various temporal and spatial scales, results provide an assessment of possible applications for various precipitation datasets. For long-term climate variation studies (~100 years), CANGRD, NCEP, WATCH and ANUSPLIN have different comparative advantages in terms of their resolution and accuracy. For synoptic and mesoscale precipitation patterns, CaPA provides appealing performance of spatial coherence. In addition to the products comparison, various downscaling methods are also surveyed to explore new verification and bias-reduction methods for improving gridded precipitation outputs for large-scale models.

Irrational Delay Revisited: Examining Five Procrastination Scales in a Global Sample.

Science.gov (United States)

Svartdal, Frode; Steel, Piers

2017-01-01

Scales attempting to measure procrastination focus on different facets of the phenomenon, yet they share a common understanding of procrastination as an unnecessary, unwanted, and disadvantageous delay. The present paper examines in a global sample ( N = 4,169) five different procrastination scales - Decisional Procrastination Scale (DPS), Irrational Procrastination Scale (IPS), Pure Procrastination Scale (PPS), Adult Inventory of Procrastination Scale (AIP), and General Procrastination Scale (GPS), focusing on factor structures and item functioning using Confirmatory Factor Analysis and Item Response Theory. The results indicated that The PPS (12 items selected from DPS, AIP, and GPS) measures different facets of procrastination even better than the three scales it is based on. An even shorter version of the PPS (5 items focusing on irrational delay), corresponds well to the nine-item IPS. Both scales demonstrate good psychometric properties and appear to be superior measures of core procrastination attributes than alternative procrastination scales.

Towards systematic evaluation of crop model outputs for global land-use models

Science.gov (United States)

Leclere, David; Azevedo, Ligia B.; Skalský, Rastislav; Balkovič, Juraj; Havlík, Petr

2016-04-01

Land provides vital socioeconomic resources to the society, however at the cost of large environmental degradations. Global integrated models combining high resolution global gridded crop models (GGCMs) and global economic models (GEMs) are increasingly being used to inform sustainable solution for agricultural land-use. However, little effort has yet been done to evaluate and compare the accuracy of GGCM outputs. In addition, GGCM datasets require a large amount of parameters whose values and their variability across space are weakly constrained: increasing the accuracy of such dataset has a very high computing cost. Innovative evaluation methods are required both to ground credibility to the global integrated models, and to allow efficient parameter specification of GGCMs. We propose an evaluation strategy for GGCM datasets in the perspective of use in GEMs, illustrated with preliminary results from a novel dataset (the Hypercube) generated by the EPIC GGCM and used in the GLOBIOM land use GEM to inform on present-day crop yield, water and nutrient input needs for 16 crops x 15 management intensities, at a spatial resolution of 5 arc-minutes. We adopt the following principle: evaluation should provide a transparent diagnosis of model adequacy for its intended use. We briefly describe how the Hypercube data is generated and how it articulates with GLOBIOM in order to transparently identify the performances to be evaluated, as well as the main assumptions and data processing involved. Expected performances include adequately representing the sub-national heterogeneity in crop yield and input needs: i) in space, ii) across crop species, and iii) across management intensities. We will present and discuss measures of these expected performances and weight the relative contribution of crop model, input data and data processing steps in performances. We will also compare obtained yield gaps and main yield-limiting factors against the M3 dataset. Next steps include

On coupling global biome models with climate models

International Nuclear Information System (INIS)

Claussen, M.

1994-01-01

The BIOME model of Prentice et al. (1992), which predicts global vegetation patterns in equilibrium with climate, is coupled with the ECHAM climate model of the Max-Planck-Institut fuer Meteorologie, Hamburg. It is found that incorporation of the BIOME model into ECHAM, regardless at which frequency, does not enhance the simulated climate variability, expressed in terms of differences between global vegetation patterns. Strongest changes are seen only between the initial biome distribution and the biome distribution computed after the first simulation period, provided that the climate-biome model is started from a biome distribution that resembles the present-day distribution. After the first simulation period, there is no significant shrinking, expanding, or shifting of biomes. Likewise, no trend is seen in global averages of land-surface parameters and climate variables. (orig.)

Environmental Impacts of Large Scale Biochar Application Through Spatial Modeling

Science.gov (United States)

Huber, I.; Archontoulis, S.

2017-12-01

In an effort to study the environmental (emissions, soil quality) and production (yield) impacts of biochar application at regional scales we coupled the APSIM-Biochar model with the pSIMS parallel platform. So far the majority of biochar research has been concentrated on lab to field studies to advance scientific knowledge. Regional scale assessments are highly needed to assist decision making. The overall objective of this simulation study was to identify areas in the USA that have the most gain environmentally from biochar's application, as well as areas which our model predicts a notable yield increase due to the addition of biochar. We present the modifications in both APSIM biochar and pSIMS components that were necessary to facilitate these large scale model runs across several regions in the United States at a resolution of 5 arcminutes. This study uses the AgMERRA global climate data set (1980-2010) and the Global Soil Dataset for Earth Systems modeling as a basis for creating its simulations, as well as local management operations for maize and soybean cropping systems and different biochar application rates. The regional scale simulation analysis is in progress. Preliminary results showed that the model predicts that high quality soils (particularly those common to Iowa cropping systems) do not receive much, if any, production benefit from biochar. However, soils with low soil organic matter ( 0.5%) do get a noteworthy yield increase of around 5-10% in the best cases. We also found N2O emissions to be spatial and temporal specific; increase in some areas and decrease in some other areas due to biochar application. In contrast, we found increases in soil organic carbon and plant available water in all soils (top 30 cm) due to biochar application. The magnitude of these increases (% change from the control) were larger in soil with low organic matter (below 1.5%) and smaller in soils with high organic matter (above 3%) and also dependent on biochar

On coupling global biome models with climate models

OpenAIRE

Claussen, M.

1994-01-01

The BIOME model of Prentice et al. (1992; J. Biogeogr. 19: 117-134), which predicts global vegetation patterns in equilibrium with climate, was coupled with the ECHAM climate model of the Max-Planck-Institut fiir Meteorologie, Hamburg, Germany. It was found that incorporation of the BIOME model into ECHAM, regardless at which frequency, does not enhance the simulated climate variability, expressed in terms of differences between global vegetation patterns. Strongest changes are seen only betw...

Global water balances reconstructed by multi-model offline simulations of land surface models under GSWP3 (Invited)

Science.gov (United States)

Oki, T.; KIM, H.; Ferguson, C. R.; Dirmeyer, P.; Seneviratne, S. I.

2013-12-01

As the climate warms, the frequency and severity of flood and drought events is projected to increase. Understanding the role that the land surface will play in reinforcing or diminishing these extremes at regional scales will become critical. In fact, the current development path from atmospheric (GCM) to coupled atmosphere-ocean (AOGCM) to fully-coupled dynamic earth system models (ESMs) has brought new awareness to the climate modeling community of the abundance of uncertainty in land surface parameterizations. One way to test the representativeness of a land surface scheme is to do so in off-line (uncoupled) mode with controlled, high quality meteorological forcing. When multiple land schemes are run in-parallel (with the same forcing data), an inter-comparison of their outputs can provide the basis for model confidence estimates and future model refinements. In 2003, the Global Soil Wetness Project Phase 2 (GSWP2) provided the first global multi-model analysis of land surface state variables and fluxes. It spanned the decade of 1986-1995. While it was state-of-the art at the time, physical schemes have since been enhanced, a number of additional processes and components in the water-energy-eco-systems nexus can now be simulated, , and the availability of global, long-term observationally-based datasets that can be used for forcing and validating models has grown. Today, the data exists to support century-scale off-line experiments. The ongoing follow-on to GSWP2, named GSWP3, capitalizes on these new feasibilities and model functionalities. The project's cornerstone is its century-scale (1901-2010), 3-hourly, 0.5° meteorological forcing dataset that has been dynamically downscaled from the Twentieth Century Reanalysis and bias-corrected using monthly Climate Research Unit (CRU) temperature and Global Precipitation Climatology Centre (GPCC) precipitation data. However, GSWP3 also has an important long-term future climate component that spans the 21st century

Large-scale Modeling of Nitrous Oxide Production: Issues of Representing Spatial Heterogeneity

Science.gov (United States)

Morris, C. K.; Knighton, J.

2017-12-01

Nitrous oxide is produced from the biological processes of nitrification and denitrification in terrestrial environments and contributes to the greenhouse effect that warms Earth's climate. Large scale modeling can be used to determine how global rate of nitrous oxide production and consumption will shift under future climates. However, accurate modeling of nitrification and denitrification is made difficult by highly parameterized, nonlinear equations. Here we show that the representation of spatial heterogeneity in inputs, specifically soil moisture, causes inaccuracies in estimating the average nitrous oxide production in soils. We demonstrate that when soil moisture is averaged from a spatially heterogeneous surface, net nitrous oxide production is under predicted. We apply this general result in a test of a widely-used global land surface model, the Community Land Model v4.5. The challenges presented by nonlinear controls on nitrous oxide are highlighted here to provide a wider context to the problem of extraordinary denitrification losses in CLM. We hope that these findings will inform future researchers on the possibilities for model improvement of the global nitrogen cycle.

Modeling sediment yield in small catchments at event scale: Model comparison, development and evaluation

Science.gov (United States)

Tan, Z.; Leung, L. R.; Li, H. Y.; Tesfa, T. K.

2017-12-01

Sediment yield (SY) has significant impacts on river biogeochemistry and aquatic ecosystems but it is rarely represented in Earth System Models (ESMs). Existing SY models focus on estimating SY from large river basins or individual catchments so it is not clear how well they simulate SY in ESMs at larger spatial scales and globally. In this study, we compare the strengths and weaknesses of eight well-known SY models in simulating annual mean SY at about 400 small catchments ranging in size from 0.22 to 200 km2 in the US, Canada and Puerto Rico. In addition, we also investigate the performance of these models in simulating event-scale SY at six catchments in the US using high-quality hydrological inputs. The model comparison shows that none of the models can reproduce the SY at large spatial scales but the Morgan model performs the better than others despite its simplicity. In all model simulations, large underestimates occur in catchments with very high SY. A possible pathway to reduce the discrepancies is to incorporate sediment detachment by landsliding, which is currently not included in the models being evaluated. We propose a new SY model that is based on the Morgan model but including a landsliding soil detachment scheme that is being developed. Along with the results of the model comparison and evaluation, preliminary findings from the revised Morgan model will be presented.

Act local, think global: how the Malawi experience of scaling up antiretroviral treatment has informed global policy

Directory of Open Access Journals (Sweden)

Anthony D. Harries

2016-09-01

Full Text Available Abstract The scale-up of antiretroviral therapy (ART in Malawi was based on a public health approach adapted to its resource-poor setting, with principles and practices borrowed from the successful tuberculosis control framework. From 2004 to 2015, the number of new patients started on ART increased from about 3000 to over 820,000. Despite being a small country, Malawi has made a significant contribution to the 15 million people globally on ART and has also contributed policy and service delivery innovations that have supported international guidelines and scale up in other countries. The first set of global guidelines for scaling up ART released by the World Health Organization (WHO in 2002 focused on providing clinical guidance. In Malawi, the ART guidelines adopted from the outset a more operational and programmatic approach with recommendations on health systems and services that were needed to deliver HIV treatment to affected populations. Seven years after the start of national scale-up, Malawi launched a new strategy offering all HIV-infected pregnant women lifelong ART regardless of the CD4-cell count, named Option B+. This strategy was subsequently incorporated into a WHO programmatic guide in 2012 and WHO ART guidelines in 2013, and has since then been adopted by the majority of countries worldwide. In conclusion, the Malawi experience of ART scale-up has become a blueprint for a public health response to HIV and has informed international efforts to end the AIDS epidemic by 2030.

Act local, think global: how the Malawi experience of scaling up antiretroviral treatment has informed global policy.

Science.gov (United States)

Harries, Anthony D; Ford, Nathan; Jahn, Andreas; Schouten, Erik J; Libamba, Edwin; Chimbwandira, Frank; Maher, Dermot

2016-09-06

The scale-up of antiretroviral therapy (ART) in Malawi was based on a public health approach adapted to its resource-poor setting, with principles and practices borrowed from the successful tuberculosis control framework. From 2004 to 2015, the number of new patients started on ART increased from about 3000 to over 820,000. Despite being a small country, Malawi has made a significant contribution to the 15 million people globally on ART and has also contributed policy and service delivery innovations that have supported international guidelines and scale up in other countries. The first set of global guidelines for scaling up ART released by the World Health Organization (WHO) in 2002 focused on providing clinical guidance. In Malawi, the ART guidelines adopted from the outset a more operational and programmatic approach with recommendations on health systems and services that were needed to deliver HIV treatment to affected populations. Seven years after the start of national scale-up, Malawi launched a new strategy offering all HIV-infected pregnant women lifelong ART regardless of the CD4-cell count, named Option B+. This strategy was subsequently incorporated into a WHO programmatic guide in 2012 and WHO ART guidelines in 2013, and has since then been adopted by the majority of countries worldwide. In conclusion, the Malawi experience of ART scale-up has become a blueprint for a public health response to HIV and has informed international efforts to end the AIDS epidemic by 2030.

A hydroclimatic model of global fire patterns

Science.gov (United States)

Boer, Matthias

2015-04-01

Satellite-based earth observation is providing an increasingly accurate picture of global fire patterns. The highest fire activity is observed in seasonally dry (sub-)tropical environments of South America, Africa and Australia, but fires occur with varying frequency, intensity and seasonality in almost all biomes on Earth. The particular combination of these fire characteristics, or fire regime, is known to emerge from the combined influences of climate, vegetation, terrain and land use, but has so far proven difficult to reproduce by global models. Uncertainty about the biophysical drivers and constraints that underlie current global fire patterns is propagated in model predictions of how ecosystems, fire regimes and biogeochemical cycles may respond to projected future climates. Here, I present a hydroclimatic model of global fire patterns that predicts the mean annual burned area fraction (F) of 0.25° x 0.25° grid cells as a function of the climatic water balance. Following Bradstock's four-switch model, long-term fire activity levels were assumed to be controlled by fuel productivity rates and the likelihood that the extant fuel is dry enough to burn. The frequency of ignitions and favourable fire weather were assumed to be non-limiting at long time scales. Fundamentally, fuel productivity and fuel dryness are a function of the local water and energy budgets available for the production and desiccation of plant biomass. The climatic water balance summarizes the simultaneous availability of biologically usable energy and water at a site, and may therefore be expected to explain a significant proportion of global variation in F. To capture the effect of the climatic water balance on fire activity I focused on the upper quantiles of F, i.e. the maximum level of fire activity for a given climatic water balance. Analysing GFED4 data for annual burned area together with gridded climate data, I found that nearly 80% of the global variation in the 0.99 quantile of F

Recent Progresses in Incorporating Human Land-Water Management into Global Land Surface Models Toward Their Integration into Earth System Models

Science.gov (United States)

Pokhrel, Yadu N.; Hanasaki, Naota; Wada, Yoshihide; Kim, Hyungjun

2016-01-01

The global water cycle has been profoundly affected by human land-water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land-water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large-scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large-scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land-water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human-water interactions within the Earths system.

Gap models and their individual-based relatives in the assessment of the consequences of global change

Science.gov (United States)

Shugart, Herman H.; Wang, Bin; Fischer, Rico; Ma, Jianyong; Fang, Jing; Yan, Xiaodong; Huth, Andreas; Armstrong, Amanda H.

2018-03-01

Individual-based models (IBMs) of complex systems emerged in the 1960s and early 1970s, across diverse disciplines from astronomy to zoology. Ecological IBMs arose with seemingly independent origins out of the tradition of understanding the ecosystems dynamics of ecosystems from a ‘bottom-up’ accounting of the interactions of the parts. Individual trees are principal among the parts of forests. Because these models are computationally demanding, they have prospered as the power of digital computers has increased exponentially over the decades following the 1970s. This review will focus on a class of forest IBMs called gap models. Gap models simulate the changes in forests by simulating the birth, growth and death of each individual tree on a small plot of land. The summation of these plots comprise a forest (or set of sample plots on a forested landscape or region). Other, more aggregated forest IBMs have been used in global applications including cohort-based models, ecosystem demography models, etc. Gap models have been used to provide the parameters for these bulk models. Currently, gap models have grown from local-scale to continental-scale and even global-scale applications to assess the potential consequences of climate change on natural forests. Modifications to the models have enabled simulation of disturbances including fire, insect outbreak and harvest. Our objective in this review is to provide the reader with an overview of the history, motivation and applications, including theoretical applications, of these models. In a time of concern over global changes, gap models are essential tools to understand forest responses to climate change, modified disturbance regimes and other change agents. Development of forest surveys to provide the starting points for simulations and better estimates of the behavior of the diversity of tree species in response to the environment are continuing needs for improvement for these and other IBMs.

"Annotated Lectures": Student-Instructor Interaction in Large-Scale Global Education

Directory of Open Access Journals (Sweden)

Roger Diehl

2009-10-01

Full Text Available We describe an "Annotated Lectures" system, which will be used in a global virtual teaching and student collaboration event on embodied intelligence presented by the University of Zurich. The lectures will be broadcasted via video-conference to lecture halls of different universities around the globe. Among other collaboration features, an "Annotated Lectures" system will be implemented in a 3D collaborative virtual environment and used by the participating students to make annotations to the video-recorded lectures, which will be sent to and answered by their supervisors, and forwarded to the lecturers in an aggregated way. The "Annotated Lectures" system aims to overcome the issues of limited studentinstructor interaction in large-scale education, and to foster an intercultural and multidisciplinary discourse among students who review the lectures in a group. After presenting the concept of the "Annotated Lectures" system, we discuss a prototype version including a description of the technical components and its expected benefit for large-scale global education.

Land cover change or land use intensification: simulating land system change with a global-scale land change model

NARCIS (Netherlands)

van Asselen, S.; Verburg, P.H.

2013-01-01

Land-use change is both a cause and consequence of many biophysical and socioeconomic changes. The CLUMondo model provides an innovative approach for global land-use change modeling to support integrated assessments. Demands for goods and services are, in the model, supplied by a variety of land

Quantifying the role of fire in the Earth system – Part 1: Improved global fire modeling in the Community Earth System Model (CESM1)

OpenAIRE

F. Li; S. Levis; D. S. Ward

2013-01-01

Modeling fire as an integral part of an Earth system model (ESM) is vital for quantifying and understanding fire–climate–vegetation interactions on a global scale and from an Earth system perspective. In this study, we introduce to the Community Earth System Model (CESM) the new global fire parameterization proposed by Li et al. (2012a, b), now with a more realistic representation of the anthropogenic impacts on fires, with a parameterization of peat fires, and with other minor modifications....