Sample records for global scale model
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Groundwater development stress: Global-scale indices compared to regional modeling
Alley, William; Clark, Brian R.; Ely, Matt; Faunt, Claudia
2018-01-01
The increased availability of global datasets and technologies such as global hydrologic models and the Gravity Recovery and Climate Experiment (GRACE) satellites have resulted in a growing number of global-scale assessments of water availability using simple indices of water stress. Developed initially for surface water, such indices are increasingly used to evaluate global groundwater resources. We compare indices of groundwater development stress for three major agricultural areas of the United States to information available from regional water budgets developed from detailed groundwater modeling. These comparisons illustrate the potential value of regional-scale analyses to supplement global hydrological models and GRACE analyses of groundwater depletion. Regional-scale analyses allow assessments of water stress that better account for scale effects, the dynamics of groundwater flow systems, the complexities of irrigated agricultural systems, and the laws, regulations, engineering, and socioeconomic factors that govern groundwater use. Strategic use of regional-scale models with global-scale analyses would greatly enhance knowledge of the global groundwater depletion problem.
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NASA Astrophysics Data System (ADS)
Marzeion, B.; Maussion, F.
2017-12-01
Mountain glaciers are one of the few remaining sub-systems of the global climate system for which no globally applicable, open source, community-driven model exists. Notable examples from the ice sheet community include the Parallel Ice Sheet Model or Elmer/Ice. While the atmospheric modeling community has a long tradition of sharing models (e.g. the Weather Research and Forecasting model) or comparing them (e.g. the Coupled Model Intercomparison Project or CMIP), recent initiatives originating from the glaciological community show a new willingness to better coordinate global research efforts following the CMIP example (e.g. the Glacier Model Intercomparison Project or the Glacier Ice Thickness Estimation Working Group). In the recent past, great advances have been made in the global availability of data and methods relevant for glacier modeling, spanning glacier outlines, automatized glacier centerline identification, bed rock inversion methods, and global topographic data sets. Taken together, these advances now allow the ice dynamics of glaciers to be modeled on a global scale, provided that adequate modeling platforms are available. Here, we present the Open Global Glacier Model (OGGM), developed to provide a global scale, modular, and open source numerical model framework for consistently simulating past and future global scale glacier change. Global not only in the sense of leading to meaningful results for all glaciers combined, but also for any small ensemble of glaciers, e.g. at the headwater catchment scale. Modular to allow combinations of different approaches to the representation of ice flow and surface mass balance, enabling a new kind of model intercomparison. Open source so that the code can be read and used by anyone and so that new modules can be added and discussed by the community, following the principles of open governance. Consistent in order to provide uncertainty measures at all realizable scales.
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Prospects for improving the representation of coastal and shelf seas in global ocean models
NASA Astrophysics Data System (ADS)
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 < 500 m deep, but this increases to ˜ 70 % for a 1/72° model, so resolving scales globally requires substantially finer resolution than the current state of the art.We quantify the 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 multiscale modelling options (e.g. finite element, finite volume or a two-way nesting approach), we consider a simple scale analysis and a conceptual grid refining approach. We put this analysis in the context of evolving computer systems, discussing model turnaround time, scalability and resource costs. Using a simple cost model compared to a reference configuration (taken to be a 1/4° global model in 2011) and the increasing performance of the UK Research Councils' computer facility, we estimate an unstructured mesh multiscale approach, resolving process scales down to 1.5 km, would use a comparable share of the computer resource by 2021, the two-way nested multiscale approach by 2022, and a 1/72° global model by 2026. However, we also note that a 1/12° global model would not have a comparable computational cost to a 1° global model in 2017 until 2027. Hence, we conclude that for computationally expensive models (e.g. for oceanographic research or operational oceanography), resolving scales to ˜ 1.5 km would be routinely practical in about a decade given substantial effort on numerical and computational development. For complex Earth system models, this extends to about 2 decades, suggesting the focus here needs to be on improved process parameterisation to meet these challenges.
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NASA Astrophysics Data System (ADS)
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.
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Global hydrodynamic modelling of flood inundation in continental rivers: How can we achieve it?
NASA Astrophysics Data System (ADS)
Yamazaki, D.
2016-12-01
Global-scale modelling of river hydrodynamics is essential for understanding global hydrological cycle, and is also required in interdisciplinary research fields . Global river models have been developed continuously for more than two decades, but modelling river flow at a global scale is still a challenging topic because surface water movement in continental rivers is a multi-spatial-scale phenomena. We have to consider the basin-wide water balance (>1000km scale), while hydrodynamics in river channels and floodplains is regulated by much smaller-scale topography (<100m scale). For example, heavy precipitation in upstream regions may later cause flooding in farthest downstream reaches. In order to realistically simulate the timing and amplitude of flood wave propagation for a long distance, consideration of detailed local topography is unavoidable. I have developed the global hydrodynamic model CaMa-Flood to overcome this scale-discrepancy of continental river flow. The CaMa-Flood divides river basins into multiple "unit-catchments", and assumes the water level is uniform within each unit-catchment. One unit-catchment is assigned to each grid-box defined at the typical spatial resolution of global climate models (10 100 km scale). Adopting a uniform water level in a >10km river segment seems to be a big assumption, but it is actually a good approximation for hydrodynamic modelling of continental rivers. The number of grid points required for global hydrodynamic simulations is largely reduced by this "unit-catchment assumption". Alternative to calculating 2-dimensional floodplain flows as in regional flood models, the CaMa-Flood treats floodplain inundation in a unit-catchment as a sub-grid physics. The water level and inundated area in each unit-catchment are diagnosed from water volume using topography parameters derived from high-resolution digital elevation models. Thus, the CaMa-Flood is at least 1000 times computationally more efficient compared to regional flood inundation models while the reality of simulated flood dynamics is kept. I will explain in detail how the CaMa-Flood model has been constructed from high-resolution topography datasets, and how the model can be used for various interdisciplinary applications.
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NASA Astrophysics Data System (ADS)
Bronstert, Axel; Heistermann, Maik; Francke, Till
2017-04-01
Hydrological models aim at quantifying the hydrological cycle and its constituent processes for particular conditions, sites or periods in time. Such models have been developed for a large range of spatial and temporal scales. One must be aware that the question which is the appropriate scale to be applied depends on the overall question under study. Therefore, it is not advisable to give a general applicable guideline on what is "the best" scale for a model. This statement is even more relevant for coupled hydrological, ecological and atmospheric models. Although a general statement about the most appropriate modelling scale is not recommendable, it is worth to have a look on what are the advantages and the shortcomings of micro-, meso- and macro-scale approaches. Such an appraisal is of increasing importance, since increasingly (very) large / global scale approaches and models are under operation and therefore the question arises how far and for what purposes such methods may yield scientifically sound results. It is important to understand that in most hydrological (and ecological, atmospheric and other) studies process scale, measurement scale, and modelling scale differ from each other. In some cases, the differences between theses scales can be of different orders of magnitude (example: runoff formation, measurement and modelling). These differences are a major source of uncertainty in description and modelling of hydrological, ecological and atmospheric processes. Let us now summarize our viewpoint of the strengths (+) and weaknesses (-) of hydrological models of different scales: Micro scale (e.g. extent of a plot, field or hillslope): (+) enables process research, based on controlled experiments (e.g. infiltration; root water uptake; chemical matter transport); (+) data of state conditions (e.g. soil parameter, vegetation properties) and boundary fluxes (e.g. rainfall or evapotranspiration) are directly measurable and reproducible; (+) equations based on first principals, partly pde-type, are available for several processes (but not for all), because measurement and modelling scale are compatible (-) the spatial model domain are hardly representative for larger spatial entities, including regions for which water resources management decisions are to be taken; straightforward upsizing is also limited by data availability and computational requirements. Meso scale (e.g. extent of a small to large catchment or region): (+) the spatial extent of the model domain has approximately the same extent as the regions for which water resources management decisions are to be taken. I.e., such models enable water resources quantification at the scale of most water management decisions; (+) data of some state conditions (e.g. vegetation cover, topography, river network and cross sections) are available; (+) data of some boundary fluxes (in particular surface runoff / channel flow) are directly measurable with mostly sufficient certainty; (+) equations, partly based on simple water budgeting, partly variants of pde-type equations, are available for most hydrological processes. This enables the construction of meso-scale distributed models reflecting the spatial heterogeneity of regions/landscapes; (-) process scale, measurement scale, and modelling scale differ from each other for a number of processes, e.g., such as runoff generation; (-) the process formulation (usually derived from micro-scale studies) cannot directly be transferred to the modelling domain. Upscaling procedures for this purpose are not readily and generally available. Macro scale (e.g. extent of a continent up to global): (+) the spatial extent of the model may cover the whole Earth. This enables an attractive global display of model results; (+) model results might be technically interchangeable or at least comparable with results from other global models, such as global climate models; (-) process scale, measurement scale, and modelling scale differ heavily from each other for all hydrological and associated processes; (-) the model domain and its results are not representative regions for which water resources management decisions are to be taken. (-) both state condition and boundary flux data are hardly available for the whole model domain. Water management data and discharge data from remote regions are particular incomplete / unavailable for this scale. This undermines the model's verifiability; (-) since process formulation and resulting modelling reliability at this scale is very limited, such models can hardly show any explanatory skills or prognostic power; (-) since both the entire model domain and the spatial sub-units cover large areas, model results represent values averaged over at least the spatial sub-unit's extent. In many cases, the applied time scale implies a long-term averaging in time, too. We emphasize the importance to be aware of the above mentioned strengths and weaknesses of those scale-specific models. (Many of the) results of the current global model studies do not reflect such limitations. In particular, we consider the averaging over large model entities in space and/or time inadequate. Many hydrological processes are of a non-linear nature, including threshold-type behaviour. Such features cannot be reflected by such large scale entities. The model results therefore can be of little or no use for water resources decisions and/or even misleading for public debates or decision making. Some rather newly developed sustainability concepts, e.g. "Planetary Boundaries" in which humanity may "continue to develop and thrive for generations to come" are based on such global-scale approaches and models. However, many of the major problems regarding sustainability on Earth, e.g. water scarcity, do not exhibit on a global but on a regional scale. While on a global scale water might look like being available in sufficient quantity and quality, there are many regions where water problems already have very harmful or even devastating effects. Therefore, it is the challenge to derive models and observation programmes for regional scales. In case a global display is desired future efforts should be directed towards the development of a global picture based on a mosaic of regional sound assessments, rather than "zooming into" the results of large-scale simulations. Still, a key question remains to be discussed, i.e. for which purpose models at this (global) scale can be used.
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NASA Technical Reports Server (NTRS)
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.
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Nunez, Paul L.; Srinivasan, Ramesh
2013-01-01
The brain is treated as a nested hierarchical complex system with substantial interactions across spatial scales. Local networks are pictured as embedded within global fields of synaptic action and action potentials. Global fields may act top-down on multiple networks, acting to bind remote networks. Because of scale-dependent properties, experimental electrophysiology requires both local and global models that match observational scales. Multiple local alpha rhythms are embedded in a global alpha rhythm. Global models are outlined in which cm-scale dynamic behaviors result largely from propagation delays in cortico-cortical axons and cortical background excitation level, controlled by neuromodulators on long time scales. The idealized global models ignore the bottom-up influences of local networks on global fields so as to employ relatively simple mathematics. The resulting models are transparently related to several EEG and steady state visually evoked potentials correlated with cognitive states, including estimates of neocortical coherence structure, traveling waves, and standing waves. The global models suggest that global oscillatory behavior of self-sustained (limit-cycle) modes lower than about 20 Hz may easily occur in neocortical/white matter systems provided: Background cortical excitability is sufficiently high; the strength of long cortico-cortical axon systems is sufficiently high; and the bottom-up influence of local networks on the global dynamic field is sufficiently weak. The global models provide "entry points" to more detailed studies of global top-down influences, including binding of weakly connected networks, modulation of gamma oscillations by theta or alpha rhythms, and the effects of white matter deficits. PMID:24505628
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A next generation air quality modeling system is being developed at the U.S. EPA to enable seamless modeling of air quality from global to regional to (eventually) local scales. State of the science chemistry and aerosol modules from the Community Multiscale Air Quality (CMAQ) mo...
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The US EPA has a plan to leverage recent advances in meteorological modeling to develop a "Next-Generation" air quality modeling system that will allow consistent modeling of problems from global to local scale. The meteorological model of choice is the Model for Predic...
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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.
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Jarnevich, Catherine S.; Young, Nicholas E.; Talbert, Marian; Talbert, Colin
2018-01-01
Understanding invasive species distributions and potential invasions often requires broad‐scale information on the environmental tolerances of the species. Further, resource managers are often faced with knowing these broad‐scale relationships as well as nuanced environmental factors related to their landscape that influence where an invasive species occurs and potentially could occur. Using invasive buffelgrass (Cenchrus ciliaris), we developed global models and local models for Saguaro National Park, Arizona, USA, based on location records and literature on physiological tolerances to environmental factors to investigate whether environmental relationships of a species at a global scale are also important at local scales. In addition to correlative models with five commonly used algorithms, we also developed a model using a priori user‐defined relationships between occurrence and environmental characteristics based on a literature review. All correlative models at both scales performed well based on statistical evaluations. The user‐defined curves closely matched those produced by the correlative models, indicating that the correlative models may be capturing mechanisms driving the distribution of buffelgrass. Given climate projections for the region, both global and local models indicate that conditions at Saguaro National Park may become more suitable for buffelgrass. Combining global and local data with correlative models and physiological information provided a holistic approach to forecasting invasive species distributions.
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Evaluation of coral reef carbonate production models at a global scale
NASA Astrophysics Data System (ADS)
Jones, N. S.; Ridgwell, A.; Hendy, E. J.
2014-09-01
Calcification by coral reef communities is estimated to account for half of all carbonate produced in shallow water environments and more than 25% of the total carbonate buried in marine sediments globally. Production of calcium carbonate by coral reefs is therefore an important component of the global carbon cycle. It is also threatened by future global warming and other global change pressures. Numerical models of reefal carbonate production are essential for understanding how carbonate deposition responds to environmental conditions including future atmospheric CO2 concentrations, but these models must first be evaluated in terms of their skill in recreating present day calcification rates. Here we evaluate four published model descriptions of reef carbonate production in terms of their predictive power, at both local and global scales, by comparing carbonate budget outputs with independent estimates. We also compile available global data on reef calcification to produce an observation-based dataset for the model evaluation. The four calcification models are based on functions sensitive to combinations of light availability, aragonite saturation (Ωa) and temperature and were implemented within a specifically-developed global framework, the Global Reef Accretion Model (GRAM). None of the four models correlated with independent rate estimates of whole reef calcification. The temperature-only based approach was the only model output to significantly correlate with coral-calcification rate observations. The absence of any predictive power for whole reef systems, even when consistent at the scale of individual corals, points to the overriding importance of coral cover estimates in the calculations. Our work highlights the need for an ecosystem modeling approach, accounting for population dynamics in terms of mortality and recruitment and hence coral cover, in estimating global reef carbonate budgets. In addition, validation of reef carbonate budgets is severely hampered by limited and inconsistent methodology in reef-scale observations.
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Global scale predictability of floods
NASA Astrophysics Data System (ADS)
Weerts, Albrecht; Gijsbers, Peter; Sperna Weiland, Frederiek
2016-04-01
Flood (and storm surge) forecasting at the continental and global scale has only become possible in recent years (Emmerton et al., 2016; Verlaan et al., 2015) due to the availability of meteorological forecast, global scale precipitation products and global scale hydrologic and hydrodynamic models. Deltares has setup GLOFFIS a research-oriented multi model operational flood forecasting system based on Delft-FEWS in an open experimental ICT facility called Id-Lab. In GLOFFIS both the W3RA and PCRGLOB-WB model are run in ensemble mode using GEFS and ECMWF-EPS (latency 2 days). GLOFFIS will be used for experiments into predictability of floods (and droughts) and their dependency on initial state estimation, meteorological forcing and the hydrologic model used. Here we present initial results of verification of the ensemble flood forecasts derived with the GLOFFIS system. Emmerton, R., Stephens, L., Pappenberger, F., Pagano, T., Weerts, A., Wood, A. Salamon, P., Brown, J., Hjerdt, N., Donnelly, C., Cloke, H. Continental and Global Scale Flood Forecasting Systems, WIREs Water (accepted), 2016 Verlaan M, De Kleermaeker S, Buckman L. GLOSSIS: Global storm surge forecasting and information system 2015, Australasian Coasts & Ports Conference, 15-18 September 2015,Auckland, New Zealand.
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Yu, Sungduk; Pritchard, Michael S.
2015-12-17
The effect of global climate model (GCM) time step—which also controls how frequently global and embedded cloud resolving scales are coupled—is examined in the Superparameterized Community Atmosphere Model ver 3.0. Systematic bias reductions of time-mean shortwave cloud forcing (~10 W/m 2) and longwave cloud forcing (~5 W/m 2) occur as scale coupling frequency increases, but with systematically increasing rainfall variance and extremes throughout the tropics. An overarching change in the vertical structure of deep tropical convection, favoring more bottom-heavy deep convection as a global model time step is reduced may help orchestrate these responses. The weak temperature gradient approximation ismore » more faithfully satisfied when a high scale coupling frequency (a short global model time step) is used. These findings are distinct from the global model time step sensitivities of conventionally parameterized GCMs and have implications for understanding emergent behaviors of multiscale deep convective organization in superparameterized GCMs. Lastly, the results may also be useful for helping to tune them.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Yu, Sungduk; Pritchard, Michael S.
The effect of global climate model (GCM) time step—which also controls how frequently global and embedded cloud resolving scales are coupled—is examined in the Superparameterized Community Atmosphere Model ver 3.0. Systematic bias reductions of time-mean shortwave cloud forcing (~10 W/m 2) and longwave cloud forcing (~5 W/m 2) occur as scale coupling frequency increases, but with systematically increasing rainfall variance and extremes throughout the tropics. An overarching change in the vertical structure of deep tropical convection, favoring more bottom-heavy deep convection as a global model time step is reduced may help orchestrate these responses. The weak temperature gradient approximation ismore » more faithfully satisfied when a high scale coupling frequency (a short global model time step) is used. These findings are distinct from the global model time step sensitivities of conventionally parameterized GCMs and have implications for understanding emergent behaviors of multiscale deep convective organization in superparameterized GCMs. Lastly, the results may also be useful for helping to tune them.« less
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NASA Technical Reports Server (NTRS)
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 future periods. Implementation differences in these and other modeling choices contribute to significant variation among global-scale crop model assessments in addition to differences in crop model implementations that also cause large differences in site-specific crop modeling (Asseng et al., 2013; Bassu et al., 2014).
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Multiscale Cloud System Modeling
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Moncrieff, Mitchell W.
2009-01-01
The central theme of this paper is to describe how cloud system resolving models (CRMs) of grid spacing approximately 1 km have been applied to various important problems in atmospheric science across a wide range of spatial and temporal scales and how these applications relate to other modeling approaches. A long-standing problem concerns the representation of organized precipitating convective cloud systems in weather and climate models. Since CRMs resolve the mesoscale to large scales of motion (i.e., 10 km to global) they explicitly address the cloud system problem. By explicitly representing organized convection, CRMs bypass restrictive assumptions associated with convective parameterization such as the scale gap between cumulus and large-scale motion. Dynamical models provide insight into the physical mechanisms involved with scale interaction and convective organization. Multiscale CRMs simulate convective cloud systems in computational domains up to global and have been applied in place of contemporary convective parameterizations in global models. Multiscale CRMs pose a new challenge for model validation, which is met in an integrated approach involving CRMs, operational prediction systems, observational measurements, and dynamical models in a new international project: the Year of Tropical Convection, which has an emphasis on organized tropical convection and its global effects.
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Challenges in Global Land Use/Land Cover Change Modeling
NASA Astrophysics Data System (ADS)
Clarke, K. C.
2011-12-01
For the purposes of projecting and anticipating human-induced land use change at the global scale, much work remains in the systematic mapping and modeling of world-wide land uses and their related dynamics. In particular, research has focused on tropical deforestation, loss of prime agricultural land, loss of wild land and open space, and the spread of urbanization. Fifteen years of experience in modeling land use and land cover change at the regional and city level with the cellular automata model SLEUTH, including cross city and regional comparisons, has led to an ability to comment on the challenges and constraints that apply to global level land use change modeling. Some issues are common to other modeling domains, such as scaling, earth geometry, and model coupling. Others relate to geographical scaling of human activity, while some are issues of data fusion and international interoperability. Grid computing now offers the prospect of global land use change simulation. This presentation summarizes what barriers face global scale land use modeling, but also highlights the benefits of such modeling activity on global change research. An approach to converting land use maps and forecasts into environmental impact measurements is proposed. Using such an approach means that multitemporal mapping, often using remotely sensed sources, and forecasting can also yield results showing the overall and disaggregated status of the environment.
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Zumpano, Camila Eugênia; Mendonça, Tânia Maria da Silva; Silva, Carlos Henrique Martins da; Correia, Helena; Arnold, Benjamin; Pinto, Rogério de Melo Costa
2017-01-23
This study aimed to perform the cross-cultural adaptation and validation of the Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health scale in the Portuguese language. The ten Global Health items were cross-culturally adapted by the method proposed in the Functional Assessment of Chronic Illness Therapy (FACIT). The instrument's final version in Portuguese was self-administered by 1,010 participants in Brazil. The scale's precision was verified by floor and ceiling effects analysis, reliability of internal consistency, and test-retest reliability. Exploratory and confirmatory factor analyses were used to assess the construct's validity and instrument's dimensionality. Calibration of the items used the Gradual Response Model proposed by Samejima. Four global items required adjustments after the pretest. Analysis of the psychometric properties showed that the Global Health scale has good reliability, with Cronbach's alpha of 0.83 and intra-class correlation of 0.89. Exploratory and confirmatory factor analyses showed good fit in the previously established two-dimensional model. The Global Physical Health and Global Mental Health scale showed good latent trait coverage according to the Gradual Response Model. The PROMIS Global Health items showed equivalence in Portuguese compared to the original version and satisfactory psychometric properties for application in clinical practice and research in the Brazilian population.
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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 where more observations are required or environmental controls are hard to constrain. © 2016 John Wiley & Sons Ltd.
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Regional atmospheric models simulate their pertinent processes over a limited portion of the global atmosphere. This portion of the atmosphere can be a large fraction, as in the case of continental-scale modeling, or small fraction, as in the case of urban-scale modeling. Regio...
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Global Magnetosphere Modeling With Kinetic Treatment of Magnetic Reconnection
NASA Astrophysics Data System (ADS)
Toth, G.; Chen, Y.; Gombosi, T. I.; Cassak, P.; Markidis, S.; Peng, B.; Henderson, M. G.
2017-12-01
Global magnetosphere simulations with a kinetic treatment of magnetic reconnection are very challenging because of the large separation of global and kinetic scales. We have developed two algorithms that can overcome these difficulties: 1) the two-way coupling of the global magnetohydrodynamic code with an embedded particle-in-cell model (MHD-EPIC) and 2) the artificial increase of the ion and electron kinetic scales. Both of these techniques improve the efficiency of the simulations by many orders of magnitude. We will describe the techniques and show that they provide correct and meaningful results. Using the coupled model and the increased kinetic scales, we will present global magnetosphere simulations with the PIC domains covering the dayside and/or tail reconnection sites. The simulation results will be compared to and validated with MMS observations.
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Evaluation of coral reef carbonate production models at a global scale
NASA Astrophysics Data System (ADS)
Jones, N. S.; Ridgwell, A.; Hendy, E. J.
2015-03-01
Calcification by coral reef communities is estimated to account for half of all carbonate produced in shallow water environments and more than 25% of the total carbonate buried in marine sediments globally. Production of calcium carbonate by coral reefs is therefore an important component of the global carbon cycle; it is also threatened by future global warming and other global change pressures. Numerical models of reefal carbonate production are needed for understanding how carbonate deposition responds to environmental conditions including atmospheric CO2 concentrations in the past and into the future. However, before any projections can be made, the basic test is to establish model skill in recreating present-day calcification rates. Here we evaluate four published model descriptions of reef carbonate production in terms of their predictive power, at both local and global scales. We also compile available global data on reef calcification to produce an independent observation-based data set for the model evaluation of carbonate budget outputs. The four calcification models are based on functions sensitive to combinations of light availability, aragonite saturation (Ωa) and temperature and were implemented within a specifically developed global framework, the Global Reef Accretion Model (GRAM). No model was able to reproduce independent rate estimates of whole-reef calcification, and the output from the temperature-only based approach was the only model to significantly correlate with coral-calcification rate observations. The absence of any predictive power for whole reef systems, even when consistent at the scale of individual corals, points to the overriding importance of coral cover estimates in the calculations. Our work highlights the need for an ecosystem modelling approach, accounting for population dynamics in terms of mortality and recruitment and hence calcifier abundance, in estimating global reef carbonate budgets. In addition, validation of reef carbonate budgets is severely hampered by limited and inconsistent methodology in reef-scale observations.
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The influence of large-scale wind power on global climate.
Keith, David W; Decarolis, Joseph F; Denkenberger, David C; Lenschow, Donald H; Malyshev, Sergey L; Pacala, Stephen; Rasch, Philip J
2004-11-16
Large-scale use of wind power can alter local and global climate by extracting kinetic energy and altering turbulent transport in the atmospheric boundary layer. We report climate-model simulations that address the possible climatic impacts of wind power at regional to global scales by using two general circulation models and several parameterizations of the interaction of wind turbines with the boundary layer. We find that very large amounts of wind power can produce nonnegligible climatic change at continental scales. Although large-scale effects are observed, wind power has a negligible effect on global-mean surface temperature, and it would deliver enormous global benefits by reducing emissions of CO(2) and air pollutants. Our results may enable a comparison between the climate impacts due to wind power and the reduction in climatic impacts achieved by the substitution of wind for fossil fuels.
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Linking Global and Regional Models to Simulate U.S. Air Quality in the Year 2050
The potential impact of global climate change on future air quality in the United States is investigated with global and regional-scale models. Regional climate model scenarios are developed by dynamically downscaling the outputs from a global chemistry and climate model and are...
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DOE Office of Scientific and Technical Information (OSTI.GOV)
McCabe, M. F.; Ershadi, A.; Jimenez, C.
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, fourmore » 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; 0.62), with values in parentheses representing the R 2, RMSD and Nash–Sutcliffe efficiency (NSE), respectively. PM-Mu (0.51; 78 W m –2; 0.45) tended to underestimate fluxes, while SEBS (0.72; 101 W m –2; 0.24) overestimated values relative to observations. A focused analysis across specific biome types and climate zones showed considerable variability in the performance of all models, with no single model consistently able to outperform any other. Results also indicated that the global gridded data tended to reduce the performance for all of the studied models when compared to the tower data, likely a response to scale mismatch and issues related to forcing quality. Rather than relying on any single model simulation, the spatial and temporal variability at both the tower- and grid-scale highlighted the potential benefits of developing an ensemble or blended evaporation product for global-scale LandFlux applications. Hence, challenges related to the robust assessment of the LandFlux product are also discussed.« less
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McCabe, M. F.; Ershadi, A.; Jimenez, C.; ...
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, fourmore » 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; 0.62), with values in parentheses representing the R 2, RMSD and Nash–Sutcliffe efficiency (NSE), respectively. PM-Mu (0.51; 78 W m –2; 0.45) tended to underestimate fluxes, while SEBS (0.72; 101 W m –2; 0.24) overestimated values relative to observations. A focused analysis across specific biome types and climate zones showed considerable variability in the performance of all models, with no single model consistently able to outperform any other. Results also indicated that the global gridded data tended to reduce the performance for all of the studied models when compared to the tower data, likely a response to scale mismatch and issues related to forcing quality. Rather than relying on any single model simulation, the spatial and temporal variability at both the tower- and grid-scale highlighted the potential benefits of developing an ensemble or blended evaporation product for global-scale LandFlux applications. Hence, challenges related to the robust assessment of the LandFlux product are also discussed.« less
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Improvements to a global-scale groundwater model to estimate the water table across New Zealand
NASA Astrophysics Data System (ADS)
Westerhoff, Rogier; Miguez-Macho, Gonzalo; White, Paul
2017-04-01
Groundwater models at the global scale have become increasingly important in recent years to assess the effects of climate change and groundwater depletion. However, these global-scale models are typically not used for studies at the catchment scale, because they are simplified and too spatially coarse. In this study, we improved the global-scale Equilibrium Water Table (EWT) model, so it could better assess water table depth and water table elevation at the national scale for New Zealand. The resulting National Water Table (NWT) model used improved input data (i.e., national input data of terrain, geology, and recharge) and model equations (e.g., a hydraulic conductivity - depth relation). The NWT model produced maps of the water table that identified the main alluvial aquifers with fine spatial detail. Two regional case studies at the catchment scale demonstrated excellent correlation between the water table elevation and observations of hydraulic head. The NWT water tables are an improved water table estimation over the EWT model. In two case studies the NWT model provided a better approximation to observed water table for deep aquifers and the improved resolution of the model provided the capability to fill the gaps in data-sparse areas. This national model calculated water table depth and elevation across regional jurisdictions. Therefore, the model is relevant where trans-boundary issues, such as source protection and catchment boundary definition, occur. The NWT model also has the potential to constrain the uncertainty of catchment-scale models, particularly where data are sparse. Shortcomings of the NWT model are caused by the inaccuracy of input data and the simplified model properties. Future research should focus on improved estimation of input data (e.g., hydraulic conductivity and terrain). However, more advanced catchment-scale groundwater models should be used where groundwater flow is dominated by confining layers and fractures.
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NASA Technical Reports Server (NTRS)
Mohr, Karen Irene; Tao, Wei-Kuo; Chern, Jiun-Dar; Kumar, Sujay V.; Peters-Lidard, Christa D.
2013-01-01
The present generation of general circulation models (GCM) use parameterized cumulus schemes and run at hydrostatic grid resolutions. To improve the representation of cloud-scale moist processes and landeatmosphere interactions, a global, Multi-scale Modeling Framework (MMF) coupled to the Land Information System (LIS) has been developed at NASA-Goddard Space Flight Center. The MMFeLIS has three components, a finite-volume (fv) GCM (Goddard Earth Observing System Ver. 4, GEOS-4), a 2D cloud-resolving model (Goddard Cumulus Ensemble, GCE), and the LIS, representing the large-scale atmospheric circulation, cloud processes, and land surface processes, respectively. The non-hydrostatic GCE model replaces the single-column cumulus parameterization of fvGCM. The model grid is composed of an array of fvGCM gridcells each with a series of embedded GCE models. A horizontal coupling strategy, GCE4fvGCM4Coupler4LIS, offered significant computational efficiency, with the scalability and I/O capabilities of LIS permitting landeatmosphere interactions at cloud-scale. Global simulations of 2007e2008 and comparisons to observations and reanalysis products were conducted. Using two different versions of the same land surface model but the same initial conditions, divergence in regional, synoptic-scale surface pressure patterns emerged within two weeks. The sensitivity of largescale circulations to land surface model physics revealed significant functional value to using a scalable, multi-model land surface modeling system in global weather and climate prediction.
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Global scale groundwater flow model
NASA Astrophysics Data System (ADS)
Sutanudjaja, Edwin; de Graaf, Inge; van Beek, Ludovicus; Bierkens, Marc
2013-04-01
As the world's largest accessible source of freshwater, groundwater plays vital role in satisfying the basic needs of human society. It serves as a primary source of drinking water and supplies water for agricultural and industrial activities. During times of drought, groundwater sustains water flows in streams, rivers, lakes and wetlands, and thus supports ecosystem habitat and biodiversity, while its large natural storage provides a buffer against water shortages. Yet, the current generation of global scale hydrological models does not include a groundwater flow component that is a crucial part of the hydrological cycle and allows the simulation of groundwater head dynamics. In this study we present a steady-state MODFLOW (McDonald and Harbaugh, 1988) groundwater model on the global scale at 5 arc-minutes resolution. Aquifer schematization and properties of this groundwater model were developed from available global lithological model (e.g. Dürr et al., 2005; Gleeson et al., 2010; Hartmann and Moorsdorff, in press). We force the groundwtaer model with the output from the large-scale hydrological model PCR-GLOBWB (van Beek et al., 2011), specifically the long term net groundwater recharge and average surface water levels derived from routed channel discharge. We validated calculated groundwater heads and depths with available head observations, from different regions, including the North and South America and Western Europe. Our results show that it is feasible to build a relatively simple global scale groundwater model using existing information, and estimate water table depths within acceptable accuracy in many parts of the world.
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NASA Astrophysics Data System (ADS)
Katavouta, Anna; Thompson, Keith
2017-04-01
A high resolution regional model (1/36 degree) of the Gulf of Maine, Scotian Shelf and adjacent deep ocean (GoMSS) is developed to downscale ocean conditions from an existing global operational system. First, predictions from the regional GoMSS model in a one-way nesting set up are evaluated using observations from multiple sources including satellite-borne sensors of surface temperature and sea level, CTDs, Argo floats and moored current meters. It is shown that on the shelf, the regional model predicts more realistic fields than the global system because it has higher resolution and includes tides that are absent from the global system. However, in deep water the regional model misplaces deep ocean eddies and meanders associated with the Gulf Stream. This is because of unrealistic internally generated variability (associated with the one-way nesting set up) that leads to decoupling of the regional model from the global system in the deep water. To overcome this problem, the large scales (length scales > 90 km) of the regional model are spectrally nudged towards the global system fields. This leads to more realistic predictions off the shelf. Wavenumber spectra show that even though spectral nudging constrains the large scales, it does not suppress the variability on small scales; on the contrary, it favours the formation of eddies with length scales below the cut-off wavelength of the spectral nudging.
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High performance computing (HPC) requirements for the new generation variable grid resolution (VGR) global climate models differ from that of traditional global models. A VGR global model with 15 km grids over the CONUS stretching to 60 km grids elsewhere will have about ~2.5 tim...
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A Land System representation for global assessments and land-use modeling.
van Asselen, Sanneke; Verburg, Peter H
2012-10-01
Current global scale land-change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land-use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (LS) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map LS using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of LS. The analysis of the spatial determinants of LS indicates strong associations between LS and a range of socioeconomic and biophysical indicators of human-environment interactions. The set of identified spatial determinants of a LS differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi-)Natural LS have more similar spatial determinants across regions and scales. Using LS in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land-use intensity and landscape composition. Because the set of most important spatial determinants of LS varies among regions and scales, land-change models that include the human drivers of land change are best parameterized at sub-global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions. © 2012 Blackwell Publishing Ltd.
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NASA Astrophysics Data System (ADS)
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.
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Optimal satellite sampling to resolve global-scale dynamics in the I-T system
NASA Astrophysics Data System (ADS)
Rowland, D. E.; Zesta, E.; Connor, H. K.; Pfaff, R. F., Jr.
2016-12-01
The recent Decadal Survey highlighted the need for multipoint measurements of ion-neutral coupling processes to study the pathways by which solar wind energy drives dynamics in the I-T system. The emphasis in the Decadal Survey is on global-scale dynamics and processes, and in particular, mission concepts making use of multiple identical spacecraft in low earth orbit were considered for the GDC and DYNAMIC missions. This presentation will provide quantitative assessments of the optimal spacecraft sampling needed to significantly advance our knowledge of I-T dynamics on the global scale.We will examine storm time and quiet time conditions as simulated by global circulation models, and determine how well various candidate satellite constellations and satellite schemes can quantify the plasma and neutral convection patterns and global-scale distributions of plasma density, neutral density, and composition, and their response to changes in the IMF. While the global circulation models are data-starved, and do not contain all the physics that we might expect to observe with a global-scale constellation mission, they are nonetheless an excellent "starting point" for discussions of the implementation of such a mission. The result will be of great utility for the design of future missions, such as GDC, to study the global-scale dynamics of the I-T system.
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The global reference atmospheric model, mod 2 (with two scale perturbation model)
NASA Technical Reports Server (NTRS)
Justus, C. G.; Hargraves, W. R.
1976-01-01
The Global Reference Atmospheric Model was improved to produce more realistic simulations of vertical profiles of atmospheric parameters. A revised two scale random perturbation model using perturbation magnitudes which are adjusted to conform to constraints imposed by the perfect gas law and the hydrostatic condition is described. The two scale perturbation model produces appropriately correlated (horizontally and vertically) small scale and large scale perturbations. These stochastically simulated perturbations are representative of the magnitudes and wavelengths of perturbations produced by tides and planetary scale waves (large scale) and turbulence and gravity waves (small scale). Other new features of the model are: (1) a second order geostrophic wind relation for use at low latitudes which does not "blow up" at low latitudes as the ordinary geostrophic relation does; and (2) revised quasi-biennial amplitudes and phases and revised stationary perturbations, based on data through 1972.
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Global Scale Atmospheric Processes Research Program Review
NASA Technical Reports Server (NTRS)
Worley, B. A. (Editor); Peslen, C. A. (Editor)
1984-01-01
Global modeling; satellite data assimilation and initialization; simulation of future observing systems; model and observed energetics; dynamics of planetary waves; First Global Atmospheric Research Program Global Experiment (FGGE) diagnosis studies; and National Research Council Research Associateship Program are discussed.
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NASA Technical Reports Server (NTRS)
Hattermann, F. F.; Krysanova, V.; Gosling, S. N.; Dankers, R.; Daggupati, P.; Donnelly, C.; Florke, M.; Huang, S.; Motovilov, Y.; Buda, S.;
2017-01-01
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 to climate variability and climate change is comparable for impact models designed for either scale. 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 better reproduction of reference conditions. However, the sensitivity of the 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, but have distinct differences in other cases, 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. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Hattermann, F. F.; Krysanova, V.; Gosling, S. N.
Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity of impact models designed for either scale to climate variability and change is comparable. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climatemore » change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a much better reproduction of reference conditions. However, the sensitivity of two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases with distinct differences in others, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability, but whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models validated against observed discharge should be used.« less
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Spatially explicit modeling of particulate nutrient flux in Large global rivers
NASA Astrophysics Data System (ADS)
Cohen, S.; Kettner, A.; Mayorga, E.; Harrison, J. A.
2017-12-01
Water, sediment, nutrient and carbon fluxes along river networks have undergone considerable alterations in response to anthropogenic and climatic changes, with significant consequences to infrastructure, agriculture, water security, ecology and geomorphology worldwide. However, in a global setting, these changes in fluvial fluxes and their spatial and temporal characteristics are poorly constrained, due to the limited availability of continuous and long-term observations. We present results from a new global-scale particulate modeling framework (WBMsedNEWS) that combines the Global NEWS watershed nutrient export model with the spatially distributed WBMsed water and sediment model. We compare the model predictions against multiple observational datasets. The results indicate that the model is able to accurately predict particulate nutrient (Nitrogen, Phosphorus and Organic Carbon) fluxes on an annual time scale. Analysis of intra-basin nutrient dynamics and fluxes to global oceans is presented.
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Global Gridded Crop Model Evaluation: Benchmarking, Skills, Deficiencies and Implications.
NASA Technical Reports Server (NTRS)
Muller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe; Deryng, Delphine; Folberth, Christian; Glotter, Michael; Hoek, Steven;
2017-01-01
Crop models are increasingly used to simulate crop yields at the global scale, but so far there is no general framework on how to assess model performance. Here we evaluate the simulation results of 14 global gridded crop modeling groups that have contributed historic crop yield simulations for maize, wheat, rice and soybean to the Global Gridded Crop Model Intercomparison (GGCMI) of the Agricultural Model Intercomparison and Improvement Project (AgMIP). Simulation results are compared to reference data at global, national and grid cell scales and we evaluate model performance with respect to time series correlation, spatial correlation and mean bias. We find that global gridded crop models (GGCMs) show mixed skill in reproducing time series correlations or spatial patterns at the different spatial scales. Generally, maize, wheat and soybean simulations of many GGCMs are capable of reproducing larger parts of observed temporal variability (time series correlation coefficients (r) of up to 0.888 for maize, 0.673 for wheat and 0.643 for soybean at the global scale) but rice yield variability cannot be well reproduced by most models. Yield variability can be well reproduced for most major producing countries by many GGCMs and for all countries by at least some. A comparison with gridded yield data and a statistical analysis of the effects of weather variability on yield variability shows that the ensemble of GGCMs can explain more of the yield variability than an ensemble of regression models for maize and soybean, but not for wheat and rice. We identify future research needs in global gridded crop modeling and for all individual crop modeling groups. In the absence of a purely observation-based benchmark for model evaluation, we propose that the best performing crop model per crop and region establishes the benchmark for all others, and modelers are encouraged to investigate how crop model performance can be increased. We make our evaluation system accessible to all crop modelers so that other modeling groups can also test their model performance against the reference data and the GGCMI benchmark.
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NASA Astrophysics Data System (ADS)
Jorba, O.; Pérez, C.; Karsten, K.; Janjic, Z.; Dabdub, D.; Baldasano, J. M.
2009-09-01
This contribution presents the ongoing developments of a new fully on-line chemical weather prediction system for meso to global scale applications. The modeling system consists of a mineral dust module and a gas-phase chemistry module coupled on-line to a unified global-regional atmospheric driver. This approach allows solving small scale processes and their interactions at local to global scales. Its unified environment maintains the consistency of all the physico-chemical processes involved. The atmospheric driver is the NCEP/NMMB numerical weather prediction model (Janjic and Black, 2007) developed at National Centers for Environmental Prediction (NCEP). It represents an evolution of the operational WRF-NMME model extending from meso to global scales. Its unified non-hydrostatic dynamical core supports regional and global simulations. The Barcelona Supercomputing Center is currently designing and implementing a chemistry transport model coupled online with the new global/regional NMMB. The new modeling system is intended to be a powerful tool for research and to provide efficient global and regional chemical weather forecasts at sub-synoptic and mesoscale resolutions. The online coupling of the chemistry follows the approach similar to that of the mineral dust module already coupled to the atmospheric driver, NMMB/BSC-DUST (Pérez et al., 2008). Chemical species are advected and mixed at the corresponding time steps of the meteorological tracers using the same numerical scheme. Advection is eulerian, positive definite and monotone. The chemical mechanism and chemistry solver is based on the Kinetic PreProcessor KPP (Damian et al., 2002) package with the main purpose of maintaining a wide flexibility when configuring the model. Such approach will allow using a simplified chemical mechanism for global applications or a more complete mechanism for high-resolution local or regional studies. Moreover, it will permit the implementation of a specific configuration for forecasting applications in regional or global domains. An emission process allows the coupling of different emission inventories sources such as RETRO, EDGAR and GEIA for the global domain, EMEP for Europe and HERMES for Spain. The photolysis scheme is based on the Fast-J scheme, coupled with physics of each model layer (e.g., aerosols, clouds, absorbers as ozone) and it considers grid-scale clouds from the atmospheric driver. The dry deposition scheme follows the deposition velocity analogy for gases, enabling the calculation of deposition fluxes from airborne concentrations. No cloud-chemistry processes are included in the system yet (no wet deposition, scavenging and aqueous chemistry). The modeling system developments will be presented and first results of the gas-phase chemistry at global scale will be discussed. REFERENCES Janjic, Z.I., and Black, T.L., 2007. An ESMF unified model for a broad range of spatial and temporal scales, Geophysical Research Abstracts, 9, 05025. Pérez, C., Haustein, K., Janjic, Z.I., Jorba, O., Baldasano, J.M., Black, T.L., and Nickovic, S., 2008. An online dust model within the meso to global NMMB: current progress and plans. AGU Fall Meeting, San Francisco, A41K-03, 2008. Damian, V., Sandu, A., Damian, M., Potra, F., and Carmichael, G.R., 2002. The kinetic preprocessor KPP - A software environment for solving chemical kinetics. Comp. Chem. Eng., 26, 1567-1579. Sandu, A., and Sander, R., 2006. Technical note:Simulating chemical systems in Fortran90 and Matlab with the Kinetic PreProcessor KPP-2.1. Atmos. Chem. and Phys., 6, 187-195.
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NASA Astrophysics Data System (ADS)
Claessens, S. J.
2016-12-01
Mass density contrasts in the Earth's crust can be detected using an inversion of terrestrial or airborne gravity data. This contribution shows a technique to detect short-scale density contrasts using in-situ gravity observations in combination with a high-resolution global gravity model that includes variations in the gravity field due to topography. The technique is exemplified at various test sites using the Global Gravity Model Plus (GGMplus), which is a 7.2 arcsec resolution model of the Earth's gravitational field, covering all land masses and near-coastal areas within +/- 60° latitude. The model is a composite of GRACE and GOCE satellite observations, the EGM2008 global gravity model, and short-scale topographic gravity effects. Since variations in the Earth's gravity field due to topography are successfully modelled by GGMplus, any remaining differences with in-situ gravity observations are primarily due to mass density variations. It is shown that this technique effectively filters out large-scale density variations, and highlights short-scale near-surface density contrasts in the Earth's crust. Numerical results using recent high-density gravity surveys are presented, which indicate a strong correlation between density contrasts found and known lines of geological significance.
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NASA Astrophysics Data System (ADS)
Nunes, A.; Ivanov, V. Y.
2014-12-01
Although current global reanalyses provide reasonably accurate large-scale features of the atmosphere, systematic errors are still found in the hydrological and energy budgets of such products. In the tropics, precipitation is particularly challenging to model, which is also adversely affected by the scarcity of hydrometeorological datasets in the region. With the goal of producing downscaled analyses that are appropriate for a climate assessment at regional scales, a regional spectral model has used a combination of precipitation assimilation with scale-selective bias correction. The latter is similar to the spectral nudging technique, which prevents the departure of the regional model's internal states from the large-scale forcing. The target area in this study is the Amazon region, where large errors are detected in reanalysis precipitation. To generate the downscaled analysis, the regional climate model used NCEP/DOE R2 global reanalysis as the initial and lateral boundary conditions, and assimilated NOAA's Climate Prediction Center (CPC) MORPHed precipitation (CMORPH), available at 0.25-degree resolution, every 3 hours. The regional model's precipitation was successfully brought closer to the observations, in comparison to the NCEP global reanalysis products, as a result of the impact of a precipitation assimilation scheme on cumulus-convection parameterization, and improved boundary forcing achieved through a new version of scale-selective bias correction. Water and energy budget terms were also evaluated against global reanalyses and other datasets.
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NASA Astrophysics Data System (ADS)
Lee, Donghoon; Ward, Philip; Block, Paul
2018-02-01
Flood-related fatalities and impacts on society surpass those from all other natural disasters globally. While the inclusion of large-scale climate drivers in streamflow (or high-flow) prediction has been widely studied, an explicit link to global-scale long-lead prediction is lacking, which can lead to an improved understanding of potential flood propensity. Here we attribute seasonal peak-flow to large-scale climate patterns, including the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO), using streamflow station observations and simulations from PCR-GLOBWB, a global-scale hydrologic model. Statistically significantly correlated climate patterns and streamflow autocorrelation are subsequently applied as predictors to build a global-scale season-ahead prediction model, with prediction performance evaluated by the mean squared error skill score (MSESS) and the categorical Gerrity skill score (GSS). Globally, fair-to-good prediction skill (20% ≤ MSESS and 0.2 ≤ GSS) is evident for a number of locations (28% of stations and 29% of land area), most notably in data-poor regions (e.g., West and Central Africa). The persistence of such relevant climate patterns can improve understanding of the propensity for floods at the seasonal scale. The prediction approach developed here lays the groundwork for further improving local-scale seasonal peak-flow prediction by identifying relevant global-scale climate patterns. This is especially attractive for regions with limited observations and or little capacity to develop flood early warning systems.
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Global river flood hazard maps: hydraulic modelling methods and appropriate uses
NASA Astrophysics Data System (ADS)
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 appropriate uses of global scale hazard maps and explore how this new approach can be invaluable in areas of the world where flood hazard and risk have not previously been assessed.
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NASA Astrophysics Data System (ADS)
Katavouta, Anna; Thompson, Keith R.
2016-08-01
The overall goal is to downscale ocean conditions predicted by an existing global prediction system and evaluate the results using observations from the Gulf of Maine, Scotian Shelf and adjacent deep ocean. The first step is to develop a one-way nested regional model and evaluate its predictions using observations from multiple sources including satellite-borne sensors of surface temperature and sea level, CTDs, Argo floats and moored current meters. It is shown that the regional model predicts more realistic fields than the global system on the shelf because it has higher resolution and includes tides that are absent from the global system. However, in deep water the regional model misplaces deep ocean eddies and meanders associated with the Gulf Stream. This is not because the regional model's dynamics are flawed but rather is the result of internally generated variability in deep water that leads to decoupling of the regional model from the global system. To overcome this problem, the next step is to spectrally nudge the regional model to the large scales (length scales > 90 km) of the global system. It is shown this leads to more realistic predictions off the shelf. Wavenumber spectra show that even though spectral nudging constrains the large scales, it does not suppress the variability on small scales; on the contrary, it favours the formation of eddies with length scales below the cutoff wavelength of the spectral nudging.
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NASA Astrophysics Data System (ADS)
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.
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An online mineral dust model within the global/regional NMMB: current progress and plans
NASA Astrophysics Data System (ADS)
Perez, C.; Haustein, K.; Janjic, Z.; Jorba, O.; Baldasano, J. M.; Black, T.; Nickovic, S.
2008-12-01
While mineral dust distribution and effects are important on global scales, they strongly depend on dust emissions that are occurring on small spatial and temporal scales. Indeed, the accuracy of surface wind speed used in dust models is crucial. Due to the high-order power dependency on wind friction velocity and the threshold behaviour of dust emissions, small errors in surface wind speed lead to large dust emission errors. Most global dust models use prescribed wind fields provided by major meteorological centres (e.g., NCEP and ECMWF) and their spatial resolution is currently about 1 degree x 1 degree . Such wind speeds tend to be strongly underestimated over arid and semi-arid areas and do not account for mesoscale systems responsible for a significant fraction of dust emissions regionally and globally. Other significant uncertainties in dust emissions resulting from such approaches are related to the misrepresentation of high subgrid-scale spatial heterogeneity in soil and vegetation boundary conditions, mainly in semi-arid areas. In order to significantly reduce these uncertainties, the Barcelona Supercomputing Center is currently implementing a mineral dust model coupled on-line with the new global/regional NMMB atmospheric model using the ESMF framework under development in NOAA/NCEP/EMC. The NMMB is an evolution of the operational WRF-NMME extending from meso to global scales, and including non-hydrostatic option and improved tracer advection. This model is planned to become the next-generation NCEP mesoscale model for operational weather forecasting in North America. Current implementation is based on the well established regional dust model and forecast system Eta/DREAM (http://www.bsc.es/projects/earthscience/DREAM/). First successful global simulations show the potentials of such an approach and compare well with DREAM regionally. Ongoing developments include improvements in dust size distribution representation, sedimentation, dry deposition, wet scavenging and dust-radiation feedback, as well as the efficient implementation of the model on High Performance Supercomputers for global simulations and forecasts at high resolution.
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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...
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Modeling Global Biogenic Emission of Isoprene: Exploration of Model Drivers
NASA Technical Reports Server (NTRS)
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.
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NASA Astrophysics Data System (ADS)
Braakhekke, Maarten; Rebel, Karin; Dekker, Stefan; Smith, Benjamin; Sutanudjaja, Edwin; van Beek, Rens; van Kampenhout, Leo; Wassen, Martin
2017-04-01
In up to 30% of the global land surface ecosystems are potentially influenced by the presence of a shallow groundwater table. In these regions upward water flux by capillary rise increases soil moisture availability in the root zone, which has a strong effect on evapotranspiration, vegetation dynamics, and fluxes of carbon and nitrogen. Most global hydrological models and several land surface models simulate groundwater table dynamics and their effects on land surface processes. However, these models typically have relatively simplistic representation of vegetation and do not consider changes in vegetation type and structure. Dynamic global vegetation models (DGVMs), describe land surface from an ecological perspective, combining detailed description of vegetation dynamics and structure, and biogeochemical processes and are thus more appropriate to simulate the ecological and biogeochemical effects of groundwater interactions. However, currently virtually all DGVMs ignore these effects, assuming that water tables are too deep to affect soil moisture in the root zone. We have implemented a tight coupling between the dynamic global ecosystem model LPJ-GUESS and the global hydrological model PCR-GLOBWB, which explicitly simulates groundwater dynamics. This coupled model allows us to explicitly account for groundwater effects on terrestrial ecosystem processes at global scale. Results of global simulations indicate that groundwater strongly influences fluxes of water, carbon and nitrogen, in many regions, adding up to a considerable effect at the global scale.
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NASA Astrophysics Data System (ADS)
Neary, L.; Kaminski, J. W.; Struzewska, J.; Ainslie, B.; McConnell, J. C.
2007-12-01
Tropospheric chemistry and air quality processes were implemented on-line in the Global Environmental Multiscale model. The integrated model, GEM-AQ, has been developed as a platform to investigate chemical weather at scales from global to urban. On the global scale, the model was exercised for five years (2001-2005) to evaluate its ability to simulate seasonal variations and regional distributions of trace gases such as ozone, nitrogen dioxide and carbon monoxide. The model results are compared with observations from satellites, aircraft measurement campaigns and balloon sondes. The same model has also been evaluated on the regional (~15km resolution) and urban scale (~3km resolution). A simulation of the formation and transport of photooxidants during the European heat wave of 2006 was performed and compared with surface observations throughout central and eastern Europe. The complex topographic region of the Lower Fraser Valley in British Columbia was the focus of another model evaluation during the PACIFIC 2001 field campaign. Comparison of model results with observations during this period will be shown.
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A high-resolution global-scale groundwater model
NASA Astrophysics Data System (ADS)
de Graaf, I. E. M.; Sutanudjaja, E. H.; van Beek, L. P. H.; Bierkens, M. F. P.
2015-02-01
Groundwater is the world's largest accessible source of fresh water. It plays a vital role in satisfying basic needs for drinking water, agriculture and industrial activities. During times of drought groundwater sustains baseflow to rivers and wetlands, thereby supporting ecosystems. Most global-scale hydrological models (GHMs) do not include a groundwater flow component, mainly due to lack of geohydrological data at the global scale. For the simulation of lateral flow and groundwater head dynamics, a realistic physical representation of the groundwater system is needed, especially for GHMs that run at finer resolutions. In this study we present a global-scale groundwater model (run at 6' resolution) using MODFLOW to construct an equilibrium water table at its natural state as the result of long-term climatic forcing. The used aquifer schematization and properties are based on available global data sets of lithology and transmissivities combined with the estimated thickness of an upper, unconfined aquifer. This model is forced with outputs from the land-surface PCRaster Global Water Balance (PCR-GLOBWB) model, specifically net recharge and surface water levels. A sensitivity analysis, in which the model was run with various parameter settings, showed that variation in saturated conductivity has the largest impact on the groundwater levels simulated. Validation with observed groundwater heads showed that groundwater heads are reasonably well simulated for many regions of the world, especially for sediment basins (R2 = 0.95). The simulated regional-scale groundwater patterns and flow paths demonstrate the relevance of lateral groundwater flow in GHMs. Inter-basin groundwater flows can be a significant part of a basin's water budget and help to sustain river baseflows, especially during droughts. Also, water availability of larger aquifer systems can be positively affected by additional recharge from inter-basin groundwater flows.
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Probing Mantle Heterogeneity Across Spatial Scales
NASA Astrophysics Data System (ADS)
Hariharan, A.; Moulik, P.; Lekic, V.
2017-12-01
Inferences of mantle heterogeneity in terms of temperature, composition, grain size, melt and crystal structure may vary across local, regional and global scales. Probing these scale-dependent effects require quantitative comparisons and reconciliation of tomographic models that vary in their regional scope, parameterization, regularization and observational constraints. While a range of techniques like radial correlation functions and spherical harmonic analyses have revealed global features like the dominance of long-wavelength variations in mantle heterogeneity, they have limited applicability for specific regions of interest like subduction zones and continental cratons. Moreover, issues like discrepant 1-D reference Earth models and related baseline corrections have impeded the reconciliation of heterogeneity between various regional and global models. We implement a new wavelet-based approach that allows for structure to be filtered simultaneously in both the spectral and spatial domain, allowing us to characterize heterogeneity on a range of scales and in different geographical regions. Our algorithm extends a recent method that expanded lateral variations into the wavelet domain constructed on a cubed sphere. The isolation of reference velocities in the wavelet scaling function facilitates comparisons between models constructed with arbitrary 1-D reference Earth models. The wavelet transformation allows us to quantify the scale-dependent consistency between tomographic models in a region of interest and investigate the fits to data afforded by heterogeneity at various dominant wavelengths. We find substantial and spatially varying differences in the spectrum of heterogeneity between two representative global Vp models constructed using different data and methodologies. Applying the orthonormality of the wavelet expansion, we isolate detailed variations in velocity from models and evaluate additional fits to data afforded by adding such complexities to long-wavelength variations. Our method provides a way to probe and evaluate localized features in a multi-scale description of mantle heterogeneity.
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On the limitations of General Circulation Climate Models
NASA Technical Reports Server (NTRS)
Stone, Peter H.; Risbey, James S.
1990-01-01
General Circulation Models (GCMs) by definition calculate large-scale dynamical and thermodynamical processes and their associated feedbacks from first principles. This aspect of GCMs is widely believed to give them an advantage in simulating global scale climate changes as compared to simpler models which do not calculate the large-scale processes from first principles. However, it is pointed out that the meridional transports of heat simulated GCMs used in climate change experiments differ from observational analyses and from other GCMs by as much as a factor of two. It is also demonstrated that GCM simulations of the large scale transports of heat are sensitive to the (uncertain) subgrid scale parameterizations. This leads to the question whether current GCMs are in fact superior to simpler models for simulating temperature changes associated with global scale climate change.
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BETR Global - A geographically explicit global-scale multimedia contaminant fate model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Macleod, M.; Waldow, H. von; Tay, P.
2011-04-01
We present two new software implementations of the BETR Global multimedia contaminant fate model. The model uses steady-state or non-steady-state mass-balance calculations to describe the fate and transport of persistent organic pollutants using a desktop computer. The global environment is described using a database of long-term average monthly conditions on a 15{sup o} x 15{sup o} grid. We demonstrate BETR Global by modeling the global sources, transport, and removal of decamethylcyclopentasiloxane (D5).
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The global gridded crop model intercomparison: Data and modeling protocols for Phase 1 (v1.0)
Elliott, J.; Müller, C.; Deryng, D.; ...
2015-02-11
We present protocols and input data for Phase 1 of the Global Gridded Crop Model Intercomparison, a project of the Agricultural Model Intercomparison and Improvement Project (AgMIP). The project consist of global simulations of yields, phenologies, and many land-surface fluxes using 12–15 modeling groups for many crops, climate forcing data sets, and scenarios over the historical period from 1948 to 2012. The primary outcomes of the project include (1) a detailed comparison of the major differences and similarities among global models commonly used for large-scale climate impact assessment, (2) an evaluation of model and ensemble hindcasting skill, (3) quantification ofmore » key uncertainties from climate input data, model choice, and other sources, and (4) a multi-model analysis of the agricultural impacts of large-scale climate extremes from the historical record.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Bogenschutz, Peter; Moeng, Chin-Hoh
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.
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ERIC Educational Resources Information Center
Aydin, Belgin; Unver, Meral Melek; Alan, Bülent; Saglam, Sercan
2017-01-01
This paper explains the process of designing a curriculum based on the Taba Model and the Global Scale of English (GSE) in an intensive language education program. The Taba Model emphasizing the involvement of the teachers and the learners in the curriculum development process was combined with the GSE, a psychometric tool measuring language…
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NASA Astrophysics Data System (ADS)
Judt, Falko
2017-04-01
A tremendous increase in computing power has facilitated the advent of global convection-resolving numerical weather prediction (NWP) models. Although this technological breakthrough allows for the seamless prediction of weather from local to global scales, the predictability of multiscale weather phenomena in these models is not very well known. To address this issue, we conducted a global high-resolution (4-km) predictability experiment using the Model for Prediction Across Scales (MPAS), a state-of-the-art global NWP model developed at the National Center for Atmospheric Research. The goals of this experiment are to investigate error growth from convective to planetary scales and to quantify the intrinsic, scale-dependent predictability limits of atmospheric motions. The globally uniform resolution of 4 km allows for the explicit treatment of organized deep moist convection, alleviating grave limitations of previous predictability studies that either used high-resolution limited-area models or global simulations with coarser grids and cumulus parameterization. Error growth is analyzed within the context of an "identical twin" experiment setup: the error is defined as the difference between a 20-day long "nature run" and a simulation that was perturbed with small-amplitude noise, but is otherwise identical. It is found that in convectively active regions, errors grow by several orders of magnitude within the first 24 h ("super-exponential growth"). The errors then spread to larger scales and begin a phase of exponential growth after 2-3 days when contaminating the baroclinic zones. After 16 days, the globally averaged error saturates—suggesting that the intrinsic limit of atmospheric predictability (in a general sense) is about two weeks, which is in line with earlier estimates. However, error growth rates differ between the tropics and mid-latitudes as well as between the troposphere and stratosphere, highlighting that atmospheric predictability is a complex problem. The comparatively slower error growth in the tropics and in the stratosphere indicates that certain weather phenomena could potentially have longer predictability than currently thought.
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AgMIP Coordinated Global and Regional Assessments for 1.5°C and 2.0°C
NASA Astrophysics Data System (ADS)
Rosenzweig, C.
2017-12-01
The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study performs a proof-of-concept of the CGRA to demonstrate advantages and challenges of the framework. This effort responds to the request by UNFCCC for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), HAPPI and CMIP5 ensemble scenarios, global gridded crop models, global agricultural economic models, site-based crop models, and within-country regional economic models. CGRA results show that at the global scale, mixed areas of positive and negative simulated yield changes, with declines in some breadbasket regions led to overall declines in productivity at both 1.5°C and 2.0°C. These projected global yield changes resulted in increases in prices of major commodities in a global economic model. Simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on region and crop, but with more negative effects on productivity at 2.0°C than at 1.5°C for the most part. In conjunction with price changes from the global economics models, these productivity declines resulted generally in small positive effects on regional farm livelihoods, showing that farming systems should continue to be viable under high mitigation scenarios. CGRA protocols focus on how mitigation actions and effects differ across scales, with main mechanisms studied in the integrated assessment models being policies and technologies that reduce direct non-CO2 emissions from agriculture, reduce CO2 emissions from land use change and forest sink enhancement, and utilize biomass for energy production. At regional scales, increasing soil organic carbon (SOC) is of active interest.
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Combining global and local approximations
NASA Technical Reports Server (NTRS)
Haftka, Raphael T.
1991-01-01
A method based on a linear approximation to a scaling factor, designated the 'global-local approximation' (GLA) method, is presented and shown capable of extending the range of usefulness of derivative-based approximations to a more refined model. The GLA approach refines the conventional scaling factor by means of a linearly varying, rather than constant, scaling factor. The capabilities of the method are demonstrated for a simple beam example with a crude and more refined FEM model.
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NASA Astrophysics Data System (ADS)
Van Loon, Anne
2017-04-01
Drought is a global challenge. To be able to manage drought effectively on global or national scales without losing smaller scale variability and local context, we need to understand what the important hydrological drought processes are at different scales. Global scale models and satellite data are providing a global overview and catchment scale studies provide detailed site-specific information. I am interested in bridging these two scale levels by learning from catchments from around the world. Much information from local case studies is currently underused on larger scales because there is too much complexity. However, some of this complexity might be crucial on the level where people are facing the consequences of drought. In this talk, I will take you on a journey around the world to unlock catchment scale information and see if the comparison of many catchments gives us additional understanding of hydrological drought processes on the global scale. I will focus on the role of storage in different compartments of the terrestrial hydrological cycle, and how we as humans interact with that storage. I will discuss aspects of spatial and temporal variability in storage that are crucial for hydrological drought development and persistence, drawing from examples of catchments with storage in groundwater, lakes and wetlands, and snow and ice. The added complexity of human activities shifts the focus from natural to catchments with anthropogenic increases in storage (reservoirs), decreases in storage (groundwater abstraction), and changes in hydrological processes (urbanisation). We learn how local information is providing valuable insights, in some cases challenging theoretical understanding or model outcomes. Despite the challenges of working across countries, with a high number of collaborators, in a multitude of languages, under data-scarce conditions, the scientific advantages of bridging scales are substantial. The comparison of catchments around the world can inform global scale models, give the needed spatial variability to satellite data, and help us make steps in understanding and managing the complex challenge of drought, now and in the future.
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NASA Astrophysics Data System (ADS)
Switzer, A.; Yap, W.; Lauro, F.; Gouramanis, C.; Dominey-Howes, D.; Labbate, M.
2016-12-01
This presentation provides an overview of the PERSIANN precipitation products from the near real time high-resolution (4km, 30 min) PERSIANN-CCS to the most recent 34+-year PERSIANN-CDR (25km, daily). It is widely believed that the hydrologic cycle has been intensifying due to global warming and the frequency and the intensity of hydrologic extremes has also been increasing. Using the long-term historical global high resolution (daily, 0.25 degree) PERSIANN-CDR dataset covering over three decades from 1983 to the present day, we assess changes in global precipitation across different spatial scales. Our results show differences in trends, depending on which spatial scale is used, highlighting the importance of spatial scale in trend analysis. In addition, while there is an easily observable increasing global temperature trend, the global precipitation trend results created by the PERSIANN-CDR dataset used in this study are inconclusive. In addition, we use PERSIANN-CDR to assess the performance of the 32 CMIP5 models in terms of extreme precipitation indices in various continent-climate zones. The assessment can provide a guide for both model developers to target regions and processes that are not yet fully captured in certain climate types, and for climate model output users to be able to select the models and/or the study areas that may best fit their applications of interest.
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NASA Astrophysics Data System (ADS)
Sorooshian, S.; Nguyen, P.; Hsu, K. L.
2017-12-01
This presentation provides an overview of the PERSIANN precipitation products from the near real time high-resolution (4km, 30 min) PERSIANN-CCS to the most recent 34+-year PERSIANN-CDR (25km, daily). It is widely believed that the hydrologic cycle has been intensifying due to global warming and the frequency and the intensity of hydrologic extremes has also been increasing. Using the long-term historical global high resolution (daily, 0.25 degree) PERSIANN-CDR dataset covering over three decades from 1983 to the present day, we assess changes in global precipitation across different spatial scales. Our results show differences in trends, depending on which spatial scale is used, highlighting the importance of spatial scale in trend analysis. In addition, while there is an easily observable increasing global temperature trend, the global precipitation trend results created by the PERSIANN-CDR dataset used in this study are inconclusive. In addition, we use PERSIANN-CDR to assess the performance of the 32 CMIP5 models in terms of extreme precipitation indices in various continent-climate zones. The assessment can provide a guide for both model developers to target regions and processes that are not yet fully captured in certain climate types, and for climate model output users to be able to select the models and/or the study areas that may best fit their applications of interest.
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Estimating global cropland production from 1961 to 2010
NASA Astrophysics Data System (ADS)
Han, Pengfei; Zeng, Ning; Zhao, Fang; Lin, Xiaohui
2017-09-01
Global cropland net primary production (NPP) has tripled over the last 50 years, contributing 17-45 % to the increase in global atmospheric CO2 seasonal amplitude. Although many regional-scale comparisons have been made between statistical data and modeling results, long-term national comparisons across global croplands are scarce due to the lack of detailed spatiotemporal management data. Here, we conducted a simulation study of global cropland NPP from 1961 to 2010 using a process-based model called Vegetation-Global Atmosphere-Soil (VEGAS) and compared the results with Food and Agriculture Organization of the United Nations (FAO) statistical data on both continental and country scales. According to the FAO data, the global cropland NPP was 1.3, 1.8, 2.2, 2.6, 3.0, and 3.6 PgC yr-1 in the 1960s, 1970s, 1980s, 1990s, 2000s, and 2010s, respectively. The VEGAS model captured these major trends on global and continental scales. The NPP increased most notably in the US Midwest, western Europe, and the North China Plain and increased modestly in Africa and Oceania. However, significant biases remained in some regions such as Africa and Oceania, especially in temporal evolution. This finding is not surprising as VEGAS is the first global carbon cycle model with full parameterization representing the Green Revolution. To improve model performance for different major regions, we modified the default values of management intensity associated with the agricultural Green Revolution differences across various regions to better match the FAO statistical data at the continental level and for selected countries. Across all the selected countries, the updated results reduced the RMSE from 19.0 to 10.5 TgC yr-1 (˜ 45 % decrease). The results suggest that these regional differences in model parameterization are due to differences in socioeconomic development. To better explain the past changes and predict the future trends, it is important to calibrate key parameters on regional scales and develop data sets for land management history.
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NASA Technical Reports Server (NTRS)
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 concepts to create realistic pseudo-datasets. Pseudo-data are averaged over coarse model grid cell areas to better understand the ability of measurements to characterize CO2 distributions and spatial gradients on both short (daily to weekly) and long (monthly to seasonal) time scales
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A Distributed Platform for Global-Scale Agent-Based Models of Disease Transmission
Parker, Jon; Epstein, Joshua M.
2013-01-01
The Global-Scale Agent Model (GSAM) is presented. The GSAM is a high-performance distributed platform for agent-based epidemic modeling capable of simulating a disease outbreak in a population of several billion agents. It is unprecedented in its scale, its speed, and its use of Java. Solutions to multiple challenges inherent in distributing massive agent-based models are presented. Communication, synchronization, and memory usage are among the topics covered in detail. The memory usage discussion is Java specific. However, the communication and synchronization discussions apply broadly. We provide benchmarks illustrating the GSAM’s speed and scalability. PMID:24465120
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Water dependency and water exploitation at global scale as indicators of water security
NASA Astrophysics Data System (ADS)
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.
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Developing and testing a global-scale regression model to quantify mean annual streamflow
NASA Astrophysics Data System (ADS)
Barbarossa, Valerio; Huijbregts, Mark A. J.; Hendriks, A. Jan; Beusen, Arthur H. W.; Clavreul, Julie; King, Henry; Schipper, Aafke M.
2017-01-01
Quantifying mean annual flow of rivers (MAF) at ungauged sites is essential for 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 based on a dataset unprecedented in size, using observations of discharge and catchment characteristics from 1885 catchments worldwide, measuring between 2 and 106 km2. In addition, we compared the performance of the regression model with the predictive ability of the spatially explicit global hydrological model PCR-GLOBWB 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 and catchment averaged mean annual precipitation and air temperature, slope and elevation. The regression model performed better than PCR-GLOBWB for the prediction of MAF, as root-mean-square error (RMSE) values were lower (0.29-0.38 compared to 0.49-0.57) and the modified index of agreement (d) was higher (0.80-0.83 compared to 0.72-0.75). Our regression model can be applied globally to estimate MAF at any point of the river network, thus providing a feasible alternative to spatially explicit process-based global hydrological models.
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Locatelli, R.; Bousquet, P.; Chevallier, F.; ...
2013-10-08
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 10more » 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. Here 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 question the consistency of transport model errors in current inverse systems.« less
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A Goddard Multi-Scale Modeling System with Unified Physics
NASA Technical Reports Server (NTRS)
Tao, W.K.; Anderson, D.; Atlas, R.; Chern, J.; Houser, P.; Hou, A.; Lang, S.; Lau, W.; Peters-Lidard, C.; Kakar, R.;
2008-01-01
Numerical cloud resolving models (CRMs), which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that CRMs agree with observations in simulating various types of clouds and cloud systems from different geographic locations. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that Numerical Weather Prediction (NWP) and regional scale model can be run in grid size similar to cloud resolving model through nesting technique. 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 szrper-parameterization or multi-scale modeling -framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign can provide initial conditions as well as validation through utilizing the Earth Satellite simulators. At Goddard, we have developed a multi-scale modeling system with unified physics. The modeling system consists a coupled GCM-CRM (or MMF); a state-of-the-art weather research forecast model (WRF) and a cloud-resolving model (Goddard Cumulus Ensemble model). In these models, the same microphysical schemes (2ICE, several 3ICE), radiation (including explicitly calculated cloud optical properties), and surface models are applied. In addition, a comprehensive unified Earth Satellite simulator has been developed at GSFC, which is designed to fully utilize the multi-scale modeling system. A brief review of the multi-scale modeling system with unified physics/simulator and examples is presented in this article.
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NASA Astrophysics Data System (ADS)
Ikeuchi, Hiroaki; Hirabayashi, Yukiko; Yamazaki, Dai; Muis, Sanne; Ward, Philip J.; Winsemius, Hessel C.; Verlaan, Martin; Kanae, Shinjiro
2017-08-01
Water-related disasters, such as fluvial floods and cyclonic storm surges, are a major concern in the world's mega-delta regions. Furthermore, the simultaneous occurrence of extreme discharges from rivers and storm surges could exacerbate flood risk, compared to when they occur separately. Hence, it is of great importance to assess the compound risks of fluvial and coastal floods at a large scale, including mega-deltas. However, most studies on compound fluvial and coastal flooding have been limited to relatively small scales, and global-scale or large-scale studies have not yet addressed both of them. The objectives of this study are twofold: to develop a global coupled river-coast flood model; and to conduct a simulation of compound fluvial flooding and storm surges in Asian mega-delta regions. A state-of-the-art global river routing model was modified to represent the influence of dynamic sea surface levels on river discharges and water levels. We conducted the experiments by coupling a river model with a global tide and surge reanalysis data set. Results show that water levels in deltas and estuaries are greatly affected by the interaction between river discharge, ocean tides and storm surges. The effects of storm surges on fluvial flooding are further examined from a regional perspective, focusing on the case of Cyclone Sidr in the Ganges-Brahmaputra-Meghna Delta in 2007. Modeled results demonstrate that a >3 m storm surge propagated more than 200 km inland along rivers. We show that the performance of global river routing models can be improved by including sea level dynamics.
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NASA Astrophysics Data System (ADS)
Wieder, W. R.; Bradford, M.; Koven, C.; Talbot, J. M.; Wood, S.; Chadwick, O.
2016-12-01
High uncertainty and low confidence in terrestrial carbon (C) cycle projections reflect the incomplete understanding of how best to represent biologically-driven C cycle processes at global scales. Ecosystem theories, and consequently biogeochemical models, are based on the assumption that different belowground communities function similarly and interact with the abiotic environment in consistent ways. This assumption of "Scale Invariance" posits that environmental conditions will change the rate of ecosystem processes, but the biotic response will be consistent across sites. Indeed, cross-site comparisons and global-scale analyses suggest that climate strongly controls rates of litter mass loss and soil organic matter turnover. Alternatively, activities of belowground communities are shaped by particular local environmental conditions, such as climate and edaphic conditions. Under this assumption of "Scale Dependence", relationships generated by evolutionary trade-offs in acquiring resources and withstanding environmental stress dictate the activities of belowground communities and their functional response to environmental change. Similarly, local edaphic conditions (e.g. permafrost soils or reactive minerals that physicochemically stabilize soil organic matter on mineral surfaces) may strongly constrain the availability of substrates that biota decompose—altering the trajectory of soil biogeochemical response to perturbations. Identifying when scale invariant assumptions hold vs. where local variation in biotic communities or edaphic conditions must be considered is critical to advancing our understanding and representation of belowground processes in the face of environmental change. Here we introduce data sets that support assumptions of scale invariance and scale dependent processes and discuss their application in global-scale biogeochemical models. We identify particular domains over which assumptions of scale invariance may be appropriate and potential thresholds where shifts in ecosystem function may be expected. Finally, we discuss the mechanistic insight that can be applied in process-based models and datasets that can evaluate models across spatial and temporal scales.
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Foundations for a multiscale collaborative Earth model
NASA Astrophysics Data System (ADS)
Afanasiev, Michael; Peter, Daniel; Sager, Korbinian; Simutė, Saulė; Ermert, Laura; Krischer, Lion; Fichtner, Andreas
2016-01-01
We present a computational framework for the assimilation of local to global seismic data into a consistent model describing Earth structure on all seismically accessible scales. This Collaborative Seismic Earth Model (CSEM) is designed to meet the following requirements: (i) Flexible geometric parametrization, capable of capturing topography and bathymetry, as well as all aspects of potentially resolvable structure, including small-scale heterogeneities and deformations of internal discontinuities. (ii) Independence of any particular wave equation solver, in order to enable the combination of inversion techniques suitable for different types of seismic data. (iii) Physical parametrization that allows for full anisotropy and for variations in attenuation and density. While not all of these parameters are always resolvable, the assimilation of data that constrain any parameter subset should be possible. (iv) Ability to accommodate successive refinements through the incorporation of updates on any scale as new data or inversion techniques become available. (v) Enable collaborative Earth model construction. The structure of the initial CSEM is represented on a variable-resolution tetrahedral mesh. It is assembled from a long-wavelength 3-D global model into which several regional-scale tomographies are embedded. We illustrate the CSEM workflow of successive updating with two examples from Japan and the Western Mediterranean, where we constrain smaller scale structure using full-waveform inversion. Furthermore, we demonstrate the ability of the CSEM to act as a vehicle for the combination of different tomographic techniques with a joint full-waveform and traveltime ray tomography of Europe. This combination broadens the exploitable frequency range of the individual techniques, thereby improving resolution. We perform two iterations of a whole-Earth full-waveform inversion using a long-period reference data set from 225 globally recorded earthquakes. At this early stage of the CSEM development, the broad global updates mostly act to remove artefacts from the assembly of the initial CSEM. During the future evolution of the CSEM, the reference data set will be used to account for the influence of small-scale refinements on large-scale global structure. The CSEM as a computational framework is intended to help bridging the gap between local, regional and global tomography, and to contribute to the development of a global multiscale Earth model. While the current construction serves as a first proof of concept, future refinements and additions will require community involvement, which is welcome at this stage already.
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Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments
NASA Astrophysics Data System (ADS)
Rosenzweig, Cynthia; Ruane, Alex C.; Antle, John; Elliott, Joshua; Ashfaq, Muhammad; Chatta, Ashfaq Ahmad; Ewert, Frank; Folberth, Christian; Hathie, Ibrahima; Havlik, Petr; Hoogenboom, Gerrit; Lotze-Campen, Hermann; MacCarthy, Dilys S.; Mason-D'Croz, Daniel; Contreras, Erik Mencos; Müller, Christoph; Perez-Dominguez, Ignacio; Phillips, Meridel; Porter, Cheryl; Raymundo, Rubi M.; Sands, Ronald D.; Schleussner, Carl-Friedrich; Valdivia, Roberto O.; Valin, Hugo; Wiebe, Keith
2018-05-01
The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study aims to perform a proof of concept of the CGRA to demonstrate advantages and challenges of the proposed framework. This effort responds to the request by the UN Framework Convention on Climate Change (UNFCCC) for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) and Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble scenarios, global gridded crop models, global agricultural economics models, site-based crop models and within-country regional economics models. The CGRA consistently links disciplines, models and scales in order to track the complex chain of climate impacts and identify key vulnerabilities, feedbacks and uncertainties in managing future risk. CGRA proof-of-concept results show that, at the global scale, there are mixed areas of positive and negative simulated wheat and maize yield changes, with declines in some breadbasket regions, at both 1.5°C and 2.0°C. Declines are especially evident in simulations that do not take into account direct CO2 effects on crops. These projected global yield changes mostly resulted in increases in prices and areas of wheat and maize in two global economics models. Regional simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on the region and the crop. In conjunction with price changes from the global economics models, productivity declines in the Punjab, Pakistan, resulted in an increase in vulnerable households and the poverty rate. This article is part of the theme issue `The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.
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Rosenzweig, Cynthia; Ruane, Alex C; Antle, John; Elliott, Joshua; Ashfaq, Muhammad; Chatta, Ashfaq Ahmad; Ewert, Frank; Folberth, Christian; Hathie, Ibrahima; Havlik, Petr; Hoogenboom, Gerrit; Lotze-Campen, Hermann; MacCarthy, Dilys S; Mason-D'Croz, Daniel; Contreras, Erik Mencos; Müller, Christoph; Perez-Dominguez, Ignacio; Phillips, Meridel; Porter, Cheryl; Raymundo, Rubi M; Sands, Ronald D; Schleussner, Carl-Friedrich; Valdivia, Roberto O; Valin, Hugo; Wiebe, Keith
2018-05-13
The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study aims to perform a proof of concept of the CGRA to demonstrate advantages and challenges of the proposed framework. This effort responds to the request by the UN Framework Convention on Climate Change (UNFCCC) for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) and Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble scenarios, global gridded crop models, global agricultural economics models, site-based crop models and within-country regional economics models. The CGRA consistently links disciplines, models and scales in order to track the complex chain of climate impacts and identify key vulnerabilities, feedbacks and uncertainties in managing future risk. CGRA proof-of-concept results show that, at the global scale, there are mixed areas of positive and negative simulated wheat and maize yield changes, with declines in some breadbasket regions, at both 1.5°C and 2.0°C. Declines are especially evident in simulations that do not take into account direct CO 2 effects on crops. These projected global yield changes mostly resulted in increases in prices and areas of wheat and maize in two global economics models. Regional simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on the region and the crop. In conjunction with price changes from the global economics models, productivity declines in the Punjab, Pakistan, resulted in an increase in vulnerable households and the poverty rate.This article is part of the theme issue 'The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'. © 2018 The Authors.
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Tropospheric ozone simulated by a global-multi-regional two-way coupling model system
NASA Astrophysics Data System (ADS)
Yan, Y.; Lin, J.; Chen, J.; Hu, L.
2015-12-01
Current global chemical transport models are limited by horizontal resolutions (100-500 km), and they cannot capture small-scale processes affecting tropospheric ozone (O3). Here we use a recently built two-way coupling system of GEOS-Chem to simulate the global tropospheric O3 in 2009. The system couples the global model (~ 200 km) and its three nested models (~ 50 km) covering Asia, North America and Europe, respectively. Benefiting from the high resolution, the nested models better capture small-scale processes than the global model alone. In the coupling system, the nested models provide results to modify the global model simulation within respective nested domains while taking the lateral boundary conditions from the global model. Due to the "coupling" effects, the two-way system significantly improves the tropospheric O3 simulation upon the global model alone, as found by comparisons with a suite of ground (1420 sites from WDCGG, GMD, EMEP, and AQS), aircraft (HIPPO and MOZAIC), and satellite measurements (two OMI products). Compared to the global model alone, the two-way coupled simulation enhances the correlation in day-to-day variation of afternoon mean O3 with the ground measurements from 0.53 to 0.68 and reduces the mean model bias from 10.8 to 6.7 ppb. Regionally, the coupled model reduces the bias by 4.6 ppb over Europe, 3.9 ppb over North America, and 3.1 ppb over other regions. The two-way coupling brings O3 vertical profiles much closer to the HIPPO and MOZAIC data, reducing the tropospheric (0-9 km) mean bias by 3-10 ppb at most MOZAIC sites and by 5.3 ppb for HIPPO profiles. The two-way coupled simulation also reduces the global tropospheric column ozone by 3.0 DU (9.5%), bringing them closer to the OMI data in all seasons. Simulation improvements are more significant in the northern hemisphere, and are primarily a result of improved representation of the nonlinear ozone chemistry, including but not limited to urban-rural contrast. The two-way coupled simulation also reduces the global tropospheric mean hydroxyl radical by 5% with enhancements by 5% in lifetimes of methyl chloroform and methane, bringing them closer to observation-based estimates. Therefore improving model representations of small-scale processes are a critical step forward to understanding the global tropospheric chemistry.
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Optimal stomatal behaviour around the world
NASA Astrophysics Data System (ADS)
Lin, Yan-Shih; Medlyn, Belinda E.; Duursma, Remko A.; Prentice, I. Colin; Wang, Han; Baig, Sofia; Eamus, Derek; de Dios, Victor Resco; Mitchell, Patrick; Ellsworth, David S.; de Beeck, Maarten Op; Wallin, Göran; Uddling, Johan; Tarvainen, Lasse; Linderson, Maj-Lena; Cernusak, Lucas A.; Nippert, Jesse B.; Ocheltree, Troy W.; Tissue, David T.; Martin-Stpaul, Nicolas K.; Rogers, Alistair; Warren, Jeff M.; de Angelis, Paolo; Hikosaka, Kouki; Han, Qingmin; Onoda, Yusuke; Gimeno, Teresa E.; Barton, Craig V. M.; Bennie, Jonathan; Bonal, Damien; Bosc, Alexandre; Löw, Markus; Macinins-Ng, Cate; Rey, Ana; Rowland, Lucy; Setterfield, Samantha A.; Tausz-Posch, Sabine; Zaragoza-Castells, Joana; Broadmeadow, Mark S. J.; Drake, John E.; Freeman, Michael; Ghannoum, Oula; Hutley, Lindsay B.; Kelly, Jeff W.; Kikuzawa, Kihachiro; Kolari, Pasi; Koyama, Kohei; Limousin, Jean-Marc; Meir, Patrick; Lola da Costa, Antonio C.; Mikkelsen, Teis N.; Salinas, Norma; Sun, Wei; Wingate, Lisa
2015-05-01
Stomatal conductance (gs) is a key land-surface attribute as it links transpiration, the dominant component of global land evapotranspiration, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of gs in predictions of global water and carbon cycle changes, a global-scale database and an associated globally applicable model of gs that allow predictions of stomatal behaviour are lacking. Here, we present a database of globally distributed gs obtained in the field for a wide range of plant functional types (PFTs) and biomes. We find that stomatal behaviour differs among PFTs according to their marginal carbon cost of water use, as predicted by the theory underpinning the optimal stomatal model and the leaf and wood economics spectrum. We also demonstrate a global relationship with climate. These findings provide a robust theoretical framework for understanding and predicting the behaviour of gs across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of ecosystem productivity, energy balance and ecohydrological processes in a future changing climate.
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Improved simulation of tropospheric ozone by a global-multi-regional two-way coupling model system
NASA Astrophysics Data System (ADS)
Yan, Y.-Y.; Lin, J.-T.; Chen, J.; Hu, L.
2015-09-01
Small-scale nonlinear chemical and physical processes over pollution source regions affect the global ozone (O3) chemistry, 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 a recently built two-way coupling system of the GEOS-Chem CTM to simulate the 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. Benefiting from the high resolution, the nested models better capture small-scale processes than the global model alone. In the coupling system, the nested models provide results to modify the global model simulation within respective nested domains while taking the lateral boundary conditions from the global model. Due to the "coupling" effects, the two-way system significantly improves the tropospheric O3 simulation upon the global model alone, as found by comparisons with a suite of ground (1420 sites from WDCGG, GMD, EMEP, and AQS), aircraft (HIPPO and MOZAIC), and satellite measurements (two OMI products). Compared to the global model alone, the two-way coupled simulation enhances the correlation in day-to-day variation of afternoon mean O3 with the ground measurements from 0.53 to 0.68, and it reduces the mean model bias from 10.8 to 6.7 ppb in annual average afternoon O3. Regionally, the coupled model reduces the bias by 4.6 ppb over Europe, 3.9 ppb over North America, and 3.1 ppb over other regions. The two-way coupling brings O3 vertical profiles much closer to the HIPPO (for remote areas) and MOZAIC (for polluted regions) data, reducing the tropospheric (0-9 km) mean bias by 3-10 ppb at most MOZAIC sites and by 5.3 ppb for HIPPO profiles. The two-way coupled simulation also reduces the global tropospheric column ozone by 3.0 DU (9.5 %, annual mean), bringing them closer to the OMI data in all seasons. Simulation improvements are more significant in the northern hemisphere, and are primarily a result of improved representation of urban-rural contrast and other small-scale processes. The two-way coupled simulation also reduces the global tropospheric mean hydroxyl radical by 5 % with enhancements by 5 % in the lifetimes of methyl chloroform (from 5.58 to 5.87 yr) and methane (from 9.63 to 10.12 yr), bringing them closer to observation-based estimates. Improving model representations of small-scale processes are a critical step forward to understanding the global tropospheric chemistry.
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The Effect of Lateral Boundary Values on Atmospheric Mercury Simulations with the CMAQ Model
Simulation results from three global-scale models of atmospheric mercury have been used to define three sets of initial condition and boundary condition (IC/BC) data for regional-scale model simulations over North America using the Community Multi-scale Air Quality (CMAQ) model. ...
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Seismic waves and earthquakes in a global monolithic model
NASA Astrophysics Data System (ADS)
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.
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Open Source Tools for Assessment of Global Water Availability, Demands, and Scarcity
NASA Astrophysics Data System (ADS)
Li, X.; Vernon, C. R.; Hejazi, M. I.; Link, R. P.; Liu, Y.; Feng, L.; Huang, Z.; Liu, L.
2017-12-01
Water availability and water demands are essential factors for estimating water scarcity conditions. To reproduce historical observations and to quantify future changes in water availability and water demand, two open source tools have been developed by the JGCRI (Joint Global Change Research Institute): Xanthos and GCAM-STWD. Xanthos is a gridded global hydrologic model, designed to quantify and analyze water availability in 235 river basins. Xanthos uses a runoff generation and a river routing modules to simulate both historical and future estimates of total runoff and streamflows on a monthly time step at a spatial resolution of 0.5 degrees. GCAM-STWD is a spatiotemporal water disaggregation model used with the Global Change Assessment Model (GCAM) to spatially downscale global water demands for six major enduse sectors (irrigation, domestic, electricity generation, mining, and manufacturing) from the region scale to the scale of 0.5 degrees. GCAM-STWD then temporally downscales the gridded annual global water demands to monthly results. These two tools, written in Python, can be integrated to assess global, regional or basin-scale water scarcity or water stress. Both of the tools are extensible to ensure flexibility and promote contribution from researchers that utilize GCAM and study global water use and supply.
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NASA Astrophysics Data System (ADS)
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.
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Tethys – A Python Package for Spatial and Temporal Downscaling of Global Water Withdrawals
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.
Downscaling of water withdrawals from regional/national to local scale is a fundamental step and also a common problem when integrating large scale economic and integrated assessment models with high-resolution detailed sectoral models. Tethys, an open-access software written in Python, is developed with statistical downscaling algorithms, to spatially and temporally downscale water withdrawal data to a finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. Tethys is used to produce monthly global gridded water withdrawal products based on estimates from the Globalmore » Change Assessment Model (GCAM).« less
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Tethys – A Python Package for Spatial and Temporal Downscaling of Global Water Withdrawals
Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.; ...
2018-02-09
Downscaling of water withdrawals from regional/national to local scale is a fundamental step and also a common problem when integrating large scale economic and integrated assessment models with high-resolution detailed sectoral models. Tethys, an open-access software written in Python, is developed with statistical downscaling algorithms, to spatially and temporally downscale water withdrawal data to a finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. Tethys is used to produce monthly global gridded water withdrawal products based on estimates from the Globalmore » Change Assessment Model (GCAM).« less
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Multi-scale Modeling of Arctic Clouds
NASA Astrophysics Data System (ADS)
Hillman, B. R.; Roesler, E. L.; Dexheimer, D.
2017-12-01
The presence and properties of clouds are critically important to the radiative budget in the Arctic, but clouds are notoriously difficult to represent in global climate models (GCMs). The challenge stems partly from a disconnect in the scales at which these models are formulated and the scale of the physical processes important to the formation of clouds (e.g., convection and turbulence). Because of this, these processes are parameterized in large-scale models. Over the past decades, new approaches have been explored in which a cloud system resolving model (CSRM), or in the extreme a large eddy simulation (LES), is embedded into each gridcell of a traditional GCM to replace the cloud and convective parameterizations to explicitly simulate more of these important processes. This approach is attractive in that it allows for more explicit simulation of small-scale processes while also allowing for interaction between the small and large-scale processes. The goal of this study is to quantify the performance of this framework in simulating Arctic clouds relative to a traditional global model, and to explore the limitations of such a framework using coordinated high-resolution (eddy-resolving) simulations. Simulations from the global model are compared with satellite retrievals of cloud fraction partioned by cloud phase from CALIPSO, and limited-area LES simulations are compared with ground-based and tethered-balloon measurements from the ARM Barrow and Oliktok Point measurement facilities.
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NASA Technical Reports Server (NTRS)
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.
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Can We Use Regression Modeling to Quantify Mean Annual Streamflow at a Global-Scale?
NASA Astrophysics Data System (ADS)
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.
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Nonhydrostatic icosahedral atmospheric model (NICAM) for global cloud resolving simulations
NASA Astrophysics Data System (ADS)
Satoh, M.; Matsuno, T.; Tomita, H.; Miura, H.; Nasuno, T.; Iga, S.
2008-03-01
A new type of ultra-high resolution atmospheric global circulation model is developed. The new model is designed to perform "cloud resolving simulations" by directly calculating deep convection and meso-scale circulations, which play key roles not only in the tropical circulations but in the global circulations of the atmosphere. Since cores of deep convection have a few km in horizontal size, they have not directly been resolved by existing atmospheric general circulation models (AGCMs). In order to drastically enhance horizontal resolution, a new framework of a global atmospheric model is required; we adopted nonhydrostatic governing equations and icosahedral grids to the new model, and call it Nonhydrostatic ICosahedral Atmospheric Model (NICAM). In this article, we review governing equations and numerical techniques employed, and present the results from the unique 3.5-km mesh global experiments—with O(10 9) computational nodes—using realistic topography and land/ocean surface thermal forcing. The results show realistic behaviors of multi-scale convective systems in the tropics, which have not been captured by AGCMs. We also argue future perspective of the roles of the new model in the next generation atmospheric sciences.
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NASA Astrophysics Data System (ADS)
Wu, M. J.; Guo, P.; Fu, N. F.; Xu, T. L.; Xu, X. S.; Jin, H. L.; Hu, X. G.
2016-06-01
The ionosphere scale height is one of the most significant ionospheric parameters, which contains information about the ion and electron temperatures and dynamics in upper ionosphere. In this paper, an empirical orthogonal function (EOF) analysis method is applied to process all the ionospheric radio occultations of GPS/COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) from the year 2007 to 2011 to reconstruct a global ionospheric scale height model. This monthly medium model has spatial resolution of 5° in geomagnetic latitude (-87.5° ~ 87.5°) and temporal resolution of 2 h in local time. EOF analysis preserves the characteristics of scale height quite well in the geomagnetic latitudinal, anural, seasonal, and diurnal variations. In comparison with COSMIC measurements of the year of 2012, the reconstructed model indicates a reasonable accuracy. In order to improve the topside model of International Reference Ionosphere (IRI), we attempted to adopt the scale height model in the Bent topside model by applying a scale factor q as an additional constraint. With the factor q functioning in the exponent profile of topside ionosphere, the IRI scale height should be forced equal to the precise COSMIC measurements. In this way, the IRI topside profile can be improved to get closer to the realistic density profiles. Internal quality check of this approach is carried out by comparing COSMIC realistic measurements and IRI with or without correction, respectively. In general, the initial IRI model overestimates the topside electron density to some extent, and with the correction introduced by COSMIC scale height model, the deviation of vertical total electron content (VTEC) between them is reduced. Furthermore, independent validation with Global Ionospheric Maps VTEC implies a reasonable improvement in the IRI VTEC with the topside model correction.
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NASA Astrophysics Data System (ADS)
Alvarado, M. J.; Lonsdale, C. R.; Yokelson, R. J.; Travis, K.; Fischer, E. V.; Lin, J. C.
2014-12-01
Forecasting the impacts of biomass burning (BB) plumes on air quality is difficult due to the complex photochemistry that takes place in the concentrated young BB plumes. The spatial grid of global and regional scale Eulerian models is generally too large to resolve BB photochemistry, which can lead to errors in predicting the formation of secondary organic aerosol (SOA) and O3, as well as the partitioning of NOyspecies. AER's Aerosol Simulation Program (ASP v2.1) can be used within plume-scale Lagrangian models to simulate this complex photochemistry. We will present results of validation studies of the ASP model against aircraft observations of young BB smoke plumes. We will also present initial results from the coupling of ASP v2.1 into the Lagrangian particle dispersion model STILT-Chem in order to better examine the interactions between BB plume chemistry and dispersion. In addition, we have used ASP to develop a sub-grid scale parameterization of the near-source chemistry of BB plumes for use in regional and global air quality models. The parameterization takes inputs from the host model, such as solar zenith angle, temperature, and fire fuel type, and calculates enhancement ratios of O3, NOx, PAN, aerosol nitrate, and other NOy species, as well as organic aerosol (OA). We will present results from the ASP-based BB parameterization as well as its implementation into the global atmospheric composition model GEOS-Chem for the SEAC4RS campaign.
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A framework for global river flood risk assessment
NASA Astrophysics Data System (ADS)
Winsemius, H. C.; Van Beek, L. P. H.; Bouwman, A.; Ward, P. J.; Jongman, B.
2012-04-01
There is an increasing need for strategic global assessments of flood risks. Such assessments may be required by: (a) International Financing Institutes and Disaster Management Agencies to evaluate where, when, and which investments in flood risk mitigation are most required; (b) (re-)insurers, who need to determine their required coverage capital; and (c) large companies to account for risks of regional investments. In this contribution, we propose a framework for global river flood risk assessment. The framework combines coarse scale resolution hazard probability distributions, derived from global hydrological model runs (typical scale about 0.5 degree resolution) with high resolution estimates of exposure indicators. The high resolution is required because floods typically occur at a much smaller scale than the typical resolution of global hydrological models, and exposure indicators such as population, land use and economic value generally are strongly variable in space and time. The framework therefore estimates hazard at a high resolution ( 1 km2) by using a) global forcing data sets of the current (or in scenario mode, future) climate; b) a global hydrological model; c) a global flood routing model, and d) importantly, a flood spatial downscaling routine. This results in probability distributions of annual flood extremes as an indicator of flood hazard, at the appropriate resolution. A second component of the framework combines the hazard probability distribution with classical flood impact models (e.g. damage, affected GDP, affected population) to establish indicators for flood risk. The framework can be applied with a large number of datasets and models and sensitivities of such choices can be evaluated by the user. The framework is applied using the global hydrological model PCR-GLOBWB, combined with a global flood routing model. Downscaling of the hazard probability distributions to 1 km2 resolution is performed with a new downscaling algorithm, applied on a number of target regions. We demonstrate the use of impact models in these regions based on global GDP, population, and land use maps. In this application, we show sensitivities of the estimated risks with regard to the use of different climate input datasets, decisions made in the downscaling algorithm, and different approaches to establish distributed estimates of GDP and asset exposure to flooding.
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Walker, Anthony P.; Quaife, Tristan; van Bodegom, Peter M.; ...
2017-06-23
Here, the maximum photosynthetic carboxylation rate (V cmax) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V cmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr –1, 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated throughmore » to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated ( r = 0.85–0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V cmax variation in the field, particularly in northern latitudes.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Walker, Anthony P.; Quaife, Tristan; van Bodegom, Peter M.
Here, the maximum photosynthetic carboxylation rate (V cmax) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V cmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr –1, 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated throughmore » to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated ( r = 0.85–0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V cmax variation in the field, particularly in northern latitudes.« less
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Challenges of model transferability to data-scarce regions (Invited)
NASA Astrophysics Data System (ADS)
Samaniego, L. E.
2013-12-01
Developing the ability to globally predict the movement of water on the land surface at spatial scales from 1 to 5 km constitute one of grand challenges in land surface modelling. Copying with this grand challenge implies that land surface models (LSM) should be able to make reliable predictions across locations and/or scales other than those used for parameter estimation. In addition to that, data scarcity and quality impose further difficulties in attaining reliable predictions of water and energy fluxes at the scales of interest. Current computational limitations impose also seriously limitations to exhaustively investigate the parameter space of LSM over large domains (e.g. greater than half a million square kilometers). Addressing these challenges require holistic approaches that integrate the best techniques available for parameter estimation, field measurements and remotely sensed data at their native resolutions. An attempt to systematically address these issues is the multiscale parameterisation technique (MPR) that links high resolution land surface characteristics with effective model parameters. This technique requires a number of pedo-transfer functions and a much fewer global parameters (i.e. coefficients) to be inferred by calibration in gauged basins. The key advantage of this technique is the quasi-scale independence of the global parameters which enables to estimate global parameters at coarser spatial resolutions and then to transfer them to (ungauged) areas and scales of interest. In this study we show the ability of this technique to reproduce the observed water fluxes and states over a wide range of climate and land surface conditions ranging from humid to semiarid and from sparse to dense forested regions. Results of transferability of global model parameters in space (from humid to semi-arid basins) and across scales (from coarser to finer) clearly indicate the robustness of this technique. Simulations with coarse data sets (e.g. EOBS forcing 25x25 km2, FAO soil map 1:5000000) using parameters obtained with high resolution information (REGNIE forcing 1x1 km2, BUEK soil map 1:1000000) in different climatic regions indicate the potential of MPR for prediction in data-scarce regions. In this presentation, we will also discuss how the transferability of global model parameters across scales and locations helps to identify deficiencies in model structure and regionalization functions.
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Global Atmosphere Watch Workshop on Measurement-Model ...
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
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A COMPARISON OF INTERCELL METRICS ON DISCRETE GLOBAL GRID SYSTEMS
A discrete global grid system (DGGS) is a spatial data model that aids in global research by serving as a framework for environmental modeling, monitoring and sampling across the earth at multiple spatial scales. Topological and geometric criteria have been proposed to evaluate a...
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NASA Astrophysics Data System (ADS)
Gädeke, Anne; Gusyev, Maksym; Magome, Jun; Sugiura, Ai; Cullmann, Johannes; Takeuchi, Kuniyoshi
2015-04-01
The global flood risk assessment is prerequisite to set global measurable targets of post-Hyogo Framework for Action (HFA) that mobilize international cooperation and national coordination towards disaster risk reduction (DRR) and requires the establishment of a uniform flood risk assessment methodology on various scales. To address these issues, the International Flood Initiative (IFI) has initiated a Flagship Project, which was launched in year 2013, to support flood risk reduction benchmarking at global, national and local levels. In the Flagship Project road map, it is planned to identify the original risk (1), to identify the reduced risk (2), and to facilitate the risk reduction actions (3). In order to achieve this goal at global, regional and local scales, international research collaboration is absolutely necessary involving domestic and international institutes, academia and research networks such as UNESCO International Centres. The joint collaboration by ICHARM and BfG was the first attempt that produced the first step (1a) results on the flood discharge estimates with inundation maps under way. As a result of this collaboration, we demonstrate the outcomes of the first step of the IFI Flagship Project to identify flood hazard in the Rhine river basin on the global and local scale. In our assessment, we utilized a distributed hydrological Block-wise TOP (BTOP) model on 20-km and 0.5-km scales with local precipitation and temperature input data between 1980 and 2004. We utilized existing 20-km BTOP model, which is applied globally, and constructed the local scale 0.5-km BTOP model for the Rhine River basin. For the BTOP model results, both calibrated 20-km and 0.5-km BTOP models had similar statistical performance and represented observed flood river discharges, epecially for 1993 and 1995 floods. From 20-km and 0.5-km BTOP simulation, the flood discharges of the selected return period were estimated using flood frequency analysis and were comparable to the the river gauging station data at the German part of the Rhine river basin. This is an important finding that both 0.5-km and 20-km BTOP models produce similar flood peak discharges although the 0.5-km BTOP model results indicate the importance of scale in the local flood hazard assessment. In summary, we highlight that this study serves as a demonstrative example of institutional collaboration and is stepping stone for the next step implementation of the IFI Flagship Project.
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Continental scale data assimilation of discharge and its effect on flow predictions
NASA Astrophysics Data System (ADS)
Weerts, Albrecht; Schellekens, Jaap; van Dijk, Albert
2017-04-01
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 exist (Emmerton et al., 2016). Current global flood forecasting system heavily rely on forecast forcing (precipitation, temperature, reference potential evaporation) to derive initial state estimates of the hydrological model for the next forecast (e.g. by glueing the first day of subsequent forecast as proxy for the historical observed forcing). It is clear that this approach is not perfect and that data assimilation can help to overcome some of the weaknesses of this approach. So far most hydrologic da studies have focused mostly on catchment scale. Here we conduct a da experiment by assimilating multiple streamflow observations across the contiguous united states (CONUS) and Europe into a global hydrological model (W3RA) and run with and without localization method using OpenDA in the global flood forecasting information system (GLOFFIS). It is shown that assimilation of streamflow holds considerable potential for improving global scale flood forecasting (improving NSE scores from 0 to 0.7 and beyond). Weakness in the model (e.g. structural problems and missing processes) and forcing that influence the performance will be highlighted.
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NASA Astrophysics Data System (ADS)
Weerts, A.; Schellekens, J.; van Dijk, A.; Molenaar, R.
2016-12-01
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 exist (Emmerton et al., 2016). Current global flood forecasting system heavily rely on forecast forcing (precipitation, temperature, reference potential evaporation) to derive initial state estimates of the hydrological model for the next forecast (e.g. by glueing the first day of subsequent forecast as proxy for the historical observed forcing). It is clear that this approach is not perfect and that data assimilation can help to overcome some of the weaknesses of this approach. So far most hydrologic da studies have focused mostly on catchment scale. Here we conduct a da experiment by assimilating multiple streamflow observations across the contiguous united states (CONUS) into a global hydrological model (W3RA) and run with and without localization method using OpenDA in the global flood forecasting information system (GLOFFIS). It is shown that assimilation of streamflow holds considerable potential for improving global scale flood forecasting (improving NSE scores from 0 to 0.7 and beyond). Weakness in the model (e.g. structural problems and missing processes) and forcing that influence the performance will be highlighted.
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Global assessment of ocean carbon export by combining satellite observations and food-web models
NASA Astrophysics Data System (ADS)
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 < 10%) to factor of 2 changes in 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.
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NASA Astrophysics Data System (ADS)
Montzka, Carsten; Herbst, Michael; Weihermüller, Lutz; Verhoef, Anne; Vereecken, Harry
2017-07-01
Agroecosystem models, regional and global climate models, and numerical weather prediction models require adequate parameterization of soil hydraulic properties. These properties are fundamental for describing and predicting water and energy exchange processes at the transition zone between solid earth and atmosphere, and regulate evapotranspiration, infiltration and runoff generation. Hydraulic parameters describing the soil water retention (WRC) and hydraulic conductivity (HCC) curves are typically derived from soil texture via pedotransfer functions (PTFs). Resampling of those parameters for specific model grids is typically performed by different aggregation approaches such a spatial averaging and the use of dominant textural properties or soil classes. These aggregation approaches introduce uncertainty, bias and parameter inconsistencies throughout spatial scales due to nonlinear relationships between hydraulic parameters and soil texture. Therefore, we present a method to scale hydraulic parameters to individual model grids and provide a global data set that overcomes the mentioned problems. The approach is based on Miller-Miller scaling in the relaxed form by Warrick, that fits the parameters of the WRC through all sub-grid WRCs to provide an effective parameterization for the grid cell at model resolution; at the same time it preserves the information of sub-grid variability of the water retention curve by deriving local scaling parameters. Based on the Mualem-van Genuchten approach we also derive the unsaturated hydraulic conductivity from the water retention functions, thereby assuming that the local parameters are also valid for this function. In addition, via the Warrick scaling parameter λ, information on global sub-grid scaling variance is given that enables modellers to improve dynamical downscaling of (regional) climate models or to perturb hydraulic parameters for model ensemble output generation. The present analysis is based on the ROSETTA PTF of Schaap et al. (2001) applied to the SoilGrids1km data set of Hengl et al. (2014). The example data set is provided at a global resolution of 0.25° at https://doi.org/10.1594/PANGAEA.870605.
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Global marine bacterial diversity peaks at high latitudes in winter
Ladau, Joshua; Sharpton, Thomas J; Finucane, Mariel M; Jospin, Guillaume; Kembel, Steven W; O'Dwyer, James; Koeppel, Alexander F; Green, Jessica L; Pollard, Katherine S
2013-01-01
Genomic approaches to characterizing bacterial communities are revealing significant differences in diversity and composition between environments. But bacterial distributions have not been mapped at a global scale. Although current community surveys are way too sparse to map global diversity patterns directly, there is now sufficient data to fit accurate models of how bacterial distributions vary across different environments and to make global scale maps from these models. We apply this approach to map the global distributions of bacteria in marine surface waters. Our spatially and temporally explicit predictions suggest that bacterial diversity peaks in temperate latitudes across the world's oceans. These global peaks are seasonal, occurring 6 months apart in the two hemispheres, in the boreal and austral winters. This pattern is quite different from the tropical, seasonally consistent diversity patterns observed for most macroorganisms. However, like other marine organisms, surface water bacteria are particularly diverse in regions of high human environmental impacts on the oceans. Our maps provide the first picture of bacterial distributions at a global scale and suggest important differences between the diversity patterns of bacteria compared with other organisms. PMID:23514781
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The credibility challenge for global fluvial flood risk analysis
NASA Astrophysics Data System (ADS)
Trigg, M. A.; Birch, C. E.; Neal, J. C.; Bates, P. D.; Smith, A.; Sampson, C. C.; Yamazaki, D.; Hirabayashi, Y.; Pappenberger, F.; Dutra, E.; Ward, P. J.; Winsemius, H. C.; Salamon, P.; Dottori, F.; Rudari, R.; Kappes, M. S.; Simpson, A. L.; Hadzilacos, G.; Fewtrell, T. J.
2016-09-01
Quantifying flood hazard is an essential component of resilience planning, emergency response, and mitigation, including insurance. Traditionally undertaken at catchment and national scales, recently, efforts have intensified to estimate flood risk globally to better allow consistent and equitable decision making. Global flood hazard models are now a practical reality, thanks to improvements in numerical algorithms, global datasets, computing power, and coupled modelling frameworks. Outputs of these models are vital for consistent quantification of global flood risk and in projecting the impacts of climate change. However, the urgency of these tasks means that outputs are being used as soon as they are made available and before such methods have been adequately tested. To address this, we compare multi-probability flood hazard maps for Africa from six global models and show wide variation in their flood hazard, economic loss and exposed population estimates, which has serious implications for model credibility. While there is around 30%-40% agreement in flood extent, our results show that even at continental scales, there are significant differences in hazard magnitude and spatial pattern between models, notably in deltas, arid/semi-arid zones and wetlands. This study is an important step towards a better understanding of modelling global flood hazard, which is urgently required for both current risk and climate change projections.
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Five regional scale models with a horizontal domain covering the European continent and its surrounding seas, one hemispheric and one global scale model participated in an atmospheric mercury modelling intercomparison study. Model-predicted concentrations in ambient air were comp...
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Progress in the Development of a Global Quasi-3-D Multiscale Modeling Framework
NASA Astrophysics Data System (ADS)
Jung, J.; Konor, C. S.; Randall, D. A.
2017-12-01
The Quasi-3-D Multiscale Modeling Framework (Q3D MMF) is a second-generation MMF, which has following advances over the first-generation MMF: 1) The cloud-resolving models (CRMs) that replace conventional parameterizations are not confined to the large-scale dynamical-core grid cells, and are seamlessly connected to each other, 2) The CRMs sense the three-dimensional large- and cloud-scale environment, 3) Two perpendicular sets of CRM channels are used, and 4) The CRMs can resolve the steep surface topography along the channel direction. The basic design of the Q3D MMF has been developed and successfully tested in a limited-area modeling framework. Currently, global versions of the Q3D MMF are being developed for both weather and climate applications. The dynamical cores governing the large-scale circulation in the global Q3D MMF are selected from two cube-based global atmospheric models. The CRM used in the model is the 3-D nonhydrostatic anelastic Vector-Vorticity Model (VVM), which has been tested with the limited-area version for its suitability for this framework. As a first step of the development, the VVM has been reconstructed on the cubed-sphere grid so that it can be applied to global channel domains and also easily fitted to the large-scale dynamical cores. We have successfully tested the new VVM by advecting a bell-shaped passive tracer and simulating the evolutions of waves resulted from idealized barotropic and baroclinic instabilities. For improvement of the model, we also modified the tracer advection scheme to yield positive-definite results and plan to implement a new physics package that includes a double-moment microphysics and an aerosol physics. The interface for coupling the large-scale dynamical core and the VVM is under development. In this presentation, we shall describe the recent progress in the development and show some test results.
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Zhang, Ling Yu; Liu, Zhao Gang
2017-12-01
Based on the data collected from 108 permanent plots of the forest resources survey in Maoershan Experimental Forest Farm during 2004-2016, this study investigated the spatial distribution of recruitment trees in natural secondary forest by global Poisson regression and geographically weighted Poisson regression (GWPR) with four bandwidths of 2.5, 5, 10 and 15 km. The simulation effects of the 5 regressions and the factors influencing the recruitment trees in stands were analyzed, a description was given to the spatial autocorrelation of the regression residuals on global and local levels using Moran's I. The results showed that the spatial distribution of the number of natural secondary forest recruitment was significantly influenced by stands and topographic factors, especially average DBH. The GWPR model with small scale (2.5 km) had high accuracy of model fitting, a large range of model parameter estimates was generated, and the localized spatial distribution effect of the model parameters was obtained. The GWPR model at small scale (2.5 and 5 km) had produced a small range of model residuals, and the stability of the model was improved. The global spatial auto-correlation of the GWPR model residual at the small scale (2.5 km) was the lowe-st, and the local spatial auto-correlation was significantly reduced, in which an ideal spatial distribution pattern of small clusters with different observations was formed. The local model at small scale (2.5 km) was much better than the global model in the simulation effect on the spatial distribution of recruitment tree number.
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NASA Astrophysics Data System (ADS)
Harris, L.; Lin, S. J.; Zhou, L.; Chen, J. H.; Benson, R.; Rees, S.
2016-12-01
Limited-area convection-permitting models have proven useful for short-range NWP, but are unable to interact with the larger scales needed for longer lead-time skill. A new global forecast model, fvGFS, has been designed combining a modern nonhydrostatic dynamical core, the GFDL Finite-Volume Cubed-Sphere dynamical core (FV3) with operational GFS physics and initial conditions, and has been shown to provide excellent global skill while improving representation of small-scale phenomena. The nested-grid capability of FV3 allows us to build a regional-to-global variable-resolution model to efficiently refine to 3-km grid spacing over the Continental US. The use of two-way grid nesting allows us to reach these resolutions very efficiently, with the operational requirement easily attainable on current supercomputing systems.Even without a boundary-layer or advanced microphysical scheme appropriate for convection-perrmitting resolutions, the effectiveness of fvGFS can be demonstrated for a variety of weather events. We demonstrate successful proof-of-concept simulations of a variety of phenomena. We show the capability to develop intense hurricanes with realistic fine-scale eyewalls and rainbands. The new model also produces skillful predictions of severe weather outbreaks and of organized mesoscale convective systems. Fine-scale orographic and boundary-layer phenomena are also simulated with excellent fidelity by fvGFS. Further expected improvements are discussed, including the introduction of more sophisticated microphysics and of scale-aware convection schemes.
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NASA Technical Reports Server (NTRS)
Chang, Jinfeng; Ciais, Philippe; Herrero, Mario; Havlik, Petr; Campioli, Matteo; Zhang, Xianzhou; Bai, Yongfei; Viovy, Nicolas; Joiner, Joanna; Wang, Xuhui;
2016-01-01
Grassland management type (grazed or mown) and intensity (intensive or extensive) play a crucial role in the greenhouse gas balance and surface energy budget of this biome, both at field scale and at large spatial scale. However, global gridded historical information on grassland management intensity is not available. Combining modelled grass-biomass productivity with statistics of the grass-biomass demand by livestock, we reconstruct gridded maps of grassland management intensity from 1901 to 2012. These maps include the minimum area of managed vs. maximum area of unmanaged grasslands and the fraction of mown vs. grazed area at a resolution of 0.5deg by 0.5deg. The grass-biomass demand is derived from a livestock dataset for 2000, extended to cover the period 19012012. The grass-biomass supply (i.e. forage grass from mown grassland and biomass grazed) is simulated by the process-based model ORCHIDEE-GM driven by historical climate change, risingCO2 concentration, and changes in nitrogen fertilization. The global area of managed grassland obtained in this study increases from 6.1 x 10(exp 6) km(exp 2) in 1901 to 12.3 x 10(exp 6) kmI(exp 2) in 2000, although the expansion pathway varies between different regions. ORCHIDEE-GM also simulated augmentation in global mean productivity and herbage-use efficiency over managed grassland during the 20th century, indicating a general intensification of grassland management at global scale but with regional differences. The gridded grassland management intensity maps are model dependent because they depend on modelled productivity. Thus specific attention was given to the evaluation of modelled productivity against a series of observations from site-level net primary productivity (NPP) measurements to two global satellite products of gross primary productivity (GPP) (MODIS-GPP and SIF data). Generally, ORCHIDEE-GM captures the spatial pattern, seasonal cycle, and inter-annual variability of grassland productivity at global scale well and thus is appropriate for global applications presented here.
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A stochastic two-scale model for pressure-driven flow between rough surfaces
Larsson, Roland; Lundström, Staffan; Wall, Peter; Almqvist, Andreas
2016-01-01
Seal surface topography typically consists of global-scale geometric features as well as local-scale roughness details and homogenization-based approaches are, therefore, readily applied. These provide for resolving the global scale (large domain) with a relatively coarse mesh, while resolving the local scale (small domain) in high detail. As the total flow decreases, however, the flow pattern becomes tortuous and this requires a larger local-scale domain to obtain a converged solution. Therefore, a classical homogenization-based approach might not be feasible for simulation of very small flows. In order to study small flows, a model allowing feasibly-sized local domains, for really small flow rates, is developed. Realization was made possible by coupling the two scales with a stochastic element. Results from numerical experiments, show that the present model is in better agreement with the direct deterministic one than the conventional homogenization type of model, both quantitatively in terms of flow rate and qualitatively in reflecting the flow pattern. PMID:27436975
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Yee, Susan Harrell; Barron, Mace G
2010-02-01
Coral reefs have experienced extensive mortality over the past few decades as a result of temperature-induced mass bleaching events. There is an increasing realization that other environmental factors, including water mixing, solar radiation, water depth, and water clarity, interact with temperature to either exacerbate bleaching or protect coral from mass bleaching. The relative contribution of these factors to variability in mass bleaching at a global scale has not been quantified, but can provide insights when making large-scale predictions of mass bleaching events. Using data from 708 bleaching surveys across the globe, a framework was developed to predict the probability of moderate or severe bleaching as a function of key environmental variables derived from global-scale remote-sensing data. The ability of models to explain spatial and temporal variability in mass bleaching events was quantified. Results indicated approximately 20% improved accuracy of predictions of bleaching when solar radiation and water mixing, in addition to elevated temperature, were incorporated into models, but predictive accuracy was variable among regions. Results provide insights into the effects of environmental parameters on bleaching at a global scale.
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NASA Technical Reports Server (NTRS)
Swift, Daniel W.
1991-01-01
The primary methodology during the grant period has been the use of micro or meso-scale simulations to address specific questions concerning magnetospheric processes related to the aurora and substorm morphology. This approach, while useful in providing some answers, has its limitations. Many of the problems relating to the magnetosphere are inherently global and kinetic. Effort during the last year of the grant period has increasingly focused on development of a global-scale hybrid code to model the entire, coupled magnetosheath - magnetosphere - ionosphere system. In particular, numerical procedures for curvilinear coordinate generation and exactly conservative differencing schemes for hybrid codes in curvilinear coordinates have been developed. The new computer algorithms and the massively parallel computer architectures now make this global code a feasible proposition. Support provided by this project has played an important role in laying the groundwork for the eventual development or a global-scale code to model and forecast magnetospheric weather.
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Multi-scale predictions of massive conifer mortality due to chronic temperature rise
NASA Astrophysics Data System (ADS)
McDowell, N. G.; Williams, A. P.; Xu, C.; Pockman, W. T.; Dickman, L. T.; Sevanto, S.; Pangle, R.; Limousin, J.; Plaut, J.; Mackay, D. S.; Ogee, J.; Domec, J. C.; Allen, C. D.; Fisher, R. A.; Jiang, X.; Muss, J. D.; Breshears, D. D.; Rauscher, S. A.; Koven, C.
2016-03-01
Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April-August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted >=50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.
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Multi-scale predictions of massive conifer mortality due to chronic temperature rise
McDowell, Nathan G.; Williams, A.P.; Xu, C.; Pockman, W. T.; Dickman, L. T.; Sevanto, Sanna; Pangle, R.; Limousin, J.; Plaut, J.J.; Mackay, D.S.; Ogee, J.; Domec, Jean-Christophe; Allen, Craig D.; Fisher, Rosie A.; Jiang, X.; Muss, J.D.; Breshears, D.D.; Rauscher, Sara A.; Koven, C.
2016-01-01
Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April–August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted ≥50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.
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Improving Global Health Education: Development of a Global Health Competency Model
Ablah, Elizabeth; Biberman, Dorothy A.; Weist, Elizabeth M.; Buekens, Pierre; Bentley, Margaret E.; Burke, Donald; Finnegan, John R.; Flahault, Antoine; Frenk, Julio; Gotsch, Audrey R.; Klag, Michael J.; Lopez, Mario Henry Rodriguez; Nasca, Philip; Shortell, Stephen; Spencer, Harrison C.
2014-01-01
Although global health is a recommended content area for the future of education in public health, no standardized global health competency model existed for master-level public health students. Without such a competency model, academic institutions are challenged to ensure that students are able to demonstrate the knowledge, skills, and attitudes (KSAs) needed for successful performance in today's global health workforce. The Association of Schools of Public Health (ASPH) sought to address this need by facilitating the development of a global health competency model through a multistage modified-Delphi process. Practitioners and academic global health experts provided leadership and guidance throughout the competency development process. The resulting product, the Global Health Competency Model 1.1, includes seven domains and 36 competencies. The Global Health Competency Model 1.1 provides a platform for engaging educators, students, and global health employers in discussion of the KSAs needed to improve human health on a global scale. PMID:24445206
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U.S. GODAE: Global Ocean Prediction With the HYbrid Coordinate Ocean Model (HYCOM)
2009-06-01
REPORT DATE (DD-MM- YYYY) 12-08-2009 2. REPORT TYPE Journal Article 3. DATES COVERED (From - To) 4. TITLE AND SUBTITLE U.S. GODAE: Global ...the lerformance and application of eddy-resolving, real-time global - and basin-scale ocean prediction systems using the HYbrid Coordinate Ocean...prediction system outputs. In addnion to providing real-time, eddy-resolving global - and basin-scale ocean prediction systems for the US Navy and NOAA, this
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Global-scale high-resolution ( 1 km) modelling of mean, maximum and minimum annual streamflow
NASA Astrophysics Data System (ADS)
Barbarossa, Valerio; Huijbregts, Mark; Hendriks, Jan; Beusen, Arthur; Clavreul, Julie; King, Henry; Schipper, Aafke
2017-04-01
Quantifying mean, maximum and minimum annual flow (AF) of rivers at ungauged sites is essential for a number of applications, including assessments of global water supply, ecosystem integrity and water footprints. AF metrics can be quantified with spatially explicit process-based models, which might be overly time-consuming and data-intensive for this purpose, or with empirical regression models that predict AF metrics based on climate and catchment characteristics. Yet, so far, regression models have mostly been developed at a regional scale and the extent to which they can be extrapolated to other regions is not known. We developed global-scale regression models that quantify mean, maximum and minimum AF as function of catchment area and catchment-averaged slope, elevation, and mean, maximum and minimum annual precipitation and air temperature. We then used these models to obtain global 30 arc-seconds (˜ 1 km) maps of mean, maximum and minimum AF for each year from 1960 through 2015, based on a newly developed hydrologically conditioned digital elevation model. We calibrated our regression models based on observations of discharge and catchment characteristics from about 4,000 catchments worldwide, ranging from 100 to 106 km2 in size, and validated them against independent measurements as well as the output of a number of process-based global hydrological models (GHMs). The variance explained by our regression models ranged up to 90% and the performance of the models compared well with the performance of existing GHMs. Yet, our AF maps provide a level of spatial detail that cannot yet be achieved by current GHMs.
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Optimal stomatal behaviour around the world
Lin, Yan-Shih; Medlyn, Belinda E.; Duursma, Remko A.; ...
2015-03-02
Stomatal conductance (g s) is a key land-surface attribute as it links transpiration, the dominant component of global land evapotranspiration, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of g s in predictions of global water and carbon cycle changes, a global-scale database and an associated globally applicable model of g s that allow predictions of stomatal behaviour are lacking. Here, we present a database of globally distributed g s obtained in the field for a wide range of plant functional types (PFTs) and biomes. We find that stomatal behaviour differs among PFTs accordingmore » to their marginal carbon cost of water use, as predicted by the theory underpinning the optimal stomatal model 1 and the leaf and wood economics spectrum 2,3. We also demonstrate a global relationship with climate. In conclusion, these findings provide a robust theoretical framework for understanding and predicting the behaviour of g s across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of ecosystem productivity, energy balance and ecohydrological processes in a future changing climate.« less
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NASA Technical Reports Server (NTRS)
Vincent, Dayton G.; Robertson, Franklin
1993-01-01
The research sponsored by this grant is a continuation and an extension of the work conducted under a previous contract, 'South Pacific Convergence Zone and Global-Scale Circulations'. In the prior work, we conducted a detailed investigation of the South Pacific convergence zone (SPCZ), and documented many of its significant features and characteristics. We also conducted studies of its interaction with global-scale circulation features through the use of both observational and modeling studies. The latter was accomplished toward the end of the contract when Dr. James Hurrell, then a Ph.D. candidate, successfully ported the NASA GLA general circulation model (GCM) to Purdue University. In our present grant, we have expanded our previous research to include studies of other convectively-driven circulation systems in the tropics besides the SPCZ. Furthermore, we have continued to examine the relationship between these convective systems and global-scale circulation patterns. Our recent research efforts have focused on three objectives: (1) determining the periodicity of large-scale bands of organized convection in the tropics, primarily synoptic to intraseasonal time scales in the Southern Hemisphere; (2) examining the relative importance of tropical versus mid-latitude forcing for Southern Hemisphere summertime subtropical jets, particularly over the Pacific Ocean; and (3) estimating tropical precipitation, especially over oceans, using observational and budget methods. A summary list of our most significant accomplishments in the past year is given.
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Multi-scale predictions of coniferous forest mortality in the northern hemisphere
NASA Astrophysics Data System (ADS)
McDowell, N. G.
2015-12-01
Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our incomplete understanding of the fundamental physiological thresholds of vegetation mortality during drought limits our ability to accurately simulate future vegetation distributions and associated climate feedbacks. Here we integrate experimental evidence with models to show potential widespread loss of needleleaf evergreen trees (NET; ~ conifers) within the Southwest USA by 2100; with rising temperature being the primary cause of mortality. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ypd) thresholds (April-August mean) beyond which photosynthesis, stomatal and hydraulic conductance, and carbohydrate availability approached zero. Empirical and mechanistic models accurately predicted NET Ypd, and 91% of predictions (10/11) exceeded mortality thresholds within the 21st century due to temperature rise. Completely independent global models predicted >50% loss of northern hemisphere NET by 2100, consistent with the findings for Southwest USA. The global models disagreed with the ecosystem process models in regards to future mortality in Southwest USA, however, highlighting the potential underestimates of future NET mortality as simulated by the global models and signifying the importance of improving regional predictions. Taken together, these results from the validated regional predictions and the global simulations predict global-scale conifer loss in coming decades under projected global warming.
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NASA Astrophysics Data System (ADS)
José Polo, María; José Pérez-Palazón, María; Saénz de Rodrigáñez, Marta; Pimentel, Rafael; Arheimer, Berit
2017-04-01
Global hydrological models provide scientists and technicians with distributed data over medium to large areas from which assessment of water resource planning and use can be easily performed. However, scale conflicts between global models' spatial resolution and the local significant spatial scales in heterogeneous areas usually pose a constraint for the direct use and application of these models' results. The SWICCA (Service for Water Indicators in Climate Change Adaptation) Platform developed under the Copernicus Climate Change Service (C3S) offers a wide range of both climate and hydrological indicators obtained on a global scale with different time and spatial resolutions. Among the different study cases supporting the SWICCA demonstration of local impact assessment, the Sierra Nevada study case (South Spain) is a representative example of mountainous coastal catchments in the Mediterranean region. This work shows the lessons learnt during the study case development to derive local impact indicator tailored to suit the local end-users of water resource in this snow-dominated area. Different approaches were followed to select the most accurate method to downscale the global data and variables to the local level in a highly abrupt topography, in a sequential step approach. 1) SWICCA global climate variable downscaling followed by river flow simulation from a local hydrological model in selected control points in the catchment, together with 2) SWICCA global river flow values downscaling to the control points followed by corrections with local transfer functions were both tested against the available local river flow series of observations during the reference period. This test was performed for the different models and the available spatial resolutions included in the SWICCA platform. From the results, the second option, that is, the use of SWICCA river flow variables, performed the best approximations, once the local transfer functions were applied to the global values and an additional correction was performed based on the relative anomalies obtained instead of the absolute values. This approach was used to derive the future projections of selected local indicators for each end-user in the area under different climate change scenarios. Despite the spatial scale conflicts, the SWICCA river flow indicators (simulated by the E-HYPEv3.1.2 model) succeeded in approximating the observations during the reference period 1970-2000 when provided on a catchment scale, once local transfer functions and further anomaly correction were performed. Satisfactory results were obtained on a monthly scale for river flow in the main stream of the watershed, and on a daily scale for the headwater streams. The accessibility to the hydrological model WiMMed, which includes a snow module, locally validated in the study area has been crucial to downscale the SWICCA results and prove their usefulness.
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How do glacier inventory data aid global glacier assessments and projections?
NASA Astrophysics Data System (ADS)
Hock, R.
2017-12-01
Large-scale glacier modeling relies heavily on datasets that are collected by many individuals across the globe, but managed and maintained in a coordinated fashion by international data centers. The Global Terrestrial Network for Glaciers (GTN-G) provides the framework for coordinating and making available a suite of data sets such as the Randolph Glacier Inventory (RGI), the Glacier Thickness Dataset or the World Glacier Inventory (WGI). These datasets have greatly increased our ability to assess global-scale glacier mass changes. These data have also been vital for projecting the glacier mass changes of all mountain glaciers in the world outside the Greenland and Antarctic ice sheet, a total >200,000 glaciers covering an area of more than 700,000 km2. Using forcing from 8 to 15 GCMs and 4 different emission scenarios, global-scale glacier evolution models project multi-model mean net mass losses of all glaciers between 7 cm and 24 cm sea-level equivalent by the end of the 21st century. Projected mass losses vary greatly depending on the choice of the forcing climate and emission scenario. Insufficiently constrained model parameters likely are an important reason for large differences found among these studies even when forced by the same emission scenario, especially on regional scales.
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Regional model calculations over annual cycles have pointed to the need for accurately representing impacts of long-range transport. Linking regional and global scale models have met with mixed success as biases in the global model can propagate and influence regional calculatio...
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NASA Astrophysics Data System (ADS)
Bloom, A. A.; Exbrayat, J. F.; van der Velde, I.; Peters, W.; Williams, M.
2014-12-01
Large uncertainties preside over terrestrial carbon flux estimates on a global scale. In particular, the strongly coupled dynamics between net ecosystem productivity and disturbance C losses are poorly constrained. To gain an improved understanding of ecosystem C dynamics from regional to global scale, we apply a Markov Chain Monte Carlo based model-data-fusion approach into the CArbon DAta-MOdel fraMework (CARDAMOM). We assimilate MODIS LAI and burned area, plant-trait data, and use the Harmonized World Soil Database (HWSD) and maps of above ground biomass as prior knowledge for initial conditions. We optimize model parameters based on (a) globally spanning observations and (b) ecological and dynamic constraints that force single parameter values and parameter inter-dependencies to be representative of real world processes. We determine the spatial and temporal dynamics of major terrestrial C fluxes and model parameter values on a global scale (GPP = 123 +/- 8 Pg C yr-1 & NEE = -1.8 +/- 2.7 Pg C yr-1). We further show that the incorporation of disturbance fluxes, and accounting for their instantaneous or delayed effect, is of critical importance in constraining global C cycle dynamics, particularly in the tropics. In a higher resolution case study centred on the Amazon Basin we show how fires not only trigger large instantaneous emissions of burned matter, but also how they are responsible for a sustained reduction of up to 50% in plant uptake following the depletion of biomass stocks. The combination of these two fire-induced effects leads to a 1 g C m-2 d-1reduction in the strength of the net terrestrial carbon sink. Through our simulations at regional and global scale, we advocate the need to assimilate disturbance metrics in global terrestrial carbon cycle models to bridge the gap between globally spanning terrestrial carbon cycle data and the full dynamics of the ecosystem C cycle. Disturbances are especially important because their quick occurrence may have long-term effects on ecosystems. Our synthetic simulations show that while tropical ecosystems uptake may reach pre-disturbance level after a decade, biomass stocks would most likely need more than a century to recover from a single extreme disturbance event.
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Potential for using regional and global datasets for national scale ecosystem service modelling
NASA Astrophysics Data System (ADS)
Maxwell, Deborah; Jackson, Bethanna
2016-04-01
Ecosystem service models are increasingly being used by planners and policy makers to inform policy development and decisions about national-level resource management. Such models allow ecosystem services to be mapped and quantified, and subsequent changes to these services to be identified and monitored. In some cases, the impact of small scale changes can be modelled at a national scale, providing more detailed information to decision makers about where to best focus investment and management interventions that could address these issues, while moving toward national goals and/or targets. National scale modelling often uses national (or local) data (for example, soils, landcover and topographical information) as input. However, there are some places where fine resolution and/or high quality national datasets cannot be easily obtained, or do not even exist. In the absence of such detailed information, regional or global datasets could be used as input to such models. There are questions, however, about the usefulness of these coarser resolution datasets and the extent to which inaccuracies in this data may degrade predictions of existing and potential ecosystem service provision and subsequent decision making. Using LUCI (the Land Utilisation and Capability Indicator) as an example predictive model, we examine how the reliability of predictions change when national datasets of soil, landcover and topography are substituted with coarser scale regional and global datasets. We specifically look at how LUCI's predictions of where water services, such as flood risk, flood mitigation, erosion and water quality, change when national data inputs are replaced by regional and global datasets. Using the Conwy catchment, Wales, as a case study, the land cover products compared are the UK's Land Cover Map (2007), the European CORINE land cover map and the ESA global land cover map. Soils products include the National Soil Map of England and Wales (NatMap) and the European Soils Database. NEXTmap elevation data, which covers the UK and parts of continental Europe, are compared to global AsterDEM and SRTM30 topographical products. While the regional and global datasets can be used to fill gaps in data requirements, the coarser resolution of these datasets means that there is greater aggregation of information over larger areas. This loss of detail impacts on the reliability of model output, particularly where significant discrepancies between datasets exist. The implications of this loss of detail in terms of spatial planning and decision making is discussed. Finally, in the context of broader development the need for better nationally and globally available data to allow LUCI and other ecosystem models to become more globally applicable is highlighted.
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Plant leaf traits, canopy processes, and global atmospheric chemistry interactions.
NASA Astrophysics Data System (ADS)
Guenther, A. B.
2017-12-01
Plants produce and emit a diverse array of volatile metabolites into the atmosphere that participate in chemical reactions that influence distributions of air pollutants and short-lived climate forcers including organic aerosol, ozone and methane. It is now widely accepted that accurate estimates of these emissions are required as inputs for regional air quality and global climate models. Predicting these emissions is complicated by the large number of volatile organic compounds, driving variables (e.g., temperature, solar radiation, abiotic and biotic stresses) and processes operating across a range of scales. Modeling efforts to characterize emission magnitude and variations will be described along with an assessment of the observations available for parameterizing and evaluating these models including discussion of the limitations and challenges associated with existing model approaches. A new approach for simulating canopy scale organic emissions on regional to global scales will be described and compared with leaf, canopy and regional scale flux measurements. The importance of including additional compounds and processes as well as improving estimates of existing ones will also be discussed.
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NASA Astrophysics Data System (ADS)
Nakano, Masuo; Wada, Akiyoshi; Sawada, Masahiro; Yoshimura, Hiromasa; Onishi, Ryo; Kawahara, Shintaro; Sasaki, Wataru; Nasuno, Tomoe; Yamaguchi, Munehiko; Iriguchi, Takeshi; Sugi, Masato; Takeuchi, Yoshiaki
2017-03-01
Recent advances in high-performance computers facilitate operational numerical weather prediction by global hydrostatic atmospheric models with horizontal resolutions of ˜ 10 km. Given further advances in such computers and the fact that the hydrostatic balance approximation becomes invalid for spatial scales < 10 km, the development of global nonhydrostatic models with high accuracy is urgently required. The Global 7 km mesh nonhydrostatic Model Intercomparison Project for improving TYphoon forecast (TYMIP-G7) is designed to understand and statistically quantify the advantages of high-resolution nonhydrostatic global atmospheric models to improve tropical cyclone (TC) prediction. A total of 137 sets of 5-day simulations using three next-generation nonhydrostatic global models with horizontal resolutions of 7 km and a conventional hydrostatic global model with a horizontal resolution of 20 km were run on the Earth Simulator. The three 7 km mesh nonhydrostatic models are the nonhydrostatic global spectral atmospheric Double Fourier Series Model (DFSM), the Multi-Scale Simulator for the Geoenvironment (MSSG) and the Nonhydrostatic ICosahedral Atmospheric Model (NICAM). The 20 km mesh hydrostatic model is the operational Global Spectral Model (GSM) of the Japan Meteorological Agency. Compared with the 20 km mesh GSM, the 7 km mesh models reduce systematic errors in the TC track, intensity and wind radii predictions. The benefits of the multi-model ensemble method were confirmed for the 7 km mesh nonhydrostatic global models. While the three 7 km mesh models reproduce the typical axisymmetric mean inner-core structure, including the primary and secondary circulations, the simulated TC structures and their intensities in each case are very different for each model. In addition, the simulated track is not consistently better than that of the 20 km mesh GSM. These results suggest that the development of more sophisticated initialization techniques and model physics is needed to further improve the TC prediction.
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Centennial-scale Holocene climate variations amplified by Antarctic Ice Sheet discharge
NASA Astrophysics Data System (ADS)
Bakker, Pepijn; Clark, Peter U.; Golledge, Nicholas R.; Schmittner, Andreas; Weber, Michael E.
2017-01-01
Proxy-based indicators of past climate change show that current global climate models systematically underestimate Holocene-epoch climate variability on centennial to multi-millennial timescales, with the mismatch increasing for longer periods. Proposed explanations for the discrepancy include ocean-atmosphere coupling that is too weak in models, insufficient energy cascades from smaller to larger spatial and temporal scales, or that global climate models do not consider slow climate feedbacks related to the carbon cycle or interactions between ice sheets and climate. Such interactions, however, are known to have strongly affected centennial- to orbital-scale climate variability during past glaciations, and are likely to be important in future climate change. Here we show that fluctuations in Antarctic Ice Sheet discharge caused by relatively small changes in subsurface ocean temperature can amplify multi-centennial climate variability regionally and globally, suggesting that a dynamic Antarctic Ice Sheet may have driven climate fluctuations during the Holocene. We analysed high-temporal-resolution records of iceberg-rafted debris derived from the Antarctic Ice Sheet, and performed both high-spatial-resolution ice-sheet modelling of the Antarctic Ice Sheet and multi-millennial global climate model simulations. Ice-sheet responses to decadal-scale ocean forcing appear to be less important, possibly indicating that the future response of the Antarctic Ice Sheet will be governed more by long-term anthropogenic warming combined with multi-centennial natural variability than by annual or decadal climate oscillations.
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Local versus global knowledge in the Barabási-Albert scale-free network model.
Gómez-Gardeñes, Jesús; Moreno, Yamir
2004-03-01
The scale-free model of Barabási and Albert (BA) gave rise to a burst of activity in the field of complex networks. In this paper, we revisit one of the main assumptions of the model, the preferential attachment (PA) rule. We study a model in which the PA rule is applied to a neighborhood of newly created nodes and thus no global knowledge of the network is assumed. We numerically show that global properties of the BA model such as the connectivity distribution and the average shortest path length are quite robust when there is some degree of local knowledge. In contrast, other properties such as the clustering coefficient and degree-degree correlations differ and approach the values measured for real-world networks.
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NASA Technical Reports Server (NTRS)
Gregg, Watson W.; Busalacchi, Antonio (Technical Monitor)
2000-01-01
A coupled ocean general circulation, biogeochemical, and radiative model was constructed to evaluate and understand the nature of seasonal variability of chlorophyll and nutrients in the global oceans. Biogeochemical processes in the model are determined from the influences of circulation and turbulence dynamics, irradiance availability. and the interactions among three functional phytoplankton groups (diatoms. chlorophytes, and picoplankton) and three nutrients (nitrate, ammonium, and silicate). Basin scale (greater than 1000 km) model chlorophyll results are in overall agreement with CZCS pigments in many global regions. Seasonal variability observed in the CZCS is also represented in the model. Synoptic scale (100-1000 km) comparisons of imagery are generally in conformance although occasional departures are apparent. Model nitrate distributions agree with in situ data, including seasonal dynamics, except for the equatorial Atlantic. The overall agreement of the model with satellite and in situ data sources indicates that the model dynamics offer a reasonably realistic simulation of phytoplankton and nutrient dynamics on synoptic scales. This is especially true given that initial conditions are homogenous chlorophyll fields. The success of the model in producing a reasonable representation of chlorophyll and nutrient distributions and seasonal variability in the global oceans is attributed to the application of a generalized, processes-driven approach as opposed to regional parameterization and the existence of multiple phytoplankton groups with different physiological and physical properties. These factors enable the model to simultaneously represent many aspects of the great diversity of physical, biological, chemical, and radiative environments encountered in the global oceans.
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Scaling a Convection-Resolving RCM to Near-Global Scales
NASA Astrophysics Data System (ADS)
Leutwyler, D.; Fuhrer, O.; Chadha, T.; Kwasniewski, G.; Hoefler, T.; Lapillonne, X.; Lüthi, D.; Osuna, C.; Schar, C.; Schulthess, T. C.; Vogt, H.
2017-12-01
In the recent years, first decade-long kilometer-scale resolution RCM simulations have been performed on continental-scale computational domains. However, the size of the planet Earth is still an order of magnitude larger and thus the computational implications of performing global climate simulations at this resolution are challenging. We explore the gap between the currently established RCM simulations and global simulations by scaling the GPU accelerated version of the COSMO model to a near-global computational domain. To this end, the evolution of an idealized moist baroclinic wave has been simulated over the course of 10 days with a grid spacing of up to 930 m. The computational mesh employs 36'000 x 16'001 x 60 grid points and covers 98.4% of the planet's surface. The code shows perfect weak scaling up to 4'888 Nodes of the Piz Daint supercomputer and yields 0.043 simulated years per day (SYPD) which is approximately one seventh of the 0.2-0.3 SYPD required to conduct AMIP-type simulations. However, at half the resolution (1.9 km) we've observed 0.23 SYPD. Besides formation of frontal precipitating systems containing embedded explicitly-resolved convective motions, the simulations reveal a secondary instability that leads to cut-off warm-core cyclonic vortices in the cyclone's core, once the grid spacing is refined to the kilometer scale. The explicit representation of embedded moist convection and the representation of the previously unresolved instabilities exhibit a physically different behavior in comparison to coarser-resolution simulations. The study demonstrates that global climate simulations using kilometer-scale resolution are imminent and serves as a baseline benchmark for global climate model applications and future exascale supercomputing systems.
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Taylor, Lyla L; Banwart, Steve A; Valdes, Paul J; Leake, Jonathan R; Beerling, David J
2012-02-19
Global weathering of calcium and magnesium silicate rocks provides the long-term sink for atmospheric carbon dioxide (CO(2)) 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.
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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
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Wildhaber, Mark L.; Wikle, Christopher K.; Anderson, Christopher J.; Franz, Kristie J.; Moran, Edward H.; Dey, Rima; Mader, Helmut; Kraml, Julia
2012-01-01
Climate change operates over a broad range of spatial and temporal scales. Understanding its effects on ecosystems requires multi-scale models. For understanding effects on fish populations of riverine ecosystems, climate predicted by coarse-resolution Global Climate Models must be downscaled to Regional Climate Models to watersheds to river hydrology to population response. An additional challenge is quantifying sources of uncertainty given the highly nonlinear nature of interactions between climate variables and community level processes. We present a modeling approach for understanding and accomodating uncertainty by applying multi-scale climate models and a hierarchical Bayesian modeling framework to Midwest fish population dynamics and by linking models for system components together by formal rules of probability. The proposed hierarchical modeling approach will account for sources of uncertainty in forecasts of community or population response. The goal is to evaluate the potential distributional changes in an ecological system, given distributional changes implied by a series of linked climate and system models under various emissions/use scenarios. This understanding will aid evaluation of management options for coping with global climate change. In our initial analyses, we found that predicted pallid sturgeon population responses were dependent on the climate scenario considered.
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Modelling Groundwater Depletion at Regional and Global Scales: Present State and Future Prospects.
NASA Technical Reports Server (NTRS)
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.
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Modeling Groundwater Depletion at Regional and Global Scales: Present State and Future Prospects
NASA Astrophysics Data System (ADS)
Wada, Yoshihide
2016-03-01
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.
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A web system of virtual morphometric globes for Mars and the Moon
NASA Astrophysics Data System (ADS)
Florinsky, I. V.; Garov, A. S.; Karachevtseva, I. P.
2018-09-01
We developed a web system of virtual morphometric globes for Mars and the Moon. As the initial data, we used 15-arc-minutes gridded global digital elevation models (DEMs) extracted from the Mars Orbiter Laser Altimeter (MOLA) and the Lunar Orbiter Laser Altimeter (LOLA) gridded archives. We derived global digital models of sixteen morphometric variables including horizontal, vertical, minimal, and maximal curvatures, as well as catchment area and topographic index. The morphometric models were integrated into the web system developed as a distributed application consisting of a client front-end and a server back-end. The following main functions are implemented in the system: (1) selection of a morphometric variable; (2) two-dimensional visualization of a calculated global morphometric model; (3) 3D visualization of a calculated global morphometric model on the sphere surface; (4) change of a globe scale; and (5) globe rotation by an arbitrary angle. Free, real-time web access to the system is provided. The web system of virtual morphometric globes can be used for geological and geomorphological studies of Mars and the Moon at the global, continental, and regional scales.
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Global-scale combustion sources of organic aerosols: sensitivity to formation and removal mechanisms
NASA Astrophysics Data System (ADS)
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.
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Globalizing Lessons Learned from Regional-scale Observatories
NASA Astrophysics Data System (ADS)
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 required to support the global network. Globalization includes the development of international networks to coordinate activities, such as the Global HF Radar network supported by GEO, the global Everyone's Glider Organization supported by WMO and IOC, and the need for professional training supported by MTS.
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Devaraju, N; Bala, G; Nemani, R
2015-09-01
Land-use changes since the start of the industrial era account for nearly one-third of the cumulative anthropogenic CO2 emissions. In addition to the greenhouse effect of CO2 emissions, changes in land use also affect climate via changes in surface physical properties such as albedo, evapotranspiration and roughness length. Recent modelling studies suggest that these biophysical components may be comparable with biochemical effects. In regard to climate change, the effects of these two distinct processes may counterbalance one another both regionally and, possibly, globally. In this article, through hypothetical large-scale deforestation simulations using a global climate model, we contrast the implications of afforestation on ameliorating or enhancing anthropogenic contributions from previously converted (agricultural) land surfaces. Based on our review of past studies on this subject, we conclude that the sum of both biophysical and biochemical effects should be assessed when large-scale afforestation is used for countering global warming, and the net effect on global mean temperature change depends on the location of deforestation/afforestation. Further, although biochemical effects trigger global climate change, biophysical effects often cause strong local and regional climate change. The implication of the biophysical effects for adaptation and mitigation of climate change in agriculture and agroforestry sectors is discussed. © 2014 John Wiley & Sons Ltd.
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Development of the Next Generation Air Quality Modeling System
A next generation air quality modeling system is being developed at the U.S. EPA to enable modeling of air quality from global to regional to (eventually) local scales. We envision that the system will have three configurations: 1. Global meteorology with seamless mesh refinemen...
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All is not loss: plant biodiversity in the anthropocene.
Ellis, Erle C; Antill, Erica C; Kreft, Holger
2012-01-01
Anthropogenic global changes in biodiversity are generally portrayed in terms of massive native species losses or invasions caused by recent human disturbance. Yet these biodiversity changes and others caused directly by human populations and their use of land tend to co-occur as long-term biodiversity change processes in the Anthropocene. Here we explore contemporary anthropogenic global patterns in vascular plant species richness at regional landscape scales by combining spatially explicit models and estimates for native species loss together with gains in exotics caused by species invasions and the introduction of agricultural domesticates and ornamental exotic plants. The patterns thus derived confirm that while native losses are likely significant across at least half of Earth's ice-free land, model predictions indicate that plant species richness has increased overall in most regional landscapes, mostly because species invasions tend to exceed native losses. While global observing systems and models that integrate anthropogenic species loss, introduction and invasion at regional landscape scales remain at an early stage of development, integrating predictions from existing models within a single assessment confirms their vast global extent and significance while revealing novel patterns and their potential drivers. Effective global stewardship of plant biodiversity in the Anthropocene will require integrated frameworks for observing, modeling and forecasting the different forms of anthropogenic biodiversity change processes at regional landscape scales, towards conserving biodiversity within the novel plant communities created and sustained by human systems.
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All Is Not Loss: Plant Biodiversity in the Anthropocene
Ellis, Erle C.; Antill, Erica C.; Kreft, Holger
2012-01-01
Anthropogenic global changes in biodiversity are generally portrayed in terms of massive native species losses or invasions caused by recent human disturbance. Yet these biodiversity changes and others caused directly by human populations and their use of land tend to co-occur as long-term biodiversity change processes in the Anthropocene. Here we explore contemporary anthropogenic global patterns in vascular plant species richness at regional landscape scales by combining spatially explicit models and estimates for native species loss together with gains in exotics caused by species invasions and the introduction of agricultural domesticates and ornamental exotic plants. The patterns thus derived confirm that while native losses are likely significant across at least half of Earth's ice-free land, model predictions indicate that plant species richness has increased overall in most regional landscapes, mostly because species invasions tend to exceed native losses. While global observing systems and models that integrate anthropogenic species loss, introduction and invasion at regional landscape scales remain at an early stage of development, integrating predictions from existing models within a single assessment confirms their vast global extent and significance while revealing novel patterns and their potential drivers. Effective global stewardship of plant biodiversity in the Anthropocene will require integrated frameworks for observing, modeling and forecasting the different forms of anthropogenic biodiversity change processes at regional landscape scales, towards conserving biodiversity within the novel plant communities created and sustained by human systems. PMID:22272360
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Spectral decomposition of internal gravity wave sea surface height in global models
NASA Astrophysics Data System (ADS)
Savage, Anna C.; Arbic, Brian K.; Alford, Matthew H.; Ansong, Joseph K.; Farrar, J. Thomas; Menemenlis, Dimitris; O'Rourke, Amanda K.; Richman, James G.; Shriver, Jay F.; Voet, Gunnar; Wallcraft, Alan J.; Zamudio, Luis
2017-10-01
Two global ocean models ranging in horizontal resolution from 1/12° to 1/48° are used to study the space and time scales of sea surface height (SSH) signals associated with internal gravity waves (IGWs). Frequency-horizontal wavenumber SSH spectral densities are computed over seven regions of the world ocean from two simulations of the HYbrid Coordinate Ocean Model (HYCOM) and three simulations of the Massachusetts Institute of Technology general circulation model (MITgcm). High wavenumber, high-frequency SSH variance follows the predicted IGW linear dispersion curves. The realism of high-frequency motions (>0.87 cpd) in the models is tested through comparison of the frequency spectral density of dynamic height variance computed from the highest-resolution runs of each model (1/25° HYCOM and 1/48° MITgcm) with dynamic height variance frequency spectral density computed from nine in situ profiling instruments. These high-frequency motions are of particular interest because of their contributions to the small-scale SSH variability that will be observed on a global scale in the upcoming Surface Water and Ocean Topography (SWOT) satellite altimetry mission. The variance at supertidal frequencies can be comparable to the tidal and low-frequency variance for high wavenumbers (length scales smaller than ˜50 km), especially in the higher-resolution simulations. In the highest-resolution simulations, the high-frequency variance can be greater than the low-frequency variance at these scales.
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NASA Astrophysics Data System (ADS)
Acharya, S.; Kaplan, D. A.; Casey, S.; Cohen, M. J.; Jawitz, J. W.
2015-05-01
Self-organized landscape patterning can arise in response to multiple processes. Discriminating among alternative patterning mechanisms, particularly where experimental manipulations are untenable, requires process-based models. Previous modeling studies have attributed patterning in the Everglades (Florida, USA) to sediment redistribution and anisotropic soil hydraulic properties. In this work, we tested an alternate theory, the self-organizing-canal (SOC) hypothesis, by developing a cellular automata model that simulates pattern evolution via local positive feedbacks (i.e., facilitation) coupled with a global negative feedback based on hydrology. The model is forced by global hydroperiod that drives stochastic transitions between two patch types: ridge (higher elevation) and slough (lower elevation). We evaluated model performance using multiple criteria based on six statistical and geostatistical properties observed in reference portions of the Everglades landscape: patch density, patch anisotropy, semivariogram ranges, power-law scaling of ridge areas, perimeter area fractal dimension, and characteristic pattern wavelength. Model results showed strong statistical agreement with reference landscapes, but only when anisotropically acting local facilitation was coupled with hydrologic global feedback, for which several plausible mechanisms exist. Critically, the model correctly generated fractal landscapes that had no characteristic pattern wavelength, supporting the invocation of global rather than scale-specific negative feedbacks.
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NASA Astrophysics Data System (ADS)
Acharya, S.; Kaplan, D. A.; Casey, S.; Cohen, M. J.; Jawitz, J. W.
2015-01-01
Self-organized landscape patterning can arise in response to multiple processes. Discriminating among alternative patterning mechanisms, particularly where experimental manipulations are untenable, requires process-based models. Previous modeling studies have attributed patterning in the Everglades (Florida, USA) to sediment redistribution and anisotropic soil hydraulic properties. In this work, we tested an alternate theory, the self-organizing canal (SOC) hypothesis, by developing a cellular automata model that simulates pattern evolution via local positive feedbacks (i.e., facilitation) coupled with a global negative feedback based on hydrology. The model is forced by global hydroperiod that drives stochastic transitions between two patch types: ridge (higher elevation) and slough (lower elevation). We evaluated model performance using multiple criteria based on six statistical and geostatistical properties observed in reference portions of the Everglades landscape: patch density, patch anisotropy, semivariogram ranges, power-law scaling of ridge areas, perimeter area fractal dimension, and characteristic pattern wavelength. Model results showed strong statistical agreement with reference landscapes, but only when anisotropically acting local facilitation was coupled with hydrologic global feedback, for which several plausible mechanisms exist. Critically, the model correctly generated fractal landscapes that had no characteristic pattern wavelength, supporting the invocation of global rather than scale-specific negative feedbacks.
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Hierarchies from D-brane instantons in globally defined calabi-yau orientifolds
Cvetič, Mirjam; Weigand, Timo
2008-06-01
We construct the first globally consistent semi-realistic Type I string vacua on an elliptically fibered manifold where the zero modes of the Euclidean D1-instanton sector allow for the generation of non-perturbative Majorana masses of an intermediate scale. In another class of global models, a D1-brane instanton can generate a Polonyi-type superpotential breaking supersymmetry at an exponentially suppressed scale.
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Regional-Scale Forcing and Feedbacks from Alternative Scenarios of Global-Scale Land Use Change
NASA Astrophysics Data System (ADS)
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 work demonstrates the importance of land use in shaping future patterns of climate change, both globally and regionally.
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From Dynamic Global Vegetation Modelling to Real-World regional and local Application
NASA Astrophysics Data System (ADS)
Steinkamp, J.; Forrest, M.; Kamm, K.; Leiblein-Wild, M.; Pachzelt, A.; Werner, C.; Hickler, T.
2015-12-01
Dynamic (global) vegetation models (DGVM) can be applied to any spatial resolution on the local, national, continental and global scale given suitable climatic and geographic input forcing data. LPJ-GUESS, the main DGVM applied in our research group, uses the plant functional type (PFT) concept in the global setup with typically about 10-20 tree PFTs (subdivided into tropical, temperate and boreal) and two herbaceous PFTs by default. When modelling smaller spatial extents, such as continental (e.g. Europe/North America) national domains, or individual sites (e.g. Frankfurt, Germany), i.e. the scale of decision making, it becomes necessary to refine the PFT representation, the model initialization and validation and, in some case, to include additional processes. I will present examples of LPJ-GUESS applications at the continental to local scale performed by our working group including i.) a European simulation representing the main tree species and Mediterranean shrubs, ii.) a climate impact study for Turkey, iii.) coupled dynamic large grazer-vegetation modelling across Africa and, iv.) modelling an allergenic and in Europe invasive shrub (Ambrosia artemisiifolia), iv.) simulating water usage by an oak-pine forest stand near Frankfurt, and v.) stand specific differences in modelling at the FACE sites. Finally, I will present some thoughts on how to advance the models in terms of more detailed and realistic PFT or species parameterizations accounting for adaptive functional trait responses also within species.
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EPA RESEARCH HIGHLIGHTS -- MODELS-3/CMAQ OFFERS COMPREHENSIVE APPROACH TO AIR QUALITY MODELING
Regional and global coordinated efforts are needed to address air quality problems that are growing in complexity and scope. Models-3 CMAQ contains a community multi-scale air quality modeling system for simulating urban to regional scale pollution problems relating to troposphe...
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Five regional scale models with a horizontal domain covering the European continent and its surrounding seas, two hemispheric and one global scale model participated in the atmospheric Hg modelling intercomparison study. The models were compared between each other and with availa...
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Natural electroweak breaking from a mirror symmetry.
Chacko, Z; Goh, Hock-Seng; Harnik, Roni
2006-06-16
We present "twin Higgs models," simple realizations of the Higgs boson as a pseudo Goldstone boson that protect the weak scale from radiative corrections up to scales of order 5-10 TeV. In the ultraviolet these theories have a discrete symmetry which interchanges each standard model particle with a corresponding particle which transforms under a twin or a mirror standard model gauge group. In addition, the Higgs sector respects an approximate global symmetry. When this global symmetry is broken, the discrete symmetry tightly constrains the form of corrections to the pseudo Goldstone Higgs potential, allowing natural electroweak symmetry breaking. Precision electroweak constraints are satisfied by construction. These models demonstrate that, contrary to the conventional wisdom, stabilizing the weak scale does not require new light particles charged under the standard model gauge groups.
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Posttest analysis of the 1:6-scale reinforced concrete containment
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pfeiffer, P.A.; Kennedy, J.M.; Marchertas, A.H.
A prediction of the response of the Sandia National Laboratories 1:6- scale reinforced concrete containment model test was made by Argonne National Laboratory. ANL along with nine other organizations performed a detailed nonlinear response analysis of the 1:6-scale model containment subjected to overpressurization in the fall of 1986. The two-dimensional code TEMP-STRESS and the three-dimensional NEPTUNE code were utilized (1) to predict the global response of the structure, (2) to identify global failure sites and the corresponding failure pressures and (3) to identify some local failure sites and pressure levels. A series of axisymmetric models was studied with the two-dimensionalmore » computer program TEMP-STRESS. The comparison of these pretest computations with test data from the containment model has provided a test for the capability of the respective finite element codes to predict global failure modes, and hence serves as a validation of these codes. Only the two-dimensional analyses will be discussed in this paper. 3 refs., 10 figs.« less
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NASA Astrophysics Data System (ADS)
Turkeltaub, T.; Ascott, M.; Gooddy, D.; Jia, X.; Shao, M.; Binley, A. M.
2017-12-01
Understanding deep percolation, travel time processes and nitrate storage in the unsaturated zone at a regional scale is crucial for sustainable management of many groundwater systems. Recently, global hydrological models have been developed to quantify the water balance at such scales and beyond. However, the coarse spatial resolution of the global hydrological models can be a limiting factor when analysing regional processes. This study compares simulations of water flow and nitrate storage based on regional and global scale approaches. The first approach was applied over the Loess Plateau of China (LPC) to investigate the water fluxes and nitrate storage and travel time to the LPC groundwater system. Using raster maps of climate variables, land use data and soil parameters enabled us to determine fluxes by employing Richards' equation and the advection - dispersion equation. These calculations were conducted for each cell on the raster map in a multiple 1-D column approach. In the second approach, vadose zone travel times and nitrate storage were estimated by coupling groundwater recharge (PCR-GLOBWB) and nitrate leaching (IMAGE) models with estimates of water table depth and unsaturated zone porosity. The simulation results of the two methods indicate similar spatial groundwater recharge, nitrate storage and travel time distribution. Intensive recharge rates are located mainly at the south central and south west parts of the aquifer's outcrops. Particularly low recharge rates were simulated in the top central area of the outcrops. However, there are significant discrepancies between the simulated absolute recharge values, which might be related to the coarse scale that is used in the PCR-GLOBWB model, leading to smoothing of the recharge estimations. Both models indicated large nitrate inventories in the south central and south west parts of the aquifer's outcrops and the shortest travel times in the vadose zone are in the south central and east parts of the outcrops. Our results suggest that, for the LPC at least, global scale models might be useful for highlighting the locations with higher recharge rates potential and nitrate contamination risk. Global modelling simulations appear ideal as a primary step in recognizing locations which require investigations at the plot, field and local scales.
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NASA Astrophysics Data System (ADS)
Im, Eun-Soon; Coppola, Erika; Giorgi, Filippo
2010-05-01
Since anthropogenic climate change is a rather important factor for the future human life all over the planet and its effects are not globally uniform, climate information at regional or local scales become more and more important for an accurate assessment of the potential impact of climate change on societies and ecosystems. High resolution information with suitably fine-scale for resolving complex geographical features could be a critical factor for successful linkage between climate models and impact assessment studies. However, scale mismatch between them still remains major problem. One method for overcoming the resolution limitations of global climate models and for adding regional details to coarse-grid global projections is to use dynamical downscaling by means of a regional climate model. In this study, the ECHAM5/MPI-OM (1.875 degree) A1B scenario simulation has been dynamically downscaled by using two different approaches within the framework of RegCM3 modeling system. First, a mosaic-type parameterization of subgrid-scale topography and land use (Sub-BATS) is applied over the European Alpine region. The Sub-BATS system is composed of 15 km coarse-grid cell and 3 km sub-grid cell. Second, we developed the RegCM3 one-way double-nested system, with the mother domain encompassing the eastern regions of Asia at 60 km grid spacing and the nested domain covering the Korean Peninsula at 20 km grid spacing. By comparing the regional climate model output and the driving global model ECHAM5/MPI-OM output, it is possible to estimate the added value of physically-based dynamical downscaling when for example impact studies at hydrological scale are performed.
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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.
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Assessing global vegetation activity using spatio-temporal Bayesian modelling
NASA Astrophysics Data System (ADS)
Mulder, Vera L.; van Eck, Christel M.; Friedlingstein, Pierre; Regnier, Pierre A. G.
2016-04-01
This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support our hypothesis. That is, the change of vegetation in space and time may be better understood when modelling vegetation change as both a dynamic and multivariate process. Therefore, future research will focus on a multivariate dynamical spatio-temporal modelling approach. This ongoing research is performed within the context of the project "Global impacts of hydrological and climatic extremes on vegetation" (project acronym: SAT-EX) which is part of the Belgian research programme for Earth Observation Stereo III.
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NASA Astrophysics Data System (ADS)
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.
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Walker, Anthony P; Quaife, Tristan; van Bodegom, Peter M; De Kauwe, Martin G; Keenan, Trevor F; Joiner, Joanna; Lomas, Mark R; MacBean, Natasha; Xu, Chongang; Yang, Xiaojuan; Woodward, F Ian
2017-09-01
The maximum photosynthetic carboxylation rate (V cmax ) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V cmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr -1 , 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated through to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r = 0.85-0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V cmax variation in the field, particularly in northern latitudes. © 2017 UT-Battelle LLC. New Phytologist © 2017 New Phytologist Trust.
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NASA Technical Reports Server (NTRS)
Walker, Anthony P.; Quaife, Tristan; Van Bodegom, Peter M.; De Kauwe, Martin G.; Keenan, Trevor F.; Joiner, Joanna; Lomas, Mark R.; MacBean, Natasha; Xu, Chongang; Yang, Xiaojuan;
2017-01-01
The maximum photosynthetic carboxylation rate (V (sub cmax)) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V(sub cmax) distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 petagrams of Carbon (PgC) per year, 65 percent of the range of a recent model intercomparison of global GPP. The variation in GPP propagated through to a 27percent coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r equals 0.85-0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V(sub cmax) variation in the field, particularly in northern latitudes.
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Global changes in biogeochemical cycles in response to human activities
NASA Technical Reports Server (NTRS)
Moore, Berrien, III; Melillo, Jerry
1994-01-01
The main objective of our research was to characterize biogeochemical cycles at continental and global scales in both terrestrial and aquatic ecosystems. This characterization applied to both natural ecosystems and those disturbed by human activity. The primary elements of interest were carbon and nitrogen and the analysis sought to quantify standing stocks and dynamic cycling processes. The translocation of major nutrients from the terrestrial landscape to the atmosphere (via trace gases) and to fluvial systems (via leaching, erosional losses, and point source pollution) were of particular importance to this study. Our aim was to develop the first generation of Earth System Models. Our research was organized around the construction and testing of component biogeochemical models which treated terrestrial ecosystem processes, aquatic nutrient transport through drainage basins, and trace gas exchanges at the continental and global scale. A suite of three complementary models were defined within this construct. The models were organized to operate at a 1/2 degree latitude by longitude level of spatial resolution and to execute at a monthly time step. This discretization afforded us the opportunity to understand the dynamics of the biosphere down to subregional scales, while simultaneously placing these dynamics into a global context.
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NASA Astrophysics Data System (ADS)
Watson, James R.; Stock, Charles A.; Sarmiento, Jorge L.
2015-11-01
Modeling the dynamics of marine populations at a global scale - from phytoplankton to fish - is necessary if we are to quantify how climate change and other broad-scale anthropogenic actions affect the supply of marine-based food. Here, we estimate the abundance and distribution of fish biomass using a simple size-based food web model coupled to simulations of global ocean physics and biogeochemistry. We focus on the spatial distribution of biomass, identifying highly productive regions - shelf seas, western boundary currents and major upwelling zones. In the absence of fishing, we estimate the total ocean fish biomass to be ∼ 2.84 ×109 tonnes, similar to previous estimates. However, this value is sensitive to the choice of parameters, and further, allowing fish to move had a profound impact on the spatial distribution of fish biomass and the structure of marine communities. In particular, when movement is implemented the viable range of large predators is greatly increased, and stunted biomass spectra characterizing large ocean regions in simulations without movement, are replaced with expanded spectra that include large predators. These results highlight the importance of considering movement in global-scale ecological models.
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Ingber, Lester; Nunez, Paul L
2011-02-01
The dynamic behavior of scalp potentials (EEG) is apparently due to some combination of global and local processes with important top-down and bottom-up interactions across spatial scales. In treating global mechanisms, we stress the importance of myelinated axon propagation delays and periodic boundary conditions in the cortical-white matter system, which is topologically close to a spherical shell. By contrast, the proposed local mechanisms are multiscale interactions between cortical columns via short-ranged non-myelinated fibers. A mechanical model consisting of a stretched string with attached nonlinear springs demonstrates the general idea. The string produces standing waves analogous to large-scale coherent EEG observed in some brain states. The attached springs are analogous to the smaller (mesoscopic) scale columnar dynamics. Generally, we expect string displacement and EEG at all scales to result from both global and local phenomena. A statistical mechanics of neocortical interactions (SMNI) calculates oscillatory behavior consistent with typical EEG, within columns, between neighboring columns via short-ranged non-myelinated fibers, across cortical regions via myelinated fibers, and also derives a string equation consistent with the global EEG model. Copyright © 2010 Elsevier Inc. All rights reserved.
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Space Observations for Global Change
NASA Technical Reports Server (NTRS)
Rasool, S. I.
1991-01-01
There is now compelling evidence that man's activities are changing both the composition of the atmospheric and the global landscape quite drastically. The consequences of these changes on the global climate of the 21st century is currently a hotly debated subject. Global models of a coupled Earth-ocean-atmosphere system are still very primitive and progress in this area appears largely data limited, specially over the global biosphere. A concerted effort on monitoring biospheric functions on scales from pixels to global and days to decades needs to be coordinated on an international scale in order to address the questions related to global change. An international program of space observations and ground research was described.
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Magliocca, Nicholas R; Brown, Daniel G; Ellis, Erle C
2014-01-01
Local changes in land use result from the decisions and actions of land-users within land systems, which are structured by local and global environmental, economic, political, and cultural contexts. Such cross-scale causation presents a major challenge for developing a general understanding of how local decision-making shapes land-use changes at the global scale. This paper implements a generalized agent-based model (ABM) as a virtual laboratory to explore how global and local processes influence the land-use and livelihood decisions of local land-users, operationalized as settlement-level agents, across the landscapes of six real-world test sites. Test sites were chosen in USA, Laos, and China to capture globally-significant variation in population density, market influence, and environmental conditions, with land systems ranging from swidden to commercial agriculture. Publicly available global data were integrated into the ABM to model cross-scale effects of economic globalization on local land-use decisions. A suite of statistics was developed to assess the accuracy of model-predicted land-use outcomes relative to observed and random (i.e. null model) landscapes. At four of six sites, where environmental and demographic forces were important constraints on land-use choices, modeled land-use outcomes were more similar to those observed across sites than the null model. At the two sites in which market forces significantly influenced land-use and livelihood decisions, the model was a poorer predictor of land-use outcomes than the null model. Model successes and failures in simulating real-world land-use patterns enabled the testing of hypotheses on land-use decision-making and yielded insights on the importance of missing mechanisms. The virtual laboratory approach provides a practical framework for systematic improvement of both theory and predictive skill in land change science based on a continual process of experimentation and model enhancement.
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Magliocca, Nicholas R.; Brown, Daniel G.; Ellis, Erle C.
2014-01-01
Local changes in land use result from the decisions and actions of land-users within land systems, which are structured by local and global environmental, economic, political, and cultural contexts. Such cross-scale causation presents a major challenge for developing a general understanding of how local decision-making shapes land-use changes at the global scale. This paper implements a generalized agent-based model (ABM) as a virtual laboratory to explore how global and local processes influence the land-use and livelihood decisions of local land-users, operationalized as settlement-level agents, across the landscapes of six real-world test sites. Test sites were chosen in USA, Laos, and China to capture globally-significant variation in population density, market influence, and environmental conditions, with land systems ranging from swidden to commercial agriculture. Publicly available global data were integrated into the ABM to model cross-scale effects of economic globalization on local land-use decisions. A suite of statistics was developed to assess the accuracy of model-predicted land-use outcomes relative to observed and random (i.e. null model) landscapes. At four of six sites, where environmental and demographic forces were important constraints on land-use choices, modeled land-use outcomes were more similar to those observed across sites than the null model. At the two sites in which market forces significantly influenced land-use and livelihood decisions, the model was a poorer predictor of land-use outcomes than the null model. Model successes and failures in simulating real-world land-use patterns enabled the testing of hypotheses on land-use decision-making and yielded insights on the importance of missing mechanisms. The virtual laboratory approach provides a practical framework for systematic improvement of both theory and predictive skill in land change science based on a continual process of experimentation and model enhancement. PMID:24489696
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NASA Technical Reports Server (NTRS)
Gregg, Watson W.
1999-01-01
A coupled general ocean circulation, biogeochemical, and radiative model was constructed to evaluate and understand the nature of seasonal variability of chlorophyll and nutrients in the global oceans. The model is driven by climatological meteorological conditions, cloud cover, and sea surface temperature. Biogeochemical processes in the model are determined from the influences of circulation and turbulence dynamics, irradiance availability, and the interactions among three functional phytoplankton groups (diatoms, chorophytes, and picoplankton) and three nutrient groups (nitrate, ammonium, and silicate). Phytoplankton groups are initialized as homogeneous fields horizontally and vertically, and allowed to distribute themselves according to the prevailing conditions. Basin-scale model chlorophyll results are in very good agreement with CZCS pigments in virtually every global region. Seasonal variability observed in the CZCS is also well represented in the model. Synoptic scale (100-1000 km) comparisons of imagery are also in good conformance, although occasional departures are apparent. Agreement of nitrate distributions with in situ data is even better, including seasonal dynamics, except for the equatorial Atlantic. The good agreement of the model with satellite and in situ data sources indicates that the model dynamics realistically simulate phytoplankton and nutrient dynamics on synoptic scales. This is especially true given that initial conditions are homogenous chlorophyll fields. The success of the model in producing a reasonable representation of chlorophyll and nutrient distributions and seasonal variability in the global oceans is attributed to the application of a generalized, processes-driven approach as opposed to regional parameterization, and the existence of multiple phytoplankton groups with different physiological and physical properties. These factors enable the model to simultaneously represent the great diversity of physical, biological, chemical, and radiative environments encountered in the global oceans.
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Teach for All: Storytelling "Shared Solutions" and Scaling Global Reform
ERIC Educational Resources Information Center
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…
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NASA Technical Reports Server (NTRS)
Running, Steven W.
1992-01-01
A primary purpose of this review is to convey lessons learned in the development of a forest ecosystem modeling approach, from it origins in 1973 as a single-tree water balance model to the current regional applications. The second intent is to use this accumulated experience to offer ideas of how terrestrial ecosystem modeling can be taken to the global scale: earth systems modeling. A logic is suggested where mechanistic ecosystem models are not themselves operated globally, but rather are used to 'calibrate' much simplified models, primarily driven by remote sensing, that could be implemented in a semiautomated way globally, and in principle could interface with atmospheric general circulation models (GCM's).
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Multi-Scale Models for the Scale Interaction of Organized Tropical Convection
NASA Astrophysics Data System (ADS)
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.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
West, Tristram O.; Le Page, Yannick LB; Huang, Maoyi
2014-06-05
Projections of land cover change generated from Integrated Assessment Models (IAM) and other economic-based models can be applied for analyses of environmental impacts at subregional and landscape scales. For those IAM and economic models that project land use at the sub-continental or regional scale, these projections must be downscaled and spatially distributed prior to use in climate or ecosystem models. Downscaling efforts to date have been conducted at the national extent with relatively high spatial resolution (30m) and at the global extent with relatively coarse spatial resolution (0.5 degree).
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The NASA/MSFC Global Reference Atmospheric Model: 1999 Version (GRAM-99)
NASA Technical Reports Server (NTRS)
Justus, C. G.; Johnson, D. L.
1999-01-01
The latest version of Global Reference Atmospheric Model (GRAM-99) is presented and discussed. GRAM-99 uses either (binary) Global Upper Air Climatic Atlas (GUACA) or (ASCII) Global Gridded Upper Air Statistics (GGUAS) CD-ROM data sets, for 0-27 km altitudes. As with earlier versions, GRAM-99 provides complete geographical and altitude coverage for each month of the year. GRAM-99 uses a specially-developed data set, based on Middle Atmosphere Program (MAP) data, for 20-120 km altitudes, and NASA's 1999 version Marshall Engineering Thermosphere (MET-99) model for heights above 90 km. Fairing techniques assure smooth transition in overlap height ranges (20-27 km and 90-120 km). GRAM-99 includes water vapor and 11 other atmospheric constituents (O3, N2O, CO, CH4, CO2, N2, O2, O, A, He and H). A variable-scale perturbation model provides both large-scale (wave) and small-scale (stochastic) deviations from mean values for thermodynamic variables and horizontal and vertical wind components. The small-scale perturbation model includes improvements in representing intermittency ("patchiness"). A major new feature is an option to substitute Range Reference Atmosphere (RRA) data for conventional GRAM climatology when a trajectory passes sufficiently near any RRA site. A complete user's guide for running the program, plus sample input and output, is provided. An example is provided for how to incorporate GRAM-99 as subroutines in other programs (e.g., trajectory codes).
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Carbon budgets of biological soil crusts at micro-, meso-, and global scales
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.
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Toward GEOS-6, A Global Cloud System Resolving Atmospheric Model
NASA Technical Reports Server (NTRS)
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
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AgMIP 1.5°C Assessment: Mitigation and Adaptation at Coordinated Global and Regional Scales
NASA Astrophysics Data System (ADS)
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.
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Significant uncertainty in global scale hydrological modeling from precipitation data errors
NASA Astrophysics Data System (ADS)
Sperna Weiland, Frederiek C.; Vrugt, Jasper A.; van Beek, Rens (L.) P. H.; Weerts, Albrecht H.; Bierkens, Marc F. P.
2015-10-01
In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we focus on large-scale hydrologic modeling and analyze the effect of parameter and rainfall data uncertainty on simulated discharge dynamics with the global hydrologic model PCR-GLOBWB. We use three rainfall data products; the CFSR reanalysis, the ERA-Interim reanalysis, and a combined ERA-40 reanalysis and CRU dataset. Parameter uncertainty is derived from Latin Hypercube Sampling (LHS) using monthly discharge data from five of the largest river systems in the world. Our results demonstrate that the default parameterization of PCR-GLOBWB, derived from global datasets, can be improved by calibrating the model against monthly discharge observations. Yet, it is difficult to find a single parameterization of PCR-GLOBWB that works well for all of the five river basins considered herein and shows consistent performance during both the calibration and evaluation period. Still there may be possibilities for regionalization based on catchment similarities. Our simulations illustrate that parameter uncertainty constitutes only a minor part of predictive uncertainty. Thus, the apparent dichotomy between simulations of global-scale hydrologic behavior and actual data cannot be resolved by simply increasing the model complexity of PCR-GLOBWB and resolving sub-grid processes. Instead, it would be more productive to improve the characterization of global rainfall amounts at spatial resolutions of 0.5° and smaller.
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NASA Astrophysics Data System (ADS)
Lin, Shian-Jiann; Harris, Lucas; Chen, Jan-Huey; Zhao, Ming
2014-05-01
A multi-scale High-Resolution Atmosphere Model (HiRAM) is being developed at NOAA/Geophysical Fluid Dynamics Laboratory. The model's dynamical framework is the non-hydrostatic extension of the vertically Lagrangian finite-volume dynamical core (Lin 2004, Monthly Wea. Rev.) constructed on a stretchable (via Schmidt transformation) cubed-sphere grid. Physical parametrizations originally designed for IPCC-type climate predictions are in the process of being modified and made more "scale-aware", in an effort to make the model suitable for multi-scale weather-climate applications, with horizontal resolution ranging from 1 km (near the target high-resolution region) to as low as 400 km (near the antipodal point). One of the main goals of this development is to enable simulation of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously thought impossible. We will present preliminary results, covering a very wide spectrum of temporal-spatial scales, ranging from simulation of tornado genesis (hours), Madden-Julian Oscillations (intra-seasonal), topical cyclones (seasonal), to Quasi Biennial Oscillations (intra-decadal), using the same global multi-scale modeling system.
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NASA Astrophysics Data System (ADS)
Nord, Mark; Cafiero, Carlo; Viviani, Sara
2016-11-01
Statistical methods based on item response theory are applied to experiential food insecurity survey data from 147 countries, areas, and territories to assess data quality and develop methods to estimate national prevalence rates of moderate and severe food insecurity at equal levels of severity across countries. Data were collected from nationally representative samples of 1,000 adults in each country. A Rasch-model-based scale was estimated for each country, and data were assessed for consistency with model assumptions. A global reference scale was calculated based on item parameters from all countries. Each country's scale was adjusted to the global standard, allowing for up to 3 of the 8 scale items to be considered unique in that country if their deviance from the global standard exceeded a set tolerance. With very few exceptions, data from all countries were sufficiently consistent with model assumptions to constitute reasonably reliable measures of food insecurity and were adjustable to the global standard with fair confidence. National prevalence rates of moderate-or-severe food insecurity assessed over a 12-month recall period ranged from 3 percent to 92 percent. The correlations of national prevalence rates with national income, health, and well-being indicators provide external validation of the food security measure.
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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 pro...
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NASA Technical Reports Server (NTRS)
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.
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A test of the hierarchical model of litter decomposition.
Bradford, Mark A; Veen, G F Ciska; Bonis, Anne; Bradford, Ella M; Classen, Aimee T; Cornelissen, J Hans C; Crowther, Thomas W; De Long, Jonathan R; Freschet, Gregoire T; Kardol, Paul; Manrubia-Freixa, Marta; Maynard, Daniel S; Newman, Gregory S; Logtestijn, Richard S P; Viketoft, Maria; Wardle, David A; Wieder, William R; Wood, Stephen A; van der Putten, Wim H
2017-12-01
Our basic understanding of plant litter decomposition informs the assumptions underlying widely applied soil biogeochemical models, including those embedded in Earth system models. Confidence in projected carbon cycle-climate feedbacks therefore depends on accurate knowledge about the controls regulating the rate at which plant biomass is decomposed into products such as CO 2 . Here we test underlying assumptions of the dominant conceptual model of litter decomposition. The model posits that a primary control on the rate of decomposition at regional to global scales is climate (temperature and moisture), with the controlling effects of decomposers negligible at such broad spatial scales. Using a regional-scale litter decomposition experiment at six sites spanning from northern Sweden to southern France-and capturing both within and among site variation in putative controls-we find that contrary to predictions from the hierarchical model, decomposer (microbial) biomass strongly regulates decomposition at regional scales. Furthermore, the size of the microbial biomass dictates the absolute change in decomposition rates with changing climate variables. Our findings suggest the need for revision of the hierarchical model, with decomposers acting as both local- and broad-scale controls on litter decomposition rates, necessitating their explicit consideration in global biogeochemical models.
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Theoretical and global scale model studies of the atmospheric sulfur/aerosol system
NASA Technical Reports Server (NTRS)
Kasibhatla, Prasad
1996-01-01
The primary focus during the third-phase of our on-going multi-year research effort has been on 3 activities. These are: (1) a global-scale model study of the anthropogenic component of the tropospheric sulfur cycle; (2) process-scale model studies of the factors influencing the distribution of aerosols in the remote marine atmosphere; and (3) an investigation of the mechanism of the OH-initiated oxidation of DMS in the remote marine boundary layer. In this paper, we describe in more detail our research activities in each of these areas. A major portion of our activities during the fourth and final phase of this project will involve the preparation and submission of manuscripts describing the results from our model studies of marine boundary-layer aerosols and DMS-oxidation mechanisms.
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NASA Astrophysics Data System (ADS)
Iwahashi, J.; Yamazaki, D.; Matsuoka, M.; Thamarux, P.; Herrick, J.; Yong, A.; Mital, U.
2017-12-01
A seamless model of landform classifications with regional accuracy will be a powerful platform for geophysical studies that forecast geologic hazards. Spatial variability as a function of landform on a global scale was captured in the automated classifications of Iwahashi and Pike (2007) and additional developments are presented here that incorporate more accurate depictions using higher-resolution elevation data than the original 1-km scale Shuttle Radar Topography Mission digital elevation model (DEM). We create polygon-based terrain classifications globally by using the 280-m DEM interpolated from the Multi-Error-Removed Improved-Terrain DEM (MERIT; Yamazaki et al., 2017). The multi-scale pixel-image analysis method, known as Multi-resolution Segmentation (Baatz and Schäpe, 2000), is first used to classify the terrains based on geometric signatures (slope and local convexity) calculated from the 280-m DEM. Next, we apply the machine learning method of "k-means clustering" to prepare the polygon-based classification at the globe-scale using slope, local convexity and surface texture. We then group the divisions with similar properties by hierarchical clustering and other statistical analyses using geological and geomorphological data of the area where landslides and earthquakes are frequent (e.g. Japan and California). We find the 280-m DEM resolution is only partially sufficient for classifying plains. We nevertheless observe that the categories correspond to reported landslide and liquefaction features at the global scale, suggesting that our model is an appropriate platform to forecast ground failure. To predict seismic amplification, we estimate site conditions using the time-averaged shear-wave velocity in the upper 30-m (VS30) measurements compiled by Yong et al. (2016) and the terrain model developed by Yong (2016; Y16). We plan to test our method on finer resolution DEMs and report our findings to obtain a more globally consistent terrain model as there are known errors in DEM derivatives at higher-resolutions. We expect the improvement in DEM resolution (4 times greater detail) and the combination of regional and global coverage will yield a consistent dataset of polygons that have the potential to improve relations to the Y16 estimates significantly.
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Synchronising data sources and filling gaps by global hydrological modelling
NASA Astrophysics Data System (ADS)
Pimentel, Rafael; Crochemore, Louise; Hasan, Abdulghani; Pineda, Luis; Isberg, Kristina; Arheimer, Berit
2017-04-01
The advances in remote sensing in the last decades combined with the creation of different open hydrological databases have generated a very large amount of useful information for global hydrological modelling. Working with this huge number of datasets to set up a global hydrological model can constitute challenges such as multiple data formats and big heterogeneity on spatial and temporal resolutions. Different initiatives have made effort to homogenize some of these data sources, i.e. GRDC (Global Runoff Data Center), HYDROSHEDS (SHuttle Elevation Derivatives at multiple Scales), GLWD (Global Lake and Wetland Database) for runoff, watershed delineation and water bodies respectively. However, not all the related issues are covered or homogenously solved at the global scale and new information is continuously available to complete the current ones. This work presents synchronising efforts to make use of different global data sources needed to set up the semi-distributed hydrological model HYPE (Hydrological Predictions for the Environment) at the global scale. These data sources included: topography for watershed delineation, gauging stations of river flow, and extention of lakes, flood plains and land cover classes. A new database with approximately 100 000 subbasins, with an average area of 1000 km2, was created. Subbasin delineation was done combining Global Width Database for Large River (GWD-LR), SRTM high-resolution elevation data and a number of forced points of interest (gauging station of river flow, lakes, reservoirs, urban areas, nuclear plants and areas with high risk of flooding). Regarding flow data, the locations of GRDC stations were checked or placed along the river network when necessary, and completed with available information from national water services in data-sparse regions. A screening of doublet stations and associated time series was necessary to efficiently combine the two types of data sources. A total number about 21 000 stations were considered as forced point. In the case of lakes, some updating relating with location and area, of GLWD was done using esa (European Space Agency) gridded water bodies dataset. Many of the original lakes were shifted in relation with topography and some of them change their extension since the creation of the database. Moreover, the location of the outlet of all these lakes was also calculated. A new definition of global floodplain areas was also included. The land covers provided by ESA and some elevation criteria were used to define elevation land classes (ELC) using for the definition of the properties of each one of the proposed subbasin. All these new features: a) the inclusion of river width in the delineation of the subbasin, going further in the consideration of river shape; b) the merging of several data bases of gauging stations of river flow into an extended global dataset; c) coherent location of the lakes, river networks and floodplains; and d) a new definition of hydrological response units also considering elevation of the subbasins, will contribute to a better implementation of global hydrological models. The first results of world-wide HYPE will be shown but the model will yet not be fully calibrated using multi-sources of observed data and information. The ambition is to receive a global scale model which can also be useful at local scales. Starting with the global picture and then going into the details.
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NASA Technical Reports Server (NTRS)
Putnam, WilliamM.
2011-01-01
In 2008 the World Modeling Summit for Climate Prediction concluded that "climate modeling will need-and is ready-to move to fundamentally new high-resolution approaches to capitalize on the seamlessness of the weather-climate continuum." Following from this, experimentation with very high-resolution global climate modeling has gained enhanced priority within many modeling groups and agencies. The NASA Goddard Earth Observing System model (GEOS-5) has been enhanced to provide a capability for the execution at the finest horizontal resolutions POS,SIOle with a global climate model today. Using this high-resolution, non-hydrostatic version of GEOS-5, we have developed a unique capability to explore the intersection of weather and climate within a seamless prediction system. Week-long weather experiments, to mUltiyear climate simulations at global resolutions ranging from 3.5- to 14-km have demonstrated the predictability of extreme events including severe storms along frontal systems, extra-tropical storms, and tropical cyclones. The primary benefits of high resolution global models will likely be in the tropics, with better predictions of the genesis stages of tropical cyclones and of the internal structure of their mature stages. Using satellite data we assess the accuracy of GEOS-5 in representing extreme weather phenomena, and their interaction within the global climate on seasonal time-scales. The impacts of convective parameterization and the frequency of coupling between the moist physics and dynamics are explored in terms of precipitation intensity and the representation of deep convection. We will also describe the seasonal variability of global tropical cyclone activity within a global climate model capable of representing the most intense category 5 hurricanes.
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NASA Astrophysics Data System (ADS)
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.
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Regional climates in the GISS global circulation model - Synoptic-scale circulation
NASA Technical Reports Server (NTRS)
Hewitson, B.; Crane, R. G.
1992-01-01
A major weakness of current general circulation models (GCMs) is their perceived inability to predict reliably the regional consequences of a global-scale change, and it is these regional-scale predictions that are necessary for studies of human-environmental response. For large areas of the extratropics, the local climate is controlled by the synoptic-scale atmospheric circulation, and it is the purpose of this paper to evaluate the synoptic-scale circulation of the Goddard Institute for Space Studies (GISS) GCM. A methodology for validating the daily synoptic circulation using Principal Component Analysis is described, and the methodology is then applied to the GCM simulation of sea level pressure over the continental United States (excluding Alaska). The analysis demonstrates that the GISS 4 x 5 deg GCM Model II effectively simulates the synoptic-scale atmospheric circulation over the United States. The modes of variance describing the atmospheric circulation of the model are comparable to those found in the observed data, and these modes explain similar amounts of variance in their respective datasets. The temporal behavior of these circulation modes in the synoptic time frame are also comparable.
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NASA Astrophysics Data System (ADS)
Zhang, Y.; Wen, J.; Xiao, Q.; You, D.
2016-12-01
Operational algorithms for land surface BRDF/Albedo products are mainly developed from kernel-driven model, combining atmospherically corrected, multidate, multiband surface reflectance to extract BRDF parameters. The Angular and Spectral Kernel Driven model (ASK model), which incorporates the component spectra as a priori knowledge, provides a potential way to make full use of the multi-sensor data with multispectral information and accumulated observations. However, the ASK model is still not feasible for global BRDF/Albedo inversions due to the lack of sufficient field measurements of component spectra at the large scale. This research outlines a parameterization scheme on the component spectra for global scale BRDF/Albedo inversions in the frame of ASK. The parameter γ(λ) can be derived from the ratio of the leaf reflectance and soil reflectance, supported by globally distributed soil spectral library, ANGERS and LOPEX leaf optical properties database. To consider the intrinsic variability in both the land cover and spectral dimension, the mean and standard deviation of γ(λ) for 28 soil units and 4 leaf types in seven MODIS bands were calculated, with a world soil map used for global BRDF/Albedo products retrieval. Compared to the retrievals from BRF datasets simulated by the PROSAIL model, ASK model shows an acceptable accuracy on the parameterization strategy, with the RMSE 0.007 higher at most than inversion by true component spectra. The results indicate that the classification on ratio contributed to capture the spectral characteristics in BBRDF/Albedo retrieval, whereas the ratio range should be controlled within 8% in each band. Ground-based measurements in Heihe river basin were used to validate the accuracy of the improved ASK model, and the generated broadband albedo products shows good agreement with in situ data, which suggests that the improvement of the component spectra on the ASK model has potential for global scale BRDF/Albedo inversions.
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Dhingra, Madhur S; Artois, Jean; Robinson, Timothy P; Linard, Catherine; Chaiban, Celia; Xenarios, Ioannis; Engler, Robin; Liechti, Robin; Kuznetsov, Dmitri; Xiao, Xiangming; Dobschuetz, Sophie Von; Claes, Filip; Newman, Scott H; Dauphin, Gwenaëlle; Gilbert, Marius
2016-01-01
Global disease suitability models are essential tools to inform surveillance systems and enable early detection. We present the first global suitability model of highly pathogenic avian influenza (HPAI) H5N1 and demonstrate that reliable predictions can be obtained at global scale. Best predictions are obtained using spatial predictor variables describing host distributions, rather than land use or eco-climatic spatial predictor variables, with a strong association with domestic duck and extensively raised chicken densities. Our results also support a more systematic use of spatial cross-validation in large-scale disease suitability modelling compared to standard random cross-validation that can lead to unreliable measure of extrapolation accuracy. A global suitability model of the H5 clade 2.3.4.4 viruses, a group of viruses that recently spread extensively in Asia and the US, shows in comparison a lower spatial extrapolation capacity than the HPAI H5N1 models, with a stronger association with intensively raised chicken densities and anthropogenic factors. DOI: http://dx.doi.org/10.7554/eLife.19571.001 PMID:27885988
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Deep water tsunami simulation at global scale using an elastoacoustic approach
NASA Astrophysics Data System (ADS)
Salazar Monroy, E. F.; Ramirez-Guzman, L.; Bielak, J.; Sanchez-Sesma, F. J.
2017-12-01
In this work, we present the results for the first stage of a tsunami global simulation project using an elastoacoustic approach. The solid-fluid interaction, which is only valid on a global scale and far distances from the coast, is modelled using a finite element scheme for a 2D geometry. Comparing analytic and numerical solutions, we observe a good fit for a homogeneous domain - with an extension of 20 km - using 15 points per wavelength. Subsequently, we performed 2D realizations taking a section from a global 3D model and projecting the Tohoku-Oki source obtained by the USGS. The 3D Global model uses the ETOPO1 and the Preliminary Reference Earth Model (Dziewonski and Anderson, 1981). We analysed 3 cross sections, defined using DART buoys as a reference for each section (i.e., initial and final profile point). Surface water elevation obtained with this coupling strategy is constrained at low frequencies (0.2 Hz). We expect that this coupling strategy could approximate the model to high frequencies and realistic scenarios considering other geometries (i.e., 3D) and a complete domain (i.e., surface and deep).
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Balcan, Duygu; Gonçalves, Bruno; Hu, Hao; Ramasco, José J.; Colizza, Vittoria
2010-01-01
Here we present the Global Epidemic and Mobility (GLEaM) model that integrates sociodemographic and population mobility data in a spatially structured stochastic disease approach to simulate the spread of epidemics at the worldwide scale. We discuss the flexible structure of the model that is open to the inclusion of different disease structures and local intervention policies. This makes GLEaM suitable for the computational modeling and anticipation of the spatio-temporal patterns of global epidemic spreading, the understanding of historical epidemics, the assessment of the role of human mobility in shaping global epidemics, and the analysis of mitigation and containment scenarios. PMID:21415939
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A program for handling map projections of small-scale geospatial raster data
Finn, Michael P.; Steinwand, Daniel R.; Trent, Jason R.; Buehler, Robert A.; Mattli, David M.; Yamamoto, Kristina H.
2012-01-01
Scientists routinely accomplish small-scale geospatial modeling using raster datasets of global extent. Such use often requires the projection of global raster datasets onto a map or the reprojection from a given map projection associated with a dataset. The distortion characteristics of these projection transformations can have significant effects on modeling results. Distortions associated with the reprojection of global data are generally greater than distortions associated with reprojections of larger-scale, localized areas. The accuracy of areas in projected raster datasets of global extent is dependent on spatial resolution. To address these problems of projection and the associated resampling that accompanies it, methods for framing the transformation space, direct point-to-point transformations rather than gridded transformation spaces, a solution to the wrap-around problem, and an approach to alternative resampling methods are presented. The implementations of these methods are provided in an open-source software package called MapImage (or mapIMG, for short), which is designed to function on a variety of computer architectures.
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NASA Astrophysics Data System (ADS)
von Känel, Lukas; Frölicher, Thomas L.; Gruber, Nicolas
2017-08-01
A surface cooling pattern in the equatorial Pacific associated with a negative phase of the Interdecadal Pacific Oscillation is the leading hypothesis to explain the smaller rate of global warming during 1998-2012, with these cooler than normal conditions thought to have accelerated the oceanic heat uptake. Here using a 30-member ensemble simulation of a global Earth system model, we show that in 10% of all simulated decades with a global cooling trend, the eastern equatorial Pacific actually warms. This implies that there is a 1 in 10 chance that decadal hiatus periods may occur without the equatorial Pacific being the dominant pacemaker. In addition, the global ocean heat uptake tends to slow down during hiatus decades implying a fundamentally different global climate feedback factor on decadal time scales than on centennial time scales and calling for caution inferring climate sensitivity from decadal-scale variability.
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Random Forests for Global and Regional Crop Yield Predictions.
Jeong, Jig Han; Resop, Jonathan P; Mueller, Nathaniel D; Fleisher, David H; Yun, Kyungdahm; Butler, Ethan E; Timlin, Dennis J; Shim, Kyo-Moon; Gerber, James S; Reddy, Vangimalla R; Kim, Soo-Hyung
2016-01-01
Accurate predictions of crop yield are critical for developing effective agricultural and food policies at the regional and global scales. We evaluated a machine-learning method, Random Forests (RF), for its ability to predict crop yield responses to climate and biophysical variables at global and regional scales in wheat, maize, and potato in comparison with multiple linear regressions (MLR) serving as a benchmark. We used crop yield data from various sources and regions for model training and testing: 1) gridded global wheat grain yield, 2) maize grain yield from US counties over thirty years, and 3) potato tuber and maize silage yield from the northeastern seaboard region. RF was found highly capable of predicting crop yields and outperformed MLR benchmarks in all performance statistics that were compared. For example, the root mean square errors (RMSE) ranged between 6 and 14% of the average observed yield with RF models in all test cases whereas these values ranged from 14% to 49% for MLR models. Our results show that RF is an effective and versatile machine-learning method for crop yield predictions at regional and global scales for its high accuracy and precision, ease of use, and utility in data analysis. RF may result in a loss of accuracy when predicting the extreme ends or responses beyond the boundaries of the training data.
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Integrating Unified Gravity Wave Physics into the NOAA Next Generation Global Prediction System
NASA Astrophysics Data System (ADS)
Alpert, J. C.; Yudin, V.; Fuller-Rowell, T. J.; Akmaev, R. A.
2017-12-01
The Unified Gravity Wave Physics (UGWP) project for the Next Generation Global Prediction System (NGGPS) is a NOAA collaborative effort between the National Centers for Environmental Prediction (NCEP), Environemntal Modeling Center (EMC) and the University of Colorado, Cooperative Institute for Research in Environmental Sciences (CU-CIRES) to support upgrades and improvements of GW dynamics (resolved scales) and physics (sub-grid scales) in the NOAA Environmental Modeling System (NEMS)†. As envisioned the global climate, weather and space weather models of NEMS will substantially improve their predictions and forecasts with the resolution-sensitive (scale-aware) formulations planned under the UGWP framework for both orographic and non-stationary waves. In particular, the planned improvements for the Global Forecast System (GFS) model of NEMS are: calibration of model physics for higher vertical and horizontal resolution and an extended vertical range of simulations, upgrades to GW schemes, including the turbulent heating and eddy mixing due to wave dissipation and breaking, and representation of the internally-generated QBO. The main priority of the UGWP project is unified parameterization of orographic and non-orographic GW effects including momentum deposition in the middle atmosphere and turbulent heating and eddies due to wave dissipation and breaking. The latter effects are not currently represented in NOAA atmosphere models. The team has tested and evaluated four candidate GW solvers integrating the selected GW schemes into the NGGPS model. Our current work and planned activity is to implement the UGWP schemes in the first available GFS/FV3 (open FV3) configuration including adapted GFDL modification for sub-grid orography in GFS. Initial global model results will be shown for the operational and research GFS configuration for spectral and FV3 dynamical cores. †http://www.emc.ncep.noaa.gov/index.php?branch=NEMS
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Log-Normal Turbulence Dissipation in Global Ocean Models
NASA Astrophysics Data System (ADS)
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.
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Inverse modeling has been used extensively on the global scale to produce top-down estimates of emissions for chemicals such as CO and CH4. Regional scale air quality studies could also benefit from inverse modeling as a tool to evaluate current emission inventories; however, ...
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NASA Astrophysics Data System (ADS)
Smith, B.; Wårlind, D.; Arneth, A.; Hickler, T.; Leadley, P.; Siltberg, J.; Zaehle, S.
2013-11-01
The LPJ-GUESS dynamic vegetation model uniquely combines an individual- and patch-based representation of vegetation dynamics with ecosystem biogeochemical cycling from regional to global scales. We present an updated version that includes plant and soil N dynamics, analysing the implications of accounting for C-N interactions on predictions and performance of the model. Stand structural dynamics and allometric scaling of tree growth suggested by global databases of forest stand structure and development were well-reproduced by the model in comparison to an earlier multi-model study. Accounting for N cycle dynamics improved the goodness-of-fit for broadleaved forests. N limitation associated with low N mineralisation rates reduces productivity of cold-climate and dry-climate ecosystems relative to mesic temperate and tropical ecosystems. In a model experiment emulating free-air CO2 enrichment (FACE) treatment for forests globally, N-limitation associated with low N mineralisation rates of colder soils reduces CO2-enhancement of NPP for boreal forests, while some temperate and tropical forests exhibit increased NPP enhancement. Under a business-as-usual future climate and emissions scenario, ecosystem C storage globally was projected to increase by c. 10%; additional N requirements to match this increasing ecosystem C were within the high N supply limit estimated on stoichiometric grounds in an earlier study. Our results highlight the importance of accounting for C-N interactions not only in studies of global terrestrial C cycling, but to understand underlying mechanisms on local scales and in different regional contexts.
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NASA Astrophysics Data System (ADS)
Smith, B.; Wårlind, D.; Arneth, A.; Hickler, T.; Leadley, P.; Siltberg, J.; Zaehle, S.
2014-04-01
The LPJ-GUESS dynamic vegetation model uniquely combines an individual- and patch-based representation of vegetation dynamics with ecosystem biogeochemical cycling from regional to global scales. We present an updated version that includes plant and soil N dynamics, analysing the implications of accounting for C-N interactions on predictions and performance of the model. Stand structural dynamics and allometric scaling of tree growth suggested by global databases of forest stand structure and development were well reproduced by the model in comparison to an earlier multi-model study. Accounting for N cycle dynamics improved the goodness of fit for broadleaved forests. N limitation associated with low N-mineralisation rates reduces productivity of cold-climate and dry-climate ecosystems relative to mesic temperate and tropical ecosystems. In a model experiment emulating free-air CO2 enrichment (FACE) treatment for forests globally, N limitation associated with low N-mineralisation rates of colder soils reduces CO2 enhancement of net primary production (NPP) for boreal forests, while some temperate and tropical forests exhibit increased NPP enhancement. Under a business-as-usual future climate and emissions scenario, ecosystem C storage globally was projected to increase by ca. 10%; additional N requirements to match this increasing ecosystem C were within the high N supply limit estimated on stoichiometric grounds in an earlier study. Our results highlight the importance of accounting for C-N interactions in studies of global terrestrial N cycling, and as a basis for understanding mechanisms on local scales and in different regional contexts.
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Clouds in ECMWF's 30 KM Resolution Global Atmospheric Forecast Model (TL639)
NASA Technical Reports Server (NTRS)
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 understanding of the upscale cascade and suggesting new cloud-radiation parameterizations for climate models.
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NASA Astrophysics Data System (ADS)
Boutin, J.; Etcheto, J.
1990-12-01
The wind speeds obtained from the Seasat A scatterometer system (SASS) and scanning multichannel microwave radiometer (SMMR) using two different algorithms were compared on a global scale. The temperature dependence of the sea surface emissivity was shown to be incorrectly modelled. After correcting this effect, regional differences up to ± 3 m s-1 are still observed between both instruments, even though they balance in global averaging, resulting in no bias between the global data sets. Validation experiments of satellite wind speeds should take into account this possibility of regional biases and insure the validity of the measurements everywhere in the global ocean.
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Fractional solubility of aerosol iron: Synthesis of a global-scale data set
NASA Astrophysics Data System (ADS)
Sholkovitz, Edward R.; Sedwick, Peter N.; Church, Thomas M.; Baker, Alexander R.; Powell, Claire F.
2012-07-01
Aerosol deposition provides a major input of the essential micronutrient iron to the open ocean. A critical parameter with respect to biological availability is the proportion of aerosol iron that enters the oceanic dissolved iron pool - the so-called fractional solubility of aerosol iron (%FeS). Here we present a global-scale compilation of total aerosol iron loading (FeT) and estimated %FeS values for ∼1100 samples collected over the open ocean, the coastal ocean, and some continental sites, including a new data set from the Atlantic Ocean. Despite the wide variety of methods that have been used to define 'soluble' aerosol iron, our global-scale compilation reveals a remarkably consistent trend in the fractional solubility of aerosol iron as a function of total aerosol iron loading, with the great bulk of the data defining an hyperbolic trend. The hyperbolic trends that we observe for both global- and regional-scale data are adequately described by a simple two-component mixing model, whereby the fractional solubility of iron in the bulk aerosol reflects the conservative mixing of 'lithogenic' mineral dust (high FeT and low %FeS) and non-lithogenic 'combustion' aerosols (low FeT and high %FeS). An increasing body of empirical and model-based evidence points to anthropogenic fuel combustion as the major source of these non-lithogenic 'combustion' aerosols, implying that human emissions are a major determinant of the fractional solubility of iron in marine aerosols. The robust global-scale relationship between %FeS and FeT provides a simple heuristic method for estimating aerosol iron solubility at the regional to global scale.
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NASA Astrophysics Data System (ADS)
Weatherill, G. A.; Pagani, M.; Garcia, J.
2016-09-01
The creation of a magnitude-homogenized catalogue is often one of the most fundamental steps in seismic hazard analysis. The process of homogenizing multiple catalogues of earthquakes into a single unified catalogue typically requires careful appraisal of available bulletins, identification of common events within multiple bulletins and the development and application of empirical models to convert from each catalogue's native scale into the required target. The database of the International Seismological Center (ISC) provides the most exhaustive compilation of records from local bulletins, in addition to its reviewed global bulletin. New open-source tools are developed that can utilize this, or any other compiled database, to explore the relations between earthquake solutions provided by different recording networks, and to build and apply empirical models in order to harmonize magnitude scales for the purpose of creating magnitude-homogeneous earthquake catalogues. These tools are described and their application illustrated in two different contexts. The first is a simple application in the Sub-Saharan Africa region where the spatial coverage and magnitude scales for different local recording networks are compared, and their relation to global magnitude scales explored. In the second application the tools are used on a global scale for the purpose of creating an extended magnitude-homogeneous global earthquake catalogue. Several existing high-quality earthquake databases, such as the ISC-GEM and the ISC Reviewed Bulletins, are harmonized into moment magnitude to form a catalogue of more than 562 840 events. This extended catalogue, while not an appropriate substitute for a locally calibrated analysis, can help in studying global patterns in seismicity and hazard, and is therefore released with the accompanying software.
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Subramanian, Savitha; Naimoli, Joseph; Matsubayashi, Toru; Peters, David H
2011-12-14
There is widespread agreement on the need for scaling up in the health sector to achieve the Millennium Development Goals (MDGs). But many countries are not on track to reach the MDG targets. The dominant approach used by global health initiatives promotes uniform interventions and targets, assuming that specific technical interventions tested in one country can be replicated across countries to rapidly expand coverage. Yet countries scale up health services and progress against the MDGs at very different rates. Global health initiatives need to take advantage of what has been learned about scaling up. A systematic literature review was conducted to identify conceptual models for scaling up health in developing countries, with the articles assessed according to the practical concerns of how to scale up, including the planning, monitoring and implementation approaches. We identified six conceptual models for scaling up in health based on experience with expanding pilot projects and diffusion of innovations. They place importance on paying attention to enhancing organizational, functional, and political capabilities through experimentation and adaptation of strategies in addition to increasing the coverage and range of health services. These scaling up approaches focus on fostering sustainable institutions and the constructive engagement between end users and the provider and financing organizations. The current approaches to scaling up health services to reach the MDGs are overly simplistic and not working adequately. Rather than relying on blueprint planning and raising funds, an approach characteristic of current global health efforts, experience with alternative models suggests that more promising pathways involve "learning by doing" in ways that engage key stakeholders, uses data to address constraints, and incorporates results from pilot projects. Such approaches should be applied to current strategies to achieve the MDGs.
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Development of mpi_EPIC model for global agroecosystem modeling
Kang, Shujiang; Wang, Dali; Jeff A. Nichols; ...
2014-12-31
Models that address policy-maker concerns about multi-scale effects of food and bioenergy production systems are computationally demanding. We integrated the message passing interface algorithm into the process-based EPIC model to accelerate computation of ecosystem effects. Simulation performance was further enhanced by applying the Vampir framework. When this enhanced mpi_EPIC model was tested, total execution time for a global 30-year simulation of a switchgrass cropping system was shortened to less than 0.5 hours on a supercomputer. The results illustrate that mpi_EPIC using parallel design can balance simulation workloads and facilitate large-scale, high-resolution analysis of agricultural production systems, management alternatives and environmentalmore » effects.« less
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Current and future levels of mercury atmospheric pollution on a global scale
NASA Astrophysics Data System (ADS)
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 research instrument for supporting the scientific justification for the Minamata Convention and monitoring of the implementation of targets of this convention, as well as the EU Mercury Strategy. This project provided the state of the art with regard to the development of the latest emission inventories for mercury, future emission scenarios, dispersion modelling of atmospheric mercury on a global and regional scale, and source-receptor techniques for mercury emission apportionment on a global scale.
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Drought Persistence Errors in Global Climate Models
NASA Astrophysics Data System (ADS)
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.
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How to normalize metatranscriptomic count data for differential expression analysis.
Klingenberg, Heiner; Meinicke, Peter
2017-01-01
Differential expression analysis on the basis of RNA-Seq count data has become a standard tool in transcriptomics. Several studies have shown that prior normalization of the data is crucial for a reliable detection of transcriptional differences. Until now it has not been clear whether and how the transcriptomic approach can be used for differential expression analysis in metatranscriptomics. We propose a model for differential expression in metatranscriptomics that explicitly accounts for variations in the taxonomic composition of transcripts across different samples. As a main consequence the correct normalization of metatranscriptomic count data under this model requires the taxonomic separation of the data into organism-specific bins. Then the taxon-specific scaling of organism profiles yields a valid normalization and allows us to recombine the scaled profiles into a metatranscriptomic count matrix. This matrix can then be analyzed with statistical tools for transcriptomic count data. For taxon-specific scaling and recombination of scaled counts we provide a simple R script. When applying transcriptomic tools for differential expression analysis directly to metatranscriptomic data with an organism-independent (global) scaling of counts the resulting differences may be difficult to interpret. The differences may correspond to changing functional profiles of the contributing organisms but may also result from a variation of taxonomic abundances. Taxon-specific scaling eliminates this variation and therefore the resulting differences actually reflect a different behavior of organisms under changing conditions. In simulation studies we show that the divergence between results from global and taxon-specific scaling can be drastic. In particular, the variation of organism abundances can imply a considerable increase of significant differences with global scaling. Also, on real metatranscriptomic data, the predictions from taxon-specific and global scaling can differ widely. Our studies indicate that in real data applications performed with global scaling it might be impossible to distinguish between differential expression in terms of transcriptomic changes and differential composition in terms of changing taxonomic proportions. As in transcriptomics, a proper normalization of count data is also essential for differential expression analysis in metatranscriptomics. Our model implies a taxon-specific scaling of counts for normalization of the data. The application of taxon-specific scaling consequently removes taxonomic composition variations from functional profiles and therefore provides a clear interpretation of the observed functional differences.
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Challenges and Opportunities in Modeling of the Global Atmosphere
NASA Astrophysics Data System (ADS)
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 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. Relaxing the hydrostatic approximation requieres careful reformulation of the model dynamics and more computations and communications. The unified Non-hydrostatic Multi-scale Model (NMMB) will be briefly 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 without modifying their amplitudes. The model has been successfully tested on various scales. The skill of the medium range forecasts produced by the NMMB is comparable to that of other major medium range models, and its computational efficiency on parallel computers is good.
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NASA Astrophysics Data System (ADS)
Tallapragada, V.
2017-12-01
NOAA's Next Generation Global Prediction System (NGGPS) has provided the unique opportunity to develop and implement a non-hydrostatic global model based on Geophysical Fluid Dynamics Laboratory (GFDL) Finite Volume Cubed Sphere (FV3) Dynamic Core at National Centers for Environmental Prediction (NCEP), making a leap-step advancement in seamless prediction capabilities across all spatial and temporal scales. Model development efforts are centralized with unified model development in the NOAA Environmental Modeling System (NEMS) infrastructure based on Earth System Modeling Framework (ESMF). A more sophisticated coupling among various earth system components is being enabled within NEMS following National Unified Operational Prediction Capability (NUOPC) standards. The eventual goal of unifying global and regional models will enable operational global models operating at convective resolving scales. Apart from the advanced non-hydrostatic dynamic core and coupling to various earth system components, advanced physics and data assimilation techniques are essential for improved forecast skill. NGGPS is spearheading ambitious physics and data assimilation strategies, concentrating on creation of a Common Community Physics Package (CCPP) and Joint Effort for Data Assimilation Integration (JEDI). Both initiatives are expected to be community developed, with emphasis on research transitioning to operations (R2O). The unified modeling system is being built to support the needs of both operations and research. Different layers of community partners are also established with specific roles/responsibilities for researchers, core development partners, trusted super-users, and operations. Stakeholders are engaged at all stages to help drive the direction of development, resources allocations and prioritization. This talk presents the current and future plans of unified model development at NCEP for weather, sub-seasonal, and seasonal climate prediction applications with special emphasis on implementation of NCEP FV3 Global Forecast System (GFS) and Global Ensemble Forecast System (GEFS) into operations by 2019.
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A CPT for Improving Turbulence and Cloud Processes in the NCEP Global Models
NASA Astrophysics Data System (ADS)
Krueger, S. K.; Moorthi, S.; Randall, D. A.; Pincus, R.; Bogenschutz, P.; Belochitski, A.; Chikira, M.; Dazlich, D. A.; Swales, D. J.; Thakur, P. K.; Yang, F.; Cheng, A.
2016-12-01
Our Climate Process Team (CPT) is based on the premise that the NCEP (National Centers for Environmental Prediction) global models can be improved by installing an integrated, self-consistent description of turbulence, clouds, deep convection, and the interactions between clouds and radiative and microphysical processes. The goal of our CPT is to unify the representation of turbulence and subgrid-scale (SGS) cloud processes and to unify the representation of SGS deep convective precipitation and grid-scale precipitation as the horizontal resolution decreases. We aim to improve the representation of small-scale phenomena by implementing a PDF-based SGS turbulence and cloudiness scheme that replaces the boundary layer turbulence scheme, the shallow convection scheme, and the cloud fraction schemes in the GFS (Global Forecast System) and CFS (Climate Forecast System) global models. We intend to improve the treatment of deep convection by introducing a unified parameterization that scales continuously between the simulation of individual clouds when and where the grid spacing is sufficiently fine and the behavior of a conventional parameterization of deep convection when and where the grid spacing is coarse. We will endeavor to improve the representation of the interactions of clouds, radiation, and microphysics in the GFS/CFS by using the additional information provided by the PDF-based SGS cloud scheme. The team is evaluating the impacts of the model upgrades with metrics used by the NCEP short-range and seasonal forecast operations.
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NASA Astrophysics Data System (ADS)
Lin, S. J.
2015-12-01
The NOAA/Geophysical Fluid Dynamics Laboratory has been developing a unified regional-global modeling system with variable resolution capabilities that can be used for severe weather predictions (e.g., tornado outbreak events and cat-5 hurricanes) and ultra-high-resolution (1-km) regional climate simulations within a consistent global modeling framework. The fundation of this flexible regional-global modeling system is the non-hydrostatic extension of the vertically Lagrangian dynamical core (Lin 2004, Monthly Weather Review) known in the community as FV3 (finite-volume on the cubed-sphere). Because of its flexability and computational efficiency, the FV3 is one of the final candidates of NOAA's Next Generation Global Prediction System (NGGPS). We have built into the modeling system a stretched (single) grid capability, a two-way (regional-global) multiple nested grid capability, and the combination of the stretched and two-way nests, so as to make convection-resolving regional climate simulation within a consistent global modeling system feasible using today's High Performance Computing System. One of our main scientific goals is to enable simulations of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously regarded as impossible. In this presentation I will demonstrate that it is computationally feasible to simulate not only super-cell thunderstorms, but also the subsequent genesis of tornadoes using a global model that was originally designed for century long climate simulations. As a unified weather-climate modeling system, we evaluated the performance of the model with horizontal resolution ranging from 1 km to as low as 200 km. In particular, for downscaling studies, we have developed various tests to ensure that the large-scale circulation within the global varaible resolution system is well simulated while at the same time the small-scale can be accurately captured within the targeted high resolution region.
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Long-range persistence in the global mean surface temperature and the global warming "time bomb"
NASA Astrophysics Data System (ADS)
Rypdal, M.; Rypdal, K.
2012-04-01
Detrended Fluctuation Analysis (DFA) and Maximum Likelihood Estimations (MLE) based on instrumental data over the last 160 years indicate that there is Long-Range Persistence (LRP) in Global Mean Surface Temperature (GMST) on time scales of months to decades. The persistence is much higher in sea surface temperature than in land temperatures. Power spectral analysis of multi-model, multi-ensemble runs of global climate models indicate further that this persistence may extend to centennial and maybe even millennial time-scales. We also support these conclusions by wavelet variogram analysis, DFA, and MLE of Northern hemisphere mean surface temperature reconstructions over the last two millennia. These analyses indicate that the GMST is a strongly persistent noise with Hurst exponent H>0.9 on time scales from decades up to at least 500 years. We show that such LRP can be very important for long-term climate prediction and for the establishment of a "time bomb" in the climate system due to a growing energy imbalance caused by the slow relaxation to radiative equilibrium under rising anthropogenic forcing. We do this by the construction of a multi-parameter dynamic-stochastic model for the GMST response to deterministic and stochastic forcing, where LRP is represented by a power-law response function. Reconstructed data for total forcing and GMST over the last millennium are used with this model to estimate trend coefficients and Hurst exponent for the GMST on multi-century time scale by means of MLE. Ensembles of solutions generated from the stochastic model also allow us to estimate confidence intervals for these estimates.
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Study of Regional Downscaled Climate and Air Quality in the United States
NASA Astrophysics Data System (ADS)
Gao, Y.; Fu, J. S.; Drake, J.; Lamarque, J.; Lam, Y.; Huang, K.
2011-12-01
Due to the increasing anthropogenic greenhouse gas emissions, the global and regional climate patterns have significantly changed. Climate change has exerted strong impact on ecosystem, air quality and human life. The global model Community Earth System Model (CESM v1.0) was used to predict future climate and chemistry under projected emission scenarios. Two new emission scenarios, Representative Community Pathways (RCP) 4.5 and RCP 8.5, were used in this study for climate and chemistry simulations. The projected global mean temperature will increase 1.2 and 1.7 degree Celcius for the RCP 4.5 and RCP 8.5 scenarios in 2050s, respectively. In order to take advantage of local detailed topography, land use data and conduct local climate impact on air quality, we downscaled CESM outputs to 4 km by 4 km Eastern US domain using Weather Research and Forecasting (WRF) Model and Community Multi-scale Air Quality modeling system (CMAQ). The evaluations between regional model outputs and global model outputs, regional model outputs and observational data were conducted to verify the downscaled methodology. Future climate change and air quality impact were also examined on a 4 km by 4 km high resolution scale.
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NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2006-01-01
Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CFWs. 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 (1 998 and 1999). 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).
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The regional and global significance of nitrogen removal in lakes and reservoirs
Harrison, J.A.; Maranger, R.J.; Alexander, Richard B.; Giblin, A.E.; Jacinthe, P.-A.; Mayorga, Emilio; Seitzinger, S.P.; Sobota, D.J.; Wollheim, W.M.
2009-01-01
Human activities have greatly increased the transport of biologically available nitrogen (N) through watersheds to potentially sensitive coastal ecosystems. Lentic water bodies (lakes and reservoirs) have the potential to act as important sinks for this reactive N as it is transported across the landscape because they offer ideal conditions for N burial in sediments or permanent loss via denitrification. However, the patterns and controls on lentic N removal have not been explored in great detail at large regional to global scales. In this paper we describe, evaluate, and apply a new, spatially explicit, annual-scale, global model of lentic N removal called NiRReLa (Nitrogen Retention in Reservoirs and Lakes). The NiRReLa model incorporates small lakes and reservoirs than have been included in previous global analyses, and also allows for separate treatment and analysis of reservoirs and natural lakes. Model runs for the mid-1990s indicate that lentic systems are indeed important sinks for N and are conservatively estimated to remove 19.7 Tg N year-1 from watersheds globally. Small lakes (<50 km2) were critical in the analysis, retaining almost half (9.3 Tg N year -1) of the global total. In model runs, capacity of lakes and reservoirs to remove watershed N varied substantially at the half-degree scale (0-100%) both as a function of climate and the density of lentic systems. Although reservoirs occupy just 6% of the global lentic surface area, we estimate they retain ~33% of the total N removed by lentic systems, due to a combination of higher drainage ratios (catchment surface area:lake or reservoir surface area), higher apparent settling velocities for N, and greater average N loading rates in reservoirs than in lakes. Finally, a sensitivity analysis of NiRReLa suggests that, on-average, N removal within lentic systems will respond more strongly to changes in land use and N loading than to changes in climate at the global scale. ?? 2008 Springer Science+Business Media B.V.
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Oceanic Fluxes of Mass, Heat and Freshwater: A Global Estimate and Perspective
NASA Technical Reports Server (NTRS)
MacDonald, Alison Marguerite
1995-01-01
Data from fifteen globally distributed, modern, high resolution, hydrographic oceanic transects are combined in an inverse calculation using large scale box models. The models provide estimates of the global meridional heat and freshwater budgets and are used to examine the sensitivity of the global circulation, both inter and intra-basin exchange rates, to a variety of external constraints provided by estimates of Ekman, boundary current and throughflow transports. A solution is found which is consistent with both the model physics and the global data set, despite a twenty five year time span and a lack of seasonal consistency among the data. The overall pattern of the global circulation suggested by the models is similar to that proposed in previously published local studies and regional reviews. However, significant qualitative and quantitative differences exist. These differences are due both to the model definition and to the global nature of the data set.
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“Modeling Trends in Air Pollutant Concentrations over the ...
Regional model calculations over annual cycles have pointed to the need for accurately representing impacts of long-range transport. Linking regional and global scale models have met with mixed success as biases in the global model can propagate and influence regional calculations and often confound interpretation of model results. Since transport is efficient in the free-troposphere and since simulations over Continental scales and annual cycles provide sufficient opportunity for “atmospheric turn-over”, i.e., exchange between the free-troposphere and the boundary-layer, a conceptual framework is needed wherein interactions between processes occurring at various spatial and temporal scales can be consistently examined. The coupled WRF-CMAQ model is expanded to hemispheric scales and model simulations over period spanning 1990-current are analyzed to examine changes in hemispheric air pollution resulting from changes in emissions over this period. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for pr
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Coupled fvGCM-GCE Modeling System, TRMM Latent Heating and Cloud Library
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2004-01-01
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 imiprove 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. A seed fund is available at NASA Goddard to build a MMF based on the 2D GCE model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF will be developed by the end of 2004 and production runs will be conducted at the beginning of 2005. The purpose of this proposal is to augment the current Goddard MMF and other cloud modeling activities. I this talk, I will present: (1) A summary of the second Cloud Modeling Workshop took place at NASA Goddard, (2) A summary of the third TRMM Latent Heating Workshop took place at Nara Japan, (3) A brief discussion on the Goddard research plan of using Weather Research Forecast (WRF) model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.
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Coupled fvGCM-GCE Modeling System, 3D Cloud-Resolving Model and Cloud Library
NASA Technical Reports Server (NTRS)
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 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. A seed fund is available at NASA Goddard to build a MMF based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF in being developed and production runs will be conducted at the beginning of 2005. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes, ( 2 ) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), (3) A cloud library generated by Goddard MMF, and 3D GCE model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.
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NASA Astrophysics Data System (ADS)
Lantuit, Hugues; Boike, Julia; Dahms, Melanie; Hubberten, Hans-Wolfgang
2013-04-01
The northern permafrost region contains approximately 50% of the estimated global below-ground organic carbon pool and more than twice as much as is contained in the current atmos-pheric carbon pool. The sheer size of this carbon pool, together with the large amplitude of predicted arctic climate change im-plies that there is a high potential for global-scale feedbacks from arctic climate change if these carbon reservoirs are desta-bilized. Nonetheless, significant gaps exist in our current state of knowledge that prevent us from producing accurate assess-ments of the vulnerability of the arctic permafrost to climate change, or of the implications of future climate change for global greenhouse gas (GHG) emissions. Specifically: • Our understanding of the physical and biogeochemical processes at play in permafrost areas is still insuffi-cient in some key aspects • Size estimates for the high latitude continental carbon and nitrogen stocks vary widely between regions and research groups. • The representation of permafrost-related processes in global climate models still tends to be rudimentary, and is one reason for the frequently poor perform-ances of climate models at high latitudes. The key objectives of PAGE21 are: • to improve our understanding of the processes affect-ing the size of the arctic permafrost carbon and nitro-gen pools through detailed field studies and monitor-ing, in order to quantify their size and their vulnerability to climate change, • to produce, assemble and assess high-quality datasets in order to develop and evaluate representations of permafrost and related processes in global models, • to improve these models accordingly, • to use these models to reduce the uncertainties in feed-backs from arctic permafrost to global change, thereby providing the means to assess the feasibility of stabili-zation scenarios, and • to ensure widespread dissemination of our results in order to provide direct input into the ongoing debate on climate-change mitigation. The concept of PAGE21 is to directly address these questions through a close interaction between monitoring activities, proc-ess studies and modeling on the pertinent temporal and spatial scales. Field sites have been selected to cover a wide range of environmental conditions for the validation of large scale mod-els, the development of permafrost monitoring capabilities, the study of permafrost processes, and for overlap with existing monitoring programs. PAGE21 will contribute to upgrading the project sites with the objective of providing a measurement baseline, both for process studies and for modeling programs. PAGE21 is determined to break down the traditional barriers in permafrost sciences between observational and model-supported site studies and large-scale climate modeling. Our concept for the interaction between site-scale studies and large-scale modeling is to establish and maintain a direct link be-tween these two areas for developing and evaluating, on all spatial scales, the land-surface modules of leading European global climate models taking part in the Coupled Model Inter-comparison Project Phase 5 (CMIP5), designed to inform the IPCC process. The timing of this project is such that the main scientific results from PAGE21, and in particular the model-based assessments will build entirely on new outputs and results from the CMIP5 Climate Model Intercomparison Project designed to inform the IPCC Fifth Assessment Report. However, PAGE21 is designed to leave a legacy that will en-dure beyond the lifetime of the projections that it produces. This legacy will comprise • an improved understanding of the key processes and parameters that determine the vulnerability of arctic permafrost to climate change, • the production of a suite of major European coupled climate models including detailed and validated repre-sentations of permafrost-related processes, that will reduce uncertainties in future climate projections pro-duced well beyond the lifetime of PAGE21, and • the training of a new generation of permafrost scien-tists who will bridge the long-standing gap between permafrost field science and global climate modeling, for the long-term benefit of science and society.
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Challenges in global modeling of wetland extent and wetland methane dynamics
NASA Astrophysics Data System (ADS)
Spahni, R.; Melton, J. R.; Wania, R.; Stocker, B. D.; Zürcher, S.; Joos, F.
2012-12-01
Global wetlands are known to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. Modelling of global wetland extent and wetland CH4 dynamics remains a challenge. Here we present results from the Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) that investigated our present ability to simulate large scale wetland characteristics (e.g. wetland type, water table, carbon cycling, gas transport, etc.) and corresponding CH4 emissions. Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The WETCHIMP experiments showed that while models disagree in spatial and temporal patterns of simulated CH4 emissions and wetland areal extent, they all do agree on a strong positive response to increased carbon dioxide concentrations. WETCHIMP made clear that we currently lack observation data sets that are adequate to evaluate model CH4 soil-atmosphere fluxes at a spatial scale comparable to model grid cells. Thus there are substantial parameter and structural uncertainties in large-scale CH4 emission models. As an illustration of the implications of CH4 emissions on climate we show results of the LPX-Bern model, as one of the models participating in WETCHIMP. LPX-Bern is forced with observed 20th century climate and climate output from an ensemble of five comprehensive climate models for a low and a high emission scenario till 2100 AD. In the high emission scenario increased substrate availability for methanogenesis due to a strong stimulation of net primary productivity, and faster soil turnover leads to an amplification of CH4 emissions with the sharpest increase in peatlands (+180% compared to present). Combined with prescribed anthropogenic CH4 emissions, simulated atmospheric CH4 concentration reaches ~4500 ppbv by 2100 AD, about 800 ppbv more than in standard IPCC scenarios. This represents a significant contribution to radiative forcing of global climate.
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Combined climate and carbon-cycle effects of large-scale deforestation
Bala, G.; Caldeira, K.; Wickett, M.; Phillips, T. J.; Lobell, D. B.; Delire, C.; Mirin, A.
2007-01-01
The prevention of deforestation and promotion of afforestation have often been cited as strategies to slow global warming. Deforestation releases CO2 to the atmosphere, which exerts a warming influence on Earth's climate. However, biophysical effects of deforestation, which include changes in land surface albedo, evapotranspiration, and cloud cover also affect climate. Here we present results from several large-scale deforestation experiments performed with a three-dimensional coupled global carbon-cycle and climate model. These simulations were performed by using a fully three-dimensional model representing physical and biogeochemical interactions among land, atmosphere, and ocean. We find that global-scale deforestation has a net cooling influence on Earth's climate, because the warming carbon-cycle effects of deforestation are overwhelmed by the net cooling associated with changes in albedo and evapotranspiration. Latitude-specific deforestation experiments indicate that afforestation projects in the tropics would be clearly beneficial in mitigating global-scale warming, but would be counterproductive if implemented at high latitudes and would offer only marginal benefits in temperate regions. Although these results question the efficacy of mid- and high-latitude afforestation projects for climate mitigation, forests remain environmentally valuable resources for many reasons unrelated to climate. PMID:17420463
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Combined climate and carbon-cycle effects of large-scale deforestation.
Bala, G; Caldeira, K; Wickett, M; Phillips, T J; Lobell, D B; Delire, C; Mirin, A
2007-04-17
The prevention of deforestation and promotion of afforestation have often been cited as strategies to slow global warming. Deforestation releases CO(2) to the atmosphere, which exerts a warming influence on Earth's climate. However, biophysical effects of deforestation, which include changes in land surface albedo, evapotranspiration, and cloud cover also affect climate. Here we present results from several large-scale deforestation experiments performed with a three-dimensional coupled global carbon-cycle and climate model. These simulations were performed by using a fully three-dimensional model representing physical and biogeochemical interactions among land, atmosphere, and ocean. We find that global-scale deforestation has a net cooling influence on Earth's climate, because the warming carbon-cycle effects of deforestation are overwhelmed by the net cooling associated with changes in albedo and evapotranspiration. Latitude-specific deforestation experiments indicate that afforestation projects in the tropics would be clearly beneficial in mitigating global-scale warming, but would be counterproductive if implemented at high latitudes and would offer only marginal benefits in temperate regions. Although these results question the efficacy of mid- and high-latitude afforestation projects for climate mitigation, forests remain environmentally valuable resources for many reasons unrelated to climate.
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Mapping permeability over the surface of the Earth
Gleeson, T.; Smith, L.; Moosdorf, N.; Hartmann, J.; Durr, H.H.; Manning, A.H.; Van Beek, L. P. H.; Jellinek, A. Mark
2011-01-01
Permeability, the ease of fluid flow through porous rocks and soils, is a fundamental but often poorly quantified component in the analysis of regional-scale water fluxes. Permeability is difficult to quantify because it varies over more than 13 orders of magnitude and is heterogeneous and dependent on flow direction. Indeed, at the regional scale, maps of permeability only exist for soil to depths of 1-2 m. Here we use an extensive compilation of results from hydrogeologic models to show that regional-scale (>5 km) permeability of consolidated and unconsolidated geologic units below soil horizons (hydrolithologies) can be characterized in a statistically meaningful way. The representative permeabilities of these hydrolithologies are used to map the distribution of near-surface (on the order of 100 m depth) permeability globally and over North America. The distribution of each hydrolithology is generally scale independent. The near-surface mean permeability is of the order of ???5 ?? 10-14 m2. The results provide the first global picture of near-surface permeability and will be of particular value for evaluating global water resources and modeling the influence of climate-surface-subsurface interactions on global climate change. Copyright ?? 2011 by the American Geophysical Union.
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Mapping permeability over the surface of the Earth
Gleeson, Tom; Smith, Leslie; Moosdorf, Nils; Hartmann, Jens; Durr, Hans H.; Manning, Andrew H.; van Beek, Ludovicus P. H.; Jellinek, A. Mark
2011-01-01
Permeability, the ease of fluid flow through porous rocks and soils, is a fundamental but often poorly quantified component in the analysis of regional-scale water fluxes. Permeability is difficult to quantify because it varies over more than 13 orders of magnitude and is heterogeneous and dependent on flow direction. Indeed, at the regional scale, maps of permeability only exist for soil to depths of 1-2 m. Here we use an extensive compilation of results from hydrogeologic models to show that regional-scale (>5 km) permeability of consolidated and unconsolidated geologic units below soil horizons (hydrolithologies) can be characterized in a statistically meaningful way. The representative permeabilities of these hydrolithologies are used to map the distribution of near-surface (on the order of 100 m depth) permeability globally and over North America. The distribution of each hydrolithology is generally scale independent. The near-surface mean permeability is of the order of -5 x 10-14 m2. The results provide the first global picture of near-surface permeability and will be of particular value for evaluating global water resources and modeling the influence of climate-surface-subsurface interactions on global climate change.
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Combined Climate and Carbon-Cycle Effects of Large-Scale Deforestation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bala, G; Caldeira, K; Wickett, M
2006-10-17
The prevention of deforestation and promotion of afforestation have often been cited as strategies to slow global warming. Deforestation releases CO{sub 2} to the atmosphere, which exerts a warming influence on Earth's climate. However, biophysical effects of deforestation, which include changes in land surface albedo, evapotranspiration, and cloud cover also affect climate. Here we present results from several large-scale deforestation experiments performed with a three-dimensional coupled global carbon-cycle and climate model. These are the first such simulations performed using a fully three-dimensional model representing physical and biogeochemical interactions among land, atmosphere, and ocean. We find that global-scale deforestation has amore » net cooling influence on Earth's climate, since the warming carbon-cycle effects of deforestation are overwhelmed by the net cooling associated with changes in albedo and evapotranspiration. Latitude-specific deforestation experiments indicate that afforestation projects in the tropics would be clearly beneficial in mitigating global-scale warming, but would be counterproductive if implemented at high latitudes and would offer only marginal benefits in temperate regions. While these results question the efficacy of mid- and high-latitude afforestation projects for climate mitigation, forests remain environmentally valuable resources for many reasons unrelated to climate.« less
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Pathways to sustainable intensification through crop water management
NASA Astrophysics Data System (ADS)
MacDonald, Graham K.; D'Odorico, Paolo; Seekell, David A.
2016-09-01
How much could farm water management interventions increase global crop production? This is the central question posed in a global modelling study by Jägermeyr et al (2016 Environ. Res. Lett. 11 025002). They define the biophysical realm of possibility for future gains in crop production related to agricultural water practices—enhancing water availability to crops and expanding irrigation by reducing non-productive water consumption. The findings of Jägermeyr et al offer crucial insight on the potential for crop water management to sustainably intensify agriculture, but they also provide a benchmark to consider the broader role of sustainable intensification targets in the global food system. Here, we reflect on how the global crop water management simulations of Jägermeyr et al could interact with: (1) farm size at more local scales, (2) downstream water users at the river basin scale, as well as (3) food trade and (4) demand-side food system strategies at the global scale. Incorporating such cross-scale linkages in future research could highlight the diverse pathways needed to harness the potential of farm-level crop water management for a more productive and sustainable global food system.
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Downscaling global precipitation for local applications - a case for the Rhine basin
NASA Astrophysics Data System (ADS)
Sperna Weiland, Frederiek; van Verseveld, Willem; Schellekens, Jaap
2017-04-01
Within the EU FP7 project eartH2Observe a global Water Resources Re-analysis (WRR) is being developed. This re-analysis consists of meteorological and hydrological water balance variables with global coverage, spanning the period 1979-2014 at 0.25 degrees resolution (Schellekens et al., 2016). The dataset can be of special interest in regions with limited in-situ data availability, yet for local scale analysis particularly in mountainous regions, a resolution of 0.25 degrees may be too coarse and downscaling the data to a higher resolution may be required. A downscaling toolbox has been made that includes spatial downscaling of precipitation based on the global WorldClim dataset that is available at 1 km resolution as a monthly climatology (Hijmans et al., 2005). The input of the down-scaling tool are either the global eartH2Observe WRR1 and WRR2 datasets based on the WFDEI correction methodology (Weedon et al., 2014) or the global Multi-Source Weighted-Ensemble Precipitation (MSWEP) dataset (Beck et al., 2016). Here we present a validation of the datasets over the Rhine catchment by means of a distributed hydrological model (wflow, Schellekens et al., 2014) using a number of precipitation scenarios. (1) We start by running the model using the local reference dataset derived by spatial interpolation of gauge observations. Furthermore we use (2) the MSWEP dataset at the native 0.25-degree resolution followed by (3) MSWEP downscaled with the WorldClim dataset and final (4) MSWEP downscaled with the local reference dataset. The validation will be based on comparison of the modeled river discharges as well as rainfall statistics. We expect that down-scaling the MSWEP dataset with the WorldClim data to higher resolution will increase its performance. To test the performance of the down-scaling routine we have added a run with MSWEP data down-scaled with the local dataset and compare this with the run based on the local dataset itself. - Beck, H. E. et al., 2016. MSWEP: 3-hourly 0.25° global gridded precipitation (1979-2015) by merging gauge, satellite, and reanalysis data, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-236, accepted for final publication. - Hijmans, R.J. et al., 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978. - Schellekens, J. et al., 2016. A global water resources ensemble of hydrological models: the eartH2Observe Tier-1 dataset, Earth Syst. Sci. Data Discuss., doi:10.5194/essd-2016-55, under review. - Schellekens, J. et al., 2014. Rapid setup of hydrological and hydraulic models using OpenStreetMap and the SRTM derived digital elevation model. Environmental Modelling&Software - Weedon, G.P. et al., 2014. The WFDEI meteorological forcing data set: WATCH Forcing Data methodology applied to ERA-Interim reanalysis data. Water Resources Research, 50, doi:10.1002/2014WR015638.
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Revised Perturbation Statistics for the Global Scale Atmospheric Model
NASA Technical Reports Server (NTRS)
Justus, C. G.; Woodrum, A.
1975-01-01
Magnitudes and scales of atmospheric perturbations about the monthly mean for the thermodynamic variables and wind components are presented by month at various latitudes. These perturbation statistics are a revision of the random perturbation data required for the global scale atmospheric model program and are from meteorological rocket network statistical summaries in the 22 to 65 km height range and NASA grenade and pitot tube data summaries in the region up to 90 km. The observed perturbations in the thermodynamic variables were adjusted to make them consistent with constraints required by the perfect gas law and the hydrostatic equation. Vertical scales were evaluated by Buell's depth of pressure system equation and from vertical structure function analysis. Tables of magnitudes and vertical scales are presented for each month at latitude 10, 30, 50, 70, and 90 degrees.
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Modeling the Earth system in the Mission to Planet Earth era
NASA Technical Reports Server (NTRS)
Unninayar, Sushel; Bergman, Kenneth H.
1993-01-01
A broad overview is made of global earth system modeling in the Mission to Planet Earth (MTPE) era for the multidisciplinary audience encompassed by the Global Change Research Program (GCRP). Time scales of global system fluctuation and change are described in Section 2. Section 3 provides a rubric for modeling the global earth system, as presently understood. The ability of models to predict the future state of the global earth system and the extent to which their predictions are reliable are covered in Sections 4 and 5. The 'engineering' use of global system models (and predictions) is covered in Section 6. Section 7 covers aspects of an increasing need for improved transform algorithms and better methods to assimilate this information into global models. Future monitoring and data requirements are detailed in Section 8. Section 9 covers the NASA-initiated concept 'Mission to Planet Earth,' which employs space and ground based measurement systems to provide the scientific basis for understanding global change. Section 10 concludes this review with general remarks concerning the state of global system modeling and observing technology and the need for future research.
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GEWEX Continental-scale International Project (GCIP)
NASA Technical Reports Server (NTRS)
Try, Paul
1993-01-01
The Global Energy and Water Cycle Experiment (GEWEX) represents the World Climate Research Program activities on clouds, radiation, and land-surface processes. The goal of the program is to reproduce and predict, by means of suitable models, the variations of the global hydrological regime and its impact on atmospheric and oceanic dynamics. However, GEWEX is also concerned with variations in regional hydrological processes and water resources and their response to changes in the environment such as increasing greenhouse gases. In fact, GEWEX contains a major new international project called the GEWEX Continental-scale International Project (GCIP), which is designed to bridge the gap between the small scales represented by hydrological models and those scales that are practical for predicting the regional impacts of climate change. The development and use of coupled mesoscale-hydrological models for this purpose is a high priority in GCIP. The objectives of GCIP are presented.
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NASA Astrophysics Data System (ADS)
Malanotte-Rizzoli, Paola; Young, Roberta E.
1995-12-01
The primary objective of this paper is to assess the relative effectiveness of data sets with different space coverage and time resolution when they are assimilated into an ocean circulation model. We focus on obtaining realistic numerical simulations of the Gulf Stream system typically of the order of 3-month duration by constructing a "synthetic" ocean simultaneously consistent with the model dynamics and the observations. The model used is the Semispectral Primitive Equation Model. The data sets are the "global" Optimal Thermal Interpolation Scheme (OTIS) 3 of the Fleet Numerical Oceanography Center providing temperature and salinity fields with global coverage and with bi-weekly frequency, and the localized measurements, mostly of current velocities, from the central and eastern array moorings of the Synoptic Ocean Prediction (SYNOP) program, with daily frequency but with a very small spatial coverage. We use a suboptimal assimilation technique ("nudging"). Even though this technique has already been used in idealized data assimilation studies, to our knowledge this is the first study in which the effectiveness of nudging is tested by assimilating real observations of the interior temperature and salinity fields. This is also the first work in which a systematic assimilation is carried out of the localized, high-quality SYNOP data sets in numerical experiments longer than 1-2 weeks, that is, not aimed to forecasting. We assimilate (1) the global OTIS 3 alone, (2) the local SYNOP observations alone, and (3) both OTIS 3 and SYNOP observations. We assess the success of the assimilations with quantitative measures of performance, both on the global and local scale. The results can be summarized as follows. The intermittent assimilation of the global OTIS 3 is necessary to keep the model "on track" over 3-month simulations on the global scale. As OTIS 3 is assimilated at every model grid point, a "gentle" weight must be prescribed to it so as not to overconstrain the model. However, in these assimilations the predicted velocity fields over the SYNOP arrays are greatly in error. The continuous assimilation of the localized SYNOP data sets with a strong weight is necessary to obtain local realistic evolutions. Then assimilation of velocity measurements alone recovers the density structure over the array area. However, the spatial coverage of the SYNOP measurements is too small to constrain the model on the global scale. Thus the blending of both types of datasets is necessary in the assimilation as they constrain different time and space scales. Our choice of "gentle" nudging weight for the global OTIS 3 and "strong" weight for the local SYNOP data provides for realistic simulations of the Gulf Stream system, both globally and locally, on the 3- to 4-month-long timescale, the one governed by the Gulf Stream jet internal dynamics.
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NASA Astrophysics Data System (ADS)
Wood, E. F.; Yuan, X.; Sheffield, J.; Pan, M.; Roundy, J.
2013-12-01
One of the key recommendations of the WCRP Global Drought Information System (GDIS) workshop is to develop an experimental real-time global monitoring and prediction system. While great advances has been made in global drought monitoring based on satellite observations and model reanalysis data, global drought forecasting has been stranded in part due to the limited skill both in climate forecast models and global hydrologic predictions. Having been working on drought monitoring and forecasting over USA for more than a decade, the Princeton land surface hydrology group is now developing an experimental global drought early warning system that is based on multiple climate forecast models and a calibrated global hydrologic model. In this presentation, we will test its capability in seasonal forecasting of meteorological, agricultural and hydrologic droughts over global major river basins, using precipitation, soil moisture and streamflow forecasts respectively. Based on the joint probability distribution between observations using Princeton's global drought monitoring system and model hindcasts and real-time forecasts from North American Multi-Model Ensemble (NMME) project, we (i) bias correct the monthly precipitation and temperature forecasts from multiple climate forecast models, (ii) downscale them to a daily time scale, and (iii) use them to drive the calibrated VIC model to produce global drought forecasts at a 1-degree resolution. A parallel run using the ESP forecast method, which is based on resampling historical forcings, is also carried out for comparison. Analysis is being conducted over global major river basins, with multiple drought indices that have different time scales and characteristics. The meteorological drought forecast does not have uncertainty from hydrologic models and can be validated directly against observations - making the validation an 'apples-to-apples' comparison. Preliminary results for the evaluation of meteorological drought onset hindcasts indicate that climate models increase drought detectability over ESP by 31%-81%. However, less than 30% of the global drought onsets can be detected by climate models. The missed drought events are associated with weak ENSO signals and lower potential predictability. Due to the high false alarms from climate models, the reliability is more important than sharpness for a skillful probabilistic drought onset forecast. Validations and skill assessments for agricultural and hydrologic drought forecasts are carried out using soil moisture and streamflow output from the VIC land surface model (LSM) forced by a global forcing data set. Given our previous drought forecasting experiences over USA and Africa, validating the hydrologic drought forecasting is a significant challenge for a global drought early warning system.
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NASA Astrophysics Data System (ADS)
Beck, Hylke; de Roo, Ad; van Dijk, Albert; McVicar, Tim; Miralles, Diego; Schellekens, Jaap; Bruijnzeel, Sampurno; de Jeu, Richard
2015-04-01
Motivated by the lack of large-scale model parameter regionalization studies, a large set of 3328 small catchments (< 10000 km2) around the globe was used to set up and evaluate five model parameterization schemes at global scale. The HBV-light model was chosen because of its parsimony and flexibility to test the schemes. The catchments were calibrated against observed streamflow (Q) using an objective function incorporating both behavioral and goodness-of-fit measures, after which the catchment set was split into subsets of 1215 donor and 2113 evaluation catchments based on the calibration performance. The donor catchments were subsequently used to derive parameter sets that were transferred to similar grid cells based on a similarity measure incorporating climatic and physiographic characteristics, thereby producing parameter maps with global coverage. Overall, there was a lack of suitable donor catchments for mountainous and tropical environments. The schemes with spatially-uniform parameter sets (EXP2 and EXP3) achieved the worst Q estimation performance in the evaluation catchments, emphasizing the importance of parameter regionalization. The direct transfer of calibrated parameter sets from donor catchments to similar grid cells (scheme EXP1) performed best, although there was still a large performance gap between EXP1 and HBV-light calibrated against observed Q. The schemes with parameter sets obtained by simultaneously calibrating clusters of similar donor catchments (NC10 and NC58) performed worse than EXP1. The relatively poor Q estimation performance achieved by two (uncalibrated) macro-scale hydrological models suggests there is considerable merit in regionalizing the parameters of such models. The global HBV-light parameter maps and ancillary data are freely available via http://water.jrc.ec.europa.eu.
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Implementing microscopic charcoal in a global climate-aerosol model
NASA Astrophysics Data System (ADS)
Gilgen, Anina; Lohmann, Ulrike; Brügger, Sandra; Adolf, Carole; Ickes, Luisa
2017-04-01
Information about past fire activity is crucial to validate fire models and to better understand their deficiencies. Several paleofire records exist, among them ice cores and sediments, which preserve fire tracers like levoglucosan, vanillic acid, or charcoal particles. In this work, we implement microscopic charcoal particles (maximum dimension 10-100 μm) into the global climate-aerosol model ECHAM6.3HAM2.3. Since we are not aware of any reliable estimates of microscopic charcoal emissions, we scaled black carbon emissions from GFAS to capture the charcoal fluxes from a calibration dataset. After that, model results were compared with a validation dataset. The coarse model resolution (T63L31; 1.9°x1.9°) impedes the model to capture local variability of charcoal fluxes. However, variability on the global scale is pronounced due to highly-variable fire emissions. In future, we plan to model charcoal fluxes in the past 1-2 centuries using fire emissions provided from fire models. Furthermore, we intend to compare modelled charcoal fluxes from prescribed fire emissions with those calculated by an interactive fire model.
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Thomas W. Bonnot; Frank R. Thompson; Joshua J. Millspaugh; D. Todd Jones-Farland
2013-01-01
Efforts to conserve regional biodiversity in the face of global climate change, habitat loss and fragmentation will depend on approaches that consider population processes at multiple scales. By combining habitat and demographic modeling, landscape-based population viability models effectively relate small-scale habitat and landscape patterns to regional population...
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Coupled fvGCM-GCE Modeling System: TRMM Latent Heating and Cloud Library
NASA Technical Reports Server (NTRS)
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 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. A seed fund is available at NASA Goddard to build a MMF based on the 2D GCE model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF will be developed by the end of 2004 and production runs will be conducted at the beginning of 2005. The purpose of this proposal is to augment the current Goddard MMF and other cloud modeling activities. In this talk, I will present: (1) A summary of the second Cloud Modeling Workshop took place at NASA Goddard, (2) A summary of the third TRMM Latent Heating Workshop took place at Nara Japan, (3) A brief discussion on the GCE model on developing a global cloud simulator.
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NASA Astrophysics Data System (ADS)
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.
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Walker, Anthony P.; Beckerman, Andrew P.; Gu, Lianhong; ...
2014-07-25
Great uncertainty exists in the global exchange of carbon between the atmosphere and the terrestrial biosphere. An important source of this uncertainty lies in the dependency of photosynthesis on the maximum rate of carboxylation (Vcmax) and the maximum rate of electron transport (Jmax). Understanding and making accurate prediction of C fluxes thus requires accurate characterization of these rates and their relationship with plant nutrient status over large geographic scales. Plant nutrient status is indicated by the traits: leaf nitrogen (N), leaf phosphorus (P), and specific leaf area (SLA). Correlations between Vcmax and Jmax and leaf nitrogen (N) are typically derivedmore » from local to global scales, while correlations with leaf phosphorus (P) and specific leaf area (SLA) have typically been derived at a local scale. Thus, there is no global-scale relationship between Vcmax and Jmax and P or SLA limiting the ability of global-scale carbon flux models do not account for P or SLA. We gathered published data from 24 studies to reveal global relationships of Vcmax and Jmax with leaf N, P, and SLA. Vcmax was strongly related to leaf N, and increasing leaf P substantially increased the sensitivity of Vcmax to leaf N. Jmax was strongly related to Vcmax, and neither leaf N, P, or SLA had a substantial impact on the relationship. Although more data are needed to expand the applicability of the relationship, we show leaf P is a globally important determinant of photosynthetic rates. In a model of photosynthesis, we showed that at high leaf N (3 gm 2), increasing leaf P from 0.05 to 0.22 gm 2 nearly doubled assimilation rates. Lastly, we show that plants may employ a conservative strategy of Jmax to Vcmax coordination that restricts photoinhibition when carboxylation is limiting at the expense of maximizing photosynthetic rates when light is limiting.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Walker, Anthony P.; Beckerman, Andrew P.; Gu, Lianhong
Great uncertainty exists in the global exchange of carbon between the atmosphere and the terrestrial biosphere. An important source of this uncertainty lies in the dependency of photosynthesis on the maximum rate of carboxylation (Vcmax) and the maximum rate of electron transport (Jmax). Understanding and making accurate prediction of C fluxes thus requires accurate characterization of these rates and their relationship with plant nutrient status over large geographic scales. Plant nutrient status is indicated by the traits: leaf nitrogen (N), leaf phosphorus (P), and specific leaf area (SLA). Correlations between Vcmax and Jmax and leaf nitrogen (N) are typically derivedmore » from local to global scales, while correlations with leaf phosphorus (P) and specific leaf area (SLA) have typically been derived at a local scale. Thus, there is no global-scale relationship between Vcmax and Jmax and P or SLA limiting the ability of global-scale carbon flux models do not account for P or SLA. We gathered published data from 24 studies to reveal global relationships of Vcmax and Jmax with leaf N, P, and SLA. Vcmax was strongly related to leaf N, and increasing leaf P substantially increased the sensitivity of Vcmax to leaf N. Jmax was strongly related to Vcmax, and neither leaf N, P, or SLA had a substantial impact on the relationship. Although more data are needed to expand the applicability of the relationship, we show leaf P is a globally important determinant of photosynthetic rates. In a model of photosynthesis, we showed that at high leaf N (3 gm 2), increasing leaf P from 0.05 to 0.22 gm 2 nearly doubled assimilation rates. Lastly, we show that plants may employ a conservative strategy of Jmax to Vcmax coordination that restricts photoinhibition when carboxylation is limiting at the expense of maximizing photosynthetic rates when light is limiting.« less
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NASA Astrophysics Data System (ADS)
Guenet, Bertrand; Esteban Moyano, Fernando; Peylin, Philippe; Ciais, Philippe; Janssens, Ivan A.
2016-03-01
Priming of soil carbon decomposition encompasses different processes through which the decomposition of native (already present) soil organic matter is amplified through the addition of new organic matter, with new inputs typically being more labile than the native soil organic matter. Evidence for priming comes from laboratory and field experiments, but to date there is no estimate of its impact at global scale and under the current anthropogenic perturbation of the carbon cycle. Current soil carbon decomposition models do not include priming mechanisms, thereby introducing uncertainty when extrapolating short-term local observations to ecosystem and regional to global scale. In this study we present a simple conceptual model of decomposition priming, called PRIM, able to reproduce laboratory (incubation) and field (litter manipulation) priming experiments. Parameters for this model were first optimized against data from 20 soil incubation experiments using a Bayesian framework. The optimized parameter values were evaluated against another set of soil incubation data independent from the ones used for calibration and the PRIM model reproduced the soil incubations data better than the original, CENTURY-type soil decomposition model, whose decomposition equations are based only on first-order kinetics. We then compared the PRIM model and the standard first-order decay model incorporated into the global land biosphere model ORCHIDEE (Organising Carbon and Hydrology In Dynamic Ecosystems). A test of both models was performed at ecosystem scale using litter manipulation experiments from five sites. Although both versions were equally able to reproduce observed decay rates of litter, only ORCHIDEE-PRIM could simulate the observed priming (R2 = 0.54) in cases where litter was added or removed. This result suggests that a conceptually simple and numerically tractable representation of priming adapted to global models is able to capture the sign and magnitude of the priming of litter and soil organic matter.
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NASA Astrophysics Data System (ADS)
Guenet, B.; Moyano, F. E.; Peylin, P.; Ciais, P.; Janssens, I. A.
2015-10-01
Priming of soil carbon decomposition encompasses different processes through which the decomposition of native (already present) soil organic matter is amplified through the addition of new organic matter, with new inputs typically being more labile than the native soil organic matter. Evidence for priming comes from laboratory and field experiments, but to date there is no estimate of its impact at global scale and under the current anthropogenic perturbation of the carbon cycle. Current soil carbon decomposition models do not include priming mechanisms, thereby introducing uncertainty when extrapolating short-term local observations to ecosystem and regional to global scale. In this study we present a simple conceptual model of decomposition priming, called PRIM, able to reproduce laboratory (incubation) and field (litter manipulation) priming experiments. Parameters for this model were first optimized against data from 20 soil incubation experiments using a Bayesian framework. The optimized parameter values were evaluated against another set of soil incubation data independent from the ones used for calibration and the PRIM model reproduced the soil incubations data better than the original, CENTURY-type soil decomposition model, whose decomposition equations are based only on first order kinetics. We then compared the PRIM model and the standard first order decay model incorporated into the global land biosphere model ORCHIDEE. A test of both models was performed at ecosystem scale using litter manipulation experiments from 5 sites. Although both versions were equally able to reproduce observed decay rates of litter, only ORCHIDEE-PRIM could simulate the observed priming (R2 = 0.54) in cases where litter was added or removed. This result suggests that a conceptually simple and numerically tractable representation of priming adapted to global models is able to capture the sign and magnitude of the priming of litter and soil organic matter.
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NASA Astrophysics Data System (ADS)
England, S.; Lillis, R. J.
2011-12-01
Knowledge of Mars' thermospheric mass density (~120--200 km altitude) is important for understanding the current state and evolution of the Martian atmosphere and for spacecraft such as the upcoming MAVEN mission that will fly through this region every orbit. Global-scale atmospheric models have been shown thus far to do an inconsistent job of matching mass density observations at these altitudes, especially on the nightside. Thus there is a clear need for a data-driven estimate of the mass density in this region. Given the wide range of conditions and locations over which these must be defined, the dataset of thermospheric mass densities derived from energy and angular distributions of super-thermal electrons measured by the MAG/ER experiment on Mars Global Surveyor, spanning 4 full Martian years, is an extremely valuable resource that can be used to enhance our prediction of these densities beyond what is given by such global-scale models. Here we present an empirical model of the thermospheric density structure based on the MAG/ER dataset. Using this new model, we assess the global-scale response of the thermosphere to dust storms in the lower atmosphere and show that this varies with latitude. Further, we examine the short- and longer-term variability of the thermospheric density and show that it exhibits a complex behavior with latitude and season that is indicative of both atmospheric conditions at lower altitudes and possible lower atmosphere wave sources.
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NASA Astrophysics Data System (ADS)
Kozyra, J. U.; Brandt, P. C.; Cattell, C. A.; Clilverd, M.; de Zeeuw, D.; Evans, D. S.; Fang, X.; Frey, H. U.; Kavanagh, A. J.; Liemohn, M. W.; Lu, G.; Mende, S. B.; Paxton, L. J.; Ridley, A. J.; Rodger, C. J.; Soraas, F.
2010-12-01
Energetic ions and electrons that precipitate into the upper atmosphere from sources throughout geospace carry the influences of space weather disturbances deeper into the atmosphere, possibly contributing to climate variability. The three-dimensional atmospheric effects of these precipitating particles are a function of the energy and species of the particles, lifetimes of reactive species generated during collisions in the atmosphere, the nature of the driving space weather disturbance, and the large-scale transport properties (meteorology) of the atmosphere in the region of impact. Unraveling the features of system-level coupling between solar magnetic variability, space weather and stratospheric dynamics requires a global view of the precipitation, along with its temporal and spatial variation. However, observations of particle precipitation at the system level are sparse and incomplete requiring they be combined with other observations and with large-scale models to provide the global context that is needed to accelerate progress. We compare satellite and ground-based observations of geospace conditions and energetic precipitation (at ring current, radiation belt and auroral energies) to a simulation of the geospace environment during 21-22 January 2005 by the BATS-R-US MHD model coupled with a self-consistent ring current solution. The aim is to explore the extent to which regions of particle precipitation track global magnetic field distortions and ways in which global models enhance our understanding of linkages between solar wind drivers and evolution of energetic particle precipitation.
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Improved pattern scaling approaches for the use in climate impact studies
NASA Astrophysics Data System (ADS)
Herger, Nadja; Sanderson, Benjamin M.; Knutti, Reto
2015-05-01
Pattern scaling is a simple way to produce climate projections beyond the scenarios run with expensive global climate models (GCMs). The simplest technique has known limitations and assumes that a spatial climate anomaly pattern obtained from a GCM can be scaled by the global mean temperature (GMT) anomaly. We propose alternatives and assess their skills and limitations. One approach which avoids scaling is to consider a period in a different scenario with the same GMT change. It is attractive as it provides patterns of any temporal resolution that are consistent across variables, and it does not distort variability. Second, we extend the traditional approach with a land-sea contrast term, which provides the largest improvements over the traditional technique. When interpolating between known bounding scenarios, the proposed methods significantly improve the accuracy of the pattern scaled scenario with little computational cost. The remaining errors are much smaller than the Coupled Model Intercomparison Project Phase 5 model spread.
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NASA Astrophysics Data System (ADS)
Tourigny, E.; Nobre, C.; Cardoso, M. F.
2012-12-01
Deforestation of tropical forests for logging and agriculture, associated to slash-and-burn practices, is a major source of CO2 emissions, both immediate due to biomass burning and future due to the elimination of a potential CO2 sink. Feedbacks between climate change and LUCC (Land-Use and Land-Cover Change) can potentially increase the loss of tropical forests and increase the rate of CO2 emissions, through mechanisms such as land and soil degradation and the increase in wildfire occurrence and severity. However, current understanding of the processes of fires (including ignition, spread and consequences) in tropical forests and climatic feedbacks are poorly understood and need further research. As the processes of LUCC and associated fires occur at local scales, linking them to large-scale atmospheric processes requires a means of up-scaling higher resolutions processes to lower resolutions. Our approach is to couple models which operate at various spatial and temporal scales: a Global Climate Model (GCM), Dynamic Global Vegetation Model (DGVM) and local-scale LUCC and fire spread model. The climate model resolves large scale atmospheric processes and forcings, which are imposed on the surface DGVM and fed-back to climate. Higher-resolution processes such as deforestation, land use management and associated (as well as natural) fires are resolved at the local level. A dynamic tiling scheme allows to represent local-scale heterogeneity while maintaining computational efficiency of the land surface model, compared to traditional landscape models. Fire behavior is modeled at the regional scale (~500m) to represent the detailed landscape using a semi-empirical fire spread model. The relatively coarse scale (as compared to other fire spread models) is necessary due to the paucity of detailed land-cover information and fire history (particularly in the tropics and developing countries). This work presents initial results of a spatially-explicit fire spread model coupled to the IBIS DGVM model. Our area of study comprises selected regions in and near the Brazilian "arc of deforestation". For model training and evaluation, several areas have been mapped using high-resolution imagery from the Landsat TM/ETM+ sensors (Figure 1). This high resolution reference data is used for local-scale simulations and also to evaluate the accuracy of the global MCD45 burned area product, which will be used in future studies covering the entire "arc of deforestation".; Area of study along the arc of deforestation and cerrado: landsat scenes used and burned area (2010) from MCD45 product.
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From global circulation to flood loss: Coupling models across the scales
NASA Astrophysics Data System (ADS)
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.
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Data-driven modeling of surface temperature anomaly and solar activity trends
Friedel, Michael J.
2012-01-01
A novel two-step modeling scheme is used to reconstruct and analyze surface temperature and solar activity data at global, hemispheric, and regional scales. First, the self-organizing map (SOM) technique is used to extend annual modern climate data from the century to millennial scale. The SOM component planes are used to identify and quantify strength of nonlinear relations among modern surface temperature anomalies (<150 years), tropical and extratropical teleconnections, and Palmer Drought Severity Indices (0–2000 years). Cross-validation of global sea and land surface temperature anomalies verifies that the SOM is an unbiased estimator with less uncertainty than the magnitude of anomalies. Second, the quantile modeling of SOM reconstructions reveal trends and periods in surface temperature anomaly and solar activity whose timing agrees with published studies. Temporal features in surface temperature anomalies, such as the Medieval Warm Period, Little Ice Age, and Modern Warming Period, appear at all spatial scales but whose magnitudes increase when moving from ocean to land, from global to regional scales, and from southern to northern regions. Some caveats that apply when interpreting these data are the high-frequency filtering of climate signals based on quantile model selection and increased uncertainty when paleoclimatic data are limited. Even so, all models find the rate and magnitude of Modern Warming Period anomalies to be greater than those during the Medieval Warm Period. Lastly, quantile trends among reconstructed equatorial Pacific temperature profiles support the recent assertion of two primary El Niño Southern Oscillation types. These results demonstrate the efficacy of this alternative modeling approach for reconstructing and interpreting scale-dependent climate variables.
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NASA Astrophysics Data System (ADS)
Hirt, Christian; Reußner, Elisabeth; Rexer, Moritz; Kuhn, Michael
2016-09-01
Over the past years, spectral techniques have become a standard to model Earth's global gravity field to 10 km scales, with the EGM2008 geopotential model being a prominent example. For some geophysical applications of EGM2008, particularly Bouguer gravity computation with spectral techniques, a topographic potential model of adequate resolution is required. However, current topographic potential models have not yet been successfully validated to degree 2160, and notable discrepancies between spectral modeling and Newtonian (numerical) integration well beyond the 10 mGal level have been reported. Here we accurately compute and validate gravity implied by a degree 2160 model of Earth's topographic masses. Our experiments are based on two key strategies, both of which require advanced computational resources. First, we construct a spectrally complete model of the gravity field which is generated by the degree 2160 Earth topography model. This involves expansion of the topographic potential to the 15th integer power of the topography and modeling of short-scale gravity signals to ultrahigh degree of 21,600, translating into unprecedented fine scales of 1 km. Second, we apply Newtonian integration in the space domain with high spatial resolution to reduce discretization errors. Our numerical study demonstrates excellent agreement (8 μGgal RMS) between gravity from both forward modeling techniques and provides insight into the convergence process associated with spectral modeling of gravity signals at very short scales (few km). As key conclusion, our work successfully validates the spectral domain forward modeling technique for degree 2160 topography and increases the confidence in new high-resolution global Bouguer gravity maps.
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Coral Reef Color: Remote and In-Situ Imaging Spectroscopy of Reef Structure and Function
NASA Astrophysics Data System (ADS)
Hochberg, E. J.
2016-02-01
Coral reefs are threatened at local to global scales by a litany of anthropogenic impacts, including overfishing, coastal development, marine and watershed pollution, rising ocean temperatures, and ocean acidification. However, available data for the primary indicator of coral reef condition — proportional cover of living coral — are surprisingly sparse and show patterns that contradict the prevailing understanding of how environment impacts reef condition. Remote sensing is the only available tool for acquiring synoptic, uniform data on reef condition at regional to global scales. Discrimination between coral and other reef benthos relies on narrow wavebands afforded by imaging spectroscopy. The same spectral information allows non-invasive quantification of photosynthetic pigment composition, which shows unexpected phenological trends. There is also potential to link biodiversity with optical diversity, though there has been no effort in that direction. Imaging spectroscopy underlies the light-use efficiency model for reef primary production by quantifying light capture, which in turn indicates biochemical capacity for CO2 assimilation. Reef calcification is strongly correlated with primary production, suggesting the possibility for an optics-based model of that aspect of reef function, as well. By scaling these spectral models for use with remote sensing, we can vastly improve our understanding of reef structure, function, and overall condition across regional to global scales. By analyzing those remote sensing products against ancillary environmental data, we can construct secondary models to predict reef futures in the era of global change. This final point is the objective of CORAL (COral Reef Airborne Laboratory), a three-year project funded under NASA's Earth Venture Suborbital-2 program to investigate the relationship between coral reef condition at the ecosystem scale and various nominal biogeophysical forcing parameters.
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Coral Reef Color: Remote and In-Situ Imaging Spectroscopy of Reef Structure and Function
NASA Astrophysics Data System (ADS)
Hochberg, E. J.
2015-12-01
Coral reefs are threatened at local to global scales by a litany of anthropogenic impacts, including overfishing, coastal development, marine and watershed pollution, rising ocean temperatures, and ocean acidification. However, available data for the primary indicator of coral reef condition — proportional cover of living coral — are surprisingly sparse and show patterns that contradict the prevailing understanding of how environment impacts reef condition. Remote sensing is the only available tool for acquiring synoptic, uniform data on reef condition at regional to global scales. Discrimination between coral and other reef benthos relies on narrow wavebands afforded by imaging spectroscopy. The same spectral information allows non-invasive quantification of photosynthetic pigment composition, which shows unexpected phenological trends. There is also potential to link biodiversity with optical diversity, though there has been no effort in that direction. Imaging spectroscopy underlies the light-use efficiency model for reef primary production by quantifying light capture, which in turn indicates biochemical capacity for CO2 assimilation. Reef calcification is strongly correlated with primary production, suggesting the possibility for an optics-based model of that aspect of reef function, as well. By scaling these spectral models for use with remote sensing, we can vastly improve our understanding of reef structure, function, and overall condition across regional to global scales. By analyzing those remote sensing products against ancillary environmental data, we can construct secondary models to predict reef futures in the era of global change. This final point is the objective of CORAL (COral Reef Airborne Laboratory), a three-year project funded under NASA's Earth Venture Suborbital-2 program to investigate the relationship between coral reef condition at the ecosystem scale and various nominal biogeophysical forcing parameters.
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Black carbon absorption at the global scale is affected by particle-scale diversity in composition.
Fierce, Laura; Bond, Tami C; Bauer, Susanne E; Mena, Francisco; Riemer, Nicole
2016-09-01
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 (Eabs) 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 Eabs=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.
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Black Carbon Absorption at the Global Scale Is Affected by Particle-Scale Diversity in Composition
NASA Technical Reports Server (NTRS)
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.
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El-Gabbas, Ahmed; Dormann, Carsten F
2018-02-01
Species distribution modeling (SDM) is an essential method in ecology and conservation. SDMs are often calibrated within one country's borders, typically along a limited environmental gradient with biased and incomplete data, making the quality of these models questionable. In this study, we evaluated how adequate are national presence-only data for calibrating regional SDMs. We trained SDMs for Egyptian bat species at two different scales: only within Egypt and at a species-specific global extent. We used two modeling algorithms: Maxent and elastic net, both under the point-process modeling framework. For each modeling algorithm, we measured the congruence of the predictions of global and regional models for Egypt, assuming that the lower the congruence, the lower the appropriateness of the Egyptian dataset to describe the species' niche. We inspected the effect of incorporating predictions from global models as additional predictor ("prior") to regional models, and quantified the improvement in terms of AUC and the congruence between regional models run with and without priors. Moreover, we analyzed predictive performance improvements after correction for sampling bias at both scales. On average, predictions from global and regional models in Egypt only weakly concur. Collectively, the use of priors did not lead to much improvement: similar AUC and high congruence between regional models calibrated with and without priors. Correction for sampling bias led to higher model performance, whatever prior used, making the use of priors less pronounced. Under biased and incomplete sampling, the use of global bats data did not improve regional model performance. Without enough bias-free regional data, we cannot objectively identify the actual improvement of regional models after incorporating information from the global niche. However, we still believe in great potential for global model predictions to guide future surveys and improve regional sampling in data-poor regions.
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NASA Astrophysics Data System (ADS)
Wong, M.; Skamarock, W. C.
2015-12-01
Global numerical weather forecast tests were performed using the global nonhydrostatic atmospheric model, Model for Prediction Across Scales (MPAS), for the NOAA Storm Prediction Center 2015 Spring Forecast Experiment (May 2015) and the Plains Elevated Convection at Night (PECAN) field campaign (June to mid-July 2015). These two sets of forecasts were performed on 50-to-3 km and 15-to-3 km smoothly-varying horizontal meshes, respectively. Both variable-resolution meshes have nominal convection-permitting 3-km grid spacing over the entire continental US. Here we evaluate the limited-area (vs. global) spectra from these NWP simulations. We will show the simulated spectral characteristics of total kinetic energy, vertical velocity variance, and precipitation during these spring and summer periods when diurnal continental convection is most active over central US. Spectral characteristics of a high-resolution global 3-km simulation (essentially no nesting) from the 20 May 2013 Moore, OK tornado case are also shown. These characteristics include spectral scaling, shape, and anisotropy, as well as the effective resolution of continental convection representation in MPAS.
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Terrestrial biosphere changes over the last 120 kyr
NASA Astrophysics Data System (ADS)
Hoogakker, B. A. A.; Smith, R. S.; Singarayer, J. S.; Marchant, R.; Prentice, I. C.; Allen, J. R. M.; Anderson, R. S.; Bhagwat, S. A.; Behling, H.; Borisova, O.; Bush, M.; Correa-Metrio, A.; de Vernal, A.; Finch, J. M.; Fréchette, B.; Lozano-Garcia, S.; Gosling, W. D.; Granoszewski, W.; Grimm, E. C.; Grüger, E.; Hanselman, J.; Harrison, S. P.; Hill, T. R.; Huntley, B.; Jiménez-Moreno, G.; Kershaw, P.; Ledru, M.-P.; Magri, D.; McKenzie, M.; Müller, U.; Nakagawa, T.; Novenko, E.; Penny, D.; Sadori, L.; Scott, L.; Stevenson, J.; Valdes, P. J.; Vandergoes, M.; Velichko, A.; Whitlock, C.; Tzedakis, C.
2016-01-01
A new global synthesis and biomization of long (> 40 kyr) pollen-data records is presented and used with simulations from the HadCM3 and FAMOUS climate models and the BIOME4 vegetation model to analyse the dynamics of the global terrestrial biosphere and carbon storage over the last glacial-interglacial cycle. Simulated biome distributions using BIOME4 driven by HadCM3 and FAMOUS at the global scale over time generally agree well with those inferred from pollen data. Global average areas of grassland and dry shrubland, desert, and tundra biomes show large-scale increases during the Last Glacial Maximum, between ca. 64 and 74 ka BP and cool substages of Marine Isotope Stage 5, at the expense of the tropical forest, warm-temperate forest, and temperate forest biomes. These changes are reflected in BIOME4 simulations of global net primary productivity, showing good agreement between the two models. Such changes are likely to affect terrestrial carbon storage, which in turn influences the stable carbon isotopic composition of seawater as terrestrial carbon is depleted in 13C.
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Estimation of Fractional Plant Lifeform Cover Using Landsat and Airborne LiDAR/hyperspectral Data
NASA Astrophysics Data System (ADS)
Parra, A. S.; Xu, Q.; Dilts, T.; Weisberg, P.; Greenberg, J. A.
2017-12-01
Land-cover change has generally been understood as the result of local, landscape or regional-scale processes with most studies focusing on case-study landscapes or smaller regions. However, as we observe similar types of land-cover change occurring across different biomes worldwide, it becomes clear that global-scale processes such as climate change and CO2 fertilization, in interaction with local influences, are underlying drivers in land-cover change patterns. Prior studies on global land-cover change may not have had a suitable spatial, temporal and thematic resolution for allowing the identification of such patterns. Furthermore, the lack of globally consistent spatial data products also constitutes a limiting factor in evaluating both proximate and ultimate causes of land-cover change. In this study, we derived a global model for broadleaf tree, needleleaf tree, shrub, herbaceous, and "other" fractional cover using Landsat imagery. Combined LiDAR/hyperspectral data sets were used for calibration and validation of the Landsat-derived products. Spatially explicit uncertainties were also created as part of the data products. Our results highlight the potential for large-scale studies that model local and global influences on land-cover transition types and rates at fine thematic, spatial, and temporal resolutions. These spatial data products are relevant for identifying patterns in land-cover change due to underlying global-scale processes and can provide valuable insights into climatic and land-use factors determining vegetation distributions.
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Forecasting of global solar radiation using anfis and armax techniques
NASA Astrophysics Data System (ADS)
Muhammad, Auwal; Gaya, M. S.; Aliyu, Rakiya; Aliyu Abdulkadir, Rabi'u.; Dauda Umar, Ibrahim; Aminu Yusuf, Lukuman; Umar Ali, Mudassir; Khairi, M. T. M.
2018-01-01
Procurement of measuring device, maintenance cost coupled with calibration of the instrument contributed to the difficulty in forecasting of global solar radiation in underdeveloped countries. Most of the available regressional and mathematical models do not capture well the behavior of the global solar radiation. This paper presents the comparison of Adaptive Neuro Fuzzy Inference System (ANFIS) and Autoregressive Moving Average with eXogenous term (ARMAX) in forecasting global solar radiation. Full-Scale (experimental) data of Nigerian metrological agency, Sultan Abubakar III international airport Sokoto was used to validate the models. The simulation results demonstrated that the ANFIS model having achieved MAPE of 5.34% outperformed the ARMAX model. The ANFIS could be a valuable tool for forecasting the global solar radiation.
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A next generation air quality modeling system is being developed at the U.S. EPA to enable modeling of air quality from global to regional to (eventually) local scales. We envision that the system will have three configurations: 1. Global meteorology with seamless mesh refinemen...
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Mapping local and global variability in plant trait distributions.
Butler, Ethan E; Datta, Abhirup; Flores-Moreno, Habacuc; Chen, Ming; Wythers, Kirk R; Fazayeli, Farideh; Banerjee, Arindam; Atkin, Owen K; Kattge, Jens; Amiaud, Bernard; Blonder, Benjamin; Boenisch, Gerhard; Bond-Lamberty, Ben; Brown, Kerry A; Byun, Chaeho; Campetella, Giandiego; Cerabolini, Bruno E L; Cornelissen, Johannes H C; Craine, Joseph M; Craven, Dylan; de Vries, Franciska T; Díaz, Sandra; Domingues, Tomas F; Forey, Estelle; González-Melo, Andrés; Gross, Nicolas; Han, Wenxuan; Hattingh, Wesley N; Hickler, Thomas; Jansen, Steven; Kramer, Koen; Kraft, Nathan J B; Kurokawa, Hiroko; Laughlin, Daniel C; Meir, Patrick; Minden, Vanessa; Niinemets, Ülo; Onoda, Yusuke; Peñuelas, Josep; Read, Quentin; Sack, Lawren; Schamp, Brandon; Soudzilovskaia, Nadejda A; Spasojevic, Marko J; Sosinski, Enio; Thornton, Peter E; Valladares, Fernando; van Bodegom, Peter M; Williams, Mathew; Wirth, Christian; Reich, Peter B
2017-12-19
Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration-specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen ([Formula: see text]) and phosphorus ([Formula: see text]), we characterize how traits vary within and among over 50,000 [Formula: see text]-km cells across the entire vegetated land surface. We do this in several ways-without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.
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A Coupled fcGCM-GCE Modeling System: A 3D Cloud Resolving Model and a Regional Scale Model
NASA Technical Reports Server (NTRS)
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 sets (or cloud library) stored at Goddard.
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Dell’Acqua, F.; Gamba, P.; Jaiswal, K.
2012-01-01
This paper discusses spatial aspects of the global exposure dataset and mapping needs for earthquake risk assessment. We discuss this in the context of development of a Global Exposure Database for the Global Earthquake Model (GED4GEM), which requires compilation of a multi-scale inventory of assets at risk, for example, buildings, populations, and economic exposure. After defining the relevant spatial and geographic scales of interest, different procedures are proposed to disaggregate coarse-resolution data, to map them, and if necessary to infer missing data by using proxies. We discuss the advantages and limitations of these methodologies and detail the potentials of utilizing remote-sensing data. The latter is used especially to homogenize an existing coarser dataset and, where possible, replace it with detailed information extracted from remote sensing using the built-up indicators for different environments. Present research shows that the spatial aspects of earthquake risk computation are tightly connected with the availability of datasets of the resolution necessary for producing sufficiently detailed exposure. The global exposure database designed by the GED4GEM project is able to manage datasets and queries of multiple spatial scales.
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Graphics Processing Unit (GPU) Acceleration of the Goddard Earth Observing System Atmospheric Model
NASA Technical Reports Server (NTRS)
Putnam, Williama
2011-01-01
The Goddard Earth Observing System 5 (GEOS-5) is the atmospheric model used by the Global Modeling and Assimilation Office (GMAO) for a variety of applications, from long-term climate prediction at relatively coarse resolution, to data assimilation and numerical weather prediction, to very high-resolution cloud-resolving simulations. GEOS-5 is being ported to a graphics processing unit (GPU) cluster at the NASA Center for Climate Simulation (NCCS). By utilizing GPU co-processor technology, we expect to increase the throughput of GEOS-5 by at least an order of magnitude, and accelerate the process of scientific exploration across all scales of global modeling, including: The large-scale, high-end application of non-hydrostatic, global, cloud-resolving modeling at 10- to I-kilometer (km) global resolutions Intermediate-resolution seasonal climate and weather prediction at 50- to 25-km on small clusters of GPUs Long-range, coarse-resolution climate modeling, enabled on a small box of GPUs for the individual researcher After being ported to the GPU cluster, the primary physics components and the dynamical core of GEOS-5 have demonstrated a potential speedup of 15-40 times over conventional processor cores. Performance improvements of this magnitude reduce the required scalability of 1-km, global, cloud-resolving models from an unfathomable 6 million cores to an attainable 200,000 GPU-enabled cores.
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NASA Astrophysics Data System (ADS)
Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.
2015-12-01
Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we contend that creating believable soil carbon predictions requires a robust, transparent, and community-available benchmarking framework. I will present an ILAMB evaluation of several of the above-mentioned approaches in ACME, and attempt to motivate community adoption of this evaluation approach.
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Emergence of universal scaling in financial markets from mean-field dynamics
NASA Astrophysics Data System (ADS)
Vikram, S. V.; Sinha, Sitabhra
2011-01-01
Collective phenomena with universal properties have been observed in many complex systems with a large number of components. Here we present a microscopic model of the emergence of scaling behavior in such systems, where the interaction dynamics between individual components is mediated by a global variable making the mean-field description exact. Using the example of financial markets, we show that asset price can be such a global variable with the critical role of coordinating the actions of agents who are otherwise independent. The resulting model accurately reproduces empirical properties such as the universal scaling of the price fluctuation and volume distributions, long-range correlations in volatility, and multiscaling.
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NASA Technical Reports Server (NTRS)
Han, Qingyuan; Rossow, William B.; Chou, Joyce; Welch, Ronald M.
1997-01-01
Cloud microphysical parameterizations have attracted a great deal of attention in recent years due to their effect on cloud radiative properties and cloud-related hydrological processes in large-scale models. The parameterization of cirrus particle size has been demonstrated as an indispensable component in the climate feedback analysis. Therefore, global-scale, long-term observations of cirrus particle sizes are required both as a basis of and as a validation of parameterizations for climate models. While there is a global scale, long-term survey of water cloud droplet sizes (Han et al.), there is no comparable study for cirrus ice crystals. This study is an effort to supply such a data set.
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NASA Astrophysics Data System (ADS)
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.
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The length of the world's glaciers - a new approach for the global calculation of center lines
NASA Astrophysics Data System (ADS)
Machguth, H.; Huss, M.
2014-09-01
Glacier length is an important measure of glacier geometry. Nevertheless, global glacier inventories are mostly lacking length data. Only recently semi-automated approaches to measure glacier length have been developed and applied regionally. Here we present a first global assessment of glacier length using an automated method that relies on glacier surface slope, distance to the glacier margins and a set of trade-off functions. The method is developed for East Greenland, evaluated for East Greenland as well as for Alaska and eventually applied to all ~ 200 000 glaciers around the globe. The evaluation highlights accurately calculated glacier length where digital elevation model (DEM) quality is high (East Greenland) and limited accuracy on low-quality DEMs (parts of Alaska). Measured length of very small glaciers is subject to a certain level of ambiguity. The global calculation shows that only about 1.5% of all glaciers are longer than 10 km, with Bering Glacier (Alaska/Canada) being the longest glacier in the world at a length of 196 km. Based on the output of our algorithm we derive global and regional area-length scaling laws. Differences among regional scaling parameters appear to be related to characteristics of topography and glacier mass balance. The present study adds glacier length as a key parameter to global glacier inventories. Global and regional scaling laws might prove beneficial in conceptual glacier models.
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Effects of climate variability on global scale flood risk
NASA Astrophysics Data System (ADS)
Ward, P.; Dettinger, M. D.; Kummu, M.; Jongman, B.; Sperna Weiland, F.; Winsemius, H.
2013-12-01
In this contribution we demonstrate the influence of climate variability on flood risk. Globally, flooding is one of the worst natural hazards in terms of economic damages; Munich Re estimates global losses in the last decade to be in excess of $240 billion. As a result, scientifically sound estimates of flood risk at the largest scales are increasingly needed by industry (including multinational companies and the insurance industry) and policy communities. Several assessments of global scale flood risk under current and conditions have recently become available, and this year has seen the first studies assessing how flood risk may change in the future due to global change. However, the influence of climate variability on flood risk has as yet hardly been studied, despite the fact that: (a) in other fields (drought, hurricane damage, food production) this variability is as important for policy and practice as long term change; and (b) climate variability has a strong influence in peak riverflows around the world. To address this issue, this contribution illustrates the influence of ENSO-driven climate variability on flood risk, at both the globally aggregated scale and the scale of countries and large river basins. Although it exerts significant and widespread influences on flood peak discharges in many parts of the world, we show that ENSO does not have a statistically significant influence on flood risk once aggregated to global totals. At the scale of individual countries, though, strong relationships exist over large parts of the Earth's surface. For example, we find particularly strong anomalies of flood risk in El Niño or La Niña years (compared to all years) in southern Africa, parts of western Africa, Australia, parts of Central Eurasia (especially for El Niño), the western USA (especially for La Niña), and parts of South America. These findings have large implications for both decadal climate-risk projections and long-term future climate change 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.
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A Prominence Puzzle Explained?
NASA Astrophysics Data System (ADS)
Yeates, A. R.; Mackay, D. H.; van Ballegooijen, A. A.
2009-02-01
Long-standing observations reveal a global organisation of the magnetic field direction in solar prominences (aka filaments), large clouds of cool dense plasma suspended in the Sun's hot corona. However, theorists have thus far been unable to explain the origin of this hemispheric pattern. In particular, simple shearing by large-scale surface motions would appear to lead to the wrong magnetic field direction. To explain the observations, we have developed a new model of the global magnetic field evolution in the solar corona over six months. For the first time our model can follow the build-up of magnetic helicity and shear on a global scale, driven by flux emergence and surface motions. The model is successful in predicting the correct magnetic field direction in the vast majority of prominences tested, and has enabled us to determine the key physical mechanisms behind the mysterious hemispheric pattern.
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Spatially-explicit models of global tree density.
Glick, Henry B; Bettigole, Charlie; Maynard, Daniel S; Covey, Kristofer R; Smith, Jeffrey R; Crowther, Thomas W
2016-08-16
Remote sensing and geographic analysis of woody vegetation provide means of evaluating the distribution of natural resources, patterns of biodiversity and ecosystem structure, and socio-economic drivers of resource utilization. While these methods bring geographic datasets with global coverage into our day-to-day analytic spheres, many of the studies that rely on these strategies do not capitalize on the extensive collection of existing field data. We present the methods and maps associated with the first spatially-explicit models of global tree density, which relied on over 420,000 forest inventory field plots from around the world. This research is the result of a collaborative effort engaging over 20 scientists and institutions, and capitalizes on an array of analytical strategies. Our spatial data products offer precise estimates of the number of trees at global and biome scales, but should not be used for local-level estimation. At larger scales, these datasets can contribute valuable insight into resource management, ecological modelling efforts, and the quantification of ecosystem services.
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NASA Astrophysics Data System (ADS)
Fujii, Yoshiaki
2011-04-01
This study suggests that the cause of the stagnation in global warming in the mid 20th century was the atmospheric nuclear explosions detonated between 1945 and 1980. The estimated GST drop due to fine dust from the actual atmospheric nuclear explosions based on the published simulation results by other researchers (a single column model and Atmosphere-Ocean General Circulation Model) has served to explain the stagnation in global warming. Atmospheric nuclear explosions can be regarded as full-scale in situ tests for nuclear winter. The non-negligible amount of GST drop from the actual atmospheric explosions suggests that nuclear winter is not just a theory but has actually occurred, albeit on a small scale. The accuracy of the simulations of GST by IPCC would also be improved significantly by introducing the influence of fine dust from the actual atmospheric nuclear explosions into their climate models; thus, global warming behavior could be more accurately predicted.
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IS THE SMALL-SCALE MAGNETIC FIELD CORRELATED WITH THE DYNAMO CYCLE?
DOE Office of Scientific and Technical Information (OSTI.GOV)
Karak, Bidya Binay; Brandenburg, Axel, E-mail: bbkarak@nordita.org
2016-01-01
The small-scale magnetic field is ubiquitous at the solar surface—even at high latitudes. From observations we know that this field is uncorrelated (or perhaps even weakly anticorrelated) with the global sunspot cycle. Our aim is to explore the origin, and particularly the cycle dependence, of such a phenomenon using three-dimensional dynamo simulations. We adopt a simple model of a turbulent dynamo in a shearing box driven by helically forced turbulence. Depending on the dynamo parameters, large-scale (global) and small-scale (local) dynamos can be excited independently in this model. Based on simulations in different parameter regimes, we find that, when onlymore » the large-scale dynamo is operating in the system, the small-scale magnetic field generated through shredding and tangling of the large-scale magnetic field is positively correlated with the global magnetic cycle. However, when both dynamos are operating, the small-scale field is produced from both the small-scale dynamo and the tangling of the large-scale field. In this situation, when the large-scale field is weaker than the equipartition value of the turbulence, the small-scale field is almost uncorrelated with the large-scale magnetic cycle. On the other hand, when the large-scale field is stronger than the equipartition value, we observe an anticorrelation between the small-scale field and the large-scale magnetic cycle. This anticorrelation can be interpreted as a suppression of the small-scale dynamo. Based on our studies we conclude that the observed small-scale magnetic field in the Sun is generated by the combined mechanisms of a small-scale dynamo and tangling of the large-scale field.« less
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NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2007-01-01
Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a superparameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (2ICE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generatio11 regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).
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NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2006-01-01
Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (21CE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generation regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).
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USDA-ARS?s Scientific Manuscript database
Through the characterization of a metapopulation cattle disease model on a directed network having source, transit, and sink nodes, we derive two global epidemic invasion thresholds. The first threshold defines the conditions necessary for an epidemic to successfully spread at the global scale. The ...
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Rupert Seidl; Thomas A. Spies; Werner Rammer; E. Ashley Steel; Robert J. Pabst; Keith. Olsen
2012-01-01
Forest ecosystems are the most important terrestrial carbon (C) storage globally, and presently mitigate anthropogenic climate change by acting as a large and persistent sink for atmospheric CO2. Yet, forest C density varies greatly in space, both globally and at stand and landscape levels. Understanding the multi-scale drivers of this variation...
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The United States Environmental Protection Agency (USEPA) and National Oceanic and Atmospheric Administration (NOAA) participate in a multi-agency examination of the effects of climate change through the U.S. Climate Change Science Program (CCSP, 2003). The EPA Global Change Rese...
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A Canonical Response in Rainfall Characteristics to Global Warming: Projections by IPCC CMIP5 Models
NASA Technical Reports Server (NTRS)
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.
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The Global Tsunami Model (GTM)
NASA Astrophysics Data System (ADS)
Thio, H. K.; Løvholt, F.; Harbitz, C. B.; Polet, J.; Lorito, S.; Basili, R.; Volpe, M.; Romano, F.; Selva, J.; Piatanesi, A.; Davies, G.; Griffin, J.; Baptista, M. A.; Omira, R.; Babeyko, A. Y.; Power, W. L.; Salgado Gálvez, M.; Behrens, J.; Yalciner, A. C.; Kanoglu, U.; Pekcan, O.; Ross, S.; Parsons, T.; LeVeque, R. J.; Gonzalez, F. I.; Paris, R.; Shäfer, A.; Canals, M.; Fraser, S. A.; Wei, Y.; Weiss, R.; Zaniboni, F.; Papadopoulos, G. A.; Didenkulova, I.; Necmioglu, O.; Suppasri, A.; Lynett, P. J.; Mokhtari, M.; Sørensen, M.; von Hillebrandt-Andrade, C.; Aguirre Ayerbe, I.; Aniel-Quiroga, Í.; Guillas, S.; Macias, J.
2016-12-01
The large tsunami disasters of the last two decades have highlighted the need for a thorough understanding of the risk posed by relatively infrequent but 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.
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The Global Tsunami Model (GTM)
NASA Astrophysics Data System (ADS)
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.
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The Global Tsunami Model (GTM)
NASA Astrophysics Data System (ADS)
Løvholt, Finn
2017-04-01
The large tsunami disasters of the last two decades have highlighted the need for a thorough understanding of the risk posed by relatively infrequent but 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.
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NASA Astrophysics Data System (ADS)
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.
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Weak Hydrological Sensitivity to Temperature Change over Land, Independent of Climate Forcing
NASA Technical Reports Server (NTRS)
Samset, B. H.; Myhre, G.; Forster, P. M.; Hodnebrog, O.; Andrews, T.; Boucher, O.; Faluvegi, G.; Flaeschner, D.; Kasoar, M.; Kharin, V.;
2018-01-01
We present the global and regional hydrological sensitivity (HS) to surface temperature changes, for perturbations to CO2, CH4, sulfate and black carbon concentrations, and solar irradiance. Based on results from ten climate models, we show how modeled global mean precipitation increases by 2-3% per kelvin of global mean surface warming, independent of driver, when the effects of rapid adjustments are removed. Previously reported differences in response between drivers are therefore mainly ascribable to rapid atmospheric adjustment processes. All models show a sharp contrast in behavior over land and over ocean, with a strong surface temperature-driven (slow) ocean HS of 3-5%/K, while the slow land HS is only 0-2%/K. Separating the response into convective and large-scale cloud processes, we find larger inter-model differences, in particular over land regions. Large-scale precipitation changes are most relevant at high latitudes, while the equatorial HS is dominated by convective precipitation changes. Black carbon stands out as the driver with the largest inter-model slow HS variability, and also the strongest contrast between a weak land and strong sea response. We identify a particular need for model investigations and observational constraints on convective precipitation in the Arctic, and large-scale precipitation around the Equator.
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1km Global Terrestrial Carbon Flux: Estimations and Evaluations
NASA Astrophysics Data System (ADS)
Murakami, K.; Sasai, T.; Kato, S.; Saito, M.; Matsunaga, T.; Hiraki, K.; Maksyutov, S. S.
2017-12-01
Estimating global scale of the terrestrial carbon flux change with high accuracy and high resolution is important to understand global environmental changes. Furthermore the estimations of the global spatiotemporal distribution may contribute to the political and social activities such as REDD+. In order to reveal the current state of terrestrial carbon fluxes covering all over the world and a decadal scale. The satellite-based diagnostic biosphere model is suitable for achieving this purpose owing to observing on the present global land surface condition uniformly at some time interval. In this study, we estimated the global terrestrial carbon fluxes with 1km grids by using the terrestrial biosphere model (BEAMS). And we evaluated our new carbon flux estimations on various spatial scales and showed the transition of forest carbon stocks in some regions. Because BEAMS required high resolution meteorological data and satellite data as input data, we made 1km interpolated data using a kriging method. The data used in this study were JRA-55, GPCP, GOSAT L4B atmospheric CO2 data as meteorological data, and MODIS land product as land surface satellite data. Interpolating process was performed on the meteorological data because of insufficient resolution, but not on MODIS data. We evaluated our new carbon flux estimations using the flux tower measurement (FLUXNET2015 Datasets) in a point scale. We used 166 sites data for evaluating our model results. These flux sites are classified following vegetation type (DBF, EBF, ENF, mixed forests, grass lands, croplands, shrub lands, Savannas, wetlands). In global scale, the BEAMS estimations was underestimated compared to the flux measurements in the case of carbon uptake and release. The monthly variations of NEP showed relatively high correlations in DBF and mixed forests, but the correlation coefficients of EBF, ENF, and grass lands were less than 0.5. In the meteorological factors, air temperature and solar radiation showed very high correlations, and slight variations were showed in precipitation data. LAI data that was another large driving factor of terrestrial carbon cycle was not included in FLUXNET2015 datasets and it could not be evaluated.
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A Power Efficient Exaflop Computer Design for Global Cloud System Resolving Climate Models.
NASA Astrophysics Data System (ADS)
Wehner, M. F.; Oliker, L.; Shalf, J.
2008-12-01
Exascale computers would allow routine ensemble modeling of the global climate system at the cloud system resolving scale. Power and cost requirements of traditional architecture systems are likely to delay such capability for many years. We present an alternative route to the exascale using embedded processor technology to design a system optimized for ultra high resolution climate modeling. These power efficient processors, used in consumer electronic devices such as mobile phones, portable music players, cameras, etc., can be tailored to the specific needs of scientific computing. We project that a system capable of integrating a kilometer scale climate model a thousand times faster than real time could be designed and built in a five year time scale for US$75M with a power consumption of 3MW. This is cheaper, more power efficient and sooner than any other existing technology.
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NASA Technical Reports Server (NTRS)
Mayr, Hans G.; Mengel, J. G.; Chan, K. L.; Huang, F. T.
2010-01-01
As Lindzen (1981) had shown, small-scale gravity waves (GW) produce the observed reversals of the zonal-mean circulation and temperature variations in the upper mesosphere. The waves also play a major role in modulating and amplifying the diurnal tides (DT) (e.g., Waltersheid, 1981; Fritts and Vincent, 1987; Fritts, 1995a). We summarize here the modeling studies with the mechanistic numerical spectral model (NSM) with Doppler spread parameterization for GW (Hines, 1997a, b), which describes in the middle atmosphere: (a) migrating and non-migrating DT, (b) planetary waves (PW), and (c) global-scale inertio gravity waves. Numerical experiments are discussed that illuminate the influence of GW filtering and nonlinear interactions between DT, PW, and zonal mean variations. Keywords: Theoretical modeling, Middle atmosphere dynamics, Gravity wave interactions, Migrating and non-migrating tides, Planetary waves, Global-scale inertio gravity waves.
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Can global hydrological models reproduce large scale river flood regimes?
NASA Astrophysics Data System (ADS)
Eisner, Stephanie; Flörke, Martina
2013-04-01
River flooding remains one of the most severe natural hazards. On the one hand, major flood events pose a serious threat to human well-being, causing deaths and considerable economic damage. On the other hand, the periodic occurrence of flood pulses is crucial to maintain the functioning of riverine floodplains and wetlands, and to preserve the ecosystem services the latter provide. In many regions, river floods reveal a distinct seasonality, i.e. they occur at a particular time during the year. This seasonality is related to regionally dominant flood generating processes which can be expressed in river flood types. While in data-rich regions (esp. Europe and North America) the analysis of flood regimes can be based on observed river discharge time series, this data is sparse or lacking in many other regions of the world. This gap of knowledge can be filled by global modeling approaches. However, to date most global modeling studies have focused on mean annual or monthly water availability and their change over time while simulating discharge extremes, both floods and droughts, still remains a challenge for large scale hydrological models. This study will explore the ability of the global hydrological model WaterGAP3 to simulate the large scale patterns of river flood regimes, represented by seasonal pattern and the dominant flood type. WaterGAP3 simulates the global terrestrial water balance on a 5 arc minute spatial grid (excluding Greenland and Antarctica) at a daily time step. The model accounts for human interference on river flow, i.e. water abstraction for various purposes, e.g. irrigation, and flow regulation by large dams and reservoirs. Our analysis will provide insight in the general ability of global hydrological models to reproduce river flood regimes and thus will promote the creation of a global map of river flood regimes to provide a spatially inclusive and comprehensive picture. Understanding present-day flood regimes can support both flood risk analysis and the assessment of potential regional impacts of climate change on river flooding.
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NASA Astrophysics Data System (ADS)
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.
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High potential for weathering and climate effects of non-vascular vegetation in the Late Ordovician
NASA Astrophysics Data System (ADS)
Porada, Philipp; Lenton, Tim; Pohl, Alexandre; Weber, Bettina; Mander, Luke; Donnadieu, Yannick; Beer, Christian; Pöschl, Ulrich; Kleidon, Axel
2017-04-01
Early non-vascular vegetation in the Late Ordovician may have strongly increased chemical weathering rates of surface rocks at the global scale. This could have led to a drawdown of atmospheric CO2 and, consequently, a decrease in global temperature and an interval of glaciations. Under current climatic conditions, usually field or laboratory experiments are used to quantify enhancement of chemical weathering rates by non-vascular vegetation. However, these experiments are constrained to a small spatial scale and a limited number of species. This complicates the extrapolation to the global scale, even more so for the geological past, where physiological properties of non-vascular vegetation may have differed from current species. Here we present a spatially explicit modelling approach to simulate large-scale chemical weathering by non-vascular vegetation in the Late Ordovician. For this purpose, we use a process-based model of lichens and bryophytes, since these organisms are probably the closest living analogue to Late Ordovician vegetation. The model explicitly represents multiple physiological strategies, which enables the simulated vegetation to adapt to Ordovician climatic conditions. We estimate productivity of Ordovician vegetation with the model, and relate it to chemical weathering by assuming that the organisms dissolve rocks to extract phosphorus for the production of new biomass. Thereby we account for limits on weathering due to reduced supply of unweathered rock material in shallow regions, as well as decreased transport capacity of runoff for dissolved weathered material in dry areas. We simulate a potential global weathering flux of 2.8 km3 (rock) per year, which we define as volume of primary minerals affected by chemical transformation. Our estimate is around 3 times larger than today's global chemical weathering flux. Furthermore, chemical weathering rates simulated by our model are highly sensitive to atmospheric CO2 concentration, which implies a strong negative feedback between weathering by non-vascular vegetation and Ordovician climate.
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Assessing Impacts of Climate Change on Food Security Worldwide
NASA Technical Reports Server (NTRS)
Rosenzweig, Cynthia E.; Antle, John; Elliott, Joshua
2015-01-01
The combination of a warming Earth and an increasing population will likely strain the world's food systems in the coming decades. Experts involved with the Agricultural Model Intercomparison and Improvement Project (AgMIP) focus on quantifying the changes through time. AgMIP, a program begun in 2010, involves about 800 climate scientists, economists, nutritionists, information technology specialists, and crop and livestock experts. In mid-September 2015, the Aspen Global Change Institute convened an AgMIP workshop to draft plans and protocols for assessing global- and regional-scale modeling of crops, livestock, economics, and nutrition across major agricultural regions worldwide. The goal of this Coordinated Global and Regional Integrated Assessments (CGRA) project is to characterize climate effects on large- and small-scale farming systems.
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NASA Astrophysics Data System (ADS)
Gabrielse, C.; Nishimura, T.; Lyons, L. R.; Gallardo-Lacourt, B.; Deng, Y.; McWilliams, K. A.; Ruohoniemi, J. M.
2017-12-01
NASA's Heliophysics Decadal Survey put forth several imperative, Key Science Goals. The second goal communicates the urgent need to "Determine the dynamics and coupling of Earth's magnetosphere, ionosphere, and atmosphere and their response to solar and terrestrial inputs...over a range of spatial and temporal scales." Sun-Earth connections (called Space Weather) have strong societal impacts because extreme events can disturb radio communications and satellite operations. The field's current modeling capabilities of such Space Weather phenomena include large-scale, global responses of the Earth's upper atmosphere to various inputs from the Sun, but the meso-scale ( 50-500 km) structures that are much more dynamic and powerful in the coupled system remain uncharacterized. Their influences are thus far poorly understood. We aim to quantify such structures, particularly auroral flows and streamers, in order to create an empirical model of their size, location, speed, and orientation based on activity level (AL index), season, solar cycle (F10.7), interplanetary magnetic field (IMF) inputs, etc. We present a statistical study of meso-scale flow channels in the nightside auroral oval and polar cap using SuperDARN. These results are used to inform global models such as the Global Ionosphere Thermosphere Model (GITM) in order to evaluate the role of meso-scale disturbances on the fully coupled magnetosphere-ionosphere-thermosphere system. Measuring the ionospheric footpoint of magnetospheric fast flows, our analysis technique from the ground also provides a 2D picture of flows and their characteristics during different activity levels that spacecraft alone cannot.
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NASA Astrophysics Data System (ADS)
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 comparing upper tropospheric budgets of NOx from aircraft and lightning sources in the modeling domain.
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NASA Astrophysics Data System (ADS)
Carozza, D. A.; Bianchi, D.; Galbraith, E. D.
2015-12-01
Environmental change and the exploitation of marine resources have had profound impacts on marine communities, with potential implications for ocean biogeochemistry and food security. In order to study such global-scale problems, it is helpful to have computationally efficient numerical models that predict the first-order features of fish biomass production as a function of the environment, based on empirical and mechanistic understandings of marine ecosystems. Here we describe the ecological module of the BiOeconomic mArine Trophic Size-spectrum (BOATS) model, which takes an Earth-system approach to modeling fish biomass at the global scale. The ecological model is designed to be used on an Earth System model grid, and determines size spectra of fish biomass by explicitly resolving life history as a function of local temperature and net primary production. Biomass production is limited by the availability of photosynthetic energy to upper trophic levels, following empirical trophic efficiency scalings, and by well-established empirical temperature-dependent growth rates. Natural mortality is calculated using an empirical size-based relationship, while reproduction and recruitment depend on both the food availability to larvae from net primary production and the production of eggs by mature adult fish. We describe predicted biomass spectra and compare them to observations, and conduct a sensitivity study to determine how the change as a function of net primary production and temperature. The model relies on a limited number of parameters compared to similar modeling efforts, while retaining realistic representations of biological and ecological processes, and is computationally efficient, allowing extensive parameter-space analyses even when implemented globally. As such, it enables the exploration of the linkages between ocean biogeochemistry, climate, and upper trophic levels at the global scale, as well as a representation of fish biomass for idealized studies of fisheries.
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NASA Astrophysics Data System (ADS)
Carozza, David Anthony; Bianchi, Daniele; Galbraith, Eric Douglas
2016-04-01
Environmental change and the exploitation of marine resources have had profound impacts on marine communities, with potential implications for ocean biogeochemistry and food security. In order to study such global-scale problems, it is helpful to have computationally efficient numerical models that predict the first-order features of fish biomass production as a function of the environment, based on empirical and mechanistic understandings of marine ecosystems. Here we describe the ecological module of the BiOeconomic mArine Trophic Size-spectrum (BOATS) model, which takes an Earth-system approach to modelling fish biomass at the global scale. The ecological model is designed to be used on an Earth-system model grid, and determines size spectra of fish biomass by explicitly resolving life history as a function of local temperature and net primary production. Biomass production is limited by the availability of photosynthetic energy to upper trophic levels, following empirical trophic efficiency scalings, and by well-established empirical temperature-dependent growth rates. Natural mortality is calculated using an empirical size-based relationship, while reproduction and recruitment depend on both the food availability to larvae from net primary production and the production of eggs by mature adult fish. We describe predicted biomass spectra and compare them to observations, and conduct a sensitivity study to determine how they change as a function of net primary production and temperature. The model relies on a limited number of parameters compared to similar modelling efforts, while retaining reasonably realistic representations of biological and ecological processes, and is computationally efficient, allowing extensive parameter-space analyses even when implemented globally. As such, it enables the exploration of the linkages between ocean biogeochemistry, climate, and upper trophic levels at the global scale, as well as a representation of fish biomass for idealized studies of fisheries.
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Global high-resolution simulations of tropospheric nitrogen dioxide using CHASER V4.0
NASA Astrophysics Data System (ADS)
Sekiya, Takashi; Miyazaki, Kazuyuki; Ogochi, Koji; Sudo, Kengo; Takigawa, Masayuki
2018-03-01
We evaluate global tropospheric nitrogen dioxide (NO2) simulations using the CHASER V4.0 global chemical transport model (CTM) at horizontal resolutions of 0.56, 1.1, and 2.8°. Model evaluation was conducted using satellite tropospheric NO2 retrievals from the Ozone Monitoring Instrument (OMI) and the Global Ozone Monitoring Experiment-2 (GOME-2) and aircraft observations from the 2014 Front Range Air Pollution and Photochemistry Experiment (FRAPPÉ). Agreement against satellite retrievals improved greatly at 1.1 and 0.56° resolutions (compared to 2.8° resolution) over polluted and biomass burning regions. The 1.1° simulation generally captured the regional distribution of the tropospheric NO2 column well, whereas 0.56° resolution was necessary to improve the model performance over areas with strong local sources, with mean bias reductions of 67 % over Beijing and 73 % over San Francisco in summer. Validation using aircraft observations indicated that high-resolution simulations reduced negative NO2 biases below 700 hPa over the Denver metropolitan area. These improvements in high-resolution simulations were attributable to (1) closer spatial representativeness between simulations and observations and (2) better representation of large-scale concentration fields (i.e., at 2.8°) through the consideration of small-scale processes. Model evaluations conducted at 0.5 and 2.8° bin grids indicated that the contributions of both these processes were comparable over most polluted regions, whereas the latter effect (2) made a larger contribution over eastern China and biomass burning areas. The evaluations presented in this paper demonstrate the potential of using a high-resolution global CTM for studying megacity-scale air pollutants across the entire globe, potentially also contributing to global satellite retrievals and chemical data assimilation.
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A climatology of gravity wave parameters based on satellite limb soundings
NASA Astrophysics Data System (ADS)
Ern, Manfred; Trinh, Quang Thai; Preusse, Peter; Riese, Martin
2017-04-01
Gravity waves are one of the main drivers of atmospheric dynamics. The resolution of most global circulation models (GCMs) and chemistry climate models (CCMs), however, is too coarse to properly resolve the small scales of gravity waves. Horizontal scales of gravity waves are in the range of tens to a few thousand kilometers. Gravity wave source processes involve even smaller scales. Therefore GCMs/CCMs usually parametrize the effect of gravity waves on the global circulation. These parametrizations are very simplified, and comparisons with global observations of gravity waves are needed for an improvement of parametrizations and an alleviation of model biases. In our study, we present a global data set of gravity wave distributions observed in the stratosphere and the mesosphere by the infrared limb sounding satellite instruments High Resolution Dynamics Limb Sounder (HIRDLS) and Sounding of the Atmosphere using Broadband Emission Radiometry (SABER). We provide various gravity wave parameters (for example, gravity variances, potential energies and absolute momentum fluxes). This comprehensive climatological data set can serve for comparison with other instruments (ground based, airborne, or other satellite instruments), as well as for comparison with gravity wave distributions, both resolved and parametrized, in GCMs and CCMs. The purpose of providing various different parameters is to make our data set useful for a large number of potential users and to overcome limitations of other observation techniques, or of models, that may be able to provide only one of those parameters. We present a climatology of typical average global distributions and of zonal averages, as well as their natural range of variations. In addition, we discuss seasonal variations of the global distribution of gravity waves, as well as limitations of our method of deriving gravity wave parameters from satellite data.
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NASA Astrophysics Data System (ADS)
Gressent, A.; Muhle, J.; Rigby, M. L.; Lunt, M. F.; Ganesan, A.; Prinn, R. G.; Krummel, P. B.; Fraser, P. J.; Steele, P.; Weiss, R. F.; Harth, C. M.; O'Doherty, S.; Young, D.; Park, S.; Li, S.; Yao, B.; Reimann, S.; Vollmer, M. K.; Maione, M.; Arduini, I.; Lunder, C. R.
2016-12-01
Sulfuryl fluoride (SO2F2) is used increasingly as a fumigant to replace methyl bromide (CH3Br), which was regulated under the Montreal Protocol (1986). Mühle et al., J. Geophys. Res., 2009) showed that SO2F2 had been accumulating in the global atmosphere with a growth rate of 5±1% per year from 1978 to 2007. They also determined, using the 2D AGAGE box model, that SO2F2 has a total atmospheric lifetime of 36±11 years mainly driven by the oceanic uptake. In addition, the global warming potential of SO2F2 has been estimated to be ≈4780 for a 100-year time horizon (Papadimitriou et al., J. Phys. Chem., 2008), which is similar to the CFC-11 (CCl3F) GWP. Thus it is a potent greenhouse gas and its emissions are expected to continue to increase in the future. Here we report the first estimations of the SO2F2 emissions and its ocean sink from January 2006 to the end of 2015 on both the global scale using a 3D Eulerian chemical transport model (MOZART-4) solving a Main Chain Monte Carlo (MCMC) inversion, and on the regional scale using a 3D Lagrangian dispersion model (NAME) via the reversible-jump trans-dimensional MCMC approach (Lunt et al., Geosci. Model Dev., 2016). The mole fractions calculated on the global scale are used as boundary conditions for emission calculations over the NAME regions in North America, Europe, East Asia and Australia. For this 10-year inversion we use observations from the AGAGE (Advanced Global Atmospheric Gases Experiment) starting with six stations in 2006, which are La Jolla (California), Mace Head (Ireland), Cape Grim (Australia), Ragged Point (Barbados), Trinidad Head (California) and Cape Matatula (Samoa). We then add observations from Gosan (South Korea) in 2007, Jungfraujoch (Switzerland) in 2008, Shandiangzi (China) and Ny-Alesund (Norway) in 2010, and Monte Cimone (Italy) in 2011, reducing the uncertainty associated with the regions located close to these stations. Results are compared to (i) the total global SO2F2 emissions estimated by the 2D AGAGE box model (Mühle et al, in prep) and (ii) the global industrial estimates. This work provides a unique quantitative understanding of the SO2F2 industrial emissions and its oceanic and photochemical sinks over the last decade.
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Satellite-Enhanced Dynamical Downscaling of Extreme Events
NASA Astrophysics Data System (ADS)
Nunes, A.
2015-12-01
Severe weather events can be the triggers of environmental disasters in regions particularly susceptible to changes in hydrometeorological conditions. In that regard, the reconstruction of past extreme weather events can help in the assessment of vulnerability and risk mitigation actions. Using novel modeling approaches, dynamical downscaling of long-term integrations from global circulation models can be useful for risk analysis, providing more accurate climate information at regional scales. Originally developed at the National Centers for Environmental Prediction (NCEP), the Regional Spectral Model (RSM) is being used in the dynamical downscaling of global reanalysis, within the South American Hydroclimate Reconstruction Project. Here, RSM combines scale-selective bias correction with assimilation of satellite-based precipitation estimates to downscale extreme weather occurrences. Scale-selective bias correction is a method employed in the downscaling, similar to the spectral nudging technique, in which the downscaled solution develops in agreement with its coarse boundaries. Precipitation assimilation acts on modeled deep-convection, drives the land-surface variables, and therefore the hydrological cycle. During the downscaling of extreme events that took place in Brazil in recent years, RSM continuously assimilated NCEP Climate Prediction Center morphing technique precipitation rates. As a result, RSM performed better than its global (reanalysis) forcing, showing more consistent hydrometeorological fields compared with more sophisticated global reanalyses. Ultimately, RSM analyses might provide better-quality initial conditions for high-resolution numerical predictions in metropolitan areas, leading to more reliable short-term forecasting of severe local storms.
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Challenges in Modeling of the Global Atmosphere
NASA Astrophysics Data System (ADS)
Janjic, Zavisa; Djurdjevic, Vladimir; Vasic, Ratko; Black, Tom
2015-04-01
The massively parallel computer architectures require that some widely adopted modeling paradigms be reconsidered in order to utilize more productively the power of 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. However, the described scenario implies that the discretization used in the model is horizontally local. The spherical geometry further complicates the problem. Various grid topologies will be discussed and examples will be shown. 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 decent size. However, the polar filtering requires transpositions involving extra communications. The spectral transform method and the semi-implicit semi-Lagrangian schemes opened the way for a wide application of the spectral representation. With some variations, these techniques are used in most major centers. However, 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 a fast Fourier transform represents a significant 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 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.
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Hydrologic Derivatives for Modeling and Analysis—A new global high-resolution database
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.
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NASA Astrophysics Data System (ADS)
Blanc, Elisabeth; Le Pichon, Alexis; Ceranna, Lars; Pilger, Christoph; Charlton Perez, Andrew; Smets, Pieter
2016-04-01
The International Monitoring System (IMS) developed for the verification of the Comprehensive nuclear-Test-Ban Treaty (CTBT) provides a unique global description of atmospheric disturbances generating infrasound such as extreme events (e.g. meteors, volcanoes, earthquakes, and severe weather) or human activity (e.g. explosions and supersonic airplanes). The analysis of the detected signals, recorded at global scales and over near 15 years at some stations, demonstrates that large-scale atmospheric disturbances strongly affect infrasound propagation. Their time scales vary from several tens of minutes to hours and days. Their effects are in average well resolved by the current model predictions; however, accurate spatial and temporal description is lacking in both weather and climate models. This study reviews recent results using the infrasound technology to characterize these large scale disturbances, including (i) wind fluctuations induced by gravity waves generating infrasound partial reflections and modifications of the infrasound waveguide, (ii) convection from thunderstorms and mountain waves generating gravity waves, (iii) stratospheric warming events which yield wind inversions in the stratosphere, (iv)planetary waves which control the global atmospheric circulation. Improved knowledge of these disturbances and assimilation in future models is an important objective of the ARISE (Atmospheric dynamics Research InfraStructure in Europe) project. This is essential in the context of the future verification of the CTBT as enhanced atmospheric models are necessary to assess the IMS network performance in higher resolution, reduce source location errors, and improve characterization methods.
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Sea spray aerosols (SSAs) impact the particle mass concentration and gas-particle partitioning in coastal environments, with implications for human and ecosystem health. Model evaluations of SSA emissions have mainly focused on the global scale, but regional-scale evaluations are...
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Spatial modeling of agricultural land use change at global scale
NASA Astrophysics Data System (ADS)
Meiyappan, P.; Dalton, M.; O'Neill, B. C.; Jain, A. K.
2014-11-01
Long-term modeling of agricultural land use is central in global scale assessments of climate change, food security, biodiversity, and climate adaptation and mitigation policies. We present a global-scale dynamic land use allocation model and show that it can reproduce the broad spatial features of the past 100 years of evolution of cropland and pastureland patterns. The modeling approach integrates economic theory, observed land use history, and data on both socioeconomic and biophysical determinants of land use change, and estimates relationships using long-term historical data, thereby making it suitable for long-term projections. The underlying economic motivation is maximization of expected profits by hypothesized landowners within each grid cell. The model predicts fractional land use for cropland and pastureland within each grid cell based on socioeconomic and biophysical driving factors that change with time. The model explicitly incorporates the following key features: (1) land use competition, (2) spatial heterogeneity in the nature of driving factors across geographic regions, (3) spatial heterogeneity in the relative importance of driving factors and previous land use patterns in determining land use allocation, and (4) spatial and temporal autocorrelation in land use patterns. We show that land use allocation approaches based solely on previous land use history (but disregarding the impact of driving factors), or those accounting for both land use history and driving factors by mechanistically fitting models for the spatial processes of land use change do not reproduce well long-term historical land use patterns. With an example application to the terrestrial carbon cycle, we show that such inaccuracies in land use allocation can translate into significant implications for global environmental assessments. The modeling approach and its evaluation provide an example that can be useful to the land use, Integrated Assessment, and the Earth system modeling communities.
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A satellite and model based flood inundation climatology of Australia
NASA Astrophysics Data System (ADS)
Schumann, G.; Andreadis, K.; Castillo, C. J.
2013-12-01
To date there is no coherent and consistent database on observed or simulated flood event inundation and magnitude at large scales (continental to global). The only compiled data set showing a consistent history of flood inundation area and extent at a near global scale is provided by the MODIS-based Dartmouth Flood Observatory. However, MODIS satellite imagery is only available from 2000 and is hampered by a number of issues associated with flood mapping using optical images (e.g. classification algorithms, cloud cover, vegetation). Here, we present for the first time a proof-of-concept study in which we employ a computationally efficient 2-D hydrodynamic model (LISFLOOD-FP) complemented with a sub-grid channel formulation to generate a complete flood inundation climatology of the past 40 years (1973-2012) for the entire Australian continent. The model was built completely from freely available SRTM-derived data, including channel widths, bank heights and floodplain topography, which was corrected for vegetation canopy height using a global ICESat canopy dataset. Channel hydraulics were resolved using actual channel data and bathymetry was estimated within the model using hydraulic geometry. On the floodplain, the model simulated the flow paths and inundation variables at a 1 km resolution. The developed model was run over a period of 40 years and a floodplain inundation climatology was generated and compared to satellite flood event observations. Our proof-of-concept study demonstrates that this type of model can reliably simulate past flood events with reasonable accuracies both in time and space. The Australian model was forced with both observed flow climatology and VIC-simulated flows in order to assess the feasibility of a model-based flood inundation climatology at the global scale.
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Sources of uncertainty in hydrological climate impact assessment: a cross-scale study
NASA Astrophysics Data System (ADS)
Hattermann, F. F.; Vetter, T.; Breuer, L.; Su, Buda; Daggupati, P.; Donnelly, C.; Fekete, B.; Flörke, F.; Gosling, S. N.; Hoffmann, P.; Liersch, S.; Masaki, Y.; Motovilov, Y.; Müller, C.; Samaniego, L.; Stacke, T.; Wada, Y.; Yang, T.; Krysnaova, V.
2018-01-01
Climate change impacts on water availability and hydrological extremes are major concerns as regards the Sustainable Development Goals. Impacts on hydrology are normally investigated as part of a modelling chain, in which climate projections from multiple climate models are used as inputs to multiple impact models, under different greenhouse gas emissions scenarios, which result in different amounts of global temperature rise. While the goal is generally to investigate the relevance of changes in climate for the water cycle, water resources or hydrological extremes, it is often the case that variations in other components of the model chain obscure the effect of climate scenario variation. This is particularly important when assessing the impacts of relatively lower magnitudes of global warming, such as those associated with the aspirational goals of the Paris Agreement. In our study, we use ANOVA (analyses of variance) to allocate and quantify the main sources of uncertainty in the hydrological impact modelling chain. In turn we determine the statistical significance of different sources of uncertainty. We achieve this by using a set of five climate models and up to 13 hydrological models, for nine large scale river basins across the globe, under four emissions scenarios. The impact variable we consider in our analysis is daily river discharge. We analyze overall water availability and flow regime, including seasonality, high flows and low flows. Scaling effects are investigated by separately looking at discharge generated by global and regional hydrological models respectively. Finally, we compare our results with other recently published studies. We find that small differences in global temperature rise associated with some emissions scenarios have mostly significant impacts on river discharge—however, climate model related uncertainty is so large that it obscures the sensitivity of the hydrological system.
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Friend or Foe? Urbanization and the Biosphere
NASA Astrophysics Data System (ADS)
Schneider, A.
2008-12-01
The environmental influence of urban areas is still often assumed to be negligible at global scales. Although local environmental conditions such as the urban heat island effect are well-documented, surprisingly little work has focused on cross-scale interactions, or the ways in which local urban processes cumulatively impact global changes. Given the rapid rates of rural-urban migration, economic development and urban spatial expansion, improved systems for measuring, monitoring and modeling the global environmental impacts of cities should receive far greater scientific attention. This presentation will summarize urban environmental issues and impacts at local, regional and global scales and introduce the fundamental concepts and tools needed to measure and respond to these problems. Newly available datasets for the distribution and intensity of urban land use will be introduced, demonstrating the importance of clearly defining 'urbanized' land for empirical studies at the global scale. The negative environmental impacts of urban development will be compared with the often over-looked "positives" of urban growth from a global environmental perspective. Progress in understanding and forecasting the global impacts of urban areas will require systematic global urban research designs that treat cities as urban systems, anthropogenic biomes and urban ecoregions. The challenges and opportunities of global environmental research on urban areas have important implications not only for current research but also for educating the next generation of earth system scientists.
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NASA Astrophysics Data System (ADS)
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.
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NASA Astrophysics Data System (ADS)
Li, Shan; Li, Laurent; Le Treut, Hervé
2016-04-01
In the 21st century, the estimated surface temperature warming projected by General Circulation Models (GCMs) is between 0.3 and 4.8 °C, depending on the scenario considered. GCMs exhibit a good representation of climate on a global scale, but they are not able to reproduce regional climate processes with the same level of accuracy. Society and policymakers need model projections to define climate change adaptation and mitigation policies on a global, regional and local scale. Climate downscaling is mostly conducted with a regional model nested into the outputs of a global model. This one-way nesting approach is generally used in the climate community without feedbacks from Regional Climate Models (RCMs) to GCMs. This lack of interaction between the two models may affect regional modes of variability, in particular those with a boundary conflict. The objective of this study is to evaluate a two-way nesting configuration that makes an interactive coupling between the RCM and the GCM, an approach against the traditional configuration of one-way nesting system. An additional aim of this work is to examine if the two-way nesting system can improve the RCM performance. The atmospheric component of the IPSL integrated climate model (LMDZ) is configured at both regional (LMDZ-regional) and global (LMDZ-global) scales. The two models have the same configuration for the dynamical framework and the physical forcings. The climatology values of sea surface temperature (SST) are prescribed for the two models. The stretched-grid of LMDZ-global is applied to a region defined by Europe, the Mediterranean, North Africa and Western North Atlantic. To ensure a good statistical significance of results, all simulations last at least 80 years. The nesting process of models is performed by a relaxation procedure of a time scale of 90 minutes. In the case of two-way nesting, the exchange between the two models is every two hours. The relaxation procedure induces a boundary conflict, particularly in the eastern boundary for temperature and geopotential height. A correlation analysis on the synoptic scale evaluates the relationship between the GCM and the RCM. The beginning of the simulations shows a great consistency of the two models. When dominant dynamics apply, RCM inherits most of the GCM signal with a consistent spatial structure. On the contrary, when the atmospheric circulation is weak, there are not that many effects transferred from the GCM to the RCM. When the RCM has its own dynamics, the boundary conflict is more pronounced. Winter season is chosen for the two-way nesting test due to the predominant role of the atmospheric dynamics in winter. The new approach of a two-way nesting system reduces boundary bias, having a influence in some cases in climate model projections. The effect of two-way nesting is enhanced when using a finer grid.
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Satellite-enhanced dynamical downscaling for the analysis of extreme events
NASA Astrophysics Data System (ADS)
Nunes, Ana M. B.
2016-09-01
The use of regional models in the downscaling of general circulation models provides a strategy to generate more detailed climate information. In that case, boundary-forcing techniques can be useful to maintain the large-scale features from the coarse-resolution global models in agreement with the inner modes of the higher-resolution regional models. Although those procedures might improve dynamics, downscaling via regional modeling still aims for better representation of physical processes. With the purpose of improving dynamics and physical processes in regional downscaling of global reanalysis, the Regional Spectral Model—originally developed at the National Centers for Environmental Prediction—employs a newly reformulated scale-selective bias correction, together with the 3-hourly assimilation of the satellite-based precipitation estimates constructed from the Climate Prediction Center morphing technique. The two-scheme technique for the dynamical downscaling of global reanalysis can be applied in analyses of environmental disasters and risk assessment, with hourly outputs, and resolution of about 25 km. Here the satellite-enhanced dynamical downscaling added value is demonstrated in simulations of the first reported hurricane in the western South Atlantic Ocean basin through comparisons with global reanalyses and satellite products available in ocean areas.
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Bringing the Global Scale to Education in Natural Resources Management
NASA Astrophysics Data System (ADS)
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.
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David E. Rupp,
2016-05-05
The 20th century climate for the Southeastern United States and surrounding areas as simulated by global climate models used in the Coupled Model Intercomparison Project Phase 5 (CMIP5) was evaluated. A suite of statistics that characterize various aspects of the regional climate was calculated from both model simulations and observation-based datasets. CMIP5 global climate models were ranked by their ability to reproduce the observed climate. Differences in the performance of the models between regions of the United States (the Southeastern and Northwestern United States) warrant a regional-scale assessment of CMIP5 models.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Wieder, William R.; Allison, Steven D.; Davidson, Eric A.
Microbes influence soil organic matter (SOM) decomposition and the long-term stabilization of carbon (C) in soils. We contend that by revising the representation of microbial processes and their interactions with the physicochemical soil environment, Earth system models (ESMs) may make more realistic global C cycle projections. Explicit representation of microbial processes presents considerable challenges due to the scale at which these processes occur. Thus, applying microbial theory in ESMs requires a framework to link micro-scale process-level understanding and measurements to macro-scale models used to make decadal- to century-long projections. Here, we review the diversity, advantages, and pitfalls of simulating soilmore » biogeochemical cycles using microbial-explicit modeling approaches. We present a roadmap for how to begin building, applying, and evaluating reliable microbial-explicit model formulations that can be applied in ESMs. Drawing from experience with traditional decomposition models we suggest: (1) guidelines for common model parameters and output that can facilitate future model intercomparisons; (2) development of benchmarking and model-data integration frameworks that can be used to effectively guide, inform, and evaluate model parameterizations with data from well-curated repositories; and (3) the application of scaling methods to integrate microbial-explicit soil biogeochemistry modules within ESMs. With contributions across scientific disciplines, we feel this roadmap can advance our fundamental understanding of soil biogeochemical dynamics and more realistically project likely soil C response to environmental change at global scales.« less
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Spatiotemporal correlation structure of the Earth's surface temperature
NASA Astrophysics Data System (ADS)
Fredriksen, Hege-Beate; Rypdal, Kristoffer; Rypdal, Martin
2015-04-01
We investigate the spatiotemporal temperature variability for several gridded instrumental and climate model data sets. The temporal variability is analysed by estimating the power spectral density and studying the differences between local and global temperatures, land and sea, and among local temperature records at different locations. The spatiotemporal correlation structure is analysed through cross-spectra that allow us to compute frequency-dependent spatial autocorrelation functions (ACFs). Our results are then compared to theoretical spectra and frequency-dependent spatial ACFs derived from a fractional stochastic-diffusive energy balance model (FEBM). From the FEBM we expect both local and global temperatures to have a long-range persistent temporal behaviour, and the spectral exponent (β) is expected to increase by a factor of two when going from local to global scales. Our comparison of the average local spectrum and the global spectrum shows good agreement with this model, although the FEBM has so far only been studied for a pure land planet and a pure ocean planet, respectively, with no seasonal forcing. Hence it cannot capture the substantial variability among the local spectra, in particular between the spectra for land and sea, and for equatorial and non-equatorial temperatures. Both models and observation data show that land temperatures in general have a low persistence, while sea surface temperatures show a higher, and also more variable degree of persistence. Near the equator the spectra deviate from the power-law shape expected from the FEBM. Instead we observe large variability at time scales of a few years due to ENSO, and a flat spectrum at longer time scales, making the spectrum more reminiscent of that of a red noise process. From the frequency-dependent spatial ACFs we observe that the spatial correlation length increases with increasing time scale, which is also consistent with the FEBM. One consequence of this is that longer-lasting structures must also be wider in space. The spatial correlation length is also observed to be longer for land than for sea. The climate model simulations studied are mainly CMIP5 control runs of length 500-1000 yr. On time scales up to several centuries we do not observe that the difference between the local and global spectral exponents vanish. This also follows from the FEBM and shows that the dynamics is spatiotemporal (not just temporal) even on these time scales.
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NASA Technical Reports Server (NTRS)
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.
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Scaling law analysis of paraffin thin films on different surfaces
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dotto, M. E. R.; Camargo, S. S. Jr.
2010-01-15
The dynamics of paraffin deposit formation on different surfaces was analyzed based on scaling laws. Carbon-based films were deposited onto silicon (Si) and stainless steel substrates from methane (CH{sub 4}) gas using radio frequency plasma enhanced chemical vapor deposition. The different substrates were characterized with respect to their surface energy by contact angle measurements, surface roughness, and morphology. Paraffin thin films were obtained by the casting technique and were subsequently characterized by an atomic force microscope in noncontact mode. The results indicate that the morphology of paraffin deposits is strongly influenced by substrates used. Scaling laws analysis for coated substratesmore » present two distinct dynamics: a local roughness exponent ({alpha}{sub local}) associated to short-range surface correlations and a global roughness exponent ({alpha}{sub global}) associated to long-range surface correlations. The local dynamics is described by the Wolf-Villain model, and a global dynamics is described by the Kardar-Parisi-Zhang model. A local correlation length (L{sub local}) defines the transition between the local and global dynamics with L{sub local} approximately 700 nm in accordance with the spacing of planes measured from atomic force micrographs. For uncoated substrates, the growth dynamics is related to Edwards-Wilkinson model.« less
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Changing global essential medicines norms to improve access to AIDS treatment: lessons from Brazil.
Nunn, A; Fonseca, E Da; Gruskin, S
2009-01-01
Brazil's large-scale, successful HIV/AIDS treatment programme is considered by many to be a model for other developing countries aiming to improve access to AIDS treatment. Far less is known about Brazil's important role in changing global norms related to international pharmaceutical policy, particularly international human rights, health and trade policies governing access to essential medicines. Prompted by Brazil's interest in preserving its national AIDS treatment policies during World Trade Organisation trade disputes with the USA, these efforts to change global essential medicines norms have had important implications for other countries, particularly those scaling up AIDS treatment. This paper analyses Brazil's contributions to global essential medicines policy and explains the relevance of Brazil's contributions to global health policy today.
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Ma, Jianyong; Shugart, Herman H; Yan, Xiaodong; Cao, Cougui; Wu, Shuang; Fang, Jing
2017-05-15
The carbon budget of forest ecosystems, an important component of the terrestrial carbon cycle, needs to be accurately quantified and predicted by ecological models. As a preamble to apply the model to estimate global carbon uptake by forest ecosystems, we used the CO 2 flux measurements from 37 forest eddy-covariance sites to examine the individual tree-based FORCCHN model's performance globally. In these initial tests, the FORCCHN model simulated gross primary production (GPP), ecosystem respiration (ER) and net ecosystem production (NEP) with correlations of 0.72, 0.70 and 0.53, respectively, across all forest biomes. The model underestimated GPP and slightly overestimated ER across most of the eddy-covariance sites. An underestimation of NEP arose primarily from the lower GPP estimates. Model performance was better in capturing both the temporal changes and magnitude of carbon fluxes in deciduous broadleaf forest than in evergreen broadleaf forest, and it performed less well for sites in Mediterranean climate. We then applied the model to estimate the carbon fluxes of forest ecosystems on global scale over 1982-2011. This application of FORCCHN gave a total GPP of 59.41±5.67 and an ER of 57.21±5.32PgCyr -1 for global forest ecosystems during 1982-2011. The forest ecosystems over this same period contributed a large carbon storage, with total NEP being 2.20±0.64PgCyr -1 . These values are comparable to and reinforce estimates reported in other studies. This analysis highlights individual tree-based model FORCCHN could be used to evaluate carbon fluxes of forest ecosystems on global scale. Copyright © 2017 Elsevier B.V. All rights reserved.
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High resolution global flood hazard map from physically-based hydrologic and hydraulic models.
NASA Astrophysics Data System (ADS)
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 corresponds to the return period corresponding to the hazard map being produced (e.g. 100 years, 500 years). Each numerical simulation models one river reach, except for the longest reaches which are split in smaller parts. Here we show results for selected river basins worldwide.
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Multi-scale landslide hazard assessment: Advances in global and regional methodologies
NASA Astrophysics Data System (ADS)
Kirschbaum, Dalia; Peters-Lidard, Christa; Adler, Robert; Hong, Yang
2010-05-01
The increasing availability of remotely sensed surface data and precipitation provides a unique opportunity to explore how smaller-scale landslide susceptibility and hazard assessment methodologies may be applicable at larger spatial scales. This research first considers an emerging satellite-based global algorithm framework, which evaluates how the landslide susceptibility and satellite derived rainfall estimates can forecast potential landslide conditions. An analysis of this algorithm using a newly developed global landslide inventory catalog suggests that forecasting errors are geographically variable due to improper weighting of surface observables, resolution of the current susceptibility map, and limitations in the availability of landslide inventory data. These methodological and data limitation issues can be more thoroughly assessed at the regional level, where available higher resolution landslide inventories can be applied to empirically derive relationships between surface variables and landslide occurrence. The regional empirical model shows improvement over the global framework in advancing near real-time landslide forecasting efforts; however, there are many uncertainties and assumptions surrounding such a methodology that decreases the functionality and utility of this system. This research seeks to improve upon this initial concept by exploring the potential opportunities and methodological structure needed to advance larger-scale landslide hazard forecasting and make it more of an operational reality. Sensitivity analysis of the surface and rainfall parameters in the preliminary algorithm indicates that surface data resolution and the interdependency of variables must be more appropriately quantified at local and regional scales. Additionally, integrating available surface parameters must be approached in a more theoretical, physically-based manner to better represent the physical processes underlying slope instability and landslide initiation. Several rainfall infiltration and hydrological flow models have been developed to model slope instability at small spatial scales. This research investigates the potential of applying a more quantitative hydrological model to larger spatial scales, utilizing satellite and surface data inputs that are obtainable over different geographic regions. Due to the significant role that data and methodological uncertainties play in the effectiveness of landslide hazard assessment outputs, the methodology and data inputs are considered within an ensemble uncertainty framework in order to better resolve the contribution and limitations of model inputs and to more effectively communicate the model skill for improved landslide hazard assessment.
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NASA Astrophysics Data System (ADS)
Kim, Jihn E.; Kyae, Bumseok; Nam, Soonkeon
2017-12-01
In string compactifications, frequently the anomalous U(1) gauge symmetry appears which belongs to E_8 × E_8' of the heterotic string. This anomalous U(1) gauge boson obtains mass at the compactification scale (≈ 10^{18 } {GeV}) by absorbing one pseudoscalar (corresponding to the model-independent axion) from the second rank antisymmetric tensor field B_{MN}. Below the compactification scale a global symmetry U(1)_{anom} results whose charge Q_anom is the original gauge U(1) charge. This is the most natural global symmetry, realizing the "invisible" axion. This global symmetry U(1)_{anom} is suitable for a flavor symmetry. In the simplest compactification model with the flipped SU(5) grand unification, all the low energy parameters are calculated in terms of the vacuum expectation values of the standard model singlets.
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Accurate Realization of GPS Vertical Global Reference Frame
NASA Technical Reports Server (NTRS)
Elosegui, Pedro
2004-01-01
The few millimeter per year level accuracy of radial global velocity estimates with the Global Positioning System (GPS) is at least an order of magnitude poorer than the accuracy of horizontal global motions. An improvement in the accuracy of radial global velocities would have a very positive impact on a number of geophysical studies of current general interest such as global sea-level and climate change, coastal hazards, glacial isostatic adjustment, atmospheric and oceanic loading, glaciology and ice mass variability, tectonic deformation and volcanic inflation, and geoid variability. The goal of this project is to improve our current understanding of GPS error sources associated with estimates of radial velocities at global scales. GPS error sources relevant to this project can be classified in two broad categories: (1) those related to the analysis of the GPS phase observable, and (2) those related to the combination of the positions and velocities of a set of globally distributed stations as determined from the analysis of GPS data important aspect in the first category include the effect on vertical rate estimates due to standard analysis choices, such as orbit modeling, network geometry, ambiguity resolution, as well as errors in models (or simply the lack of models) for clocks, multipath, phase-center variations, atmosphere, and solid-Earth tides. The second category includes the possible methods of combining and defining terrestrial reference flames for determining vertical velocities in a global scale. The latter has been the subject of our research activities during this reporting period.
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A high resolution global scale groundwater model
NASA Astrophysics Data System (ADS)
de Graaf, I. E.; Sutanudjaja, E.; Van Beek, L. P.; Bierkens, M. F.
2013-12-01
As the world's largest accessible source of freshwater, groundwater plays a vital role in satisfying the basic needs of human society. It serves as a primary source of drinking water and also supplies water for agricultural and industrial activities. During times of drought, the large natural groundwater storage provides a buffer against water shortage and sustains flows to rivers and wetlands, supporting ecosystem habitats and biodiversity. Yet, the current generation of global scale hydrological models (GHMs) do not include a groundwater flow component, although it is a crucial part of the hydrological cycle. Thus, a realistic physical representation of the groundwater system that allows for the simulation of groundwater head dynamics and lateral flows is essential for GHMs that increasingly run at finer resolution. In this study we present a transient global groundwater model with a resolution of 5 arc-minutes (approximately 10 km at the equator) using MODFLOW (McDonald and Harbaugh, 1988). Aquifer schematization and properties of this groundwater model were developed from available global lithological maps and datasets (Dürr et al., 2005; Gleeson et al., 2010; Hartmann and Moosdorf, 2013) combined with information about e.g. aquifer thickness and presence of less permeable, impermeable, and semi-impermeable layers. For the parameterization, we relied entirely on available global datasets and did not calibrate the model so that it can equally be expanded to data poor environments. We forced the groundwater model with the output from the global hydrological model PCR-GLOBWB (van Beek et al., 2011), specifically the net groundwater recharge and average surface water levels derived from routed channel discharge. We validated simulated groundwater heads with observations, from North America and Australia, resulting in a coefficient of determination of 0.8 and 0.7 respectively. This shows that it is feasible to build a global groundwater model using best available global information, and estimated water table depths are within acceptable accuracy in many parts of the world.
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Advances in understanding, models and parameterisations of biosphere-atmosphere ammonia exchange
NASA Astrophysics Data System (ADS)
Flechard, C. R.; Massad, R.-S.; Loubet, B.; Personne, E.; Simpson, D.; Bash, J. O.; Cooter, E. J.; Nemitz, E.; Sutton, M. A.
2013-03-01
Atmospheric ammonia (NH3) dominates global emissions of total reactive nitrogen (Nr), while emissions from agricultural production systems contribute about two thirds of global NH3 emissions; the remaining third emanates from oceans, natural vegetation, humans, wild animals and biomass burning. On land, NH3 emitted from the various sources eventually returns to the biosphere by dry deposition to sink areas, predominantly semi-natural vegetation, and by wet and dry deposition as ammonium (NH4+) to all surfaces. However, the land/atmosphere exchange of gaseous NH3 is in fact bi-directional over unfertilized as well as fertilized ecosystems, with periods and areas of emission and deposition alternating in time (diurnal, seasonal) and space (patchwork landscapes). The exchange is controlled by a range of environmental factors, including meteorology, surface layer turbulence, thermodynamics, air and surface heterogeneous-phase chemistry, canopy geometry, plant development stage, leaf age, organic matter decomposition, soil microbial turnover, and, in agricultural systems, by fertilizer application rate, fertilizer type, soil type, crop type, and agricultural management practices. We review the range of processes controlling NH3 emission and uptake in the different parts of the soil-canopy-atmosphere continuum, with NH3 emission potentials defined at the substrate and leaf levels by different [NH4+] / [H+] ratios (Γ). Surface/atmosphere exchange models for NH3 are necessary to compute the temporal and spatial patterns of emissions and deposition at the soil, plant, field, landscape, regional and global scales, in order to assess the multiple environmental impacts of air-borne and deposited NH3 and NH4+. Models of soil/vegetation/atmosphereem NH3 exchange are reviewed from the substrate and leaf scales to the global scale. They range from simple steady-state, "big leaf" canopy resistance models, to dynamic, multi-layer, multi-process, multi-chemical species schemes. Their level of complexity depends on their purpose, the spatial scale at which they are applied, the current level of parameterisation, and the availability of the input data they require. State-of-the-art solutions for determining the emission/sink Γ potentials through the soil/canopy system include coupled, interactive chemical transport models (CTM) and soil/ecosystem modelling at the regional scale. However, it remains a matter for debate to what extent realistic options for future regional and global models should be based on process-based mechanistic versus empirical and regression-type models. Further discussion is needed on the extent and timescale by which new approaches can be used, such as integration with ecosystem models and satellite observations.
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Advances in understanding, models and parameterizations of biosphere-atmosphere ammonia exchange
NASA Astrophysics Data System (ADS)
Flechard, C. R.; Massad, R.-S.; Loubet, B.; Personne, E.; Simpson, D.; Bash, J. O.; Cooter, E. J.; Nemitz, E.; Sutton, M. A.
2013-07-01
Atmospheric ammonia (NH3) dominates global emissions of total reactive nitrogen (Nr), while emissions from agricultural production systems contribute about two-thirds of global NH3 emissions; the remaining third emanates from oceans, natural vegetation, humans, wild animals and biomass burning. On land, NH3 emitted from the various sources eventually returns to the biosphere by dry deposition to sink areas, predominantly semi-natural vegetation, and by wet and dry deposition as ammonium (NH4+) to all surfaces. However, the land/atmosphere exchange of gaseous NH3 is in fact bi-directional over unfertilized as well as fertilized ecosystems, with periods and areas of emission and deposition alternating in time (diurnal, seasonal) and space (patchwork landscapes). The exchange is controlled by a range of environmental factors, including meteorology, surface layer turbulence, thermodynamics, air and surface heterogeneous-phase chemistry, canopy geometry, plant development stage, leaf age, organic matter decomposition, soil microbial turnover, and, in agricultural systems, by fertilizer application rate, fertilizer type, soil type, crop type, and agricultural management practices. We review the range of processes controlling NH3 emission and uptake in the different parts of the soil-canopy-atmosphere continuum, with NH3 emission potentials defined at the substrate and leaf levels by different [NH4+] / [H+] ratios (Γ). Surface/atmosphere exchange models for NH3 are necessary to compute the temporal and spatial patterns of emissions and deposition at the soil, plant, field, landscape, regional and global scales, in order to assess the multiple environmental impacts of airborne and deposited NH3 and NH4+. Models of soil/vegetation/atmosphere NH3 exchange are reviewed from the substrate and leaf scales to the global scale. They range from simple steady-state, "big leaf" canopy resistance models, to dynamic, multi-layer, multi-process, multi-chemical species schemes. Their level of complexity depends on their purpose, the spatial scale at which they are applied, the current level of parameterization, and the availability of the input data they require. State-of-the-art solutions for determining the emission/sink Γ potentials through the soil/canopy system include coupled, interactive chemical transport models (CTM) and soil/ecosystem modelling at the regional scale. However, it remains a matter for debate to what extent realistic options for future regional and global models should be based on process-based mechanistic versus empirical and regression-type models. Further discussion is needed on the extent and timescale by which new approaches can be used, such as integration with ecosystem models and satellite observations.
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GloFAS-Seasonal: Operational Seasonal Ensemble River Flow Forecasts at the Global Scale
NASA Astrophysics Data System (ADS)
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 outlook while providing useful information to users and partners. We demonstrate the first version of an operational GloFAS seasonal outlook, outlining the model set-up and presenting a first look at the seasonal forecasts that will be displayed in the GloFAS interface, and discuss the initial results of the forecast evaluation.
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Mapping local and global variability in plant trait distributions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Butler, Ethan E.; Datta, Abhirup; Flores-Moreno, Habacuc
2017-12-01
Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusingmore » on a set of plant traits closely coupled to photosynthesis and foliar respiration—specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen (N m) and phosphorus (P m), we characterize how traits vary within and among over 50,000 ~50×50-km cells across the entire vegetated land surface. We do this in several ways—without defining the PFT of each grid cell and using 4 or 14 PFTs; each model’s predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps further reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.« less
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NASA Astrophysics Data System (ADS)
Barajas-Solano, D. A.; Tartakovsky, A. M.
2017-12-01
We present a multiresolution method for the numerical simulation of flow and reactive transport in porous, heterogeneous media, based on the hybrid Multiscale Finite Volume (h-MsFV) algorithm. The h-MsFV algorithm allows us to couple high-resolution (fine scale) flow and transport models with lower resolution (coarse) models to locally refine both spatial resolution and transport models. The fine scale problem is decomposed into various "local'' problems solved independently in parallel and coordinated via a "global'' problem. This global problem is then coupled with the coarse model to strictly ensure domain-wide coarse-scale mass conservation. The proposed method provides an alternative to adaptive mesh refinement (AMR), due to its capacity to rapidly refine spatial resolution beyond what's possible with state-of-the-art AMR techniques, and the capability to locally swap transport models. We illustrate our method by applying it to groundwater flow and reactive transport of multiple species.
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NASA Astrophysics Data System (ADS)
Flint, A. L.; Flint, L. E.
2010-12-01
The characterization of hydrologic response to current and future climates is of increasing importance to many countries around the world that rely heavily on changing and uncertain water supplies. Large-scale models that can calculate a spatially distributed water balance and elucidate groundwater recharge and surface water flows for large river basins provide a basis of estimates of changes due to future climate projections. Unfortunately many regions in the world have very sparse data for parameterization or calibration of hydrologic models. For this study, the Tigris and Euphrates River basins were used for the development of a regional water balance model at 180-m spatial scale, using the Basin Characterization Model, to estimate historical changes in groundwater recharge and surface water flows in the countries of Turkey, Syria, Iraq, Iran, and Saudi Arabia. Necessary input parameters include precipitation, air temperature, potential evapotranspiration (PET), soil properties and thickness, and estimates of bulk permeability from geologic units. Data necessary for calibration includes snow cover, reservoir volumes (from satellite data and historic, pre-reservoir elevation data) and streamflow measurements. Global datasets for precipitation, air temperature, and PET were available at very large spatial scales (50 km) through the world scale databases, finer scale WorldClim climate data, and required downscaling to fine scales for model input. Soils data were available through world scale soil maps but required parameterization on the basis of textural data to estimate soil hydrologic properties. Soil depth was interpreted from geomorphologic interpretation and maps of quaternary deposits, and geologic materials were categorized from generalized geologic maps of each country. Estimates of bedrock permeability were made on the basis of literature and data on driller’s logs and adjusted during calibration of the model to streamflow measurements where available. Results of historical water balance calculations throughout the Tigris and Euphrates River basins will be shown along with details of processing input data to provide spatial continuity and downscaling. Basic water availability analysis for recharge and runoff is readily available from a determinisitic solar radiation energy balance model and a global potential evapotranspiration model and global estimates of precipitation and air temperature. Future climate estimates can be readily applied to the same water and energy balance models to evaluate future water availability for countries around the globe.
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Development of new impact functions for global risk caused by climate change
NASA Astrophysics Data System (ADS)
Miyazaki, C.
2014-12-01
The purpose of our study is to identify and quantify global-scale risks which can be caused by future climate change. In particular, we focus on the global-scale risks which have critical impacts to human environments. Use of impact functions is one of the common way to quantify global-scale risks. Output of impact function is climate impacts (e.g. economic damage by temperature increasing) and input can be global temperature increasing and/or socioeconomic condition (e.g. GDP). As the first step of study, we referred to AR5 WG II report (AR5, hereafter) and comprehensive inventories of climate change risks developed by Strategic R&D Area Project of the Environment Research and Technology Development Fund (ICA-RUS project). Then we extracted information which can be used to develop impact function from them. By following SPM/AR5, we focused on 11 sectors and extracted quantitative description on climate impacts from the AR5 and paper/reports cited in AR5. As a result, we identified about 40 risk items to focus as global-scale risks by climate change. Using the collected information, we tentatively made impact function on sea level rise and so on. In addition, we also extracted the impact functions used in Integrated Assessment Models (IAMs). The literature survey on IAM suggested the risk items considered in IAMs are limited. For instance, although FUND model provides detailed impact functions compared with most of other IAMs, its impact functions deal with only several sectors (e.g. agriculture, forestry, biodiversity, sea level rise, human health, energy demand and water resources). The survey on impact functions in IAMs also suggested impact function for abrupt climate change (so-called Tipping Element) is premature. Moreover, as example for quantifying health risk by our calculation, we also present the result on global-scale projection of the health burden attributable to childhood undernutrition (Ishida et al., 2014, ERL).
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Microphysics in Multi-scale Modeling System with Unified Physics
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2012-01-01
Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Walker, Anthony P.; Quaife, Tristan; van Bodegom, Peter M.
Here, the maximum photosynthetic carboxylation rate (V cmax) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V cmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr –1, 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated throughmore » to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated ( r = 0.85–0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V cmax variation in the field, particularly in northern latitudes.« less
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NASA/MSFC FY90 Global Scale Atmospheric Processes Research Program Review
NASA Technical Reports Server (NTRS)
Leslie, Fred W. (Editor)
1990-01-01
Research supported by the Global Atmospheric Research Program at the Marshall Space Flight Center on atmospheric remote sensing, meteorology, numerical weather forecasting, satellite data analysis, cloud precipitation, atmospheric circulation, atmospheric models and related topics is discussed.
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The Australian Computational Earth Systems Simulator
NASA Astrophysics Data System (ADS)
Mora, P.; Muhlhaus, H.; Lister, G.; Dyskin, A.; Place, D.; Appelbe, B.; Nimmervoll, N.; Abramson, D.
2001-12-01
Numerical simulation of the physics and dynamics of the entire earth system offers an outstanding opportunity for advancing earth system science and technology but represents a major challenge due to the range of scales and physical processes involved, as well as the magnitude of the software engineering effort required. However, new simulation and computer technologies are bringing this objective within reach. Under a special competitive national funding scheme to establish new Major National Research Facilities (MNRF), the Australian government together with a consortium of Universities and research institutions have funded construction of the Australian Computational Earth Systems Simulator (ACcESS). The Simulator or computational virtual earth will provide the research infrastructure to the Australian earth systems science community required for simulations of dynamical earth processes at scales ranging from microscopic to global. It will consist of thematic supercomputer infrastructure and an earth systems simulation software system. The Simulator models and software will be constructed over a five year period by a multi-disciplinary team of computational scientists, mathematicians, earth scientists, civil engineers and software engineers. The construction team will integrate numerical simulation models (3D discrete elements/lattice solid model, particle-in-cell large deformation finite-element method, stress reconstruction models, multi-scale continuum models etc) with geophysical, geological and tectonic models, through advanced software engineering and visualization technologies. When fully constructed, the Simulator aims to provide the software and hardware infrastructure needed to model solid earth phenomena including global scale dynamics and mineralisation processes, crustal scale processes including plate tectonics, mountain building, interacting fault system dynamics, and micro-scale processes that control the geological, physical and dynamic behaviour of earth systems. ACcESS represents a part of Australia's contribution to the APEC Cooperation for Earthquake Simulation (ACES) international initiative. Together with other national earth systems science initiatives including the Japanese Earth Simulator and US General Earthquake Model projects, ACcESS aims to provide a driver for scientific advancement and technological breakthroughs including: quantum leaps in understanding of earth evolution at global, crustal, regional and microscopic scales; new knowledge of the physics of crustal fault systems required to underpin the grand challenge of earthquake prediction; new understanding and predictive capabilities of geological processes such as tectonics and mineralisation.
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NASA Astrophysics Data System (ADS)
Machguth, H.; Huss, M.
2014-05-01
Glacier length is an important measure of glacier geometry but global glacier inventories are mostly lacking length data. Only recently semi-automated approaches to measure glacier length have been developed and applied regionally. Here we present a first global assessment of glacier length using a fully automated method based on glacier surface slope, distance to the glacier margins and a set of trade-off functions. The method is developed for East Greenland, evaluated for the same area as well as for Alaska, and eventually applied to all ∼200 000 glaciers around the globe. The evaluation highlights accurately calculated glacier length where DEM quality is good (East Greenland) and limited precision on low quality DEMs (parts of Alaska). Measured length of very small glaciers is subject to a certain level of ambiguity. The global calculation shows that only about 1.5% of all glaciers are longer than 10 km with Bering Glacier (Alaska/Canada) being the longest glacier in the world at a length of 196 km. Based on model output we derive global and regional area-length scaling laws. Differences among regional scaling parameters appear to be related to characteristics of topography and glacier mass balance. The present study adds glacier length as a central parameter to global glacier inventories. Global and regional scaling laws might proof beneficial in conceptual glacier models.
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Carbon cycle confidence and uncertainty: Exploring variation among soil biogeochemical models
Wieder, William R.; Hartman, Melannie D.; Sulman, Benjamin N.; ...
2017-11-09
Emerging insights into factors responsible for soil organic matter stabilization and decomposition are being applied in a variety of contexts, but new tools are needed to facilitate the understanding, evaluation, and improvement of soil biogeochemical theory and models at regional to global scales. To isolate the effects of model structural uncertainty on the global distribution of soil carbon stocks and turnover times we developed a soil biogeochemical testbed that forces three different soil models with consistent climate and plant productivity inputs. The models tested here include a first-order, microbial implicit approach (CASA-CNP), and two recently developed microbially explicit models thatmore » can be run at global scales (MIMICS and CORPSE). When forced with common environmental drivers, the soil models generated similar estimates of initial soil carbon stocks (roughly 1,400 Pg C globally, 0–100 cm), but each model shows a different functional relationship between mean annual temperature and inferred turnover times. Subsequently, the models made divergent projections about the fate of these soil carbon stocks over the 20th century, with models either gaining or losing over 20 Pg C globally between 1901 and 2010. Single-forcing experiments with changed inputs, tem- perature, and moisture suggest that uncertainty associated with freeze-thaw processes as well as soil textural effects on soil carbon stabilization were larger than direct temper- ature uncertainties among models. Finally, the models generated distinct projections about the timing and magnitude of seasonal heterotrophic respiration rates, again reflecting structural uncertainties that were related to environmental sensitivities and assumptions about physicochemical stabilization of soil organic matter. Here, by providing a computationally tractable and numerically consistent framework to evaluate models we aim to better understand uncertainties among models and generate insights about fac- tors regulating the turnover of soil organic matter.« less
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Carbon cycle confidence and uncertainty: Exploring variation among soil biogeochemical models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wieder, William R.; Hartman, Melannie D.; Sulman, Benjamin N.
Emerging insights into factors responsible for soil organic matter stabilization and decomposition are being applied in a variety of contexts, but new tools are needed to facilitate the understanding, evaluation, and improvement of soil biogeochemical theory and models at regional to global scales. To isolate the effects of model structural uncertainty on the global distribution of soil carbon stocks and turnover times we developed a soil biogeochemical testbed that forces three different soil models with consistent climate and plant productivity inputs. The models tested here include a first-order, microbial implicit approach (CASA-CNP), and two recently developed microbially explicit models thatmore » can be run at global scales (MIMICS and CORPSE). When forced with common environmental drivers, the soil models generated similar estimates of initial soil carbon stocks (roughly 1,400 Pg C globally, 0–100 cm), but each model shows a different functional relationship between mean annual temperature and inferred turnover times. Subsequently, the models made divergent projections about the fate of these soil carbon stocks over the 20th century, with models either gaining or losing over 20 Pg C globally between 1901 and 2010. Single-forcing experiments with changed inputs, tem- perature, and moisture suggest that uncertainty associated with freeze-thaw processes as well as soil textural effects on soil carbon stabilization were larger than direct temper- ature uncertainties among models. Finally, the models generated distinct projections about the timing and magnitude of seasonal heterotrophic respiration rates, again reflecting structural uncertainties that were related to environmental sensitivities and assumptions about physicochemical stabilization of soil organic matter. Here, by providing a computationally tractable and numerically consistent framework to evaluate models we aim to better understand uncertainties among models and generate insights about fac- tors regulating the turnover of soil organic matter.« less
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a Model Study of Small-Scale World Map Generalization
NASA Astrophysics Data System (ADS)
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.
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Exploring Land Use and Land Cover Change and Feedbacks in the Global Change Assessment Model
NASA Astrophysics Data System (ADS)
Chen, M.; Vernon, C. R.; Huang, M.; Calvin, K. V.; Le Page, Y.; Kraucunas, I.
2017-12-01
Land Use and Land Cover Change (LULCC) is a major driver of global and regional environmental change. Projections of land use change are thus an essential component in Integrated Assessment Models (IAMs) to study feedbacks between transformation of energy systems and land productivity under the context of climate change. However, the spatial scale of IAMs, e.g., the Global Change Assessment Model (GCAM), is typically larger than the scale of terrestrial processes in the human-Earth system, LULCC downscaling therefore becomes a critical linkage among these multi-scale and multi-sector processes. Parametric uncertainties in LULCC downscaling algorithms, however, have been under explored, especially in the context of how such uncertainties could propagate to affect energy systems in a changing climate. In this study, we use a LULCC downscaling model, Demeter, to downscale GCAM-based future land use scenarios into fine spatial scales, and explore the sensitivity of downscaled land allocations to key parameters. Land productivity estimates (e.g., biomass production and crop yield) based on the downscaled LULCC scenarios are then fed to GCAM to evaluate how energy systems might change due to altered water and carbon cycle dynamics and their interactions with the human system, , which would in turn affect future land use projections. We demonstrate that uncertainties in LULCC downscaling can result in significant differences in simulated scenarios, indicating the importance of quantifying parametric uncertainties in LULCC downscaling models for integrated assessment studies.
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Large-scale Modeling of Nitrous Oxide Production: Issues of Representing Spatial Heterogeneity
NASA Astrophysics Data System (ADS)
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.
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NASA Astrophysics Data System (ADS)
Drapeau, L.; Mangiarotti, S.; Le Jean, F.; Gascoin, S.; Jarlan, L.
2014-12-01
The global modeling technique provides a way to obtain ordinary differential equations from single time series1. This technique, initiated in the 1990s, could be applied successfully to numerous theoretic and experimental systems. More recently it could be applied to environmental systems2,3. Here this technique is applied to seasonal snow cover area in the Pyrenees mountain (Europe) and Mont Lebanon (Mediterranean region). The snowpack evolution is complex because it results from combination of processes driven by physiography (elevation, slope, land cover...) and meteorological variables (precipitation, temperature, wind speed...), which are highly heterogeneous in such regions. Satellite observations in visible bands offer a powerful tool to monitor snow cover areas at global scale, with large resolutions range. Although this observable does not directly inform about snow water equivalent, its dynamical behavior strongly relies on it. Therefore, snow cover area is likely to be a good proxy of the global dynamics and global modeling technique a well adapted approach. The MOD10A2 product (500m) generated from MODIS by the NASA is used after a pretreatment is applied to minimize clouds effect. The global modeling technique is then applied using two packages4,5. The analysis is performed with two time series for the whole period (2000-2012) and year by year. Low-dimensional chaotic models are obtained in many cases. Such models provide a strong argument for chaos since involving the two necessary conditions in a synthetic way: determinism and strong sensitivity to initial conditions. The models comparison suggests important non-stationnarities at interannual scale which prevent from detecting long term changes. 1: Letellier et al 2009. Frequently asked questions about global modeling, Chaos, 19, 023103. 2: Maquet et al 2007. Global models from the Canadian lynx cycles as a direct evidence for chaos in real ecosystems. J. of Mathematical Biology, 55 (1), 21-39 3: Mangiarotti et al 2014. Two chaotic global models for cereal crops cycles observed from satellite in Northern Morocco. Chaos, 24, 023130. 4 : Mangiarotti et al 2012. Polynomial search and Global modelling: two algorithms for modeling chaos. Physical Review E, 86(4), 046205. 5: http://cran.r-project.org/web/packages/PoMoS/index.html.
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Egberink, Iris J L; Meijer, Rob R
2011-06-01
The authors investigated the psychometric properties of the subscales of the Self-Perception Profile for Children with item response theory (IRT) models using a sample of 611 children. Results from a nonparametric Mokken analysis and a parametric IRT approach for boys (n = 268) and girls (n = 343) were compared. The authors found that most scales formed weak scales and that measurement precision was relatively low and only present for latent trait values indicating low self-perception. The subscales Physical Appearance and Global Self-Worth formed one strong scale. Children seem to interpret Global Self-Worth items as if they measure Physical Appearance. Furthermore, the authors found that strong Mokken scales (such as Global Self-Worth) consisted mostly of items that repeat the same item content. They conclude that researchers should be very careful in interpreting the total scores on the different Self-Perception Profile for Children scales. Finally, implications for further research are discussed.
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The impact of lake and reservoir parameterization on global streamflow simulation.
Zajac, Zuzanna; Revilla-Romero, Beatriz; Salamon, Peter; Burek, Peter; Hirpa, Feyera A; Beck, Hylke
2017-05-01
Lakes and reservoirs affect the timing and magnitude of streamflow, and are therefore essential hydrological model components, especially in the context of global flood forecasting. However, the parameterization of lake and reservoir routines on a global scale is subject to considerable uncertainty due to lack of information on lake hydrographic characteristics and reservoir operating rules. In this study we estimated the effect of lakes and reservoirs on global daily streamflow simulations of a spatially-distributed LISFLOOD hydrological model. We applied state-of-the-art global sensitivity and uncertainty analyses for selected catchments to examine the effect of uncertain lake and reservoir parameterization on model performance. Streamflow observations from 390 catchments around the globe and multiple performance measures were used to assess model performance. Results indicate a considerable geographical variability in the lake and reservoir effects on the streamflow simulation. Nash-Sutcliffe Efficiency (NSE) and Kling-Gupta Efficiency (KGE) metrics improved for 65% and 38% of catchments respectively, with median skill score values of 0.16 and 0.2 while scores deteriorated for 28% and 52% of the catchments, with median values -0.09 and -0.16, respectively. The effect of reservoirs on extreme high flows was substantial and widespread in the global domain, while the effect of lakes was spatially limited to a few catchments. As indicated by global sensitivity analysis, parameter uncertainty substantially affected uncertainty of model performance. Reservoir parameters often contributed to this uncertainty, although the effect varied widely among catchments. The effect of reservoir parameters on model performance diminished with distance downstream of reservoirs in favor of other parameters, notably groundwater-related parameters and channel Manning's roughness coefficient. This study underscores the importance of accounting for lakes and, especially, reservoirs and using appropriate parameterization in large-scale hydrological simulations.
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NASA Astrophysics Data System (ADS)
Omrani, Hiba; Drobinski, Philippe; Dubos, Thomas
2010-05-01
In this work, we consider the effect of indiscriminate and spectral nudging on the large and small scales of an idealized model simulation. The model is a two layer quasi-geostrophic model on the beta-plane driven at its boundaries by the « global » version with periodic boundary condition. This setup mimics the configuration used for regional climate modelling. The effect of large-scale nudging is studied by using the "perfect model" approach. Two sets of experiments are 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 Limited Area Model (LAM) where the size of the LAM domain comes into play in addition to the first set of simulations. The study shows that the indiscriminate nudging time that minimizes the error at both the large and small scales is reached for a nudging time close to the predictability time, for spectral nudging, the optimum nudging time should tend to zero since the best large scale dynamics is supposed to be given by the driving large-scale fields are generally given at much lower frequency than the model time step(e,g, 6-hourly analysis) with a basic interpolation between the fields, the optimum nudging time differs from zero, however remaining smaller than the predictability time.
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Global terrestrial N2O budget for present and future
NASA Astrophysics Data System (ADS)
Olin, Stefan; Xing, Xu-Ri; Wårlind, David; Eliasson, Peter; Smith, Ben; Arneth, Almut
2017-04-01
Nitrogen (N) plays an important role in plant productivity and physiology and is the main limiting nutrient in a majority of the terrestrial ecosystems. The enhanced input of anthropogenic reactive nitrogen (Nr) in agriculture have enhanced global food production, but with adverse effects on biodiversity and water quality, and substantially increased emissions of N trace gases that affect air quality and climate. Emissions of N gases affects the climate, either through cloud forming nitrogen oxides (NOx) gases or as greenhouse gases, where nitrous oxide (N2O) is the most important being approximately 300 times more potent than carbon dioxide (CO2). In this study we use the process-based global vegetation model Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) (Olin et al. 2015) that recently have incorporated a new soil N transformation scheme, adopted from Xu-Ri and Prentice (2008), which makes it possible to study the N2O emission respond to changes in climate and CO2 concentration as well as anthropogenic N enhancements on a global scale. We present here results from the validation of the new model against site-scale N2O measurements from agricultural and non-agricultural ecosystems. We will also present results from a study to examine how land use, land use change and anthropogenic N fertilisation influence historical and future global N2O emissions. This new development represents a key component within future projects in CMIP6 (LUMIP) and in EC-Earth for the EU Horizon 2020 project CRESCENDO. Olin, S., Lindeskog, M., Pugh, T., Schurgers, G., Mischurow, M., Wårlind, D., Zaehle, S., Stocker, B., Smith, B. and Arneth, A. 2015. Soil carbon management in large-scale Earth system modelling: implications for crop yields and nitrogen leaching. Earth System Dynamics, 6, 745-768. Xu-Ri and Prentice IC. 2008. Terrestrial nitrogen cycle simulation with a dynamic global vegetation model. Global Change Biology, 14, 1745-1764.
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Time-lag effects of global vegetation responses to climate change.
Wu, Donghai; Zhao, Xiang; Liang, Shunlin; Zhou, Tao; Huang, Kaicheng; Tang, Bijian; Zhao, Wenqian
2015-09-01
Climate conditions significantly affect vegetation growth in terrestrial ecosystems. Due to the spatial heterogeneity of ecosystems, the vegetation responses to climate vary considerably with the diverse spatial patterns and the time-lag effects, which are the most important mechanism of climate-vegetation interactive effects. Extensive studies focused on large-scale vegetation-climate interactions use the simultaneous meteorological and vegetation indicators to develop models; however, the time-lag effects are less considered, which tends to increase uncertainty. In this study, we aim to quantitatively determine the time-lag effects of global vegetation responses to different climatic factors using the GIMMS3g NDVI time series and the CRU temperature, precipitation, and solar radiation datasets. First, this study analyzed the time-lag effects of global vegetation responses to different climatic factors. Then, a multiple linear regression model and partial correlation model were established to statistically analyze the roles of different climatic factors on vegetation responses, from which the primary climate-driving factors for different vegetation types were determined. The results showed that (i) both the time-lag effects of the vegetation responses and the major climate-driving factors that significantly affect vegetation growth varied significantly at the global scale, which was related to the diverse vegetation and climate characteristics; (ii) regarding the time-lag effects, the climatic factors explained 64% variation of the global vegetation growth, which was 11% relatively higher than the model ignoring the time-lag effects; (iii) for the area with a significant change trend (for the period 1982-2008) in the global GIMMS3g NDVI (P < 0.05), the primary driving factor was temperature; and (iv) at the regional scale, the variation in vegetation growth was also related to human activities and natural disturbances. Considering the time-lag effects is quite important for better predicting and evaluating the vegetation dynamics under the background of global climate change. © 2015 John Wiley & Sons Ltd.
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NASA Astrophysics Data System (ADS)
Fuhrer, Oliver; Chadha, Tarun; Hoefler, Torsten; Kwasniewski, Grzegorz; Lapillonne, Xavier; Leutwyler, David; Lüthi, Daniel; Osuna, Carlos; Schär, Christoph; Schulthess, Thomas C.; Vogt, Hannes
2018-05-01
The best hope for reducing long-standing global climate model biases is by increasing resolution to the kilometer scale. Here we present results from an ultrahigh-resolution non-hydrostatic climate model for a near-global setup running on the full Piz Daint supercomputer on 4888 GPUs (graphics processing units). The dynamical core of the model has been completely rewritten using a domain-specific language (DSL) for performance portability across different hardware architectures. Physical parameterizations and diagnostics have been ported using compiler directives. To our knowledge this represents the first complete atmospheric model being run entirely on accelerators on this scale. At a grid spacing of 930 m (1.9 km), we achieve a simulation throughput of 0.043 (0.23) simulated years per day and an energy consumption of 596 MWh per simulated year. Furthermore, we propose a new memory usage efficiency (MUE) metric that considers how efficiently the memory bandwidth - the dominant bottleneck of climate codes - is being used.
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Breivik, Knut; Armitage, James M; Wania, Frank; Sweetman, Andrew J; Jones, Kevin C
2016-01-19
Elevated concentrations of various industrial-use Persistent Organic Pollutants (POPs), such as polychlorinated biphenyls (PCBs), have been reported in some developing areas in subtropical and tropical regions known to be destinations of e-waste. We used a recent inventory of the global generation and exports of e-waste to develop various global scale emission scenarios for industrial-use organic contaminants (IUOCs). For representative IUOCs (RIUOCs), only hypothetical emissions via passive volatilization from e-waste were considered whereas for PCBs, historical emissions throughout the chemical life-cycle (i.e., manufacturing, use, disposal) were included. The environmental transport and fate of RIUOCs and PCBs were then simulated using the BETR Global 2.0 model. Export of e-waste is expected to increase and sustain global emissions beyond the baseline scenario, which assumes no export. A comparison between model predictions and observations for PCBs in selected recipient regions generally suggests a better agreement when exports are accounted for. This study may be the first to integrate the global transport of IUOCs in waste with their long-range transport in air and water. The results call for integrated chemical management strategies on a global scale.
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NASA Astrophysics Data System (ADS)
Adam, L.; Döll, P.; Prigent, C.; Papa, F.
2010-08-01
Floodplains play an important role in the terrestrial water cycle and are very important for biodiversity. Therefore, an improved representation of the dynamics of floodplain water flows and storage in global hydrological and land surface models is required. To support model validation, we combined monthly time series of satellite-derived inundation areas (Papa et al., 2010) with data on irrigated rice areas (Portmann et al., 2010). In this way, we obtained global-scale time series of naturally inundated areas (NIA), with monthly values of inundation extent during 1993-2004 and a spatial resolution of 0.5°. For most grid cells (0.5°×0.5°), the mean annual maximum of NIA agrees well with the static open water extent of the Global Lakes and Wetlands database (GLWD) (Lehner and Döll, 2004), but in 16% of the cells NIA is larger than GLWD. In some regions, like Northwestern Europe, NIA clearly overestimates inundated areas, probably because of confounding very wet soils with inundated areas. In other areas, such as South Asia, it is likely that NIA can help to enhance GLWD. NIA data will be very useful for developing and validating a floodplain modeling algorithm for the global hydrological model WGHM. For example, we found that monthly NIAs correlate with observed river discharges.
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Many regional and global climate models include aerosol indirect effects (AIE) on grid-scale/resolved clouds. However, the interaction between aerosols and convective clouds remains highly uncertain, as noted in the IPCC AR4 report. The objective of this work is to help fill in ...
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Relaxation of the composite Higgs little hierarchy
NASA Astrophysics Data System (ADS)
Batell, Brian; Fedderke, Michael A.; Wang, Lian-Tao
2017-12-01
We describe a composite Higgs scenario in which a cosmological relaxation mechanism naturally gives rise to a hierarchy between the weak scale and the scale of spontaneous global symmetry breaking. This is achieved through the scanning of sources of explicit global symmetry breaking by a relaxion field during an exponentially long period of inflation in the early universe. We explore this mechanism in detail in a specific composite Higgs scenario with QCD-like dynamics, based on an ultraviolet SU( N )TC `technicolor' confining gauge theory with three Dirac technifermion flavors. We find that we can successfully generate a hierarchy of scales ξ≡〈 h〉2/ F π 2 ≳ 1.2 × 10- 4 (i.e., compositeness scales F π ˜ 20 TeV) without tuning. This evades all current electroweak precision bounds on our (custodial violating) model. While directly observing the heavy composite states in this model will be challenging, a future electroweak precision measurement program can probe most of the natural parameter space for the model. We also highlight signatures of more general composite Higgs models in the cosmological relaxation framework, including some implications for flavor and dark matter.
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Winterhalter, Wade E.
2011-09-01
Global climate change is expected to impact biological populations through a variety of mechanisms including increases in the length of their growing season. Climate models are useful tools for predicting how season length might change in the future. However, the accuracy of these models tends to be rather low at regional geographic scales. Here, I determined the ability of several atmosphere and ocean general circulating models (AOGCMs) to accurately simulate historical season lengths for a temperate ectotherm across the continental United States. I also evaluated the effectiveness of regional-scale correction factors to improve the accuracy of these models. I foundmore » that both the accuracy of simulated season lengths and the effectiveness of the correction factors to improve the model's accuracy varied geographically and across models. These results suggest that regional specific correction factors do not always adequately remove potential discrepancies between simulated and historically observed environmental parameters. As such, an explicit evaluation of the correction factors' effectiveness should be included in future studies of global climate change's impact on biological populations.« less
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Cytology of DNA Replication Reveals Dynamic Plasticity of Large-Scale Chromatin Fibers.
Deng, Xiang; Zhironkina, Oxana A; Cherepanynets, Varvara D; Strelkova, Olga S; Kireev, Igor I; Belmont, Andrew S
2016-09-26
In higher eukaryotic interphase nuclei, the 100- to >1,000-fold linear compaction of chromatin is difficult to reconcile with its function as a template for transcription, replication, and repair. It is challenging to imagine how DNA and RNA polymerases with their associated molecular machinery would move along the DNA template without transient decondensation of observed large-scale chromatin "chromonema" fibers [1]. Transcription or "replication factory" models [2], in which polymerases remain fixed while DNA is reeled through, are similarly difficult to conceptualize without transient decondensation of these chromonema fibers. Here, we show how a dynamic plasticity of chromatin folding within large-scale chromatin fibers allows DNA replication to take place without significant changes in the global large-scale chromatin compaction or shape of these large-scale chromatin fibers. Time-lapse imaging of lac-operator-tagged chromosome regions shows no major change in the overall compaction of these chromosome regions during their DNA replication. Improved pulse-chase labeling of endogenous interphase chromosomes yields a model in which the global compaction and shape of large-Mbp chromatin domains remains largely invariant during DNA replication, with DNA within these domains undergoing significant movements and redistribution as they move into and then out of adjacent replication foci. In contrast to hierarchical folding models, this dynamic plasticity of large-scale chromatin organization explains how localized changes in DNA topology allow DNA replication to take place without an accompanying global unfolding of large-scale chromatin fibers while suggesting a possible mechanism for maintaining epigenetic programming of large-scale chromatin domains throughout DNA replication. Copyright © 2016 Elsevier Ltd. All rights reserved.
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NASA Astrophysics Data System (ADS)
Lammers, Richard; Hock, Regine; Prusevich, Alexander; Bliss, Andrew; Radic, Valentina; Glidden, Stanley; Grogan, Danielle; Frolking, Steve
2014-05-01
Glacier and small ice cap melt water contributions to the global hydrologic cycle are an important component of human water supply and for sea level rise. This melt water is used in many arid and semi-arid parts of the world for direct human consumption as well as indirect consumption by irrigation for crops, serving as frozen reservoirs of water that supplement runoff during warm and dry periods of summer when it is needed the most. Additionally, this melt water reaching the oceans represents a direct input to sea level rise and therefore accurate estimates of this contribution have profound economic and geopolitical implications. It has been demonstrated that, on the scale of glacierized river catchments, land surface hydrological models can successfully simulate glacier contribution to streamflow. However, at global scales, the implementation of glacier melt in hydrological models has been rudimentary or non-existent. In this study, a global glacier mass balance model is coupled with the University of New Hampshire Water Balance/Transport Model (WBM) to assess recent and projected future glacier contributions to the hydrological cycle over the global land surface (excluding the ice sheets of Greenland and Antarctica). For instance, results of WBM simulations indicate that seasonal glacier melt water in many arid climate watersheds comprises 40 % or more of their discharge. Implicitly coupled glacier and WBM models compute monthly glacier mass changes and resulting runoff at the glacier terminus for each individual glacier from the globally complete Randolph Glacier Inventory including over 200 000 glaciers. The time series of glacier runoff is aggregated over each hydrological modeling unit and delivered to the hydrological model for routing downstream and mixing with non-glacial contribution of runoff to each drainage basin outlet. WBM tracks and uses glacial and non-glacial components of the in-stream water for filling reservoirs, transfers of water between drainage basins (inter-basin hydrological transfers), and irrigation along the global system of rivers with net discharge to the ocean. Climate scenarios from global climate models prepared for IPCC AR5 are used to explore an expected range of possible future glacier outflow variability to estimate the impacts on human use of these valuable waters and their poorly understood net contribution to sea level change.
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NASA Astrophysics Data System (ADS)
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.
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NASA Astrophysics Data System (ADS)
Durmaz, Murat; Karslioglu, Mahmut Onur
2015-04-01
There are various global and regional methods that have been proposed for the modeling of ionospheric vertical total electron content (VTEC). Global distribution of VTEC is usually modeled by spherical harmonic expansions, while tensor products of compactly supported univariate B-splines can be used for regional modeling. In these empirical parametric models, the coefficients of the basis functions as well as differential code biases (DCBs) of satellites and receivers can be treated as unknown parameters which can be estimated from geometry-free linear combinations of global positioning system observables. In this work we propose a new semi-parametric multivariate adaptive regression B-splines (SP-BMARS) method for the regional modeling of VTEC together with satellite and receiver DCBs, where the parametric part of the model is related to the DCBs as fixed parameters and the non-parametric part adaptively models the spatio-temporal distribution of VTEC. The latter is based on multivariate adaptive regression B-splines which is a non-parametric modeling technique making use of compactly supported B-spline basis functions that are generated from the observations automatically. This algorithm takes advantage of an adaptive scale-by-scale model building strategy that searches for best-fitting B-splines to the data at each scale. The VTEC maps generated from the proposed method are compared numerically and visually with the global ionosphere maps (GIMs) which are provided by the Center for Orbit Determination in Europe (CODE). The VTEC values from SP-BMARS and CODE GIMs are also compared with VTEC values obtained through calibration using local ionospheric model. The estimated satellite and receiver DCBs from the SP-BMARS model are compared with the CODE distributed DCBs. The results show that the SP-BMARS algorithm can be used to estimate satellite and receiver DCBs while adaptively and flexibly modeling the daily regional VTEC.
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Conformal standard model with an extended scalar sector
NASA Astrophysics Data System (ADS)
Latosinski, Adam; Lewandowski, Adrian; Meissner, Krzysztof A.; Nicolai, Hermann
2015-10-01
We present an extended version of the Conformal Standard Model (characterized by the absence of any new intermediate scales between the electroweak scale and the Planck scale) with an enlarged scalar sector coupling to right-chiral neutrinos. The scalar potential and the Yukawa couplings involving only right-chiral neutrinos are invariant under a new global symmetry SU(3) N that complements the standard U(1) B-L symmetry, and is broken explicitly only by the Yukawa interaction, of order O (10-6), coupling right-chiral neutrinos and the electroweak lepton doublets. We point out four main advantages of this enlargement, namely: (1) the economy of the (non-supersymmetric) Standard Model, and thus its observational success, is preserved; (2) thanks to the enlarged scalar sector the RG improved one-loop effective potential is everywhere positive with a stable global minimum, thereby avoiding the notorious instability of the Standard Model vacuum; (3) the pseudo-Goldstone bosons resulting from spontaneous breaking of the SU(3) N symmetry are natural Dark Matter candidates with calculable small masses and couplings; and (4) the Majorana Yukawa coupling matrix acquires a form naturally adapted to leptogenesis. The model is made perturbatively consistent up to the Planck scale by imposing the vanishing of quadratic divergences at the Planck scale (`softly broken conformal symmetry'). Observable consequences of the model occur mainly via the mixing of the new scalars and the standard model Higgs boson.
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Application of SIR-C SAR to Hydrology
NASA Technical Reports Server (NTRS)
Engman, Edwin T.; ONeill, Peggy; Wood, Eric; Pauwels, Valentine; Hsu, Ann; Jackson, Tom; Shi, J. C.; Prietzsch, Corinna
1996-01-01
The progress, results and future plans regarding the following objectives are presented: (1) Determine and compare soil moisture patterns within one or more humid watersheds using SAR data, ground-based measurements, and hydrologic modeling; (2) Use radar data to characterize the hydrologic regime within a catchment and to identify the runoff producing characteristics of humid zone watersheds; and (3) Use radar data as the basis for scaling up from small scale, near-point process models to larger scale water balance models necessary to define and quantify the land phase of GCM's (Global Circulation Models).
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NASA Astrophysics Data System (ADS)
Tomassini, Lorenzo; Field, Paul R.; Honnert, Rachel; Malardel, Sylvie; McTaggart-Cowan, Ron; Saitou, Kei; Noda, Akira T.; Seifert, Axel
2017-03-01
A stratocumulus-to-cumulus transition as observed in a cold air outbreak over the North Atlantic Ocean is compared in global climate and numerical weather prediction models and a large-eddy simulation model as part of the Working Group on Numerical Experimentation "Grey Zone" project. The focus of the project is to investigate to what degree current convection and boundary layer parameterizations behave in a scale-adaptive manner in situations where the model resolution approaches the scale of convection. Global model simulations were performed at a wide range of resolutions, with convective parameterizations turned on and off. The models successfully simulate the transition between the observed boundary layer structures, from a well-mixed stratocumulus to a deeper, partly decoupled cumulus boundary layer. There are indications that surface fluxes are generally underestimated. The amount of both cloud liquid water and cloud ice, and likely precipitation, are under-predicted, suggesting deficiencies in the strength of vertical mixing in shear-dominated boundary layers. But also regulation by precipitation and mixed-phase cloud microphysical processes play an important role in the case. With convection parameterizations switched on, the profiles of atmospheric liquid water and cloud ice are essentially resolution-insensitive. This, however, does not imply that convection parameterizations are scale-aware. Even at the highest resolutions considered here, simulations with convective parameterizations do not converge toward the results of convection-off experiments. Convection and boundary layer parameterizations strongly interact, suggesting the need for a unified treatment of convective and turbulent mixing when addressing scale-adaptivity.
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NASA Technical Reports Server (NTRS)
Boering, Kristie A.; Connell, Peter; Rotman, Douglas
2005-01-01
Until recently, the stable isotopic composition of chemically and datively important stratospheric species, such as ozone (O3), carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4), was largely unexplored, despite indications from the few measurements available and theoretical studies that global-scale isotopic variations will provide a unique tool for quantifying rates of global-scale mass transport into, within, and out of the stratosphere and for understanding the mechanisms of chemical reactions involved in ozone production. The number and geographical extent of observations are beginning to increase rapidly, however, as access to the stratosphere, both directly and by remote-sensing, has increased over the last 10 years and as new analytical techniques have been developed that make global-scale isotope measurements by whole-air sampling more feasible. The objective of this study, begun in April 1999, is to incorporate into the Livermore 2D model the likely photochemical fractionation processes that determine the isotopic compositions of stratospheric CO2, N2O, CH4, and O3, and to use the model results and new observations from NASA field campaigns in 1996 and 1997 to investigate stratospheric chemistry and mass transport. Additionally, since isotopic signatures from the stratosphere are transferred to the troposphere by downward transport at middle and high latitudes, the isotopic compositions may also serve as sensitive tracers of stratosphere-totroposphere transport. Comparisons of model results with stratospheric and upper tropospheric observations from these campaigns, as well as with ground-based observations from new NOAA and NSF-sponsored studies, will help determine whether the magnitudes of the stratospheric fractionation processes are large enough to use as global-scale tracers of transport into the troposphere and, if so, will be used to help constrain the degree of coupling between the troposphere and the stratosphere.
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NASA Technical Reports Server (NTRS)
Robertson, Franklin R.; Christy, John R.; Goodman, Steven J.; Miller, Tim L.; Fitzjarrald, Dan; Lapenta, Bill; Wang, Shouping
1991-01-01
The primary objective is to determine the scope and interactions of the global water cycle with all components of the Earth system and to understand how it stimulates and regulates changes on both global and regional scales. The following subject areas are covered: (1) water vapor variability; (2) multi-phase water analysis; (3) diabatic heating; (4) MSU (Microwave Sounding Unit) temperature analysis; (5) Optimal precipitation and streamflow analysis; (6) CCM (Community Climate Model) hydrological cycle; (7) CCM1 climate sensitivity to lower boundary forcing; and (8) mesoscale modeling of atmosphere/surface interaction.
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Large Scale Flood Risk Analysis using a New Hyper-resolution Population Dataset
NASA Astrophysics Data System (ADS)
Smith, A.; Neal, J. C.; Bates, P. D.; Quinn, N.; Wing, O.
2017-12-01
Here we present the first national scale flood risk analyses, using high resolution Facebook Connectivity Lab population data and data from a hyper resolution flood hazard model. In recent years the field of large scale hydraulic modelling has been transformed by new remotely sensed datasets, improved process representation, highly efficient flow algorithms and increases in computational power. These developments have allowed flood risk analysis to be undertaken in previously unmodeled territories and from continental to global scales. Flood risk analyses are typically conducted via the integration of modelled water depths with an exposure dataset. Over large scales and in data poor areas, these exposure data typically take the form of a gridded population dataset, estimating population density using remotely sensed data and/or locally available census data. The local nature of flooding dictates that for robust flood risk analysis to be undertaken both hazard and exposure data should sufficiently resolve local scale features. Global flood frameworks are enabling flood hazard data to produced at 90m resolution, resulting in a mis-match with available population datasets which are typically more coarsely resolved. Moreover, these exposure data are typically focused on urban areas and struggle to represent rural populations. In this study we integrate a new population dataset with a global flood hazard model. The population dataset was produced by the Connectivity Lab at Facebook, providing gridded population data at 5m resolution, representing a resolution increase over previous countrywide data sets of multiple orders of magnitude. Flood risk analysis undertaken over a number of developing countries are presented, along with a comparison of flood risk analyses undertaken using pre-existing population datasets.
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Linking Belowground Plant Traits With Ecosystem Processes: A Multi-Biome Perspective
NASA Astrophysics Data System (ADS)
Iversen, C. M.; Norby, R. J.; Childs, J.; McCormack, M. L.; Walker, A. P.; Hanson, P. J.; Warren, J.; Sloan, V. L.; Sullivan, P. F.; Wullschleger, S.; Powell, A. S.
2015-12-01
Fine plant roots are short-lived, narrow-diameter roots that play an important role in ecosystem carbon, water, and nutrient cycling in biomes ranging from the tundra to the tropics. Root ecologists make measurements at a millimeter scale to answer a question with global implications: In response to a changing climate, how do fine roots modulate the exchange of carbon between soils and the atmosphere and how will this response affect our future climate? In a Free-Air CO2 Enrichment experiment in Oak Ridge, TN, elevated [CO2] caused fine roots to dive deeper into the soil profile in search of limiting nitrogen, which led to increased soil C storage in deep soils. In contrast, the fine roots of trees and shrubs in an ombrotrophic bog are constrained to nutrient-poor, oxic soils above the average summer water table depth, though this may change with warmer, drier conditions. Tundra plant species are similarly constrained to surface organic soils by permafrost or waterlogged soils, but have many adaptations that alter ecosystem C fluxes, including aerenchyma that oxygenate the rhizosphere but also allow direct methane flux to the atmosphere. FRED, a global root trait database, will allow terrestrial biosphere models to represent the complexity of root traits across the globe, informing both model representation of ecosystem C and nutrient fluxes, but also the gaps where measurements are needed on plant-soil interactions (for example, in the tropical biome). While the complexity of mm-scale measurements may never have a place in large-scale global models, close collaboration between empiricists and modelers can help to guide the scaling of important, yet small-scale, processes to quantify their important roles in larger-scale ecosystem fluxes.
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Global terrestrial biogeochemistry: Perturbations, interactions, and time scales
DOE Office of Scientific and Technical Information (OSTI.GOV)
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 lifetimemore » 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.« less
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Harnessing Big Data to Represent 30-meter Spatial Heterogeneity in Earth System Models
NASA Astrophysics Data System (ADS)
Chaney, N.; Shevliakova, E.; Malyshev, S.; Van Huijgevoort, M.; Milly, C.; Sulman, B. N.
2016-12-01
Terrestrial land surface processes play a critical role in the Earth system; they have a profound impact on the global climate, food and energy production, freshwater resources, and biodiversity. One of the most fascinating yet challenging aspects of characterizing terrestrial ecosystems is their field-scale (˜30 m) spatial heterogeneity. It has been observed repeatedly that the water, energy, and biogeochemical cycles at multiple temporal and spatial scales have deep ties to an ecosystem's spatial structure. Current Earth system models largely disregard this important relationship leading to an inadequate representation of ecosystem dynamics. In this presentation, we will show how existing global environmental datasets can be harnessed to explicitly represent field-scale spatial heterogeneity in Earth system models. For each macroscale grid cell, these environmental data are clustered according to their field-scale soil and topographic attributes to define unique sub-grid tiles. The state-of-the-art Geophysical Fluid Dynamics Laboratory (GFDL) land model is then used to simulate these tiles and their spatial interactions via the exchange of water, energy, and nutrients along explicit topographic gradients. Using historical simulations over the contiguous United States, we will show how a robust representation of field-scale spatial heterogeneity impacts modeled ecosystem dynamics including the water, energy, and biogeochemical cycles as well as vegetation composition and distribution.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Hejazi, Mohamad I.; Edmonds, James A.; Clarke, Leon E.
2014-01-01
Water scarcity conditions over the 21st century both globally and regionally are assessed in the context of climate change, by estimating both water availability and water demand within the Global Change Assessment Model (GCAM), a leading community integrated assessment model of energy, agriculture, climate, and water. To quantify changes in future water availability, a new gridded water-balance global hydrologic model – namely, the Global Water Availability Model (GWAM) – is developed and evaluated. Global water demands for six major demand sectors (irrigation, livestock, domestic, electricity generation, primary energy production, and manufacturing) are modeled in GCAM at the regional scale (14more » geopolitical regions, 151 sub-regions) and then spatially downscaled to 0.5 o x 0.5o resolution to match the scale of GWAM. Using a baseline scenario (i.e., no climate change mitigation policy) with radiative forcing reaching 8.8 W/m2 (equivalent to the SRES A1Fi emission scenario) and a global population of 14 billion by 2095, global annual water demand grows from about 9% of total annual renewable freshwater in 2005 to about 32% by 2095. This results in almost half of the world population living under extreme water scarcity by the end of the 21st century. Regionally, the demand for water exceeds the amount of water availability in two GCAM regions, the Middle East and India. Additionally, in years 2050 and 2095, 20% and 27% of the global population, respectively, is projected to live in areas (grid cells) that will experience greater water demands than the amount of available water in a year (i.e., the water scarcity index (WSI) > 1.0). This study implies an increasingly prominent role for water in future human decisions, and highlights the importance of including water in integrated assessment of global change.« less
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NASA Astrophysics Data System (ADS)
Rouholahnejad, E.; Fan, Y.; Kirchner, J. W.; Miralles, D. G.
2017-12-01
Most Earth system models (ESM) average over considerable sub-grid heterogeneity in land surface properties, and overlook subsurface lateral flow. This could potentially bias evapotranspiration (ET) estimates and has implications for future temperature predictions, since overestimations in ET imply greater latent heat fluxes and potential underestimation of dry and warm conditions in the context of climate change. Here we quantify the bias in evaporation estimates that may arise from the fact that ESMs average over considerable heterogeneity in surface properties, and also neglect lateral transfer of water across the heterogeneous landscapes at global scale. We use a Budyko framework to express ET as a function of P and PET to derive simple sub-grid closure relations that quantify how spatial heterogeneity and lateral transfer could affect average ET as seen from the atmosphere. We show that averaging over sub-grid heterogeneity in P and PET, as typical Earth system models do, leads to overestimation of average ET. Our analysis at global scale shows that the effects of sub-grid heterogeneity will be most pronounced in steep mountainous areas where the topographic gradient is high and where P is inversely correlated with PET across the landscape. In addition, we use the Total Water Storage (TWS) anomaly estimates from the Gravity Recovery and Climate Experiment (GRACE) remote sensing product and assimilate it into the Global Land Evaporation Amsterdam Model (GLEAM) to correct for existing free drainage lower boundary condition in GLEAM and quantify whether, and how much, accounting for changes in terrestrial storage can improve the simulation of soil moisture and regional ET fluxes at global scale.
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NASA Astrophysics Data System (ADS)
Yan, Y.-Y.; Lin, J.-T.; Kuang, Y.; Yang, D.; Zhang, L.
2014-07-01
Global chemical transport models (CTMs) are used extensively to study air pollution and transport at a global scale. These models are limited by coarse horizontal resolutions, not allowing for detailed representation of small-scale nonlinear processes over the pollutant source regions. Here we couple the global GEOS-Chem CTM and its three high-resolution nested models to simulate the tropospheric carbon monoxide (CO) over the Pacific Ocean during five HIAPER Pole-to-Pole Observations (HIPPO) campaigns between 2009 and 2011. We develop a two-way coupler, PKUCPL, to integrate simulation results for chemical constituents from the global model (at 2.5° long. × 2° lat.) and the three nested models (at 0.667° long. × 0.5° lat.) covering Asia, North America and Europe, respectively. The coupler obtains nested model results to modify the global model simulation within the respective nested domains, and simultaneously acquires global model results to provide lateral boundary conditions for the nested models. Compared to the global model alone, the two-way coupled simulation results in enhanced CO concentrations in the nested domains. Sensitivity tests suggest the enhancement to be a result of improved representation of the spatial distributions of CO, nitrogen oxides and non-methane volatile organic compounds, the meteorological dependence of natural emissions, and other resolution-dependent processes. The relatively long lifetime of CO allows for the enhancement to be accumulated and carried across the globe. We find that the two-way coupled simulation increases the global tropospheric mean CO concentrations in 2009 by 10.4%, with a greater enhancement at 13.3% in the Northern Hemisphere. Coincidently, the global tropospheric mean hydroxyl radical (OH) is reduced by 4.2% (as compared to the interannual variability of OH at 2.3%), resulting in a 4.2% enhancement in the methyl chloroform lifetime (MCF, via reaction with tropospheric OH). The resulting CO and OH contents and MCF lifetime are closer to observation-based estimates. Both the global and the two-way coupled models capture the general spatiotemporal patterns of HIPPO CO over the Pacific. The two-way coupled simulation is much closer to HIPPO CO, with a mean bias of 1.1 ppb (1.4%) below 9 km compared to the bias at -7.2 ppb (-9.2%) for the global model. The improvement is most apparent over the North Pacific. Our test simulations show that the global model could resemble the two-way coupled simulation (especially below 4 km) by increasing its global CO emissions by 15% for HIPPO-1 and HIPPO-3, by 25% for HIPPO-2 and HIPPO-4, and by 35% for HIPPO-5. This has important implications for using the global model to constrain CO emissions. Thus, the two-way coupled simulation is a significantly improved model tool to studying the global impacts of air pollutants from major anthropogenic source regions.
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A Preliminary Model Study of the Large-Scale Seasonal Cycle in Bottom Pressure Over the Global Ocean
NASA Technical Reports Server (NTRS)
Ponte, Rui M.
1998-01-01
Output from the primitive equation model of Semtner and Chervin is used to examine the seasonal cycle in bottom pressure (Pb) over the global ocean. Effects of the volume-conserving formulation of the model on the calculation Of Pb are considered. The estimated seasonal, large-scale Pb signals have amplitudes ranging from less than 1 cm over most of the deep ocean to several centimeters over shallow, boundary regions. Variability generally increases toward the western sides of the basins, and is also larger in some Southern Ocean regions. An oscillation between subtropical and higher latitudes in the North Pacific is clear. Comparison with barotropic simulations indicates that, on basin scales, seasonal Pb variability is related to barotropic dynamics and the seasonal cycle in Ekman pumping, and results from a small, net residual in mass divergence from the balance between Ekman and Sverdrup flows.
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Prediction Activities at NASA's Global Modeling and Assimilation Office
NASA Technical Reports Server (NTRS)
Schubert, Siegfried
2010-01-01
The Global Modeling and Assimilation Office (GMAO) is a core NASA resource for the development and use of satellite observations through the integrating tools of models and assimilation systems. Global ocean, atmosphere and land surface models are developed as components of assimilation and forecast systems that are used for addressing the weather and climate research questions identified in NASA's science mission. In fact, the GMAO is actively engaged in addressing one of NASA's science mission s key questions concerning how well transient climate variations can be understood and predicted. At weather time scales the GMAO is developing ultra-high resolution global climate models capable of resolving high impact weather systems such as hurricanes. The ability to resolve the detailed characteristics of weather systems within a global framework greatly facilitates addressing fundamental questions concerning the link between weather and climate variability. At sub-seasonal time scales, the GMAO is engaged in research and development to improve the use of land information (especially soil moisture), and in the improved representation and initialization of various sub-seasonal atmospheric variability (such as the MJO) that evolves on time scales longer than weather and involves exchanges with both the land and ocean The GMAO has a long history of development for advancing the seasonal-to-interannual (S-I) prediction problem using an older version of the coupled atmosphere-ocean general circulation model (AOGCM). This includes the development of an Ensemble Kalman Filter (EnKF) to facilitate the multivariate assimilation of ocean surface altimetry, and an EnKF developed for the highly inhomogeneous nature of the errors in land surface models, as well as the multivariate assimilation needed to take advantage of surface soil moisture and snow observations. The importance of decadal variability, especially that associated with long-term droughts is well recognized by the climate community. An improved understanding of the nature of decadal variability and its predictability has important implications for efforts to assess the impacts of global change in the coming decades. In fact, the GMAO has taken on the challenge of carrying out experimental decadal predictions in support of the IPCC AR5 effort.
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A NEW LAND-SURFACE MODEL IN MM5
There has recently been a general realization that more sophisticated modeling of land-surface processes can be important for mesoscale meteorology models. Land-surface models (LSMs) have long been important components in global-scale climate models because of their more compl...
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Dark matter and global symmetries
Mambrini, Yann; Profumo, Stefano; Queiroz, Farinaldo S.
2016-08-03
General considerations in general relativity and quantum mechanics are known to potentially rule out continuous global symmetries in the context of any consistent theory of quantum gravity. Assuming the validity of such considerations, we derive stringent bounds from gamma-ray, X-ray, cosmic-ray, neutrino, and CMB data on models that invoke global symmetries to stabilize the dark matter particle. We compute up-to-date, robust model-independent limits on the dark matter lifetime for a variety of Planck-scale suppressed dimension-five effective operators. We then specialize our analysis and apply our bounds to specific models including the Two-Higgs-Doublet, Left-Right, Singlet Fermionic, Zee-Babu, 3-3-1 and Radiative See-Sawmore » models. Here, assuming that (i) global symmetries are broken at the Planck scale, that (ii) the non-renormalizable operators mediating dark matter decay have O(1) couplings, that (iii) the dark matter is a singlet field, and that (iv) the dark matter density distribution is well described by a NFW profile, we are able to rule out fermionic, vector, and scalar dark matter candidates across a broad mass range (keV-TeV), including the WIMP regime« less
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Century long observation constrained global dynamic downscaling and hydrologic implication
NASA Astrophysics Data System (ADS)
Kim, H.; Yoshimura, K.; Chang, E.; Famiglietti, J. S.; Oki, T.
2012-12-01
It has been suggested that greenhouse gas induced warming climate causes the acceleration of large scale hydrologic cycles, and, indeed, many regions on the Earth have been suffered by hydrologic extremes getting more frequent. However, historical observations are not able to provide enough information in comprehensive manner to understand their long-term variability and/or global distributions. In this study, a century long high resolution global climate data is developed in order to break through existing limitations. 20th Century Reanalysis (20CR) which has relatively low spatial resolution (~2.0°) and longer term availability (140 years) is dynamically downscaled into global T248 (~0.5°) resolution using Experimental Climate Prediction Center (ECPC) Global Spectral Model (GSM) by spectral nudging data assimilation technique. Also, Global Precipitation Climatology Centre (GPCC) and Climate Research Unit (CRU) observational data are adopted to reduce model dependent uncertainty. Downscaled product successfully represents realistic geographical detail keeping low frequency signal in mean state and spatiotemporal variability, while previous bias correction method fails to reproduce high frequency variability. Newly developed data is used to investigate how long-term large scale terrestrial hydrologic cycles have been changed globally and how they have been interacted with various climate modes, such as El-Niño Southern Oscillation (ENSO) and Atlantic Multidecadal Oscillation (AMO). As a further application, it will be used to provide atmospheric boundary condition of multiple land surface models in the Global Soil Wetness Project Phase 3 (GSWP3).
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NASA Astrophysics Data System (ADS)
Yang, B.; Lee, D. K.
2016-12-01
Understanding spatial distribution of irrigation requirement is critically important for agricultural water management. However, many studies considering future agricultural water management in Korea assessed irrigation requirement on watershed or administrative district scale, but have not accounted the spatial distribution. Lumped hydrologic model has typically used in Korea for simulating watershed scale irrigation requirement, while distribution hydrologic model can simulate the spatial distribution grid by grid. To overcome this shortcoming, here we applied a grid base global hydrologic model (H08) into local scale to estimate spatial distribution under future irrigation requirement of Korean Peninsula. Korea is one of the world's most densely populated countries, with also high produce and demand of rice which requires higher soil moisture than other crops. Although, most of the precipitation concentrate in particular season and disagree with crop growth season. This precipitation character makes management of agricultural water which is approximately 60% of total water usage critical issue in Korea. Furthermore, under future climate change, the precipitation predicted to be more concentrated and necessary need change of future water management plan. In order to apply global hydrological model into local scale, we selected appropriate major crops under social and local climate condition in Korea to estimate cropping area and yield, and revised the cropping area map more accurately. As a result, future irrigation requirement estimation varies under each projection, however, slightly decreased in most case. The simulation reveals, evapotranspiration increase slightly while effective precipitation also increase to balance the irrigation requirement. This finding suggest practical guideline to decision makers for further agricultural water management plan including future development of water supply plan to resolve water scarcity.
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Resolving the Kinetic Reconnection Length Scale in Global Magnetospheric Simulations with MHD-EPIC
NASA Astrophysics Data System (ADS)
Toth, G.; Chen, Y.; Cassak, P.; Jordanova, V.; Peng, B.; Markidis, S.; Gombosi, T. I.
2016-12-01
We have recently developed a new modeling capability: the Magnetohydrodynamics with Embedded Particle-in-Cell (MHD-EPIC) algorithm with support from Los Alamos SHIELDS and NSF INSPIRE grants. We have implemented MHD-EPIC into the Space Weather Modeling Framework (SWMF) using the implicit Particle-in-Cell (iPIC3D) and the BATS-R-US extended magnetohydrodynamic codes. The MHD-EPIC model allows two-way coupled simulations in two and three dimensions with multiple embedded PIC regions. Both BATS-R-US and iPIC3D are massively parallel codes. The MHD-EPIC approach allows global magnetosphere simulations with embedded kinetic simulations. For small magnetospheres, like Ganymede or Mercury, we can easily resolve the ion scales around the reconnection sites. Modeling the Earth magnetosphere is very challenging even with our efficient MHD-EPIC model due to the large separation between the global and ion scales. On the other hand the large separation of scales may be exploited: the solution may not be sensitive to the ion inertial length as long as it is small relative to the global scales. The ion inertial length can be varied by changing the ion mass while keeping the MHD mass density, the velocity, and pressure the same for the initial and boundary conditions. Our two-dimensional MHD-EPIC simulations for the dayside reconnection region show in fact, that the overall solution is not sensitive to ion inertial length. The shape, size and frequency of flux transfer events are very similar for a wide range of ion masses. Our results mean that 3D MHD-EPIC simulations for the Earth and other large magnetospheres can be made computationally affordable by artificially increasing the ion mass: the required grid resolution and time step in the PIC model are proportional to the ion inertial length. Changing the ion mass by a factor of 4, for example, speeds up the PIC code by a factor of 256. In fact, this approach allowed us to perform an hour-long 3D MHD-EPIC simulations for the Earth magnetosphere.
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NASA Astrophysics Data System (ADS)
Nikurashin, Maxim; Gunn, Andrew
2017-04-01
The meridional overturning circulation (MOC) is a planetary-scale oceanic flow which is of direct importance to the climate system: it transports heat meridionally and regulates the exchange of CO2 with the atmosphere. The MOC is forced by wind and heat and freshwater fluxes at the surface and turbulent mixing in the ocean interior. A number of conceptual theories for the sensitivity of the MOC to changes in forcing have recently been developed and tested with idealized numerical models. However, the skill of the simple conceptual theories to describe the MOC simulated with higher complexity global models remains largely unknown. In this study, we present a systematic comparison of theoretical and modelled sensitivity of the MOC and associated deep ocean stratification to vertical mixing and southern hemisphere westerlies. The results show that theories that simplify the ocean into a single-basin, zonally-symmetric box are generally in a good agreement with a realistic, global ocean circulation model. Some disagreement occurs in the abyssal ocean, where complex bottom topography is not taken into account by simple theories. Distinct regimes, where the MOC has a different sensitivity to wind or mixing, as predicted by simple theories, are also clearly shown by the global ocean model. The sensitivity of the Indo-Pacific, Atlantic, and global basins is analysed separately to validate the conceptual understanding of the upper and lower overturning cells in the theory.
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NASA Astrophysics Data System (ADS)
Voldoire, Aurore; Decharme, Bertrand; Pianezze, Joris; Lebeaupin Brossier, Cindy; Sevault, Florence; Seyfried, Léo; Garnier, Valérie; Bielli, Soline; Valcke, Sophie; Alias, Antoinette; Accensi, Mickael; Ardhuin, Fabrice; Bouin, Marie-Noëlle; Ducrocq, Véronique; Faroux, Stéphanie; Giordani, Hervé; Léger, Fabien; Marsaleix, Patrick; Rainaud, Romain; Redelsperger, Jean-Luc; Richard, Evelyne; Riette, Sébastien
2017-11-01
This study presents the principles of the new coupling interface based on the SURFEX multi-surface model and the OASIS3-MCT coupler. As SURFEX can be plugged into several atmospheric models, it can be used in a wide range of applications, from global and regional coupled climate systems to high-resolution numerical weather prediction systems or very fine-scale models dedicated to process studies. The objective of this development is to build and share a common structure for the atmosphere-surface coupling of all these applications, involving on the one hand atmospheric models and on the other hand ocean, ice, hydrology, and wave models. The numerical and physical principles of SURFEX interface between the different component models are described, and the different coupled systems in which the SURFEX OASIS3-MCT-based coupling interface is already implemented are presented.
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A Heuristic Approach to Global Landslide Susceptibility Mapping
NASA Technical Reports Server (NTRS)
Stanley, Thomas; Kirschbaum, Dalia B.
2017-01-01
Landslides can have significant and pervasive impacts to life and property around the world. Several attempts have been made to predict the geographic distribution of landslide activity at continental and global scales. These efforts shared common traits such as resolution, modeling approach, and explanatory variables. The lessons learned from prior research have been applied to build a new global susceptibility map from existing and previously unavailable data. Data on slope, faults, geology, forest loss, and road networks were combined using a heuristic fuzzy approach. The map was evaluated with a Global Landslide Catalog developed at the National Aeronautics and Space Administration, as well as several local landslide inventories. Comparisons to similar susceptibility maps suggest that the subjective methods commonly used at this scale are, for the most part, reproducible. However, comparisons of landslide susceptibility across spatial scales must take into account the susceptibility of the local subset relative to the larger study area. The new global landslide susceptibility map is intended for use in disaster planning, situational awareness, and for incorporation into global decision support systems.
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Global patterns of groundwater table depth.
Fan, Y; Li, H; Miguez-Macho, G
2013-02-22
Shallow groundwater affects terrestrial ecosystems by sustaining river base-flow and root-zone soil water in the absence of rain, but little is known about the global patterns of water table depth and where it provides vital support for land ecosystems. We present global observations of water table depth compiled from government archives and literature, and fill in data gaps and infer patterns and processes using a groundwater model forced by modern climate, terrain, and sea level. Patterns in water table depth explain patterns in wetlands at the global scale and vegetation gradients at regional and local scales. Overall, shallow groundwater influences 22 to 32% of global land area, including ~15% as groundwater-fed surface water features and 7 to 17% with the water table or its capillary fringe within plant rooting depths.
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Changing global essential medicines norms to improve access to AIDS treatment: Lessons from Brazil
Nunn, A.; Fonseca, E. Da; Gruskin, S.
2009-01-01
Brazil's large-scale, successful HIV/AIDS treatment programme is considered by many to be a model for other developing countries aiming to improve access to AIDS treatment. Far less is known about Brazil's important role in changing global norms related to international pharmaceutical policy, particularly international human rights, health and trade policies governing access to essential medicines. Prompted by Brazil's interest in preserving its national AIDS treatment policies during World Trade Organisation trade disputes with the USA, these efforts to change global essential medicines norms have had important implications for other countries, particularly those scaling up AIDS treatment. This paper analyses Brazil's contributions to global essential medicines policy and explains the relevance of Brazil's contributions to global health policy today. PMID:19333805
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NASA Astrophysics Data System (ADS)
Yeh, P. J. F.; Chen, Y.; Lo, M. H.; Wada, Y.; Famiglietti, J. S.; Reager, J. T., II; Zhang, C.; Wu, R. J.
2017-12-01
Groundwater depletion (GWD) is an anthropogenic driver of changes in terrestrial water storage (TWS). Despite small in magnitudes comparing to most terrestrial hydrologic fluxes, it has important long-term contributions to global sea level rise (SLR). Past studies on the evaluation of the contributions from GWD to SLR were generally limited to a global-scale context and a long-term average perspective. This study examines the impacts of GWD on both terrestrial and atmospheric water balances and quantify the respective contribution to global sea level rise (SLR) using a global climate modelling approach. The annual contributions to global SLR from each continent during the modelling period 1900-1999 are quantified and compared. The contribution from each continent can be decomposed into a direct effect via the change in continental river discharges (R) and an indirect effect via the change in atmosphere water vapour convergence from ocean to land (C). An increase in R and a reduction in C would contribute positively to global SLR. The contribution due to GWD to SLR is compared with the contribution due to natural variability of TWS. Through this study, different dynamics and mechanisms responsible for the GWD contribution to SLR in different continents and time horizons can be identified for better understanding this globally significant environmental issue under warming climate.
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Biodiversity and ecosystem stability across scales in metacommunities
Wang, Shaopeng; Loreau, Michel
2016-01-01
Although diversity-stability relationships have been extensively studied in local ecosystems, the global biodiversity crisis calls for an improved understanding of these relationships in a spatial context. Here we use a dynamical model of competitive metacommunities to study the relationships between species diversity and ecosystem variability across scales. We derive analytic relationships under a limiting case; these results are extended to more general cases with numerical simulations. Our model shows that, while alpha diversity decreases local ecosystem variability, beta diversity generally contributes to increasing spatial asynchrony among local ecosystems. Consequently, both alpha and beta diversity provide stabilizing effects for regional ecosystems, through local and spatial insurance effects, respectively. We further show that at the regional scale, the stabilizing effect of biodiversity increases as spatial environmental correlation increases. Our findings have important implications for understanding the interactive effects of global environmental changes (e.g. environmental homogenization) and biodiversity loss on ecosystem sustainability at large scales. PMID:26918536
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Measurement of Global Radiation using Photovoltaic Panels
NASA Astrophysics Data System (ADS)
Veroustraete, Frank; Bronders, Jan; Lefevre, Filip; Mensink, Clemens
2014-05-01
The Vito Unit - Environmental and Spatial Aspects (RMA) - for many of its models makes use of global solar radiation. From this viewpoint and also from the notion that this variable is seldom measured or available at the local scale and at high multi-temporal frequencies, it can be stated that many models are fed with low quality estimates of global solar radiation at the local to regional scales. A project was initiated called SUNSPIDER with the following objective. To make use of photovoltaic solar panels to measure solar radiation at the highest spatio-temporal resolution, from the local to the regional scales and from minutes to years. To integrate the measured solar fields in different application fields like, plant systems and agriculture, agro-meteorology and hydrology and last but not least solar energy applications. In Belgium about 250.000 PV installations have been built leading to about 6% electric power supply from photovoltaics on a yearly basis. Last year in June, the supply reached a peak of more than 20% of the total power input on the Belgian grid. A database of Belgian residential solar panel sites will be compiled. The database will serve as an input to an inverted PV model to be able to perform radiation calculations specifically for each of the validated panel sites based on minutely logged power data. Data acquisition for these sites will start each time a site is validated and hence imported in the database. Keywords: Photovoltaic Panels; PV modelling; Global Radiation.
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Wave Propagation in Non-Stationary Statistical Mantle Models at the Global Scale
NASA Astrophysics Data System (ADS)
Meschede, M.; Romanowicz, B. A.
2014-12-01
We study the effect of statistically distributed heterogeneities that are smaller than the resolution of current tomographic models on seismic waves that propagate through the Earth's mantle at teleseismic distances. Current global tomographic models are missing small-scale structure as evidenced by the failure of even accurate numerical synthetics to explain enhanced coda in observed body and surface waveforms. One way to characterize small scale heterogeneity is to construct random models and confront observed coda waveforms with predictions from these models. Statistical studies of the coda typically rely on models with simplified isotropic and stationary correlation functions in Cartesian geometries. We show how to construct more complex random models for the mantle that can account for arbitrary non-stationary and anisotropic correlation functions as well as for complex geometries. Although this method is computationally heavy, model characteristics such as translational, cylindrical or spherical symmetries can be used to greatly reduce the complexity such that this method becomes practical. With this approach, we can create 3D models of the full spherical Earth that can be radially anisotropic, i.e. with different horizontal and radial correlation functions, and radially non-stationary, i.e. with radially varying model power and correlation functions. Both of these features are crucial for a statistical description of the mantle in which structure depends to first order on the spherical geometry of the Earth. We combine different random model realizations of S velocity with current global tomographic models that are robust at long wavelengths (e.g. Meschede and Romanowicz, 2014, GJI submitted), and compute the effects of these hybrid models on the wavefield with a spectral element code (SPECFEM3D_GLOBE). We finally analyze the resulting coda waves for our model selection and compare our computations with observations. Based on these observations, we make predictions about the strength of unresolved small-scale structure and extrinsic attenuation.
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NASA Astrophysics Data System (ADS)
LI, T., II; Wu, P.; Steffen, H.; Wang, H.
2017-12-01
The global ice history model ICE-6G_C was constructed based on the laterally homogeneous earth model VM5a. The combined model of glacial isostatic adjustment (GIA) called ICE-6G_C (VM5a) fits global observations of GIA simultaneously well. However, seismic and geological observations clearly show that the Earth's mantle is laterally heterogeneous. Our aim therefore is to search for the best laterally heterogeneous viscosity models with ICE-6G_C ice history that is able to fit the global relative sea-level (RSL) data, the peak uplift rates (from GNSS) and peak g-dot rates (from the GRACE satellite mission) in Laurentia and Fennoscandia simultaneously. The Coupled Laplace-Finite Element Method is used to compute gravitationally self-consistent sea levels with time dependent coastlines and rotational feedback in addition to changes in deformation, gravity and the state of stress. As a start, the VM5a Earth model is used as the radial background viscosity structure but other radial background viscosity models will also be investigated. Lateral mantle viscosity structure is obtained by the superposition of the radial background viscosity and the lateral viscosity perturbations logarithmically. The latter is inferred from a seismic tomography model using a scaling relationship that takes into account the effects of anharmonicity, anelasticity and non-thermal effects. We will show that several laterally heterogeneous mantle viscosity models can fit the global sea level, GPS and GRACE data better than laterally homogeneous models, provided that the scaling relationship for mantle heterogeneity under northern Europe is allowed to be different from that under Laurentia. In addition, the effects of laterally heterogeneous lithosphere, as inferred from seismic tomography, and the lateral changes in sub-lithospheric properties will also be presented.
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A suite of global, cross-scale topographic variables for environmental and biodiversity modeling
NASA Astrophysics Data System (ADS)
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.
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Karst medium characterization and simulation of groundwater flow in Lijiang Riversed, China
NASA Astrophysics Data System (ADS)
Hu, B. X.
2015-12-01
It is important to study water and carbon cycle processes for water resource management, pollution prevention and global warming influence on southwest karst region of China. Lijiang river basin is selected as our study region. Interdisciplinary field and laboratory experiments with various technologies are conducted to characterize the karst aquifers in detail. Key processes in the karst water cycle and carbon cycle are determined. Based on the MODFLOW-CFP model, new watershed flow and carbon cycle models are developed coupled subsurface and surface water flow models, flow and chemical/biological models. Our study is focused on the karst springshed in Mao village. The mechanisms coupling carbon cycle and water cycle are explored. Parallel computing technology is used to construct the numerical model for the carbon cycle and water cycle in the small scale watershed, which are calibrated and verified by field observations. The developed coupling model for the small scale watershed is extended to a large scale watershed considering the scale effect of model parameters and proper model structure simplification. The large scale watershed model is used to study water cycle and carbon cycle in Lijiang rivershed, and to calculate the carbon flux and carbon sinks in the Lijiang river basin. The study results provide scientific methods for water resources management and environmental protection in southwest karst region corresponding to global climate change. This study could provide basic theory and simulation method for geological carbon sequestration in China karst region.
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Simulation of groundwater flow and evaluation of carbon sink in Lijiang Rivershed, China
NASA Astrophysics Data System (ADS)
Hu, Bill X.; Cao, Jianhua; Tong, Juxiu; Gao, Bing
2016-04-01
It is important to study water and carbon cycle processes for water resource management, pollution prevention and global warming influence on southwest karst region of China. Lijiang river basin is selected as our study region. Interdisciplinary field and laboratory experiments with various technologies are conducted to characterize the karst aquifers in detail. Key processes in the karst water cycle and carbon cycle are determined. Based on the MODFLOW-CFP model, new watershed flow and carbon cycle models are developed coupled subsurface and surface water flow models, flow and chemical/biological models. Our study is focused on the karst springshed in Mao village. The mechanisms coupling carbon cycle and water cycle are explored. Parallel computing technology is used to construct the numerical model for the carbon cycle and water cycle in the small scale watershed, which are calibrated and verified by field observations. The developed coupling model for the small scale watershed is extended to a large scale watershed considering the scale effect of model parameters and proper model structure simplification. The large scale watershed model is used to study water cycle and carbon cycle in Lijiang rivershed, and to calculate the carbon flux and carbon sinks in the Lijiang river basin. The study results provide scientific methods for water resources management and environmental protection in southwest karst region corresponding to global climate change. This study could provide basic theory and simulation method for geological carbon sequestration in China karst region.
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Global scale modeling of riverine sediment loads: tropical rivers in a global context
NASA Astrophysics Data System (ADS)
Cohen, Sagy; Syvitski, James; Kettner, Albert
2015-04-01
A global scale riverine sediment flux model (termed WBMsed) is introduced. The model predicts spatially and temporally explicit water, suspended sediment and nutrients flux in relatively high resolutions (6 arc-min and daily). Modeled riverine suspended sediment flux through global catchments is used in conjunction with observational data for 35 tropical basins to highlight key basin scaling relationships. A 50 year, daily model simulation illuminates how precipitation, relief, lithology and drainage basin area affect sediment load, yield and concentration. Tropical river systems, wherein much of a drainage basin experiences tropical climate are strongly influenced by the annual and inter-annual variations of the Inter-tropical Convergence Zone (ITCZ) and its derivative monsoonal winds, have comparatively low inter-annual variation in sediment yield. Rivers draining rainforests and those subjected to tropical monsoons typically demonstrate high runoff, but with notable exceptions. High rainfall intensities from burst weather events are common in the tropics. The release of rain-forming aerosols also appears to uniquely increase regional rainfall, but its geomorphic manifestation is hard to detect. Compared to other more temperate river systems, climate-driven tropical rivers do not appear to transport a disproportionate amount of particulate load to the world's oceans, and their warmer, less viscous waters are less competent. Multiple-year hydrographs reveal that seasonality is a dominant feature of most tropical rivers, but the rivers of Papua New Guinea are somewhat unique being less seasonally modulated. Local sediment yield within the Amazon is highest near the Andes, but decreases towards the ocean as the river's discharge is diluted by water influxes from sediment-deprived rainforest tributaries
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On the use of a physically-based baseflow timescale in land surface models.
NASA Astrophysics Data System (ADS)
Jost, A.; Schneider, A. C.; Oudin, L.; Ducharne, A.
2017-12-01
Groundwater discharge is an important component of streamflow and estimating its spatio-temporal variation in response to changes in recharge is of great value to water resource planning, and essential for modelling accurate large scale water balance in land surface models (LSMs). First-order representation of groundwater as a single linear storage element is frequently used in LSMs for the sake of simplicity, but requires a suitable parametrization of the aquifer hydraulic behaviour in the form of the baseflow characteristic timescale (τ). Such a modelling approach can be hampered by the lack of available calibration data at global scale. Hydraulic groundwater theory provides an analytical framework to relate the baseflow characteristics to catchment descriptors. In this study, we use the long-time solution of the linearized Boussinesq equation to estimate τ at global scale, as a function of groundwater flow length and aquifer hydraulic diffusivity. Our goal is to evaluate the use of this spatially variable and physically-based τ in the ORCHIDEE surface model in terms of simulated river discharges across large catchments. Aquifer transmissivity and drainable porosity stem from GLHYMPS high-resolution datasets whereas flow length is derived from an estimation of drainage density, using the GRIN global river network. ORCHIDEE is run in offline mode and its results are compared to a reference simulation using an almost spatially constant topographic-dependent τ. We discuss the limits of our approach in terms of both the relevance and accuracy of global estimates of aquifer hydraulic properties and the extent to which the underlying assumptions in the analytical method are valid.
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Three-dimensional Structure of the Milky Way Dust: Modeling of LAMOST Data
NASA Astrophysics Data System (ADS)
Li, Linlin; Shen, Shiyin; Hou, Jinliang; Yuan, Haibo; Xiang, Maosheng; Chen, Bingqiu; Huang, Yang; Liu, Xiaowei
2018-05-01
We present a three-dimensional modeling of the Milky Way dust distribution by fitting the value-added star catalog of the LAMOST spectral survey. The global dust distribution can be described by an exponential disk with a scale length of 3192 pc and a scale height of 103 pc. In this modeling, the Sun is located above the dust disk with a vertical distance of 23 pc. Besides the global smooth structure, two substructures around the solar position are also identified. The one located at 150° < l < 200° and ‑5° < b < ‑30° is consistent with the Gould Belt model of Gontcharov, and the other one located at 140° < l < 165° and 0° < b < 15° is associated with the Camelopardalis molecular clouds.
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NASA Astrophysics Data System (ADS)
Hogrefe, Christian; Liu, Peng; Pouliot, George; Mathur, Rohit; Roselle, Shawn; Flemming, Johannes; Lin, Meiyun; Park, Rokjin J.
2018-03-01
This study analyzes simulated regional-scale ozone burdens both near the surface and aloft, estimates process contributions to these burdens, and calculates the sensitivity of the simulated regional-scale ozone burden to several key model inputs with a particular emphasis on boundary conditions derived from hemispheric or global-scale models. The Community Multiscale Air Quality (CMAQ) model simulations supporting this analysis were performed over the continental US for the year 2010 within the context of the Air Quality Model Evaluation International Initiative (AQMEII) and Task Force on Hemispheric Transport of Air Pollution (TF-HTAP) activities. CMAQ process analysis (PA) results highlight the dominant role of horizontal and vertical advection on the ozone burden in the mid-to-upper troposphere and lower stratosphere. Vertical mixing, including mixing by convective clouds, couples fluctuations in free-tropospheric ozone to ozone in lower layers. Hypothetical bounding scenarios were performed to quantify the effects of emissions, boundary conditions, and ozone dry deposition on the simulated ozone burden. Analysis of these simulations confirms that the characterization of ozone outside the regional-scale modeling domain can have a profound impact on simulated regional-scale ozone. This was further investigated by using data from four hemispheric or global modeling systems (Chemistry - Integrated Forecasting Model (C-IFS), CMAQ extended for hemispheric applications (H-CMAQ), the Goddard Earth Observing System model coupled to chemistry (GEOS-Chem), and AM3) to derive alternate boundary conditions for the regional-scale CMAQ simulations. The regional-scale CMAQ simulations using these four different boundary conditions showed that the largest ozone abundance in the upper layers was simulated when using boundary conditions from GEOS-Chem, followed by the simulations using C-IFS, AM3, and H-CMAQ boundary conditions, consistent with the analysis of the ozone fields from the global models along the CMAQ boundaries. Using boundary conditions from AM3 yielded higher springtime ozone columns burdens in the middle and lower troposphere compared to boundary conditions from the other models. For surface ozone, the differences between the AM3-driven CMAQ simulations and the CMAQ simulations driven by other large-scale models are especially pronounced during spring and winter where they can reach more than 10 ppb for seasonal mean ozone mixing ratios and as much as 15 ppb for domain-averaged daily maximum 8 h average ozone on individual days. In contrast, the differences between the C-IFS-, GEOS-Chem-, and H-CMAQ-driven regional-scale CMAQ simulations are typically smaller. Comparing simulated surface ozone mixing ratios to observations and computing seasonal and regional model performance statistics revealed that boundary conditions can have a substantial impact on model performance. Further analysis showed that boundary conditions can affect model performance across the entire range of the observed distribution, although the impacts tend to be lower during summer and for the very highest observed percentiles. The results are discussed in the context of future model development and analysis opportunities.
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Climate Controls AM Fungal Distributions from Global to Local Scales
NASA Astrophysics Data System (ADS)
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 composition and root colonization, with weaker influences of plant identity and soil nutrients. These two studies across scales suggest prevailing effects of climate on AM fungal distributions. Thus, incorporating climate when forecasting future ranges of AM fungi will enhance predictions of AM fungal abundance and associated ecosystem functions.
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Traveling Weather Disturbances in Mars Southern Extratropics: Sway of the Great Impact Basins
NASA Technical Reports Server (NTRS)
Hollingsworth, Jeffery L.
2016-01-01
As on Earth, between late autumn and early spring on Mars middle and high latitudes within its atmosphere support strong mean thermal contrasts between the equator and poles (i.e. "baroclinicity"). Data collected during the Viking era and observations from both the Mars Global Surveyor (MGS) and Mars Reconnaissance Orbiter (MRO) indicate that this strong baroclinicity supports vigorous, large-scale eastward traveling weather systems (i.e. transient synoptic-period waves). Within a rapidly rotating, differentially heated, shallow atmosphere such as on Earth and Mars, such large-scale, extratropical weather disturbances are critical components of the global circulation. These wave-like disturbances act as agents in the transport of heat and momentum, and moreover generalized tracer quantities (e.g., atmospheric dust, water vapor and water-ice clouds) between low and high latitudes of the planet. The character of large-scale, traveling extratropical synoptic-period disturbances in Mars' southern hemisphere during late winter through early spring is investigated using a high-resolution Mars global climate model (Mars GCM). This global circulation model imposes interactively lifted (and radiatively active) dust based on a threshold value of the instantaneous surface stress. Compared to observations, the model exhibits a reasonable "dust cycle" (i.e. globally averaged, a more dusty atmosphere during southern spring and summer occurs). In contrast to their northern-hemisphere counterparts, southern synoptic-period weather disturbances and accompanying frontal waves have smaller meridional and zonal scales, and are far less intense synoptically. Influences of the zonally asymmetric (i.e. east-west varying) topography on southern large-scale weather disturbances are examined. Simulations that adapt Mars' full topography compared to simulations that utilize synthetic topographies emulating essential large-scale features of the southern middle latitudes indicate that Mars' transient barotropic/baroclinic eddies are significantly influenced by the great impact basins of this hemisphere (e.g., Argyre and Hellas). In addition, the occurrence of a southern storm zone in late winter and early spring is keyed particularly to the western hemisphere via orographic influences arising from the Tharsis highlands, and the Argyre and Hellas impact basins. Geographically localized transient-wave activity diagnostics are constructed that illuminate fundamental differences amongst such simulations and these are described.
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Traveling Weather Disturbances in Mars' Southern Extratropics: Sway of the Great Impact Basins
NASA Astrophysics Data System (ADS)
Hollingsworth, Jeffery L.
2016-04-01
As on Earth, between late autumn and early spring on Mars middle and high latitudes within its atmosphere support strong mean thermal contrasts between the equator and poles (i.e., "baroclinicity"). Data collected during the Viking era and observations from both the Mars Global Surveyor (MGS) and Mars Reconnaissance Orbiter (MRO) indicate that this strong baroclinicity supports vigorous, large-scale eastward traveling weather systems (i.e., transient synoptic-period waves). Within a rapidly rotating, differentially heated, shallow atmosphere such as on Earth and Mars, such large-scale, extratropical weather disturbances are critical components of the global circulation. These wave-like disturbances act as agents in the transport of heat and momentum, and moreover generalized tracer quantities (e.g., atmospheric dust, water vapor and water-ice clouds) between low and high latitudes of the planet. The character of large-scale, traveling extratropical synoptic-period disturbances in Mars' southern hemisphere during late winter through early spring is investigated using a high-resolution Mars global climate model (Mars GCM). This global circulation model imposes interactively lifted (and radiatively active) dust based on a threshold value of the instantaneous surface stress. Compared to observations, the model exhibits a reasonable "dust cycle" (i.e., globally averaged, a more dusty atmosphere during southern spring and summer occurs). In contrast to their northern-hemisphere counterparts, southern synoptic-period weather disturbances and accompanying frontal waves have smaller meridional and zonal scales, and are far less intense synoptically. Influences of the zonally asymmetric (i.e., east-west varying) topography on southern large-scale weather disturbances are examined. Simulations that adapt Mars' full topography compared to simulations that utilize synthetic topographies emulating essential large-scale features of the southern middle latitudes indicate that Mars' transient barotropic/baroclinic eddies are significantly influenced by the great impact basins of this hemisphere (e.g., Argyre and Hellas). In addition, the occurrence of a southern storm zone in late winter and early spring is keyed particularly to the western hemisphere via orographic influences arising from the Tharsis highlands, and the Argyre and Hellas impact basins. Geographically localized transient-wave activity diagnostics are constructed that illuminate fundamental differences amongst such simulations and these are described.
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Towards an purely data driven view on the global carbon cycle and its spatiotemporal variability
NASA Astrophysics Data System (ADS)
Zscheischler, Jakob; Mahecha, Miguel; Reichstein, Markus; Avitabile, Valerio; Carvalhais, Nuno; Ciais, Philippe; Gans, Fabian; Gruber, Nicolas; Hartmann, Jens; Herold, Martin; Jung, Martin; Landschützer, Peter; Laruelle, Goulven; Lauerwald, Ronny; Papale, Dario; Peylin, Philippe; Regnier, Pierre; Rödenbeck, Christian; Cuesta, Rosa Maria Roman; Valentini, Ricardo
2015-04-01
Constraining carbon (C) fluxes between the Earth's surface and the atmosphere at regional scale via observations is essential for understanding the Earth's carbon budget and predicting future atmospheric C concentrations. Carbon budgets have often been derived based on merging observations, statistical models and process-based models, for example in the Global Carbon Project (GCP). However, it would be helpful to derive global C budgets and fluxes at global scale as independent as possible from model assumptions to obtain an independent reference. Long-term in-situ measurements of land and ocean C stocks and fluxes have enabled the derivation of a new generation of data driven upscaled data products. Here, we combine a wide range of in-situ derived estimates of terrestrial and aquatic C fluxes for one decade. The data were produced and/or collected during the FP7 project GEOCARBON and include surface-atmosphere C fluxes from the terrestrial biosphere, fossil fuels, fires, land use change, rivers, lakes, estuaries and open ocean. By including spatially explicit uncertainties in each dataset we are able to identify regions that are well constrained by observations and areas where more measurements are required. Although the budget cannot be closed at the global scale, we provide, for the first time, global time-varying maps of the most important C fluxes, which are all directly derived from observations. The resulting spatiotemporal patterns of C fluxes and their uncertainties inform us about the needs for intensifying global C observation activities. Likewise, we provide priors for inversion exercises or to identify regions of high (and low) uncertainty of integrated C fluxes. We discuss the reasons for regions of high observational uncertainties, and for biases in the budget. Our data synthesis might also be used as empirical reference for other local and global C budgeting exercises.
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Thompson, Robert Stephen; Hostetler, Steven W.; Bartlein, Patrick J.; Anderson, Katherine H.
1998-01-01
Historical and geological data indicate that significant changes can occur in the Earth's climate on time scales ranging from years to millennia. In addition to natural climatic change, climatic changes may occur in the near future due to increased concentrations of carbon dioxide and other trace gases in the atmosphere that are the result of human activities. International research efforts using atmospheric general circulation models (AGCM's) to assess potential climatic conditions under atmospheric carbon dioxide concentrations of twice the pre-industrial level (a '2 X CO2' atmosphere) conclude that climate would warm on a global basis. However, it is difficult to assess how the projected warmer climatic conditions would be distributed on a regional scale and what the effects of such warming would be on the landscape, especially for temperate mountainous regions such as the Western United States. In this report, we present a strategy to assess the regional sensitivity to global climatic change. The strategy makes use of a hierarchy of models ranging from an AGCM, to a regional climate model, to landscape-scale process models of hydrology and vegetation. A 2 X CO2 global climate simulation conducted with the National Center for Atmospheric Research (NCAR) GENESIS AGCM on a grid of approximately 4.5o of latitude by 7.5o of longitude was used to drive the NCAR regional climate model (RegCM) over the Western United States on a grid of 60 km by 60 km. The output from the RegCM is used directly (for hydrologic models) or interpolated onto a 15-km grid (for vegetation models) to quantify possible future environmental conditions on a spatial scale relevant to policy makers and land managers.
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NASA Technical Reports Server (NTRS)
Lettenmaier, Dennis P. (Editor); Rind, D. (Editor)
1992-01-01
The present conference on the hydrological aspects of global climate change discusses land-surface schemes for future climate models, modeling of the land-surface boundary in climate models as a composite of independent vegetation, a land-surface hydrology parameterizaton with subgrid variability for general circulation models, and conceptual aspects of a statistical-dynamical approach to represent landscape subgrid-scale heterogeneities in atmospheric models. Attention is given to the impact of global warming on river runoff, the influence of atmospheric moisture transport on the fresh water balance of the Atlantic drainage basin, a comparison of observations and model simulations of tropospheric water vapor, and the use of weather types to disaggregate the prediction of general circulation models. Topics addressed include the potential response of an Arctic watershed during a period of global warming and the sensitivity of groundwater recharge estimates to climate variability and change.
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The scaling structure of the global road network
Giometto, Andrea; Shai, Saray; Bertuzzo, Enrico; Mucha, Peter J.; Rinaldo, Andrea
2017-01-01
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. PMID:29134071
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The scaling structure of the global road network.
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.
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Global quantum discord and matrix product density operators
NASA Astrophysics Data System (ADS)
Huang, Hai-Lin; Cheng, Hong-Guang; Guo, Xiao; Zhang, Duo; Wu, Yuyin; Xu, Jian; Sun, Zhao-Yu
2018-06-01
In a previous study, we have proposed a procedure to study global quantum discord in 1D chains whose ground states are described by matrix product states [Z.-Y. Sun et al., Ann. Phys. 359, 115 (2015)]. In this paper, we show that with a very simple generalization, the procedure can be used to investigate quantum mixed states described by matrix product density operators, such as quantum chains at finite temperatures and 1D subchains in high-dimensional lattices. As an example, we study the global discord in the ground state of a 2D transverse-field Ising lattice, and pay our attention to the scaling behavior of global discord in 1D sub-chains of the lattice. We find that, for any strength of the magnetic field, global discord always shows a linear scaling behavior as the increase of the length of the sub-chains. In addition, global discord and the so-called "discord density" can be used to indicate the quantum phase transition in the model. Furthermore, based upon our numerical results, we make some reliable predictions about the scaling of global discord defined on the n × n sub-squares in the lattice.
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NASA Astrophysics Data System (ADS)
Shastri, Hiteshri; Ghosh, Subimal; Karmakar, Subhankar
2017-02-01
Forecasting of extreme precipitation events at a regional scale is of high importance due to their severe impacts on society. The impacts are stronger in urban regions due to high flood potential as well high population density leading to high vulnerability. Although significant scientific improvements took place in the global models for weather forecasting, they are still not adequate at a regional scale (e.g., for an urban region) with high false alarms and low detection. There has been a need to improve the weather forecast skill at a local scale with probabilistic outcome. Here we develop a methodology with quantile regression, where the reliably simulated variables from Global Forecast System are used as predictors and different quantiles of rainfall are generated corresponding to that set of predictors. We apply this method to a flood-prone coastal city of India, Mumbai, which has experienced severe floods in recent years. We find significant improvements in the forecast with high detection and skill scores. We apply the methodology to 10 ensemble members of Global Ensemble Forecast System and find a reduction in ensemble uncertainty of precipitation across realizations with respect to that of original precipitation forecasts. We validate our model for the monsoon season of 2006 and 2007, which are independent of the training/calibration data set used in the study. We find promising results and emphasize to implement such data-driven methods for a better probabilistic forecast at an urban scale primarily for an early flood warning.
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NASA Technical Reports Server (NTRS)
Li, Yong; Moorthi, S.; Bates, J. Ray; Suarez, Max J.
1994-01-01
High order horizontal diffusion of the form K Delta(exp 2m) is widely used in spectral models as a means of preventing energy accumulation at the shortest resolved scales. In the spectral context, an implicit formation of such diffusion is trivial to implement. The present note describes an efficient method of implementing implicit high order diffusion in global finite difference models. The method expresses the high order diffusion equation as a sequence of equations involving Delta(exp 2). The solution is obtained by combining fast Fourier transforms in longitude with a finite difference solver for the second order ordinary differential equation in latitude. The implicit diffusion routine is suitable for use in any finite difference global model that uses a regular latitude/longitude grid. The absence of a restriction on the timestep makes it particularly suitable for use in semi-Lagrangian models. The scale selectivity of the high order diffusion gives it an advantage over the uncentering method that has been used to control computational noise in two-time-level semi-Lagrangian models.
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NASA Astrophysics Data System (ADS)
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 precipitation/evaporation may be up to 10 Wm-2 (about 0.35 mm day-1) larger than the estimate obtained from GPCP. While the main part of this discrepancy is thought to be due to the underestimation of remotely-sensed ocean precipitation, there is also considerable uncertainty about 'unobserved' precipitation over land, in particular in the form of snow in regions of high latitude/altitude. We aim to contribute to this discussion, at least at a qualitative level, by considering case studies of how area-averaged mountain precipitation is represented in different observational datasets and by HadGEM3-GA3 at different resolutions. Our results show that the AGCM simulates considerably more orographic precipitation at higher resolution. We find this at the global scale both for the winter and summer hemispheres, as well as in several case studies in mid-latitude regions. Gridded observations based on gauge measurements generally capture the mesoscale spatial variability of precipitation, but differ strongly from one another in the magnitude of area-averaged precipitation, so that they are of very limited use for evaluating this aspect of the modelled climate. We are currently conducting a sensitivity experiment (coarse-grained orography in high-resolution HadGEM3) to further investigate the resolution sensitivity seen in the model.
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Reduced-Order Biogeochemical Flux Model for High-Resolution Multi-Scale Biophysical Simulations
NASA Astrophysics Data System (ADS)
Smith, Katherine; Hamlington, Peter; Pinardi, Nadia; Zavatarelli, Marco
2017-04-01
Biogeochemical tracers and their interactions with upper ocean physical processes such as submesoscale circulations and small-scale turbulence are critical for understanding the role of the ocean in the global carbon cycle. These interactions can cause small-scale spatial and temporal heterogeneity in tracer distributions that can, in turn, greatly affect carbon exchange rates between the atmosphere and interior ocean. For this reason, it is important to take into account small-scale biophysical interactions when modeling the global carbon cycle. However, explicitly resolving these interactions in an earth system model (ESM) is currently infeasible due to the enormous associated computational cost. As a result, understanding and subsequently parameterizing how these small-scale heterogeneous distributions develop and how they relate to larger resolved scales is critical for obtaining improved predictions of carbon exchange rates in ESMs. In order to address this need, we have developed the reduced-order, 17 state variable Biogeochemical Flux Model (BFM-17) that follows the chemical functional group approach, which allows for non-Redfield stoichiometric ratios and the exchange of matter through units of carbon, nitrate, and phosphate. This model captures the behavior of open-ocean biogeochemical systems without substantially increasing computational cost, thus allowing the model to be combined with computationally-intensive, fully three-dimensional, non-hydrostatic large eddy simulations (LES). In this talk, we couple BFM-17 with the Princeton Ocean Model and show good agreement between predicted monthly-averaged results and Bermuda testbed area field data (including the Bermuda-Atlantic Time-series Study and Bermuda Testbed Mooring). Through these tests, we demonstrate the capability of BFM-17 to accurately model open-ocean biochemistry. Additionally, we discuss the use of BFM-17 within a multi-scale LES framework and outline how this will further our understanding of turbulent biophysical interactions in the upper ocean.
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Reduced-Order Biogeochemical Flux Model for High-Resolution Multi-Scale Biophysical Simulations
NASA Astrophysics Data System (ADS)
Smith, K.; Hamlington, P.; Pinardi, N.; Zavatarelli, M.; Milliff, R. F.
2016-12-01
Biogeochemical tracers and their interactions with upper ocean physical processes such as submesoscale circulations and small-scale turbulence are critical for understanding the role of the ocean in the global carbon cycle. These interactions can cause small-scale spatial and temporal heterogeneity in tracer distributions which can, in turn, greatly affect carbon exchange rates between the atmosphere and interior ocean. For this reason, it is important to take into account small-scale biophysical interactions when modeling the global carbon cycle. However, explicitly resolving these interactions in an earth system model (ESM) is currently infeasible due to the enormous associated computational cost. As a result, understanding and subsequently parametrizing how these small-scale heterogeneous distributions develop and how they relate to larger resolved scales is critical for obtaining improved predictions of carbon exchange rates in ESMs. In order to address this need, we have developed the reduced-order, 17 state variable Biogeochemical Flux Model (BFM-17). This model captures the behavior of open-ocean biogeochemical systems without substantially increasing computational cost, thus allowing the model to be combined with computationally-intensive, fully three-dimensional, non-hydrostatic large eddy simulations (LES). In this talk, we couple BFM-17 with the Princeton Ocean Model and show good agreement between predicted monthly-averaged results and Bermuda testbed area field data (including the Bermuda-Atlantic Time Series and Bermuda Testbed Mooring). Through these tests, we demonstrate the capability of BFM-17 to accurately model open-ocean biochemistry. Additionally, we discuss the use of BFM-17 within a multi-scale LES framework and outline how this will further our understanding of turbulent biophysical interactions in the upper ocean.
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NASA Astrophysics Data System (ADS)
Yoshimura, K.; Oki, T.; Ohte, N.; Kanae, S.; Ichiyanagi, K.
2004-12-01
A simple water isotope circulation model on a global scale that includes a Rayleigh equation and the use of _grealistic_h external meteorological forcings estimates short-term variability of precipitation 18O. The results are validated by Global Network of Isotopes in Precipitation (GNIP) monthly observations and by daily observations at three sites in Thailand. This good agreement highlights the importance of large scale transport and mixing of vapor masses as a control factor for spatial and temporal variability of precipitation isotopes, rather than in-cloud micro processes. It also indicates the usefulness of the model and the isotopes observation databases for evaluation of two-dimensional atmospheric water circulation fields in forcing datasets. In this regard, two offline simulations for 1978-1993 with major reanalyses, i.e. NCEP and ERA15, were implemented, and the results show that, over Europe ERA15 better matched observations at both monthly and interannual time scales, mainly owing to better precipitation fields in ERA15, while in the tropics both produced similarly accurate isotopic fields. The isotope analyses diagnose accuracy of two-dimensional water circulation fields in datasets with a particular focus on precipitation processes.
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Is Global Warming Accelerating?
NASA Astrophysics Data System (ADS)
Shukla, J.; Delsole, T. M.; Tippett, M. K.
2009-12-01
A global pattern that fluctuates naturally on decadal time scales is identified in climate simulations and observations. This newly discovered component, called the Global Multidecadal Oscillation (GMO), is related to the Atlantic Meridional Oscillation and shown to account for a substantial fraction of decadal fluctuations in the observed global average sea surface temperature. IPCC-class climate models generally underestimate the variance of the GMO, and hence underestimate the decadal fluctuations due to this component of natural variability. Decomposing observed sea surface temperature into a component due to anthropogenic and natural radiative forcing plus the GMO, reveals that most multidecadal fluctuations in the observed global average sea surface temperature can be accounted for by these two components alone. The fact that the GMO varies naturally on multidecadal time scales implies that it can be predicted with some skill on decadal time scales, which provides a scientific rationale for decadal predictions. Furthermore, the GMO is shown to account for about half of the warming in the last 25 years and hence a substantial fraction of the recent acceleration in the rate of increase in global average sea surface temperature. Nevertheless, in terms of the global average “well-observed” sea surface temperature, the GMO can account for only about 0.1° C in transient, decadal-scale fluctuations, not the century-long 1° C warming that has been observed during the twentieth century.
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Mechanisms of the global electric circuit and lightning variability on the ENSO time scale
NASA Astrophysics Data System (ADS)
Mareev, Evgeny; Volodin, Evgeny; Slyunyaev, Nikolay
2017-04-01
Many studies of lightning activity on the El Niño-Southern Oscillation (ENSO) time scale show increased activity over tropical land areas during the warm El Niño phase (e.g., Satori et al., 2009; Price, 2009). The mechanisms of this variability—particularly in terms of its role in the global electric circuit (GEC)—are still under debate (e.g., Williams and Mareev, 2014). In this study a general circulation model of the atmosphere and ocean INMCM4.0 (Institute of Numerical Mathematics Coupled Model) is used for modelling the GEC variability on the ENSO time scale. The ionospheric potential (IP) and the lightning flash rate are calculated to study regional peculiarities and possible mechanisms of lightning variation. The IP parameterisation is used (Mareev and Volodin, 2014) which takes into account quasi-stationary currents of electrified clouds (including thunderstorms) as principal contributors into the DC global circuit. The account of conductivity variation in the IP parameterisation is suggested based on the approach realised in (Slyunyaev et al., 2014). Comparison of simulation results with the observational data on lightning activity on the ENSO time scale is discussed. Numerical simulations suggest that the inter-annual IP variability is low and does not exceed 1% of the mean value, being tightly correlated with the mean sea surface temperature (SST) in the Pacific Ocean (180W-100W, 5S-5N—El Niño area). The IP maximum corresponds to the SST minimum. This result can be explained taking into account that during El Niño (positive temperature anomaly) precipitations in the equatorial part of the Pacific increase while in other tropic zones including the land areas they decrease. Comparison of simulation results with the observational data on lightning activity on the ENSO time scale is discussed. During the El Niño period in the model, the mean aerosol content in the atmosphere decrease, which is caused by the weakening of the winds over Sahara and South-West Asia lifting dust into the atmosphere. Taking into consideration the decrease in the number of thunderstorms, this does not explain the observed global lightning variation. As another possible explanation for the enhanced El Niño lightning activity, the variation of the atmospheric aerosols and cloud condensation nuclei due to fires is discussed. The work was supported by a grant from the Government of the Russian Federation (contract no. 14.B25.31.0023) and by RFBR grant no. 16-05-01086. References Mareev E.A., Volodin E.M. (2014), Variation of the global electric circuit and ionospheric potential in a general circulation model, Geophys. Res. Lett., V. 41, P. 9009-9016. Sátori G., Williams E., Lemperger I. (2009), Variability of global lightning activity on the ENSO time scale, Atmos. Res., V. 91, P. 500-507. Price C. (2009), Will a drier climate result in a more lightning?, Atmos. Res., V. 91, P. 479-484. Williams E.R., Mareev E.A. (2014), Recent progress on the global electrical circuit, Atmos. Res., V. 135-136, P. 208-227. Slyunyaev N.N., Mareev E.A., Kalinin A.V., Zhidkov A.A. (2014), Influence of large-scale conductivity inhomogeneities in the atmosphere on the global electric circuit, J. Atmos. Sci., V. 71, P. 4382-4396.
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Large Scale Skill in Regional Climate Modeling and the Lateral Boundary Condition Scheme
NASA Astrophysics Data System (ADS)
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 limited in view of the integrations having being done only for 10-day forecasts. Even so, one should note that they are among very few done using forecast as opposed to reanalysis or analysis global driving data. Our results suggest that (1) running the Eta as an RCM no significant loss of large-scale kinetic energy with time seems to be taking place; (2) no disadvantage from using the Eta LBC scheme compared to the relaxation scheme is seen, while enjoying the advantage of the scheme being significantly less demanding than the relaxation given that it needs driver model fields at the outermost domain boundary only; and (3) the Eta RCM skill in forecasting large scales, with no large scale nudging, seems to be just about the same as that of the driver model, or, in the terminology of Castro et al., the Eta RCM does not lose "value of the large scale" which exists in the larger global analyses used for the initial condition and for verification.
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A new, accurate, global hydrography data for remote sensing and modelling of river hydrodynamics
NASA Astrophysics Data System (ADS)
Yamazaki, D.
2017-12-01
A high-resolution hydrography data is an important baseline data for remote sensing and modelling of river hydrodynamics, given the spatial scale of river network is much smaller than that of land hydrology or atmosphere/ocean circulations. For about 10 years, HydroSHEDS, developed based on the SRTM3 DEM, has been the only available global-scale hydrography data. However, the data availability at the time of HydroSHEDS development limited the quality of the represented river networks. Here, we developed a new global hydrography data using latest geodata such as the multi-error-removed elevation data (MERIT DEM), Landsat-based global water body data (GSWO & G3WBM), cloud-sourced open geography database (OpenStreetMap). The new hydrography data covers the entire globe (including boreal regions above 60N), and it represents more detailed structure of the world river network and contains consistent supplementary data layers such as hydrologically adjusted elevations and river channel width. In the AGU meeting, the developing methodology, assessed quality, and potential applications of the new global hydrography data will be introduced.
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NMMB/BSC-DUST: an online mineral dust atmospheric model from meso to global scales
NASA Astrophysics Data System (ADS)
Haustein, K.; Pérez, C.; Jorba, O.; Baldasano, J. M.; Janjic, Z.; Black, T.; Nickovic, S.
2009-04-01
While mineral dust distribution and effects are important at global scales, they strongly depend on dust emissions that are controlled on small spatial and temporal scales. Most global dust models use prescribed wind fields provided by meteorological centers (e.g., NCEP and ECMWF) and their spatial resolution is currently never better than about 1°×1°. Regional dust models offer substantially higher resolution (10-20 km) and are typically coupled with weather forecast models that simulate processes that GCMs either cannot resolve or can resolve only poorly. These include internal circulation features such as the low-level nocturnal jet which is a crucial feature for dust emission in several dust ‘hot spot' sources in North Africa. Based on our modeling experience with the BSC-DREAM regional forecast model (http://www.bsc.es/projects/earthscience/DREAM/) we are currently implementing an improved mineral dust model [Pérez et al., 2008] coupled online with the new global/regional NMMB atmospheric model under development in NOAA/NCEP/EMC [Janjic, 2005]. The NMMB is an evolution of the operational WRF-NMME extending from meso to global scales. The NMMB will become the next-generation NCEP model for operational weather forecast in 2010. The corresponding unified non-hydrostatic dynamical core ranges from meso to global scale allowing regional and global simulations. It has got an add-on non-hydrostatic module and it is based on the Arakawa B-grid and hybrid pressure-sigma vertical coordinates. NMMB is fully embedded into the Earth System Modeling Framework (ESMF), treating dynamics and physics separately and coupling them easily within the ESMF structure. Our main goal is to provide global dust forecasts up to 7 days at mesoscale resolutions. New features of the model include a physically-based dust emission scheme after White [1979], Iversen and White [1982] and Marticorena and Bergametti [1995] that takes the effects of saltation and sandblasting into account. Viscous sublayer approach [Janjic, 1994] for dust injection in the lower atmosphere is maintained as applied in DREAM [Nickovic et al., 2001]. Soil moisture effects are considered following Fecan et al. [1999]. A new source function for the land surface is calculated using the USGS 1km landuse database, the NESDIS 5-years monthly climatology for the vegetation fraction, and preferential source areas according the topographic approach after Ginoux et al. [2001]. Furthermore, 4 top soil texture classes (coarse sand, fine/medium sand, silt, clay) are introduced, based on the new STASGO-FAO 1km soil database and modified following Tegen et al. [2002]. The dry deposition scheme accounts for the effects of sedimentation and turbulent mixout following the approach of Giorgi [1986]. Finally, in-cloud and below-cloud wet scavenging for grid-scale and convective precipitation is applied following Slinn [1983; 1984] and Loosmore and Cederwall [2004]. Dust radiative feedback on meteorology is not yet considered. In order to explore the assets and drawbacks of the new model, we perform global simulations of the dust cycle at 0.3°x0.45° to demonstrate the ability of the model to capture the large scale and seasonal patterns. These fundamental evaluations serve as starting point for further testing as well as future developments of the NMMb-DUST. In a second step, we study the behavior of the model during the SAMUM-I phase [Haustein et al., 2009] and the BODEX campaign [Todd et al., 2008], focusing on how the model reproduces moist convection and low level jet in North Africa at mesoscale resolutions. References: Fecan, F., B. Marticorena and G. Bergametti. (1999). Parameterization of the increase of the aeolian erosion threshold wind friction velocity due to soil moisture for arid and semi arid areas. Annales Geophysicae, 17, 149-157. Ginoux, P. et al. (2001). Sources and distribution of dust aerosols simulated with the GOCART model. J. Geophys. Res., 106, D17, 20255-20273. Giorgi, F. (1986). A particle dry-deposition parameterization scheme for use in tracer transport models. J. Geophys. Res., 91, 9794-9804. Haustein, K. et al. (2009). Regional dust model performance during SAMUM-I 2006. Geophys. Res. Letters, in press. Iversen, J.D. and B. R. White (1982). Saltation threshold on Earth, Mars and Venus. Sedimentology, 29, 111-119. Janjic, Z. I. (1994). The Step-Mountain Eta Coordinate Model: Further Developments of the Convection, Viscous Sublayer, and Turbulence Closure Schemes. Monthly Weather Review, 122, 927-945. Janjic, Z. I. (2005). A unified model approach from meso to global scales. Geophysical Research Abstracts, 7, 05582, 2005, EGU05-A-05582. Loosmore, G. A. and Cederwall, R. T. (2004). Precipitation scavenging of atmospheric aerosols for emergency response applications: testing an updated model with new real-time data. Atmospheric Environment, 38, 993-1003. Marticorena, B. and G. Bergametti (1995). Modeling the atmospheric dust cycle: 1. Design of a soil-derived dust emission scheme. J. Geophys. Res., 100, D8, 16415-16430. Nickovic, S., G. Kallos, A. Papadopoulos, and O. Kakaliagou (2001). A model for prediction of desert dust cycle in the atmosphere. Journal of Geophysical Research 106, D16, 18113-18129. Pérez, C. et al. (2008). An online mineral dust model within the global/regional NMMB: Current progress and plans. AGU Fall Meeting, 14-19 December 2008, San Francisco, USA. Slinn, W. G. N. (1983). A potpourri of deposition and resuspension questions. In: Pruppacher, Semonin and Slinn (Editors), Precip. Scavenging., Dry Deposition, and Resuspension. Elsevier, New York (1983), 1361-1416. Slinn, W.G.N. (1984). Precipitation scavenging. In: Randerson, D. (Editor), Atmospheric Science and Power Production. OSTI, Oak Ridge, 466-532. Tegen, I. et al. (2002). Impact of vegetation and preferential source areas on global dust aerosol: Results from a model study. J. Geophys. Res., 107, D21, doi:10.1029/2001JD000963. Todd, M. (2008). Quantifying uncertainty in estimates of mineral dust flux: An intercomparison of model performance over the Bodele Depression, northern Chad. J. Geophys. Res., 113, D24107, doi:10.1029/2008JD010476. White, B. (1979). Soil transport by winds on Mars. J. Geophys. Res., 84, 4643-4651.
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NASA Astrophysics Data System (ADS)
Sinha, T.; Gangodagamage, C.; Ale, S.; Frazier, A. G.; Giambelluca, T. W.; Kumagai, T.; Nakai, T.; Sato, H.
2017-12-01
Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs.
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NASA Technical Reports Server (NTRS)
Bretherton, Christopher S.
2002-01-01
The goal of this project was to compare observations of marine and arctic boundary layers with: (1) parameterization systems used in climate and weather forecast models; and (2) two and three dimensional eddy resolving (LES) models for turbulent fluid flow. Based on this comparison, we hoped to better understand, predict, and parameterize the boundary layer structure and cloud amount, type, and thickness as functions of large scale conditions that are predicted by global climate models. The principal achievements of the project were as follows: (1) Development of a novel boundary layer parameterization for large-scale models that better represents the physical processes in marine boundary layer clouds; and (2) Comparison of column output from the ECMWF global forecast model with observations from the SHEBA experiment. Overall the forecast model did predict most of the major precipitation events and synoptic variability observed over the year of observation of the SHEBA ice camp.
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Fast and Slow Precipitation Responses to Individual Climate Forcers: A PDRMIP Multimodel Study
NASA Technical Reports Server (NTRS)
Samset, B. H.; Myhre, G.; Forster, P.M.; Hodnebrog, O.; Andrews, T.; Faluvegi, G.; Flaschner, D.; Kasoar, M.; Kharin, V.; Kirkevag, A.;
2016-01-01
Precipitation is expected to respond differently to various drivers of anthropogenic climate change. We present the first results from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), where nine global climate models have perturbed CO2, CH4, black carbon, sulfate, and solar insolation. We divide the resulting changes to global mean and regional precipitation into fast responses that scale with changes in atmospheric absorption and slow responses scaling with surface temperature change. While the overall features are broadly similar between models, we find significant regional intermodel variability, especially over land. Black carbon stands out as a component that may cause significant model diversity in predicted precipitation change. Processes linked to atmospheric absorption are less consistently modeled than those linked to top-of-atmosphere radiative forcing. We identify a number of land regions where the model ensemble consistently predicts that fast precipitation responses to climate perturbations dominate over the slow, temperature-driven responses.
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NASA Astrophysics Data System (ADS)
Dowell, M.; Moore, T.; Follows, M.; Dutkiewicz, S.
2006-12-01
In recent years there has been significant progress both in the use of satellite ocean colour remote sensing and coupled hydrodynamic biological models for producing maps of different dominant phytoplankton groups in the global ocean. In parallel to these initiatives, there is ongoing research largely following on from Alan Longhurst's seminal work on defining a template of distinct ecological and biogeochemical provinces for the oceans based on their physical and biochemical characteristics. For these products and models to be of maximum use in their subsequent inclusion in re-analysis and climate scale models, there is a need to understand how the "observed" distributions of dominant phytoplankton (realized niche) coincide with of the environmental constraints in which they occur (fundamental niche). In the current paper, we base our analysis on the recently published results on the distribution of dominant phytoplankton species at global scale, resulting both from satellite and model analysis. Furthermore, we will present research in defining biogeochemical provinces using satellite and model data inputs and a fuzzy logic based approach. This will be compared with ongoing modelling efforts, which include competitive exclusion and therefore compatible with the definition of the realized ecological niche, to define the emergent distribution of dominant phytoplankton species. Ultimately we investigate the coherence of these two distinct approaches in studying phytoplankton distributions and propose the significance of this in the context of modelling and analysis at various scales.
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Hydrodynamic modelling and global datasets: Flow connectivity and SRTM data, a Bangkok case study.
NASA Astrophysics Data System (ADS)
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 that important subgrid processes are missing from hydrodynamic models leading to poor model predictive capabilities. Specifically here, the issue of flow connectivity during flood events is explored using geostatistical techniques to quantify the change of flow connectivity on floodplains due to grid rescaling methods. We also test whether this method of assessing connectivity can be used as new tool in the quantification of flood risk that moves beyond the simple flood extent approach, encapsulating threshold changes and data limitations.
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Improved simulation of tropospheric ozone by a global-multi-regional two-way coupling model system
NASA Astrophysics Data System (ADS)
Yan, Yingying; Lin, Jintai; Chen, Jinxuan; Hu, Lu
2016-02-01
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 with the ground measurements from 0.53 to 0.68, and it reduces the mean model bias from 10.8 to 6.7 ppb. Regionally, the coupled system reduces the bias by 4.6 ppb over Europe, 3.9 ppb over North America and 3.1 ppb over other regions. The two-way coupling brings O3 vertical profiles much closer to the HIPPO (for remote areas) and MOZAIC (for polluted regions) data, reducing the tropospheric (0-9 km) mean bias by 3-10 ppb at most MOZAIC sites and by 5.3 ppb for HIPPO profiles. The two-way coupled simulation also reduces the global tropospheric column ozone by 3.0 DU (9.5 %, annual mean), bringing them closer to the OMI data in all seasons. Additionally, the two-way coupled simulation also reduces the global tropospheric mean hydroxyl radical by 5 % with improved estimates of methyl chloroform and methane lifetimes. Simulation improvements are more significant in the Northern Hemisphere, and are mainly driven by improved representation of spatial inhomogeneity in chemistry/emissions. Within the nested domains, the two-way coupled simulation reduces surface ozone biases relative to typical GEOS-Chem one-way nested simulations, due to much improved LBCs. The bias reduction is 1-7 times the bias reduction from the global to the one-way nested simulation. Improving model representations of small-scale processes is important for understanding the global and regional tropospheric chemistry.
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Modeling large-scale human alteration of land surface hydrology and climate
NASA Astrophysics Data System (ADS)
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 water and energy balances, highlighting the need to incorporate human activities such as irrigation into the framework of global climate models and Earth system models for better prediction of future changes under increasing human influence and continuing global climate change.
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NASA Astrophysics Data System (ADS)
Pi, X.; Butala, M.; Vergados, P.; Mannucci, A. J.; Komjathy, A.; Wang, C.; Rosen, G.; Schunk, R. W.; Scherliess, L.; Eccles, V.; Gardner, L. C.; Sojka, J. J.; Zhu, L.
2015-12-01
Under the U.S. NASA and NSF collaborative space weather modeling initiative, a Multimodel Ensemble Prediction System (MEPS) for ionosphere-thermosphere-electrodynamics is being developed. The system includes several Global Assimilative Ionospheric Models (GAIMs) developed by the investigators from Utah State University, Jet Propulsion Laboratory, and University of Southern California. In this study, four GAIMs are applied to a study of ionospheric response to the 17 March 2015 St. Patrick's Day storm. It is the most severe geomagnetic storm in the current solar cycle so far. The daily planetary magnetic Ap index and magnetic Kp, Dst, as well as AE indices reached their very high values, i.e., 108, 8, -202 nT, and 2269 nT, respectively. In the assimilative modeling, GPS data from hundreds of globally-distributed ground stations and a number of COSMIC satellites are assimilated into GAIMs to reproduce ionospheric 3-D volume densities and 2-D total electron content (TEC) during the severe storm. Evolution of strong, latitudinally-dependent, and hemispherically asymmetric ionospheric disturbances is revealed through the assimilative modeling. Using the same GPS data, Global Maps of Ionospheric Irregularities and Scintillation (GMIIS) have also been produced. Comparisons of the modeled large-scale ionospheric disturbances and measured small-scale ionospheric irregularities offer additional insight into the M-I-T coupling processes in different regions during varying storm phases. This presentation will provide a picture of distinguished multi-scale ionospheric response to the coronal mass ejection (CME) event during the major geomagnetic storm.
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NASA/MSFC FY88 Global Scale Atmospheric Processes Research Program Review
NASA Technical Reports Server (NTRS)
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.
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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.
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van Gennip, Simon J; Popova, Ekaterina E; Yool, Andrew; Pecl, Gretta T; Hobday, Alistair J; Sorte, Cascade J B
2017-07-01
Ocean warming, acidification, deoxygenation and reduced productivity are widely considered to be the major stressors to ocean ecosystems induced by emissions of CO 2 . However, an overlooked stressor is the change in ocean circulation in response to climate change. Strong changes in the intensity and position of the western boundary currents have already been observed, and the consequences of such changes for ecosystems are beginning to emerge. In this study, we address climatically induced changes in ocean circulation on a global scale but relevant to propagule dispersal for species inhabiting global shelf ecosystems, using a high-resolution global ocean model run under the IPCC RCP 8.5 scenario. The ¼ degree model resolution allows improved regional realism of the ocean circulation beyond that of available CMIP5-class models. We use a Lagrangian approach forced by modelled ocean circulation to simulate the circulation pathways that disperse planktonic life stages. Based on trajectory backtracking, we identify present-day coastal retention, dominant flow and dispersal range for coastal regions at the global scale. Projecting into the future, we identify areas of the strongest projected circulation change and present regional examples with the most significant modifications in their dominant pathways. Climatically induced changes in ocean circulation should be considered as an additional stressor of marine ecosystems in a similar way to ocean warming or acidification. © 2017 John Wiley & Sons Ltd.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Greene, David L
2007-02-01
The global energy system faces sweeping changes in the next few decades, with potentially critical implications for the global economy and the global environment. It is important that global institutions have the tools necessary to predict, analyze and plan for such massive change. This report summarizes the proceedings of an international workshop concerning methods of forecasting, analyzing, and planning for global energy transitions and their economic and environmental consequences. A specific case, it focused on the transition from conventional to unconventional oil and other energy sources likely to result from a peak in non-OPEC and/or global production of conventional oil.more » Leading energy models from around the world in government, academia and the private sector met, reviewed the state-of-the-art of global energy modeling and evaluated its ability to analyze and predict large-scale energy transitions.« less
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Integrated modelling of anthropogenic land-use and land-cover change on the global scale
NASA Astrophysics Data System (ADS)
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 that can serve as basis for further impact analysis. An exemplary simulation study with LandSHIFT is presented, based on scenario assumptions from the UNEP Global Environmental Outlook 4. Time horizon of the analysis is the year 2050. Changes of future food production on country level are computed by the agro-economy model IMPACT as a function of demography, economic development and global trade pattern. Together with scenario assumptions on climatic change and population growth, this data serves as model input to compute the changing land-use und land-cover. The continental and global scale model results are then analysed with respect to changes in the spatial pattern of natural vegetation as well as the resulting effects on evapotranspiration processes and land surface parameters. Furthermore, possible linkages of LandSHIFT to the different components of Earth System models (e.g. climate and natural vegetation) are discussed.
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A new synoptic scale resolving global climate simulation using the Community Earth System Model
NASA Astrophysics Data System (ADS)
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."
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NASA Downscaling Project: Final Report
NASA Technical Reports Server (NTRS)
Ferraro, Robert; Waliser, Duane; Peters-Lidard, Christa
2017-01-01
A team of researchers from NASA Ames Research Center, Goddard Space Flight Center, the Jet Propulsion Laboratory, and Marshall Space Flight Center, along with university partners at UCLA, conducted an investigation to explore whether downscaling coarse resolution global climate model (GCM) predictions might provide valid insights into the regional impacts sought by decision makers. Since the computational cost of running global models at high spatial resolution for any useful climate scale period is prohibitive, the hope for downscaling is that a coarse resolution GCM provides sufficiently accurate synoptic scale information for a regional climate model (RCM) to accurately develop fine scale features that represent the regional impacts of a changing climate. As a proxy for a prognostic climate forecast model, and so that ground truth in the form of satellite and in-situ observations could be used for evaluation, the MERRA and MERRA - 2 reanalyses were used to drive the NU - WRF regional climate model and a GEOS - 5 replay. This was performed at various resolutions that were at factors of 2 to 10 higher than the reanalysis forcing. A number of experiments were conducted that varied resolution, model parameterizations, and intermediate scale nudging, for simulations over the continental US during the period from 2000 - 2010. The results of these experiments were compared to observational datasets to evaluate the output.
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Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng
2016-01-05
Large-scale atmospheric forcing data can greatly impact the simulations of atmospheric process models including Large Eddy Simulations (LES), Cloud Resolving Models (CRMs) and Single-Column Models (SCMs), and impact the development of physical parameterizations in global climate models. This study describes the development of an ensemble variationally constrained objective analysis of atmospheric large-scale forcing data and its application to evaluate the cloud biases in the Community Atmospheric Model (CAM5). Sensitivities of the variational objective analysis to background data, error covariance matrix and constraint variables are described and used to quantify the uncertainties in the large-scale forcing data. Application of the ensemblemore » forcing in the CAM5 SCM during March 2000 intensive operational period (IOP) at the Southern Great Plains (SGP) of the Atmospheric Radiation Measurement (ARM) program shows systematic biases in the model simulations that cannot be explained by the uncertainty of large-scale forcing data, which points to the deficiencies of physical parameterizations. The SCM is shown to overestimate high clouds and underestimate low clouds. These biases are found to also exist in the global simulation of CAM5 when it is compared with satellite data.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng
Large-scale atmospheric forcing data can greatly impact the simulations of atmospheric process models including Large Eddy Simulations (LES), Cloud Resolving Models (CRMs) and Single-Column Models (SCMs), and impact the development of physical parameterizations in global climate models. This study describes the development of an ensemble variationally constrained objective analysis of atmospheric large-scale forcing data and its application to evaluate the cloud biases in the Community Atmospheric Model (CAM5). Sensitivities of the variational objective analysis to background data, error covariance matrix and constraint variables are described and used to quantify the uncertainties in the large-scale forcing data. Application of the ensemblemore » forcing in the CAM5 SCM during March 2000 intensive operational period (IOP) at the Southern Great Plains (SGP) of the Atmospheric Radiation Measurement (ARM) program shows systematic biases in the model simulations that cannot be explained by the uncertainty of large-scale forcing data, which points to the deficiencies of physical parameterizations. The SCM is shown to overestimate high clouds and underestimate low clouds. These biases are found to also exist in the global simulation of CAM5 when it is compared with satellite data.« less
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NASA Technical Reports Server (NTRS)
Ferraro, Robert; Waliser, Duane; Peters-Lidard, Christa
2017-01-01
A team of researchers from NASA Ames Research Center, Goddard Space Flight Center, the Jet Propulsion Laboratory, and Marshall Space Flight Center, along with university partners at UCLA, conducted an investigation to explore whether downscaling coarse resolution global climate model (GCM) predictions might provide valid insights into the regional impacts sought by decision makers. Since the computational cost of running global models at high spatial resolution for any useful climate scale period is prohibitive, the hope for downscaling is that a coarse resolution GCM provides sufficiently accurate synoptic scale information for a regional climate model (RCM) to accurately develop fine scale features that represent the regional impacts of a changing climate. As a proxy for a prognostic climate forecast model, and so that ground truth in the form of satellite and in-situ observations could be used for evaluation, the MERRA and MERRA-2 reanalyses were used to drive the NU-WRF regional climate model and a GEOS-5 replay. This was performed at various resolutions that were at factors of 2 to 10 higher than the reanalysis forcing. A number of experiments were conducted that varied resolution, model parameterizations, and intermediate scale nudging, for simulations over the continental US during the period from 2000-2010. The results of these experiments were compared to observational datasets to evaluate the output.
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Magnetosphere Modeling: From Cartoons to Simulations
NASA Astrophysics Data System (ADS)
Gombosi, T. I.
2017-12-01
Over the last half a century physics-based global computer simulations became a bridge between experiment and basic theory and now it represents the "third pillar" of geospace research. Today, many of our scientific publications utilize large-scale simulations to interpret observations, test new ideas, plan campaigns, or design new instruments. Realistic simulations of the complex Sun-Earth system have been made possible by the dramatically increased power of both computing hardware and numerical algorithms. Early magnetosphere models were based on simple E&M concepts (like the Chapman-Ferraro cavity) and hydrodynamic analogies (bow shock). At the beginning of the space age current system models were developed culminating in the sophisticated Tsyganenko-type description of the magnetic configuration. The first 3D MHD simulations of the magnetosphere were published in the early 1980s. A decade later there were several competing global models that were able to reproduce many fundamental properties of the magnetosphere. The leading models included the impact of the ionosphere by using a height-integrated electric potential description. Dynamic coupling of global and regional models started in the early 2000s by integrating a ring current and a global magnetosphere model. It has been recognized for quite some time that plasma kinetic effects play an important role. Presently, global hybrid simulations of the dynamic magnetosphere are expected to be possible on exascale supercomputers, while fully kinetic simulations with realistic mass ratios are still decades away. In the 2010s several groups started to experiment with PIC simulations embedded in large-scale 3D MHD models. Presently this integrated MHD-PIC approach is at the forefront of magnetosphere simulations and this technique is expected to lead to some important advances in our understanding of magnetosheric physics. This talk will review the evolution of magnetosphere modeling from cartoons to current systems, to global MHD to MHD-PIC and discuss the role of state-of-the-art models in forecasting space weather.
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Simplifiying global biogeochemistry models to evaluate methane emissions
NASA Astrophysics Data System (ADS)
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 further model development and improvement. However, an important goal for our model is to use it in field settings as a tool to deconvolve the different processes that contribute to the net transfer of methane from soils to atmosphere.
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Uncertainties in Past and Future Global Water Availability
NASA Astrophysics Data System (ADS)
Sheffield, J.; Kam, J.
2014-12-01
Understanding how water availability changes on inter-annual to decadal time scales and how it may change in the future under climate change are a key part of understanding future stresses on water and food security. Historic evaluations of water availability on regional to global scales are generally based on large-scale model simulations with their associated uncertainties, in particular for long-term changes. Uncertainties are due to model errors and missing processes, parameter uncertainty, and errors in meteorological forcing data. Recent multi-model inter-comparisons and impact studies have highlighted large differences for past reconstructions, due to different simplifying assumptions in the models or the inclusion of physical processes such as CO2 fertilization. Modeling of direct anthropogenic factors such as water and land management also carry large uncertainties in their physical representation and from lack of socio-economic data. Furthermore, there is little understanding of the impact of uncertainties in the meteorological forcings that underpin these historic simulations. Similarly, future changes in water availability are highly uncertain due to climate model diversity, natural variability and scenario uncertainty, each of which dominates at different time scales. In particular, natural climate variability is expected to dominate any externally forced signal over the next several decades. We present results from multi-land surface model simulations of the historic global availability of water in the context of natural variability (droughts) and long-term changes (drying). The simulations take into account the impact of uncertainties in the meteorological forcings and the incorporation of water management in the form of reservoirs and irrigation. The results indicate that model uncertainty is important for short-term drought events, and forcing uncertainty is particularly important for long-term changes, especially uncertainty in precipitation due to reduced gauge density in recent years. We also discuss uncertainties in future projections from these models as driven by bias-corrected and downscaled CMIP5 climate projections, in the context of the balance between climate model robustness and climate model diversity.
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Wei, Yaxing; Liu, Shishi; Huntzinger, Deborah N.; ...
2014-12-05
Ecosystems are important and dynamic components of the global carbon cycle, and terrestrial biospheric models (TBMs) are crucial tools in further understanding of how terrestrial carbon is stored and exchanged with the atmosphere across a variety of spatial and temporal scales. Improving TBM skills, and quantifying and reducing their estimation uncertainties, pose significant challenges. The Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) is a formal multi-scale and multi-model intercomparison effort set up to tackle these challenges. The MsTMIP protocol prescribes standardized environmental driver data that are shared among model teams to facilitate model model and model observation comparisons. Inmore » this article, we describe the global and North American environmental driver data sets prepared for the MsTMIP activity to both support their use in MsTMIP and make these data, along with the processes used in selecting/processing these data, accessible to a broader audience. Based on project needs and lessons learned from past model intercomparison activities, we compiled climate, atmospheric CO 2 concentrations, nitrogen deposition, land use and land cover change (LULCC), C3 / C4 grasses fractions, major crops, phenology and soil data into a standard format for global (0.5⁰ x 0.5⁰ resolution) and regional (North American: 0.25⁰ x 0.25⁰ resolution) simulations. In order to meet the needs of MsTMIP, improvements were made to several of the original environmental data sets, by improving the quality, and/or changing their spatial and temporal coverage, and resolution. The resulting standardized model driver data sets are being used by over 20 different models participating in MsTMIP. Lastly, the data are archived at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC, http://daac.ornl.gov) to provide long-term data management and distribution.« less
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This paper reviews the controls on aeolian processes and their consequences at plant-interspace, patch-landscape, and regional-global scales. Based on this review, we define the requirements for a cross-scale model of wind erosion in structurally complex arid and semiarid ecosyst...
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USDA-ARS?s Scientific Manuscript database
Agriculture covers 40% of Earth’s ice-free land area and has broad impacts on global biogeochemical cycles. While some agricultural management changes are small in scale or impact, others have the potential to shift biogeochemical cycles at landscape and larger scales if widely adopted. Understandin...
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A Global Landslide Nowcasting System using Remotely Sensed Information
NASA Astrophysics Data System (ADS)
Kirschbaum, Dalia; Stanely, Thomas
2017-04-01
A global Landslide Hazard Assessment model for Situational Awareness (LHASA) has been developed that combines susceptibility information with satellite-based precipitation to provide an indication of potential landslide activity at the global scale every 30 minutes. This model utilizes a 1-km global susceptibility map derived from information on slope, geology, road networks, fault zones, and forest loss. A multi-satellite dataset from the Global Precipitation Measurement (GPM) mission is used to identify the current and antecedent rainfall conditions from the past 7 days. When both rainfall and susceptibility are high, a "nowcast" is issued to indicate areas where a landslide may be likely. The global LHASA model is currently being run in near real-time every 30 minutes and the outputs are available in several different formats at https://pmm.nasa.gov/precip-apps. This talk outlines the LHASA system, discusses the performance metrics and potential applications of the LHASA system.
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A global scale mechanistic model of photosynthetic capacity (LUNA V1.0)
Ali, Ashehad A.; Xu, Chonggang; Rogers, Alistair; ...
2016-02-12
Although plant photosynthetic capacity as determined by the maximum carboxylation rate (i.e., V c,max25) and the maximum electron transport rate (i.e., J max25) at a reference temperature (generally 25 °C) is known to vary considerably in space and time in response to environmental conditions, it is typically parameterized in Earth system models (ESMs) with tabulated values associated with plant functional types. In this study, we have developed a mechanistic model of leaf utilization of nitrogen for assimilation (LUNA) to predict photosynthetic capacity at the global scale under different environmental conditions. We adopt an optimality hypothesis to nitrogen allocation among lightmore » capture, electron transport, carboxylation and respiration. The LUNA model is able to reasonably capture the measured spatial and temporal patterns of photosynthetic capacity as it explains ~55 % of the global variation in observed values of V c,max25 and ~65 % of the variation in the observed values of J max25. Model simulations with LUNA under current and future climate conditions demonstrate that modeled values of V c,max25 are most affected in high-latitude regions under future climates. In conclusion, ESMs that relate the values of V c,max25 or J max25 to plant functional types only are likely to substantially overestimate future global photosynthesis.« less
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The Spatial Scaling of Global Rainfall Extremes
NASA Astrophysics Data System (ADS)
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.
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The use of imprecise processing to improve accuracy in weather & climate prediction
NASA Astrophysics Data System (ADS)
Düben, Peter D.; McNamara, Hugh; Palmer, T. N.
2014-08-01
The use of stochastic processing hardware and low precision arithmetic in atmospheric models is investigated. Stochastic processors allow hardware-induced faults in calculations, sacrificing bit-reproducibility and precision in exchange for improvements in performance and potentially accuracy of forecasts, due to a reduction in power consumption that could allow higher resolution. A similar trade-off is achieved using low precision arithmetic, with improvements in computation and communication speed and savings in storage and memory requirements. As high-performance computing becomes more massively parallel and power intensive, these two approaches may be important stepping stones in the pursuit of global cloud-resolving atmospheric modelling. The impact of both hardware induced faults and low precision arithmetic is tested using the Lorenz '96 model and the dynamical core of a global atmosphere model. In the Lorenz '96 model there is a natural scale separation; the spectral discretisation used in the dynamical core also allows large and small scale dynamics to be treated separately within the code. Such scale separation allows the impact of lower-accuracy arithmetic to be restricted to components close to the truncation scales and hence close to the necessarily inexact parametrised representations of unresolved processes. By contrast, the larger scales are calculated using high precision deterministic arithmetic. Hardware faults from stochastic processors are emulated using a bit-flip model with different fault rates. Our simulations show that both approaches to inexact calculations do not substantially affect the large scale behaviour, provided they are restricted to act only on smaller scales. By contrast, results from the Lorenz '96 simulations are superior when small scales are calculated on an emulated stochastic processor than when those small scales are parametrised. This suggests that inexact calculations at the small scale could reduce computation and power costs without adversely affecting the quality of the simulations. This would allow higher resolution models to be run at the same computational cost.
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A multi-scale methodology for comparing GCM and RCM results over the Eastern Mediterranean
NASA Astrophysics Data System (ADS)
Samuels, Rana; Krichak, Simon; Breitgand, Joseph; Alpert, Pinhas
2010-05-01
The importance of skillful climate modeling is increasingly being realized as results are being incorporated into environmental, economic, and even business planning. Global circulation models (GCMs) employed by the IPCC provide results at spatial scales of hundreds of kilometers, which is useful for understanding global trends but not appropriate for use as input into regional and local impacts models used to inform policy and development. To address this shortcoming, regional climate models (RCMs) which dynamically downscale the results of the GCMs are used. In this study we present first results of a dynamically downscaled RCM focusing on the Eastern Mediterranean region. For the historical 1960-2000 time period, results at a spatial scale of both 25 km and 50 km are compared with historical station data from 5 locations across Israel as well as with the results of 3 GCM models (ECHAM5, NOAA GFDL, and CCCMA) at annual, monthly and daily time scales. Results from a recently completed Japanese GCM at a spatial scale of 20 km are also included. For the historical validation period, we show that as spatial scale increases the skill in capturing annual and inter-annual temperature and rainfall also increases. However, for intra-seasonal rainfall characteristics important for hydrological and agricultural planning (eg. dry and wet spells, number of rain days) the GCM results (including the 20 km Japanese model) capture the historical trends better than the dynamically downscaled RegCM. For future scenarios of temperature and precipitation changes, we compare results across the models for the available time periods, generating a range of future trends.
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Regional and global forcing of glacier retreat during the last deglaciation.
Shakun, Jeremy D; Clark, Peter U; He, Feng; Lifton, Nathaniel A; Liu, Zhengyu; Otto-Bliesner, Bette L
2015-08-21
The ongoing retreat of glaciers globally is one of the clearest manifestations of recent global warming associated with rising greenhouse gas concentrations. By comparison, the importance of greenhouse gases in driving glacier retreat during the most recent deglaciation, the last major interval of global warming, is unclear due to uncertainties in the timing of retreat around the world. Here we use recently improved cosmogenic-nuclide production-rate calibrations to recalculate the ages of 1,116 glacial boulders from 195 moraines that provide broad coverage of retreat in mid-to-low-latitude regions. This revised history, in conjunction with transient climate model simulations, suggests that while several regional-scale forcings, including insolation, ice sheets and ocean circulation, modulated glacier responses regionally, they are unable to account for global-scale retreat, which is most likely related to increasing greenhouse gas concentrations.
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NASA Astrophysics Data System (ADS)
Bundel, A.; Kulikova, I.; Kruglova, E.; Muravev, A.
2003-04-01
The scope of the study is to estimate the relationship between large-scale circulation regimes, various instability indices and global precipitation with different boundary conditions, considered as external forcing. The experiments were carried out in the ensemble-prediction framework of the dynamic-statistical monthly forecast scheme run in the Hydrometeorological Research Center of Russia every ten days. The extension to seasonal intervals makes it necessary to investigate the role of slowly changing boundary conditions among which the sea surface temperature (SST) may be defined as the most effective factor. Continuous integrations of the global spectral T41L15 model for the whole year 2000 (starting from January 1) were performed with the climatic SST and the Reynolds Archive SSTs. Monthly values of the SST were projected on the year days using spline interpolation technique. First, the global precipitation values in experiments were compared to the GPCP (Global Precipitation Climate Program) daily observation data. Although the global mean precipitation is underestimated by the model, some large-scale regional amounts correspond to the real ones (e.g. for Europe) fairly well. On the whole, however, anomaly phases failed to be reproduced. The precipitation averaged over the whole land revealed a greater sensitivity to the SSTs than that over the oceans. The wavelet analysis was applied to separate the low- and high-frequency signal of the SST influence on the large-scale circulation and precipitation. A derivative of the Wallace-Gutzler teleconnection index for the East-Atlantic oscillation was taken as the circulation characteristic. The daily oscillation index values and precipitation amounts averaged over Europe were decomposed using wavelet approach with different “mother wavelets” up to approximation level 3. It was demonstrated that an increase in the precipitation amount over Europe was associated with the zonal flow intensification over the Northern Atlantic when the real SSTs were used. Blocking structures in the circulation caused decreasing precipitation amounts. The wavelet approach gave a more distinctive discrimination in the modeled circulation and precipitation patterns versus different external forcing than a number of other statistical techniques. Several atmospheric instability indices (e.g. the Phillips like parameters, Richardson number etc) were additionally used in post-processing for a more detailed validation of the modeled large-scale and total precipitation amounts. It was shown that a reasonable variety of instability indices must be used for such validations and for precipitation output corrections. Their statistical stability may be substantiated only on the ensemble modeling basis. This work was performed with the financial support of the Russian Foundation for Basic Research (02-05-64655).
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A high resolution global scale groundwater model
NASA Astrophysics Data System (ADS)
de Graaf, Inge; Sutanudjaja, Edwin; van Beek, Rens; Bierkens, Marc
2014-05-01
As the world's largest accessible source of freshwater, groundwater plays a vital role in satisfying the basic needs of human society. It serves as a primary source of drinking water and supplies water for agricultural and industrial activities. During times of drought, groundwater storage provides a large natural buffer against water shortage and sustains flows to rivers and wetlands, supporting ecosystem habitats and biodiversity. Yet, the current generation of global scale hydrological models (GHMs) do not include a groundwater flow component, although it is a crucial part of the hydrological cycle. Thus, a realistic physical representation of the groundwater system that allows for the simulation of groundwater head dynamics and lateral flows is essential for GHMs that increasingly run at finer resolution. In this study we present a global groundwater model with a resolution of 5 arc-minutes (approximately 10 km at the equator) using MODFLOW (McDonald and Harbaugh, 1988). With this global groundwater model we eventually intend to simulate the changes in the groundwater system over time that result from variations in recharge and abstraction. Aquifer schematization and properties of this groundwater model were developed from available global lithological maps and datasets (Dürr et al., 2005; Gleeson et al., 2010; Hartmann and Moosdorf, 2013), combined with our estimate of aquifer thickness for sedimentary basins. We forced the groundwater model with the output from the global hydrological model PCR-GLOBWB (van Beek et al., 2011), specifically the net groundwater recharge and average surface water levels derived from routed channel discharge. For the parameterization, we relied entirely on available global datasets and did not calibrate the model so that it can equally be expanded to data poor environments. Based on our sensitivity analysis, in which we run the model with various hydrogeological parameter settings, we observed that most variance in groundwater depth is explained by variation in saturated conductivity, and, for the sediment basins, also by variation in recharge. We validated simulated groundwater heads with piezometer heads (available from www.glowasis.eu), resulting in a coefficient of determination for sedimentary basins of 0.92 with regression constant of 0.8. This shows the used method is suitable to build a global groundwater model using best available global information, and estimated water table depths are within acceptable accuracy in many parts of the world.
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Using Global Plate Velocity Boundary Conditions for Embedded Regional Geodynamic Models
NASA Astrophysics Data System (ADS)
Taramon Gomez, Jorge; Morgan, Jason; Perez-Gussinye, Marta
2015-04-01
The treatment of far-field boundary conditions is one of the most poorly resolved issues for regional modeling of geodynamic processes. In viscous flow, the choice of far-field boundary conditions often strongly shapes the large-scale structure of a geosimulation. The mantle velocity field along the sidewalls and base of a modeling region is typically much more poorly known than the geometry of past global motions of the surface plates as constrained by global plate motion reconstructions. For regional rifting models it has become routine to apply highly simplified 'plate spreading' or 'uniform rifting' boundary conditions to a 3-D model that limits its ability to simulate the geodynamic evolution of a specific rifted margin. One way researchers are exploring the sensitivity of regional models to uncertain boundary conditions is to use a nested modeling approach in which a global model is used to determine a large-scale flow pattern that is imposed as a constraint along the boundaries of the region to be modeled. Here we explore the utility of a different approach that takes advantage of the ability of finite element models to use unstructured meshes than can embed much higher resolution sub-regions within a spherical global mesh. In our initial project to validate this approach, we create a global spherical mesh in which a higher resolution sub-region is created around the nascent South Atlantic Rifting Margin. Global Plate motion BCs and plate boundaries are applied for the time of the onset of rifting, continuing through several 10s of Ma of rifting. Thermal, compositional, and melt-related buoyancy forces are only non-zero within the high-resolution subregion, elsewhere, motions are constrained by surface plate-motion constraints. The total number of unknowns needed to solve an embedded regional model with this approach is less than 1/3 larger than that needed for a structured-mesh solution on a Cartesian or spherical cap sub-regional mesh. Here we illustrate the initial steps within this workflow for creating time-varying surface boundary conditions (using GPlates), and a time-variable unstructured 3-D spherical mesh.
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Weak hydrological sensitivity to temperature change over land, independent of climate forcing
NASA Astrophysics Data System (ADS)
Samset, Bjorn H.
2017-04-01
As the global surface temperature changes, so will patterns and rates of precipitation. Theoretically, these changes can be understood in terms of changes to the energy balance of the atmosphere, caused by introducing drivers of climate change such as greenhouse gases, aerosols and altered insolation. Climate models, however, disagree strongly in their prediction of precipitation changes, both for historical and future emission pathways, and per degree of surface warming in idealized experiments. The latter value, often termed the apparent hydrological sensitivity, has also been found to differ substantially between climate drivers. Here, we present the global and regional hydrological sensitivity (HS) to surface temperature changes, for perturbations to CO2, CH4, sulfate and black carbon concentrations, and solar irradiance. Based on results from 10 climate models participating in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), we show how modeled global mean precipitation increases by 2-3 % per kelvin of global mean surface warming, independent of driver, when the effects of rapid adjustments are removed. Previously reported differences in response between drivers are therefore mainly ascribable to rapid atmospheric adjustment processes. All models show a sharp contrast in behavior over land and over ocean, with a strong surface temperature driven (slow) ocean HS of 3-5 %/K, while the slow land HS is only 0-2 %/K. Separating the response into convective and large-scale cloud processes, we find larger inter-model differences, in particular over land regions. Large-scale precipitation changes are most relevant at high latitudes, while the equatorial HS is dominated by convective precipitation changes. Black carbon stands out as the driver with the largest inter-model slow HS variability, and also the strongest contrast between a weak land and strong sea response. Convective precipitation in the Arctic and large scale precipitation around the Equator are found to be topics where further model investigations and observational constraints may provide rapid improvements to modelling of the precipitation response to future, CO2 dominated climate change.
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NASA Astrophysics Data System (ADS)
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 mechanistic representation of leaf-level nitrogen allocation and a theoretically consistent treatment of competition with belowground consumers leads to overall improvements in CLM4.5's global carbon cycling predictions.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Allen, Melissa R.; Aziz, H. M. Abdul; Coletti, Mark A.
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 limitedmore » 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.« less
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Year of Tropical Convection (YOTC): Status and Research Agenda
NASA Astrophysics Data System (ADS)
Moncrieff, M. W.; Waliser, D. E.
2009-12-01
The realistic representation of tropical convection in global models is a long-standing challenge for numerical weather prediction and an emerging grand challenge for climate prediction in respect to its physical basis. Insufficient knowledge and practical capabilities in this area disadvantage the modeling and prediction of prominent multi-scale phenomena such as the ITCZ, ENSO, monsoons and their active/break periods, the MJO, subtropical stratus decks, near-surface ocean properties, and tropical cyclones. Science elements include the diurnal cycle of precipitation, multi-scale convective organization, the global energy and water cycle, and interaction between the tropics and extra-tropics which interact strongly on timescales of weeks-to-months: the intersection of weather and climate. To address such challenges, the WCRP and WWRP/THORPEX are conducting a joint international research project, the Year of Tropical Convection (YOTC) which is a coordinated observing, modeling and forecasting project. The focus-year and integrated framework is intended to exploit the vast observational datasets, the modern high-resolution modeling frameworks, and theoretical insights. The over-arching objective is to advance the characterization, diagnosis, modeling, parameterization and prediction of multi-scale organized tropical phenomena and their interaction with the global circulation. The “Year” (May 2008 - April 2010) is intended to leverage recent major investments in Earth Science infrastructure and overlapping observational activities, e.g., Asian Monsoon Years (AMY) and the THORPEX Pacific Asian Regional Campaign (T-PARC). The research agenda involves phenomena and scale-interactions that are problematic for prediction models and have important socio-economic implications: MJO and convectively coupled equatorial waves; easterly waves and tropical cyclones; the monsoons including their intraseasonal variability; the diurnal cycle of precipitation; and two-way tropical-extratropical interaction. This presentation will summarize the status of the above.
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NASA Astrophysics Data System (ADS)
Anderegg, L. D.; Berner, L. T.; Badgley, G.; Hillerislambers, J.; Law, B. E.
2017-12-01
Functional traits could facilitate ecological prediction by provide scale-free tools for modeling ecosystem function. Yet much of their utility lies in three key assumptions: 1) that global patterns of trait covariation are the result of universal trade-offs independent of taxonomic scale, so empirical trait-trait relationships can be used to constrain vegetation models 2) that traits respond predictably to environmental gradients and can therefore be reliably quantified to parameterize models and 3) that well sampled traits influence productivity. We use an extensive dataset of within-species leaf trait variation in North American conifers combined with global leaf trait datasets to test these assumptions. We examine traits central to the `leaf economics spectrum', and quantify patterns of trait variation at multiple taxonomic scales. We also test whether site environment explains geographic trait variation within conifers, and ask whether foliar traits explain geographic variation in relative growth rates. We find that most leaf traits vary primarily between rather than within species globally, but that a large fraction of within-PFT trait variation is within-species. We also find that some leaf economics spectrum relationships differ in sign within versus between species, particularly the relationship between leaf lifespan and LMA. In conifers, we find weak and inconsistent relationships between site environment and leaf traits, making it difficult capture within-species leaf trait variation for regional model parameterization. Finally, we find limited relationships between tree relative growth rate and any foliar trait other than leaf lifespan, with leaf traits jointly explaining 42% of within-species growth variation but environmental factors explaining 77% of variation. We suggest that additional traits, particularly whole plant allometry/allocation traits may be better than leaf traits for improving vegetation model performance at smaller taxonomic and spatial scales.
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Modeling the QBO and SAO Driven by Gravity Waves
NASA Technical Reports Server (NTRS)
Mayr, H. G.; Mengel, J. G.; Chan, K. L.; Porter, H. S.
1999-01-01
Hines' Doppler spread parameterization (DSP) for small scale gravity waves (GW) is applied in a global scale numerical spectral model (NSM) to describe the semi-annual and quasi-biennial oscillations (SAO and QBO) as well as the long term interannual variations that are driven by wave mean flow interactions. This model has been successful in simulating the salient features observed near the equator at altitudes above 20 km, including the QBO extension into the upper mesosphere inferred from UARS measurements. The model has now been extended to describe also the mean zonal and meridional circulations of the upper troposphere and lower stratosphere that affect the equatorial QBO and its global scale extension. This is accomplished in part through tuning of the GW parameterization, and preliminary results lead to the following conclusions: (1) To reproduce the upwelling at equatorial latitudes associated with the Brewer/Dobson circulation that in part is modulated in the model by the vertical component of the Coriolis force, the eddy diffusivity in the lower stratosphere had to be enhanced and the related GW spectrum modified to bring it in closer agreement with the form recommended for the DSP. (2) To compensate for the required increase in the diffusivity, the observed QBO requires a larger GW source that is closer to the middle of the range recommended for the DSP. (3) Through global scale momentum redistribution, the above developments are conducive to extending the QBO and SAO oscillations to higher latitudes. Multi-year interannual oscillations are generated through wave filtering by the solar driven annual oscillation in the zonal circulation. (4) In a 3D version of the model, wave momentum is absorbed and dissipated by tides and planetary waves. Thus, a somewhat larger GW source is required to generate realistic amplitudes for the QBO and SAO.
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Remedying excessive numerical diapycnal mixing in a global 0.25° NEMO configuration
NASA Astrophysics Data System (ADS)
Megann, Alex; Nurser, George; Storkey, Dave
2016-04-01
If numerical ocean models are to simulate faithfully the upwelling branches of the global overturning circulation, they need to have a good representation of the diapycnal mixing processes which contribute to conversion of the bottom and deep waters produced in high latitudes into less dense watermasses. It is known that the default class of depth-coordinate ocean models such as NEMO and MOM5, as used in many state-of-the art coupled climate models and Earth System Models, have excessive numerical diapycnal mixing, resulting from irreversible advection across coordinate surfaces. The GO5.0 configuration of the NEMO ocean model, on an "eddy-permitting" 0.25° global grid, is used in the current UK GC1 and GC2 coupled models. Megann and Nurser (2016) have shown, using the isopycnal watermass analysis of Lee et al (2002), that spurious numerical mixing is substantially larger than the explicit mixing prescribed by the mixing scheme used by the model. It will be shown that increasing the biharmonic viscosity by a factor of three tends to suppress small-scale noise in the vertical velocity in the model. This significantly reduces the numerical mixing in GO5.0, and we shall show that it also leads to large-scale improvements in model biases.
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Regional reanalysis without local data: Exploiting the downscaling paradigm
NASA Astrophysics Data System (ADS)
von Storch, Hans; Feser, Frauke; Geyer, Beate; Klehmet, Katharina; Li, Delei; Rockel, Burkhardt; Schubert-Frisius, Martina; Tim, Nele; Zorita, Eduardo
2017-08-01
This paper demonstrates two important aspects of regional dynamical downscaling of multidecadal atmospheric reanalysis. First, that in this way skillful regional descriptions of multidecadal climate variability may be constructed in regions with little or no local data. Second, that the concept of large-scale constraining allows global downscaling, so that global reanalyses may be completed by additions of consistent detail in all regions of the world. Global reanalyses suffer from inhomogeneities. However, their large-scale componenst are mostly homogeneous; Therefore, the concept of downscaling may be applied to homogeneously complement the large-scale state of the reanalyses with regional detail—wherever the condition of homogeneity of the description of large scales is fulfilled. Technically, this can be done by dynamical downscaling using a regional or global climate model, which's large scales are constrained by spectral nudging. This approach has been developed and tested for the region of Europe, and a skillful representation of regional weather risks—in particular marine risks—was identified. We have run this system in regions with reduced or absent local data coverage, such as Central Siberia, the Bohai and Yellow Sea, Southwestern Africa, and the South Atlantic. Also, a global simulation was computed, which adds regional features to prescribed global dynamics. Our cases demonstrate that spatially detailed reconstructions of the climate state and its change in the recent three to six decades add useful supplementary information to existing observational data for midlatitude and subtropical regions of the world.
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NASA Astrophysics Data System (ADS)
Yan, Y.-Y.; Lin, J.-T.; Kuang, Y.; Yang, D.; Zhang, L.
2014-12-01
Global chemical transport models (CTMs) are used extensively to study air pollution and transport at a global scale. These models are limited by coarse horizontal resolutions that do not allow for a detailed representation of small-scale nonlinear processes over the pollutant source regions. Here we couple the global GEOS-Chem CTM and its three high-resolution nested models to simulate the tropospheric carbon monoxide (CO) over the Pacific Ocean during five High-performance Instrumented Airborne Platform for Environmental Research (HIAPER) Pole-to-Pole Observations (HIPPO) campaigns between 2009 and 2011. We develop a two-way coupler, the PeKing University CouPLer (PKUCPL), allowing for the exchange and interaction of chemical constituents between the global model (at 2.5° long. × 2° lat.) and the three nested models (at 0.667° long. × 0.5° lat.) covering Asia, North America, and Europe. The coupler obtains nested model results to modify the global model simulation within the respective nested domains, and simultaneously acquires global model results to provide lateral boundary conditions (LBCs) for the nested models. Compared to the global model alone, the two-way coupled simulation results in enhanced CO concentrations in the nested domains. Sensitivity tests suggest the enhancement to be a result of improved representation of the spatial distributions of CO, nitrogen oxides, and non-methane volatile organic compounds, the meteorological dependence of natural emissions, and other resolution-dependent processes. The relatively long lifetime of CO allows for the enhancement to be accumulated and carried across the globe. We found that the two-way coupled simulation increased the global tropospheric mean CO concentrations in 2009 by 10.4%, with a greater enhancement at 13.3% in the Northern Hemisphere. Coincidently, the global tropospheric mean hydroxyl radical (OH) was reduced by 4.2%, resulting in a 4.2% enhancement in the methyl chloroform lifetime (MCF; via reaction with tropospheric OH). The resulting CO and OH contents and MCF lifetime are closer to observation-based estimates. Both the global and the two-way coupled models capture the general spatiotemporal patterns of HIPPO CO over the Pacific. The two-way coupled simulation is much closer to HIPPO CO, with a mean bias of 1.1 ppb (1.4%) below 9 km compared to the bias at -7.2 ppb (-9.2%) for the global model alone. The improvement is most apparent over the North Pacific. Our test simulations show that the global model alone could resemble the two-way coupled simulation (especially below 4 km) by increasing its global CO emissions by 15% for HIPPO-1 and HIPPO-3, by 25% for HIPPO-2 and HIPPO-4, and by 35% for HIPPO-5. This has important implications for using the global model alone to constrain CO emissions. Thus, the two-way coupled simulation is a significantly improved model tool for studying the global impacts of air pollutants from major anthropogenic source regions.
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Atmospheric Science Data Center
2017-05-11
... Information Creating a Unified Airborne Database for Assessment and Validation of Global Models of Atmospheric ... (3) To generate a standardized in-situ observational database with best possible matching temporal and spatial scales to model ...
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From Gene Expression to the Earth System: Isotopic Constraints on Nitrogen Cycling Across Scales
NASA Astrophysics Data System (ADS)
Houlton, B. Z.
2015-12-01
A central motivation of the Biogeosciences is to understand the cycling of biologically essential elements over multiple scales of space and time. This charge is vital to basic knowledge of Earth system functioning. It is also relevant to many of the global challenges we face, such as climate change, biodiversity conservation, and the multifaceted role of global fertilizer use in maximizing human health and well-being. Nitrogen is connected to all of these; yet it has been one of the more vexing elements to quantitatively appraise across systems and scales. Here I discuss how research in my group has been exploring the use of natural nitrogen isotope abundance (15N/14N) as a biogeochemical tracer - from the level of gene expression to nitrogen's role in global climate change. First, I present evidence for a positive correlation between the bacterial genes that encode for gaseous nitrogen production (i.e., nirS) and the 15N/14N of soil extractable nitrate pools across an array of terrestrial ecosystems. Second, I demonstrate how these local-scale results fit with our work on ecosystem-scale nitrogen isotope budgets, where we quantify a uniformly small isotope effect (i.e., < 1 per mil) of nitrogen leaching losses from tropical rainforest to highly disturbed arid sites. Third, I present results from our global isotope model, which is based on results from our field investigations, providing a new nitrogen "benchmarking" scheme for global computational models and climate change forecasts. Finally, I move to a new research frontier where we have been developing a technique to measure the nitrogen isotope composition of ancient terrestrial plant compounds (i.e., chlorins) buried in the soil. This research aims to address the response of the nitrogen cycle to glacial-interglacial transitions over millennia, which is beyond the window of experimental testing. Together, this research highlights the utility of nitrogen isotope composition in addressing the myriad scales of this element's interaction with Earth's environment, and supports the working hypothesis that bacterial denitrification is the major fractionating pathway of nitrogen loss from the terrestrial biosphere, much like the global ocean.
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NASA Astrophysics Data System (ADS)
Pritchard, M. S.; Bretherton, C. S.; DeMott, C. A.
2014-12-01
New trade-offs are discussed in the cloud superparameterization approach to explicitly representing deep convection in global climate models. Intrinsic predictability tests show that the memory of cloud-resolving-scale organization is not critical for producing desired modes of organized convection such as the Madden-Julian Oscillation (MJO). This has implications for the feasibility of data assimilation and real-world initialization for superparameterized weather forecasting. Climate simulation sensitivity tests demonstrate that 400% acceleration of cloud superparameterization is possible by restricting the 32-128 km scale regime without deteriorating the realism of the simulated MJO but the number of cloud resolving model grid columns is discovered to constrain the efficiency of vertical mixing, with consequences for the simulated liquid cloud climatology. Tuning opportunities for next generation accelerated superparameterized climate models are discussed.
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A Neural Network Model for K(λ) Retrieval and Application to Global Kpar Monitoring.
Chen, Jun; Zhu, Yuanli; Wu, Yongsheng; Cui, Tingwei; Ishizaka, Joji; Ju, Yongtao
2015-01-01
Accurate estimation of diffuse attenuation coefficients in the visible wavelengths Kd(λ) from remotely sensed data is particularly challenging in global oceanic and coastal waters. The objectives of the present study are to evaluate the applicability of a semi-analytical Kd(λ) retrieval model (SAKM) and Jamet's neural network model (JNNM), and then develop a new neural network Kd(λ) retrieval model (NNKM). Based on the comparison of Kd(λ) predicted by these models with in situ measurements taken from the global oceanic and coastal waters, all of the NNKM, SAKM, and JNNM models work well in Kd(λ) retrievals, but the NNKM model works more stable and accurate than both SAKM and JNNM models. The near-infrared band-based and shortwave infrared band-based combined model is used to remove the atmospheric effects on MODIS data. The Kd(λ) data was determined from the atmospheric corrected MODIS data using the NNKM, JNNM, and SAKM models. The results show that the NNKM model produces <30% uncertainty in deriving Kd(λ) from global oceanic and coastal waters, which is 4.88-17.18% more accurate than SAKM and JNNM models. Furthermore, we employ an empirical approach to calculate Kpar from the NNKM model-derived diffuse attenuation coefficient at visible bands (443, 488, 555, and 667 nm). The results show that our model presents a satisfactory performance in deriving Kpar from the global oceanic and coastal waters with 20.2% uncertainty. The Kpar are quantified from MODIS data atmospheric correction using our model. Comparing with field measurements, our model produces ~31.0% uncertainty in deriving Kpar from Bohai Sea. Finally, the applicability of our model for general oceanographic studies is briefly illuminated by applying it to climatological monthly mean remote sensing reflectance for time ranging from July, 2002- July 2014 at the global scale. The results indicate that the high Kd(λ) and Kpar values are usually found around the coastal zones in the high latitude regions, while low Kd(λ) and Kpar values are usually found in the open oceans around the low-latitude regions. These results could improve our knowledge about the light field under waters at either the global or basin scales, and be potentially used into general circulation models to estimate the heat flux between atmosphere and ocean.
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NASA Astrophysics Data System (ADS)
Scheibe, T. D.; Yang, X.; Song, X.; Chen, X.; Hammond, G. E.; Song, H. S.; Hou, Z.; Murray, C. J.; Tartakovsky, A. M.; Tartakovsky, G.; Yang, X.; Zachara, J. M.
2016-12-01
Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs.
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NASA Technical Reports Server (NTRS)
Emmitt, G. D.; Wood, S. A.; Morris, M.
1990-01-01
Lidar Atmospheric Wind Sounder (LAWS) Simulation Models (LSM) were developed to evaluate the potential impact of global wind observations on the basic understanding of the Earth's atmosphere and on the predictive skills of current forecast models (GCM and regional scale). Fully integrated top to bottom LAWS Simulation Models for global and regional scale simulations were developed. The algorithm development incorporated the effects of aerosols, water vapor, clouds, terrain, and atmospheric turbulence into the models. Other additions include a new satellite orbiter, signal processor, line of sight uncertainty model, new Multi-Paired Algorithm and wind error analysis code. An atmospheric wind field library containing control fields, meteorological fields, phenomena fields, and new European Center for Medium Range Weather Forecasting (ECMWF) data was also added. The LSM was used to address some key LAWS issues and trades such as accuracy and interpretation of LAWS information, data density, signal strength, cloud obscuration, and temporal data resolution.
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Impact of lateral boundary conditions on regional analyses
NASA Astrophysics Data System (ADS)
Chikhar, Kamel; Gauthier, Pierre
2017-04-01
Regional and global climate models are usually validated by comparison to derived observations or reanalyses. Using a model in data assimilation results in a direct comparison to observations to produce its own analyses that may reveal systematic errors. In this study, regional analyses over North America are produced based on the fifth-generation Canadian Regional Climate Model (CRCM5) combined with the variational data assimilation system of the Meteorological Service of Canada (MSC). CRCM5 is driven at its boundaries by global analyses from ERA-interim or produced with the global configuration of the CRCM5. Assimilation cycles for the months of January and July 2011 revealed systematic errors in winter through large values in the mean analysis increments. This bias is attributed to the coupling of the lateral boundary conditions of the regional model with the driving data particularly over the northern boundary where a rapidly changing large scale circulation created significant cross-boundary flows. Increasing the time frequency of the lateral driving and applying a large-scale spectral nudging improved significantly the circulation through the lateral boundaries which translated in a much better agreement with observations.
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NASA Astrophysics Data System (ADS)
Biercamp, Joachim; Adamidis, Panagiotis; Neumann, Philipp
2017-04-01
With the exa-scale era approaching, length and time scales used for climate research on one hand and numerical weather prediction on the other hand blend into each other. The Centre of Excellence in Simulation of Weather and Climate in Europe (ESiWACE) represents a European consortium comprising partners from climate, weather and HPC in their effort to address key scientific challenges that both communities have in common. A particular challenge is to reach global models with spatial resolutions that allow simulating convective clouds and small-scale ocean eddies. These simulations would produce better predictions of trends and provide much more fidelity in the representation of high-impact regional events. However, running such models in operational mode, i.e with sufficient throughput in ensemble mode clearly will require exa-scale computing and data handling capability. We will discuss the ESiWACE initiative and relate it to work-in-progress on high-resolution simulations in Europe. We present recent strong scalability measurements from ESiWACE to demonstrate current computability in weather and climate simulation. A special focus in this particular talk is on the Icosahedal Nonhydrostatic (ICON) model used for a comparison of high resolution regional and global simulations with high quality observation data. We demonstrate that close-to-optimal parallel efficiency can be achieved in strong scaling global resolution experiments on Mistral/DKRZ, e.g. 94% for 5km resolution simulations using 36k cores on Mistral/DKRZ. Based on our scalability and high-resolution experiments, we deduce and extrapolate future capabilities for ICON that are expected for weather and climate research at exascale.
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NASA Astrophysics Data System (ADS)
wErnEr, B.
2012-12-01
Environmental challenges are dynamically generated within the dominant global culture principally by the mismatch between short-time-scale market and political forces driving resource extraction/use and longer-time-scale accommodations of the Earth system to these changes. Increasing resource demand is leading to the development of two-way, nonlinear interactions between human societies and environmental systems that are becoming global in extent, either through globalized markets and other institutions or through coupling to global environmental systems such as climate. These trends are further intensified by dissipation-reducing technological advances in transactions, communication and transport, which suppress emergence of longer-time-scale economic and political levels of description and facilitate long-distance connections, and by predictive environmental modeling, which strengthens human connections to a short-time-scale virtual Earth, and weakens connections to the longer time scales of the actual Earth. Environmental management seeks to steer fast scale economic and political interests of a coupled human-environmental system towards longer-time-scale consideration of benefits and costs by operating within the confines of the dominant culture using a linear, engineering-type connection to the system. Perhaps as evidenced by widespread inability to meaningfully address such global environmental challenges as climate change and soil degradation, nonlinear connections reduce the ability of managers to operate outside coupled human-environmental systems, decreasing their effectiveness in steering towards sustainable interactions and resulting in managers slaved to short-to-intermediate-term interests. In sum, the dynamics of the global coupled human-environmental system within the dominant culture precludes management for stable, sustainable pathways and promotes instability. Environmental direct action, resistance taken from outside the dominant culture, as in protests, blockades and sabotage by indigenous peoples, workers, anarchists and other activist groups, increases dissipation within the coupled system over fast to intermediate scales and pushes for changes in the dominant culture that favor transition to a stable, sustainable attractor. These dynamical relationships are illustrated and explored using a numerical model that simulates the short-, intermediate- and long-time-scale dynamics of the coupled human-environmental system. At fast scales, economic and political interests exploit environmental resources through a maze of environmental management and resistance, guided by virtual Earth predictions. At intermediate scales, managers become slaved to economic and political interests, which adapt to and repress resistance, and resistance is guided by patterns of environmental destruction. At slow scales, resistance interacts with the cultural context, which co-evolves with the environment. The transition from unstable dynamics to sustainability is sensitively dependent on the level of participation in and repression of resistance. Because of their differing impact inside and outside the dominant culture, virtual Earth predictions can either promote or oppose sustainability. Supported by the National Science Foundation, Geomorphology and Land Use Dynamics Program.
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NASA Astrophysics Data System (ADS)
Dutta, Dushmanta; Vaze, Jai; Kim, Shaun; Hughes, Justin; Yang, Ang; Teng, Jin; Lerat, Julien
2017-04-01
Existing global and continental scale river models, mainly designed for integrating with global climate models, are of very coarse spatial resolutions and lack many important hydrological processes, such as overbank flow, irrigation diversion, groundwater seepage/recharge, which operate at a much finer resolution. Thus, these models are not suitable for producing water accounts, which have become increasingly important for water resources planning and management at regional and national scales. A continental scale river system model called Australian Water Resource Assessment River System model (AWRA-R) has been developed and implemented for national water accounting in Australia using a node-link architecture. The model includes major hydrological processes, anthropogenic water utilisation and storage routing that influence the streamflow in both regulated and unregulated river systems. Two key components of the model are an irrigation model to compute water diversion for irrigation use and associated fluxes and stores and a storage-based floodplain inundation model to compute overbank flow from river to floodplain and associated floodplain fluxes and stores. The results in the Murray-Darling Basin shows highly satisfactory performance of the model with median daily Nash-Sutcliffe Efficiency (NSE) of 0.64 and median annual bias of less than 1% for the period of calibration (1970-1991) and median daily NSE of 0.69 and median annual bias of 12% for validation period (1992-2014). The results have demonstrated that the performance of the model is less satisfactory when the key processes such as overbank flow, groundwater seepage and irrigation diversion are switched off. The AWRA-R model, which has been operationalised by the Australian Bureau of Meteorology for continental scale water accounting, has contributed to improvements in the national water account by substantially reducing accounted different volume (gain/loss).
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Dynamical organization towards consensus in the Axelrod model on complex networks
NASA Astrophysics Data System (ADS)
Guerra, Beniamino; Poncela, Julia; Gómez-Gardeñes, Jesús; Latora, Vito; Moreno, Yamir
2010-05-01
We analyze the dynamics toward cultural consensus in the Axelrod model on scale-free networks. By looking at the microscopic dynamics of the model, we are able to show how culture traits spread across different cultural features. We compare the diffusion at the level of cultural features to the growth of cultural consensus at the global level, finding important differences between these two processes. In particular, we show that even when most of the cultural features have reached macroscopic consensus, there are still no signals of globalization. Finally, we analyze the topology of consensus clusters both for global culture and at the feature level of representation.
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Towards a unified Global Weather-Climate Prediction System
NASA Astrophysics Data System (ADS)
Lin, S. J.
2016-12-01
The Geophysical Fluid Dynamics Laboratory has been developing a unified regional-global modeling system with variable resolution capabilities that can be used for severe weather predictions and kilometer scale regional climate simulations within a unified global modeling system. The foundation of this flexible modeling system is the nonhydrostatic Finite-Volume Dynamical Core on the Cubed-Sphere (FV3). A unique aspect of FV3 is that it is "vertically Lagrangian" (Lin 2004), essentially reducing the equation sets to two dimensions, and is the single most important reason why FV3 outperforms other non-hydrostatic cores. Owning to its accuracy, adaptability, and computational efficiency, the FV3 has been selected as the "engine" for NOAA's Next Generation Global Prediction System (NGGPS). We have built into the modeling system a stretched grid, a two-way regional-global nested grid, and an optimal combination of the stretched and two-way nests capability, making kilometer-scale regional simulations within a global modeling system feasible. Our main scientific goal is to enable simulations of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously regarded as impossible. In this presentation I will demonstrate that, with the FV3, it is computationally feasible to simulate not only super-cell thunderstorms, but also the subsequent genesis of tornado-like vortices using a global model that was originally designed for climate simulations. The development and tuning strategy between traditional weather and climate models are fundamentally different due to different metrics. We were able to adapt and use traditional "climate" metrics or standards, such as angular momentum conservation, energy conservation, and flux balance at top of the atmosphere, and gain insight into problems of traditional weather prediction model for medium-range weather prediction, and vice versa. Therefore, the unification in weather and climate models can happen not just at the algorithm or parameterization level, but also in the metric and tuning strategy used for both applications, and ultimately, with benefits to both weather and climate applications.
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A Generalized Simple Formulation of Convective Adjustment ...
Convective adjustment timescale (τ) for cumulus clouds is one of the most influential parameters controlling parameterized convective precipitation in climate and weather simulation models at global and regional scales. Due to the complex nature of deep convection, a prescribed value or ad hoc representation of τ is used in most global and regional climate/weather models making it a tunable parameter and yet still resulting in uncertainties in convective precipitation simulations. In this work, a generalized simple formulation of τ for use in any convection parameterization for shallow and deep clouds is developed to reduce convective precipitation biases at different grid spacing. Unlike existing other methods, our new formulation can be used with field campaign measurements to estimate τ as demonstrated by using data from two different special field campaigns. Then, we implemented our formulation into a regional model (WRF) for testing and evaluation. Results indicate that our simple τ formulation can give realistic temporal and spatial variations of τ across continental U.S. as well as grid-scale and subgrid scale precipitation. We also found that as the grid spacing decreases (e.g., from 36 to 4-km grid spacing), grid-scale precipitation dominants over subgrid-scale precipitation. The generalized τ formulation works for various types of atmospheric conditions (e.g., continental clouds due to heating and large-scale forcing over la
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Global sensitivity analysis of multiscale properties of porous materials
NASA Astrophysics Data System (ADS)
Um, Kimoon; Zhang, Xuan; Katsoulakis, Markos; Plechac, Petr; Tartakovsky, Daniel M.
2018-02-01
Ubiquitous uncertainty about pore geometry inevitably undermines the veracity of pore- and multi-scale simulations of transport phenomena in porous media. It raises two fundamental issues: sensitivity of effective material properties to pore-scale parameters and statistical parameterization of Darcy-scale models that accounts for pore-scale uncertainty. Homogenization-based maps of pore-scale parameters onto their Darcy-scale counterparts facilitate both sensitivity analysis (SA) and uncertainty quantification. We treat uncertain geometric characteristics of a hierarchical porous medium as random variables to conduct global SA and to derive probabilistic descriptors of effective diffusion coefficients and effective sorption rate. Our analysis is formulated in terms of solute transport diffusing through a fluid-filled pore space, while sorbing to the solid matrix. Yet it is sufficiently general to be applied to other multiscale porous media phenomena that are amenable to homogenization.
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NASA Astrophysics Data System (ADS)
Malekan, Mohammad; Barros, Felício B.
2017-12-01
Generalized or extended finite element method (G/XFEM) models the crack by enriching functions of partition of unity type with discontinuous functions that represent well the physical behavior of the problem. However, this enrichment functions are not available for all problem types. Thus, one can use numerically-built (global-local) enrichment functions to have a better approximate procedure. This paper investigates the effects of micro-defects/inhomogeneities on a main crack behavior by modeling the micro-defects/inhomogeneities in the local problem using a two-scale G/XFEM. The global-local enrichment functions are influenced by the micro-defects/inhomogeneities from the local problem and thus change the approximate solution of the global problem with the main crack. This approach is presented in detail by solving three different linear elastic fracture mechanics problems for different cases: two plane stress and a Reissner-Mindlin plate problems. The numerical results obtained with the two-scale G/XFEM are compared with the reference solutions from the analytical, numerical solution using standard G/XFEM method and ABAQUS as well, and from the literature.
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A new Method for the Estimation of Initial Condition Uncertainty Structures in Mesoscale Models
NASA Astrophysics Data System (ADS)
Keller, J. D.; Bach, L.; Hense, A.
2012-12-01
The estimation of fast growing error modes of a system is a key interest of ensemble data assimilation when assessing uncertainty in initial conditions. Over the last two decades three methods (and variations of these methods) have evolved for global numerical weather prediction models: ensemble Kalman filter, singular vectors and breeding of growing modes (or now ensemble transform). While the former incorporates a priori model error information and observation error estimates to determine ensemble initial conditions, the latter two techniques directly address the error structures associated with Lyapunov vectors. However, in global models these structures are mainly associated with transient global wave patterns. When assessing initial condition uncertainty in mesoscale limited area models, several problems regarding the aforementioned techniques arise: (a) additional sources of uncertainty on the smaller scales contribute to the error and (b) error structures from the global scale may quickly move through the model domain (depending on the size of the domain). To address the latter problem, perturbation structures from global models are often included in the mesoscale predictions as perturbed boundary conditions. However, the initial perturbations (when used) are often generated with a variant of an ensemble Kalman filter which does not necessarily focus on the large scale error patterns. In the framework of the European regional reanalysis project of the Hans-Ertel-Center for Weather Research we use a mesoscale model with an implemented nudging data assimilation scheme which does not support ensemble data assimilation at all. In preparation of an ensemble-based regional reanalysis and for the estimation of three-dimensional atmospheric covariance structures, we implemented a new method for the assessment of fast growing error modes for mesoscale limited area models. The so-called self-breeding is development based on the breeding of growing modes technique. Initial perturbations are integrated forward for a short time period and then rescaled and added to the initial state again. Iterating this rapid breeding cycle provides estimates for the initial uncertainty structure (or local Lyapunov vectors) given a specific norm. To avoid that all ensemble perturbations converge towards the leading local Lyapunov vector we apply an ensemble transform variant to orthogonalize the perturbations in the sub-space spanned by the ensemble. By choosing different kind of norms to measure perturbation growth, this technique allows for estimating uncertainty patterns targeted at specific sources of errors (e.g. convection, turbulence). With case study experiments we show applications of the self-breeding method for different sources of uncertainty and different horizontal scales.
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Estimating heterotrophic respiration at large scales: challenges, approaches, and next steps
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bond-Lamberty, Benjamin; Epron, Daniel; Harden, Jennifer W.
2016-06-27
Heterotrophic respiration (HR), the aerobic and anaerobic processes mineralizing organic matter, is a key carbon flux but one impossible to measure at scales significantly larger than small experimental plots. This impedes our ability to understand carbon and nutrient cycles, benchmark models, or reliably upscale point measurements. Given that a new generation of highly mechanistic, genomic-specific global models is not imminent, we suggest that a useful step to improve this situation would be the development of "Decomposition Functional Types" (DFTs). Analogous to plant functional types (PFTs), DFTs would abstract and capture important differences in HR metabolism and flux dynamics, allowing modelsmore » to efficiently group and vary these characteristics across space and time. We argue that DFTs should be initially informed by top-down expert opinion, but ultimately developed using bottom-up, data-driven analyses, and provide specific examples of potential dependent and independent variables that could be used. We present and discuss an example clustering analysis to show how model-produced annual HR can be broken into distinct groups associated with global variability in biotic and abiotic factors, and demonstrate that these groups are distinct from already-existing PFTs. A similar analysis, incorporating observational data, could form a basis for future DFTs. Finally, we suggest next steps and critical priorities: collection and synthesis of existing data; more in-depth analyses combining open data with high-performance computing; rigorous testing of analytical results; and planning by the global modeling community for decoupling decomposition from fixed site data. These are all critical steps to build a foundation for DFTs in global models, thus providing the ecological and climate change communities with robust, scalable estimates of HR at large scales.« less
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The status and challenge of global fire modelling
Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; ...
2016-06-09
Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less
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The status and challenge of global fire modelling
NASA Astrophysics Data System (ADS)
Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; Kelley, Douglas I.; Prentice, I. Colin; Rabin, Sam S.; Archibald, Sally; Mouillot, Florent; Arnold, Steve R.; Artaxo, Paulo; Bachelet, Dominique; Ciais, Philippe; Forrest, Matthew; Friedlingstein, Pierre; Hickler, Thomas; Kaplan, Jed O.; Kloster, Silvia; Knorr, Wolfgang; Lasslop, Gitta; Li, Fang; Mangeon, Stephane; Melton, Joe R.; Meyn, Andrea; Sitch, Stephen; Spessa, Allan; van der Werf, Guido R.; Voulgarakis, Apostolos; Yue, Chao
2016-06-01
Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.
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The status and challenge of global fire modelling
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.
Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less
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Changes in Intense Precipitation Events in West Africa and the central U.S. under Global Warming
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cook, Kerry H.; Vizy, Edward
The purpose of the proposed project is to improve our understanding of the physical processes and large-scale connectivity of changes in intense precipitation events (high rainfall rates) under global warming in West Africa and the central U.S., including relationships with low-frequency modes of variability. This is in response to the requested subject area #2 “simulation of climate extremes under a changing climate … to better quantify the frequency, duration, and intensity of extreme events under climate change and elucidate the role of low frequency climate variability in modulating extremes.” We will use a regional climate model and emphasize an understandingmore » of the physical processes that lead to an intensification of rainfall. The project objectives are as follows: 1. Understand the processes responsible for simulated changes in warm-season rainfall intensity and frequency over West Africa and the Central U.S. associated with greenhouse gas-induced global warming 2. Understand the relationship between changes in warm-season rainfall intensity and frequency, which generally occur on regional space scales, and the larger-scale global warming signal by considering modifications of low-frequency modes of variability. 3. Relate changes simulated on regional space scales to global-scale theories of how and why atmospheric moisture levels and rainfall should change as climate warms.« less
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NASA Astrophysics Data System (ADS)
Jang, W.; Engda, T. A.; Neff, J. C.; Herrick, J.
2017-12-01
Many crop models are increasingly used to evaluate crop yields at regional and global scales. However, implementation of these models across large areas using fine-scale grids is limited by computational time requirements. In order to facilitate global gridded crop modeling with various scenarios (i.e., different crop, management schedule, fertilizer, and irrigation) using the Environmental Policy Integrated Climate (EPIC) model, we developed a distributed parallel computing framework in Python. Our local desktop with 14 cores (28 threads) was used to test the distributed parallel computing framework in Iringa, Tanzania which has 406,839 grid cells. High-resolution soil data, SoilGrids (250 x 250 m), and climate data, AgMERRA (0.25 x 0.25 deg) were also used as input data for the gridded EPIC model. The framework includes a master file for parallel computing, input database, input data formatters, EPIC model execution, and output analyzers. Through the master file for parallel computing, the user-defined number of threads of CPU divides the EPIC simulation into jobs. Then, Using EPIC input data formatters, the raw database is formatted for EPIC input data and the formatted data moves into EPIC simulation jobs. Then, 28 EPIC jobs run simultaneously and only interesting results files are parsed and moved into output analyzers. We applied various scenarios with seven different slopes and twenty-four fertilizer ranges. Parallelized input generators create different scenarios as a list for distributed parallel computing. After all simulations are completed, parallelized output analyzers are used to analyze all outputs according to the different scenarios. This saves significant computing time and resources, making it possible to conduct gridded modeling at regional to global scales with high-resolution data. For example, serial processing for the Iringa test case would require 113 hours, while using the framework developed in this study requires only approximately 6 hours, a nearly 95% reduction in computing time.
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NASA Technical Reports Server (NTRS)
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.
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NASA Astrophysics Data System (ADS)
Bring, Arvid; Asokan, Shilpa M.; Jaramillo, Fernando; Jarsjö, Jerker; Levi, Lea; Pietroń, Jan; Prieto, Carmen; Rogberg, Peter; Destouni, Georgia
2015-06-01
The multimodel ensemble of the Coupled Model Intercomparison Project, Phase 5 (CMIP5) synthesizes the latest research in global climate modeling. The freshwater system on land, particularly runoff, has so far been of relatively low priority in global climate models, despite the societal and ecosystem importance of freshwater changes, and the science and policy needs for such model output on drainage basin scales. Here we investigate the implications of CMIP5 multimodel ensemble output data for the freshwater system across a set of drainage basins in the Northern Hemisphere. Results of individual models vary widely, with even ensemble mean results differing greatly from observations and implying unrealistic long-term systematic changes in water storage and level within entire basins. The CMIP5 projections of basin-scale freshwater fluxes differ considerably more from observations and among models for the warm temperate study basins than for the Arctic and cold temperate study basins. In general, the results call for concerted research efforts and model developments for improving the understanding and modeling of the freshwater system and its change drivers. Specifically, more attention to basin-scale water flux analyses should be a priority for climate model development, and an important focus for relevant model-based advice for adaptation to climate change.
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NASA Astrophysics Data System (ADS)
Skamarock, W. C.
2015-12-01
One of the major problems in atmospheric model applications is the representation of deep convection within the models; explicit simulation of deep convection on fine meshes performs much better than sub-grid parameterized deep convection on coarse meshes. Unfortunately, the high cost of explicit convective simulation has meant it has only been used to down-scale global simulations in weather prediction and regional climate applications, typically using traditional one-way interactive nesting technology. We have been performing real-time weather forecast tests using a global non-hydrostatic atmospheric model (the Model for Prediction Across Scales, MPAS) that employs a variable-resolution unstructured Voronoi horizontal mesh (nominally hexagons) to span hydrostatic to nonhydrostatic scales. The smoothly varying Voronoi mesh eliminates many downscaling problems encountered using traditional one- or two-way grid nesting. Our test weather forecasts cover two periods - the 2015 Spring Forecast Experiment conducted at the NOAA Storm Prediction Center during the month of May in which we used a 50-3 km mesh, and the PECAN field program examining nocturnal convection over the US during the months of June and July in which we used a 15-3 km mesh. An important aspect of this modeling system is that the model physics be scale-aware, particularly the deep convection parameterization. These MPAS simulations employ the Grell-Freitas scale-aware convection scheme. Our test forecasts show that the scheme produces a gradual transition in the deep convection, from the deep unstable convection being handled entirely by the convection scheme on the coarse mesh regions (dx > 15 km), to the deep convection being almost entirely explicit on the 3 km NA region of the meshes. We will present results illustrating the performance of critical aspects of the MPAS model in these tests.
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Visualization and dissemination of global crustal models on virtual globes
NASA Astrophysics Data System (ADS)
Zhu, Liang-feng; Pan, Xin; Sun, Jian-zhong
2016-05-01
Global crustal models, such as CRUST 5.1 and its descendants, are very useful in a broad range of geoscience applications. The current method for representing the existing global crustal models relies heavily on dedicated computer programs to read and work with those models. Therefore, it is not suited to visualize and disseminate global crustal information to non-geological users. This shortcoming is becoming obvious as more and more people from both academic and non-academic institutions are interested in understanding the structure and composition of the crust. There is a pressing need to provide a modern, universal and user-friendly method to represent and visualize the existing global crustal models. In this paper, we present a systematic framework to easily visualize and disseminate the global crustal structure on virtual globes. Based on crustal information exported from the existing global crustal models, we first create a variety of KML-formatted crustal models with different levels of detail (LODs). And then the KML-formatted models can be loaded into a virtual globe for 3D visualization and model dissemination. A Keyhole Markup Language (KML) generator (Crust2KML) is developed to automatically convert crustal information obtained from the CRUST 1.0 model into KML-formatted global crustal models, and a web application (VisualCrust) is designed to disseminate and visualize those models over the Internet. The presented framework and associated implementations can be conveniently exported to other applications to support visualizing and analyzing the Earth's internal structure on both regional and global scales in a 3D virtual-globe environment.
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Will E-Business Shape the Future of Open and Distance Learning?
ERIC Educational Resources Information Center
Oblinger, Diana
2001-01-01
Explores the impact that electronic business is likely to have on the growth of open and distance learning. Discusses global consortia and global virtual universities; technological developments, including Web qualities; value chains; pricing models; the importance of scale; operating efficiencies; and increasing competition. (Author/LRW)
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NASA Technical Reports Server (NTRS)
Roble, R. G.; Hays, P. B.
1979-01-01
The paper presents a model of global atmospheric electricity used to examine the effect of upper atmospheric generators on the global electrical circuit. The model represents thunderstorms as dipole current generators randomly distributed in areas of known thunderstorm frequency; the electrical conductivity in the model increases with altitude, and electrical effects are coupled with a passive magnetosphere along geomagnetic field lines. The large horizontal-scale potential differences at ionospheric heights map downward into the lower atmosphere where the perturbations in the ground electric field are superimposed on the diurnal variation. Finally, changes in the upper atmospheric conductivity due to solar flares, polar cap absorptions, and Forbush decreases are shown to alter the downward mapping of the high-latitude potential pattern and the global distribution of fields and currents.
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NASA Astrophysics Data System (ADS)
Pritchard, M. S.; Kooperman, G. J.; Zhao, Z.; Wang, M.; Russell, L. M.; Somerville, R. C.; Ghan, S. J.
2011-12-01
Evaluating the fidelity of new aerosol physics in climate models is confounded by uncertainties in source emissions, systematic error in cloud parameterizations, and inadequate sampling of long-range plume concentrations. To explore the degree to which cloud parameterizations distort aerosol processing and scavenging, the Pacific Northwest National Laboratory (PNNL) Aerosol-Enabled Multi-Scale Modeling Framework (AE-MMF), a superparameterized branch of the Community Atmosphere Model Version 5 (CAM5), is applied to represent the unusually active and well sampled North American wildfire season in 2004. In the AE-MMF approach, the evolution of double moment aerosols in the exterior global resolved scale is linked explicitly to convective statistics harvested from an interior cloud resolving scale. The model is configured in retroactive nudged mode to observationally constrain synoptic meteorology, and Arctic wildfire activity is prescribed at high space/time resolution using data from the Global Fire Emissions Database. Comparisons against standard CAM5 bracket the effect of superparameterization to isolate the role of capturing rainfall intermittency on the bulk characteristics of 2004 Arctic plume transport. Ground based lidar and in situ aircraft wildfire plume constraints from the International Consortium for Atmospheric Research on Transport and Transformation field campaign are used as a baseline for model evaluation.
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NASA Astrophysics Data System (ADS)
Featherstone, Nicholas A.; Miesch, Mark S.
2013-03-01
Meridional circulations and rotational shear serve as a key ingredient in many models of the solar dynamo, likely playing an important role in the maintenance and timing of the solar cycle. These global-scale flows must themselves be driven by the large-scale overturning convection thought to pervade the outer layers of the Sun. As these deep interior motions are inaccessible to local helioseismic analyses in virtually all respects, global-scale numerical models have become a widely-used tool for probing their dynamics. Such models must confront a number of challenges, however, if they are to yield an accurate description of the convection zone. These difficulties stem in part from the Sun's location in parameter space being far removed from anything accessible to modern supercomputers, but also from questions concerning how to best capture the salient, but generally unresolvable, physics of the tachocline and near-photospheric layers. In recent years, global-scale models have made good contact with observations in spite of these challenges, presumably owing to their ability to accurately reflect the large-scale balances established throughout the convection zone. Due to their success in reproducing many aspects of the solar differential rotation and the solar cycle in particular, we might be encouraged to ask what insights numerical models can provide into phenomena that are much more difficult to observe directly. Of particular interest is the possibility that deep modeling efforts might provide some glimpses into the nature of the Sun's deep meridional circulation. I will describe the essential elements common amongst many global-scale models of the solar convection zone, with some discussion of the strengths and weaknesses associated with the assumptions inherent in a typical model setup. I will then present a class of solar convection models that demonstrate the existence of two distinct regimes of meridional circulation. These two regimes depend predominantly on the the vigor of the convective driving and possess, in one instance, a single monolithic cell of circulation in each hemisphere, and in the other instance, a single cell at high latitudes with multiple cells at low latitudes. The transition between these two regimes in the context of solar simulations serves to motivate the need for careful treatment of heat transport in the upper and lower convection zone. After discussing the nature of this transition, I will examine how thermal perturbations associated with the inclusion of a tachocline might alter this phenomenon. Finally, I will compare various strategies employed by different authors to address the nature of heat transport in the upper boundary layer, focusing on the implications of each approach for the resulting velocity amplitudes and the convective heat flux established throughout the bulk of the convection zone. Convective amplitudes associated with those regimes that produce a nearly solar-like differential rotation are in generally good agreement with those based on theoretical predictions, but are somewhat higher than those inferred through helioseismic analysis.
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3D Reconnection and SEP Considerations in the CME-Flare Problem
NASA Astrophysics Data System (ADS)
Moschou, S. P.; Cohen, O.; Drake, J. J.; Sokolov, I.; Borovikov, D.; Alvarado Gomez, J. D.; Garraffo, C.
2017-12-01
Reconnection is known to play a major role in particle acceleration in both solar and astrophysical regimes, yet little is known about its connection with the global scales and its comparative contribution in the generation of SEPs with respect to other acceleration mechanisms, such as the shock at a fast CME front, in the presence of a global structure such as a CME. Coupling efforts, combining both particle and global scales, are necessary to answer questions about the fundamentals of the energetic processes evolved. We present such a coupling modeling effort that looks into particle acceleration through reconnection in a self-consistent CME-flare model in both particle and fluid regimes. Of special interest is the supra-thermal component of the acceleration due to the reconnection that will at a later time interact colliding with the solar atmospheric material of the more dense chromospheric layer and radiate in hard X- and γ-rays for super-thermal electrons and protons respectively. Two cutting edge computational codes are used to capture the global CME and flare dynamics, specifically a two fluid MHD code and a 3D PIC code for the flare scales. Finally, we are connecting the simulations with current observations in different wavelengths in an effort to shed light to the unified CME-flare picture.
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NASA Astrophysics Data System (ADS)
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. We analyze the differences obtained using a simpler fluorescence model in ORCHIDEE hypothesizing a linear relationship between SIF and GPP, and an independent simultaneous assimilation of three data-streams (in situ flux measurements, satellite derived NDVI and atmospheric CO2 concentrations).
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Kenneth F. Raffa; Brian H. Aukema; Barbara J. Bentz; Allan L. Carroll; Jeffrey A. Hicke; Monica G. Turner; William H. Romme
2008-01-01
Biome-scale disturbances by eruptive herbivores provide valuable insights into species interactions, ecosystem-function, and impacts of global change. We present a conceptual framework using one system as a model, emphasizing interactions across levels of biological hierarchy and spatiotemporal scales. Bark beetles are major natural disturbance agents in western North...
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Factorial Structure of Rosenberg's Self-Esteem Scale among Crack-Cocaine Drug Users.
ERIC Educational Resources Information Center
Wang, Jichuan; Siegal, Harvey A.; Falck, Russell S.; Carlson, Robert G.
2001-01-01
Used nine different confirmatory factor analysis models to test the factorial structure of Rosenberg's (M. Rosenberg, 1965) self-esteem scale with a sample of 430 crack-cocaine users. Results partly support earlier research to show a single global self-esteem factor underlying responses to the Rosenberg scale, method effects associated with item…
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Xiong, Wei; Balkovic, Juraj; van der Velde, M.
Crop models are increasingly used to assess impacts of climate change/variability and management practices on productivity and environmental performance of alternative cropping systems. Calibration is an important procedure to improve reliability of model simulations, especially for large area applications. However, global-scale crop model calibration has rarely been exercised due to limited data availability and expensive computing cost. Here we present a simple approach to calibrate Environmental Policy Integrated Climate (EPIC) model for a global implementation of rice. We identify four parameters (potential heat unit – PHU, planting density – PD, harvest index – HI, and biomass energy ratio – BER)more » and calibrate them regionally to capture the spatial pattern of reported rice yield in 2000. Model performance is assessed by comparing simulated outputs with independent FAO national data. The comparison demonstrates that the global calibration scheme performs satisfactorily in reproducing the spatial pattern of rice yield, particularly in main rice production areas. Spatial agreement increases substantially when more parameters are selected and calibrated, but with varying efficiencies. Among the parameters, PHU and HI exhibit the highest efficiencies in increasing the spatial agreement. Simulations with different calibration strategies generate a pronounced discrepancy of 5–35% in mean yields across latitude bands, and a small to moderate difference in estimated yield variability and yield changing trend for the period of 1981–2000. Present calibration has little effects in improving simulated yield variability and trends at both regional and global levels, suggesting further works are needed to reproduce temporal variability of reported yields. This study highlights the importance of crop models’ calibration, and presents the possibility of a transparent and consistent up scaling approach for global crop simulations given current availability of global databases of weather, soil, crop calendar, fertilizer and irrigation management information, and reported yield.« less
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NASA Astrophysics Data System (ADS)
Chanard, Kristel; Fleitout, Luce; Calais, Eric; Rebischung, Paul; Avouac, Jean-Philippe
2018-04-01
We model surface displacements induced by variations in continental water, atmospheric pressure, and nontidal oceanic loading, derived from the Gravity Recovery and Climate Experiment (GRACE) for spherical harmonic degrees two and higher. As they are not observable by GRACE, we use at first the degree-1 spherical harmonic coefficients from Swenson et al. (2008, https://doi.org/10.1029/2007JB005338). We compare the predicted displacements with the position time series of 689 globally distributed continuous Global Navigation Satellite System (GNSS) stations. While GNSS vertical displacements are well explained by the model at a global scale, horizontal displacements are systematically underpredicted and out of phase with GNSS station position time series. We then reestimate the degree 1 deformation field from a comparison between our GRACE-derived model, with no a priori degree 1 loads, and the GNSS observations. We show that this approach reconciles GRACE-derived loading displacements and GNSS station position time series at a global scale, particularly in the horizontal components. Assuming that they reflect surface loading deformation only, our degree-1 estimates can be translated into geocenter motion time series. We also address and assess the impact of systematic errors in GNSS station position time series at the Global Positioning System (GPS) draconitic period and its harmonics on the comparison between GNSS and GRACE-derived annual displacements. Our results confirm that surface mass redistributions observed by GRACE, combined with an elastic spherical and layered Earth model, can be used to provide first-order corrections for loading deformation observed in both horizontal and vertical components of GNSS station position time series.
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NASA Astrophysics Data System (ADS)
Sulman, B. N.; Brzostek, E. R.; Menge, D.; Malyshev, S.; Shevliakova, E.
2017-12-01
Earth System Model (ESM) projections of terrestrial carbon (C) uptake are critical to understanding the future of the global C cycle. Current ESMs include intricate representations of photosynthetic C fixation in plants, allowing them to simulate the stimulatory effect of increasing atmospheric CO2 levels on photosynthesis. However, they lack sophisticated representations of plant nutrient acquisition, calling into question their ability to project the future land C sink. We conducted simulations using a new model of terrestrial C and nitrogen (N) cycling within the Geophysical Fluid Dynamics Laboratory (GFDL) global land model LM4 that uses a return on investment framework to simulate global patterns of N acquisition via fixation of N2 from the atmosphere, scavenging of inorganic N from soil solution, and mining of organic N from soil organic matter (SOM). We show that these strategies drive divergent C cycle responses to elevated CO2 at the ecosystem scale, with the scavenging strategy leading to N limitation of plant growth and the mining strategy facilitating stimulation of plant biomass accumulation over decadal time scales. In global simulations, shifts in N acquisition from inorganic N scavenging to organic N mining along with increases in N fixation supported long-term acceleration of C uptake under elevated CO2. Our results indicate that the ability of the land C sink to mitigate atmospheric CO2 levels is tightly coupled to the functional diversity of ecosystems and their capacity to change their N acquisition strategies over time. Incorporation of these mechanisms into ESMs is necessary to improve confidence in model projections of the global C cycle.
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Phillips, Rachel; Gandhi, Mihir; Cheung, Yin Bun; Findlay, Michael P; Win, Khin Maung; Hai, Hoang Hoa; Yang, Jin Mo; Lobo, Rolley Rey; Soo, Khee Chee; Chow, Pierce K H
2015-08-01
To examine the performance of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) global health status/quality of life (QoL) scale and two summary scores to detect changes in the QoL profile over time, according to changes in the individual scales. Data came from 167 clinical trial patients with unresectable (advanced) hepatocellular carcinoma. The global health status/QoL scale of the questionnaire contained two items: overall health and overall QoL. Nordin and Hinz proposed summary scores for the questionnaire. A mixed-effect model was fitted to estimate trends in scores over time. Predominantly the individual scale scores declined over time; however, the global health status/QoL score was stable [rate of change = -0.3 per month; 95% confidence interval (CI): -1.2, 0.6]. Nordin's summary score, which gave equal weight to the 15 questionnaire scales, and Hinz's summary score, which gave equal weight to the 30 questionnaire items, showed a statistically significant decline over time, 3.4 (95% CI: -4.5, -2.4) and 4.2 (95% CI: -5.3, -3.0) points per month, respectively. In contrast to the global health status/QoL scale, the summary scores proposed by Nordin and Hinz detected changes in subjects' QoL profile described by the EORTC QLQ-C30 individual scales. Copyright © 2015 Elsevier Inc. All rights reserved.
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Sabbagh, Robert; Chatterjee, Suman; Chawla, Arun; Hoogenes, Jen; Kapoor, Anil; Matsumoto, Edward D
2012-05-01
Learning laparoscopic urethrovesical anastomosis is a crucial step in laparoscopic radical prostatectomy. Previously we noted that practice on a low fidelity urethrovesical model was more effective for trainees than basic suturing drills on a foam pad when learning laparoscopic urethrovesical anastomosis skills. We evaluated learner transfer of skills, specifically whether skills learned on the urethrovesical model would transfer to a high fidelity, live animal model. A total of 28 senior residents, fellows and staff surgeons in urology, general surgery and gynecology were randomized to 2 hours of laparoscopic urethrovesical anastomosis training on a urethrovesical model (group 1) or to basic laparoscopic suturing and knot tying on foam pads (group 2). All participants then performed timed laparoscopic urethrovesical anastomosis on anesthetized female pigs. A blinded urologist scored subject videotaped performance using checklist, global rating scale and end product rating scores. Group 1 was significantly more adept than group 2 at the laparoscopic urethrovesical anastomosis pig task when measured by the checklist, global rating scale and end product rating (each p <0.05). Time to completion was similar in the 2 groups. No statistically significant difference was noted in global rating scale and checklist scores for laparoscopic urethrovesical anastomosis performed on the urethrovesical model vs the pig. Training on a urethrovesical model is superior to training with basic laparoscopic suturing on a foam pad for performing laparoscopic urethrovesical anastomosis skills on an anesthetized female pig. Skills learned on a urethrovesical model transfer to a high fidelity, live animal model. Copyright © 2012 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.
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Recent assimilation developments of FOAM the Met Office ocean forecast system
NASA Astrophysics Data System (ADS)
Lea, Daniel; Martin, Matthew; Waters, Jennifer; Mirouze, Isabelle; While, James; King, Robert
2015-04-01
FOAM is the Met Office's operational ocean forecasting system. This system comprises a range of models from a 1/4 degree resolution global to 1/12 degree resolution regional models and shelf seas models at 7 km resolution. The system is made up of the ocean model NEMO (Nucleus for European Modeling of the Ocean), the Los Alomos sea ice model CICE and the NEMOVAR assimilation run in 3D-VAR FGAT mode. Work is ongoing to transition to both a higher resolution global ocean model at 1/12 degrees and to run FOAM in coupled models. The FOAM system generally performs well. One area of concern however is the performance in the tropics where spurious oscillations and excessive vertical velocity gradients are found after assimilation. NEMOVAR includes a balance operator which in the extra-tropics uses geostrophic balance to produce velocity increments which balance the density increments applied. In the tropics, however, the main balance is between the pressure gradients produced by the density gradient and the applied wind stress. A scheme is presented which aims to maintain this balance when increments are applied. Another issue in FOAM is that there are sometimes persistent temperature and salinity errors which are not effectively corrected by the assimilation. The standard NEMOVAR has a single correlation length scale based on the local Rossby radius. This means that observations in the extra tropics have influence on the model only on short length-scales. In order to maximise the information extracted from the observations and to correct large scale model biases a multiple correlation length-scale scheme has been developed. This includes a larger length scale which spreads observation information further. Various refinements of the scheme are also explored including reducing the longer length scale component at the edge of the sea ice and in areas with high potential vorticity gradients. A related scheme which varies the correlation length scale in the shelf seas is also described.
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Coupled land surface/hydrologic/atmospheric models
NASA Technical Reports Server (NTRS)
Pielke, Roger; Steyaert, Lou; Arritt, Ray; Lahtakia, Mercedes; Smith, Chris; Ziegler, Conrad; Soong, Su Tzai; Avissar, Roni; Wetzel, Peter; Sellers, Piers
1993-01-01
The topics covered include the following: prototype land cover characteristics data base for the conterminous United States; surface evapotranspiration effects on cumulus convection and implications for mesoscale models; the use of complex treatment of surface hydrology and thermodynamics within a mesoscale model and some related issues; initialization of soil-water content for regional-scale atmospheric prediction models; impact of surface properties on dryline and MCS evolution; a numerical simulation of heavy precipitation over the complex topography of California; representing mesoscale fluxes induced by landscape discontinuities in global climate models; emphasizing the role of subgrid-scale heterogeneity in surface-air interaction; and problems with modeling and measuring biosphere-atmosphere exchanges of energy, water, and carbon on large scales.
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An operational global-scale ocean thermal analysis system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Clancy, R. M.; Pollak, K.D.; Phoebus, P.A.
1990-04-01
The Optimum Thermal Interpolation System (OTIS) is an ocean thermal analysis system designed for operational use at FNOC. It is based on the optimum interpolation of the assimilation technique and functions in an analysis-prediction-analysis data assimilation cycle with the TOPS mixed-layer model. OTIS provides a rigorous framework for combining real-time data, climatology, and predictions from numerical ocean prediction models to produce a large-scale synoptic representation of ocean thermal structure. The techniques and assumptions used in OTIS are documented and results of operational tests of global scale OTIS at FNOC are presented. The tests involved comparisons of OTIS against an existingmore » operational ocean thermal structure model and were conducted during February, March, and April 1988. Qualitative comparison of the two products suggests that OTIS gives a more realistic representation of subsurface anomalies and horizontal gradients and that it also gives a more accurate analysis of the thermal structure, with improvements largest below the mixed layer. 37 refs.« less