Failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Klein, R.; Tannahill, J.; Ivanova, D.; Brandon, S.; Domyancic, D.; Zhang, Y.

2013-08-01

Simulations using IPCC (Intergovernmental Panel on Climate Change)-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We applied support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicted model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures were determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations were the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.

Towards a community Earth System Model

NASA Astrophysics Data System (ADS)

Blackmon, M.

2003-04-01

The Community Climate System Model, version 2 (CCSM2), was released in June 2002. CCSM2 has several new components and features, which I will discuss briefly. I will also show a few results from a multi-century equilibrium run with this model, emphasizing the improvements over the earlier simulation using the original CSM. A few flaws and inadequacies in CCSM2 have been identified. I will also discuss briefly work underway to improve the model and present results, if available. CCSM2, with improvements, will be the basis for the development of a Community Earth System Model (CESM). The highest priority for expansion of the model involves incorporation of biogeosciences into the coupled model system, with emphasis given to the carbon, nitrogen and iron cycles. The overall goal of the biogeosciences project within CESM is to understand the regulation of planetary energetics, planetary ecology, and planetary metabolism through exchanges of energy, momentum, and materials among atmosphere, land, and ocean, and the response of the climate system through these processes to changes in land cover and land use. In particular, this research addresses how biogeochemical coupling of carbon, nitrogen, and iron cycles affects climate and how human perturbations of these cycles alter climate. To accomplish these goals, the Community Land Model, the land component of CCSM2, is being developed to include river routing, carbon and nitrogen cycles, emissions of mineral aerosols and biogenic volatile organic compounds, dry deposition of various gases, and vegetation dynamics. The carbon and nitrogen cycles are being implemented using parameterizations developed as part of a state-of-the-art ecosystem biogeochemistry model. The primary goal of this research is to provide an accurate net flux of CO2 between the land and the atmosphere so that CESM can be used to study the dynamics of the coupled climate-carbon system. Emissions of biogenic volatile organic compounds are also based on a state-of-the-art emissions model and depend on plant type, leaf area index, photosynthetically active radiation, and leaf temperature. Dust emissions and deposition are being developed to implement a fully coupled dust cycle in CCSM, including the radiative effects of dust and carbon feedbacks related to fertilization of ocean and terrestrial ecosystems. Dust mobilization depends on surface wind speed, soil moisture, plant cover, and soil texture. Dust dry deposition processes include sedimentation and turbulent mix-out. A major research focus is how natural and human-mediated changes in land cover and ecosystem functions alter surface energy fluxes, the hydrological cycle, and biogeochemical cycles. Human land uses include conversion of natural vegetation to cropland, soil degradation, and urbanization. Climate feedbacks associated with natural changes in land cover are being assessed by developing and implementing a model of natural vegetation dynamics for use with the Community Land Model. Development of a marine ecosystem model is also underway. The ecosystem model is based on the global, mixed-layer marine ecosystem model of Moore et al., which includes parameterizations for such things as iron limitation and scavenging, zooplankton grazing, nitrogen fixation, calcification, and ballast-based remineralization. A series of experiments is being planned to assess the coupling of the ecology to the biogeochemistry, to adequately tune some of the model parameters that are poorly constrained by data, to explore new parameterizations and processes (e.g., riverine and atmospheric inputs of nutrients), and to conduct uncoupled application studies (e.g., deliberate carbon sequestration, retrospective historical simulations, iron-dust deposition response). Longer term plans include investigating biogeochemical processes in the coastal zone and how to incorporate these processes into a global ocean model, either through subgrid-scale parameterizations or model nesting. A Whole Atmosphere Community Climate Model(WACCM) is being developed. The vertical extent of the model is 150 km at present, but extension to 500 km is eventually expected. Interactive chemistry is being incorporated. This model will be used as the atmospheric component of CESM for some experiments. One expected application is the study of solar variability and its impact on climate variability in the troposphere and at the atmosphere, ocean, land interface. Preliminary results using some of these model components will be shown. A timeline for development and use of the models will be given.

Uncertainties in Future Regional Sea Level Trends: How to Deal with the Internal Climate Variability?

NASA Astrophysics Data System (ADS)

Becker, M.; Karpytchev, M.; Hu, A.; Deser, C.; Lennartz-Sassinek, S.

2017-12-01

Today, the Climate models (CM) are the main tools for forecasting sea level rise (SLR) at global and regional scales. The CM forecasts are accompanied by inherent uncertainties. Understanding and reducing these uncertainties is becoming a matter of increasing urgency in order to provide robust estimates of SLR impact on coastal societies, which need sustainable choices of climate adaptation strategy. These CM uncertainties are linked to structural model formulation, initial conditions, emission scenario and internal variability. The internal variability is due to complex non-linear interactions within the Earth Climate System and can induce diverse quasi-periodic oscillatory modes and long-term persistences. To quantify the effects of internal variability, most studies used multi-model ensembles or sea level projections from a single model ran with perturbed initial conditions. However, large ensembles are not generally available, or too small, and computationally expensive. In this study, we use a power-law scaling of sea level fluctuations, as observed in many other geophysical signals and natural systems, which can be used to characterize the internal climate variability. From this specific statistical framework, we (1) use the pre-industrial control run of the National Center for Atmospheric Research Community Climate System Model (NCAR-CCSM) to test the robustness of the power-law scaling hypothesis; (2) employ the power-law statistics as a tool for assessing the spread of regional sea level projections due to the internal climate variability for the 21st century NCAR-CCSM; (3) compare the uncertainties in predicted sea level changes obtained from a NCAR-CCSM multi-member ensemble simulations with estimates derived for power-law processes, and (4) explore the sensitivity of spatial patterns of the internal variability and its effects on regional sea level projections.

Simulating global and local surface temperature changes due to Holocene anthropogenic land cover change

NASA Astrophysics Data System (ADS)

He, F.; Vavrus, S. J.; Kutzbach, J. E.; Ruddiman, W. F.; Kaplan, J. O.; Krumhardt, K. M.

2015-12-01

Surface albedo changes from anthropogenic land cover change (ALCC) represent the second-largest negative radiative forcing behind aerosol during the industrial era. Using a new reconstruction of ALCC during the Holocene era by Kaplan et al. [2011], we quantify the local and global temperature response induced by Holocene ALCC in the Community Climate System Model, version 4 (CCSM4). With 1-degree resolution of the CCSM4 slab-ocean model,we find that Holocene ALCC cause a global cooling of 0.17 °C due to the biogeophysical effects of land-atmosphere exchange of momentum, moisture, radiative and heat fluxes. On the global scale, the biogeochemical effects of Holocene ALCC from carbon emissions dominate the biogeophysical effects by causing 0.9 °C global warming. The net effects of Holocene ALCC amount to a global warming of 0.73 °C during the pre-industrial era, which is comparable to the ~0.8 °C warming during industrial times. On local to regional scales, such as parts of Europe, North America and Asia, the biogeophysical effects of Holocene ALCC are significant and comparable to the biogeochemical effect. The lack of ocean dynamics in the 1° CCSM4 slab-ocean simulations could underestimate the climate sensitivity because of the lack of feedbacks from ocean heat transport [Kutzbach et al., 2013; Manabe and Bryan, 1985]. In 1° CCSM4 fully coupled simulations, the climate sensitivity is ~65% larger than the 1° CCSM4 slab-ocean simulations during the Holocene (5.3 °C versus 3.2 °C) [Kutzbach et al., 2013]. With this greater climate sensitivity, the biogeochemical effects of Holocene ALCC could have caused a global warming of ~1.5 °C, and the net biogeophysical and biogeochemical effects of Holocene ALCC could cause a global warming of 1.2 °C during the preindustrial era in our simulations, which is 50% higher than the global warming of ~0.8 °C during industrial times.

Climate change and watershed mercury export: a multiple projection and model analysis

USGS Publications Warehouse

Golden, Heather E.; Knightes, Christopher D.; Conrads, Paul; Feaster, Toby D.; Davis, Gary M.; Benedict, Stephen T.; Bradley, Paul M.

2013-01-01

Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. An ensemble of watershed models was applied in the present study to simulate and evaluate the responses of hydrological and total Hg (THg) fluxes from the landscape to the watershed outlet and in-stream THg concentrations to contrasting climate change projections for a watershed in the southeastern coastal plain of the United States. Simulations were conducted under stationary atmospheric deposition and land cover conditions to explicitly evaluate the effect of projected precipitation and temperature on watershed Hg export (i.e., the flux of Hg at the watershed outlet). Based on downscaled inputs from 2 global circulation models that capture extremes of projected wet (Community Climate System Model, Ver 3 [CCSM3]) and dry (ECHAM4/HOPE-G [ECHO]) conditions for this region, watershed model simulation results suggest a decrease of approximately 19% in ensemble-averaged mean annual watershed THg fluxes using the ECHO climate-change model and an increase of approximately 5% in THg fluxes with the CCSM3 model. Ensemble-averaged mean annual ECHO in-stream THg concentrations increased 20%, while those of CCSM3 decreased by 9% between the baseline and projected simulation periods. Watershed model simulation results using both climate change models suggest that monthly watershed THg fluxes increase during the summer, when projected flow is higher than baseline conditions. The present study's multiple watershed model approach underscores the uncertainty associated with climate change response projections and their use in climate change management decisions. Thus, single-model predictions can be misleading, particularly in developmental stages of watershed Hg modeling.

Military and Veteran Student Achievement in Postsecondary Education: A Structural Equation Model Using the Community College Survey of Men (CCSM)

ERIC Educational Resources Information Center

De LaGarza, Thomas R.; Manuel, Marcus A.; Wood, J. Luke; Harris, Frank, III

2016-01-01

Few quantitative studies exist on veteran success in postsecondary education, and existing qualitative research has also not accurately identified factors related to veteran achievement or pathways to success in postsecondary education. In this article, the Community College Survey of Men (CCSM) evaluates predictors of student success for…

Climate change and watershed mercury export: a multiple projection and model analysis.

PubMed

Golden, Heather E; Knightes, Christopher D; Conrads, Paul A; Feaster, Toby D; Davis, Gary M; Benedict, Stephen T; Bradley, Paul M

2013-09-01

Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. An ensemble of watershed models was applied in the present study to simulate and evaluate the responses of hydrological and total Hg (THg) fluxes from the landscape to the watershed outlet and in-stream THg concentrations to contrasting climate change projections for a watershed in the southeastern coastal plain of the United States. Simulations were conducted under stationary atmospheric deposition and land cover conditions to explicitly evaluate the effect of projected precipitation and temperature on watershed Hg export (i.e., the flux of Hg at the watershed outlet). Based on downscaled inputs from 2 global circulation models that capture extremes of projected wet (Community Climate System Model, Ver 3 [CCSM3]) and dry (ECHAM4/HOPE-G [ECHO]) conditions for this region, watershed model simulation results suggest a decrease of approximately 19% in ensemble-averaged mean annual watershed THg fluxes using the ECHO climate-change model and an increase of approximately 5% in THg fluxes with the CCSM3 model. Ensemble-averaged mean annual ECHO in-stream THg concentrations increased 20%, while those of CCSM3 decreased by 9% between the baseline and projected simulation periods. Watershed model simulation results using both climate change models suggest that monthly watershed THg fluxes increase during the summer, when projected flow is higher than baseline conditions. The present study's multiple watershed model approach underscores the uncertainty associated with climate change response projections and their use in climate change management decisions. Thus, single-model predictions can be misleading, particularly in developmental stages of watershed Hg modeling. Copyright © 2013 SETAC.

Uncertainty Quantification of Equilibrium Climate Sensitivity in CCSM4

NASA Astrophysics Data System (ADS)

Covey, C. C.; Lucas, D. D.; Tannahill, J.; Klein, R.

2013-12-01

Uncertainty in the global mean equilibrium surface warming due to doubled atmospheric CO2, as computed by a "slab ocean" configuration of the Community Climate System Model version 4 (CCSM4), is quantified using 1,039 perturbed-input-parameter simulations. The slab ocean configuration reduces the model's e-folding time when approaching an equilibrium state to ~5 years. This time is much less than for the full ocean configuration, consistent with the shallow depth of the upper well-mixed layer of the ocean represented by the "slab." Adoption of the slab ocean configuration requires the assumption of preset values for the convergence of ocean heat transport beneath the upper well-mixed layer. A standard procedure for choosing these values maximizes agreement with the full ocean version's simulation of the present-day climate when input parameters assume their default values. For each new set of input parameter values, we computed the change in ocean heat transport implied by a "Phase 1" model run in which sea surface temperatures and sea ice concentrations were set equal to present-day values. The resulting total ocean heat transport (= standard value + change implied by Phase 1 run) was then input into "Phase 2" slab ocean runs with varying values of atmospheric CO2. Our uncertainty estimate is based on Latin Hypercube sampling over expert-provided uncertainty ranges of N = 36 adjustable parameters in the atmosphere (CAM4) and sea ice (CICE4) components of CCSM4. Two-dimensional projections of our sampling distribution for the N(N-1)/2 possible pairs of input parameters indicate full coverage of the N-dimensional parameter space, including edges. We used a machine learning-based support vector regression (SVR) statistical model to estimate the probability density function (PDF) of equilibrium warming. This fitting procedure produces a PDF that is qualitatively consistent with the raw histogram of our CCSM4 results. Most of the values from the SVR statistical model are within ~0.1 K of the raw results, well below the inter-decile range inferred below. Independent validation of the fit indicates residual errors that are distributed about zero with a standard deviation of 0.17 K. Analysis of variance shows that the equilibrium warming in CCSM4 is mainly linear in parameter changes. Thus, in accord with the Central Limit Theorem of statistics, the PDF of the warming is approximately Gaussian, i.e. symmetric about its mean value (3.0 K). Since SVR allows for highly nonlinear fits, the symmetry is not an artifact of the fitting procedure. The 10-90 percentile range of the PDF is 2.6-3.4 K, consistent with earlier estimates from CCSM4 but narrower than estimates from other models, which sometimes produce a high-temperature asymmetric tail in the PDF. This work was performed under auspices of the US Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344, and was funded by LLNL's Uncertainty Quantification Strategic Initiative (Laboratory Directed Research and Development Project 10-SI-013).

Desert dust and anthropogenic aerosol interactions in the Community Climate System Model coupled-carbon-climate model

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

Mahowald, Natalie; Rothenberg, D.; Lindsay, Keith

2011-02-01

Coupled-carbon-climate simulations are an essential tool for predicting the impact of human activity onto the climate and biogeochemistry. Here we incorporate prognostic desert dust and anthropogenic aerosols into the CCSM3.1 coupled carbon-climate model and explore the resulting interactions with climate and biogeochemical dynamics through a series of transient anthropogenic simulations (20th and 21st centuries) and sensitivity studies. The inclusion of prognostic aerosols into this model has a small net global cooling effect on climate but does not significantly impact the globally averaged carbon cycle; we argue that this is likely to be because the CCSM3.1 model has a small climatemore » feedback onto the carbon cycle. We propose a mechanism for including desert dust and anthropogenic aerosols into a simple carbon-climate feedback analysis to explain the results of our and previous studies. Inclusion of aerosols has statistically significant impacts on regional climate and biogeochemistry, in particular through the effects on the ocean nitrogen cycle and primary productivity of altered iron inputs from desert dust deposition.« less

Internal Variability-Generated Uncertainty in East Asian Climate Projections Estimated with 40 CCSM3 Ensembles.

PubMed

Yao, Shuai-Lei; Luo, Jing-Jia; Huang, Gang

2016-01-01

Regional climate projections are challenging because of large uncertainty particularly stemming from unpredictable, internal variability of the climate system. Here, we examine the internal variability-induced uncertainty in precipitation and surface air temperature (SAT) trends during 2005-2055 over East Asia based on 40 member ensemble projections of the Community Climate System Model Version 3 (CCSM3). The model ensembles are generated from a suite of different atmospheric initial conditions using the same SRES A1B greenhouse gas scenario. We find that projected precipitation trends are subject to considerably larger internal uncertainty and hence have lower confidence, compared to the projected SAT trends in both the boreal winter and summer. Projected SAT trends in winter have relatively higher uncertainty than those in summer. Besides, the lower-level atmospheric circulation has larger uncertainty than that in the mid-level. Based on k-means cluster analysis, we demonstrate that a substantial portion of internally-induced precipitation and SAT trends arises from internal large-scale atmospheric circulation variability. These results highlight the importance of internal climate variability in affecting regional climate projections on multi-decadal timescales.

Detection and Attribution of Regional Climate Change

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

Bala, G; Mirin, A

2007-01-19

We developed a high resolution global coupled modeling capability to perform breakthrough studies of the regional climate change. The atmospheric component in our simulation uses a 1{sup o} latitude x 1.25{sup o} longitude grid which is the finest resolution ever used for the NCAR coupled climate model CCSM3. Substantial testing and slight retuning was required to get an acceptable control simulation. The major accomplishment is the validation of this new high resolution configuration of CCSM3. There are major improvements in our simulation of the surface wind stress and sea ice thickness distribution in the Arctic. Surface wind stress and oceanmore » circulation in the Antarctic Circumpolar Current are also improved. Our results demonstrate that the FV version of the CCSM coupled model is a state of the art climate model whose simulation capabilities are in the class of those used for IPCC assessments. We have also provided 1000 years of model data to Scripps Institution of Oceanography to estimate the natural variability of stream flow in California. In the future, our global model simulations will provide boundary data to high-resolution mesoscale model that will be used at LLNL. The mesoscale model would dynamically downscale the GCM climate to regional scale on climate time scales.« less

Regional trends in early-monsoon rainfall over Vietnam and CCSM4 attribution

NASA Astrophysics Data System (ADS)

Li, R.; Wang, S. S.-Y.; Gillies, R. R.; Buckley, B. M.; Yoon, J.-H.; Cho, C.

2018-04-01

The analysis of precipitation trends for Vietnam revealed that early-monsoon precipitation has increased over the past three decades but to varying degrees over the northern, central and southern portions of the country. Upon investigation, it was found that the change in early-monsoon precipitation is associated with changes in the low-level cyclonic airflow over the South China Sea and Indochina that is embedded in the large-scale atmospheric circulation associated with a "La Niña-like" anomalous sea surface temperature pattern with warming in the western Pacific and Indian Oceans and cooling in the eastern Pacific. The Community Climate System Model version 4 (CCSM4) was subsequently used for an attribution analysis. Over northern Vietnam an early-monsoon increase in precipitation is attributed to changes in both greenhouse gases and natural forcing. For central Vietnam, the observed increase in early-monsoon precipitation is reproduced by the simulation forced with greenhouse gases. However, over southern Vietnam the early-monsoon precipitation increase is less definitive where aerosols were seen to be preponderant but natural forcing through the role of the Interdecadal Pacific Oscillation may well be a factor that is not resolved by CCSM4. Increased early-monsoonal precipitation over the coastal lowland and deltas has the potential to amplify economic and human losses.

Future changes in regional precipitation simulated by a half-degree coupled climate model: Sensitivity to horizontal resolution

DOE PAGES

Shields, Christine A.; Kiehl, Jeffrey T.; Meehl, Gerald A.

2016-06-02

The global fully coupled half-degree Community Climate System Model Version 4 (CCSM4) was integrated for a suite of climate change ensemble simulations including five historical runs, five Representative Concentration Pathway 8.5 [RCP8.5) runs, and a long Pre-Industrial control run. This study focuses on precipitation at regional scales and its sensitivity to horizontal resolution. The half-degree historical CCSM4 simulations are compared to observations, where relevant, and to the standard 1° CCSM4. Both the halfdegree and 1° resolutions are coupled to a nominal 1° ocean. North American and South Asian/Indian monsoon regimes are highlighted because these regimes demonstrate improvements due to highermore » resolution, primarily because of better-resolved topography. Agriculturally sensitive areas are analyzed and include Southwest, Central, and Southeast U.S., Southern Europe, and Australia. Both mean and extreme precipitation is discussed for convective and large-scale precipitation processes. Convective precipitation tends to decrease with increasing resolution and large-scale precipitation tends to increase. Improvements for the half-degree agricultural regions can be found for mean and extreme precipitation in the Southeast U.S., Southern Europe, and Australian regions. Climate change responses differ between the model resolutions for the U.S. Southwest/Central regions and are seasonally dependent in the Southeast and Australian regions. Both resolutions project a clear drying signal across Southern Europe due to increased greenhouse warming. As a result, differences between resolutions tied to the representation of convective and large-scale precipitation play an important role in the character of the climate change and depend on regional influences.« less

Analyzing the Response of Climate Perturbations to (Tropical) Cyclones using the WRF Model

NASA Astrophysics Data System (ADS)

Tewari, M.; Mittal, R.; Radhakrishnan, C.; Cipriani, J.; Watson, C.

2015-12-01

An analysis of global climate models shows considerable changes in the intensity and characteristics of future, warm climate cyclones. At regional scales, deviations in cyclone characteristics are often derived using idealized perturbations in the humidity, temperature and surface conditions. In this work, a more realistic approach is adopted by applying climate perturbations from the Community Climate System Model (CCSM4) to ERA-interim data to generate the initial and boundary conditions for future climate simulations. The climate signal perturbations are generated from the differences in 21 years of mean data from CCSM4 with representative concentration pathways (RCP8.5) for the periods: (a) 2070-2090 (future climate), (b) 2025-2045 (near-future climate) and (c) 1985-2005 (current climate). Four individual cyclone cases are simulated with and without climate perturbations using the Weather Research and Forecasting model with a nested configuration. Each cyclone is characterized by variations in intensity, landfall location, precipitation and societal damage. To calculate societal damage, we use the recently introduced Cyclone Damage Potential (CDP) index evolved from the Willis Hurricane Index (WHI). As CDP has been developed for general societal applications, this work should provide useful insights for resilience analyses and industry (e.g., re-insurance).

PyMCT: A Very High Level Language Coupling Tool For Climate System Models

NASA Astrophysics Data System (ADS)

Tobis, M.; Pierrehumbert, R. T.; Steder, M.; Jacob, R. L.

2006-12-01

At the Climate Systems Center of the University of Chicago, we have been examining strategies for applying agile programming techniques to complex high-performance modeling experiments. While the "agile" development methodology differs from a conventional requirements process and its associated milestones, the process remain a formal one. It is distinguished by continuous improvement in functionality, large numbers of small releases, extensive and ongoing testing strategies, and a strong reliance on very high level languages (VHLL). Here we report on PyMCT, which we intend as a core element in a model ensemble control superstructure. PyMCT is a set of Python bindings for MCT, the Fortran-90 based Model Coupling Toolkit, which forms the infrastructure for the inter-component communication in the Community Climate System Model (CCSM). MCT provides a scalable model communication infrastructure. In order to take maximum advantage of agile software development methodologies, we exposed MCT functionality to Python, a prominent VHLL. We describe how the scalable architecture of MCT allows us to overcome the relatively weak runtime performance of Python, so that the performance of the combined system is not severely impacted. To demonstrate these advantages, we reimplemented the CCSM coupler in Python. While this alone offers no new functionality, it does provide a rigorous test of PyMCT functionality and performance. We reimplemented the CPL6 library, presenting an interesting case study of the comparison between conventional Fortran-90 programming and the higher abstraction level provided by a VHLL. The powerful abstractions provided by Python will allow much more complex experimental paradigms. In particular, we hope to build on the scriptability of our coupling strategy to enable systematic sensitivity tests. Our most ambitious objective is to combine our efforts with Bayesian inverse modeling techniques toward objective tuning at the highest level, across model architectures.

Simulation of different types of ENSO impacts on South Asian Monsoon in CCSM4

NASA Astrophysics Data System (ADS)

Islam, Siraj ul; Tang, Youmin

2017-02-01

It has been found in observation that there are different types of influences of El Nino Southern Oscillation (ENSO) on the South Asian Monsoon (SAM). A correct description and representation of these teleconnections is critical for climate models to simulate and predict SAM. In this study, we examine these teleconnections in NCAR CAM4 and CCSM4 models, including the strength and weakness of these models in preserving different types of ENSO-SAM relationships. By using observational and simulation dataset, the composite analysis, based on specific selection criteria, is performed for both SAM rainfall and the eastern equatorial Pacific sea surface temperature (SST) anomalies. Anomalous SAM rainfall is characterized in three different types i.e. the indirect influence of the SST anomalies of preceding winter (DJF-only), direct influence of the SST anomalies of concurrent summer (JJAS-only) and the combined influence of both preceding winter and concurrent summer (DJF&JJAS). The analysis reveals that CAM4 uncoupled simulation can reasonably well reproduce the anomalous SAM rainfall in DJF-only and DJF&JJAS types whereas the model fails to simulate the anomalous rainfall in the JJAS-only type. The better performance of CAM4, particularly in DJF&JJAS type, comes from its realistic simulation of moisture content and thermal contrast. Its failure to preserve the ENSO-SAM relationship of JJAS-only type is due to the absence of ENSO induced warming in Northern Indian Ocean via atmospheric circulation which is indirectly linked to the lack of air-sea coupling. The role of Indian Ocean in controlling the ENSO-SAM teleconnections of the DJF&JJAS type is further investigated using CAM4 sensitivity experiments. It is found that in absence of Indian Ocean SST, the anomalous SAM summer rainfall suppresses in the DJF&JJAS type, suggesting the important modulation by Indian Ocean SST probably through the preceding winter equatorial Pacific SST forcing and the atmospheric circulations. On the other hand, CCSM4 shows large systematical errors in DJF-only and DJF&JJAS types and reproduce weak anomalous SAM rainfall. The failure of CCSM4 in simulating DJF-only and DJF&JJAS types is found mainly due to the errors in its SST simulation. The JJAS-only type is better reproduced in the CCSM4 simulation as compared to CAM4 and observation composites. Strong convergence over the SAM region which intensifies the anomalous SAM is seen to be responsible for its better simulation in this type. It is found that the atmospheric circulations in CCSM4 contribute more than the thermal contrast in modulating the intensity of anomalous rainfall in JJAS-only type. This study suggests that, although air-sea coupling is important for better SAM simulation and its relationship with ENSO, the SST bias in coupled model can significantly degrade ENSO-SAM relationship.

A Prototype Two-Decade Fully-Coupled Fine-Resolution CCSM Simulation

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

McClean, Julie L.; Bader, David C; Bryan, Frank O.

2011-01-01

A fully coupled global simulation using the Community Climate System Model (CCSM) was configured using grid resolutions of 0.1{sup o} for the ocean and sea-ice, and 0.25{sup o} for the atmosphere and land, and was run under present-day greenhouse gas conditions for 20 years. It represents one of the first efforts to simulate the planetary system at such high horizontal resolution. The climatology of the circulation of the atmosphere and the upper ocean were compared with observational data and reanalysis products to identify persistent mean climate biases. Intensified and contracted polar vortices, and too cold sea surface temperatures (SSTs) inmore » the subpolar and mid-latitude Northern Hemisphere were the dominant biases produced by the model. Intense category 4 cyclones formed spontaneously in the tropical North Pacific. A case study of the ocean response to one such event shows the realistic formation of a cold SST wake, mixed layer deepening, and warming below the mixed layer. Too many tropical cyclones formed in the North Pacific however, due to too high SSTs in the tropical eastern Pacific. In the North Atlantic anomalously low SSTs lead to a dearth of hurricanes. Agulhas eddy pathways are more realistic than in equivalent stand-alone ocean simulations forced with atmospheric reanalysis.« less

Congruence between distribution modelling and phylogeographical analyses reveals Quaternary survival of a toadflax species (Linaria elegans) in oceanic climate areas of a mountain ring range.

PubMed

Fernández-Mazuecos, Mario; Vargas, Pablo

2013-06-01

· The role of Quaternary climatic shifts in shaping the distribution of Linaria elegans, an Iberian annual plant, was investigated using species distribution modelling and molecular phylogeographical analyses. Three hypotheses are proposed to explain the Quaternary history of its mountain ring range. · The distribution of L. elegans was modelled using the maximum entropy method and projected to the last interglacial and to the last glacial maximum (LGM) using two different paleoclimatic models: the Community Climate System Model (CCSM) and the Model for Interdisciplinary Research on Climate (MIROC). Two nuclear and three plastid DNA regions were sequenced for 24 populations (119 individuals sampled). Bayesian phylogenetic, phylogeographical, dating and coalescent-based population genetic analyses were conducted. · Molecular analyses indicated the existence of northern and southern glacial refugia and supported two routes of post-glacial recolonization. These results were consistent with the LGM distribution as inferred under the CCSM paleoclimatic model (but not under the MIROC model). Isolation between two major refugia was dated back to the Riss or Mindel glaciations, > 100 kyr before present (bp). · The Atlantic distribution of inferred refugia suggests that the oceanic (buffered)-continental (harsh) gradient may have played a key and previously unrecognized role in determining Quaternary distribution shifts of Mediterranean plants. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Studying the impact of climate change on flooding in 12 river basins using CCSM4 output

NASA Astrophysics Data System (ADS)

Thiele-Eich, I.; Hopson, T. M.; Gilleland, E.; Lamarque, J.; Hu, A.

2011-12-01

The goal of this study is to analyze the impact of climate change on flood frequency changes in twelve large river basins by assessing the changes in upper catchment precipitation as well as the impact of sea-level rise at the river mouths. Using the recently released model output of the CCSM4 for upper catchment precipitation in twelve large river basins as well as the sea-level rise anomalies at the respective river mouths, we assess the impact of climate change on the return periods of flooding in the individual basins. Upper catchment precipitation, discharge as well as annual mean thermosteric sea-level rise are taken from the four CCSM4 1° 20th Century ensemble members as well as from six CCSM4 1° ensemble members for the RCP scenarios RCP8.5, 6.0, 4.5 and 2.6. In a next step, return levels are compared from both 20th century and future model simulations for time slices at 2030, 2050, 2070 and 2090. It can be seen that what is e.g. a 20 year flood in present-day climate has a return period of ~15/10 years (RCP 2.6/8.5) in 2070. This effect strengthens as time progresses in the 21st century. Especially in low-lying countries such as Bangladesh, changes in sea-level rise can be expected to influence present-day flood characteristics. Sea-level rise anomalies for the 21st century are taken from CCSM4 model output at each of the river mouths. The backwater effect of sea-level rise can be estimated by referring to the geometry of the river channel and calculating an effective additional discharge both at the river mouth and inland. Judging from our work, the increase in effective discharge due to sea-level rise cannot be neglected when discussing flooding in the respective river basins. Impact of sea-level rise on changes in return levels will be investigated further. To blend both precipitation and sea-level effects together, we use extreme-value theory to calculate how the tails of the current river discharge distribution in both the lower and middle reaches of the river basins will be impacted by changing climate.

Bladder outlet obstruction triggers neural plasticity in sensory pathways and contributes to impaired sensitivity in erectile dysfunction.

PubMed

Malykhina, Anna P; Lei, Qi; Chang, Shaohua; Pan, Xiao-Qing; Villamor, Antonio N; Smith, Ariana L; Seftel, Allen D

2013-05-15

Lower urinary tract symptoms (LUTS) and erectile dysfunction (ED) are common problems in aging males worldwide. The objective of this work was to evaluate the effects of bladder neck nerve damage induced by partial bladder outlet obstruction (PBOO) on sensory innervation of the corpus cavernosum (CC) and CC smooth muscle (CCSM) using a rat model of PBOO induced by a partial ligation of the bladder neck. Retrograde labeling technique was used to label dorsal root ganglion (DRG) neurons that innervate the urinary bladder and CC. Contractility and relaxation of the CCSM was studied in vitro, and expression of nitric oxide synthase (NOS) was evaluated by Western blotting. Concentration of the sensory neuropeptides substance P (SP) and calcitonin gene-related peptide was measured by ELISA. Partial obstruction of the bladder neck caused a significant hypertrophy of the urinary bladders (2.5-fold increase at 2 wk). Analysis of L6-S2 DRG sections determined that sensory ganglia received input from both the urinary bladder and CC with 5-7% of all neurons double labeled from both organs. The contractile responses of CC muscle strips to KCl and phenylephrine were decreased after PBOO, followed by a reduced relaxation response to nitroprusside. A significant decrease in neuronal NOS expression, but not in endothelial NOS or protein kinase G (PKG-1), was detected in the CCSM of the obstructed animals. Additionally, PBOO caused some impairment to sensory nerves as evidenced by a fivefold downregulation of SP in the CC (P ≤ 0.001). Our results provide evidence that PBOO leads to the impairment of bladder neck afferent innervation followed by a decrease in CCSM relaxation, downregulation of nNOS expression, and reduced content of sensory neuropeptides in the CC smooth muscle. These results suggest that nerve damage in PBOO may contribute to LUTS-ED comorbidity and trigger secondary changes in the contraction/relaxation mechanisms of CCSM.

Downscaling of sea level and fluxes in the Malacca and Singapore Straits using A2 scenario projections of AR4 GCMs

NASA Astrophysics Data System (ADS)

Tkalich, Pavel; Koshebutsky, Volodymyr; Maderich, Vladimir; Thompson, Bijoy

2013-04-01

IPCC-coordinated work has been completed within Fourth Assessment Report (AR4) to project climate and ocean variables for the 21st century using coupled atmospheric-ocean General Circulation Models (GCMs). Resolution of the GCMs is not sufficient to resolve local features of narrow Malacca and Singapore Straits, having complex coastal line and bathymetry; therefore, dynamical downscaling of ocean variables from the global grid to the regional scale is advisable using ocean models, such as Regional Ocean Modeling System (ROMS). ROMS is customized for the domain centered on the Singapore and Malacca Straits, extending from 98°E to 109°E and 6°S to 14°N. Following IPCC methodology, the modelling is done for the past reference period 1961-1990, and then for the 21st century projections; subsequently, established past and projected trends and variability of ocean parameters are inter-compared. Boundary conditions for the past reference period are extracted from Simple Ocean Data Assimilation (SODA), while the projections are made using A2 scenario runs of ECHAM5 and CCSM3 GCMs. Atmospheric forcing for ROMS is downscaled with WRF using ERA-40 dataset for the past period, and outputs of atmospheric variables of respective GCMs for the projections. ROMS-downscaled regional sea level change during 1961-1990, corrected for the global thermosteric effect, land-ice melting and Global Isostatic Adjustment (GIA) effect, corresponds to a mean total trend of 1.52 mm/year, which is higher than the global estimate 1.25 mm/year and observed global sea-level rise (1.44 mm/year) for the same period. Local linear trend in the Singapore Strait (0.9 mm/year) corresponds to the observed trend at Victoria Dock tide gauge (1.1 mm/year) for the past period. Mean discharges through the Karimata, Malacca and Singapore Straits are 0.9, 0.21 and 0.12 Sv, respectively, fall in the range of observations and recent model estimates. A2 scenario projections using ROMS-ECHAM5 and ROMS-CCSM3 for 2011-2099 suggest that linear trends of sea level rise in Singapore Strait are 5.4 and 6.1 mm/year, respectively. These values fall in the range of global estimates of 3.0-8.5 mm/year. Mean sea level rise is expected around 0.43 m (ROMS-ECHAM5) and 0.47 m (ROMS-CCSM3) in 2099 relative to mean sea level in 2011. These values are greater than median estimation of global sea rise 0.32 under scenario A2. Mean discharge through Singapore Strait for scenario A2 during 2011 to 2099 is projected to be 0.062 Sv for ROMS-ECHAM5 and 0.11 Sv for ROMS-CCSM3. These projections are comparable to the discharges during 1961-1990 (0.065 and 0.11 Sv, respectively). The linear trend in discharges for the period 2011-2099 is relatively small with statistical confidence level being less than 95%. An important feature computationally discovered is the transient reversal of flow in the Singapore Strait during southwest monsoon. In general, the reversals of flow in ROMS-ECHAM5 and ROMS-CCSM3 are observed respectively to occur 1/3 and 1/5 of the whole period.

Reconciling divergent trends and millennial variations in Holocene temperatures.

PubMed

Marsicek, Jeremiah; Shuman, Bryan N; Bartlein, Patrick J; Shafer, Sarah L; Brewer, Simon

2018-01-31

Cooling during most of the past two millennia has been widely recognized and has been inferred to be the dominant global temperature trend of the past 11,700 years (the Holocene epoch). However, long-term cooling has been difficult to reconcile with global forcing, and climate models consistently simulate long-term warming. The divergence between simulations and reconstructions emerges primarily for northern mid-latitudes, for which pronounced cooling has been inferred from marine and coastal records using multiple approaches. Here we show that temperatures reconstructed from sub-fossil pollen from 642 sites across North America and Europe closely match simulations, and that long-term warming, not cooling, defined the Holocene until around 2,000 years ago. The reconstructions indicate that evidence of long-term cooling was limited to North Atlantic records. Early Holocene temperatures on the continents were more than two degrees Celsius below those of the past two millennia, consistent with the simulated effects of remnant ice sheets in the climate model Community Climate System Model 3 (CCSM3). CCSM3 simulates increases in 'growing degree days'-a measure of the accumulated warmth above five degrees Celsius per year-of more than 300 kelvin days over the Holocene, consistent with inferences from the pollen data. It also simulates a decrease in mean summer temperatures of more than two degrees Celsius, which correlates with reconstructed marine trends and highlights the potential importance of the different subseasonal sensitivities of the records. Despite the differing trends, pollen- and marine-based reconstructions are correlated at millennial-to-centennial scales, probably in response to ice-sheet and meltwater dynamics, and to stochastic dynamics similar to the temperature variations produced by CCSM3. Although our results depend on a single source of palaeoclimatic data (pollen) and a single climate-model simulation, they reinforce the notion that climate models can adequately simulate climates for periods other than the present-day. They also demonstrate that amplified warming in recent decades increased temperatures above the mean of any century during the past 11,000 years.

Reconciling divergent trends and millennial variations in Holocene temperatures

NASA Astrophysics Data System (ADS)

Marsicek, Jeremiah; Shuman, Bryan N.; Bartlein, Patrick J.; Shafer, Sarah L.; Brewer, Simon

2018-02-01

Cooling during most of the past two millennia has been widely recognized and has been inferred to be the dominant global temperature trend of the past 11,700 years (the Holocene epoch). However, long-term cooling has been difficult to reconcile with global forcing, and climate models consistently simulate long-term warming. The divergence between simulations and reconstructions emerges primarily for northern mid-latitudes, for which pronounced cooling has been inferred from marine and coastal records using multiple approaches. Here we show that temperatures reconstructed from sub-fossil pollen from 642 sites across North America and Europe closely match simulations, and that long-term warming, not cooling, defined the Holocene until around 2,000 years ago. The reconstructions indicate that evidence of long-term cooling was limited to North Atlantic records. Early Holocene temperatures on the continents were more than two degrees Celsius below those of the past two millennia, consistent with the simulated effects of remnant ice sheets in the climate model Community Climate System Model 3 (CCSM3). CCSM3 simulates increases in ‘growing degree days’—a measure of the accumulated warmth above five degrees Celsius per year—of more than 300 kelvin days over the Holocene, consistent with inferences from the pollen data. It also simulates a decrease in mean summer temperatures of more than two degrees Celsius, which correlates with reconstructed marine trends and highlights the potential importance of the different subseasonal sensitivities of the records. Despite the differing trends, pollen- and marine-based reconstructions are correlated at millennial-to-centennial scales, probably in response to ice-sheet and meltwater dynamics, and to stochastic dynamics similar to the temperature variations produced by CCSM3. Although our results depend on a single source of palaeoclimatic data (pollen) and a single climate-model simulation, they reinforce the notion that climate models can adequately simulate climates for periods other than the present-day. They also demonstrate that amplified warming in recent decades increased temperatures above the mean of any century during the past 11,000 years.

Climate Sensitivity to Realistic Solar Heating of Snow and Ice

NASA Astrophysics Data System (ADS)

Flanner, M.; Zender, C. S.

2004-12-01

Snow and ice-covered surfaces are highly reflective and play an integral role in the planetary radiation budget. However, GCMs typically prescribe snow reflection and absorption based on minimal knowledge of snow physical characteristics. We performed climate sensitivity simulations with the NCAR CCSM including a new physically-based multi-layer snow radiative transfer model. The model predicts the effects of vertically resolved heating, absorbing aerosol, and snowpack transparency on snowpack evolution and climate. These processes significantly reduce the model's near-infrared albedo bias over deep snowpacks. While the current CCSM implementation prescribes all solar radiative absorption to occur in the top 2 cm of snow, we estimate that about 65% occurs beneath this level. Accounting for the vertical distribution of snowpack heating and more realistic reflectance significantly alters snowpack depth, surface albedo, and surface air temperature over Northern Hemisphere regions. Implications for the strength of the ice-albedo feedback will be discussed.

The Earth System Grid Center for Enabling Technologies (ESG-CET): Scaling the Earth System Grid to Petascale Data

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

Williams, Dean N.

2007-09-27

This report, which summarizes work carried out by the ESG-CET during the period April 1, 2007 through September 30, 2007, includes discussion of overall progress, period goals, highlights, collaborations and presentations. To learn more about our project, please visit the Earth System Grid website. In addition, this report will be forwarded to the DOE SciDAC project management, the Office of Biological and Environmental Research (OBER) project management, national and international stakeholders (e.g., the Community Climate System Model (CCSM), the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5), the Climate Science Computational End Station (CCES), etc.), and collaborators. Themore » ESG-CET executive committee consists of David Bernholdt, ORNL; Ian Foster, ANL; Don Middleton, NCAR; and Dean Williams, LLNL. The ESG-CET team is a collective of researchers and scientists with diverse domain knowledge, whose home institutions include seven laboratories (ANL, LANL, LBNL, LLNL, NCAR, ORNL, PMEL) and one university (ISI/USC); all work in close collaboration with the project's stakeholders and domain researchers and scientists. During this semi-annual reporting period, the ESG-CET increased its efforts on completing requirement documents, framework design, and component prototyping. As we strove to complete and expand the overall ESG-CET architectural plans and use-case scenarios to fit our constituency's scope of use, we continued to provide production-level services to the community. These services continued for IPCC AR4, CCES, and CCSM, and were extended to include Cloud Feedback Model Intercomparison Project (CFMIP) data.« less

Reduced connection between the East Asian Summer Monsoon and Southern Hemisphere Circulation on interannual timescales under intense global warming

NASA Astrophysics Data System (ADS)

Yu, Tianlei; Guo, Pinwen; Cheng, Jun; Hu, Aixue; Lin, Pengfei; Yu, Yongqiang

2018-03-01

Previous studies show a close relationship between the East Asian Summer Monsoon (EASM) and Southern Hemisphere (SH) circulation on interannual timescales. In this study, we investigate whether this close relationship will change under intensive greenhouse-gas effect by analyzing simulations under two different climate background states: preindustrial era and Representative Concentration Pathway (RCP) 8.5 stabilization from the Community Climate System Model Version 4 (CCSM4). Results show a significantly reduced relationship under stabilized RCP8.5 climate state, such a less correlated EASM with the sea level pressure in the southern Indian Ocean and the SH branch of local Hadley Cell. Further analysis suggests that the collapse of the Atlantic Meridional Overturning Circulation (AMOC) due to this warming leads to a less vigorous northward meridional heat transport, a decreased intertropical temperature contrast in boreal summer, which produces a weaker cross-equatorial Hadley Cell in the monsoonal region and a reduced Interhemispheric Mass Exchange (IME). Since the monsoonal IME acts as a bridge connecting EASM and SH circulation, the reduced IME weakens this connection. By performing freshwater hosing experiment using the Flexible Global Ocean—Atmosphere—Land System model, Grid-point Version 2 (FGOALS-g2), we show a weakened relationship between the EASM and SH circulation as in CCSM4 when AMOC collapses. Our results suggest that a substantially weakened AMOC is the main driver leading to the EASM, which is less affected by SH circulation in the future warmer climate.

The role of climate and vegetation on woolly mammoth extinction on St. Paul Island, Alaska and megafauna extinction in North America in the late Quaternary

NASA Astrophysics Data System (ADS)

Wang, Y.; Porter, W.; Miller, P. A.; Graham, R. W.; Williams, J. W.

2016-12-01

Estimate of megafauna behaviors dynamically under associated environmental factors is important to understand the mechanisms and causes of the late Quaternary megafaunal extinctions. On St. Paul Island, an isolated remnant of the Bering Land Bridge, a late-surviving population of woolly mammoth (Mammuthus primigenius) persisted until 5,600 cal BP, while 37 out of 54 megafauna species in the continent of North America, all herbivores, went extinct at the end of Pleistocene between 13,800 and 11,500 cal BP. Proposed natural drivers of the extinction events include abrupt temperature changes, food resource loss and freshwater shortage. Here we tested these three hypothesized mechanisms, using a physiological model (Niche Mapper) to estimate individual megafauna behaviors from the perspectives of metabolic rate, individual vegetation and freshwater requirement under simulated climates from Community Climate System Model version 3 (CCSM3), vegetation reconstructions based on dynamic LPJ-GUESS model and woolly mammoth and megafauna species trait data reconstructed based on mammal fossils. Preliminary simulations of woolly mammoth on St. Paul Island point to the importance of net vegetation primary productivity and freshwater availability as limits on the carrying capacity of St. Paul for mammoth populations, with a low carrying capacity in the middle Holocene making this population highly vulnerable to extinction. Results also indicate that the abrupt warming based around 14,000 cal BP in Bering land bridge on CCSM3 simulations causes woolly mammoth extinction, by driving metabolic rate high up beyond the active basic metabolic rate. Analysis suggests a positive relationship between temperature and metabolic rate, and woolly mammoth would go extinct when summer temperature is up to 12 °C or higher. However the temperature reconstructed based on regional proxies is relatively stable compared to CCSM3 simulations, and leads to stable metabolic rate of woolly mammoth and no extinction events. Proposed simulations of megafauna species in North America indicate the role of ice sheets in limiting habitats. This work helps resolve the drivers of extinction for a small island surviving woolly mammoth population and worldwide megafauna extinctions in the late Quaternary.

[Probability, Cambridge Conference on School Mathematics Feasibility Study No. 7.

ERIC Educational Resources Information Center

Davis, R.

These materials were written with the aim of reflecting the thinking of the Cambridge Conference on School Mathematics (CCSM) regarding the goals and objectives for school mathematics. They represent a practical response to a proposal by CCSM that some elements of probability be introduced in the elementary grades. These materials provide children…

How Well Has Global Ocean Heat Content Variability Been Measured?

NASA Astrophysics Data System (ADS)

Nelson, A.; Weiss, J.; Fox-Kemper, B.; Fabienne, G.

2016-12-01

We introduce a new strategy that uses synthetic observations of an ensemble of model simulations to test the fidelity of an observational strategy, quantifying how well it captures the statistics of variability. We apply this test to the 0-700m global ocean heat content anomaly (OHCA) as observed with in-situ measurements by the Coriolis Dataset for Reanalysis (CORA), using the Community Climate System Model (CCSM) version 3.5. One-year running mean OHCAs for the years 2005 onward are found to faithfully capture the variability. During these years, synthetic observations of the model are strongly correlated at 0.94±0.06 with the actual state of the model. Overall, sub-annual variability and data before 2005 are significantly affected by the variability of the observing system. In contrast, the sometimes-used weighted integral of observations is not a good indicator of OHCA as variability in the observing system contaminates dynamical variability.

North Pacific Mesoscale Coupled Air-Ocean Simulations Compared with Observations

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

Cerovecki, Ivana; McClean, Julie; Koracin, Darko

2014-11-14

The overall objective of this study was to improve the representation of regional ocean circulation in the North Pacific by using high resolution atmospheric forcing that accurately represents mesoscale processes in ocean-atmosphere regional (North Pacific) model configuration. The goal was to assess the importance of accurate representation of mesoscale processes in the atmosphere and the ocean on large scale circulation. This is an important question, as mesoscale processes in the atmosphere which are resolved by the high resolution mesoscale atmospheric models such as Weather Research and Forecasting (WRF), are absent in commonly used atmospheric forcing such as CORE forcing, employedmore » in e.g. the Community Climate System Model (CCSM).« less

Towards the Prediction of Decadal to Centennial Climate Processes in the Coupled Earth System Model

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

Liu, Zhengyu; Kutzbach, J.; Jacob, R.

2011-12-05

In this proposal, we have made major advances in the understanding of decadal and long term climate variability. (a) We performed a systematic study of multidecadal climate variability in FOAM-LPJ and CCSM-T31, and are starting exploring decadal variability in the IPCC AR4 models. (b) We develop several novel methods for the assessment of climate feedbacks in the observation. (c) We also developed a new initialization scheme DAI (Dynamical Analogue Initialization) for ensemble decadal prediction. (d) We also studied climate-vegetation feedback in the observation and models. (e) Finally, we started a pilot program using Ensemble Kalman Filter in CGCM for decadalmore » climate prediction.« less

Evaluation of CMIP5 models in the context of food security assessments in Sahel and Eastern Africa

NASA Astrophysics Data System (ADS)

Shukla, S.; Funk, C. C.; Dettinger, M. D.; Robertson, F. R.

2012-12-01

Global climate change will adversely impact agricultural production in many African countries, mainly in the Sahel region and Eastern Africa that are already considered food insecure regions. The impacts of climate change will be particularly severe in these food insecure countries due to their high dependence on domestic agriculture production, rapid population growth, and lack of technological advances. Early planning and the targeted use of resources will therefore be critical to informing and motivating climate change adaptation actions that can save lives and mitigate economic losses. We seek to use Climate Model Intercomparison Project Phase-5 (CMIP5) global climate model projections to assess and attribute food and water security conditions in the above mentioned regions over next two decades or so. As a first order of business, however, we need to understand how the different models represent the tropical ocean response to anthropogenic warming. We pursue this question through an evaluation of the performance of eight different coupled ocean-atmosphere models under the conditions of the 'historical' experiment. The historical experiment forces the simulations with observed 1850-2005 greenhouse gas, aerosol and land cover. While all the models show substantial warming of the tropical oceans, the pattern and atmospheric response to that warming varies substantially. This analysis suggests that the Community Climate System Model (CCSM4) provides the most realistic 1850-2005 changes over the Indo-Pacific. We then present initial downscaling results, based on large scale forcing from the CCSM4, combined with statistical downscaling based on a combination of monthly simulations from Community Atmopsheric Model 4 (CAM4) and observed gridded time series of African rainfall and air temperatures.

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

Tribbia, Joseph

NCAR brought the latest version of the Community Earth System Model (version 1, CESM1) into the mix of models in the NMME effort. This new version uses our newest atmospheric model CAM5 and produces a coupled climate and ENSO that are generally as good or better than those of the Community Climate System Model version 4 (CCSM4). Compared to CCSM4, the new coupled model has a superior climate response with respect to low clouds in both the subtropical stratus regimes and the Arctic. However, CESM1 has been run to date using a prognostic aerosol model that more than doubles itsmore » computational cost. We are currently evaluating a version of the new model using prescribed aerosols and expect it will be ready for integrations in summer 2012. Because of this NCAR has not been able to complete the hindcast integrations using the NCAR loosely-coupled ensemble Kalman filter assimilation method nor has it contributed to the current (Stage I) NMME operational utilization. The expectation is that this model will be included in the NMME in late 2012 or early 2013. The initialization method will utilize the Ensemble Kalman Filter Assimilation methods developed at NCAR using the Data Assimilation Research Testbed (DART) in conjunction with Jeff Anderson’s team in CISL. This methodology has been used in our decadal prediction contributions to CMIP5. During the course of this project, NCAR has setup and performed all the needed hindcast and forecast simulations and provide the requested fields to our collaborators. In addition, NCAR researchers have participated fully in research themes (i) and (ii). Specifically, i) we have begun to evaluate and optimize our system in hindcast mode, focusing on the optimal number of ensemble members, methodologies to recalibrate individual dynamical models, and accessing our forecasts across multiple time scales, i.e., beyond two weeks, and ii) we have begun investigation of the role of different ocean initial conditions in seasonal forecasts. The completion of the calibration hindcasts for Seasonal to Interannual (SI) predictions and the maintenance of the data archive associated with the NCAR portion of this effort has been the responsibility of the Project Scientist I (Alicia Karspeck) that was partially supported on this project.« less

An Exploratory Assessment of the Validity of the Community College Survey of Men (CCSM): Implications for Serving Veteran Men

ERIC Educational Resources Information Center

De La Garza, Thomas; Wood, J. Luke; Harris, Frank, III

2015-01-01

The Community College Survey of Men (CCSM) assesses predictors of student success for historically underrepresented and underserved men in community colleges. The instrument is designed to inform programming and service-delivery for male students (Wood & Harris, 2013). While the instrument was designed for community college men in general,…

Extreme Water Levels in Bangladesh: Past Trends, Future Projections and their Impact on Mortality

NASA Astrophysics Data System (ADS)

Thiele-Eich, I.; Burkart, K.; Hopson, T. M.; Simmer, C.

2014-12-01

Climate change is expected to have an impact on meteorological and therefore hydrological extremes, thereby possibly altering the vulnerability of exposed populations. Our study focuses on Bangladesh, which is particularly vulnerable to changes in extremes due to both the large population at risk, as well as geographical characteristics such as the low-rising slope of the country through which the outflow of the combined catchments of the Ganges, Brahmaputra and Meghna rivers (GBM, ~1.75 million km2) is channeled.Time series of daily discharge and water level data for the past 100 years were analyzed with respect to trends in frequency, magnitude and duration, focusing on rare but particularly high-risk events using extreme-value theory. Mortality data is available for a five-year period (2003-2007), with a distributed lag non-linear model used to examine possible connections between extreme water levels and mortality. Then, using output from the Community Climate System Model CCSM4, projections were made regarding future flooding due to changes in precipitation intensity and frequency, while also accounting for the backwater effect of sea-level rise. For this, the upper catchment precipitation as well as monthly mean thermosteric sea-level rise at the river mouth outflow were taken from the four CCSM4 1° 20th Century ensemble members as well as from six CCSM4 1° ensemble members for the RCP scenarios RCP 2.6, 4.5, 6.0 and 8.5.Results show that while e.g. the mean water level did not significantly rise during the past 100 years, a change in extreme water levels can be detected. In addition, annual minimum water levels have decreased, which is of particular importance as there is a significant connection to an increase in mortality for low water levels. While mortality does not seem to increase significantly due to extreme floods, our results indicate that return levels projected for the future shift progressively, with the effect being strongest for RCP 8.5. Further measures to strengthen the resilience of the exposed population are therefore required to ensure that climate change effects do not overwhelm the population's coping capacities.

CLARREO shortwave observing system simulation experiments of the twenty-first century: Simulator design and implementation

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

Feldman, D.R.; Algieri, C.A.; Ong, J.R.

2011-04-01

Projected changes in the Earth system will likely be manifested in changes in reflected solar radiation. This paper introduces an operational Observational System Simulation Experiment (OSSE) to calculate the signals of future climate forcings and feedbacks in top-of-atmosphere reflectance spectra. The OSSE combines simulations from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report for the NCAR Community Climate System Model (CCSM) with the MODTRAN radiative transfer code to calculate reflectance spectra for simulations of current and future climatic conditions over the 21st century. The OSSE produces narrowband reflectances and broadband fluxes, the latter of which have been extensivelymore » validated against archived CCSM results. The shortwave reflectance spectra contain atmospheric features including signals from water vapor, liquid and ice clouds, and aerosols. The spectra are also strongly influenced by the surface bidirectional reflectance properties of predicted snow and sea ice and the climatological seasonal cycles of vegetation. By comparing and contrasting simulated reflectance spectra based on emissions scenarios with increasing projected and fixed present-day greenhouse gas and aerosol concentrations, we find that prescribed forcings from increases in anthropogenic sulfate and carbonaceous aerosols are detectable and are spatially confined to lower latitudes. Also, changes in the intertropical convergence zone and poleward shifts in the subsidence zones and the storm tracks are all detectable along with large changes in snow cover and sea ice fraction. These findings suggest that the proposed NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission to measure shortwave reflectance spectra may help elucidate climate forcings, responses, and feedbacks.« less

Reemergence of sea ice cover anomalies and the role of the sea ice-albedo feedback in CCSM simulations

NASA Astrophysics Data System (ADS)

Deweaver, E. T.

2008-12-01

The dramatic sea ice decline of 2007 and lack of recovery in 2008 raise the question of a "tipping point" for Arctic sea ice, beyond which the transition to a seasonal sea ice state becomes abrupt and irreversible. The tipping point is essentially a "memory catastrophe", in which a dramatic loss of sea ice in one summer is "remembered" in reduced ice thickness over the winter season and leads to a comparably dramatic loss the following summer. The dominant contributor to this memory is presumably the sea ice - albedo feedback (SIAF), in which excess insolation absorbed due to low summer ice cover leads to a shorter ice growth season and hence thinner ice. While these dynamics are clearly important, they are difficult to quantify given the lack of long-term observations in the Arctic and the suddenness of the recent loss. Alternatively, we attempt to quantify the contribution of the SIAF to the year-to-year memory of sea ice cover anomalies in simulations of the NCAR Community Climate System Model (CCSM) under 20th century conditions. Lagged autocorrelation plots of sea ice area anomalies show that anomalies in one year tend to "reemerge" in the following year. Further experiments using a slab ocean model (SOM) are used to assess the contribution of oceanic processes to the year-to-year reemergence. This contribution is substantial, particularly in the winter season, and includes memory due to the standard mixed layer reemergence mechanism and low-frequency ocean heat transport anomalies. The contribution of the SIAF to persistence in the SOM experiment is determined through additional experiments in which the SIAF is disabled by fixing surface albedo to its climatological value regardless of sea ice concentration anomalies. SIAF causes a 50% increase in the magnitude of the anomalies but a relatively small increase in their persistence. Persistence is not dramatically increased because the enhancement of shortwave flux anomalies by SIAF is compensated by stronger turbulent heat flux losses in the cold season. The role of turbulent heat fluxes is somewhat inconsistent with the retrospective 20th century simulations from PIOMAS, in which increased insolation is balanced by longwave heat loss. By fitting the area anomaly time series for the SIAF and no-SIAF integrations to an AR1 process, the change in net feedback due to SIAF is calculated. The change in net feedback implies that SIAF increases the climate sensitivity of September sea ice to external forcing (greenhouse gas increases) by about 20%. The modest increase in sea ice sensitivity is confirmed by further climate change experiments with and without SIAF with the CCSM/SOM model. The small role for SIAF is somewhat surprising given the prevalence of "abrupt loss" events in CCSM climate change simulations. However, it is consistent with claims that the dominant factor in abrupt loss events is the sea ice thickness at the event onset.

Weighting of NMME temperature and precipitation forecasts across Europe

NASA Astrophysics Data System (ADS)

Slater, Louise J.; Villarini, Gabriele; Bradley, A. Allen

2017-09-01

Multi-model ensemble forecasts are obtained by weighting multiple General Circulation Model (GCM) outputs to heighten forecast skill and reduce uncertainties. The North American Multi-Model Ensemble (NMME) project facilitates the development of such multi-model forecasting schemes by providing publicly-available hindcasts and forecasts online. Here, temperature and precipitation forecasts are enhanced by leveraging the strengths of eight NMME GCMs (CCSM3, CCSM4, CanCM3, CanCM4, CFSv2, GEOS5, GFDL2.1, and FLORb01) across all forecast months and lead times, for four broad climatic European regions: Temperate, Mediterranean, Humid-Continental and Subarctic-Polar. We compare five different approaches to multi-model weighting based on the equally weighted eight single-model ensembles (EW-8), Bayesian updating (BU) of the eight single-model ensembles (BU-8), BU of the 94 model members (BU-94), BU of the principal components of the eight single-model ensembles (BU-PCA-8) and BU of the principal components of the 94 model members (BU-PCA-94). We assess the forecasting skill of these five multi-models and evaluate their ability to predict some of the costliest historical droughts and floods in recent decades. Results indicate that the simplest approach based on EW-8 preserves model skill, but has considerable biases. The BU and BU-PCA approaches reduce the unconditional biases and negative skill in the forecasts considerably, but they can also sometimes diminish the positive skill in the original forecasts. The BU-PCA models tend to produce lower conditional biases than the BU models and have more homogeneous skill than the other multi-models, but with some loss of skill. The use of 94 NMME model members does not present significant benefits over the use of the 8 single model ensembles. These findings may provide valuable insights for the development of skillful, operational multi-model forecasting systems.

The Community College Survey of Men: An Initial Validation of the Instrument's Non-Cognitive Outcomes Construct

ERIC Educational Resources Information Center

Wood, J. \\Luke; Harris, Frank, III.

2013-01-01

The purpose of this manuscript is to discuss the utility of the Community College Survey of Men (CCSM[c]), an instrument designed to examine predictors of student success for men in community colleges. The authors highlight initial validation results from a recent pilot of the CCSM[c], with a focus on the non-cognitive outcomes construct employed…

Snow Climatology of Arctic Sea Ice: Comparison of Reanalysis and Climate Model Data with In Situ Measurements

NASA Astrophysics Data System (ADS)

Chevooruvalappil Chandran, B.; Pittana, M.; Haas, C.

2015-12-01

Snow on sea ice is a critical and complex factor influencing sea ice processes. Deep snow with a high albedo and low thermal conductivity inhibits ice growth in winter and minimizes ice loss in summer. Very shallow or absent snow promotes ice growth in winter and ice loss in summer. The timing of snow ablation critically impacts summer sea ice mass balance. Here we assess the accuracy of various snow on sea ice data products from reanalysis and modeling comparing them with in situ measurements. The latter are based on the Warren et al. (1999) monthly climatology derived from snow ruler measurements between 1954-1991, and on daily snow depth retrievals from few drifting ice mass balance buoys (IMB) with sufficiently long observations spanning the summer season. These were compared with snow depth data from the National Center for Environmental Prediction Department of Energy Reanalysis 2 (NCEP), the Community Climate System Model 4 (CCSM4), and the Canadian Earth System Model 2 (CanESM2). Results are quite variable in different years and regions. However, there is often good agreement between CanESM2 and IMB snow depth during the winter accumulation and spring melt periods. Regional analyses show that over the western Arctic covered primarily with multiyear ice NCEP snow depths are in good agreement with the Warren climatology while CCSM4 overestimates snow depth. However, in the Eastern Arctic which is dominated by first-year ice the opposite behavior is observed. Compared to the Warren climatology CanESM2 underestimates snow depth in all regions. Differences between different snow depth products are as large as 10 to 20 cm, with large consequences for the sea ice mass balance. However, it is also very difficult to evaluate the accuracy of reanalysis and model snow depths due to a lack of extensive, continuous in situ measurements.

Surface temperature dataset for North America obtained by application of optimal interpolation algorithm merging tree-ring chronologies and climate model output

NASA Astrophysics Data System (ADS)

Chen, Xin; Xing, Pei; Luo, Yong; Nie, Suping; Zhao, Zongci; Huang, Jianbin; Wang, Shaowu; Tian, Qinhua

2017-02-01

A new dataset of surface temperature over North America has been constructed by merging climate model results and empirical tree-ring data through the application of an optimal interpolation algorithm. Errors of both the Community Climate System Model version 4 (CCSM4) simulation and the tree-ring reconstruction were considered to optimize the combination of the two elements. Variance matching was used to reconstruct the surface temperature series. The model simulation provided the background field, and the error covariance matrix was estimated statistically using samples from the simulation results with a running 31-year window for each grid. Thus, the merging process could continue with a time-varying gain matrix. This merging method (MM) was tested using two types of experiment, and the results indicated that the standard deviation of errors was about 0.4 °C lower than the tree-ring reconstructions and about 0.5 °C lower than the model simulation. Because of internal variabilities and uncertainties in the external forcing data, the simulated decadal warm-cool periods were readjusted by the MM such that the decadal variability was more reliable (e.g., the 1940-1960s cooling). During the two centuries (1601-1800 AD) of the preindustrial period, the MM results revealed a compromised spatial pattern of the linear trend of surface temperature, which is in accordance with the phase transition of the Pacific decadal oscillation and Atlantic multidecadal oscillation. Compared with pure CCSM4 simulations, it was demonstrated that the MM brought a significant improvement to the decadal variability of the gridded temperature via the merging of temperature-sensitive tree-ring records.

Developing Models for Predictive Climate Science

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

Drake, John B; Jones, Philip W

2007-01-01

The Community Climate System Model results from a multi-agency collaboration designed to construct cutting-edge climate science simulation models for a broad research community. Predictive climate simulations are currently being prepared for the petascale computers of the near future. Modeling capabilities are continuously being improved in order to provide better answers to critical questions about Earth's climate. Climate change and its implications are front page news in today's world. Could global warming be responsible for the July 2006 heat waves in Europe and the United States? Should more resources be devoted to preparing for an increase in the frequency of strongmore » tropical storms and hurricanes like Katrina? Will coastal cities be flooded due to a rise in sea level? The National Climatic Data Center (NCDC), which archives all weather data for the nation, reports that global surface temperatures have increased over the last century, and that the rate of increase is three times greater since 1976. Will temperatures continue to climb at this rate, will they decline again, or will the rate of increase become even steeper? To address such a flurry of questions, scientists must adopt a systematic approach and develop a predictive framework. With responsibility for advising on energy and technology strategies, the DOE is dedicated to advancing climate research in order to elucidate the causes of climate change, including the role of carbon loading from fossil fuel use. Thus, climate science--which by nature involves advanced computing technology and methods--has been the focus of a number of DOE's SciDAC research projects. Dr. John Drake (ORNL) and Dr. Philip Jones (LANL) served as principal investigators on the SciDAC project, 'Collaborative Design and Development of the Community Climate System Model for Terascale Computers.' The Community Climate System Model (CCSM) is a fully-coupled global system that provides state-of-the-art computer simulations of the Earth's past, present, and future climate states. The collaborative SciDAC team--including over a dozen researchers at institutions around the country--developed, validated, documented, and optimized the performance of CCSM using the latest software engineering approaches, computational technology, and scientific knowledge. Many of the factors that must be accounted for in a comprehensive model of the climate system are illustrated in figure 1.« less

Global vegetation productivity response to climatic oscillations during the satellite era.

PubMed

Gonsamo, Alemu; Chen, Jing M; Lombardozzi, Danica

2016-10-01

Climate control on global vegetation productivity patterns has intensified in response to recent global warming. Yet, the contributions of the leading internal climatic variations to global vegetation productivity are poorly understood. Here, we use 30 years of global satellite observations to study climatic variations controls on continental and global vegetation productivity patterns. El Niño-Southern Oscillation (ENSO) phases (La Niña, neutral, and El Niño years) appear to be a weaker control on global-scale vegetation productivity than previously thought, although continental-scale responses are substantial. There is also clear evidence that other non-ENSO climatic variations have a strong control on spatial patterns of vegetation productivity mainly through their influence on temperature. Among the eight leading internal climatic variations, the East Atlantic/West Russia Pattern extensively controls the ensuing year vegetation productivity of the most productive tropical and temperate forest ecosystems of the Earth's vegetated surface through directionally consistent influence on vegetation greenness. The Community Climate System Model (CCSM4) simulations do not capture the observed patterns of vegetation productivity responses to internal climatic variations. Our analyses show the ubiquitous control of climatic variations on vegetation productivity and can further guide CCSM and other Earth system models developments to represent vegetation response patterns to unforced variability. Several winter time internal climatic variation indices show strong potentials on predicting growing season vegetation productivity two to six seasons ahead which enables national governments and farmers forecast crop yield to ensure supplies of affordable food, famine early warning, and plan management options to minimize yield losses ahead of time. © 2016 John Wiley & Sons Ltd.

How will climate change affect watershed mercury export in a representative Coastal Plain watershed?

NASA Astrophysics Data System (ADS)

Golden, H. E.; Knightes, C. D.; Conrads, P. A.; Feaster, T.; Davis, G. M.; Benedict, S. T.; Bradley, P. M.

2012-12-01

Future climate change is expected to drive variations in watershed hydrological processes and water quality across a wide range of physiographic provinces, ecosystems, and spatial scales. How such shifts in climatic conditions will impact watershed mercury (Hg) dynamics and hydrologically-driven Hg transport is a significant concern. We simulate the responses of watershed hydrological and total Hg (HgT) fluxes and concentrations to a unified set of past and future climate change projections in a Coastal Plain basin using multiple watershed models. We use two statistically downscaled global precipitation and temperature models, ECHO, a hybrid of the ECHAM4 and HOPE-G models, and the Community Climate System Model (CCSM3) across two thirty-year simulations (1980 to 2010 and 2040 to 2070). We apply three watershed models to quantify and bracket potential changes in hydrologic and HgT fluxes, including the Visualizing Ecosystems for Land Management Assessment Model for Hg (VELMA-Hg), the Grid Based Mercury Model (GBMM), and TOPLOAD, a water quality constituent model linked to TOPMODEL hydrological simulations. We estimate a decrease in average annual HgT fluxes in response to climate change using the ECHO projections and an increase with the CCSM3 projections in the study watershed. Average monthly HgT fluxes increase using both climate change projections between in the late spring (March through May), when HgT concentrations and flow are high. Results suggest that hydrological transport associated with changes in precipitation and temperature is the primary mechanism driving HgT flux response to climate change. Our multiple model/multiple projection approach allows us to bracket the relative response of HgT fluxes to climate change, thereby illustrating the uncertainty associated with the projections. In addition, our approach allows us to examine potential variations in climate change-driven water and HgT export based on different conceptualizations of watershed HgT dynamics and the representative mathematical structures underpinning existing watershed Hg models.

Modeled ecohydrological responses to climate change at seven small watersheds in the northeastern United States

Treesearch

Afshin Pourmokhtarian; Charles T. Driscoll; John L. Campbell; Katharine Hayhoe; Anne M. K. Stoner; Mary Beth Adams; Douglas Burns; Ivan Fernandez; Myron J. Mitchell; James B. Shanley

2016-01-01

A cross-site analysis was conducted on seven diverse, forested watersheds in the northeastern United States to evaluate hydrological responses (evapotranspiration, soil moisture, seasonal and annual streamflow, and water stress) to projections of future climate. We used output from four atmosphere–ocean general circulation models (AOGCMs; CCSM4, HadGEM2-CC, MIROC5, and...

Exploring the Mass Balance and Sea Level Contribution of Global Glaciers During the Last Interglaciation and Mid-Holocene

NASA Astrophysics Data System (ADS)

Smith, S.; Ullman, D. J.; He, F.; Carlson, A. E.; Marzeion, B.; Maussion, F.

2017-12-01

Understanding the behavior of the world's glaciers during previous interglaciations is key to interpreting the sensitivity and behavior of the cryosphere under scenarios of future anthropogenic warming. Previous studies of the Last Interglaciation (LIG, 130 ka to 116 ka) indicate elevated global temperatures and higher sea levels than the Holocene, but most assessments of the impact on the cryosphere have focused on the mass balance and volume change of polar ice sheets. In assessing sea-level sources, most studies assume complete deglacation of global glaciers, but this has yet to be tested. In addition, the significant changes in orbital forcing during the LIG and the associated impacts on climate seasonality and variability may have led to unique glacier evolution.Here, we explore the effect of LIG climate on the global glacier budget. We employ the Open Global Glacier Model (OGGM), forced by simulated LIG equilibrium climate anomalies (127 ka) from the Community Climate System Model Version 3 (CCSM3). OGGM is a glacier mass balance and dynamics model, specifically designed to reconstruct global glacier volume change. Our simulations have been conducted in an equilibrium state to determine the effect of the prolonged climate forcing of the LIG. Due to unknown flow characteristics of glaciers during the LIG, we explore the parametric uncertainty in the mass balance and flow sensitivity parameters. As a point of comparison, we also conduct a series of simulations using forcing anomalies from the CCSM3 mid-Holocene (6 ka) experiment. Results from both experiments show that glacier mass balance is highly sensitive to these sensitivity parameters, pointing at the need for glacier margin calibration for OGGM in paleoclimate applications.

Boundary conditions for the Middle Miocene Climate Transition (MMCT v1.0)

NASA Astrophysics Data System (ADS)

Frigola, Amanda; Prange, Matthias; Schulz, Michael

2018-04-01

The Middle Miocene Climate Transition was characterized by major Antarctic ice sheet expansion and global cooling during the interval ˜ 15-13 Ma. Here we present two sets of boundary conditions for global general circulation models characterizing the periods before (Middle Miocene Climatic Optimum; MMCO) and after (Middle Miocene Glaciation; MMG) the transition. These boundary conditions include Middle Miocene global topography, bathymetry, and vegetation. Additionally, Antarctic ice volume and geometry, sea level, and atmospheric CO2 concentration estimates for the MMCO and the MMG are reviewed. The MMCO and MMG boundary conditions have been successfully applied to the Community Climate System Model version 3 (CCSM3) to provide evidence of their suitability for global climate modeling. The boundary-condition files are available for use as input in a wide variety of global climate models and constitute a valuable tool for modeling studies with a focus on the Middle Miocene.

Regional and global climate for the mid-Pliocene using CCSM4 with PlioMIP2 boundary conditions

NASA Astrophysics Data System (ADS)

Chandan, D.; Peltier, W. R.

2016-12-01

The mid-Pliocene ( 3 Mya) hothouse continues to intrigue the climate community regarding the nature of the feedback mechanisms that could have amplified the warming that is expected from a modest concentration of atmospheric carbon-dioxide ( 300-400 ppmv). The Pliocene Model Intercomparison Project (PlioMIP) was created to help understand the mid-Pliocene climate through intercomparison between different climate models. The results from the first phase of this program revealed substantial variations between participating models and the pervasive inability of the models to capture the SST anomalies over equatorial upwelling regions and at high-latitude sites in the North Atlantic. The second phase, PlioMIP2 (Haywood et al., 2016), which has only recently begun, considerably revises the boundary conditions that are to be used with coupled-climate models, especially in high-latitude regions. The set of PlioMIP2 experiments which have been proposed will facilitate the attribution of the total warming to that arising from changes in (i) atmospheric CO2, (ii) orography and (iii) sea-ice extent, using the factor analysis methodology of Lunt et al., 2012. We have performed several very long, high-quality climate simulations from the PlioMIP2 set using the fully-coupled CCSM4/CESM1 model. We present our analysis of the mid-Pliocene climate based upon the results of these simulations and draw special attention to the extent of polar-amplification, the temperature pattern in the equatorial pacific and the existence and character of ENSO. In order to assess the regional and global impact of the new boundary conditions, our results are compared to the CCSM4 climate obtained using boundary conditions from the first phase of PlioMIP (Rosenbloom et al., 2013), to the PRISM3 (Dowsett et al., 2010) estimates for mid-Pliocene SST (relevant for the time-interval of study in PlioMIP), and to our own compilation of SST estimates for the time interval which is the focus in PlioMIP2. Dowsett et al., 2010, Stratigraphy (7) 123-129Haywood et al., 2016, CP (12) 663-675Lunt et al., 2012, EPSL (321-322) 128-138Rosenbloom et al., 2013, GMD (6) 549-561

Bias correction of temperature produced by the Community Climate System Model using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Moghim, S.; Hsu, K.; Bras, R. L.

2013-12-01

General Circulation Models (GCMs) are used to predict circulation and energy transfers between the atmosphere and the land. It is known that these models produce biased results that will have impact on their uses. This work proposes a new method for bias correction: the equidistant cumulative distribution function-artificial neural network (EDCDFANN) procedure. The method uses artificial neural networks (ANNs) as a surrogate model to estimate bias-corrected temperature, given an identification of the system derived from GCM models output variables. A two-layer feed forward neural network is trained with observations during a historical period and then the adjusted network can be used to predict bias-corrected temperature for future periods. To capture the extreme values this method is combined with the equidistant CDF matching method (EDCDF, Li et al. 2010). The proposed method is tested with the Community Climate System Model (CCSM3) outputs using air and skin temperature, specific humidity, shortwave and longwave radiation as inputs to the ANN. This method decreases the mean square error and increases the spatial correlation between the modeled temperature and the observed one. The results indicate the EDCDFANN has potential to remove the biases of the model outputs.

Impact of revised and potential future albedo estimates on CCSM3 simulations of growing-season surface temperature fields for North America

Treesearch

Warren E. Heilman; David Y. Hollinger; Xiuping Li; Xindi Bain; Shiyuan. Zhong

2010-01-01

Recently published albedo research has resulted in improved growing-season albedo estimates for forest and grassland vegetation. The impact of these improved estimates on the ability of climate models to simulate growing-season surface temperature patterns is unknown. We have developed a set of current-climate surface temperature scenarios for North America using the...

Comparison of current and paleorecharge on the Yucatan Peninsula, Mexico

NASA Astrophysics Data System (ADS)

Van Pelt, S.; Allen, D. M.; Kohfeld, K. E.

2016-12-01

During the Terminal Classic Period (TCP) 800-1000 AD, the Yucatan Peninsula is thought to have experienced a 150-year long series of droughts that contributed to the demise of the Mayan civilization. The occurrence of this type of event suggests that similar precipitation extremes could occur again, and severely impact water supplies. Studying the past occurrence of droughts may provide more insight into the possible timing and intensity of droughts. However, observed data of the past climate is limited to proxy records, which are not detailed enough for groundwater modeling. The goals of this study were two-fold: (a) to generate a daily paleoclimate time series for use in a recharge model, and (b) to compare current and past recharge on the Yucatan Peninsula. Past temperature and precipitation were reconstructed using a novel backwards shift factor approach using output from two experiments of the Community Climate System Model Version 4 (CCSM4). Shift factors were applied using two approaches: (1) application of shift factors to a stochastic weather series based on the observed climate, and (2) application of shift factors directly to the observed climate. The second method (direct shift factor approach) was found to be more suitable for the Yucatan Peninsula, as the observed median annual precipitation was poorly reproduced in the stochastic data. The reconstructed precipitation was used in the recharge model, which used the unsaturated component of the modeling program MIKE SHE. The comparison of the TCP and the current climate models indicated that on average, 1.74% more recharge occurred annually during the TCP. The seasonal water balance components showed that the majority of this higher recharge occurred during the wet season, with little to no increase in recharge during the dry season. Due to issues with the CCSM4 model data, changes in climate variability were not able to be incorporated into this study. If variability were incorporated, the TCP climate may have had more extreme precipitation values which are not represented in the recharge model, and the Yucatan Peninsula may have been susceptible to dry season droughts.

Regional sea level variability in a high-resolution global coupled climate model

NASA Astrophysics Data System (ADS)

Palko, D.; Kirtman, B. P.

2016-12-01

The prediction of trends at regional scales is essential in order to adapt to and prepare for the effects of climate change. However, GCMs are unable to make reliable predictions at regional scales. The prediction of local sea level trends is particularly critical. The main goal of this research is to utilize high-resolution (HR) (0.1° resolution in the ocean) coupled model runs of CCSM4 to analyze regional sea surface height (SSH) trends. Unlike typical, lower resolution (1.0°) GCM runs these HR runs resolve features in the ocean, like the Gulf Stream, which may have a large effect on regional sea level. We characterize the variability of regional SSH along the Atlantic coast of the US using tide gauge observations along with fixed radiative forcing runs of CCSM4 and HR interactive ensemble runs. The interactive ensemble couples an ensemble mean atmosphere with a single ocean realization. This coupling results in a 30% decrease in the strength of the Atlantic meridional overturning circulation; therefore, the HR interactive ensemble is analogous to a HR hosing experiment. By characterizing the variability in these high-resolution GCM runs and observations we seek to understand what processes influence coastal SSH along the Eastern Coast of the United States and better predict future SLR.

Merging tree ring chronologies and climate system model simulated temperature by optimal interpolation algorithm in North America

NASA Astrophysics Data System (ADS)

Chen, Xin; Xing, Pei; Luo, Yong; Zhao, Zongci; Nie, Suping; Huang, Jianbin; Wang, Shaowu; Tian, Qinhua

2015-04-01

A new dataset of annual mean surface temperature has been constructed over North America in recent 500 years by performing optimal interpolation (OI) algorithm. Totally, 149 series totally were screened out including 69 tree ring width (MXD) and 80 tree ring width (TRW) chronologies are screened from International Tree Ring Data Bank (ITRDB). The simulated annual mean surface temperature derives from the past1000 experiment results of Community Climate System Model version 4 (CCSM4). Different from existing research that applying data assimilation approach to (General Circulation Models) GCMs simulation, the errors of both the climate model simulation and tree ring reconstruction were considered, with a view to combining the two parts in an optimal way. Variance matching (VM) was employed to calibrate tree ring chronologies on CRUTEM4v, and corresponding errors were estimated through leave-one-out process. Background error covariance matrix was estimated from samples of simulation results in a running 30-year window in a statistical way. Actually, the background error covariance matrix was calculated locally within the scanning range (2000km in this research). Thus, the merging process continued with a time-varying local gain matrix. The merging method (MM) was tested by two kinds of experiments, and the results indicated standard deviation of errors can be reduced by about 0.3 degree centigrade lower than tree ring reconstructions and 0.5 degree centigrade lower than model simulation. During the recent Obvious decadal variability can be identified in MM results including the evident cooling (0.10 degree per decade) in 1940-60s, wherein the model simulation exhibit a weak increasing trend (0.05 degree per decade) instead. MM results revealed a compromised spatial pattern of the linear trend of surface temperature during a typical period (1601-1800 AD) in Little Ice Age, which basically accorded with the phase transitions of the Pacific decadal oscillation (PDO) and Atlantic multi-decadal oscillation (AMO). Through the empirical orthogonal functions and power spectrum analysis, it was demonstrated that, compared with the pure simulations of CCSM4, MM made significant improvement of decadal variability for the gridded temperature in North America by merging the temperature-sensitive tree ring records.

Chebyshev collocation spectral method for one-dimensional radiative heat transfer in linearly anisotropic-scattering cylindrical medium

NASA Astrophysics Data System (ADS)

Zhou, Rui-Rui; Li, Ben-Wen

2017-03-01

In this study, the Chebyshev collocation spectral method (CCSM) is developed to solve the radiative integro-differential transfer equation (RIDTE) for one-dimensional absorbing, emitting and linearly anisotropic-scattering cylindrical medium. The general form of quadrature formulas for Chebyshev collocation points is deduced. These formulas are proved to have the same accuracy as the Gauss-Legendre quadrature formula (GLQF) for the F-function (geometric function) in the RIDTE. The explicit expressions of the Lagrange basis polynomials and the differentiation matrices for Chebyshev collocation points are also given. These expressions are necessary for solving an integro-differential equation by the CCSM. Since the integrand in the RIDTE is continuous but non-smooth, it is treated by the segments integration method (SIM). The derivative terms in the RIDTE are carried out to improve the accuracy near the origin. In this way, a fourth order accuracy is achieved by the CCSM for the RIDTE, whereas it's only a second order one by the finite difference method (FDM). Several benchmark problems (BPs) with various combinations of optical thickness, medium temperature distribution, degree of anisotropy, and scattering albedo are solved. The results show that present CCSM is efficient to obtain high accurate results, especially for the optically thin medium. The solutions rounded to seven significant digits are given in tabular form, and show excellent agreement with the published data. Finally, the solutions of RIDTE are used as benchmarks for the solution of radiative integral transfer equations (RITEs) presented by Sutton and Chen (JQSRT 84 (2004) 65-103). A non-uniform grid refined near the wall is advised to improve the accuracy of RITEs solutions.

Objective spatiotemporal proxy-model comparisons of the Asian monsoon for the last millennium

NASA Astrophysics Data System (ADS)

Anchukaitis, K. J.; Cook, E. R.; Ammann, C. M.; Buckley, B. M.; D'Arrigo, R. D.; Jacoby, G.; Wright, W. E.; Davi, N.; Li, J.

2008-12-01

The Asian monsoon system can be studied using a complementary proxy/simulation approach which evaluates climate models using estimates of past precipitation and temperature, and which subsequently applies the best understanding of the physics of the climate system as captured in general circulation models to evaluate the broad-scale dynamics behind regional paleoclimate reconstructions. Here, we use a millennial-length climate field reconstruction of monsoon season summer (JJA) drought, developed from tree- ring proxies, with coupled climate simulations from NCAR CSM1.4 and CCSM3 to evaluate the cause of large- scale persistent droughts over the last one thousand years. Direct comparisons are made between the external forced response within the climate model and the spatiotemporal field reconstruction. In order to identify patterns of drought associated with internal variability in the climate system, we use a model/proxy analog technique which objectively selects epochs in the model that most closely reproduce those observed in the reconstructions. The concomitant ocean-atmosphere dynamics are then interpreted in order to identify and understand the internal climate system forcing of low frequency monsoon variability. We examine specific periods of extensive or intensive regional drought in the 15th, 17th, and 18th centuries, many of which are coincident with major cultural changes in the region.

Evaluation of the skill of North-American Multi-Model Ensemble (NMME) Global Climate Models in predicting average and extreme precipitation and temperature over the continental USA

NASA Astrophysics Data System (ADS)

Slater, Louise J.; Villarini, Gabriele; Bradley, Allen A.

2016-08-01

This paper examines the forecasting skill of eight Global Climate Models from the North-American Multi-Model Ensemble project (CCSM3, CCSM4, CanCM3, CanCM4, GFDL2.1, FLORb01, GEOS5, and CFSv2) over seven major regions of the continental United States. The skill of the monthly forecasts is quantified using the mean square error skill score. This score is decomposed to assess the accuracy of the forecast in the absence of biases (potential skill) and in the presence of conditional (slope reliability) and unconditional (standardized mean error) biases. We summarize the forecasting skill of each model according to the initialization month of the forecast and lead time, and test the models' ability to predict extended periods of extreme climate conducive to eight `billion-dollar' historical flood and drought events. Results indicate that the most skillful predictions occur at the shortest lead times and decline rapidly thereafter. Spatially, potential skill varies little, while actual model skill scores exhibit strong spatial and seasonal patterns primarily due to the unconditional biases in the models. The conditional biases vary little by model, lead time, month, or region. Overall, we find that the skill of the ensemble mean is equal to or greater than that of any of the individual models. At the seasonal scale, the drought events are better forecast than the flood events, and are predicted equally well in terms of high temperature and low precipitation. Overall, our findings provide a systematic diagnosis of the strengths and weaknesses of the eight models over a wide range of temporal and spatial scales.

Simulation of Extreme Arctic Cyclones in IPCC AR5 Experiments

DTIC Science & Technology

2012-09-30

of the present-day Arctic atmosphere in CCSM4. J. Climate, 2676-2695. Overeem, I ., R . S. Anderson, C. W. Wobus, G. D. Clow, F. E. Urban, and N...intensity of extreme Arctic cyclones? APPROACH I am targeting these objectives through a retrospective analysis of the transient 20th century...simulations (spanning years 1850-2005) among the GCMs participating in the latest Coupled Model Intercomparison Project (CMIP5). I am including 14

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

LaRow, Timothy

The SSTs used in our study come from the Community Climate System Model version 4 (CCSM4) (Gent et al 2011) and from the Canadian Centre for Climate Modeling and Analysis (CanESM2) (Chylek et al20ll) climate models from the fifth Coupled Model Intercomparison Project (CMIP5) (Taylor et al2012). We've examined the tropical cyclones using both the historical simulation that employs volcanic and aerosol forcing as well as the representative concentration pathway 4.5 (RCP4.5). In addition, we've compared the present day North Atlantic tropical cyclone metrics from a previous study (LaRow, 2013) to these climate change experiments. The experimental setup is shownmore » in Table 1. We considered the CMIP5 experiment number '3.2 historical' (Taylor et al,201l), which provides simulations of the recent past (1850-2005). The second set of CMIP5 SSTs is the RCp4.5 experiment where the radiative forcing stabilizes at 45W m-2 after 2100 (experiment number 4.1 in Taylor etal2}ll).« less

LPJ-GUESS Simulated Western North America Mid-latitude Vegetation Changes for 15-10 ka Using the CCSM3 TraCE Climate Simulation

NASA Astrophysics Data System (ADS)

Shafer, S. L.; Bartlein, P. J.

2017-12-01

The period from 15-10 ka was a time of rapid vegetation changes in North America. Continental ice sheets in northern North America were receding, exposing new habitat for vegetation, and regions distant from the ice sheets experienced equally large environmental changes. Northern hemisphere temperatures during this period were increasing, promoting transitions from cold-adapted to temperate plant taxa at mid-latitudes. Long, transient paleovegetation simulations can provide important information on vegetation responses to climate changes, including both the spatial dynamics and rates of species distribution changes over time. Paleovegetation simulations also can fill the spatial and temporal gaps in observed paleovegetation records (e.g., pollen data from lake sediments), allowing us to test hypotheses about past vegetation changes (e.g., the location of past refugia). We used the CCSM3 TraCE transient climate simulation as input for LPJ-GUESS, a general ecosystem model, to simulate vegetation changes from 15-10 ka for parts of western North America at mid-latitudes ( 35-55° N). For these simulations, LPJ-GUESS was parameterized to simulate key tree taxa for western North America (e.g., Pseudotsuga, Tsuga, Quercus, etc.). The CCSM3 TraCE transient climate simulation data were regridded onto a 10-minute grid of the study area. We analyzed the simulated spatial and temporal dynamics of these taxa and compared the simulated changes with observed paleovegetation changes recorded in pollen and plant macrofossil data (e.g., data from the Neotoma Paleoecology Database). In general, the LPJ-GUESS simulations reproduce the general patterns of paleovegetation responses to climate change, although the timing of some simulated vegetation changes do not match the observed paleovegetation record. We describe the areas and time periods with the greatest data-model agreement and disagreement, and discuss some of the strengths and weaknesses of the simulated climate and vegetation data. The magnitude and rate of the simulated past vegetation changes are compared with projected future vegetation changes for the region.

Do Responses to Different Anthropogenic Forcings Add Linearly in Climate Models?

NASA Technical Reports Server (NTRS)

Marvel, Kate; Schmidt, Gavin A.; Shindell, Drew; Bonfils, Celine; LeGrande, Allegra N.; Nazarenko, Larissa; Tsigaridis, Kostas

2015-01-01

Many detection and attribution and pattern scaling studies assume that the global climate response to multiple forcings is additive: that the response over the historical period is statistically indistinguishable from the sum of the responses to individual forcings. Here, we use the NASA Goddard Institute for Space Studies (GISS) and National Center for Atmospheric Research Community Climate System Model (CCSM) simulations from the CMIP5 archive to test this assumption for multi-year trends in global-average, annual-average temperature and precipitation at multiple timescales. We find that responses in models forced by pre-computed aerosol and ozone concentrations are generally additive across forcings; however, we demonstrate that there are significant nonlinearities in precipitation responses to di?erent forcings in a configuration of the GISS model that interactively computes these concentrations from precursor emissions. We attribute these to di?erences in ozone forcing arising from interactions between forcing agents. Our results suggest that attribution to specific forcings may be complicated in a model with fully interactive chemistry and may provide motivation for other modeling groups to conduct further single-forcing experiments.

Do responses to different anthropogenic forcings add linearly in climate models?

DOE PAGES

Marvel, Kate; Schmidt, Gavin A.; Shindell, Drew; ...

2015-10-14

Many detection and attribution and pattern scaling studies assume that the global climate response to multiple forcings is additive: that the response over the historical period is statistically indistinguishable from the sum of the responses to individual forcings. Here, we use the NASA Goddard Institute for Space Studies (GISS) and National Center for Atmospheric Research Community Climate System Model (CCSM4) simulations from the CMIP5 archive to test this assumption for multi-year trends in global-average, annual-average temperature and precipitation at multiple timescales. We find that responses in models forced by pre-computed aerosol and ozone concentrations are generally additive across forcings. However,more » we demonstrate that there are significant nonlinearities in precipitation responses to different forcings in a configuration of the GISS model that interactively computes these concentrations from precursor emissions. We attribute these to differences in ozone forcing arising from interactions between forcing agents. Lastly, our results suggest that attribution to specific forcings may be complicated in a model with fully interactive chemistry and may provide motivation for other modeling groups to conduct further single-forcing experiments.« less

Modeling the Pineapple Express phenomenon via Multivariate Extreme Value Theory

NASA Astrophysics Data System (ADS)

Weller, G.; Cooley, D. S.

2011-12-01

The pineapple express (PE) phenomenon is responsible for producing extreme winter precipitation events in the coastal and mountainous regions of the western United States. Because the PE phenomenon is also associated with warm temperatures, the heavy precipitation and associated snowmelt can cause destructive flooding. In order to study impacts, it is important that regional climate models from NARCCAP are able to reproduce extreme precipitation events produced by PE. We define a daily precipitation quantity which captures the spatial extent and intensity of precipitation events produced by the PE phenomenon. We then use statistical extreme value theory to model the tail dependence of this quantity as seen in an observational data set and each of the six NARCCAP regional models driven by NCEP reanalysis. We find that most NCEP-driven NARCCAP models do exhibit tail dependence between daily model output and observations. Furthermore, we find that not all extreme precipitation events are pineapple express events, as identified by Dettinger et al. (2011). The synoptic-scale atmospheric processes that drive extreme precipitation events produced by PE have only recently begun to be examined. Much of the current work has focused on pattern recognition, rather than quantitative analysis. We use daily mean sea-level pressure (MSLP) fields from NCEP to develop a "pineapple express index" for extreme precipitation, which exhibits tail dependence with our observed precipitation quantity for pineapple express events. We build a statistical model that connects daily precipitation output from the WRFG model, daily MSLP fields from NCEP, and daily observed precipitation in the western US. Finally, we use this model to simulate future observed precipitation based on WRFG output driven by the CCSM model, and our pineapple express index derived from future CCSM output. Our aim is to use this model to develop a better understanding of the frequency and intensity of extreme precipitation events produced by PE under climate change.

An integrated assessment modeling framework for uncertainty studies in global and regional climate change: the MIT IGSM-CAM (version 1.0)

NASA Astrophysics Data System (ADS)

Monier, E.; Scott, J. R.; Sokolov, A. P.; Forest, C. E.; Schlosser, C. A.

2013-12-01

This paper describes a computationally efficient framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyze uncertainties in emissions resulting from both uncertainties in the underlying socio-economic characteristics of the economic model and in the choice of climate-related policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response to changes in greenhouse gases and aerosols concentrations, e.g., climate sensitivity, ocean heat uptake rate, and strength of the aerosol forcing. The IGSM-CAM is not only able to realistically simulate the present-day mean climate and the observed trends at the global and continental scale, but it also simulates ENSO variability with realistic time scales, seasonality and patterns of SST anomalies, albeit with stronger magnitudes than observed. The IGSM-CAM shares the same general strengths and limitations as the Coupled Model Intercomparison Project Phase 3 (CMIP3) models in simulating present-day annual mean surface temperature and precipitation. Over land, the IGSM-CAM shows similar biases to the NCAR Community Climate System Model (CCSM) version 3, which shares the same atmospheric model. This study also presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios, and three sets of climate parameters. Results of the simulations with the chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century changes in global mean surface air temperature from previous work with the IGSM. Because the IGSM-CAM framework only considers one particular climate model, it cannot be used to assess the structural modeling uncertainty arising from differences in the parameterization suites of climate models. However, comparison of the IGSM-CAM projections with simulations of 31 CMIP5 models under the RCP4.5 and RCP8.5 scenarios show that the range of warming at the continental scale shows very good agreement between the two ensemble simulations, except over Antarctica, where the IGSM-CAM overestimates the warming. This demonstrates that by sampling the climate system response, the IGSM-CAM, even though it relies on one single climate model, can essentially reproduce the range of future continental warming simulated by more than 30 different models. Precipitation changes projected in the IGSM-CAM simulations and the CMIP5 multi-model ensemble both display a large uncertainty at the continental scale. The two ensemble simulations show good agreement over Asia and Europe. However, the ranges of precipitation changes do not overlap - but display similar size - over Africa and South America, two continents where models generally show little agreement in the sign of precipitation changes and where CCSM3 tends to be an outlier. Overall, the IGSM-CAM provides an efficient and consistent framework to explore the large uncertainty in future projections of global and regional climate change associated with uncertainty in the climate response and projected emissions.

Amplified Late Pliocene terrestrial warmth in northern high latitudes from greater radiative forcing and closed Arctic Ocean gateways

NASA Astrophysics Data System (ADS)

Feng, Ran; Otto-Bliesner, Bette L.; Fletcher, Tamara L.; Tabor, Clay R.; Ballantyne, Ashley P.; Brady, Esther C.

2017-05-01

Proxy reconstructions of the mid-Piacenzian warm period (mPWP, between 3.264 and 3.025 Ma) suggest terrestrial temperatures were much warmer in the northern high latitudes (55°-90°N, referred to as NHL) than present-day. Climate models participating in the Pliocene Model Intercomparison Project Phase 1 (PlioMIP1) tend to underestimate this warmth. For instance, the underestimate is ∼10 °C on average across NHL and up to 17 °C in the Canadian Arctic region in the Community Climate System Model version 4 (CCSM4). Here, we explore potential mPWP climate forcings that might contribute to this mPWP mismatch. We carry out seven experiments to assess terrestrial temperature responses to Pliocene Arctic gateway closure, variations in CO2 level, and orbital forcing at millennial time scale. To better compare the full range of simulated terrestrial temperatures with sparse proxy data, we introduce a pattern recognition technique that simplifies the model surface temperatures to a few representative patterns that can be validate with the limited terrestrial proxy data. The pattern recognition technique reveals two prominent features of simulated Pliocene surface temperature responses. First, distinctive patterns of amplified warming occur in the NHL, which can be explained by lowered surface elevation of Greenland, pattern and amount of Arctic sea ice loss, and changing strength of Atlantic meridional overturning circulation. Second, patterns of surface temperature response are similar among experiments with different forcing mechanisms. This similarity is due to strong feedbacks from responses in surface albedo and troposphere water vapor content to sea ice changes, which overwhelm distinctions in forcings from changes in insolation, CO2 forcing, and Arctic gateway closure. By comparing CCSM4 simulations with proxy records, we demonstrate that both model and proxy records show similar patterns of mPWP NHL terrestrial warmth, but the model underestimates the magnitude. High insolation, greater CO2 forcing, and Arctic gateways closure each contributes to reduce the underestimate by enhancing the Arctic warmth of 1-2 °C. These results highlight the importance of considering proxy NHL warmth in the context of Pliocene Arctic gateway changes, and variations in insolation and CO2 forcing.

Modern (1992–2011) and projected (2012–99) peak snowpack and May–July runoff for the Fort Peck Lake and Lake Sakakawea watersheds in the Upper Missouri River Basin

USGS Publications Warehouse

Stamm, John F.; Todey, Dennis; Mayes Bousted, Barbara; Rossi, Shawn; Norton, Parker A.; Carter, Janet M.

2016-02-09

Annual peak snowpack was projected to have a downward trend for the Fort Peck Lake watershed and an upward trend for the lower Lake Sakakawea watershed. Projections of May–July runoff had a significant downward trend for the Fort Peck Lake, lower Lake Sakakawea, and Lake Sakakawea (combination of Fort Peck Lake and lower Lake Sakakawea) watersheds. Downward trends in projected May–July runoff indicated that power production at Fort Peck Dam might be affected particularly in the later part of the simulation (2061–99); however, confidence in projected May–July runoff for the later part of the simulation was less certain because bias-corrected air temperatures from CCSM3 and CCSM4 commonly fell outside of the observed range used for calibration. Projected May–July runoff combined for the Fort Peck Lake and lower Lake Sakakawea watersheds were on the order of magnitude of the 2011 flood for 1 simulation year for each of the CCSM-based simulations. High peak snowpack and precipitation in April, May, and June in the plains was associated with large May–July runoff events; therefore, high precipitation at lower elevations in the Fort Peck Lake and lower Lake Sakakawea watersheds was a factor in the simulation of extreme runoff events at the magnitude of the 2011 flood.

Field information links permafrost carbon to physical vulnerabilities of thawing

NASA Astrophysics Data System (ADS)

Harden, Jennifer W.; Koven, Charles D.; Ping, Chien-Lu; Hugelius, Gustaf; David McGuire, A.; Camill, Phillip; Jorgenson, Torre; Kuhry, Peter; Michaelson, Gary J.; O'Donnell, Jonathan A.; Schuur, Edward A. G.; Tarnocai, Charles; Johnson, Kristopher; Grosse, Guido

2012-08-01

Deep soil profiles containing permafrost (Gelisols) were characterized for organic carbon (C) and total nitrogen (N) stocks to 3 m depths. Using the Community Climate System Model (CCSM4) we calculate cumulative distributions of active layer thickness (ALT) under current and future climates. The difference in cumulative ALT distributions over time was multiplied by C and N contents of soil horizons in Gelisol suborders to calculate newly thawed C and N. Thawing ranged from 147 PgC with 10 PgN by 2050 (representative concentration pathway RCP scenario 4.5) to 436 PgC with 29 PgN by 2100 (RCP 8.5). Organic horizons that thaw are vulnerable to combustion, and all horizon types are vulnerable to shifts in hydrology and decomposition. The rates and extent of such losses are unknown and can be further constrained by linking field and modelling approaches. These changes have the potential for strong additional loading to our atmosphere, water resources, and ecosystems.

Field information links permafrost carbon to physical vulnerabilities of thawing

USGS Publications Warehouse

Harden, Jennifer W.; Koven, Charles; Ping, Chien-Lu; Hugelius, Gustaf; McGuire, A. David; Camill, P.; Jorgenson, Torre; Kuhry, Peter; Michaelson, Gary; O'Donnell, Jonathan A.; Schuur, Edward A.G.; Tamocai, Charles; Johnson, Kevin; Grosse, G.

2012-01-01

Deep soil profiles containing permafrost (Gelisols) were characterized for organic carbon (C) and total nitrogen (N) stocks to 3m depths. Using the Community Climate System Model (CCSM4) we calculate cumulative probability functions (PDFs) for active layer depths under current and future climates. The difference in PDFs over time was multiplied by C and N contents of soil horizons in Gelisol suborders to calculate newly thawed C and N, Thawing ranged from 147 PgC with 10 PgN by 2050 (representative concentration pathway RCP scenario 4.5) to 436 PgC with 29 PgN by 2100 (RCP 8.5). Organic horizons that thaw are vulnerable to combustion, and all horizon types are vulnerable to shifts in hydrology and decomposition. The rates and extent of such losses are unknown and can be further constrained by linking field and modelling approaches. These changes have the potential for strong additional loading to our atmosphere, water resources, and ecosystems.

Explicit Convection over the Western Pacific Warm Pool in the Community Atmospheric Model.

NASA Astrophysics Data System (ADS)

Ziemiaski, Micha Z.; Grabowski, Wojciech W.; Moncrieff, Mitchell W.

2005-05-01

This paper reports on the application of the cloud-resolving convection parameterization (CRCP) to the Community Atmospheric Model (CAM), the atmospheric component of the Community Climate System Model (CCSM). The cornerstone of CRCP is the use of a two-dimensional zonally oriented cloud-system-resolving model to represent processes on mesoscales at the subgrid scale of a climate model. Herein, CRCP is applied at each climate model column over the tropical western Pacific warm pool, in a domain spanning 10°S-10°N, 150°-170°E. Results from the CRCP simulation are compared with CAM in its standard configuration.The CRCP simulation shows significant improvements of the warm pool climate. The cloud condensate distribution is much improved as well as the bias of the tropopause height. More realistic structure of the intertropical convergence zone (ITCZ) during the boreal winter and better representation of the variability of convection are evident. In particular, the diurnal cycle of precipitation has phase and amplitude in good agreement with observations. Also improved is the large-scale organization of the tropical convection, especially superclusters associated with Madden-Julian oscillation (MJO)-like systems. Location and propagation characteristics, as well as lower-tropospheric cyclonic and upper-tropospheric anticyclonic gyres, are more realistic than in the standard CAM. Finally, the simulations support an analytic theory of dynamical coupling between organized convection and equatorial beta-plane vorticity dynamics associated with MJO-like systems.

ParCAT: A Parallel Climate Analysis Toolkit

NASA Astrophysics Data System (ADS)

Haugen, B.; Smith, B.; Steed, C.; Ricciuto, D. M.; Thornton, P. E.; Shipman, G.

2012-12-01

Climate science has employed increasingly complex models and simulations to analyze the past and predict the future of our climate. The size and dimensionality of climate simulation data has been growing with the complexity of the models. This growth in data is creating a widening gap between the data being produced and the tools necessary to analyze large, high dimensional data sets. With single run data sets increasing into 10's, 100's and even 1000's of gigabytes, parallel computing tools are becoming a necessity in order to analyze and compare climate simulation data. The Parallel Climate Analysis Toolkit (ParCAT) provides basic tools that efficiently use parallel computing techniques to narrow the gap between data set size and analysis tools. ParCAT was created as a collaborative effort between climate scientists and computer scientists in order to provide efficient parallel implementations of the computing tools that are of use to climate scientists. Some of the basic functionalities included in the toolkit are the ability to compute spatio-temporal means and variances, differences between two runs and histograms of the values in a data set. ParCAT is designed to facilitate the "heavy lifting" that is required for large, multidimensional data sets. The toolkit does not focus on performing the final visualizations and presentation of results but rather, reducing large data sets to smaller, more manageable summaries. The output from ParCAT is provided in commonly used file formats (NetCDF, CSV, ASCII) to allow for simple integration with other tools. The toolkit is currently implemented as a command line utility, but will likely also provide a C library for developers interested in tighter software integration. Elements of the toolkit are already being incorporated into projects such as UV-CDAT and CMDX. There is also an effort underway to implement portions of the CCSM Land Model Diagnostics package using ParCAT in conjunction with Python and gnuplot. ParCAT is implemented in C to provide efficient file IO. The file IO operations in the toolkit use the parallel-netcdf library; this enables the code to use the parallel IO capabilities of modern HPC systems. Analysis that currently requires an estimated 12+ hours with the traditional CCSM Land Model Diagnostics Package can now be performed in as little as 30 minutes on a single desktop workstation and a few minutes for relatively small jobs completed on modern HPC systems such as ORNL's Jaguar.

Evaluation of Multi-Model Ensemble System for Seasonal and Monthly Prediction

NASA Astrophysics Data System (ADS)

Zhang, Q.; Van den Dool, H. M.

2013-12-01

Since August 2011, the realtime seasonal forecasts of U.S. National Multi-Model Ensemble (NMME) have been made on 8th of each month by NCEP Climate Prediction Center (CPC). During the first year, the participating models were NCEP/CFSv1&2, GFDL/CM2.2, NCAR/U.Miami/COLA/CCSM3, NASA/GEOS5, IRI/ ECHAM-a & ECHAM-f for the realtime NMME forecast. The Canadian Meteorological Center CanCM3 and CM4 replaced the CFSv1 and IRI's models in the second year. The NMME team at CPC collects three variables, including precipitation, 2-meter temperature and sea surface temperature from each modeling center on a 1x1 global grid, removes systematic errors, makes the grand ensemble mean with equal weight for each model and constructs a probability forecast with equal weight for each member. The team then provides the NMME forecast to the operational CPC forecaster responsible for the seasonal and monthly outlook each month. Verification of the seasonal and monthly prediction from NMME is conducted by calculating the anomaly correlation (AC) from the 30-year hindcasts (1982-2011) of individual model and NMME ensemble. The motivation of this study is to provide skill benchmarks for future improvements of the NMME seasonal and monthly prediction system. The experimental (Phase I) stage of the project already supplies routine guidance to users of the NMME forecasts.

Modeling Future Fire danger over North America in a Changing Climate

NASA Astrophysics Data System (ADS)

Jain, P.; Paimazumder, D.; Done, J.; Flannigan, M.

2016-12-01

Fire danger ratings are used to determine wildfire potential due to weather and climate factors. The Fire Weather Index (FWI), part of the Canadian Forest Fire Danger Rating System (CFFDRS), incorporates temperature, relative humidity, windspeed and precipitation to give a daily fire danger rating that is used by wildfire management agencies in an operational context. Studies using GCM output have shown that future wildfire danger will increase in a warming climate. However, these studies are somewhat limited by the coarse spatial resolution (typically 100-400km) and temporal resolution (typically 6-hourly to monthly) of the model output. Future wildfire potential over North America based on FWI is calculated using output from the Weather, Research and Forecasting (WRF) model, which is used to downscale future climate scenarios from the bias-corrected Community Climate System Model (CCSM) under RCP8.5 scenarios at a spatial resolution of 36km. We consider five eleven year time slices: 1990-2000, 2020-2030, 2030-2040, 2050-2060 and 2080-2090. The dynamically downscaled simulation improves determination of future extreme weather by improving both spatial and temporal resolution over most GCM models. To characterize extreme fire weather we calculate annual numbers of spread days (days for which FWI > 19) and annual 99th percentile of FWI. Additionally, an extreme value analysis based on the peaks-over-threshold method allows us to calculate the return values for extreme FWI values.

Studying the impact of climate change on flooding in large river basins

NASA Astrophysics Data System (ADS)

Thiele-Eich, I.; Hopson, T.; Gilleland, E.; Lamarque, J.-F.; Hu, A.; Simmer, C.

2012-04-01

Assessing the potential impact of global climate change on hydrological extremes becomes crucial for regions such as Bangladesh, where a high population density results in a large exposure to risks associated with extreme flooding. In addition, low-lying countries such as Bangladesh are especially vulnerable to sea-level rise and its influence on present-day flood characteristics. By combining the impact of climate change on upper catchment precipitation as well as on sea-level rise at the river mouths, we attempt to analyze the development of flood characteristics such as frequency and magnitude in large river basins. Since flood duration is also of great importance to people exposed to flooding, the development of the number of days with extreme flooding is evaluated for possible trends in the future. Data used includes historical observations from the Global Runoff Data Centre, while recently released model output for upper catchment precipitation and annual mean thermosteric sea-level rise is taken from the four CCSM4 1° 20th Century ensemble members, as well as from six CCSM4 1° ensemble members for the reference concentration pathway scenarios RCP8.5, 6.0, 4.5 and 2.6. A peak-over-threshold approach is used to quantify the expected future changes in flood return levels, where discharge exceedances over a certain threshold are fit to a Generalized Pareto Distribution. Return levels are compared from both 20th century and future model simulations for time slices at 2030, 2050, 2070 and 2090. It can be seen that return periods of flood events decrease as the 21st century progresses in all RCP scenarios, with this shift most pronounced in RCP 8.5. The evaluation of flood duration, or the number of days with discharges above a certain threshold, yields an increase. While the number of days with flooding increases in all RCP scenarios, with the largest increase seen at the end of the 21st century, this increase is only statistically significant for RCP 8.5. Finally, we study how sea-level rise governs the flooding behavior further upstream by calculating the effective additional discharge due to the backwater effect of sea-level rise. Sea-level rise anomalies for the 21st century are taken from CCSM4 model output at each of the river mouths. Judging from our work, the increase in effective discharge due to sea-level rise cannot be neglected when discussing flooding in the respective river basins. Impact of sea-level rise on changes in return levels will be investigated further by using extreme-value theory to calculate how the tails of the current river discharge distribution will be shifted by changing climate.

Understanding climate variability and global climate change using high-resolution GCM simulations

NASA Astrophysics Data System (ADS)

Feng, Xuelei

In this study, three climate processes are examined using long-term simulations from multiple climate models with increasing horizontal resolutions. These simulations include the European Center for Medium-range Weather Forecasts (ECMWF) atmospheric general circulation model (AGCM) runs forced with observed sea surface temperatures (SST) (the Athena runs) and a set of coupled ocean-atmosphere seasonal hindcasts (the Minerva runs). Both sets of runs use different AGCM resolutions, the highest at 16 km. A pair of the Community Climate System Model (CCSM) simulations with ocean general circulation model (OGCM) resolutions at 100 and 10 km are also examined. The higher resolution CCSM run fully resolves oceanic mesoscale eddies. The resolution influence on the precipitation climatology over the Gulf Stream (GS) region is first investigated. In the Athena simulations, the resolution increase generates enhanced mean GS precipitation moderately in both large-scale and sub-scale rainfalls in the North Atlantic, with the latter more tightly confined near the oceanic front. However, the non-eddy resolving OGCM in the Minerva runs simulates a weaker oceanic front and weakens the mean GS precipitation response. On the other hand, an increase in CCSM oceanic resolutions from non-eddy-resolving to eddy resolving regimes greatly improves the model's GS precipitation climatology, resulting in both stronger intensity and more realistic structure. Further analyses show that the improvement of the GS precipitation climatology due to resolution increases is caused by the enhanced atmospheric response to an increased SST gradient near the oceanic front, which leads to stronger surface convergence and upper level divergence. Another focus of this study is on the global warming impacts on precipitation characteristic changes using the high-resolution Athena simulations under the SST forcing from the observations and a global warming scenario. As a comparison, results from the coarse resolution simulation are also analyzed to examine the dependence on resolution. The increasing rates of globally averaged precipitation amount for the high and low resolution simulations are 1.7%/K-1 and 1.8%/K-1, respectively. The sensitivities for heavy, moderate, light and drizzle rain are 6.8, -1.2, 0.0, 0.2%/K-1 for low and 6.3, -1.5, 0.4, -0.2%/K -1 for high resolution simulations. The number of rainy days decreases in a warming scenario, by 3.4 and 4.2 day/year-1, respectively. The most sensitive response of 6.3-6.8%/K-1 for the heavy rain approaches that of the 7%/K-1 for the Clausius-Clapeyron scaling limit. During the twenty-first century simulation, the increases in precipitation are larger over high latitude and wet regions in low and mid-latitudes. Over the dry regions, such as the subtropics, the precipitation amount and frequency decrease. There is a higher occurrence of low and heavy rain from the tropics to mid-latitudes at the expense of the decreases in the frequency of moderate rain. In the third part, the inter-annual variability of the northern hemisphere storm tracks is examined. In the Athena simulations, the leading modes of the observed storm track variability are reproduced realistically by all runs. In general, the fluctuations of the model storm tracks in the North Pacific and Atlantic basins are largely independent of each other. Within each basin, the variations are characterized by the intensity change near the climatological center and the meridional shift of the storm track location. These two modes are associated with major teleconnection patterns of the low frequency atmospheric variations. These model results are not sensitive to resolution. Using the Minerva hindcast initialized in November, it is shown that a portion of the winter (December-January) storm track variability is predictable, mainly due to the influences of the atmospheric wave trains induced by the El Nino and Southern Oscillation.

Projecting Future Water Levels of the Laurentian Great Lakes

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Great Plains Drought in Simulations of Twentieth Century

NASA Astrophysics Data System (ADS)

McCrary, R. R.; Randall, D. A.

2008-12-01

The Great Plains region of the United States was influenced by a number of multi-year droughts during the twentieth century. Most notable were the "Dust Bowl" drought of the 1930s and the 1950s Great Plains drought. In this study we evaluate the ability of three of the Coupled Global Climate Models (CGCMs) used in the Fourth Assessment Report (AR4) of the IPCC to simulate Great Plains drought with the same frequency and intensity as was observed during the twentieth century. The models chosen for this study are: GFDL CM 2.0, NCAR CCSM3, and UKMO HadCM3. We find that the models accurately capture the climatology of the hydrologic cycle of the Great Plains, but that they tend to overestimate the variability in Great Plains precipitation. We also find that in each model simulation at least one long-term drought occurs over the Great Plains region during their representations 20th Century Climate. The multi-year droughts produced by the models exhibit similar magnitudes and spatial scales as was observed during the twentieth century. This study also investigates the relative roles that external forcing from the tropical Pacific and local feedbacks between the land surface and the atmosphere have in the initiation and perpetuation of Great Plains drought in each model. We find that cool, La Nina-like conditions in the tropical pacific are often associated with long-term drought conditions over the Great Plains in GFDL CM 2.0 and UKMO HadCM3, but there appears to be no systematic relationship between tropical Pacific SST variability and Great Plains drought in CCSM3. It is possible the strong coupling between the land surface and the atmosphere in the NCAR model causes precipitation anomalies to lock into phase over the Great Plains thereby perpetuating drought conditions. Results from this study are intended to help assess whether or not these climate models are credible for use in the assessment of future drought over the Great Plains region of the United States.

Applying downscaled global climate model data to a hydrodynamic surface-water and groundwater model

USGS Publications Warehouse

Swain, Eric; Stefanova, Lydia; Smith, Thomas

2014-01-01

Precipitation data from Global Climate Models have been downscaled to smaller regions. Adapting this downscaled precipitation data to a coupled hydrodynamic surface-water/groundwater model of southern Florida allows an examination of future conditions and their effect on groundwater levels, inundation patterns, surface-water stage and flows, and salinity. The downscaled rainfall data include the 1996-2001 time series from the European Center for Medium-Range Weather Forecasting ERA-40 simulation and both the 1996-1999 and 2038-2057 time series from two global climate models: the Community Climate System Model (CCSM) and the Geophysical Fluid Dynamic Laboratory (GFDL). Synthesized surface-water inflow datasets were developed for the 2038-2057 simulations. The resulting hydrologic simulations, with and without a 30-cm sea-level rise, were compared with each other and field data to analyze a range of projected conditions. Simulations predicted generally higher future stage and groundwater levels and surface-water flows, with sea-level rise inducing higher coastal salinities. A coincident rise in sea level, precipitation and surface-water flows resulted in a narrower inland saline/fresh transition zone. The inland areas were affected more by the rainfall difference than the sea-level rise, and the rainfall differences make little difference in coastal inundation, but a larger difference in coastal salinities.

Evaluation of Probable Maximum Precipitation and Flood under Climate Change in the 21st Century

NASA Astrophysics Data System (ADS)

Gangrade, S.; Kao, S. C.; Rastogi, D.; Ashfaq, M.; Naz, B. S.; Kabela, E.; Anantharaj, V. G.; Singh, N.; Preston, B. L.; Mei, R.

2016-12-01

Critical infrastructures are potentially vulnerable to extreme hydro-climatic events. Under a warming environment, the magnitude and frequency of extreme precipitation and flood are likely to increase enhancing the needs to more accurately quantify the risks due to climate change. In this study, we utilized an integrated modeling framework that includes the Weather Research Forecasting (WRF) model and a high resolution distributed hydrology soil vegetation model (DHSVM) to simulate probable maximum precipitation (PMP) and flood (PMF) events over Alabama-Coosa-Tallapoosa River Basin. A total of 120 storms were selected to simulate moisture maximized PMP under different meteorological forcings, including historical storms driven by Climate Forecast System Reanalysis (CFSR) and baseline (1981-2010), near term future (2021-2050) and long term future (2071-2100) storms driven by Community Climate System Model version 4 (CCSM4) under Representative Concentrations Pathway 8.5 emission scenario. We also analyzed the sensitivity of PMF to various antecedent hydrologic conditions such as initial soil moisture conditions and tested different compulsive approaches. Overall, a statistical significant increase is projected for future PMP and PMF, mainly attributed to the increase of background air temperature. The ensemble of simulated PMP and PMF along with their sensitivity allows us to better quantify the potential risks associated with hydro-climatic extreme events on critical energy-water infrastructures such as major hydropower dams and nuclear power plants.

A consistent prescription of stratospheric aerosol for both radiation and chemistry in the Community Earth System Model (CESM1)

DOE PAGES

Neely, III, Ryan Reynolds; Conley, Andrew J.; Vitt, Francis; ...

2016-07-25

Here we describe an updated parameterization for prescribing stratospheric aerosol in the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM1). The need for a new parameterization is motivated by the poor response of the CESM1 (formerly referred to as the Community Climate System Model, version 4, CCSM4) simulations contributed to the Coupled Model Intercomparison Project 5 (CMIP5) to colossal volcanic perturbations to the stratospheric aerosol layer (such as the 1991 Pinatubo eruption or the 1883 Krakatau eruption) in comparison to observations. In particular, the scheme used in the CMIP5 simulations by CESM1 simulated a global mean surface temperature decreasemore » that was inconsistent with the GISS Surface Temperature Analysis (GISTEMP), NOAA's National Climatic Data Center, and the Hadley Centre of the UK Met Office (HADCRUT4). The new parameterization takes advantage of recent improvements in historical stratospheric aerosol databases to allow for variations in both the mass loading and size of the prescribed aerosol. An ensemble of simulations utilizing the old and new schemes shows CESM1's improved response to the 1991 Pinatubo eruption. Most significantly, the new scheme more accurately simulates the temperature response of the stratosphere due to local aerosol heating. Here, results also indicate that the new scheme decreases the global mean temperature response to the 1991 Pinatubo eruption by half of the observed temperature change, and modelled climate variability precludes statements as to the significance of this change.« less

The Community Land Model and Its Climate Statistics as a Component of the Community Climate System Model

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

Dickinson, Robert E.; Oleson, Keith; Bonan, Gordon

2006-01-01

Several multidecadal simulations have been carried out with the new version of the Community Climate System Model (CCSM). This paper reports an analysis of the land component of these simulations. Global annual averages over land appear to be within the uncertainty of observational datasets, but the seasonal cycle over land of temperature and precipitation appears to be too weak. These departures from observations appear to be primarily a consequence of deficiencies in the simulation of the atmospheric model rather than of the land processes. High latitudes of northern winter are biased sufficiently warm to have a significant impact on themore » simulated value of global land temperature. The precipitation is approximately doubled from what it should be at some locations, and the snowpack and spring runoff are also excessive. The winter precipitation over Tibet is larger than observed. About two-thirds of this precipitation is sublimated during the winter, but what remains still produces a snowpack that is very large compared to that observed with correspondingly excessive spring runoff. A large cold anomaly over the Sahara Desert and Sahel also appears to be a consequence of a large anomaly in downward longwave radiation; low column water vapor appears to be most responsible. The modeled precipitation over the Amazon basin is low compared to that observed, the soil becomes too dry, and the temperature is too warm during the dry season.« less

The impact of SciDAC on US climate change research and the IPCCAR4

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

Wehner, Michael

2005-07-08

SciDAC has invested heavily in climate change research. We offer a candid opinion as to the impact of the DOE laboratories' SciDAC projects on the upcoming Fourth Assessment Report of the Intergovernmental Panel on Climate Change. As a result of the direct importance of climate change to society, climate change research is highly coordinated at the international level. The Intergovernmental Panel on Climate Change (IPCC) is charged with providing regular reports on the state of climate change research to government policymakers. These reports are the product of thousands of scientists efforts. A series of reviews involving both scientists and policymakersmore » make them among the most reviewed documents produced in any scientific field. The high profile of these reports acts a driver to many researchers in the climate sciences. The Fourth Assessment Report (AR4) is scheduled to be released in 2007. SciDAC sponsored research has enabled the United States climate modeling community to make significant contributions to this report. Two large multi-Laboratory SciDAC projects are directly relevant to the activities of the IPCC. The first, entitled ''Collaborative Design and Development of the Community Climate System Model for Terascale Computers'', has made important software contributions to the recently released third version of the Community Climate System Model (CCSM3.0) developed at the National Center for Atmospheric Research. This is a multi-institutional project involving Los Alamos National Laboratory, Oak Ridge National Laboratory, Lawrence Berkeley National Laboratory, Pacific Northwest National Laboratory, Argonne National Laboratory, Lawrence Livermore National Laboratory and the National Center for Atmospheric Research. The original principal investigators were Robert Malone and John B. Drake. The current principal investigators are Phil Jones and John B. Drake. The second project, entitled ''Earth System Grid II: Turning Climate Datasets into Community Resources'' aims to facilitate the distribution of the copious amounts of data produced by coupled climate model integrations to the general scientific community. This is also a multi-institutional project involving Argonne National Laboratory, Oak Ridge National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Livermore National Laboratory and the National Center for Atmospheric Research. The principal investigators are Ian Foster, Don Middleton and Dean Williams. Perhaps most significant among the activities of the ''Collaborative Design'', project was the development of an efficient multi-processor coupling package. CCSM3.0 is an extraordinarily complicated physics code. The fully coupled model consists of separate submodels of the atmosphere, ocean, sea ice and land. In addition, comprehensive biogeochemistry and atmospheric chemistry submodels are under intensive current development. Each of these submodels is a large and sophisticated program in its own right. Furthermore, in the coupled model, each of the submodels, including the coupler, is a separate multiprocessor executable program. The coupler package must efficiently coordinate the communication as well as interpolate or aggregate information between these programs. This regridding function is necessary because each major subsystem (air, water or surface) is allowed to have its own independent grid.« less

Glacial inception during the late Holocene without carbon emissions from early agriculture: lessons from the stage-19 glacial inception

NASA Astrophysics Data System (ADS)

He, F.; Vavrus, S. J.; Kutzbach, J. E.; Ruddiman, W. F.; Tzedakis, P. C.

2013-12-01

Decreases in orbitally-forced summer insolation along with downward trends in greenhouse gases (GHG) have been precursors to incipient glaciation in the past. In the last several thousand years of the current interglacial, while summer insolation has decreased, there was a reversal of the downward trends in CH4 and CO2 concentration within the Holocene around 5,000 and 7,000 years ago. While the cause of this reversal remains unresolved, a leading hypothesis is Ruddiman's Early Anthropogenic Hypothesis that early agriculture, starting several thousand years ago, caused emissions of GHG large enough to reverse natural downward trends in CO2 and CH4 and kept Earth's climate anomalously warm, with the corollary that this may have prevented incipient glaciation during the late Holocene. Here we use the 1-degree, fully coupled Community Climate System Model version 4 (CCSM4) with climate forcings (orbital parameters and GHG) of a previous glacial inception to investigate whether glacial inception should have occurred prior to the industrial revolution if the concentrations of CH4 and CO2 had followed their natural downward trends throughout the Holocene. Tzedakis et al. [2012] show that for the previous eight interglacials, Stage 11 and Stage 19 are the best analogs of the Holocene because of their low eccentricities, and Stage 19 is a better analog than Stage 11 for the Holocene due to the in-phase relationship between obliquity and precession. Furthermore, their study suggests that 777 ka BP (777,000 years before present) is the timing of glacial inception for Stage 19, based on the occurrence of the earliest bipolar seesaw event associated with glacial melting. Not only do the orbital parameters at 777 ka BP resemble pre-industrial conditions, but the concentrations of CO2 at that time were essentially the same as their expected 'natural' pre-industrial values in the absence of anthropogenic greenhouse emissions. Our multi-millennial coupled CCSM4 simulations show that the 'natural' climatic forcings (GHG, orbital parameters) during pre-industrial (corresponding here to year 1850) produce essentially the same global climate as at the glacial inception of Stage 19. The simulation of 'natural' pre-industrial climate also produces similar Northern Hemisphere permanent snow cover as at the glacial inception of Stage 19, which is almost twice as large as the permanent snow in the CCSM4 control run with observed year-1850 GHG concentrations. We also found that the Atlantic Meridional Overturning Circulation slows down in the simulations of the glacial inceptions and contributes to the strong cooling and growth of permanent snow cover in Northern Hemisphere polar regions. Our study provides supports for the overdue glaciation hypothesis that early agriculture may have prevented incipient glaciation during the late Holocene. Tzedakis, P. C., J. E. T. Channell, D. A. Hodell, H. F. Kleiven, and L. C. Skinner (2012), Determining the natural length of the current interglacial, Nature Geoscience, 5(2), 138-141.

The role of mineral dust aerosols in polar amplification

NASA Astrophysics Data System (ADS)

Lambert, F.; Kug, J.; Park, R.; Jin, F.; Lee, J. H.

2010-12-01

During today’s global warming, as well as during glacial-interglacial changes, temperature increase is larger in polar areas than the global average, a phenomenon called “polar amplification”. Model studies suggest ice cap melting due to greenhouse gas induced temperature rise, and consequent decrease of albedo and enhanced oceanic and atmospheric heat transport, as the primary cause for this phenomenon in nowadays Arctic. However, the underlying causes for polar amplification on glacial-interglacial timescales are still unclear, especially in the Antarctic where sea ice coverage does not change as drastically as in the North. Recent results have shown that the temperature increase is not limited to the surface and that these changes can not be explained by snow and ice changes alone. Starting with dust flux measurements from ice cores in Greenland and Antarctica, we have estimated tropospheric concentrations using deposition velocities and vertical concentration profiles for Holocene and LGM conditions from the National Center for Atmospheric Research’s Community Climate System Model (CCSM3) and a 3-D global chemical transport model (GEOS-Chem). The radiative forcing due to mineral dust aerosols was then estimated using the GEOS-Chem model, based on the particle properties found in the ice. Preliminary results point towards positive forcing of dust because of the high albedo of the underlying ice sheets.

Experiences with "Acute" Food Insecurity among College Students

ERIC Educational Resources Information Center

Wood, J. Luke; Harris, Frank, III

2018-01-01

This study sought to understand which racial/ethnic student groups experience food insecurity and the extent to which other external insecurities and challenges are predictive of acute food insecurity. Data were derived from the Community College Success Measure (CCSM), an institutional needs assessment tool used by colleges to examine challenges…

Flexible Environments for Grand-Challenge Simulation in Climate Science

NASA Astrophysics Data System (ADS)

Pierrehumbert, R.; Tobis, M.; Lin, J.; Dieterich, C.; Caballero, R.

2004-12-01

Current climate models are monolithic codes, generally in Fortran, aimed at high-performance simulation of the modern climate. Though they adequately serve their designated purpose, they present major barriers to application in other problems. Tailoring them to paleoclimate of planetary simulations, for instance, takes months of work. Theoretical studies, where one may want to remove selected processes or break feedback loops, are similarly hindered. Further, current climate models are of little value in education, since the implementation of textbook concepts and equations in the code is obscured by technical detail. The Climate Systems Center at the University of Chicago seeks to overcome these limitations by bringing modern object-oriented design into the business of climate modeling. Our ultimate goal is to produce an end-to-end modeling environment capable of configuring anything from a simple single-column radiative-convective model to a full 3-D coupled climate model using a uniform, flexible interface. Technically, the modeling environment is implemented as a Python-based software component toolkit: key number-crunching procedures are implemented as discrete, compiled-language components 'glued' together and co-ordinated by Python, combining the high performance of compiled languages and the flexibility and extensibility of Python. We are incrementally working towards this final objective following a series of distinct, complementary lines. We will present an overview of these activities, including PyOM, a Python-based finite-difference ocean model allowing run-time selection of different Arakawa grids and physical parameterizations; CliMT, an atmospheric modeling toolkit providing a library of 'legacy' radiative, convective and dynamical modules which can be knitted into dynamical models, and PyCCSM, a version of NCAR's Community Climate System Model in which the coupler and run-control architecture are re-implemented in Python, augmenting its flexibility and adaptability.

Predicting Nitrate Transport under Future Climate Scenarios beneath the Nebraska Management Systems Evaluation Area (MSEA) site

NASA Astrophysics Data System (ADS)

Li, Y.; Akbariyeh, S.; Gomez Peña, C. A.; Bartlet-Hunt, S.

2017-12-01

Understanding the impacts of future climate change on soil hydrological processes and solute transport is crucial to develop appropriate strategies to minimize adverse impacts of agricultural activities on groundwater quality. The goal of this work is to evaluate the direct effects of climate change on the fate and transport of nitrate beneath a center-pivot irrigated corn field in Nebraska Management Systems Evaluation Area (MSEA) site. Future groundwater recharge rate and actual evapotranspiration rate were predicted based on an inverse modeling approach using climate data generated by Weather Research and Forecasting (WRF) model under the RCP 8.5 scenario, which was downscaled from global CCSM4 model to a resolution of 24 by 24 km2. A groundwater flow model was first calibrated based on historical groundwater table measurement and was then applied to predict future groundwater table in the period 2057-2060. Finally, predicted future groundwater recharge rate, actual evapotranspiration rate, and groundwater level, together with future precipitation data from WRF, were used in a three-dimensional (3D) model, which was validated based on rich historic data set collected from 1993-1996, to predict nitrate concentration in soil and groundwater from the year 2057 to 2060. Future groundwater recharge was found to be decreasing in the study area compared to average groundwater recharge data from the literature. Correspondingly, groundwater elevation was predicted to decrease (1 to 2 ft) over the five years of simulation. Predicted higher transpiration data from climate model resulted in lower infiltration of nitrate concentration in subsurface within the root zone.

Predicting Nitrate Transport under Future Climate Scenarios beneath the Nebraska Management Systems Evaluation Area (MSEA) site

NASA Astrophysics Data System (ADS)

Li, Y.; Akbariyeh, S.; Gomez Peña, C. A.; Bartlet-Hunt, S.

2016-12-01

Understanding the impacts of future climate change on soil hydrological processes and solute transport is crucial to develop appropriate strategies to minimize adverse impacts of agricultural activities on groundwater quality. The goal of this work is to evaluate the direct effects of climate change on the fate and transport of nitrate beneath a center-pivot irrigated corn field in Nebraska Management Systems Evaluation Area (MSEA) site. Future groundwater recharge rate and actual evapotranspiration rate were predicted based on an inverse modeling approach using climate data generated by Weather Research and Forecasting (WRF) model under the RCP 8.5 scenario, which was downscaled from global CCSM4 model to a resolution of 24 by 24 km2. A groundwater flow model was first calibrated based on historical groundwater table measurement and was then applied to predict future groundwater table in the period 2057-2060. Finally, predicted future groundwater recharge rate, actual evapotranspiration rate, and groundwater level, together with future precipitation data from WRF, were used in a three-dimensional (3D) model, which was validated based on rich historic data set collected from 1993-1996, to predict nitrate concentration in soil and groundwater from the year 2057 to 2060. Future groundwater recharge was found to be decreasing in the study area compared to average groundwater recharge data from the literature. Correspondingly, groundwater elevation was predicted to decrease (1 to 2 ft) over the five years of simulation. Predicted higher transpiration data from climate model resulted in lower infiltration of nitrate concentration in subsurface within the root zone.

Variability and predictability of decadal mean temperature and precipitation over China in the CCSM4 last millennium simulation

NASA Astrophysics Data System (ADS)

Ying, Kairan; Frederiksen, Carsten S.; Zheng, Xiaogu; Lou, Jiale; Zhao, Tianbao

2018-02-01

The modes of variability that arise from the slow-decadal (potentially predictable) and intra-decadal (unpredictable) components of decadal mean temperature and precipitation over China are examined, in a 1000 year (850-1850 AD) experiment using the CCSM4 model. Solar variations, volcanic aerosols, orbital forcing, land use, and greenhouse gas concentrations provide the main forcing and boundary conditions. The analysis is done using a decadal variance decomposition method that identifies sources of potential decadal predictability and uncertainty. The average potential decadal predictabilities (ratio of slow-to-total decadal variance) are 0.62 and 0.37 for the temperature and rainfall over China, respectively, indicating that the (multi-)decadal variations of temperature are dominated by slow-decadal variability, while precipitation is dominated by unpredictable decadal noise. Possible sources of decadal predictability for the two leading predictable modes of temperature are the external radiative forcing, and the combined effects of slow-decadal variability of the Arctic oscillation (AO) and the Pacific decadal oscillation (PDO), respectively. Combined AO and PDO slow-decadal variability is associated also with the leading predictable mode of precipitation. External radiative forcing as well as the slow-decadal variability of PDO are associated with the second predictable rainfall mode; the slow-decadal variability of Atlantic multi-decadal oscillation (AMO) is associated with the third predictable precipitation mode. The dominant unpredictable decadal modes are associated with intra-decadal/inter-annual phenomena. In particular, the El Niño-Southern Oscillation and the intra-decadal variability of the AMO, PDO and AO are the most important sources of prediction uncertainty.

The Madden-Julian Oscillation in the NCAR Community Earth System Model Coupled Data Assimilation System

NASA Astrophysics Data System (ADS)

Chatterjee, A.; Anderson, J. L.; Moncrieff, M.; Collins, N.; Danabasoglu, G.; Hoar, T.; Karspeck, A. R.; Neale, R. B.; Raeder, K.; Tribbia, J. J.

2014-12-01

We present a quantitative evaluation of the simulated MJO in analyses produced with a coupled data assimilation (CDA) framework developed at the National Center for Atmosphere Research. This system is based on the Community Earth System Model (CESM; previously known as the Community Climate System Model -CCSM) interfaced to a community facility for ensemble data assimilation (Data Assimilation Research Testbed - DART). The system (multi-component CDA) assimilates data into each of the respective ocean/atmosphere/land model components during the assimilation step followed by an exchange of information between the model components during the forecast step. Note that this is an advancement over many existing prototypes of coupled data assimilation systems, which typically assimilate observations only in one of the model components (i.e., single-component CDA). The more realistic treatment of air-sea interactions and improvements to the model mean state in the multi-component CDA recover many aspects of MJO representation, from its space-time structure and propagation (see Figure 1) to the governing relationships between precipitation and sea surface temperature on intra-seasonal scales. Standard qualitative and process-based diagnostics identified by the MJO Task Force (currently under the auspices of the Working Group on Numerical Experimentation) have been used to detect the MJO signals across a suite of coupled model experiments involving both multi-component and single-component DA experiments as well as a free run of the coupled CESM model (i.e., CMIP5 style without data assimilation). Short predictability experiments during the boreal winter are used to demonstrate that the decay rates of the MJO convective anomalies are slower in the multi-component CDA system, which allows it to retain the MJO dynamics for a longer period. We anticipate that the knowledge gained through this study will enhance our understanding of the MJO feedback mechanisms across the air-sea interface, especially regarding ocean impacts on the MJO as well as highlight the capability of coupled data assimilation systems for related tropical intraseasonal variability predictions.

Predicting coral bleaching hotspots: the role of regional variability in thermal stress and potential adaptation rates

NASA Astrophysics Data System (ADS)

Teneva, Lida; Karnauskas, Mandy; Logan, Cheryl A.; Bianucci, Laura; Currie, Jock C.; Kleypas, Joan A.

2012-03-01

Sea surface temperature fields (1870-2100) forced by CO2-induced climate change under the IPCC SRES A1B CO2 scenario, from three World Climate Research Programme Coupled Model Intercomparison Project Phase 3 (WCRP CMIP3) models (CCSM3, CSIRO MK 3.5, and GFDL CM 2.1), were used to examine how coral sensitivity to thermal stress and rates of adaption affect global projections of coral-reef bleaching. The focus of this study was two-fold, to: (1) assess how the impact of Degree-Heating-Month (DHM) thermal stress threshold choice affects potential bleaching predictions and (2) examine the effect of hypothetical adaptation rates of corals to rising temperature. DHM values were estimated using a conventional threshold of 1°C and a variability-based threshold of 2σ above the climatological maximum Coral adaptation rates were simulated as a function of historical 100-year exposure to maximum annual SSTs with a dynamic rather than static climatological maximum based on the previous 100 years, for a given reef cell. Within CCSM3 simulations, the 1°C threshold predicted later onset of mild bleaching every 5 years for the fraction of reef grid cells where 1°C > 2σ of the climatology time series of annual SST maxima (1961-1990). Alternatively, DHM values using both thresholds, with CSIRO MK 3.5 and GFDL CM 2.1 SSTs, did not produce drastically different onset timing for bleaching every 5 years. Across models, DHMs based on 1°C thermal stress threshold show the most threatened reefs by 2100 could be in the Central and Western Equatorial Pacific, whereas use of the variability-based threshold for DHMs yields the Coral Triangle and parts of Micronesia and Melanesia as bleaching hotspots. Simulations that allow corals to adapt to increases in maximum SST drastically reduce the rates of bleaching. These findings highlight the importance of considering the thermal stress threshold in DHM estimates as well as potential adaptation models in future coral bleaching projections.

Evaluation of the North American Multi-Model Ensemble System for Monthly and Seasonal Prediction

NASA Astrophysics Data System (ADS)

Zhang, Q.

2014-12-01

Since August 2011, the real time seasonal forecasts of the U.S. National Multi-Model Ensemble (NMME) have been made on 8th of each month by NCEP Climate Prediction Center (CPC). The participating models were NCEP/CFSv1&2, GFDL/CM2.2, NCAR/U.Miami/COLA/CCSM3, NASA/GEOS5, IRI/ ECHAM-a & ECHAM-f in the first year of the real time NMME forecast. Two Canadian coupled models CMC/CanCM3 and CM4 joined in and CFSv1 and IRI's models dropped out in the second year. The NMME team at CPC collects monthly means of three variables, precipitation, temperature at 2m and sea surface temperature from each modeling center on a 1x1 global grid, removes systematic errors, makes the grand ensemble mean in equal weight for each model mean and probability forecast with equal weight for each member of each model. This provides the NMME forecast locked in schedule for the CPC operational seasonal and monthly outlook. The basic verification metrics of seasonal and monthly prediction of NMME are calculated as an evaluation of skill, including both deterministic and probabilistic forecasts for the 3-year real time (August, 2011- July 2014) period and the 30-year retrospective forecast (1982-2011) of the individual models as well as the NMME ensemble. The motivation of this study is to provide skill benchmarks for future improvements of the NMME seasonal and monthly prediction system. We also want to establish whether the real time and hindcast periods (used for bias correction in real time) are consistent. The experimental phase I of the project already supplies routine guidance to users of the NMME forecasts.

Geometry Report; Cambridge Conference on School Mathematics Feasibility Study No. 39.

ERIC Educational Resources Information Center

Stolzenberg, Gabriel

These materials were written with the aim of reflecting the thinking of the Cambridge Conference on School Mathematics (CCSM) regarding the goals and objectives for school mathematics. This report deals with some seventh grade mathematical concepts taught at Cambridge Friends' School. The discovery approach was utilized by the teacher in order to…

Final Report of Cambridge Conference on School Mathematics, January 1962 - August 1970.

ERIC Educational Resources Information Center

Cambridge Conference on School Mathematics, Newton, MA.

The Cambridge Conference on School Mathematics (CCSM) was an association of prominent mathematicians who had a concern for mathematics education at school level, from kindergarten through grade twelve. These mathematicians organized three main conferences in three areas of mathematics education, and have carried on activities related to the…

Feedback attribution of the land-sea warming contrast in a global warming simulation of the NCAR CCSM4

DOE PAGES

Sejas, Sergio A.; Albert, Oriene S.; Cai, Ming; ...

2014-12-02

One of the salient features in both observations and climate simulations is a stronger land warming than sea. This paper provides a quantitative understanding of the main processes that contribute to the land-sea warming asymmetry in a global warming simulation of the NCAR CCSM4. The CO 2 forcing alone warms the surface nearly the same for both land and sea, suggesting that feedbacks are responsible for the warming contrast. Our analysis on one hand confirms that the principal contributor to the above-unity land-to-sea warming ratio is the evaporation feedback; on the other hand the results indicate that the sensible heatmore » flux feedback has the largest land-sea warming difference that favors a greater ocean than land warming. Furthermore, the results uniquely highlight the importance of other feedbacks in establishing the above-unity land-to-sea warming ratio. Particularly, the SW cloud feedback and the ocean heat storage in the transient response are key contributors to the greater warming over land than sea.« less

Feedback attribution of the land-sea warming contrast in a global warming simulation of the NCAR CCSM4

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

Sejas, Sergio A.; Albert, Oriene S.; Cai, Ming

One of the salient features in both observations and climate simulations is a stronger land warming than sea. This paper provides a quantitative understanding of the main processes that contribute to the land-sea warming asymmetry in a global warming simulation of the NCAR CCSM4. The CO 2 forcing alone warms the surface nearly the same for both land and sea, suggesting that feedbacks are responsible for the warming contrast. Our analysis on one hand confirms that the principal contributor to the above-unity land-to-sea warming ratio is the evaporation feedback; on the other hand the results indicate that the sensible heatmore » flux feedback has the largest land-sea warming difference that favors a greater ocean than land warming. Furthermore, the results uniquely highlight the importance of other feedbacks in establishing the above-unity land-to-sea warming ratio. Particularly, the SW cloud feedback and the ocean heat storage in the transient response are key contributors to the greater warming over land than sea.« less

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Mineral dust transport and deposition to Antarctica: a climate model perspective

NASA Astrophysics Data System (ADS)

Albani, S.; Mahowald, N. M.; Maggi, V.; Delmonte, B.

2009-04-01

Windblown mineral dust is a useful proxy for paleoclimates. Its life cycle is determined by climate conditions in the source areas, and following the hydrological cycle, and the intensity and dynamics of the atmospheric circulation. In addition aeolian dust itself is an active component of the climate system, influencing the radiative balance of the atmosphere through its interaction with incoming solar radiation and outgoing planetary radiation. The mineral aerosols also have indirect effects on climate, and are linked to interactions with cloud microphysics and atmospheric chemistry as well as to dust's role of carrier of iron and other elements that constitute limitating nutrients for phytoplancton to remote ocean areas. We use climate model (CCSM) simulations that include a scheme for dust mobilization, transport and deposition in order to describe the evolution of dust deposition in some Antarctic ice cores sites where mineral dust records are available. Our focus is to determine the source apportionment for dust deposited to Antarctica under current and Last Glacial Maximum climate conditions, as well as to give an insight in the spatial features of transport patterns. The understanding of spatial and temporal representativeness of an ice core record is crucial to determine its value as a proxy of past climates and a necessary step in order to produce a global picture of how the dust component of the climate system has changed through time.

[Cambridge Conference on School Mathematics Feasibility Studies 9-13.

ERIC Educational Resources Information Center

Cambridge Conference on School Mathematics, Newton, MA.

These materials are a part of a series of studies sponsored by the Cambridge Conference on School Mathematics which reflects the ideas of CCSM regarding the goals and objectives for school mathematics K-12. Feasibility Studies 9-13 contain a wide range of topics. The following are the titles and brief descriptions of these studies. Number…

Symmetry Motion Classes; Cambridge Conference on School Mathematics Feasibility Study No. 40.

ERIC Educational Resources Information Center

McLane, Lyn

These materials were written with the aim of reflecting the thinking of The Cambridge Conference on School Mathematics (CCSM) regarding the goals and objectives for school mathematics. This document details the planning and response for each of ten lessons involving symmetry motions. The problems focused on (1) combining motions in a given order,…

Informal Geometry for Young Children; Cambridge Conference on School Mathematics; Feasibility Study No. 34b.

ERIC Educational Resources Information Center

Walter, Marion

These materials were written with the aim of reflecting the thinking of The Cambridge Conference on School Mathematics (CCSM) regarding the goals and objectives for school mathematics. These materials are intended to provide children with a variety of informal activities in intuitive geometry in the elementary school. Opportunities are provided…

Inequalities and Real Numbers as a Basis for School Mathematics, Cambridge Conference on School Mathematics Feasibility Study No. 38.

ERIC Educational Resources Information Center

Lomon, Earle

These materials were developed as a practical response to some of the recommendations of the 1963 Cambridge Conference on School Mathematics (CCSM). Experimental sessions are described in detail in this report. In the Estabrook Elementary School, Lexington, Massachusetts, first grade children (1964-65 Academic Year) concentrated on material…

Probability Lessons at Hancock School, Lexington; Cambridge Conference on School Mathematics Feasibility Study No. 41.

ERIC Educational Resources Information Center

McLane, Lyn

These materials were written with the aim of reflecting the thinking of Cambridge Conference on School Mathematics (CCSM) regarding the goals and objectives for school mathematics. Presented are plans for teaching 23 probability lessons in the elementary grades at Hancock School, Lexington, Massachusetts. The discovery approach was utilized by the…

Measuring Five Preconditions of Success for African American Male Students in Community Colleges

ERIC Educational Resources Information Center

McManus, Kimberly Ozella

2017-01-01

The purpose of this study was to measure and compare five preconditions for success of African American male community college students at community colleges by determining if there is a relationship between a) GPA and credits earned, utilizing Wood and Harris' (2012; 2016) Community College Survey of Men (CCSM, 2014) and Community College Success…

An Experimental Text in Transformational Geometry, Student Text; Cambridge Conference on School Mathematics Feasibility Study No. 43a.

ERIC Educational Resources Information Center

Cambridge Conference on School Mathematics, Newton, MA.

This is part of a student text which was written with the aim of reflecting the thinking of The Cambridge Conference on School Mathematics (CCSM) regarding the goals and objectives for mathematics. The instructional materials were developed for teaching geometry in the secondary schools. This document is chapter six and titled Motions and…

Inequality Lessons at Adams School, Lexington; Cambridge Conference on School Mathematics Feasibility Study No. 42.

ERIC Educational Resources Information Center

Fitzgerald, B.

These materials were written with the aim of reflecting the thinking of The Cambridge Conference on School Mathematics (CCSM) regarding the goals and objectives for school mathematics. Presented are plans for teaching 15 inequality lessons for above average first grade students. The discovery approach is utilized by the teacher in order to involve…

78 FR 72926 - Bald and Golden Eagles; Migratory Birds; Phase I Development of the Chokecherry-Sierra Madre Wind...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-04

... which this notice primarily pertains, would consist of approximately 500 wind turbines, a haul road, a... development for CCSM Phase II, which will consist of about 500 additional wind turbines (roughly 1500 MW), at...-FXMB12310600000] Bald and Golden Eagles; Migratory Birds; Phase I Development of the Chokecherry-Sierra Madre Wind...

Application of Inverse Modeling to Estimate Groundwater Recharge under Future Climate Scenario

NASA Astrophysics Data System (ADS)

Akbariyeh, S.; Wang, T.; Bartelt-Hunt, S.; Li, Y.

2016-12-01

Climate variability and change will impose profound influences on groundwater systems. Accurate estimation of groundwater recharge is extremely important for predicting the flow and contaminant transport in the subsurface, which, however, remains as one of the most challenging tasks in the field of hydrology. Using an inverse modeling technique and HYDRUS 1D software, we predicted the spatial distribution of groundwater recharge across the Upper Platte basin in Nebraska, USA, based on 5-year projected future climate and soil moisture data (2057-2060). The climate data was obtained from Weather Research and Forecasting (WRF) model under RCP 8.5 scenario, which was downscaled from global CCSM4 model to a resolution of 24 by 24 km2. Precipitation, potential evapotranspiration, and soil moisture data were extracted from 76 grids located within the Upper Platte basin to perform the inverse modeling. Hargreaves equation was used to calculate the potential evapotranspiration according to latitude, maximum and minimum temperature, and leaf area index (LAI) data at each node. Van-Genuchten parameters were optimized using the inverse algorithm to minimize the error between input and modeled soil moisture data. The groundwater recharge was calculated as the amount of water that passed the lower boundary of the best fitted model. The year of 2057 was used as a spin-up period to minimize the impact of initial conditions. The model was calibrated for years 2058 to 2059 and validation was performed for 2060. This work demonstrates an efficient approach to estimating groundwater recharge based on climate modeling results, which will aid groundwater resources management under future climate scenarios.

A fresh look at the Last Glacial Maximum using Paleoclimate Data Assimilation

NASA Astrophysics Data System (ADS)

Malevich, S. B.; Tierney, J. E.; Hakim, G. J.; Tardif, R.

2017-12-01

Quantifying climate conditions during the Last Glacial Maximum ( 21ka) can help us to understand climate responses to forcing and climate states that are poorly represented in the instrumental record. Paleoclimate proxies may be used to estimate these climate conditions, but proxies are sparsely distributed and possess uncertainties from environmental and biogeochemical processes. Alternatively, climate model simulations provide a full-field view, but may predict unrealistic climate states or states not faithful to proxy records. Here, we use data assimilation - combining climate proxy records with a theoretical understanding from climate models - to produce field reconstructions of the LGM that leverage the information from both data and models. To date, data assimilation has mainly been used to produce reconstructions of climate fields through the last millennium. We expand this approach in order to produce a climate fields for the Last Glacial Maximum using an ensemble Kalman filter assimilation. Ensemble samples were formed from output from multiple models including CCSM3, CESM2.1, and HadCM3. These model simulations are combined with marine sediment proxies for upper ocean temperature (TEX86, UK'37, Mg/Ca and δ18O of foraminifera), utilizing forward models based on a newly developed suite of Bayesian proxy system models. We also incorporate age model and radiocarbon reservoir uncertainty into our reconstructions using Bayesian age modeling software. The resulting fields show familiar patterns based on comparison with previous proxy-based reconstructions, but additionally reveal novel patterns of large-scale shifts in ocean-atmosphere dynamics, as the surface temperature data inform upon atmospheric circulation and precipitation patterns.

Using Seasonal Forecasting Data for Vessel Routing

NASA Astrophysics Data System (ADS)

Bell, Ray; Kirtman, Ben

2017-04-01

We present an assessment of seasonal forecasting of surface wind speed, significant wave height and ocean surface current speed in the North Pacific for potential use of vessel routing from Singapore to San Diego. WaveWatchIII is forced with surface winds and ocean surface currents from the Community Climate System Model 4 (CCSM4) retrospective forecasts for the period of 1982-2015. Several lead time forecasts are used from zero months to six months resulting in 2,720 model years, ensuring the findings from this study are robust. July surface wind speed and significant wave height can be skillfully forecast with a one month lead time, with the western North Pacific being the most predictable region. Beyond May initial conditions (lead time of two months) the El Niño Southern Oscillation (ENSO) Spring predictability barrier limits skill of significant wave height but there is skill for surface wind speed with January initial conditions (lead time of six months). In a separate study of vessel routing between Norfolk, Virginia and Gibraltar we demonstrate the benefit of a multimodel approach using the North American Multimodel Ensemble (NMME). In collaboration with Charles River Analytics an all-encompassing forecast is presented by using machine learning on the various ensembles which can be using used for industry applications.

Robust effects of cloud superparameterization on simulated daily rainfall intensity statistics across multiple versions of the Community Earth System Model

DOE PAGES

Kooperman, Gabriel J.; Pritchard, Michael S.; Burt, Melissa A.; ...

2016-02-01

This study evaluates several important statistics of daily rainfall based on frequency and amount distributions as simulated by a global climate model whose precipitation does not depend on convective parameterization—Super-Parameterized Community Atmosphere Model (SPCAM). Three superparameterized and conventional versions of CAM, coupled within the Community Earth System Model (CESM1 and CCSM4), are compared against two modern rainfall products (GPCP 1DD and TRMM 3B42) to discriminate robust effects of superparameterization that emerge across multiple versions. The geographic pattern of annual-mean rainfall is mostly insensitive to superparameterization, with only slight improvements in the double-ITCZ bias. However, unfolding intensity distributions reveal several improvementsmore » in the character of rainfall simulated by SPCAM. The rainfall rate that delivers the most accumulated rain (i.e., amount mode) is systematically too weak in all versions of CAM relative to TRMM 3B42 and does not improve with horizontal resolution. It is improved by superparameterization though, with higher modes in regions of tropical wave, Madden-Julian Oscillation, and monsoon activity. Superparameterization produces better representations of extreme rates compared to TRMM 3B42, without sensitivity to horizontal resolution seen in CAM. SPCAM produces more dry days over land and fewer over the ocean. Updates to CAM’s low cloud parameterizations have narrowed the frequency peak of light rain, converging toward SPCAM. Poleward of 50°, where more rainfall is produced by resolved-scale processes in CAM, few differences discriminate the rainfall properties of the two models. Lastly, these results are discussed in light of their implication for future rainfall changes in response to climate forcing.« less

Multi-centennial upper-ocean heat content reconstruction using online data assimilation

NASA Astrophysics Data System (ADS)

Perkins, W. A.; Hakim, G. J.

2017-12-01

The Last Millennium Reanalysis (LMR) provides an advanced paleoclimate ensemble data assimilation framework for multi-variate climate field reconstructions over the Common Era. Although reconstructions in this framework with full Earth system models remain prohibitively expensive, recent work has shown improved ensemble reconstruction validation using computationally inexpensive linear inverse models (LIMs). Here we leverage these techniques in pursuit of a new multi-centennial field reconstruction of upper-ocean heat content (OHC), synthesizing model dynamics with observational constraints from proxy records. OHC is an important indicator of internal climate variability and responds to planetary energy imbalances. Therefore, a consistent extension of the OHC record in time will help inform aspects of low-frequency climate variability. We use the Community Climate System Model version 4 (CCSM4) and Max Planck Institute (MPI) last millennium simulations to derive the LIMs, and the PAGES2K v.2.0 proxy database to perform annually resolved reconstructions of upper-OHC, surface air temperature, and wind stress over the last 500 years. Annual OHC reconstructions and uncertainties for both the global mean and regional basins are compared against observational and reanalysis data. We then investigate differences in dynamical behavior at decadal and longer time scales between the reconstruction and simulations in the last-millennium Coupled Model Intercomparison Project version 5 (CMIP5). Preliminary investigation of 1-year forecast skill for an OHC-only LIM shows largely positive spatial grid point local anomaly correlations (LAC) with a global average LAC of 0.37. Compared to 1-year OHC persistence forecast LAC (global average LAC of 0.30), the LIM outperforms the persistence forecasts in the tropical Indo-Pacific region, the equatorial Atlantic, and in certain regions near the Antarctic Circumpolar Current. In other regions, the forecast correlations are less than the persistence case but still positive overall.

Glaciological reconstruction of Holocene ice margins in northwestern Greenland

NASA Astrophysics Data System (ADS)

Birkel, S. D.; Osterberg, E. C.; Kelly, M. A.; Axford, Y.

2014-12-01

The past few decades of climate warming have brought overall margin retreat to the Greenland Ice Sheet. In order to place recent and projected changes in context, we are undertaking a collaborative field-modeling study that aims to reconstruct the Holocene history of ice-margin fluctuation near Thule (~76.5°N, 68.7°W), and also along the North Ice Cap (NIC) in the Nunatarssuaq region (~76.7°N, 67.4°W). Fieldwork reported by Kelly et al. (2013) reveals that ice in the study areas was less extensive than at present ca. 4700 (GIS) and ca. 880 (NIC) cal. years BP, presumably in response to a warmer climate. We are now exploring Holocene ice-climate coupling using the University of Maine Ice Sheet Model (UMISM). Our approach is to first test what imposed climate anomalies can afford steady state ice margins in accord with field data. A second test encompasses transient simulation of the Holocene, with climate boundary conditions supplied by existing paleo runs of the Community Climate System Model version 4 (CCSM4), and a climate forcing signal derived from Greenland ice cores. In both cases, the full ice sheet is simulated at 10 km resolution with nested domains at 0.5 km for the study areas. UMISM experiments are underway, and results will be reported at the meeting.

Modeling Climate and Societal Resilience in the Mediterranean During the Last Millennium

NASA Astrophysics Data System (ADS)

Wagner, S.; Xoplaki, E.; Luterbacher, J.; Zorita, E.; Fleitmann, D.; Preiser-Kapeller, J.; Toreti, A., , Dr; Sargent, A. M.; Bozkurt, D.; White, S.; Haldon, J. F.; Akçer-Ön, S.; Izdebski, A.

2017-12-01

Past civilisations were influenced by complex external and internal forces, including changes in the environment, climate, politics and economy. A geographical hotspot of the interplay between those agents is the Mediterranean, a cradle of cultural and scientific development. We analyse a novel compilation of high-quality hydroclimate proxy records and spatial reconstructions from the Mediterranean and compare them with two Earth System Model simulations (CCSM4, MPI-ESM-P) for three historical time intervals - the Crusaders, 1095-1290 CE; the Mamluk regime in Transjordan, 1260-1516 CE; and the Ottoman crisis and Celâlî Rebellion, 1580-1610 CE - when environmental and climatic stress tested the resilience of complex societies. ESMs provide important information on the dynamical mechanisms and underlying processes that led to anomalous hydroclimatic conditions of the past. We find that the multidecadal precipitation and drought variations in the Central and Eastern Mediterranean during the three periods cannot be explained by external forcings (solar variations, tropical volcanism); rather they were driven by internal climate dynamics. The integrated analysis of palaeoclimate proxies, climate reconstructions and model simulations sheds light on our understanding of past climate change and its societal impact. Finally, our research emphasises the need to further study the societal dimension of environmental and climate change in the past, in order to properly understand the role that climate has played in human history.

Provisional Approaches to Goals for School Mathematics; Cambridge Conference on School Mathematics Feasibility Study No. 37.

ERIC Educational Resources Information Center

Cambridge Conference on School Mathematics, Newton, MA.

These materials were written with the aim of reflecting the thinking of Cambridge Conference on School Mathematics (CCSM) regarding the goals and objectives for school mathematics K-6. In view of the experiences of other curriculum groups and of the general discussions since 1963, the present report initiates the next step in evolving the "Goals".…

An integrated crop model and GIS decision support system for assisting agronomic decision making under climate change.

PubMed

Kadiyala, M D M; Nedumaran, S; Singh, Piara; S, Chukka; Irshad, Mohammad A; Bantilan, M C S

2015-07-15

The semi-arid tropical (SAT) regions of India are suffering from low productivity which may be further aggravated by anticipated climate change. The present study analyzes the spatial variability of climate change impacts on groundnut yields in the Anantapur district of India and examines the relative contribution of adaptation strategies. For this purpose, a web based decision support tool that integrates crop simulation model and Geographical Information System (GIS) was developed to assist agronomic decision making and this tool can be scalable to any location and crop. The climate change projections of five global climate models (GCMs) relative to the 1980-2010 baseline for Anantapur district indicates an increase in rainfall activity to the tune of 10.6 to 25% during Mid-century period (2040-69) with RCP 8.5. The GCMs also predict warming exceeding 1.4 to 2.4°C by 2069 in the study region. The spatial crop responses to the projected climate indicate a decrease in groundnut yields with four GCMs (MPI-ESM-MR, MIROC5, CCSM4 and HadGEM2-ES) and a contrasting 6.3% increase with the GCM, GFDL-ESM2M. The simulation studies using CROPGRO-Peanut model reveals that groundnut yields can be increased on average by 1.0%, 5.0%, 14.4%, and 20.2%, by adopting adaptation options of heat tolerance, drought tolerant cultivars, supplemental irrigation and a combination of drought tolerance cultivar and supplemental irrigation respectively. The spatial patterns of relative benefits of adaptation options were geographically different and the greatest benefits can be achieved by adopting new cultivars having drought tolerance and with the application of one supplemental irrigation at 60days after sowing. Copyright © 2015 Elsevier B.V. All rights reserved.

Generation of High Resolution Land Surface Parameters in the Community Land Model

NASA Astrophysics Data System (ADS)

Ke, Y.; Coleman, A. M.; Wigmosta, M. S.; Leung, L.; Huang, M.; Li, H.

2010-12-01

The Community Land Model (CLM) is the land surface model used for the Community Atmosphere Model (CAM) and the Community Climate System Model (CCSM). It examines the physical, chemical, and biological processes across a variety of spatial and temporal scales. Currently, efforts are being made to improve the spatial resolution of the CLM, in part, to represent finer scale hydrologic characteristics. Current land surface parameters of CLM4.0, in particular plant functional types (PFT) and leaf area index (LAI), are generated from MODIS and calculated at a 0.05 degree resolution. These MODIS-derived land surface parameters have also been aggregated to coarser resolutions (e.g., 0.5, 1.0 degrees). To evaluate the response of CLM across various spatial scales, higher spatial resolution land surface parameters need to be generated. In this study we examine the use of Landsat TM/ETM+ imagery and data fusion techniques for generating land surface parameters at a 1km resolution within the Pacific Northwest United States. . Land cover types and PFTs are classified based on Landsat multi-season spectral information, DEM, National Land Cover Database (NLCD) and the USDA-NASS Crop Data Layer (CDL). For each PFT, relationships between MOD15A2 high quality LAI values, Landsat-based vegetation indices, climate variables, terrain, and laser-altimeter derived vegetation height are used to generate monthly LAI values at a 30m resolution. The high-resolution PFT and LAI data are aggregated to create a 1km model grid resolution. An evaluation and comparison of CLM land surface response at both fine and moderate scale is presented.

Climate change likely to favor shift toward warmer climate states of the Pliocene and Eocene

NASA Astrophysics Data System (ADS)

Burke, K. D.; Williams, J. W.

2017-12-01

As the world warms due to rising greenhouse gas concentrations, the climate system is moving toward a state without precedent in the historical record. Various past climate states have been proposed as potential analogues or model systems for the coming decades, including the early to middle Holocene, the last interglacial, the middle Pliocene, and the early Eocene. However, until now, such comparisons have been qualitative. To compare these time periods to the projected climate states for the 21st and 22nd centuries, we conduct a climate similarity analysis using the standardized Euclidean distance metric (SED) and seasonal means of surface air temperature and precipitation. We make this future-to-past comparison using 30-year mean climatologies, for every decade between 2020 and 2280 AD (27 total comparisons). The list of past earth system states includes the historical period (1940-1970 AD), a pre-industrial control (ca. 1850), the middle Holocene (ca. 6 ka), the last glacial maximum (ca. 21 ka), the last interglacial (ca. 125 ka), the middle Pliocene (ca. 3 Ma), and the early Eocene (ca. 50-55 Ma). To reduce uncertainties resulting from choice of earth system model, analyses are based on simulations from three earth system models (HadCM, CCSM, NASA/GISS Model-E), using in part experiments from PMIP2, PMIP3/CMIP5, EoMIP, and PlioMIP. Results are presented for two representative concentration pathways (RCP's 4.5, 8.5). By 2050 AD, the most common past climate analogue is sourced from the Pliocene for RCP 8.5, while by 2190 AD, the Eocene becomes the source of the most common past climate analogue. For RCP 4.5, in which radiative forcings stabilize this century, the Pliocene becomes the most important past climate analogue by 2100 AD. Low latitude climates are the first to most closely resemble these past earth warm periods. The mid-latitudes then follow this pattern by the end of the 22nd century. Although no past state of the earth system is a perfect analogue for the Anthropocene, these analyses clarify the similarities between the expected climates of the future and the geological climates of the past.

Application of Seasonal CRM Integrations to Develop Statistics and Improved GCM Parameterization of Subgrid Cloud-Radiation Interactions

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

Xiaoqing Wu; Xin-Zhong Liang; Sunwook Park

2007-01-23

The works supported by this ARM project lay the solid foundation for improving the parameterization of subgrid cloud-radiation interactions in the NCAR CCSM and the climate simulations. We have made a significant use of CRM simulations and concurrent ARM observations to produce long-term, consistent cloud and radiative property datasets at the cloud scale (Wu et al. 2006, 2007). With these datasets, we have investigated the mesoscale enhancement of cloud systems on surface heat fluxes (Wu and Guimond 2006), quantified the effects of cloud horizontal inhomogeneity and vertical overlap on the domain-averaged radiative fluxes (Wu and Liang 2005), and subsequently validatedmore » and improved the physically-based mosaic treatment of subgrid cloud-radiation interactions (Liang and Wu 2005). We have implemented the mosaic treatment into the CCM3. The 5-year (1979-1983) AMIP-type simulation showed significant impacts of subgrid cloud-radiation interaction on the climate simulations (Wu and Liang 2005). We have actively participated in CRM intercomparisons that foster the identification and physical understanding of common errors in cloud-scale modeling (Xie et al. 2005; Xu et al. 2005, Grabowski et al. 2005).« less

Influence of Decadal Variability of Global Oceans on South Asian Monsoon and ENSO-Monsoon Relation

NASA Astrophysics Data System (ADS)

Krishnamurthy, Lakshmi

This study has investigated the influence of the decadal variability associated with global oceans on South Asian monsoon and El Nino-Southern Oscillation (ENSO)-monsoon relation. The results are based on observational analysis using long records of monsoon rainfall and circulation and coupled general circulation model experiments using the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM) version 4 model. The multi-channel singular spectrum analysis (MSSA) of the observed rainfall over India yields three decadal modes. The first mode (52 year period) is associated with the Atlantic Multidecadal Oscillation (AMO), the second one (21 year) with the Pacific Decadal Oscillation (PDO) and the third mode (13 year) with the Atlantic tripole. The existence of these decadal modes in the monsoon was also found in the control simulation of NCAR CCSM4. The regionally de-coupled model experiments performed to isolate the influence of North Pacific and North Atlantic also substantiate the above results. The relation between the decadal modes in the monsoon rainfall with the known decadal modes in global SST is examined. The PDO has significant negative correlation with the Indian Monsoon Rainfall (IMR). The mechanism for PDO-monsoon relation is hypothesized through the seasonal footprinting mechanism and further through Walker and Hadley circulations. The model results also confirm the negative correlation between PDO and IMR and the mechanism through which PDO influences monsoon. Both observational and model analysis show that droughts (floods) are more likely over India than floods (droughts) when ENSO and PDO are in their warm (cold) phase. This study emphasizes the importance of carefully distinguishing the different decadal modes in the SST in the North Atlantic Ocean as they have different impacts on the monsoon. The AMO exhibits significant positive correlation with the IMR while the Atlantic tripole has significant negative correlation with the IMR. The AMO influences the Indian monsoon through atmospheric winds related to high summer North Atlantic Oscillation (NAO) mode leading to enhanced moisture flow over the Indian subcontinent. The Atlantic tripole mode affects the rainfall over India by enhancing the moisture flow through the equatorial westerly winds associated with the NAO. The model also simulates the positive and negative relation of AMO and tripole, respectively, with the monsoon rainfall. The model also indicates the enhanced moisture flow over India related to the positive phase of AMO through the equatorial westerly flow. But, for the tripole mode, the model indicates flow of moisture through the Bay of Bengal in contrast to observations where it is through the Arabian Sea. The reason for the absence of decadal mode in IMR inherent to the Indian Ocean is also explored. The SSA on dipole mode index (DMI) index reveals three modes. The first two modes are related to the biennial and canonical ENSO at interannual timescale while the third mode varies on decadal timescale and is related to PDO. The wind regression pattern associated with the PDO-IOD mode shows northeasterly winds enhancing the southeasterly flow from the southeastern Indian Ocean related to the Indian Ocean dipole (IOD) mode. The model also shows the influence of canonical ENSO and PDO influence on IOD, although the variance explained by PDO mode is lower in the model relative to observations.

Predictive Skill of Meteorological Drought Based on Multi-Model Ensemble Forecasts: A Real-Time Assessment

NASA Astrophysics Data System (ADS)

Chen, L. C.; Mo, K. C.; Zhang, Q.; Huang, J.

2014-12-01

Drought prediction from monthly to seasonal time scales is of critical importance to disaster mitigation, agricultural planning, and multi-purpose reservoir management. Starting in December 2012, NOAA Climate Prediction Center (CPC) has been providing operational Standardized Precipitation Index (SPI) Outlooks using the North American Multi-Model Ensemble (NMME) forecasts, to support CPC's monthly drought outlooks and briefing activities. The current NMME system consists of six model forecasts from U.S. and Canada modeling centers, including the CFSv2, CM2.1, GEOS-5, CCSM3.0, CanCM3, and CanCM4 models. In this study, we conduct an assessment of the predictive skill of meteorological drought using real-time NMME forecasts for the period from May 2012 to May 2014. The ensemble SPI forecasts are the equally weighted mean of the six model forecasts. Two performance measures, the anomaly correlation coefficient and root-mean-square errors against the observations, are used to evaluate forecast skill.Similar to the assessment based on NMME retrospective forecasts, predictive skill of monthly-mean precipitation (P) forecasts is generally low after the second month and errors vary among models. Although P forecast skill is not large, SPI predictive skill is high and the differences among models are small. The skill mainly comes from the P observations appended to the model forecasts. This factor also contributes to the similarity of SPI prediction among the six models. Still, NMME SPI ensemble forecasts have higher skill than those based on individual models or persistence, and the 6-month SPI forecasts are skillful out to four months. The three major drought events occurred during the 2012-2014 period, the 2012 Central Great Plains drought, the 2013 Upper Midwest flash drought, and 2013-2014 California drought, are used as examples to illustrate the system's strength and limitations. For precipitation-driven drought events, such as the 2012 Central Great Plains drought, NMME SPI forecasts perform well in predicting drought severity and spatial patterns. For fast-developing drought events, such as the 2013 Upper Midwest flash drought, the system failed to capture the onset of the drought.

Climate model uncertainty in impact assessments for agriculture: A multi-ensemble case study on maize in sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Dale, Amy; Fant, Charles; Strzepek, Kenneth; Lickley, Megan; Solomon, Susan

2017-03-01

We present maize production in sub-Saharan Africa as a case study in the exploration of how uncertainties in global climate change, as reflected in projections from a range of climate model ensembles, influence climate impact assessments for agriculture. The crop model AquaCrop-OS (Food and Agriculture Organization of the United Nations) was modified to run on a 2° × 2° grid and coupled to 122 climate model projections from multi-model ensembles for three emission scenarios (Coupled Model Intercomparison Project Phase 3 [CMIP3] SRES A1B and CMIP5 Representative Concentration Pathway [RCP] scenarios 4.5 and 8.5) as well as two "within-model" ensembles (NCAR CCSM3 and ECHAM5/MPI-OM) designed to capture internal variability (i.e., uncertainty due to chaos in the climate system). In spite of high uncertainty, most notably in the high-producing semi-arid zones, we observed robust regional and sub-regional trends across all ensembles. In agreement with previous work, we project widespread yield losses in the Sahel region and Southern Africa, resilience in Central Africa, and sub-regional increases in East Africa and at the southern tip of the continent. Spatial patterns of yield losses corresponded with spatial patterns of aridity increases, which were explicitly evaluated. Internal variability was a major source of uncertainty in both within-model and between-model ensembles and explained the majority of the spatial distribution of uncertainty in yield projections. Projected climate change impacts on maize production in different regions and nations ranged from near-zero or positive (upper quartile estimates) to substantially negative (lower quartile estimates), highlighting a need for risk management strategies that are adaptive and robust to uncertainty.

Comparing Apples to Apples: Paleoclimate Model-Data comparison via Proxy System Modeling

NASA Astrophysics Data System (ADS)

Dee, Sylvia; Emile-Geay, Julien; Evans, Michael; Noone, David

2014-05-01

The wealth of paleodata spanning the last millennium (hereinafter LM) provides an invaluable testbed for CMIP5-class GCMs. However, comparing GCM output to paleodata is non-trivial. High-resolution paleoclimate proxies generally contain a multivariate and non-linear response to regional climate forcing. Disentangling the multivariate environmental influences on proxies like corals, speleothems, and trees can be complex due to spatiotemporal climate variability, non-stationarity, and threshold dependence. Given these and other complications, many paleodata-GCM comparisons take a leap of faith, relating climate fields (e.g. precipitation, temperature) to geochemical signals in proxy data (e.g. δ18O in coral aragonite or ice cores) (e.g. Braconnot et al., 2012). Isotope-enabled GCMs are a step in the right direction, with water isotopes providing a connector point between GCMs and paleodata. However, such studies are still rare, and isotope fields are not archived as part of LM PMIP3 simulations. More importantly, much of the complexity in how proxy systems record and transduce environmental signals remains unaccounted for. In this study we use proxy system models (PSMs, Evans et al., 2013) to bridge this conceptual gap. A PSM mathematically encodes the mechanistic understanding of the physical, geochemical and, sometimes biological influences on each proxy. To translate GCM output to proxy space, we have synthesized a comprehensive, consistently formatted package of published PSMs, including δ18O in corals, tree ring cellulose, speleothems, and ice cores. Each PSM is comprised of three sub-models: sensor, archive, and observation. For the first time, these different components are coupled together for four major proxy types, allowing uncertainties due to both dating and signal interpretation to be treated within a self-consistent framework. The output of this process is an ensemble of many (say N = 1,000) realizations of the proxy network, all equally plausible under assumed dating uncertainties. We demonstrate the utility of the PSM framework with an integrative multi-PSM simulation. An intermediate-complexity AGCM with isotope physics (SPEEDY-IER, (Molteni, 2003, Dee et al., in prep)) is used to simulate the isotope hydrology and atmospheric response to SSTs derived from the LM PMIP3 integration of the CCSM4 model (Landrum et al., 2012). Relevant dynamical and isotope variables are then used to drive PSMs, emulating a realistic multiproxy network (Emile-Geay et al., 2013). We then ask the following question: given our best knowledge of proxy systems, what aspects of GCM behavior may be validated, and with what uncertainties? We approach this question via a three-tiered 'perfect model' study. A random realization of the simulated proxy data (hereafter 'PaleoObs') is used as a benchmark in the following comparisons: (1) AGCM output (without isotopes) vs. PaleoObs; (2) AGCM output (with isotopes) vs. PaleoObs; (3) coupled AGCM-PSM-simulated proxy ensemble vs. PaleoObs. Enhancing model-data comparison using PSMs highlights uncertainties that may arise from ignoring non-linearities in proxy-climate relationships, or the presence of age uncertainties (as is most typically done is paleoclimate model-data intercomparison). Companion experiments leveraging the 3 sub-model compartmentalization of PSMs allows us to quantify the contribution of each sub-system to the observed model-data discrepancies. We discuss potential repercussions for model-data comparison and implications for validating predictive climate models using paleodata. References Braconnot, P., Harrison, S. P., Kageyama, M., Bartlein, P. J., Masson-Delmotte, V., Abe-Ouchi, A., Otto-Bliesner, B., Zhao, Y., 06 2012. Evaluation of climate models using palaeoclimatic data. Nature Clim. Change 2 (6), 417-424. URL http://dx.doi.org/10.1038/nclimate1456 Emile-Geay, J., Cobb, K. M., Mann, M. E., Wittenberg, A. T., Apr 01 2013. Estimating central equatorial pacific sst variability over the past millennium. part i: Methodology and validation. Journal of Climate 26 (7), 2302-2328. URL http://search.proquest.com/docview/1350277733?accountid=14749 Evans, M., Tolwinski-Ward, S. E., Thompson, D. M., Anchukaitis, K. J., 2013. Applications of proxy system modeling in high resolution paleoclimatology. Quaternary Science Reviews. URL http://adsabs.harvard.edu/abs/2012QuInt.279U.134E Landrum, L., Otto-Bliesner, B. L., Wahl, E. R., Capotondi, A., Lawrence, P. J., Teng, H., 2012. Last Millennium Climate and Its Variability in CCSM4. Journal of Climate (submitted) Molteni, F., 2003. Atmospheric simulations using a GCM with simplified physical parametrizations. I model climatology and variability in multi-decadal experiments. Climate Dynamics, 175-191

High-resolution regional climate simulations of precipitation and snowpack over the US northern Rockies in a changing climate

NASA Astrophysics Data System (ADS)

Wang, Y.; Geerts, B.; Liu, C.

2015-12-01

This work first examines the performance of a regional climate model in capturing orographic precipitation and snowpack dynamics in the northern US Rockies. The Weather Research and Forecasting (WRF) model is run at a sufficiently fine resolution (4-km horizontal grid spacing), over a sub-continental domain driven by the Climate Forecast System Reanalysis (CFSR), to examine WRF's ability to simulate the observed seasonal precipitation and snowpack dynamics. WRF retrospective simulations are being run over a 30-year period from 1980 to 2010. Observations from Snow Telemetry (SNOTEL, providing precipitation rate and snowpack snow water equivalent (SWE)) and the Parameter-elevation Regressions on Independent Slopes Model (PRISM, providing fine-scale monthly mean values of precipitation and temperature) are used for validation. The results show that WRF captures observed seasonal precipitation and snowpack build-up reasonably well. The second part of this work is in progress. A pseudo-global warming (PGW) technique is used to perturb the retrospective reanalysis with the anticipated change according to the consensus global model guidance under the CMIP5 "high emissions" (RCP8.5) scenario produced by the CCSM4. This technique preserves low-frequency general circulation patterns and the characteristics of storms entering the domain. The WRF model is rerun over 30 years centered on 2050 with perturbed initial and boundary conditions. The results will be used to examine the effect of climate variability and projected global warming on the statistical distributions of precipitation amounts and SWE in the studied domain.

Attributing Contributions of Climate Feedbacks to the Seasonal Cycle of Surface Warming due to CO2 Increase

NASA Astrophysics Data System (ADS)

Sejas, S.; Cai, M.

2012-12-01

Surfing warming due to CO2 doubling is a robust feature of coupled general circulation models (GCM), as noted in the IPCC AR4 assessment report. In this study, the contributions of different climate feedbacks to the magnitude, spatial distribution, and seasonality of the surface warming is examined using data from NCAR's CCSM4. In particular, a focus is placed on polar regions to see which feedbacks play a role in polar amplification and its seasonal pattern. A new climate feedback analysis method is used to isolate the surface warming or cooling contributions of both radiative and non-radiative (dynamical) climate feedbacks to the total (actual) surface temperature change given by the CCSM4. These contributions (or partial surface temperature changes) are additive and their total is approximately equal to the actual surface temperature change. What is found is that the effects of CO2 doubling alone warms the surface throughout with a maximum in polar regions, which indicates the CO2 forcing alone has a degree of polar warming amplification. Water vapor feedback is a positive feedback throughout but is most responsible for the surface warming found in the tropics. Polar warming amplification is found to be strongest away from summer (especially in NH), which is primarily caused by a positive feedback due to cloud feedbacks but with the surface temperature change due to the CO2 forcing alone and the ocean dynamics and storage feedback also playing an important role. Contrary to popular belief, surface albedo feedback (SAF) does not account for much of the polar amplification. SAF tries to amplify polar warming, but in summer. No major polar amplification is seen in summer for the actual surface temperature, so SAF is not the feedback responsible for polar amplification. This is actually a consequence of the ocean dynamics and storage feedback, which negates the effects of SAF to a large degree.

Comparing Mid-Century Climate Change Projections at Convective Resolving Scales (2-km) for Life Zones Within Puerto Rico

NASA Astrophysics Data System (ADS)

Bowden, J.; Wootten, A.; Terando, A. J.; Boyles, R.; Misra, V.; Bhardwaj, A.

2016-12-01

Puerto Rico is home to over 3.5 million people and numerous endemic plant and animal species that may be at risk as a result of anthropogenic climate change. This study downscales three CMIP5 Global Circulation Models (GCMs) to a 2-km horizontal resolution using different regional climate models (RCMs) to resolve the island's climate. Here we compare projected climate change from a single GCM, CCSM4, from two RCMs centered on the mid-century, 2041-2060, for a high greenhouse gas emission scenario, RCP8.5. We will discuss similarities and differences in ecologically relevant climate variables, which were selected based on dialogue with experts who have knowledge about potential biological impacts of climate change for current life zones within Puerto Rico. Notable differences appear between the RCMs and include regions with critical ecosystems, such as the El Yunque National Forest in northeast Puerto Rico. This study helps to highlight RCMs structural uncertainty at convective resolving scales.

A global model simulation for 3-D radiative transfer impact on surface hydrology over the Sierra Nevada and Rocky Mountains

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

Lee, W. -L.; Gu, Y.; Liou, K. N.

2015-05-19

We investigate 3-D mountain effects on solar flux distributions and their impact on surface hydrology over the western United States, specifically the Rocky Mountains and the Sierra Nevada, using the global CCSM4 (Community Climate System Model version 4; Community Atmosphere Model/Community Land Model – CAM4/CLM4) with a 0.23° × 0.31° resolution for simulations over 6 years. In a 3-D radiative transfer parameterization, we have updated surface topography data from a resolution of 1 km to 90 m to improve parameterization accuracy. In addition, we have also modified the upward-flux deviation (3-D–PP (plane-parallel)) adjustment to ensure that the energy balance atmore » the surface is conserved in global climate simulations based on 3-D radiation parameterization. We show that deviations in the net surface fluxes are not only affected by 3-D mountains but also influenced by feedbacks of cloud and snow in association with the long-term simulations. Deviations in sensible heat and surface temperature generally follow the patterns of net surface solar flux. The monthly snow water equivalent (SWE) deviations show an increase in lower elevations due to reduced snowmelt, leading to a reduction in cumulative runoff. Over higher-elevation areas, negative SWE deviations are found because of increased solar radiation available at the surface. Simulated precipitation increases for lower elevations, while it decreases for higher elevations, with a minimum in April. Liquid runoff significantly decreases at higher elevations after April due to reduced SWE and precipitation.« less

A framework for modeling anthropogenic impacts on waterbird habitats: addressing future uncertainty in conservation planning

USGS Publications Warehouse

Matchett, Elliott L.; Fleskes, Joseph P.; Young, Charles A.; Purkey, David R.

2015-01-01

The amount and quality of natural resources available for terrestrial and aquatic wildlife habitats are expected to decrease throughout the world in areas that are intensively managed for urban and agricultural uses. Changes in climate and management of increasingly limited water supplies may further impact water resources essential for sustaining habitats. In this report, we document adapting a Water Evaluation and Planning (WEAP) system model for the Central Valley of California. We demonstrate using this adapted model (WEAP-CVwh) to evaluate impacts produced from plausible future scenarios on agricultural and wetland habitats used by waterbirds and other wildlife. Processed output from WEAP-CVwh indicated varying levels of impact caused by projected climate, urbanization, and water supply management in scenarios used to exemplify this approach. Among scenarios, the NCAR-CCSM3 A2 climate projection had a greater impact than the CNRM-CM3 B1 climate projection, whereas expansive urbanization had a greater impact than strategic urbanization, on annual availability of waterbird habitat. Scenarios including extensive rice-idling or substantial instream flow requirements on important water supply sources produced large impacts on annual availability of waterbird habitat. In the year corresponding with the greatest habitat reduction for each scenario, the scenario including instream flow requirements resulted in the greatest decrease in habitats throughout all months of the wintering period relative to other scenarios. This approach provides a new and useful tool for habitat conservation planning in the Central Valley and a model to guide similar research investigations aiming to inform conservation, management, and restoration of important wildlife habitats.

Improved atmosphere-ocean coupled modeling in the tropics for climate prediction

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

Zhang, Minghua

2015-01-01

We investigated the initial development of the double ITCZ in the Community Climate System Model (CCSM Version 3) in the central Pacific. Starting from a resting initial condition of the ocean in January, the model developed a warm bias of sea-surface temperature (SST) in the central Pacific from 5oS to 10oS in the first three months. We found this initial bias to be caused by excessive surface shortwave radiation that is also present in the standalone atmospheric model. The initial bias is further amplified by biases in both surface latent heat flux and horizontal heat transport in the upper ocean.more » These biases are caused by the responses of surface winds to SST bias and the thermocline structure to surface wind curls. We also showed that the warming biases in surface solar radiation and latent heat fluxes are seasonally offset by cooling biases from reduced solar radiation after the austral summer due to cloud responses and in the austral fall due to enhanced evaporation when the maximum SST is closest to the equator. The warming biases from the dynamic heat transport by ocean currents however stay throughout all seasons once they are developed, which are eventually balanced by enhanced energy exchange and penetration of solar radiation below the mixed layer. Our results also showed that the equatorial cold tongue develops after the warm biases in the south central Pacific, and the overestimation of surface shortwave radiation recurs in the austral summer in each year.« less

Using transfer functions to quantify El Niño Southern Oscillation dynamics in data and models.

PubMed

MacMartin, Douglas G; Tziperman, Eli

2014-09-08

Transfer function tools commonly used in engineering control analysis can be used to better understand the dynamics of El Niño Southern Oscillation (ENSO), compare data with models and identify systematic model errors. The transfer function describes the frequency-dependent input-output relationship between any pair of causally related variables, and can be estimated from time series. This can be used first to assess whether the underlying relationship is or is not frequency dependent, and if so, to diagnose the underlying differential equations that relate the variables, and hence describe the dynamics of individual subsystem processes relevant to ENSO. Estimating process parameters allows the identification of compensating model errors that may lead to a seemingly realistic simulation in spite of incorrect model physics. This tool is applied here to the TAO array ocean data, the GFDL-CM2.1 and CCSM4 general circulation models, and to the Cane-Zebiak ENSO model. The delayed oscillator description is used to motivate a few relevant processes involved in the dynamics, although any other ENSO mechanism could be used instead. We identify several differences in the processes between the models and data that may be useful for model improvement. The transfer function methodology is also useful in understanding the dynamics and evaluating models of other climate processes.

Use of circulation types classifications to evaluate AR4 climate models over the Euro-Atlantic region

NASA Astrophysics Data System (ADS)

Pastor, M. A.; Casado, M. J.

2012-10-01

This paper presents an evaluation of the multi-model simulations for the 4th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) in terms of their ability to simulate the ERA40 circulation types over the Euro-Atlantic region in winter season. Two classification schemes, k-means and SANDRA, have been considered to test the sensitivity of the evaluation results to the classification procedure. The assessment allows establishing different rankings attending spatial and temporal features of the circulation types. Regarding temporal characteristics, in general, all AR4 models tend to underestimate the frequency of occurrence. The best model simulating spatial characteristics is the UKMO-HadGEM1 whereas CCSM3, UKMO-HadGEM1 and CGCM3.1(T63) are the best simulating the temporal features, for both classification schemes. This result agrees with the AR4 models ranking obtained when having analysed the ability of the same AR4 models to simulate Euro-Atlantic variability modes. This study has proved the utility of applying such a synoptic climatology approach as a diagnostic tool for models' assessment. The ability of the models to properly reproduce the position of ridges and troughs and the frequency of synoptic patterns, will therefore improve our confidence in the response of models to future climate changes.

Glacial Inception and Carbon Cycle in CCSM4

NASA Astrophysics Data System (ADS)

Jochum, M.; Bailey, D. A.; Fasullo, J.; Kay, J. E.; Levis, S.; Lindsay, K. T.; Moore, J. K.; Otto-Bliesner, B. L.; Peacock, S.

2010-12-01

CCSM4 with ocean and land ecosystem and freely evolving atmospheric carbondioxide is used to quantify the response of carbon fluxes and climate to changes in orbital forcing. Compared to the present-day simulation, the simulation with the Earth's orbital parameters from 115.000 years ago features significantly cooler northern high latitudes, but only moderately cooler southern high latitudes. This asymmetry is explained by the sea-ice/snow albedo feedback; the MOC is almost unchanged. Most importantly, there is a substantial build up of snow cover on Baffin Island and North Canada - the origins of the Laurentide Ice Sheet. The strong northern high-latitude cooling and the direct insolation induced tropical warming lead to global shifts in precipitation and winds of the same order. However, the differences in global net air-sea carbon fluxes are small, and provide no support for the hypothesis that the solubility pump is responsible for the intial drawdown of atmospheric CO2 during a glacial inception. This surprising result is due to several effects, two of which stand out: Firstly, colder SST leads to higher solubility, but also to increased sea-ice concentration, which blocks air-sea exchange; and secondly, the weakening of the Southern Ocean winds that is predicted by some idealized studies occurs only in part of the basin, and is compensated by stronger winds in other parts.

Patterns of tropical Pacific convection anomalies and associated extratropical wave trains in AMIP5

NASA Astrophysics Data System (ADS)

Ding, Shuoyi; Chen, Wen; Graf, Hans-F.; Guo, Yuanyuan

2018-05-01

In this paper, the performance of 18 Coupled Model Intercomparison Project Phase 5 (CMIP5) models forced by observational SSTs in simulating the tropical Pacific convective variation and the atmospheric responses in the extratropics are assessed. The multi-model ensemble mean results of 18 CMIP5 models show that five major patterns of tropical Pacific convection anomaly in winter can indeed be well reproduced, however, the simulation of the corresponding extratropical responses for each pattern exists some deficiency except for the La Niña pattern compared with observations. We defined an optimized subset of well performing models (ACCESS1.0, CanAM4, CCSM4, CMCC-CM, HadGEM2-A, MPI-ESM-MR) in tropical Pacific deep convection according to the ranking of model skill score. These models exhibit approximately identical convection anomaly patterns in both amplitude and spatial structure to the observation, which potentially might improve the representation of extratropical teleconnections with the tropical Pacific, especially for the CP El Niño (CPEN), EP El Niño (EPEN) and western CP (W-CP) patterns. Both evident atmospheric anomalies of CPEN and EPEN patterns over the NA/E sector and the northeastward propagating wave trains of W-CP pattern can be quite well simulated in the high-skilled models.

Impact of topography-radiation interaction on surface energy budget of the Tibetan Plateau in GCM simulations

NASA Astrophysics Data System (ADS)

Lee, W. L.; Liou, K. N.; Gu, Y.; Wang, C. C.; Wu, C. H.; Hsu, H. H.

2017-12-01

We have develop a parameterization to quantify the effect of 3-D topography on surface solar radiation, including multiple reflection and heating difference at sunward and shaded slopes of mountains. A series of sensitivity tests using NCAR CCSM4 with and without this parameterization have been carried out to investigate this effect in climate simulations. The result indicates that missing the 3-D radiation-topography interaction could be a key factor leading to cold biases over the Tibetan Plateau in winter in all of the CMIP5 models. Consequently, the snowmelt rate in the Tibetan Plateau could be underestimated in most future projections. In addition, the topographic effect can also increase the net surface solar radiation at the southern slope of the Himalayas in summer. The temporal and spatial distribution of monsoon precipitation and circulation could also be influenced.

Quantifying Proxy Influence in the Last Millennium Reanalysis

NASA Astrophysics Data System (ADS)

Hakim, G. J.; Anderson, D. N.; Emile-Geay, J.; Noone, D.; Tardif, R.

2017-12-01

We examine the influence of proxies in the climate field reconstruction known as the Last Millennium Reanalysis (Hakim et al. 2016; JGR-A). This data assimilation framework uses the CCSM4 Last Millennium simulation as an agnostic prior, proxies from the PAGES 2k Consortium (2017; Sci. Data), and an offline ensemble square-root filter for assimilation. Proxies are forward modeled using an observation model ("proxy system model") that maps from the prior space to the proxy space. We assess proxy impact using the method of Cardinali et al. (2004; QJRMS), where influence is measured in observation space; that is, at the location of observations. Influence is determined by three components: the prior at the location, the proxy at the location, and remote proxies as mediated by the spatial covariance information in the prior. Consequently, on a per-proxy basis, influence is higher for spatially isolated proxies having small error, and influence is lower for spatially dense proxies having large error. Results show that proxy influence depends strongly on the observation model. Assuming the proxies depend linearly on annual mean temperature yields the largest per-proxy influence for coral d18O and coral Sr/Ca records, and smallest influence for tree-ring width. On a global basis (summing over all proxies of a given type), tree-ring width and coral d18O have the largest influence. A seasonal model for the proxies yields very different results. In this case we model the proxies linearly on objectively determined seasonal temperature, except for tree proxies, which are fit to a bivariate model on seasonal temperature and precipitation. In this experiment, on a per-proxy basis, tree-ring density has by far the greatest influence. Total proxy influence is dominated by tree-ring width followed by tree-ring density. Compared to the results for the annual-mean observation model, the experiment where proxies are measured seasonally has more than double the total influence (sum over all proxies); this experiment also has higher verification scores when measured against other 20th century temperature reconstructions. These results underscore the importance of improving proxy system models, since they increase the amount of information available for data-assimilation-based reconstructions.

Sr/Ca and δ18O records of a coral from Sanya: reconstructions of temperature and precipitation in the northern South China Sea in the late Holocene

NASA Astrophysics Data System (ADS)

Wagner, S.; Xoplaki, E.; Luterbacher, J.; Zorita, E.; Fleitmann, D.; Preiser-Kapeller, J.; Toreti, A., , Dr; Sargent, A. M.; Bozkurt, D.; White, S.; Haldon, J. F.; Akçer-Ön, S.; Izdebski, A.

2016-12-01

Past civilisations were influenced by complex external and internal forces, including changes in the environment, climate, politics and economy. A geographical hotspot of the interplay between those agents is the Mediterranean, a cradle of cultural and scientific development. We analyse a novel compilation of high-quality hydroclimate proxy records and spatial reconstructions from the Mediterranean and compare them with two Earth System Model simulations (CCSM4, MPI-ESM-P) for three historical time intervals - the Crusaders, 1095-1290 CE; the Mamluk regime in Transjordan, 1260-1516 CE; and the Ottoman crisis and Celâlî Rebellion, 1580-1610 CE - when environmental and climatic stress tested the resilience of complex societies. ESMs provide important information on the dynamical mechanisms and underlying processes that led to anomalous hydroclimatic conditions of the past. We find that the multidecadal precipitation and drought variations in the Central and Eastern Mediterranean during the three periods cannot be explained by external forcings (solar variations, tropical volcanism); rather they were driven by internal climate dynamics. The integrated analysis of palaeoclimate proxies, climate reconstructions and model simulations sheds light on our understanding of past climate change and its societal impact. Finally, our research emphasises the need to further study the societal dimension of environmental and climate change in the past, in order to properly understand the role that climate has played in human history.

The contribution of sea-level rise to flooding in large river catchments

NASA Astrophysics Data System (ADS)

Thiele-Eich, I.; Hopson, T. M.; Gilleland, E.; Lamarque, J.; Hu, A.; Simmer, C.

2012-12-01

Climate change is expected to both impact sea level rise as well as flooding. Our study focuses on the combined effect of climate change on upper catchment precipitation as well as on sea-level rise at the river mouths and the impact this will have on river flooding both at the coast and further upstream. We concentrate on the eight catchments of the Amazonas, Congo, Orinoco, Ganges/Brahmaputra/Meghna, Mississippi, St. Lawrence, Danube and Niger rivers. To assess the impact of climate change, upper catchment precipitation as well as monthly mean thermosteric sea-level rise at the river mouth outflow are taken from the four CCSM4 1° 20th Century ensemble members as well as from six CCSM4 1° ensemble members for the RCP scenarios RCP8.5, 6.0, 4.5 and 2.6. Continuous daily time series for average catchment precipitation and discharge are available for each of the catchments. To arrive at a future discharge time series, we used these observations to develop a simple statistical hydrological model which can be applied to the modelled future upper catchment precipitation values. The analysis of this surrogate discharge time series alone already yields significant changes in flood return levels as well as flood duration. Using the geometry of the river channel, the backwater effect of sea-level rise is incorporated in our analysis of both flood frequencies and magnitudes by calculating the effective additional discharge due to the increase in water level at the river mouth outflow, as well as its tapering impact upstream. By combining these effects, our results focus on the merged impact of changes in extreme precipitation with increases in river height due to sea-level rise at the river mouths. Judging from our preliminary results, the increase in effective discharge due to sea-level rise cannot be neglected when discussing late 21st century flooding in the respective river basins. In particular, we find that especially in countries with low elevation gradient, flood characteristics are impacted by changes in sea-level rise as far inland as 150 kilometers. Therefore, a larger population than the coastal inhabitants alone are exposed to risks of further projected increases of sea-level rise. A prime example for a megacity greatly put at risk by this is Dhaka City in Bangladesh, with a population of roughly 14 million people.

Climate and Ocean Circulation During "The Boring Billion" Simulated by CCSM3

NASA Astrophysics Data System (ADS)

Liu, P.; Hu, Y.; Liu, Y.

2017-12-01

The Boring Billion is referred to the era between approximately 1.8 and 0.8 billion years ago. Geological evidence suggests that no dramatic climate changes in the billions of years, at least in terms of permanent glaciation. The atmospheric oxygen maintained at a relatively low level without significant perturbations. Life had a certain degree of evolution with a quite gentle pace. Relative to the Great Oxidation Event occurred previously, and the Snowball Earth Event and Cambrian Explosion occurred afterwards, this billion years was calm in all aspects so it's often referred to as "the Boring Billion". Why were both the climate and oxygen concentration so stable, and how the anoxic condition in the deep ocean maintained are the questions that motivated our research. We use the Atmosphere Ocean General Circulation Model CCSM3 in this study. The climate of the Boring Billion is simulated for two distinct continental configurations reconstructed for 1540 Ma and 1420 Ma, with continental fragments concentrating towards the North Pole and equator, respectively. The solar constant is set to be 10% weaker than that of the present day. The results show that when the concentration of CO2 is 20 times the present atmospheric level (PAL), the global mean surface temperatures are 19 ° C and 20 ° C for the 1540 Ma and 1420 Ma continental configuration, respectively. Large scale permanent glaciers cannot develop in such a warm climate even for the continents at the polar region. The largest mixed-layer depth in the high-latitude ocean is approximately 1200 m and meridional overturning circulation can reach depth of 3000 m with strength of 40 Sv for both continental configuration. This implies that the material and energy exchange between shallow and deep ocean, as well as atmosphere and ocean, is efficient. When CO2 concentration is reduced to 10 PAL, 5 PAL or 2.5 PAL, global average temperature becomes 16 ° C, 13 ° C and 2 ° C respectively, and permanent glaciers start to form at the polar regions. Therefore, our simulations suggest that the CO2 concentration had to be close to or higher than 20 PAL in order for the simulated climate to be consistent with the observations. Moreover, the oceans were not dynamically stratified, to maintain an anoxic deep ocean biogeochemical processes which are not included in the model have to be invoked.

The impacts of climate, land use, and demography on fires during the 21st century simulated by CLM-CN

NASA Astrophysics Data System (ADS)

Kloster, S.; Mahowald, N. M.; Randerson, J. T.; Lawrence, P. J.

2012-01-01

Landscape fires during the 21st century are expected to change in response to multiple agents of global change. Important controlling factors include climate controls on the length and intensity of the fire season, fuel availability, and fire management, which are already anthropogenically perturbed today and are predicted to change further in the future. An improved understanding of future fires will contribute to an improved ability to project future anthropogenic climate change, as changes in fire activity will in turn impact climate. In the present study we used a coupled-carbon-fire model to investigate how changes in climate, demography, and land use may alter fire emissions. We used climate projections following the SRES A1B scenario from two different climate models (ECHAM5/MPI-OM and CCSM) and changes in population. Land use and harvest rates were prescribed according to the RCP 45 scenario. In response to the combined effect of all these drivers, our model estimated, depending on our choice of climate projection, an increase in future (2075-2099) fire carbon emissions by 17 and 62% compared to present day (1985-2009). The largest increase in fire emissions was predicted for Southern Hemisphere South America for both climate projections. For Northern Hemisphere Africa, a region that contributed significantly to the global total fire carbon emissions, the response varied between a decrease and an increase depending on the climate projection. We disentangled the contribution of the single forcing factors to the overall response by conducting an additional set of simulations in which each factor was individually held constant at pre-industrial levels. The two different projections of future climate change evaluated in this study led to increases in global fire carbon emissions by 22% (CCSM) and 66% (ECHAM5/MPI-OM). The RCP 45 projection of harvest and land use led to a decrease in fire carbon emissions by -5%. The RCP 26 and RCP 60 harvest and landuse projections caused decreases around -20%. Changes in human ignition led to an increase of 20%. When we also included changes in fire management efforts to suppress fires in densely populated areas, global fire carbon emission decreased by -6% in response to changes in population density. We concluded from this study that changes in fire emissions in the future are controlled by multiple interacting factors. Although changes in climate led to an increase in future fire emissions this could be globally counterbalanced by coupled changes in land use, harvest, and demography.

Uncertainties in the Modelled CO2 Threshold for Antarctic Glaciation

NASA Technical Reports Server (NTRS)

Gasson, E.; Lunt, D. J.; DeConto, R.; Goldner, A.; Heinemann, M.; Huber, M.; LeGrande, A. N.; Pollard, D.; Sagoo, N.; Siddall, M.;

An international land-biosphere model benchmarking activity for the IPCC Fifth Assessment Report (AR5)

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

Hoffman, Forrest M; Randerson, James T; Thornton, Peter E

2009-12-01

The need to capture important climate feedbacks in general circulation models (GCMs) has resulted in efforts to include atmospheric chemistry and land and ocean biogeochemistry into the next generation of production climate models, called Earth System Models (ESMs). While many terrestrial and ocean carbon models have been coupled to GCMs, recent work has shown that such models can yield a wide range of results (Friedlingstein et al., 2006). This work suggests that a more rigorous set of global offline and partially coupled experiments, along with detailed analyses of processes and comparisons with measurements, are needed. The Carbon-Land Model Intercomparison Projectmore » (C-LAMP) was designed to meet this need by providing a simulation protocol and model performance metrics based upon comparisons against best-available satellite- and ground-based measurements (Hoffman et al., 2007). Recently, a similar effort in Europe, called the International Land Model Benchmark (ILAMB) Project, was begun to assess the performance of European land surface models. These two projects will now serve as prototypes for a proposed international land-biosphere model benchmarking activity for those models participating in the IPCC Fifth Assessment Report (AR5). Initially used for model validation for terrestrial biogeochemistry models in the NCAR Community Land Model (CLM), C-LAMP incorporates a simulation protocol for both offline and partially coupled simulations using a prescribed historical trajectory of atmospheric CO2 concentrations. Models are confronted with data through comparisons against AmeriFlux site measurements, MODIS satellite observations, NOAA Globalview flask records, TRANSCOM inversions, and Free Air CO2 Enrichment (FACE) site measurements. Both sets of experiments have been performed using two different terrestrial biogeochemistry modules coupled to the CLM version 3 in the Community Climate System Model version 3 (CCSM3): the CASA model of Fung, et al., and the carbon-nitrogen (CN) model of Thornton. Comparisons of the CLM3 offline results against observational datasets have been performed and are described in Randerson et al. (2009). CLM version 4 has been evaluated using C-LAMP, showing improvement in many of the metrics. Efforts are now underway to initiate a Nitrogen-Land Model Intercomparison Project (N-LAMP) to better constrain the effects of the nitrogen cycle in biosphere models. Presented will be new results from C-LAMP for CLM4, initial N-LAMP developments, and the proposed land-biosphere model benchmarking activity.« less

The Nested Regional Climate Model: An Approach Toward Prediction Across Scales

NASA Astrophysics Data System (ADS)

Hurrell, J. W.; Holland, G. J.; Large, W. G.

2008-12-01

The reality of global climate change has become accepted and society is rapidly moving to questions of consequences on space and time scales that are relevant to proper planning and development of adaptation strategies. There are a number of urgent challenges for the scientific community related to improved and more detailed predictions of regional climate change on decadal time scales. Two important examples are potential impacts of climate change on North Atlantic hurricane activity and on water resources over the intermountain West. The latter is dominated by complex topography, so that accurate simulations of regional climate variability and change require much finer spatial resolution than is provided with state-of-the-art climate models. Climate models also do not explicitly resolve tropical cyclones, even though these storms have dramatic societal impacts and play an important role in regulating climate. Moreover, the debate over the impact of global warming on tropical cyclones has at times been acrimonious, and the lack of hard evidence has left open opportunities for misinterpretation and justification of pre-existing beliefs. These and similar topics are being assessed at NCAR, in partnership with university colleagues, through the development of a Nested Regional Climate Model (NRCM). This is an ambitious effort to combine a state of the science mesoscale weather model (WRF), a high resolution regional ocean modeling system (ROMS), and a climate model (CCSM) to better simulate the complex, multi-scale interactions intrinsic to atmospheric and oceanic fluid motions that are limiting our ability to predict likely future changes in regional weather statistics and climate. The NRCM effort is attracting a large base of earth system scientists together with societal groups as diverse as the Western Governor's Association and the offshore oil industry. All of these groups require climate data on scales of a few kilometers (or less), so that the NRCM program is producing unique data sets of climate change scenarios of immense interest. In addition, all simulations are archived in a form that will be readily accessible to other researchers, thus enabling a wider group to investigate these important issues.

Diversity of precipitation characteristics in contiguous United States: climatology, interannual variation, and change in the warming climate

NASA Astrophysics Data System (ADS)

Chen, Chen; Chang, Won; Kong, Wenwen; Wang, Jiali; Rao Kotamarthi, V.; Stein, Michael L.; Moyer, Elisabeth J.

2017-04-01

Individual precipitation events induce different levels of hydrological impacts given their diverse characteristics, not only in precipitation amount but also in precipitation rate, duration, and size. It thus calls for an understanding of the diversity in precipitation characteristics and its influence on the total precipitation in contiguous United States. The framework we use to look into the precipitation diversity includes three steps: 1. we analyze the precipitation in observations (StageIV, 4kmx4km, 1h) and regional climate models (CCSM4-WRF downscaling,12kmx12km, 3h), in which the high spatio-temporal resolution enables us to "see" individual precipitation events. 2. switching from the Eulerian to Lagrangian perspective, we track individual rainstorms using Chang et al. (2016), in which algorithm both small and big events are identified to ensure the full spectrum diversity. 3. we use a set of metrics to characterize varying aspects of diversity and decompose their contributions to the total precipitation in CONUS. We also measure the variation and change in event frequency. The overall understandings are the following: 1. as to the climatology, though certain rainstorms with longer duration or larger size have better abilities to produce precipitation, the scarcity limits their overall contributions to the seasonal precipitation in CONUS. 2. as to the interannual variation, for a wetter year when the total precipitation is larger than normal and events are more frequent, the averaged rainstorm size is larger though the intensified precipitation rate shortens the rainstorm duration. 3. as to the change in a warming climate (as in Chang et al. 2016), CCSM4-WRF projection under RCP8.5 scenario suggests that, along with the increasing precipitation amount and intensity, the averaged rainstorm duration become longer but the size becomes overall smaller. The total number of events does not change much. 4. different relations governing the interannual variation and mean state change suggest that the physics across varying time scales could be orthogonal and thus require individual investigation and comparison to reach an overall understanding.

Assessment of climate change impact on yield of major crops in the Banas River Basin, India.

PubMed

Dubey, Swatantra Kumar; Sharma, Devesh

2018-09-01

Crop growth models like AquaCrop are useful in understanding the impact of climate change on crop production considering the various projections from global circulation models and regional climate models. The present study aims to assess the climate change impact on yield of major crops in the Banas River Basin i.e., wheat, barley and maize. Banas basin is part of the semi-arid region of Rajasthan state in India. AquaCrop model is used to calculate the yield of all the three crops for a historical period of 30years (1981-2010) and then compared with observed yield data. Root Mean Square Error (RMSE) values are calculated to assess the model accuracy in prediction of yield. Further, the calibrated model is used to predict the possible impacts of climate change and CO 2 concentration on crop yield using CORDEX-SA climate projections of three driving climate models (CNRM-CM5, CCSM4 and MPI-ESM-LR) for two different scenarios (RCP4.5 and RCP8.5) for the future period 2021-2050. RMSE values of simulated yield with respect to observed yield of wheat, barley and maize are 11.99, 16.15 and 19.13, respectively. It is predicted that crop yield of all three crops will increase under the climate change conditions for future period (2021-2050). Copyright © 2018 Elsevier B.V. All rights reserved.

Quantifying the Impact of Mountain Pine Beetle Disturbances on Forest Carbon Pools and Fluxes in the Western US using the NCAR Community Land Model

NASA Astrophysics Data System (ADS)

Edburg, S. L.; Hicke, J. A.; Lawrence, D. M.; Thornton, P. E.

2009-12-01

Forest disturbances, such as fire, insects, and land-use change, significantly alter carbon budgets by changing carbon pools and fluxes. The mountain pine beetle (MPB) kills millions of hectares of trees in the western US, similar to the area killed by fire. Mountain pine beetles kill host trees by consuming the inner bark tissue, and require host tree death for reproduction. Despite being a significant disturbance to forested ecosystems, insects such as MPB are typically not represented in biogeochemical models, thus little is known about their impact on the carbon cycle. We investigate the role of past MPB outbreaks on carbon cycling in the western US using the NCAR Community Land Model with Carbon and Nitrogen cycles (CLM-CN). CLM-CN serves as the land model to the Community Climate System Model (CCSM), providing exchanges of energy, momentum, water, carbon, and nitrogen between the land and atmosphere. We run CLM-CN over the western US extending to eastern Colorado with a spatial resolution of 0.5° and a half hour time step. The model is first spun-up with repeated NCEP forcing (1948-1972) until carbon stocks and fluxes reach equilibrium (~ 3000 years), and then run from 1850 to 2004 with NCEP forcing and a dynamic plant functional type (PFT) database. Carbon stocks from this simulation are compared with stocks from the Forest Inventory Analysis (FIA) program. We prescribe MPB mortality area, once per year, in CLM-CN using USFS Aerial Detection Surveys (ADS) from the last few decades. We simulate carbon impacts of tree mortality by MPB within a model grid cell by moving carbon from live vegetative pools (leaf, stem, and roots) to dead pools (woody debris, litter, and dead roots). We compare carbon pools and fluxes for two simulations, one without MPB outbreaks and one with MPB outbreaks.

Comparison of multi-proxy data with past1000 model output over the Terminal Classic Period (800-1000 A.D.) on the Yucatan Peninsula.

NASA Astrophysics Data System (ADS)

Van Pelt, S.; Kohfeld, K. E.; Allen, D. M.

2015-12-01

The decline of the Mayan Civilization is thought to be caused by a series of droughts that affected the Yucatan Peninsula during the Terminal Classic Period (T.C.P.) 800-1000 AD. The goals of this study are two-fold: (a) to compare paleo-model simulations of the past 1000 years with a compilation of multiple proxies of changes in moisture conditions for the Yucatan Peninsula during the T.C.P. and (b) to use this comparison to inform the modeling of groundwater recharge in this region, with a focus on generating the daily climate data series needed as input to a groundwater recharge model. To achieve the first objective, we compiled a dataset of 5 proxies from seven locations across the Yucatan Peninsula, to be compared with temperature and precipitation output from the Community Climate System Model Version 4 (CCSM4), which is part of the Coupled Model Intercomparison Project Phase 5 (CMIP5) past1000 experiment. The proxy dataset includes oxygen isotopes from speleothems and gastropod/ostrocod shells (11 records); and sediment density, mineralogy, and magnetic susceptibility records from lake sediment cores (3 records). The proxy dataset is supplemented by a compilation of reconstructed temperatures using pollen and tree ring records for North America (archived in the PAGES2k global network data). Our preliminary analysis suggests that many of these datasets show evidence of drier and warmer climate on the Yucatan Peninsula around the T.C.P. when compared to modern conditions, although the amplitude and timing of individual warming and drying events varies between sites. This comparison with modeled output will ultimately be used to inform backward shift factors that will be input to a stochastic weather generator. These shift factors will be based on monthly changes in temperature and precipitation and applied to a modern daily climate time series for the Yucatan Peninsula to produce a daily climate time series for the T.C.P.

The structure and large-scale organization of extreme cold waves over the conterminous United States

NASA Astrophysics Data System (ADS)

Xie, Zuowei; Black, Robert X.; Deng, Yi

2017-12-01

Extreme cold waves (ECWs) occurring over the conterminous United States (US) are studied through a systematic identification and documentation of their local synoptic structures, associated large-scale meteorological patterns (LMPs), and forcing mechanisms external to the US. Focusing on the boreal cool season (November-March) for 1950‒2005, a hierarchical cluster analysis identifies three ECW patterns, respectively characterized by cold surface air temperature anomalies over the upper midwest (UM), northwestern (NW), and southeastern (SE) US. Locally, ECWs are synoptically organized by anomalous high pressure and northerly flow. At larger scales, the UM LMP features a zonal dipole in the mid-tropospheric height field over North America, while the NW and SE LMPs each include a zonal wave train extending from the North Pacific across North America into the North Atlantic. The Community Climate System Model version 4 (CCSM4) in general simulates the three ECW patterns quite well and successfully reproduces the observed enhancements in the frequency of their associated LMPs. La Niña and the cool phase of the Pacific Decadal Oscillation (PDO) favor the occurrence of NW ECWs, while the warm PDO phase, low Arctic sea ice extent and high Eurasian snow cover extent (SCE) are associated with elevated SE-ECW frequency. Additionally, high Eurasian SCE is linked to increases in the occurrence likelihood of UM ECWs.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Effects of the Bering Strait closure on AMOC and global climate under different background climates

NASA Astrophysics Data System (ADS)

Hu, Aixue; Meehl, Gerald A.; Han, Weiqing; Otto-Bliestner, Bette; Abe-Ouchi, Ayako; Rosenbloom, Nan

2015-03-01

Previous studies have suggested that the status of the Bering Strait may have a significant influence on global climate variability on centennial, millennial, and even longer time scales. Here we use multiple versions of the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM, versions 2 and 3) to investigate the influence of the Bering Strait closure/opening on the Atlantic Meridional Overturning Circulation (AMOC) and global mean climate under present-day, 15 thousand-year before present (kyr BP), and 112 kyr BP climate boundary conditions. Our results show that regardless of the version of the model used or the widely different background climates, the Bering Strait's closure produces a robust result of a strengthening of the AMOC, and an increase in the northward meridional heat transport in the Atlantic. As a consequence, the climate becomes warmer in the North Atlantic and the surrounding regions, but cooler in the North Pacific, leading to a seesaw-like climate change between these two basins. For the first time it is noted that the absence of the Bering Strait throughflow causes a slower motion of Arctic sea ice, a reduced upper ocean water exchange between the Arctic and North Atlantic, reduced sea ice export and less fresh water in the North Atlantic. These changes contribute positively to the increased upper ocean density there, thus strengthening the AMOC. Potentially these changes in the North Atlantic could have a significant effect on the ice sheets both upstream and downstream in ice age climate, and further influence global sea level changes.

Multi-model Ensemble Regional Climate Projection of the Maritime Continent using the MIT Regional Climate Model

NASA Astrophysics Data System (ADS)

Kang, S.; IM, E. S.; Eltahir, E. A. B.

2016-12-01

In this study, the future change in precipitation due to global warming is investigated over the Maritime Continent using the MIT Regional Climate Model (MRCM). A total of nine 30-year projections under multi-GCMs (CCSM, MPI, ACCESS) and multi-scenarios of emissions (Control, RCP4.5, RCP8.5) are dynamically downscaled using the MRCM with 12km horizontal resolution. Since downscaled results tend to systematically overestimate the precipitation regardless of GCM used as lateral boundary conditions, the Parametric Quantile Mapping (PQM) is applied to reduce this wet bias. The cross validation for the control simulation shows that the PQM method seems to retain the spatial pattern and temporal variability of raw simulation, however it effectively reduce the wet bias. Based on ensemble projections produced by dynamical downscaling and statistical bias correction, a reduction of future precipitation is discernible, in particular during dry season (June-July-August). For example, intense precipitation in Singapore is expected to be reduced in RCP8.5 projection compared to control simulation. However, the geographical patterns and magnitude of changes still remain uncertain, suffering from statistical insignificance and a lack of model agreement. Acknowledgements This research is supported by the National Research Foundation Singapore under its Campus for Research Excellence and Technological Enterprise programme. The Center for Environmental Sensing and Modeling is an interdisciplinary research group of the Singapore-MIT Alliance for Research and Technology

The Importance of Explicitly Representing Soil Carbon with Depth over the Permafrost Region in Earth System Models: Implications for Atmospheric Carbon Dynamics at Multiple Temporal Scales between 1960 and 2300.

NASA Astrophysics Data System (ADS)

McGuire, A. D.

2014-12-01

We conducted an assessment of changes in permafrost area and carbon storage simulated by process-based models between 1960 and 2300. The models participating in this comparison were those that had joined the model integration team of the Vulnerability of Permafrost Carbon Research Coordination Network (see http://www.biology.ufl.edu/permafrostcarbon/). Each of the models in this comparison conducted simulations over the permafrost land region in the Northern Hemisphere driven by CCSM4-simulated climate for RCP 4.5 and 8.5 scenarios. Among the models, the area of permafrost (defined as the area for which active layer thickness was less than 3 m) ranged between 13.2 and 20.0 million km2. Between 1960 and 2300, models indicated the loss of permafrost area between 5.1 to 6.0 million km2 for RCP 4.5 and between 7.1 and 15.2 million km2 for RCP 8.5. Among the models, the density of soil carbon storage in 1960 ranged between 13 and 42 thousand g C m-2; models that explicitly represented carbon with depth had estimates greater than 27 thousand g C m-2. For the RCP 4.5 scenario, changes in soil carbon between 1960 and 2300 ranged between losses of 32 Pg C to gains of 58 Pg C, in which models that explicitly represent soil carbon with depth simulated losses or lower gains of soil carbon in comparison with those that did not. For the RCP 8.5 scenario, changes in soil carbon between 1960 and 2300 ranged between losses of 642 Pg C to gains of 66 Pg C, in which those models that represent soil carbon explicitly with depth all simulated losses, while those that do not all simulated gains. These results indicate that there are substantial differences in responses of carbon dynamics between model that do and do not explicitly represent soil carbon with depth in the permafrost region. We present analyses of the implications of the differences for atmospheric carbon dynamics at multiple temporal scales between 1960 and 2300.

Projected climate and vegetation changes and potential biotic effects for Fort Benning, Georgia; Fort Hood, Texas; and Fort Irwin, California

USGS Publications Warehouse

Shafer, S.L.; Atkins, J.; Bancroft, B.A.; Bartlein, P.J.; Lawler, J.J.; Smith, B.; Wilsey, C.B.

2012-01-01

The responses of species and ecosystems to future climate changes will present challenges for conservation and natural resource managers attempting to maintain both species populations and essential habitat. This report describes projected future changes in climate and vegetation for three study areas surrounding the military installations of Fort Benning, Georgia, Fort Hood, Texas, and Fort Irwin, California. Projected climate changes are described for the time period 2070–2099 (30-year mean) as compared to 1961–1990 (30-year mean) for each study area using data simulated by the coupled atmosphere-ocean general circulation models CCSM3, CGCM3.1(T47), and UKMO-HadCM3, run under the B1, A1B, and A2 future greenhouse gas emissions scenarios. These climate data are used to simulate potential changes in important components of the vegetation for each study area using LPJ, a dynamic global vegetation model, and LPJ-GUESS, a dynamic vegetation model optimized for regional studies. The simulated vegetation results are compared with observed vegetation data for the study areas. Potential effects of the simulated future climate and vegetation changes for species and habitats of management concern are discussed in each study area, with a particular focus on federally listed threatened and endangered species.

Trend analysis of watershed-scale precipitation over Northern California by means of dynamically-downscaled CMIP5 future climate projections.

PubMed

Ishida, K; Gorguner, M; Ercan, A; Trinh, T; Kavvas, M L

2017-08-15

The impacts of climate change on watershed-scale precipitation through the 21st century were investigated over eight study watersheds in Northern California based on dynamically downscaled CMIP5 future climate projections from three GCMs (CCSM4, HadGEM2-ES, and MIROC5) under the RCP4.5 and RCP8.5 future climate scenarios. After evaluating the modeling capability of the WRF model, the six future climate projections were dynamically downscaled by means of the WRF model over Northern California at 9km grid resolution and hourly temporal resolution during a 94-year period (2006-2100). The biases in the model simulations were corrected, and basin-average precipitation over the eight study watersheds was calculated from the dynamically downscaled precipitation data. Based on the dynamically downscaled basin-average precipitation, trends in annual depth and annual peaks of basin-average precipitation during the 21st century were analyzed over the eight study watersheds. The analyses in this study indicate that there may be differences between trends of annual depths and annual peaks of watershed-scale precipitation during the 21st century. Furthermore, trends in watershed-scale precipitation under future climate conditions may be different for different watersheds depending on their location and topography even if they are in the same region. Copyright © 2017 Elsevier B.V. All rights reserved.

Three types of Indian Ocean Basin modes

NASA Astrophysics Data System (ADS)

Guo, Feiyan; Liu, Qinyu; Yang, Jianling; Fan, Lei

2017-04-01

The persistence of the Indian Ocean Basin Mode (IOBM) from March to August is important for the prediction of Asian summer monsoon. Based on the observational data and the pre-industrial control run outputs of the Community Climate System Model, version 4 (CCSM4), the IOBM is categorized into three types: the first type can persist until August; the second type transforms from the positive (negative) IOBM into the negative (positive) Indian Ocean Dipole Mode (IODM), accompanied by the El Niño-to-La Niña (La Niña-to-El Niño) transition in the boreal summer; the third type transforms from the positive (negative) IOBM into the positive (negative) IODM in early summer. It is discovered that aside from the influence of anomalous Walker Circulation resulted from the phase transition of ENSO, the persistence of Australia high anomaly (AHA) over the southeastern tropical Indian Ocean (TIO) and the west of Australia from March to May is favorable for the positive (negative) IOBM transformation into the positive (negative) IODM in the boreal summer. The stronger equatorially asymmetric sea surface temperature anomalies (SSTAs) in the boreal spring are the main mechanism for the persistence of IOBM, because the asymmetric atmospheric responses to the stronger equatorially asymmetric SSTAs in the TIO confine the AHA to the east of Australia from May to August. This result indicates a possibility of predicting summer atmospheric circulation based on the equatorial symmetry of SSTAs in the TIO in spring.

Future Projections from the Effects of Heat Stress on Livestock: for the US and New England Region

NASA Astrophysics Data System (ADS)

McCabe, E.; Buzan, J. R.; Huber, M.; Krishnan, S.

2015-12-01

Future climate change will result in variations in heat stress experienced by livestock, which will consequently impact health, well-being, and yield. In this study, we estimate future yield changes for livestock due to heat stress in New England. We use the Community Land Model version 4.5 (CLM4.5), a component of the Community Earth System Model (CESM) that is developed by the National Center for Atmospheric Research (NCAR). The simulation uses RCP8.5 boundary conditions, and is driven by CCSM4 atmospheric forcing from the CMIP5 archive, that conducts simulations of the past and next century. Heat stress metrics are calculated using the HumanIndexMod in CLM4.5 for the early and late 21st century. For example, the humidity index for comfort and physiology, wet bulb temperature and swamp cooler efficiency. Results indicate that in the New England Region, temperatures will increase by 4 °C and in New Hampshire specifically by 3 °C. Temperature humidity index for comfort and physiology, swamp cooler efficiency and wet bulb are all projected to rise by the end of the century. While it is obvious that these elevations in temperature will have a negative effect on animals inhibiting their performance and output, our analysis also emphasizes the role of changes in humidity in heat stress. We show that heat stress caused by temperature and humidity increases, will decrease overall production yield for dairy and beef cattle, sows, finishing hogs and poultry, as a result of heat stress and other major climatic factors. We estimate and discuss resulting economic losses for the livestock industries and the impact in the United States and New England Region.

How Synchronous was the Transition into the Younger Dryas across the Euro-Atlantic Region?

NASA Astrophysics Data System (ADS)

Schenk, F.; Muschitiello, F.; Heikkilä, M. P.; Väliranta, M.; Tarasov, L.; Brandefelt, J.; Johansson, A. V.; Naslund, J. O.; Wohlfarth, B.

2015-12-01

Observations of a currently weakening subpolar gyre south of Greenland has again increased scientific attention regarding the role of the Atlantic Meridional Overturning Circulation (AMOC) for the regional to global climate. The rapid climate shift of the Younger Dryas (YD, GS-1) cold reversal during the last deglaciation is attributed to an abrupt slowdown or collapse of the AMOC due to a strong meltwater pulse and/or the rapid disintegration of the Laurentide Ice sheet. Although such a dramatic event is not expected for the future, the spatiotemporal climatic response to such a slowdown is an interesting test case. Two recently well dated proxy records around the North Sea region suggest a non-synchronous early cooling/onset of the YD compared to Greenland (NGRIP). Presentation #61803 discusses the hypothesis of a local cooling as a response to increased ice berg calving and/or meltwater from Fenno-Scandinavian Ice Sheet (FIS) during the late Alleröd warm phase (GI-1a). Here we study CCSM3 model output from the quasi-transient atmosphere-ocean simulation (TraCE) where no strong contribution from FIS is considered from the late Alleröd into the YD. We evaluate to which extent the spatiotemporal temperature response to the AMOC slowdown of the simulation is synchronous over the Euro-Atlantic region and how atmospheric teleconnections reorganize during the rapid shift into the YD. In addition, we run time-slice experiments at high spatial resolution of around 100 km with the Community Earth System Model CESM1.0.5 for the late Alleröd and YD to compare spatial climatic differences for both periods taking into account the regional influence from continental ice sheets in more detail.

Tide, Ocean and Climate on Exoplanets

NASA Astrophysics Data System (ADS)

Si, Y.; Yang, J.

2017-12-01

On Earth, tide is a main part of the driving force for the deep ocean overturning circulation. For habitable planets around low-mass stars, the tidal force is expected to be much stronger than that on Earth, due to the fact that the habitable zone is very close to the host stars and that tide force is inversely proportional to the orbital distance cubed. The deep ocean overturning circulation on this type of planets is therefore expected to be much stronger than that on Earth, if all else being equal. We test this hypothesis using a fully coupled atmosphere-ocean model, the Community Climate System Model version 3 (CCSM3). Our results show that the intensity of oceanic meridional overturning circulation (MOC) is approximately proportional to κ1/3, where κ is the mixing coefficient across density interfaces and it is mainly determined by the strength of the tidal force. As a result of the enhanced MOC, more heat is transported to dark regions and sea ice melts completely there, and meanwhile more heat is mixed from the surface to the deep ocean and thereby the entire ocean becomes much warmer (Fig. 1). A positive cloud feedback further warms the global ocean and atmosphere. These results imply that one planet with a stronger tidal force will likely enter a globally ice-covered snowball state at a lower stellar flux and enter a moist greenhouse or runaway greenhouse state at also a lower stellar flux, meaning that the tidal force acts to push the habitable zone outward. This study significantly improves our understanding of the possible coupling between planetary orbit, ocean, climate, and habitability on exoplanets.

A Software Prototype For Accessing Large Climate Simulation Data Through Digital Globe Interface

NASA Astrophysics Data System (ADS)

Chaudhuri, A.; Sorokine, A.

2010-12-01

The IPCC suite of global Earth system models produced terabytes of data for the CMIP3/AR4 archive and is expected to reach the petabyte scale by CMIP5/AR5. Dynamic downscaling of global models based on regional climate models can potentially lead to even larger data volumes. The model simulations for global or regional climate models like CCSM3 or WRF are typically run on supercomputers like the ORNL/DOE Jaguar and the results are stored on high performance storage systems. Access to these results from a user workstation is impeded by a number of factors such as enormous data size, limited bandwidth of standard office networks, data formats which are not fully supported by applications. So, a user-friendly interface for accessing and visualizing these results over standard Internet connection is required to facilitate collaborative work among geographically dispersed groups of scientists. To address this problem, we have developed a virtual globe based application which enables the scientists to query, visualize and analyze the results without the need of large data transfers to desktops and department-level servers. We have used open-source NASA WorldWind as a virtual globe platform and extended it with modules capable of visualizing model outputs stored in NetCDF format, while the data resides on the high-performance system. Based on the query placed by the scientist, our system initiates data processing routines on the high performance storage system to subset the data and reduce its size and then transfer it back to scientist's workstation through secure shell tunnel. The whole operation is kept totally transparent to the scientist and for the most part is controlled from a point-and-click GUI. The virtual globe also serves as a common platform for geospatial data, allowing smooth integration of the model simulation results with geographic data from other sources such as various web services or user-specific data in local files, if required. Also the system has the capability of building and updating a metadata catalog on the high performance storage that presents a simplified summary of the stored variables, hiding the low-level details such as physical location, size or format of the files from the user. Since data are often contributed to the system from multiple sources, the metadata catalog provides the user with a bird's eye view of the recent status of the database. As a next step, we plan on parallelizing the metadata updating and query-driven data selection routines to reduce the query response time. At current stage, the system can be immediately useful in making climate model simulation results available to a greater number of researchers who need simple and intuitive visualization of the simulation data or want to perform some analysis on it. The system's utility can reach beyond this particular application since it is generic enough to be ported to other high performance systems and to enable easy access to other types of geographic data.

Air-Sea Interaction Processes in Low and High-Resolution Coupled Climate Model Simulations for the Southeast Pacific

NASA Astrophysics Data System (ADS)

Porto da Silveira, I.; Zuidema, P.; Kirtman, B. P.

2017-12-01

The rugged topography of the Andes Cordillera along with strong coastal upwelling, strong sea surface temperatures (SST) gradients and extensive but geometrically-thin stratocumulus decks turns the Southeast Pacific (SEP) into a challenge for numerical modeling. In this study, hindcast simulations using the Community Climate System Model (CCSM4) at two resolutions were analyzed to examine the importance of resolution alone, with the parameterizations otherwise left unchanged. The hindcasts were initialized on January 1 with the real-time oceanic and atmospheric reanalysis (CFSR) from 1982 to 2003, forming a 10-member ensemble. The two resolutions are (0.1o oceanic and 0.5o atmospheric) and (1.125o oceanic and 0.9o atmospheric). The SST error growth in the first six days of integration (fast errors) and those resulted from model drift (saturated errors) are assessed and compared towards evaluating the model processes responsible for the SST error growth. For the high-resolution simulation, SST fast errors are positive (+0.3oC) near the continental borders and negative offshore (-0.1oC). Both are associated with a decrease in cloud cover, a weakening of the prevailing southwesterly winds and a reduction of latent heat flux. The saturated errors possess a similar spatial pattern, but are larger and are more spatially concentrated. This suggests that the processes driving the errors already become established within the first week, in contrast to the low-resolution simulations. These, instead, manifest too-warm SSTs related to too-weak upwelling, driven by too-strong winds and Ekman pumping. Nevertheless, the ocean surface tends to be cooler in the low-resolution simulation than the high-resolution due to a higher cloud cover. Throughout the integration, saturated SST errors become positive and could reach values up to +4oC. These are accompanied by upwelling dumping and a decrease in cloud cover. High and low resolution models presented notable differences in how SST errors variability drove atmospheric changes, especially because the high resolution is sensitive to resurgence regions. This allows the model to resolve cloud heights and establish different radiative feedbacks.

The Carbon-Land Model Intercomparison Project (C-LAMP): A Model-Data Comparison System for Evaluation of Coupled Biosphere-Atmosphere Models

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

Hoffman, Forrest M; Randerson, Jim; Thornton, Peter E

2009-01-01

The need to capture important climate feebacks in general circulation models (GCMs) has resulted in new efforts to include atmospheric chemistry and land and ocean biogeochemistry into the next generation of production climate models, now often referred to as Earth System Models (ESMs). While many terrestrial and ocean carbon models have been coupled to GCMs, recent work has shown that such models can yield a wide range of results, suggesting that a more rigorous set of offline and partially coupled experiments, along with detailed analyses of processes and comparisons with measurements, are warranted. The Carbon-Land Model Intercomparison Project (C-LAMP) providesmore » a simulation protocol and model performance metrics based upon comparisons against best-available satellite- and ground-based measurements (Hoffman et al., 2007). C-LAMP provides feedback to the modeling community regarding model improvements and to the measurement community by suggesting new observational campaigns. C-LAMP Experiment 1 consists of a set of uncoupled simulations of terrestrial carbon models specifically designed to examine the ability of the models to reproduce surface carbon and energy fluxes at multiple sites and to exhibit the influence of climate variability, prescribed atmospheric carbon dioxide (CO{sub 2}), nitrogen (N) deposition, and land cover change on projections of terrestrial carbon fluxes during the 20th century. Experiment 2 consists of partially coupled simulations of the terrestrial carbon model with an active atmosphere model exchanging energy and moisture fluxes. In all experiments, atmospheric CO{sub 2} follows the prescribed historical trajectory from C{sup 4}MIP. In Experiment 2, the atmosphere model is forced with prescribed sea surface temperatures (SSTs) and corresponding sea ice concentrations from the Hadley Centre; prescribed CO{sub 2} is radiatively active; and land, fossil fuel, and ocean CO{sub 2} fluxes are advected by the model. Both sets of experiments have been performed using two different terrestrial biogeochemistry modules coupled to the Community Land Model version 3 (CLM3) in the Community Climate System Model version 3 (CCSM3): The CASA model of Fung, et al., and the carbon-nitrogen (CN) model of Thornton. Comparisons against Ameriflus site measurements, MODIS satellite observations, NOAA flask records, TRANSCOM inversions, and Free Air CO{sub 2} Enrichment (FACE) site measurements, and other datasets have been performed and are described in Randerson et al. (2009). The C-LAMP diagnostics package was used to validate improvements to CASA and CN for use in the next generation model, CLM4. It is hoped that this effort will serve as a prototype for an international carbon-cycle model benchmarking activity for models being used for the Inter-governmental Panel on Climate Change (IPCC) Fifth Assessment Report. More information about C-LAMP, the experimental protocol, performance metrics, output standards, and model-data comparisons from the CLM3-CASA and CLM3-CN models are available at http://www.climatemodeling.org/c-lamp.« less

Tracking Extra Tropical Cyclones to Explore how the Jet Stream Shifted During The Last Glacial Maximum

NASA Astrophysics Data System (ADS)

Garrett, H.

2016-12-01

The behavior of the jet stream during the last glacial maximum (LGM 21ka) has been the focus of multiple studies but remains highly debated. Proxy data shows that during this time in the United States, the northwest was drier than modern conditions and the southwest was wetter than modern conditions. To explain this there are two competing hypothesis, one which suggests that the jet stream shifted uniformly south and the other which suggests a stronger jet that split shifting both north and south. For this study we used TECA, to reanalyze model out-put, looking at the frequency and patterns of Extra Tropical Cyclones (ETC's), which have been found to be steered by the jet stream. We used the CCSM4 model based on its agreement with proxy data, and compared data from both the LGM and pre-industrial time periods. Initial results show a dramatic shift of ETC's north by about 10º-15º degrees and a decrease in frequency compared to pre-industrial conditions, coupled with a less pronounced southward shift of 5º-10º degrees.This evidence supports the idea that the jet stream split during the LGM. A stronger understanding of jet stream behavior will help to improve future models and prediction capabilities to prepare for hydro-climate change in drought sensitive areas.

Downscaling Future Climate Change Projections for Water Resource Applications: A Case Study for Mesoamerica (Invited)

NASA Astrophysics Data System (ADS)

Oglesby, R. J.; Rowe, C. M.; Munoz-Arriola, F.

2013-12-01

Mesoamerica is a region that is potentially at severe risk due to future climate change. This is especially true for the water resources required for agriculture, human consumption, and hydroelectric power generation. Yet global climate models cannot properly resolve surface climate in the region, due to it's complex topography and nearness to oceans. Precipitation in particular is poorly handled. Further, Mesoamerica is hardly the only region worldwide for which these issues exist. To address this deficiency, a series of high-resolution (4-12 km) dynamical downscaling simulations of future climate change between now and 2060 have been made for Mesoamerica and the Caribbean. We used the Weather Research and Forecasting (WRF) regional climate model to downscale results from the NCAR CCSM4 CMIP5 RCP8.5 global simulation. The entire region is covered at 12 km horizontal spatial resolution, with as much as possible (especially in mountainous regions) at 4 km. We compare a control period (2006-2010) with 50 years into the future (2056-2060). Basic results for surface climate will be presented, as well as a developing strategy for explicitly employing these results in projecting the implications for water resources in the region. Connections will also be made to other regions around the globe that could benefit from this type of integrated modeling and analysis.

Who's driving?: Separating Fire, CO2, and Climate Change Influences on Vegetation and Carbon Dynamics on MC2 Results for Western Oregon and Washington, United States

NASA Astrophysics Data System (ADS)

Sheehan, T.; Bachelet, D. M.; Ferschweiler, K.

2016-12-01

For Oregon and Washington west of the Cascade Mountain crest, results from the MC2 global dynamic vegetation model have projected a shift in potential vegetation type from predominantly conifer to predominantly mixed forest over the 21st century, with a shift from mixed to conifer in some areas. Carbon stocks have been projected to fall over this period. We ran MC2 using the CCSM4 RCP 8.5 climate future downscaled to 2.5 arc minute resolution with 5 different configurations: no fire; assumed ignitions without fire suppression; assumed ignitions with fire suppression; assumed ignitions with fire suppression and with CO2 concentration held at the preindustrial level; and stochastic ignitions without fire suppression. Results show that vegetation change is the result of climate change alone, while carbon is influenced by both fire occurrence and CO2-induced increased water use efficiency. While model results do not indicate a large change in carbon dynamics concomitant with the shift in vegetation, it is reasonable to expect that a change in conditions resulting in such a change in vegetation type would stress the existing vegetation resulting in some mortality and loss of live carbon.

The Global and Local Climatic Response to the Collapse of the West Antarctic Ice Sheet

NASA Astrophysics Data System (ADS)

Huybers, K. M.; Singh, H.; Steiger, N. J.; Frierson, D. M.; Steig, E. J.; Bitz, C. M.

2014-12-01

Glaciologists have suggested that a relatively small external forcing may compromise the stability of the West Antarctic Ice Sheet (WAIS). Further, there is compelling physical evidence that the WAIS has collapsed in the past, at times when the mean global temperature was only a few degrees warmer than it is today. In addition to a rapid increase in global sea level, the collapse of the WAIS could also affect the global circulation of the atmosphere. Ice sheets are some of the largest topographic features on Earth, causing large regional anomalies in albedo and radiative balance. Our work uses idealized aquaplanet models in tandem with a fully coupled ocean/atmosphere/sea-ice model (CCSM4) to compare the atmospheric, radiative, and oceanic response to a complete loss of the WAIS. Initial findings indicate that the loss of the WAIS leads to a weakening and equator-ward shift of the zonal winds, a development of strong zonal asymmetries in the meridional wind, and a northward migration of the Intertropical Convergence Zone. We aim to characterize how the local and global climate is affected by the presence of the WAIS, and how changes in the distribution of Southern Hemisphere ice may be represented in the proxy record.

Isolating the atmospheric circulation response to Arctic sea-ice loss in the coupled climate system

NASA Astrophysics Data System (ADS)

Kushner, Paul; Blackport, Russell

2017-04-01

In the coupled climate system, projected global warming drives extensive sea-ice loss, but sea-ice loss drives warming that amplifies and can be confounded with the global warming process. This makes it challenging to cleanly attribute the atmospheric circulation response to sea-ice loss within coupled earth-system model (ESM) simulations of greenhouse warming. In this study, many centuries of output from coupled ocean/atmosphere/land/sea-ice ESM simulations driven separately by sea-ice albedo reduction and by projected greenhouse-dominated radiative forcing are combined to cleanly isolate the hemispheric scale response of the circulation to sea-ice loss. To isolate the sea-ice loss signal, a pattern scaling approach is proposed in which the local multidecadal mean atmospheric response is assumed to be separately proportional to the total sea-ice loss and to the total low latitude ocean surface warming. The proposed approach estimates the response to Arctic sea-ice loss with low latitude ocean temperatures fixed and vice versa. The sea-ice response includes a high northern latitude easterly zonal wind response, an equatorward shift of the eddy driven jet, a weakening of the stratospheric polar vortex, an anticyclonic sea level pressure anomaly over coastal Eurasia, a cyclonic sea level pressure anomaly over the North Pacific, and increased wintertime precipitation over the west coast of North America. Many of these responses are opposed by the response to low-latitude surface warming with sea ice fixed. However, both sea-ice loss and low latitude surface warming act in concert to reduce storm track strength throughout the mid and high latitudes. The responses are similar in two related versions of the National Center for Atmospheric Research earth system models, apart from the stratospheric polar vortex response. Evidence is presented that internal variability can easily contaminate the estimates if not enough independent climate states are used to construct them. References: Blackport, R. and P. Kushner, 2017: Isolating the atmospheric circulation response to Arctic sea-ice loss in the coupled climate system. J. Climate, in press. Blackport, R. and P. Kushner, 2016: The Transient and Equilibrium Climate Response to Rapid Summertime Sea Ice Loss in CCSM4. J. Climate, 29, 401-417, doi: 10.1175/JCLI-D-15-0284.1.

Diagnostic Evaluation of Nmme Precipitation and Temperature Forecasts for the Continental United States

NASA Astrophysics Data System (ADS)

Karlovits, G. S.; Villarini, G.; Bradley, A.; Vecchi, G. A.

2014-12-01

Forecasts of seasonal precipitation and temperature can provide information in advance of potentially costly disruptions caused by flood and drought conditions. The consequences of these adverse hydrometeorological conditions may be mitigated through informed planning and response, given useful and skillful forecasts of these conditions. However, the potential value and applicability of these forecasts is unavoidably linked to their forecast quality. In this work we evaluate the skill of four global circulation models (GCMs) part of the North American Multi-Model Ensemble (NMME) project in forecasting seasonal precipitation and temperature over the continental United States. The GCMs we consider are the Geophysical Fluid Dynamics Laboratory (GFDL)-CM2.1, NASA Global Modeling and Assimilation Office (NASA-GMAO)-GEOS-5, The Center for Ocean-Land-Atmosphere Studies - Rosenstiel School of Marine & Atmospheric Science (COLA-RSMAS)-CCSM3, Canadian Centre for Climate Modeling and Analysis (CCCma) - CanCM4. These models are available at a resolution of 1-degree and monthly, with a minimum forecast lead time of nine months, up to one year. These model ensembles are compared against gridded monthly temperature and precipitation data created by the PRISM Climate Group, which represent the reference observation dataset in this work. Aspects of forecast quality are quantified using a diagnostic skill score decomposition that allows the evaluation of the potential skill and conditional and unconditional biases associated with these forecasts. The evaluation of the decomposed GCM forecast skill over the continental United States, by season and by lead time allows for a better understanding of the utility of these models for flood and drought predictions. Moreover, it also represents a diagnostic tool that could provide model developers feedback about strengths and weaknesses of their models.

Upper-Ocean Heat Balance Processes and the Walker Circulation in CMIP5 Model Projections

NASA Technical Reports Server (NTRS)

Robertson, F. R.; Roberts, J. B.; Funk, C.; Lyon, B.; Ricciardulli, L.

2012-01-01

Considerable uncertainty remains as to the importance of mechanisms governing decadal and longer variability of the Walker Circulation, its connection to the tropical climate system, and prospects for tropical climate change in the face of anthropogenic forcing. Most contemporary climate models suggest that in response to elevated CO2 and a warmer but more stratified atmosphere, the required upward mass flux in tropical convection will diminish along with the Walker component of the tropical mean circulation as well. Alternatively, there is also evidence to suggest that the shoaling and increased vertical stratification of the thermocline in the eastern Pacific will enable a muted SST increase there-- preserving or even enhancing some of the dynamical forcing for the Walker cell flow. Over the past decade there have been observational indications of an acceleration in near-surface easterlies, a strengthened Pacific zonal SST gradient, and globally-teleconnected dislocations in precipitation. But is this evidence in support of an ocean dynamical thermostat process posited to accompany anthropogenic forcing, or just residual decadal fluctuations associated with variations in warm and cold ENSO events and other stochastic forcing? From a modeling perspective we try to make headway on this question by examining zonal variations in surface energy fluxes and dynamics governing tropical upper ocean heat content evolution in the WCRP CMIP5 model projections. There is some diversity among model simulations; for example, the CCSM4 indicates net ocean warming over the IndoPacific region while the CSIRO model concentrates separate warming responses over the central Pacific and Indian Ocean regions. The models, as with observations, demonstrate strong local coupling between variations in column water vapor, downward surface longwave radiation and SST; but the spatial patterns of changes in the sign of this relationship differ among models and, for models as a whole, with observations. Our analysis focuses initially on probing the inter-model differences in energy fluxes / transports and Walker Circulation response to forcing. We then attempt to identify statistically the El Nino- / La Nina-related ocean heat content variability unique to each model and regress out the associated energy flux, ocean heat transport and Walker response on these shorter time scales for comparison to that of the anthropogenic signals.

Linking climate change and karst hydrology to evaluate species vulnerability: The Edwards and Madison aquifers (Invited)

NASA Astrophysics Data System (ADS)

Mahler, B. J.; Long, A. J.; Stamm, J. F.; Poteet, M.; Symstad, A.

2013-12-01

Karst aquifers present an extreme case of flow along structurally variable pathways, making them highly dynamic systems and therefore likely to respond rapidly to climate change. In turn, many biological communities and ecosystems associated with karst are sensitive to hydrologic changes. We explored how three sites in the Edwards aquifer (Texas) and two sites in the Madison aquifer (South Dakota) might respond to projected climate change from 2011 to 2050. Ecosystems associated with these karst aquifers support federally listed endangered and threatened species and state-listed species of concern, including amphibians, birds, insects, and plants. The vulnerability of selected species associated with projected climate change was assessed. The Advanced Research Weather and Research Forecasting (WRF) model was used to simulate projected climate at a 36-km grid spacing for three weather stations near the study sites, using boundary and initial conditions from the global climate model Community Climate System Model (CCSM3) and an A2 emissions scenario. Daily temperature and precipitation projections from the WRF model were used as input for the hydrologic Rainfall-Response Aquifer and Watershed Flow (RRAWFLOW) model and the Climate Change Vulnerability Index (CCVI) model. RRAWFLOW is a lumped-parameter model that simulates hydrologic response at a single site, combining the responses of quick and slow flow that commonly characterize karst aquifers. CCVI uses historical and projected climate and hydrologic metrics to determine the vulnerability of selected species on the basis of species exposure to climate change, sensitivity to factors associated with climate change, and capacity to adapt to climate change. An upward trend in temperature was projected for 2011-2050 at all three weather stations; there was a trend (downward) in annual precipitation only for the weather station in Texas. A downward trend in mean annual spring flow or groundwater level was projected for all of the Edwards sites, but there was no significant trend for the Madison sites. Of 16 Edwards aquifer species evaluated (four amphibians, six arthropods, one fish, one mollusk, and four plants), 12 were scored as highly or moderately vulnerable under the projected climate change scenario. In contrast, all of the 8 Madison aquifer species evaluated (two mammals, one bird, one mollusk, and four plants) were scored as moderately vulnerable, stable, or intermediate between the two. The inclusion of hydrologic projections in the vulnerability assessment was essential for interpreting the effects of climate change on aquatic species of conservations concern, such as endemic salamanders. The linkage of climate, hydrologic, and vulnerability models provided a bridge to project the effects of global climate change on local karst aquifer and stream systems and selected species.

Water Isotope Proxy-Proxy and Proxy-Model Convergence for Late Pleistocene East Asian Monsoon Rainfall Reconstructions

NASA Astrophysics Data System (ADS)

Clemens, S. C.; Holbourn, A.; Kubota, Y.; Lee, K. E.; Liu, Z.; Chen, G.

2017-12-01

Confidence in reconstruction of East Asian paleomonsoon rainfall using precipitation isotope proxies is a matter of considerable debate, largely due to the lack of correlation between precipitation amount and isotopic composition in the present climate. We present four new, very highly resolved records spanning the past 300,000 years ( 200 year sample spacing) from IODP Site U1429 in the East China Sea. We demonstrate that all the orbital- and millennial-scale variance in the onshore Yangtze River Valley speleothem δ18O record1 is also embedded in the offshore Site U1429 seawater δ18O record (derived from the planktonic foraminifer Globigerinoides ruber and sea surface temperature reconstructions). Signal replication in these two independent terrestrial and marine archives, both controlled by the same monsoon system, uniquely identifies δ18O of precipitation as the primary driver of the precession-band variance in both records. This proxy-proxy convergence also eliminates a wide array of other drivers that have been called upon as potential contaminants to the precipitation δ18O signal recorded by these proxies. We compare East Asian precipitation isotope proxy records to precipitation amount from a CCSM3 transient climate model simulation of the past 300,000 years using realistic insolation, ice volume, greenhouse gasses, and sea level boundary conditions. This model-proxy comparison suggests that both Yangtze River Valley precipitation isotope proxies (seawater and speleothem δ18O) track changes in summer-monsoon rainfall amount at orbital time scales, as do precipitation isotope records from the Pearl River Valley2 (leaf wax δ2H) and Borneo3 (speleothem δ18O). Notably, these proxy records all have significantly different spectral structure indicating strongly regional rainfall patterns that are also consistent with model results. Transient, isotope-enabled model simulations will be necessary to more thoroughly evaluate these promising results, and to evaluate potentially distinct regional mechanisms linking rainfall amount to precipitation isotopes at orbital and millennial time scales in other monsoon regions. 1 Cheng et al., 10.1038/nature18591 2 Thomas et al., 10.1130/G36289.1 3 Carolin et al., 10.1016/j.epsl.2016.01.028

LPJ-GUESS Simulated North America Vegetation for 21-0 ka Using the TraCE-21ka Climate Simulation

NASA Astrophysics Data System (ADS)

Shafer, S. L.; Bartlein, P. J.

2016-12-01

Transient climate simulations that span multiple millennia (e.g., TraCE-21ka) have become more common as computing power has increased, allowing climate models to complete long simulations in relatively short periods of time (i.e., months). These climate simulations provide information on the potential rate, variability, and spatial expression of past climate changes. They also can be used as input data for other environmental models to simulate transient changes for different components of paleoenvironmental systems, such as vegetation. Long, transient paleovegetation simulations can provide information on a range of ecological processes, describe the spatial and temporal patterns of changes in species distributions, and identify the potential locations of past species refugia. Paleovegetation simulations also can be used to fill in spatial and temporal gaps in observed paleovegetation data (e.g., pollen records from lake sediments) and to test hypotheses of past vegetation change. We used the TraCE-21ka transient climate simulation for 21-0 ka from CCSM3, a coupled atmosphere-ocean general circulation model. The TraCE-21ka simulated temperature, precipitation, and cloud data were regridded onto a 10-minute grid of North America. These regridded climate data, along with soil data and atmospheric carbon dioxide concentrations, were used as input to LPJ-GUESS, a general ecosystem model, to simulate North America vegetation from 21-0 ka. LPJ-GUESS simulates many of the processes controlling the distribution of vegetation (e.g., competition), although some important processes (e.g., dispersal) are not simulated. We evaluate the LPJ-GUESS-simulated vegetation (in the form of plant functional types and biomes) for key time periods and compare the simulated vegetation with observed paleovegetation data, such as data archived in the Neotoma Paleoecology Database. In general, vegetation simulated by LPJ-GUESS reproduces the major North America vegetation patterns (e.g., forest, grassland) with regional areas of disagreement between simulated and observed vegetation. We describe the regions and time periods with the greatest data-model agreement and disagreement, and discuss some of the strengths and weaknesses of both the simulated climate and simulated vegetation data.

Evaluation of a new satellite-based precipitation dataset for climate studies in the Xiang River basin, Southern China

NASA Astrophysics Data System (ADS)

Zhu, Q.; Xu, Y. P.; Hsu, K. L.

2017-12-01

A new satellite-based precipitation dataset, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) with long-term time series dating back to 1983 can be one valuable dataset for climate studies. This study investigates the feasibility of using PERSIANN-CDR as a reference dataset for climate studies. Sixteen CMIP5 models are evaluated over the Xiang River basin, southern China, by comparing their performance on precipitation projection and streamflow simulation, particularly on extreme precipitation and streamflow events. The results show PERSIANN-CDR is a valuable dataset for climate studies, even on extreme precipitation events. The precipitation estimates and their extreme events from CMIP5 models are improved significantly compared with rain gauge observations after bias-correction by the PERSIANN-CDR precipitation estimates. Given streamflows simulated with raw and bias-corrected precipitation estimates from 16 CMIP5 models, 10 out of 16 are improved after bias-correction. The impact of bias-correction on extreme events for streamflow simulations are unstable, with eight out of 16 models can be clearly claimed they are improved after the bias-correction. Concerning the performance of raw CMIP5 models on precipitation, IPSL-CM5A-MR excels the other CMIP5 models, while MRI-CGCM3 outperforms on extreme events with its better performance on six extreme precipitation metrics. Case studies also show that raw CCSM4, CESM1-CAM5, and MRI-CGCM3 outperform other models on streamflow simulation, while MIROC5-ESM-CHEM, MIROC5-ESM and IPSL-CM5A-MR behaves better than the other models after bias-correction.

Coupled Global-Regional Climate Model Simulations of Future Changes in Hydrology over Central America

NASA Astrophysics Data System (ADS)

Oglesby, R. J.; Erickson, D. J.; Hernandez, J. L.; Irwin, D.

2005-12-01

Central America covers a relatively small area, but is topographically very complex, has long coast-lines, large inland bodies of water, and very diverse land cover which is both natural and human-induced. As a result, Central America is plagued by hydrologic extremes, especially major flooding and drought events, in a region where many people still barely manage to eke out a living through subsistence. Therefore, considerable concern exists about whether these extreme events will change, either in magnitude or in number, as climate changes in the future. To address this concern, we have used global climate model simulations of future climate change to drive a regional climate model centered on Central America. We use the IPCC `business as usual' scenario 21st century run made with the NCAR CCSM3 global model to drive the regional model MM5 at 12 km resolution. We chose the `business as usual' scenario to focus on the largest possible changes that are likely to occur. Because we are most interested in near-term changes, our simulations are for the years 2010, 2015, and 2025. A long `present-day run (for 2005) allows us to distinguish between climate variability and any signal due to climate change. Furthermore, a multi-year run with MM5 forced by NCEP reanalyses allows an assessment of how well the coupled global-regional model performs over Central America. Our analyses suggest that the coupled model does a credible job simulating the current climate and hydrologic regime, though lack of sufficient observations strongly complicates this comparison. The suite of model runs for the future years is currently nearing completion, and key results will be presented at the meeting.

Historical and Possible Future Changes in Permafrost and Active Layer Thickness in Alaska: Implications to Landscape Changes and Permafrost Carbon Pool.

NASA Astrophysics Data System (ADS)

Marchenko, S. S.; Helene, G.; Euskirchen, E. S.; Breen, A. L.; McGuire, D.; Rupp, S. T.; Romanovsky, V. E.; Walsh, J. E.

2017-12-01

The Soil Temperature and Active Layer Thickness (ALT) Gridded Data was developed to quantify the nature and rate of permafrost degradation and its impact on ecosystems, infrastructure, CO2 and CH4 fluxes and net C storage following permafrost thaw across Alaska. To develop this database, we used the process-based permafrost dynamics model GIPL2 developed in the Geophysical Institute Permafrost Lab, UAF and which is the permafrost module of the Integrated Ecosystem Model (IEM) for Alaska and Northwest Canada. The climate forcing data for simulations were developed by the Scenarios Network for Alaska and Arctic Planning (SNAP, http://www.snap.uaf.edu/). These data are based on the historical CRU3.1 data set for the retrospective analysis period (1901-2009) and the five model averaged data were derived from the five CMIP5/AR5 IPCC Global Circulation Models that performed the best in Alaska and other northern regions: NCAR-CCSM4, GFDL-CM3, GISS-E2-R, IPSL-CM5A-LR, MRI-CGCM3. A composite of all five-model outputs for the RCP4.5 and RCP8.5 were used in these particular permafrost dynamics simulations. Data sets were downscaled to a 771 m resolution, using the Parameter-elevation Regressions on Independent Slopes Model (PRISM) climatology. Additional input data (snow characteristics, soil thermal properties, soil water content, organic matter accumulation or its loss due to fire, etc.) came from the Terrestrial Ecosystem Model (TEM) and the ALFRESCO (ALaska FRame-based EcoSystem COde) model simulations. We estimated the dynamics of permafrost temperature, active layer thickness, area occupied by permafrost, and volume of seasonally thawed soils within the 4.75 upper meters (original TEM soil column) across the Alaska domain. Simulations of future changes in permafrost indicate that, by the end of the 21st century, late-Holocene permafrost in Alaska will be actively thawing at all locations and that some Late Pleistocene carbon-rich peatlands underlain by permafrost will start to thaw at some locations. The modeling results also indicate how different types of ecosystems affect the thermal state of permafrost and its stability. The release of carbon and the net effect of this thawing depends on the balance between increased productivity and respiration, which depend, in part, on soil moisture dynamics.

Predicting habitat suitability and geographic distribution of anchovy (Engraulis ringens) due to climate change in the coastal areas off Chile

NASA Astrophysics Data System (ADS)

Silva, Claudio; Andrade, Isabel; Yáñez, Eleuterio; Hormazabal, Samuel; Barbieri, María Ángela; Aranis, Antonio; Böhm, Gabriela

2016-08-01

The effects of climate change on ocean conditions will have impacts on fish stocks, primarily through physiological and behavioural effects, such as changes in growth, reproduction, mortality and distribution. Habitat and distribution predictions for marine fishery species under climate change scenarios are important for understanding the overall impacts of such global changes on the human society and on the ecosystem. In this study, we examine the impacts of climate change on anchovy fisheries off Chile using predicted changes in global models according to the National Centre for Atmospheric Research (NCAR) Community Climate System Model 3.0 (CCSM3) and IPCC high future CO2 emission scenario A2, habitat suitability index (HSI) models and satellite-based sea surface temperature (SST) and chlorophyll-a (Chl-a) estimates from high-resolution regional models for the simulation period 2015-2065. Predictions of SST from global climate models were regionalised using the Delta statistical downscaling technique. Predictions of chlorophyll-a were developed using historical Chl-a and SST (2003-2013) satellite data and applying a harmonic model. The results show an increase in SST of up to 2.5 °C by 2055 in the north and central-south area for an A2 scenario. The habitat suitability index model was developed using historical (2001-2011) monthly fisheries and environmental data. The catch per unit effort (CPUE) was used as an abundance index in developing the HSI models and was calculated as the total catch (ton) by hold capacity (m3) in a 10‧ × 10‧ fishing grid square of anchovy, integrated over one month of fishing activity. The environmental data included the distance to coast (DC), thermal (SST) and food availability (Chl-a) conditions. The HSI modelling consists of estimating SI curves based on available evidence regarding the optimum range of environmental conditions for anchovy and estimating an integrated HSI using the Arithmetic Mean Model (AMM) method. The results of this work show that the model has produced robust estimates of habitat suitability and geographic distribution off Chile and has been especially effective in capturing the spatial and temporal variability of CPUE. Using IDRISI geographical information system (GIS), these HSI models simulated monthly changes in the habitat suitability (i.e., relative abundance) and distribution of anchovy off Chile forced by changes in the regionalised SST and Chl-a as projected by the NCAR model under the A2 emission scenario. The simulations predicted a moderate negative change of 17% and 13% for the north and central-south areas, respectively, in the habitat suitability (i.e., potential relative abundance) of anchovy by 2055.

Modeled response of the West Nile virus vector Culex quinquefasciatus to changing climate using the dynamic mosquito simulation model

NASA Astrophysics Data System (ADS)

Morin, Cory W.; Comrie, Andrew C.

2010-09-01

Climate can strongly influence the population dynamics of disease vectors and is consequently a key component of disease ecology. Future climate change and variability may alter the location and seasonality of many disease vectors, possibly increasing the risk of disease transmission to humans. The mosquito species Culex quinquefasciatus is a concern across the southern United States because of its role as a West Nile virus vector and its affinity for urban environments. Using established relationships between atmospheric variables (temperature and precipitation) and mosquito development, we have created the Dynamic Mosquito Simulation Model (DyMSiM) to simulate Cx. quinquefasciatus population dynamics. The model is driven with climate data and validated against mosquito count data from Pasco County, Florida and Coachella Valley, California. Using 1-week and 2-week filters, mosquito trap data are reproduced well by the model ( P < 0.0001). Dry environments in southern California produce different mosquito population trends than moist locations in Florida. Florida and California mosquito populations are generally temperature-limited in winter. In California, locations are water-limited through much of the year. Using future climate projection data generated by the National Center for Atmospheric Research CCSM3 general circulation model, we applied temperature and precipitation offsets to the climate data at each location to evaluate mosquito population sensitivity to possible future climate conditions. We found that temperature and precipitation shifts act interdependently to cause remarkable changes in modeled mosquito population dynamics. Impacts include a summer population decline from drying in California due to loss of immature mosquito habitats, and in Florida a decrease in late-season mosquito populations due to drier late summer conditions.

A spurious warming trend in the NMME equatorial Pacific SST hindcasts

NASA Astrophysics Data System (ADS)

Shin, Chul-Su; Huang, Bohua

2017-06-01

Using seasonal hindcasts of six different models participating in the North American Multimodel Ensemble project, the trend of the predicted sea surface temperature (SST) in the tropical Pacific for 1982-2014 at each lead month and its temporal evolution with respect to the lead month are investigated for all individual models. Since the coupled models are initialized with the observed ocean, atmosphere, land states from observation-based reanalysis, some of them using their own data assimilation process, one would expect that the observed SST trend is reasonably well captured in their seasonal predictions. However, although the observed SST features a weak-cooling trend for the 33-year period with La Niña-like spatial pattern in the tropical central-eastern Pacific all year round, it is demonstrated that all models having a time-dependent realistic concentration of greenhouse gases (GHG) display a warming trend in the equatorial Pacific that amplifies as the lead-time increases. In addition, these models' behaviors are nearly independent of the starting month of the hindcasts although the growth rates of the trend vary with the lead month. This key characteristic of the forecasted SST trend in the equatorial Pacific is also identified in the NCAR CCSM3 hindcasts that have the GHG concentration for a fixed year. This suggests that a global warming forcing may not play a significant role in generating the spurious warming trend of the coupled models' SST hindcasts in the tropical Pacific. This model SST trend in the tropical central-eastern Pacific, which is opposite to the observed one, causes a developing El Niño-like warming bias in the forecasted SST with its peak in boreal winter. Its implications for seasonal prediction are discussed.

Indo-Pacific Variability on Seasonal to Multidecadal Time Scales. Part I: Intrinsic SST Modes in Models and Observations

NASA Astrophysics Data System (ADS)

Slawinska, Joanna; Giannakis, Dimitrios

2017-07-01

The variability of Indo-Pacific SST on seasonal to multidecadal timescales is investigated using a recently introduced technique called nonlinear Laplacian spectral analysis (NLSA). Through this technique, drawbacks associated with ad hoc pre-filtering of the input data are avoided, enabling recovery of low-frequency and intermittent modes not previously accessible via classical approaches. Here, a multiscale hierarchy of spatiotemporal modes is identified for Indo-Pacific SST in millennial control runs of CCSM4 and CM3 and in HadISST data. On interannual timescales, a mode with spatiotemporal patterns corresponding to the fundamental component of ENSO emerges, along with ENSO-modulated annual modes consistent with combination mode theory. The ENSO combination modes also feature prominent activity in the Indian Ocean, explaining significant fraction of the SST variance in regions associated with the Indian Ocean dipole. A pattern resembling the tropospheric biennial oscillation emerges in addition to ENSO and the associated combination modes. On multidecadal timescales, the dominant NLSA mode in the model data is predominantly active in the western tropical Pacific. The interdecadal Pacific oscillation also emerges as a distinct NLSA mode, though with smaller explained variance than the western Pacific multidecadal mode. Analogous modes on interannual and decadal timescales are also identified in HadISST data for the industrial era, as well as in model data of comparable timespan, though decadal modes are either absent or of degraded quality in these datasets.

Precipitation event tracking reveals that precipitation characteristics respond differently under seasonal, interannual, and anthropogenic forcing

NASA Astrophysics Data System (ADS)

Chen, C.; Chang, W.; Kong, W.; Wang, J.; Kotamarthi, V. R.; Stein, M.; Moyer, E. J.

2017-12-01

Change in precipitation characteristics is an especially concerning potential impact of climate change, and both model and observational studies suggest that increases in precipitation intensity are likely. However, studies to date have focused on mean accumulated precipitation rather than on the characteristics of individual events. We report here on a study using a novel rainstorm identification tracking algorithm (Chang et al. 2016) that allows evaluating changes in spatio-temporal characteristics of events. We analyze high-resolution precipitation from dynamically downscaled regional climate simulations over the continental U.S. (WRF driven by CCSM4) of present and future climate conditions. We show that precipitation events show distinct characteristic changes for natural seasonal and interannual variations and for anthropogenic greenhouse-gas forcing. In all cases, wetter seasons/years/future climate states are associated with increased precipitation intensity, but other precipitation characteristics respond differently to the different drivers. For example, under anthropogenic forcing, future wetter climate states involve smaller individual event sizes (partially offsetting their increased intensity). Under natural variability, however, wetter years involve larger mean event sizes. Event identification and tracking algorithms thus allow distinguishing drivers of different types of precipitation changes, and in relating those changes to large-scale processes.

Assesment of future river habitat suitability under climate change scenarios in a mesoscale Alpine watershed of Italy (Serio River, Italian Alps)

NASA Astrophysics Data System (ADS)

Groppelli, B.; Confortola, G.; Soncini, A.; Bocchiola, D.; Rosso, R.

2011-12-01

We merge hydraulic river modelling, use of suitability functions for fish guild colonization and hydrological modelling of catchment response to investigate future (until 2100) hydrological cycle and fish habitat suitability for an Alpine catchment in Italy, Serio river (drainage area 450 Km2, average altitude 1300 m a.s.l., main channel length ca. 36 km). Based upon detailed river channel morphology data for 73 river sections and direct local investigation we then set up and tune a quasi 2-D (i.e. with floodplains) hydraulic model for in channel flows hydraulics, depending upon daily in stream discharge. We then evaluate distributed values of hydraulic variables and therein composite habitat suitability indexes CS for a representative target species (brown trout, Salmo Trutta Fario L.), resulting into usable wetted area WUA for fish colonization. We consider both juvenile JUV and adults AD, and we evaluate the frequency (days in a year/season) of yearly/seasonal, spatially distributed and bulk (whole stream) habitat quality. We then provide synthetic indicators of (yearly/seasonal) suitability level and duration within the river. We then set up a minimal (T, P), properly tuned hydrological model able to mimick Serio river's hydrological cycle. We then use downscaled future precipitation and temperature from three general circulation models, GCMs (PCM, CCSM3, and HadCM3) available within the IPCC's data base chosen for the purpose based upon previous studies, to feed our hydrological model and provide projected hydrological regime of the catchment, together with modified habitat suitability. We then comment upon modified flow regime, habitat suitability as obtained and related uncertainty. The proposed results may be of use for river managers and may provide a template for investigation about future river habitat quality pending climate change.

Understanding Climate Uncertainty with an Ocean Focus

NASA Astrophysics Data System (ADS)

Tokmakian, R. T.

2009-12-01

Uncertainty in climate simulations arises from various aspects of the end-to-end process of modeling the Earth’s climate. First, there is uncertainty from the structure of the climate model components (e.g. ocean/ice/atmosphere). Even the most complex models are deficient, not only in the complexity of the processes they represent, but in which processes are included in a particular model. Next, uncertainties arise from the inherent error in the initial and boundary conditions of a simulation. Initial conditions are the state of the weather or climate at the beginning of the simulation and other such things, and typically come from observations. Finally, there is the uncertainty associated with the values of parameters in the model. These parameters may represent physical constants or effects, such as ocean mixing, or non-physical aspects of modeling and computation. The uncertainty in these input parameters propagates through the non-linear model to give uncertainty in the outputs. The models in 2020 will no doubt be better than today’s models, but they will still be imperfect, and development of uncertainty analysis technology is a critical aspect of understanding model realism and prediction capability. Smith [2002] and Cox and Stephenson [2007] discuss the need for methods to quantify the uncertainties within complicated systems so that limitations or weaknesses of the climate model can be understood. In making climate predictions, we need to have available both the most reliable model or simulation and a methods to quantify the reliability of a simulation. If quantitative uncertainty questions of the internal model dynamics are to be answered with complex simulations such as AOGCMs, then the only known path forward is based on model ensembles that characterize behavior with alternative parameter settings [e.g. Rougier, 2007]. The relevance and feasibility of using "Statistical Analysis of Computer Code Output" (SACCO) methods for examining uncertainty in ocean circulation due to parameter specification will be described and early results using the ocean/ice components of the CCSM climate model in a designed experiment framework will be shown. Cox, P. and D. Stephenson, Climate Change: A Changing Climate for Prediction, 2007, Science 317 (5835), 207, DOI: 10.1126/science.1145956. Rougier, J. C., 2007: Probabilistic Inference for Future Climate Using an Ensemble of Climate Model Evaluations, Climatic Change, 81, 247-264. Smith L., 2002, What might we learn from climate forecasts? Proc. Nat’l Academy of Sciences, Vol. 99, suppl. 1, 2487-2492 doi:10.1073/pnas.012580599.

The Role of Ocean Eddies in the Southern Ocean Response to Observed Greenhouse Gas Forcing

NASA Astrophysics Data System (ADS)

Bilgen, S. I.; Kirtman, B. P.

2017-12-01

The Southern Ocean (SO) is crucial to understanding the possible future response to a changing climate. This is a principal region where energy is conveyed to the ocean by the westerly winds and it is here that mesoscale ocean eddies field dominate meridional heat and momentum transport. Compared to the Arctic, the Antarctic and the surrounding SO have a "delayed warming" anthropogenic greenhouse gas (GHG) response. Understanding the role of the ocean dynamics in modulating the mesoscale atmosphere-ocean interactions in the SO in a fully coupled regime is crucial to efforts aimed at predicting the consequences of the warming and variability to the climate system. The response of model run at multiple resolutions (eddy permitting, eddy resolving) to both GHG forcing and historical forcing are examined in NCAR CCSM4 with four experiments. The first simulation, 0.5° atmosphere coupled to ocean and sea ice components with 1° resolution (LR). The second simulation uses the identical atmospheric model but coupled to 0.1° ocean and sea ice component models (HR). For the third and fourth experiments, the global ocean is simulated for LR an HR models, and a climate change scenario are produced by applying a fixed (present-day) CO2 concentration. The analysis focuses on the last 55 years of two individual 155 year simulations. We discuss results from a set of state-of-art model experiments in comparison with observational estimates and explore mechanisms by examining sea surface temperature, westerly winds, surface heat flux, ocean heat transport. In LR simulations, the patterns and mechanisms of SO changes under GHG forcing are similar to those over the historical period: warming is damped southward of the ACC and enhanced to the north, however major changes between the HR simulations are explored. We find that in recent decades the Southern Annual Mode has shown a distinct upward trend, the result of an anthropogenic global warming. Also, HR simulations show that strengthening of the SAM and associated surface wind stress have been invoked to posit enhancement in the strength of the upwelling of the MOC, and increases eddy activity of the ACC. The results also indicate that eddy-permitting models are not able to capture the eddy-driven SST response since ocean dynamics is playing crucial role in the HR simulation but not in the LR models.

Implications of global warming for regional climate and water resources of tropical islands: Case studies over Sri Lanka and Puerto Rico

NASA Astrophysics Data System (ADS)

Mawalagedara, R.; Kumar, D.; Oglesby, R. J.; Ganguly, A. R.

2013-12-01

The IPCC AR4 identifies small islands as particularly vulnerable to climate change. Here we consider the cases of two tropical islands: Sri Lanka in the Indian Ocean and Puerto Rico in the Caribbean. The islands share a predominantly tropical climate with diverse topography and hence significant spatial variability of regional climate. Seasonal variability in temperatures is relatively small, but spatial variations can be large owing to topography. Precipitation mechanisms and patterns over the two islands are different however. Sri Lanka receives a majority of the annual rainfall from the summer and winter monsoons, with convective rainfall dominating in the inter-monsoon period. Rainfall generating mechanisms over Puerto Rico can range from orographic lifting, disturbances embedded in Easterly waves and synoptic frontal systems. Here we compare the projected changes in the regional and seasonal means and extremes of temperature and precipitation over the two islands during the middle of this century with the present conditions. Two 5-year regional climate model runs for each region, representing the present (2006-2010) and future (2056-2060) conditions, are performed using the Weather Research and Forecasting model with the lateral boundary conditions provided using the output from CCSM4 RCP8.5 greenhouse gas emissions pathway simulation from the CMIP5 ensemble. The consequences of global warming for water resources and the overall economy are examined. While both economies have substantial contributions from tourism, there are major differences: The agricultural sector is much more important over Sri Lanka compared to Puerto Rico, while the latter exhibits no recent growth in population or in urbanization trends unlike the former. Policy implications for water sustainability and security are discussed, which highlight how despite the differences, certain lessons learned may generalize across the two relatively small tropical islands, which in turn have diverse economic, infrastructural, and societal constraints.

Forecasting distributions of an aquatic invasive species (Nitellopsis obtusa) under future climate scenarios

PubMed Central

Varela, Sara; Larkin, Daniel J.; Phelps, Nicholas B. D.

2017-01-01

Starry stonewort (Nitellopsis obtusa) is an alga that has emerged as an aquatic invasive species of concern in the United States. Where established, starry stonewort can interfere with recreational uses of water bodies and potentially have ecological impacts. Incipient invasion of starry stonewort in Minnesota provides an opportunity to predict future expansion in order to target early detection and strategic management. We used ecological niche models to identify suitable areas for starry stonewort in Minnesota based on global occurrence records and present-day and future climate conditions. We assessed sensitivity of forecasts to different parameters, using four emission scenarios (i.e., RCP 2.6, RCP 4.5, RCP 6, and RCP 8.5) from five future climate models (i.e., CCSM, GISS, IPSL, MIROC, and MRI). From our niche model analyses, we found that (i) occurrences from the entire range, instead of occurrences restricted to the invaded range, provide more informed models; (ii) default settings in Maxent did not provide the best model; (iii) the model calibration area and its background samples impact model performance; (iv) model projections to future climate conditions should be restricted to analogous environments; and (v) forecasts in future climate conditions should include different future climate models and model calibration areas to better capture uncertainty in forecasts. Under present climate, the most suitable areas for starry stonewort are predicted to be found in central and southeastern Minnesota. In the future, suitable areas for starry stonewort are predicted to shift in geographic range under some future climate models and to shrink under others, with most permutations indicating a net decrease of the species’ suitable range. Our suitability maps can serve to design short-term plans for surveillance and education, while future climate models suggest a plausible reduction of starry stonewort spread in the long-term if the trends in climate warming remain. PMID:28704433

Forecasting distributions of an aquatic invasive species (Nitellopsis obtusa) under future climate scenarios.

PubMed

Romero-Alvarez, Daniel; Escobar, Luis E; Varela, Sara; Larkin, Daniel J; Phelps, Nicholas B D

2017-01-01

Starry stonewort (Nitellopsis obtusa) is an alga that has emerged as an aquatic invasive species of concern in the United States. Where established, starry stonewort can interfere with recreational uses of water bodies and potentially have ecological impacts. Incipient invasion of starry stonewort in Minnesota provides an opportunity to predict future expansion in order to target early detection and strategic management. We used ecological niche models to identify suitable areas for starry stonewort in Minnesota based on global occurrence records and present-day and future climate conditions. We assessed sensitivity of forecasts to different parameters, using four emission scenarios (i.e., RCP 2.6, RCP 4.5, RCP 6, and RCP 8.5) from five future climate models (i.e., CCSM, GISS, IPSL, MIROC, and MRI). From our niche model analyses, we found that (i) occurrences from the entire range, instead of occurrences restricted to the invaded range, provide more informed models; (ii) default settings in Maxent did not provide the best model; (iii) the model calibration area and its background samples impact model performance; (iv) model projections to future climate conditions should be restricted to analogous environments; and (v) forecasts in future climate conditions should include different future climate models and model calibration areas to better capture uncertainty in forecasts. Under present climate, the most suitable areas for starry stonewort are predicted to be found in central and southeastern Minnesota. In the future, suitable areas for starry stonewort are predicted to shift in geographic range under some future climate models and to shrink under others, with most permutations indicating a net decrease of the species' suitable range. Our suitability maps can serve to design short-term plans for surveillance and education, while future climate models suggest a plausible reduction of starry stonewort spread in the long-term if the trends in climate warming remain.

Water, climate change and society in Bangladesh

NASA Astrophysics Data System (ADS)

Thiele-Eich, Insa; Aßheuer, Tibor; Simmer, Clemens

2017-04-01

Due to its location in the extensive Ganges-Brahmaputra-Meghna river delta, Bangladesh faces multiple natural hazards, in particular flooding, droughts and sea-level rise. In addition to climate change, transboundary water sharing issues resulting from dam structures such as Farakka Barrage complicate a prognosis on how the rapidly growing population will be affected in the 21st century. This is particularly important as our previous research suggests that the Greater Dhaka population already experiences a significant increase in mortality during droughts (Thiele-Eich et al., 2015). We attempt to explore the complex interactions between the hydrological system under climate change and anthropogenic impacts due to dams as well as a growing population. Our approach consists of a quantitative assessment of climate change using over fourty years of meteorological data (Bangladesh Meteorological Department) and hydrological data (Bangladesh Water Development Board), and CCSM4 climate model output (NCAR, 1950-2100). In addition to an extensive literature review, we also conducted qualitative interviews with slum dwellers in the megacity Dhaka, the capital of Bangladesh. Results show that significant changes in flood characteristics are expected for the later part of the 21st century, although they are difficult to quantify down to exact numbers due to large uncertainties. These changes take place over longer stretches of time and thus enable the population of Bangladesh to adapt slowly. Resources such as social capital, which is one of the main tools for slum dwellers to be able to cope with flooding can be altered over time, and as such the system can be considered overall stable and resilient. The presented results will also focus on how the riparian and coastal population is impacted by the interplay of natural changes such as sea-level rise and anthropogenic changes such as Farakka Barrage and the associated reduction in dry season flow. Thiele-Eich, I.; Burkart, K.; Simmer, C. Trends in Water Level and Flooding in Dhaka, Bangladesh and Their Impact on Mortality. Int. J. Environ. Res. Public Health 2015, 12, 1196-1215.

Climate Modelling Shows Increased Risk to Eucalyptus sideroxylon on the Eastern Coast of Australia Compared to Eucalyptus albens

PubMed Central

Shabani, Farzin; Ahmadi, Mohsen

2017-01-01

Aim: To identify the extent and direction of range shift of Eucalyptus sideroxylon and E. albens in Australia by 2050 through an ensemble forecast of four species distribution models (SDMs). Each was generated using four global climate models (GCMs), under two representative concentration pathways (RCPs). Location: Australia. Methods: We used four SDMs of (i) generalized linear model, (ii) MaxEnt, (iii) random forest, and (iv) boosted regression tree to construct SDMs for species E. sideroxylon and E. albens under four GCMs including (a) MRI-CGCM3, (b) MIROC5, (c) HadGEM2-AO and (d) CCSM4, under two RCPs of 4.5 and 6.0. Here, the true skill statistic (TSS) index was used to assess the accuracy of each SDM. Results: Results showed that E. albens and E. sideroxylon will lose large areas of their current suitable range by 2050 and E. sideroxylon is projected to gain in eastern and southeastern Australia. Some areas were also projected to remain suitable for each species between now and 2050. Our modelling showed that E. sideroxylon will lose suitable habitat on the western side and will not gain any on the eastern side because this region is one the most heavily populated areas in the country, and the populated areas are moving westward. The predicted decrease in E. sideroxylon’s distribution suggests that land managers should monitor its population closely, and evaluate whether it meets criteria for a protected legal status. Main conclusions: Both Eucalyptus sideroxylon and E. albens will be negatively affected by climate change and it is projected that E. sideroxylon will be at greater risk of losing habitat than E. albens. PMID:29186755

Circumpolar arctic tundra biomass and productivity dynamics in response to projected climate change and herbivory.

PubMed

Yu, Qin; Epstein, Howard; Engstrom, Ryan; Walker, Donald

2017-09-01

Satellite remote sensing data have indicated a general 'greening' trend in the arctic tundra biome. However, the observed changes based on remote sensing are the result of multiple environmental drivers, and the effects of individual controls such as warming, herbivory, and other disturbances on changes in vegetation biomass, community structure, and ecosystem function remain unclear. We apply ArcVeg, an arctic tundra vegetation dynamics model, to estimate potential changes in vegetation biomass and net primary production (NPP) at the plant community and functional type levels. ArcVeg is driven by soil nitrogen output from the Terrestrial Ecosystem Model, existing densities of Rangifer populations, and projected summer temperature changes by the NCAR CCSM4.0 general circulation model across the Arctic. We quantified the changes in aboveground biomass and NPP resulting from (i) observed herbivory only; (ii) projected climate change only; and (iii) coupled effects of projected climate change and herbivory. We evaluated model outputs of the absolute and relative differences in biomass and NPP by country, bioclimate subzone, and floristic province. Estimated potential biomass increases resulting from temperature increase only are approximately 5% greater than the biomass modeled due to coupled warming and herbivory. Such potential increases are greater in areas currently occupied by large or dense Rangifer herds such as the Nenets-occupied regions in Russia (27% greater vegetation increase without herbivores). In addition, herbivory modulates shifts in plant community structure caused by warming. Plant functional types such as shrubs and mosses were affected to a greater degree than other functional types by either warming or herbivory or coupled effects of the two. © 2017 John Wiley & Sons Ltd.

Influence of tropical atmospheric variability on Weddell Sea deep water convection

NASA Astrophysics Data System (ADS)

Kleppin, H.

2016-02-01

Climate reconstructions from ice core records in Greenland and Antarctica have revealed a series of abrupt climate transitions, showing a distinct relationship between northern and southern hemisphere climate during the last glacial period. The recent ice core records from West Antarctica (WAIS) point towards an atmospheric teleconnection as a possible trigger for the interhemispheric climate variability (Markle et al., 2015). An unforced simulation of the Community Climate System Model, version 4 (CCSM4) reveals Greenland warming and cooling events, caused by stochastic atmospheric forcing, that resemble Dansgaard-Oeschger cycles in pattern and magnitude (Kleppin et al., 2015). Anti-phased temperature changes in the Southern Hemisphere are small in magnitude and have a spatially varying pattern. We argue that both north and south high latitude climate variability is triggered by changes in tropical atmospheric deep convection in the western tropical Pacific. The atmospheric wave guide provides a fast communication pathway connecting the deep tropics and the polar regions. In the Southern Hemisphere this is manifested as a distinct pressure pattern over West Antarctica. These altered atmospheric surface conditions over the convective region can lead to destabilization of the water column and thus to convective overturning in the Weddell Sea. However, opposed to what is seen in the Northern Hemisphere no centennial scale variability can establish, due to the absence of a strong feedback mechanism between ocean, atmosphere and sea ice. Kleppin, H., Jochum, M., Otto-Bliesner, B., Shields, C. A., & Yeager, S. (2015). Stochastic Atmospheric Forcing as a Cause of Greenland Climate Transitions. Journal of Climate, (2015). Markle, B. and Coauthors (2015, April). Atmospheric teleconnections between the tropics and high southern latitudes during millennial climate change. In EGU General Assembly Conference Abstracts (Vol. 17, p. 2569).

­Weather and climate change drivers of agricultural pesticide use in the US

NASA Astrophysics Data System (ADS)

Larsen, A.; Deschenes, O.

2016-12-01

Agricultural pesticides have numerous negative consequences for human and environmental health due to direct exposure, and associated air pollution, water contamination and biodiversity losses. As such, understanding the abiotic and biotic drivers of pesticide variability is a scientific and policy priority. Temperature is a direct determinant of insect pest development rates, and as such, it is anticipated that insect pest damage and insecticide use will increase in a warmer climate. Yet, the complexity of plant-insect interactions, diversity of crop growing regions, and uncertainty of climate forecasts have hampered predictions regarding where and to what degree climate change may alter insecticide use. Here we use a county-level, panel data set including the USDA Census of Agriculture and the National Climatic Data Center (NCDC) Global Historical Climatology Network-Daily (GHCN-Daily) for 1987-2012 to statistically evaluate how a rich set of weather variables (e.g. degree days, frosts, precipitation) affect current insecticide use patterns in the continental US. Using climate predictions from National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM) we then estimate how different climate change emissions scenarios (i.e. A2, B1) are likely to impact insecticide use in different agricultural regions of the US. We find an increase in growing season temperature (degree days) leads to an increase in insecticides on average, and in most regions of the US. However, our results indicate that the effect of a warm year is heterogeneous in time with, for example, a warm January leading to a more consistent increase in insecticides than a warm July. Therefore, we estimate that while future climate change will lead to an overall increase in insecticide use, the degree to which that increase materializes will depend on how warming manifests during the year.

A Study of the Climate Change during 21st Century over Peninsular Malaysia Watersheds

NASA Astrophysics Data System (ADS)

Kavvas, M. L.; Ercan, A.; Ishida, K.; Chen, Z. R.; Jang, S.; Amin, M. Z. M.; Shaaban, A. J.

2016-12-01

15 coarse-resolution (150 - 300 km) climate projections for the 21st century by 3 different coupled land-atmosphere-ocean GCMs (ECHAM5 of the Max Planck Institute of Meteorology of Germany, CCSM3 of the National Center for Atmospheric Research (NCAR) of the United States, and MRI-CGCM2.3.2 of the Meteorological Research Institute of Japan) under 4 different greenhouse gas emission scenarios (B1, A1B, A2, A1FI) were dynamically downscaled at hourly intervals by a regional hydro-climate model of Peninsular Malaysia (RegHCM-PM) that consisted of Regional Atmospheric Model MM5 that was coupled with WEHY watershed hydrology model over Peninsular Malaysia (PM), at the scale of the hillslopes of 13 selected watersheds (Batu Pahat, Johor, Muda, Kelang, Kelantan, Linggi, Muar, Pahang, Perak, Selangor, Dungun, Kemaman and Kuantan) and 12 selected intervening coastal regions in order to assess the impact of climate change on the climate conditions at the selected watersheds and coastal regions of PM. From the downscaled climate projections it can be concluded that the mean annual precipitation gradually increases toward the end of the 21st century over each of the 13 watersheds and the 12 coastal regions. The basin-average mean annual temperature increases in the range of 2.50C - 2.950C over PM during the 2010 -2100 period when compared to the 1970-2000 historical period. The ensemble average basin-average annual potential evapotranspiration increases gradually throughout the 21st century over all watersheds.

Modeling Forest Composition and Carbon Dynamics Under Projected Climate-Fire Interactions in the Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Liang, S.; Hurteau, M. D.; Westerling, A. L.

2014-12-01

The Sierra Nevada Mountains are occupied by a diversity of forest types that sort by elevation. The interaction of changing climate and altered disturbance regimes (e.g. fire) has the potential to drive changes in forest distribution as a function of species-specific response. Quantifying the effects of these drivers on species distributions and productivity under future climate-fire interactions is necessary for informing mitigation and adaptation efforts. In this study, we assimilated forest inventory and soil survey data and species life history traits into a landscape model, LANDIS-II, to quantify the response of forest dynamics to the interaction of climate change and large wildfire frequency in the Sierra Nevada. We ran 100-year simulations forced with historical climate and climate projections from three models (GFDL, CNRM and CCSM3) driven by the A2 emission scenario. We found that non-growing season NPP is greatly enhanced by 15%-150%, depending on the specific climate projection. The greatest increase occurs in subalpine forests. Species-specific response varied as a function of life history characteristics. The distribution of drought and fire-tolerant species, such as ponderosa pine, expanded by 7.3-9.6% from initial conditions, while drought and fire-intolerant species, such as white fir, showed little change in the absence of fire. Changes in wildfire size and frequency influence species distributions by altering the successional stage of burned patches. The range of responses to different climate models demonstrates the sensitivity of these forests to climate variability. The scale of climate projections relative to the scale of forest simulations presents a source of uncertainty, particularly at the ecotone between forest types and for identifying topographically mediated climate refugia. Improving simulations will likely require higher resolution climate projections.

Coupled Climate Model Simulations to Bracket the Impacts of Increasing Asian Aerosols Emissions and Aggressive Future Clean Air Policies

NASA Astrophysics Data System (ADS)

Dubey, M. K.; Zhang, Y.; Sun, S.; Olsen, S.; Dean, S.; Bleck, R.; Chylek, P.; Lohmann, U.

2007-12-01

We report ensemble simulations of the climatic impacts of changing anthropogenic aerosols (sulfate, organic and black carbon), which bracket two policy scenarios: increased emissions over China and India by a factor of three over current levels and a global reduction of aerosols by a factor of ten, using the NCAR-CCSM3 and NASA- GISS coupled ocean atmosphere models. Tripling the anthropogenic aerosols over China and India has a small cooling effect (about -0.12°C) on the global mean surface air temperature with a slight reduction in global mean precipitation by ~ -0.8%. On the other hand, global reduction of anthropogenic aerosols by a factor of ten would warm the global surface temperatures by 0.4 °C - 0.8 °C in less than 10 years after the reduction takes place as well as an increase in global precipitation by 3.0% - 3.3%. Comparisons of NCAR and NASA model simulations also suggest that the indirect effects of aerosols are about 1-2 times the direct effects of aerosols. Tripling Asian anthropogenic aerosols results in regional cooling and a reduction in precipitation primarily in Asia, with cooling (warming) also noted over the high latitudes of Northern (Southern) Hemisphere. Warming and increase in precipitation in the case of global reduction of aerosols are concentrated mainly over polluted land areas in both hemispheres. Tropical regions experience large changes in precipitation in both scenarios. We provide new insights into the climate model sensitivities of global mean temperatures and rainfall to aerosol forcing. Our results underscore the urgency of reducing greenhouse gas accumulation rates as the world reduces air pollution to improve human health and that potential increased Asian pollution, offsets only a small fraction of the warming by greenhouse gases.

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model.

PubMed

Shafer, Sarah L; Bartlein, Patrick J; Gray, Elizabeth M; Pelltier, Richard T

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0-58.0°N latitude by 136.6-103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070-2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

Impact of Climate Change on Energy Demand in the Midwestern USA

NASA Astrophysics Data System (ADS)

Yan, M. B.; Zhang, F.; Franklin, M.; Kotamarthi, V. R.

2008-12-01

The impact of climate change on energy demand and use is a significant issue for developing future GHG emission scenarios and developing adaptation and mitigation strategies. A number of studies have evaluated the increase in GHG emissions as a result of changes in energy production from fossil fuels, but the consequences of climate change on energy consumption have not been the focus of many studies. Here we focus on the impacts of climate change on energy use at a regional scale using the Midwestern USA as a test. The paper presents results of analyzing energy use in response to ambient temperature changes in a 17-year period from 1989 to 2006 and projection of energy use under future climate scenarios (2010-2061). This study consisted of a two-step procedure. In the first step, sensitivity of historic energy demand, specifically electricity and natural gas in residential and commercial sectors (42% of end-use energy), with respect to many climatic and non-climatic variables was examined. State-specific regression models were developed to quantify the relationship between energy use and climatic variables using degree days. We found that model parameters and base temperatures for estimating heating and cooling days varied by state and energy sector, mainly depending on climate conditions, infrastructure, economic factors, and seasonal change in energy use. In the second step, we applied these models to predict future energy demand using output data generated by the Community Climate System Model (CCSM) for the SRES A1B scenario used in the IPCC AR-4. The annual demands of electricity and natural gas were predicted for each state from 2010 to 2061. The model results indicate that the average annual electricity demand will increase 3%-5% for the southern states and 1%-3% for the northern states in the region by 2061 and that the demand for natural gas is expected to be reduced in all states. A seasonal analysis of energy distribution in response to climate variables identifies a significant peak in demand in July-August (11%-16% in southern states and 6%-10% in the northern states). These findings suggest that the energy sector is vulnerable to climate change even in the northern Midwest region of the US. Furthermore, we demonstrate that a state-level assessment can help to better identify adaptation strategies for future regional energy sector changes.

Sub-daily Statistical Downscaling of Meteorological Variables Using Neural Networks

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

Kumar, Jitendra; Brooks, Bjørn-Gustaf J.; Thornton, Peter E

2012-01-01

A new open source neural network temporal downscaling model is described and tested using CRU-NCEP reanal ysis and CCSM3 climate model output. We downscaled multiple meteorological variables in tandem from monthly to sub-daily time steps while also retaining consistent correlations between variables. We found that our feed forward, error backpropagation approach produced synthetic 6 hourly meteorology with biases no greater than 0.6% across all variables and variance that was accurate within 1% for all variables except atmospheric pressure, wind speed, and precipitation. Correlations between downscaled output and the expected (original) monthly means exceeded 0.99 for all variables, which indicates thatmore » this approach would work well for generating atmospheric forcing data consistent with mass and energy conserved GCM output. Our neural network approach performed well for variables that had correlations to other variables of about 0.3 and better and its skill was increased by downscaling multiple correlated variables together. Poor replication of precipitation intensity however required further post-processing in order to obtain the expected probability distribution. The concurrence of precipitation events with expected changes in sub ordinate variables (e.g., less incident shortwave radiation during precipitation events) were nearly as consistent in the downscaled data as in the training data with probabilities that differed by no more than 6%. Our downscaling approach requires training data at the target time step and relies on a weak assumption that climate variability in the extrapolated data is similar to variability in the training data.« less

Projected effects of vegetation feedbacks on drought characteristics with SPEI over West Africa using the RegCM-CLM-CN-DV

NASA Astrophysics Data System (ADS)

Jaehyeong, L.; Kim, Y.; Erfanian, A.; Wang, G.; Um, M. J.

2017-12-01

This study utilizes the Standardized Precipitation-Evapotranspiration Index (SPEI) to investigate the projected effect of vegetation feedbacks on drought in West Africa using the Regional Climate Model coupled to the NCAR Community Land Model with both the Carbon and Nitrogen module (CN) and Dynamic Vegetation module (DV) activated (RegCM-CLM-CN-DV). The role of vegetation feedbacks is examined based on simulations with and without dynamic vegetation. The four different future climate scenarios from CCSM, GFDL, MIROC and MPI are used as the boundary conditions of RegCM for two historical and future periods, i.e., for 1981 to 2000 and for 2081 to 2100, respectively. Using SPEI, the duration, frequency, severity and spatial extents are quantified over West Africa and analyzed for two regions of the Sahel and the Gulf of Guinea. In this study, we find that the estimated annual SPEIs clearly indicate that the projected future droughts over the Sahel are enhanced and prolonged when DV is activated. The opposite is shown over the Gulf of Guinea in general. AcknowledgementsThis work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2015R1C1A2A01054800), by the Korea Meteorological Administration R&D Program under Grant KMIPA 2015-6180 and by the Yonsei University Future-leading Research Initiative of 2015(2016-22-0061).

On the recent warming in the subcloud layer entropy and vertically integrated moist static energy over South Asian Monsoon region.

NASA Astrophysics Data System (ADS)

Konduru, R.; Gupta, A.; Matsumoto, J.; Takahashi, H. G.

2017-12-01

In order to explain monsoon circulation, surface temperature gradients described as most traditional concept. However, it cannot explain certain important aspects of monsoon circulation. Later, convective quasi-equilibrium framework and vertically integrated atmospheric energy budget has become recognized theories to explain the monsoon circulation. In this article, same theories were analyzed and observed for the duration 1979-2010 over south Asian summer monsoon region. With the help of NCEP-R2, NOAA 20th Century, and Era-Interim reanalysis an important feature was noticed pertained to subcloud layer entropy and vertical moist static energy. In the last 32 years, subcloud layer entropy and vertically integrated moist static energy has shown significant seasonal warming all over the region with peak over the poleward flank of the cross-equatorial cell. The important reason related to the warming was found to be increase in surface enthalpy fluxes. Instead, other dynamical contributions pertained to the warming was also observed. Increase in positive anomalies of vertical advection of moist static energy over northern Bay of Bengal, Central India, Peninsular India, Eastern Arabian Sea, and Equatorial Indian Ocean was found to be an important dynamic factor contributing for warming of vertically integrated moist static energy. Along with it vertical moist stability has also supported the argument. Similar interpretations were perceived in the AMIP simulation of CCSM4 model. Further modeling experiments on this warming will be helpful to know the exact mechanism behind it.

Modeled ecohydrological responses to climate change at seven small watersheds in the northeastern United States

USGS Publications Warehouse

Pourmokhtarian, Afshin; Driscoll, Charles T.; Campbell, John L.; Hayhoe, Katharine; Stoner, Anne M. K.; Adams, Mary Beth; Burns, Douglas; Fernandez, Ivan; Mitchell, Myron J.; Shanley, James B.

2017-01-01

A cross-site analysis was conducted on seven diverse, forested watersheds in the northeastern United States to evaluate hydrological responses (evapotranspiration, soil moisture, seasonal and annual streamflow, and water stress) to projections of future climate. We used output from four atmosphere–ocean general circulation models (AOGCMs; CCSM4, HadGEM2-CC, MIROC5, and MRI-CGCM3) included in Phase 5 of the Coupled Model Intercomparison Project, coupled with two Representative Concentration Pathways (RCP 8.5 and 4.5). The coarse resolution AOGCMs outputs were statistically downscaled using an asynchronous regional regression model to provide finer resolution future climate projections as inputs to the deterministic dynamic ecosystem model PnET-BGC. Simulation results indicated that projected warmer temperatures and longer growing seasons in the northeastern United States are anticipated to increase evapotranspiration across all sites, although invoking CO2 effects on vegetation (growth enhancement and increases in water use efficiency (WUE)) diminish this response. The model showed enhanced evapotranspiration resulted in drier growing season conditions across all sites and all scenarios in the future. Spruce-fir conifer forests have a lower optimum temperature for photosynthesis, making them more susceptible to temperature stress than more tolerant hardwood species, potentially giving hardwoods a competitive advantage in the future. However, some hardwood forests are projected to experience seasonal water stress, despite anticipated increases in precipitation, due to the higher temperatures, earlier loss of snow packs, longer growing seasons, and associated water deficits. Considering future CO2effects on WUE in the model alleviated water stress across all sites. Modeled streamflow responses were highly variable, with some sites showing significant increases in annual water yield, while others showed decreases. This variability in streamflow responses poses a challenge to water resource management in the northeastern United States. Our analyses suggest that dominant vegetation type and soil type are important attributes in determining future hydrological responses to climate change.

Projecting Climate Change Impacts on Wildfire Probabilities

NASA Astrophysics Data System (ADS)

Westerling, A. L.; Bryant, B. P.; Preisler, H.

2008-12-01

We present preliminary results of the 2008 Climate Change Impact Assessment for wildfire in California, part of the second biennial science report to the California Climate Action Team organized via the California Climate Change Center by the California Energy Commission's Public Interest Energy Research Program pursuant to Executive Order S-03-05 of Governor Schwarzenegger. In order to support decision making by the State pertaining to mitigation of and adaptation to climate change and its impacts, we model wildfire occurrence monthly from 1950 to 2100 under a range of climate scenarios from the Intergovernmental Panel on Climate Change. We use six climate change models (GFDL CM2.1, NCAR PCM1, CNRM CM3, MPI ECHAM5, MIROC3.2 med, NCAR CCSM3) under two emissions scenarios--A2 (C02 850ppm max atmospheric concentration) and B1(CO2 550ppm max concentration). Climate model output has been downscaled to a 1/8 degree (~12 km) grid using two alternative methods: a Bias Correction and Spatial Donwscaling (BCSD) and a Constructed Analogues (CA) downscaling. Hydrologic variables have been simulated from temperature, precipitation, wind and radiation forcing data using the Variable Infiltration Capacity (VIC) Macroscale Hydrologic Model. We model wildfire as a function of temperature, moisture deficit, and land surface characteristics using nonlinear logistic regression techniques. Previous work on wildfire climatology and seasonal forecasting has demonstrated that these variables account for much of the inter-annual and seasonal variation in wildfire. The results of this study are monthly gridded probabilities of wildfire occurrence by fire size class, and estimates of the number of structures potentially affected by fires. In this presentation we will explore the range of modeled outcomes for wildfire in California, considering the effects of emissions scenarios, climate model sensitivities, downscaling methods, hydrologic simulations, statistical model specifications for california wildfire, and their intersection with a range of development scenarios for California.

Modeled ecohydrological responses to climate change at seven small watersheds in the northeastern United States.

PubMed

Pourmokhtarian, Afshin; Driscoll, Charles T; Campbell, John L; Hayhoe, Katharine; Stoner, Anne M K; Adams, Mary Beth; Burns, Douglas; Fernandez, Ivan; Mitchell, Myron J; Shanley, James B

2017-02-01

A cross-site analysis was conducted on seven diverse, forested watersheds in the northeastern United States to evaluate hydrological responses (evapotranspiration, soil moisture, seasonal and annual streamflow, and water stress) to projections of future climate. We used output from four atmosphere-ocean general circulation models (AOGCMs; CCSM4, HadGEM2-CC, MIROC5, and MRI-CGCM3) included in Phase 5 of the Coupled Model Intercomparison Project, coupled with two Representative Concentration Pathways (RCP 8.5 and 4.5). The coarse resolution AOGCMs outputs were statistically downscaled using an asynchronous regional regression model to provide finer resolution future climate projections as inputs to the deterministic dynamic ecosystem model PnET-BGC. Simulation results indicated that projected warmer temperatures and longer growing seasons in the northeastern United States are anticipated to increase evapotranspiration across all sites, although invoking CO 2 effects on vegetation (growth enhancement and increases in water use efficiency (WUE)) diminish this response. The model showed enhanced evapotranspiration resulted in drier growing season conditions across all sites and all scenarios in the future. Spruce-fir conifer forests have a lower optimum temperature for photosynthesis, making them more susceptible to temperature stress than more tolerant hardwood species, potentially giving hardwoods a competitive advantage in the future. However, some hardwood forests are projected to experience seasonal water stress, despite anticipated increases in precipitation, due to the higher temperatures, earlier loss of snow packs, longer growing seasons, and associated water deficits. Considering future CO 2 effects on WUE in the model alleviated water stress across all sites. Modeled streamflow responses were highly variable, with some sites showing significant increases in annual water yield, while others showed decreases. This variability in streamflow responses poses a challenge to water resource management in the northeastern United States. Our analyses suggest that dominant vegetation type and soil type are important attributes in determining future hydrological responses to climate change. © 2016 John Wiley & Sons Ltd.

Reconstructing paleoclimate fields using online data assimilation with a linear inverse model

NASA Astrophysics Data System (ADS)

Perkins, Walter A.; Hakim, Gregory J.

2017-05-01

We examine the skill of a new approach to climate field reconstructions (CFRs) using an online paleoclimate data assimilation (PDA) method. Several recent studies have foregone climate model forecasts during assimilation due to the computational expense of running coupled global climate models (CGCMs) and the relatively low skill of these forecasts on longer timescales. Here we greatly diminish the computational cost by employing an empirical forecast model (linear inverse model, LIM), which has been shown to have skill comparable to CGCMs for forecasting annual-to-decadal surface temperature anomalies. We reconstruct annual-average 2 m air temperature over the instrumental period (1850-2000) using proxy records from the PAGES 2k Consortium Phase 1 database; proxy models for estimating proxy observations are calibrated on GISTEMP surface temperature analyses. We compare results for LIMs calibrated using observational (Berkeley Earth), reanalysis (20th Century Reanalysis), and CMIP5 climate model (CCSM4 and MPI) data relative to a control offline reconstruction method. Generally, we find that the usage of LIM forecasts for online PDA increases reconstruction agreement with the instrumental record for both spatial fields and global mean temperature (GMT). Specifically, the coefficient of efficiency (CE) skill metric for detrended GMT increases by an average of 57 % over the offline benchmark. LIM experiments display a common pattern of skill improvement in the spatial fields over Northern Hemisphere land areas and in the high-latitude North Atlantic-Barents Sea corridor. Experiments for non-CGCM-calibrated LIMs reveal region-specific reductions in spatial skill compared to the offline control, likely due to aspects of the LIM calibration process. Overall, the CGCM-calibrated LIMs have the best performance when considering both spatial fields and GMT. A comparison with the persistence forecast experiment suggests that improvements are associated with the linear dynamical constraints of the forecast and not simply persistence of temperature anomalies.

Genetic and ecological insights into glacial refugia of walnut (Juglans regia L.)

PubMed Central

Aradhya, Mallikarjuna; Ibrahimov, Zakir; Toktoraliev, Biimyrza; Maghradze, David; Musayev, Mirza; Bobokashvili, Zviadi; Preece, John E.

2017-01-01

The distribution and survival of trees during the last glacial maximum (LGM) has been of interest to paleoecologists, biogeographers, and geneticists. Ecological niche models that associate species occurrence and abundance with climatic variables are widely used to gain ecological and evolutionary insights and to predict species distributions over space and time. The present study deals with the glacial history of walnut to address questions related to past distributions through genetic analysis and ecological modeling of the present, LGM and Last Interglacial (LIG) periods. A maximum entropy method was used to project the current walnut distribution model on to the LGM (21–18 kyr BP) and LIG (130–116 kyr BP) climatic conditions. Model tuning identified the walnut data set filtered at 10 km spatial resolution as the best for modeling the current distribution and to hindcast past (LGM and LIG) distributions of walnut. The current distribution model predicted southern Caucasus, parts of West and Central Asia extending into South Asia encompassing northern Afghanistan, Pakistan, northwestern Himalayan region, and southwestern Tibet, as the favorable climatic niche matching the modern distribution of walnut. The hindcast of distributions suggested the occurrence of walnut during LGM was somewhat limited to southern latitudes from southern Caucasus, Central and South Asian regions extending into southwestern Tibet, northeastern India, Himalayan region of Sikkim and Bhutan, and southeastern China. Both CCSM and MIROC projections overlapped, except that MIROC projected a significant presence of walnut in the Balkan Peninsula during the LGM. In contrast, genetic analysis of the current walnut distribution suggested a much narrower area in northern Pakistan and the surrounding areas of Afghanistan, northwestern India, and southern Tajikistan as a plausible hotspot of diversity where walnut may have survived glaciations. Overall, the findings suggest that walnut perhaps survived the last glaciations in several refugia across a wide geographic area between 30° and 45° North latitude. However, humans probably played a significant role in the recent history and modern distribution of walnut. PMID:29023476

Genetic and ecological insights into glacial refugia of walnut (Juglans regia L.).

PubMed

Aradhya, Mallikarjuna; Velasco, Dianne; Ibrahimov, Zakir; Toktoraliev, Biimyrza; Maghradze, David; Musayev, Mirza; Bobokashvili, Zviadi; Preece, John E

2017-01-01

The distribution and survival of trees during the last glacial maximum (LGM) has been of interest to paleoecologists, biogeographers, and geneticists. Ecological niche models that associate species occurrence and abundance with climatic variables are widely used to gain ecological and evolutionary insights and to predict species distributions over space and time. The present study deals with the glacial history of walnut to address questions related to past distributions through genetic analysis and ecological modeling of the present, LGM and Last Interglacial (LIG) periods. A maximum entropy method was used to project the current walnut distribution model on to the LGM (21-18 kyr BP) and LIG (130-116 kyr BP) climatic conditions. Model tuning identified the walnut data set filtered at 10 km spatial resolution as the best for modeling the current distribution and to hindcast past (LGM and LIG) distributions of walnut. The current distribution model predicted southern Caucasus, parts of West and Central Asia extending into South Asia encompassing northern Afghanistan, Pakistan, northwestern Himalayan region, and southwestern Tibet, as the favorable climatic niche matching the modern distribution of walnut. The hindcast of distributions suggested the occurrence of walnut during LGM was somewhat limited to southern latitudes from southern Caucasus, Central and South Asian regions extending into southwestern Tibet, northeastern India, Himalayan region of Sikkim and Bhutan, and southeastern China. Both CCSM and MIROC projections overlapped, except that MIROC projected a significant presence of walnut in the Balkan Peninsula during the LGM. In contrast, genetic analysis of the current walnut distribution suggested a much narrower area in northern Pakistan and the surrounding areas of Afghanistan, northwestern India, and southern Tajikistan as a plausible hotspot of diversity where walnut may have survived glaciations. Overall, the findings suggest that walnut perhaps survived the last glaciations in several refugia across a wide geographic area between 30° and 45° North latitude. However, humans probably played a significant role in the recent history and modern distribution of walnut.

The Effect of Orbital Configuration on the Possible Climates and Habitability of Kepler-62f.

PubMed

Shields, Aomawa L; Barnes, Rory; Agol, Eric; Charnay, Benjamin; Bitz, Cecilia; Meadows, Victoria S

2016-06-01

As lower-mass stars often host multiple rocky planets, gravitational interactions among planets can have significant effects on climate and habitability over long timescales. Here we explore a specific case, Kepler-62f (Borucki et al., 2013 ), a potentially habitable planet in a five-planet system with a K2V host star. N-body integrations reveal the stable range of initial eccentricities for Kepler-62f is 0.00 ≤ e ≤ 0.32, absent the effect of additional, undetected planets. We simulate the tidal evolution of Kepler-62f in this range and find that, for certain assumptions, the planet can be locked in a synchronous rotation state. Simulations using the 3-D Laboratoire de Météorologie Dynamique (LMD) Generic global climate model (GCM) indicate that the surface habitability of this planet is sensitive to orbital configuration. With 3 bar of CO2 in its atmosphere, we find that Kepler-62f would only be warm enough for surface liquid water at the upper limit of this eccentricity range, providing it has a high planetary obliquity (between 60° and 90°). A climate similar to that of modern-day Earth is possible for the entire range of stable eccentricities if atmospheric CO2 is increased to 5 bar levels. In a low-CO2 case (Earth-like levels), simulations with version 4 of the Community Climate System Model (CCSM4) GCM and LMD Generic GCM indicate that increases in planetary obliquity and orbital eccentricity coupled with an orbital configuration that places the summer solstice at or near pericenter permit regions of the planet with above-freezing surface temperatures. This may melt ice sheets formed during colder seasons. If Kepler-62f is synchronously rotating and has an ocean, CO2 levels above 3 bar would be required to distribute enough heat to the nightside of the planet to avoid atmospheric freeze-out and permit a large enough region of open water at the planet's substellar point to remain stable. Overall, we find multiple plausible combinations of orbital and atmospheric properties that permit surface liquid water on Kepler-62f. Extrasolar planets-Habitability-Planetary environments. Astrobiology 16, 443-464.

The Effect of Orbital Configuration on the Possible Climates and Habitability of Kepler-62f

PubMed Central

Barnes, Rory; Agol, Eric; Charnay, Benjamin; Bitz, Cecilia; Meadows, Victoria S.

2016-01-01

Abstract As lower-mass stars often host multiple rocky planets, gravitational interactions among planets can have significant effects on climate and habitability over long timescales. Here we explore a specific case, Kepler-62f (Borucki et al., 2013), a potentially habitable planet in a five-planet system with a K2V host star. N-body integrations reveal the stable range of initial eccentricities for Kepler-62f is 0.00 ≤ e ≤ 0.32, absent the effect of additional, undetected planets. We simulate the tidal evolution of Kepler-62f in this range and find that, for certain assumptions, the planet can be locked in a synchronous rotation state. Simulations using the 3-D Laboratoire de Météorologie Dynamique (LMD) Generic global climate model (GCM) indicate that the surface habitability of this planet is sensitive to orbital configuration. With 3 bar of CO2 in its atmosphere, we find that Kepler-62f would only be warm enough for surface liquid water at the upper limit of this eccentricity range, providing it has a high planetary obliquity (between 60° and 90°). A climate similar to that of modern-day Earth is possible for the entire range of stable eccentricities if atmospheric CO2 is increased to 5 bar levels. In a low-CO2 case (Earth-like levels), simulations with version 4 of the Community Climate System Model (CCSM4) GCM and LMD Generic GCM indicate that increases in planetary obliquity and orbital eccentricity coupled with an orbital configuration that places the summer solstice at or near pericenter permit regions of the planet with above-freezing surface temperatures. This may melt ice sheets formed during colder seasons. If Kepler-62f is synchronously rotating and has an ocean, CO2 levels above 3 bar would be required to distribute enough heat to the nightside of the planet to avoid atmospheric freeze-out and permit a large enough region of open water at the planet's substellar point to remain stable. Overall, we find multiple plausible combinations of orbital and atmospheric properties that permit surface liquid water on Kepler-62f. Key Words: Extrasolar planets—Habitability—Planetary environments. Astrobiology 16, 443–464. PMID:27176715

Future climate change enhances rainfall seasonality in a regional model of western Maritime Continent

NASA Astrophysics Data System (ADS)

Kang, Suchul; Im, Eun-Soon; Eltahir, Elfatih A. B.

2018-03-01

In this study, future changes in rainfall due to global climate change are investigated over the western Maritime Continent based on dynamically downscaled climate projections using the MIT Regional Climate Model (MRCM) with 12 km horizontal resolution. A total of nine 30-year regional climate projections driven by multi-GCMs projections (CCSM4, MPI-ESM-MR and ACCESS1.0) under multi-scenarios of greenhouse gases emissions (Historical: 1976-2005, RCP4.5 and RCP8.5: 2071-2100) from phase 5 of the Coupled Model Inter-comparison Project (CMIP5) are analyzed. Focusing on dynamically downscaled rainfall fields, the associated systematic biases originating from GCM and MRCM are removed based on observations using Parametric Quantile Mapping method in order to enhance the reliability of future projections. The MRCM simulations with bias correction capture the spatial patterns of seasonal rainfall as well as the frequency distribution of daily rainfall. Based on projected rainfall changes under both RCP4.5 and RCP8.5 scenarios, the ensemble of MRCM simulations project a significant decrease in rainfall over the western Maritime Continent during the inter-monsoon periods while the change in rainfall is not relevant during wet season. The main mechanism behind the simulated decrease in rainfall is rooted in asymmetries of the projected changes in seasonal dynamics of the meridional circulation along different latitudes. The sinking motion, which is marginally positioned in the reference simulation, is enhanced and expanded under global climate change, particularly in RCP8.5 scenario during boreal fall season. The projected enhancement of rainfall seasonality over the western Maritime Continent suggests increased risk of water stress for natural ecosystems as well as man-made water resources reservoirs.

The fate of Amazonian ecosystems over the coming century arising from changes in climate, atmospheric CO2, and land use.

PubMed

Zhang, Ke; de Almeida Castanho, Andrea D; Galbraith, David R; Moghim, Sanaz; Levine, Naomi M; Bras, Rafael L; Coe, Michael T; Costa, Marcos H; Malhi, Yadvinder; Longo, Marcos; Knox, Ryan G; McKnight, Shawna; Wang, Jingfeng; Moorcroft, Paul R

2015-02-20

There is considerable interest in understanding the fate of the Amazon over the coming century in the face of climate change, rising atmospheric CO 2 levels, ongoing land transformation, and changing fire regimes within the region. In this analysis, we explore the fate of Amazonian ecosystems under the combined impact of these four environmental forcings using three terrestrial biosphere models (ED2, IBIS, and JULES) forced by three bias-corrected IPCC AR4 climate projections (PCM1, CCSM3, and HadCM3) under two land-use change scenarios. We assess the relative roles of climate change, CO 2 fertilization, land-use change, and fire in driving the projected changes in Amazonian biomass and forest extent. Our results indicate that the impacts of climate change are primarily determined by the direction and severity of projected changes in regional precipitation: under the driest climate projection, climate change alone is predicted to reduce Amazonian forest cover by an average of 14%. However, the models predict that CO 2 fertilization will enhance vegetation productivity and alleviate climate-induced increases in plant water stress, and, as a result, sustain high biomass forests, even under the driest climate scenario. Land-use change and climate-driven changes in fire frequency are predicted to cause additional aboveground biomass loss and reductions in forest extent. The relative impact of land use and fire dynamics compared to climate and CO 2 impacts varies considerably, depending on both the climate and land-use scenario, and on the terrestrial biosphere model used, highlighting the importance of improved quantitative understanding of all four factors - climate change, CO 2 fertilization effects, fire, and land use - to the fate of the Amazon over the coming century. © 2015 John Wiley & Sons Ltd.

Generalized Dissimilarity Modeling of Late-Quaternary Variations in Pollen-Based Compositional Dissimilarity

NASA Astrophysics Data System (ADS)

Williams, J. W.; Blois, J.; Ferrier, S.; Manion, G.; Fitzpatrick, M.; Veloz, S.; He, F.; Liu, Z.; Otto-Bliesner, B. L.

2011-12-01

In Quaternary paleoecology and paleoclimatology, compositionally dissimilar fossil assemblages usually indicate dissimilar environments; this relationship underpins assemblage-level techniques for paleoenvironmental reconstruction such as mutual climatic ranges or the modern analog technique. However, there has been relatively little investigation into the form of the relationship between compositional dissimilarity and climatic dissimilarity. Here we apply generalized dissimilarity modeling (GDM; Ferrier et al. 2007) as a tool for modeling the expected non-linear relationships between compositional and climatic dissimilarity. We use the CCSM3.0 transient paleoclimatic simulations from the SynTrace working group (Liu et al. 2009) and a new generation of fossil pollen maps from eastern North America (Blois et al. 2011) to 1) assess the spatial relationships between compositional dissimilarity and climatic dissimilarity and 2) whether these spatial relationships change over time. We used a taxonomic list of 106 genus-level pollen types, six climatic variables (winter precipitation and mean temperature, summer precipitation and temperature, seasonality of precipitation, and seasonality of temperature) that were chosen to minimize collinearity, and a cross-referenced pollen and climate dataset mapped for time slices spaced 1000 years apart. When GDM was trained for one time slice, the correlation between predicted and observed spatial patterns of community dissimilarity for other times ranged between 0.3 and 0.73. The selection of climatic predictor variables changed over time, as did the form of the relationship between compositional turnover and climatic predictors. Summer temperature was the only variable selected for all time periods. These results thus suggest that the relationship between compositional dissimilarity in pollen assemblages (and, by implication, beta diversity in plant communities) and climatic dissimilarity can change over time, for reasons to be further studied.

The role of the uncertainty in assessing future scenarios of water shortage in alluvial aquifers

NASA Astrophysics Data System (ADS)

Romano, Emanuele; Camici, Stefania; Brocca, Luca; Moramarco, Tommaso; Guyennon, Nicolas; Preziosi, Elisabetta

2015-04-01

There are many evidences that the combined effects of variations in precipitation and temperature due to climate change can result in a significant change of the recharge to groundwater at different time scales. A possible reduction of effective infiltration can result in a significant decrease, temporary or permanent, of the availability of the resource and, consequently, the sustainable pumping rate should be reassessed. In addition to this, one should also consider the so called indirect impacts of climate change, resulting from human intervention (e.g. augmentation of abstractions) which are feared to be even more important than the direct ones in the medium term: thus, a possible increase of episodes of shortage (i.e. the inability of the groundwater system to completely supply the water demand) can result both from change in the climate forcing and change in the demand. In order to assess future scenarios of water shortage a modelling chain is often used. It includes: 1) the use of General Circulation Models to estimate changes in temperature and precipitation; 2) downscaling procedures to match modeling scenarios to the observed meteorological time series; 3) soil-atmosphere modelling to estimate the time variation of the recharge to the aquifer; 4) groundwater flow models to simulate the water budget and piezometric head evolution; 5) future scenarios of groundwater quantitative status that include scenarios of demand variation. It is well known that each of these processing steps is affected by an intrinsic uncertainty that propagates through the whole chain leading to a final uncertainty on the piezometric head scenarios. The estimate of such an uncertainty is a key point for a correct management of groundwater resources, in case of water shortage due to prolonged droughts as well as for planning purposes. This study analyzes the uncertainty of the processing chain from GCM scenarios to its impact on an alluvial aquifer in terms of exploitation sustainability. To this goal, three GCMs (ECHAM5, PCM and CCSM3) and two downscaling methods (Linear Rescaling and Quantile Mapping) are used to generate future scenarios of precipitation and temperature; the Thornthwaite-Mather soil water balance model is used to estimate the recharge to the aquifer; the evolution in time of the piezometric heads is estimated through a numerical model developed using the MODFLOW2005 code. Finally, different scenarios of water demand are applied. Final results show that the uncertainty due to the groundwater flow model calibration/validation in steady-state conditions is comparable to that arising from the whole processing chain from the GCM choice to the effective infiltration estimates. Simulations in transient conditions show the high impact of the uncertainty related to the calibration of the storage coefficient, that significantly drives the resilience of the system, thus the ability of the aquifer to sustain the demand during the periods of prolonged drought.

The effects of climate downscaling technique and observational data set on modeled ecological responses.

PubMed

Pourmokhtarian, Afshin; Driscoll, Charles T; Campbell, John L; Hayhoe, Katharine; Stoner, Anne M K

2016-07-01

Assessments of future climate change impacts on ecosystems typically rely on multiple climate model projections, but often utilize only one downscaling approach trained on one set of observations. Here, we explore the extent to which modeled biogeochemical responses to changing climate are affected by the selection of the climate downscaling method and training observations used at the montane landscape of the Hubbard Brook Experimental Forest, New Hampshire, USA. We evaluated three downscaling methods: the delta method (or the change factor method), monthly quantile mapping (Bias Correction-Spatial Disaggregation, or BCSD), and daily quantile regression (Asynchronous Regional Regression Model, or ARRM). Additionally, we trained outputs from four atmosphere-ocean general circulation models (AOGCMs) (CCSM3, HadCM3, PCM, and GFDL-CM2.1) driven by higher (A1fi) and lower (B1) future emissions scenarios on two sets of observations (1/8º resolution grid vs. individual weather station) to generate the high-resolution climate input for the forest biogeochemical model PnET-BGC (eight ensembles of six runs).The choice of downscaling approach and spatial resolution of the observations used to train the downscaling model impacted modeled soil moisture and streamflow, which in turn affected forest growth, net N mineralization, net soil nitrification, and stream chemistry. All three downscaling methods were highly sensitive to the observations used, resulting in projections that were significantly different between station-based and grid-based observations. The choice of downscaling method also slightly affected the results, however not as much as the choice of observations. Using spatially smoothed gridded observations and/or methods that do not resolve sub-monthly shifts in the distribution of temperature and/or precipitation can produce biased results in model applications run at greater temporal and/or spatial resolutions. These results underscore the importance of carefully considering field observations used for training, as well as the downscaling method used to generate climate change projections, for smaller-scale modeling studies. Different sources of variability including selection of AOGCM, emissions scenario, downscaling technique, and data used for training downscaling models, result in a wide range of projected forest ecosystem responses to future climate change. © 2016 by the Ecological Society of America.

Advancing Climate Change and Impacts Science Through Climate Informatics

NASA Astrophysics Data System (ADS)

Lenhardt, W.; Pouchard, L. C.; King, A. W.; Branstetter, M. L.; Kao, S.; Wang, D.

2010-12-01

This poster will outline the work to date on developing a climate informatics capability at Oak Ridge National Laboratory (ORNL). The central proposition of this effort is that the application of informatics and information science to the domain of climate change science is an essential means to bridge the realm of high performance computing (HPC) and domain science. The goal is to facilitate knowledge capture and the creation of new scientific insights. For example, a climate informatics capability will help with the understanding and use of model results in domain sciences that were not originally in the scope. From there, HPC can also benefit from feedback as the new approaches may lead to better parameterization in the models. In this poster we will summarize the challenges associated with climate change science that can benefit from the systematic application of informatics and we will highlight our work to date in creating the climate informatics capability to address these types of challenges. We have identified three areas that are particularly challenging in the context of climate change science: 1) integrating model and observational data across different spatial and temporal scales, 2) model linkages, i.e. climate models linked to other models such as hydrologic models, and 3) model diagnostics. Each of these has a methodological component and an informatics component. Our project under way at ORNL seeks to develop new approaches and tools in the context of linking climate change and water issues. We are basing our work on the following four use cases: 1) Evaluation/test of CCSM4 biases in hydrology (precipitation, soil water, runoff, river discharge) over the Rio Grande Basin. User: climate modeler. 2) Investigation of projected changes in hydrology of Rio Grande Basin using the VIC (Variable Infiltration Capacity Macroscale) Hydrologic Model. User: watershed hydrologist/modeler. 3) Impact of climate change on agricultural productivity of the Rio Grande Basin. User: climate impact scientist, agricultural economist. 4) Renegotiation of the 1944 “Treaty for the Utilization of Waters of the Colorado and Tijuana Rivers and of the Rio Grande”. User: A US State Department analyst or their counterpart in Mexico.

Simulated decadal modes of the NH atmospheric circulation arising from intra-decadal variability, external forcing and slow-decadal climate processes

NASA Astrophysics Data System (ADS)

Lou, Jiale; Zheng, Xiaogu; Frederiksen, Carsten S.; Liu, Haibo; Grainger, Simon; Ying, Kairan

2017-04-01

A decadal variance decomposition method is applied to the Northern Hemisphere (NH) 500-hPa geopotential height (GPH) and the sea level pressure (SLP) taken from the last millennium (850-1850 AD) experiment with the coupled climate model CCSM4, to estimate the contribution of the intra-decadal variability to the inter-decadal variability. By removing the intra-decadal variability from the total inter-decadal variability, the residual variability is more likely to be associated with slowly varying external forcings and slow-decadal climate processes, and therefore is referred to as slow-decadal variability. The results show that the (multi-)decadal changes of the NH 500-hPa GPH are primarily dominated by slow-decadal variability, whereas the NH SLP field is primarily dominated by the intra-decadal variability. At both pressure levels, the leading intra-decadal modes each have features related to the El Niño-southern oscillation, the intra-decadal variability of the Pacific decadal oscillation (PDO) and the Arctic oscillation (AO); while the leading slow-decadal modes are associated with external radiative forcing (mostly with volcanic aerosol loadings), the Atlantic multi-decadal oscillation and the slow-decadal variability of AO and PDO. Moreover, the radiative forcing has much weaker effect to the SLP than that to the 500-hPa GPH.

The Norwegian Earth System Model, NorESM1-M - Part 2: Climate response and scenario projections

NASA Astrophysics Data System (ADS)

Iversen, T.; Bentsen, M.; Bethke, I.; Debernard, J. B.; Kirkevåg, A.; Seland, Ø.; Drange, H.; Kristjansson, J. E.; Medhaug, I.; Sand, M.; Seierstad, I. A.

2013-03-01

NorESM is a generic name of the Norwegian earth system model. The first version is named NorESM1, and has been applied with medium spatial resolution to provide results for CMIP5 (http://cmip-pcmdi.llnl.gov/cmip5/index.html) without (NorESM1-M) and with (NorESM1-ME) interactive carbon-cycling. Together with the accompanying paper by Bentsen et al. (2012), this paper documents that the core version NorESM1-M is a valuable global climate model for research and for providing complementary results to the evaluation of possible anthropogenic climate change. NorESM1-M is based on the model CCSM4 operated at NCAR, but the ocean model is replaced by a modified version of MICOM and the atmospheric model is extended with online calculations of aerosols, their direct effect and their indirect effect on warm clouds. Model validation is presented in the companion paper (Bentsen et al., 2012). NorESM1-M is estimated to have equilibrium climate sensitivity of ca. 2.9 K and a transient climate response of ca. 1.4 K. This sensitivity is in the lower range amongst the models contributing to CMIP5. Cloud feedbacks dampen the response, and a strong AMOC reduces the heat fraction available for increasing near-surface temperatures, for evaporation and for melting ice. The future projections based on RCP scenarios yield a global surface air temperature increase of almost one standard deviation lower than a 15-model average. Summer sea-ice is projected to decrease considerably by 2100 and disappear completely for RCP8.5. The AMOC is projected to decrease by 12%, 15-17%, and 32% for the RCP2.6, 4.5, 6.0, and 8.5, respectively. Precipitation is projected to increase in the tropics, decrease in the subtropics and in southern parts of the northern extra-tropics during summer, and otherwise increase in most of the extra-tropics. Changes in the atmospheric water cycle indicate that precipitation events over continents will become more intense and dry spells more frequent. Extra-tropical storminess in the Northern Hemisphere is projected to shift northwards. There are indications of more frequent occurrence of spring and summer blocking in the Euro-Atlantic sector, while the amplitude of ENSO events weakens although they tend to appear more frequently. These indications are uncertain because of biases in the model's representation of present-day conditions. Positive phase PNA and negative phase NAO both appear less frequently under the RCP8.5 scenario, but also this result is considered uncertain. Single-forcing experiments indicate that aerosols and greenhouse gases produce similar geographical patterns of response for near-surface temperature and precipitation. These patterns tend to have opposite signs, although with important exceptions for precipitation at low latitudes. The asymmetric aerosol effects between the two hemispheres lead to a southward displacement of ITCZ. Both forcing agents, thus, tend to reduce Northern Hemispheric subtropical precipitation.

Investigating the potential impacts of local climate change on the meltwater supply of a small snow-fed mountain river system: A case study of the Animas River, Colorado

NASA Astrophysics Data System (ADS)

Day, C. A.

2010-12-01

The western US receives up to 80% of its annual streamflow from snowmelt fed river systems during the mid-to-late spring season. Changes in winter and spring air temperature and precipitation patterns have, however, begun to alter this sensitive hydroclimatological process, both in terms of the timing and magnitude of snowmelt events and the responding streamflow. Monitoring and planning for these changes in the future may well prove crucial for local water resource planners who traditionally rely on historical trends or means for water resource planning. Local-level water resource planners also often do not have the data or tools at the right resolution available to them for the same planning purposes. This goal of this research was to identify how changes in the local winter-spring climate may alter the hydrological response of a typical small mountain snowmelt fed river system, the Animas River in SW Colorado. To achieve this, a statistical downscaling technique was applied to increase the resolution of, and build a linear relationship between, historical upper atmospheric reanalysis data to surface level mean air temperature and precipitation for several climate stations located across the basin for 1950-2007. The same technique was then used to increase the resolution of two GCM scenarios from the NCAR CCSM3 model SRES-AR4 data runs (a 'business as usual’ or A1B scenario, and an increase in global greenhouse gas emissions or A2 scenario) using the same relationships between the historical upper atmospheric reanalysis data and the surface station climate data. Snowmelt streamflow magnitude and timing were then projected to 2099 based on their historical relationship to mean monthly winter and spring air temperature and precipitation before being compared to the historical averages. Results indicated a shift in the timing of the snowmelt streamflow to earlier in the spring, and a reduction in the magnitude of peak spring streamflow following increasing spring temperatures and decreasing winter precipitation across the basin. These techniques and methods may provide a starting framework for local-level water resource planners to monitor and prepare for any future changes to basinwide hydroclimatology.

Projected future vegetation changes for the northwest United States and southwest Canada at a fine spatial resolution using a dynamic global vegetation model.

USGS Publications Warehouse

Shafer, Sarah; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model

PubMed Central

Shafer, Sarah L.; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas. PMID:26488750

Flow cytometry, microsatellites and niche models reveal the origins and geographical structure of Alnus glutinosa populations in Europe

PubMed Central

Mandák, Bohumil; Vít, Petr; Krak, Karol; Trávníček, Pavel; Havrdová, Alena; Hadincová, Věroslava; Zákravský, Petr; Jarolímová, Vlasta; Bacles, Cecile Fanny Emilie; Douda, Jan

2016-01-01

Background and Aims Polyploidy in plants has been studied extensively. In many groups, two or more cytotypes represent separate biological entities with distinct distributions, histories and ecology. This study examines the distribution and origins of cytotypes of Alnus glutinosa in Europe, North Africa and western Asia. Methods A combined approach was used involving flow cytometry and microsatellite analysis of 12 loci in 2200 plants from 209 populations combined with species distribution modelling using MIROC and CCSM climatic models, in order to analyse (1) ploidy and genetic variation, (2) the origin of tetraploid A. glutinosa, considering A. incana as a putative parent, and (3) past distributions of the species. Key Results The occurrence of tetraploid populations of A. glutinosa in Europe is determined for the first time. The distribution of tetraploids is far from random, forming two geographically well-delimited clusters located in the Iberian Peninsula and the Dinaric Alps. Based on microsatellite analysis, both tetraploid clusters are probably of autopolyploid origin, with no indication that A. incana was involved in their evolutionary history. A projection of the MIROC distribution model into the Last Glacial Maximum (LGM) showed that (1) populations occurring in the Iberian Peninsula and North Africa were probably interconnected during the LGM and (2) populations occurring in the Dinaric Alps did not exist throughout the last glacial periods, having retreated southwards into lowland areas of the Balkan Peninsula. Conclusions Newly discovered tetraploid populations are situated in the putative main glacial refugia, and neither of them was likely to have been involved in the colonization of central and northern Europe after glacial withdrawal. This could mean that neither the Iberian Peninsula nor the western part of the Balkan Peninsula served as effective refugial areas for northward post-glacial expansion of A. glutinosa. PMID:26467247

A climate model study of an intense Asian Monsoon in a La Niña-like climate of MIS-13

NASA Astrophysics Data System (ADS)

Karami, M. P.; Berger, A.; Herold, N.; Yin, Q. Z.

2012-04-01

Studying the paleo-monsoon during past interglacials is a valuable approach to improve our understanding of the monsoon system in present-day and future climates. We focus on Marine Isotopic stage 13 (MIS-13; ~0.5 Ma) which was a relatively cool interglacial, but with a paradoxically intense monsoonal precipitation over eastern and southern Asia. Our main goal is to understand the physics-based mechanism driving the intense monsoon, specifically the East Asian Summer Monsoon (EASM), during MIS-13. We applied both an intermediate complexity model (LOVECLIM) as well as fully coupled general circulation models (HadCM3 and CCSM3) to simulate pre-industrial and MIS-13 climates. The boundary conditions for MIS-13 were chosen for 506 ka with Northern-Hemisphere (NH) summer at perihelion and a CO2 concentration of 240 ppm. For pre-industrial, NH-winter occurring at perihelion and a CO2 concentration of 280 ppm were prescribed. Preliminary analysis of the model results shows different atmospheric and oceanic features in MIS-13 compared to the pre-industrial which could affect the EASM. The Northern Pacific Subtropical High (NPSH), which is an important factor in controlling the EASM, strengthened and extended to the northwest in MIS-13 partially due to cooling of the central Pacific Ocean. This in turn brought more moisture from the Central Pacific to the EASM-region and caused a northwestward shift and bending of the low-level jet along East Asia. The change in the low-level jet subsequently increased the meridional wind velocity at 850 mbar in the EASM-region providing more moisture from the tropical Pacific and Indian Oceans. In addition, higher sea-surface temperature in the Indian Ocean during MIS-13 further increased the source of moisture for the EASM. The Asian low, which is another component of the EASM-system, also shifted eastward moving the rain band northward. Moreover, it was found that MIS-13 had a dominant La Niña condition in the tropical Pacific. La Niña-type climate is normally expected to favor increases in precipitation in the EASM through the NPSH as can be seen in MIS-13. Whether there was ENSO variability around the La Niña-like background climatic state of MIS-13 or not is under further investigation. The correlation between the sea-surface temperature variability in the tropical Pacific and the EASM precipitation was found to increase in MIS-13 compared to the pre-industrial which is another factor explaining the intensified EASM in MIS13. Although our model results show high precipitation for MIS-13 qualitatively consistent with data, we are still interested in other factors that could increase the precipitation even further. *This work is supported by the European Research Council Advanced Grant EMIS (No 227348 of the Programme 'ideas')

Strategic Planning for Drought Mitigation Under Climate Change

NASA Astrophysics Data System (ADS)

Cai, X.; Zeng, R.; Valocchi, A. J.; Song, J.

2012-12-01

Droughts continue to be a major natural hazard and mounting evidence of global warming confronts society with a pressing question: Will climate change aggravate the risk of drought at local scale? It is important to explore what additional risk will be imposed by climate change and what level of strategic measures should be undertaken now to avoid vulnerable situations in the future, given that tactical measures may not avoid large damage. This study addresses the following key questions on strategic planning for drought mitigation under climate change: What combination of strategic and tactical measures will move the societal system response from a vulnerable situation to a resilient one with minimum cost? Are current infrastructures and their operation enough to mitigate the damage of future drought, or do we need in-advance infrastructure expansion for future drought preparedness? To address these questions, this study presents a decision support framework based on a coupled simulation and optimization model. A quasi-physically based watershed model is established for the Frenchman Creek Basin (FCB), part of the Republic River Basin, where groundwater based irrigation plays a significant role in agriculture production and local hydrological cycle. The physical model is used to train a statistical surrogate model, which predicts the watershed responses under future climate conditions. The statistical model replaces the complex physical model in the simulation-optimization framework, which makes the models computationally tractable. Decisions for drought preparedness include traditional short-term tactical measures (e.g. facility operation) and long-term or in-advance strategic measures, which require capital investment. A scenario based three-stage stochastic optimization model assesses the roles of strategic measures and tactical measures in drought preparedness and mitigation. Two benchmark climate prediction horizons, 2040s and 2090s, represent mid-term and long-term planning, respectively, compared to the baseline of the climate of 1980-2000. To handle uncertainty in climate change projections, outputs from three General Circulation Models (GCMs) with Regional Climate Model (RCM) for dynamic downscaling (PCM-RCM, Hadley-RCM, and CCSM-RCM) and four CO2 emission scenarios are used to represent the various possible climatic conditions in the mid-term (2040's) and long-term (2090's) time horizons. The model results show the relative roles of mid- and long-term investments and the complementary relationships between wait-and-see decisions and here-and-now decisions on infrastructure expansion. Even the best tactical measures (irrigation operation) alone are not sufficient for drought mitigation in the future. Infrastructure expansion is critical especially for environmental conversation purposes. With increasing budget, investment should be shifted from tactical measures to strategic measures for drought preparedness. Infrastructure expansion is preferred for the long term plan than the mid-term plan, i.e., larger investment is proposed in 2040s than the current, due to a larger likelihood of drought in 2090s than 2040s. Thus larger BMP expansion is proposed in 2040s for droughts preparedness in 2090s.

Statistical Surrogate Models for Estimating Probability of High-Consequence Climate Change

NASA Astrophysics Data System (ADS)

Field, R.; Constantine, P.; Boslough, M.

2011-12-01

We have posed the climate change problem in a framework similar to that used in safety engineering, by acknowledging that probabilistic risk assessments focused on low-probability, high-consequence climate events are perhaps more appropriate than studies focused simply on best estimates. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We have developed specialized statistical surrogate models (SSMs) that can be used to make predictions about the tails of the associated probability distributions. A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field, that is, a random variable for every fixed location in the atmosphere at all times. The SSM can be calibrated to available spatial and temporal data from existing climate databases, or to a collection of outputs from general circulation models. Because of its reduced size and complexity, the realization of a large number of independent model outputs from a SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework was also developed to provide quantitative measures of confidence, via Bayesian credible intervals, to assess these risks. To illustrate the use of the SSM, we considered two collections of NCAR CCSM 3.0 output data. The first collection corresponds to average December surface temperature for years 1990-1999 based on a collection of 8 different model runs obtained from the Program for Climate Model Diagnosis and Intercomparison (PCMDI). We calibrated the surrogate model to the available model data and make various point predictions. We also analyzed average precipitation rate in June, July, and August over a 54-year period assuming a cyclic Y2K ocean model. We applied the calibrated surrogate model to study the probability that the precipitation rate falls below certain thresholds and utilized the Bayesian approach to quantify our confidence in these predictions. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under Contract DE-AC04-94AL85000.

Reconstructing Common Era Climate Fields Using Data Assimilation, Proxies, and a Linear Climate Model

NASA Astrophysics Data System (ADS)

Perkins, W. A.; Hakim, G. J.

2016-12-01

In this work, we examine the skill of a new approach to performing climate field reconstructions (CFRs) using a form of online paleoclimate data assimilation (PDA). Many previous studies have foregone climate model forecasts during assimilation due to the computational expense of running coupled global climate models (CGCMs), and the relatively low skill of these forecasts on longer timescales. Here we greatly diminish the computational costs by employing an empirical forecast model (known as a linear inverse model; LIM), which has been shown to have comparable skill to CGCMs. CFRs of annually averaged 2m air temperature anomalies are compared between the Last Millennium Reanalysis framework (no forecasting or "offline"), a persistence forecast, and four LIM forecasting experiments over the instrumental period (1850 - 2000). We test LIM calibrations for observational (Berkeley Earth), reanalysis (20th Century Reanalysis), and CMIP5 climate model (CCSM4 and MPI) data. Generally, we find that the usage of LIM forecasts for online PDA increases reconstruction agreement with the instrumental record for both spatial and global mean temperature (GMT). The detrended GMT skill metrics show the most dramatic increases in skill with coefficient of efficiency (CE) improvements over the no-forecasting benchmark averaging 57%. LIM experiments display a common pattern of spatial field increases in CE skill over northern hemisphere land areas and in the high-latitude North Atlantic - Barents Sea corridor (Figure 1). However, the non-GCM-calibrated LIMs introduce other deficiencies into the spatial skill of these reconstructions, likely due to aspects of the LIM calibration process. Overall, the CMIP5 LIMs have the best performance when considering both spatial fields and GMT. A comparison with the persistence forecast experiment suggests that improvements are associated with the usage of the LIM forecasts, and not simple persistence of temperature anomalies over time. These results show that the use of LIM forecasting can help add further dynamical constraint to CFRs. As we move forward, this will be an important factor in fully utilizing dynamically consistent information from the proxy record while reconstructing the past millennium.

The effect of the MJO on the energetics of El Niño

NASA Astrophysics Data System (ADS)

Lybarger, Nicholas D.; Stan, Cristiana

2017-12-01

The energy budget of the Pacific Ocean is evaluated in the Super-Parameterized Community Climate Model version 4 (SP-CCSM4) on intraseasonal time scales. The budget terms are decomposed to isolate the MJO influence and the ocean current associated with Kelvin waves. Using this decomposition, one can distinguish between El Niño events with strong and weak MJO influence. Composites of El Niño events based on the wind power component associated with the MJO induced wind stress and oceanic Kelvin waves ({{W}_{{MJO},{K}}} ) are compared with composites based only on the atmospheric variability and based only on the oceanic variability. It was found that the composite of events when {{W}_{{MJO},{K}}} is near maximum (+ NMJO,K) shows a greater magnitude of mean perturbation wind power, buoyancy power, and available potential energy than any other case, which is consistent with the greater amplitude Kelvin wave perturbations on the thermocline, as well as the greater amplitude of SST anomalies at the peak of the event. For + NMJO,K, latent heat flux anomalies out of the ocean along the coast of New Guinea are seen coincident with deepening of the mixed layer depth there, suggesting that this is an important region for the thermodynamic influence of the MJO on the ocean. Latent heat flux anomalies into the ocean are seen across the ITCZ in the spring, suggesting a basin wide influence by the MJO on the ocean surface radiation budget in + NMJO,K.

Estimating the uncertainty of the impact of climate change on alluvial aquifers. Case study in central Italy

NASA Astrophysics Data System (ADS)

Romano, Emanuele; Camici, Stefania; Brocca, Luca; Moramarco, Tommaso; Pica, Federico; Preziosi, Elisabetta

2014-05-01

There is evidence that the precipitation pattern in Europe is trending towards more humid conditions in the northern region and drier conditions in the southern and central-eastern regions. However, a great deal of uncertainty concerns how the changes in precipitations will have an impact on water resources, particularly on groundwater, and this uncertainty should be evaluated on the basis of that coming from 1) future climate scenarios of Global Circulation Models (GCMs) and 2) modeling chains including the downscaling technique, the infiltration model and the calibration/validation procedure used to develop the groundwater flow model. With the aim of quantifying the uncertainty of these components, the Valle Umbra porous aquifer (Central Italy) has been considered as a case study. This aquifer, that is exploited for human consumption and irrigation, is mainly fed by the effective infiltration from the ground surface and partly by the inflow from the carbonate aquifers bordering the valley. A numerical groundwater flow model has been developed through the finite difference MODFLOW2005 code and it has been calibrated and validated considering the recharge regime computed through a Thornthwaite-Mather infiltration model under the climate conditions observed in the period 1956-2012. Future scenarios (2010-2070) of temperature and precipitation have been obtained from three different GMCs: ECHAM-5 (Max Planck Institute, Germany), PCM (National Centre Atmospheric Research) and CCSM3 (National Centre Atmospheric Research). Each scenario has been downscaled (DSC) to the data of temperature and precipitation collected in the baseline period 1960-1990 at the stations located in the study area through two different statistical techniques (linear rescaling and quantile mapping). Then, stochastic rainfall and temperature time series are generated through the Neyman-Scott Rectangular Pulses model (NSRP) for precipitation and the Fractionally Differenced ARIMA model (FARIMA) for temperature. Such a procedure has allowed to estimate, through the Thornthwaite-Mather model, the uncertainty related to the future scenarios of recharge to the aquifer. Finally, all the scenarios of recharge have been used as input to the groundwater flow model and the results have been evaluated in terms of the uncertainty on the computed aquifer heads and total budget. The main results have indicated that most of the uncertainty on the impact to the aquifer arise from the uncertainty on the first part of the processing chain GCM-DSC.

The Fate of Amazonian Ecosystems over the Coming Century Arising from Changes in Climate, Atmospheric CO2 and Land-use

NASA Astrophysics Data System (ADS)

Moorcroft, P. R.; Zhang, K.; Castanho, A. D. D. A.; Galbraith, D.; Moghim, S.; Levine, N. M.; Bras, R. L.; Coe, M. T.; Costa, M. H.; Malhi, Y.; Longo, M.; Knox, R. G.; McKnight, S. L.; Wang, J.

2014-12-01

There is considerable interest and uncertainty regarding the expected fate of the Amazon over the coming century in face of the combined impacts of climate change, rising atmospheric CO2 levels, and on-going land transformation in the region. In this analysis, we explore the fate of Amazonian ecosystems under projected climate, CO2 and land-use change in the 21st century using three state-of-the-art terrestrial biosphere models (ED2, IBIS, and JULES) driven by three representative, bias-corrected GCM climate projections (PCM1, CCSM3, and HadCM3) under the SRES A2 scenario, coupled with two land-use change scenarios. We assess the relative roles of climate change, CO2 fertilization, land-use change, and fire in driving the projected changes in Amazonian biomass and forest extent. Our results indicate that the impacts of climate change depend strongly on the direction and severity of projected changes in precipitation regimes within the region: under the driest climate projection, climate change alone is predicted to reduce Amazonian forest cover by an average of 14%; however, the models predict that CO2 fertilization will enhance vegetation productivity and alleviate climate-induced increases in plant water stress, and as a result sustain high biomass forests, even under the driest climate scenario. Land-use change and changes in fire frequency are predicted cause additional aboveground live biomass loss and changes in forest extent. The relative impact of land-use and fire dynamics versus the impacts of climate and CO2 on the Amazon varies considerably, depending on both the climate and land-use scenarios used and on the terrestrial biosphere model, highlighting the importance of improved understanding of all four factors -- future climate, CO2 fertilization effects, fire and land-use -- to the fate of the Amazon over the coming century.

Response of Sierra Nevada forests to projected climate-wildfire interactions.

PubMed

Liang, Shuang; Hurteau, Matthew D; Westerling, Anthony LeRoy

2017-05-01

Climate influences forests directly and indirectly through disturbance. The interaction of climate change and increasing area burned has the potential to alter forest composition and community assembly. However, the overall forest response is likely to be influenced by species-specific responses to environmental change and the scale of change in overstory species cover. In this study, we sought to quantify how projected changes in climate and large wildfire size would alter forest communities and carbon (C) dynamics, irrespective of competition from nontree species and potential changes in other fire regimes, across the Sierra Nevada, USA. We used a species-specific, spatially explicit forest landscape model (LANDIS-II) to evaluate forest response to climate-wildfire interactions under historical (baseline) climate and climate projections from three climate models (GFDL, CCSM3, and CNRM) forced by a medium-high emission scenario (A2) in combination with corresponding climate-specific large wildfire projections. By late century, we found modest changes in the spatial distribution of dominant species by biomass relative to baseline, but extensive changes in recruitment distribution. Although forest recruitment declined across much of the Sierra, we found that projected climate and wildfire favored the recruitment of more drought-tolerant species over less drought-tolerant species relative to baseline, and this change was greatest at mid-elevations. We also found that projected climate and wildfire decreased tree species richness across a large proportion of the study area and transitioned more area to a C source, which reduced landscape-level C sequestration potential. Our study, although a conservative estimate, suggests that by late century, forest community distributions may not change as intact units as predicted by biome-based modeling, but are likely to trend toward simplified community composition as communities gradually disaggregate and the least tolerant species are no longer able to establish. The potential exists for substantial community composition change and forest simplification beyond this century. © 2016 John Wiley & Sons Ltd.

Decadal Climate Information Needs of Stakeholders for Decision Support in Water and Agriculture Production Sectors: A Case Study in the Missouri River Basin

NASA Astrophysics Data System (ADS)

Mehta, V. M.; Knutson, C.; Rosenberg, N.

2012-12-01

Many decadal climate prediction efforts have been initiated under the World Climate Research Programme's Coupled Model Intercomparison Project 5. There is considerable ongoing discussion about model deficiencies, initialization techniques, and data requirements, but not much attention is being given to decadal climate information (DCI) needs of stakeholders for decision support. We report the results of exploratory activities undertaken to assess DCI needs in water resources and agriculture sectors, using the Missouri River Basin (the Basin) as a case study. This assessment was achieved through discussions with 120 representative stakeholders. Stakeholders' awareness of decadal dry and wet spells and their societal impacts in the Basin is established; and stakeholders' DCI needs and potential barriers to their use of DCI are enumerated. We find that impacts, including economic impacts, of DCV on water and agricultural production in the Basin are distinctly identifiable and characterizable. Stakeholders have clear notions about their needs for DCI and have offered specific suggestions as to how these might be met. But, while stakeholders are eager to have climate information, including decadal climate outlooks (DCOs), there are many barriers to the use of such information. The first and foremost is that the credibility of DCOs is yet to be established. Secondly, the nature of institutional rules and regulations, laws, and legal precedents that pose obstacles to the use of DCOs must be better understood and means to modify these, where possible, must be sought. For the benefit of climate scientists, these and other stakeholder needs will also be articulated in this talk. We are engaged in a project to assess simulation and hindcast skills of DCV phenomena and their associations with hydro-meteorological variability in the Basin in the HadCM3, GFDL-CM2.1, NCAR CCSM4, and MIROC5 global coupled models participating in the WCRP's CMIP5 project. Results from this project will also be described and compared with stakeholder information needs.

The Norwegian Earth System Model, NorESM1-M - Part 2: Climate response and scenario projections

NASA Astrophysics Data System (ADS)

Iversen, T.; Bentsen, M.; Bethke, I.; Debernard, J. B.; Kirkevåg, A.; Seland, Ø.; Drange, H.; Kristjánsson, J. E.; Medhaug, I.; Sand, M.; Seierstad, I. A.

2012-09-01

The NorESM1-M simulation results for CMIP5 (http://cmip-pcmdi.llnl.gov/cmip5/index.html) are described and discussed. Together with the accompanying paper by Bentsen et al. (2012), this paper documents that NorESM1-M is a valuable global climate model for research and for providing complementary results to the evaluation of possible man made climate change. NorESM is based on the model CCSM4 operated at NCAR on behalf of many contributors in USA. The ocean model is replaced by a developed version of MICOM and the atmospheric model is extended with on-line calculations of aerosols, their direct effect, and their indirect effect on warm clouds. Model validation is presented in a companion paper (Bentsen et al., 2012). NorESM1-M is estimated to have equilibrium climate sensitivity slightly smaller than 2.9 K, a transient climate response just below 1.4 K, and is less sensitive than most other models. Cloud feedbacks damp the response, and a strong AMOC reduces the heat fraction available for increasing near surface temperatures, for evaporation, and for melting ice. The future projections based on RCP scenarios yield global surface air temperature increase almost one standard deviation lower than a 15-model average. Summer sea-ice is projected to decrease considerably by 2100, and completely for RCP8.5. The AMOC is projected to reduce by 12%, 15-17%, and 32% for the RCP2.6, 4.5, 6.0 and 8.5 respectively. Precipitation is projected to increase in the tropics, decrease in the subtropics and in southern parts of the northern extra-tropics during summer, and otherwise increase in most of the extra-tropics. Changes in the atmospheric water cycle indicate that precipitation events over continents will become more intense and dry spells more frequent. Extra-tropical storminess in the Northern Hemisphere is projected to shift northwards. There are indications of more frequent spring and summer blocking in the Euro-Atlantic sectors and that ENSO events weaken but appear more frequent. These indications are uncertain because of biases in the model's representation of present-day conditions. There are indications that positive phase PNA and negative phase NAO become less frequent under the RCP8.5 scenario, but also this result is considered uncertain. Single-forcing experiments indicate that aerosols and greenhouse gases produce similar geographical patterns of response for near surface temperature and precipitation. These patterns tend to have opposite sign, with important exceptions for precipitation at low latitudes. The asymmetric aerosol effects between the two hemispheres leads to a southward displacement of ITCZ. Both forcing agents thus tend to reduce northern hemispheric subtropical precipitation.

The Last Millennium Reanalysis: Improvements to proxies and proxy modeling

NASA Astrophysics Data System (ADS)

Tardif, R.; Hakim, G. J.; Emile-Geay, J.; Noone, D.; Anderson, D. M.

2017-12-01

The Last Millennium Reanalysis (LMR) employs a paleoclimate data assimilation (PDA) approach to produce climate field reconstructions (CFRs). Here, we focus on two key factors in PDA generated CFRs: the set of assimilated proxy records and forward models (FMs) used to estimate proxies from climate model output. In the initial configuration of the LMR [Hakim et al., 2016], the proxy dataset of [PAGES2k Consortium, 2013] was used, along with univariate linear FMs calibrated against annually-averaged 20th century temperature datasets. In an updated configuration, proxy records from the recent dataset [PAGES2k Consortium, 2017] are used, while a hierarchy of statistical FMs are tested: (1) univariate calibrated on annual temperature as in the initial configuration, (2) univariate against temperature as in (1) but calibration performed using expert-derived seasonality for individual proxy records, (3) as in (2) but expert proxy seasonality replaced by seasonal averaging determined objectively as part of the calibration process, (4) linear objective seasonal FMs as in (3) but objectively selecting relationships calibrated either on temperature or precipitation, and (5) bivariate linear models calibrated on temperature and precipitation with objectively-derived seasonality. (4) and (5) specifically aim at better representing the physical drivers of tree ring width proxies. Reconstructions generated using the CCSM4 Last Millennium simulation as an uninformed prior are evaluated against various 20th century data products. Results show the benefits of using the new proxy collection, particularly on the detrended global mean temperature and spatial patterns. The positive impact of using proper seasonality and temperature/moisture sensitivities for tree ring width records is also notable. This updated configuration will be used for the first generation of LMR-generated CFRs to be publicly released. These also provide a benchmark for future efforts aimed at evaluating the impact of additional proxy records and/or more sophisticated physically-based forward models. References: Hakim, G. J., and co-authors (2016), J. Geophys. Res. Atmos., doi:10.1002/2016JD024751 PAGES2K Consortium (2013), Nat. Geosci., doi:10.1038/ngeo1797 PAGES2k Consortium (2017), Sci. Data. doi:10.1038/sdata.2017.88

Prediction of future hydrological regimes in poorly gauged high altitude basins: the case study of the upper Indus, Pakistan

NASA Astrophysics Data System (ADS)

Bocchiola, D.; Diolaiuti, G.; Soncini, A.; Mihalcea, C.; D'Agata, C.; Mayer, C.; Lambrecht, A.; Rosso, R.; Smiraglia, C.

2011-04-01

In the mountain regions of the Hindu Kush, Karakoram and Himalaya (HKH) the "third polar ice cap" of our planet, glaciers play the role of "water towers" by providing significant amount of melt water, especially in the dry season, essential for agriculture, drinking purposes, and hydropower production. Recently, most glaciers in the HKH have been retreating and losing mass, mainly due to significant regional warming, thus calling for assessment of future water resources availability for populations down slope. However, hydrology of these high altitude catchments is poorly studied and little understood. Most such catchments are poorly gauged, thus posing major issues in flow prediction therein, and representing in facts typical grounds of application of PUB concepts, where simple and portable hydrological modeling based upon scarce data amount is necessary for water budget estimation, and prediction under climate change conditions. In this preliminarily study, future (2060) hydrological flows in a particular watershed (Shigar river at Shigar, ca. 7000 km2), nested within the upper Indus basin and fed by seasonal melt from major glaciers, are investigated. The study is carried out under the umbrella of the SHARE-Paprika project, aiming at evaluating the impact of climate change upon hydrology of the upper Indus river. We set up a minimal hydrological model, tuned against a short series of observed ground climatic data from a number of stations in the area, in situ measured ice ablation data, and remotely sensed snow cover data. The future, locally adjusted, precipitation and temperature fields for the reference decade 2050-2059 from CCSM3 model, available within the IPCC's panel, are then fed to the hydrological model. We adopt four different glaciers' cover scenarios, to test sensitivity to decreased glacierized areas. The projected flow duration curves, and some selected flow descriptors are evaluated. The uncertainty of the results is then addressed, and use of the model for nearby catchments discussed. The proposed approach is valuable as a tool to investigate the hydrology of poorly gauged high altitude areas, and to project forward their hydrological behavior pending climate change.

Prediction of future hydrological regimes in poorly gauged high altitude basins: the case study of the upper Indus, Pakistan

NASA Astrophysics Data System (ADS)

Bocchiola, D.; Diolaiuti, G.; Soncini, A.; Mihalcea, C.; D'Agata, C.; Mayer, C.; Lambrecht, A.; Rosso, R.; Smiraglia, C.

2011-07-01

In the mountain regions of the Hindu Kush, Karakoram and Himalaya (HKH) the "third polar ice cap" of our planet, glaciers play the role of "water towers" by providing significant amount of melt water, especially in the dry season, essential for agriculture, drinking purposes, and hydropower production. Recently, most glaciers in the HKH have been retreating and losing mass, mainly due to significant regional warming, thus calling for assessment of future water resources availability for populations down slope. However, hydrology of these high altitude catchments is poorly studied and little understood. Most such catchments are poorly gauged, thus posing major issues in flow prediction therein, and representing in fact typical grounds of application of PUB concepts, where simple and portable hydrological modeling based upon scarce data amount is necessary for water budget estimation, and prediction under climate change conditions. In this preliminarily study, future (2060) hydrological flows in a particular watershed (Shigar river at Shigar, ca. 7000 km2), nested within the upper Indus basin and fed by seasonal melt from major glaciers, are investigated. The study is carried out under the umbrella of the SHARE-Paprika project, aiming at evaluating the impact of climate change upon hydrology of the upper Indus river. We set up a minimal hydrological model, tuned against a short series of observed ground climatic data from a number of stations in the area, in situ measured ice ablation data, and remotely sensed snow cover data. The future, locally adjusted, precipitation and temperature fields for the reference decade 2050-2059 from CCSM3 model, available within the IPCC's panel, are then fed to the hydrological model. We adopt four different glaciers' cover scenarios, to test sensitivity to decreased glacierized areas. The projected flow duration curves, and some selected flow descriptors are evaluated. The uncertainty of the results is then addressed, and use of the model for nearby catchments discussed. The proposed approach is valuable as a tool to investigate the hydrology of poorly gauged high altitude areas, and to project forward their hydrological behavior pending climate change.

Climate change versus deforestation: Implications for tree species distribution in the dry forests of southern Ecuador

PubMed Central

Hildebrandt, Patrick; Cueva, Jorge; Espinosa, Carlos Iván; Stimm, Bernd; Günter, Sven

2017-01-01

Seasonally dry forests in the neotropics are heavily threatened by a combination of human disturbances and climate change; however, the severity of these threats is seldom contrasted. This study aims to quantify and compare the effects of deforestation and climate change on the natural spatial ranges of 17 characteristic tree species of southern Ecuador dry deciduous forests, which are heavily fragmented and support high levels of endemism as part of the Tumbesian ecoregion. We used 660 plant records to generate species distribution models and land-cover data to project species ranges for two time frames: a simulated deforestation scenario from 2008 to 2014 with native forest to anthropogenic land-use conversion, and an extreme climate change scenario (CCSM4.0, RCP 8.5) for 2050, which assumed zero change from human activities. To assess both potential threats, we compared the estimated annual rates of species loss (i.e., range shifts) affecting each species. Deforestation loss for all species averaged approximately 71 km2/year, while potential climate-attributed loss was almost 21 km2/year. Moreover, annual area loss rates due to deforestation were significantly higher than those attributed to climate-change (P < 0.01). However, projections into the future scenario show evidence of diverging displacement patterns, indicating the potential formation of novel ecosystems, which is consistent with other species assemblage predictions as result of climate change. Furthermore, we provide recommendations for management and conservation, prioritizing the most threatened species such as Albizia multiflora, Ceiba trichistandra, and Cochlospermum vitifolium. PMID:29267357

Climate change versus deforestation: Implications for tree species distribution in the dry forests of southern Ecuador.

PubMed

Manchego, Carlos E; Hildebrandt, Patrick; Cueva, Jorge; Espinosa, Carlos Iván; Stimm, Bernd; Günter, Sven

2017-01-01

Seasonally dry forests in the neotropics are heavily threatened by a combination of human disturbances and climate change; however, the severity of these threats is seldom contrasted. This study aims to quantify and compare the effects of deforestation and climate change on the natural spatial ranges of 17 characteristic tree species of southern Ecuador dry deciduous forests, which are heavily fragmented and support high levels of endemism as part of the Tumbesian ecoregion. We used 660 plant records to generate species distribution models and land-cover data to project species ranges for two time frames: a simulated deforestation scenario from 2008 to 2014 with native forest to anthropogenic land-use conversion, and an extreme climate change scenario (CCSM4.0, RCP 8.5) for 2050, which assumed zero change from human activities. To assess both potential threats, we compared the estimated annual rates of species loss (i.e., range shifts) affecting each species. Deforestation loss for all species averaged approximately 71 km2/year, while potential climate-attributed loss was almost 21 km2/year. Moreover, annual area loss rates due to deforestation were significantly higher than those attributed to climate-change (P < 0.01). However, projections into the future scenario show evidence of diverging displacement patterns, indicating the potential formation of novel ecosystems, which is consistent with other species assemblage predictions as result of climate change. Furthermore, we provide recommendations for management and conservation, prioritizing the most threatened species such as Albizia multiflora, Ceiba trichistandra, and Cochlospermum vitifolium.

Trade wind inversion variability, dynamics and future change in Hawai'i

NASA Astrophysics Data System (ADS)

Cao, Guangxia

Using 1979-2003 radiosonde data at Hilo and Lihu'e, Hawai'i, the trade-wind inversion (TWI) is found to occur approximately 82% of the time at each station, with average base heights of 2225 +/- 14.3 m (781.9 +/- 1.4 hPa) for Hilo and 2076 +/- 12.5 m (798.8 +/- 1.2 hPa) for Lihu'e. A Weather Research and Forecast (WRF) meso-scale meteorological simulation suggests that island topography and heating contribute to the lifting of the TWI base at Hilo. Inversion base height has a September maximum and a secondary maximum in April. Frequency of inversion occurrence is significantly higher during winters and lower during summers of El Nino years. During the period of 1979-2003, the inversion frequency of occurrence is on upward trend at Hilo for spring (MAM), summer (JJA), and fall (SON) seasons and at Lihu'e for all seasons and for annual values. Composite analysis shows that patterns of geopotential height (GPH), air temperature, u- and v-wind, omega wind, relative and specific humidity, upward longwave radiation flux, net longwave radiation flux, precipitable water, convective precipitation rate, and total cloud cover significantly respond to the TWI base height. For example, the GPH pattern contains a distinctive Pacific North America Teleconnection (PNA) signature, and the magnitudes of PNA centers over 45°N, 165°W for the difference between none and inversion is over 40 m at 200 hPa and 25 m at 850 hPa. The monthly composites show that months with lower (higher) inversion base height and higher (lower) inversion occurrence frequency are linked with the following characteristics: lower (higher) GPH anomalies centered at 30°N, 160°W, lower (higher) temperature anomalies within 300--700 hPa, stronger (weaker) easterly at low levels and northerly anomaly over Hawai'i, and small upward (downward) vertical wind or rising (sinking) motion north of Hawai'i. Using the above characteristics to study the Community Climate System Model (CCSM) composites leads to the prediction that the TWI under increased CO2 forcing atmosphere will be lower in base height and more frequently.

Single-Column Modeling, GCM Parameterizations and Atmospheric Radiation Measurement Data

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

Somerville, R.C.J.; Iacobellis, S.F.

2005-03-18

Our overall goal is identical to that of the Atmospheric Radiation Measurement (ARM) Program: the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data at all three ARM sites, and the implementation and testing of these parameterizations in global and regional models. To test recently developed prognostic parameterizations based on detailed cloud microphysics, we have first compared single-column model (SCM) output with ARM observations at the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Topical Western Pacific (TWP) sites. We focus on the predicted cloud amounts and on a suite of radiativemore » quantities strongly dependent on clouds, such as downwelling surface shortwave radiation. Our results demonstrate the superiority of parameterizations based on comprehensive treatments of cloud microphysics and cloud-radiative interactions. At the SGP and NSA sites, the SCM results simulate the ARM measurements well and are demonstrably more realistic than typical parameterizations found in conventional operational forecasting models. At the TWP site, the model performance depends strongly on details of the scheme, and the results of our diagnostic tests suggest ways to develop improved parameterizations better suited to simulating cloud-radiation interactions in the tropics generally. These advances have made it possible to take the next step and build on this progress, by incorporating our parameterization schemes in state-of-the-art 3D atmospheric models, and diagnosing and evaluating the results using independent data. Because the improved cloud-radiation results have been obtained largely via implementing detailed and physically comprehensive cloud microphysics, we anticipate that improved predictions of hydrologic cycle components, and hence of precipitation, may also be achievable. We are currently testing the performance of our ARM-based parameterizations in state-of-the--art global and regional models. One fruitful strategy for evaluating advances in parameterizations has turned out to be using short-range numerical weather prediction as a test-bed within which to implement and improve parameterizations for modeling and predicting climate variability. The global models we have used to date are the CAM atmospheric component of the National Center for Atmospheric Research (NCAR) CCSM climate model as well as the National Centers for Environmental Prediction (NCEP) numerical weather prediction model, thus allowing testing in both climate simulation and numerical weather prediction modes. We present detailed results of these tests, demonstrating the sensitivity of model performance to changes in parameterizations.« less

Projecting future grassland performance in the Greater Platte River Basin to assess sustainability for potential biofuel feedstock areas

NASA Astrophysics Data System (ADS)

Gu, Y.; Wylie, B. K.; Phuyal, K.

2012-12-01

In previous studies, we used vegetation condition information from archival records of satellite data (i.e., 10-year time series of Normalized Difference Vegetation Index (NDVI) data), site geophysical and biophysical features (e.g., elevation, slope and aspect, and soils), and weather and climate drivers to build ecosystem performance (EP) models to dynamically monitor EP (DMEP) in the Greater Platte River Basin (GPRB). Ecosystem performance is a surrogate approach for measuring ecosystem productivity. We estimated ecosystem site potentials (i.e., long-term ecosystem productivities), weather-based expected EP (EEP), and rangeland conditions based on these EP models. Validation of the EP results using ground observations (e.g., percentage of bare soil, LANDFIRE maps, stocking rate, and crop yield data) demonstrated the reliability of these EP models. We used this DMEP method to identify grasslands that are potentially suitable for cellulosic biofuel feedstock (e.g., switchgrass) development in the GPRB. The objectives of this study are to (1) project the future grassland EP; (2) assess the changes and trends of the future EP; and (3) examine the future sustainability of the identified biofuel feedstock areas in the GPRB. We used the EP models and future climate projections to estimate future (e.g., 2050 and 2099) climate-based projections of grassland performance in the GPRB. The future climate data were derived from the National Center for Atmospheric Research (NCAR) Community Climate System Model 3.0 (CCSM3) "SRES A1B" (a "middle" emissions path) obtained from the "Bias Corrected and Downscaled WCRP CMIP3 Climate Projections" archive (http://gdo-dcp.ucllnl.org/downscaled_cmip3_projections). Results show that, under climate scenario A1B, the potential biofuel feedstock areas in the more mesic Eastern part of the GPRB will remain productive in the future (the spatially averaged EPs for these areas are 3335 kg ha-1 year-1, 3355 kg ha-1 year-1, and 3341 kg ha-1 year-1 for the site potential, the 2050 EEP, and the 2099 EEP, respectively). Therefore, the identified potential biofuel feedstock areas will continue to be sustainable for future biofuel development. On the other hand, the identified non-biofuel grasslands in the drier Western part of the GPRB would be expected to stay unproductive, with a slight decline in the EP trend in the future (spatially averaged EPs are 1983 kg ha-1 year-1, 1977 kg ha-1 year-1, and 1964 kg ha-1 year-1 for the site potential, the 2050 EEP, and the 2099 EEP, respectively). Thus, these areas will continue to be unsuitable for biofuel feedstock development in the future. The resulting future grassland EEP maps can be used as a reference by land managers to assess the future sustainability and feasibility of the potential biofuel feedstock areas.

Future permafrost degradation positively enhances Arctic ecohydrological processes

NASA Astrophysics Data System (ADS)

Park, Hotaek; Walsh, John

2013-04-01

Permafrost is considered vulnerable to increasing temperatures. Air temperatures over the Arctic have indeed increased considerably over the last century. Most climate models project that the warming will continue, enhancing permafrost degradation. The degradation of permafrost has the potential to initiate numerous feedbacks, predominantly positive, in the Arctic climatic, hydrological, and biogeochemical processes. For instance, the Arctic terrestrial evapotranspiration during summer season tends to overpass precipitation of the period. The unbalance of water budget seems to be offset by permafrost contribution. A considerable amount of soil carbon cumulating within the permafrost is also released with permafrost degradation. However, it is still uncertain on how much amount of soil carbon will be released. Furthermore, the largest uncertainty is on the magnitude of permafrost degradation under the future climate change. Therefore, the major purpose of this study is to reduce the uncertainties relating to permafrost degradation and then is to assess influences of permafrost dynamics on ecohydrological processes. A land surface model CHANGE, including hydrological and biogeochemical processes, was applied to the pan-Arctic terrestrial region over the period 1901-2100. For exploring the influence of permafrost dynamics on ecohydrological processes in the future, outputs from four scenarios (RCP 4.5, 6.0, and 8.5) of three GCMs (MIROC, CCSM4, and HadGCM2) were used for the simulation of CHANGE. Permafrost positively degraded with temperature warming. By 2091-2100, permafrost extent was decreased 30-75% and active layer thickness increased about 55-125 cm, compared to 1991-2010. Evapotranspiration (ET) and net primary productivity (NPP) also increased about 15-55%. However, higher ET resulted in soil dryness. On the other hand, the increased NPP enhanced soil organic matter, which increased soil water-holding capacity and limited soil warming due to its insulation effect. The model also predicted a cumulative efflux of 50-120 Gt C of permafrost carbon to the atmosphere by 2100. The thaw and decay of permafrost carbon is irreversible and amplify surface warming to initiate a positive permafrost carbon feedback on climate. On the other hand, the conditions implicated to permafrost degradation tended to keep summertime ET and NPP relatively high.

Assimilating Non-linear Effects of Customized Large-Scale Climate Predictors on Downscaled Precipitation over the Tropical Andes

NASA Astrophysics Data System (ADS)

Molina, J. M.; Zaitchik, B. F.

2016-12-01

Recent findings considering high CO2 emission scenarios (RCP8.5) suggest that the tropical Andes may experience a massive warming and a significant precipitation increase (decrease) during the wet (dry) seasons by the end of the 21st century. Variations on rainfall-streamflow relationships and seasonal crop yields significantly affect human development in this region and make local communities highly vulnerable to climate change and variability. We developed an expert-informed empirical statistical downscaling (ESD) algorithm to explore and construct robust global climate predictors to perform skillful RCP8.5 projections of in-situ March-May (MAM) precipitation required for impact modeling and adaptation studies. We applied our framework to a topographically-complex region of the Colombian Andes where a number of previous studies have reported El Niño-Southern Oscillation (ENSO) as the main driver of climate variability. Supervised machine learning algorithms were trained with customized and bias-corrected predictors from NCEP reanalysis, and a cross-validation approach was implemented to assess both predictive skill and model selection. We found weak and not significant teleconnections between precipitation and lagged seasonal surface temperatures over El Niño3.4 domain, which suggests that ENSO fails to explain MAM rainfall variability in the study region. In contrast, series of Sea Level Pressure (SLP) over American Samoa -likely associated with the South Pacific Convergence Zone (SPCZ)- explains more than 65% of the precipitation variance. The best prediction skill was obtained with Selected Generalized Additive Models (SGAM) given their ability to capture linear/nonlinear relationships present in the data. While SPCZ-related series exhibited a positive linear effect in the rainfall response, SLP predictors in the north Atlantic and central equatorial Pacific showed nonlinear effects. A multimodel (MIROC, CanESM2 and CCSM) ensemble of ESD projections revealed an increased variability and a positive and significant trend in the MAM precipitation mean in the next decades, with accentuated changes and projection uncertainty after 2050. ESD traces (2050-2100) from MIROC presented the highest changes in the precipitation mean ( 60%) when compared with the observations.

Evaluation of Historical and Projected Surface Air Temperature Simulations over China in CMIP5

NASA Astrophysics Data System (ADS)

Chen, L.; Frauenfeld, O. W.

2013-12-01

Projections of future temperature in China are crucial for assessments of climate change and implementation of appropriate adaptation and mitigation strategies. With the upcoming Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5), the fifth phase of the Coupled Model Intercomparison Project (CMIP5) was developed for assessing the latest state-of-the-art climate models and their projections. In this study, monthly surface air temperature from 20 CMIP5 models and four experiments (historical, RCP 2.6, RCP 4.5, and RCP 8.5) were used to investigate the temperature variability over China during the 20th century, and future changes for the 21st century. Two observational datasets (CRU TS 3.1 and the global terrestrial air temperature dataset from the University of Delaware) were adopted to evaluate the performance of the CMIP5 multimodel ensemble average, the performance of individual models, as well as the possible improvements in CMIP5 relative to CMIP3. Results show that both CMIP3 and CMIP5 have cold biases over most parts of China. CMIP5 displays a slightly better agreement with the observations than CMIP3, but substantial cold biases still exist over the Tibetan Plateau, especially in the cold season. These biases are also characterized by the greatest discrepancies among the individual models, indicating the models' limitations over this mountainous region. Both CMIP3 and CMIP5 show poor agreement with observed 20th-century temperature trends such that the spatial and seasonal patterns of the trends are not captured in the multimodel ensemble averages. Comparing individual models we find that MPI-ESM-LR, CanESM2, MIROC-ESM, and CCSM4 exhibit better skill than the other models in this part of the world. Projections of future temperature suggest that there will be a gradual increase in annual surface air temperature in China during the 21st century at a rate of 0.60°C/decade and 0.27°C/decade under the RCP 8.5 and RCP 4.5 scenarios, respectively. RCP 2.6 shows the slowest warming at a rate of 0.10°C/decade for the whole 21st century, but temperature will increase until 2040, and then remain stable or even decrease slightly. Based on the three emission scenarios, annual temperatures are projected to rise by 1.7-5.7°C by the end of the 21st century, and the greatest warming will occur over northern China and the Tibetan Plateau.

Diachronous high-latitude North Atlantic temperature evolution across the last interglaciation

NASA Astrophysics Data System (ADS)

Carlson, A. E.; He, F.; Clark, P. U.

2017-12-01

A direct response of Northern Hemisphere temperatures to last interglacial boreal summer insolation forcing and atmospheric carbon dioxide concentration would predict early interglacial warmth followed by a gradual cooling trend across the last interglaciation (128-116 ka). In contrast, some Labrador and Greenland-Iceland-Norwegian (GIN) sea surface temperature (SST) records show relatively cool early last-interglacial SSTs followed by warming in the latter part of the interglaciation. This phenomenon has sometimes been attributed to meltwater forcing from continued retreat of the Greenland ice sheet through the last interglaciation that suppressed North Atlantic overturning circulation, in agreement with proxy records. Here we investigate this observation with the first fully-coupled transient general circulation model simulation of the last interglacial period using CCSM3. Termination II deglacial meltwater forcing is stopped at 129 ka and the subsequent simulation is forced by changing orbital parameters and atmospheric greenhouse gases. We find that Labrador and GIN SSTs remain relatively cool followed by warming to peak interglacial temperatures after 124 ka. We show that this delayed warming is due to reduced convection in the GIN sea, despite a cessation of meltwater forcing at 129 ka, with convection onset at 124 ka and attendant sea-ice retreat in response to orbital- and greenhouse gas-forcing alone. Our results demonstrate that delayed high-latitude North Atlantic SST warming during the last interglaciation does not necessitate meltwater forcing from the Greenland ice sheet, rectifying the apparent disconnect between a small meltwater forcing (<2.5 m of sea-level rise over 8 ka, or <0.004 Sverdrups into the Labrador and GIN seas) and a relatively large North Atlantic overturning response.

Climate implications of including albedo effects in terrestrial carbon policy

NASA Astrophysics Data System (ADS)

Jones, A. D.; Collins, W.; Torn, M. S.; Calvin, K. V.

2012-12-01

Proposed strategies for managing terrestrial carbon in order to mitigate anthropogenic climate change, such as financial incentives for afforestation, soil carbon sequestration, or biofuel production, largely ignore the direct effects of land use change on climate via biophysical processes that alter surface energy and water budgets. Subsequent influences on temperature, hydrology, and atmospheric circulation at regional and global scales could potentially help or hinder climate stabilization efforts. Because these policies often rely on payments or credits expressed in units of CO2-equivalents, accounting for biophysical effects would require a metric for comparing the strength of biophysical climate perturbation from land use change to that of emitting CO2. One such candidate metric that has been suggested in the literature on land use impacts is radiative forcing, which underlies the global warming potential metric used to compare the climate effects of various greenhouse gases with one another. Expressing land use change in units of radiative forcing is possible because albedo change results in a net top-of-atmosphere radiative flux change. However, this approach has also been critiqued on theoretical grounds because not all climatic changes associated with land use change are principally radiative in nature, e.g. changes in hydrology or the vertical distribution of heat within the atmosphere, and because the spatial scale of land use change forcing differs from that of well-mixed greenhouse gases. To explore the potential magnitude of this discrepancy in the context of plausible scenarios of future land use change, we conduct three simulations with the Community Climate System Model 4 (CCSM4) utilizing a slab ocean model. Each simulation examines the effect of a stepwise change in forcing relative to a pre-industrial control simulation: 1) widespread conversion of forest land to crops resulting in approximately 1 W/m2 global-mean radiative forcing from albedo change, 2) an increase in CO2 concentrations that exactly balances the forcing from land use change at the global level, and 3) a simulation combining the first two effects, resulting in net zero global-mean forcing as would occur in an idealized carbon cap-and-trade scheme that accounts for the albedo effect of land use change. The pattern of land use change that we examine is derived from an integrated assessment model that accounts for population, demographic, technological, and policy changes over the 21st century. We find significant differences in the pattern of climate change associated with each of these forcing scenarios, demonstrating the non-additivity of radiative forcing from land-use change and greenhouse gases in the context of a hypothetical scenario of future land use change. These results have implications for the development of land use and climate policies.

Mechanisms Underlying Early Medieval Droughts in Mesoamerica

NASA Astrophysics Data System (ADS)

Bhattacharya, T.; Chiang, J. C. H.

2015-12-01

Multidecadal drought during the early Medieval Climate Anomaly (MCA, 800-1200 CE) in Mesoamerica has been implicated in the demise of many pre-Columbian societies, including the Maya. The mechanisms behind these droughts, however, are poorly understood. Researchers most often interpret these records as tracking the mean position of the ITCZ, with a southward shifted ITCZ resulting in Mesoamerican drought. This is puzzling, however, because our dynamical understanding of the ITCZ and its role in interhemispheric heat transport would suggest a more northward shifted ITCZ during the MCA. Here, we evaluate two hypotheses to reconcile existing proxies and dynamics. First, we assess whether evidence for dry conditions during the MCA is robust across multiple Mesoamerican proxy records, focusing on the influence of radiometric dating uncertainty on estimates of drought timing. Second, we use control simulations of CCSM4 and HadCM3, as well as a broader synthesis of oceanic and terrestrial proxies, to explore the mechanisms responsible for long-term drought in Mesoamerica. Ultimately, we suggest that a temporary slowdown of the AMOC, either internally or externally forced, combined with local and regional land surface feedbacks can explain these droughts in Mesoamerica.

Collaborative Project. 3D Radiative Transfer Parameterization Over Mountains/Snow for High-Resolution Climate Models. Fast physics and Applications

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

Liou, Kuo-Nan

2016-02-09

Under the support of the aforementioned DOE Grant, we have made two fundamental contributions to atmospheric and climate sciences: (1) Develop an efficient 3-D radiative transfer parameterization for application to intense and intricate inhomogeneous mountain/snow regions. (2) Innovate a stochastic parameterization for light absorption by internally mixed black carbon and dust particles in snow grains for understanding and physical insight into snow albedo reduction in climate models. With reference to item (1), we divided solar fluxes reaching mountain surfaces into five components: direct and diffuse fluxes, direct- and diffuse-reflected fluxes, and coupled mountain-mountain flux. “Exact” 3D Monte Carlo photon tracingmore » computations can then be performed for these solar flux components to compare with those calculated from the conventional plane-parallel (PP) radiative transfer program readily available in climate models. Subsequently, Parameterizations of the deviations of 3D from PP results for five flux components are carried out by means of the multiple linear regression analysis associated with topographic information, including elevation, solar incident angle, sky view factor, and terrain configuration factor. We derived five regression equations with high statistical correlations for flux deviations and successfully incorporated this efficient parameterization into WRF model, which was used as the testbed in connection with the Fu-Liou-Gu PP radiation scheme that has been included in the WRF physics package. Incorporating this 3D parameterization program, we conducted simulations of WRF and CCSM4 to understand and evaluate the mountain/snow effect on snow albedo reduction during seasonal transition and the interannual variability for snowmelt, cloud cover, and precipitation over the Western United States presented in the final report. With reference to item (2), we developed in our previous research a geometric-optics surface-wave approach (GOS) for the computation of light absorption and scattering by complex and inhomogeneous particles for application to aggregates and snow grains with external and internal mixing structures. We demonstrated that a small black (BC) particle on the order of 1 μm internally mixed with snow grains could effectively reduce visible snow albedo by as much as 5–10%. Following this work and within the context of DOE support, we have made two key accomplishments presented in the attached final report.« less

The Global Warming Hiatus Tied to the North Atlantic Oscillation and Its Prediction

NASA Astrophysics Data System (ADS)

Li, J.; Sun, C.

2015-12-01

The twentieth century Northern Hemisphere mean surface temperature (NHT) is characterized by a multidecadal warming-cooling-warming pattern followed by a flat trend since about 2000 (recent warming hiatus). Here we demonstrate that the multidcadal variability in NHT including the recent warming hiatus is tied to the North Atlantic Oscillation (NAO) and the NAO is implicated as a useful predictor of NHT multidecadal variability. Observational analysis shows that the NAO leads both the detrended NHT and oceanic Atlantic Multidecadal Oscillation (AMO) by 15-20 years. Theoretical analysis illuminates that the NAO precedes NHT multidecadal variability through its delayed effect on the AMO due to the large thermal inertia associated with slow oceanic processes. The CCSM4 model is employed to investigate possible physical mechanisms. The positive NAO forces the strengthening of the Atlantic meridional overturning circulation (AMOC) and induces a basin-wide uniform sea surface temperature (SST) warming that corresponds to the AMO. The SST field exhibits a delayed response to the preceding enhanced AMOC, and shows a pattern similar to the North Atlantic tripole (NAT), with SST warming in the northern North Atlantic and cooling in the southern part. This SST pattern (negative NAT phase) may lead to an atmospheric response that resembles the negative NAO phase, and subsequently the oscillation proceeds, but in the opposite sense. Based on these mechanisms, a simple delayed oscillator model is established to explain the quasi-periodic multidecadal variability of the NAO. The magnitude of the NAO forcing of the AMOC/AMO and the time delay of the AMOC/AMO feedback are two key parameters of the delayed oscillator. For a given set of parameters, the quasi 60-year cycle of the NAO can be well predicted. This delayed oscillator model is useful for understanding of the oscillatory mechanism of the NAO, which has potential for decadal predictions as well as the interpretation of proxy data records. An NAO-based linear model is therefore established to predict the NHT, which gives an excellent hindcast for NHT in 1971-2011 with the recent flat trend well predicted. NHT in 2012-2027 is predicted to fall slightly over the next decades, due to the recent NAO decadal weakening that temporarily offsets the anthropogenically induced warming.

Regional climate simulations over complex topography using WRF: Andalusian present climate

NASA Astrophysics Data System (ADS)

Argüeso, D.; Hidalgo-Muñoz, J. M.; Calandria-Hernández, D.; Gámiz-Fortis, S. R.; Esteban-Parra, M. J.; Castro-Díez, Y.

2010-09-01

In this study three WRF simulations were carried out and analyzed to assess its accuracy to describe the main climate features of Southern Spain in terms of maximum temperature, minimum temperature and precipitation. Present climate was represented by the last 30 year of the 20th Century (1970-1999). The model was evaluated using an observational network distributed throughout Andalusia that comprised both temperatures and precipitation. Since comparison between site-specific measurements and model grid points is definitely troublesome due to differences in spatial-scale, a multi-step regionalization strategy was adopted to upscale observational information. This is of particular importance when studying complex topography regions such as Andalusia, with a wide range of climate conditions in a relative small area. Additionally, WRF outputs were also compared with SPAIN02, a 20-km resolution gridded dataset of precipitation for further validation of the model performance. The model set up consisted in two domains with one-way nesting and spectral nudging. The target domain has a resolution of 10km with 136 by 136 points covering the whole Iberian Peninsula and nested in a coarser domain of 30-km resolution and 130 by 120 grid points. Both domains have 35 vertical levels. Three different driving data were used to provide the boundary conditions, one reanalysis (ERA-40) and two control runs from different General Circulation Models (ECHAM5 and CCSM 3.0). A conservative 7-month spin-up period was added to the 30-year simulation so that dependence on initial conditions can be completely removed. Physics options were chosen on the basis of previous parameterization sensitivity tests over Andalusia that led to a compromise configuration that adequately describes the different subclimates. Probability distributions of daily values as well as monthly statistics were examined to determine the uncertainties associated to each variable and take them into consideration for future regional high-resolution projections of climate change scenarios. These analyses permitted to conclude that WRF is an extremely useful tool due to the significant value-added information produced with respect to the driving data. Nonetheless, according to differences in performance between regions it has also been shown that results must be interpreted carefully depending on the region characteristics. Acknowledgements: The Spanish Ministry of Science and Innovation, with additional support from the European Community Funds (FEDER), project CGL2007-61151/CLI, and the Regional Government of Andalusia project P06-RNM-01622, have financed this study.

The spectral details of observed and simulated short-term water vapor feedbacks of El Niño-Southern Oscillation

NASA Astrophysics Data System (ADS)

Pan, F.; Huang, X.; Chen, X.

2015-12-01

Radiative kernel method has been validated and widely used in the study of climate feedbacks. This study uses spectrally resolved longwave radiative kernels to examine the short-term water vapor feedbacks associated with the ENSO cycles. Using a 500-year GFDL CM3 and a 100-year NCAR CCSM4 pre-industry control simulation, we have constructed two sets of longwave spectral radiative kernels. We then composite El Niño, La Niña and ENSO-neutral states and estimate the water vapor feedbacks associated with the El Niño and La Niña phases of ENSO cycles in both simulations. Similar analysis is also applied to 35-year (1979-2014) ECMWF ERA-interim reanalysis data, which is deemed as observational results here. When modeled and observed broadband feedbacks are compared to each other, they show similar geographic patterns but with noticeable discrepancies in the contrast between the tropics and extra-tropics. Especially, in El Niño phase, the feedback estimated from reanalysis is much greater than those from the model simulations. Considering the observational data span, we carry out a sensitivity test to explore the variability of feedback-deriving using 35-year data. To do so, we calculate the water vapor feedback within every 35-year segment of the GFDL CM3 control run by two methods: one is to composite El Nino or La Nina phases as mentioned above and the other is to regressing the TOA flux perturbation caused by water vapor change (δR_H­2O) against the global-mean surface temperature a­­­­nomaly. We find that the short-term feedback strengths derived from composite method can change considerably from one segment to another segment, while the feedbacks by regression method are less sensitive to the choice of segment and their strengths are also much smaller than those from composite analysis. This study suggests that caution is warranted in order to infer long-term feedbacks from a few decades of observations. When spectral details of the global-mean feedbacks are examined, more inconsistencies can be revealed in many spectral bands, especially H2O continuum absorption bands and window regions. These discrepancies can be attributed back to differences in observed and modeled water vapor profiles in responses to tropical SST.

Projections of wind-waves in South China Sea for the 21st century

NASA Astrophysics Data System (ADS)

Mohammed, Aboobacker; Dykyi, Pavlo; Zheleznyak, Mark; Tkalich, Pavel

2013-04-01

IPCC-coordinated work has been completed within Fourth Assessment Report (AR4) to project climate and ocean variables for the 21st century using coupled atmospheric-ocean General Circulation Models (GCMs). GCMs are not having a wind-wave variable due to a poor grid resolution; therefore, dynamical downscaling of wind-waves to the regional scale is advisable using well established models, such as Wave Watch III (WWIII) and SWAN. Rectilinear-coordinates WWIII model is adapted for the far field comprising the part of Pacific and Indian Oceans centered at the South China Sea and Sunda Shelf (90 °E-130 °E, 10 °S - 26.83 °N) with a resolution of 10' (about 18 km). Near-field unstructured-mesh SWAN model covers Sunda Shelf and centered on Singapore Strait, while reading lateral boundary values from WWIII model. The unstructured grid has the coarsest resolution in the South China Sea (6 to 10 km), medium resolution in the Malacca Strait (1 to 2 km), and the finest resolution in the Singapore Strait (400 m) and along the Singapore coastline (up to 100 m). Following IPCC methodology, the model chain is validated climatologically for the past period 1961-1990 against Voluntary Observing Ship (VOS) data; additionally, the models are validated using recent high-resolution satellite data. The calibrated model chain is used to project waves to 21st century using WRF-downscaled wind speed output of CCSM GCM run for A1FI climate change scenario. To comply with IPCC methodology the entire modeling period is split into three 30-years periods for which statistical parameters are computed individually. Time series of significant wave height at key points near Singapore and on ship sea routes in the SCS are statistically analysed to get probability distribution functions (PDFs) of extreme values. Climatological maps of mean and maximum significant wave height (SWH) values, and mean wave period are built for Singapore region for each 30-yrs period. Linear trends of mean SWH values for northeast (NE) and southwest (SW) monsoons have been derived. The maximum values of predicted 100 year return period (YRP) SWH are obtained for the 1st 30-yrs period (2011-2040). In the deep eastern part of the Singapore, 100yrp SWH are 2.4 - 2.8 m, whereas those at the shallow nearshore areas are 1.7-2.3 m. On the ship routes at Sunda Shelf the 100 YRP SWHs are 1.1 - 3.2 m, and those at the SCS routes are 3.6 - 10.4 m. The biggest changes in future against hindcasted SWH is in first 30-yrs, where extreme 100 YRP SWH will grow up in the range from 36%-120% at points near Singapore and to 39%-108% at ship sea routes.

Drastic shifts in the Levant hydroclimate during the last interglacial indicate changes in the tropical climate and winter storm tracks

NASA Astrophysics Data System (ADS)

Kiro, Y.; Goldstein, S. L.; Kushnir, Y.; Lazar, B.; Stein, M.

2017-12-01

Marine Isotope Stage (MIS) 5e was a warm interglacial with where with significantly varying insolation and hence varied significantly throughout this time suggesting highly variable climate. The ICDP Dead Sea Deep Drilling Project recovered a 460m record of the past 220ka, reflecting the variable climate along MIS 5e. This time interval is reflected by alternating halite and detritus sequences, including 20m of halite-free detritus during the peak insolation at 125 ka. The Dead Sea salt budget indicates that the Levant climate was extremely arid when halite formed, reaching 20% of the present runoff. The halite-free detritus layer reflects increased precipitation to levels similar to present day, assuming similar spatial and temporal rainfall patterns. However, the 234U/238U activity ratio in the lake, reflected by authigenic minerals (aragonite, gypsum and halite), shifts from values of 1.5 (reflecting the Jordan River, the present main water source) down to 1.3 at 125-122ka during the MIS5e insolation peak and 1.0 at 118-116ka. The low 234U/238U reflects increased flash floods and eastern water sources (234U/238U 1.05-1.2) from the drier part of the watershed in the desert belt. The intermediate 234U/238U of 1.3 suggests that the Jordan River, fed from Mediterranean-sourced storm tracks, continued to flow along with an increase in southern and eastern water sources. NCAR CCSM3 climate model runs for 125ka indicate increases in both Summer and Winter precipitation. The drastic decrease to 234U/238U 1.0 occurs during the driest period, indicating a near shutdown of Jordan River flow, and water input only through flash floods and southern and eastern sources. The 120ka climate model runs shows a decrease in Winter and increase in Fall precipitation as a result of an increased precipitation in the tropics. The extreme aridity, associated with increased flooding is similar to patterns expected due to future warming. The increase in aridity is the result of expansion of the desert-belt and increases in southern precipitation and indicates an important link between the tropical and mid-latitude climate.

ENSO and its modulations on annual and multidecadal timescales revealed by Nonlinear Laplacian Spectral Analysis

NASA Astrophysics Data System (ADS)

Giannakis, D.; Slawinska, J. M.

2016-12-01

The variability of the Indo-Pacific Ocean on interannual to multidecadal timescales is investigated in a millennial control run of CCSM4 and in observations using a recently introduced technique called Nonlinear Laplacian Spectral Analysis (NLSA). Through this technique, drawbacks associated with ad hoc pre-filtering of the input data are avoided, enabling recovery of low-frequency and intermittent modes not accessible previously via classical approaches. Here, a multiscale hierarchy of modes is identified for Indo-Pacific SST and numerous linkages between these patterns are revealed. On interannual timescales, a mode with spatiotemporal pattern corresponding to the fundamental component of ENSO emerges, along with modulations of the annual cycle by ENSO in agreement with ENSO combination mode theory. In spatiotemporal reconstructions, these patterns capture the seasonal southward migration of SST and zonal wind anomalies associated with termination of El Niño and La Niña events. Notably, this family of modes explains a significant portion of SST variance in Eastern Indian Ocean regions employed in the definition of Indian Ocean dipole (IOD) indices, suggesting that it should be useful for understanding the linkage of these indices with ENSO and the interaction of the Indian and Pacific Oceans. In model data, we find that the ENSO and ENSO combination modes are modulated on multidecadal timescales by a mode predominantly active in the western tropical Pacific - we call this mode West Pacific Multidecadal Oscillation (WPMO). Despite the relatively low variance explained by this mode, its dynamical role appears to be significant as it has clear sign-dependent modulating relationships with the interannual modes carrying most of the variance. In particular, cold WPMO events are associated with anomalous Central Pacific westerlies favoring stronger ENSO events, while warm WPMO events suppress ENSO activity. Moreover, the WPMO has significant climatic impacts as demonstrated here through its strong correlation with decadal precipitation over Australia. As an extension of this work, we discuss the deterministic and stochastic aspects of the variability of these modes and their potential predictability based on nonparametric kernel analog forecasting techniques.

Future stable water isotope projection with an isotope-AGCM driven by CMIP5 SSTs

NASA Astrophysics Data System (ADS)

Yoshimura, K.

2016-12-01

Stable water isotope ratios (dD and d18O) are widely used as proxy of past climate changes, and it is extremely important to understand and predict the mechanism of current isotopic spatio-temporal behavior with regard to the on-going climate change. However, as compared many studies on reproduction of isotopes for the past, there are few studies on future projection of isotopes. Therefore, in this study, a set of experiments using an isotope-incorporate AGCM (IsoGSM) with SST and sea ice field simulated from multiple CMIP5 models, namely MIROC5, CCSM4, and MRI-CGCM3, were conducted for the end of 20th century (1980-1990) and the end of 21st century (2080-2090) under RCP2.6 and RCP8.5 scenarios. Thus the responses in stable water isotope ratio in precipitation and water vapor in accordance to the global warming were investigated. As results, the changes in global surface air temperature were about +1K and +3K with RCP2.6 and RCP8.5, respectively. Similarly, the global precipitation changes were about +0.07mm/day (about +2%) and +0.18mm/day (about +5%), and the global precipitable water changes were about +2mm (+7%) and +6mm (+24%), respectively. The moisture was increased in accordance to the Clausius-Clapayron theory (7%/K), but the increase in precipitation is not that large. This indicates that the global hydrological cycle was slowed down in the globally warmed experiments. On the other hand, for the isotopic signals, the changes in globally averaged d18O in precipitation were about 0.2‰ and 0.4‰, and those in precipitable water were 0.2‰ and 0.5‰, in RCP2.6 and RCP8.5, respectively. It is well-known that there are temperature effect (positive correlation in air temperature and precipitation isotopes) and amount effect (negative correlation in precipitation amount and isotopes), but in the globally warmed world, these effects were offset, and only weaker temperature effect was appeared in the global mean isotope signals. Regional details will be shown in the presentation.

Hydrological cycle during the early Eocene: What can we learn from leaf waxes?

NASA Astrophysics Data System (ADS)

Krishnan, S.; Pagani, M.; Huber, M.

2012-12-01

Understanding how rapid warming modified global precipitation patterns during periods of global warming is essential to forecasting the impact of future climate change. The early Eocene (~55-52 Ma) represents a period of peak warmth for the past 65 million years with global temperatures ~10 degrees C warmer than present. This period is also known for at least three, greenhouse gas-induced episodes of rapid global warming (hyperthermals: PETM; ~55 Ma, ETM-2; ~53.7 Ma and ETM-3; 52.8 Ma), often considered extreme analogues to modern climate change. Hyperthermals are also characterized by negative carbon isotope excursions (CIE), which reflect the input of isotopically light carbon responsible for observed temperature increases. A novel proxy used for hydrological reconstructions uses the hydrogen isotopic composition of compound-specific biomarkers preserved in the sedimentary record. For terrestrial leaf-wax lipids (e.g., n-alkanes), the hydrogen isotopic composition primarily reflects the isotopic composition of meteoric waters, which is dependent on distance of vapor transport, number of rainout events, precipitation amount, and evapotranspiration. Isotopic compositions of PETM n-alkanes (δDalkanes) recovered from the Arctic Ocean show a substantial deuterium (D)-enrichment at the onset of the CIE which was argued to potentially reflect reduced rainout in the mid-latitudes, resulting in increased precipitation in the Arctic (Pagani et al., 2006). D-depleted values of n-alkanes during peak warmth of the PETM suggest either modification of local precipitation or a global change in the fraction of rainout. In this study, we evaluate the veracity of previous conclusions by compiling existing δDalkanes records (including from Mar-2X, Venezuela; Tawanui, New Zealand; Wilkes Land, Antarctica; and the Lomonsov Ridge, Arctic) with new records from the Pacific and Atlantic oceans and marginal marine sections (including Cicogna, Italy; Giraffe Core, Canadian High Arctic). To determine the background state of the hydrological cycle in a warmer world, we measured early Eocene δDalkanes at these sites. This compilation was then compared against results from the isotope-coupled National Center for Atmospheric Research (NCAR) Community Climate System Model v3.0 (CCSM) global climate model, with Eocene boundary conditions and two different pCO2 levels (2240 and 4480 ppm). Preliminary analyses suggest that the model is able to simulate the equator-pole trends in precipitation δD. However, predicted values are offset from the n-alkane data by up to 40‰. To study changes in the hydrological cycle with rapid warming, we analyze n-alkane δD and δ13C values for the PETM and ETM-2. Leads and lags between the carbon and hydrogen isotopic records help constrain the timing and type of hydrological shifts with respect to carbon input. Preliminary results from the ETM-2 recovered from the Arctic indicate similar hydrological changes during both hyperthermals. A pre-event increase in δD values (of 60‰ during the PETM and 25‰ during ETM-2) is observed, followed by a decrease in δD (~10-15‰ for both the events) during the peak of the CIE. A significant pre-PETM D-enrichment at mid-latitudes is not evident, however, more negative δD values during the CIE is observed in some sites. The reasons for these isotopic shifts and their implication for the local and global water cycles will be discussed.

Changes in future air quality, deposition, and aerosol-cloud interactions under future climate and emission scenarios

NASA Astrophysics Data System (ADS)

Glotfelty, Timothy; Zhang, Yang; Karamchandani, Prakash; Streets, David G.

2016-08-01

The prospect of global climate change will have wide scale impacts, such as ecological stress and human health hazards. One aspect of concern is future changes in air quality that will result from changes in both meteorological forcing and air pollutant emissions. In this study, the GU-WRF/Chem model is employed to simulate the impact of changing climate and emissions following the IPCC AR4 SRES A1B scenario. An average of 4 future years (2020, 2030, 2040, and 2050) is compared against an average of 2 current years (2001 and 2010). Under this scenario, by the Mid-21st century global air quality is projected to degrade with a global average increase of 2.5 ppb in the maximum 8-hr O3 level and of 0.3 μg m-3 in 24-hr average PM2.5. However, PM2.5 changes are more regional due to regional variations in primary aerosol emissions and emissions of gaseous precursor for secondary PM2.5. Increasing NOx emissions in this scenario combines with a wetter climate elevating levels of OH, HO2, H2O2, and the nitrate radical and increasing the atmosphere's near surface oxidation state. This differs from findings under the RCP scenarios that experience declines in OH from reduced NOx emissions, stratospheric recovery of O3, and increases in CH4 and VOCs. Increasing NOx and O3 levels enhances the nitrogen and O3 deposition, indicating potentially enhanced crop damage and ecosystem stress under this scenario. The enhanced global aerosol level results in enhancements in aerosol optical depth, cloud droplet number concentration, and cloud optical thickness. This leads to dimming at the Earth's surface with a global average reduction in shortwave radiation of 1.2 W m-2. This enhanced dimming leads to a more moderate warming trend and different trends in radiation than those found in NCAR's CCSM simulation, which does not include the advanced chemistry and aerosol treatment of GU-WRF/Chem and cannot simulate the impacts of changing climate and emissions with the same level of detailed treatments. This study indicates that effective climate mitigation and emission control strategies are needed to prevent future health impact and ecosystem stress. Further, studies that are used to develop these strategies should use fully coupled models with sophisticated chemical and aerosol-interaction treatments that can provide a more realistic representation of the atmosphere.

Evolution in Intensity and Frequency of Extreme Events of Precipitation in Northeast Region and Brazilian Amazon in XXI Century

NASA Astrophysics Data System (ADS)

Fonseca, P. M.; Veiga, J. A.; Correia, F. S.; Brito, A. L.

2013-05-01

The aim of this research was evaluate changes in frequency and intensity of extreme events of precipitation in Brazilian Amazon and Northeast Region, doubling CO2 concentration in agreement of IPCC A2 emissions scenarios (Nakicenovic et al., 2001). For this evaluation was used ETA model (Chou et al., 2011), forced with CCSM3 Global model data (Meehl, 2006) to run 4 experiments, only for January, February and March: 1980-1990, 2000-2010, 2040-2050 and 2090-2100. Using the first decade as reference (1980-1990), was evaluated changes occurred in following decades, with a methodology to classify extremes events adapted from Frich (2002) and Gao (2006). Higher was the class, more intense is the event. An increase of 25% was observed in total precipitation in Brazilian Amazon for the end of XXI century and 12% for extreme events type 1, 9% for events type 2 and 10% for type 3. By the other hand, a 17% decrease of precipitation in Brazilian Northeast was observed, and a pronounced decay of 24% and 15% in extreme events contribution type 1 and 2 to total amount of precipitation, respectively. The difference between total normal type events was positive in this three decades compared with reference decade 1980-1990, varying positively from 4 to 6 thousand events included in normality by decade, these events was decreased in your majority of Class 1 events, which presented a decay of at least 3.500 events by each decade. This suggests an intensification of extreme events, considering that the amount of precipitation by class increased, and the number of events by class decreased. To Northeast region, an increasing in 9% of contribution to events type 3 class was observed, as well as in the frequency of this type of events (about of 700 more events). Major decreasing in number of classes extreme events occur in 2000-2010, to classes 1 and 3, with 7,2 and 5,6%, and by the end of century in class 3, with 4,5%. For the three analyzed decades a total decrease of 8.400 events was accounted. This first results support an increase in occurrence of determined extreme events classes/types of precipitation, but also an increase of precipitation in raining seasons in Amazon region, as well as an increase in the intensity of dry season in Northeast region.

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

Glotfelty, Timothy; Zhang, Yang; Karamchandani, Prakash

The prospect of global climate change will have wide scale impacts, such as ecological stress and human health hazards. One aspect of concern is future changes in air quality that will result from changes in both meteorological forcing and air pollutant emissions. In this study, the GU-WRF/Chem model is employed to simulate the impact of changing climate and emissions following the IPCC AR4 SRES A1B scenario. An average of 4 future years (2020, 2030, 2040, and 2050) is compared against an average of 2 current years (2001 and 2010). Under this scenario, by the Mid-21st century global air quality ismore » projected to degrade with a global average increase of 2.5 ppb in the maximum 8-hr O 3 level and of 0.3 mg m 3 in 24-hr average PM2.5. However, PM2.5 changes are more regional due to regional variations in primary aerosol emissions and emissions of gaseous precursor for secondary PM2.5. Increasing NOx emissions in this scenario combines with a wetter climate elevating levels of OH, HO 2, H 2O 2, and the nitrate radical and increasing the atmosphere’s near surface oxidation state. This differs from findings under the RCP scenarios that experience declines in OH from reduced NOx emissions, stratospheric recovery of O 3, and increases in CH 4 and VOCs. Increasing NO x and O 3 levels enhances the nitrogen and O 3 deposition, indicating potentially enhanced crop damage and ecosystem stress under this scenario. The enhanced global aerosol level results in enhancements in aerosol optical depth, cloud droplet number concentration, and cloud optical thickness. This leads to dimming at the Earth’s surface with a global average reduction in shortwave radiation of 1.2 W m 2 . This enhanced dimming leads to a more moderate warming trend and different trends in radiation than those found in NCAR’s CCSM simulation, which does not include the advanced chemistry and aerosol treatment of GU-WRF/Chem and cannot simulate the impacts of changing climate and emissions with the same level of detailed treatments. This study indicates that effective climate mitigation and emission control strategies are needed to prevent future health impact and ecosystem stress. Further, studies that are used to develop these strategies should use fully coupled models with sophisticated chemical and aerosol-interaction treatments that can provide a more realistic representation of the atmosphere.« less

'Work it out': evaluation of a chronic condition self-management program for urban Aboriginal and Torres Strait Islander people, with or at risk of cardiovascular disease.

PubMed

Mills, Kyly; Gatton, Michelle L; Mahoney, Ray; Nelson, Alison

2017-09-26

Chronic diseases disproportionately burden Aboriginal and Torres Strait Islander people in Australia, with cardiovascular (CV) diseases being the greatest contributor. To improve quality of life and life expectancy for people living with CV disease, secondary prevention strategies such as rehabilitation and self-management programs are critical. However, there is no published evidence examining the effect of chronic condition self-management (CCSM) group programs for Aboriginal and Torres Strait Islander people who have, or are at risk of, CV disease specifically. This study evaluates the Work It Out program for its effect on clinical outcome measures in urban Aboriginal and Torres Strait Islander participants with or at risk of CV disease. This study was underpinned by a conceptual framework based on Aboriginal and Torres Strait Islander community control. Participants had at least one diagnosed CV disease, or at least one CV disease risk factor. Short-term changes in clinical outcome measures over (approximately) 12 weeks were evaluated with a quasi-experimental, pre-post test design, using paired t-tests. Factors contributing to positive changes were tested using general linear models. The outcome measures included blood pressure (mmHg), weight (kg), body mass index (kg/m 2 ), waist and hip circumference (cm), waist to hip ratio (waist cm/hip cm) and six minute walk test (6MWT). Changes in several clinical outcome measures were detected, either within the entire group (n = 85) or within specific participant sub-groups. Participant's 6MWT distance improved by an average 0.053 km (95% CI: 0.01-0.07 km). The change in distance travelled was influenced by number of social and emotional wellbeing conditions participants presented with. The weight of participants classified with extreme obesity decreased on average by 1.6 kg (95% CI: 0.1-3.0 kg). Participants with high baseline systolic blood pressure demonstrated a mean decrease of 11 mmHg (95% CI: 3.2-18.8 mmHg). Change in blood pressure was influenced by the number of cardiovascular conditions participants experienced. Short-term improvements seen in some measures could indicate a trend for improvement in other indicators over the longer term. These results suggest the Work It Out program could be a useful model for cardiovascular rehabilitation and prevention for other urban Aboriginal and Torres Strait Islander populations.

Sensitivity of Methane Lifetime and Transport to Sulfate Geoengineering

NASA Astrophysics Data System (ADS)

Aquila, V.; Pitari, G.; Tilmes, S.; Cionni, I.; de Luca, N.; Di Genova, G.; Iachetti, D.

2014-12-01

Sulfate geoengineering, made by sustained injection of SO2 in the tropical lower stratosphere, may impact the abundance of tropospheric methane through several photochemical mechanisms affecting the tropospheric OH abundance and hence the methane lifetime. Changes of the stratospheric Brewer-Dobson circulation also play a role in the upper tropospheric CH4 transport. Three mechanisms lead to lower OH concentrations and a longer CH4 lifetime: (a) solar radiation scattering increases the planetary albedo and cools the surface, with a tropospheric water vapor decrease as a response to this cooling. (b) The tropospheric UV budget is upset by the additional aerosol scattering and stratospheric ozone changes: the net effect is meridionally not uniform, with a net decrease in the tropics, thus producing less tropospheric O(1D). (c) The extra-tropical downwelling motion from the lower stratosphere tends to increase the sulfate aerosol surface area density available for heterogeneous chemical reactions in the mid-upper troposphere, thus reducing the amount of NOx and tropospheric O3 production. On the other hand, the tropical lower stratosphere is warmed by solar and planetary radiation absorption by the aerosols. The heating rates perturbation are strongly latitude dependent, producing a significant change of the pole-to-equator temperature gradient and mean zonal wind distribution, with a net increase of tropical upwelling. A stronger meridional component of the Brewer-Dobson circulation increases the extra-tropical stratosphere to troposphere transport of CH4 poorer air, resulting in less CH4 transported in the UTLS. The net effect on tropospheric OH may be positive or negative depending on the net result of different superimposed species perturbations in the UTLS, i.e. CH4 (negative), NOy and O3 (positive). Three climate-chemistry coupled models are used here to explore the above radiative, chemical and dynamical mechanisms affecting the methane lifetime (ULAQ-CCM, GEOSCCM, CCSM-CAM4). First results show that the CH4 lifetime may become significantly longer (by about 10%) with a sustained injection of 2.5 Tg-S/yr started in year 2020, which implies an increase of tropospheric CH4 (200 ppbv) and a positive indirect radiative forcing of sulfate geoengineering due to CH4 changes (+0.1 W/m2 in the 2045).

Analyzing the future climate change of Upper Blue Nile River basin using statistical downscaling techniques

NASA Astrophysics Data System (ADS)

Fenta Mekonnen, Dagnenet; Disse, Markus

2018-04-01

Climate change is becoming one of the most threatening issues for the world today in terms of its global context and its response to environmental and socioeconomic drivers. However, large uncertainties between different general circulation models (GCMs) and coarse spatial resolutions make it difficult to use the outputs of GCMs directly, especially for sustainable water management at regional scale, which introduces the need for downscaling techniques using a multimodel approach. This study aims (i) to evaluate the comparative performance of two widely used statistical downscaling techniques, namely the Long Ashton Research Station Weather Generator (LARS-WG) and the Statistical Downscaling Model (SDSM), and (ii) to downscale future climate scenarios of precipitation, maximum temperature (Tmax) and minimum temperature (Tmin) of the Upper Blue Nile River basin at finer spatial and temporal scales to suit further hydrological impact studies. The calibration and validation result illustrates that both downscaling techniques (LARS-WG and SDSM) have shown comparable and good ability to simulate the current local climate variables. Further quantitative and qualitative comparative performance evaluation was done by equally weighted and varying weights of statistical indexes for precipitation only. The evaluation result showed that SDSM using the canESM2 CMIP5 GCM was able to reproduce more accurate long-term mean monthly precipitation but LARS-WG performed best in capturing the extreme events and distribution of daily precipitation in the whole data range. Six selected multimodel CMIP3 GCMs, namely HadCM3, GFDL-CM2.1, ECHAM5-OM, CCSM3, MRI-CGCM2.3.2 and CSIRO-MK3 GCMs, were used for downscaling climate scenarios by the LARS-WG model. The result from the ensemble mean of the six GCM showed an increasing trend for precipitation, Tmax and Tmin. The relative change in precipitation ranged from 1.0 to 14.4 % while the change for mean annual Tmax may increase from 0.4 to 4.3 °C and the change for mean annual Tmin may increase from 0.3 to 4.1 °C. The individual result of the HadCM3 GCM has a good agreement with the ensemble mean result. HadCM3 from CMIP3 using A2a and B2a scenarios and canESM2 from CMIP5 GCMs under RCP2.6, RCP4.5 and RCP8.5 scenarios were downscaled by SDSM. The result from the two GCMs under five different scenarios agrees with the increasing direction of three climate variables (precipitation, Tmax and Tmin). The relative change of the downscaled mean annual precipitation ranges from 2.1 to 43.8 % while the change for mean annual Tmax and Tmin may increase in the range from 0.4 to 2.9 °C and from 0.3 to 1.6 °C respectively.

An experimental study of the carbonation of serpentinite and partially serpentinised peridotites

NASA Astrophysics Data System (ADS)

Lacinska, Alicja M.; Styles, Michael T.; Bateman, Keith; Hall, Matthew; Brown, Paul D.

2017-06-01

In situ sequestration of CO2 in mantle peridotites has been proposed as a method to alleviate the amount of anthropogenic CO2 in the atmosphere. This study presents the results of eight-month long laboratory fluid-rock experiments on representative mantle rocks from the Oman-United Arab Emirates ophiolite to investigate this process. Small core samples (3 cm long) were reacted in wet supercritical CO2 and CO2-saturated brine at 100 bar and 70°C. The extent of carbonate formation, and hence the degree of carbon sequestration, varied greatly depending on rock type, with serpentinite (lizardite-dominated) exhibiting the highest capacity, manifested by the precipitation of magnesite MgCO3 and ferroan magnesite (Mg,Fe)CO3. The carbonate precipitation occurred predominantly on the surface of the core and subordinately within cross-cutting fractures. The extent of the CO2 reactions appeared to be principally controlled by the chemical and mineralogical composition of the rock, as well as the rock texture, with all these factors influencing the extent and rate of mineral dissolution and release of Mg and Fe for subsequent reaction with the CO2. It was calculated that ≈ 0.7 g of CO2 was captured by reacting ≈ 23 g of serpentinite, determined by the mass of magnesite formed. This equates to ≈ 30 kg CO2 per tonne of host rock, equivalent to ≈ 3% carbonation in half a year. However, recycling of carbonate present in veins within the original rock sample could mean that the overall amount is around 2%. The increased reactivity of serpentinite was associated with preferential dissolution of more reactive types of serpentine minerals and brucite, that were mainly present in the cross-cutting veins. The bulk of the serpentinite rock was little affected. This study, using relatively short term experiments, suggests that serpentinite might be a good host rock for CO2 sequestration, although long term experiments might prove that dunite and harzburgite could be an effective in an engineered system of CCSM. Wet scCO2 proved to be chemically aggressive than CO2-saturated brine and its ingress along fractures and grain boundaries resulted in greater host rock dissolution and subsequent carbonate precipitation.

The Global Climate Anomaly in 1940-1942

NASA Astrophysics Data System (ADS)

Brönnimann, S.; Luterbacher, J.; Staehelin, J.; Svendby, T. M.

2003-12-01

An unprecedented climatic anomaly occurred in the tropics and in the Northern Hemisphere in 1940-1942. During a strong and prolonged El Niño [Bigg & Inoué, QJRMS 118 (1992), 125], extremely cold winters were observed in Europe, accompanied by very warm temperatures in Alaska and large parts of the Arctic and a cold North Pacific. The anomalies were strong (comprising the two coldest European winters of the 20th century) and extraordinarily persistent. In addition, exceptionally high values of total ozone are reported [Langlo, Geofys. Publ. 18/6 (1952)], pointing to an anomalous stratospheric circulation. Events of this magnitude have a strong economical and environmental impact; the 1940s anomaly even affected World War II. Studying this anomaly in detail contributes to (1) document the extent of 20th century climate variability, (2) understand large-scale coupling processes between the tropics and the extratropics and between the troposphere and the stratosphere and (3) develop tools to analyze past upper-level climate variability prior to 1948, i.e., the reanalysis period. For this study we have compiled, digitized, and re-evaluated several tens of thousands of temperature and pressure profiles from aircraft and radiosonde ascents up to 50 hPa [Brönnimann, Int. J. Clim. 23 (2003), 769]. The upper-air data were supplemented with data from the Earth's surface and used to statistically reconstruct monthly upper-level fields for the extratropical Northern Hemisphere up to 100 hPa [Brönnimann & Luterbacher, Clim. Dyn., submitted]. Although the quality of the reconstructed stratospheric fields is not comparable to more recent data, it is sufficient to allow a broad characterization of the circulation at 100 hPa during the early 1940s. In addition to upper-air data, several total ozone series from the 1940s were re-evaluated [Brönnimann et al., QJRMS 129 (2003), 2819], providing further information on the stratosphere. In this paper we present an analysis of these new data sets and compare the results to climate model data. It is demonstrated that the climate anomaly at the ground was accompanied in the lower stratosphere by a weak polar vortex and warm temperatures over the polar region, Eurasia, and the North Pacific. The total ozone data show a peak in 1940-1942 in all available records, at sites as far apart as China, North America, central Europe, and the Arctic. The co-occurrence of warm tropical SSTs (due to El Niño), a weak polar vortex and warm lower stratosphere over polar regions, and a total ozone increase is in agreement with findings by van Loon and Labitzke [Mon. Wea. Rev. 115 (1987), 357]. Using the 290-yr control run of the Community Climate System Model CCSM-2.0 provided by UCAR we show that such large-scale coupling events are related to an exceptionally large difference between tropical and northern-extratropical SSTs such as during strong El Niños. The coupling most likely proceeds through a change in planetary wave activity in the northern extratropics that manifests itself in a strong Aleutian low and a weak Icelandic low and in a disturbance of the polar vortex in the stratosphere. The 1940-1942 climate anomaly is not well known among scientists, but it is unprecedented in strength, yet exemplary in character, providing a unique opportunity to study large-scale climate variability.

Regional Climate Change Hotspots over Africa

NASA Astrophysics Data System (ADS)

Anber, U.

2009-04-01

Regional Climate Change Index (RCCI), is developed based on regional mean precipitation change, mean surface air temperature change, and change in precipitation and temperature interannual variability. The RCCI is a comparative index designed to identify the most responsive regions to climate change, or Hot- Spots. The RCCI is calculated for Seven land regions over North Africa and Arabian region from the latest set of climate change projections by 14 global climates for the A1B, A2 and B1 IPCC emission scenarios. The concept of climate change can be approaches from the viewpoint of vulnerability or from that of climate response. In the former case a Hot-Spot can be defined as a region for which potential climate change impacts on the environment or different activity sectors can be particularly pronounced. In the other case, a Hot-Spot can be defined as a region whose climate is especially responsive to global change. In particular, the characterization of climate change response-based Hot-Spot can provide key information to identify and investigate climate change Hot-Spots based on results from multi-model ensemble of climate change simulations performed by modeling groups from around the world as contributions to the Assessment Report of Intergovernmental Panel on Climate Change (IPCC). A Regional Climate Change Index (RCCI) is defined based on four variables: change in regional mean surface air temperature relative to the global average temperature change ( or Regional Warming Amplification Factor, RWAF ), change in mean regional precipitation ( , of present day value ), change in regional surface air temperature interannual variability ( ,of present day value), change in regional precipitation interannual variability ( , of present day value ). In the definition of the RCCI it is important to include quantities other than mean change because often mean changes are not the only important factors for specific impacts. We thus also include inter annual variability, which is critical for many activity sectors, such as agriculture and water management. The RCCI is calculated for the above mentioned set of global climate change simulations and is inter compared across regions to identify climate change, Hot- Spots, that is regions with the largest values of RCCI. It is important to stress that, as will be seen, the RCCI is a comparative index, that is a small RCCI value does not imply a small absolute change, but only a small climate response compared to other regions. The models used are: CCMA-3-T47 CNRM-CM3 CSIRO-MK3 GFDL-CM2-0 GISS-ER INMCM3 IPSL-CM4 MIROC3-2M MIUB-ECHO-G MPI-ECHAM5 MRI-CGCM2 NCAR-CCSM3 NCAR-PCM1 UKMO-HADCM3 Note that the 3 IPCC emission scenarios, A1B, B1 and A2 almost encompass the entire IPCC scenario range, the A2 being close to the high end of the range, the B1 close to the low end and the A1B lying toward the middle of the range. The model data are obtained from the IPCC site and are interpolated onto a common 1 degree grid to facilitate intercomparison. The RCCI is here defined as in Giorgi (2006), except that the entire yea is devided into two six months periods, D J F M A M and J J A S O N. RCCI=[n(∆P)＋n(∆σP)+n(RWAF)+n(∆σT)]D...M + [n(∆P)＋n(∆σP)+n(RWAF)+n(∆σT)]J…N (1)

Interpolation and Meta-Analysis of IPCC AR4 General Circulation Model Scenarios applied to North America

NASA Astrophysics Data System (ADS)

Price, D. T.; Joyce, L. A.; McKenney, D. W.

2009-12-01

Projections of future climate simulated by four state-of-art general circulation models (GCM), namely the U.S. NCAR CCSM 3.0, Canadian CGCM 3.1, Australian CSIRO Mk. 3.5 and Japanese MIROC 3.2, forced by each of the IPCC AR4 SRA2, SRB1 and SRA1B greenhouse gas (GHG) emissions scenarios, were downscaled for Canada and the continental USA. For each GCM projection, monthly climate values for a rectangle covering North America were interpolated using ANUSPLIN (e.g., Hutchinson 1995), to a common 0.0833° geographic grid. The resulting 12 high resolution scenarios provide projected change factors for monthly solar radiation, windspeed and vapor pressure, air temperature and precipitation, for the 21st century, referenced to the averages of simulated monthly means for 1961-1990. The 12 interpolated scenario data sets were subjected to a meta-analysis. Data for each projected variable of each climate scenario were averaged for three consecutive 30-year periods (starting in 2011), to create scenario maps of changes in annual and seasonal means. The contiguous 48 U.S. States were grouped into seven regions based on the classification of Bailey (1994), with Alaska forming an eighth region, while Canada was divided into twelve regions based on the Canadian Terrestrial Ecozones (Wiken, 1986). In each region, data were spatially averaged (with area-weighting) and used to create graphs and summary tables of annual and seasonal trends, including long-term changes in interannual variability. Overall, the meta-analysis showed remarkable agreement among the four GCMs, in terms both of their sensitivity to increasing GHG forcing (SRB1→SRA1B→SRA2) and in the relative magnitudes of the climate changes projected for each scenario in each region. Temperatures were projected to increase by 2-4 °C in the southern USA (summer) to as much as 4-8 °C in northern Canada and Alaska (winter minima), by the mid-2080s, relative to 2000. Precipitation was projected to increase by 5-10% over the same period, but with distinct seasonal trends that differed among regions; one GCM projected significant decreases in precipitation in the southern USA. Solar radiation inputs were generally projected to decline slightly, showing consistent inverse relationships to projected precipitation changes, while vapor pressure generally increased, particularly in summer and particularly in coastal regions. Projected changes in interannual variability (based on ratios of predicted to observed standard deviations of annual and seasonal means for 2071-2100 and 1961-1990) were generally less consistent but often tended to decrease with increasing GHG forcing. The data sets will support national and regional climate change impacts studies, including the USDA Forest Service National Renewable Resource Assessment for 2010 and Canadian forest vulnerability assessment for the Canadian Council of Forest Ministers in 2011.

In vitro and in vivo aphrodisiac properties of the seed extract from Allium tuberosum on corpus cavernosum smooth muscle relaxation and sexual behavior parameters in male Wistar rats.

PubMed

Tang, Xingli; Olatunji, Opeyemi J; Zhou, Yifeng; Hou, Xilin

2017-12-01

Allium tuberosum is a well-known spice as well as a herb in traditional Chinese medicine, used for increasing libido and treating erectile dysfunction. However, not many studies have been done to evaluate the sexual enhancing properties of A. tuberosum. The aim of this study was to evaluate the aphrodisiac and vasorelaxant properties of A. tuberosum on corpus cavernosum smooth muscle (CCSM) as well as checking the effect on enhancing male rat sexual behavior, libido, potency as well as its spermatogenic properties. The seeds were powdered and sequentially extracted with hexane, ethyl acetate and butanol. Male Wistar rats were administered with graded doses of the n-BuOH extracts (ATB) of A. tuberosum (50, 100, 200 and 400 mg/kg) and Viagra was used as the positive control drug. The extract/drug was administered by gastric probe once daily for 45 days and the sexual behavior was analyzed by exposing the male rats to female rats in the estrus period. ATB relaxed corpus cavernosum smooth muscle (68.9%) at a concentration of 200 μg/ml. The results obtained from the animal studies indicated that ATB significantly increased mount frequency (MF), intromission frequency (IF), ejaculation frequency (EF), ejaculation latency (EL) and markedly reduced post ejaculatory interval (PEI), mount latency (ML), and intromission latency (IL). Furthermore, a remarkable increase in the test for potency was observed as witnessed by marked increase in erections, quick flips, long flips and total reflex. In addition, ATB significantly improved the sperm viability and count as well as increased the concentrations of testosterone, follicle stimulating hormone (FSH), and phosphatases in the treated animals. Thus our results suggest that A. tuberosum could stimulate sexual arousal and enhance sexual execution in male rats, thus providing valuable experimental evidence that A. tuberosum possesses sexual enhancing properties.

How Novel are 21st Century Climates? A Global Assessment of Future Climates and their Analogs Back Through the Eocene

NASA Astrophysics Data System (ADS)

Burke, K. D.; Williams, J. W.; Jackson, S. T.

2016-12-01

Climate change is a multivariate process, where changes in the environmental space of a location will likely drive biotic responses of the flora and fauna that inhabit the region. In the face of a rapidly changing climate it is important to understand what the future may hold for ecosystems. One method commonly applied to understand how dissimilar future climates will be relative to the modern period is no-analog analysis. This has been done for 21st century climates relative to the modern period, but has not been extended through the paleorecord. Using HadCM3, CCSM3 TraCE-21ka, PMIP3, PlioMIP2 and EoMIP climate simulations, we assess global and regional climatic novelty by identifying the closest analogs in these periods for both future (21st century) and modern climates. This baseline offers a full range climate space with significant overlap of modern and future projected climates, and allows us to assess both emergences and disappearances of analog climate conditions throughout the past. This extended baseline includes past glacial and interglacial climates, as well as past earth warm periods. Past earth warm periods such as the middle to late Pliocene and the early Eocene may be most similar to projections of future climate, so it is important to evaluate our understanding of these global climates. Here we calculate dissimilarity to quantify novelty and no-analog conditions using the Standardized Euclidian Distance, as well as the Mahalanobis distance. Our work shows that nearest climate analogs for the modern period, as well as future climates, existed and disappeared during past warm periods. These results suggest that though climate change may be regionally novel relative to the modern period for some locations, analogs do exist through the paleorecord which in some cases reduce novelty. Nevertheless, novelty remains high in some locations suggesting that some future climates may be unprecedented.

Parameterizing Size Distribution in Ice Clouds

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

DeSlover, Daniel; Mitchell, David L.

2009-09-25

PARAMETERIZING SIZE DISTRIBUTIONS IN ICE CLOUDS David L. Mitchell and Daniel H. DeSlover ABSTRACT An outstanding problem that contributes considerable uncertainty to Global Climate Model (GCM) predictions of future climate is the characterization of ice particle sizes in cirrus clouds. Recent parameterizations of ice cloud effective diameter differ by a factor of three, which, for overcast conditions, often translate to changes in outgoing longwave radiation (OLR) of 55 W m-2 or more. Much of this uncertainty in cirrus particle sizes is related to the problem of ice particle shattering during in situ sampling of the ice particle size distribution (PSD).more » Ice particles often shatter into many smaller ice fragments upon collision with the rim of the probe inlet tube. These small ice artifacts are counted as real ice crystals, resulting in anomalously high concentrations of small ice crystals (D < 100 µm) and underestimates of the mean and effective size of the PSD. Half of the cirrus cloud optical depth calculated from these in situ measurements can be due to this shattering phenomenon. Another challenge is the determination of ice and liquid water amounts in mixed phase clouds. Mixed phase clouds in the Arctic contain mostly liquid water, and the presence of ice is important for determining their lifecycle. Colder high clouds between -20 and -36 oC may also be mixed phase but in this case their condensate is mostly ice with low levels of liquid water. Rather than affecting their lifecycle, the presence of liquid dramatically affects the cloud optical properties, which affects cloud-climate feedback processes in GCMs. This project has made advancements in solving both of these problems. Regarding the first problem, PSD in ice clouds are uncertain due to the inability to reliably measure the concentrations of the smallest crystals (D < 100 µm), known as the “small mode”. Rather than using in situ probe measurements aboard aircraft, we employed a treatment of ice cloud optical properties formulated in terms of PSD parameters in combination with remote measurements of thermal radiances to characterize the small mode. This is possible since the absorption efficiency (Qabs) of small mode crystals is larger at 12 µm wavelength relative to 11 µm wavelength due to the process of wave resonance or photon tunneling more active at 12 µm. This makes the 12/11 µm absorption optical depth ratio (or equivalently the 12/11 µm Qabs ratio) a means for detecting the relative concentration of small ice particles in cirrus. Using this principle, this project tested and developed PSD schemes that can help characterize cirrus clouds at each of the three ARM sites: SGP, NSA and TWP. This was the main effort of this project. These PSD schemes and ice sedimentation velocities predicted from them have been used to test the new cirrus microphysics parameterization in the GCM known as the Community Climate Systems Model (CCSM) as part of an ongoing collaboration with NCAR. Regarding the second problem, we developed and did preliminary testing on a passive thermal method for retrieving the total water path (TWP) of Arctic mixed phase clouds where TWPs are often in the range of 20 to 130 g m-2 (difficult for microwave radiometers to accurately measure). We also developed a new radar method for retrieving the cloud ice water content (IWC), which can be vertically integrated to yield the ice water path (IWP). These techniques were combined to determine the IWP and liquid water path (LWP) in Arctic clouds, and hence the fraction of ice and liquid water. We have tested this approach using a case study from the ARM field campaign called M-PACE (Mixed-Phase Arctic Cloud Experiment). This research led to a new satellite remote sensing method that appears promising for detecting low levels of liquid water in high clouds typically between -20 and -36 oC. We hope to develop this method in future research.« less

Reconstructing the post-LGM decay of the Eurasian Ice Sheets with Ice Sheet Models; data-model comparison and focus on the Storfjorden (Svalbard) ice stream dynamics history

NASA Astrophysics Data System (ADS)

Petrini, Michele; Kirchner, Nina; Colleoni, Florence; Camerlenghi, Angelo; Rebesco, Michele; Lucchi, Renata G.; Forte, Emanuele; Colucci, Renato R.

2017-04-01

The challenge of reconstructing palaeo-ice sheets past growth and decay represent a critical task to better understand mechanisms of present and future global climate change. Last Glacial Maximum (LGM), and the subsequent deglaciation until Pre-Industrial time (PI) represent an excellent testing ground for numerical Ice Sheet Models (ISMs), due to the abundant data available that can be used in an ISM as boundary conditions, forcings or constraints to test the ISMs results. In our study, we simulate with ISMs the post-LGM decay of the Eurasian Ice Sheets, with a focus on the marine-based Svalbard-Barents Sea-Kara Sea Ice Sheet. In particular, we aim to reconstruct the Storfjorden ice stream dynamics history by comparing the model results with the marine geological data (MSGLs, GZWs, sediment cores analysis) available from the area, e.g., Pedrosa et al. 2011, Rebesco et al. 2011, 2013, Lucchi et al. 2013. Two hybrid SIA/SSA ISMs are employed, GRISLI, Ritz et al. 2001, and PSU, Pollard&DeConto 2012. These models differ mainly in the complexity with which grounding line migration is treated. Climate forcing is interpolated by means of climate indexes between LGM and PI climate. Regional climate indexes are constructed based on the non-accelerated deglaciation transient experiment carried out with CCSM3, Liu et al. 2009. Indexes representative of the climate evolution over Siberia, Svalbard and Scandinavia are employed. The impact of such refined representation as opposed to the common use of the NGRIP δ18O index for transient experiments is analysed. In this study, the ice-ocean interaction is crucial to reconstruct the Storfjorden ice stream dynamics history. To investigate the sensitivity of the ice shelf/stream retreat to ocean temperature, we allow for a space-time variation of basal melting under the ice shelves by testing two-equations implementations based on Martin et al. 2011 forced with simulated ocean temperature and salinity from the TraCE-21ka coupled climate simulation. In this presentation, we will show work in progress, address open issues, and sketch future work. In particular, we invite the community to suggest possibilities for model-data comparison and integration. Liu, Z., Otto-Bliesner, B.L., He, F., Brady, E.C., Tomas, R., Clark, P.U., Carlson, A.E., Lynch-Stieglitz, J., Curry, W., Brook, E. and Erickson, D., 2009. Transient simulation of last deglaciation with a new mechanism for Bólling-Alleród warming. Science, 325(5938), pp.310-314. Lucchi, R.G., Camerlenghi, A., Rebesco, M., Colmenero-Hidalgo, E., Sierro, F.J., Sagnotti, L., Urgeles, R., Melis, R., Morigi, C., Bárcena, M.A. and Giorgetti, G., 2013. Postglacial sedimentary processes on the Storfjorden and Kveithola trough mouth fans: Significance of extreme glacimarine sedimentation. Global and planetary change, 111, pp.309-326. Martin, M.A., Winkelmann, R., Haseloff, M., Albrecht, T., Bueler, E., Khroulev, C. and Levermann, A., 2011. The Potsdam Parallel Ice Sheet Model (PISM-PIK)-Part 2: Dynamic equilibrium simulation of the Antarctic ice sheet. The Cryosphere, 5(3), pp.727-740. Pedrosa, M.T., Camerlenghi, A., De Mol, B., Urgeles, R., Rebesco, M. and Lucchi, R.G., 2011. Seabed morphology and shallow sedimentary structure of the Storfjorden and Kveithola trough-mouth fans (north west Barents Sea). Marine Geology, 286(1), pp.65-81. Pollard, D. and DeConto, R.M., 2012. Description of a hybrid ice sheet-shelf model, and application to Antarctica. Geoscientific Model Development, 5(5), pp.1273-1295. Rebesco, M., Liu, Y., Camerlenghi, A., Winsborrow, M., Laberg, J.S., Caburlotto, A., Diviacco, P., Accettella, D., Sauli, C., Wardell, N. and Tomini, I., 2011. Deglaciation of the western margin of the Barents Sea Ice Sheet-a swath bathymetric and sub-bottom seismic study from the Kveithola Trough. Marine Geology, 279(1), pp.141-147. Rebesco, M., Laberg, J., Pedrosa, M., Camerlenghi, A., Lucchi, R., Zgur, F. and Wardell, N., 2013. Onset and growth of Trough-Mouth Fans on the North-Western Barents Sea margin e implications for the evolution of the Barents Sea/Svalbard Ice Sheet. Quaternary Science Reviews, 30, pp.1-8. Ritz, C., Rommelaere, V. and Dumas, C., 2001. Modeling the evolution of Antarctic ice sheet over the last 420,000 years: Implications for altitude changes in the Vostok region. Journal of Geophysical Research: Atmospheres, 106(D23), pp.31943-31964.

Modification of ENSO and ENSO-related atmospheric characteristics due to future climate change

NASA Astrophysics Data System (ADS)

Matveeva, Tatiana; Gushchina, Daria

2017-04-01

The El Niño/Southern Oscillation (ENSO) is the strongest natural climate interannual fluctuation in Tropical Pacific, it affects regional and global climate. There are two types of this phenomenon: East Pacific (EP) El Niño characterized by maximum of SST anomalies centered over the eastern tropical Pacific and Central Pacific (CP) El Niño with SST warming in the center of the Pacific Ocean [Ashok et al., 2007; Kug et al., 2009]. The ability of CMIP5 coupled ocean-atmosphere general circulation models (CGCMs) to simulate two flavors of El Niño correctly was estimated using EOF-analysis technique of SST anomalies [Takahashi et al., 2011] in the recent studies [Matveeva and Gushchina, 2016]. It was shown that only several CGCMs were able to reproduce two types of ENSO. The ENSO-related characteristics can alter due to global climate change. However, scientific community can't be sure whether ENSO activity will be enhanced or damped under global warming. In this study, we choose the 6 "best" CGCMs (BNU-ESM, CCSM4, CNRM-CM5, FIO-ESM, INM-CM4, MIROC5) which simulated spatial and temporal features of the two types of El Niño the most realistic way. To obtain a complete result we analyzed anomalies of complex ENSO-related characteristics (SST, rainfall, vertical movement, atmospheric circulation in the upper and lower troposphere) during two types of El Niño events. We compared the spatial distribution of these anomalies depending future climate scenarios (we took two scenarios with significant differences - RCP 2.6 and RCP 8.5 [Taylor et al., 2012]). It was shown the large difference in model's estimates ENSO-related anomalies' changes for future climate. The main aspect of this study is the analysis of the ENSO characteristics' modification (frequency, amplitude, the ratio between EP and CP El Niño) under different scenarios of warming. We didn't expect any significant change of frequency for two types of El Nino. It was shown that there was no well-defined relation between the amplitude change and the "rigidity" of scenarios. Whereas at the end of XXI century the ratio between EP and CP El Niño may decrease, i.e. the number of CP El Niño in RCP 8.5 will increase. The study was supported by the Russian Foundation for Basic Research (grants No.15-05-06693 and No.16-35-00394 mol_a). References: 1. Ashok, K., Behera, S. K., Rao, S. A.,Weng, H., Yamagata, T., 2007: El Niño Modoki and its possible teleconnection. J. Geophys. Res. 112, C11007. 2. Kug, J.-S., F.-F. Jin, and S.-I. An, 2009: Two types of El Niño events: Cold tongue El Niño and warm pool El Niño. J. Climate, 22, 1499-1515. 3. Matveeva T., Gushchina D., 2016: The Role of Intraseasonal Atmosphere Variability in ENSO Generation in Future Climate. European Geosciences Union General Assembly 2016. Geophysical Research Abstracts, 18, EGU2016-235-2. 4. Takahashi, K., Montecinos, A., Goubanova, K., Dewitte, B., 2011: ENSO regimes: Reinterpreting the canonical and Modoki El Niño. Geophys. Res. Lett. 38, L10704. 5. Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc., 93, 485-498.

Relationship between extreme Precipitation and Temperature over Japan: An analysis from Multi-GCMs and Multi-RCMs products

NASA Astrophysics Data System (ADS)

Nayak, S.; Dairaku, K.; Takayabu, I.

2014-12-01

According to the IPCC reports, the concentration of CO­2 has been increasing and projected to be increased significantly in future (IPCC, 2012). This can have significant impacts on climate. For instance, Dairaku and Emori (2006) examined over south Asia by doubling CO2 and documented an increase in precipitation intensities during Indian summer monsoon. This would increase natural disasters such as floods, landslide, coastal disaster, erosion etc. Recent studies investigated whether the rate of increase of extreme precipitation is related with the rate expected by Clausius-Clapeyron (CC) relationship (approximately 7% per degree temperature rise). In our study, we examine whether this rate can increase or decrease in the future regional climate scenarios over Japan. We have analysed the ensemble experiments by three RCMs(NHRCM, NRAMS, WRF) forced by JRA25 as well as three GCMs (CCSM4, MIROC5, MRI-GCM3) for the current climate (1981-2000) and future scenario (2081-2100, RCP4.5) over Japan. We have stratified the extreme (99th, 95th, 90th, 75th percentile) precipitation of daily sum and daily maximum of hourly precipitation intensities of wet events based on daily mean temperature in bins of 1°C width for annual as well as for each season (DJF, MAM, JJA, SON). The results indicate that precipitation intensity increases when temperature increases roughly up to 22 °C and further increase of temperature decreases the precipitation intensities. The obtained results are consistent and match with the observation (APHRODITE dataset) over Japan. The decrease of precipitation at higher temperature mainly can be found in JJA. It is also noticed that the rate of specific humidity is estimated higher during JJA than other seasons. The rate of increase of extreme precipitation is similar to the rate expected by CC relation except DJF (nearly twice of CC relation) in current climate. This rate becomes to be significantly larger in future scenario for higher temperatures than in current climate.Acknowledgement: This study is conducted as part of a research at NIED, Japan (PI: Koji Dairaku) of Research Program on Climate Change Adaptation (RECCA) and was supported by the SOUSEI Program, funded by Ministry of Education, Culture, Sports, Science and Technology, Government of Japan.

Continuous system modeling

NASA Technical Reports Server (NTRS)

Cellier, Francois E.

1991-01-01

A comprehensive and systematic introduction is presented for the concepts associated with 'modeling', involving the transition from a physical system down to an abstract description of that system in the form of a set of differential and/or difference equations, and basing its treatment of modeling on the mathematics of dynamical systems. Attention is given to the principles of passive electrical circuit modeling, planar mechanical systems modeling, hierarchical modular modeling of continuous systems, and bond-graph modeling. Also discussed are modeling in equilibrium thermodynamics, population dynamics, and system dynamics, inductive reasoning, artificial neural networks, and automated model synthesis.

Feature-based component model for design of embedded systems

NASA Astrophysics Data System (ADS)

Zha, Xuan Fang; Sriram, Ram D.

2004-11-01

An embedded system is a hybrid of hardware and software, which combines software's flexibility and hardware real-time performance. Embedded systems can be considered as assemblies of hardware and software components. An Open Embedded System Model (OESM) is currently being developed at NIST to provide a standard representation and exchange protocol for embedded systems and system-level design, simulation, and testing information. This paper proposes an approach to representing an embedded system feature-based model in OESM, i.e., Open Embedded System Feature Model (OESFM), addressing models of embedded system artifacts, embedded system components, embedded system features, and embedded system configuration/assembly. The approach provides an object-oriented UML (Unified Modeling Language) representation for the embedded system feature model and defines an extension to the NIST Core Product Model. The model provides a feature-based component framework allowing the designer to develop a virtual embedded system prototype through assembling virtual components. The framework not only provides a formal precise model of the embedded system prototype but also offers the possibility of designing variation of prototypes whose members are derived by changing certain virtual components with different features. A case study example is discussed to illustrate the embedded system model.

The Value of SysML Modeling During System Operations: A Case Study

NASA Technical Reports Server (NTRS)

Dutenhoffer, Chelsea; Tirona, Joseph

2013-01-01

System models are often touted as engineering tools that promote better understanding of systems, but these models are typically created during system design. The Ground Data System (GDS) team for the Dawn spacecraft took on a case study to see if benefits could be achieved by starting a model of a system already in operations. This paper focuses on the four steps the team undertook in modeling the Dawn GDS: defining a model structure, populating model elements, verifying that the model represented reality, and using the model to answer system-level questions and simplify day-to-day tasks. Throughout this paper the team outlines our thought processes and the system insights the model provided.

The value of SysML modeling during system operations: A case study

NASA Astrophysics Data System (ADS)

Dutenhoffer, C.; Tirona, J.

System models are often touted as engineering tools that promote better understanding of systems, but these models are typically created during system design. The Ground Data System (GDS) team for the Dawn spacecraft took on a case study to see if benefits could be achieved by starting a model of a system already in operations. This paper focuses on the four steps the team undertook in modeling the Dawn GDS: defining a model structure, populating model elements, verifying that the model represented reality, and using the model to answer system-level questions and simplify day-to-day tasks. Throughout this paper the team outlines our thought processes and the system insights the model provided.

A Model-Driven Visualization Tool for Use with Model-Based Systems Engineering Projects

NASA Technical Reports Server (NTRS)

Trase, Kathryn; Fink, Eric

2014-01-01

Model-Based Systems Engineering (MBSE) promotes increased consistency between a system's design and its design documentation through the use of an object-oriented system model. The creation of this system model facilitates data presentation by providing a mechanism from which information can be extracted by automated manipulation of model content. Existing MBSE tools enable model creation, but are often too complex for the unfamiliar model viewer to easily use. These tools do not yet provide many opportunities for easing into the development and use of a system model when system design documentation already exists. This study creates a Systems Modeling Language (SysML) Document Traceability Framework (SDTF) for integrating design documentation with a system model, and develops an Interactive Visualization Engine for SysML Tools (InVEST), that exports consistent, clear, and concise views of SysML model data. These exported views are each meaningful to a variety of project stakeholders with differing subjects of concern and depth of technical involvement. InVEST allows a model user to generate multiple views and reports from a MBSE model, including wiki pages and interactive visualizations of data. System data can also be filtered to present only the information relevant to the particular stakeholder, resulting in a view that is both consistent with the larger system model and other model views. Viewing the relationships between system artifacts and documentation, and filtering through data to see specialized views improves the value of the system as a whole, as data becomes information

Communication system modeling

NASA Technical Reports Server (NTRS)

Holland, L. D.; Walsh, J. R., Jr.; Wetherington, R. D.

1971-01-01

This report presents the results of work on communications systems modeling and covers three different areas of modeling. The first of these deals with the modeling of signals in communication systems in the frequency domain and the calculation of spectra for various modulations. These techniques are applied in determining the frequency spectra produced by a unified carrier system, the down-link portion of the Command and Communications System (CCS). The second modeling area covers the modeling of portions of a communication system on a block basis. A detailed analysis and modeling effort based on control theory is presented along with its application to modeling of the automatic frequency control system of an FM transmitter. A third topic discussed is a method for approximate modeling of stiff systems using state variable techniques.

Adaptive System Modeling for Spacecraft Simulation

NASA Technical Reports Server (NTRS)

Thomas, Justin

2011-01-01

This invention introduces a methodology and associated software tools for automatically learning spacecraft system models without any assumptions regarding system behavior. Data stream mining techniques were used to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). Evaluation on historical ISS telemetry data shows that adaptive system modeling reduces simulation error anywhere from 50 to 90 percent over existing approaches. The purpose of the methodology is to outline how someone can create accurate system models from sensor (telemetry) data. The purpose of the software is to support the methodology. The software provides analysis tools to design the adaptive models. The software also provides the algorithms to initially build system models and continuously update them from the latest streaming sensor data. The main strengths are as follows: Creates accurate spacecraft system models without in-depth system knowledge or any assumptions about system behavior. Automatically updates/calibrates system models using the latest streaming sensor data. Creates device specific models that capture the exact behavior of devices of the same type. Adapts to evolving systems. Can reduce computational complexity (faster simulations).

Moving alcohol prevention research forward-Part II: new directions grounded in community-based system dynamics modeling.

PubMed

Apostolopoulos, Yorghos; Lemke, Michael K; Barry, Adam E; Lich, Kristen Hassmiller

2018-02-01

Given the complexity of factors contributing to alcohol misuse, appropriate epistemologies and methodologies are needed to understand and intervene meaningfully. We aimed to (1) provide an overview of computational modeling methodologies, with an emphasis on system dynamics modeling; (2) explain how community-based system dynamics modeling can forge new directions in alcohol prevention research; and (3) present a primer on how to build alcohol misuse simulation models using system dynamics modeling, with an emphasis on stakeholder involvement, data sources and model validation. Throughout, we use alcohol misuse among college students in the United States as a heuristic example for demonstrating these methodologies. System dynamics modeling employs a top-down aggregate approach to understanding dynamically complex problems. Its three foundational properties-stocks, flows and feedbacks-capture non-linearity, time-delayed effects and other system characteristics. As a methodological choice, system dynamics modeling is amenable to participatory approaches; in particular, community-based system dynamics modeling has been used to build impactful models for addressing dynamically complex problems. The process of community-based system dynamics modeling consists of numerous stages: (1) creating model boundary charts, behavior-over-time-graphs and preliminary system dynamics models using group model-building techniques; (2) model formulation; (3) model calibration; (4) model testing and validation; and (5) model simulation using learning-laboratory techniques. Community-based system dynamics modeling can provide powerful tools for policy and intervention decisions that can result ultimately in sustainable changes in research and action in alcohol misuse prevention. © 2017 Society for the Study of Addiction.

A novel simulation theory and model system for multi-field coupling pipe-flow system

NASA Astrophysics Data System (ADS)

Chen, Yang; Jiang, Fan; Cai, Guobiao; Xu, Xu

2017-09-01

Due to the lack of a theoretical basis for multi-field coupling in many system-level models, a novel set of system-level basic equations for flow/heat transfer/combustion coupling is put forward. Then a finite volume model of quasi-1D transient flow field for multi-species compressible variable-cross-section pipe flow is established by discretising the basic equations on spatially staggered grids. Combining with the 2D axisymmetric model for pipe-wall temperature field and specific chemical reaction mechanisms, a finite volume model system is established; a set of specific calculation methods suitable for multi-field coupling system-level research is structured for various parameters in this model; specific modularisation simulation models can be further derived in accordance with specific structures of various typical components in a liquid propulsion system. This novel system can also be used to derive two sub-systems: a flow/heat transfer two-field coupling pipe-flow model system without chemical reaction and species diffusion; and a chemical equilibrium thermodynamic calculation-based multi-field coupling system. The applicability and accuracy of two sub-systems have been verified through a series of dynamic modelling and simulations in earlier studies. The validity of this system is verified in an air-hydrogen combustion sample system. The basic equations and the model system provide a unified universal theory and numerical system for modelling and simulation and even virtual testing of various pipeline systems.

Rule-based simulation models

NASA Technical Reports Server (NTRS)

Nieten, Joseph L.; Seraphine, Kathleen M.

1991-01-01

Procedural modeling systems, rule based modeling systems, and a method for converting a procedural model to a rule based model are described. Simulation models are used to represent real time engineering systems. A real time system can be represented by a set of equations or functions connected so that they perform in the same manner as the actual system. Most modeling system languages are based on FORTRAN or some other procedural language. Therefore, they must be enhanced with a reaction capability. Rule based systems are reactive by definition. Once the engineering system has been decomposed into a set of calculations using only basic algebraic unary operations, a knowledge network of calculations and functions can be constructed. The knowledge network required by a rule based system can be generated by a knowledge acquisition tool or a source level compiler. The compiler would take an existing model source file, a syntax template, and a symbol table and generate the knowledge network. Thus, existing procedural models can be translated and executed by a rule based system. Neural models can be provide the high capacity data manipulation required by the most complex real time models.

What can formal methods offer to digital flight control systems design

NASA Technical Reports Server (NTRS)

Good, Donald I.

1990-01-01

Formal methods research begins to produce methods which will enable mathematic modeling of the physical behavior of digital hardware and software systems. The development of these methods directly supports the NASA mission of increasing the scope and effectiveness of flight system modeling capabilities. The conventional, continuous mathematics that is used extensively in modeling flight systems is not adequate for accurate modeling of digital systems. Therefore, the current practice of digital flight control system design has not had the benefits of extensive mathematical modeling which are common in other parts of flight system engineering. Formal methods research shows that by using discrete mathematics, very accurate modeling of digital systems is possible. These discrete modeling methods will bring the traditional benefits of modeling to digital hardware and hardware design. Sound reasoning about accurate mathematical models of flight control systems can be an important part of reducing risk of unsafe flight control.

Component model reduction via the projection and assembly method

NASA Technical Reports Server (NTRS)

Bernard, Douglas E.

1989-01-01

The problem of acquiring a simple but sufficiently accurate model of a dynamic system is made more difficult when the dynamic system of interest is a multibody system comprised of several components. A low order system model may be created by reducing the order of the component models and making use of various available multibody dynamics programs to assemble them into a system model. The difficulty is in choosing the reduced order component models to meet system level requirements. The projection and assembly method, proposed originally by Eke, solves this difficulty by forming the full order system model, performing model reduction at the the system level using system level requirements, and then projecting the desired modes onto the components for component level model reduction. The projection and assembly method is analyzed to show the conditions under which the desired modes are captured exactly; to the numerical precision of the algorithm.

The System of Systems Architecture Feasibility Assessment Model

DTIC Science & Technology

2016-06-01

OF SYSTEMS ARCHITECTURE FEASIBILITY ASSESSMENT MODEL by Stephen E. Gillespie June 2016 Dissertation Supervisor Eugene Paulo THIS PAGE...Dissertation 4. TITLE AND SUBTITLE THE SYSTEM OF SYSTEMS ARCHITECTURE FEASIBILITY ASSESSMENT MODEL 5. FUNDING NUMBERS 6. AUTHOR(S) Stephen E...SoS architecture feasibility assessment model (SoS-AFAM). Together, these extend current model- based systems engineering (MBSE) and SoS engineering

Using the Model Coupling Toolkit to couple earth system models

USGS Publications Warehouse

Warner, J.C.; Perlin, N.; Skyllingstad, E.D.

2008-01-01

Continued advances in computational resources are providing the opportunity to operate more sophisticated numerical models. Additionally, there is an increasing demand for multidisciplinary studies that include interactions between different physical processes. Therefore there is a strong desire to develop coupled modeling systems that utilize existing models and allow efficient data exchange and model control. The basic system would entail model "1" running on "M" processors and model "2" running on "N" processors, with efficient exchange of model fields at predetermined synchronization intervals. Here we demonstrate two coupled systems: the coupling of the ocean circulation model Regional Ocean Modeling System (ROMS) to the surface wave model Simulating WAves Nearshore (SWAN), and the coupling of ROMS to the atmospheric model Coupled Ocean Atmosphere Prediction System (COAMPS). Both coupled systems use the Model Coupling Toolkit (MCT) as a mechanism for operation control and inter-model distributed memory transfer of model variables. In this paper we describe requirements and other options for model coupling, explain the MCT library, ROMS, SWAN and COAMPS models, methods for grid decomposition and sparse matrix interpolation, and provide an example from each coupled system. Methods presented in this paper are clearly applicable for coupling of other types of models. ?? 2008 Elsevier Ltd. All rights reserved.

Virtual Observation System for Earth System Model: An Application to ACME Land Model Simulations

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

Wang, Dali; Yuan, Fengming; Hernandez, Benjamin

Investigating and evaluating physical-chemical-biological processes within an Earth system model (EMS) can be very challenging due to the complexity of both model design and software implementation. A virtual observation system (VOS) is presented to enable interactive observation of these processes during system simulation. Based on advance computing technologies, such as compiler-based software analysis, automatic code instrumentation, and high-performance data transport, the VOS provides run-time observation capability, in-situ data analytics for Earth system model simulation, model behavior adjustment opportunities through simulation steering. A VOS for a terrestrial land model simulation within the Accelerated Climate Modeling for Energy model is also presentedmore » to demonstrate the implementation details and system innovations.« less

Virtual Observation System for Earth System Model: An Application to ACME Land Model Simulations

DOE PAGES

Wang, Dali; Yuan, Fengming; Hernandez, Benjamin; ...

2017-01-01

Investigating and evaluating physical-chemical-biological processes within an Earth system model (EMS) can be very challenging due to the complexity of both model design and software implementation. A virtual observation system (VOS) is presented to enable interactive observation of these processes during system simulation. Based on advance computing technologies, such as compiler-based software analysis, automatic code instrumentation, and high-performance data transport, the VOS provides run-time observation capability, in-situ data analytics for Earth system model simulation, model behavior adjustment opportunities through simulation steering. A VOS for a terrestrial land model simulation within the Accelerated Climate Modeling for Energy model is also presentedmore » to demonstrate the implementation details and system innovations.« less

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.

Model-Based Prognostics of Hybrid Systems

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Roychoudhury, Indranil; Bregon, Anibal

2015-01-01

Model-based prognostics has become a popular approach to solving the prognostics problem. However, almost all work has focused on prognostics of systems with continuous dynamics. In this paper, we extend the model-based prognostics framework to hybrid systems models that combine both continuous and discrete dynamics. In general, most systems are hybrid in nature, including those that combine physical processes with software. We generalize the model-based prognostics formulation to hybrid systems, and describe the challenges involved. We present a general approach for modeling hybrid systems, and overview methods for solving estimation and prediction in hybrid systems. As a case study, we consider the problem of conflict (i.e., loss of separation) prediction in the National Airspace System, in which the aircraft models are hybrid dynamical systems.

World Energy Projection System Plus Model Documentation: Commercial Module

EIA Publications

2016-01-01

The Commercial Model of the World Energy Projection System Plus (WEPS ) is an energy demand modeling system of the world commercial end?use sector at a regional level. This report describes the version of the Commercial Model that was used to produce the commercial sector projections published in the International Energy Outlook 2016 (IEO2016). The Commercial Model is one of 13 components of the WEPS system. The WEPS is a modular system, consisting of a number of separate energy models that are communicate and work with each other through an integrated system model. The model components are each developed independently, but are designed with well?defined protocols for system communication and interactivity. The WEPS modeling system uses a shared database (the “restart” file) that allows all the models to communicate with each other when they are run in sequence over a number of iterations. The overall WEPS system uses an iterative solution technique that forces convergence of consumption and supply pressures to solve for an equilibrium price.

[Model-based biofuels system analysis: a review].

PubMed

Chang, Shiyan; Zhang, Xiliang; Zhao, Lili; Ou, Xunmin

2011-03-01

Model-based system analysis is an important tool for evaluating the potential and impacts of biofuels, and for drafting biofuels technology roadmaps and targets. The broad reach of the biofuels supply chain requires that biofuels system analyses span a range of disciplines, including agriculture/forestry, energy, economics, and the environment. Here we reviewed various models developed for or applied to modeling biofuels, and presented a critical analysis of Agriculture/Forestry System Models, Energy System Models, Integrated Assessment Models, Micro-level Cost, Energy and Emission Calculation Models, and Specific Macro-level Biofuel Models. We focused on the models' strengths, weaknesses, and applicability, facilitating the selection of a suitable type of model for specific issues. Such an analysis was a prerequisite for future biofuels system modeling, and represented a valuable resource for researchers and policy makers.

The Earth System Prediction Suite: Toward a Coordinated U.S. Modeling Capability

DOE PAGES

Theurich, Gerhard; DeLuca, C.; Campbell, T.; ...

2016-08-22

The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open-source terms or to credentialed users. Furthermore, the ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the United States. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC)more » Layer, a set of ESMF-based component templates and interoperability conventions. Our shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multiagency development of coupled modeling systems; controlled experimentation and testing; and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NAVGEM), the Hybrid Coordinate Ocean Model (HYCOM), and the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and the Goddard Earth Observing System Model, version 5 (GEOS-5), atmospheric general circulation model.« less

The Earth System Prediction Suite: Toward a Coordinated U.S. Modeling Capability

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

Theurich, Gerhard; DeLuca, C.; Campbell, T.

The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open-source terms or to credentialed users. Furthermore, the ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the United States. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC)more » Layer, a set of ESMF-based component templates and interoperability conventions. Our shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multiagency development of coupled modeling systems; controlled experimentation and testing; and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NAVGEM), the Hybrid Coordinate Ocean Model (HYCOM), and the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and the Goddard Earth Observing System Model, version 5 (GEOS-5), atmospheric general circulation model.« less

Computer-aided operations engineering with integrated models of systems and operations

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Ryan, Dan; Fleming, Land

1994-01-01

CONFIG 3 is a prototype software tool that supports integrated conceptual design evaluation from early in the product life cycle, by supporting isolated or integrated modeling, simulation, and analysis of the function, structure, behavior, failures and operation of system designs. Integration and reuse of models is supported in an object-oriented environment providing capabilities for graph analysis and discrete event simulation. Integration is supported among diverse modeling approaches (component view, configuration or flow path view, and procedure view) and diverse simulation and analysis approaches. Support is provided for integrated engineering in diverse design domains, including mechanical and electro-mechanical systems, distributed computer systems, and chemical processing and transport systems. CONFIG supports abstracted qualitative and symbolic modeling, for early conceptual design. System models are component structure models with operating modes, with embedded time-related behavior models. CONFIG supports failure modeling and modeling of state or configuration changes that result in dynamic changes in dependencies among components. Operations and procedure models are activity structure models that interact with system models. CONFIG is designed to support evaluation of system operability, diagnosability and fault tolerance, and analysis of the development of system effects of problems over time, including faults, failures, and procedural or environmental difficulties.

Research on complex 3D tree modeling based on L-system

NASA Astrophysics Data System (ADS)

Gang, Chen; Bin, Chen; Yuming, Liu; Hui, Li

2018-03-01

L-system as a fractal iterative system could simulate complex geometric patterns. Based on the field observation data of trees and knowledge of forestry experts, this paper extracted modeling constraint rules and obtained an L-system rules set. Using the self-developed L-system modeling software the L-system rule set was parsed to generate complex tree 3d models.The results showed that the geometrical modeling method based on l-system could be used to describe the morphological structure of complex trees and generate 3D tree models.

Cyber Physical System Modelling of Distribution Power Systems for Dynamic Demand Response

NASA Astrophysics Data System (ADS)

Chu, Xiaodong; Zhang, Rongxiang; Tang, Maosen; Huang, Haoyi; Zhang, Lei

2018-01-01

Dynamic demand response (DDR) is a package of control methods to enhance power system security. A CPS modelling and simulation platform for DDR in distribution power systems is presented in this paper. CPS modelling requirements of distribution power systems are analyzed. A coupled CPS modelling platform is built for assessing DDR in the distribution power system, which combines seamlessly modelling tools of physical power networks and cyber communication networks. Simulations results of IEEE 13-node test system demonstrate the effectiveness of the modelling and simulation platform.

An Integrated High Resolution Hydrometeorological Modeling Testbed using LIS and WRF

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Peters-Lidard, Christa D.; Eastman, Joseph L.; Tao, Wei-Kuo

2007-01-01

Scientists have made great strides in modeling physical processes that represent various weather and climate phenomena. Many modeling systems that represent the major earth system components (the atmosphere, land surface, and ocean) have been developed over the years. However, developing advanced Earth system applications that integrates these independently developed modeling systems have remained a daunting task due to limitations in computer hardware and software. Recently, efforts such as the Earth System Modeling Ramework (ESMF) and Assistance for Land Modeling Activities (ALMA) have focused on developing standards, guidelines, and computational support for coupling earth system model components. In this article, the development of a coupled land-atmosphere hydrometeorological modeling system that adopts these community interoperability standards, is described. The land component is represented by the Land Information System (LIS), developed by scientists at the NASA Goddard Space Flight Center. The Weather Research and Forecasting (WRF) model, a mesoscale numerical weather prediction system, is used as the atmospheric component. LIS includes several community land surface models that can be executed at spatial scales as fine as 1km. The data management capabilities in LIS enable the direct use of high resolution satellite and observation data for modeling. Similarly, WRF includes several parameterizations and schemes for modeling radiation, microphysics, PBL and other processes. Thus the integrated LIS-WRF system facilitates several multi-model studies of land-atmosphere coupling that can be used to advance earth system studies.

About Regional Energy Deployment System Model-ReEDS | Regional Energy

Science.gov Websites

Deployment System Model | Energy Analysis | NREL About Regional Energy Deployment System Model -ReEDS About Regional Energy Deployment System Model-ReEDS The Regional Energy Deployment System (ReEDS ) is a long-term, capacity-expansion model for the deployment of electric power generation technologies

Propulsion System Dynamic Modeling for the NASA Supersonic Concept Vehicle: AeroPropulsoServoElasticity

NASA Technical Reports Server (NTRS)

Kopasakis, George; Connolly, Joseph; Seidel, Jonathan

2014-01-01

A summary of the propulsion system modeling under NASA's High Speed Project (HSP) AeroPropulsoServoElasticity (APSE) task is provided with a focus on the propulsion system for the low-boom supersonic configuration developed by Lockheed Martin and referred to as the N+2 configuration. This summary includes details on the effort to date to develop computational models for the various propulsion system components. The objective of this paper is to summarize the model development effort in this task, while providing more detail in the modeling areas that have not been previously published. The purpose of the propulsion system modeling and the overall APSE effort is to develop an integrated dynamic vehicle model to conduct appropriate unsteady analysis of supersonic vehicle performance. This integrated APSE system model concept includes the propulsion system model, and the vehicle structural-aerodynamics model. The development to date of such a preliminary integrated model will also be summarized in this report.propulsion system dynamics, the structural dynamics, and aerodynamics.

Analysis about modeling MEC7000 excitation system of nuclear power unit

NASA Astrophysics Data System (ADS)

Liu, Guangshi; Sun, Zhiyuan; Dou, Qian; Liu, Mosi; Zhang, Yihui; Wang, Xiaoming

2018-02-01

Aiming at the importance of accurate modeling excitation system in stability calculation of nuclear power plant inland and lack of research in modeling MEC7000 excitation system,this paper summarize a general method to modeling and simulate MEC7000 excitation system. Among this method also solve the key issues of computing method of IO interface parameter and the conversion process of excitation system measured model to BPA simulation model. At last complete the simulation modeling of MEC7000 excitation system first time in domestic. By used No-load small disturbance check, demonstrates that the proposed model and algorithm is corrective and efficient.

System Dynamics Approach for Critical Infrastructure and Decision Support. A Model for a Potable Water System.

NASA Astrophysics Data System (ADS)

Pasqualini, D.; Witkowski, M.

2005-12-01

The Critical Infrastructure Protection / Decision Support System (CIP/DSS) project, supported by the Science and Technology Office, has been developing a risk-informed Decision Support System that provides insights for making critical infrastructure protection decisions. The system considers seventeen different Department of Homeland Security defined Critical Infrastructures (potable water system, telecommunications, public health, economics, etc.) and their primary interdependencies. These infrastructures have been modeling in one model called CIP/DSS Metropolitan Model. The modeling approach used is a system dynamics modeling approach. System dynamics modeling combines control theory and the nonlinear dynamics theory, which is defined by a set of coupled differential equations, which seeks to explain how the structure of a given system determines its behavior. In this poster we present a system dynamics model for one of the seventeen critical infrastructures, a generic metropolitan potable water system (MPWS). Three are the goals: 1) to gain a better understanding of the MPWS infrastructure; 2) to identify improvements that would help protect MPWS; and 3) to understand the consequences, interdependencies, and impacts, when perturbations occur to the system. The model represents raw water sources, the metropolitan water treatment process, storage of treated water, damage and repair to the MPWS, distribution of water, and end user demand, but does not explicitly represent the detailed network topology of an actual MPWS. The MPWS model is dependent upon inputs from the metropolitan population, energy, telecommunication, public health, and transportation models as well as the national water and transportation models. We present modeling results and sensitivity analysis indicating critical choke points, negative and positive feedback loops in the system. A general scenario is also analyzed where the potable water system responds to a generic disruption.

THE EARTH SYSTEM PREDICTION SUITE: Toward a Coordinated U.S. Modeling Capability

PubMed Central

Theurich, Gerhard; DeLuca, C.; Campbell, T.; Liu, F.; Saint, K.; Vertenstein, M.; Chen, J.; Oehmke, R.; Doyle, J.; Whitcomb, T.; Wallcraft, A.; Iredell, M.; Black, T.; da Silva, AM; Clune, T.; Ferraro, R.; Li, P.; Kelley, M.; Aleinov, I.; Balaji, V.; Zadeh, N.; Jacob, R.; Kirtman, B.; Giraldo, F.; McCarren, D.; Sandgathe, S.; Peckham, S.; Dunlap, R.

2017-01-01

The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open source terms or to credentialed users. The ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the U.S. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC) Layer, a set of ESMF-based component templates and interoperability conventions. This shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multi-agency development of coupled modeling systems, controlled experimentation and testing, and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NavGEM), HYbrid Coordinate Ocean Model (HYCOM), and Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS®); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and GEOS-5 atmospheric general circulation model. PMID:29568125

THE EARTH SYSTEM PREDICTION SUITE: Toward a Coordinated U.S. Modeling Capability.

PubMed

Theurich, Gerhard; DeLuca, C; Campbell, T; Liu, F; Saint, K; Vertenstein, M; Chen, J; Oehmke, R; Doyle, J; Whitcomb, T; Wallcraft, A; Iredell, M; Black, T; da Silva, A M; Clune, T; Ferraro, R; Li, P; Kelley, M; Aleinov, I; Balaji, V; Zadeh, N; Jacob, R; Kirtman, B; Giraldo, F; McCarren, D; Sandgathe, S; Peckham, S; Dunlap, R

2016-07-01

The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open source terms or to credentialed users. The ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the U.S. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC) Layer, a set of ESMF-based component templates and interoperability conventions. This shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multi-agency development of coupled modeling systems, controlled experimentation and testing, and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NavGEM), HYbrid Coordinate Ocean Model (HYCOM), and Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS ® ); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and GEOS-5 atmospheric general circulation model.

The Earth System Prediction Suite: Toward a Coordinated U.S. Modeling Capability

NASA Technical Reports Server (NTRS)

Theurich, Gerhard; DeLuca, C.; Campbell, T.; Liu, F.; Saint, K.; Vertenstein, M.; Chen, J.; Oehmke, R.; Doyle, J.; Whitcomb, T.;

Watershed System Model: The Essentials to Model Complex Human-Nature System at the River Basin Scale

NASA Astrophysics Data System (ADS)

Li, Xin; Cheng, Guodong; Lin, Hui; Cai, Ximing; Fang, Miao; Ge, Yingchun; Hu, Xiaoli; Chen, Min; Li, Weiyue

2018-03-01

Watershed system models are urgently needed to understand complex watershed systems and to support integrated river basin management. Early watershed modeling efforts focused on the representation of hydrologic processes, while the next-generation watershed models should represent the coevolution of the water-land-air-plant-human nexus in a watershed and provide capability of decision-making support. We propose a new modeling framework and discuss the know-how approach to incorporate emerging knowledge into integrated models through data exchange interfaces. We argue that the modeling environment is a useful tool to enable effective model integration, as well as create domain-specific models of river basin systems. The grand challenges in developing next-generation watershed system models include but are not limited to providing an overarching framework for linking natural and social sciences, building a scientifically based decision support system, quantifying and controlling uncertainties, and taking advantage of new technologies and new findings in the various disciplines of watershed science. The eventual goal is to build transdisciplinary, scientifically sound, and scale-explicit watershed system models that are to be codesigned by multidisciplinary communities.

System Operations Studies : Feeder System Model. User's Manual.

DOT National Transportation Integrated Search

1982-11-01

The Feeder System Model (FSM) is one of the analytic models included in the System Operations Studies (SOS) software package developed for urban transit systems analysis. The objective of the model is to assign a proportion of the zone-to-zone travel...

A model for plant lighting system selection.

PubMed

Ciolkosz, D E; Albright, L D; Sager, J C; Langhans, R W

2002-01-01

A decision model is presented that compares lighting systems for a plant growth scenario and chooses the most appropriate system from a given set of possible choices. The model utilizes a Multiple Attribute Utility Theory approach, and incorporates expert input and performance simulations to calculate a utility value for each lighting system being considered. The system with the highest utility is deemed the most appropriate system. The model was applied to a greenhouse scenario, and analyses were conducted to test the model's output for validity. Parameter variation indicates that the model performed as expected. Analysis of model output indicates that differences in utility among the candidate lighting systems were sufficiently large to give confidence that the model's order of selection was valid.

Rethinking the Systems Engineering Process in Light of Design Thinking

DTIC Science & Technology

2016-04-30

systems engineering process models (Blanchard & Fabrycky, 1990) and the majority of engineering design education (Dym et al., 2005). The waterfall model ...Engineering Career Competency Model Clifford Whitcomb, Systems Engineering Professor, NPS Corina White, Systems Engineering Research Associate, NPS...Postgraduate School (NPS) in Monterey, CA. He teaches and conducts research in the design of enterprise systems, systems modeling , and system

Modeling in the Classroom: An Evolving Learning Tool

NASA Astrophysics Data System (ADS)

Few, A. A.; Marlino, M. R.; Low, R.

2006-12-01

Among the early programs (early 1990s) focused on teaching Earth System Science were the Global Change Instruction Program (GCIP) funded by NSF through UCAR and the Earth System Science Education Program (ESSE) funded by NASA through USRA. These two programs introduced modeling as a learning tool from the beginning, and they provided workshops, demonstrations and lectures for their participating universities. These programs were aimed at university-level education. Recently, classroom modeling is experiencing a revival of interest. Drs John Snow and Arthur Few conducted two workshops on modeling at the ESSE21 meeting in Fairbanks, Alaska, in August 2005. The Digital Library for Earth System Education (DLESE) at http://www.dlese.org provides web access to STELLA models and tutorials, and UCAR's Education and Outreach (EO) program holds workshops that include training in modeling. An important innovation to the STELLA modeling software by isee systems, http://www.iseesystems.com, called "isee Player" is available as a free download. The Player allows users to view and run STELLA models, change model parameters, share models with colleagues and students, and make working models available on the web. This is important because the expert can create models, and the user can learn how the modeled system works. Another aspect of this innovation is that the educational benefits of modeling concepts can be extended throughout most of the curriculum. The procedure for building a working computer model of an Earth Science System follows this general format: (1) carefully define the question(s) for which you seek the answer(s); (2) identify the interacting system components and inputs contributing to the system's behavior; (3) collect the information and data that will be required to complete the conceptual model; (4) construct a system diagram (graphic) of the system that displays all of system's central questions, components, relationships and required inputs. At this stage in the process the conceptual model of the system is compete and a clear understanding of how the system works is achieved. When appropriate software is available the advanced classes can proceed to (5) creating a computer model of the system and testing the conceptual model. For classes lacking these advanced capabilities they may view and run models using the free isee Player and shared working models. In any event there is understanding to be gained in every step of the procedure outlined above. You can view some examples at http://www.ruf.rice.edu/~few/. We plan to populate this site with samples of Earth science systems for use in Earth system science education.

ASTP ranging system mathematical model

NASA Technical Reports Server (NTRS)

Ellis, M. R.; Robinson, L. H.

1973-01-01

A mathematical model is presented of the VHF ranging system to analyze the performance of the Apollo-Soyuz test project (ASTP). The system was adapted for use in the ASTP. The ranging system mathematical model is presented in block diagram form, and a brief description of the overall model is also included. A procedure for implementing the math model is presented along with a discussion of the validation of the math model and the overall summary and conclusions of the study effort. Detailed appendices of the five study tasks are presented: early late gate model development, unlock probability development, system error model development, probability of acquisition and model development, and math model validation testing.

Strategic preparedness for recovery from catastrophic risks to communities and infrastructure systems of systems.

PubMed

Haimes, Yacov Y

2012-11-01

Natural and human-induced disasters affect organizations in myriad ways because of the inherent interconnectedness and interdependencies among human, cyber, and physical infrastructures, but more importantly, because organizations depend on the effectiveness of people and on the leadership they provide to the organizations they serve and represent. These human-organizational-cyber-physical infrastructure entities are termed systems of systems. Given the multiple perspectives that characterize them, they cannot be modeled effectively with a single model. The focus of this article is: (i) the centrality of the states of a system in modeling; (ii) the efficacious role of shared states in modeling systems of systems, in identification, and in the meta-modeling of systems of systems; and (iii) the contributions of the above to strategic preparedness, response to, and recovery from catastrophic risk to such systems. Strategic preparedness connotes a decision-making process and its associated actions. These must be: implemented in advance of a natural or human-induced disaster, aimed at reducing consequences (e.g., recovery time, community suffering, and cost), and/or controlling their likelihood to a level considered acceptable (through the decisionmakers' implicit and explicit acceptance of various risks and tradeoffs). The inoperability input-output model (IIM), which is grounded on Leontief's input/output model, has enabled the modeling of interdependent subsystems. Two separate modeling structures are introduced. These are: phantom system models (PSM), where shared states constitute the essence of modeling coupled systems; and the IIM, where interdependencies among sectors of the economy are manifested by the Leontief matrix of technological coefficients. This article demonstrates the potential contributions of these two models to each other, and thus to more informative modeling of systems of systems schema. The contributions of shared states to this modeling and to systems identification are presented with case studies. © 2012 Society for Risk Analysis.

Modeling and control design of a wind tunnel model support

NASA Technical Reports Server (NTRS)

Howe, David A.

1990-01-01

The 12-Foot Pressure Wind Tunnel at Ames Research Center is being restored. A major part of the restoration is the complete redesign of the aircraft model supports and their associated control systems. An accurate trajectory control servo system capable of positioning a model (with no measurable overshoot) is needed. Extremely small errors in scaled-model pitch angle can increase airline fuel costs for the final aircraft configuration by millions of dollars. In order to make a mechanism sufficiently accurate in pitch, a detailed structural and control-system model must be created and then simulated on a digital computer. The model must contain linear representations of the mechanical system, including masses, springs, and damping in order to determine system modes. Electrical components, both analog and digital, linear and nonlinear must also be simulated. The model of the entire closed-loop system must then be tuned to control the modes of the flexible model-support structure. The development of a system model, the control modal analysis, and the control-system design are discussed.

Research on simulation of supercritical steam turbine system in large thermal power station

NASA Astrophysics Data System (ADS)

Zhou, Qiongyang

2018-04-01

In order to improve the stability and safety of supercritical steam turbine system operation in large thermal power station, the body of the steam turbine is modeled in this paper. And in accordance with the hierarchical modeling idea, the steam turbine body model, condensing system model, deaeration system model and regenerative system model are combined to build a simulation model of steam turbine system according to the connection relationship of each subsystem of steam turbine. Finally, the correctness of the model is verified by design and operation data of the 600MW supercritical unit. The results show that the maximum simulation error of the model is 2.15%, which meets the requirements of the engineering. This research provides a platform for the research on the variable operating conditions of the turbine system, and lays a foundation for the construction of the whole plant model of the thermal power plant.

Electromagnetic interference modeling and suppression techniques in variable-frequency drive systems

NASA Astrophysics Data System (ADS)

Yang, Le; Wang, Shuo; Feng, Jianghua

2017-11-01

Electromagnetic interference (EMI) causes electromechanical damage to the motors and degrades the reliability of variable-frequency drive (VFD) systems. Unlike fundamental frequency components in motor drive systems, high-frequency EMI noise, coupled with the parasitic parameters of the trough system, are difficult to analyze and reduce. In this article, EMI modeling techniques for different function units in a VFD system, including induction motors, motor bearings, and rectifierinverters, are reviewed and evaluated in terms of applied frequency range, model parameterization, and model accuracy. The EMI models for the motors are categorized based on modeling techniques and model topologies. Motor bearing and shaft models are also reviewed, and techniques that are used to eliminate bearing current are evaluated. Modeling techniques for conventional rectifierinverter systems are also summarized. EMI noise suppression techniques, including passive filter, Wheatstone bridge balance, active filter, and optimized modulation, are reviewed and compared based on the VFD system models.

Some Approaches to Modeling Complex Information Systems.

ERIC Educational Resources Information Center

Rao, V. Venkata; Zunde, Pranas

1982-01-01

Brief discussion of state-of-the-art of modeling complex information systems distinguishes between macrolevel and microlevel modeling of such systems. Network layout and hierarchical system models, simulation, information acquisition and dissemination, databases and information storage, and operating systems are described and assessed. Thirty-four…

Systems Operation Studies for Automated Guideway Transit Systems : System Availability Model User's Manual

DOT National Transportation Integrated Search

1981-01-01

The System Availability Model (SAM) is a system-level model which provides measures of vehicle and passenger availability. The SAM operates in conjunction with the AGT discrete Event Simulation Model (DESM). The DESM output is the normal source of th...

A Model-Based Expert System for Space Power Distribution Diagnostics

NASA Technical Reports Server (NTRS)

Quinn, Todd M.; Schlegelmilch, Richard F.

1994-01-01

When engineers diagnose system failures, they often use models to confirm system operation. This concept has produced a class of advanced expert systems that perform model-based diagnosis. A model-based diagnostic expert system for the Space Station Freedom electrical power distribution test bed is currently being developed at the NASA Lewis Research Center. The objective of this expert system is to autonomously detect and isolate electrical fault conditions. Marple, a software package developed at TRW, provides a model-based environment utilizing constraint suspension. Originally, constraint suspension techniques were developed for digital systems. However, Marple provides the mechanisms for applying this approach to analog systems such as the test bed, as well. The expert system was developed using Marple and Lucid Common Lisp running on a Sun Sparc-2 workstation. The Marple modeling environment has proved to be a useful tool for investigating the various aspects of model-based diagnostics. This report describes work completed to date and lessons learned while employing model-based diagnostics using constraint suspension within an analog system.

Particle Tracking Model (PTM) with Coastal Modeling System (CMS)

DTIC Science & Technology

2015-11-04

Coastal Inlets Research Program Particle Tracking Model (PTM) with Coastal Modeling System ( CMS ) The Particle Tracking Model (PTM) is a Lagrangian...currents and waves. The Coastal Inlets Research Program (CIRP) supports the PTM with the Coastal Modeling System ( CMS ), which provides coupled wave...and current forcing for PTM simulations. CMS -PTM is implemented in the Surface-water Modeling System, a GUI environment for input development

Object-Oriented Modeling of an Energy Harvesting System Based on Thermoelectric Generators

NASA Astrophysics Data System (ADS)

Nesarajah, Marco; Frey, Georg

This paper deals with the modeling of an energy harvesting system based on thermoelectric generators (TEG), and the validation of the model by means of a test bench. TEGs are capable to improve the overall energy efficiency of energy systems, e.g. combustion engines or heating systems, by using the remaining waste heat to generate electrical power. Previously, a component-oriented model of the TEG itself was developed in Modelica® language. With this model any TEG can be described and simulated given the material properties and the physical dimension. Now, this model was extended by the surrounding components to a complete model of a thermoelectric energy harvesting system. In addition to the TEG, the model contains the cooling system, the heat source, and the power electronics. To validate the simulation model, a test bench was built and installed on an oil-fired household heating system. The paper reports results of the measurements and discusses the validity of the developed simulation models. Furthermore, the efficiency of the proposed energy harvesting system is derived and possible improvements based on design variations tested in the simulation model are proposed.

An Integrated Modeling and Simulation Methodology for Intelligent Systems Design and Testing

DTIC Science & Technology

2002-08-01

simulation and actual execution. KEYWORDS: Model Continuity, Modeling, Simulation, Experimental Frame, Real Time Systems , Intelligent Systems...the methodology for a stand-alone real time system. Then it will scale up to distributed real time systems . For both systems, step-wise simulation...MODEL CONTINUITY Intelligent real time systems monitor, respond to, or control, an external environment. This environment is connected to the digital

System Dynamics Modeling of Transboundary Systems: The Bear River Basin Model

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

Gerald Sehlke; Jake Jacobson

2005-09-01

System dynamics is a computer-aided approach to evaluating the interrelationships of different components and activities within complex systems. Recently, system dynamics models have been developed in areas such as policy design, biological and medical modeling, energy and the environmental analysis, and in various other areas in the natural and social sciences. The Idaho National Engineering and Environmental Laboratory, a multi-purpose national laboratory managed by the Department of Energy, has developed a systems dynamics model in order to evaluate its utility for modeling large complex hydrological systems. We modeled the Bear River Basin, a transboundary basin that includes portions of Idaho,more » Utah and Wyoming. We found that system dynamics modeling is very useful for integrating surface water and groundwater data and for simulating the interactions between these sources within a given basin. In addition, we also found system dynamics modeling is useful for integrating complex hydrologic data with other information (e.g., policy, regulatory and management criteria) to produce a decision support system. Such decision support systems can allow managers and stakeholders to better visualize the key hydrologic elements and management constraints in the basin, which enables them to better understand the system via the simulation of multiple “what-if” scenarios. Although system dynamics models can be developed to conduct traditional hydraulic/hydrologic surface water or groundwater modeling, we believe that their strength lies in their ability to quickly evaluate trends and cause–effect relationships in large-scale hydrological systems; for integrating disparate data; for incorporating output from traditional hydraulic/hydrologic models; and for integration of interdisciplinary data, information and criteria to support better management decisions.« less

System Dynamics Modeling of Transboundary Systems: the Bear River Basin Model

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

Gerald Sehlke; Jacob J. Jacobson

2005-09-01

System dynamics is a computer-aided approach to evaluating the interrelationships of different components and activities within complex systems. Recently, system dynamics models have been developed in areas such as policy design, biological and medical modeling, energy and the environmental analysis, and in various other areas in the natural and social sciences. The Idaho National Engineering and Environmental Laboratory, a multi-purpose national laboratory managed by the Department of Energy, has developed a systems dynamics model in order to evaluate its utility for modeling large complex hydrological systems. We modeled the Bear River Basin, a transboundary basin that includes portions of Idaho,more » Utah and Wyoming. We found that system dynamics modeling is very useful for integrating surface water and ground water data and for simulating the interactions between these sources within a given basin. In addition, we also found system dynamics modeling is useful for integrating complex hydrologic data with other information (e.g., policy, regulatory and management criteria) to produce a decision support system. Such decision support systems can allow managers and stakeholders to better visualize the key hydrologic elements and management constraints in the basin, which enables them to better understand the system via the simulation of multiple “what-if” scenarios. Although system dynamics models can be developed to conduct traditional hydraulic/hydrologic surface water or ground water modeling, we believe that their strength lies in their ability to quickly evaluate trends and cause–effect relationships in large-scale hydrological systems; for integrating disparate data; for incorporating output from traditional hydraulic/hydrologic models; and for integration of interdisciplinary data, information and criteria to support better management decisions.« less

Model tracking system for low-level radioactive waste disposal facilities: License application interrogatories and responses

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

Benbennick, M.E.; Broton, M.S.; Fuoto, J.S.

This report describes a model tracking system for a low-level radioactive waste (LLW) disposal facility license application. In particular, the model tracks interrogatories (questions, requests for information, comments) and responses. A set of requirements and desired features for the model tracking system was developed, including required structure and computer screens. Nine tracking systems were then reviewed against the model system requirements and only two were found to meet all requirements. Using Kepner-Tregoe decision analysis, a model tracking system was selected.

Model-based Systems Engineering: Creation and Implementation of Model Validation Rules for MOS 2.0

NASA Technical Reports Server (NTRS)

Schmidt, Conrad K.

2013-01-01

Model-based Systems Engineering (MBSE) is an emerging modeling application that is used to enhance the system development process. MBSE allows for the centralization of project and system information that would otherwise be stored in extraneous locations, yielding better communication, expedited document generation and increased knowledge capture. Based on MBSE concepts and the employment of the Systems Modeling Language (SysML), extremely large and complex systems can be modeled from conceptual design through all system lifecycles. The Operations Revitalization Initiative (OpsRev) seeks to leverage MBSE to modernize the aging Advanced Multi-Mission Operations Systems (AMMOS) into the Mission Operations System 2.0 (MOS 2.0). The MOS 2.0 will be delivered in a series of conceptual and design models and documents built using the modeling tool MagicDraw. To ensure model completeness and cohesiveness, it is imperative that the MOS 2.0 models adhere to the specifications, patterns and profiles of the Mission Service Architecture Framework, thus leading to the use of validation rules. This paper outlines the process by which validation rules are identified, designed, implemented and tested. Ultimately, these rules provide the ability to maintain model correctness and synchronization in a simple, quick and effective manner, thus allowing the continuation of project and system progress.

System analysis through bond graph modeling

NASA Astrophysics Data System (ADS)

McBride, Robert Thomas

2005-07-01

Modeling and simulation form an integral role in the engineering design process. An accurate mathematical description of a system provides the design engineer the flexibility to perform trade studies quickly and accurately to expedite the design process. Most often, the mathematical model of the system contains components of different engineering disciplines. A modeling methodology that can handle these types of systems might be used in an indirect fashion to extract added information from the model. This research examines the ability of a modeling methodology to provide added insight into system analysis and design. The modeling methodology used is bond graph modeling. An investigation into the creation of a bond graph model using the Lagrangian of the system is provided. Upon creation of the bond graph, system analysis is performed. To aid in the system analysis, an object-oriented approach to bond graph modeling is introduced. A framework is provided to simulate the bond graph directly. Through object-oriented simulation of a bond graph, the information contained within the bond graph can be exploited to create a measurement of system efficiency. A definition of system efficiency is given. This measurement of efficiency is used in the design of different controllers of varying architectures. Optimal control of a missile autopilot is discussed within the framework of the calculated system efficiency.

Analysis hierarchical model for discrete event systems

NASA Astrophysics Data System (ADS)

Ciortea, E. M.

2015-11-01

The This paper presents the hierarchical model based on discrete event network for robotic systems. Based on the hierarchical approach, Petri network is analysed as a network of the highest conceptual level and the lowest level of local control. For modelling and control of complex robotic systems using extended Petri nets. Such a system is structured, controlled and analysed in this paper by using Visual Object Net ++ package that is relatively simple and easy to use, and the results are shown as representations easy to interpret. The hierarchical structure of the robotic system is implemented on computers analysed using specialized programs. Implementation of hierarchical model discrete event systems, as a real-time operating system on a computer network connected via a serial bus is possible, where each computer is dedicated to local and Petri model of a subsystem global robotic system. Since Petri models are simplified to apply general computers, analysis, modelling, complex manufacturing systems control can be achieved using Petri nets. Discrete event systems is a pragmatic tool for modelling industrial systems. For system modelling using Petri nets because we have our system where discrete event. To highlight the auxiliary time Petri model using transport stream divided into hierarchical levels and sections are analysed successively. Proposed robotic system simulation using timed Petri, offers the opportunity to view the robotic time. Application of goods or robotic and transmission times obtained by measuring spot is obtained graphics showing the average time for transport activity, using the parameters sets of finished products. individually.

SYSTEMS BIOLOGY MODEL DEVELOPMENT AND APPLICATION

EPA Science Inventory

System biology models holistically describe, in a quantitative fashion, the relationships between different levels of a biologic system. Relationships between individual components of a system are delineated. System biology models describe how the components of the system inter...

Propulsion System Dynamic Modeling of the NASA Supersonic Concept Vehicle for AeroPropulsoServoElasticity

NASA Technical Reports Server (NTRS)

Kopasakis, George; Connolly, Joseph W.; Seiel, Jonathan

2016-01-01

A summary of the propulsion system modeling under NASA's High Speed Project (HSP) AeroPropulsoServoElasticity (APSE) task is provided with a focus on the propulsion system for the low-boom supersonic configuration developed by Lockheed Martin and referred to as the N+2 configuration. This summary includes details on the effort to date to develop computational models for the various propulsion system components. The objective of this paper is to summarize the model development effort in this task, while providing more detail in the modeling areas that have not been previously published. The purpose of the propulsion system modeling and the overall APSE effort is to develop an integrated dynamic vehicle model to conduct appropriate unsteady analysis of supersonic vehicle performance. This integrated APSE system model concept includes the propulsion system model, and the vehicle structural aerodynamics model. The development to date of such a preliminary integrated model will also be summarized in this report

Propulsion System Dynamic Modeling of the NASA Supersonic Concept Vehicle for AeroPropulsoServoElasticity

NASA Technical Reports Server (NTRS)

Kopasakis, George; Connolly, Joseph W.; Seidel, Jonathan

2014-01-01

A summary of the propulsion system modeling under NASA's High Speed Project (HSP) AeroPropulsoServoElasticity (APSE) task is provided with a focus on the propulsion system for the lowboom supersonic configuration developed by Lockheed Martin and referred to as the N+2 configuration. This summary includes details on the effort to date to develop computational models for the various propulsion system components. The objective of this paper is to summarize the model development effort in this task, while providing more detail in the modeling areas that have not been previously published. The purpose of the propulsion system modeling and the overall APSE effort is to develop an integrated dynamic vehicle model to conduct appropriate unsteady analysis of supersonic vehicle performance. This integrated APSE system model concept includes the propulsion system model, and the vehicle structural-aerodynamics model. The development to date of such a preliminary integrated model will also be summarized in this report.

Electric Propulsion System Modeling for the Proposed Prometheus 1 Mission

NASA Technical Reports Server (NTRS)

Fiehler, Douglas; Dougherty, Ryan; Manzella, David

2005-01-01

The proposed Prometheus 1 spacecraft would utilize nuclear electric propulsion to propel the spacecraft to its ultimate destination where it would perform its primary mission. As part of the Prometheus 1 Phase A studies, system models were developed for each of the spacecraft subsystems that were integrated into one overarching system model. The Electric Propulsion System (EPS) model was developed using data from the Prometheus 1 electric propulsion technology development efforts. This EPS model was then used to provide both performance and mass information to the Prometheus 1 system model for total system trades. Development of the EPS model is described, detailing both the performance calculations as well as its evolution over the course of Phase A through three technical baselines. Model outputs are also presented, detailing the performance of the model and its direct relationship to the Prometheus 1 technology development efforts. These EP system model outputs are also analyzed chronologically showing the response of the model development to the four technical baselines during Prometheus 1 Phase A.

An Introduction to Markov Modeling: Concepts and Uses

NASA Technical Reports Server (NTRS)

Boyd, Mark A.; Lau, Sonie (Technical Monitor)

1998-01-01

Kharkov modeling is a modeling technique that is widely useful for dependability analysis of complex fault tolerant systems. It is very flexible in the type of systems and system behavior it can model. It is not, however, the most appropriate modeling technique for every modeling situation. The first task in obtaining a reliability or availability estimate for a system is selecting which modeling technique is most appropriate to the situation at hand. A person performing a dependability analysis must confront the question: is Kharkov modeling most appropriate to the system under consideration, or should another technique be used instead? The need to answer this gives rise to other more basic questions regarding Kharkov modeling: what are the capabilities and limitations of Kharkov modeling as a modeling technique? How does it relate to other modeling techniques? What kind of system behavior can it model? What kinds of software tools are available for performing dependability analyses with Kharkov modeling techniques? These questions and others will be addressed in this tutorial.

New model performance index for engineering design of control systems

NASA Technical Reports Server (NTRS)

1970-01-01

Performance index includes a model representing linear control-system design specifications. Based on a geometric criterion for approximation of the model by the actual system, the index can be interpreted directly in terms of the desired system response model without actually having the model's time response.

Uncertainty Analysis of Coupled Socioeconomic-Cropping Models: Building Confidence in Climate Change Decision-Support Tools for Local Stakeholders

NASA Astrophysics Data System (ADS)

Malard, J. J.; Rojas, M.; Adamowski, J. F.; Gálvez, J.; Tuy, H. A.; Melgar-Quiñonez, H.

2015-12-01

While cropping models represent the biophysical aspects of agricultural systems, system dynamics modelling offers the possibility of representing the socioeconomic (including social and cultural) aspects of these systems. The two types of models can then be coupled in order to include the socioeconomic dimensions of climate change adaptation in the predictions of cropping models.We develop a dynamically coupled socioeconomic-biophysical model of agricultural production and its repercussions on food security in two case studies from Guatemala (a market-based, intensive agricultural system and a low-input, subsistence crop-based system). Through the specification of the climate inputs to the cropping model, the impacts of climate change on the entire system can be analysed, and the participatory nature of the system dynamics model-building process, in which stakeholders from NGOs to local governmental extension workers were included, helps ensure local trust in and use of the model.However, the analysis of climate variability's impacts on agroecosystems includes uncertainty, especially in the case of joint physical-socioeconomic modelling, and the explicit representation of this uncertainty in the participatory development of the models is important to ensure appropriate use of the models by the end users. In addition, standard model calibration, validation, and uncertainty interval estimation techniques used for physically-based models are impractical in the case of socioeconomic modelling. We present a methodology for the calibration and uncertainty analysis of coupled biophysical (cropping) and system dynamics (socioeconomic) agricultural models, using survey data and expert input to calibrate and evaluate the uncertainty of the system dynamics as well as of the overall coupled model. This approach offers an important tool for local decision makers to evaluate the potential impacts of climate change and their feedbacks through the associated socioeconomic system.

Adaptive Modeling of the International Space Station Electrical Power System

NASA Technical Reports Server (NTRS)

Thomas, Justin Ray

2007-01-01

Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.

A model-based executive for commanding robot teams

NASA Technical Reports Server (NTRS)

Barrett, Anthony

2005-01-01

The paper presents a way to robustly command a system of systems as a single entity. Instead of modeling each component system in isolation and then manually crafting interaction protocols, this approach starts with a model of the collective population as a single system. By compiling the model into separate elements for each component system and utilizing a teamwork model for coordination, it circumvents the complexities of manually crafting robust interaction protocols. The resulting systems are both globally responsive by virtue of a team oriented interaction model and locally responsive by virtue of a distributed approach to model-based fault detection, isolation, and recovery.

Fuzzy model-based servo and model following control for nonlinear systems.

PubMed

Ohtake, Hiroshi; Tanaka, Kazuo; Wang, Hua O

2009-12-01

This correspondence presents servo and nonlinear model following controls for a class of nonlinear systems using the Takagi-Sugeno fuzzy model-based control approach. First, the construction method of the augmented fuzzy system for continuous-time nonlinear systems is proposed by differentiating the original nonlinear system. Second, the dynamic fuzzy servo controller and the dynamic fuzzy model following controller, which can make outputs of the nonlinear system converge to target points and to outputs of the reference system, respectively, are introduced. Finally, the servo and model following controller design conditions are given in terms of linear matrix inequalities. Design examples illustrate the utility of this approach.

Integrating the Advanced Human Eye Model (AHEM) and optical instrument models to model complete visual optical systems inclusive of the typical or atypical eye

NASA Astrophysics Data System (ADS)

Donnelly, William J., III

2012-06-01

PURPOSE: To present a commercially available optical modeling software tool to assist the development of optical instrumentation and systems that utilize and/or integrate with the human eye. METHODS: A commercially available flexible eye modeling system is presented, the Advanced Human Eye Model (AHEM). AHEM is a module that the engineer can use to perform rapid development and test scenarios on systems that integrate with the eye. Methods include merging modeled systems initially developed outside of AHEM and performing a series of wizard-type operations that relieve the user from requiring an optometric or ophthalmic background to produce a complete eye inclusive system. Scenarios consist of retinal imaging of targets and sources through integrated systems. Uses include, but are not limited to, optimization, telescopes, microscopes, spectacles, contact and intraocular lenses, ocular aberrations, cataract simulation and scattering, and twin eye model (binocular) systems. RESULTS: Metrics, graphical data, and exportable CAD geometry are generated from the various modeling scenarios.

Model predictive control based on reduced order models applied to belt conveyor system.

PubMed

Chen, Wei; Li, Xin

2016-11-01

In the paper, a model predictive controller based on reduced order model is proposed to control belt conveyor system, which is an electro-mechanics complex system with long visco-elastic body. Firstly, in order to design low-degree controller, the balanced truncation method is used for belt conveyor model reduction. Secondly, MPC algorithm based on reduced order model for belt conveyor system is presented. Because of the error bound between the full-order model and reduced order model, two Kalman state estimators are applied in the control scheme to achieve better system performance. Finally, the simulation experiments are shown that balanced truncation method can significantly reduce the model order with high-accuracy and model predictive control based on reduced-model performs well in controlling the belt conveyor system. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Review of the systems biology of the immune system using agent-based models.

PubMed

Shinde, Snehal B; Kurhekar, Manish P

2018-06-01

The immune system is an inherent protection system in vertebrate animals including human beings that exhibit properties such as self-organisation, self-adaptation, learning, and recognition. It interacts with the other allied systems such as the gut and lymph nodes. There is a need for immune system modelling to know about its complex internal mechanism, to understand how it maintains the homoeostasis, and how it interacts with the other systems. There are two types of modelling techniques used for the simulation of features of the immune system: equation-based modelling (EBM) and agent-based modelling. Owing to certain shortcomings of the EBM, agent-based modelling techniques are being widely used. This technique provides various predictions for disease causes and treatments; it also helps in hypothesis verification. This study presents a review of agent-based modelling of the immune system and its interactions with the gut and lymph nodes. The authors also review the modelling of immune system interactions during tuberculosis and cancer. In addition, they also outline the future research directions for the immune system simulation through agent-based techniques such as the effects of stress on the immune system, evolution of the immune system, and identification of the parameters for a healthy immune system.

Multiple system modelling of waste management

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

Eriksson, Ola, E-mail: ola.eriksson@hig.se; Department of Building, Energy and Environmental Engineering, University of Gaevle, SE 801 76 Gaevle; Bisaillon, Mattias, E-mail: mattias.bisaillon@profu.se

2011-12-15

Highlights: > Linking of models will provide a more complete, correct and credible picture of the systems. > The linking procedure is easy to perform and also leads to activation of project partners. > The simulation procedure is a bit more complicated and calls for the ability to run both models. - Abstract: Due to increased environmental awareness, planning and performance of waste management has become more and more complex. Therefore waste management has early been subject to different types of modelling. Another field with long experience of modelling and systems perspective is energy systems. The two modelling traditions havemore » developed side by side, but so far there are very few attempts to combine them. Waste management systems can be linked together with energy systems through incineration plants. The models for waste management can be modelled on a quite detailed level whereas surrounding systems are modelled in a more simplistic way. This is a problem, as previous studies have shown that assumptions on the surrounding system often tend to be important for the conclusions. In this paper it is shown how two models, one for the district heating system (MARTES) and another one for the waste management system (ORWARE), can be linked together. The strengths and weaknesses with model linking are discussed when compared to simplistic assumptions on effects in the energy and waste management systems. It is concluded that the linking of models will provide a more complete, correct and credible picture of the consequences of different simultaneous changes in the systems. The linking procedure is easy to perform and also leads to activation of project partners. However, the simulation procedure is a bit more complicated and calls for the ability to run both models.« less

Photovoltaic performance models - A report card

NASA Technical Reports Server (NTRS)

Smith, J. H.; Reiter, L. R.

1985-01-01

Models for the analysis of photovoltaic (PV) systems' designs, implementation policies, and economic performance, have proliferated while keeping pace with rapid changes in basic PV technology and extensive empirical data compiled for such systems' performance. Attention is presently given to the results of a comparative assessment of ten well documented and widely used models, which range in complexity from first-order approximations of PV system performance to in-depth, circuit-level characterizations. The comparisons were made on the basis of the performance of their subsystem, as well as system, elements. The models fall into three categories in light of their degree of aggregation into subsystems: (1) simplified models for first-order calculation of system performance, with easily met input requirements but limited capability to address more than a small variety of design considerations; (2) models simulating PV systems in greater detail, encompassing types primarily intended for either concentrator-incorporating or flat plate collector PV systems; and (3) models not specifically designed for PV system performance modeling, but applicable to aspects of electrical system design. Models ignoring subsystem failure or degradation are noted to exclude operating and maintenance characteristics as well.

A structural model decomposition framework for systems health management

NASA Astrophysics Data System (ADS)

Roychoudhury, I.; Daigle, M.; Bregon, A.; Pulido, B.

Systems health management (SHM) is an important set of technologies aimed at increasing system safety and reliability by detecting, isolating, and identifying faults; and predicting when the system reaches end of life (EOL), so that appropriate fault mitigation and recovery actions can be taken. Model-based SHM approaches typically make use of global, monolithic system models for online analysis, which results in a loss of scalability and efficiency for large-scale systems. Improvement in scalability and efficiency can be achieved by decomposing the system model into smaller local submodels and operating on these submodels instead. In this paper, the global system model is analyzed offline and structurally decomposed into local submodels. We define a common model decomposition framework for extracting submodels from the global model. This framework is then used to develop algorithms for solving model decomposition problems for the design of three separate SHM technologies, namely, estimation (which is useful for fault detection and identification), fault isolation, and EOL prediction. We solve these model decomposition problems using a three-tank system as a case study.

A Structural Model Decomposition Framework for Systems Health Management

NASA Technical Reports Server (NTRS)

Roychoudhury, Indranil; Daigle, Matthew J.; Bregon, Anibal; Pulido, Belamino

2013-01-01

Systems health management (SHM) is an important set of technologies aimed at increasing system safety and reliability by detecting, isolating, and identifying faults; and predicting when the system reaches end of life (EOL), so that appropriate fault mitigation and recovery actions can be taken. Model-based SHM approaches typically make use of global, monolithic system models for online analysis, which results in a loss of scalability and efficiency for large-scale systems. Improvement in scalability and efficiency can be achieved by decomposing the system model into smaller local submodels and operating on these submodels instead. In this paper, the global system model is analyzed offline and structurally decomposed into local submodels. We define a common model decomposition framework for extracting submodels from the global model. This framework is then used to develop algorithms for solving model decomposition problems for the design of three separate SHM technologies, namely, estimation (which is useful for fault detection and identification), fault isolation, and EOL prediction. We solve these model decomposition problems using a three-tank system as a case study.

Application of field dependent polynomial model

NASA Astrophysics Data System (ADS)

Janout, Petr; Páta, Petr; Skala, Petr; Fliegel, Karel; Vítek, Stanislav; Bednář, Jan

2016-09-01

Extremely wide-field imaging systems have many advantages regarding large display scenes whether for use in microscopy, all sky cameras, or in security technologies. The Large viewing angle is paid by the amount of aberrations, which are included with these imaging systems. Modeling wavefront aberrations using the Zernike polynomials is known a longer time and is widely used. Our method does not model system aberrations in a way of modeling wavefront, but directly modeling of aberration Point Spread Function of used imaging system. This is a very complicated task, and with conventional methods, it was difficult to achieve the desired accuracy. Our optimization techniques of searching coefficients space-variant Zernike polynomials can be described as a comprehensive model for ultra-wide-field imaging systems. The advantage of this model is that the model describes the whole space-variant system, unlike the majority models which are partly invariant systems. The issue that this model is the attempt to equalize the size of the modeled Point Spread Function, which is comparable to the pixel size. Issues associated with sampling, pixel size, pixel sensitivity profile must be taken into account in the design. The model was verified in a series of laboratory test patterns, test images of laboratory light sources and consequently on real images obtained by an extremely wide-field imaging system WILLIAM. Results of modeling of this system are listed in this article.

Evaluation of load flow and grid expansion in a unit-commitment and expansion optimization model SciGRID International Conference on Power Grid Modelling

NASA Astrophysics Data System (ADS)

Senkpiel, Charlotte; Biener, Wolfgang; Shammugam, Shivenes; Längle, Sven

2018-02-01

Energy system models serve as a basis for long term system planning. Joint optimization of electricity generating technologies, storage systems and the electricity grid leads to lower total system cost compared to an approach in which the grid expansion follows a given technology portfolio and their distribution. Modelers often face the problem of finding a good tradeoff between computational time and the level of detail that can be modeled. This paper analyses the differences between a transport model and a DC load flow model to evaluate the validity of using a simple but faster transport model within the system optimization model in terms of system reliability. The main findings in this paper are that a higher regional resolution of a system leads to better results compared to an approach in which regions are clustered as more overloads can be detected. An aggregation of lines between two model regions compared to a line sharp representation has little influence on grid expansion within a system optimizer. In a DC load flow model overloads can be detected in a line sharp case, which is therefore preferred. Overall the regions that need to reinforce the grid are identified within the system optimizer. Finally the paper recommends the usage of a load-flow model to test the validity of the model results.

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking

PubMed Central

Gilbert, David

2016-01-01

Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour, the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems. PMID:27187178

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.

PubMed

Pârvu, Ovidiu; Gilbert, David

2016-01-01

Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour, the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems.

Coupled socioeconomic-crop modelling for the participatory local analysis of climate change impacts on smallholder farmers in Guatemala

NASA Astrophysics Data System (ADS)

Malard, J. J.; Adamowski, J. F.; Wang, L. Y.; Rojas, M.; Carrera, J.; Gálvez, J.; Tuy, H. A.; Melgar-Quiñonez, H.

2015-12-01

The modelling of the impacts of climate change on agriculture requires the inclusion of socio-economic factors. However, while cropping models and economic models of agricultural systems are common, dynamically coupled socio-economic-biophysical models have not received as much success. A promising methodology for modelling the socioeconomic aspects of coupled natural-human systems is participatory system dynamics modelling, in which stakeholders develop mental maps of the socio-economic system that are then turned into quantified simulation models. This methodology has been successful in the water resources management field. However, while the stocks and flows of water resources have also been represented within the system dynamics modelling framework and thus coupled to the socioeconomic portion of the model, cropping models are ill-suited for such reformulation. In addition, most of these system dynamics models were developed without stakeholder input, limiting the scope for the adoption and implementation of their results. We therefore propose a new methodology for the analysis of climate change variability on agroecosystems which uses dynamically coupled system dynamics (socio-economic) and biophysical (cropping) models to represent both physical and socioeconomic aspects of the agricultural system, using two case studies (intensive market-based agricultural development versus subsistence crop-based development) from rural Guatemala. The system dynamics model component is developed with relevant governmental and NGO stakeholders from rural and agricultural development in the case study regions and includes such processes as education, poverty and food security. Common variables with the cropping models (yield and agricultural management choices) are then used to dynamically couple the two models together, allowing for the analysis of the agroeconomic system's response to and resilience against various climatic and socioeconomic shocks.

From Data-Sharing to Model-Sharing: SCEC and the Development of Earthquake System Science (Invited)

NASA Astrophysics Data System (ADS)

Jordan, T. H.

2009-12-01

Earthquake system science seeks to construct system-level models of earthquake phenomena and use them to predict emergent seismic behavior—an ambitious enterprise that requires high degree of interdisciplinary, multi-institutional collaboration. This presentation will explore model-sharing structures that have been successful in promoting earthquake system science within the Southern California Earthquake Center (SCEC). These include disciplinary working groups to aggregate data into community models; numerical-simulation working groups to investigate system-specific phenomena (process modeling) and further improve the data models (inverse modeling); and interdisciplinary working groups to synthesize predictive system-level models. SCEC has developed a cyberinfrastructure, called the Community Modeling Environment, that can distribute the community models; manage large suites of numerical simulations; vertically integrate the hardware, software, and wetware needed for system-level modeling; and promote the interactions among working groups needed for model validation and refinement. Various socio-scientific structures contribute to successful model-sharing. Two of the most important are “communities of trust” and collaborations between government and academic scientists on mission-oriented objectives. The latter include improvements of earthquake forecasts and seismic hazard models and the use of earthquake scenarios in promoting public awareness and disaster management.

Enhancement of the Acquisition Process for a Combat System-A Case Study to Model the Workflow Processes for an Air Defense System Acquisition

DTIC Science & Technology

2009-12-01

Business Process Modeling BPMN Business Process Modeling Notation SoA Service-oriented Architecture UML Unified Modeling Language CSP...system developers. Supporting technologies include Business Process Modeling Notation ( BPMN ), Unified Modeling Language (UML), model-driven architecture

Integration of Earth System Models and Workflow Management under iRODS for the Northeast Regional Earth System Modeling Project

NASA Astrophysics Data System (ADS)

Lengyel, F.; Yang, P.; Rosenzweig, B.; Vorosmarty, C. J.

2012-12-01

The Northeast Regional Earth System Model (NE-RESM, NSF Award #1049181) integrates weather research and forecasting models, terrestrial and aquatic ecosystem models, a water balance/transport model, and mesoscale and energy systems input-out economic models developed by interdisciplinary research team from academia and government with expertise in physics, biogeochemistry, engineering, energy, economics, and policy. NE-RESM is intended to forecast the implications of planning decisions on the region's environment, ecosystem services, energy systems and economy through the 21st century. Integration of model components and the development of cyberinfrastructure for interacting with the system is facilitated with the integrated Rule Oriented Data System (iRODS), a distributed data grid that provides archival storage with metadata facilities and a rule-based workflow engine for automating and auditing scientific workflows.

CONFIG - Adapting qualitative modeling and discrete event simulation for design of fault management systems

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Basham, Bryan D.

1989-01-01

CONFIG is a modeling and simulation tool prototype for analyzing the normal and faulty qualitative behaviors of engineered systems. Qualitative modeling and discrete-event simulation have been adapted and integrated, to support early development, during system design, of software and procedures for management of failures, especially in diagnostic expert systems. Qualitative component models are defined in terms of normal and faulty modes and processes, which are defined by invocation statements and effect statements with time delays. System models are constructed graphically by using instances of components and relations from object-oriented hierarchical model libraries. Extension and reuse of CONFIG models and analysis capabilities in hybrid rule- and model-based expert fault-management support systems are discussed.

OOMM--Object-Oriented Matrix Modelling: an instrument for the integration of the Brasilia Regional Health Information System.

PubMed

Cammarota, M; Huppes, V; Gaia, S; Degoulet, P

1998-01-01

The development of Health Information Systems is widely determined by the establishment of the underlying information models. An Object-Oriented Matrix Model (OOMM) is described which target is to facilitate the integration of the overall health system. The model is based on information modules named micro-databases that are structured in a three-dimensional network: planning, health structures and information systems. The modelling tool has been developed as a layer on top of a relational database system. A visual browser facilitates the development and maintenance of the information model. The modelling approach has been applied to the Brasilia University Hospital since 1991. The extension of the modelling approach to the Brasilia regional health system is considered.

On domain modelling of the service system with its application to enterprise information systems

NASA Astrophysics Data System (ADS)

Wang, J. W.; Wang, H. F.; Ding, J. L.; Furuta, K.; Kanno, T.; Ip, W. H.; Zhang, W. J.

2016-01-01

Information systems are a kind of service systems and they are throughout every element of a modern industrial and business system, much like blood in our body. Types of information systems are heterogeneous because of extreme uncertainty in changes in modern industrial and business systems. To effectively manage information systems, modelling of the work domain (or domain) of information systems is necessary. In this paper, a domain modelling framework for the service system is proposed and its application to the enterprise information system is outlined. The framework is defined based on application of a general domain modelling tool called function-context-behaviour-principle-state-structure (FCBPSS). The FCBPSS is based on a set of core concepts, namely: function, context, behaviour, principle, state and structure and system decomposition. Different from many other applications of FCBPSS in systems engineering, the FCBPSS is applied to both infrastructure and substance systems, which is novel and effective to modelling of service systems including enterprise information systems. It is to be noted that domain modelling of systems (e.g. enterprise information systems) is a key to integration of heterogeneous systems and to coping with unanticipated situations facing to systems.

A Model-Driven Development Method for Management Information Systems

NASA Astrophysics Data System (ADS)

Mizuno, Tomoki; Matsumoto, Keinosuke; Mori, Naoki

Traditionally, a Management Information System (MIS) has been developed without using formal methods. By the informal methods, the MIS is developed on its lifecycle without having any models. It causes many problems such as lack of the reliability of system design specifications. In order to overcome these problems, a model theory approach was proposed. The approach is based on an idea that a system can be modeled by automata and set theory. However, it is very difficult to generate automata of the system to be developed right from the start. On the other hand, there is a model-driven development method that can flexibly correspond to changes of business logics or implementing technologies. In the model-driven development, a system is modeled using a modeling language such as UML. This paper proposes a new development method for management information systems applying the model-driven development method to a component of the model theory approach. The experiment has shown that a reduced amount of efforts is more than 30% of all the efforts.

Computer model of cardiovascular control system responses to exercise

NASA Technical Reports Server (NTRS)

Croston, R. C.; Rummel, J. A.; Kay, F. J.

1973-01-01

Approaches of systems analysis and mathematical modeling together with computer simulation techniques are applied to the cardiovascular system in order to simulate dynamic responses of the system to a range of exercise work loads. A block diagram of the circulatory model is presented, taking into account arterial segments, venous segments, arterio-venous circulation branches, and the heart. A cardiovascular control system model is also discussed together with model test results.

Implementation of a Sage-Based Stirling Model Into a System-Level Numerical Model of the Fission Power System Technology Demonstration Unit

NASA Technical Reports Server (NTRS)

Briggs, Maxwell H.

2011-01-01

The Fission Power System (FPS) project is developing a Technology Demonstration Unit (TDU) to verify the performance and functionality of a subscale version of the FPS reference concept in a relevant environment, and to verify component and system models. As hardware is developed for the TDU, component and system models must be refined to include the details of specific component designs. This paper describes the development of a Sage-based pseudo-steady-state Stirling convertor model and its implementation into a system-level model of the TDU.

Model-Based Safety Analysis

NASA Technical Reports Server (NTRS)

Joshi, Anjali; Heimdahl, Mats P. E.; Miller, Steven P.; Whalen, Mike W.

2006-01-01

System safety analysis techniques are well established and are used extensively during the design of safety-critical systems. Despite this, most of the techniques are highly subjective and dependent on the skill of the practitioner. Since these analyses are usually based on an informal system model, it is unlikely that they will be complete, consistent, and error free. In fact, the lack of precise models of the system architecture and its failure modes often forces the safety analysts to devote much of their effort to gathering architectural details about the system behavior from several sources and embedding this information in the safety artifacts such as the fault trees. This report describes Model-Based Safety Analysis, an approach in which the system and safety engineers share a common system model created using a model-based development process. By extending the system model with a fault model as well as relevant portions of the physical system to be controlled, automated support can be provided for much of the safety analysis. We believe that by using a common model for both system and safety engineering and automating parts of the safety analysis, we can both reduce the cost and improve the quality of the safety analysis. Here we present our vision of model-based safety analysis and discuss the advantages and challenges in making this approach practical.

Modeling of Spacecraft Advanced Chemical Propulsion Systems

NASA Technical Reports Server (NTRS)

Benfield, Michael P. J.; Belcher, Jeremy A.

2004-01-01

This paper outlines the development of the Advanced Chemical Propulsion System (ACPS) model for Earth and Space Storable propellants. This model was developed by the System Technology Operation of SAIC-Huntsville for the NASA MSFC In-Space Propulsion Project Office. Each subsystem of the model is described. Selected model results will also be shown to demonstrate the model's ability to evaluate technology changes in chemical propulsion systems.

The use of discrete-event simulation modeling to compare handwritten and electronic prescribing systems.

PubMed

Ghany, Ahmad; Vassanji, Karim; Kuziemsky, Craig; Keshavjee, Karim

2013-01-01

Electronic prescribing (e-prescribing) is expected to bring many benefits to Canadian healthcare, such as a reduction in errors and adverse drug reactions. As there currently is no functioning e-prescribing system in Canada that is completely electronic, we are unable to evaluate the performance of a live system. An alternative approach is to use simulation modeling for evaluation. We developed two discrete-event simulation models, one of the current handwritten prescribing system and one of a proposed e-prescribing system, to compare the performance of these two systems. We were able to compare the number of processes in each model, workflow efficiency, and the distribution of patients or prescriptions. Although we were able to compare these models to each other, using discrete-event simulation software was challenging. We were limited in the number of variables we could measure. We discovered non-linear processes and feedback loops in both models that could not be adequately represented using discrete-event simulation software. Finally, interactions between entities in both models could not be modeled using this type of software. We have come to the conclusion that a more appropriate approach to modeling both the handwritten and electronic prescribing systems would be to use a complex adaptive systems approach using agent-based modeling or systems-based modeling.

NASA Workshop on Distributed Parameter Modeling and Control of Flexible Aerospace Systems

NASA Technical Reports Server (NTRS)

Marks, Virginia B. (Compiler); Keckler, Claude R. (Compiler)

1994-01-01

Although significant advances have been made in modeling and controlling flexible systems, there remains a need for improvements in model accuracy and in control performance. The finite element models of flexible systems are unduly complex and are almost intractable to optimum parameter estimation for refinement using experimental data. Distributed parameter or continuum modeling offers some advantages and some challenges in both modeling and control. Continuum models often result in a significantly reduced number of model parameters, thereby enabling optimum parameter estimation. The dynamic equations of motion of continuum models provide the advantage of allowing the embedding of the control system dynamics, thus forming a complete set of system dynamics. There is also increased insight provided by the continuum model approach.

Overview of the GRC Stirling Convertor System Dynamic Model

NASA Technical Reports Server (NTRS)

Lewandowski, Edward J.; Regan, Timothy F.

2004-01-01

A Stirling Convertor System Dynamic Model has been developed at the Glenn Research Center for controls, dynamics, and systems development of free-piston convertor power systems. It models the Stirling cycle thermodynamics, heat flow, gas, mechanical, and mounting dynamics, the linear alternator, and the controller. The model's scope extends from the thermal energy input to thermal, mechanical dynamics, and electrical energy out, allowing one to study complex system interactions among subsystems. The model is a non-linear time-domain model containing sub-cycle dynamics, allowing it to simulate transient and dynamic phenomena that other models cannot. The model details and capability are discussed.

System Dynamic Analysis of a Wind Tunnel Model with Applications to Improve Aerodynamic Data Quality

NASA Technical Reports Server (NTRS)

Buehrle, Ralph David

1997-01-01

The research investigates the effect of wind tunnel model system dynamics on measured aerodynamic data. During wind tunnel tests designed to obtain lift and drag data, the required aerodynamic measurements are the steady-state balance forces and moments, pressures, and model attitude. However, the wind tunnel model system can be subjected to unsteady aerodynamic and inertial loads which result in oscillatory translations and angular rotations. The steady-state force balance and inertial model attitude measurements are obtained by filtering and averaging data taken during conditions of high model vibrations. The main goals of this research are to characterize the effects of model system dynamics on the measured steady-state aerodynamic data and develop a correction technique to compensate for dynamically induced errors. Equations of motion are formulated for the dynamic response of the model system subjected to arbitrary aerodynamic and inertial inputs. The resulting modal model is examined to study the effects of the model system dynamic response on the aerodynamic data. In particular, the equations of motion are used to describe the effect of dynamics on the inertial model attitude, or angle of attack, measurement system that is used routinely at the NASA Langley Research Center and other wind tunnel facilities throughout the world. This activity was prompted by the inertial model attitude sensor response observed during high levels of model vibration while testing in the National Transonic Facility at the NASA Langley Research Center. The inertial attitude sensor cannot distinguish between the gravitational acceleration and centrifugal accelerations associated with wind tunnel model system vibration, which results in a model attitude measurement bias error. Bias errors over an order of magnitude greater than the required device accuracy were found in the inertial model attitude measurements during dynamic testing of two model systems. Based on a theoretical modal approach, a method using measured vibration amplitudes and measured or calculated modal characteristics of the model system is developed to correct for dynamic bias errors in the model attitude measurements. The correction method is verified through dynamic response tests on two model systems and actual wind tunnel test data.

Systems Operation Studies for Automated Guideway Transit Systems : Availability Model Functional Specification

DOT National Transportation Integrated Search

1981-01-01

The System Availability Model (SAM) is a system-level model which provides measures of vehicle and passenger availability. The SAM will be used to evaluate the system-level influence of availability concepts employed in AGT systems. This functional s...

Practical limits for reverse engineering of dynamical systems: a statistical analysis of sensitivity and parameter inferability in systems biology models.

PubMed

Erguler, Kamil; Stumpf, Michael P H

2011-05-01

The size and complexity of cellular systems make building predictive models an extremely difficult task. In principle dynamical time-course data can be used to elucidate the structure of the underlying molecular mechanisms, but a central and recurring problem is that many and very different models can be fitted to experimental data, especially when the latter are limited and subject to noise. Even given a model, estimating its parameters remains challenging in real-world systems. Here we present a comprehensive analysis of 180 systems biology models, which allows us to classify the parameters with respect to their contribution to the overall dynamical behaviour of the different systems. Our results reveal candidate elements of control in biochemical pathways that differentially contribute to dynamics. We introduce sensitivity profiles that concisely characterize parameter sensitivity and demonstrate how this can be connected to variability in data. Systematically linking data and model sloppiness allows us to extract features of dynamical systems that determine how well parameters can be estimated from time-course measurements, and associates the extent of data required for parameter inference with the model structure, and also with the global dynamical state of the system. The comprehensive analysis of so many systems biology models reaffirms the inability to estimate precisely most model or kinetic parameters as a generic feature of dynamical systems, and provides safe guidelines for performing better inferences and model predictions in the context of reverse engineering of mathematical models for biological systems.

Model reduction by trimming for a class of semi-Markov reliability models and the corresponding error bound

NASA Technical Reports Server (NTRS)

White, Allan L.; Palumbo, Daniel L.

1991-01-01

Semi-Markov processes have proved to be an effective and convenient tool to construct models of systems that achieve reliability by redundancy and reconfiguration. These models are able to depict complex system architectures and to capture the dynamics of fault arrival and system recovery. A disadvantage of this approach is that the models can be extremely large, which poses both a model and a computational problem. Techniques are needed to reduce the model size. Because these systems are used in critical applications where failure can be expensive, there must be an analytically derived bound for the error produced by the model reduction technique. A model reduction technique called trimming is presented that can be applied to a popular class of systems. Automatic model generation programs were written to help the reliability analyst produce models of complex systems. This method, trimming, is easy to implement and the error bound easy to compute. Hence, the method lends itself to inclusion in an automatic model generator.

Two degree of freedom internal model control-PID design for LFC of power systems via logarithmic approximations.

PubMed

Singh, Jay; Chattterjee, Kalyan; Vishwakarma, C B

2018-01-01

Load frequency controller has been designed for reduced order model of single area and two-area reheat hydro-thermal power system through internal model control - proportional integral derivative (IMC-PID) control techniques. The controller design method is based on two degree of freedom (2DOF) internal model control which combines with model order reduction technique. Here, in spite of taking full order system model a reduced order model has been considered for 2DOF-IMC-PID design and the designed controller is directly applied to full order system model. The Logarithmic based model order reduction technique is proposed to reduce the single and two-area high order power systems for the application of controller design.The proposed IMC-PID design of reduced order model achieves good dynamic response and robustness against load disturbance with the original high order system. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Neural system modeling and simulation using Hybrid Functional Petri Net.

PubMed

Tang, Yin; Wang, Fei

2012-02-01

The Petri net formalism has been proved to be powerful in biological modeling. It not only boasts of a most intuitive graphical presentation but also combines the methods of classical systems biology with the discrete modeling technique. Hybrid Functional Petri Net (HFPN) was proposed specially for biological system modeling. An array of well-constructed biological models using HFPN yielded very interesting results. In this paper, we propose a method to represent neural system behavior, where biochemistry and electrical chemistry are both included using the Petri net formalism. We built a model for the adrenergic system using HFPN and employed quantitative analysis. Our simulation results match the biological data well, showing that the model is very effective. Predictions made on our model further manifest the modeling power of HFPN and improve the understanding of the adrenergic system. The file of our model and more results with their analysis are available in our supplementary material.

An expert system for water quality modelling.

PubMed

Booty, W G; Lam, D C; Bobba, A G; Wong, I; Kay, D; Kerby, J P; Bowen, G S

1992-12-01

The RAISON-micro (Regional Analysis by Intelligent System ON a micro-computer) expert system is being used to predict the effects of mine effluents on receiving waters in Ontario. The potential of this system to assist regulatory agencies and mining industries to define more acceptable effluent limits was shown in an initial study. This system has been further developed so that the expert system helps the model user choose the most appropriate model for a particular application from a hierarchy of models. The system currently contains seven models which range from steady state to time dependent models, for both conservative and nonconservative substances in rivers and lakes. The menu driven expert system prompts the model user for information such as the nature of the receiving water system, the type of effluent being considered, and the range of background data available for use as input to the models. The system can also be used to determine the nature of the environmental conditions at the site which are not available in the textual information database, such as the components of river flow. Applications of the water quality expert system are presented for representative mine sites in the Timmins area of Ontario.

A logical model of cooperating rule-based systems

NASA Technical Reports Server (NTRS)

Bailin, Sidney C.; Moore, John M.; Hilberg, Robert H.; Murphy, Elizabeth D.; Bahder, Shari A.

1989-01-01

A model is developed to assist in the planning, specification, development, and verification of space information systems involving distributed rule-based systems. The model is based on an analysis of possible uses of rule-based systems in control centers. This analysis is summarized as a data-flow model for a hypothetical intelligent control center. From this data-flow model, the logical model of cooperating rule-based systems is extracted. This model consists of four layers of increasing capability: (1) communicating agents, (2) belief-sharing knowledge sources, (3) goal-sharing interest areas, and (4) task-sharing job roles.

Reliability model generator

NASA Technical Reports Server (NTRS)

Cohen, Gerald C. (Inventor); McMann, Catherine M. (Inventor)

1991-01-01

An improved method and system for automatically generating reliability models for use with a reliability evaluation tool is described. The reliability model generator of the present invention includes means for storing a plurality of low level reliability models which represent the reliability characteristics for low level system components. In addition, the present invention includes means for defining the interconnection of the low level reliability models via a system architecture description. In accordance with the principles of the present invention, a reliability model for the entire system is automatically generated by aggregating the low level reliability models based on the system architecture description.

A hierarchy for modeling high speed propulsion systems

NASA Technical Reports Server (NTRS)

Hartley, Tom T.; Deabreu, Alex

1991-01-01

General research efforts on reduced order propulsion models for control systems design are overviewed. Methods for modeling high speed propulsion systems are discussed including internal flow propulsion systems that do not contain rotating machinery such as inlets, ramjets, and scramjets. The discussion is separated into four sections: (1) computational fluid dynamics model for the entire nonlinear system or high order nonlinear models; (2) high order linearized model derived from fundamental physics; (3) low order linear models obtained from other high order models; and (4) low order nonlinear models. Included are special considerations on any relevant control system designs. The methods discussed are for the quasi-one dimensional Euler equations of gasdynamic flow. The essential nonlinear features represented are large amplitude nonlinear waves, moving normal shocks, hammershocks, subsonic combustion via heat addition, temperature dependent gases, detonation, and thermal choking.

Top-level modeling of an als system utilizing object-oriented techniques

NASA Astrophysics Data System (ADS)

Rodriguez, L. F.; Kang, S.; Ting, K. C.

The possible configuration of an Advanced Life Support (ALS) System capable of supporting human life for long-term space missions continues to evolve as researchers investigate potential technologies and configurations. To facilitate the decision process the development of acceptable, flexible, and dynamic mathematical computer modeling tools capable of system level analysis is desirable. Object-oriented techniques have been adopted to develop a dynamic top-level model of an ALS system.This approach has several advantages; among these, object-oriented abstractions of systems are inherently modular in architecture. Thus, models can initially be somewhat simplistic, while allowing for adjustments and improvements. In addition, by coding the model in Java, the model can be implemented via the World Wide Web, greatly encouraging the utilization of the model. Systems analysis is further enabled with the utilization of a readily available backend database containing information supporting the model. The subsystem models of the ALS system model include Crew, Biomass Production, Waste Processing and Resource Recovery, Food Processing and Nutrition, and the Interconnecting Space. Each subsystem model and an overall model have been developed. Presented here is the procedure utilized to develop the modeling tool, the vision of the modeling tool, and the current focus for each of the subsystem models.

Using object-oriented analysis techniques to support system testing

NASA Astrophysics Data System (ADS)

Zucconi, Lin

1990-03-01

Testing of real-time control systems can be greatly facilitated by use of object-oriented and structured analysis modeling techniques. This report describes a project where behavior, process and information models built for a real-time control system were used to augment and aid traditional system testing. The modeling techniques used were an adaptation of the Ward/Mellor method for real-time systems analysis and design (Ward85) for object-oriented development. The models were used to simulate system behavior by means of hand execution of the behavior or state model and the associated process (data and control flow) and information (data) models. The information model, which uses an extended entity-relationship modeling technique, is used to identify application domain objects and their attributes (instance variables). The behavioral model uses state-transition diagrams to describe the state-dependent behavior of the object. The process model uses a transformation schema to describe the operations performed on or by the object. Together, these models provide a means of analyzing and specifying a system in terms of the static and dynamic properties of the objects which it manipulates. The various models were used to simultaneously capture knowledge about both the objects in the application domain and the system implementation. Models were constructed, verified against the software as-built and validated through informal reviews with the developer. These models were then hand-executed.

Human systems dynamics: Toward a computational model

NASA Astrophysics Data System (ADS)

Eoyang, Glenda H.

2012-09-01

A robust and reliable computational model of complex human systems dynamics could support advancements in theory and practice for social systems at all levels, from intrapersonal experience to global politics and economics. Models of human interactions have evolved from traditional, Newtonian systems assumptions, which served a variety of practical and theoretical needs of the past. Another class of models has been inspired and informed by models and methods from nonlinear dynamics, chaos, and complexity science. None of the existing models, however, is able to represent the open, high dimension, and nonlinear self-organizing dynamics of social systems. An effective model will represent interactions at multiple levels to generate emergent patterns of social and political life of individuals and groups. Existing models and modeling methods are considered and assessed against characteristic pattern-forming processes in observed and experienced phenomena of human systems. A conceptual model, CDE Model, based on the conditions for self-organizing in human systems, is explored as an alternative to existing models and methods. While the new model overcomes the limitations of previous models, it also provides an explanatory base and foundation for prospective analysis to inform real-time meaning making and action taking in response to complex conditions in the real world. An invitation is extended to readers to engage in developing a computational model that incorporates the assumptions, meta-variables, and relationships of this open, high dimension, and nonlinear conceptual model of the complex dynamics of human systems.

System Simulation Modeling: A Case Study Illustration of the Model Development Life Cycle

Treesearch

Janice K. Wiedenbeck; D. Earl Kline

1994-01-01

Systems simulation modeling techniques offer a method of representing the individual elements of a manufacturing system and their interactions. By developing and experimenting with simulation models, one can obtain a better understanding of the overall physical system. Forest products industries are beginning to understand the importance of simulation modeling to help...

The (Mathematical) Modeling Process in Biosciences.

PubMed

Torres, Nestor V; Santos, Guido

2015-01-01

In this communication, we introduce a general framework and discussion on the role of models and the modeling process in the field of biosciences. The objective is to sum up the common procedures during the formalization and analysis of a biological problem from the perspective of Systems Biology, which approaches the study of biological systems as a whole. We begin by presenting the definitions of (biological) system and model. Particular attention is given to the meaning of mathematical model within the context of biology. Then, we present the process of modeling and analysis of biological systems. Three stages are described in detail: conceptualization of the biological system into a model, mathematical formalization of the previous conceptual model and optimization and system management derived from the analysis of the mathematical model. All along this work the main features and shortcomings of the process are analyzed and a set of rules that could help in the task of modeling any biological system are presented. Special regard is given to the formative requirements and the interdisciplinary nature of this approach. We conclude with some general considerations on the challenges that modeling is posing to current biology.

An online model composition tool for system biology models

PubMed Central

2013-01-01

Background There are multiple representation formats for Systems Biology computational models, and the Systems Biology Markup Language (SBML) is one of the most widely used. SBML is used to capture, store, and distribute computational models by Systems Biology data sources (e.g., the BioModels Database) and researchers. Therefore, there is a need for all-in-one web-based solutions that support advance SBML functionalities such as uploading, editing, composing, visualizing, simulating, querying, and browsing computational models. Results We present the design and implementation of the Model Composition Tool (Interface) within the PathCase-SB (PathCase Systems Biology) web portal. The tool helps users compose systems biology models to facilitate the complex process of merging systems biology models. We also present three tools that support the model composition tool, namely, (1) Model Simulation Interface that generates a visual plot of the simulation according to user’s input, (2) iModel Tool as a platform for users to upload their own models to compose, and (3) SimCom Tool that provides a side by side comparison of models being composed in the same pathway. Finally, we provide a web site that hosts BioModels Database models and a separate web site that hosts SBML Test Suite models. Conclusions Model composition tool (and the other three tools) can be used with little or no knowledge of the SBML document structure. For this reason, students or anyone who wants to learn about systems biology will benefit from the described functionalities. SBML Test Suite models will be a nice starting point for beginners. And, for more advanced purposes, users will able to access and employ models of the BioModels Database as well. PMID:24006914

Microphysics in the Multi-Scale Modeling Systems with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

2011-01-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. 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 NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) 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-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, the microphysics developments of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the heavy precipitation processes will be presented.

Systems and context modeling approach to requirements analysis

NASA Astrophysics Data System (ADS)

Ahuja, Amrit; Muralikrishna, G.; Patwari, Puneet; Subhrojyoti, C.; Swaminathan, N.; Vin, Harrick

2014-08-01

Ensuring completeness and correctness of the requirements for a complex system such as the SKA is challenging. Current system engineering practice includes developing a stakeholder needs definition, a concept of operations, and defining system requirements in terms of use cases and requirements statements. We present a method that enhances this current practice into a collection of system models with mutual consistency relationships. These include stakeholder goals, needs definition and system-of-interest models, together with a context model that participates in the consistency relationships among these models. We illustrate this approach by using it to analyze the SKA system requirements.

Agent autonomy approach to probabilistic physics-of-failure modeling of complex dynamic systems with interacting failure mechanisms

NASA Astrophysics Data System (ADS)

Gromek, Katherine Emily

A novel computational and inference framework of the physics-of-failure (PoF) reliability modeling for complex dynamic systems has been established in this research. The PoF-based reliability models are used to perform a real time simulation of system failure processes, so that the system level reliability modeling would constitute inferences from checking the status of component level reliability at any given time. The "agent autonomy" concept is applied as a solution method for the system-level probabilistic PoF-based (i.e. PPoF-based) modeling. This concept originated from artificial intelligence (AI) as a leading intelligent computational inference in modeling of multi agents systems (MAS). The concept of agent autonomy in the context of reliability modeling was first proposed by M. Azarkhail [1], where a fundamentally new idea of system representation by autonomous intelligent agents for the purpose of reliability modeling was introduced. Contribution of the current work lies in the further development of the agent anatomy concept, particularly the refined agent classification within the scope of the PoF-based system reliability modeling, new approaches to the learning and the autonomy properties of the intelligent agents, and modeling interacting failure mechanisms within the dynamic engineering system. The autonomous property of intelligent agents is defined as agent's ability to self-activate, deactivate or completely redefine their role in the analysis. This property of agents and the ability to model interacting failure mechanisms of the system elements makes the agent autonomy fundamentally different from all existing methods of probabilistic PoF-based reliability modeling. 1. Azarkhail, M., "Agent Autonomy Approach to Physics-Based Reliability Modeling of Structures and Mechanical Systems", PhD thesis, University of Maryland, College Park, 2007.

Quantitative computational models of molecular self-assembly in systems biology

PubMed Central

Thomas, Marcus; Schwartz, Russell

2017-01-01

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally. PMID:28535149

Quantitative computational models of molecular self-assembly in systems biology.

PubMed

Thomas, Marcus; Schwartz, Russell

2017-05-23

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally.

Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

2011-01-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. 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 NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) 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, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to use of the multi-satellite simulator tqimproy precipitation processes will be discussed.

User's guide to the Reliability Estimation System Testbed (REST)

NASA Technical Reports Server (NTRS)

Nicol, David M.; Palumbo, Daniel L.; Rifkin, Adam

1992-01-01

The Reliability Estimation System Testbed is an X-window based reliability modeling tool that was created to explore the use of the Reliability Modeling Language (RML). RML was defined to support several reliability analysis techniques including modularization, graphical representation, Failure Mode Effects Simulation (FMES), and parallel processing. These techniques are most useful in modeling large systems. Using modularization, an analyst can create reliability models for individual system components. The modules can be tested separately and then combined to compute the total system reliability. Because a one-to-one relationship can be established between system components and the reliability modules, a graphical user interface may be used to describe the system model. RML was designed to permit message passing between modules. This feature enables reliability modeling based on a run time simulation of the system wide effects of a component's failure modes. The use of failure modes effects simulation enhances the analyst's ability to correctly express system behavior when using the modularization approach to reliability modeling. To alleviate the computation bottleneck often found in large reliability models, REST was designed to take advantage of parallel processing on hypercube processors.

Modeling Sustainability: Population, Inequality, Consumption, and Bidirectional Coupling of the Earth and Human Systems

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

Motesharrei, Safa; Rivas, Jorge; Kalnay, Eugenia

Over the last two centuries, the impact of the Human System has grown dramatically, becoming strongly dominant within the Earth System in many different ways. Consumption, inequality, and population have increased extremely fast, especially since about 1950, threatening to overwhelm the many critical functions and ecosystems of the Earth System. Changes in the Earth System, in turn, have important feedback effects on the Human System, with costly and potentially serious consequences. However, current models do not incorporate these critical feedbacks. Here, we argue that in order to understand the dynamics of either system, Earth System Models must be coupled withmore » Human System Models through bidirectional couplings representing the positive, negative, and delayed feedbacks that exist in the real systems. In particular, key Human System variables, such as demographics, inequality, economic growth, and migration, are not coupled with the Earth System but are instead driven by exogenous estimates, such as United Nations population projections.This makes current models likely to miss important feedbacks in the real Earth–Human system, especially those that may result in unexpected or counterintuitive outcomes, and thus requiring different policy interventions from current models. Lastly, the importance and imminence of sustainability challenges, the dominant role of the Human System in the Earth System, and the essential roles the Earth System plays for the Human System, all call for collaboration of natural scientists, social scientists, and engineers in multidisciplinary research and modeling to develop coupled Earth–Human system models for devising effective science-based policies and measures to benefit current and future generations.« less

Modeling Sustainability: Population, Inequality, Consumption, and Bidirectional Coupling of the Earth and Human Systems

NASA Technical Reports Server (NTRS)

Motesharrei, Safa; Rivas, Jorge; Kalnay, Eugenia; Asrar, Ghassem R.; Busalacchi, Antonio J.; Cahalan, Robert F.; Cane, Mark A.; Colwell, Rita R.; Feng, Kuishuang; Franklin, Rachel S.;

Modeling Sustainability: Population, Inequality, Consumption, and Bidirectional Coupling of the Earth and Human Systems

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

Motesharrei, Safa; Rivas, Jorge; Kalnay, Eugenia

Over the last two centuries, the impact of the Human System has grown dramatically, becoming strongly dominant within the Earth System in many different ways. Consumption, inequality, and population have increased extremely fast, especially since about 1950, threatening to overwhelm the many critical functions and ecosystems of the Earth System. Changes in the Earth System, in turn, have important feedback effects on the Human System, with costly and potentially serious consequences. However, current models do not incorporate these critical feedbacks. We argue that in order to understand the dynamics of either system, Earth System Models must be coupled with Humanmore » System Models through bidirectional couplings representing the positive, negative, and delayed feedbacks that exist in the real systems. In particular, key Human System variables, such as demographics, inequality, economic growth, and migration, are not coupled with the Earth System but are instead driven by exogenous estimates, such as United Nations population projections. This makes current models likely to miss important feedbacks in the real Earth–Human system, especially those that may result in unexpected or counterintuitive outcomes, and thus requiring different policy interventions from current models. The importance and imminence of sustainability challenges, the dominant role of the Human System in the Earth System, and the essential roles the Earth System plays for the Human System, all call for collaboration of natural scientists, social scientists, and engineers in multidisciplinary research and modeling to develop coupled Earth–Human system models for devising effective science-based policies and measures to benefit current and future generations.« less

Modeling Sustainability: Population, Inequality, Consumption, and Bidirectional Coupling of the Earth and Human Systems

DOE PAGES

Motesharrei, Safa; Rivas, Jorge; Kalnay, Eugenia; ...

2016-12-11

Over the last two centuries, the impact of the Human System has grown dramatically, becoming strongly dominant within the Earth System in many different ways. Consumption, inequality, and population have increased extremely fast, especially since about 1950, threatening to overwhelm the many critical functions and ecosystems of the Earth System. Changes in the Earth System, in turn, have important feedback effects on the Human System, with costly and potentially serious consequences. However, current models do not incorporate these critical feedbacks. Here, we argue that in order to understand the dynamics of either system, Earth System Models must be coupled withmore » Human System Models through bidirectional couplings representing the positive, negative, and delayed feedbacks that exist in the real systems. In particular, key Human System variables, such as demographics, inequality, economic growth, and migration, are not coupled with the Earth System but are instead driven by exogenous estimates, such as United Nations population projections.This makes current models likely to miss important feedbacks in the real Earth–Human system, especially those that may result in unexpected or counterintuitive outcomes, and thus requiring different policy interventions from current models. Lastly, the importance and imminence of sustainability challenges, the dominant role of the Human System in the Earth System, and the essential roles the Earth System plays for the Human System, all call for collaboration of natural scientists, social scientists, and engineers in multidisciplinary research and modeling to develop coupled Earth–Human system models for devising effective science-based policies and measures to benefit current and future generations.« less

Integrated Workforce Modeling System

NASA Technical Reports Server (NTRS)

Moynihan, Gary P.

2000-01-01

There are several computer-based systems, currently in various phases of development at KSC, which encompass some component, aspect, or function of workforce modeling. These systems may offer redundant capabilities and/or incompatible interfaces. A systems approach to workforce modeling is necessary in order to identify and better address user requirements. This research has consisted of two primary tasks. Task 1 provided an assessment of existing and proposed KSC workforce modeling systems for their functionality and applicability to the workforce planning function. Task 2 resulted in the development of a proof-of-concept design for a systems approach to workforce modeling. The model incorporates critical aspects of workforce planning, including hires, attrition, and employee development.

Lessons Learned from using a Livingstone Model to Diagnose a Main Propulsion System

NASA Technical Reports Server (NTRS)

Sweet, Adam; Bajwa, Anupa

2003-01-01

NASA researchers have demonstrated that qualitative, model-based reasoning can be used for fault detection in a Main Propulsion System (MPS), a complex, continuous system. At the heart of this diagnostic system is Livingstone, a discrete, propositional logic-based inference engine. Livingstone comprises a language for specifying a discrete model of the system and a set of algorithms that use the model to track the system's state. Livingstone uses the model to test assumptions about the state of a component - observations from the system are compared with values predicted by the model. The intent of this paper is to summarize some advantages of Livingstone seen through our modeling experience: for instance, flexibility in modeling, speed and maturity. We also describe some shortcomings we perceived in the implementation of Livingstone, such as modeling continuous dynamics and handling of transients. We list some upcoming enhancements to the next version of Livingstone that may resolve some of the current limitations.

The Earth System Model

NASA Technical Reports Server (NTRS)

Schoeberl, Mark; Rood, Richard B.; Hildebrand, Peter; Raymond, Carol

2003-01-01

The Earth System Model is the natural evolution of current climate models and will be the ultimate embodiment of our geophysical understanding of the planet. These models are constructed from components - atmosphere, ocean, ice, land, chemistry, solid earth, etc. models and merged together through a coupling program which is responsible for the exchange of data from the components. Climate models and future earth system models will have standardized modules, and these standards are now being developed by the ESMF project funded by NASA. The Earth System Model will have a variety of uses beyond climate prediction. The model can be used to build climate data records making it the core of an assimilation system, and it can be used in OSSE experiments to evaluate. The computing and storage requirements for the ESM appear to be daunting. However, the Japanese ES theoretical computing capability is already within 20% of the minimum requirements needed for some 2010 climate model applications. Thus it seems very possible that a focused effort to build an Earth System Model will achieve succcss.

On Using SysML, DoDAF 2.0 and UPDM to Model the Architecture for the NOAA's Joint Polar Satellite System (JPSS) Ground System (GS)

NASA Technical Reports Server (NTRS)

Hayden, Jeffrey L.; Jeffries, Alan

2012-01-01

The JPSS Ground System is a lIexible system of systems responsible for telemetry, tracking & command (TT &C), data acquisition, routing and data processing services for a varied lIeet of satellites to support weather prediction, modeling and climate modeling. To assist in this engineering effort, architecture modeling tools are being employed to translate the former NPOESS baseline to the new JPSS baseline, The paper will focus on the methodology for the system engineering process and the use of these architecture modeling tools within that process, The Department of Defense Architecture Framework version 2,0 (DoDAF 2.0) viewpoints and views that are being used to describe the JPSS GS architecture are discussed. The Unified Profile for DoOAF and MODAF (UPDM) and Systems Modeling Language (SysML), as ' provided by extensions to the MagicDraw UML modeling tool, are used to develop the diagrams and tables that make up the architecture model. The model development process and structure are discussed, examples are shown, and details of handling the complexities of a large System of Systems (SoS), such as the JPSS GS, with an equally complex modeling tool, are described

Mathematical circulatory system model

NASA Technical Reports Server (NTRS)

Lakin, William D. (Inventor); Stevens, Scott A. (Inventor)

2010-01-01

A system and method of modeling a circulatory system including a regulatory mechanism parameter. In one embodiment, a regulatory mechanism parameter in a lumped parameter model is represented as a logistic function. In another embodiment, the circulatory system model includes a compliant vessel, the model having a parameter representing a change in pressure due to contraction of smooth muscles of a wall of the vessel.

Context in Models of Human-Machine Systems

NASA Technical Reports Server (NTRS)

Callantine, Todd J.; Null, Cynthia H. (Technical Monitor)

1998-01-01

All human-machine systems models represent context. This paper proposes a theory of context through which models may be usefully related and integrated for design. The paper presents examples of context representation in various models, describes an application to developing models for the Crew Activity Tracking System (CATS), and advances context as a foundation for integrated design of complex dynamic systems.

Automated reverse engineering of nonlinear dynamical systems

PubMed Central

Bongard, Josh; Lipson, Hod

2007-01-01

Complex nonlinear dynamics arise in many fields of science and engineering, but uncovering the underlying differential equations directly from observations poses a challenging task. The ability to symbolically model complex networked systems is key to understanding them, an open problem in many disciplines. Here we introduce for the first time a method that can automatically generate symbolic equations for a nonlinear coupled dynamical system directly from time series data. This method is applicable to any system that can be described using sets of ordinary nonlinear differential equations, and assumes that the (possibly noisy) time series of all variables are observable. Previous automated symbolic modeling approaches of coupled physical systems produced linear models or required a nonlinear model to be provided manually. The advance presented here is made possible by allowing the method to model each (possibly coupled) variable separately, intelligently perturbing and destabilizing the system to extract its less observable characteristics, and automatically simplifying the equations during modeling. We demonstrate this method on four simulated and two real systems spanning mechanics, ecology, and systems biology. Unlike numerical models, symbolic models have explanatory value, suggesting that automated “reverse engineering” approaches for model-free symbolic nonlinear system identification may play an increasing role in our ability to understand progressively more complex systems in the future. PMID:17553966

Automated reverse engineering of nonlinear dynamical systems.

PubMed

Bongard, Josh; Lipson, Hod

2007-06-12

Complex nonlinear dynamics arise in many fields of science and engineering, but uncovering the underlying differential equations directly from observations poses a challenging task. The ability to symbolically model complex networked systems is key to understanding them, an open problem in many disciplines. Here we introduce for the first time a method that can automatically generate symbolic equations for a nonlinear coupled dynamical system directly from time series data. This method is applicable to any system that can be described using sets of ordinary nonlinear differential equations, and assumes that the (possibly noisy) time series of all variables are observable. Previous automated symbolic modeling approaches of coupled physical systems produced linear models or required a nonlinear model to be provided manually. The advance presented here is made possible by allowing the method to model each (possibly coupled) variable separately, intelligently perturbing and destabilizing the system to extract its less observable characteristics, and automatically simplifying the equations during modeling. We demonstrate this method on four simulated and two real systems spanning mechanics, ecology, and systems biology. Unlike numerical models, symbolic models have explanatory value, suggesting that automated "reverse engineering" approaches for model-free symbolic nonlinear system identification may play an increasing role in our ability to understand progressively more complex systems in the future.

Dynamic characteristics of motor-gear system under load saltations and voltage transients

NASA Astrophysics Data System (ADS)

Bai, Wenyu; Qin, Datong; Wang, Yawen; Lim, Teik C.

2018-02-01

In this paper, a dynamic model of a motor-gear system is proposed. The model combines a nonlinear permeance network model (PNM) of a squirrel-cage induction motor and a coupled lateral-torsional dynamic model of a planetary geared rotor system. The external excitations including voltage transients and load saltations, as well as the internal excitations such as spatial effects, magnetic circuits topology and material nonlinearity in the motor, and time-varying mesh stiffness and damping in the planetary gear system are considered in the proposed model. Then, the simulation results are compared with those predicted by the electromechanical model containing a dynamic motor model with constant inductances. The comparison showed that the electromechanical system model with the PNM motor model yields more reasonable results than the electromechanical system model with the lumped-parameter electric machine. It is observed that electromechanical coupling effect can induce additional and severe gear vibrations. In addition, the external conditions, especially the voltage transients, will dramatically affect the dynamic characteristics of the electromechanical system. Finally, some suggestions are offered based on this analysis for improving the performance and reliability of the electromechanical system.

Model-Based Systems Engineering With the Architecture Analysis and Design Language (AADL) Applied to NASA Mission Operations

NASA Technical Reports Server (NTRS)

Munoz Fernandez, Michela Miche

2014-01-01

The potential of Model Model Systems Engineering (MBSE) using the Architecture Analysis and Design Language (AADL) applied to space systems will be described. AADL modeling is applicable to real-time embedded systems- the types of systems NASA builds. A case study with the Juno mission to Jupiter showcases how this work would enable future missions to benefit from using these models throughout their life cycle from design to flight operations.

Protocol for Reliability Assessment of Structural Health Monitoring Systems Incorporating Model-assisted Probability of Detection (MAPOD) Approach

DTIC Science & Technology

2011-09-01

a quality evaluation with limited data, a model -based assessment must be...that affect system performance, a multistage approach to system validation, a modeling and experimental methodology for efficiently addressing a ...affect system performance, a multistage approach to system validation, a modeling and experimental methodology for efficiently addressing a wide range

Control by model error estimation

NASA Technical Reports Server (NTRS)

Likins, P. W.; Skelton, R. E.

1976-01-01

Modern control theory relies upon the fidelity of the mathematical model of the system. Truncated modes, external disturbances, and parameter errors in linear system models are corrected by augmenting to the original system of equations an 'error system' which is designed to approximate the effects of such model errors. A Chebyshev error system is developed for application to the Large Space Telescope (LST).

The Design and Development of the Dragoon Intelligent Tutoring System for Model Construction: Lessons Learned

ERIC Educational Resources Information Center

Wetzel, Jon; VanLehn, Kurt; Butler, Dillan; Chaudhari, Pradeep; Desai, Avaneesh; Feng, Jingxian; Grover, Sachin; Joiner, Reid; Kong-Sivert, Mackenzie; Patade, Vallabh; Samala, Ritesh; Tiwari, Megha; van de Sande, Brett

2017-01-01

This paper describes Dragoon, a simple intelligent tutoring system which teaches the construction of models of dynamic systems. Modelling is one of seven practices dictated in two new sets of educational standards in the U.S.A., and Dragoon is one of the first systems for teaching model construction for dynamic systems. Dragoon can be classified…

Ontology for Life-Cycle Modeling of Water Distribution Systems: Application of Model View Definition Attributes

DTIC Science & Technology

2013-06-01

ER D C/ CE RL C R- 13 -5 Ontology for Life-Cycle Modeling of Water Distribution Systems : Application of Model View Definition...2013 Ontology for Life-Cycle Modeling of Water Distribution Systems : Application of Model View Definition Attributes Kristine K. Fallon, Robert A...interior plumbing systems and the information exchange requirements for every participant in the design. The findings were used to develop an

Modeling the long-term evolution of space debris

DOEpatents

Nikolaev, Sergei; De Vries, Willem H.; Henderson, John R.; Horsley, Matthew A.; Jiang, Ming; Levatin, Joanne L.; Olivier, Scot S.; Pertica, Alexander J.; Phillion, Donald W.; Springer, Harry K.

2017-03-07

A space object modeling system that models the evolution of space debris is provided. The modeling system simulates interaction of space objects at simulation times throughout a simulation period. The modeling system includes a propagator that calculates the position of each object at each simulation time based on orbital parameters. The modeling system also includes a collision detector that, for each pair of objects at each simulation time, performs a collision analysis. When the distance between objects satisfies a conjunction criterion, the modeling system calculates a local minimum distance between the pair of objects based on a curve fitting to identify a time of closest approach at the simulation times and calculating the position of the objects at the identified time. When the local minimum distance satisfies a collision criterion, the modeling system models the debris created by the collision of the pair of objects.

GEM System: automatic prototyping of cell-wide metabolic pathway models from genomes.

PubMed

Arakawa, Kazuharu; Yamada, Yohei; Shinoda, Kosaku; Nakayama, Yoichi; Tomita, Masaru

2006-03-23

Successful realization of a "systems biology" approach to analyzing cells is a grand challenge for our understanding of life. However, current modeling approaches to cell simulation are labor-intensive, manual affairs, and therefore constitute a major bottleneck in the evolution of computational cell biology. We developed the Genome-based Modeling (GEM) System for the purpose of automatically prototyping simulation models of cell-wide metabolic pathways from genome sequences and other public biological information. Models generated by the GEM System include an entire Escherichia coli metabolism model comprising 968 reactions of 1195 metabolites, achieving 100% coverage when compared with the KEGG database, 92.38% with the EcoCyc database, and 95.06% with iJR904 genome-scale model. The GEM System prototypes qualitative models to reduce the labor-intensive tasks required for systems biology research. Models of over 90 bacterial genomes are available at our web site.

A modeling framework for exposing risks in complex systems.

PubMed

Sharit, J

2000-08-01

This article introduces and develops a modeling framework for exposing risks in the form of human errors and adverse consequences in high-risk systems. The modeling framework is based on two components: a two-dimensional theory of accidents in systems developed by Perrow in 1984, and the concept of multiple system perspectives. The theory of accidents differentiates systems on the basis of two sets of attributes. One set characterizes the degree to which systems are interactively complex; the other emphasizes the extent to which systems are tightly coupled. The concept of multiple perspectives provides alternative descriptions of the entire system that serve to enhance insight into system processes. The usefulness of these two model components derives from a modeling framework that cross-links them, enabling a variety of work contexts to be exposed and understood that would otherwise be very difficult or impossible to identify. The model components and the modeling framework are illustrated in the case of a large and comprehensive trauma care system. In addition to its general utility in the area of risk analysis, this methodology may be valuable in applications of current methods of human and system reliability analysis in complex and continually evolving high-risk systems.

Two models for identification and predicting behaviour of an induction motor system

NASA Astrophysics Data System (ADS)

Kuo, Chien-Hsun

2018-01-01

System identification or modelling is the process of building mathematical models of dynamical systems based on the available input and output data from the systems. This paper introduces system identification by using ARX (Auto Regressive with eXogeneous input) and ARMAX (Auto Regressive Moving Average with eXogeneous input) models. Through the identified system model, the predicted output could be compared with the measured one to help prevent the motor faults from developing into a catastrophic machine failure and avoid unnecessary costs and delays caused by the need to carry out unscheduled repairs. The induction motor system is illustrated as an example. Numerical and experimental results are shown for the identified induction motor system.

Model calibration and issues related to validation, sensitivity analysis, post-audit, uncertainty evaluation and assessment of prediction data needs

USGS Publications Warehouse

Tiedeman, Claire; Hill, Mary C.

2007-01-01

When simulating natural and engineered groundwater flow and transport systems, one objective is to produce a model that accurately represents important aspects of the true system. However, using direct measurements of system characteristics, such as hydraulic conductivity, to construct a model often produces simulated values that poorly match observations of the system state, such as hydraulic heads, flows and concentrations (for example, Barth et al., 2001). This occurs because of inaccuracies in the direct measurements and because the measurements commonly characterize system properties at different scales from that of the model aspect to which they are applied. In these circumstances, the conservation of mass equations represented by flow and transport models can be used to test the applicability of the direct measurements, such as by comparing model simulated values to the system state observations. This comparison leads to calibrating the model, by adjusting the model construction and the system properties as represented by model parameter values, so that the model produces simulated values that reasonably match the observations.

Verification of an analytic modeler for capillary pump loop thermal control systems

NASA Technical Reports Server (NTRS)

Schweickart, R. B.; Neiswanger, L.; Ku, J.

1987-01-01

A number of computer programs have been written to model two-phase heat transfer systems for space use. These programs support the design of thermal control systems and provide a method of predicting their performance in the wide range of thermal environments of space. Predicting the performance of one such system known as the capillary pump loop (CPL) is the intent of the CPL Modeler. By modeling two developed CPL systems and comparing the results with actual test data, the CPL Modeler has proven useful in simulating CPL operation. Results of the modeling effort are discussed, together with plans for refinements to the modeler.

Overcoming limitations of model-based diagnostic reasoning systems

NASA Technical Reports Server (NTRS)

Holtzblatt, Lester J.; Marcotte, Richard A.; Piazza, Richard L.

1989-01-01

The development of a model-based diagnostic system to overcome the limitations of model-based reasoning systems is discussed. It is noted that model-based reasoning techniques can be used to analyze the failure behavior and diagnosability of system and circuit designs as part of the system process itself. One goal of current research is the development of a diagnostic algorithm which can reason efficiently about large numbers of diagnostic suspects and can handle both combinational and sequential circuits. A second goal is to address the model-creation problem by developing an approach for using design models to construct the GMODS model in an automated fashion.

Retrospective revaluation in sequential decision making: a tale of two systems.

PubMed

Gershman, Samuel J; Markman, Arthur B; Otto, A Ross

2014-02-01

Recent computational theories of decision making in humans and animals have portrayed 2 systems locked in a battle for control of behavior. One system--variously termed model-free or habitual--favors actions that have previously led to reward, whereas a second--called the model-based or goal-directed system--favors actions that causally lead to reward according to the agent's internal model of the environment. Some evidence suggests that control can be shifted between these systems using neural or behavioral manipulations, but other evidence suggests that the systems are more intertwined than a competitive account would imply. In 4 behavioral experiments, using a retrospective revaluation design and a cognitive load manipulation, we show that human decisions are more consistent with a cooperative architecture in which the model-free system controls behavior, whereas the model-based system trains the model-free system by replaying and simulating experience.

Understanding earth system models: how Global Sensitivity Analysis can help

NASA Astrophysics Data System (ADS)

Pianosi, Francesca; Wagener, Thorsten

2017-04-01

Computer models are an essential element of earth system sciences, underpinning our understanding of systems functioning and influencing the planning and management of socio-economic-environmental systems. Even when these models represent a relatively low number of physical processes and variables, earth system models can exhibit a complicated behaviour because of the high level of interactions between their simulated variables. As the level of these interactions increases, we quickly lose the ability to anticipate and interpret the model's behaviour and hence the opportunity to check whether the model gives the right response for the right reasons. Moreover, even if internally consistent, an earth system model will always produce uncertain predictions because it is often forced by uncertain inputs (due to measurement errors, pre-processing uncertainties, scarcity of measurements, etc.). Lack of transparency about the scope of validity, limitations and the main sources of uncertainty of earth system models can be a strong limitation to their effective use for both scientific and decision-making purposes. Global Sensitivity Analysis (GSA) is a set of statistical analysis techniques to investigate the complex behaviour of earth system models in a structured, transparent and comprehensive way. In this presentation, we will use a range of examples across earth system sciences (with a focus on hydrology) to demonstrate how GSA is a fundamental element in advancing the construction and use of earth system models, including: verifying the consistency of the model's behaviour with our conceptual understanding of the system functioning; identifying the main sources of output uncertainty so to focus efforts for uncertainty reduction; finding tipping points in forcing inputs that, if crossed, would bring the system to specific conditions we want to avoid.

Enhancing metaproteomics-The value of models and defined environmental microbial systems

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

Herbst, Florian-Alexander; Lünsmann, Vanessa; Kjeldal, Henrik

2016-01-21

Metaproteomics - the large-scale characterization of the entire protein complement of environmental microbiota at a given point in time - added unique features and possibilities to study environmental microbial communities and to unravel these “black boxes”. New technical challenges arose which were not an issue for classical proteome analytics before and choosing the appropriate model system applicable to the research question can be difficult. Here, we reviewed different model systems for metaproteome analysis. Following a short introduction to microbial communities and systems, we discussed the most used systems ranging from technical systems over rhizospheric models to systems for the medicalmore » field. This includes acid mine drainage, anaerobic digesters, activated sludge, planted fixed bed reactors, gastrointestinal simulators and in vivo models. Model systems are useful to evaluate the challenges encountered within (but not limited to) metaproteomics, including species complexity and coverage, biomass availability or reliable protein extraction. The implementation of model systems can be considered as a step forward to better understand microbial responses and ecological distribution of member organisms. In the future, novel improvements are necessary to fully engage complex environmental systems.« less

Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science.

PubMed

Jones, James W; Antle, John M; Basso, Bruno; Boote, Kenneth J; Conant, Richard T; Foster, Ian; Godfray, H Charles J; Herrero, Mario; Howitt, Richard E; Janssen, Sander; Keating, Brian A; Munoz-Carpena, Rafael; Porter, Cheryl H; Rosenzweig, Cynthia; Wheeler, Tim R

2017-07-01

We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and need to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.

Toward a New Generation of Agricultural System Data, Models, and Knowledge Products: State of Agricultural Systems Science

NASA Technical Reports Server (NTRS)

Jones, James W.; Antle, John M.; Basso, Bruno; Boote, Kenneth J.; Conant, Richard T.; Foster, Ian; Godfray, H. Charles J.; Herrero, Mario; Howitt, Richard E.; Janssen, Sander;

Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science

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

Jones, James W.; Antle, John M.; Basso, Bruno

We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and needmore » to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.« less

Modeling Complex Cross-Systems Software Interfaces Using SysML

NASA Technical Reports Server (NTRS)

Mandutianu, Sanda; Morillo, Ron; Simpson, Kim; Liepack, Otfrid; Bonanne, Kevin

2013-01-01

The complex flight and ground systems for NASA human space exploration are designed, built, operated and managed as separate programs and projects. However, each system relies on one or more of the other systems in order to accomplish specific mission objectives, creating a complex, tightly coupled architecture. Thus, there is a fundamental need to understand how each system interacts with the other. To determine if a model-based system engineering approach could be utilized to assist with understanding the complex system interactions, the NASA Engineering and Safety Center (NESC) sponsored a task to develop an approach for performing cross-system behavior modeling. This paper presents the results of applying Model Based Systems Engineering (MBSE) principles using the System Modeling Language (SysML) to define cross-system behaviors and how they map to crosssystem software interfaces documented in system-level Interface Control Documents (ICDs).

Control Activity in Support of NASA Turbine Based Combined Cycle (TBCC) Research

NASA Technical Reports Server (NTRS)

Stueber, Thomas J.; Vrnak, Daniel R.; Le, Dzu K.; Ouzts, Peter J.

2010-01-01

Control research for a Turbine Based Combined Cycle (TBCC) propulsion system is the current focus of the Hypersonic Guidance, Navigation, and Control (GN&C) discipline team. The ongoing work at the NASA Glenn Research Center (GRC) supports the Hypersonic GN&C effort in developing tools to aid the design of control algorithms to manage a TBCC airbreathing propulsion system during a critical operating period. The critical operating period being addressed in this paper is the span when the propulsion system transitions from one cycle to another, referred to as mode transition. One such tool, that is a basic need for control system design activities, is computational models (hereto forth referred to as models) of the propulsion system. The models of interest for designing and testing controllers are Control Development Models (CDMs) and Control Validation Models (CVMs). CDMs and CVMs are needed for each of the following propulsion system elements: inlet, turbine engine, ram/scram dual-mode combustor, and nozzle. This paper presents an overall architecture for a TBCC propulsion system model that includes all of the propulsion system elements. Efforts are under way, focusing on one of the propulsion system elements, to develop CDMs and CVMs for a TBCC propulsion system inlet. The TBCC inlet aerodynamic design being modeled is that of the Combined-Cycle Engine (CCE) Testbed. The CCE Testbed is a large-scale model of an aerodynamic design that was verified in a small-scale screening experiment. The modeling approach includes employing existing state-of-the-art simulation codes, developing new dynamic simulations, and performing system identification experiments on the hardware in the NASA GRC 10 by10-Foot Supersonic Wind Tunnel. The developed CDMs and CVMs will be available for control studies prior to hardware buildup. The system identification experiments on the CCE Testbed will characterize the necessary dynamics to be represented in CDMs for control design. These system identification models will also be the reference models to validate the CDM and CVM models. Validated models will give value to the tools used to develop the models.

Mechanical model development of rolling bearing-rotor systems: A review

NASA Astrophysics Data System (ADS)

Cao, Hongrui; Niu, Linkai; Xi, Songtao; Chen, Xuefeng

2018-03-01

The rolling bearing rotor (RBR) system is the kernel of many rotating machines, which affects the performance of the whole machine. Over the past decades, extensive research work has been carried out to investigate the dynamic behavior of RBR systems. However, to the best of the authors' knowledge, no comprehensive review on RBR modelling has been reported yet. To address this gap in the literature, this paper reviews and critically discusses the current progress of mechanical model development of RBR systems, and identifies future trends for research. Firstly, five kinds of rolling bearing models, i.e., the lumped-parameter model, the quasi-static model, the quasi-dynamic model, the dynamic model, and the finite element (FE) model are summarized. Then, the coupled modelling between bearing models and various rotor models including De Laval/Jeffcott rotor, rigid rotor, transfer matrix method (TMM) models and FE models are presented. Finally, the paper discusses the key challenges of previous works and provides new insights into understanding of RBR systems for their advanced future engineering applications.

Mathematical model comparing of the multi-level economics systems

NASA Astrophysics Data System (ADS)

Brykalov, S. M.; Kryanev, A. V.

2017-12-01

The mathematical model (scheme) of a multi-level comparison of the economic system, characterized by the system of indices, is worked out. In the mathematical model of the multi-level comparison of the economic systems, the indicators of peer review and forecasting of the economic system under consideration can be used. The model can take into account the uncertainty in the estimated values of the parameters or expert estimations. The model uses the multi-criteria approach based on the Pareto solutions.

[Modeling and implementation method for the automatic biochemistry analyzer control system].

PubMed

Wang, Dong; Ge, Wan-cheng; Song, Chun-lin; Wang, Yun-guang

2009-03-01

In this paper the system structure The automatic biochemistry analyzer is a necessary instrument for clinical diagnostics. First of is analyzed. The system problems description and the fundamental principles for dispatch are brought forward. Then this text puts emphasis on the modeling for the automatic biochemistry analyzer control system. The objects model and the communications model are put forward. Finally, the implementation method is designed. It indicates that the system based on the model has good performance.

The (Mathematical) Modeling Process in Biosciences

PubMed Central

Torres, Nestor V.; Santos, Guido

2015-01-01

In this communication, we introduce a general framework and discussion on the role of models and the modeling process in the field of biosciences. The objective is to sum up the common procedures during the formalization and analysis of a biological problem from the perspective of Systems Biology, which approaches the study of biological systems as a whole. We begin by presenting the definitions of (biological) system and model. Particular attention is given to the meaning of mathematical model within the context of biology. Then, we present the process of modeling and analysis of biological systems. Three stages are described in detail: conceptualization of the biological system into a model, mathematical formalization of the previous conceptual model and optimization and system management derived from the analysis of the mathematical model. All along this work the main features and shortcomings of the process are analyzed and a set of rules that could help in the task of modeling any biological system are presented. Special regard is given to the formative requirements and the interdisciplinary nature of this approach. We conclude with some general considerations on the challenges that modeling is posing to current biology. PMID:26734063

An Integrated Qualitative and Quantitative Biochemical Model Learning Framework Using Evolutionary Strategy and Simulated Annealing.

PubMed

Wu, Zujian; Pang, Wei; Coghill, George M

2015-01-01

Both qualitative and quantitative model learning frameworks for biochemical systems have been studied in computational systems biology. In this research, after introducing two forms of pre-defined component patterns to represent biochemical models, we propose an integrative qualitative and quantitative modelling framework for inferring biochemical systems. In the proposed framework, interactions between reactants in the candidate models for a target biochemical system are evolved and eventually identified by the application of a qualitative model learning approach with an evolution strategy. Kinetic rates of the models generated from qualitative model learning are then further optimised by employing a quantitative approach with simulated annealing. Experimental results indicate that our proposed integrative framework is feasible to learn the relationships between biochemical reactants qualitatively and to make the model replicate the behaviours of the target system by optimising the kinetic rates quantitatively. Moreover, potential reactants of a target biochemical system can be discovered by hypothesising complex reactants in the synthetic models. Based on the biochemical models learned from the proposed framework, biologists can further perform experimental study in wet laboratory. In this way, natural biochemical systems can be better understood.

Stirling System Modeling for Space Nuclear Power Systems

NASA Technical Reports Server (NTRS)

Lewandowski, Edward J.; Johnson, Paul K.

2008-01-01

A dynamic model of a high-power Stirling convertor has been developed for space nuclear power systems modeling. The model is based on the Component Test Power Convertor (CTPC), a 12.5-kWe free-piston Stirling convertor. The model includes the fluid heat source, the Stirling convertor, output power, and heat rejection. The Stirling convertor model includes the Stirling cycle thermodynamics, heat flow, mechanical mass-spring damper systems, and the linear alternator. The model was validated against test data. Both nonlinear and linear versions of the model were developed. The linear version algebraically couples two separate linear dynamic models; one model of the Stirling cycle and one model of the thermal system, through the pressure factors. Future possible uses of the Stirling system dynamic model are discussed. A pair of commercially available 1-kWe Stirling convertors is being purchased by NASA Glenn Research Center. The specifications of those convertors may eventually be incorporated into the dynamic model and analysis compared to the convertor test data. Subsequent potential testing could include integrating the convertors into a pumped liquid metal hot-end interface. This test would provide more data for comparison to the dynamic model analysis.

Modelling Root Systems Using Oriented Density Distributions

NASA Astrophysics Data System (ADS)

Dupuy, Lionel X.

2011-09-01

Root architectural models are essential tools to understand how plants access and utilize soil resources during their development. However, root architectural models use complex geometrical descriptions of the root system and this has limitations to model interactions with the soil. This paper presents the development of continuous models based on the concept of oriented density distribution function. The growth of the root system is built as a hierarchical system of partial differential equations (PDEs) that incorporate single root growth parameters such as elongation rate, gravitropism and branching rate which appear explicitly as coefficients of the PDE. Acquisition and transport of nutrients are then modelled by extending Darcy's law to oriented density distribution functions. This framework was applied to build a model of the growth and water uptake of barley root system. This study shows that simplified and computer effective continuous models of the root system development can be constructed. Such models will allow application of root growth models at field scale.

Modeling method of time sequence model based grey system theory and application proceedings

NASA Astrophysics Data System (ADS)

Wei, Xuexia; Luo, Yaling; Zhang, Shiqiang

2015-12-01

This article gives a modeling method of grey system GM(1,1) model based on reusing information and the grey system theory. This method not only extremely enhances the fitting and predicting accuracy of GM(1,1) model, but also maintains the conventional routes' merit of simple computation. By this way, we have given one syphilis trend forecast method based on reusing information and the grey system GM(1,1) model.

Visual prosthesis wireless energy transfer system optimal modeling.

PubMed

Li, Xueping; Yang, Yuan; Gao, Yong

2014-01-16

Wireless energy transfer system is an effective way to solve the visual prosthesis energy supply problems, theoretical modeling of the system is the prerequisite to do optimal energy transfer system design. On the basis of the ideal model of the wireless energy transfer system, according to visual prosthesis application condition, the system modeling is optimized. During the optimal modeling, taking planar spiral coils as the coupling devices between energy transmitter and receiver, the effect of the parasitic capacitance of the transfer coil is considered, and especially the concept of biological capacitance is proposed to consider the influence of biological tissue on the energy transfer efficiency, resulting in the optimal modeling's more accuracy for the actual application. The simulation data of the optimal model in this paper is compared with that of the previous ideal model, the results show that under high frequency condition, the parasitic capacitance of inductance and biological capacitance considered in the optimal model could have great impact on the wireless energy transfer system. The further comparison with the experimental data verifies the validity and accuracy of the optimal model proposed in this paper. The optimal model proposed in this paper has a higher theoretical guiding significance for the wireless energy transfer system's further research, and provide a more precise model reference for solving the power supply problem in visual prosthesis clinical application.

Update on the Department of the Navy Systems Engineering Career Competency Model Acquisition Activities

DTIC Science & Technology

2016-04-30

Model Acquisition Activities Clifford Whitcomb, Systems Engineering Professor, NPS Corina White, Systems Engineering Research Associate, NPS...Engineering Acquisition Activities Karen Holness, Assistant Professor, NPS Update on the Department of the Navy Systems Engineering Career Competency Model ...Career Competency Model Clifford A. Whitcomb—is a Professor in the Systems Engineering Department at the Naval Postgraduate School, in Monterey, CA

Modeling of Water-Breathing Propulsion Systems Utilizing the Aluminum-Seawater Reaction and Solid-Oxide Fuel Cells

DTIC Science & Technology

2011-01-01

ABSTRACT Title of Document: MODELING OF WATER-BREATHING PROPULSION SYSTEMS UTILIZING THE ALUMINUM-SEAWATER REACTION AND SOLID...Hybrid Aluminum Combustor (HAC): a novel underwater power system based on the exothermic reaction of aluminum with seawater. The system is modeled ...using a NASA-developed framework called Numerical Propulsion System Simulation (NPSS) by assembling thermodynamic models developed for each component

The organization of an autonomous learning system

NASA Technical Reports Server (NTRS)

Kanerva, Pentti

1988-01-01

The organization of systems that learn from experience is examined, human beings and animals being prime examples of such systems. How is their information processing organized. They build an internal model of the world and base their actions on the model. The model is dynamic and predictive, and it includes the systems' own actions and their effects. In modeling such systems, a large pattern of features represents a moment of the system's experience. Some of the features are provided by the system's senses, some control the system's motors, and the rest have no immediate external significance. A sequence of such patterns then represents the system's experience over time. By storing such sequences appropriately in memory, the system builds a world model based on experience. In addition to the essential function of memory, fundamental roles are played by a sensory system that makes raw information about the world suitable for memory storage and by a motor system that affects the world. The relation of sensory and motor systems to the memory is discussed, together with how favorable actions can be learned and unfavorable actions can be avoided. Results in classical learning theory are explained in terms of the model, more advanced forms of learning are discussed, and the relevance of the model to the frame problem of robotics is examined.

Mathematical Modeling Of Life-Support Systems

NASA Technical Reports Server (NTRS)

Seshan, Panchalam K.; Ganapathi, Balasubramanian; Jan, Darrell L.; Ferrall, Joseph F.; Rohatgi, Naresh K.

1994-01-01

Generic hierarchical model of life-support system developed to facilitate comparisons of options in design of system. Model represents combinations of interdependent subsystems supporting microbes, plants, fish, and land animals (including humans). Generic model enables rapid configuration of variety of specific life support component models for tradeoff studies culminating in single system design. Enables rapid evaluation of effects of substituting alternate technologies and even entire groups of technologies and subsystems. Used to synthesize and analyze life-support systems ranging from relatively simple, nonregenerative units like aquariums to complex closed-loop systems aboard submarines or spacecraft. Model, called Generic Modular Flow Schematic (GMFS), coded in such chemical-process-simulation languages as Aspen Plus and expressed as three-dimensional spreadsheet.

Application of growing nested Petri nets for modeling robotic systems operating under risk

NASA Astrophysics Data System (ADS)

Sorokin, E. V.; Senkov, A. V.

2017-10-01

The paper studies the peculiarities of modeling robotic systems engaged in mining. Existing modeling mechanisms are considered, which are based on nested Petri nets, and a new formalism of growing Petri nets is presented that allows modeling robotic systems operating under risk. Modeling is provided both for the regular operation mode and for non-standard modes in which individual elements of the system can perform uncharacteristic functions. The example shows growing Petri nets that are used for modeling extraction of flat coal seams by a robotic system consisting of several different-type autonomous robots.

Comparison of Centralized-Manual, Centralized-Computerized, and Decentralized-Computerized Order and Management Information Models for the Turkish Air Force Logistics System.

DTIC Science & Technology

1986-09-01

differentiation between the systems. This study will investigate an appropriate Order Processing and Management Information System (OP&MIS) to link base-level...methodology: 1. Reviewed the current order processing and information model of the TUAF Logistics System. (centralized-manual model) 2. Described the...RDS program’s order processing and information system. (centralized-computerized model) 3. Described the order irocessing and information system of

Benchmark Comparison of Dual- and Quad-Core Processor Linux Clusters with Two Global Climate Modeling Workloads

NASA Technical Reports Server (NTRS)

McGalliard, James

2008-01-01

This viewgraph presentation details the science and systems environments that NASA High End computing program serves. Included is a discussion of the workload that is involved in the processing for the Global Climate Modeling. The Goddard Earth Observing System Model, Version 5 (GEOS-5) is a system of models integrated using the Earth System Modeling Framework (ESMF). The GEOS-5 system was used for the Benchmark tests, and the results of the tests are shown and discussed. Tests were also run for the Cubed Sphere system, results for these test are also shown.

Model Error Budgets

NASA Technical Reports Server (NTRS)

Briggs, Hugh C.

2008-01-01

An error budget is a commonly used tool in design of complex aerospace systems. It represents system performance requirements in terms of allowable errors and flows these down through a hierarchical structure to lower assemblies and components. The requirements may simply be 'allocated' based upon heuristics or experience, or they may be designed through use of physics-based models. This paper presents a basis for developing an error budget for models of the system, as opposed to the system itself. The need for model error budgets arises when system models are a principle design agent as is increasingly more common for poorly testable high performance space systems.

Managing Analysis Models in the Design Process

NASA Technical Reports Server (NTRS)

Briggs, Clark

2006-01-01

Design of large, complex space systems depends on significant model-based support for exploration of the design space. Integrated models predict system performance in mission-relevant terms given design descriptions and multiple physics-based numerical models. Both the design activities and the modeling activities warrant explicit process definitions and active process management to protect the project from excessive risk. Software and systems engineering processes have been formalized and similar formal process activities are under development for design engineering and integrated modeling. JPL is establishing a modeling process to define development and application of such system-level models.

Simulating fail-stop in asynchronous distributed systems

NASA Technical Reports Server (NTRS)

Sabel, Laura; Marzullo, Keith

1994-01-01

The fail-stop failure model appears frequently in the distributed systems literature. However, in an asynchronous distributed system, the fail-stop model cannot be implemented. In particular, it is impossible to reliably detect crash failures in an asynchronous system. In this paper, we show that it is possible to specify and implement a failure model that is indistinguishable from the fail-stop model from the point of view of any process within an asynchronous system. We give necessary conditions for a failure model to be indistinguishable from the fail-stop model, and derive lower bounds on the amount of process replication needed to implement such a failure model. We present a simple one-round protocol for implementing one such failure model, which we call simulated fail-stop.

Zebrafish models for functional and toxicological screening of nanoscale drug delivery systems: promoting preclinical applications

PubMed Central

Lee, Keon Yong; Jang, Gun Hyuk; Byun, Cho Hyun; Jeun, Minhong

2017-01-01

Preclinical screening with animal models is an important initial step in clinical translation of new drug delivery systems. However, establishing efficacy, biodistribution, and biotoxicity of complex, multicomponent systems in small animal models can be expensive and time-consuming. Zebrafish models represent an alternative for preclinical studies for nanoscale drug delivery systems. These models allow easy optical imaging, large sample size, and organ-specific studies, and hence an increasing number of preclinical studies are employing zebrafish models. In this review, we introduce various models and discuss recent studies of nanoscale drug delivery systems in zebrafish models. Also in the end, we proposed a guideline for the preclinical trials to accelerate the progress in this field. PMID:28515222

Zebrafish models for functional and toxicological screening of nanoscale drug delivery systems: promoting preclinical applications.

PubMed

Lee, Keon Yong; Jang, Gun Hyuk; Byun, Cho Hyun; Jeun, Minhong; Searson, Peter C; Lee, Kwan Hyi

2017-06-30

Preclinical screening with animal models is an important initial step in clinical translation of new drug delivery systems. However, establishing efficacy, biodistribution, and biotoxicity of complex, multicomponent systems in small animal models can be expensive and time-consuming. Zebrafish models represent an alternative for preclinical studies for nanoscale drug delivery systems. These models allow easy optical imaging, large sample size, and organ-specific studies, and hence an increasing number of preclinical studies are employing zebrafish models. In this review, we introduce various models and discuss recent studies of nanoscale drug delivery systems in zebrafish models. Also in the end, we proposed a guideline for the preclinical trials to accelerate the progress in this field. © 2017 The Author(s).

Transient Control of Synchronous Machine Active and Reactive Power in Micro-grid Power Systems

NASA Astrophysics Data System (ADS)

Weber, Luke G.

There are two main topics associated with this dissertation. The first is to investigate phase-to-neutral fault current magnitude occurring in generators with multiple zero-sequence current sources. The second is to design, model, and tune a linear control system for operating a micro-grid in the event of a separation from the electric power system. In the former case, detailed generator, AC8B excitation system, and four-wire electric power system models are constructed. Where available, manufacturers data is used to validate the generator and exciter models. A gain-delay with frequency droop control is used to model an internal combustion engine and governor. The four wire system is connected through a transformer impedance to an infinite bus. Phase-to-neutral faults are imposed on the system, and fault magnitudes analyzed against three-phase faults to gauge their severity. In the latter case, a balanced three-phase system is assumed. The model structure from the former case - but using data for a different generator - is incorporated with a model for an energy storage device and a net load model to form a micro-grid. The primary control model for the energy storage device has a high level of detail, as does the energy storage device plant model in describing the LC filter and transformer. A gain-delay battery and inverter model is used at the front end. The net load model is intended to be the difference between renewable energy sources and load within a micro-grid system that has separated from the grid. Given the variability of both renewable generation and load, frequency and voltage stability are not guaranteed. This work is an attempt to model components of a proposed micro-grid system at the University of Wisconsin Milwaukee, and design, model, and tune a linear control system for operation in the event of a separation from the electric power system. The control module is responsible for management of frequency and active power, and voltage and reactive power. The scope of this work is to • develop a mathematical model for a salient pole, 2 damper winding synchronous generator with d axis saturation suitable for transient analysis, • develop a mathematical model for a voltage regulator and excitation system using the IEEE AC8B voltage regulator and excitation system template, • develop mathematical models for an energy storage primary control system, LC filter and transformer suitable for transient analysis, • combine the generator and energy storage models in a micro-grid context, • develop mathematical models for electric system components in the stationary abc frame and rotating dq reference frame, • develop a secondary control network for dispatch of micro-grid assets, • establish micro-grid limits of stable operation for step changes in load and power commands based on simulations of model data assuming net load on the micro-grid, and • use generator and electric system models to assess the generator current magnitude during phase-to-ground faults.

Kinetic models for nitrogen inhibition in ANAMMOX and nitrification process on deammonification system at room temperature.

PubMed

De Prá, Marina C; Kunz, Airton; Bortoli, Marcelo; Scussiato, Lucas A; Coldebella, Arlei; Vanotti, Matias; Soares, Hugo M

2016-02-01

In this study were fitted the best kinetic model for nitrogen removal inhibition by ammonium and/or nitrite in three different nitrogen removal systems operated at 25 °C: a nitrifying system (NF) containing only ammonia oxidizing bacteria (AOB), an ANAMMOX system (AMX) containing only ANAMMOX bacteria, and a deammonification system (DMX) containing both AOB and ANAMMOX bacteria. NF system showed inhibition by ammonium and was best described by Andrews model. The AMX system showed a strong inhibition by nitrite and Edwards model presented a best system representation. For DMX system, the increased substrate concentration (until 1060 mg NH3-N/L) tested was not limiting for the ammonia consumption rate and the Monod model was the best model to describe this process. The AOB and ANAMMOX sludges combined in the DMX system displayed a better activity, substrate affinity and excellent substrate tolerance than in nitrifying and ANAMMOX process. Copyright © 2015 Elsevier Ltd. All rights reserved.

Detailed Modeling of Distillation Technologies for Closed-Loop Water Recovery Systems

NASA Technical Reports Server (NTRS)

Allada, Rama Kumar; Lange, Kevin E.; Anderson, Molly S.

2011-01-01

Detailed chemical process simulations are a useful tool in designing and optimizing complex systems and architectures for human life support. Dynamic and steady-state models of these systems help contrast the interactions of various operating parameters and hardware designs, which become extremely useful in trade-study analyses. NASA?s Exploration Life Support technology development project recently made use of such models to compliment a series of tests on different waste water distillation systems. This paper presents efforts to develop chemical process simulations for three technologies: the Cascade Distillation System (CDS), the Vapor Compression Distillation (VCD) system and the Wiped-Film Rotating Disk (WFRD) using the Aspen Custom Modeler and Aspen Plus process simulation tools. The paper discusses system design, modeling details, and modeling results for each technology and presents some comparisons between the model results and recent test data. Following these initial comparisons, some general conclusions and forward work are discussed.

A discrete control model of PLANT

NASA Technical Reports Server (NTRS)

Mitchell, C. M.

1985-01-01

A model of the PLANT system using the discrete control modeling techniques developed by Miller is described. Discrete control models attempt to represent in a mathematical form how a human operator might decompose a complex system into simpler parts and how the control actions and system configuration are coordinated so that acceptable overall system performance is achieved. Basic questions include knowledge representation, information flow, and decision making in complex systems. The structure of the model is a general hierarchical/heterarchical scheme which structurally accounts for coordination and dynamic focus of attention. Mathematically, the discrete control model is defined in terms of a network of finite state systems. Specifically, the discrete control model accounts for how specific control actions are selected from information about the controlled system, the environment, and the context of the situation. The objective is to provide a plausible and empirically testable accounting and, if possible, explanation of control behavior.

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

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

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

System Dynamics Modeling for Supply Chain Information Sharing

NASA Astrophysics Data System (ADS)

Feng, Yang

In this paper, we try to use the method of system dynamics to model supply chain information sharing. Firstly, we determine the model boundaries, establish system dynamics model of supply chain before information sharing, analyze the model's simulation results under different changed parameters and suggest improvement proposal. Then, we establish system dynamics model of supply chain information sharing and make comparison and analysis on the two model's simulation results, to show the importance of information sharing in supply chain management. We wish that all these simulations would provide scientific supports for enterprise decision-making.

A hierarchical approach to reliability modeling of fault-tolerant systems. M.S. Thesis

NASA Technical Reports Server (NTRS)

Gossman, W. E.

1986-01-01

A methodology for performing fault tolerant system reliability analysis is presented. The method decomposes a system into its subsystems, evaluates vent rates derived from the subsystem's conditional state probability vector and incorporates those results into a hierarchical Markov model of the system. This is done in a manner that addresses failure sequence dependence associated with the system's redundancy management strategy. The method is derived for application to a specific system definition. Results are presented that compare the hierarchical model's unreliability prediction to that of a more complicated tandard Markov model of the system. The results for the example given indicate that the hierarchical method predicts system unreliability to a desirable level of accuracy while achieving significant computational savings relative to component level Markov model of the system.

Generic solar photovoltaic system dynamic simulation model specification

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

Ellis, Abraham; Behnke, Michael Robert; Elliott, Ryan Thomas

This document is intended to serve as a specification for generic solar photovoltaic (PV) system positive-sequence dynamic models to be implemented by software developers and approved by the WECC MVWG for use in bulk system dynamic simulations in accordance with NERC MOD standards. Two specific dynamic models are included in the scope of this document. The first, a Central Station PV System model, is intended to capture the most important dynamic characteristics of large scale (> 10 MW) PV systems with a central Point of Interconnection (POI) at the transmission level. The second, a Distributed PV System model, is intendedmore » to represent an aggregation of smaller, distribution-connected systems that comprise a portion of a composite load that might be modeled at a transmission load bus.« less

The Meteorology-Chemistry Interface Processor (MCIP) for the CMAQ Modeling System: Updates through MCIPv3.4.1

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) modeling system is a state-of-the science regional air quality modeling system. The CMAQ modeling system has been primarily developed by the U.S. Environmental Protection Agency, and it has been publically and freely available for more...

Performance modeling of automated manufacturing systems

NASA Astrophysics Data System (ADS)

Viswanadham, N.; Narahari, Y.

A unified and systematic treatment is presented of modeling methodologies and analysis techniques for performance evaluation of automated manufacturing systems. The book is the first treatment of the mathematical modeling of manufacturing systems. Automated manufacturing systems are surveyed and three principal analytical modeling paradigms are discussed: Markov chains, queues and queueing networks, and Petri nets.

Mathematical and Computational Modeling in Complex Biological Systems

PubMed Central

Li, Wenyang; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology. PMID:28386558

Mathematical and Computational Modeling in Complex Biological Systems.

PubMed

Ji, Zhiwei; Yan, Ke; Li, Wenyang; Hu, Haigen; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology.

Coal conversion systems design and process modeling. Volume 1: Application of MPPR and Aspen computer models

NASA Technical Reports Server (NTRS)

1981-01-01

The development of a coal gasification system design and mass and energy balance simulation program for the TVA and other similar facilities is described. The materials-process-product model (MPPM) and the advanced system for process engineering (ASPEN) computer program were selected from available steady state and dynamic models. The MPPM was selected to serve as the basis for development of system level design model structure because it provided the capability for process block material and energy balance and high-level systems sizing and costing. The ASPEN simulation serves as the basis for assessing detailed component models for the system design modeling program. The ASPEN components were analyzed to identify particular process blocks and data packages (physical properties) which could be extracted and used in the system design modeling program. While ASPEN physical properties calculation routines are capable of generating physical properties required for process simulation, not all required physical property data are available, and must be user-entered.

A Model for Communications Satellite System Architecture Assessment

DTIC Science & Technology

2011-09-01

This is shown in Equation 4. The total system cost includes all development, acquisition, fielding, operations, maintenance and upgrades, and system...protection. A mathematical model was implemented to enable the analysis of communications satellite system architectures based on multiple system... implemented to enable the analysis of communications satellite system architectures based on multiple system attributes. Utilization of the model in

Integrative approaches for modeling regulation and function of the respiratory system.

PubMed

Ben-Tal, Alona; Tawhai, Merryn H

2013-01-01

Mathematical models have been central to understanding the interaction between neural control and breathing. Models of the entire respiratory system-which comprises the lungs and the neural circuitry that controls their ventilation-have been derived using simplifying assumptions to compartmentalize each component of the system and to define the interactions between components. These full system models often rely-through necessity-on empirically derived relationships or parameters, in addition to physiological values. In parallel with the development of whole respiratory system models are mathematical models that focus on furthering a detailed understanding of the neural control network, or of the several functions that contribute to gas exchange within the lung. These models are biophysically based, and rely on physiological parameters. They include single-unit models for a breathing lung or neural circuit, through to spatially distributed models of ventilation and perfusion, or multicircuit models for neural control. The challenge is to bring together these more recent advances in models of neural control with models of lung function, into a full simulation for the respiratory system that builds upon the more detailed models but remains computationally tractable. This requires first understanding the mathematical models that have been developed for the respiratory system at different levels, and which could be used to study how physiological levels of O2 and CO2 in the blood are maintained. Copyright © 2013 Wiley Periodicals, Inc.

System/observer/controller identification toolbox

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Horta, Lucas G.; Phan, Minh

1992-01-01

System Identification is the process of constructing a mathematical model from input and output data for a system under testing, and characterizing the system uncertainties and measurement noises. The mathematical model structure can take various forms depending upon the intended use. The SYSTEM/OBSERVER/CONTROLLER IDENTIFICATION TOOLBOX (SOCIT) is a collection of functions, written in MATLAB language and expressed in M-files, that implements a variety of modern system identification techniques. For an open loop system, the central features of the SOCIT are functions for identification of a system model and its corresponding forward and backward observers directly from input and output data. The system and observers are represented by a discrete model. The identified model and observers may be used for controller design of linear systems as well as identification of modal parameters such as dampings, frequencies, and mode shapes. For a closed-loop system, an observer and its corresponding controller gain directly from input and output data.

A real time Pegasus propulsion system model for VSTOL piloted simulation evaluation

NASA Technical Reports Server (NTRS)

Mihaloew, J. R.; Roth, S. P.; Creekmore, R.

1981-01-01

A real time propulsion system modeling technique suitable for use in man-in-the-loop simulator studies was developd. This technique provides the system accuracy, stability, and transient response required for integrated aircraft and propulsion control system studies. A Pegasus-Harrier propulsion system was selected as a baseline for developing mathematical modeling and simulation techniques for VSTOL. Initially, static and dynamic propulsion system characteristics were modeled in detail to form a nonlinear aerothermodynamic digital computer simulation of a Pegasus engine. From this high fidelity simulation, a real time propulsion model was formulated by applying a piece-wise linear state variable methodology. A hydromechanical and water injection control system was also simulated. The real time dynamic model includes the detail and flexibility required for the evaluation of critical control parameters and propulsion component limits over a limited flight envelope. The model was programmed for interfacing with a Harrier aircraft simulation. Typical propulsion system simulation results are presented.

Modeling joint restoration strategies for interdependent infrastructure systems.

PubMed

Zhang, Chao; Kong, Jingjing; Simonovic, Slobodan P

2018-01-01

Life in the modern world depends on multiple critical services provided by infrastructure systems which are interdependent at multiple levels. To effectively respond to infrastructure failures, this paper proposes a model for developing optimal joint restoration strategy for interdependent infrastructure systems following a disruptive event. First, models for (i) describing structure of interdependent infrastructure system and (ii) their interaction process, are presented. Both models are considering the failure types, infrastructure operating rules and interdependencies among systems. Second, an optimization model for determining an optimal joint restoration strategy at infrastructure component level by minimizing the economic loss from the infrastructure failures, is proposed. The utility of the model is illustrated using a case study of electric-water systems. Results show that a small number of failed infrastructure components can trigger high level failures in interdependent systems; the optimal joint restoration strategy varies with failure occurrence time. The proposed models can help decision makers to understand the mechanisms of infrastructure interactions and search for optimal joint restoration strategy, which can significantly enhance safety of infrastructure systems.

The TEF modeling and analysis approach to advance thermionic space power technology

NASA Astrophysics Data System (ADS)

Marshall, Albert C.

1997-01-01

Thermionics space power systems have been proposed as advanced power sources for future space missions that require electrical power levels significantly above the capabilities of current space power systems. The Defense Special Weapons Agency's (DSWA) Thermionic Evaluation Facility (TEF) is carrying out both experimental and analytical research to advance thermionic space power technology to meet this expected need. A Modeling and Analysis (M&A) project has been created at the TEF to develop analysis tools, evaluate concepts, and guide research. M&A activities are closely linked to the TEF experimental program, providing experiment support and using experimental data to validate models. A planning exercise has been completed for the M&A project, and a strategy for implementation was developed. All M&A activities will build on a framework provided by a system performance model for a baseline Thermionic Fuel Element (TFE) concept. The system model is composed of sub-models for each of the system components and sub-systems. Additional thermionic component options and model improvements will continue to be incorporated in the basic system model during the course of the program. All tasks are organized into four focus areas: 1) system models, 2) thermionic research, 3) alternative concepts, and 4) documentation and integration. The M&A project will provide a solid framework for future thermionic system development.

Applying Service-Oriented Architecture on The Development of Groundwater Modeling Support System

NASA Astrophysics Data System (ADS)

Li, C. Y.; WANG, Y.; Chang, L. C.; Tsai, J. P.; Hsiao, C. T.

2016-12-01

Groundwater simulation has become an essential step on the groundwater resources management and assessment. There are many stand-alone pre- and post-processing software packages to alleviate the model simulation loading, but the stand-alone software do not consider centralized management of data and simulation results neither do they provide network sharing functions. Hence, it is difficult to share and reuse the data and knowledge (simulation cases) systematically within or across companies. Therefore, this study develops a centralized and network based groundwater modeling support system to assist model construction. The system is based on service-oriented architecture and allows remote user to develop their modeling cases on internet. The data and cases (knowledge) are thus easy to manage centralized. MODFLOW is the modeling engine of the system, which is the most popular groundwater model in the world. The system provides a data warehouse to restore groundwater observations, MODFLOW Support Service, MODFLOW Input File & Shapefile Convert Service, MODFLOW Service, and Expert System Service to assist researchers to build models. Since the system architecture is service-oriented, it is scalable and flexible. The system can be easily extended to include the scenarios analysis and knowledge management to facilitate the reuse of groundwater modeling knowledge.

System Dynamics Modeling for Public Health: Background and Opportunities

PubMed Central

Homer, Jack B.; Hirsch, Gary B.

2006-01-01

The systems modeling methodology of system dynamics is well suited to address the dynamic complexity that characterizes many public health issues. The system dynamics approach involves the development of computer simulation models that portray processes of accumulation and feedback and that may be tested systematically to find effective policies for overcoming policy resistance. System dynamics modeling of chronic disease prevention should seek to incorporate all the basic elements of a modern ecological approach, including disease outcomes, health and risk behaviors, environmental factors, and health-related resources and delivery systems. System dynamics shows promise as a means of modeling multiple interacting diseases and risks, the interaction of delivery systems and diseased populations, and matters of national and state policy. PMID:16449591

Parameter and Structure Inference for Nonlinear Dynamical Systems

NASA Technical Reports Server (NTRS)

Morris, Robin D.; Smelyanskiy, Vadim N.; Millonas, Mark

2006-01-01

A great many systems can be modeled in the non-linear dynamical systems framework, as x = f(x) + xi(t), where f() is the potential function for the system, and xi is the excitation noise. Modeling the potential using a set of basis functions, we derive the posterior for the basis coefficients. A more challenging problem is to determine the set of basis functions that are required to model a particular system. We show that using the Bayesian Information Criteria (BIC) to rank models, and the beam search technique, that we can accurately determine the structure of simple non-linear dynamical system models, and the structure of the coupling between non-linear dynamical systems where the individual systems are known. This last case has important ecological applications.

An Information System Development Method Combining Business Process Modeling with Executable Modeling and its Evaluation by Prototyping

NASA Astrophysics Data System (ADS)

Okawa, Tsutomu; Kaminishi, Tsukasa; Hirabayashi, Syuichi; Suzuki, Ryo; Mitsui, Hiroyasu; Koizumi, Hisao

The business in the enterprise is closely related with the information system to such an extent that the business activities are difficult without the information system. The system design technique that considers the business process well, and that enables a quick system development is requested. In addition, the demand for the development cost is also severe than before. To cope with the current situation, the modeling technology named BPM(Business Process Management/Modeling)is drawing attention and becoming important as a key technology. BPM is a technology to model business activities as business processes and visualize them to improve the business efficiency. However, a general methodology to develop the information system using the analysis result of BPM doesn't exist, and a few development cases are reported. This paper proposes an information system development method combining business process modeling with executable modeling. In this paper we describe a guideline to support consistency of development and development efficiency and the framework enabling to develop the information system from model. We have prototyped the information system with the proposed method and our experience has shown that the methodology is valuable.

Simplifying and upscaling water resources systems models that combine natural and engineered components

NASA Astrophysics Data System (ADS)

McIntyre, N.; Keir, G.

2014-12-01

Water supply systems typically encompass components of both natural systems (e.g. catchment runoff, aquifer interception) and engineered systems (e.g. process equipment, water storages and transfers). Many physical processes of varying spatial and temporal scales are contained within these hybrid systems models. The need to aggregate and simplify system components has been recognised for reasons of parsimony and comprehensibility; and the use of probabilistic methods for modelling water-related risks also prompts the need to seek computationally efficient up-scaled conceptualisations. How to manage the up-scaling errors in such hybrid systems models has not been well-explored, compared to research in the hydrological process domain. Particular challenges include the non-linearity introduced by decision thresholds and non-linear relations between water use, water quality, and discharge strategies. Using a case study of a mining region, we explore the nature of up-scaling errors in water use, water quality and discharge, and we illustrate an approach to identification of a scale-adjusted model including an error model. Ways forward for efficient modelling of such complex, hybrid systems are discussed, including interactions with human, energy and carbon systems models.

A Novel Approach to Develop the Lower Order Model of Multi-Input Multi-Output System

NASA Astrophysics Data System (ADS)

Rajalakshmy, P.; Dharmalingam, S.; Jayakumar, J.

2017-10-01

A mathematical model is a virtual entity that uses mathematical language to describe the behavior of a system. Mathematical models are used particularly in the natural sciences and engineering disciplines like physics, biology, and electrical engineering as well as in the social sciences like economics, sociology and political science. Physicists, Engineers, Computer scientists, and Economists use mathematical models most extensively. With the advent of high performance processors and advanced mathematical computations, it is possible to develop high performing simulators for complicated Multi Input Multi Ouptut (MIMO) systems like Quadruple tank systems, Aircrafts, Boilers etc. This paper presents the development of the mathematical model of a 500 MW utility boiler which is a highly complex system. A synergistic combination of operational experience, system identification and lower order modeling philosophy has been effectively used to develop a simplified but accurate model of a circulation system of a utility boiler which is a MIMO system. The results obtained are found to be in good agreement with the physics of the process and with the results obtained through design procedure. The model obtained can be directly used for control system studies and to realize hardware simulators for boiler testing and operator training.

Automated method for the systematic interpretation of resonance peaks in spectrum data

DOEpatents

Damiano, B.; Wood, R.T.

1997-04-22

A method is described for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical model. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system. 1 fig.

The water-energy nexus at water supply and its implications on the integrated water and energy management.

PubMed

Khalkhali, Masoumeh; Westphal, Kirk; Mo, Weiwei

2018-09-15

Water and energy are highly interdependent in the modern world, and hence, it is important to understand their constantly changing and nonlinear interconnections to inform the integrated management of water and energy. In this study, a hydrologic model, a water systems model, and an energy model were developed and integrated into a system dynamics modeling framework. This framework was then applied to a water supply system in the northeast US to capture its water-energy interactions under a set of future population, climate, and system operation scenarios. A hydrologic model was first used to simulate the system's hydrologic inflows and outflows under temperature and precipitation changes on a weekly-basis. A water systems model that combines the hydrologic model and management rules (e.g., water release and transfer) was then developed to dynamically simulate the system's water storage and water head. Outputs from the water systems model were used in the energy model to estimate hydropower generation. It was found that critical water-energy synergies and tradeoffs exist, and there is a possibility for integrated water and energy management to achieve better outcomes. This analysis also shows the importance of a holistic understanding of the systems as a whole, which would allow utility managers to make proactive long-term management decisions. The modeling framework is generalizable to other water supply systems with hydropower generation capacities to inform the integrated management of water and energy resources. Copyright © 2018 Elsevier B.V. All rights reserved.

Identification of propulsion systems

NASA Technical Reports Server (NTRS)

Merrill, Walter; Guo, Ten-Huei; Duyar, Ahmet

1991-01-01

This paper presents a tutorial on the use of model identification techniques for the identification of propulsion system models. These models are important for control design, simulation, parameter estimation, and fault detection. Propulsion system identification is defined in the context of the classical description of identification as a four step process that is unique because of special considerations of data and error sources. Propulsion system models are described along with the dependence of system operation on the environment. Propulsion system simulation approaches are discussed as well as approaches to propulsion system identification with examples for both air breathing and rocket systems.

Use case driven approach to develop simulation model for PCS of APR1400 simulator

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

Dong Wook, Kim; Hong Soo, Kim; Hyeon Tae, Kang

2006-07-01

The full-scope simulator is being developed to evaluate specific design feature and to support the iterative design and validation in the Man-Machine Interface System (MMIS) design of Advanced Power Reactor (APR) 1400. The simulator consists of process model, control logic model, and MMI for the APR1400 as well as the Power Control System (PCS). In this paper, a use case driven approach is proposed to develop a simulation model for PCS. In this approach, a system is considered from the point of view of its users. User's view of the system is based on interactions with the system and themore » resultant responses. In use case driven approach, we initially consider the system as a black box and look at its interactions with the users. From these interactions, use cases of the system are identified. Then the system is modeled using these use cases as functions. Lower levels expand the functionalities of each of these use cases. Hence, starting from the topmost level view of the system, we proceeded down to the lowest level (the internal view of the system). The model of the system thus developed is use case driven. This paper will introduce the functionality of the PCS simulation model, including a requirement analysis based on use case and the validation result of development of PCS model. The PCS simulation model using use case will be first used during the full-scope simulator development for nuclear power plant and will be supplied to Shin-Kori 3 and 4 plant. The use case based simulation model development can be useful for the design and implementation of simulation models. (authors)« less

Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei--Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

2010-01-01

In recent years, exponentially increasing computer power extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 sq km in three-dimensions. 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 NWP and mesoscale models can be run in grid size similar to cloud resolving models through nesting technique. 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, W8F). (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 results from using multi-scale modeling systems to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use the multi-satellite simulator to improve precipitation processes will be discussed.

Using Multi-Scale Modeling Systems to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2010-01-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. 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 NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. 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 results from using multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

Dragon pulse information management system (DPIMS): A unique model-based approach to implementing domain agnostic system of systems and behaviors

NASA Astrophysics Data System (ADS)

Anderson, Thomas S.

2016-05-01

The Global Information Network Architecture is an information technology based on Vector Relational Data Modeling, a unique computational paradigm, DoD network certified by USARMY as the Dragon Pulse Informa- tion Management System. This network available modeling environment for modeling models, where models are configured using domain relevant semantics and use network available systems, sensors, databases and services as loosely coupled component objects and are executable applications. Solutions are based on mission tactics, techniques, and procedures and subject matter input. Three recent ARMY use cases are discussed a) ISR SoS. b) Modeling and simulation behavior validation. c) Networked digital library with behaviors.

Model Based Mission Assurance: Emerging Opportunities for Robotic Systems

NASA Technical Reports Server (NTRS)

Evans, John W.; DiVenti, Tony

2016-01-01

The emergence of Model Based Systems Engineering (MBSE) in a Model Based Engineering framework has created new opportunities to improve effectiveness and efficiencies across the assurance functions. The MBSE environment supports not only system architecture development, but provides for support of Systems Safety, Reliability and Risk Analysis concurrently in the same framework. Linking to detailed design will further improve assurance capabilities to support failures avoidance and mitigation in flight systems. This also is leading new assurance functions including model assurance and management of uncertainty in the modeling environment. Further, the assurance cases, a structured hierarchal argument or model, are emerging as a basis for supporting a comprehensive viewpoint in which to support Model Based Mission Assurance (MBMA).

PRMS-IV, the precipitation-runoff modeling system, version 4

USGS Publications Warehouse

Markstrom, Steven L.; Regan, R. Steve; Hay, Lauren E.; Viger, Roland J.; Webb, Richard M.; Payn, Robert A.; LaFontaine, Jacob H.

2015-01-01

Computer models that simulate the hydrologic cycle at a watershed scale facilitate assessment of variability in climate, biota, geology, and human activities on water availability and flow. This report describes an updated version of the Precipitation-Runoff Modeling System. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of various combinations of climate and land use on streamflow and general watershed hydrology. Several new model components were developed, and all existing components were updated, to enhance performance and supportability. This report describes the history, application, concepts, organization, and mathematical formulation of the Precipitation-Runoff Modeling System and its model components. This updated version provides improvements in (1) system flexibility for integrated science, (2) verification of conservation of water during simulation, (3) methods for spatial distribution of climate boundary conditions, and (4) methods for simulation of soil-water flow and storage.

Cascading Failures in Bi-partite Graphs: Model for Systemic Risk Propagation

PubMed Central

Huang, Xuqing; Vodenska, Irena; Havlin, Shlomo; Stanley, H. Eugene

2013-01-01

As economic entities become increasingly interconnected, a shock in a financial network can provoke significant cascading failures throughout the system. To study the systemic risk of financial systems, we create a bi-partite banking network model composed of banks and bank assets and propose a cascading failure model to describe the risk propagation process during crises. We empirically test the model with 2007 US commercial banks balance sheet data and compare the model prediction of the failed banks with the real failed banks after 2007. We find that our model efficiently identifies a significant portion of the actual failed banks reported by Federal Deposit Insurance Corporation. The results suggest that this model could be useful for systemic risk stress testing for financial systems. The model also identifies that commercial rather than residential real estate assets are major culprits for the failure of over 350 US commercial banks during 2008–2011. PMID:23386974

Modeling acclimatization by hybrid systems: condition changes alter biological system behavior models.

PubMed

Assar, Rodrigo; Montecino, Martín A; Maass, Alejandro; Sherman, David J

2014-07-01

In order to describe the dynamic behavior of a complex biological system, it is useful to combine models integrating processes at different levels and with temporal dependencies. Such combinations are necessary for modeling acclimatization, a phenomenon where changes in environmental conditions can induce drastic changes in the behavior of a biological system. In this article we formalize the use of hybrid systems as a tool to model this kind of biological behavior. A modeling scheme called strong switches is proposed. It allows one to take into account both minor adjustments to the coefficients of a continuous model, and, more interestingly, large-scale changes to the structure of the model. We illustrate the proposed methodology with two applications: acclimatization in wine fermentation kinetics, and acclimatization of osteo-adipo differentiation system linking stimulus signals to bone mass. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Predicting the Overall Spatial Quality of Automotive Audio Systems

NASA Astrophysics Data System (ADS)

Koya, Daisuke

The spatial quality of automotive audio systems is often compromised due to their unideal listening environments. Automotive audio systems need to be developed quickly due to industry demands. A suitable perceptual model could evaluate the spatial quality of automotive audio systems with similar reliability to formal listening tests but take less time. Such a model is developed in this research project by adapting an existing model of spatial quality for automotive audio use. The requirements for the adaptation were investigated in a literature review. A perceptual model called QESTRAL was reviewed, which predicts the overall spatial quality of domestic multichannel audio systems. It was determined that automotive audio systems are likely to be impaired in terms of the spatial attributes that were not considered in developing the QESTRAL model, but metrics are available that might predict these attributes. To establish whether the QESTRAL model in its current form can accurately predict the overall spatial quality of automotive audio systems, MUSHRA listening tests using headphone auralisation with head tracking were conducted to collect results to be compared against predictions by the model. Based on guideline criteria, the model in its current form could not accurately predict the overall spatial quality of automotive audio systems. To improve prediction performance, the QESTRAL model was recalibrated and modified using existing metrics of the model, those that were proposed from the literature review, and newly developed metrics. The most important metrics for predicting the overall spatial quality of automotive audio systems included those that were interaural cross-correlation (IACC) based, relate to localisation of the frontal audio scene, and account for the perceived scene width in front of the listener. Modifying the model for automotive audio systems did not invalidate its use for domestic audio systems. The resulting model predicts the overall spatial quality of 2- and 5-channel automotive audio systems with a cross-validation performance of R. 2 = 0.85 and root-mean-squareerror (RMSE) = 11.03%.

Real-Time Reliability Verification for UAV Flight Control System Supporting Airworthiness Certification.

PubMed

Xu, Haiyang; Wang, Ping

2016-01-01

In order to verify the real-time reliability of unmanned aerial vehicle (UAV) flight control system and comply with the airworthiness certification standard, we proposed a model-based integration framework for modeling and verification of time property. Combining with the advantages of MARTE, this framework uses class diagram to create the static model of software system, and utilizes state chart to create the dynamic model. In term of the defined transformation rules, the MARTE model could be transformed to formal integrated model, and the different part of the model could also be verified by using existing formal tools. For the real-time specifications of software system, we also proposed a generating algorithm for temporal logic formula, which could automatically extract real-time property from time-sensitive live sequence chart (TLSC). Finally, we modeled the simplified flight control system of UAV to check its real-time property. The results showed that the framework could be used to create the system model, as well as precisely analyze and verify the real-time reliability of UAV flight control system.

Real-Time Reliability Verification for UAV Flight Control System Supporting Airworthiness Certification

PubMed Central

Xu, Haiyang; Wang, Ping

2016-01-01

In order to verify the real-time reliability of unmanned aerial vehicle (UAV) flight control system and comply with the airworthiness certification standard, we proposed a model-based integration framework for modeling and verification of time property. Combining with the advantages of MARTE, this framework uses class diagram to create the static model of software system, and utilizes state chart to create the dynamic model. In term of the defined transformation rules, the MARTE model could be transformed to formal integrated model, and the different part of the model could also be verified by using existing formal tools. For the real-time specifications of software system, we also proposed a generating algorithm for temporal logic formula, which could automatically extract real-time property from time-sensitive live sequence chart (TLSC). Finally, we modeled the simplified flight control system of UAV to check its real-time property. The results showed that the framework could be used to create the system model, as well as precisely analyze and verify the real-time reliability of UAV flight control system. PMID:27918594

Dynamic Modeling of Process Technologies for Closed-Loop Water Recovery Systems

NASA Technical Reports Server (NTRS)

Allada, Rama Kumar; Lange, Kevin; Anderson, Molly

2011-01-01

Detailed chemical process simulations are a useful tool in designing and optimizing complex systems and architectures for human life support. Dynamic and steady-state models of these systems help contrast the interactions of various operating parameters and hardware designs, which become extremely useful in trade-study analyses. NASA s Exploration Life Support technology development project recently made use of such models to compliment a series of tests on different waste water distillation systems. This paper presents dynamic simulations of chemical process for primary processor technologies including: the Cascade Distillation System (CDS), the Vapor Compression Distillation (VCD) system, the Wiped-Film Rotating Disk (WFRD), and post-distillation water polishing processes such as the Volatiles Removal Assembly (VRA) that were developed using the Aspen Custom Modeler and Aspen Plus process simulation tools. The results expand upon previous work for water recovery technology models and emphasize dynamic process modeling and results. The paper discusses system design, modeling details, and model results for each technology and presents some comparisons between the model results and available test data. Following these initial comparisons, some general conclusions and forward work are discussed.

Translation from UML to Markov Model: A Performance Modeling Framework

NASA Astrophysics Data System (ADS)

Khan, Razib Hayat; Heegaard, Poul E.

Performance engineering focuses on the quantitative investigation of the behavior of a system during the early phase of the system development life cycle. Bearing this on mind, we delineate a performance modeling framework of the application for communication system that proposes a translation process from high level UML notation to Continuous Time Markov Chain model (CTMC) and solves the model for relevant performance metrics. The framework utilizes UML collaborations, activity diagrams and deployment diagrams to be used for generating performance model for a communication system. The system dynamics will be captured by UML collaboration and activity diagram as reusable specification building blocks, while deployment diagram highlights the components of the system. The collaboration and activity show how reusable building blocks in the form of collaboration can compose together the service components through input and output pin by highlighting the behavior of the components and later a mapping between collaboration and system component identified by deployment diagram will be delineated. Moreover the UML models are annotated to associate performance related quality of service (QoS) information which is necessary for solving the performance model for relevant performance metrics through our proposed framework. The applicability of our proposed performance modeling framework in performance evaluation is delineated in the context of modeling a communication system.

Combustion system CFD modeling at GE Aircraft Engines

NASA Technical Reports Server (NTRS)

Burrus, D.; Mongia, H.; Tolpadi, Anil K.; Correa, S.; Braaten, M.

1995-01-01

This viewgraph presentation discusses key features of current combustion system CFD modeling capabilities at GE Aircraft Engines provided by the CONCERT code; CONCERT development history; modeling applied for designing engine combustion systems; modeling applied to improve fundamental understanding; CONCERT3D results for current production combustors; CONCERT3D model of NASA/GE E3 combustor; HYBRID CONCERT CFD/Monte-Carlo modeling approach; and future modeling directions.

Combustion system CFD modeling at GE Aircraft Engines

NASA Astrophysics Data System (ADS)

Burrus, D.; Mongia, H.; Tolpadi, Anil K.; Correa, S.; Braaten, M.

1995-03-01

This viewgraph presentation discusses key features of current combustion system CFD modeling capabilities at GE Aircraft Engines provided by the CONCERT code; CONCERT development history; modeling applied for designing engine combustion systems; modeling applied to improve fundamental understanding; CONCERT3D results for current production combustors; CONCERT3D model of NASA/GE E3 combustor; HYBRID CONCERT CFD/Monte-Carlo modeling approach; and future modeling directions.

System Behavior Models: A Survey of Approaches

DTIC Science & Technology

2016-06-01

MODELS: A SURVEY OF APPROACHES by Scott R. Ruppel June 2016 Thesis Advisor: Kristin Giammarco Second Reader: John M. Green THIS PAGE...Thesis 4. TITLE AND SUBTITLE SYSTEM BEHAVIOR MODELS: A SURVEY OF APPROACHES 5. FUNDING NUMBERS 6. AUTHOR(S) Scott R. Ruppel 7. PERFORMING...Monterey Phoenix, Petri nets, behavior modeling, model-based systems engineering, modeling approaches, modeling survey 15. NUMBER OF PAGES 85 16

Numerical Modeling of Pressurization of Cryogenic Propellant Tank for Integrated Vehicle Fluid System

NASA Technical Reports Server (NTRS)

Majumdar, Alok K.; LeClair, Andre C.; Hedayat, Ali

2016-01-01

This paper presents a numerical model of pressurization of a cryogenic propellant tank for the Integrated Vehicle Fluid (IVF) system using the Generalized Fluid System Simulation Program (GFSSP). The IVF propulsion system, being developed by United Launch Alliance, uses boiloff propellants to drive thrusters for the reaction control system as well as to run internal combustion engines to develop power and drive compressors to pressurize propellant tanks. NASA Marshall Space Flight Center (MSFC) has been running tests to verify the functioning of the IVF system using a flight tank. GFSSP, a finite volume based flow network analysis software developed at MSFC, has been used to develop an integrated model of the tank and the pressurization system. This paper presents an iterative algorithm for converging the interface boundary conditions between different component models of a large system model. The model results have been compared with test data.

Remaining lifetime modeling using State-of-Health estimation

NASA Astrophysics Data System (ADS)

Beganovic, Nejra; Söffker, Dirk

2017-08-01

Technical systems and system's components undergo gradual degradation over time. Continuous degradation occurred in system is reflected in decreased system's reliability and unavoidably lead to a system failure. Therefore, continuous evaluation of State-of-Health (SoH) is inevitable to provide at least predefined lifetime of the system defined by manufacturer, or even better, to extend the lifetime given by manufacturer. However, precondition for lifetime extension is accurate estimation of SoH as well as the estimation and prediction of Remaining Useful Lifetime (RUL). For this purpose, lifetime models describing the relation between system/component degradation and consumed lifetime have to be established. In this contribution modeling and selection of suitable lifetime models from database based on current SoH conditions are discussed. Main contribution of this paper is the development of new modeling strategies capable to describe complex relations between measurable system variables, related system degradation, and RUL. Two approaches with accompanying advantages and disadvantages are introduced and compared. Both approaches are capable to model stochastic aging processes of a system by simultaneous adaption of RUL models to current SoH. The first approach requires a priori knowledge about aging processes in the system and accurate estimation of SoH. An estimation of SoH here is conditioned by tracking actual accumulated damage into the system, so that particular model parameters are defined according to a priori known assumptions about system's aging. Prediction accuracy in this case is highly dependent on accurate estimation of SoH but includes high number of degrees of freedom. The second approach in this contribution does not require a priori knowledge about system's aging as particular model parameters are defined in accordance to multi-objective optimization procedure. Prediction accuracy of this model does not highly depend on estimated SoH. This model has lower degrees of freedom. Both approaches rely on previously developed lifetime models each of them corresponding to predefined SoH. Concerning first approach, model selection is aided by state-machine-based algorithm. In the second approach, model selection conditioned by tracking an exceedance of predefined thresholds is concerned. The approach is applied to data generated from tribological systems. By calculating Root Squared Error (RSE), Mean Squared Error (MSE), and Absolute Error (ABE) the accuracy of proposed models/approaches is discussed along with related advantages and disadvantages. Verification of the approach is done using cross-fold validation, exchanging training and test data. It can be stated that the newly introduced approach based on data (denoted as data-based or data-driven) parametric models can be easily established providing detailed information about remaining useful/consumed lifetime valid for systems with constant load but stochastically occurred damage.

An architecture for the development of real-time fault diagnosis systems using model-based reasoning

NASA Technical Reports Server (NTRS)

Hall, Gardiner A.; Schuetzle, James; Lavallee, David; Gupta, Uday

1992-01-01

Presented here is an architecture for implementing real-time telemetry based diagnostic systems using model-based reasoning. First, we describe Paragon, a knowledge acquisition tool for offline entry and validation of physical system models. Paragon provides domain experts with a structured editing capability to capture the physical component's structure, behavior, and causal relationships. We next describe the architecture of the run time diagnostic system. The diagnostic system, written entirely in Ada, uses the behavioral model developed offline by Paragon to simulate expected component states as reflected in the telemetry stream. The diagnostic algorithm traces causal relationships contained within the model to isolate system faults. Since the diagnostic process relies exclusively on the behavioral model and is implemented without the use of heuristic rules, it can be used to isolate unpredicted faults in a wide variety of systems. Finally, we discuss the implementation of a prototype system constructed using this technique for diagnosing faults in a science instrument. The prototype demonstrates the use of model-based reasoning to develop maintainable systems with greater diagnostic capabilities at a lower cost.