Soil moisture variability across different scales in an Indian watershed for satellite soil moisture product validation

NASA Astrophysics Data System (ADS)

Singh, Gurjeet; Panda, Rabindra K.; Mohanty, Binayak P.; Jana, Raghavendra B.

2016-05-01

Strategic ground-based sampling of soil moisture across multiple scales is necessary to validate remotely sensed quantities such as NASA's Soil Moisture Active Passive (SMAP) product. In the present study, in-situ soil moisture data were collected at two nested scale extents (0.5 km and 3 km) to understand the trend of soil moisture variability across these scales. This ground-based soil moisture sampling was conducted in the 500 km2 Rana watershed situated in eastern India. The study area is characterized as sub-humid, sub-tropical climate with average annual rainfall of about 1456 mm. Three 3x3 km square grids were sampled intensively once a day at 49 locations each, at a spacing of 0.5 km. These intensive sampling locations were selected on the basis of different topography, soil properties and vegetation characteristics. In addition, measurements were also made at 9 locations around each intensive sampling grid at 3 km spacing to cover a 9x9 km square grid. Intensive fine scale soil moisture sampling as well as coarser scale samplings were made using both impedance probes and gravimetric analyses in the study watershed. The ground-based soil moisture samplings were conducted during the day, concurrent with the SMAP descending overpass. Analysis of soil moisture spatial variability in terms of areal mean soil moisture and the statistics of higher-order moments, i.e., the standard deviation, and the coefficient of variation are presented. Results showed that the standard deviation and coefficient of variation of measured soil moisture decreased with extent scale by increasing mean soil moisture.

The importance of topography controlled sub-grid process heterogeneity in distributed hydrological models

NASA Astrophysics Data System (ADS)

Nijzink, R. C.; Samaniego, L.; Mai, J.; Kumar, R.; Thober, S.; Zink, M.; Schäfer, D.; Savenije, H. H. G.; Hrachowitz, M.

2015-12-01

Heterogeneity of landscape features like terrain, soil, and vegetation properties affect the partitioning of water and energy. However, it remains unclear to which extent an explicit representation of this heterogeneity at the sub-grid scale of distributed hydrological models can improve the hydrological consistency and the robustness of such models. In this study, hydrological process complexity arising from sub-grid topography heterogeneity was incorporated in the distributed mesoscale Hydrologic Model (mHM). Seven study catchments across Europe were used to test whether (1) the incorporation of additional sub-grid variability on the basis of landscape-derived response units improves model internal dynamics, (2) the application of semi-quantitative, expert-knowledge based model constraints reduces model uncertainty; and (3) the combined use of sub-grid response units and model constraints improves the spatial transferability of the model. Unconstrained and constrained versions of both, the original mHM and mHMtopo, which allows for topography-based sub-grid heterogeneity, were calibrated for each catchment individually following a multi-objective calibration strategy. In addition, four of the study catchments were simultaneously calibrated and their feasible parameter sets were transferred to the remaining three receiver catchments. In a post-calibration evaluation procedure the probabilities of model and transferability improvement, when accounting for sub-grid variability and/or applying expert-knowledge based model constraints, were assessed on the basis of a set of hydrological signatures. In terms of the Euclidian distance to the optimal model, used as overall measure for model performance with respect to the individual signatures, the model improvement achieved by introducing sub-grid heterogeneity to mHM in mHMtopo was on average 13 %. The addition of semi-quantitative constraints to mHM and mHMtopo resulted in improvements of 13 and 19 % respectively, compared to the base case of the unconstrained mHM. Most significant improvements in signature representations were, in particular, achieved for low flow statistics. The application of prior semi-quantitative constraints further improved the partitioning between runoff and evaporative fluxes. Besides, it was shown that suitable semi-quantitative prior constraints in combination with the transfer function based regularization approach of mHM, can be beneficial for spatial model transferability as the Euclidian distances for the signatures improved on average by 2 %. The effect of semi-quantitative prior constraints combined with topography-guided sub-grid heterogeneity on transferability showed a more variable picture of improvements and deteriorations, but most improvements were observed for low flow statistics.

The importance of topography-controlled sub-grid process heterogeneity and semi-quantitative prior constraints in distributed hydrological models

NASA Astrophysics Data System (ADS)

Nijzink, Remko C.; Samaniego, Luis; Mai, Juliane; Kumar, Rohini; Thober, Stephan; Zink, Matthias; Schäfer, David; Savenije, Hubert H. G.; Hrachowitz, Markus

2016-03-01

Heterogeneity of landscape features like terrain, soil, and vegetation properties affects the partitioning of water and energy. However, it remains unclear to what extent an explicit representation of this heterogeneity at the sub-grid scale of distributed hydrological models can improve the hydrological consistency and the robustness of such models. In this study, hydrological process complexity arising from sub-grid topography heterogeneity was incorporated into the distributed mesoscale Hydrologic Model (mHM). Seven study catchments across Europe were used to test whether (1) the incorporation of additional sub-grid variability on the basis of landscape-derived response units improves model internal dynamics, (2) the application of semi-quantitative, expert-knowledge-based model constraints reduces model uncertainty, and whether (3) the combined use of sub-grid response units and model constraints improves the spatial transferability of the model. Unconstrained and constrained versions of both the original mHM and mHMtopo, which allows for topography-based sub-grid heterogeneity, were calibrated for each catchment individually following a multi-objective calibration strategy. In addition, four of the study catchments were simultaneously calibrated and their feasible parameter sets were transferred to the remaining three receiver catchments. In a post-calibration evaluation procedure the probabilities of model and transferability improvement, when accounting for sub-grid variability and/or applying expert-knowledge-based model constraints, were assessed on the basis of a set of hydrological signatures. In terms of the Euclidian distance to the optimal model, used as an overall measure of model performance with respect to the individual signatures, the model improvement achieved by introducing sub-grid heterogeneity to mHM in mHMtopo was on average 13 %. The addition of semi-quantitative constraints to mHM and mHMtopo resulted in improvements of 13 and 19 %, respectively, compared to the base case of the unconstrained mHM. Most significant improvements in signature representations were, in particular, achieved for low flow statistics. The application of prior semi-quantitative constraints further improved the partitioning between runoff and evaporative fluxes. In addition, it was shown that suitable semi-quantitative prior constraints in combination with the transfer-function-based regularization approach of mHM can be beneficial for spatial model transferability as the Euclidian distances for the signatures improved on average by 2 %. The effect of semi-quantitative prior constraints combined with topography-guided sub-grid heterogeneity on transferability showed a more variable picture of improvements and deteriorations, but most improvements were observed for low flow statistics.

NCAR global model topography generation software for unstructured grids

NASA Astrophysics Data System (ADS)

Lauritzen, P. H.; Bacmeister, J. T.; Callaghan, P. F.; Taylor, M. A.

2015-06-01

It is the purpose of this paper to document the NCAR global model topography generation software for unstructured grids. Given a model grid, the software computes the fraction of the grid box covered by land, the gridbox mean elevation, and associated sub-grid scale variances commonly used for gravity wave and turbulent mountain stress parameterizations. The software supports regular latitude-longitude grids as well as unstructured grids; e.g. icosahedral, Voronoi, cubed-sphere and variable resolution grids. As an example application and in the spirit of documenting model development, exploratory simulations illustrating the impacts of topographic smoothing with the NCAR-DOE CESM (Community Earth System Model) CAM5.2-SE (Community Atmosphere Model version 5.2 - Spectral Elements dynamical core) are shown.

Uncertainty quantification in LES of channel flow

DOE PAGES

Safta, Cosmin; Blaylock, Myra; Templeton, Jeremy; ...

2016-07-12

Here, in this paper, we present a Bayesian framework for estimating joint densities for large eddy simulation (LES) sub-grid scale model parameters based on canonical forced isotropic turbulence direct numerical simulation (DNS) data. The framework accounts for noise in the independent variables, and we present alternative formulations for accounting for discrepancies between model and data. To generate probability densities for flow characteristics, posterior densities for sub-grid scale model parameters are propagated forward through LES of channel flow and compared with DNS data. Synthesis of the calibration and prediction results demonstrates that model parameters have an explicit filter width dependence andmore » are highly correlated. Discrepancies between DNS and calibrated LES results point to additional model form inadequacies that need to be accounted for.« less

Shallow cumuli ensemble statistics for development of a stochastic parameterization

NASA Astrophysics Data System (ADS)

Sakradzija, Mirjana; Seifert, Axel; Heus, Thijs

2014-05-01

According to a conventional deterministic approach to the parameterization of moist convection in numerical atmospheric models, a given large scale forcing produces an unique response from the unresolved convective processes. This representation leaves out the small-scale variability of convection, as it is known from the empirical studies of deep and shallow convective cloud ensembles, there is a whole distribution of sub-grid states corresponding to the given large scale forcing. Moreover, this distribution gets broader with the increasing model resolution. This behavior is also consistent with our theoretical understanding of a coarse-grained nonlinear system. We propose an approach to represent the variability of the unresolved shallow-convective states, including the dependence of the sub-grid states distribution spread and shape on the model horizontal resolution. Starting from the Gibbs canonical ensemble theory, Craig and Cohen (2006) developed a theory for the fluctuations in a deep convective ensemble. The micro-states of a deep convective cloud ensemble are characterized by the cloud-base mass flux, which, according to the theory, is exponentially distributed (Boltzmann distribution). Following their work, we study the shallow cumulus ensemble statistics and the distribution of the cloud-base mass flux. We employ a Large-Eddy Simulation model (LES) and a cloud tracking algorithm, followed by a conditional sampling of clouds at the cloud base level, to retrieve the information about the individual cloud life cycles and the cloud ensemble as a whole. In the case of shallow cumulus cloud ensemble, the distribution of micro-states is a generalized exponential distribution. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate the shallow convective cloud ensemble and to test the convective ensemble theory. Stochastic model simulates a compound random process, with the number of convective elements drawn from a Poisson distribution, and cloud properties sub-sampled from a generalized ensemble distribution. We study the role of the different cloud subtypes in a shallow convective ensemble and how the diverse cloud properties and cloud lifetimes affect the system macro-state. To what extent does the cloud-base mass flux distribution deviate from the simple Boltzmann distribution and how does it affect the results from the stochastic model? Is the memory, provided by the finite lifetime of individual clouds, of importance for the ensemble statistics? We also test for the minimal information given as an input to the stochastic model, able to reproduce the ensemble mean statistics and the variability in a convective ensemble. An important property of the resulting distribution of the sub-grid convective states is its scale-adaptivity - the smaller the grid-size, the broader the compound distribution of the sub-grid states.

Scaling between reanalyses and high-resolution land-surface modelling in mountainous areas - enabling better application and testing of reanalyses in heterogeneous environments

NASA Astrophysics Data System (ADS)

Gruber, S.; Fiddes, J.

2013-12-01

In mountainous topography, the difference in scale between atmospheric reanalyses (typically tens of kilometres) and relevant processes and phenomena near the Earth surface, such as permafrost or snow cover (meters to tens of meters) is most obvious. This contrast of scales is one of the major obstacles to using reanalysis data for the simulation of surface phenomena and to confronting reanalyses with independent observation. At the example of modelling permafrost in mountain areas (but simple to generalise to other phenomena and heterogeneous environments), we present and test methods against measurements for (A) scaling atmospheric data from the reanalysis to the ground level and (B) smart sampling of the heterogeneous landscape in order to set up a lumped model simulation that represents the high-resolution land surface. TopoSCALE (Part A, see http://dx.doi.org/10.5194/gmdd-6-3381-2013) is a scheme, which scales coarse-grid climate fields to fine-grid topography using pressure level data. In addition, it applies necessary topographic corrections e.g. those variables required for computation of radiation fields. This provides the necessary driving fields to the LSM. Tested against independent ground data, this scheme has been shown to improve the scaling and distribution of meteorological parameters in complex terrain, as compared to conventional methods, e.g. lapse rate based approaches. TopoSUB (Part B, see http://dx.doi.org/10.5194/gmd-5-1245-2012) is a surface pre-processor designed to sample a fine-grid domain (defined by a digital elevation model) along important topographical (or other) dimensions through a clustering scheme. This allows constructing a lumped model representing the main sources of fine-grid variability and applying a 1D LSM efficiently over large areas. Results can processed to derive (i) summary statistics at coarse-scale re-analysis grid resolution, (ii) high-resolution data fields spatialized to e.g., the fine-scale digital elevation model grid, or (iii) validation products for locations at which measurements exist, only. The ability of TopoSUB to approximate results simulated by a 2D distributed numerical LSM at a factor of ~10,000 less computations is demonstrated by comparison of 2D and lumped simulations. Successful application of the combined scheme in the European Alps is reported and based on its results, open issues for future research are outlined.

Horizontal Residual Mean Circulation: Evaluation of Spatial Correlations in Coarse Resolution Ocean Models

NASA Astrophysics Data System (ADS)

Li, Y.; McDougall, T. J.

2016-02-01

Coarse resolution ocean models lack knowledge of spatial correlations between variables on scales smaller than the grid scale. Some researchers have shown that these spatial correlations play a role in the poleward heat flux. In order to evaluate the poleward transport induced by the spatial correlations at a fixed horizontal position, an equation is obtained to calculate the approximate transport from velocity gradients. The equation involves two terms that can be added to the quasi-Stokes streamfunction (based on temporal correlations) to incorporate the contribution of spatial correlations. Moreover, these new terms do not need to be parameterized and is ready to be evaluated by using model data directly. In this study, data from a high resolution ocean model have been used to estimate the accuracy of this HRM approach for improving the horizontal property fluxes in coarse-resolution ocean models. A coarse grid is formed by sub-sampling and box-car averaging the fine grid scale. The transport calculated on the coarse grid is then compared to the transport on original high resolution grid scale accumulated over a corresponding number of grid boxes. The preliminary results have shown that the estimate on coarse resolution grids roughly match the corresponding transports on high resolution grids.

Numerical Simulation of The Mediterranean Sea Using Diecast: Interaction Between Basin, Sub-basin and Local Scale Features and Natural Variability.

NASA Astrophysics Data System (ADS)

Fernández, V.; Dietrich, D. E.; Haney, R. L.; Tintoré, J.

In situ and satellite data obtained during the last ten years have shown that the circula- tion in the Mediterranean Sea is extremely complex in space, with significant features ranging from mesoscale to sub-basin and basin scale, and highly variable in time, with mesoscale to seasonal and interannual signals. Also, the steep bottom topography and the variable atmospheric conditions from one sub-basin to another, make the circula- tion to be composed of numerous energetic and narrow coastal currents, density fronts and mesoscale structures that interact at sub-basin scale with the large scale circula- tion. To simulate numerically and better understand these features, besides high grid resolution, a low numerical dispersion and low physical dissipation ocean model is required. We present the results from a 1/8z horizontal resolution numerical simula- tion of the Mediterranean Sea using DieCAST ocean model, which meets the above requirements since it is stable with low general dissipation and uses accurate fourth- order-accurate approximations with low numerical dispersion. The simulations are carried out with climatological surface forcing using monthly mean winds and relax- ation towards climatological values of temperature and salinity. The model reproduces the main features of the large basin scale circulation, as well as the seasonal variabil- ity of sub-basin scale currents that are well documented by observations in straits and channels. In addition, DieCAST brings out natural fronts and eddies that usually do not appear in numerical simulations of the Mediterranean and that lead to a natural interannual variability. The role of this intrinsic variability in the general circulation will be discussed.

Horizontal Variability of Water and Its Relationship to Cloud Fraction near the Tropical Tropopause: Using Aircraft Observations of Water Vapor to Improve the Representation of Grid-scale Cloud Formation in GEOS-5

NASA Technical Reports Server (NTRS)

Selkirk, Henry B.; Molod, Andrea M.

2014-01-01

Large-scale models such as GEOS-5 typically calculate grid-scale fractional cloudiness through a PDF parameterization of the sub-gridscale distribution of specific humidity. The GEOS-5 moisture routine uses a simple rectangular PDF varying in height that follows a tanh profile. While below 10 km this profile is informed by moisture information from the AIRS instrument, there is relatively little empirical basis for the profile above that level. ATTREX provides an opportunity to refine the profile using estimates of the horizontal variability of measurements of water vapor, total water and ice particles from the Global Hawk aircraft at or near the tropopause. These measurements will be compared with estimates of large-scale cloud fraction from CALIPSO and lidar retrievals from the CPL on the aircraft. We will use the variability measurements to perform studies of the sensitivity of the GEOS-5 cloud-fraction to various modifications to the PDF shape and to its vertical profile.

Downscaling scheme to drive soil-vegetation-atmosphere transfer models

NASA Astrophysics Data System (ADS)

Schomburg, Annika; Venema, Victor; Lindau, Ralf; Ament, Felix; Simmer, Clemens

2010-05-01

The earth's surface is characterized by heterogeneity at a broad range of scales. Weather forecast models and climate models are not able to resolve this heterogeneity at the smaller scales. Many processes in the soil or at the surface, however, are highly nonlinear. This holds, for example, for evaporation processes, where stomata or aerodynamic resistances are nonlinear functions of the local micro-climate. Other examples are threshold dependent processes, e.g., the generation of runoff or the melting of snow. It has been shown that using averaged parameters in the computation of these processes leads to errors and especially biases, due to the involved nonlinearities. Thus it is necessary to account for the sub-grid scale surface heterogeneities in atmospheric modeling. One approach to take the variability of the earth's surface into account is the mosaic approach. Here the soil-vegetation-atmosphere transfer (SVAT) model is run on an explicit higher resolution than the atmospheric part of a coupled model, which is feasible due to generally lower computational costs of a SVAT model compared to the atmospheric part. The question arises how to deal with the scale differences at the interface between the two resolutions. Usually the assumption of a homogeneous forcing for all sub-pixels is made. However, over a heterogeneous surface, usually the boundary layer is also heterogeneous. Thus, by assuming a constant atmospheric forcing again biases in the turbulent heat fluxes may occur due to neglected atmospheric forcing variability. Therefore we have developed and tested a downscaling scheme to disaggregate the atmospheric variables of the lower atmosphere that are used as input to force a SVAT model. Our downscaling scheme consists of three steps: 1) a bi-quadratic spline interpolation of the coarse-resolution field; 2) a "deterministic" part, where relationships between surface and near-surface variables are exploited; and 3) a noise-generation step, in which the still missing, not explained, variance is added as noise. The scheme has been developed and tested based on high-resolution (400 m) model output of the weather forecast (and regional climate) COSMO model. Downscaling steps 1 and 2 reduce the error made by the homogeneous assumption considerably, whereas the third step leads to close agreement of the sub-grid scale variance with the reference. This is, however, achieved at the cost of higher root mean square errors. Thus, before applying the downscaling system to atmospheric data a decision should be made whether the lowest possible errors (apply only downscaling step 1 and 2) or a most realistic sub-grid scale variability (apply also step 3) is desired. This downscaling scheme is currently being implemented into the COSMO model, where it will be used in combination with the mosaic approach. However, this downscaling scheme can also be applied to drive stand-alone SVAT models or hydrological models, which usually also need high-resolution atmospheric forcing data.

Spatiotemporal Variability of Turbulence Kinetic Energy Budgets in the Convective Boundary Layer over Both Simple and Complex Terrain

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

Rai, Raj K.; Berg, Larry K.; Pekour, Mikhail

The assumption of sub-grid scale (SGS) horizontal homogeneity within a model grid cell, which forms the basis of SGS turbulence closures used by mesoscale models, becomes increasingly tenuous as grid spacing is reduced to a few kilometers or less, such as in many emerging high-resolution applications. Herein, we use the turbulence kinetic energy (TKE) budget equation to study the spatio-temporal variability in two types of terrain—complex (Columbia Basin Wind Energy Study [CBWES] site, north-eastern Oregon) and flat (ScaledWind Farm Technologies [SWiFT] site, west Texas) using the Weather Research and Forecasting (WRF) model. In each case six-nested domains (three domains eachmore » for mesoscale and large-eddy simulation [LES]) are used to downscale the horizontal grid spacing from 10 km to 10 m using the WRF model framework. The model output was used to calculate the values of the TKE budget terms in vertical and horizontal planes as well as the averages of grid cells contained in the four quadrants (a quarter area) of the LES domain. The budget terms calculated along the planes and the mean profile of budget terms show larger spatial variability at CBWES site than at the SWiFT site. The contribution of the horizontal derivative of the shear production term to the total production shear was found to be 45% and 15% of the total shear, at the CBWES and SWiFT sites, respectively, indicating that the horizontal derivatives applied in the budget equation should not be ignored in mesoscale model parameterizations, especially for cases with complex terrain with <10 km scale.« less

Improving sub-grid scale accuracy of boundary features in regional finite-difference models

USGS Publications Warehouse

Panday, Sorab; Langevin, Christian D.

2012-01-01

As an alternative to grid refinement, the concept of a ghost node, which was developed for nested grid applications, has been extended towards improving sub-grid scale accuracy of flow to conduits, wells, rivers or other boundary features that interact with a finite-difference groundwater flow model. The formulation is presented for correcting the regular finite-difference groundwater flow equations for confined and unconfined cases, with or without Newton Raphson linearization of the nonlinearities, to include the Ghost Node Correction (GNC) for location displacement. The correction may be applied on the right-hand side vector for a symmetric finite-difference Picard implementation, or on the left-hand side matrix for an implicit but asymmetric implementation. The finite-difference matrix connectivity structure may be maintained for an implicit implementation by only selecting contributing nodes that are a part of the finite-difference connectivity. Proof of concept example problems are provided to demonstrate the improved accuracy that may be achieved through sub-grid scale corrections using the GNC schemes.

A new Downscaling Approach for SMAP, SMOS and ASCAT by predicting sub-grid Soil Moisture Variability based on Soil Texture

NASA Astrophysics Data System (ADS)

Montzka, C.; Rötzer, K.; Bogena, H. R.; Vereecken, H.

2017-12-01

Improving the coarse spatial resolution of global soil moisture products from SMOS, SMAP and ASCAT is currently an up-to-date topic. Soil texture heterogeneity is known to be one of the main sources of soil moisture spatial variability. A method has been developed that predicts the soil moisture standard deviation as a function of the mean soil moisture based on soil texture information. It is a closed-form expression using stochastic analysis of 1D unsaturated gravitational flow in an infinitely long vertical profile based on the Mualem-van Genuchten model and first-order Taylor expansions. With the recent development of high resolution maps of basic soil properties such as soil texture and bulk density, relevant information to estimate soil moisture variability within a satellite product grid cell is available. Here, we predict for each SMOS, SMAP and ASCAT grid cell the sub-grid soil moisture variability based on the SoilGrids1km data set. We provide a look-up table that indicates the soil moisture standard deviation for any given soil moisture mean. The resulting data set provides important information for downscaling coarse soil moisture observations of the SMOS, SMAP and ASCAT missions. Downscaling SMAP data by a field capacity proxy indicates adequate accuracy of the sub-grid soil moisture patterns.

How well do the GCMs replicate the historical precipitation variability in the Colorado River Basin?

NASA Astrophysics Data System (ADS)

Guentchev, G.; Barsugli, J. J.; Eischeid, J.; Raff, D. A.; Brekke, L.

2009-12-01

Observed precipitation variability measures are compared to measures obtained using the World Climate Research Programme (WCRP) Coupled Model Intercomparison Project (CMIP3) General Circulation Models (GCM) data from 36 model projections downscaled by Brekke at al. (2007) and 30 model projections downscaled by Jon Eischeid. Three groups of variability measures are considered in this historical period (1951-1999) comparison: a) basic variability measures, such as standard deviation, interdecadal standard deviation; b) exceedance probability values, i.e., 10% (extreme wet years) and 90% (extreme dry years) exceedance probability values of series of n-year running mean annual amounts, where n=1,12; 10% exceedance probability values of annual maximum monthly precipitation (extreme wet months); and c) runs variability measures, e.g., frequency of negative and positive runs of annual precipitation amounts, total number of the negative and positive runs. Two gridded precipitation data sets produced from observations are used: the Maurer et al. (2002) and the Daly et al. (1994) Precipitation Regression on Independent Slopes Method (PRISM) data sets. The data consist of monthly grid-point precipitation averaged on a United States Geological Survey (USGS) hydrological sub-region scale. The statistical significance of the obtained model minus observed measure differences is assessed using a block bootstrapping approach. The analyses were performed on annual, seasonal and monthly scale. The results indicate that the interdecadal standard deviation is underestimated, in general, on all time scales by the downscaled model data. The differences are statistically significant at a 0.05 significance level for several Lower Colorado Basin sub-regions on annual and seasonal scale, and for several sub-regions located mostly in the Upper Colorado River Basin for the months of March, June, July and November. Although the models simulate drier extreme wet years, wetter extreme dry years and drier extreme wet months for the Upper Colorado basin, the differences are mostly not-significant. Exceptions are the results about the extreme wet years for n=3 for sub-region White-Yampa, for n=6, 7, and 8 for sub-region Upper Colorado-Dolores, and about the extreme dry years for n=11 for sub-region Great Divide-Upper Green. None of the results for the sub-regions in the Lower Colorado Basin were significant. For most of the Upper Colorado sub-regions the models simulate significantly lower frequency of negative and positive 4-6 year runs, while for several sub-regions a significantly higher frequency of 2-year negative runs is evident in the model versus the Maurer data comparisons. The model projections versus the PRISM data comparison reveals similar results for the negative runs, while for the positive runs the results indicate that the models simulate higher frequency of the 2-6 year runs. The results for the Lower Colorado basin sub-regions are similar, in general, to these for the Upper Colorado sub-regions. The differences between the simulated and the observed total number of negative or positive runs were not significant for almost all of the sub-regions within the Colorado River Basin.

Biological and physical controls on O2/Ar, Ar and pCO2 variability at the Western Antarctic Peninsula and in the Drake Passage

NASA Astrophysics Data System (ADS)

Eveleth, R.; Cassar, N.; Doney, S. C.; Munro, D. R.; Sweeney, C.

2017-05-01

Using simultaneous sub-kilometer resolution underway measurements of surface O2/Ar, total O2 and pCO2 from annual austral summer surveys in 2012, 2013 and 2014, we explore the impacts of biological and physical processes on the O2 and pCO2 system spatial and interannual variability at the Western Antarctic Peninsula (WAP). In the WAP, mean O2/Ar supersaturation was (7.6±9.1)% and mean pCO2 supersaturation was (-28±22)%. We see substantial spatial variability in O2 and pCO2 including sub-mesoscale/mesoscale variability with decorrelation length scales of 4.5 km, consistent with the regional Rossby radius. This variability is embedded within onshore-offshore gradients. O2 in the LTER grid region is driven primarily by biological processes as seen by the median ratio of the magnitude of biological oxygen (O2/Ar) to physical oxygen (Ar) supersaturation anomalies (%) relative to atmospheric equilibrium (2.6), however physical processes have a more pronounced influence in the southern onshore region of the grid where we see active sea-ice melting. Total O2 measurements should be interpreted with caution in regions of significant sea-ice formation and melt and glacial meltwater input. pCO2 undersaturation predominantly reflects biological processes in the LTER grid. In contrast we compare these results to the Drake Passage where gas supersaturations vary by smaller magnitudes and decorrelate at length scales of 12 km, in line with latitudinal changes in the regional Rossby radius. Here biological processes induce smaller O2/Ar supersaturations (mean (0.14±1.3)%) and pCO2 undersaturations (mean (-2.8±3.9)%) than in the WAP, and pressure changes, bubble and gas exchange fluxes drive stable Ar supersaturations.

Insights into the physico-chemical evolution of pyrogenic organic carbon emissions from biomass burning using coupled Lagrangian-Eulerian simulations

NASA Astrophysics Data System (ADS)

Suciu, L. G.; Griffin, R. J.; Masiello, C. A.

2017-12-01

Wildfires and prescribed burning are important sources of particulate and gaseous pyrogenic organic carbon (PyOC) emissions to the atmosphere. These emissions impact atmospheric chemistry, air quality and climate, but the spatial and temporal variabilities of these impacts are poorly understood, primarily because small and fresh fire plumes are not well predicted by three-dimensional Eulerian chemical transport models due to their coarser grid size. Generally, this results in underestimation of downwind deposition of PyOC, hydroxyl radical reactivity, secondary organic aerosol formation and ozone (O3) production. However, such models are very good for simulation of multiple atmospheric processes that could affect the lifetimes of PyOC emissions over large spatiotemporal scales. Finer resolution models, such as Lagrangian reactive plumes models (or plume-in-grid), could be used to trace fresh emissions at the sub-grid level of the Eulerian model. Moreover, Lagrangian plume models need background chemistry predicted by the Eulerian models to accurately simulate the interactions of the plume material with the background air during plume aging. Therefore, by coupling the two models, the physico-chemical evolution of the biomass burning plumes can be tracked from local to regional scales. In this study, we focus on the physico-chemical changes of PyOC emissions from sub-grid to grid levels using an existing chemical mechanism. We hypothesize that finer scale Lagrangian-Eulerian simulations of several prescribed burns in the U.S. will allow more accurate downwind predictions (validated by airborne observations from smoke plumes) of PyOC emissions (i.e., submicron particulate matter, organic aerosols, refractory black carbon) as well as O3 and other trace gases. Simulation results could be used to optimize the implementation of additional PyOC speciation in the existing chemical mechanism.

Fast Grid Frequency Support from Distributed Inverter-Based Resources

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

Hoke, Anderson F

This presentation summarizes power hardware-in-the-loop testing performed to evaluate the ability of distributed inverter-coupled generation to support grid frequency on the fastest time scales. The research found that distributed PV inverters and other DERs can effectively support the grid on sub-second time scales.

Predictive Model for Particle Residence Time Distributions in Riser Reactors. Part 1: Model Development and Validation

DOE PAGES

Foust, Thomas D.; Ziegler, Jack L.; Pannala, Sreekanth; ...

2017-02-28

Here in this computational study, we model the mixing of biomass pyrolysis vapor with solid catalyst in circulating riser reactors with a focus on the determination of solid catalyst residence time distributions (RTDs). A comprehensive set of 2D and 3D simulations were conducted for a pilot-scale riser using the Eulerian-Eulerian two-fluid modeling framework with and without sub-grid-scale models for the gas-solids interaction. A validation test case was also simulated and compared to experiments, showing agreement in the pressure gradient and RTD mean and spread. For simulation cases, it was found that for accurate RTD prediction, the Johnson and Jackson partialmore » slip solids boundary condition was required for all models and a sub-grid model is useful so that ultra high resolutions grids that are very computationally intensive are not required. Finally, we discovered a 2/3 scaling relation for the RTD mean and spread when comparing resolved 2D simulations to validated unresolved 3D sub-grid-scale model simulations.« less

Multi-dimensional upwinding-based implicit LES for the vorticity transport equations

NASA Astrophysics Data System (ADS)

Foti, Daniel; Duraisamy, Karthik

2017-11-01

Complex turbulent flows such as rotorcraft and wind turbine wakes are characterized by the presence of strong coherent structures that can be compactly described by vorticity variables. The vorticity-velocity formulation of the incompressible Navier-Stokes equations is employed to increase numerical efficiency. Compared to the traditional velocity-pressure formulation, high order numerical methods and sub-grid scale models for the vorticity transport equation (VTE) have not been fully investigated. Consistent treatment of the convection and stretching terms also needs to be addressed. Our belief is that, by carefully designing sharp gradient-capturing numerical schemes, coherent structures can be more efficiently captured using the vorticity-velocity formulation. In this work, a multidimensional upwind approach for the VTE is developed using the generalized Riemann problem-based scheme devised by Parish et al. (Computers & Fluids, 2016). The algorithm obtains high resolution by augmenting the upwind fluxes with transverse and normal direction corrections. The approach is investigated with several canonical vortex-dominated flows including isolated and interacting vortices and turbulent flows. The capability of the technique to represent sub-grid scale effects is also assessed. Navy contract titled ``Turbulence Modelling Across Disparate Length Scales for Naval Computational Fluid Dynamics Applications,'' through Continuum Dynamics, Inc.

Experimental and LES investigation of premixed methane/air flame propagating in a tube with a thin obstacle

NASA Astrophysics Data System (ADS)

Chen, Peng; Guo, Shilong; Li, Yanchao; Zhang, Yutao

2017-03-01

In this paper, an experimental and numerical investigation of premixed methane/air flame dynamics in a closed combustion vessel with a thin obstacle is described. In the experiment, high-speed video photography and a pressure transducer are used to study the flame shape changes and pressure dynamics. In the numerical simulation, four sub-grid scale viscosity models and three sub-grid scale combustion models are evaluated for their individual prediction compared with the experimental data. High-speed photographs show that the flame propagation process can be divided into five stages: spherical flame, finger-shaped flame, jet flame, mushroom-shaped flame and bidirectional propagation flame. Compared with the other sub-grid scale viscosity models and sub-grid scale combustion models, the dynamic Smagorinsky-Lilly model and the power-law flame wrinkling model are better able to predict the flame behaviour, respectively. Thus, coupling the dynamic Smagorinsky-Lilly model and the power-law flame wrinkling model, the numerical results demonstrate that flame shape change is a purely hydrodynamic phenomenon, and the mushroom-shaped flame and bidirectional propagation flame are the result of flame-vortex interaction. In addition, the transition from "corrugated flamelets" to "thin reaction zones" is observed in the simulation.

Impact of Sub-grid Soil Textural Properties on Simulations of Hydrological Fluxes at the Continental Scale Mississippi River Basin

NASA Astrophysics Data System (ADS)

Kumar, R.; Samaniego, L. E.; Livneh, B.

2013-12-01

Knowledge of soil hydraulic properties such as porosity and saturated hydraulic conductivity is required to accurately model the dynamics of near-surface hydrological processes (e.g. evapotranspiration and root-zone soil moisture dynamics) and provide reliable estimates of regional water and energy budgets. Soil hydraulic properties are commonly derived from pedo-transfer functions using soil textural information recorded during surveys, such as the fractions of sand and clay, bulk density, and organic matter content. Typically large scale land-surface models are parameterized using a relatively coarse soil map with little or no information on parametric sub-grid variability. In this study we analyze the impact of sub-grid soil variability on simulated hydrological fluxes over the Mississippi River Basin (≈3,240,000 km2) at multiple spatio-temporal resolutions. A set of numerical experiments were conducted with the distributed mesoscale hydrologic model (mHM) using two soil datasets: (a) the Digital General Soil Map of the United States or STATSGO2 (1:250 000) and (b) the recently collated Harmonized World Soil Database based on the FAO-UNESCO Soil Map of the World (1:5 000 000). mHM was parameterized with the multi-scale regionalization technique that derives distributed soil hydraulic properties via pedo-transfer functions and regional coefficients. Within the experimental framework, the 3-hourly model simulations were conducted at four spatial resolutions ranging from 0.125° to 1°, using meteorological datasets from the NLDAS-2 project for the time period 1980-2012. Preliminary results indicate that the model was able to capture observed streamflow behavior reasonably well with both soil datasets, in the major sub-basins (i.e. the Missouri, the Upper Mississippi, the Ohio, the Red, and the Arkansas). However, the spatio-temporal patterns of simulated water fluxes and states (e.g. soil moisture, evapotranspiration) from both simulations, showed marked differences; particularly at a shorter time scale (hours to days) in regions with coarse texture sandy soils. Furthermore, the partitioning of total runoff into near-surface interflows and baseflow components was also significantly different between the two simulations. Simulations with the coarser soil map produced comparatively higher baseflows. At longer time scales (months to seasons) where climatic factors plays a major role, the integrated fluxes and states from both sets of model simulations match fairly closely, despite the apparent discrepancy in the partitioning of total runoff.

Verification of sub-grid filtered drag models for gas-particle fluidized beds with immersed cylinder arrays

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

Sarkar, Avik; Sun, Xin; Sundaresan, Sankaran

2014-04-23

The accuracy of coarse-grid multiphase CFD simulations of fluidized beds may be improved via the inclusion of filtered constitutive models. In our previous study (Sarkar et al., Chem. Eng. Sci., 104, 399-412), we developed such a set of filtered drag relationships for beds with immersed arrays of cooling tubes. Verification of these filtered drag models is addressed in this work. Predictions from coarse-grid simulations with the sub-grid filtered corrections are compared against accurate, highly-resolved simulations of full-scale turbulent and bubbling fluidized beds. The filtered drag models offer a computationally efficient yet accurate alternative for obtaining macroscopic predictions, but the spatialmore » resolution of meso-scale clustering heterogeneities is sacrificed.« less

Determining the Effect of the Lunar Nodal Cycle on Tidal Mixing and North Pacific Climate Variability

NASA Astrophysics Data System (ADS)

Ullman, D. J.; Schmittner, A.; Danabasoglu, G.; Norton, N. J.; Müller, M.

2016-02-01

Oscillations in the moon's orbit around the earth modulate regional tidal dissipation with a periodicity of 18.6 years. In regions where the diurnal tidal constituents dominate diapycnal mixing, this Lunar Nodal Cycle (LNC) may be significant enough to influence ocean circulation, sea surface temperature, and climate variability. Such periodicity in the LNC as an external forcing may provide a mechanistic source for Pacific decadal variability (i.e. Pacific Decadal Oscillation, PDO) where diurnal tidal constituents are strong. We have introduced three enhancements to the latest version of the Community Earth System Model (CESM) to better simulate tidal-forced mixing. First, we have produced a sub-grid scale bathymetry scheme that better resolves the vertical distribution of the barotropic energy flux in regions where the native CESM grid does not resolve high spatial-scale bathymetric features. Second, we test a number of alternative barotropic tidal constituent energy flux fields that are derived from various satellite altimeter observations and tidal models. Third, we introduce modulations of the individual diurnal and semi-diurnal tidal constituents, ranging from monthly to decadal periods, as derived from the full lunisolar tidal potential. Using both ocean-only and fully-coupled configurations, we test the influence of these enhancements, particularly the LNC modulations, on ocean mixing and bidecadal climate variability in CESM.

Studies of Sub-Synchronous Oscillations in Large-Scale Wind Farm Integrated System

NASA Astrophysics Data System (ADS)

Yue, Liu; Hang, Mend

2018-01-01

With the rapid development and construction of large-scale wind farms and grid-connected operation, the series compensation wind power AC transmission is gradually becoming the main way of power usage and improvement of wind power availability and grid stability, but the integration of wind farm will change the SSO (Sub-Synchronous oscillation) damping characteristics of synchronous generator system. Regarding the above SSO problem caused by integration of large-scale wind farms, this paper focusing on doubly fed induction generator (DFIG) based wind farms, aim to summarize the SSO mechanism in large-scale wind power integrated system with series compensation, which can be classified as three types: sub-synchronous control interaction (SSCI), sub-synchronous torsional interaction (SSTI), sub-synchronous resonance (SSR). Then, SSO modelling and analysis methods are categorized and compared by its applicable areas. Furthermore, this paper summarizes the suppression measures of actual SSO projects based on different control objectives. Finally, the research prospect on this field is explored.

Parameterizing Grid-Averaged Longwave Fluxes for Inhomogeneous Marine Boundary Layer Clouds

NASA Technical Reports Server (NTRS)

Barker, Howard W.; Wielicki, Bruce A.

1997-01-01

This paper examines the relative impacts on grid-averaged longwave flux transmittance (emittance) for Marine Boundary Layer (MBL) cloud fields arising from horizontal variability of optical depth tau and cloud sides, First, using fields of Landsat-inferred tau and a Monte Carlo photon transport algorithm, it is demonstrated that mean all-sky transmittances for 3D variable MBL clouds can be computed accurately by the conventional method of linearly weighting clear and cloudy transmittances by their respective sky fractions. Then, the approximations of decoupling cloud and radiative properties and assuming independent columns are shown to be adequate for computation of mean flux transmittance. Since real clouds have nonzero geometric thicknesses, cloud fractions A'(sub c) presented to isotropic beams usually exceed the more familiar vertically projected cloud fractions A(sub c). It is shown, however, that when A(sub c)less than or equal to 0.9, biases for all-sky transmittance stemming from use of A(sub c) as opposed to A'(sub c) are roughly 2-5 times smaller than, and opposite in sign to, biases due to neglect of horizontal variability of tau. By neglecting variable tau, all-sky transmittances are underestimated often by more than 0.1 for A(sub c) near 0.75 and this translates into relative errors that can exceed 40% (corresponding errors for all-sky emittance are about 20% for most values of A(sub c). Thus, priority should be given to development of General Circulation Model (GCM) parameterizations that account for the effects of horizontal variations in unresolved tau, effects of cloud sides are of secondary importance. On this note, an efficient stochastic model for computing grid-averaged cloudy-sky flux transmittances is furnished that assumes that distributions of tau, for regions comparable in size to GCM grid cells, can be described adequately by gamma distribution functions. While the plane-parallel, homogeneous model underestimates cloud transmittance by about an order of magnitude when 3D variable cloud transmittances are less than or equal to 0.2 and by approx. 20% to 100% otherwise, the stochastic model reduces these biases often by more than 80%.

Sea level anomaly in the North Atlantic and seas around Europe: Long-term variability and response to North Atlantic teleconnection patterns.

PubMed

Iglesias, Isabel; Lorenzo, M Nieves; Lázaro, Clara; Fernandes, M Joana; Bastos, Luísa

2017-12-31

Sea level anomaly (SLA), provided globally by satellite altimetry, is considered a valuable proxy for detecting long-term changes of the global ocean, as well as short-term and annual variations. In this manuscript, monthly sea level anomaly grids for the period 1993-2013 are used to characterise the North Atlantic Ocean variability at inter-annual timescales and its response to the North Atlantic main patterns of atmospheric circulation variability (North Atlantic Oscillation, Eastern Atlantic, Eastern Atlantic/Western Russia, Scandinavian and Polar/Eurasia) and main driven factors as sea level pressure, sea surface temperature and wind fields. SLA variability and long-term trends are analysed for the North Atlantic Ocean and several sub-regions (North, Baltic and Mediterranean and Black seas, Bay of Biscay extended to the west coast of the Iberian Peninsula, and the northern North Atlantic Ocean), depicting the SLA fluctuations at basin and sub-basin scales, aiming at representing the regions of maximum sea level variability. A significant correlation between SLA and the different phases of the teleconnection patterns due to the generated winds, sea level pressure and sea surface temperature anomalies, with a strong variability on temporal and spatial scales, has been identified. Long-term analysis reveals the existence of non-stationary inter-annual SLA fluctuations in terms of the temporal scale. Spectral density analysis has shown the existence of long-period signals in the SLA inter-annual component, with periods of ~10, 5, 4 and 2years, depending on the analysed sub-region. Also, a non-uniform increase in sea level since 1993 is identified for all sub-regions, with trend values between 2.05mm/year, for the Bay of Biscay region, and 3.98mm/year for the Baltic Sea (no GIA correction considered). The obtained results demonstrated a strong link between the atmospheric patterns and SLA, as well as strong long-period fluctuations of this variable in spatial and temporal scales. Copyright © 2017 Elsevier B.V. All rights reserved.

Characterization of Cloud Water-Content Distribution

NASA Technical Reports Server (NTRS)

Lee, Seungwon

2010-01-01

The development of realistic cloud parameterizations for climate models requires accurate characterizations of subgrid distributions of thermodynamic variables. To this end, a software tool was developed to characterize cloud water-content distributions in climate-model sub-grid scales. This software characterizes distributions of cloud water content with respect to cloud phase, cloud type, precipitation occurrence, and geo-location using CloudSat radar measurements. It uses a statistical method called maximum likelihood estimation to estimate the probability density function of the cloud water content.

Development of renormalization group analysis of turbulence

NASA Technical Reports Server (NTRS)

Smith, L. M.

1990-01-01

The renormalization group (RG) procedure for nonlinear, dissipative systems is now quite standard, and its applications to the problem of hydrodynamic turbulence are becoming well known. In summary, the RG method isolates self similar behavior and provides a systematic procedure to describe scale invariant dynamics in terms of large scale variables only. The parameterization of the small scales in a self consistent manner has important implications for sub-grid modeling. This paper develops the homogeneous, isotropic turbulence and addresses the meaning and consequence of epsilon-expansion. The theory is then extended to include a weak mean flow and application of the RG method to a sequence of models is shown to converge to the Navier-Stokes equations.

The spectral element method (SEM) on variable-resolution grids: evaluating grid sensitivity and resolution-aware numerical viscosity

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

Guba, O.; Taylor, M. A.; Ullrich, P. A.

2014-11-27

We evaluate the performance of the Community Atmosphere Model's (CAM) spectral element method on variable-resolution grids using the shallow-water equations in spherical geometry. We configure the method as it is used in CAM, with dissipation of grid scale variance, implemented using hyperviscosity. Hyperviscosity is highly scale selective and grid independent, but does require a resolution-dependent coefficient. For the spectral element method with variable-resolution grids and highly distorted elements, we obtain the best results if we introduce a tensor-based hyperviscosity with tensor coefficients tied to the eigenvalues of the local element metric tensor. The tensor hyperviscosity is constructed so that, formore » regions of uniform resolution, it matches the traditional constant-coefficient hyperviscosity. With the tensor hyperviscosity, the large-scale solution is almost completely unaffected by the presence of grid refinement. This later point is important for climate applications in which long term climatological averages can be imprinted by stationary inhomogeneities in the truncation error. We also evaluate the robustness of the approach with respect to grid quality by considering unstructured conforming quadrilateral grids generated with a well-known grid-generating toolkit and grids generated by SQuadGen, a new open source alternative which produces lower valence nodes.« less

The spectral element method on variable resolution grids: evaluating grid sensitivity and resolution-aware numerical viscosity

DOE PAGES

Guba, O.; Taylor, M. A.; Ullrich, P. A.; ...

2014-06-25

We evaluate the performance of the Community Atmosphere Model's (CAM) spectral element method on variable resolution grids using the shallow water equations in spherical geometry. We configure the method as it is used in CAM, with dissipation of grid scale variance implemented using hyperviscosity. Hyperviscosity is highly scale selective and grid independent, but does require a resolution dependent coefficient. For the spectral element method with variable resolution grids and highly distorted elements, we obtain the best results if we introduce a tensor-based hyperviscosity with tensor coefficients tied to the eigenvalues of the local element metric tensor. The tensor hyperviscosity ismore » constructed so that for regions of uniform resolution it matches the traditional constant coefficient hyperviscsosity. With the tensor hyperviscosity the large scale solution is almost completely unaffected by the presence of grid refinement. This later point is important for climate applications where long term climatological averages can be imprinted by stationary inhomogeneities in the truncation error. We also evaluate the robustness of the approach with respect to grid quality by considering unstructured conforming quadrilateral grids generated with a well-known grid-generating toolkit and grids generated by SQuadGen, a new open source alternative which produces lower valence nodes.« less

The influence of sub-grid scale motions on particle collision in homogeneous isotropic turbulence

NASA Astrophysics Data System (ADS)

Xiong, Yan; Li, Jing; Liu, Zhaohui; Zheng, Chuguang

2018-02-01

The absence of sub-grid scale (SGS) motions leads to severe errors in particle pair dynamics, which represents a great challenge to the large eddy simulation of particle-laden turbulent flow. In order to address this issue, data from direct numerical simulation (DNS) of homogenous isotropic turbulence coupled with Lagrangian particle tracking are used as a benchmark to evaluate the corresponding results of filtered DNS (FDNS). It is found that the filtering process in FDNS will lead to a non-monotonic variation of the particle collision statistics, including radial distribution function, radial relative velocity, and the collision kernel. The peak of radial distribution function shifts to the large-inertia region due to the lack of SGS motions, and the analysis of the local flowstructure characteristic variable at particle position indicates that the most effective interaction scale between particles and fluid eddies is increased in FDNS. Moreover, this scale shifting has an obvious effect on the odd-order moments of the probability density function of radial relative velocity, i.e. the skewness, which exhibits a strong correlation to the variance of radial distribution function in FDNS. As a whole, the radial distribution function, together with radial relative velocity, can compensate the SGS effects for the collision kernel in FDNS when the Stokes number based on the Kolmogorov time scale is greater than 3.0. However, it still leaves considerable errors for { St}_k <3.0.

ED(MF)n: Humidity-Convection Feedbacks in a Mass Flux Scheme Based on Resolved Size Densities

NASA Astrophysics Data System (ADS)

Neggers, R.

2014-12-01

Cumulus cloud populations remain at least partially unresolved in present-day numerical simulations of global weather and climate, and accordingly their impact on the larger-scale flow has to be represented through parameterization. Various methods have been developed over the years, ranging in complexity from the early bulk models relying on a single plume to more recent approaches that attempt to reconstruct the underlying probability density functions, such as statistical schemes and multiple plume approaches. Most of these "classic" methods capture key aspects of cumulus cloud populations, and have been successfully implemented in operational weather and climate models. However, the ever finer discretizations of operational circulation models, driven by advances in the computational efficiency of supercomputers, is creating new problems for existing sub-grid schemes. Ideally, a sub-grid scheme should automatically adapt its impact on the resolved scales to the dimension of the grid-box within which it is supposed to act. It can be argued that this is only possible when i) the scheme is aware of the range of scales of the processes it represents, and ii) it can distinguish between contributions as a function of size. How to conceptually represent this knowledge of scale in existing parameterization schemes remains an open question that is actively researched. This study considers a relatively new class of models for sub-grid transport in which ideas from the field of population dynamics are merged with the concept of multi plume modelling. More precisely, a multiple mass flux framework for moist convective transport is formulated in which the ensemble of plumes is created in "size-space". It is argued that thus resolving the underlying size-densities creates opportunities for introducing scale-awareness and scale-adaptivity in the scheme. The behavior of an implementation of this framework in the Eddy Diffusivity Mass Flux (EDMF) model, named ED(MF)n, is examined for a standard case of subtropical marine shallow cumulus. We ask if a system of multiple independently resolved plumes is able to automatically create the vertical profile of bulk (mass) flux at which the sub-grid scale transport balances the imposed larger-scale forcings in the cloud layer.

Trends and Natural Variability of Spring Onset in the Coterminous United States as Evaluated by a New Gridded Dataset of Spring Indices

NASA Astrophysics Data System (ADS)

Ault, T.; Schwartz, M. D.; Zurita-Milla, R.; Weltzin, J. F.; Betancourt, J. L.

2015-12-01

Climate change is expected to modify the timing of seasonal transitions this century, impacting wildlife migrations, ecosystem function, and agricultural activity. Tracking seasonal transitions in a consistent manner across space and through time requires indices that can be used for monitoring and managing biophysical and ecological systems during the coming decades. Here a new gridded dataset of spring indices is described and used to understand interannual, decadal, and secular trends across the coterminous US. This dataset is derived from daily interpolated meteorological data, and results are compared with historical station data to ensure the trends and variations are robust. Regional trends in the first leaf index range from -0.8 to -1.6 days per decade, while first bloom index trends are between -0.4 and -1.2 for most regions. However, these trends are modulated by interannual to multidecadal variations, which are substantial throughout the regions considered here. These findings emphasize the important role large-scale climate modes of variability play in modulating spring onset on interannual to multidecadal timescales. Finally, there is some potential for successful sub-seasonal forecasts of spring onset, as indices from most regions are significantly correlated with antecedent large-scale modes of variability.

Impact of cloud horizontal inhomogeneity and directional sampling on the retrieval of cloud droplet size by the POLDER instrument

NASA Astrophysics Data System (ADS)

Shang, H.; Chen, L.; Bréon, F. M.; Letu, H.; Li, S.; Wang, Z.; Su, L.

2015-11-01

The principles of cloud droplet size retrieval via Polarization and Directionality of the Earth's Reflectance (POLDER) requires that clouds be horizontally homogeneous. The retrieval is performed by combining all measurements from an area of 150 km × 150 km to compensate for POLDER's insufficient directional sampling. Using POLDER-like data simulated with the RT3 model, we investigate the impact of cloud horizontal inhomogeneity and directional sampling on the retrieval and analyze which spatial resolution is potentially accessible from the measurements. Case studies show that the sub-grid-scale variability in droplet effective radius (CDR) can significantly reduce valid retrievals and introduce small biases to the CDR (~ 1.5 μm) and effective variance (EV) estimates. Nevertheless, the sub-grid-scale variations in EV and cloud optical thickness (COT) only influence the EV retrievals and not the CDR estimate. In the directional sampling cases studied, the retrieval using limited observations is accurate and is largely free of random noise. Several improvements have been made to the original POLDER droplet size retrieval. For example, measurements in the primary rainbow region (137-145°) are used to ensure retrievals of large droplet (> 15 μm) and to reduce the uncertainties caused by cloud heterogeneity. We apply the improved method using the POLDER global L1B data from June 2008, and the new CDR results are compared with the operational CDRs. The comparison shows that the operational CDRs tend to be underestimated for large droplets because the cloudbow oscillations in the scattering angle region of 145-165° are weak for cloud fields with CDR > 15 μm. Finally, a sub-grid-scale retrieval case demonstrates that a higher resolution, e.g., 42 km × 42 km, can be used when inverting cloud droplet size distribution parameters from POLDER measurements.

Trends in soil moisture and real evapotranspiration in Douro River for the period 1980-2010

NASA Astrophysics Data System (ADS)

García-Valdecasas-Ojeda, Matilde; de Franciscis, Sebastiano; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

This study analyzes the evolution of different hydrological variables, such as soil moisture and real evapotranspiration, for the last 30 years, in the Douro Basin, the most extensive basin in the Iberian Peninsula. The different components of the real evaporation, connected to the soil moisture content, can be important when analyzing the intensity of droughts and heat waves, and particularly relevant for the study of the climate change impacts. The real evapotranspiration and soil moisture data are provided by simulations obtained using the Variable Infiltration Capacity (VIC) hydrological model. This model is a large-scale hydrologic model and allows estimates of different variables in the hydrological system of a basin. Land surface is modeled as a grid of large and uniform cells with sub-grid heterogeneity (e.g. land cover), while water influx is local, only depending from the interaction between grid cells and local atmosphere environment. Observational data of temperature and precipitation from Spain02 dataset are used as input variables for VIC model. The simulations have a spatial resolution of about 9 km, and the analysis is carried out on a seasonal time-scale. Additionally, we compare these results with those obtained from a dynamical downscaling driven by ERA-Interim data using the Weather Research and Forecasting (WRF) model, with the same spatial resolution. The results obtained from Spain02 data show a decrease in soil moisture at different parts of the basin during spring and summer, meanwhile soil moisture seems to be increased for autumn. No significant changes are found for real evapotranspiration. Keywords: real evapotranspiration, soil moisture, Douro Basin, trends, VIC, WRF. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

From Sub-basin to Grid Scale Soil Moisture Disaggregation in SMART, A Semi-distributed Hydrologic Modeling Framework

NASA Astrophysics Data System (ADS)

Ajami, H.; Sharma, A.

2016-12-01

A computationally efficient, semi-distributed hydrologic modeling framework is developed to simulate water balance at a catchment scale. The Soil Moisture and Runoff simulation Toolkit (SMART) is based upon the delineation of contiguous and topologically connected Hydrologic Response Units (HRUs). In SMART, HRUs are delineated using thresholds obtained from topographic and geomorphic analysis of a catchment, and simulation elements are distributed cross sections or equivalent cross sections (ECS) delineated in first order sub-basins. ECSs are formulated by aggregating topographic and physiographic properties of the part or entire first order sub-basins to further reduce computational time in SMART. Previous investigations using SMART have shown that temporal dynamics of soil moisture are well captured at a HRU level using the ECS delineation approach. However, spatial variability of soil moisture within a given HRU is ignored. Here, we examined a number of disaggregation schemes for soil moisture distribution in each HRU. The disaggregation schemes are either based on topographic based indices or a covariance matrix obtained from distributed soil moisture simulations. To assess the performance of the disaggregation schemes, soil moisture simulations from an integrated land surface-groundwater model, ParFlow.CLM in Baldry sub-catchment, Australia are used. ParFlow is a variably saturated sub-surface flow model that is coupled to the Common Land Model (CLM). Our results illustrate that the statistical disaggregation scheme performs better than the methods based on topographic data in approximating soil moisture distribution at a 60m scale. Moreover, the statistical disaggregation scheme maintains temporal correlation of simulated daily soil moisture while preserves the mean sub-basin soil moisture. Future work is focused on assessing the performance of this scheme in catchments with various topographic and climate settings.

Precipitation Estimate Using NEXRAD Ground-Based Radar Images: Validation, Calibration and Spatial Analysis

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

Zhang, Xuesong

2012-12-17

Precipitation is an important input variable for hydrologic and ecological modeling and analysis. Next Generation Radar (NEXRAD) can provide precipitation products that cover most of the continental United States with a high resolution display of approximately 4 × 4 km2. Two major issues concerning the applications of NEXRAD data are (1) lack of a NEXRAD geo-processing and geo-referencing program and (2) bias correction of NEXRAD estimates. In this chapter, a geographic information system (GIS) based software that can automatically support processing of NEXRAD data for hydrologic and ecological models is presented. Some geostatistical approaches to calibrating NEXRAD data using rainmore » gauge data are introduced, and two case studies on evaluating accuracy of NEXRAD Multisensor Precipitation Estimator (MPE) and calibrating MPE with rain-gauge data are presented. The first case study examines the performance of MPE in mountainous region versus south plains and cold season versus warm season, as well as the effect of sub-grid variability and temporal scale on NEXRAD performance. From the results of the first case study, performance of MPE was found to be influenced by complex terrain, frozen precipitation, sub-grid variability, and temporal scale. Overall, the assessment of MPE indicates the importance of removing bias of the MPE precipitation product before its application, especially in the complex mountainous region. The second case study examines the performance of three MPE calibration methods using rain gauge observations in the Little River Experimental Watershed in Georgia. The comparison results show that no one method can perform better than the others in terms of all evaluation coefficients and for all time steps. For practical estimation of precipitation distribution, implementation of multiple methods to predict spatial precipitation is suggested.« less

Optimal variable-grid finite-difference modeling for porous media

NASA Astrophysics Data System (ADS)

Liu, Xinxin; Yin, Xingyao; Li, Haishan

2014-12-01

Numerical modeling of poroelastic waves by the finite-difference (FD) method is more expensive than that of acoustic or elastic waves. To improve the accuracy and computational efficiency of seismic modeling, variable-grid FD methods have been developed. In this paper, we derived optimal staggered-grid finite difference schemes with variable grid-spacing and time-step for seismic modeling in porous media. FD operators with small grid-spacing and time-step are adopted for low-velocity or small-scale geological bodies, while FD operators with big grid-spacing and time-step are adopted for high-velocity or large-scale regions. The dispersion relations of FD schemes were derived based on the plane wave theory, then the FD coefficients were obtained using the Taylor expansion. Dispersion analysis and modeling results demonstrated that the proposed method has higher accuracy with lower computational cost for poroelastic wave simulation in heterogeneous reservoirs.

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

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies

NASA Astrophysics Data System (ADS)

Williams, Paul; Howe, Nicola; Gregory, Jonathan; Smith, Robin; Joshi, Manoj

2016-04-01

In climate simulations, the impacts of the sub-grid scales on the resolved scales are conventionally represented using deterministic closure schemes, which assume that the impacts are uniquely determined by the resolved scales. Stochastic parameterization relaxes this assumption, by sampling the sub-grid variability in a computationally inexpensive manner. This presentation shows that the simulated climatological state of the ocean is improved in many respects by implementing a simple stochastic parameterization of ocean eddies into a coupled atmosphere-ocean general circulation model. Simulations from a high-resolution, eddy-permitting ocean model are used to calculate the eddy statistics needed to inject realistic stochastic noise into a low-resolution, non-eddy-permitting version of the same model. A suite of four stochastic experiments is then run to test the sensitivity of the simulated climate to the noise definition, by varying the noise amplitude and decorrelation time within reasonable limits. The addition of zero-mean noise to the ocean temperature tendency is found to have a non-zero effect on the mean climate. Specifically, in terms of the ocean temperature and salinity fields both at the surface and at depth, the noise reduces many of the biases in the low-resolution model and causes it to more closely resemble the high-resolution model. The variability of the strength of the global ocean thermohaline circulation is also improved. It is concluded that stochastic ocean perturbations can yield reductions in climate model error that are comparable to those obtained by refining the resolution, but without the increased computational cost. Therefore, stochastic parameterizations of ocean eddies have the potential to significantly improve climate simulations. Reference PD Williams, NJ Howe, JM Gregory, RS Smith, and MM Joshi (2016) Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies. Journal of Climate, under revision.

Sub-seasonal temperature variability in the tropical upper troposphere and lower stratosphere observed with GPS radio occultation

NASA Astrophysics Data System (ADS)

Scherllin-Pirscher, Barbara; Randel, William J.; Kim, Joowan

2017-04-01

We investigate sub-seasonal temperature variability in the tropical upper troposphere and lower stratosphere (UTLS) region using daily gridded fields of GPS radio occultation measurements. The unprecedented vertical resolution (from about 100 m in the troposphere to about 1.5 km in the stratosphere) and high accuracy and precision (0.7 K to 1 K between 8 km and 25 km) make these data ideal for characterizing temperature oscillations with short vertical wavelengths. Long-term behavior of sub-seasonal temperature variability is investigated using the entire RO record from January 2002 to December 2014 (13 years of data). Transient sub-seasonal waves including eastward-propagating Kelvin waves (isolated with space-time spectral analysis) dominate large-scale zonal temperature variability in the tropical tropopause region and in the lower stratosphere. Above 20 km, Kelvin waves are strongly modulated by the quasi-biennial oscillation (QBO). Enhanced wave activity can be found during the westerly shear phase of the QBO. In the tropical tropopause region, however, sub-seasonal waves are highly transient in time. Several peaks of Kelvin-wave activity coincide with short-term fluctuations in tropospheric deep convection, but other episodes are not evidently related. Also, there are no obvious relationships with zonal winds or stability fields near the tropical tropopause. Further investigations of convective forcing and atmospheric background conditions along the waves' trajectories are needed to better understand sub-seasonal temperature variability near the tropopause. For more details, see Scherllin-Pirscher, B., Randel, W. J., and Kim, J.: Tropical temperature variability and Kelvin-wave activity in the UTLS from GPS RO measurements, Atmos. Chem. Phys., 17, 793-806, doi:10.5194/acp-17-793-2017, 2017. http://www.atmos-chem-phys.net/17/793/2017/acp-17-793-2017.html

Sub-grid drag model for immersed vertical cylinders in fluidized beds

DOE PAGES

Verma, Vikrant; Li, Tingwen; Dietiker, Jean -Francois; ...

2017-01-03

Immersed vertical cylinders are often used as heat exchanger in gas-solid fluidized beds. Computational Fluid Dynamics (CFD) simulations are computationally expensive for large scale systems with bundles of cylinders. Therefore sub-grid models are required to facilitate simulations on a coarse grid, where internal cylinders are treated as a porous medium. The influence of cylinders on the gas-solid flow tends to enhance segregation and affect the gas-solid drag. A correction to gas-solid drag must be modeled using a suitable sub-grid constitutive relationship. In the past, Sarkar et al. have developed a sub-grid drag model for horizontal cylinder arrays based on 2Dmore » simulations. However, the effect of a vertical cylinder arrangement was not considered due to computational complexities. In this study, highly resolved 3D simulations with vertical cylinders were performed in small periodic domains. These simulations were filtered to construct a sub-grid drag model which can then be implemented in coarse-grid simulations. Gas-solid drag was filtered for different solids fractions and a significant reduction in drag was identified when compared with simulation without cylinders and simulation with horizontal cylinders. Slip velocities significantly increase when vertical cylinders are present. Lastly, vertical suspension drag due to vertical cylinders is insignificant however substantial horizontal suspension drag is observed which is consistent to the finding for horizontal cylinders.« less

Evaluation of decadal hindcasts using satellite simulators

NASA Astrophysics Data System (ADS)

Spangehl, Thomas; Mazurkiewicz, Alex; Schröder, Marc

2013-04-01

The evaluation of dynamical ensemble forecast systems requires a solid validation of basic processes such as the global atmospheric water and energy cycle. The value of any validation approach strongly depends on the quality of the observational data records used. Current approaches utilize in situ measurements, remote sensing data and reanalyses. Related data records are subject to a number of uncertainties and limitations such as representativeness, spatial and temporal resolution and homogeneity. However, recently several climate data records with known and sufficient quality became available. In particular, the satellite data records offer the opportunity to obtain reference information on global scales including the oceans. Here we consider the simulation of satellite radiances from the climate model output enabling an evaluation in the instrument's parameter space to avoid uncertainties stemming from the application of retrieval schemes in order to minimise uncertainties on the reference side. Utilizing the CFMIP Observation Simulator Package (COSP) we develop satellite simulators for the Tropical Rainfall Measuring Mission precipitation radar (TRMM PR) and the Infrared Atmospheric Sounding Interferometer (IASI). The simulators are applied within the MiKlip project funded by BMBF (German Federal Ministry of Education and Research) to evaluate decadal climate predictions performed with the MPI-ESM developed at the Max Planck Institute for Meteorology. While TRMM PR enables the evaluation of the vertical structure of precipitation over tropical and sub-tropical areas, IASI is used to support the global evaluation of clouds and radiation. In a first step the reliability of the developed simulators needs to be explored. The simulation of radiances in the instrument space requires the generation of sub-grid scale variability from the climate model output. Furthermore, assumptions are made to simulate radiances such as, for example, the distribution of different hydrometeor types. Therefore, testing is performed to determine the extent to which the quality of the simulator results depends on the applied methods used to generate sub-grid variability (e.g. sub-grid resolution). Moreover, the sensitivity of results to the choice of different distributions of hydrometeors is explored. The model evaluation is carried out in a statistical manner using histograms of radar reflectivities (TRMM PR) and brightness temperatures (IASI). Finally, methods to deduce data suitable for probabilistic evaluation of decadal hindcasts such as simple indices are discussed.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul

2016-04-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning retrospective predictions at the decadal (5-years), seasonal and sub-seasonal time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and sub-seasonal time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Spatial Variability of Snowpack Properties On Small Slopes

NASA Astrophysics Data System (ADS)

Pielmeier, C.; Kronholm, K.; Schneebeli, M.; Schweizer, J.

The spatial variability of alpine snowpacks is created by a variety of parameters like deposition, wind erosion, sublimation, melting, temperature, radiation and metamor- phism of the snow. Spatial variability is thought to strongly control the avalanche initi- ation and failure propagation processes. Local snowpack measurements are currently the basis for avalanche warning services and there exist contradicting hypotheses about the spatial continuity of avalanche active snow layers and interfaces. Very little about the spatial variability of the snowpack is known so far, therefore we have devel- oped a systematic and objective method to measure the spatial variability of snowpack properties, layering and its relation to stability. For a complete coverage, the analysis of the spatial variability has to entail all scales from mm to km. In this study the small to medium scale spatial variability is investigated, i.e. the range from centimeters to tenths of meters. During the winter 2000/2001 we took systematic measurements in lines and grids on a flat snow test field with grid distances from 5 cm to 0.5 m. Fur- thermore, we measured systematic grids with grid distances between 0.5 m and 2 m in undisturbed flat fields and on small slopes above the tree line at the Choerbschhorn, in the region of Davos, Switzerland. On 13 days we measured the spatial pattern of the snowpack stratigraphy with more than 110 snow micro penetrometer measure- ments at slopes and flat fields. Within this measuring grid we placed 1 rutschblock and 12 stuffblock tests to measure the stability of the snowpack. With the large num- ber of measurements we are able to use geostatistical methods to analyse the spatial variability of the snowpack. Typical correlation lengths are calculated from semivari- ograms. Discerning the systematic trends from random spatial variability is analysed using statistical models. Scale dependencies are shown and recurring scaling patterns are outlined. The importance of the small and medium scale spatial variability for the larger (kilometer) scale spatial variability as well as for the avalanche formation are discussed. Finally, an outlook on spatial models for the snowpack variability is given.

Scale-dependent coupling of hysteretic capillary pressure, trapping, and fluid mobilities

NASA Astrophysics Data System (ADS)

Doster, F.; Celia, M. A.; Nordbotten, J. M.

2012-12-01

Many applications of multiphase flow in porous media, including CO2-storage and enhanced oil recovery, require mathematical models that span a large range of length scales. In the context of numerical simulations, practical grid sizes are often on the order of tens of meters, thereby de facto defining a coarse model scale. Under particular conditions, it is possible to approximate the sub-grid-scale distribution of the fluid saturation within a grid cell; that reconstructed saturation can then be used to compute effective properties at the coarse scale. If both the density difference between the fluids and the vertical extend of the grid cell are large, and buoyant segregation within the cell on a sufficiently shorte time scale, then the phase pressure distributions are essentially hydrostatic and the saturation profile can be reconstructed from the inferred capillary pressures. However, the saturation reconstruction may not be unique because the parameters and parameter functions of classical formulations of two-phase flow in porous media - the relative permeability functions, the capillary pressure -saturation relationship, and the residual saturations - show path dependence, i.e. their values depend not only on the state variables but also on their drainage and imbibition histories. In this study we focus on capillary pressure hysteresis and trapping and show that the contribution of hysteresis to effective quantities is dependent on the vertical length scale. By studying the transition from the two extreme cases - the homogeneous saturation distribution for small vertical extents and the completely segregated distribution for large extents - we identify how hysteretic capillary pressure at the local scale induces hysteresis in all coarse-scale quantities for medium vertical extents and finally vanishes for large vertical extents. Our results allow for more accurate vertically integrated modeling while improving our understanding of the coupling of capillary pressure and relative permeabilities over larger length scales.

Grid sensitivity capability for large scale structures

NASA Technical Reports Server (NTRS)

Nagendra, Gopal K.; Wallerstein, David V.

1989-01-01

The considerations and the resultant approach used to implement design sensitivity capability for grids into a large scale, general purpose finite element system (MSC/NASTRAN) are presented. The design variables are grid perturbations with a rather general linking capability. Moreover, shape and sizing variables may be linked together. The design is general enough to facilitate geometric modeling techniques for generating design variable linking schemes in an easy and straightforward manner. Test cases have been run and validated by comparison with the overall finite difference method. The linking of a design sensitivity capability for shape variables in MSC/NASTRAN with an optimizer would give designers a powerful, automated tool to carry out practical optimization design of real life, complicated structures.

THE RELATIONSHIP BETWEEN {nu}{sub max} AND AGE t FROM ZAMS TO RGB-TIP FOR LOW-MASS STARS

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

Tang, Y. K.; Gai, N., E-mail: tyk450@163.com, E-mail: ning.gai@hotmail.com

2013-07-10

Stellar age is an important quantity in astrophysics, which is useful for many fields both in the universe and galaxies. It cannot be determined by direct measurements, but can only be estimated or inferred. We attempt to find a useful indicator of stellar age, which is accurate from the zero-age main sequence to the tip of red giant branch for low-mass stars. Using the Yale Rotation and Evolution Code (YREC), a grid of stellar models has been constructed. Meanwhile, the frequency of maximum oscillations' power {nu}{sub max} and the large frequency separation {Delta}{nu} are calculated using the scaling relations. Formore » the stars, the masses of which are from 0.8 M{sub Sun} to 2.8 M{sub Sun }, we can obtain the {nu}{sub max} and stellar age by combing the scaling relations with the four sets of grid models (YREC, Dotter et al., Marigo et al., and YY isochrones). We find that {nu}{sub max} is tightly correlated and decreases monotonically with the age of the star from the main sequence to the red giant evolutionary stages. Moreover, we find that the line shapes of the curves in the Age versus {nu}{sub max} diagram, which is plotted by the four sets of grid models, are consistent for red giants with masses from 1.1 M{sub Sun} to 2.8 M{sub Sun }. For red giants, the differences of correlation coefficients between Age and {nu}{sub max} for different grid models are minor and can be ignored. Interestingly, we find two peaks that correspond to the subgiants and bump of red giants in the Age versus {nu}{sub max} diagram. By general linear least-squares, we make the polynomial fitting and deduce the relationship between log(Age) and log({nu}{sub max}) in red giants' evolutionary state.« less

HPC Aspects of Variable-Resolution Global Climate Modeling using a Multi-scale Convection Parameterization

EPA Science Inventory

High performance computing (HPC) requirements for the new generation variable grid resolution (VGR) global climate models differ from that of traditional global models. A VGR global model with 15 km grids over the CONUS stretching to 60 km grids elsewhere will have about ~2.5 tim...

The effects of spatial heterogeneity and subsurface lateral transfer on evapotranspiration estimates in large scale Earth system models

NASA Astrophysics Data System (ADS)

Rouholahnejad, E.; Fan, Y.; Kirchner, J. W.; Miralles, D. G.

2017-12-01

Most Earth system models (ESM) average over considerable sub-grid heterogeneity in land surface properties, and overlook subsurface lateral flow. This could potentially bias evapotranspiration (ET) estimates and has implications for future temperature predictions, since overestimations in ET imply greater latent heat fluxes and potential underestimation of dry and warm conditions in the context of climate change. Here we quantify the bias in evaporation estimates that may arise from the fact that ESMs average over considerable heterogeneity in surface properties, and also neglect lateral transfer of water across the heterogeneous landscapes at global scale. We use a Budyko framework to express ET as a function of P and PET to derive simple sub-grid closure relations that quantify how spatial heterogeneity and lateral transfer could affect average ET as seen from the atmosphere. We show that averaging over sub-grid heterogeneity in P and PET, as typical Earth system models do, leads to overestimation of average ET. Our analysis at global scale shows that the effects of sub-grid heterogeneity will be most pronounced in steep mountainous areas where the topographic gradient is high and where P is inversely correlated with PET across the landscape. In addition, we use the Total Water Storage (TWS) anomaly estimates from the Gravity Recovery and Climate Experiment (GRACE) remote sensing product and assimilate it into the Global Land Evaporation Amsterdam Model (GLEAM) to correct for existing free drainage lower boundary condition in GLEAM and quantify whether, and how much, accounting for changes in terrestrial storage can improve the simulation of soil moisture and regional ET fluxes at global scale.

Interannual Variability in Global Soil Respiration on a 0.5 Degree Grid Cell Basis (1980-1994)

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

Raich, J.W.

2003-09-15

We used a climate-driven regression model to develop spatially resolved estimates of soil-CO{sub 2} emissions from the terrestrial land surface for each month from January 1980 to December 1994, to evaluate the effects of interannual variations in climate on global soil-to-atmosphere CO{sub 2} fluxes. The mean annual global soil-CO{sub 2} flux over this 15-y period was estimated to be 80.4 (range 79.3-81.8) Pg C. Monthly variations in global soil-CO{sub 2} emissions followed closely the mean temperature cycle of the Northern Hemisphere. Globally, soil-CO{sub 2} emissions reached their minima in February and peaked in July and August. Tropical and subtropical evergreenmore » broad-leaved forests contributed more soil-derived CO{sub 2} to the atmosphere than did any other vegetation type ({approx}30% of the total) and exhibited a biannual cycle in their emissions. Soil-CO{sub 2} emissions in other biomes exhibited a single annual cycle that paralleled the seasonal temperature cycle. Interannual variability in estimated global soil-CO{sub 2} production is substantially less than is variability in net carbon uptake by plants (i.e., net primary productivity). Thus, soils appear to buffer atmospheric CO{sub 2} concentrations against far more dramatic seasonal and interannual differences in plant growth. Within seasonally dry biomes (savannas, bushlands, and deserts), interannual variability in soil-CO{sub 2} emissions correlated significantly with interannual differences in precipitation. At the global scale, however, annual soil-CO{sub 2} fluxes correlated with mean annual temperature, with a slope of 3.3 PgCY{sup -1} per degree Celsius. Although the distribution of precipitation influences seasonal and spatial patterns of soil-CO{sub 2} emissions, global warming is likely to stimulate CO{sub 2} emissions from soils.« less

OVERSMART Reporting Tool for Flow Computations Over Large Grid Systems

NASA Technical Reports Server (NTRS)

Kao, David L.; Chan, William M.

2012-01-01

Structured grid solvers such as NASA's OVERFLOW compressible Navier-Stokes flow solver can generate large data files that contain convergence histories for flow equation residuals, turbulence model equation residuals, component forces and moments, and component relative motion dynamics variables. Most of today's large-scale problems can extend to hundreds of grids, and over 100 million grid points. However, due to the lack of efficient tools, only a small fraction of information contained in these files is analyzed. OVERSMART (OVERFLOW Solution Monitoring And Reporting Tool) provides a comprehensive report of solution convergence of flow computations over large, complex grid systems. It produces a one-page executive summary of the behavior of flow equation residuals, turbulence model equation residuals, and component forces and moments. Under the automatic option, a matrix of commonly viewed plots such as residual histograms, composite residuals, sub-iteration bar graphs, and component forces and moments is automatically generated. Specific plots required by the user can also be prescribed via a command file or a graphical user interface. Output is directed to the user s computer screen and/or to an html file for archival purposes. The current implementation has been targeted for the OVERFLOW flow solver, which is used to obtain a flow solution on structured overset grids. The OVERSMART framework allows easy extension to other flow solvers.

Toward a Unified Representation of Atmospheric Convection in Variable-Resolution Climate Models

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

Walko, Robert

2016-11-07

The purpose of this project was to improve the representation of convection in atmospheric weather and climate models that employ computational grids with spatially-variable resolution. Specifically, our work targeted models whose grids are fine enough over selected regions that convection is resolved explicitly, while over other regions the grid is coarser and convection is represented as a subgrid-scale process. The working criterion for a successful scheme for representing convection over this range of grid resolution was that identical convective environments must produce very similar convective responses (i.e., the same precipitation amount, rate, and timing, and the same modification of themore » atmospheric profile) regardless of grid scale. The need for such a convective scheme has increased in recent years as more global weather and climate models have adopted variable resolution meshes that are often extended into the range of resolving convection in selected locations.« less

Hydrological characterization of Guadalquivir River Basin for the period 1980-2010 using VIC model

NASA Astrophysics Data System (ADS)

García-Valdecasas-Ojeda, Matilde; de Franciscis, Sebastiano; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

This study analyzes the changes of soil moisture and real evapotranspiration (ETR), during the last 30 years, in the Guadalquivir River Basin, located in the south of the Iberian Peninsula. Soil moisture content is related with the different components of the real evaporation, it is a relevant factor when analyzing the intensity of droughts and heat waves, and particularly, for the impact study of the climate change. The soil moisture and real evapotranspiration data consist of simulations obtained by using the Variable Infiltration Capacity (VIC) hydrological model. This is a large-scale hydrologic model and allows the estimations of different variables in the hydrological system of a basin. Land surface is modeled as a grid of large and uniform cells with sub-grid heterogeneity (e.g. land cover), while water influx is local, only depending from the interaction between grid cell and local atmosphere environment. Observational data of temperature and precipitation from Spain02 dataset have been used as input variables for VIC model. Additionally, estimates of actual evapotranspiration and soil moisture are also analyzed using temperature, precipitation, wind, humidity and radiation as input variables for VIC. These variables are obtained from a dynamical downscaling from ERA-Interim data by the Weather Research and Forecasting (WRF) model. The simulations have a spatial resolution about 9 km and the analysis is done on a seasonal time-scale. Preliminary results show that ETR presents very low values for autumn from WRF simulations compared with VIC simulations. Only significant positive trends are found during autumn for the western part of the basin for the ETR obtained with VIC model, meanwhile no significant trends are found for the ETR WRF simulations. Keywords: Soil moisture, Real evapotranspiration, Guadalquivir Basin, trends, VIC, WRF. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

The evaluation and development of the Met Office Unified Model using surface and space borne radar.

NASA Astrophysics Data System (ADS)

Petch, J.

2012-12-01

The Met Office Unified Model is used for the prediction of weather and climate on time scales of hours through to centuries. Therefore, the parametrizations in that model need to work on weather and climate timescale, and with grid-lengths from hundres of meters through to several hundred kilometres. Focusing on the development of the cloud and radiation schemes I will discuss how we are using ground-based remote-sensing observations from Chilbolton (England) and a combination of Cloudsat and Calipso data to evaluate and improve the performance of the model. I will show how the prediction of the clouds has improved since the AR5 version of the model and how we have developed an improved cloud generator to rebresent the sub-grid variability of clouds for radiative transfer.

Simulation of Anomalous Regional Climate Events with a Variable Resolution Stretched Grid GCM

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.

1999-01-01

The stretched-grid approach provides an efficient down-scaling and consistent interactions between global and regional scales due to using one variable-resolution model for integrations. It is a workable alternative to the widely used nested-grid approach introduced over a decade ago as a pioneering step in regional climate modeling. A variable-resolution General Circulation Model (GCM) employing a stretched grid, with enhanced resolution over the US as the area of interest, is used for simulating two anomalous regional climate events, the US summer drought of 1988 and flood of 1993. The special mode of integration using a stretched-grid GCM and data assimilation system is developed that allows for imitating the nested-grid framework. The mode is useful for inter-comparison purposes and for underlining the differences between these two approaches. The 1988 and 1993 integrations are performed for the two month period starting from mid May. Regional resolutions used in most of the experiments is 60 km. The major goal and the result of the study is obtaining the efficient down-scaling over the area of interest. The monthly mean prognostic regional fields for the stretched-grid integrations are remarkably close to those of the verifying analyses. Simulated precipitation patterns are successfully verified against gauge precipitation observations. The impact of finer 40 km regional resolution is investigated for the 1993 integration and an example of recovering subregional precipitation is presented. The obtained results show that the global variable-resolution stretched-grid approach is a viable candidate for regional and subregional climate studies and applications.

Variable Grid Traveltime Tomography for Near-surface Seismic Imaging

NASA Astrophysics Data System (ADS)

Cai, A.; Zhang, J.

2017-12-01

We present a new algorithm of traveltime tomography for imaging the subsurface with automated variable grids upon geological structures. The nonlinear traveltime tomography along with Tikhonov regularization using conjugate gradient method is a conventional method for near surface imaging. However, model regularization for any regular and even grids assumes uniform resolution. From geophysical point of view, long-wavelength and large scale structures can be reliably resolved, the details along geological boundaries are difficult to resolve. Therefore, we solve a traveltime tomography problem that automatically identifies large scale structures and aggregates grids within the structures for inversion. As a result, the number of velocity unknowns is reduced significantly, and inversion intends to resolve small-scale structures or the boundaries of large-scale structures. The approach is demonstrated by tests on both synthetic and field data. One synthetic model is a buried basalt model with one horizontal layer. Using the variable grid traveltime tomography, the resulted model is more accurate in top layer velocity, and basalt blocks, and leading to a less number of grids. The field data was collected in an oil field in China. The survey was performed in an area where the subsurface structures were predominantly layered. The data set includes 476 shots with a 10 meter spacing and 1735 receivers with a 10 meter spacing. The first-arrival traveltime of the seismogram is picked for tomography. The reciprocal errors of most shots are between 2ms and 6ms. The normal tomography results in fluctuations in layers and some artifacts in the velocity model. In comparison, the implementation of new method with proper threshold provides blocky model with resolved flat layer and less artifacts. Besides, the number of grids reduces from 205,656 to 4,930 and the inversion produces higher resolution due to less unknowns and relatively fine grids in small structures. The variable grid traveltime tomography provides an alternative imaging solution for blocky structures in the subsurface and builds a good starting model for waveform inversion and statics.

Development and analysis of prognostic equations for mesoscale kinetic energy and mesoscale (subgrid scale) fluxes for large-scale atmospheric models

NASA Technical Reports Server (NTRS)

Avissar, Roni; Chen, Fei

1993-01-01

Generated by landscape discontinuities (e.g., sea breezes) mesoscale circulation processes are not represented in large-scale atmospheric models (e.g., general circulation models), which have an inappropiate grid-scale resolution. With the assumption that atmospheric variables can be separated into large scale, mesoscale, and turbulent scale, a set of prognostic equations applicable in large-scale atmospheric models for momentum, temperature, moisture, and any other gaseous or aerosol material, which includes both mesoscale and turbulent fluxes is developed. Prognostic equations are also developed for these mesoscale fluxes, which indicate a closure problem and, therefore, require a parameterization. For this purpose, the mean mesoscale kinetic energy (MKE) per unit of mass is used, defined as E-tilde = 0.5 (the mean value of u'(sub i exp 2), where u'(sub i) represents the three Cartesian components of a mesoscale circulation (the angle bracket symbol is the grid-scale, horizontal averaging operator in the large-scale model, and a tilde indicates a corresponding large-scale mean value). A prognostic equation is developed for E-tilde, and an analysis of the different terms of this equation indicates that the mesoscale vertical heat flux, the mesoscale pressure correlation, and the interaction between turbulence and mesoscale perturbations are the major terms that affect the time tendency of E-tilde. A-state-of-the-art mesoscale atmospheric model is used to investigate the relationship between MKE, landscape discontinuities (as characterized by the spatial distribution of heat fluxes at the earth's surface), and mesoscale sensible and latent heat fluxes in the atmosphere. MKE is compared with turbulence kinetic energy to illustrate the importance of mesoscale processes as compared to turbulent processes. This analysis emphasizes the potential use of MKE to bridge between landscape discontinuities and mesoscale fluxes and, therefore, to parameterize mesoscale fluxes generated by such subgrid-scale landscape discontinuities in large-scale atmospheric models.

Black hole feeding and feedback: the physics inside the `sub-grid'

NASA Astrophysics Data System (ADS)

Negri, A.; Volonteri, M.

2017-05-01

Black holes (BHs) are believed to be a key ingredient of galaxy formation. However, the galaxy-BH interplay is challenging to study due to the large dynamical range and complex physics involved. As a consequence, hydrodynamical cosmological simulations normally adopt sub-grid models to track the unresolved physical processes, in particular BH accretion; usually the spatial scale where the BH dominates the hydrodynamical processes (the Bondi radius) is unresolved, and an approximate Bondi-Hoyle accretion rate is used to estimate the growth of the BH. By comparing hydrodynamical simulations at different resolutions (300, 30, 3 pc) using a Bondi-Hoyle approximation to sub-parsec runs with non-parametrized accretion, our aim is to probe how well an approximated Bondi accretion is able to capture the BH accretion physics and the subsequent feedback on the galaxy. We analyse an isolated galaxy simulation that includes cooling, star formation, Type Ia and Type II supernovae, BH accretion and active galactic nuclei feedback (radiation pressure, Compton heating/cooling) where mass, momentum and energy are deposited in the interstellar medium through conical winds. We find that on average the approximated Bondi formalism can lead to both over- and underestimations of the BH growth, depending on resolution and on how the variables entering into the Bondi-Hoyle formalism are calculated.

An Experimental Investigation of Unsteady Surface Pressure on an Airfoil in Turbulence

NASA Technical Reports Server (NTRS)

Mish, Patrick F.; Devenport, William J.

2003-01-01

Measurements of fluctuating surface pressure were made on a NACA 0015 airfoil immersed in grid generated turbulence. The airfoil model has a 2 ft chord and spans the 6 ft Virginia Tech Stability Wind Tunnel test section. Two grids were used to investigate the effects of turbulence length scale on the surface pressure response. A large grid which produced turbulence with an integral scale 13% of the chord and a smaller grid which produced turbulence with an integral scale 1.3% of the chord. Measurements were performed at angles of attack, alpha from 0 to 20 . An array of microphones mounted subsurface was used to measure the unsteady surface pressure. The goal of this measurement was to characterize the effects of angle of attack on the inviscid response. Lift spectra calculated from pressure measurements at each angle of attack revealed two distinct interaction regions; for omega(sub r) = omega b / U(sub infinity) is less than 10 a reduction in unsteady lift of up to 7 decibels (dB) occurs while an increase occurs for omega(sub r) is greater than 10 as the angle of attack is increased. The reduction in unsteady lift at low omega(sub r) with increasing angle of attack is a result that has never before been shown either experimentally or theoretically. The source of the reduction in lift spectral level appears to be closely related to the distortion of inflow turbulence based on analysis of surface pressure spanwise correlation length scales. Furthermore, while the distortion of the inflow appears to be critical in this experiment, this effect does not seem to be significant in larger integral scale (relative to the chord) flows based on the previous experimental work of McKeough suggesting the airfoils size relative to the inflow integral scale is critical in defining how the airfoil will respond under variation of angle of attack. A prediction scheme is developed that correctly accounts for the effects of distortion when the inflow integral scale is small relative to the airfoil chord. This scheme utilizes Rapid Distortion Theory to account for the distortion of the inflow with the distortion field modeled using a circular cylinder.

Flexible Energy Scheduling Tool for Integrating Variable Generation | Grid

Science.gov Websites

, security-constrained economic dispatch, and automatic generation control programs. DOWNLOAD PAPER Electric commitment, security-constrained economic dispatch, and automatic generation control sub-models. Each sub resolutions and operating strategies can be explored. FESTIV produces not only economic metrics but also

Large eddy simulation of piloted pulverised coal combustion using extended flamelet/progress variable model

NASA Astrophysics Data System (ADS)

Wen, Xu; Luo, Kun; Jin, Hanhui; Fan, Jianren

2017-09-01

An extended flamelet/progress variable (EFPV) model for simulating pulverised coal combustion (PCC) in the context of large eddy simulation (LES) is proposed, in which devolatilisation, char surface reaction and radiation are all taken into account. The pulverised coal particles are tracked in the Lagrangian framework with various sub-models and the sub-grid scale (SGS) effects of turbulent velocity and scalar fluctuations on the coal particles are modelled by the velocity-scalar joint filtered density function (VSJFDF) model. The presented model is then evaluated by LES of an experimental piloted coal jet flame and comparing the numerical results with the experimental data and the results from the eddy break up (EBU) model. Detailed quantitative comparisons are carried out. It is found that the proposed model performs much better than the EBU model on radial velocity and species concentrations predictions. Comparing against the adiabatic counterpart, we find that the predicted temperature is evidently lowered and agrees well with the experimental data if the conditional sampling method is adopted.

Investigating the dependence of SCM simulated precipitation and clouds on the spatial scale of large-scale forcing at SGP [Investigating the scale dependence of SCM simulated precipitation and cloud by using gridded forcing data at SGP

DOE PAGES

Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng

2017-08-05

Large-scale forcing data, such as vertical velocity and advective tendencies, are required to drive single-column models (SCMs), cloud-resolving models, and large-eddy simulations. Previous studies suggest that some errors of these model simulations could be attributed to the lack of spatial variability in the specified domain-mean large-scale forcing. This study investigates the spatial variability of the forcing and explores its impact on SCM simulated precipitation and clouds. A gridded large-scale forcing data during the March 2000 Cloud Intensive Operational Period at the Atmospheric Radiation Measurement program's Southern Great Plains site is used for analysis and to drive the single-column version ofmore » the Community Atmospheric Model Version 5 (SCAM5). When the gridded forcing data show large spatial variability, such as during a frontal passage, SCAM5 with the domain-mean forcing is not able to capture the convective systems that are partly located in the domain or that only occupy part of the domain. This problem has been largely reduced by using the gridded forcing data, which allows running SCAM5 in each subcolumn and then averaging the results within the domain. This is because the subcolumns have a better chance to capture the timing of the frontal propagation and the small-scale systems. As a result, other potential uses of the gridded forcing data, such as understanding and testing scale-aware parameterizations, are also discussed.« less

A first large-scale flood inundation forecasting model

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

Schumann, Guy J-P; Neal, Jeffrey C.; Voisin, Nathalie

2013-11-04

At present continental to global scale flood forecasting focusses on predicting at a point discharge, with little attention to the detail and accuracy of local scale inundation predictions. Yet, inundation is actually the variable of interest and all flood impacts are inherently local in nature. This paper proposes a first large scale flood inundation ensemble forecasting model that uses best available data and modeling approaches in data scarce areas and at continental scales. The model was built for the Lower Zambezi River in southeast Africa to demonstrate current flood inundation forecasting capabilities in large data-scarce regions. The inundation model domainmore » has a surface area of approximately 170k km2. ECMWF meteorological data were used to force the VIC (Variable Infiltration Capacity) macro-scale hydrological model which simulated and routed daily flows to the input boundary locations of the 2-D hydrodynamic model. Efficient hydrodynamic modeling over large areas still requires model grid resolutions that are typically larger than the width of many river channels that play a key a role in flood wave propagation. We therefore employed a novel sub-grid channel scheme to describe the river network in detail whilst at the same time representing the floodplain at an appropriate and efficient scale. The modeling system was first calibrated using water levels on the main channel from the ICESat (Ice, Cloud, and land Elevation Satellite) laser altimeter and then applied to predict the February 2007 Mozambique floods. Model evaluation showed that simulated flood edge cells were within a distance of about 1 km (one model resolution) compared to an observed flood edge of the event. Our study highlights that physically plausible parameter values and satisfactory performance can be achieved at spatial scales ranging from tens to several hundreds of thousands of km2 and at model grid resolutions up to several km2. However, initial model test runs in forecast mode revealed that it is crucial to account for basin-wide hydrological response time when assessing lead time performances notwithstanding structural limitations in the hydrological model and possibly large inaccuracies in precipitation data.« less

Comparison of Large eddy dynamo simulation using dynamic sub-grid scale (SGS) model with a fully resolved direct simulation in a rotating spherical shell

NASA Astrophysics Data System (ADS)

Matsui, H.; Buffett, B. A.

2017-12-01

The flow in the Earth's outer core is expected to have vast length scale from the geometry of the outer core to the thickness of the boundary layer. Because of the limitation of the spatial resolution in the numerical simulations, sub-grid scale (SGS) modeling is required to model the effects of the unresolved field on the large-scale fields. We model the effects of sub-grid scale flow and magnetic field using a dynamic scale similarity model. Four terms are introduced for the momentum flux, heat flux, Lorentz force and magnetic induction. The model was previously used in the convection-driven dynamo in a rotating plane layer and spherical shell using the Finite Element Methods. In the present study, we perform large eddy simulations (LES) using the dynamic scale similarity model. The scale similarity model is implement in Calypso, which is a numerical dynamo model using spherical harmonics expansion. To obtain the SGS terms, the spatial filtering in the horizontal directions is done by taking the convolution of a Gaussian filter expressed in terms of a spherical harmonic expansion, following Jekeli (1981). A Gaussian field is also applied in the radial direction. To verify the present model, we perform a fully resolved direct numerical simulation (DNS) with the truncation of the spherical harmonics L = 255 as a reference. And, we perform unresolved DNS and LES with SGS model on coarser resolution (L= 127, 84, and 63) using the same control parameter as the resolved DNS. We will discuss the verification results by comparison among these simulations and role of small scale fields to large scale fields through the role of the SGS terms in LES.

A Virtual Study of Grid Resolution on Experiments of a Highly-Resolved Turbulent Plume

NASA Astrophysics Data System (ADS)

Maisto, Pietro M. F.; Marshall, Andre W.; Gollner, Michael J.; Fire Protection Engineering Department Collaboration

2017-11-01

An accurate representation of sub-grid scale turbulent mixing is critical for modeling fire plumes and smoke transport. In this study, PLIF and PIV diagnostics are used with the saltwater modeling technique to provide highly-resolved instantaneous field measurements in unconfined turbulent plumes useful for statistical analysis, physical insight, and model validation. The effect of resolution was investigated employing a virtual interrogation window (of varying size) applied to the high-resolution field measurements. Motivated by LES low-pass filtering concepts, the high-resolution experimental data in this study can be analyzed within the interrogation windows (i.e. statistics at the sub-grid scale) and on interrogation windows (i.e. statistics at the resolved scale). A dimensionless resolution threshold (L/D*) criterion was determined to achieve converged statistics on the filtered measurements. Such a criterion was then used to establish the relative importance between large and small-scale turbulence phenomena while investigating specific scales for the turbulent flow. First order data sets start to collapse at a resolution of 0.3D*, while for second and higher order statistical moments the interrogation window size drops down to 0.2D*.

Renormalization group estimates of transport coefficients in the advection of a passive scalar by incompressible turbulence

NASA Technical Reports Server (NTRS)

Zhou, YE; Vahala, George

1993-01-01

The advection of a passive scalar by incompressible turbulence is considered using recursive renormalization group procedures in the differential sub grid shell thickness limit. It is shown explicitly that the higher order nonlinearities induced by the recursive renormalization group procedure preserve Galilean invariance. Differential equations, valid for the entire resolvable wave number k range, are determined for the eddy viscosity and eddy diffusivity coefficients, and it is shown that higher order nonlinearities do not contribute as k goes to 0, but have an essential role as k goes to k(sub c) the cutoff wave number separating the resolvable scales from the sub grid scales. The recursive renormalization transport coefficients and the associated eddy Prandtl number are in good agreement with the k-dependent transport coefficients derived from closure theories and experiments.

Calculating Soil Wetness, Evapotranspiration and Carbon Cycle Processes Over Large Grid Areas Using a New Scaling Technique

NASA Technical Reports Server (NTRS)

Sellers, Piers

2012-01-01

Soil wetness typically shows great spatial variability over the length scales of general circulation model (GCM) grid areas (approx 100 km ), and the functions relating evapotranspiration and photosynthetic rate to local-scale (approx 1 m) soil wetness are highly non-linear. Soil respiration is also highly dependent on very small-scale variations in soil wetness. We therefore expect significant inaccuracies whenever we insert a single grid area-average soil wetness value into a function to calculate any of these rates for the grid area. For the particular case of evapotranspiration., this method - use of a grid-averaged soil wetness value - can also provoke severe oscillations in the evapotranspiration rate and soil wetness under some conditions. A method is presented whereby the probability distribution timction(pdf) for soil wetness within a grid area is represented by binning. and numerical integration of the binned pdf is performed to provide a spatially-integrated wetness stress term for the whole grid area, which then permits calculation of grid area fluxes in a single operation. The method is very accurate when 10 or more bins are used, can deal realistically with spatially variable precipitation, conserves moisture exactly and allows for precise modification of the soil wetness pdf after every time step. The method could also be applied to other ecological problems where small-scale processes must be area-integrated, or upscaled, to estimate fluxes over large areas, for example in treatments of the terrestrial carbon budget or trace gas generation.

EXAMINATION OF MODEL PREDICTIONS AT DIFFERENT HORIZONTAL GRID RESOLUTIONS

EPA Science Inventory

While fluctuations in meteorological and air quality variables occur on a continuum of spatial scales, the horizontal grid spacing of coupled meteorological and photochemical models sets a lower limit on the spatial scales that they can resolve. However, both computational costs ...

An innovative expression model of human health risk based on the quantitative analysis of soil metals sources contribution in different spatial scales.

PubMed

Zhang, Yimei; Li, Shuai; Wang, Fei; Chen, Zhuang; Chen, Jie; Wang, Liqun

2018-09-01

Toxicity of heavy metals from industrialization poses critical concern, and analysis of sources associated with potential human health risks is of unique significance. Assessing human health risk of pollution sources (factored health risk) concurrently in the whole and the sub region can provide more instructive information to protect specific potential victims. In this research, we establish a new expression model of human health risk based on quantitative analysis of sources contribution in different spatial scales. The larger scale grids and their spatial codes are used to initially identify the level of pollution risk, the type of pollution source and the sensitive population at high risk. The smaller scale grids and their spatial codes are used to identify the contribution of various sources of pollution to each sub region (larger grid) and to assess the health risks posed by each source for each sub region. The results of case study show that, for children (sensitive populations, taking school and residential area as major region of activity), the major pollution source is from the abandoned lead-acid battery plant (ALP), traffic emission and agricultural activity. The new models and results of this research present effective spatial information and useful model for quantifying the hazards of source categories and human health a t complex industrial system in the future. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Agricultural soil contamination from As and Cd and its responses to landscape heterogeneity at multiple scales in Guangzhou, China].

PubMed

Xu, Hui Qiu; Huang, Yin Hua; Wu, Zhi Feng; Cheng, Jiong; Li, Cheng

2016-10-01

Based on 641 agricultural top soil samples (0-20 cm) and land use map in 2005 of Guangzhou, we used single-factor pollution indices and Pearson/Spearman correlation and partial redundancy analyses and quantified the soil contamination with As and Cd and their relationships with landscape heterogeneity at three grid scales of 2 km×2 km, 5 km×5 km, and 10 km×10 km as well as the determinant landscape heterogeneity factors at a certain grid scale. 5.3% and 7.2% of soil samples were contaminated with As and Cd, respectively. At the three scales, the agricultural soil As and Cd contamination were generally significantly correlated with parent materials' composition, river/road density and landscape patterns of several land use types, indicating the parent materials, sewage irrigation and human activities (e.g., industrial and traffic activities, and the additions of pesticides and fertilizers) were possibly the main input pathways of trace metals. Three subsets of landscape heterogeneity variables (i.e., parent materials, distance-density variables, and landscape patterns) could explain 12.7%-42.9% of the variation of soil contamination with As and Cd, of which the explanatory power increased with the grid scale and the determinant factors varied with scales. Parent materials had higher contribution to the variations of soil contamination at the 2 and 10 km grid scales, while the contributions of landscape patterns and distance-density variables generally increased with the grid scale. Adjusting the distribution of cropland and optimizing the landscape pattern of land use types are important ways to reduce soil contamination at local scales, which urban planners and decision makers should pay more attention to.

Global Gridded Crop Model Evaluation: Benchmarking, Skills, Deficiencies and Implications.

NASA Technical Reports Server (NTRS)

Muller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe; Deryng, Delphine; Folberth, Christian; Glotter, Michael; Hoek, Steven;

The Spectrum of Wind Power Fluctuations

NASA Astrophysics Data System (ADS)

Bandi, Mahesh

2016-11-01

Wind is a variable energy source whose fluctuations threaten electrical grid stability and complicate dynamical load balancing. The power generated by a wind turbine fluctuates due to the variable wind speed that blows past the turbine. Indeed, the spectrum of wind power fluctuations is widely believed to reflect the Kolmogorov spectrum; both vary with frequency f as f - 5 / 3. This variability decreases when aggregate power fluctuations from geographically distributed wind farms are averaged at the grid via a mechanism known as geographic smoothing. Neither the f - 5 / 3 wind power fluctuation spectrum nor the mechanism of geographic smoothing are understood. In this work, we explain the wind power fluctuation spectrum from the turbine through grid scales. The f - 5 / 3 wind power fluctuation spectrum results from the largest length scales of atmospheric turbulence of order 200 km influencing the small scales where individual turbines operate. This long-range influence spatially couples geographically distributed wind farms and synchronizes farm outputs over a range of frequencies and decreases with increasing inter-farm distance. Consequently, aggregate grid-scale power fluctuations remain correlated, and are smoothed until they reach a limiting f - 7 / 3 spectrum. This work was funded by the Collective Interactions Unit, OIST Graduate University, Japan.

Validation of Smithsonian Astrophysical Observatory's OMI Water Vapor Product

NASA Astrophysics Data System (ADS)

Wang, H.; Gonzalez Abad, G.; Liu, X.; Chance, K.

2015-12-01

We perform a comprehensive validation of SAO's OMI water vapor product. The SAO OMI water vapor slant column is retrieved using the 430 - 480 nm wavelength range. In addition to water vapor, the retrieval considers O3, NO2, liquid water, O4, C2H2O2, the Ring effect, water ring, 3rd order polynomial, common mode and under-sampling. The slant column is converted to vertical column using AMF. AMF is calculated using GEOS-Chem water vapor profile shape, OMCLDO2 cloud information and OMLER surface albedo information. We validate our product using NCAR's GPS network data over the world and RSS's gridded microwave data over the ocean. We also compare our product with the total precipitable water derived from the AERONET ground-based sun photometer data, the GlobVapour gridded product, and other datasets. We investigate the influence of sub-grid scale variability and filtering criteria on the comparison. We study the influence of clouds, aerosols and a priori profiles on the retrieval. We also assess the long-term performance and stability of our product and seek ways to improve it.

Numerical Simulation of Bow Waves and Transom-Stern Flows

NASA Astrophysics Data System (ADS)

Dommermuth, Douglas G.; Schlageter, Eric A.; Talcott, John C.; Wyatt, Donald C.; Novikov, Evgeny A.

1997-11-01

A stratified-flow formulation is used to model the breaking bow wave and the separated transom-stern flow that are generated by a ship moving with forward speed. The interface of the air with the water is identified as the zero level-set of a three-dimensional function. The ship is modeled using a body-force technique on a cartesian grid. The three-dimensional body-force is generated using a surface panelization of the entire ship, including the above-water geometry up to and including the deck. The effects of surface tension are modeled as a source term that is concentrated at the air-water interface. The effects of gravity are modeled as a volumetric force. The three-dimensional, unsteady, Navier-Stokes equations are expressed in primitive-variable form. A LES formulation with a Smagorinsky sub-grid-scale model is used to model turbulence. Numerical convergence is demonstrated using 128x64x65, 256x128x129, and 512x256x257 grid points. The numerical results compare well to whisker-probe measurements of the free-surface elevation generated by a naval combatant.

Impact of Variable SST on Simulated Warm Season Precipitation

NASA Astrophysics Data System (ADS)

Saleeby, S. M.; Cotton, W. R.

2007-05-01

The Colorado State University - Regional Atmospheric Modeling System (CSU-RAMS) is being used to examine the variability in monsoon-related warm season precipitation over Mexico and the United States due to variability in SST. Given recent improvements and increased resolution in satellite derived SSTs it is pertinent to examine the sensitivity of the RAMS model to the variety of SST data sources that are available. In particular, we are examining this dependence across continental scales over the full warm season, as well as across the regional scale centered around the Gulf of California on time scales of individual surge events. In this study we performed an ensemble of simulations that include the 2002, 2003, and 2004 warm seasons with use of the Climatology, Reynold's, AVHRR, and MODIS SSTs. From the seasonal 90-day simulations with 30km grid spacing, it was found that variations in surface latent heat flux are directly linked to differences in SST. Regions with cooler (warmer) SST have decreased (increased) moisture flux from the ocean which is in proportion to the magnitude of the SST difference. Over the eastern Pacific, differences in low-level horizontal moisture flux show a general trend toward reduced fluxes over cooler waters and very little inland impact. Over the Gulf of Mexico, however, there is substantial variability for each dataset comparison, despite having only limited variability among the SST data. Causes of this unexpected variability are not straight-forward. Precipitation impacts are greatest near the southern coast of Mexico and along the Sierra Madres. Precipitation variability over the CONUS is rather chaotic and is limited to areas impacted by the Gulf of Mexico or monsoon convection. Another unexpected outcome is the lack of variability in areas near the northern Gulf of California where SST and latent heat flux variability is a maximum. From the 7-day surge period simulations at 7km grid spacing, we found that SST differences on the higher resolution nested grid reveal fine scale variability that is otherwise smoothed out or unapparent on the coarser grid. Unlike the coarse grid, the latent heat flux, temperature, and moisture transport differences on the fine grid reveal an inland impact. This is likely due to fine scale variability in onshore moisture transport and sea- breeze circulations which may alter monsoonal convection and precipitation. However, only the largest SST differences (spatially and in magnitude) tend to invoke large, coherent responses in moisture flux. The SST variability at high resolution produces relatively large differences in precipitation that are focused along the slopes of the SMO, with a tendency toward greater variability along the western slope adjacent to the coast. The precipitation differences are of fine resolution, with variability of +/- 30 mm (over 5 days) along the length of the SMO. Variability on the fine grid also invokes precipitation changes over AZ/NM that are not resolved on the coarse grid. Vertical cross-sections examined along the GoC during the surge episode revealed variations in the moisture and temperature structure of the surge. The cooler SSTs in the climatological dataset produced the greatest variability compared to the other datasets. The surge produced from climatology SSTs was nearly 5g/kg drier and up to 4°C cooler compared to surges influenced by the SST datasets. The overall northward propagation of the surge appeared unaffected by the SSTs.

A Variable Resolution Stretched Grid General Circulation Model: Regional Climate Simulation

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence L.; Govindaraju, Ravi C.; Suarez, Max J.

2000-01-01

The development of and results obtained with a variable resolution stretched-grid GCM for the regional climate simulation mode, are presented. A global variable resolution stretched- grid used in the study has enhanced horizontal resolution over the U.S. as the area of interest The stretched-grid approach is an ideal tool for representing regional to global scale interaction& It is an alternative to the widely used nested grid approach introduced over a decade ago as a pioneering step in regional climate modeling. The major results of the study are presented for the successful stretched-grid GCM simulation of the anomalous climate event of the 1988 U.S. summer drought- The straightforward (with no updates) two month simulation is performed with 60 km regional resolution- The major drought fields, patterns and characteristics such as the time averaged 500 hPa heights precipitation and the low level jet over the drought area. appear to be close to the verifying analyses for the stretched-grid simulation- In other words, the stretched-grid GCM provides an efficient down-scaling over the area of interest with enhanced horizontal resolution. It is also shown that the GCM skill is sustained throughout the simulation extended to one year. The developed and tested in a simulation mode stretched-grid GCM is a viable tool for regional and subregional climate studies and applications.

Potential biases in evapotranspiration estimates from Earth system models due to spatial heterogeneity and lateral moisture redistribution

NASA Astrophysics Data System (ADS)

Rouholahnejad, E.; Kirchner, J. W.

2016-12-01

Evapotranspiration (ET) is a key process in land-climate interactions and affects the dynamics of the atmosphere at local and regional scales. In estimating ET, most earth system models average over considerable sub-grid heterogeneity in land surface properties, precipitation (P), and potential evapotranspiration (PET). This spatial averaging could potentially bias ET estimates, due to the nonlinearities in the underlying relationships. In addition, most earth system models ignore lateral redistribution of water within and between grid cells, which could potentially alter both local and regional ET. Here we present a first attempt to quantify the effects of spatial heterogeneity and lateral redistribution on grid-cell-averaged ET as seen from the atmosphere over heterogeneous landscapes. Using a Budyko framework to express ET as a function of P and PET, we quantify how sub-grid heterogeneity affects average ET at the scale of typical earth system model grid cells. We show that averaging over sub-grid heterogeneity in P and PET, as typical earth system models do, leads to overestimates of average ET. We use a similar approach to quantify how lateral redistribution of water could affect average ET, as seen from the atmosphere. We show that where the aridity index P/PET increases with altitude, gravitationally driven lateral redistribution will increase average ET, implying that models that neglect lateral moisture redistribution will underestimate average ET. In contrast, where the aridity index P/PET decreases with altitude, gravitationally driven lateral redistribution will decrease average ET. This approach yields a simple conceptual framework and mathematical expressions for determining whether, and how much, spatial heterogeneity and lateral redistribution can affect regional ET fluxes as seen from the atmosphere. This analysis provides the basis for quantifying heterogeneity and redistribution effects on ET at regional and continental scales, which will be the focus of future work.

Tropical precipitation extremes: Response to SST-induced warming in aquaplanet simulations

NASA Astrophysics Data System (ADS)

Bhattacharya, Ritthik; Bordoni, Simona; Teixeira, João.

2017-04-01

Scaling of tropical precipitation extremes in response to warming is studied in aquaplanet experiments using the global Weather Research and Forecasting (WRF) model. We show how the scaling of precipitation extremes is highly sensitive to spatial and temporal averaging: while instantaneous grid point extreme precipitation scales more strongly than the percentage increase (˜7% K-1) predicted by the Clausius-Clapeyron (CC) relationship, extremes for zonally and temporally averaged precipitation follow a slight sub-CC scaling, in agreement with results from Climate Model Intercomparison Project (CMIP) models. The scaling depends crucially on the employed convection parameterization. This is particularly true when grid point instantaneous extremes are considered. These results highlight how understanding the response of precipitation extremes to warming requires consideration of dynamic changes in addition to the thermodynamic response. Changes in grid-scale precipitation, unlike those in convective-scale precipitation, scale linearly with the resolved flow. Hence, dynamic changes include changes in both large-scale and convective-scale motions.

Numerical modeling and analysis of the effect of Greek complex topography on tornado genesis

NASA Astrophysics Data System (ADS)

Matsangouras, I. T.; Pytharoulis, I.; Nastos, P. T.

2014-02-01

Tornadoes have been reported in Greece over the last decades in specific sub-geographical areas and have been associated with strong synoptic forcing. It is well known that meteorological conditions over Greece are affected at various scales by the significant variability of topography, the Ionian Sea at the west and the Aegean Sea at the east. However, there is still uncertainty regarding topography's importance on tornadic generation and development. The aim of this study is to investigate the role of topography in significant tornado genesis events that were triggered under strong synoptic scale forcing over Greece. Three tornado events that occurred over the last years in Thiva (Boeotia, 17 November 2007), Vrastema (Chalkidiki, 12 February 2010) and Vlychos (Lefkada, 20 September 2011) have been selected for numerical experiments. These events were associated with synoptic scale forcing, while their intensity was T4-T5 (Torro scale) and caused significant damage. The simulations were performed using the non-hydrostatic Weather Research and Forecasting model (WRF), initialized with ECMWF gridded analyses, with telescoping nested grids that allow the representation of atmospheric circulations ranging from the synoptic scale down to the meso scale. In the experiments the topography of the inner grid was modified by: (a) 0% (actual topography) and (b) -100% (without topography). The aim was to determine whether the occurrence of tornadoes - mainly identified by various severe weather instability indices - could be indicated by modifying topography. The main utilized instability variables concerned the Bulk Richardson number shear (BRN), the energy helicity index (EHI), the storm-relative environmental helicity (SRH) and the maximum convective available potential energy (MCAPE, for parcel with maximum theta-e). Additional a verification of model was conducted for every sensitivity experiment accompanied with analysis absolute vorticity budget. Numerical simulations revealed that the complex topography was denoted as an important factor during 17 November 2007 and 12 February 2010 events, based on EHI and BRN analyses. Topography around 20 September 2011 event was characterized as the least factor based on EHI, SRH, BRN analyses.

Simulation of Boundary-Layer Cumulus and Stratocumulus Clouds using a Cloud-Resolving Model With Low- and Third-Order Turbulence Closures

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man; Cheng, Anning

2007-01-01

The effects of subgrid-scale condensation and transport become more important as the grid spacings increase from those typically used in large-eddy simulation (LES) to those typically used in cloud-resolving models (CRMs). Incorporation of these effects can be achieved by a joint probability density function approach that utilizes higher-order moments of thermodynamic and dynamic variables. This study examines how well shallow cumulus and stratocumulus clouds are simulated by two versions of a CRM that is implemented with low-order and third-order turbulence closures (LOC and TOC) when a typical CRM horizontal resolution is used and what roles the subgrid-scale and resolved-scale processes play as the horizontal grid spacing of the CRM becomes finer. Cumulus clouds were mostly produced through subgrid-scale transport processes while stratocumulus clouds were produced through both subgrid-scale and resolved-scale processes in the TOC version of the CRM when a typical CRM grid spacing is used. The LOC version of the CRM relied upon resolved-scale circulations to produce both cumulus and stratocumulus clouds, due to small subgrid-scale transports. The mean profiles of thermodynamic variables, cloud fraction and liquid water content exhibit significant differences between the two versions of the CRM, with the TOC results agreeing better with the LES than the LOC results. The characteristics, temporal evolution and mean profiles of shallow cumulus and stratocumulus clouds are weakly dependent upon the horizontal grid spacing used in the TOC CRM. However, the ratio of the subgrid-scale to resolved-scale fluxes becomes smaller as the horizontal grid spacing decreases. The subcloud-layer fluxes are mostly due to the resolved scales when a grid spacing less than or equal to 1 km is used. The overall results of the TOC simulations suggest that a 1-km grid spacing is a good choice for CRM simulation of shallow cumulus and stratocumulus.

Subgrid Modeling Geomorphological and Ecological Processes in Salt Marsh Evolution

NASA Astrophysics Data System (ADS)

Shi, F.; Kirby, J. T., Jr.; Wu, G.; Abdolali, A.; Deb, M.

2016-12-01

Numerical modeling a long-term evolution of salt marshes is challenging because it requires an extensive use of computational resources. Due to the presence of narrow tidal creeks, variations of salt marsh topography can be significant over spatial length scales on the order of a meter. With growing availability of high-resolution bathymetry measurements, like LiDAR-derived DEM data, it is increasingly desirable to run a high-resolution model in a large domain and for a long period of time to get trends of sedimentation patterns, morphological change and marsh evolution. However, high spatial-resolution poses a big challenge in both computational time and memory storage, when simulating a salt marsh with dimensions of up to O(100 km^2) with a small time step. In this study, we have developed a so-called Pre-storage, Sub-grid Model (PSM, Wu et al., 2015) for simulating flooding and draining processes in salt marshes. The simulation of Brokenbridge salt marsh, Delaware, shows that, with the combination of the sub-grid model and the pre-storage method, over 2 orders of magnitude computational speed-up can be achieved with minimal loss of model accuracy. We recently extended PSM to include a sediment transport component and models for biomass growth and sedimentation in the sub-grid model framework. The sediment transport model is formulated based on a newly derived sub-grid sediment concentration equation following Defina's (2000) area-averaging procedure. Suspended sediment transport is modeled by the advection-diffusion equation in the coarse grid level, but the local erosion and sedimentation rates are integrated over the sub-grid level. The morphological model is based on the existing morphological model in NearCoM (Shi et al., 2013), extended to include organic production from the biomass model. The vegetation biomass is predicted by a simple logistic equation model proposed by Marani et al. (2010). The biomass component is loosely coupled with hydrodynamic and sedimentation models owing to the different time scales of the physical and ecological processes. The coupled model is being applied to Delaware marsh evolution in response to rising sea level and changing sediment supplies.

Regional Climate Simulation with a Variable Resolution Stretched Grid GCM: The Regional Down-Scaling Effects

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence L.; Suarez, Max; Sawyer, William; Govindaraju, Ravi C.

1999-01-01

The results obtained with the variable resolution stretched grid (SG) GEOS GCM (Goddard Earth Observing System General Circulation Models) are discussed, with the emphasis on the regional down-scaling effects and their dependence on the stretched grid design and parameters. A variable resolution SG-GCM and SG-DAS using a global stretched grid with fine resolution over an area of interest, is a viable new approach to REGIONAL and subregional CLIMATE studies and applications. The stretched grid approach is an ideal tool for representing regional to global scale interactions. It is an alternative to the widely used nested grid approach introduced a decade ago as a pioneering step in regional climate modeling. The GEOS SG-GCM is used for simulations of the anomalous U.S. climate events of 1988 drought and 1993 flood, with enhanced regional resolution. The height low level jet, precipitation and other diagnostic patterns are successfully simulated and show the efficient down-scaling over the area of interest the U.S. An imitation of the nested grid approach is performed using the developed SG-DAS (Data Assimilation System) that incorporates the SG-GCM. The SG-DAS is run with withholding data over the area of interest. The design immitates the nested grid framework with boundary conditions provided from analyses. No boundary condition buffer is needed for the case due to the global domain of integration used for the SG-GCM and SG-DAS. The experiments based on the newly developed versions of the GEOS SG-GCM and SG-DAS, with finer 0.5 degree (and higher) regional resolution, are briefly discussed. The major aspects of parallelization of the SG-GCM code are outlined. The KEY OBJECTIVES of the study are: 1) obtaining an efficient DOWN-SCALING over the area of interest with fine and very fine resolution; 2) providing CONSISTENT interactions between regional and global scales including the consistent representation of regional ENERGY and WATER BALANCES; 3) providing a high computational efficiency for future SG-GCM and SG-DAS versions using PARALLEL codes.

Sub-grid drag models for horizontal cylinder arrays immersed in gas-particle multiphase flows

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

Sarkar, Avik; Sun, Xin; Sundaresan, Sankaran

2013-09-08

Immersed cylindrical tube arrays often are used as heat exchangers in gas-particle fluidized beds. In multiphase computational fluid dynamics (CFD) simulations of large fluidized beds, explicit resolution of small cylinders is computationally infeasible. Instead, the cylinder array may be viewed as an effective porous medium in coarse-grid simulations. The cylinders' influence on the suspension as a whole, manifested as an effective drag force, and on the relative motion between gas and particles, manifested as a correction to the gas-particle drag, must be modeled via suitable sub-grid constitutive relationships. In this work, highly resolved unit-cell simulations of flow around an arraymore » of horizontal cylinders, arranged in a staggered configuration, are filtered to construct sub-grid, or `filtered', drag models, which can be implemented in coarse-grid simulations. The force on the suspension exerted by the cylinders is comprised of, as expected, a buoyancy contribution, and a kinetic component analogous to fluid drag on a single cylinder. Furthermore, the introduction of tubes also is found to enhance segregation at the scale of the cylinder size, which, in turn, leads to a reduction in the filtered gas-particle drag.« less

Searching for the right scale in catchment hydrology: the effect of soil spatial variability in simulated states and fluxes

NASA Astrophysics Data System (ADS)

Baroni, Gabriele; Zink, Matthias; Kumar, Rohini; Samaniego, Luis; Attinger, Sabine

2017-04-01

The advances in computer science and the availability of new detailed data-sets have led to a growing number of distributed hydrological models applied to finer and finer grid resolutions for larger and larger catchment areas. It was argued, however, that this trend does not necessarily guarantee better understanding of the hydrological processes or it is even not necessary for specific modelling applications. In the present study, this topic is further discussed in relation to the soil spatial heterogeneity and its effect on simulated hydrological state and fluxes. To this end, three methods are developed and used for the characterization of the soil heterogeneity at different spatial scales. The methods are applied at the soil map of the upper Neckar catchment (Germany), as example. The different soil realizations are assessed regarding their impact on simulated state and fluxes using the distributed hydrological model mHM. The results are analysed by aggregating the model outputs at different spatial scales based on the Representative Elementary Scale concept (RES) proposed by Refsgaard et al. (2016). The analysis is further extended in the present study by aggregating the model output also at different temporal scales. The results show that small scale soil variabilities are not relevant when the integrated hydrological responses are considered e.g., simulated streamflow or average soil moisture over sub-catchments. On the contrary, these small scale soil variabilities strongly affect locally simulated states and fluxes i.e., soil moisture and evapotranspiration simulated at the grid resolution. A clear trade-off is also detected by aggregating the model output by spatial and temporal scales. Despite the scale at which the soil variabilities are (or are not) relevant is not universal, the RES concept provides a simple and effective framework to quantify the predictive capability of distributed models and to identify the need for further model improvements e.g., finer resolution input. For this reason, the integration in this analysis of all the relevant input factors (e.g., precipitation, vegetation, geology) could provide a strong support for the definition of the right scale for each specific model application. In this context, however, the main challenge for a proper model assessment will be the correct characterization of the spatio- temporal variability of each input factor. Refsgaard, J.C., Højberg, A.L., He, X., Hansen, A.L., Rasmussen, S.H., Stisen, S., 2016. Where are the limits of model predictive capabilities?: Representative Elementary Scale - RES. Hydrol. Process. doi:10.1002/hyp.11029

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

Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng

Large-scale forcing data, such as vertical velocity and advective tendencies, are required to drive single-column models (SCMs), cloud-resolving models, and large-eddy simulations. Previous studies suggest that some errors of these model simulations could be attributed to the lack of spatial variability in the specified domain-mean large-scale forcing. This study investigates the spatial variability of the forcing and explores its impact on SCM simulated precipitation and clouds. A gridded large-scale forcing data during the March 2000 Cloud Intensive Operational Period at the Atmospheric Radiation Measurement program's Southern Great Plains site is used for analysis and to drive the single-column version ofmore » the Community Atmospheric Model Version 5 (SCAM5). When the gridded forcing data show large spatial variability, such as during a frontal passage, SCAM5 with the domain-mean forcing is not able to capture the convective systems that are partly located in the domain or that only occupy part of the domain. This problem has been largely reduced by using the gridded forcing data, which allows running SCAM5 in each subcolumn and then averaging the results within the domain. This is because the subcolumns have a better chance to capture the timing of the frontal propagation and the small-scale systems. As a result, other potential uses of the gridded forcing data, such as understanding and testing scale-aware parameterizations, are also discussed.« less

A grid of MHD models for stellar mass loss and spin-down rates of solar analogs

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

Cohen, O.; Drake, J. J.

2014-03-01

Stellar winds are believed to be the dominant factor in the spin-down of stars over time. However, stellar winds of solar analogs are poorly constrained due to observational challenges. In this paper, we present a grid of magnetohydrodynamic models to study and quantify the values of stellar mass loss and angular momentum loss rates as a function of the stellar rotation period, magnetic dipole component, and coronal base density. We derive simple scaling laws for the loss rates as a function of these parameters, and constrain the possible mass loss rate of stars with thermally driven winds. Despite the successmore » of our scaling law in matching the results of the model, we find a deviation between the 'solar dipole' case and a real case based on solar observations that overestimates the actual solar mass loss rate by a factor of three. This implies that the model for stellar fields might require a further investigation with additional complexity. Mass loss rates in general are largely controlled by the magnetic field strength, with the wind density varying in proportion to the confining magnetic pressure B {sup 2}. We also find that the mass loss rates obtained using our grid models drop much faster with the increase in rotation period than scaling laws derived using observed stellar activity. For main-sequence solar-like stars, our scaling law for angular momentum loss versus poloidal magnetic field strength retrieves the well-known Skumanich decline of angular velocity with time, Ω{sub *}∝t {sup –1/2}, if the large-scale poloidal magnetic field scales with rotation rate as B{sub p}∝Ω{sub ⋆}{sup 2}.« less

Use of upscaled elevation and surface roughness data in two-dimensional surface water models

USGS Publications Warehouse

Hughes, J.D.; Decker, J.D.; Langevin, C.D.

2011-01-01

In this paper, we present an approach that uses a combination of cell-block- and cell-face-averaging of high-resolution cell elevation and roughness data to upscale hydraulic parameters and accurately simulate surface water flow in relatively low-resolution numerical models. The method developed allows channelized features that preferentially connect large-scale grid cells at cell interfaces to be represented in models where these features are significantly smaller than the selected grid size. The developed upscaling approach has been implemented in a two-dimensional finite difference model that solves a diffusive wave approximation of the depth-integrated shallow surface water equations using preconditioned Newton–Krylov methods. Computational results are presented to show the effectiveness of the mixed cell-block and cell-face averaging upscaling approach in maintaining model accuracy, reducing model run-times, and how decreased grid resolution affects errors. Application examples demonstrate that sub-grid roughness coefficient variations have a larger effect on simulated error than sub-grid elevation variations.

Numerical modeling and analysis of the effect of complex Greek topography on tornadogenesis

NASA Astrophysics Data System (ADS)

Matsangouras, I. T.; Pytharoulis, I.; Nastos, P. T.

2014-07-01

Tornadoes have been reported in Greece over recent decades in specific sub-geographical areas and have been associated with strong synoptic forcing. While it has been established that meteorological conditions over Greece are affected at various scales by the significant variability of topography, the Ionian Sea to the west and the Aegean Sea to the east, there is still uncertainty regarding topography's importance on tornadic generation and development. The aim of this study is to investigate the role of topography in significant tornadogenesis events that were triggered under strong synoptic scale forcing over Greece. Three tornado events that occurred over the last years in Thebes (Boeotia, 17 November 2007), Vrastema (Chalkidiki, 12 February 2010) and Vlychos (Lefkada, 20 September 2011) were selected for numerical experiments. These events were associated with synoptic scale forcing, while their intensities were T4-T5 (on the TORRO scale), causing significant damage. The simulations were performed using the non-hydrostatic weather research and forecasting model (WRF), initialized by European Centre for Medium-Range Weather Forecasts (ECMWF) gridded analyses, with telescoping nested grids that allow for the representation of atmospheric circulations ranging from the synoptic scale down to the mesoscale. In the experiments, the topography of the inner grid was modified by: (a) 0% (actual topography) and (b) -100% (without topography), making an effort to determine whether the occurrence of tornadoes - mainly identified by various severe weather instability indices - could be indicated by modifying topography. The principal instability variables employed consisted of the bulk Richardson number (BRN) shear, the energy helicity index (EHI), the storm-relative environmental helicity (SRH), and the maximum convective available potential energy (MCAPE, for parcels with maximum θe). Additionally, a model verification was conducted for every sensitivity experiment accompanied by analysis of the absolute vorticity budget. Numerical simulations revealed that the complex topography constituted an important factor during the 17 November 2007 and 12 February 2010 events, based on EHI, SRH, BRN, and MCAPE analyses. Conversely, topography around the 20 September 2011 event was characterized as the least significant factor based on EHI, SRH, BRN, and MCAPE analyses.

Renewable Electricity Futures. Operational Analysis of the Western Interconnection at Very High Renewable Penetrations

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

Brinkman, Gregory

2015-09-01

The Renewable Electricity Futures Study (RE Futures)--an analysis of the costs and grid impacts of integrating large amounts of renewable electricity generation into the U.S. power system--examined renewable energy resources, technical issues regarding the integration of these resources into the grid, and the costs associated with high renewable penetration scenarios. These scenarios included up to 90% of annual generation from renewable sources, although most of the analysis was focused on 80% penetration scenarios. Hourly production cost modeling was performed to understand the operational impacts of high penetrations. One of the conclusions of RE Futures was that further work was necessarymore » to understand whether the operation of the system was possible at sub-hourly time scales and during transient events. This study aimed to address part of this by modeling the operation of the power system at sub-hourly time scales using newer methodologies and updated data sets for transmission and generation infrastructure. The goal of this work was to perform a detailed, sub-hourly analysis of very high penetration scenarios for a single interconnection (the Western Interconnection). It focused on operational impacts, and it helps verify that the operational results from the capacity expansion models are useful. The primary conclusion of this study is that sub-hourly operation of the grid is possible with renewable generation levels between 80% and 90%.« less

Evolution of aerosol downwind of a major highway

NASA Astrophysics Data System (ADS)

Liggio, J.; Staebler, R. M.; Brook, J.; Li, S.; Vlasenko, A. L.; Sjostedt, S. J.; Gordon, M.; Makar, P.; Mihele, C.; Evans, G. J.; Jeong, C.; Wentzell, J. J.; Lu, G.; Lee, P.

2010-12-01

Primary aerosol from traffic emissions can have a considerable impact local and regional scale air quality. In order to assess the effect of these emissions and of future emissions scenarios, air quality models are required which utilize emissions representative of real world conditions. Often, the emissions processing systems which provide emissions input for the air quality models rely on laboratory testing of individual vehicles under non-ambient conditions. However, on the sub-grid scale particle evolution may lead to changes in the primary emitted size distribution and gas-particle partitioning that are not properly considered when the emissions are ‘instantly mixed’ within the grid volume. The affect of this modeling convention on model results is not well understood. In particular, changes in organic gas/particle partitioning may result in particle evaporation or condensation onto pre-existing aerosol. The result is a change in the particle distribution and/or an increase in the organic mass available for subsequent gas-phase oxidation. These effects may be missing from air-quality models, and a careful analysis of field data is necessary to quantify their impact. A study of the sub-grid evolution of aerosols (FEVER; Fast Evolution of Vehicle Emissions from Roadways) was conducted in the Toronto area in the summer of 2010. The study included mobile measurements of particle size distributions with a Fast mobility particle sizer (FMPS), aerosol composition with an Aerodyne aerosol mass spectrometer (AMS), black carbon (SP2, PA, LII), VOCs (PTR-MS) and other trace gases. The mobile laboratory was used to measure the concentration gradient of the emissions at perpendicular distances from the highway as well as the physical and chemical evolution of the aerosol. Stationary sites at perpendicular distances and upwind from the highway also monitored the particle size distribution. In addition, sonic anemometers mounted on the mobile lab provided measurements of turbulent dispersion as a function of distance from the highway, and a traffic camera was used to determine traffic density, composition and speed. These measurements differ from previous studies in that turbulence is measured under realistic conditions and hence the relationship of the aerosol evolution to atmospheric stability and mixing will also be quantified. Preliminary results suggest that aerosol size and composition does change on the sub-grid scale, and sub-grid scale parameterizations of turbulence and particle chemistry should be included in models to accurately represent these effects.

Improvements for retrieval of cloud droplet size by the POLDER instrument

NASA Astrophysics Data System (ADS)

Shang, H.; Husi, L.; Bréon, F. M.; Ma, R.; Chen, L.; Wang, Z.

2017-12-01

The principles of cloud droplet size retrieval via Polarization and Directionality of the Earth's Reflectance (POLDER) requires that clouds be horizontally homogeneous. The retrieval is performed by combining all measurements from an area of 150 km × 150 km to compensate for POLDER's insufficient directional sampling. Using POLDER-like data simulated with the RT3 model, we investigate the impact of cloud horizontal inhomogeneity and directional sampling on the retrieval and analyze which spatial resolution is potentially accessible from the measurements. Case studies show that the sub-grid-scale variability in droplet effective radius (CDR) can significantly reduce valid retrievals and introduce small biases to the CDR ( 1.5µm) and effective variance (EV) estimates. Nevertheless, the sub-grid-scale variations in EV and cloud optical thickness (COT) only influence the EV retrievals and not the CDR estimate. In the directional sampling cases studied, the retrieval using limited observations is accurate and is largely free of random noise. Several improvements have been made to the original POLDER droplet size retrieval. For example, measurements in the primary rainbow region (137-145°) are used to ensure retrievals of large droplet (>15 µm) and to reduce the uncertainties caused by cloud heterogeneity. A premium resoltion of 0.8° is determined by considering successful retrievals and cloud horizontal homogeneity. The improved algorithm is applied to measurements of POLDER in 2008, and we further compared our retrievals with cloud effective radii estimations of Moderate Resolution Imaging Spectroradiometer (MODIS). The results indicate that in global scale, the cloud effective radii and effective variance is larger in the central ocean than inland and coast areas. Over heavy polluted regions, the cloud droplets has small effective radii and narraw distribution due to the influence of aerosol particles.

GRID-BASED EXPLORATION OF COSMOLOGICAL PARAMETER SPACE WITH SNAKE

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

Mikkelsen, K.; Næss, S. K.; Eriksen, H. K., E-mail: kristin.mikkelsen@astro.uio.no

2013-11-10

We present a fully parallelized grid-based parameter estimation algorithm for investigating multidimensional likelihoods called Snake, and apply it to cosmological parameter estimation. The basic idea is to map out the likelihood grid-cell by grid-cell according to decreasing likelihood, and stop when a certain threshold has been reached. This approach improves vastly on the 'curse of dimensionality' problem plaguing standard grid-based parameter estimation simply by disregarding grid cells with negligible likelihood. The main advantages of this method compared to standard Metropolis-Hastings Markov Chain Monte Carlo methods include (1) trivial extraction of arbitrary conditional distributions; (2) direct access to Bayesian evidences; (3)more » better sampling of the tails of the distribution; and (4) nearly perfect parallelization scaling. The main disadvantage is, as in the case of brute-force grid-based evaluation, a dependency on the number of parameters, N{sub par}. One of the main goals of the present paper is to determine how large N{sub par} can be, while still maintaining reasonable computational efficiency; we find that N{sub par} = 12 is well within the capabilities of the method. The performance of the code is tested by comparing cosmological parameters estimated using Snake and the WMAP-7 data with those obtained using CosmoMC, the current standard code in the field. We find fully consistent results, with similar computational expenses, but shorter wall time due to the perfect parallelization scheme.« less

TopoSCALE v.1.0: downscaling gridded climate data in complex terrain

NASA Astrophysics Data System (ADS)

Fiddes, J.; Gruber, S.

2014-02-01

Simulation of land surface processes is problematic in heterogeneous terrain due to the the high resolution required of model grids to capture strong lateral variability caused by, for example, topography, and the lack of accurate meteorological forcing data at the site or scale it is required. Gridded data products produced by atmospheric models can fill this gap, however, often not at an appropriate spatial resolution to drive land-surface simulations. In this study we describe a method that uses the well-resolved description of the atmospheric column provided by climate models, together with high-resolution digital elevation models (DEMs), to downscale coarse-grid climate variables to a fine-scale subgrid. The main aim of this approach is to provide high-resolution driving data for a land-surface model (LSM). The method makes use of an interpolation of pressure-level data according to topographic height of the subgrid. An elevation and topography correction is used to downscale short-wave radiation. Long-wave radiation is downscaled by deriving a cloud-component of all-sky emissivity at grid level and using downscaled temperature and relative humidity fields to describe variability with elevation. Precipitation is downscaled with a simple non-linear lapse and optionally disaggregated using a climatology approach. We test the method in comparison with unscaled grid-level data and a set of reference methods, against a large evaluation dataset (up to 210 stations per variable) in the Swiss Alps. We demonstrate that the method can be used to derive meteorological inputs in complex terrain, with most significant improvements (with respect to reference methods) seen in variables derived from pressure levels: air temperature, relative humidity, wind speed and incoming long-wave radiation. This method may be of use in improving inputs to numerical simulations in heterogeneous and/or remote terrain, especially when statistical methods are not possible, due to lack of observations (i.e. remote areas or future periods).

On the Subgrid-Scale Modeling of Compressible Turbulence

NASA Technical Reports Server (NTRS)

Squires, Kyle; Zeman, Otto

1990-01-01

A new sub-grid scale model is presented for the large-eddy simulation of compressible turbulence. In the proposed model, compressibility contributions have been incorporated in the sub-grid scale eddy viscosity which, in the incompressible limit, reduce to a form originally proposed by Smagorinsky (1963). The model has been tested against a simple extension of the traditional Smagorinsky eddy viscosity model using simulations of decaying, compressible homogeneous turbulence. Simulation results show that the proposed model provides greater dissipation of the compressive modes of the resolved-scale velocity field than does the Smagorinsky eddy viscosity model. For an initial r.m.s. turbulence Mach number of 1.0, simulations performed using the Smagorinsky model become physically unrealizable (i.e., negative energies) because of the inability of the model to sufficiently dissipate fluctuations due to resolved scale velocity dilations. The proposed model is able to provide the necessary dissipation of this energy and maintain the realizability of the flow. Following Zeman (1990), turbulent shocklets are considered to dissipate energy independent of the Kolmogorov energy cascade. A possible parameterization of dissipation by turbulent shocklets for Large-Eddy Simulation is also presented.

Subgrid-scale parameterization and low-frequency variability: a response theory approach

NASA Astrophysics Data System (ADS)

Demaeyer, Jonathan; Vannitsem, Stéphane

2016-04-01

Weather and climate models are limited in the possible range of resolved spatial and temporal scales. However, due to the huge space- and time-scale ranges involved in the Earth System dynamics, the effects of many sub-grid processes should be parameterized. These parameterizations have an impact on the forecasts or projections. It could also affect the low-frequency variability present in the system (such as the one associated to ENSO or NAO). An important question is therefore to know what is the impact of stochastic parameterizations on the Low-Frequency Variability generated by the system and its model representation. In this context, we consider a stochastic subgrid-scale parameterization based on the Ruelle's response theory and proposed in Wouters and Lucarini (2012). We test this approach in the context of a low-order coupled ocean-atmosphere model, detailed in Vannitsem et al. (2015), for which a part of the atmospheric modes is considered as unresolved. A natural separation of the phase-space into a slow invariant set and its fast complement allows for an analytical derivation of the different terms involved in the parameterization, namely the average, the fluctuation and the long memory terms. Its application to the low-order system reveals that a considerable correction of the low-frequency variability along the invariant subset can be obtained. This new approach of scale separation opens new avenues of subgrid-scale parameterizations in multiscale systems used for climate forecasts. References: Vannitsem S, Demaeyer J, De Cruz L, Ghil M. 2015. Low-frequency variability and heat transport in a low-order nonlinear coupled ocean-atmosphere model. Physica D: Nonlinear Phenomena 309: 71-85. Wouters J, Lucarini V. 2012. Disentangling multi-level systems: averaging, correlations and memory. Journal of Statistical Mechanics: Theory and Experiment 2012(03): P03 003.

Towards retrieving critical relative humidity from ground-based remote sensing observations

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

Van Weverberg, Kwinten; Boutle, Ian; Morcrette, Cyril J.

2016-08-22

Nearly all parameterisations of large-scale cloud require the specification of the critical relative humidity (RHcrit). This is the gridbox-mean relative humidity at which the subgrid fluctuations in temperature and water vapour become so large that part of a subsaturated gridbox becomes saturated and cloud starts to form. Until recently, the lack of high-resolution observations of temperature and moisture variability has hindered a reasonable estimate of the RHcrit from observations. However, with the advent of ground-based measurements from Raman lidar, it becomes possible to obtain long records of temperature and moisture (co-)variances with sub-minute sample rates. Lidar observations are inherently noisymore » and any analysis of higher-order moments will be very dependent on the ability to quantify and remove this noise. We present an exporatory study aimed at understanding whether current noise levels of lidar-retrieved temperature and water vapour are sufficient to obtain a reasonable estimate of the RHcrit. We show that vertical profiles of RHcrit can be derived for a gridbox length of up to about 30 km (120) with an uncertainty of about 4 % (2 %). RHcrit tends to be smallest near the scale height and seems to be fairly insensitive to the horizontal grid spacing at the scales investigated here (30 - 120 km). However, larger sensitivity was found to the vertical grid spacing. As the grid spacing decreases from 400 to 100 m, RHcrit is observed to increase by about 6 %, which is more than the uncertainty in the RHcrit retrievals.« less

Energy-Water-Land-Climate Nexus: Modeling Impacts from the Asset to Regional Scale

NASA Astrophysics Data System (ADS)

Tidwell, V. C.; Bennett, K. E.; Middleton, R. S.; Behery, S.; Macknick, J.; Corning-Padilla, A.; Brinkman, G.; Meng, M.

2016-12-01

A critical challenge for the energy-water-land nexus is understanding and modeling the connection between the natural system—including changes in climate, land use/cover, and streamflow—and the engineered system including water for energy, agriculture, and society. Equally important is understanding the linkage across scales; that is, how impacts at the asset level aggregate to influence behavior at the local to regional scale. Toward this need, a case study was conducted featuring multi-sector and multi-scale modeling centered on the San Juan River basin (a watershed that accounts for one-tenth of the Colorado River drainage area). Simulations were driven by statistically downscaled climate data from three global climate models (emission scenario RCP 8.5) and planned growth in regional water demand. The Variable Infiltration Capacity (VIC) hydrologic model was fitted with a custom vegetation mortality sub-model and used to estimate tributary inflows to the San Juan River and estimate reservoir evaporation. San Juan River operations, including releases from Navajo Reservoir, were subsequently modeled using RiverWare to estimate impacts on water deliveries out to the year 2100. Major water demands included two large coal-fired power plants, a local electric utility, river-side irrigation, the Navajo Indian Irrigation Project and instream flows managed for endangered aquatic species. Also tracked were basin exports, including water (downstream flows to the Colorado River and interbasin transfers to the Rio Grande) and interstate electric power transmission. Implications for the larger western electric grid were assessed using PLEXOS, a sub-hourly dispatch, electric production-cost model. Results highlight asset-level interactions at the energy-water-land nexus driven by climate and population dynamics; specifically, growing vulnerabilities to shorted water deliveries. Analyses also explored linkages across geographic scales from the San Juan to the larger Colorado River and Rio Grande basins as well as the western power grid.

CO2 Flux Estimation Errors Associated with Moist Atmospheric Processes

NASA Technical Reports Server (NTRS)

Parazoo, N. C.; Denning, A. S.; Kawa, S. R.; Pawson, S.; Lokupitiya, R.

2012-01-01

Vertical transport by moist sub-grid scale processes such as deep convection is a well-known source of uncertainty in CO2 source/sink inversion. However, a dynamical link between vertical transport, satellite based retrievals of column mole fractions of CO2, and source/sink inversion has not yet been established. By using the same offline transport model with meteorological fields from slightly different data assimilation systems, we examine sensitivity of frontal CO2 transport and retrieved fluxes to different parameterizations of sub-grid vertical transport. We find that frontal transport feeds off background vertical CO2 gradients, which are modulated by sub-grid vertical transport. The implication for source/sink estimation is two-fold. First, CO2 variations contained in moist poleward moving air masses are systematically different from variations in dry equatorward moving air. Moist poleward transport is hidden from orbital sensors on satellites, causing a sampling bias, which leads directly to small but systematic flux retrieval errors in northern mid-latitudes. Second, differences in the representation of moist sub-grid vertical transport in GEOS-4 and GEOS-5 meteorological fields cause differences in vertical gradients of CO2, which leads to systematic differences in moist poleward and dry equatorward CO2 transport and therefore the fraction of CO2 variations hidden in moist air from satellites. As a result, sampling biases are amplified and regional scale flux errors enhanced, most notably in Europe (0.43+/-0.35 PgC /yr). These results, cast from the perspective of moist frontal transport processes, support previous arguments that the vertical gradient of CO2 is a major source of uncertainty in source/sink inversion.

Unstructured grid modelling of offshore wind farm impacts on seasonally stratified shelf seas

NASA Astrophysics Data System (ADS)

Cazenave, Pierre William; Torres, Ricardo; Allen, J. Icarus

2016-06-01

Shelf seas comprise approximately 7% of the world's oceans and host enormous economic activity. Development of energy installations (e.g. Offshore Wind Farms (OWFs), tidal turbines) in response to increased demand for renewable energy requires a careful analysis of potential impacts. Recent remote sensing observations have identified kilometre-scale impacts from OWFs. Existing modelling evaluating monopile impacts has fallen into two camps: small-scale models with individually resolved turbines looking at local effects; and large-scale analyses but with sub-grid scale turbine parameterisations. This work straddles both scales through a 3D unstructured grid model (FVCOM): wind turbine monopiles in the eastern Irish Sea are explicitly described in the grid whilst the overall grid domain covers the south-western UK shelf. Localised regions of decreased velocity extend up to 250 times the monopile diameter away from the monopile. Shelf-wide, the amplitude of the M2 tidal constituent increases by up to 7%. The turbines enhance localised vertical mixing which decreases seasonal stratification. The spatial extent of this extends well beyond the turbines into the surrounding seas. With significant expansion of OWFs on continental shelves, this work highlights the importance of how OWFs may impact coastal (e.g. increased flooding risk) and offshore (e.g. stratification and nutrient cycling) areas.

Evaluating penalized logistic regression models to predict Heat-Related Electric grid stress days

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

Bramer, Lisa M.; Rounds, J.; Burleyson, C. D.

Understanding the conditions associated with stress on the electricity grid is important in the development of contingency plans for maintaining reliability during periods when the grid is stressed. In this paper, heat-related grid stress and the relationship with weather conditions were examined using data from the eastern United States. Penalized logistic regression models were developed and applied to predict stress on the electric grid using weather data. The inclusion of other weather variables, such as precipitation, in addition to temperature improved model performance. Several candidate models and combinations of predictive variables were examined. A penalized logistic regression model which wasmore » fit at the operation-zone level was found to provide predictive value and interpretability. Additionally, the importance of different weather variables observed at various time scales were examined. Maximum temperature and precipitation were identified as important across all zones while the importance of other weather variables was zone specific. In conclusion, the methods presented in this work are extensible to other regions and can be used to aid in planning and development of the electrical grid.« less

Evaluating penalized logistic regression models to predict Heat-Related Electric grid stress days

DOE PAGES

Bramer, Lisa M.; Rounds, J.; Burleyson, C. D.; ...

2017-09-22

Understanding the conditions associated with stress on the electricity grid is important in the development of contingency plans for maintaining reliability during periods when the grid is stressed. In this paper, heat-related grid stress and the relationship with weather conditions were examined using data from the eastern United States. Penalized logistic regression models were developed and applied to predict stress on the electric grid using weather data. The inclusion of other weather variables, such as precipitation, in addition to temperature improved model performance. Several candidate models and combinations of predictive variables were examined. A penalized logistic regression model which wasmore » fit at the operation-zone level was found to provide predictive value and interpretability. Additionally, the importance of different weather variables observed at various time scales were examined. Maximum temperature and precipitation were identified as important across all zones while the importance of other weather variables was zone specific. In conclusion, the methods presented in this work are extensible to other regions and can be used to aid in planning and development of the electrical grid.« less

Techniques and resources for storm-scale numerical weather prediction

NASA Technical Reports Server (NTRS)

Droegemeier, Kelvin; Grell, Georg; Doyle, James; Soong, Su-Tzai; Skamarock, William; Bacon, David; Staniforth, Andrew; Crook, Andrew; Wilhelmson, Robert

1993-01-01

The topics discussed include the following: multiscale application of the 5th-generation PSU/NCAR mesoscale model, the coupling of nonhydrostatic atmospheric and hydrostatic ocean models for air-sea interaction studies; a numerical simulation of cloud formation over complex topography; adaptive grid simulations of convection; an unstructured grid, nonhydrostatic meso/cloud scale model; efficient mesoscale modeling for multiple scales using variable resolution; initialization of cloud-scale models with Doppler radar data; and making effective use of future computing architectures, networks, and visualization software.

From GCM grid cell to agricultural plot: scale issues affecting modelling of climate impact

PubMed Central

Baron, Christian; Sultan, Benjamin; Balme, Maud; Sarr, Benoit; Traore, Seydou; Lebel, Thierry; Janicot, Serge; Dingkuhn, Michael

2005-01-01

General circulation models (GCM) are increasingly capable of making relevant predictions of seasonal and long-term climate variability, thus improving prospects of predicting impact on crop yields. This is particularly important for semi-arid West Africa where climate variability and drought threaten food security. Translating GCM outputs into attainable crop yields is difficult because GCM grid boxes are of larger scale than the processes governing yield, involving partitioning of rain among runoff, evaporation, transpiration, drainage and storage at plot scale. This study analyses the bias introduced to crop simulation when climatic data is aggregated spatially or in time, resulting in loss of relevant variation. A detailed case study was conducted using historical weather data for Senegal, applied to the crop model SARRA-H (version for millet). The study was then extended to a 10°N–17° N climatic gradient and a 31 year climate sequence to evaluate yield sensitivity to the variability of solar radiation and rainfall. Finally, a down-scaling model called LGO (Lebel–Guillot–Onibon), generating local rain patterns from grid cell means, was used to restore the variability lost by aggregation. Results indicate that forcing the crop model with spatially aggregated rainfall causes yield overestimations of 10–50% in dry latitudes, but nearly none in humid zones, due to a biased fraction of rainfall available for crop transpiration. Aggregation of solar radiation data caused significant bias in wetter zones where radiation was limiting yield. Where climatic gradients are steep, these two situations can occur within the same GCM grid cell. Disaggregation of grid cell means into a pattern of virtual synoptic stations having high-resolution rainfall distribution removed much of the bias caused by aggregation and gave realistic simulations of yield. It is concluded that coupling of GCM outputs with plot level crop models can cause large systematic errors due to scale incompatibility. These errors can be avoided by transforming GCM outputs, especially rainfall, to simulate the variability found at plot level. PMID:16433096

Finite-difference modeling with variable grid-size and adaptive time-step in porous media

NASA Astrophysics Data System (ADS)

Liu, Xinxin; Yin, Xingyao; Wu, Guochen

2014-04-01

Forward modeling of elastic wave propagation in porous media has great importance for understanding and interpreting the influences of rock properties on characteristics of seismic wavefield. However, the finite-difference forward-modeling method is usually implemented with global spatial grid-size and time-step; it consumes large amounts of computational cost when small-scaled oil/gas-bearing structures or large velocity-contrast exist underground. To overcome this handicap, combined with variable grid-size and time-step, this paper developed a staggered-grid finite-difference scheme for elastic wave modeling in porous media. Variable finite-difference coefficients and wavefield interpolation were used to realize the transition of wave propagation between regions of different grid-size. The accuracy and efficiency of the algorithm were shown by numerical examples. The proposed method is advanced with low computational cost in elastic wave simulation for heterogeneous oil/gas reservoirs.

Increased tree-ring network density reveals more precise estimations of sub-regional hydroclimate variability and climate dynamics in the Midwest, USA

NASA Astrophysics Data System (ADS)

Maxwell, Justin T.; Harley, Grant L.

2017-08-01

Understanding the historic variability in the hydroclimate provides important information on possible extreme dry or wet periods that in turn inform water management plans. Tree rings have long provided historical context of hydroclimate variability of the U.S. However, the tree-ring network used to create these countrywide gridded reconstructions is sparse in certain locations, such as the Midwest. Here, we increase ( n = 20) the spatial resolution of the tree-ring network in southern Indiana and compare a summer (June-August) Palmer Drought Severity Index (PDSI) reconstruction to existing gridded reconstructions of PDSI for this region. We find both droughts and pluvials that were previously unknown that rival the most intense PDSI values during the instrumental period. Additionally, historical drought occurred in Indiana that eclipsed instrumental conditions with regard to severity and duration. During the period 1962-2004 CE, we find that teleconnections of drought conditions through the Atlantic Meridional Overturning Circulation have a strong influence ( r = -0.60, p < 0.01) on secondary tree growth in this region for the late spring-early summer season. These findings highlight the importance of continuing to increase the spatial resolution of the tree-ring network used to infer past climate dynamics to capture the sub-regional spatial variability. Increasing the spatial resolution of the tree-ring network for a given region can better identify sub-regional variability, improve the accuracy of regional tree-ring PDSI reconstructions, and provide better information for climatic teleconnections.

Spatio-temporal variability of soil water content on the local scale in a Mediterranean mountain area (Vallcebre, North Eastern Spain). How different spatio-temporal scales reflect mean soil water content

NASA Astrophysics Data System (ADS)

Molina, Antonio J.; Latron, Jérôme; Rubio, Carles M.; Gallart, Francesc; Llorens, Pilar

2014-08-01

As a result of complex human-land interactions and topographic variability, many Mediterranean mountain catchments are covered by agricultural terraces that have locally modified the soil water content dynamic. Understanding these local-scale dynamics helps us grasp better how hydrology behaves on the catchment scale. Thus, this study examined soil water content variability in the upper 30 cm of the soil on a Mediterranean abandoned terrace in north-east Spain. Using a dataset of high spatial (regular grid of 128 automatic TDR probes at 2.5 m intervals) and temporal (20-min time step) resolution, gathered throughout a 84-day period, the spatio-temporal variability of soil water content at the local scale and the way that different spatio-temporal scales reflect the mean soil water content were investigated. Soil water content spatial variability and its relation to wetness conditions were examined, along with the spatial structuring of the soil water content within the terrace. Then, the ability of single probes and of different combinations of spatial measurements (transects and grids) to provide a good estimate of mean soil water content on the terrace scale was explored by means of temporal stability analyses. Finally, the effect of monitoring frequency on the magnitude of detectable daily soil water content variations was studied. Results showed that soil water content spatial variability followed a bimodal pattern of increasing absolute variability with increasing soil water content. In addition, a linear trend of decreasing soil water content as the distance from the inner part of the terrace increased was identified. Once this trend was subtracted, resulting semi-variograms suggested that the spatial resolution examined was too high to appreciate spatial structuring in the data. Thus, the spatial pattern should be considered as random. Of all the spatial designs tested, the 10 × 10 m mesh grid (9 probes) was considered the most suitable option for a good, time-stable estimate of mean soil water content, as no improvement was obtained with the 5 × 5 m mesh grid (30 probes). Finally, the results of temporal aggregation showed that decreasing the monitoring frequency down to 8 h during wetting-up periods and to 1 day during drying-down ones did not result in a loss of information on daily soil water content variations.

Eddy-driven low-frequency variability: physics and observability through altimetry

NASA Astrophysics Data System (ADS)

Penduff, Thierry; Sérazin, Guillaume; Arbic, Brian; Mueller, Malte; Richman, James G.; Shriver, Jay F.; Morten, Andrew J.; Scott, Robert B.

2015-04-01

Model studies have revealed the propensity of the eddying ocean circulation to generate strong low-frequency variability (LFV) intrinsically, i.e. without low-frequency atmospheric variability. In the present study, gridded satellite altimeter products, idealized quasi-geostrophic (QG) turbulent simulations, and realistic high-resolution global ocean simulations are used to study the spontaneous tendency of mesoscale (relatively high frequency and high wavenumber) kinetic energy to non-linearly cascade towards larger time and space scales. The QG model reveals that large-scale variability, arising from the well-known spatial inverse cascade, is associated with low frequencies. Low-frequency, low-wavenumber energy is maintained primarily by nonlinearities in the QG model, with forcing (by large-scale shear) and friction playing secondary roles. In realistic simulations, nonlinearities also generally drive kinetic energy to low frequencies and low wavenumbers. In some, but not all, regions of the gridded altimeter product, surface kinetic energy is also found to cascade toward low frequencies. Exercises conducted with the realistic model suggest that the spatial and temporal filtering inherent in the construction of gridded satellite altimeter maps may contribute to the discrepancies seen in some regions between the direction of frequency cascade in models versus gridded altimeter maps. Finally, the range of frequencies that are highly energized and engaged these cascades appears much greater than the range of highly energized and engaged wavenumbers. Global eddying simulations, performed in the context of the CHAOCEAN project in collaboration with the CAREER project, provide estimates of the range of timescales that these oceanic nonlinearities are likely to feed without external variability.

A LES-Langevin model for turbulence

NASA Astrophysics Data System (ADS)

Dolganov, Rostislav; Dubrulle, Bérengère; Laval, Jean-Philippe

2006-11-01

The rationale for Large Eddy Simulation is rooted in our inability to handle all degrees of freedom (N˜10^16 for Re˜10^7). ``Deterministic'' models based on eddy-viscosity seek to reproduce the intensification of the energy transport. However, they fail to reproduce backward energy transfer (backscatter) from small to large scale, which is an essentiel feature of the turbulence near wall or in boundary layer. To capture this backscatter, ``stochastic'' strategies have been developed. In the present talk, we shall discuss such a strategy, based on a Rapid Distorsion Theory (RDT). Specifically, we first divide the small scale contribution to the Reynolds Stress Tensor in two parts: a turbulent viscosity and the pseudo-Lamb vector, representing the nonlinear cross terms of resolved and sub-grid scales. We then estimate the dynamics of small-scale motion by the RDT applied to Navier-Stockes equation. We use this to model the cross term evolution by a Langevin equation, in which the random force is provided by sub-grid pressure terms. Our LES model is thus made of a truncated Navier-Stockes equation including the turbulent force and a generalized Langevin equation for the latter, integrated on a twice-finer grid. The backscatter is automatically included in our stochastic model of the pseudo-Lamb vector. We apply this model to the case of homogeneous isotropic turbulence and turbulent channel flow.

The effects of sub-ice-shelf melting on dense shelf water formation and export in idealized simulations of Antarctic margins

NASA Astrophysics Data System (ADS)

Marques, Gustavo; Stern, Alon; Harrison, Matthew; Sergienko, Olga; Hallberg, Robert

2017-04-01

Dense shelf water (DSW) is formed in coastal polynyas around Antarctica as a result of intense cooling and brine rejection. A fraction of this water reaches ice shelves cavities and is modified due to interactions with sub-ice-shelf melt water. This modified water mass contributes to the formation of Antarctic Bottom Water, and consequently, influences the large-scale ocean circulation. Here, we investigate the role of sub-ice-shelf melting in the formation and export of DSW using idealized simulations with an isopycnal ocean model (MOM6) coupled with a sea ice model (SIS2) and a thermodynamic active ice shelf. A set of experiments is conducted with variable horizontal grid resolutions (0.5, 1.0 and 2.0 km), ice shelf geometries and atmospheric forcing. In all simulations DSW is spontaneously formed in coastal polynyas due to the combined effect of the imposed atmospheric forcing and the ocean state. Our results show that sub-ice-shelf melting can significantly change the rate of dense shelf water outflows, highlighting the importance of this process to correctly represent bottom water formation.

Multiscale verification of water fluxes and states over Pan European river basins

NASA Astrophysics Data System (ADS)

Samaniego, Luis; Rakovec, Oldrich; Schaefer, David; Kumar, Rohini; Cuntz, Matthias; Mai, Juliane; Craven, John

2014-05-01

Developing the ability to predict the movement of water at regional scales with a spatial resolution from 1 to 5 km is one of grand challenges in land surface modelling. Coping with this grand challenge implies that land surface models (LSM) should be able to make reliable predictions across locations and/or scales other than those used for parameter estimation. Validating LSM only against integral basin response such as streamflow is a necessary but not a sufficient condition to warranty the appropriate partitioning of incoming precipitation and radiation into different water budget components. Extensive in-situ observations of state variables (e.g., soil moisture), on the contrary, are not feasible at regional scales. Remote sensing has been considered as the solution for this dilemma because they constitute a cost-effective source of information and provide a valuable insight about the spatio-temporal patterns of state variables. Their main disadvantage is their large uncertainty. The mesoscale hydrologic model (mHM 5.0 http://www.ufz.de/index.php?en=31389) is used in this study to estimate uncalibrated water fluxes and states and then to investigate which are the effects of conditioning this model with freely available multiple-scale data sets. The main characteristic of mHM is the treatment of the sub-grid variability of input variables and model parameters which clearly distinguishes this model from existing precipitation-runoff models or land surface models. It uses a Multiscale Parameter Regionalization (MPR) to account for the sub-grid variability and to avoid systematic re-calibration. Another key characteristic of mHM is that it can simultaneously estimate fluxes in nested-scales and/or in multiple basins keeping its global parameters (i.e., regionalization coefficients) unaltered across scales and basins. These key characteristics of the model would allow to assimilate disparate sources of information such as satellite data, streamflow gauging stations, and eddy covariance data at their native resolutions. To address these objectives, mHM was set up over more than 280 Pan-European river basins. This model was forced with the gridded EOBS data set (25x25 km2) obtained from the European Climate Assessment & Dataset projec. The required morphological data was derived from the FAO soil map (1:5,000,000), the SRTM DEM (500 m) and three CORINE land cover scenes (500 m). MODIS LAI (NASA) was used to estimate a dynamic LAI model for every land cover class. mHM simulations were obtained at 25 km spatial resolution for the period 1950-2012. The multi-scale verification of simulated water fluxes was carried out using observation data sets such as: latent heat flux obtained from more than 150 eddy flux stations (FLUXNET), streamflow in more than 250 gauging stations (GRDC), and the remotely sensed Earth's gravity field anomalies retrieved by the Gravity Recovery and Climate Experiment (GRACE) release 05 (Landerer and Swenson, 2012, WRR). The former are used a proxy of the total water storage anomalies in mHM. In Germany, over 1000 weakly groundwater stage stations were used to evaluate and/or condition groundwater level anomalies. mHM water storage anomalies simulated over Europe from 2003 to 2012 at monthly time step were compared with those of GRACE. Results lead to the conclusion that mHM water fluxes are robust since less than 25% of river basins exhibit Nash-Sutcliffe efficiencies (NSE) of 0.5 or less. Likewise, the soil moisture and groundwater anomalies, specially in severe drought years such as 2003, exhibit a large spatial correlation with those obtained from remotely sensed products. Comparison against observed latent heat indicates that the dynamics and magnitude of the simulated values were well captured by the model at most locations. In general, deficient model performance (NSE

Saptio-temporal complementarity of wind and solar power in India

NASA Astrophysics Data System (ADS)

Lolla, Savita; Baidya Roy, Somnath; Chowdhury, Sourangshu

2015-04-01

Wind and solar power are likely to be a part of the solution to the climate change problem. That is why they feature prominently in the energy policies of all industrial economies including India. One of the major hindrances that is preventing an explosive growth of wind and solar energy is the issue of intermittency. This is a major problem because in a rapidly moving economy, energy production must match the patterns of energy demand. Moreover, sudden increase and decrease in energy supply may destabilize the power grids leading to disruptions in power supply. In this work we explore if the patterns of variability in wind and solar energy availability can offset each other so that a constant supply can be guaranteed. As a first step, this work focuses on seasonal-scale variability for each of the 5 regional power transmission grids in India. Communication within each grid is better than communication between grids. Hence, it is assumed that the grids can switch sources relatively easily. Wind and solar resources are estimated using the MERRA Reanalysis data for the 1979-2013 period. Solar resources are calculated with a 20% conversion efficiency. Wind resources are estimated using a 2 MW turbine power curve. Total resources are obtained by optimizing location and number of wind/solar energy farms. Preliminary results show that the southern and western grids are more appropriate for cogeneration than the other grids. Many studies on wind-solar cogeneration have focused on temporal complementarity at local scale. However, this is one of the first studies to explore spatial complementarity over regional scales. This project may help accelerate renewable energy penetration in India by identifying regional grid(s) where the renewable energy intermittency problem can be minimized.

Upscaling the impact of convective overshooting (COV) through BRAMS: a continental and wet-season scale study of the water vapour (WV) budget in the tropical tropopause layer (TTL).

NASA Astrophysics Data System (ADS)

Behera, Abhinna; Rivière, Emmanuel; Marécal, Virginie; Rysman, Jean-François; Claud, Chantal; Burgalat, Jérémie

2017-04-01

The stratospheric water vapour (WV) has a conceding impact on the radiative and chemical budget of Earth's atmosphere. The convective overshooting (COV) at the tropics is well admitted for playing a role in transporting directly WV to the stratosphere. Nonetheless, its impact on the lower stratosphere is yet to be determined at global scale, as the satellite and other air-borne measurements are not of having fine enough resolution to quantify this impact at large scale. Therefore, efforts have been made to quantify the influence of COV over the WV budget in the tropical tropopause layer (TTL) through modelling. Our approach is to build two synthetic tropical wet-seasons; where one would be having only deep convection (DC) but no COV at all, and the second one would be having the COV, and in both cases the WV budget in the TTL would be estimated. Before that, a French-Brazilian TRO-pico campaign was carried out at Bauru, Brazil in order to understand the influence of COV on the WV budget in the TTL. The radio-sounding, and the small balloon-borne WV measurements from the campaign are being utilized to validate the model simulation. Brazilian version of Regional Atmospheric Modeling System (BRAMS) is used with a single grid system to simulate a WV variability in a wet-season. Grell's convective parameterization with ensemble closure, microphysics with double moment scheme and 7 types of hydrometeors are incorporated to simulate the WV variability for a wet-season at the tropics. The grid size of simulation is chosen to be 20 km x 20 km horizontally and from surface to 30 km altitude, so that there cannot be COV at all, only DC due to such a relatively coarse resolution. The European Centre for Medium-range Weather Forecasts (ECMWF) operational analyses data are used every 6 hours for grid initialization and boundary conditions, and grid center nudging. The simulation is carried out for a full wet-season (Nov 2012 - Mar 2013) at Brazilian scale, so that it would coincide with the TRO-pico campaign measurements. As of first step, we have already shown that, this model with only DC is well capable of producing key features of the TTL. Hence in the second step, keeping all the settings same in the model, a sub-grid scale process/parameterization is being developed in order to reproduce COV in the model. Then, we would be able to compare these two atmospheres, and it would describe quantitatively the impact of COV on the WV budget in the TTL at a continental scale. This on-going work reports about the further advancement done to introduce the COV parameterization in BRAMS by incorporating the information from satellite-borne and balloon-borne measurements. The preliminary results of the simulation with COV nudging, achieved till date of EGU assembly, will be presented.

Analysis of Surface Heterogeneity Effects with Mesoscale Terrestrial Modeling Platforms

NASA Astrophysics Data System (ADS)

Simmer, C.

2015-12-01

An improved understanding of the full variability in the weather and climate system is crucial for reducing the uncertainty in weather forecasting and climate prediction, and to aid policy makers to develop adaptation and mitigation strategies. A yet unknown part of uncertainty in the predictions from the numerical models is caused by the negligence of non-resolved land surface heterogeneity and the sub-surface dynamics and their potential impact on the state of the atmosphere. At the same time, mesoscale numerical models using finer horizontal grid resolution [O(1)km] can suffer from inconsistencies and neglected scale-dependencies in ABL parameterizations and non-resolved effects of integrated surface-subsurface lateral flow at this scale. Our present knowledge suggests large-eddy-simulation (LES) as an eventual solution to overcome the inadequacy of the physical parameterizations in the atmosphere in this transition scale, yet we are constrained by the computational resources, memory management, big-data, when using LES for regional domains. For the present, there is a need for scale-aware parameterizations not only in the atmosphere but also in the land surface and subsurface model components. In this study, we use the recently developed Terrestrial Systems Modeling Platform (TerrSysMP) as a numerical tool to analyze the uncertainty in the simulation of surface exchange fluxes and boundary layer circulations at grid resolutions of the order of 1km, and explore the sensitivity of the atmospheric boundary layer evolution and convective rainfall processes on land surface heterogeneity.

Smaller global and regional carbon emissions from gross land use change when considering sub-grid secondary land cohorts in a global dynamic vegetation model

NASA Astrophysics Data System (ADS)

Yue, Chao; Ciais, Philippe; Li, Wei

2018-02-01

Several modelling studies reported elevated carbon emissions from historical land use change (ELUC) by including bidirectional transitions on the sub-grid scale (termed gross land use change), dominated by shifting cultivation and other land turnover processes. However, most dynamic global vegetation models (DGVMs) that have implemented gross land use change either do not account for sub-grid secondary lands, or often have only one single secondary land tile over a model grid cell and thus cannot account for various rotation lengths in shifting cultivation and associated secondary forest age dynamics. Therefore, it remains uncertain how realistic the past ELUC estimations are and how estimated ELUC will differ between the two modelling approaches with and without multiple sub-grid secondary land cohorts - in particular secondary forest cohorts. Here we investigated historical ELUC over 1501-2005 by including sub-grid forest age dynamics in a DGVM. We run two simulations, one with no secondary forests (Sageless) and the other with sub-grid secondary forests of six age classes whose demography is driven by historical land use change (Sage). Estimated global ELUC for 1501-2005 is 176 Pg C in Sage compared to 197 Pg C in Sageless. The lower ELUC values in Sage arise mainly from shifting cultivation in the tropics under an assumed constant rotation length of 15 years, being 27 Pg C in Sage in contrast to 46 Pg C in Sageless. Estimated cumulative ELUC values from wood harvest in the Sage simulation (31 Pg C) are however slightly higher than Sageless (27 Pg C) when the model is forced by reconstructed harvested areas because secondary forests targeted in Sage for harvest priority are insufficient to meet the prescribed harvest area, leading to wood harvest being dominated by old primary forests. An alternative approach to quantify wood harvest ELUC, i.e. always harvesting the close-to-mature forests in both Sageless and Sage, yields similar values of 33 Pg C by both simulations. The lower ELUC from shifting cultivation in Sage simulations depends on the predefined forest clearing priority rules in the model and the assumed rotation length. A set of sensitivity model runs over Africa reveal that a longer rotation length over the historical period likely results in higher emissions. Our results highlight that although gross land use change as a former missing emission component is included by a growing number of DGVMs, its contribution to overall ELUC remains uncertain and tends to be overestimated when models ignore sub-grid secondary forests.

Radio-loud AGN Variability from Propagating Relativistic Jets

NASA Astrophysics Data System (ADS)

Li, Yutong; Schuh, Terance; Wiita, Paul J.

2018-06-01

The great majority of variable emission in radio-loud AGNs is understood to arise from the relativistic flows of plasma along two oppositely directed jets. We study this process using the Athena hydrodynamics code to simulate propagating three-dimensional relativistic jets for a wide range of input jet velocities and jet-to-ambient matter density ratios. We then focus on those simulations that remain essentially stable for extended distances (60-120 times the jet radius). Adopting results for the densities, pressures and velocities from these propagating simulations we estimate emissivities from each cell. The observed emissivity from each cell is strongly dependent upon its variable Doppler boosting factor, which depends upon the changing bulk velocities in those zones with respect to our viewing angle to the jet. We then sum the approximations to the fluxes from a large number of zones upstream of the primary reconfinement shock. The light curves so produced are similar to those of blazars, although turbulence on sub-grid scales is likely to be important for the variability on the shortest timescales.

Circulation and multiple-scale variability in the Southern California Bight

NASA Astrophysics Data System (ADS)

Dong, Changming; Idica, Eileen Y.; McWilliams, James C.

2009-09-01

The oceanic circulation in the Southern California Bight (SCB) is influenced by the large-scale California Current offshore, tropical remote forcing through the coastal wave guide alongshore, and local atmospheric forcing. The region is characterized by local complexity in the topography and coastline. All these factors engender variability in the circulation on interannual, seasonal, and intraseasonal time scales. This study applies the Regional Oceanic Modeling System (ROMS) to the SCB circulation and its multiple-scale variability. The model is configured in three levels of nested grids with the parent grid covering the whole US West Coast. The first child grid covers a large southern domain, and the third grid zooms in on the SCB region. The three horizontal grid resolutions are 20 km, 6.7 km, and 1 km, respectively. The external forcings are momentum, heat, and freshwater flux at the surface and adaptive nudging to gyre-scale SODA reanalysis fields at the boundaries. The momentum flux is from a three-hourly reanalysis mesoscale MM5 wind with a 6 km resolution for the finest grid in the SCB. The oceanic model starts in an equilibrium state from a multiple-year cyclical climatology run, and then it is integrated from years 1996 through 2003. In this paper, the 8-year simulation at the 1 km resolution is analyzed and assessed against extensive observational data: High-Frequency (HF) radar data, current meters, Acoustic Doppler Current Profilers (ADCP) data, hydrographic measurements, tide gauges, drifters, altimeters, and radiometers. The simulation shows that the domain-scale surface circulation in the SCB is characterized by the Southern California Cyclonic Gyre, comprised of the offshore equatorward California Current System and the onshore poleward Southern California Countercurrent. The simulation also exhibits three subdomain-scale, persistent ( i.e., standing), cyclonic eddies related to the local topography and wind forcing: the Santa Barbara Channel Eddy, the Central-SCB Eddy, and the Catalina-Clemente Eddy. Comparisons with observational data reveal that ROMS reproduces a realistic mean state of the SCB oceanic circulation, as well as its interannual (mainly as a local manifestation of an ENSO event), seasonal, and intraseasonal (eddy-scale) variations. We find high correlations of the wind curl with both the alongshore pressure gradient (APG) and the eddy kinetic energy level in their variations on time scales of seasons and longer. The geostrophic currents are much stronger than the wind-driven Ekman flows at the surface. The model exhibits intrinsic eddy variability with strong topographically related heterogeneity, westward-propagating Rossby waves, and poleward-propagating coastally-trapped waves (albeit with smaller amplitude than observed due to missing high-frequency variations in the southern boundary conditions).

Variability of interconnected wind plants: correlation length and its dependence on variability time scale

DOE PAGES

St. Martin, Clara M.; Lundquist, Julie K.; Handschy, Mark A.

2015-04-02

The variability in wind-generated electricity complicates the integration of this electricity into the electrical grid. This challenge steepens as the percentage of renewably-generated electricity on the grid grows, but variability can be reduced by exploiting geographic diversity: correlations between wind farms decrease as the separation between wind farms increases. However, how far is far enough to reduce variability? Grid management requires balancing production on various timescales, and so consideration of correlations reflective of those timescales can guide the appropriate spatial scales of geographic diversity grid integration. To answer 'how far is far enough,' we investigate the universal behavior of geographic diversity by exploring wind-speed correlations using three extensive datasets spanning continents, durations and time resolution. First, one year of five-minute wind power generation data from 29 wind farms span 1270 km across Southeastern Australia (Australian Energy Market Operator). Second, 45 years of hourly 10 m wind-speeds from 117 stations span 5000 km across Canada (National Climate Data Archive of Environment Canada). Finally, four years of five-minute wind-speeds from 14 meteorological towers span 350 km of the Northwestern US (Bonneville Power Administration). After removing diurnal cycles and seasonal trends from all datasets, we investigate dependence of correlation length on time scale by digitally high-pass filtering the data on 0.25–2000 h timescales and calculating correlations between sites for each high-pass filter cut-off. Correlations fall to zero with increasing station separation distance, but the characteristic correlation length varies with the high-pass filter applied: the higher the cut-off frequency, the smaller the station separation required to achieve de-correlation. Remarkable similarities between these three datasets reveal behavior that, if universal, could be particularly useful for grid management. For high-pass filter time constants shorter than about τ = 38 h, all datasets exhibit a correlation lengthmore » $$\\xi $$ that falls at least as fast as $${{\\tau }^{-1}}$$ . Since the inter-site separation needed for statistical independence falls for shorter time scales, higher-rate fluctuations can be effectively smoothed by aggregating wind plants over areas smaller than otherwise estimated.« less

Variability of interconnected wind plants: correlation length and its dependence on variability time scale

NASA Astrophysics Data System (ADS)

St. Martin, Clara M.; Lundquist, Julie K.; Handschy, Mark A.

2015-04-01

The variability in wind-generated electricity complicates the integration of this electricity into the electrical grid. This challenge steepens as the percentage of renewably-generated electricity on the grid grows, but variability can be reduced by exploiting geographic diversity: correlations between wind farms decrease as the separation between wind farms increases. But how far is far enough to reduce variability? Grid management requires balancing production on various timescales, and so consideration of correlations reflective of those timescales can guide the appropriate spatial scales of geographic diversity grid integration. To answer ‘how far is far enough,’ we investigate the universal behavior of geographic diversity by exploring wind-speed correlations using three extensive datasets spanning continents, durations and time resolution. First, one year of five-minute wind power generation data from 29 wind farms span 1270 km across Southeastern Australia (Australian Energy Market Operator). Second, 45 years of hourly 10 m wind-speeds from 117 stations span 5000 km across Canada (National Climate Data Archive of Environment Canada). Finally, four years of five-minute wind-speeds from 14 meteorological towers span 350 km of the Northwestern US (Bonneville Power Administration). After removing diurnal cycles and seasonal trends from all datasets, we investigate dependence of correlation length on time scale by digitally high-pass filtering the data on 0.25-2000 h timescales and calculating correlations between sites for each high-pass filter cut-off. Correlations fall to zero with increasing station separation distance, but the characteristic correlation length varies with the high-pass filter applied: the higher the cut-off frequency, the smaller the station separation required to achieve de-correlation. Remarkable similarities between these three datasets reveal behavior that, if universal, could be particularly useful for grid management. For high-pass filter time constants shorter than about τ = 38 h, all datasets exhibit a correlation length ξ that falls at least as fast as {{τ }-1} . Since the inter-site separation needed for statistical independence falls for shorter time scales, higher-rate fluctuations can be effectively smoothed by aggregating wind plants over areas smaller than otherwise estimated.

Simulating large-scale crop yield by using perturbed-parameter ensemble method

NASA Astrophysics Data System (ADS)

Iizumi, T.; Yokozawa, M.; Sakurai, G.; Nishimori, M.

2010-12-01

Toshichika Iizumi, Masayuki Yokozawa, Gen Sakurai, Motoki Nishimori Agro-Meteorology Division, National Institute for Agro-Environmental Sciences, Japan Abstract One of concerning issues of food security under changing climate is to predict the inter-annual variation of crop production induced by climate extremes and modulated climate. To secure food supply for growing world population, methodology that can accurately predict crop yield on a large scale is needed. However, for developing a process-based large-scale crop model with a scale of general circulation models (GCMs), 100 km in latitude and longitude, researchers encounter the difficulties in spatial heterogeneity of available information on crop production such as cultivated cultivars and management. This study proposed an ensemble-based simulation method that uses a process-based crop model and systematic parameter perturbation procedure, taking maize in U.S., China, and Brazil as examples. The crop model was developed modifying the fundamental structure of the Soil and Water Assessment Tool (SWAT) to incorporate the effect of heat stress on yield. We called the new model PRYSBI: the Process-based Regional-scale Yield Simulator with Bayesian Inference. The posterior probability density function (PDF) of 17 parameters, which represents the crop- and grid-specific features of the crop and its uncertainty under given data, was estimated by the Bayesian inversion analysis. We then take 1500 ensemble members of simulated yield values based on the parameter sets sampled from the posterior PDF to describe yearly changes of the yield, i.e. perturbed-parameter ensemble method. The ensemble median for 27 years (1980-2006) was compared with the data aggregated from the county yield. On a country scale, the ensemble median of the simulated yield showed a good correspondence with the reported yield: the Pearson’s correlation coefficient is over 0.6 for all countries. In contrast, on a grid scale, the correspondence is still high in most grids regardless of the countries. However, the model showed comparatively low reproducibility in the slope areas, such as around the Rocky Mountains in South Dakota, around the Great Xing'anling Mountains in Heilongjiang, and around the Brazilian Plateau. As there is a wide-ranging local climate conditions in the complex terrain, such as the slope of mountain, the GCM grid-scale weather inputs is likely one of major sources of error. The results of this study highlight the benefits of the perturbed-parameter ensemble method in simulating crop yield on a GCM grid scale: (1) the posterior PDF of parameter could quantify the uncertainty of parameter value of the crop model associated with the local crop production aspects; (2) the method can explicitly account for the uncertainty of parameter value in the crop model simulations; (3) the method achieve a Monte Carlo approximation of probability of sub-grid scale yield, accounting for the nonlinear response of crop yield to weather and management; (4) the method is therefore appropriate to aggregate the simulated sub-grid scale yields to a grid-scale yield and it may be a reason for high performance of the model in capturing inter-annual variation of yield.

Research into the influence of spatial variability and scale on the parameterization of hydrological processes

NASA Technical Reports Server (NTRS)

Wood, Eric F.

1993-01-01

The objectives of the research were as follows: (1) Extend the Representative Elementary Area (RE) concept, first proposed and developed in Wood et al, (1988), to the water balance fluxes of the interstorm period (redistribution, evapotranspiration and baseflow) necessary for the analysis of long-term water balance processes. (2) Derive spatially averaged water balance model equations for spatially variable soil, topography and vegetation, over A RANGE OF CLIMATES. This is a necessary step in our goal to derive consistent hydrologic results up to GCM grid scales necessary for global climate modeling. (3) Apply the above macroscale water balance equations with remotely sensed data and begin to explore the feasibility of parameterizing the water balance constitutive equations at GCM grid scale.

Downscaling of global climate change estimates to regional scales: An application to Iberian rainfall in wintertime

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

von Storch, H.; Zorita, E.; Cubasch, U.

A statistical strategy to deduct regional-scale features from climate general circulation model (GCM) simulations has been designed and tested. The main idea is to interrelate the characteristic patterns of observed simultaneous variations of regional climate parameters and of large-scale atmospheric flow using the canonical correlation technique. The large-scale North Atlantic sea level pressure (SLP) is related to the regional, variable, winter (DJF) mean Iberian Peninsula rainfall. The skill of the resulting statistical model is shown by reproducing, to a good approximation, the winter mean Iberian rainfall from 1900 to present from the observed North Atlantic mean SLP distributions. It ismore » shown that this observed relationship between these two variables is not well reproduced in the output of a general circulation model (GCM). The implications for Iberian rainfall changes as the response to increasing atmospheric greenhouse-gas concentrations simulated by two GCM experiments are examined with the proposed statistical model. In an instantaneous [open quotes]2 CO[sub 2][close quotes] doubling experiment, using the simulated change of the mean North Atlantic SLP field to predict Iberian rainfall yields, there is an insignificant increase of area-averaged rainfall of I mm/month, with maximum values of 4 mm/month in the northwest of the peninsula. In contrast, for the four GCM grid points representing the lberian Peninsula, the change is - 10 mm/month, with a minimum of - 19 mm/month in the southwest. In the second experiment, with the IPCC scenario A ([open quotes]business as usual[close quotes]) increase of CO[sub 2], the statistical-model results partially differ from the directly simulated rainfall changes: in the experimental range of 100 years, the area-averaged rainfall decreases by 7 mm/month (statistical model), and by 9 mm/month (GCM); at the same time the amplitude of the interdecadal variability is quite different. 17 refs., 10 figs.« less

Ensuring Safety of Navigation: A Three-Tiered Approach

NASA Astrophysics Data System (ADS)

Johnson, S. D.; Thompson, M.; Brazier, D.

2014-12-01

The primary responsibility of the Hydrographic Department at the Naval Oceanographic Office (NAVOCEANO) is to support US Navy surface and sub-surface Safety of Navigation (SoN) requirements. These requirements are interpreted, surveys are conducted, and accurate products are compiled and archived for future exploitation. For a number of years NAVOCEANO has employed a two-tiered data-basing structure to support SoN. The first tier (Data Warehouse, or DWH) provides access to the full-resolution sonar and lidar data. DWH preserves the original data such that any scale product can be built. The second tier (Digital Bathymetric Database - Variable resolution, or DBDB-V) served as the final archive for SoN chart scale, gridded products compiled from source bathymetry. DBDB-V has been incorporated into numerous DoD tactical decision aids and serves as the foundation bathymetry for ocean modeling. With the evolution of higher density survey systems and the addition of high-resolution gridded bathymetry product requirements, a two-tiered model did not provide an efficient solution for SoN. The two-tiered approach required scientists to exploit full-resolution data in order to build any higher resolution product. A new perspective on the archival and exploitation of source data was required. This new perspective has taken the form of a third tier, the Navigation Surface Database (NSDB). NSDB is an SQLite relational database populated with International Hydrographic Organization (IHO), S-102 compliant Bathymetric Attributed Grids (BAGs). BAGs archived within NSDB are developed at the highest resolution that the collection sensor system can support and contain nodal estimates for depth, uncertainty, separation values and metadata. Gridded surface analysis efforts culminate in the generation of the source resolution BAG files and their storage within NSDB. Exploitation of these resources eliminates the time and effort needed to re-grid and re-analyze native source file formats.

Evaluating penalized logistic regression models to predict Heat-Related Electric grid stress days

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

Bramer, L. M.; Rounds, J.; Burleyson, C. D.

Understanding the conditions associated with stress on the electricity grid is important in the development of contingency plans for maintaining reliability during periods when the grid is stressed. In this paper, heat-related grid stress and the relationship with weather conditions is examined using data from the eastern United States. Penalized logistic regression models were developed and applied to predict stress on the electric grid using weather data. The inclusion of other weather variables, such as precipitation, in addition to temperature improved model performance. Several candidate models and datasets were examined. A penalized logistic regression model fit at the operation-zone levelmore » was found to provide predictive value and interpretability. Additionally, the importance of different weather variables observed at different time scales were examined. Maximum temperature and precipitation were identified as important across all zones while the importance of other weather variables was zone specific. The methods presented in this work are extensible to other regions and can be used to aid in planning and development of the electrical grid.« less

Using Unsupervised Learning to Unlock the Potential of Hydrologic Similarity

NASA Astrophysics Data System (ADS)

Chaney, N.; Newman, A. J.

2017-12-01

By clustering environmental data into representative hydrologic response units (HRUs), hydrologic similarity aims to harness the covariance between a system's physical environment and its hydrologic response to create reduced-order models. This is the primary approach through which sub-grid hydrologic processes are represented in large-scale models (e.g., Earth System Models). Although the possibilities of hydrologic similarity are extensive, its practical implementations have been limited to 1-d bins of oversimplistic metrics of hydrologic response (e.g., topographic index)—this is a missed opportunity. In this presentation we will show how unsupervised learning is unlocking the potential of hydrologic similarity; clustering methods enable generalized frameworks to effectively and efficiently harness the petabytes of global environmental data to robustly characterize sub-grid heterogeneity in large-scale models. To illustrate the potential that unsupervised learning has towards advancing hydrologic similarity, we introduce a hierarchical clustering algorithm (HCA) that clusters very high resolution (30-100 meters) elevation, soil, climate, and land cover data to assemble a domain's representative HRUs. These HRUs are then used to parameterize the sub-grid heterogeneity in land surface models; for this study we use the GFDL LM4 model—the land component of the GFDL Earth System Model. To explore HCA and its impacts on the hydrologic system we use a ¼ grid cell in southeastern California as a test site. HCA is used to construct an ensemble of 9 different HRU configurations—each configuration has a different number of HRUs; for each ensemble member LM4 is run between 2002 and 2014 with a 26 year spinup. The analysis of the ensemble of model simulations show that: 1) clustering the high-dimensional environmental data space leads to a robust representation of the role of the physical environment in the coupled water, energy, and carbon cycles at a relatively low number of HRUs; 2) the reduced-order model with around 300 HRUs effectively reproduces the fully distributed model simulation (30 meters) with less than 1/1000 of computational expense; 3) assigning each grid cell of the fully distributed grid to an HRU via HCA enables novel visualization methods for large-scale models—this has significant implications for how these models are applied and evaluated. We will conclude by outlining the potential that this work has within operational prediction systems including numerical weather prediction, Earth System models, and Early Warning systems.

The Importance of Biotic vs. Abiotic Drivers of Local Plant Community Composition Along Regional Bioclimatic Gradients

PubMed Central

Klanderud, Kari; Vandvik, Vigdis; Goldberg, Deborah

2015-01-01

We assessed if the relative importance of biotic and abiotic factors for plant community composition differs along environmental gradients and between functional groups, and asked which implications this may have in a warmer and wetter future. The study location is a unique grid of sites spanning regional-scale temperature and precipitation gradients in boreal and alpine grasslands in southern Norway. Within each site we sampled vegetation and associated biotic and abiotic factors, and combined broad- and fine-scale ordination analyses to assess the relative explanatory power of these factors for species composition. Although the community responses to biotic and abiotic factors did not consistently change as predicted along the bioclimatic gradients, abiotic variables tended to explain a larger proportion of the variation in species composition towards colder sites, whereas biotic variables explained more towards warmer sites, supporting the stress gradient hypothesis. Significant interactions with precipitation suggest that biotic variables explained more towards wetter climates in the sub alpine and boreal sites, but more towards drier climates in the colder alpine. Thus, we predict that biotic interactions may become more important in alpine and boreal grasslands in a warmer future, although more winter precipitation may counteract this trend in oceanic alpine climates. Our results show that both local and regional scales analyses are needed to disentangle the local vegetation-environment relationships and their regional-scale drivers, and biotic interactions and precipitation must be included when predicting future species assemblages. PMID:26091266

The Importance of Biotic vs. Abiotic Drivers of Local Plant Community Composition Along Regional Bioclimatic Gradients.

PubMed

Klanderud, Kari; Vandvik, Vigdis; Goldberg, Deborah

2015-01-01

We assessed if the relative importance of biotic and abiotic factors for plant community composition differs along environmental gradients and between functional groups, and asked which implications this may have in a warmer and wetter future. The study location is a unique grid of sites spanning regional-scale temperature and precipitation gradients in boreal and alpine grasslands in southern Norway. Within each site we sampled vegetation and associated biotic and abiotic factors, and combined broad- and fine-scale ordination analyses to assess the relative explanatory power of these factors for species composition. Although the community responses to biotic and abiotic factors did not consistently change as predicted along the bioclimatic gradients, abiotic variables tended to explain a larger proportion of the variation in species composition towards colder sites, whereas biotic variables explained more towards warmer sites, supporting the stress gradient hypothesis. Significant interactions with precipitation suggest that biotic variables explained more towards wetter climates in the sub alpine and boreal sites, but more towards drier climates in the colder alpine. Thus, we predict that biotic interactions may become more important in alpine and boreal grasslands in a warmer future, although more winter precipitation may counteract this trend in oceanic alpine climates. Our results show that both local and regional scales analyses are needed to disentangle the local vegetation-environment relationships and their regional-scale drivers, and biotic interactions and precipitation must be included when predicting future species assemblages.

Validation of the RegCM4-Subgrid module for the high resolution climate simulation over Korea

NASA Astrophysics Data System (ADS)

Lee, C.; Im, E.; Chang, K.; Choi, Y.

2010-12-01

Given the discernable evidences of climate changes due to human activity, there is a growing demand for the reliable climate change scenario in response to future emission forcing. One of the most significant impacts of climate changes can be that on the hydrological process. Changes in the seasonality and the low and high rainfall extremes can influence the water balance of river basin, with several consequences for societies and ecosystems. In fact, recent studies have reported that East Asia including the Korean peninsula is regarded to be a highly vulnerability region under global warming, especially for water resources. As an attempt to accurately assess the impact of climate change over Korea, we developed the dynamical downscaling system using the RegCM4 with a mosaic-type parameterization of subgrid-scale topography and land use (Sub-BATS). The Sub-BATS system is composed of 20 km coarse-grid cell and 4 km sub-grid cell. Before a full climate change simulation is carried out, we performed the simulation spanning the 19-year periods (1989-2007) with the lateral boundary fields obtained from the ERA-Interim reanalysis. The Korean peninsula is characterized by narrow mountain systems surrounded by ocean, and covered by a relatively dense observational network (approximate 400 stations), which provides an excellent dataset to validate a finescale downscaled results over the region. The evaluation of simulated surface variables (e.g. temperature, precipitation, snow, runoff) shows the usefulness of the RegCM4-Subgrid module as a tool to produce fine scale climate information of surface processes for coupling with hydrological model over the Korean peninsula Acknowledgements This work was supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government(MEST) (No. 2009-0085533), and by the "Advanced research on industrial meteorology" and " Development of meteorological resources for green growth." of National Institute of Meteorological Research (NIMR), funded by the Korea Meteorological Administration(KMA).

Evaluation of CASL boiling model for DNB performance in full scale 5x5 fuel bundle with spacer grids

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

Kim, Seung Jun

As one of main tasks for FY17 CASL-THM activity, Evaluation study on applicability of the CASL baseline boiling model for 5x5 DNB application is conducted and the predictive capability of the DNB analysis is reported here. While the baseline CASL-boiling model (GEN- 1A) approach has been successfully implemented and validated with a single pipe application in the previous year’s task, the extended DNB validation for realistic sub-channels with detailed spacer grid configurations are tasked in FY17. The focus area of the current study is to demonstrate the robustness and feasibility of the CASL baseline boiling model for DNB performance inmore » a full 5x5 fuel bundle application. A quantitative evaluation of the DNB predictive capability is performed by comparing with corresponding experimental measurements (i.e. reference for the model validation). The reference data are provided from the Westinghouse Electricity Company (WEC). Two different grid configurations tested here include Non-Mixing Vane Grid (NMVG), and Mixing Vane Grid (MVG). Thorough validation studies with two sub-channel configurations are performed at a wide range of realistic PWR operational conditions.« less

A sub-grid, mixture-fraction-based thermodynamic equilibrium model for gas phase combustion in FIRETEC: development and results

Treesearch

M. M. Clark; T. H. Fletcher; R. R. Linn

2010-01-01

The chemical processes of gas phase combustion in wildland fires are complex and occur at length-scales that are not resolved in computational fluid dynamics (CFD) models of landscape-scale wildland fire. A new approach for modelling fire chemistry in HIGRAD/FIRETEC (a landscape-scale CFD wildfire model) applies a mixture– fraction model relying on thermodynamic...

Jessica Katz | NREL

Science.gov Websites

, Arizona State University (2006-2008) Featured Publications Katz, J.; Cochran, J. (2015). Integrating Variable Renewable Energy to the Grid: Key Issues. 2pp. NREL Report No. NREL/FS-6A20-63033. Katz, J .; Cochran, J. (2015). Scaling Up Renewable Energy Generation: Aligning Targets and Incentives with Grid

Variable-Resolution Ensemble Climatology Modeling of Sierra Nevada Snowpack within the Community Earth System Model (CESM)

NASA Astrophysics Data System (ADS)

Rhoades, A.; Ullrich, P. A.; Zarzycki, C. M.; Levy, M.; Taylor, M.

2014-12-01

Snowpack is crucial for the western USA, providing around 75% of the total fresh water supply (Cayan et al., 1996) and buffering against seasonal aridity impacts on agricultural, ecosystem, and urban water demands. The resilience of the California water system is largely dependent on natural stores provided by snowpack. This resilience has shown vulnerabilities due to anthropogenic global climate change. Historically, the northern Sierras showed a net decline of 50-75% in snow water equivalent (SWE) while the southern Sierras showed a net accumulation of 30% (Mote et al., 2005). Future trends of SWE highlight that western USA SWE may decline by 40-70% (Pierce and Cayan, 2013), snowfall may decrease by 25-40% (Pierce and Cayan, 2013), and more winter storms may tend towards rain rather than snow (Bales et al., 2006). The volatility of Sierran snowpack presents a need for scientific tools to help water managers and policy makers assess current and future trends. A burgeoning tool to analyze these trends comes in the form of variable-resolution global climate modeling (VRGCM). VRGCMs serve as a bridge between regional and global models and provide added resolution in areas of need, eliminate lateral boundary forcings, provide model runtime speed up, and utilize a common dynamical core, physics scheme and sub-grid scale parameterization package. A cubed-sphere variable-resolution grid with 25 km horizontal resolution over the western USA was developed for use in the Community Atmosphere Model (CAM) within the Community Earth System Model (CESM). A 25-year three-member ensemble climatology (1980-2005) is presented and major snowpack metrics such as SWE, snow depth, snow cover, and two-meter surface temperature are assessed. The ensemble simulation is also compared to observational, reanalysis, and WRF model datasets. The variable-resolution model provides a mechanism for reaching towards non-hydrostatic scales and simulations are currently being developed with refined nests of 12.5km resolution over California.

Spatial Distribution of Stony Desertification and Key Influencing Factors on Different Sampling Scales in Small Karst Watersheds

PubMed Central

Zhang, Zhenming; Zhou, Yunchao; Wang, Shijie

2018-01-01

Karst areas are typical ecologically fragile areas, and stony desertification has become the most serious ecological and economic problems in these areas worldwide as well as a source of disasters and poverty. A reasonable sampling scale is of great importance for research on soil science in karst areas. In this paper, the spatial distribution of stony desertification characteristics and its influencing factors in karst areas are studied at different sampling scales using a grid sampling method based on geographic information system (GIS) technology and geo-statistics. The rock exposure obtained through sampling over a 150 m × 150 m grid in the Houzhai River Basin was utilized as the original data, and five grid scales (300 m × 300 m, 450 m × 450 m, 600 m × 600 m, 750 m × 750 m, and 900 m × 900 m) were used as the subsample sets. The results show that the rock exposure does not vary substantially from one sampling scale to another, while the average values of the five subsamples all fluctuate around the average value of the entire set. As the sampling scale increases, the maximum value and the average value of the rock exposure gradually decrease, and there is a gradual increase in the coefficient of variability. At the scale of 150 m × 150 m, the areas of minor stony desertification, medium stony desertification, and major stony desertification in the Houzhai River Basin are 7.81 km2, 4.50 km2, and 1.87 km2, respectively. The spatial variability of stony desertification at small scales is influenced by many factors, and the variability at medium scales is jointly influenced by gradient, rock content, and rock exposure. At large scales, the spatial variability of stony desertification is mainly influenced by soil thickness and rock content. PMID:29652811

Spatial Distribution of Stony Desertification and Key Influencing Factors on Different Sampling Scales in Small Karst Watersheds.

PubMed

Zhang, Zhenming; Zhou, Yunchao; Wang, Shijie; Huang, Xianfei

2018-04-13

Karst areas are typical ecologically fragile areas, and stony desertification has become the most serious ecological and economic problems in these areas worldwide as well as a source of disasters and poverty. A reasonable sampling scale is of great importance for research on soil science in karst areas. In this paper, the spatial distribution of stony desertification characteristics and its influencing factors in karst areas are studied at different sampling scales using a grid sampling method based on geographic information system (GIS) technology and geo-statistics. The rock exposure obtained through sampling over a 150 m × 150 m grid in the Houzhai River Basin was utilized as the original data, and five grid scales (300 m × 300 m, 450 m × 450 m, 600 m × 600 m, 750 m × 750 m, and 900 m × 900 m) were used as the subsample sets. The results show that the rock exposure does not vary substantially from one sampling scale to another, while the average values of the five subsamples all fluctuate around the average value of the entire set. As the sampling scale increases, the maximum value and the average value of the rock exposure gradually decrease, and there is a gradual increase in the coefficient of variability. At the scale of 150 m × 150 m, the areas of minor stony desertification, medium stony desertification, and major stony desertification in the Houzhai River Basin are 7.81 km², 4.50 km², and 1.87 km², respectively. The spatial variability of stony desertification at small scales is influenced by many factors, and the variability at medium scales is jointly influenced by gradient, rock content, and rock exposure. At large scales, the spatial variability of stony desertification is mainly influenced by soil thickness and rock content.

Influence of sub-kilometer precipitation datasets on simulated snowpack and glacier winter balance in alpine terrain.

NASA Astrophysics Data System (ADS)

Vionnet, Vincent; Six, Delphine; Auger, Ludovic; Lafaysse, Matthieu; Quéno, Louis; Réveillet, Marion; Dombrowski-Etchevers, Ingrid; Thibert, Emmanuel; Dumont, Marie

2017-04-01

Capturing spatial and temporal variabilities of meteorological conditions at fine scale is necessary for modelling snowpack and glacier winter mass balance in alpine terrain. In particular, precipitation amount and phase are strongly influenced by the complex topography. In this study, we assess the impact of three sub-kilometer precipitation datasets (rainfall and snowfall) on distributed simulations of snowpack and glacier winter mass balance with the detailed snowpack model Crocus for winter 2011-2012. The different precipitation datasets at 500-m grid spacing over part of the French Alps (200*200 km2 area) are coming either from (i) the SAFRAN precipitation analysis specially developed for alpine terrain, or from (ii) operational outputs of the atmospheric model AROME at 2.5-km grid spacing downscaled to 500 m with fixed lapse rate or from (iii) a version of the atmospheric model AROME at 500-m grid spacing. Others atmospherics forcings (air temperature and humidity, incoming longwave and shortwave radiation, wind speed) are taken from the AROME simulations at 500-m grid spacing. These atmospheric forcings are firstly compared against a network of automatic weather stations. Results are analysed with respect to station location (valley, mid- and high-altitude). The spatial pattern of seasonal snowfall and its dependency with elevation is then analysed for the different precipitation datasets. Large differences between SAFRAN and the two versions of AROME are found at high-altitude. Finally, results of Crocus snowpack simulations are evaluated against (i) punctual in-situ measurements of snow depth and snow water equivalent, and (ii) maps of snow covered areas retrieved from optical satellite data (MODIS). Measurements of winter accumulation of six glaciers of the French Alps are also used and provide very valuable information on precipitation at high-altitude where the conventional observation network is scarce. This study illustrates the potential and limitations of high-resolution atmospheric models to drive simulations of snowpack and glacier winter mass balance in alpine terrain.

PBSM3D: A finite volume, scalar-transport blowing snow model for use with variable resolution meshes

NASA Astrophysics Data System (ADS)

Marsh, C.; Wayand, N. E.; Pomeroy, J. W.; Wheater, H. S.; Spiteri, R. J.

2017-12-01

Blowing snow redistribution results in heterogeneous snowcovers that are ubiquitous in cold, windswept environments. Capturing this spatial and temporal variability is important for melt and runoff simulations. Point scale blowing snow transport models are difficult to apply in fully distributed hydrological models due to landscape heterogeneity and complex wind fields. Many existing distributed snow transport models have empirical wind flow and/or simplified wind direction algorithms that perform poorly in calculating snow redistribution where there are divergent wind flows, sharp topography, and over large spatial extents. Herein, a steady-state scalar transport model is discretized using the finite volume method (FVM), using parameterizations from the Prairie Blowing Snow Model (PBSM). PBSM has been applied in hydrological response units and grids to prairie, arctic, glacier, and alpine terrain and shows a good capability to represent snow redistribution over complex terrain. The FVM discretization takes advantage of the variable resolution mesh in the Canadian Hydrological Model (CHM) to ensure efficient calculations over small and large spatial extents. Variable resolution unstructured meshes preserve surface heterogeneity but result in fewer computational elements versus high-resolution structured (raster) grids. Snowpack, soil moisture, and streamflow observations were used to evaluate CHM-modelled outputs in a sub-arctic and an alpine basin. Newly developed remotely sensed snowcover indices allowed for validation over large basins. CHM simulations of snow hydrology were improved by inclusion of the blowing snow model. The results demonstrate the key role of snow transport processes in creating pre-melt snowcover heterogeneity and therefore governing post-melt soil moisture and runoff generation dynamics.

Comparison of Two Grid Refinement Approaches for High Resolution Regional Climate Modeling: MPAS vs WRF

NASA Astrophysics Data System (ADS)

Leung, L.; Hagos, S. M.; Rauscher, S.; Ringler, T.

2012-12-01

This study compares two grid refinement approaches using global variable resolution model and nesting for high-resolution regional climate modeling. The global variable resolution model, Model for Prediction Across Scales (MPAS), and the limited area model, Weather Research and Forecasting (WRF) model, are compared in an idealized aqua-planet context with a focus on the spatial and temporal characteristics of tropical precipitation simulated by the models using the same physics package from the Community Atmosphere Model (CAM4). For MPAS, simulations have been performed with a quasi-uniform resolution global domain at coarse (1 degree) and high (0.25 degree) resolution, and a variable resolution domain with a high-resolution region at 0.25 degree configured inside a coarse resolution global domain at 1 degree resolution. Similarly, WRF has been configured to run on a coarse (1 degree) and high (0.25 degree) resolution tropical channel domain as well as a nested domain with a high-resolution region at 0.25 degree nested two-way inside the coarse resolution (1 degree) tropical channel. The variable resolution or nested simulations are compared against the high-resolution simulations that serve as virtual reality. Both MPAS and WRF simulate 20-day Kelvin waves propagating through the high-resolution domains fairly unaffected by the change in resolution. In addition, both models respond to increased resolution with enhanced precipitation. Grid refinement induces zonal asymmetry in precipitation (heating), accompanied by zonal anomalous Walker like circulations and standing Rossby wave signals. However, there are important differences between the anomalous patterns in MPAS and WRF due to differences in the grid refinement approaches and sensitivity of model physics to grid resolution. This study highlights the need for "scale aware" parameterizations in variable resolution and nested regional models.

Effect of particle size distribution on the hydrodynamics of dense CFB risers

NASA Astrophysics Data System (ADS)

Bakshi, Akhilesh; Khanna, Samir; Venuturumilli, Raj; Altantzis, Christos; Ghoniem, Ahmed

2015-11-01

Circulating Fluidized Beds (CFB) are favorable in the energy and chemical industries, due to their high efficiency. While accurate hydrodynamic modeling is essential for optimizing performance, most CFB riser simulations are performed assuming equally-sized solid particles, owing to limited computational resources. Even though this approach yields reasonable predictions, it neglects commonly observed experimental findings suggesting the strong effect of particle size distribution (psd) on the hydrodynamics and chemical conversion. Thus, this study is focused on the inclusion of discrete particle sizes to represent the psd and its effect on fluidization via 2D numerical simulations. The particle sizes and corresponding mass fluxes are obtained using experimental data in dense CFB riser while the modeling framework is described in Bakshi et al 2015. Simulations are conducted at two scales: (a) fine grid to resolve heterogeneous structures and (b) coarse grid using EMMS sub-grid modifications. Using suitable metrics which capture bed dynamics, this study provides insights into segregation and mixing of particles as well as highlights need for improved sub-grid models.

A Variable-Resolution Stretched-Grid General Circulation Model and Data Assimilation System with Multiple Areas of Interest: Studying the Anomalous Regional Climate Events of 1998

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence; Govindaraju, Ravi C.; Atlas, Robert (Technical Monitor)

2002-01-01

The new stretched-grid design with multiple (four) areas of interest, one at each global quadrant, is implemented into both a stretched-grid GCM (general circulation model) and a stretched-grid data assimilation system (DAS). The four areas of interest include: the U.S./Northern Mexico, the El Nino area/Central South America, India/China, and the Eastern Indian Ocean/Australia. Both the stretched-grid GCM and DAS annual (November 1997 through December 1998) integrations are performed with 50 km regional resolution. The efficient regional down-scaling to mesoscales is obtained for each of the four areas of interest while the consistent interactions between regional and global scales and the high quality of global circulation, are preserved. This is the advantage of the stretched-grid approach. The global variable resolution DAS incorporating the stretched-grid GCM has been developed and tested as an efficient tool for producing regional analyses and diagnostics with enhanced mesoscale resolution. The anomalous regional climate events of 1998 that occurred over the U.S., Mexico, South America, China, India, African Sahel, and Australia are investigated in both simulation and data assimilation modes. Tree assimilated products are also used, along with gauge precipitation data, for validating the simulation results. The obtained results show that the stretched-grid GCM and DAS are capable of producing realistic high quality simulated and assimilated products at mesoscale resolution for regional climate studies and applications.

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

NASA Astrophysics Data System (ADS)

Skamarock, W. C.

2015-12-01

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

The vertical dependence in the horizontal variability of salinity and temperature at the ocean surface

NASA Astrophysics Data System (ADS)

Asher, W.; Drushka, K.; Jessup, A. T.; Clark, D.

2016-02-01

Satellite-mounted microwave radiometers measure sea surface salinity (SSS) as an area-averaged quantity in the top centimeter of the ocean over the footprint of the instrument. If the horizontal variability in SSS is large inside this footprint, sub-grid-scale variability in SSS can affect comparison of the satellite-retrieved SSS with in situ measurements. Understanding the magnitude of horizontal variability in SSS over spatial scales that are relevant to the satellite measurements is therefore important. Horizontal variability of SSS at the ocean surface can be studied in situ using data recorded by thermosalinographs (TSGs) that sample water from a depth of a few meters. However, it is possible measurements made at this depth might underestimate the horizontal variability at the surface because salinity and temperature can become vertically stratified in a very near surface layer due to the effects of rain, solar heating, and evaporation. This vertical stratification could prevent horizontal gradients from propagating to the sampling depths of ship-mounted TSGs. This presentation will discuss measurements made using an underway salinity profiling system installed on the R/V Thomas Thompson that made continuous measurements of SSS and SST in the Pacific Ocean. The system samples at nominal depths of 2-m, 3-m, and 5-m, allowing the depth dependence of the horizontal variability in SSS and SST to be measured. Horizontal variability in SST is largest at low wind speeds during daytime, when a diurnal warm layer forms. In contrast, the diurnal signal in the variability of SSS was smaller with variability being slightly larger at night. When studied as a function of depth, the results show that over 100-km scales, the horizontal variability in both SSS and SST at a depth of 2 m is approximately a factor of 4 higher than the variability at 5 m.

New datasets for quantifying snow-vegetation-atmosphere interactions in boreal birch and conifer forests

NASA Astrophysics Data System (ADS)

Reid, T. D.; Essery, R.; Rutter, N.; Huntley, B.; Baxter, R.; Holden, R.; King, M.; Hancock, S.; Carle, J.

2012-12-01

Boreal forests exert a strong influence on weather and climate by modifying the surface energy and radiation balance. However, global climate and numerical weather prediction models use forest parameter values from simple look-up tables or maps that are derived from limited satellite data, on large grid scales. In reality, Arctic landscapes are inherently heterogeneous, with highly variable land cover types and structures on a variety of spatial scales. There is value in collecting detailed field data for different areas of vegetation cover, to assess the accuracy of large-scale assumptions. To address these issues, a consortium of researchers funded by the UK's Natural Environment Research Council have collected extensive data on radiation, meteorology, snow cover and canopy structure at two contrasting Arctic forest sites. The chosen study sites were an area of boreal birch forest near Abisko, Sweden in March/April 2011 and mixed conifer forest at Sodankylä, Finland in March/April 2012. At both sites, arrays comprising ten shortwave pyranometers and four longwave pyrgeometers were deployed for periods of up to 50 days, under forest plots of varying canopy structures and densities. In addition, downwelling longwave irradiance and global and diffuse shortwave irradiances were recorded at nearby open sites representing the top-of-canopy conditions. Meteorological data were recorded at all sub-canopy and open sites using automatic weather stations. Over the same periods, tree skin temperatures were measured on selected trees using contact thermocouples, infrared thermocouples and thermal imagery. Canopy structure was accurately quantified through manual surveys, extensive hemispherical photography and terrestrial laser scans of every study plot. Sub-canopy snow depth and snow water equivalent were measured on fine-scale grids at each study plot. Regular site maintenance ensured a high quality dataset covering the important Arctic spring period. The data have several applications, for example in forest ecology, canopy radiative transfer models, snow hydrological modelling, and land surface schemes, for a variety of canopy types from sparse, leafless birch to dense pine and spruce. The work also allows the comparison of modern, highly detailed methods such as laser scanning and thermal imagery with older, well-established data collection methods. By combining these data with airborne and satellite remote sensing data, snow-vegetation-atmosphere interactions could be estimated over a wide area of the heterogeneous boreal landscape. This could improve estimates of crucial parameters such as land surface albedo on the grid scales required for global or regional weather and climate models.

Merging Station Observations with Large-Scale Gridded Data to Improve Hydrological Predictions over Chile

NASA Astrophysics Data System (ADS)

Peng, L.; Sheffield, J.; Verbist, K. M. J.

2016-12-01

Hydrological predictions at regional-to-global scales are often hampered by the lack of meteorological forcing data. The use of large-scale gridded meteorological data is able to overcome this limitation, but these data are subject to regional biases and unrealistic values at local scale. This is especially challenging in regions such as Chile, where climate exhibits high spatial heterogeneity as a result of long latitude span and dramatic elevation changes. However, regional station-based observational datasets are not fully exploited and have the potential of constraining biases and spatial patterns. This study aims at adjusting precipitation and temperature estimates from the Princeton University global meteorological forcing (PGF) gridded dataset to improve hydrological simulations over Chile, by assimilating 982 gauges from the Dirección General de Aguas (DGA). To merge station data with the gridded dataset, we use a state-space estimation method to produce optimal gridded estimates, considering both the error of the station measurements and the gridded PGF product. The PGF daily precipitation, maximum and minimum temperature at 0.25° spatial resolution are adjusted for the period of 1979-2010. Precipitation and temperature gauges with long and continuous records (>70% temporal coverage) are selected, while the remaining stations are used for validation. The leave-one-out cross validation verifies the robustness of this data assimilation approach. The merged dataset is then used to force the Variable Infiltration Capacity (VIC) hydrological model over Chile at daily time step which are compared to the observations of streamflow. Our initial results show that the station-merged PGF precipitation effectively captures drizzle and the spatial pattern of storms. Overall the merged dataset has significant improvements compared to the original PGF with reduced biases and stronger inter-annual variability. The invariant spatial pattern of errors between the station data and the gridded product opens up the possibility of merging real-time satellite and intermittent gauge observations to produce more accurate real-time hydrological predictions.

On the sub-model errors of a generalized one-way coupling scheme for linking models at different scales

NASA Astrophysics Data System (ADS)

Zeng, Jicai; Zha, Yuanyuan; Zhang, Yonggen; Shi, Liangsheng; Zhu, Yan; Yang, Jinzhong

2017-11-01

Multi-scale modeling of the localized groundwater flow problems in a large-scale aquifer has been extensively investigated under the context of cost-benefit controversy. An alternative is to couple the parent and child models with different spatial and temporal scales, which may result in non-trivial sub-model errors in the local areas of interest. Basically, such errors in the child models originate from the deficiency in the coupling methods, as well as from the inadequacy in the spatial and temporal discretizations of the parent and child models. In this study, we investigate the sub-model errors within a generalized one-way coupling scheme given its numerical stability and efficiency, which enables more flexibility in choosing sub-models. To couple the models at different scales, the head solution at parent scale is delivered downward onto the child boundary nodes by means of the spatial and temporal head interpolation approaches. The efficiency of the coupling model is improved either by refining the grid or time step size in the parent and child models, or by carefully locating the sub-model boundary nodes. The temporal truncation errors in the sub-models can be significantly reduced by the adaptive local time-stepping scheme. The generalized one-way coupling scheme is promising to handle the multi-scale groundwater flow problems with complex stresses and heterogeneity.

Scaling effects on spring phenology detections from MODIS data at multiple spatial resolutions over the contiguous United States

NASA Astrophysics Data System (ADS)

Peng, Dailiang; Zhang, Xiaoyang; Zhang, Bing; Liu, Liangyun; Liu, Xinjie; Huete, Alfredo R.; Huang, Wenjiang; Wang, Siyuan; Luo, Shezhou; Zhang, Xiao; Zhang, Helin

2017-10-01

Land surface phenology (LSP) has been widely retrieved from satellite data at multiple spatial resolutions, but the spatial scaling effects on LSP detection are poorly understood. In this study, we collected enhanced vegetation index (EVI, 250 m) from collection 6 MOD13Q1 product over the contiguous United States (CONUS) in 2007 and 2008, and generated a set of multiple spatial resolution EVI data by resampling 250 m to 2 × 250 m and 3 × 250 m, 4 × 250 m, …, 35 × 250 m. These EVI time series were then used to detect the start of spring season (SOS) at various spatial resolutions. Further the SOS variation across scales was examined at each coarse resolution grid (35 × 250 m ≈ 8 km, refer to as reference grid) and ecoregion. Finally, the SOS scaling effects were associated with landscape fragment, proportion of primary land cover type, and spatial variability of seasonal greenness variation within each reference grid. The results revealed the influences of satellite spatial resolutions on SOS retrievals and the related impact factors. Specifically, SOS significantly varied lineally or logarithmically across scales although the relationship could be either positive or negative. The overall SOS values averaged from spatial resolutions between 250 m and 35 × 250 m at large ecosystem regions were generally similar with a difference less than 5 days, while the SOS values within the reference grid could differ greatly in some local areas. Moreover, the standard deviation of SOS across scales in the reference grid was less than 5 days in more than 70% of area over the CONUS, which was smaller in northeastern than in southern and western regions. The SOS scaling effect was significantly associated with heterogeneity of vegetation properties characterized using land landscape fragment, proportion of primary land cover type, and spatial variability of seasonal greenness variation, but the latter was the most important impact factor.

Inference of turbulence parameters from a ROMS simulation using the k-ε closure scheme

NASA Astrophysics Data System (ADS)

Thyng, Kristen M.; Riley, James J.; Thomson, Jim

2013-12-01

Comparisons between high resolution turbulence data from Admiralty Inlet, WA (USA), and a 65-meter horizontal grid resolution simulation using the hydrostatic ocean modelling code, Regional Ocean Modeling System (ROMS), show that the model's k-ε turbulence closure scheme performs reasonably well. Turbulent dissipation rates and Reynolds stresses agree within a factor of two, on average. Turbulent kinetic energy (TKE) also agrees within a factor of two, but only for motions within the observed inertial sub-range of frequencies (i.e., classic approximately isotropic turbulence). TKE spectra from the observations indicate that there is significant energy at lower frequencies than the inertial sub-range; these scales are not captured by the model closure scheme nor the model grid resolution. To account for scales not present in the model, the inertial sub-range is extrapolated to lower frequencies and then integrated to obtain an inferred, diagnostic total TKE, with improved agreement with the observed total TKE. The realistic behavior of the dissipation rate and Reynolds stress, combined with the adjusted total TKE, imply that ROMS simulations can be used to understand and predict spatial and temporal variations in turbulence. The results are suggested for application to siting tidal current turbines.

Using IKONOS Imagery to Estimate Surface Soil Property Variability in Two Alabama Physiographies

NASA Technical Reports Server (NTRS)

Sullivan, Dana; Shaw, Joey; Rickman, Doug

2005-01-01

Knowledge of surface soil properties is used to assess past erosion and predict erodibility, determine nutrient requirements, and assess surface texture for soil survey applications. This study was designed to evaluate high resolution IKONOS multispectral data as a soil- mapping tool. Imagery was acquired over conventionally tilled fields in the Coastal Plain and Tennessee Valley physiographic regions of Alabama. Acquisitions were designed to assess the impact of surface crusting, roughness and tillage on our ability to depict soil property variability. Soils consisted mostly of fine-loamy, kaolinitic, thermic Plinthic Kandiudults at the Coastal Plain site and fine, kaolinitic, thermic Rhodic Paleudults at the Tennessee Valley site. Soils were sampled in 0.20 ha grids to a depth of 15 cm and analyzed for % sand (0.05 - 2 mm), silt (0.002 -0.05 mm), clay (less than 0.002 mm), citrate dithionite extractable iron (Fe(sub d)) and soil organic carbon (SOC). Four methods of evaluating variability in soil attributes were evaluated: 1) kriging of soil attributes, 2) co-kriging with soil attributes and reflectance data, 3) multivariate regression based on the relationship between reflectance and soil properties, and 4) fuzzy c-means clustering of reflectance data. Results indicate that co-kriging with remotely sensed data improved field scale estimates of surface SOC and clay content compared to kriging and regression methods. Fuzzy c-means worked best using RS data acquired over freshly tilled fields, reducing soil property variability within soil zones compared to field scale soil property variability.

Water balance model for Kings Creek

NASA Technical Reports Server (NTRS)

Wood, Eric F.

1990-01-01

Particular attention is given to the spatial variability that affects the representation of water balance at the catchment scale in the context of macroscale water-balance modeling. Remotely sensed data are employed for parameterization, and the resulting model is developed so that subgrid spatial variability is preserved and therefore influences the grid-scale fluxes of the model. The model permits the quantitative evaluation of the surface-atmospheric interactions related to the large-scale hydrologic water balance.

Parameterization of Small-Scale Processes

DTIC Science & Technology

1989-09-01

1989, Honolulu, Hawaii !7 COSATI CODES 18 SUBJECT TERMS (Continue on reverse if necessary and identify by block number) FELD GROUP SIJB- GROUP general...detailed sensitivit. studies to assess the dependence of results on the edd\\ viscosities and diffusivities by a direct comparison with certain observations...better sub-grid scale parameterization is to mount a concerted s .arch for model fits to observations. These would require exhaustive sensitivity studies

Applying an economical scale-aware PDF-based turbulence closure model in NOAA NCEP GCMs

NASA Astrophysics Data System (ADS)

Belochitski, A.; Krueger, S. K.; Moorthi, S.; Bogenschutz, P.; Pincus, R.

2016-12-01

A novel unified representation of sub-grid scale (SGS) turbulence, cloudiness, and shallow convection is being implemented into the NOAA NCEP Global Forecasting System (GFS) general circulation model. The approach, known as Simplified High Order Closure (SHOC), is based on predicting a joint PDF of SGS thermodynamic variables and vertical velocity and using it to diagnose turbulent diffusion coefficients, SGS fluxes, condensation and cloudiness. Unlike other similar methods, only one new prognostic variable, turbulent kinetic energy (TKE), needs to be intoduced, making the technique computationally efficient.SHOC is now incorporated into a version of GFS, as well as into the next generation of the NCEP global model - NOAA Environmental Modeling System (NEMS). Turbulent diffusion coefficients computed by SHOC are now used in place of those produced by the boundary layer turbulence and shallow convection parameterizations. Large scale microphysics scheme is no longer used to calculate cloud fraction or the large-scale condensation/deposition. Instead, SHOC provides these variables. Radiative transfer parameterization uses cloudiness computed by SHOC.Outstanding problems include high level tropical cloud fraction being too high in SHOC runs, possibly related to the interaction of SHOC with condensate detrained from deep convection.Future work will consist of evaluating model performance and tuning the physics if necessary, by performing medium-range NWP forecasts with prescribed initial conditions, and AMIP-type climate tests with prescribed SSTs. Depending on the results, the model will be tuned or parameterizations modified. Next, SHOC will be implemented in the NCEP CFS, and tuned and evaluated for climate applications - seasonal prediction and long coupled climate runs. Impact of new physics on ENSO, MJO, ISO, monsoon variability, etc will be examined.

Amelioration de la qualite d'energie d'un systeme de conversion d'energie eolienne a base de machine asynchrone a double alimentation et connecte au reseau electrique =

NASA Astrophysics Data System (ADS)

Abderrahim, Iheb

Wind power generation has grown strongly in the last decade. This results in the development of Wind Energy Conversion System WECS at the levels of modeling and electrical control. Modern WECS operate at varying wind speeds and are equipped with synchronous and asynchronous generators. Among these generators, the Doubly-Fed Induction Generator (DFIG) offers several advantages and capabilities of active and reactive power in four quadrants. WECS based DFIG also causes less conversion costs and minimum energy losses compared with a WECS based on a synchronous generator powered entirely by full scale of power converters. The connection of such a system to the electrical distribution network involves bidirectional operation of networks. This is clearly established in sub and super synchronous operating modes of DFIG. The grid provides the active power to the rotor of DFIG in sub synchronous operating mode and receives the active power of the rotor in super synchronous operating mode of DFIG. Energy quality is thus of major importance during the integration of wind power to the grid. Poor wave quality can affect network stability and could even cause major problems and consequences. This is even more critical where non-linear loads such as the switching power supplies and variable speed drives, are connected to the grid. The idea of this research work is how to mitigate the problems associated with the wave quality while ensuring better implementation of DFIG so that the whole of WECS remains insensitive to external disturbances and parametric variations. The Grid Side Converter (GSC) must be able to compensate harmonics, current unbalance and reactive power injected by a nonlinear three-phase unbalanced load connected to the grid. In addition to these innovative features to improve the conditions of operation of the grid, it provides also the power flow during different modes of operation of the DFIG. It is considered a simple, efficient and cost competitive solution by saving the use of other power equipment. At the same time, the energy efficiency of wind power conversion chain should be improved by extracting the MPPT. Searching allows us to select vector control and control in synchronous reference to achieve these objectives. WECS based DFIG is simulated in MATLAB SIMULINK in the presence of a non-linear balanced and unbalanced three-phase load.

Assessment of zero-equation SGS models for simulating indoor environment

NASA Astrophysics Data System (ADS)

Taghinia, Javad; Rahman, Md Mizanur; Tse, Tim K. T.

2016-12-01

The understanding of air-flow in enclosed spaces plays a key role to designing ventilation systems and indoor environment. The computational fluid dynamics aspects dictate that the large eddy simulation (LES) offers a subtle means to analyze complex flows with recirculation and streamline curvature effects, providing more robust and accurate details than those of Reynolds-averaged Navier-Stokes simulations. This work assesses the performance of two zero-equation sub-grid scale models: the Rahman-Agarwal-Siikonen-Taghinia (RAST) model with a single grid-filter and the dynamic Smagorinsky model with grid-filter and test-filter scales. This in turn allows a cross-comparison of the effect of two different LES methods in simulating indoor air-flows with forced and mixed (natural + forced) convection. A better performance against experiments is indicated with the RAST model in wall-bounded non-equilibrium indoor air-flows; this is due to its sensitivity toward both the shear and vorticity parameters.

Modelling Pesticide Leaching At Column, Field and Catchment Scales I. Analysis of Soil Variability At Field and Catchment Scales

NASA Astrophysics Data System (ADS)

Gärdenäs, A.; Jarvis, N.; Alavi, G.

The spatial variability of soil characteristics was studied in a small agricultural catch- ment (Vemmenhög, 9 km2) at the field and catchment scales. This analysis serves as a basis for assumptions concerning upscaling approaches used to model pesticide leaching from the catchment with the MACRO model (Jarvis et al., this meeting). The work focused on the spatial variability of two key soil properties for pesticide fate in soil, organic carbon and clay content. The Vemmenhög catchment (9 km2) is formed in a glacial till deposit in southernmost Sweden. The landscape is undulating (30 - 65 m a.s.l.) and 95 % of the area is used for crop production (winter rape, winter wheat, sugar beet and spring barley). The climate is warm temperate. Soil samples for or- ganic C and texture were taken on a small regular grid at Näsby Farm, (144 m x 144 m, sampling distance: 6-24 m, 77 points) and on an irregular large grid covering the whole catchment (sampling distance: 333 m, 46 points). At the field scale, it could be shown that the organic C content was strongly related to landscape position and height (R2= 73 %, p < 0.001, n=50). The organic C content of hollows in the landscape is so high that they contribute little to the total loss of pesticides (Jarvis et al., this meeting). Clay content is also related to landscape position, being larger at the hilltop locations resulting in lower near-saturated hydraulic conductivity. Hence, macropore flow can be expected to be more pronounced (see also Roulier & Jarvis, this meeting). The variability in organic C was similar for the field and catchment grids, which made it possible to krige the organic C content of the whole catchment using data from both grids and an uneven lag distance.

Addressing sub-scan variability of tundra snow properties in ground-based Ku- and X-band scatterometer observations

NASA Astrophysics Data System (ADS)

King, J. M.; Kasurak, A.; Kelly, R. E.; Duguay, C. R.; Derksen, C.; Rutter, N.; Sandells, M.; Watts, T.

2012-12-01

During the winter of 2010-2011 ground-based Ku- (17.2 GHz) and X-band (9.6 GHz) scatterometers were deployed near Churchill, Manitoba, Canada to evaluate the potential for dual-frequency observation of tundra snow properties. Field-based scatterometer observations when combined with in-situ snowpack properties and physically based models, provide the means necessary to develop and evaluate local scale property retrievals. To form meaningful analysis of the observed physical interaction space, potential sources of bias and error in the observed backscatter must be identified and quantified. This paper explores variation in observed Ku- and X-band backscatter in relation to the physical complexities of shallow tundra snow whose properties evolve at scales smaller than the observing instrument. The University of Waterloo scatterometer (UW-Scat) integrates observations over wide azimuth sweeps, several meters in length, to minimize errors resulting from radar fade and poor signal-to-noise ratios. Under ideal conditions, an assumption is made that the observed snow target is homogeneous. Despite an often-outward appearance of homogeneity, topographic elements of the Canadian open tundra produce significant local scale variability in snow properties, including snow water equivalent (SWE). Snow at open tundra sites observed during this campaign was found to vary by as much as 20 cm in depth and 40 mm in SWE within the scatterometer field of view. Previous studies suggest that changes in snow properties on this order will produce significant variation in backscatter, potentially introducing bias into products used for analysis. To assess the influence of sub-scan variability, extensive snow surveys were completed within the scatterometer field of view immediately after each scan at 32 sites. A standardized sampling protocol captured a grid of geo-located measurements, characterizing the horizontal variability of bulk properties including depth, density, and SWE. Based upon these measurements, continuous surfaces were generated to represent the observed snow target. Two snow pits were also completed within the field of view, quantifying vertical variability in density, permittivity, temperature, grain size, and stratigraphy. A new post-processing method is applied to divide the previously aggregated scatterometer observations into smaller sub-sets, which are then co-located with the physical snow observations. Sub-scan backscatter coefficients and their relationship to tundra snowpack parameters are then explored. The results presented here provide quantitative methods relevant to the radar observation science of snow and, therefore, to potential future space-borne missions such as the Cold Regions Hydrology High-resolution Observatory (CoReH2O), a candidate European Space Agency Earth Explorer mission. Moreover, this paper provides guidelines for future studies exploring ground-based scatterometer observations of tundra snow.

A spatial classification and database for management, research, and policy making: The Great Lakes aquatic habitat framework

USGS Publications Warehouse

Wang, Lizhu; Riseng, Catherine M.; Mason, Lacey; Werhrly, Kevin; Rutherford, Edward; McKenna, James E.; Castiglione, Chris; Johnson, Lucinda B.; Infante, Dana M.; Sowa, Scott P.; Robertson, Mike; Schaeffer, Jeff; Khoury, Mary; Gaiot, John; Hollenhurst, Tom; Brooks, Colin N.; Coscarelli, Mark

2015-01-01

Managing the world's largest and most complex freshwater ecosystem, the Laurentian Great Lakes, requires a spatially hierarchical basin-wide database of ecological and socioeconomic information that is comparable across the region. To meet such a need, we developed a spatial classification framework and database — Great Lakes Aquatic Habitat Framework (GLAHF). GLAHF consists of catchments, coastal terrestrial, coastal margin, nearshore, and offshore zones that encompass the entire Great Lakes Basin. The catchments captured in the database as river pour points or coastline segments are attributed with data known to influence physicochemical and biological characteristics of the lakes from the catchments. The coastal terrestrial zone consists of 30-m grid cells attributed with data from the terrestrial region that has direct connection with the lakes. The coastal margin and nearshore zones consist of 30-m grid cells attributed with data describing the coastline conditions, coastal human disturbances, and moderately to highly variable physicochemical and biological characteristics. The offshore zone consists of 1.8-km grid cells attributed with data that are spatially less variable compared with the other aquatic zones. These spatial classification zones and their associated data are nested within lake sub-basins and political boundaries and allow the synthesis of information from grid cells to classification zones, within and among political boundaries, lake sub-basins, Great Lakes, or within the entire Great Lakes Basin. This spatially structured database could help the development of basin-wide management plans, prioritize locations for funding and specific management actions, track protection and restoration progress, and conduct research for science-based decision making.

More reliable forecasts with less precise computations: a fast-track route to cloud-resolved weather and climate simulators?

PubMed Central

Palmer, T. N.

2014-01-01

This paper sets out a new methodological approach to solving the equations for simulating and predicting weather and climate. In this approach, the conventionally hard boundary between the dynamical core and the sub-grid parametrizations is blurred. This approach is motivated by the relatively shallow power-law spectrum for atmospheric energy on scales of hundreds of kilometres and less. It is first argued that, because of this, the closure schemes for weather and climate simulators should be based on stochastic–dynamic systems rather than deterministic formulae. Second, as high-wavenumber elements of the dynamical core will necessarily inherit this stochasticity during time integration, it is argued that the dynamical core will be significantly over-engineered if all computations, regardless of scale, are performed completely deterministically and if all variables are represented with maximum numerical precision (in practice using double-precision floating-point numbers). As the era of exascale computing is approached, an energy- and computationally efficient approach to cloud-resolved weather and climate simulation is described where determinism and numerical precision are focused on the largest scales only. PMID:24842038

More reliable forecasts with less precise computations: a fast-track route to cloud-resolved weather and climate simulators?

PubMed

Palmer, T N

2014-06-28

This paper sets out a new methodological approach to solving the equations for simulating and predicting weather and climate. In this approach, the conventionally hard boundary between the dynamical core and the sub-grid parametrizations is blurred. This approach is motivated by the relatively shallow power-law spectrum for atmospheric energy on scales of hundreds of kilometres and less. It is first argued that, because of this, the closure schemes for weather and climate simulators should be based on stochastic-dynamic systems rather than deterministic formulae. Second, as high-wavenumber elements of the dynamical core will necessarily inherit this stochasticity during time integration, it is argued that the dynamical core will be significantly over-engineered if all computations, regardless of scale, are performed completely deterministically and if all variables are represented with maximum numerical precision (in practice using double-precision floating-point numbers). As the era of exascale computing is approached, an energy- and computationally efficient approach to cloud-resolved weather and climate simulation is described where determinism and numerical precision are focused on the largest scales only.

Statistical downscaling of mean temperature, maximum temperature, and minimum temperature on the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Jiang, L.

2017-12-01

Climate change is considered to be one of the greatest environmental threats. Global climate models (GCMs) are the primary tool used for studying climate change. However, GCMs are limited because of their coarse spatial resolution and inability to resolve important sub-grid scale features such as terrain and clouds. Statistical downscaling methods can be used to downscale large-scale variables to local-scale. In this study, we assess the applicability of the Statistical Downscaling Model (SDSM) in downscaling the outputs from Beijing Normal University Earth System Model (BNU-ESM). The study focus on the the Loess Plateau, China, and the variables for downscaling include daily mean temperature (TMEAN), maximum temperature (TMAX) and minimum temperature (TMIN). The results show that SDSM performs well for these three climatic variables on the Loess Plateau. After downscaling, the root mean square errors for TMEAN, TMAX, TMIN for BNU-ESM were reduced by 70.9%, 75.1%, and 67.2%, respectively. All the rates of change in TMEAN, TMAX and TMIN during the 21st century decreased after SDSM downscaling. We also show that SDSM can effectively reduce uncertainty, compared with the raw model outputs. TMEAN uncertainty was reduced by 27.1%, 26.8%, and 16.3% for the future scenarios of RCP 2.6, RCP 4.5 and RCP 8.5, respectively. The corresponding reductions in uncertainty were 23.6%, 30.7%, and 18.7% for TMAX; 37.6%, 31.8%, and 23.2% for TMIN.

Decoding the spatial signatures of multi-scale climate variability - a climate network perspective

NASA Astrophysics Data System (ADS)

Donner, R. V.; Jajcay, N.; Wiedermann, M.; Ekhtiari, N.; Palus, M.

2017-12-01

During the last years, the application of complex networks as a versatile tool for analyzing complex spatio-temporal data has gained increasing interest. Establishing this approach as a new paradigm in climatology has already provided valuable insights into key spatio-temporal climate variability patterns across scales, including novel perspectives on the dynamics of the El Nino Southern Oscillation or the emergence of extreme precipitation patterns in monsoonal regions. In this work, we report first attempts to employ network analysis for disentangling multi-scale climate variability. Specifically, we introduce the concept of scale-specific climate networks, which comprises a sequence of networks representing the statistical association structure between variations at distinct time scales. For this purpose, we consider global surface air temperature reanalysis data and subject the corresponding time series at each grid point to a complex-valued continuous wavelet transform. From this time-scale decomposition, we obtain three types of signals per grid point and scale - amplitude, phase and reconstructed signal, the statistical similarity of which is then represented by three complex networks associated with each scale. We provide a detailed analysis of the resulting connectivity patterns reflecting the spatial organization of climate variability at each chosen time-scale. Global network characteristics like transitivity or network entropy are shown to provide a new view on the (global average) relevance of different time scales in climate dynamics. Beyond expected trends originating from the increasing smoothness of fluctuations at longer scales, network-based statistics reveal different degrees of fragmentation of spatial co-variability patterns at different scales and zonal shifts among the key players of climate variability from tropically to extra-tropically dominated patterns when moving from inter-annual to decadal scales and beyond. The obtained results demonstrate the potential usefulness of systematically exploiting scale-specific climate networks, whose general patterns are in line with existing climatological knowledge, but provide vast opportunities for further quantifications at local, regional and global scales that are yet to be explored.

CHARACTERISTIC LENGTH SCALE OF INPUT DATA IN DISTRIBUTED MODELS: IMPLICATIONS FOR MODELING GRID SIZE. (R824784)

EPA Science Inventory

The appropriate spatial scale for a distributed energy balance model was investigated by: (a) determining the scale of variability associated with the remotely sensed and GIS-generated model input data; and (b) examining the effects of input data spatial aggregation on model resp...

A Stochastic Model of Space-Time Variability of Mesoscale Rainfall: Statistics of Spatial Averages

NASA Technical Reports Server (NTRS)

Kundu, Prasun K.; Bell, Thomas L.

2003-01-01

A characteristic feature of rainfall statistics is that they depend on the space and time scales over which rain data are averaged. A previously developed spectral model of rain statistics that is designed to capture this property, predicts power law scaling behavior for the second moment statistics of area-averaged rain rate on the averaging length scale L as L right arrow 0. In the present work a more efficient method of estimating the model parameters is presented, and used to fit the model to the statistics of area-averaged rain rate derived from gridded radar precipitation data from TOGA COARE. Statistical properties of the data and the model predictions are compared over a wide range of averaging scales. An extension of the spectral model scaling relations to describe the dependence of the average fraction of grid boxes within an area containing nonzero rain (the "rainy area fraction") on the grid scale L is also explored.

Spatio-Temporal Variability of Groundwater Storage in India

NASA Technical Reports Server (NTRS)

Bhanja, Soumendra; Rodell, Matthew; Li, Bailing; Mukherjee, Abhijit

2016-01-01

Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Ground water storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent).In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.

Spatio-temporal variability of groundwater storage in India.

PubMed

Bhanja, Soumendra N; Rodell, Matthew; Li, Bailing; Mukherjee, Abhijit

2017-01-01

Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Groundwater storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent). In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.

Enhanced light extraction from organic light-emitting devices using a sub-anode grid (Presentation Recording)

NASA Astrophysics Data System (ADS)

Qu, Yue; Slootsky, Michael; Forrest, Stephen

2015-10-01

We demonstrate a method for extracting waveguided light trapped in the organic and indium tin oxide layers of bottom emission organic light emitting devices (OLEDs) using a patterned planar grid layer (sub-anode grid) between the anode and the substrate. The scattering layer consists of two transparent materials with different refractive indices on a period sufficiently large to avoid diffraction and other unwanted wavelength-dependent effects. The position of the sub-anode grid outside of the OLED active region allows complete freedom in varying its dimensions and materials from which it is made without impacting the electrical characteristics of the device itself. Full wave electromagnetic simulation is used to study the efficiency dependence on refractive indices and geometric parameters of the grid. We show the fabrication process and characterization of OLEDs with two different grids: a buried sub-anode grid consisting of two dielectric materials, and an air sub-anode grid consisting of a dielectric material and gridline voids. Using a sub-anode grid, substrate plus air modes quantum efficiency of an OLED is enhanced from (33+/-2)% to (40+/-2)%, resulting in an increase in external quantum efficiency from (14+/-1)% to (18+/-1)%, with identical electrical characteristics to that of a conventional device. By varying the thickness of the electron transport layer (ETL) of sub-anode grid OLEDs, we find that all power launched into the waveguide modes is scattered into substrate. We also demonstrate a sub-anode grid combined with a thick ETL significantly reduces surface plasmon polaritons, and results in an increase in substrate plus air modes by a >50% compared with a conventional OLED. The wavelength, viewing angle and molecular orientational independence provided by this approach make this an attractive and general solution to the problem of extracting waveguided light and reducing plasmon losses in OLEDs.

A machine learning approach for efficient uncertainty quantification using multiscale methods

NASA Astrophysics Data System (ADS)

Chan, Shing; Elsheikh, Ahmed H.

2018-02-01

Several multiscale methods account for sub-grid scale features using coarse scale basis functions. For example, in the Multiscale Finite Volume method the coarse scale basis functions are obtained by solving a set of local problems over dual-grid cells. We introduce a data-driven approach for the estimation of these coarse scale basis functions. Specifically, we employ a neural network predictor fitted using a set of solution samples from which it learns to generate subsequent basis functions at a lower computational cost than solving the local problems. The computational advantage of this approach is realized for uncertainty quantification tasks where a large number of realizations has to be evaluated. We attribute the ability to learn these basis functions to the modularity of the local problems and the redundancy of the permeability patches between samples. The proposed method is evaluated on elliptic problems yielding very promising results.

Aspects on HTS applications in confined power grids

NASA Astrophysics Data System (ADS)

Arndt, T.; Grundmann, J.; Kuhnert, A.; Kummeth, P.; Nick, W.; Oomen, M.; Schacherer, C.; Schmidt, W.

2014-12-01

In an increasing number of electric power grids the share of distributed energy generation is also increasing. The grids have to cope with a considerable change of power flow, which has an impact on the optimum topology of the grids and sub-grids (high-voltage, medium-voltage and low-voltage sub-grids) and the size of quasi-autonomous grid sections. Furthermore the stability of grids is influenced by its size. Thus special benefits of HTS applications in the power grid might become most visible in confined power grids.

Evapotranspiration and cloud variability at regional sub-grid scales

NASA Astrophysics Data System (ADS)

Vila-Guerau de Arellano, Jordi; Sikma, Martin; Pedruzo-Bagazgoitia, Xabier; van Heerwaarden, Chiel; Hartogensis, Oscar; Ouwersloot, Huug

2017-04-01

In regional and global models uncertainties arise due to our incomplete understanding of the coupling between biochemical and physical processes. Representing their impact depends on our ability to calculate these processes using physically sound parameterizations, since they are unresolved at scales smaller than the grid size. More specifically over land, the coupling between evapotranspiration, turbulent transport of heat and moisture, and clouds lacks a combined representation to take these sub-grid scales interactions into account. Our approach is based on understanding how radiation, surface exchange, turbulent transport and moist convection are interacting from the leaf- to the cloud scale. We therefore place special emphasis on plant stomatal aperture as the main regulator of CO2-assimilation and water transpiration, a key source of moisture source to the atmosphere. Plant functionality is critically modulated by interactions with atmospheric conditions occurring at very short spatiotemporal scales such as cloud radiation perturbations or water vapour turbulent fluctuations. By explicitly resolving these processes, the LES (large-eddy simulation) technique is enabling us to characterize and better understand the interactions between canopies and the local atmosphere. This includes the adaption time of vegetation to rapid changes in atmospheric conditions driven by turbulence or the presence of cumulus clouds. Our LES experiments are based on explicitly coupling the diurnal atmospheric dynamics to a plant physiology model. Our general hypothesis is that different partitioning of direct and diffuse radiation leads to different responses of the vegetation. As a result there are changes in the water use efficiencies and shifts in the partitioning of sensible and latent heat fluxes under the presence of clouds. Our presentation is as follows. First, we discuss the ability of LES to reproduce the surface energy balance including photosynthesis and CO2 soil respiration coupled to the dynamics of a convective boundary layer. LES results are compared with a complete set of surface and upper-air meteorological and carbon-dioxide observations gathered during a representative day at the 213-meter meteorological tall tower at Cabauw. Second, we perform systematic numerical experiments under a wide range of background wind conditions and stomatal aperture response time. Our analysis unravel how thin clouds, characterized by lower values of the cloud optical depth, have a different impact on evapotranspiration compared to thick clouds due to differences in the partitioning between direct and diffuse radiation at canopy level. Related to this detailed simulation, we discuss how new instrumental techniques, e.g. scintillometery, enable us to obtain new observational insight of the coupling between clouds and vegetation. We will close the presentation with open questions regarding the need to include parameterizations for these interactions at short spatiotemporal scales in regional or climate models.

Bias correction of surface downwelling longwave and shortwave radiation for the EWEMBI dataset

NASA Astrophysics Data System (ADS)

Lange, Stefan

2018-05-01

Many meteorological forcing datasets include bias-corrected surface downwelling longwave and shortwave radiation (rlds and rsds). Methods used for such bias corrections range from multi-year monthly mean value scaling to quantile mapping at the daily timescale. An additional downscaling is necessary if the data to be corrected have a higher spatial resolution than the observational data used to determine the biases. This was the case when EartH2Observe (E2OBS; Calton et al., 2016) rlds and rsds were bias-corrected using more coarsely resolved Surface Radiation Budget (SRB; Stackhouse Jr. et al., 2011) data for the production of the meteorological forcing dataset EWEMBI (Lange, 2016). This article systematically compares various parametric quantile mapping methods designed specifically for this purpose, including those used for the production of EWEMBI rlds and rsds. The methods vary in the timescale at which they operate, in their way of accounting for physical upper radiation limits, and in their approach to bridging the spatial resolution gap between E2OBS and SRB. It is shown how temporal and spatial variability deflation related to bilinear interpolation and other deterministic downscaling approaches can be overcome by downscaling the target statistics of quantile mapping from the SRB to the E2OBS grid such that the sub-SRB-grid-scale spatial variability present in the original E2OBS data is retained. Cross validations at the daily and monthly timescales reveal that it is worthwhile to take empirical estimates of physical upper limits into account when adjusting either radiation component and that, overall, bias correction at the daily timescale is more effective than bias correction at the monthly timescale if sampling errors are taken into account.

Factorial inferential grid grouping and representativeness analysis for a systematic selection of representative grids

NASA Astrophysics Data System (ADS)

Cheng, Guanhui; Huang, Guohe; Dong, Cong; Xu, Ye; Yao, Yao

2017-08-01

A factorial inferential grid grouping and representativeness analysis (FIGGRA) approach is developed to achieve a systematic selection of representative grids in large-scale climate change impact assessment and adaptation (LSCCIAA) studies and other fields of Earth and space sciences. FIGGRA is applied to representative-grid selection for temperature (Tas) and precipitation (Pr) over the Loess Plateau (LP) to verify methodological effectiveness. FIGGRA is effective at and outperforms existing grid-selection approaches (e.g., self-organizing maps) in multiple aspects such as clustering similar grids, differentiating dissimilar grids, and identifying representative grids for both Tas and Pr over LP. In comparison with Pr, the lower spatial heterogeneity and higher spatial discontinuity of Tas over LP lead to higher within-group similarity, lower between-group dissimilarity, lower grid grouping effectiveness, and higher grid representativeness; the lower interannual variability of the spatial distributions of Tas results in lower impacts of the interannual variability on the effectiveness of FIGGRA. For LP, the spatial climatic heterogeneity is the highest in January for Pr and in October for Tas; it decreases from spring, autumn, summer to winter for Tas and from summer, spring, autumn to winter for Pr. Two parameters, i.e., the statistical significance level (α) and the minimum number of grids in every climate zone (Nmin), and their joint effects are significant for the effectiveness of FIGGRA; normalization of a nonnormal climate-variable distribution is helpful for the effectiveness only for Pr. For FIGGRA-based LSCCIAA studies, a low value of Nmin is recommended for both Pr and Tas, and a high and medium value of α for Pr and Tas, respectively.

THE MASS-LOSS RETURN FROM EVOLVED STARS TO THE LARGE MAGELLANIC CLOUD. VI. LUMINOSITIES AND MASS-LOSS RATES ON POPULATION SCALES

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

Riebel, D.; Meixner, M.; Srinivasan, S.

We present results from the first application of the Grid of Red Supergiant and Asymptotic Giant Branch ModelS (GRAMS) model grid to the entire evolved stellar population of the Large Magellanic Cloud (LMC). GRAMS is a pre-computed grid of 80,843 radiative transfer models of evolved stars and circumstellar dust shells composed of either silicate or carbonaceous dust. We fit GRAMS models to {approx}30,000 asymptotic giant branch (AGB) and red supergiant (RSG) stars in the LMC, using 12 bands of photometry from the optical to the mid-infrared. Our published data set consists of thousands of evolved stars with individually determined evolutionarymore » parameters such as luminosity and mass-loss rate. The GRAMS grid has a greater than 80% accuracy rate discriminating between oxygen- and carbon-rich chemistry. The global dust injection rate to the interstellar medium (ISM) of the LMC from RSGs and AGB stars is on the order of 2.1 Multiplication-Sign 10{sup -5} M{sub Sun} yr{sup -1}, equivalent to a total mass injection rate (including the gas) into the ISM of {approx}6 Multiplication-Sign 10{sup -3} M{sub Sun} yr{sup -1}. Carbon stars inject two and a half times as much dust into the ISM as do O-rich AGB stars, but the same amount of mass. We determine a bolometric correction factor for C-rich AGB stars in the K{sub s} band as a function of J - K{sub s} color, BC{sub K{sub s}}= -0.40(J-K{sub s}){sup 2} + 1.83(J-K{sub s}) + 1.29. We determine several IR color proxies for the dust mass-loss rate (M-dot{sub d}) from C-rich AGB stars, such as log M-dot{sub d} = (-18.90/((K{sub s}-[8.0])+3.37) - 5.93. We find that a larger fraction of AGB stars exhibiting the 'long-secondary period' phenomenon are more O-rich than stars dominated by radial pulsations, and AGB stars without detectable mass loss do not appear on either the first-overtone or fundamental-mode pulsation sequences.« less

Filtered sub-grid constitutive models for fluidized gas-particle flows constructed from 3-D simulations

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

Sarkar, Avik; Milioli, Fernando E.; Ozarkar, Shailesh

2016-10-01

The accuracy of fluidized-bed CFD predictions using the two-fluid model can be improved significantly, even when using coarse grids, by replacing the microscopic kinetic-theory-based closures with coarse-grained constitutive models. These coarse-grained constitutive relationships, called filtered models, account for the unresolved gas-particle structures (clusters and bubbles) via sub-grid corrections. Following the previous 2-D approaches of Igci et al. [AIChE J., 54(6), 1431-1448, 2008] and Milioli et al. [AIChE J., 59(9), 3265-3275, 2013], new filtered models are constructed from highly-resolved 3-D simulations of gas-particle flows. Although qualitatively similar to the older 2-D models, the new 3-D relationships exhibit noticeable quantitative and functionalmore » differences. In particular, the filtered stresses are strongly dependent on the gas-particle slip velocity. Closures for the filtered inter-phase drag, gas- and solids-phase pressures and viscosities are reported. A new model for solids stress anisotropy is also presented. These new filtered 3-D constitutive relationships are better suited to practical coarse-grid 3-D simulations of large, commercial-scale devices.« less

Wafer-scale aluminum nano-plasmonics

NASA Astrophysics Data System (ADS)

George, Matthew C.; Nielson, Stew; Petrova, Rumyana; Frasier, James; Gardner, Eric

2014-09-01

The design, characterization, and optical modeling of aluminum nano-hole arrays are discussed for potential applications in surface plasmon resonance (SPR) sensing, surface-enhanced Raman scattering (SERS), and surface-enhanced fluorescence spectroscopy (SEFS). In addition, recently-commercialized work on narrow-band, cloaked wire grid polarizers composed of nano-stacked metal and dielectric layers patterned over 200 mm diameter wafers for projection display applications is reviewed. The stacked sub-wavelength nanowire grid results in a narrow-band reduction in reflectance by 1-2 orders of magnitude, which can be tuned throughout the visible spectrum for stray light control.

California's Snow Gun and its implications for mass balance predictions under greenhouse warming

NASA Astrophysics Data System (ADS)

Howat, I.; Snyder, M.; Tulaczyk, S.; Sloan, L.

2003-12-01

Precipitation has received limited treatment in glacier and snowpack mass balance models, largely due to the poor resolution and confidence of precipitation predictions relative to temperature predictions derived from atmospheric models. Most snow and glacier mass balance models rely on statistical or lapse rate-based downscaling of general or regional circulation models (GCM's and RCM's), essentially decoupling sub-grid scale, orographically-driven evolution of atmospheric heat and moisture. Such models invariably predict large losses in the snow and ice volume under greenhouse warming. However, positive trends in the mass balance of glaciers in some warming maritime climates, as well as at high elevations of the Greenland Ice Sheet, suggest that increased precipitation may play an important role in snow- and glacier-climate interactions. Here, we present a half century of April snowpack data from the Sierra Nevada and Cascade mountains of California, USA. This high-density network of snow-course data indicates that a gain in winter snow accumulation at higher elevations has compensated loss in snow volume at lower elevations by over 50% and has led to glacier expansion on Mt. Shasta. These trends are concurrent with a region-wide increase in winter temperatures up to 2° C. They result from the orographic lifting and saturation of warmer, more humid air leading to increased precipitation at higher elevations. Previous studies have invoked such a "Snow Gun" effect to explain contemporaneous records of Tertiary ocean warming and rapid glacial expansion. A climatological context of the California's "snow gun" effect is elucidated by correlation between the elevation distribution of April SWE observations and the phase of the Pacific Decadal Oscillation and the El Nino Southern Oscillation, both controlling the heat and moisture delivered to the U.S. Pacific coast. The existence of a significant "Snow Gun" effect presents two challenges to snow and glacier mass balance modeling. Firstly, the link between amplification of orographic precipitation and the temporal evolution of ocean-climate oscillations indicates that prediction of future mass balance trends requires consideration of the timing and amplitude of such oscillations. Only recently have ocean-atmosphere models begun to realistically produce such temporal variability. Secondly, the steepening snow mass-balance elevation-gradient associated with the "Snow Gun" implies greater spatial variability in balance with warming. In a warming climate, orographic processes at a scale finer that the highest resolution RCM (>20km grid) become increasingly important and predictions based on lower elevations become increasingly inaccurate for higher elevations. Therefore, thermodynamic interaction between atmospheric heat, moisture and topography must be included in downscaling techniques. In order to demonstrate the importance of the thermodynamic downscaling in mass balance predictions, we nest a high-resolution (100m grid), coupled Orographic Precipitation and Surface Energy balance Model (OPSEM) into the RegC2.5 RCM (40 km grid) and compare results. We apply this nesting technique to Mt. Shasta, California, an area of high topography (~4000m) relative to its RegCM2.5 grid elevation (1289m). These models compute average April snow volume under present and doubled-present Atmospheric CO2 concentrations. While the RegCM2.5 regional model predicts an 83% decrease in April SWE, OPSEM predicts a 16% increase. These results indicate that thermodynamic interactions between the atmosphere and topography at sub- RCM grid resolution must be considered in mass balance models.

Strong influence of variable treatment on the performance of numerically defined ecological regions.

PubMed

Snelder, Ton; Lehmann, Anthony; Lamouroux, Nicolas; Leathwick, John; Allenbach, Karin

2009-10-01

Numerical clustering has frequently been used to define hierarchically organized ecological regionalizations, but there has been little robust evaluation of their performance (i.e., the degree to which regions discriminate areas with similar ecological character). In this study we investigated the effect of the weighting and treatment of input variables on the performance of regionalizations defined by agglomerative clustering across a range of hierarchical levels. For this purpose, we developed three ecological regionalizations of Switzerland of increasing complexity using agglomerative clustering. Environmental data for our analysis were drawn from a 400 m grid and consisted of estimates of 11 environmental variables for each grid cell describing climate, topography and lithology. Regionalization 1 was defined from the environmental variables which were given equal weights. We used the same variables in Regionalization 2 but weighted and transformed them on the basis of a dissimilarity model that was fitted to land cover composition data derived for a random sample of cells from interpretation of aerial photographs. Regionalization 3 was a further two-stage development of Regionalization 2 where specific classifications, also weighted and transformed using dissimilarity models, were applied to 25 small scale "sub-domains" defined by Regionalization 2. Performance was assessed in terms of the discrimination of land cover composition for an independent set of sites using classification strength (CS), which measured the similarity of land cover composition within classes and the dissimilarity between classes. Regionalization 2 performed significantly better than Regionalization 1, but the largest gains in performance, compared to Regionalization 1, occurred at coarse hierarchical levels (i.e., CS did not increase significantly beyond the 25-region level). Regionalization 3 performed better than Regionalization 2 beyond the 25-region level and CS values continued to increase to the 95-region level. The results show that the performance of regionalizations defined by agglomerative clustering are sensitive to variable weighting and transformation. We conclude that large gains in performance can be achieved by training classifications using dissimilarity models. However, these gains are restricted to a narrow range of hierarchical levels because agglomerative clustering is unable to represent the variation in importance of variables at different spatial scales. We suggest that further advances in the numerical definition of hierarchically organized ecological regionalizations will be possible with techniques developed in the field of statistical modeling of the distribution of community composition.

Conservation conflicts across Africa.

PubMed

Balmford, A; Moore, J L; Brooks, T; Burgess, N; Hansen, L A; Williams, P; Rahbek, C

2001-03-30

There is increasing evidence that areas of outstanding conservation importance may coincide with dense human settlement or impact. We tested the generality of these findings using 1 degree-resolution data for sub-Saharan Africa. We find that human population density is positively correlated with species richness of birds, mammals, snakes, and amphibians. This association holds for widespread, narrowly endemic, and threatened species and looks set to persist in the face of foreseeable population growth. Our results contradict earlier expectations of low conflict based on the idea that species richness decreases and human impact increases with primary productivity. We find that across Africa, both variables instead exhibit unimodal relationships with productivity. Modifying priority-setting to take account of human density shows that, at this scale, conflicts between conservation and development are not easily avoided, because many densely inhabited grid cells contain species found nowhere else.

The Use of CASES-97 Observations to Assess and Parameterize the Impact of Land-Surface Heterogeneity on Area-Average Surface Heat Fluxes for Large-Scale Coupled Atmosphere-Hydrology Models

NASA Technical Reports Server (NTRS)

Chen, Fei; Yates, David; LeMone, Margaret

2001-01-01

To understand the effects of land-surface heterogeneity and the interactions between the land-surface and the planetary boundary layer at different scales, we develop a multiscale data set. This data set, based on the Cooperative Atmosphere-Surface Exchange Study (CASES97) observations, includes atmospheric, surface, and sub-surface observations obtained from a dense observation network covering a large region on the order of 100 km. We use this data set to drive three land-surface models (LSMs) to generate multi-scale (with three resolutions of 1, 5, and 10 kilometers) gridded surface heat flux maps for the CASES area. Upon validating these flux maps with measurements from surface station and aircraft, we utilize them to investigate several approaches for estimating the area-integrated surface heat flux for the CASES97 domain of 71x74 square kilometers, which is crucial for land surface model development/validation and area water and energy budget studies. This research is aimed at understanding the relative contribution of random turbulence versus organized mesoscale circulations to the area-integrated surface flux at the scale of 100 kilometers, and identifying the most important effective parameters for characterizing the subgrid-scale variability for large-scale atmosphere-hydrology models.

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-cloud Aerosols over Ocean Using CALIOP and MODIS Data

NASA Technical Reports Server (NTRS)

Zhang, Z.; Meyer, K.; Platnick, S.; Oreopoulos, L.; Lee, D.; Yu, H.

2013-01-01

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It accounts for the overlapping of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure. Effects of sub-grid scale cloud and aerosol variations on DRE are accounted for. It is computationally efficient through using grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table in radiative transfer calculations. We verified that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous shortwave DRE that generally agrees with more rigorous pixel-level computation within 4%. We have also computed the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global ocean based on 4 yr of CALIOP and MODIS data. We found that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds.

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-Cloud Aerosols Using CALIOP and MODIS Data

NASA Technical Reports Server (NTRS)

Zhang, Z.; Meyer, K.; Platnick, S.; Oreopoulos, L.; Lee, D.; Yu, H.

2014-01-01

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It accounts for the overlapping of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure. Effects of sub-grid scale cloud and aerosol variations on DRE are accounted for. It is computationally efficient through using grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table in radiative transfer calculations. We verified that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous shortwave DRE that generally agrees with more rigorous pixel-level computation within 4. We have also computed the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global ocean based on 4 yr of CALIOP and MODIS data. We found that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds.

Cloud Modeling

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

Where is the ideal location for a US East Coast offshore grid?

NASA Astrophysics Data System (ADS)

Dvorak, Michael J.; Stoutenburg, Eric D.; Archer, Cristina L.; Kempton, Willett; Jacobson, Mark Z.

2012-03-01

This paper identifies the location of an “ideal” offshore wind energy (OWE) grid on the U.S. East Coast that would (1) provide the highest overall and peak-time summer capacity factor, (2) use bottom-mounted turbine foundations (depth ≤50 m), (3) connect regional transmissions grids from New England to the Mid-Atlantic, and (4) have a smoothed power output, reduced hourly ramp rates and hours of zero power. Hourly, high-resolution mesoscale weather model data from 2006-2010 were used to approximate wind farm output. The offshore grid was located in the waters from Long Island, New York to the Georges Bank, ≈450 km east. Twelve candidate 500 MW wind farms were located randomly throughout that region. Four wind farms (2000 MW total capacity) were selected for their synergistic meteorological characteristics that reduced offshore grid variability. Sites likely to have sea breezes helped increase the grid capacity factor during peak time in the spring and summer months. Sites far offshore, dominated by powerful synoptic-scale storms, were included for their generally higher but more variable power output. By interconnecting all 4 farms via an offshore grid versus 4 individual interconnections, power was smoothed, the no-power events were reduced from 9% to 4%, and the combined capacity factor was 48% (gross). By interconnecting offshore wind energy farms ≈450 km apart, in regions with offshore wind energy resources driven by both synoptic-scale storms and mesoscale sea breezes, substantial reductions in low/no-power hours and hourly ramp rates can be made.

Enhanced Representation of Turbulent Flow Phenomena in Large-Eddy Simulations of the Atmospheric Boundary Layer using Grid Refinement with Pseudo-Spectral Numerics

NASA Astrophysics Data System (ADS)

Torkelson, G. Q.; Stoll, R., II

2017-12-01

Large Eddy Simulation (LES) is a tool commonly used to study the turbulent transport of momentum, heat, and moisture in the Atmospheric Boundary Layer (ABL). For a wide range of ABL LES applications, representing the full range of turbulent length scales in the flow field is a challenge. This is an acute problem in regions of the ABL with strong velocity or scalar gradients, which are typically poorly resolved by standard computational grids (e.g., near the ground surface, in the entrainment zone). Most efforts to address this problem have focused on advanced sub-grid scale (SGS) turbulence model development, or on the use of massive computational resources. While some work exists using embedded meshes, very little has been done on the use of grid refinement. Here, we explore the benefits of grid refinement in a pseudo-spectral LES numerical code. The code utilizes both uniform refinement of the grid in horizontal directions, and stretching of the grid in the vertical direction. Combining the two techniques allows us to refine areas of the flow while maintaining an acceptable grid aspect ratio. In tests that used only refinement of the vertical grid spacing, large grid aspect ratios were found to cause a significant unphysical spike in the stream-wise velocity variance near the ground surface. This was especially problematic in simulations of stably-stratified ABL flows. The use of advanced SGS models was not sufficient to alleviate this issue. The new refinement technique is evaluated using a series of idealized simulation test cases of neutrally and stably stratified ABLs. These test cases illustrate the ability of grid refinement to increase computational efficiency without loss in the representation of statistical features of the flow field.

New planetary boundary layer parametrization in ECHAM5-HAM: Dynamical refinement of the vertical resolution

NASA Astrophysics Data System (ADS)

Siegenthaler-Le Drian, C.; Spichtinger, P.; Lohmann, U.

2010-09-01

Marine stratocumulus-capped boundary layers exhibit a strong net cooling impact on the Earth-Atmosphere system. Moreover, they are highly persistent over subtropical oceans. Therefore climate models need to represent them well in order to make reliable projections of future climate. One of the reasons for the absence of stratocumuli in the general circulation model ECHAM5-HAM (Roeckner et al., 2003; Stier et al., 2005) is due to the limited vertical resolution. In the current model version, no vertical sub-grid scale variability of clouds is taken into account, such that clouds occupy the full vertical layer. Around the inversion on top of the planetary boundary layer (PBL), conserved variables often have a steep gradient, which in a GCM may produce large discretization errors (Bretherton and Park, 2009). This inversion has a large diurnal cycle and varies with location around the globe, which is difficult to represent in a classical, coarse Eulerian approach. Furthermore, Lenderink and Holtslag (2000) and Lock (2001) showed that an inconsistent numerical representation between the entrainment parametrization and the other schemes, particularly with the vertical advection can lead to the occurrence of 'numerical entrainment'. The problem can be resolved by introducing a dynamical inversion as introduced by Grenier and Bretherton (2001) and Lock (2001). As these features can be seen in our version of ECHAM5-HAM, our implementation is aimed to reduce the numerical entrainment and to better represent stratocumuli in ECHAM5-HAM. To better resolve stratocumulus clouds, their inversion and the interaction between the turbulent diffusion and the vertical advection, the vertical grid is dynamically refined. The new grid is based on the reconstruction of the profiles of variables experiencing a sharp gradient (temperature, mixing ratio) applying the method presented in Grenier and Bretherton (2001). In typical stratocumulus regions, an additional grid level is thus associated with the PBL top. In case a cloud can be formed, a new level is associated with the lifting condensation level as well. The regular grid plus the two additional levels define the new dynamical grid, which varies geographically and temporally. The physical processes are computed on this new dynamical grid, Consequently, the sharp gradients and the interaction between the different processes can be better resolved. Some results of this new parametrization will be presented. On a single column model set-up, the reconstruction method accurately finds the inversion at the PBL top for the EPIC stratocumulus case. Also, on a global scale, the occurrence of a successful reconstruction, which is restricted in typical stratocumulus regions, occurs with a high frequency. The impact of the new dynamical grid on clouds and the radiation balance will be presented in the talk. References [Bretherton and Park, 2009] Bretherton, C. S. and Park, S. (2009). A new moist turbulence parametrization in the community atmosphere model. J. Climate, 22:3422-3448. [Grenier and Bretherton, 2001] Grenier, H. and Bretherton, C. S. (2001). A moist parametrization for large-scale models and its application to subtropical cloud-topped marine boundary layers. Mon. Wea. Rev., 129:357-377. [Lenderink and Holtslag, 2000] Lenderink, G. and Holtslag, A. M. (2000). Evaluation of the kinetic energy approach for modeling turbulent fluxes in stratocumulus. Mon. Wea. Rev., 128:244-258. [Lock, 2001] Lock, A. P. (2001). The numerical representation of entrainment in parametrizations of boundary layer turbulent mixing. Mon. Wea. Rev., 129:1148-1163. [Roeckner et al., 2003] Roeckner, E., Bäuml, G., Bonaventura, L. et al. (2003). The atmospheric general circulation model echam5, part I: Model description. Technical Report 349, Max-Planck-Institute for Meteorology, Hamburg,Germany. [Stier et al., 2005] Stier, P., Feichter, J., Kinne, S. et al. (2005). The aerosol-climate model ECHAM5-HAM. Atmos. Chem. Phys., 5:1125-1156.

Spatio-temporal atmospheric circulation variability around the Antarctic Peninsula based on hemispheric circulation modes and weather types

NASA Astrophysics Data System (ADS)

Wachter, Paul; Beck, Christoph; Philipp, Andreas; Jacobeit, Jucundus; Höppner, Kathrin

2017-04-01

Large parts of the Polar Regions are affected by a warming trend associated with substantial changes in the cryosphere. In Antarctica this positive trend pattern is most dominant in the western part of the continent and on the Antarctic Peninsula (AP). An important driving mechanism of temperature variability and trends in this region is the atmospheric circulation. Changes in atmospheric circulation modes and frequencies of circulation types have major impacts on temperature characteristics at a certain station or region. We present results of a statistical downscaling study focused on AP temperature variability showing both results of large-scale atmospheric circulation modes and regional weather type classifications derived from monthly and daily gridded reanalysis data sets. In order to investigate spatial trends and variabilities of the Southern Annular Mode (SAM), we analyze spatio-temporally resolved SAM-pattern maps from 1979 to 2015. First results show dominant multi-annual to decadal pattern variabilities which can be directly linked to temperature variabilities at the Antarctic Peninsula. A sub-continental to regional view on the influence of atmospheric circulation on AP temperature variability is given by the analysis of weather type classifications (WTC). With this analysis we identify significant changes in the frequency of occurrence of highly temperature-relevant circulation patterns. The investigated characteristics of weather type frequencies can also be related to the identified changes of the SAM.

Calculations of High-Temperature Jet Flow Using Hybrid Reynolds-Average Navier-Stokes Formulations

NASA Technical Reports Server (NTRS)

Abdol-Hamid, Khaled S.; Elmiligui, Alaa; Giriamaji, Sharath S.

2008-01-01

Two multiscale-type turbulence models are implemented in the PAB3D solver. The models are based on modifying the Reynolds-averaged Navier Stokes equations. The first scheme is a hybrid Reynolds-averaged- Navier Stokes/large-eddy-simulation model using the two-equation k(epsilon) model with a Reynolds-averaged-Navier Stokes/large-eddy-simulation transition function dependent on grid spacing and the computed turbulence length scale. The second scheme is a modified version of the partially averaged Navier Stokes model in which the unresolved kinetic energy parameter f(sub k) is allowed to vary as a function of grid spacing and the turbulence length scale. This parameter is estimated based on a novel two-stage procedure to efficiently estimate the level of scale resolution possible for a given flow on a given grid for partially averaged Navier Stokes. It has been found that the prescribed scale resolution can play a major role in obtaining accurate flow solutions. The parameter f(sub k) varies between zero and one and is equal to one in the viscous sublayer and when the Reynolds-averaged Navier Stokes turbulent viscosity becomes smaller than the large-eddy-simulation viscosity. The formulation, usage methodology, and validation examples are presented to demonstrate the enhancement of PAB3D's time-accurate turbulence modeling capabilities. The accurate simulations of flow and turbulent quantities will provide a valuable tool for accurate jet noise predictions. Solutions from these models are compared with Reynolds-averaged Navier Stokes results and experimental data for high-temperature jet flows. The current results show promise for the capability of hybrid Reynolds-averaged Navier Stokes and large eddy simulation and partially averaged Navier Stokes in simulating such flow phenomena.

MODFLOW-LGR: Practical application to a large regional dataset

NASA Astrophysics Data System (ADS)

Barnes, D.; Coulibaly, K. M.

2011-12-01

In many areas of the US, including southwest Florida, large regional-scale groundwater models have been developed to aid in decision making and water resources management. These models are subsequently used as a basis for site-specific investigations. Because the large scale of these regional models is not appropriate for local application, refinement is necessary to analyze the local effects of pumping wells and groundwater related projects at specific sites. The most commonly used approach to date is Telescopic Mesh Refinement or TMR. It allows the extraction of a subset of the large regional model with boundary conditions derived from the regional model results. The extracted model is then updated and refined for local use using a variable sized grid focused on the area of interest. MODFLOW-LGR, local grid refinement, is an alternative approach which allows model discretization at a finer resolution in areas of interest and provides coupling between the larger "parent" model and the locally refined "child." In the present work, these two approaches are tested on a mining impact assessment case in southwest Florida using a large regional dataset (The Lower West Coast Surficial Aquifer System Model). Various metrics for performance are considered. They include: computation time, water balance (as compared to the variable sized grid), calibration, implementation effort, and application advantages and limitations. The results indicate that MODFLOW-LGR is a useful tool to improve local resolution of regional scale models. While performance metrics, such as computation time, are case-dependent (model size, refinement level, stresses involved), implementation effort, particularly when regional models of suitable scale are available, can be minimized. The creation of multiple child models within a larger scale parent model makes it possible to reuse the same calibrated regional dataset with minimal modification. In cases similar to the Lower West Coast model, where a model is larger than optimal for direct application as a parent grid, a combination of TMR and LGR approaches should be used to develop a suitable parent grid.

Forward Modeling of Atmospheric Carbon Dioxide in GEOS-5: Uncertainties Related to Surface Fluxes and Sub-Grid Transport

NASA Technical Reports Server (NTRS)

Pawson, Steven; Ott, Lesley E.; Zhu, Zhengxin; Bowman, Kevin; Brix, Holger; Collatz, G. James; Dutkiewicz, Stephanie; Fisher, Joshua B.; Gregg, Watson W.; Hill, Chris;

Coupled Modes over Indian Ocean at Sub-seasonal time Scales and its Prediction

NASA Astrophysics Data System (ADS)

Jung, E.; Kirtman, B. P.

2014-12-01

Sub-seasonal variability over the Indian Ocean, such as Madden-Julian Oscillation impacts weather and climate globally. However, the prediction of tropical sub-seasonal variability (TSV) remains a challenge, and understanding air-sea interactions on TSV time-scales is likely to be an important part of the prediction problem. The purpose of this paper is to examine the predictability of sub-seasonal variability in the tropical Indo-Pacific region. The analysis emphasizes on variability associated with coupled air-sea interactions in observational estimates, and how well these coupled modes are simulated and predicted within the context of a 30-year retrospective forecast experiment with a state-of-the-art atmosphere-ocean coupled model. The analysis shows that Sea Surface Temperature anomalies (SSTA) over the Indian Ocean tend to precede precipitation anomalies by 7-11 days with maximum amplitude over the Arabian Sea and the Bay of Bengal for summer and along the Seychelles-Chagos Thermocline Ridge (SCTR) region for winter. Though these coupled modes are captured by the models, the forecasts fail to predict its evolution. Based on the diagnosis of these coupled modes, we introduce a SCTR-SST index and an index that measures the modulation of the low-frequency amplitude (LFAM) of sub-seasonal SSTA variability over SCTR as a way to predict the coupled modes. Based on correlation with the observed variability, SCTR-SST has forecast skill of about 45 days over the Indian Ocean. However the sub-seasonal SSTAs in the predictions and the observational estimates do not have any direct ENSO tele-connection. In contrast, the LFAM of the sub-seasonal SSTA variance over SCTR is strongly correlated with ENSO, suggesting enhanced sub-seasonal variance on seasonal time-scales is potentially predictable.

Demonstration of Essential Reliability Services by a 300-MW Solar Photovoltaic Power Plant

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

Loutan, Clyde; Klauer, Peter; Chowdhury, Sirajul

The California Independent System Operator (CAISO), First Solar, and the National Renewable Energy Laboratory (NREL) conducted a demonstration project on a large utility-scale photovoltaic (PV) power plant in California to test its ability to provide essential ancillary services to the electric grid. With increasing shares of solar- and wind-generated energy on the electric grid, traditional generation resources equipped with automatic governor control (AGC) and automatic voltage regulation controls -- specifically, fossil thermal -- are being displaced. The deployment of utility-scale, grid-friendly PV power plants that incorporate advanced capabilities to support grid stability and reliability is essential for the large-scale integrationmore » of PV generation into the electric power grid, among other technical requirements. A typical PV power plant consists of multiple power electronic inverters and can contribute to grid stability and reliability through sophisticated 'grid-friendly' controls. In this way, PV power plants can be used to mitigate the impact of variability on the grid, a role typically reserved for conventional generators. In August 2016, testing was completed on First Solar's 300-MW PV power plant, and a large amount of test data was produced and analyzed that demonstrates the ability of PV power plants to use grid-friendly controls to provide essential reliability services. These data showed how the development of advanced power controls can enable PV to become a provider of a wide range of grid services, including spinning reserves, load following, voltage support, ramping, frequency response, variability smoothing, and frequency regulation to power quality. Specifically, the tests conducted included various forms of active power control such as AGC and frequency regulation; droop response; and reactive power, voltage, and power factor controls. This project demonstrated that advanced power electronics and solar generation can be controlled to contribute to system-wide reliability. It was shown that the First Solar plant can provide essential reliability services related to different forms of active and reactive power controls, including plant participation in AGC, primary frequency control, ramp rate control, and voltage regulation. For AGC participation in particular, by comparing the PV plant testing results to the typical performance of individual conventional technologies, we showed that regulation accuracy by the PV plant is 24-30 points better than fast gas turbine technologies. The plant's ability to provide volt-ampere reactive control during periods of extremely low power generation was demonstrated as well. The project team developed a pioneering demonstration concept and test plan to show how various types of active and reactive power controls can leverage PV generation's value from being a simple variable energy resource to a resource that provides a wide range of ancillary services. With this project's approach to a holistic demonstration on an actual, large, utility-scale, operational PV power plant and dissemination of the obtained results, the team sought to close some gaps in perspectives that exist among various stakeholders in California and nationwide by providing real test data.« less

Improving and Understanding Climate Models: Scale-Aware Parameterization of Cloud Water Inhomogeneity and Sensitivity of MJO Simulation to Physical Parameters in a Convection Scheme

NASA Astrophysics Data System (ADS)

Xie, Xin

Microphysics and convection parameterizations are two key components in a climate model to simulate realistic climatology and variability of cloud distribution and the cycles of energy and water. When a model has varying grid size or simulations have to be run with different resolutions, scale-aware parameterization is desirable so that we do not have to tune model parameters tailored to a particular grid size. The subgrid variability of cloud hydrometers is known to impact microphysics processes in climate models and is found to highly depend on spatial scale. A scale- aware liquid cloud subgrid variability parameterization is derived and implemented in the Community Earth System Model (CESM) in this study using long-term radar-based ground measurements from the Atmospheric Radiation Measurement (ARM) program. When used in the default CESM1 with the finite-volume dynamic core where a constant liquid inhomogeneity parameter was assumed, the newly developed parameterization reduces the cloud inhomogeneity in high latitudes and increases it in low latitudes. This is due to both the smaller grid size in high latitudes, and larger grid size in low latitudes in the longitude-latitude grid setting of CESM as well as the variation of the stability of the atmosphere. The single column model and general circulation model (GCM) sensitivity experiments show that the new parameterization increases the cloud liquid water path in polar regions and decreases it in low latitudes. Current CESM1 simulation suffers from the bias of both the pacific double ITCZ precipitation and weak Madden-Julian oscillation (MJO). Previous studies show that convective parameterization with multiple plumes may have the capability to alleviate such biases in a more uniform and physical way. A multiple-plume mass flux convective parameterization is used in Community Atmospheric Model (CAM) to investigate the sensitivity of MJO simulations. We show that MJO simulation is sensitive to entrainment rate specification. We found that shallow plumes can generate and sustain the MJO propagation in the model.

STAMMEX high resolution gridded daily precipitation dataset over Germany: a new potential for regional precipitation climate research

NASA Astrophysics Data System (ADS)

Zolina, Olga; Simmer, Clemens; Kapala, Alice; Mächel, Hermann; Gulev, Sergey; Groisman, Pavel

2014-05-01

We present new high resolution precipitation daily grids developed at Meteorological Institute, University of Bonn and German Weather Service (DWD) under the STAMMEX project (Spatial and Temporal Scales and Mechanisms of Extreme Precipitation Events over Central Europe). Daily precipitation grids have been developed from the daily-observing precipitation network of DWD, which runs one of the World's densest rain gauge networks comprising more than 7500 stations. Several quality-controlled daily gridded products with homogenized sampling were developed covering the periods 1931-onwards (with 0.5 degree resolution), 1951-onwards (0.25 degree and 0.5 degree), and 1971-2000 (0.1 degree). Different methods were tested to select the best gridding methodology that minimizes errors of integral grid estimates over hilly terrain. Besides daily precipitation values with uncertainty estimates (which include standard estimates of the kriging uncertainty as well as error estimates derived by a bootstrapping algorithm), the STAMMEX data sets include a variety of statistics that characterize temporal and spatial dynamics of the precipitation distribution (quantiles, extremes, wet/dry spells, etc.). Comparisons with existing continental-scale daily precipitation grids (e.g., CRU, ECA E-OBS, GCOS) which include considerably less observations compared to those used in STAMMEX, demonstrate the added value of high-resolution grids for extreme rainfall analyses. These data exhibit spatial variability pattern and trends in precipitation extremes, which are missed or incorrectly reproduced over Central Europe from coarser resolution grids based on sparser networks. The STAMMEX dataset can be used for high-quality climate diagnostics of precipitation variability, as a reference for reanalyses and remotely-sensed precipitation products (including the upcoming Global Precipitation Mission products), and for input into regional climate and operational weather forecast models. We will present numerous application of the STAMMEX grids spanning from case studies of the major Central European floods to long-term changes in different precipitation statistics, including those accounting for the alternation of dry and wet periods and precipitation intensities associated with prolonged rainy episodes.

Experimental Study of Vane Heat Transfer and Aerodynamics at Elevated Levels of Turbulence

NASA Technical Reports Server (NTRS)

Ames, Forrest E.

1994-01-01

A four vane subsonic cascade was used to investigate how free stream turbulence influences pressure surface heat transfer. A simulated combustor turbulence generator was built to generate high level (13 percent) large scale (Lu approximately 44 percent inlet span) turbulence. The mock combustor was also moved upstream to generate a moderate level (8.3 percent) of turbulence for comparison to smaller scale grid generated turbulence (7.8 percent). The high level combustor turbulence caused an average pressure surface heat transfer augmentation of 56 percent above the low turbulence baseline. The smaller scale grid turbulence produced the next greatest effect on heat transfer and demonstrated the importance of scale on heat transfer augmentation. In general, the heat transfer scaling parameter U(sub infinity) TU(sub infinity) LU(sub infinity)(exp -1/3) was found to hold for the turbulence. Heat transfer augmentation was also found to scale approximately on Re(sub ex)(exp 1/3) at constant turbulence conditions. Some evidence of turbulence intensification in terms of elevated dissipation rates was found along the pressure surface outside the boundary layer. However, based on the level of dissipation and the resulting heat transfer augmentation, the amplification of turbulence has only a moderate effect on pressure surface heat transfer. The flow field turbulence does drive turbulent production within the boundary layer which in turn causes the high levels of heat transfer augmentation. Unlike heat transfer, the flow field straining was found to have a significant effect on turbulence isotropy. On examination of the one dimensional spectra for u' and v', the effect to isotropy was largely limited to lower wavenumber spectra. The higher wavenumber spectra showed little or no change. The high level large scale turbulence was found to have a strong influence on wake development. The free stream turbulence significantly enhanced mixing resulting in broader and shallower wakes than the baseline case. High levels of flow field turbulence were found to correlate with a significant increase in total pressure loss in the core of the flow. Documenting the wake growth and characteristics provides boundary conditions for the downstream rotor.

Modelling spatial and temporal variability of hydrologic impacts under climate changes over the Nenjiang River Basin, China

NASA Astrophysics Data System (ADS)

Chen, Hao; Zhang, Wanchang

2017-10-01

The Variable Infiltration Capacity (VIC) hydrologic model was adopted for investigating spatial and temporal variability of hydrologic impacts of climate change over the Nenjiang River Basin (NRB) based on a set of gridded forcing dataset at 1/12th degree resolution from 1970 to 2013. Basin-scale changes in the input forcing data and the simulated hydrological variables of the NRB, as well as station-scale changes in discharges for three major hydrometric stations were examined, which suggested that the model was performed fairly satisfactory in reproducing the observed discharges, meanwhile, the snow cover and evapotranspiration in temporal and spatial patterns were simulated reasonably corresponded to the remotely sensed ones. Wetland maps produced by multi-sources satellite images covering the entire basin between 1978 and 2008 were also utilized for investigating the responses and feedbacks of hydrological regimes on wetland dynamics. Results revealed that significant decreasing trends appeared in annual, spring and autumn streamflow demonstrated strong affection of precipitation and temperature changes over the study watershed, and the effects of climate change on the runoff reduction varied in the sub-basin area over different time scales. The proportion of evapotranspiration to precipitation characterized several severe fluctuations in droughts and floods took place in the region, which implied the enhanced sensitiveness and vulnerability of hydrologic regimes to changing environment of the region. Furthermore, it was found that the different types of wetlands undergone quite unique variation features with the varied hydro-meteorological conditions over the region, such as precipitation, evapotranspiration and soil moisture. This study provided effective scientific basis for water resource managers to develop effective eco-environment management plans and strategies that address the consequences of climate changes.

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

Som, Sibendu; Wang, Zihan; Pei, Yuanjiang

A state-of-the-art spray modeling methodology, recently presented by Senecal et al. [ , , ], is applied to Large Eddy Simulations (LES) of vaporizing gasoline sprays. Simulations of non-combusting Spray G (gasoline fuel) from the Engine Combustion Network are performed. Adaptive mesh refinement (AMR) with cell sizes from 0.09 mm to 0.5 mm are utilized to further demonstrate grid convergence of the dynamic structure LES model for the gasoline sprays. Grid settings are recommended to optimize the accuracy/runtime tradeoff for LES-based spray simulations at different injection pressure conditions typically encountered in gasoline direct injection (GDI) applications. The influence of LESmore » sub-grid scale (SGS) models is explored by comparing the results from dynamic structure and Smagorinsky based models against simulations without any SGS model. Twenty different realizations are simulated by changing the random number seed used in the spray sub-models. It is shown that for global quantities such as spray penetration, comparing a single LES simulation to experimental data is reasonable. Through a detailed analysis using the relevance index (RI) criteria, recommendations are made regarding the minimum number of LES realizations required for accurate prediction of the gasoline sprays.« less

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, A.; Catalano, F.; De Felice, M.; van den Hurk, B.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

2016-12-01

The European consortium earth system model (EC-Earth; http://www.ec-earth.org) has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.

2017-08-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (twentieth century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2 m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.

2017-04-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Differential Item Functioning in the SF-36 Physical Functioning and Mental Health Sub-Scales: A Population-Based Investigation in the Canadian Multicentre Osteoporosis Study.

PubMed

Lix, Lisa M; Wu, Xiuyun; Hopman, Wilma; Mayo, Nancy; Sajobi, Tolulope T; Liu, Juxin; Prior, Jerilynn C; Papaioannou, Alexandra; Josse, Robert G; Towheed, Tanveer E; Davison, K Shawn; Sawatzky, Richard

2016-01-01

Self-reported health status measures, like the Short Form 36-item Health Survey (SF-36), can provide rich information about the overall health of a population and its components, such as physical, mental, and social health. However, differential item functioning (DIF), which arises when population sub-groups with the same underlying (i.e., latent) level of health have different measured item response probabilities, may compromise the comparability of these measures. The purpose of this study was to test for DIF on the SF-36 physical functioning (PF) and mental health (MH) sub-scale items in a Canadian population-based sample. Study data were from the prospective Canadian Multicentre Osteoporosis Study (CaMos), which collected baseline data in 1996-1997. DIF was tested using a multiple indicators multiple causes (MIMIC) method. Confirmatory factor analysis defined the latent variable measurement model for the item responses and latent variable regression with demographic and health status covariates (i.e., sex, age group, body weight, self-perceived general health) produced estimates of the magnitude of DIF effects. The CaMos cohort consisted of 9423 respondents; 69.4% were female and 51.7% were less than 65 years. Eight of 10 items on the PF sub-scale and four of five items on the MH sub-scale exhibited DIF. Large DIF effects were observed on PF sub-scale items about vigorous and moderate activities, lifting and carrying groceries, walking one block, and bathing or dressing. On the MH sub-scale items, all DIF effects were small or moderate in size. SF-36 PF and MH sub-scale scores were not comparable across population sub-groups defined by demographic and health status variables due to the effects of DIF, although the magnitude of this bias was not large for most items. We recommend testing and adjusting for DIF to ensure comparability of the SF-36 in population-based investigations.

Development of a Regional Structured and Unstructured Grid Methodology for Chemically Reactive Turbulent Flows

NASA Astrophysics Data System (ADS)

Stefanski, Douglas Lawrence

A finite volume method for solving the Reynolds Averaged Navier-Stokes (RANS) equations on unstructured hybrid grids is presented. Capabilities for handling arbitrary mixtures of reactive gas species within the unstructured framework are developed. The modeling of turbulent effects is carried out via the 1998 Wilcox k -- o model. This unstructured solver is incorporated within VULCAN -- a multi-block structured grid code -- as part of a novel patching procedure in which non-matching interfaces between structured blocks are replaced by transitional unstructured grids. This approach provides a fully-conservative alternative to VULCAN's non-conservative patching methods for handling such interfaces. In addition, the further development of the standalone unstructured solver toward large-eddy simulation (LES) applications is also carried out. Dual time-stepping using a Crank-Nicholson formulation is added to recover time-accuracy, and modeling of sub-grid scale effects is incorporated to provide higher fidelity LES solutions for turbulent flows. A switch based on the work of Ducros, et al., is implemented to transition from a monotonicity-preserving flux scheme near shocks to a central-difference method in vorticity-dominated regions in order to better resolve small-scale turbulent structures. The updated unstructured solver is used to carry out large-eddy simulations of a supersonic constrained mixing layer.

Impact of small-scale storage systems on the photovoltaic penetration potential at the municipal scale

NASA Astrophysics Data System (ADS)

Ramirez Camargo, Luis; Dorner, Wolfgang

2016-04-01

The yearly cumulated technical energy generation potential of grid-connected roof-top photovoltaic power plants is significantly larger than the demand of domestic buildings in sparsely populated municipalities in central Europe. However, an energy balance with cumulated annual values does not deliver the right picture about the actual potential for photovoltaics since these run on a highly variable energy source as solar radiation. The mismatch between the periods of generation and demand creates hard limitations for the deployment of the theoretical energy generation potential of roof-top photovoltaics. The actual penetration of roof-top photovoltaic is restricted by the energy quality requirements of the grid and/or the available storage capacity for the electricity production beyond the coverage of own demands. In this study we evaluate in how far small-scale storage systems can contribute to increment the grid-connected roof-top photovoltaic penetration in domestic buildings at a municipal scale. To accomplish this, we calculate, in a first step, the total technical roof-top photovoltaic energy generation potential of a municipality in a high spatiotemporal resolution using a procedure that relies on geographic information systems. Posteriorly, we constrain the set of potential photovoltaic plants to the ones that would be necessary to cover the total yearly demand of the municipality. We assume that photovoltaic plants with the highest yearly yield are the ones that should be installed. For this sub-set of photovoltaic plants we consider five scenarios: 1) no storage 2) one 7 kWh battery is installed in every building with a roof-top photovoltaic plant 3) one 10 kWh battery is installed in every building with a roof-top photovoltaic plant 4) one 7 kWh battery is installed in every domestic building in the municipality 5) one 10 kWh battery is installed in every domestic building in the municipality. Afterwards we evaluate the energy balance of the municipality using a series of indicators. These indicators include: a) the total photovoltaic installed capacity, b) the total storage installed capacity, c) the output variability, d) the total unfulfilled demand, e) total excess energy, f) total properly supplied energy, g) the loss of power supply probability, h) the amount of hours of supply higher than the highest demand in a year, i) the number of hours, when supply is 1.5. times higher than the highest demand in a year, and j) the additional storage energy capacity and power required to store all excess energy generated by the photovoltaic installations. The comparison of the proposed indicators serves to quantify the contribution that household-sized small-scale storage systems would make to the energy balance of the studied municipality. Increased installed energy storage capacity allows a higher roof-top photovoltaic share and improves energy utilization, variability and reliability indicators. The proposed methodology serves also to determine the amount of storage capacity with the highest positive impact on the local energy balance.

Impacts of weather versus climate and driver uncertainty on multi-centennial ecosystem model simulations

NASA Astrophysics Data System (ADS)

Rollinson, C.; Simkins, J.; Fer, I.; Desai, A. R.; Dietze, M.

2017-12-01

Simulations of ecosystem dynamics and comparisons with empirical data require accurate, continuous, and often sub-daily meteorology records that are spatially aligned to the scale of the empirical data. A wealth of meteorology data for the past, present, and future is available through site-specific observations, modern reanalysis products, and gridded GCM simulations. However, these products are mismatched in spatial and temporal resolution, often with both different means and seasonal patterns. We have designed and implemented a two-step meteorological downscaling and ensemble generation method that combines multiple meteorology data products through debiasing and temporal downscaling protocols. Our methodology is designed to preserve the covariance among seven meteorological variables for use as drivers in ecosystem model simulations: temperature, precipitation, short- and longwave radiation, surface pressure, humidity, and wind. Furthermore, our method propagates uncertainty through the downscaling process and results in ensembles of meteorology that can be compared to paleoclimate reconstructions and used to analyze the effects of both high- and low-frequency climate anomalies on ecosystem dynamics. Using a multiple linear regression approach, we have combined hourly, 0.125-degree gridded data from the NLDAS (1980-present) with CRUNCEP (1901-2010) and CMIP5 historical (1850-2005), past millennium (850-1849), and future (1950-2100) GCM simulations. This has resulted in an ensemble of continuous, hourly-resolved meteorology from from the paleo era into the future with variability in weather events as well as low-frequency climatic changes. We investigate the influence of extreme sub-daily weather phenomena versus long-term climatic changes in an ensemble of ecosystem models that range in atmospheric and biological complexity. Through data assimilation with paleoclimate reconstructions of past climate, we can improve data-model comparisons using observations of vegetation change from the past 1200 years. Accounting for driver uncertainty in model evaluation can help determine the relative influence of structural versus parameterization errors in ecosystem modelings.

A New Stellar Atmosphere Grid and Comparisons with HST /STIS CALSPEC Flux Distributions

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

Bohlin, Ralph C.; Fleming, Scott W.; Gordon, Karl D.

The Space Telescope Imaging Spectrograph has measured the spectral energy distributions for several stars of types O, B, A, F, and G. These absolute fluxes from the CALSPEC database are fit with a new spectral grid computed from the ATLAS-APOGEE ATLAS9 model atmosphere database using a chi-square minimization technique in four parameters. The quality of the fits are compared for complete LTE grids by Castelli and Kurucz (CK04) and our new comprehensive LTE grid (BOSZ). For the cooler stars, the fits with the MARCS LTE grid are also evaluated, while the hottest stars are also fit with the NLTE Lanzmore » and Hubeny OB star grids. Unfortunately, these NLTE models do not transition smoothly in the infrared to agree with our new BOSZ LTE grid at the NLTE lower limit of T {sub eff} = 15,000 K. The new BOSZ grid is available via the Space Telescope Institute MAST archive and has a much finer sampled IR wavelength scale than CK04, which will facilitate the modeling of stars observed by the James Webb Space Telescope . Our result for the angular diameter of Sirius agrees with the ground-based interferometric value.« less

Global CO2 Distributions over Land from the Greenhouse Gases Observing Satellite (GOSAT)

NASA Technical Reports Server (NTRS)

Hammerling, Dorit M.; Michalak, Anna M.; O'Dell, Christopher; Kawa, Randolph S.

2012-01-01

January 2009 saw the successful launch of the first space-based mission specifically designed for measuring greenhouse gases, the Japanese Greenhouse gases Observing SATellite (GOSAT). We present global land maps (Level 3 data) of column-averaged CO2 concentrations (X(sub CO2)) derived using observations from the GOSAT ACOS retrieval algorithm, for July through December 2009. The applied geostatistical mapping approach makes it possible to generate maps at high spatial and temporal resolutions that include uncertainty measures and that are derived directly from the Level 2 observations, without invoking an atmospheric transport model or estimates of CO2 uptake and emissions. As such, they are particularly well suited for comparison studies. Results show that the Level 3 maps for July to December 2009 on a lO x 1.250 grid, at six-day resolution capture much of the synoptic scale and regional variability of X(sub CO2), in addition to its overall seasonality. The uncertainty estimates, which reflect local data coverage, X(sub CO2) variability, and retrieval errors, indicate that the Southern latitudes are relatively well-constrained, while the Sahara Desert and the high Northern latitudes are weakly-constrained. A probabilistic comparison to the PCTM/GEOS-5/CASA-GFED model reveals that the most statistically significant discrepancies occur in South America in July and August, and central Asia in September to December. While still preliminary, these results illustrate the usefulness of a high spatiotemporal resolution, data-driven Level 3 data product for direct interpretation and comparison of satellite observations of highly dynamic parameters such as atmospheric CO2.

Inter-model variability in hydrological extremes projections for Amazonian sub-basins

NASA Astrophysics Data System (ADS)

Andres Rodriguez, Daniel; Garofolo, Lucas; Lázaro de Siqueira Júnior, José; Samprogna Mohor, Guilherme; Tomasella, Javier

2014-05-01

Irreducible uncertainties due to knowledge's limitations, chaotic nature of climate system and human decision-making process drive uncertainties in Climate Change projections. Such uncertainties affect the impact studies, mainly when associated to extreme events, and difficult the decision-making process aimed at mitigation and adaptation. However, these uncertainties allow the possibility to develop exploratory analyses on system's vulnerability to different sceneries. The use of different climate model's projections allows to aboard uncertainties issues allowing the use of multiple runs to explore a wide range of potential impacts and its implications for potential vulnerabilities. Statistical approaches for analyses of extreme values are usually based on stationarity assumptions. However, nonstationarity is relevant at the time scales considered for extreme value analyses and could have great implications in dynamic complex systems, mainly under climate change transformations. Because this, it is required to consider the nonstationarity in the statistical distribution parameters. We carried out a study of the dispersion in hydrological extremes projections using climate change projections from several climate models to feed the Distributed Hydrological Model of the National Institute for Spatial Research, MHD-INPE, applied in Amazonian sub-basins. This model is a large-scale hydrological model that uses a TopModel approach to solve runoff generation processes at the grid-cell scale. MHD-INPE model was calibrated for 1970-1990 using observed meteorological data and comparing observed and simulated discharges by using several performance coeficients. Hydrological Model integrations were performed for present historical time (1970-1990) and for future period (2010-2100). Because climate models simulate the variability of the climate system in statistical terms rather than reproduce the historical behavior of climate variables, the performances of the model's runs during the historical period, when feed with climate model data, were tested using descriptors of the Flow Duration Curves. The analyses of projected extreme values were carried out considering the nonstationarity of the GEV distribution parameters and compared with extremes events in present time. Results show inter-model variability in a broad dispersion on projected extreme's values. Such dispersion implies different degrees of socio-economic impacts associated to extreme hydrological events. Despite the no existence of one optimum result, this variability allows the analyses of adaptation strategies and its potential vulnerabilities.

Simulation of Deep Convective Clouds with the Dynamic Reconstruction Turbulence Closure

NASA Astrophysics Data System (ADS)

Shi, X.; Chow, F. K.; Street, R. L.; Bryan, G. H.

2017-12-01

The terra incognita (TI), or gray zone, in simulations is a range of grid spacing comparable to the most energetic eddy diameter. Spacing in mesoscale and simulations is much larger than the eddies, and turbulence is parameterized with one-dimensional vertical-mixing. Large eddy simulations (LES) have grid spacing much smaller than the energetic eddies, and use three-dimensional models of turbulence. Studies of convective weather use convection-permitting resolutions, which are in the TI. Neither mesoscale-turbulence nor LES models are designed for the TI, so TI turbulence parameterization needs to be discussed. Here, the effects of sub-filter scale (SFS) closure schemes on the simulation of deep tropical convection are evaluated by comparing three closures, i.e. Smagorinsky model, Deardorff-type TKE model and the dynamic reconstruction model (DRM), which partitions SFS turbulence into resolvable sub-filter scales (RSFS) and unresolved sub-grid scales (SGS). The RSFS are reconstructed, and the SGS are modeled with a dynamic eddy viscosity/diffusivity model. The RSFS stresses/fluxes allow backscatter of energy/variance via counter-gradient stresses/fluxes. In high-resolution (100m) simulations of tropical convection use of these turbulence models did not lead to significant differences in cloud water/ice distribution, precipitation flux, or vertical fluxes of momentum and heat. When model resolutions are coarsened, the Smagorinsky and TKE models overestimate cloud ice and produces large-amplitude downward heat flux in the middle troposphere (not found in the high-resolution simulations). This error is a result of unrealistically large eddy diffusivities, i.e., the eddy diffusivity of the DRM is on the order of 1 for the coarse resolution simulations, the eddy diffusivity of the Smagorinsky and TKE model is on the order of 100. Splitting the eddy viscosity/diffusivity scalars into vertical and horizontal components by using different length scales and strain rate components helps to reduce the errors, but does not completely remedy the problem. In contrast, the coarse resolution simulations using the DRM produce results that are more consistent with the high-resolution results, suggesting that the DRM is a more appropriate turbulence model for simulating convection in the TI.

Urban runoff (URO) process for MODFLOW 2005: simulation of sub-grid scale urban hydrologic processes in Broward County, FL

USGS Publications Warehouse

Decker, Jeremy D.; Hughes, J.D.

2013-01-01

Climate change and sea-level rise could cause substantial changes in urban runoff and flooding in low-lying coast landscapes. A major challenge for local government officials and decision makers is to translate the potential global effects of climate change into actionable and cost-effective adaptation and mitigation strategies at county and municipal scales. A MODFLOW process is used to represent sub-grid scale hydrology in urban settings to help address these issues. Coupled interception, surface water, depression, and unsaturated zone storage are represented. A two-dimensional diffusive wave approximation is used to represent overland flow. Three different options for representing infiltration and recharge are presented. Additional features include structure, barrier, and culvert flow between adjacent cells, specified stage boundaries, critical flow boundaries, source/sink surface-water terms, and the bi-directional runoff to MODFLOW Surface-Water Routing process. Some abilities of the Urban RunOff (URO) process are demonstrated with a synthetic problem using four land uses and varying cell coverages. Precipitation from a hypothetical storm was applied and cell by cell surface-water depth, groundwater level, infiltration rate, and groundwater recharge rate are shown. Results indicate the URO process has the ability to produce time-varying, water-content dependent infiltration and leakage, and successfully interacts with MODFLOW.

Self-organizing map network-based precipitation regionalization for the Tibetan Plateau and regional precipitation variability

NASA Astrophysics Data System (ADS)

Wang, Nini; Yin, Jianchuan

2017-12-01

A precipitation-based regionalization for the Tibetan Plateau (TP) was investigated for regional precipitation trend analysis and frequency analysis using data from 1113 grid points covering the period 1900-2014. The results utilizing self-organizing map (SOM) network suggest that four clusters of precipitation coherent zones can be identified, including the southwestern edge, the southern edge, the southeastern region, and the north central region. Regionalization results of the SOM network satisfactorily represent the influences of the atmospheric circulation systems such as the East Asian summer monsoon, the south Asian summer monsoon, and the mid-latitude westerlies. Regionalization results also well display the direct impacts of physical geographical features of the TP such as orography, topography, and land-sea distribution. Regional-scale annual precipitation trend as well as regional differences of annual and seasonal total precipitation were investigated by precipitation index such as precipitation concentration index (PCI) and Standardized Anomaly Index (SAI). Results demonstrate significant negative long-term linear trends in southeastern TP and the north central part of the TP, indicating arid and semi-arid regions in the TP are getting drier. The empirical mode decomposition (EMD) method shows an evolution of the main cycle with 4 and 12 months for all the representative grids of four sub-regions. The cross-wavelet analysis suggests that predominant and effective period of Indian Ocean Dipole (IOD) on monthly precipitation is around ˜12 months, except for the representative grid of the northwestern region.

Development of Spatiotemporal Bias-Correction Techniques for Downscaling GCM Predictions

NASA Astrophysics Data System (ADS)

Hwang, S.; Graham, W. D.; Geurink, J.; Adams, A.; Martinez, C. J.

2010-12-01

Accurately representing the spatial variability of precipitation is an important factor for predicting watershed response to climatic forcing, particularly in small, low-relief watersheds affected by convective storm systems. Although Global Circulation Models (GCMs) generally preserve spatial relationships between large-scale and local-scale mean precipitation trends, most GCM downscaling techniques focus on preserving only observed temporal variability on point by point basis, not spatial patterns of events. Downscaled GCM results (e.g., CMIP3 ensembles) have been widely used to predict hydrologic implications of climate variability and climate change in large snow-dominated river basins in the western United States (Diffenbaugh et al., 2008; Adam et al., 2009). However fewer applications to smaller rain-driven river basins in the southeastern US (where preserving spatial variability of rainfall patterns may be more important) have been reported. In this study a new method was developed to bias-correct GCMs to preserve both the long term temporal mean and variance of the precipitation data, and the spatial structure of daily precipitation fields. Forty-year retrospective simulations (1960-1999) from 16 GCMs were collected (IPCC, 2007; WCRP CMIP3 multi-model database: https://esg.llnl.gov:8443/), and the daily precipitation data at coarse resolution (i.e., 280km) were interpolated to 12km spatial resolution and bias corrected using gridded observations over the state of Florida (Maurer et al., 2002; Wood et al, 2002; Wood et al, 2004). In this method spatial random fields which preserved the observed spatial correlation structure of the historic gridded observations and the spatial mean corresponding to the coarse scale GCM daily rainfall were generated. The spatiotemporal variability of the spatio-temporally bias-corrected GCMs were evaluated against gridded observations, and compared to the original temporally bias-corrected and downscaled CMIP3 data for the central Florida. The hydrologic response of two southwest Florida watersheds to the gridded observation data, the original bias corrected CMIP3 data, and the new spatiotemporally corrected CMIP3 predictions was compared using an integrated surface-subsurface hydrologic model developed by Tampa Bay Water.

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

NASA Astrophysics Data System (ADS)

Pouliot, George Antoine

2000-10-01

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

Methane Emissions From Western Siberian Wetlands: Heterogeneity and Sensitivity to Climate Change

NASA Astrophysics Data System (ADS)

Bohn, T. J.; Lettenmaier, D. P.; Podest, E.; McDonald, K. C.; Sathulur, K.; Bowling, L. C.; Friborg, T.

2007-12-01

Prediction of methane emissions from high-latitude wetlands is important given concerns about their sensitivity to a warming climate. As a basis for prediction of wetland methane emissions at regional scales, we have coupled the Variable Infiltration Capacity macroscale hydrological model (VIC) with the Biosphere-Energy-Transfer- Hydrology terrestrial ecosystem model (BETHY) and a wetland methane emissions model to make large-scale estimates of methane emissions as a function of soil temperature, water table depth, and net primary productivity (NPP), with a parameterization of the sub-grid heterogeneity of the water table depth based on topographic wetness index. Using landcover classifications derived from L-band satellite synthetic aperture radar imagery, we simulated methane emissions for the Chaya River basin in western Siberia, an area that includes the Bakchar Bog, for a retrospective baseline period of 1980-1999, and evaluated their sensitivity to increases in temperature of 0-5 °C and increases in precipitation of 0-15%. The interactions of temperature and precipitation, through their effects on the water table depth, play an important role in determining methane emissions from these wetlands. The balance between these effects varies spatially, and their net effect depends in part on sub- grid topographic heterogeneity. Higher temperatures alone increase methane production in saturated areas, but cause those saturated areas to shrink in extent, resulting in a net reduction in methane emissions. Higher precipitation alone raises water tables and expands the saturated area, resulting in a net increase in methane emissions. Combining a temperature increase of 3 °C and an increase of 10% in precipitation, to represent the climate conditions likely in western Siberia at the end of this century, results in roughly a doubling of annual methane emissions. This work was carried out at the University of Washington, at Purdue University, and at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

Sub-grid-scale description of turbulent magnetic reconnection in magnetohydrodynamics

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

Widmer, F., E-mail: widmer@mps.mpg.de; Institut für Astrophysik, Georg-August-Universität, Friedrich-Hund-Platz 1, 37077 Göttingen; Büchner, J.

Magnetic reconnection requires, at least locally, a non-ideal plasma response. In collisionless space and astrophysical plasmas, turbulence could transport energy from large to small scales where binary particle collisions are rare. We have investigated the influence of small scale magnetohydrodynamics (MHD) turbulence on the reconnection rate in the framework of a compressible MHD approach including sub-grid-scale (SGS) turbulence. For this sake, we considered Harris-type and force-free current sheets with finite guide magnetic fields directed out of the reconnection plane. The goal is to find out whether unresolved by conventional simulations MHD turbulence can enhance the reconnection process in high-Reynolds-number astrophysicalmore » plasmas. Together with the MHD equations, we solve evolution equations for the SGS energy and cross-helicity due to turbulence according to a Reynolds-averaged turbulence model. The SGS turbulence is self-generated and -sustained through the inhomogeneities of the mean fields. By this way, the feedback of the unresolved turbulence into the MHD reconnection process is taken into account. It is shown that the turbulence controls the regimes of reconnection by its characteristic timescale τ{sub t}. The dependence on resistivity was investigated for large-Reynolds-number plasmas for Harris-type as well as force-free current sheets with guide field. We found that magnetic reconnection depends on the relation between the molecular and apparent effective turbulent resistivity. We found that the turbulence timescale τ{sub t} decides whether fast reconnection takes place or whether the stored energy is just diffused away to small scale turbulence. If the amount of energy transferred from large to small scales is enhanced, fast reconnection can take place. Energy spectra allowed us to characterize the different regimes of reconnection. It was found that reconnection is even faster for larger Reynolds numbers controlled by the molecular resistivity η, as long as the initial level of turbulence is not too large. This implies that turbulence plays an important role to reach the limit of fast reconnection in large Reynolds number plasmas even for smaller amounts of turbulence.« less

Regional climates in the GISS general circulation model: Surface air temperature

NASA Technical Reports Server (NTRS)

Hewitson, Bruce

1994-01-01

One of the more viable research techniques into global climate change for the purpose of understanding the consequent environmental impacts is based on the use of general circulation models (GCMs). However, GCMs are currently unable to reliably predict the regional climate change resulting from global warming, and it is at the regional scale that predictions are required for understanding human and environmental responses. Regional climates in the extratropics are in large part governed by the synoptic-scale circulation and the feasibility of using this interscale relationship is explored to provide a way of moving to grid cell and sub-grid cell scales in the model. The relationships between the daily circulation systems and surface air temperature for points across the continental United States are first developed in a quantitative form using a multivariate index based on principal components analysis (PCA) of the surface circulation. These relationships are then validated by predicting daily temperature using observed circulation and comparing the predicted values with the observed temperatures. The relationships predict surface temperature accurately over the major portion of the country in winter, and for half the country in summer. These relationships are then applied to the surface synoptic circulation of the Goddard Institute for Space Studies (GISS) GCM control run, and a set of surface grid cell temperatures are generated. These temperatures, based on the larger-scale validated circulation, may now be used with greater confidence at the regional scale. The generated temperatures are compared to those of the model and show that the model has regional errors of up to 10 C in individual grid cells.

Spatial scaling of net primary productivity using subpixel landcover information

NASA Astrophysics Data System (ADS)

Chen, X. F.; Chen, Jing M.; Ju, Wei M.; Ren, L. L.

2008-10-01

Gridding the land surface into coarse homogeneous pixels may cause important biases on ecosystem model estimations of carbon budget components at local, regional and global scales. These biases result from overlooking subpixel variability of land surface characteristics. Vegetation heterogeneity is an important factor introducing biases in regional ecological modeling, especially when the modeling is made on large grids. This study suggests a simple algorithm that uses subpixel information on the spatial variability of land cover type to correct net primary productivity (NPP) estimates, made at coarse spatial resolutions where the land surface is considered as homogeneous within each pixel. The algorithm operates in such a way that NPP obtained from calculations made at coarse spatial resolutions are multiplied by simple functions that attempt to reproduce the effects of subpixel variability of land cover type on NPP. Its application to a carbon-hydrology coupled model(BEPS-TerrainLab model) estimates made at a 1-km resolution over a watershed (named Baohe River Basin) located in the southwestern part of Qinling Mountains, Shaanxi Province, China, improved estimates of average NPP as well as its spatial variability.

Grid-cell-based crop water accounting for the famine early warning system

USGS Publications Warehouse

Verdin, J.; Klaver, R.

2002-01-01

Rainfall monitoring is a regular activity of food security analysts for sub-Saharan Africa due to the potentially disastrous impact of drought. Crop water accounting schemes are used to track rainfall timing and amounts relative to phenological requirements, to infer water limitation impacts on yield. Unfortunately, many rain gauge reports are available only after significant delays, and the gauge locations leave large gaps in coverage. As an alternative, a grid-cell-based formulation for the water requirement satisfaction index (WRSI) was tested for maize in Southern Africa. Grids of input variables were obtained from remote sensing estimates of rainfall, meteorological models, and digital soil maps. The spatial WRSI was computed for the 1996–97 and 1997–98 growing seasons. Maize yields were estimated by regression and compared with a limited number of reports from the field for the 1996–97 season in Zimbabwe. Agreement at a useful level (r = 0·80) was observed. This is comparable to results from traditional analysis with station data. The findings demonstrate the complementary role that remote sensing, modelling, and geospatial analysis can play in an era when field data collection in sub-Saharan Africa is suffering an unfortunate decline.

The role of optimality in characterizing CO2 seepage from geological carbon sequestration sites

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

Cortis, Andrea; Oldenburg, Curtis M.; Benson, Sally M.

Storage of large amounts of carbon dioxide (CO{sub 2}) in deep geological formations for greenhouse gas mitigation is gaining momentum and moving from its conceptual and testing stages towards widespread application. In this work we explore various optimization strategies for characterizing surface leakage (seepage) using near-surface measurement approaches such as accumulation chambers and eddy covariance towers. Seepage characterization objectives and limitations need to be defined carefully from the outset especially in light of large natural background variations that can mask seepage. The cost and sensitivity of seepage detection are related to four critical length scales pertaining to the size ofmore » the: (1) region that needs to be monitored; (2) footprint of the measurement approach, and (3) main seepage zone; and (4) region in which concentrations or fluxes are influenced by seepage. Seepage characterization objectives may include one or all of the tasks of detecting, locating, and quantifying seepage. Each of these tasks has its own optimal strategy. Detecting and locating seepage in a region in which there is no expected or preferred location for seepage nor existing evidence for seepage requires monitoring on a fixed grid, e.g., using eddy covariance towers. The fixed-grid approaches needed to detect seepage are expected to require large numbers of eddy covariance towers for large-scale geologic CO{sub 2} storage. Once seepage has been detected and roughly located, seepage zones and features can be optimally pinpointed through a dynamic search strategy, e.g., employing accumulation chambers and/or soil-gas sampling. Quantification of seepage rates can be done through measurements on a localized fixed grid once the seepage is pinpointed. Background measurements are essential for seepage detection in natural ecosystems. Artificial neural networks are considered as regression models useful for distinguishing natural system behavior from anomalous behavior suggestive of CO{sub 2} seepage without need for detailed understanding of natural system processes. Because of the local extrema in CO{sub 2} fluxes and concentrations in natural systems, simple steepest-descent algorithms are not effective and evolutionary computation algorithms are proposed as a paradigm for dynamic monitoring networks to pinpoint CO{sub 2} seepage areas.« less

Domain decomposition by the advancing-partition method for parallel unstructured grid generation

NASA Technical Reports Server (NTRS)

Banihashemi, legal representative, Soheila (Inventor); Pirzadeh, Shahyar Z. (Inventor)

2012-01-01

In a method for domain decomposition for generating unstructured grids, a surface mesh is generated for a spatial domain. A location of a partition plane dividing the domain into two sections is determined. Triangular faces on the surface mesh that intersect the partition plane are identified. A partition grid of tetrahedral cells, dividing the domain into two sub-domains, is generated using a marching process in which a front comprises only faces of new cells which intersect the partition plane. The partition grid is generated until no active faces remain on the front. Triangular faces on each side of the partition plane are collected into two separate subsets. Each subset of triangular faces is renumbered locally and a local/global mapping is created for each sub-domain. A volume grid is generated for each sub-domain. The partition grid and volume grids are then merged using the local-global mapping.

Understanding generalized inversions of nuclear magnetic resonance transverse relaxation time in porous media

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

Mitchell, J., E-mail: JMitchell16@slb.com; Chandrasekera, T. C.

2014-12-14

The nuclear magnetic resonance transverse relaxation time T{sub 2}, measured using the Carr-Purcell-Meiboom-Gill (CPMG) experiment, is a powerful method for obtaining unique information on liquids confined in porous media. Furthermore, T{sub 2} provides structural information on the porous material itself and has many applications in petrophysics, biophysics, and chemical engineering. Robust interpretation of T{sub 2} distributions demands appropriate processing of the measured data since T{sub 2} is influenced by diffusion through magnetic field inhomogeneities occurring at the pore scale, caused by the liquid/solid susceptibility contrast. Previously, we introduced a generic model for the diffusion exponent of the form −ant{sub e}{supmore » k} (where n is the number and t{sub e} the temporal separation of spin echoes, and a is a composite diffusion parameter) in order to distinguish the influence of relaxation and diffusion in CPMG data. Here, we improve the analysis by introducing an automatic search for the optimum power k that best describes the diffusion behavior. This automated method is more efficient than the manual trial-and-error grid search adopted previously, and avoids variability through subjective judgments of experimentalists. Although our method does not avoid the inherent assumption that the diffusion exponent depends on a single k value, we show through simulation and experiment that it is robust in measurements of heterogeneous systems that violate this assumption. In this way, we obtain quantitative T{sub 2} distributions from complicated porous structures and demonstrate the analysis with examples of ceramics used for filtration and catalysis, and limestone of relevance to the construction and petroleum industries.« less

Maintaining Balance: The Increasing Role of Energy Storage for Renewable Integration

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

Stenclik, Derek; Denholm, Paul; Chalamala, Babu

For nearly a century, global power systems have focused on three key functions: to generate, transmit, and distribute electricity as a real-time commodity. Physics requires that electricity generation always be in real-time balance with load, despite variability in load on timescales ranging from sub-second disturbances to multi-year trends. With the increasing role of variable generation from wind and solar, retirements of fossil fuel-based generation, and a changing consumer demand profile, grid operators are using new methods to maintain this balance.

Maintaining Balance: The Increasing Role of Energy Storage for Renewable Integration

DOE PAGES

Stenclik, Derek; Denholm, Paul; Chalamala, Babu

2017-10-17

For nearly a century, global power systems have focused on three key functions: to generate, transmit, and distribute electricity as a real-time commodity. Physics requires that electricity generation always be in real-time balance with load, despite variability in load on timescales ranging from sub-second disturbances to multi-year trends. With the increasing role of variable generation from wind and solar, retirements of fossil fuel-based generation, and a changing consumer demand profile, grid operators are using new methods to maintain this balance.

Evaluation of cumulus cloud – radiation interaction effects on air quality –relevant meteorological variables from WRF, from a regional climate perspective

EPA Science Inventory

Aware only of the resolved, grid-scale clouds, the Weather Research & Forecasting model (WRF) does not consider the interactions between subgrid-scale convective clouds and radiation. One consequence of this omission may be WRF’s overestimation of surface precipitation during sum...

Achieving a 100% Renewable Grid: Operating Electric Power Systems with Extremely High Levels of Variable Renewable Energy

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

Kroposki, Benjamin; Johnson, Brian; Zhang, Yingchen

What does it mean to achieve a 100% renewable grid? Several countries already meet or come close to achieving this goal. Iceland, for example, supplies 100% of its electricity needs with either geothermal or hydropower. Other countries that have electric grids with high fractions of renewables based on hydropower include Norway (97%), Costa Rica (93%), Brazil (76%), and Canada (62%). Hydropower plants have been used for decades to create a relatively inexpensive, renewable form of energy, but these systems are limited by natural rainfall and geographic topology. Around the world, most good sites for large hydropower resources have already beenmore » developed. So how do other areas achieve 100% renewable grids? Variable renewable energy (VRE), such as wind and solar photovoltaic (PV) systems, will be a major contributor, and with the reduction in costs for these technologies during the last five years, large-scale deployments are happening around the world.« less

Demonstration of Active Power Controls by Utility-Scale PV Power Plant in an Island Grid: Preprint

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

Gevorgian, Vahan; O'Neill, Barbara

The National Renewable Energy Laboratory (NREL), AES, and the Puerto Rico Electric Power Authority conducted a demonstration project on a utility-scale photovoltaic (PV) plant to test the viability of providing important ancillary services from this facility. As solar generation increases globally, there is a need for innovation and increased operational flexibility. A typical PV power plant consists of multiple power electronic inverters and can contribute to grid stability and reliability through sophisticated 'grid-friendly' controls. In this way, it may mitigate the impact of its variability on the grid and contribute to important system requirements more like traditional generators. In 2015,more » testing was completed on a 20-MW AES plant in Puerto Rico, and a large amount of test data was produced and analyzed that demonstrates the ability of PV power plants to provide various types of new grid-friendly controls. This data showed how active power controls can leverage PV's value from being simply an intermittent energy resource to providing additional ancillary services for an isolated island grid. Specifically, the tests conducted included PV plant participation in automatic generation control, provision of droop response, and fast frequency response.« less

Regional Climate Simulation and Data Assimilation with Variable-Resolution GCMs

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.

2002-01-01

Variable resolution GCMs using a global stretched grid (SG) with enhanced regional resolution over one or multiple areas of interest represents a viable new approach to regional climateklimate change and data assimilation studies and applications. The multiple areas of interest, at least one within each global quadrant, include the major global mountains and major global monsoonal circulations over North America, South America, India-China, and Australia. They also can include the polar domains, and the European and African regions. The SG-approach provides an efficient regional downscaling to mesoscales, and it is an ideal tool for representing consistent interactions of globaYlarge- and regionallmeso- scales while preserving the high quality of global circulation. Basically, the SG-GCM simulations are no different from those of the traditional uniform-grid GCM simulations besides using a variable-resolution grid. Several existing SG-GCMs developed by major centers and groups are briefly described. The major discussion is based on the GEOS (Goddard Earth Observing System) SG-GCM regional climate simulations.

The FIM-iHYCOM Model in SubX: Evaluation of Subseasonal Errors and Variability

NASA Astrophysics Data System (ADS)

Green, B.; Sun, S.; Benjamin, S.; Grell, G. A.; Bleck, R.

2017-12-01

NOAA/ESRL/GSD has produced both real-time and retrospective forecasts for the Subseasonal Experiment (SubX) using the FIM-iHYCOM model. FIM-iHYCOM couples the atmospheric Flow-following finite volume Icosahedral Model (FIM) to an icosahedral-grid version of the Hybrid Coordinate Ocean Model (HYCOM). This coupled model is unique in terms of its grid structure: in the horizontal, the icosahedral meshes are perfectly matched for FIM and iHYCOM, eliminating the need for a flux interpolator; in the vertical, both models use adaptive arbitrary Lagrangian-Eulerian hybrid coordinates. For SubX, FIM-iHYCOM initializes four time-lagged ensemble members around each Wednesday, which are integrated forward to provide 32-day forecasts. While it has already been shown that this model has similar predictive skill as NOAA's operational CFSv2 in terms of the RMM index, FIM-iHYCOM is still fairly new and thus its overall performance needs to be thoroughly evaluated. To that end, this study examines model errors as a function of forecast lead week (1-4) - i.e., model drift - for key variables including 2-m temperature, precipitation, and SST. Errors are evaluated against two reanalysis products: CFSR, from which FIM-iHYCOM initial conditions are derived, and the quasi-independent ERA-Interim. The week 4 error magnitudes are similar between FIM-iHYCOM and CFSv2, albeit with different spatial distributions. Also, intraseasonal variability as simulated in these two models will be compared with reanalyses. The impact of hindcast frequency (4 times per week, once per week, or once per day) on the model climatology is also examined to determine the implications for systematic error correction in FIM-iHYCOM.

A critical source area phosphorus index with topographic transport factors using high resolution LiDAR digital elevation models

NASA Astrophysics Data System (ADS)

Thomas, Ian; Murphy, Paul; Fenton, Owen; Shine, Oliver; Mellander, Per-Erik; Dunlop, Paul; Jordan, Phil

2015-04-01

A new phosphorus index (PI) tool is presented which aims to improve the identification of critical source areas (CSAs) of phosphorus (P) losses from agricultural land to surface waters. In a novel approach, the PI incorporates topographic indices rather than watercourse proximity as proxies for runoff risk, to account for the dominant control of topography on runoff-generating areas and P transport pathways. Runoff propensity and hydrological connectivity are modelled using the Topographic Wetness Index (TWI) and Network Index (NI) respectively, utilising high resolution digital elevation models (DEMs) derived from Light Detection and Ranging (LiDAR) to capture the influence of micro-topographic features on runoff pathways. Additionally, the PI attempts to improve risk estimates of particulate P losses by incorporating an erosion factor that accounts for fine-scale topographic variability within fields. Erosion risk is modelled using the Unit Stream Power Erosion Deposition (USPED) model, which integrates DEM-derived upslope contributing area and Universal Soil Loss Equation (USLE) factors. The PI was developed using field, sub-field and sub-catchment scale datasets of P source, mobilisation and transport factors, for four intensive agricultural catchments in Ireland representing different agri-environmental conditions. Datasets included soil test P concentrations, degree of P saturation, soil attributes, land use, artificial subsurface drainage locations, and 2 m resolution LiDAR DEMs resampled from 0.25 m resolution data. All factor datasets were integrated within a Geographical Information System (GIS) and rasterised to 2 m resolution. For each factor, values were categorised and assigned relative risk scores which ranked P loss potential. Total risk scores were calculated for each grid cell using a component formulation, which summed the products of weighted factor risk scores for runoff and erosion pathways. Results showed that the new PI was able to predict in-field risk variability and hence was able to identify CSAs at the sub-field scale. PI risk estimates and component scores were analysed at catchment and subcatchment scales, and validated using measured dissolved, particulate and total P losses at subcatchment snapshot sites and gauging stations at catchment outlets. The new PI provides CSA delineations at higher precision compared to conventional PIs, and more robust P transport risk estimates. The tool can be used to target cost-effective mitigation measures for P management within single farm units and wider catchments.

Can high resolution topographic surveys provide reliable grain size estimates?

NASA Astrophysics Data System (ADS)

Pearson, Eleanor; Smith, Mark; Klaar, Megan; Brown, Lee

2017-04-01

High resolution topographic surveys contain a wealth of information that is not always exploited in the generation of Digital Elevation Models (DEMs). In particular, several authors have related sub-grid scale topographic variability (or 'surface roughness') to particle grain size by deriving empirical relationships between the two. Such relationships would permit rapid analysis of the spatial distribution of grain size over entire river reaches, providing data to drive distributed hydraulic models and revolutionising monitoring of river restoration projects. However, comparison of previous roughness-grain-size relationships shows substantial variability between field sites and do not take into account differences in patch-scale facies. This study explains this variability by identifying the factors that influence roughness-grain-size relationships. Using 275 laboratory and field-based Structure-from-Motion (SfM) surveys, we investigate the influence of: inherent survey error; irregularity of natural gravels; particle shape; grain packing structure; sorting; and form roughness on roughness-grain-size relationships. A suite of empirical relationships is presented in the form of a decision tree which improves estimations of grain size. Results indicate that the survey technique itself is capable of providing accurate grain size estimates. By accounting for differences in patch facies, R2 was seen to improve from 0.769 to R2 > 0.9 for certain facies. However, at present, the method is unsuitable for poorly sorted gravel patches. In future, a combination of a surface roughness proxy with photosieving techniques using SfM-derived orthophotos may offer improvements on using either technique individually.

Modal Analysis for Grid Operation

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

MANGO software is to provide a solution for improving small signal stability of power systems through adjusting operator-controllable variables using PMU measurement. System oscillation problems are one of the major threats to the grid stability and reliability in California and the Western Interconnection. These problems result in power fluctuations, lower grid operation efficiency, and may even lead to large-scale grid breakup and outages. This MANGO software aims to solve this problem by automatically generating recommended operation procedures termed Modal Analysis for Grid Operation (MANGO) to improve damping of inter-area oscillation modes. The MANGO procedure includes three steps: recognizing small signalmore » stability problems, implementing operating point adjustment using modal sensitivity, and evaluating the effectiveness of the adjustment. The MANGO software package is designed to help implement the MANGO procedure.« less

Climate and Water Vulnerability of the US Electricity Grid Under High Penetrations of Renewable Energy

NASA Astrophysics Data System (ADS)

Macknick, J.; Miara, A.; O'Connell, M.; Vorosmarty, C. J.; Newmark, R. L.

2017-12-01

The US power sector is highly dependent upon water resources for reliable operations, primarily for thermoelectric cooling and hydropower technologies. Changes in the availability and temperature of water resources can limit electricity generation and cause outages at power plants, which substantially affect grid-level operational decisions. While the effects of water variability and climate changes on individual power plants are well documented, prior studies have not identified the significance of these impacts at the regional systems-level at which the grid operates, including whether there are risks for large-scale blackouts, brownouts, or increases in production costs. Adequately assessing electric grid system-level impacts requires detailed power sector modeling tools that can incorporate electric transmission infrastructure, capacity reserves, and other grid characteristics. Here, we present for the first time, a study of how climate and water variability affect operations of the power sector, considering different electricity sector configurations (low vs. high renewable) and environmental regulations. We use a case study of the US Eastern Interconnection, building off the Eastern Renewable Generation Integration Study (ERGIS) that explored operational challenges of high penetrations of renewable energy on the grid. We evaluate climate-water constraints on individual power plants, using the Thermoelectric Power and Thermal Pollution (TP2M) model coupled with the PLEXOS electricity production cost model, in the context of broader electricity grid operations. Using a five minute time step for future years, we analyze scenarios of 10% to 30% renewable energy penetration along with considerations of river temperature regulations to compare the cost, performance, and reliability tradeoffs of water-dependent thermoelectric generation and variable renewable energy technologies under climate stresses. This work provides novel insights into the resilience and reliability of different configurations of the US electric grid subject to changing climate conditions.

Challenges of Representing Sub-Grid Physics in an Adaptive Mesh Refinement Atmospheric Model

NASA Astrophysics Data System (ADS)

O'Brien, T. A.; Johansen, H.; Johnson, J. N.; Rosa, D.; Benedict, J. J.; Keen, N. D.; Collins, W.; Goodfriend, E.

2015-12-01

Some of the greatest potential impacts from future climate change are tied to extreme atmospheric phenomena that are inherently multiscale, including tropical cyclones and atmospheric rivers. Extremes are challenging to simulate in conventional climate models due to existing models' coarse resolutions relative to the native length-scales of these phenomena. Studying the weather systems of interest requires an atmospheric model with sufficient local resolution, and sufficient performance for long-duration climate-change simulations. To this end, we have developed a new global climate code with adaptive spatial and temporal resolution. The dynamics are formulated using a block-structured conservative finite volume approach suitable for moist non-hydrostatic atmospheric dynamics. By using both space- and time-adaptive mesh refinement, the solver focuses computational resources only where greater accuracy is needed to resolve critical phenomena. We explore different methods for parameterizing sub-grid physics, such as microphysics, macrophysics, turbulence, and radiative transfer. In particular, we contrast the simplified physics representation of Reed and Jablonowski (2012) with the more complex physics representation used in the System for Atmospheric Modeling of Khairoutdinov and Randall (2003). We also explore the use of a novel macrophysics parameterization that is designed to be explicitly scale-aware.

The Applied Mathematics for Power Systems (AMPS)

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

Chertkov, Michael

2012-07-24

Increased deployment of new technologies, e.g., renewable generation and electric vehicles, is rapidly transforming electrical power networks by crossing previously distinct spatiotemporal scales and invalidating many traditional approaches for designing, analyzing, and operating power grids. This trend is expected to accelerate over the coming years, bringing the disruptive challenge of complexity, but also opportunities to deliver unprecedented efficiency and reliability. Our Applied Mathematics for Power Systems (AMPS) Center will discover, enable, and solve emerging mathematics challenges arising in power systems and, more generally, in complex engineered networks. We will develop foundational applied mathematics resulting in rigorous algorithms and simulation toolboxesmore » for modern and future engineered networks. The AMPS Center deconstruction/reconstruction approach 'deconstructs' complex networks into sub-problems within non-separable spatiotemporal scales, a missing step in 20th century modeling of engineered networks. These sub-problems are addressed within the appropriate AMPS foundational pillar - complex systems, control theory, and optimization theory - and merged or 'reconstructed' at their boundaries into more general mathematical descriptions of complex engineered networks where important new questions are formulated and attacked. These two steps, iterated multiple times, will bridge the growing chasm between the legacy power grid and its future as a complex engineered network.« less

Assessment of sub-grid scale dispersion closure with regularized deconvolution method in a particle-laden turbulent jet

NASA Astrophysics Data System (ADS)

Wang, Qing; Zhao, Xinyu; Ihme, Matthias

2017-11-01

Particle-laden turbulent flows are important in numerous industrial applications, such as spray combustion engines, solar energy collectors etc. It is of interests to study this type of flows numerically, especially using large-eddy simulations (LES). However, capturing the turbulence-particle interaction in LES remains challenging due to the insufficient representation of the effect of sub-grid scale (SGS) dispersion. In the present work, a closure technique for the SGS dispersion using regularized deconvolution method (RDM) is assessed. RDM was proposed as the closure for the SGS dispersion in a counterflow spray that is studied numerically using finite difference method on a structured mesh. A presumed form of LES filter is used in the simulations. In the present study, this technique has been extended to finite volume method with an unstructured mesh, where no presumption on the filter form is required. The method is applied to a series of particle-laden turbulent jets. Parametric analyses of the model performance are conducted for flows with different Stokes numbers and Reynolds numbers. The results from LES will be compared against experiments and direct numerical simulations (DNS).

High Resolution Simulations of Future Climate in West Africa Using a Variable-Resolution Atmospheric Model

NASA Astrophysics Data System (ADS)

Adegoke, J. O.; Engelbrecht, F.; Vezhapparambu, S.

2013-12-01

In previous work demonstrated the application of a var¬iable-resolution global atmospheric model, the conformal-cubic atmospheric model (CCAM), across a wide range of spatial and time scales to investigate the ability of the model to provide realistic simulations of present-day climate and plausible projections of future climate change over sub-Saharan Africa. By applying the model in stretched-grid mode the versatility of the model dynamics, numerical formulation and physical parameterizations to function across a range of length scales over the region of interest, was also explored. We primarily used CCAM to illustrate the capability of the model to function as a flexible downscaling tool at the climate-change time scale. Here we report on additional long term climate projection studies performed by downscaling at much higher resolutions (8 Km) over an area that stretches from just south of Sahara desert to the southern coast of the Niger Delta and into the Gulf of Guinea. To perform these simulations, CCAM was provided with synoptic-scale forcing of atmospheric circulation from 2.5 deg resolution NCEP reanalysis at 6-hourly interval and SSTs from NCEP reanalysis data uses as lower boundary forcing. CCAM 60 Km resolution downscaled to 8 Km (Schmidt factor 24.75) then 8 Km resolution simulation downscaled to 1 Km (Schmidt factor 200) over an area approximately 50 Km x 50 Km in the southern Lake Chad Basin (LCB). Our intent in conducting these high resolution model runs was to obtain a deeper understanding of linkages between the projected future climate and the hydrological processes that control the surface water regime in this part of sub-Saharan Africa.

Coupled ice sheet - climate simulations of the last glacial inception and last glacial maximum with a model of intermediate complexity that includes a dynamical downscaling of heat and moisture

NASA Astrophysics Data System (ADS)

Quiquet, Aurélien; Roche, Didier M.

2017-04-01

Comprehensive fully coupled ice sheet - climate models allowing for multi-millenia transient simulations are becoming available. They represent powerful tools to investigate ice sheet - climate interactions during the repeated retreats and advances of continental ice sheets of the Pleistocene. However, in such models, most of the time, the spatial resolution of the ice sheet model is one order of magnitude lower than the one of the atmospheric model. As such, orography-induced precipitation is only poorly represented. In this work, we briefly present the most recent improvements of the ice sheet - climate coupling within the model of intermediate complexity iLOVECLIM. On the one hand, from the native atmospheric resolution (T21), we have included a dynamical downscaling of heat and moisture at the ice sheet model resolution (40 km x 40 km). This downscaling accounts for feedbacks of sub-grid precipitation on large scale energy and water budgets. From the sub-grid atmospheric variables, we compute an ice sheet surface mass balance required by the ice sheet model. On the other hand, we also explicitly use oceanic temperatures to compute sub-shelf melting at a given depth. Based on palaeo evidences for rate of change of eustatic sea level, we discuss the capability of our new model to correctly simulate the last glacial inception ( 116 kaBP) and the ice volume of the last glacial maximum ( 21 kaBP). We show that the model performs well in certain areas (e.g. Canadian archipelago) but some model biases are consistent over time periods (e.g. Kara-Barents sector). We explore various model sensitivities (e.g. initial state, vegetation, albedo) and we discuss the importance of the downscaling of precipitation for ice nucleation over elevated area and for the surface mass balance of larger ice sheets.

Error Estimates of the Ares I Computed Turbulent Ascent Longitudinal Aerodynamic Analysis

NASA Technical Reports Server (NTRS)

Abdol-Hamid, Khaled S.; Ghaffari, Farhad

2012-01-01

Numerical predictions of the longitudinal aerodynamic characteristics for the Ares I class of vehicles, along with the associated error estimate derived from an iterative convergence grid refinement, are presented. Computational results are based on an unstructured grid, Reynolds-averaged Navier-Stokes analysis. The validity of the approach to compute the associated error estimates, derived from a base grid to an extrapolated infinite-size grid, was first demonstrated on a sub-scaled wind tunnel model at representative ascent flow conditions for which the experimental data existed. Such analysis at the transonic flow conditions revealed a maximum deviation of about 23% between the computed longitudinal aerodynamic coefficients with the base grid and the measured data across the entire roll angles. This maximum deviation from the wind tunnel data was associated with the computed normal force coefficient at the transonic flow condition and was reduced to approximately 16% based on the infinite-size grid. However, all the computed aerodynamic coefficients with the base grid at the supersonic flow conditions showed a maximum deviation of only about 8% with that level being improved to approximately 5% for the infinite-size grid. The results and the error estimates based on the established procedure are also presented for the flight flow conditions.

ANFIS-based modelling for coagulant dosage in drinking water treatment plant: a case study.

PubMed

Heddam, Salim; Bermad, Abdelmalek; Dechemi, Noureddine

2012-04-01

Coagulation is the most important stage in drinking water treatment processes for the maintenance of acceptable treated water quality and economic plant operation, which involves many complex physical and chemical phenomena. Moreover, coagulant dosing rate is non-linearly correlated to raw water characteristics such as turbidity, conductivity, pH, temperature, etc. As such, coagulation reaction is hard or even impossible to control satisfactorily by conventional methods. Traditionally, jar tests are used to determine the optimum coagulant dosage. However, this is expensive and time-consuming and does not enable responses to changes in raw water quality in real time. Modelling can be used to overcome these limitations. In this study, an Adaptive Neuro-Fuzzy Inference System (ANFIS) was used for modelling of coagulant dosage in drinking water treatment plant of Boudouaou, Algeria. Six on-line variables of raw water quality including turbidity, conductivity, temperature, dissolved oxygen, ultraviolet absorbance, and the pH of water, and alum dosage were used to build the coagulant dosage model. Two ANFIS-based Neuro-fuzzy systems are presented. The two Neuro-fuzzy systems are: (1) grid partition-based fuzzy inference system (FIS), named ANFIS-GRID, and (2) subtractive clustering based (FIS), named ANFIS-SUB. The low root mean square error and high correlation coefficient values were obtained with ANFIS-SUB method of a first-order Sugeno type inference. This study demonstrates that ANFIS-SUB outperforms ANFIS-GRID due to its simplicity in parameter selection and its fitness in the target problem.

The Addenbrooke's Cognitive Examination Revised (ACE-R) and its sub-scores: normative values in an Italian population sample.

PubMed

Siciliano, Mattia; Raimo, Simona; Tufano, Dario; Basile, Giuseppe; Grossi, Dario; Santangelo, Franco; Trojano, Luigi; Santangelo, Gabriella

2016-03-01

The Addenbrooke's Cognitive Examination Revised (ACE-R) is a rapid screening battery, including five sub-scales to explore different cognitive domains: attention/orientation, memory, fluency, language and visuospatial. ACE-R is considered useful in discriminating cognitively normal subjects from patients with mild dementia. The aim of present study was to provide normative values for ACE-R total score and sub-scale scores in a large sample of Italian healthy subjects. Five hundred twenty-six Italian healthy subjects (282 women and 246 men) of different ages (age range 20-93 years) and educational level (from primary school to university) underwent ACE-R and Montreal Cognitive Assessment (MoCA). Multiple linear regression analysis revealed that age and education significantly influenced performance on ACE-R total score and sub-scale scores. A significant effect of gender was found only in sub-scale attention/orientation. From the derived linear equation, a correction grid for raw scores was built. Inferential cut-offs score were estimated using a non-parametric technique and equivalent scores (ES) were computed. Correlation analysis showed a good significant correlation between ACE-R adjusted scores with MoCA adjusted scores (r = 0.612, p < 0.001). The present study provided normative data for the ACE-R in an Italian population useful for both clinical and research purposes.

The modelling of dispersion in 2-D tidal flow over an uneven bed

NASA Astrophysics Data System (ADS)

Kalkwijk, Jan P. Th.

This paper deals with the effective mixing by topographic induced velocity variations in 2-D tidal flow. This type of mixing is characterized by tidally-averaged dispersion coefficients, which depend on the magnitude of the depth variations with respect to a mean depth, the velocity variations and the basic dispersion coefficients. The analysis is principally based on a Taylor type approximation (large clouds, small concentration variations) of the 2-D advection diffusion equation and a 2-D velocity field that behaves harmonically both in time and in space. Neglecting transient phenomena and applying time and space averaging the effective dispersion coefficients can be derived. Under certain circumstances it is possible to relate the velocity variations to the depth variations, so that finally effective dispersion coefficients can be determined using the power spectrum of the depth variations. In a special paragraph attention is paid to the modelling of sub-grid mixing in case of numerical integration of the advection-diffusion equation. It appears that the dispersion coefficients taking account of the sub-grid mixing are not only determined by the velocity variations within a certain grid cell, but also by the velocity variations at a larger scale.

Statistical downscaling of mean temperature, maximum temperature, and minimum temperature on the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Lin, Jiang; Miao, Chiyuan

2017-04-01

Climate change is considered to be one of the greatest environmental threats. This has urged scientific communities to focus on the hot topic. Global climate models (GCMs) are the primary tool used for studying climate change. However, GCMs are limited because of their coarse spatial resolution and inability to resolve important sub-grid scale features such as terrain and clouds. Statistical downscaling methods can be used to downscale large-scale variables to local-scale. In this study, we assess the applicability of the widely used Statistical Downscaling Model (SDSM) for the Loess Plateau, China. The observed variables included daily mean temperature (TMEAN), maximum temperature (TMAX) and minimum temperature (TMIN) from 1961 to 2005. The and the daily atmospheric data were taken from reanalysis data from 1961 to 2005, and global climate model outputs from Beijing Normal University Earth System Model (BNU-ESM) from 1961 to 2099 and from observations . The results show that SDSM performs well for these three climatic variables on the Loess Plateau. After downscaling, the root mean square errors for TMEAN, TMAX, TMIN for BNU-ESM were reduced by 70.9%, 75.1%, and 67.2%, respectively. All the rates of change in TMEAN, TMAX and TMIN during the 21st century decreased after SDSM downscaling. We also show that SDSM can effectively reduce uncertainty, compared with the raw model outputs. TMEAN uncertainty was reduced by 27.1%, 26.8%, and 16.3% for the future scenarios of RCP 2.6, RCP 4.5 and RCP 8.5, respectively. The corresponding reductions in uncertainty were 23.6%, 30.7%, and 18.7% for TMAX, ; and 37.6%, 31.8%, and 23.2% for TMIN.

Energy dynamics and current sheet structure in fluid and kinetic simulations of decaying magnetohydrodynamic turbulence

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

Makwana, K. D., E-mail: kirit.makwana@gmx.com; Cattaneo, F.; Zhdankin, V.

Simulations of decaying magnetohydrodynamic (MHD) turbulence are performed with a fluid and a kinetic code. The initial condition is an ensemble of long-wavelength, counter-propagating, shear-Alfvén waves, which interact and rapidly generate strong MHD turbulence. The total energy is conserved and the rate of turbulent energy decay is very similar in both codes, although the fluid code has numerical dissipation, whereas the kinetic code has kinetic dissipation. The inertial range power spectrum index is similar in both the codes. The fluid code shows a perpendicular wavenumber spectral slope of k{sub ⊥}{sup −1.3}. The kinetic code shows a spectral slope of k{submore » ⊥}{sup −1.5} for smaller simulation domain, and k{sub ⊥}{sup −1.3} for larger domain. We estimate that collisionless damping mechanisms in the kinetic code can account for the dissipation of the observed nonlinear energy cascade. Current sheets are geometrically characterized. Their lengths and widths are in good agreement between the two codes. The length scales linearly with the driving scale of the turbulence. In the fluid code, their thickness is determined by the grid resolution as there is no explicit diffusivity. In the kinetic code, their thickness is very close to the skin-depth, irrespective of the grid resolution. This work shows that kinetic codes can reproduce the MHD inertial range dynamics at large scales, while at the same time capturing important kinetic physics at small scales.« less

A stochastic parameterization for deep convection using cellular automata

NASA Astrophysics Data System (ADS)

Bengtsson, L.; Steinheimer, M.; Bechtold, P.; Geleyn, J.

2012-12-01

Cumulus parameterizations used in most operational weather and climate models today are based on the mass-flux concept which took form in the early 1970's. In such schemes it is assumed that a unique relationship exists between the ensemble-average of the sub-grid convection, and the instantaneous state of the atmosphere in a vertical grid box column. However, such a relationship is unlikely to be described by a simple deterministic function (Palmer, 2011). Thus, because of the statistical nature of the parameterization challenge, it has been recognized by the community that it is important to introduce stochastic elements to the parameterizations (for instance: Plant and Craig, 2008, Khouider et al. 2010, Frenkel et al. 2011, Bentsson et al. 2011, but the list is far from exhaustive). There are undoubtedly many ways in which stochastisity can enter new developments. In this study we use a two-way interacting cellular automata (CA), as its intrinsic nature possesses many qualities interesting for deep convection parameterization. In the one-dimensional entraining plume approach, there is no parameterization of horizontal transport of heat, moisture or momentum due to cumulus convection. In reality, mass transport due to gravity waves that propagate in the horizontal can trigger new convection, important for the organization of deep convection (Huang, 1988). The self-organizational characteristics of the CA allows for lateral communication between adjacent NWP model grid-boxes, and temporal memory. Thus the CA scheme used in this study contain three interesting components for representation of cumulus convection, which are not present in the traditional one-dimensional bulk entraining plume method: horizontal communication, memory and stochastisity. The scheme is implemented in the high resolution regional NWP model ALARO, and simulations show enhanced organization of convective activity along squall-lines. Probabilistic evaluation demonstrate an enhanced spread in large-scale variables in regions where convective activity is large. A two month extended evaluation of the deterministic behaviour of the scheme indicate a neutral impact on forecast skill. References: Bengtsson, L., H. Körnich, E. Källén, and G. Svensson, 2011: Large-scale dynamical response to sub-grid scale organization provided by cellular automata. Journal of the Atmospheric Sciences, 68, 3132-3144. Frenkel, Y., A. Majda, and B. Khouider, 2011: Using the stochastic multicloud model to improve tropical convective parameterization: A paradigm example. Journal of the Atmospheric Sciences, doi: 10.1175/JAS-D-11-0148.1. Huang, X.-Y., 1988: The organization of moist convection by internal 365 gravity waves. Tellus A, 42, 270-285. Khouider, B., J. Biello, and A. Majda, 2010: A Stochastic Multicloud Model for Tropical Convection. Comm. Math. Sci., 8, 187-216. Palmer, T., 2011: Towards the Probabilistic Earth-System Simulator: A Vision for the Future of Climate and Weather Prediction. Quarterly Journal of the Royal Meteorological Society 138 (2012) 841-861 Plant, R. and G. Craig, 2008: A stochastic parameterization for deep convection based on equilibrium statistics. J. Atmos. Sci., 65, 87-105.

Mixing in 3D Sparse Multi-Scale Grid Generated Turbulence

NASA Astrophysics Data System (ADS)

Usama, Syed; Kopec, Jacek; Tellez, Jackson; Kwiatkowski, Kamil; Redondo, Jose; Malik, Nadeem

2017-04-01

Flat 2D fractal grids are known to alter turbulence characteristics downstream of the grid as compared to the regular grids with the same blockage ratio and the same mass inflow rates [1]. This has excited interest in the turbulence community for possible exploitation for enhanced mixing and related applications. Recently, a new 3D multi-scale grid design has been proposed [2] such that each generation of length scale of turbulence grid elements is held in its own frame, the overall effect is a 3D co-planar arrangement of grid elements. This produces a 'sparse' grid system whereby each generation of grid elements produces a turbulent wake pattern that interacts with the other wake patterns downstream. A critical motivation here is that the effective blockage ratio in the 3D Sparse Grid Turbulence (3DSGT) design is significantly lower than in the flat 2D counterpart - typically the blockage ratio could be reduced from say 20% in 2D down to 4% in the 3DSGT. If this idea can be realized in practice, it could potentially greatly enhance the efficiency of turbulent mixing and transfer processes clearly having many possible applications. Work has begun on the 3DSGT experimentally using Surface Flow Image Velocimetry (SFIV) [3] at the European facility in the Max Planck Institute for Dynamics and Self-Organization located in Gottingen, Germany and also at the Technical University of Catalonia (UPC) in Spain, and numerically using Direct Numerical Simulation (DNS) at King Fahd University of Petroleum & Minerals (KFUPM) in Saudi Arabia and in University of Warsaw in Poland. DNS is the most useful method to compare the experimental results with, and we are studying different types of codes such as Imcompact3d, and OpenFoam. Many variables will eventually be investigated for optimal mixing conditions. For example, the number of scale generations, the spacing between frames, the size ratio of grid elements, inflow conditions, etc. We will report upon the first set of findings from the 3DSGT by the time of the conference. {Acknowledgements}: This work has been supported partly by the EuHIT grant, 'Turbulence Generated by Sparse 3D Multi-Scale Grid (M3SG)', 2017. {References} [1] S. Laizet, J. C. Vassilicos. DNS of Fractal-Generated Turbulence. Flow Turbulence Combust 87:673705, (2011). [2] N. A. Malik. Sparse 3D Multi-Scale Grid Turbulence Generator. USPTO Application no. 14/710,531, Patent Pending, (2015). [3] J. Tellez, M. Gomez, B. Russo, J.M. Redondo. Surface Flow Image Velocimetry (SFIV) for hydraulics applications. 18th Int. Symposium on the Application of Laser Imaging Techniques in Fluid Mechanics, Lisbon, Portugal (2016).

Evaluation of subgrid-scale turbulence models using a fully simulated turbulent flow

NASA Technical Reports Server (NTRS)

Clark, R. A.; Ferziger, J. H.; Reynolds, W. C.

1977-01-01

An exact turbulent flow field was calculated on a three-dimensional grid with 64 points on a side. The flow simulates grid-generated turbulence from wind tunnel experiments. In this simulation, the grid spacing is small enough to include essentially all of the viscous energy dissipation, and the box is large enough to contain the largest eddy in the flow. The method is limited to low-turbulence Reynolds numbers, in our case R sub lambda = 36.6. To complete the calculation using a reasonable amount of computer time with reasonable accuracy, a third-order time-integration scheme was developed which runs at about the same speed as a simple first-order scheme. It obtains this accuracy by saving the velocity field and its first-time derivative at each time step. Fourth-order accurate space-differencing is used.

Upscaling of Hydraulic Conductivity using the Double Constraint Method

NASA Astrophysics Data System (ADS)

El-Rawy, Mustafa; Zijl, Wouter; Batelaan, Okke

2013-04-01

The mathematics and modeling of flow through porous media is playing an increasingly important role for the groundwater supply, subsurface contaminant remediation and petroleum reservoir engineering. In hydrogeology hydraulic conductivity data are often collected at a scale that is smaller than the grid block dimensions of a groundwater model (e.g. MODFLOW). For instance, hydraulic conductivities determined from the field using slug and packer tests are measured in the order of centimeters to meters, whereas numerical groundwater models require conductivities representative of tens to hundreds of meters of grid cell length. Therefore, there is a need for upscaling to decrease the number of grid blocks in a groundwater flow model. Moreover, models with relatively few grid blocks are simpler to apply, especially when the model has to run many times, as is the case when it is used to assimilate time-dependent data. Since the 1960s different methods have been used to transform a detailed description of the spatial variability of hydraulic conductivity to a coarser description. In this work we will investigate a relatively simple, but instructive approach: the Double Constraint Method (DCM) to identify the coarse-scale conductivities to decrease the number of grid blocks. Its main advantages are robustness and easy implementation, enabling to base computations on any standard flow code with some post processing added. The inversion step of the double constraint method is based on a first forward run with all known fluxes on the boundary and in the wells, followed by a second forward run based on the heads measured on the phreatic surface (i.e. measured in shallow observation wells) and in deeper observation wells. Upscaling, in turn is inverse modeling (DCM) to determine conductivities in coarse-scale grid blocks from conductivities in fine-scale grid blocks. In such a way that the head and flux boundary conditions applied to the fine-scale model are also honored at the coarse-scale. Exemplification will be presented for the Kleine Nete catchment, Belgium. As a result we identified coarse-scale conductivities while decreasing the number of grid blocks with the advantage that a model run costs less computation time and requires less memory space. In addition, ranking of models was investigated.

Efficient radiative transfer methods for continuum and line transfer in large three-dimensional models

NASA Astrophysics Data System (ADS)

Juvela, Mika J.

The relationship between physical conditions of an interstellar cloud and the observed radiation is defined by the radiative transfer problem. Radiative transfer calculations are needed if, e.g., one wants to disentangle abundance variations from excitation effects or wants to model variations of dust properties inside an interstellar cloud. New observational facilities (e.g., ALMA and Herschel) will bring improved accuracy both in terms of intensity and spatial resolution. This will enable detailed studies of the densest sub-structures of interstellar clouds and star forming regions. Such observations must be interpreted with accurate radiative transfer methods and realistic source models. In many cases this will mean modelling in three dimensions. High optical depths and observed wide range of linear scales are, however, challenging for radiative transfer modelling. A large range of linear scales can be accessed only with hierarchical models. Figure 1 shows an example of the use of a hierarchical grid for radiative transfer calculations when the original model cloud (L=10 pc, =500 cm-3) was based a MHD simulation carried out on a regular grid (Juvela & Padoan, 2005). For computed line intensities an accuracy of 10% was still reached when the number of individual cells (and the run time) was reduced by a factor of ten. This illustrates how, as long as cloud is not extremely optically thick, most of the emission comes from a small sub-volume. It is also worth noting that while errors are ~10% for any given point they are much smaller when compared with intensity variations. In particular, calculations on hierarchical grid recovered the spatial power spectrum of line emission with very good accuracy. Monte Carlo codes are used widely in both continuum and line transfer calculations. Like any lambda iteration schemes these suffer from slow convergence when models are optically thick. In line transfer Accelerated Monte Carlo methods (AMC) present a partial solution to this problem (Juvela & Padoan, 2000; Hogerheijde & van der Tak, 2000). AMC methods can be used similarly in continuum calculations to speed up the computation of dust temperatures (Juvela, 2005). The sampling problems associated with high optical depths can be solved with weighted sampling and the handling of models with τV ~ 1000 is perfectly feasible. Transiently heated small dust grains pose another problem because the calculation of their temperature distribution is very time consuming. However, a 3D model will contain thousands of cells at very similar conditions. If dust temperature distributions are calculated only once for such a set an approximate solution can be found in a much shorter time time. (Juvela & Padoan, 2003; see Figure 2a). MHD simulations with Automatic Mesh Refinement (AMR) techniques present an exciting development for the modelling of interstellar clouds. Cloud models consist of a hierarchy of grids with different grid steps and the ratio between the cloud size and the smallest resolution elements can be 106 or even larger. We are currently working on radiative transfer codes (line and continuum) that could be used efficiently on such grids (see Figure 2b). The radiative transfer problem can be solved relatively independently on each of the sub-grids. This means that the use of convergence acceleration methods can be limited to those sub-grids where they are needed and, on the other hand, parallelization of the code is straightforward.

Influence of grid resolution, parcel size and drag models on bubbling fluidized bed simulation

DOE PAGES

Lu, Liqiang; Konan, Arthur; Benyahia, Sofiane

2017-06-02

Here in this paper, a bubbling fluidized bed is simulated with different numerical parameters, such as grid resolution and parcel size. We examined also the effect of using two homogeneous drag correlations and a heterogeneous drag based on the energy minimization method. A fast and reliable bubble detection algorithm was developed based on the connected component labeling. The radial and axial solids volume fraction profiles are compared with experiment data and previous simulation results. These results show a significant influence of drag models on bubble size and voidage distributions and a much less dependence on numerical parameters. With a heterogeneousmore » drag model that accounts for sub-scale structures, the void fraction in the bubbling fluidized bed can be well captured with coarse grid and large computation parcels. Refining the CFD grid and reducing the parcel size can improve the simulation results but with a large increase in computation cost.« less

Toward Improving Predictability of Extreme Hydrometeorological Events: the Use of Multi-scale Climate Modeling in the Northern High Plains

NASA Astrophysics Data System (ADS)

Munoz-Arriola, F.; Torres-Alavez, J.; Mohamad Abadi, A.; Walko, R. L.

2014-12-01

Our goal is to investigate possible sources of predictability of hydrometeorological extreme events in the Northern High Plains. Hydrometeorological extreme events are considered the most costly natural phenomena. Water deficits and surpluses highlight how the water-climate interdependence becomes crucial in areas where single activities drive economies such as Agriculture in the NHP. Nonetheless we recognize the Water-Climate interdependence and the regulatory role that human activities play, we still grapple to identify what sources of predictability could be added to flood and drought forecasts. To identify the benefit of multi-scale climate modeling and the role of initial conditions on flood and drought predictability on the NHP, we use the Ocean Land Atmospheric Model (OLAM). OLAM is characterized by a dynamic core with a global geodesic grid with hexagonal (and variably refined) mesh cells and a finite volume discretization of the full compressible Navier Stokes equations, a cut-grid cell method for topography (that reduces error in computational gradient computation and anomalous vertical dispersion). Our hypothesis is that wet conditions will drive OLAM's simulations of precipitation to wetter conditions affecting both flood forecast and drought forecast. To test this hypothesis we simulate precipitation during identified historical flood events followed by drought events in the NHP (i.e. 2011-2012 years). We initialized OLAM with CFS-data 1-10 days previous to a flooding event (as initial conditions) to explore (1) short-term and high-resolution and (2) long-term and coarse-resolution simulations of flood and drought events, respectively. While floods are assessed during a maximum of 15-days refined-mesh simulations, drought is evaluated during the following 15 months. Simulated precipitation will be compared with the Sub-continental Observation Dataset, a gridded 1/16th degree resolution data obtained from climatological stations in Canada, US, and Mexico. This in-progress research will ultimately contribute to integrate OLAM and VIC models and improve predictability of extreme hydrometeorological events.

Wave resource variability: Impacts on wave power supply over regional to international scales

NASA Astrophysics Data System (ADS)

Smith, Helen; Fairley, Iain; Robertson, Bryson; Abusara, Mohammad; Masters, Ian

2017-04-01

The intermittent, irregular and variable nature of the wave energy resource has implications for the supply of wave-generated electricity into the grid. Intermittency of renewable power may lead to frequency and voltage fluctuations in the transmission and distribution networks. A matching supply of electricity must be planned to meet the predicted demand, leading to a need for gas-fired and back-up generating plants to supplement intermittent supplies, and potentially limiting the integration of intermittent power into the grid. Issues relating to resource intermittency and their mitigation through the development of spatially separated sites have been widely researched in the wind industry, but have received little attention to date in the less mature wave industry. This study analyses the wave resource over three different spatial scales to investigate the potential impacts of the temporal and spatial resource variability on the grid supply. The primary focus is the Southwest UK, a region already home to multiple existing and proposed wave energy test sites. Concurrent wave buoy data from six locations, supported by SWAN wave model hindcast data, are analysed to assess the correlation of the resource across the region and the variation in wave power with direction. Power matrices for theoretical nearshore and offshore devices are used to calculate the maximum step change in generated power across the region as the number of deployment sites is increased. The step change analysis is also applied across national and international spatial scales using output from the European Centre for Medium-range Weather Forecasting (ECMWF) ERA-Interim hindcast model. It is found that the deployment of multiple wave energy sites, whether on a regional, national or international scale, results in both a reduction in step changes in power and reduced times of zero generation, leading to an overall smoothing of the wave-generated electrical power. This has implications for the planning and siting of future wave energy arrays when the industry reaches the point of large-scale deployment.

A Scale-Invariant Model of Statistical Mechanics and Modified Forms of the First and the Second Laws of Thermodynamics

NASA Technical Reports Server (NTRS)

Sohrab, Siavash H.; Pitch, Nancy (Technical Monitor)

1999-01-01

A scale-invariant statistical theory of fields is presented that leads to invariant definition of density, velocity, temperature, and pressure, The definition of Boltzmann constant is introduced as k(sub k) = m(sub k)v(sub k)c = 1.381 x 10(exp -23) J x K(exp -1), suggesting that the Kelvin absolute temperature scale is equivalent to a length scale. Two new state variables called the reversible heat Q(sub rev) = TS and the reversible work W(sub rev) = PV are introduced. The modified forms of the first and second law of thermodynamics are presented. The microscopic definition of heat (work) is presented as the kinetic energy due to the random (peculiar) translational, rotational, and pulsational motions. The Gibbs free energy of an element at scale Beta is identified as the total system energy at scale (Beta-1), thus leading to an invariant form of the first law of thermodynamics U(sub Beta) = Q(sub Beta) - W(sub Beta) +N(e3)U(sub Beta-1).

Modelling field scale spatial variation in water run-off, soil moisture, N2O emissions and herbage biomass of a grazed pasture using the SPACSYS model.

PubMed

Liu, Yi; Li, Yuefen; Harris, Paul; Cardenas, Laura M; Dunn, Robert M; Sint, Hadewij; Murray, Phil J; Lee, Michael R F; Wu, Lianhai

2018-04-01

In this study, we evaluated the ability of the SPACSYS model to simulate water run-off, soil moisture, N 2 O fluxes and grass growth using data generated from a field of the North Wyke Farm Platform. The field-scale model is adapted via a linked and grid-based approach (grid-to-grid) to account for not only temporal dynamics but also the within-field spatial variation in these key ecosystem indicators. Spatial variability in nutrient and water presence at the field-scale is a key source of uncertainty when quantifying nutrient cycling and water movement in an agricultural system. Results demonstrated that the new spatially distributed version of SPACSYS provided a worthy improvement in accuracy over the standard (single-point) version for biomass productivity. No difference in model prediction performance was observed for water run-off, reflecting the closed-system nature of this variable. Similarly, no difference in model prediction performance was found for N 2 O fluxes, but here the N 2 O predictions were noticeably poor in both cases. Further developmental work, informed by this study's findings, is proposed to improve model predictions for N 2 O. Soil moisture results with the spatially distributed version appeared promising but this promise could not be objectively verified.

Grid-cell-based crop water accounting for the famine early warning system

NASA Astrophysics Data System (ADS)

Verdin, James; Klaver, Robert

2002-06-01

Rainfall monitoring is a regular activity of food security analysts for sub-Saharan Africa due to the potentially disastrous impact of drought. Crop water accounting schemes are used to track rainfall timing and amounts relative to phenological requirements, to infer water limitation impacts on yield. Unfortunately, many rain gauge reports are available only after significant delays, and the gauge locations leave large gaps in coverage. As an alternative, a grid-cell-based formulation for the water requirement satisfaction index (WRSI) was tested for maize in Southern Africa. Grids of input variables were obtained from remote sensing estimates of rainfall, meteorological models, and digital soil maps. The spatial WRSI was computed for the 1996-97 and 1997-98 growing seasons. Maize yields were estimated by regression and compared with a limited number of reports from the field for the 1996-97 season in Zimbabwe. Agreement at a useful level (r = 0·80) was observed. This is comparable to results from traditional analysis with station data. The findings demonstrate the complementary role that remote sensing, modelling, and geospatial analysis can play in an era when field data collection in sub-Saharan Africa is suffering an unfortunate decline. Published in 2002 by John Wiley & Sons, Ltd.

Long-term hydrometeorological trends in the Midwest region based on a century long gridded hydrometeorological dataset and simulations from a macro-scale hydrology model

NASA Astrophysics Data System (ADS)

Chiu, C. M.; Hamlet, A. F.

2014-12-01

Climate change is likely to impact the Great Lakes region and Midwest region via changes in Great Lakes water levels, agricultural impacts, river flooding, urban stormwater impacts, drought, water temperature, and impacts to terrestrial and aquatic ecosystems. Self-consistent and temporally homogeneous long-term data sets of precipitation and temperature over the entire Great Lakes region and Midwest regions are needed to provide inputs to hydrologic models, assess historical trends in hydroclimatic variables, and downscale global and regional-scale climate models. To support these needs a new hybrid gridded meteorological forcing dataset at 1/16 degree resolution based on data from co-op station records, the U. S Historical Climatology Network (HCN) , the Historical Canadian Climate Database (HCCD), and Precipitation Regression on Independent Slopes Method (PRISM) has been assembled over the Great Lakes and Midwest region from 1915-2012 at daily time step. These data were then used as inputs to the macro-scale Variable Infiltration Capacity (VIC) hydrology model, implemented over the Midwest and Great Lakes region at 1/16 degree resolution, to produce simulated hydrologic variables that are amenable to long-term trend analysis. Trends in precipitation and temperature from the new meteorological driving data sets, as well as simulated hydrometeorological variables such as snowpack, soil moisture, runoff, and evaporation over the 20th century are presented and discussed.

Generating High Resolution Climate Scenarios Through Regional Climate Modelling Over Southern Africa

NASA Astrophysics Data System (ADS)

Ndhlovu, G. Z.; Woyessa, Y. E.; Vijayaraghavan, S.

2017-12-01

limate change has impacted the global environment and the Continent of Africa, especially Southern Africa, regarded as one of the most vulnerable regions in Africa, has not been spared from these impacts. Global Climate Models (GCMs) with coarse horizontal resolutions of 150-300 km do not provide sufficient details at the local basin scale due to mismatch between the size of river basins and the grid cell of the GCM. This makes it difficult to apply the outputs of GCMs directly to impact studies such as hydrological modelling. This necessitates the use of regional climate modelling at high resolutions that provide detailed information at regional and local scales to study both climate change and its impacts. To this end, an experiment was set up and conducted with PRECIS, a regional climate model, to generate climate scenarios at a high resolution of 25km for the local region in Zambezi River basin of Southern Africa. The major input data used included lateral and surface boundary conditions based on the GCMs. The data is processed, analysed and compared with CORDEX climate change project data generated for Africa. This paper, highlights the major differences of the climate scenarios generated by PRECIS Model and CORDEX Project for Africa and further gives recommendations for further research on generation of climate scenarios. The climatic variables such as precipitation and temperatures have been analysed for flood and droughts in the region. The paper also describes the setting up and running of an experiment using a high-resolution PRECIS model. In addition, a description has been made in running the model and generating the output variables on a sub basin scale. Regional climate modelling which provides information on climate change impact may lead to enhanced understanding of adaptive water resources management. Understanding the regional climate modelling results on sub basin scale is the first step in analysing complex hydrological processes and a basis for designing of adaptation and mitigation strategies in the region. Key words: Climate change, regional climate modelling, hydrological processes, extremes, scenarios [1] Corresponding author: Email:gndhlovu@cut.ac.za Tel:+27 (0) 51 507 3072

Effect of Variable Spatial Scales on USLE-GIS Computations

NASA Astrophysics Data System (ADS)

Patil, R. J.; Sharma, S. K.

2017-12-01

Use of appropriate spatial scale is very important in Universal Soil Loss Equation (USLE) based spatially distributed soil erosion modelling. This study aimed at assessment of annual rates of soil erosion at different spatial scales/grid sizes and analysing how changes in spatial scales affect USLE-GIS computations using simulation and statistical variabilities. Efforts have been made in this study to recommend an optimum spatial scale for further USLE-GIS computations for management and planning in the study area. The present research study was conducted in Shakkar River watershed, situated in Narsinghpur and Chhindwara districts of Madhya Pradesh, India. Remote Sensing and GIS techniques were integrated with Universal Soil Loss Equation (USLE) to predict spatial distribution of soil erosion in the study area at four different spatial scales viz; 30 m, 50 m, 100 m, and 200 m. Rainfall data, soil map, digital elevation model (DEM) and an executable C++ program, and satellite image of the area were used for preparation of the thematic maps for various USLE factors. Annual rates of soil erosion were estimated for 15 years (1992 to 2006) at four different grid sizes. The statistical analysis of four estimated datasets showed that sediment loss dataset at 30 m spatial scale has a minimum standard deviation (2.16), variance (4.68), percent deviation from observed values (2.68 - 18.91 %), and highest coefficient of determination (R2 = 0.874) among all the four datasets. Thus, it is recommended to adopt this spatial scale for USLE-GIS computations in the study area due to its minimum statistical variability and better agreement with the observed sediment loss data. This study also indicates large scope for use of finer spatial scales in spatially distributed soil erosion modelling.

Characterization of Slosh Damping for Ortho-Grid and Iso-Grid Internal Tank Structures

NASA Technical Reports Server (NTRS)

Westra, Douglas G.; Sansone, Marco D.; Eberhart, Chad J.; West, Jeffrey S.

2016-01-01

Grid stiffened tank structures such as Ortho-Grid and Iso-Grid are widely used in cryogenic tanks for providing stiffening to the tank while reducing mass, compared to tank walls of constant cross-section. If the structure is internal to the tank, it will positively affect the fluid dynamic behavior of the liquid propellant, in regard to fluid slosh damping. As NASA and commercial companies endeavor to explore the solar system, vehicles will by necessity become more mass efficient, and design margin will be reduced where possible. Therefore, if the damping characteristics of the Ortho-Grid and Iso-Grid structure is understood, their positive damping effect can be taken into account in the systems design process. Historically, damping by internal structures has been characterized by rules of thumb and for Ortho-Grid, empirical design tools intended for slosh baffles of much larger cross-section have been used. There is little or no information available to characterize the slosh behavior of Iso-Grid internal structure. Therefore, to take advantage of these structures for their positive damping effects, there is much need for obtaining additional data and tools to characterize them. Recently, the NASA Marshall Space Flight Center conducted both sub-scale testing and computational fluid dynamics (CFD) simulations of slosh damping for Ortho-Grid and Iso-Grid tanks for cylindrical tanks containing water. Enhanced grid meshing techniques were applied to the geometrically detailed and complex Ortho-Grid and Iso-Grid structures. The Loci-STREAM CFD program with the Volume of Fluid Method module for tracking and locating the water-air fluid interface was used to conduct the simulations. The CFD simulations were validated with the test data and new empirical models for predicting damping and frequency of Ortho-Grid and Iso-Grid structures were generated.

Photochemical grid model performance with varying horizontal grid resolution and sub-grid plume treatment for the Martins Creek near-field SO2 study

NASA Astrophysics Data System (ADS)

Baker, Kirk R.; Hawkins, Andy; Kelly, James T.

2014-12-01

Near source modeling is needed to assess primary and secondary pollutant impacts from single sources and single source complexes. Source-receptor relationships need to be resolved from tens of meters to tens of kilometers. Dispersion models are typically applied for near-source primary pollutant impacts but lack complex photochemistry. Photochemical models provide a realistic chemical environment but are typically applied using grid cell sizes that may be larger than the distance between sources and receptors. It is important to understand the impacts of grid resolution and sub-grid plume treatments on photochemical modeling of near-source primary pollution gradients. Here, the CAMx photochemical grid model is applied using multiple grid resolutions and sub-grid plume treatment for SO2 and compared with a receptor mesonet largely impacted by nearby sources approximately 3-17 km away in a complex terrain environment. Measurements are compared with model estimates of SO2 at 4- and 1-km resolution, both with and without sub-grid plume treatment and inclusion of finer two-way grid nests. Annual average estimated SO2 mixing ratios are highest nearest the sources and decrease as distance from the sources increase. In general, CAMx estimates of SO2 do not compare well with the near-source observations when paired in space and time. Given the proximity of these sources and receptors, accuracy in wind vector estimation is critical for applications that pair pollutant predictions and observations in time and space. In typical permit applications, predictions and observations are not paired in time and space and the entire distributions of each are directly compared. Using this approach, model estimates using 1-km grid resolution best match the distribution of observations and are most comparable to similar studies that used dispersion and Lagrangian modeling systems. Model-estimated SO2 increases as grid cell size decreases from 4 km to 250 m. However, it is notable that the 1-km model estimates using 1-km meteorological model input are higher than the 1-km model simulation that used interpolated 4-km meteorology. The inclusion of sub-grid plume treatment did not improve model skill in predicting SO2 in time and space and generally acts to keep emitted mass aloft.

Last millennium Northern Hemisphere summer temperatures from tree rings: Part II, spatially resolved reconstructions

NASA Astrophysics Data System (ADS)

Anchukaitis, Kevin J.; Wilson, Rob; Briffa, Keith R.; Büntgen, Ulf; Cook, Edward R.; D'Arrigo, Rosanne; Davi, Nicole; Esper, Jan; Frank, David; Gunnarson, Björn E.; Hegerl, Gabi; Helama, Samuli; Klesse, Stefan; Krusic, Paul J.; Linderholm, Hans W.; Myglan, Vladimir; Osborn, Timothy J.; Zhang, Peng; Rydval, Milos; Schneider, Lea; Schurer, Andrew; Wiles, Greg; Zorita, Eduardo

2017-05-01

Climate field reconstructions from networks of tree-ring proxy data can be used to characterize regional-scale climate changes, reveal spatial anomaly patterns associated with atmospheric circulation changes, radiative forcing, and large-scale modes of ocean-atmosphere variability, and provide spatiotemporal targets for climate model comparison and evaluation. Here we use a multiproxy network of tree-ring chronologies to reconstruct spatially resolved warm season (May-August) mean temperatures across the extratropical Northern Hemisphere (40-90°N) using Point-by-Point Regression (PPR). The resulting annual maps of temperature anomalies (750-1988 CE) reveal a consistent imprint of volcanism, with 96% of reconstructed grid points experiencing colder conditions following eruptions. Solar influences are detected at the bicentennial (de Vries) frequency, although at other time scales the influence of insolation variability is weak. Approximately 90% of reconstructed grid points show warmer temperatures during the Medieval Climate Anomaly when compared to the Little Ice Age, although the magnitude varies spatially across the hemisphere. Estimates of field reconstruction skill through time and over space can guide future temporal extension and spatial expansion of the proxy network.

Multi-scale enhancement of climate prediction over land by improving the model sensitivity to vegetation variability

NASA Astrophysics Data System (ADS)

Alessandri, A.; Catalano, F.; De Felice, M.; Hurk, B. V. D.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

2017-12-01

Here we demonstrate, for the first time, that the implementation of a realistic representation of vegetation in Earth System Models (ESMs) can significantly improve climate simulation and prediction across multiple time-scales. The effective sub-grid vegetation fractional coverage vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the surface resistance to evapotranspiration, albedo, roughness lenght, and soil field capacity. To adequately represent this effect in the EC-Earth ESM, we included an exponential dependence of the vegetation cover on the Leaf Area Index.By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal (2-4 months) and weather (4 days) time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation-cover consistently correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.Above results are discussed in a peer-review paper just being accepted for publication on Climate Dynamics (Alessandri et al., 2017; doi:10.1007/s00382-017-3766-y).

Evapotranspiration from nonuniform surfaces - A first approach for short-term numerical weather prediction

NASA Technical Reports Server (NTRS)

Wetzel, Peter J.; Chang, Jy-Tai

1988-01-01

Observations of surface heterogeneity of soil moisture from scales of meters to hundreds of kilometers are discussed, and a relationship between grid element size and soil moisture variability is presented. An evapotranspiration model is presented which accounts for the variability of soil moisture, standing surface water, and vegetation internal and stomatal resistance to moisture flow from the soil. The mean values and standard deviations of these parameters are required as input to the model. Tests of this model against field observations are reported, and extensive sensitivity tests are presented which explore the importance of including subgrid-scale variability in an evapotranspiration model.

Sensitivity of summer ensembles of fledgling superparameterized U.S. mesoscale convective systems to cloud resolving model microphysics and grid configuration

DOE PAGES

Elliott, Elizabeth J.; Yu, Sungduk; Kooperman, Gabriel J.; ...

2016-05-01

The sensitivities of simulated mesoscale convective systems (MCSs) in the central U.S. to microphysics and grid configuration are evaluated here in a global climate model (GCM) that also permits global-scale feedbacks and variability. Since conventional GCMs do not simulate MCSs, studying their sensitivities in a global framework useful for climate change simulations has not previously been possible. To date, MCS sensitivity experiments have relied on controlled cloud resolving model (CRM) studies with limited domains, which avoid internal variability and neglect feedbacks between local convection and larger-scale dynamics. However, recent work with superparameterized (SP) GCMs has shown that eastward propagating MCS-likemore » events are captured when embedded CRMs replace convective parameterizations. This study uses a SP version of the Community Atmosphere Model version 5 (SP-CAM5) to evaluate MCS sensitivities, applying an objective empirical orthogonal function algorithm to identify MCS-like events, and harmonizing composite storms to account for seasonal and spatial heterogeneity. A five-summer control simulation is used to assess the magnitude of internal and interannual variability relative to 10 sensitivity experiments with varied CRM parameters, including ice fall speed, one-moment and two-moment microphysics, and grid spacing. MCS sensitivities were found to be subtle with respect to internal variability, and indicate that ensembles of over 100 storms may be necessary to detect robust differences in SP-GCMs. Furthermore, these results emphasize that the properties of MCSs can vary widely across individual events, and improving their representation in global simulations with significant internal variability may require comparison to long (multidecadal) time series of observed events rather than single season field campaigns.« less

Climatic and landscape controls on travel time distributions across Europe

NASA Astrophysics Data System (ADS)

Kumar, Rohini; Rao, Suresh; Hesse, Falk; Borchardt, Dietrich; Fleckenstein, Jan; Jawitz, James; Musolff, Andreas; Rakovec, Oldrich; Samaniego, Luis; Yang, Soohyun; Zink, Matthias; Attinger, Sabine

2017-04-01

Travel time distributions (TTDs) are fundamental descriptors to characterize the functioning of storage, mixing and release of water and solutes in a river basin. Identifying the relative importance (and controls) of climate and landscape attributes on TDDs is fundamental to improve our understanding of the underlying mechanism controlling the spatial heterogeneity of TTDs, and their moments (e.g., mean TT). Studies aimed at elucidating such controls have focused on either theoretical developments to gain (physical) insights using mostly synthetic datasets or empirical relationships using limited datasets from experimental sites. A study painting a general picture of emerging controls at a continental scale is still lacking. In this study, we make use of spatially resolved hydrologic fluxes and states generated through an observationally driven, mesoscale Hydrologic Model (mHM; www.ufz.de/mhm) to comprehensively characterize the dominant controls of climate and landscape attributes on TDDs in the vadose zone across the entire European region. mHM uses a novel Multiscale Parameter Regionalization (MPR; Samaniego et al., 2010 and Kumar et al., 2013) scheme that encapsulates fine scale landscape attributes (e.g., topography, soil, and vegetation characteristics) to account for the sub-grid variability in model parameterization. The model was established at 25 km spatial resolution to simulate the daily gridded fluxes and states over Europe for the period 1955-2015. We utilized recent developments in TTDs theory (e.g., Botter et al., 2010, Harman et al., 2011) to characterize the stationary and non-stationary behavior of water particles transported through the vadose zone at every grid cell. Our results suggest a complex set of interactions between climate and landscape properties controlling the spatial heterogeneity of the mean travel time (TT). The spatial variability in the mean TT across the Pan-EU generally follows the climatic gradient with lower values in humid regions and higher in semi-arid or drier regions. The results signifies the role of a landscape attributes like plant available soil-water-storage capacity, when expressed in a dimensionless number that also include climate attributes such as average rain depth and aridity index, forms a potentially useful predictor for explaining the spatial heterogeneity of mean TTs. Finally, the study also highlights the time-varying behavior of TTDs and discusses the seasonal variation in mean TTs across Europe.

Forecasting Global Point Rainfall using ECMWF's Ensemble Forecasting System

NASA Astrophysics Data System (ADS)

Pillosu, Fatima; Hewson, Timothy; Zsoter, Ervin; Baugh, Calum

2017-04-01

ECMWF (the European Centre for Medium range Weather Forecasts), in collaboration with the EFAS (European Flood Awareness System) and GLOFAS (GLObal Flood Awareness System) teams, has developed a new operational system that post-processes grid box rainfall forecasts from its ensemble forecasting system to provide global probabilistic point-rainfall predictions. The project attains a higher forecasting skill by applying an understanding of how different rainfall generation mechanisms lead to different degrees of sub-grid variability in rainfall totals. In turn this approach facilitates identification of cases in which very localized extreme totals are much more likely. This approach aims also to improve the rainfall input required in different hydro-meteorological applications. Flash flood forecasting, in particular in urban areas, is a good example. In flash flood scenarios precipitation is typically characterised by high spatial variability and response times are short. In this case, to move beyond radar based now casting, the classical approach has been to use very high resolution hydro-meteorological models. Of course these models are valuable but they can represent only very limited areas, may not be spatially accurate and may give reasonable results only for limited lead times. On the other hand, our method aims to use a very cost-effective approach to downscale global rainfall forecasts to a point scale. It needs only rainfall totals from standard global reporting stations and forecasts over a relatively short period to train it, and it can give good results even up to day 5. For these reasons we believe that this approach better satisfies user needs around the world. This presentation aims to describe two phases of the project: The first phase, already completed, is the implementation of this new system to provide 6 and 12 hourly point-rainfall accumulation probabilities. To do this we use a limited number of physically relevant global model parameters (i.e. convective precipitation ratio, speed of steering winds, CAPE - Convective Available Potential Energy - and solar radiation), alongside the rainfall forecasts themselves, to define the "weather types" that in turn define the expected sub-grid variability. The calibration and computational strategy intrinsic to the system will be illustrated. The quality of the global point rainfall forecasts is also illustrated by analysing recent case studies in which extreme totals and a greatly elevated flash flood risk could be foreseen some days in advance but especially by a longer-term verification that arises out of retrospective global point rainfall forecasting for 2016. The second phase, currently in development, is focussing on the relationships with other relevant geographical aspects, for instance, orography and coastlines. Preliminary results will be presented. These are promising but need further study to fully understand their impact on the spatial distribution of point rainfall totals.

Smart Grid Adoption Likeliness Framework: Comparing Idaho and National Residential Consumers' Perceptions

NASA Astrophysics Data System (ADS)

Baiya, Evanson G.

New energy technologies that provide real-time visibility of the electricity grid's performance, along with the ability to address unusual events in the grid and allow consumers to manage their energy use, are being developed in the United States. Primary drivers for the new technologies include the growing energy demand, tightening environmental regulations, aging electricity infrastructure, and rising consumer demand to become more involved in managing individual energy usage. In the literature and in practice, it is unclear if, and to what extent, residential consumers will adopt smart grid technologies. The purpose of this quantitative study was to examine the relationships between demographic characteristics, perceptions, and the likelihood of adopting smart grid technologies among residential energy consumers. The results of a 31-item survey were analyzed for differences within the Idaho consumers and compared against national consumers. Analysis of variance was used to examine possible differences between the dependent variable of likeliness to adopt smart grid technologies and the independent variables of age, gender, residential ownership, and residential location. No differences were found among Idaho consumers in their likeliness to adopt smart grid technologies. An independent sample t-test was used to examine possible differences between the two groups of Idaho consumers and national consumers in their level of interest in receiving detailed feedback information on energy usage, the added convenience of the smart grid, renewable energy, the willingness to pay for infrastructure costs, and the likeliness to adopt smart grid technologies. The level of interest in receiving detailed feedback information on energy usage was significantly different between the two groups (t = 3.11, p = .0023), while the other variables were similar. The study contributes to technology adoption research regarding specific consumer perceptions and provides a framework that estimates the likeliness of adopting smart grid technologies by residential consumers. The study findings could assist public utility managers and technology adoption researchers as they develop strategies to enable wide-scale adoption of smart grid technologies as a solution to the energy problem. Future research should be conducted among commercial and industrial energy consumers to further validate the findings and conclusions of this research.

Multigrid calculation of three-dimensional viscous cascade flows

NASA Technical Reports Server (NTRS)

Arnone, A.; Liou, M.-S.; Povinelli, L. A.

1991-01-01

A 3-D code for viscous cascade flow prediction was developed. The space discretization uses a cell-centered scheme with eigenvalue scaling to weigh the artificial dissipation terms. Computational efficiency of a four stage Runge-Kutta scheme is enhanced by using variable coefficients, implicit residual smoothing, and a full multigrid method. The Baldwin-Lomax eddy viscosity model is used for turbulence closure. A zonal, nonperiodic grid is used to minimize mesh distortion in and downstream of the throat region. Applications are presented for an annular vane with and without end wall contouring, and for a large scale linear cascade. The calculation is validated by comparing with experiments and by studying grid dependency.

Multigrid calculation of three-dimensional viscous cascade flows

NASA Technical Reports Server (NTRS)

Arnone, A.; Liou, M.-S.; Povinelli, L. A.

1991-01-01

A three-dimensional code for viscous cascade flow prediction has been developed. The space discretization uses a cell-centered scheme with eigenvalue scaling to weigh the artificial dissipation terms. Computational efficiency of a four-stage Runge-Kutta scheme is enhanced by using variable coefficients, implicit residual smoothing, and a full-multigrid method. The Baldwin-Lomax eddy-viscosity model is used for turbulence closure. A zonal, nonperiodic grid is used to minimize mesh distortion in and downstream of the throat region. Applications are presented for an annular vane with and without end wall contouring, and for a large-scale linear cascade. The calculation is validated by comparing with experiments and by studying grid dependency.

Linear scaling computation of the Fock matrix. VI. Data parallel computation of the exchange-correlation matrix

NASA Astrophysics Data System (ADS)

Gan, Chee Kwan; Challacombe, Matt

2003-05-01

Recently, early onset linear scaling computation of the exchange-correlation matrix has been achieved using hierarchical cubature [J. Chem. Phys. 113, 10037 (2000)]. Hierarchical cubature differs from other methods in that the integration grid is adaptive and purely Cartesian, which allows for a straightforward domain decomposition in parallel computations; the volume enclosing the entire grid may be simply divided into a number of nonoverlapping boxes. In our data parallel approach, each box requires only a fraction of the total density to perform the necessary numerical integrations due to the finite extent of Gaussian-orbital basis sets. This inherent data locality may be exploited to reduce communications between processors as well as to avoid memory and copy overheads associated with data replication. Although the hierarchical cubature grid is Cartesian, naive boxing leads to irregular work loads due to strong spatial variations of the grid and the electron density. In this paper we describe equal time partitioning, which employs time measurement of the smallest sub-volumes (corresponding to the primitive cubature rule) to load balance grid-work for the next self-consistent-field iteration. After start-up from a heuristic center of mass partitioning, equal time partitioning exploits smooth variation of the density and grid between iterations to achieve load balance. With the 3-21G basis set and a medium quality grid, equal time partitioning applied to taxol (62 heavy atoms) attained a speedup of 61 out of 64 processors, while for a 110 molecule water cluster at standard density it achieved a speedup of 113 out of 128. The efficiency of equal time partitioning applied to hierarchical cubature improves as the grid work per processor increases. With a fine grid and the 6-311G(df,p) basis set, calculations on the 26 atom molecule α-pinene achieved a parallel efficiency better than 99% with 64 processors. For more coarse grained calculations, superlinear speedups are found to result from reduced computational complexity associated with data parallelism.

DEM Based Modeling: Grid or TIN? The Answer Depends

NASA Astrophysics Data System (ADS)

Ogden, F. L.; Moreno, H. A.

2015-12-01

The availability of petascale supercomputing power has enabled process-based hydrological simulations on large watersheds and two-way coupling with mesoscale atmospheric models. Of course with increasing watershed scale come corresponding increases in watershed complexity, including wide ranging water management infrastructure and objectives, and ever increasing demands for forcing data. Simulations of large watersheds using grid-based models apply a fixed resolution over the entire watershed. In large watersheds, this means an enormous number of grids, or coarsening of the grid resolution to reduce memory requirements. One alternative to grid-based methods is the triangular irregular network (TIN) approach. TINs provide the flexibility of variable resolution, which allows optimization of computational resources by providing high resolution where necessary and low resolution elsewhere. TINs also increase required effort in model setup, parameter estimation, and coupling with forcing data which are often gridded. This presentation discusses the costs and benefits of the use of TINs compared to grid-based methods, in the context of large watershed simulations within the traditional gridded WRF-HYDRO framework and the new TIN-based ADHydro high performance computing watershed simulator.

Schnek: A C++ library for the development of parallel simulation codes on regular grids

NASA Astrophysics Data System (ADS)

Schmitz, Holger

2018-05-01

A large number of algorithms across the field of computational physics are formulated on grids with a regular topology. We present Schnek, a library that enables fast development of parallel simulations on regular grids. Schnek contains a number of easy-to-use modules that greatly reduce the amount of administrative code for large-scale simulation codes. The library provides an interface for reading simulation setup files with a hierarchical structure. The structure of the setup file is translated into a hierarchy of simulation modules that the developer can specify. The reader parses and evaluates mathematical expressions and initialises variables or grid data. This enables developers to write modular and flexible simulation codes with minimal effort. Regular grids of arbitrary dimension are defined as well as mechanisms for defining physical domain sizes, grid staggering, and ghost cells on these grids. Ghost cells can be exchanged between neighbouring processes using MPI with a simple interface. The grid data can easily be written into HDF5 files using serial or parallel I/O.

Trends and natural variability of North American spring onset as evaluated by a new gridded dataset of spring indices

USGS Publications Warehouse

Ault, Toby R.; Schwartz, Mark D.; Zurita-Milla, Raul; Weltzin, Jake F.; Betancourt, Julio L.

2015-01-01

Climate change is expected to modify the timing of seasonal transitions this century, impacting wildlife migrations, ecosystem function, and agricultural activity. Tracking seasonal transitions in a consistent manner across space and through time requires indices that can be used for monitoring and managing biophysical and ecological systems during the coming decades. Here a new gridded dataset of spring indices is described and used to understand interannual, decadal, and secular trends across the coterminous United States. This dataset is derived from daily interpolated meteorological data, and the results are compared with historical station data to ensure the trends and variations are robust. Regional trends in the first leaf index range from 20.8 to 21.6 days decade21, while first bloom index trends are between20.4 and 21.2 for most regions. However, these trends are modulated by interannual to multidecadal variations, which are substantial throughout the regions considered here. These findings emphasize the important role large-scale climate modes of variability play in modulating spring onset on interannual to multidecadal time scales. Finally, there is some potential for successful subseasonal forecasts of spring onset, as indices from most regions are significantly correlated with antecedent large-scale modes of variability.

Regional Data Assimilation Using a Stretched-Grid Approach and Ensemble Calculations

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, M. S.; Takacs, L. L.; Govindaraju, R. C.; Atlas, Robert (Technical Monitor)

2002-01-01

The global variable resolution stretched grid (SG) version of the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) incorporating the GEOS SG-GCM (Fox-Rabinovitz 2000, Fox-Rabinovitz et al. 2001a,b), has been developed and tested as an efficient tool for producing regional analyses and diagnostics with enhanced mesoscale resolution. The major area of interest with enhanced regional resolution used in different SG-DAS experiments includes a rectangle over the U.S. with 50 or 60 km horizontal resolution. The analyses and diagnostics are produced for all mandatory levels from the surface to 0.2 hPa. The assimilated regional mesoscale products are consistent with global scale circulation characteristics due to using the SG-approach. Both the stretched grid and basic uniform grid DASs use the same amount of global grid-points and are compared in terms of regional product quality.

A Prototype Nonhydrostatic Regional-to-Global Nested-Grid Atmosphere Model for Medium-range Weather Forecasting

NASA Astrophysics Data System (ADS)

Harris, L.; Lin, S. J.; Zhou, L.; Chen, J. H.; Benson, R.; Rees, S.

2016-12-01

Limited-area convection-permitting models have proven useful for short-range NWP, but are unable to interact with the larger scales needed for longer lead-time skill. A new global forecast model, fvGFS, has been designed combining a modern nonhydrostatic dynamical core, the GFDL Finite-Volume Cubed-Sphere dynamical core (FV3) with operational GFS physics and initial conditions, and has been shown to provide excellent global skill while improving representation of small-scale phenomena. The nested-grid capability of FV3 allows us to build a regional-to-global variable-resolution model to efficiently refine to 3-km grid spacing over the Continental US. The use of two-way grid nesting allows us to reach these resolutions very efficiently, with the operational requirement easily attainable on current supercomputing systems.Even without a boundary-layer or advanced microphysical scheme appropriate for convection-perrmitting resolutions, the effectiveness of fvGFS can be demonstrated for a variety of weather events. We demonstrate successful proof-of-concept simulations of a variety of phenomena. We show the capability to develop intense hurricanes with realistic fine-scale eyewalls and rainbands. The new model also produces skillful predictions of severe weather outbreaks and of organized mesoscale convective systems. Fine-scale orographic and boundary-layer phenomena are also simulated with excellent fidelity by fvGFS. Further expected improvements are discussed, including the introduction of more sophisticated microphysics and of scale-aware convection schemes.

Application of a predator-prey overlap metric to determine the impact of sub-grid scale feeding dynamics on ecosystem productivity

NASA Astrophysics Data System (ADS)

Greer, A. T.; Woodson, C. B.

2016-02-01

Because of the complexity and extremely large size of marine ecosystems, research attention has a strong focus on modelling the system through space and time to elucidate processes driving ecosystem state. One of the major weaknesses of current modelling approaches is the reliance on a particular grid cell size (usually 10's of km in the horizontal & water column mean) to capture the relevant processes, even though empirical research has shown that marine systems are highly structured on fine scales, and this structure can persist over relatively long time scales (days to weeks). Fine-scale features can have a strong influence on the predator-prey interactions driving trophic transfer. Here we apply a statistic, the AB ratio, used to quantify increased predator production due to predator-prey overlap on fine scales in a manner that is computationally feasible for larger scale models. We calculated the AB ratio for predator-prey distributions throughout the scientific literature, as well as for data obtained with a towed plankton imaging system, demonstrating that averaging across a typical model grid cell neglects the fine-scale predator-prey overlap that is an essential component of ecosystem productivity. Organisms from a range of trophic levels and oceanographic regions tended to overlap with their prey both in the horizontal and vertical dimensions. When predator swimming over a diel cycle was incorporated, the amount of production indicated by the AB ratio increased substantially. For the plankton image data, the AB ratio was higher with increasing sampling resolution, especially when prey were highly aggregated. We recommend that ecosystem models incorporate more fine-scale information both to more accurately capture trophic transfer processes and to capitalize on the increasing sampling resolution and data volume from empirical studies.

A landscape model for predicting potential natural vegetation of the Olympic Peninsula USA using boundary equations and newly developed environmental variables.

Treesearch

Jan A. Henderson; Robin D. Lesher; David H. Peter; Chris D. Ringo

2011-01-01

A gradient-analysis-based model and grid-based map are presented that use the potential vegetation zone as the object of the model. Several new variables are presented that describe the environmental gradients of the landscape at different scales. Boundary algorithms are conceptualized, and then defined, that describe the environmental boundaries between vegetation...

Non-universality of the turbulent spectra at sub-ion scales in the solar wind: dispersive effects vs the Doppler shif

NASA Astrophysics Data System (ADS)

Sahraoui, F.; Huang, S.

2017-12-01

Large surveys of power spectral density (PSD) of the magnetic fluctuations in the solar wind have reported different slopes distributions at MHD, sub-ion and sub-electron scales; the smaller the scale the broader the distribution. Several explanations of the variability the slopes at sub-ion scales have been proposed. Here, we present a new one that has been overlooked in the literature, which is based on the relative importance of the dispersive effects w.r.t. the Doppler shift due to the flow speed. We build a toy model based on a dispersion relation of a linear mode that matches at high frequency (ω ≳ ω ci) the Alfvén (resp. whistler) mode at high oblique (resp. quasi-parallel) propagation angles θ kB. Starting with double power-law spectrum of turbulence {k⊥}-1.66 in the inertial range and {k⊥}-2.8 at the sub-ion scales, the transformed spectrum (in frequency f) as it would be measured in the spacecraft frame shows a broad range of slopes at the sub-ion scales that depend both on the angle θ kB and the flow speed V. Varying θ kB in the range 10o-100o and V in the range 400-800 km/s, the resulting distribution of slopes at the sub-ion scales reproduces quite well the observed one in the solar wind. Fluctuations in the solar wind speed and the anisotropy of the turbulence may explain (or at least contribute to) the variability of the spectral slopes reported in the solar wind.

Compounded effects of heat waves and droughts over the Western Electricity Grid: spatio-temporal scales of impacts and predictability toward mitigation and adaptation.

NASA Astrophysics Data System (ADS)

Voisin, N.; Kintner-Meyer, M.; Skaggs, R.; Xie, Y.; Wu, D.; Nguyen, T. B.; Fu, T.; Zhou, T.

2016-12-01

Heat waves and droughts are projected to be more frequent and intense. We have seen in the past the effects of each of those extreme climate events on electricity demand and constrained electricity generation, challenging power system operations. Our aim here is to understand the compounding effects under historical conditions. We present a benchmark of Western US grid performance under 55 years of historical climate, and including droughts, using 2010-level of water demand and water management infrastructure, and 2010-level of electricity grid infrastructure and operations. We leverage CMIP5 historical hydrology simulations and force a large scale river routing- reservoir model with 2010-level sectoral water demands. The regulated flow at each water-dependent generating plants is processed to adjust water-dependent electricity generation parameterization in a production cost model, that represents 2010-level power system operations with hourly energy demand of 2010. The resulting benchmark includes a risk distribution of several grid performance metrics (unserved energy, production cost, carbon emission) as a function of inter-annual variability in regional water availability and predictability using large scale climate oscillations. In the second part of the presentation, we describe an approach to map historical heat waves onto this benchmark grid performance using a building energy demand model. The impact of the heat waves, combined with the impact of droughts, is explored at multiple scales to understand the compounding effects. Vulnerabilities of the power generation and transmission systems are highlighted to guide future adaptation.

Towards an automatic statistical model for seasonal precipitation prediction and its application to Central and South Asian headwater catchments

NASA Astrophysics Data System (ADS)

Gerlitz, Lars; Gafurov, Abror; Apel, Heiko; Unger-Sayesteh, Katy; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

Statistical climate forecast applications typically utilize a small set of large scale SST or climate indices, such as ENSO, PDO or AMO as predictor variables. If the predictive skill of these large scale modes is insufficient, specific predictor variables such as customized SST patterns are frequently included. Hence statistically based climate forecast models are either based on a fixed number of climate indices (and thus might not consider important predictor variables) or are highly site specific and barely transferable to other regions. With the aim of developing an operational seasonal forecast model, which is easily transferable to any region in the world, we present a generic data mining approach which automatically selects potential predictors from gridded SST observations and reanalysis derived large scale atmospheric circulation patterns and generates robust statistical relationships with posterior precipitation anomalies for user selected target regions. Potential predictor variables are derived by means of a cellwise correlation analysis of precipitation anomalies with gridded global climate variables under consideration of varying lead times. Significantly correlated grid cells are subsequently aggregated to predictor regions by means of a variability based cluster analysis. Finally for every month and lead time, an individual random forest based forecast model is automatically calibrated and evaluated by means of the preliminary generated predictor variables. The model is exemplarily applied and evaluated for selected headwater catchments in Central and South Asia. Particularly the for winter and spring precipitation (which is associated with westerly disturbances in the entire target domain) the model shows solid results with correlation coefficients up to 0.7, although the variability of precipitation rates is highly underestimated. Likewise for the monsoonal precipitation amounts in the South Asian target areas a certain skill of the model could be detected. The skill of the model for the dry summer season in Central Asia and the transition seasons over South Asia is found to be low. A sensitivity analysis by means on well known climate indices reveals the major large scale controlling mechanisms for the seasonal precipitation climate of each target area. For the Central Asian target areas, both, the El Nino Southern Oscillation and the North Atlantic Oscillation are identified as important controlling factors for precipitation totals during moist spring season. Drought conditions are found to be triggered by a warm ENSO phase in combination with a positive phase of the NAO. For the monsoonal summer precipitation amounts over Southern Asia, the model suggests a distinct negative response to El Nino events.

Implication of observed cloud variability for parameterizations of microphysical and radiative transfer processes in climate models

NASA Astrophysics Data System (ADS)

Huang, D.; Liu, Y.

2014-12-01

The effects of subgrid cloud variability on grid-average microphysical rates and radiative fluxes are examined by use of long-term retrieval products at the Tropical West Pacific (TWP), Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites of the Department of Energy's Atmospheric Radiation Measurement (ARM) Program. Four commonly used distribution functions, the truncated Gaussian, Gamma, lognormal, and Weibull distributions, are constrained to have the same mean and standard deviation as observed cloud liquid water content. The PDFs are then used to upscale relevant physical processes to obtain grid-average process rates. It is found that the truncated Gaussian representation results in up to 30% mean bias in autoconversion rate whereas the mean bias for the lognormal representation is about 10%. The Gamma and Weibull distribution function performs the best for the grid-average autoconversion rate with the mean relative bias less than 5%. For radiative fluxes, the lognormal and truncated Gaussian representations perform better than the Gamma and Weibull representations. The results show that the optimal choice of subgrid cloud distribution function depends on the nonlinearity of the process of interest and thus there is no single distribution function that works best for all parameterizations. Examination of the scale (window size) dependence of the mean bias indicates that the bias in grid-average process rates monotonically increases with increasing window sizes, suggesting the increasing importance of subgrid variability with increasing grid sizes.

WegenerNet 1km-scale sub-daily rainfall data and their application: a hydrological modeling study on the sensitivity of small-catchment runoff to spatial rainfall variability

NASA Astrophysics Data System (ADS)

Oh, Sungmin; Hohmann, Clara; Foelsche, Ulrich; Fuchsberger, Jürgen; Rieger, Wolfgang; Kirchengast, Gottfried

2017-04-01

WegenerNet Feldbach region (WEGN), a pioneering experiment for weather and climate observations, has recently completed its first 10-year precipitation measurement cycle. The WEGN has measured precipitation, temperature, humidity, and other parameters since the beginning of 2007, supporting local-level monitoring and modeling studies, over an area of about 20 km x 15 km centered near the City of Feldbach (46.93 ˚ N, 15.90 ˚ E) in the Alpine forelands of southeast Austria. All the 151 stations in the network are now equipped with high-quality Meteoservis sensors as of August 2016, following an equipment with Friedrichs sensors at most stations before, and continue to provide high-resolution (2 km2/5-min) gauge based precipitation measurements for interested users in hydro-meteorological communities. Here we will present overall characteristics of the WEGN, with a focus on sub-daily precipitation measurements, from the data processing (data quality control, gridded data products generation, etc.) to data applications (e.g., ground validation of satellite estimates). The latter includes our recent study on the propagation of uncertainty from rainfall to runoff. The study assesses responses of small-catchment runoff to spatial rainfall variability in the WEGN region over the Raab valley, using a physics-based distributed hydrological model; Water Flow and Balance Simulation Model (WaSiM), developed at ETH Zurich (Schulla, ETH Zurich, 1997). Given that uncertainty due to resolution of rainfall measurements is believed to be a significant source of error in hydrologic modeling especially for convective rainfall that dominates in the region during summer, the high-resolution of WEGN data furnishes a great opportunity to analyze effects of rainfall events on the runoff at different spatial resolutions. Furthermore, the assessment can be conducted not only for the lower Raab catchment (area of about 500 km2) but also for its sub-catchments (areas of about 30-70 km2). Beside the question how many stations are necessary for reliable hydrological modeling, different interpolation methods like Inverse Distance Interpolation, Elevation Dependent Regression, and combinations will be tested. This presentation will show the first results from a scale-depending analysis of spatial and temporal structures of heavy rainfall events and responses of simulated runoff at the event scale in the WEGN region.

Algebraic dynamic multilevel method for compositional flow in heterogeneous porous media

NASA Astrophysics Data System (ADS)

Cusini, Matteo; Fryer, Barnaby; van Kruijsdijk, Cor; Hajibeygi, Hadi

2018-02-01

This paper presents the algebraic dynamic multilevel method (ADM) for compositional flow in three dimensional heterogeneous porous media in presence of capillary and gravitational effects. As a significant advancement compared to the ADM for immiscible flows (Cusini et al., 2016) [33], here, mass conservation equations are solved along with k-value based thermodynamic equilibrium equations using a fully-implicit (FIM) coupling strategy. Two different fine-scale compositional formulations are considered: (1) the natural variables and (2) the overall-compositions formulation. At each Newton's iteration the fine-scale FIM Jacobian system is mapped to a dynamically defined (in space and time) multilevel nested grid. The appropriate grid resolution is chosen based on the contrast of user-defined fluid properties and on the presence of specific features (e.g., well source terms). Consistent mapping between different resolutions is performed by the means of sequences of restriction and prolongation operators. While finite-volume restriction operators are employed to ensure mass conservation at all resolutions, various prolongation operators are considered. In particular, different interpolation strategies can be used for the different primary variables, and multiscale basis functions are chosen as pressure interpolators so that fine scale heterogeneities are accurately accounted for across different resolutions. Several numerical experiments are conducted to analyse the accuracy, efficiency and robustness of the method for both 2D and 3D domains. Results show that ADM provides accurate solutions by employing only a fraction of the number of grid-cells employed in fine-scale simulations. As such, it presents a promising approach for large-scale simulations of multiphase flow in heterogeneous reservoirs with complex non-linear fluid physics.

Evaluation of different rainfall products over India for the summer monsoon

NASA Astrophysics Data System (ADS)

Prakash, Satya; Mitra, Ashis; Turner, Andrew; Collins, Mathew; AchutoRao, Krishna

2015-04-01

Summer rainfall over India forms an integral part of the Asian monsoon, which plays a key role in the global water cycle and climate system through coupled atmospheric and oceanic processes. Accurate prediction of Indian summer monsoon rainfall and its variability at various spatiotemporal scales are crucial for agriculture, water resources and hydroelectric-power sectors. Reliable rainfall observations are very important for verification of numerical model outputs and model development. However, high spatiotemporal variability of rainfall makes it difficult to measure adequately with ground-based instruments over a large region of various surface types from deserts to oceans. A number of multi-satellite rainfall products are available to users at different spatial and temporal scales. Each rainfall product has some advantages as well as limitations, hence it is essential to find a suitable region-specific data set among these rainfall products for a particular user application, such as water resources, agricultural modelling etc. In this study, we examine seasonal-mean and daily rainfall datasets for monsoon model validation. First, six multi-satellite and gauge-only rainfall products were evaluated over India at seasonal scale for 27 (JJAS 1979-2005) summer monsoon seasons against gridded 0.5-degree IMD gauge-based rainfall. Various skill metrics are computed to assess the potential of these data sets in representation of large-scale monsoon rainfall at all-India and sub-regional scales. Among the gauge-only data sets, APHRODITE and GPCC appear to outperform the others whereas GPCP is better than CMAP in the merged multi-satellite category. However, there are significant differences among these data sets indicating uncertainty in the observed rainfall over this region, with important implications for the evaluation of model simulations. At the daily scale, TRMM TMPA-3B42 is one of the best available products and is widely used for various hydro-meteorological applications. The existing version 6 (V6) products of TRMM underwent major changes and version 7 (V7) products were released in late 2012, and we compare these to the IMD daily gridded data over the 1998-2010 period. We show a clear improvement in V7 over V6 in the South Asian monsoon region using various skill metrics. Over typical monsoon rainfall zones, biases are improved by 5-10% in V7 over higher-rainfall regions. These results will help users to select appropriate rainfall product for their application. With the recent launch of the GPM Core Observatory, the release of a more advanced high-resolution multi-satellite rainfall product is expected soon.

Renormalization group analysis of turbulence

NASA Technical Reports Server (NTRS)

Smith, Leslie M.

1989-01-01

The objective is to understand and extend a recent theory of turbulence based on dynamic renormalization group (RNG) techniques. The application of RNG methods to hydrodynamic turbulence was explored most extensively by Yakhot and Orszag (1986). An eddy viscosity was calculated which was consistent with the Kolmogorov inertial range by systematic elimination of the small scales in the flow. Further, assumed smallness of the nonlinear terms in the redefined equations for the large scales results in predictions for important flow constants such as the Kolmogorov constant. It is emphasized that no adjustable parameters are needed. The parameterization of the small scales in a self-consistent manner has important implications for sub-grid modeling.

Sensitivity of U.S. summer precipitation to model resolution and convective parameterizations across gray zone resolutions

NASA Astrophysics Data System (ADS)

Gao, Yang; Leung, L. Ruby; Zhao, Chun; Hagos, Samson

2017-03-01

Simulating summer precipitation is a significant challenge for climate models that rely on cumulus parameterizations to represent moist convection processes. Motivated by recent advances in computing that support very high-resolution modeling, this study aims to systematically evaluate the effects of model resolution and convective parameterizations across the gray zone resolutions. Simulations using the Weather Research and Forecasting model were conducted at grid spacings of 36 km, 12 km, and 4 km for two summers over the conterminous U.S. The convection-permitting simulations at 4 km grid spacing are most skillful in reproducing the observed precipitation spatial distributions and diurnal variability. Notable differences are found between simulations with the traditional Kain-Fritsch (KF) and the scale-aware Grell-Freitas (GF) convection schemes, with the latter more skillful in capturing the nocturnal timing in the Great Plains and North American monsoon regions. The GF scheme also simulates a smoother transition from convective to large-scale precipitation as resolution increases, resulting in reduced sensitivity to model resolution compared to the KF scheme. Nonhydrostatic dynamics has a positive impact on precipitation over complex terrain even at 12 km and 36 km grid spacings. With nudging of the winds toward observations, we show that the conspicuous warm biases in the Southern Great Plains are related to precipitation biases induced by large-scale circulation biases, which are insensitive to model resolution. Overall, notable improvements in simulating summer rainfall and its diurnal variability through convection-permitting modeling and scale-aware parameterizations suggest promising venues for improving climate simulations of water cycle processes.

Observing the Cosmic Microwave Background Polarization with Variable-delay Polarization Modulators for the Cosmology Large Angular Scale Surveyor

NASA Astrophysics Data System (ADS)

Harrington, Kathleen; CLASS Collaboration

2018-01-01

The search for inflationary primordial gravitational waves and the optical depth to reionization, both through their imprint on the large angular scale correlations in the polarization of the cosmic microwave background (CMB), has created the need for high sensitivity measurements of polarization across large fractions of the sky at millimeter wavelengths. These measurements are subjected to instrumental and atmospheric 1/f noise, which has motivated the development of polarization modulators to facilitate the rejection of these large systematic effects.Variable-delay polarization modulators (VPMs) are used in the Cosmology Large Angular Scale Surveyor (CLASS) telescopes as the first element in the optical chain to rapidly modulate the incoming polarization. VPMs consist of a linearly polarizing wire grid in front of a moveable flat mirror; varying the distance between the grid and the mirror produces a changing phase shift between polarization states parallel and perpendicular to the grid which modulates Stokes U (linear polarization at 45°) and Stokes V (circular polarization). The reflective and scalable nature of the VPM enables its placement as the first optical element in a reflecting telescope. This simultaneously allows a lock-in style polarization measurement and the separation of sky polarization from any instrumental polarization farther along in the optical chain.The Q-Band CLASS VPM was the first VPM to begin observing the CMB full time in 2016. I will be presenting its design and characterization as well as demonstrating how modulating polarization significantly rejects atmospheric and instrumental long time scale noise.

Part 2 of a Computational Study of a Drop-Laden Mixing Layer

NASA Technical Reports Server (NTRS)

Okongo, Nora; Bellan, Josette

2004-01-01

This second of three reports on a computational study of a mixing layer laden with evaporating liquid drops presents the evaluation of Large Eddy Simulation (LES) models. The LES models were evaluated on an existing database that had been generated using Direct Numerical Simulation (DNS). The DNS method and the database are described in the first report of this series, Part 1 of a Computational Study of a Drop-Laden Mixing Layer (NPO-30719), NASA Tech Briefs, Vol. 28, No.7 (July 2004), page 59. The LES equations, which are derived by applying a spatial filter to the DNS set, govern the evolution of the larger scales of the flow and can therefore be solved on a coarser grid. Consistent with the reduction in grid points, the DNS drops would be represented by fewer drops, called computational drops in the LES context. The LES equations contain terms that cannot be directly computed on the coarser grid and that must instead be modeled. Two types of models are necessary: (1) those for the filtered source terms representing the effects of drops on the filtered flow field and (2) those for the sub-grid scale (SGS) fluxes arising from filtering the convective terms in the DNS equations. All of the filtered-sourceterm models that were developed were found to overestimate the filtered source terms. For modeling the SGS fluxes, constant-coefficient Smagorinsky, gradient, and scale-similarity models were assessed and calibrated on the DNS database. The Smagorinsky model correlated poorly with the SGS fluxes, whereas the gradient and scale-similarity models were well correlated with the SGS quantities that they represented.

Sub-grid scale combustion models for large eddy simulation of unsteady premixed flame propagation around obstacles.

PubMed

Di Sarli, Valeria; Di Benedetto, Almerinda; Russo, Gennaro

2010-08-15

In this work, an assessment of different sub-grid scale (sgs) combustion models proposed for large eddy simulation (LES) of steady turbulent premixed combustion (Colin et al., Phys. Fluids 12 (2000) 1843-1863; Flohr and Pitsch, Proc. CTR Summer Program, 2000, pp. 61-82; Kim and Menon, Combust. Sci. Technol. 160 (2000) 119-150; Charlette et al., Combust. Flame 131 (2002) 159-180; Pitsch and Duchamp de Lageneste, Proc. Combust. Inst. 29 (2002) 2001-2008) was performed to identify the model that best predicts unsteady flame propagation in gas explosions. Numerical results were compared to the experimental data by Patel et al. (Proc. Combust. Inst. 29 (2002) 1849-1854) for premixed deflagrating flame in a vented chamber in the presence of three sequential obstacles. It is found that all sgs combustion models are able to reproduce qualitatively the experiment in terms of step of flame acceleration and deceleration around each obstacle, and shape of the propagating flame. Without adjusting any constants and parameters, the sgs model by Charlette et al. also provides satisfactory quantitative predictions for flame speed and pressure peak. Conversely, the sgs combustion models other than Charlette et al. give correct predictions only after an ad hoc tuning of constants and parameters. Copyright 2010 Elsevier B.V. All rights reserved.

Stochastic four-way coupling of gas-solid flows for Large Eddy Simulations

NASA Astrophysics Data System (ADS)

Curran, Thomas; Denner, Fabian; van Wachem, Berend

2017-11-01

The interaction of solid particles with turbulence has for long been a topic of interest for predicting the behavior of industrially relevant flows. For the turbulent fluid phase, Large Eddy Simulation (LES) methods are widely used for their low computational cost, leaving only the sub-grid scales (SGS) of turbulence to be modelled. Although LES has seen great success in predicting the behavior of turbulent single-phase flows, the development of LES for turbulent gas-solid flows is still in its infancy. This contribution aims at constructing a model to describe the four-way coupling of particles in an LES framework, by considering the role particles play in the transport of turbulent kinetic energy across the scales. Firstly, a stochastic model reconstructing the sub-grid velocities for the particle tracking is presented. Secondly, to solve particle-particle interaction, most models involve a deterministic treatment of the collisions. We finally introduce a stochastic model for estimating the collision probability. All results are validated against fully resolved DNS-DPS simulations. The final goal of this contribution is to propose a global stochastic method adapted to two-phase LES simulation where the number of particles considered can be significantly increased. Financial support from PetroBras is gratefully acknowledged.

Challenges and Opportunities in Modeling of the Global Atmosphere

NASA Astrophysics Data System (ADS)

Janjic, Zavisa; Djurdjevic, Vladimir; Vasic, Ratko

2016-04-01

Modeling paradigms on global scales may need to be reconsidered in order to better utilize the power of massively parallel processing. For high computational efficiency with distributed memory, each core should work on a small subdomain of the full integration domain, and exchange only few rows of halo data with the neighbouring cores. Note that the described scenario strongly favors horizontally local discretizations. This is relatively easy to achieve in regional models. However, the spherical geometry complicates the problem. The latitude-longitude grid with local in space and explicit in time differencing has been an early choice and remained in use ever since. The problem with this method is that the grid size in the longitudinal direction tends to zero as the poles are approached. So, in addition to having unnecessarily high resolution near the poles, polar filtering has to be applied in order to use a time step of a reasonable size. However, the polar filtering requires transpositions involving extra communications as well as more computations. The spectral transform method and the semi-implicit semi-Lagrangian schemes opened the way for application of spectral representation. With some variations, such techniques are currently dominating in global models. Unfortunately, the horizontal non-locality is inherent to the spectral representation and implicit time differencing, which inhibits scaling on a large number of cores. In this respect the lat-lon grid with polar filtering is a step in the right direction, particularly at high resolutions where the Legendre transforms become increasingly expensive. Other grids with reduced variability of grid distances, such as various versions of the cubed sphere and the hexagonal/pentagonal ("soccer ball") grids, were proposed almost fifty years ago. However, on these grids, large-scale (wavenumber 4 and 5) fictitious solutions ("grid imprinting") with significant amplitudes can develop. Due to their large scales, that are comparable to the scales of the dominant Rossby waves, such fictitious solutions are hard to identify and remove. Another new challenge on the global scale is that the limit of validity of the hydrostatic approximation is rapidly being approached. Relaxing the hydrostatic approximation requieres careful reformulation of the model dynamics and more computations and communications. The unified Non-hydrostatic Multi-scale Model (NMMB) will be briefly discussed as an example. The non-hydrostatic dynamics were designed in such a way as to avoid over-specification. The global version is run on the latitude-longitude grid, and the polar filter selectively slows down the waves that would otherwise be unstable without modifying their amplitudes. The model has been successfully tested on various scales. The skill of the medium range forecasts produced by the NMMB is comparable to that of other major medium range models, and its computational efficiency on parallel computers is good.

Grid scale drives the scale and long-term stability of place maps

PubMed Central

Mallory, Caitlin S; Hardcastle, Kiah; Bant, Jason S; Giocomo, Lisa M

2018-01-01

Medial entorhinal cortex (MEC) grid cells fire at regular spatial intervals and project to the hippocampus, where place cells are active in spatially restricted locations. One feature of the grid population is the increase in grid spatial scale along the dorsal-ventral MEC axis. However, the difficulty in perturbing grid scale without impacting the properties of other functionally-defined MEC cell types has obscured how grid scale influences hippocampal coding and spatial memory. Here, we use a targeted viral approach to knock out HCN1 channels selectively in MEC, causing grid scale to expand while leaving other MEC spatial and velocity signals intact. Grid scale expansion resulted in place scale expansion in fields located far from environmental boundaries, reduced long-term place field stability and impaired spatial learning. These observations, combined with simulations of a grid-to-place cell model and position decoding of place cells, illuminate how grid scale impacts place coding and spatial memory. PMID:29335607

Advanced Grid-Friendly Controls Demonstration Project for Utility-Scale PV Power Plants

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

Gevorgian, Vahan; O'Neill, Barbara

A typical photovoltaic (PV) power plant consists of multiple power electronic inverters and can contribute to grid stability and reliability through sophisticated 'grid-friendly' controls. The availability and dissemination of actual test data showing the viability of advanced utility-scale PV controls among all industry stakeholders can leverage PV's value from being simply an energy resource to providing additional ancillary services that range from variability smoothing and frequency regulation to power quality. Strategically partnering with a selected utility and/or PV power plant operator is a key condition for a successful demonstration project. The U.S. Department of Energy's (DOE's) Solar Energy Technologies Officemore » selected the National Renewable Energy Laboratory (NREL) to be a principal investigator in a two-year project with goals to (1) identify a potential partner(s), (2) develop a detailed scope of work and test plan for a field project to demonstrate the gird-friendly capabilities of utility-scale PV power plants, (3) facilitate conducting actual demonstration tests, and (4) disseminate test results among industry stakeholders via a joint NREL/DOE publication and participation in relevant technical conferences. The project implementation took place in FY 2014 and FY 2015. In FY14, NREL established collaborations with AES and First Solar Electric, LLC, to conduct demonstration testing on their utility-scale PV power plants in Puerto Rico and Texas, respectively, and developed test plans for each partner. Both Puerto Rico Electric Power Authority and the Electric Reliability Council of Texas expressed interest in this project because of the importance of such advanced controls for the reliable operation of their power systems under high penetration levels of variable renewable generation. During FY15, testing was completed on both plants, and a large amount of test data was produced and analyzed that demonstrates the ability of PV power plants to provide various types of new grid-friendly controls.« less

The effect of sulfate concentration on (sub)millimeter-scale sulfide δ 34S in hypersaline cyanobacterial mats over the diurnal cycle

NASA Astrophysics Data System (ADS)

Fike, David A.; Finke, Niko; Zha, Jessica; Blake, Garrett; Hoehler, Tori M.; Orphan, Victoria J.

2009-10-01

Substantial isotopic fractionations are associated with many microbial sulfur metabolisms and measurements of the bulk δ 34S isotopic composition of sulfur species (predominantly sulfates and/or sulfides) have been a key component in developing our understanding of both modern and ancient biogeochemical cycling. However, the interpretations of bulk δ 34S measurements are often non-unique, making reconstructions of paleoenvironmental conditions or microbial ecology challenging. In particular, the link between the μm-scale microbial activity that generates isotopic signatures and their eventual preservation as a bulk rock value in the geologic record has remained elusive, in large part because of the difficulty of extracting sufficient material at small scales. Here we investigate the potential for small-scale (˜100 μm-1 cm) δ 34S variability to provide additional constraints for environmental and/or ecological reconstructions. We have investigated the impact of sulfate concentrations (0.2, 1, and 80 mM SO 4) on the δ 34S composition of hydrogen sulfide produced over the diurnal (day/night) cycle in cyanobacterial mats from Guerrero Negro, Baja California Sur, Mexico. Sulfide was captured as silver sulfide on the surface of a 2.5 cm metallic silver disk partially submerged beneath the mat surface. Subsequent analyses were conducted on a Cameca 7f-GEO secondary ion mass spectrometer (SIMS) to record spatial δ 34S variability within the mats under different environmental conditions. Isotope measurements were made in a 2-dimensional grid for each incubation, documenting both lateral and vertical isotopic variation within the mats. Typical grids consisted of ˜400-800 individual measurements covering a lateral distance of ˜1 mm and a vertical depth of ˜5-15 mm. There is a large isotopic enrichment (˜10-20‰) in the uppermost mm of sulfide in those mats where [SO 4] was non-limiting (field and lab incubations at 80 mM). This is attributed to rapid recycling of sulfur (elevated sulfate reduction rates and extensive sulfide oxidation) at and above the chemocline. This isotopic gradient is observed in both day and night enrichments and suggests that, despite the close physical association between cyanobacteria and select sulfate-reducing bacteria, photosynthetic forcing has no substantive impact on δ 34S in these cyanobacterial mats. Perhaps equally surprising, large, spatially-coherent δ 34S oscillations (˜20-30‰ over 1 mm) occurred at depths up to ˜1.5 cm below the mat surface. These gradients must arise in situ from differential microbial metabolic activity and fractionation during sulfide production at depth. Sulfate concentrations were the dominant control on the spatial variability of sulfide δ 34S. Decreased sulfate concentrations diminished both vertical and lateral δ 34S variability, suggesting that small-scale variations of δ 34S can be diagnostic for reconstructing past sulfate concentrations, even when original sulfate δ 34S is unknown.

Improvement of Systematic Bias of mean state and the intraseasonal variability of CFSv2 through superparameterization and revised cloud-convection-radiation parameterization

NASA Astrophysics Data System (ADS)

Mukhopadhyay, P.; Phani Murali Krishna, R.; Goswami, Bidyut B.; Abhik, S.; Ganai, Malay; Mahakur, M.; Khairoutdinov, Marat; Dudhia, Jimmy

2016-05-01

Inspite of significant improvement in numerical model physics, resolution and numerics, the general circulation models (GCMs) find it difficult to simulate realistic seasonal and intraseasonal variabilities over global tropics and particularly over Indian summer monsoon (ISM) region. The bias is mainly attributed to the improper representation of physical processes. Among all the processes, the cloud and convective processes appear to play a major role in modulating model bias. In recent times, NCEP CFSv2 model is being adopted under Monsoon Mission for dynamical monsoon forecast over Indian region. The analyses of climate free run of CFSv2 in two resolutions namely at T126 and T382, show largely similar bias in simulating seasonal rainfall, in capturing the intraseasonal variability at different scales over the global tropics and also in capturing tropical waves. Thus, the biases of CFSv2 indicate a deficiency in model's parameterization of cloud and convective processes. Keeping this in background and also for the need to improve the model fidelity, two approaches have been adopted. Firstly, in the superparameterization, 32 cloud resolving models each with a horizontal resolution of 4 km are embedded in each GCM (CFSv2) grid and the conventional sub-grid scale convective parameterization is deactivated. This is done to demonstrate the role of resolving cloud processes which otherwise remain unresolved. The superparameterized CFSv2 (SP-CFS) is developed on a coarser version T62. The model is integrated for six and half years in climate free run mode being initialised from 16 May 2008. The analyses reveal that SP-CFS simulates a significantly improved mean state as compared to default CFS. The systematic bias of lesser rainfall over Indian land mass, colder troposphere has substantially been improved. Most importantly the convectively coupled equatorial waves and the eastward propagating MJO has been found to be simulated with more fidelity in SP-CFS. The reason of such betterment in model mean state has been found to be due to the systematic improvement in moisture field, temperature profile and moist instability. The model also has better simulated the cloud and rainfall relation. This initiative demonstrates the role of cloud processes on the mean state of coupled GCM. As the superparameterization approach is computationally expensive, so in another approach, the conventional Simplified Arakawa Schubert (SAS) scheme is replaced by a revised SAS scheme (RSAS) and also the old and simplified cloud scheme of Zhao-Karr (1997) has been replaced by WSM6 in CFSV2 (hereafter CFS-CR). The primary objective of such modifications is to improve the distribution of convective rain in the model by using RSAS and the grid-scale or the large scale nonconvective rain by WSM6. The WSM6 computes the tendency of six class (water vapour, cloud water, ice, snow, graupel, rain water) hydrometeors at each of the model grid and contributes in the low, middle and high cloud fraction. By incorporating WSM6, for the first time in a global climate model, we are able to show a reasonable simulation of cloud ice and cloud liquid water distribution vertically and spatially as compared to Cloudsat observations. The CFS-CR has also showed improvement in simulating annual rainfall cycle and intraseasonal variability over the ISM region. These improvements in CFS-CR are likely to be associated with improvement of the convective and stratiform rainfall distribution in the model. These initiatives clearly address a long standing issue of resolving the cloud processes in climate model and demonstrate that the improved cloud and convective process paramterizations can eventually reduce the systematic bias and improve the model fidelity.

Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?

DOE PAGES

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel; ...

2016-10-20

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vs in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?

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

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vs in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Vertical eddy diffusivity as a control parameter in the tropical Pacific

NASA Astrophysics Data System (ADS)

Martinez Avellaneda, N.; Cornuelle, B.

2011-12-01

Ocean models suffer from errors in the treatment of turbulent sub-grid-scale motions responsible for mixing and energy dissipation. Unrealistic small-scale physics in models can have large-scale consequences, such as biases in the upper ocean temperature, a symptom of poorly-simulated upwelling, currents and air-sea interactions. This is of special importance in the tropical Pacific Ocean (TP), which is home to energetic air-sea interactions that affect global climate. It has been shown in a number of studies that the simulated ENSO variability is highly dependent on the state of the ocean (e.g.: background mixing). Moreover, the magnitude of the vertical numerical diffusion is of primary importance in properly reproducing the Pacific equatorial thermocline. This work is part of a NASA-funded project to estimate the space- and time-varying ocean mixing coefficients in an eddy-permitting (1/3dgr) model of the TP to obtain an improved estimate of its time-varying circulation and its underlying dynamics. While an estimation procedure for the TP (26dgr S - 30dgr N) in underway using the MIT general circulation model, complementary adjoint-based sensitivity studies have been carried out for the starting ocean state from Forget (2010). This analysis aids the interpretation of the estimated mixing coefficients and possible error compensation. The focus of the sensitivity tests is the Equatorial Undercurrent and sub-thermocline jets (i.e., Tsuchiya Jets), which have been thought to have strong dependence on vertical diffusivity and should provide checks on the estimated mixing parameters. In order to build intuition for the vertical diffusivity adjoint results in the TP, adjoint and forward perturbed simulations were carried out for an idealized sharp thermocline in a rectangular domain.

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

DOE PAGES

Schwalm, C.; Huntzinger, Deborah N.; Cook, Robert B.; ...

2015-03-11

Significant changes in the water cycle are expected under current global environmental change. Robust assessment of present-day water cycle dynamics at continental to global scales is confounded by shortcomings in the observed record. Modeled assessments also yield conflicting results which are linked to differences in model structure and simulation protocol. Here we compare simulated gridded (1 spatial resolution) runoff from six terrestrial biosphere models (TBMs), seven reanalysis products, and one gridded surface station product in the contiguous United States (CONUS) from 2001 to 2005. We evaluate the consistency of these 14 estimates with stream gauge data, both as depleted flowmore » and corrected for net withdrawals (2005 only), at the CONUS and water resource region scale, as well as examining similarity across TBMs and reanalysis products at the grid cell scale. Mean runoff across all simulated products and regions varies widely (range: 71 to 356 mm yr(-1)) relative to observed continental-scale runoff (209 or 280 mm yr(-1) when corrected for net withdrawals). Across all 14 products 8 exhibit Nash-Sutcliffe efficiency values in excess of 0.8 and three are within 10% of the observed value. Region-level mismatch exhibits a weak pattern of overestimation in western and underestimation in eastern regions although two products are systematically biased across all regions and largely scales with water use. Although gridded composite TBM and reanalysis runoff show some regional similarities, individual product values are highly variable. At the coarse scales used here we find that progress in better constraining simulated runoff requires standardized forcing data and the explicit incorporation of human effects (e.g., water withdrawals by source, fire, and land use change). (C) 2015 Elsevier B.V. All rights reserved.« less

Spectral analysis of one-way and two-way downscaling applications for a tidally driven coastal ocean forecasting system

NASA Astrophysics Data System (ADS)

Solano, Miguel; Gonzalez, Juan; Canals, Miguel; Capella, Jorge; Morell, Julio; Leonardi, Stefano

2017-04-01

A prevailing problem for a tidally driven coastal ocean has been the adequate imposition of open boundary conditions. This study aims at assessing the role of open boundary conditions and tidal forcing for one and two way downscaling applications at high resolution. The operational system is based on the Caribbean Coastal Ocean Forecasting System (COFS) that uses the Regional Ocean Modeling System (ROMS), a split-explicit ocean model in which the barotropic (2D) and baroclinic (3D) modes advance separately. This COFS uses a uniform horizontal grid with 1km resolution, but a grid sensitivity analysis is performed for both one and two way downscaling methodologies with horizontal resolutions up to 700m. Initial and lateral boundary conditions are derived from the U.S Naval Oceanographic Office (NAVOCEANO) operational AmSeas model forecast, a 3-km resolution of the regional Navy Coastal Ocean Model (NCOM) that encompasses the Gulf of Mexico and Caribbean Sea. Meteorological conditions are interpolated from the Navy's COAMPS model with the exception of surface stresses, which are computed from a 2-km application of the WRF model used by NCEP's National Digital Forecast Database. Tidal forcing is performed in two different ways: 1) tidal and sub-tidal variability is imposed to the barotropic and baroclinic modes by downscaling from the AmSeas NCOM regional model and 2) tidal variability is imposed using ROMS harmonic tidal forcing from OTPS and sub-tidal conditions are imposed by filtering high frequencies out the NCOM regional solution. Special focus is given to the latter approach, where the nudging time scales and the boundary update frequency play an important role in the evolution of the ocean state for short 3-day forecasts. A spectral analysis of the sea surface height and barotropic velocity is performed via Fourier's transform, continuous 1-D wavelet transforms, and classic harmonic analysis. Tide signals are then reconstructed and removed from the OBC's in 3 ways: 1) using Rich Pawlowicz's t_tide package (classic harmonic analysis), 2) with traditional band-pass filters (e.g. Lanczos) and 3) using Proper Orthogonal Decomposition. The tide filtering approach shows great improvement in the high frequency response of tidal motions at the open boundaries. Results are validated with NOAA tide gauges, Acoustic Doppler Current Profilers, High Frequency Radars (6km and 2km resolution). A floating drifter experiment is performed in coastal zones, in which 12 drifters were deployed at different coastal zones and tracked for several days. The results show an improvement of the forecast skill with the proper implementation of the tide filtering approach by adjusting the nudging time scales and adequately removing the tidal signals. Significant improvement is found in the tracking skill of the floating drifters for the one-way grid and the two-way nested application also shows some improvement over the offline downscaling approach at higher resolutions.

Evaluating Lightning-generated NOx (LNOx) Parameterization based on Cloud Top Height at Resolutions with Partially-resolved Convection for Upper Tropospheric Chemistry Studies

NASA Astrophysics Data System (ADS)

Wong, J.; Barth, M. C.; Noone, D. C.

2012-12-01

Lightning-generated nitrogen oxides (LNOx) is an important precursor to tropospheric ozone production. With a meteorological time-scale variability similar to that of the ozone chemical lifetime, it can nonlinearly perturb tropospheric ozone concentration. Coupled with upper-air circulation patterns, LNOx can accumulate in significant amount in the upper troposphere with other precursors, thus enhancing ozone production (see attached figure). While LNOx emission has been included and tuned extensively in global climate models, its inclusions in regional chemistry models are seldom tested. Here we present a study that evaluates the frequently used Price and Rind parameterization based on cloud-top height at resolutions that partially resolve deep convection using the Weather Research and Forecasting model with Chemistry (WRF-Chem) over the contiguous United States. With minor modifications, the parameterization is shown to generate integrated flash counts close to those observed. However, the modeled frequency distribution of cloud-to-ground flashes do not represent well for storms with high flash rates, bringing into question the applicability of the intra-cloud/ground partitioning (IC:CG) formulation of Price and Rind in some studies. Resolution dependency also requires attention when sub-grid cloud-tops are used instead of the originally intended grid-averaged cloud-top. LNOx passive tracers being gathered by monsoonal upper tropospheric anticyclone.

Navier-Stokes simulation of rotor-body flowfield in hover using overset grids

NASA Technical Reports Server (NTRS)

Srinivasan, G. R.; Ahmad, J. U.

1993-01-01

A free-wake Navier-Stokes numerical scheme and multiple Chimera overset grids have been utilized for calculating the quasi-steady hovering flowfield of a Boeing-360 rotor mounted on an axisymmetric whirl-tower. The entire geometry of this rotor-body configuration is gridded-up with eleven different overset grids. The composite grid has 1.3 million grid points for the entire flow domain. The numerical results, obtained using coarse grids and a rigid rotor assumption, show a thrust value that is within 5% of the experimental value at a flow condition of M(sub tip) = 0.63, Theta(sub c) = 8 deg, and Re = 2.5 x 10(exp 6). The numerical method thus demonstrates the feasibility of using a multi-block scheme for calculating the flowfields of complex configurations consisting of rotating and non-rotating components.

The Impact of ARM on Climate Modeling. Chapter 26

NASA Technical Reports Server (NTRS)

Randall, David A.; Del Genio, Anthony D.; Donner, Leo J.; Collins, William D.; Klein, Stephen A.

2016-01-01

Climate models are among humanity's most ambitious and elaborate creations. They are designed to simulate the interactions of the atmosphere, ocean, land surface, and cryosphere on time scales far beyond the limits of deterministic predictability, and including the effects of time-dependent external forcings. The processes involved include radiative transfer, fluid dynamics, microphysics, and some aspects of geochemistry, biology, and ecology. The models explicitly simulate processes on spatial scales ranging from the circumference of the Earth down to one hundred kilometers or smaller, and implicitly include the effects of processes on even smaller scales down to a micron or so. The atmospheric component of a climate model can be called an atmospheric global circulation model (AGCM). In an AGCM, calculations are done on a three-dimensional grid, which in some of today's climate models consists of several million grid cells. For each grid cell, about a dozen variables are time-stepped as the model integrates forward from its initial conditions. These so-called prognostic variables have special importance because they are the only things that a model remembers from one time step to the next; everything else is recreated on each time step by starting from the prognostic variables and the boundary conditions. The prognostic variables typically include information about the mass of dry air, the temperature, the wind components, water vapor, various condensed-water species, and at least a few chemical species such as ozone. A good way to understand how climate models work is to consider the lengthy and complex process used to develop one. Lets imagine that a new AGCM is to be created, starting from a blank piece of paper. The model may be intended for a particular class of applications, e.g., high-resolution simulations on time scales of a few decades. Before a single line of code is written, the conceptual foundation of the model must be designed through a creative envisioning that starts from the intended application and is based on current understanding of how the atmosphere works and the inventory of mathematical methods available.

Coupled numerical approach combining finite volume and lattice Boltzmann methods for multi-scale multi-physicochemical processes

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

Chen, Li; He, Ya-Ling; Kang, Qinjun

2013-12-15

A coupled (hybrid) simulation strategy spatially combining the finite volume method (FVM) and the lattice Boltzmann method (LBM), called CFVLBM, is developed to simulate coupled multi-scale multi-physicochemical processes. In the CFVLBM, computational domain of multi-scale problems is divided into two sub-domains, i.e., an open, free fluid region and a region filled with porous materials. The FVM and LBM are used for these two regions, respectively, with information exchanged at the interface between the two sub-domains. A general reconstruction operator (RO) is proposed to derive the distribution functions in the LBM from the corresponding macro scalar, the governing equation of whichmore » obeys the convection–diffusion equation. The CFVLBM and the RO are validated in several typical physicochemical problems and then are applied to simulate complex multi-scale coupled fluid flow, heat transfer, mass transport, and chemical reaction in a wall-coated micro reactor. The maximum ratio of the grid size between the FVM and LBM regions is explored and discussed. -- Highlights: •A coupled simulation strategy for simulating multi-scale phenomena is developed. •Finite volume method and lattice Boltzmann method are coupled. •A reconstruction operator is derived to transfer information at the sub-domains interface. •Coupled multi-scale multiple physicochemical processes in micro reactor are simulated. •Techniques to save computational resources and improve the efficiency are discussed.« less

HiPEP Ion Optics System Evaluation Using Gridlets

NASA Technical Reports Server (NTRS)

Willliams, John D.; Farnell, Cody C.; Laufer, D. Mark; Martinez, Rafael A.

2004-01-01

Experimental measurements are presented for sub-scale ion optics systems comprised of 7 and 19 aperture pairs with geometrical features that are similar to the HiPEP ion optics system. Effects of hole diameter and grid-to-grid spacing are presented as functions of applied voltage and beamlet current. Recommendations are made for the beamlet current range where the ion optics system can be safely operated without experiencing direct impingement of high energy ions on the accelerator grid surface. Measurements are also presented of the accelerator grid voltage where beam plasma electrons backstream through the ion optics system. Results of numerical simulations obtained with the ffx code are compared to both the impingement limit and backstreaming measurements. An emphasis is placed on identifying differences between measurements and simulation predictions to highlight areas where more research is needed. Relatively large effects are observed in simulations when the discharge chamber plasma properties and ion optics geometry are varied. Parameters investigated using simulations include the applied voltages, grid spacing, hole-to-hole spacing, doubles-to-singles ratio, plasma potential, and electron temperature; and estimates are provided for the sensitivity of impingement limits on these parameters.

A Priori Analyses of Three Subgrid-Scale Models for One-Parameter Families of Filters

NASA Technical Reports Server (NTRS)

Pruett, C. David; Adams, Nikolaus A.

1998-01-01

The decay of isotropic turbulence a compressible flow is examined by direct numerical simulation (DNS). A priori analyses of the DNS data are then performed to evaluate three subgrid-scale (SGS) models for large-eddy simulation (LES): a generalized Smagorinsky model (M1), a stress-similarity model (M2), and a gradient model (M3). The models exploit one-parameter second- or fourth-order filters of Pade type, which permit the cutoff wavenumber k(sub c) to be tuned independently of the grid increment (delta)x. The modeled (M) and exact (E) SGS-stresses are compared component-wise by correlation coefficients of the form C(E,M) computed over the entire three-dimensional fields. In general, M1 correlates poorly against exact stresses (C < 0.2), M3 correlates moderately well (C approx. 0.6), and M2 correlates remarkably well (0.8 < C < 1.0). Specifically, correlations C(E, M2) are high provided the grid and test filters are of the same order. Moreover, the highest correlations (C approx.= 1.0) result whenever the grid and test filters are identical (in both order and cutoff). Finally, present results reveal the exact SGS stresses obtained by grid filters of differing orders to be only moderately well correlated. Thus, in LES the model should not be specified independently of the filter.

The topographic distribution of annual incoming solar radiation in the Rio Grande River basin

NASA Technical Reports Server (NTRS)

Dubayah, R.; Van Katwijk, V.

1992-01-01

We model the annual incoming solar radiation topoclimatology for the Rio Grande River basin in Colorado, U.S.A. Hourly pyranometer measurements are combined with satellite reflectance data and 30-m digital elevation models within a topographic solar radiation algorithm. Our results show that there is large spatial variability within the basin, even at an annual integration length, but the annual, basin-wide mean is close to that measured by the pyranometers. The variance within 16 sq km and 100 sq km regions is a linear function of the average slope in the region, suggesting a possible parameterization for sub-grid-cell variability.

The Super Tuesday Outbreak: Forecast Sensitivities to Single-Moment Microphysics Schemes

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Case, Jonathan L.; Dembek, Scott R.; Jedlovec, Gary J.; Lapenta, William M.

2008-01-01

Forecast precipitation and radar characteristics are used by operational centers to guide the issuance of advisory products. As operational numerical weather prediction is performed at increasingly finer spatial resolution, convective precipitation traditionally represented by sub-grid scale parameterization schemes is now being determined explicitly through single- or multi-moment bulk water microphysics routines. Gains in forecasting skill are expected through improved simulation of clouds and their microphysical processes. High resolution model grids and advanced parameterizations are now available through steady increases in computer resources. As with any parameterization, their reliability must be measured through performance metrics, with errors noted and targeted for improvement. Furthermore, the use of these schemes within an operational framework requires an understanding of limitations and an estimate of biases so that forecasters and model development teams can be aware of potential errors. The National Severe Storms Laboratory (NSSL) Spring Experiments have produced daily, high resolution forecasts used to evaluate forecast skill among an ensemble with varied physical parameterizations and data assimilation techniques. In this research, high resolution forecasts of the 5-6 February 2008 Super Tuesday Outbreak are replicated using the NSSL configuration in order to evaluate two components of simulated convection on a large domain: sensitivities of quantitative precipitation forecasts to assumptions within a single-moment bulk water microphysics scheme, and to determine if these schemes accurately depict the reflectivity characteristics of well-simulated, organized, cold frontal convection. As radar returns are sensitive to the amount of hydrometeor mass and the distribution of mass among variably sized targets, radar comparisons may guide potential improvements to a single-moment scheme. In addition, object-based verification metrics are evaluated for their utility in gauging model performance and QPF variability.

Direct comparisons of ice cloud macro- and microphysical properties simulated by the Community Atmosphere Model version 5 with HIPPO aircraft observations

NASA Astrophysics Data System (ADS)

Wu, Chenglai; Liu, Xiaohong; Diao, Minghui; Zhang, Kai; Gettelman, Andrew; Lu, Zheng; Penner, Joyce E.; Lin, Zhaohui

2017-04-01

In this study we evaluate cloud properties simulated by the Community Atmosphere Model version 5 (CAM5) using in situ measurements from the HIAPER Pole-to-Pole Observations (HIPPO) campaign for the period of 2009 to 2011. The modeled wind and temperature are nudged towards reanalysis. Model results collocated with HIPPO flight tracks are directly compared with the observations, and model sensitivities to the representations of ice nucleation and growth are also examined. Generally, CAM5 is able to capture specific cloud systems in terms of vertical configuration and horizontal extension. In total, the model reproduces 79.8 % of observed cloud occurrences inside model grid boxes and even higher (94.3 %) for ice clouds (T ≤ -40 °C). The missing cloud occurrences in the model are primarily ascribed to the fact that the model cannot account for the high spatial variability of observed relative humidity (RH). Furthermore, model RH biases are mostly attributed to the discrepancies in water vapor, rather than temperature. At the micro-scale of ice clouds, the model captures the observed increase of ice crystal mean sizes with temperature, albeit with smaller sizes than the observations. The model underestimates the observed ice number concentration (Ni) and ice water content (IWC) for ice crystals larger than 75 µm in diameter. Modeled IWC and Ni are more sensitive to the threshold diameter for autoconversion of cloud ice to snow (Dcs), while simulated ice crystal mean size is more sensitive to ice nucleation parameterizations than to Dcs. Our results highlight the need for further improvements to the sub-grid RH variability and ice nucleation and growth in the model.

Assessment of Seasonal Water Balance Components over India Using Macroscale Hydrological Model

NASA Astrophysics Data System (ADS)

Joshi, S.; Raju, P. V.; Hakeem, K. A.; Rao, V. V.; Yadav, A.; Issac, A. M.; Diwakar, P. G.; Dadhwal, V. K.

2016-12-01

Hydrological models provide water balance components which are useful for water resources assessment and for capturing the seasonal changes and impact of anthropogenic interventions and climate change. The study under description is a national level modeling framework for country India using wide range of geo-spatial and hydro-meteorological data sets for estimating daily Water Balance Components (WBCs) at 0.15º grid resolution using Variable Infiltration Capacity model. The model parameters were optimized through calibration of model computed stream flow with field observed yielding Nash-Sutcliffe efficiency between 0.5 to 0.7. The state variables, evapotranspiration (ET) and soil moisture were also validated, obtaining R2 values of 0.57 and 0.69, respectively. Using long-term meteorological data sets, model computation were carried to capture hydrological extremities. During 2013, 2014 and 2015 monsoon seasons, WBCs were estimated and were published in web portal with 2-day time lag. In occurrence of disaster events, weather forecast was ingested, high surface runoff zones were identified for forewarning and disaster preparedness. Cumulative monsoon season rainfall of 2013, 2014 and 2015 were 105, 89 and 91% of long period average (LPA) respectively (Source: India Meteorological Department). Analysis of WBCs indicated that corresponding seasonal surface runoff was 116, 81 and 86% LPA and evapotranspiration was 109, 104 and 90% LPA. Using the grid-wise data, the spatial variation in WBCs among river basins/administrative regions was derived to capture the changes in surface runoff, ET between the years and in comparison with LPA. The model framework is operational and is providing periodic account of national level water balance fluxes which are useful for quantifying spatial and temporal variation in basin/sub-basin scale water resources, periodical water budgeting to form vital inputs for studies on water resources and climate change.

Discrete Adjoint-Based Design Optimization of Unsteady Turbulent Flows on Dynamic Unstructured Grids

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.; Diskin, Boris; Yamaleev, Nail K.

2009-01-01

An adjoint-based methodology for design optimization of unsteady turbulent flows on dynamic unstructured grids is described. The implementation relies on an existing unsteady three-dimensional unstructured grid solver capable of dynamic mesh simulations and discrete adjoint capabilities previously developed for steady flows. The discrete equations for the primal and adjoint systems are presented for the backward-difference family of time-integration schemes on both static and dynamic grids. The consistency of sensitivity derivatives is established via comparisons with complex-variable computations. The current work is believed to be the first verified implementation of an adjoint-based optimization methodology for the true time-dependent formulation of the Navier-Stokes equations in a practical computational code. Large-scale shape optimizations are demonstrated for turbulent flows over a tiltrotor geometry and a simulated aeroelastic motion of a fighter jet.

Power grid operation risk management: V2G deployment for sustainable development

NASA Astrophysics Data System (ADS)

Haddadian, Ghazale J.

The production, transmission, and delivery of cost--efficient energy to supply ever-increasing peak loads along with a quest for developing a low-carbon economy require significant evolutions in the power grid operations. Lower prices of vast natural gas resources in the United States, Fukushima nuclear disaster, higher and more intense energy consumptions in China and India, issues related to energy security, and recent Middle East conflicts, have urged decisions makers throughout the world to look into other means of generating electricity locally. As the world look to combat climate changes, a shift from carbon-based fuels to non-carbon based fuels is inevitable. However, the variability of distributed generation assets in the electricity grid has introduced major reliability challenges for power grid operators. While spearheading sustainable and reliable power grid operations, this dissertation develops a multi-stakeholder approach to power grid operation design; aiming to address economic, security, and environmental challenges of the constrained electricity generation. It investigates the role of Electric Vehicle (EV) fleets integration, as distributed and mobile storage assets to support high penetrations of renewable energy sources, in the power grid. The vehicle-to-grid (V2G) concept is considered to demonstrate the bidirectional role of EV fleets both as a provider and consumer of energy in securing a sustainable power grid operation. The proposed optimization modeling is the application of Mixed-Integer Linear Programing (MILP) to large-scale systems to solve the hourly security-constrained unit commitment (SCUC) -- an optimal scheduling concept in the economic operation of electric power systems. The Monte Carlo scenario-based approach is utilized to evaluate different scenarios concerning the uncertainties in the operation of power grid system. Further, in order to expedite the real-time solution of the proposed approach for large-scale power systems, it considers a two-stage model using the Benders Decomposition (BD). The numerical simulation demonstrate that the utilization of smart EV fleets in power grid systems would ensure a sustainable grid operation with lower carbon footprints, smoother integration of renewable sources, higher security, and lower power grid operation costs. The results, additionally, illustrate the effectiveness of the proposed MILP approach and its potentials as an optimization tool for sustainable operation of large scale electric power systems.

Spatial Scale Variability of NH3 and Impacts to interpolated Concentration Grids

EPA Science Inventory

Over the past decade, reduced nitrogen (NH3, NH4) has become an important component of atmospheric nitrogen deposition due to increases in agricultural activities and reductions in oxidized sulfur and nitrogen emissions from the power sector and mobile sources. Reduced nitrogen i...

An Examination of the Sea Ice Rheology for Seasonal Ice Zones Based on Ice Drift and Thickness Observations

NASA Astrophysics Data System (ADS)

Toyota, Takenobu; Kimura, Noriaki

2018-02-01

The validity of the sea ice rheological model formulated by Hibler (1979), which is widely used in present numerical sea ice models, is examined for the Sea of Okhotsk as an example of the seasonal ice zone (SIZ), based on satellite-derived sea ice velocity, concentration and thickness. Our focus was the formulation of the yield curve, the shape of which can be estimated from ice drift pattern based on the energy equation of deformation, while the strength of the ice cover that determines its magnitude was evaluated using ice concentration and thickness data. Ice drift was obtained with a grid spacing of 37.5 km from the AMSR-E 89 GHz brightness temperature using a maximum cross-correlation method. The ice thickness was obtained with a spatial resolution of 100 m from a regression of the PALSAR backscatter coefficients with ice thickness. To assess scale dependence, the ice drift data derived from a coastal radar covering a 70 km range in the southernmost Sea of Okhotsk were similarly analyzed. The results obtained were mostly consistent with Hibler's formulation that was based on the Arctic Ocean on both scales with no dependence on a time scale, and justify the treatment of sea ice as a plastic material, with an elliptical shaped yield curve to some extent. However, it also highlights the difficulty in parameterizing sub-grid scale ridging in the model because grid scale ice velocities reduce the deformation magnitude by half due to the large variation of the deformation field in the SIZ.

Evaluating a Local Ensemble Transform Kalman Filter snow cover data assimilation method to estimate SWE within a high-resolution hydrologic modeling framework across Western US mountainous regions

NASA Astrophysics Data System (ADS)

Oaida, C. M.; Andreadis, K.; Reager, J. T., II; Famiglietti, J. S.; Levoe, S.

2017-12-01

Accurately estimating how much snow water equivalent (SWE) is stored in mountainous regions characterized by complex terrain and snowmelt-driven hydrologic cycles is not only greatly desirable, but also a big challenge. Mountain snowpack exhibits high spatial variability across a broad range of spatial and temporal scales due to a multitude of physical and climatic factors, making it difficult to observe or estimate in its entirety. Combing remotely sensed data and high resolution hydrologic modeling through data assimilation (DA) has the potential to provide a spatially and temporally continuous SWE dataset at horizontal scales that capture sub-grid snow spatial variability and are also relevant to stakeholders such as water resource managers. Here, we present the evaluation of a new snow DA approach that uses a Local Ensemble Transform Kalman Filter (LETKF) in tandem with the Variable Infiltration Capacity macro-scale hydrologic model across the Western United States, at a daily temporal resolution, and a horizontal resolution of 1.75 km x 1.75 km. The LETKF is chosen for its relative simplicity, ease of implementation, and computational efficiency and scalability. The modeling/DA system assimilates daily MODIS Snow Covered Area and Grain Size (MODSCAG) fractional snow cover over, and has been developed to efficiently calculate SWE estimates over extended periods of time and covering large regional-scale areas at relatively high spatial resolution, ultimately producing a snow reanalysis-type dataset. Here we focus on the assessment of SWE produced by the DA scheme over several basins in California's Sierra Nevada Mountain range where Airborne Snow Observatory data is available, during the last five water years (2013-2017), which include both one of the driest and one of the wettest years. Comparison against such a spatially distributed SWE observational product provides a greater understanding of the model's ability to estimate SWE and SWE spatial variability, and highlights under which conditions snow cover DA can add value in estimating SWE.

Skill assessment of the coupled physical-biogeochemical operational Mediterranean Forecasting System

NASA Astrophysics Data System (ADS)

Cossarini, Gianpiero; Clementi, Emanuela; Salon, Stefano; Grandi, Alessandro; Bolzon, Giorgio; Solidoro, Cosimo

2016-04-01

The Mediterranean Monitoring and Forecasting Centre (Med-MFC) is one of the regional production centres of the European Marine Environment Monitoring Service (CMEMS-Copernicus). Med-MFC operatively manages a suite of numerical model systems (3DVAR-NEMO-WW3 and 3DVAR-OGSTM-BFM) that provides gridded datasets of physical and biogeochemical variables for the Mediterranean marine environment with a horizontal resolution of about 6.5 km. At the present stage, the operational Med-MFC produces ten-day forecast: daily for physical parameters and bi-weekly for biogeochemical variables. The validation of the coupled model system and the estimate of the accuracy of model products are key issues to ensure reliable information to the users and the downstream services. Product quality activities at Med-MFC consist of two levels of validation and skill analysis procedures. Pre-operational qualification activities focus on testing the improvement of the quality of a new release of the model system and relays on past simulation and historical data. Then, near real time (NRT) validation activities aim at the routinely and on-line skill assessment of the model forecast and relays on the NRT available observations. Med-MFC validation framework uses both independent (i.e. Bio-Argo float data, in-situ mooring and vessel data of oxygen, nutrients and chlorophyll, moored buoys, tide-gauges and ADCP of temperature, salinity, sea level and velocity) and semi-independent data (i.e. data already used for assimilation, such as satellite chlorophyll, Satellite SLA and SST and in situ vertical profiles of temperature and salinity from XBT, Argo and Gliders) We give evidence that different variables (e.g. CMEMS-products) can be validated at different levels (i.e. at the forecast level or at the level of model consistency) and at different spatial and temporal scales. The fundamental physical parameters temperature, salinity and sea level are routinely validated on daily, weekly and quarterly base at regional and sub-regional scale and along specific vertical layers (temperature and salinity); while velocity fields are daily validated against in situ coastal moorings. Since the velocity skill cannot be accurately assessed through coastal measurements due to the actual model horizontal resolution (~6.5 km), new validation metrics and procedures are under investigation. Chlorophyll is the only biogeochemical variable that can be validated routinely at the temporal and spatial scale of the weekly forecast, while nutrients and oxygen predictions can be validated locally or at sub-basin and seasonal scales. For the other biogeochemical variables (i.e. primary production, carbonate system variables) only the accuracy of the average dynamics and model consistency can be evaluated. Then, we discuss the limiting factors of the present validation framework, and the quality and extension of the observing system that would be needed for improving the reliability of the physical and biogeochemical Mediterranean forecast services.

Sources and pathways of the upscale effects on the Southern Hemisphere jet in MPAS-CAM4 variable-resolution simulations

DOE PAGES

Sakaguchi, Koichi; Lu, Jian; Leung, L. Ruby; ...

2016-10-22

Impacts of regional grid refinement on large-scale circulations (“upscale effects”) were detected in a previous study that used the Model for Prediction Across Scales-Atmosphere coupled to the physics parameterizations of the Community Atmosphere Model version 4. The strongest upscale effect was identified in the Southern Hemisphere jet during austral winter. This study examines the detailed underlying processes by comparing two simulations at quasi-uniform resolutions of 30 and 120 km to three variable-resolution simulations in which the horizontal grids are regionally refined to 30 km in North America, South America, or Asia from 120 km elsewhere. In all the variable-resolution simulations,more » precipitation increases in convective areas inside the high-resolution domains, as in the reference quasi-uniform high-resolution simulation. With grid refinement encompassing the tropical Americas, the increased condensational heating expands the local divergent circulations (Hadley cell) meridionally such that their descending branch is shifted poleward, which also pushes the baroclinically unstable regions, momentum flux convergence, and the eddy-driven jet poleward. This teleconnection pathway is not found in the reference high-resolution simulation due to a strong resolution sensitivity of cloud radiative forcing that dominates the aforementioned teleconnection signals. The regional refinement over Asia enhances Rossby wave sources and strengthens the upper level southerly flow, both facilitating the cross-equatorial propagation of stationary waves. Evidence indicates that this teleconnection pathway is also found in the reference high-resolution simulation. Lastly, the result underlines the intricate diagnoses needed to understand the upscale effects in global variable-resolution simulations, with implications for science investigations using the computationally efficient modeling framework.« less

Sources and pathways of the upscale effects on the Southern Hemisphere jet in MPAS-CAM4 variable-resolution simulations

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

Sakaguchi, Koichi; Lu, Jian; Leung, L. Ruby

Impacts of regional grid refinement on large-scale circulations (“upscale effects”) were detected in a previous study that used the Model for Prediction Across Scales-Atmosphere coupled to the physics parameterizations of the Community Atmosphere Model version 4. The strongest upscale effect was identified in the Southern Hemisphere jet during austral winter. This study examines the detailed underlying processes by comparing two simulations at quasi-uniform resolutions of 30 and 120 km to three variable-resolution simulations in which the horizontal grids are regionally refined to 30 km in North America, South America, or Asia from 120 km elsewhere. In all the variable-resolution simulations,more » precipitation increases in convective areas inside the high-resolution domains, as in the reference quasi-uniform high-resolution simulation. With grid refinement encompassing the tropical Americas, the increased condensational heating expands the local divergent circulations (Hadley cell) meridionally such that their descending branch is shifted poleward, which also pushes the baroclinically unstable regions, momentum flux convergence, and the eddy-driven jet poleward. This teleconnection pathway is not found in the reference high-resolution simulation due to a strong resolution sensitivity of cloud radiative forcing that dominates the aforementioned teleconnection signals. The regional refinement over Asia enhances Rossby wave sources and strengthens the upper level southerly flow, both facilitating the cross-equatorial propagation of stationary waves. Evidence indicates that this teleconnection pathway is also found in the reference high-resolution simulation. Lastly, the result underlines the intricate diagnoses needed to understand the upscale effects in global variable-resolution simulations, with implications for science investigations using the computationally efficient modeling framework.« less

Quantifying variabilty of the solar resource using the Kriging method

NASA Astrophysics Data System (ADS)

Monger, Samuel Haze

Energy consumption will steadily rise in coming years and if fossil fuels, particularly coal, continue to be the primary resource for electricity generation our planet is going to face many hardships. Solar energy is the most abundant resource available to humankind, and although solar generated power is still expensive, the technology is in a state of rapid development as governments strive to meet renewable energy goals as part of the effort to slow climate change and become less dependent on finite resources. However there are many valid concerns associated with integrating high levels of solar energy with the transmission grid due to the rapid changes in power output and voltage from photovoltaic generated electricity due to drops in the solar resource. Therefore, a study was conducted to address issues in this field of research by attempting to quantify the variability of solar irradiance at a specific area using a uniform grid of 45 irradiance sensors. Another goal of this study was to determine if fewer measurement stations could be used in the quantification of variability. This thesis addresses these issues by using the Sandia Variability Index and the dead band ramp algorithm in a statistical analysis on irradiance fluctuations in the regulation and sub-regulation time frames. A kriging method will be introduced which accurately predicts variability using only four stations.

Simulation of Extreme Arctic Cyclones in IPCC AR5 Experiments

DTIC Science & Technology

2014-05-15

atmospheric fields, including sea level pressure ( SLP ), on daily and sub-daily time scales at 2° horizontal resolution. A higher-resolution and more...its 21st-century simulation. Extreme cyclones were defined as occurrences of daily mean SLP at least 40 hPa below the climatological annual-average... SLP at a grid point. As such, no cyclone-tracking algorithm was employed, because the purpose here is to identify instances of extremely strong

CIELO-A GIS integrated model for climatic and water balance simulation in islands environments

NASA Astrophysics Data System (ADS)

Azevedo, E. B.; Pereira, L. S.

2003-04-01

The model CIELO (acronym for "Clima Insular à Escala Local") is a physically based model that simulates the climatic variables in an island using data from a single synoptic reference meteorological station. The reference station "knows" its position in the orographic and dynamic regime context. The domain of computation is a GIS raster grid parameterised with a digital elevation model (DEM). The grid is oriented following the direction of the air masses circulation through a specific algorithm named rotational terrain model (RTM). The model consists of two main sub-models. One, relative to the advective component simulation, assumes the Foehn effect to reproduce the dynamic and thermodynamic processes occurring when an air mass moves through the island orographic obstacle. This makes possible to simulate the air temperature, air humidity, cloudiness and precipitation as influenced by the orography along the air displacement. The second concerns the radiative component as affected by the clouds of orographic origin and by the shadow produced by the relief. The initial state parameters are computed starting from the reference meteorological station across the DEM transept until the sea level at the windward side. Then, starting from the sea level, the model computes the local scale meteorological parameters according to the direction of the air displacement, which is adjusted with the RTM. The air pressure, temperature and humidity are directly calculated for each cell in the computational grid, while several algorithms are used to compute the cloudiness, net radiation, evapotranspiration, and precipitation. The model presented in this paper has been calibrated and validated using data from some meteorological stations and a larger number of rainfall stations located at various elevations in the Azores Islands.

Simplified galaxy formation with mesh-less hydrodynamics

NASA Astrophysics Data System (ADS)

Lupi, Alessandro; Volonteri, Marta; Silk, Joseph

2017-09-01

Numerical simulations have become a necessary tool to describe the complex interactions among the different processes involved in galaxy formation and evolution, unfeasible via an analytic approach. The last decade has seen a great effort by the scientific community in improving the sub-grid physics modelling and the numerical techniques used to make numerical simulations more predictive. Although the recently publicly available code gizmo has proven to be successful in reproducing galaxy properties when coupled with the model of the MUFASA simulations and the more sophisticated prescriptions of the Feedback In Realistic Environment (FIRE) set-up, it has not been tested yet using delayed cooling supernova feedback, which still represent a reasonable approach for large cosmological simulations, for which detailed sub-grid models are prohibitive. In order to limit the computational cost and to be able to resolve the disc structure in the galaxies we perform a suite of zoom-in cosmological simulations with rather low resolution centred around a sub-L* galaxy with a halo mass of 3 × 1011 M⊙ at z = 0, to investigate the ability of this simple model, coupled with the new hydrodynamic method of gizmo, to reproduce observed galaxy scaling relations (stellar to halo mass, stellar and baryonic Tully-Fisher, stellar mass-metallicity and mass-size). We find that the results are in good agreement with the main scaling relations, except for the total stellar mass, larger than that predicted by the abundance matching technique, and the effective sizes for the most massive galaxies in the sample, which are too small.

Integrating fine-scale soil data into species distribution models: preparing Soil Survey Geographic (SSURGO) data from multiple counties

Treesearch

Matthew P. Peters; Louis R. Iverson; Anantha M. Prasad; Steve N. Matthews

2013-01-01

Fine-scale soil (SSURGO) data were processed at the county level for 37 states within the eastern United States, initially for use as predictor variables in a species distribution model called DISTRIB II. Values from county polygon files converted into a continuous 30-m raster grid were aggregated to 4-km cells and integrated with other environmental and site condition...

Testing the skill of numerical hydraulic modeling to simulate spatiotemporal flooding patterns in the Logone floodplain, Cameroon

NASA Astrophysics Data System (ADS)

Fernández, Alfonso; Najafi, Mohammad Reza; Durand, Michael; Mark, Bryan G.; Moritz, Mark; Jung, Hahn Chul; Neal, Jeffrey; Shastry, Apoorva; Laborde, Sarah; Phang, Sui Chian; Hamilton, Ian M.; Xiao, Ningchuan

2016-08-01

Recent innovations in hydraulic modeling have enabled global simulation of rivers, including simulation of their coupled wetlands and floodplains. Accurate simulations of floodplains using these approaches may imply tremendous advances in global hydrologic studies and in biogeochemical cycling. One such innovation is to explicitly treat sub-grid channels within two-dimensional models, given only remotely sensed data in areas with limited data availability. However, predicting inundated area in floodplains using a sub-grid model has not been rigorously validated. In this study, we applied the LISFLOOD-FP hydraulic model using a sub-grid channel parameterization to simulate inundation dynamics on the Logone River floodplain, in northern Cameroon, from 2001 to 2007. Our goal was to determine whether floodplain dynamics could be simulated with sufficient accuracy to understand human and natural contributions to current and future inundation patterns. Model inputs in this data-sparse region include in situ river discharge, satellite-derived rainfall, and the shuttle radar topography mission (SRTM) floodplain elevation. We found that the model accurately simulated total floodplain inundation, with a Pearson correlation coefficient greater than 0.9, and RMSE less than 700 km2, compared to peak inundation greater than 6000 km2. Predicted discharge downstream of the floodplain matched measurements (Nash-Sutcliffe efficiency of 0.81), and indicated that net flow from the channel to the floodplain was modeled accurately. However, the spatial pattern of inundation was not well simulated, apparently due to uncertainties in SRTM elevations. We evaluated model results at 250, 500 and 1000-m spatial resolutions, and found that results are insensitive to spatial resolution. We also compared the model output against results from a run of LISFLOOD-FP in which the sub-grid channel parameterization was disabled, finding that the sub-grid parameterization simulated more realistic dynamics. These results suggest that analysis of global inundation is feasible using a sub-grid model, but that spatial patterns at sub-kilometer resolutions still need to be adequately predicted.

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

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

McCabe, M. F.; Ershadi, A.; Jimenez, C.

Determining the spatial distribution and temporal development of evaporation at regional and global scales is required to improve our understanding of the coupled water and energy cycles and to better monitor any changes in observed trends and variability of linked hydrological processes. With recent international efforts guiding the development of long-term and globally distributed flux estimates, continued product assessments are required to inform upon the selection of suitable model structures and also to establish the appropriateness of these multi-model simulations for global application. In support of the objectives of the Global Energy and Water Cycle Exchanges (GEWEX) LandFlux project, fourmore » commonly used evaporation models are evaluated against data from tower-based eddy-covariance observations, distributed across a range of biomes and climate zones. The selected schemes include the Surface Energy Balance System (SEBS) approach, the Priestley–Taylor Jet Propulsion Laboratory (PT-JPL) model, the Penman–Monteith-based Mu model (PM-Mu) and the Global Land Evaporation Amsterdam Model (GLEAM). Here we seek to examine the fidelity of global evaporation simulations by examining the multi-model response to varying sources of forcing data. To do this, we perform parallel and collocated model simulations using tower-based data together with a global-scale grid-based forcing product. Through quantifying the multi-model response to high-quality tower data, a better understanding of the subsequent model response to the coarse-scale globally gridded data that underlies the LandFlux product can be obtained, while also providing a relative evaluation and assessment of model performance. Using surface flux observations from 45 globally distributed eddy-covariance stations as independent metrics of performance, the tower-based analysis indicated that PT-JPL provided the highest overall statistical performance (0.72; 61 W m –2; 0.65), followed closely by GLEAM (0.68; 64 W m –2; 0.62), with values in parentheses representing the R 2, RMSD and Nash–Sutcliffe efficiency (NSE), respectively. PM-Mu (0.51; 78 W m –2; 0.45) tended to underestimate fluxes, while SEBS (0.72; 101 W m –2; 0.24) overestimated values relative to observations. A focused analysis across specific biome types and climate zones showed considerable variability in the performance of all models, with no single model consistently able to outperform any other. Results also indicated that the global gridded data tended to reduce the performance for all of the studied models when compared to the tower data, likely a response to scale mismatch and issues related to forcing quality. Rather than relying on any single model simulation, the spatial and temporal variability at both the tower- and grid-scale highlighted the potential benefits of developing an ensemble or blended evaporation product for global-scale LandFlux applications. Hence, challenges related to the robust assessment of the LandFlux product are also discussed.« less

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

DOE PAGES

McCabe, M. F.; Ershadi, A.; Jimenez, C.; ...

2016-01-26

Determining the spatial distribution and temporal development of evaporation at regional and global scales is required to improve our understanding of the coupled water and energy cycles and to better monitor any changes in observed trends and variability of linked hydrological processes. With recent international efforts guiding the development of long-term and globally distributed flux estimates, continued product assessments are required to inform upon the selection of suitable model structures and also to establish the appropriateness of these multi-model simulations for global application. In support of the objectives of the Global Energy and Water Cycle Exchanges (GEWEX) LandFlux project, fourmore » commonly used evaporation models are evaluated against data from tower-based eddy-covariance observations, distributed across a range of biomes and climate zones. The selected schemes include the Surface Energy Balance System (SEBS) approach, the Priestley–Taylor Jet Propulsion Laboratory (PT-JPL) model, the Penman–Monteith-based Mu model (PM-Mu) and the Global Land Evaporation Amsterdam Model (GLEAM). Here we seek to examine the fidelity of global evaporation simulations by examining the multi-model response to varying sources of forcing data. To do this, we perform parallel and collocated model simulations using tower-based data together with a global-scale grid-based forcing product. Through quantifying the multi-model response to high-quality tower data, a better understanding of the subsequent model response to the coarse-scale globally gridded data that underlies the LandFlux product can be obtained, while also providing a relative evaluation and assessment of model performance. Using surface flux observations from 45 globally distributed eddy-covariance stations as independent metrics of performance, the tower-based analysis indicated that PT-JPL provided the highest overall statistical performance (0.72; 61 W m –2; 0.65), followed closely by GLEAM (0.68; 64 W m –2; 0.62), with values in parentheses representing the R 2, RMSD and Nash–Sutcliffe efficiency (NSE), respectively. PM-Mu (0.51; 78 W m –2; 0.45) tended to underestimate fluxes, while SEBS (0.72; 101 W m –2; 0.24) overestimated values relative to observations. A focused analysis across specific biome types and climate zones showed considerable variability in the performance of all models, with no single model consistently able to outperform any other. Results also indicated that the global gridded data tended to reduce the performance for all of the studied models when compared to the tower data, likely a response to scale mismatch and issues related to forcing quality. Rather than relying on any single model simulation, the spatial and temporal variability at both the tower- and grid-scale highlighted the potential benefits of developing an ensemble or blended evaporation product for global-scale LandFlux applications. Hence, challenges related to the robust assessment of the LandFlux product are also discussed.« less

Variations/Changes in Daily Precipitation Extremes Derived from Satellite-Based Products

NASA Astrophysics Data System (ADS)

Gu, G.; Adler, R. F.

2017-12-01

Interannual/decadal-scale variations/changes in daily precipitation extremes are investigated by means of satellite-based high-spatiotemporal resolution precipitation products, including TRMM-TMPA, PERSIANN-CDR-Daily, GPCP 1DD, etc. Extreme precipitation indices at grids are first defined, including the maximum daily precipitation amount (Rx1day), the simple precipitation intensity index (SDII), the conditional (Rcond) daily precipitation rate (Pr>0 mm day-1), and monthly frequencies of rainy (FOCc) and wet (FOCw) days. Other two precipitation intensity indices, i.e., mean daily precipitation rates for Pr ≥10 mm day-1 (Pr10II) and for Pr ≥ 20 mm day-1 (Pr20II), are also constructed. Consistency analyses of daily extreme indices among these data sets are then performed by comparing corresponding averages over large domains such as tropical (30oN-30oS) land, ocean, land+ocean, for their common period (post-1997). This can provide a preliminary uncertainty analysis of these data sets in describing daily extreme precipitation events. Discrepancies can readily be found among these products regarding the magnitudes of area-averaged extreme indices. However, generally consistent temporal variations can be found among the indices derived from different satellite products. Interannual variability in daily precipitation extremes are then examined and compared at grids by exploring their relations with the El Nino-Southern Oscillation (ENSO). Linear correlation and composite analyses are used to examine the impact of ENSO on these extreme indices at grids and over large domains during the post-1997 period. Decadal-scale variability/change in daily extreme events is further examined by using the PERSIANN-CDR-Daily that can cover the entire post-1983 period, based on its general consistency with other two products during the post-1979 period. We specifically focus on exploring and discriminating the effects of decadal-scale internal variability such as the Pacific Decadal Oscillation (PDO) and anthropogenic forcings including the greenhouse-gases (GHG) related warming. Comparisons are also made over global land with the results from two gridded daily rain-gauge products, GPCC Full-record daily (1988-2013) and NOAA/CPC Unified daily (1979-present).

Synoptic scale wind field properties from the SEASAT SASS

NASA Technical Reports Server (NTRS)

Pierson, W. J., Jr.; Sylvester, W. B.; Salfi, R. E.

1984-01-01

Dealiased SEASAT SEASAT A Scatterometer System SASS vector winds obtained during the Gulf Of Alaska SEASAT Experiment GOASEX program are processed to obtain superobservations centered on a one degree by one degree grid. The grid. The results provide values for the combined effects of mesoscale variability and communication noise on the individual SASS winds. These superobservations winds are then processed further to obtain estimates of synoptic scale vector winds stress fields, the horizontal divergence of the wind, the curl of the wind stress and the vertical velocity at 200 m above the sea surface, each with appropriate standard deviations of the estimates for each grid point value. They also explain the concentration of water vapor, liquid water and precipitation found by means of the SMMR Scanning Multichannel Microwave Radiometer at fronts and occlusions in terms of strong warm, moist air advection in the warm air sector accompanied by convergence in the friction layer. Their quality is far superior to that of analyses based on conventional data, which are shown to yield many inconsistencies.

Closing the scale gap between land surface parameterizations and GCMs with a new scheme, SiB3-Bins: SOIL MOISTURE SCALE GAP

DOE PAGES

Baker, I. T.; Sellers, P. J.; Denning, A. S.; ...

2017-03-01

The interaction of land with the atmosphere is sensitive to soil moisture (W). Evapotranspiration (ET) reacts to soil moisture in a nonlinear way, f(W), as soils dry from saturation to wilt point. This nonlinear behavior and the fact that soil moisture varies on scales as small as 1–10 m in nature, while numerical general circulation models (GCMs) have grid cell sizes on the order of 1 to 100s of kilometers, makes the calculation of grid cell-average ET problematic. It is impractical to simulate the land in GCMs on the small scales seen in nature, so techniques have been developed tomore » represent subgrid scale heterogeneity, including: (1) statistical-dynamical representations of grid subelements of varying wetness, (2) relaxation of f(W), (3) moderating f(W) with approximations of catchment hydrology, (4) “tiling” the landscape into vegetation types, and (5) hyperresolution. Here we present an alternative method for representing subgrid variability in W, one proven in a conceptual framework where landscape-scale W is represented as a series of “Bins” of increasing wetness from dry to saturated. The grid cell-level f(W) is defined by the integral of the fractional area of the wetness bins and the value of f(W) associated with each. This approach accounts for the spatiotemporal dynamics of W. We implemented this approach in the SiB3 land surface parameterization and then evaluated its performance against a control, which assumes a horizontally uniform field of W. We demonstrate that the Bins method, with a physical basis, attenuates unrealistic jumps in model state and ET seen in the control runs.« less

Closing the scale gap between land surface parameterizations and GCMs with a new scheme, SiB3-Bins: SOIL MOISTURE SCALE GAP

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

Baker, I. T.; Sellers, P. J.; Denning, A. S.

The interaction of land with the atmosphere is sensitive to soil moisture (W). Evapotranspiration (ET) reacts to soil moisture in a nonlinear way, f(W), as soils dry from saturation to wilt point. This nonlinear behavior and the fact that soil moisture varies on scales as small as 1–10 m in nature, while numerical general circulation models (GCMs) have grid cell sizes on the order of 1 to 100s of kilometers, makes the calculation of grid cell-average ET problematic. It is impractical to simulate the land in GCMs on the small scales seen in nature, so techniques have been developed tomore » represent subgrid scale heterogeneity, including: (1) statistical-dynamical representations of grid subelements of varying wetness, (2) relaxation of f(W), (3) moderating f(W) with approximations of catchment hydrology, (4) “tiling” the landscape into vegetation types, and (5) hyperresolution. Here we present an alternative method for representing subgrid variability in W, one proven in a conceptual framework where landscape-scale W is represented as a series of “Bins” of increasing wetness from dry to saturated. The grid cell-level f(W) is defined by the integral of the fractional area of the wetness bins and the value of f(W) associated with each. This approach accounts for the spatiotemporal dynamics of W. We implemented this approach in the SiB3 land surface parameterization and then evaluated its performance against a control, which assumes a horizontally uniform field of W. We demonstrate that the Bins method, with a physical basis, attenuates unrealistic jumps in model state and ET seen in the control runs.« less

The impact of the resolution of meteorological datasets on catchment-scale drought studies

NASA Astrophysics Data System (ADS)

Hellwig, Jost; Stahl, Kerstin

2017-04-01

Gridded meteorological datasets provide the basis to study drought at a range of scales, including catchment scale drought studies in hydrology. They are readily available to study past weather conditions and often serve real time monitoring as well. As these datasets differ in spatial/temporal coverage and spatial/temporal resolution, for most studies there is a tradeoff between these features. Our investigation examines whether biases occur when studying drought on catchment scale with low resolution input data. For that, a comparison among the datasets HYRAS (covering Central Europe, 1x1 km grid, daily data, 1951 - 2005), E-OBS (Europe, 0.25° grid, daily data, 1950-2015) and GPCC (whole world, 0.5° grid, monthly data, 1901 - 2013) is carried out. Generally, biases in precipitation increase with decreasing resolution. Most important variations are found during summer. In low mountain range of Central Europe the datasets of sparse resolution (E-OBS, GPCC) overestimate dry days and underestimate total precipitation since they are not able to describe high spatial variability. However, relative measures like the correlation coefficient reveal good consistencies of dry and wet periods, both for absolute precipitation values and standardized indices like the Standardized Precipitation Index (SPI) or Standardized Precipitation Evaporation Index (SPEI). Particularly the most severe droughts derived from the different datasets match very well. These results indicate that absolute values of sparse resolution datasets applied to catchment scale might be critical to use for an assessment of the hydrological drought at catchment scale, whereas relative measures for determining periods of drought are more trustworthy. Therefore, studies on drought, that downscale meteorological data, should carefully consider their data needs and focus on relative measures for dry periods if sufficient for the task.

Maximization of permanent trapping of CO{sub 2} and co-contaminants in the highest-porosity formations of the Rock Springs Uplift (Southwest Wyoming): experimentation and multi-scale modeling

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

Piri, Mohammad

2014-03-31

Under this project, a multidisciplinary team of researchers at the University of Wyoming combined state-of-the-art experimental studies, numerical pore- and reservoir-scale modeling, and high performance computing to investigate trapping mechanisms relevant to geologic storage of mixed scCO{sub 2} in deep saline aquifers. The research included investigations in three fundamental areas: (i) the experimental determination of two-phase flow relative permeability functions, relative permeability hysteresis, and residual trapping under reservoir conditions for mixed scCO{sub 2}-­brine systems; (ii) improved understanding of permanent trapping mechanisms; (iii) scientifically correct, fine grid numerical simulations of CO{sub 2} storage in deep saline aquifers taking into account themore » underlying rock heterogeneity. The specific activities included: (1) Measurement of reservoir-­conditions drainage and imbibition relative permeabilities, irreducible brine and residual mixed scCO{sub 2} saturations, and relative permeability scanning curves (hysteresis) in rock samples from RSU; (2) Characterization of wettability through measurements of contact angles and interfacial tensions under reservoir conditions; (3) Development of physically-­based dynamic core-­scale pore network model; (4) Development of new, improved high-­performance modules for the UW-­team simulator to provide new capabilities to the existing model to include hysteresis in the relative permeability functions, geomechanical deformation and an equilibrium calculation (Both pore-­ and core-­scale models were rigorously validated against well-­characterized core-­ flooding experiments); and (5) An analysis of long term permanent trapping of mixed scCO{sub 2} through high-­resolution numerical experiments and analytical solutions. The analysis takes into account formation heterogeneity, capillary trapping, and relative permeability hysteresis.« less

Using Conventional Hydropower to Help Alleviate Variable Resource Grid Integration Challenges in the Western U.S

NASA Astrophysics Data System (ADS)

Veselka, T. D.; Poch, L.

2011-12-01

Integrating high penetration levels of wind and solar energy resources into the power grid is a formidable challenge in virtually all interconnected systems due to the fact that supply and demand must remain in balance at all times. Since large scale electricity storage is currently not economically viable, generation must exactly match electricity demand plus energy losses in the system as time unfolds. Therefore, as generation from variable resources such as wind and solar fluctuate, production from generating resources that are easier to control and dispatch need to compensate for these fluctuations while at the same time respond to both instantaneous change in load and follow daily load profiles. The grid in the Western U.S. is not exempt to grid integration challenges associated with variable resources. However, one advantage that the power system in the Western U.S. has over many other regional power systems is that its footprint contains an abundance of hydropower resources. Hydropower plants, especially those that have reservoir water storage, can physically change electricity production levels very quickly both via a dispatcher and through automatic generation control. Since hydropower response time is typically much faster than other dispatchable resources such as steam or gas turbines, it is well suited to alleviate variable resource grid integration issues. However, despite an abundance of hydropower resources and the current low penetration of variable resources in the Western U.S., problems have already surfaced. This spring in the Pacific Northwest, wetter than normal hydropower conditions in combination with transmission constraints resulted in controversial wind resource shedding. This action was taken since water spilling would have increased dissolved oxygen levels downstream of dams thereby significantly degrading fish habitats. The extent to which hydropower resources will be able to contribute toward a stable and reliable Western grid is currently being studied. Typically these studies consider the inherent flexibility of hydropower technologies, but tend to fall short on details regarding grid operations, institutional arrangements, and hydropower environmental regulations. This presentation will focus on an analysis that Argonne National Laboratory is conducting in collaboration with the Western Area Power Administration (Western). The analysis evaluates the extent to which Western's hydropower resources may help with grid integration challenges via a proposed Energy Imbalance Market. This market encompasses most of the Western Electricity Coordinating Council footprint. It changes grid operations such that the real-time dispatch would be, in part, based on a 5-minute electricity market. The analysis includes many factors such as site-specific environmental considerations at each of its hydropower facilities, long-term firm purchase agreements, and hydropower operating objectives and goals. Results of the analysis indicate that site-specific details significantly affect the ability of hydropower plant to respond to grid needs in a future which will have a high penetration of variable resources.

North Atlantic sub-decadal variability in climate models

NASA Astrophysics Data System (ADS)

Reintges, Annika; Martin, Thomas; Latif, Mojib; Park, Wonsun

2017-04-01

The North Atlantic Oscillation (NAO) is the dominant variability mode for the winter climate of the North Atlantic sector. During a positive (negative) NAO phase, the sea level pressure (SLP) difference between the subtropical Azores high and the subpolar Icelandic low is anomalously strong (weak). This affects, for example, temperature, precipitation, wind, and surface heat flux over the North Atlantic, and over large parts of Europe. In observations we find enhanced sub-decadal variability of the NAO index that goes along with a dipolar sea surface temperature (SST) pattern. The corresponding SLP and SST patterns are reproduced in a control experiment of the Kiel Climate Model (KCM). Large-scale air-sea interaction is suggested to be essential for the North Atlantic sub-decadal variability in the KCM. The Atlantic Meridional Overturning Circulation (AMOC) plays a key role, setting the timescale of the variability by providing a delayed negative feedback to the NAO. The interplay of the NAO and the AMOC on the sub-decadal timescale is further investigated in the CMIP5 model ensemble. For example, the average CMIP5 model AMOC pattern associated with sub-decadal variability is characterized by a deep-reaching dipolar structure, similar to the KCM's sub-decadal AMOC variability pattern. The results suggest that dynamical air-sea interactions are crucial to generate enhanced sub-decadal variability in the North Atlantic climate.

Spatial Representativeness of Surface-Measured Variations of Downward Solar Radiation

NASA Astrophysics Data System (ADS)

Schwarz, M.; Folini, D.; Hakuba, M. Z.; Wild, M.

2017-12-01

When using time series of ground-based surface solar radiation (SSR) measurements in combination with gridded data, the spatial and temporal representativeness of the point observations must be considered. We use SSR data from surface observations and high-resolution (0.05°) satellite-derived data to infer the spatiotemporal representativeness of observations for monthly and longer time scales in Europe. The correlation analysis shows that the squared correlation coefficients (R2) between SSR times series decrease linearly with increasing distance between the surface observations. For deseasonalized monthly mean time series, R2 ranges from 0.85 for distances up to 25 km between the stations to 0.25 at distances of 500 km. A decorrelation length (i.e., the e-folding distance of R2) on the order of 400 km (with spread of 100-600 km) was found. R2 from correlations between point observations and colocated grid box area means determined from satellite data were found to be 0.80 for a 1° grid. To quantify the error which arises when using a point observation as a surrogate for the area mean SSR of larger surroundings, we calculated a spatial sampling error (SSE) for a 1° grid of 8 (3) W/m2 for monthly (annual) time series. The SSE based on a 1° grid, therefore, is of the same magnitude as the measurement uncertainty. The analysis generally reveals that monthly mean (or longer temporally aggregated) point observations of SSR capture the larger-scale variability well. This finding shows that comparing time series of SSR measurements with gridded data is feasible for those time scales.

Introducing Enabling Computational Tools to the Climate Sciences: Multi-Resolution Climate Modeling with Adaptive Cubed-Sphere Grids

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

Jablonowski, Christiane

The research investigates and advances strategies how to bridge the scale discrepancies between local, regional and global phenomena in climate models without the prohibitive computational costs of global cloud-resolving simulations. In particular, the research explores new frontiers in computational geoscience by introducing high-order Adaptive Mesh Refinement (AMR) techniques into climate research. AMR and statically-adapted variable-resolution approaches represent an emerging trend for atmospheric models and are likely to become the new norm in future-generation weather and climate models. The research advances the understanding of multi-scale interactions in the climate system and showcases a pathway how to model these interactions effectively withmore » advanced computational tools, like the Chombo AMR library developed at the Lawrence Berkeley National Laboratory. The research is interdisciplinary and combines applied mathematics, scientific computing and the atmospheric sciences. In this research project, a hierarchy of high-order atmospheric models on cubed-sphere computational grids have been developed that serve as an algorithmic prototype for the finite-volume solution-adaptive Chombo-AMR approach. The foci of the investigations have lied on the characteristics of both static mesh adaptations and dynamically-adaptive grids that can capture flow fields of interest like tropical cyclones. Six research themes have been chosen. These are (1) the introduction of adaptive mesh refinement techniques into the climate sciences, (2) advanced algorithms for nonhydrostatic atmospheric dynamical cores, (3) an assessment of the interplay between resolved-scale dynamical motions and subgrid-scale physical parameterizations, (4) evaluation techniques for atmospheric model hierarchies, (5) the comparison of AMR refinement strategies and (6) tropical cyclone studies with a focus on multi-scale interactions and variable-resolution modeling. The results of this research project demonstrate significant advances in all six research areas. The major conclusions are that statically-adaptive variable-resolution modeling is currently becoming mature in the climate sciences, and that AMR holds outstanding promise for future-generation weather and climate models on high-performance computing architectures.« less

Adaptive EAGLE dynamic solution adaptation and grid quality enhancement

NASA Technical Reports Server (NTRS)

Luong, Phu Vinh; Thompson, J. F.; Gatlin, B.; Mastin, C. W.; Kim, H. J.

1992-01-01

In the effort described here, the elliptic grid generation procedure in the EAGLE grid code was separated from the main code into a subroutine, and a new subroutine which evaluates several grid quality measures at each grid point was added. The elliptic grid routine can now be called, either by a computational fluid dynamics (CFD) code to generate a new adaptive grid based on flow variables and quality measures through multiple adaptation, or by the EAGLE main code to generate a grid based on quality measure variables through static adaptation. Arrays of flow variables can be read into the EAGLE grid code for use in static adaptation as well. These major changes in the EAGLE adaptive grid system make it easier to convert any CFD code that operates on a block-structured grid (or single-block grid) into a multiple adaptive code.

Scenario generation for stochastic optimization problems via the sparse grid method

DOE PAGES

Chen, Michael; Mehrotra, Sanjay; Papp, David

2015-04-19

We study the use of sparse grids in the scenario generation (or discretization) problem in stochastic programming problems where the uncertainty is modeled using a continuous multivariate distribution. We show that, under a regularity assumption on the random function involved, the sequence of optimal objective function values of the sparse grid approximations converges to the true optimal objective function values as the number of scenarios increases. The rate of convergence is also established. We treat separately the special case when the underlying distribution is an affine transform of a product of univariate distributions, and show how the sparse grid methodmore » can be adapted to the distribution by the use of quadrature formulas tailored to the distribution. We numerically compare the performance of the sparse grid method using different quadrature rules with classic quasi-Monte Carlo (QMC) methods, optimal rank-one lattice rules, and Monte Carlo (MC) scenario generation, using a series of utility maximization problems with up to 160 random variables. The results show that the sparse grid method is very efficient, especially if the integrand is sufficiently smooth. In such problems the sparse grid scenario generation method is found to need several orders of magnitude fewer scenarios than MC and QMC scenario generation to achieve the same accuracy. As a result, it is indicated that the method scales well with the dimension of the distribution--especially when the underlying distribution is an affine transform of a product of univariate distributions, in which case the method appears scalable to thousands of random variables.« less

Sensitivity simulations of superparameterised convection in a general circulation model

NASA Astrophysics Data System (ADS)

Rybka, Harald; Tost, Holger

2015-04-01

Cloud Resolving Models (CRMs) covering a horizontal grid spacing from a few hundred meters up to a few kilometers have been used to explicitly resolve small-scale and mesoscale processes. Special attention has been paid to realistically represent cloud dynamics and cloud microphysics involving cloud droplets, ice crystals, graupel and aerosols. The entire variety of physical processes on the small-scale interacts with the larger-scale circulation and has to be parameterised on the coarse grid of a general circulation model (GCM). Since more than a decade an approach to connect these two types of models which act on different scales has been developed to resolve cloud processes and their interactions with the large-scale flow. The concept is to use an ensemble of CRM grid cells in a 2D or 3D configuration in each grid cell of the GCM to explicitly represent small-scale processes avoiding the use of convection and large-scale cloud parameterisations which are a major source for uncertainties regarding clouds. The idea is commonly known as superparameterisation or cloud-resolving convection parameterisation. This study presents different simulations of an adapted Earth System Model (ESM) connected to a CRM which acts as a superparameterisation. Simulations have been performed with the ECHAM/MESSy atmospheric chemistry (EMAC) model comparing conventional GCM runs (including convection and large-scale cloud parameterisations) with the improved superparameterised EMAC (SP-EMAC) modeling one year with prescribed sea surface temperatures and sea ice content. The sensitivity of atmospheric temperature, precipiation patterns, cloud amount and types is observed changing the embedded CRM represenation (orientation, width, no. of CRM cells, 2D vs. 3D). Additionally, we also evaluate the radiation balance with the new model configuration, and systematically analyse the impact of tunable parameters on the radiation budget and hydrological cycle. Furthermore, the subgrid variability (individual CRM cell output) is analysed in order to illustrate the importance of a highly varying atmospheric structure inside a single GCM grid box. Finally, the convective transport of Radon is observed comparing different transport procedures and their influence on the vertical tracer distribution.

Representing anthropogenic gross land use change, wood harvest, and forest age dynamics in a global vegetation model ORCHIDEE-MICT v8.4.2

NASA Astrophysics Data System (ADS)

Yue, Chao; Ciais, Philippe; Luyssaert, Sebastiaan; Li, Wei; McGrath, Matthew J.; Chang, Jinfeng; Peng, Shushi

2018-01-01

Land use change (LUC) is among the main anthropogenic disturbances in the global carbon cycle. Here we present the model developments in a global dynamic vegetation model ORCHIDEE-MICT v8.4.2 for a more realistic representation of LUC processes. First, we included gross land use change (primarily shifting cultivation) and forest wood harvest in addition to net land use change. Second, we included sub-grid evenly aged land cohorts to represent secondary forests and to keep track of the transient stage of agricultural lands since LUC. Combination of these two features allows the simulation of shifting cultivation with a rotation length involving mainly secondary forests instead of primary ones. Furthermore, a set of decision rules regarding the land cohorts to be targeted in different LUC processes have been implemented. Idealized site-scale simulation has been performed for miombo woodlands in southern Africa assuming an annual land turnover rate of 5 % grid cell area between forest and cropland. The result shows that the model can correctly represent forest recovery and cohort aging arising from agricultural abandonment. Such a land turnover process, even though without a net change in land cover, yields carbon emissions largely due to the imbalance between the fast release from forest clearing and the slow uptake from agricultural abandonment. The simulation with sub-grid land cohorts gives lower emissions than without, mainly because the cleared secondary forests have a lower biomass carbon stock than the mature forests that are otherwise cleared when sub-grid land cohorts are not considered. Over the region of southern Africa, the model is able to account for changes in different forest cohort areas along with the historical changes in different LUC activities, including regrowth of old forests when LUC area decreases. Our developments provide possibilities to account for continental or global forest demographic change resulting from past anthropogenic and natural disturbances.

Assessment of spatial variability of major-ion concentrations and del oxygen-18 values in surface snow, Upper Fremont Glacier, Wyoming, USA

USGS Publications Warehouse

Naftz, D.L.; Schuster, P.F.; Reddy, M.M.

1994-01-01

One hundred samples were collected from the surface of the Upper Fremont Glacier at equally spaced intervals defined by an 8100m2 snow grid to asesss the significance of lateral variability in major-ion concentrations and del oxygen-18 values. Comparison of the observed variability of each chemical constituent to the variability expected by measurement error indicated substantial lateral variability with the surface-snow layer. Results of the nested ANOVA indicate most of the variance for every constituent is in the values grouped at the two smaller geographic scales (between 506m2 and within 506m2 sections). The variance data from the snow grid were used to develop equations to evaluate the significance of both positive and negative concentration/value peaks of nitrate and del oxygen-18 with depth, in a 160m ice core. Values of del oxygen-18 in the section from 110-150m below the surface consistently vary outside the expected limits and possibly represents cooler temperatures during the Little Ice Age from about 1810 to 1725 A.D. -from Authors

Online dynamical downscaling of temperature and precipitation within the iLOVECLIM model (version 1.1)

NASA Astrophysics Data System (ADS)

Quiquet, Aurélien; Roche, Didier M.; Dumas, Christophe; Paillard, Didier

2018-02-01

This paper presents the inclusion of an online dynamical downscaling of temperature and precipitation within the model of intermediate complexity iLOVECLIM v1.1. We describe the following methodology to generate temperature and precipitation fields on a 40 km × 40 km Cartesian grid of the Northern Hemisphere from the T21 native atmospheric model grid. Our scheme is not grid specific and conserves energy and moisture in the same way as the original climate model. We show that we are able to generate a high-resolution field which presents a spatial variability in better agreement with the observations compared to the standard model. Although the large-scale model biases are not corrected, for selected model parameters, the downscaling can induce a better overall performance compared to the standard version on both the high-resolution grid and on the native grid. Foreseen applications of this new model feature include the improvement of ice sheet model coupling and high-resolution land surface models.

ISINGLASS Auroral Sounding Rocket Campaign Data Synthesis: Radar, Imagery, and In Situ Observations

NASA Astrophysics Data System (ADS)

Clayton, R.; Lynch, K. A.; Evans, T.; Hampton, D. L.; Burleigh, M.; Zettergren, M. D.; Varney, R. H.; Reimer, A.; Hysell, D. L.; Michell, R.; Samara, M.; Grubbs, G. A., II

2017-12-01

E-field and flow variations across auroral arc boundaries are typically sub-grid measurements for ground based sensors such as radars and imagers, even for quiet stable arcs. In situ measurements can provide small scale resolution, but only provide a snapshot at a localized time and place. Using ground based and in situ measurements of the ISINGLASS auroral sounding rocket campaign in conjunction, we use the in situ measurements to validate ground based synthesis of these small scale observations based on the classification of auroral arcs in Marklund(1984). With validation of this technique, sub-grid information can be gained from radar data using particular visible auroral features during times where only ground based measurements are present. The ISINGLASS campaign (Poker Flat Alaska, Winter 2017) included the nights of Feb 22 2017 and Mar 02 2017, which possessed multiple stable arc boundaries that can be used for synthesis, including the two events into which the ISINGLASS rockets were launched. On Mar 02 from 0700 to 0800 UT, two stable slowly southward-propagating auroral arcs persisted within the instrument field of view, and lasted for a period of >15min. The second of these events contains the 36.304 rocket trajectory, while both events have full ground support from camera imagery and radar. Data synthesis from these events is accomplished using Butler (2010), Vennell (2009), and manually selected auroral boundaries from ground based cameras. With determination of the auroral arc boundaries from ground based imagery, a prediction of the fields along the length of a long straight arc boundary can be made using the ground based radar data, even on a sub-radar-grid scale, using the Marklund arc boundary classification. We assume that fields everywhere along a long stable arc boundary should be the same. Given a long stable arc, measurements anywhere along the arc (i.e. from PFISR) can be replicated along the length of the boundary. This prediction can then be validated from the in situ measurements of the fields from the ISINGLASS campaign. Upon successful synthesis and validation of the ground based data for the times where in situ data are present, the same analysis will be applied to similar long straight stable arcs during the campaign window when ground support is present to further explore the data synthesis method.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Model Validation for Propulsion - On the TFNS and LES Subgrid Models for a Bluff Body Stabilized Flame

NASA Technical Reports Server (NTRS)

Wey, Thomas

2017-01-01

This paper summarizes the reacting results of simulating a bluff body stabilized flame experiment of Volvo Validation Rig using a releasable edition of the National Combustion Code (NCC). The turbulence models selected to investigate the configuration are the sub-grid scaled kinetic energy coupled large eddy simulation (K-LES) and the time-filtered Navier-Stokes (TFNS) simulation. The turbulence chemistry interaction used is linear eddy mixing (LEM).

Dynamically reconfigurable photovoltaic system

DOEpatents

Okandan, Murat; Nielson, Gregory N.

2016-05-31

A PV system composed of sub-arrays, each having a group of PV cells that are electrically connected to each other. A power management circuit for each sub-array has a communications interface and serves to connect or disconnect the sub-array to a programmable power grid. The power grid has bus rows and bus columns. A bus management circuit is positioned at a respective junction of a bus column and a bus row and is programmable through its communication interface to connect or disconnect a power path in the grid. As a result, selected sub-arrays are connected by selected power paths to be in parallel so as to produce a low system voltage, and, alternately in series so as to produce a high system voltage that is greater than the low voltage by at least a factor of ten.

Dynamically reconfigurable photovoltaic system

DOEpatents

Okandan, Murat; Nielson, Gregory N.

2016-12-27

A PV system composed of sub-arrays, each having a group of PV cells that are electrically connected to each other. A power management circuit for each sub-array has a communications interface and serves to connect or disconnect the sub-array to a programmable power grid. The power grid has bus rows and bus columns. A bus management circuit is positioned at a respective junction of a bus column and a bus row and is programmable through its communication interface to connect or disconnect a power path in the grid. As a result, selected sub-arrays are connected by selected power paths to be in parallel so as to produce a low system voltage, and, alternately in series so as to produce a high system voltage that is greater than the low voltage by at least a factor of ten.

Evaluation of a 12-km Satellite-Era Reanalysis of Surface Mass Balance for the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Cullather, R. I.; Nowicki, S.; Zhao, B.; Max, S.

2016-12-01

The recent contribution to sea level change from the Greenland Ice Sheet is thought to be strongly driven by surface processes including melt and runoff. Global reanalyses are potential means of reconstructing the historical time series of ice sheet surface mass balance (SMB), but lack spatial resolution needed to resolve ablation areas along the periphery of the ice sheet. In this work, the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) is used to examine the spatial and temporal variability of surface melt over the Greenland Ice Sheet. MERRA-2 is produced for the period 1980 to the present at a grid spacing of ½° latitude by ⅝° longitude, and includes snow hydrology processes including compaction, meltwater percolation and refreezing, runoff, and a prognostic surface albedo. The configuration of the MERRA-2 system allows for the background model - the Goddard Earth Observing System model, version 5 (GEOS-5) - to be carried in phase space through analyzed states via the computation of analysis increments, a capability referred to as "replay". Here, a MERRA-2 replay integration is conducted in which atmospheric forcing fields are interpolated and adjusted to sub- atmospheric grid-scale resolution. These adjustments include lapse-rate effects on temperature, humidity, precipitation, and other atmospheric variables that are known to have a strong elevation dependency over ice sheets. The surface coupling is performed such that mass and energy are conserved. The atmospheric forcing influences the surface representation, which operates on land surface tiles with an approximate 12-km spacing. This produces a high-resolution, downscaled SMB which is interactively coupled to the reanalysis model. We compare the downscaled SMB product with other reanalyses, regional climate model values, and a second MERRA-2 replay in which the background model has been replaced with a 12-km, non-hydrostatic version of GEOS-5. The assessment focuses on regional changes in SMB and SMB components, the identification of changes and temporal variability in the SMB equilibrium line, and the relation between SMB and other climate variables related to general circulation.

Groundwater Variability in a Sandstone Catchment and Linkages with Large-scale Climatic Circulatio

NASA Astrophysics Data System (ADS)

Hannah, D. M.; Lavers, D. A.; Bradley, C.

2015-12-01

Groundwater is a crucial water resource that sustains river ecosystems and provides public water supply. Furthermore, during periods of prolonged high rainfall, groundwater-dominated catchments can be subject to protracted flooding. Climate change and associated projected increases in the frequency and intensity of hydrological extremes have implications for groundwater levels. This study builds on previous research undertaken on a Chalk catchment by investigating groundwater variability in a UK sandstone catchment: the Tern in Shropshire. In contrast to the Chalk, sandstone is characterised by a more lagged response to precipitation inputs; and, as such, it is important to determine the groundwater behaviour and its links with the large-scale climatic circulation to improve process understanding of recharge, groundwater level and river flow responses to hydroclimatological drivers. Precipitation, river discharge and groundwater levels for borehole sites in the Tern basin over 1974-2010 are analysed as the target variables; and we use monthly gridded reanalysis data from the Twentieth Century Reanalysis Project (20CR). First, groundwater variability is evaluated and associations with precipitation / discharge are explored using monthly concurrent and lagged correlation analyses. Second, gridded 20CR reanalysis data are used in composite and correlation analyses to identify the regions of strongest climate-groundwater association. Results show that reasonably strong climate-groundwater connections exist in the Tern basin, with a several months lag. These lags are associated primarily with the time taken for recharge waters to percolate through to the groundwater table. The uncovered patterns improve knowledge of large-scale climate forcing of groundwater variability and may provide a basis to inform seasonal prediction of groundwater levels, which would be useful for strategic water resource planning.

Time-Lapse Geophysical Measurements targeting Spatial and Temporal Variability in Biogenic Gas Production from Peat Soils in a Hydrologically Controlled Wetland in the Florida Everglades

NASA Astrophysics Data System (ADS)

Wright, W. J.; Shahan, T.; Sharp, N.; Comas, X.

2015-12-01

Peat soils are known to release globally significant amounts of methane (CH4) and carbon dioxide (CO2) to the atmosphere. However, uncertainties still remain regarding the spatio-temporal distribution of gas accumulations and triggering mechanisms of gas releasing events. Furthermore, most research on peatland gas dynamics has traditionally been focused on high latitude peatlands. Therefore, understanding gas dynamics in low-latitude peatlands (e.g. the Florida Everglades) is key to global climate research. Recent studies in the Everglades have demonstrated that biogenic gas flux values may vary when considering different temporal and spatial scales of measurements. The work presented here targets spatial variability in gas production and release at the plot scale in an approximately 85 m2 area, and targets temporal variability with data collected during the spring months of two different years. This study is located in the Loxahatchee Impoundment Landscape Assessment (LILA), a hydrologically controlled, landscape scale (30 Ha) model of the Florida Everglades. Ground penetrating radar (GPR) has been used in the past to investigate biogenic gas dynamics in peat soils, and is used in this study to monitor changes of in situ gas storage. Each year, a grid of GPR profiles was collected to image changes in gas distribution in 2d on a weekly basis, and several flux chambers outfitted with time-lapse cameras captured high resolution (hourly) gas flux measurements inside the GPR grid. Combining these methods allows us to use a mass balance approach to estimate spatial variability in gas production rates, and capture temporal variability in gas flux rates.

Influence of topographic heterogeneity on the abandance of larch forest in eastern Siberia

NASA Astrophysics Data System (ADS)

Sato, H.; Kobayashi, H.

2016-12-01

In eastern Siberia, larches (Larix spp.) often exist in pure stands, constructing the world's largest coniferous forest, of which changes can significantly affect the earth's albedo and the global carbon balance. We have conducted simulation studies for this vegetation, aiming to forecast its structures and functions under changing climate (1, 2). In previous studies of simulating vegetation at large geographical scales, the examining area is divided into coarse grid cells such as 0.5 * 0.5 degree resolution, and topographical heterogeneities within each grid cell are just ignored. However, in Siberian larch area, which is located on the environmental edge of existence of forest ecosystem, abundance of larch trees largely depends on topographic condition at the scale of tens to hundreds meters. We, therefore, analyzed patterns of within-grid-scale heterogeneity of larch LAI as a function of topographic condition, and examined its underlying reason. For this analysis, larch LAI was estimated for each 1/112 degree from the SPOT-VEGETATION data, and topographic properties such as angularity and aspect direction were estimated form the ASTER-GDEM data. Through this analysis, we found that, for example, sign of correlation between angularity and larch LAI depends on hydrological condition on the grid cell. We then refined the hydrological sub-model of our vegetation model SEIB-DGVM, and validated whether the modified model can reconstruct these patterns, and examined its impact on the estimation of biomass and vegetation productivity of entire larch region. -- References --1. Sato, H., et al. (2010). "Simulation study of the vegetation structure and function in eastern Siberian larch forests using the individual-based vegetation model SEIB-DGVM." Forest Ecology and Management 259(3): 301-311.2. Sato, H., et al. (2016). "Endurance of larch forest ecosystems in eastern Siberia under warming trends." Ecology and Evolution

On the Representation of Subgrid Microtopography Effects in Process-based Hydrologic Models

NASA Astrophysics Data System (ADS)

Jan, A.; Painter, S. L.; Coon, E. T.

2017-12-01

Increased availability of high-resolution digital elevation are enabling process-based hydrologic modeling on finer and finer scales. However, spatial variability in surface elevation (microtopography) exists below the scale of a typical hyper-resolution grid cell and has the potential to play a significant role in water retention, runoff, and surface/subsurface interactions. Though the concept of microtopographic features (depressions, obstructions) and the associated implications on flow and discharge are well established, representing those effects in watershed-scale integrated surface/subsurface hydrology models remains a challenge. Using the complex and coupled hydrologic environment of the Arctic polygonal tundra as an example, we study the effects of submeter topography and present a subgrid model parameterized by small-scale spatial heterogeneities for use in hyper-resolution models with polygons at a scale of 15-20 meters forming the surface cells. The subgrid model alters the flow and storage terms in the diffusion wave equation for surface flow. We compare our results against sub-meter scale simulations (acts as a benchmark for our simulations) and hyper-resolution models without the subgrid representation. The initiation of runoff in the fine-scale simulations is delayed and the recession curve is slowed relative to simulated runoff using the hyper-resolution model with no subgrid representation. Our subgrid modeling approach improves the representation of runoff and water retention relative to models that ignore subgrid topography. We evaluate different strategies for parameterizing subgrid model and present a classification-based method to efficiently move forward to larger landscapes. This work was supported by the Interoperable Design of Extreme-scale Application Software (IDEAS) project and the Next-Generation Ecosystem Experiments-Arctic (NGEE Arctic) project. NGEE-Arctic is supported by the Office of Biological and Environmental Research in the DOE Office of Science.

Linking field-based ecological data with remotely sensed data using a geographic information system in two malaria endemic urban areas of Kenya.

PubMed

Eisele, Thomas P; Keating, Joseph; Swalm, Chris; Mbogo, Charles M; Githeko, Andrew K; Regens, James L; Githure, John I; Andrews, Linda; Beier, John C

2003-12-10

BACKGROUND: Remote sensing technology provides detailed spectral and thermal images of the earth's surface from which surrogate ecological indicators of complex processes can be measured. METHODS: Remote sensing data were overlaid onto georeferenced entomological and human ecological data randomly sampled during April and May 2001 in the cities of Kisumu (population asymptotically equal to 320,000) and Malindi (population asymptotically equal to 81,000), Kenya. Grid cells of 270 meters x 270 meters were used to generate spatial sampling units for each city for the collection of entomological and human ecological field-based data. Multispectral Thermal Imager (MTI) satellite data in the visible spectrum at five meter resolution were acquired for Kisumu and Malindi during February and March 2001, respectively. The MTI data were fit and aggregated to the 270 meter x 270 meter grid cells used in field-based sampling using a geographic information system. The normalized difference vegetation index (NDVI) was calculated and scaled from MTI data for selected grid cells. Regression analysis was used to assess associations between NDVI values and entomological and human ecological variables at the grid cell level. RESULTS: Multivariate linear regression showed that as household density increased, mean grid cell NDVI decreased (global F-test = 9.81, df 3,72, P-value = <0.01; adjusted R2 = 0.26). Given household density, the number of potential anopheline larval habitats per grid cell also increased with increasing values of mean grid cell NDVI (global F-test = 14.29, df 3,36, P-value = <0.01; adjusted R2 = 0.51). CONCLUSIONS: NDVI values obtained from MTI data were successfully overlaid onto georeferenced entomological and human ecological data spatially sampled at a scale of 270 meters x 270 meters. Results demonstrate that NDVI at such a scale was sufficient to describe variations in entomological and human ecological parameters across both cities.

A High Order Finite Difference Scheme with Sharp Shock Resolution for the Euler Equations

NASA Technical Reports Server (NTRS)

Gerritsen, Margot; Olsson, Pelle

1996-01-01

We derive a high-order finite difference scheme for the Euler equations that satisfies a semi-discrete energy estimate, and present an efficient strategy for the treatment of discontinuities that leads to sharp shock resolution. The formulation of the semi-discrete energy estimate is based on a symmetrization of the Euler equations that preserves the homogeneity of the flux vector, a canonical splitting of the flux derivative vector, and the use of difference operators that satisfy a discrete analogue to the integration by parts procedure used in the continuous energy estimate. Around discontinuities or sharp gradients, refined grids are created on which the discrete equations are solved after adding a newly constructed artificial viscosity. The positioning of the sub-grids and computation of the viscosity are aided by a detection algorithm which is based on a multi-scale wavelet analysis of the pressure grid function. The wavelet theory provides easy to implement mathematical criteria to detect discontinuities, sharp gradients and spurious oscillations quickly and efficiently.

IGMS: An Integrated ISO-to-Appliance Scale Grid Modeling System

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

Palmintier, Bryan; Hale, Elaine; Hansen, Timothy M.

This paper describes the Integrated Grid Modeling System (IGMS), a novel electric power system modeling platform for integrated transmission-distribution analysis that co-simulates off-the-shelf tools on high performance computing (HPC) platforms to offer unprecedented resolution from ISO markets down to appliances and other end uses. Specifically, the system simultaneously models hundreds or thousands of distribution systems in co-simulation with detailed Independent System Operator (ISO) markets and AGC-level reserve deployment. IGMS uses a new MPI-based hierarchical co-simulation framework to connect existing sub-domain models. Our initial efforts integrate opensource tools for wholesale markets (FESTIV), bulk AC power flow (MATPOWER), and full-featured distribution systemsmore » including physics-based end-use and distributed generation models (many instances of GridLAB-D[TM]). The modular IGMS framework enables tool substitution and additions for multi-domain analyses. This paper describes the IGMS tool, characterizes its performance, and demonstrates the impacts of the coupled simulations for analyzing high-penetration solar PV and price responsive load scenarios.« less

Atmospheric mechanisms governing the spatial and temporal variability of phenological phases in central Europe

NASA Astrophysics Data System (ADS)

Scheifinger, Helfried; Menzel, Annette; Koch, Elisabeth; Peter, Christian; Ahas, Rein

2002-11-01

A data set of 17 phenological phases from Germany, Austria, Switzerland and Slovenia spanning the time period from 1951 to 1998 has been made available for analysis together with a gridded temperature data set (1° × 1° grid) and the North Atlantic Oscillation (NAO) index time series. The disturbances of the westerlies constitute the main atmospheric source for the temporal variability of phenological events in Europe. The trend, the standard deviation and the discontinuity of the phenological time series at the end of the 1980s can, to a great extent, be explained by the NAO. A number of factors modulate the influence of the NAO in time and space. The seasonal northward shift of the westerlies overlaps with the sequence of phenological spring phases, thereby gradually reducing its influence on the temporal variability of phenological events with progression of spring (temporal loss of influence). This temporal process is reflected by a pronounced decrease in trend and standard deviation values and common variability with the NAO with increasing year-day. The reduced influence of the NAO with increasing distance from the Atlantic coast is not only apparent in studies based on the data set of the International Phenological Gardens, but also in the data set of this study with a smaller spatial extent (large-scale loss of influence). The common variance between phenological and NAO time series displays a discontinuous drop from the European Atlantic coast towards the Alps. On a local and regional scale, mountainous terrain reduces the influence of the large-scale atmospheric flow from the Atlantic via a proposed decoupling mechanism. Valleys in mountainous terrain have the inclination to harbour temperature inversions over extended periods of time during the cold season, which isolate the valley climate from the large-scale atmospheric flow at higher altitudes. Most phenological stations reside at valley bottoms and are thus largely decoupled in their temporal variability from the influence of the westerly flow regime (local-scale loss of influence). This study corroborates an increasing number of similar investigations that find that vegetation does react in a sensitive way to variations of its atmospheric environment across various temporal and spatial scales.

New Approaches to Quantifying Transport Model Error in Atmospheric CO2 Simulations

NASA Technical Reports Server (NTRS)

Ott, L.; Pawson, S.; Zhu, Z.; Nielsen, J. E.; Collatz, G. J.; Gregg, W. W.

2012-01-01

In recent years, much progress has been made in observing CO2 distributions from space. However, the use of these observations to infer source/sink distributions in inversion studies continues to be complicated by difficulty in quantifying atmospheric transport model errors. We will present results from several different experiments designed to quantify different aspects of transport error using the Goddard Earth Observing System, Version 5 (GEOS-5) Atmospheric General Circulation Model (AGCM). In the first set of experiments, an ensemble of simulations is constructed using perturbations to parameters in the model s moist physics and turbulence parameterizations that control sub-grid scale transport of trace gases. Analysis of the ensemble spread and scales of temporal and spatial variability among the simulations allows insight into how parameterized, small-scale transport processes influence simulated CO2 distributions. In the second set of experiments, atmospheric tracers representing model error are constructed using observation minus analysis statistics from NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA). The goal of these simulations is to understand how errors in large scale dynamics are distributed, and how they propagate in space and time, affecting trace gas distributions. These simulations will also be compared to results from NASA's Carbon Monitoring System Flux Pilot Project that quantified the impact of uncertainty in satellite constrained CO2 flux estimates on atmospheric mixing ratios to assess the major factors governing uncertainty in global and regional trace gas distributions.

The Effect of Ocean Currents on Sea Surface Temperature Anomalies

NASA Technical Reports Server (NTRS)

Stammer, Detlef; Leeuwenburgh, Olwijn

2000-01-01

We investigate regional and global-scale correlations between observed anomalies in sea surface temperature and height. A strong agreement between the two fields is found over a broad range of latitudes for different ocean basins. Both time-longitude plots and wavenumber-frequency spectra suggest an advective forcing of SST anomalies by a first-mode baroclinic wave field on spatial scales down to 400 km and time scales as short as 1 month. Even though the magnitude of the mean background temperature gradient is determining for the effectiveness of the forcing, there is no obvious seasonality that can be detected in the amplitudes of SST anomalies. Instead, individual wave signatures in the SST can in some cases be followed over periods of two years. The phase relationship between SST and SSH anomalies is dependent upon frequency and wavenumber and displays a clear decrease of the phase lag toward higher latitudes where the two fields come into phase at low frequencies. Estimates of the damping coefficient are larger than generally obtained for a purely atmospheric feedback. From a global frequency spectrum a damping time scale of 2-3 month was found. Regionally results are very variable and range from 1 month near strong currents to 10 month at low latitudes and in the sub-polar North Atlantic. Strong agreement is found between the first global EOF modes of 10 day averaged and spatially smoothed SST and SSH grids. The accompanying time series display low frequency oscillations in both fields.

THE DEVELOPMENT OF A 1990 GLOBAL INVENTORY FOR SO(X) AND NO(X) ON A 1(DEGREE) X 1(DEGREE) LATITUDE-LONGITUDE GRID.

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

VAN HEYST,B.J.

1999-10-01

Sulfur and nitrogen oxides emitted to the atmosphere have been linked to the acidification of water bodies and soils and perturbations in the earth's radiation balance. In order to model the global transport and transformation of SO{sub x} and NO{sub x}, detailed spatial and temporal emission inventories are required. Benkovitz et al. (1996) published the development of an inventory of 1985 global emissions of SO{sub x} and NO{sub x} from anthropogenic sources. The inventory was gridded to a 1{degree} x 1{degree} latitude-longitude grid and has served as input to several global modeling studies. There is now a need to providemore » modelers with an update of this inventory to a more recent year, with a split of the emissions into elevated and low level sources. This paper describes the development of a 1990 update of the SO{sub x} and NO{sub x} global inventories that also includes a breakdown of sources into 17 sector groups. The inventory development starts with a gridded global default EDGAR inventory (Olivier et al, 1996). In countries where more detailed national inventories are available, these are used to replace the emissions for those countries in the global default. The gridded emissions are distributed into two height levels (0-100m and >100m) based on the final plume heights that are estimated to be typical for the various sectors considered. The sources of data as well as some of the methodologies employed to compile and develop the 1990 global inventory for SO{sub x} and NO{sub x} are discussed. The results reported should be considered to be interim since the work is still in progress and additional data sets are expected to become available.« less

High Resolution Regional Climate Modeling for Lebanon, Eastern Mediterranean Coast

NASA Astrophysics Data System (ADS)

Katurji, Marwan; Soltanzadeh, Iman; Kuhnlein, Meike; Zawar-Reza, Peyman

2013-04-01

The Eastern Mediterranean coast consists of Lebanon, Palestine, Syria, Israel and a small part of southern Turkey. The region lies between latitudes 30 degrees S and 40 degrees N, which makes its climate affected by westerly propagating wintertime cyclones spinning off mid-latitude troughs (December, January and February), while during summer (June, July and August) the area is strongly affected by the sub-tropical anti-cyclonic belt as a result of the descending air of the Hadley cell circulation system. The area is considered to be in a transitional zone between tropical to mid-latitude climate regimes, and having a coastal topography up to 3000 m in elevation (like in the Western Ranges of Lebanon), which emphasizes the complexity of climate variability in this area under future predictions of climate change. This research incorporates both regional climate numerical simulations, Tropical Rainfall Measuring Mission (TRMM) satellite derived and surface rain gauge rainfall data to evaluate the Regional Climate Model (RegCM) version 4 ability to represent both the mean and variance of observed precipitation in the Eastern Mediterranean Region, with emphasis on the Lebanese coastal terrain and mountain ranges. The adopted methodology involves dynamically down scaling climate data from reanalysis synoptic files through a double nesting procedure. The retrospective analysis of 13 years with both 50 and 10 km spatial resolution allows for the assessment of the model results on both a climate scale and specific high intensity precipitating events. The spatial averaged mean bias error in precipitation rate for the rainy season predicted by RegCM 50 and 10 km resolution grids was 0.13 and 0.004 mm hr-1 respectively. When correlating RegCM and TRMM precipitation rate for the domain covering Lebanon's coastal mountains, the root mean square error (RMSE) for the mean quantities over the 13-year period was only 0.03, while the RMSE for the standard deviation was higher by one order of magnitude. Initial results showed good spatial variability agreement for precipitation with the satellite-derived data with improved results for the 10 km grid resolution setup. Also, results show a larger uncertainty within RegCM for predicting extreme precipitation events. Future work will investigate the ability of RegCM to simulate these extreme deviations in precipitation. The results from this research can be helpful for the better design of future regional climate down scaling predictions under climate change scenarios.

The development of an hourly gridded rainfall product for hydrological applications in England and Wales

NASA Astrophysics Data System (ADS)

Liguori, Sara; O'Loughlin, Fiachra; Souvignet, Maxime; Coxon, Gemma; Freer, Jim; Woods, Ross

2014-05-01

This research presents a newly developed observed sub-daily gridded precipitation product for England and Wales. Importantly our analysis specifically allows a quantification of rainfall errors from grid to the catchment scale, useful for hydrological model simulation and the evaluation of prediction uncertainties. Our methodology involves the disaggregation of the current one kilometre daily gridded precipitation records available for the United Kingdom[1]. The hourly product is created using information from: 1) 2000 tipping-bucket rain gauges; and 2) the United Kingdom Met-Office weather radar network. These two independent datasets provide rainfall estimates at temporal resolutions much smaller than the current daily gridded rainfall product; thus allowing the disaggregation of the daily rainfall records to an hourly timestep. Our analysis is conducted for the period 2004 to 2008, limited by the current availability of the datasets. We analyse the uncertainty components affecting the accuracy of this product. Specifically we explore how these uncertainties vary spatially, temporally and with climatic regimes. Preliminary results indicate scope for improvement of hydrological model performance by the utilisation of this new hourly gridded rainfall product. Such product will improve our ability to diagnose and identify structural errors in hydrological modelling by including the quantification of input errors. References [1] Keller V, Young AR, Morris D, Davies H (2006) Continuous Estimation of River Flows. Technical Report: Estimation of Precipitation Inputs. in Agency E (ed.). Environmental Agency.

Variational estimation of process parameters in a simplified atmospheric general circulation model

NASA Astrophysics Data System (ADS)

Lv, Guokun; Koehl, Armin; Stammer, Detlef

2016-04-01

Parameterizations are used to simulate effects of unresolved sub-grid-scale processes in current state-of-the-art climate model. The values of the process parameters, which determine the model's climatology, are usually manually adjusted to reduce the difference of model mean state to the observed climatology. This process requires detailed knowledge of the model and its parameterizations. In this work, a variational method was used to estimate process parameters in the Planet Simulator (PlaSim). The adjoint code was generated using automatic differentiation of the source code. Some hydrological processes were switched off to remove the influence of zero-order discontinuities. In addition, the nonlinearity of the model limits the feasible assimilation window to about 1day, which is too short to tune the model's climatology. To extend the feasible assimilation window, nudging terms for all state variables were added to the model's equations, which essentially suppress all unstable directions. In identical twin experiments, we found that the feasible assimilation window could be extended to over 1-year and accurate parameters could be retrieved. Although the nudging terms transform to a damping of the adjoint variables and therefore tend to erases the information of the data over time, assimilating climatological information is shown to provide sufficient information on the parameters. Moreover, the mechanism of this regularization is discussed.

Optimal configurations of spatial scale for grid cell firing under noise and uncertainty

PubMed Central

Towse, Benjamin W.; Barry, Caswell; Bush, Daniel; Burgess, Neil

2014-01-01

We examined the accuracy with which the location of an agent moving within an environment could be decoded from the simulated firing of systems of grid cells. Grid cells were modelled with Poisson spiking dynamics and organized into multiple ‘modules’ of cells, with firing patterns of similar spatial scale within modules and a wide range of spatial scales across modules. The number of grid cells per module, the spatial scaling factor between modules and the size of the environment were varied. Errors in decoded location can take two forms: small errors of precision and larger errors resulting from ambiguity in decoding periodic firing patterns. With enough cells per module (e.g. eight modules of 100 cells each) grid systems are highly robust to ambiguity errors, even over ranges much larger than the largest grid scale (e.g. over a 500 m range when the maximum grid scale is 264 cm). Results did not depend strongly on the precise organization of scales across modules (geometric, co-prime or random). However, independent spatial noise across modules, which would occur if modules receive independent spatial inputs and might increase with spatial uncertainty, dramatically degrades the performance of the grid system. This effect of spatial uncertainty can be mitigated by uniform expansion of grid scales. Thus, in the realistic regimes simulated here, the optimal overall scale for a grid system represents a trade-off between minimizing spatial uncertainty (requiring large scales) and maximizing precision (requiring small scales). Within this view, the temporary expansion of grid scales observed in novel environments may be an optimal response to increased spatial uncertainty induced by the unfamiliarity of the available spatial cues. PMID:24366144

A web system of virtual morphometric globes for Mars and the Moon

NASA Astrophysics Data System (ADS)

Florinsky, I. V.; Garov, A. S.; Karachevtseva, I. P.

2018-09-01

We developed a web system of virtual morphometric globes for Mars and the Moon. As the initial data, we used 15-arc-minutes gridded global digital elevation models (DEMs) extracted from the Mars Orbiter Laser Altimeter (MOLA) and the Lunar Orbiter Laser Altimeter (LOLA) gridded archives. We derived global digital models of sixteen morphometric variables including horizontal, vertical, minimal, and maximal curvatures, as well as catchment area and topographic index. The morphometric models were integrated into the web system developed as a distributed application consisting of a client front-end and a server back-end. The following main functions are implemented in the system: (1) selection of a morphometric variable; (2) two-dimensional visualization of a calculated global morphometric model; (3) 3D visualization of a calculated global morphometric model on the sphere surface; (4) change of a globe scale; and (5) globe rotation by an arbitrary angle. Free, real-time web access to the system is provided. The web system of virtual morphometric globes can be used for geological and geomorphological studies of Mars and the Moon at the global, continental, and regional scales.

Role of Smarter Grids in Variable Renewable Resource Integration (Presentation)

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

Miller, M.

2012-07-01

This presentation discusses the role of smarter grids in variable renewable resource integration and references material from a forthcoming ISGAN issue paper: Smart Grid Contributions to Variable Renewable Resource Integration, co-written by the presenter and currently in review.

Verification of High Resolution Soil Moisture and Latent Heat in Germany

NASA Astrophysics Data System (ADS)

Samaniego, L. E.; Warrach-Sagi, K.; Zink, M.; Wulfmeyer, V.

2012-12-01

Improving our understanding of soil-land-surface-atmosphere feedbacks is fundamental to make reliable predictions of water and energy fluxes on land systems influenced by anthropogenic activities. Estimating, for instance, which would be the likely consequences of changing climatic regimes on water availability and crop yield, requires of high resolution soil moisture. Modeling it at large-scales, however, is difficult and uncertain because of the interplay between state variables and fluxes and the significant parameter uncertainty of the predicting models. At larger scales, the sub-grid variability of the variables involved and the nonlinearity of the processes complicate the modeling exercise even further because parametrization schemes might be scale dependent. Two contrasting modeling paradigms (WRF/Noah-MP and mHM) were employed to quantify the effects of model and data complexity on soil moisture and latent heat over Germany. WRF/Noah-MP was forced ERA-interim on the boundaries of the rotated CORDEX-Grid (www.meteo.unican.es/wiki/cordexwrf) with a spatial resolution of 0.11o covering Europe during the period from 1989 to 2009. Land cover and soil texture were represented in WRF/Noah-MP with 1×1~km MODIS images and a single horizon, coarse resolution European-wide soil map with 16 soil texture classes, respectively. To ease comparison, the process-based hydrological model mHM was forced with daily precipitation and temperature fields generated by WRF during the same period. The spatial resolution of mHM was fixed at 4×4~km. The multiscale parameter regionalization technique (MPR, Samaniego et al. 2010) was embedded in mHM to be able to estimate effective model parameters using hyper-resolution input data (100×100~km) obtained from Corine land cover and detailed soil texture fields for various horizons comprising 72 soil texture classes for Germany, among other physiographical variables. mHM global parameters, in contrast with those of Noah-MP, were obtained by closing the water balance over major river basins in Germany. Simulated soil moisture and latent heat flux were also evaluated at several eddy covariance sites in Germany. Comparison of monthly soil moisture and latent heat fields obtained with both models over Germany exhibited significant differences, which are mainly attributed to the subgrid variability of key model parameters such as porosity and aerodynamic resistance. Comparison of soil moisture fields obtained with WRF/Noah-MP and mHM forced with grided metereological observations (German Meteorological Service) showed that the differences between both models are mainly due to a combination of precipitation bias and different soil texture resolution. However, EOF analyses indicate that CORDEX results start recovering structures due to soil and vegetation properties. This experiment clearly highlighted the importance of hyper resolution input data to address these challenge. High resolution mHM simulations also indicate that the parametric uncertainty of land surface models is significant, and should not be neglected if a model is to be employed for application at regional scales, e.g. for drought monitoring.

Large eddy simulation of premixed and non-premixed combustion in a Stagnation Point Reverse Flow combustor

NASA Astrophysics Data System (ADS)

Undapalli, Satish

A new combustor referred to as Stagnation Point Reverse Flow (SPRF) combustor has been developed at Georgia Tech to meet the increasingly stringent emission regulations. The combustor incorporates a novel design to meet the conflicting requirements of low pollution and high stability in both premixed and non-premixed modes. The objective of this thesis work is to perform Large Eddy Simulations (LES) on this lab-scale combustor and elucidate the underlying physics that has resulted in its excellent performance. To achieve this, numerical simulations have been performed in both the premixed and non-premixed combustion modes, and velocity field, species field, entrainment characteristics, flame structure, emissions, and mixing characteristics have been analyzed. Simulations have been carried out first for a non-reactive case to resolve relevant fluid mechanics without heat release by the computational grid. The computed mean and RMS quantities in the non-reacting case compared well with the experimental data. Next, the simulations were extended for the premixed reactive case by employing different sub-grid scale combustion chemistry closures: Eddy Break Up (EBU), Artificially Thickened Flame (TF) and Linear Eddy Mixing (LEM) models. Results from the EBU and TF models exhibit reasonable agreement with the experimental velocity field. However, the computed thermal and species fields have noticeable discrepancies. Only LEM with LES (LEMLES), which is an advanced scalar approach, has been able to accurately predict both the velocity and species fields. Scalar mixing plays an important role in combustion, and this is solved directly at the sub-grid scales in LEM. As a result, LEM accurately predicts the scalar fields. Due to the two way coupling between the super-grid and sub-grid quantities, the velocity predictions also compare very well with the experiments. In other approaches, the sub-grid effects have been either modeled using conventional approaches (EBU) or need some ad hoc adjustments to account these effects accurately (TF). The results from LEMLES, using a reduced chemical mechanism, have been analyzed in the premixed mode. The results show that mass entrainment occurs along the shear layer in the combustor. The entrained mass carries products into the reactant stream and provides reactant preheating. Thus, product entrainment enhances the reaction rates and help stabilize the flame even at very lean conditions. These products have been shown to enter into the flame through local extinction zones present on the flame surface. The flame structure has been further analyzed, and the combustion mode was found to be primarily in thin reaction zones. Closer to the injector, there are isolated regions, where the combustion mode is in broken reaction zones, while the downstream flame structure is closer to a flamelet regime. The emissions in the combustor have been studied using simple global mechanisms for NO x. Computations have shown extremely low NOx values, comparable to the measured emissions. These low emissions have been shown to be primarily due to the low temperatures in the combustor. LEMLES computations have also been performed with a detailed chemistry to capture more accurate flame structure. The flame in the detailed chemistry case shows more extinction zones close to the injector than that in the reduced chemical mechanism. The LEMLES approach has also been used to resolve the combustion mode in the non-premixed case. The studies have indicated that the mixing of the fuel and air close to the injector controls the combustion process. The predictions in the near field have been shown to be very sensitive to the inflow conditions. Analysis has shown that the fuel and air mixing occurs to lean proportions in the combustor before any burning takes place. The flame structure in the non-premixed mode was very similar to the premixed mode. Along with the fuel air mixing, the products also mixed with the reactants and provided the preheating effects to stabilize the flame in the downstream region of the combustor.

A multi-resolution approach to electromagnetic modeling.

NASA Astrophysics Data System (ADS)

Cherevatova, M.; Egbert, G. D.; Smirnov, M. Yu

2018-04-01

We present a multi-resolution approach for three-dimensional magnetotelluric forward modeling. Our approach is motivated by the fact that fine grid resolution is typically required at shallow levels to adequately represent near surface inhomogeneities, topography, and bathymetry, while a much coarser grid may be adequate at depth where the diffusively propagating electromagnetic fields are much smoother. This is especially true for forward modeling required in regularized inversion, where conductivity variations at depth are generally very smooth. With a conventional structured finite-difference grid the fine discretization required to adequately represent rapid variations near the surface are continued to all depths, resulting in higher computational costs. Increasing the computational efficiency of the forward modeling is especially important for solving regularized inversion problems. We implement a multi-resolution finite-difference scheme that allows us to decrease the horizontal grid resolution with depth, as is done with vertical discretization. In our implementation, the multi-resolution grid is represented as a vertical stack of sub-grids, with each sub-grid being a standard Cartesian tensor product staggered grid. Thus, our approach is similar to the octree discretization previously used for electromagnetic modeling, but simpler in that we allow refinement only with depth. The major difficulty arose in deriving the forward modeling operators on interfaces between adjacent sub-grids. We considered three ways of handling the interface layers and suggest a preferable one, which results in similar accuracy as the staggered grid solution, while retaining the symmetry of coefficient matrix. A comparison between multi-resolution and staggered solvers for various models show that multi-resolution approach improves on computational efficiency without compromising the accuracy of the solution.

Small vulnerable sets determine large network cascades in power grids

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

Yang, Yang; Nishikawa, Takashi; Motter, Adilson E.

The understanding of cascading failures in complex systems has been hindered by the lack of realistic large-scale modeling and analysis that can account for variable system conditions. By using the North American power grid, we identified, quantified, and analyzed the set of network components that are vulnerable to cascading failures under any out of multiple conditions. We show that the vulnerable set consists of a small but topologically central portion of the network and that large cascades are disproportionately more likely to be triggered by initial failures close to this set. These results elucidate aspects of the origins and causesmore » of cascading failures relevant for grid design and operation and demonstrate vulnerability analysis methods that are applicable to a wider class of cascade-prone networks.« less

Small vulnerable sets determine large network cascades in power grids

DOE PAGES

Yang, Yang; Nishikawa, Takashi; Motter, Adilson E.

2017-11-17

The understanding of cascading failures in complex systems has been hindered by the lack of realistic large-scale modeling and analysis that can account for variable system conditions. By using the North American power grid, we identified, quantified, and analyzed the set of network components that are vulnerable to cascading failures under any out of multiple conditions. We show that the vulnerable set consists of a small but topologically central portion of the network and that large cascades are disproportionately more likely to be triggered by initial failures close to this set. These results elucidate aspects of the origins and causesmore » of cascading failures relevant for grid design and operation and demonstrate vulnerability analysis methods that are applicable to a wider class of cascade-prone networks.« less

How Do Microphysical Processes Influence Large-Scale Precipitation Variability and Extremes?

DOE PAGES

Hagos, Samson; Ruby Leung, L.; Zhao, Chun; ...

2018-02-10

Convection permitting simulations using the Model for Prediction Across Scales-Atmosphere (MPAS-A) are used to examine how microphysical processes affect large-scale precipitation variability and extremes. An episode of the Madden-Julian Oscillation is simulated using MPAS-A with a refined region at 4-km grid spacing over the Indian Ocean. It is shown that cloud microphysical processes regulate the precipitable water (PW) statistics. Because of the non-linear relationship between precipitation and PW, PW exceeding a certain critical value (PWcr) contributes disproportionately to precipitation variability. However, the frequency of PW exceeding PWcr decreases rapidly with PW, so changes in microphysical processes that shift the columnmore » PW statistics relative to PWcr even slightly have large impacts on precipitation variability. Furthermore, precipitation variance and extreme precipitation frequency are approximately linearly related to the difference between the mean and critical PW values. Thus observed precipitation statistics could be used to directly constrain model microphysical parameters as this study demonstrates using radar observations from DYNAMO field campaign.« less

How Do Microphysical Processes Influence Large-Scale Precipitation Variability and Extremes?

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

Hagos, Samson; Ruby Leung, L.; Zhao, Chun

Convection permitting simulations using the Model for Prediction Across Scales-Atmosphere (MPAS-A) are used to examine how microphysical processes affect large-scale precipitation variability and extremes. An episode of the Madden-Julian Oscillation is simulated using MPAS-A with a refined region at 4-km grid spacing over the Indian Ocean. It is shown that cloud microphysical processes regulate the precipitable water (PW) statistics. Because of the non-linear relationship between precipitation and PW, PW exceeding a certain critical value (PWcr) contributes disproportionately to precipitation variability. However, the frequency of PW exceeding PWcr decreases rapidly with PW, so changes in microphysical processes that shift the columnmore » PW statistics relative to PWcr even slightly have large impacts on precipitation variability. Furthermore, precipitation variance and extreme precipitation frequency are approximately linearly related to the difference between the mean and critical PW values. Thus observed precipitation statistics could be used to directly constrain model microphysical parameters as this study demonstrates using radar observations from DYNAMO field campaign.« less

Tectonics and Volcanism During the Cretaceous Normal Superchron Seafloor in the Western Pacific Ocean

NASA Astrophysics Data System (ADS)

O'Brien, E.

2017-12-01

We have conducted an integration study on the origin and evolution of the tectonics and volcanism of seafloor in the Western Pacific Ocean that took place during the Cretaceous Normal Superchron (CNS) where sparse data has so far precluded detailed investigation. We have compiled the latest satellite-based gravity, gravity gradient, and magnetic grids (EMAG2 v.3) for this region. These crustal-scale high-resolution grids suggest that the CNS seafloor contains fossilized lithospheric morphology possibly attributed to the interaction between Cretaceous supervolcanism activity and Mid-Cretaceous Pacific mid ocean ridge systems that have continuously expanded the Pacific Plate. We recognize previously identified fossilized microplates west of the Magellan Rise, short-lived abandoned propagating rifts and fracture zones, all of which show significant rotation of seafloor fabric. In addition to these large scale observations, we have also compiled marine geological information from previously drilled cores and new data from a Kongsberg Topas PS18 Parametric Sub-Bottom Profiler collected on a transect from Honolulu, Hawaii to Apra, Guam acquired during research cruise SKQ2014S2. In particular, the narrow beam and high bandwidth signal of the Topas PS18 sub-bottom profiler provides sonar data of the seabed with a resolution and depth penetration that is unprecedented compared with previously available surveys in the region. A preliminary assessment of this high resolution Topas data allows us to better characterize sub-seafloor sediment properties and identify features, including the Upper Transparent Layer with identifiable pelagic clay and porcelanite-chert reflectors as well as tectonic features such as the westernmost tip of the Waghenaer Fracture Zone.

Examinations of Linkages Between the Northwest Mexican Monsoon and Great Plains Precipitation

NASA Astrophysics Data System (ADS)

Saleeby, S. M.; Cotton, W. R.

2001-12-01

The Regional Atmospheric Modeling System (RAMS) is being used to examine linkages between the Mexican monsoon and precipitation in the Great Plains region of the United States. Currently, available datasets have allowed for seasonal runs for July and August of the 1993 flood year in the midwest US and the 1997 El Nino year. There is also a plan to perform a full monsoon season simulation of the drought summer of 1988 once precipitation data becomes available. Preliminary results of this ongoing study are presented here. The model configuration consists of a 120km resolution coarse grid that covers a region from west of Hawaii to Bermuda and from south of the equator up into Canada. Two 40km resolution nested grids exist, with one covering the western two-thirds of the United States and Mexico and the other covering the Pacific ITCZ. A 10km fine grid and 2.5km cloud resolving grid are spawned over the region of monsoon surges to explicitly resolve convection. The model is initialized with NCEP reanalysis data, surface obs, rawinsonde data, variable soil moisture, and weekly averaged SST's. RAMS is running with two-stream Harrington radiation, one moment microphysics, and Kuo cumulus parameterization. The completed 1993 and 1997 seasonal simulations are now being examined and verified again NCEP reanalysis data and high resolution precipitation data. Initial model results look promising when verified against the NCEP upper level fields, such that the model is able to capture the large scale dynamics. For the duration of both seasonal runs, RAMS successfully simulates the mid and upper level geopotential heights, the temperature, and winds. The large scale 700mb and 500mb anti-cyclone over the US and Mexico is resolved, as well as the easterly flow over Mexico. Model fields are also being examined to isolate monsoon surge events which are characterized by increased precipitation over the Sierra Madres and a northward moisture surge into the northern extent of the Gulf of California and southern Arizona. Within the coarse grids, the RAMS model has successfully resolved the low-level jet that persists in the Gulf of California and the local maximum in mixing ratio that persists over the gulf. It has also captured the upslope flow over the Sierra Madres that forces the moist air into the higher elevation to the east. This provides the necessary lifting and moisture for the development of intense convection and resulting large amounts of precipitation that occur along the Sierra Madre mountain range. Examination of model-predicted low-level moisture transport reveals that moisture advected from the Gulf of California is the primary monsoon moisture source, rather than the Gulf of Mexico. Time averages of moisture transport, mixing ratio, winds, and precipitation for July 1993 reveal the prominent diurnal cycle variations that exist due to radiative effects and land-sea interactions; the maximum in convection, precipitation rate, and moisture transport occurs around 00Z. Seasonal accumulated precipitation amounts in the model are successful in predicting the placement of precipitation and relative amounts for most of the 40km continental grid, but there is an overestimation of precipitation along the northern Sierra Madre Occidental and an underestimation in the US mid-west. During the 1993 flood summer, much of the mid-west US precipitation fell in association with mesoscale convective systems; it is suspected that other cumulus parameterizations may provide better prediction of sub-grid scale convective precipitation. >http://hugo.atmos.colostate.edu/www/monsoon/monsoon.html

Physics-based distributed snow models in the operational arena: Current and future challenges

NASA Astrophysics Data System (ADS)

Winstral, A. H.; Jonas, T.; Schirmer, M.; Helbig, N.

2017-12-01

The demand for modeling tools robust to climate change and weather extremes along with coincident increases in computational capabilities have led to an increase in the use of physics-based snow models in operational applications. Current operational applications include the WSL-SLF's across Switzerland, ASO's in California, and USDA-ARS's in Idaho. While the physics-based approaches offer many advantages there remain limitations and modeling challenges. The most evident limitation remains computation times that often limit forecasters to a single, deterministic model run. Other limitations however remain less conspicuous amidst the assumptions that these models require little to no calibration based on their foundation on physical principles. Yet all energy balance snow models seemingly contain parameterizations or simplifications of processes where validation data are scarce or present understanding is limited. At the research-basin scale where many of these models were developed these modeling elements may prove adequate. However when applied over large areas, spatially invariable parameterizations of snow albedo, roughness lengths and atmospheric exchange coefficients - all vital to determining the snowcover energy balance - become problematic. Moreover as we apply models over larger grid cells, the representation of sub-grid variability such as the snow-covered fraction adds to the challenges. Here, we will demonstrate some of the major sensitivities of distributed energy balance snow models to particular model constructs, the need for advanced and spatially flexible methods and parameterizations, and prompt the community for open dialogue and future collaborations to further modeling capabilities.

Challenges in Modeling of the Global Atmosphere

NASA Astrophysics Data System (ADS)

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

2015-04-01

The massively parallel computer architectures require that some widely adopted modeling paradigms be reconsidered in order to utilize more productively the power of parallel processing. For high computational efficiency with distributed memory, each core should work on a small subdomain of the full integration domain, and exchange only few rows of halo data with the neighbouring cores. However, the described scenario implies that the discretization used in the model is horizontally local. The spherical geometry further complicates the problem. Various grid topologies will be discussed and examples will be shown. The latitude-longitude grid with local in space and explicit in time differencing has been an early choice and remained in use ever since. The problem with this method is that the grid size in the longitudinal direction tends to zero as the poles are approached. So, in addition to having unnecessarily high resolution near the poles, polar filtering has to be applied in order to use a time step of decent size. However, the polar filtering requires transpositions involving extra communications. The spectral transform method and the semi-implicit semi-Lagrangian schemes opened the way for a wide application of the spectral representation. With some variations, these techniques are used in most major centers. However, the horizontal non-locality is inherent to the spectral representation and implicit time differencing, which inhibits scaling on a large number of cores. In this respect the lat-lon grid with a fast Fourier transform represents a significant step in the right direction, particularly at high resolutions where the Legendre transforms become increasingly expensive. Other grids with reduced variability of grid distances such as various versions of the cubed sphere and the hexagonal/pentagonal ("soccer ball") grids were proposed almost fifty years ago. However, on these grids, large-scale (wavenumber 4 and 5) fictitious solutions ("grid imprinting") with significant amplitudes can develop. Due to their large scales, that are comparable to the scales of the dominant Rossby waves, such fictitious solutions are hard to identify and remove. Another new challenge on the global scale is that the limit of validity of the hydrostatic approximation is rapidly being approached. Having in mind the sensitivity of extended deterministic forecasts to small disturbances, we may need global non-hydrostatic models sooner than we think. The unified Non-hydrostatic Multi-scale Model (NMMB) that is being developed at the National Centers for Environmental Prediction (NCEP) as a part of the new NOAA Environmental Modeling System (NEMS) will be discussed as an example. The non-hydrostatic dynamics were designed in such a way as to avoid over-specification. The global version is run on the latitude-longitude grid, and the polar filter selectively slows down the waves that would otherwise be unstable. The model formulation has been successfully tested on various scales. A global forecasting system based on the NMMB has been run in order to test and tune the model. The skill of the medium range forecasts produced by the NMMB is comparable to that of other major medium range models. The computational efficiency of the global NMMB on parallel computers is good.

The Impact of Varying the Physics Grid Resolution Relative to the Dynamical Core Resolution in CAM-SE-CSLAM

NASA Astrophysics Data System (ADS)

Herrington, A. R.; Lauritzen, P. H.; Reed, K. A.

2017-12-01

The spectral element dynamical core of the Community Atmosphere Model (CAM) has recently been coupled to an approximately isotropic, finite-volume grid per implementation of the conservative semi-Lagrangian multi-tracer transport scheme (CAM-SE-CSLAM; Lauritzen et al. 2017). In this framework, the semi-Lagrangian transport of tracers are computed on the finite-volume grid, while the adiabatic dynamics are solved using the spectral element grid. The physical parameterizations are evaluated on the finite-volume grid, as opposed to the unevenly spaced Gauss-Lobatto-Legendre nodes of the spectral element grid. Computing the physics on the finite-volume grid reduces numerical artifacts such as grid imprinting, possibly because the forcing terms are no longer computed at element boundaries where the resolved dynamics are least smooth. The separation of the physics grid and the dynamics grid allows for a unique opportunity to understand the resolution sensitivity in CAM-SE-CSLAM. The observed large sensitivity of CAM to horizontal resolution is a poorly understood impediment to improved simulations of regional climate using global, variable resolution grids. Here, a series of idealized moist simulations are presented in which the finite-volume grid resolution is varied relative to the spectral element grid resolution in CAM-SE-CSLAM. The simulations are carried out at multiple spectral element grid resolutions, in part to provide a companion set of simulations, in which the spectral element grid resolution is varied relative to the finite-volume grid resolution, but more generally to understand if the sensitivity to the finite-volume grid resolution is consistent across a wider spectrum of resolved scales. Results are interpreted in the context of prior ideas regarding resolution sensitivity of global atmospheric models.

Self-modulating pressure gauge

DOEpatents

Edwards, D. Jr.; Lanni, C.P.

1979-08-07

An ion gauge is disclosed having a reduced x-ray limit and means for measuring that limit. The gauge comprises an ion gauge of the Bayard-Alpert type having a short collector and having means for varying the grid-collector voltage. The x-ray limit (i.e. the collector current resulting from x-rays striking the collector) may then be determined by the formula: I/sub x/ = ..cap alpha..I/sub l/ - I/sub h//..cap alpha.. - l where: I/sub x/ = x-ray limit, I/sub l/ and I/sub h/ = the collector current at the lower and higher grid voltage respectively; and, ..cap alpha.. = the ratio of the collector current due to positive ions at the higher voltage to that at the lower voltage.

Interaction Between the Atmospheric Boundary Layer and Wind Energy: From Continental-Scale to Turbine-Scale

NASA Astrophysics Data System (ADS)

St. Martin, Clara Mae

Wind turbines and groups of wind turbines, or "wind plants", interact with the complex and heterogeneous boundary layer of the atmosphere. We define the boundary layer as the portion of the atmosphere directly influenced by the surface, and this layer exhibits variability on a range of temporal and spatial scales. While early developments in wind energy could ignore some of this variability, recent work demonstrates that improved understanding of atmosphere-turbine interactions leads to the discovery of new ways to approach turbine technology development as well as processes such as performance validation and turbine operations. This interaction with the atmosphere occurs at several spatial and temporal scales from continental-scale to turbine-scale. Understanding atmospheric variability over continental-scales and across plants can facilitate reliance on wind energy as a baseload energy source on the electrical grid. On turbine scales, understanding the atmosphere's contribution to the variability in power production can improve the accuracy of power production estimates as we continue to implement more wind energy onto the grid. Wind speed and directional variability within a plant will affect wind turbine wakes within the plants and among neighboring plants, and a deeper knowledge of these variations can help mitigate effects of wakes and possibly even allow the manipulation of these wakes for increased production. Herein, I present the extent of my PhD work, in which I studied outstanding questions at these scales at the intersections of wind energy and atmospheric science. My work consists of four distinct projects. At the coarsest scales, I analyze the separation between wind plant sites needed for statistical independence in order to reduce variability for grid-integration of wind. At lower wind speeds, periods of unstable and more turbulent conditions produce more power than periods of stable and less turbulent conditions, while at wind speeds closer to rated wind speed, periods of unstable and more turbulent conditions produce less power than periods of stable and less turbulent conditions. Using these new, stability- and turbulence-specific power curves to calculate annual energy production (AEP) estimates results in smaller AEPs than if calculated using no stability and turbulence filters, which could have implications for manufacturers and operators. In my third project, I address the problem of expensive power production validation. Rather than erecting towers to provide upwind wind measurements, I explore the utility of using nacelle-mounted anemometers for power curve verification studies. I calculate empirical nacelle transfer functions (NTFs) with upwind tower and turbine measurements. The fifth-order and second-order NTFs show a linear relationship between upwind wind speed and nacelle wind speed at wind speeds less than about 9 m s-1 , but this relationship becomes non-linear at wind speeds higher than about 9 m s-1. The use of NTFs results in AEPs within 1 % of an AEP using upwind wind speeds. Additionally, during periods of unstable conditions as well as during more turbulent conditions, the nacelle-mounted anemometer underestimates the upwind wind speed more than during periods of stable conditions and less turbulence conditions at some wind speed bins below rated speed. Finally, in my fourth project, I consider spatial scales on the order of a wind plant. Using power production data from over 300 turbines from four neighboring wind farms in the western US along with simulations using the Weather Research and Forecasting model's Wind Farm Parameterization (WRF-WFP), I investigate the advantage of using the WFP to simulate wakes. During this case, winds from the west and north-northwest range from about 5 to 11 m s-1. A down-ramp occurs in this case study, which WRF predicts too early. The early prediction of the down-ramp likely affects the error in WRF-predicted power, the results of which show exaggerated wake effects. While these projects span a range of spatio-temporal scales, a unifying theme is the important aspect of atmospheric variation on wind power production, wind power production estimates, and means for facilitating the integration of wind-generated electricity into power grids. Future work, such as universal NTFs for sites with similar characteristics, NTFs for waked turbines, or the deployment of lidars on turbine nacelles for operation purposes, should continue to study the mutually-important interconnections between these two fields. (Abstract shortened by ProQuest.).

Multigrid one shot methods for optimal control problems: Infinite dimensional control

NASA Technical Reports Server (NTRS)

Arian, Eyal; Taasan, Shlomo

1994-01-01

The multigrid one shot method for optimal control problems, governed by elliptic systems, is introduced for the infinite dimensional control space. ln this case, the control variable is a function whose discrete representation involves_an increasing number of variables with grid refinement. The minimization algorithm uses Lagrange multipliers to calculate sensitivity gradients. A preconditioned gradient descent algorithm is accelerated by a set of coarse grids. It optimizes for different scales in the representation of the control variable on different discretization levels. An analysis which reduces the problem to the boundary is introduced. It is used to approximate the two level asymptotic convergence rate, to determine the amplitude of the minimization steps, and the choice of a high pass filter to be used when necessary. The effectiveness of the method is demonstrated on a series of test problems. The new method enables the solutions of optimal control problems at the same cost of solving the corresponding analysis problems just a few times.

Optimal control in microgrid using multi-agent reinforcement learning.

PubMed

Li, Fu-Dong; Wu, Min; He, Yong; Chen, Xin

2012-11-01

This paper presents an improved reinforcement learning method to minimize electricity costs on the premise of satisfying the power balance and generation limit of units in a microgrid with grid-connected mode. Firstly, the microgrid control requirements are analyzed and the objective function of optimal control for microgrid is proposed. Then, a state variable "Average Electricity Price Trend" which is used to express the most possible transitions of the system is developed so as to reduce the complexity and randomicity of the microgrid, and a multi-agent architecture including agents, state variables, action variables and reward function is formulated. Furthermore, dynamic hierarchical reinforcement learning, based on change rate of key state variable, is established to carry out optimal policy exploration. The analysis shows that the proposed method is beneficial to handle the problem of "curse of dimensionality" and speed up learning in the unknown large-scale world. Finally, the simulation results under JADE (Java Agent Development Framework) demonstrate the validity of the presented method in optimal control for a microgrid with grid-connected mode. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Identification of reliable gridded reference data for statistical downscaling methods in Alberta

NASA Astrophysics Data System (ADS)

Eum, H. I.; Gupta, A.

2017-12-01

Climate models provide essential information to assess impacts of climate change at regional and global scales. However, statistical downscaling methods have been applied to prepare climate model data for various applications such as hydrologic and ecologic modelling at a watershed scale. As the reliability and (spatial and temporal) resolution of statistically downscaled climate data mainly depend on a reference data, identifying the most reliable reference data is crucial for statistical downscaling. A growing number of gridded climate products are available for key climate variables which are main input data to regional modelling systems. However, inconsistencies in these climate products, for example, different combinations of climate variables, varying data domains and data lengths and data accuracy varying with physiographic characteristics of the landscape, have caused significant challenges in selecting the most suitable reference climate data for various environmental studies and modelling. Employing various observation-based daily gridded climate products available in public domain, i.e. thin plate spline regression products (ANUSPLIN and TPS), inverse distance method (Alberta Townships), and numerical climate model (North American Regional Reanalysis) and an optimum interpolation technique (Canadian Precipitation Analysis), this study evaluates the accuracy of the climate products at each grid point by comparing with the Adjusted and Homogenized Canadian Climate Data (AHCCD) observations for precipitation, minimum and maximum temperature over the province of Alberta. Based on the performance of climate products at AHCCD stations, we ranked the reliability of these publically available climate products corresponding to the elevations of stations discretized into several classes. According to the rank of climate products for each elevation class, we identified the most reliable climate products based on the elevation of target points. A web-based system was developed to allow users to easily select the most reliable reference climate data at each target point based on the elevation of grid cell. By constructing the best combination of reference data for the study domain, the accurate and reliable statistically downscaled climate projections could be significantly improved.

The power of structural modeling of sub-grid scales - application to astrophysical plasmas

NASA Astrophysics Data System (ADS)

Georgiev Vlaykov, Dimitar; Grete, Philipp

2015-08-01

In numerous astrophysical phenomena the dynamical range can span 10s of orders of magnitude. This implies more than billions of degrees-of-freedom and precludes direct numerical simulations from ever being a realistic possibility. A physical model is necessary to capture the unresolved physics occurring at the sub-grid scales (SGS).Structural modeling is a powerful concept which renders itself applicable to various physical systems. It stems from the idea of capturing the structure of the SGS terms in the evolution equations based on the scale-separation mechanism and independently of the underlying physics. It originates in the hydrodynamics field of large-eddy simulations. We apply it to the study of astrophysical MHD.Here, we present a non-linear SGS model for compressible MHD turbulence. The model is validated a priori at the tensorial, vectorial and scalar levels against of set of high-resolution simulations of stochastically forced homogeneous isotropic turbulence in a periodic box. The parameter space spans 2 decades in sonic Mach numbers (0.2 - 20) and approximately one decade in magnetic Mach number ~(1-8). This covers the super-Alfvenic sub-, trans-, and hyper-sonic regimes, with a range of plasma beta from 0.05 to 25. The Reynolds number is of the order of 103.At the tensor level, the model components correlate well with the turbulence ones, at the level of 0.8 and above. Vectorially, the alignment with the true SGS terms is encouraging with more than 50% of the model within 30° of the data. At the scalar level we look at the dynamics of the SGS energy and cross-helicity. The corresponding SGS flux terms have median correlations of ~0.8. Physically, the model represents well the two directions of the energy cascade.In comparison, traditional functional models exhibit poor local correlations with the data already at the scalar level. Vectorially, they are indifferent to the anisotropy of the SGS terms. They often struggle to represent the energy backscatter from small to large scales as well as the turbulent dynamo mechanism.Overall, the new model surpasses the traditional ones in all tests by a large margin.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Integrating Variable Renewable Energy into the Grid: Key Issues, Greening the Grid (Spanish Version)

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

This is the Spanish version of 'Greening the Grid - Integrating Variable Renewable Energy into the Grid: Key Issues'. To foster sustainable, low-emission development, many countries are establishing ambitious renewable energy targets for their electricity supply. Because solar and wind tend to be more variable and uncertain than conventional sources, meeting these targets will involve changes to power system planning and operations. Grid integration is the practice of developing efficient ways to deliver variable renewable energy (VRE) to the grid. Good integration methods maximize the cost-effectiveness of incorporating VRE into the power system while maintaining or increasing system stability andmore » reliability. When considering grid integration, policy makers, regulators, and system operators consider a variety of issues, which can be organized into four broad topics: New Renewable Energy Generation, New Transmission, Increased System Flexibility, and Planning for a High RE Future.« less

Near-surface wind variability over the broader Adriatic region: insights from an ensemble of regional climate models

NASA Astrophysics Data System (ADS)

Belušić, Andreina; Prtenjak, Maja Telišman; Güttler, Ivan; Ban, Nikolina; Leutwyler, David; Schär, Christoph

2018-06-01

Over the past few decades the horizontal resolution of regional climate models (RCMs) has steadily increased, leading to a better representation of small-scale topographic features and more details in simulating dynamical aspects, especially in coastal regions and over complex terrain. Due to its complex terrain, the broader Adriatic region represents a major challenge to state-of-the-art RCMs in simulating local wind systems realistically. The objective of this study is to identify the added value in near-surface wind due to the refined grid spacing of RCMs. For this purpose, we use a multi-model ensemble composed of CORDEX regional climate simulations at 0.11° and 0.44° grid spacing, forced by the ERA-Interim reanalysis, a COSMO convection-parameterizing simulation at 0.11° and a COSMO convection-resolving simulation at 0.02° grid spacing. Surface station observations from this region and satellite QuikSCAT data over the Adriatic Sea have been compared against daily output obtained from the available simulations. Both day-to-day wind and its frequency distribution are examined. The results indicate that the 0.44° RCMs rarely outperform ERA-Interim reanalysis, while the performance of the high-resolution simulations surpasses that of ERA-Interim. We also disclose that refining the grid spacing to a few km is needed to properly capture the small-scale wind systems. Finally, we show that the simulations frequently yield the accurate angle of local wind regimes, such as for the Bora flow, but overestimate the associated wind magnitude. Finally, spectral analysis shows good agreement between measurements and simulations, indicating the correct temporal variability of the wind speed.

Comparison of Grid Nudging and Spectral Nudging Techniques for Dynamical Climate Downscaling within the WRF Model

NASA Astrophysics Data System (ADS)

Fan, X.; Chen, L.; Ma, Z.

2010-12-01

Climate downscaling has been an active research and application area in the past several decades focusing on regional climate studies. Dynamical downscaling, in addition to statistical methods, has been widely used in downscaling as the advanced modern numerical weather and regional climate models emerge. The utilization of numerical models enables that a full set of climate variables are generated in the process of downscaling, which are dynamically consistent due to the constraints of physical laws. While we are generating high resolution regional climate, the large scale climate patterns should be retained. To serve this purpose, nudging techniques, including grid analysis nudging and spectral nudging, have been used in different models. There are studies demonstrating the benefit and advantages of each nudging technique; however, the results are sensitive to many factors such as nudging coefficients and the amount of information to nudge to, and thus the conclusions are controversy. While in a companion work of developing approaches for quantitative assessment of the downscaled climate, in this study, the two nudging techniques are under extensive experiments in the Weather Research and Forecasting (WRF) model. Using the same model provides fair comparability. Applying the quantitative assessments provides objectiveness of comparison. Three types of downscaling experiments were performed for one month of choice. The first type is serving as a base whereas the large scale information is communicated through lateral boundary conditions only; the second is using the grid analysis nudging; and the third is using spectral nudging. Emphases are given to the experiments of different nudging coefficients and nudging to different variables in the grid analysis nudging; while in spectral nudging, we focus on testing the nudging coefficients, different wave numbers on different model levels to nudge.

Multi-scale streamflow variability responses to precipitation over the headwater catchments in southern China

NASA Astrophysics Data System (ADS)

Niu, Jun; Chen, Ji; Wang, Keyi; Sivakumar, Bellie

2017-08-01

This paper examines the multi-scale streamflow variability responses to precipitation over 16 headwater catchments in the Pearl River basin, South China. The long-term daily streamflow data (1952-2000), obtained using a macro-scale hydrological model, the Variable Infiltration Capacity (VIC) model, and a routing scheme, are studied. Temporal features of streamflow variability at 10 different timescales, ranging from 6 days to 8.4 years, are revealed with the Haar wavelet transform. The principal component analysis (PCA) is performed to categorize the headwater catchments with the coherent modes of multi-scale wavelet spectra. The results indicate that three distinct modes, with different variability distributions at small timescales and seasonal scales, can explain 95% of the streamflow variability. A large majority of the catchments (i.e. 12 out of 16) exhibit consistent mode feature on multi-scale variability throughout three sub-periods (1952-1968, 1969-1984, and 1985-2000). The multi-scale streamflow variability responses to precipitation are identified to be associated with the regional flood and drought tendency over the headwater catchments in southern China.

Bayesian Non-Stationary Index Gauge Modeling of Gridded Precipitation Extremes

NASA Astrophysics Data System (ADS)

Verdin, A.; Bracken, C.; Caldwell, J.; Balaji, R.; Funk, C. C.

2017-12-01

We propose a Bayesian non-stationary model to generate watershed scale gridded estimates of extreme precipitation return levels. The Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset is used to obtain gridded seasonal precipitation extremes over the Taylor Park watershed in Colorado for the period 1981-2016. For each year, grid cells within the Taylor Park watershed are aggregated to a representative "index gauge," which is input to the model. Precipitation-frequency curves for the index gauge are estimated for each year, using climate variables with significant teleconnections as proxies. Such proxies enable short-term forecasting of extremes for the upcoming season. Disaggregation ratios of the index gauge to the grid cells within the watershed are computed for each year and preserved to translate the index gauge precipitation-frequency curve to gridded precipitation-frequency maps for select return periods. Gridded precipitation-frequency maps are of the same spatial resolution as CHIRPS (0.05° x 0.05°). We verify that the disaggregation method preserves spatial coherency of extremes in the Taylor Park watershed. Validation of the index gauge extreme precipitation-frequency method consists of ensuring extreme value statistics are preserved on a grid cell basis. To this end, a non-stationary extreme precipitation-frequency analysis is performed on each grid cell individually, and the resulting frequency curves are compared to those produced by the index gauge disaggregation method.

Maintaining Balance: The Increasing Role of Energy Storage for Renewable Integration

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

Stenclik, Derek; Denholm, Paul; Chalamala, Babu

For nearly a century, global power systems have focused on three key functions: generating, transmitting, and distributing electricity as a real-time commodity. Physics requires that electricity generation always be in real-time balance with load-despite variability in load on time scales ranging from subsecond disturbances to multiyear trends. With the increasing role of variable generation from wind and solar, the retirement of fossil-fuel-based generation, and a changing consumer demand profile, grid operators are using new methods to maintain this balance.

Surface Wind and Upper-Ocean Variability Associated with the Madden-Julian Oscillation Simulated by the Coupled Ocean-Atmosphere Mesoscale Prediction System

DTIC Science & Technology

2013-07-01

observed data at one location include variability caused by small -scale atmospheric convec- tion and wind variations that cannot be resolved by the... data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this...high-resolution nested grid (9 km) for the atmospheric component is used for the central Indian Ocean. While observational data are assimilated into the

Contrasting responses of water use efficiency to drought across global terrestrial ecosystems

PubMed Central

Yang, Yuting; Guan, Huade; Batelaan, Okke; McVicar, Tim R.; Long, Di; Piao, Shilong; Liang, Wei; Liu, Bing; Jin, Zhao; Simmons, Craig T.

2016-01-01

Drought is an intermittent disturbance of the water cycle that profoundly affects the terrestrial carbon cycle. However, the response of the coupled water and carbon cycles to drought and the underlying mechanisms remain unclear. Here we provide the first global synthesis of the drought effect on ecosystem water use efficiency (WUE = gross primary production (GPP)/evapotranspiration (ET)). Using two observational WUE datasets (i.e., eddy-covariance measurements at 95 sites (526 site-years) and global gridded diagnostic modelling based on existing observation and a data-adaptive machine learning approach), we find a contrasting response of WUE to drought between arid (WUE increases with drought) and semi-arid/sub-humid ecosystems (WUE decreases with drought), which is attributed to different sensitivities of ecosystem processes to changes in hydro-climatic conditions. WUE variability in arid ecosystems is primarily controlled by physical processes (i.e., evaporation), whereas WUE variability in semi-arid/sub-humid regions is mostly regulated by biological processes (i.e., assimilation). We also find that shifts in hydro-climatic conditions over years would intensify the drought effect on WUE. Our findings suggest that future drought events, when coupled with an increase in climate variability, will bring further threats to semi-arid/sub-humid ecosystems and potentially result in biome reorganization, starting with low-productivity and high water-sensitivity grassland. PMID:26983909

SoilGrids1km — Global Soil Information Based on Automated Mapping

PubMed Central

Hengl, Tomislav; de Jesus, Jorge Mendes; MacMillan, Robert A.; Batjes, Niels H.; Heuvelink, Gerard B. M.; Ribeiro, Eloi; Samuel-Rosa, Alessandro; Kempen, Bas; Leenaars, Johan G. B.; Walsh, Markus G.; Gonzalez, Maria Ruiperez

2014-01-01

Background Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As such, there is a growing requirement for global soil information. Although several global soil information systems already exist, these tend to suffer from inconsistencies and limited spatial detail. Methodology/Principal Findings We present SoilGrids1km — a global 3D soil information system at 1 km resolution — containing spatial predictions for a selection of soil properties (at six standard depths): soil organic carbon (g kg−1), soil pH, sand, silt and clay fractions (%), bulk density (kg m−3), cation-exchange capacity (cmol+/kg), coarse fragments (%), soil organic carbon stock (t ha−1), depth to bedrock (cm), World Reference Base soil groups, and USDA Soil Taxonomy suborders. Our predictions are based on global spatial prediction models which we fitted, per soil variable, using a compilation of major international soil profile databases (ca. 110,000 soil profiles), and a selection of ca. 75 global environmental covariates representing soil forming factors. Results of regression modeling indicate that the most useful covariates for modeling soils at the global scale are climatic and biomass indices (based on MODIS images), lithology, and taxonomic mapping units derived from conventional soil survey (Harmonized World Soil Database). Prediction accuracies assessed using 5–fold cross-validation were between 23–51%. Conclusions/Significance SoilGrids1km provide an initial set of examples of soil spatial data for input into global models at a resolution and consistency not previously available. Some of the main limitations of the current version of SoilGrids1km are: (1) weak relationships between soil properties/classes and explanatory variables due to scale mismatches, (2) difficulty to obtain covariates that capture soil forming factors, (3) low sampling density and spatial clustering of soil profile locations. However, as the SoilGrids system is highly automated and flexible, increasingly accurate predictions can be generated as new input data become available. SoilGrids1km are available for download via http://soilgrids.org under a Creative Commons Non Commercial license. PMID:25171179

On the role of snow cover ablation variability and synoptic-scale atmospheric forcings at the sub-basin scale within the Great Lakes watershed

NASA Astrophysics Data System (ADS)

Suriano, Zachary J.

2018-02-01

Synoptic-scale atmospheric conditions play a critical role in determining the frequency and intensity of snow cover ablation in the mid-latitudes. Using a synoptic classification technique, distinct regional circulation patterns influencing the Great Lakes basin of North America are identified and examined in conjunction with daily snow ablation events from 1960 to 2009. This approach allows for the influence of each synoptic weather type on ablation to be examined independently and for the monthly and inter-annual frequencies of the weather types to be tracked over time. Because of the spatial heterogeneity of snow cover and the relatively large geographic extent of the Great Lakes basin, snow cover ablation events and the synoptic-scale patterns that cause them are examined for each of the Great Lakes watershed's five primary sub-basins to understand the regional complexities of snow cover ablation variability. Results indicate that while many synoptic weather patterns lead to ablation across the basins, they can be generally grouped into one of only a few primary patterns: southerly flow, high-pressure overhead, and rain-on-snow patterns. As expected, the patterns leading to ablation are not necessarily consistent between the five sub-basins due to the seasonality of snow cover and the spatial variability of temperature, moisture, wind, and incoming solar radiation associated with the particular synoptic weather types. Significant trends in the inter-annual frequency of ablation-inducing synoptic types do exist for some sub-basins, indicating a potential change in the hydrologic impact of these patterns over time.

Impacts of uncertainties in European gridded precipitation observations on regional climate analysis

PubMed Central

Gobiet, Andreas

2016-01-01

ABSTRACT Gridded precipitation data sets are frequently used to evaluate climate models or to remove model output biases. Although precipitation data are error prone due to the high spatio‐temporal variability of precipitation and due to considerable measurement errors, relatively few attempts have been made to account for observational uncertainty in model evaluation or in bias correction studies. In this study, we compare three types of European daily data sets featuring two Pan‐European data sets and a set that combines eight very high‐resolution station‐based regional data sets. Furthermore, we investigate seven widely used, larger scale global data sets. Our results demonstrate that the differences between these data sets have the same magnitude as precipitation errors found in regional climate models. Therefore, including observational uncertainties is essential for climate studies, climate model evaluation, and statistical post‐processing. Following our results, we suggest the following guidelines for regional precipitation assessments. (1) Include multiple observational data sets from different sources (e.g. station, satellite, reanalysis based) to estimate observational uncertainties. (2) Use data sets with high station densities to minimize the effect of precipitation undersampling (may induce about 60% error in data sparse regions). The information content of a gridded data set is mainly related to its underlying station density and not to its grid spacing. (3) Consider undercatch errors of up to 80% in high latitudes and mountainous regions. (4) Analyses of small‐scale features and extremes are especially uncertain in gridded data sets. For higher confidence, use climate‐mean and larger scale statistics. In conclusion, neglecting observational uncertainties potentially misguides climate model development and can severely affect the results of climate change impact assessments. PMID:28111497

Impacts of uncertainties in European gridded precipitation observations on regional climate analysis.

PubMed

Prein, Andreas F; Gobiet, Andreas

2017-01-01

Gridded precipitation data sets are frequently used to evaluate climate models or to remove model output biases. Although precipitation data are error prone due to the high spatio-temporal variability of precipitation and due to considerable measurement errors, relatively few attempts have been made to account for observational uncertainty in model evaluation or in bias correction studies. In this study, we compare three types of European daily data sets featuring two Pan-European data sets and a set that combines eight very high-resolution station-based regional data sets. Furthermore, we investigate seven widely used, larger scale global data sets. Our results demonstrate that the differences between these data sets have the same magnitude as precipitation errors found in regional climate models. Therefore, including observational uncertainties is essential for climate studies, climate model evaluation, and statistical post-processing. Following our results, we suggest the following guidelines for regional precipitation assessments. (1) Include multiple observational data sets from different sources (e.g. station, satellite, reanalysis based) to estimate observational uncertainties. (2) Use data sets with high station densities to minimize the effect of precipitation undersampling (may induce about 60% error in data sparse regions). The information content of a gridded data set is mainly related to its underlying station density and not to its grid spacing. (3) Consider undercatch errors of up to 80% in high latitudes and mountainous regions. (4) Analyses of small-scale features and extremes are especially uncertain in gridded data sets. For higher confidence, use climate-mean and larger scale statistics. In conclusion, neglecting observational uncertainties potentially misguides climate model development and can severely affect the results of climate change impact assessments.

The development of a sub-daily gridded rainfall product to improve hydrological predictions in Great Britain

NASA Astrophysics Data System (ADS)

Quinn, Niall; Freer, Jim; Coxon, Gemma; O'Loughlin, Fiachra; Woods, Ross; Liguori, Sara

2015-04-01

In Great Britain and many other regions of the world, flooding resulting from short duration, high intensity rainfall events can lead to significant economic losses and fatalities. At present, such extreme events are often poorly evaluated using hydrological models due, in part, to their rarity and relatively short duration and a lack of appropriate data. Such storm characteristics are not well represented by daily rainfall records currently available using volumetric gauges and/or derived gridded products. This research aims to address this important data gap by developing a sub-daily gridded precipitation product for Great Britain. Our focus is to better understand these storm events and some of the challenges and uncertainties in quantifying such data across catchment scales. Our goal is to both improve such rainfall characterisation and derive an input to drive hydrological model simulations. Our methodology involves the collation, error checking, and spatial interpolation of approximately 2000 rain gauges located across Great Britain, provided by the Scottish Environment Protection Agency (SEPA) and the Environment Agency (EA). Error checking was conducted over the entirety of the TBR data available, utilising a two stage approach. First, rain gauge data at each site were examined independently, with data exceeding reasonable thresholds marked as suspect. Second, potentially erroneous data were marked using a neighbourhood analysis approach whereby measurements at a given gauge were deemed suspect if they did not fall within defined bounds of measurements at neighbouring gauges. A total of eight error checks were conducted. To provide the user with the greatest flexibility possible, the error markers associated with each check have been recorded at every site. This approach aims to enable the user to choose which checks they deem most suitable for a particular application. The quality assured TBR dataset was then spatially interpolated to produce a national scale gridded rainfall product. Finally, radar rainfall data provided by the UK Met Office was assimilated, where available, to provide an optimal hourly estimate of rainfall, given the error variance associated with both datasets. This research introduces a sub-daily rainfall product that will be of particular value to hydrological modellers requiring rainfall inputs at higher temporal resolutions than those currently available nationally. Further research will aim to quantify the uncertainties in the rainfall product in order to improve our ability to diagnose and identify structural errors in hydrological modelling of extreme events. Here we present our initial findings.

Development of fine-resolution analyses and expanded large-scale forcing properties. Part II: Scale-awareness and application to single-column model experiments

DOE PAGES

Feng, Sha; Vogelmann, Andrew M.; Li, Zhijin; ...

2015-01-20

Fine-resolution three-dimensional fields have been produced using the Community Gridpoint Statistical Interpolation (GSI) data assimilation system for the U.S. Department of Energy’s Atmospheric Radiation Measurement Program (ARM) Southern Great Plains region. The GSI system is implemented in a multi-scale data assimilation framework using the Weather Research and Forecasting model at a cloud-resolving resolution of 2 km. From the fine-resolution three-dimensional fields, large-scale forcing is derived explicitly at grid-scale resolution; a subgrid-scale dynamic component is derived separately, representing subgrid-scale horizontal dynamic processes. Analyses show that the subgrid-scale dynamic component is often a major component over the large-scale forcing for grid scalesmore » larger than 200 km. The single-column model (SCM) of the Community Atmospheric Model version 5 (CAM5) is used to examine the impact of the grid-scale and subgrid-scale dynamic components on simulated precipitation and cloud fields associated with a mesoscale convective system. It is found that grid-scale size impacts simulated precipitation, resulting in an overestimation for grid scales of about 200 km but an underestimation for smaller grids. The subgrid-scale dynamic component has an appreciable impact on the simulations, suggesting that grid-scale and subgrid-scale dynamic components should be considered in the interpretation of SCM simulations.« less

Autonomous Energy Grids: Preprint

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

Kroposki, Benjamin D; Dall-Anese, Emiliano; Bernstein, Andrey

With much higher levels of distributed energy resources - variable generation, energy storage, and controllable loads just to mention a few - being deployed into power systems, the data deluge from pervasive metering of energy grids, and the shaping of multi-level ancillary-service markets, current frameworks to monitoring, controlling, and optimizing large-scale energy systems are becoming increasingly inadequate. This position paper outlines the concept of 'Autonomous Energy Grids' (AEGs) - systems that are supported by a scalable, reconfigurable, and self-organizing information and control infrastructure, can be extremely secure and resilient (self-healing), and self-optimize themselves in real-time for economic and reliable performancemore » while systematically integrating energy in all forms. AEGs rely on scalable, self-configuring cellular building blocks that ensure that each 'cell' can self-optimize when isolated from a larger grid as well as partaking in the optimal operation of a larger grid when interconnected. To realize this vision, this paper describes the concepts and key research directions in the broad domains of optimization theory, control theory, big-data analytics, and complex system modeling that will be necessary to realize the AEG vision.« less

Driving factors of a vegetation shift from Scots pine to pubescent oak in dry Alpine forests.

PubMed

Rigling, Andreas; Bigler, Christof; Eilmann, Britta; Feldmeyer-Christe, Elisabeth; Gimmi, Urs; Ginzler, Christian; Graf, Ulrich; Mayer, Philipp; Vacchiano, Giorgio; Weber, Pascale; Wohlgemuth, Thomas; Zweifel, Roman; Dobbertin, Matthias

2013-01-01

An increasing number of studies have reported on forest declines and vegetation shifts triggered by drought. In the Swiss Rhone valley (Valais), one of the driest inner-Alpine regions, the species composition in low elevation forests is changing: The sub-boreal Scots pine (Pinus sylvestris L.) dominating the dry forests is showing high mortality rates. Concurrently the sub-Mediterranean pubescent oak (Quercus pubescens Willd.) has locally increased in abundance. However, it remains unclear whether this local change in species composition is part of a larger-scale vegetation shift. To study variability in mortality and regeneration in these dry forests we analysed data from the Swiss national forest inventory (NFI) on a regular grid between 1983 and 2003, and combined it with annual mortality data from a monitoring site. Pine mortality was found to be highest at low elevation (below 1000 m a.s.l.). Annual variation in pine mortality was correlated with a drought index computed for the summer months prior to observed tree death. A generalized linear mixed-effects model indicated for the NFI data increased pine mortality on dryer sites with high stand competition, particularly for small-diameter trees. Pine regeneration was low in comparison to its occurrence in the overstorey, whereas oak regeneration was comparably abundant. Although both species regenerated well at dry sites, pine regeneration was favoured at cooler sites at higher altitude and oak regeneration was more frequent at warmer sites, indicating a higher adaptation potential of oaks under future warming. Our results thus suggest that an extended shift in species composition is actually occurring in the pine forests in the Valais. The main driving factors are found to be climatic variability, particularly drought, and variability in stand structure and topography. Thus, pine forests at low elevations are developing into oak forests with unknown consequences for these ecosystems and their goods and services. © 2012 Blackwell Publishing Ltd.

Modeling Street-Level Inundation in Galveston, Texas City, and Houston during 2008 Hurricane Ike: Now and Implications for the Future

NASA Astrophysics Data System (ADS)

Loftis, D.

2016-02-01

In the wake of Hurricane Katrina (2005), Hurricane Ike (2008) is the second most devastating tropical cyclone to make landfall in the Gulf of Mexico in recent history. The path of the eye of Hurricane Ike passing directly over the Galveston's City Center requires the finesse of a street-level hydrodynamic model to accurately resolve the spatial inundation extent observed during the storm. A version of the Holland wind model was coupled with a sub-grid hydrodynamic model to address the complexity of spatially-varying hurricane force winds on the irregular movement of fluid though the streets of the coastal cities adjacent to the Galveston Bay. Sub-grid modeling technology is useful for incorporating high-resolution lidar-derived elevation measurements into the conventional hydrodynamic modeling framework to resolve detailed topographic features for inclusion in a hydrological transport model for storm surge simulations. Buildings were mosaicked into a lidar-derived Digital Surface Model at 5m spatial resolution for the study area, and in turn, embedded within a sub-grid layer of the hydrodynamic model mesh in a cross-scale approach to address the movement of Ike's storm surge from the Gulf of Mexico through the Galveston Bay, up estuaries and onto land. Model predictions for timing and depth of flooding during Hurricane Ike were compared with 8 verified water level gauges throughout the study area to evaluate the effectiveness of the sub-grid model's partial wetting and drying scheme. Statistical comparison yielded a mean R2 of 0.914, a relative error of 4.19%, and a root-mean-squared error of 19.47cm. A rigorous point-to-point comparison between street-level model results and 217 high water mark observations collected by the USGS and FEMA at several sites after the storm revealed that the model predicted the depth of inundation comparably well with an aggregate root-mean-squared error 0.283m. Finally, sea-level rise scenarios using Hurricane Ike as a base case revealed future storm-induced inundation could extend 0.6-2.8 km inland corresponding to increases in mean sea level of 37.5-150 cm based upon IPCC climate change prediction scenarios specified in their 5th assessment report in 2013.

Untangling the contribution of aspect, drainage position and elevation to the spatial variability of fine surface fuels in south east Australian forests

NASA Astrophysics Data System (ADS)

Sheridan, Gary; nyman, petter; Duff, Tom; Baillie, Craig; Bovill, William; Lane, Patrick; Tolhurst, Kevin

2015-04-01

The prediction of fuel moisture content is important for estimating the rate of spread of wildfires, the ignition probability of firebrands, and for the efficient scheduling of prescribed fire. The moisture content of fine surface fuels varies spatially at large scales (10's to 100's km) due to variation in meteorological variables (eg. temperature, relative humidity, precipitation). At smaller scales (100's of metres) in steep topography spatial variability is attributed to topographic influences that include differences in radiation due to aspect and slope, differences in precipitation, temperature and relative humidity due to elevation, and differences in soil moisture due to hillslope drainage position. Variable forest structure and canopy shading adds further to the spatial variability in surface fuel moisture. In this study we aim to combine daily 5km resolution gridded weather data with 20m resolution DEM and vegetation structure data to predict the spatial variability of fine surface fuels in steep topography. Microclimate stations were established in south east Australia to monitor surface fine fuel moisture continuously (every 15 minutes) using newly developed instrumented litter packs, in addition to temperature and relative humidity measurements inside the litter pack, and measurement of precipitation and energy inputs above and below the forest canopy. Microclimate stations were established across a gradient of aspect (5 stations), drainage position (7 stations), elevation (15 stations), and canopy cover conditions (6 stations). The data from this extensive network of microclimate stations across a broad spectrum of topographic conditions is being analysed to enable the downscaling of gridded weather data to spatial scales that are relevant to the connectivity of wildfire fuels and to the scheduling and outcome of prescribed fires. The initial results from the first year of this study are presented here.

A study of the variable impedance surface concept as a means for reducing noise from jet interaction with deployed lift-augmenting flaps

NASA Technical Reports Server (NTRS)

Hayden, R. E.; Kadman, Y.; Chanaud, R. C.

1972-01-01

The feasibility of quieting the externally-blown-flap (EBF) noise sources which are due to interaction of jet exhaust flow with deployed flaps was demonstrated on a 1/15-scale 3-flap EBF model. Sound field characteristics were measured and noise reduction fundamentals were reviewed in terms of source models. Test of the 1/15-scale model showed broadband noise reductions of up to 20 dB resulting from combination of variable impedance flap treatment and mesh grids placed in the jet flow upstream of the flaps. Steady-state lift, drag, and pitching moment were measured with and without noise reduction treatment.

MULTIWAVELENGTH OBSERVATIONS OF 3C 454.3. III. EIGHTEEN MONTHS OF AGILE MONITORING OF THE 'CRAZY DIAMOND'

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

Vercellone, S.; Romano, P.; D'Ammando, F.

2010-03-20

We report on 18 months of multiwavelength observations of the blazar 3C 454.3 (Crazy Diamond) carried out in the period 2007 July-2009 January. In particular, we show the results of the AGILE campaigns which took place on 2008 May-June, 2008 July-August, and 2008 October-2009 January. During the 2008 May-2009 January period, the source average flux was highly variable, with a clear fading trend toward the end of the period, from an average gamma-ray flux F{sub E>100{sub MeV}} {approx}> 200 x 10{sup -8} photons cm{sup -2} s{sup -1} in 2008 May-June, to F{sub E>100{sub MeV}} {approx} 80 x 10{sup -8} photonsmore » cm{sup -2} s{sup -1} in 2008 October-2009 January. The average gamma-ray spectrum between 100 MeV and 1 GeV can be fit by a simple power law, showing a moderate softening (from GAMMA{sub GRID} {approx} 2.0 to GAMMA{sub GRID} {approx} 2.2) toward the end of the observing campaign. Only 3sigma upper limits can be derived in the 20-60 keV energy band with Super-AGILE, because the source was considerably off-axis during the whole time period. In 2007 July-August and 2008 May-June, 3C 454.3 was monitored by Rossi X-ray Timing Explorer (RXTE). The RXTE/Proportional Counter Array (PCA) light curve in the 3-20 keV energy band shows variability correlated with the gamma-ray one. The RXTE/PCA average flux during the two time periods is F{sub 3-20{sub keV}} = 8.4 x 10{sup -11} erg cm{sup -2} s{sup -1}, and F{sub 3-20{sub keV}} = 4.5 x 10{sup -11} erg cm{sup -2} s{sup -1}, respectively, while the spectrum (a power law with photon index GAMMA{sub PCA} = 1.65 +- 0.02) does not show any significant variability. Consistent results are obtained with the analysis of the RXTE/High-Energy X-Ray Timing Experiment quasi-simultaneous data. We also carried out simultaneous Swift observations during all AGILE campaigns. Swift/XRT detected 3C 454.3 with an observed flux in the 2-10 keV energy band in the range (0.9-7.5) x 10{sup -11} erg cm{sup -2} s{sup -1} and a photon index in the range GAMMA{sub XRT} = 1.33-2.04. In the 15-150 keV energy band, when detected, the source has an average flux of about 5 mCrab. GASP-WEBT monitored 3C 454.3 during the whole 2007-2008 period in the radio, millimeter, near-IR, and optical bands. The observations show an extremely variable behavior at all frequencies, with flux peaks almost simultaneous with those at higher energies. A correlation analysis between the optical and the gamma-ray fluxes shows that the gamma-optical correlation occurs with a time lag of tau = -0.4{sup +0.6}{sub -0.8} days, consistent with previous findings for this source. An analysis of 15 GHz and 43 GHz VLBI core radio flux observations in the period 2007 July-2009 February shows an increasing trend of the core radio flux, anti-correlated with the higher frequency data, allowing us to derive the value of the source magnetic field. Finally, the modeling of the broadband spectral energy distributions for the still unpublished data, and the behavior of the long-term light curves in different energy bands, allow us to compare the jet properties during different emission states, and to study the geometrical properties of the jet on a time-span longer than one year.« less

Multi-scale controls on spatial variability in river biogeochemical cycling

NASA Astrophysics Data System (ADS)

Blaen, Phillip; Kurz, Marie; Knapp, Julia; Mendoza-Lera, Clara; Lee-Cullin, Joe; Klaar, Megan; Drummond, Jennifer; Jaeger, Anna; Zarnetske, Jay; Lewandowski, Joerg; Marti, Eugenia; Ward, Adam; Fleckenstein, Jan; Datry, Thibault; Larned, Scott; Krause, Stefan

2016-04-01

Excessive nutrient concentrations are common in surface waters and groundwaters in agricultural catchments worldwide. Increasing geomorphological heterogeneity in river channels may help to attenuate nutrient pollution by facilitating water exchange fluxes with the hyporheic zone; a site of intense microbial activity where biogeochemical cycling rates can be high. However, the controls on spatial variability in biogeochemical cycling, particularly at scales relevant for river managers, are largely unknown. Here, we aimed to assess: 1) how differences in river geomorphological heterogeneity control solute transport and rates of biogeochemical cycling at sub-reach scales (102 m); and 2) the relative magnitude of these differences versus those relating to reach scale substrate variability (103 m). We used the reactive tracer resazurin (Raz), a weakly fluorescent dye that transforms to highly fluorescent resorufin (Rru) under mildly reducing conditions, as a proxy to assess rates of biogeochemical cycling in a lowland river in southern England. Solute tracer tests were conducted in two reaches with contrasting substrates: one sand-dominated and the other gravel-dominated. Each reach was divided into sub-reaches that varied in geomorphic complexity (e.g. by the presence of pool-riffle sequences or the abundance of large woody debris). Slug injections of Raz and the conservative tracer fluorescein were conducted in each reach during baseflow conditions (Q ≈ 80 L/s) and breakthrough curves monitored using in-situ fluorometers. Preliminary results indicate overall Raz:Rru transformation rates in the gravel-dominated reach were more than 50% higher than those in the sand-dominated reach. However, high sub-reach variability in Raz:Rru transformation rates and conservative solute transport parameters suggests small scale targeted management interventions to alter geomorphic heterogeneity may be effective in creating hotspots of river biogeochemical cycling and nutrient load attenuation.

A detailed model for simulation of catchment scale subsurface hydrologic processes

NASA Technical Reports Server (NTRS)

Paniconi, Claudio; Wood, Eric F.

1993-01-01

A catchment scale numerical model is developed based on the three-dimensional transient Richards equation describing fluid flow in variably saturated porous media. The model is designed to take advantage of digital elevation data bases and of information extracted from these data bases by topographic analysis. The practical application of the model is demonstrated in simulations of a small subcatchment of the Konza Prairie reserve near Manhattan, Kansas. In a preliminary investigation of computational issues related to model resolution, we obtain satisfactory numerical results using large aspect ratios, suggesting that horizontal grid dimensions may not be unreasonably constrained by the typically much smaller vertical length scale of a catchment and by vertical discretization requirements. Additional tests are needed to examine the effects of numerical constraints and parameter heterogeneity in determining acceptable grid aspect ratios. In other simulations we attempt to match the observed streamflow response of the catchment, and we point out the small contribution of the streamflow component to the overall water balance of the catchment.

National Assessment of Energy Storage for Grid Balancing and Arbitrage: Phase 1, WECC

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

Kintner-Meyer, Michael CW; Balducci, Patrick J.; Colella, Whitney G.

2012-06-01

To examine the role that energy storage could play in mitigating the impacts of the stochastic variability of wind generation on regional grid operation, the Pacific Northwest National Laboratory (PNNL) examined a hypothetical 2020 grid scenario in which additional wind generation capacity is built to meet renewable portfolio standard targets in the Western Interconnection. PNNL developed a stochastic model for estimating the balancing requirements using historical wind statistics and forecasting error, a detailed engineering model to analyze the dispatch of energy storage and fast-ramping generation devices for estimating size requirements of energy storage and generation systems for meeting new balancingmore » requirements, and financial models for estimating the life-cycle cost of storage and generation systems in addressing the future balancing requirements for sub-regions in the Western Interconnection. Evaluated technologies include combustion turbines, sodium sulfur (Na-S) batteries, lithium ion batteries, pumped-hydro energy storage, compressed air energy storage, flywheels, redox flow batteries, and demand response. Distinct power and energy capacity requirements were estimated for each technology option, and battery size was optimized to minimize costs. Modeling results indicate that in a future power grid with high-penetration of renewables, the most cost competitive technologies for meeting balancing requirements include Na-S batteries and flywheels.« less

Mechanics of Flapping Flight: Analytical Formulations of Unsteady Aerodynamics, Kinematic Optimization, Flight Dynamics, and Control

NASA Astrophysics Data System (ADS)

Taneja, Jayant Kumar

Electricity is an indispensable commodity to modern society, yet it is delivered via a grid architecture that remains largely unchanged over the past century. A host of factors are conspiring to topple this dated yet venerated design: developments in renewable electricity generation technology, policies to reduce greenhouse gas emissions, and advances in information technology for managing energy systems. Modern electric grids are emerging as complex distributed systems in which a portfolio of power generation resources, often incorporating fluctuating renewable resources such as wind and solar, must be managed dynamically to meet uncontrolled, time-varying demand. Uncertainty in both supply and demand makes control of modern electric grids fundamentally more challenging, and growing portfolios of renewables exacerbate the challenge. We study three electricity grids: the state of California, the province of Ontario, and the country of Germany. To understand the effects of increasing renewables, we develop a methodology to scale renewables penetration. Analyzing these grids yields key insights about rigid limits to renewables penetration and their implications in meeting long-term emissions targets. We argue that to achieve deep penetration of renewables, the operational model of the grid must be inverted, changing the paradigm from load-following supplies to supply-following loads. To alleviate the challenge of supply-demand matching on deeply renewable grids, we first examine well-known techniques, including altering management of existing supply resources, employing utility-scale energy storage, targeting energy efficiency improvements, and exercising basic demand-side management. Then, we create several instantiations of supply-following loads -- including refrigerators, heating and cooling systems, and laptop computers -- by employing a combination of sensor networks, advanced control techniques, and enhanced energy storage. We examine the capacity of each load for supply-following and study the behaviors of populations of these loads, assessing their potential at various levels of deployment throughout the California electricity grid. Using combinations of supply-following strategies, we can reduce peak natural gas generation by 19% on a model of the California grid with 60% renewables. We then assess remaining variability on this deeply renewable grid incorporating supply-following loads, characterizing additional capabilities needed to ensure supply-demand matching in future sustainable electricity grids.

Development of an effective and potentially scalable weather generator for temperature and growing degree days

NASA Astrophysics Data System (ADS)

Rahmani, Elham; Friederichs, Petra; Keller, Jan; Hense, Andreas

2016-05-01

The main purpose of this study is to develop an easy-to-use weather generator (WG) for the downscaling of gridded data to point measurements at regional scale. The WG is applied to daily averaged temperatures and annual growing degree days (GDD) of wheat. This particular choice of variables is motivated by future investigations on temperature impacts as the most important climate variable for wheat cultivation under irrigation in Iran. The proposed statistical downscaling relates large-scale ERA-40 reanalysis to local daily temperature and annual GDD. Long-term local observations in Iran are used at 16 synoptic stations from 1961 to 2001, which is the common period with ERA-40 data. We perform downscaling using two approaches: the first is a linear regression model that uses the ERA-40 fingerprints (FP) defined by the squared correlation with local variability, and the second employs a linear multiple regression (MR) analysis to relate the large-scale information at the neighboring grid points to the station data. Extending the usual downscaling, we implement a WG providing uncertainty information and realizations of the local temperatures and GDD by adding a Gaussian random noise. ERA-40 reanalysis well represents the local daily temperature as well as the annual GDD variability. For 2-m temperature, the FPs are more localized during the warm compared with the cold season. While MR is slightly superior for daily temperature time series, FP seems to perform best for annual GDD. We further assess the quality of the WGs applying probabilistic verification scores like the continuous ranked probability score (CRPS) and the respective skill score. They clearly demonstrate the superiority of WGs compared with a deterministic downscaling.

Large-scale Agroecosytem's Resiliency to Extreme Hydrometeorological and Climate Extreme Events in the Missouri River Basin

NASA Astrophysics Data System (ADS)

Munoz-Arriola, F.; Smith, K.; Corzo, G.; Chacon, J.; Carrillo-Cruz, C.

2015-12-01

A major challenge for water, energy and food security relies on the capability of agroecosyststems and ecosystems to adapt to a changing climate and land use changes. The interdependency of these forcings, understood through our ability to monitor and model processes across scales, indicate the "depth" of their impact on agroecosystems and ecosystems, and consequently our ability to predict the system's ability to return to a "normal" state. We are particularly interested in explore two questions: (1) how hydrometeorological and climate extreme events (HCEs) affect sub-seasonal to interannual changes in evapotranspiration and soil moisture? And (2) how agroecosystems recover from the effect of such events. To address those questions we use the land surface hydrologic Variable Infiltration Capacity (VIC) model and the Moderate Resolution Imaging Spectrometer-Leaf Area Index (MODIS-LAI) over two time spans (1950-2013 using a seasonal fixed LAI cycle) and 2001-2013 (an 8-day MODIS-LAI). VIC is forced by daily/16th degree resolution precipitation, minimum and maximum temperature, and wind speed. In this large-scale experiment, resiliency is defined by the capacity of a particular agroecosystem, represented by a grid cell's ET, SM, and LAI to return to a historical average. This broad, yet simplistic definition will contribute to identify the possible components and their scales involved in agroecosystems and ecosystems capacity to adapt to the incidence of HCEs and technologies used to intensify agriculture and diversify their use for food and energy production. Preliminary results show that dynamical changes in land use, tracked by MODIS data, require larger time spans to address properly the influence of technologic improvements in crop production as well as the competition for land for biofuel vs. food production. On the other hand, fixed seasonal changes in land use allow us just to identify hydrologic changes mainly due to climate variability.

Experimental Investigation of the Behavior of Sub-Grid Scale Motions in Turbulent Shear Flow

NASA Technical Reports Server (NTRS)

Cantwell, Brian

1992-01-01

Experiments have been carried out on a vertical jet of helium issuing into a co-flow of air at a fixed exit velocity ratio of 2.0. At all the experimental conditions studied, the flow exhibits a strong self excited periodicity. The natural frequency behavior of the jet, the underlying fine-scale flow structure, and the transition to turbulence have been studied over a wide range of flow conditions. The experiments were conducted in a variable pressure facility which made it possible to vary the Reynolds number and Richardson number independently. A stroboscopic schlieren system was used for flow visualization and single-component Laser Doppler Anemometry was used to measure the axial component of velocity. The flow exhibits several interesting features. The presence of co-flow eliminates the random meandering typical of buoyant plumes in a quiescent environment and the periodicity of the helium jet under high Richardson number conditions is striking. Under these conditions transition to turbulence consists of a rapid but highly structured and repeatable breakdown and intermingling of jet and freestream fluid. At Ri = 1.6 the three-dimensional structure of the flow is seen to repeat from cycle to cycle. The point of transition moves closer to the jet exit as either the Reynolds number or the Richardson number increases. The wavelength of the longitudinal instability increases with Richardson number. At low Richardson numbers, the natural frequency scales on an inertial time scale. At high Richardson number the natural frequency scales on a buoyancy time scale. The transition from one flow regime to another occurs over a narrow range of Richardson numbers from 0.7 to 1. A buoyancy Strouhal number is used to correlate the high Richardson number frequency behavior.

Fine-scale application of WRF-CAM5 during a dust storm episode over East Asia: Sensitivity to grid resolutions and aerosol activation parameterizations

NASA Astrophysics Data System (ADS)

Wang, Kai; Zhang, Yang; Zhang, Xin; Fan, Jiwen; Leung, L. Ruby; Zheng, Bo; Zhang, Qiang; He, Kebin

2018-03-01

An advanced online-coupled meteorology and chemistry model WRF-CAM5 has been applied to East Asia using triple-nested domains at different grid resolutions (i.e., 36-, 12-, and 4-km) to simulate a severe dust storm period in spring 2010. Analyses are performed to evaluate the model performance and investigate model sensitivity to different horizontal grid sizes and aerosol activation parameterizations and to examine aerosol-cloud interactions and their impacts on the air quality. A comprehensive model evaluation of the baseline simulations using the default Abdul-Razzak and Ghan (AG) aerosol activation scheme shows that the model can well predict major meteorological variables such as 2-m temperature (T2), water vapor mixing ratio (Q2), 10-m wind speed (WS10) and wind direction (WD10), and shortwave and longwave radiation across different resolutions with domain-average normalized mean biases typically within ±15%. The baseline simulations also show moderate biases for precipitation and moderate-to-large underpredictions for other major variables associated with aerosol-cloud interactions such as cloud droplet number concentration (CDNC), cloud optical thickness (COT), and cloud liquid water path (LWP) due to uncertainties or limitations in the aerosol-cloud treatments. The model performance is sensitive to grid resolutions, especially for surface meteorological variables such as T2, Q2, WS10, and WD10, with the performance generally improving at finer grid resolutions for those variables. Comparison of the sensitivity simulations with an alternative (i.e., the Fountoukis and Nenes (FN) series scheme) and the default (i.e., AG scheme) aerosol activation scheme shows that the former predicts larger values for cloud variables such as CDNC and COT across all grid resolutions and improves the overall domain-average model performance for many cloud/radiation variables and precipitation. Sensitivity simulations using the FN series scheme also have large impacts on radiations, T2, precipitation, and air quality (e.g., decreasing O3) through complex aerosol-radiation-cloud-chemistry feedbacks. The inclusion of adsorptive activation of dust particles in the FN series scheme has similar impacts on the meteorology and air quality but to lesser extent as compared to differences between the FN series and AG schemes. Compared to the overall differences between the FN series and AG schemes, impacts of adsorptive activation of dust particles can contribute significantly to the increase of total CDNC (∼45%) during dust storm events and indicate their importance in modulating regional climate over East Asia.

Simulating multi-scale oceanic processes around Taiwan on unstructured grids

NASA Astrophysics Data System (ADS)

Yu, Hao-Cheng; Zhang, Yinglong J.; Yu, Jason C. S.; Terng, C.; Sun, Weiling; Ye, Fei; Wang, Harry V.; Wang, Zhengui; Huang, Hai

2017-11-01

We validate a 3D unstructured-grid (UG) model for simulating multi-scale processes as occurred in Northwestern Pacific around Taiwan using recently developed new techniques (Zhang et al., Ocean Modeling, 102, 64-81, 2016) that require no bathymetry smoothing even for this region with prevalent steep bottom slopes and many islands. The focus is on short-term forecast for several months instead of long-term variability. Compared with satellite products, the errors for the simulated Sea-surface Height (SSH) and Sea-surface Temperature (SST) are similar to a reference data-assimilated global model. In the nearshore region, comparison with 34 tide gauges located around Taiwan indicates an average RMSE of 13 cm for the tidal elevation. The average RMSE for SST at 6 coastal buoys is 1.2 °C. The mean transport and eddy kinetic energy compare reasonably with previously published values and the reference model used to provide boundary and initial conditions. The model suggests ∼2-day interruption of Kuroshio east of Taiwan during a typhoon period. The effect of tidal mixing is shown to be significant nearshore. The multi-scale model is easily extendable to target regions of interest due to its UG framework and a flexible vertical gridding system, which is shown to be superior to terrain-following coordinates.

Efficient computation paths for the systematic analysis of sensitivities

NASA Astrophysics Data System (ADS)

Greppi, Paolo; Arato, Elisabetta

2013-01-01

A systematic sensitivity analysis requires computing the model on all points of a multi-dimensional grid covering the domain of interest, defined by the ranges of variability of the inputs. The issues to efficiently perform such analyses on algebraic models are handling solution failures within and close to the feasible region and minimizing the total iteration count. Scanning the domain in the obvious order is sub-optimal in terms of total iterations and is likely to cause many solution failures. The problem of choosing a better order can be translated geometrically into finding Hamiltonian paths on certain grid graphs. This work proposes two paths, one based on a mixed-radix Gray code and the other, a quasi-spiral path, produced by a novel heuristic algorithm. Some simple, easy-to-visualize examples are presented, followed by performance results for the quasi-spiral algorithm and the practical application of the different paths in a process simulation tool.

Inter-Annual Variability of the Acoustic Propagation in the Mediterranean Sea Identified from a Synoptic Monthly Gridded Database as Compared with GDEM

DTIC Science & Technology

2016-12-01

VARIABILITY OF THE ACOUSTIC PROPAGATION IN THE MEDITERRANEAN SEA IDENTIFIED FROM A SYNOPTIC MONTHLY GRIDDED DATABASE AS COMPARED WITH GDEM by...ANNUAL VARIABILITY OF THE ACOUSTIC PROPAGATION IN THE MEDITERRANEAN SEA IDENTIFIED FROM A SYNOPTIC MONTHLY GRIDDED DATABASE AS COMPARED WITH GDEM 5...profiles obtained from the synoptic monthly gridded World Ocean Database (SMD-WOD) and Generalized Digital Environmental Model (GDEM) temperature (T

A two-dimensional composite grid numerical model based on the reduced system for oceanography

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

Xie, Y.F.; Browning, G.L.; Chesshire, G.

The proper mathematical limit of a hyperbolic system with multiple time scales, the reduced system, is a system that contains no high-frequency motions and is well posed if suitable boundary conditions are chosen for the initial-boundary value problem. The composite grid method, a robust and efficient grid-generation technique that smoothly and accurately treats general irregular boundaries, is used to approximate the two-dimensional version of the reduced system for oceanography on irregular ocean basins. A change-of-variable technique that substantially increases the accuracy of the model and a method for efficiently solving the elliptic equation for the geopotential are discussed. Numerical resultsmore » are presented for circular and kidney-shaped basins by using a set of analytic solutions constructed in this paper.« less

Structure and modeling of turbulence

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

Novikov, E.A.

The {open_quotes}vortex strings{close_quotes} scale l{sub s} {approximately} LRe{sup -3/10} (L-external scale, Re - Reynolds number) is suggested as a grid scale for the large-eddy simulation. Various aspects of the structure of turbulence and subgrid modeling are described in terms of conditional averaging, Markov processes with dependent increments and infinitely divisible distributions. The major request from the energy, naval, aerospace and environmental engineering communities to the theory of turbulence is to reduce the enormous number of degrees of freedom in turbulent flows to a level manageable by computer simulations. The vast majority of these degrees of freedom is in the small-scalemore » motion. The study of the structure of turbulence provides a basis for subgrid-scale (SGS) models, which are necessary for the large-eddy simulations (LES).« less

Benefits Analysis of Smart Grid Projects. White paper, 2014-2016

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

Marnay, Chris; Liu, Liping; Yu, JianCheng

Smart grids are rolling out internationally, with the United States (U.S.) nearing completion of a significant USD4-plus-billion federal program funded under the American Recovery and Reinvestment Act (ARRA-2009). The emergence of smart grids is widespread across developed countries. Multiple approaches to analyzing the benefits of smart grids have emerged. The goals of this white paper are to review these approaches and analyze examples of each to highlight their differences, advantages, and disadvantages. This work was conducted under the auspices of a joint U.S.-China research effort, the Climate Change Working Group (CCWG) Implementation Plan, Smart Grid. We present comparative benefits assessmentsmore » (BAs) of smart grid demonstrations in the U.S. and China along with a BA of a pilot project in Europe. In the U.S., we assess projects at two sites: (1) the University of California, Irvine campus (UCI), which consists of two distinct demonstrations: Southern California Edison’s (SCE) Irvine Smart Grid Demonstration Project (ISGD) and the UCI campus itself; and (2) the Navy Yard (TNY) area in Philadelphia, which has been repurposed as a mixed commercial-industrial, and possibly residential, development. In China, we cover several smart-grid aspects of the Sino-Singapore Tianjin Eco-city (TEC) and the Shenzhen Bay Technology and Ecology City (B-TEC). In Europe, we look at a BA of a pilot smart grid project in the Malagrotta area west of Rome, Italy, contributed by the Joint Research Centre (JRC) of the European Commission. The Irvine sub-project BAs use the U.S. Department of Energy (U.S. DOE) Smart Grid Computational Tool (SGCT), which is built on methods developed by the Electric Power Research Institute (EPRI). The TEC sub-project BAs apply Smart Grid Multi-Criteria Analysis (SG-MCA) developed by the State Grid Corporation of China (SGCC) based on the analytic hierarchy process (AHP) with fuzzy logic. The B-TEC and TNY sub-project BAs are evaluated using new approaches developed by those project teams. JRC has adopted an approach similar to EPRI’s but tailored to the Malagrotta distribution grid.« less

Generalized emission functions for photon emission from quark-gluon plasma

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

Suryanarayana, S. V.

The Landau-Pomeranchuk-Migdal effects on photon emission from the quark-gluon plasma have been studied as a function of photon mass, at a fixed temperature of the plasma. The integral equations for the transverse vector function [f-tilde)(p-tilde){sub (perpendicular)})] and the longitudinal function [g-tilde)(p-tilde){sub (perpendicular)})] consisting of multiple scattering effects are solved by the self-consistent iterations method and also by the variational method for the variable set {l_brace}p{sub 0},q{sub 0},Q{sup 2}{r_brace}. We considered the bremsstrahlung and the off shell annihilation (aws) processes. We define two new dynamical scaling variables, x{sub T},x{sub L}, for bremsstrahlung and aws processes which are functions of variables p{submore » 0},q{sub 0},Q{sup 2}. We define four new emission functions for massive photon emission represented by g{sub T}{sup b},g{sub T}{sup a},g{sub L}{sup b},g{sub L}{sup a} and we constructed these using the exact numerical solutions of the integral equations. These four emission functions have been parametrized by suitable simple empirical fits. Using the empirical emission functions, we calculated the imaginary part of the photon polarization tensor as a function of photon mass and energy.« less

Large temporal scale and capacity subsurface bulk energy storage with CO2

NASA Astrophysics Data System (ADS)

Saar, M. O.; Fleming, M. R.; Adams, B. M.; Ogland-Hand, J.; Nelson, E. S.; Randolph, J.; Sioshansi, R.; Kuehn, T. H.; Buscheck, T. A.; Bielicki, J. M.

2017-12-01

Decarbonizing energy systems by increasing the penetration of variable renewable energy (VRE) technologies requires efficient and short- to long-term energy storage. Very large amounts of energy can be stored in the subsurface as heat and/or pressure energy in order to provide both short- and long-term (seasonal) storage, depending on the implementation. This energy storage approach can be quite efficient, especially where geothermal energy is naturally added to the system. Here, we present subsurface heat and/or pressure energy storage with supercritical carbon dioxide (CO2) and discuss the system's efficiency, deployment options, as well as its advantages and disadvantages, compared to several other energy storage options. CO2-based subsurface bulk energy storage has the potential to be particularly efficient and large-scale, both temporally (i.e., seasonal) and spatially. The latter refers to the amount of energy that can be stored underground, using CO2, at a geologically conducive location, potentially enabling storing excess power from a substantial portion of the power grid. The implication is that it would be possible to employ centralized energy storage for (a substantial part of) the power grid, where the geology enables CO2-based bulk subsurface energy storage, whereas the VRE technologies (solar, wind) are located on that same power grid, where (solar, wind) conditions are ideal. However, this may require reinforcing the power grid's transmission lines in certain parts of the grid to enable high-load power transmission from/to a few locations.

Multi-scale responses of scattering layers to environmental variability in Monterey Bay, California

NASA Astrophysics Data System (ADS)

Urmy, Samuel S.; Horne, John K.

2016-07-01

A 38 kHz upward-facing echosounder was deployed on the seafloor at a depth of 875 m in Monterey Bay, CA, USA (36° 42.748‧N, 122° 11.214‧W) from 27 February 2009 to 18 August 2010. This 18-month record of acoustic backscatter was compared to oceanographic time series from a nearby data buoy to investigate the responses of animals in sound-scattering layers to oceanic variability at seasonal and sub-seasonal time scales. Pelagic animals, as measured by acoustic backscatter, moved higher in the water column and decreased in abundance during spring upwelling, attributed to avoidance of a shoaling oxycline and advection offshore. Seasonal changes were most evident in a non-migrating scattering layer near 500 m depth that disappeared in spring and reappeared in summer, building to a seasonal maximum in fall. At sub-seasonal time scales, similar responses were observed after individual upwelling events, though they were much weaker than the seasonal relationship. Correlations of acoustic backscatter with oceanographic variability also differed with depth. Backscatter in the upper water column decreased immediately following upwelling, then increased approximately 20 days later. Similar correlations existed deeper in the water column, but at increasing lags, suggesting that near-surface productivity propagated down the water column at 10-15 m d-1, consistent with sinking speeds of marine snow measured in Monterey Bay. Sub-seasonal variability in backscatter was best correlated with sea-surface height, suggesting that passive physical transport was most important at these time scales.

A gridded hourly rainfall dataset for the UK applied to a national physically-based modelling system

NASA Astrophysics Data System (ADS)

Lewis, Elizabeth; Blenkinsop, Stephen; Quinn, Niall; Freer, Jim; Coxon, Gemma; Woods, Ross; Bates, Paul; Fowler, Hayley

2016-04-01

An hourly gridded rainfall product has great potential for use in many hydrological applications that require high temporal resolution meteorological data. One important example of this is flood risk management, with flooding in the UK highly dependent on sub-daily rainfall intensities amongst other factors. Knowledge of sub-daily rainfall intensities is therefore critical to designing hydraulic structures or flood defences to appropriate levels of service. Sub-daily rainfall rates are also essential inputs for flood forecasting, allowing for estimates of peak flows and stage for flood warning and response. In addition, an hourly gridded rainfall dataset has significant potential for practical applications such as better representation of extremes and pluvial flash flooding, validation of high resolution climate models and improving the representation of sub-daily rainfall in weather generators. A new 1km gridded hourly rainfall dataset for the UK has been created by disaggregating the daily Gridded Estimates of Areal Rainfall (CEH-GEAR) dataset using comprehensively quality-controlled hourly rain gauge data from over 1300 observation stations across the country. Quality control measures include identification of frequent tips, daily accumulations and dry spells, comparison of daily totals against the CEH-GEAR daily dataset, and nearest neighbour checks. The quality control procedure was validated against historic extreme rainfall events and the UKCP09 5km daily rainfall dataset. General use of the dataset has been demonstrated by testing the sensitivity of a physically-based hydrological modelling system for Great Britain to the distribution and rates of rainfall and potential evapotranspiration. Of the sensitivity tests undertaken, the largest improvements in model performance were seen when an hourly gridded rainfall dataset was combined with potential evapotranspiration disaggregated to hourly intervals, with 61% of catchments showing an increase in NSE between observed and simulated streamflows as a result of more realistic sub-daily meteorological forcing.

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

Wang, Zihan; Swantek, Andrew; Scarcelli, Riccardo

This paper focuses on detailed numerical simulations of direct injection diesel and gasoline sprays from production grade, multi-hole injectors. In a dual-fuel engine the direct injection of both the fuels can facilitate appropriate mixture preparation prior to ignition and combustion. Diesel and gasoline sprays were simulated using high-fidelity Large Eddy Simulations (LES) with the dynamic structure sub-grid scale model. Numerical predictions of liquid penetration, fuel density distribution as well as transverse integrated mass (TIM) at different axial locations versus time were compared against x-ray radiography data obtained from Argonne National Laboratory. A necessary, but often overlooked, criterion of grid-convergence ismore » ensured by using Adaptive Mesh Refinement (AMR) for both diesel and gasoline. Nine different realizations were performed and the effects of random seeds on spray behavior were investigated. Additional parametric studies under different ambient and injection conditions were performed to study their influence on global and local flow structures for gasoline sprays. It is concluded that LES can generally well capture all experimental trends and comes close to matching the x-ray data. Discrepancies between experimental and simulation results can be correlated to uncertainties in boundary and initial conditions such as rate of injection and spray and turbulent dispersion sub-model constants.« less

Star Clusters within FIRE

NASA Astrophysics Data System (ADS)

Perez, Adrianna; Moreno, Jorge; Naiman, Jill; Ramirez-Ruiz, Enrico; Hopkins, Philip F.

2017-01-01

In this work, we analyze the environments surrounding star clusters of simulated merging galaxies. Our framework employs Feedback In Realistic Environments (FIRE) model (Hopkins et al., 2014). The FIRE project is a high resolution cosmological simulation that resolves star forming regions and incorporates stellar feedback in a physically realistic way. The project focuses on analyzing the properties of the star clusters formed in merging galaxies. The locations of these star clusters are identified with astrodendro.py, a publicly available dendrogram algorithm. Once star cluster properties are extracted, they will be used to create a sub-grid (smaller than the resolution scale of FIRE) of gas confinement in these clusters. Then, we can examine how the star clusters interact with these available gas reservoirs (either by accreting this mass or blowing it out via feedback), which will determine many properties of the cluster (star formation history, compact object accretion, etc). These simulations will further our understanding of star formation within stellar clusters during galaxy evolution. In the future, we aim to enhance sub-grid prescriptions for feedback specific to processes within star clusters; such as, interaction with stellar winds and gas accretion onto black holes and neutron stars.

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

Elliott, Elizabeth J.; Yu, Sungduk; Kooperman, Gabriel J.

The sensitivities of simulated mesoscale convective systems (MCSs) in the central U.S. to microphysics and grid configuration are evaluated here in a global climate model (GCM) that also permits global-scale feedbacks and variability. Since conventional GCMs do not simulate MCSs, studying their sensitivities in a global framework useful for climate change simulations has not previously been possible. To date, MCS sensitivity experiments have relied on controlled cloud resolving model (CRM) studies with limited domains, which avoid internal variability and neglect feedbacks between local convection and larger-scale dynamics. However, recent work with superparameterized (SP) GCMs has shown that eastward propagating MCS-likemore » events are captured when embedded CRMs replace convective parameterizations. This study uses a SP version of the Community Atmosphere Model version 5 (SP-CAM5) to evaluate MCS sensitivities, applying an objective empirical orthogonal function algorithm to identify MCS-like events, and harmonizing composite storms to account for seasonal and spatial heterogeneity. A five-summer control simulation is used to assess the magnitude of internal and interannual variability relative to 10 sensitivity experiments with varied CRM parameters, including ice fall speed, one-moment and two-moment microphysics, and grid spacing. MCS sensitivities were found to be subtle with respect to internal variability, and indicate that ensembles of over 100 storms may be necessary to detect robust differences in SP-GCMs. Furthermore, these results emphasize that the properties of MCSs can vary widely across individual events, and improving their representation in global simulations with significant internal variability may require comparison to long (multidecadal) time series of observed events rather than single season field campaigns.« less

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

On the use of MODIS and TRMM products to simulate hydrological processes in the La Plata Basin

NASA Astrophysics Data System (ADS)

Saavedra Valeriano, O. C.; Koike, T.; Berbery, E. H.

2009-12-01

La Plata basin is targeted to establish a distributed water-energy balance model using NASA and JAXA satellite products to estimate fluxes like the river discharge at sub-basin scales. The coupled model is called the Water and Energy Budget-based Distributed Hydrological Model (WEB-DHM), already tested with success in the Little Washita basin, Oklahoma, and the upper Tone River in Japan. The model demonstrated the ability to reproduce point-scale energy fluxes, CO2 flux, and river discharges. Moreover, the model showed the ability to predict the basin-scale surface soil moisture evolution in a spatially distributed fashion. In the context of the La Plata Basin, the first step was to set-up the water balance component of the distributed hydrological model of the entire basin using available global geographical data sets. The geomorphology of the basin was extracted using 1-km DEM resolution (obtained from EROS, Hydro 1K). The total delineated watershed reached 3.246 millions km2, identifying 145 sub-basins with a computing grid of 10-km. The distribution of land cover, land surface temperature, LAI and FPAR were obtained from MODIS products. In a first instance, the model was forced by gridded rainfall from the Climate Prediction Center (derived from available rain gauges) and satellite precipitation from TRMM 3B42 (NASA & JAXA). The simulated river discharge using both sources of data was compared and the overall low flow and normal peaks were identified. It was found that the extreme peaks tend to be overestimated when using TRMM 3B42. However, TRMM data allows tracking rainfall patterns which might be missed by the sparse distribution of rain gauges over some areas of the basin.

Comparison of AGE and Spectral Methods for the Simulation of Far-Wakes

NASA Technical Reports Server (NTRS)

Bisset, D. K.; Rogers, M. M.; Kega, Dennis (Technical Monitor)

1999-01-01

Turbulent flow simulation methods based on finite differences are attractive for their simplicity, flexibility and efficiency, but not always for accuracy or stability. This report demonstrates that a good compromise is possible with the Advected Grid Explicit (AGE) method. AGE has proven to be both efficient and accurate for simulating turbulent free-shear flows, including planar mixing layers and planar jets. Its efficiency results from its localized fully explicit finite difference formulation (Bisset 1998a,b) that is very straightforward to compute, outweighing the need for a fairly small timestep. Also, most of the successful simulations were slightly under-resolved, and therefore they were, in effect, large-eddy simulations (LES) without a sub-grid-scale (SGS) model, rather than direct numerical simulations (DNS). The principle is that the role of the smallest scales of turbulent motion (when the Reynolds number is not too low) is to dissipate turbulent energy, and therefore they do not have to be simulated when the numerical method is inherently dissipative at its resolution limits. Such simulations are termed 'auto-LES' (LES with automatic SGS modeling) in this report.

INITIAL APPL;ICATION OF THE ADAPTIVE GRID AIR POLLUTION MODEL

EPA Science Inventory

The paper discusses an adaptive-grid algorithm used in air pollution models. The algorithm reduces errors related to insufficient grid resolution by automatically refining the grid scales in regions of high interest. Meanwhile the grid scales are coarsened in other parts of the d...

Evaluation of TRMM multi-satellite precipitation analysis (TMPA) against terrestrial measurement over a humid sub-tropical basin, India

NASA Astrophysics Data System (ADS)

Kumar, Dheeraj; Gautam, Amar Kant; Palmate, Santosh S.; Pandey, Ashish; Suryavanshi, Shakti; Rathore, Neha; Sharma, Nayan

2017-08-01

To support the GPM mission which is homologous to its predecessor, the Tropical Rainfall Measuring Mission (TRMM), this study has been undertaken to evaluate the accuracy of Tropical Rainfall Measuring Mission multi-satellite precipitation analysis (TMPA) daily-accumulated precipitation products for 5 years (2008-2012) using the statistical methods and contingency table method. The analysis was performed on daily, monthly, seasonal and yearly basis. The TMPA precipitation estimates were also evaluated for each grid point i.e. 0.25° × 0.25° and for 18 rain gauge stations of the Betwa River basin, India. Results indicated that TMPA precipitation overestimates the daily and monthly precipitation in general, particularly for the middle sub-basin in the non-monsoon season. Furthermore, precision of TMPA precipitation estimates declines with the decrease of altitude at both grid and sub-basin scale. The study also revealed that TMPA precipitation estimates provide better accuracy in the upstream of the basin compared to downstream basin. Nevertheless, the detection capability of daily TMPA precipitation improves with increase in altitude for drizzle rain events. However, the detection capability decreases during non-monsoon and monsoon seasons when capturing moderate and heavy rain events, respectively. The veracity of TMPA precipitation estimates was improved during the rainy season than during the dry season at all scenarios investigated. The analyses suggest that there is a need for better precipitation estimation algorithm and extensive accuracy verification against terrestrial precipitation measurement to capture the different types of rain events more reliably over the sub-humid tropical regions of India.

Sub-grid scale precipitation in ALCMs: re-assessing the land surface sensitivity using a single column model

NASA Astrophysics Data System (ADS)

Pitman, Andrew J.; Yang, Zong-Liang; Henderson-Sellers, Ann

1993-10-01

The sensitivity of a land surface scheme to the distribution of precipitation within a general circulation model's grid element is investigated. Earlier experiments which showed considerable sensitivity of the runoff and evaporation simulation to the distribution of precipitation are repeated in the light of other results which show no sensitivity of evaporation to the distribution of precipitation. Results show that while the earlier results over-estimated the sensitivity of the surface hydrology to the precipitation distribution, the general conclusion that the system is sensitive is supported. It is found that changing the distribution of precipitation from falling over 100% of the grid square to falling over 10% leads to a reduction in evaporation from 1578 mm y-1 to 1195 mm y -1 while runoff increases from 278 mm y-1 to 602 mm y-1. The sensitivity is explained in terms of evaporation being dominated by available energy when precipitation falls over nearly the entire grid square, but by moisture availability (mainly intercepted water) when it falls over little of the grid square. These results also indicate that earlier work using stand-alone forcing to drive land surface schemes ‘off-line’, and to investigate the sensitivity of land surface codes to various parameters, leads to results which are non-repeatable in single column simulations.

EVOLUTION OF CATACLYSMIC VARIABLES AND RELATED BINARIES CONTAINING A WHITE DWARF

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

Kalomeni, B.; Rappaport, S.; Molnar, M.

We present a binary evolution study of cataclysmic variables (CVs) and related systems with white dwarf (WD) accretors, including for example, AM CVn systems, classical novae, supersoft X-ray sources (SXSs), and systems with giant donor stars. Our approach intentionally avoids the complications associated with population synthesis algorithms, thereby allowing us to present the first truly comprehensive exploration of all of the subsequent binary evolution pathways that zero-age CVs might follow (assuming fully non-conservative, Roche-lobe overflow onto an accreting WD) using the sophisticated binary stellar evolution code MESA. The grid consists of 56,000 initial models, including 14 WD accretor masses, 43more » donor-star masses (0.1–4.7 M {sub ⊙}), and 100 orbital periods. We explore evolution tracks in the orbital period and donor-mass ( P {sub orb}– M {sub don}) plane in terms of evolution dwell times, masses of the WD accretor, accretion rate, and chemical composition of the center and surface of the donor star. We report on the differences among the standard CV tracks, those with giant donor stars, and ultrashort period systems. We show where in parameter space one can expect to find SXSs, present a diagnostic to distinguish among different evolutionary paths to forming AM CVn binaries, quantify how the minimum orbital period in CVs depends on the chemical composition of the donor star, and update the P {sub orb}( M {sub wd}) relation for binaries containing WDs whose progenitors lost their envelopes via stable Roche-lobe overflow. Finally, we indicate where in the P {sub orb}– M {sub don} the accretion disks will tend to be stable against the thermal-viscous instability, and where gravitational radiation signatures may be found with LISA.« less

Using Computing and Data Grids for Large-Scale Science and Engineering

NASA Technical Reports Server (NTRS)

Johnston, William E.

2001-01-01

We use the term "Grid" to refer to a software system that provides uniform and location independent access to geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. These emerging data and computing Grids promise to provide a highly capable and scalable environment for addressing large-scale science problems. We describe the requirements for science Grids, the resulting services and architecture of NASA's Information Power Grid (IPG) and DOE's Science Grid, and some of the scaling issues that have come up in their implementation.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Relative spatial soil geochemical variability along two transects across the United States and Canada

USGS Publications Warehouse

Garrett, Robert G.

2009-01-01

The patterns of relative variability differ by transect and horizon. The N–S transect A-horizon soils show significant between-40-km scale variability for 29 elements, with only 4 elements (Ca, Mg, Pb and Sr) showing in excess of 50% of their variability at the within-40-km and ‘at-site’ scales. In contrast, the C-horizon data demonstrate significant between-40-km scale variability for 26 elements, with 21 having in excess of 50% of their variability at the within-40-km and ‘at-site’ scales. In 36 instances, the ‘at-site’ variability is statistically significant in terms of the sample preparation and analysis variability. It is postulated that this contrast between the A- and C- horizons along the N–S transect, that is dominated by agricultural land uses, is due to the local homogenization of Ap-horizon soils by tillage reducing the ‘at-site’ variability. The spatial variability is distributed similarly between scales for the A- and C-horizon soils of the E–W transect. For all elements, there is significant variability at the within-40-km scale. Notwithstanding this, there is significant between-40-km variability for 28 and 20 of the elements in the A- and C-horizon data, respectively. The differences between the two transects are attributed to (1) geology, the N–S transect runs generally parallel to regional strikes, whereas the E–W transect runs across regional structures and lithologies; and (2) land use, with agricultural tillage dominating along the N–S transect. The spatial analysis of the transect data indicates that continental-scale maps demonstrating statistically significant patterns of geochemical variability may be prepared for many elements from data on soil samples collected on a 40 x 40 km grid or similar sampling designs resulting in a sample density of 1 site per 1600 km2.

Scaling invariance of spherical projectile fragmentation upon high-velocity impact on a thin continuous shield

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

Myagkov, N. N., E-mail: nn-myagkov@mail.ru

The problem of aluminum projectile fragmentation upon high-velocity impact on a thin aluminum shield is considered. A distinctive feature of this description is that the fragmentation has been numerically simulated using the complete system of equations of deformed solid mechanics by a method of smoothed particle hydrodynamics in three-dimensional setting. The transition from damage to fragmentation is analyzed and scaling relations are derived in terms of the impact velocity (V), ratio of shield thickness to projectile diameter (h/D), and ultimate strength (σ{sub p}) in the criterion of projectile and shield fracture. Analysis shows that the critical impact velocity V{sub c}more » (separating the damage and fragmentation regions) is a power function of σ{sub p} and h/D. In the supercritical region (V > V{sub c}), the weight-average fragment mass asymptotically tends to a power function of the impact velocity with exponent independent of h/D and σ{sub p}. Mean cumulative fragment mass distributions at the critical point are scale-invariant with respect to parameters h/D and σ{sub p}. Average masses of the largest fragments are also scale-invariant at V > V{sub c}, but only with respect to variable parameter σ{sub p}.« less

Map visualization of groundwater withdrawals at the sub-basin scale

NASA Astrophysics Data System (ADS)

Goode, Daniel J.

2016-06-01

A simple method is proposed to visualize the magnitude of groundwater withdrawals from wells relative to user-defined water-resource metrics. The map is solely an illustration of the withdrawal magnitudes, spatially centered on wells—it is not capture zones or source areas contributing recharge to wells. Common practice is to scale the size (area) of withdrawal well symbols proportional to pumping rate. Symbols are drawn large enough to be visible, but not so large that they overlap excessively. In contrast to such graphics-based symbol sizes, the proposed method uses a depth-rate index (length per time) to visualize the well withdrawal rates by volumetrically consistent areas, called "footprints". The area of each individual well's footprint is the withdrawal rate divided by the depth-rate index. For example, the groundwater recharge rate could be used as a depth-rate index to show how large withdrawals are relative to that recharge. To account for the interference of nearby wells, composite footprints are computed by iterative nearest-neighbor distribution of excess withdrawals on a computational and display grid having uniform square cells. The map shows circular footprints at individual isolated wells and merged footprint areas where wells' individual footprints overlap. Examples are presented for depth-rate indexes corresponding to recharge, to spatially variable stream baseflow (normalized by basin area), and to the average rate of water-table decline (scaled by specific yield). These depth-rate indexes are water-resource metrics, and the footprints visualize the magnitude of withdrawals relative to these metrics.

Map visualization of groundwater withdrawals at the sub-basin scale

USGS Publications Warehouse

Goode, Daniel J.

2016-01-01

A simple method is proposed to visualize the magnitude of groundwater withdrawals from wells relative to user-defined water-resource metrics. The map is solely an illustration of the withdrawal magnitudes, spatially centered on wells—it is not capture zones or source areas contributing recharge to wells. Common practice is to scale the size (area) of withdrawal well symbols proportional to pumping rate. Symbols are drawn large enough to be visible, but not so large that they overlap excessively. In contrast to such graphics-based symbol sizes, the proposed method uses a depth-rate index (length per time) to visualize the well withdrawal rates by volumetrically consistent areas, called “footprints”. The area of each individual well’s footprint is the withdrawal rate divided by the depth-rate index. For example, the groundwater recharge rate could be used as a depth-rate index to show how large withdrawals are relative to that recharge. To account for the interference of nearby wells, composite footprints are computed by iterative nearest-neighbor distribution of excess withdrawals on a computational and display grid having uniform square cells. The map shows circular footprints at individual isolated wells and merged footprint areas where wells’ individual footprints overlap. Examples are presented for depth-rate indexes corresponding to recharge, to spatially variable stream baseflow (normalized by basin area), and to the average rate of water-table decline (scaled by specific yield). These depth-rate indexes are water-resource metrics, and the footprints visualize the magnitude of withdrawals relative to these metrics.

A high-resolution European dataset for hydrologic modeling

NASA Astrophysics Data System (ADS)

Ntegeka, Victor; Salamon, Peter; Gomes, Goncalo; Sint, Hadewij; Lorini, Valerio; Thielen, Jutta

2013-04-01

There is an increasing demand for large scale hydrological models not only in the field of modeling the impact of climate change on water resources but also for disaster risk assessments and flood or drought early warning systems. These large scale models need to be calibrated and verified against large amounts of observations in order to judge their capabilities to predict the future. However, the creation of large scale datasets is challenging for it requires collection, harmonization, and quality checking of large amounts of observations. For this reason, only a limited number of such datasets exist. In this work, we present a pan European, high-resolution gridded dataset of meteorological observations (EFAS-Meteo) which was designed with the aim to drive a large scale hydrological model. Similar European and global gridded datasets already exist, such as the HadGHCND (Caesar et al., 2006), the JRC MARS-STAT database (van der Goot and Orlandi, 2003) and the E-OBS gridded dataset (Haylock et al., 2008). However, none of those provide similarly high spatial resolution and/or a complete set of variables to force a hydrologic model. EFAS-Meteo contains daily maps of precipitation, surface temperature (mean, minimum and maximum), wind speed and vapour pressure at a spatial grid resolution of 5 x 5 km for the time period 1 January 1990 - 31 December 2011. It furthermore contains calculated radiation, which is calculated by using a staggered approach depending on the availability of sunshine duration, cloud cover and minimum and maximum temperature, and evapotranspiration (potential evapotranspiration, bare soil and open water evapotranspiration). The potential evapotranspiration was calculated using the Penman-Monteith equation with the above-mentioned meteorological variables. The dataset was created as part of the development of the European Flood Awareness System (EFAS) and has been continuously updated throughout the last years. The dataset variables are used as inputs to the hydrological calibration and validation of EFAS as well as for establishing long-term discharge "proxy" climatologies which can then in turn be used for statistical analysis to derive return periods or other time series derivatives. In addition, this dataset will be used to assess climatological trends in Europe. Unfortunately, to date no baseline dataset at the European scale exists to test the quality of the herein presented data. Hence, a comparison against other existing datasets can therefore only be an indication of data quality. Due to availability, a comparison was made for precipitation and temperature only, arguably the most important meteorological drivers for hydrologic models. A variety of analyses was undertaken at country scale against data reported to EUROSTAT and E-OBS datasets. The comparison revealed that while the datasets showed overall similar temporal and spatial patterns, there were some differences in magnitudes especially for precipitation. It is not straightforward to define the specific cause for these differences. However, in most cases the comparatively low observation station density appears to be the principal reason for the differences in magnitude.

Influence of lubrication forces in direct numerical simulations of particle-laden flows

NASA Astrophysics Data System (ADS)

Maitri, Rohit; Peters, Frank; Padding, Johan; Kuipers, Hans

2016-11-01

Accurate numerical representation of particle-laden flows is important for fundamental understanding and optimizing the complex processes such as proppant transport in fracking. Liquid-solid flows are fundamentally different from gas-solid flows because of lower density ratios (solid to fluid) and non-negligible lubrication forces. In this interface resolved model, fluid-solid coupling is achieved by incorporating the no-slip boundary condition implicitly at particle's surfaces by means of an efficient second order ghost-cell immersed boundary method. A fixed Eulerian grid is used for solving the Navier-Stokes equations and the particle-particle interactions are implemented using the soft sphere collision and sub-grid scale lubrication model. Due to the range of influence of lubrication force on a smaller scale than the grid size, it is important to implement the lubrication model accurately. In this work, different implementations of the lubrication model on particle dynamics are studied for various flow conditions. The effect of a particle surface roughness on lubrication force and the particle transport is also investigated. This study is aimed at developing a validated methodology to incorporate lubrication models in direct numerical simulation of particle laden flows. This research is supported from Grant 13CSER014 of the Foundation for Fundamental Research on Matter (FOM), which is part of the Netherlands Organisation for Scientific Research (NWO).

The self-organization of grid cells in 3D

PubMed Central

Stella, Federico; Treves, Alessandro

2015-01-01

Do we expect periodic grid cells to emerge in bats, or perhaps dolphins, exploring a three-dimensional environment? How long will it take? Our self-organizing model, based on ring-rate adaptation, points at a complex answer. The mathematical analysis leads to asymptotic states resembling face centered cubic (FCC) and hexagonal close packed (HCP) crystal structures, which are calculated to be very close to each other in terms of cost function. The simulation of the full model, however, shows that the approach to such asymptotic states involves several sub-processes over distinct time scales. The smoothing of the initially irregular multiple fields of individual units and their arrangement into hexagonal grids over certain best planes are observed to occur relatively quickly, even in large 3D volumes. The correct mutual orientation of the planes, though, and the coordinated arrangement of different units, take a longer time, with the network showing no sign of convergence towards either a pure FCC or HCP ordering. DOI: http://dx.doi.org/10.7554/eLife.05913.001 PMID:25821989

Wind and Solar on the Power Grid: Myths and Misperceptions, Greening the Grid (Spanish Version)

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

Authors: Denholm, Paul; Cochran, Jaquelin; Brancucci Martinez-Anido, Carlo

This is the Spanish version of the 'Greening the Grid - Wind and Solar on the Power Grid: Myths and Misperceptions'. Wind and solar are inherently more variable and uncertain than the traditional dispatchable thermal and hydro generators that have historically provided a majority of grid-supplied electricity. The unique characteristics of variable renewable energy (VRE) resources have resulted in many misperceptions regarding their contribution to a low-cost and reliable power grid. Common areas of concern include: 1) The potential need for increased operating reserves, 2) The impact of variability and uncertainty on operating costs and pollutant emissions of thermal plants,more » and 3) The technical limits of VRE penetration rates to maintain grid stability and reliability. This fact sheet corrects misperceptions in these areas.« less

Fat fractal scaling of drainage networks from a random spatial network model

USGS Publications Warehouse

Karlinger, Michael R.; Troutman, Brent M.

1992-01-01

An alternative quantification of the scaling properties of river channel networks is explored using a spatial network model. Whereas scaling descriptions of drainage networks previously have been presented using a fractal analysis primarily of the channel lengths, we illustrate the scaling of the surface area of the channels defining the network pattern with an exponent which is independent of the fractal dimension but not of the fractal nature of the network. The methodology presented is a fat fractal analysis in which the drainage basin minus the channel area is considered the fat fractal. Random channel networks within a fixed basin area are generated on grids of different scales. The sample channel networks generated by the model have a common outlet of fixed width and a rule of upstream channel narrowing specified by a diameter branching exponent using hydraulic and geomorphologic principles. Scaling exponents are computed for each sample network on a given grid size and are regressed against network magnitude. Results indicate that the size of the exponents are related to magnitude of the networks and generally decrease as network magnitude increases. Cases showing differences in scaling exponents with like magnitudes suggest a direction of future work regarding other topologic basin characteristics as potential explanatory variables.

Short-term wind speed prediction based on the wavelet transformation and Adaboost neural network

NASA Astrophysics Data System (ADS)

Hai, Zhou; Xiang, Zhu; Haijian, Shao; Ji, Wu

2018-03-01

The operation of the power grid will be affected inevitably with the increasing scale of wind farm due to the inherent randomness and uncertainty, so the accurate wind speed forecasting is critical for the stability of the grid operation. Typically, the traditional forecasting method does not take into account the frequency characteristics of wind speed, which cannot reflect the nature of the wind speed signal changes result from the low generality ability of the model structure. AdaBoost neural network in combination with the multi-resolution and multi-scale decomposition of wind speed is proposed to design the model structure in order to improve the forecasting accuracy and generality ability. The experimental evaluation using the data from a real wind farm in Jiangsu province is given to demonstrate the proposed strategy can improve the robust and accuracy of the forecasted variable.

Multi-Megawatt-Scale Power-Hardware-in-the-Loop Interface for Testing Ancillary Grid Services by Converter-Coupled Generation: Preprint

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

Koralewicz, Przemyslaw J; Gevorgian, Vahan; Wallen, Robert B

Power-hardware-in-the-loop (PHIL) is a simulation tool that can support electrical systems engineers in the development and experimental validation of novel, advanced control schemes that ensure the robustness and resiliency of electrical grids that have high penetrations of low-inertia variable renewable resources. With PHIL, the impact of the device under test on a generation or distribution system can be analyzed using a real-time simulator (RTS). PHIL allows for the interconnection of the RTS with a 7 megavolt ampere (MVA) power amplifier to test multi-megawatt renewable assets available at the National Wind Technology Center (NWTC). This paper addresses issues related to themore » development of a PHIL interface that allows testing hardware devices at actual scale. In particular, the novel PHIL interface algorithm and high-speed digital interface, which minimize the critical loop delay, are discussed.« less

Multi-Megawatt-Scale Power-Hardware-in-the-Loop Interface for Testing Ancillary Grid Services by Converter-Coupled Generation

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

Koralewicz, Przemyslaw J; Gevorgian, Vahan; Wallen, Robert B

Power-hardware-in-the-loop (PHIL) is a simulation tool that can support electrical systems engineers in the development and experimental validation of novel, advanced control schemes that ensure the robustness and resiliency of electrical grids that have high penetrations of low-inertia variable renewable resources. With PHIL, the impact of the device under test on a generation or distribution system can be analyzed using a real-time simulator (RTS). PHIL allows for the interconnection of the RTS with a 7 megavolt ampere (MVA) power amplifier to test multi-megawatt renewable assets available at the National Wind Technology Center (NWTC). This paper addresses issues related to themore » development of a PHIL interface that allows testing hardware devices at actual scale. In particular, the novel PHIL interface algorithm and high-speed digital interface, which minimize the critical loop delay, are discussed.« less

Balancing Area Coordination: Efficiently Integrating Renewable Energy Into the Grid, Greening the Grid

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

Katz, Jessica; Denholm, Paul; Cochran, Jaquelin

2015-06-01

Greening the Grid provides technical assistance to energy system planners, regulators, and grid operators to overcome challenges associated with integrating variable renewable energy into the grid. Coordinating balancing area operation can promote more cost and resource efficient integration of variable renewable energy, such as wind and solar, into power systems. This efficiency is achieved by sharing or coordinating balancing resources and operating reserves across larger geographic boundaries.

High Resolution Aerosol Data from MODIS Satellite for Urban Air Quality Studies

NASA Technical Reports Server (NTRS)

Chudnovsky, A.; Lyapustin, A.; Wang, Y.; Tang, C.; Schwartz, J.; Koutrakis, P.

2013-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not suitable for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(sub 2.5) as measured by the 27 EPA ground monitoring stations was investigated. These results were also compared to conventional MODIS 10 km AOD retrievals (MOD04) for the same days and locations. The coefficients of determination for MOD04 and for MAIAC are R(exp 2) =0.45 and 0.50 respectively, suggested that AOD is a reasonably good proxy for PM(sub 2.5) ground concentrations. Finally, we studied the relationship between PM(sub 2.5) and AOD at the intra-urban scale (10 km) in Boston. The fine resolution results indicated spatial variability in particle concentration at a sub-10 kilometer scale. A local analysis for the Boston area showed that the AOD-PM(sub 2.5) relationship does not depend on relative humidity and air temperatures below approximately 7 C. The correlation improves for temperatures above 7 - 16 C. We found no dependence on the boundary layer height except when the former was in the range 250-500 m. Finally, we apply a mixed effects model approach to MAIAC aerosol optical depth (AOD) retrievals from MODIS to predict PM(sub 2.5) concentrations within the greater Boston area. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations (out-of-sample R(exp 2) of 0.86). Therefore, adjustment for the daily variability in the AOD-PM(sub 2.5) relationship provides a means for obtaining spatially-resolved PM(sub 2.5) concentrations.

Solar radiation variability over La Réunion island and associated larger-scale dynamics

NASA Astrophysics Data System (ADS)

Mialhe, Pauline; Morel, Béatrice; Pohl, Benjamin; Bessafi, Miloud; Chabriat, Jean-Pierre

2017-04-01

This study aims to examine the solar radiation variability over La Réunion island and its relationship with large-scale circulation. The Satellite Application Facility on Climate Monitoring (CM SAF) produces a Shortwave Incoming Solar radiation (SIS) data record called Solar surfAce RAdiation Heliosat - East (SARAH-E). A comparison to in situ observations from Météo-France measurements networks quantifies the skill of SARAH-E grids which we use as dataset. First step of the work, irradiance mean cycles are calculated to describe the diurnal-seasonal SIS behaviour over La Réunion island. By analogy with the climate anomalies, instantaneous deviations are computed after removal of the mean states. Finally, we associate these anomalies with larger-scale atmospheric dynamics into the South West Indian Ocean by applying multivariate clustering analyses (Hierarchical Ascending Classification, k-means).

Terrestrial precipitation and soil moisture: A case study over southern Arizona and data development

NASA Astrophysics Data System (ADS)

Stillman, Susan

Quantifying climatological precipitation and soil moisture as well as interannual variability and trends requires extensive observation. This work focuses on the analysis of available precipitation and soil moisture data and the development of new ways to estimate these quantities. Precipitation and soil moisture characteristics are highly dependent on the spatial and temporal scales. We begin at the point scale, examining hourly precipitation and soil moisture at individual gauges. First, we focus on the Walnut Gulch Experimental Watershed (WGEW), a 150 km2 area in southern Arizona. The watershed has been measuring rainfall since 1956 with a very high density network of approximately 0.6 gauges per km2. Additionally, there are 19 soil moisture probes at 5 cm depth with data starting in 2002. In order to extend the measurement period, we have developed a water balance model which estimates monsoon season (Jul-Sep) soil moisture using only precipitation for input, and calibrated so that the modeled soil moisture fits best with the soil moisture measured by each of the 19 probes from 2002-2012. This observationally constrained soil moisture is highly correlated with the collocated probes (R=0.88), and extends the measurement period from 10 to 56 years and the number of gauges from 19 to 88. Then, we focus on the spatiotemporal variability within the watershed and the ability to estimate area averaged quantities. Spatially averaged precipitation and observationally constrained soil moisture from the 88 gauges is then used to evaluate various gridded datasets. We find that gauge-based precipitation products perform best followed by reanalyses and then satellite-based products. Coupled Model Intercomparison Project Phase 5 (CMIP5) models perform the worst and overestimate cold season precipitation while offsetting the monsoon peak precipitation forward or backward by a month. Satellite-based soil moisture is the best followed by land data assimilation systems and reanalyses. We show that while WGEW is small compared to the grid size of many of the evaluated products, unlike scaling from point to area, the effect of scaling from smaller to larger area is small. Finally, we focus on global precipitation. Global monthly gauge based precipitation data has become widely available in recent years and is necessary for analyzing the climatological and anomaly precipitation fields as well as for calibrating and evaluating other gridded products such as satellite-based and modeled precipitation. However, frequency and intensity of precipitation are also important in the partitioning of water and energy fluxes. Therefore, because daily and sub-daily observed precipitation is limited to recent years, the number of raining days per month (N) is needed. We show that the only currently available long-term N product, developed by the Climate Research Unit (CRU), is deficient in certain areas, particularly where CRU gauge data is sparse. We then develop a new global 110-year N product, which shows significant improvement over CRU using three regional daily precipitation products with far more gauges than are used in CRU.

Conceptual Design of the Everglades Depth Estimation Network (EDEN) Grid

USGS Publications Warehouse

Jones, John W.; Price, Susan D.

2007-01-01

INTRODUCTION The Everglades Depth Estimation Network (EDEN) offers a consistent and documented dataset that can be used to guide large-scale field operations, to integrate hydrologic and ecological responses, and to support biological and ecological assessments that measure ecosystem responses to the Comprehensive Everglades Restoration Plan (Telis, 2006). Ground elevation data for the greater Everglades and the digital ground elevation models derived from them form the foundation for all EDEN water depth and associated ecologic/hydrologic modeling (Jones, 2004, Jones and Price, 2007). To use EDEN water depth and duration information most effectively, it is important to be able to view and manipulate information on elevation data quality and other land cover and habitat characteristics across the Everglades region. These requirements led to the development of the geographic data layer described in this techniques and methods report. Relying on extensive experience in GIS data development, distribution, and analysis, a great deal of forethought went into the design of the geographic data layer used to index elevation and other surface characteristics for the Greater Everglades region. To allow for simplicity of design and use, the EDEN area was broken into a large number of equal-sized rectangles ('Cells') that in total are referred to here as the 'grid'. Some characteristics of this grid, such as the size of its cells, its origin, the area of Florida it is designed to represent, and individual grid cell identifiers, could not be changed once the grid database was developed. Therefore, these characteristics were selected to design as robust a grid as possible and to ensure the grid's long-term utility. It is desirable to include all pertinent information known about elevation and elevation data collection as grid attributes. Also, it is very important to allow for efficient grid post-processing, sub-setting, analysis, and distribution. This document details the conceptual design of the EDEN grid spatial parameters and cell attribute-table content.

An Assessment of the Length and Variability of Mercury's Magnetotail

NASA Technical Reports Server (NTRS)

Milan, S. E.; Slavin, J. A.

2011-01-01

We employ Mariner 10 measurements of the interplanetary magnetic field in the vicinity of Mercury to estimate the rate of magnetic reconnection between the interplanetary magnetic field and the Hermean magnetosphere. We derive a time-series of the open magnetic flux in Mercury's magnetosphere. from which we can deduce the length of the magnetotail The length of the magnetotail is shown to be highly variable. with open field lines stretching between 15R(sub H) and 8S0R(sub H) downstream of the planet (median 150R(sub H)). Scaling laws allow the tail length at perihelion to be deduced from the aphelion Mariner 10 observations.

The North American Drought Atlas: Tree-Ring Reconstructions of Drought Variability for Climate Modeling and Assessment

NASA Astrophysics Data System (ADS)

Cook, E. R.

2007-05-01

The North American Drought Atlas describes a detailed reconstruction of drought variability from tree rings over most of North America for the past 500-1000 years. The first version of it, produced over three years ago, was based on a network of 835 tree-ring chronologies and a 286-point grid of instrumental Palmer Drought Severity Indices (PDSI). These gridded PDSI reconstructions have been used in numerous published studies now that range from modeling fire in the American West, to the impact of drought on palaeo-Indian societies, and to the determination of the primary causes of drought over North America through climate modeling experiments. Some examples of these applications will be described to illustrate the scientific value of these large-scale reconstructions of drought. Since the development and free public release of Version 1 of the North American Drought Atlas (see http:iridl.ldeo.columbia.edu/SOURCES/.LDEO/.TRL/.NADA2004/.pdsi-atlas.html), great improvements have been made in the critical tree-ring network used to reconstruct PDSI at each grid point. This network has now been enlarged to 1743 annual tree-ring chronologies, which greatly improves the density of tree-ring records in certain parts of the grid, especially in Canada and Mexico. In addition, the number of tree-ring records that extend back before AD 1400 has been substantially increased. These developments justify the creation of Version 2 of the North American Drought Atlas. In this talk I will describe this new version of the drought atlas and some of its properties that make it a significant improvement over the previous version. The new product provides enhanced resolution of the spatial and temporal variability of prolonged drought such as the late 16th century event that impacted regions of both Mexico and the United States. I will also argue for the North American Drought Atlas being used as a template for the development of large-scale drought reconstructions in other land areas of the Northern Hemisphere where sufficient tree-ring data exist. By doing so, the importance of this product to the modeling community will be significantly enhanced.

Towards a More Biologically-meaningful Climate Characterization: Variability in Space and Time at Multiple Scales

NASA Astrophysics Data System (ADS)

Christianson, D. S.; Kaufman, C. G.; Kueppers, L. M.; Harte, J.

2013-12-01

Sampling limitations and current modeling capacity justify the common use of mean temperature values in summaries of historical climate and future projections. However, a monthly mean temperature representing a 1-km2 area on the landscape is often unable to capture the climate complexity driving organismal and ecological processes. Estimates of variability in addition to mean values are more biologically meaningful and have been shown to improve projections of range shifts for certain species. Historical analyses of variance and extreme events at coarse spatial scales, as well as coarse-scale projections, show increasing temporal variability in temperature with warmer means. Few studies have considered how spatial variance changes with warming, and analysis for both temporal and spatial variability across scales is lacking. It is unclear how the spatial variability of fine-scale conditions relevant to plant and animal individuals may change given warmer coarse-scale mean values. A change in spatial variability will affect the availability of suitable habitat on the landscape and thus, will influence future species ranges. By characterizing variability across both temporal and spatial scales, we can account for potential bias in species range projections that use coarse climate data and enable improvements to current models. In this study, we use temperature data at multiple spatial and temporal scales to characterize spatial and temporal variability under a warmer climate, i.e., increased mean temperatures. Observational data from the Sierra Nevada (California, USA), experimental climate manipulation data from the eastern and western slopes of the Rocky Mountains (Colorado, USA), projected CMIP5 data for California (USA) and observed PRISM data (USA) allow us to compare characteristics of a mean-variance relationship across spatial scales ranging from sub-meter2 to 10,000 km2 and across temporal scales ranging from hours to decades. Preliminary spatial analysis at fine-spatial scales (sub-meter to 10-meter) shows greater temperature variability with warmer mean temperatures. This is inconsistent with the inherent assumption made in current species distribution models that fine-scale variability is static, implying that current projections of future species ranges may be biased -- the direction and magnitude requiring further study. While we focus our findings on the cross-scaling characteristics of temporal and spatial variability, we also compare the mean-variance relationship between 1) experimental climate manipulations and observed conditions and 2) temporal versus spatial variance, i.e., variability in a time-series at one location vs. variability across a landscape at a single time. The former informs the rich debate concerning the ability to experimentally mimic a warmer future. The latter informs space-for-time study design and analyses, as well as species persistence via a combined spatiotemporal probability of suitable future habitat.

Evaluating GCM land surface hydrology parameterizations by computing river discharges using a runoff routing model: Application to the Mississippi basin

NASA Technical Reports Server (NTRS)

Liston, G. E.; Sud, Y. C.; Wood, E. F.

1994-01-01

To relate general circulation model (GCM) hydrologic output to readily available river hydrographic data, a runoff routing scheme that routes gridded runoffs through regional- or continental-scale river drainage basins is developed. By following the basin overland flow paths, the routing model generates river discharge hydrographs that can be compared to observed river discharges, thus allowing an analysis of the GCM representation of monthly, seasonal, and annual water balances over large regions. The runoff routing model consists of two linear reservoirs, a surface reservoir and a groundwater reservoir, which store and transport water. The water transport mechanisms operating within these two reservoirs are differentiated by their time scales; the groundwater reservoir transports water much more slowly than the surface reservior. The groundwater reservior feeds the corresponding surface store, and the surface stores are connected via the river network. The routing model is implemented over the Global Energy and Water Cycle Experiment (GEWEX) Continental-Scale International Project Mississippi River basin on a rectangular grid of 2 deg X 2.5 deg. Two land surface hydrology parameterizations provide the gridded runoff data required to run the runoff routing scheme: the variable infiltration capacity model, and the soil moisture component of the simple biosphere model. These parameterizations are driven with 4 deg X 5 deg gridded climatological potential evapotranspiration and 1979 First Global Atmospheric Research Program (GARP) Global Experiment precipitation. These investigations have quantified the importance of physically realistic soil moisture holding capacities, evaporation parameters, and runoff mechanisms in land surface hydrology formulations.

Z-Earth: 4D topography from space combining short-baseline stereo and lidar

NASA Astrophysics Data System (ADS)

Dewez, T. J.; Akkari, H.; Kaab, A. M.; Lamare, M. L.; Doyon, G.; Costeraste, J.

2013-12-01

The advent of free-of-charge global topographic data sets SRTM and Aster GDEM have enabled testing a host of geoscience hypotheses. Availability of such data is now considered standard, and though resolved at 30-m to 90-m pixel size, they are today regarded as obsolete and inappropriate given the regularly updated sub-meter imagery coming through web services like Google Earth. Two features will thus help meet the current topographic data needs of the Geoscience communities: field-scale-compatible elevation datasets (i.e. meter-scale digital models and sub-meter elevation precision) and provision for regularly updated topography to tackle earth surface changes in 4D, while retaining the key for success: data availability at no charge. A new space borne instrumental concept called Z-Earth has undergone phase 0 study at CNES, the French space agency to fulfill these aims. The scientific communities backing this proposal are that of natural hazards, glaciology and biomass. The system under study combines a short-baseline native stereo imager and a lidar profiler. This combination provides spatially resolved elevation swaths together with absolute along-track elevation control point profiles. Acquisition is designed for revisit time better than a year. Intended products not only target single pass digital surface models, color orthoimages and small footprint full-wave-form lidar profiles to update existing topographic coverage, but also time series of them. 3D change detection targets centimetre-scale horizontal precision and metric vertical precision, in complement of -now traditional- spectral change detection. To assess the actual concept value, two real-size experiments were carried out. We used sub-meter-scale Pleiades panchromatic stereo-images to generate digital surface models and check them against dense airborne lidar coverages, one heliborne set purposely flown in Corsica (50-100pts/sq.m) and a second one retrieved from OpenTopography.org (~10pts/sq.m.). In Corsica, over a challenging 45-degree-grade tree-covered mountain side, the Pleiades 2-m-grid-posting digital surface model described the topography with a median error of -4.75m +/-2.59m (NMAD). A planimetric bias between both datasets was found to be about 7m to the South. This planimetric misregistration, though well within Pleiades specifications, partly explains the dramatic effect on elevation difference. In the Redmond area (eastern Oregon), a very gentle desert landscape, elevation differences also contained a vertical median bias of -4.02m+/-1.22m (NMAD). Though here, sub-pixel planimetric registration between stereo DSM and lidar coverage was enforced. This real-size experiment hints that sub-meter accuracy for 2-m-grid-posting DSM is an achievable goal when combining stereoimaging and lidar.

Small-Grid Dithers for the JWST Coronagraphs

NASA Technical Reports Server (NTRS)

Lajoie, Charles-Philippe; Soummer, Remi; Pueyo, Laurent; Hines, Dean C.; Nelan, Edmund P.; Perrin, Marshall; Clampin, Mark; Isaacs, John C.

2016-01-01

We discuss new results of coronagraphic simulations demonstrating a novel mode for JWST that utilizes sub-pixel dithered reference images, called Small-Grid Dithers, to optimize coronagraphic PSF subtraction. These sub-pixel dithers are executed with the Fine Steering Mirror under fine guidance, are accurate to approx.2-3 milliarcseconds (1-s/axis), and provide ample speckle diversity to reconstruct an optimized synthetic reference PSF using LOCI or KLIP. We also discuss the performance gains of Small-Grid Dithers compared to the standard undithered scenario, and show potential contrast gain factors for the NIRCam and MIRI coronagraphs ranging from 2 to more than 10, respectively.

CFD Script for Rapid TPS Damage Assessment

NASA Technical Reports Server (NTRS)

McCloud, Peter

2013-01-01

This grid generation script creates unstructured CFD grids for rapid thermal protection system (TPS) damage aeroheating assessments. The existing manual solution is cumbersome, open to errors, and slow. The invention takes a large-scale geometry grid and its large-scale CFD solution, and creates a unstructured patch grid that models the TPS damage. The flow field boundary condition for the patch grid is then interpolated from the large-scale CFD solution. It speeds up the generation of CFD grids and solutions in the modeling of TPS damages and their aeroheating assessment. This process was successfully utilized during STS-134.

Methods and apparatus of analyzing electrical power grid data

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

Hafen, Ryan P.; Critchlow, Terence J.; Gibson, Tara D.

Apparatus and methods of processing large-scale data regarding an electrical power grid are described. According to one aspect, a method of processing large-scale data regarding an electrical power grid includes accessing a large-scale data set comprising information regarding an electrical power grid; processing data of the large-scale data set to identify a filter which is configured to remove erroneous data from the large-scale data set; using the filter, removing erroneous data from the large-scale data set; and after the removing, processing data of the large-scale data set to identify an event detector which is configured to identify events of interestmore » in the large-scale data set.« less

Full-Scale Numerical Modeling of Turbulent Processes in the Earth's Ionosphere

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

Eliasson, B.; Stenflo, L.; Department of Physics, Linkoeping University, SE-581 83 Linkoeping

2008-10-15

We present a full-scale simulation study of ionospheric turbulence by means of a generalized Zakharov model based on the separation of variables into high-frequency and slow time scales. The model includes realistic length scales of the ionospheric profile and of the electromagnetic and electrostatic fields, and uses ionospheric plasma parameters relevant for high-latitude radio facilities such as Eiscat and HAARP. A nested grid numerical method has been developed to resolve the different length-scales, while avoiding severe restrictions on the time step. The simulation demonstrates the parametric decay of the ordinary mode into Langmuir and ion-acoustic waves, followed by a Langmuirmore » wave collapse and short-scale caviton formation, as observed in ionospheric heating experiments.« less

A Comparison of Hybrid Reynolds Averaged Navier Stokes/Large Eddy Simulation (RANS/LES) and Unsteady RANS Predictions of Separated Flow for a Variable Speed Power Turbine Blade Operating with Low Inlet Turbulence Levels

DTIC Science & Technology

2017-10-01

Facility is a large-scale cascade that allows detailed flow field surveys and blade surface measurements.10–12 The facility has a continuous run ...structured grids at 2 flow conditions, cruise and takeoff, of the VSPT blade . Computations were run in parallel on a Department of Defense...RANS/LES) and Unsteady RANS Predictions of Separated Flow for a Variable-Speed Power- Turbine Blade Operating with Low Inlet Turbulence Levels

A principle of economy predicts the functional architecture of grid cells.

PubMed

Wei, Xue-Xin; Prentice, Jason; Balasubramanian, Vijay

2015-09-03

Grid cells in the brain respond when an animal occupies a periodic lattice of 'grid fields' during navigation. Grids are organized in modules with different periodicity. We propose that the grid system implements a hierarchical code for space that economizes the number of neurons required to encode location with a given resolution across a range equal to the largest period. This theory predicts that (i) grid fields should lie on a triangular lattice, (ii) grid scales should follow a geometric progression, (iii) the ratio between adjacent grid scales should be √e for idealized neurons, and lie between 1.4 and 1.7 for realistic neurons, (iv) the scale ratio should vary modestly within and between animals. These results explain the measured grid structure in rodents. We also predict optimal organization in one and three dimensions, the number of modules, and, with added assumptions, the ratio between grid periods and field widths.

Development of a hybrid 3-D hydrological model to simulate hillslopes and the regional unconfined aquifer system in Earth system models

NASA Astrophysics Data System (ADS)

Hazenberg, P.; Broxton, P. D.; Brunke, M.; Gochis, D.; Niu, G. Y.; Pelletier, J. D.; Troch, P. A. A.; Zeng, X.

2015-12-01

The terrestrial hydrological system, including surface and subsurface water, is an essential component of the Earth's climate system. Over the past few decades, land surface modelers have built one-dimensional (1D) models resolving the vertical flow of water through the soil column for use in Earth system models (ESMs). These models generally have a relatively coarse model grid size (~25-100 km) and only account for sub-grid lateral hydrological variations using simple parameterization schemes. At the same time, hydrologists have developed detailed high-resolution (~0.1-10 km grid size) three dimensional (3D) models and showed the importance of accounting for the vertical and lateral redistribution of surface and subsurface water on soil moisture, the surface energy balance and ecosystem dynamics on these smaller scales. However, computational constraints have limited the implementation of the high-resolution models for continental and global scale applications. The current work presents a hybrid-3D hydrological approach is presented, where the 1D vertical soil column model (available in many ESMs) is coupled with a high-resolution lateral flow model (h2D) to simulate subsurface flow and overland flow. H2D accounts for both local-scale hillslope and regional-scale unconfined aquifer responses (i.e. riparian zone and wetlands). This approach was shown to give comparable results as those obtained by an explicit 3D Richards model for the subsurface, but improves runtime efficiency considerably. The h3D approach is implemented for the Delaware river basin, where Noah-MP land surface model (LSM) is used to calculated vertical energy and water exchanges with the atmosphere using a 10km grid resolution. Noah-MP was coupled within the WRF-Hydro infrastructure with the lateral 1km grid resolution h2D model, for which the average depth-to-bedrock, hillslope width function and soil parameters were estimated from digital datasets. The ability of this h3D approach to simulate the hydrological dynamics of the Delaware River basin will be assessed by comparing the model results (both hydrological performance and numerical efficiency) with the standard setup of the NOAH-MP model and a high-resolution (1km) version of NOAH-MP, which also explicitly accounts for lateral subsurface and overland flow.

Tariff Considerations for Micro-Grids in Sub-Saharan Africa

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

Reber, Timothy J.; Booth, Samuel S.; Cutler, Dylan S.

This report examines some of the key drivers and considerations policymakers and decision makers face when deciding if and how to regulate electricity tariffs for micro-grids. Presenting a range of tariff options, from mandating some variety of national (uniform) tariff to allowing micro-grid developers and operators to set fully cost-reflective tariffs, it examines various benefits and drawbacks of each. In addition, the report and explores various types of cross-subsidies and other transitional forms of regulation that may offer a regulatory middle ground that can help balance the often competing goals of providing price control on electricity service in the namemore » of social good while still providing a means for investors to ensure high enough returns on their investment to attract the necessary capital financing to the market. Using the REopt tool developed by the U.S. Department of Energy's National Renewable Energy Laboratory to inform their study, the authors modeled a few representative micro-grid systems and the resultant levelized cost of electricity, lending context and scale to the consideration of these tariff questions. This simple analysis provides an estimate of the gap between current tariff regimes and the tariffs that would be necessary for developers to recover costs and attract investment, offering further insight into the potential scale of subsidies or other grants that may be required to enable micro-grid development under current regulatory structures. It explores potential options for addressing this gap while trying to balance This report examines some of the key drivers and considerations policymakers and decision makers face when deciding if and how to regulate electricity tariffs for micro-grids. Presenting a range of tariff options, from mandating some variety of national (uniform) tariff to allowing micro-grid developers and operators to set fully cost-reflective tariffs, it examines various benefits and drawbacks of each. In addition, the report and explores various types of cross-subsidies and other transitional forms of regulation that may offer a regulatory middle ground that can help balance the often competing goals of providing price control on electricity service in the name of social good while still providing a means for investors to ensure high enough returns on their investment to attract the necessary capital financing to the market. Using the REopt tool developed by the U.S. Department of Energy's National Renewable Energy Laboratory to inform their study, the authors modeled a few representative micro-grid systems and the resultant levelized cost of electricity, lending context and scale to the consideration of these tariff questions. This simple analysis provides an estimate of the gap between current tariff regimes and the tariffs that would be necessary for developers to recover costs and attract investment, offering further insight into the potential scale of subsidies or other grants that may be required to enable micro-grid development under current regulatory structures. It explores potential options for addressing this gap while trying to balance stakeholder needs, from subsidized national tariffs to lightly regulated cost-reflective tariffs to more of a compromise approach, such as different standards of regulation based on the size of a micro-grid.takeholder needs, from subsidized national tariffs to lightly regulated cost-reflective tariffs to more of a compromise approach, such as different standards of regulation based on the size of a micro-grid.« less

Helicon Plasma Source Optimization Studies for VASIMR

NASA Technical Reports Server (NTRS)

Goulding, R. H.; Baity, F. W.; Barber, G. C.; Carter, M. D.; ChangDiaz, F. R.; Pavarin, D.; Sparks, D. O.; Squire J. P.

1999-01-01

A helicon plasma source at Oak Ridge National Laboratory is being used to investigate operating scenarios relevant to the VASIMR (VAriable Specific Impulse Magnetoplasma Rocket). These include operation at high magnetic field (> = 0.4 T), high frequency (<= 30 MHz), high power (< = 3 kW), and with light ions (He+, H+). To date, He plasmas have been produced with n(sub e0) = 1.7 x 10(exp 19)/cu m (measured with an axially movable 4mm microwave interferometer), with Pin = I kW at f = 13.56 MHz and absolute value of B(sub 0) = 0.16 T. In the near future, diagnostics including a mass flow meter and a gridded energy analyzer array will be added to investigate fueling efficiency and the source power balance. The latest results, together with modeling results using the EMIR rf code, will be presented.

Very-high-Reynolds-number vortex dynamics via Coherent-vorticity-Preserving (CvP) Large-eddy simulations

NASA Astrophysics Data System (ADS)

Chapelier, Jean-Baptiste; Wasistho, Bono; Scalo, Carlo

2017-11-01

A new approach to Large-Eddy Simulation (LES) is introduced, where subgrid-scale (SGS) dissipation is applied proportionally to the degree of local spectral broadening, hence mitigated in regions dominated by large-scale vortical motion. The proposed CvP-LES methodology is based on the evaluation of the ratio of the test-filtered to resolved (or grid-filtered) enstrophy: σ = ξ ∧ / ξ . Values of σ = 1 indicate low sub-test-filter turbulent activity, justifying local deactivation of any subgrid-scale model. Values of σ < 1 span conditions ranging from incipient spectral broadening σ <= 1 , to equilibrium turbulence σ =σeq < 1 , where σeq is solely as a function of the test-to-grid filter-width ratio Δ ∧ / Δ , derived assuming a Kolmogorov's spectrum. Eddy viscosity is fully restored for σ <=σeq . The proposed approach removes unnecessary SGS dissipation, can be applied to any eddy-viscosity model, is algorithmically simple and computationally inexpensive. A CvP-LES of a pair of unstable helical vortices, representative of rotor-blade wake dynamics, show the ability of the method to sort the coherent motion from the small-scale dynamics. This work is funded by subcontract KSC-17-001 between Purdue University and Kord Technologies, Inc (Huntsville), under the US Navy Contract N68335-17-C-0159 STTR-Phase II, Purdue Proposal No. 00065007, Topic N15A-T002.

Numerical modeling of separated flows at moderate Reynolds numbers appropriate for turbine blades and unmanned aero vehicles

NASA Astrophysics Data System (ADS)

Castiglioni, Giacomo

Flows over airfoils and blades in rotating machinery, for unmanned and micro-aerial vehicles, wind turbines, and propellers consist of a laminar boundary layer near the leading edge that is often followed by a laminar separation bubble and transition to turbulence further downstream. Typical Reynolds averaged Navier-Stokes turbulence models are inadequate for such flows. Direct numerical simulation is the most reliable, but is also the most computationally expensive alternative. This work assesses the capability of immersed boundary methods and large eddy simulations to reduce the computational requirements for such flows and still provide high quality results. Two-dimensional and three-dimensional simulations of a laminar separation bubble on a NACA-0012 airfoil at Rec = 5x104 and at 5° of incidence have been performed with an immersed boundary code and a commercial code using body fitted grids. Several sub-grid scale models have been implemented in both codes and their performance evaluated. For the two-dimensional simulations with the immersed boundary method the results show good agreement with the direct numerical simulation benchmark data for the pressure coefficient Cp and the friction coefficient Cf, but only when using dissipative numerical schemes. There is evidence that this behavior can be attributed to the ability of dissipative schemes to damp numerical noise coming from the immersed boundary. For the three-dimensional simulations the results show a good prediction of the separation point, but an inaccurate prediction of the reattachment point unless full direct numerical simulation resolution is used. The commercial code shows good agreement with the direct numerical simulation benchmark data in both two and three-dimensional simulations, but the presence of significant, unquantified numerical dissipation prevents a conclusive assessment of the actual prediction capabilities of very coarse large eddy simulations with low order schemes in general cases. Additionally, a two-dimensional sweep of angles of attack from 0° to 5° is performed showing a qualitative prediction of the jump in lift and drag coefficients due to the appearance of the laminar separation bubble. The numerical dissipation inhibits the predictive capabilities of large eddy simulations whenever it is of the same order of magnitude or larger than the sub-grid scale dissipation. The need to estimate the numerical dissipation is most pressing for low-order methods employed by commercial computational fluid dynamics codes. Following the recent work of Schranner et al., the equations and procedure for estimating the numerical dissipation rate and the numerical viscosity in a commercial code are presented. The method allows for the computation of the numerical dissipation rate and numerical viscosity in the physical space for arbitrary sub-domains in a self-consistent way, using only information provided by the code in question. The method is first tested for a three-dimensional Taylor-Green vortex flow in a simple cubic domain and compared with benchmark results obtained using an accurate, incompressible spectral solver. Afterwards the same procedure is applied for the first time to a realistic flow configuration, specifically to the above discussed laminar separation bubble flow over a NACA 0012 airfoil. The method appears to be quite robust and its application reveals that for the code and the flow in question the numerical dissipation can be significantly larger than the viscous dissipation or the dissipation of the classical Smagorinsky sub-grid scale model, confirming the previously qualitative finding.

Global hydrodynamic modelling of flood inundation in continental rivers: How can we achieve it?

NASA Astrophysics Data System (ADS)

Yamazaki, D.

2016-12-01

Global-scale modelling of river hydrodynamics is essential for understanding global hydrological cycle, and is also required in interdisciplinary research fields . Global river models have been developed continuously for more than two decades, but modelling river flow at a global scale is still a challenging topic because surface water movement in continental rivers is a multi-spatial-scale phenomena. We have to consider the basin-wide water balance (>1000km scale), while hydrodynamics in river channels and floodplains is regulated by much smaller-scale topography (<100m scale). For example, heavy precipitation in upstream regions may later cause flooding in farthest downstream reaches. In order to realistically simulate the timing and amplitude of flood wave propagation for a long distance, consideration of detailed local topography is unavoidable. I have developed the global hydrodynamic model CaMa-Flood to overcome this scale-discrepancy of continental river flow. The CaMa-Flood divides river basins into multiple "unit-catchments", and assumes the water level is uniform within each unit-catchment. One unit-catchment is assigned to each grid-box defined at the typical spatial resolution of global climate models (10 100 km scale). Adopting a uniform water level in a >10km river segment seems to be a big assumption, but it is actually a good approximation for hydrodynamic modelling of continental rivers. The number of grid points required for global hydrodynamic simulations is largely reduced by this "unit-catchment assumption". Alternative to calculating 2-dimensional floodplain flows as in regional flood models, the CaMa-Flood treats floodplain inundation in a unit-catchment as a sub-grid physics. The water level and inundated area in each unit-catchment are diagnosed from water volume using topography parameters derived from high-resolution digital elevation models. Thus, the CaMa-Flood is at least 1000 times computationally more efficient compared to regional flood inundation models while the reality of simulated flood dynamics is kept. I will explain in detail how the CaMa-Flood model has been constructed from high-resolution topography datasets, and how the model can be used for various interdisciplinary applications.

Using High Resolution Regional Climate Models to Quantify the Snow Albedo Feedback in a Region of Complex Terrain

NASA Astrophysics Data System (ADS)

Letcher, T.; Minder, J. R.

2015-12-01

High resolution regional climate models are used to characterize and quantify the snow albedo feedback (SAF) over the complex terrain of the Colorado Headwaters region. Three pairs of 7-year control and pseudo global warming simulations (with horizontal grid spacings of 4, 12, and 36 km) are used to study how the SAF modifies the regional climate response to a large-scale thermodynamic perturbation. The SAF substantially enhances warming within the Headwaters domain, locally as much as 5 °C in regions of snow loss. The SAF also increases the inter-annual variability of the springtime warming within Headwaters domain under the perturbed climate. Linear feedback analysis is used quantify the strength of the SAF. The SAF attains a maximum value of 4 W m-2 K-1 during April when snow loss coincides with strong incoming solar radiation. On sub-seasonal timescales, simulations at 4 km and 12 km horizontal grid-spacing show good agreement in the strength and timing of the SAF, whereas a 36km simulation shows greater discrepancies that are tired to differences in snow accumulation and ablation caused by smoother terrain. An analysis of the regional energy budget shows that transport by atmospheric motion acts as a negative feedback to regional warming, damping the effects of the SAF. On the mesoscale, this transport causes non-local warming in locations with no snow. The methods presented here can be used generally to quantify the role of the SAF in other regional climate modeling experiments.

The Influence of the 2006 Indonesian Biomass Burning Aerosols on Tropical Dynamics Studied with the GEOS-5 AGCM

NASA Technical Reports Server (NTRS)

Ott, Lesley; Duncan, Bryan; Pawson, Steven; Colarco, Peter; Chin, Mian; Randles, Cynthia; Diehl, Thomas; Nielsen, Eric

2009-01-01

The direct and semi-direct effects of aerosols produced by Indonesian biomass burning (BB) during August November 2006 on tropical dynamics have been examined using NASA's Goddard Earth Observing System, Version 5 (GEOS-5) atmospheric general circulation model (AGCM). The AGCM includes CO, which is transported by resolved and sub-grid processes and subject to a linearized chemical loss rate. Simulations were driven by two sets of aerosol forcing fields calculated offline, one that included Indonesian BB aerosol emissions and one that did not. In order to separate the influence of the aerosols from internal model variability, the means of two ten-member ensembles were compared. Diabatic heating from BB aerosols increased temperatures over Indonesia between 150 and 400 hPa. The higher temperatures resulted in strong increases in upward grid-scale vertical motion, which increased water vapor and CO over Indonesia. In October, the largest increases in water vapor were found in the mid-troposphere (25%) while the largest increases in CO occurred just below the tropopause (80 ppbv or 50%). Diabatic heating from the Indonesian BB aerosols caused CO to increase by 9% throughout the tropical tropopause layer in November and 5% in the lower stratosphere in December. The results demonstrate that aerosol heating plays an important role in the transport of BB pollution and troposphere-to-stratosphere transport. Changes in vertical motion and cloudiness induced by aerosol heating can also alter the transport and phase of water vapor in the upper troposphere/lower stratosphere.

Some effects of horizontal discretization on linear baroclinic and symmetric instabilities

NASA Astrophysics Data System (ADS)

Barham, William; Bachman, Scott; Grooms, Ian

2018-05-01

The effects of horizontal discretization on linear baroclinic and symmetric instabilities are investigated by analyzing the behavior of the hydrostatic Eady problem in ocean models on the B and C grids. On the C grid a spurious baroclinic instability appears at small wavelengths. This instability does not disappear as the grid scale decreases; instead, it simply moves to smaller horizontal scales. The peak growth rate of the spurious instability is independent of the grid scale as the latter decreases. It is equal to cf /√{Ri} where Ri is the balanced Richardson number, f is the Coriolis parameter, and c is a nondimensional constant that depends on the Richardson number. As the Richardson number increases c increases towards an upper bound of approximately 1/2; for large Richardson numbers the spurious instability is faster than the Eady instability. To suppress the spurious instability it is recommended to use fourth-order centered tracer advection along with biharmonic viscosity and diffusion with coefficients (Δx) 4 f /(32√{Ri}) or larger where Δx is the grid scale. On the B grid, the growth rates of baroclinic and symmetric instabilities are too small, and converge upwards towards the correct values as the grid scale decreases; no spurious instabilities are observed. In B grid models at eddy-permitting resolution, the reduced growth rate of baroclinic instability may contribute to partially-resolved eddies being too weak. On the C grid the growth rate of symmetric instability is better (larger) than on the B grid, and converges upwards towards the correct value as the grid scale decreases.

Effects of heat exchanger tubes on hydrodynamics and CO 2 capture of a sorbent-based fluidized bed reactor

DOE PAGES

Lai, Canhai; Xu, Zhijie; Li, Tingwen; ...

2017-08-05

In virtual design and scale up of pilot-scale carbon capture systems, the coupled reactive multiphase flow problem must be solved to predict the adsorber's performance and capture efficiency under various operation conditions. This paper focuses on the detailed computational fluid dynamics (CFD) modeling of a pilot-scale fluidized bed adsorber equipped with vertical cooling tubes. Multiphase Flow with Interphase eXchanges (MFiX), an open-source multiphase flow CFD solver, is used for the simulations with custom code to simulate the chemical reactions and filtered sub-grid models to capture the effect of the unresolved details in the coarser mesh for simulations with reasonable accuracymore » and manageable computational effort. Previously developed filtered models for horizontal cylinder drag, heat transfer, and reaction kinetics have been modified to derive the 2D filtered models representing vertical cylinders in the coarse-grid CFD simulations. The effects of the heat exchanger configurations (i.e., horizontal or vertical tubes) on the adsorber's hydrodynamics and CO 2 capture performance are then examined. A one-dimensional three-region process model is briefly introduced for comparison purpose. The CFD model matches reasonably well with the process model while provides additional information about the flow field that is not available with the process model.« less

SDCLIREF - A sub-daily gridded reference dataset

NASA Astrophysics Data System (ADS)

Wood, Raul R.; Willkofer, Florian; Schmid, Franz-Josef; Trentini, Fabian; Komischke, Holger; Ludwig, Ralf

2017-04-01

Climate change is expected to impact the intensity and frequency of hydrometeorological extreme events. In order to adequately capture and analyze extreme rainfall events, in particular when assessing flood and flash flood situations, data is required at high spatial and sub-daily resolution which is often not available in sufficient density and over extended time periods. The ClimEx project (Climate Change and Hydrological Extreme Events) addresses the alteration of hydrological extreme events under climate change conditions. In order to differentiate between a clear climate change signal and the limits of natural variability, unique Single-Model Regional Climate Model Ensembles (CRCM5 driven by CanESM2, RCP8.5) were created for a European and North-American domain, each comprising 50 members of 150 years (1951-2100). In combination with the CORDEX-Database, this newly created ClimEx-Ensemble is a one-of-a-kind model dataset to analyze changes of sub-daily extreme events. For the purpose of bias-correcting the regional climate model ensembles as well as for the baseline calibration and validation of hydrological catchment models, a new sub-daily (3h) high-resolution (500m) gridded reference dataset (SDCLIREF) was created for a domain covering the Upper Danube and Main watersheds ( 100.000km2). As the sub-daily observations lack a continuous time series for the reference period 1980-2010, the need for a suitable method to bridge the gap of the discontinuous time series arouse. The Method of Fragments (Sharma and Srikanthan (2006); Westra et al. (2012)) was applied to transform daily observations to sub-daily rainfall events to extend the time series and densify the station network. Prior to applying the Method of Fragments and creating the gridded dataset using rigorous interpolation routines, data collection of observations, operated by several institutions in three countries (Germany, Austria, Switzerland), and the subsequent quality control of the observations was carried out. Among others, the quality control checked for steps, extensive dry seasons, temporal consistency and maximum hourly values. The resulting SDCLIREF dataset provides a robust precipitation reference for hydrometeorological applications in unprecedented high spatio-temporal resolution. References: Sharma, A.; Srikanthan, S. (2006): Continuous Rainfall Simulation: A Nonparametric Alternative. In: 30th Hydrology and Water Resources Symposium 4-7 December 2006, Launceston, Tasmania. Westra, S.; Mehrotra, R.; Sharma, A.; Srikanthan, R. (2012): Continuous rainfall simulation. 1. A regionalized subdaily disaggregation approach. In: Water Resour. Res. 48 (1). DOI: 10.1029/2011WR010489.

Numerical simulation and prediction of coastal ocean circulation

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

Chen, P.

1992-01-01

Numerical simulation and prediction of coastal ocean circulation have been conducted in three cases. 1. A process-oriented modeling study is conducted to study the interaction of a western boundary current (WBC) with coastal water, and its responses to upstream topographic irregularities. It is hypothesized that the interaction of propagating WBC frontal waves and topographic Rossby waves are responsible for upstream variability. 2. A simulation of meanders and eddies in the Norwegian Coastal Current (NCC) for February and March of 1988 is conducted with a newly developed nested dynamic interactive model. The model employs a coarse-grid, large domain to account formore » non-local forcing and a fine-grid nested domain to resolve meanders and eddies. The model is forced by wind stresses, heat fluxes and atmospheric pressure corresponding Feb/March of 1988, and accounts for river/fjord discharges, open ocean inflow and outflow, and M[sub 2] tides. The simulation reproduced fairly well the observed circulation, tides, and salinity features in the North Sea, Norwegian Trench and NCC region in the large domain and fairly realistic meanders and eddies in the NCC in the nested region. 3. A methodology for practical coastal ocean hindcast/forecast is developed, taking advantage of the disparate time scales of various forcing and considering wind to be the dominant factor in affecting density fluctuation in the time scale of 1 to 10 days. The density field obtained from a prognostic simulation is analyzed by the empirical orthogonal function method (EOF), and correlated with the wind; these information are then used to drive a circulation model which excludes the density calculation. The method is applied to hindcast the circulation in the New York Bight for spring and summer season of 1988. The hindcast fields compare favorably with the results obtained from the prognostic circulation model.« less

A Molecular Dynamics Simulation of the Turbulent Couette Minimal Flow Unit

NASA Astrophysics Data System (ADS)

Smith, Edward

2016-11-01

What happens to turbulent motions below the Kolmogorov length scale? In order to explore this question, a 300 million molecule Molecular Dynamics (MD) simulation is presented for the minimal Couette channel in which turbulence can be sustained. The regeneration cycle and turbulent statistics show excellent agreement to continuum based computational fluid dynamics (CFD) at Re=400. As MD requires only Newton's laws and a form of inter-molecular potential, it captures a much greater range of phenomena without requiring the assumptions of Newton's law of viscosity, thermodynamic equilibrium, fluid isotropy or the limitation of grid resolution. The fundamental nature of MD means it is uniquely placed to explore the nature of turbulent transport. A number of unique insights from MD are presented, including energy budgets, sub-grid turbulent energy spectra, probability density functions, Lagrangian statistics and fluid wall interactions. EPSRC Post Doctoral Prize Fellowship.

A NEW THREE-DIMENSIONAL SOLAR WIND MODEL IN SPHERICAL COORDINATES WITH A SIX-COMPONENT GRID

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

Feng, Xueshang; Zhang, Man; Zhou, Yufen, E-mail: fengx@spaceweather.ac.cn

In this paper, we introduce a new three-dimensional magnetohydrodynamics numerical model to simulate the steady state ambient solar wind from the solar surface to 215 R {sub s} or beyond, and the model adopts a splitting finite-volume scheme based on a six-component grid system in spherical coordinates. By splitting the magnetohydrodynamics equations into a fluid part and a magnetic part, a finite volume method can be used for the fluid part and a constrained-transport method able to maintain the divergence-free constraint on the magnetic field can be used for the magnetic induction part. This new second-order model in space andmore » time is validated when modeling the large-scale structure of the solar wind. The numerical results for Carrington rotation 2064 show its ability to produce structured solar wind in agreement with observations.« less

Wall modeled LES of wind turbine wakes with geometrical effects

NASA Astrophysics Data System (ADS)

Bricteux, Laurent; Benard, Pierre; Zeoli, Stephanie; Moureau, Vincent; Lartigue, Ghislain; Vire, Axelle

2017-11-01

This study focuses on prediction of wind turbine wakes when geometrical effects such as nacelle, tower, and built environment, are taken into account. The aim is to demonstrate the ability of a high order unstructured solver called YALES2 to perform wall modeled LES of wind turbine wake turbulence. The wind turbine rotor is modeled using an Actuator Line Model (ALM) while the geometrical details are explicitly meshed thanks to the use of an unstructured grid. As high Reynolds number flows are considered, sub-grid scale models as well as wall modeling are required. The first test case investigated concerns a wind turbine flow located in a wind tunnel that allows to validate the proposed methodology using experimental data. The second test case concerns the simulation of a wind turbine wake in a complex environment (e.g. a Building) using realistic turbulent inflow conditions.

Hardware-in-the-loop grid simulator system and method

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

Fox, John Curtiss; Collins, Edward Randolph; Rigas, Nikolaos

A hardware-in-the-loop (HIL) electrical grid simulation system and method that combines a reactive divider with a variable frequency converter to better mimic and control expected and unexpected parameters in an electrical grid. The invention provides grid simulation in a manner to allow improved testing of variable power generators, such as wind turbines, and their operation once interconnected with an electrical grid in multiple countries. The system further comprises an improved variable fault reactance (reactive divider) capable of providing a variable fault reactance power output to control a voltage profile, therein creating an arbitrary recovery voltage. The system further comprises anmore » improved isolation transformer designed to isolate zero-sequence current from either a primary or secondary winding in a transformer or pass the zero-sequence current from a primary to a secondary winding.« less

Land-Atmosphere Coupling in the Multi-Scale Modelling Framework

NASA Astrophysics Data System (ADS)

Kraus, P. M.; Denning, S.

2015-12-01

The Multi-Scale Modeling Framework (MMF), in which cloud-resolving models (CRMs) are embedded within general circulation model (GCM) gridcells to serve as the model's cloud parameterization, has offered a number of benefits to GCM simulations. The coupling of these cloud-resolving models directly to land surface model instances, rather than passing averaged atmospheric variables to a single instance of a land surface model, the logical next step in model development, has recently been accomplished. This new configuration offers conspicuous improvements to estimates of precipitation and canopy through-fall, but overall the model exhibits warm surface temperature biases and low productivity.This work presents modifications to a land-surface model that take advantage of the new multi-scale modeling framework, and accommodate the change in spatial scale from a typical GCM range of ~200 km to the CRM grid-scale of 4 km.A parameterization is introduced to apportion modeled surface radiation into direct-beam and diffuse components. The diffuse component is then distributed among the land-surface model instances within each GCM cell domain. This substantially reduces the number excessively low light values provided to the land-surface model when cloudy conditions are modeled in the CRM, associated with its 1-D radiation scheme. The small spatial scale of the CRM, ~4 km, as compared with the typical ~200 km GCM scale, provides much more realistic estimates of precipitation intensity, this permits the elimination of a model parameterization of canopy through-fall. However, runoff at such scales can no longer be considered as an immediate flow to the ocean. Allowing sub-surface water flow between land-surface instances within the GCM domain affords better realism and also reduces temperature and productivity biases.The MMF affords a number of opportunities to land-surface modelers, providing both the advantages of direct simulation at the 4 km scale and a much reduced conceptual gap between model resolution and parameterized processes.

Evaluation of tropical channel refinement using MPAS-A aquaplanet simulations

DOE PAGES

Martini, Matus N.; Gustafson, Jr., William I.; O'Brien, Travis A.; ...

2015-09-13

Climate models with variable-resolution grids offer a computationally less expensive way to provide more detailed information at regional scales and increased accuracy for processes that cannot be resolved by a coarser grid. This study uses the Model for Prediction Across Scales–Atmosphere (MPAS22A), consisting of a nonhydrostatic dynamical core and a subset of Advanced Research Weather Research and Forecasting (ARW-WRF) model atmospheric physics that have been modified to include the Community Atmosphere Model version 5 (CAM5) cloud fraction parameterization, to investigate the potential benefits of using increased resolution in an tropical channel. The simulations are performed with an idealized aquaplanet configurationmore » using two quasi-uniform grids, with 30 km and 240 km grid spacing, and two variable-resolution grids spanning the same grid spacing range; one with a narrow (20°S–20°N) and one with a wide (30°S–30°N) tropical channel refinement. Results show that increasing resolution in the tropics impacts both the tropical and extratropical circulation. Compared to the quasi-uniform coarse grid, the narrow-channel simulation exhibits stronger updrafts in the Ferrel cell as well as in the middle of the upward branch of the Hadley cell. The wider tropical channel has a closer correspondence to the 30 km quasi-uniform simulation. However, the total atmospheric poleward energy transports are similar in all simulations. The largest differences are in the low-level cloudiness. The refined channel simulations show improved tropical and extratropical precipitation relative to the global 240 km simulation when compared to the global 30 km simulation. All simulations have a single ITCZ. Furthermore, the relatively small differences in mean global and tropical precipitation rates among the simulations are a promising result, and the evidence points to the tropical channel being an effective method for avoiding the extraneous numerical artifacts seen in earlier studies that only refined portion of the tropics.« less

Discerning spatial and temporal LAI and clear-sky FAPAR variability during summer at the Toolik Lake vegetation monitoring grid (North Slope, Alaska)

NASA Astrophysics Data System (ADS)

Heim, B.; Beamish, A. L.; Walker, D. A.; Epstein, H. E.; Sachs, T.; Chabrillat, S.; Buchhorn, M.; Prakash, A.

2016-12-01

Ground data for the validation of satellite-derived terrestrial Essential Climate Variables (ECVs) at high latitudes are sparse. Also for regional model evaluation (e.g. climate models, land surface models, permafrost models), we lack accurate ranges of terrestrial ground data and face the problem of a large mismatch in scale. Within the German research programs `Regional Climate Change' (REKLIM) and the Environmental Mapping and Analysis Program (EnMAP), we conducted a study on ground data representativeness for vegetation-related variables within a monitoring grid at the Toolik Lake Long-Term Ecological Research station; the Toolik Lake station lies in the Kuparuk River watershed on the North Slope of the Brooks Mountain Range in Alaska. The Toolik Lake grid covers an area of 1 km2 containing Eight five grid points spaced 100 meters apart. Moist acidic tussock tundra is the most dominant vegetation type within the grid. Eight five permanent 1 m2 plots were also established to be representative of the individual gridpoints. Researchers from the University of Alaska Fairbanks have undertaken assessments at these plots, including Leaf Area Index (LAI) and field spectrometry to derive the Normalized Difference Vegetation Index (NDVI). During summer 2016, we conducted field spectrometry and LAI measurements at selected plots during early, peak and late summer. We experimentally measured LAI on more spatially extensive Elementary Sampling Units (ESUs) to investigate the spatial representativeness of the permanent 1 m2 plots and to map ESUs for various tundra types. LAI measurements are potentially influenced by landscape-inherent microtopography, sparse vascular plant cover, and dead woody matter. From field spectrometer measurements, we derived a clear-sky mid-day Fraction of Absorbed Photosynthetically Active Radiation (FAPAR). We will present the first data analyses comparing FAPAR and LAI, and maps of biophysically-focused ESUs for evaluation of the use of remote sensing data to estimate these ecosystem properties.

User's Guide - WRF Lightning Assimilation

EPA Pesticide Factsheets

This document describes how to run WRF with the lightning assimilation technique described in Heath et al. (2016). The assimilation method uses gridded lightning data to trigger and suppress sub-grid deep convection in Kain-Fritsch.

Spatiotemporal Variability of Drought in Pakistan through High-Resolution Daily Gridded In-Situ Observations

NASA Astrophysics Data System (ADS)

Bashir, F.; Zeng, X.; Gupta, H. V.; Hazenberg, P.

2017-12-01

Drought as an extreme event may have far reaching socio-economic impacts on agriculture based economies like Pakistan. Effective assessment of drought requires high resolution spatiotemporally continuous hydrometeorological information. For this purpose, new in-situ daily observations based gridded analyses of precipitation, maximum, minimum and mean temperature and diurnal temperature range are developed, that covers whole Pakistan on 0.01º latitude-longitude for a 54-year period (1960-2013). The number of participating meteorological observatories used in these gridded analyses is 2 to 6 times greater than any other similar product available. This data set is used to identify extreme wet and dry periods and their spatial patterns across Pakistan using Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI). Periodicity of extreme events is estimated at seasonal to decadal scales. Spatiotemporal signatures of drought incidence indicating its extent and longevity in different areas may help water resource managers and policy makers to mitigate the severity of the drought and its impact on food security through suitable adaptive techniques. Moreover, this high resolution gridded in-situ observations of precipitation and temperature is used to evaluate other coarser-resolution gridded products.

Measured and modeled dry deposition velocities over the ESCOMPTE area

NASA Astrophysics Data System (ADS)

Michou, M.; Laville, P.; Serça, D.; Fotiadi, A.; Bouchou, P.; Peuch, V.-H.

2005-03-01

Measurements of the dry deposition velocity of ozone have been made by the eddy correlation method during ESCOMPTE (Etude sur Site pour COntraindre les Modèles de Pollution atmosphérique et de Transport d'Emissions). The strong local variability of natural ecosystems was sampled over several weeks in May, June and July 2001 for four sites with varying surface characteristics. The sites included a maize field, a Mediterranean forest, a Mediterranean shrub-land, and an almost bare soil. Measurements of nitrogen oxide deposition fluxes by the relaxed eddy correlation method have also been carried out at the same bare soil site. An evaluation of the deposition velocities computed by the surface module of the multi-scale Chemistry and Transport Model MOCAGE is presented. This module relies on a resistance approach, with a detailed treatment of the stomatal contribution to the surface resistance. Simulations at the finest model horizontal resolution (around 10 km) are compared to observations. If the seasonal variations are in agreement with the literature, comparisons between raw model outputs and observations, at the different measurement sites and for the specific observing periods, are contrasted. As the simulated meteorology at the scale of 10 km nicely captures the observed situations, the default set of surface characteristics (averaged at the resolution of a grid cell) appears to be one of the main reasons for the discrepancies found with observations. For each case, sensitivity studies have been performed in order to see the impact of adjusting the surface characteristics to the observed ones, when available. Generally, a correct agreement with the observations of deposition velocities is obtained. This advocates for a sub-grid scale representation of surface characteristics for the simulation of dry deposition velocities over such a complex area. Two other aspects appear in the discussion. Firstly, the strong influence of the soil water content to the plant response, specifically in conditions of stress, is confirmed. Second, we point out the difficulty in interpreting measurements of nitrogen oxide deposition velocities: a synergetic approach combining measurements and modeling is practical.

Discrete variable representation in electronic structure theory: quadrature grids for least-squares tensor hypercontraction.

PubMed

Parrish, Robert M; Hohenstein, Edward G; Martínez, Todd J; Sherrill, C David

2013-05-21

We investigate the application of molecular quadratures obtained from either standard Becke-type grids or discrete variable representation (DVR) techniques to the recently developed least-squares tensor hypercontraction (LS-THC) representation of the electron repulsion integral (ERI) tensor. LS-THC uses least-squares fitting to renormalize a two-sided pseudospectral decomposition of the ERI, over a physical-space quadrature grid. While this procedure is technically applicable with any choice of grid, the best efficiency is obtained when the quadrature is tuned to accurately reproduce the overlap metric for quadratic products of the primary orbital basis. Properly selected Becke DFT grids can roughly attain this property. Additionally, we provide algorithms for adopting the DVR techniques of the dynamics community to produce two different classes of grids which approximately attain this property. The simplest algorithm is radial discrete variable representation (R-DVR), which diagonalizes the finite auxiliary-basis representation of the radial coordinate for each atom, and then combines Lebedev-Laikov spherical quadratures and Becke atomic partitioning to produce the full molecular quadrature grid. The other algorithm is full discrete variable representation (F-DVR), which uses approximate simultaneous diagonalization of the finite auxiliary-basis representation of the full position operator to produce non-direct-product quadrature grids. The qualitative features of all three grid classes are discussed, and then the relative efficiencies of these grids are compared in the context of LS-THC-DF-MP2. Coarse Becke grids are found to give essentially the same accuracy and efficiency as R-DVR grids; however, the latter are built from explicit knowledge of the basis set and may guide future development of atom-centered grids. F-DVR is found to provide reasonable accuracy with markedly fewer points than either Becke or R-DVR schemes.