High-resolution modelling of atmospheric dispersion of dense gas using TWODEE-2.1: application to the 1986 Lake Nyos limnic eruption

NASA Astrophysics Data System (ADS)

Folch, Arnau; Barcons, Jordi; Kozono, Tomofumi; Costa, Antonio

2017-06-01

Atmospheric dispersal of a gas denser than air can threat the environment and surrounding communities if the terrain and meteorological conditions favour its accumulation in topographic depressions, thereby reaching toxic concentration levels. Numerical modelling of atmospheric gas dispersion constitutes a useful tool for gas hazard assessment studies, essential for planning risk mitigation actions. In complex terrains, microscale winds and local orographic features can have a strong influence on the gas cloud behaviour, potentially leading to inaccurate results if not captured by coarser-scale modelling. We introduce a methodology for microscale wind field characterisation based on transfer functions that couple a mesoscale numerical weather prediction model with a microscale computational fluid dynamics (CFD) model for the atmospheric boundary layer. The resulting time-dependent high-resolution microscale wind field is used as input for a shallow-layer gas dispersal model (TWODEE-2.1) to simulate the time evolution of CO2 gas concentration at different heights above the terrain. The strategy is applied to review simulations of the 1986 Lake Nyos event in Cameroon, where a huge CO2 cloud released by a limnic eruption spread downslopes from the lake, suffocating thousands of people and animals across the Nyos and adjacent secondary valleys. Besides several new features introduced in the new version of the gas dispersal code (TWODEE-2.1), we have also implemented a novel impact criterion based on the percentage of human fatalities depending on CO2 concentration and exposure time. New model results are quantitatively validated using the reported percentage of fatalities at several locations. The comparison with previous simulations that assumed coarser-scale steady winds and topography illustrates the importance of high-resolution modelling in complex terrains.

Development of High-Resolution Dynamic Dust Source Function - A Case Study with a Strong Dust Storm in a Regional Model

NASA Technical Reports Server (NTRS)

Kim, Dongchul; Chin, Mian; Kemp, Eric M.; Tao, Zhining; Peters-Lidard, Christa D.; Ginoux, Paul

2017-01-01

A high-resolution dynamic dust source has been developed in the NASA Unified-Weather Research and Forecasting (NU-WRF) model to improve the existing coarse static dust source. In the new dust source map, topographic depression is in 1-km resolution and surface bareness is derived using the Normalized Difference Vegetation Index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS). The new dust source better resolves the complex topographic distribution over the Western United States where its magnitude is higher than the existing, coarser resolution static source. A case study is conducted with an extreme dust storm that occurred in Phoenix, Arizona in 0203 UTC July 6, 2011. The NU-WRF model with the new high-resolution dynamic dust source is able to successfully capture the dust storm, which was not achieved with the old source identification. However the case study also reveals several challenges in reproducing the time evolution of the short-lived, extreme dust storm events.

Development of High-Resolution Dynamic Dust Source Function -A Case Study with a Strong Dust Storm in a Regional Model

PubMed Central

Kim, Dongchul; Chin, Mian; Kemp, Eric M.; Tao, Zhining; Peters-Lidard, Christa D.; Ginoux, Paul

2018-01-01

A high-resolution dynamic dust source has been developed in the NASA Unified-Weather Research and Forecasting (NU-WRF) model to improve the existing coarse static dust source. In the new dust source map, topographic depression is in 1-km resolution and surface bareness is derived using the Normalized Difference Vegetation Index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS). The new dust source better resolves the complex topographic distribution over the Western United States where its magnitude is higher than the existing, coarser resolution static source. A case study is conducted with an extreme dust storm that occurred in Phoenix, Arizona in 02-03 UTC July 6, 2011. The NU-WRF model with the new high-resolution dynamic dust source is able to successfully capture the dust storm, which was not achieved with the old source identification. However the case study also reveals several challenges in reproducing the time evolution of the short-lived, extreme dust storm events. PMID:29632432

Development of High-Resolution Dynamic Dust Source Function -A Case Study with a Strong Dust Storm in a Regional Model.

PubMed

Kim, Dongchul; Chin, Mian; Kemp, Eric M; Tao, Zhining; Peters-Lidard, Christa D; Ginoux, Paul

2017-06-01

A high-resolution dynamic dust source has been developed in the NASA Unified-Weather Research and Forecasting (NU-WRF) model to improve the existing coarse static dust source. In the new dust source map, topographic depression is in 1-km resolution and surface bareness is derived using the Normalized Difference Vegetation Index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS). The new dust source better resolves the complex topographic distribution over the Western United States where its magnitude is higher than the existing, coarser resolution static source. A case study is conducted with an extreme dust storm that occurred in Phoenix, Arizona in 02-03 UTC July 6, 2011. The NU-WRF model with the new high-resolution dynamic dust source is able to successfully capture the dust storm, which was not achieved with the old source identification. However the case study also reveals several challenges in reproducing the time evolution of the short-lived, extreme dust storm events.

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

USGS Publications Warehouse

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

2015-01-01

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

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

PubMed Central

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

2015-01-01

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

Impact of surface coupling grids on tropical cyclone extremes in high-resolution atmospheric simulations

DOE PAGES

Zarzycki, Colin M.; Reed, Kevin A.; Bacmeister, Julio T.; ...

2016-02-25

This article discusses the sensitivity of tropical cyclone climatology to surface coupling strategy in high-resolution configurations of the Community Earth System Model. Using two supported model setups, we demonstrate that the choice of grid on which the lowest model level wind stress and surface fluxes are computed may lead to differences in cyclone strength in multi-decadal climate simulations, particularly for the most intense cyclones. Using a deterministic framework, we show that when these surface quantities are calculated on an ocean grid that is coarser than the atmosphere, the computed frictional stress is misaligned with wind vectors in individual atmospheric gridmore » cells. This reduces the effective surface drag, and results in more intense cyclones when compared to a model configuration where the ocean and atmosphere are of equivalent resolution. Our results demonstrate that the choice of computation grid for atmosphere–ocean interactions is non-negligible when considering climate extremes at high horizontal resolution, especially when model components are on highly disparate grids.« less

Quantifying scaling effects on satellite-derived forest area estimates for the conterminous USA

Treesearch

Daolan Zheng; L.S. Heath; M.J. Ducey; J.E. Smith

2009-01-01

We quantified the scaling effects on forest area estimates for the conterminous USA using regression analysis and the National Land Cover Dataset 30m satellite-derived maps in 2001 and 1992. The original data were aggregated to: (1) broad cover types (forest vs. non-forest); and (2) coarser resolutions (1km and 10 km). Standard errors of the model estimates were 2.3%...

Sensitivity of mesoscale-model forecast skill to some initial-data characteristics, data density, data position, analysis procedure and measurement error

NASA Technical Reports Server (NTRS)

Warner, Thomas T.; Key, Lawrence E.; Lario, Annette M.

1989-01-01

The effects of horizontal and vertical data resolution, data density, data location, different objective analysis algorithms, and measurement error on mesoscale-forecast accuracy are studied with observing-system simulation experiments. Domain-averaged errors are shown to generally decrease with time. It is found that the vertical distribution of error growth depends on the initial vertical distribution of the error itself. Larger gravity-inertia wave noise is produced in forecasts with coarser vertical data resolution. The use of a low vertical resolution observing system with three data levels leads to more forecast errors than moderate and high vertical resolution observing systems with 8 and 14 data levels. Also, with poor vertical resolution in soundings, the initial and forecast errors are not affected by the horizontal data resolution.

Tracking fronts in solutions of the shallow-water equations

NASA Astrophysics Data System (ADS)

Bennett, Andrew F.; Cummins, Patrick F.

1988-02-01

A front-tracking algorithm of Chern et al. (1986) is tested on the shallow-water equations, using the Parrett and Cullen (1984) and Williams and Hori (1970) initial state, consisting of smooth finite amplitude waves depending on one space dimension alone. At high resolution the solution is almost indistinguishable from that obtained with the Glimm algorithm. The latter is known to converge to the true frontal solution, but is 20 times less efficient at the same resolution. The solutions obtained using the front-tracking algorithm at 8 times coarser resolution are quite acceptable, indicating a very substantial gain in efficiency, which encourages application in realistic ocean models possessing two or three space dimensions.

High-resolution space-time characterization of convective rain cells: implications on spatial aggregation and temporal sampling operated by coarser resolution instruments

NASA Astrophysics Data System (ADS)

Marra, Francesco; Morin, Efrat

2017-04-01

Forecasting the occurrence of flash floods and debris flows is fundamental to save lives and protect infrastructures and properties. These natural hazards are generated by high-intensity convective storms, on space-time scales that cannot be properly monitored by conventional instrumentation. Consequently, a number of early-warning systems are nowadays based on remote sensing precipitation observations, e.g. from weather radars or satellites, that proved effective in a wide range of situations. However, the uncertainty affecting rainfall estimates represents an important issue undermining the operational use of early-warning systems. The uncertainty related to remote sensing estimates results from (a) an instrumental component, intrinsic of the measurement operation, and (b) a discretization component, caused by the discretization of the continuous rainfall process. Improved understanding on these sources of uncertainty will provide crucial information to modelers and decision makers. This study aims at advancing knowledge on the (b) discretization component. To do so, we take advantage of an extremely-high resolution X-Band weather radar (60 m, 1 min) recently installed in the Eastern Mediterranean. The instrument monitors a semiarid to arid transition area also covered by an accurate C-Band weather radar and by a relatively sparse rain gauge network ( 1 gauge/ 450 km2). Radar quantitative precipitation estimation includes corrections reducing the errors due to ground echoes, orographic beam blockage and attenuation of the signal in heavy rain. Intense, convection-rich, flooding events recently occurred in the area serve as study cases. We (i) describe with very high detail the spatiotemporal characteristics of the convective cores, and (ii) quantify the uncertainty due to spatial aggregation (spatial discretization) and temporal sampling (temporal discretization) operated by coarser resolution remote sensing instruments. We show that instantaneous rain intensity decreases very steeply with the distance from the core of convection with intensity observed at 1 km (2 km) being 10-40% (1-20%) of the core value. The use of coarser temporal resolutions leads to gaps in the observed rainfall and even relatively high resolutions (5 min) can be affected by the problem. We conclude providing to the final user indications about the effects of the discretization component of estimation uncertainty and suggesting viable ways to decrease them.

Spatial Modeling and Uncertainty Assessment of Fine Scale Surface Processes Based on Coarse Terrain Elevation Data

NASA Astrophysics Data System (ADS)

Rasera, L. G.; Mariethoz, G.; Lane, S. N.

2017-12-01

Frequent acquisition of high-resolution digital elevation models (HR-DEMs) over large areas is expensive and difficult. Satellite-derived low-resolution digital elevation models (LR-DEMs) provide extensive coverage of Earth's surface but at coarser spatial and temporal resolutions. Although useful for large scale problems, LR-DEMs are not suitable for modeling hydrologic and geomorphic processes at scales smaller than their spatial resolution. In this work, we present a multiple-point geostatistical approach for downscaling a target LR-DEM based on available high-resolution training data and recurrent high-resolution remote sensing images. The method aims at generating several equiprobable HR-DEMs conditioned to a given target LR-DEM by borrowing small scale topographic patterns from an analogue containing data at both coarse and fine scales. An application of the methodology is demonstrated by using an ensemble of simulated HR-DEMs as input to a flow-routing algorithm. The proposed framework enables a probabilistic assessment of the spatial structures generated by natural phenomena operating at scales finer than the available terrain elevation measurements. A case study in the Swiss Alps is provided to illustrate the methodology.

A data mining approach for sharpening satellite thermal imagery over land

USDA-ARS?s Scientific Manuscript database

Thermal infrared (TIR) imagery is normally acquired at coarser pixel resolution than that of shortwave sensors on the same satellite platform and often the TIR resolution is not suitable for monitoring crop conditions of individual fields or the impacts of land cover changes which are at significant...

A review of potential image fusion methods for remote sensing-based irrigation management: Part II

USDA-ARS?s Scientific Manuscript database

Satellite-based sensors provide data at either greater spectral and coarser spatial resolutions, or lower spectral and finer spatial resolutions due to complementary spectral and spatial characteristics of optical sensor systems. In order to overcome this limitation, image fusion has been suggested ...

Data Descriptor: TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015

Treesearch

John T. Abatzoglou; Solomon Z. Dobrowski; Sean A. Parks; Katherine C. Hegewisch

2018-01-01

We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958–2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from...

Potential for using regional and global datasets for national scale ecosystem service modelling

NASA Astrophysics Data System (ADS)

Maxwell, Deborah; Jackson, Bethanna

2016-04-01

Ecosystem service models are increasingly being used by planners and policy makers to inform policy development and decisions about national-level resource management. Such models allow ecosystem services to be mapped and quantified, and subsequent changes to these services to be identified and monitored. In some cases, the impact of small scale changes can be modelled at a national scale, providing more detailed information to decision makers about where to best focus investment and management interventions that could address these issues, while moving toward national goals and/or targets. National scale modelling often uses national (or local) data (for example, soils, landcover and topographical information) as input. However, there are some places where fine resolution and/or high quality national datasets cannot be easily obtained, or do not even exist. In the absence of such detailed information, regional or global datasets could be used as input to such models. There are questions, however, about the usefulness of these coarser resolution datasets and the extent to which inaccuracies in this data may degrade predictions of existing and potential ecosystem service provision and subsequent decision making. Using LUCI (the Land Utilisation and Capability Indicator) as an example predictive model, we examine how the reliability of predictions change when national datasets of soil, landcover and topography are substituted with coarser scale regional and global datasets. We specifically look at how LUCI's predictions of where water services, such as flood risk, flood mitigation, erosion and water quality, change when national data inputs are replaced by regional and global datasets. Using the Conwy catchment, Wales, as a case study, the land cover products compared are the UK's Land Cover Map (2007), the European CORINE land cover map and the ESA global land cover map. Soils products include the National Soil Map of England and Wales (NatMap) and the European Soils Database. NEXTmap elevation data, which covers the UK and parts of continental Europe, are compared to global AsterDEM and SRTM30 topographical products. While the regional and global datasets can be used to fill gaps in data requirements, the coarser resolution of these datasets means that there is greater aggregation of information over larger areas. This loss of detail impacts on the reliability of model output, particularly where significant discrepancies between datasets exist. The implications of this loss of detail in terms of spatial planning and decision making is discussed. Finally, in the context of broader development the need for better nationally and globally available data to allow LUCI and other ecosystem models to become more globally applicable is highlighted.

Mesh-Sequenced Realizations for Evaluation of Subgrid-Scale Models for Turbulent Combustion (Short Term Innovative Research Program)

DTIC Science & Technology

2018-02-15

conservation equations. The closure problem hinges on the evaluation of the filtered chemical production rates. In MRA/MSR, simultaneous large-eddy...simulations of a reactive flow are performed at different mesh resolution levels. The solutions at each coarser mesh level are constrained by the filtered ...include the replacement of chemical production rates with those filtered from the underlying fine mesh and the construction of ‘exact’ forms for

Simulation of population-based commuter exposure to NO₂ using different air pollution models.

PubMed

Ragettli, Martina S; Tsai, Ming-Yi; Braun-Fahrländer, Charlotte; de Nazelle, Audrey; Schindler, Christian; Ineichen, Alex; Ducret-Stich, Regina E; Perez, Laura; Probst-Hensch, Nicole; Künzli, Nino; Phuleria, Harish C

2014-05-12

We simulated commuter routes and long-term exposure to traffic-related air pollution during commute in a representative population sample in Basel (Switzerland), and evaluated three air pollution models with different spatial resolution for estimating commute exposures to nitrogen dioxide (NO2) as a marker of long-term exposure to traffic-related air pollution. Our approach includes spatially and temporally resolved data on actual commuter routes, travel modes and three air pollution models. Annual mean NO2 commuter exposures were similar between models. However, we found more within-city and within-subject variability in annual mean (±SD) NO2 commuter exposure with a high resolution dispersion model (40 ± 7 µg m(-3), range: 21-61) than with a dispersion model with a lower resolution (39 ± 5 µg m(-3); range: 24-51), and a land use regression model (41 ± 5 µg m(-3); range: 24-54). Highest median cumulative exposures were calculated along motorized transport and bicycle routes, and the lowest for walking. For estimating commuter exposure within a city and being interested also in small-scale variability between roads, a model with a high resolution is recommended. For larger scale epidemiological health assessment studies, models with a coarser spatial resolution are likely sufficient, especially when study areas include suburban and rural areas.

Cloud-Free Satellite Image Mosaics with Regression Trees and Histogram Matching.

Treesearch

E.H. Helmer; B. Ruefenacht

2005-01-01

Cloud-free optical satellite imagery simplifies remote sensing, but land-cover phenology limits existing solutions to persistent cloudiness to compositing temporally resolute, spatially coarser imagery. Here, a new strategy for developing cloud-free imagery at finer resolution permits simple automatic change detection. The strategy uses regression trees to predict...

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.

Multi-scale coupled modelling of waves and currents on the Catalan shelf.

NASA Astrophysics Data System (ADS)

Grifoll, M.; Warner, J. C.; Espino, M.; Sánchez-Arcilla, A.

2012-04-01

Catalan shelf circulation is characterized by a background along-shelf flow to the southwest (including some meso-scale features) plus episodic storm driven patterns. To investigate these dynamics, a coupled multi-scale modeling system is applied to the Catalan shelf (North-western Mediterranean Sea). The implementation consists of a set of increasing-resolution nested models, based on the circulation model ROMS and the wave model SWAN as part of the COAWST modeling system, covering from the slope and shelf region (~1 km horizontal resolution) down to a local area around Barcelona city (~40 m). The system is initialized with MyOcean products in the coarsest outer domain, and uses atmospheric forcing from other sources for the increasing resolution inner domains. Results of the finer resolution domains exhibit improved agreement with observations relative to the coarser model results. Several hydrodynamic configurations were simulated to determine dominant forcing mechanisms and hydrodynamic processes that control coastal scale processes. The numerical results reveal that the short term (hours to days) inner-shelf variability is strongly influenced by local wind variability, while sea-level slope, baroclinic effects, radiation stresses and regional circulation constitute second-order processes. Additional analysis identifies the significance of shelf/slope exchange fluxes, river discharge and the effect of the spatial resolution of the atmospheric fluxes.

The Spatial Resolution of Visual Attention.

ERIC Educational Resources Information Center

Intriligator, James; Cavanaugh, Patrick

2001-01-01

Used two tasks to evaluate the grain of visual attention, the minimum spacing at which attention can select individual items. Results for eight adults on a tracking task and five adults on an individuation task show that selection has a coarser grain than visual resolution and suggest that the parietal area is the most likely locus of the…

A multi-resolution approach to electromagnetic modelling

NASA Astrophysics Data System (ADS)

Cherevatova, M.; Egbert, G. D.; Smirnov, M. Yu

2018-07-01

We present a multi-resolution approach for 3-D magnetotelluric forward modelling. 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. With a conventional structured finite difference grid, the fine discretization required to adequately represent rapid variations near the surface is continued to all depths, resulting in higher computational costs. Increasing the computational efficiency of the forward modelling 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 subgrids, with each subgrid being a standard Cartesian tensor product staggered grid. Thus, our approach is similar to the octree discretization previously used for electromagnetic modelling, but simpler in that we allow refinement only with depth. The major difficulty arose in deriving the forward modelling operators on interfaces between adjacent subgrids. 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 shows that multi-resolution approach improves on computational efficiency without compromising the accuracy of the solution.

Simulation of Population-Based Commuter Exposure to NO2 Using Different Air Pollution Models

PubMed Central

Ragettli, Martina S.; Tsai, Ming-Yi; Braun-Fahrländer, Charlotte; de Nazelle, Audrey; Schindler, Christian; Ineichen, Alex; Ducret-Stich, Regina E.; Perez, Laura; Probst-Hensch, Nicole; Künzli, Nino; Phuleria, Harish C.

2014-01-01

We simulated commuter routes and long-term exposure to traffic-related air pollution during commute in a representative population sample in Basel (Switzerland), and evaluated three air pollution models with different spatial resolution for estimating commute exposures to nitrogen dioxide (NO2) as a marker of long-term exposure to traffic-related air pollution. Our approach includes spatially and temporally resolved data on actual commuter routes, travel modes and three air pollution models. Annual mean NO2 commuter exposures were similar between models. However, we found more within-city and within-subject variability in annual mean (±SD) NO2 commuter exposure with a high resolution dispersion model (40 ± 7 µg m−3, range: 21–61) than with a dispersion model with a lower resolution (39 ± 5 µg m−3; range: 24–51), and a land use regression model (41 ± 5 µg m−3; range: 24–54). Highest median cumulative exposures were calculated along motorized transport and bicycle routes, and the lowest for walking. For estimating commuter exposure within a city and being interested also in small-scale variability between roads, a model with a high resolution is recommended. For larger scale epidemiological health assessment studies, models with a coarser spatial resolution are likely sufficient, especially when study areas include suburban and rural areas. PMID:24823664

The influence of model grid resolution on estimation of national scale nitrogen deposition and exceedance of critical levels

NASA Astrophysics Data System (ADS)

Dore, A. J.; Kryza, M.; Hall, J. R.; Hallsworth, S.; Keller, V. J. D.; Vieno, M.; Sutton, M. A.

2011-12-01

The Fine Resolution Atmospheric Multi-pollutant Exchange model (FRAME) has been applied to model the spatial distribution of nitrogen deposition and air concentration over the UK at a 1 km spatial resolution. The modelled deposition and concentration data were gridded at resolutions of 1 km, 5 km and 50 km to test the sensitivity of calculations of the exceedance of critical loads for nitrogen deposition to the deposition data resolution. The modelled concentrations of NO2 were validated by comparison with measurements from the rural sites in the national monitoring network and were found to achieve better agreement with the high resolution 1 km data. High resolution plots were found to represent a more physically realistic distribution of nitrogen air concentrations and deposition resulting from use of 1 km resolution precipitation and emissions data as compared to 5 km resolution data. Summary statistics for national scale exceedance of the critical load for nitrogen deposition were not highly sensitive to the grid resolution of the deposition data but did show greater area exceedance with coarser grid resolution due to spatial averaging of high nitrogen deposition hot spots. Local scale deposition at individual Sites of Special Scientific Interest and high precipitation upland sites was sensitive to choice of grid resolution of deposition data. Use of high resolution data tended to generate lower deposition values in sink areas for nitrogen dry deposition (Sites of Scientific Interest) and higher values in high precipitation upland areas. In areas with generally low exceedance (Scotland) and for certain vegetation types (montane), the exceedance statistics were more sensitive to model data resolution.

The influence of model grid resolution on estimation of national scale nitrogen deposition and exceedance of critical loads

NASA Astrophysics Data System (ADS)

Dore, A. J.; Kryza, M.; Hall, J. R.; Hallsworth, S.; Keller, V. J. D.; Vieno, M.; Sutton, M. A.

2012-05-01

The Fine Resolution Atmospheric Multi-pollutant Exchange model (FRAME) was applied to model the spatial distribution of reactive nitrogen deposition and air concentration over the United Kingdom at a 1 km spatial resolution. The modelled deposition and concentration data were gridded at resolutions of 1 km, 5 km and 50 km to test the sensitivity of calculations of the exceedance of critical loads for nitrogen deposition to the deposition data resolution. The modelled concentrations of NO2 were validated by comparison with measurements from the rural sites in the national monitoring network and were found to achieve better agreement with the high resolution 1 km data. High resolution plots were found to represent a more physically realistic distribution of reactive nitrogen air concentrations and deposition resulting from use of 1 km resolution precipitation and emissions data as compared to 5 km resolution data. Summary statistics for national scale exceedance of the critical load for nitrogen deposition were not highly sensitive to the grid resolution of the deposition data but did show greater area exceedance with coarser grid resolution due to spatial averaging of high nitrogen deposition hot spots. Local scale deposition at individual Sites of Special Scientific Interest and high precipitation upland sites was sensitive to choice of grid resolution of deposition data. Use of high resolution data tended to generate lower deposition values in sink areas for nitrogen dry deposition (Sites of Scientific Interest) and higher values in high precipitation upland areas. In areas with generally low exceedance (Scotland) and for certain vegetation types (montane), the exceedance statistics were more sensitive to model data resolution.

Overview of Proposal on High Resolution Climate Model Simulations of Recent Hurricane and Typhoon Activity: The Impact of SSTs and the Madden Julian Oscillation

NASA Technical Reports Server (NTRS)

Schubert, Siegfried; Kang, In-Sik; Reale, Oreste

2009-01-01

This talk gives an update on the progress and further plans for a coordinated project to carry out and analyze high-resolution simulations of tropical storm activity with a number of state-of-the-art global climate models. Issues addressed include, the mechanisms by which SSTs control tropical storm. activity on inter-annual and longer time scales, the modulation of that activity by the Madden Julian Oscillation on sub-seasonal time scales, as well as the sensitivity of the results to model formulation. The project also encourages companion coarser resolution runs to help assess resolution dependence, and. the ability of the models to capture the large-scale and long-terra changes in the parameters important for hurricane development. Addressing the above science questions is critical to understanding the nature of the variability of the Asian-Australian monsoon and its regional impacts, and thus CLIVAR RAMP fully endorses the proposed tropical storm simulation activity. The project is open to all interested organizations and investigators, and the results from the runs will be shared among the participants, as well as made available to the broader scientific community for analysis.

Challenges of model transferability to data-scarce regions (Invited)

NASA Astrophysics Data System (ADS)

Samaniego, L. E.

2013-12-01

Developing the ability to globally predict the movement of water on the land surface at spatial scales from 1 to 5 km constitute one of grand challenges in land surface modelling. Copying with this grand challenge implies that land surface models (LSM) should be able to make reliable predictions across locations and/or scales other than those used for parameter estimation. In addition to that, data scarcity and quality impose further difficulties in attaining reliable predictions of water and energy fluxes at the scales of interest. Current computational limitations impose also seriously limitations to exhaustively investigate the parameter space of LSM over large domains (e.g. greater than half a million square kilometers). Addressing these challenges require holistic approaches that integrate the best techniques available for parameter estimation, field measurements and remotely sensed data at their native resolutions. An attempt to systematically address these issues is the multiscale parameterisation technique (MPR) that links high resolution land surface characteristics with effective model parameters. This technique requires a number of pedo-transfer functions and a much fewer global parameters (i.e. coefficients) to be inferred by calibration in gauged basins. The key advantage of this technique is the quasi-scale independence of the global parameters which enables to estimate global parameters at coarser spatial resolutions and then to transfer them to (ungauged) areas and scales of interest. In this study we show the ability of this technique to reproduce the observed water fluxes and states over a wide range of climate and land surface conditions ranging from humid to semiarid and from sparse to dense forested regions. Results of transferability of global model parameters in space (from humid to semi-arid basins) and across scales (from coarser to finer) clearly indicate the robustness of this technique. Simulations with coarse data sets (e.g. EOBS forcing 25x25 km2, FAO soil map 1:5000000) using parameters obtained with high resolution information (REGNIE forcing 1x1 km2, BUEK soil map 1:1000000) in different climatic regions indicate the potential of MPR for prediction in data-scarce regions. In this presentation, we will also discuss how the transferability of global model parameters across scales and locations helps to identify deficiencies in model structure and regionalization functions.

Biogenic isoprene emissions driven by regional weather predictions using different initialization methods: case studies during the SEAC4RS and DISCOVER-AQ airborne campaigns

NASA Astrophysics Data System (ADS)

Huang, Min; Carmichael, Gregory R.; Crawford, James H.; Wisthaler, Armin; Zhan, Xiwu; Hain, Christopher R.; Lee, Pius; Guenther, Alex B.

2017-08-01

Land and atmospheric initial conditions of the Weather Research and Forecasting (WRF) model are often interpolated from a different model output. We perform case studies during NASA's SEAC4RS and DISCOVER-AQ Houston airborne campaigns, demonstrating that using land initial conditions directly downscaled from a coarser resolution dataset led to significant positive biases in the coupled NASA-Unified WRF (NUWRF, version 7) surface and near-surface air temperature and planetary boundary layer height (PBLH) around the Missouri Ozarks and Houston, Texas, as well as poorly partitioned latent and sensible heat fluxes. Replacing land initial conditions with the output from a long-term offline Land Information System (LIS) simulation can effectively reduce the positive biases in NUWRF surface air temperature by ˜ 2 °C. We also show that the LIS land initialization can modify surface air temperature errors almost 10 times as effectively as applying a different atmospheric initialization method. The LIS-NUWRF-based isoprene emission calculations by the Model of Emissions of Gases and Aerosols from Nature (MEGAN, version 2.1) are at least 20 % lower than those computed using the coarser resolution data-initialized NUWRF run, and are closer to aircraft-observation-derived emissions. Higher resolution MEGAN calculations are prone to amplified discrepancies with aircraft-observation-derived emissions on small scales. This is possibly a result of some limitations of MEGAN's parameterization and uncertainty in its inputs on small scales, as well as the representation error and the neglect of horizontal transport in deriving emissions from aircraft data. This study emphasizes the importance of proper land initialization to the coupled atmospheric weather modeling and the follow-on emission modeling. We anticipate it to also be critical to accurately representing other processes included in air quality modeling and chemical data assimilation. Having more confidence in the weather inputs is also beneficial for determining and quantifying the other sources of uncertainties (e.g., parameterization, other input data) of the models that they drive.

Coarsening of physics for biogeochemical model in NEMO

NASA Astrophysics Data System (ADS)

Bricaud, Clement; Le Sommer, Julien; Madec, Gurvan; Deshayes, Julie; Chanut, Jerome; Perruche, Coralie

2017-04-01

Ocean mesoscale and submesoscale turbulence contribute to ocean tracer transport and to shaping ocean biogeochemical tracers distribution. Representing adequately tracer transport in ocean models therefore requires to increase model resolution so that the impact of ocean turbulence is adequately accounted for. But due to supercomputers power and storage limitations, global biogeochemical models are not yet run routinely at eddying resolution. Still, because the "effective resolution" of eddying ocean models is much coarser than the physical model grid resolution, tracer transport can be reconstructed to a large extent by computing tracer transport and diffusion with a model grid resolution close to the effective resolution of the physical model. This observation has motivated the implementation of a new capability in NEMO ocean model (http://www.nemo-ocean.eu/) that allows to run the physical model and the tracer transport model at different grid resolutions. In a first time, we present results obtained with this new capability applied to a synthetic age tracer in a global eddying model configuration. In this model configuration, ocean dynamic is computed at ¼° resolution but tracer transport is computed at 3/4° resolution. The solution obtained is compared to 2 reference setup ,one at ¼° resolution for both physics and passive tracer models and one at 3/4° resolution for both physics and passive tracer model. We discuss possible options for defining the vertical diffusivity coefficient for the tracer transport model based on information from the high resolution grid. We describe the impact of this choice on the distribution and one the penetration of the age tracer. In a second time we present results obtained by coupling the physics with the biogeochemical model PISCES. We look at the impact of this methodology on some tracers distribution and dynamic. The method described here can found applications in ocean forecasting, such as the Copernicus Marine service operated by Mercator-Ocean, and in Earth System Models for climate applications.

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Comparison of Envisat ASAR GM, AMSR-E Passive Microwave, and MODIS Optical Remote Sensing for Flood Monitoring in Australia

NASA Astrophysics Data System (ADS)

Ticehurst, C. J.; Bartsch, A.; Doubkova, M.; van Dijk, A. I. J. M.

2009-11-01

Continuous flood monitoring can support emergency response, water management and environmental monitoring. Optical sensors such as MODIS allow inundation mapping with high spatial and temporal resolution (250-1000 m, twice daily) but are affected by cloud cover. Passive microwave sensors also acquire observations at high temporal resolution, but coarser spatial resolution (e.g. ca. 5-70 km for AMSR-E) and smaller footprints are also affected by cloud and/or rain. ScanSAR systems allow all-weather monitoring but require spatial resolution to be traded off against coverage and/or temporal resolution; e.g. the ENVISAT ASAR Global Mode observes at ca. 1 km over large regions about twice a week. The complementary role of the AMSR-E and ASAR GM data to that of MODIS is here introduced for three flood events and locations across Australia. Additional improvements can be made by integrating digital elevation models and stream flow gauging data.

The Separate Physics and Dynamics Experiment (SPADE) framework for determining resolution awareness: A case study of microphysics

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

Gustafson, William I.; Ma, Po-Lun; Xiao, Heng

2013-08-29

The ability to use multi-resolution dynamical cores for weather and climate modeling is pushing the atmospheric community towards developing scale aware or, more specifically, resolution aware parameterizations that will function properly across a range of grid spacings. Determining the resolution dependence of specific model parameterizations is difficult due to strong resolution dependencies in many pieces of the model. This study presents the Separate Physics and Dynamics Experiment (SPADE) framework that can be used to isolate the resolution dependent behavior of specific parameterizations without conflating resolution dependencies from other portions of the model. To demonstrate the SPADE framework, the resolution dependencemore » of the Morrison microphysics from the Weather Research and Forecasting model and the Morrison-Gettelman microphysics from the Community Atmosphere Model are compared for grid spacings spanning the cloud modeling gray zone. It is shown that the Morrison scheme has stronger resolution dependence than Morrison-Gettelman, and that the ability of Morrison-Gettelman to use partial cloud fractions is not the primary reason for this difference. This study also discusses how to frame the issue of resolution dependence, the meaning of which has often been assumed, but not clearly expressed in the atmospheric modeling community. It is proposed that parameterization resolution dependence can be expressed in terms of "resolution dependence of the first type," RA1, which implies that the parameterization behavior converges towards observations with increasing resolution, or as "resolution dependence of the second type," RA2, which requires that the parameterization reproduces the same behavior across a range of grid spacings when compared at a given coarser resolution. RA2 behavior is considered the ideal, but brings with it serious implications due to limitations of parameterizations to accurately estimate reality with coarse grid spacing. The type of resolution awareness developers should target in their development depends upon the particular modeler’s application.« less

Assessment of the effects of horizontal grid resolution on long ...

EPA Pesticide Factsheets

The objective of this study is to determine the adequacy of using a relatively coarse horizontal resolution (i.e. 36 km) to simulate long-term trends of pollutant concentrations and radiation variables with the coupled WRF-CMAQ model. WRF-CMAQ simulations over the continental United State are performed over the 2001 to 2010 time period at two different horizontal resolutions of 12 and 36 km. Both simulations used the same emission inventory and model configurations. Model results are compared both in space and time to assess the potential weaknesses and strengths of using coarse resolution in long-term air quality applications. The results show that the 36 km and 12 km simulations are comparable in terms of trends analysis for both pollutant concentrations and radiation variables. The advantage of using the coarser 36 km resolution is a significant reduction of computational cost, time and storage requirement which are key considerations when performing multiple years of simulations for trend analysis. However, if such simulations are to be used for local air quality analysis, finer horizontal resolution may be beneficial since it can provide information on local gradients. In particular, divergences between the two simulations are noticeable in urban, complex terrain and coastal regions. The National Exposure Research Laboratory’s Atmospheric Modeling Division (AMAD) conducts research in support of EPA’s mission to protect human health and the environment.

Synthetic aperture radar images with composite azimuth resolution

DOEpatents

Bielek, Timothy P; Bickel, Douglas L

2015-03-31

A synthetic aperture radar (SAR) image is produced by using all phase histories of a set of phase histories to produce a first pixel array having a first azimuth resolution, and using less than all phase histories of the set to produce a second pixel array having a second azimuth resolution that is coarser than the first azimuth resolution. The first and second pixel arrays are combined to produce a third pixel array defining a desired SAR image that shows distinct shadows of moving objects while preserving detail in stationary background clutter.

The application of Global Sensitivity Analysis to quantify the dominant input factors for hydraulic model simulations

NASA Astrophysics Data System (ADS)

Savage, James; Pianosi, Francesca; Bates, Paul; Freer, Jim; Wagener, Thorsten

2015-04-01

Predicting flood inundation extents using hydraulic models is subject to a number of critical uncertainties. For a specific event, these uncertainties are known to have a large influence on model outputs and any subsequent analyses made by risk managers. Hydraulic modellers often approach such problems by applying uncertainty analysis techniques such as the Generalised Likelihood Uncertainty Estimation (GLUE) methodology. However, these methods do not allow one to attribute which source of uncertainty has the most influence on the various model outputs that inform flood risk decision making. Another issue facing modellers is the amount of computational resource that is available to spend on modelling flood inundations that are 'fit for purpose' to the modelling objectives. Therefore a balance needs to be struck between computation time, realism and spatial resolution, and effectively characterising the uncertainty spread of predictions (for example from boundary conditions and model parameterisations). However, it is not fully understood how much of an impact each factor has on model performance, for example how much influence changing the spatial resolution of a model has on inundation predictions in comparison to other uncertainties inherent in the modelling process. Furthermore, when resampling fine scale topographic data in the form of a Digital Elevation Model (DEM) to coarser resolutions, there are a number of possible coarser DEMs that can be produced. Deciding which DEM is then chosen to represent the surface elevations in the model could also influence model performance. In this study we model a flood event using the hydraulic model LISFLOOD-FP and apply Sobol' Sensitivity Analysis to estimate which input factor, among the uncertainty in model boundary conditions, uncertain model parameters, the spatial resolution of the DEM and the choice of resampled DEM, have the most influence on a range of model outputs. These outputs include whole domain maximum inundation indicators and flood wave travel time in addition to temporally and spatially variable indicators. This enables us to assess whether the sensitivity of the model to various input factors is stationary in both time and space. Furthermore, competing models are assessed against observations of water depths from a historical flood event. Consequently we are able to determine which of the input factors has the most influence on model performance. Initial findings suggest the sensitivity of the model to different input factors varies depending on the type of model output assessed and at what stage during the flood hydrograph the model output is assessed. We have also found that initial decisions regarding the characterisation of the input factors, for example defining the upper and lower bounds of the parameter sample space, can be significant in influencing the implied sensitivities.

Simulation of a 7.7 MW onshore wind farm with the Actuator Line Model

NASA Astrophysics Data System (ADS)

Guggeri, A.; Draper, M.; Usera, G.

2017-05-01

Recently, the Actuator Line Model (ALM) has been evaluated with coarser resolution and larger time steps than what is generally recommended, taking into account an atmospheric sheared and turbulent inflow condition. The aim of the present paper is to continue these studies, assessing the capability of the ALM to represent the wind turbines’ interactions in an onshore wind farm. The ‘Libertad’ wind farm, which consists of four 1.9MW Vestas V100 wind turbines, was simulated considering different wind directions, and the results were compared with the wind farm SCADA data, finding good agreement between them. A sensitivity analysis was performed to evaluate the influence of the spatial resolution, finding acceptable agreement, although some differences were found. It is believed that these differences are due to the characteristics of the different Atmospheric Boundary Layer (ABL) simulations taken as inflow condition (precursor simulations).

Evaluation of a multi-scale WRF-CAM5 simulation during the 2010 East Asian Summer Monsoon

DOE PAGES

Campbell, Patrick; Zhang, Yang; Wang, Kai; ...

2017-09-08

The Weather Research and Forecasting model with Chemistry (WRF-Chem) with the physics package of the Community Atmosphere Model Version 5 (CAM5) has been applied at multiple scales over Eastern China (EC) and the Yangtze River Delta (YRD) to evaluate how increased horizontal resolution with physics designed for a coarser resolution climate model impacts aerosols and clouds, and the resulting precipitation characteristics and performance during the 2010 East Asian Summer Monsoon (EASM). Despite large underpredictions in surface aerosol concentrations and aerosol optical depth, there is good spatial agreement with surface observations of chemical predictions, and increasing spatial resolution tends to improvemore » performance. Model bias and normalized root mean square values for precipitation predictions are relatively small, but there are significant differences when comparing modeled and observed probability density functions for precipitation in EC and YRD. Increasing model horizontal resolution tends to reduce model bias and error for precipitation predictions. The surface and column aerosol loading is maximized between about 32°N and 42°N in early to mid-May during the 2010 EASM, and then shifts north while decreasing in magnitude during July and August. Changing model resolution moderately changes the spatiotemporal relationships between aerosols, cloud properties, and precipitation during the EASM, thus demonstrating the importance of model grid resolution in simulating EASM circulation and rainfall patterns over EC and the YRD. In conclusion, results from this work demonstrate the capability and limitations in the aerosol, cloud, and precipitation representation of WRF-CAM5 for regional-scale applications down to relatively fine horizontal resolutions. Further WRF-CAM5 model development and application in this area is needed.« less

Evaluation of a multi-scale WRF-CAM5 simulation during the 2010 East Asian Summer Monsoon

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

Campbell, Patrick; Zhang, Yang; Wang, Kai

The Weather Research and Forecasting model with Chemistry (WRF-Chem) with the physics package of the Community Atmosphere Model Version 5 (CAM5) has been applied at multiple scales over Eastern China (EC) and the Yangtze River Delta (YRD) to evaluate how increased horizontal resolution with physics designed for a coarser resolution climate model impacts aerosols and clouds, and the resulting precipitation characteristics and performance during the 2010 East Asian Summer Monsoon (EASM). Despite large underpredictions in surface aerosol concentrations and aerosol optical depth, there is good spatial agreement with surface observations of chemical predictions, and increasing spatial resolution tends to improvemore » performance. Model bias and normalized root mean square values for precipitation predictions are relatively small, but there are significant differences when comparing modeled and observed probability density functions for precipitation in EC and YRD. Increasing model horizontal resolution tends to reduce model bias and error for precipitation predictions. The surface and column aerosol loading is maximized between about 32N and 42N in early to mid-May during the 2010 EASM, and then shifts north while decreasing in magnitude during July and August. Changing model resolution moderately changes the spatiotemporal relationships between aerosols, cloud properties, and precipitation during the EASM, thus demonstrating the importance of model grid resolution in simulating EASM circulation and rainfall patterns over EC and the YRD. Results from this work demonstrate the capability and limitations in the aerosol, cloud, and precipitation representation of WRF-CAM5 for regional-scale applications down to relatively fine horizontal resolutions. Further WRF-CAM5 model development and application in this area is needed.« less

Evaluation of a multi-scale WRF-CAM5 simulation during the 2010 East Asian Summer Monsoon

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

Campbell, Patrick; Zhang, Yang; Wang, Kai

The Weather Research and Forecasting model with Chemistry (WRF-Chem) with the physics package of the Community Atmosphere Model Version 5 (CAM5) has been applied at multiple scales over Eastern China (EC) and the Yangtze River Delta (YRD) to evaluate how increased horizontal resolution with physics designed for a coarser resolution climate model impacts aerosols and clouds, and the resulting precipitation characteristics and performance during the 2010 East Asian Summer Monsoon (EASM). Despite large underpredictions in surface aerosol concentrations and aerosol optical depth, there is good spatial agreement with surface observations of chemical predictions, and increasing spatial resolution tends to improvemore » performance. Model bias and normalized root mean square values for precipitation predictions are relatively small, but there are significant differences when comparing modeled and observed probability density functions for precipitation in EC and YRD. Increasing model horizontal resolution tends to reduce model bias and error for precipitation predictions. The surface and column aerosol loading is maximized between about 32°N and 42°N in early to mid-May during the 2010 EASM, and then shifts north while decreasing in magnitude during July and August. Changing model resolution moderately changes the spatiotemporal relationships between aerosols, cloud properties, and precipitation during the EASM, thus demonstrating the importance of model grid resolution in simulating EASM circulation and rainfall patterns over EC and the YRD. In conclusion, results from this work demonstrate the capability and limitations in the aerosol, cloud, and precipitation representation of WRF-CAM5 for regional-scale applications down to relatively fine horizontal resolutions. Further WRF-CAM5 model development and application in this area is needed.« less

Quantifying the importance of spatial resolution and other factors through global sensitivity analysis of a flood inundation model

NASA Astrophysics Data System (ADS)

Thomas Steven Savage, James; Pianosi, Francesca; Bates, Paul; Freer, Jim; Wagener, Thorsten

2016-11-01

Where high-resolution topographic data are available, modelers are faced with the decision of whether it is better to spend computational resource on resolving topography at finer resolutions or on running more simulations to account for various uncertain input factors (e.g., model parameters). In this paper we apply global sensitivity analysis to explore how influential the choice of spatial resolution is when compared to uncertainties in the Manning's friction coefficient parameters, the inflow hydrograph, and those stemming from the coarsening of topographic data used to produce Digital Elevation Models (DEMs). We apply the hydraulic model LISFLOOD-FP to produce several temporally and spatially variable model outputs that represent different aspects of flood inundation processes, including flood extent, water depth, and time of inundation. We find that the most influential input factor for flood extent predictions changes during the flood event, starting with the inflow hydrograph during the rising limb before switching to the channel friction parameter during peak flood inundation, and finally to the floodplain friction parameter during the drying phase of the flood event. Spatial resolution and uncertainty introduced by resampling topographic data to coarser resolutions are much more important for water depth predictions, which are also sensitive to different input factors spatially and temporally. Our findings indicate that the sensitivity of LISFLOOD-FP predictions is more complex than previously thought. Consequently, the input factors that modelers should prioritize will differ depending on the model output assessed, and the location and time of when and where this output is most relevant.

Assessing the competing roles of model resolution and meteorological forcing fidelity in hyperresolution simulations of snowpack and streamflow in the southern Rocky Mountains

NASA Astrophysics Data System (ADS)

Gochis, D. J.; Dugger, A. L.; Karsten, L. R.; Barlage, M. J.; Sampson, K. M.; Yu, W.; Pan, L.; McCreight, J. L.; Howard, K.; Busto, J.; Deems, J. S.

2017-12-01

Hydrometeorological processes vary over comparatively short length scales in regions of complex terrain such as the southern Rocky Mountains. Changes in temperature, precipitation, wind and solar radiation can vary significantly across elevation gradients, terrain landform and land cover conditions throughout the region. Capturing such variability in hydrologic models can necessitate the utilization of so-called `hyper-resolution' spatial meshes with effective element spacings of less than 100m. However, it is often difficult to obtain meteorological forcings of high quality in such regions at those resolutions which can result in significant uncertainty in fundamental in hydrologic model inputs. In this study we examine the comparative influences of meteorological forcing data fidelity and spatial resolution on seasonal simulations of snowpack evolution, runoff and streamflow in a set of high mountain watersheds in southern Colorado. We utilize the operational, NOAA National Water Model configuration of the community WRF-Hydro system as a baseline and compare against it, additional model scenarios with differing specifications of meteorological forcing data, with and without topographic downscaling adjustments applied, with and without experimental high resolution radar derived precipitation estimates and with WRF-Hydro configurations of progressively finer spatial resolution. The results suggest significant influence from and importance of meteorological downscaling techniques in controlling spatial distributions of meltout and runoff timing. The use of radar derived precipitation exhibits clear sensitivity on hydrologic simulation skill compared with the use of coarser resolution, background precipitation analyses. Advantages and disadvantages of the utilization of progressively higher resolution model configurations both in terms of computational requirements and model fidelity are also discussed.

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.

Hyper-Resolution Groundwater Modeling using MODFLOW 6

NASA Astrophysics Data System (ADS)

Hughes, J. D.; Langevin, C.

2017-12-01

MODFLOW 6 is the latest version of the U.S. Geological Survey's modular hydrologic model. MODFLOW 6 was developed to synthesize many of the recent versions of MODFLOW into a single program, improve the way different process models are coupled, and to provide an object-oriented framework for adding new types of models and packages. The object-oriented framework and underlying numerical solver make it possible to tightly couple any number of hyper-resolution models within coarser regional models. The hyper-resolution models can be used to evaluate local-scale groundwater issues that may be affected by regional-scale forcings. In MODFLOW 6, hyper-resolution meshes can be maintained as separate model datasets, similar to MODFLOW-LGR, which simplifies the development of a coarse regional model with imbedded hyper-resolution models from a coarse regional model. For example, the South Atlantic Coastal Plain regional water availability model was converted from a MODFLOW-2000 model to a MODFLOW 6 model. The horizontal discretization of the original model is approximately 3,218 m x 3,218 m. Hyper-resolution models of the Aiken and Sumter County water budget areas in South Carolina with a horizontal discretization of approximately 322 m x 322 m were developed and were tightly coupled to a modified version of the original coarse regional model that excluded these areas. Hydraulic property and aquifer geometry data from the coarse model were mapped to the hyper-resolution models. The discretization of the hyper-resolution models is fine enough to make detailed analyses of the effect that changes in groundwater withdrawals in the production aquifers have on the water table and surface-water/groundwater interactions. The approach used in this analysis could be applied to other regional water availability models that have been developed by the U.S. Geological Survey to evaluate local scale groundwater issues.

Anthropogenic heat flux: advisable spatial resolutions when input data are scarce

NASA Astrophysics Data System (ADS)

Gabey, A. M.; Grimmond, C. S. B.; Capel-Timms, I.

2018-02-01

Anthropogenic heat flux (QF) may be significant in cities, especially under low solar irradiance and at night. It is of interest to many practitioners including meteorologists, city planners and climatologists. QF estimates at fine temporal and spatial resolution can be derived from models that use varying amounts of empirical data. This study compares simple and detailed models in a European megacity (London) at 500 m spatial resolution. The simple model (LQF) uses spatially resolved population data and national energy statistics. The detailed model (GQF) additionally uses local energy, road network and workday population data. The Fractions Skill Score (FSS) and bias are used to rate the skill with which the simple model reproduces the spatial patterns and magnitudes of QF, and its sub-components, from the detailed model. LQF skill was consistently good across 90% of the city, away from the centre and major roads. The remaining 10% contained elevated emissions and "hot spots" representing 30-40% of the total city-wide energy. This structure was lost because it requires workday population, spatially resolved building energy consumption and/or road network data. Daily total building and traffic energy consumption estimates from national data were within ± 40% of local values. Progressively coarser spatial resolutions to 5 km improved skill for total QF, but important features (hot spots, transport network) were lost at all resolutions when residential population controlled spatial variations. The results demonstrate that simple QF models should be applied with conservative spatial resolution in cities that, like London, exhibit time-varying energy use patterns.

LANDSAT-D investigations in snow hydrology. [Sierra Nevada Mountains

NASA Technical Reports Server (NTRS)

Dozier, J.

1983-01-01

Thematic mapper data for the southern Sierra Nevada area were registered to digital topographic data and compared to LANDSAT MSS and NOAA-7 AVHRR data of snow covered areas in order to determine the errors associated with using coarser resolution and to qualify the information lost when high resolution data are not available. Both the zenith and the azimuth variations in the radiative field are considered in an atmospheric radiative transfer model which deals with a plane parallel structured atmosphere composed of different layers, each assumed to be homogeneous in composition and to have a linear in tau temperature profile. Astronomical parameters for each layer are Earth-Sun distance and solar flux at the top of the atmosphere. Atmospheric parameters include pressure temperature, chemical composition of the air molecules, and the composition and size of the aerosol, water droplets, and ice crystals. Outputs of the model are the monochromatic radiance and irradiance at each level. The use of the model in atmospheric correction of remotely sensed data is discussed.

Benchmarking urban flood models of varying complexity and scale using high resolution terrestrial LiDAR data

NASA Astrophysics Data System (ADS)

Fewtrell, Timothy J.; Duncan, Alastair; Sampson, Christopher C.; Neal, Jeffrey C.; Bates, Paul D.

2011-01-01

This paper describes benchmark testing of a diffusive and an inertial formulation of the de St. Venant equations implemented within the LISFLOOD-FP hydraulic model using high resolution terrestrial LiDAR data. The models are applied to a hypothetical flooding scenario in a section of Alcester, UK which experienced significant surface water flooding in the June and July floods of 2007 in the UK. The sensitivity of water elevation and velocity simulations to model formulation and grid resolution are analyzed. The differences in depth and velocity estimates between the diffusive and inertial approximations are within 10% of the simulated value but inertial effects persist at the wetting front in steep catchments. Both models portray a similar scale dependency between 50 cm and 5 m resolution which reiterates previous findings that errors in coarse scale topographic data sets are significantly larger than differences between numerical approximations. In particular, these results confirm the need to distinctly represent the camber and curbs of roads in the numerical grid when simulating surface water flooding events. Furthermore, although water depth estimates at grid scales coarser than 1 m appear robust, velocity estimates at these scales seem to be inconsistent compared to the 50 cm benchmark. The inertial formulation is shown to reduce computational cost by up to three orders of magnitude at high resolutions thus making simulations at this scale viable in practice compared to diffusive models. For the first time, this paper highlights the utility of high resolution terrestrial LiDAR data to inform small-scale flood risk management studies.

Resolving Tropical Cyclone Intensity in Models

NASA Astrophysics Data System (ADS)

Davis, C. A.

2018-02-01

In recent years, global weather forecast models and global climate models have begun to depict intense tropical cyclones, even up to category 5 on the Saffir-Simpson scale. In light of the limitation of horizontal resolution in such models, the author performs calculations, using the extended Best Track data for Atlantic tropical cyclones, to estimate the ability of models with differing grid spacing to represent Atlantic tropical cyclone intensity statistically. Results indicate that, under optimistic assumptions, models with horizontal grid spacing of one fourth degree or coarser should not produce a realistic number of category 4 and 5 storms unless there are errors in spatial attributes of the wind field. Furthermore, the case of Irma (2017) is used to demonstrate the importance of a realistic depiction of angular momentum and to motivate the use of angular momentum in model evaluation.

Scaling Properties of Arctic Sea Ice Deformation in a High‐Resolution Viscous‐Plastic Sea Ice Model and in Satellite Observations

PubMed Central

Losch, Martin; Menemenlis, Dimitris

2018-01-01

Abstract Sea ice models with the traditional viscous‐plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan‐Arctic sea ice‐ocean simulation, the small‐scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data. PMID:29576996

Scaling Properties of Arctic Sea Ice Deformation in a High-Resolution Viscous-Plastic Sea Ice Model and in Satellite Observations

NASA Astrophysics Data System (ADS)

Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

2018-01-01

Sea ice models with the traditional viscous-plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan-Arctic sea ice-ocean simulation, the small-scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

Scaling Properties of Arctic Sea Ice Deformation in a High-Resolution Viscous-Plastic Sea Ice Model and in Satellite Observations.

PubMed

Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

2018-01-01

Sea ice models with the traditional viscous-plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan-Arctic sea ice-ocean simulation, the small-scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

Biomechanics meets the ecological niche: the importance of temporal data resolution.

PubMed

Kearney, Michael R; Matzelle, Allison; Helmuth, Brian

2012-03-15

The emerging field of mechanistic niche modelling aims to link the functional traits of organisms to their environments to predict survival, reproduction, distribution and abundance. This approach has great potential to increase our understanding of the impacts of environmental change on individuals, populations and communities by providing functional connections between physiological and ecological response to increasingly available spatial environmental data. By their nature, such mechanistic models are more data intensive in comparison with the more widely applied correlative approaches but can potentially provide more spatially and temporally explicit predictions, which are often needed by decision makers. A poorly explored issue in this context is the appropriate level of temporal resolution of input data required for these models, and specifically the error in predictions that can be incurred through the use of temporally averaged data. Here, we review how biomechanical principles from heat-transfer and metabolic theory are currently being used as foundations for mechanistic niche models and consider the consequences of different temporal resolutions of environmental data for modelling the niche of a behaviourally thermoregulating terrestrial lizard. We show that fine-scale temporal resolution (daily) data can be crucial for unbiased inference of climatic impacts on survival, growth and reproduction. This is especially so for species with little capacity for behavioural buffering, because of behavioural or habitat constraints, and for detecting temporal trends. However, coarser-resolution data (long-term monthly averages) can be appropriate for mechanistic studies of climatic constraints on distribution and abundance limits in thermoregulating species at broad spatial scales.

Evaluating hydrography, circulation and transport in a coastal archipelago using a high-resolution 3D hydrodynamic model

NASA Astrophysics Data System (ADS)

Tuomi, Laura; Miettunen, Elina; Alenius, Pekka; Myrberg, Kai

2018-04-01

We used a 3D hydrodynamic model, COHERENS, to simulate the temperature, salinity and currents in an extremely complicated area, the Archipelago Sea in the Baltic Sea. The high-resolution model domain with approximately 460 m resolution was nested inside a coarser resolution ( 3.7 km) grid covering the entire Baltic Sea. The verification of the model results against temperature and salinity measurements showed that the model well captured the seasonal temperature cycle in the surface layer, both in the inner and outer archipelago. In the inner archipelago, the model tended to reproduce higher temperatures in the bottom layer than were measured. The modelled vertical temperature and salinity stratifications were not as pronounced as the measured ones but did describe the overall vertical structure. There was large year-to-year variability in the annual mean surface circulation, both in direction and magnitude. In the deeper channels crossing the Archipelago Sea, there were some year-to-year differences in the magnitudes of the bottom layer currents, but there was very little difference in the directions. These differences were studied by introducing passive tracers into the model through river discharge and as point sources. The results showed that the prevailing wind conditions resulted in southward net transport from the Bothnian Sea towards the Baltic Proper. However, due to the variability in the wind conditions in some years, a significant proportion of transport can also be towards north, from the Baltic Proper to the Bothnian Sea.

Fusing Unmanned Aerial Vehicle Imagery with High Resolution Hydrologic Modeling (Invited)

NASA Astrophysics Data System (ADS)

Vivoni, E. R.; Pierini, N.; Schreiner-McGraw, A.; Anderson, C.; Saripalli, S.; Rango, A.

2013-12-01

After decades of development and applications, high resolution hydrologic models are now common tools in research and increasingly used in practice. More recently, high resolution imagery from unmanned aerial vehicles (UAVs) that provide information on land surface properties have become available for civilian applications. Fusing the two approaches promises to significantly advance the state-of-the-art in terms of hydrologic modeling capabilities. This combination will also challenge assumptions on model processes, parameterizations and scale as land surface characteristics (~0.1 to 1 m) may now surpass traditional model resolutions (~10 to 100 m). Ultimately, predictions from high resolution hydrologic models need to be consistent with the observational data that can be collected from UAVs. This talk will describe our efforts to develop, utilize and test the impact of UAV-derived topographic and vegetation fields on the simulation of two small watersheds in the Sonoran and Chihuahuan Deserts at the Santa Rita Experimental Range (Green Valley, AZ) and the Jornada Experimental Range (Las Cruces, NM). High resolution digital terrain models, image orthomosaics and vegetation species classification were obtained from a fixed wing airplane and a rotary wing helicopter, and compared to coarser analyses and products, including Light Detection and Ranging (LiDAR). We focus the discussion on the relative improvements achieved with UAV-derived fields in terms of terrain-hydrologic-vegetation analyses and summer season simulations using the TIN-based Real-time Integrated Basin Simulator (tRIBS) model. Model simulations are evaluated at each site with respect to a high-resolution sensor network consisting of six rain gauges, forty soil moisture and temperature profiles, four channel runoff flumes, a cosmic-ray soil moisture sensor and an eddy covariance tower over multiple summer periods. We also discuss prospects for the fusion of high resolution models with novel observations from UAVs, including synthetic aperture radar and multispectral imagery.

Probabilistic #D data fusion for multiresolution surface generation

NASA Technical Reports Server (NTRS)

Manduchi, R.; Johnson, A. E.

2002-01-01

In this paper we present an algorithm for adaptive resolution integration of 3D data collected from multiple distributed sensors. The input to the algorithm is a set of 3D surface points and associated sensor models. Using a probabilistic rule, a surface probability function is generated that represents the probability that a particular volume of space contains the surface. The surface probability function is represented using an octree data structure; regions of space with samples of large conariance are stored at a coarser level than regions of space containing samples with smaller covariance. The algorithm outputs an adaptive resolution surface generated by connecting points that lie on the ridge of surface probability with triangles scaled to match the local discretization of space given by the algorithm, we present results from 3D data generated by scanning lidar and structure from motion.

A new, multi-resolution bedrock elevation map of the Greenland ice sheet

NASA Astrophysics Data System (ADS)

Griggs, J. A.; Bamber, J. L.; Grisbed Consortium

2010-12-01

Gridded bedrock elevation for the Greenland ice sheet has previously been constructed with a 5 km posting. The true resolution of the data set was, in places, however, considerably coarser than this due to the across-track spacing of ice-penetrating radar transects. Errors were estimated to be on the order of a few percent in the centre of the ice sheet, increasing markedly in relative magnitude near the margins, where accurate thickness is particularly critical for numerical modelling and other applications. We use new airborne and satellite estimates of ice thickness and surface elevation to determine the bed topography for the whole of Greenland. This is a dynamic product, which will be updated frequently as new data, such as that from NASA’s Operation Ice Bridge, becomes available. The University of Kansas has in recent years, flown an airborne ice-penetrating radar system with close flightline spacing over several key outlet glacier systems. This allows us to produce a multi-resolution bedrock elevation dataset with the high spatial resolution needed for ice dynamic modelling over these key outlet glaciers and coarser resolution over the more sparsely sampled interior. Airborne ice thickness and elevation from CReSIS obtained between 1993 and 2009 are combined with JPL/UCI/Iowa data collected by the WISE (Warm Ice Sounding Experiment) covering the marginal areas along the south west coast from 2009. Data collected in the 1970’s by the Technical University of Denmark were also used in interior areas with sparse coverage from other sources. Marginal elevation data from the ICESat laser altimeter and the Greenland Ice Mapping Program were used to help constrain the ice thickness and bed topography close to the ice sheet margin where, typically, the terrestrial observations have poor sampling between flight tracks. The GRISBed consortium currently consists of: W. Blake, S. Gogineni, A. Hoch, C. M. Laird, C. Leuschen, J. Meisel, J. Paden, J. Plummer, F. Rodriguez-Morales and L. Smith, CReSIS, University of Kansas; E. Rignot, JPL and University of California, Irvine; Y. Gim, JPL; J. Mouginot, University of California, Irvine; D. Kirchner, University of Iowa; I. Howat, Byrd Polar Research Center, Ohio State University; I. Joughin and B. Smith, University of Washington; T. Scambos, NSIDC; S. Martin, University of Washington; T. Wagner, NASA.

The impact of wind energy turbine piles on ocean dynamics

NASA Astrophysics Data System (ADS)

Grashorn, Sebastian; Stanev, Emil V.

2016-04-01

The small- and meso-scale ocean response to wind parks has not been investigated in the southern North Sea until now with the help of high-resolution numerical modelling. Obstacles such as e.g. wind turbine piles may influence the ocean current system and produce turbulent kinetic energy which could affect sediment dynamics in the surrounding area. Two setups of the unstructured-grid model SCHISM (Semi-implicit Cross-scale Hydroscience Integrated System Model) have been developed for an idealized channel including a surface piercing cylindrical obstacle representing the pile and a more realistic test case including four exemplary piles. Experiments using a constant flow around the obstacles and a rotating M2 tidal wave are carried out. The resulting current and turbulence patterns are investigated to estimate the influence of the obstacles on the surrounding ocean dynamics. We demonstrate that using an unstructured ocean model provides the opportunity to embed a high-resolution representation of a wind park turbine pile system into a coarser North Sea setup, which is needed in order to perform a seamless investigation of the resulting geophysical processes.

Moving towards Hyper-Resolution Hydrologic Modeling

NASA Astrophysics Data System (ADS)

Rouf, T.; Maggioni, V.; Houser, P.; Mei, Y.

2017-12-01

Developing a predictive capability for terrestrial hydrology across landscapes, with water, energy and nutrients as the drivers of these dynamic systems, faces the challenge of scaling meter-scale process understanding to practical modeling scales. Hyper-resolution land surface modeling can provide a framework for addressing science questions that we are not able to answer with coarse modeling scales. In this study, we develop a hyper-resolution forcing dataset from coarser resolution products using a physically based downscaling approach. These downscaling techniques rely on correlations with landscape variables, such as topography, roughness, and land cover. A proof-of-concept has been implemented over the Oklahoma domain, where high-resolution observations are available for validation purposes. Hourly NLDAS (North America Land Data Assimilation System) forcing data (i.e., near-surface air temperature, pressure, and humidity) have been downscaled to 500m resolution over the study area for 2015-present. Results show that correlation coefficients between the downscaled temperature dataset and ground observations are consistently higher than the ones between the NLDAS temperature data at their native resolution and ground observations. Not only correlation coefficients are higher, but also the deviation around the 1:1 line in the density scatterplots is smaller for the downscaled dataset than the original one with respect to the ground observations. Results are therefore encouraging as they demonstrate that the 500m temperature dataset has a good agreement with the ground information and can be adopted to force the land surface model for soil moisture estimation. The study has been expanded to wind speed and direction, incident longwave and shortwave radiation, pressure, and precipitation. Precipitation is well known to vary dramatically with elevation and orography. Therefore, we are pursuing a downscaling technique based on both topographical and vegetation characteristics.

Effect of DEM resolution on rainfall-triggered landslide modeling within a triangulated network-based model. A case study in the Luquillo Forest, Puerto Rico

NASA Astrophysics Data System (ADS)

Arnone, E.; Dialynas, Y. G.; Noto, L. V.; Bras, R. L.

2013-12-01

Catchment slope distribution is one of the topographic characteristics that significantly control rainfall-triggered landslide modeling, in both direct and indirect ways. Slope directly determines the soil volume associated with instability. Indirectly slope also affects the subsurface lateral redistribution of soil moisture across the basin, which in turn determines the water pore pressure conditions that impact slope stability. In this study, we investigate the influence of DEM resolution on slope stability and the slope stability analysis by using a distributed eco-hydrological and landslide model, the tRIBS-VEGGIE (Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator - VEGetation Generator for Interactive Evolution). The model implements a triangulated irregular network to describe the topography, and it is capable of evaluating vegetation dynamics and predicting shallow landslides triggered by rainfall. The impact of DEM resolution on the landslide prediction was studied using five TINs derived from five grid DEMs at different resolutions, i.e. 10, 20, 30, 50 and 70 m respectively. The analysis was carried out on the Mameyes Basin, located in the Luquillo Experimental Forest in Puerto Rico, where previous landslide analyses have been carried out. Results showed that the use of the irregular mesh reduced the loss of accuracy in the derived slope distribution when coarser resolutions were used. The impact of the different resolutions on soil moisture patterns was important only when the lateral redistribution was considerable, depending on hydrological properties and rainfall forcing. In some cases, the use of different DEM resolutions did not significantly affect tRIBS-VEGGIE landslide output, in terms of landslide locations, and values of slope and soil moisture at failure.

Forest carbon dynamics associated with growth and disturbances in Oklahoma and Texas, 1992-2006

Treesearch

Daolan Zheng; Linda S. Heath; Mark J. Ducey; James E. Smith

2013-01-01

Quantifying forest carbon changes associated with growth and major disturbances is important for management of greenhouse gas emissions related to forests. Regional-level approaches with improved local growth data may refine estimates obtained using coarser resolution information. This study integrates remote-sensing-derived land cover change products, harvest data,...

MODFLOW-2005, The U.S. Geological Survey Modular Ground-Water Model - Documentation of the Multiple-Refined-Areas Capability of Local Grid Refinement (LGR) and the Boundary Flow and Head (BFH) Package

USGS Publications Warehouse

Mehl, Steffen W.; Hill, Mary C.

2007-01-01

This report documents the addition of the multiple-refined-areas capability to shared node Local Grid Refinement (LGR) and Boundary Flow and Head (BFH) Package of MODFLOW-2005, the U.S. Geological Survey modular, three-dimensional, finite-difference ground-water flow model. LGR now provides the capability to simulate ground-water flow by using one or more block-shaped, higher resolution local grids (child model) within a coarser grid (parent model). LGR accomplishes this by iteratively coupling separate MODFLOW-2005 models such that heads and fluxes are balanced across the shared interfacing boundaries. The ability to have multiple, nonoverlapping areas of refinement is important in situations where there is more than one area of concern within a regional model. In this circumstance, LGR can be used to simulate these distinct areas with higher resolution grids. LGR can be used in two-and three-dimensional, steady-state and transient simulations and for simulations of confined and unconfined ground-water systems. The BFH Package can be used to simulate these situations by using either the parent or child models independently.

High resolution simulations on the North Aegean Sea seasonal circulation

NASA Astrophysics Data System (ADS)

Kourafalou, V. H.; Barbopoulos, K.

2003-01-01

The seasonal characteristics of the circulation in the North Aegean Sea are examined with the aid of a climatological type simulation (three-year run with perpetual year forcing) on a fine resolution grid (2.5 km by 2.5 km). The model is based on the Princeton Ocean Model with a parameterisation of plume dynamics that is employed for the input of waters with hydrographic properties that are different than the properties of basin waters, as the Black Sea Water (BSW) outflow through the Dardanelles Strait and riverine sources. The model is nested with a sequence of coarser regional and basin-wide models that provide for the long-term interaction between the study area and the Eastern Mediterranean at large. The results are employed to discuss the response of the North Aegean to the important circulation forcing mechanisms in the region, namely wind stress, heat and salt fluxes, buoyancy due to rivers and the BSW outflow (which is low in salinity and occasionally low in temperature) and the interaction with the Southern Aegean. The high resolution allows for the detailed representation of the complicated topography that presides in the region. This helps produce a rich eddy field and it allows for variability in the pathways of BSW that has implications in the basin hydrography and circulation.

Sediment delivery estimates in water quality models altered by resolution and source of topographic data.

PubMed

Beeson, Peter C; Sadeghi, Ali M; Lang, Megan W; Tomer, Mark D; Daughtry, Craig S T

2014-01-01

Moderate-resolution (30-m) digital elevation models (DEMs) are normally used to estimate slope for the parameterization of non-point source, process-based water quality models. These models, such as the Soil and Water Assessment Tool (SWAT), use the Universal Soil Loss Equation (USLE) and Modified USLE to estimate sediment loss. The slope length and steepness factor, a critical parameter in USLE, significantly affects sediment loss estimates. Depending on slope range, a twofold difference in slope estimation potentially results in as little as 50% change or as much as 250% change in the LS factor and subsequent sediment estimation. Recently, the availability of much finer-resolution (∼3 m) DEMs derived from Light Detection and Ranging (LiDAR) data has increased. However, the use of these data may not always be appropriate because slope values derived from fine spatial resolution DEMs are usually significantly higher than slopes derived from coarser DEMs. This increased slope results in considerable variability in modeled sediment output. This paper addresses the implications of parameterizing models using slope values calculated from DEMs with different spatial resolutions (90, 30, 10, and 3 m) and sources. Overall, we observed over a 2.5-fold increase in slope when using a 3-m instead of a 90-m DEM, which increased modeled soil loss using the USLE calculation by 130%. Care should be taken when using LiDAR-derived DEMs to parameterize water quality models because doing so can result in significantly higher slopes, which considerably alter modeled sediment loss. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Development of a spatio-temporal disaggregation method (DisNDVI) for generating a time series of fine resolution NDVI images

NASA Astrophysics Data System (ADS)

Bindhu, V. M.; Narasimhan, B.

2015-03-01

Normalized Difference Vegetation Index (NDVI), a key parameter in understanding the vegetation dynamics, has high spatial and temporal variability. However, continuous monitoring of NDVI is not feasible at fine spatial resolution (<60 m) owing to the long revisit time needed by the satellites to acquire the fine spatial resolution data. Further, the study attains significance in the case of humid tropical regions of the earth, where the prevailing atmospheric conditions restrict availability of fine resolution cloud free images at a high temporal frequency. As an alternative to the lack of high resolution images, the current study demonstrates a novel disaggregation method (DisNDVI) which integrates the spatial information from a single fine resolution image and temporal information in terms of crop phenology from time series of coarse resolution images to generate estimates of NDVI at fine spatial and temporal resolution. The phenological variation of the pixels captured at the coarser scale provides the basis for relating the temporal variability of the pixel with the NDVI available at fine resolution. The proposed methodology was tested over a 30 km × 25 km spatially heterogeneous study area located in the south of Tamil Nadu, India. The robustness of the algorithm was assessed by an independent comparison of the disaggregated NDVI and observed NDVI obtained from concurrent Landsat ETM+ imagery. The results showed good spatial agreement across the study area dominated with agriculture and forest pixels, with a root mean square error of 0.05. The validation done at the coarser scale showed that disaggregated NDVI spatially averaged to 240 m compared well with concurrent MODIS NDVI at 240 m (R2 > 0.8). The validation results demonstrate the effectiveness of DisNDVI in improving the spatial and temporal resolution of NDVI images for utility in fine scale hydrological applications such as crop growth monitoring and estimation of evapotranspiration.

MODFLOW-LGR-Modifications to the streamflow-routing package (SFR2) to route streamflow through locally refined grids

USGS Publications Warehouse

Mehl, Steffen W.; Hill, Mary C.

2011-01-01

This report documents modifications to the Streamflow-Routing Package (SFR2) to route streamflow through grids constructed using the multiple-refined-areas capability of shared node Local Grid Refinement (LGR) of MODFLOW-2005. MODFLOW-2005 is the U.S. Geological Survey modular, three-dimensional, finite-difference groundwater-flow model. LGR provides the capability to simulate groundwater flow by using one or more block-shaped, higher resolution local grids (child model) within a coarser grid (parent model). LGR accomplishes this by iteratively coupling separate MODFLOW-2005 models such that heads and fluxes are balanced across the shared interfacing boundaries. Compatibility with SFR2 allows for streamflow routing across grids. LGR can be used in two- and three-dimensional, steady-state and transient simulations and for simulations of confined and unconfined groundwater systems.

Research on regional numerical weather prediction

NASA Technical Reports Server (NTRS)

Kreitzberg, C. W.

1976-01-01

Extension of the predictive power of dynamic weather forecasting to scales below the conventional synoptic or cyclonic scales in the near future is assessed. Lower costs per computation, more powerful computers, and a 100 km mesh over the North American area (with coarser mesh extending beyond it) are noted at present. Doubling the resolution even locally (to 50 km mesh) would entail a 16-fold increase in costs (including vertical resolution and halving the time interval), and constraints on domain size and length of forecast. Boundary conditions would be provided by the surrounding 100 km mesh, and time-varying lateral boundary conditions can be considered to handle moving phenomena. More physical processes to treat, more efficient numerical techniques, and faster computers (improved software and hardware) backing up satellite and radar data could produce further improvements in forecasting in the 1980s. Boundary layer modeling, initialization techniques, and quantitative precipitation forecasting are singled out among key tasks.

Highly Coarse-Grained Representations of Transmembrane Proteins

PubMed Central

2017-01-01

Numerous biomolecules and biomolecular complexes, including transmembrane proteins (TMPs), are symmetric or at least have approximate symmetries. Highly coarse-grained models of such biomolecules, aiming at capturing the essential structural and dynamical properties on resolution levels coarser than the residue scale, must preserve the underlying symmetry. However, making these models obey the correct physics is in general not straightforward, especially at the highly coarse-grained resolution where multiple (∼3–30 in the current study) amino acid residues are represented by a single coarse-grained site. In this paper, we propose a simple and fast method of coarse-graining TMPs obeying this condition. The procedure involves partitioning transmembrane domains into contiguous segments of equal length along the primary sequence. For the coarsest (lowest-resolution) mappings, it turns out to be most important to satisfy the symmetry in a coarse-grained model. As the resolution is increased to capture more detail, however, it becomes gradually more important to match modular repeats in the secondary structure (such as helix-loop repeats) instead. A set of eight TMPs of various complexity, functionality, structural topology, and internal symmetry, representing different classes of TMPs (ion channels, transporters, receptors, adhesion, and invasion proteins), has been examined. The present approach can be generalized to other systems possessing exact or approximate symmetry, allowing for reliable and fast creation of multiscale, highly coarse-grained mappings of large biomolecular assemblies. PMID:28043122

Multisensor data fusion across time and space

NASA Astrophysics Data System (ADS)

Villeneuve, Pierre V.; Beaven, Scott G.; Reed, Robert A.

2014-06-01

Field measurement campaigns typically deploy numerous sensors having different sampling characteristics for spatial, temporal, and spectral domains. Data analysis and exploitation is made more difficult and time consuming as the sample data grids between sensors do not align. This report summarizes our recent effort to demonstrate feasibility of a processing chain capable of "fusing" image data from multiple independent and asynchronous sensors into a form amenable to analysis and exploitation using commercially-available tools. Two important technical issues were addressed in this work: 1) Image spatial registration onto a common pixel grid, 2) Image temporal interpolation onto a common time base. The first step leverages existing image matching and registration algorithms. The second step relies upon a new and innovative use of optical flow algorithms to perform accurate temporal upsampling of slower frame rate imagery. Optical flow field vectors were first derived from high-frame rate, high-resolution imagery, and then finally used as a basis for temporal upsampling of the slower frame rate sensor's imagery. Optical flow field values are computed using a multi-scale image pyramid, thus allowing for more extreme object motion. This involves preprocessing imagery to varying resolution scales and initializing new vector flow estimates using that from the previous coarser-resolution image. Overall performance of this processing chain is demonstrated using sample data involving complex too motion observed by multiple sensors mounted to the same base. Multiple sensors were included, including a high-speed visible camera, up to a coarser resolution LWIR camera.

Multi-resolution MPS method

NASA Astrophysics Data System (ADS)

Tanaka, Masayuki; Cardoso, Rui; Bahai, Hamid

2018-04-01

In this work, the Moving Particle Semi-implicit (MPS) method is enhanced for multi-resolution problems with different resolutions at different parts of the domain utilising a particle splitting algorithm for the finer resolution and a particle merging algorithm for the coarser resolution. The Least Square MPS (LSMPS) method is used for higher stability and accuracy. Novel boundary conditions are developed for the treatment of wall and pressure boundaries for the Multi-Resolution LSMPS method. A wall is represented by polygons for effective simulations of fluid flows with complex wall geometries and the pressure boundary condition allows arbitrary inflow and outflow, making the method easier to be used in flow simulations of channel flows. By conducting simulations of channel flows and free surface flows, the accuracy of the proposed method was verified.

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

Cornford, S. L.; Martin, D. F.; Lee, V.

At least in conventional hydrostatic ice-sheet models, the numerical error associated with grounding line dynamics can be reduced by modifications to the discretization scheme. These involve altering the integration formulae for the basal traction and/or driving stress close to the grounding line and exhibit lower – if still first-order – error in the MISMIP3d experiments. MISMIP3d may not represent the variety of real ice streams, in that it lacks strong lateral stresses, and imposes a large basal traction at the grounding line. We study resolution sensitivity in the context of extreme forcing simulations of the entire Antarctic ice sheet, using the BISICLES adaptive mesh ice-sheet model with two schemes: the original treatment, and a scheme, which modifies the discretization of the basal traction. The second scheme does indeed improve accuracy – by around a factor of two – for a given mesh spacing, butmore » $$\\lesssim 1$$ km resolution is still necessary. For example, in coarser resolution simulations Thwaites Glacier retreats so slowly that other ice streams divert its trunk. In contrast, with $$\\lesssim 1$$ km meshes, the same glacier retreats far more quickly and triggers the final phase of West Antarctic collapse a century before any such diversion can take place.« less

Evaluation of multi-resolution satellite sensors for assessing water quality and bottom depth of Lake Garda.

PubMed

Giardino, Claudia; Bresciani, Mariano; Cazzaniga, Ilaria; Schenk, Karin; Rieger, Patrizia; Braga, Federica; Matta, Erica; Brando, Vittorio E

2014-12-15

In this study we evaluate the capabilities of three satellite sensors for assessing water composition and bottom depth in Lake Garda, Italy. A consistent physics-based processing chain was applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat-8 Operational Land Imager (OLI) and RapidEye. Images gathered on 10 June 2014 were corrected for the atmospheric effects with the 6SV code. The computed remote sensing reflectance (Rrs) from MODIS and OLI were converted into water quality parameters by adopting a spectral inversion procedure based on a bio-optical model calibrated with optical properties of the lake. The same spectral inversion procedure was applied to RapidEye and to OLI data to map bottom depth. In situ measurements of Rrs and of concentrations of water quality parameters collected in five locations were used to evaluate the models. The bottom depth maps from OLI and RapidEye showed similar gradients up to 7 m (r = 0.72). The results indicate that: (1) the spatial and radiometric resolutions of OLI enabled mapping water constituents and bottom properties; (2) MODIS was appropriate for assessing water quality in the pelagic areas at a coarser spatial resolution; and (3) RapidEye had the capability to retrieve bottom depth at high spatial resolution. Future work should evaluate the performance of the three sensors in different bio-optical conditions.

Evaluating the influence of spatial resolution of Landsat predictors on the accuracy of biomass models for large-area estimation across the eastern USA

NASA Astrophysics Data System (ADS)

Deo, Ram K.; Domke, Grant M.; Russell, Matthew B.; Woodall, Christopher W.; Andersen, Hans-Erik

2018-05-01

Aboveground biomass (AGB) estimates for regional-scale forest planning have become cost-effective with the free access to satellite data from sensors such as Landsat and MODIS. However, the accuracy of AGB predictions based on passive optical data depends on spatial resolution and spatial extent of target area as fine resolution (small pixels) data are associated with smaller coverage and longer repeat cycles compared to coarse resolution data. This study evaluated various spatial resolutions of Landsat-derived predictors on the accuracy of regional AGB models at three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We combined national forest inventory data with Landsat-derived predictors at spatial resolutions ranging from 30–1000 m to understand the optimal spatial resolution of optical data for large-area (regional) AGB estimation. Ten generic models were developed using the data collected in 2014, 2015 and 2016, and the predictions were evaluated (i) at the county-level against the estimates of the USFS Forest Inventory and Analysis Program which relied on EVALIDator tool and national forest inventory data from the 2009–2013 cycle and (ii) within a large number of strips (~1 km wide) predicted via LiDAR metrics at 30 m spatial resolution. The county-level estimates by the EVALIDator and Landsat models were highly related (R 2 > 0.66), although the R 2 varied significantly across sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively, with models of coarser resolution. The Landsat-based total AGB estimates were larger than the LiDAR-based total estimates within the strips, however the mean of AGB predictions by LiDAR were mostly within one-standard deviations of the mean predictions obtained from the Landsat-based model at any of the resolutions. We conclude that satellite data at resolutions up to 1000 m provide acceptable accuracy for continental scale analysis of AGB.

The impact of vertical resolution in mesoscale model AROME forecasting of radiation fog

NASA Astrophysics Data System (ADS)

Philip, Alexandre; Bergot, Thierry; Bouteloup, Yves; Bouyssel, François

2015-04-01

Airports short-term forecasting of fog has a security and economic impact. Numerical simulations have been performed with the mesoscale model AROME (Application of Research to Operations at Mesoscale) (Seity et al. 2011). Three vertical resolutions (60, 90 and 156 levels) are used to show the impact of radiation fog on numerical forecasting. Observations at Roissy Charles De Gaulle airport are compared to simulations. Significant differences in the onset, evolution and dissipation of fog were found. The high resolution simulation is in better agreement with observations than a coarser one. The surface boundary layer and incoming long-wave radiations are better represented. A more realistic behaviour of liquid water content evolution allows a better anticipation of low visibility procedures (ceiling < 60m and/or visibility < 600m). The case study of radiation fog shows that it is necessary to have a well defined vertical grid to better represent local phenomena. A statistical study over 6 months (October 2011 - March 2012 ) using different configurations was carried out. Statistically, results were the same as in the case study of radiation fog. Seity Y., P. Brousseau, S. Malardel, G. Hello, P. Bénard, F. Bouttier, C. Lac, V. Masson, 2011: The AROME-France convective scale operational model. Mon.Wea.Rev., 139, 976-991.

Data for Figures and Tables in Journal Article Assessment of the Effects of Horizontal Grid Resolution on Long-Term Air Quality Trends using Coupled WRF-CMAQ Simulations, doi:10.1016/j.atmosenv.2016.02.036

EPA Pesticide Factsheets

The dataset represents the data depicted in the Figures and Tables of a Journal Manuscript with the following abstract: The objective of this study is to determine the adequacy of using a relatively coarse horizontal resolution (i.e. 36 km) to simulate long-term trends of pollutant concentrations and radiation variables with the coupled WRF-CMAQ model. WRF-CMAQ simulations over the continental United State are performed over the 2001 to 2010 time period at two different horizontal resolutions of 12 and 36 km. Both simulations used the same emission inventory and model configurations. Model results are compared both in space and time to assess the potential weaknesses and strengths of using coarse resolution in long-term air quality applications. The results show that the 36 km and 12 km simulations are comparable in terms of trends analysis for both pollutant concentrations and radiation variables. The advantage of using the coarser 36 km resolution is a significant reduction of computational cost, time and storage requirement which are key considerations when performing multiple years of simulations for trend analysis. However, if such simulations are to be used for local air quality analysis, finer horizontal resolution may be beneficial since it can provide information on local gradients. In particular, divergences between the two simulations are noticeable in urban, complex terrain and coastal regions.This dataset is associated with the following publication

SOMAR-LES: A framework for multi-scale modeling of turbulent stratified oceanic flows

NASA Astrophysics Data System (ADS)

Chalamalla, Vamsi K.; Santilli, Edward; Scotti, Alberto; Jalali, Masoud; Sarkar, Sutanu

2017-12-01

A new multi-scale modeling technique, SOMAR-LES, is presented in this paper. Localized grid refinement gives SOMAR (the Stratified Ocean Model with Adaptive Resolution) access to small scales of the flow which are normally inaccessible to general circulation models (GCMs). SOMAR-LES drives a LES (Large Eddy Simulation) on SOMAR's finest grids, forced with large scale forcing from the coarser grids. Three-dimensional simulations of internal tide generation, propagation and scattering are performed to demonstrate this multi-scale modeling technique. In the case of internal tide generation at a two-dimensional bathymetry, SOMAR-LES is able to balance the baroclinic energy budget and accurately model turbulence losses at only 10% of the computational cost required by a non-adaptive solver running at SOMAR-LES's fine grid resolution. This relative cost is significantly reduced in situations with intermittent turbulence or where the location of the turbulence is not known a priori because SOMAR-LES does not require persistent, global, high resolution. To illustrate this point, we consider a three-dimensional bathymetry with grids adaptively refined along the tidally generated internal waves to capture remote mixing in regions of wave focusing. The computational cost in this case is found to be nearly 25 times smaller than that of a non-adaptive solver at comparable resolution. In the final test case, we consider the scattering of a mode-1 internal wave at an isolated two-dimensional and three-dimensional topography, and we compare the results with Legg (2014) numerical experiments. We find good agreement with theoretical estimates. SOMAR-LES is less dissipative than the closure scheme employed by Legg (2014) near the bathymetry. Depending on the flow configuration and resolution employed, a reduction of more than an order of magnitude in computational costs is expected, relative to traditional existing solvers.

Evaluation of Statistical Downscaling Skill at Reproducing Extreme Events

NASA Astrophysics Data System (ADS)

McGinnis, S. A.; Tye, M. R.; Nychka, D. W.; Mearns, L. O.

2015-12-01

Climate model outputs usually have much coarser spatial resolution than is needed by impacts models. Although higher resolution can be achieved using regional climate models for dynamical downscaling, further downscaling is often required. The final resolution gap is often closed with a combination of spatial interpolation and bias correction, which constitutes a form of statistical downscaling. We use this technique to downscale regional climate model data and evaluate its skill in reproducing extreme events. We downscale output from the North American Regional Climate Change Assessment Program (NARCCAP) dataset from its native 50-km spatial resolution to the 4-km resolution of University of Idaho's METDATA gridded surface meterological dataset, which derives from the PRISM and NLDAS-2 observational datasets. We operate on the major variables used in impacts analysis at a daily timescale: daily minimum and maximum temperature, precipitation, humidity, pressure, solar radiation, and winds. To interpolate the data, we use the patch recovery method from the Earth System Modeling Framework (ESMF) regridding package. We then bias correct the data using Kernel Density Distribution Mapping (KDDM), which has been shown to exhibit superior overall performance across multiple metrics. Finally, we evaluate the skill of this technique in reproducing extreme events by comparing raw and downscaled output with meterological station data in different bioclimatic regions according to the the skill scores defined by Perkins et al in 2013 for evaluation of AR4 climate models. We also investigate techniques for improving bias correction of values in the tails of the distributions. These techniques include binned kernel density estimation, logspline kernel density estimation, and transfer functions constructed by fitting the tails with a generalized pareto distribution.

The Rise of Complexity in Flood Forecasting: Opportunities, Challenges and Tradeoffs

NASA Astrophysics Data System (ADS)

Wood, A. W.; Clark, M. P.; Nijssen, B.

2017-12-01

Operational flood forecasting is currently undergoing a major transformation. Most national flood forecasting services have relied for decades on lumped, highly calibrated conceptual hydrological models running on local office computing resources, providing deterministic streamflow predictions at gauged river locations that are important to stakeholders and emergency managers. A variety of recent technological advances now make it possible to run complex, high-to-hyper-resolution models for operational hydrologic prediction over large domains, and the US National Weather Service is now attempting to use hyper-resolution models to create new forecast services and products. Yet other `increased-complexity' forecasting strategies also exist that pursue different tradeoffs between model complexity (i.e., spatial resolution, physics) and streamflow forecast system objectives. There is currently a pressing need for a greater understanding in the hydrology community of the opportunities, challenges and tradeoffs associated with these different forecasting approaches, and for a greater participation by the hydrology community in evaluating, guiding and implementing these approaches. Intermediate-resolution forecast systems, for instance, use distributed land surface model (LSM) physics but retain the agility to deploy ensemble methods (including hydrologic data assimilation and hindcast-based post-processing). Fully coupled numerical weather prediction (NWP) systems, another example, use still coarser LSMs to produce ensemble streamflow predictions either at the model scale or after sub-grid scale runoff routing. Based on the direct experience of the authors and colleagues in research and operational forecasting, this presentation describes examples of different streamflow forecast paradigms, from the traditional to the recent hyper-resolution, to illustrate the range of choices facing forecast system developers. We also discuss the degree to which the strengths and weaknesses of each strategy map onto the requirements for different types of forecasting services (e.g., flash flooding, river flooding, seasonal water supply prediction).

Assessing representation errors of IAGOS CO2, CO and CH4 profile observations: the impact of spatial variations in near-field emissions

NASA Astrophysics Data System (ADS)

Boschetti, Fabio; Thouret, Valerie; Nedelec, Philippe; Chen, Huilin; Gerbig, Christoph

2015-04-01

Airborne platforms have their main strength in the ability of collecting mixing ratio and meteorological data at different heights across a vertical profile, allowing an insight in the internal structure of the atmosphere. However, rental airborne platforms are usually expensive, limiting the number of flights that can be afforded and hence on the amount of data that can be collected. To avoid this disadvantage, the MOZAIC/IAGOS (Measurements of Ozone and water vapor by Airbus In-service airCraft/In-service Aircraft for a Global Observing System) program makes use of commercial airliners, providing data on a regular basis. It is therefore considered an important tool in atmospheric investigations. However, due to the nature of said platforms, MOZAIC/IAGOS's profiles are located near international airports, which are usually significant emission sources, and are in most cases close to major urban settlements, characterized by higher anthropogenic emissions compared to rural areas. When running transport models at finite resolution, these local emissions can heavily affect measurements resulting in biases in model/observation mismatch. Model/observation mismatch can include different aspects in both horizontal and vertical direction, for example spatial and temporal resolution of the modeled fluxes, or poorly represented convective transport or turbulent mixing in the boundary layer. In the framework of the IGAS (IAGOS for GMES Atmospheric Service) project, whose aim is to improve connections between data collected by MOZAIC/IAGOS and Copernicus Atmospheric Service, the present study is focused on the effect of the spatial resolution of emission fluxes, referred to here as representation error. To investigate this, the Lagrangian transport model STILT (Stochastic Time Inverted Lagrangian Transport) was coupled with EDGAR (Emission Database for Global Atmospheric Research) version-4.3 emission inventory at European regional scale. EDGAR's simulated fluxes for CO, CO2 and CH4 with a spatial resolution of 10x10 km for the time frame 2006-2011 was be aggregated into coarser and coarser grid cells in order to evaluate the representation error at different spatial scales. The dependence of representation error from wind direction and month of the year was evaluated for different location in the European domain, for both random and bias component. The representation error was then validated against the model-data mismatch derived from the comparison of MACC (Monitoring Atmospheric Composition and Climate) reanalysis with IAGOS observations for CO to investigate its suitability for modeling applications. We found that the random and bias components of the representation error show a similar pattern dependent on wind direction. In addition, we found a clear linear relationship between the representation error and the model-data mismatch for both (random and bias) components, indicating that about 50% of the model-data mismatch is related to the representation error. This suggests that the representation error derived using STILT provides useful information for better understanding causes for model-data mismatch.

GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice

PubMed Central

Dolinoy, Dana C.; Miranda, Marie Lynn

2004-01-01

The Toxics Release Inventory (TRI) requires facilities with 10 or more full-time employees that process > 25,000 pounds in aggregate or use > 10,000 pounds of any one TRI chemical to report releases annually. However, little is known about releases from non-TRI-reporting facilities, nor has attention been given to the very localized equity impacts associated with air toxics releases. Using geographic information systems and industrial source complex dispersion modeling, we developed methods for characterizing air releases from TRI-reporting as well as non-TRI-reporting facilities at four levels of geographic resolution. We characterized the spatial distribution and concentration of air releases from one representative industry in Durham County, North Carolina (USA). Inclusive modeling of all facilities rather than modeling of TRI sites alone significantly alters the magnitude and spatial distribution of modeled air concentrations. Modeling exposure receptors at more refined levels of geographic resolution reveals localized, neighborhood-level exposure hot spots that are not apparent at coarser geographic scales. Multivariate analysis indicates that inclusive facility modeling at fine levels of geographic resolution reveals exposure disparities by income and race. These new methods significantly enhance the ability to model air toxics, perform equity analysis, and clarify conflicts in the literature regarding environmental justice findings. This work has substantial implications for how to structure TRI reporting requirements, as well as methods and types of analysis that will successfully elucidate the spatial distribution of exposure potentials across geographic, income, and racial lines. PMID:15579419

Does resolution of flow field observation influence apparent habitat use and energy expenditure in juvenile coho salmon?

NASA Astrophysics Data System (ADS)

Tullos, D. D.; Walter, C.; Dunham, J.

2016-12-01

This study investigated how the resolution of observation influences interpretation of how fish, juvenile Coho Salmon (Oncorhynchus kisutch), exploit the hydraulic environment in streams. Our objectives were to evaluate how spatial resolution of the flow field observation influenced: 1) the velocities considered to be representative of habitat units; 2) patterns of use of the hydraulic environment by fish; and 3) estimates of energy expenditure. We addressed these objectives using observations within a 1:1 scale physical model of a full-channel log jam in an outdoor experimental stream. Velocities were measured with Acoustic Doppler Velocimetry at a 10 cm grid spacing, whereas fish locations and tailbeat frequencies were documented over time using underwater videogrammetry. Results highlighted that resolution of observation did impact perceived habitat use and energy expenditure, as did the location of measurement within habitat units and the use of averaging to summarize velocities within a habitat unit. In this experiment, the range of velocities and energy expenditure estimates increased with coarsening resolution, reducing the likelihood of measuring the velocities locally experienced by fish. In addition, the coarser resolutions contributed to fish appearing to select velocities that were higher than what was measured at finer resolutions. These findings indicate the need for careful attention to and communication of resolution of observation in investigating the hydraulic environment and in determining the habitat needs and bioenergetics of aquatic biota.

Bounding uncertainty in volumetric geometric models for terrestrial lidar observations of ecosystems.

PubMed

Paynter, Ian; Genest, Daniel; Peri, Francesco; Schaaf, Crystal

2018-04-06

Volumetric models with known biases are shown to provide bounds for the uncertainty in estimations of volume for ecologically interesting objects, observed with a terrestrial laser scanner (TLS) instrument. Bounding cuboids, three-dimensional convex hull polygons, voxels, the Outer Hull Model and Square Based Columns (SBCs) are considered for their ability to estimate the volume of temperate and tropical trees, as well as geomorphological features such as bluffs and saltmarsh creeks. For temperate trees, supplementary geometric models are evaluated for their ability to bound the uncertainty in cylinder-based reconstructions, finding that coarser volumetric methods do not currently constrain volume meaningfully, but may be helpful with further refinement, or in hybridized models. Three-dimensional convex hull polygons consistently overestimate object volume, and SBCs consistently underestimate volume. Voxel estimations vary in their bias, due to the point density of the TLS data, and occlusion, particularly in trees. The response of the models to parametrization is analysed, observing unexpected trends in the SBC estimates for the drumlin dataset. Establishing that this result is due to the resolution of the TLS observations being insufficient to support the resolution of the geometric model, it is suggested that geometric models with predictable outcomes can also highlight data quality issues when they produce illogical results.

Bounding uncertainty in volumetric geometric models for terrestrial lidar observations of ecosystems

PubMed Central

Genest, Daniel; Peri, Francesco; Schaaf, Crystal

2018-01-01

Volumetric models with known biases are shown to provide bounds for the uncertainty in estimations of volume for ecologically interesting objects, observed with a terrestrial laser scanner (TLS) instrument. Bounding cuboids, three-dimensional convex hull polygons, voxels, the Outer Hull Model and Square Based Columns (SBCs) are considered for their ability to estimate the volume of temperate and tropical trees, as well as geomorphological features such as bluffs and saltmarsh creeks. For temperate trees, supplementary geometric models are evaluated for their ability to bound the uncertainty in cylinder-based reconstructions, finding that coarser volumetric methods do not currently constrain volume meaningfully, but may be helpful with further refinement, or in hybridized models. Three-dimensional convex hull polygons consistently overestimate object volume, and SBCs consistently underestimate volume. Voxel estimations vary in their bias, due to the point density of the TLS data, and occlusion, particularly in trees. The response of the models to parametrization is analysed, observing unexpected trends in the SBC estimates for the drumlin dataset. Establishing that this result is due to the resolution of the TLS observations being insufficient to support the resolution of the geometric model, it is suggested that geometric models with predictable outcomes can also highlight data quality issues when they produce illogical results. PMID:29503722

Short-Range Prediction of Monsoon Precipitation by NCMRWF Regional Unified Model with Explicit Convection

NASA Astrophysics Data System (ADS)

Mamgain, Ashu; Rajagopal, E. N.; Mitra, A. K.; Webster, S.

2018-03-01

There are increasing efforts towards the prediction of high-impact weather systems and understanding of related dynamical and physical processes. High-resolution numerical model simulations can be used directly to model the impact at fine-scale details. Improvement in forecast accuracy can help in disaster management planning and execution. National Centre for Medium Range Weather Forecasting (NCMRWF) has implemented high-resolution regional unified modeling system with explicit convection embedded within coarser resolution global model with parameterized convection. The models configurations are based on UK Met Office unified seamless modeling system. Recent land use/land cover data (2012-2013) obtained from Indian Space Research Organisation (ISRO) are also used in model simulations. Results based on short-range forecast of both the global and regional models over India for a month indicate that convection-permitting simulations by the high-resolution regional model is able to reduce the dry bias over southern parts of West Coast and monsoon trough zone with more intense rainfall mainly towards northern parts of monsoon trough zone. Regional model with explicit convection has significantly improved the phase of the diurnal cycle of rainfall as compared to the global model. Results from two monsoon depression cases during study period show substantial improvement in details of rainfall pattern. Many categories in rainfall defined for operational forecast purposes by Indian forecasters are also well represented in case of convection-permitting high-resolution simulations. For the statistics of number of days within a range of rain categories between `No-Rain' and `Heavy Rain', the regional model is outperforming the global model in all the ranges. In the very heavy and extremely heavy categories, the regional simulations show overestimation of rainfall days. Global model with parameterized convection have tendency to overestimate the light rainfall days and underestimate the heavy rain days compared to the observation data.

Sensitivity of chemical transport model simulations to the duration of chemical and transport operators: a case study with GEOS-Chem v10-01

NASA Astrophysics Data System (ADS)

Philip, S.; Martin, R. V.; Keller, C. A.

2015-11-01

Chemical transport models involve considerable computational expense. Fine temporal resolution offers accuracy at the expense of computation time. Assessment is needed of the sensitivity of simulation accuracy to the duration of chemical and transport operators. We conduct a series of simulations with the GEOS-Chem chemical transport model at different temporal and spatial resolutions to examine the sensitivity of simulated atmospheric composition to temporal resolution. Subsequently, we compare the tracers simulated with operator durations from 10 to 60 min as typically used by global chemical transport models, and identify the timesteps that optimize both computational expense and simulation accuracy. We found that longer transport timesteps increase concentrations of emitted species such as nitrogen oxides and carbon monoxide since a more homogeneous distribution reduces loss through chemical reactions and dry deposition. The increased concentrations of ozone precursors increase ozone production at longer transport timesteps. Longer chemical timesteps decrease sulfate and ammonium but increase nitrate due to feedbacks with in-cloud sulfur dioxide oxidation and aerosol thermodynamics. The simulation duration decreases by an order of magnitude from fine (5 min) to coarse (60 min) temporal resolution. We assess the change in simulation accuracy with resolution by comparing the root mean square difference in ground-level concentrations of nitrogen oxides, ozone, carbon monoxide and secondary inorganic aerosols with a finer temporal or spatial resolution taken as truth. Simulation error for these species increases by more than a factor of 5 from the shortest (5 min) to longest (60 min) temporal resolution. Chemical timesteps twice that of the transport timestep offer more simulation accuracy per unit computation. However, simulation error from coarser spatial resolution generally exceeds that from longer timesteps; e.g. degrading from 2° × 2.5° to 4° × 5° increases error by an order of magnitude. We recommend prioritizing fine spatial resolution before considering different temporal resolutions in offline chemical transport models. We encourage the chemical transport model users to specify in publications the durations of operators due to their effects on simulation accuracy.

Numerical simulations and parameterizations of volcanic plumes observed at Reunion Island

NASA Astrophysics Data System (ADS)

Gurwinder Sivia, Sandra; Gheusi, Francois; Mari, Celine; DiMuro, Andrea; Tulet, Pierre

2013-04-01

Volcanoes are natural composite hazards. The volcanic ejecta can have considerable impact on human health. Volcanic gases and ash, can be especially harmful to people with lung disease such as asthma. Volcanic gases that pose the greatest potential hazards are sulfur dioxide, carbon dioxide, and hydrogen fluoride. Locally, sulfur dioxide gas can lead to acid rain and air pollution downwind from a volcano. These gases can come from lava flows as well as volcano eruptive plumes. This acidic pollution can be transported by wind over large distances. To comply with regulatory rules, modeling tools are needed to accurately predict the contribution of volcanic emissions to air quality degradation. Unfortunately, the ability of existing models to simulate volcanic plume production and dispersion is currently limited by inaccurate volcanic emissions and uncertainties in plume-rise estimates. The present work is dedicated to the study of deep injections of volcanic emissions into the troposphere developed as consequence of intense but localized input of heat near eruptive mouths. This work covers three aspects. First a precise quantification of heat sources in terms of surface, geometry and heat source intensity is done for the Piton de la Fournaise volcano. Second, large eddy simulation (LES) are performed with the Meso-NH model to determine the dynamics and vertical development of volcanic plumes. The estimated energy fluxes and the geometry of the heat source is used at the bottom boundary to generate and sustain the plume, while, passive tracers are used to represent volcanic gases and their injection into the atmosphere. The realism of the simulated plumes is validated on the basis of plume observations. The LES simulations finally serve as references for the development of column parameterizations for the coarser resolution version of the model which is the third aspect of the present work. At spatial resolution coarser than ~1km, buoyant volcanic plumes are sub-grid processes. A new parameterization for the injection height is presented which is based on a modified version of the eddy-diffusivity/mass-flux scheme initially developed for the simulation of convective boundary layer.

Toward Multi-Model Frameworks Addressing Multi-Sector Dynamics, Risks, and Resiliency

NASA Astrophysics Data System (ADS)

Moss, R. H.; Fisher-Vanden, K.; Barrett, C.; Kraucunas, I.; Rice, J.; Sue Wing, I.; Bhaduri, B. L.; Reed, P. M.

2016-12-01

This presentation will report on the findings of recent modeling studies and a series of workshops and other efforts convened under the auspices of the US Global Change Research Program (USGCRP) to improve integration of critical infrastructure, natural resources, integrated assessment, and human systems modeling. The focus is issues related to drought and increased variability of water supply at the energy-water-land nexus. One motivation for the effort is the potential for impact cascades across coupled built, natural, and socioeconomic systems stressed by social and environmental change. The design is for an adaptable modeling framework that will includes a repository of independently-developed modeling tools of varying complexity - from coarser grid, longer time-horizon to higher-resolution shorter-term models of socioeconomic systems, infrastructure, and natural resources. The models draw from three interlocking research communities: Earth system, impacts/adaptation/vulnerability, and integrated assessment. A key lesson will be explored, namely the importance of defining a clear use perspective to limit dimensionality, focus modeling, and facilitate uncertainty characterization and communication.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

The global flood map published online at http://www.fmglobal.com/research-and-resources/global-flood-map at 90m resolution is being used worldwide to understand flood risk exposure, exercise certain measures of mitigation, and/or transfer the residual risk financially through flood insurance programs. The modeling system is based on a physically-based hydrologic model to simulate river discharges, and 2D shallow-water hydrodynamic model to simulate inundation. The model can be applied to large-scale flood hazard mapping thanks to several solutions that maximize its efficiency and the use of parallel computing. The hydrologic component of the modeling system is the Hillslope River Routing (HRR) hydrologic model. HRR simulates hydrological processes using a Green-Ampt parameterization, and is calibrated against observed discharge data from several publicly-available datasets. For inundation mapping, we use a 2D Finite-Volume Shallow-Water model with wetting/drying. We introduce here a grid Up-Scaling Technique (UST) for hydraulic modeling to perform simulations at higher resolution at global scale with relatively short computational times. A 30m SRTM is now available worldwide along with higher accuracy and/or resolution local Digital Elevation Models (DEMs) in many countries and regions. UST consists of aggregating computational cells, thus forming a coarser grid, while retaining the topographic information from the original full-resolution mesh. The full-resolution topography is used for building relationships between volume and free surface elevation inside cells and computing inter-cell fluxes. This approach almost achieves computational speed typical of the coarse grids while preserving, to a significant extent, the accuracy offered by the much higher resolution available DEM. The simulations are carried out along each river of the network by forcing the hydraulic model with the streamflow hydrographs generated by HRR. Hydrographs are scaled so that the peak corresponds to the return period corresponding to the hazard map being produced (e.g. 100 years, 500 years). Each numerical simulation models one river reach, except for the longest reaches which are split in smaller parts. Here we show results for selected river basins worldwide.

Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO 2 emissions

DOE PAGES

Feng, Sha; Lauvaux, Thomas; Newman, Sally; ...

2016-07-22

Megacities are major sources of anthropogenic fossil fuel CO 2 (FFCO 2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km 2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO 2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO 2 emission product, Hestia-LA, to simulate atmospheric CO 2 concentrations across the LA megacity at spatial resolutions as fine as ~1 km. We evaluated multiple WRF configurations, selecting one that minimizedmore » errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO 2 emission products to evaluate the impact of the spatial resolution of the CO 2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO 2 concentrations. We find that high spatial resolution in the fossil fuel CO 2 emissions is more important than in the atmospheric model to capture CO 2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO 2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO 2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO 2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO 2 emissions monitoring in the LA megacity requires FFCO 2 emissions modelling with ~1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.« less

Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO 2 emissions

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

Feng, Sha; Lauvaux, Thomas; Newman, Sally

Megacities are major sources of anthropogenic fossil fuel CO 2 (FFCO 2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km 2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO 2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO 2 emission product, Hestia-LA, to simulate atmospheric CO 2 concentrations across the LA megacity at spatial resolutions as fine as ~1 km. We evaluated multiple WRF configurations, selecting one that minimizedmore » errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO 2 emission products to evaluate the impact of the spatial resolution of the CO 2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO 2 concentrations. We find that high spatial resolution in the fossil fuel CO 2 emissions is more important than in the atmospheric model to capture CO 2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO 2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO 2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO 2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO 2 emissions monitoring in the LA megacity requires FFCO 2 emissions modelling with ~1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.« less

Comparison of MODIS and SWAT evapotranspiration over a complex terrain at different spatial scales

NASA Astrophysics Data System (ADS)

Abiodun, Olanrewaju O.; Guan, Huade; Post, Vincent E. A.; Batelaan, Okke

2018-05-01

In most hydrological systems, evapotranspiration (ET) and precipitation are the largest components of the water balance, which are difficult to estimate, particularly over complex terrain. In recent decades, the advent of remotely sensed data based ET algorithms and distributed hydrological models has provided improved spatially upscaled ET estimates. However, information on the performance of these methods at various spatial scales is limited. This study compares the ET from the MODIS remotely sensed ET dataset (MOD16) with the ET estimates from a SWAT hydrological model on graduated spatial scales for the complex terrain of the Sixth Creek Catchment of the Western Mount Lofty Ranges, South Australia. ET from both models was further compared with the coarser-resolution AWRA-L model at catchment scale. The SWAT model analyses are performed on daily timescales with a 6-year calibration period (2000-2005) and 7-year validation period (2007-2013). Differences in ET estimation between the SWAT and MOD16 methods of up to 31, 19, 15, 11 and 9 % were observed at respectively 1, 4, 9, 16 and 25 km2 spatial resolutions. Based on the results of the study, a spatial scale of confidence of 4 km2 for catchment-scale evapotranspiration is suggested in complex terrain. Land cover differences, HRU parameterisation in AWRA-L and catchment-scale averaging of input climate data in the SWAT semi-distributed model were identified as the principal sources of weaker correlations at higher spatial resolution.

Influence of grid resolution in fluid-model simulation of nanosecond dielectric barrier discharge plasma actuator

NASA Astrophysics Data System (ADS)

Hua, Weizhuo; Fukagata, Koji

2018-04-01

Two-dimensional numerical simulation of a surface dielectric barrier discharge (SDBD) plasma actuator, driven by a nanosecond voltage pulse, is conducted. A special focus is laid upon the influence of grid resolution on the computational result. It is found that the computational result is not very sensitive to the streamwise grid spacing, whereas the wall-normal grid spacing has a critical influence. In particular, the computed propagation velocity changes discontinuously around the wall-normal grid spacing about 2 μm due to a qualitative change of discharge structure. The present result suggests that a computational grid finer than that was used in most of previous studies is required to correctly capture the structure and dynamics of streamer: when a positive nanosecond voltage pulse is applied to the upper electrode, a streamer forms in the vicinity of upper electrode and propagates along the dielectric surface with a maximum propagation velocity of 2 × 108 cm/s, and a gap with low electron and ion density (i.e., plasma sheath) exists between the streamer and dielectric surface. Difference between the results obtained using the finer and the coarser grid is discussed in detail in terms of the electron transport at a position near the surface. When the finer grid is used, the low electron density near the surface is caused by the absence of ionization avalanche: in that region, the electrons generated by ionization is compensated by drift-diffusion flux. In contrast, when the coarser grid is used, underestimated drift-diffusion flux cannot compensate the electrons generated by ionization, and it leads to an incorrect increase of electron density.

Outcomes and challenges of global high-resolution non-hydrostatic atmospheric simulations using the K computer

NASA Astrophysics Data System (ADS)

Satoh, Masaki; Tomita, Hirofumi; Yashiro, Hisashi; Kajikawa, Yoshiyuki; Miyamoto, Yoshiaki; Yamaura, Tsuyoshi; Miyakawa, Tomoki; Nakano, Masuo; Kodama, Chihiro; Noda, Akira T.; Nasuno, Tomoe; Yamada, Yohei; Fukutomi, Yoshiki

2017-12-01

This article reviews the major outcomes of a 5-year (2011-2016) project using the K computer to perform global numerical atmospheric simulations based on the non-hydrostatic icosahedral atmospheric model (NICAM). The K computer was made available to the public in September 2012 and was used as a primary resource for Japan's Strategic Programs for Innovative Research (SPIRE), an initiative to investigate five strategic research areas; the NICAM project fell under the research area of climate and weather simulation sciences. Combining NICAM with high-performance computing has created new opportunities in three areas of research: (1) higher resolution global simulations that produce more realistic representations of convective systems, (2) multi-member ensemble simulations that are able to perform extended-range forecasts 10-30 days in advance, and (3) multi-decadal simulations for climatology and variability. Before the K computer era, NICAM was used to demonstrate realistic simulations of intra-seasonal oscillations including the Madden-Julian oscillation (MJO), merely as a case study approach. Thanks to the big leap in computational performance of the K computer, we could greatly increase the number of cases of MJO events for numerical simulations, in addition to integrating time and horizontal resolution. We conclude that the high-resolution global non-hydrostatic model, as used in this five-year project, improves the ability to forecast intra-seasonal oscillations and associated tropical cyclogenesis compared with that of the relatively coarser operational models currently in use. The impacts of the sub-kilometer resolution simulation and the multi-decadal simulations using NICAM are also reviewed.

Reconstructing the 20th century high-resolution climate of the southeastern United States

NASA Astrophysics Data System (ADS)

Dinapoli, Steven M.; Misra, Vasubandhu

2012-10-01

We dynamically downscale the 20th Century Reanalysis (20CR) to a 10-km grid resolution from 1901 to 2008 over the southeastern United States and the Gulf of Mexico using the Regional Spectral Model. The downscaled data set, which we call theFlorida Climate Institute-Florida State University Land-Atmosphere Reanalysis for theSoutheastern United States at 10-km resolution (FLAReS1.0), will facilitate the study of the effects of low-frequency climate variability and major historical climate events on local hydrology and agriculture. To determine the suitability of the FLAReS1.0 downscaled data set for any subsequent applied climate studies, we compare the annual, seasonal, and diurnal variability of temperature and precipitation in the model to various observation data sets. In addition, we examine the model's depiction of several meteorological phenomena that affect the climate of the region, including extreme cold waves, summer sea breezes and associated convective activity, tropical cyclone landfalls, and midlatitude frontal systems. Our results show that temperature and precipitation variability are well-represented by FLAReS1.0 on most time scales, although systematic biases do exist in the data. FLAReS1.0 accurately portrays some of the major weather phenomena in the region, but the severity of extreme weather events is generally underestimated. The high resolution of FLAReS1.0 makes it more suitable for local climate studies than the coarser 20CR.

Statistical Examination of the Resolution of a Block-Scale Urban Drainage Model

NASA Astrophysics Data System (ADS)

Goldstein, A.; Montalto, F. A.; Digiovanni, K. A.

2009-12-01

Stormwater drainage models are utilized by cities in order to plan retention systems to prevent combined sewage overflows and design for development. These models aggregate subcatchments and ignore small pipelines providing a coarse representation of a sewage network. This study evaluates the importance of resolution by comparing two models developed on a neighborhood scale for predicting the total quantity and peak flow of runoff to observed runoff measured at the site. The low and high resolution models were designed for a 2.6 ha block in Bronx, NYC in EPA Stormwater Management Model (SWMM) using a single catchment and separate subcatchments based on surface cover, respectively. The surface covers represented included sidewalks, street, buildings, and backyards. Characteristics for physical surfaces and the infrastructure in the high resolution mode were determined from site visits, sewer pipe maps, aerial photographs, and GIS data-sets provided by the NYC Department of City Planning. Since the low resolution model was depicted at a coarser scale, generalizations were assumed about the overall average characteristics of the catchment. Rainfall and runoff data were monitored over a four month period during the summer rainy season. A total of 53 rain fall events were recorded but only 29 storms produced significant amount of runoffs to be evaluated in the simulations. To determine which model was more accurate at predicting the observed runoff, three characteristics for each storm were compared: peak runoff, total runoff, and time to peak. Two statistical tests were used to determine the significance of the results: the percent difference for each storm and the overall Chi-squared Goodness of Fit distribution for both the low and high resolution model. These tests will evaluate if there is a statistical difference depending on the resolution of scale of the stormwater model. The scale of representation is being evaluated because it could have a profound impact on how low-impact development strategies are assessed. Rerouting flows to delay the time of entry into the combined sewage is the primary goal of stormwater source controls which may be better differentiated in a high resolution as opposed to low resolution model. The preliminary hypothesis is that the low resolution model simplifies watershed by defining attributes uniformly across the watershed. In the high resolution model, the physical flow can be more accurate depicted by connected the various subcatchments. For example, the runoff from buildings can directly be routed to the backyard. The main drawback to the high resolution model is the risk of adding uncertainty due to the number of parameters.

Mesoscale Air-Sea Interactions along the Gulf Stream: An Eddy-Resolving and Convection-Permitting Coupled Regional Climate Model Study

NASA Astrophysics Data System (ADS)

Hsieh, J. S.; Chang, P.; Saravanan, R.

2017-12-01

Frontal and mesoscale air-sea interactions along the Gulf Stream (GS) during boreal winter are investigated using an eddy-resolving and convection-permitting coupled regional climate model with atmospheric grid resolutions varying from meso-β (27-km) to -r (9-km and 3-km nest) scales in WRF and a 9-km ocean model (ROMS) that explicitly resolves the ocean mesoscale eddies across the North Atlantic basin. The mesoscale wavenumber energy spectra for the simulated surface wind stress and SST demonstrate good agreement with the observed spectra calculated from the observational QuikSCAT and AMSR-E datasets, suggesting that the model well captures the energy cascade of the mesoscale eddies in both the atmosphere and the ocean. Intercomparison among different resolution simulations indicates that after three months of integration the simulated GS path tends to overshoot beyond the separation point in the 27-km WRF coupled experiments than the observed climatological path of the GS, whereas the 3-km nested and 9-km WRF coupled simulations realistically simulate GS separation. The GS overshoot in 27-km WRF coupled simulations is accompanied with a significant SST warming bias to the north of the GS extension. Such biases are associated with the deficiency of wind stress-SST coupling strengths simulated by the coupled model with a coarser resolution in WRF. It is found that the model at 27-km grid spacing can approximately simulate 72% (62%) of the observed mean coupling strength between surface wind stress curl (divergence) and crosswind (downwind) SST gradient while by increasing the WRF resolutions to 9 km or 3 km the coupled model can much better capture the observed coupling strengths.

Evaluation of cool season precipitation event characteristics over the Northeast US in a suite of downscaled climate model hindcasts

NASA Astrophysics Data System (ADS)

Loikith, Paul C.; Waliser, Duane E.; Kim, Jinwon; Ferraro, Robert

2017-08-01

Cool season precipitation event characteristics are evaluated across a suite of downscaled climate models over the northeastern US. Downscaled hindcast simulations are produced by dynamically downscaling the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA2) using the National Aeronautics and Space Administration (NASA)-Unified Weather Research and Forecasting (WRF) regional climate model (RCM) and the Goddard Earth Observing System Model, Version 5 (GEOS-5) global climate model. NU-WRF RCM simulations are produced at 24, 12, and 4-km horizontal resolutions using a range of spectral nudging schemes while the MERRA2 global downscaled run is provided at 12.5-km. All model runs are evaluated using four metrics designed to capture key features of precipitation events: event frequency, event intensity, even total, and event duration. Overall, the downscaling approaches result in a reasonable representation of many of the key features of precipitation events over the region, however considerable biases exist in the magnitude of each metric. Based on this evaluation there is no clear indication that higher resolution simulations result in more realistic results in general, however many small-scale features such as orographic enhancement of precipitation are only captured at higher resolutions suggesting some added value over coarser resolution. While the differences between simulations produced using nudging and no nudging are small, there is some improvement in model fidelity when nudging is introduced, especially at a cutoff wavelength of 600 km compared to 2000 km. Based on the results of this evaluation, dynamical regional downscaling using NU-WRF results in a more realistic representation of precipitation event climatology than the global downscaling of MERRA2 using GEOS-5.

Characterization of ASTER GDEM Elevation Data over Vegetated Area Compared with Lidar Data

NASA Technical Reports Server (NTRS)

Ni, Wenjian; Sun, Guoqing; Ranson, Kenneth J.

2013-01-01

Current researches based on areal or spaceborne stereo images with very high resolutions (less than 1 meter) have demonstrated that it is possible to derive vegetation height from stereo images. The second version of the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) is a state-of-the-art global elevation data-set developed by stereo images. However, the resolution of ASTER stereo images (15 meters) is much coarser than areal stereo images, and the ASTER GDEM is compiled products from stereo images acquired over 10 years. The forest disturbances as well as forest growth are inevitable in 10 years time span. In this study, the features of ASTER GDEM over vegetated areas under both flat and mountainous conditions were investigated by comparisons with lidar data. The factors possibly affecting the extraction of vegetation canopy height considered include (1) co-registration of DEMs; (2) spatial resolution of digital elevation models (DEMs); (3) spatial vegetation structure; and (4) terrain slope. The results show that accurate co-registration between ASTER GDEM and the National Elevation Dataset (NED) is necessary over mountainous areas. The correlation between ASTER GDEM minus NED and vegetation canopy height is improved from 0.328 to 0.43 by degrading resolutions from 1 arc-second to 5 arc-seconds and further improved to 0.6 if only homogenous vegetated areas were considered.

Bathymetry Estimations Using Vicariously Calibrated HICO Data

DTIC Science & Technology

2013-07-16

prototype sensor installed on the International Space Station (ISS) designed to explore the management and capability of a space-borne hyperspectral sensor ...management of the HICO sensor . Bathymetry information is essential for naval operations in coastal regions. However, bathymetry may not be available in... sensors with coarser resolutions. Furthermore, its contiguous hyperspectral range is well suited to be used as input to the Hyperspectral Optimization

Impact of temporal upscaling and chemical transport model horizontal resolution on reducing ozone exposure misclassification

NASA Astrophysics Data System (ADS)

Xu, Yadong; Serre, Marc L.; Reyes, Jeanette M.; Vizuete, William

2017-10-01

We have developed a Bayesian Maximum Entropy (BME) framework that integrates observations from a surface monitoring network and predictions from a Chemical Transport Model (CTM) to create improved exposure estimates that can be resolved into any spatial and temporal resolution. The flexibility of the framework allows for input of data in any choice of time scales and CTM predictions of any spatial resolution with varying associated degrees of estimation error and cost in terms of implementation and computation. This study quantifies the impact on exposure estimation error due to these choices by first comparing estimations errors when BME relied on ozone concentration data either as an hourly average, the daily maximum 8-h average (DM8A), or the daily 24-h average (D24A). Our analysis found that the use of DM8A and D24A data, although less computationally intensive, reduced estimation error more when compared to the use of hourly data. This was primarily due to the poorer CTM model performance in the hourly average predicted ozone. Our second analysis compared spatial variability and estimation errors when BME relied on CTM predictions with a grid cell resolution of 12 × 12 km2 versus a coarser resolution of 36 × 36 km2. Our analysis found that integrating the finer grid resolution CTM predictions not only reduced estimation error, but also increased the spatial variability in daily ozone estimates by 5 times. This improvement was due to the improved spatial gradients and model performance found in the finer resolved CTM simulation. The integration of observational and model predictions that is permitted in a BME framework continues to be a powerful approach for improving exposure estimates of ambient air pollution. The results of this analysis demonstrate the importance of also understanding model performance variability and its implications on exposure error.

Numerical simulation of the observed near-surface East India Coastal Current on the continental slope

NASA Astrophysics Data System (ADS)

Mukherjee, A.; Shankar, D.; Chatterjee, Abhisek; Vinayachandran, P. N.

2018-06-01

We simulate the East India Coastal Current (EICC) using two numerical models (resolution 0.1° × 0.1°), an oceanic general circulation model (OGCM) called Modular Ocean Model and a simpler, linear, continuously stratified (LCS) model, and compare the simulated current with observations from moorings equipped with acoustic Doppler current profilers deployed on the continental slope in the western Bay of Bengal (BoB). We also carry out numerical experiments to analyse the processes. Both models simulate well the annual cycle of the EICC, but the performance degrades for the intra-annual and intraseasonal components. In a model-resolution experiment, both models (run at a coarser resolution of 0.25° × 0.25°) simulate well the currents in the equatorial Indian Ocean (EIO), but the performance of the high-resolution LCS model as well as the coarse-resolution OGCM, which is good in the EICC regime, degrades in the eastern and northern BoB. An experiment on forcing mechanisms shows that the annual EICC is largely forced by the local alongshore winds in the western BoB and remote forcing due to Ekman pumping over the BoB, but forcing from the EIO has a strong impact on the intra-annual EICC. At intraseasonal periods, local (equatorial) forcing dominates in the south (north) because the Kelvin wave propagates equatorward in the western BoB. A stratification experiment with the LCS model shows that changing the background stratification from EIO to BoB leads to a stronger surface EICC owing to strong coupling of higher order vertical modes with wind forcing for the BoB profiles. These high-order modes, which lead to energy propagating down into the ocean in the form of beams, are important only for the current and do not contribute significantly to the sea level.

Diabatic modification of potential vorticity in extratropical cyclones

NASA Astrophysics Data System (ADS)

Chagnon, J.

2012-12-01

Representation of diabatic processes and their impact on extratropical cyclones is a likely source of skill degradation in operational numerical weather prediction systems. This investigation examines the source, structure, and magnitude of diabatic potential vorticity (PV) anomalies generated by small-scale and parameterized processes in both mesoscale and global model simulations of extratropical cyclones in the North Atlantic. Simulations of several cold season extratropical storms have been performed using the Met Office Unified Model. Several cases simulated were drawn from the DIAbatic influences on Mesoscale structures in ExTratropical cyclones (DIAMET) observational campaign during which the National Environmental Research Council (NERC) Facility for Airborne Atmospheric Measurement (FAAM) BAE-146 aircraft was deployed. The influence of specific modelled processes was quantified using a set of tracers, each of which represents a history of the PV contributed by a specific segment of the model (e.g., boundary-layer scheme, cloud microphysics, convection scheme , radiation, etc.). This presentation will highlight several differences and similarities in high and low resolution simulations. For example, in high resolution simulations, tropopause folds are sharpened by a tripolar PV anomaly arising from the convection, boundary-layer, and microphysics schemes; this structure is not present in coarser global model simulations. However, a dipole of PV straddling the tropopause is diagnosed in both coarse- and fine-resolution simulations. The PV dipole, which is strongly influenced by long-wave radiative cooling, increases the gradient of PV near the tropopause and therefore modifies the characteristics Rossby wave propagation and moist baroclinic wave growth.

Prediction skill of tropical synoptic scale transients from ECMWF and NCEP ensemble prediction systems

DOE PAGES

Taraphdar, S.; Mukhopadhyay, P.; Leung, L. Ruby; ...

2016-12-05

The prediction skill of tropical synoptic scale transients (SSTR) such as monsoon low and depression during the boreal summer of 2007–2009 are assessed using high resolution ECMWF and NCEP TIGGE forecasts data. By analyzing 246 forecasts for lead times up to 10 days, it is found that the models have good skills in forecasting the planetary scale means but the skills of SSTR remain poor, with the latter showing no skill beyond 2 days for the global tropics and Indian region. Consistent forecast skills among precipitation, velocity potential, and vorticity provide evidence that convection is the primary process responsible formore » precipitation. The poor skills of SSTR can be attributed to the larger random error in the models as they fail to predict the locations and timings of SSTR. Strong correlation between the random error and synoptic precipitation suggests that the former starts to develop from regions of convection. As the NCEP model has larger biases of synoptic scale precipitation, it has a tendency to generate more random error that ultimately reduces the prediction skill of synoptic systems in that model. Finally, the larger biases in NCEP may be attributed to the model moist physics and/or coarser horizontal resolution compared to ECMWF.« less

Prediction skill of tropical synoptic scale transients from ECMWF and NCEP ensemble prediction systems

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

Taraphdar, S.; Mukhopadhyay, P.; Leung, L. Ruby

The prediction skill of tropical synoptic scale transients (SSTR) such as monsoon low and depression during the boreal summer of 2007–2009 are assessed using high resolution ECMWF and NCEP TIGGE forecasts data. By analyzing 246 forecasts for lead times up to 10 days, it is found that the models have good skills in forecasting the planetary scale means but the skills of SSTR remain poor, with the latter showing no skill beyond 2 days for the global tropics and Indian region. Consistent forecast skills among precipitation, velocity potential, and vorticity provide evidence that convection is the primary process responsible formore » precipitation. The poor skills of SSTR can be attributed to the larger random error in the models as they fail to predict the locations and timings of SSTR. Strong correlation between the random error and synoptic precipitation suggests that the former starts to develop from regions of convection. As the NCEP model has larger biases of synoptic scale precipitation, it has a tendency to generate more random error that ultimately reduces the prediction skill of synoptic systems in that model. Finally, the larger biases in NCEP may be attributed to the model moist physics and/or coarser horizontal resolution compared to ECMWF.« less

Adaptive mesh refinement versus subgrid friction interpolation in simulations of Antarctic ice dynamics

DOE PAGES

Cornford, S. L.; Martin, D. F.; Lee, V.; ...

2016-05-13

At least in conventional hydrostatic ice-sheet models, the numerical error associated with grounding line dynamics can be reduced by modifications to the discretization scheme. These involve altering the integration formulae for the basal traction and/or driving stress close to the grounding line and exhibit lower – if still first-order – error in the MISMIP3d experiments. MISMIP3d may not represent the variety of real ice streams, in that it lacks strong lateral stresses, and imposes a large basal traction at the grounding line. We study resolution sensitivity in the context of extreme forcing simulations of the entire Antarctic ice sheet, using the BISICLES adaptive mesh ice-sheet model with two schemes: the original treatment, and a scheme, which modifies the discretization of the basal traction. The second scheme does indeed improve accuracy – by around a factor of two – for a given mesh spacing, butmore » $$\\lesssim 1$$ km resolution is still necessary. For example, in coarser resolution simulations Thwaites Glacier retreats so slowly that other ice streams divert its trunk. In contrast, with $$\\lesssim 1$$ km meshes, the same glacier retreats far more quickly and triggers the final phase of West Antarctic collapse a century before any such diversion can take place.« less

The accuracy of temperature distributions used to derive the net transport for a zonally averaged model

NASA Technical Reports Server (NTRS)

Remsberg, Ellis E.; Bhatt, Praful P.

1994-01-01

Comparisons of satellite-derived temperatures with correlative temperatures indicate that the LIMS temperatures are accurate and contain more of the needed vertical resolution for calculating a residual mean circulation for transporting tracer-like species. Generally, the LIMS temperatures are accurate to at least 2 K. Other satellite data sets are comprised of temperatures with coarser vertical resolution, leading to biases that occur with an error pattern that is characteristic of their resolution. Their biases exceed 2 K at some altitudes. Retrievals of species using an infrared limb emission technique are sensitive to any temperature bias. Generally, the IMS comparisons with other data sets for ozone and water vapor are good to better than 20 percent; this represents an independent confirmation of the quality of LIMS and temperatures. Zonal mean comparisons between LIMS and SAMS temperatures also indicate agreement to better than 2 K from about 7 to 2hPa. Therefore, we are confident that SAMS N2O and CH4 are relatively free of temperature bias in that region. These factors support the generally good agreement in G90 between model N2O transported using a LIMS-derived RMC and the N2O contours from SAMS.

Impact of buildings on surface solar radiation over urban Beijing

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

Zhao, Bin; Liou, Kuo-Nan; Gu, Yu

The rugged surface of an urban area due to varying buildings can interact with solar beams and affect both the magnitude and spatiotemporal distribution of surface solar fluxes. Here we systematically examine the impact of buildings on downward surface solar fluxes over urban Beijing by using a 3-D radiation parameterization that accounts for 3-D building structures vs. the conventional plane-parallel scheme. We find that the resulting downward surface solar flux deviations between the 3-D and the plane-parallel schemes are generally ±1–10 W m -2 at 800 m grid resolution and within ±1 W m -2 at 4 km resolution. Pairsmore » of positive–negative flux deviations on different sides of buildings are resolved at 800 m resolution, while they offset each other at 4 km resolution. Flux deviations from the unobstructed horizontal surface at 4 km resolution are positive around noon but negative in the early morning and late afternoon. The corresponding deviations at 800 m resolution, in contrast, show diurnal variations that are strongly dependent on the location of the grids relative to the buildings. Both the magnitude and spatiotemporal variations of flux deviations are largely dominated by the direct flux. Furthermore, we find that flux deviations can potentially be an order of magnitude larger by using a finer grid resolution. Atmospheric aerosols can reduce the magnitude of downward surface solar flux deviations by 10–65 %, while the surface albedo generally has a rather moderate impact on flux deviations. The results imply that the effect of buildings on downward surface solar fluxes may not be critically significant in mesoscale atmospheric models with a grid resolution of 4 km or coarser. However, the effect can play a crucial role in meso-urban atmospheric models as well as microscale urban dispersion models with resolutions of 1 m to 1 km.« less

Scaling of surface energy fluxes using remotely sensed data

NASA Astrophysics Data System (ADS)

French, Andrew Nichols

Accurate estimates of evapotranspiration (ET) across multiple terrains would greatly ease challenges faced by hydrologists, climate modelers, and agronomists as they attempt to apply theoretical models to real-world situations. One ET estimation approach uses an energy balance model to interpret a combination of meteorological observations taken at the surface and data captured by remote sensors. However, results of this approach have not been accurate because of poor understanding of the relationship between surface energy flux and land cover heterogeneity, combined with limits in available resolution of remote sensors. The purpose of this study was to determine how land cover and image resolution affect ET estimates. Using remotely sensed data collected over El Reno, Oklahoma, during four days in June and July 1997, scale effects on the estimation of spatially distributed ET were investigated. Instantaneous estimates of latent and sensible heat flux were calculated using a two-source surface energy balance model driven by thermal infrared, visible-near infrared, and meteorological data. The heat flux estimates were verified by comparison to independent eddy-covariance observations. Outcomes of observations taken at coarser resolutions were simulated by aggregating remote sensor data and estimated surface energy balance components from the finest sensor resolution (12 meter) to hypothetical resolutions as coarse as one kilometer. Estimated surface energy flux components were found to be significantly dependent on observation scale. For example, average evaporative fraction varied from 0.79, using 12-m resolution data, to 0.93, using 1-km resolution data. Resolution effects upon flux estimates were related to a measure of landscape heterogeneity known as operational scale, reflecting the size of dominant landscape features. Energy flux estimates based on data at resolutions less than 100 m and much greater than 400 m showed a scale-dependent bias. But estimates derived from data taken at about 400-m resolution (the operational scale at El Reno) were susceptible to large error due to mixing of surface types. The El Reno experiments show that accurate instantaneous estimates of ET require precise image alignment and image resolutions finer than landscape operational scale. These findings are valuable for the design of sensors and experiments to quantify spatially-varying hydrologic processes.

Landsat 7 thermal-IR image sharpening using an artificial neural network and sensor model

USGS Publications Warehouse

Lemeshewsky, G.P.; Schowengerdt, R.A.; ,

2001-01-01

The enhanced thematic mapper (plus) (ETM+) instrument on Landsat 7 shares the same basic design as the TM sensors on Landsats 4 and 5, with some significant improvements. In common are six multispectral bands with a 30-m ground-projected instantaneous field of view (GIFOV). However, the thermaL-IR (TIR) band now has a 60-m GIFOV, instead of 120-m. Also, a 15-m panchromatic band has been added. The artificial neural network (NN) image sharpening method described here uses data from the higher spatial resolution ETM+ bands to enhance (sharpen) the spatial resolution of the TIR imagery. It is based on an assumed correlation over multiple scales of resolution, between image edge contrast patterns in the TIR band and several other spectral bands. A multilayer, feedforward NN is trained to approximate TIR data at 60m, given degraded (from 30-m to 60-m) spatial resolution input from spectral bands 7, 5, and 2. After training, the NN output for full-resolution input generates an approximation of a TIR image at 30-m resolution. Two methods are used to degrade the spatial resolution of the imagery used for NN training, and the corresponding sharpening results are compared. One degradation method uses a published sensor transfer function (TF) for Landsat 5 to simulate sensor coarser resolution imagery from higher resolution imagery. For comparison, the second degradation method is simply Gaussian low pass filtering and subsampling, wherein the Gaussian filter approximates the full width at half maximum amplitude characteristics of the TF-based spatial filter. Two fixed-size NNs (that is, number of weights and processing elements) were trained separately with the degraded resolution data, and the sharpening results compared. The comparison evaluates the relative influence of the degradation technique employed and whether or not it is desirable to incorporate a sensor TF model. Preliminary results indicate some improvements for the sensor model-based technique. Further evaluation using a higher resolution reference image and strict application of sensor model to data is recommended.

Biocellion: accelerating computer simulation of multicellular biological system models

PubMed Central

Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

2014-01-01

Motivation: Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. Results: We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Availability and implementation: Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. Contact: seunghwa.kang@pnnl.gov PMID:25064572

Does resolution of flow field observation influence apparent habitat use and energy expenditure in juvenile coho salmon?

USGS Publications Warehouse

Tullos, Desiree D.; Walter, Cara; Dunham, Jason B.

2016-01-01

This study investigated how the resolution of observation influences interpretation of how fish, juvenile Coho Salmon (Oncorhynchus kisutch), exploit the hydraulic environment in streams. Our objectives were to evaluate how spatial resolution of the flow field observation influenced: (1) the velocities considered to be representative of habitat units; (2) patterns of use of the hydraulic environment by fish; and (3) estimates of energy expenditure. We addressed these objectives using observations within a 1:1 scale physical model of a full-channel log jam in an outdoor experimental stream. Velocities were measured with Acoustic Doppler Velocimetry at a 10 cm grid spacing, whereas fish locations and tailbeat frequencies were documented over time using underwater videogrammetry. Results highlighted that resolution of observation did impact perceived habitat use and energy expenditure, as did the location of measurement within habitat units and the use of averaging to summarize velocities within a habitat unit. In this experiment, the range of velocities and energy expenditure estimates increased with coarsening resolution (grid spacing from 10 to 100 cm), reducing the likelihood of measuring the velocities locally experienced by fish. In addition, the coarser resolutions contributed to fish appearing to select velocities that were higher than what was measured at finer resolutions. These findings indicate the need for careful attention to and communication of resolution of observation in investigating the hydraulic environment and in determining the habitat needs and bioenergetics of aquatic biota.

Regional photochemical air quality modeling in the Mexico-US border area

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

Mendoza, A.; Russell, A.G.; Mejia, G.M.

1998-12-31

The Mexico-United States border area has become an increasingly important region due to its commercial, industrial and urban growth. As a result, environmental concerns have risen. Treaties like the North American Free Trade Agreement (NAFTA) have further motivated the development of environmental impact assessment in the area. Of particular concern are air quality, and how the activities on both sides of the border contribute to its degradation. This paper presents results of applying a three-dimensional photochemical airshed model to study air pollution dynamics along the Mexico-United States border. In addition, studies were conducted to assess how size resolution impacts themore » model performance. The model performed within acceptable statistic limits using 12.5 x 12.5 km{sup 2} grid cells, and the benefits using finer grids were limited. Results were further used to assess the influence of grid-cell size on the modeling of control strategies, where coarser grids lead to significant loss of information.« less

Improved large-scale hydrological modelling through the assimilation of streamflow and downscaled satellite soil moisture observations.

NASA Astrophysics Data System (ADS)

López López, Patricia; Wanders, Niko; Sutanudjaja, Edwin; Renzullo, Luigi; Sterk, Geert; Schellekens, Jaap; Bierkens, Marc

2015-04-01

The coarse spatial resolution of global hydrological models (typically > 0.25o) often limits their ability to resolve key water balance processes for many river basins and thus compromises their suitability for water resources management, especially when compared to locally-tunes river models. A possible solution to the problem may be to drive the coarse resolution models with high-resolution meteorological data as well as to assimilate ground-based and remotely-sensed observations of key water cycle variables. While this would improve the modelling resolution of the global model, the impact of prediction accuracy remains largely an open question. In this study we investigated the impact that assimilating streamflow and satellite soil moisture observations have on global hydrological model estimation, driven by coarse- and high-resolution meteorological observations, for the Murrumbidgee river basin in Australia. The PCR-GLOBWB global hydrological model is forced with downscaled global climatological data (from 0.5o downscaled to 0.1o resolution) obtained from the WATCH Forcing Data (WFDEI) and local high resolution gauging station based gridded datasets (0.05o), sourced from the Australian Bureau of Meteorology. Downscaled satellite derived soil moisture (from 0.5o downscaled to 0.1o resolution) from AMSR-E and streamflow observations collected from 25 gauging stations are assimilated using an ensemble Kalman filter. Several scenarios are analysed to explore the added value of data assimilation considering both local and global climatological data. Results show that the assimilation of streamflow observations result in the largest improvement of the model estimates. The joint assimilation of both streamflow and downscaled soil moisture observations leads to further improved in streamflow simulations (10% reduction in RMSE), mainly in the headwater catchments (up to 10,000 km2). Results also show that the added contribution of data assimilation, for both soil moisture and streamflow, is more pronounced when the global meteorological data are used to force the models. This is caused by the higher uncertainty and coarser resolution of the global forcing. This study demonstrates that it is possible to improve hydrological simulations forced by coarse resolution meteorological data with downscaled satellite soil moisture and streamflow observations and bring them closer to a hydrological model forced with local climatological data. These findings are important in light of the efforts that are currently done to go to global hyper-resolution modelling and can significantly help to advance this research.

Effects of spatial resolution ratio in image fusion

USGS Publications Warehouse

Ling, Y.; Ehlers, M.; Usery, E.L.; Madden, M.

2008-01-01

In image fusion, the spatial resolution ratio can be defined as the ratio between the spatial resolution of the high-resolution panchromatic image and that of the low-resolution multispectral image. This paper attempts to assess the effects of the spatial resolution ratio of the input images on the quality of the fused image. Experimental results indicate that a spatial resolution ratio of 1:10 or higher is desired for optimal multisensor image fusion provided the input panchromatic image is not downsampled to a coarser resolution. Due to the synthetic pixels generated from resampling, the quality of the fused image decreases as the spatial resolution ratio decreases (e.g. from 1:10 to 1:30). However, even with a spatial resolution ratio as small as 1:30, the quality of the fused image is still better than the original multispectral image alone for feature interpretation. In cases where the spatial resolution ratio is too small (e.g. 1:30), to obtain better spectral integrity of the fused image, one may downsample the input high-resolution panchromatic image to a slightly lower resolution before fusing it with the multispectral image.

Resolving vorticity-driven lateral fire spread using the WRF-Fire coupled atmosphere-fire numerical model

NASA Astrophysics Data System (ADS)

Simpson, C. C.; Sharples, J. J.; Evans, J. P.

2014-05-01

Fire channelling is a form of dynamic fire behaviour, during which a wildland fire spreads rapidly across a steep lee-facing slope in a direction transverse to the background winds, and is often accompanied by a downwind extension of the active flaming region and extreme pyro-convection. Recent work using the WRF-Fire coupled atmosphere-fire model has demonstrated that fire channelling can be characterised as vorticity-driven lateral fire spread (VDLS). In this study, 16 simulations are conducted using WRF-Fire to examine the sensitivity of resolving VDLS to spatial resolution and atmosphere-fire coupling within the WRF-Fire model framework. The horizontal grid spacing is varied between 25 and 90 m, and the two-way atmosphere-fire coupling is either enabled or disabled. At high spatial resolution, the atmosphere-fire coupling increases the peak uphill and lateral spread rate by a factor of up to 2.7 and 9.5. The enhancement of the uphill and lateral spread rate diminishes at coarser spatial resolution, and VDLS is not modelled for a horizontal grid spacing of 90 m. The laterally spreading fire fronts become the dominant contributors of the extreme pyro-convection. The resolved fire-induced vortices responsible for driving the lateral spread in the coupled simulations have non-zero vorticity along each unit vector direction, and develop due to an interaction between the background winds and vertical return circulations generated at the flank of the fire front as part of the pyro-convective updraft. The results presented in this study demonstrate that both high spatial resolution and two-way atmosphere-fire coupling are required to reproduce VDLS within the current WRF-Fire model framework.

Evaluation of snowmelt simulation in the Weather Research and Forecasting model

NASA Astrophysics Data System (ADS)

Jin, Jiming; Wen, Lijuan

2012-05-01

The objective of this study is to better understand and improve snowmelt simulations in the advanced Weather Research and Forecasting (WRF) model by coupling it with the Community Land Model (CLM) Version 3.5. Both WRF and CLM are developed by the National Center for Atmospheric Research. The automated Snow Telemetry (SNOTEL) station data over the Columbia River Basin in the northwestern United States are used to evaluate snowmelt simulations generated with the coupled WRF-CLM model. These SNOTEL data include snow water equivalent (SWE), precipitation, and temperature. The simulations cover the period of March through June 2002 and focus mostly on the snowmelt season. Initial results show that when compared to observations, WRF-CLM significantly improves the simulations of SWE, which is underestimated when the release version of WRF is coupled with the Noah and Rapid Update Cycle (RUC) land surface schemes, in which snow physics is oversimplified. Further analysis shows that more realistic snow surface energy allocation in CLM is an important process that results in improved snowmelt simulations when compared to that in Noah and RUC. Additional simulations with WRF-CLM at different horizontal spatial resolutions indicate that accurate description of topography is also vital to SWE simulations. WRF-CLM at 10 km resolution produces the most realistic SWE simulations when compared to those produced with coarser spatial resolutions in which SWE is remarkably underestimated. The coupled WRF-CLM provides an important tool for research and forecasts in weather, climate, and water resources at regional scales.

Modeled Full-Flight Aircraft Emissions Impacts on Air Quality and Their Sensitivity to Grid Resolution

NASA Astrophysics Data System (ADS)

Vennam, L. P.; Vizuete, W.; Talgo, K.; Omary, M.; Binkowski, F. S.; Xing, J.; Mathur, R.; Arunachalam, S.

2017-12-01

Aviation is a unique anthropogenic source with four-dimensional varying emissions, peaking at cruise altitudes (9-12 km). Aircraft emission budgets in the upper troposphere lower stratosphere region and their potential impacts on upper troposphere and surface air quality are not well understood. Our key objective is to use chemical transport models (with prescribed meteorology) to predict aircraft emissions impacts on the troposphere and surface air quality. We quantified the importance of including full-flight intercontinental emissions and increased horizontal grid resolution. The full-flight aviation emissions in the Northern Hemisphere contributed 1.3% (mean, min-max: 0.46, 0.3-0.5 ppbv) and 0.2% (0.013, 0.004-0.02 μg/m3) of total O3 and PM2.5 concentrations at the surface, with Europe showing slightly higher impacts (1.9% (O3 0.69, 0.5-0.85 ppbv) and 0.5% (PM2.5 0.03, 0.01-0.05 μg/m3)) than North America (NA) and East Asia. We computed seasonal aviation-attributable mass flux vertical profiles and aviation perturbations along isentropic surfaces to quantify the transport of cruise altitude emissions at the hemispheric scale. The comparison of coarse (108 × 108 km2) and fine (36 × 36 km2) grid resolutions in NA showed 70 times and 13 times higher aviation impacts for O3 and PM2.5 in coarser domain. These differences are mainly due to the inability of the coarse resolution simulation to capture nonlinearities in chemical processes near airport locations and other urban areas. Future global studies quantifying aircraft contributions should consider model resolution and perhaps use finer scales near major aviation source regions.

Modeled Full-Flight Aircraft Emissions Impacts on Air Quality and Their Sensitivity to Grid Resolution

PubMed Central

Vennam, L. P.; Vizuete, W.; Talgo, K.; Omary, M.; Binkowski, F. S.; Xing, J.; Mathur, R.; Arunachalam, S.

2018-01-01

Aviation is a unique anthropogenic source with four-dimensional varying emissions, peaking at cruise altitudes (9–12 km). Aircraft emission budgets in the upper troposphere lower stratosphere region and their potential impacts on upper troposphere and surface air quality are not well understood. Our key objective is to use chemical transport models (with prescribed meteorology) to predict aircraft emissions impacts on the troposphere and surface air quality. We quantified the importance of including full-flight intercontinental emissions and increased horizontal grid resolution. The full-flight aviation emissions in the Northern Hemisphere contributed ~1.3% (mean, min–max: 0.46, 0.3–0.5 ppbv) and 0.2% (0.013, 0.004–0.02 μg/m3) of total O3 and PM2.5 concentrations at the surface, with Europe showing slightly higher impacts (1.9% (O3 0.69, 0.5–0.85 ppbv) and 0.5% (PM2.5 0.03, 0.01–0.05 μg/m3)) than North America (NA) and East Asia. We computed seasonal aviation-attributable mass flux vertical profiles and aviation perturbations along isentropic surfaces to quantify the transport of cruise altitude emissions at the hemispheric scale. The comparison of coarse (108 × 108 km2) and fine (36 × 36 km2) grid resolutions in NA showed ~70 times and ~13 times higher aviation impacts for O3 and PM2.5 in coarser domain. These differences are mainly due to the inability of the coarse resolution simulation to capture nonlinearities in chemical processes near airport locations and other urban areas. Future global studies quantifying aircraft contributions should consider model resolution and perhaps use finer scales near major aviation source regions. PMID:29707471

A Regional CO2 Observing System Simulation Experiment Using ASCENDS Observations and WRF-STILT Footprints

NASA Technical Reports Server (NTRS)

Wang, James S.; Kawa, S. Randolph; Eluszkiewicz, Janusz; Collatz, G. J.; Mountain, Marikate; Henderson, John; Nehrkorn, Thomas; Aschbrenner, Ryan; Zaccheo, T. Scott

2012-01-01

Knowledge of the spatiotemporal variations in emissions and uptake of CO2 is hampered by sparse measurements. The recent advent of satellite measurements of CO2 concentrations is increasing the density of measurements, and the future mission ASCENDS (Active Sensing of CO2 Emissions over Nights, Days and Seasons) will provide even greater coverage and precision. Lagrangian atmospheric transport models run backward in time can quantify surface influences ("footprints") of diverse measurement platforms and are particularly well suited for inverse estimation of regional surface CO2 fluxes at high resolution based on satellite observations. We utilize the STILT Lagrangian particle dispersion model, driven by WRF meteorological fields at 40-km resolution, in a Bayesian synthesis inversion approach to quantify the ability of ASCENDS column CO2 observations to constrain fluxes at high resolution. This study focuses on land-based biospheric fluxes, whose uncertainties are especially large, in a domain encompassing North America. We present results based on realistic input fields for 2007. Pseudo-observation random errors are estimated from backscatter and optical depth measured by the CALIPSO satellite. We estimate a priori flux uncertainties based on output from the CASA-GFED (v.3) biosphere model and make simple assumptions about spatial and temporal error correlations. WRF-STILT footprints are convolved with candidate vertical weighting functions for ASCENDS. We find that at a horizontal flux resolution of 1 degree x 1 degree, ASCENDS observations are potentially able to reduce average weekly flux uncertainties by 0-8% in July, and 0-0.5% in January (assuming an error of 0.5 ppm at the Railroad Valley reference site). Aggregated to coarser resolutions, e.g. 5 degrees x 5 degrees, the uncertainty reductions are larger and more similar to those estimated in previous satellite data observing system simulation experiments.

Modeled Full-Flight Aircraft Emissions Impacts on Air Quality and Their Sensitivity to Grid Resolution.

PubMed

Vennam, L P; Vizuete, W; Talgo, K; Omary, M; Binkowski, F S; Xing, J; Mathur, R; Arunachalam, S

2017-01-01

Aviation is a unique anthropogenic source with four-dimensional varying emissions, peaking at cruise altitudes (9-12 km). Aircraft emission budgets in the upper troposphere lower stratosphere region and their potential impacts on upper troposphere and surface air quality are not well understood. Our key objective is to use chemical transport models (with prescribed meteorology) to predict aircraft emissions impacts on the troposphere and surface air quality. We quantified the importance of including full-flight intercontinental emissions and increased horizontal grid resolution. The full-flight aviation emissions in the Northern Hemisphere contributed ~1.3% (mean, min-max: 0.46, 0.3-0.5 ppbv) and 0.2% (0.013, 0.004-0.02 μg/m 3 ) of total O 3 and PM 2.5 concentrations at the surface, with Europe showing slightly higher impacts (1.9% (O 3 0.69, 0.5-0.85 ppbv) and 0.5% (PM 2.5 0.03, 0.01-0.05 μg/m 3 )) than North America (NA) and East Asia. We computed seasonal aviation-attributable mass flux vertical profiles and aviation perturbations along isentropic surfaces to quantify the transport of cruise altitude emissions at the hemispheric scale. The comparison of coarse (108 × 108 km 2 ) and fine (36 × 36 km 2 ) grid resolutions in NA showed ~70 times and ~13 times higher aviation impacts for O 3 and PM 2.5 in coarser domain. These differences are mainly due to the inability of the coarse resolution simulation to capture nonlinearities in chemical processes near airport locations and other urban areas. Future global studies quantifying aircraft contributions should consider model resolution and perhaps use finer scales near major aviation source regions.

Marine ice sheet model performance depends on basal sliding physics and sub-shelf melting

NASA Astrophysics Data System (ADS)

Gladstone, Rupert Michael; Warner, Roland Charles; Galton-Fenzi, Benjamin Keith; Gagliardini, Olivier; Zwinger, Thomas; Greve, Ralf

2017-01-01

Computer models are necessary for understanding and predicting marine ice sheet behaviour. However, there is uncertainty over implementation of physical processes at the ice base, both for grounded and floating glacial ice. Here we implement several sliding relations in a marine ice sheet flow-line model accounting for all stress components and demonstrate that model resolution requirements are strongly dependent on both the choice of basal sliding relation and the spatial distribution of ice shelf basal melting.Sliding relations that reduce the magnitude of the step change in basal drag from grounded ice to floating ice (where basal drag is set to zero) show reduced dependence on resolution compared to a commonly used relation, in which basal drag is purely a power law function of basal ice velocity. Sliding relations in which basal drag goes smoothly to zero as the grounding line is approached from inland (due to a physically motivated incorporation of effective pressure at the bed) provide further reduction in resolution dependence.A similar issue is found with the imposition of basal melt under the floating part of the ice shelf: melt parameterisations that reduce the abruptness of change in basal melting from grounded ice (where basal melt is set to zero) to floating ice provide improved convergence with resolution compared to parameterisations in which high melt occurs adjacent to the grounding line.Thus physical processes, such as sub-glacial outflow (which could cause high melt near the grounding line), impact on capability to simulate marine ice sheets. If there exists an abrupt change across the grounding line in either basal drag or basal melting, then high resolution will be required to solve the problem. However, the plausible combination of a physical dependency of basal drag on effective pressure, and the possibility of low ice shelf basal melt rates next to the grounding line, may mean that some marine ice sheet systems can be reliably simulated at a coarser resolution than currently thought necessary.

Forecast of drifter trajectories using a Rapid Environmental Assessment based on CTD observations

NASA Astrophysics Data System (ADS)

Sorgente, R.; Tedesco, C.; Pessini, F.; De Dominicis, M.; Gerin, R.; Olita, A.; Fazioli, L.; Di Maio, A.; Ribotti, A.

2016-11-01

A high resolution submesoscale resolving ocean model was implemented in a limited area north of Island of Elba where a maritime exercise, named Serious Game 1 (SG1), took place on May 2014 in the framework of the project MEDESS-4MS (Mediterranean Decision Support System for Marine Safety). During the exercise, CTD data have been collected responding to the necessity of a Rapid Environmental Assessment, i.e. to a rapid evaluation of the marine conditions able to provide sensible information for initialisation of modelling tools, in the scenario of possible maritime accidents. The aim of this paper is to evaluate the impact of such mesoscale-resolving CTD observations on short-term forecasts of the surface currents, within the framework of possible oil-spill related emergencies. For this reason, modelling outputs were compared with Lagrangian observations at sea: the high resolution modelled currents, together with the ones of the coarser sub-regional model WMED, are used to force the MEDSLIK-II oil-spill model to simulate drifter trajectories. Both ocean models have been assessed by comparing the prognostic scalar and vector fields as an independent CTD data set and with real drifter trajectories acquired during SG1. The diagnosed and prognosed circulation reveals that the area was characterised by water masses of Atlantic origin influenced by small mesoscale cyclonic and anti-cyclonic eddies, which govern the spatial and temporal evolution of the drifter trajectories and of the water masses distribution. The assimilation of CTD data into the initial conditions of the high resolution model highly improves the accuracy of the short-term forecast in terms of location and structure of the thermocline and positively influence the ability of the model in reproducing the observed paths of the surface drifters.

Evaluation of the Surface Representation of the Greenland Ice Sheet in a General Circulation Model

NASA Technical Reports Server (NTRS)

Cullather, Richard I.; Nowicki, Sophie M. J.; Zhao, Bin; Suarez, Max J.

2014-01-01

Simulated surface conditions of the Goddard Earth Observing System model, version 5 (GEOS 5) atmospheric general circulation model (AGCM) are examined for the contemporary Greenland Ice Sheet (GrIS). A surface parameterization that explicitly models surface processes including snow compaction, meltwater percolation and refreezing, and surface albedo is found to remedy an erroneous deficit in the annual net surface energy flux and provide an adequate representation of surface mass balance (SMB) in an evaluation using simulations at two spatial resolutions. The simulated 1980-2008 GrIS SMB average is 24.7+/-4.5 cm yr(- 1) water-equivalent (w.e.) at.5 degree model grid spacing, and 18.2+/-3.3 cm yr(- 1) w.e. for 2 degree grid spacing. The spatial variability and seasonal cycle of the simulation compare favorably to recent studies using regional climate models, while results from 2 degree integrations reproduce the primary features of the SMB field. In comparison to historical glaciological observations, the coarser resolution model overestimates accumulation in the southern areas of the GrIS, while the overall SMB is underestimated. These changes relate to the sensitivity of accumulation and melt to the resolution of topography. The GEOS-5 SMB fields contrast with available corresponding atmospheric models simulations from the Coupled Model Intercomparison Project (CMIP5). It is found that only a few of the CMIP5 AGCMs examined provide significant summertime runoff, a dominant feature of the GrIS seasonal cycle. This is a condition that will need to be remedied if potential contributions to future eustatic change from polar ice sheets are to be examined with GCMs.

A new method to assess the added value of high-resolution regional climate simulations: application to the EURO-CORDEX dataset

NASA Astrophysics Data System (ADS)

Soares, P. M. M.; Cardoso, R. M.

2017-12-01

Regional climate models (RCM) are used with increasing resolutions pursuing to represent in an improved way regional to local scale atmospheric phenomena. The EURO-CORDEX simulations at 0.11° and simulations exploiting finer grid spacing approaching the convective-permitting regimes are representative examples. The climate runs are computationally very demanding and do not always show improvements. These depend on the region, variable and object of study. The gains or losses associated with the use of higher resolution in relation to the forcing model (global climate model or reanalysis), or to different resolution RCM simulations, is known as added value. Its characterization is a long-standing issue, and many different added-value measures have been proposed. In the current paper, a new method is proposed to assess the added value of finer resolution simulations, in comparison to its forcing data or coarser resolution counterparts. This approach builds on a probability density function (PDF) matching score, giving a normalised measure of the difference between diverse resolution PDFs, mediated by the observational ones. The distribution added value (DAV) is an objective added value measure that can be applied to any variable, region or temporal scale, from hindcast or historical (non-synchronous) simulations. The DAVs metric and an application to the EURO-CORDEX simulations, for daily temperatures and precipitation, are here presented. The EURO-CORDEX simulations at both resolutions (0.44o,0.11o) display a clear added value in relation to ERA-Interim, with values around 30% in summer and 20% in the intermediate seasons, for precipitation. When both RCM resolutions are directly compared the added value is limited. The regions with the larger precipitation DAVs are areas where convection is relevant, e.g. Alps and Iberia. When looking at the extreme precipitation PDF tail, the higher resolution improvement is generally greater than the low resolution for seasons and regions. For temperature, the added value is smaller. AcknowledgmentsThe authors wish to acknowledge SOLAR (PTDC/GEOMET/7078/2014) and FCT UID/GEO/50019/ 2013 (Instituto Dom Luiz) projects.

Resolving vorticity-driven lateral fire spread using the WRF-Fire coupled atmosphere-fire numerical model

NASA Astrophysics Data System (ADS)

Simpson, C. C.; Sharples, J. J.; Evans, J. P.

2014-09-01

Vorticity-driven lateral fire spread (VLS) is a form of dynamic fire behaviour, during which a wildland fire spreads rapidly across a steep leeward slope in a direction approximately transverse to the background winds. VLS is often accompanied by a downwind extension of the active flaming region and intense pyro-convection. In this study, the WRF-Fire (WRF stands for Weather Research and Forecasting) coupled atmosphere-fire model is used to examine the sensitivity of resolving VLS to both the horizontal and vertical grid spacing, and the fire-to-atmosphere coupling from within the model framework. The atmospheric horizontal and vertical grid spacing are varied between 25 and 90 m, and the fire-to-atmosphere coupling is either enabled or disabled. At high spatial resolutions, the inclusion of fire-to-atmosphere coupling increases the upslope and lateral rate of spread by factors of up to 2.7 and 9.5, respectively. This increase in the upslope and lateral rate of spread diminishes at coarser spatial resolutions, and VLS is not modelled for a horizontal and vertical grid spacing of 90 m. The lateral fire spread is driven by fire whirls formed due to an interaction between the background winds and the vertical circulation generated at the flank of the fire front as part of the pyro-convective updraft. The laterally advancing fire fronts become the dominant contributors to the extreme pyro-convection. The results presented in this study demonstrate that both high spatial resolution and two-way atmosphere-fire coupling are required to model VLS with WRF-Fire.

Spatial aspects of building and population exposure data and their implications for global earthquake exposure modeling

USGS Publications Warehouse

Dell’Acqua, F.; Gamba, P.; Jaiswal, K.

2012-01-01

This paper discusses spatial aspects of the global exposure dataset and mapping needs for earthquake risk assessment. We discuss this in the context of development of a Global Exposure Database for the Global Earthquake Model (GED4GEM), which requires compilation of a multi-scale inventory of assets at risk, for example, buildings, populations, and economic exposure. After defining the relevant spatial and geographic scales of interest, different procedures are proposed to disaggregate coarse-resolution data, to map them, and if necessary to infer missing data by using proxies. We discuss the advantages and limitations of these methodologies and detail the potentials of utilizing remote-sensing data. The latter is used especially to homogenize an existing coarser dataset and, where possible, replace it with detailed information extracted from remote sensing using the built-up indicators for different environments. Present research shows that the spatial aspects of earthquake risk computation are tightly connected with the availability of datasets of the resolution necessary for producing sufficiently detailed exposure. The global exposure database designed by the GED4GEM project is able to manage datasets and queries of multiple spatial scales.

Detailed Characterization of Nearshore Processes During NCEX

NASA Astrophysics Data System (ADS)

Holland, K.; Kaihatu, J. M.; Plant, N.

2004-12-01

Recent technology advances have allowed the coupling of remote sensing methods with advanced wave and circulation models to yield detailed characterizations of nearshore processes. This methodology was demonstrated as part of the Nearshore Canyon EXperiment (NCEX) in La Jolla, CA during Fall 2003. An array of high-resolution, color digital cameras was installed to monitor an alongshore distance of nearly 2 km out to depths of 25 m. This digital imagery was analyzed over the three-month period through an automated process to produce hourly estimates of wave period, wave direction, breaker height, shoreline position, sandbar location, and bathymetry at numerous locations during daylight hours. Interesting wave propagation patterns in the vicinity of the canyons were observed. In addition, directional wave spectra and swash / surf flow velocities were estimated using more computationally intensive methods. These measurements were used to provide forcing and boundary conditions for the Delft3D wave and circulation model, giving additional estimates of nearshore processes such as dissipation and rip currents. An optimal approach for coupling these remotely sensed observations to the numerical model was selected to yield accurate, but also timely characterizations. This involved assimilation of directional spectral estimates near the offshore boundary to mimic forcing conditions achieved under traditional approaches involving nested domains. Measurements of breaker heights and flow speeds were also used to adaptively tune model parameters to provide enhanced accuracy. Comparisons of model predictions and video observations show significant correlation. As compared to nesting within larger-scale and coarser resolution models, the advantages of providing boundary conditions data using remote sensing is much improved resolution and fidelity. For example, rip current development was both modeled and observed. These results indicate that this approach to data-model coupling is tenable and may be useful in near-real-time characterizations required by many applied scenarios.

Leveraging North Carolina's QL2 Lidar to Quantify Sensitivity of National Water Model Derived Flood Inundation Extent to DEM Resolution

NASA Astrophysics Data System (ADS)

Lovette, J. P.; Lenhardt, W. C.; Blanton, B.; Duncan, J. M.; Stillwell, L.

2017-12-01

The National Water Model (NWM) has provided a novel framework for near real time flood inundation mapping across CONUS at a 10m resolution. In many regions, this spatial scale is quickly being surpassed through the collection of high resolution lidar (1 - 3m). As one of the leading states in data collection for flood inundation mapping, North Carolina is currently improving their previously available 20 ft statewide elevation product to a Quality Level 2 (QL2) product with a nominal point spacing of 0.7 meters. This QL2 elevation product increases the ground points by roughly ten times over the previous statewide lidar product, and by over 250 times when compared to the 10m NED elevation grid. When combining these new lidar data with the discharge estimates from the NWM, we can further improve statewide flood inundation maps and predictions of at-risk areas. In the context of flood risk management, these improved predictions with higher resolution elevation models consistently represent an improvement on coarser products. Additionally, the QL2 lidar also includes coarse land cover classification data for each point return, opening the possibility for expanding analysis beyond the use of only digital elevation models (e.g. improving estimates of surface roughness, identifying anthropogenic features in floodplains, characterizing riparian zones, etc.). Using the NWM Height Above Nearest Drainage approach, we compare flood inundation extents derived from multiple lidar-derived grid resolutions to assess the tradeoff between precision and computational load in North Carolina's coastal river basins. The elevation data distributed through the state's new lidar collection program provide spatial resolutions ranging from 5-50 feet, with most inland areas also including a 3 ft product. Data storage increases by almost two orders of magnitude across this range, as does processing load. In order to further assess the validity of the higher resolution elevation products on flood inundation, we examine the NWM outputs from Hurricane Matthew, which devastated southeastern North Carolina in October 2016. When compared with numerous surveyed high water marks across the coastal plain, this assessment provides insight on the impacts of grid resolution on flood inundation extent.

Biocellion: accelerating computer simulation of multicellular biological system models.

PubMed

Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

2014-11-01

Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Effect of spatial averaging on multifractal properties of meteorological time series

NASA Astrophysics Data System (ADS)

Hoffmann, Holger; Baranowski, Piotr; Krzyszczak, Jaromir; Zubik, Monika

2016-04-01

Introduction The process-based models for large-scale simulations require input of agro-meteorological quantities that are often in the form of time series of coarse spatial resolution. Therefore, the knowledge about their scaling properties is fundamental for transferring locally measured fluctuations to larger scales and vice-versa. However, the scaling analysis of these quantities is complicated due to the presence of localized trends and non-stationarities. Here we assess how spatially aggregating meteorological data to coarser resolutions affects the data's temporal scaling properties. While it is known that spatial aggregation may affect spatial data properties (Hoffmann et al., 2015), it is unknown how it affects temporal data properties. Therefore, the objective of this study was to characterize the aggregation effect (AE) with regard to both temporal and spatial input data properties considering scaling properties (i.e. statistical self-similarity) of the chosen agro-meteorological time series through multifractal detrended fluctuation analysis (MFDFA). Materials and Methods Time series coming from years 1982-2011 were spatially averaged from 1 to 10, 25, 50 and 100 km resolution to assess the impact of spatial aggregation. Daily minimum, mean and maximum air temperature (2 m), precipitation, global radiation, wind speed and relative humidity (Zhao et al., 2015) were used. To reveal the multifractal structure of the time series, we used the procedure described in Baranowski et al. (2015). The diversity of the studied multifractals was evaluated by the parameters of time series spectra. In order to analyse differences in multifractal properties to 1 km resolution grids, data of coarser resolutions was disaggregated to 1 km. Results and Conclusions Analysing the spatial averaging on multifractal properties we observed that spatial patterns of the multifractal spectrum (MS) of all meteorological variables differed from 1 km grids and MS-parameters were biased by -29.1 % (precipitation; width of MS) up to >4 % (min. Temperature, Radiation; asymmetry of MS). Also, the spatial variability of MS parameters was strongly affected at the highest aggregation (100 km). Obtained results confirm that spatial data aggregation may strongly affect temporal scaling properties. This should be taken into account when upscaling for large-scale studies. Acknowledgements The study was conducted within FACCE MACSUR. Please see Baranowski et al. (2015) for details on funding. References Baranowski, P., Krzyszczak, J., Sławiński, C. et al. (2015). Climate Research 65, 39-52. Hoffman, H., G. Zhao, L.G.J. Van Bussel et al. (2015). Climate Research 65, 53-69. Zhao, G., Siebert, S., Rezaei E. et al. (2015). Agricultural and Forest Meteorology 200, 156-171.

Sensitivity of chemistry-transport model simulations to the duration of chemical and transport operators: a case study with GEOS-Chem v10-01

NASA Astrophysics Data System (ADS)

Philip, Sajeev; Martin, Randall V.; Keller, Christoph A.

2016-05-01

Chemistry-transport models involve considerable computational expense. Fine temporal resolution offers accuracy at the expense of computation time. Assessment is needed of the sensitivity of simulation accuracy to the duration of chemical and transport operators. We conduct a series of simulations with the GEOS-Chem chemistry-transport model at different temporal and spatial resolutions to examine the sensitivity of simulated atmospheric composition to operator duration. Subsequently, we compare the species simulated with operator durations from 10 to 60 min as typically used by global chemistry-transport models, and identify the operator durations that optimize both computational expense and simulation accuracy. We find that longer continuous transport operator duration increases concentrations of emitted species such as nitrogen oxides and carbon monoxide since a more homogeneous distribution reduces loss through chemical reactions and dry deposition. The increased concentrations of ozone precursors increase ozone production with longer transport operator duration. Longer chemical operator duration decreases sulfate and ammonium but increases nitrate due to feedbacks with in-cloud sulfur dioxide oxidation and aerosol thermodynamics. The simulation duration decreases by up to a factor of 5 from fine (5 min) to coarse (60 min) operator duration. We assess the change in simulation accuracy with resolution by comparing the root mean square difference in ground-level concentrations of nitrogen oxides, secondary inorganic aerosols, ozone and carbon monoxide with a finer temporal or spatial resolution taken as "truth". Relative simulation error for these species increases by more than a factor of 5 from the shortest (5 min) to longest (60 min) operator duration. Chemical operator duration twice that of the transport operator duration offers more simulation accuracy per unit computation. However, the relative simulation error from coarser spatial resolution generally exceeds that from longer operator duration; e.g., degrading from 2° × 2.5° to 4° × 5° increases error by an order of magnitude. We recommend prioritizing fine spatial resolution before considering different operator durations in offline chemistry-transport models. We encourage chemistry-transport model users to specify in publications the durations of operators due to their effects on simulation accuracy.

Hydrological regime as key to the morpho-texture and activity of braided streams

NASA Astrophysics Data System (ADS)

Storz-Peretz, Y.; Laronne, J. B.

2012-04-01

Braided streams are a common fluvial pattern in different climates. However, studies of gravel braided streams have mainly been conducted in humid braided systems or in flume simulations thereof, leaving arid braided streams scarcely investigated. Dryland rivers have bare catchments, rapid flow recession and unarmoured channel beds which are responsible for very high bedload discharges, thereby increasing the likelihood for braiding. Our main objective is to characterize the morpho-texture of the main morphological elements - mid-channel bars, chutes and anabranches (braid-cells) in the dryland braided system and compare them to their humid counterparts. Selected areas of the dryland braided Wadis Ze'elim, Rahaf and Roded in the SE hyper-arid Israel were measured, as were La-Bleone river in the French pre-alps along with the Saisera and Cimoliana rivers in NE Italy representing humid braided systems. Terrestrial Laser Scanning (TLS) of morphological units produced point clouds from which high resolution accurate Digital Elevation Models (DEMs) were extracted. Active braid cells in humid environments were also surveyed by electronic theodolite. Roughness and upper tail Grain Size Distribution (GSD) quantiles were derived from the scanned point clouds or from Wolman sampling. Results indicate that dryland anabranches tend to be finer-grained and less armoured than the bars, contrary to the humid braided systems, where the main or larger anabranches are coarser-grained and more armoured than the bars. Chutes are commonly similar or coarser-grained than the bars they dissect, in accordance with their steeper gradients due to the considerable relief of the bar-anabranch. The morpho-texture displayed in the steep braided Saisera River, located in the Italian Dolomites having the highest annual precipitation, has similarity to that of the dryland braided channels. In drylands coarse gravel is deposited mainly as bars due to the high flux of bedload, whereas the rapid flow recession is responsible for deposition of finer sediment with minimal winnowing in the branch channels. Therefore, channels are finer-grained than the bars. This process is associated with the mid-channel deposition of central bars. However, the steeper chutes and coarser anabranches are associated with erosive braiding processes, such as chute cutoffs and multiple bar dissection, allowing winnowing to occur also during rapid recession. Hence coarser-grained anabranches in drylands are essentially chutes. Lengthy flow recession in humid braided channels allows winnowing of fines, thereby generating armored channels, the finer sedimentary particles often deposited downstream as unit bars. Therefore, channels are coarser-grained than the bars they surround. Even though the steep Saisera is in a humid region, its hydrological regime is ephemeral with rapid and short recessions, responsible for a morpho-texture similar to that of dryland braided streams. Hence, the hydrologic regimen is a key to understanding the morpho-textural character of braided channels and for the higher activity of the ephemeral unarmoured channels in sub-barful events compared to their humid counterparts.

Regional simulation of Indian summer monsoon intraseasonal oscillations at gray-zone resolution

NASA Astrophysics Data System (ADS)

Chen, Xingchao; Pauluis, Olivier M.; Zhang, Fuqing

2018-01-01

Simulations of the Indian summer monsoon by the cloud-permitting Weather Research and Forecasting (WRF) model at gray-zone resolution are described in this study, with a particular emphasis on the model ability to capture the monsoon intraseasonal oscillations (MISOs). Five boreal summers are simulated from 2007 to 2011 using the ERA-Interim reanalysis as the lateral boundary forcing data. Our experimental setup relies on a horizontal grid spacing of 9 km to explicitly simulate deep convection without the use of cumulus parameterizations. When compared to simulations with coarser grid spacing (27 km) and using a cumulus scheme, the 9 km simulations reduce the biases in mean precipitation and produce more realistic low-frequency variability associated with MISOs. Results show that the model at the 9 km gray-zone resolution captures the salient features of the summer monsoon. The spatial distributions and temporal evolutions of monsoon rainfall in the WRF simulations verify qualitatively well against observations from the Tropical Rainfall Measurement Mission (TRMM), with regional maxima located over Western Ghats, central India, Himalaya foothills, and the west coast of Myanmar. The onset, breaks, and withdrawal of the summer monsoon in each year are also realistically captured by the model. The MISO-phase composites of monsoon rainfall, low-level wind, and precipitable water anomalies in the simulations also agree qualitatively with the observations. Both the simulations and observations show a northeastward propagation of the MISOs, with the intensification and weakening of the Somali Jet over the Arabian Sea during the active and break phases of the Indian summer monsoon.

Multi Scale Modeling of Continuous Aramid Fiber Reinforced Polymer Matrix Composites Used in Ballistic Protection Applications

DTIC Science & Technology

2014-11-16

related to identification of the type and the extent of data generated at a finer length scale to the adjacent coarser length scale, as well as seamless ...data generated at a finer length scale to the adjacent coarser length scale, as well as seamless integration of different length scales into a unified...composite laminate consisting of 32 laminae and impacted (at a 0° obliquity angle and an incident velocity of 500 m/s) by a 0.30 caliber steel

Incorporating Sentinel-2-like remote sensing products in the hydrometeorological modelling over an agricultural area in south west France

NASA Astrophysics Data System (ADS)

Rivalland, Vincent; Gascoin, Simon; Etchanchu, Jordi; Coustau, Mathieu; Cros, Jérôme; Tallec, Tiphaine

2016-04-01

The Sentinel-2 mission will enable to monitor the land cover and the vegetation phenology at high-resolution (HR) every 5 days. However, current Land Surface Models (LSM) typically use land cover and vegetation parameters derived from previous low to mid resolution satellite missions. Here we studied the effect of introducing Sentinel-2-like data in the simulation of the land surface energy and water fluxes in a region dominated by cropland. Simulations were performed with the ISBA-SURFEX LSM, which is used in the operational hydrometeorological chain of Meteo-France for hydrological forecasts and drought monitoring. By default, SURFEX vegetation land surface parameters and temporal evolution are from the ECOCLIMAP II European database mostly derived from MODIS products at 1 km resolution. The model was applied to an experimental area of 30 km by 30 km in south west France. In this area the resolution of ECOCLIMAP is coarser than the typical size of a crop field. This means that several crop types can be mixed in a pixel. In addition ECOCLIMAP provides a climatology of the vegetation phenology and thus does not account for the interannual effects of the climate and land management on the crop growth. In this work, we used a series of 26 Formosat-2 images at 8-m resolution acquired in 2006. From this dataset, we derived a land cover map and a leaf area index map (LAI) at each date, which were substituted to the ECOCLIMAP land cover map and the LAI maps. The model output water and energy fluxes were compared to a standard simulation using ECOCLIMAP only and to in situ measurements of soil moisture, latent and sensible heat fluxes. The results show that the introduction of the HR products improved the timing of the evapotranspiration. The impact was the most visible on the crops having a growing season in summer (maize, sunflower), because the growth period is more sensitive to the climate.

Full Spatial Resolution Infrared Sounding Application in the Preconvection Environment

NASA Astrophysics Data System (ADS)

Liu, C.; Liu, G.; Lin, T.

2013-12-01

Advanced infrared (IR) sounders such as the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI) provide atmospheric temperature and moisture profiles with high vertical resolution and high accuracy in preconvection environments. The derived atmospheric stability indices such as convective available potential energy (CAPE) and lifted index (LI) from advanced IR soundings can provide critical information 1 ; 6 h before the development of severe convective storms. Three convective storms are selected for the evaluation of applying AIRS full spatial resolution soundings and the derived products on providing warning information in the preconvection environments. In the first case, the AIRS full spatial resolution soundings revealed local extremely high atmospheric instability 3 h ahead of the convection on the leading edge of a frontal system, while the second case demonstrates that the extremely high atmospheric instability is associated with the local development of severe thunderstorm in the following hours. The third case is a local severe storm that occurred on 7-8 August 2010 in Zhou Qu, China, which caused more than 1400 deaths and left another 300 or more people missing. The AIRS full spatial resolution LI product shows the atmospheric instability 3.5 h before the storm genesis. The CAPE and LI from AIRS full spatial resolution and operational AIRS/AMSU soundings along with Geostationary Operational Environmental Satellite (GOES) Sounder derived product image (DPI) products were analyzed and compared. Case studies show that full spatial resolution AIRS retrievals provide more useful warning information in the preconvection environments for determining favorable locations for convective initiation (CI) than do the coarser spatial resolution operational soundings and lower spectral resolution GOES Sounder retrievals. The retrieved soundings are also tested in a regional data assimilation WRF 3D-var system to evaluate the potential assist in the NWP model.

High resolution climate scenarios for snowmelt modelling in small alpine catchments

NASA Astrophysics Data System (ADS)

Schirmer, M.; Peleg, N.; Burlando, P.; Jonas, T.

2017-12-01

Snow in the Alps is affected by climate change with regard to duration, timing and amount. This has implications with respect to important societal issues as drinking water supply or hydropower generation. In Switzerland, the latter received a lot of attention following the political decision to phase out of nuclear electricity production. An increasing number of authorization requests for small hydropower plants located in small alpine catchments was observed in the recent years. This situation generates ecological conflicts, while the expected climate change poses a threat to water availability thus putting at risk investments in such hydropower plants. Reliable high-resolution climate scenarios are thus required, which account for small-scale processes to achieve realistic predictions of snowmelt runoff and its variability in small alpine catchments. We therefore used a novel model chain by coupling a stochastic 2-dimensional weather generator (AWE-GEN-2d) with a state-of-the-art energy balance snow cover model (FSM). AWE-GEN-2d was applied to generate ensembles of climate variables at very fine temporal and spatial resolution, thus providing all climatic input variables required for the energy balance modelling. The land-surface model FSM was used to describe spatially variable snow cover accumulation and melt processes. The FSM was refined to allow applications at very high spatial resolution by specifically accounting for small-scale processes, such as a subgrid-parametrization of snow covered area or an improved representation of forest-snow processes. For the present study, the model chain was tested for current climate conditions using extensive observational dataset of different spatial and temporal coverage. Small-scale spatial processes such as elevation gradients or aspect differences in the snow distribution were evaluated using airborne LiDAR data. 40-year of monitoring data for snow water equivalent, snowmelt and snow-covered area for entire Switzerland was used to verify snow distribution patterns at coarser spatial and temporal scale. The ability of the model chain to reproduce current climate conditions in small alpine catchments makes this model combination an outstanding candidate to produce high resolution climate scenarios of snowmelt in small alpine catchments.

Potential for added value in precipitation simulated by high-resolution nested Regional Climate Models and observations

NASA Astrophysics Data System (ADS)

di Luca, Alejandro; de Elía, Ramón; Laprise, René

2012-03-01

Regional Climate Models (RCMs) constitute the most often used method to perform affordable high-resolution regional climate simulations. The key issue in the evaluation of nested regional models is to determine whether RCM simulations improve the representation of climatic statistics compared to the driving data, that is, whether RCMs add value. In this study we examine a necessary condition that some climate statistics derived from the precipitation field must satisfy in order that the RCM technique can generate some added value: we focus on whether the climate statistics of interest contain some fine spatial-scale variability that would be absent on a coarser grid. The presence and magnitude of fine-scale precipitation variance required to adequately describe a given climate statistics will then be used to quantify the potential added value (PAV) of RCMs. Our results show that the PAV of RCMs is much higher for short temporal scales (e.g., 3-hourly data) than for long temporal scales (16-day average data) due to the filtering resulting from the time-averaging process. PAV is higher in warm season compared to cold season due to the higher proportion of precipitation falling from small-scale weather systems in the warm season. In regions of complex topography, the orographic forcing induces an extra component of PAV, no matter the season or the temporal scale considered. The PAV is also estimated using high-resolution datasets based on observations allowing the evaluation of the sensitivity of changing resolution in the real climate system. The results show that RCMs tend to reproduce relatively well the PAV compared to observations although showing an overestimation of the PAV in warm season and mountainous regions.

Finding the best resolution for the Kingman-Tajima coalescent: theory and applications.

PubMed

Sainudiin, Raazesh; Stadler, Tanja; Véber, Amandine

2015-05-01

Many summary statistics currently used in population genetics and in phylogenetics depend only on a rather coarse resolution of the underlying tree (the number of extant lineages, for example). Hence, for computational purposes, working directly on these resolutions appears to be much more efficient. However, this approach seems to have been overlooked in the past. In this paper, we describe six different resolutions of the Kingman-Tajima coalescent together with the corresponding Markov chains, which are essential for inference methods. Two of the resolutions are the well-known n-coalescent and the lineage death process due to Kingman. Two other resolutions were mentioned by Kingman and Tajima, but never explicitly formalized. Another two resolutions are novel, and complete the picture of a multi-resolution coalescent. For all of them, we provide the forward and backward transition probabilities, the probability of visiting a given state as well as the probability of a given realization of the full Markov chain. We also provide a description of the state-space that highlights the computational gain obtained by working with lower-resolution objects. Finally, we give several examples of summary statistics that depend on a coarser resolution of Kingman's coalescent, on which simulations are usually based.

Scaling a Convection-Resolving RCM to Near-Global Scales

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Adaptively Parameterized Tomography of the Western Hellenic Subduction Zone

NASA Astrophysics Data System (ADS)

Hansen, S. E.; Papadopoulos, G. A.

2017-12-01

The Hellenic subduction zone (HSZ) is the most seismically active region in Europe and plays a major role in the active tectonics of the eastern Mediterranean. This complicated environment has the potential to generate both large magnitude (M > 8) earthquakes and tsunamis. Situated above the western end of the HSZ, Greece faces a high risk from these geologic hazards, and characterizing this risk requires detailed understanding of the geodynamic processes occurring in this area. However, despite previous investigations, the kinematics of the HSZ are still controversial. Regional tomographic studies have yielded important information about the shallow seismic structure of the HSZ, but these models only image down to 150 km depth within small geographic areas. Deeper structure is constrained by global tomographic models but with coarser resolution ( 200-300 km). Additionally, current tomographic models focused on the HSZ were generated with regularly-spaced gridding, and this type of parameterization often over-emphasizes poorly sampled regions of the model or under-represents small-scale structure. Therefore, we are developing a new, high-resolution image of the mantle structure beneath the western HSZ using an adaptively parameterized seismic tomography approach. By combining multiple, regional travel-time datasets in the context of a global model, with adaptable gridding based on the sampling density of high-frequency data, this method generates a composite model of mantle structure that is being used to better characterize geodynamic processes within the HSZ, thereby allowing for improved hazard assessment. Preliminary results will be shown.

Additional studies of forest classification accuracy as influenced by multispectral scanner spatial resolution

NASA Technical Reports Server (NTRS)

Sadowski, F. E.; Sarno, J. E.

1976-01-01

First, an analysis of forest feature signatures was used to help explain the large variation in classification accuracy that can occur among individual forest features for any one case of spatial resolution and the inconsistent changes in classification accuracy that were demonstrated among features as spatial resolution was degraded. Second, the classification rejection threshold was varied in an effort to reduce the large proportion of unclassified resolution elements that previously appeared in the processing of coarse resolution data when a constant rejection threshold was used for all cases of spatial resolution. For the signature analysis, two-channel ellipse plots showing the feature signature distributions for several cases of spatial resolution indicated that the capability of signatures to correctly identify their respective features is dependent on the amount of statistical overlap among signatures. Reductions in signature variance that occur in data of degraded spatial resolution may not necessarily decrease the amount of statistical overlap among signatures having large variance and small mean separations. Features classified by such signatures may thus continue to have similar amounts of misclassified elements in coarser resolution data, and thus, not necessarily improve in classification accuracy.

Broadband Heating Rate Profile Project (BBHRP) - SGP ripbe370mcfarlane

DOE Data Explorer

Riihimaki, Laura; Shippert, Timothy

2014-11-05

The objective of the ARM Broadband Heating Rate Profile (BBHRP) Project is to provide a structure for the comprehensive assessment of our ability to model atmospheric radiative transfer for all conditions. Required inputs to BBHRP include surface albedo and profiles of atmospheric state (temperature, humidity), gas concentrations, aerosol properties, and cloud properties. In the past year, the Radiatively Important Parameters Best Estimate (RIPBE) VAP was developed to combine all of the input properties needed for BBHRP into a single gridded input file. Additionally, an interface between the RIPBE input file and the RRTM was developed using the new ARM integrated software development environment (ISDE) and effort was put into developing quality control (qc) flags and provenance information on the BBHRP output files so that analysis of the output would be more straightforward. This new version of BBHRP, sgp1bbhrpripbeC1.c1, uses the RIPBE files as input to RRTM, and calculates broadband SW and LW fluxes and heating rates at 1-min resolution using the independent column approximation. The vertical resolution is 45 m in the lower and middle troposphere to match the input cloud properties, but is at coarser resolution in the upper atmosphere. Unlike previous versions, the vertical grid is the same for both clear-sky and cloudy-sky calculations.

Broadband Heating Rate Profile Project (BBHRP) - SGP 1bbhrpripbe1mcfarlane

DOE Data Explorer

Riihimaki, Laura; Shippert, Timothy

2014-11-05

The objective of the ARM Broadband Heating Rate Profile (BBHRP) Project is to provide a structure for the comprehensive assessment of our ability to model atmospheric radiative transfer for all conditions. Required inputs to BBHRP include surface albedo and profiles of atmospheric state (temperature, humidity), gas concentrations, aerosol properties, and cloud properties. In the past year, the Radiatively Important Parameters Best Estimate (RIPBE) VAP was developed to combine all of the input properties needed for BBHRP into a single gridded input file. Additionally, an interface between the RIPBE input file and the RRTM was developed using the new ARM integrated software development environment (ISDE) and effort was put into developing quality control (qc) flags and provenance information on the BBHRP output files so that analysis of the output would be more straightforward. This new version of BBHRP, sgp1bbhrpripbeC1.c1, uses the RIPBE files as input to RRTM, and calculates broadband SW and LW fluxes and heating rates at 1-min resolution using the independent column approximation. The vertical resolution is 45 m in the lower and middle troposphere to match the input cloud properties, but is at coarser resolution in the upper atmosphere. Unlike previous versions, the vertical grid is the same for both clear-sky and cloudy-sky calculations.

Broadband Heating Rate Profile Project (BBHRP) - SGP ripbe1mcfarlane

DOE Data Explorer

Riihimaki, Laura; Shippert, Timothy

2014-11-05

The objective of the ARM Broadband Heating Rate Profile (BBHRP) Project is to provide a structure for the comprehensive assessment of our ability to model atmospheric radiative transfer for all conditions. Required inputs to BBHRP include surface albedo and profiles of atmospheric state (temperature, humidity), gas concentrations, aerosol properties, and cloud properties. In the past year, the Radiatively Important Parameters Best Estimate (RIPBE) VAP was developed to combine all of the input properties needed for BBHRP into a single gridded input file. Additionally, an interface between the RIPBE input file and the RRTM was developed using the new ARM integrated software development environment (ISDE) and effort was put into developing quality control (qc) flags and provenance information on the BBHRP output files so that analysis of the output would be more straightforward. This new version of BBHRP, sgp1bbhrpripbeC1.c1, uses the RIPBE files as input to RRTM, and calculates broadband SW and LW fluxes and heating rates at 1-min resolution using the independent column approximation. The vertical resolution is 45 m in the lower and middle troposphere to match the input cloud properties, but is at coarser resolution in the upper atmosphere. Unlike previous versions, the vertical grid is the same for both clear-sky and cloudy-sky calculations.

Spatial Resolution Effect on Forest Road Gradient Calculation and Erosion Modelling

NASA Astrophysics Data System (ADS)

Cao, L.; Elliot, W.

2017-12-01

Road erosion is one of the main sediment sources in a forest watershed and should be properly evaluated. With the help of GIS technology, road topography can be determined and soil loss can be predicted at a watershed scale. As a vector geographical feature, the road gradient should be calculated following road direction rather than hillslope direction. This calculation might be difficult with a coarse (30-m) DEM which only provides the underlying topography information. This study was designed to explore the effect of road segmentation and DEM resolution on the road gradient calculation and erosion prediction at a watershed scale. The Water Erosion Prediction Project (WEPP) model was run on road segments of 9 lengths ranging from 40m to 200m. Road gradient was calculated from three DEM data sets: 1m LiDAR, and 10m and 30m USGS DEMs. The 1m LiDAR DEM calculated gradients were very close to the field observed road gradients, so we assumed the 1m LiDAR DEM predicted the true road gradient. The results revealed that longer road segments skipped detail topographical undulations and resulted in lower road gradients. Coarser DEMs computed steeper road gradients as larger grid cells covered more adjacent areas outside road resulting in larger elevation differences. Field surveyed results also revealed that coarser DEM might result in more gradient deviation in a curved road segment when it passes through a convex or concave slope. As road segment length increased, the gradient difference between three DEMs was reduced. There were no significant differences between road gradients of different segment lengths and DEM resolution when segments were longer than 100m. For long segments, the 10m DEM calculated road gradient was similar to the 1m LiDAR gradient. When evaluating the effects of road segment length, the predicted erosion rate decreased with increasing length when road gradient was less than 3%. In cases where the road gradients exceed 3% and rill erosion dominates, predicted erosion rates exponentially increased with segment length. At the watershed scale, most of the predicted soil loss occurred on segments with gradients ranging from 3% to 9%. Based on the road gradient calculated with the 10-m and 30-m DEMs, soil loss was overestimated when compared to the 1m LiDAR DEM. Both the 10m and 30m DEM result in similar total road soil loss.

Evaluation of the Actuator Line Model with coarse resolutions

NASA Astrophysics Data System (ADS)

Draper, M.; Usera, G.

2015-06-01

The aim of the present paper is to evaluate the Actuator Line Model (ALM) in spatial resolutions coarser than what is generally recommended, also using larger time steps. To accomplish this, the ALM has been implemented in the open source code caffa3d.MBRi and validated against experimental measurements of two wind tunnel campaigns (stand alone wind turbine and two wind turbines in line, case A and B respectively), taking into account two spatial resolutions: R/8 and R/15 (R is the rotor radius). A sensitivity analysis in case A was performed in order to get some insight into the influence of the smearing factor (3D Gaussian distribution) and time step size in power and thrust, as well as in the wake, without applying a tip loss correction factor (TLCF), for one tip speed ratio (TSR). It is concluded that as the smearing factor is larger or time step size is smaller the power is increased, but the velocity deficit is not as much affected. From this analysis, a smearing factor was obtained in order to calculate precisely the power coefficient for that TSR without applying TLCF. Results with this approach were compared with another simulation choosing a larger smearing factor and applying Prandtl's TLCF, for three values of TSR. It is found that applying the TLCF improves the power estimation and weakens the influence of the smearing factor. Finally, these 2 alternatives were tested in case B, confirming that conclusion.

Concurrent multiscale modeling of microstructural effects on localization behavior in finite deformation solid mechanics

DOE PAGES

Alleman, Coleman N.; Foulk, James W.; Mota, Alejandro; ...

2017-11-06

The heterogeneity in mechanical fields introduced by microstructure plays a critical role in the localization of deformation. In order to resolve this incipient stage of failure, it is therefore necessary to incorporate microstructure with sufficient resolution. On the other hand, computational limitations make it infeasible to represent the microstructure in the entire domain at the component scale. Here, the authors demonstrate the use of concurrent multiscale modeling to incorporate explicit, finely resolved microstructure in a critical region while resolving the smoother mechanical fields outside this region with a coarser discretization to limit computational cost. The microstructural physics is modeled withmore » a high-fidelity model that incorporates anisotropic crystal elasticity and rate-dependent crystal plasticity to simulate the behavior of a stainless steel alloy. The component-scale material behavior is treated with a lower fidelity model incorporating isotropic linear elasticity and rate-independent J 2 plasticity. The microstructural and component scale subdomains are modeled concurrently, with coupling via the Schwarz alternating method, which solves boundary-value problems in each subdomain separately and transfers solution information between subdomains via Dirichlet boundary conditions. In this study, the framework is applied to model incipient localization in tensile specimens during necking.« less

Concurrent multiscale modeling of microstructural effects on localization behavior in finite deformation solid mechanics

NASA Astrophysics Data System (ADS)

Alleman, Coleman N.; Foulk, James W.; Mota, Alejandro; Lim, Hojun; Littlewood, David J.

2018-02-01

The heterogeneity in mechanical fields introduced by microstructure plays a critical role in the localization of deformation. To resolve this incipient stage of failure, it is therefore necessary to incorporate microstructure with sufficient resolution. On the other hand, computational limitations make it infeasible to represent the microstructure in the entire domain at the component scale. In this study, the authors demonstrate the use of concurrent multiscale modeling to incorporate explicit, finely resolved microstructure in a critical region while resolving the smoother mechanical fields outside this region with a coarser discretization to limit computational cost. The microstructural physics is modeled with a high-fidelity model that incorporates anisotropic crystal elasticity and rate-dependent crystal plasticity to simulate the behavior of a stainless steel alloy. The component-scale material behavior is treated with a lower fidelity model incorporating isotropic linear elasticity and rate-independent J2 plasticity. The microstructural and component scale subdomains are modeled concurrently, with coupling via the Schwarz alternating method, which solves boundary-value problems in each subdomain separately and transfers solution information between subdomains via Dirichlet boundary conditions. In this study, the framework is applied to model incipient localization in tensile specimens during necking.

Concurrent multiscale modeling of microstructural effects on localization behavior in finite deformation solid mechanics

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

Alleman, Coleman N.; Foulk, James W.; Mota, Alejandro

The heterogeneity in mechanical fields introduced by microstructure plays a critical role in the localization of deformation. In order to resolve this incipient stage of failure, it is therefore necessary to incorporate microstructure with sufficient resolution. On the other hand, computational limitations make it infeasible to represent the microstructure in the entire domain at the component scale. Here, the authors demonstrate the use of concurrent multiscale modeling to incorporate explicit, finely resolved microstructure in a critical region while resolving the smoother mechanical fields outside this region with a coarser discretization to limit computational cost. The microstructural physics is modeled withmore » a high-fidelity model that incorporates anisotropic crystal elasticity and rate-dependent crystal plasticity to simulate the behavior of a stainless steel alloy. The component-scale material behavior is treated with a lower fidelity model incorporating isotropic linear elasticity and rate-independent J 2 plasticity. The microstructural and component scale subdomains are modeled concurrently, with coupling via the Schwarz alternating method, which solves boundary-value problems in each subdomain separately and transfers solution information between subdomains via Dirichlet boundary conditions. In this study, the framework is applied to model incipient localization in tensile specimens during necking.« less

Multiple Point Statistics algorithm based on direct sampling and multi-resolution images

NASA Astrophysics Data System (ADS)

Julien, S.; Renard, P.; Chugunova, T.

2017-12-01

Multiple Point Statistics (MPS) has become popular for more than one decade in Earth Sciences, because these methods allow to generate random fields reproducing highly complex spatial features given in a conceptual model, the training image, while classical geostatistics techniques based on bi-point statistics (covariance or variogram) fail to generate realistic models. Among MPS methods, the direct sampling consists in borrowing patterns from the training image to populate a simulation grid. This latter is sequentially filled by visiting each of these nodes in a random order, and then the patterns, whose the number of nodes is fixed, become narrower during the simulation process, as the simulation grid is more densely informed. Hence, large scale structures are caught in the beginning of the simulation and small scale ones in the end. However, MPS may mix spatial characteristics distinguishable at different scales in the training image, and then loose the spatial arrangement of different structures. To overcome this limitation, we propose to perform MPS simulation using a decomposition of the training image in a set of images at multiple resolutions. Applying a Gaussian kernel onto the training image (convolution) results in a lower resolution image, and iterating this process, a pyramid of images depicting fewer details at each level is built, as it can be done in image processing for example to lighten the space storage of a photography. The direct sampling is then employed to simulate the lowest resolution level, and then to simulate each level, up to the finest resolution, conditioned to the level one rank coarser. This scheme helps reproduce the spatial structures at any scale of the training image and then generate more realistic models. We illustrate the method with aerial photographies (satellite images) and natural textures. Indeed, these kinds of images often display typical structures at different scales and are well-suited for MPS simulation techniques.

Finely Resolved On-Road PM2.5 and Estimated Premature Mortality in Central North Carolina.

PubMed

Chang, Shih Ying; Vizuete, William; Serre, Marc; Vennam, Lakshmi Pradeepa; Omary, Mohammad; Isakov, Vlad; Breen, Michael; Arunachalam, Saravanan

2017-12-01

To quantify the on-road PM 2.5 -related premature mortality at a national scale, previous approaches to estimate concentrations at a 12-km × 12-km or larger grid cell resolution may not fully characterize concentration hotspots that occur near roadways and thus the areas of highest risk. Spatially resolved concentration estimates from on-road emissions to capture these hotspots may improve characterization of the associated risk, but are rarely used for estimating premature mortality. In this study, we compared the on-road PM 2.5 -related premature mortality in central North Carolina with two different concentration estimation approaches-(i) using the Community Multiscale Air Quality (CMAQ) model to model concentration at a coarser resolution of a 36-km × 36-km grid resolution, and (ii) using a hybrid of a Gaussian dispersion model, CMAQ, and a space-time interpolation technique to provide annual average PM 2.5 concentrations at a Census-block level (∼105,000 Census blocks). The hybrid modeling approach estimated 24% more on-road PM 2.5 -related premature mortality than CMAQ. The major difference is from the primary on-road PM 2.5 where the hybrid approach estimated 2.5 times more primary on-road PM 2.5 -related premature mortality than CMAQ due to predicted exposure hotspots near roadways that coincide with high population areas. The results show that 72% of primary on-road PM 2.5 premature mortality occurs within 1,000 m from roadways where 50% of the total population resides, highlighting the importance to characterize near-road primary PM 2.5 and suggesting that previous studies may have underestimated premature mortality due to PM 2.5 from traffic-related emissions. © 2017 Society for Risk Analysis.

Three-dimensional hydrodynamic Bondi-Hoyle accretion. 2: Homogeneous medium at Mach 3 with gamma = 5/3

NASA Technical Reports Server (NTRS)

Ruffert, Maximilian; Arnett, David

1994-01-01

We investigate the hydrodynamics of three-dimensional classical Bondi-Hoyle accretion. Totally absorbing spheres of varying sizes (from 10 down to 0.01 accretion radii) move at Mach 3 relative to a homogeneous and slightly perturbed medium, which is taken to be an ideal gas (gamma = 5/3). To accommodate the long-range gravitational forces, the extent of the computational volume is 32(exp 3) accretion radii. We examine the influence of numerical procedure on physical behavior. The hydrodynamics is modeled by the 'piecewise parabolic method.' No energy sources (nuclear burning) or sinks (radiation, conduction) are included. The resolution in the vicinity of the accretor is increased by multiply nesting several (5-10) grids around the sphere, each finer grid being a factor of 2 smaller in zone dimension that the next coarser grid. The largest dynamic range (ratio of size of the largest grid to size of the finest zone) is 16,384. This allows us to include a coarse model for the surface of the accretor (vacuum sphere) on the finest grid, while at the same time evolving the gas on the coarser grids. Initially (at time t = 0-10), a shock front is set up, a Mach cone develops, and the accretion column is observable. Eventually the flow becomes unstable, destroying axisymmetry. This happens approximately when the mass accretion rate reaches the values (+/- 10%) predicted by the Bondi-Hoyle accretion formula (factor of 2 included). However, our three-dimensional models do not show the highly dynamic flip-flop flow so prominent in two-dimensional calculations performed by other authors. The flow, and thus the accretion rate of all quantities, shows quasi-periodic (P approximately equals 5) cycles between quiescent and active states. The interpolation formula proposed in an accompanying paper is found to follow the collected numerical data to within approximately 30%. The specific angular momentum accreted is of the same order of magnitude as the values previously found for two-dimensional flows.

Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

NASA Astrophysics Data System (ADS)

Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

2015-12-01

Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we contend that creating believable soil carbon predictions requires a robust, transparent, and community-available benchmarking framework. I will present an ILAMB evaluation of several of the above-mentioned approaches in ACME, and attempt to motivate community adoption of this evaluation approach.

Spatio-temporal modeling with GIS and remote sensing for schistosomiasis control in Sichuan, China

NASA Astrophysics Data System (ADS)

Xu, Bing

Schistosomiasis is a water-borne parasitic disease endemic in tropical and subtropical areas. Its transmission requires certain kind of snail as the intermediate host. Some efforts have been made to mapping snail habitats with remote sensing and schistosomiasis transmission modeling. However, the modeling is limited to isolated residential groups and does not include spatial interaction among those groups. Remotely sensed data are only used in snail habitat classification, not in estimation of snail abundance that is an important parameter in schistosomiasis transmission modeling. This research overcomes the above two problems using innovative geographic information system (GIS) and remote sensing technology. A mountainous environment near Xichang, China, is chosen as the test site. Environmental and epidemiological data are stored in a GIS to support modeling. Snail abundance is estimated from land-cover and land-use fractions derived from high spatial resolution IKONOS satellite data. Spatial interaction is determined in consideration of neighborhoods, group areas, relative slopes among groups, and natural barriers. Land-cover and land-use information extracted from 4 m high resolution IKONOS data is used as reference in scaling up to the regional level. The scale-up is done with coarser resolution satellite data including Landsat Thematic Mapper (TM), EO-1 Advanced Land Imager (ALI) and Hyperion data all at 30 m resolution. Snail abundance is estimated by regressing snail survey data with land-cover and land-use fractions. An R2 of 0.87 is obtained between the average snail density predicted and that surveyed at the group level. With such a model, a snail density map is generated for all residential groups in the study area. A spatio-temporal model of schistosomiasis transmission is finally built to incorporate the spatial interaction caused by miracidia and cercaria migration. Comparing the model results with and without spatial interaction has revealed a number of advantages of the spatio-temporal model. Particularly, with the inclusion of spatial interaction, more effective control of schistosomiasis transmission over the whole study area can be achieved.

COSP: Satellite simulation software for model assessment

DOE PAGES

Bodas-Salcedo, A.; Webb, M. J.; Bony, S.; ...

2011-08-01

Errors in the simulation of clouds in general circulation models (GCMs) remain a long-standing issue in climate projections, as discussed in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. This highlights the need for developing new analysis techniques to improve our knowledge of the physical processes at the root of these errors. The Cloud Feedback Model Intercomparison Project (CFMIP) pursues this objective, and under that framework the CFMIP Observation Simulator Package (COSP) has been developed. COSP is a flexible software tool that enables the simulation of several satellite-borne active and passive sensor observations from model variables. The flexibilitymore » of COSP and a common interface for all sensors facilitates its use in any type of numerical model, from high-resolution cloud-resolving models to the coarser-resolution GCMs assessed by the IPCC, and the scales in between used in weather forecast and regional models. The diversity of model parameterization techniques makes the comparison between model and observations difficult, as some parameterized variables (e.g., cloud fraction) do not have the same meaning in all models. The approach followed in COSP permits models to be evaluated against observations and compared against each other in a more consistent manner. This thus permits a more detailed diagnosis of the physical processes that govern the behavior of clouds and precipitation in numerical models. The World Climate Research Programme (WCRP) Working Group on Coupled Modelling has recommended the use of COSP in a subset of climate experiments that will be assessed by the next IPCC report. Here we describe COSP, present some results from its application to numerical models, and discuss future work that will expand its capabilities.« less

Assessment of radar resolution requirements for soil moisture estimation from simulated satellite imagery. [Kansas

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Dobson, M. C.; Moezzi, S.

1982-01-01

Radar simulations were performed at five-day intervals over a twenty-day period and used to estimate soil moisture from a generalized algorithm requiring only received power and the mean elevation of a test site near Lawrence, Kansas. The results demonstrate that the soil moisture of about 90% of the 20-m by 20-m pixel elements can be predicted with an accuracy of + or - 20% of field capacity within relatively flat agricultural portions of the test site. Radar resolutions of 93 m by 100 m with 23 looks or coarser gave the best results, largely because of the effects of signal fading. For the distribution of land cover categories, soils, and elevation in the test site, very coarse radar resolutions of 1 km by 1 km and 2.6 km by 3.1 km gave the best results for wet moisture conditions while a finer resolution of 93 m by 100 m was found to yield superior results for dry to moist soil conditions.

An Active Fire Temperature Retrieval Model Using Hyperspectral Remote Sensing

NASA Astrophysics Data System (ADS)

Quigley, K. W.; Roberts, D. A.; Miller, D.

2017-12-01

Wildfire is both an important ecological process and a dangerous natural threat that humans face. In situ measurements of wildfire temperature are notoriously difficult to collect due to dangerous conditions. Imaging spectrometry data has the potential to provide some of the most accurate and highest temporally-resolved active fire temperature retrieval information for monitoring and modeling. Recent studies on fire temperature retrieval have used have used Multiple Endmember Spectral Mixture Analysis applied to Airborne Visible applied to Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) bands to model fire temperatures within the regions marked to contain fire, but these methods are less effective at coarser spatial resolutions, as linear mixing methods are degraded by saturation within the pixel. The assumption of a distribution of temperatures within pixels allows us to model pixels with an effective maximum and likely minimum temperature. This assumption allows a more robust approach to modeling temperature at different spatial scales. In this study, instrument-corrected radiance is forward-modeled for different ranges of temperatures, with weighted temperatures from an effective maximum temperature to a likely minimum temperature contributing to the total radiance of the modeled pixel. Effective maximum fire temperature is estimated by minimizing the Root Mean Square Error (RMSE) between modeled and measured fires. The model was tested using AVIRIS collected over the 2016 Sherpa Fire in Santa Barbara County, California,. While only in situ experimentation would be able to confirm active fire temperatures, the fit of the data to modeled radiance can be assessed, as well as the similarity in temperature distributions seen on different spatial resolution scales. Results show that this model improves upon current modeling methods in producing similar effective temperatures on multiple spatial scales as well as a similar modeled area distribution of those temperatures.

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

A Semi-Structured MODFLOW-USG Model to Evaluate Local Water Sources to Wells for Decision Support.

PubMed

Feinstein, Daniel T; Fienen, Michael N; Reeves, Howard W; Langevin, Christian D

2016-07-01

In order to better represent the configuration of the stream network and simulate local groundwater-surface water interactions, a version of MODFLOW with refined spacing in the topmost layer was applied to a Lake Michigan Basin (LMB) regional groundwater-flow model developed by the U.S. Geological. Regional MODFLOW models commonly use coarse grids over large areas; this coarse spacing precludes model application to local management issues (e.g., surface-water depletion by wells) without recourse to labor-intensive inset models. Implementation of an unstructured formulation within the MODFLOW framework (MODFLOW-USG) allows application of regional models to address local problems. A "semi-structured" approach (uniform lateral spacing within layers, different lateral spacing among layers) was tested using the LMB regional model. The parent 20-layer model with uniform 5000-foot (1524-m) lateral spacing was converted to 4 layers with 500-foot (152-m) spacing in the top glacial (Quaternary) layer, where surface water features are located, overlying coarser resolution layers representing deeper deposits. This semi-structured version of the LMB model reproduces regional flow conditions, whereas the finer resolution in the top layer improves the accuracy of the simulated response of surface water to shallow wells. One application of the semi-structured LMB model is to provide statistical measures of the correlation between modeled inputs and the simulated amount of water that wells derive from local surface water. The relations identified in this paper serve as the basis for metamodels to predict (with uncertainty) surface-water depletion in response to shallow pumping within and potentially beyond the modeled area, see Fienen et al. (2015a). Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

A semi-structured MODFLOW-USG model to evaluate local water sources to wells for decision support

USGS Publications Warehouse

Feinstein, Daniel T.; Fienen, Michael N.; Reeves, Howard W.; Langevin, Christian D.

2016-01-01

In order to better represent the configuration of the stream network and simulate local groundwater-surface water interactions, a version of MODFLOW with refined spacing in the topmost layer was applied to a Lake Michigan Basin (LMB) regional groundwater-flow model developed by the U.S. Geological. Regional MODFLOW models commonly use coarse grids over large areas; this coarse spacing precludes model application to local management issues (e.g., surface-water depletion by wells) without recourse to labor-intensive inset models. Implementation of an unstructured formulation within the MODFLOW framework (MODFLOW-USG) allows application of regional models to address local problems. A “semi-structured” approach (uniform lateral spacing within layers, different lateral spacing among layers) was tested using the LMB regional model. The parent 20-layer model with uniform 5000-foot (1524-m) lateral spacing was converted to 4 layers with 500-foot (152-m) spacing in the top glacial (Quaternary) layer, where surface water features are located, overlying coarser resolution layers representing deeper deposits. This semi-structured version of the LMB model reproduces regional flow conditions, whereas the finer resolution in the top layer improves the accuracy of the simulated response of surface water to shallow wells. One application of the semi-structured LMB model is to provide statistical measures of the correlation between modeled inputs and the simulated amount of water that wells derive from local surface water. The relations identified in this paper serve as the basis for metamodels to predict (with uncertainty) surface-water depletion in response to shallow pumping within and potentially beyond the modeled area, see Fienen et al. (2015a).

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.

Effect of Spatial Resolution for Characterizing Soil Properties from Imaging Spectrometer Data

NASA Astrophysics Data System (ADS)

Dutta, D.; Kumar, P.; Greenberg, J. A.

2015-12-01

The feasibility of quantifying soil constituents over large areas using airborne hyperspectral data [0.35 - 2.5 μm] in an ensemble bootstrapping lasso algorithmic framework has been demonstrated previously [1]. However the effects of coarsening the spatial resolution of hyperspectral data on the quantification of soil constituents are unknown. We use Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data collected at 7.6m resolution over Birds Point New Madrid (BPNM) floodway for up-scaling and generating multiple coarser resolution datasets including the 60m Hyperspectral Infrared Imager (HyspIRI) like data. HyspIRI is a proposed visible shortwave/thermal infrared mission, which will provide global data over a spectral range of 0.35 - 2.5μm at a spatial resolution of 60m. Our results show that the lasso method, which is based on point scale observational data, is scalable. We found consistent good model performance (R2) values (0.79 < R2 < 0.82) and correct classifications as per USDA soil texture classes at multiple spatial resolutions. The results further demonstrate that the attributes of the pdf for different soil constituents across the landscape and the within-pixel variance are well preserved across scales. Our analysis provides a methodological framework with a sufficient set of metrics for assessing the performance of scaling up analysis from point scale observational data and may be relevant for other similar remote sensing studies. [1] Dutta, D.; Goodwell, A.E.; Kumar, P.; Garvey, J.E.; Darmody, R.G.; Berretta, D.P.; Greenberg, J.A., "On the Feasibility of Characterizing Soil Properties From AVIRIS Data," Geoscience and Remote Sensing, IEEE Transactions on, vol.53, no.9, pp.5133,5147, Sept. 2015. doi: 10.1109/TGRS.2015.2417547.

North American CO2 fluxes for 2007-2015 from NOAA's CarbonTracker-Lagrange Regional Inverse Modeling Framework

NASA Astrophysics Data System (ADS)

Andrews, A. E.; Hu, L.; Thoning, K. W.; Nehrkorn, T.; Mountain, M. E.; Jacobson, A. R.; Michalak, A.; Dlugokencky, E. J.; Sweeney, C.; Worthy, D. E. J.; Miller, J. B.; Fischer, M. L.; Biraud, S.; van der Velde, I. R.; Basu, S.; Tans, P. P.

2017-12-01

CarbonTracker-Lagrange (CT-L) is a new high-resolution regional inverse modeling system for improved estimation of North American CO2 fluxes. CT-L uses footprints from the Stochastic Time-Inverted Lagrangian Transport (STILT) model driven by high-resolution (10 to 30 km) meteorological fields from the Weather Research and Forecasting (WRF) model. We performed a suite of synthetic-data experiments to evaluate a variety of inversion configurations, including (1) solving for scaling factors to an a priori flux versus additive corrections, (2) solving for fluxes at 3-hrly resolution versus at coarser temporal resolution, (3) solving for fluxes at 1o × 1o resolution versus at large eco-regional scales. Our framework explicitly and objectively solves for the optimal solution with a full error covariance matrix with maximum likelihood estimation, thereby enabling rigorous uncertainty estimates for the derived fluxes. In the synthetic-data inversions, we find that solving for weekly scaling factors of a priori Net Ecosystem Exchange (NEE) at 1o × 1o resolution with optimization of diurnal cycles of CO2 fluxes yields faithful retrieval of the specified "true" fluxes as those solved at 3-hrly resolution. In contrast, a scheme that does not allow for optimization of diurnal cycles of CO2 fluxes suffered from larger aggregation errors. We then applied the optimal inversion setup to estimate North American fluxes for 2007-2015 using real atmospheric CO2 observations, multiple prior estimates of NEE, and multiple boundary values estimated from the NOAA's global Eulerian CarbonTracker (CarbonTracker) and from an empirical approach. Our derived North American land CO2 fluxes show larger seasonal amplitude than those estimated from the CarbonTracker, removing seasonal biases in the CarbonTracker's simulated CO2 mole fractions. Independent evaluations using in-situ CO2 eddy covariance flux measurements and independent aircraft profiles also suggest an improved estimation on North American CO2 fluxes from CT-L. Furthermore, our derived CO2 flux anomalies over North America corresponding to the 2012 North American drought and the 2015 El Niño are larger than derived by the CarbonTracker. They also indicate different responses of ecosystems to those anomalous climatic events.

Future climate change scenarios in Central America at high spatial resolution.

PubMed

Imbach, Pablo; Chou, Sin Chan; Lyra, André; Rodrigues, Daniela; Rodriguez, Daniel; Latinovic, Dragan; Siqueira, Gracielle; Silva, Adan; Garofolo, Lucas; Georgiou, Selena

2018-01-01

The objective of this work is to assess the downscaling projections of climate change over Central America at 8-km resolution using the Eta Regional Climate Model, driven by the HadGEM2-ES simulations of RCP4.5 emission scenario. The narrow characteristic of continent supports the use of numerical simulations at very high-horizontal resolution. Prior to assessing climate change, the 30-year baseline period 1961-1990 is evaluated against different sources of observations of precipitation and temperature. The mean seasonal precipitation and temperature distribution show reasonable agreement with observations. Spatial correlation of the Eta, 8-km resolution, simulations against observations show clear advantage over the driver coarse global model simulations. Seasonal cycle of precipitation confirms the added value of the Eta at 8-km over coarser resolution simulations. The Eta simulations show a systematic cold bias in the region. Climate features of the Mid-Summer Drought and the Caribbean Low-Level Jet are well simulated by the Eta model at 8-km resolution. The assessment of the future climate change is based on the 30-year period 2021-2050, under RCP4.5 scenario. Precipitation is generally reduced, in particular during the JJA and SON, the rainy season. Warming is expected over the region, but stronger in the northern portion of the continent. The Mid-Summer Drought may develop in regions that do not occur during the baseline period, and where it occurs the strength may increase in the future scenario. The Caribbean Low-Level Jet shows little change in the future. Extreme temperatures have positive trend within the period 2021-2050, whereas extreme precipitation, measured by R50mm and R90p, shows positive trend in the eastern coast, around Costa Rica, and negative trends in the northern part of the continent. Negative trend in the duration of dry spell, which is an estimate based on evapotranspiration, is projected in most part of the continent. Annual mean water excess has negative trends in most part of the continent, which suggests decreasing water availability in the future scenario.

Future climate change scenarios in Central America at high spatial resolution

PubMed Central

Imbach, Pablo; Chou, Sin Chan; Rodrigues, Daniela; Rodriguez, Daniel; Latinovic, Dragan; Siqueira, Gracielle; Silva, Adan; Garofolo, Lucas; Georgiou, Selena

2018-01-01

The objective of this work is to assess the downscaling projections of climate change over Central America at 8-km resolution using the Eta Regional Climate Model, driven by the HadGEM2-ES simulations of RCP4.5 emission scenario. The narrow characteristic of continent supports the use of numerical simulations at very high-horizontal resolution. Prior to assessing climate change, the 30-year baseline period 1961–1990 is evaluated against different sources of observations of precipitation and temperature. The mean seasonal precipitation and temperature distribution show reasonable agreement with observations. Spatial correlation of the Eta, 8-km resolution, simulations against observations show clear advantage over the driver coarse global model simulations. Seasonal cycle of precipitation confirms the added value of the Eta at 8-km over coarser resolution simulations. The Eta simulations show a systematic cold bias in the region. Climate features of the Mid-Summer Drought and the Caribbean Low-Level Jet are well simulated by the Eta model at 8-km resolution. The assessment of the future climate change is based on the 30-year period 2021–2050, under RCP4.5 scenario. Precipitation is generally reduced, in particular during the JJA and SON, the rainy season. Warming is expected over the region, but stronger in the northern portion of the continent. The Mid-Summer Drought may develop in regions that do not occur during the baseline period, and where it occurs the strength may increase in the future scenario. The Caribbean Low-Level Jet shows little change in the future. Extreme temperatures have positive trend within the period 2021–2050, whereas extreme precipitation, measured by R50mm and R90p, shows positive trend in the eastern coast, around Costa Rica, and negative trends in the northern part of the continent. Negative trend in the duration of dry spell, which is an estimate based on evapotranspiration, is projected in most part of the continent. Annual mean water excess has negative trends in most part of the continent, which suggests decreasing water availability in the future scenario. PMID:29694355

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part 1; Method and Uncertainties

NASA Technical Reports Server (NTRS)

Olson, William S.; Kummerow, Christian D.; Yang, Song; Petty, Grant W.; Tao, Wei-Kuo; Bell, Thomas L.; Braun, Scott A.; Wang, Yansen; Lang, Stephen E.; Johnson, Daniel E.

2004-01-01

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating/drying profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and non-convective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud resolving model simulations, and from the Bayesian formulation itself. Synthetic rain rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in instantaneous rain rate estimates at 0.5 deg resolution range from approximately 50% at 1 mm/h to 20% at 14 mm/h. These errors represent about 70-90% of the mean random deviation between collocated passive microwave and spaceborne radar rain rate estimates. The cumulative algorithm error in TMI estimates at monthly, 2.5 deg resolution is relatively small (less than 6% at 5 mm/day) compared to the random error due to infrequent satellite temporal sampling (8-35% at the same rain rate).

Deep convective cloud characterizations from both broadband imager and hyperspectral infrared sounder measurements

NASA Astrophysics Data System (ADS)

Ai, Yufei; Li, Jun; Shi, Wenjing; Schmit, Timothy J.; Cao, Changyong; Li, Wanbiao

2017-02-01

Deep convective storms have contributed to airplane accidents, making them a threat to aviation safety. The most common method to identify deep convective clouds (DCCs) is using the brightness temperature difference (BTD) between the atmospheric infrared (IR) window band and the water vapor (WV) absorption band. The effectiveness of the BTD method for DCC detection is highly related to the spectral resolution and signal-to-noise ratio (SNR) of the WV band. In order to understand the sensitivity of BTD to spectral resolution and SNR for DCC detection, a BTD to noise ratio method using the difference between the WV and IR window radiances is developed to assess the uncertainty of DCC identification for different instruments. We examined the case of AirAsia Flight QZ8501. The brightness temperatures (Tbs) over DCCs from this case are simulated for BTD sensitivity studies by a fast forward radiative transfer model with an opaque cloud assumption for both broadband imager (e.g., Multifunction Transport Satellite imager, MTSAT-2 imager) and hyperspectral IR sounder (e.g., Atmospheric Infrared Sounder) instruments; we also examined the relationship between the simulated Tb and the cloud top height. Results show that despite the coarser spatial resolution, BTDs measured by a hyperspectral IR sounder are much more sensitive to high cloud tops than broadband BTDs. As demonstrated in this study, a hyperspectral IR sounder can identify DCCs with better accuracy.

Discrete element modelling of bedload transport

NASA Astrophysics Data System (ADS)

Loyer, A.; Frey, P.

2011-12-01

Discrete element modelling (DEM) has been widely used in solid mechanics and in granular physics. In this type of modelling, each individual particle is taken into account and intergranular interactions are modelled with simple laws (e.g. Coulomb friction). Gravity and contact forces permit to solve the dynamical behaviour of the system. DEM is interesting to model configurations and access to parameters not directly available in laboratory experimentation, hence the term "numerical experimentations" sometimes used to describe DEM. DEM was used to model bedload transport experiments performed at the particle scale with spherical glass beads in a steep and narrow flume. Bedload is the larger material that is transported on the bed on stream channels. It has a great geomorphic impact. Physical processes ruling bedload transport and more generally coarse-particle/fluid systems are poorly known, arguably because granular interactions have been somewhat neglected. An existing DEM code (PFC3D) already computing granular interactions was used. We implemented basic hydrodynamic forces to model the fluid interactions (buoyancy, drag, lift). The idea was to use the minimum number of ingredients to match the experimental results. Experiments were performed with one-size and two-size mixtures of coarse spherical glass beads entrained by a shallow turbulent and supercritical water flow down a steep channel with a mobile bed. The particle diameters were 4 and 6mm, the channel width 6.5mm (about the same width as the coarser particles) and the channel inclination was typically 10%. The water flow rate and the particle rate were kept constant at the upstream entrance and adjusted to obtain bedload transport equilibrium. Flows were filmed from the side by a high-speed camera. Using image processing algorithms made it possible to determine the position, velocity and trajectory of both smaller and coarser particles. Modelled and experimental particle velocity and concentration depth profiles were compared in the case of the one-size mixture. The turbulent fluid velocity profile was prescribed and attached to the variable upper bedline. Provided the upper bedline was calculated with a refined space and time resolution, a fair agreement between DEM and experiments was reached. Experiments with two-size mixtures were designed to study vertical grain size sorting or segregation patterns. Sorting is arguably the reason why the predictive capacity of bedload formulations remains so poor. Modelling of the two-size mixture was also performed and gave promising qualitative results.

Smoking-related emphysema is associated with idiopathic pulmonary fibrosis and rheumatoid lung.

PubMed

Antoniou, Katerina M; Walsh, Simon L; Hansell, David M; Rubens, Michael R; Marten, Katharina; Tennant, Rachel; Hansel, Trevor; Desai, Sujal R; Siafakas, Nikolaos M; du Bois, Roland M; Wells, Athol U

2013-11-01

A combined pulmonary fibrosis/emphysema syndrome has been proposed, but the basis for this syndrome is currently uncertain. The aim was to evaluate the prevalence of emphysema in idiopathic pulmonary fibrosis (IPF) and rheumatoid lung (rheumatoid arthritis-interstitial lung disease (RA-ILD)), and to compare the morphological features of lung fibrosis between smokers and non-smokers. Using high-resolution computed tomography, the prevalence of emphysema and the pack-year smoking histories associated with emphysema were compared between current/ex-smokers with IPF (n = 186) or RA-ILD (n = 46), and non-chronic obstructive pulmonary disease (COPD) controls (n = 103) and COPD controls (n = 34). The coarseness of fibrosis was compared between smokers and non-smokers. Emphysema, present in 66/186 (35%) patients with IPF and 22/46 (48%) smokers with RA-ILD, was associated with lower pack-year smoking histories than in control groups (P < 0.05 for all comparisons). The presence of emphysema in IPF was positively linked to the pack-year smoking history (odds ratio 1.04, 95% confidence interval (CI) 1.02-1.06, P < 0.0005). In IPF, fibrosis was coarser in smokers than in non-smokers on univariate and multivariate analysis (P < 0.01 for all comparisons). In RA-ILD, fibrosis was coarser in patients with emphysema but did not differ significantly between smokers and non-smokers. In IPF and RA-ILD, a high prevalence of concurrent emphysema, in association with low pack-year smoking histories, and an association between coarser pulmonary fibrosis and a history of smoking in IPF together provide support for possible pathogenetic linkage to smoking in both diseases. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.

Integrating expert- and algorithm-derived data to generate a hemispheric ice edge

NASA Astrophysics Data System (ADS)

Tsatsoulis, C.; Komp, E.

The Arctic ice edge is the area of the Arctic where sea ice concentration is less than 15%, and is considered navigable by most vessels. Experts at the National Ice Center generate a daily ice edge product that is available to the public. Data of preference is that of active, high resolution satellite sensors such as RADARSAT which yields all-weather images of 100m resolution, and a second source is OLS data with 550m resolution. Unfortunately, RADARSAT does not provide full, daily coverage of the Arctic and OLS can be obscured by clouds. The SSM/I sensor provides complete coverage of the Arctic at 25km resolution and is independent of cloud cover and solar illumination during the Arctic winter. SSM/I data is analyzed by the NASA Team algorithm to establish ice concentration. Our work integrates the ice edge created by experts using high resolution data with the ice edge generated out of the coarser SSM/I microwave data. The result is a product that combines human and algorithmic outputs, deals with gross differences in resolution of the underlying data sets, and results in a useful, operational product.

Model representations of aerosol layers transported from North America over the Atlantic Ocean during the Two-Column Aerosol Project

NASA Astrophysics Data System (ADS)

Fast, Jerome D.; Berg, Larry K.; Zhang, Kai; Easter, Richard C.; Ferrare, Richard A.; Hair, Johnathan W.; Hostetler, Chris A.; Liu, Ying; Ortega, Ivan; Sedlacek, Arthur; Shilling, John E.; Shrivastava, Manish; Springston, Stephen R.; Tomlinson, Jason M.; Volkamer, Rainer; Wilson, Jacqueline; Zaveri, Rahul A.; Zelenyuk, Alla

2016-08-01

The ability of the Weather Research and Forecasting model with chemistry (WRF-Chem) version 3.7 and the Community Atmosphere Model version 5.3 (CAM5) in simulating profiles of aerosol properties is quantified using extensive in situ and remote sensing measurements from the Two-Column Aerosol Project (TCAP) conducted during July of 2012. TCAP was supported by the U.S. Department of Energy's Atmospheric Radiation Measurement program and was designed to obtain observations within two atmospheric columns; one fixed over Cape Cod, Massachusetts, and the other several hundred kilometers over the ocean. The performance is quantified using most of the available aircraft and surface measurements during July, and 2 days are examined in more detail to identify the processes responsible for the observed aerosol layers. The higher-resolution WRF-Chem model produced more aerosol mass in the free troposphere than the coarser-resolution CAM5 model so that the fraction of aerosol optical thickness above the residual layer from WRF-Chem was more consistent with lidar measurements. We found that the free troposphere layers are likely due to mean vertical motions associated with synoptic-scale convergence that lifts aerosols from the boundary layer. The vertical displacement and the time period associated with upward transport in the troposphere depend on the strength of the synoptic system and whether relatively high boundary layer aerosol concentrations are present where convergence occurs. While a parameterization of subgrid scale convective clouds applied in WRF-Chem modulated the concentrations of aerosols aloft, it did not significantly change the overall altitude and depth of the layers.

Effect of flour particle size on microstructural, rheological and physico-sensory characteristics of bread and south Indian parotta.

PubMed

Sakhare, Suresh D; Inamdar, Aashitosh A; Soumya, C; Indrani, D; Rao, G Venkateswara

2014-12-01

Wheat flour fractioned by sieving into four different particle size fractions namely finer fractions (<75 and 75-118 μm), coarser fractions (118-150 and >150 μm) were analyzed for their chemical, rheological, bread & parotta making characteristics. The finer fractions had lower ash, higher dry gluten, damaged starch and sodium dodecysulphate (SDS)-sedimentation value than the coarser fractions. The flour from finer fractions gave bread with best sensory and textural attributes. The parottas from finer fractions showed significantly higher sensory scores for colour, texture, layers, mouthfeel and overall quality score than the coarser fractions. In the micrograph of finer flour fractions, higher number of loosened single starch granules than the aggregates of starch and protein matrix were seen as compared to coarser fractions. These studies indicate that the flour from the finer fractions produce higher quality bread, parotta owing to the presence of higher damaged starch content, quantity and quality of protein in these fractions than coarser fractions.

Comparing the Potential of Multispectral and Hyperspectral Data for Monitoring Oil Spill Impact.

PubMed

Khanna, Shruti; Santos, Maria J; Ustin, Susan L; Shapiro, Kristen; Haverkamp, Paul J; Lay, Mui

2018-02-12

Oil spills from offshore drilling and coastal refineries often cause significant degradation of coastal environments. Early oil detection may prevent losses and speed up recovery if monitoring of the initial oil extent, oil impact, and recovery are in place. Satellite imagery data can provide a cost-effective alternative to expensive airborne imagery or labor intensive field campaigns for monitoring effects of oil spills on wetlands. However, these satellite data may be restricted in their ability to detect and map ecosystem recovery post-spill given their spectral measurement properties and temporal frequency. In this study, we assessed whether spatial and spectral resolution, and other sensor characteristics influence the ability to detect and map vegetation stress and mortality due to oil. We compared how well three satellite multispectral sensors: WorldView2, RapidEye and Landsat EMT+, match the ability of the airborne hyperspectral AVIRIS sensor to map oil-induced vegetation stress, recovery, and mortality after the DeepWater Horizon oil spill in the Gulf of Mexico in 2010. We found that finer spatial resolution (3.5 m) provided better delineation of the oil-impacted wetlands and better detection of vegetation stress along oiled shorelines in saltmarsh wetland ecosystems. As spatial resolution become coarser (3.5 m to 30 m) the ability to accurately detect and map stressed vegetation decreased. Spectral resolution did improve the detection and mapping of oil-impacted wetlands but less strongly than spatial resolution, suggesting that broad-band data may be sufficient to detect and map oil-impacted wetlands. AVIRIS narrow-band data performs better detecting vegetation stress, followed by WorldView2, RapidEye and then Landsat 15 m (pan sharpened) data. Higher quality sensor optics and higher signal-to-noise ratio (SNR) may also improve detection and mapping of oil-impacted wetlands; we found that resampled coarser resolution AVIRIS data with higher SNR performed better than either of the three satellite sensors. The ability to acquire imagery during certain times (midday, low tide, etc.) or a certain date (cloud-free, etc.) is also important in these tidal wetlands; WorldView2 imagery captured at high-tide detected a narrower band of shoreline affected by oil likely because some of the impacted wetland was below the tideline. These results suggest that while multispectral data may be sufficient for detecting the extent of oil-impacted wetlands, high spectral and spatial resolution, high-quality sensor characteristics, and the ability to control time of image acquisition may improve assessment and monitoring of vegetation stress and recovery post oil spills.

Comparing the Potential of Multispectral and Hyperspectral Data for Monitoring Oil Spill Impact

PubMed Central

Santos, Maria J.; Ustin, Susan L.; Haverkamp, Paul J.; Lay, Mui

2018-01-01

Oil spills from offshore drilling and coastal refineries often cause significant degradation of coastal environments. Early oil detection may prevent losses and speed up recovery if monitoring of the initial oil extent, oil impact, and recovery are in place. Satellite imagery data can provide a cost-effective alternative to expensive airborne imagery or labor intensive field campaigns for monitoring effects of oil spills on wetlands. However, these satellite data may be restricted in their ability to detect and map ecosystem recovery post-spill given their spectral measurement properties and temporal frequency. In this study, we assessed whether spatial and spectral resolution, and other sensor characteristics influence the ability to detect and map vegetation stress and mortality due to oil. We compared how well three satellite multispectral sensors: WorldView2, RapidEye and Landsat EMT+, match the ability of the airborne hyperspectral AVIRIS sensor to map oil-induced vegetation stress, recovery, and mortality after the DeepWater Horizon oil spill in the Gulf of Mexico in 2010. We found that finer spatial resolution (3.5 m) provided better delineation of the oil-impacted wetlands and better detection of vegetation stress along oiled shorelines in saltmarsh wetland ecosystems. As spatial resolution become coarser (3.5 m to 30 m) the ability to accurately detect and map stressed vegetation decreased. Spectral resolution did improve the detection and mapping of oil-impacted wetlands but less strongly than spatial resolution, suggesting that broad-band data may be sufficient to detect and map oil-impacted wetlands. AVIRIS narrow-band data performs better detecting vegetation stress, followed by WorldView2, RapidEye and then Landsat 15 m (pan sharpened) data. Higher quality sensor optics and higher signal-to-noise ratio (SNR) may also improve detection and mapping of oil-impacted wetlands; we found that resampled coarser resolution AVIRIS data with higher SNR performed better than either of the three satellite sensors. The ability to acquire imagery during certain times (midday, low tide, etc.) or a certain date (cloud-free, etc.) is also important in these tidal wetlands; WorldView2 imagery captured at high-tide detected a narrower band of shoreline affected by oil likely because some of the impacted wetland was below the tideline. These results suggest that while multispectral data may be sufficient for detecting the extent of oil-impacted wetlands, high spectral and spatial resolution, high-quality sensor characteristics, and the ability to control time of image acquisition may improve assessment and monitoring of vegetation stress and recovery post oil spills. PMID:29439504

Diagnosis of boreal summer intraseasonal oscillation in high resolution NCEP climate forecast system

NASA Astrophysics Data System (ADS)

Abhik, S.; Mukhopadhyay, P.; Krishna, R. P. M.; Salunke, Kiran D.; Dhakate, Ashish R.; Rao, Suryachandra A.

2016-05-01

The present study examines the ability of high resolution (T382) National Centers for Environmental Prediction coupled atmosphere-ocean climate forecast system version 2 (CFS T382) in simulating the salient spatio-temporal characteristics of the boreal summertime mean climate and the intraseasonal variability. The shortcomings of the model are identified based on the observation and compared with earlier reported biases of the coarser resolution of CFS (CFS T126). It is found that the CFS T382 reasonably mimics the observed features of basic state climate during boreal summer. But some prominent biases are noted in simulating the precipitation, tropospheric temperature (TT) and sea surface temperature (SST) over the global tropics. Although CFS T382 primarily reproduces the observed distribution of the intraseasonal variability over the Indian summer monsoon region, some difficulty remains in simulating the boreal summer intraseasonal oscillation (BSISO) characteristics. The simulated eastward propagation of BSISO decays rapidly across the Maritime Continent, while the northward propagation appears to be slightly slower than observation. However, the northward propagating BSISO convection propagates smoothly from the equatorial region to the northern latitudes with observed magnitude. Moreover, the observed northwest-southeast tilted rain band is not well reproduced in CFS T382. The warm mean SST bias and inadequate simulation of high frequency modes appear to be responsible for the weak simulation of eastward propagating BSISO. Unlike CFS T126, the simulated mean SST and TT exhibit warm biases, although the mean precipitation and simulated BSISO characteristics are largely similar in both the resolutions of CFS. Further analysis of the convectively coupled equatorial waves (CCEWs) indicates that model overestimates the gravest equatorial Rossby waves and underestimates the Kelvin and mixed Rossby-gravity waves. Based on analysis of CCEWs, the study further explains the possible reasons behind the realistic simulation of northward propagating BSISO in CFS T382, even though the model shows substantial biases in simulating mean state and other BSISO modes.

An Observation-based Assessment of Instrument Requirements for a Future Precipitation Process Observing System

NASA Astrophysics Data System (ADS)

Nelson, E.; L'Ecuyer, T. S.; Wood, N.; Smalley, M.; Kulie, M.; Hahn, W.

2017-12-01

Global models exhibit substantial biases in the frequency, intensity, duration, and spatial scales of precipitation systems. Much of this uncertainty stems from an inadequate representation of the processes by which water is cycled between the surface and atmosphere and, in particular, those that govern the formation and maintenance of cloud systems and their propensity to form the precipitation. Progress toward improving precipitation process models requires observing systems capable of quantifying the coupling between the ice content, vertical mass fluxes, and precipitation yield of precipitating cloud systems. Spaceborne multi-frequency, Doppler radar offers a unique opportunity to address this need but the effectiveness of such a mission is heavily dependent on its ability to actually observe the processes of interest in the widest possible range of systems. Planning for a next generation precipitation process observing system should, therefore, start with a fundamental evaluation of the trade-offs between sensitivity, resolution, sampling, cost, and the overall potential scientific yield of the mission. Here we provide an initial assessment of the scientific and economic trade-space by evaluating hypothetical spaceborne multi-frequency radars using a combination of current real-world and model-derived synthetic observations. Specifically, we alter the field of view, vertical resolution, and sensitivity of a hypothetical Ka- and W-band radar system and propagate those changes through precipitation detection and intensity retrievals. The results suggest that sampling biases introduced by reducing sensitivity disproportionately affect the light rainfall and frozen precipitation regimes that are critical for warm cloud feedbacks and ice sheet mass balance, respectively. Coarser spatial resolution observations introduce regime-dependent biases in both precipitation occurrence and intensity that depend on cloud regime, with even the sign of the bias varying within a single storm system. It is suggested that the next generation spaceborne radar have a minimum sensitivity of -5 dBZ and spatial resolution of at least 3 km at all frequencies to adequately sample liquid and ice phase precipitation processes globally.

Simulating Virtual Terminal Area Weather Data Bases for Use in the Wake Vortex Avoidance System (Wake VAS) Prediction Algorithm

NASA Technical Reports Server (NTRS)

Kaplan, Michael L.; Lin, Yuh-Lang

2004-01-01

During the research project, sounding datasets were generated for the region surrounding 9 major airports, including Dallas, TX, Boston, MA, New York, NY, Chicago, IL, St. Louis, MO, Atlanta, GA, Miami, FL, San Francico, CA, and Los Angeles, CA. The numerical simulation of winter and summer environments during which no instrument flight rule impact was occurring at these 9 terminals was performed using the most contemporary version of the Terminal Area PBL Prediction System (TAPPS) model nested from 36 km to 6 km to 1 km horizontal resolution and very detailed vertical resolution in the planetary boundary layer. The soundings from the 1 km model were archived at 30 minute time intervals for a 24 hour period and the vertical dependent variables as well as derived quantities, i.e., 3-dimensional wind components, temperatures, pressures, mixing ratios, turbulence kinetic energy and eddy dissipation rates were then interpolated to 5 m vertical resolution up to 1000 m elevation above ground level. After partial validation against field experiment datasets for Dallas as well as larger scale and much coarser resolution observations at the other 8 airports, these sounding datasets were sent to NASA for use in the Virtual Air Space and Modeling program. The application of these datasets being to determine representative airport weather environments to diagnose the response of simulated wake vortices to realistic atmospheric environments. These virtual datasets are based on large scale observed atmospheric initial conditions that are dynamically interpolated in space and time. The 1 km nested-grid simulated datasets providing a very coarse and highly smoothed representation of airport environment meteorological conditions. Details concerning the airport surface forcing are virtually absent from these simulated datasets although the observed background atmospheric processes have been compared to the simulated fields and the fields were found to accurately replicate the flows surrounding the airport where coarse verification data were available as well as where airport scale datasets were available.

Multiscale measurement error models for aggregated small area health data.

PubMed

Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin

2016-08-01

Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser level. To adjust for predictor uncertainty due to aggregation, we applied measurement error models in the framework of multiscale approach. To assess the benefit of using multiscale measurement error models, we compare the performance of multiscale models with and without measurement error in both real and simulated data. We found that ignoring the measurement error in multiscale models underestimates the regression coefficient, while it overestimates the variance of the spatially structured random effect. On the other hand, accounting for the measurement error in multiscale models provides a better model fit and unbiased parameter estimates. © The Author(s) 2016.

Hyperspectral and multispectral satellite sensors for mapping chlorophyll content in a Mediterranean Pinus sylvestris L. plantation

NASA Astrophysics Data System (ADS)

Navarro-Cerrillo, Rafael Mª; Trujillo, Jesus; de la Orden, Manuel Sánchez; Hernández-Clemente, Rocío

2014-02-01

A new generation of narrow-band hyperspectral remote sensing data offers an alternative to broad-band multispectral data for the estimation of vegetation chlorophyll content. This paper examines the potential of some of these sensors comparing red-edge and simple ratio indices to develop a rapid and cost-effective system for monitoring Mediterranean pine plantations in Spain. Chlorophyll content retrieval was analyzed with the red-edge R750/R710 index and the simple ratio R800/R560 index using the PROSPECT-5 leaf model and the Discrete Anisotropic Radiative Transfer (DART) and experimental approach. Five sensors were used: AHS, CHRIS/Proba, Hyperion, Landsat and QuickBird. The model simulation results obtained with synthetic spectra demonstrated the feasibility of estimating Ca + b content in conifers using the simple ratio R800/R560 index formulated with different full widths at half maximum (FWHM) at the leaf level. This index yielded a r2 = 0.69 for a FWHM of 30 nm and r2 = 0.55 for a FWHM of 70 nm. Experimental results compared the regression coefficients obtained with various multispectral and hyperspectral images with different spatial resolutions at the stand level. The strongest relationships where obtained using high-resolution hyperspectral images acquired with the AHS sensor (r2 = 0.65) while coarser spatial and spectral resolution images yielded a lower root mean square error (QuickBird r2 = 0.42; Landsat r2 = 0.48; Hyperion r2 = 0.56; CHRIS/Proba r2 = 0.57). This study shows the need to estimate chlorophyll content in forest plantations at the stand level with high spatial and spectral resolution sensors. Nevertheless, these results also show the accuracy obtained with medium-resolution sensors when monitoring physiological processes. Generating biochemical maps at the stand level could play a critical rule in the early detection of forest decline processes enabling their use in precision forestry.

The Modularized Software Package ASKI - Full Waveform Inversion Based on Waveform Sensitivity Kernels Utilizing External Seismic Wave Propagation Codes

NASA Astrophysics Data System (ADS)

Schumacher, F.; Friederich, W.

2015-12-01

We present the modularized software package ASKI which is a flexible and extendable toolbox for seismic full waveform inversion (FWI) as well as sensitivity or resolution analysis operating on the sensitivity matrix. It utilizes established wave propagation codes for solving the forward problem and offers an alternative to the monolithic, unflexible and hard-to-modify codes that have typically been written for solving inverse problems. It is available under the GPL at www.rub.de/aski. The Gauss-Newton FWI method for 3D-heterogeneous elastic earth models is based on waveform sensitivity kernels and can be applied to inverse problems at various spatial scales in both Cartesian and spherical geometries. The kernels are derived in the frequency domain from Born scattering theory as the Fréchet derivatives of linearized full waveform data functionals, quantifying the influence of elastic earth model parameters on the particular waveform data values. As an important innovation, we keep two independent spatial descriptions of the earth model - one for solving the forward problem and one representing the inverted model updates. Thereby we account for the independent needs of spatial model resolution of forward and inverse problem, respectively. Due to pre-integration of the kernels over the (in general much coarser) inversion grid, storage requirements for the sensitivity kernels are dramatically reduced.ASKI can be flexibly extended to other forward codes by providing it with specific interface routines that contain knowledge about forward code-specific file formats and auxiliary information provided by the new forward code. In order to sustain flexibility, the ASKI tools must communicate via file output/input, thus large storage capacities need to be accessible in a convenient way. Storing the complete sensitivity matrix to file, however, permits the scientist full manual control over each step in a customized procedure of sensitivity/resolution analysis and full waveform inversion.

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

NASA Astrophysics Data System (ADS)

Judt, Falko

2017-04-01

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

Compiling and Mapping Global Permeability of the Unconsolidated and Consolidated Earth: GLobal HYdrogeology MaPS 2.0 (GLHYMPS 2.0)

NASA Astrophysics Data System (ADS)

Huscroft, Jordan; Gleeson, Tom; Hartmann, Jens; Börker, Janine

2018-02-01

The spatial distribution of subsurface parameters such as permeability are increasingly relevant for regional to global climate, land surface, and hydrologic models that are integrating groundwater dynamics and interactions. Despite the large fraction of unconsolidated sediments on Earth's surface with a wide range of permeability values, current global, high-resolution permeability maps distinguish solely fine-grained and coarse-grained unconsolidated sediments. Representative permeability values are derived for a wide variety of unconsolidated sediments and applied to a new global map of unconsolidated sediments to produce the first geologically constrained, two-layer global map of shallower and deeper permeability. The new mean logarithmic permeability of the Earth's surface is -12.7 ± 1.7 m2 being 1 order of magnitude higher than that derived from previous maps, which is consistent with the dominance of the coarser sediments. The new data set will benefit a variety of scientific applications including the next generation of climate, land surface, and hydrology models at regional to global scales.

Integrated Blowoff and Breakup Calculations for Asteroid Deflection by Nuclear Ablation

NASA Astrophysics Data System (ADS)

Bruck Syal, M.; Owen, M.; Dearborn, D. S.; Miller, P. L.

2016-12-01

When the warning timing is short, hazardous asteroids or comets can only be deflected off of an Earth-impacting trajectory by a nuclear device [1]. Here we model asteroid response to a standoff nuclear explosion, a problem which requires sub-millimeter spatial resolution at the body's surface to fully capture x-ray energy deposition. The first stage of the calculation focuses on modeling blowoff momentum from vaporized material, using a problem domain confined to the uppermost surface of the asteroid. Once the blowoff momentum transfer process is complete, the problem is remapped into a coarser resolution and the remainder of the asteroid body is added to the calculation, so that asteroid response can be tracked over longer timescales. This two-stage approach enables an integrated assessment of both the efficacy of momentum delivery and damage incurred by the bulk of the asteroid. Investigating the degree of post-ablation fracture, fragmentation, and fragment dispersion is necessary for modeling the outcomes of cases intended to fully fragment and disperse the body (disruption), as well as cases where the bulk of the asteroid should remain intact (deflection). We begin with 500-m spherical asteroids but also extend our analysis to radar-derived asteroid shape models. [1] Dearborn, D.S.P., Miller, P.L., 2014. Deflecting or Disrupting a Threatening Object, in: Pelton, J.N., Allahdadi, F. (Eds.), Handbook of Cosmic Hazards and Planetary Defense, Springer. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52- 07NA27344. LLNL-ABS-699631.

Simulating the characteristics of tropical cyclones over the South West Indian Ocean using a Stretched-Grid Global Climate Model

NASA Astrophysics Data System (ADS)

Maoyi, Molulaqhooa L.; Abiodun, Babatunde J.; Prusa, Joseph M.; Veitch, Jennifer J.

2018-03-01

Tropical cyclones (TCs) are one of the most devastating natural phenomena. This study examines the capability of a global climate model with grid stretching (CAM-EULAG, hereafter CEU) in simulating the characteristics of TCs over the South West Indian Ocean (SWIO). In the study, CEU is applied with a variable increment global grid that has a fine horizontal grid resolution (0.5° × 0.5°) over the SWIO and coarser resolution (1° × 1°—2° × 2.25°) over the rest of the globe. The simulation is performed for the 11 years (1999-2010) and validated against the Joint Typhoon Warning Center (JTWC) best track data, global precipitation climatology project (GPCP) satellite data, and ERA-Interim (ERAINT) reanalysis. CEU gives a realistic simulation of the SWIO climate and shows some skill in simulating the spatial distribution of TC genesis locations and tracks over the basin. However, there are some discrepancies between the observed and simulated climatic features over the Mozambique channel (MC). Over MC, CEU simulates a substantial cyclonic feature that produces a higher number of TC than observed. The dynamical structure and intensities of the CEU TCs compare well with observation, though the model struggles to produce TCs with a deep pressure centre as low as the observed. The reanalysis has the same problem. The model captures the monthly variation of TC occurrence well but struggles to reproduce the interannual variation. The results of this study have application in improving and adopting CEU for seasonal forecasting over the SWIO.

Extending a prototype knowledge- and object-based image analysis model to coarser spatial resolution imagery: an example from the Missouri River

USGS Publications Warehouse

Strong, Laurence L.

2012-01-01

A prototype knowledge- and object-based image analysis model was developed to inventory and map least tern and piping plover habitat on the Missouri River, USA. The model has been used to inventory the state of sandbars annually for 4 segments of the Missouri River since 2006 using QuickBird imagery. Interpretation of the state of sandbars is difficult when images for the segment are acquired at different river stages and different states of vegetation phenology and canopy cover. Concurrent QuickBird and RapidEye images were classified using the model and the spatial correspondence of classes in the land cover and sandbar maps were analysed for the spatial extent of the images and at nest locations for both bird species. Omission and commission errors were low for unvegetated land cover classes used for nesting by both bird species and for land cover types with continuous vegetation cover and water. Errors were larger for land cover classes characterized by a mixture of sand and vegetation. Sandbar classification decisions are made using information on land cover class proportions and disagreement between sandbar classes was resolved using fuzzy membership possibilities. Regression analysis of area for a paired sample of 47 sandbars indicated an average positive bias, 1.15 ha, for RapidEye that did not vary with sandbar size. RapidEye has potential to reduce temporal uncertainty about least tern and piping plover habitat but would not be suitable for mapping sandbar erosion, and characterization of sandbar shapes or vegetation patches at fine spatial resolution.

Extending a prototype knowledge and object based image analysis model to coarser spatial resolution imagery: an example from the Missouri River

USGS Publications Warehouse

Strong, Laurence L.

2012-01-01

A prototype knowledge- and object-based image analysis model was developed to inventory and map least tern and piping plover habitat on the Missouri River, USA. The model has been used to inventory the state of sandbars annually for 4 segments of the Missouri River since 2006 using QuickBird imagery. Interpretation of the state of sandbars is difficult when images for the segment are acquired at different river stages and different states of vegetation phenology and canopy cover. Concurrent QuickBird and RapidEye images were classified using the model and the spatial correspondence of classes in the land cover and sandbar maps were analysed for the spatial extent of the images and at nest locations for both bird species. Omission and commission errors were low for unvegetated land cover classes used for nesting by both bird species and for land cover types with continuous vegetation cover and water. Errors were larger for land cover classes characterized by a mixture of sand and vegetation. Sandbar classification decisions are made using information on land cover class proportions and disagreement between sandbar classes was resolved using fuzzy membership possibilities. Regression analysis of area for a paired sample of 47 sandbars indicated an average positive bias, 1.15 ha, for RapidEye that did not vary with sandbar size. RapidEye has potential to reduce temporal uncertainty about least tern and piping plover habitat but would not be suitable for mapping sandbar erosion, and characterization of sandbar shapes or vegetation patches at fine spatial resolution.

Simulations of Cyclone Sidr in the Bay of Bengal with a High-Resolution Model: Sensitivity to Large-Scale Boundary Forcing

NASA Technical Reports Server (NTRS)

Kumar, Anil; Done, James; Dudhia, Jimy; Niyogi, Dev

2011-01-01

The predictability of Cyclone Sidr in the Bay of Bengal was explored in terms of track and intensity using the Advanced Research Hurricane Weather Research Forecast (AHW) model. This constitutes the first application of the AHW over an area that lies outside the region of the North Atlantic for which this model was developed and tested. Several experiments were conducted to understand the possible contributing factors that affected Sidr s intensity and track simulation by varying the initial start time and domain size. Results show that Sidr s track was strongly controlled by the synoptic flow at the 500-hPa level, seen especially due to the strong mid-latitude westerly over north-central India. A 96-h forecast produced westerly winds over north-central India at the 500-hPa level that were notably weaker; this likely caused the modeled cyclone track to drift from the observed actual track. Reducing the model domain size reduced model error in the synoptic-scale winds at 500 hPa and produced an improved cyclone track. Specifically, the cyclone track appeared to be sensitive to the upstream synoptic flow, and was, therefore, sensitive to the location of the western boundary of the domain. However, cyclone intensity remained largely unaffected by this synoptic wind error at the 500-hPa level. Comparison of the high resolution, moving nested domain with a single coarser resolution domain showed little difference in tracks, but resulted in significantly different intensities. Experiments on the domain size with regard to the total precipitation simulated by the model showed that precipitation patterns and 10-m surface winds were also different. This was mainly due to the mid-latitude westerly flow across the west side of the model domain. The analysis also suggested that the total precipitation pattern and track was unchanged when the domain was extended toward the east, north, and south. Furthermore, this highlights our conclusion that Sidr was influenced from the west side of the domain. The displacement error was significantly reduced after the domain size from the western model boundary was decreased. Study results demonstrate the capability and need of a high-resolution mesoscale modeling framework for simulating the complex interactions that contribute to the formation of tropical cyclones over the Bay of Bengal region

Tropical Cyclone Intensity in Global Models

NASA Astrophysics Data System (ADS)

Davis, C. A.; Wang, W.; Ahijevych, D.

2017-12-01

In recent years, global prediction and climate models have begun to depict intense tropical cyclones, even up to Category 5 on the Saffir-Simpson scale. In light of the limitation of horizontal resolution in such models, we examine the how well these models treat tropical cyclone intensity, measured from several different perspectives. The models evaluated include the operational Global Forecast System, with a grid spacing of about 13 km, and the Model for Prediction Across Scales, with a variable resolution of 15 km over the Northwest Pacific transitioning to 60 km elsewhere. We focus on the Northwest Pacific for the period July-October, 2016. Results indicate that discrimination of tropical cyclone intensity is reasonably good up to roughly category 3 storms. The models are able to capture storms of category 4 intensity, but still exhibit a negative intensity bias of 20-30 knots at lead times beyond 5 days. This is partly indicative of the large number of super-typhoons that occurred in 2016. The question arises of how well global models should represent intensity, given that it is unreasonable for them to depict the inner core of many intense tropical cyclones with a grid increment of 13-15 km. We compute an expected "best-case" prediction of intensity based on filtering the observed wind profiles of Atlantic tropical cyclones according to different hypothetical model resolutions. The Atlantic is used because of the significant number of reconnaissance missions and more reliable estimate of wind radii. Results indicate that, even under the most optimistic assumptions, models with horizontal grid spacing of 1/4 degree or coarser should not produce a realistic number of category 4 and 5 storms unless there are errors in spatial attributes of the wind field. Furthermore, models with a grid spacing of 1/4 degree or greater are unlikely to systematically discriminate hurricanes with differing intensity. Finally, for simple wind profiles, it is shown how an accurate representation of maximum wind on a coarse grid will lead to an overestimate of horizontally integrated kinetic energy by a factor of two or more.

The effects of digital elevation model resolution on the calculation and predictions of topographic wetness indices.

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

Drover, Damion, Ryan

2011-12-01

One of the largest exports in the Southeast U.S. is forest products. Interest in biofuels using forest biomass has increased recently, leading to more research into better forest management BMPs. The USDA Forest Service, along with the Oak Ridge National Laboratory, University of Georgia and Oregon State University are researching the impacts of intensive forest management for biofuels on water quality and quantity at the Savannah River Site in South Carolina. Surface runoff of saturated areas, transporting excess nutrients and contaminants, is a potential water quality issue under investigation. Detailed maps of variable source areas and soil characteristics would thereforemore » be helpful prior to treatment. The availability of remotely sensed and computed digital elevation models (DEMs) and spatial analysis tools make it easy to calculate terrain attributes. These terrain attributes can be used in models to predict saturated areas or other attributes in the landscape. With laser altimetry, an area can be flown to produce very high resolution data, and the resulting data can be resampled into any resolution of DEM desired. Additionally, there exist many maps that are in various resolutions of DEM, such as those acquired from the U.S. Geological Survey. Problems arise when using maps derived from different resolution DEMs. For example, saturated areas can be under or overestimated depending on the resolution used. The purpose of this study was to examine the effects of DEM resolution on the calculation of topographic wetness indices used to predict variable source areas of saturation, and to find the best resolutions to produce prediction maps of soil attributes like nitrogen, carbon, bulk density and soil texture for low-relief, humid-temperate forested hillslopes. Topographic wetness indices were calculated based on the derived terrain attributes, slope and specific catchment area, from five different DEM resolutions. The DEMs were resampled from LiDAR, which is a laser altimetry remote sensing method, obtained from the USDA Forest Service at Savannah River Site. The specific DEM resolutions were chosen because they are common grid cell sizes (10m, 30m, and 50m) used in mapping for management applications and in research. The finer resolutions (2m and 5m) were chosen for the purpose of determining how finer resolutions performed compared with coarser resolutions at predicting wetness and related soil attributes. The wetness indices were compared across DEMs and with each other in terms of quantile and distribution differences, then in terms of how well they each correlated with measured soil attributes. Spatial and non-spatial analyses were performed, and predictions using regression and geostatistics were examined for efficacy relative to each DEM resolution. Trends in the raw data and analysis results were also revealed.« less

Analysis of Multi-Scale Radiometric Data Collected during the Cold Land Processes Experiment-1 (CLPX-1)

NASA Technical Reports Server (NTRS)

Tedesco, M.; Kim, E. J.; Gasiewski, A.; Stankov, B.

2005-01-01

Brightness temperature maps at 18.7 and 37 GHz collected at the Fraser and North Park Meso-Scale Areas during the Cold Land Processes Experiment by the NOAA Polarimetric Scanning Radiometer (PSWA) airborne sensor are analyzed. The Fraser site is mostly covered by forest with a typical snowpack depth of 1 m while North Park has no forest cover and is characterized by patches of shallow snow. We examine histograms of the brightness temperatures at 500 m resolution for both the Fraser and North Park areas. The histograms can be modelled by a log-normal distribution in the case of the Fraser MSA and by a bi-modal distribution in the case of the North Park MSA. The histograms of the brightness temperatures at coarser resolutions are also plotted to study the effects of sensor resolution on the shape of the distribution, on the values of the average brightness temperatures and standard deviations. Finally, the values of brightness temperatures obtained by re-sampling (aggregating) the data at 25 km resolution are compared with the values of the brightness temperatures collected by the Advanced Microwave Scanning Radiometer (AMSR-E) and Special Sensor Microwave/Imager (SSMII) satellite radiometers. The results show that in both areas for sensor footprint larger than 5000 m, the brightness temperatures show a flat distribution and the memory of the initial distribution is lost. The values of the brightness temperatures measured by the satellite radiometers are in good agreement with the values obtained averaging the airborne data, even if some discrepancies occur.

Developing a regional retrospective ensemble precipitation dataset for watershed hydrology modeling, Idaho, USA

NASA Astrophysics Data System (ADS)

Flores, A. N.; Smith, K.; LaPorte, P.

2011-12-01

Applications like flood forecasting, military trafficability assessment, and slope stability analysis necessitate the use of models capable of resolving hydrologic states and fluxes at spatial scales of hillslopes (e.g., 10s to 100s m). These models typically require precipitation forcings at spatial scales of kilometers or better and time intervals of hours. Yet in especially rugged terrain that typifies much of the Western US and throughout much of the developing world, precipitation data at these spatiotemporal resolutions is difficult to come by. Ground-based weather radars have significant problems in high-relief settings and are sparsely located, leaving significant gaps in coverage and high uncertainties. Precipitation gages provide accurate data at points but are very sparsely located and their placement is often not representative, yielding significant coverage gaps in a spatial and physiographic sense. Numerical weather prediction efforts have made precipitation data, including critically important information on precipitation phase, available globally and in near real-time. However, these datasets present watershed modelers with two problems: (1) spatial scales of many of these datasets are tens of kilometers or coarser, (2) numerical weather models used to generate these datasets include a land surface parameterization that in some circumstances can significantly affect precipitation predictions. We report on the development of a regional precipitation dataset for Idaho that leverages: (1) a dataset derived from a numerical weather prediction model, (2) gages within Idaho that report hourly precipitation data, and (3) a long-term precipitation climatology dataset. Hourly precipitation estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA) are stochastically downscaled using a hybrid orographic and statistical model from their native resolution (1/2 x 2/3 degrees) to a resolution of approximately 1 km. Downscaled precipitation realizations are conditioned on hourly observations from reporting gages and then conditioned again on the Parameter-elevation Regressions on Independent Slopes Model (PRISM) at the monthly timescale to reflect orographic precipitation trends common to watersheds of the Western US. While this methodology potentially introduces cross-pollination of errors due to the re-use of precipitation gage data, it nevertheless achieves an ensemble-based precipitation estimate and appropriate measures of uncertainty at a spatiotemporal resolution appropriate for watershed modeling.

Change of spatial information under rescaling: A case study using multi-resolution image series

NASA Astrophysics Data System (ADS)

Chen, Weirong; Henebry, Geoffrey M.

Spatial structure in imagery depends on a complicated interaction between the observational regime and the types and arrangements of entities within the scene that the image portrays. Although block averaging of pixels has commonly been used to simulate coarser resolution imagery, relatively little attention has been focused on the effects of simple rescaling on spatial structure and the explanation and a possible solution to the problem. Yet, if there are significant differences in spatial variance between rescaled and observed images, it may affect the reliability of retrieved biogeophysical quantities. To investigate these issues, a nested series of high spatial resolution digital imagery was collected at a research site in eastern Nebraska in 2001. An airborne Kodak DCS420IR camera acquired imagery at three altitudes, yielding nominal spatial resolutions ranging from 0.187 m to 1 m. The red and near infrared (NIR) bands of the co-registered image series were normalized using pseudo-invariant features, and the normalized difference vegetation index (NDVI) was calculated. Plots of grain sorghum planted in orthogonal crop row orientations were extracted from the image series. The finest spatial resolution data were then rescaled by averaging blocks of pixels to produce a rescaled image series that closely matched the spatial resolution of the observed image series. Spatial structures of the observed and rescaled image series were characterized using semivariogram analysis. Results for NDVI and its component bands show, as expected, that decreasing spatial resolution leads to decreasing spatial variability and increasing spatial dependence. However, compared to the observed data, the rescaled images contain more persistent spatial structure that exhibits limited variation in both spatial dependence and spatial heterogeneity. Rescaling via simple block averaging fails to consider the effect of scene object shape and extent on spatial information. As the features portrayed by pixels are equally weighted regardless of the shape and extent of the underlying scene objects, the rescaled image retains more of the original spatial information than would occur through direct observation at a coarser sensor spatial resolution. In contrast, for the observed images, due to the effect of the modulation transfer function (MTF) of the imaging system, high frequency features like edges are blurred or lost as the pixel size increases, resulting in greater variation in spatial structure. Successive applications of a low-pass spatial convolution filter are shown to mimic a MTF. Accordingly, it is recommended that such a procedure be applied prior to rescaling by simple block averaging, if insufficient image metadata exist to replicate the net MTF of the imaging system, as might be expected in land cover change analysis studies using historical imagery.

Evaluation of simplified stream-aquifer depletion models for water rights administration

USGS Publications Warehouse

Sophocleous, Marios; Koussis, Antonis; Martin, J.L.; Perkins, S.P.

1995-01-01

We assess the predictive accuracy of Glover's (1974) stream-aquifer analytical solutions, which are commonly used in administering water rights, and evaluate the impact of the assumed idealizations on administrative and management decisions. To achieve these objectives, we evaluate the predictive capabilities of the Glover stream-aquifer depletion model against the MODFLOW numerical standard, which, unlike the analytical model, can handle increasing hydrogeologic complexity. We rank-order and quantify the relative importance of the various assumptions on which the analytical model is based, the three most important being: (1) streambed clogging as quantified by streambed-aquifer hydraulic conductivity contrast; (2) degree of stream partial penetration; and (3) aquifer heterogeneity. These three factors relate directly to the multidimensional nature of the aquifer flow conditions. From these considerations, future efforts to reduce the uncertainty in stream depletion-related administrative decisions should primarily address these three factors in characterizing the stream-aquifer process. We also investigate the impact of progressively coarser model grid size on numerically estimating stream leakage and conclude that grid size effects are relatively minor. Therefore, when modeling is required, coarser model grids could be used thus minimizing the input data requirements.

Evaluation of model-predicted hazardous air pollutants (HAPs) near a mid-sized U.S. airport

NASA Astrophysics Data System (ADS)

Vennam, Lakshmi Pradeepa; Vizuete, William; Arunachalam, Saravanan

2015-10-01

Accurate modeling of aircraft-emitted pollutants in the vicinity of airports is essential to study the impact on local air quality and to answer policy and health-impact related issues. To quantify air quality impacts of airport-related hazardous air pollutants (HAPs), we carried out a fine-scale (4 × 4 km horizontal resolution) Community Multiscale Air Quality model (CMAQ) model simulation at the T.F. Green airport in Providence (PVD), Rhode Island. We considered temporally and spatially resolved aircraft emissions from the new Aviation Environmental Design Tool (AEDT). These model predictions were then evaluated with observations from a field campaign focused on assessing HAPs near the PVD airport. The annual normalized mean error (NME) was in the range of 36-70% normalized mean error for all HAPs except for acrolein (>70%). The addition of highly resolved aircraft emissions showed only marginally incremental improvements in performance (1-2% decrease in NME) of some HAPs (formaldehyde, xylene). When compared to a coarser 36 × 36 km grid resolution, the 4 × 4 km grid resolution did improve performance by up to 5-20% NME for formaldehyde and acetaldehyde. The change in power setting (from traditional International Civil Aviation Organization (ICAO) 7% to observation studies based 4%) doubled the aircraft idling emissions of HAPs, but led to only a 2% decrease in NME. Overall modeled aircraft-attributable contributions are in the range of 0.5-28% near a mid-sized airport grid-cell with maximum impacts seen only within 4-16 km from the airport grid-cell. Comparison of CMAQ predictions with HAP estimates from EPA's National Air Toxics Assessment (NATA) did show similar annual mean concentrations and equally poor performance. Current estimates of HAPs for PVD are a challenge for modeling systems and refinements in our ability to simulate aircraft emissions have made only incremental improvements. Even with unrealistic increases in HAPs aviation emissions the model could not match observed concentrations near the runway airport site. Our results suggest other uncertainties in the modeling system such as meteorology, HAPs chemistry, or other emission sources require increased scrutiny.

Intercomparison of AIRS and HIRDLS stratospheric gravity wave observations

NASA Astrophysics Data System (ADS)

Meyer, Catrin I.; Ern, Manfred; Hoffmann, Lars; Trinh, Quang Thai; Alexander, M. Joan

2018-01-01

We investigate stratospheric gravity wave observations by the Atmospheric InfraRed Sounder (AIRS) aboard NASA's Aqua satellite and the High Resolution Dynamics Limb Sounder (HIRDLS) aboard NASA's Aura satellite. AIRS operational temperature retrievals are typically not used for studies of gravity waves, because their vertical and horizontal resolution is rather limited. This study uses data of a high-resolution retrieval which provides stratospheric temperature profiles for each individual satellite footprint. Therefore the horizontal sampling of the high-resolution retrieval is 9 times better than that of the operational retrieval. HIRDLS provides 2-D spectral information of observed gravity waves in terms of along-track and vertical wavelengths. AIRS as a nadir sounder is more sensitive to short-horizontal-wavelength gravity waves, and HIRDLS as a limb sounder is more sensitive to short-vertical-wavelength gravity waves. Therefore HIRDLS is ideally suited to complement AIRS observations. A calculated momentum flux factor indicates that the waves seen by AIRS contribute significantly to momentum flux, even if the AIRS temperature variance may be small compared to HIRDLS. The stratospheric wave structures observed by AIRS and HIRDLS often agree very well. Case studies of a mountain wave event and a non-orographic wave event demonstrate that the observed phase structures of AIRS and HIRDLS are also similar. AIRS has a coarser vertical resolution, which results in an attenuation of the amplitude and coarser vertical wavelengths than for HIRDLS. However, AIRS has a much higher horizontal resolution, and the propagation direction of the waves can be clearly identified in geographical maps. The horizontal orientation of the phase fronts can be deduced from AIRS 3-D temperature fields. This is a restricting factor for gravity wave analyses of limb measurements. Additionally, temperature variances with respect to stratospheric gravity wave activity are compared on a statistical basis. The complete HIRDLS measurement period from January 2005 to March 2008 is covered. The seasonal and latitudinal distributions of gravity wave activity as observed by AIRS and HIRDLS agree well. A strong annual cycle at mid- and high latitudes is found in time series of gravity wave variances at 42 km, which has its maxima during wintertime and its minima during summertime. The variability is largest during austral wintertime at 60° S. Variations in the zonal winds at 2.5 hPa are associated with large variability in gravity wave variances. Altogether, gravity wave variances of AIRS and HIRDLS are complementary to each other. Large parts of the gravity wave spectrum are covered by joint observations. This opens up fascinating vistas for future gravity wave research.

Model representations of aerosol layers transported from North America over the Atlantic Ocean during the Two-Column Aerosol Project

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

Fast, Jerome D.; Berg, Larry K.; Zhang, Kai

2016-08-22

The ability of the Weather Research and Forecasting model with chemistry (WRF-Chem) version 3.7 and the Community Atmosphere Model version 5.3 (CAM5) in simulating profiles of aerosol properties is quantified using extensive in situ and remote sensing measurements from the Two Column Aerosol Project (TCAP) conducted during July of 2012. TCAP was supported by the U.S. Department of Energy’s Atmospheric Radiation Measurement program and was designed to obtain observations within two atmospheric columns; one fixed over Cape Cod, Massachusetts and the other several hundred kilometers over the ocean. The performance is quantified using most of the available aircraft and surfacemore » measurements during July, and two days are examined in more detail to identify the processes responsible for the observed aerosol layers. The higher resolution WRF-Chem model produced more aerosol mass in the free troposphere than the coarser resolution CAM5 model so that the fraction of aerosol optical thickness above the residual layer from WRF-Chem was more consistent with lidar measurements. We found that the free troposphere layers are likely due to mean vertical motions associated with synoptic-scale convergence that lifts aerosols from the boundary layer. The vertical displacement and the time period associated with upward transport in the troposphere depend on the strength of the synoptic system and whether relatively high boundary layer aerosol concentrations are present where convergence occurs. While a parameterization of subgrid scale convective clouds applied in WRF-Chem modulated the concentrations of aerosols aloft, it did not significantly change the overall altitude and depth of the layers.« less

Model representations of aerosol layers transported from North America over the Atlantic Ocean during the Two-Column Aerosol Project

DOE PAGES

Fast, Jerome D.; Berg, Larry K.; Zhang, Kai; ...

2016-08-22

The ability of the Weather Research and Forecasting model with chemistry (WRF-Chem) version 3.7 and the Community Atmosphere Model version 5.3 (CAM5) in simulating profiles of aerosol properties is quantified using extensive in situ and remote sensing measurements from the Two-Column Aerosol Project (TCAP) conducted during July of 2012. TCAP was supported by the U.S. Department of Energy's Atmospheric Radiation Measurement program and was designed to obtain observations within two atmospheric columns; one fixed over Cape Cod, Massachusetts, and the other several hundred kilometers over the ocean. The performance is quantified using most of the available aircraft and surface measurementsmore » during July, and 2 days are examined in more detail to identify the processes responsible for the observed aerosol layers. The higher-resolution WRF-Chem model produced more aerosol mass in the free troposphere than the coarser-resolution CAM5 model so that the fraction of aerosol optical thickness above the residual layer from WRF-Chem was more consistent with lidar measurements. We found that the free troposphere layers are likely due to mean vertical motions associated with synoptic-scale convergence that lifts aerosols from the boundary layer. The vertical displacement and the time period associated with upward transport in the troposphere depend on the strength of the synoptic system and whether relatively high boundary layer aerosol concentrations are present where convergence occurs. In conclusion, while a parameterization of subgrid scale convective clouds applied in WRF-Chem modulated the concentrations of aerosols aloft, it did not significantly change the overall altitude and depth of the layers.« less

Rediscovery of the doldrums in storm-resolving simulations over the tropical Atlantic

NASA Astrophysics Data System (ADS)

Klocke, Daniel; Brueck, Matthias; Hohenegger, Cathy; Stevens, Bjorn

2017-12-01

The doldrums — a zone of calm and variable winds in the deep tropics between the trades — were of key importance to nineteenth century maritime travel. As a result, the region was a focus in atmospheric science at that time. However, as sailing ships were replaced by steamboats, scientific interest shifted to the heavy precipitating storms within the doldrums: the deep convective systems of the intertropical convergence zone. Now, in storm-system-resolving simulations over a period of two months that cover a large part of the tropical Atlantic, the doldrums are one of the most prominent features. The doldrums are substantially less pronounced in coarser-resolution simulations that use a parameterization for convection, despite their large-scale extent. We conclude that explicitly representing the storm scale dynamics and their coupling to the surface wind on the storm-system scales helps to maintain the systems of winds that define the doldrums. We suggest that the lack of these wind systems could explain the persistent tropical precipitation biases in climate models.

Downscaling of Seasonal Landsat-8 and MODIS Land Surface Temperature (LST) in Kolkata, India

NASA Astrophysics Data System (ADS)

Garg, R. D.; Guha, S.; Mondal, A.; Lakshmi, V.; Kundu, S.

2017-12-01

The quality of life of urban people is affected by urban heat environment. The urban heat studies can be carried out using remotely sensed thermal infrared imagery for retrieving Land Surface Temperature (LST). Currently, high spatial resolution (<200 m) thermal images are limited and their temporal resolution is low (e.g., 17 days of Landsat-8). Coarse spatial resolution (1000 m) and high temporal resolution (daily) thermal images of MODIS (Moderate Resolution Imaging Spectroradiometer) are frequently available. The present study is to downscale spatially coarser resolution of the thermal image to fine resolution thermal image using regression based downscaling technique. This method is based on the relationship between (LST) and vegetation indices (e.g., Normalized Difference Vegetation Index or NDVI) over a heterogeneous landscape. The Kolkata metropolitan city, which experiences a tropical wet-and-dry type of climate has been selected for the study. This study applied different seasonal open source satellite images viz., Landsat-8 and Terra MODIS. The Landsat-8 images are aggregated at 960 m resolution and downscaled into 480, 240 120 and 60 m. Optical and thermal resolution of Landsat-8 and MODIS are 30 m and 60 m; 250 m and 1000 m respectively. The homogeneous land cover areas have shown better accuracy than heterogeneous land cover areas. The downscaling method plays a crucial role while the spatial resolution of thermal band renders it unable for advanced study. Key words: Land Surface Temperature (LST), Downscale, MODIS, Landsat, Kolkata

Water level observations from Unmanned Aerial Vehicles (UAVs) for improving probabilistic estimations of interaction between rivers and groundwater

NASA Astrophysics Data System (ADS)

Bandini, Filippo; Butts, Michael; Vammen Jacobsen, Torsten; Bauer-Gottwein, Peter

2016-04-01

Integrated hydrological models are generally calibrated against observations of river discharge and piezometric head in groundwater aquifers. Integrated hydrological models are rarely calibrated against spatially distributed water level observations measured by either in-situ stations or spaceborne platforms. Indeed in-situ observations derived from ground-based stations are generally spaced too far apart to capture spatial patterns in the water surface. On the other hand spaceborne observations have limited spatial resolution. Additionally satellite observations have a temporal resolution which is not ideal for observing the temporal patterns of the hydrological variables during extreme events. UAVs (Unmanned Aerial Vehicles) offer several advantages: i) high spatial resolution; ii) tracking of the water body better than any satellite technology; iii) timing of the sampling merely depending on the operators. In this case study the Mølleåen river (Denmark) and its catchment have been simulated through an integrated hydrological model (MIKE 11-MIKE SHE). This model was initially calibrated against observations of river discharge retrieved by in-situ stations and against piezometric head of the aquifers. Subsequently the hydrological model has been calibrated against dense spatially distributed water level observations, which could potentially be retrieved by UAVs. Error characteristics of synthetic UAV water level observations were taken from a recent proof-of-concept study. Since the technology for ranging water level is under development, UAV synthetic water level observations were extracted from another model of the river with higher spatial resolution (cross sections located every 10 m). This model with high resolution is assumed to be absolute truth for the purpose of this work. The river model with the coarser resolution has been calibrated against the synthetic water level observations through Differential Evolution Adaptive Metropolis (DREAM) algorithm, an efficient global Markov Chain Monte Carlo (MCMC) in high-dimensional spaces. Calibration against water level has demonstrated a significant improvement of the estimation of the exchange flow between groundwater and river branch. Groundwater flux and direction are now better simulated. Reliability and sharpness of the probabilistic forecasts are assessed with the sharpness, the interval skill score (ISS) of the 95{%} confidence interval, and with the root mean square error (RMSE) of the maximum a posteriori probability (MAP). The binary outcome (either gaining or loosing stream) of the flow direction is assessed with Brier score (BS). After water level calibration the sharpness of the estimations is approximately doubled with respect to the model calibrated only against discharge, ISS has improved from 2.4-7to 7.8-8 m^3/s\\cdot m, RMSE from 9.2-8 to 2.4-8 m^3/s\\cdot m^and BS is halved from 0.58 to 0.25.

Effects of Real-Time NASA Vegetation Data on Model Forecasts of Severe Weather

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Bell, Jordan R.; LaFontaine, Frank J.; Peters-Lidard, Christa D.

2012-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Greenness Vegetation Fraction (GVF) dataset, which is updated daily using swaths of Normalized Difference Vegetation Index data from the Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA-EOS Aqua and Terra satellites. NASA SPoRT started generating daily real-time GVF composites at 1-km resolution over the Continental United States beginning 1 June 2010. A companion poster presentation (Bell et al.) primarily focuses on impact results in an offline configuration of the Noah land surface model (LSM) for the 2010 warm season, comparing the SPoRT/MODIS GVF dataset to the current operational monthly climatology GVF available within the National Centers for Environmental Prediction (NCEP) and Weather Research and Forecasting (WRF) models. This paper/presentation primarily focuses on individual case studies of severe weather events to determine the impacts and possible improvements by using the real-time, high-resolution SPoRT-MODIS GVFs in place of the coarser-resolution NCEP climatological GVFs in model simulations. The NASA-Unified WRF (NU-WRF) modeling system is employed to conduct the sensitivity simulations of individual events. The NU-WRF is an integrated modeling system based on the Advanced Research WRF dynamical core that is designed to represents aerosol, cloud, precipitation, and land processes at satellite-resolved scales in a coupled simulation environment. For this experiment, the coupling between the NASA Land Information System (LIS) and the WRF model is utilized to measure the impacts of the daily SPoRT/MODIS versus the monthly NCEP climatology GVFs. First, a spin-up run of the LIS is integrated for two years using the Noah LSM to ensure that the land surface fields reach an equilibrium state on the 4-km grid mesh used. Next, the spin-up LIS is run in two separate modes beginning on 1 June 2010, one continuing with the climatology GVFs while the other uses the daily SPoRT/MODIS GVFs. Finally, snapshots of the LIS land surface fields are used to initialize two different simulations of the NU-WRF, one running with climatology LIS and GVFs, and the other running with experimental LIS and NASA/SPoRT GVFs. In this paper/presentation, case study results will be highlighted in regions with significant differences in GVF between the NCEP climatology and SPoRT product during severe weather episodes.

Representing soil moisture - precipitation feedbacks in the Sahel: spatial scale and parameterisation

NASA Astrophysics Data System (ADS)

Taylor, C.; Birch, C.; Parker, D.; Guichard, F.; Nikulin, G.; Dixon, N.

2013-12-01

Land surface properties influence the life cycle of convective systems across West Africa via space-time variability in sensible and latent heat fluxes. Previous observational and modelling studies have shown that areas with strong mesoscale variability in vegetation cover or soil moisture induce coherent structures in the daytime planetary boundary layer. In particular, horizontal gradients in sensible heat flux can induce convergence zones which favour the initiation of deep convection. A recent study based on satellite data (Taylor et al. 2011), illustrated the climatological importance of soil moisture gradients in the initiation of long-lived Mesoscale Convective Systems (MCS) in the Sahel. Here we provide a unique assessment of how models of different spatial resolutions represent soil moisture - precipitation feedbacks in the region, and compare their behaviour to observations. Specifically we examine whether the inability of large-scale models to capture the observed preference for afternoon rain over drier soil in semi-arid regions [Taylor et al., 2012] is due to inadequate spatial resolution and/or systematic bias in convective parameterisations. Firstly, we use a convection-permitting simulation at 4km resolution to explore the underlying mechanisms responsible for soil moisture controls on daytime convective initiation in the Sahel. The model reproduces very similar spatial structure as the observations in terms of antecedent soil moisture in the vicinity of a large sample of convective initiations. We then examine how this same model, run at coarser resolution, simulates the feedback of soil moisture on daily rainfall. In particular we examine the impact of switching on the convective parameterisation on rainfall persistence, and compare the findings with 10 regional climate models (RCMs). Finally, we quantify the impact of the feedback on dry-spell return times using a simple statistical model. The results highlight important weaknesses in convective parameterisations which are likely to impact land surface sensitivity studies and hydroclimatic variability on certain time and space scales. Taylor, C.M., Gounou, A., Guichard, F., Harris, P.P., Ellis, R.J.,Couvreux, F., and M. De Kauwe. 2011, Frequency of Sahelian storm initiation enhanced over mesoscale soil-moisture patterns, Nature Geoscience, 4, 430-433, doi:10.1038/ngeo1173 Taylor, C.M., de Jeu, R.A.M., Guichard, F., Harris, P.P, and W.A. Dorigo. 2012, Afternoon rain more likely over drier soils, Nature, 489, 423-426, doi:10.1038/nature11377

Representativeness of regional and global mass-balance measurement networks (Invited)

NASA Astrophysics Data System (ADS)

Cogley, J. G.; Moholdt, G.; Gardner, A. S.

2013-12-01

We showed in a recent publication that regional estimates of glacier mass budgets, obtained by interpolation from in-situ measurements, were markedly more negative than corresponding estimates by satellite gravimetry (GRACE) and satellite altimetry (ICESat) during 2003-2009. Examining the ICESat data in more detail, we found that in-situ records tend to be located in areas where glaciers are thinning more rapidly than as observed in their regional surroundings. Because neither GRACE nor ICESat can provide information for times before 2002-2003, and may not operate without interruption in the future, we explore possible explanations of and remedies for the identified bias in the in-situ network. Sparse spatial sampling, coupled with previously undetected spatial variability of mass balance at scales between the 10-km in-situ scale and the 350-km gravimetric scale, appears to be the leading explanation. Satisfactory remedies are not obvious. Selecting glaciers for in-situ measurement that are more representative will yield only incremental improvements. There appears to be no alternative to mass-balance modelling as a versatile tool for estimation of regional mass balance. However the meteorological data for forcing the surface components of glacier models have coarser resolution than is desirable and are themselves uncertain, especially in the remote regions where much of the glacier ice is found. Measurements of frontal (dynamic) mass changes are still difficult, and modelling of these changes remains underdeveloped in spite of recent advances. Thus research on a broad scale is called for in order to meet the challenge of producing more accurate hindcasts and projections of glacier mass budgets with fine spatial and temporal resolution.

Future changes in the Mediterranean water budget projected by an ensemble of regional climate models

NASA Astrophysics Data System (ADS)

Sanchez-Gomez, E.; Somot, S.; Mariotti, A.

2009-11-01

The Mediterranean basin is a region characterized by its vulnerability to changes in the water cycle. Hence, the impact of global warming on the water resources in the Mediterranean zone is one of the major concerns for the scientific community. The future climate projections used to elaborate the IPCC report of 2007 show great alterations in the evaporation and precipitation over the Mediterranean Sea at the end of 21st century. In this work we investigate the changes in the Mediterranean Sea water budget by using SRES-A1B scenario experiments performed with high resolution (25 km) regional climate models (RCMs). The RCMs provide good estimates of the water budget components, in particular with a significant improvement of the runoff and Black Sea discharge terms compared to the coarser resolution general circulation models (GCMs) used in the last Intergovernmental Panel of Climate Change (IPCC) report. As for the case of GCMs, the RCMs show that the Mediterranean water budget is likely to be significantly altered at the end of 21st century. The response of the hydrological variables to global warming starts to be statistically significant from 2050, though some alterations are already observed before 2050. The RCMs predict an increase of evaporation, and a decrease of precipitation, and river and Black Sea discharge, yielding to a large increase of the Mediterranean fresh water deficit. The freshwater deficit for the period 2070-2099 related to 1950-1999 presents a mean increase of +40% for both RCMs and GCMs.

Landsat-based Earth Observations and Crowd-sourced Data Provide Near Real-time Monitoring of Chimpanzee Habitat

NASA Astrophysics Data System (ADS)

Nackoney, J.; Pintea, L.; Jantz, S.; Hansen, M.

2015-12-01

The endangered chimpanzee (Pan troglodytes) is threatened by habitat loss from resource extraction and land conversion, as well as hunting, disease and the illegal pet trade. It has been estimated that more than 70% of chimpanzee's tropical forest habitats in Africa are now threatened by land use change. Recent developments in remote sensing and cloud computing enable the use of satellite observations to provide a synoptic view of chimpanzee habitats at finer spatial and temporal resolutions that are locally relevant and consistent across the entire species' range. We present a practical Decision Support System to be used by the Jane Goodall Institute and partners to annually monitor and forecast chimpanzee habitat health in Africa. The system integrates Earth observations from 30-meter resolution Landsat data with a species-specific habitat model and a model forecasting future land use change, enhanced by crowd-sourced field data collected by local communities and rangers using the Open Data Kit app and Android mobile smartphones and tablets. While coarser-scale and static chimpanzee habitat models have been previously developed, this project is the first to develop a dynamic monitoring system updated annually via Earth observations data that will systematically monitor threats and changes in habitat over time. Since the chimpanzee is an important keystone, flagship and umbrella species, an annual chimpanzee habitat health index would support conservation goals of other species within its large 2.5 million sq. km range and could be an important indicator of overall ecosystem health of tropical forests in Africa.

Local Atmospheric Response to an Open-Ocean Polynya in a High-Resolution Climate Model

DOE PAGES

Weijer, Wilbert; Veneziani, Milena; Stössel, Achim; ...

2017-03-01

For this scientific paper, we study the atmospheric response to an open-ocean polynya in the Southern Ocean by analyzing the results from an atmospheric and oceanic synoptic-scale resolving Community Earth System Model (CESM) simulation. While coarser-resolution versions of CESM generally do not produce open-ocean polynyas in the Southern Ocean, they do emerge and disappear on interannual timescales in the synoptic-scale simulation. This provides an ideal opportunity to study the polynya’s impact on the overlying and surrounding atmosphere. This has been pursued here by investigating the seasonal cycle of differences of surface and air-column variables between polynya and non-polynya years. Ourmore » results indicate significant local impacts on turbulent heat fluxes, precipitation, cloud characteristics, and radiative fluxes. In particular, we find that clouds over polynyas are optically thicker and higher than clouds over sea ice during non-polynya years. Although the lower albedo of polynyas significantly increases the net shortwave absorption, the enhanced cloud brightness tempers this increase by almost 50%. Also, in this model, enhanced longwave radiation emitted from the warmer surface of polynyas is balanced by stronger downwelling fluxes from the thicker cloud deck. Impacts are found to be sensitive to the synoptic wind direction. Strongest regional impacts are found when northeasterly winds cross the polynya and interact with katabatic winds. Finally, surface air pressure anomalies over the polynya are only found to be significant when cold, dry air masses strike over the polynya, i.e. in case of southerly winds.« less

A review of the LATEX project: mesoscale to submesoscale processes in a coastal environment

NASA Astrophysics Data System (ADS)

Petrenko, Anne A.; Doglioli, Andrea M.; Nencioli, Francesco; Kersalé, Marion; Hu, Ziyuan; d'Ovidio, Francesco

2017-04-01

The main objective of the LAgrangian Transport EXperiment (LATEX) project was to study the influence of coastal mesoscale and submesoscale physical processes on circulation dynamics, cross-shelf exchanges, and biogeochemistry in the western continental shelf of the Gulf of Lion, Northwestern Mediterranean Sea. LATEX was a five-year multidisciplinary project based on the combined analysis of numerical model simulations and multi-platform field experiments. The model component included a ten-year realistic 3D numerical simulation, with a 1 km horizontal resolution over the gulf, nested in a coarser 3 km resolution model. The in situ component involved four cruises, including a large-scale multidisciplinary campaign with two research vessels in 2010. This review concentrates on the physics results of LATEX, addressing three main subjects: (1) the investigation of the mesoscale to submesoscale processes. The eddies are elliptic, baroclinic, and anticyclonic; the strong thermal and saline front is density compensated. Their generation processes are studied; (2) the development of sampling strategies for their direct observations. LATEX has implemented an adaptive strategy Lagrangian tool, with a reference software available on the web, to perform offshore campaigns in a Lagrangian framework; (3) the quantification of horizontal mixing and cross-shelf exchanges. Lateral diffusivity coefficients, calculated in various ways including a novel technique, are in the range classically encountered for their associated scales. Cross-shelf fluxes have been calculated, after retrieving the near-inertial oscillation contribution. Further perspectives are discussed, especially for the ongoing challenge of studying submesoscale features remotely and from in situ data.

Local Atmospheric Response to an Open-Ocean Polynya in a High-Resolution Climate Model

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

Weijer, Wilbert; Veneziani, Milena; Stössel, Achim

For this scientific paper, we study the atmospheric response to an open-ocean polynya in the Southern Ocean by analyzing the results from an atmospheric and oceanic synoptic-scale resolving Community Earth System Model (CESM) simulation. While coarser-resolution versions of CESM generally do not produce open-ocean polynyas in the Southern Ocean, they do emerge and disappear on interannual timescales in the synoptic-scale simulation. This provides an ideal opportunity to study the polynya’s impact on the overlying and surrounding atmosphere. This has been pursued here by investigating the seasonal cycle of differences of surface and air-column variables between polynya and non-polynya years. Ourmore » results indicate significant local impacts on turbulent heat fluxes, precipitation, cloud characteristics, and radiative fluxes. In particular, we find that clouds over polynyas are optically thicker and higher than clouds over sea ice during non-polynya years. Although the lower albedo of polynyas significantly increases the net shortwave absorption, the enhanced cloud brightness tempers this increase by almost 50%. Also, in this model, enhanced longwave radiation emitted from the warmer surface of polynyas is balanced by stronger downwelling fluxes from the thicker cloud deck. Impacts are found to be sensitive to the synoptic wind direction. Strongest regional impacts are found when northeasterly winds cross the polynya and interact with katabatic winds. Finally, surface air pressure anomalies over the polynya are only found to be significant when cold, dry air masses strike over the polynya, i.e. in case of southerly winds.« less

A multigrid method for steady Euler equations on unstructured adaptive grids

NASA Technical Reports Server (NTRS)

Riemslagh, Kris; Dick, Erik

1993-01-01

A flux-difference splitting type algorithm is formulated for the steady Euler equations on unstructured grids. The polynomial flux-difference splitting technique is used. A vertex-centered finite volume method is employed on a triangular mesh. The multigrid method is in defect-correction form. A relaxation procedure with a first order accurate inner iteration and a second-order correction performed only on the finest grid, is used. A multi-stage Jacobi relaxation method is employed as a smoother. Since the grid is unstructured a Jacobi type is chosen. The multi-staging is necessary to provide sufficient smoothing properties. The domain is discretized using a Delaunay triangular mesh generator. Three grids with more or less uniform distribution of nodes but with different resolution are generated by successive refinement of the coarsest grid. Nodes of coarser grids appear in the finer grids. The multigrid method is started on these grids. As soon as the residual drops below a threshold value, an adaptive refinement is started. The solution on the adaptively refined grid is accelerated by a multigrid procedure. The coarser multigrid grids are generated by successive coarsening through point removement. The adaption cycle is repeated a few times. Results are given for the transonic flow over a NACA-0012 airfoil.

Reconstruction of a Three Hourly 1-km Land Surface Air Temperature Dataset in the Qinghai-Tibet Plateau

NASA Astrophysics Data System (ADS)

Zhou, J.; Ding, L.

2017-12-01

Land surface air temperature (SAT) is an important parameter in the modeling of radiation balance and energy budget of the earth surface. Generally, SAT is measured at ground meteorological stations; then SAT mapping is possible though a spatial interpolation process. The interpolated SAT map relies on the spatial distribution of ground stations, the terrain, and many other factors; thus, it has great uncertainties in regions with complicated terrain. Instead, SAT map can also be obtained through physical modeling of interactions between the land surface and the atmosphere. Such dataset generally has coarse spatial resolution (e.g. coarser than 0.1°) and cannot satisfy the applications at fine scales, e.g. 1 km. This presentation reports the reconstruction of a three hourly 1-km SAT dataset from 2001 to 2015 over the Qinghai-Tibet Plateau. The terrain in the Qinghai-Tibet Plateau, especially in the eastern part, is extremely complicated. Two SAT datasets with good qualities are used in this study. The first one is from the 3h China Meteorological Forcing Dataset with a 0.1° resolution released by the Institute of Tibetan Plateau Research, Chinese Academy of Sciences (Yang et al., 2010); the second one is from the ERA-Interim product with the same temporal resolution and a 0.125° resolution. A statistical approach is developed to downscale the spatial resolution of the derived SAT to 1-km. The elevation and the normalized difference vegetation index (NDVI) are selected as two scaling factors in the downscaling approach. Results demonstrate there is significantly negative correlation between the SAT and elevation in all seasons; there is also significantly negative correlation between the SAT and NDVI in the vegetation growth seasons, while the correlation decreases in the other seasons. Therefore, a temporally dynamic downscaling approach is feasible to enhance the spatial resolution of the SAT. Compared with the SAT at the 0.1° or 0.125°, the reconstructed 1-km SAT can provide much more spatial details in areas with complicated terrain. Additionally, the 1-km SAT agrees well with the ground measured air temperatures as well as the SAT before downscaling. The reconstructed SAT will be beneficial for the modeling of surface radiation balance and energy budget over the Qinghai-Tibet Plateau.

Small scale H I structure and the soft X-ray background

NASA Technical Reports Server (NTRS)

Jahoda, K.; Mccammon, D.; Lockman, F. J.

1986-01-01

The observed anticorrelation between diffuse soft X-ray flux and H I column density has been explained as absorption of soft X-rays produced in a hot galactic halo, assuming that the neutral interstellar material is sufficiently clumped to reduce the soft X-ray absorption cross section by a factor of two to three. A 21 cm emission line study of H I column density variations at intermediate and high galactic latitudes to 10' spatial resolution has been done. The results confirm conclusions from preliminary work at coarser resolution, and in combination with other data appear to rule out the hypothesis that clumping of neutral interstellar matter on any angular scale significantly reduces X-ray absorption cross sections in the 0.13 - 0.28 keV energy range. It is concluded therefore that the observed anticorrelation is not primarily a consequence of absorption of soft X-rays produced in a hot galactic halo.

Data assimilation in optimizing and integrating soil and water quality water model predictions at different scales

USDA-ARS?s Scientific Manuscript database

Relevant data about subsurface water flow and solute transport at relatively large scales that are of interest to the public are inherently laborious and in most cases simply impossible to obtain. Upscaling in which fine-scale models and data are used to predict changes at the coarser scales is the...

Development of an Objective High Spatial Resolution Soil Moisture Index

NASA Astrophysics Data System (ADS)

Zavodsky, B.; Case, J.; White, K.; Bell, J. R.

2015-12-01

Drought detection, analysis, and mitigation has become a key challenge for a diverse set of decision makers, including but not limited to operational weather forecasters, climatologists, agricultural interests, and water resource management. One tool that is heavily used is the United States Drought Monitor (USDM), which is derived from a complex blend of objective data and subjective analysis on a state-by-state basis using a variety of modeled and observed precipitation, soil moisture, hydrologic, and vegetation and crop health data. The NASA Short-term Prediction Research and Transition (SPoRT) Center currently runs a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework. The LIS-Noah is run at 3-km resolution for local numerical weather prediction (NWP) and situational awareness applications at select NOAA/National Weather Service (NWS) forecast offices over the Continental U.S. (CONUS). To enhance the practicality of the LIS-Noah output for drought monitoring and assessing flood potential, a 30+-year soil moisture climatology has been developed in an attempt to place near real-time soil moisture values in historical context at county- and/or watershed-scale resolutions. This LIS-Noah soil moisture climatology and accompanying anomalies is intended to complement the current suite of operational products, such as the North American Land Data Assimilation System phase 2 (NLDAS-2), which are generated on a coarser-resolution grid that may not capture localized, yet important soil moisture features. Daily soil moisture histograms are used to identify the real-time soil moisture percentiles at each grid point according to the county or watershed in which the grid point resides. Spatial plots are then produced that map the percentiles as proxies to the different USDM categories. This presentation will highlight recent developments of this gridded, objective soil moisture index, comparison to subjective analyses, and application examples.

Validation of a 30m resolution flood hazard model of the conterminous United States

NASA Astrophysics Data System (ADS)

Sampson, C. C.; Wing, O.; Smith, A.; Bates, P. D.; Neal, J. C.

2017-12-01

We present a 30m resolution two-dimensional hydrodynamic model of the entire conterminous US that has been used to simulate continent-wide flood extent for ten return periods. The model uses a highly efficient numerical solution of the shallow water equations to simulate fluvial flooding in catchments down to 50 km2 and pluvial flooding in all catchments. We use the US National Elevation Dataset (NED) to determine topography for the model and the US Army Corps of Engineers National Levee Dataset to explicitly represent known flood defences. Return period flows and rainfall intensities are estimated using regionalized frequency analyses. We validate these simulations against the complete catalogue of Federal Emergency Management Agency (FEMA) Special Flood Hazard Area maps. We also compare the results obtained from the NED-based continental model with results from a 90m resolution global hydraulic model built using SRTM terrain and identical boundary conditions. Where the FEMA Special Flood Hazard Areas are based on high quality local models the NED-based continental scale model attains a Hit Rate of 86% and a Critical Success Index (CSI) of 0.59; both are typical of scores achieved when comparing high quality reach-scale models to observed event data. The NED model also consistently outperformed the coarser SRTM model. The correspondence between the continental model and FEMA improves in temperate areas and for basins above 400 km2. Given typical hydraulic modeling uncertainties in the FEMA maps, it is probable that the continental-scale model can replicate them to within error. The continental model covers the entire continental US, compared to only 61% for FEMA, and also maps flooding in smaller watersheds not included in the FEMA coverage. The simulations were performed using computing hardware costing less than 100k, whereas the FEMA flood layers are built from thousands of individual local studies that took several decades to develop at an estimated cost (up to 2013) of 4.5 - $7.5bn. The continental model is relatively straightforward to modify and could be re-run under different scenarios, such as climate change. The results show that continental-scale models may now offer sufficient rigor to inform some decision-making needs with far lower cost and greater coverage than traditional patchwork approaches.

Data Assimilation of AirSWOT and Synthetically Derived SWOT Observations of Water Surface Elevation in a Multichannel River

NASA Astrophysics Data System (ADS)

Altenau, E. H.; Pavelsky, T.; Andreadis, K.; Bates, P. D.; Neal, J. C.

2017-12-01

Multichannel rivers continue to be challenging features to quantify, especially at regional and global scales, which is problematic because accurate representations of such environments are needed to properly monitor the earth's water cycle as it adjusts to climate change. It has been demonstrated that higher-complexity, 2D models outperform lower-complexity, 1D models in simulating multichannel river hydraulics at regional scales due to the inclusion of the channel network's connectivity. However, new remote sensing measurements from the future Surface Water and Ocean Topography (SWOT) mission and it's airborne analog AirSWOT offer new observations that can be used to try and improve the lower-complexity, 1D models to achieve accuracies closer to the higher-complexity, 2D codes. Here, we use an Ensemble Kalman Filter (EnKF) to assimilate AirSWOT water surface elevation (WSE) measurements from a 2015 field campaign into a 1D hydrodynamic model along a 90 km reach of Tanana River, AK. This work is the first to test data assimilation methods using real SWOT-like data from AirSWOT. Additionally, synthetic SWOT observations of WSE are generated across the same study site using a fine-resolution 2D model and assimilated into the coarser-resolution 1D model. Lastly, we compare the abilities of AirSWOT and the synthetic-SWOT observations to improve spatial and temporal model outputs in WSEs. Results indicate 1D model outputs of spatially distributed WSEs improve as observational coverage increases, and improvements in temporal fluctuations in WSEs depend on the number of observations. Furthermore, results reveal that assimilation of AirSWOT observations produce greater error reductions in 1D model outputs compared to synthetic SWOT observations due to lower measurement errors. Both AirSWOT and the synthetic SWOT observations significantly lower spatial and temporal errors in 1D model outputs of WSEs.

On the Solidification and Structure Formation during Casting of Large Inserts in Ferritic Nodular Cast Iron

NASA Astrophysics Data System (ADS)

Tadesse, Abel; Fredriksson, Hasse

2018-06-01

The graphite nodule count and size distributions for boiling water reactor (BWR) and pressurized water reactor (PWR) inserts were investigated by taking samples at heights of 2160 and 1150 mm, respectively. In each cross section, two locations were taken into consideration for both the microstructural and solidification modeling. The numerical solidification modeling was performed in a two-dimensional model by considering the nucleation and growth in eutectic ductile cast iron. The microstructural results reveal that the nodule size and count distribution along the cross sections are different in each location for both inserts. Finer graphite nodules appear in the thinner sections and close to the mold walls. The coarser nodules are distributed mostly in the last solidified location. The simulation result indicates that the finer nodules are related to a higher cooling rate and a lower degree of microsegregation, whereas the coarser nodules are related to a lower cooling rate and a higher degree of microsegregation. The solidification time interval and the last solidifying locations in the BWR and PWR are also different.

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.

Bearing faults identification and resonant band demodulation based on wavelet de-noising methods and envelope analysis

NASA Astrophysics Data System (ADS)

Abdelrhman, Ahmed M.; Sei Kien, Yong; Salman Leong, M.; Meng Hee, Lim; Al-Obaidi, Salah M. Ali

2017-07-01

The vibration signals produced by rotating machinery contain useful information for condition monitoring and fault diagnosis. Fault severities assessment is a challenging task. Wavelet Transform (WT) as a multivariate analysis tool is able to compromise between the time and frequency information in the signals and served as a de-noising method. The CWT scaling function gives different resolutions to the discretely signals such as very fine resolution at lower scale but coarser resolution at a higher scale. However, the computational cost increased as it needs to produce different signal resolutions. DWT has better low computation cost as the dilation function allowed the signals to be decomposed through a tree of low and high pass filters and no further analysing the high-frequency components. In this paper, a method for bearing faults identification is presented by combing Continuous Wavelet Transform (CWT) and Discrete Wavelet Transform (DWT) with envelope analysis for bearing fault diagnosis. The experimental data was sampled by Case Western Reserve University. The analysis result showed that the proposed method is effective in bearing faults detection, identify the exact fault’s location and severity assessment especially for the inner race and outer race faults.

Investigating the scale-adaptivity of a shallow cumulus parameterization scheme with LES

NASA Astrophysics Data System (ADS)

Brast, Maren; Schemann, Vera; Neggers, Roel

2017-04-01

In this study we investigate the scale-adaptivity of a new parameterization scheme for shallow cumulus clouds in the gray zone. The Eddy-Diffusivity Multiple Mass-Flux (or ED(MF)n ) scheme is a bin-macrophysics scheme, in which subgrid transport is formulated in terms of discretized size densities. While scale-adaptivity in the ED-component is achieved using a pragmatic blending approach, the MF-component is filtered such that only the transport by plumes smaller than the grid size is maintained. For testing, ED(MF)n is implemented in a large-eddy simulation (LES) model, replacing the original subgrid-scheme for turbulent transport. LES thus plays the role of a non-hydrostatic testing ground, which can be run at different resolutions to study the behavior of the parameterization scheme in the boundary-layer gray zone. In this range convective cumulus clouds are partially resolved. We find that at high resolutions the clouds and the turbulent transport are predominantly resolved by the LES, and the transport represented by ED(MF)n is small. This partitioning changes towards coarser resolutions, with the representation of shallow cumulus clouds becoming exclusively carried by the ED(MF)n. The way the partitioning changes with grid-spacing matches the results of previous LES studies, suggesting some scale-adaptivity is captured. Sensitivity studies show that a scale-inadaptive ED component stays too active at high resolutions, and that the results are fairly insensitive to the number of transporting updrafts in the ED(MF)n scheme. Other assumptions in the scheme, such as the distribution of updrafts across sizes and the value of the area fraction covered by updrafts, are found to affect the location of the gray zone.

Geographically weighted regression based methods for merging satellite and gauge precipitation

NASA Astrophysics Data System (ADS)

Chao, Lijun; Zhang, Ke; Li, Zhijia; Zhu, Yuelong; Wang, Jingfeng; Yu, Zhongbo

2018-03-01

Real-time precipitation data with high spatiotemporal resolutions are crucial for accurate hydrological forecasting. To improve the spatial resolution and quality of satellite precipitation, a three-step satellite and gauge precipitation merging method was formulated in this study: (1) bilinear interpolation is first applied to downscale coarser satellite precipitation to a finer resolution (PS); (2) the (mixed) geographically weighted regression methods coupled with a weighting function are then used to estimate biases of PS as functions of gauge observations (PO) and PS; and (3) biases of PS are finally corrected to produce a merged precipitation product. Based on the above framework, eight algorithms, a combination of two geographically weighted regression methods and four weighting functions, are developed to merge CMORPH (CPC MORPHing technique) precipitation with station observations on a daily scale in the Ziwuhe Basin of China. The geographical variables (elevation, slope, aspect, surface roughness, and distance to the coastline) and a meteorological variable (wind speed) were used for merging precipitation to avoid the artificial spatial autocorrelation resulting from traditional interpolation methods. The results show that the combination of the MGWR and BI-square function (MGWR-BI) has the best performance (R = 0.863 and RMSE = 7.273 mm/day) among the eight algorithms. The MGWR-BI algorithm was then applied to produce hourly merged precipitation product. Compared to the original CMORPH product (R = 0.208 and RMSE = 1.208 mm/hr), the quality of the merged data is significantly higher (R = 0.724 and RMSE = 0.706 mm/hr). The developed merging method not only improves the spatial resolution and quality of the satellite product but also is easy to implement, which is valuable for hydrological modeling and other applications.

Climate change projections over three metropolitan regions in Southeast Brazil using the non-hydrostatic Eta regional climate model at 5-km resolution

NASA Astrophysics Data System (ADS)

Lyra, Andre; Tavares, Priscila; Chou, Sin Chan; Sueiro, Gustavo; Dereczynski, Claudine; Sondermann, Marcely; Silva, Adan; Marengo, José; Giarolla, Angélica

2018-04-01

The objective of this work is to assess changes in three metropolitan regions of Southeast Brazil (Rio de Janeiro, São Paulo, and Santos) based on the projections produced by the Eta Regional Climate Model (RCM) at very high spatial resolution, 5 km. The region, which is densely populated and extremely active economically, is frequently affected by intense rainfall events that trigger floods and landslides during the austral summer. The analyses are carried out for the period between 1961 and 2100. The 5-km simulations are results from a second downscaling nesting in the HadGEM2-ES RCP4.5 and RCP8.5 simulations. Prior to the assessment of the projections, the higher resolution simulations were evaluated for the historical period (1961-1990). The comparison between the 5-km and the coarser driver model simulations shows that the spatial patterns of precipitation and temperature of the 5-km Eta simulations are in good agreement with the observations. The simulated frequency distribution of the precipitation and temperature extremes from the 5-km Eta RCM is consistent with the observed structure and extreme values. Projections of future climate change using the 5-km Eta runs show stronger warming in the region, primarily during the summer season, while precipitation is strongly reduced. Projected temperature extremes show widespread heating with maximum temperatures increasing by approximately 9 °C in the three metropolitan regions by the end of the century in the RCP8.5 scenario. A trend of drier climate is also projected using indices based on daily precipitation, which reaches annual rainfall reductions of more than 50 % in the state of Rio de Janeiro and between 40 and 45 % in São Paulo and Santos. The magnitude of these changes has negative implications to the population health conditions, energy security, and economy.

WRF added value to capture the spatio-temporal drought variability

NASA Astrophysics Data System (ADS)

García-Valdecasas Ojeda, Matilde; Quishpe-Vásquez, César; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

Regional Climate Models (RCM) has been widely used as a tool to perform high resolution climate fields in areas with high climate variability such as Spain. However, the outputs provided by downscaling techniques have many sources of uncertainty associated at different aspects. In this study, the ability of the Weather Research and Forecasting (WRF) model to capture drought conditions has been analyzed. The WRF simulation was carried out for a period that spanned from 1980 to 2010 over a domain centered in the Iberian Peninsula with a spatial resolution of 0.088°, and nested in the coarser EURO-CORDEX domain (0.44° spatial resolution). To investigate the spatiotemporal drought variability, the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) has been computed at two different timescales: 3- and 12-months due to its suitability to study agricultural and hydrological droughts. The drought indices computed from WRF outputs were compared with those obtained from the observational (MOTEDAS and MOPREDAS) datasets. In order to assess the added value provided by downscaled fields, these indices were also computed from the ERA-Interim Re-Analysis database, which provides the lateral and boundary conditions of the WRF simulations. Results from this study indicate that WRF provides a noticeable benefit with respect to ERA-Interim for many regions in Spain in terms of drought indices, greater for SPI than for SPEI. The improvement offered by WRF depends on the region, index and timescale analyzed, being greater at longer timescales. These findings prove the reliability of the downscaled fields to detect drought events and, therefore, it is a remarkable source of knowledge for a suitable decision making related to water-resource management. Keywords: Drought, added value, Regional Climate Models, WRF, SPEI, SPI. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Errors and improvements in the use of archived meteorological data for chemical transport modeling: an analysis using GEOS-Chem v11-01 driven by GEOS-5 meteorology

NASA Astrophysics Data System (ADS)

Yu, Karen; Keller, Christoph A.; Jacob, Daniel J.; Molod, Andrea M.; Eastham, Sebastian D.; Long, Michael S.

2018-01-01

Global simulations of atmospheric chemistry are commonly conducted with off-line chemical transport models (CTMs) driven by archived meteorological data from general circulation models (GCMs). The off-line approach has the advantages of simplicity and expediency, but it incurs errors due to temporal averaging in the meteorological archive and the inability to reproduce the GCM transport algorithms exactly. The CTM simulation is also often conducted at coarser grid resolution than the parent GCM. Here we investigate this cascade of CTM errors by using 222Rn-210Pb-7Be chemical tracer simulations off-line in the GEOS-Chem CTM at rectilinear 0.25° × 0.3125° (≈ 25 km) and 2° × 2.5° (≈ 200 km) resolutions and online in the parent GEOS-5 GCM at cubed-sphere c360 (≈ 25 km) and c48 (≈ 200 km) horizontal resolutions. The c360 GEOS-5 GCM meteorological archive, updated every 3 h and remapped to 0.25° × 0.3125°, is the standard operational product generated by the NASA Global Modeling and Assimilation Office (GMAO) and used as input by GEOS-Chem. We find that the GEOS-Chem 222Rn simulation at native 0.25° × 0.3125° resolution is affected by vertical transport errors of up to 20 % relative to the GEOS-5 c360 online simulation, in part due to loss of transient organized vertical motions in the GCM (resolved convection) that are temporally averaged out in the 3 h meteorological archive. There is also significant error caused by operational remapping of the meteorological archive from a cubed-sphere to a rectilinear grid. Decreasing the GEOS-Chem resolution from 0.25° × 0.3125° to 2° × 2.5° induces further weakening of vertical transport as transient vertical motions are averaged out spatially and temporally. The resulting 222Rn concentrations simulated by the coarse-resolution GEOS-Chem are overestimated by up to 40 % in surface air relative to the online c360 simulations and underestimated by up to 40 % in the upper troposphere, while the tropospheric lifetimes of 210Pb and 7Be against aerosol deposition are affected by 5-10 %. The lost vertical transport in the coarse-resolution GEOS-Chem simulation can be partly restored by recomputing the convective mass fluxes at the appropriate resolution to replace the archived convective mass fluxes and by correcting for bias in the spatial averaging of boundary layer mixing depths.

Emotion-induced trade-offs in spatiotemporal vision.

PubMed

Bocanegra, Bruno R; Zeelenberg, René

2011-05-01

It is generally assumed that emotion facilitates human vision in order to promote adaptive responses to a potential threat in the environment. Surprisingly, we recently found that emotion in some cases impairs the perception of elementary visual features (Bocanegra & Zeelenberg, 2009b). Here, we demonstrate that emotion improves fast temporal vision at the expense of fine-grained spatial vision. We tested participants' threshold resolution with Landolt circles containing a small spatial or brief temporal discontinuity. The prior presentation of a fearful face cue, compared with a neutral face cue, impaired spatial resolution but improved temporal resolution. In addition, we show that these benefits and deficits were triggered selectively by the global configural properties of the faces, which were transmitted only through low spatial frequencies. Critically, the common locus of these opposite effects suggests a trade-off between magno- and parvocellular-type visual channels, which contradicts the common assumption that emotion invariably improves vision. We show that, rather than being a general "boost" for all visual features, affective neural circuits sacrifice the slower processing of small details for a coarser but faster visual signal.

Stennis Space Center Verification & Validation Capabilities

NASA Technical Reports Server (NTRS)

Pagnutti, Mary; Ryan, Robert E.; Holekamp, Kara; ONeal, Duane; Knowlton, Kelly; Ross, Kenton; Blonski, Slawomir

2005-01-01

Scientists within NASA s Applied Sciences Directorate have developed a well-characterized remote sensing Verification & Validation (V&V) site at the John C. Stennis Space Center (SSC). This site enables the in-flight characterization of satellite and airborne high spatial and moderate resolution remote sensing systems and their products. The smaller scale of the newer high resolution remote sensing systems allows scientists to characterize geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the techniques used to characterize data from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active lidar systems. SSC employs geodetic targets, edge targets, radiometric tarps, atmospheric monitoring equipment, and thermal calibration ponds to characterize remote sensing data products. The SSC Instrument Validation Lab is a key component of the V&V capability and is used to calibrate field instrumentation and to provide National Institute of Standards and Technology traceability. This poster presents a description of the SSC characterization capabilities and examples of calibration data.

Investigation of microwave hologram techniques for application to earth resources

NASA Technical Reports Server (NTRS)

Larson, R. W.; Bayma, R. W.; Evans, M. B.; Zelenka, J. S.; Doss, H. W.; Ferris, J. E.

1974-01-01

An investigation of microwave hologram techniques for application to earth resources was conducted during the period from June 1971 to November 1972. The objective of this investigation has been to verify the feasibility of an orbital microwave holographic radar experiment. The primary advantage of microwave hologram radar (MHR) over the side-looking airborne radar (SLAR) is that of aspect or viewing angle; the MHR has a viewing angle identical with that of photography and IR systems. The combination of these systems can thus extend the multispectral analysis concept to span optical through microwave wavelengths. Another advantage is the capacity of the MHR system to generate range contours by operating in a two-frequency mode. It should be clear that along-track resolution of an MHR can be comparable with SLAR systems, but cross-track resolution will be approximately an order of magnitude coarser than the range resolution achievable with an arbitrary SLAR system. An advantage of the MHR over the SLAR is that less average transmitter power is required. This reduction in power results from the much larger receiving apertures associated with MHR systems.

200,000 years of monsoonal history recorded on the lower Bengal Fan - strong response to insolation forcing

NASA Astrophysics Data System (ADS)

Weber, Michael E.; Lantzsch, Hendrik; Dekens, Petra; Das, Supriyo K.; Reilly, Brendan T.; Martos, Yasmina M.; Meyer-Jacob, Carsten; Agrahari, Sandip; Ekblad, Alf; Titschack, Jürgen; Holmes, Beth; Wolfgramm, Philipp

2018-07-01

We conducted a multidisciplinary study to provide the stratigraphic and palaeoclimatic context of monsoonal rainfall dynamics and their responses to orbital forcing for the Bay of Bengal. Using sediment lightness we established an age model at orbital resolution for International Ocean Discovery Programme (IODP) Core U1452C-1H that covers the last 200 ka in the lower Bengal Fan. The low-resolution δ18O of G. sacculifer is consistent with global δ18O records, at least for major glacial-to-interglacial transitions. The variability of total organic carbon, total nitrogen, and the δ13C composition of organic matter indicate the marine origin of organic matter. Marine primary productivity likely increased during insolation minima, indicative for an enhanced NE monsoon during glacials and stadials. Pristine insolation forcing is also documented for wet-bulk density, red-green color variability, and grain-size variations, indicating that darker and coarser-grained material deposited at higher sedimentation rates during insolation minima. Stronger NE monsoon likely amplified ocean-atmosphere interactions over the Indian Ocean, leading to stronger upwelling through shoaling the thermocline, and higher delivery of sediment to the Bay of Bengal due to higher soil erosion on land. In addition, lower glacial and stadial sea levels as well as stronger westward surface circulation favored delivery of coarser-grained fluvial material to the lower Bengal Fan. At the same time the stronger NE monsoon might have increased the aeolian supply. Total inorganic carbon, the Ca/Ti ratio, and biogenic silica vary dominantly on obliquity frequencies, suggesting mobilization and transport of lithogenic material primarily during lowered sea levels and/or higher influence of the Northern Hemisphere westerlies on the dust transport from the Tibetan Plateau. The close resemblance of sediment lightness and the climate record of Antarctic ice cores over multiple glacial cycles indicate close relationship between high southern latitude and tropical Asian climate through shifts in position of the Intertropical Convergence Zone. The Bengal Fan monsoonal record shows very clear and strict responses to insolation forcing in the lower part from 200 ka to the Younger Toba Tuff during Marine Isotope Stage (MIS) 7 - 5, and less distinct response patterns after deposition of the ash during MIS 4 - 2, consistent with low-amplitude changes in insolation.

Comparisons of Anvil Cirrus Spatial Characteristics between Airborne Observations in DC3 Campaign and WRF Simulations

NASA Astrophysics Data System (ADS)

D'Alessandro, J.; Diao, M.; Chen, M.

2015-12-01

John D'Alessandro1, Minghui Diao1, Ming Chen2, George Bryan2, Hugh Morrison21. Department of Meteorology and Climate Science, San Jose State University2. Mesoscale & Microscale Meteorology Division, National Center for Atmospheric Research, Boulder, CO, 80301 Ice crystal formation requires the prerequisite condition of ice supersaturation, i.e., relative humidity with respect to ice (RHi) greater than 100%. The formation and evolution of ice supersaturated regions (ISSRs) has large impact on the subsequent formation of ice clouds. To examine the characteristics of simulated ice supersaturated regions at various model spatial resolutions, case studies between airborne in-situ measurements in the NSF Deep Convective, Clouds and Chemistry (DC3) campaign (May - June 2012) and WRF simulations are conducted in this work. Recent studies using ~200 m in-situ observations showed that ice supersaturated regions are mostly around 1 km in horizontal scale (Diao et al. 2014). Yet it is still unclear if such observed characteristics can be represented by WRF simulations at various spatial resolutions. In this work, we compare the WRF simulated anvil cirrus spatial characteristics with those observed in the DC3 campaign over the southern great plains in US. The WRF model is run at 1 km and 3 km horizontal grid spacing with a recent update of Thompson microphysics scheme. Our comparisons focus on the spatial characteristics of ISSRs and cirrus clouds, including the distributions of their horizontal scales, the maximum relative humidity with respect to ice (RHi) and the relationship between RHi and temperature. Our previous work on the NCAR CM1 cloud-resolving model shows that the higher resolution runs (i.e., 250m and 1km) generally have better agreement with observations than the coarser resolution (4km) runs. We will examine if similar trend exists for WRF simulations in deep convection cases. In addition, we will compare the simulation results between WRF and CM1, particularly for spatial correlations between ISSRs and cirrus and their evolution (based on the method of Diao et al. 2013). Overall, our work will help to assess the representation of ISSRs and cirrus in WRF simulation based on comparisons with in-situ observations.

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part 1; Improved Method and Uncertainties

NASA Technical Reports Server (NTRS)

Olson, William S.; Kummerow, Christian D.; Yang, Song; Petty, Grant W.; Tao, Wei-Kuo; Bell, Thomas L.; Braun, Scott A.; Wang, Yansen; Lang, Stephen E.; Johnson, Daniel E.;

Evaluating MODIS snow products for modelling snowmelt runoff: Case study of the Rio Grande headwaters

NASA Astrophysics Data System (ADS)

Steele, Caitriana; Dialesandro, John; James, Darren; Elias, Emile; Rango, Albert; Bleiweiss, Max

2017-12-01

Snow-covered area (SCA) is a key variable in the Snowmelt-Runoff Model (SRM) and in other models for simulating discharge from snowmelt. Landsat Thematic Mapper (TM), Enhanced Thematic Mapper (ETM +) or Operational Land Imager (OLI) provide remotely sensed data at an appropriate spatial resolution for mapping SCA in small headwater basins, but the temporal resolution of the data is low and may not always provide sufficient cloud-free dates. The coarser spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) offers better temporal resolution and in cloudy years, MODIS data offer the best alternative for mapping snow cover when finer spatial resolution data are unavailable. However, MODIS' coarse spatial resolution (500 m) can obscure fine spatial patterning in snow cover and some MODIS products are not sensitive to end-of-season snow cover. In this study, we aimed to test MODIS snow products for use in simulating snowmelt runoff from smaller headwater basins by a) comparing maps of TM and MODIS-based SCA and b) determining how SRM streamflow simulations are changed by the different estimates of seasonal snow depletion. We compared gridded MODIS snow products (Collection 5 MOD10A1 fractional and binary SCA; SCA derived from Collection 6 MOD10A1 Normalised Difference Snow Index (NDSI) Snow Cover), and the MODIS Snow Covered-Area and Grain size retrieval (MODSCAG) canopy-corrected fractional SCA (SCAMG), with reference SCA maps (SCAREF) generated from binary classification of TM imagery. SCAMG showed strong agreement with SCAREF; excluding true negatives (where both methods agreed no snow was present) the median percent difference between SCAREF and SCAMG ranged between -2.4% and 4.7%. We simulated runoff for each of the four study years using SRM populated with and calibrated for snow depletion curves derived from SCAREF. We then substituted in each of the MODIS-derived depletion curves. With efficiency coefficients ranging between 0.73 and 0.93, SRM simulation results from the SCAMG runs yielded the best results of all the MODIS products and only slightly underestimated discharge volume (between 7 and 11% of measured annual discharge). SRM simulations that used SCA derived from Collection 6 NDSI Snow Cover also yielded promising results, with efficiency coefficients ranging between 0.73 and 0.91. In conclusion, we recommend that when simulating snowmelt runoff from small basins (<4000 km2) with SRM, we recommend that users select either canopy-corrected MODSCAG or create their own site-specific products from the Collection 6 MOD10A1 NDSI.

GWM-2005 - A Groundwater-Management Process for MODFLOW-2005 with Local Grid Refinement (LGR) Capability

USGS Publications Warehouse

Ahlfeld, David P.; Baker, Kristine M.; Barlow, Paul M.

2009-01-01

This report describes the Groundwater-Management (GWM) Process for MODFLOW-2005, the 2005 version of the U.S. Geological Survey modular three-dimensional groundwater model. GWM can solve a broad range of groundwater-management problems by combined use of simulation- and optimization-modeling techniques. These problems include limiting groundwater-level declines or streamflow depletions, managing groundwater withdrawals, and conjunctively using groundwater and surface-water resources. GWM was initially released for the 2000 version of MODFLOW. Several modifications and enhancements have been made to GWM since its initial release to increase the scope of the program's capabilities and to improve its operation and reporting of results. The new code, which is called GWM-2005, also was designed to support the local grid refinement capability of MODFLOW-2005. Local grid refinement allows for the simulation of one or more higher resolution local grids (referred to as child models) within a coarser grid parent model. Local grid refinement is often needed to improve simulation accuracy in regions where hydraulic gradients change substantially over short distances or in areas requiring detailed representation of aquifer heterogeneity. GWM-2005 can be used to formulate and solve groundwater-management problems that include components in both parent and child models. Although local grid refinement increases simulation accuracy, it can also substantially increase simulation run times.

The Impact Snow Albedo Feedback over Mountain Regions as Examined through High-Resolution Regional Climate Change Experiments over the Rocky Mountains

NASA Astrophysics Data System (ADS)

Letcher, Theodore

As the climate warms, the snow albedo feedback (SAF) will play a substantial role in shaping the climate response of mid-latitude mountain regions with transient snow cover. One such region is the Rocky Mountains of the western United States where large snow packs accumulate during the winter and persist throughout the spring. In this dissertation, the Weather Research and Forecast model (WRF) configured as a regional climate model is used to investigate the role of the SAF in determining the regional climate response to forced anthropogenic climate change. The regional effects of climate change are investigated by using the pseudo global warming (PGW) framework, which is an experimental configuration in a which a mean climate perturbation is added to the boundary forcing of a regional model, thus preserving the large-scale circulation entering the region through the model boundaries and isolating the mesoscale climate response. Using this framework, the impact of the SAF on the regional energetics and atmospheric dynamics is examined and quantified. Linear feedback analysis is used to quantify the strength of the SAF over the Headwaters region of the Colorado Rockies for a series of high-resolution PGW experiments. This technique is used to test sensitivity of the feedback strength to model resolution and land surface model. Over the Colorado Rockies, and integrated over the entire spring season, the SAF strength is largely insensitive to model resolution, however there are more substantial differences on the sub-seasonal (monthly) timescale. In contrast, the SAF strength over this region is very sensitive to choice of land surface model. These simulations are also used to investigate how spatial and diurnal variability in warming caused by the SAF influences the dynamics of thermally driven mountain-breeze circulations. It is shown that, the SAF causes stronger daytime mountain-breeze circulations by increasing the warming on the mountains slopes thus enhancing the thermal contrast between the mountain slopes and the surrounding lowlands which drives these wind systems. This analysis is extended to investigate the impacts that the SAF has on the large-scale mountain-plain circulation that develops east of the Rockies over the Great Plains. To help isolate the SAF, a more idealized regional climate experiment which isolates the SAF is performed. It was found that SAF may influence thermally driven atmospheric dynamics up-to 200km east of the Mountains where the SAF originates, suggesting broader regional impacts of the SAF which may not be well resolved by coarser resolution global climate models. The implications of these changes on pollution transport and moist convection are also explored using these simulations.

Inferential consequences of modeling rather than measuring snow accumulation in studies of animal ecology

USGS Publications Warehouse

Cross, Paul C.; Klaver, Robert W.; Brennan, Angela; Creel, Scott; Beckmann, Jon P.; Higgs, Megan D.; Scurlock, Brandon M.

2013-01-01

Abstract. It is increasingly common for studies of animal ecology to use model-based predictions of environmental variables as explanatory or predictor variables, even though model prediction uncertainty is typically unknown. To demonstrate the potential for misleading inferences when model predictions with error are used in place of direct measurements, we compared snow water equivalent (SWE) and snow depth as predicted by the Snow Data Assimilation System (SNODAS) to field measurements of SWE and snow depth. We examined locations on elk (Cervus canadensis) winter ranges in western Wyoming, because modeled data such as SNODAS output are often used for inferences on elk ecology. Overall, SNODAS predictions tended to overestimate field measurements, prediction uncertainty was high, and the difference between SNODAS predictions and field measurements was greater in snow shadows for both snow variables compared to non-snow shadow areas. We used a simple simulation of snow effects on the probability of an elk being killed by a predator to show that, if SNODAS prediction uncertainty was ignored, we might have mistakenly concluded that SWE was not an important factor in where elk were killed in predatory attacks during the winter. In this simulation, we were interested in the effects of snow at finer scales (2) than the resolution of SNODAS. If bias were to decrease when SNODAS predictions are averaged over coarser scales, SNODAS would be applicable to population-level ecology studies. In our study, however, averaging predictions over moderate to broad spatial scales (9–2200 km2) did not reduce the differences between SNODAS predictions and field measurements. This study highlights the need to carefully evaluate two issues when using model output as an explanatory variable in subsequent analysis: (1) the model’s resolution relative to the scale of the ecological question of interest and (2) the implications of prediction uncertainty on inferences when using model predictions as explanatory or predictor variables.

The modelled surface mass balance of the Antarctic Peninsula at 5.5 km horizontal resolution

NASA Astrophysics Data System (ADS)

van Wessem, J. M.; Ligtenberg, S. R. M.; Reijmer, C. H.; van de Berg, W. J.; van den Broeke, M. R.; Barrand, N. E.; Thomas, E. R.; Turner, J.; Wuite, J.; Scambos, T. A.; van Meijgaard, E.

2016-02-01

This study presents a high-resolution (˜ 5.5 km) estimate of surface mass balance (SMB) over the period 1979-2014 for the Antarctic Peninsula (AP), generated by the regional atmospheric climate model RACMO2.3 and a firn densification model (FDM). RACMO2.3 is used to force the FDM, which calculates processes in the snowpack, such as meltwater percolation, refreezing and runoff. We evaluate model output with 132 in situ SMB observations and discharge rates from six glacier drainage basins, and find that the model realistically simulates the strong spatial variability in precipitation, but that significant biases remain as a result of the highly complex topography of the AP. It is also clear that the observations significantly underrepresent the high-accumulation regimes, complicating a full model evaluation. The SMB map reveals large accumulation gradients, with precipitation values above 3000 mm we yr-1 in the western AP (WAP) and below 500 mm we yr-1 in the eastern AP (EAP), not resolved by coarser data sets such as ERA-Interim. The average AP ice-sheet-integrated SMB, including ice shelves (an area of 4.1 × 105 km2), is estimated at 351 Gt yr-1 with an interannual variability of 58 Gt yr-1, which is dominated by precipitation (PR) (365 ± 57 Gt yr-1). The WAP (2.4 × 105 km2) SMB (276 ± 47 Gt yr-1), where PR is large (276 ± 47 Gt yr-1), dominates over the EAP (1.7 × 105 km2) SMB (75 ± 11 Gt yr-1) and PR (84 ± 11 Gt yr-1). Total sublimation is 11 ± 2 Gt yr-1 and meltwater runoff into the ocean is 4 ± 4 Gt yr-1. There are no significant trends in any of the modelled AP SMB components, except for snowmelt that shows a significant decrease over the last 36 years (-0.36 Gt yr-2).

Generalized lattice Boltzmann equation with forcing term for computation of wall-bounded turbulent flows.

PubMed

Premnath, Kannan N; Pattison, Martin J; Banerjee, Sanjoy

2009-02-01

In this paper, we present a framework based on the generalized lattice Boltzmann equation (GLBE) using multiple relaxation times with forcing term for eddy capturing simulation of wall-bounded turbulent flows. Due to its flexibility in using disparate relaxation times, the GLBE is well suited to maintaining numerical stability on coarser grids and in obtaining improved solution fidelity of near-wall turbulent fluctuations. The subgrid scale (SGS) turbulence effects are represented by the standard Smagorinsky eddy viscosity model, which is modified by using the van Driest wall-damping function to account for reduction of turbulent length scales near walls. In order to be able to simulate a wider class of problems, we introduce forcing terms, which can represent the effects of general nonuniform forms of forces, in the natural moment space of the GLBE. Expressions for the strain rate tensor used in the SGS model are derived in terms of the nonequilibrium moments of the GLBE to include such forcing terms, which comprise a generalization of those presented in a recent work [Yu, Comput. Fluids 35, 957 (2006)]. Variable resolutions are introduced into this extended GLBE framework through a conservative multiblock approach. The approach, whose optimized implementation is also discussed, is assessed for two canonical flow problems bounded by walls, viz., fully developed turbulent channel flow at a shear or friction Reynolds number (Re) of 183.6 based on the channel half-width and three-dimensional (3D) shear-driven flows in a cubical cavity at a Re of 12 000 based on the side length of the cavity. Comparisons of detailed computed near-wall turbulent flow structure, given in terms of various turbulence statistics, with available data, including those from direct numerical simulations (DNS) and experiments showed good agreement. The GLBE approach also exhibited markedly better stability characteristics and avoided spurious near-wall turbulent fluctuations on coarser grids when compared with the single-relaxation-time (SRT)-based approach. Moreover, its implementation showed excellent parallel scalability on a large parallel cluster with over a thousand processors.

Probabilistic global maps of the CO2 column at daily and monthly scales from sparse satellite measurements

NASA Astrophysics Data System (ADS)

Chevallier, Frédéric; Broquet, Grégoire; Pierangelo, Clémence; Crisp, David

2017-07-01

The column-average dry air-mole fraction of carbon dioxide in the atmosphere (XCO2) is measured by scattered satellite measurements like those from the Orbiting Carbon Observatory (OCO-2). We show that global continuous maps of XCO2 (corresponding to level 3 of the satellite data) at daily or coarser temporal resolution can be inferred from these data with a Kalman filter built on a model of persistence. Our application of this approach on 2 years of OCO-2 retrievals indicates that the filter provides better information than a climatology of XCO2 at both daily and monthly scales. Provided that the assigned observation uncertainty statistics are tuned in each grid cell of the XCO2 maps from an objective method (based on consistency diagnostics), the errors predicted by the filter at daily and monthly scales represent the true error statistics reasonably well, except for a bias in the high latitudes of the winter hemisphere and a lack of resolution (i.e., a too small discrimination skill) of the predicted error standard deviations. Due to the sparse satellite sampling, the broad-scale patterns of XCO2 described by the filter seem to lag behind the real signals by a few weeks. Finally, the filter offers interesting insights into the quality of the retrievals, both in terms of random and systematic errors.

Downscaling MODIS Land Surface Temperature for Urban Public Health Applications

NASA Technical Reports Server (NTRS)

Al-Hamdan, Mohammad; Crosson, William; Estes, Maurice, Jr.; Estes, Sue; Quattrochi, Dale; Johnson, Daniel

2013-01-01

This study is part of a project funded by the NASA Applied Sciences Public Health Program, which focuses on Earth science applications of remote sensing data for enhancing public health decision-making. Heat related death is currently the number one weather-related killer in the United States. Mortality from these events is expected to increase as a function of climate change. This activity sought to augment current Heat Watch/Warning Systems (HWWS) with NASA remotely sensed data, and models used in conjunction with socioeconomic and heatrelated mortality data. The current HWWS do not take into account intra-urban spatial variation in risk assessment. The purpose of this effort is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with estimates of land surface temperature (LST) derived from thermal remote sensing data. In order to further improve the consideration of intra-urban variations in risk from extreme heat, we also developed and evaluated a number of spatial statistical techniques for downscaling the 1-km daily MODerate-resolution Imaging Spectroradiometer (MODIS) LST data to 60 m using Landsat-derived LST data, which have finer spatial but coarser temporal resolution than MODIS. In this paper, we will present these techniques, which have been demonstrated and validated for Phoenix, AZ using data from the summers of 2000-2006.

PF2fit: Polar Fast Fourier Matched Alignment of Atomistic Structures with 3D Electron Microscopy Maps.

PubMed

Bettadapura, Radhakrishna; Rasheed, Muhibur; Vollrath, Antje; Bajaj, Chandrajit

2015-10-01

There continue to be increasing occurrences of both atomistic structure models in the PDB (possibly reconstructed from X-ray diffraction or NMR data), and 3D reconstructed cryo-electron microscopy (3D EM) maps (albeit at coarser resolution) of the same or homologous molecule or molecular assembly, deposited in the EMDB. To obtain the best possible structural model of the molecule at the best achievable resolution, and without any missing gaps, one typically aligns (match and fits) the atomistic structure model with the 3D EM map. We discuss a new algorithm and generalized framework, named PF(2) fit (Polar Fast Fourier Fitting) for the best possible structural alignment of atomistic structures with 3D EM. While PF(2) fit enables only a rigid, six dimensional (6D) alignment method, it augments prior work on 6D X-ray structure and 3D EM alignment in multiple ways: Scoring. PF(2) fit includes a new scoring scheme that, in addition to rewarding overlaps between the volumes occupied by the atomistic structure and 3D EM map, rewards overlaps between the volumes complementary to them. We quantitatively demonstrate how this new complementary scoring scheme improves upon existing approaches. PF(2) fit also includes two scoring functions, the non-uniform exterior penalty and the skeleton-secondary structure score, and implements the scattering potential score as an alternative to traditional Gaussian blurring. Search. PF(2) fit utilizes a fast polar Fourier search scheme, whose main advantage is the ability to search over uniformly and adaptively sampled subsets of the space of rigid-body motions. PF(2) fit also implements a new reranking search and scoring methodology that considerably improves alignment metrics in results obtained from the initial search.

Computationally efficient methods for modelling laser wakefield acceleration in the blowout regime

NASA Astrophysics Data System (ADS)

Cowan, B. M.; Kalmykov, S. Y.; Beck, A.; Davoine, X.; Bunkers, K.; Lifschitz, A. F.; Lefebvre, E.; Bruhwiler, D. L.; Shadwick, B. A.; Umstadter, D. P.; Umstadter

2012-08-01

Electron self-injection and acceleration until dephasing in the blowout regime is studied for a set of initial conditions typical of recent experiments with 100-terawatt-class lasers. Two different approaches to computationally efficient, fully explicit, 3D particle-in-cell modelling are examined. First, the Cartesian code vorpal (Nieter, C. and Cary, J. R. 2004 VORPAL: a versatile plasma simulation code. J. Comput. Phys. 196, 538) using a perfect-dispersion electromagnetic solver precisely describes the laser pulse and bubble dynamics, taking advantage of coarser resolution in the propagation direction, with a proportionally larger time step. Using third-order splines for macroparticles helps suppress the sampling noise while keeping the usage of computational resources modest. The second way to reduce the simulation load is using reduced-geometry codes. In our case, the quasi-cylindrical code calder-circ (Lifschitz, A. F. et al. 2009 Particle-in-cell modelling of laser-plasma interaction using Fourier decomposition. J. Comput. Phys. 228(5), 1803-1814) uses decomposition of fields and currents into a set of poloidal modes, while the macroparticles move in the Cartesian 3D space. Cylindrical symmetry of the interaction allows using just two modes, reducing the computational load to roughly that of a planar Cartesian simulation while preserving the 3D nature of the interaction. This significant economy of resources allows using fine resolution in the direction of propagation and a small time step, making numerical dispersion vanishingly small, together with a large number of particles per cell, enabling good particle statistics. Quantitative agreement of two simulations indicates that these are free of numerical artefacts. Both approaches thus retrieve the physically correct evolution of the plasma bubble, recovering the intrinsic connection of electron self-injection to the nonlinear optical evolution of the driver.

PF2 fit: Polar Fast Fourier Matched Alignment of Atomistic Structures with 3D Electron Microscopy Maps

PubMed Central

Bettadapura, Radhakrishna; Rasheed, Muhibur; Vollrath, Antje; Bajaj, Chandrajit

2015-01-01

There continue to be increasing occurrences of both atomistic structure models in the PDB (possibly reconstructed from X-ray diffraction or NMR data), and 3D reconstructed cryo-electron microscopy (3D EM) maps (albeit at coarser resolution) of the same or homologous molecule or molecular assembly, deposited in the EMDB. To obtain the best possible structural model of the molecule at the best achievable resolution, and without any missing gaps, one typically aligns (match and fits) the atomistic structure model with the 3D EM map. We discuss a new algorithm and generalized framework, named PF2 fit (Polar Fast Fourier Fitting) for the best possible structural alignment of atomistic structures with 3D EM. While PF2 fit enables only a rigid, six dimensional (6D) alignment method, it augments prior work on 6D X-ray structure and 3D EM alignment in multiple ways: Scoring. PF2 fit includes a new scoring scheme that, in addition to rewarding overlaps between the volumes occupied by the atomistic structure and 3D EM map, rewards overlaps between the volumes complementary to them. We quantitatively demonstrate how this new complementary scoring scheme improves upon existing approaches. PF2 fit also includes two scoring functions, the non-uniform exterior penalty and the skeleton-secondary structure score, and implements the scattering potential score as an alternative to traditional Gaussian blurring. Search. PF2 fit utilizes a fast polar Fourier search scheme, whose main advantage is the ability to search over uniformly and adaptively sampled subsets of the space of rigid-body motions. PF2 fit also implements a new reranking search and scoring methodology that considerably improves alignment metrics in results obtained from the initial search. PMID:26469938

Spectral Mixture Analysis to map burned areas in Brazil's deforestation arc from 1992 to 2011

NASA Astrophysics Data System (ADS)

Antunes Daldegan, G.; Ribeiro, F.; Roberts, D. A.

2017-12-01

The two most extensive biomes in South America, the Amazon and the Cerrado, are subject to several fire events every dry season. Both are known for their ecological and environmental importance. However, due to the intensive human occupation over the last four decades, they have been facing high deforestation rates. The Cerrado biome is adapted to fire and is considered a fire-dependent landscape. In contrast, the Amazon as a tropical moist broadleaf forest does not display similar characteristics and is classified as a fire-sensitive landscape. Nonetheless, studies have shown that forest areas that have already been burned become more prone to experience recurrent burns. Remote sensing has been extensively used by a large number of researchers studying fire occurrence at a global scale, as well as in both landscapes aforementioned. Digital image processing aiming to map fire activity has been applied to a number of imagery from sensors of various spatial, temporal, and spectral resolutions. More specifically, several studies have used Landsat data to map fire scars in the Amazon forest and in the Cerrado. An advantage of using Landsat data is the potential to map fire scars at a finer spatial resolution, when compared to products derived from imagery of sensors featuring better temporal resolution but coarser spatial resolution, such as MODIS (Moderate Resolution Imaging Spectrometer) and GOES (Geostationary Operational Environmental Satellite). This study aimed to map burned areas present in the Amazon-Cerrado transition zone by applying Spectral Mixture Analysis on Landsat imagery for a period of 20 years (1992-2011). The study area is a subset of this ecotone, centered at the State of Mato Grosso. By taking advantage of the Landsat 5TM and Landsat 7ETM+ imagery collections available in Google Earth Engine platform and applying Spectral Mixture Analysis (SMA) techniques over them permitted to model fire scar fractions and delimitate burned areas. Overlaying yearly burned areas allowed to identify areas with high fire recurrence.

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.

Giga-LES of Hector the Convector keeping the tallest updrafts undiluted

NASA Astrophysics Data System (ADS)

Dauhut, Thibaut; Chaboureau, Jean-Pierre; Escobar, Juan; Mascart, Patrick

2015-04-01

The trend of stratospheric water vapour during the past decades is not correctly reproduced by current GCMs. This may be due to lack of representation of rapid water transfers from troposphere to stratosphere. Our modeling study focused on a particular case of tropical very deep convection which takes an active part in this transport. We aimed at understanding its dynamics and the stratosphere moistening processes. We selected a Hector thunderstorm observed on 30 November 2005 over Tiwi Islands, Australia, during the SCOUT-O3 field campaign. Plumes of ice particles reaching 19 km altitude were measured by lidar aboard the Geophysica stratospheric aircraft. We performed a Giga Large-Eddy Simulation of Hector (100 m horizontal resolution, more than 1 billion grid points) using cutting-edge computing resources, as well as a series of simulations with coarser and coarser horizontal resolutions, from 200 m to 1600 m. A strong morning sea breeze deviated boundary layer westerlies and led to intense convergence of humid air over Tiwi Islands. Deep convection triggered around 12:15 pm and quickly reached 14 km altitude. The associated cold pools organised and generated upward motions at the surface. The most intense upward transport started 1 hour later and lasted around 2 hours. As a result, a couple of updrafts overshot the tropopause carrying ice crystals in the stratosphere. Part of the ice particles precipitated then whereas the remainder sublimated in the lower stratosphere. The consequent vapour pockets were transported and diluted within the stratosphere by easterlies. While moistening appeared to be robust with respect to the grid spacing used, grid spacing on the order of 100 m may be necessary for a reliable estimate of hydration (Dauhut et al. ASL 2014, doi: 10.1002/asl2.534). A comprehensive analysis of individual updrafts and their properties once sorted by their height has been carried out. The couple of updrafts that reach the stratosphere presents a higher buoyancy, stronger vertical velocities and larger hydrometeor contents compared to the ordinary deep convective updrafts. At the cloud base, the stronger horizontal convergence due to the cold pools generated by the previous deep convective updrafts strengthens the vertical velocity while no differences in the size of the cloud base have been found. At 10 km altitude, the overshooting updrafts show a much larger core size suggesting that the reduced lateral mixing promotes the tropopause overshoot. Similar results are obtained whatever the resolution. The preconditioning through cold pools generation and troposphere moistening is found to be determinant for the transition from the deep to the very deep convection. This study was supported by the StratoClim project.

Cloud Computing-based Platform for Drought Decision-Making using Remote Sensing and Modeling Products: Preliminary Results for Brazil

NASA Astrophysics Data System (ADS)

Vivoni, E.; Mascaro, G.; Shupe, J. W.; Hiatt, C.; Potter, C. S.; Miller, R. L.; Stanley, J.; Abraham, T.; Castilla-Rubio, J.

2012-12-01

Droughts and their hydrological consequences are a major threat to food security throughout the world. In arid and semiarid regions dependent on irrigated agriculture, prolonged droughts lead to significant and recurring economic and social losses. In this contribution, we present preliminary results on integrating a set of multi-resolution drought indices into a cloud computing-based visualization platform. We focused our initial efforts on Brazil due to a severe, on-going drought in a large agricultural area in the northeastern part of the country. The online platform includes drought products developed from: (1) a MODIS-based water stress index (WSI) based on inferences from normalized difference vegetation index and land surface temperature fields, (2) a volumetric water content (VWC) index obtained from application of the NASA CASA model, and (3) a set of AVHRR-based vegetation health indices obtained from NOAA/NESDIS. The drought indices are also presented in terms of anomalies with respect to a baseline period. Since our main objective is to engage stakeholders and decision-makers in Brazil, we incorporated other relevant geospatial data into the platform, including irrigation areas, dams and reservoirs, administrative units and annual climate information. We will also present a set of use cases developed to help stakeholders explore, query and provide feedback that allowed fine-tuning of the drought product delivery, presentation and analysis tools. Finally, we discuss potential next steps in development of the online platform, including applications at finer resolutions in specific basins and at a coarser global scale.

Accuracy of stream habitat interpolations across spatial scales

USGS Publications Warehouse

Sheehan, Kenneth R.; Welsh, Stuart A.

2013-01-01

Stream habitat data are often collected across spatial scales because relationships among habitat, species occurrence, and management plans are linked at multiple spatial scales. Unfortunately, scale is often a factor limiting insight gained from spatial analysis of stream habitat data. Considerable cost is often expended to collect data at several spatial scales to provide accurate evaluation of spatial relationships in streams. To address utility of single scale set of stream habitat data used at varying scales, we examined the influence that data scaling had on accuracy of natural neighbor predictions of depth, flow, and benthic substrate. To achieve this goal, we measured two streams at gridded resolution of 0.33 × 0.33 meter cell size over a combined area of 934 m2 to create a baseline for natural neighbor interpolated maps at 12 incremental scales ranging from a raster cell size of 0.11 m2 to 16 m2 . Analysis of predictive maps showed a logarithmic linear decay pattern in RMSE values in interpolation accuracy for variables as resolution of data used to interpolate study areas became coarser. Proportional accuracy of interpolated models (r2 ) decreased, but it was maintained up to 78% as interpolation scale moved from 0.11 m2 to 16 m2 . Results indicated that accuracy retention was suitable for assessment and management purposes at various scales different from the data collection scale. Our study is relevant to spatial modeling, fish habitat assessment, and stream habitat management because it highlights the potential of using a single dataset to fulfill analysis needs rather than investing considerable cost to develop several scaled datasets.

Assessing biomass of diverse coastal marsh ecosystems using statistical and machine learning models

NASA Astrophysics Data System (ADS)

Mo, Yu; Kearney, Michael S.; Riter, J. C. Alexis; Zhao, Feng; Tilley, David R.

2018-06-01

The importance and vulnerability of coastal marshes necessitate effective ways to closely monitor them. Optical remote sensing is a powerful tool for this task, yet its application to diverse coastal marsh ecosystems consisting of different marsh types is limited. This study samples spectral and biophysical data from freshwater, intermediate, brackish, and saline marshes in Louisiana, and develops statistical and machine learning models to assess the marshes' biomass with combined ground, airborne, and spaceborne remote sensing data. It is found that linear models derived from NDVI and EVI are most favorable for assessing Leaf Area Index (LAI) using multispectral data (R2 = 0.7 and 0.67, respectively), and the random forest models are most useful in retrieving LAI and Aboveground Green Biomass (AGB) using hyperspectral data (R2 = 0.91 and 0.84, respectively). It is also found that marsh type and plant species significantly impact the linear model development (P < .05 in both cases). Sensors with coarser spatial resolution yield lower LAI values because the fine water networks are not detected and mixed into the vegetation pixels. The Landsat OLI-derived map shows the LAI of coastal mashes in Louisiana mostly ranges from 0 to 5.0, and is highest for freshwater marshes and for marshes in the Atchafalaya Bay delta. The CASI-derived maps show that LAI of saline marshes at Bay Batiste typically ranges from 0.9 to 1.5, and the AGB is mostly less than 900 g/m2. This study provides solutions for assessing the biomass of Louisiana's coastal marshes using various optical remote sensing techniques, and highlights the impacts of the marshes' species composition on the model development and the sensors' spatial resolution on biomass mapping, thereby providing useful tools for monitoring the biomass of coastal marshes in Louisiana and diverse coastal marsh ecosystems elsewhere.

SMAP Data Assimilation at the GMAO

NASA Technical Reports Server (NTRS)

Reichle, R.; De Lannoy, G.; Liu, Q.; Ardizzone, J.

2016-01-01

The NASA Soil Moisture Active Passive (SMAP) mission has been providing L-band (1.4 GHz) passive microwave brightness temperature (Tb) observations since April 2015. These observations are sensitive to surface(0-5 cm) soil moisture. Several of the key applications targeted by SMAP, however, require knowledge of deeper-layer, root zone (0-100 cm) soil moisture, which is not directly measured by SMAP. The NASA Global Modeling and Assimilation Office (GMAO) contributes to SMAP by providing Level 4 data, including the Level 4 Surface and Root Zone Soil Moisture(L4_SM) product, which is based on the assimilation of SMAP Tb observations in the ensemble-based NASA GEOS-5 land surface data assimilation system. The L4_SM product offers global data every three hours at 9 km resolution, thereby interpolating and extrapolating the coarser- scale (40 km) SMAP observations in time and in space (both horizontally and vertically). Since October 31, 2015, beta-version L4_SM data have been available to the public from the National Snow and Ice Data Center for the period March 31, 2015, to near present, with a mean latency of approx. 2.5 days.

Super-resolution mapping using multi-viewing CHRIS/PROBA data

NASA Astrophysics Data System (ADS)

Dwivedi, Manish; Kumar, Vinay

2016-04-01

High-spatial resolution Remote Sensing (RS) data provides detailed information which ensures high-definition visual image analysis of earth surface features. These data sets also support improved information extraction capabilities at a fine scale. In order to improve the spatial resolution of coarser resolution RS data, the Super Resolution Reconstruction (SRR) technique has become widely acknowledged which focused on multi-angular image sequences. In this study multi-angle CHRIS/PROBA data of Kutch area is used for SR image reconstruction to enhance the spatial resolution from 18 m to 6m in the hope to obtain a better land cover classification. Various SR approaches like Projection onto Convex Sets (POCS), Robust, Iterative Back Projection (IBP), Non-Uniform Interpolation and Structure-Adaptive Normalized Convolution (SANC) chosen for this study. Subjective assessment through visual interpretation shows substantial improvement in land cover details. Quantitative measures including peak signal to noise ratio and structural similarity are used for the evaluation of the image quality. It was observed that SANC SR technique using Vandewalle algorithm for the low resolution image registration outperformed the other techniques. After that SVM based classifier is used for the classification of SRR and data resampled to 6m spatial resolution using bi-cubic interpolation. A comparative analysis is carried out between classified data of bicubic interpolated and SR derived images of CHRIS/PROBA and SR derived classified data have shown a significant improvement of 10-12% in the overall accuracy. The results demonstrated that SR methods is able to improve spatial detail of multi-angle images as well as the classification accuracy.

Performance Improvements of the CYCOFOS Flow Model

NASA Astrophysics Data System (ADS)

Radhakrishnan, Hari; Moulitsas, Irene; Syrakos, Alexandros; Zodiatis, George; Nikolaides, Andreas; Hayes, Daniel; Georgiou, Georgios C.

2013-04-01

The CYCOFOS-Cyprus Coastal Ocean Forecasting and Observing System has been operational since early 2002, providing daily sea current, temperature, salinity and sea level forecasting data for the next 4 and 10 days to end-users in the Levantine Basin, necessary for operational application in marine safety, particularly concerning oil spills and floating objects predictions. CYCOFOS flow model, similar to most of the coastal and sub-regional operational hydrodynamic forecasting systems of the MONGOOS-Mediterranean Oceanographic Network for Global Ocean Observing System is based on the POM-Princeton Ocean Model. CYCOFOS is nested with the MyOcean Mediterranean regional forecasting data and with SKIRON and ECMWF for surface forcing. The increasing demand for higher and higher resolution data to meet coastal and offshore downstream applications motivated the parallelization of the CYCOFOS POM model. This development was carried out in the frame of the IPcycofos project, funded by the Cyprus Research Promotion Foundation. The parallel processing provides a viable solution to satisfy these demands without sacrificing accuracy or omitting any physical phenomena. Prior to IPcycofos project, there are been several attempts to parallelise the POM, as for example the MP-POM. The existing parallel code models rely on the use of specific outdated hardware architectures and associated software. The objective of the IPcycofos project is to produce an operational parallel version of the CYCOFOS POM code that can replicate the results of the serial version of the POM code used in CYCOFOS. The parallelization of the CYCOFOS POM model use Message Passing Interface-MPI, implemented on commodity computing clusters running open source software and not depending on any specialized vendor hardware. The parallel CYCOFOS POM code constructed in a modular fashion, allowing a fast re-locatable downscaled implementation. The MPI takes advantage of the Cartesian nature of the POM mesh, and use the built-in functionality of MPI routines to split the mesh, using a weighting scheme, along longitude and latitude among the processors. Each server processor work on the model based on domain decomposition techniques. The new parallel CYCOFOS POM code has been benchmarked against the serial POM version of CYCOFOS for speed, accuracy, and resolution and the results are more than satisfactory. With a higher resolution CYCOFOS Levantine model domain the forecasts need much less time than the serial CYCOFOS POM coarser version, both with identical accuracy.

Genetic implications of the trace element distribution pattern in the upper knox carbonate rocks, copper ridge district, East Tennessee

NASA Astrophysics Data System (ADS)

Churnet, Habte G.; Misra, Kula C.

1981-11-01

The Lower Ordovician, Upper Knox Group rocks (the Kingsport and Mascot formations) in the Copper Ridge district consist predominantly of fine-grained dolostones, medium and coarser grained dolostones, and limestones. Dolomite crystals of medium and coarser grained dolostones show up to eight cathodoluminescent zones of variable width and intensity. Electron microprobe analyses indicate that the zoning is related to variation in Fe/Mn ratios, the brighter luminescent zones corresponding to lower ratios. Superposed on this growth zoning is a compositional zoning characterized by a general increase in Fe from core to rim of individual dolomite crystals. Field and petrographic studies (Churnet, 1979; Churnet et al., 1981) indicate that the fine-grained dolostones formed in supratidal to upper intratidal environments, whereas the precursor lime muds of the limestones as well as of the medium and coarser grained dolostones formed in shallow subtidal to lower intertidal environments. The large areal extent of the dolostones must have required a regionally abundant source of Mg such as marine water. Yet, both limestones and dolostones have low Na and Sr contents suggestive of their formation in solutions more dilute than normal marine water. It is proposed that the fine-grained dolostones formed by aggradation of initially very fine-grained dolostones in presence of fresh water, and that the limestones stabilized and the medium and coarser grained dolostones formed in environments of mixed marine and fresh waters. Considered in the light of ordering of partition coefficients, such a mixing model can account for the observed correlation pattern of trace elements (especially, SMn and SrFe) as well as the Fe distribution in the zoned dolomite crystals. Variation of the partition coefficient of Mn due to fluctuations in the relative proportions of fresh and marine waters in the diagenetic solution may explain the different Fe/Mn ratios observed in the growth zones (luminescence bands) of zoned dolomite crystals.

Modeling the reduction in soil loss due to soil armouring caused by rainfall erosion

USDA-ARS?s Scientific Manuscript database

Surface soil properties can change as a result of soil disturbances, erosion, or deposition. One process that can significantly change surface soil properties is soil armouring, which is the selective removal of finer particles by rill or interrill erosion, leaving an armoured layer of coarser parti...

Exploiting MISR products at the full spatial resolution (275m) to document changes in land properties in and around the Kruger National Park, South Africa

NASA Astrophysics Data System (ADS)

Verstraete, M. M.; Hunt, L. A.; Pinty, B.; Clerici, M.; Scholes, R. J.

2009-12-01

The MISR instrument on NASA's Terra platform has been acquiring data globally and continuously for almost 10 years. A wide range of atmospheric and land products are operationally generated at the LaRC ASDC, at spatial resolutions of 1.1 km or coarser. Yet, the intrinsic spatial resolution of that sensor is 275m and 12 out of the 36 spectro-directional data channels are transmitted to the ground segment at that resolution. Recent algorithmic developments have permitted us to reconstruct reasonable estimates of the other 24 channels and to account for atmospheric effects at the full original spatial resolution. Spectro-directional reflectances have been processed to characterize the anisotropy of observed land surfaces and then optimally estimate various geophysical properties of the environment such as the fluxes of radiation in and out of plant canopies, the albedo, FAPAR, etc. These detailed products allow us to investigate ecological and environmental changes in much greater spatial and thematic detail than was previously possible. The paper outlines the various methodological steps implemented and exhibits concrete results for a region of moderate size (280 by 380 km) in South Africa. Practical downstream applications of this approach include monitoring desertification and biomass burning, documenting urbanization or characterizing the phenology of vegetation.

Stennis Space Center Verification & Validation Capabilities

NASA Technical Reports Server (NTRS)

Pagnutti, Mary; Ryan, Robert E.; Holekamp, Kara; O'Neal, Duane; Knowlton, Kelly; Ross, Kenton; Blonski, Slawomir

2007-01-01

Scientists within NASA#s Applied Research & Technology Project Office (formerly the Applied Sciences Directorate) have developed a well-characterized remote sensing Verification & Validation (V&V) site at the John C. Stennis Space Center (SSC). This site enables the in-flight characterization of satellite and airborne high spatial resolution remote sensing systems and their products. The smaller scale of the newer high resolution remote sensing systems allows scientists to characterize geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the techniques used to characterize data from the earlier, coarser spatial resolution systems. Scientists have used the SSC V&V site to characterize thermal infrared systems. Enhancements are being considered to characterize active lidar systems. SSC employs geodetic targets, edge targets, radiometric tarps, atmospheric monitoring equipment, and thermal calibration ponds to characterize remote sensing data products. Similar techniques are used to characterize moderate spatial resolution sensing systems at selected nearby locations. The SSC Instrument Validation Lab is a key component of the V&V capability and is used to calibrate field instrumentation and to provide National Institute of Standards and Technology traceability. This poster presents a description of the SSC characterization capabilities and examples of calibration data.

Multi-Length Scale-Enriched Continuum-Level Material Model for Kevlar (registered trademark)-Fiber-Reinforced Polymer-Matrix Composites

DTIC Science & Technology

2013-03-01

of coarser-scale materials and structures containing Kevlar fibers (e.g., yarns, fabrics, plies, lamina, and laminates ). Journal of Materials...Multi-Length Scale-Enriched Continuum-Level Material Model for Kevlar -Fiber-Reinforced Polymer-Matrix Composites M. Grujicic, B. Pandurangan, J.S...extensive set of molecular-level computational analyses regarding the role of various microstructural/morphological defects on the Kevlar fiber

Hazardous thunderstorm intensification over Lake Victoria

PubMed Central

Thiery, Wim; Davin, Edouard L.; Seneviratne, Sonia I.; Bedka, Kristopher; Lhermitte, Stef; van Lipzig, Nicole P. M.

2016-01-01

Weather extremes have harmful impacts on communities around Lake Victoria, where thousands of fishermen die every year because of intense night-time thunderstorms. Yet how these thunderstorms will evolve in a future warmer climate is still unknown. Here we show that Lake Victoria is projected to be a hotspot of future extreme precipitation intensification by using new satellite-based observations, a high-resolution climate projection for the African Great Lakes and coarser-scale ensemble projections. Land precipitation on the previous day exerts a control on night-time occurrence of extremes on the lake by enhancing atmospheric convergence (74%) and moisture availability (26%). The future increase in extremes over Lake Victoria is about twice as large relative to surrounding land under a high-emission scenario, as only over-lake moisture advection is high enough to sustain Clausius–Clapeyron scaling. Our results highlight a major hazard associated with climate change over East Africa and underline the need for high-resolution projections to assess local climate change. PMID:27658848

VizieR Online Data Catalog: LMC and Cen A 1.3-10GHz polarization behavior (Anderson+, 2016)

NASA Astrophysics Data System (ADS)

Anderson, C. S.; Gaensler, B. M.; Feain, I. J.

2016-08-01

The targets for our study were selected from among two archival polarization data sets, which were observed and processed by several independent groups. i.e. LMC observations spanning from 1994 Oct to 1996 Jan in 1.328-1.432GHz band; Cen A observations spanning from 2006 Dec to 2008 Feb in 1.296-1.480GHz band. We observed the 40 sample sources using the Australia Telescope Compact Array (ATCA) over 1.1-3.1GHz (16cm), 4.5-6.5GHz (6cm), and 8.0-10.0GHz (3cm) in full polarization with a nominal 1MHz channel resolution between 2012 Feb 10-12 and 2012 Aug 17-19. We imaged each source in Stokes I, Q, and U at 20MHz intervals through the 16 and 6cm bands, and at a substantially coarser resolution of 200MHz in the 3cm band. See sections 2 and 3 for further explanations. (2 data files).

Potential for Small Unmanned Aircraft Systems applications for identifying groundwater-surface water exchange in a meandering river reach

USGS Publications Warehouse

Pai, H.; Malenda, H.; Briggs, Martin A.; Singha, K.; González-Pinzón, R.; Gooseff, M.; Tyler, S.W.; ,

2017-01-01

The exchange of groundwater and surface water (GW-SW), including dissolved constituents and energy, represents a critical yet challenging characterization problem for hydrogeologists and stream ecologists. Here, we describe the use of a suite of high spatial-resolution remote-sensing techniques, collected using a small unmanned aircraft system (sUAS), to provide novel and complementary data to analyze GW-SW exchange. sUAS provided centimeter-scale resolution topography and water surface elevations, which are often drivers of exchange along the river corridor. Additionally, sUAS-based vegetation imagery, vegetation-top elevation, and normalized difference vegetation index (NDVI) mapping indicated GW-SW exchange patterns that are difficult to characterize from the land surface and may not be resolved from coarser satellite-based imagery. We combined these data with estimates of sediment hydraulic conductivity to provide a direct estimate of GW “shortcutting” through meander necks, which was corroborated by temperature data at the riverbed interface.

Potential for Small Unmanned Aircraft Systems Applications for Identifying Groundwater-Surface Water Exchange in a Meandering River Reach

NASA Astrophysics Data System (ADS)

Pai, H.; Malenda, H. F.; Briggs, M. A.; Singha, K.; González-Pinzón, R.; Gooseff, M. N.; Tyler, S. W.

2017-12-01

The exchange of groundwater and surface water (GW-SW), including dissolved constituents and energy, represents a critical yet challenging characterization problem for hydrogeologists and stream ecologists. Here we describe the use of a suite of high spatial resolution remote sensing techniques, collected using a small unmanned aircraft system (sUAS), to provide novel and complementary data to analyze GW-SW exchange. sUAS provided centimeter-scale resolution topography and water surface elevations, which are often drivers of exchange along the river corridor. Additionally, sUAS-based vegetation imagery, vegetation-top elevation, and normalized difference vegetation index mapping indicated GW-SW exchange patterns that are difficult to characterize from the land surface and may not be resolved from coarser satellite-based imagery. We combined these data with estimates of sediment hydraulic conductivity to provide a direct estimate of GW "shortcutting" through meander necks, which was corroborated by temperature data at the riverbed interface.

Generation of Accurate Lateral Boundary Conditions for a Surface-Water Groundwater Interaction Model

NASA Astrophysics Data System (ADS)

Khambhammettu, P.; Tsou, M.; Panday, S. M.; Kool, J.; Wei, X.

2010-12-01

The 106 mile long Peace River in Florida flows south from Lakeland to Charlotte Harbor and has a drainage basin of approximately 2,350 square miles. A long-term decline in stream flows and groundwater potentiometric levels has been observed in the region. Long-term trends in rainfall, along with effects of land use changes on runoff, surface-water storage, recharge and evapotranspiration patterns, and increased groundwater and surface-water withdrawals have contributed to this decline. The South West Florida Water Management District (SWFWMD) has funded the development of the Peace River Integrated Model (PRIM) to assess the effects of land use, water use, and climatic changes on stream flows and to evaluate the effectiveness of various management alternatives for restoring stream flows. The PRIM was developed using MODHMS, a fully integrated surface-water groundwater flow and transport simulator developed by HydroGeoLogic, Inc. The development of the lateral boundary conditions (groundwater inflow and outflow) for the PRIM in both historical and predictive contexts is discussed in this presentation. Monthly-varying specified heads were used to define the lateral boundary conditions for the PRIM. These head values were derived from the coarser Southern District Groundwater Model (SDM). However, there were discrepancies between the simulated SDM heads and measured heads: the likely causes being spatial (use of a coarser grid) and temporal (monthly average pumping rates and recharge rates) approximations in the regional SDM. Finer re-calibration of the SDM was not feasible, therefore, an innovative approach was adopted to remove the discrepancies. In this approach, point discrepancies/residuals between the observed and simulated heads were kriged with an appropriate variogram to generate a residual surface. This surface was then added to the simulated head surface of the SDM to generate a corrected head surface. This approach preserves the trends associated with groundwater pumping / recharge in the SDM and adds the kriged residual surface as variations back to the trend. The variations could be from the scale effects of grid resolution and from the temporal averaging of stresses (pumping, recharge, etc.,). The validity of the approach is demonstrated by visual and statistical comparison of the observed and simulated heads before and after correction. For predictive simulations, an Artificial Neural Network was trained to predict heads at monitoring wells based on precipitation and pumping. These predicted head values could then be used as surrogate observations for correcting the results of the regional SDM. In summary, an appropriate approach to link a regional groundwater model to a detailed surface-water groundwater interaction model is demonstrated with an example.

The potential of hydrodynamic analysis for the interpretation of Martian fluvial activities

NASA Astrophysics Data System (ADS)

Kim, Jungrack; Schumann, Guy; Neal, Jeffrey; Lin, Shih-Yuan

2014-05-01

After liquid water was identified as the agent of ancient Martian fluvial activities, the valley and channels on the Martian surface were investigated by a number of remote sensing and in-situ measurements. In particular, the stereo DTMs and ortho images from various successful orbital sensors are being effectively used to trace the origin and consequences of Martian hydrological channels. For instance, to analyze the Martian fluvial activities more quantitatively using the topographic products, Burr et al. (2003) employed 1D hydrodynamic models such as HEC-RAS together with the topography by MOLA to derive water flow estimates for the Athabasca Valles area on Mars [1]. Where extensive floodplain flows or detailed 2D bathymetry for the river channel exist, it may be more accurate to simulate flows in two dimensions, especially if the direction of flow is unclear a priori. Thus in this study we demonstrated a quantitative modeling method utilizing multi-resolution Martian DTMs, constructed in line with Kim and Muller's (2009) [2] approach, and an advanced hydraulics model LISFLOOD-FP (Bates et al., 2010) [3], which simulates in-channel dynamic wave behavior by solving for 2D shallow water equations without advection. Martian gravitation and manning constants were adjusted in the hydraulic model and the inflow values were iteratively refined from the outputs of the coarser to the finer model. Then we chose the target areas among Martian fluvial geomorphologies and tested the effectiveness of high resolution hydraulic modeling to retrieve the characteristics of fluvial systems. Test sites were established in the Athabasca Valles, Bahram Vallis, and Naktong Vallis respectively. Since those sites are proposed to be originated by different fluvial mechanisms, it is expected that the outputs from hydraulics modeling will provide important clues about the evolution of each fluvial system. Hydraulics modeling in the test areas with terrestrial simulation parameters was also conducted to explore the different characteristics of two planets' fluvial activities. Ultimately, this study proved the effectiveness of multi-resolution modeling using 150-1.2m DTMs and 2D hydraulics to study the Martian fluvial system. In future study, we will elaborate the hydrodynamic model to investigate the sediment transformation mechanism in Martian fluvial activities using hydrodynamic properties such as flow speed. References: [1] Burr, D.M. (2003).Hydraulic modelling of Athabasca Vallis, Mars. Hydrological Sciences Journal, 48(4), 655-664. [2] Kim, J.R. & Muller, J-P.,(2009).Multi resolution topographic data extraction from Martian stereo imagery.Planetary and Space Science. 57, 2095-2112. [3] Bates, P.D., Horritt, M.S., & Fewtrell, T.J. (2010). A simple inertial formulation of the shallow water equations for efficient two-dimensional flood inundation modelling. Journal of Hydrology, 387(1), 33-45.

Ames Stereo Pipeline for Operation IceBridge

NASA Astrophysics Data System (ADS)

Beyer, R. A.; Alexandrov, O.; McMichael, S.; Fong, T.

2017-12-01

We are using the NASA Ames Stereo Pipeline to process Operation IceBridge Digital Mapping System (DMS) images into terrain models and to align them with the simultaneously acquired LIDAR data (ATM and LVIS). The expected outcome is to create a contiguous, high resolution terrain model for each flight that Operation IceBridge has flown during its eight year history of Arctic and Antarctic flights. There are some existing terrain models in the NSIDC repository that cover 2011 and 2012 (out of the total period of 2009 to 2017), which were made with the Agisoft Photoscan commercial software. Our open-source stereo suite has been verified to create terrains of similar quality. The total number of images we expect to process is around 5 million. There are numerous challenges with these data: accurate determination and refinement of camera pose when the images were acquired based on data logged during the flights and/or using information from existing orthoimages, aligning terrains with little or no features, images containing clouds, JPEG artifacts in input imagery, inconsistencies in how data was acquired/archived over the entire period, not fully reliable camera calibration files, and the sheer amount of data. We will create the majority of terrain models at 40 cm/pixel with a vertical precision of 10 to 20 cm. In some circumstances when the aircraft was flying higher than usual, those values will get coarser. We will create orthoimages at 10 cm/pixel (with the same caveat that some flights are at higher altitudes). These will differ from existing orthoimages by using the underlying terrain we generate rather than some pre-existing very low-resolution terrain model that may differ significantly from what is on the ground at the time of IceBridge acquisition.The results of this massive processing will be submitted to the NSIDC so that cryosphere researchers will be able to use these data for their investigations.

Lidar aboveground vegetation biomass estimates in shrublands: Prediction, uncertainties and application to coarser scales

USGS Publications Warehouse

Li, Aihua; Dhakal, Shital; Glenn, Nancy F.; Spaete, Luke P.; Shinneman, Douglas; Pilliod, David S.; Arkle, Robert; McIlroy, Susan

2017-01-01

Our study objectives were to model the aboveground biomass in a xeric shrub-steppe landscape with airborne light detection and ranging (Lidar) and explore the uncertainty associated with the models we created. We incorporated vegetation vertical structure information obtained from Lidar with ground-measured biomass data, allowing us to scale shrub biomass from small field sites (1 m subplots and 1 ha plots) to a larger landscape. A series of airborne Lidar-derived vegetation metrics were trained and linked with the field-measured biomass in Random Forests (RF) regression models. A Stepwise Multiple Regression (SMR) model was also explored as a comparison. Our results demonstrated that the important predictors from Lidar-derived metrics had a strong correlation with field-measured biomass in the RF regression models with a pseudo R2 of 0.76 and RMSE of 125 g/m2 for shrub biomass and a pseudo R2 of 0.74 and RMSE of 141 g/m2 for total biomass, and a weak correlation with field-measured herbaceous biomass. The SMR results were similar but slightly better than RF, explaining 77–79% of the variance, with RMSE ranging from 120 to 129 g/m2 for shrub and total biomass, respectively. We further explored the computational efficiency and relative accuracies of using point cloud and raster Lidar metrics at different resolutions (1 m to 1 ha). Metrics derived from the Lidar point cloud processing led to improved biomass estimates at nearly all resolutions in comparison to raster-derived Lidar metrics. Only at 1 m were the results from the point cloud and raster products nearly equivalent. The best Lidar prediction models of biomass at the plot-level (1 ha) were achieved when Lidar metrics were derived from an average of fine resolution (1 m) metrics to minimize boundary effects and to smooth variability. Overall, both RF and SMR methods explained more than 74% of the variance in biomass, with the most important Lidar variables being associated with vegetation structure and statistical measures of this structure (e.g., standard deviation of height was a strong predictor of biomass). Using our model results, we developed spatially-explicit Lidar estimates of total and shrub biomass across our study site in the Great Basin, U.S.A., for monitoring and planning in this imperiled ecosystem.

Effects of the bottom boundary condition in numerical investigations of dense water cascading on a slope

NASA Astrophysics Data System (ADS)

Berntsen, Jarle; Alendal, Guttorm; Avlesen, Helge; Thiem, Øyvind

2018-05-01

The flow of dense water along continental slopes is considered. There is a large literature on the topic based on observations and laboratory experiments. In addition, there are many analytical and numerical studies of dense water flows. In particular, there is a sequence of numerical investigations using the dynamics of overflow mixing and entrainment (DOME) setup. In these papers, the sensitivity of the solutions to numerical parameters such as grid size and numerical viscosity coefficients and to the choices of methods and models is investigated. In earlier DOME studies, three different bottom boundary conditions and a range of vertical grid sizes are applied. In other parts of the literature on numerical studies of oceanic gravity currents, there are statements that appear to contradict choices made on bottom boundary conditions in some of the DOME papers. In the present study, we therefore address the effects of the bottom boundary condition and vertical resolution in numerical investigations of dense water cascading on a slope. The main finding of the present paper is that it is feasible to capture the bottom Ekman layer dynamics adequately and cost efficiently by using a terrain-following model system using a quadratic drag law with a drag coefficient computed to give near-bottom velocity profiles in agreement with the logarithmic law of the wall. Many studies of dense water flows are performed with a quadratic bottom drag law and a constant drag coefficient. It is shown that when using this bottom boundary condition, Ekman drainage will not be adequately represented. In other studies of gravity flow, a no-slip bottom boundary condition is applied. With no-slip and a very fine resolution near the seabed, the solutions are essentially equal to the solutions obtained with a quadratic drag law and a drag coefficient computed to produce velocity profiles matching the logarithmic law of the wall. However, with coarser resolution near the seabed, there may be a substantial artificial blocking effect when using no-slip.

Running GCM physics and dynamics on different grids: Algorithm and tests

NASA Astrophysics Data System (ADS)

Molod, A.

2006-12-01

The major drawback in the use of sigma coordinates in atmospheric GCMs, namely the error in the pressure gradient term near sloping terrain, leaves the use of eta coordinates an important alternative. A central disadvantage of an eta coordinate, the inability to retain fine resolution in the vertical as the surface rises above sea level, is addressed here. An `alternate grid' technique is presented which allows the tendencies of state variables due to the physical parameterizations to be computed on a vertical grid (the `physics grid') which retains fine resolution near the surface, while the remaining terms in the equations of motion are computed using an eta coordinate (the `dynamics grid') with coarser vertical resolution. As a simple test of the technique a set of perpetual equinox experiments using a simplified lower boundary condition with no land and no topography were performed. The results show that for both low and high resolution alternate grid experiments, much of the benefit of increased vertical resolution for the near surface meridional wind (and mass streamfield) can be realized by enhancing the vertical resolution of the `physics grid' in the manner described here. In addition, approximately half of the increase in zonal jet strength seen with increased vertical resolution can be realized using the `alternate grid' technique. A pair of full GCM experiments with realistic lower boundary conditions and topography were also performed. It is concluded that the use of the `alternate grid' approach offers a promising way forward to alleviate a central problem associated with the use of the eta coordinate in atmospheric GCMs.

Lidar-based multinomial classification algorithms for tropical forest degradation status: Implications for biomass estimation

NASA Astrophysics Data System (ADS)

Duffy, P.; Keller, M.; Longo, M.; Morton, D. C.; dos-Santos, M. N.; Pinagé, E. R.

2017-12-01

There is an urgent need to quantify the effects of land use and land cover change on carbon stocks in tropical forests to support REDD+ policies and improve characterization of global carbon budgets. This need is underscored by the fact that the variability in forest biomass estimates from global forest carbon maps is artificially low relative to estimates generated from forest inventory and high-resolution airborne lidar data. Both deforestation and degradation processes (e.g. logging, fire, and fragmentation) affect carbon fluxes at varying spatial and temporal scales. While the spatial extent and impact of deforestation has been relatively well characterized, the quantification of degradation processes is still poorly constrained. In the Brazilian Amazon, the largest source of uncertainty in CO2 emissions estimates is data on changes in tropical forest carbon stocks through time, followed closely by incomplete information on the carbon losses from forest degradation. In this work, we present a method for classifying the degradation status of tropical forests using higher order moments (skewness and kurtosis) of lidar return distributions aggregated at grids with resolution ranging from 50 m to 250 m. Across multiple spatial resolutions, we quantify the strength of the functional relationship between the lidar returns and the classification based on historical time series of Landsat imagery. Our results show that the higher order moments of the lidar return distributions provide sufficient information to build multinomial models that accurately classify the landscape into intact, logged, and burned forests. Model fit improved with coarser spatial resolution with Kappa statistics of 0.70 at 50 m, and 0.77 at 250 m. In addition, multi-class AUC was estimated as 0.87 at 50 m, and 0.95 at 250 m. This classification provides important information regarding the applicability of the use of lidar data for regional monitoring of recent logging, as well as the trajectory of the carbon budget. Differentiating between the biomass changes associated with deforestation and degradation processes is critical for accurate accounting of disturbance impacts on carbon cycling within the Brazilian Amazon and global tropical forests.

Forest cover of North America in the 1970s mapped using Landsat MSS data

NASA Astrophysics Data System (ADS)

Feng, M.; Sexton, J. O.; Channan, S.; Townshend, J. R.

2015-12-01

The distribution and changes in Earth's forests impact hydrological, biogeochemical, and energy fluxes, as well as ecosystems' capacity to support biodiversity and human economies. Long-term records of forest cover are needed across a broad range of investigation, including climate and carbon-cycle modeling, hydrological studies, habitat analyzes, biological conservation, and land-use planning. Satellite-based observations enable mapping and monitoring of forests at ecologically and economically relevant resolutions and continental or even global extents. Following early forest-mapping efforts using coarser resolution remote sensing data such as the Advanced Very High Resolution Radiometer (AVHRR) and MODerate-resolution Imaging Spectroradiometer (MODIS), forests have been mapped regionally at < 100-m resolution using Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+). These "Landsat-class" sensors offer precise calibration, but they provide observations only over the past three decades—a relatively short period for delineating the long-term changes of forests. Starting in 1971, the Multispectral Scanner (MSS) was the first generation of sensors aboard the Landsat satellites. MSS thus provides a unique resource to extend observations by at least a decade longer in history than records based on Landsat TM and ETM+. Leveraging more recent Landsat-based forest-cover products developed by the Global Land Cover Facility (GLCF) as reference, we developed an automated approach to detect forests using MSS data by leveraging the multispectral and phenological characteristics of forests observed in MSS time-series. The forest-cover map is produced with layers representing the year of observation, detection of forest-cover change relative to 1990, and the uncertainty of forest-cover and -change layers. The approach has been implemented with open-source libraries to facilitate processing large volumes of Landsat MSS images on high-performance computing machines. As the first result of our global mapping effort, we present the forest cover for North America. More than 25,000 Landsat MSS scenes were processed to provide a 120-meter resolution forest cover for North America, which will be made publicly available on the GLCF website (http://www.landcover.org).

Scale Dependence of Cirrus Horizontal Heterogeneity Effects on TOA Measurements. Part I; MODIS Brightness Temperatures in the Thermal Infrared

NASA Technical Reports Server (NTRS)

Fauchez, Thomas; Platnick, Steven; Meyer, Kerry; Cornet, Celine; Szczap, Frederic; Varnai, Tamas

2017-01-01

This paper presents a study on the impact of cirrus cloud heterogeneities on MODIS simulated thermal infrared (TIR) brightness temperatures (BTs) at the top of the atmosphere (TOA) as a function of spatial resolution from 50 meters to 10 kilometers. A realistic 3-D (three-dimensional) cirrus field is generated by the 3DCLOUD model (average optical thickness of 1.4, cloudtop and base altitudes at 10 and 12 kilometers, respectively, consisting of aggregate column crystals of D (sub eff) equals 20 microns), and 3-D thermal infrared radiative transfer (RT) is simulated with the 3DMCPOL (3-D Monte Carlo Polarized) code. According to previous studies, differences between 3-D BT computed from a heterogenous pixel and 1-D (one-dimensional) RT computed from a homogeneous pixel are considered dependent at nadir on two effects: (i) the optical thickness horizontal heterogeneity leading to the plane-parallel homogeneous bias (PPHB); and the (ii) horizontal radiative transport (HRT) leading to the independent pixel approximation error (IPAE). A single but realistic cirrus case is simulated and, as expected, the PPHB mainly impacts the low-spatial resolution results (above approximately 250 meters), with averaged values of up to 5-7 K (thousand), while the IPAE mainly impacts the high-spatial resolution results (below approximately 250 meters) with average values of up to 1-2 K (thousand). A sensitivity study has been performed in order to extend these results to various cirrus optical thicknesses and heterogeneities by sampling the cirrus in several ranges of parameters. For four optical thickness classes and four optical heterogeneity classes, we have found that, for nadir observations, the spatial resolution at which the combination of PPHB and HRT effects is the smallest, falls between 100 and 250 meters. These spatial resolutions thus appear to be the best choice to retrieve cirrus optical properties with the smallest cloud heterogeneity-related total bias in the thermal infrared. For off-nadir observations, the average total effect is increased and the minimum is shifted to coarser spatial resolutions.

Sensitivities of Summertime Mesoscale Circulations in the Coastal Carolinas to Modifications of the Kain-Fritsch Cumulus Parameterization.

PubMed

Sims, Aaron P; Alapaty, Kiran; Raman, Sethu

2017-01-01

Two mesoscale circulations, the Sandhills circulation and the sea breeze, influence the initiation of deep convection over the Sandhills and the coast in the Carolinas during the summer months. The interaction of these two circulations causes additional convection in this coastal region. Accurate representation of mesoscale convection is difficult as numerical models have problems with the prediction of the timing, amount, and location of precipitation. To address this issue, the authors have incorporated modifications to the Kain-Fritsch (KF) convective parameterization scheme and evaluated these mesoscale interactions using a high-resolution numerical model. The modifications include changes to the subgrid-scale cloud formulation, the convective turnover time scale, and the formulation of the updraft entrainment rates. The use of a grid-scaling adjustment parameter modulates the impact of the KF scheme as a function of the horizontal grid spacing used in a simulation. Results indicate that the impact of this modified cumulus parameterization scheme is more effective on domains with coarser grid sizes. Other results include a decrease in surface and near-surface temperatures in areas of deep convection (due to the inclusion of the effects of subgrid-scale clouds on the radiation), improvement in the timing of convection, and an increase in the strength of deep convection.

The impact of wave number selection and spin up time when using spectral nudging for dynamical downscaling applications

NASA Astrophysics Data System (ADS)

Gómez, Breogán; Miguez-Macho, Gonzalo

2017-04-01

Nudging techniques are commonly used to constrain the evolution of numerical models to a reference dataset that is typically of a lower resolution. The nudged model retains some of the features of the reference field while incorporating its own dynamics to the solution. These characteristics have made nudging very popular in dynamic downscaling applications that cover from shot range, single case studies, to multi-decadal regional climate simulations. Recently, a variation of this approach called Spectral Nudging, has gained popularity for its ability to maintain the higher temporal and spatial variability of the model results, while forcing the large scales in the solution with a coarser resolution field. In this work, we focus on a not much explored aspect of this technique: the impact of selecting different cut-off wave numbers and spin-up times. We perform four-day long simulations with the WRF model, daily for three different one-month periods that include a free run and several Spectral Nudging experiments with cut-off wave numbers ranging from the smallest to the largest possible (full Grid Nudging). Results show that Spectral Nudging is very effective at imposing the selected scales onto the solution, while allowing the limited area model to incorporate finer scale features. The model error diminishes rapidly as the nudging expands over broader parts of the spectrum, but this decreasing trend ceases sharply at cut-off wave numbers equivalent to a length scale of about 1000 km, and the error magnitude changes minimally thereafter. This scale corresponds to the Rossby Radius of deformation, separating synoptic from convective scales in the flow. When nudging above this value is applied, a shifting of the synoptic patterns can occur in the solution, yielding large model errors. However, when selecting smaller scales, the fine scale contribution of the model is damped, thus making 1000 km the appropriate scale threshold to nudge in order to balance both effects. Finally, we note that longer spin-up times are needed for model errors to stabilize when using Spectral Nudging than with Grid Nudging. Our results suggest that this time is between 36 and 48 hours.

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model. 2; Aggregation

NASA Technical Reports Server (NTRS)

Schamschula, Marius; Crosson, William L.; Inguva, Ramarao; Yates, Thomas; Laymen, Charles A.; Caulfield, John

1998-01-01

This is a follow up on the preceding presentation by Crosson. The grid size for remote microwave measurements is much coarser than the hydrological model computational grids. To validate the hydrological models with measurements we propose mechanisms to aggregate the hydrological model outputs for soil moisture to allow comparison with measurements. Weighted neighborhood averaging methods are proposed to facilitate the comparison. We will also discuss such complications as misalignment, rotation and other distortions introduced by a generalized sensor image.

Can next-generation soil data products improve soil moisture modelling at the continental scale? An assessment using a new microclimate package for the R programming environment

NASA Astrophysics Data System (ADS)

Kearney, Michael R.; Maino, James L.

2018-06-01

Accurate models of soil moisture are vital for solving core problems in meteorology, hydrology, agriculture and ecology. The capacity for soil moisture modelling is growing rapidly with the development of high-resolution, continent-scale gridded weather and soil data together with advances in modelling methods. In particular, the GlobalSoilMap.net initiative represents next-generation, depth-specific gridded soil products that may substantially increase soil moisture modelling capacity. Here we present an implementation of Campbell's infiltration and redistribution model within the NicheMapR microclimate modelling package for the R environment, and use it to assess the predictive power provided by the GlobalSoilMap.net product Soil and Landscape Grid of Australia (SLGA, ∼100 m) as well as the coarser resolution global product SoilGrids (SG, ∼250 m). Predictions were tested in detail against 3 years of root-zone (3-75 cm) soil moisture observation data from 35 monitoring sites within the OzNet project in Australia, with additional tests of the finalised modelling approach against cosmic-ray neutron (CosmOz, 0-50 cm, 9 sites from 2011 to 2017) and satellite (ASCAT, 0-2 cm, continent-wide from 2007 to 2009) observations. The model was forced by daily 0.05° (∼5 km) gridded meteorological data. The NicheMapR system predicted soil moisture to within experimental error for all data sets. Using the SLGA or the SG soil database, the OzNet soil moisture could be predicted with a root mean square error (rmse) of ∼0.075 m3 m-3 and a correlation coefficient (r) of 0.65 consistently through the soil profile without any parameter tuning. Soil moisture predictions based on the SLGA and SG datasets were ≈ 17% closer to the observations than when using a chloropleth-derived soil data set (Digital Atlas of Australian Soils), with the greatest improvements occurring for deeper layers. The CosmOz observations were predicted with similar accuracy (r = 0.76 and rmse of ∼0.085 m3 m-3). Comparisons at the continental scale to 0-2 cm satellite data (ASCAT) showed that the SLGA/SG datasets increased model fit over simulations using the DAAS soil properties (r ∼ 0.63 &rmse 15% vs. r 0.48 &rmse 18%, respectively). Overall, our results demonstrate the advantages of using GlobalSoilMap.net products in combination with gridded weather data for modelling soil moisture at fine spatial and temporal resolution at the continental scale.

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

NASA Astrophysics Data System (ADS)

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

2010-09-01

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

Atmospheric Downscaling using Genetic Programming

NASA Astrophysics Data System (ADS)

Zerenner, Tanja; Venema, Victor; Simmer, Clemens

2013-04-01

Coupling models for the different components of the Soil-Vegetation-Atmosphere-System requires up-and downscaling procedures. Subject of our work is the downscaling scheme used to derive high resolution forcing data for land-surface and subsurface models from coarser atmospheric model output. The current downscaling scheme [Schomburg et. al. 2010, 2012] combines a bi-quadratic spline interpolation, deterministic rules and autoregressive noise. For the development of the scheme, training and validation data sets have been created by carrying out high-resolution runs of the atmospheric model. The deterministic rules in this scheme are partly based on known physical relations and partly determined by an automated search for linear relationships between the high resolution fields of the atmospheric model output and high resolution data on surface characteristics. Up to now deterministic rules are available for downscaling surface pressure and partially, depending on the prevailing weather conditions, for near surface temperature and radiation. Aim of our work is to improve those rules and to find deterministic rules for the remaining variables, which require downscaling, e.g. precipitation or near surface specifc humidity. To accomplish that, we broaden the search by allowing for interdependencies between different atmospheric parameters, non-linear relations, non-local and time-lagged relations. To cope with the vast number of possible solutions, we use genetic programming, a method from machine learning, which is based on the principles of natural evolution. We are currently working with GPLAB, a Genetic Programming toolbox for Matlab. At first we have tested the GP system to retrieve the known physical rule for downscaling surface pressure, i.e. the hydrostatic equation, from our training data. We have found this to be a simple task to the GP system. Furthermore we have improved accuracy and efficiency of the GP solution by implementing constant variation and optimization as genetic operators. Next we have worked on an improvement of the downscaling rule for the two-meter-temperature. We have added an if-function with four input arguments to the function set. Since this has shown to increase bloat we have additionally modified our fitness function by including penalty terms for both the size of the solutions and the number intron nodes, i.e program parts that are never evaluated. Starting from the known downscaling rule for the two-meter temperature, which linearly exploits the orography anomalies allowed or disallowed by a certain temperature gradient, our GP system has been able to find an improvement. The rule produced by the GP clearly shows a better performance concerning the reproduced small-scale variability.

Ocean Color Products Supporting the Assessment of Good Environmental Status: Development of a Spatial Distribution Model for the Seagrass Posidonia Oceanica (L.) Delille, 1813

NASA Astrophysics Data System (ADS)

Zucchetta, M.; Taji, M. A.; Mangin, A.; Pastres, R.

2015-12-01

Posidonia oceanica (L.) Delile, 1813 is a seagrass species endemic to the Mediterranean Sea, which is considered as one of the key habitats of the coastal areas. This species forms large meadows sensitive to several anthropogenic pressures, that can be regarded as indicators of environment quality in coastal environments and its distributional patterns should be take into account when evaluating the Environmental Status following the Ecosystem approach promoted by the Mediterranean Action Plan of UNEP and the EU Marine Strategy Framework Directive (2008/56/EC). The aim of this study was to develop a Species Distribution Model for P. oceanica, to be applied to the whole Mediterranean North African coast, in order to obtain an estimation of the potential distribution of this species in the region to be considered as an indicator for the assessment of good Environmental Status. As the study area is a data-poor zone with regard to seagrass distribution (i.e. only for some areas detailed distribution maps are available), the Species Distribution Model (SDM) was calibrated using high resolution data from 5 Mediterranean sites, located in Italy and Spain and validated using available data from the North African coast. Usually, when developing SDMs species occupancy data is available at coarser resolution than the information of environmental variables, and thus has to be downscaled at the appropriate grain to be coupled to the environmental conditions. Tackling the case of P. oceanica we had to face the opposite problem: the quality (in terms of resolution) of the information on seagrass distribution is generally very high compared to the environmental data available over large scale in marine domains (e.g. global bathymetry data). The high resolution application and the model transfer (from calibration areas to North African coast) was possible taking advantage of Ocean Color products: the probability of presence of the species in a given area was modelled using a binomial generalized linear model as a function of the bathymetry and some water characteristics mainly obtained from satellite data. Full resolution (c.a. 300m) Medium Resolution Imaging Spectrometer (MERIS) sensor imagery have been processed in order to extract a set of environmental variables to be coupled to seagrass distribution in the areas used to calibrate the model and for the whole North Africa coast (i.e. model application area). For the period 2003-2011 we processed data of: 1) the diffuse attenuation coefficient 2) coloured dissolved organic matter 3) Particle backscatter at 443nm; 4) Euphotic depth, estimated considering the coefficient of extinction of light; 5) Euphotic depth/ depth ratio, combining the estimation of euphotic depth with the bathymetry. Other variables have been resampled at MERIS full resolution, like data obtained from Moderate Resolution Imaging Spectroradiometer (MODIS; Sea Surface Temperature and Photosynthetically Available Radiation) or by model simulation (e.g. water salinity). The fitted model suggests that water transparency plays a major role, but also other variables, such as salinity and photosynthetically available radiation at surface, are important at larger spatial scales in explaining meadows distribution. The availability of high resolution time-series of input data allowed us to apply the validated model to the whole NA coast. Using model predictions to identify areas with suitable conditions for P. oceanica, it was possible to develop an indicator of potential habitat use and to define baseline reference conditions, necessary for the assessment of Good Environmental Status in Mediterranean coastal waters. This work shows how the Ocean and Land Colour Instrument (OLCI) within the Sentinel-3 mission can be exploited - thanks to the way opened by MERIS - to carry out the operational monitoring needed for the implementation of the UNEP MAP and EU MSFD Ecosystem Approach to the integrated management of land, water and living resources.

Environmental drivers of epibenthic megafauna on a deep temperate continental shelf: A multiscale approach

NASA Astrophysics Data System (ADS)

Lacharité, Myriam; Metaxas, Anna

2018-03-01

Evaluating the role of abiotic factors in influencing the distribution of deep-water (>75-100 m depth) epibenthic megafaunal communities at mid-to-high latitudes is needed to estimate effects of environmental change, and support marine spatial planning since these factors can be effectively mapped. Given the disparity in scales at which these factors operate, incorporating multiple spatial and temporal scales is necessary. In this study, we determined the relative importance of 3 groups of environmental drivers at different scales (sediment, geomorphology, and oceanography) on epibenthic megafauna on a deep temperate continental shelf in the eastern Gulf of Maine (northwest Atlantic). Twenty benthic photographic transects (range: 611-1021 m; total length surveyed: 18,902 m; 996 images; average of 50 ± 16 images per transect) were performed in July and August 2009 to assess the abundance, composition and diversity of these communities. Surficial geology was assessed using seafloor imagery processed with a novel approach based on computer vision. A bathymetric terrain model (horizontal resolution: 100 m) was used to derive bathymetric variability in the vicinity of transects (1.5, 5 km). Oceanography at the seafloor (temperature, salinity, current speed, current direction) over 10 years (1999-2008) was determined using empirical (World Ocean Database 2013) and modelled data (Finite-Volume Community Ocean Model; 45 vertical layers; horizontal resolution: 1.7-9.5 km). The relative influence of environmental drivers differed between community traits. Abundance was enhanced primarily by swift current speeds, while higher diversity was observed in coarser and more heterogeneous substrates. In both cases, the role of geomorphological features was secondary to these drivers. Environmental variables were poor predictors of change in community composition at the scale of the eastern Gulf of Maine. This study demonstrated the need for explicitly incorporating scales into habitat modelling studies in these regions, and targeting specific drivers for community traits of interest.

Further influence of the eastern boundary on the seasonal variability of the Atlantic Meridional Overturning Circulation at 26N

NASA Astrophysics Data System (ADS)

Baehr, Johanna; Schmidt, Christian

2016-04-01

The seasonal cycle of the Atlantic Meridional Overturning Circulation (AMOC) at 26.5 N has been shown to arise predominantly from sub-surface density variations at the Eastern boundary. Here, we suggest that these sub-surface density variations have their origin in the seasonal variability of the Canary Current system, in particular the Poleward Undercurrent (PUC). We use a high-resolution ocean model (STORM) for which we show that the seasonal variability resembles observations for both sub-surface density variability and meridional transports. In particular, the STORM model simulation density variations at the eastern boundary show seasonal variations reaching down to well over 1000m, a pattern that most model simulations systematically underestimate. We find that positive wind stress curl anomalies in late summer and already within one degree off the eastern boundary result -through water column stretching- in strong transport anomlies in PUC in fall, coherent down to 1000m depth. Simultaneously with a westward propagation of these transport anomalies, we find in winter a weak PUC between 200 m and 500m, and southward transports between 600m and 1300m. This variability is in agreement with the observationally-based suggestion of a seasonal reversal of the meridional transports at intermediate depths. Our findings extend earlier studies which suggested that the seasonal variability at of the meridional transports across 26N is created by changes in the basin-wide thermocline through wind-driven upwelling at the eastern boundary analyzing wind stress curl anomalies 2 degrees off the eastern boundary. Our results suggest that the investigation of AMOC variability and particular its seasonal cycle modulations require the analysis of boundary wind stress curl and the upper ocean transports within 1 degree off the eastern boundary. These findings also implicate that without high-resolution coverage of the eastern boundary, coarser model simulation might not fully represent the AMOC's seasonal variability.

Computational Simulation of Breast Compression Based on Segmented Breast and Fibroglandular Tissues on Magnetic Resonance Images

PubMed Central

Shih, Tzu-Ching; Chen, Jeon-Hor; Liu, Dongxu; Nie, Ke; Sun, Lizhi; Lin, Muqing; Chang, Daniel; Nalcioglu, Orhan; Su, Min-Ying

2010-01-01

This study presents a finite element based computational model to simulate the three-dimensional deformation of the breast and the fibroglandular tissues under compression. The simulation was based on 3D MR images of the breast, and the craniocaudal and mediolateral oblique compression as used in mammography was applied. The geometry of whole breast and the segmented fibroglandular tissues within the breast were reconstructed using triangular meshes by using the Avizo® 6.0 software package. Due to the large deformation in breast compression, a finite element model was used to simulate the non-linear elastic tissue deformation under compression, using the MSC.Marc® software package. The model was tested in 4 cases. The results showed a higher displacement along the compression direction compared to the other two directions. The compressed breast thickness in these 4 cases at 60% compression ratio was in the range of 5-7 cm, which is the typical range of thickness in mammography. The projection of the fibroglandular tissue mesh at 60% compression ratio was compared to the corresponding mammograms of two women, and they demonstrated spatially matched distributions. However, since the compression was based on MRI, which has much coarser spatial resolution than the in-plane resolution of mammography, this method is unlikely to generate a synthetic mammogram close to the clinical quality. Whether this model may be used to understand the technical factors that may impact the variations in breast density measurements needs further investigation. Since this method can be applied to simulate compression of the breast at different views and different compression levels, another possible application is to provide a tool for comparing breast images acquired using different imaging modalities – such as MRI, mammography, whole breast ultrasound, and molecular imaging – that are performed using different body positions and different compression conditions. PMID:20601773

Computational simulation of breast compression based on segmented breast and fibroglandular tissues on magnetic resonance images.

PubMed

Shih, Tzu-Ching; Chen, Jeon-Hor; Liu, Dongxu; Nie, Ke; Sun, Lizhi; Lin, Muqing; Chang, Daniel; Nalcioglu, Orhan; Su, Min-Ying

2010-07-21

This study presents a finite element-based computational model to simulate the three-dimensional deformation of a breast and fibroglandular tissues under compression. The simulation was based on 3D MR images of the breast, and craniocaudal and mediolateral oblique compression, as used in mammography, was applied. The geometry of the whole breast and the segmented fibroglandular tissues within the breast were reconstructed using triangular meshes by using the Avizo 6.0 software package. Due to the large deformation in breast compression, a finite element model was used to simulate the nonlinear elastic tissue deformation under compression, using the MSC.Marc software package. The model was tested in four cases. The results showed a higher displacement along the compression direction compared to the other two directions. The compressed breast thickness in these four cases at a compression ratio of 60% was in the range of 5-7 cm, which is a typical range of thickness in mammography. The projection of the fibroglandular tissue mesh at a compression ratio of 60% was compared to the corresponding mammograms of two women, and they demonstrated spatially matched distributions. However, since the compression was based on magnetic resonance imaging (MRI), which has much coarser spatial resolution than the in-plane resolution of mammography, this method is unlikely to generate a synthetic mammogram close to the clinical quality. Whether this model may be used to understand the technical factors that may impact the variations in breast density needs further investigation. Since this method can be applied to simulate compression of the breast at different views and different compression levels, another possible application is to provide a tool for comparing breast images acquired using different imaging modalities--such as MRI, mammography, whole breast ultrasound and molecular imaging--that are performed using different body positions and under different compression conditions.

Applying Lidar and High-Resolution Multispectral Imagery for Improved Quantification and Mapping of Tundra Vegetation Structure and Distribution in the Alaskan Arctic

NASA Astrophysics Data System (ADS)

Greaves, Heather E.

Climate change is disproportionately affecting high northern latitudes, and the extreme temperatures, remoteness, and sheer size of the Arctic tundra biome have always posed challenges that make application of remote sensing technology especially appropriate. Advances in high-resolution remote sensing continually improve our ability to measure characteristics of tundra vegetation communities, which have been difficult to characterize previously due to their low stature and their distribution in complex, heterogeneous patches across large landscapes. In this work, I apply terrestrial lidar, airborne lidar, and high-resolution airborne multispectral imagery to estimate tundra vegetation characteristics for a research area near Toolik Lake, Alaska. Initially, I explored methods for estimating shrub biomass from terrestrial lidar point clouds, finding that a canopy-volume based algorithm performed best. Although shrub biomass estimates derived from airborne lidar data were less accurate than those from terrestrial lidar data, algorithm parameters used to derive biomass estimates were similar for both datasets. Additionally, I found that airborne lidar-based shrub biomass estimates were just as accurate whether calibrated against terrestrial lidar data or harvested shrub biomass--suggesting that terrestrial lidar potentially could replace destructive biomass harvest. Along with smoothed Normalized Differenced Vegetation Index (NDVI) derived from airborne imagery, airborne lidar-derived canopy volume was an important predictor in a Random Forest model trained to estimate shrub biomass across the 12.5 km2 covered by our lidar and imagery data. The resulting 0.80 m resolution shrub biomass maps should provide important benchmarks for change detection in the Toolik area, especially as deciduous shrubs continue to expand in tundra regions. Finally, I applied 33 lidar- and imagery-derived predictor layers in a validated Random Forest modeling approach to map vegetation community distribution at 20 cm resolution across the data collection area, creating maps that will enable validation of coarser maps, as well as study of fine-scale ecological processes in the area. These projects have pushed the limits of what can be accomplished for vegetation mapping using airborne remote sensing in a challenging but important region; it is my hope that the methods explored here will illuminate potential paths forward as landscapes and technologies inevitably continue to change.

Mapping and detecting bark beetle-caused tree mortality in the western United States

NASA Astrophysics Data System (ADS)

Meddens, Arjan J. H.

Recently, insect outbreaks across North America have dramatically increased and the forest area affected by bark beetles is similar to that affected by fire. Remote sensing offers the potential to detect insect outbreaks with high accuracy. Chapter one involved detection of insect-caused tree mortality on the tree level for a 90km2 area in northcentral Colorado. Classes of interest included green trees, multiple stages of post-insect attack tree mortality including dead trees with red needles ("red-attack") and dead trees without needles ("gray-attack"), and non-forest. The results illustrated that classification of an image with a spatial resolution similar to the area of a tree crown outperformed that from finer and coarser resolution imagery for mapping tree mortality and non-forest classes. I also demonstrated that multispectral imagery could be used to separate multiple postoutbreak attack stages (i.e., red-attack and gray-attack) from other classes in the image. In Chapter 2, I compared and improved methods for detecting bark beetle-caused tree mortality using medium-resolution satellite data. I found that overall classification accuracy was similar between single-date and multi-date classification methods. I developed regression models to predict percent red attack within a 30-m grid cell and these models explained >75% of the variance using three Landsat spectral explanatory variables. Results of the final product showed that approximately 24% of the forest within the Landsat scene was comprised of tree mortality caused by bark beetles. In Chapter 3, I developed a gridded data set with 1-km2 resolution using aerial survey data and improved estimates of tree mortality across the western US and British Columbia. In the US, I also produced an upper estimate by forcing the mortality area to match that from high-resolution imagery in Idaho, Colorado, and New Mexico. Cumulative mortality area from all bark beetles was 5.46 Mha in British Columbia in 2001-2010 and 0.47-5.37 Mha (lower and upper estimate) in the western conterminous US during 1997-2010. Improved methods for detection and mapping of insect outbreak areas will lead to improved assessments of the effects of these forest disturbances on the economy, carbon cycle (and feedback to climate change), fuel loads, hydrology and forest ecology.

The added value of stochastic spatial disaggregation for short-term rainfall forecasts currently available in Canada

NASA Astrophysics Data System (ADS)

Gagnon, Patrick; Rousseau, Alain N.; Charron, Dominique; Fortin, Vincent; Audet, René

2017-11-01

Several businesses and industries rely on rainfall forecasts to support their day-to-day operations. To deal with the uncertainty associated with rainfall forecast, some meteorological organisations have developed products, such as ensemble forecasts. However, due to the intensive computational requirements of ensemble forecasts, the spatial resolution remains coarse. For example, Environment and Climate Change Canada's (ECCC) Global Ensemble Prediction System (GEPS) data is freely available on a 1-degree grid (about 100 km), while those of the so-called High Resolution Deterministic Prediction System (HRDPS) are available on a 2.5-km grid (about 40 times finer). Potential users are then left with the option of using either a high-resolution rainfall forecast without uncertainty estimation and/or an ensemble with a spectrum of plausible rainfall values, but at a coarser spatial scale. The objective of this study was to evaluate the added value of coupling the Gibbs Sampling Disaggregation Model (GSDM) with ECCC products to provide accurate, precise and consistent rainfall estimates at a fine spatial resolution (10-km) within a forecast framework (6-h). For 30, 6-h, rainfall events occurring within a 40,000-km2 area (Québec, Canada), results show that, using 100-km aggregated reference rainfall depths as input, statistics of the rainfall fields generated by GSDM were close to those of the 10-km reference field. However, in forecast mode, GSDM outcomes inherit of the ECCC forecast biases, resulting in a poor performance when GEPS data were used as input, mainly due to the inherent rainfall depth distribution of the latter product. Better performance was achieved when the Regional Deterministic Prediction System (RDPS), available on a 10-km grid and aggregated at 100-km, was used as input to GSDM. Nevertheless, most of the analyzed ensemble forecasts were weakly consistent. Some areas of improvement are identified herein.

The impact of soil moisture extremes and their spatiotemporal variability on Zambian maize yields

NASA Astrophysics Data System (ADS)

Zhao, Y.; Estes, L. D.; Vergopolan, N.

2017-12-01

Food security in sub-Saharan Africa is highly sensitive to climate variability. While it is well understood that extreme heat has substantial negative impacts on crop yield, the impacts of precipitation extremes, particularly over large spatial extents, are harder to quantify. There are three primary reasons for this difficulty, which are (1) lack of high quality, high resolution precipitation data, (2) rainfall data provide incomplete information on plant water availability, the variable that most directly affects crop performance, and (3) the type of rainfall extreme that most affects crop yields varies throughout the crop development stage. With respect to the first reason, the spatial and temporal variation of precipitation is much greater than that of temperature, yet the spatial resolution of rainfall data is typically even coarser than it is for temperature, particularly within Africa. Even if there were high-resolution rainfall data, the amount of water available to crops also depends on other physical factors that affect evapotranspiration, which are strongly influenced by heterogeneity in the land surface related to topography, soil properties, and land cover. In this context, soil moisture provides a better measure of crop water availability than rainfall. Furthermore, soil moisture has significantly different influences on crop yield depending on the crop's growth stage. The goal of this study is to understand how the spatiotemporal scales of soil moisture extremes interact with crops, more specifically, the timing and the spatial scales of extreme events like droughts and flooding. In this study, we simulate daily-1km soil moisture using HydroBlocks - a physically based land surface model - and compare it with precipitation and remote sensing derived maize yields between 2000 and 2016 in Zambia. We use a novel combination of the SCYM (scalable satellite-based yield mapper) method with DSSAT crop model, which is a mechanistic model responsive to water stress. Understanding the relationships between soil moisture spatiotemporal variability and yields can help to improve agricultural drought risk assessment and seasonal crop yield forecasting as well as early season warning of potential famines.

Detecting Soil Moisture Related Impacts on Gross Primary Productivity using the MODIS-based Photochemical Reflectance Index

NASA Astrophysics Data System (ADS)

He, M.; Kimball, J. S.; Running, S. W.; Ballantyne, A.; Guan, K.; Huemmrich, K. F.

2016-12-01

Satellite remote sensing provides continuous observations of vegetation properties that can be used to estimate ecosystem gross primary production (GPP). The Photochemical Reflectance Index (PRI) has been shown to be sensitive to photosynthetic light use efficiency (LUE), GPP and canopy water-stress. The NASA EOS MODIS (Moderate Resolution Imaging Spectroradiometer) sensor provides potential PRI estimation globally at daily time step and 1-km spatial resolution for more than 10 years. Here, we use the MODIS based PRI with eddy covariance CO2 flux measurements and meteorological observations from 20 tower sites representing 5 major plant functional types (PFT) within the continental USA (CONUS) to assess GPP sensitivity to seasonal water supply variability. The sPRI (scaled PRI) derived using MODIS band 13 as a reference band (sPRI13) generally shows higher correspondence with tower GPP observations than other potential MODIS reference bands (MODIS band 1, 4, 10 and 12). The sPRI13 was used to represent soil moisture related water supply constraints to LUE within a terrestrial carbon flux model to estimate GPP (GPPPRI). The GPPPRI calculations show generally strong relationships with tower GPP observations (0.457 ≤ R2 ≤ 0.818), except for lower GPPPRI performance over evergreen needleleaf forest (ENF) sites. A regional model sensitivity analysis using the sPRI13 as a proxy for soil moisture related water supply limits indicated that water restrictions limit GPP over more than 21% of the CONUS domain, particularly in northwest and southwest CONUS subregions, and drier climate areas where atmospheric moisture deficits (VPD) alone are insufficient to represent both atmosphere demand and soil water supply controls affecting productivity. Our results indicate strong potential of the MODIS sPRI13 to represent GPP sensitivity to seasonal soil moisture related water supply variability, with enhanced (1-km resolution) delineation of these processes closer to the scale of in situ tower observations, providing an effective tool to characterize sub-grid spatial heterogeneity in soil moisture related water supply controls that inform coarser scale observations and estimates determined from other satellite observations and global carbon, and climate models.

Impact of land surface conditions on the predictability of hydrologic processes and mountain-valley circulations in the North American Monsoon region

NASA Astrophysics Data System (ADS)

Xiang, T.; Vivoni, E. R.; Gochis, D. J.; Mascaro, G.

2015-12-01

Heterogeneous land surface conditions are essential components of land-atmosphere interactions in regions of complex terrain and have the potential to affect convective precipitation formation. Yet, due to their high complexity, hydrologic processes over mountainous regions are not well understood, and are usually parameterized in simple ways within coupled land-atmosphere modeling frameworks. With the improving model physics and spatial resolution of numerical weather prediction models, there is an urgent need to understand how land surface processes affect local and regional meteorological processes. In the North American Monsoon (NAM) region, the summer rainy season is accompanied by a dramatic greening of mountain ecosystems that adds spatiotemporal variability in vegetation which is anticipated to impact the conditions leading to convection, mountain-valley circulations and mesoscale organization. In this study, we present results from a detailed analysis of a high-resolution (1 km) land surface model, Noah-MP, in a large, mountainous watershed of the NAM region - the Rio Sonora (21,264 km2) in Mexico. In addition to capturing the spatial variations in terrain and soil distributions, recently-developed features in Noah-MP allow the model to read time-varying vegetation parameters derived from remotely-sensed vegetation indices; however, this new implementation has not been fully evaluated. Therefore, we assess the simulated spatiotemporal fields of soil moisture, surface temperature and surface energy fluxes through comparisons to remote sensing products and results from coarser land surface models obtained from the North American Land Data Assimilation System. We focus attention on the impact of vegetation changes along different elevation bands on the diurnal cycle of surface energy fluxes to provide a baseline for future analyses of mountain-valley circulations using a coupled land-atmosphere modeling system. Our study also compares limited streamflow observations in the large watershed to simulations using the terrain and channel routing when Noah-MP is run within the WRF-Hydro modeling framework, with the goals of validating the rainfall-runoff partitioning and translating the spatiotemporal mountain processes into improvements in streamflow predictions.

Numerical modeling of landslide-generated tsunami using adaptive unstructured meshes

NASA Astrophysics Data System (ADS)

Wilson, Cian; Collins, Gareth; Desousa Costa, Patrick; Piggott, Matthew

2010-05-01

Landslides impacting into or occurring under water generate waves, which can have devastating environmental consequences. Depending on the characteristics of the landslide the waves can have significant amplitude and potentially propagate over large distances. Linear models of classical earthquake-generated tsunamis cannot reproduce the highly nonlinear generation mechanisms required to accurately predict the consequences of landslide-generated tsunamis. Also, laboratory-scale experimental investigation is limited to simple geometries and short time-scales before wave reflections contaminate the data. Computational fluid dynamics models based on the nonlinear Navier-Stokes equations can simulate landslide-tsunami generation at realistic scales. However, traditional chessboard-like structured meshes introduce superfluous resolution and hence the computing power required for such a simulation can be prohibitively high, especially in three dimensions. Unstructured meshes allow the grid spacing to vary rapidly from high resolution in the vicinity of small scale features to much coarser, lower resolution in other areas. Combining this variable resolution with dynamic mesh adaptivity allows such high resolution zones to follow features like the interface between the landslide and the water whilst minimising the computational costs. Unstructured meshes are also better suited to representing complex geometries and bathymetries allowing more realistic domains to be simulated. Modelling multiple materials, like water, air and a landslide, on an unstructured adaptive mesh poses significant numerical challenges. Novel methods of interface preservation must be considered and coupled to a flow model in such a way that ensures conservation of the different materials. Furthermore this conservation property must be maintained during successive stages of mesh optimisation and interpolation. In this paper we validate a new multi-material adaptive unstructured fluid dynamics model against the well-known Lituya Bay landslide-generated wave experiment and case study [1]. In addition, we explore the effect of physical parameters, such as the shape, velocity and viscosity of the landslide, on wave amplitude and run-up, to quantify their influence on the landslide-tsunami hazard. As well as reproducing the experimental results, the model is shown to have excellent conservation and bounding properties. It also requires fewer nodes than an equivalent resolution fixed mesh simulation, therefore minimising at least one aspect of the computational cost. These computational savings are directly transferable to higher dimensions and some initial three dimensional results are also presented. These reproduce the experiments of DiRisio et al. [2], where an 80cm long landslide analogue was released from the side of an 8.9m diameter conical island in a 50 × 30m tank of water. The resulting impact between the landslide and the water generated waves with an amplitude of 1cm at wave gauges around the island. The range of scales that must be considered in any attempt to numerically reproduce this experiment makes it an ideal case study for our multi-material adaptive unstructured fluid dynamics model. [1] FRITZ, H. M., MOHAMMED, F., & YOO, J. 2009. Lituya Bay Landslide Impact Generated Mega-Tsunami 50th Anniversary. Pure and Applied Geophysics, 166(1), 153-175. [2] DIRISIO, M., DEGIROLAMO, P., BELLOTTI, G., PANIZZO, A., ARISTODEMO, F.,

Mapping fractional woody cover in semi-arid savannahs using multi-seasonal composites from Landsat data

NASA Astrophysics Data System (ADS)

Higginbottom, Thomas P.; Symeonakis, Elias; Meyer, Hanna; van der Linden, Sebastian

2018-05-01

Increasing attention is being directed at mapping the fractional woody cover of savannahs using Earth-observation data. In this study, we test the utility of Landsat TM/ ETM-based spectral-temporal variability metrics for mapping regional-scale woody cover in the Limpopo Province of South Africa, for 2010. We employ a machine learning framework to compare the accuracies of Random Forest models derived using metrics calculated from different seasons. We compare these results to those from fused Landsat-PALSAR data to establish if seasonal metrics can compensate for structural information from the PALSAR signal. Furthermore, we test the applicability of a statistical variable selection method, the recursive feature elimination (RFE), in the automation of the model building process in order to reduce model complexity and processing time. All of our tests were repeated at four scales (30, 60, 90, and 120 m-pixels) to investigate the role of spatial resolution on modelled accuracies. Our results show that multi-seasonal composites combining imagery from both the dry and wet seasons produced the highest accuracies (R2 = 0.77, RMSE = 9.4, at the 120 m scale). When using a single season of observations, dry season imagery performed best (R2 = 0.74, RMSE = 9.9, at the 120 m resolution). Combining Landsat and radar imagery was only marginally beneficial, offering a mean relative improvement of 1% in accuracy at the 120 m scale. However, this improvement was concentrated in areas with lower densities of woody coverage (<30%), which are areas of concern for environmental monitoring. At finer spatial resolutions, the inclusion of SAR data actually reduced accuracies. Overall, the RFE was able to produce the most accurate model (R2 = 0.8, RMSE = 8.9, at the 120 m pixel scale). For mapping savannah woody cover at the 30 m pixel scale, we suggest that monitoring methodologies continue to exploit the Landsat archive, but should aim to use multi-seasonal derived information. When the coarser 120 m pixel scale is adequate, integration of Landsat and SAR data should be considered, especially in areas with lower woody cover densities. The use of multiple seasonal compositing periods offers promise for large-area mapping of savannahs, even in regions with a limited historical Landsat coverage.

Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia.

PubMed

Dorji, Passang; Fearns, Peter

2017-01-01

The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor's radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit.

Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia

PubMed Central

Fearns, Peter

2017-01-01

The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor’s radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit. PMID:28380059

Pathways of geomorphic evolution of sandstone escarpments in the Góry Stołowe tableland (SW Poland) - Insights from LiDAR-based high-resolution DEM

NASA Astrophysics Data System (ADS)

Migoń, Piotr; Kasprzak, Marek

2016-05-01

The tableland of the Stołowe Mountains (SW Poland), with its prominent mesas and sandstone-capped escarpments, belongs to the most spectacular geomorphic landscapes of Central Europe. While the gross morphological features of the area have long been recognized, the evolutionary pathways of densely forested and poorly accessible escarpment slopes remained poorly understood. In this paper we use LiDAR data to shed a new light on landform inventories within the escarpments, their spatial patterns and, using process-from-form reasoning, on the longer-term evolution of the escarpments. Four sites, two on each major escarpment, have been subject to detailed analysis which involved examination of shaded relief, slope, plan and profile curvature and topographic wetness index. In each case, the 1 × 1 m model was used, while for the most complex site at Mt. Szczeliniec Wielki the results were compared with the 5 × 5 m model to check the impact of model resolution on geomorphic interpretation. Despite some loss of information involved in model re-interpolation to the coarser scale, the main features of escarpment morphology could still be recognized. On the other hand, automatic landform classification based on the calculation of Topographic Position Index from the 10 × 10 m model and performed for the entire tableland failed to reveal differences between various sections of the escarpments, detectable on finer models. The analysis of spatial patterns of minor landforms within the escarpments, identified on LiDAR-derived models shows that no single pathway of escarpment evolution exists. Both the upper slopes (in sandstone caprock) and the mid-slopes (in weaker rocks) show signs of instability and these are not necessarily coupled. Large-scale caprock failures do occur but seem rare and localized. Sandstone free faces are rather subject to continuous slow retreat by detachment of individual joint-bound blocks. Another zone of instability occurs well below the caprock and the dominant processes are shallow landslips initiated within weak, deformable rocks.

Synergistic Use of SMOS Measurements with SMAP Derived and In-situ Data over Valencia Anchor Station by Using Downscaling Technique

NASA Astrophysics Data System (ADS)

Ansari Amoli, Abdolreza; Lopez-Baeza, Ernesto; Mahmoudi, Ali; Mahmoodi, Ali

2016-07-01

Synergistic Use of SMOS Measurements with SMAP Derived and In-situ Data over the Valencia Anchor Station by Using a Downscaling Technique Ansari Amoli, A.(1),Mahmoodi, A.(2) and Lopez-Baeza, E.(3) (1) Department of Earth Physics and Thermodynamics, University of Valencia, Spain (2) Centre d'Etudes Spatiales de la BIOsphère (CESBIO), France (3) Department of Earth Physics and Thermodynamics, University of Valencia, Spain Soil moisture products from active sensors are not operationally available. Passive remote sensors return more accurate estimates, but their resolution is much coarser. One solution to overcome this problem is the synergy between radar and radiometric data by using disaggregation (downscaling) techniques. Few studies have been conducted to merge high resolution radar and coarse resolution radiometer measurements in order to obtain an intermediate resolution product. In this paper we present an algorithm using combined available SMAP (Soil Moisture Active and Passive) radar and SMOS (Soil Moisture and Ocean Salinity) radiometer measurements to estimate surface soil moisture over the Valencia Anchor Station (VAS), Valencia, Spain. The goal is to combine the respective attributes of the radar and radiometer observations to estimate soil moisture at a resolution of 3 km. The algorithm disaggregates the coarse resolution SMOS (15 km) radiometer brightness temperature product based on the spatial variation of the high resolution SMAP (3 km) radar backscatter. The disaggregation of the radiometer brightness temperature uses the radar backscatter spatial patterns within the radiometer footprint that are inferred from the radar measurements. For this reason the radar measurements within the radiometer footprint are scaled by parameters that are derived from the temporal fluctuations in the radar and radiometer measurements.

AIRS Subpixel Cloud Characterization Using MODIS Cloud Products.

NASA Astrophysics Data System (ADS)

Li, Jun; Menzel, W. Paul; Sun, Fengying; Schmit, Timothy J.; Gurka, James

2004-08-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS's) Aqua satellite enable improved global monitoring of the distribution of clouds. MODIS is able to provide, at high spatial resolution (1 5 km), a cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), and cloud optical thickness (COT). AIRS is able to provide CTP, ECA, CPS, and COT at coarser spatial resolution (13.5 km at nadir) but with much better accuracy using its high-spectral-resolution measurements. The combined MODIS AIRS system offers the opportunity for improved cloud products over those possible from either system alone. The key steps for synergistic use of imager and sounder radiance measurements are 1) collocation in space and time and 2) imager cloud amount, type, and phase determination within the sounder pixel. The MODIS and AIRS measurements from the EOS Aqua satellite provide the opportunity to study the synergistic use of advanced imager and sounder measurements. As the first step, the MODIS classification procedure is applied to identify various surface and cloud types within an AIRS footprint. Cloud-layer information (lower, midlevel, or high clouds) and phase information (water, ice, or mixed-phase clouds) within the AIRS footprint are sorted and characterized using MODIS 1-km-spatial-resolution data. The combined MODIS and AIRS data for various scenes are analyzed to study the utility of the synergistic use of high-spatial-resolution imager products and high-spectral-resolution sounder radiance measurements. There is relevance to the optimal use of data from the Advanced Baseline Imager (ABI) and Hyperspectral Environmental Suite (HES) systems, which are to fly on the Geostationary Operational Environmental Satellite (GOES)-R.

Aerial photography flight quality assessment with GPS/INS and DEM data

NASA Astrophysics Data System (ADS)

Zhao, Haitao; Zhang, Bing; Shang, Jiali; Liu, Jiangui; Li, Dong; Chen, Yanyan; Zuo, Zhengli; Chen, Zhengchao

2018-01-01

The flight altitude, ground coverage, photo overlap, and other acquisition specifications of an aerial photography flight mission directly affect the quality and accuracy of the subsequent mapping tasks. To ensure smooth post-flight data processing and fulfill the pre-defined mapping accuracy, flight quality assessments should be carried out in time. This paper presents a novel and rigorous approach for flight quality evaluation of frame cameras with GPS/INS data and DEM, using geometric calculation rather than image analysis as in the conventional methods. This new approach is based mainly on the collinearity equations, in which the accuracy of a set of flight quality indicators is derived through a rigorous error propagation model and validated with scenario data. Theoretical analysis and practical flight test of an aerial photography mission using an UltraCamXp camera showed that the calculated photo overlap is accurate enough for flight quality assessment of 5 cm ground sample distance image, using the SRTMGL3 DEM and the POSAV510 GPS/INS data. An even better overlap accuracy could be achieved for coarser-resolution aerial photography. With this new approach, the flight quality evaluation can be conducted on site right after landing, providing accurate and timely information for decision making.

Comparison and validation of gridded precipitation datasets for Spain

NASA Astrophysics Data System (ADS)

Quintana-Seguí, Pere; Turco, Marco; Míguez-Macho, Gonzalo

2016-04-01

In this study, two gridded precipitation datasets are compared and validated in Spain: the recently developed SAFRAN dataset and the Spain02 dataset. These are validated using rain gauges and they are also compared to the low resolution ERA-Interim reanalysis. The SAFRAN precipitation dataset has been recently produced, using the SAFRAN meteorological analysis, which is extensively used in France (Durand et al. 1993, 1999; Quintana-Seguí et al. 2008; Vidal et al., 2010) and which has recently been applied to Spain (Quintana-Seguí et al., 2015). SAFRAN uses an optimal interpolation (OI) algorithm and uses all available rain gauges from the Spanish State Meteorological Agency (Agencia Estatal de Meteorología, AEMET). The product has a spatial resolution of 5 km and it spans from September 1979 to August 2014. This dataset has been produced mainly to be used in large scale hydrological applications. Spain02 (Herrera et al. 2012, 2015) is another high quality precipitation dataset for Spain based on a dense network of quality-controlled stations and it has different versions at different resolutions. In this study we used the version with a resolution of 0.11°. The product spans from 1971 to 2010. Spain02 is well tested and widely used, mainly, but not exclusively, for RCM model validation and statistical downscliang. ERA-Interim is a well known global reanalysis with a spatial resolution of ˜79 km. It has been included in the comparison because it is a widely used product for continental and global scale studies and also in smaller scale studies in data poor countries. Thus, its comparison with higher resolution products of a data rich country, such as Spain, allows us to quantify the errors made when using such datasets for national scale studies, in line with some of the objectives of the EU-FP7 eartH2Observe project. The comparison shows that SAFRAN and Spain02 perform similarly, even though their underlying principles are different. Both products are largely better than ERA-Interim, which has a much coarser representation of the relief, which is crucial for precipitation. These results are a contribution to the Spanish Case Study of the eartH2Observe project, which is focused on the simulation of drought processes in Spain using Land-Surface Models (LSM). This study will also be helpful in the Spanish MARCO project, which aims at improving the ability of RCMs to simulate hydrometeorological extremes.

Integrating biodiversity distribution knowledge: toward a global map of life.

PubMed

Jetz, Walter; McPherson, Jana M; Guralnick, Robert P

2012-03-01

Global knowledge about the spatial distribution of species is orders of magnitude coarser in resolution than other geographically-structured environmental datasets such as topography or land cover. Yet such knowledge is crucial in deciphering ecological and evolutionary processes and in managing global change. In this review, we propose a conceptual and cyber-infrastructure framework for refining species distributional knowledge that is novel in its ability to mobilize and integrate diverse types of data such that their collective strengths overcome individual weaknesses. The ultimate aim is a public, online, quality-vetted 'Map of Life' that for every species integrates and visualizes available distributional knowledge, while also facilitating user feedback and dynamic biodiversity analyses. First milestones toward such an infrastructure have now been implemented. Copyright © 2011 Elsevier Ltd. All rights reserved.

Effects of Nonsphericity on the Behavior of Lorenz-Mie Resonances in Scattering Characteristics of Liquid-Cloud Droplets

NASA Technical Reports Server (NTRS)

Dlugach, Janna M.; Mishchenko, Michael I.

2014-01-01

By using the results of highly accurate T-matrix computations for randomly oriented oblate and prolate spheroids and Chebyshev particles with varying degrees of asphericity, we analyze the effects of a deviation of water-droplet shapes from that of a perfect sphere on the behavior of Lorenz-Mie morphology-dependent resonances of various widths. We demonstrate that the positions and profiles of the resonances can change significantly with increasing asphericity. The absolute degree of asphericity required to suppress a Lorenz-Mie resonance is approximately proportional to the resonance width. Our results imply that numerical averaging of scattering characteristics of real cloud droplets over sizes may rely on a significantly coarser size-parameter resolution than that required for ideal, perfectly spherical particles.

The use of thematic mapper data for land cover discrimination: Preliminary results from the UK SATMaP programme

NASA Technical Reports Server (NTRS)

Jackson, M. J.; Baker, J. R.; Townshend, J. R. G.; Gayler, J. E.; Hardy, J. R.

1983-01-01

The principal objectives of the UK SATMaP program are to determine thematic mapper (TM) performance with particular reference to spatial resolution properties and geometric characteristics of the data. So far, analysis is restricted to images from the U.S. and concentrates on spectra and radiometric properties. The results indicate that the data are inherently three dimensional compared with the two dimensional character of MSS data. Preliminary classification results indicate the importance of the near infrared band (TM 4), at least one middle infrared band (TM 5 or TM 6) and at least one of the visible bands (preferably either TM 3 or TM 1). The thermal infrared also appears to have discriminatory ability despite its coarser spatial resolution. For band 4 the forward and reverse scans show somewhat different spectral responses in one scene but this effect is absent in the other analyzed. From examination of the histograms it would appear that the full 8-bit quantization is not being effectively utilized for all the bands.

The Effects of Dissipation and Coarse Grid Resolution for Multigrid in Flow Problems

NASA Technical Reports Server (NTRS)

Eliasson, Peter; Engquist, Bjoern

1996-01-01

The objective of this paper is to investigate the effects of the numerical dissipation and the resolution of the solution on coarser grids for multigrid with the Euler equation approximations. The convergence is accomplished by multi-stage explicit time-stepping to steady state accelerated by FAS multigrid. A theoretical investigation is carried out for linear hyperbolic equations in one and two dimensions. The spectra reveals that for stability and hence robustness of spatial discretizations with a small amount of numerical dissipation the grid transfer operators have to be accurate enough and the smoother of low temporal accuracy. Numerical results give grid independent convergence in one dimension. For two-dimensional problems with a small amount of numerical dissipation, however, only a few grid levels contribute to an increased speed of convergence. This is explained by the small numerical dissipation leading to dispersion. Increasing the mesh density and hence making the problem over resolved increases the number of mesh levels contributing to an increased speed of convergence. If the steady state equations are elliptic, all grid levels contribute to the convergence regardless of the mesh density.

Grating-based X-ray Dark-field Computed Tomography of Living Mice.

PubMed

Velroyen, A; Yaroshenko, A; Hahn, D; Fehringer, A; Tapfer, A; Müller, M; Noël, P B; Pauwels, B; Sasov, A; Yildirim, A Ö; Eickelberg, O; Hellbach, K; Auweter, S D; Meinel, F G; Reiser, M F; Bech, M; Pfeiffer, F

2015-10-01

Changes in x-ray attenuating tissue caused by lung disorders like emphysema or fibrosis are subtle and thus only resolved by high-resolution computed tomography (CT). The structural reorganization, however, is of strong influence for lung function. Dark-field CT (DFCT), based on small-angle scattering of x-rays, reveals such structural changes even at resolutions coarser than the pulmonary network and thus provides access to their anatomical distribution. In this proof-of-concept study we present x-ray in vivo DFCTs of lungs of a healthy, an emphysematous and a fibrotic mouse. The tomographies show excellent depiction of the distribution of structural - and thus indirectly functional - changes in lung parenchyma, on single-modality slices in dark field as well as on multimodal fusion images. Therefore, we anticipate numerous applications of DFCT in diagnostic lung imaging. We introduce a scatter-based Hounsfield Unit (sHU) scale to facilitate comparability of scans. In this newly defined sHU scale, the pathophysiological changes by emphysema and fibrosis cause a shift towards lower numbers, compared to healthy lung tissue.

Grating-based X-ray Dark-field Computed Tomography of Living Mice

PubMed Central

Velroyen, A.; Yaroshenko, A.; Hahn, D.; Fehringer, A.; Tapfer, A.; Müller, M.; Noël, P.B.; Pauwels, B.; Sasov, A.; Yildirim, A.Ö.; Eickelberg, O.; Hellbach, K.; Auweter, S.D.; Meinel, F.G.; Reiser, M.F.; Bech, M.; Pfeiffer, F.

2015-01-01

Changes in x-ray attenuating tissue caused by lung disorders like emphysema or fibrosis are subtle and thus only resolved by high-resolution computed tomography (CT). The structural reorganization, however, is of strong influence for lung function. Dark-field CT (DFCT), based on small-angle scattering of x-rays, reveals such structural changes even at resolutions coarser than the pulmonary network and thus provides access to their anatomical distribution. In this proof-of-concept study we present x-ray in vivo DFCTs of lungs of a healthy, an emphysematous and a fibrotic mouse. The tomographies show excellent depiction of the distribution of structural – and thus indirectly functional – changes in lung parenchyma, on single-modality slices in dark field as well as on multimodal fusion images. Therefore, we anticipate numerous applications of DFCT in diagnostic lung imaging. We introduce a scatter-based Hounsfield Unit (sHU) scale to facilitate comparability of scans. In this newly defined sHU scale, the pathophysiological changes by emphysema and fibrosis cause a shift towards lower numbers, compared to healthy lung tissue. PMID:26629545

Study of the Effect of Temporal Sampling Frequency on DSCOVR Observations Using the GEOS-5 Nature Run Results (Part I): Earths Radiation Budget

NASA Technical Reports Server (NTRS)

Holdaway, Daniel; Yang, Yuekui

2016-01-01

Satellites always sample the Earth-atmosphere system in a finite temporal resolution. This study investigates the effect of sampling frequency on the satellite-derived Earth radiation budget, with the Deep Space Climate Observatory (DSCOVR) as an example. The output from NASA's Goddard Earth Observing System Version 5 (GEOS-5) Nature Run is used as the truth. The Nature Run is a high spatial and temporal resolution atmospheric simulation spanning a two-year period. The effect of temporal resolution on potential DSCOVR observations is assessed by sampling the full Nature Run data with 1-h to 24-h frequencies. The uncertainty associated with a given sampling frequency is measured by computing means over daily, monthly, seasonal and annual intervals and determining the spread across different possible starting points. The skill with which a particular sampling frequency captures the structure of the full time series is measured using correlations and normalized errors. Results show that higher sampling frequency gives more information and less uncertainty in the derived radiation budget. A sampling frequency coarser than every 4 h results in significant error. Correlations between true and sampled time series also decrease more rapidly for a sampling frequency less than 4 h.

Visible AO Observations at Halpha for Accreting Young Planets

NASA Astrophysics Data System (ADS)

Close, L. M.; Follette, K.; Males, J. R.; Morzinski, K.; Rodigas, T. J.; Hinz, P.; Wu, Y.-L.; Apai, D.; Najita, J.; Puglisi, A.; Esposito, S.; Riccardi, A.; Bailey, V.; Xompero, M.; Briguglio, R.; Weinberger, A.

2014-01-01

We utilized the new high-order (250-378 mode) Magellan Adaptive Optics system (MagAO) to obtain very high-resolution science in the visible with MagAO's VisAO CCD camera. In the good-median seeing conditions of Magellan (0.5-0.7'') we find MagAO delivers individual short exposure images as good as 19 mas optical resolution. Due to telescope vibrations, long exposure (60s) r' (0.63μm) images are slightly coarser at FWHM = 23-29 mas (Strehl ~ 28%) with bright (R < 9 mag) guide stars. These are the highest resolution filled-aperture images published to date. Images of the young (~ 1 Myr) Orion Trapezium θ1 Ori A, B, and C cluster members were obtained with VisAO. In particular, the 32 mas binary θ1 Ori C 1 C 2 was easily resolved in non-interferometric images for the first time. Relative positions of the bright trapezium binary stars were measured with ~ 0.6-5 mas accuracy. In the second commissioning run we were able to correct 378 modes and achieved good contrasts (Strehl>20% on young transition disks at Hα). We discuss the contrasts achieved at Hα and the possibility of detecting low mass (~ 1-5 Mjup) planets (past 5AU) with our new SAPPHIRES survey with MagAO at Hα.

Designing ecological climate change impact assessments to reflect key climatic drivers

USGS Publications Warehouse

Sofaer, Helen R.; Barsugli, Joseph J.; Jarnevich, Catherine S.; Abatzoglou, John T.; Talbert, Marian; Miller, Brian W.; Morisette, Jeffrey T.

2017-01-01

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling.

Designing ecological climate change impact assessments to reflect key climatic drivers.

PubMed

Sofaer, Helen R; Barsugli, Joseph J; Jarnevich, Catherine S; Abatzoglou, John T; Talbert, Marian K; Miller, Brian W; Morisette, Jeffrey T

2017-07-01

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive - such as means or extremes - can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the 'model space' approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling. © 2017 John Wiley & Sons Ltd.

Prevalence of pure versus mixed snow cover pixels across spatial resolutions in alpine environments: implications for binary and fractional remote sensing approaches

USGS Publications Warehouse

Selkowitz, David J.; Forster, Richard; Caldwell, Megan K.

2014-01-01

Remote sensing of snow-covered area (SCA) can be binary (indicating the presence/absence of snow cover at each pixel) or fractional (indicating the fraction of each pixel covered by snow). Fractional SCA mapping provides more information than binary SCA, but is more difficult to implement and may not be feasible with all types of remote sensing data. The utility of fractional SCA mapping relative to binary SCA mapping varies with the intended application as well as by spatial resolution, temporal resolution and period of interest, and climate. We quantified the frequency of occurrence of partially snow-covered (mixed) pixels at spatial resolutions between 1 m and 500 m over five dates at two study areas in the western U.S., using 0.5 m binary SCA maps derived from high spatial resolution imagery aggregated to fractional SCA at coarser spatial resolutions. In addition, we used in situ monitoring to estimate the frequency of partially snow-covered conditions for the period September 2013–August 2014 at 10 60-m grid cell footprints at two study areas with continental snow climates. Results from the image analysis indicate that at 40 m, slightly above the nominal spatial resolution of Landsat, mixed pixels accounted for 25%–93% of total pixels, while at 500 m, the nominal spatial resolution of MODIS bands used for snow cover mapping, mixed pixels accounted for 67%–100% of total pixels. Mixed pixels occurred more commonly at the continental snow climate site than at the maritime snow climate site. The in situ data indicate that some snow cover was present between 186 and 303 days, and partial snow cover conditions occurred on 10%–98% of days with snow cover. Four sites remained partially snow-free throughout most of the winter and spring, while six sites were entirely snow covered throughout most or all of the winter and spring. Within 60 m grid cells, the late spring/summer transition from snow-covered to snow-free conditions lasted 17–56 days and averaged 37 days. Our results suggest that mixed snow-covered snow-free pixels are common at the spatial resolutions imaged by both the Landsat and MODIS sensors. This highlights the additional information available from fractional SCA products and suggests fractional SCA can provide a major advantage for hydrological and climatological monitoring and modeling, particularly when accurate representation of the spatial distribution of snow cover is critical.

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.

Accounting for groundwater in stream fish thermal habitat responses to climate change

USGS Publications Warehouse

Snyder, Craig D.; Hitt, Nathaniel P.; Young, John A.

2015-01-01

Forecasting climate change effects on aquatic fauna and their habitat requires an understanding of how water temperature responds to changing air temperature (i.e., thermal sensitivity). Previous efforts to forecast climate effects on brook trout habitat have generally assumed uniform air-water temperature relationships over large areas that cannot account for groundwater inputs and other processes that operate at finer spatial scales. We developed regression models that accounted for groundwater influences on thermal sensitivity from measured air-water temperature relationships within forested watersheds in eastern North America (Shenandoah National Park, USA, 78 sites in 9 watersheds). We used these reach-scale models to forecast climate change effects on stream temperature and brook trout thermal habitat, and compared our results to previous forecasts based upon large-scale models. Observed stream temperatures were generally less sensitive to air temperature than previously assumed, and we attribute this to the moderating effect of shallow groundwater inputs. Predicted groundwater temperatures from air-water regression models corresponded well to observed groundwater temperatures elsewhere in the study area. Predictions of brook trout future habitat loss derived from our fine-grained models were far less pessimistic than those from prior models developed at coarser spatial resolutions. However, our models also revealed spatial variation in thermal sensitivity within and among catchments resulting in a patchy distribution of thermally suitable habitat. Habitat fragmentation due to thermal barriers therefore may have an increasingly important role for trout population viability in headwater streams. Our results demonstrate that simple adjustments to air-water temperature regression models can provide a powerful and cost-effective approach for predicting future stream temperatures while accounting for effects of groundwater.

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.

MODFLOW-2005, the U.S. Geological Survey modular ground-water model - documentation of shared node local grid refinement (LGR) and the boundary flow and head (BFH) package

USGS Publications Warehouse

Mehl, Steffen W.; Hill, Mary C.

2006-01-01

This report documents the addition of shared node Local Grid Refinement (LGR) to MODFLOW-2005, the U.S. Geological Survey modular, transient, three-dimensional, finite-difference ground-water flow model. LGR provides the capability to simulate ground-water flow using one block-shaped higher-resolution local grid (a child model) within a coarser-grid parent model. LGR accomplishes this by iteratively coupling two separate MODFLOW-2005 models such that heads and fluxes are balanced across the shared interfacing boundary. LGR can be used in two-and three-dimensional, steady-state and transient simulations and for simulations of confined and unconfined ground-water systems. Traditional one-way coupled telescopic mesh refinement (TMR) methods can have large, often undetected, inconsistencies in heads and fluxes across the interface between two model grids. The iteratively coupled shared-node method of LGR provides a more rigorous coupling in which the solution accuracy is controlled by convergence criteria defined by the user. In realistic problems, this can result in substantially more accurate solutions and require an increase in computer processing time. The rigorous coupling enables sensitivity analysis, parameter estimation, and uncertainty analysis that reflects conditions in both model grids. This report describes the method used by LGR, evaluates LGR accuracy and performance for two- and three-dimensional test cases, provides input instructions, and lists selected input and output files for an example problem. It also presents the Boundary Flow and Head (BFH) Package, which allows the child and parent models to be simulated independently using the boundary conditions obtained through the iterative process of LGR.

Role of grain-size in phyllonitisation: Insights from mineralogy, microstructures, strain analyses and numerical modeling

NASA Astrophysics Data System (ADS)

Bose, Narayan; Dutta, Dripta; Mukherjee, Soumyajit

2018-07-01

Brittle Y- and P-planes exist in an exposure of greywacke in the Garhwal Lesser Himalaya, India. Although, Y-planes are well developed throughout, the P-planes are prominent only in some parts (domain-A), and not elsewhere (domain-B). To investigate why the P-planes developed selectively, the following studies were undertaken: 1. Clay-separated XRD analyses: clinochlore and illite are present in both the domains. 2. Strain analyses by Rf-φ method: it deduces strain magnitudes of ∼1.8 for the ductile deformed quartz grains from both the domains A and B. 3. Grain size analyses of quartz clasts: domain-A is mostly composed of finer grains (area up to 40,000 μm2), whereas domain-B consists of a population of coarser grains (area >45,000 μm2). A 2D finite element modeling of linear elastic material was performed using COMSOL software to investigate the control of grain-size variation on the generation brittle shear planes. The results of numerical modeling corroborate the known fact that an increase in grain-size reduces the elastic strain energy density. A broader grain-size distribution increases the effects of diffusion creep and resists the onset of dislocation creep. Thus, rocks with coarser grain population (domain B) tend to resist the generation of shear fractures, unlike their fine-grained counterpart (domain A).

Tracking recent climate and anthropogenic change in Central America in sediments form the lower fan of the Rio Yaqui, Gulf of California, Mexico

NASA Astrophysics Data System (ADS)

Aiello, I. W.; Ravelo, A. C.; Moraes, R.; Swarzenski, P. W.

2015-12-01

We report the results of preliminary sedimentologic analyses of a ~3.3m long piston core (P13) collected in the lower fan of the Rio Yaqui (Guaymas Basin, Gulf of California; depth, 1859m) by UNAM's (Universidad Nacional Autónoma de México) research ship El Puma in 2014. The core was collected to test the potential for high-resolution reconstructions of basin-scale paleoclimate in the Pacific and the Mesoamerican region. Shipboard and post-cruise analyses include magnetic susceptibility (MS), smear slide counts and laser diffraction particle size analysis. The core is being analyzed for X-Ray Fluorescence (XRF) and color reflectance, and a 210Pb age model is being constructed. Preliminary results show that Rio Yaqui lower fan sediment differs significantly from that in the Guaymas Basin, which is dominantly diatom ooze. The lower ~2m of core P13 show prominent alternations (~10-20cm) between very-fine-grained, clay intervals characterized by higher MS and mixed diatom and clay intervals, with coarser grain size and lower MS values. In contrast, the upper ~1m has distinctive high MS sand turbidites alternating with diatom-rich layers. Previous core studies from nearby ODP Leg 64 site show sedimentation rates of ~1.2 m/ka; as these sites are further away from the Yaqui delta the sedimentation rates for core P13 should be higher possibly recording only the last few hundred years of sedimentation. Clay/diatom cycles in the lower part of the core could record decadal- or ENSO-scale wet/aridity cycles in the Sonoran Mainland. Conversely, the coarser siliciclastic intervals and the diatom layers in the upper part of the core could reflect the last few decades of land usage in the watershed of the Rio Yaqui, the most important river in the state of Sonora, Mexico. These include large modifications to the river's hydrography (e.g. construction of dams and aqueducts), rapidly expanding mass agricultural practices in the region, and increased eutrophication in the Gulf.

Climate change scenarios of heat waves in Central Europe and their uncertainties

NASA Astrophysics Data System (ADS)

Lhotka, Ondřej; Kyselý, Jan; Farda, Aleš

2018-02-01

The study examines climate change scenarios of Central European heat waves with a focus on related uncertainties in a large ensemble of regional climate model (RCM) simulations from the EURO-CORDEX and ENSEMBLES projects. Historical runs (1970-1999) driven by global climate models (GCMs) are evaluated against the E-OBS gridded data set in the first step. Although the RCMs are found to reproduce the frequency of heat waves quite well, those RCMs with the coarser grid (25 and 50 km) considerably overestimate the frequency of severe heat waves. This deficiency is improved in higher-resolution (12.5 km) EURO-CORDEX RCMs. In the near future (2020-2049), heat waves are projected to be nearly twice as frequent in comparison to the modelled historical period, and the increase is even larger for severe heat waves. Uncertainty originates mainly from the selection of RCMs and GCMs because the increase is similar for all concentration scenarios. For the late twenty-first century (2070-2099), a substantial increase in heat wave frequencies is projected, the magnitude of which depends mainly upon concentration scenario. Three to four heat waves per summer are projected in this period (compared to less than one in the recent climate), and severe heat waves are likely to become a regular phenomenon. This increment is primarily driven by a positive shift of temperature distribution, but changes in its scale and enhanced temporal autocorrelation of temperature also contribute to the projected increase in heat wave frequencies.

Assessment of future extreme climate events over the Porto wine Region

NASA Astrophysics Data System (ADS)

Viceto, Carolina; Cardoso, Susana; Marta-Almeida, Martinho; Gorodetskaya, Irina; Rocha, Alfredo

2017-04-01

The Douro Demarcated Region (DDR) is a wine region, in the northern Portugal, recognized for the Porto wine, which is responsible for more than 60% of the total value of national wine exportations. Since the viticulture is highly dependent on weather/climate patterns, the global warming is expected to affect the areas suitable to the growth of a certain variety of grape, its production and quality. This highlights the need of regional studies that assess the future climate changes effects in the vineyard, which might allow an early adjustment. We explore future climate change in the DDR region using a high-resolution regional climate model for Weather Research and Forecasting (WRF) forced by the Max Planck Institute Earth System Model - low resolution (MPI-ESM-LR). Two future periods have been simulated using the emission scenario RCP8.5 - for the mid- (2046-2065) and late 21st century (2081-2100) - and compared to a reference period (1986-2005). The RCP8.5 is a "baseline" scenario without any climate mitigation and corresponds to the pathway with the highest greenhouse gas emissions compared to other scenarios developed by the Intergovernmental Panel for Climate Change. Our regional WRF implementation uses three online-nested domains with increasing resolution at a downscaling ratio of three. The coarser domain of 81-km resolution covers part of the North Atlantic Ocean and most of the Europe. The innermost 9-km horizontal resolution domain includes the Iberian Peninsula, a portion of Northern Africa and the adjacent part of the Atlantic Ocean and Mediterranean Sea. Our study uses this 9-km resolution domain and focuses on a confined area, which comprises the DDR. Such dynamical downscaling approach gives an advantage to assess climate effects on the DDR region, where the high horizontal resolution allows including effects of the oceanic coastline, local riverbeds and complex topography. The climatology of the DDR region determines the more suitable wine variety to be produced (Porto and Douro wine), while climate variability affects the annual productivity and quality of the grape harvest. Our study investigates changes in the extreme climate events in the future model runs, through a set of climate change indicators defined by the WRCP's Expert Team in Climate Change Detection and Indices, which uses variables such as daily maximum and minimum temperatures and precipitation amounts. Furthermore, we explore heat waves and their properties (duration, intensity and recovery factor). The analysis shows an increase of the mean temperature in the DDR higher than 2°C by the mid-21st century and 4.5°C by the end of the century, relatively to the reference period. Moreover, we found a major predisposition towards higher values of minimum and maximum daily temperatures and a decrease in the total precipitation during both future periods. These preliminary results indicate increased climatic stress on the DDR wine production and increased vulnerability of the wine varieties in this region.

Using pan-sharpened high resolution satellite data to improve impervious surfaces estimation

NASA Astrophysics Data System (ADS)

Xu, Ru; Zhang, Hongsheng; Wang, Ting; Lin, Hui

2017-05-01

Impervious surface is an important environmental and socio-economic indicator for numerous urban studies. While a large number of researches have been conducted to estimate the area and distribution of impervious surface from satellite data, the accuracy for impervious surface estimation (ISE) is insufficient due to high diversity of urban land cover types. This study evaluated the use of panchromatic (PAN) data in very high resolution satellite image for improving the accuracy of ISE by various pan-sharpening approaches, with a further comprehensive analysis of its scale effects. Three benchmark pan-sharpening approaches, Gram-Schmidt (GS), PANSHARP and principal component analysis (PCA) were applied to WorldView-2 in three spots of Hong Kong. The on-screen digitization were carried out based on Google Map and the results were viewed as referenced impervious surfaces. The referenced impervious surfaces and the ISE results were then re-scaled to various spatial resolutions to obtain the percentage of impervious surfaces. The correlation coefficient (CC) and root mean square error (RMSE) were adopted as the quantitative indicator to assess the accuracy. The accuracy differences between three research areas were further illustrated by the average local variance (ALV) which was used for landscape pattern analysis. The experimental results suggested that 1) three research regions have various landscape patterns; 2) ISE accuracy extracted from pan-sharpened data was better than ISE from original multispectral (MS) data; and 3) this improvement has a noticeable scale effects with various resolutions. The improvement was reduced slightly as the resolution became coarser.

MODFLOW–LGR—Documentation of ghost node local grid refinement (LGR2) for multiple areas and the boundary flow and head (BFH2) package

USGS Publications Warehouse

Mehl, Steffen W.; Hill, Mary C.

2013-01-01

This report documents the addition of ghost node Local Grid Refinement (LGR2) to MODFLOW-2005, the U.S. Geological Survey modular, transient, three-dimensional, finite-difference groundwater flow model. LGR2 provides the capability to simulate groundwater flow using multiple block-shaped higher-resolution local grids (a child model) within a coarser-grid parent model. LGR2 accomplishes this by iteratively coupling separate MODFLOW-2005 models such that heads and fluxes are balanced across the grid-refinement interface boundary. LGR2 can be used in two-and three-dimensional, steady-state and transient simulations and for simulations of confined and unconfined groundwater systems. Traditional one-way coupled telescopic mesh refinement methods can have large, often undetected, inconsistencies in heads and fluxes across the interface between two model grids. The iteratively coupled ghost-node method of LGR2 provides a more rigorous coupling in which the solution accuracy is controlled by convergence criteria defined by the user. In realistic problems, this can result in substantially more accurate solutions and require an increase in computer processing time. The rigorous coupling enables sensitivity analysis, parameter estimation, and uncertainty analysis that reflects conditions in both model grids. This report describes the method used by LGR2, evaluates accuracy and performance for two-and three-dimensional test cases, provides input instructions, and lists selected input and output files for an example problem. It also presents the Boundary Flow and Head (BFH2) Package, which allows the child and parent models to be simulated independently using the boundary conditions obtained through the iterative process of LGR2.

Can Earth System Model Provide Reasonable Natural Runoff Estimates to Support Water Management Studies?

NASA Astrophysics Data System (ADS)

Kao, S. C.; Shi, X.; Kumar, J.; Ricciuto, D. M.; Mao, J.; Thornton, P. E.

2017-12-01

With the concern of changing hydrologic regime, there is a crucial need to better understand how water availability may change and influence water management decisions in the projected future climate conditions. Despite that surface hydrology has long been simulated by land model within the Earth System modeling (ESM) framework, given the coarser horizontal resolution and lack of engineering-level calibration, raw runoff from ESM is generally discarded by water resource managers when conducting hydro-climate impact assessments. To identify a likely path to improve the credibility of ESM-simulated natural runoff, we conducted regional model simulation using the land component (ALM) of the Accelerated Climate Modeling for Energy (ACME) version 1 focusing on the conterminous United States (CONUS). Two very different forcing data sets, including (1) the conventional 0.5° CRUNCEP (v5, 1901-2013) and (2) the 1-km Daymet (v3, 1980-2013) aggregated to 0.5°, were used to conduct 20th century transient simulation with satellite phenology. Additional meteorologic and hydrologic observations, including PRISM precipitation and U.S. Geological Survey WaterWatch runoff, were used for model evaluation. For various CONUS hydrologic regions (such as Pacific Northwest), we found that Daymet can significantly improve the reasonableness of simulated ALM runoff even without intensive calibration. The large dry bias of CRUNCEP precipitation (evaluated by PRISM) in multiple CONUS hydrologic regions is believed to be the main reason causing runoff underestimation. The results suggest that when driving with skillful precipitation estimates, ESM has the ability to produce reasonable natural runoff estimates to support further water management studies. Nevertheless, model calibration will be required for regions (such as Upper Colorado) where ill performance is showed for multiple different forcings.

On Improving 4-km Mesoscale Model Simulations

NASA Astrophysics Data System (ADS)

Deng, Aijun; Stauffer, David R.

2006-03-01

A previous study showed that use of analysis-nudging four-dimensional data assimilation (FDDA) and improved physics in the fifth-generation Pennsylvania State University National Center for Atmospheric Research Mesoscale Model (MM5) produced the best overall performance on a 12-km-domain simulation, based on the 18 19 September 1983 Cross-Appalachian Tracer Experiment (CAPTEX) case. However, reducing the simulated grid length to 4 km had detrimental effects. The primary cause was likely the explicit representation of convection accompanying a cold-frontal system. Because no convective parameterization scheme (CPS) was used, the convective updrafts were forced on coarser-than-realistic scales, and the rainfall and the atmospheric response to the convection were too strong. The evaporative cooling and downdrafts were too vigorous, causing widespread disruption of the low-level winds and spurious advection of the simulated tracer. In this study, a series of experiments was designed to address this general problem involving 4-km model precipitation and gridpoint storms and associated model sensitivities to the use of FDDA, planetary boundary layer (PBL) turbulence physics, grid-explicit microphysics, a CPS, and enhanced horizontal diffusion. Some of the conclusions include the following: 1) Enhanced parameterized vertical mixing in the turbulent kinetic energy (TKE) turbulence scheme has shown marked improvements in the simulated fields. 2) Use of a CPS on the 4-km grid improved the precipitation and low-level wind results. 3) Use of the Hong and Pan Medium-Range Forecast PBL scheme showed larger model errors within the PBL and a clear tendency to predict much deeper PBL heights than the TKE scheme. 4) Combining observation-nudging FDDA with a CPS produced the best overall simulations. 5) Finer horizontal resolution does not always produce better simulations, especially in convectively unstable environments, and a new CPS suitable for 4-km resolution is needed. 6) Although use of current CPSs may violate their underlying assumptions related to the size of the convective element relative to the grid size, the gridpoint storm problem was greatly reduced by applying a CPS to the 4-km grid.

LLNL Scientists Use NERSC to Advance Global Aerosol Simulations

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

Bergmann, D J; Chuang, C; Rotman, D

2004-10-13

While ''greenhouse gases'' have been the focus of climate change research for a number of years, DOE's ''Aerosol Initiative'' is now examining how aerosols (small particles of approximately micron size) affect the climate on both a global and regional scale. Scientists in the Atmospheric Science Division at Lawrence Livermore National Laboratory (LLNL) are using NERSC's IBM supercomputer and LLNL's IMPACT (atmospheric chemistry) model to perform simulations showing the historic effects of sulfur aerosols at a finer spatial resolution than ever done before. Simulations were carried out for five decades, from the 1950s through the 1990s. The results clearly show themore » effects of the changing global pattern of sulfur emissions. Whereas in 1950 the United States emitted 41 percent of the world's sulfur aerosols, this figure had dropped to 15 percent by 1990, due to conservation and anti-pollution policies. By contrast, the fraction of total sulfur emissions of European origin has only dropped by a factor of 2 and the Asian emission fraction jumped six fold during the same time, from 7 percent in 1950 to 44 percent in 1990. Under a special allocation of computing time provided by the Office of Science INCITE (Innovative and Novel Computational Impact on Theory and Experiment) program, Dan Bergmann, working with a team of LLNL scientists including Cathy Chuang, Philip Cameron-Smith, and Bala Govindasamy, was able to carry out a large number of calculations during the past month, making the aerosol project one of the largest users of NERSC resources. The applications ran on 128 and 256 processors. The objective was to assess the effects of anthropogenic (man-made) sulfate aerosols. The IMPACT model calculates the rate at which SO{sub 2} (a gas emitted by industrial activity) is oxidized and forms particles known as sulfate aerosols. These particles have a short lifespan in the atmosphere, often washing out in about a week. This means that their effects on climate tend to be more regional, occurring near the area where the SO{sub 2} is emitted. To accurately study these regional effects, Bergmann needed to run the simulations at a finer horizontal resolution, as the coarser resolution (typically 300km by 300km) of other climate models are insufficient for studying changes on a regional scale. Livermore's use of CAM3, the Community Atmospheric Model which is a high-resolution climate model developed at NCAR (with collaboration from DOE), allows a 100km by 100km grid to be applied. NERSC's terascale computing capability provided the needed computational horsepower to run the application at the finer level.« less

Airflow and air quality simulations over the western mountainous region with a four-dimensional data assimilation technique

NASA Astrophysics Data System (ADS)

Yamada, Tetsuji; Kao, Chih-Yue; Bunker, Susan

We apply a three-dimensional meteorological model with a four-dimensional data assimilation (4-DDA) technique to simulate diurnal variations of wind, temperature, water vapor, and turbulence in a region extending from the west coast to east of the Rockies and from northern Mexico to Wyoming. The wind data taken during the 1985 SCENES ( Subregional Cooperative Electric Utility, Dept. of Defense, National Park Service, and Environmental Protection Agency Study on Visibility) field experiments are successfully assimilated into the model through the 4-DDA technique by 'nudging' the modeled winds toward the observed winds. The modeled winds and turbulence fields are then used in a Lagrangian random-particle statistical model to investigate how pollutants from potential sources are transported and diffused. Finally, we calculate the ground concentrations through a kernel density estimator. Two scenarios in different weather patterns are investigated with simulation periods up to 6 days. One is associated with the evolution of a surface cold front and the other under a high-pressure stagnant condition. In the frontal case, the impact of air-mass movement on the ground concentrations of pollutants released from the Los Angeles area is well depicted by the model. Also, the pollutants produced from Los Angeles can be transported to the Grand Canyon area within 24 h. However, if we use only the data that were obtained from the regular NWS rawinsonde network, whose temporal and spatial resolutions are coarser than those of the special network, the plume goes north-northeast and never reaches the Grand Canyon area. In the stagnant case, the pollutants meander around the source area and can have significant impact on local air quality.

Evolvable social agents for bacterial systems modeling.

PubMed

Paton, Ray; Gregory, Richard; Vlachos, Costas; Saunders, Jon; Wu, Henry

2004-09-01

We present two approaches to the individual-based modeling (IbM) of bacterial ecologies and evolution using computational tools. The IbM approach is introduced, and its important complementary role to biosystems modeling is discussed. A fine-grained model of bacterial evolution is then presented that is based on networks of interactivity between computational objects representing genes and proteins. This is followed by a coarser grained agent-based model, which is designed to explore the evolvability of adaptive behavioral strategies in artificial bacteria represented by learning classifier systems. The structure and implementation of the two proposed individual-based bacterial models are discussed, and some results from simulation experiments are presented, illustrating their adaptive properties.

Estimation of the atmosphere-ocean fluxes of greenhouse gases and aerosols at the finer resolution of the coastal ocean.

NASA Astrophysics Data System (ADS)

Vieira, Vasco; Sahlée, Erik; Jurus, Pavel; Clementi, Emanuela; Pettersson, Heidi; Mateus, Marcos

2016-04-01

The balances and fluxes of greenhouse gases and aerosols between atmosphere and ocean are fundamental for Earth's heat budget. Hence, the scientific community needs to know and simulate them with accuracy in order to monitor climate change from Earth-Observation satellites and to produce reliable estimates of climate change using Earth-System Models (ESM). So far, ESM have represented earth's surface with coarser resolutions so that each cell of the marine domain is dominated by the open ocean. In such case it is enough to use simple algorithms considering the wind speed 10m above sea-surface (u10) as sole driver of the gas transfer velocity. The formulation by Wanninkhof (1992) is broadly accepted as the best. However, the ESM community is becoming increasingly aware of the need to model with finer resolutions. Then, it is no longer enough to only consider u10 when modelling gas transfer velocities across the coastal oceans' surfaces. More comprehensive formulations are required that adjust better to local conditions by also accounting for the effects of sea-surface agitation, wave breaking, atmospheric stability of the Surface Boundary Layer, current drag with the bottom, surfactants and rain. Accurate algorithms are also fundamental to monitor atmosphere and ocean greenhouse gas concentrations using satellite data and reverse modelling. Past satellite missions ERS, Envisat, Jason-2, Aqua, Terra and Metop, have already been remotely sensing the ocean's surface at much finer resolutions than ESM using instruments like MERIS, MODIS, AMR, AATSR, MIPAS, Poseidon-3, SCIAMACHY, SeaWiFS, and IASI. The planned new satellite missions Sentinel-3, OCO-2 and GOSAT will further increase the resolutions. We developed a framework to congregate competing formulations for the estimation of the solubility and transfer velocity of virtually any gas on the biosphere taking into consideration the atmosphere and ocean fundamental variables and their derived geophysical processes mentioned above. First, we tested with measured data from the Baltic. Then, we adapted it to a coupler for atmosphere (WRF) and ocean (WW3-NEMO) model components and tested with simulated data relative to the Mediterranean and coastal North Atlantic. Computational speed was greatly improved by calculus vectorization and parallelization. The classical solubility formulation was compared to a recent alternative relying in a different chemistry background. Differences between solubility formulations resulted in a bias of 3.86×106 ton of CO2, 880.7 ton of CH4 and 401 ton of N2O dissolved in the first meter below the sea-surface of the modelled region, corresponding to 5.9% of the N2O yearly discharged by European estuaries. These differences concentrated in sensitive areas for Earth-System dynamics: the cooler polar waters and warmer less-saline coastal waters. The classical transfer velocity formulation using solely u10 was compared to alternatives using the friction velocity, atmospheric stability, sea-surface agitation and wave breaking. Differences between estimated transfer velocities concentrated at the coastal ocean and resulted in 55.82% of the gas volume transferred over the sea-surface of the modelled region during the 66h simulated period.

Source apportionment studies on particulate matter in Beijing/China

NASA Astrophysics Data System (ADS)

Suppan, P.; Shen, R.; Shao, L.; Schrader, S.; Schäfer, K.; Norra, S.; Vogel, B.; Cen, K.; Wang, Y.

2013-05-01

More than 15 million people in the greater area of Beijing are still suffering from severe air pollution levels caused by sources within the city itself but also from external impacts like severe dust storms and long range advection from the southern and central part of China. Within this context particulate matter (PM) is the major air pollutant in the greater area of Beijing (Garland et al., 2009). PM did not serve only as lead substance for air quality levels and therefore for adverse health impact effects but also for a strong influence on the climate system by changing e.g. the radiative balance. Investigations on emission reductions during the Olympic Summer Games in 2008 have caused a strong reduction on coarser particles (PM10) but not on smaller particles (PM2.5). In order to discriminate the composition of the particulate matter levels, the different behavior of coarser and smaller particles investigations on source attribution, particle characteristics and external impacts on the PM levels of the city of Beijing by measurements and modeling are performed: a) Examples of long term measurements of PM2.5 filter sampling in 2010/2011 with the objectives of detailed chemical (source attribution, carbon fraction, organic speciation and inorganic composition) and isotopic analyses as well as toxicological assessment in cooperation with several institutions (Karlsruhe Institute of Technology (IfGG/IMG), Helmholtz Zentrum München (HMGU), University Rostock (UR), Chinese University of Mining and Technology Beijing, CUMTB) will be discussed. b) The impact of dust storm events on the overall pollution level of particulate matter in the greater area of Beijing is being assessed by the online coupled comprehensive model system COSMO-ART. First results of the dust storm modeling in northern China (2011, April 30th) demonstrates very well the general behavior of the meteorological parameters temperature and humidity as well as a good agreement between modeled and measured dust storm concentration variability at Beijing in the course of time. The results show the importance of intertwine investigations of measurements and modeling, the analysis of local air pollution levels as well as the impact and analysis of advective processes in the greater region of Beijing. Comprehensive investigations on particulate matter are a prerequisite for the knowledge of the source strengths and source attribution to the overall air pollution level. Only this knowledge can help to formulate and to introduce specific reduction measures to reduce coarser as well as finer particulates.

Reference evapotranspiration from coarse-scale and dynamically downscaled data in complex terrain: Sensitivity to interpolation and resolution

NASA Astrophysics Data System (ADS)

Strong, Courtenay; Khatri, Krishna B.; Kochanski, Adam K.; Lewis, Clayton S.; Allen, L. Niel

2017-05-01

The main objective of this study was to investigate whether dynamically downscaled high resolution (4-km) climate data from the Weather Research and Forecasting (WRF) model provide physically meaningful additional information for reference evapotranspiration (E) calculation compared to the recently published GridET framework that uses interpolation from coarser-scale simulations run at 32-km resolution. The analysis focuses on complex terrain of Utah in the western United States for years 1985-2010, and comparisons were made statewide with supplemental analyses specifically for regions with irrigated agriculture. E was calculated using the standardized equation and procedures proposed by the American Society of Civil Engineers from hourly data, and climate inputs from WRF and GridET were debiased relative to the same set of observations. For annual mean values, E from WRF (EW) and E from GridET (EG) both agreed well with E derived from observations (r2 = 0.95, bias < 2 mm). Domain-wide, EW and EG were well correlated spatially (r2 = 0.89), however local differences ΔE =EW -EG were as large as +439 mm year-1 (+26%) in some locations, and ΔE averaged +36 mm year-1. After linearly removing the effects of contrasts in solar radiation and wind speed, which are characteristically less reliable under downscaling in complex terrain, approximately half the residual variance was accounted for by contrasts in temperature and humidity between GridET and WRF. These contrasts stemmed from GridET interpolating using an assumed lapse rate of Γ = 6.5 K km-1, whereas WRF produced a thermodynamically-driven lapse rate closer to 5 K km-1 as observed in mountainous terrain. The primary conclusions are that observed lapse rates in complex terrain differ markedly from the commonly assumed Γ = 6.5 K km-1, these lapse rates can be realistically resolved via dynamical downscaling, and use of constant Γ produces differences in E of order as large as 102 mm year-1.

Soil moisture retrieval from Sentinel-1 satellite data

NASA Astrophysics Data System (ADS)

Benninga, Harm-Jan; van der Velde, Rogier; Su, Zhongbo

2016-04-01

Reliable up-to-date information on the current water availability and models to evaluate management scenarios are indispensable for skilful water management. The Sentinel-1 radar satellite programme provides an opportunity to monitor water availability (as surface soil moisture) from space on an operational basis at unprecedented fine spatial and temporal resolutions. However, the influences of soil roughness and vegetation cover complicate the retrieval of soil moisture states from radar data. In this contribution, we investigate the sensitivity of Sentinel-1 radar backscatter to soil moisture states and vegetation conditions. The analyses are based on 105 Sentinel-1 images in the period from October 2014 to January 2016 covering the Twente region in the Netherlands. This area is almost flat and has a heterogeneous landscape, including agricultural (mainly grass, cereal and corn), forested and urban land covers. In-situ measurements at 5 cm depth collected from the Twente soil moisture monitoring network are used as reference. This network consists of twenty measurement stations (most of them at agricultural fields) distributed across an area of 50 km × 40 km. The Normalized Difference Vegetation Index (NDVI) derived from optical images is adopted as proxy to represent seasonal variability in vegetation conditions. The results from this sensitivity study provide insight into the potential capability of Sentinel-1 data for the estimation of soil moisture states and they will facilitate the further development of operational retrieval methods. An operationally applicable soil moisture retrieval method requires an algorithm that is usable without the need for area specific model calibration with detailed field information (regarding roughness and vegetation). Because it is not yet clear which method provides the most reliable soil moisture retrievals from Sentinel-1 data, multiple soil moisture retrieval methods will be studied in which the fine spatiotemporal resolution and the dual-polarized information of Sentinel-1 are utilized. Three candidate algorithms are presented at the conference, which are a data-driven algorithm, inversion of a radar scattering model and downscaling of coarser resolution soil moisture products. The research is part of the OWAS1S project (Optimizing Water Availability with Sentinel-1 Satellites), which stands for integration of the freely available global Sentinel-1 data and local knowledge on soil physical processes, to optimize water management of regional water systems and to develop value-added products for agriculture.

Remote sensing of vegetation and land-cover change in Arctic Tundra Ecosystems

USGS Publications Warehouse

Stow, Douglas A.; Hope, Allen; McGuire, David; Verbyla, David; Gamon, John A.; Huemmrich, Fred; Houston, Stan; Racine, Charles H.; Sturm, Matthew; Tape, Ken D.; Hinzman, Larry D.; Yoshikawa, Kenji; Tweedie, Craig E.; Noyle, Brian; Silapaswan, Cherie; Douglas, David C.; Griffith, Brad; Jia, Gensuo; Howard E. Epstein,; Walker, Donald A.; Daeschner, Scott; Petersen, Aaron; Zhou, Liming; Myneni, Ranga B.

2004-01-01

The objective of this paper is to review research conducted over the past decade on the application of multi-temporal remote sensing for monitoring changes of Arctic tundra lands. Emphasis is placed on results from the National Science Foundation Land–Air–Ice Interactions (LAII) program and on optical remote sensing techniques. Case studies demonstrate that ground-level sensors on stationary or moving track platforms and wide-swath imaging sensors on polar orbiting satellites are particularly useful for capturing optical remote sensing data at sufficient frequency to study tundra vegetation dynamics and changes for the cloud prone Arctic. Less frequent imaging with high spatial resolution instruments on aircraft and lower orbiting satellites enable more detailed analyses of land cover change and calibration/validation of coarser resolution observations.The strongest signals of ecosystem change detected thus far appear to correspond to expansion of tundra shrubs and changes in the amount and extent of thaw lakes and ponds. Changes in shrub cover and extent have been documented by modern repeat imaging that matches archived historical aerial photography. NOAA Advanced Very High Resolution Radiometer (AVHRR) time series provide a 20-year record for determining changes in greenness that relates to photosynthetic activity, net primary production, and growing season length. The strong contrast between land materials and surface waters enables changes in lake and pond extent to be readily measured and monitored.

Measurement Sets and Sites Commonly Used for Characterization

NASA Technical Reports Server (NTRS)

Pagnutti, Mary; Holekamp, Kara; Ryan, Robert; Sellers, Richard; Davis, Bruce; Zanoni, Vicki

2002-01-01

Scientists at NASA's Earth Science Applications Directorate are creating a well-characterized Verification & Validation (V&V) site at the Stennis Space Center. This site enables the in-flight characterization of remote sensing systems and the data they acquire. The data are predominantly acquired by commercial, high spatial resolution satellite systems, such as IKONOS and QuickBird 2, and airborne systems. The smaller scale of these newer high resolution remote sensing systems allows scientists to characterize the geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the techniques used to characterize data from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active LIDAR systems. SSC employs geodetic targets, edge targets, radiometric tarps, and thermal calibration ponds to characterize remote sensing data products. This paper presents a proposed set of required measurements for visible through long-wave infrared remote sensing systems and a description of the Stennis characterization. Other topics discussed include: 1) The use of ancillary atmospheric and solar measurements taken at SSC that support various characterizations; 2) Additional sites used for radiometric, geometric, and spatial characterization in the continental United States; 3) The need for a standardized technique to be adopted by CEOS and other organizations.

Measurement Sets and Sites Commonly used for Characterizations

NASA Technical Reports Server (NTRS)

Pagnutti, Mary; Holekamp, Kara; Ryan, Robert; Blonski, Slawomir; Sellers, Richard; Davis, Bruce; Zanoni, Vicki

2002-01-01

Scientists with NASA's Earth Science Applications Directorate are creating a well-characterized Verification & Validation (V&V) site at the Stennis Space Center (SSC). This site enables the in-flight characterization of remote sensing systems and the data that they require. The data are predominantly acquired by commercial, high-spatial resolution satellite systems, such as IKONOS and QuickBird 2, and airborne systems. The smaller scale of these newer high-resolution remote sensing systems allows scientists to characterize the geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active Light Detection and Ranging (LIDAR) systems. SSC employs geodetic targets, edge targets, radiometric tarps, and thermal calibration ponds to characterize remote sensing data products. This paper presents a proposed set of required measurements for visible-through-longwave infrared remote sensing systems, and a description of the Stennis characterization. Other topics discussed inslude: 1) use of ancillary atmospheric and solar measurements taken at SSC that support various characterizations, 2) other sites used for radiometric, geometric, and spatial characterization in the continental United States,a nd 3) the need for a standardized technique to be adopted by the Committee on Earth Observation Satellites (CEOS) and other organizations.

Assessing the Predictability of Convection using Ensemble Data Assimilation of Simulated Radar Observations in an LETKF system

NASA Astrophysics Data System (ADS)

Lange, Heiner; Craig, George

2014-05-01

This study uses the Local Ensemble Transform Kalman Filter (LETKF) to perform storm-scale Data Assimilation of simulated Doppler radar observations into the non-hydrostatic, convection-permitting COSMO model. In perfect model experiments (OSSEs), it is investigated how the limited predictability of convective storms affects precipitation forecasts. The study compares a fine analysis scheme with small RMS errors to a coarse scheme that allows for errors in position, shape and occurrence of storms in the ensemble. The coarse scheme uses superobservations, a coarser grid for analysis weights, a larger localization radius and larger observation error that allow a broadening of the Gaussian error statistics. Three hour forecasts of convective systems (with typical lifetimes exceeding 6 hours) from the detailed analyses of the fine scheme are found to be advantageous to those of the coarse scheme during the first 1-2 hours, with respect to the predicted storm positions. After 3 hours in the convective regime used here, the forecast quality of the two schemes appears indiscernible, judging by RMSE and verification methods for rain-fields and objects. It is concluded that, for operational assimilation systems, the analysis scheme might not necessarily need to be detailed to the grid scale of the model. Depending on the forecast lead time, and on the presence of orographic or synoptic forcing that enhance the predictability of storm occurrences, analyses from a coarser scheme might suffice.

Geophysical constraints on Rio Grande rift structure and stratigraphy from magnetotelluric models and borehole resistivity logs, northern New Mexico

USGS Publications Warehouse

Rodriguez, Brian D.; Sawyer, David A.; Hudson, Mark R.; Grauch, V.J.S.

2013-01-01

Two- and three-dimensional electrical resistivity models derived from the magnetotelluric method were interpreted to provide more accurate hydrogeologic parameters for the Albuquerque and Española Basins. Analysis and interpretation of the resistivity models are aided by regional borehole resistivity data. Examination of the magnetotelluric response of hypothetical stratigraphic cases using resistivity characterizations from the borehole data elucidates two scenarios where the magnetotelluric method provides the strongest constraints. In the first scenario, the magnetotelluric method constrains the thickness of extensive volcanic cover, the underlying thickness of coarser-grained facies of buried Santa Fe Group sediments, and the depth to Precambrian basement or overlying Pennsylvanian limestones. In the second scenario, in the absence of volcanic cover, the magnetotelluric method constrains the thickness of coarser-grained facies of buried Santa Fe Group sediments and the depth to Precambrian basement or overlying Pennsylvanian limestones. Magnetotelluric surveys provide additional constraints on the relative positions of basement rocks and the thicknesses of Paleozoic, Mesozoic, and Tertiary sedimentary rocks in the region of the Albuquerque and Española Basins. The northern extent of a basement high beneath the Cerros del Rio volcanic field is delineated. Our results also reveal that the largest offset of the Hubbell Spring fault zone is located 5 km west of the exposed scarp. By correlating our resistivity models with surface geology and the deeper stratigraphic horizons using deep well log data, we are able to identify which of the resistivity variations in the upper 2 km belong to the upper Santa Fe Group sediment

Developing strong concurrent multiphysics multiscale coupling to understand the impact of microstructural mechanisms on the structural scale

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

Foulk, James W.; Alleman, Coleman N.; Mota, Alejandro

The heterogeneity in mechanical fields introduced by microstructure plays a critical role in the localization of deformation. To resolve this incipient stage of failure, it is therefore necessary to incorporate microstructure with sufficient resolution. On the other hand, computational limitations make it infeasible to represent the microstructure in the entire domain at the component scale. In this study, the authors demonstrate the use of concurrent multi- scale modeling to incorporate explicit, finely resolved microstructure in a critical region while resolving the smoother mechanical fields outside this region with a coarser discretization to limit computational cost. The microstructural physics is modeledmore » with a high-fidelity model that incorporates anisotropic crystal elasticity and rate-dependent crystal plasticity to simulate the behavior of a stainless steel alloy. The component-scale material behavior is treated with a lower fidelity model incorporating isotropic linear elasticity and rate-independent J 2 plas- ticity. The microstructural and component scale subdomains are modeled concurrently, with coupling via the Schwarz alternating method, which solves boundary-value problems in each subdomain separately and transfers solution information between subdomains via Dirichlet boundary conditions. Beyond cases studies in concurrent multiscale, we explore progress in crystal plastic- ity through modular designs, solution methodologies, model verification, and extensions to Sierra/SM and manycore applications. Advances in conformal microstructures having both hexahedral and tetrahedral workflows in Sculpt and Cubit are highlighted. A structure-property case study in two-phase metallic composites applies the Materials Knowledge System to local metrics for void evolution. Discussion includes lessons learned, future work, and a summary of funded efforts and proposed work. Finally, an appendix illustrates the need for two-way coupling through a single degree of freedom.« less

Spatio-temporal representativeness of ground-based downward solar radiation measurements

NASA Astrophysics Data System (ADS)

Schwarz, Matthias; Wild, Martin; Folini, Doris

2017-04-01

Surface solar radiation (SSR) is most directly observed with ground based pyranometer measurements. Besides measurement uncertainties, which arise from the pyranometer instrument itself, also errors attributed to the limited spatial representativeness of observations from single sites for their large-scale surrounding have to be taken into account when using such measurements for energy balance studies. In this study the spatial representativeness of 157 homogeneous European downward surface solar radiation time series from the Global Energy Balance Archive (GEBA) and the Baseline Surface Radiation Network (BSRN) were examined for the period 1983-2015 by using the high resolution (0.05°) surface solar radiation data set from the Satellite Application Facility on Climate Monitoring (CM-SAF SARAH) as a proxy for the spatiotemporal variability of SSR. By correlating deseasonalized monthly SSR time series form surface observations against single collocated satellite derived SSR time series, a mean spatial correlation pattern was calculated and validated against purely observational based patterns. Generally decreasing correlations with increasing distance from station, with high correlations (R2 = 0.7) in proximity to the observational sites (±0.5°), was found. When correlating surface observations against time series from spatially averaged satellite derived SSR data (and thereby simulating coarser and coarser grids), very high correspondence between sites and the collocated pixels has been found for pixel sizes up to several degrees. Moreover, special focus was put on the quantification of errors which arise in conjunction to spatial sampling when estimating the temporal variability and trends for a larger region from a single surface observation site. For 15-year trends on a 1° grid, errors due to spatial sampling in the order of half of the measurement uncertainty for monthly mean values were found.

Downscaling of Aircraft-, Landsat-, and MODIS-based Land Surface Temperature Images with Support Vector Machines

NASA Astrophysics Data System (ADS)

Ha, W.; Gowda, P. H.; Oommen, T.; Howell, T. A.; Hernandez, J. E.

2010-12-01

High spatial resolution Land Surface Temperature (LST) images are required to estimate evapotranspiration (ET) at a field scale for irrigation scheduling purposes. Satellite sensors such as Landsat 5 Thematic Mapper (TM) and Moderate Resolution Imaging Spectroradiometer (MODIS) can offer images at several spectral bandwidths including visible, near-infrared (NIR), shortwave-infrared, and thermal-infrared (TIR). The TIR images usually have coarser spatial resolutions than those from non-thermal infrared bands. Due to this technical constraint of the satellite sensors on these platforms, image downscaling has been proposed in the field of ET remote sensing. This paper explores the potential of the Support Vector Machines (SVM) to perform downscaling of LST images derived from aircraft (4 m spatial resolution), TM (120 m), and MODIS (1000 m) using normalized difference vegetation index images derived from simultaneously acquired high resolution visible and NIR data (1 m for aircraft, 30 m for TM, and 250 m for MODIS). The SVM is a new generation machine learning algorithm that has found a wide application in the field of pattern recognition and time series analysis. The SVM would be ideally suited for downscaling problems due to its generalization ability in capturing non-linear regression relationship between the predictand and the multiple predictors. Remote sensing data acquired over the Texas High Plains during the 2008 summer growing season will be used in this study. Accuracy assessment of the downscaled 1, 30, and 250 m LST images will be made by comparing them with LST data measured with infrared thermometers at a small spatial scale, upscaled 30 m aircraft-based LST images, and upscaled 250 m TM-based LST images, respectively.

Near-infrared spectral mapping of Titan's mountains and channels

USGS Publications Warehouse

Barnes, J.W.; Radebaugh, J.; Brown, R.H.; Wall, S.; Soderblom, L.; Lunine, J.; Burr, D.; Sotin, Christophe; Le, Mouelic S.; Rodriguez, S.; Buratti, B.J.; Clark, R.; Baines, K.H.; Jaumann, R.; Nicholson, P.D.; Kirk, R.L.; Lopes, R.; Lorenz, R.D.; Mitchell, Ken; Wood, C.A.

2007-01-01

We investigate the spectral reflectance properties of channels and mountain ranges on Titan using data from Cassini's Visual and Infrared Mapping Spectrometer (VIMS) obtained during the T9 encounter (26 December 2005). We identify the location of channels and mountains using synthetic aperture radar maps obtained from Cassini's RADAR instrument during the T13 (30 April 2006) flyby. Channels are evident even in VIMS imaging with spatial resolution coarser than the channel size. The channels share spectral characteristics with Titan's dark blue terrain (e.g., the Huygens landing site) that is consistent with an enhancement in water ice content relative to the rest of Titan. We use this fact to measure widths of ???1 km for the largest channels. Comparison of the data sets shows that in our study area within the equatorial bright spectral unit east of Xanadu, mountains are darker and bluer than surrounding smooth terrain. These results are consistent with the equatorial bright terrain possessing a veneer of material that is thinner in the regions where there are mountains and streambeds that have likely undergone more recent and extensive erosion. We suggest a model for the geographic relationship of the dark blue, dark brown, and equatorial bright spectral units based on our findings. Copyright 2007 by the American Geophysical Union.

Land surface temperature downscaling using random forest regression: primary result and sensitivity analysis

NASA Astrophysics Data System (ADS)

Pan, Xin; Cao, Chen; Yang, Yingbao; Li, Xiaolong; Shan, Liangliang; Zhu, Xi

2018-04-01

The land surface temperature (LST) derived from thermal infrared satellite images is a meaningful variable in many remote sensing applications. However, at present, the spatial resolution of the satellite thermal infrared remote sensing sensor is coarser, which cannot meet the needs. In this study, LST image was downscaled by a random forest model between LST and multiple predictors in an arid region with an oasis-desert ecotone. The proposed downscaling approach was evaluated using LST derived from the MODIS LST product of Zhangye City in Heihe Basin. The primary result of LST downscaling has been shown that the distribution of downscaled LST matched with that of the ecosystem of oasis and desert. By the way of sensitivity analysis, the most sensitive factors to LST downscaling were modified normalized difference water index (MNDWI)/normalized multi-band drought index (NMDI), soil adjusted vegetation index (SAVI)/ shortwave infrared reflectance (SWIR)/normalized difference vegetation index (NDVI), normalized difference building index (NDBI)/SAVI and SWIR/NDBI/MNDWI/NDWI for the region of water, vegetation, building and desert, with LST variation (at most) of 0.20/-0.22 K, 0.92/0.62/0.46 K, 0.28/-0.29 K and 3.87/-1.53/-0.64/-0.25 K in the situation of +/-0.02 predictor perturbances, respectively.

Ensemble simulations to study the impact of land use change of Atlanta to regional climate

NASA Astrophysics Data System (ADS)

Liu, P.; Hu, Y.; Stone, B.; Vargo, J.; Nenes, A.; Russell, A.; Trail, M.; Tsimpidi, A.

2012-12-01

Studies show that urban areas may be the "first responders" to climate change (Rosenzweig et al., 2010). Of particular interest is the potential increased temperatures in urban areas, due to use of structures and surfaces that increase local heating, and how that may impact health, air quality and other environmental factors. In response, interest has grown as to how the modification of land use in urban areas, in order to mitigate the adverse effects of urbanization can serve to reduce local temperatures, and how climate is impacted more regionally. Studies have been conducted to investigate the impact of land use change on local or regional climate by dynamic downscaling using regional climate models (RCMs), the boundary conditions (BCs) and initial conditions (ICs) of which result from coarser-resolution reanalysis data or general circulation models (GCMs). However, few studies have focused on demonstrating whether the land use change in local areas significantly impacts the climate of the larger region of the domain, and the spatial scale of the impact from urban-scale changes. This work investigated the significance of the impact of land use change in the Atlanta city area on different scales, using a range of modeling resolutions, including the contiguous US (with 36km resolution), the southeastern US (with 12km resolution) and the state of Georgia (with 4km resolution). We used WRF version 3.1.1 with and ran continuous from June to August of a simulated year 2050, driven by GISS ModelE with inputs corresponding to RCP4.5. During the simulation, spectral nudging is used in the 36km resolution domain to maintain the climate patterns with scales larger than 2000km. Two-way nesting is also used in order to take into account the feedback of nesting domains across model domains. Two land use cases over the Atlanta city are chosen. For the base case, most of the urban area of Atlanta is covered with forest; while for the second, "impervious" case, all the urban area within 30 miles of the center of Atlanta is replaced with asphalt. This choice is made to maximize the potential effects and scales of impact. To make the two cases different as much as possible, a constant green vegetation fraction of 1.0 is assigned to the forest over the Atlanta; while 0.0 is assigned to the asphalt. To test the significance of the impact of land use change, 5 ensemble members were generated for each land use case using different initial conditions. The results of student's t test found that the impact of land use change in Atlanta city has a very local impact. This finding indicates that using WRF, applied at continental and regional scales, with BCs from the GCM and with spectral nudging, is appropriate. Although our results showed the impact is very local, results may change when meteorological conditions change or the area where land use changes is increased. Therefore, when investigating the land use change relevant issues, similar testing is suggested in order to demonstrate that the domain is large enough so that downscaling by RCMs is an appropriate approach. References: Rosenzweig, C., W. Solecki, S.A. Hammer, and S. Mehrotra, 2010: Cities lead the way in climate-change action. Nature, 467, 909-911, doi:10.1038/467909a

Potential Long-Term Records of Surface Albedo at Fine Spatiotemporal Resolution from Landsat/Sentinle-2A Surface Reflectance and MODIS/VIIRS BRDF

NASA Astrophysics Data System (ADS)

Li, Z.; Schaaf, C.; Shuai, Y.; Liu, Y.; Sun, Q.; Erb, A.; Wang, Z.

2016-12-01

The land surface albedo products at fine spatial resolutions are generated by coupling surface reflectance (SR) from Landsat (30 m) or Sentinel-2A (20 m) with concurrent surface anisotropy information (the Bidirectional Reflectance Distribution Function - BRDF) at coarser spatial resolutions from sequential multi-angular observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) or its successor, the Visible Infrared Imaging Radiometer Suite (VIIRS). We assess the comparability of four types of fine-resolution albedo products (black-sky and white-sky albedos over the shortwave broad band) generated by coupling, (1) Landsat-8 Optical Land Imager (OLI) SR with MODIS BRDF; (2) OLI SR with VIIRS BRDF; (3) Sentinel-2A MultiSpectral Instrument (MSI) SR with MODIS BRDF; and (4) MSI SR with VIIRS BRDF. We evaluate the accuracy of these four types of fine-resolution albedo products using ground tower measurements of surface albedo over six SURFace RADiation Network (SURFRAD) sites in the United States. For comparison with the ground measurements, we estimate the actual (blue-sky) albedo values at the six sites by using the satellite-based retrievals of black-sky and white-sky albedos and taking into account the proportion of direct and diffuse solar radiation from the ground measurements at the sites. The coupling of the OLI and MSI SR with MODIS BRDF has already been shown to provide accurate fine-resolution albedo values. With demonstration of a high agreement in BRDF products from MODIS and VIIRS, we expect to see consistency between all four types of fine-resolution albedo products. This assurance of consistency between the couplings of both OLI and MSI with both MODIS and VIIRS guarantees the production of long-term records of surface albedo at fine spatial resolutions and an increased temporal resolution. Such products will be critical in studying land surface changes and associated surface energy balance over the dynamic and heterogeneous landscapes most susceptible to climate change (such as arctic, coastal, and high-elevation zones).

Evaluation of CAESAR-Lisflood as a tool for modelling river channel change and floodplain sediment residence times.

NASA Astrophysics Data System (ADS)

Feeney, Christopher; Smith, Hugh; Chiverrell, Richard; Hooke, Janet; Cooper, James

2017-04-01

Sediment residence time represents the duration of particle storage, from initial deposition to remobilisation, within reservoirs such as floodplains. Residence time influences rates of downstream redistribution of sediment and associated contaminants and is a useful indicator of landform stability and hence, preservation potential of alluvial archives of environmental change. River channel change controls residence times, reworking sediments via lateral migration, avulsion and incision through floodplain deposits. As reworking progresses, the floodplain age distribution is 'updated', reflecting the time since 'older' sediments were removed and replaced with 'younger' ones. The relationship between ages and the spatial extents they occupy can be used to estimate the average floodplain sediment residence times. While dating techniques, historic maps and remote sensing can reconstruct age distributions from historic reworking, modelling provides advantages, including: i) capturing detailed river channel changes and resulting floodplain ages over longer timescales and higher resolutions than from historic mapping, and ii) control over inputs to simulate hypothetical scenarios to investigate the effects of different environmental drivers on residence times. CAESAR-Lisflood is a landform evolution model capable of simulating variable channel width, divergent flow, and both braided and meandering planforms. However, the model's ability to accurately simulate channel changes requires evaluation if it is to be useful for quantitative evaluation of floodplain sediment residence times. This study aims to simulate recent historic river channel changes along ten 1 km reaches in northern England. Simulation periods were defined by available overlapping historic map and mean daily flow datasets, ranging 27-39 years. LiDAR-derived 2 m DEMs were modified to smooth out present-day channels and burn in historic channel locations. To reduce run times, DEMs were resampled to coarser resolutions based on the size of the channel and historic rate of lateral channel migration. Separate pre-defined coarse and finer channel bed and floodplain grain size distributions were used, respectively, in combination with constructed reach DEMs for model simulations. Calibration was performed by modifying selected parameters to obtain best fits between observed and modelled channel planforms. Initial simulations suggest the model can broadly reproduce observed planform change and is comparable in terms of channel sinuosities and the mean radius of curvature. As such, CAESAR-Lisflood may provide a useful tool for evaluating floodplain sediment residence times under environmental change scenarios.

Are catchment-wide erosion rates really "Catchment-Wide"? Effects of grain size on erosion rates determined from 10Be

NASA Astrophysics Data System (ADS)

Reitz, M. A.; Seeber, L.; Schaefer, J. M.; Ferguson, E. K.

2012-12-01

Early studies pioneering the method for catchment wide erosion rates by measuring 10Be in alluvial sediment were taken at river mouths and used the sand size grain fraction from the riverbeds in order to average upstream erosion rates and measure erosion patterns. Finer particles (<0.0625 mm) were excluded to reduce the possibility of a wind-blown component of sediment and coarser particles (>2 mm) were excluded to better approximate erosion from the entire upstream catchment area (coarse grains are generally found near the source). Now that the sensitivity of 10Be measurements is rapidly increasing, we can precisely measure erosion rates from rivers eroding active tectonic regions. These active regions create higher energy drainage systems that erode faster and carry coarser sediment. In these settings, does the sand-sized fraction fully capture the average erosion of the upstream drainage area? Or does a different grain size fraction provide a more accurate measure of upstream erosion? During a study of the Neto River in Calabria, southern Italy, we took 8 samples along the length of the river, focusing on collecting samples just below confluences with major tributaries, in order to use the high-resolution erosion rate data to constrain tectonic motion. The samples we measured were sieved to either a 0.125 mm - 0.710 mm fraction or the 0.125 mm - 4 mm fraction (depending on how much of the former was available). After measuring these 8 samples for 10Be and determining erosion rates, we used the approach by Granger et al. [1996] to calculate the subcatchment erosion rates between each sample point. In the subcatchments of the river where we used grain sizes up to 4 mm, we measured very low 10Be concentrations (corresponding to high erosion rates) and calculated nonsensical subcatchment erosion rates (i.e. negative rates). We, therefore, hypothesize that the coarser grain sizes we included are preferentially sampling a smaller upstream area, and not the entire upstream catchment, which is assumed when measurements are based solely on the sand sized fraction. To test this hypothesis, we used samples with a variety of grain sizes from the Shillong Plateau. We sieved 5 samples into three grain size fractions: 0.125 mm - 710 mm, 710 mm - 4 mm, and >4 mm and measured 10Be concentrations in each fraction. Although there is some variation in the grain size fraction that yields the highest erosion rate, generally, the coarser grain size fractions have higher erosion rates. More significant are the results when calculating the subcatchment erosion rates, which suggest that even medium sized grains (710 mm - 4 mm) are sampling an area smaller than the entire upstream area; this finding is consistent with the nonsensical results from the Neto River study. This result has numerous implications for the interpretations of 10Be erosion rates: most importantly, an alluvial sample may not be averaging the entire upstream area, even when using the sand size fraction - resulting erosion rates more pertinent for that sample point rather than the entire catchment.

SeaWiFS technical report series. Volume 4: An analysis of GAC sampling algorithms. A case study

NASA Technical Reports Server (NTRS)

Yeh, Eueng-Nan (Editor); Hooker, Stanford B. (Editor); Hooker, Stanford B. (Editor); Mccain, Charles R. (Editor); Fu, Gary (Editor)

1992-01-01

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) instrument will sample at approximately a 1 km resolution at nadir which will be broadcast for reception by realtime ground stations. However, the global data set will be comprised of coarser four kilometer data which will be recorded and broadcast to the SeaWiFS Project for processing. Several algorithms for degrading the one kilometer data to four kilometer data are examined using imagery from the Coastal Zone Color Scanner (CZCS) in an effort to determine which algorithm would best preserve the statistical characteristics of the derived products generated from the one kilometer data. Of the algorithms tested, subsampling based on a fixed pixel within a 4 x 4 pixel array is judged to yield the most consistent results when compared to the one kilometer data products.

Observation-Corrected Precipitation Estimates in GEOS-5

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Liu, Qing

2014-01-01

Several GEOS-5 applications, including the GEOS-5 seasonal forecasting system and the MERRA-Land data product, rely on global precipitation data that have been corrected with satellite and or gauge-based precipitation observations. This document describes the methodology used to generate the corrected precipitation estimates and their use in GEOS-5 applications. The corrected precipitation estimates are derived by disaggregating publicly available, observationally based, global precipitation products from daily or pentad totals to hourly accumulations using background precipitation estimates from the GEOS-5 atmospheric data assimilation system. Depending on the specific combination of the observational precipitation product and the GEOS-5 background estimates, the observational product may also be downscaled in space. The resulting corrected precipitation data product is at the finer temporal and spatial resolution of the GEOS-5 background and matches the observed precipitation at the coarser scale of the observational product, separately for each day (or pentad) and each grid cell.

Asynchronous multilevel adaptive methods for solving partial differential equations on multiprocessors - Performance results

NASA Technical Reports Server (NTRS)

Mccormick, S.; Quinlan, D.

1989-01-01

The fast adaptive composite grid method (FAC) is an algorithm that uses various levels of uniform grids (global and local) to provide adaptive resolution and fast solution of PDEs. Like all such methods, it offers parallelism by using possibly many disconnected patches per level, but is hindered by the need to handle these levels sequentially. The finest levels must therefore wait for processing to be essentially completed on all the coarser ones. A recently developed asynchronous version of FAC, called AFAC, completely eliminates this bottleneck to parallelism. This paper describes timing results for AFAC, coupled with a simple load balancing scheme, applied to the solution of elliptic PDEs on an Intel iPSC hypercube. These tests include performance of certain processes necessary in adaptive methods, including moving grids and changing refinement. A companion paper reports on numerical and analytical results for estimating convergence factors of AFAC applied to very large scale examples.

GIS interpolations of witness tree records (1839-1866) for northern Wisconsin at multiple scales

USGS Publications Warehouse

He, H.S.; Mladenoff, D.J.; Sickley, T.A.; Guntenspergen, G.R.

2000-01-01

To construct forest landscape of pre-European settlement periods, we developed a GIS interpolation approach to convert witness tree records of the U.S. General Land Office (GLO) survey from point to polygon data, which better described continuously distributed vegetation. The witness tree records (1839-1866) were processed for a 3-million ha landscape in northern Wisconsin, U.S.A. at different scales. We provided implications of processing results at each scale. Compared with traditional GLO mapping that has fixed mapping scales and generalized classifications, our approach allows presettlement forest landscapes to be analysed at the individual species level and reconstructed under various classifications. We calculated vegetation indices including relative density, dominance, and importance value for each species, and quantitatively described the possible outcomes when GLO records are analysed at three different scales (resolution). The 1 x 1-section resolution preserved spatial information but derived the most conservative estimates of species distributions measured in percentage area, which increased at coarser resolutions. Such increases under the 2 x 2-section resolution were in the order of three to four times for the least common species, two to three times for the medium to most common species, and one to two times for the most common or highly contagious species. We marred the distributions of hemlock and sugar maple from the pre-European settlement period based on their witness tree locations and reconstructed presettlement forest landscapes based on species importance values derived for all species. The results provide a unique basis to further study land cover changes occurring after European settlement.

Can we map the interannual variability of the whole upper Southern Ocean with the current database of hydrographic observations?

NASA Astrophysics Data System (ADS)

Heuzé, C.; Vivier, F.; Le Sommer, J.; Molines, J.-M.; Penduff, T.

2015-12-01

With the advent of Argo floats, it now seems feasible to study the interannual variations of upper ocean hydrographic properties of the historically undersampled Southern Ocean. To do so, scattered hydrographic profiles often first need to be mapped. To investigate biases and errors associated both with the limited space-time distribution of the profiles and with the mapping methods, we colocate the mixed-layer depth (MLD) output from a state-of-the-art 1/12° DRAKKAR simulation onto the latitude, longitude, and date of actual in situ profiles from 2005 to 2014. We compare the results obtained after remapping using a nearest neighbor (NN) interpolation and an objective analysis (OA) with different spatiotemporal grid resolutions and decorrelation scales. NN is improved with a coarser resolution. OA performs best with low decorrelation scales, avoiding too strong a smoothing, but returns values over larger areas with large decorrelation scales and low temporal resolution, as more points are available. For all resolutions OA represents better the annual extreme values than NN. Both methods underestimate the seasonal cycle in MLD. MLD biases are lower than 10 m on average but can exceed 250 m locally in winter. We argue that current Argo data should not be mapped to infer decadal trends in MLD, as all methods are unable to reproduce existing trends without creating unrealistic extra ones. We also show that regions of the subtropical Atlantic, Indian, and Pacific Oceans, and the whole ice-covered Southern Ocean, still cannot be mapped even by the best method because of the lack of observational data.

Assessing the impacts of canopy openness and flight parameters on detecting a sub-canopy tropical invasive plant using a small unmanned aerial system

NASA Astrophysics Data System (ADS)

Perroy, Ryan L.; Sullivan, Timo; Stephenson, Nathan

2017-03-01

Small unmanned aerial systems (sUAS) have great potential to facilitate the early detection and management of invasive plants. Here we show how very high-resolution optical imagery, collected from small consumer-grade multirotor UAS platform at altitudes of 30-120 m above ground level (agl), can be used to detect individual miconia (Miconia calvescens) plants in a highly invaded tropical rainforest environment on the island of Hawai'i. The central aim of this research was to determine how overstory vegetation cover, imagery resolution, and camera look-angle impact the aerial detection of known individual miconia plants. For our finest resolution imagery (1.37 cm ground sampling distance collected at 30 m agl), we obtained a 100% detection rate for sub-canopy plants with above-crown openness values >40% and a 69% detection rate for those with >20% openness. We were unable to detect any plants with <10% above crown openness. Detection rates progressively declined with coarser spatial resolution imagery, ending in a 0% detection rate for the 120 m agl flights (ground sampling distance of 5.31 cm). The addition of forward-looking oblique imagery improved detection rates for plants below overstory vegetation, though this effect decreased with increasing flight altitude. While dense overstory canopy cover, limited flight times, and visual line of sight regulations present formidable obstacles for detecting miconia and other invasive plant species, we show that sUAS platforms carrying optical sensors can be an effective component of an integrated management plan within challenging subcanopy forest environments.

Remote Sensing of Snow Cover. Section; Snow Extent

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Frei, Allan; Drey, Stephen J.

2012-01-01

Snow was easily identified in the first image obtained from the Television Infrared Operational Satellite-1 (TIROS-1) weather satellite in 1960 because the high albedo of snow presents a good contrast with most other natural surfaces. Subsequently, the National Oceanic and Atmospheric Administration (NOAA) began to map snow using satellite-borne instruments in 1966. Snow plays an important role in the Earth s energy balance, causing more solar radiation to be reflected back into space as compared to most snow-free surfaces. Seasonal snow cover also provides a critical water resource through meltwater emanating from rivers that originate from high-mountain areas such as the Tibetan Plateau. Meltwater from mountain snow packs flows to some of the world s most densely-populated areas such as Southeast Asia, benefiting over 1 billion people (Immerzeel et al., 2010). In this section, we provide a brief overview of the remote sensing of snow cover using visible and near-infrared (VNIR) and passive-microwave (PM) data. Snow can be mapped using the microwave part of the electromagnetic spectrum, even in darkness and through cloud cover, but at a coarser spatial resolution than when using VNIR data. Fusing VNIR and PM algorithms to produce a blended product offers synergistic benefits. Snow-water equivalent (SWE), snow extent, and melt onset are important parameters for climate models and for the initialization of atmospheric forecasts at daily and seasonal time scales. Snowmelt data are also needed as input to hydrological models to improve flood control and irrigation management.

High-Throughput Phenotyping of Plant Height: Comparing Unmanned Aerial Vehicles and Ground LiDAR Estimates.

PubMed

Madec, Simon; Baret, Fred; de Solan, Benoît; Thomas, Samuel; Dutartre, Dan; Jezequel, Stéphane; Hemmerlé, Matthieu; Colombeau, Gallian; Comar, Alexis

2017-01-01

The capacity of LiDAR and Unmanned Aerial Vehicles (UAVs) to provide plant height estimates as a high-throughput plant phenotyping trait was explored. An experiment over wheat genotypes conducted under well watered and water stress modalities was conducted. Frequent LiDAR measurements were performed along the growth cycle using a phénomobile unmanned ground vehicle. UAV equipped with a high resolution RGB camera was flying the experiment several times to retrieve the digital surface model from structure from motion techniques. Both techniques provide a 3D dense point cloud from which the plant height can be estimated. Plant height first defined as the z -value for which 99.5% of the points of the dense cloud are below. This provides good consistency with manual measurements of plant height (RMSE = 3.5 cm) while minimizing the variability along each microplot. Results show that LiDAR and structure from motion plant height values are always consistent. However, a slight under-estimation is observed for structure from motion techniques, in relation with the coarser spatial resolution of UAV imagery and the limited penetration capacity of structure from motion as compared to LiDAR. Very high heritability values ( H 2 > 0.90) were found for both techniques when lodging was not present. The dynamics of plant height shows that it carries pertinent information regarding the period and magnitude of the plant stress. Further, the date when the maximum plant height is reached was found to be very heritable ( H 2 > 0.88) and a good proxy of the flowering stage. Finally, the capacity of plant height as a proxy for total above ground biomass and yield is discussed.

Functional exploratory data analysis for high-resolution measurements of urban particulate matter.

PubMed

Ranalli, M Giovanna; Rocco, Giorgia; Jona Lasinio, Giovanna; Moroni, Beatrice; Castellini, Silvia; Crocchianti, Stefano; Cappelletti, David

2016-09-01

In this work we propose the use of functional data analysis (FDA) to deal with a very large dataset of atmospheric aerosol size distribution resolved in both space and time. Data come from a mobile measurement platform in the town of Perugia (Central Italy). An OPC (Optical Particle Counter) is integrated on a cabin of the Minimetrò, an urban transportation system, that moves along a monorail on a line transect of the town. The OPC takes a sample of air every six seconds and counts the number of particles of urban aerosols with a diameter between 0.28 μm and 10 μm and classifies such particles into 21 size bins according to their diameter. Here, we adopt a 2D functional data representation for each of the 21 spatiotemporal series. In fact, space is unidimensional since it is measured as the distance on the monorail from the base station of the Minimetrò. FDA allows for a reduction of the dimensionality of each dataset and accounts for the high space-time resolution of the data. Functional cluster analysis is then performed to search for similarities among the 21 size channels in terms of their spatiotemporal pattern. Results provide a good classification of the 21 size bins into a relatively small number of groups (between three and four) according to the season of the year. Groups including coarser particles have more similar patterns, while those including finer particles show a more different behavior according to the period of the year. Such features are consistent with the physics of atmospheric aerosol and the highlighted patterns provide a very useful ground for prospective model-based studies. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High-Throughput Phenotyping of Plant Height: Comparing Unmanned Aerial Vehicles and Ground LiDAR Estimates

PubMed Central

Madec, Simon; Baret, Fred; de Solan, Benoît; Thomas, Samuel; Dutartre, Dan; Jezequel, Stéphane; Hemmerlé, Matthieu; Colombeau, Gallian; Comar, Alexis

2017-01-01

The capacity of LiDAR and Unmanned Aerial Vehicles (UAVs) to provide plant height estimates as a high-throughput plant phenotyping trait was explored. An experiment over wheat genotypes conducted under well watered and water stress modalities was conducted. Frequent LiDAR measurements were performed along the growth cycle using a phénomobile unmanned ground vehicle. UAV equipped with a high resolution RGB camera was flying the experiment several times to retrieve the digital surface model from structure from motion techniques. Both techniques provide a 3D dense point cloud from which the plant height can be estimated. Plant height first defined as the z-value for which 99.5% of the points of the dense cloud are below. This provides good consistency with manual measurements of plant height (RMSE = 3.5 cm) while minimizing the variability along each microplot. Results show that LiDAR and structure from motion plant height values are always consistent. However, a slight under-estimation is observed for structure from motion techniques, in relation with the coarser spatial resolution of UAV imagery and the limited penetration capacity of structure from motion as compared to LiDAR. Very high heritability values (H2> 0.90) were found for both techniques when lodging was not present. The dynamics of plant height shows that it carries pertinent information regarding the period and magnitude of the plant stress. Further, the date when the maximum plant height is reached was found to be very heritable (H2> 0.88) and a good proxy of the flowering stage. Finally, the capacity of plant height as a proxy for total above ground biomass and yield is discussed. PMID:29230229

Numerical Upscaling of Solute Transport in Fractured Porous Media Based on Flow Aligned Blocks

NASA Astrophysics Data System (ADS)

Leube, P.; Nowak, W.; Sanchez-Vila, X.

2013-12-01

High-contrast or fractured-porous media (FPM) pose one of the largest unresolved challenges for simulating large hydrogeological systems. The high contrast in advective transport between fast conduits and low-permeability rock matrix, including complex mass transfer processes, leads to the typical complex characteristics of early bulk arrivals and long tailings. Adequate direct representation of FPM requires enormous numerical resolutions. For large scales, e.g. the catchment scale, and when allowing for uncertainty in the fracture network architecture or in matrix properties, computational costs quickly reach an intractable level. In such cases, multi-scale simulation techniques have become useful tools. They allow decreasing the complexity of models by aggregating and transferring their parameters to coarser scales and so drastically reduce the computational costs. However, these advantages come at a loss of detail and accuracy. In this work, we develop and test a new multi-scale or upscaled modeling approach based on block upscaling. The novelty is that individual blocks are defined by and aligned with the local flow coordinates. We choose a multi-rate mass transfer (MRMT) model to represent the remaining sub-block non-Fickian behavior within these blocks on the coarse scale. To make the scale transition simple and to save computational costs, we capture sub-block features by temporal moments (TM) of block-wise particle arrival times to be matched with the MRMT model. By predicting spatial mass distributions of injected tracers in a synthetic test scenario, our coarse-scale solution matches reasonably well with the corresponding fine-scale reference solution. For predicting higher TM-orders (such as arrival time and effective dispersion), the prediction accuracy steadily decreases. This is compensated to some extent by the MRMT model. If the MRMT model becomes too complex, it loses its effect. We also found that prediction accuracy is sensitive to the choice of the effective dispersion coefficients and on the block resolution. A key advantage of the flow-aligned blocks is that the small-scale velocity field is reproduced quite accurately on the block-scale through their flow alignment. Thus, the block-scale transverse dispersivities remain in the similar magnitude as local ones, and they do not have to represent macroscopic uncertainty. Also, the flow-aligned blocks minimize numerical dispersion when solving the large-scale transport problem.

Projected climatic changes on drought conditions over Spain

NASA Astrophysics Data System (ADS)

García-Valdecasas Ojeda, Matilde; Quishpe-Vásquez, César; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

In a context of global warming, the evapotranspiration processes will have a strong influence on drought severity. For this reason, the Standardized Precipitation Evapotranspiration Index (SPEI) was computed at different timescales in order to explore the projected drought changes for the main watersheds in Spain. For that, the Weather Research and Forecasting (WRF) model has been used in order to obtain current (1980-2010) and future (2021-2050 and 2071-2100) climate output fields. WRF model was used over a domain that spans the Iberian Peninsula with a spatial resolution of 0.088°, and nested in the coarser 0.44° EURO-CORDEX domain, and driving by the global bias-corrected climate model output data from version 1 of NCAR's Community Earth System Model (CESM1), using two different Representative Concentration Pathway (RCP) scenarios: RCP 4.5 and RCP 8.5. Besides, to examine the behavior of this drought index, a comparison with the Standardized Precipitation Index (SPI), which does not consider the evapotranspiration effects, was also performed. Additionally the relationship between the SPEI index and the soil moisture has also been analyzed. The results of this study suggest an increase in the severity and duration of drought, being larger when the SPEI index is used to define drought events. This fact confirms the relevance of taking into account the evapotranspiration processes to detect future drought events. The results also show a noticeable relationship between the SPEI and the simulated soil moisture content, which is more significant at higher timescales. Keywords: Drought, SPEI, SPI, Climatic change, Projections, WRF. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model. 3; Disaggregation

NASA Technical Reports Server (NTRS)

Caulfield, John; Crosson, William L.; Inguva, Ramarao; Laymon, Charles A.; Schamschula, Marius

1998-01-01

This is a followup on the preceding presentation by Crosson and Schamschula. The grid size for remote microwave measurements is much coarser than the hydrological model computational grids. To validate the hydrological models with measurements we propose mechanisms to disaggregate the microwave measurements to allow comparison with outputs from the hydrological models. Weighted interpolation and Bayesian methods are proposed to facilitate the comparison. While remote measurements occur at a large scale, they reflect underlying small-scale features. We can give continuing estimates of the small scale features by correcting the simple 0th-order, starting with each small-scale model with each large-scale measurement using a straightforward method based on Kalman filtering.

A theoretically consistent stochastic cascade for temporal disaggregation of intermittent rainfall

NASA Astrophysics Data System (ADS)

Lombardo, F.; Volpi, E.; Koutsoyiannis, D.; Serinaldi, F.

2017-06-01

Generating fine-scale time series of intermittent rainfall that are fully consistent with any given coarse-scale totals is a key and open issue in many hydrological problems. We propose a stationary disaggregation method that simulates rainfall time series with given dependence structure, wet/dry probability, and marginal distribution at a target finer (lower-level) time scale, preserving full consistency with variables at a parent coarser (higher-level) time scale. We account for the intermittent character of rainfall at fine time scales by merging a discrete stochastic representation of intermittency and a continuous one of rainfall depths. This approach yields a unique and parsimonious mathematical framework providing general analytical formulations of mean, variance, and autocorrelation function (ACF) for a mixed-type stochastic process in terms of mean, variance, and ACFs of both continuous and discrete components, respectively. To achieve the full consistency between variables at finer and coarser time scales in terms of marginal distribution and coarse-scale totals, the generated lower-level series are adjusted according to a procedure that does not affect the stochastic structure implied by the original model. To assess model performance, we study rainfall process as intermittent with both independent and dependent occurrences, where dependence is quantified by the probability that two consecutive time intervals are dry. In either case, we provide analytical formulations of main statistics of our mixed-type disaggregation model and show their clear accordance with Monte Carlo simulations. An application to rainfall time series from real world is shown as a proof of concept.

An application of statistical mechanics for representing equilibrium perimeter distributions of tropical convective clouds

NASA Astrophysics Data System (ADS)

Garrett, T. J.; Alva, S.; Glenn, I. B.; Krueger, S. K.

2015-12-01

There are two possible approaches for parameterizing sub-grid cloud dynamics in a coarser grid model. The most common is to use a fine scale model to explicitly resolve the mechanistic details of clouds to the best extent possible, and then to parameterize these behaviors cloud state for the coarser grid. A second is to invoke physical intuition and some very general theoretical principles from equilibrium statistical mechanics. This approach avoids any requirement to resolve time-dependent processes in order to arrive at a suitable solution. The second approach is widely used elsewhere in the atmospheric sciences: for example the Planck function for blackbody radiation is derived this way, where no mention is made of the complexities of modeling a large ensemble of time-dependent radiation-dipole interactions in order to obtain the "grid-scale" spectrum of thermal emission by the blackbody as a whole. We find that this statistical approach may be equally suitable for modeling convective clouds. Specifically, we make the physical argument that the dissipation of buoyant energy in convective clouds is done through mixing across a cloud perimeter. From thermodynamic reasoning, one might then anticipate that vertically stacked isentropic surfaces are characterized by a power law dlnN/dlnP = -1, where N(P) is the number clouds of perimeter P. In a Giga-LES simulation of convective clouds within a 100 km square domain we find that such a power law does appear to characterize simulated cloud perimeters along isentropes, provided a sufficient cloudy sample. The suggestion is that it may be possible to parameterize certain important aspects of cloud state without appealing to computationally expensive dynamic simulations.

Environmental Controls on Multi-Scale Soil Nutrient Variability in the Tropics: the Importance of Land-Cover Change

NASA Astrophysics Data System (ADS)

Holmes, K. W.; Kyriakidis, P. C.; Chadwick, O. A.; Matricardi, E.; Soares, J. V.; Roberts, D. A.

2003-12-01

The natural controls on soil variability and the spatial scales at which correlation exists among soil and environmental variables are critical information for evaluating the effects of deforestation. We detect different spatial scales of variability in soil nutrient levels over a large region (hundreds of thousands of km2) in the Amazon, analyze correlations among soil properties at these different scales, and evaluate scale-specific relationships among soil properties and the factors potentially driving soil development. Statistical relationships among physical drivers of soil formation, namely geology, precipitation, terrain attributes, classified soil types, and land cover derived from remote sensing, were included to determine which factors are related to soil biogeochemistry at each spatial scale. Surface and subsurface soil profile data from a 3000 sample database collected in Rond“nia, Brazil, were used to investigate patterns in pH, phosphorus, nitrogen, organic carbon, effective cation exchange capacity, calcium, magnesium, potassium, aluminum, sand, and clay in this environment grading from closed canopy tropical forest to savanna. We focus on pH in this presentation for simplicity, because pH is the single most important soil characteristic for determining the chemical environment of higher plants and soil microbial activity. We determined four spatial scales which characterize integrated patterns of soil chemistry: less than 3 km; 3 to 10 km; 10 to 68 km; and from 68 to 550 km (extent of study area). Although the finest observable scale was fixed by the field sampling density, the coarser scales were determined from relationships in the data through coregionalization modeling, rather than being imposed by the researcher. Processes which affect soils over short distances, such as land cover and terrain attributes, were good predictors of fine scale spatial components of nutrients; processes which affect soils over very large distances, such as precipitation and geology, were better predictors at coarse spatial scales. However, this result may be affected by the resolution of the available predictor maps. Land-cover change exerted a strong influence on soil chemistry at fine spatial scales, and had progressively less of an effect at coarser scales. It is important to note that land cover, and interactions among land cover and the other predictors, continued to be a significant predictor of soil chemistry at every spatial scale up to hundreds of thousands of kilometers.

Surface-water radon-222 distribution along the west-central Florida shelf

USGS Publications Warehouse

Smith, C.G.; Robbins, L.L.

2012-01-01

In February 2009 and August 2009, the spatial distribution of radon-222 in surface water was mapped along the west-central Florida shelf as collaboration between the Response of Florida Shelf Ecosystems to Climate Change project and a U.S. Geological Survey Mendenhall Research Fellowship project. This report summarizes the surface distribution of radon-222 from two cruises and evaluates potential physical controls on radon-222 fluxes. Radon-222 is an inert gas produced overwhelmingly in sediment and has a short half-life of 3.8 days; activities in surface water ranged between 30 and 170 becquerels per cubic meter. Overall, radon-222 activities were enriched in nearshore surface waters relative to offshore waters. Dilution in offshore waters is expected to be the cause of the low offshore activities. While thermal stratification of the water column during the August survey may explain higher radon-222 activities relative to the February survey, radon-222 activity and integrated surface-water inventories decreased exponentially from the shoreline during both cruises. By estimating radon-222 evasion by wind from nearby buoy data and accounting for internal production from dissolved radium-226, its radiogenic long-lived parent, a simple one-dimensional model was implemented to determine the role that offshore mixing, benthic influx, and decay have on the distribution of excess radon-222 inventories along the west Florida shelf. For multiple statistically based boundary condition scenarios (first quartile, median, third quartile, and maximum radon-222 inshore of 5 kilometers), the cross-shelf mixing rates and average nearshore submarine groundwater discharge (SGD) rates varied from 100.38 to 10-3.4 square kilometers per day and 0.00 to 1.70 centimeters per day, respectively. This dataset and modeling provide the first attempt to assess cross-shelf mixing and SGD on such a large spatial scale. Such estimates help scale up SGD rates that are often made at 1- to 10-meter resolution to a coarser but more regionally applicable scale of 1- to 10-kilometer resolution. More stringent analyses and model evaluation are required, but results and analyses presented in this report provide the foundation for conducting a more rigorous statistical assessment.

Evaluation and sensitivity testing of a coupled Landsat-MODIS downscaling method for land surface temperature and vegetation indices in semi-arid regions

NASA Astrophysics Data System (ADS)

Kim, Jongyoun; Hogue, Terri S.

2012-01-01

The current study investigates a method to provide land surface parameters [i.e., land surface temperature (LST) and normalized difference vegetation index (NDVI)] at a high spatial (˜30 and 60 m) and temporal (daily and 8-day) resolution by combining advantages from Landsat and moderate-resolution imaging spectroradiometer (MODIS) satellites. We adopt a previously developed subtraction method that merges the spatial detail of higher-resolution imagery (Landsat) with the temporal change observed in coarser or moderate-resolution imagery (MODIS). Applying the temporal difference between MODIS images observed at two different dates to a higher-resolution Landsat image allows prediction of a combined or fused image (Landsat+MODIS) at a future date. Evaluation of the resultant merged products is undertaken within the Southeastern Arizona region where data is available from a range of flux tower sites. The Landsat+MODIS fused products capture the raw Landsat values and also reflect the MODIS temporal variation. The predicted Landsat+MODIS LST improves mean absolute error around 5°C at the more heterogeneous sites compared to the original satellite products. The fused Landsat+MODIS NDVI product also shows good correlation to ground-based data and is relatively consistent except during the acute (monsoon) growing season. The sensitivity of the fused product relative to temporal gaps in Landsat data appears to be more affected by uncertainty associated with regional precipitation and green-up, than the length of the gap associated with Landsat viewing, suggesting the potential to use a minimal number of original Landsat images during relatively stable land surface and climate conditions. Our extensive validation yields insight on the ability of the proposed method to integrate multiscale platforms and the potential for reducing costs associated with high-resolution satellite systems (e.g., SPOT, QuickBird, IKONOS).

Transitional hemodynamics in intracranial aneurysms - Comparative velocity investigations with high resolution lattice Boltzmann simulations, normal resolution ANSYS simulations, and MR imaging.

PubMed

Jain, Kartik; Jiang, Jingfeng; Strother, Charles; Mardal, Kent-André

2016-11-01

Blood flow in intracranial aneurysms has, until recently, been considered to be disturbed but still laminar. Recent high resolution computational studies have demonstrated, in some situations, however, that the flow may exhibit high frequency fluctuations that resemble weakly turbulent or transitional flow. Due to numerous assumptions required for simplification in computational fluid dynamics (CFD) studies, the occurrence of these events, in vivo, remains unsettled. The detection of these fluctuations in aneurysmal blood flow, i.e., hemodynamics by CFD, poses additional challenges as such phenomena cannot be captured in clinical data acquisition with magnetic resonance (MR) due to inadequate temporal and spatial resolutions. The authors' purpose was to address this issue by comparing results from highly resolved simulations, conventional resolution laminar simulations, and MR measurements, identify the differences, and identify their causes. Two aneurysms in the basilar artery, one with disturbed yet laminar flow and the other with transitional flow, were chosen. One set of highly resolved direct numerical simulations using the lattice Boltzmann method (LBM) and another with adequate resolutions under laminar flow assumption were conducted using a commercially available ANSYS Fluent solver. The velocity fields obtained from simulation results were qualitatively and statistically compared against each other and with MR acquisition. Results from LBM, ANSYS Fluent, and MR agree well qualitatively and quantitatively for one of the aneurysms with laminar flow in which fluctuations were <80 Hz. The comparisons for the second aneurysm with high fluctuations of > ∼ 600 Hz showed vivid differences between LBM, ANSYS Fluent, and magnetic resonance imaging. After ensemble averaging and down-sampling to coarser space and time scales, these differences became minimal. A combination of MR derived data and CFD can be helpful in estimating the hemodynamic environment of intracranial aneurysms. Adequately resolved CFD would suffice gross assessment of hemodynamics, potentially in a clinical setting, and highly resolved CFD could be helpful in a detailed and retrospective understanding of the physiological mechanisms.

Understanding Multifunctional Agricultural Land by Using Low Cost and Open Source Solutions to Quantify Ecosystem Function and Services

NASA Astrophysics Data System (ADS)

Forsmoo, Joel; Anderson, Karen; Brazier, Richard; Macleod, Kit; Wilkinson, Mark

2016-04-01

There is a need to advance our understanding of how the spatial structure of farmed landscapes contributes to the provision of functions and services. Agricultural land is of critical importance in NW Europe, covering large parts of NW Europe's temperate land. Moreover, these agricultural areas are primarily intensively managed, with a focus on maximizing food and fibre production. Such landscapes therefore can provide a wealth of ecosystem goods and services (ESs) including regulation of climate, erosion regulation, hydrology, water quality, nutrient cycling and biodiversity conservation. However, it has been shown they are key sources of sediment, phosphorous, nitrogen and storm runoff contributing to flooding, and therefore it is likely that most agricultural landscapes do not maximize the services or benefits that they might provide. The focus of this study is the spatio-temporal assessment of carbon sequestration (particularly through proxies such as above-ground biomass) and hydrological processes on agricultural land. Understanding and quantifying both of these is important to (a) inform payments for ecosystem services frameworks, (b) evaluate and improve carbon sequestration models, (c) manage the flood risk, (d) downstream water security and (e) water quality. Quantifying both of these ESs is dependent on data describing the fine spatial and temporal structure and function of the landscape. Common practice has been to use remote sensing techniques, e.g. satellites, providing coarse spatial resolution (around 30cm at 20° off nadir) and/or temporal resolution (around 5 days revisit time at <20° off nadir). In this paper we will explain how imaging data from lightweight and easily deployed unmanned aerial vehicles (UAVs) can be used to generate structure from motion (SFM) products describing the very fine detailed (<3 cm pixel resolution) structure of the agricultural environment. We will demonstrate how these products can be delivered using advanced free and open source post-processing alternatives and low cost sensors (digital cameras) and platforms (UAVs). We furthermore draw attention to the influence post-processing solutions have on the accuracy of the final product, the digital surface model (DSM), by using recently acquired data. Specifically, when applied in a structurally complex field site with irregular surface roughness patterns, over a land use gradient, from livestock grazing to agricultural crops. We will demonstrate the added value of using very fine detail data, highlighting important structural properties and patterns overlooked with coarser spatial resolution data.

An Engineering Solution for Solving Mesh Size Effects in the Simulation of Delamination with Cohesive Zone Models

NASA Technical Reports Server (NTRS)

Turon, A.; Davila, C. G.; Camanho, P. P.; Costa, J.

2007-01-01

This paper presents a methodology to determine the parameters to be used in the constitutive equations of Cohesive Zone Models employed in the simulation of delamination in composite materials by means of decohesion finite elements. A closed-form expression is developed to define the stiffness of the cohesive layer. A novel procedure that allows the use of coarser meshes of decohesion elements in large-scale computations is also proposed. The procedure ensures that the energy dissipated by the fracture process is computed correctly. It is shown that coarse-meshed models defined using the approach proposed here yield the same results as the models with finer meshes normally used for the simulation of fracture processes.

The modelled surface mass balance of the Antarctic Peninsula at 5.5 km horizontal resolution

NASA Astrophysics Data System (ADS)

van Wessem, J. M.; Ligtenberg, S. R. M.; Reijmer, C. H.; van de Berg, W. J.; van den Broeke, M. R.; Barrand, N. E.; Thomas, E. R.; Turner, J.; Wuite, J.; Scambos, T. A.; van Meijgaard, E.

2015-09-01

This study presents a high-resolution (~ 5.5 km) estimate of Surface Mass Balance (SMB) over the period 1979-2014 for the Antarctic Peninsula (AP), generated by the regional atmospheric climate model RACMO2.3 and a Firn Densification Model (FDM). RACMO2.3 is used to force the FDM, which calculates processes in the snowpack, such as meltwater percolation, refreezing and runoff. We evaluate model output with 132 in-situ SMB observations and discharge rates from 6 glacier drainage basins, and find that the model realistically simulates the strong spatial variability in precipitation, but that significant biases remain as a result of the highly complex topography of the AP. It is also clear that the observations significantly underrepresent the high-accumulation regimes. The SMB map reveals large accumulation gradients, with precipitation values above 3000 mm we yr-1 over the western AP (WAP) and below 500 mm we yr-1 on the eastern AP (EAP), not resolved by coarser data-sets such as ERA-Interim. The other SMB components are one order of magnitude smaller, with drifting snow sublimation the largest ablation term removing up to 100 mm we yr-1 of mass. Snowmelt is widespread over the AP, reaching 500 mm we yr-1 towards the northern ice shelves, but the meltwater mostly refreezes. As a result runoff fluxes are low, but still considerable (200 mm we yr-1) over the Larsen (B/C), Wilkins and George VI ice shelves. The average AP ice sheet integrated SMB, including ice shelves (an area of 4.1 × 105 km2), is estimated at 351 Gt yr-1 with an interannual variability of 58 Gt yr-1, which is dominated by precipitation (PR) (365 ± 57 Gt yr-1). The WAP (2.4 × 105 km2) SMB (276 ± 47 Gt yr-1), where PR is large (276 ± 47 Gt yr-1), dominates over the EAP (1.7 × 105 km2) SMB (75 ± 11 Gt yr-1) and PR (84 ± 11 Gt yr-1). Total sublimation is 11 ± 2 Gt yr-1 and meltwater runoff into the ocean is 4 ± 4 Gt yr-1. There are no significant trends in any of the AP SMB components, except for snowmelt that shows a significant decrease over the last 36 years (-0.36 Gt yr-2).

Drought and heatwaves in Europe: historical reconstruction and future projections

NASA Astrophysics Data System (ADS)

Samaniego, Luis; Thober, Stephan; Kumar, Rohini; Rakovec, Olda; Wood, Eric; Sheffield, Justin; Pan, Ming; Wanders, Niko; Prudhomme, Christel

2017-04-01

Heat waves and droughts are creeping hydro-meteorological events that may bring societies and natural systems to their limits by inducing large famines, increasing health risks to the population, creating drinking and irrigation water shortfalls, inducing natural fires and degradation of soil and water quality, and in many cases causing large socio-economic losses. Europe, in particular, has endured large scale drought-heat-wave events during the recent past (e.g., 2003 European drought), which have induced enormous socio-economic losses as well as casualties. Recent studies showed that the prediction of droughts and heatwaves is subject to large-scale forcing and parametric uncertainties that lead to considerable uncertainties in the projections of extreme characteristics such as drought magnitude/duration and area under drought, among others. Future projections are also heavily influenced by the RCP scenario uncertainty as well as the coarser spatial resolution of the models. The EDgE project funded by the Copernicus programme (C3S) provides an unique opportunity to investigate the evolution of droughts and heatwaves from 1950 until 2099 over the Pan-EU domain at a scale of 5x5 km2. In this project, high-resolution multi-model hydrologic simulations with the mHM (www.ufz.de/mhm), Noah-MP, VIC and PCR-GLOBWB have been completed for the historical period 1955-2015. Climate projections have been carried out with five CMIP-5 GCMs: GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1-M from 2006 to 2099 under RCP2.6 and RCP8.5. Using these multi-model unprecedented simulations, daily soil moisture index and temperature anomalies since 1955 until 2099 will be estimated. Using the procedure proposed by Samaniego et al. (2013), the probabilities of exceeding the benchmark events in the reference period 1980-2010 will be estimated for each RCP scenario. References http://climate.copernicus.eu/edge-end-end-demonstrator-improved-decision-making-water-sector-europe Samaniego, L., R. Kumar, and M. Zink, 2013: Implications of parameter uncertainty on soil moisture drought analysis in Germany. J. Hydrometeor., 14, 47-68, doi:10.1175/JHM-D-12-075.1. Samaniego, L., et al. 2016: Propagation of forcing and model uncertainties on to hydrological drought characteristics in a multi-model century-long experiment in large river basins. Climatic Change. 1-15.

On the use of kinetic energy preserving DG-schemes for large eddy simulation

NASA Astrophysics Data System (ADS)

Flad, David; Gassner, Gregor

2017-12-01

Recently, element based high order methods such as Discontinuous Galerkin (DG) methods and the closely related flux reconstruction (FR) schemes have become popular for compressible large eddy simulation (LES). Element based high order methods with Riemann solver based interface numerical flux functions offer an interesting dispersion dissipation behavior for multi-scale problems: dispersion errors are very low for a broad range of scales, while dissipation errors are very low for well resolved scales and are very high for scales close to the Nyquist cutoff. In some sense, the inherent numerical dissipation caused by the interface Riemann solver acts as a filter of high frequency solution components. This observation motivates the trend that element based high order methods with Riemann solvers are used without an explicit LES model added. Only the high frequency type inherent dissipation caused by the Riemann solver at the element interfaces is used to account for the missing sub-grid scale dissipation. Due to under-resolution of vortical dominated structures typical for LES type setups, element based high order methods suffer from stability issues caused by aliasing errors of the non-linear flux terms. A very common strategy to fight these aliasing issues (and instabilities) is so-called polynomial de-aliasing, where interpolation is exchanged with projection based on an increased number of quadrature points. In this paper, we start with this common no-model or implicit LES (iLES) DG approach with polynomial de-aliasing and Riemann solver dissipation and review its capabilities and limitations. We find that the strategy gives excellent results, but only when the resolution is such, that about 40% of the dissipation is resolved. For more realistic, coarser resolutions used in classical LES e.g. of industrial applications, the iLES DG strategy becomes quite inaccurate. We show that there is no obvious fix to this strategy, as adding for instance a sub-grid-scale models on top doesn't change much or in worst case decreases the fidelity even more. Finally, the core of this work is a novel LES strategy based on split form DG methods that are kinetic energy preserving. The scheme offers excellent stability with full control over the amount and shape of the added artificial dissipation. This premise is the main idea of the work and we will assess the LES capabilities of the novel split form DG approach when applied to shock-free, moderate Mach number turbulence. We will demonstrate that the novel DG LES strategy offers similar accuracy as the iLES methodology for well resolved cases, but strongly increases fidelity in case of more realistic coarse resolutions.

Projection of Changes in Regional Climate and Air Quality in the Great Lakes Basin between 2000 and 2050 for the RCP8.5 Emissions Scenario using the GEM-AQ Model

NASA Astrophysics Data System (ADS)

Lupu, A.; Semeniuk, K.; McConnell, J. C.; Kaminski, J. W.; Toyota, K.; Neary, L.

2012-12-01

The Global Environmental Multiscale Air Quality (GEM-AQ) model was run in global and limited area model (LAM) modes for the baseline year 2000 and one future year, 2050, on three different horizontal grids of increasing resolution from global (1.5°) to North American (LAM, 0.45°) to Ontario regional scale (LAM, 0.15°). For the future simulation we used the high greenhouse emissions scenario RCP8.5. Boundary conditions for the LAM runs were taken from the coarser resolution runs. All simulations had 54 vertical sigma-pressure hybrid levels from the ground to the stratopause (˜50 km), which should give a good representation of ozone injection to the troposphere from the stratosphere. The model uses the interactive land surface scheme ISBA. Sea surface and lake temperatures are prescribed, but ice cover is partially interactive based on prescribed fields. A lake model, FLAKE, was coupled to GEM-AQ in order to capture the impacts of the Great Lakes on the meteorology when the model is run at high resolution. For the Ontario regional simulation the interactive lake model allowed for self-consistent water temperatures and moisture fluxes. The simulation for the year 2000 shows that the model is able to reproduce the observed monthly surface temperatures across the US. The monthly surface ozone is reproduced at the level of detail of most other air quality models with year 2000 weather as opposed to a free run forced by SSTs. Our year 2050 simulation shows that ozone levels during the summer throughout most of Ontario and Canada will increase. Regions south of the latitude of Lake Superior will generally see decreased levels of summer (JJA) ozone, except for around large urban areas such as Toronto, Chicago and Montreal. However, NOx levels will decrease during the summer, reflecting decreased emissions. Ozone levels in the US will generally improve. Other indices rather than simple averages yield a different perspective. If the MDA8 ozone metric and NO2 one-hour 98th percentile are used, then it is found that air quality across Canada and US will generally improve. From the perspective of meteorology, the most significant surface warming that is likely to occur by 2050 is during winter. The winter warming also reflects changes in large scale circulation with baroclinic eddy storm tracks moving north. Winter warming contributes to a surface ozone increase by 2050 in spite of reduced emissions. In addition, we note that in the Ontario region and environs for 2050 there is a significant increase (˜40) in the number of DD5 days, i.e. days where the temperature is above 5°C, a metric useful for the length of the growing season for agriculture. This also means that conditions that impact forests and movement of disease vectors will also change.

Martian aeolian features and deposits - Comparisons with general circulation model results

NASA Astrophysics Data System (ADS)

Greeley, R.; Skypeck, A.; Pollack, J. B.

1993-02-01

The relationships between near-surface winds and the distribution of wind-related features are investigated by means of a general circulation model of Mars' atmosphere. Predictions of wind surface stress as a function of season and dust optical depth are used to investigate the distribution and orientation of wind streaks, yardangs, and rock abundance on the surface. The global distribution of rocks on the surface correlates well with predicted wind stress, particularly during the dust storm season. The rocky areas are sites of strong winds, suggesting that fine material is swept away by the wind, leaving rocks and coarser material behind.

Estimation of Spatial Trends in LAI in Heterogeneous Semi-arid Ecosystems using Full Waveform Lidar

NASA Astrophysics Data System (ADS)

Glenn, N. F.; Ilangakoon, N.; Spaete, L.; Dashti, H.

2017-12-01

Leaf area index (LAI) is a key structural trait that is defined by the plant functional type (PFT) and controlled by prevailing climate- and human-driven ecosystem stresses. Estimates of LAI using remote sensing techniques are limited by the uncertainties of vegetation inter and intra-gap fraction estimates; this is especially the case in sparse, low stature vegetated ecosystems. Small footprint full waveform lidar digitizes the total amount of return energy with the direction information as a near continuous waveform at a high vertical resolution (1 ns). Thus waveform lidar provides additional data matrices to capture vegetation gaps as well as PFTs that can be used to constrain the uncertainties of LAI estimates. In this study, we calculated a radiometrically calibrated full waveform parameter called backscatter cross section, along with other data matrices from the waveform to estimate vegetation gaps across plots (10 m x 10 m) in a semi-arid ecosystem in the western US. The LAI was then estimated using empirical relationships with directional gap fraction. Full waveform-derived gap fraction based LAI showed a high correlation with field observed shrub LAI (R2 = 0.66, RMSE = 0.24) compared to discrete return lidar based LAI (R2 = 0.01, RMSE = 0.5). The data matrices derived from full waveform lidar classified a number of deciduous and evergreen tree species, shrub species, and bare ground with an overall accuracy of 89% at 10 m. A similar analysis was performed at 1m with overall accuracy of 80%. The next step is to use these relationships to map the PFTs LAI at 10 m spatial scale across the larger study regions. The results show the exciting potential of full waveform lidar to identify plant functional types and LAI in low-stature vegetation dominated semi-arid ecosystems, an ecosystem in which many other remote sensing techniques fail. These results can be used to assess ecosystem state, habitat suitability as well as to constrain model uncertainties in vegetation dynamic models with a combination of other remote sensing techniques. Multi-spatial resolution (1 m and 10 m) studies provide basic information on the applicability and detection thresholds of future global satellite sensors designed at coarser spatial resolutions (e.g. GEDI, ICESat-2) in semi-arid ecosystems.

High-resolution humidity profiles retrieved from wind profiler radar measurements

NASA Astrophysics Data System (ADS)

Saïd, Frédérique; Campistron, Bernard; Di Girolamo, Paolo

2018-03-01

The retrieval of humidity profiles from wind profiler radars has already been documented in the past 30 years and is known to be neither as straightforward and nor as robust as the retrieval of the wind velocity. The main constraint to retrieve the humidity profile is the necessity to combine measurements from the wind profiler and additional measurements (such as observations from radiosoundings at a coarser time resolution). Furthermore, the method relies on some assumptions and simplifications that restrict the scope of its application. The first objective of this paper is to identify the obstacles and limitations and solve them, or at least define the field of applicability. To improve the method, we propose using the radar capacity to detect transition levels, such as the top level of the boundary layer, marked by a maximum in the radar reflectivity. This forces the humidity profile from the free troposphere and from the boundary layer to coincide at this level, after an optimization of the calibration coefficients, and reduces the error. The resulting mean bias affecting the specific humidity profile never exceeds 0.25 g kg-1. The second objective is to explore the capability of the algorithm to retrieve the humidity vertical profiles for an operational purpose by comparing the results with observations from a Raman lidar.

Assimilation of optical and radar remote sensing data in 3D mapping of soil properties over large areas.

PubMed

Poggio, Laura; Gimona, Alessandro

2017-02-01

Soil is very important for many land functions. To achieve sustainability it is important to understand how soils vary over space in the landscape. Remote sensing data can be instrumental in mapping and spatial modelling of soil properties, resources and their variability. The aims of this study were to compare satellite sensors (MODIS, Landsat, Sentinel-1 and Sentinel-2) with varying spatial, temporal and spectral resolutions for Digital Soil Mapping (DSM) of a set of soil properties in Scotland, evaluate the potential benefits of adding Sentinel-1 data to DSM models, select the most suited mix of sensors for DSM to map the considered set of soil properties and validate the results of topsoil (2D) and whole profile (3D) models. The results showed that the use of a mixture of sensors proved more effective to model and map soil properties than single sensors. The use of radar Sentinel-1 data proved useful for all soil properties, improving the prediction capability of models with only optical bands. The use of MODIS time series provided stronger relationships than the use of temporal snapshots. The results showed good validation statistics with a RMSE below 20% of the range for all considered soil properties. The RMSE improved from previous studies including only MODIS sensor and using a coarser prediction grid. The performance of the models was similar to previous studies at regional, national or continental scale. A mix of optical and radar data proved useful to map soil properties along the profile. The produced maps of soil properties describing both lateral and vertical variability, with associated uncertainty, are important for further modelling and management of soil resources and ecosystem services. Coupled with further data the soil properties maps could be used to assess soil functions and therefore conditions and suitability of soils for a range of purposes. Copyright © 2016 Elsevier B.V. All rights reserved.

Hierarchical Object-based Image Analysis approach for classification of sub-meter multispectral imagery in Tanzania

NASA Astrophysics Data System (ADS)

Chung, C.; Nagol, J. R.; Tao, X.; Anand, A.; Dempewolf, J.

2015-12-01

Increasing agricultural production while at the same time preserving the environment has become a challenging task. There is a need for new approaches for use of multi-scale and multi-source remote sensing data as well as ground based measurements for mapping and monitoring crop and ecosystem state to support decision making by governmental and non-governmental organizations for sustainable agricultural development. High resolution sub-meter imagery plays an important role in such an integrative framework of landscape monitoring. It helps link the ground based data to more easily available coarser resolution data, facilitating calibration and validation of derived remote sensing products. Here we present a hierarchical Object Based Image Analysis (OBIA) approach to classify sub-meter imagery. The primary reason for choosing OBIA is to accommodate pixel sizes smaller than the object or class of interest. Especially in non-homogeneous savannah regions of Tanzania, this is an important concern and the traditional pixel based spectral signature approach often fails. Ortho-rectified, calibrated, pan sharpened 0.5 meter resolution data acquired from DigitalGlobe's WorldView-2 satellite sensor was used for this purpose. Multi-scale hierarchical segmentation was performed using multi-resolution segmentation approach to facilitate the use of texture, neighborhood context, and the relationship between super and sub objects for training and classification. eCognition, a commonly used OBIA software program, was used for this purpose. Both decision tree and random forest approaches for classification were tested. The Kappa index agreement for both algorithms surpassed the 85%. The results demonstrate that using hierarchical OBIA can effectively and accurately discriminate classes at even LCCS-3 legend.

Exploring the Usefulness of MISR-HR Products to Estimate Maize Crop Extent and Using Field Evidence to Evaluate the Results in South Africa's Free State Province

NASA Astrophysics Data System (ADS)

Verstraete, M. M.; Knox, N. M.; Hunt, L. A.; Kleyn, L.

2014-12-01

The MISR instrument on NASA's Terra platform has been operating for almost 15 years. Standard products are generated at a spatial resolution of 1.1 km or coarser, but a recently developed method to re-analyze the Level-1B2 data allows the retrieval of biogeophysical products at the native spatial resolution of the instrument (275 m). This development opens new opportunities to better address issues such as the management of agricultural production and food security. South African maize production is of great economic and social importance, not only nationally, but on the global market too, being one of the top ten maize producing countries. Seasonal maize production statistics are currently based on a combination of field measurements and estimates derived from manually digitizing high resolution imagery from the SPOT satellite. The field measurements are collected using the Producer Independent Crop Estimate System (PICES) developed by Crop Estimates Committee of the Department of Agriculture, Forestry and Fisheries. There is a strong desire to improve the quality of these statistics, to generate those earlier, and to automate the process to encompass larger areas. This paper will explore the feasibility of using the MISR-HR spectral and directional products, combined with the finer spatial resolution and the relatively frequent coverage afforded by that instrument, to address these needs. The study area is based in the Free State, South Africa, one of the primary maize growing areas in the country, and took place during the 2012-2013 summer growing season. The significance of the outcomes will be evaluated in the context of the 14+ years of available MISR data.

Can we map the interannual variability of the whole upper Southern Ocean with the current database of hydrographic observations?

NASA Astrophysics Data System (ADS)

Heuzé, Céline; Vivier, Frédéric; Le Sommer, Julien; Molines, Jean-Marc; Penduff, Thierry

2016-04-01

With the advent of Argo floats, it now seems feasible to study the interannual variations of upper ocean hydrographic properties of the historically undersampled Southern Ocean. To do so, scattered hydrographic profiles often first need to be mapped. To investigate biases and errors associated both with the limited space-time distribution of the profiles and with the mapping methods, we colocate the mixed layer depth (MLD) output from a state-of-the-art 1/12° DRAKKAR simulation onto the latitude, longitude and date of actual in-situ profiles from 2005 to 2014. We compare the results obtained after remapping using a nearest-neighbor (NN) interpolation and an objective analysis (OA) with different spatio-temporal grid resolutions and decorrelation scales. NN is improved with a coarser resolution. OA performs best with low decorrelation scales, avoiding too strong a smoothing, but returns values over larger areas with large decorrelation scales and low temporal resolution, as more points are available. For all resolutions OA represents better the annual extreme values than NN. Both methods underestimate the seasonal cycle in MLD. MLD biases are lower than 10 m on average but can exceed 250 m locally in winter. We argue that current Argo data should not be mapped to infer decadal trends in MLD, as all methods are unable to reproduce existing trends without creating unrealistic extra ones. We also show that regions of the subtropical Atlantic, Indian and Pacific Oceans, and the whole ice-covered Southern Ocean, still cannot be mapped even by the best method because of the lack of observational data. This article is protected by copyright. All rights reserved.

Albedo, Land Cover, and Daytime Surface Temperature Variation Across an Urbanized Landscape

NASA Astrophysics Data System (ADS)

Trlica, A.; Hutyra, L. R.; Schaaf, C. L.; Erb, A.; Wang, J. A.

2017-11-01

Land surface albedo is a key parameter controlling the local energy budget, and altering the albedo of built surfaces has been proposed as a tool to mitigate high near-surface temperatures in the urban heat island. However, most research on albedo in urban landscapes has used coarse-resolution data, and few studies have attempted to relate albedo to other urban land cover characteristics. This study provides an empirical description of urban summertime albedo using 30 m remote sensing measurements in the metropolitan area around Boston, Massachusetts, relating albedo to metrics of impervious cover fraction, tree canopy coverage, population density, and land surface temperature (LST). At 30 m spatial resolution, median albedo over the study area (excluding open water) was 0.152 (0.112-0.187). Trends of lower albedo with increasing urbanization metrics and temperature emerged only after aggregating data to 500 m or the boundaries of individual towns, at which scale a -0.01 change in albedo was associated with a 29 (25-35)% decrease in canopy cover, a 27 (24-30)% increase in impervious cover, and an increase in population from 11 to 386 km-2. The most intensively urbanized towns in the region showed albedo up to 0.035 lower than the least urbanized towns, and mean mid-morning LST 12.6°C higher. Trends in albedo derived from 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) measurements were comparable, but indicated a strong contribution of open water at this coarser resolution. These results reveal linkages between albedo and urban land cover character, and offer empirical context for climate resilient planning and future landscape functional changes with urbanization.

Evaluation of Lithofacies Up-Scaling Methods for Probabilistic Prediction of Carbon Dioxide Behavior

NASA Astrophysics Data System (ADS)

Park, J. Y.; Lee, S.; Lee, Y. I.; Kihm, J. H.; Kim, J. M.

2017-12-01

Behavior of carbon dioxide injected into target reservoir (storage) formations is highly dependent on heterogeneities of geologic lithofacies and properties. These heterogeneous lithofacies and properties basically have probabilistic characteristics. Thus, their probabilistic evaluation has to be implemented properly into predicting behavior of injected carbon dioxide in heterogeneous storage formations. In this study, a series of three-dimensional geologic modeling is performed first using SKUA-GOCAD (ASGA and Paradigm) to establish lithofacies models of the Janggi Conglomerate in the Janggi Basin, Korea within a modeling domain. The Janggi Conglomerate is composed of mudstone, sandstone, and conglomerate, and it has been identified as a potential reservoir rock (clastic saline formation) for geologic carbon dioxide storage. Its lithofacies information are obtained from four boreholes and used in lithofacies modeling. Three different up-scaling methods (i.e., nearest to cell center, largest proportion, and random) are applied, and lithofacies modeling is performed 100 times for each up-scaling method. The lithofacies models are then compared and analyzed with the borehole data to evaluate the relative suitability of the three up-scaling methods. Finally, the lithofacies models are converted into coarser lithofacies models within the same modeling domain with larger grid blocks using the three up-scaling methods, and a series of multiphase thermo-hydrological numerical simulation is performed using TOUGH2-MP (Zhang et al., 2008) to predict probabilistically behavior of injected carbon dioxide. The coarser lithofacies models are also compared and analyzed with the borehole data and finer lithofacies models to evaluate the relative suitability of the three up-scaling methods. Three-dimensional geologic modeling, up-scaling, and multiphase thermo-hydrological numerical simulation as linked methodologies presented in this study can be utilized as a practical probabilistic evaluation tool to predict behavior of injected carbon dioxide and even to analyze its leakage risk. This work was supported by the Korea CCS 2020 Project of the Korea Carbon Capture and Sequestration R&D Center (KCRC) funded by the National Research Foundation (NRF), Ministry of Science and ICT (MSIT), Korea.

Impact of Soil Moisture Assimilation on Land Surface Model Spin-Up and Coupled LandAtmosphere Prediction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Lawston, P.

2016-01-01

Advances in satellite monitoring of the terrestrial water cycle have led to a concerted effort to assimilate soil moisture observations from various platforms into offline land surface models (LSMs). One principal but still open question is that of the ability of land data assimilation (LDA) to improve LSM initial conditions for coupled short-term weather prediction. In this study, the impact of assimilating Advanced Microwave Scanning Radiometer for EOS (AMSR-E) soil moisture retrievals on coupled WRF Model forecasts is examined during the summers of dry (2006) and wet (2007) surface conditions in the southern Great Plains. LDA is carried out using NASAs Land Information System (LIS) and the Noah LSM through an ensemble Kalman filter (EnKF) approach. The impacts of LDA on the 1) soil moisture and soil temperature initial conditions for WRF, 2) land-atmosphere coupling characteristics, and 3) ambient weather of the coupled LIS-WRF simulations are then assessed. Results show that impacts of soil moisture LDA during the spin-up can significantly modify LSM states and fluxes, depending on regime and season. Results also indicate that the use of seasonal cumulative distribution functions (CDFs) is more advantageous compared to the traditional annual CDF bias correction strategies. LDA performs consistently regardless of atmospheric forcing applied, with greater improvements seen when using coarser, global forcing products. Downstream impacts on coupled simulations vary according to the strength of the LDA impact at the initialization, where significant modifications to the soil moisture flux- PBL-ambient weather process chain are observed. Overall, this study demonstrates potential for future, higher-resolution soil moisture assimilation applications in weather and climate research.

Neural Summation in the Hawkmoth Visual System Extends the Limits of Vision in Dim Light.

PubMed

Stöckl, Anna Lisa; O'Carroll, David Charles; Warrant, Eric James

2016-03-21

Most of the world's animals are active in dim light and depend on good vision for the tasks of daily life. Many have evolved visual adaptations that permit a performance superior to that of manmade imaging devices [1]. In insects, a major model visual system, nocturnal species show impressive visual abilities ranging from flight control [2, 3], to color discrimination [4, 5], to navigation using visual landmarks [6-8] or dim celestial compass cues [9, 10]. In addition to optical adaptations that improve their sensitivity in dim light [11], neural summation of light in space and time-which enhances the coarser and slower features of the scene at the expense of noisier finer and faster features-has been suggested to improve sensitivity in theoretical [12-14], anatomical [15-17], and behavioral [18-20] studies. How these summation strategies function neurally is, however, presently unknown. Here, we quantified spatial and temporal summation in the motion vision pathway of a nocturnal hawkmoth. We show that spatial and temporal summation combine supralinearly to substantially increase contrast sensitivity and visual information rate over four decades of light intensity, enabling hawkmoths to see at light levels 100 times dimmer than without summation. Our results reveal how visual motion is calculated neurally in dim light and how spatial and temporal summation improve sensitivity while simultaneously maximizing spatial and temporal resolution, thus extending models of insect motion vision derived predominantly from diurnal flies. Moreover, the summation strategies we have revealed may benefit manmade vision systems optimized for variable light levels [21]. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multi-year mapping of irrigated croplands over the US High Plains Aquifer using satellite data

NASA Astrophysics Data System (ADS)

Deines, J.; Kendall, A. D.; Hyndman, D. W.

2016-12-01

Irrigated agriculture is the largest consumer of freshwater globally. Effective water management is crucial to support ongoing agricultural intensification to meet increasing demand for food, fuel, and fiber production. Knowledge of where and when irrigation occurs is critical for effective management and hydrological modeling, yet data on patterns of irrigation through time are surprisingly rare. Existing regional datasets in the United States tend to be either aspatial county-level estimates or static, single-year remotely sensed products with relatively low spatial resolution ( 250 m or coarser). Spatially explicit, dynamic maps are needed to understand water use trends, create accurate hydrological models, and inform forecasts of future water availability under projected climate change. In the High Plains Aquifer (HPA), repeat mapping efforts in 2002 and 2007 indicated only 60% of irrigated lands were static between these periods. To better understand annual irrigation dynamics, we used remote sensing to produce annual maps of irrigated cropland across the HPA region from a data fusion of Landsat satellites, annual time series of vegetation indices, and ancillary data such as precipitation, soil properties, and terrain slope. We performed machine learning classification using Google Earth Engine, allowing efficient image processing over a large region for multiple years. We then analyzed maps for water use trends and found that although total irrigated area has increased only slightly, there was substantial variability in the spatial pattern of irrigated lands over time. This dataset will support efforts towards groundwater sustainability by providing consistent, spatially explicit tracking of irrigation dynamics over time.

High-resolution LIDAR and ground observations of snow cover in a complex forested terrain in the Sierra Nevada - implications for optical remote sensing of seasonal snow.

NASA Astrophysics Data System (ADS)

Kostadinov, T. S.; Harpold, A.; Hill, R.; McGwire, K.

2017-12-01

Seasonal snow cover is a key component of the hydrologic regime in many regions of the world, especially those in temperate latitudes with mountainous terrain and dry summers. Such regions support large human populations which depend on the mountain snowpack for their water supplies. It is thus important to quantify snow cover accurately and continuously in these regions. Optical remote-sensing methods are able to detect snow and leverage space-borne spectroradiometers with global coverage such as MODIS to produce global snow cover maps. However, snow is harder to detect accurately in mountainous forested terrain, where topography influences retrieval algorithms, and importantly - forest canopies complicate radiative transfer and obfuscate the snow. Current satellite snow cover algorithms assume that fractional snow-covered area (fSCA) under the canopy is the same as the fSCA in the visible portion of the pixel. In-situ observations and first principles considerations indicate otherwise, therefore there is a need for improvement of the under-canopy correction of snow cover. Here, we leverage multiple LIDAR overflights and in-situ observations with a distributed fiber-optic temperature sensor (DTS) to quantify snow cover under canopy as opposed to gap areas at the Sagehen Experimental Forest in the Northern Sierra Nevada, California, USA. Snow-off LIDAR overflights from 2014 are used to create a baseline high-resolution digital elevation model and classify pixels at 1 m resolution as canopy-covered or gap. Low canopy pixels are excluded from the analysis. Snow-on LIDAR overflights conducted by the Airborne Snow Observatory in 2016 are then used to classify all pixels as snow-covered or not and quantify fSCA under canopies vs. in gap areas over the Sagehen watershed. DTS observations are classified as snow-covered or not based on diel temperature fluctuations and used as validation for the LIDAR observations. LIDAR- and DTS-derived fSCA is also compared with retrievals from hyperspectral imaging spectroradiometer (AVIRIS) data. Initial evidence suggest fSCA was generally lower under canopy and that overall snow cover estimates were overestimated as a result. Implications for a canopy correction applicable to coarser-resolution sensors like MODIS are discussed, as are topography and view angle effects.

Trends in atmospheric evaporative demand in Great Britain using high-resolution meteorological data

NASA Astrophysics Data System (ADS)

Robinson, Emma L.; Blyth, Eleanor M.; Clark, Douglas B.; Finch, Jon; Rudd, Alison C.

2017-02-01

Observations of climate are often available on very different spatial scales from observations of the natural environments and resources that are affected by climate change. In order to help bridge the gap between these scales using modelling, a new dataset of daily meteorological variables was created at 1 km resolution over Great Britain for the years 1961-2012, by interpolating coarser resolution climate data and including the effects of local topography. These variables were used to calculate atmospheric evaporative demand (AED) at the same spatial and temporal resolution. Two functions that represent AED were chosen: one is a standard form of potential evapotranspiration (PET) and the other is a derived PET measure used by hydrologists that includes the effect of water intercepted by the canopy (PETI). Temporal trends in these functions were calculated, with PET found to be increasing in all regions, and at an overall rate of 0.021 ± 0.021 mm day-1 decade-1 in Great Britain. PETI was found to be increasing at a rate of 0.019 ± 0.020 mm day-1 decade-1 in Great Britain, but this was not statistically significant. However, there was a trend in PETI in England of 0.023 ± 0.023 mm day-1 decade-1. The trends were found to vary by season, with spring PET increasing by 0.043 ± 0.019 mm day-1 decade-1 (0.038 ± 0.018 mm day-1 decade-1 when the interception correction is included) in Great Britain, while there is no statistically significant trend in other seasons. The trends were attributed analytically to trends in the climate variables; the overall positive trend was predominantly driven by rising air temperature, although rising specific humidity had a negative effect on the trend. Recasting the analysis in terms of relative humidity revealed that the overall effect is that falling relative humidity causes the PET to rise. Increasing downward short- and longwave radiation made an overall positive contribution to the PET trend, while decreasing wind speed made a negative contribution to the trend in PET. The trend in spring PET was particularly strong due to a strong decrease in relative humidity and increase in downward shortwave radiation in the spring.

Computer Simulations of Ion Transport in Polymer Electrolyte Membranes.

PubMed

Mogurampelly, Santosh; Borodin, Oleg; Ganesan, Venkat

2016-06-07

Understanding the mechanisms and optimizing ion transport in polymer membranes have been the subject of active research for more than three decades. We present an overview of the progress and challenges involved with the modeling and simulation aspects of the ion transport properties of polymer membranes. We are concerned mainly with atomistic and coarser level simulation studies and discuss some salient work in the context of pure binary and single ion conducting polymer electrolytes, polymer nanocomposites, block copolymers, and ionic liquid-based hybrid electrolytes. We conclude with an outlook highlighting future directions.

Improvement of CFD Methods for Modeling Full Scale Circulating Fluidized Bed Combustion Systems

NASA Astrophysics Data System (ADS)

Shah, Srujal; Klajny, Marcin; Myöhänen, Kari; Hyppänen, Timo

With the currently available methods of computational fluid dynamics (CFD), the task of simulating full scale circulating fluidized bed combustors is very challenging. In order to simulate the complex fluidization process, the size of calculation cells should be small and the calculation should be transient with small time step size. For full scale systems, these requirements lead to very large meshes and very long calculation times, so that the simulation in practice is difficult. This study investigates the requirements of cell size and the time step size for accurate simulations, and the filtering effects caused by coarser mesh and longer time step. A modeling study of a full scale CFB furnace is presented and the model results are compared with experimental data.

Multiscale study on stochastic reconstructions of shale samples

NASA Astrophysics Data System (ADS)

Lili, J.; Lin, M.; Jiang, W. B.

2016-12-01

Shales are known to have multiscale pore systems, composed of macroscale fractures, micropores, and nanoscale pores within gas or oil-producing organic material. Also, shales are fissile and laminated, and the heterogeneity in horizontal is quite different from that in vertical. Stochastic reconstructions are extremely useful in situations where three-dimensional information is costly and time consuming. Thus the purpose of our paper is to reconstruct stochastically equiprobable 3D models containing information from several scales. In this paper, macroscale and microscale images of shale structure in the Lower Silurian Longmaxi are obtained by X-ray microtomography and nanoscale images are obtained by scanning electron microscopy. Each image is representative for all given scales and phases. Especially, the macroscale is four times coarser than the microscale, which in turn is four times lower in resolution than the nanoscale image. Secondly, the cross correlation-based simulation method (CCSIM) and the three-step sampling method are combined together to generate stochastic reconstructions for each scale. It is important to point out that the boundary points of pore and matrix are selected based on multiple-point connectivity function in the sampling process, and thus the characteristics of the reconstructed image can be controlled indirectly. Thirdly, all images with the same resolution are developed through downscaling and upscaling by interpolation, and then we merge multiscale categorical spatial data into a single 3D image with predefined resolution (the microscale image). 30 realizations using the given images and the proposed method are generated. The result reveals that the proposed method is capable of preserving the multiscale pore structure, both vertically and horizontally, which is necessary for accurate permeability prediction. The variogram curves and pore-size distribution for both original 3D sample and the generated 3D realizations are compared. The result indicates that the agreement between the original 3D sample and the generated stochastic realizations is excellent. This work is supported by "973" Program (2014CB239004), the Key Instrument Developing Project of the CAS (ZDYZ2012-1-08-02) and the National Natural Science Foundation of China (Grant No. 41574129).

Method for filtering solvent and tar sand mixtures

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

Kelterborn, J. C.; Stone, R. A.

1985-09-03

A method for filtering spent tar sands from a bitumen and organic solvent solution comprises separating the solution into two streams wherein the bulk of the coarser spent tar sand is in a first stream and has an average particle size of about 10 to about 100 mesh and the bulk of the finer spent tar sand is in a second stream; producing a filter cake by filtering the coarser spent tar sand from the first stream; and filtering the finer spent tar sand from the second stream with the filter cake. The method is particularly useful for filtering solutionsmore » of bitumen extracted from bitumen containing diatomite, spent diatomite and organic solvent.« less

Four-way coupling of a three-dimensional debris flow solver to a Lagrangian Particle Simulation: method and first results

NASA Astrophysics Data System (ADS)

von Boetticher, Albrecht; Rickenmann, Dieter; McArdell, Brian; Kirchner, James W.

2017-04-01

Debris flows are dense flowing mixtures of water, clay, silt, sand and coarser particles. They are a common natural hazard in mountain regions and frequently cause severe damage. Modeling debris flows to design protection measures is still challenging due to the complex interactions within the inhomogeneous material mixture, and the sensitivity of the flow process to the channel geometry. The open-source, OpenFOAM-based finite-volume debris flow model debrisInterMixing (von Boetticher et al, 2016) defines rheology parameters based on the material properties of the debris flow mixture to reduce the number of free model parameters. As a simplification in this first model version, gravel was treated as a Coulomb-viscoplastic fluid, neglecting grain-to-grain collisions and the coupling between the coarser gravel grains and the interstitial fluid. Here we present an extension of that solver, accounting for the particle-to-particle and particle-to-boundary contacts with a Lagrangian Particle Simulation composed of spherical grains and a user-defined grain size distribution. The grain collisions of the Lagrangian particles add granular flow behavior to the finite-volume simulation of the continuous phases. The two-way coupling exchanges momentum between the phase-averaged flow in a finite volume cell, and among all individual particles contained in that cell, allowing the user to choose from a number of different drag models. The momentum exchange is implemented in the momentum equation and in the pressure equation (ensuring continuity) of the so-called PISO-loop, resulting in a stable 4-way coupling (particle-to-particle, particle-to-boundary, particle-to-fluid and fluid-to-particle) that represents the granular and viscous flow behavior of debris flow material. We will present simulations that illustrate the relative benefits and drawbacks of explicitly representing grain collisions, compared to the original debrisInterMixing solver.

Evaluating the capability of Landsat 8 OLI and SPOT 6 for discriminating invasive alien species in the African Savanna landscape

NASA Astrophysics Data System (ADS)

Kganyago, Mahlatse; Odindi, John; Adjorlolo, Clement; Mhangara, Paidamoyo

2018-05-01

Globally, there is paucity of accurate information on the spatial distribution and patch sizes of Invasive Alien Plants (IAPs) species. Such information is needed to aid optimisation of control mechanisms to prevent further spread of IAPs and minimize their impacts. Recent studies have shown the capability of very high spatial (<1 m) and spectral resolution (<10 nm) data for discriminating vegetation species. However, very high spatial resolution may introduce significant intra-species spectral variability and result in reduced mapping accuracy, while higher spectral resolution data are commonly limited to smaller areas, are costly and computationally expensive. Alternatively, medium and high spatial resolution data are available at low or no cost and have limitedly been evaluated for their potential in determining invasion patterns relevant for invasion ecology and aiding effective IAPs management. In this study medium and high resolution datasets from Landsat Operational Land Imager (OLI) and SPOT 6 sensors respectively, were evaluated for mapping the distribution and patch sizes of IAP, Parthenium hysterophorus in the savannah landscapes of KwaZulu-Natal, South Africa. Support Vector Machines (SVM) classifier was used for classification of both datasets. Results indicated that SPOT 6 had a higher overall accuracy (86%) than OLI (83%) in mapping P. hysterophorus. The study found larger distributions and patch sizes in OLI than in SPOT 6 as a result of possible P. hysterophorus expansion due to temporal differences between images and coarser pixels were insufficient to delineate gaps inside larger patches. On the other hand, SPOT 6 showed better capabilities of delineating gaps and boundaries of patches, hence had better estimates of distribution and patch sizes. Overall, the study showed that OLI may be suitable for mapping well-established patches for the purpose of large scale monitoring, while SPOT 6 can be used for mapping small patches and prioritising them for eradication to prevent further spread at a landscape scale.

Early Spring Post-Fire Snow Albedo Dynamics in High Latitude Boreal Forests Using Landsat-8 OLI Data

NASA Technical Reports Server (NTRS)

Wang, Zhuosen; Erb, Angela M.; Schaaf, Crystal B.; Sun, Qingsong; Liu, Yan; Yang, Yun; Shuai, Yanmin; Casey, Kimberly A.; Roman, Miguel O.

2016-01-01

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (less than 100 m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high-burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500 m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems.

Early spring post-fire snow albedo dynamics in high latitude boreal forests using Landsat-8 OLI data

PubMed Central

Wang, Zhuosen; Erb, Angela M.; Schaaf, Crystal B.; Sun, Qingsong; Liu, Yan; Yang, Yun; Shuai, Yanmin; Casey, Kimberly A.; Román, Miguel O.

2018-01-01

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (< 100m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high- burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems. PMID:29769751

Early spring post-fire snow albedo dynamics in high latitude boreal forests using Landsat-8 OLI data.

PubMed

Wang, Zhuosen; Erb, Angela M; Schaaf, Crystal B; Sun, Qingsong; Liu, Yan; Yang, Yun; Shuai, Yanmin; Casey, Kimberly A; Román, Miguel O

2016-11-01

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (< 100m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high- burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems.

A New High-Resolution N2O Emission Inventory for China in 2008

NASA Astrophysics Data System (ADS)

Shang, Z.; Zhou, F.; Ciais, P.; Tao, S.; Piao, S.; Raymond, P. A.; He, C.; Li, B.; Wang, R.; Wang, X.; Peng, S.; Zeng, Z.; Chen, H.; Ying, N.; Hou, X.; Xu, P.

2014-12-01

The amount and geographic distribution of N2O emissions over China remain largely uncertain. Most of existing emission inventories use uniform emission factors (EFs) and the associated parameters and apply spatial proxies to downscale national or provincial data, resulting in the introduction of spatial bias. In this study, county-level and 0.1° × 0.1° gridded anthropogenic N2O emission inventories for China (PKU-N2O) in 2008 are developed based on high-resolution activity data and regional EFs and parameters. These new estimates are compared with estimates from EDGAR v4.2, GAINS-China, National Development and Reform Commission of China (NDRC), and with two sensitivity tests: one that uses high-resolution activity data but the default IPCC methodology (S1) and the other that uses regional EFs and parameters but starts from coarser-resolution activity data. The total N2O emissions are 2150 GgN2O/yr (interquartile range from 1174 to 2787 GgN2O/yr). Agriculture contributes 64% of the total, followed by energy (17%), indirect emissions (12%), wastes (5%), industry (2.8%), and wildfires (0.2%). Our national emission total is 17% greater than that of the EDGAR v4.2 global product sampled over China and is also greater than the GAINS-China, NDRC, and S1 estimates by 10%, 50%, and 17%, respectively. We also found that using uniform EFs and parameters or starting from national/provincial data causes systematic spatial biases compared to PKU-N2O. In addition, the considerable differences between the relative contributions of the six sectors across the six Agro-Climate Zones primarily reflect the different distributions of industrial activities and land use. Eastern China (8.7% area of China) is the largest contributor of N2O emissions and accounts for nearly 25% of the total. Spatial analysis also shows nonlinear relationships between N2O emission intensities and urbanization. Per-capita and per-GDP N2O emissions increase gradually with an increase in the urban population fraction from 0.3 to 0.9 among 2884 counties, and N2O emission density increases with urban expansion. Moreover, additional experiments and the use of a reliable data-driven approach or process-based models can improve the spatial resolution and reduce the uncertainties in PKU-N2O, especially from agricultural soils and manure management.

Variability in form and growth of sediment waves on turbidite channel levees

USGS Publications Warehouse

Normark, W.R.; Piper, D.J.W.; Posamentier, H.; Pirmez, C.; Migeon, S.

2002-01-01

Fine-grained sediment waves have been observed in many modern turbidite systems, generally restricted to the overbank depositional element. Sediment waves developed on six submarine fan systems are compared using high-resolution seismic-reflection profiles, sediment core samples (including ODP drilling), multibeam bathymetry, 3D seismic-reflection imaging (including examples of burried features), and direct measurements of turbidity currents that overflow their channels. These submarine fan examples extend over more than three orders of magnitude in physical scale. The presence or absence of sediment waves is not simply a matter of either the size of the turbidite channel-levee systems or the dominant initiation process for the turbidity currents that overflow the channels to form the wave fields. Both sediment-core data and seismic-reflection profiles document the upslope migration of the wave forms, with thicker and coarser beds deposited on the up-current flank of the waves. Some wave fields are orthogonal to channel trend and were initiated by large flows whose direction was controlled by upflow morphology, whereas fields subparallel to channel levees resulted from local spillover. In highly meandering systems, sediment waves may mimic meander planform. Larger sediment waves form on channel-levee systems with thicker overflow of turbidity currents, but available data indicate that sediment waves can be maintaned during conditions of relatively thin overflow. Coarser-grained units in sediment waves are typically laminated and thin-bedded sand as much as several centimetres thick, but sand beds as thick as several tens of centimetres have been documented from both modern and buried systems. Current production of hydrocarbons from sediment-wave deposits suggests that it is important to develop criteria for recognising this overbank element in outcrop exposures and borehole data, where the wavelength of typical waves (several kilometres) generally exceeds outcrop scales and wave heights, which are reduced as a result of consolidation during burial, may be too subtle to recognise. Crown Copyright ?? 2002 Published by Elsevier Science B.V. All rights reserved.

Soil sealing and vesicular layer formation as initial structure development and its effect on infiltration

NASA Astrophysics Data System (ADS)

Badorreck, A.; Gerke, H. H.; Weller, U.; Vontobel, P.

2009-04-01

In the Lusatia mining district (NE-Germany) an artificial catchment was constructed to study initial ecosystem development and runoff generation. As a key process in this early stage, we investigate the surface structure dynamics as it strongly influences erosion, infiltration, matter dynamics, and vegetation establishment. The presented work focuses on observations of soil pore structure formation at the surface at five sites in the catchment and in an adjacent "younger" area composed of comparable sediments. Moreover we've conducted infiltration experiments in the lab and field to relate the soil pore structure to the hydraulic properties. The surface soil was sampled in cylindrical rings (10 cm³) down to 2 cm depth from which bulk density profiles were obtained using X-ray computed tomography (CT) (at UFZ- Halle, Germany) with a resolution of 0.084 mm. The influence of structure on infiltration was investigated using neutron radiography (at the NEUTRA facility of the Paul-Scherrer-Institut, Villigen, Switzerland) to visualise two-dimensional (2D) infiltration patterns. The slab-type samples were equilibrated to different initial water contents and then exposed to drip irrigation (to simulate rainfall) while a series of neutron radiographs were taken. In addition, field measurements with a miniature tension infiltrometer were conduced. The micro-tomographies exhibit formation of surface sealing whose thickness and intensity vary with silt and clay content. The CT images show several coarser- and finer-textured micro-layers at the sample surfaces that were formed as a consequence of repeated washing in of finer particles in underlying coarser sediment. In micro-depressions, the uppermost layers consist of sorted fine sand and silt due to wind erosion. Similar as for desert pavements, a vesicular pore structure developed in these sediments on top, but also scattered in fine sand- and silt-enriched micro-layers. The infiltration rates were severely affected by the surface crusts; however, the rates were independent of the vesicular pore layer.

The parsec-scale relationship between ICO and AV in local molecular clouds

NASA Astrophysics Data System (ADS)

Lee, Cheoljong; Leroy, Adam K.; Bolatto, Alberto D.; Glover, Simon C. O.; Indebetouw, Remy; Sandstrom, Karin; Schruba, Andreas

2018-03-01

We measure the parsec-scale relationship between integrated CO intensity (ICO) and visual extinction (AV) in 24 local molecular clouds using maps of CO emission and dust optical depth from Planck. This relationship informs our understanding of CO emission across environments, but clean Milky Way measurements remain scarce. We find uniform ICO for a given AV, with the results bracketed by previous studies of the Pipe and Perseus clouds. Our measured ICO-AV relation broadly agrees with the standard Galactic CO-to-H2 conversion factor, the relation found for the Magellanic clouds at coarser resolution, and numerical simulations by Glover & Clark (2016). This supports the idea that CO emission primarily depends on shielding, which protects molecules from dissociating radiation. Evidence for CO saturation at high AV and a threshold for CO emission at low AV varies remains uncertain due to insufficient resolution and ambiguities in background subtraction. Resolution of order 0.1 pc may be required to measure these features. We use this ICO-AV relation to predict how the CO-to-H2 conversion factor (XCO) would change if the Solar Neighbourhood clouds had different dust-to-gas ratio (metallicity). The calculations highlight the need for improved observations of the CO emission threshold and H I shielding layer depth. They are also sensitive to the shape of the column density distribution. Because local clouds collectively show a self-similar distribution, we predict a shallow metallicity dependence for XCO down to a few tenths of solar metallicity. However, our calculations also imply dramatic variations in cloud-to-cloud XCO at subsolar metallicity.

Source apportionment and air quality impact assessment studies in Beijing/China

NASA Astrophysics Data System (ADS)

Suppan, P.; Schrader, S.; Shen, R.; Ling, H.; Schäfer, K.; Norra, S.; Vogel, B.; Wang, Y.

2012-04-01

More than 15 million people in the greater area of Beijing are still suffering from severe air pollution levels caused by sources within the city itself but also from external impacts like severe dust storms and long range advection from the southern and central part of China. Within this context particulate matter (PM) is the major air pollutant in the greater area of Beijing (Garland et al., 2009). PM did not serve only as lead substance for air quality levels and therefore for adverse health impact effects but also for a strong influence on the climate system by changing e.g. the radiative balance. Investigations on emission reductions during the Olympic Summer Games in 2008 have caused a strong reduction on coarser particles (PM10) but not on smaller particles (PM2.5). In order to discriminate the composition of the particulate matter levels, the different behavior of coarser and smaller particles investigations on source attribution, particle characteristics and external impacts on the PM levels of the city of Beijing by measurements and modeling are performed: Examples of long term measurements of PM2.5 filter sampling in 2005 with the objectives of detailed chemical (source attribution, carbon fraction, organic speciation and inorganic composition) and isotopic analyses as well as toxicological assessment in cooperation with several institutions (Karlsruhe Institute of Technology (IfGG/IMG), Helmholtz Zentrum München (HMGU), University Rostock (UR), Chinese University of Mining and Technology Beijing, CUMTB) will be discussed. Further experimental studies include the operation of remote sensing systems to determine continuously the MLH (by a ceilometer) and gaseous air pollutants near the ground (by DOAS systems) as well as at the 320 m measurement tower (adhesive plates at different heights for passive particle collection) in cooperation with the Institute of Atmospheric Physics (IAP) of the Chinese Academy of Sciences (CAS). The influence of the MLH on the air pollution concentration could be demonstrated and will be discussed. The impact of dust storm events on the overall pollution level of particulate matter in the greater area of Beijing is being assessed by the online coupled comprehensive model system COSMO-ART. First results of the dust storm modeling in northern China (2006, April 3rd until 12th) demonstrates very well the general behavior of the meteorological parameters temperature and humidity as well as a good agreement between modeled and measured dust storm concentration variability at Beijing in the course of time. The results show the importance of intertwine investigations of measurements and modeling, the analysis of local air pollution levels as well as the impact and analysis of advective process in the greater region of Beijing. Comprehensive investigations on particulate matter are a prerequisite for the knowledge of the source strengths and source attribution to the overall air pollution level. Only this knowledge can help to formulate and to introduce specific reduction measures to reduce coarser as well as finer particulates.

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.

Multiscale sagebrush rangeland habitat modeling in the Gunnison Basin of Colorado

USGS Publications Warehouse

Homer, Collin G.; Aldridge, Cameron L.; Meyer, Debra K.; Schell, Spencer J.

2013-01-01

North American sagebrush-steppe ecosystems have decreased by about 50 percent since European settlement. As a result, sagebrush-steppe dependent species, such as the Gunnison sage-grouse, have experienced drastic range contractions and population declines. Coordinated ecosystem-wide research, integrated with monitoring and management activities, is needed to help maintain existing sagebrush habitats; however, products that accurately model and map sagebrush habitats in detail over the Gunnison Basin in Colorado are still unavailable. The goal of this project is to provide a rigorous large-area sagebrush habitat classification and inventory with statistically validated products and estimates of precision across the Gunnison Basin. This research employs a combination of methods, including (1) modeling sagebrush rangeland as a series of independent objective components that can be combined and customized by any user at multiple spatial scales; (2) collecting ground measured plot data on 2.4-meter QuickBird satellite imagery in the same season the imagery is acquired; (3) modeling of ground measured data on 2.4-meter imagery to maximize subsequent extrapolation; (4) acquiring multiple seasons (spring, summer, and fall) of Landsat Thematic Mapper imagery (30-meter) for optimal modeling; (5) using regression tree classification technology that optimizes data mining of multiple image dates, ratios, and bands with ancillary data to extrapolate ground training data to coarser resolution Landsat Thematic Mapper; and 6) employing accuracy assessment of model predictions to enable users to understand their dependencies. Results include the prediction of four primary components including percent bare ground, percent herbaceous, percent shrub, and percent litter, and four secondary components including percent sagebrush (Artemisia spp.), percent big sagebrush (Artemisia tridentata), percent Wyoming sagebrush (Artemisia tridentata wyomingensis), and shrub height (centimeters). Results were validated with an independent accuracy assessment, with root mean square error values ranging from 3.5 (percent big sagebrush) to 10.8 (percent bare ground) at the QuickBird scale, and from 4.5 (percent Wyoming sagebrush) to 12.4 (percent herbaceous) at the full Landsat scale. These results offer significant improvement in sagebrush ecosystem quantification across the Gunnison Basin, and also provide maximum flexibility to users to employ for a wide variety of applications. Further refinement of these remote sensing component predictions in the future will be most likely achieved by focusing on more extensive ground plot sampling, employing new high and moderate-resolution satellite sensors that offer additional spectral bands for vegetation discrimination, and capturing more dates of satellite imagery to better represent phenological variation.

Assessing changes to South African maize production areas in 2055 using empirical and process-based crop models

NASA Astrophysics Data System (ADS)

Estes, L.; Bradley, B.; Oppenheimer, M.; Beukes, H.; Schulze, R. E.; Tadross, M.

2010-12-01

Rising temperatures and altered precipitation patterns associated with climate change pose a significant threat to crop production, particularly in developing countries. In South Africa, a semi-arid country with a diverse agricultural sector, anthropogenic climate change is likely to affect staple crops and decrease food security. Here, we focus on maize production, South Africa’s most widely grown crop and one with high socio-economic value. We build on previous coarser-scaled studies by working at a finer spatial resolution and by employing two different modeling approaches: the process-based DSSAT Cropping System Model (CSM, version 4.5), and an empirical distribution model (Maxent). For climate projections, we use an ensemble of 10 general circulation models (GCMs) run under both high and low CO2 emissions scenarios (SRES A2 and B1). The models were down-scaled to historical climate records for 5838 quinary-scale catchments covering South Africa (mean area = 164.8 km2), using a technique based on self-organizing maps (SOMs) that generates precipitation patterns more consistent with observed gradients than those produced by the parent GCMs. Soil hydrological and mechanical properties were derived from textural and compositional data linked to a map of 26422 land forms (mean area = 46 km2), while organic carbon from 3377 soil profiles was mapped using regression kriging with 8 spatial predictors. CSM was run using typical management parameters for the several major dryland maize production regions, and with projected CO2 values. The Maxent distribution model was trained using maize locations identified using annual phenology derived from satellite images coupled with airborne crop sampling observations. Temperature and precipitation projections were based on GCM output, with an additional 10% increase in precipitation to simulate higher water-use efficiency under future CO2 concentrations. The two modeling approaches provide spatially explicit projections of gains and losses in maize productivity. We identify several areas-particularly along the southern and eastern boundaries of current production-with potential for increased productivity. However, larger areas, primarily in the more arid western and northern production regions, are likely to experience diminished productivity. The combination of process-based and distribution models for agricultural impacts assessments provides a useful comparison of two different crop modeling frameworks, as well as the finest scale investigation using a spatially-explicit implementation of a process-based model for South Africa. The large GCM ensemble and multiple emissions scenarios provide a broad climate risk assessment for current maize production. SOM downscaling can help improve climate impacts assessments by increasing their resolution, and by circumventing GCM precipitation schemes whose outcomes are highly divergent.

Cross-polar transport and scavenging of Siberian aerosols containing black carbon during the 2012 ACCESS summer campaign

NASA Astrophysics Data System (ADS)

Raut, Jean-Christophe; Marelle, Louis; Fast, Jerome D.; Thomas, Jennie L.; Weinzierl, Bernadett; Law, Katharine S.; Berg, Larry K.; Roiger, Anke; Easter, Richard C.; Heimerl, Katharina; Onishi, Tatsuo; Delanoë, Julien; Schlager, Hans

2017-09-01

During the ACCESS airborne campaign in July 2012, extensive boreal forest fires resulted in significant aerosol transport to the Arctic. A 10-day episode combining intense biomass burning over Siberia and low-pressure systems over the Arctic Ocean resulted in efficient transport of plumes containing black carbon (BC) towards the Arctic, mostly in the upper troposphere (6-8 km). A combination of in situ observations (DLR Falcon aircraft), satellite analysis and WRF-Chem simulations is used to understand the vertical and horizontal transport mechanisms of BC with a focus on the role of wet removal. Between the northwestern Norwegian coast and the Svalbard archipelago, the Falcon aircraft sampled plumes with enhanced CO concentrations up to 200 ppbv and BC mixing ratios up to 25 ng kg-1. During transport to the Arctic region, a large fraction of BC particles are scavenged by two wet deposition processes, namely wet removal by large-scale precipitation and removal in wet convective updrafts, with both processes contributing almost equally to the total accumulated deposition of BC. Our results underline that applying a finer horizontal resolution (40 instead of 100 km) improves the model performance, as it significantly reduces the overestimation of BC levels observed at a coarser resolution in the mid-troposphere. According to the simulations at 40 km, the transport efficiency of BC (TEBC) in biomass burning plumes was larger (60 %), because it was impacted by small accumulated precipitation along trajectory (1 mm). In contrast TEBC was small (< 30 %) and accumulated precipitation amounts were larger (5-10 mm) in plumes influenced by urban anthropogenic sources and flaring activities in northern Russia, resulting in transport to lower altitudes. TEBC due to large-scale precipitation is responsible for a sharp meridional gradient in the distribution of BC concentrations. Wet removal in cumulus clouds is the cause of modeled vertical gradient of TEBC, especially in the mid-latitudes, reflecting the distribution of convective precipitation, but is dominated in the Arctic region by the large-scale wet removal associated with the formation of stratocumulus clouds in the planetary boundary layer (PBL) that produce frequent drizzle.

Downscaling Land Surface Temperature in an Urban Area: A Case Study for Hamburg, Germany

NASA Astrophysics Data System (ADS)

Bechtel, Benjamin; Zakšek, Klemen

2013-04-01

Land surface temperature (LST) is an important parameter for the urban radiation and heat balance and a boundary condition for the atmospheric urban heat island (UHI). The increase in urban surface temperatures compared to the surrounding area (surface urban heat island, SUHI) has been described and analysed with satellite-based measurements for several decades. Besides continuous progress in the development of new sensors, an operational monitoring is still severely limited by physical constraints regarding the spatial and temporal resolution of the satellite data. Essentially, two measurement concepts must be distinguished: Sensors on geostationary platforms have high temporal (several times per hour) and poor spatial resolution (~ 5 km) while those on low earth orbiters have high spatial (~ 100-1000 m) resolution and a long return period (one day to several weeks). To enable an observation with high temporal and spatial resolution, a downscaling scheme for LST from the Spinning Enhanced Visible Infra-Red Imager (SEVIRI) sensor onboard the geostationary meteorological Meteosat 9 to spatial resolutions between 100 and 1000 m was developed and tested for Hamburg in this case study. Therefore, various predictor sets (including parameters derived from multi-temporal thermal data, NDVI, and morphological parameters) were tested. The relationship between predictors and LST was empirically calibrated in the low resolution domain and then transferred to the high resolution domain. The downscaling was validated with LST data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) for the same time. Aggregated parameters from multi-temporal thermal data (in particular annual cycle parameters and principal components) proved particularly suitable. The results for the highest resolution of 100 m showed a high explained variance (R² = 0.71) and relatively low root mean square errors (RMSE = 2.2 K). Larger predictor sets resulted in higher errors, because they tended to overfit. As expected the results were better for coarser spatial resolutions (R² = 0.80, RMSE = 1.8 K for 500 m). These results are similar or slightly better than in previous studies, although we are not aware of any study with a comparably large downscaling factor. A considerable percentage of the error is systematic due to the different viewing geometry of the sensors (the high resolution LST was overestimated about 1.3 K). The study shows that downscaling of SEVIRI LST is possible up to a resolution of 100 m for urban areas and that multi-temporal thermal data are particularly suitable as predictors.

Feasibility analysis of using inverse modeling for estimating natural groundwater recharge from a large-scale soil moisture monitoring network

NASA Astrophysics Data System (ADS)

Wang, Tiejun; Franz, Trenton E.; Yue, Weifeng; Szilagyi, Jozsef; Zlotnik, Vitaly A.; You, Jinsheng; Chen, Xunhong; Shulski, Martha D.; Young, Aaron

2016-02-01

Despite the importance of groundwater recharge (GR), its accurate estimation still remains one of the most challenging tasks in the field of hydrology. In this study, with the help of inverse modeling, long-term (6 years) soil moisture data at 34 sites from the Automated Weather Data Network (AWDN) were used to estimate the spatial distribution of GR across Nebraska, USA, where significant spatial variability exists in soil properties and precipitation (P). To ensure the generality of this study and its potential broad applications, data from public domains and literature were used to parameterize the standard Hydrus-1D model. Although observed soil moisture differed significantly across the AWDN sites mainly due to the variations in P and soil properties, the simulations were able to capture the dynamics of observed soil moisture under different climatic and soil conditions. The inferred mean annual GR from the calibrated models varied over three orders of magnitude across the study area. To assess the uncertainties of the approach, estimates of GR and actual evapotranspiration (ETa) from the calibrated models were compared to the GR and ETa obtained from other techniques in the study area (e.g., remote sensing, tracers, and regional water balance). Comparison clearly demonstrated the feasibility of inverse modeling and large-scale (>104 km2) soil moisture monitoring networks for estimating GR. In addition, the model results were used to further examine the impacts of climate and soil on GR. The data showed that both P and soil properties had significant impacts on GR in the study area with coarser soils generating higher GR; however, different relationships between GR and P emerged at the AWDN sites, defined by local climatic and soil conditions. In general, positive correlations existed between annual GR and P for the sites with coarser-textured soils or under wetter climatic conditions. With the rapidly expanding soil moisture monitoring networks around the globe, this study may have important applications in aiding water resources management in different regions.

Sub-pixel Area Calculation Methods for Estimating Irrigated Areas.

PubMed

Thenkabailc, Prasad S; Biradar, Chandrashekar M; Noojipady, Praveen; Cai, Xueliang; Dheeravath, Venkateswarlu; Li, Yuanjie; Velpuri, Manohar; Gumma, Muralikrishna; Pandey, Suraj

2007-10-31

The goal of this paper was to develop and demonstrate practical methods forcomputing sub-pixel areas (SPAs) from coarse-resolution satellite sensor data. Themethods were tested and verified using: (a) global irrigated area map (GIAM) at 10-kmresolution based, primarily, on AVHRR data, and (b) irrigated area map for India at 500-mbased, primarily, on MODIS data. The sub-pixel irrigated areas (SPIAs) from coarse-resolution satellite sensor data were estimated by multiplying the full pixel irrigated areas(FPIAs) with irrigated area fractions (IAFs). Three methods were presented for IAFcomputation: (a) Google Earth Estimate (IAF-GEE); (b) High resolution imagery (IAF-HRI); and (c) Sub-pixel de-composition technique (IAF-SPDT). The IAF-GEE involvedthe use of "zoom-in-views" of sub-meter to 4-meter very high resolution imagery (VHRI)from Google Earth and helped determine total area available for irrigation (TAAI) or netirrigated areas that does not consider intensity or seasonality of irrigation. The IAF-HRI isa well known method that uses finer-resolution data to determine SPAs of the coarser-resolution imagery. The IAF-SPDT is a unique and innovative method wherein SPAs aredetermined based on the precise location of every pixel of a class in 2-dimensionalbrightness-greenness-wetness (BGW) feature-space plot of red band versus near-infraredband spectral reflectivity. The SPIAs computed using IAF-SPDT for the GIAM was within2 % of the SPIA computed using well known IAF-HRI. Further the fractions from the 2 methods were significantly correlated. The IAF-HRI and IAF-SPDT help to determine annualized or gross irrigated areas (AIA) that does consider intensity or seasonality (e.g., sum of areas from season 1, season 2, and continuous year-round crops). The national census based irrigated areas for the top 40 irrigated nations (which covers about 90% of global irrigation) was significantly better related (and had lesser uncertainties and errors) when compared to SPIAs than FPIAs derived using 10-km and 500-m data. The SPIAs were closer to actual areas whereas FPIAs grossly over-estimate areas. The research clearly demonstrated the value and the importance of sub-pixel areas as opposed to full pixel areas and presented 3 innovative methods for computing the same.

Recent advances in time series InSAR

NASA Astrophysics Data System (ADS)

Hooper, Andrew; Bekaert, David; Spaans, Karsten

2010-05-01

Despite the multiple successes of InSAR at measuring surface displacement, in many instances the signal over much of an image either decorrelates too quickly to be useful or is swamped by atmospheric noise. Time series InSAR methods seek to address these issues by essentially increasing the signal-to-noise ratio (SNR) through the use of more data. These techniques are particularly useful for applications where the strain rates detected at the surface are low, such as postseismic/interseismic motion, magma/fluid movement, landslides and reservoir exploitation. Our previous developments in this field have included a persistent scatterer algorithm based on spatial correlation, a full resolution small baseline approach based on the same strategy, and procedure for combining the two [Hooper, GRL, 2008]. This combined method works well on small areas (up to one frame) at ERS or Envisat strip-map resolution. However, in applying it to larger areas, such as the Guerrero region of Mexico and western Anatolia in Turkey, or when processing data at higher resolution, e.g. from TerraSAR-X, computer resource problems can arise. We have therefore altered the processing strategy to involve smarter use of computer memory. Further improvement is achieved by the resampling of the selected pixels (whether persistent scatterers or distributed scatterers) to a coarser resolution - usually we do not require a resolution on the scale of individual resolution cells for geophysical applications. Aliasing is avoided by summing the phase of nearby selected pixels, weighted according to their estimated SNR. This is akin to smart multilooking, but note that better results can be achieved than by starting the analysis with low-resolution (multilooked) data. Another development concerns selecting pixels only in images where they appear reliable. This allows for resolution cells that become correlated/decorrelated either in a temporary fashion, e.g., due to snow cover, or in a permanent way due to the appearance or removal of scatterers. The detection algorithm relies on the degree of spatial correlation for the pixel of interest in each image. We have also modified our 3-D phase-unwrapping algorithms to allow for the resulting differing combinations of coherent pixels in every interferogram. We demonstrate our improved techniques on volcanoes in Iceland and the 2006 slow-slip event in Guerrero, Mexico.

Analysis of the potential of near ground measurements of CO2 and CH4 in London, UK for the monitoring of city-scale emissions using an atmospheric transport model

NASA Astrophysics Data System (ADS)

Boon, A.; Broquet, G.; Clifford, D. J.; Chevallier, F.; Butterfield, D. M.; Pison, I.; Ramonet, M.; Paris, J. D.; Ciais, P.

2015-11-01

Carbon dioxide (CO2) and methane (CH4) mole fractions were measured at four near ground sites located in and around London during the summer of 2012 in view to investigate the potential of assimilating such measurements in an atmospheric inversion system for the monitoring of the CO2 and CH4 emissions in the London area. These data were analysed and compared with simulations using a modelling framework suited to building an inversion system: a 2 km horizontal resolution South of England configuration of the transport model CHIMERE driven by European Centre for Medium-Range Weather Forecasting (ECMWF) meteorological forcing, coupled to a 1 km horizontal resolution emission inventory (the UK National Atmospheric Emission Inventory). First comparisons reveal that local sources have a large impact on measurements and these local sources cannot be represented in the model at 2 km resolution. We evaluate methods to minimise some of the other critical sources of misfits between the observation data and the model simulation that overlap the signature of the errors in the emission inventory. These methods should make it easier to identify the corrections that should be applied to the inventory. Analysis is supported by observations from meteorological sites around the city and a three-week period of atmospheric mixing layer height estimations from lidar measurements. The difficulties of modelling the mixing layer depth and thus CO2 and CH4 concentrations during the night, morning and late afternoon led us to focus on the afternoon period for all further analyses. The misfits between observations and model simulations are high for both CO2 and CH4 (i.e., their root mean square (RMS) is between 8 and 12 parts per million (ppm) for CO2 and between 30 and 55 parts per billion (ppb) for CH4 at a given site). By analysing the gradients between the urban sites and a suburban or rural reference site, we are able to decrease the impact of uncertainties in the fluxes and transport outside the London area and in the model domain boundary conditions, and to better focus attention on the signature of London urban CO2 and CH4 emissions. This considerably improves the statistical agreement between the model and observations for CO2 (model-data RMS misfit of between 3 and 7 ppm) and to a lesser degree for CH4 (model-data RMS misfit of between 29 and 38 ppb). Between one of the urban sites and either reference site, selecting the gradients during periods wherein the reference site is upwind of the urban site further decreases the statistics of the misfits in general even though not systematically. In a final attempt to focus on the signature of the city anthropogenic emission in the mole fraction measurements, we use a theoretical ratio of gradients of CO to gradients of CO2 from fossil fuel emissions in the London area to diagnose observation based fossil fuel CO2 gradients, and compare them with the modelled ones. This estimate increases the consistency between the model and the measurements when considering one of the urban sites, but not when considering the other. While this study evaluates different approaches for increasing the consistency between the mesoscale model and the near ground data, and manages to decrease the random component of the analysed model data misfits to an extent that should not be prohibitive to extracting the signal from the London urban emissions, large biases remain in the final misfits. These biases are likely to be due to local emissions, to which the urban near ground sites are highly sensitive. This questions our current ability to exploit urban near ground data for the atmospheric inversion of city emissions based on models at spatial resolution coarser than 2 km.

A fast multi-resolution approach to tomographic PIV

NASA Astrophysics Data System (ADS)

Discetti, Stefano; Astarita, Tommaso

2012-03-01

Tomographic particle image velocimetry (Tomo-PIV) is a recently developed three-component, three-dimensional anemometric non-intrusive measurement technique, based on an optical tomographic reconstruction applied to simultaneously recorded images of the distribution of light intensity scattered by seeding particles immersed into the flow. Nowadays, the reconstruction process is carried out mainly by iterative algebraic reconstruction techniques, well suited to handle the problem of limited number of views, but computationally intensive and memory demanding. The adoption of the multiplicative algebraic reconstruction technique (MART) has become more and more accepted. In the present work, a novel multi-resolution approach is proposed, relying on the adoption of a coarser grid in the first step of the reconstruction to obtain a fast estimation of a reliable and accurate first guess. A performance assessment, carried out on three-dimensional computer-generated distributions of particles, shows a substantial acceleration of the reconstruction process for all the tested seeding densities with respect to the standard method based on 5 MART iterations; a relevant reduction in the memory storage is also achieved. Furthermore, a slight accuracy improvement is noticed. A modified version, improved by a multiplicative line of sight estimation of the first guess on the compressed configuration, is also tested, exhibiting a further remarkable decrease in both memory storage and computational effort, mostly at the lowest tested seeding densities, while retaining the same performances in terms of accuracy.

Ensemble forecasting for renewable energy applications - status and current challenges for their generation and verification

NASA Astrophysics Data System (ADS)

Pinson, Pierre

2016-04-01

The operational management of renewable energy generation in power systems and electricity markets requires forecasts in various forms, e.g., deterministic or probabilistic, continuous or categorical, depending upon the decision process at hand. Besides, such forecasts may also be necessary at various spatial and temporal scales, from high temporal resolutions (in the order of minutes) and very localized for an offshore wind farm, to coarser temporal resolutions (hours) and covering a whole country for day-ahead power scheduling problems. As of today, weather predictions are a common input to forecasting methodologies for renewable energy generation. Since for most decision processes, optimal decisions can only be made if accounting for forecast uncertainties, ensemble predictions and density forecasts are increasingly seen as the product of choice. After discussing some of the basic approaches to obtaining ensemble forecasts of renewable power generation, it will be argued that space-time trajectories of renewable power production may or may not be necessitate post-processing ensemble forecasts for relevant weather variables. Example approaches and test case applications will be covered, e.g., looking at the Horns Rev offshore wind farm in Denmark, or gridded forecasts for the whole continental Europe. Eventually, we will illustrate some of the limitations of current frameworks to forecast verification, which actually make it difficult to fully assess the quality of post-processing approaches to obtain renewable energy predictions.

Surface Soil Moisture Retrieval Using SSM/I and Its Comparison with ESTAR: A Case Study Over a Grassland Region

NASA Technical Reports Server (NTRS)

Jackson, T.; Hsu, A. Y.; ONeill, P. E.

1999-01-01

This study extends a previous investigation on estimating surface soil moisture using the Special Sensor Microwave/Imager (SSM/I) over a grassland region. Although SSM/I is not optimal for soil moisture retrieval, it can under some conditions provide information. Rigorous analyses over land have been difficult due to the lack of good validation data sets. A scientific objective of the Southern Great Plains 1997 (SGP97) Hydrology Experiment was to investigate whether the retrieval algorithms for surface soil moisture developed at higher spatial resolution using truck-and aircraft-based passive microwave sensors can be extended to the coarser resolutions expected from satellite platform. With the data collected for the SGP97, the objective of this study is to compare the surface soil moisture estimated from the SSM/I data with those retrieved from the L-band Electronically Scanned Thinned Array Radiometer (ESTAR) data, the core sensor for the experiment, using the same retrieval algorithm. The results indicated that an error of estimate of 7.81% could be achieved with SSM/I data as contrasted to 2.82% with ESTAR data over three intensive sampling areas of different vegetation regimes. It confirms the results of previous study that SSM/I data can be used to retrieve surface soil moisture information at a regional scale under certain conditions.

LSA SAF Meteosat FRP Products: Part 2 - Evaluation and demonstration of use in the Copernicus Atmosphere Monitoring Service (CAMS)

NASA Astrophysics Data System (ADS)

Roberts, G.; Wooster, M. J.; Xu, W.; Freeborn, P. H.; Morcrette, J.-J.; Jones, L.; Benedetti, A.; Kaiser, J.

2015-06-01

Characterising the dynamics of landscape scale wildfires at very high temporal resolutions is best achieved using observations from Earth Observation (EO) sensors mounted onboard geostationary satellites. As a result, a number of operational active fire products have been developed from the data of such sensors. An example of which are the Fire Radiative Power (FRP) products, the FRP-PIXEL and FRP-GRID products, generated by the Land Surface Analysis Satellite Applications Facility (LSA SAF) from imagery collected by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on-board the Meteosat Second Generation (MSG) series of geostationary EO satellites. The processing chain developed to deliver these FRP products detects SEVIRI pixels containing actively burning fires and characterises their FRP output across four geographic regions covering Europe, part of South America and northern and southern Africa. The FRP-PIXEL product contains the highest spatial and temporal resolution FRP dataset, whilst the FRP-GRID product contains a spatio-temporal summary that includes bias adjustments for cloud cover and the non-detection of low FRP fire pixels. Here we evaluate these two products against active fire data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS), and compare the results to those for three alternative active fire products derived from SEVIRI imagery. The FRP-PIXEL product is shown to detect a substantially greater number of active fire pixels than do alternative SEVIRI-based products, and comparison to MODIS on a per-fire basis indicates a strong agreement and low bias in terms of FRP values. However, low FRP fire pixels remain undetected by SEVIRI, with errors of active fire pixel detection commission and omission compared to MODIS ranging between 9-13 and 65-77% respectively in Africa. Higher errors of omission result in greater underestimation of regional FRP totals relative to those derived from simultaneously collected MODIS data, ranging from 35% over the Northern Africa region to 89% over the European region. High errors of active fire omission and FRP underestimation are found over Europe and South America, and result from SEVIRI's larger pixel area over these regions. An advantage of using FRP for characterising wildfire emissions is the ability to do so very frequently and in near real time (NRT). To illustrate the potential of this approach, wildfire fuel consumption rates derived from the SEVIRI FRP-PIXEL product are used to characterise smoke emissions of the 2007 Peloponnese wildfires within the European Centre for Medium-Range Weather Forecasting (ECMWF) Integrated Forecasting System (IFS), as a demonstration of what can be achieved when using geostationary active fire data within the Copernicus Atmosphere Monitoring System (CAMS). Qualitative comparison of the modelled smoke plumes with MODIS optical imagery illustrates that the model captures the temporal and spatial dynamics of the plume very well, and that high temporal resolution emissions estimates such as those available from geostationary orbit are important for capturing the sub-daily variability in smoke plume parameters such as aerosol optical depth (AOD), which are increasingly less well resolved using daily or coarser temporal resolution emissions datasets. Quantitative comparison of modelled AOD with coincident MODIS and AERONET AOD indicates that the former is overestimated by ∼ 20-30%, but captures the observed AOD dynamics with a high degree of fidelity. The case study highlights the potential of using geostationary FRP data to drive fire emissions estimates for use within atmospheric transport models such as those currently implemented as part of the Monitoring Atmospheric Composition and Climate (MACC) programme within the CAMS.

Mapping Eroded Areas on Mountain Grassland with Terrestrial Photogrammetry and Object-Based Image Analysis

NASA Astrophysics Data System (ADS)

Mayr, Andreas; Rutzinger, Martin; Bremer, Magnus; Geitner, Clemens

2016-06-01

In the Alps as well as in other mountain regions steep grassland is frequently affected by shallow erosion. Often small landslides or snow movements displace the vegetation together with soil and/or unconsolidated material. This results in bare earth surface patches within the grass covered slope. Close-range and remote sensing techniques are promising for both mapping and monitoring these eroded areas. This is essential for a better geomorphological process understanding, to assess past and recent developments, and to plan mitigation measures. Recent developments in image matching techniques make it feasible to produce high resolution orthophotos and digital elevation models from terrestrial oblique images. In this paper we propose to delineate the boundary of eroded areas for selected scenes of a study area, using close-range photogrammetric data. Striving for an efficient, objective and reproducible workflow for this task, we developed an approach for automated classification of the scenes into the classes grass and eroded. We propose an object-based image analysis (OBIA) workflow which consists of image segmentation and automated threshold selection for classification using the Excess Green Vegetation Index (ExG). The automated workflow is tested with ten different scenes. Compared to a manual classification, grass and eroded areas are classified with an overall accuracy between 90.7% and 95.5%, depending on the scene. The methods proved to be insensitive to differences in illumination of the scenes and greenness of the grass. The proposed workflow reduces user interaction and is transferable to other study areas. We conclude that close-range photogrammetry is a valuable low-cost tool for mapping this type of eroded areas in the field with a high level of detail and quality. In future, the output will be used as ground truth for an area-wide mapping of eroded areas in coarser resolution aerial orthophotos acquired at the same time.

Imaging the Fine-Scale Structure of the San Andreas Fault in the Northern Gabilan Range with Explosion and Earthquake Sources

NASA Astrophysics Data System (ADS)

Xin, H.; Thurber, C. H.; Zhang, H.; Wang, F.

2014-12-01

A number of geophysical studies have been carried out along the San Andreas Fault (SAF) in the Northern Gabilan Range (NGR) with the purpose of characterizing in detail the fault zone structure. Previous seismic research has revealed the complex structure of the crustal volume in the NGR region in two-dimensions (Thurber et al., 1996, 1997), and there has been some work on the three-dimensional (3D) structure at a coarser scale (Lin and Roecker, 1997). In our study we use earthquake body-wave arrival times and differential times (P and S) and explosion arrival times (only P) to image the 3D P- and S-wave velocity structure of the upper crust along the SAF in the NGR using double-difference (DD) tomography. The earthquake and explosion data types have complementary strengths - the earthquake data have good resolution at depth and resolve both Vp and Vs structure, although only where there are sufficient seismic rays between hypocenter and stations, whereas the explosions contribute very good near-surface resolution but for P waves only. The original dataset analyzed by Thurber et al. (1996, 1997) included data from 77 local earthquakes and 8 explosions. We enlarge the dataset with 114 more earthquakes that occurred in the study area, obtain improved S-wave picks using an automated picker, and include absolute and cross-correlation differential times. The inversion code we use is the algorithm tomoDD (Zhang and Thurber, 2003). We assess how the P and S velocity models and earthquake locations vary as we alter the inversion parameters and the inversion grid. The new inversion results show clearly the fine-scale structure of the SAF at depth in 3D, sharpening the image of the velocity contrast from the southwest side to the northeast side.

Comparison of Measured and WRF-LES Turbulence Statistics in a Real Convective Boundary Layer over Complex Terrain

NASA Astrophysics Data System (ADS)

Rai, R. K.; Berg, L. K.; Kosovic, B.; Mirocha, J. D.; Pekour, M. S.; Shaw, W. J.

2015-12-01

Resolving the finest turbulent scales present in the lower atmosphere using numerical simulations helps to study the processes that occur in the atmospheric boundary layer, such as the turbulent inflow condition to the wind plant and the generation of the wake behind wind turbines. This work employs several nested domains in the WRF-LES framework to simulate conditions in a convectively driven cloud free boundary layer at an instrumented field site in complex terrain. The innermost LES domain (30 m spatial resolution) receives the boundary forcing from two other coarser resolution LES outer domains, which in turn receive boundary conditions from two WRF-mesoscale domains. Wind and temperature records from sonic anemometers mounted at two vertical levels (30 m and 60 m) are compared with the LES results in term of first and second statistical moments as well as power spectra and distributions of wind velocity. For the two mostly used boundary layer parameterizations (MYNN and YSU) tested in the WRF mesoscale domains, the MYNN scheme shows slightly better agreement with the observations for some quantities, such as time averaged velocity and Turbulent Kinetic Energy (TKE). However, LES driven by WRF-mesoscale simulations using either parameterization have similar velocity spectra and distributions of velocity. For each component of the wind velocity, WRF-LES power spectra are found to be comparable to the spectra derived from the measured data (for the frequencies that are accurately represented by WRF-LES). Furthermore, the analysis of LES results shows a noticeable variability of the mean and variance even over small horizontal distances that would be considered sub-grid scale in mesoscale simulations. This observed statistical variability in space and time can be utilized to further analyze the turbulence quantities over a heterogeneous surface and to improve the turbulence parameterization in the mesoscale model.

The influence of grain size, grain color, and suspended-sediment concentration on light attenuation: why fine-grained terrestrial sediment is bad for coral reef ecosystems

USGS Publications Warehouse

Storlazzi, Curt; Norris, Benjamin; Rosenberger, Kurt

2015-01-01

Sediment has been shown to be a major stressor to coral reefs globally. Although many researchers have tested the impact of sedimentation on coral reef ecosystems in both the laboratory and the field and some have measured the impact of suspended sediment on the photosynthetic response of corals, there has yet to be a detailed investigation on how properties of the sediment itself can affect light availability for photosynthesis. We show that finer-grained and darker-colored sediment at higher suspended-sediment concentrations attenuates photosynthetically active radiation (PAR) significantly more than coarser, lighter-colored sediment at lower concentrations and provide PAR attenuation coefficients for various grain sizes, colors, and suspended-sediment concentrations that are needed for biophysical modeling. Because finer-grained sediment particles settle more slowly and are more susceptible to resuspension, they remain in the water column longer, thus causing greater net impact by reducing light essential for photosynthesis over a greater duration. This indicates that coral reef monitoring studies investigating sediment impacts should concentrate on measuring fine-grained lateritic and volcanic soils, as opposed to coarser-grained siliceous and carbonate sediment. Similarly, coastal restoration efforts and engineering solutions addressing long-term coral reef ecosystem health should focus on preferentially retaining those fine-grained soils rather than coarse silt and sand particles.

Deep Learning @15 Petaflops/second: Semi-supervised pattern detection for 15 Terabytes of climate data

NASA Astrophysics Data System (ADS)

Collins, W. D.; Wehner, M. F.; Prabhat, M.; Kurth, T.; Satish, N.; Mitliagkas, I.; Zhang, J.; Racah, E.; Patwary, M.; Sundaram, N.; Dubey, P.

2017-12-01

Anthropogenically-forced climate changes in the number and character of extreme storms have the potential to significantly impact human and natural systems. Current high-performance computing enables multidecadal simulations with global climate models at resolutions of 25km or finer. Such high-resolution simulations are demonstrably superior in simulating extreme storms such as tropical cyclones than the coarser simulations available in the Coupled Model Intercomparison Project (CMIP5) and provide the capability to more credibly project future changes in extreme storm statistics and properties. The identification and tracking of storms in the voluminous model output is very challenging as it is impractical to manually identify storms due to the enormous size of the datasets, and therefore automated procedures are used. Traditionally, these procedures are based on a multi-variate set of physical conditions based on known properties of the class of storms in question. In recent years, we have successfully demonstrated that Deep Learning produces state of the art results for pattern detection in climate data. We have developed supervised and semi-supervised convolutional architectures for detecting and localizing tropical cyclones, extra-tropical cyclones and atmospheric rivers in simulation data. One of the primary challenges in the applicability of Deep Learning to climate data is in the expensive training phase. Typical networks may take days to converge on 10GB-sized datasets, while the climate science community has ready access to O(10 TB)-O(PB) sized datasets. In this work, we present the most scalable implementation of Deep Learning to date. We successfully scale a unified, semi-supervised convolutional architecture on all of the Cori Phase II supercomputer at NERSC. We use IntelCaffe, MKL and MLSL libraries. We have optimized single node MKL libraries to obtain 1-4 TF on single KNL nodes. We have developed a novel hybrid parameter update strategy to improve scaling to 9600 KNL nodes (600,000 cores). We obtain 15PF performance over the course of the training run; setting a new watermark for the HPC and Deep Learning communities. This talk will share insights on how to obtain this extreme level of performance, current gaps/challenges and implications for the climate science community.

Macroecological factors shape local-scale spatial patterns in agriculturalist settlements.

PubMed

Tao, Tingting; Abades, Sebastián; Teng, Shuqing; Huang, Zheng Y X; Reino, Luís; Chen, Bin J W; Zhang, Yong; Xu, Chi; Svenning, Jens-Christian

2017-11-15

Macro-scale patterns of human systems ranging from population distribution to linguistic diversity have attracted recent attention, giving rise to the suggestion that macroecological rules shape the assembly of human societies. However, in which aspects the geography of our own species is shaped by macroecological factors remains poorly understood. Here, we provide a first demonstration that macroecological factors shape strong local-scale spatial patterns in human settlement systems, through an analysis of spatial patterns in agriculturalist settlements in eastern mainland China based on high-resolution Google Earth images. We used spatial point pattern analysis to show that settlement spatial patterns are characterized by over-dispersion at fine spatial scales (0.05-1.4 km), consistent with territory segregation, and clumping at coarser spatial scales beyond the over-dispersion signals, indicating territorial clustering. Statistical modelling shows that, at macroscales, potential evapotranspiration and topographic heterogeneity have negative effects on territory size, but positive effects on territorial clustering. These relationships are in line with predictions from territory theory for hunter-gatherers as well as for many animal species. Our results help to disentangle the complex interactions between intrinsic spatial processes in agriculturalist societies and external forcing by macroecological factors. While one may speculate that humans can escape ecological constraints because of unique abilities for environmental modification and globalized resource transportation, our work highlights that universal macroecological principles still shape the geography of current human agricultural societies. © 2017 The Author(s).

Performance of fluorescence retrieval methods and fluorescence spectrum reconstruction under various sensor spectral configurations

NASA Astrophysics Data System (ADS)

Li, Rong; Zhao, Feng

2015-10-01

Solar-induced chlorophyll fluorescence is closely related to photosynthesis and can serve as an indicator of plant status. Several methods have been proposed to retrieve fluorescence signal (Fs) either at specific spectral bands or within the whole fluorescence emission region. In this study, we investigated the precision of the fluorescence signal obtained through these methods under various sensor spectral characteristics. Simulated datasets generated by the SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes) model with known `true' Fs as well as an experimental dataset are exploited to investigate four commonly used Fs retrieval methods, namely the original Fraunhofer Line Discriminator method (FLD), the 3 bands FLD (3FLD), the improved FLD (iFLD), and the Spectral Fitting Methods (SFMs). Fluorescence Spectrum Reconstruction (FSR) method is also investigated using simulated datasets. The sensor characteristics of spectral resolution (SR) and signal-to-noise ratio (SNR) are taken into account. According to the results, finer SR and SNR both lead to better accuracy. Lowest precision is obtained for the FLD method with strong overestimation. Some improvements are made by the 3FLD method, but it still tends to overestimate. Generally, the iFLD method and the SFMs provide better accuracy. As to FSR, the shape and magnitude of reconstructed Fs are generally consistent with the `true' Fs distributions when fine SR is exploited. With coarser SR, however, though R2 of the retrieved Fs may be high, large bias is likely to be obtained as well.

Hydrogen-assisted stable crack growth in iron-3 wt% silicon steel

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

Marrow, T.J.; Prangnell, P.; Aindow, M.

1996-08-01

Observations of internal hydrogen cleavage in Fe-3Si are reported. Hydrogen-assisted stable crack growth (H-SCG) is associated with cleavage striations of a 300 nm spacing, observed using scanning electron microscopy (SEM) and atomic force microscopy (AFM). High resolution SEM revealed finer striations, previously undetected, with a spacing of approximately 30 nm. These were parallel to the coarser striations. Scanning tunneling microscopy (STM) also showed the fine striation spacing, and gave a striation height of approximately 15 nm. The crack front was not parallel to the striations. Transmission electron microscopy (TEM) of crack tip plastic zones showed {l_brace}112{r_brace} and {l_brace}110{r_brace} slip, withmore » a high dislocation density (around 10{sup 14}m{sup {minus}2}). The slip plane spacing was approximately 15--30 nm. Parallel arrays of high dislocation density were observed in the wake of the hydrogen cleavage crack. It is concluded that H-ScG in Fe-3Si occurs by periodic brittle cleavage on the {l_brace}001{r_brace} planes. This is preceded by dislocation emission. The coarse striations are produced by crack tip blunting and the fine striations by dislocations attracted by image forces to the fracture surface after cleavage. The effects of temperature, pressure and yield strength on the kinetics of H-SCG can be predicted using a model for diffusion of hydrogen through the plastic zone.« less

Development of the Vista Methane Emissions Inventory for Southern California: A GIS-Based Approach for Mapping Methane Emissions

NASA Astrophysics Data System (ADS)

Carranza, V.; Frausto-Vicencio, I.; Rafiq, T.; Verhulst, K. R.; Hopkins, F. M.; Rao, P.; Duren, R. M.; Miller, C. E.

2016-12-01

Atmospheric methane (CH4) is the second most prevalent anthropogenic greenhouse gas. Improved estimates of CH4 emissions from cities is essential for carbon cycle science and climate mitigation efforts. Development of spatially-resolved carbon emissions data sets may offer significant advances in understanding and managing carbon emissions from cities. Urban CH4 emissions in particular require spatially resolved emission maps to help resolve uncertainties in the CH4 budget. This study presents a Geographic Information System (GIS)-based approach to mapping CH4 emissions using locations of infrastructure known to handle and emit methane. We constrain the spatial distribution of sources to the facility level for the major CH4 emitting sources in the South Coast Air Basin. GIS spatial modeling was combined with publicly available datasets to determine the distribution of potential CH4 sources. The datasets were processed and validated to ensure accuracy in the location of individual sources. This information was then used to develop the Vista emissions prior, which is a one-year long, spatially-resolved CH4 emissions estimate. Methane emissions were calculated and spatially allocated to produce 1 km x 1 km gridded CH4 emission map spanning the Los Angeles Basin. In future work, the Vista CH4 emissions prior will be compared with existing, coarser-resolution emissions estimates and will be evaluated in inverse modeling studies using atmospheric observations. The Vista CH4 emissions inventory presents the first detailed spatial maps of CH4 sources and emissions estimates in the Los Angeles Basin and is a critical step towards sectoral attribution of CH4 emissions at local to regional scales.

Evaluation of different digital elevation models for analyzing drainage morphometric parameters in a mountainous terrain: a case study of the Supin-Upper Tons Basin, Indian Himalayas.

PubMed

Das, Sayantan; Patel, Priyank Pravin; Sengupta, Somasis

2016-01-01

With myriad geospatial datasets now available for terrain information extraction and particularly streamline demarcation, there arises questions regarding the scale, accuracy and sensitivity of the initial dataset from which these aspects are derived, as they influence all other parameters computed subsequently. In this study, digital elevation models (DEM) derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER V2), Shuttle Radar Topography Mission (SRTM V4, C-Band, 3 arc-second), Cartosat -1 (CartoDEM 1.0) and topographical maps (R.F. 1:250,000 and 1:50,000), have been used to individually extract and analyze the relief, surface, size, shape and texture properties of a mountainous drainage basin. Nestled inside a mountainous setting, the basin is a semi-elongated one with high relief ratio (>90), steep slopes (25°-30°) and high drainage density (>3.5 km/sq km), as computed from the different DEMs. The basin terrain and stream network is extracted from each DEM, whose morphometric attributes are compared with the surveyed stream networks present in the topographical maps, with resampling of finer DEM datasets to coarser resolutions, to reduce scale-implications during the delineation process. Ground truth verifications for altitudinal accuracy have also been done by a GPS survey. DEMs derived from the 1:50,000 topographical map and ASTER GDEM V2 data are found to be more accurate and consistent in terms of absolute accuracy, than the other generated or available DEM data products, on basis of the morphometric parameters extracted from each. They also exhibit a certain degree of proximity to the surveyed topographical map.

Origin and Variability of Upper Tropospheric Nitrogen Oxides and Ozone at Northern Mid-Latitudes

NASA Technical Reports Server (NTRS)

Grewe, V.; Brunner, D.; Dameris, M.; Grenfell, J. L.; Hein, R.; Shindell, D.; Staehelin, J.

1999-01-01

Measurements of NO(x) and ozone performed during the NOXAR project are compared with results from the coupled chemistry-climate models ECHAM4.L39(DLR)/CHEM and GISS-model. The measurements are based on flights between Europe and the East coast of America and between Europe and the Far East in the latitude range 40 deg N to 65 deg N. The comparison concentrates on tropopause altitudes and reveals strong longitudinal variations of seasonal mean NO,, of 200 pptv. Either model reproduced strong variations 3 km below but not at the tropopause, indicating a strong missing NO(x) or NO(y) sink over remote areas, e.g. NO(x) to HNO3 conversion by OH from additional OH sources or HNO3 wash-out. Vertical profiles show maximum NO(x) values 2-3 km below the tropopause with a strong seasonal cycle. ECHAM4.L39(DLR)/CHEM reproduces a maximum, although located at the tropopause with a less pronounced seasonal cycle, whereas the GISS model reproduces the seasonal cycle but not the profile's shape due to its coarser vertical resolution. A comparison of NO(x) frequency distributions reveals that both models are capable of reproducing the observed variability, except that ECHAM4.L39(DLR)/CHEM shows no very high NO(x) mixing ratios. Ozone mean values, vertical profiles and frequency distributions are much better reproduced in either model, indicating that the NO(x) frequency distribution, namely the most frequent NO(x) mixing ratio, is more important for the tropospheric photochemical ozone production than its mean value. Both models show that among all sources, NO(x) from lightning contributes most to the seasonal cycle of NO(x) at tropopause altitudes. The impact of lightning in the upper troposphere on NO(x) does not vary strongly with altitude, whereas the impact of surface emissions decreases with altitude. However, the models show significant differences in lightning induced NO(x) concentrations, especially in winter, which may be related to the different treatment of the lower stratospheric coupling between dynamics and chemistry.

Poly-Pattern Compressive Segmentation of ASTER Data for GIS

NASA Technical Reports Server (NTRS)

Myers, Wayne; Warner, Eric; Tutwiler, Richard

2007-01-01

Pattern-based segmentation of multi-band image data, such as ASTER, produces one-byte and two-byte approximate compressions. This is a dual segmentation consisting of nested coarser and finer level pattern mappings called poly-patterns. The coarser A-level version is structured for direct incorporation into geographic information systems in the manner of a raster map. GIs renderings of this A-level approximation are called pattern pictures which have the appearance of color enhanced images. The two-byte version consisting of thousands of B-level segments provides a capability for approximate restoration of the multi-band data in selected areas or entire scenes. Poly-patterns are especially useful for purposes of change detection and landscape analysis at multiple scales. The primary author has implemented the segmentation methodology in a public domain software suite.

Enhancing PTFs with remotely sensed data for multi-scale soil water retention estimation

NASA Astrophysics Data System (ADS)

Jana, Raghavendra B.; Mohanty, Binayak P.

2011-03-01

SummaryUse of remotely sensed data products in the earth science and water resources fields is growing due to increasingly easy availability of the data. Traditionally, pedotransfer functions (PTFs) employed for soil hydraulic parameter estimation from other easily available data have used basic soil texture and structure information as inputs. Inclusion of surrogate/supplementary data such as topography and vegetation information has shown some improvement in the PTF's ability to estimate more accurate soil hydraulic parameters. Artificial neural networks (ANNs) are a popular tool for PTF development, and are usually applied across matching spatial scales of inputs and outputs. However, different hydrologic, hydro-climatic, and contaminant transport models require input data at different scales, all of which may not be easily available from existing databases. In such a scenario, it becomes necessary to scale the soil hydraulic parameter values estimated by PTFs to suit the model requirements. Also, uncertainties in the predictions need to be quantified to enable users to gauge the suitability of a particular dataset in their applications. Bayesian Neural Networks (BNNs) inherently provide uncertainty estimates for their outputs due to their utilization of Markov Chain Monte Carlo (MCMC) techniques. In this paper, we present a PTF methodology to estimate soil water retention characteristics built on a Bayesian framework for training of neural networks and utilizing several in situ and remotely sensed datasets jointly. The BNN is also applied across spatial scales to provide fine scale outputs when trained with coarse scale data. Our training data inputs include ground/remotely sensed soil texture, bulk density, elevation, and Leaf Area Index (LAI) at 1 km resolutions, while similar properties measured at a point scale are used as fine scale inputs. The methodology was tested at two different hydro-climatic regions. We also tested the effect of varying the support scale of the training data for the BNNs by sequentially aggregating finer resolution training data to coarser resolutions, and the applicability of the technique to upscaling problems. The BNN outputs are corrected for bias using a non-linear CDF-matching technique. Final results show good promise of the suitability of this Bayesian Neural Network approach for soil hydraulic parameter estimation across spatial scales using ground-, air-, or space-based remotely sensed geophysical parameters. Inclusion of remotely sensed data such as elevation and LAI in addition to in situ soil physical properties improved the estimation capabilities of the BNN-based PTF in certain conditions.

The First Four Year's of Orthoimages from NEON's Airborne Observation Platform

NASA Astrophysics Data System (ADS)

Adler, J.; Gallery, W. O.

2016-12-01

The National Ecological Observatory Network (NEON), funded by the National Science Foundation (NSF), has been collecting orthorectified images in conjunction with lidar and spectrometer data for the past four years. The NEON project breaks up the United States into 20 regional areas from Puerto Rico to the North Slope of Alaska, with each region (Domain) typically having three specific sites of interest. Each site spans between 100km2 - 720km2 in area. Currently there are over 125,000 orthorectified images online from 6 Domains for the public and scientific community to freely download. These images are expected to assist researchers in many areas including vegetation cover, dominant vegetation type, and environmental change detection. In 2016 the NEON Airborne Observation Platform (AOP) group has collected digital imagery at 8.5 cm resolution over approximately 30 sites, for a total of 60,000 orthoimages. This presentation details the current status of the surveys conducted to date, and describes the scientific details of how NEON publishes Level 1 and Level 3 products. In particular, the onboard lidar system's contribution to the orthorectification process is outlined, in addition to the routines utilized for correcting white balance and exposure. Additionally, key flight parameters needed to produce NEON's complementary data of multi-sensor (camera/lidar/spectrometer) instruments are discussed. Problems with validating the orthoimages with the coarser resolution lidar system are addressed, to include the utilization of ground-truth locations. Lastly, methods to access NEON's publically available 10cm resolution orthoimages (in both individual image format, and in 1km by 1km tiles) are presented. A brief overview of the 2017 field season's nine new sites completes the presentation.

Drone based estimation of actual evapotranspiration over different forest types

NASA Astrophysics Data System (ADS)

Marzahn, Philip; Gampe, David; Castro, Saulo; Vega-Araya, Mauricio; Sanchez-Azofeifa, Arturo; Ludwig, Ralf

2017-04-01

Actual evapotranspiration (Eta) plays an important role in surface-atmosphere interactions. Traditionally, Eta is measured by means of lysimeters, eddy-covariance systems or fiber optics, providing estimates which are spatially restricted to a footprint from a few square meters up to several hectares . In the past, several methods have been developed to derive Eta by means of multi-spectral remote sensing data using thermal and VIS/NIR satellite imagery of the land surface. As such approaches do have their justification on coarser scales, they do not provide Eta information on the fine resolution plant level over large areas which is mandatory for the detection of water stress or tree mortality. In this study, we present a comparison of a drone based assessment of Eta with eddy-covariance measurements over two different forest types - a deciduous forest in Alberta, Canada and a tropical dry forest in Costa Rica. Drone based estimates of Eta were calculated applying the Triangle-Method proposed by Jiang and Islam (1999). The Triangle-Method estimates actual evapotranspiration (Eta) by means of the Normalized Difference Vegetation Index (NDVI) and land surface temperature (LST) provided by two camera systems (MicaSense RedEdge, FLIR TAU2 640) flown simultaneously on an octocopter. . Results indicate a high transferability of the original approach from Jiang and Islam (1999) developed for coarse to medium resolution satellite imagery tothe high resolution drone data, leading to a deviation in Eta estimates of 10% compared to the eddy-covariance measurements. In addition, the spatial footprint of the eddy-covariance measurement can be detected with this approach, by showing the spatial heterogeneities of Eta due to the spatial distribution of different trees and understory vegetation.

Multiscale registration algorithm for alignment of meshes

NASA Astrophysics Data System (ADS)

Vadde, Srikanth; Kamarthi, Sagar V.; Gupta, Surendra M.

2004-03-01

Taking a multi-resolution approach, this research work proposes an effective algorithm for aligning a pair of scans obtained by scanning an object's surface from two adjacent views. This algorithm first encases each scan in the pair with an array of cubes of equal and fixed size. For each scan in the pair a surrogate scan is created by the centroids of the cubes that encase the scan. The Gaussian curvatures of points across the surrogate scan pair are compared to find the surrogate corresponding points. If the difference between the Gaussian curvatures of any two points on the surrogate scan pair is less than a predetermined threshold, then those two points are accepted as a pair of surrogate corresponding points. The rotation and translation values between the surrogate scan pair are determined by using a set of surrogate corresponding points. Using the same rotation and translation values the original scan pairs are aligned. The resulting registration (or alignment) error is computed to check the accuracy of the scan alignment. When the registration error becomes acceptably small, the algorithm is terminated. Otherwise the above process is continued with cubes of smaller and smaller sizes until the algorithm is terminated. However at each finer resolution the search space for finding the surrogate corresponding points is restricted to the regions in the neighborhood of the surrogate points that were at found at the preceding coarser level. The surrogate corresponding points, as the resolution becomes finer and finer, converge to the true corresponding points on the original scans. This approach offers three main benefits: it improves the chances of finding the true corresponding points on the scans, minimize the adverse effects of noise in the scans, and reduce the computational load for finding the corresponding points.

Tracking stormwater discharge plumes and water quality of the Tijuana River with multispectral aerial imagery

NASA Astrophysics Data System (ADS)

Svejkovsky, Jan; Nezlin, Nikolay P.; Mustain, Neomi M.; Kum, Jamie B.

2010-04-01

Spatial-temporal characteristics and environmental factors regulating the behavior of stormwater runoff from the Tijuana River in southern California were analyzed utilizing very high resolution aerial imagery, and time-coincident environmental and bacterial sampling data. Thirty nine multispectral aerial images with 2.1-m spatial resolution were collected after major rainstorms during 2003-2008. Utilizing differences in color reflectance characteristics, the ocean surface was classified into non-plume waters and three components of the runoff plume reflecting differences in age and suspended sediment concentrations. Tijuana River discharge rate was the primary factor regulating the size of the freshest plume component and its shorelong extensions to the north and south. Wave direction was found to affect the shorelong distribution of the shoreline-connected fresh plume components much more strongly than wind direction. Wave-driven sediment resuspension also significantly contributed to the size of the oldest plume component. Surf zone bacterial samples collected near the time of each image acquisition were used to evaluate the contamination characteristics of each plume component. The bacterial contamination of the freshest plume waters was very high (100% of surf zone samples exceeded California standards), but the oldest plume areas were heterogeneous, including both polluted and clean waters. The aerial imagery archive allowed study of river runoff characteristics on a plume component level, not previously done with coarser satellite images. Our findings suggest that high resolution imaging can quickly identify the spatial extents of the most polluted runoff but cannot be relied upon to always identify the entire polluted area. Our results also indicate that wave-driven transport is important in distributing the most contaminated plume areas along the shoreline.

Conservation threats and the phylogenetic utility of IUCN Red List rankings in Incilius toads.

PubMed

Schachat, Sandra R; Mulcahy, Daniel G; Mendelson, Joseph R

2016-02-01

Phylogenetic analysis of extinction threat is an emerging tool in the field of conservation. However, there are problems with the methods and data as commonly used. Phylogenetic sampling usually extends to the level of family or genus, but International Union for Conservation of Nature (IUCN) rankings are available only for individual species, and, although different species within a taxonomic group may have the same IUCN rank, the species may have been ranked as such for different reasons. Therefore, IUCN rank may not reflect evolutionary history and thus may not be appropriate for use in a phylogenetic context. To be used appropriately, threat-risk data should reflect the cause of extinction threat rather than the IUCN threat ranking. In a case study of the toad genus Incilius, with phylogenetic sampling at the species level (so that the resolution of the phylogeny matches character data from the IUCN Red List), we analyzed causes of decline and IUCN threat rankings by calculating metrics of phylogenetic signal (such as Fritz and Purvis' D). We also analyzed the extent to which cause of decline and threat ranking overlap by calculating phylogenetic correlation between these 2 types of character data. Incilius species varied greatly in both threat ranking and cause of decline; this variability would be lost at a coarser taxonomic resolution. We found far more phylogenetic signal, likely correlated with evolutionary history, for causes of decline than for IUCN threat ranking. Individual causes of decline and IUCN threat rankings were largely uncorrelated on the phylogeny. Our results demonstrate the importance of character selection and taxonomic resolution when extinction threat is analyzed in a phylogenetic context. © 2015 Society for Conservation Biology.

Testing Snow Melt Algorithms in High Relief Topography Using Calibrated Enhanced-Resolution Brightness Temperatures, Hunza River Basin, Pakistan

NASA Astrophysics Data System (ADS)

Ramage, J. M.; Brodzik, M. J.; Hardman, M.; Troy, T. J.

2017-12-01

Snow is a vital part of the terrestrial hydrological cycle, a crucial resource for people and ecosystems. In mountainous regions snow is extensive, variable, and challenging to document. Snow melt timing and duration are important factors affecting the transfer of snow mass to soil moisture and runoff. Passive microwave brightness temperature (Tb) changes at 36 and 18 GHz are a sensitive way to detect snow melt onset due to their sensitivity to the abrupt change in emissivity. They are widely used on large icefields and high latitude watersheds. The coarse resolution ( 25 km) of historically available data has precluded effective use in high relief, heterogeneous regions, and gaps between swaths also create temporal data gaps at lower latitudes. New enhanced resolution data products generated from a scatterometer image reconstruction for radiometer (rSIR) technique are available at the original frequencies. We use these Calibrated Enhanced-resolution Brightness (CETB) Temperatures Earth System Data Records (ESDR) to evaluate existing snow melt detection algorithms that have been used in other environments, including the cross polarized gradient ratio (XPGR) and the diurnal amplitude variations (DAV) approaches. We use the 36/37 GHz (3.125 km resolution) and 18/19 GHz (6.25 km resolution) vertically and horizontally polarized datasets from the Special Sensor Microwave Imager (SSM/I) and Advanced Microwave Radiometer for EOS (AMSR-E) and evaluate them for use in this high relief environment. The new data are used to assess glacier and snow melt records in the Hunza River Basin [area 13,000 sq. km, located at 36N, 74E], a tributary to the Upper Indus Basin, Pakistan. We compare the melt timing results visually and quantitatively to the corresponding EASE-Grid 2.0 25-km dataset, SRTM topography, and surface temperatures from station and reanalysis data. The new dataset is coarser than the topography, but is able to differentiate signals of melt/refreeze timing for different altitudes and land cover in this remote area with significant hazards from snow melt and glacier discharge. The improved spatial resolution, enhanced to 3-6 km, and retaining twice daily observations is a key improvement to fully analyze snowpack melt characteristics in remote mountainous regions.

Comparison of S-NPP VIIRS land surface temperature with SEVIRI

NASA Astrophysics Data System (ADS)

Ermida, Sofia L.; Trigo, Isabel F.; Liu, Yuling; Yu, Yunyue

2017-04-01

Land surface temperature (LST) is one of the key parameters in the physics of land surface processes. LST can be globally measured from space by infrared radiometers, with a wide range of spatial and temporal resolutions depending on the sensor design and orbit. The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument is the primary sensor onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite, which was launched in recent years. VIIRS was designed to improve upon the capabilities of the operational AVHRR and provide observation continuity with MODIS. A Split Window approach has been applied to the VIIRS moderate resolution channels M15 and M16 centered at 10.76 µm and 12.01 µm, respectively. VIIRS has a swath of 3000 km and a spatial resolution of 745m (nadir) up to about 1600 m (limb view), leading to relatively high re-visiting frequency. LST is retrieved for a wide range of viewing angles along the VIIRS path, allowing the study of the variability of LST with viewing geometry for various land cover types. Here we present a comparison of VIRS LST data with data provided by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on-board EUMETSAT's Meteosat Second Generation (MSG). SEVIRI-based LST is available every 15-minute, but at coarser spatial resolution (3-km at nadir) when compared to VIIRS LST. The analysis is performed over 6 areas over the SEVIRI disk characterized by different surface conditions. VIIRS has generally slightly warmer night-time LST compared with SEVIRI, with differences smaller than 2K. Larger differences are found during daytime, with VIIRS presenting overall lower LST values up to 5K. These differences are also analysed taking into account the surface type, view zenith angle (VZA) and topography. As seen in previous comparison studies, high VZA and elevation values are associated to higher discrepancies of the LST products.

Satellite Sounder Data Assimilation for Improving Alaska Region Weather Forecast

NASA Technical Reports Server (NTRS)

Zhu, Jiang; Stevens, E.; Zavodsky, B. T.; Zhang, X.; Heinrichs, T.; Broderson, D.

2014-01-01

Data assimilation has been demonstrated very useful in improving both global and regional numerical weather prediction. Alaska has very coarser surface observation sites. On the other hand, it gets much more satellite overpass than lower 48 states. How to utilize satellite data to improve numerical prediction is one of hot topics among weather forecast community in Alaska. The Geographic Information Network of Alaska (GINA) at University of Alaska is conducting study on satellite data assimilation for WRF model. AIRS/CRIS sounder profile data are used to assimilate the initial condition for the customized regional WRF model (GINA-WRF model). Normalized standard deviation, RMSE, and correlation statistic analysis methods are applied to analyze one case of 48 hours forecasts and one month of 24-hour forecasts in order to evaluate the improvement of regional numerical model from Data assimilation. The final goal of the research is to provide improved real-time short-time forecast for Alaska regions.

The impact of forest structure and spatial scale on the relationship between ground plot above ground biomass and GEDI lidar waveforms

NASA Astrophysics Data System (ADS)

Armston, J.; Marselis, S.; Hancock, S.; Duncanson, L.; Tang, H.; Kellner, J. R.; Calders, K.; Disney, M.; Dubayah, R.

2017-12-01

The NASA Global Ecosystem Dynamics Investigation (GEDI) will place a multi-beam waveform lidar instrument on the International Space Station (ISS) to provide measurements of forest vertical structure globally. These measurements of structure will underpin empirical modelling of above ground biomass density (AGBD) at the scale of individual GEDI lidar footprints (25m diameter). The GEDI pre-launch calibration strategy for footprint level models relies on linking AGBD estimates from ground plots with GEDI lidar waveforms simulated from coincident discrete return airborne laser scanning data. Currently available ground plot data have variable and often large uncertainty at the spatial resolution of GEDI footprints due to poor colocation, allometric model error, sample size and plot edge effects. The relative importance of these sources of uncertainty partly depends on the quality of ground measurements and region. It is usually difficult to know the magnitude of these uncertainties a priori so a common approach to mitigate their influence on model training is to aggregate ground plot and waveform lidar data to a coarser spatial scale (0.25-1ha). Here we examine the impacts of these principal sources of uncertainty using a 3D simulation approach. Sets of realistic tree models generated from terrestrial laser scanning (TLS) data or parametric modelling matched to tree inventory data were assembled from four contrasting forest plots across tropical rainforest, deciduous temperate forest, and sclerophyll eucalypt woodland sites. These tree models were used to simulate geometrically explicit 3D scenes with variable tree density, size class and spatial distribution. GEDI lidar waveforms are simulated over ground plots within these scenes using monte carlo ray tracing, allowing the impact of varying ground plot and waveform colocation error, forest structure and edge effects on the relationship between ground plot AGBD and GEDI lidar waveforms to be directly assessed. We quantify the sensitivity of calibration equations relating GEDI lidar structure measurements and AGBD to these factors at a range of spatial scales (0.0625-1ha) and discuss the implications for the expanding use of existing in situ ground plot data by GEDI.

Laboratory evaluation of the Sequoia Scientific LISST-ABS acoustic backscatter sediment sensor

USGS Publications Warehouse

Snazelle, Teri T.

2017-12-18

Sequoia Scientific’s LISST-ABS is an acoustic backscatter sensor designed to measure suspended-sediment concentration at a point source. Three LISST-ABS were evaluated at the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF). Serial numbers 6010, 6039, and 6058 were assessed for accuracy in solutions with varying particle-size distributions and for the effect of temperature on sensor accuracy. Certified sediment samples composed of different ranges of particle size were purchased from Powder Technology Inc. These sediment samples were 30–80-micron (µm) Arizona Test Dust; less than 22-µm ISO 12103-1, A1 Ultrafine Test Dust; and 149-µm MIL-STD 810E Silica Dust. The sensor was able to accurately measure suspended-sediment concentration when calibrated with sediment of the same particle-size distribution as the measured. Overall testing demonstrated that sensors calibrated with finer sized sediments overdetect sediment concentrations with coarser sized sediments, and sensors calibrated with coarser sized sediments do not detect increases in sediment concentrations from small and fine sediments. These test results are not unexpected for an acoustic-backscatter device and stress the need for using accurate site-specific particle-size distributions during sensor calibration. When calibrated for ultrafine dust with a less than 22-µm particle size (silt) and with the Arizona Test Dust with a 30–80-µm range, the data from sensor 6039 were biased high when fractions of the coarser (149-µm) Silica Dust were added. Data from sensor 6058 showed similar results with an elevated response to coarser material when calibrated with a finer particle-size distribution and a lack of detection when subjected to finer particle-size sediment. Sensor 6010 was also tested for the effect of dissimilar particle size during the calibration and showed little effect. Subsequent testing revealed problems with this sensor, including an inadequate temperature compensation, making this data questionable. The sensor was replaced by Sequoia Scientific with serial number 6039. Results from the extended temperature testing showed proper temperature compensation for sensor 6039, and results from the dissimilar calibration/testing particle-size distribution closely corroborated the results from sensor 6058.

Mineral Fractionation during Sediment Comminution and Transport in Fluvio-Deltaic and Lacustrine Rocks of the Bradbury Group, Gale Crater, Mars

NASA Astrophysics Data System (ADS)

Siebach, K. L.; Baker, M. B.; Grotzinger, J. P.; McLennan, S. M.; Gellert, R.; Thompson, L. M.; Hurowitz, J.

2017-12-01

Mineral distribution patterns in sediments of the Bradbury group in Gale crater, interpreted from observations by the Mars Science Laboratory rover Curiosity, show the importance of transport mechanics in source-to-sink processes on Mars. The Bradbury group is comprised of basalt-derived mudstones to conglomerates exposed along the modern floor of Gale crater and analyzed along a 9-km traverse of the Curiosity rover. Over 110 bulk chemistry analyses of the rocks were acquired, along with two XRD mineralogical analyses of the mudstone. These rocks are uniquely suited for analysis of source-to-sink processes because they exhibit a wide range of compositions, but (based on multiple chemical weathering proxies) they appear to have experienced negligible cation-loss during weathering and erosion. Chemical variations between analyses correlate with sediment grain sizes, with coarser-grained rocks enriched in plagioclase components SiO2, Al2O3, and Na2O, and finer-grained rocks enriched in components of mafic minerals, consistent with grain-size sorting of mineral fractions during sediment transport. Further geochemical and mineralogical modeling supports the importance of mineral fractionation: even though the limited XRD data suggests that some fraction (if not all) of the rocks contain clays and an amorphous component, models show that 90% of the compositions measured are consistent with sorting of primary igneous minerals from a plagioclase-phyric subalkaline basalt (i.e., no corrections for cation-loss are required). The distribution of K2O, modeled as a potassium feldspar component, is an exception to the major-element trends because it does not correlate with grain size, but has an elevation-dependent signal likely correlated with the introduction of a second source material. However, the dominant compositional trends within the Bradbury group sedimentary rocks are correlated with grain size and consistent with mineral fractionation of minimally-weathered plagioclase-phyric basalts; the plagioclase phenocrysts settle into coarser deposits and the finer deposits are dominated by mafic minerals.

A 1500-year holocene caribbean climate archive from the Blue Hole, lighthouse reef, belize

USGS Publications Warehouse

Gischler, E.; Shinn, E.A.; Oschmann, W.; Fiebig, J.; Buster, N.A.

2008-01-01

Sediment cores (up to 6 m in length) from the bottom of the Blue Hole, a 125 m deep Pleistocene sinkhole located in the lagoon of Lighthouse Reef Atoll, Belize, consist of undisturbed, annually layered biogenic carbonate muds and silts with intercalated coarser grained storm beds. The sedimentation rate of the layered sections is 2.5 mm/y on average, and the long cores span the past 1500 years. Oxygen isotopes of laminated sediment provide a late Holocene climate proxy: A high-resolution ??18O time series traces the final Migration Period Pessimum, the Medieval Warm Period, the Little Ice Age, and the subsequent temperature rise. Carbon isotopes (??13C) decrease up core and show the impacts of the decline of the Mayan culture and the Suess effect. Time series analyses of ??18O and ??13C content reveal 88-, 60-, 52-, and 32-year cyclicities, and suggest solar forcing. Storm event beds are most common during AD 650-850, around AD 1000, during AD 1200-1300, and AD 1450-1550. Major storm beds are rare during the past 500 years BP.

In Situ Validation of the Soil Moisture Active Passive (SMAP) Satellite Mission

NASA Technical Reports Server (NTRS)

Jackson, T.; Cosh, M.; Crow, W.; Colliander, A.; Walker, J.

2011-01-01

SMAP is a new NASA mission proposed for 2014 that would provide a number of soil moisture and freeze/thaw products. The soil moisture products span spatial resolutions from 3 to 40 km. In situ soil moisture observations will be one of the key elements of the validation program for SMAP. Data from the currently available set of soil moisture observing sites and networks need improvement if they are to be useful. Problems include a lack of standardization of instrumentation and installation and the disparity in spatial scale between the point-scale in situ data (a few centimeters) and the coarser satellite products. SMAP has initiated activities to resolve these issues for some of the existing resources. The other challenge to soil moisture validation is the need to expand the number of sites and their geographic distribution. SMAP is attempting to increase the number of sites and their value in validation through collaboration. The issues and solutions involving in situ validation being investigated will be described along with recent results from SMAP validation projects.

An observationally-driven kinetic approach to coronal heating

NASA Astrophysics Data System (ADS)

Moraitis, K.; Toutountzi, A.; Isliker, H.; Georgoulis, M.; Vlahos, L.; Chintzoglou, G.

2016-11-01

Aims: Coronal heating through the explosive release of magnetic energy remains an open problem in solar physics. Recent hydrodynamical models attempt an investigation by placing swarms of "nanoflares" at random sites and times in modeled one-dimensional coronal loops. We investigate the problem in three dimensions, using extrapolated coronal magnetic fields of observed solar active regions. Methods: We applied a nonlinear force-free field extrapolation above an observed photospheric magnetogram of NOAA active region (AR) 11 158. We then determined the locations, energy contents, and volumes of "unstable" areas, namely areas prone to releasing magnetic energy due to locally accumulated electric current density. Statistical distributions of these volumes and their fractal dimension are inferred, investigating also their dependence on spatial resolution. Further adopting a simple resistivity model, we inferred the properties of the fractally distributed electric fields in these volumes. Next, we monitored the evolution of 105 particles (electrons and ions) obeying an initial Maxwellian distribution with a temperature of 10 eV, by following their trajectories and energization when subjected to the resulting electric fields. For computational convenience, the length element of the magnetic-field extrapolation is 1 arcsec, or 725 km, much coarser than the particles' collisional mean free path in the low corona (0.1-1 km). Results: The presence of collisions traps the bulk of the plasma around the unstable volumes, or current sheets (UCS), with only a tail of the distribution gaining substantial energy. Assuming that the distance between UCS is similar to the collisional mean free path we find that the low active-region corona is heated to 100-200 eV, corresponding to temperatures exceeding 2 MK, within tens of seconds for electrons and thousands of seconds for ions. Conclusions: Fractally distributed, nanoflare-triggening fragmented UCS in the active-region corona can heat electrons and ions with minor enhancements of the local resistivity. This statistical result is independent from the nature of the extrapolation and the spatial resolution of the modeled active-region corona. This finding should be coupled with a complete plasma treatment to determine whether a quasi-steady temperature similar to that of the ambient corona can be maintained, either via a kinetic or via a hybrid, kinetic and fluid, plasma treatment. The finding can also be extended to the quiet solar corona, provided that the currently undetected nanoflares are frequent enough to account for the lower (compared to active regions) energy losses in this case.

SU-F-T-179: Fast and Accurate Profile Acquisition for Proton Beam Using Multi-Ion Chamber Arrays

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

Wang, X; Zou, J; Chen, T

2016-06-15

Purpose: Proton beam profile measurement is more time-consuming than photon beam. Due to the energy modulation during proton delivery, chambers have to move step-by-step instead of continuously. Multi-ion chamber arrays are appealing to this task since multiple measurements can be performed at once. However, their utilization suffers from sparse spatial resolution and potential intrinsic volume-averaging effect of the disk-shaped ion chambers. We proposed an approach to measure proton beam profiles accurately and efficiently. Methods: Mevion S250 proton system and IBA Matrixx ion chamber arrays were used in this study. Matrixx has interchamber distance of 7.62 mm, and chamber diameter ofmore » 4.5 mm. We measured the same beam profile by moving the Matrixx seven times with 1 mm each time along y axis. All 7 measurements were superimposed to get a “finer” profile with 1 mm spatial resolution. Coarser resolution profiles of 2 mm and 3 mm were also generated by using subsets of measurements. Those profiles were compared to the TPS calculated beam profile. Gamma analysis was performed for 2D dose maps to evaluate the difference to TPS dose plane. Results: Preliminary results showed a large discrepancy between the TPS calculated profile and the single measurement profile with 7.6 mm resolution. A good match could be achieved when the resolution reduced to 3 mm by adding one extra measurement. Gamma analysis for 2D dose map of a 10×10 field showed a passing rate (γ ≤ 1) of 90.6% using a 3% and 3mm criterion for single measurement, which increased to 92.3% for 2-measurement superimposition, and slightly further increased to 92.9% for 7-measurement superimposition. Conclusion: The results indicated that 2 measurements shifted by 3mm using Matrixx generated a smooth proton beam profile with good matching to Eclipse beam profile. We suggest using this 2-measurement approach in clinic for double scattering proton beam profile measurement.« less

'Fluffy' Type A Ca-, Al-rich inclusions in the Allende meteorite

NASA Technical Reports Server (NTRS)

Macpherson, G. J.; Grossman, L.

1984-01-01

Inclusions called 'fluffy' Type A's or FTA's in the Allende meteorite are examined as possible candidates for relict vapor-solid condensate grains, remaining from the original solar nebula. Type A inclusions are characterized by abundant melilite and absence of primary anorthite and titaniferous pyroxene. Fluffy Type A's were probably loosely bound clumps of crystals drifting in the solar nebula, analogous to dustballs or snowflakes. Polished thin sections of all samples were studied optically and with a JEOL JSM-35 scanning electron microscope. It is reasonably clear that neither whole FTA's nor constituent nodules of the coarser grained ones were ever molten. Despite solid-state recrystallization which has affected these inclusions to varying degrees, the coarser grained material remaining in many of them is probably a relic of vapor-solid condensation in the solar nebula.

Simultaneous reduction and carburization of ilmenite

NASA Astrophysics Data System (ADS)

Coley, K. S.; Terry, B. S.; Grieveson, P.

1995-05-01

Western Australian ilmenite was reduced using “Collie” coal at temperatures in the range 1587 to 1790 K to form carbon-saturated iron and titanium oxycarbide. The oxycarbide phase formed from Ti3O5 at temperatures below 1686 K and from Ti2O3 at temperatures above 1686 K. At 1686 K, both mechanisms occurred. The reaction rate was controlled by oxidation of carbon by carbon dioxide generated by reduction of the oxide phase. The final product at temperatures up to 1686 K was a fine dispersion of titanium oxycarbide in iron. At 1790 K, the reducing oxide tended to remain intact and formed a coarser distribution. In general, manganese impurities from the ilmenite were confined to the iron phase in the product, although some of the coarser oxycarbide particles formed at 1790 K contained trapped manganese at the internal pores.

Metal powder production by gas atomization

NASA Technical Reports Server (NTRS)

Ting, E. Y.; Grant, N. J.

1986-01-01

The confined liquid, gas-atomization process was investigated. Results from a two-dimensional water model showed the importance of atomization pressure, as well as delivery tube and atomizer design. The atomization process at the tip of the delivery tube was photographed. Results from the atomization of a modified 7075 aluminum alloy yielded up to 60 wt pct. powders that were finer than 45 microns in diameter. Two different atomizer designs were evaluated. The amount of fine powders produced was correlated to a calculated gas-power term. An optimal gas-power value existed for maximized fine powder production. Atomization at gas-power greater than or less than this optimal value produced coarser powders.

Subsurface flows in the seasonally stratified central North Sea : analysis of drifter tracks through observations and modelling

NASA Astrophysics Data System (ADS)

Chambers, C.; McCloghrie, P.; Fernand, L.; Brown, J.; Young, E. F.

2003-04-01

Holey-sock drifters have been tracked by ARGOS satellite in the Central North Sea during summer-stratified conditions of 1996, 1997, 1999, 2001 and 2002. Drogued at depths of 20-30m, they aim to capture the baroclinic jets set up by isolated cold pool bottom fronts. These cold pools of relict winter water remain through the summer in areas of low tidal energy and are effectively sealed off from overlying waters by a strong thermocline. Observational and modelling studies have identified such dynamics in the basins both north of the Dogger Bank - Fladen Grounds - and south - Oyster Grounds. The drifter tracks used in this study were interpolated and tidally filtered to produce regular time interval drifter positions. By correlation with wind data from the UK Meteorological Office Unified Model output, the locally wind-driven and baroclinic components of the drifters' flow were determined. Following assessments of (1) individual drifter tracks and (2) spatial/temporal segmentation of the collective drifter tracks, a regional and interannual understanding of the area has been built up. Additional observational data (including that gathered with high resolution towed undulating CTD's on a Scanfish) have been used to support and quantify the flows, as has a 3-D density-resolving model based on the Princeton Ocean Model (POM). The drifters have been simulated using a particle-tracking model run on POM's flow field output, simulating the paths of drifters at depth. Through running the two together in various modes, it has been possible to account for certain parts of the drifters' tracks. These results contribute to a previously coarser understanding of North Sea circulation and show the importance of seasonal structure there. They demonstrate that fast baroclinic jets have the potential to transport biological and contaminant matter (e.g., fish larvae/eggs; and nutrients/heavy metals) in different and more organised flow fields than those previously recognised. This understanding is essential to the monitoring and management of such a semi-enclosed and intensively used area as the North Sea.

New insights into the geodiversity of the southeast Indian Ocean seafloor revealed by Malaysia Airlines flight MH370 search data

NASA Astrophysics Data System (ADS)

Picard, K.; Brooke, B. B.; Harris, P. T.; Siwabessy, J. P. W.; Coffin, M. F.; Tran, M.; Spinoccia, M.; Weales, J.; Macmillan-Lawler, M.; Sullivan, J.

2017-12-01

A large multibeam echo sounder (MBES) dataset (710, 000 km2, inclusive of transit data) was acquired in the SE Indian Ocean to assist the search for Malaysia Airlines Flight 370 (MH370). Here, we present the results of a geomorphic analysis of this new data and compare with the Global Seafloor Geomorphic Features Map (GSFM) that is based on coarser resolution satellite-derived bathymetry data. The analyses show that abyssal plains and basins are significantly more rugged than their representation in the GSFM, with a 20% increase in the extent of hills and mountains. The new model also reveals four times more seamounts than presented in the GSFM, suggesting a greater number of these features than previously estimated for the broader region and indeed globally. This is important considering the potential ecological significance of these high-relief structures. Analyses of the new data also enabled knolls, fans, valleys, canyons, troughs and holes to be identified, doubling the number of discrete features mapped and revealing the true geodiversity of the deep ocean in this area. This high-resolution mapping of the seafloor also provides new insights into the geological evolution of the region, both in terms of structural, tectonic, and sedimentary processes. For example, sub-parallel ridges extend over approximately 20% of the area mapped and their form and alignment provide valuable insight into Southeast Indian Ridge seafloor spreading processes. Rifting is recorded along the Broken Ridge - Diamantina Escarpment, with rift blocks and well-bedded sedimentary bedrock exposures discernible down to 2,400 m water depth. Ocean floor sedimentary processes are represented in sediment mass transport features, especially along and north of Broken Ridge, and pockmarks (the finest-scale features mapped) south of Diamantina Trench. The new MBES data highlight the complexity of the search area and serve to demonstrate how little we know about the 85-90% of the ocean floor that has not been mapped with this technology. The availability of high-resolution and accurate maps of the ocean floor can clearly provide new insights into the Earth's geological evolution, modern ocean floor processes, and the location of sites that are likely to have relatively high biodiversity.

All-weather Land Surface Temperature Estimation from Satellite Data

NASA Astrophysics Data System (ADS)

Zhou, J.; Zhang, X.

2017-12-01

Satellite remote sensing, including the thermal infrared (TIR) and passive microwave (MW), provides the possibility to observe LST at large scales. For better modeling the land surface processes with high temporal resolutions, all-weather LST from satellite data is desirable. However, estimation of all-weather LST faces great challenges. On the one hand, TIR remote sensing is limited to clear-sky situations; this drawback reduces its usefulness under cloudy conditions considerably, especially in regions with frequent and/or permanent clouds. On the other hand, MW remote sensing suffers from much greater thermal sampling depth (TSD) and coarser spatial resolution than TIR; thus, MW LST is generally lower than TIR LST, especially at daytime. Two case studies addressing the challenges mentioned previously are presented here. The first study is for the development of a novel thermal sampling depth correction method (TSDC) to estimate the MW LST over barren land; this second study is for the development of a feasible method to merge the TIR and MW LSTs by addressing the coarse resolution of the latter one. In the first study, the core of the TSDC method is a new formulation of the passive microwave radiation balance equation, which allows linking bulk MW radiation to the soil temperature at a specific depth, i.e. the representative temperature: this temperature is then converted to LST through an adapted soil heat conduction equation. The TSDC method is applied to the 6.9 GHz channel in vertical polarization of AMSR-E. Evaluation shows that LST estimated by the TSDC method agrees well with the MODIS LST. Validation is based on in-situ LSTs measured at the Gobabeb site in western Namibia. The results demonstrate the high accuracy of the TSDC method: it yields a root-mean squared error (RMSE) of 2 K and ignorable systematic error over barren land. In the second study, the method consists of two core processes: (1) estimation of MW LST from MW brightness temperature and (2) three-time-scale decomposition of LST. The method is applied to two MW sensors (i.e. AMSR-E and AMSR2) and MODIS in northeast China and its surrounding area, with dominating land covers of forest and cropland. By comparing against the in-situ LST and surface air temperature, we find the merged LST has similar accuracy to the MODIS LST in version 6 and good image quality.

REFLECT: Logiciel de restitution des reflectances au sol pour l'amelioration de la qualite de l'information extraite des images satellitales a haute resolution spatiale

NASA Astrophysics Data System (ADS)

Bouroubi, Mohamed Yacine

Multi-spectral satellite imagery, especially at high spatial resolution (finer than 30 m on the ground), represents an invaluable source of information for decision making in various domains in connection with natural resources management, environment preservation or urban planning and management. The mapping scales may range from local (finer resolution than 5 m) to regional (resolution coarser than 5m). The images are characterized by objects reflectance in the electromagnetic spectrum witch represents the key information in many applications. However, satellite sensor measurements are also affected by parasite input due to illumination and observation conditions, to the atmosphere, to topography and to sensor properties. Two questions have oriented this research. What is the best approach to retrieve surface reflectance with the measured values while taking into account these parasite factors? Is this retrieval a sine qua non condition for reliable image information extraction for the diverse domains of application for the images (mapping, environmental monitoring, landscape change detection, resources inventory, etc.)? The goals we have delineated for this research are as follow: (1) Develop software to retrieve ground reflectance while taking into account the aspects mentioned earlier. This software had to be modular enough to allow improvement and adaptation to diverse remote sensing application problems; and (2) Apply this software in various context (urban, agricultural, forest) and analyse results to evaluate the accuracy gain of extracted information from remote sensing imagery transformed in ground reflectance images to demonstrate the necessity of operating in this way, whatever the type of application. During this research, we have developed a tool to retrieve ground reflectance (the new version of the REFLECT software). This software is based on the formulas (and routines) of the 6S code (Second Simulation of Satellite Signal in the Solar Spectrum) and on the dark targets method to estimated the aerosol optical thickness, representing the most difficult factor to correct. Substantial improvements have been made to the existing models. These improvements essentially concern the aerosols properties (integration of a more recent model, improvement of the dark targets selection to estimate the AOD), the adjacency effect, the adaptation to most used high resolution (Landsat TM and ETM+, all HR SPOT 1 to 5, EO-1 ALI and ASTER) and very high resolution (QuickBird et Ikonos) sensors and the correction of topographic effects with a model that separate direct and diffuse solar radiation components and the adaptation of this model to forest canopy. Validation has shown that ground reflectance estimation with REFLECT is performed with an accuracy of approximately +/-0.01 in reflectance units (for in the visible, near-infrared and middle-infrared spectral bands) even for a surface with varying topography. This software has allowed demonstrating, through apparent reflectance simulations, how much parasite factors influencing numerical values of the images may alter the ground reflectance (errors ranging from 10 to 50%). REFLECT has also been used to examine the usefulness of ground reflectance instead of raw data for various common remote sensing applications in domains such as classification, change detection, agriculture and forestry. In most applications (multi-temporal change monitoring, use of vegetation indices, biophysical parameters estimation, etc.) image correction is a crucial step to obtain reliable results. From the computer environment standpoint, REFLECT is organized as a series of menus, corresponding to different steps of: input parameters introducing, gas transmittances calculation, AOD estimation, and finally image correction application, with the possibility of using the fast option witch process an image of 5000 by 5000 pixels in approximately 15 minutes. (Abstract shortened by UMI.)

Terrain representation impact on periurban catchment morphological properties

NASA Astrophysics Data System (ADS)

Rodriguez, F.; Bocher, E.; Chancibault, K.

2013-04-01

SummaryModelling the hydrological behaviour of suburban catchments requires an estimation of environmental features, including land use and hydrographic networks. Suburban areas display a highly heterogeneous composition and encompass many anthropogenic elements that affect water flow paths, such as ditches, sewers, culverts and embankments. The geographical data available, either raster or vector data, may be of various origins and resolutions. Urban databases often offer very detailed data for sewer networks and 3D streets, yet the data covering rural zones may be coarser. This study is intended to highlight the sensitivity of geographical data as well as the data discretisation method used on the essential features of a periurban catchment, i.e. the catchment border and the drainage network. Three methods are implemented for this purpose. The first is the DEM (for digital elevation model) treatment method, which has traditionally been applied in the field of catchment hydrology. The second is based on urban database analysis and focuses on vector data, i.e. polygons and segments. The third method is a TIN (or triangular irregular network), which provides a consistent description of flow directions from an accurate representation of slope. It is assumed herein that the width function is representative of the catchment's hydrological response. The periurban Chézine catchment, located within the Nantes metropolitan area in western France, serves as the case study. The determination of both the main morphological features and the hydrological response of a suburban catchment varies significantly according to the discretization method employed, especially on upstream rural areas. Vector- and TIN-based methods allow representing the higher drainage density of urban areas, and consequently reveal the impact of these areas on the width function, since the DEM method fails. TINs seem to be more appropriate to take streets into account, because it allows a finer representation of topographical discontinuities. These results may help future developments of distributed hydrological models on periurban areas.

Composite solvers for linear saddle point problems arising from the incompressible Stokes equations with highly heterogeneous viscosity structure

NASA Astrophysics Data System (ADS)

Sanan, P.; Schnepp, S. M.; May, D.; Schenk, O.

2014-12-01

Geophysical applications require efficient forward models for non-linear Stokes flow on high resolution spatio-temporal domains. The bottleneck in applying the forward model is solving the linearized, discretized Stokes problem which takes the form of a large, indefinite (saddle point) linear system. Due to the heterogeniety of the effective viscosity in the elliptic operator, devising effective preconditioners for saddle point problems has proven challenging and highly problem-dependent. Nevertheless, at least three approaches show promise for preconditioning these difficult systems in an algorithmically scalable way using multigrid and/or domain decomposition techniques. The first is to work with a hierarchy of coarser or smaller saddle point problems. The second is to use the Schur complement method to decouple and sequentially solve for the pressure and velocity. The third is to use the Schur decomposition to devise preconditioners for the full operator. These involve sub-solves resembling inexact versions of the sequential solve. The choice of approach and sub-methods depends crucially on the motivating physics, the discretization, and available computational resources. Here we examine the performance trade-offs for preconditioning strategies applied to idealized models of mantle convection and lithospheric dynamics, characterized by large viscosity gradients. Due to the arbitrary topological structure of the viscosity field in geodynamical simulations, we utilize low order, inf-sup stable mixed finite element spatial discretizations which are suitable when sharp viscosity variations occur in element interiors. Particular attention is paid to possibilities within the decoupled and approximate Schur complement factorization-based monolithic approaches to leverage recently-developed flexible, communication-avoiding, and communication-hiding Krylov subspace methods in combination with `heavy' smoothers, which require solutions of large per-node sub-problems, well-suited to solution on hybrid computational clusters. To manage the combinatorial explosion of solver options (which include hybridizations of all the approaches mentioned above), we leverage the modularity of the PETSc library.

Intercomparison of Satellite-Derived Snow-Cover Maps

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Tait, Andrew B.; Foster, James L.; Chang, Alfred T. C.; Allen, Milan

1999-01-01

In anticipation of the launch of the Earth Observing System (EOS) Terra, and the PM-1 spacecraft in 1999 and 2000, respectively, efforts are ongoing to determine errors of satellite-derived snow-cover maps. EOS Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer-E (AMSR-E) snow-cover products will be produced. For this study we compare snow maps covering the same study area acquired from different sensors using different snow- mapping algorithms. Four locations are studied: 1) southern Saskatchewan; 2) a part of New England (New Hampshire, Vermont and Massachusetts) and eastern New York; 3) central Idaho and western Montana; and 4) parts of North and South Dakota. Snow maps were produced using a prototype MODIS snow-mapping algorithm used on Landsat Thematic Mapper (TM) scenes of each study area at 30-m and when the TM data were degraded to 1 -km resolution. National Operational Hydrologic Remote Sensing Center (NOHRSC) 1 -km resolution snow maps were also used, as were snow maps derived from 1/2 deg. x 1/2 deg. resolution Special Sensor Microwave Imager (SSM/1) data. A land-cover map derived from the International Geosphere-Biosphere Program (IGBP) land-cover map of North America was also registered to the scenes. The TM, NOHRSC and SSM/I snow maps, and land-cover maps were compared digitally. In most cases, TM-derived maps show less snow cover than the NOHRSC and SSM/I maps because areas of incomplete snow cover in forests (e.g., tree canopies, branches and trunks) are seen in the TM data, but not in the coarser-resolution maps. The snow maps generally agree with respect to the spatial variability of the snow cover. The 30-m resolution TM data provide the most accurate snow maps, and are thus used as the baseline for comparison with the other maps. Comparisons show that the percent change in amount of snow cover relative to the 3 0-m resolution TM maps is lowest using the TM I -km resolution maps, ranging from 0 to 40%. The highest percent change (less than 100%) is found in the New England study area, probably due to the presence of patchy snow cover. A scene with patchy snow cover is more difficult to map accurately than is a scene with a well-defined snowline such as is found on the North and South Dakota scene where the percent change ranged from 0 to 40%. There are also some important differences in the amount of snow mapped using the two different SSM/I algorithms because they utilize different channels.

Visualization of soil structure and pore structure modifications by pioneering ground beetles (Cicindelidae) in surface sediments of an artificial catchment

NASA Astrophysics Data System (ADS)

Badorreck, Annika; Gerke, Horst H.; Weller, Ulrich; Vontobel, Peter

2010-05-01

An artificial catchment was constructed to study initial soil and ecosystem development. As a key process, the pore structure dynamics in the soil at the surface strongly influences erosion, infiltration, matter dynamics, and vegetation establishment. Little is known, however, about the first macropore formation in the very early stage. This presentation focuses on observations of soil pore geometry and its effect on water flow at the surface comparing samples from three sites in the catchment and in an adjacent "younger" site composed of comparable sediments. The surface soil was sampled in cylindrical plastic rings (10 cm³) down to 2 cm depth in three replicates each site and six where caves from pioneering ground-dwelling beetles Cicindelidae were found. The samples were scanned with micro-X-ray computed tomography (at UFZ-Halle, Germany) with a resolution of 0.084 mm. The infiltration dynamics were visualized with neutronradiography (at Paul-Scherer-Institute, Switzerland) on slab-type soil samples in 2D. The micro-tomographies exhibit formation of surface sealing whose thickness and intensity vary with silt and clay content. The CT images show several coarser- and finer-textured micro-layers at the sample surfaces that were formed as a consequence of repeated washing in of finer particles in underlying coarser sediment. In micro-depressions, the uppermost layers consist of sorted fine sand and silt due to wind erosion. Similar as for desert pavements, a vesicular pore structure developed in these sediments on top, but also scattered in fine sand- and silt-enriched micro-layers. The ground-dwelling activity of Cicindelidae beetles greatly modifies the soil structure through forming caves in the first centimetres of the soil. Older collapsed caves, which form isolated pores within mixed zones, were also found. The infiltration rates were severely affected both, by surface crusts and activity of ground-dwelling beetles. The observations demonstrate relatively high abiotic and biotic dynamics of soil pore structure in the soil surface even during the very early development stages. The structure formation has potentially great effects on changing runoff and infiltration by forming sealing layers or preferential flow paths.

Sediment dynamics and the burial and exhumation of bedrock reefs along an emergent coastline as elucidated by repetitive sonar surveys: Northern Monterey Bay, CA

USGS Publications Warehouse

Storlazzi, C.D.; Fregoso, T.A.; Golden, N.E.; Finlayson, D.P.

2011-01-01

Two high-resolution bathymetric and acoustic backscatter sonar surveys were conducted along the energetic emergent inner shelf of northern Monterey Bay, CA, USA, in the fall of 2005 and the spring of 2006 to determine the impact of winter storm waves, beach erosion, and river floods on biologically-important siliclastic bedrock reef habitats. The surveys extended from water depths of 4 m to 22 m and covered an area of 3.14 km2, 45.8% of which was bedrock, gravel, and coarse-grained sand and 54.2% was fine-grained sand. Our analyses of the bathymetric and acoustic backscatter data demonstrates that during the 6 months between surveys, 11.4% of the study area was buried by fine-grained sand while erosion resulted in the exposure of bedrock or coarse-grained sand over 26.5% of the study area. The probability of burial decreased with increasing water depth and rugosity; the probability of exhumation increased with increasing wave-induced near-bed shear stress, seabed slope and rugosity. Much of the detected change was at the boundary between bedrock and unconsolidated sediment due to sedimentation and erosion burying or exhuming bedrock, respectively. In a number of cases, however, the change in seabed character was apparently due to changes in sediment grain size when scour exposed what appeared to be an underlying coarser-grained lag or the burial of coarser-grained sand and gravel by fine-grained sand. These findings suggest that, in some places, (a) burial and exhumation of nearshore bedrock reefs along rocky, energetic inner shelves occurs over seasonal timescales and appears related to intrinsic factors such as seabed morphology and extrinsic factors such as wave forces, and (b) single acoustic surveys typically employed for geologic characterization and/or habitat mapping may not adequately characterize the geomorphologic and sedimentologic nature of these types of environments that typify most of the Pacific Ocean and up to 50% of the world's coastlines.

Differences in soluble organic carbon chemistry in pore waters sampled from different pore size domains

DOE PAGES

Bailey, Vanessa L.; Smith, A. P.; Tfaily, Malak; ...

2017-01-11

Spatial isolation of soil organic carbon (SOC) in different sized pores may be a mechanism by which otherwise labile carbon (C) could be protected in soils. When soil water content increases, the hydrologic connectivity of soil pores also increases, allowing greater transport of SOC and other resources from protected locations, to microbially colonized locations more favorable to decomposition. The heterogeneous distribution of specialized decomposers, C, and other resources throughout the soil indicates that the metabolism or persistence of soil C compounds is highly dependent on short-distance transport processes. The objective of this research was to characterize the complexity of Cmore » in pore waters held at weak and strong water tensions (effectively soil solution held behind coarse- and fine-pore throats, respectively) and evaluate the microbial decomposability of these pore waters. We saturated intact soil cores and extracted pore waters with increasing suction pressures to sequentially sample pore waters from increasingly fine pore domains. Ultrahigh resolution mass spectrometry of the SOC was used to profile the major biochemical classes (i.e., lipids, proteins, lignin, carbohydrates, and condensed aromatics) of compounds present in the pore waters; some of these samples were then used as substrates for growth of Cellvibrio japonicus (DSMZ 16018), Streptomyces cellulosae (ATCC ® 25439™), and Trichoderma reseei (QM6a) in 7 day incubations. The soluble C in finer pores was more complex than the soluble C in coarser pores, and the incubations revealed that the more complex C in these fine pores is not recalcitrant. The decomposition of this complex C led to greater losses of C through respiration than the simpler C from coarser pore waters. Our research suggests that soils that experience repeated cycles of drying and wetting may be accompanied by repeated cycles of increased CO 2 fluxes that are driven by i) the transport of C from protected pools into active, ii) the chemical quality of the potentially soluble C, and iii) the type of microorganisms most likely to metabolize this C.« less

Differences in soluble organic carbon chemistry in pore waters sampled from different pore size domains

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

Bailey, Vanessa L.; Smith, A. P.; Tfaily, Malak

Spatial isolation of soil organic carbon (SOC) in different sized pores may be a mechanism by which otherwise labile carbon (C) could be protected in soils. When soil water content increases, the hydrologic connectivity of soil pores also increases, allowing greater transport of SOC and other resources from protected locations, to microbially colonized locations more favorable to decomposition. The heterogeneous distribution of specialized decomposers, C, and other resources throughout the soil indicates that the metabolism or persistence of soil C compounds is highly dependent on short-distance transport processes. The objective of this research was to characterize the complexity of Cmore » in pore waters held at weak and strong water tensions (effectively soil solution held behind coarse- and fine-pore throats, respectively) and evaluate the microbial decomposability of these pore waters. We saturated intact soil cores and extracted pore waters with increasing suction pressures to sequentially sample pore waters from increasingly fine pore domains. Ultrahigh resolution mass spectrometry of the SOC was used to profile the major biochemical classes (i.e., lipids, proteins, lignin, carbohydrates, and condensed aromatics) of compounds present in the pore waters; some of these samples were then used as substrates for growth of Cellvibrio japonicus (DSMZ 16018), Streptomyces cellulosae (ATCC ® 25439™), and Trichoderma reseei (QM6a) in 7 day incubations. The soluble C in finer pores was more complex than the soluble C in coarser pores, and the incubations revealed that the more complex C in these fine pores is not recalcitrant. The decomposition of this complex C led to greater losses of C through respiration than the simpler C from coarser pore waters. Our research suggests that soils that experience repeated cycles of drying and wetting may be accompanied by repeated cycles of increased CO 2 fluxes that are driven by i) the transport of C from protected pools into active, ii) the chemical quality of the potentially soluble C, and iii) the type of microorganisms most likely to metabolize this C.« less

Sensitivity of landscape metrics to changing scale of remote sensing data in spatial pattern analysis: effect, criticality and scaling.

NASA Astrophysics Data System (ADS)

Xu, C.; Zhao, S.; Zhao, B.

2017-12-01

Spatial heterogeneity is scale-dependent, that is, the quantification and representation of spatial pattern vary with the resolution and extent. Overwhelming practices focused on scale effect of landscape metrics, and predicable scaling relationships found among some of them are thought to be the most effective and precise way to quantify multi-scale characteristics. However, previous studies tended to consider a narrow range of scales, and few focused on the critical threshold of scaling function. Here we examine the scalograms of 38 widely-used landscape-level metrics in a more integral spectrum of grain size among 96 landscapes with various extent (i.e. from 25km2 up towards to 221 km2), which sampled randomly from NLCD product. Our goal is to explore the existence of scaling domain and whether the response of metrics to changing resolution would be influenced by spatial extent. Results clearly show the existence of scaling domain for 13 of them (Type II), while the behaviors of other 13 (Type I) exhibit simple scaling functions and the rest (Type III) demonstrate various forms like no obvious change or fluctuation across the integral spectrum of grain size. In addition, an invariant power law scaling relationship was found between critical resolution and spatial extent for metrics falling into Type II, as the critical resolution is proportional to Eρ (ρ is a constant, and E is the extent). All the scaling exponents (ρ) are positive, suggesting that the critical resolutions for these characteristics of landscape structure can be relaxed as the spatial extent expands. This agrees well with empirical perception that coarser grain size might be allowed for spatial data with larger extent. Furthermore, the parameters of scaling functions for metrics falling into Type I and Type II vary with spatial extent, and power law or logarithmic relationships could be identified between them for some metrics. Our finding support the existence of self-organized criticality for a hierarchically-structured landscape. Although the underlying mechanism driving the scaling relationship remains unclear, it could provide guidance toward general principles in spatial pattern analysis and on selecting the proper resolution to avoid the misrepresentation of spatial pattern and profound biases in further ecological progress research.

Image Simulation and Assessment of the Colour and Spatial Capabilities of the Colour and Stereo Surface Imaging System (CaSSIS) on the ExoMars Trace Gas Orbiter

NASA Astrophysics Data System (ADS)

Tornabene, Livio L.; Seelos, Frank P.; Pommerol, Antoine; Thomas, Nicholas; Caudill, C. M.; Becerra, Patricio; Bridges, John C.; Byrne, Shane; Cardinale, Marco; Chojnacki, Matthew; Conway, Susan J.; Cremonese, Gabriele; Dundas, Colin M.; El-Maarry, M. R.; Fernando, Jennifer; Hansen, Candice J.; Hansen, Kayle; Harrison, Tanya N.; Henson, Rachel; Marinangeli, Lucia; McEwen, Alfred S.; Pajola, Maurizio; Sutton, Sarah S.; Wray, James J.

2018-02-01

This study aims to assess the spatial and visible/near-infrared (VNIR) colour/spectral capabilities of the 4-band Colour and Stereo Surface Imaging System (CaSSIS) aboard the ExoMars 2016 Trace Grace Orbiter (TGO). The instrument response functions for the CaSSIS imager was used to resample spectral libraries, modelled spectra and to construct spectrally ( i.e., in I/F space) and spatially consistent simulated CaSSIS image cubes of various key sites of interest and for ongoing scientific investigations on Mars. Coordinated datasets from Mars Reconnaissance Orbiter (MRO) are ideal, and specifically used for simulating CaSSIS. The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) provides colour information, while the Context Imager (CTX), and in a few cases the High-Resolution Imaging Science Experiment (HiRISE), provides the complementary spatial information at the resampled CaSSIS unbinned/unsummed pixel resolution (4.6 m/pixel from a 400-km altitude). The methodology used herein employs a Gram-Schmidt spectral sharpening algorithm to combine the ˜18-36 m/pixel CRISM-derived CaSSIS colours with I/F images primarily derived from oversampled CTX images. One hundred and eighty-one simulated CaSSIS 4-colour image cubes (at 18-36 m/pixel) were generated (including one of Phobos) based on CRISM data. From these, thirty-three "fully"-simulated image cubes of thirty unique locations on Mars ( i.e., with 4 colour bands at 4.6 m/pixel) were made. All simulated image cubes were used to test both the colour capabilities of CaSSIS by producing standard colour RGB images, colour band ratio composites (CBRCs) and spectral parameters. Simulated CaSSIS CBRCs demonstrated that CaSSIS will be able to readily isolate signatures related to ferrous (Fe2+) iron- and ferric (Fe3+) iron-bearing deposits on the surface of Mars, ices and atmospheric phenomena. Despite the lower spatial resolution of CaSSIS when compared to HiRISE, the results of this work demonstrate that CaSSIS will not only compliment HiRISE-scale studies of various geological and seasonal phenomena, it will also enhance them by providing additional colour and geologic context through its wider and longer full-colour coverage (˜9.4 × 50 km), and its increased sensitivity to iron-bearing materials from its two IR bands (RED and NIR). In a few examples, subtle surface changes that were not easily detected by HiRISE were identified in the simulated CaSSIS images. This study also demonstrates the utility of the Gram-Schmidt spectral pan-sharpening technique to extend VNIR colour/spectral capabilities from a lower spatial resolution colour/spectral dataset to a single-band or panchromatic image greyscale image with higher resolution. These higher resolution colour products (simulated CaSSIS or otherwise) are useful as means to extend both geologic context and mapping of datasets with coarser spatial resolutions. The results of this study indicate that the TGO mission objectives, as well as the instrument-specific mission objectives, will be achievable with CaSSIS.

Responses of plant available water and forest productivity to variably layered coarse textured soils

NASA Astrophysics Data System (ADS)

Huang, Mingbin; Barbour, Lee; Elshorbagy, Amin; Si, Bing; Zettl, Julie

2010-05-01

Reforestation is a primary end use for reconstructed soils following oil sands mining in northern Alberta, Canada. Limited soil water conditions strongly restrict plant growth. Previous research has shown that layering of sandy soils can produce enhanced water availability for plant growth; however, the effect of gradation on these enhancements is not well defined. The objective of this study was to evaluate the effect of soil texture (gradation and layering) on plant available water and consequently on forest productivity for reclaimed coarse textured soils. A previously validated system dynamics (SD) model of soil moisture dynamics was coupled with ecophysiological and biogeochemical processes model, Biome-BGC-SD, to simulate forest dynamics for different soil profiles. These profiles included contrasting 50 cm textural layers of finer sand overlying coarser sand in which the sand layers had either a well graded or uniform soil texture. These profiles were compared to uniform profiles of the same sands. Three tree species of jack pine (Pinus banksiana Lamb.), white spruce (Picea glauce Voss.), and trembling aspen (Populus tremuloides Michx.) were simulated using a 50 year climatic data base from northern Alberta. Available water holding capacity (AWHC) was used to identify soil moisture regime, and leaf area index (LAI) and net primary production (NPP) were used as indices of forest productivity. Published physiological parameters were used in the Biome-BGC-SD model. Relative productivity was assessed by comparing model predictions to the measured above-ground biomass dynamics for the three tree species, and was then used to study the responses of forest leaf area index and potential productivity to AWHC on different soil profiles. Simulated results indicated soil layering could significantly increase AWHC in the 1-m profile for coarse textured soils. This enhanced AWHC could result in an increase in forest LAI and NPP. The increased extent varied with soil textures and vegetative types. The simulated results showed that the presence of 50 cm of coarser graded sand overlying 50 cm of finer graded sand is the most effective reclaimed prescription to increase AWHC and forest productivity among the studied soil profiles.

Strength Development of High-Strength Ductile Concrete Incorporating Metakaolin and PVA Fibers

PubMed Central

Nuruddin, Muhammad Fadhil; Shafiq, Nasir

2014-01-01

The mechanical properties of high-strength ductile concrete (HSDC) have been investigated using Metakaolin (MK) as the cement replacing material and PVA fibers. Total twenty-seven (27) mixes of concrete have been examined with varying content of MK and PVA fibers. It has been found that the coarser type PVA fibers provide strengths competitive to control or higher than control. Concrete with coarser type PVA fibers has also refined microstructure, but the microstructure has been undergone with the increase in aspect ratio of fibers. The microstructure of concrete with MK has also more refined and packing of material is much better with MK. PVA fibers not only give higher stiffness but also showed the deflection hardening response. Toughness Index of HSDC reflects the improvement in flexural toughness over the plain concrete and the maximum toughness indices have been observed with 10% MK and 2% volume fraction of PVA fibers. PMID:24707202

Strength development of high-strength ductile concrete incorporating Metakaolin and PVA fibers.

PubMed

Nuruddin, Muhammad Fadhil; Khan, Sadaqat Ullah; Shafiq, Nasir; Ayub, Tehmina

2014-01-01

The mechanical properties of high-strength ductile concrete (HSDC) have been investigated using Metakaolin (MK) as the cement replacing material and PVA fibers. Total twenty-seven (27) mixes of concrete have been examined with varying content of MK and PVA fibers. It has been found that the coarser type PVA fibers provide strengths competitive to control or higher than control. Concrete with coarser type PVA fibers has also refined microstructure, but the microstructure has been undergone with the increase in aspect ratio of fibers. The microstructure of concrete with MK has also more refined and packing of material is much better with MK. PVA fibers not only give higher stiffness but also showed the deflection hardening response. Toughness Index of HSDC reflects the improvement in flexural toughness over the plain concrete and the maximum toughness indices have been observed with 10% MK and 2% volume fraction of PVA fibers.

Unweighted least squares phase unwrapping by means of multigrid techniques

NASA Astrophysics Data System (ADS)

Pritt, Mark D.

1995-11-01

We present a multigrid algorithm for unweighted least squares phase unwrapping. This algorithm applies Gauss-Seidel relaxation schemes to solve the Poisson equation on smaller, coarser grids and transfers the intermediate results to the finer grids. This approach forms the basis of our multigrid algorithm for weighted least squares phase unwrapping, which is described in a separate paper. The key idea of our multigrid approach is to maintain the partial derivatives of the phase data in separate arrays and to correct these derivatives at the boundaries of the coarser grids. This maintains the boundary conditions necessary for rapid convergence to the correct solution. Although the multigrid algorithm is an iterative algorithm, we demonstrate that it is nearly as fast as the direct Fourier-based method. We also describe how to parallelize the algorithm for execution on a distributed-memory parallel processor computer or a network-cluster of workstations.

UAV-based remote sensing surveys of lava flow fields: a case study from Etna's 1974 channel-fed lava flows

NASA Astrophysics Data System (ADS)

Favalli, Massimiliano; Fornaciai, Alessandro; Nannipieri, Luca; Harris, Andrew; Calvari, Sonia; Lormand, Charline

2018-03-01

During an eruption, time scales of topographic change are fast and involve vertical and planimetric evolution of millimeters to meters as the event progresses. Repeat production of high spatial resolution terrain models of lava flow fields over time scales of a few hours is thus a high-value capability in tracking the buildup of the deposit. Among the wide range of terrestrial and aerial methods available to collect such topographic data, the use of an unmanned aerial vehicle (UAV) as an acquisition platform, together with structure from motion (SfM) photogrammetry, has become especially useful. This approach allows high-frequency production of centimeter-scale terrain models over kilometer-scale areas, including dangerous and inaccessible zones, with low cost and minimal hazard to personnel. This study presents the application of such an integrated UAV-SfM method to generate a high spatial resolution digital terrain model and orthomosaic of Mount Etna's January-February 1974 lava flow field. The SfM method, applied to images acquired using a UAV platform, enabled the extraction of a very high spatial resolution (20 cm) digital elevation model and the generation of a 3-cm orthomosaic covering an area of 1.35 km2. This spatial resolution enabled us to analyze the morphology of sub-meter-scale features, such as folds, blocks, and cracks, over kilometer-scale areas. The 3-cm orthomosaic allowed us to further push the analysis to centimeter-scale grain size distribution of the lava surface. Using these data, we define three types of crust structure and relate them to positions within a channel-fed ´áā flow system. These crust structures are (i) flow parallel shear lines, (ii) raft zones, and (iii) folded zones. Flow parallel shear lines are found at the channel edges, and are 2-m-wide and 0.25-m-deep zones running along the levee base and in which cracking is intense. They result from intense shearing between the moving channel lava and the static levee lava. In zones where initial levees are just beginning to form, these subtle features are the only marker that delimits the moving lava from the stagnant marginal lava. Rafts generally form as the system changes from a stable to a transitional channel regime. Over this 170-m-long zone, the channel broadens from 8 to 70 m and rafts are characterized by topographically higher and poorly cracked areas, surrounded by lower, heavily cracked areas. We interpret the rafts as forming due to breakup of crust zones, previously moving in a coherent manner in the narrow proximal channel reach. Folded zones involve arcuate, cross-flow ridges with their apexes pointing down-flow, where ridges have relatively small clasts and depressions are of coarser-grained breccia. Our folds have wavelengths of 10 m and amplitudes of 1 m; are found towards the flow front, down-flow of the raft zones; and are associated with piling up of lava behind a static or slowly moving flow front. The very high spatial resolution topographic data available from UAV-SfM allow us to resolve surfaces where roughness has a vertical and horizontal scale of variation that is less than 1 m. This is the case over pāhoehoe and ´áā flow surfaces, and thus allows us to explore those new structures that are only apparent in the sub-metric data. Moreover, during future eruptions, the possibility to acquire such information in near-real time will allow a prompt analysis of developing lava flow fields and structures therein, such as developing lava channel systems, so as to contribute to timely hazard assessment, modeling, and projections.

Smoothing the Marmousi Model

NASA Astrophysics Data System (ADS)

Žáček, K.

Summary- The only way to make an excessively complex velocity model suitable for application of ray-based methods, such as the Gaussian beam or Gaussian packet methods, is to smooth it. We have smoothed the Marmousi model by choosing a coarser grid and by minimizing the second spatial derivatives of the slowness. This was done by minimizing the relevant Sobolev norm of slowness. We show that minimizing the relevant Sobolev norm of slowness is a suitable technique for preparing the optimum models for asymptotic ray theory methods. However, the price we pay for a model suitable for ray tracing is an increase of the difference between the smoothed and original model. Similarly, the estimated error in the travel time also increases due to the difference between the models. In smoothing the Marmousi model, we have found the estimated error of travel times at the verge of acceptability. Due to the low frequencies in the wavefield of the original Marmousi data set, we have found the Gaussian beams and Gaussian packets at the verge of applicability even in models sufficiently smoothed for ray tracing.

Global/local methods for probabilistic structural analysis

NASA Technical Reports Server (NTRS)

Millwater, H. R.; Wu, Y.-T.

1993-01-01

A probabilistic global/local method is proposed to reduce the computational requirements of probabilistic structural analysis. A coarser global model is used for most of the computations with a local more refined model used only at key probabilistic conditions. The global model is used to establish the cumulative distribution function (cdf) and the Most Probable Point (MPP). The local model then uses the predicted MPP to adjust the cdf value. The global/local method is used within the advanced mean value probabilistic algorithm. The local model can be more refined with respect to the g1obal model in terms of finer mesh, smaller time step, tighter tolerances, etc. and can be used with linear or nonlinear models. The basis for this approach is described in terms of the correlation between the global and local models which can be estimated from the global and local MPPs. A numerical example is presented using the NESSUS probabilistic structural analysis program with the finite element method used for the structural modeling. The results clearly indicate a significant computer savings with minimal loss in accuracy.

Global/local methods for probabilistic structural analysis

NASA Astrophysics Data System (ADS)

Millwater, H. R.; Wu, Y.-T.

1993-04-01

A probabilistic global/local method is proposed to reduce the computational requirements of probabilistic structural analysis. A coarser global model is used for most of the computations with a local more refined model used only at key probabilistic conditions. The global model is used to establish the cumulative distribution function (cdf) and the Most Probable Point (MPP). The local model then uses the predicted MPP to adjust the cdf value. The global/local method is used within the advanced mean value probabilistic algorithm. The local model can be more refined with respect to the g1obal model in terms of finer mesh, smaller time step, tighter tolerances, etc. and can be used with linear or nonlinear models. The basis for this approach is described in terms of the correlation between the global and local models which can be estimated from the global and local MPPs. A numerical example is presented using the NESSUS probabilistic structural analysis program with the finite element method used for the structural modeling. The results clearly indicate a significant computer savings with minimal loss in accuracy.

Transboundary Transport of Biomass Burning Emissions in Southeast Asia and Contribution to Local Air Quality During the 2006 Fire Event

NASA Astrophysics Data System (ADS)

Aouizerats, B.; van der Werf, G.; Balasubramanian, R.; Betha, R.

2014-12-01

Smoke from biomass and peat burning has a notable impact on ambient air quality and climate in the Southeast Asia (SEA) region. We modeled the largest fire-induced haze episode in the past decade (2006) that originated in Indonesia using WRF-Chem. Our study addressed 3 research questions: (1) Can the WRF-Chem model reproduce observations of both aerosol and CO concentrations in this complex region? (2) What is the evolution in the chemical composition of the aerosol fire plume during its atmospheric transport? and (3) What is the relative contribution of these fires to air quality in the urbanized area of the city-state of Singapore? To test model performance, we used three independent datasets for comparison (PM10 in Singapore, CO measurements in Sumatra, and AOD column observations from 4 satellite-based sensors). We found reasonable agreement of the model runs with ground-based measurements of both CO and PM10. However, the comparison with AOD was less favorable and indicated the model underestimated AOD. In the past, modeling studies using only AOD as a constraint have often boosted fire emissions to get a better agreement with observations. In our case, this approach would seriously deteriorate the difference with ground-based observations. Finally, our results show that about 21% of the total mass loading of ambient PM10 during the July-October study period in Singapore was due to the influence of biomass and peat burning in Sumatra, with an increased contribution during high burning periods. The composition of this biomass burning plume was largely dominated by primary organic carbon. In total, our model results indicated that during 35 days aerosol concentrations in Singapore were above the threshold of 50 μg m-3 day-1 (WHO threshold). During 17 days this deterioration was due to Indonesian fires, based on the difference between the simulations with and without fires. Local air pollution in combination with recirculation of air masses was probably the main cause of the lack of good air quality during the other 18 days. This finding is mostly due to the relatively fine scale of our model set-up; coarser resolution models would have likely attributed the increased aerosol loads to burning in Borneo from which plumes were advected close to Singapore, but did not contribute to local pollution according to our model.

The influence of 14CO2 releases from regional nuclear facilities at the Heidelberg 14CO2 sampling site (1986-2014)

NASA Astrophysics Data System (ADS)

Kuderer, Matthias; Hammer, Samuel; Levin, Ingeborg

2018-06-01

Atmospheric Δ14CO2 measurements are a well-established tool to estimate the regional fossil-fuel-derived CO2 component. However, emissions from nuclear facilities can significantly alter the regional Δ14CO2 level. In order to accurately quantify the signal originating from fossil CO2 emissions, a correction term for anthropogenic 14CO2 sources has to be determined. In this study, the HYSPLIT atmospheric dispersion model has been applied to calculate this correction for the long-term Δ14CO2 monitoring site in Heidelberg. Wind fields with a spatial resolution of 2.5° × 2.5°, 1° × 1°, and 0.5° × 0.5° show systematic deviations, with coarser resolved wind fields leading to higher mean values for the correction. The finally applied mean Δ14CO2 correction for the period from 1986-2014 is 2.3 ‰ with a standard deviation of 2.1 ‰ and maximum values up to 15.2 ‰. These results are based on the 0.5° × 0.5° wind field simulations in years when these fields were available (2009, 2011-2014), and for the other years they are based on 2.5° × 2.5° wind field simulations, corrected with a factor of 0.43. After operations at the Philippsburg boiling water reactor ceased in 2011, the monthly nuclear correction terms decreased to less than 2 ‰, with a mean value of 0.44 ± 0.32 ‰ from 2012 to 2014.

An algorithm for calculating minimum Euclidean distance between two geographic features

NASA Astrophysics Data System (ADS)

Peuquet, Donna J.

1992-09-01

An efficient algorithm is presented for determining the shortest Euclidean distance between two features of arbitrary shape that are represented in quadtree form. These features may be disjoint point sets, lines, or polygons. It is assumed that the features do not overlap. Features also may be intertwined and polygons may be complex (i.e. have holes). Utilizing a spatial divide-and-conquer approach inherent in the quadtree data model, the basic rationale is to narrow-in on portions of each feature quickly that are on a facing edge relative to the other feature, and to minimize the number of point-to-point Euclidean distance calculations that must be performed. Besides offering an efficient, grid-based alternative solution, another unique and useful aspect of the current algorithm is that is can be used for rapidly calculating distance approximations at coarser levels of resolution. The overall process can be viewed as a top-down parallel search. Using one list of leafcode addresses for each of the two features as input, the algorithm is implemented by successively dividing these lists into four sublists for each descendant quadrant. The algorithm consists of two primary phases. The first determines facing adjacent quadrant pairs where part or all of the two features are separated between the two quadrants, respectively. The second phase then determines the closest pixel-level subquadrant pairs within each facing quadrant pair at the lowest level. The key element of the second phase is a quick estimate distance heuristic for further elimination of locations that are not as near as neighboring locations.

Performance of multi-physics ensembles in convective precipitation events over northeastern Spain

NASA Astrophysics Data System (ADS)

García-Ortega, E.; Lorenzana, J.; Merino, A.; Fernández-González, S.; López, L.; Sánchez, J. L.

2017-07-01

Convective precipitation with hail greatly affects southwestern Europe, causing major economic losses. The local character of this meteorological phenomenon is a serious obstacle to forecasting. Therefore, the development of reliable short-term forecasts constitutes an essential challenge to minimizing and managing risks. However, deterministic outcomes are affected by different uncertainty sources, such as physics parameterizations. This study examines the performance of different combinations of physics schemes of the Weather Research and Forecasting model to describe the spatial distribution of precipitation in convective environments with hail falls. Two 30-member multi-physics ensembles, with two and three domains of maximum resolution 9 and 3km each, were designed using various combinations of cumulus, microphysics and radiation schemes. The experiment was evaluated for 10 convective precipitation days with hail over 2005-2010 in northeastern Spain. Different indexes were used to evaluate the ability of each ensemble member to capture the precipitation patterns, which were compared with observations of a rain-gauge network. A standardized metric was constructed to identify optimal performers. Results show interesting differences between the two ensembles. In two domain simulations, the selection of cumulus parameterizations was crucial, with the Betts-Miller-Janjic scheme the best. In contrast, the Kain-Fristch cumulus scheme gave the poorest results, suggesting that it should not be used in the study area. Nevertheless, in three domain simulations, the cumulus schemes used in coarser domains were not critical and the best results depended mainly on microphysics schemes. The best performance was shown by Morrison, New Thomson and Goddard microphysics.

Cross-polar transport and scavenging of Siberian aerosols containing black carbon during the 2012 ACCESS summer campaign

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

Raut, Jean -Christophe; Marelle, Louis; Fast, Jerome D.

During the ACCESS airborne campaign in July 2012, extensive boreal forest fires resulted in significant aerosol transport to the Arctic. A 10-day episode combining intense biomass burning over Siberia and low-pressure systems over the Arctic Ocean resulted in efficient transport of plumes containing black carbon (BC) towards the Arctic, mostly in the upper troposphere (6–8 km). Here, a combination of in situ observations (DLR Falcon aircraft), satellite analysis and WRF-Chem simulations is used to understand the vertical and horizontal transport mechanisms of BC with a focus on the role of wet removal. Between the northwestern Norwegian coast and the Svalbardmore » archipelago, the Falcon aircraft sampled plumes with enhanced CO concentrations up to 200 ppbv and BC mixing ratios up to 25 ng kg –1. During transport to the Arctic region, a large fraction of BC particles are scavenged by two wet deposition processes, namely wet removal by large-scale precipitation and removal in wet convective updrafts, with both processes contributing almost equally to the total accumulated deposition of BC. Our results underline that applying a finer horizontal resolution (40 instead of 100 km) improves the model performance, as it significantly reduces the overestimation of BC levels observed at a coarser resolution in the mid-troposphere. According to the simulations at 40 km, the transport efficiency of BC (TE BC) in biomass burning plumes was larger (60 %), because it was impacted by small accumulated precipitation along trajectory (1 mm). In contrast TE BC was small (< 30 %) and accumulated precipitation amounts were larger (5–10 mm) in plumes influenced by urban anthropogenic sources and flaring activities in northern Russia, resulting in transport to lower altitudes. TE BC due to large-scale precipitation is responsible for a sharp meridional gradient in the distribution of BC concentrations. Wet removal in cumulus clouds is the cause of modeled vertical gradient of TE BC, especially in the mid-latitudes, reflecting the distribution of convective precipitation, but is dominated in the Arctic region by the large-scale wet removal associated with the formation of stratocumulus clouds in the planetary boundary layer (PBL) that produce frequent drizzle.« less

Cross-polar transport and scavenging of Siberian aerosols containing black carbon during the 2012 ACCESS summer campaign

DOE PAGES

Raut, Jean -Christophe; Marelle, Louis; Fast, Jerome D.; ...

2017-09-15

During the ACCESS airborne campaign in July 2012, extensive boreal forest fires resulted in significant aerosol transport to the Arctic. A 10-day episode combining intense biomass burning over Siberia and low-pressure systems over the Arctic Ocean resulted in efficient transport of plumes containing black carbon (BC) towards the Arctic, mostly in the upper troposphere (6–8 km). Here, a combination of in situ observations (DLR Falcon aircraft), satellite analysis and WRF-Chem simulations is used to understand the vertical and horizontal transport mechanisms of BC with a focus on the role of wet removal. Between the northwestern Norwegian coast and the Svalbardmore » archipelago, the Falcon aircraft sampled plumes with enhanced CO concentrations up to 200 ppbv and BC mixing ratios up to 25 ng kg –1. During transport to the Arctic region, a large fraction of BC particles are scavenged by two wet deposition processes, namely wet removal by large-scale precipitation and removal in wet convective updrafts, with both processes contributing almost equally to the total accumulated deposition of BC. Our results underline that applying a finer horizontal resolution (40 instead of 100 km) improves the model performance, as it significantly reduces the overestimation of BC levels observed at a coarser resolution in the mid-troposphere. According to the simulations at 40 km, the transport efficiency of BC (TE BC) in biomass burning plumes was larger (60 %), because it was impacted by small accumulated precipitation along trajectory (1 mm). In contrast TE BC was small (< 30 %) and accumulated precipitation amounts were larger (5–10 mm) in plumes influenced by urban anthropogenic sources and flaring activities in northern Russia, resulting in transport to lower altitudes. TE BC due to large-scale precipitation is responsible for a sharp meridional gradient in the distribution of BC concentrations. Wet removal in cumulus clouds is the cause of modeled vertical gradient of TE BC, especially in the mid-latitudes, reflecting the distribution of convective precipitation, but is dominated in the Arctic region by the large-scale wet removal associated with the formation of stratocumulus clouds in the planetary boundary layer (PBL) that produce frequent drizzle.« less

Development of an eddy-resolving reanalysis using the 1/12° global HYbrid Coordinate Ocean Model and the Navy Coupled Ocean Data Assimilation Scheme

NASA Astrophysics Data System (ADS)

Allard, Richard; Metzger, E. Joseph; Broome, Robert; Franklin, Deborah; Smedstad, Ole Martin; Wallcraft, Alan

2013-04-01

Multiple international agencies have performed atmospheric reanalyses using static dynamical models and assimilation schemes while ingesting all available quality controlled observational data. Some are clearly aimed at climate time scales while others focus on the more recent time period in which assimilated satellite data are used to constrain the system. Typically these are performed at horizontal and vertical resolutions that are coarser than the existing operational atmospheric prediction system. Multiple agencies have also performed ocean reanalyses using some of the atmospheric forcing products described above. However, only a few are eddy-permitting and none are capable of resolving oceanic mesoscale features (eddies and current meanders) across the entire globe. To fill this void, the Naval Research Laboratory is performing an eddy-resolving 1993-2010 ocean reanalysis using the 1/12° global HYbrid Coordinate Ocean Model (HYCOM) that employs the Navy Coupled Ocean Data Assimilation (NCODA) scheme. A 1/12° global HYCOM/NCODA prediction system has been running in real-time at the Naval Oceanographic Office (NAVOCEANO) since 22 December 2006. It has undergone operational testing and will become an operational product by early 2013. It is capable of nowcasting and forecasting the oceanic "weather" which includes the 3D ocean temperature, salinity and current structure, the surface mixed layer, and the location of mesoscale features such as eddies, meandering currents and fronts. The system has a mid-latitude resolution of ~7 km and employs 32 hybrid vertical coordinate surfaces. Compared to traditional isopycnal coordinate models, the hybrid vertical coordinate extends the geographic range of applicability toward shallow coastal seas and the unstratified parts of the world ocean. HYCOM contains a built-in thermodynamic ice model, where ice grows and melts due to heat flux and sea surface temperature (SST) changes, but it does not contain advanced rheological physics. The ice edge is constrained by satellite ice concentration. Once per day, NCODA performs a 3D ocean analysis using all available observational data and the 1-day HYCOM forecast as the first guess in a sequential incremental update cycle. Observational data include surface observations from satellites, including sea surface height (SSH) anomalies, SST, and sea ice concentrations, plus in-situ SST observations from ships and buoys as well as temperature and salinity profiles from XBTs, CTDs and Argo profiling floats. Surface information is projected downward using synthetic profiles from the Modular Ocean Data Assimilation System (MODAS) at those locations with a predefined SSH anomaly. Unlike previous reanalyses, this ocean reanalysis will be integrated at the same horizontal and vertical resolution as the operational system running at NAVOCEANO. The system is forced with atmospheric output from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) and the observations listed above. The reanalysis began in 1993 because of the advent of satellite altimeter data that will constrain the oceanic mesoscale. Significant effort has been put into obtaining and quality controlling all input observational data, with special emphasis on the profile data. The computational resources are obtained through the High Performance Computing Modernization Office.

Regional Climate Model sesitivity to different parameterizations schemes with WRF over Spain

NASA Astrophysics Data System (ADS)

García-Valdecasas Ojeda, Matilde; Raquel Gámiz-Fortis, Sonia; Hidalgo-Muñoz, Jose Manuel; Argüeso, Daniel; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2015-04-01

The ability of the Weather Research and Forecasting (WRF) model to simulate the regional climate depends on the selection of an adequate combination of parameterization schemes. This study assesses WRF sensitivity to different parameterizations using six different runs that combined three cumulus, two microphysics and three surface/planetary boundary layer schemes in a topographically complex region such as Spain, for the period 1995-1996. Each of the simulations spanned a period of two years, and were carried out at a spatial resolution of 0.088° over a domain encompassing the Iberian Peninsula and nested in the coarser EURO-CORDEX domain (0.44° resolution). The experiments were driven by Interim ECMWF Re-Analysis (ERA-Interim) data. In addition, two different spectral nudging configurations were also analysed. The simulated precipitation and maximum and minimum temperatures from WRF were compared with Spain02 version 4 observational gridded datasets. The comparison was performed at different time scales with the purpose of evaluating the model capability to capture mean values and high-order statistics. ERA-Interim data was also compared with observations to determine the improvement obtained using dynamical downscaling with respect to the driving data. For this purpose, several parameters were analysed by directly comparing grid-points. On the other hand, the observational gridded data were grouped using a multistep regionalization to facilitate the comparison in term of monthly annual cycle and the percentiles of daily values analysed. The results confirm that no configuration performs best, but some combinations that produce better results could be chosen. Concerning temperatures, WRF provides an improvement over ERA-Interim. Overall, model outputs reduce the biases and the RMSE for monthly-mean maximum and minimum temperatures and are higher correlated with observations than ERA-Interim. The analysis shows that the Yonsei University planetary boundary layer scheme is the most appropriate parameterization in term of temperatures because it better describes monthly minimum temperatures and seems to perform well for maximum temperatures. Regarding precipitation, ERA-Interim time series are slightly higher correlated with observations than WRF, but the bias and the RMSE are largely worse. These results also suggest that CAM V.5.1 2-moment 5-class microphysics schemes should not be used due to the computational cost with no apparent gain with respect to simpler schemes such as WRF single-moment 3-class. For the convection scheme, this study suggests that Betts-Miller-Janjic scheme is an appropriate choice due to its robustness and Kain-Fritsch cumulus scheme should not be used over this region. KEY WORDS: Regional climate modelling, physics schemes, parameterizations, WRF. ACKNOWLEDGEMENTS This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Toward Characterizing the 4D Structure of Precipitation at the Headwater Catchment Scale in Mountainous Regions

NASA Astrophysics Data System (ADS)

Barros, A. P.; Prat, O. P.; Sun, X.; Shrestha, P.; Miller, D.

2009-04-01

The classic conceptual model of orographic rainfall depicts strong stationary horizontal gradients in rainfall accumulations and landcover contrasts across topographic divides (i.e. the rainshadow) at the broad scale of mountain ranges, or isolated orographic features. Whereas this model is sufficient to fingerprint the land-modulation of precipitation at the macroscale in climate studies, and can be useful to force geological models of land evolution for example, it fails to describe the active 4D space-time gradients that are critical at the fundamental scale of mountain hydrometeorology and hydrology, that is the headwater catchment. That is, the scale at which flash-floods are generated and landslides are triggered. Our work surveying the spatial and temporal habits of clouds and rainfall for some of the world's major mountain ranges from remotely-sensed data shows a close alignment of spatial scaling behavior with landform down to the mountain fold scale, that is the ridge-valley. Likewise, we find that diurnal and seasonal cycles are organized and constrained by topography from the macro- to the meso- to the alpha-scale of individual basins varying with synoptic weather conditions. At the catchment scale, the diurnal cycle exhibits an oscillatory behavior with storm features moving up and down from the ridge crests to the valley floor and back and forth from head to mouth along the valley with strong variations in rainfall intensity and duration. Direct observations to provide quantitative estimates of precipitation at this scale are beyond the capability of satellite-based observations present and anticipated in the next 10-20 years. This limitation can be addressed by assimilating the space-time modes of variability of rainfall into satellite-observations at coarser scale using multiscale blending algorithms. The challenge is to characterize the modes of space-time variability of precipitation in a systematic, and quantitative fashion that can be generalized. It requires understanding the physical controls that govern the diurnal cycle and how these physical controls translate into spatial and temporal variability of dynamics and microphysics of precipitation in headwater catchments, and especially in the context of extreme events for natural hazards assessments. Toward this goal, we have initiated a sequence of number of intense observing period (IOP) campaigns in the Great Smoky Mountains National Park using radiosondes, tethersondes, microrain radars, and a high resolution raingauge network that for the first time monitors rainfall systematically along ridges in the Appalachians. Along with field observations, a high-resolution coupled model has been implemented to diagnose the evolution of the 4D structure of regional circulations and associated precipitation for IOP conditions and for reconstructing historical extremes associated with the interaction of tropical cyclones with the mountains. A synthesis of data analysis and model simulations will be presented.

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

Ray Casting of Large Multi-Resolution Volume Datasets

NASA Astrophysics Data System (ADS)

Lux, C.; Fröhlich, B.

2009-04-01

High quality volume visualization through ray casting on graphics processing units (GPU) has become an important approach for many application domains. We present a GPU-based, multi-resolution ray casting technique for the interactive visualization of massive volume data sets commonly found in the oil and gas industry. Large volume data sets are represented as a multi-resolution hierarchy based on an octree data structure. The original volume data is decomposed into small bricks of a fixed size acting as the leaf nodes of the octree. These nodes are the highest resolution of the volume. Coarser resolutions are represented through inner nodes of the hierarchy which are generated by down sampling eight neighboring nodes on a finer level. Due to limited memory resources of current desktop workstations and graphics hardware only a limited working set of bricks can be locally maintained for a frame to be displayed. This working set is chosen to represent the whole volume at different local resolution levels depending on the current viewer position, transfer function and distinct areas of interest. During runtime the working set of bricks is maintained in CPU- and GPU memory and is adaptively updated by asynchronously fetching data from external sources like hard drives or a network. The CPU memory hereby acts as a secondary level cache for these sources from which the GPU representation is updated. Our volume ray casting algorithm is based on a 3D texture-atlas in GPU memory. This texture-atlas contains the complete working set of bricks of the current multi-resolution representation of the volume. This enables the volume ray casting algorithm to access the whole working set of bricks through only a single 3D texture. For traversing rays through the volume, information about the locations and resolution levels of visited bricks are required for correct compositing computations. We encode this information into a small 3D index texture which represents the current octree subdivision on its finest level and spatially organizes the bricked data. This approach allows us to render a bricked multi-resolution volume data set utilizing only a single rendering pass with no loss of compositing precision. In contrast most state-of-the art volume rendering systems handle the bricked data as individual 3D textures, which are rendered one at a time while the results are composited into a lower precision frame buffer. Furthermore, our method enables us to integrate advanced volume rendering techniques like empty-space skipping, adaptive sampling and preintegrated transfer functions in a very straightforward manner with virtually no extra costs. Our interactive volume ray tracing implementation allows high quality visualizations of massive volume data sets of tens of Gigabytes in size on standard desktop workstations.

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.

Closing the gap between regional and global travel time tomography

USGS Publications Warehouse

Bijwaard, H.; Spakman, W.; Engdahl, E.R.

1998-01-01

Recent global travel time tomography studies by Zhou [1996] and van der Hilst et al. [1997] have been performed with cell parameterizations of the order of those frequently used in regional tomography studies (i.e., with cell sizes of 1??-2??). These new global models constitute a considerable improvement over previous results that were obtained with rather coarse parameterizations (5?? cells). The inferred structures are, however, of larger scale than is usually obtained in regional models, and it is not clear where and if individual cells are actually resolved. This study aims at resolving lateral heterogeneity on scales as small as 0.6?? in the upper mantle and 1.2??-3?? in the lower mantle. This allows for the adequate mapping of expected small-scale structures induced by, for example, lithosphere subduction, deep mantle upwellings, and mid-ocean ridges. There are three major contributions that allow for this advancement. First, we employ an irregular grid of nonoverlapping cells adapted to the heterogeneous sampling of the Earth's mantle by seismic waves [Spakman and Bijwaard, 1998]. Second, we exploit the global data set of Engdahl et al. [1998], which is a reprocessed version of the global data set of the International Seismological Centre. Their reprocessing included hypocenter redetermination and phase reidentification. Finally, we combine all data used (P, pP, and pwP phases) into nearly 5 million ray bundles with a limited spatial extent such that averaging over large mantle volumes is prevented while the signal-to-noise ratio is improved. In the approximate solution of the huge inverse problem we obtain a variance reduction of 57.1%. Synthetic sensitivity tests indicate horizontal resolution on the scale of the smallest cells (0.6?? or 1.2??) in the shallow parts of subduction zones decreasing to approximately 2??-3?? resolution in well-sampled regions in the lower mantle. Vertical resolution can be worse (up to several hundreds of kilometers) in subduction zones with rays predominantly pointing along dip. Important features of the solution are as follows: 100-200 km thick high-velocity slabs beneath all major subduction zones, sometimes flattening in the transition zone and sometimes directly penetrating into the lower mantle; large high-velocity anomalies in the lower mantle that have been attributed to subduction of the Tethys ocean and the Farallon plate; and low-velocity anomalies continuing across the 660 km discontinuity to hotspots at the surface under Iceland, east Africa, the Canary Islands, Yellowstone, and the Society Islands. Our findings corroborate that the 660 km boundary may resist but not prevent (present day) large-scale mass transfer from upper to lower mantle or vice versa. This observation confirms the results of previous, global mantle studies that employed coarser parameterizations. Copyright 1998 by the American Geophysical Union.

Investigating the Greenland ice sheet evolution under changing climate using a three-dimensional full-Stokes model

NASA Astrophysics Data System (ADS)

Seddik, H.; Greve, R.; Zwinger, T.; Gillet-Chaulet, F.; Gagliardini, O.

2010-12-01

A three-dimensional, thermo-mechanically coupled model is applied to the Greenland ice sheet. The model implements the full-Stokes equations for the ice dynamics, and the system is solved with the finite-element method (FEM) using the open source multi-physics package Elmer (http://www.csc.fi/elmer/). The finite-element mesh for the computational domain has been created using the Greenland surface and bedrock DEM data with a spatial resolution of 5 km (SeaRise community effort, based on Bamber and others, 2001). The study is particularly aimed at better understanding the ice dynamics near the major Greenland ice streams. The meshing procedure starts with the bedrock footprint where a mesh with triangle elements and a resolution of 5 km is constructed. Since the resulting mesh is unnecessarily dense in areas with slow ice dynamics, an anisotropic mesh adaptation procedure has been introduced. Using the measured surface velocities to evaluate the Hessian matrix of the velocities, a metric tensor is computed at the mesh vertices in order to define the adaptation scheme. The resulting meshed footprint obtained with the automatic tool YAMS shows a high density of elements in the vicinities of the North-East Greenland Ice Stream (NEGIS), the Jakobshavn ice stream (JIS) and the Kangerdlugssuaq (KL) and Helheim (HH) glaciers. On the other hand, elements with a coarser resolution are generated away from the ice streams and domain margins. The final three-dimensional mesh is obtained by extruding the 2D footprint with 21 vertical layers, so that the resulting mesh contains 400860 wedge elements and 233583 nodes. The numerical solution of the Stokes and the heat transfer equations involves direct and iterative solvers depending on the simulation case, and both methods are coupled with stabilization procedures. The boundary conditions are such that the temperature at the surface uses the present-day mean annual air temperature given by a parameterization or directly from the available data, the geothermal heat flux at the bedrock is prescribed as spatially constant and the lateral sides are open boundaries. A non-linear Weertman law is used for the basal sliding. The project goal is to better assess the effects of dynamical changes of the Greenland ice sheet on sea level rise under global-warming conditions. Hence, the simulations have been conducted in order to investigate the ice sheet evolution using the climate forcing experiments defined in the SeaRISE project. For that purpose, four different experiments have been conducted, (i) constant climate control run beginning at present (epoch 2004-1-1 0:0:0) and running up to 500 years holding the climate constant to its present state, (ii) constant climate forcing with increased basal lubrication, (iii) AR4 climate run forced by anomalies derived from results given in the IPCC 4th Assessment Report (AR4) for the A1B emission scenario, (iv) AR4 climate run with increased basal lubrication.

Modeling Aerosol Microphysical and Radiative Effects on Clouds and Implications for the Effects of Black and Brown Carbon on Clouds

NASA Astrophysics Data System (ADS)

Ten Hoeve, J. E.; Jacobson, M. Z.

2010-12-01

Satellite observational studies have found an increase in cloud fraction (CF) and cloud optical depth (COD) with increasing aerosol optical depth (AOD) followed by a decreasing CF/COD with increasing AOD at higher AODs over the Amazon Basin. The shape of this curve is similar to that of a boomerang, and thus the effect has been dubbed the "boomerang effect.” The increase in CF/COD with increasing AOD at low AODs is ascribed to the first and second indirect effects and is referred to as a microphysical effect of aerosols on clouds. The decrease in CF/COD at higher AODs is ascribed to enhanced warming of clouds due to absorbing aerosols, either as inclusions in drops or interstitially between drops. This is referred to as a radiative effect. To date, the interaction of the microphysical and radiative effects has not been simulated with a regional or global computer model. Here, we simulate the boomerang effect with the nested global-through-urban climate, air pollution, weather forecast model, GATOR-GCMOM, for the Amazon biomass burning season of 2006. We also compare the model with an extensive set of data, including satellite data from MODIS, TRMM, and CALIPSO, in situ surface observations, upper-air data, and AERONET data. Biomass burning emissions are obtained from the Global Fire Emissions Database (GFEDv2), and are combined with MODIS land cover data along with biomass burning emission factors. A high-resolution domain, nested within three increasingly coarser domains, is employed over the heaviest biomass burning region within the arc of deforestation. Modeled trends in cloud properties with aerosol loading compare well with MODIS observed trends, allowing causation of these observed correlations, including of the boomerang effect, to be determined by model results. The impact of aerosols on various cloud parameters, such as cloud optical thickness, cloud fraction, cloud liquid water/ice content, and precipitation, are shown through differences between simulations that include and exclude biomass burning emissions. This study suggests by cause and effect through numerical modeling that aerosol radiative effects counteract microphysical effects at high AODs, a result previously shown by correlation alone. As such, computer models that exclude treatment of cloud radiative effects are likely to overpredict the indirect effects of aerosols on clouds and underestimate the warming due to aerosols containing black carbon.

A Model-Based Study of Ecohydrological Controls in the Mojave Desert

NASA Astrophysics Data System (ADS)

Ng, G. C.; Bedford, D.; Miller, D. M.

2010-12-01

Desert ecosystems represent extreme conditions near the limits of viability for vegetation. Their dependence on scarce resources make them vulnerable to climate and land use change. Understanding how ecohydrological conditions impact plants in such regions is critical for ecological sustainability. Various relationships have been observed in the field between vegetation growth and meteorology, terrain, and plant physiology. Quantifying the complex interactions of those influences on vegetation dynamics can be facilitated with a physically-based ecohydrological model. To assess ecohydrological controls in the Mojave Desert, we employ the CLM4.0 land-surface model with the Carbon-Nitrogen model component to simulate vegetation dynamics [Olesen et al., 2010]. Using an ecohydrological model with fully prognostic vegetation variables is essential for representing the coupled dynamics between plants and soil moisture. We apply the CLM4.0-CN model to a study basin in the Mojave National Preserve that covers a variety of conditions. Soils range from coarse-textured wash sediments to low-permeability desert pavements. Higher elevations in the basin experience cooler and moister conditions than the lower wash areas. The dominant vegetation types in the basin include the evergreen shrub Larrea tridentata (creosote) and the drought-deciduous shrub Ambrosia dumosa. Simulations are conducted over a 50 year period to investigate both seasonal and interannual dynamics. Sensitivity tests indicate that high temporal resolution rainfall inputs (at least hourly) are important for properly resolving ecohydrological dynamics at the study site. As expected, preliminary results show that both coarser soils and milder climate facilitate vegetation growth in this moisture-limited region. However, results indicate that effects of soil texture variations become subordinate with milder climate. The model also reveals how drought-deciduous and evergreen shrub types respond differently to various conditions. Due to its quick response to sporadic wet episodes, the drought-deciduous Ambrosia thrives under harsher (hotter and drier) climates in simulations. The evergreen Larrea shrub becomes more competitive with more consistent moisture of the relatively milder climates in the basin. Multi-decadal simulations indicate that anomalously wet years can yield a sustained boost in vegetation in following years, especially for Larrea. These model results coincide with many observed vegetation patterns in the field, and they serve to elucidate and quantify the contributing factors that impact desert vegetation.

Air pollution modeling over very complex terrain: An evaluation of WRF-Chem over Switzerland for two 1-year periods

NASA Astrophysics Data System (ADS)

Ritter, Mathias; Müller, Mathias D.; Tsai, Ming-Yi; Parlow, Eberhard

2013-10-01

The fully coupled chemistry module (WRF-Chem) within the Weather Research and Forecasting (WRF) model has been implemented over a Swiss domain for the years 2002 and 1991. The very complex terrain requires a high horizontal resolution (2 × 2 km2), which is achieved by nesting the Swiss domain into a coarser European one. The temporal and spatial distribution of O3, NO2 and PM10 as well as temperature and solar radiation are evaluated against ground-based measurements. The model performs well for the meteorological parameters with Pearson correlation coefficients of 0.92 for temperature and 0.88-0.89 for solar radiation. Temperature has root mean square errors (RMSE) of 3.30 K and 3.51 K for 2002 and 1991 and solar radiation has RMSEs of 122.92 and 116.35 for 2002 and 1991, respectively. For the modeled air pollutants, a multi-linear regression post-processing was used to eliminate systematic bias. Seasonal variations of post-processed air pollutants are represented correctly. However, short-term peaks of several days are not captured by the model. Averaged daily maximum and daily values of O3 achieved Pearson correlation coefficients of 0.69-0.77 whereas averaged NO2 and PM10 had the highest correlations for yearly average values (0.68-0.78). The spatial distribution reveals the importance of PM10 advection from the Po valley to southern Switzerland (Ticino). The absolute errors are ranging from - 10 to 15 μg/m3 for ozone, - 9 to 3 μg/m3 for NO2 and - 4 to 3 μg/m3 for PM10. However, larger errors occur along heavily trafficked roads, in street canyons or on mountains. We also compare yearly modeled results against a dedicated Swiss dispersion model for NO2 and PM10. The dedicated dispersion model has a slightly better statistical performance, but WRF-Chem is capable of computing the temporal evolution of three-dimensional data for a variety of air pollutants and meteorological parameters. Overall, WRF-Chem with the application of post-processing algorithms can produce encouraging statistical values over very complex terrain which are competitive with similar studies.

Using tephra layers as absolute and relative chronological markers: an example from Lake Suigetsu, Japan

NASA Astrophysics Data System (ADS)

Smith, V.; Albert, P. G.; Staff, R.; Mark, D. F.; Bronk Ramsey, C.; Nakagawa, T.

2014-12-01

The Lake Suigetsu cores (SG06 and SG14) from Honshu Island, central Japan, provide a high-resolution paleoenvironmental record for the last ~200 kyrs. The composite record is ~85 m-long and it contains numerous tephras, more than 35 visible and numerous non-visible layers (cryptotephra). The major and trace element glass chemistry of these tephras allows the layers to be correlated to specific eruptions and tephra layers in other archives [1]. The record preserves large eruptions from volcanoes from Kyushu, Honshu, South Korea, and smaller explosive events from more proximal volcanoes, Daisen and Sanbe. The Lake Suigetsu has a very detailed varve and radiocarbon chronology [2] that has been exploited to provide precise ages for the tephra layers from the last 50 kyrs [1]. These ages can constrain the tempo of volcanic activity, and the age models of other sedimentary (paleoenvironmental and archaeological) records that contain the tephra. The deeper parts of the Suigetsu core are not continuosly annually laminated and are outside the radiocarbon timeframe and therefore do not have a well constrined chronology. The tephra layers can be used to provide an absolute chronology as eruption deposits from South Korea, Daisen and Sanbe often contain K-rich crystal phases, which can be dated using 40Ar/39Ar methods. Correlating these distal tephra layers in Lake Suigetsu to proximal deposits, using the glass chemistry, is essential as large crystals are required to obtain precise 40Ar/39Ar ages and these are only abundant in the coarser proximal deposits [3, 4]. These widespread marker layers can be also be used for relative chronology. Identifying the same tephras in disparate high-resolution archives allows them to be directly compared so that leads and lags in paleoclimate can be identified on the regional to continental scale, providing some insight into the fundamental drivers of the Earth's climate system. References: [1] Smith et al. (2013) Quaternary Science Reviews 67, 121-137. [2] Bronk Ramsey et al. (2012) Science 338, 370-374. [3] Smith et al. (2011) Quaternary Science Reviews 30, 2845-2850. [4] Mark et al. (2014) Quaternary Geochronology 21, 90-103.

Identification and classification of structural soil conservation measures based on very high resolution stereo satellite data.

PubMed

Eckert, Sandra; Tesfay Ghebremicael, Selamawit; Hurni, Hans; Kohler, Thomas

2017-05-15

Land degradation affects large areas of land around the globe, with grave consequences for those living off the land. Major efforts are being made to implement soil and water conservation measures that counteract soil erosion and help secure vital ecosystem services. However, where and to what extent such measures have been implemented is often not well documented. Knowledge about this could help to identify areas where soil and water conservation measures are successfully supporting sustainable land management, as well as areas requiring urgent rehabilitation of conservation structures such as terraces and bunds. This study explores the potential of the latest satellite-based remote sensing technology for use in assessing and monitoring the extent of existing soil and water conservation structures. We used a set of very high resolution stereo Geoeye-1 satellite data, from which we derived a detailed digital surface model as well as a set of other spectral, terrain, texture, and filtered information layers. We developed and applied an object-based classification approach, working on two segmentation levels. On the coarser level, the aim was to delimit certain landscape zones. Information about these landscape zones is useful in distinguishing different types of soil and water conservation structures, as each zone contains certain specific types of structures. On the finer level, the goal was to extract and identify different types of linear soil and water conservation structures. The classification rules were based mainly on spectral, textural, shape, and topographic properties, and included object relationships. This approach enabled us to identify and separate from other classes the majority (78.5%) of terraces and bunds, as well as most hillside terraces (81.25%). Omission and commission errors are similar to those obtained by the few existing studies focusing on the same research objective but using different types of remotely sensed data. Based on our results, we estimate that the construction of the conservation structures in our study area in Eritrea required over 300,000 person-days of work, which underlines the huge efforts involved in soil and water conservation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Exploring the mutual enhancement between droughts and heatwaves in Europe

NASA Astrophysics Data System (ADS)

Samaniego, L. E.; Kumar, R.; Thober, S.; Pan, M.; Prudhomme, C.; Sheffield, J.; Wanders, N.; Wood, E. F.

2016-12-01

Extensive analyses of past and future changes in essential hydrologicalvariables such as soil moisture based on climate and/or land surfacemodel projections have been carried out during the last decades. Recentstudies, however, showed that no comprehensive picture of theanticipated changes has evolved basically due to the large uncertaintiesin both observed and projected changes as well as their coarser spatialresolution. So far, concluding statements cannot be drawn, in particularfor droughts and heat waves, although the key role of soil moisture foramplifying heat waves and its skill for predicting temperature has beenidentified. In this study, we hypothesized that the mutual enhancementbetween droughts and heat waves is intensified as the climate warms. Putdifferently, a drought can make a hot day hotter while a heat wave canexacerbate a moderate drought event into an extreme one. Europe, in particular, has endured large scale drought-heat-wave eventsduring the recent past (e.g., 2003), which have induced enormoussocio-economic losses as well as casualties. Testing thepreviously posed hypothesis within the Pan-EU domain has been limitedmainly by the availability of reliable and high-resolution data sets. The EDgE project commissioned by the ECMWF (C3S) provides a uniqueopportunity to test this hypothesis. High-resolution multi-modelhydrologic simulations over the Pan-EU domain at a scale of 5x5 km2 havebeen completed for the historical period 1955-2015 with the mHM(www.ufz.de/mhm) and PCR-GLOBWB. Noah-MP and VIC simulations will beaccomplished soon. Using these multi-model unprecedented simulations, daily soil moistureindex and temperature anomalies from 1955 to 2015 will beestimated. The stochastic relationships between these variables will beinvestigated with empirical copulas. The main goal of this study is totest whether a significant Granger causality existsbetween soil moisture and temperature anomaly fields over thePan-EU. The advantage of this testing framework stems from the fact thatit is based on predictability instead of correlation to identifycausation, as it is the case with standard correlation-basedapproaches. Preliminary tests indicate that the mutual enhancementhypothesis cannot be rejected in hot-spot areas enduring heavyanthropogenic disturbances.

Transitioning Enhanced Land Surface Initialization and Model Verification Capabilities to the Kenya Meteorological Department (KMD)

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Mungai, John; Sakwa, Vincent; Zavodsky, Bradley T.; Srikishen, Jayanthi; Limaye, Ashutosh; Blankenship, Clay B.

2016-01-01

Flooding, severe weather, and drought are key forecasting challenges for the Kenya Meteorological Department (KMD), based in Nairobi, Kenya. Atmospheric processes leading to convection, excessive precipitation and/or prolonged drought can be strongly influenced by land cover, vegetation, and soil moisture content, especially during anomalous conditions and dry/wet seasonal transitions. It is thus important to represent accurately land surface state variables (green vegetation fraction, soil moisture, and soil temperature) in Numerical Weather Prediction (NWP) models. The NASA SERVIR and the Short-term Prediction Research and Transition (SPoRT) programs in Huntsville, AL have established a working partnership with KMD to enhance its regional modeling capabilities. SPoRT and SERVIR are providing experimental land surface initialization datasets and model verification capabilities for capacity building at KMD. To support its forecasting operations, KMD is running experimental configurations of the Weather Research and Forecasting (WRF; Skamarock et al. 2008) model on a 12-km/4-km nested regional domain over eastern Africa, incorporating the land surface datasets provided by NASA SPoRT and SERVIR. SPoRT, SERVIR, and KMD participated in two training sessions in March 2014 and June 2015 to foster the collaboration and use of unique land surface datasets and model verification capabilities. Enhanced regional modeling capabilities have the potential to improve guidance in support of daily operations and high-impact weather and climate outlooks over Eastern Africa. For enhanced land-surface initialization, the NASA Land Information System (LIS) is run over Eastern Africa at 3-km resolution, providing real-time land surface initialization data in place of interpolated global model soil moisture and temperature data available at coarser resolutions. Additionally, real-time green vegetation fraction (GVF) composites from the Suomi-NPP VIIRS instrument is being incorporated into the KMD-WRF runs, using the product generated by NOAA/NESDIS. Model verification capabilities are also being transitioned to KMD using NCAR's Model *Corresponding author address: Jonathan Case, ENSCO, Inc., 320 Sparkman Dr., Room 3008, Huntsville, AL, 35805. Email: Jonathan.Case-1@nasa.gov Evaluation Tools (MET; Brown et al. 2009) software in conjunction with a SPoRT-developed scripting package, in order to quantify and compare errors in simulated temperature, moisture and precipitation in the experimental WRF model simulations. This extended abstract and accompanying presentation summarizes the efforts and training done to date to support this unique regional modeling initiative at KMD. To honor the memory of Dr. Peter J. Lamb and his extensive efforts in bolstering weather and climate science and capacity-building in Africa, we offer this contribution to the special Peter J. Lamb symposium. The remainder of this extended abstract is organized as follows. The collaborating international organizations involved in the project are presented in Section 2. Background information on the unique land surface input datasets is presented in Section 3. The hands-on training sessions from March 2014 and June 2015 are described in Section 4. Sample experimental WRF output and verification from the June 2015 training are given in Section 5. A summary is given in Section 6, followed by Acknowledgements and References.

REMEDIATION OF RADIUM FROM CONTAMINATED SOIL

EPA Science Inventory

The objective of this study was to demonstrate the application of a physico-chemical separation process for the removal of radium from a sample of contaminated soil at the Ottawa, Illinois, site near Chicago. The size/activity distribution analyzed among the particles coarser tha...

AN EVALUATION OF STORM DRAINAGE INLET DEVICES FOR STORMWATER QUALITY TREATMENT

EPA Science Inventory

The activities summarized in this paper included the testing of three representative stormwater control devices that were located at storm drainage inlets. The two proprietary devices utilized screening and filtering (using filter fabric and a coarser mesh). A conventional catchb...

Multiscale Modeling of Diffusion in a Crowded Environment.

PubMed

Meinecke, Lina

2017-11-01

We present a multiscale approach to model diffusion in a crowded environment and its effect on the reaction rates. Diffusion in biological systems is often modeled by a discrete space jump process in order to capture the inherent noise of biological systems, which becomes important in the low copy number regime. To model diffusion in the crowded cell environment efficiently, we compute the jump rates in this mesoscopic model from local first exit times, which account for the microscopic positions of the crowding molecules, while the diffusing molecules jump on a coarser Cartesian grid. We then extract a macroscopic description from the resulting jump rates, where the excluded volume effect is modeled by a diffusion equation with space-dependent diffusion coefficient. The crowding molecules can be of arbitrary shape and size, and numerical experiments demonstrate that those factors together with the size of the diffusing molecule play a crucial role on the magnitude of the decrease in diffusive motion. When correcting the reaction rates for the altered diffusion we can show that molecular crowding either enhances or inhibits chemical reactions depending on local fluctuations of the obstacle density.

Spatial and temporal variation in distribution of mangroves in Moreton Bay, subtropical Australia: a comparison of pattern metrics and change detection analyses based on aerial photographs

NASA Astrophysics Data System (ADS)

Manson, F. J.; Loneragan, N. R.; Phinn, S. R.

2003-07-01

An assessment of the changes in the distribution and extent of mangroves within Moreton Bay, southeast Queensland, Australia, was carried out. Two assessment methods were evaluated: spatial and temporal pattern metrics analysis, and change detection analysis. Currently, about 15,000 ha of mangroves are present in Moreton Bay. These mangroves are important ecosystems, but are subject to disturbance from a number of sources. Over the past 25 years, there has been a loss of more than 3800 ha, as a result of natural losses and mangrove clearing (e.g. for urban and industrial development, agriculture and aquaculture). However, areas of new mangroves have become established over the same time period, offsetting these losses to create a net loss of about 200 ha. These new mangroves have mainly appeared in the southern bay region and the bay islands, particularly on the landward edge of existing mangroves. In addition, spatial patterns and species composition of mangrove patches have changed. The pattern metrics analysis provided an overview of mangrove distribution and change in the form of single metric values, while the change detection analysis gave a more detailed and spatially explicit description of change. An analysis of the effects of spatial scales on the pattern metrics indicated that they were relatively insensitive to scale at spatial resolutions less than 50 m, but that most metrics became sensitive at coarser resolutions, a finding which has implications for mapping of mangroves based on remotely sensed data.