Geoelectrical characterisation of basement aquifers: the case of Iberekodo, southwestern Nigeria

NASA Astrophysics Data System (ADS)

Aizebeokhai, Ahzegbobor P.; Oyeyemi, Kehinde D.

2018-03-01

Basement aquifers, which occur within the weathered and fractured zones of crystalline bedrocks, are important groundwater resources in tropical and subtropical regions. The development of basement aquifers is complex owing to their high spatial variability. Geophysical techniques are used to obtain information about the hydrologic characteristics of the weathered and fractured zones of the crystalline basement rocks, which relates to the occurrence of groundwater in the zones. The spatial distributions of these hydrologic characteristics are then used to map the spatial variability of the basement aquifers. Thus, knowledge of the spatial variability of basement aquifers is useful in siting wells and boreholes for optimal and perennial yield. Geoelectrical resistivity is one of the most widely used geophysical methods for assessing the spatial variability of the weathered and fractured zones in groundwater exploration efforts in basement complex terrains. The presented study focuses on combining vertical electrical sounding with two-dimensional (2D) geoelectrical resistivity imaging to characterise the weathered and fractured zones in a crystalline basement complex terrain in southwestern Nigeria. The basement aquifer was delineated, and the nature, extent and spatial variability of the delineated basement aquifer were assessed based on the spatial variability of the weathered and fractured zones. The study shows that a multiple-gradient array for 2D resistivity imaging is sensitive to vertical and near-surface stratigraphic features, which have hydrological implications. The integration of resistivity sounding with 2D geoelectrical resistivity imaging is efficient and enhances near-surface characterisation in basement complex terrain.

[Spatial variability of surface soil nutrients in the landslide area of Beichuan County, South- west China, after 5 · 12 Wenchuan Earthquake].

PubMed

Mai, Ji-shan; Zhao, Ting-ning; Zheng, Jiang-kun; Shi, Chang-qing

2015-12-01

Based on grid sampling and laboratory analysis, spatial variability of surface soil nutrients was analyzed with GS⁺ and other statistics methods on the landslide area of Fenghuang Mountain, Leigu Town, Beichuan County. The results showed that except for high variability of available phosphorus, other soil nutrients exhibited moderate variability. The ratios of nugget to sill of the soil available phosphorus and soil organic carbon were 27.9% and 28.8%, respectively, showing moderate spatial correlation, while the ratios of nugget to sill of the total nitrogen (20.0%), total phosphorus (24.3%), total potassium (11.1%), available nitrogen (11.2%), and available potassium (22.7%) suggested strong spatial correlation. The total phosphorus had the maximum range (1232.7 m), followed by available nitrogen (541.27 m), total nitrogen (468.35 m), total potassium (136.0 m), available potassium (128.7 m), available phosphorus (116.6 m), and soil organic carbon (93.5 m). Soil nutrients had no significant variation with the increase of altitude, but gradually increased from the landslide area, the transition area, to the little-impacted area. The total and available phosphorus contents of the landslide area decreased by 10.3% and 79.7% compared to that of the little-impacted area, respectively. The soil nutrient contents in the transition area accounted for 31.1%-87.2% of that of the little-impacted area, with the nant reason for the spatial variability of surface soil nutrients.

An LES study on the spatial variability impact of surface sensible heat flux (SHF) on the convective boundary layer (CBL)

NASA Astrophysics Data System (ADS)

Kang, S. L.; Chun, J.; Kumar, A.

2015-12-01

We study the spatial variability impact of surface sensible heat flux (SHF) on the convective boundary layer (CBL), using the Weather Research and Forecasting (WRF) model in large eddy simulation (LES) mode. In order to investigate the response of the CBL to multi-scale feature of the surface SHF field over a local area of several tens of kilometers or smaller, an analytic surface SHF map is crated as a function of the chosen feature. The spatial variation in the SHF map is prescribed with a two-dimensional analytical perturbation field, which is generated by using the inverse transform technique of the Fourier series whose coefficients are controlled, of which spectrum to have a particular slope in the chosen range of wavelength. Then, the CBL responses to various SHF heterogeneities are summarized as a function of the spectral slope, in terms of mean structure, turbulence statistics and cross-scale processes. The range of feasible SHF heterogeneities is obtained from the SHF maps produced by a land surface model (LSM) of the WRF system. The LSM-derived SHF maps are a function of geographical data on various resolutions. Based on the numerical experiment results with the surface heterogeneities in the range, we will discuss the uncertainty in the SHF heterogeneity and its impact on the atmosphere in a numerical model. Also we will present the range of spatial scale of the surface SHF heterogeneity that significantly influence on the whole CBL. Lastly, we will report the test result of the hypothesis that the spatial variability of SHF is more representative of surface thermal heterogeneity than is the latent heat flux over the local area of several tens of kilometers or smaller.

Ground-based measurement of surface temperature and thermal emissivity

NASA Technical Reports Server (NTRS)

Owe, M.; Van De Griend, A. A.

1994-01-01

Motorized cable systems for transporting infrared thermometers have been used successfully during several international field campaigns. Systems may be configured with as many as four thermal sensors up to 9 m above the surface, and traverse a 30 m transect. Ground and canopy temperatures are important for solving the surface energy balance. The spatial variability of surface temperature is often great, so that averaged point measurements result in highly inaccurate areal estimates. The cable systems are ideal for quantifying both temporal and spatial variabilities. Thermal emissivity is also necessary for deriving the absolute physical temperature, and measurements may be made with a portable measuring box.

Spatial Variability of Wet Troposphere Delays Over Inland Water Bodies

NASA Astrophysics Data System (ADS)

Mehran, Ali; Clark, Elizabeth A.; Lettenmaier, Dennis P.

2017-11-01

Satellite radar altimetry has enabled the study of water levels in large lakes and reservoirs at a global scale. The upcoming Surface Water and Ocean Topography (SWOT) satellite mission (scheduled launch 2020) will simultaneously measure water surface extent and elevation at an unprecedented accuracy and resolution. However, SWOT retrieval accuracy will be affected by a number of factors, including wet tropospheric delay—the delay in the signal's passage through the atmosphere due to atmospheric water content. In past applications, the wet tropospheric delay over large inland water bodies has been corrected using atmospheric moisture profiles based on atmospheric reanalysis data at relatively coarse (tens to hundreds of kilometers) spatial resolution. These products cannot resolve subgrid variations in wet tropospheric delays at the spatial resolutions (of 1 km and finer) that SWOT is intended to resolve. We calculate zenith wet tropospheric delays (ZWDs) and their spatial variability from Weather Research and Forecasting (WRF) numerical weather prediction model simulations at 2.33 km spatial resolution over the southwestern U.S., with attention in particular to Sam Rayburn, Ray Hubbard, and Elephant Butte Reservoirs which have width and length dimensions that are of order or larger than the WRF spatial resolution. We find that spatiotemporal variability of ZWD over the inland reservoirs depends on climatic conditions at the reservoir location, as well as distance from ocean, elevation, and surface area of the reservoir, but that the magnitude of subgrid variability (relative to analysis and reanalysis products) is generally less than 10 mm.

Predator-guided sampling reveals biotic structure in the bathypelagic.

PubMed

Benoit-Bird, Kelly J; Southall, Brandon L; Moline, Mark A

2016-02-24

We targeted a habitat used differentially by deep-diving, air-breathing predators to empirically sample their prey's distributions off southern California. Fine-scale measurements of the spatial variability of potential prey animals from the surface to 1,200 m were obtained using conventional fisheries echosounders aboard a surface ship and uniquely integrated into a deep-diving autonomous vehicle. Significant spatial variability in the size, composition, total biomass, and spatial organization of biota was evident over all spatial scales examined and was consistent with the general distribution patterns of foraging Cuvier's beaked whales (Ziphius cavirostris) observed in separate studies. Striking differences found in prey characteristics between regions at depth, however, did not reflect differences observed in surface layers. These differences in deep pelagic structure horizontally and relative to surface structure, absent clear physical differences, change our long-held views of this habitat as uniform. The revelation that animals deep in the water column are so spatially heterogeneous at scales from 10 m to 50 km critically affects our understanding of the processes driving predator-prey interactions, energy transfer, biogeochemical cycling, and other ecological processes in the deep sea, and the connections between the productive surface mixed layer and the deep-water column. © 2016 The Author(s).

Evaluation of the global MODIS 30 arc-second spatially and temporally complete snow-free land surface albedo and reflectance anisotropy dataset

NASA Astrophysics Data System (ADS)

Sun, Qingsong; Wang, Zhuosen; Li, Zhan; Erb, Angela; Schaaf, Crystal B.

2017-06-01

Land surface albedo is an essential variable for surface energy and climate modeling as it describes the proportion of incident solar radiant flux that is reflected from the Earth's surface. To capture the temporal variability and spatial heterogeneity of the land surface, satellite remote sensing must be used to monitor albedo accurately at a global scale. However, large data gaps caused by cloud or ephemeral snow have slowed the adoption of satellite albedo products by the climate modeling community. To address the needs of this community, we used a number of temporal and spatial gap-filling strategies to improve the spatial and temporal coverage of the global land surface MODIS BRDF, albedo and NBAR products. A rigorous evaluation of the gap-filled values shows good agreement with original high quality data (RMSE = 0.027 for the NIR band albedo, 0.020 for the red band albedo). This global snow-free and cloud-free MODIS BRDF and albedo dataset (established from 2001 to 2015) offers unique opportunities to monitor and assess the impact of the changes on the Earth's land surface.

Range expansion through fragmented landscapes under a variable climate

PubMed Central

Bennie, Jonathan; Hodgson, Jenny A; Lawson, Callum R; Holloway, Crispin TR; Roy, David B; Brereton, Tom; Thomas, Chris D; Wilson, Robert J

2013-01-01

Ecological responses to climate change may depend on complex patterns of variability in weather and local microclimate that overlay global increases in mean temperature. Here, we show that high-resolution temporal and spatial variability in temperature drives the dynamics of range expansion for an exemplar species, the butterfly Hesperia comma. Using fine-resolution (5 m) models of vegetation surface microclimate, we estimate the thermal suitability of 906 habitat patches at the species' range margin for 27 years. Population and metapopulation models that incorporate this dynamic microclimate surface improve predictions of observed annual changes to population density and patch occupancy dynamics during the species' range expansion from 1982 to 2009. Our findings reveal how fine-scale, short-term environmental variability drives rates and patterns of range expansion through spatially localised, intermittent episodes of expansion and contraction. Incorporating dynamic microclimates can thus improve models of species range shifts at spatial and temporal scales relevant to conservation interventions. PMID:23701124

An examination of the spatial variability of the United States surface water balance using the Budyko relationship for current and projected climates

NASA Astrophysics Data System (ADS)

Ficklin, D. L.; Abatzoglou, J. T.

2017-12-01

The spatial variability in the balance between surface runoff (Q) and evapotranspiration (ET) is critical for understanding water availability. The Budyko framework suggests that this balance is solely a function of aridity. Observed deviations from this framework for individual watersheds, however, can vary significantly, resulting in uncertainty in using the Budyko framework in ungauged catchments and under future climate and land use scenarios. Here, we model the spatial variability in the partitioning of precipitation into Q and ET using a set of climatic, physiographic, and vegetation metrics for 211 near-natural watersheds across the contiguous United States (CONUS) within Budyko's framework through the free parameter ω. Using a generalized additive model, we found that precipitation seasonality, the ratio of soil water holding capacity to precipitation, topographic slope, and the fraction of precipitation falling as snow explained 81.2% of the variability in ω. This ω model applied to the Budyko framework explained 97% of the spatial variability in long-term Q for an independent set of near-natural watersheds. The developed ω model was also used to estimate the entire CONUS surface water balance for both contemporary and mid-21st century conditions. The contemporary CONUS surface water balance compared favorably to more sophisticated land-surface modeling efforts. For mid-21st century conditions, the model simulated an increase in the fraction of precipitation used by ET across the CONUS with declines in Q for much of the eastern CONUS and mountainous watersheds across the western US. The Budyko framework using the modeled ω lends itself to an alternative approach for assessing the potential response of catchment water balance to climate change to complement other approaches.

The Variability of the Horizontal Circulation in the Troposphere and Stratosphere: A Comparison

NASA Technical Reports Server (NTRS)

Perlwitz, Judith; Graf, Hans-F.; Hansem, James E. (Technical Monitor)

2001-01-01

The variability of the horizontal circulation in the stratosphere and troposphere of the Northern Hemisphere (NH) is compared by using various approaches. Spatial degrees of freedom (dof) on different time scales were derived. Modes of variability were computed in geopotential height fields at the tropospheric and stratospheric pressure levels by applying multivariate statistical approaches. Features of the spatial and temporal variability of the winterly zonal wind were studied with the help of recurrence and persistence analyses. The geopotential height and zonally-averaged zonal wind at the 50-, 500- and 1000-hPa level are used to investigate the behavior of the horizontal circulation in the lower stratosphere, mid-troposphere and at the near surface level, respectively. It is illustrated that the features of the variability of the horizontal circulation are very similar in the mid-troposphere and at the near surface level. Due to the filtering of tropospheric disturbances by the stratospheric and upper tropospheric zonal mean flow, the variability of the stratospheric circulation exhibits less spatial complexity than the circulation at tropospheric pressure levels. There exist enormous differences in the number of degrees of freedom (or free variability modes) between both atmospheric layers. Results of the analyses clearly show that the concept of a zonally symmetric AO with a simple structure in the troposphere similar to the one in the stratosphere is not valid. It is concluded that the spatially filtered climate change signal can be detected earlier in the stratosphere than in the mid-troposphere or at the near surface level.

Spatial Surface PM2.5 Concentration Estimates for Wildfire Smoke Plumes in the Western U.S. Using Satellite Retrievals and Data Assimilation Techniques

NASA Astrophysics Data System (ADS)

Loria Salazar, S. M.; Holmes, H.

2015-12-01

Health effects studies of aerosol pollution have been extended spatially using data assimilation techniques that combine surface PM2.5 concentrations and Aerosol Optical Depth (AOD) from satellite retrievals. While most of these models were developed for the dark-vegetated eastern U.S. they are being used in the semi-arid western U.S. to remotely sense atmospheric aerosol concentrations. These models are helpful to understand the spatial variability of surface PM2.5concentrations in the western U.S. because of the sparse network of surface monitoring stations. However, the models developed for the eastern U.S. are not robust in the western U.S. due to different aerosol formation mechanisms, transport phenomena, and optical properties. This region is a challenge because of complex terrain, anthropogenic and biogenic emissions, secondary organic aerosol formation, smoke from wildfires, and low background aerosol concentrations. This research concentrates on the use and evaluation of satellite remote sensing to estimate surface PM2.5 concentrations from AOD satellite retrievals over California and Nevada during the summer months of 2012 and 2013. The aim of this investigation is to incorporate a spatial statistical model that uses AOD from AERONET as well as MODIS, surface PM2.5 concentrations, and land-use regression to characterize spatial surface PM2.5 concentrations. The land use regression model uses traditional inputs (e.g. meteorology, population density, terrain) and non-traditional variables (e.g. FIre Inventory from NCAR (FINN) emissions and MODIS albedo product) to account for variability related to smoke plume trajectories and land use. The results will be used in a spatially resolved health study to determine the association between wildfire smoke exposure and cardiorespiratory health endpoints. This relationship can be used with future projections of wildfire emissions related to climate change and droughts to quantify the expected health impact.

An index of floodplain surface complexity

USGS Publications Warehouse

Scown, Murray W.; Thoms, Martin C.; DeJager, Nathan R.

2016-01-01

Floodplain surface topography is an important component of floodplain ecosystems. It is the primary physical template upon which ecosystem processes are acted out, and complexity in this template can contribute to the high biodiversity and productivity of floodplain ecosystems. There has been a limited appreciation of floodplain surface complexity because of the traditional focus on temporal variability in floodplains as well as limitations to quantifying spatial complexity. An index of floodplain surface complexity (FSC) is developed in this paper and applied to eight floodplains from different geographic settings. The index is based on two key indicators of complexity, variability in surface geometry (VSG) and the spatial organisation of surface conditions (SPO), and was determined at three sampling scales. FSC, VSG, and SPO varied between the eight floodplains and these differences depended upon sampling scale. Relationships between these measures of spatial complexity and seven geomorphological and hydrological drivers were investigated. There was a significant decline in all complexity measures with increasing floodplain width, which was explained by either a power, logarithmic, or exponential function. There was an initial rapid decline in surface complexity as floodplain width increased from 1.5 to 5 km, followed by little change in floodplains wider than 10 km. VSG also increased significantly with increasing sediment yield. No significant relationships were determined between any of the four hydrological variables and floodplain surface complexity.

Spatial variations in drainage efficiency in a boreal wetland environment as a function of lidar and radar-derived deviations from the regional hydraulic gradient

NASA Astrophysics Data System (ADS)

Hopkinson, C.; Brisco, B.; Chasmer, L.; Devito, K.; Montgomery, J. S.; Patterson, S.; Petrone, R. M.

2017-12-01

The dense forest cover of the Western Boreal Plains of northern Alberta is underlain by a mix of glacial moraines, sandy outwash sediments and clay plains possessing spatially variable hydraulic conductivities. The region is also characterised by a large number of post-glacial surface depression wetlands that have seasonally and topographically limited surface connectivity. Consequently, drainage along shallow regional hydraulic gradients may be dominated either by variations in surface geology or local variations in Et. Long-term government lake level monitoring is sparse in this region, but over a decade of hydrometeorological monitoring has taken place around the Utikuma Regional Study Area (URSA), a research site led by the University of Alberta. In situ lake and ground water level data are here combined with time series of airborne lidar and RadarSat II synthetic aperture radar (SAR) data to assess the spatial variability of water levels during late summer period characterised by flow recession. Long term Lidar data were collected or obtained by the authors in August of 2002, 2008, 2011 and 2016, while seasonal SAR data were captured approximately every 24 days during the summers of 2015, 2016 and 2017. Water levels for wetlands exceeding 100m2 in area across a north-trending 20km x 5km topographic gradient north of Utikuma Lake were extracted directly from the lidar and indirectly from the SAR. The recent seasonal variability in spatial water levels was extracted from SAR, while the lidar data illustrated more long term trends associated with land use and riparian vegetation succession. All water level data collected in August were combined and averaged at multiple scales using a raster focal statistics function to generate a long term spatial map of the regional hydraulic gradient and scale-dependent variations. Areas of indicated high and low drainage efficiency were overlain onto layers of landcover and surface geology to ascertain causal relationships. Areas associated with high spatial variability in water level illustrate reduced drainage connectivity, while areas of reduced variability indicate high surface connectivity and/or hydraulic conductivity. The hypothesis of surface geology controls on local wetland connectivity and landscape drainage efficiency is supported through this analysis.

Deriving Surface NO2 Mixing Ratios from DISCOVER-AQ ACAM Observations: A Method to Assess Surface NO2 Spatial Variability

NASA Astrophysics Data System (ADS)

Silverman, M. L.; Szykman, J.; Chen, G.; Crawford, J. H.; Janz, S. J.; Kowalewski, M. G.; Lamsal, L. N.; Long, R.

2015-12-01

Studies have shown that satellite NO2 columns are closely related to ground level NO2 concentrations, particularly over polluted areas. This provides a means to assess surface level NO2 spatial variability over a broader area than what can be monitored from ground stations. The characterization of surface level NO2 variability is important to understand air quality in urban areas, emissions, health impacts, photochemistry, and to evaluate the performance of chemical transport models. Using data from the NASA DISCOVER-AQ campaign in Baltimore/Washington we calculate NO2 mixing ratios from the Airborne Compact Atmospheric Mapper (ACAM), through four different methods to derive surface concentration from column measurements. High spectral resolution lidar (HSRL) mixed layer heights, vertical P3B profiles, and CMAQ vertical profiles are used to scale ACAM vertical column densities. The derived NO2 mixing ratios are compared to EPA ground measurements taken at Padonia and Edgewood. We find similar results from scaling with HSRL mixed layer heights and normalized P3B vertical profiles. The HSRL mixed layer heights are then used to scale ACAM vertical column densities across the DISCOVER-AQ flight pattern to assess spatial variability of NO2 over the area. This work will help define the measurement requirements for future satellite instruments.

Spatial and temporal variability of soil temperature, moisture and surface soil properties

NASA Technical Reports Server (NTRS)

Hajek, B. F.; Dane, J. H.

1993-01-01

The overall objectives of this research were to: (l) Relate in-situ measured soil-water content and temperature profiles to remotely sensed surface soil-water and temperature conditions; to model simultaneous heat and water movement for spatially and temporally changing soil conditions; (2) Determine the spatial and temporal variability of surface soil properties affecting emissivity, reflectance, and material and energy flux across the soil surface. This will include physical, chemical, and mineralogical characteristics of primary soil components and aggregate systems; and (3) Develop surface soil classes of naturally occurring and distributed soil property assemblages and group classes to be tested with respect to water content, emissivity and reflectivity. This document is a report of studies conducted during the period funded by NASA grants. The project was designed to be conducted over a five year period. Since funding was discontinued after three years, some of the research started was not completed. Additional publications are planned whenever funding can be obtained to finalize data analysis for both the arid and humid locations.

Spatial correlations of interdecadal variation in global surface temperatures

NASA Technical Reports Server (NTRS)

Mann, Michael E.; Park, Jeffrey

1993-01-01

We have analyzed spatial correlation patterns of interdecadal global surface temperature variability from an empirical perspective. Using multitaper coherence estimates from 140-yr records, we find that correlations between hemispheres are significant at about 95 percent confidence for nonrandomness for most of the frequency band in the 0.06-0.24 cyc/yr range. Coherence estimates of pairs of 100-yr grid-point temperature data series near 5-yr period reveal teleconnection patterns consistent with known patterns of ENSO variability. Significant correlated variability is observed near 15 year period, with the dominant teleconnection pattern largely confined to the Northern Hemisphere. Peak-to-peak Delta-T is at about 0.5 deg, with simultaneous warming and cooling of discrete patches on the earth's surface. A global average of this pattern would largely cancel.

Evapotranspiration and runoff from large land areas: Land surface hydrology for atmospheric general circulation models

NASA Technical Reports Server (NTRS)

Famiglietti, J. S.; Wood, Eric F.

1993-01-01

A land surface hydrology parameterization for use in atmospheric GCM's is presented. The parameterization incorporates subgrid scale variability in topography, soils, soil moisture and precipitation. The framework of the model is the statistical distribution of a topography-soils index, which controls the local water balance fluxes, and is therefore taken to represent the large land area. Spatially variable water balance fluxes are integrated with respect to the topography-soils index to yield our large topography-soils distribution, and interval responses are weighted by the probability of occurrence of the interval. Grid square averaged land surface fluxes result. The model functions independently as a macroscale water balance model. Runoff ratio and evapotranspiration efficiency parameterizations are derived and are shown to depend on the spatial variability of the above mentioned properties and processes, as well as the dynamics of land surface-atmosphere interactions.

The influence of lithology on surface water sources

EPA Science Inventory

Understanding the temporal and spatial variability of surface water sources within a basin is vital to our ability to manage the impacts of climate variability and land cover change. Water stable isotopes can be used as a tool to determine geographic and seasonal sources of water...

Standard Deviation of Spatially-Averaged Surface Cross Section Data from the TRMM Precipitation Radar

NASA Technical Reports Server (NTRS)

Meneghini, Robert; Jones, Jeffrey A.

2010-01-01

We investigate the spatial variability of the normalized radar cross section of the surface (NRCS or Sigma(sup 0)) derived from measurements of the TRMM Precipitation Radar (PR) for the period from 1998 to 2009. The purpose of the study is to understand the way in which the sample standard deviation of the Sigma(sup 0) data changes as a function of spatial resolution, incidence angle, and surface type (land/ocean). The results have implications regarding the accuracy by which the path integrated attenuation from precipitation can be inferred by the use of surface scattering properties.

Spatial variability of wildland fuel characteristics in northern Rocky Mountain ecosystems

Treesearch

Robert E. Keane; Kathy Gray; Valentina Bacciu

2012-01-01

We investigated the spatial variability of a number of wildland fuel characteristics for the major fuel components found in six common northern Rocky Mountain ecosystems. Surface fuel characteristics of loading, particle density, bulk density, and mineral content were measured for eight fuel components - four downed dead woody fuel size classes (1, 10, 100, 1000 hr),...

Multi-platform validation of a high-resolution model in the Western Mediterranean Sea: insight into spatial-temporal variability

NASA Astrophysics Data System (ADS)

Aguiar, Eva; Mourre, Baptiste; Heslop, Emma; Juza, Mélanie; Escudier, Romain; Tintoré, Joaquín

2017-04-01

This study focuses on the validation of the high resolution Western Mediterranean Operational model (WMOP) developed at SOCIB, the Balearic Islands Coastal Observing and Forecasting System. The Mediterranean Sea is often seen as a small scale ocean laboratory where energetic eddies, fronts and circulation features have important ecological consequences. The Medclic project is a program between "La Caixa" Foundation and SOCIB which aims at characterizing and forecasting the "oceanic weather" in the Western Mediterranean Sea, specifically investigating the interactions between the general circulation and mesoscale processes. We use a WMOP 2009-2015 free run hindcast simulation and available observational datasets (altimetry, moorings and gliders) to both assess the numerical simulation and investigate the ocean variability. WMOP has a 2-km spatial resolution and uses CMEMS Mediterranean products as initial and boundary conditions, with surface forcing from the high-resolution Spanish Meteorological Agency model HIRLAM. Different aspects of the spatial and temporal variability in the model are validated from local to regional and basin scales: (1) the principal axis of variability of the surface circulation using altimetry and moorings along the Iberian coast, (2) the inter-annual changes of the surface flows incorporating also glider data, (3) the propagation of mesoscale eddies formed in the Algerian sub-basin using altimetry, and (4) the statistical properties of eddies (number, rotation, size) applying an eddy tracker detection method in the Western Mediterranean Sea. With these key points evaluated in the model, EOF analysis of sea surface height maps are used to investigate spatial patterns of variability associated with eddies, gyres and the basis-scale circulation and so gain insight into the interconnections between sub-basins, as well as the interactions between physical processes at different scales.

Thermal infrared imagery as a tool for analysing the variability of surface saturated areas at various temporal and spatial scales

NASA Astrophysics Data System (ADS)

Glaser, Barbara; Antonelli, Marta; Pfister, Laurent; Klaus, Julian

2017-04-01

Surface saturated areas are important for the on- and offset of hydrological connectivity within the hillslope-riparian-stream continuum. This is reflected in concepts such as variable contributing areas or critical source areas. However, we still lack a standardized method for areal mapping of surface saturation and for observing its spatiotemporal variability. Proof-of-concept studies in recent years have shown the potential of thermal infrared (TIR) imagery to record surface saturation dynamics at various temporal and spatial scales. Thermal infrared imagery is thus a promising alternative to conventional approaches, such as the squishy boot method or the mapping of vegetation. In this study we use TIR images to investigate the variability of surface saturated areas at different temporal and spatial scales in the forested Weierbach catchment (0.45 km2) in western Luxembourg. We took TIR images of the riparian zone with a hand-held FLIR infrared camera at fortnightly intervals over 18 months at nine different locations distributed over the catchment. Not all of the acquired images were suitable for a derivation of the surface saturated areas, as various factors influence the usability of the TIR images (e.g. temperature contrasts, shadows, fog). Nonetheless, we obtained a large number of usable images that provided a good insight into the dynamic behaviour of surface saturated areas at different scales. The images revealed how diverse the evolution of surface saturated areas can be throughout the hydrologic year. For some locations with similar morphology or topography we identified diverging saturation dynamics, while other locations with different morphology / topography showed more similar behaviour. Moreover, we were able to assess the variability of the dynamics of expansion / contraction of saturated areas within the single locations, which can help to better understand the mechanisms behind surface saturation development.

Understanding thermal circulations and near-surface turbulence processes in a small mountain valley

NASA Astrophysics Data System (ADS)

Pardyjak, E.; Dupuy, F.; Durand, P.; Gunawardena, N.; Thierry, H.; Roubin, P.

2017-12-01

The interaction of turbulence and thermal circulations in complex terrain can be significantly different from idealized flat terrain. In particular, near-surface horizontal spatial and temporal variability of winds and thermodynamic variables can be significant event over very small spatial scales. The KASCADE (KAtabatic winds and Stability over CAdarache for Dispersion of Effluents) 2017 conducted from January through March 2017 was designed to address these issues and to ultimately improve prediction of dispersion in complex terrain, particularly during stable atmospheric conditions. We have used a relatively large number of sensors to improve our understanding of the spatial and temporal development, evolution and breakdown of topographically driven flows. KASCADE 2017 consisted of continuous observations and fourteen Intensive Observation Periods (IOPs) conducted in the Cadarache Valley located in southeastern France. The Cadarache Valley is a relatively small valley (5 km x 1 km) with modest slopes and relatively small elevation differences between the valley floor and nearby hilltops ( 100 m). During winter, winds in the valley are light and stably stratified at night leading to thermal circulations as well as complex near-surface atmospheric layering. In this presentation we present results quantifying spatial variability of thermodynamic and turbulence variables as a function of different large -scale forcing conditions (e.g., quiescent conditions, strong westerly flow, and Mistral flow). In addition, we attempt to characterize highly-regular nocturnal horizontal wind meandering and associated turbulence statistics.

Patterns of Canopy and Surface Layer Consumption in a Boreal Forest Fire from Repeat Airborne Lidar

NASA Technical Reports Server (NTRS)

Alonzo, Michael; Morton, Douglas C.; Cook, Bruce D.; Andersen, Hans-Erik; Babcock, Chad; Pattison, Robert

2017-01-01

Fire in the boreal region is the dominant agent of forest disturbance with direct impacts on ecosystem structure, carbon cycling, and global climate. Global and biome-scale impacts are mediated by burn severity, measured as loss of forest canopy and consumption of the soil organic layer. To date, knowledge of the spatial variability in burn severity has been limited by sparse field sampling and moderate resolution satellite data. Here, we used pre- and post-fire airborne lidar data to directly estimate changes in canopy vertical structure and surface elevation for a 2005 boreal forest fire on Alaskas Kenai Peninsula. We found that both canopy and surface losses were strongly linked to pre-fire species composition and exhibited important fine-scale spatial variability at sub-30m resolution. The fractional reduction in canopy volume ranged from 0.61 in lowland black spruce stands to 0.27 in mixed white spruce and broad leaf forest. Residual structure largely reflects standing dead trees, highlighting the influence of pre-fire forest structure on delayed carbon losses from above ground biomass, post-fire albedo, and variability in understory light environments. Median loss of surface elevation was highest in lowland black spruce stands (0.18 m) but much lower in mixed stands (0.02 m), consistent with differences in pre-fire organic layer accumulation. Spatially continuous depth-of-burn estimates from repeat lidar measurements provide novel information to constrain carbon emissions from the surface organic layer and may inform related research on post-fire successional trajectories. Spectral measures of burn severity from Landsat were correlated with canopy (r = 0.76) and surface (r = -0.71) removal in black spruce stands but captured less of the spatial variability in fire effects for mixed stands (canopy r = 0.56, surface r = -0.26), underscoring the difficulty in capturing fire effects in heterogeneous boreal forest landscapes using proxy measures of burn severity from Landsat.

Patterns of canopy and surface layer consumption in a boreal forest fire from repeat airborne lidar

NASA Astrophysics Data System (ADS)

Alonzo, Michael; Morton, Douglas C.; Cook, Bruce D.; Andersen, Hans-Erik; Babcock, Chad; Pattison, Robert

2017-05-01

Fire in the boreal region is the dominant agent of forest disturbance with direct impacts on ecosystem structure, carbon cycling, and global climate. Global and biome-scale impacts are mediated by burn severity, measured as loss of forest canopy and consumption of the soil organic layer. To date, knowledge of the spatial variability in burn severity has been limited by sparse field sampling and moderate resolution satellite data. Here, we used pre- and post-fire airborne lidar data to directly estimate changes in canopy vertical structure and surface elevation for a 2005 boreal forest fire on Alaska’s Kenai Peninsula. We found that both canopy and surface losses were strongly linked to pre-fire species composition and exhibited important fine-scale spatial variability at sub-30 m resolution. The fractional reduction in canopy volume ranged from 0.61 in lowland black spruce stands to 0.27 in mixed white spruce and broadleaf forest. Residual structure largely reflects standing dead trees, highlighting the influence of pre-fire forest structure on delayed carbon losses from aboveground biomass, post-fire albedo, and variability in understory light environments. Median loss of surface elevation was highest in lowland black spruce stands (0.18 m) but much lower in mixed stands (0.02 m), consistent with differences in pre-fire organic layer accumulation. Spatially continuous depth-of-burn estimates from repeat lidar measurements provide novel information to constrain carbon emissions from the surface organic layer and may inform related research on post-fire successional trajectories. Spectral measures of burn severity from Landsat were correlated with canopy (r = 0.76) and surface (r = -0.71) removal in black spruce stands but captured less of the spatial variability in fire effects for mixed stands (canopy r = 0.56, surface r = -0.26), underscoring the difficulty in capturing fire effects in heterogeneous boreal forest landscapes using proxy measures of burn severity from Landsat.

One perspective on spatial variability in geologic mapping

USGS Publications Warehouse

Markewich, H.W.; Cooper, S.C.

1991-01-01

This paper discusses some of the differences between geologic mapping and soil mapping, and how the resultant maps are interpreted. The role of spatial variability in geologic mapping is addressed only indirectly because in geologic mapping there have been few attempts at quantification of spatial differences. This is largely because geologic maps deal with temporal as well as spatial variability and consider time, age, and origin, as well as composition and geometry. Both soil scientists and geologists use spatial variability to delineate mappable units; however, the classification systems from which these mappable units are defined differ greatly. Mappable soil units are derived from systematic, well-defined, highly structured sets of taxonomic criteria; whereas mappable geologic units are based on a more arbitrary heirarchy of categories that integrate many features without strict values or definitions. Soil taxonomy is a sorting tool used to reduce heterogeneity between soil units. Thus at the series level, soils in any one series are relatively homogeneous because their range of properties is small and well-defined. Soil maps show the distribution of soils on the land surface. Within a map area, soils, which are often less than 2 m thick, show a direct correlation to topography and to active surface processes as well as to parent material.

Climatic and physiographic controls of spatial variability in surface water balance over the contiguous United States using the Budyko relationship

NASA Astrophysics Data System (ADS)

Abatzoglou, John T.; Ficklin, Darren L.

2017-09-01

The geographic variability in the partitioning of precipitation into surface runoff (Q) and evapotranspiration (ET) is fundamental to understanding regional water availability. The Budyko equation suggests this partitioning is strictly a function of aridity, yet observed deviations from this relationship for individual watersheds impede using the framework to model surface water balance in ungauged catchments and under future climate and land use scenarios. A set of climatic, physiographic, and vegetation metrics were used to model the spatial variability in the partitioning of precipitation for 211 watersheds across the contiguous United States (CONUS) within Budyko's framework through the free parameter ω. A generalized additive model found that four widely available variables, precipitation seasonality, the ratio of soil water holding capacity to precipitation, topographic slope, and the fraction of precipitation falling as snow, explained 81.2% of the variability in ω. The ω model applied to the Budyko equation explained 97% of the spatial variability in long-term Q for an independent set of watersheds. The ω model was also applied to estimate the long-term water balance across the CONUS for both contemporary and mid-21st century conditions. The modeled partitioning of observed precipitation to Q and ET compared favorably across the CONUS with estimates from more sophisticated land-surface modeling efforts. For mid-21st century conditions, the model simulated an increase in the fraction of precipitation used by ET across the CONUS with declines in Q for much of the eastern CONUS and mountainous watersheds across the western United States.

Scales of Spatial Heterogeneity of Plastic Marine Debris in the Northeast Pacific Ocean

PubMed Central

Goldstein, Miriam C.; Titmus, Andrew J.; Ford, Michael

2013-01-01

Plastic debris has been documented in many marine ecosystems, including remote coastlines, the water column, the deep sea, and subtropical gyres. The North Pacific Subtropical Gyre (NPSG), colloquially called the “Great Pacific Garbage Patch,” has been an area of particular scientific and public concern. However, quantitative assessments of the extent and variability of plastic in the NPSG have been limited. Here, we quantify the distribution, abundance, and size of plastic in a subset of the eastern Pacific (approximately 20–40°N, 120–155°W) over multiple spatial scales. Samples were collected in Summer 2009 using surface and subsurface plankton net tows and quantitative visual observations, and Fall 2010 using surface net tows only. We documented widespread, though spatially variable, plastic pollution in this portion of the NPSG and adjacent waters. The overall median microplastic numerical concentration in Summer 2009 was 0.448 particles m−2 and in Fall 2010 was 0.021 particles m−2, but plastic concentrations were highly variable over the submesoscale (10 s of km). Size-frequency spectra were skewed towards small particles, with the most abundant particles having a cross-sectional area of approximately 0.01 cm2. Most microplastic was found on the sea surface, with the highest densities detected in low-wind conditions. The numerical majority of objects were small particles collected with nets, but the majority of debris surface area was found in large objects assessed visually. Our ability to detect high-plastic areas varied with methodology, as stations with substantial microplastic did not necessarily also contain large visually observable objects. A power analysis of our data suggests that high variability of surface microplastic will make future changes in abundance difficult to detect without substantial sampling effort. Our findings suggest that assessment and monitoring of oceanic plastic debris must account for high spatial variability, particularly in regards to the evaluation of initiatives designed to reduce marine debris. PMID:24278233

Scales of spatial heterogeneity of plastic marine debris in the northeast pacific ocean.

PubMed

Goldstein, Miriam C; Titmus, Andrew J; Ford, Michael

2013-01-01

Plastic debris has been documented in many marine ecosystems, including remote coastlines, the water column, the deep sea, and subtropical gyres. The North Pacific Subtropical Gyre (NPSG), colloquially called the "Great Pacific Garbage Patch," has been an area of particular scientific and public concern. However, quantitative assessments of the extent and variability of plastic in the NPSG have been limited. Here, we quantify the distribution, abundance, and size of plastic in a subset of the eastern Pacific (approximately 20-40°N, 120-155°W) over multiple spatial scales. Samples were collected in Summer 2009 using surface and subsurface plankton net tows and quantitative visual observations, and Fall 2010 using surface net tows only. We documented widespread, though spatially variable, plastic pollution in this portion of the NPSG and adjacent waters. The overall median microplastic numerical concentration in Summer 2009 was 0.448 particles m(-2) and in Fall 2010 was 0.021 particles m(-2), but plastic concentrations were highly variable over the submesoscale (10 s of km). Size-frequency spectra were skewed towards small particles, with the most abundant particles having a cross-sectional area of approximately 0.01 cm(2). Most microplastic was found on the sea surface, with the highest densities detected in low-wind conditions. The numerical majority of objects were small particles collected with nets, but the majority of debris surface area was found in large objects assessed visually. Our ability to detect high-plastic areas varied with methodology, as stations with substantial microplastic did not necessarily also contain large visually observable objects. A power analysis of our data suggests that high variability of surface microplastic will make future changes in abundance difficult to detect without substantial sampling effort. Our findings suggest that assessment and monitoring of oceanic plastic debris must account for high spatial variability, particularly in regards to the evaluation of initiatives designed to reduce marine debris.

Virtual mission stage I: Implications of a spaceborne surface water mission

NASA Astrophysics Data System (ADS)

Clark, E. A.; Alsdorf, D. E.; Bates, P.; Wilson, M. D.; Lettenmaier, D. P.

2004-12-01

The interannual and interseasonal variability of the land surface water cycle depend on the distribution of surface water in lakes, wetlands, reservoirs, and river systems; however, measurements of hydrologic variables are sparsely distributed, even in industrialized nations. Moreover, the spatial extent and storage variations of lakes, reservoirs, and wetlands are poorly known. We are developing a virtual mission to demonstrate the feasibility of observing surface water extent and variations from a spaceborne platform. In the first stage of the virtual mission, on which we report here, surface water area and fluxes are emulated using simulation modeling over three continental scale river basins, including the Ohio River, the Amazon River and an Arctic river. The Variable Infiltration Capacity (VIC) macroscale hydrologic model is used to simulate evapotranspiration, soil moisture, snow accumulation and ablation, and runoff and streamflow over each basin at one-eighth degree resolution. The runoff from this model is routed using a linear transfer model to provide input to a much more detailed flow hydraulics model. The flow hydraulics model then routes runoff through various channel and floodplain morphologies at a 250 m spatial and 20 second temporal resolution over a 100 km by 500 km domain. This information is used to evaluate trade-offs between spatial and temporal resolutions of a hypothetical high resolution spaceborne altimeter by synthetically sampling the resultant model-predicted water surface elevations.

Graffiti for science - erosion painting reveals spatially variable erosivity of sediment-laden flows

NASA Astrophysics Data System (ADS)

Beer, Alexander R.; Kirchner, James W.; Turowski, Jens M.

2016-12-01

Spatially distributed detection of bedrock erosion is a long-standing challenge. Here we show how the spatial distribution of surface erosion can be visualized and analysed by observing the erosion of paint from natural bedrock surfaces. If the paint is evenly applied, it creates a surface with relatively uniform erodibility, such that spatial variability in the erosion of the paint reflects variations in the erosivity of the flow and its entrained sediment. In a proof-of-concept study, this approach provided direct visual verification that sediment impacts were focused on upstream-facing surfaces in a natural bedrock gorge. Further, erosion painting demonstrated strong cross-stream variations in bedrock erosion, even in the relatively narrow (5 m wide) gorge that we studied. The left side of the gorge experienced high sediment throughput with abundant lateral erosion on the painted wall up to 80 cm above the bed, but the right side of the gorge only showed a narrow erosion band 15-40 cm above the bed, likely due to deposited sediment shielding the lower part of the wall. This erosion pattern therefore reveals spatial stream bed aggradation that occurs during flood events in this channel. The erosion painting method provides a simple technique for mapping sediment impact intensities and qualitatively observing spatially distributed erosion in bedrock stream reaches. It can potentially find wide application in both laboratory and field studies.

Spatial response surface modelling in the presence of data paucity for the evaluation of potential human health risk due to the contamination of potable water resources.

PubMed

Liu, Shen; McGree, James; Hayes, John F; Goonetilleke, Ashantha

2016-10-01

Potential human health risk from waterborne diseases arising from unsatisfactory performance of on-site wastewater treatment systems is driven by landscape factors such as topography, soil characteristics, depth to water table, drainage characteristics and the presence of surface water bodies. These factors are present as random variables which are spatially distributed across a region. A methodological framework is presented that can be applied to model and evaluate the influence of various factors on waterborne disease potential. This framework is informed by spatial data and expert knowledge. For prediction at unsampled sites, interpolation methods were used to derive a spatially smoothed surface of disease potential which takes into account the uncertainty due to spatial variation at any pre-determined level of significance. This surface was constructed by accounting for the influence of multiple variables which appear to contribute to disease potential. The framework developed in this work strengthens the understanding of the characteristics of disease potential and provides predictions of this potential across a region. The study outcomes presented constitutes an innovative approach to environmental monitoring and management in the face of data paucity. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

The Effects of Fine-scale Soil Moisture and Canopy Heterogeneities on Energy and Soil Water Fluxes in a Temperate Mixed Deciduous Forest

NASA Astrophysics Data System (ADS)

He, L.; Ivanov, V. Y.; Bohrer, G.; Maurer, K.; Vogel, C. S.; Moghaddam, M.

2011-12-01

Vegetation is heterogeneous at different scales, influencing spatially variable energy and water exchanges between land-surface and atmosphere. Current land surface parameterizations of large-scale models consider spatial variability at a scale of a few kilometers and treat vegetation cover as aggregated patches with uniform properties. However, the coupling mechanisms between fine-scale soil moisture, vegetation, and energy fluxes such as evapotranspiration are strongly nonlinear; the aggregation of surface variations may produce biased energy fluxes. This study aims to improve the understanding of the scale impact in atmosphere-biosphere-hydrosphere interactions, which affects predictive capabilities of land surface models. The study uses a high-resolution, physically-based ecohydrological model tRIBS + VEGGIE as a data integration tool to upscale the heterogeneity of canopy distribution resolved at a few meters to the watershed scale. The study was carried out for a spatially heterogeneous, temperate mixed forest environment of Northern Michigan located near the University of Michigan Biological Station (UMBS). Energy and soil water dynamics were simulated at the tree-canopy resolution in the horizontal plane for a small domain (~2 sq. km) located within a footprint of the AmeriFlux tower. A variety of observational data were used to constrain and confirm the model, including a 3-m profile continuous soil moisture dataset and energy flux data (measured at the AmeriFlux tower footprint). A scenario with a spatially uniform canopy, corresponding to the commonly used 'big-leaf' scheme in land surface parameterizations was used to infer the effects of coarse-scale averaging. To gain insights on how heterogeneous canopy and soil moisture interact and contribute to the domain-averaged transpiration, several scenarios of tree-scale leaf area and soil moisture spatial variability were designed. Specifically, for the same mean states, the scenarios of variability of canopy biomass account for the spatial distribution of photosynthesis (and thus the stomatal resistance), the aerodynamic and leaf boundary layer resistances as well as the differential radiation forcing due to tall tree exposure and lateral shading of short trees. The numerical experiments show that by transpiring spatially varying amounts of water, heterogeneous canopies adjust the spatial soil water state to the scaled inverse of the canopy biomass regardless of the initial moisture state. Such a spatial distribution can be further wiped out because of the differential water stress. The aggregation of canopy-scale atmosphere-biosphere-hydrosphere interactions demonstrates non-linear relationship between soil moisture and evapotranspiration, influencing domain-averaged energy fluxes.

Spectral and spatial variability of undisturbed and disturbed grass under different view and illumination directions

NASA Astrophysics Data System (ADS)

Borel-Donohue, Christoph C.; Shivers, Sarah Wells; Conover, Damon

2017-05-01

It is well known that disturbed grass covered surfaces show variability with view and illumination conditions. A good example is a grass field in a soccer stadium that shows stripes indicating in which direction the grass was mowed. These spatial variations are due to a complex interplay of spectral characteristics of grass blades, density, their length and orientations. Viewing a grass surface from nadir or near horizontal directions results in observing different components. Views from a vertical direction show more variations due to reflections from the randomly oriented grass blades and their shadows. Views from near horizontal show a mixture of reflected and transmitted light from grass blades. An experiment was performed on a mowed grass surface which had paths of simulated heavy foot traffic laid down in different directions. High spatial resolution hyperspectral data cubes were taken by an imaging spectrometer covering the visible through near infrared over a period of time covering several hours. Ground truth grass reflectance spectra with a hand held spectrometer were obtained of undisturbed and disturbed areas. Close range images were taken of selected areas with a hand held camera which were then used to reconstruct the 3D geometry of the grass using structure-from-motion algorithms. Computer graphics rendering using raytracing of reconstructed and procedurally created grass surfaces were used to compute BRDF models. In this paper, we discuss differences between observed and simulated spectral and spatial variability. Based on the measurements and/or simulations, we derive simple spectral index methods to detect spatial disturbances and apply scattering models.

Detecting high spatial variability of ice shelf basal mass balance, Roi Baudouin Ice Shelf, Antarctica

NASA Astrophysics Data System (ADS)

Berger, Sophie; Drews, Reinhard; Helm, Veit; Sun, Sainan; Pattyn, Frank

2017-11-01

Ice shelves control the dynamic mass loss of ice sheets through buttressing and their integrity depends on the spatial variability of their basal mass balance (BMB), i.e. the difference between refreezing and melting. Here, we present an improved technique - based on satellite observations - to capture the small-scale variability in the BMB of ice shelves. As a case study, we apply the methodology to the Roi Baudouin Ice Shelf, Dronning Maud Land, East Antarctica, and derive its yearly averaged BMB at 10 m horizontal gridding. We use mass conservation in a Lagrangian framework based on high-resolution surface velocities, atmospheric-model surface mass balance and hydrostatic ice-thickness fields (derived from TanDEM-X surface elevation). Spatial derivatives are implemented using the total-variation differentiation, which preserves abrupt changes in flow velocities and their spatial gradients. Such changes may reflect a dynamic response to localized basal melting and should be included in the mass budget. Our BMB field exhibits much spatial detail and ranges from -14.7 to 8.6 m a-1 ice equivalent. Highest melt rates are found close to the grounding line where the pressure melting point is high, and the ice shelf slope is steep. The BMB field agrees well with on-site measurements from phase-sensitive radar, although independent radar profiling indicates unresolved spatial variations in firn density. We show that an elliptical surface depression (10 m deep and with an extent of 0.7 km × 1.3 km) lowers by 0.5 to 1.4 m a-1, which we tentatively attribute to a transient adaptation to hydrostatic equilibrium. We find evidence for elevated melting beneath ice shelf channels (with melting being concentrated on the channel's flanks). However, farther downstream from the grounding line, the majority of ice shelf channels advect passively (i.e. no melting nor refreezing) toward the ice shelf front. Although the absolute, satellite-based BMB values remain uncertain, we have high confidence in the spatial variability on sub-kilometre scales. This study highlights expected challenges for a full coupling between ice and ocean models.

First-order Probabilistic Analysis of the Effects of Heterogeneity on Pore-water Pressure in a Hillslope

NASA Astrophysics Data System (ADS)

Cai, J.; Yan, E.; Yeh, T. C. J.

2015-12-01

Pore-water pressure in a hillslope is a critical control of its stability. The main objective of this paper is to introduce a first-order moment analysis to investigate the pressure head variability within a hypothetical hillslope, induced by steady rainfall infiltration. This approach accounts for the uncertainties and spatial variation of the hydraulic conductivity, and is based on a first-order Taylor approximation of pressure perturbations calculated by a variably saturated, finite element flow model. Using this approach, the effects of variance (σ2lnKs) and spatial structure anisotropy (λh/λv) of natural logarithm of saturated hydraulic conductivity, and normalized vertical infiltration flux (q/ks) on the hillslope pore-water pressure are evaluated. We found that the responses of pressure head variability (σ2p) are quite different between unsaturated region and saturated region divided by the phreatic surface. Above the phreatic surface, a higher variability in pressure head is obtained from a higher σ2lnKs, a higher λh/λv and a smaller q/ks; while below the phreatic surface, a higher σ2lnKs, a lower λh/λv or a larger q/ks would lead to a higher variability in pressure head, and greater range of fluctuation of the phreatic surface within the hillslope. σ2lnKs has greatest impact on σ2p within the slope and λh/λv has smallest impact. All three variables have greater influence on maximum σ2p within the saturated region below the phreatic surface than that within the unsaturated region above the phreatic surface. The results obtained from this study are useful to understand the influence of hydraulic conductivity variations on slope seepage and stability under different slope conditions and material spatial distributions.

Surface NO2 fields derived from joint use of OMI and GOME-2A observations with EMEP model output

NASA Astrophysics Data System (ADS)

Schneider, Philipp; Svendby, Tove; Stebel, Kerstin

2016-04-01

Nitrogen dioxide (NO2) is one of the most prominent air pollutants. Emitted primarily by transport and industry, NO2 has a major impact on health and economy. In contrast to the very sparse network of air quality monitoring stations, satellite data of NO2 is ubiquitous and allows for quantifying the NO2 levels worldwide. However, one drawback of satellite-derived NO2 products is that they provide solely an estimate of the entire tropospheric column, whereas what is generally needed for air quality applications are the concentrations of NO2 near the surface. Here we derive surface NO2 concentration fields from OMI and GOME-2A tropospheric column products using the EMEP chemical transport model as auxiliary information. The model is used for providing information of the boundary layer contribution to the total tropospheric column. For preparation of deriving the surface product, a comprehensive model-based analysis of the spatial and temporal patterns of the NO2 surface-to-column ratio in Europe was carried out for the year 2011. The results from this analysis indicate that the spatial patterns of the surface-to-column ratio vary only slightly. While the highest ratio values can be found in some shipping lanes, the spatial variability of the ratio in some of the most polluted areas of Europe is not very high. Some but not all urban agglomeration shows high ratio values. Focusing on the temporal behavior, the analysis showed that the European-wide average ratio varies throughout the year. The surface-to-column ratio increases from January all the way through April when it reaches its maximum, then decreases relatively rapidly to average levels and then stays mostly constant throughout the summer. The minimum ratio is observed in December. The knowledge gained from analyzing the spatial and temporal patterns of the surface-to-column ratio was then used to produce surface NO2 products from the daily NO2 data for OMI and GOME-2A. This was carried out using two methods, namely using 1) hourly surface-to-column ratio at the time of the satellite overpass as well as 2) using annual average ratios thus eliminating the temporal variability and focusing solely on the spatial patterns. A validation of the resulting surface NO2 fields was performed using station observations of NO2 as provided by the Airbase database maintained by the European Environment Agency. First results indicate that the methodology is capable of producing surface concentration fields that reproduce the station-observed surface NO2 levels significantly better than the model surface fields as measured by the root mean squared error. The results also show that the spatial patterns of the surface-to-column ratio are more significant than its temporal variability. In addition to deriving satellite-based surface NO2, we further present initial results of a geostatistical methodology for downscaling satellite products of NO2 to spatial scales that are more relevant for applications in urban air quality. This is being carried out by applying area-to-point kriging techniques while using high-resolution (1-2 km spatial resolution) runs of a chemical transport model as a spatial proxy. In combination, these two techniques for deriving surface NO2 and spatially downscaling satellite-based NO2 fields have significant potential for improving satellite-based monitoring and mapping of regional and local-scale air pollution.

High-speed limnology: using advanced sensors to investigate spatial variability in biogeochemistry and hydrology.

PubMed

Crawford, John T; Loken, Luke C; Casson, Nora J; Smith, Colin; Stone, Amanda G; Winslow, Luke A

2015-01-06

Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h(-1)) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial-aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data.

High-speed limnology: Using advanced sensors to investigate spatial variability in biogeochemistry and hydrology

USGS Publications Warehouse

Crawford, John T.; Loken, Luke C.; Casson, Nora J.; Smith, Collin; Stone, Amanda G.; Winslow, Luke A.

2015-01-01

Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h–1) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial–aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data.

Using SMOS brightness temperature and derived surface-soil moisture to characterize surface conditions and validate land surface models.

NASA Astrophysics Data System (ADS)

Polcher, Jan; Barella-Ortiz, Anaïs; Piles, Maria; Gelati, Emiliano; de Rosnay, Patricia

2017-04-01

The SMOS satellite, operated by ESA, observes the surface in the L-band. On continental surface these observations are sensitive to moisture and in particular surface-soil moisture (SSM). In this presentation we will explore how the observations of this satellite can be exploited over the Iberian Peninsula by comparing its results with two land surface models : ORCHIDEE and HTESSEL. Measured and modelled brightness temperatures show a good agreement in their temporal evolution, but their spatial structures are not consistent. An empirical orthogonal function analysis of the brightness temperature's error identifies a dominant structure over the south-west of the Iberian Peninsula which evolves during the year and is maximum in autumn and winter. Hypotheses concerning forcing-induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for the weak spatial correlations. The analysis of spatial inconsistencies between modelled and measured TBs is important, as these can affect the estimation of geophysical variables and TB assimilation in operational models, as well as result in misleading validation studies. When comparing the surface-soil moisture of the models with the product derived operationally by ESA from SMOS observations similar results are found. The spatial correlation over the IP between SMOS and ORCHIDEE SSM estimates is poor (ρ 0.3). A single value decomposition (SVD) analysis of rainfall and SSM shows that the co-varying patterns of these variables are in reasonable agreement between both products. Moreover the first three SVD soil moisture patterns explain over 80% of the SSM variance simulated by the model while the explained fraction is only 52% of the remotely sensed values. These results suggest that the rainfall-driven soil moisture variability may not account for the poor spatial correlation between SMOS and ORCHIDEE products. Other reasons have to be sought to explain the poor agreement in spatial patterns between satellite derived and modelled SSM. This presentation will hopefully contribute to the discussion of how SMOS and other observations can be used to prepare, carry-out and exploit a field campaign over the Iberian Peninsula which aims at improving our understanding of semi-arid land surface processes.

Spatial variability of shortwave radiative fluxes in the context of snowmelt

NASA Astrophysics Data System (ADS)

Pinker, Rachel T.; Ma, Yingtao; Hinkelman, Laura; Lundquist, Jessica

2014-05-01

Snow-covered mountain ranges are a major source of water supply for run-off and groundwater recharge. Snowmelt supplies as much as 75% of surface water in basins of the western United States. Factors that affect the rate of snow melt include incoming shortwave and longwave radiation, surface albedo, snow emissivity, snow surface temperature, sensible and latent heat fluxes, ground heat flux, and energy transferred to the snowpack from deposited snow or rain. The net radiation generally makes up about 80% of the energy balance and is dominated by the shortwave radiation. Complex terrain poses a great challenge for obtaining the needed information on radiative fluxes from satellites due to elevation issues, spatially-variable cloud cover, rapidly changing surface conditions during snow fall and snow melt, lack of high quality ground truth for evaluation of the satellite based estimates, as well as scale issues between the ground observations and the satellite footprint. In this study we utilize observations of high spatial resolution (5-km) as available from the Moderate Resolution Imaging Spectro-radiometer (MODIS) to derive surface shortwave radiative fluxes in complex terrain, with attention to the impact of slopes on the amount of radiation received. The methodology developed has been applied to several water years (January to July during 2003, 2004, 2005 and 2009) over the western part of the United States, and the available information was used to derive metrics on spatial and temporal variability in the shortwave fluxes. It is planned to apply the findings from this study for testing improvements in Snow Water Equivalent (SWE) estimates.

Characteristics of the horizontal and vertical distributions of dimethyl sulfide throughout the Amundsen Sea Polynya.

PubMed

Kim, Intae; Hahm, Doshik; Park, Keyhong; Lee, Youngju; Choi, Jung-Ok; Zhang, Miming; Chen, Liqi; Kim, Hyun-Cheol; Lee, SangHoon

2017-04-15

We investigated horizontal and vertical distributions of DMS in the upper water column of the Amundsen Sea Polynya and Pine Island Polynya during the austral summer (January-February) of 2016 using a membrane inlet mass spectrometer (MIMS) onboard the Korean icebreaker R/V Araon. The surface water concentrations of DMS varied from <1 to 400nM. The highest DMS (up to 300nM) were observed in sea ice-polynya transition zones and near the Getz ice shelf, where both the first local ice melting and high plankton productivity were observed. In other regions, high DMS concentration was generally accompanied by higher chlorophyll and ΔO 2 /Ar. The large spatial variability of DMS and primary productivity in the surface water of the Amundsen Sea seems to be attributed to melting conditions of sea ice, relative dominance of Phaeocystis Antarctica as a DMS producer, and timing differences between bloom and subsequent DMS productions. The depth profiles of DMS and ΔO 2 /Ar were consistent with the horizontal surface data, showing noticeable spatial variability. However, despite the large spatial variability, in contrast to the previous results from 2009, DMS concentrations and ΔO 2 /Ar in the surface water were indistinct between the two major domains: the sea ice zone and polynya region. The discrepancy may be associated with inter-annual variations of phytoplankton assemblages superimposed on differences in sea-ice conditions, blooming period, and spatial coverage along the vast surface area of the Amundsen Sea. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial scales of light transmission through Antarctic pack ice: Surface flooding vs. floe-size distribution

NASA Astrophysics Data System (ADS)

Arndt, S.; Meiners, K.; Krumpen, T.; Ricker, R.; Nicolaus, M.

2016-12-01

Snow on sea ice plays a crucial role for interactions between the ocean and atmosphere within the climate system of polar regions. Antarctic sea ice is covered with snow during most of the year. The snow contributes substantially to the sea-ice mass budget as the heavy snow loads can depress the ice below water level causing flooding. Refreezing of the snow and seawater mixture results in snow-ice formation on the ice surface. The snow cover determines also the amount of light being reflected, absorbed, and transmitted into the upper ocean, determining the surface energy budget of ice-covered oceans. The amount of light penetrating through sea ice into the upper ocean is of critical importance for the timing and amount of bottom sea-ice melt, biogeochemical processes and under-ice ecosystems. Here, we present results of several recent observations in the Weddell Sea measuring solar radiation under Antarctic sea ice with instrumented Remotely Operated Vehicles (ROV). The combination of under-ice optical measurements with simultaneous characterization of surface properties, such as sea-ice thickness and snow depth, allows the identification of key processes controlling the spatial distribution of the under-ice light. Thus, our results show how the distinction between flooded and non-flooded sea-ice regimes dominates the spatial scales of under-ice light variability for areas smaller than 100-by-100m. In contrast, the variability on larger scales seems to be controlled by the floe-size distribution and the associated lateral incidence of light. These results are related to recent studies on the spatial variability of Arctic under-ice light fields focusing on the distinctly differing dominant surface properties between the northern (e.g. summer melt ponds) and southern (e.g. year-round snow cover, surface flooding) hemisphere sea-ice cover.

Comparing daily temperature averaging methods: the role of surface and atmosphere variables in determining spatial and seasonal variability

NASA Astrophysics Data System (ADS)

Bernhardt, Jase; Carleton, Andrew M.

2018-05-01

The two main methods for determining the average daily near-surface air temperature, twice-daily averaging (i.e., [Tmax+Tmin]/2) and hourly averaging (i.e., the average of 24 hourly temperature measurements), typically show differences associated with the asymmetry of the daily temperature curve. To quantify the relative influence of several land surface and atmosphere variables on the two temperature averaging methods, we correlate data for 215 weather stations across the Contiguous United States (CONUS) for the period 1981-2010 with the differences between the two temperature-averaging methods. The variables are land use-land cover (LULC) type, soil moisture, snow cover, cloud cover, atmospheric moisture (i.e., specific humidity, dew point temperature), and precipitation. Multiple linear regression models explain the spatial and monthly variations in the difference between the two temperature-averaging methods. We find statistically significant correlations between both the land surface and atmosphere variables studied with the difference between temperature-averaging methods, especially for the extreme (i.e., summer, winter) seasons (adjusted R2 > 0.50). Models considering stations with certain LULC types, particularly forest and developed land, have adjusted R2 values > 0.70, indicating that both surface and atmosphere variables control the daily temperature curve and its asymmetry. This study improves our understanding of the role of surface and near-surface conditions in modifying thermal climates of the CONUS for a wide range of environments, and their likely importance as anthropogenic forcings—notably LULC changes and greenhouse gas emissions—continues.

Spatial Variability of Soil-Water Storage in the Southern Sierra Critical Zone Observatory: Measurement and Prediction

NASA Astrophysics Data System (ADS)

Oroza, C.; Bales, R. C.; Zheng, Z.; Glaser, S. D.

2017-12-01

Predicting the spatial distribution of soil moisture in mountain environments is confounded by multiple factors, including complex topography, spatial variably of soil texture, sub-surface flow paths, and snow-soil interactions. While remote-sensing tools such as passive-microwave monitoring can measure spatial variability of soil moisture, they only capture near-surface soil layers. Large-scale sensor networks are increasingly providing soil-moisture measurements at high temporal resolution across a broader range of depths than are accessible from remote sensing. It may be possible to combine these in-situ measurements with high-resolution LIDAR topography and canopy cover to estimate the spatial distribution of soil moisture at high spatial resolution at multiple depths. We study the feasibility of this approach using six years (2009-2014) of daily volumetric water content measurements at 10-, 30-, and 60-cm depths from the Southern Sierra Critical Zone Observatory. A non-parametric, multivariate regression algorithm, Random Forest, was used to predict the spatial distribution of depth-integrated soil-water storage, based on the in-situ measurements and a combination of node attributes (topographic wetness, northness, elevation, soil texture, and location with respect to canopy cover). We observe predictable patterns of predictor accuracy and independent variable ranking during the six-year study period. Predictor accuracy is highest during the snow-cover and early recession periods but declines during the dry period. Soil texture has consistently high feature importance. Other landscape attributes exhibit seasonal trends: northness peaks during the wet-up period, and elevation and topographic-wetness index peak during the recession and dry period, respectively.

On the temporal and spatial variability of near-surface soil moisture for the identification of representative in situ soil moisture monitoring stations

USDA-ARS?s Scientific Manuscript database

The high spatio-temporal variability of soil moisture complicates the validation of remotely sensed soil moisture products using in-situ monitoring stations. Therefore, a standard methodology for selecting the most repre- sentative stations for the purpose of validating satellites and land surface ...

Verification of land-atmosphere coupling in forecast models, reanalyses and land surface models using flux site observations.

PubMed

Dirmeyer, Paul A; Chen, Liang; Wu, Jiexia; Shin, Chul-Su; Huang, Bohua; Cash, Benjamin A; Bosilovich, Michael G; Mahanama, Sarith; Koster, Randal D; Santanello, Joseph A; Ek, Michael B; Balsamo, Gianpaolo; Dutra, Emanuel; Lawrence, D M

2018-02-01

We confront four model systems in three configurations (LSM, LSM+GCM, and reanalysis) with global flux tower observations to validate states, surface fluxes, and coupling indices between land and atmosphere. Models clearly under-represent the feedback of surface fluxes on boundary layer properties (the atmospheric leg of land-atmosphere coupling), and may over-represent the connection between soil moisture and surface fluxes (the terrestrial leg). Models generally under-represent spatial and temporal variability relative to observations, which is at least partially an artifact of the differences in spatial scale between model grid boxes and flux tower footprints. All models bias high in near-surface humidity and downward shortwave radiation, struggle to represent precipitation accurately, and show serious problems in reproducing surface albedos. These errors create challenges for models to partition surface energy properly and errors are traceable through the surface energy and water cycles. The spatial distribution of the amplitude and phase of annual cycles (first harmonic) are generally well reproduced, but the biases in means tend to reflect in these amplitudes. Interannual variability is also a challenge for models to reproduce. Our analysis illuminates targets for coupled land-atmosphere model development, as well as the value of long-term globally-distributed observational monitoring.

Advances in satellite remote sensing of environmental variables for epidemiological applications.

PubMed

Goetz, S J; Prince, S D; Small, J

2000-01-01

Earth-observing satellites have provided an unprecedented view of the land surface but have been exploited relatively little for the measurement of environmental variables of particular relevance to epidemiology. Recent advances in techniques to recover continuous fields of air temperature, humidity, and vapour pressure deficit from remotely sensed observations have significant potential for disease vector monitoring and related epidemiological applications. We report on the development of techniques to map environmental variables with relevance to the prediction of the relative abundance of disease vectors and intermediate hosts. Improvements to current methods of obtaining information on vegetation properties, canopy and surface temperature and soil moisture over large areas are also discussed. Algorithms used to measure these variables incorporate visible, near-infrared and thermal infrared radiation observations derived from time series of satellite-based sensors, focused here primarily but not exclusively on the Advanced Very High Resolution Radiometer (AVHRR) instruments. The variables compare favourably with surface measurements over a broad array of conditions at several study sites, and maps of retrieved variables captured patterns of spatial variability comparable to, and locally more accurate than, spatially interpolated meteorological observations. Application of multi-temporal maps of these variables are discussed in relation to current epidemiological research on the distribution and abundance of some common disease vectors.

[Spatial variation characteristics of surface soil water content, bulk density and saturated hydraulic conductivity on Karst slopes].

PubMed

Zhang, Chuan; Chen, Hong-Song; Zhang, Wei; Nie, Yun-Peng; Ye, Ying-Ying; Wang, Ke-Lin

2014-06-01

Surface soil water-physical properties play a decisive role in the dynamics of deep soil water. Knowledge of their spatial variation is helpful in understanding the processes of rainfall infiltration and runoff generation, which will contribute to the reasonable utilization of soil water resources in mountainous areas. Based on a grid sampling scheme (10 m x 10 m) and geostatistical methods, this paper aimed to study the spatial variability of surface (0-10 cm) soil water content, soil bulk density and saturated hydraulic conductivity on a typical shrub slope (90 m x 120 m, projected length) in Karst area of northwest Guangxi, southwest China. The results showed that the surface soil water content, bulk density and saturated hydraulic conductivity had different spatial dependence and spatial structure. Sample variogram of the soil water content was fitted well by Gaussian models with the nugget effect, while soil bulk density and saturated hydraulic conductivity were fitted well by exponential models with the nugget effect. Variability of soil water content showed strong spatial dependence, while the soil bulk density and saturated hydraulic conductivity showed moderate spatial dependence. The spatial ranges of the soil water content and saturated hydraulic conductivity were small, while that of the soil bulk density was much bigger. In general, the soil water content increased with the increase of altitude while it was opposite for the soil bulk densi- ty. However, the soil saturated hydraulic conductivity had a random distribution of large amounts of small patches, showing high spatial heterogeneity. Soil water content negatively (P < 0.01) correlated with the bulk density and saturated hydraulic conductivity, while there was no significant correlation between the soil bulk density and saturated hydraulic conductivity.

Surface Variability of Short-wavelength Radiation and Temperature on Exoplanets around M Dwarfs

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

Zhang, Xin; Tian, Feng; Wang, Yuwei

2017-03-10

It is a common practice to use 3D General Circulation Models (GCM) with spatial resolution of a few hundred kilometers to simulate the climate of Earth-like exoplanets. The enhanced albedo effect of clouds is especially important for exoplanets in the habitable zones around M dwarfs that likely have fixed substellar regions and substantial cloud coverage. Here, we carry out mesoscale model simulations with 3 km spatial resolution driven by the initial and boundary conditions in a 3D GCM and find that it could significantly underestimate the spatial variability of both the incident short-wavelength radiation and the temperature at planet surface.more » Our findings suggest that mesoscale models with cloud-resolving capability be considered for future studies of exoplanet climate.« less

Sea Surface Salinity Variability from Simulations and Observations: Preparing for Aquarius

NASA Technical Reports Server (NTRS)

Jacob, S. Daniel; LeVine, David M.

2010-01-01

Oceanic fresh water transport has been shown to play an important role in the global hydrological cycle. Sea surface salinity (SSS) is representative of the surface fresh water fluxes and the upcoming Aquarius mission scheduled to be launched in December 2010 will provide excellent spatial and temporal SSS coverage to better estimate the net exchange. In most ocean general circulation models, SSS is relaxed to climatology to prevent model drift. While SST remains a well observed variable, relaxing to SST reduces the range of SSS variability in the simulations (Fig.1). The main objective of the present study is to simulate surface tracers using a primitive equation ocean model for multiple forcing data sets to identify and establish a baseline SSS variability. The simulated variability scales are compared to those from near-surface argo salinity measurements.

An advanced stochastic weather generator for simulating 2-D high-resolution climate variables

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2017-07-01

A new stochastic weather generator, Advanced WEather GENerator for a two-dimensional grid (AWE-GEN-2d) is presented. The model combines physical and stochastic approaches to simulate key meteorological variables at high spatial and temporal resolution: 2 km × 2 km and 5 min for precipitation and cloud cover and 100 m × 100 m and 1 h for near-surface air temperature, solar radiation, vapor pressure, atmospheric pressure, and near-surface wind. The model requires spatially distributed data for the calibration process, which can nowadays be obtained by remote sensing devices (weather radar and satellites), reanalysis data sets and ground stations. AWE-GEN-2d is parsimonious in terms of computational demand and therefore is particularly suitable for studies where exploring internal climatic variability at multiple spatial and temporal scales is fundamental. Applications of the model include models of environmental systems, such as hydrological and geomorphological models, where high-resolution spatial and temporal meteorological forcing is crucial. The weather generator was calibrated and validated for the Engelberg region, an area with complex topography in the Swiss Alps. Model test shows that the climate variables are generated by AWE-GEN-2d with a level of accuracy that is sufficient for many practical applications.

Groundwater-fed irrigation impacts spatially distributed temporal scaling behavior of the natural system: a spatio-temporal framework for understanding water management impacts

NASA Astrophysics Data System (ADS)

Condon, Laura E.; Maxwell, Reed M.

2014-03-01

Regional scale water management analysis increasingly relies on integrated modeling tools. Much recent work has focused on groundwater-surface water interactions and feedbacks. However, to our knowledge, no study has explicitly considered impacts of management operations on the temporal dynamics of the natural system. Here, we simulate twenty years of hourly moisture dependent, groundwater-fed irrigation using a three-dimensional, fully integrated, hydrologic model (ParFlow-CLM). Results highlight interconnections between irrigation demand, groundwater oscillation frequency and latent heat flux variability not previously demonstrated. Additionally, the three-dimensional model used allows for novel consideration of spatial patterns in temporal dynamics. Latent heat flux and water table depth both display spatial organization in temporal scaling, an important finding given the spatial homogeneity and weak scaling observed in atmospheric forcings. Pumping and irrigation amplify high frequency (sub-annual) variability while attenuating low frequency (inter-annual) variability. Irrigation also intensifies scaling within irrigated areas, essentially increasing temporal memory in both the surface and the subsurface. These findings demonstrate management impacts that extend beyond traditional water balance considerations to the fundamental behavior of the system itself. This is an important step to better understanding groundwater’s role as a buffer for natural variability and the impact that water management has on this capacity.

Spatial variability of organic matter molecular composition and elemental geochemistry in surface sediments of a small boreal Swedish lake

NASA Astrophysics Data System (ADS)

Tolu, Julie; Rydberg, Johan; Meyer-Jacob, Carsten; Gerber, Lorenz; Bindler, Richard

2017-04-01

The composition of sediment organic matter (OM) exerts a strong control on biogeochemical processes in lakes, such as those involved in the fate of carbon, nutrients and trace metals. While between-lake spatial variability of OM quality is increasingly investigated, we explored in this study how the molecular composition of sediment OM varies spatially within a single lake and related this variability to physical parameters and elemental geochemistry. Surface sediment samples (0-10 cm) from 42 locations in Härsvatten - a small boreal forest lake with a complex basin morphometry - were analyzed for OM molecular composition using pyrolysis gas chromatography mass spectrometry for the contents of 23 major and trace elements and biogenic silica. We identified 162 organic compounds belonging to different biochemical classes of OM (e.g., carbohydrates, lignin and lipids). Close relationships were found between the spatial patterns of sediment OM molecular composition and elemental geochemistry. Differences in the source types of OM (i.e., terrestrial, aquatic plant and algal) were linked to the individual basin morphometries and chemical status of the lake. The variability in OM molecular composition was further driven by the degradation status of these different source pools, which appeared to be related to sedimentary physicochemical parameters (e.g., redox conditions) and to the molecular structure of the organic compounds. Given the high spatial variation in OM molecular composition within Härsvatten and its close relationship with elemental geochemistry, the potential for large spatial variability across lakes should be considered when studying biogeochemical processes involved in the cycling of carbon, nutrients and trace elements or when assessing lake budgets.

Quantifying Spatially Integrated Floodplain and Wetland Systems for the Conterminous US

EPA Science Inventory

Wetlands interact with other waters across a variable connectivity continuum, from permanent to transient, from fast to slow, and from primarily surface water to exclusively groundwater flows. Floodplain wetlands typically experience fast and frequent surface and near-surface gro...

Acoustic Determination of Near-Surface Soil Properties

DTIC Science & Technology

2008-12-01

requiring geostatistical analysis, while nearby others are spatially independent. In studies involving many different soil properties and chemistry ...Am 116(6), p. 3354-3369. Kravchenko, N., C.W. Boast, D.G. Bullock, 1991. Fractal analysis of soil spatial variability. Agronomy Journal 91

Spatial correlation of shear-wave velocity within San Francisco Bay Sediments

USGS Publications Warehouse

Thompson, E.M.; Baise, L.G.; Kayen, R.E.

2006-01-01

Sediment properties are spatially variable at all scales, and this variability at smaller scales influences high frequency ground motions. We show that surface shear-wave velocity is highly correlated within San Francisco Bay Area sediments using shear-wave velocity measurements from 210 seismic cone penetration tests. We use this correlation to estimate the surface sediment velocity structure using geostatistics. We find that the variance of the estimated shear-wave velocity is reduced using ordinary kriging, and that including this velocity structure in 2D ground motion simulations of a moderate sized earthquake improves the accuracy of the synthetics. Copyright ASCE 2006.

Representation of vegetation by continental data sets derived from NOAA-AVHRR data

NASA Technical Reports Server (NTRS)

Justice, C. O.; Townshend, J. R. G.; Kalb, V. L.

1991-01-01

Images of the normalized difference vegetation index (NDVI) are examined with specific attention given to the effect of spatial scales on the understanding of surface phenomena. A scale variance analysis is conducted on NDVI annual and seasonal images of Africa taken from 1987 NOAA-AVHRR data at spatial scales ranging from 8-512 km. The scales at which spatial variation takes place are determined and the relative magnitude of the variations are considered. Substantial differences are demonstrated, notably an increase in spatial variation with coarsening spatial resolution. Different responses in scale variance as a function of spatial resolution are noted in an analysis of maximum value composites for February and September; the difference is most marked in areas with very seasonal vegetation. The spatial variation at different scales is attributed to different factors, and methods involving the averaging of areas of transition and surface heterogeneity can oversimplify surface conditions. The spatial characteristics and the temporal variability of areas should be considered to accurately apply satellite data to global models.

Spatial structure and scaling of macropores in hydrological process at small catchment scale

NASA Astrophysics Data System (ADS)

Silasari, Rasmiaditya; Broer, Martine; Blöschl, Günter

2013-04-01

During rainfall events, the formation of overland flow can occur under the circumstances of saturation excess and/or infiltration excess. These conditions are affected by the soil moisture state which represents the soil water content in micropores and macropores. Macropores act as pathway for the preferential flows and have been widely studied locally. However, very little is known about their spatial structure and conductivity of macropores and other flow characteristic at the catchment scale. This study will analyze these characteristics to better understand its importance in hydrological processes. The research will be conducted in Petzenkirchen Hydrological Open Air Laboratory (HOAL), a 64 ha catchment located 100 km west of Vienna. The land use is divided between arable land (87%), pasture (5%), forest (6%) and paved surfaces (2%). Video cameras will be installed on an agricultural field to monitor the overland flow pattern during rainfall events. A wireless soil moisture network is also installed within the monitored area. These field data will be combined to analyze the soil moisture state and the responding surface runoff occurrence. The variability of the macropores spatial structure of the observed area (field scale) then will be assessed based on the topography and soil data. Soil characteristics will be supported with laboratory experiments on soil matrix flow to obtain proper definitions of the spatial structure of macropores and its variability. A coupled physically based distributed model of surface and subsurface flow will be used to simulate the variability of macropores spatial structure and its effect on the flow behaviour. This model will be validated by simulating the observed rainfall events. Upscaling from field scale to catchment scale will be done to understand the effect of macropores variability on larger scales by applying spatial stochastic methods. The first phase in this study is the installation and monitoring configuration of video cameras and soil moisture monitoring equipment to obtain the initial data of overland flow occurrence and soil moisture state relationships.

Water availability as a driver of spatial and temporal variability in vegetation in the La Mancha plain (Spain): Implications for the land-surface energy, water and carbon budget

NASA Astrophysics Data System (ADS)

Los, Sietse

2017-04-01

Vegetation is water limited in large areas of Spain and therefore a close link exists between vegetation greenness observed from satellite and moisture availability. Here we exploit this link to infer spatial and temporal variability in moisture from MODIS NDVI data and thermal data. Discrepancies in the precipitation - vegetation relationship indicate areas with an alternative supply of water (i.e. not rainfall), this can be natural where moisture is supplied by upwelling groundwater, or can be artificial where crops are irrigated. As a result spatial and temporal variability in vegetation in the La Mancha Plain appears closely linked to topography, geology, rainfall and land use. Crop land shows large variability in year-to-year vegetation greenness; for some areas this variability is linked to variability in rainfall but in other cases this variability is linked to irrigation. The differences in irrigation treatment within one plant functional type, in this case crops, will lead to errors in land surface models when ignored. The magnitude of these effects on the energy, carbon and water balance are assessed at the scale of 250 m to 200 km. Estimating the water balance correctly is of particular important since in some areas in Spain more water is used for irrigation than is supplemented by rainfall.

Variations in debris distribution and thickness on Himalayan debris-covered glaciers

NASA Astrophysics Data System (ADS)

Gibson, Morgan; Rowan, Ann; Irvine-Fynn, Tristram; Quincey, Duncan; Glasser, Neil

2016-04-01

Many Himalayan glaciers are characterised by extensive supraglacial debris coverage; in Nepal 33% of glaciers exhibit a continuous layer of debris covering their ablation areas. The presence of such a debris layer modulates a glacier's response to climatic change. However, the impact of this modulation is poorly constrained due to inadequate quantification of the impact of supraglacial debris on glacier surface energy balance. Few data exist to describe spatial and temporal variations in parameters such as debris thickness, albedo and surface roughness in energy balance calculations. Consequently, improved understanding of how debris affects Himalayan glacier ablation requires the assessment of surface energy balance model sensitivity to spatial and temporal variability in these parameters. Measurements of debris thickness, surface temperature, reflectance and roughness were collected across Khumbu Glacier during the pre- and post-monsoon seasons of 2014 and 2015. The extent of the spatial variation in each of these parameters are currently being incorporated into a point-based glacier surface energy balance model (CMB-RES, Collier et al., 2014, The Cryosphere), applied on a pixel-by-pixel basis to the glacier surface, to ascertain the sensitivity of glacier surface energy balance and ablation values to these debris parameters. A time series of debris thickness maps have been produced for Khumbu Glacier over a 15-year period (2000-2015) using Mihalcea et al.'s (2008, Cold Reg. Sci. Technol.) method, which utilised multi-temporal ASTER thermal imagery and our in situ debris surface temperature and thickness measurements. Change detection between these maps allowed the identification of variations in debris thickness that could be compared to discrete measurements, glacier surface velocity and morphology of the debris-covered area. Debris thickness was found to vary spatially between 0.1 and 4 metres within each debris thickness map, and temporally on the order of 1 to 2 m. Temporal variability was a result of differential surface lowering, spatial variability in glacier surface velocities and intermittent input of debris to the glacier surface through mass movement. Most debris thickening is seen in initially thin areas of debris (< 0.4 m) or within ~1 km of the glacier terminus. Surface energy balance modelling is currently underway to determine the effect of these variations in debris thickness, and other parameters mentioned previously. Future work will be to calculate debris transport flux on the surface of Khumbu Glacier using the time series of debris thickness maps. Debris flux and refined energy balance calculations will then be incorporated into a 3-D ice flow model to determine the response of Khumbu Glacier to debris transport and climatic changes.

Water balance model for Kings Creek

NASA Technical Reports Server (NTRS)

Wood, Eric F.

1990-01-01

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

A Skilful Marine Sclerochronological Network Based Reconstruction of North Atlantic Subpolar Gyre Dynamics

NASA Astrophysics Data System (ADS)

Reynolds, D.; Hall, I. R.; Slater, S. M.; Scourse, J. D.; Wanamaker, A. D.; Halloran, P. R.; Garry, F. K.

2017-12-01

Spatial network analyses of precisely dated, and annually resolved, tree-ring proxy records have facilitated robust reconstructions of past atmospheric climate variability and the associated mechanisms and forcings that drive it. In contrast, a lack of similarly dated marine archives has constrained the use of such techniques in the marine realm, despite the potential for developing a more robust understanding of the role basin scale ocean dynamics play in the global climate system. Here we show that a spatial network of marine molluscan sclerochronological oxygen isotope (δ18Oshell) series spanning the North Atlantic region provides a skilful reconstruction of basin scale North Atlantic sea surface temperatures (SSTs). Our analyses demonstrate that the composite marine series (referred to as δ18Oproxy_PC1) is significantly sensitive to inter-annual variability in North Atlantic SSTs (R=-0.61 P<0.01) and surface air temperatures (SATs; R=-0.67, P<0.01) over the 20th century. Subpolar gyre (SPG) SSTs dominates variability in the δ18Oproxy_PC1 series at sub-centennial frequencies (R=-0.51, P<0.01). Comparison of the δ18Oproxy_PC1 series against variability in the strength of the European Slope Current and maximum North Atlantic meridional overturning circulation derived from numeric climate models (CMIP5), indicates that variability in the SPG region, associated with the strength of the surface currents of the North Atlantic, are playing a significant role in shaping the multi-decadal scale SST variability over the industrial era. These analyses demonstrate that spatial networks developed from sclerochronological archives can provide powerful baseline archives of past ocean variability that can facilitate the development of a quantitative understanding for the role the oceans play in the global climate systems and constraining uncertainties in numeric climate models.

Spatial Structure of a Braided River: Metric Resolution Hydrodynamic Modeling Reveals What SWOT Might See

NASA Astrophysics Data System (ADS)

Schubert, J.; Sanders, B. F.; Andreadis, K.

2013-12-01

The Surface Water and Ocean Topography (SWOT) mission, currently under study by NASA (National Aeronautics and Space Administration) and CNES (Centre National d'Etudes Spatiales), is designed to provide global spatial measurements of surface water properties at resolutions better than 10 m and with centimetric accuracy. The data produced by SWOT will include irregularly spaced point clouds of the water surface height, with point spacings from roughly 2-50 m depending on a point's location within SWOT's swath. This could offer unprecedented insight into the spatial structure of rivers. Features that may be resolved include backwater profiles behind dams, drawdown profiles, uniform flow sections, critical flow sections, and even riffle-pool flow structures. In the event that SWOT scans a river during a major flood, it becomes possible to delineate the limits of the flood as well as the spatial structure of the water surface elevation, yielding insight into the dynamic interaction of channels and flood plains. The Platte River in Nebraska, USA, is a braided river with a width and slope of approximately 100 m and 100 cm/km, respectively. A 1 m resolution Digital Terrain Model (DTM) of the river basin, based on airborne lidar collected during low-flow conditions, was used to parameterize a two-dimensional, variable resolution, unstructured grid, hydrodynamic model that uses 3 m resolution triangles in low flow channels and 10 m resolution triangles in the floodplain. Use of a fine resolution mesh guarantees that local variability in topography is resolved, and after applying the hydrodynamic model, the effects of topographic variability are expressed as variability in the water surface height, depth-averaged velocity and flow depth. Flow is modeled over a reach length of 10 km for multi-day durations to capture both frequent (diurnal variations associated with regulated flow) and infrequent (extreme flooding) flow phenomena. Model outputs reveal a number of interesting features, including a high degree of variability in the water depth and velocity and lesser variability in the free-surface profile and river discharge. Hydraulic control sections are also revealed, and shown to depend on flow stage. Reach-averaging of model output is applied to study the macro-scale balance of forces in this system, and the scales at which such a force balance is appropriate. We find that the reach-average slope exhibits a declining reach-length dependence with increasing reach length, up to reach lengths of 1 km. Hence, 1 km appears to be the minimum appropriate length for reach-averaging, and at this scale, a diffusive-wave momentum balance is a reasonable approximation suitable for emerging models of discharge estimation that rely only on SWOT-observable river properties (width, height, slope, etc.).

Tracking fine-scale seasonal evolution of surface water extent in Central Alaska and the Canadian Shield

NASA Astrophysics Data System (ADS)

Cooley, S. W.; Smith, L. C.; Pitcher, L. H.; Pavelsky, T.; Topp, S.

2017-12-01

Quantifying spatial and temporal variability in surface water storage at high latitudes is critical for assessing environmental sensitivity to climate change. Traditionally the tradeoff between high spatial and high temporal resolution space-borne optical imagery has limited the ability to track fine-scale changes in surface water extent. However, the recent launch of hundreds of earth-imaging CubeSats by commercial satellite companies such as Planet opens up new possibilities for monitoring surface water from space. In this study we present a comparison of seasonal evolution of surface water extent in two study areas with differing geologic, hydrologic and permafrost regimes, namely, the Yukon Flats in Central Alaska and the Canadian Shield north of Yellowknife, N.W.T. Using near-daily 3m Planet CubeSat imagery, we track individual lake surface area from break-up to freeze-up during summer 2017 and quantify the spatial and temporal variability in inundation extent. We validate our water delineation method and inundation extent time series using WorldView imagery, coincident in situ lake shoreline mapping and pressure transducer data for 19 lakes in the Northwest Territories and Alaska collected during the NASA Arctic Boreal Vulnerability Experiment (ABoVE) 2017 field campaign. The results of this analysis demonstrate the value of CubeSat imagery for dynamic surface water research particularly at high latitudes and illuminate fine-scale drivers of cold regions surface water extent.

A Study on the Effects of Spatial Scale on Snow Process in Hyper-Resolution Hydrological Modelling over Mountainous Areas

NASA Astrophysics Data System (ADS)

Garousi Nejad, I.; He, S.; Tang, Q.; Ogden, F. L.; Steinke, R. C.; Frazier, N.; Tarboton, D. G.; Ohara, N.; Lin, H.

2017-12-01

Spatial scale is one of the main considerations in hydrological modeling of snowmelt in mountainous areas. The size of model elements controls the degree to which variability can be explicitly represented versus what needs to be parameterized using effective properties such as averages or other subgrid variability parameterizations that may degrade the quality of model simulations. For snowmelt modeling terrain parameters such as slope, aspect, vegetation and elevation play an important role in the timing and quantity of snowmelt that serves as an input to hydrologic runoff generation processes. In general, higher resolution enhances the accuracy of the simulation since fine meshes represent and preserve the spatial variability of atmospheric and surface characteristics better than coarse resolution. However, this increases computational cost and there may be a scale beyond which the model response does not improve due to diminishing sensitivity to variability and irreducible uncertainty associated with the spatial interpolation of inputs. This paper examines the influence of spatial resolution on the snowmelt process using simulations of and data from the Animas River watershed, an alpine mountainous area in Colorado, USA, using an unstructured distributed physically based hydrological model developed for a parallel computing environment, ADHydro. Five spatial resolutions (30 m, 100 m, 250 m, 500 m, and 1 km) were used to investigate the variations in hydrologic response. This study demonstrated the importance of choosing the appropriate spatial scale in the implementation of ADHydro to obtain a balance between representing spatial variability and the computational cost. According to the results, variation in the input variables and parameters due to using different spatial resolution resulted in changes in the obtained hydrological variables, especially snowmelt, both at the basin-scale and distributed across the model mesh.

Spatial distribution visualization of PWM continuous variable-rate spray

USDA-ARS?s Scientific Manuscript database

Chemical application is a dynamic spatial distribution process, during which spray liquid covers the targets with certain thickness and uniformity. Therefore, it is important to study the 2-D and 3-D (dimensional) spray distribution to evaluate spraying quality. The curve-surface generation methods ...

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

Tang, Q; Xie, S

This report describes the Atmospheric Radiation Measurement (ARM) Best Estimate (ARMBE) 2-dimensional (2D) gridded surface data (ARMBE2DGRID) value-added product. Spatial variability is critically important to many scientific studies, especially those that involve processes of great spatial variations at high temporal frequency (e.g., precipitation, clouds, radiation, etc.). High-density ARM sites deployed at the Southern Great Plains (SGP) allow us to observe the spatial patterns of variables of scientific interests. The upcoming megasite at SGP with its enhanced spatial density will facilitate the studies at even finer scales. Currently, however, data are reported only at individual site locations at different time resolutionsmore » for different datastreams. It is difficult for users to locate all the data they need and requires extra effort to synchronize the data. To address these problems, the ARMBE2DGRID value-added product merges key surface measurements at the ARM SGP sites and interpolates the data to a regular 2D grid to facilitate the data application.« less

Empirical modeling of spatial and temporal variation in warm season nocturnal air temperatures in two North Idaho mountain ranges, USA

Treesearch

Zachery A. Holden; Michael A. Crimmins; Samuel A. Cushman; Jeremy S. Littell

2010-01-01

Accurate, fine spatial resolution predictions of surface air temperatures are critical for understanding many hydrologic and ecological processes. This study examines the spatial and temporal variability in nocturnal air temperatures across a mountainous region of Northern Idaho. Principal components analysis (PCA) was applied to a network of 70 Hobo temperature...

Characterization of metal adsorption variability in a sand and gravel aquifer, Cape Cod, Massachusetts, U.S.A

USGS Publications Warehouse

Fuller, C.C.; Davis, J.A.; Coston, J.A.; Dixon, E.

1996-01-01

Several geochemical properties of an aquifer sediment that control metal-ion adsorption were investigated to determine their potential use as indicators of the spatial variability of metal adsorption. Over the length of a 4.5-m-long core from a sand and gravel aquifer, lead (Pb2+) and zinc (Zn2+) adsorption at constant chemical conditions (pH 5.3) varied by a factor of 2 and 4, respectively. Pb2+ and Zn2+ were adsorbed primarily by Fe- and Al-oxide coatings on quartz-grain surfaces. Per unit surface area, both Pb2+ and Zn2+ adsorption were significantly correlated with the amount of Fe and Al that dissolved from the aquifer material in a partial chemical extraction. The variability in conditional binding constants for Pb2+ and Zn2+ adsorption (log KADS) derived from a simple non-electrostatic surface complexation model were also predicted by extracted Fe and Al normalized to surface area. Because the abundance of Fe- and Al-oxide coatings that dominate adsorption does not vary inversely with grain size by a simple linear relationship, only a weak, negative correlation was found between the spatial variability of Pb2+ adsorption and grain size in this aquifer. The correlation between Zn2+ adsorption and grain size was not significant. Partial chemical extractions combined with surface-area measurements have potential use for estimating metal adsorption variability in other sand and gravel aquifers of negligible carbonate and organic carbon content.

Spatial variability of harmful algal blooms in Milford Lake, Kansas, July and August 2015

USGS Publications Warehouse

Foster, Guy M.; Graham, Jennifer L.; Stiles, Tom C.; Boyer, Marvin G.; King, Lindsey R.; Loftin, Keith A.

2017-01-09

Cyanobacterial harmful algal blooms (CyanoHABs) tend to be spatially variable vertically in the water column and horizontally across the lake surface because of in-lake and weather-driven processes and can vary by orders of magnitude in concentration across relatively short distances (meters or less). Extreme spatial variability in cyanobacteria and associated compounds poses unique challenges to collecting representative samples for scientific study and public-health protection. The objective of this study was to assess the spatial variability of cyanobacteria and microcystin in Milford Lake, Kansas, using data collected on July 27 and August 31, 2015. Spatially dense near-surface data were collected by the U.S. Geological Survey, nearshore data were collected by the Kansas Department of Health and Environment, and open-water data were collected by U.S. Army Corps of Engineers. CyanoHABs are known to be spatially variable, but that variability is rarely quantified. A better understanding of the spatial variability of cyanobacteria and microcystin will inform sampling and management strategies for Milford Lake and for other lakes with CyanoHAB issues throughout the Nation.The CyanoHABs in Milford Lake during July and August 2015 displayed the extreme spatial variability characteristic of cyanobacterial blooms. The phytoplankton community was almost exclusively cyanobacteria (greater than 90 percent) during July and August. Cyanobacteria (measured directly by cell counts and indirectly by regression-estimated chlorophyll) and microcystin (measured directly by enzyme-linked immunosorbent assay [ELISA] and indirectly by regression estimates) concentrations varied by orders of magnitude throughout the lake. During July and August 2015, cyanobacteria and microcystin concentrations decreased in the downlake (towards the outlet) direction.Nearshore and open-water surface grabs were collected and analyzed for microcystin as part of this study. Samples were collected in the uplake (Zone C), midlake (Zone B), and downlake (Zone A) parts of the lake. Overall, no consistent pattern was indicated as to which sample location (nearshore or open water) had the highest microcystin concentrations. In July, the maximum microcystin concentration observed in each zone was detected at a nearshore site, and in August, maximum microcystin concentrations in each zone were detected at an open-water site.The Kansas Department of Health and Environment uses two guidance levels (a watch and a warning level) to issue recreational public-health advisories for CyanoHABs in Kansas lakes. The levels are based on concentrations of microcystin and numbers of cyanobacteria. In July and August, discrete water-quality samples were predominantly indicative of warning status in Zone C, watch status in Zone B, and no advisories in Zone A. Regression-estimated microcystin concentrations, which provided more thorough coverage of Milford Lake (n=683–720) than discrete samples (n=21–24), generally indicated the same overall pattern. Regardless of the individual agencies sampling approach, the overall public-health advisory status of each zone in Milford Lake was similar according to the Kansas Department of Health and Environment guidance levels.

Spatial Distribution of a Large Herbivore Community at Waterholes: An Assessment of Its Stability over Years in Hwange National Park, Zimbabwe.

PubMed

Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé

2016-01-01

The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes.

Spatial Distribution of a Large Herbivore Community at Waterholes: An Assessment of Its Stability over Years in Hwange National Park, Zimbabwe

PubMed Central

Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé

2016-01-01

The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes. PMID:27074044

Spatial and temporal variability of interhemispheric transport times

NASA Astrophysics Data System (ADS)

Wu, Xiaokang; Yang, Huang; Waugh, Darryn W.; Orbe, Clara; Tilmes, Simone; Lamarque, Jean-Francois

2018-05-01

The seasonal and interannual variability of transport times from the northern midlatitude surface into the Southern Hemisphere is examined using simulations of three idealized age tracers: an ideal age tracer that yields the mean transit time from northern midlatitudes and two tracers with uniform 50- and 5-day decay. For all tracers the largest seasonal and interannual variability occurs near the surface within the tropics and is generally closely coupled to movement of the Intertropical Convergence Zone (ITCZ). There are, however, notable differences in variability between the different tracers. The largest seasonal and interannual variability in the mean age is generally confined to latitudes spanning the ITCZ, with very weak variability in the southern extratropics. In contrast, for tracers subject to spatially uniform exponential loss the peak variability tends to be south of the ITCZ, and there is a smaller contrast between tropical and extratropical variability. These differences in variability occur because the distribution of transit times from northern midlatitudes is very broad and tracers with more rapid loss are more sensitive to changes in fast transit times than the mean age tracer. These simulations suggest that the seasonal-interannual variability in the southern extratropics of trace gases with predominantly NH midlatitude sources may differ depending on the gases' chemical lifetimes.

Spatial heterogeneity of within-stream methane concentrations

NASA Astrophysics Data System (ADS)

Crawford, John T.; Loken, Luke C.; West, William E.; Crary, Benjamin; Spawn, Seth A.; Gubbins, Nicholas; Jones, Stuart E.; Striegl, Robert G.; Stanley, Emily H.

2017-05-01

Streams, rivers, and other freshwater features may be significant sources of CH4 to the atmosphere. However, high spatial and temporal variabilities hinder our ability to understand the underlying processes of CH4 production and delivery to streams and also challenge the use of scaling approaches across large areas. We studied a stream having high geomorphic variability to assess the underlying scale of CH4 spatial variability and to examine whether the physical structure of a stream can explain the variation in surface CH4. A combination of high-resolution CH4 mapping, a survey of groundwater CH4 concentrations, quantitative analysis of methanogen DNA, and sediment CH4 production potentials illustrates the spatial and geomorphic controls on CH4 emissions to the atmosphere. We observed significant spatial clustering with high CH4 concentrations in organic-rich stream reaches and lake transitions. These sites were also enriched in the methane-producing mcrA gene and had highest CH4 production rates in the laboratory. In contrast, mineral-rich reaches had significantly lower concentrations and had lesser abundances of mcrA. Strong relationships between CH4 and the physical structure of this aquatic system, along with high spatial variability, suggest that future investigations will benefit from viewing streams as landscapes, as opposed to ecosystems simply embedded in larger terrestrial mosaics. In light of such high spatial variability, we recommend that future workers evaluate stream networks first by using similar spatial tools in order to build effective sampling programs.

Spatial and Temporal Variabilities of Solar and Longwave Radiation Fluxes below a Coniferous Forest in the French Alps

NASA Astrophysics Data System (ADS)

Sicart, J. E.; Ramseyer, V.; Lejeune, Y.; Essery, R.; Webster, C.; Rutter, N.

2017-12-01

At high altitudes and latitudes, snow has a large influence on hydrological processes. Large fractions of these regions are covered by forests, which have a strong influence on snow accumulation and melting processes. Trees absorb a large part of the incoming shortwave radiation and this heat load is mostly dissipated as longwave radiation. Trees shelter the snow surface from wind, so sub-canopy snowmelt depends mainly on the radiative fluxes: vegetation attenuates the transmission of shortwave radiation but enhances longwave irradiance to the surface. An array of 13 pyranometers and 11 pyrgeometers was deployed on the snow surface below a coniferous forest at the CEN-MeteoFrance Col de Porte station in the French Alps (1325 m asl) during the 2017 winter in order to investigate spatial and temporal variabilities of solar and infrared irradiances in different meteorological conditions. Sky view factors measured with hemispherical photographs at each radiometer location were in a narrow range from 0.2 to 0.3. The temperature of the vegetation was measured with IR thermocouples and an IR camera. In clear sky conditions, the attenuation of solar radiation by the canopy reached 96% and its spatial variability exceeded 100 W m-2. Longwave irradiance varied by 30 W m-2 from dense canopy to gap areas. In overcast conditions, the spatial variabilities of solar and infrared irradiances were reduced and remained closely related to the sky view factor. A simple radiative model taking into account the penetration through the canopy of the direct and diffuse solar radiation, and isotropic infrared emission of the vegetation as a blackbody emitter, accurately reproduced the dynamics of the radiation fluxes at the snow surface. Model results show that solar transmissivity of the canopy in overcast conditions is an excellent proxy of the sky view factor and the emitting temperature of the vegetation remained close to the air temperature in this typically dense Alpine forest.

Climatic change by cloudiness linked to the spatial variability of sea surface temperatures

NASA Technical Reports Server (NTRS)

Otterman, J.

1975-01-01

An active role in modifying the earth's climate is suggested for low cloudiness over the circumarctic oceans. Such cloudiness, linked to the spatial differences in ocean surface temperatures, was studied. The temporal variations from year to year of ocean temperature patterns can be pronounced and therefore, the low cloudiness over this region should also show strong temporal variations, affecting the albedo of the earth and therefore the climate. Photographs are included.

Spatial variability in land-atmosphere coupling strength at the ARM Southern Great Plains site under different cloud regimes

NASA Astrophysics Data System (ADS)

Tang, Q.; Xie, S.; Zhang, Y.

2016-12-01

The paucity of land/soil observations is a long-standing limitation for land-atmosphere (LA) coupling studies, in particular for estimating the spatial variability in the coupling strengths. Spatially dense atmospheric radiation measurement (ARM) sites deployed at the U.S. Southern Great Plains (SGP) covers a wide range of vegetation, surface, and soil types, and thus allow us to observe the spatial patterns of LA coupling. The upcoming "super site" at SGP will facilitate these studies at even finer scales. While many previous studies have focused only on the observations from the central facility (CF) site or the domain mean from multiple sites, in the present work we examine the robustness of many key surface and land observations (e.g., radiation, turbulence fluxes, soil moisture, etc.) at extended sites besides the CF site for a decade. The coupling strengths are estimated with temporal covariations between important variables. We subsample the data to different categories based on different cloud regimes (e.g., clear sky, shallow cumulus, and deep cumulus. These cloud regimes are strongly impacted by local factors. The spatial variability of coupling strengths at different ARM sites is assessed with respect to dominant drivers (i.e., vegetation, land type, etc.). The results of this study will provide insights for improving the representation of LA coupling in climate models by providing observational constraints to parameterizations, e.g., shallow convective schemes. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-698523

[Spatial differentiation and impact factors of Yutian Oasis's soil surface salt based on GWR model].

PubMed

Yuan, Yu Yun; Wahap, Halik; Guan, Jing Yun; Lu, Long Hui; Zhang, Qin Qin

2016-10-01

In this paper, topsoil salinity data gathered from 24 sampling sites in the Yutian Oasis were used, nine different kinds of environmental variables closely related to soil salinity were selec-ted as influencing factors, then, the spatial distribution characteristics of topsoil salinity and spatial heterogeneity of influencing factors were analyzed by combining the spatial autocorrelation with traditional regression analysis and geographically weighted regression model. Results showed that the topsoil salinity in Yutian Oasis was not of random distribution but had strong spatial dependence, and the spatial autocorrelation index for topsoil salinity was 0.479. Groundwater salinity, groundwater depth, elevation and temperature were the main factors influencing topsoil salt accumulation in arid land oases and they were spatially heterogeneous. The nine selected environmental variables except soil pH had significant influences on topsoil salinity with spatial disparity. GWR model was superior to the OLS model on interpretation and estimation of spatial non-stationary data, also had a remarkable advantage in visualization of modeling parameters.

Land surface hydrology parameterization for atmospheric general circulation models including subgrid scale spatial variability

NASA Technical Reports Server (NTRS)

Entekhabi, D.; Eagleson, P. S.

1989-01-01

Parameterizations are developed for the representation of subgrid hydrologic processes in atmospheric general circulation models. Reasonable a priori probability density functions of the spatial variability of soil moisture and of precipitation are introduced. These are used in conjunction with the deterministic equations describing basic soil moisture physics to derive expressions for the hydrologic processes that include subgrid scale variation in parameters. The major model sensitivities to soil type and to climatic forcing are explored.

North Polar Radiative Flux Variability from 2002 Through 2014

NASA Technical Reports Server (NTRS)

Rutan, David; Rose, Fred; Doelling, David; Kato, Seiji; Smith, Bill, Jr.

2017-01-01

NASA's Clouds and the Earth's Radiant Energy System (CERES) project produces the SYN1Deg data product. SYN1deg provides global, 1deg gridded, hourly estimates of Top of Atmosphere (TOA) (CERES observations and calculations) and atmospheric and surface radiative flux (calculations). Examples of 12 year North Polar averages of some variables are shown to the right. Given recent interest in polar science we focus here on TOA and Surface validation of calculated irradiant fluxes. TOA upward longwave irradiance calculations match the CERES observations well both spatially and temporally with correlations remaining strong through PC 6. Compare SYN1Deg Calculations & Meteorological Teleconnections. TOA reflected shortwave irradiance calculations match the CERES observations well both spatially and temporally with correlations remaining string through PC 7. Comparing SYN1Deg calculations to teleconnection patterns requires expanding the area to 30N for EOF analyses. Correlating the Principal Components of various variables to teleconnection time series indicates which variable is most highly correlated with which teleconnection signal. The tables indicate the Pacific North American Oscillation is most correlated to the OLR EOF 1, and the North American Oscillation is correlated most closely to surface LW flux down EOF 1.

Vegetation Coverage and Impervious Surface Area Estimated Based on the Estarfm Model and Remote Sensing Monitoring

NASA Astrophysics Data System (ADS)

Hu, Rongming; Wang, Shu; Guo, Jiao; Guo, Liankun

2018-04-01

Impervious surface area and vegetation coverage are important biophysical indicators of urban surface features which can be derived from medium-resolution images. However, remote sensing data obtained by a single sensor are easily affected by many factors such as weather conditions, and the spatial and temporal resolution can not meet the needs for soil erosion estimation. Therefore, the integrated multi-source remote sensing data are needed to carry out high spatio-temporal resolution vegetation coverage estimation. Two spatial and temporal vegetation coverage data and impervious data were obtained from MODIS and Landsat 8 remote sensing images. Based on the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), the vegetation coverage data of two scales were fused and the data of vegetation coverage fusion (ESTARFM FVC) and impervious layer with high spatiotemporal resolution (30 m, 8 day) were obtained. On this basis, the spatial variability of the seepage-free surface and the vegetation cover landscape in the study area was measured by means of statistics and spatial autocorrelation analysis. The results showed that: 1) ESTARFM FVC and impermeable surface have higher accuracy and can characterize the characteristics of the biophysical components covered by the earth's surface; 2) The average impervious surface proportion and the spatial configuration of each area are different, which are affected by natural conditions and urbanization. In the urban area of Xi'an, which has typical characteristics of spontaneous urbanization, landscapes are fragmented and have less spatial dependence.

Remote sensing of exposure to NO2: Satellite versus ground-based measurement in a large urban area

NASA Astrophysics Data System (ADS)

Bechle, Matthew J.; Millet, Dylan B.; Marshall, Julian D.

2013-04-01

Remote sensing may be a useful tool for exploring spatial variability of air pollution exposure within an urban area. To evaluate the extent to which satellite data from the Ozone Monitoring Instrument (OMI) can resolve urban-scale gradients in ground-level nitrogen dioxide (NO2) within a large urban area, we compared estimates of surface NO2 concentrations derived from OMI measurements and US EPA ambient monitoring stations. OMI, aboard NASA's Aura satellite, provides daily afternoon (˜13:30 local time) measurements of NO2 tropospheric column abundance. We used scaling factors (surface-to-column ratios) to relate satellite column measurements to ground-level concentrations. We compared 4138 sets of paired data for 25 monitoring stations in the South Coast Air Basin of California for all of 2005. OMI measurements include more data gaps than the ground monitors (60% versus 5% of available data, respectively), owing to cloud contamination and imposed limits on pixel size. The spatial correlation between OMI columns and corrected in situ measurements is strong (r = 0.93 for annual average data), indicating that the within-urban spatial signature of surface NO2 is well resolved by the satellite sensor. Satellite-based surface estimates employing scaling factors from an urban model provide a reliable measure (annual mean bias: -13%; seasonal mean bias: <1% [spring] to -22% [fall]) of fine-scale surface NO2. We also find that OMI provides good spatial density in the study region (average area [km2] per measurement: 730 for the satellite sensor vs. 1100 for the monitors). Our findings indicate that satellite observations of NO2 from the OMI sensor provide a reliable measure of spatial variability in ground-level NO2 exposure for a large urban area.

Complementary effects of surface water and groundwater on soil moisture dynamics in a degraded coastal floodplain forest

NASA Astrophysics Data System (ADS)

Kaplan, D.; Muñoz-Carpena, R.

2011-02-01

SummaryRestoration of degraded floodplain forests requires a robust understanding of surface water, groundwater, and vadose zone hydrology. Soil moisture is of particular importance for seed germination and seedling survival, but is difficult to monitor and often overlooked in wetland restoration studies. This research hypothesizes that the complex effects of surface water and shallow groundwater on the soil moisture dynamics of floodplain wetlands are spatially complementary. To test this hypothesis, 31 long-term (4-year) hydrological time series were collected in the floodplain of the Loxahatchee River (Florida, USA), where watershed modifications have led to reduced freshwater flow, altered hydroperiod and salinity, and a degraded ecosystem. Dynamic factor analysis (DFA), a time series dimension reduction technique, was applied to model temporal and spatial variation in 12 soil moisture time series as linear combinations of common trends (representing shared, but unexplained, variability) and explanatory variables (selected from 19 additional candidate hydrological time series). The resulting dynamic factor models yielded good predictions of observed soil moisture series (overall coefficient of efficiency = 0.90) by identifying surface water elevation, groundwater elevation, and net recharge (cumulative rainfall-cumulative evapotranspiration) as important explanatory variables. Strong and complementary linear relationships were found between floodplain elevation and surface water effects (slope = 0.72, R2 = 0.86, p < 0.001), and between elevation and groundwater effects (slope = -0.71, R2 = 0.71, p = 0.001), while the effect of net recharge was homogenous across the experimental transect (slope = 0.03, R2 = 0.05, p = 0.242). This study provides a quantitative insight into the spatial structure of groundwater and surface water effects on soil moisture that will be useful for refining monitoring plans and developing ecosystem restoration and management scenarios in degraded coastal floodplains.

Modeling surface response of the Greenland Ice Sheet to interglacial climate

NASA Astrophysics Data System (ADS)

Rau, Dominik; Rogozhina, Irina

2013-04-01

We present a new parameterization of surface mass balance (SMB) of the Greenland Ice Sheet (GIS) under interglacial climate conditions validated against recent satellite observations on a regional scale. Based on detailed analysis of the modeled surface melting and refreezing rates, we conclude that the existing SMB parameterizations fail to capture either spatial pattern or amplitude of the observed surface response of the GIS. This is due to multiple simplifying assumptions adopted by the majority of modeling studies within the frame of the positive degree day method. Modeled spatial distribution of surface melting is found to be highly sensitive to a choice of daily temperature standard deviation (SD) and degree-day factors, which are generally assumed to have uniform distribution across the entire Greenland region. However, the use of uniform SD distribution and the range of commonly used SD values are absolutely unsupported by the ERA-40 and ERA-Interim climate data. In this region, SD distribution is highly inhomogeneous and characterized by low amplitudes during the summer months in the areas where most surface ice melting occurs. In addition, the use of identical degree day factors on both the eastern and western slopes of the GIS results in overestimation of surface runoff along the western coast of Greenland and significant underestimation along its eastern coast. Our approach is to make use of (i) spatially and seasonally variable SDs derived from ERA-40 and ERA-Interim time series, and (ii) spatially variable degree-day factors, measured across Greenland, Arctic Canada, Norway, Spitsbergen and Iceland. We demonstrate that the new approach is extremely efficient for modeling the evolution of the GIS during the observational period and the entire Holocene interglacial.

Aerosol direct effect on solar radiation over the eastern Mediterranean Sea based on AVHRR satellite measurements

NASA Astrophysics Data System (ADS)

Georgakaki, Paraskevi; Papadimas, Christos D.; Hatzianastassiou, Nikos; Fotiadi, Aggeliki; Matsoukas, Christos; Stackhouse, Paul; Kanakidou, Maria; Vardavas, Ilias M.

2017-04-01

Despite the improved scientific understanding of the direct effect of aerosols on solar radiation (direct radiative effect, DRE) improvements are necessary, for example regarding the accuracy of the magnitude of estimated DREs and their spatial and temporal variability. This variability cannot be ensured by in-situ surface and airborne measurements, while it is also relatively difficult to capture through satellite observations. This becomes even more difficult when complete spatial coverage of extended areas is required, especially concerning areas that host various aerosol types with variable physico-chemical and optical aerosol properties. Better assessments of aerosol DREs are necessary, relying on aerosol optical properties with high spatial and temporal variation. The present study aims to provide a refined, along these lines, assessment of aerosol DREs over the eastern Mediterranean (EM) Sea, which is a key area for aerosol studies. Daily DREs are computed for 1˚ x1˚ latitude-longitude grids with the FORTH detailed spectral radiation transfer model (RTM) using input data for various atmospheric and surface parameters, such as clouds, water vapor, ozone and surface albedo, taken from the NASA-Langley Global Earth Observing System (GEOS) database. The model spectral aerosol optical depth (AOD), single scattering albedo and asymmetry parameter are taken from the Global Aerosol Data Set and the NOAA Climate Data Record (CDR) version 2 of Advanced Very High resolution Radiometer (AVHRR) AOD dataset which is available over oceans at 0.63 microns and at 0.1˚ x0.1˚ . The aerosol DREs are computed at the surface, the top-of-atmosphere and within the atmosphere, over the period 1985-1995. Preliminary model results for the period 1990-1993 reveal a significant spatial and temporal variability of DREs over the EM Sea, for example larger values over the Aegean and Black Seas, surrounded by land areas with significant anthropogenic aerosol sources, and over the southernmost parts of EM Sea, affected by frequent Saharan dust export. The mean regional annual AODs range from 0.17±0.05 to 0.23±0.06. The corresponding regional annual DREs at surface range from -14±3 to -18±4 W/m2 (surface radiative cooling), while in the atmosphere they vary between 7±2 and 10±2 W/m2 (atmospheric heating), yielding a planetary cooling above the EM Sea between -6±1 and -8±2 W/m2. However, these AOD and DRE values vary depending on the criteria of data spatial and temporal availability applied in the AOD and DRE calculation, because of the limited availability of retrieved AVHRR AOD over specific areas and in specific days. The DREs reach larger magnitudes at pixel-level; for example the surface DREs slightly exceed -30 W/m2, whereas they take larger values (magnitudes larger than -50 W/m2 in summer) when computed on a monthly basis, and even larger values on daily basis. The model results underline the high spatial and temporal variability of aerosol DREs, and the care that must be taken when averaging over space and time. It also points to the need for availability of aerosol data with concurrent high spatial and temporal coverage and resolution, which should be sought in ongoing and future satellite missions.

Spatial Variability and Distribution of the Metals in Surface Runoff in a Nonferrous Metal Mine

PubMed Central

Ren, Bozhi; Chen, Yangbo; Zhu, Guocheng; Wang, Zhenghua; Zheng, Xie

2016-01-01

The spatial variation and distribution features of the metals tested in the surface runoff in Xikuangshan Bao Daxing miming area were analyzed by combining statistical methods with a geographic information system (GIS). The results showed that the maximum concentrations of those five kinds of the metals (Sb, Zn, Cu, Pb, and Cd) in the surface runoff of the antimony mining area were lower than the standard value except the concentration of metal Ni. Their concentrations were 497.1, 2.0, 1.8, 22.2, and 22.1 times larger than the standard value, respectively. This metal pollution was mainly concentrated in local areas, which were seriously polluted. The variation coefficient of Sb, Zn, Cu, Ni, Pb, and Cd was between 0.4 to 0.6, wherein the Sb's spatial variability coefficient is 50.56%, indicating a strong variability. Variation coefficients of the rest of metals were less than 50%, suggesting a moderate variability. The spatial structure analysis showed that the squared correlation coefficient (R 2) of the models fitting for Sb, Zn, Cu, Ni, Pb, and Cd was between 0.721 and 0.976; the ratio of the nugget value (C 0) to the abutment value (C + C 0) was between 0.0767 and 0.559; the semivariogram of Sb, Zn, Ni, and Pb was in agreement with a spherical model, while semivariogram of Cu and Cd was in agreement with Gaussian model, and both had a strong spatial correlation. The trend and spatial distribution indicated that those pollution distributions resulting from Ni, Pb, and Cd are similar, mainly concentrated in both ends of north and south in eastern part. The main reasons for the pollution were attributed to the residents living, transportation, and industrial activities; the Sb distribution was concentrated mainly in the central part, of which the pollution was assigned to the mining and the industrial activity; the pollution distributions of Zn and Cu were similar, mainly concentrated in both ends of north and south as well as in west; the sources of the metals were widely distributed. PMID:27069713

Spatial variability of concentrations of chlorophyll a, dissolved organic matter and suspended particles in the surface layer of the Kara Sea in September 2011 from lidar data

NASA Astrophysics Data System (ADS)

Pelevin, V. V.; Zavjalov, P. O.; Belyaev, N. A.; Konovalov, B. V.; Kravchishina, M. D.; Mosharov, S. A.

2017-01-01

The article presents results of underway remote laser sensing of the surface water layer in continuous automatic mode using the UFL-9 fluorescent lidar onboard the R/V Akademik Mstislav Keldysh during cruise 59 in the Kara Sea in 2011. The description of the lidar, the approach to interpreting seawater fluorescence data, and certain methodical aspects of instrument calibration and measurement are presented. Calibration of the lidar is based on laboratory analysis of water samples taken from the sea surface during the cruise. Spatial distribution of chlorophyll a, total organic carbon and suspended matter concentrations in the upper quasi-homogeneous layer are mapped and the characteristic scales of the variability are estimated. Some dependencies between the patchiness of the upper water layer and the atmospheric forcing and freshwater runoff are shown.

Study on temporal and spatial variations of urban land use based on land change data

NASA Astrophysics Data System (ADS)

Jiang, Ping; Liu, Yanfang; Fan, Min; Zhang, Yang

2009-10-01

With the rapid development of urbanization, demands of urban land increase in succession, hence, to analyze temporal and spatial variations of urban land use becomes more and more important. In this paper, the principle of trend surface analysis and formula of urban land sprawl index ( ULSI) are expatiated at first, and then based on land change data of Jiayu county, the author fits quadratic trend surface by choosing urban land area as dependent variable and urbanization and GDP as independent variables from 1996 to 2006, draws isoline of trend surface and residual values; and then urban land sprawl indexes of towns are calculated on the basis of urban land area of 1996 and 2006 and distribution map of ULSI is plotted. After analyzing those results, we can conclude that there is consanguineous relationship between urban land area and urbanization, economic level etc.

Two-Layer Variable Infiltration Capacity Land Surface Representation for General Circulation Models

NASA Technical Reports Server (NTRS)

Xu, L.

1994-01-01

A simple two-layer variable infiltration capacity (VIC-2L) land surface model suitable for incorporation in general circulation models (GCMs) is described. The model consists of a two-layer characterization of the soil within a GCM grid cell, and uses an aerodynamic representation of latent and sensible heat fluxes at the land surface. The effects of GCM spatial subgrid variability of soil moisture and a hydrologically realistic runoff mechanism are represented in the soil layers. The model was tested using long-term hydrologic and climatalogical data for Kings Creek, Kansas to estimate and validate the hydrological parameters. Surface flux data from three First International Satellite Land Surface Climatology Project Field Experiments (FIFE) intensive field compaigns in the summer and fall of 1987 in central Kansas, and from the Anglo-Brazilian Amazonian Climate Observation Study (ABRACOS) in Brazil were used to validate the mode-simulated surface energy fluxes and surface temperature.

Scale issues in soil hydrology related to measurement and simulation: A case study in Colorado

USDA-ARS?s Scientific Manuscript database

State variables, such as soil water content (SWC), are typically measured or inferred at very small scales while being simulated at larger scales relevant to spatial management or hillslope areas. Thus there is an implicit spatial disparity that is often ignored. Surface runoff, on the other hand, ...

Real Time Land-Surface Hydrologic Modeling Over Continental US

NASA Technical Reports Server (NTRS)

Houser, Paul R.

1998-01-01

The land surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. Spatially and temporally variable rainfall and available energy, combined with land surface heterogeneity cause complex variations in all processes related to surface hydrology. The characterization of the spatial and temporal variability of water and energy cycles are critical to improve our understanding of land surface-atmosphere interaction and the impact of land surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes. This has motivated the NWP to impose ad hoc corrections to the land surface states to prevent this drift. A proposed methodology is to develop Land Data Assimilation schemes (LDAS), which are uncoupled models forced with observations, and not affected by NWP forcing biases. The proposed research is being implemented as a real time operation using an existing Surface Vegetation Atmosphere Transfer Scheme (SVATS) model at a 40 km degree resolution across the United States to evaluate these critical science questions. The model will be forced with real time output from numerical prediction models, satellite data, and radar precipitation measurements. Model parameters will be derived from the existing GIS vegetation and soil coverages. The model results will be aggregated to various scales to assess water and energy balances and these will be validated with various in-situ observations.

Sharpening method of satellite thermal image based on the geographical statistical model

NASA Astrophysics Data System (ADS)

Qi, Pengcheng; Hu, Shixiong; Zhang, Haijun; Guo, Guangmeng

2016-04-01

To improve the effectiveness of thermal sharpening in mountainous regions, paying more attention to the laws of land surface energy balance, a thermal sharpening method based on the geographical statistical model (GSM) is proposed. Explanatory variables were selected from the processes of land surface energy budget and thermal infrared electromagnetic radiation transmission, then high spatial resolution (57 m) raster layers were generated for these variables through spatially simulating or using other raster data as proxies. Based on this, the local adaptation statistical relationship between brightness temperature (BT) and the explanatory variables, i.e., the GSM, was built at 1026-m resolution using the method of multivariate adaptive regression splines. Finally, the GSM was applied to the high-resolution (57-m) explanatory variables; thus, the high-resolution (57-m) BT image was obtained. This method produced a sharpening result with low error and good visual effect. The method can avoid the blind choice of explanatory variables and remove the dependence on synchronous imagery at visible and near-infrared bands. The influences of the explanatory variable combination, sampling method, and the residual error correction on sharpening results were analyzed deliberately, and their influence mechanisms are reported herein.

Variability of water quality across headwater catchments with distinct soils and hydrologic systems in central Missouri

USDA-ARS?s Scientific Manuscript database

Surface water and groundwater contamination by herbicides and fertilizers continues to be a major water quality problem in central Missouri. The purpose of this study was to examine spatial variability of water quality among three different headwater catchments – Goodwater Creek Experimental Watersh...

Spatial heterogeneity of within-stream methane concentrations

USGS Publications Warehouse

Crawford, John T.; Loken, Luke C.; West, William E.; Crary, Benjamin; Spawn, Seth A.; Gubbins, Nicholas; Jones, Stuart E.; Striegl, Robert G.; Stanley, Emily H.

2017-01-01

Streams, rivers, and other freshwater features may be significant sources of CH4 to the atmosphere. However, high spatial and temporal variabilities hinder our ability to understand the underlying processes of CH4 production and delivery to streams and also challenge the use of scaling approaches across large areas. We studied a stream having high geomorphic variability to assess the underlying scale of CH4 spatial variability and to examine whether the physical structure of a stream can explain the variation in surface CH4. A combination of high-resolution CH4 mapping, a survey of groundwater CH4 concentrations, quantitative analysis of methanogen DNA, and sediment CH4 production potentials illustrates the spatial and geomorphic controls on CH4 emissions to the atmosphere. We observed significant spatial clustering with high CH4 concentrations in organic-rich stream reaches and lake transitions. These sites were also enriched in the methane-producing mcrA gene and had highest CH4 production rates in the laboratory. In contrast, mineral-rich reaches had significantly lower concentrations and had lesser abundances of mcrA. Strong relationships between CH4and the physical structure of this aquatic system, along with high spatial variability, suggest that future investigations will benefit from viewing streams as landscapes, as opposed to ecosystems simply embedded in larger terrestrial mosaics. In light of such high spatial variability, we recommend that future workers evaluate stream networks first by using similar spatial tools in order to build effective sampling programs.

Surface terrain characteristics and monsoon season mass balance of debris-covered glaciers in the Khumbu Himal, Nepal, obtained from high resolution Pléiades imagery.

NASA Astrophysics Data System (ADS)

Klug, Christoph; Nicholson, Lindsey; Rieg, Lorenzo; Sailer, Rudolf; Wirbel, Anna

2016-04-01

Debris-covered glaciers in the eastern Himalaya have pronounced surface relief consisting of hummocks and hollows, ice cliffs, lakes and former lake beds. This relief and spatially variable surface properties are expected to influence the spatially distributed surface energy balance and related ice mass loss and atmospheric interactions, but only a few studies have so far explicitly examined the nature of the surface terrain and its textures . In this work we present a new high-resolution digital terrain model (DTM) of a portion of the Khumbu Himal in the eastern Nepalese Himalaya, derived from Pléiades satellite imagery sampled in spring 2015. We use this DTM to study the terrain characteristics of five sample glaciers and analyse the inter- and intra- glacier variability of terrain characteristics in the context of glacier flow velocities and surface changes presented in previous studies in the area. In parallel to this analysis we also present the seasonal geodetic mass balance between spring and fall 2015, and relate it to the terrain properties, surface velocity and limited knowledge of the local lapse rates in meteorological conditions during this monsoon season.

Enceladus Plume Structure and Time Variability: Comparison of Cassini Observations

PubMed Central

Perry, Mark E.; Hansen, Candice J.; Waite, J. Hunter; Porco, Carolyn C.; Spencer, John R.; Howett, Carly J. A.

2017-01-01

Abstract During three low-altitude (99, 66, 66 km) flybys through the Enceladus plume in 2010 and 2011, Cassini's ion neutral mass spectrometer (INMS) made its first high spatial resolution measurements of the plume's gas density and distribution, detecting in situ the individual gas jets within the broad plume. Since those flybys, more detailed Imaging Science Subsystem (ISS) imaging observations of the plume's icy component have been reported, which constrain the locations and orientations of the numerous gas/grain jets. In the present study, we used these ISS imaging results, together with ultraviolet imaging spectrograph stellar and solar occultation measurements and modeling of the three-dimensional structure of the vapor cloud, to constrain the magnitudes, velocities, and time variability of the plume gas sources from the INMS data. Our results confirm a mixture of both low and high Mach gas emission from Enceladus' surface tiger stripes, with gas accelerated as fast as Mach 10 before escaping the surface. The vapor source fluxes and jet intensities/densities vary dramatically and stochastically, up to a factor 10, both spatially along the tiger stripes and over time between flyby observations. This complex spatial variability and dynamics may result from time-variable tidal stress fields interacting with subsurface fissure geometry and tortuosity beyond detectability, including changing gas pathways to the surface, and fluid flow and boiling in response evolving lithostatic stress conditions. The total plume gas source has 30% uncertainty depending on the contributions assumed for adiabatic and nonadiabatic gas expansion/acceleration to the high Mach emission. The overall vapor plume source rate exhibits stochastic time variability up to a factor ∼5 between observations, reflecting that found in the individual gas sources/jets. Key Words: Cassini at Saturn—Geysers—Enceladus—Gas dynamics—Icy satellites. Astrobiology 17, 926–940. PMID:28872900

Defining surfaces for skewed, highly variable data

USGS Publications Warehouse

Helsel, D.R.; Ryker, S.J.

2002-01-01

Skewness of environmental data is often caused by more than simply a handful of outliers in an otherwise normal distribution. Statistical procedures for such datasets must be sufficiently robust to deal with distributions that are strongly non-normal, containing both a large proportion of outliers and a skewed main body of data. In the field of water quality, skewness is commonly associated with large variation over short distances. Spatial analysis of such data generally requires either considerable effort at modeling or the use of robust procedures not strongly affected by skewness and local variability. Using a skewed dataset of 675 nitrate measurements in ground water, commonly used methods for defining a surface (least-squares regression and kriging) are compared to a more robust method (loess). Three choices are critical in defining a surface: (i) is the surface to be a central mean or median surface? (ii) is either a well-fitting transformation or a robust and scale-independent measure of center used? (iii) does local spatial autocorrelation assist in or detract from addressing objectives? Published in 2002 by John Wiley & Sons, Ltd.

Precipitation phase partitioning variability across the Northern Hemisphere

NASA Astrophysics Data System (ADS)

Jennings, K. S.; Winchell, T. S.; Livneh, B.; Molotch, N. P.

2017-12-01

Precipitation phase drives myriad hydrologic, climatic, and biogeochemical processes. Despite its importance, many of the land surface models used to simulate such processes and their sensitivity to climate warming rely on simple, spatially uniform air temperature thresholds to partition rainfall and snowfall. Our analysis of a 29-year dataset with 18.7 million observations of precipitation phase from 12,143 stations across the Northern Hemisphere land surface showed marked spatial variability in the near-surface air temperature at which precipitation is equally likely to fall as rain and snow, the 50% rain-snow threshold. This value averaged 1.0°C and ranged from -0.4°C to 2.4°C for 95% of the stations analyzed. High-elevation continental areas such as the Rocky Mountains of the western U.S. and the Tibetan Plateau of central Asia generally exhibited the warmest thresholds, in some cases exceeding 3.0°C. Conversely, the coldest thresholds were observed on the Pacific Coast of North America, the southeast U.S., and parts of Eurasia, with values dropping below -0.5°C. Analysis of the meteorological conditions during storm events showed relative humidity exerted the strongest control on phase partitioning, with surface pressure playing a secondary role. Lower relative humidity and surface pressure were both associated with warmer 50% rain-snow thresholds. Additionally, we trained a binary logistic regression model on the observations to classify rain and snow events and found including relative humidity as a predictor variable significantly increased model performance between 0.6°C and 3.8°C when phase partitioning is most uncertain. We then used the optimized model and a spatially continuous reanalysis product to map the 50% rain-snow threshold across the Northern Hemisphere. The map reproduced patterns in the observed thresholds with a mean bias of 0.5°C relative to the station data. The above results suggest land surface models could be improved by incorporating relative humidity into their precipitation phase prediction schemes or by using a spatially variable, optimized rain-snow temperature threshold. This is particularly important for climate warming simulations where misdiagnosing a shift from snow to rain or inaccurately quantifying snowfall fraction would likely lead to biased results.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA).

PubMed

Reichenau, Tim G; Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA)

PubMed Central

Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI. PMID:27391858

Introducing MISR Version 23: Resolution and Content Improvements to MISR Aerosol and Land Surface Product

NASA Astrophysics Data System (ADS)

Garay, M. J.; Bull, M. A.; Witek, M. L.; Diner, D. J.; Seidel, F.

2017-12-01

Since early 2000, the Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra satellite has been providing operational Level 2 (swath-based) aerosol optical depth (AOD) and particle property retrievals at 17.6 km spatial resolution and atmospherically corrected land surface products at 1.1 km resolution. A major, multi-year development effort has led to the release of updated operational MISR Level 2 aerosol and land surface retrieval products. The spatial resolution of the aerosol product has been increased to 4.4 km, allowing more detailed characterization of aerosol spatial variability, especially near local sources and in urban areas. The product content has been simplified and updated to include more robust measures of retrieval uncertainty and other fields to benefit users. The land surface product has also been updated to incorporate the Version 23 aerosol product as input and to improve spatial coverage, particularly over mountainous terrain and snow/ice-covered surfaces. We will describe the major upgrades incorporated in Version 23, present validation of the aerosol product, and describe some of the applications enabled by these product updates.

Combining Individual-Based Modeling and Food Microenvironment Descriptions To Predict the Growth of Listeria monocytogenes on Smear Soft Cheese

PubMed Central

Ferrier, Rachel; Hezard, Bernard; Lintz, Adrienne; Stahl, Valérie

2013-01-01

An individual-based modeling (IBM) approach was developed to describe the behavior of a few Listeria monocytogenes cells contaminating smear soft cheese surface. The IBM approach consisted of assessing the stochastic individual behaviors of cells on cheese surfaces and knowing the characteristics of their surrounding microenvironments. We used a microelectrode for pH measurements and micro-osmolality to assess the water activity of cheese microsamples. These measurements revealed a high variability of microscale pH compared to that of macroscale pH. A model describing the increase in pH from approximately 5.0 to more than 7.0 during ripening was developed. The spatial variability of the cheese surface characterized by an increasing pH with radius and higher pH on crests compared to that of hollows on cheese rind was also modeled. The microscale water activity ranged from approximately 0.96 to 0.98 and was stable during ripening. The spatial variability on cheese surfaces was low compared to between-cheese variability. Models describing the microscale variability of cheese characteristics were combined with the IBM approach to simulate the stochastic growth of L. monocytogenes on cheese, and these simulations were compared to bacterial counts obtained from irradiated cheeses artificially contaminated at different ripening stages. The simulated variability of L. monocytogenes counts with the IBM/microenvironmental approach was consistent with the observed one. Contrasting situations corresponding to no growth or highly contaminated foods could be deduced from these models. Moreover, the IBM approach was more effective than the traditional population/macroenvironmental approach to describe the actual bacterial behavior variability. PMID:23872572

Exploring the Linkage of Sea Surface Temperature Variability on Three Spatial Scales

NASA Astrophysics Data System (ADS)

Luo, L.; Capone, D. G.; Hutchins, D.; Kiefer, D.

2011-12-01

As part of a project examining climate change in the Southern California Bight at the University of Southern California, we studied the linkage of the variability of sea surface temperature across three nested spatial scales, the north Pacific Basin, the West Coast of North American, and the Southern California Bight. Specifically, we analyzed daily GHRSST images between September 1981 and July 2009. In order to remove seasonal changes in temperature and focus upon differences between years, we calculate weekly mean temperature for each pixel from the time series, and then subjected the anomalies for the 3 spatial scales to empirical orthogonal function (EOF) analysis. The corresponding temporal expansion coefficients and spatial components (eigenvector) for each EOF mode were then generated to examine the temporal and spatial patterns of SST change. The results showed that the El Nino Southern Oscillation (ENSO) has a clear influence on the SST variability across all the three spatial scales, especially the 1st EOF mode which represents the largest variance. The comparison between the time coefficients of the 1st EOF mode and the Oceanic Nino Index (ONI) suggested that the EOF mode 1 of the Pacific Basin region matched well with almost all the El Nino and La Nina signals while the West Coast of North American captured only the strong signals and the Southern California Bight captures still fewer of the signals. This clearly indicated that the Southern California Bight is relatively insensitive to ENSO signal relative to other locations along the West Coast. The 1st EOF Mode for the West Coast of North American was also clearly influenced by upwelling. The cross correlation coefficient between each pair of the EOF mode 1 temporal expansion coefficients for the three spatial scales suggested that they were significantly correlated to each other. The effect of the Pacific Decadal Oscillation (PDO) on the SST change was also demonstrated by the temporal variability of the temporal expansion coefficients of the 2nd EOF mode. However, the correlations of 2nd EOF mode time coefficients between the three scales appeared relatively low compared the 1st EOF mode. In summary sea surface temperature in the Southern California Bight behaves like a node that is relatively insensitive to ENSO, PDO, and upwelling signals.

Small scale variability of snow properties on Antarctic sea ice

NASA Astrophysics Data System (ADS)

Wever, Nander; Leonard, Katherine; Paul, Stephan; Jacobi, Hans-Werner; Proksch, Martin; Lehning, Michael

2016-04-01

Snow on sea ice plays an important role in air-ice-sea interactions, as snow accumulation may for example increase the albedo. Snow is also able to smooth the ice surface, thereby reducing the surface roughness, while at the same time it may generate new roughness elements by interactions with the wind. Snow density is a key property in many processes, for example by influencing the thermal conductivity of the snow layer, radiative transfer inside the snow as well as the effects of aerodynamic forcing on the snowpack. By comparing snow density and grain size from snow pits and snow micro penetrometer (SMP) measurements, highly resolved density and grain size profiles were acquired during two subsequent cruises of the RV Polarstern in the Weddell Sea, Antarctica, between June and October 2013. During the first cruise, SMP measurements were done along two approximately 40 m transects with a horizontal resolution of approximately 30 cm. During the second cruise, one transect was made with approximately 7.5 m resolution over a distance of 500 m. Average snow densities are about 300 kg/m3, but the analysis also reveals a high spatial variability in snow density on sea ice in both horizontal and vertical direction, ranging from roughly 180 to 360 kg/m3. This variability is expressed by coherent snow structures over several meters. On the first cruise, the measurements were accompanied by terrestrial laser scanning (TLS) on an area of 50x50 m2. The comparison with the TLS data indicates that the spatial variability is exhibiting similar spatial patterns as deviations in surface topology. This suggests a strong influence from surface processes, for example wind, on the temporal development of density or grain size profiles. The fundamental relationship between variations in snow properties, surface roughness and changes therein as investigated in this study is interpreted with respect to large-scale ice movement and the mass balance.

Ammonia and Methane Dairy Emission Plumes in the San Joaquin Valley of California from Individual Feedlot to Regional Scales

NASA Technical Reports Server (NTRS)

Miller, David J.; Sun, Kang; Pan, Da; Zondlo, Mark A.; Nowak, John B.; Liu, Zhen; Diskin, Glenn; Sachse, Glen; Beyersdorf, Andreas; Ferrare, Richard;

Ammonia and methane dairy emissions in the San Joaquin Valley of California from individual feedlot to regional scale

DOE PAGES

Miller, David J.; Sun, Kang; Tao, Lei; ...

2015-09-27

Agricultural ammonia (NH 3) emissions are highly uncertain, with high spatiotemporal variability and a lack of widespread in situ measurements. Regional NH 3 emission estimates using mass balance or emission ratio approaches are uncertain due to variable NH 3 sources and sinks as well as unknown plume correlations with other dairy source tracers. We characterize the spatial distributions of NH 3 and methane (CH 4) dairy plumes using in situ surface and airborne measurements in the Tulare dairy feedlot region of the San Joaquin Valley, California, during the NASA Deriving Information on Surface conditions from Column and Vertically Resolved Observationsmore » Relevant to Air Quality 2013 field campaign. Surface NH 3 and CH 4 mixing ratios exhibit large variability with maxima localized downwind of individual dairy feedlots. The geometric mean NH 3:CH 4 enhancement ratio derived from surface measurements is 0.15 ± 0.03 ppmv ppmv –1. Individual dairy feedlots with spatially distinct NH 3 and CH 4 source pathways led to statistically significant correlations between NH 3 and CH 4 in 68% of the 69 downwind plumes sampled. At longer sampling distances, the NH 3:CH 4 enhancement ratio decreases 20–30%, suggesting the potential for NH 3 deposition as a loss term for plumes within a few kilometers downwind of feedlots. Aircraft boundary layer transect measurements directly above surface mobile measurements in the dairy region show comparable gradients and geometric mean enhancement ratios within measurement uncertainties, even when including NH 3 partitioning to submicron particles. Individual NH 3 and CH 4 plumes sampled at close proximity where losses are minimal are not necessarily correlated due to lack of mixing and distinct source pathways. As a result, our analyses have important implications for constraining NH 3 sink and plume variability influences on regional NH 3 emission estimates and for improving NH 3 emission inventory spatial allocations.« less

Surface compositional variation on the comet 67P/Churyumov-Gerasimenko by OSIRIS data

NASA Astrophysics Data System (ADS)

Barucci, M. A.; Fornasier, S.; Feller, C.; Perna, D.; Hasselmann, H.; Deshapriya, J. D. P.; Fulchignoni, M.; Besse, S.; Sierks, H.; Forgia, F.; Lazzarin, M.; Pommerol, A.; Oklay, N.; Lara, L.; Scholten, F.; Preusker, F.; Leyrat, C.; Pajola, M.; Osiris-Rosetta Team

2015-10-01

Since the Rosetta mission arrived at the comet 67P/Churyumov-Gerasimenko (67/P C-G) on July 2014, the comet nucleus has been mapped by both OSIRIS (Optical, Spectroscopic, and Infrared Remote Imaging System, [1]) NAC (Narrow Angle Camera) and WAC (Wide Angle Camera) acquiring a huge quantity of surface's images at different wavelength bands, under variable illumination conditions and spatial resolution, and producing the most detailed maps at the highest spatial resolution of a comet nucleus surface.67/P C-G's nucleus shows an irregular bi-lobed shape of complex morphology with terrains showing intricate features [2, 3] and a heterogeneity surface at different scales.

Structural Variability of Tropospheric Growth Factors Transforming Mid-latitude Cyclones to Severe Storms over the North Atlantic

NASA Astrophysics Data System (ADS)

Wild, Simon; Befort, Daniel J.; Leckebusch, Gregor C.

2015-04-01

The development of European surface wind storms out of normal mid-latitude cyclones is substantially influenced by upstream tropospheric growth factors over the Northern Atlantic. The main factors include divergence and vorticity advection in the upper troposphere, latent heat release and the presence of instabilities of short baroclinic waves of suitable wave lengths. In this study we examine a subset of these potential growth factors and their related influences on the transformation of extra-tropical cyclones into severe damage prone surface storm systems. Previous studies have shown links between specific growth factors and surface wind storms related to extreme cyclones. In our study we investigate in further detail spatial and temporal variability patterns of these upstream processes at different vertical levels of the troposphere. The analyses will comprise of the three growth factors baroclinicity, latent heat release and upper tropospheric divergence. Our definition of surface wind storms is based on the Storm Severity Index (SSI) alongside a wind tracking algorithm identifying areas of exceedances of the local 98th percentile of the 10m wind speed. We also make use of a well-established extra-tropical cyclone identification and tracking algorithm. These cyclone tracks form the base for a composite analysis of the aforementioned growth factors using ERA-Interim Reanalysis from 1979 - 2014 for the extended winter season (ONDJFM). Our composite analysis corroborates previous similar studies but extends them by using an impact based algorithm for the identification of strong wind systems. Based on this composite analysis we further identify variability patterns for each growth factor most important for the transformation of a cyclone into a surface wind storm. We thus also address the question whether the link between storm intensity and related growth factor anomaly taking into account its spatial variability is stable and can be quantified. While the robustness of our preliminary results is generally dependent on the growth factor investigated, some examples include i) the overall availability of latent heat seems to be less important than its spatial structure around the cyclone core and ii) the variability of upper-tropospheric baroclinicity appears to be highest north of the surface position of the cyclone, especially for those that transform into a surface storm.

Exploring Statistical Characterizations of Morphologic Change and Variability: Fire Island, New York

NASA Astrophysics Data System (ADS)

Lentz, E. E.; Hapke, C. J.

2012-12-01

A comprehensive understanding of coastal barrier behavior requires high-resolution observations that capture a wide range of morphological changes occurring over a range of spatial and temporal scales. Fire Island National Seashore, located along the coast of Long Island, New York, is a well studied barrier island coast where understanding how morphological changes contribute to barrier island vulnerability have important implications for coastal land management. Previous work has shown that morphologic differences in eastern and western reaches are attributable to the underlying geology and variations sediment transport in the system. In this study, we further explore western and eastern differences and variability with lidar-derived topographic surfaces to provide a unique and comprehensive investigation of dune-beach change at Fire Island, New York. Continuous topographic surfaces generated from 12 lidar surveys collected between 1998 and 2011 are used to examine the three-dimensional variability over a range of time periods over the 50 km long island. Because surveys were collected over a range of seasons and in response to a number of storm events, we explore morphologic configurations reflecting the seasonality, post-storm configuration, and replenishment response to the system through the generation of a representative or average surface. These averaged surfaces provide the context for what would be an expected or typical coastal configuration under certain conditions, and through comparison with an individual event, can be used to derive an event-specific spatial-change signature. To investigate anthropogenic influences, differences in morphology between a survey collected after a substantial beach replenishment project and a typical fair-weather configuration averaged from six surveys are determined. Storm response variations are also explored by assessing differences between Tropical Storm Irene (2011), Nor'Ida (2009), and a typical post-storm configuration averaged from five post-storm surveys. In addition to averaged surfaces, surveys are combined to generate a new raster surface reflecting cell by cell standard deviations over a defined period. Standard deviation surfaces are generated to highlight 1) where areas of highest and lowest morphologic variation are located over the entire period, and 2) whether spatial similarities exist in variability between storm and non-storm morphologies. Results show there are distinct and variable responses in eastern and western reaches attributable to wave climate, profile gradient, and offshore bathymetry, as well as to a general along-coast increase in sediment availability.

Application of a fully integrated surface-subsurface physically based flow model for evaluating groundwater recharge from a flash flood event

NASA Astrophysics Data System (ADS)

Pino, Cristian; Herrera, Paulo; Therrien, René

2017-04-01

In many arid regions around the world groundwater recharge occurs during flash floods. This transient spatially and temporally concentrated flood-recharge process takes place through the variably saturated zone between surface and usually the deep groundwater table. These flood events are characterized by rapid and extreme changes in surface flow depth and velocity and soil moisture conditions. Infiltration rates change over time controlled by the hydraulic gradients and the unsaturated hydraulic conductivity at the surface-subsurface interface. Today is a challenge to assess the spatial and temporal distribution of groundwater recharge from flash flood events under real field conditions at different scales in arid areas. We apply an integrated surface-subsurface variably saturated physically-based flow model at the watershed scale to assess the recharge process during and after a flash flood event registered in an arid fluvial valley in Northern Chile. We are able to reproduce reasonably well observed groundwater levels and surface flow discharges during and after the flood with a calibrated model. We also investigate the magnitude and spatio-temporal distribution of recharge and the response of the system to variations of different surface and subsurface parameters, initial soil moisture content and groundwater table depths and surface flow conditions. We demonstrate how an integrated physically based model allows the exploration of different spatial and temporal system states, and that the analysis of the results of the simulations help us to improve our understanding of the recharge processes in similar type of systems that are common to many arid areas around the world.

Characterizing the Diurnal Cycle of Land Surface Temperature and Evapotranspiration at High Spatial Resolution Using Thermal Observations from sUAS.

NASA Astrophysics Data System (ADS)

Dutta, D.; Drewry, D.; Johnson, W. R.

2017-12-01

The surface temperature of plant canopies is an important indicator of the stomatal regulation of plant water use and the associated water flux from plants to atmosphere (evapotranspiration (ET)). Remotely sensed thermal observations using compact, low-cost, lightweight sensors from small unmanned aerial systems (sUAS) have the potential to provide surface temperature (ST) and ET estimates at unprecedented spatial and temporal resolutions, allowing us to characterize the intra-field diurnal variations in canopy ST and ET for a variety of vegetation systems. However, major challenges exist for obtaining accurate surface temperature estimates from low-cost uncooled microbolometer-type sensors. Here we describe the development of calibration methods using thermal chamber experiments, taking into account the ambient optics and sensor temperatures, and applying simple models of spatial non-uniformity correction to the sensor focal-plane-array. We present a framework that can be used to derive accurate surface temperatures using radiometric observations from low-cost sensors, and demonstrate this framework using a sUAS-mounted sensor across a diverse set of calibration and vegetation targets. Further, we demonstrate the use of the Surface Temperature Initiated Closure (STIC) model for computing spatially explicit, high spatial resolution ET estimates across several well-monitored agricultural systems, as driven by sUAS acquired surface temperatures. STIC provides a physically-based surface energy balance framework for the simultaneous retrieval of the surface and atmospheric vapor conductances and surface energy fluxes, by physically integrating radiometric surface temperature information into the Penman-Monteith equation. Results of our analysis over agricultural systems in Ames, IA and Davis, CA demonstrate the power of this approach for quantifying the intra-field spatial variability in the diurnal cycle of plant water use at sub-meter resolutions.

Surface fluxes and water balance of spatially varying vegetation within a small mountainous headwater catchment

USDA-ARS?s Scientific Manuscript database

Understanding the role of ecosystems in modulating energy, water and carbon fluxes is critical to quantifying the variability in energy, carbon, and water balances across landscapes. This study compares and contrasts the seasonal surface fluxes of sensible heat, latent heat and carbon fluxes measur...

A reanalysis dataset of the South China Sea.

PubMed

Zeng, Xuezhi; Peng, Shiqiu; Li, Zhijin; Qi, Yiquan; Chen, Rongyu

2014-01-01

Ocean reanalysis provides a temporally continuous and spatially gridded four-dimensional estimate of the ocean state for a better understanding of the ocean dynamics and its spatial/temporal variability. Here we present a 19-year (1992-2010) high-resolution ocean reanalysis dataset of the upper ocean in the South China Sea (SCS) produced from an ocean data assimilation system. A wide variety of observations, including in-situ temperature/salinity profiles, ship-measured and satellite-derived sea surface temperatures, and sea surface height anomalies from satellite altimetry, are assimilated into the outputs of an ocean general circulation model using a multi-scale incremental three-dimensional variational data assimilation scheme, yielding a daily high-resolution reanalysis dataset of the SCS. Comparisons between the reanalysis and independent observations support the reliability of the dataset. The presented dataset provides the research community of the SCS an important data source for studying the thermodynamic processes of the ocean circulation and meso-scale features in the SCS, including their spatial and temporal variability.

A reanalysis dataset of the South China Sea

PubMed Central

Zeng, Xuezhi; Peng, Shiqiu; Li, Zhijin; Qi, Yiquan; Chen, Rongyu

2014-01-01

Ocean reanalysis provides a temporally continuous and spatially gridded four-dimensional estimate of the ocean state for a better understanding of the ocean dynamics and its spatial/temporal variability. Here we present a 19-year (1992–2010) high-resolution ocean reanalysis dataset of the upper ocean in the South China Sea (SCS) produced from an ocean data assimilation system. A wide variety of observations, including in-situ temperature/salinity profiles, ship-measured and satellite-derived sea surface temperatures, and sea surface height anomalies from satellite altimetry, are assimilated into the outputs of an ocean general circulation model using a multi-scale incremental three-dimensional variational data assimilation scheme, yielding a daily high-resolution reanalysis dataset of the SCS. Comparisons between the reanalysis and independent observations support the reliability of the dataset. The presented dataset provides the research community of the SCS an important data source for studying the thermodynamic processes of the ocean circulation and meso-scale features in the SCS, including their spatial and temporal variability. PMID:25977803

Spatial heterogeneity of leaf area index across scales from simulation and remote sensing

NASA Astrophysics Data System (ADS)

Reichenau, Tim G.; Korres, Wolfgang; Montzka, Carsten; Schneider, Karl

2016-04-01

Leaf area index (LAI, single sided leaf area per ground area) influences mass and energy exchange of vegetated surfaces. Therefore LAI is an input variable for many land surface schemes of coupled large scale models, which do not simulate LAI. Since these models typically run on rather coarse resolution grids, LAI is often inferred from coarse resolution remote sensing. However, especially in agriculturally used areas, a grid cell of these products often covers more than a single land-use. In that case, the given LAI does not apply to any single land-use. Therefore, the overall spatial heterogeneity in these datasets differs from that on resolutions high enough to distinguish areas with differing land-use. Detailed process-based plant growth models simulate LAI for separate plant functional types or specific species. However, limited availability of observations causes reduced spatial heterogeneity of model input data (soil, weather, land-use). Since LAI is strongly heterogeneous in space and time and since processes depend on LAI in a nonlinear way, a correct representation of LAI spatial heterogeneity is also desirable on coarse resolutions. The current study assesses this issue by comparing the spatial heterogeneity of LAI from remote sensing (RapidEye) and process-based simulations (DANUBIA simulation system) across scales. Spatial heterogeneity is assessed by analyzing LAI frequency distributions (spatial variability) and semivariograms (spatial structure). Test case is the arable land in the fertile loess plain of the Rur catchment near the Germany-Netherlands border.

High resolution modelling of soil moisture patterns with TerrSysMP: A comparison with sensor network data

NASA Astrophysics Data System (ADS)

Gebler, S.; Hendricks Franssen, H.-J.; Kollet, S. J.; Qu, W.; Vereecken, H.

2017-04-01

The prediction of the spatial and temporal variability of land surface states and fluxes with land surface models at high spatial resolution is still a challenge. This study compares simulation results using TerrSysMP including a 3D variably saturated groundwater flow model (ParFlow) coupled to the Community Land Model (CLM) of a 38 ha managed grassland head-water catchment in the Eifel (Germany), with soil water content (SWC) measurements from a wireless sensor network, actual evapotranspiration recorded by lysimeters and eddy covariance stations and discharge observations. TerrSysMP was discretized with a 10 × 10 m lateral resolution, variable vertical resolution (0.025-0.575 m), and the following parameterization strategies of the subsurface soil hydraulic parameters: (i) completely homogeneous, (ii) homogeneous parameters for different soil horizons, (iii) different parameters for each soil unit and soil horizon and (iv) heterogeneous stochastic realizations. Hydraulic conductivity and Mualem-Van Genuchten parameters in these simulations were sampled from probability density functions, constructed from either (i) soil texture measurements and Rosetta pedotransfer functions (ROS), or (ii) estimated soil hydraulic parameters by 1D inverse modelling using shuffle complex evolution (SCE). The results indicate that the spatial variability of SWC at the scale of a small headwater catchment is dominated by topography and spatially heterogeneous soil hydraulic parameters. The spatial variability of the soil water content thereby increases as a function of heterogeneity of soil hydraulic parameters. For lower levels of complexity, spatial variability of the SWC was underrepresented in particular for the ROS-simulations. Whereas all model simulations were able to reproduce the seasonal evapotranspiration variability, the poor discharge simulations with high model bias are likely related to short-term ET dynamics and the lack of information about bedrock characteristics and an on-site drainage system in the uncalibrated model. In general, simulation performance was better for the SCE setups. The SCE-simulations had a higher inverse air entry parameter resulting in SWC dynamics in better correspondence with data than the ROS simulations during dry periods. This illustrates that small scale measurements of soil hydraulic parameters cannot be transferred to the larger scale and that interpolated 1D inverse parameter estimates result in an acceptable performance for the catchment.

Scales of snow depth variability in high elevation rangeland sagebrush

NASA Astrophysics Data System (ADS)

Tedesche, Molly E.; Fassnacht, Steven R.; Meiman, Paul J.

2017-09-01

In high elevation semi-arid rangelands, sagebrush and other shrubs can affect transport and deposition of wind-blown snow, enabling the formation of snowdrifts. Datasets from three field experiments were used to investigate the scales of spatial variability of snow depth around big mountain sagebrush ( Artemisia tridentata Nutt.) at a high elevation plateau rangeland in North Park, Colorado, during the winters of 2002, 2003, and 2008. Data were collected at multiple resolutions (0.05 to 25 m) and extents (2 to 1000 m). Finer scale data were collected specifically for this study to examine the correlation between snow depth, sagebrush microtopography, the ground surface, and the snow surface, as well as the temporal consistency of snow depth patterns. Variograms were used to identify the spatial structure and the Moran's I statistic was used to determine the spatial correlation. Results show some temporal consistency in snow depth at several scales. Plot scale snow depth variability is partly a function of the nature of individual shrubs, as there is some correlation between the spatial structure of snow depth and sagebrush, as well as between the ground and snow depth. The optimal sampling resolution appears to be 25-cm, but over a large area, this would require a multitude of samples, and thus a random stratified approach is recommended with a fine measurement resolution of 5-cm.

Observed and simulated hydrologic response for a first-order catchment during extreme rainfall 3 years after wildfire disturbance

USGS Publications Warehouse

Ebel, Brian A.; Rengers, Francis K.; Tucker, Gregory E.

2016-01-01

Hydrologic response to extreme rainfall in disturbed landscapes is poorly understood because of the paucity of measurements. A unique opportunity presented itself when extreme rainfall in September 2013 fell on a headwater catchment (i.e., <1 ha) in Colorado, USA that had previously been burned by a wildfire in 2010. We compared measurements of soil-hydraulic properties, soil saturation from subsurface sensors, and estimated peak runoff during the extreme rainfall with numerical simulations of runoff generation and subsurface hydrologic response during this event. The simulations were used to explore differences in runoff generation between the wildfire-affected headwater catchment, a simulated unburned case, and for uniform versus spatially variable parameterizations of soil-hydraulic properties that affect infiltration and runoff generation in burned landscapes. Despite 3 years of elapsed time since the 2010 wildfire, observations and simulations pointed to substantial surface runoff generation in the wildfire-affected headwater catchment by the infiltration-excess mechanism while no surface runoff was generated in the unburned case. The surface runoff generation was the result of incomplete recovery of soil-hydraulic properties in the burned area, suggesting recovery takes longer than 3 years. Moreover, spatially variable soil-hydraulic property parameterizations produced longer duration but lower peak-flow infiltration-excess runoff, compared to uniform parameterization, which may have important hillslope sediment export and geomorphologic implications during long duration, extreme rainfall. The majority of the simulated surface runoff in the spatially variable cases came from connected near-channel contributing areas, which was a substantially smaller contributing area than the uniform simulations.

Estimating net solar radiation using Landsat Thematic Mapper and digital elevation data

NASA Technical Reports Server (NTRS)

Dubayah, R.

1992-01-01

A radiative transfer algorithm is combined with digital elevation and satellite reflectance data to model spatial variability in net solar radiation at fine spatial resolution. The method is applied to the tall-grass prairie of the 16 x 16 sq km FIFE site (First ISLSCP Field Experiment) of the International Satellite Land Surface Climatology Project. Spectral reflectances as measured by the Landsat Thematic Mapper (TM) are corrected for atmospheric and topographic effects using field measurements and accurate 30-m digital elevation data in a detailed model of atmosphere-surface interaction. The spectral reflectances are then integrated to produce estimates of surface albedo in the range 0.3-3.0 microns. This map of albedo is used in an atmospheric and topographic radiative transfer model to produce a map of net solar radiation. A map of apparent net solar radiation is also derived using only the TM reflectance data, uncorrected for topography, and the average field-measured downwelling solar irradiance. Comparison with field measurements at 10 sites on the prairie shows that the topographically derived radiation map accurately captures the spatial variability in net solar radiation, but the apparent map does not.

Hydrologic Remote Sensing and Land Surface Data Assimilation.

PubMed

Moradkhani, Hamid

2008-05-06

Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface-atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF) and Particle filter (PF), for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law) and could be a strong alternative to EnKF which is subject to some limitations including the linear updating rule and assumption of jointly normal distribution of errors in state variables and observation.

Spatial variability and landscape controls of near-surface permafrost within the Alaskan Yukon River Basin

USGS Publications Warehouse

Pastick, Neal J.; Jorgenson, M. Torre; Wylie, Bruce K.; Rose, Joshua R.; Rigge, Matthew; Walvoord, Michelle Ann

2014-01-01

The distribution of permafrost is important to understand because of permafrost's influence on high-latitude ecosystem structure and functions. Moreover, near-surface (defined here as within 1 m of the Earth's surface) permafrost is particularly susceptible to a warming climate and is generally poorly mapped at regional scales. Subsequently, our objectives were to (1) develop the first-known binary and probabilistic maps of near-surface permafrost distributions at a 30 m resolution in the Alaskan Yukon River Basin by employing decision tree models, field measurements, and remotely sensed and mapped biophysical data; (2) evaluate the relative contribution of 39 biophysical variables used in the models; and (3) assess the landscape-scale factors controlling spatial variations in permafrost extent. Areas estimated to be present and absent of near-surface permafrost occupy approximately 46% and 45% of the Alaskan Yukon River Basin, respectively; masked areas (e.g., water and developed) account for the remaining 9% of the landscape. Strong predictors of near-surface permafrost include climatic indices, land cover, topography, and Landsat 7 Enhanced Thematic Mapper Plus spectral information. Our quantitative modeling approach enabled us to generate regional near-surface permafrost maps and provide essential information for resource managers and modelers to better understand near-surface permafrost distribution and how it relates to environmental factors and conditions.

Global Variability and Changes in Ocean Total Alkalinity from Aquarius Satellite

NASA Astrophysics Data System (ADS)

Fine, R. A.; Willey, D. A.; Millero, F. J., Jr.

2016-02-01

To document effects of ocean acidification it is important to have an understanding of the processes and parameters that influence alkalinity. Alkalinity is a gauge on the ability of seawater to neutralize acids. We use Aquarius satellite data, which allow unprecedented global mapping of surface total alkalinity as it correlates strongly with salinity and to a lesser extent with temperature. Spatial variability in total alkalinity and salinity exceed temporal variability, the latter includes seasonal and differences compared to climatological data. The northern hemisphere has more spatial and monthly variability in total alkalinity and salinity, while less variability in Southern Ocean alkalinity is due to less salinity variability and upwelling of waters enriched in alkalinity. Satellite alkalinity data are providing a global baseline that can be used for comparing with future carbon data, and for evaluating spatial and temporal variability and past trends. For the first time it is shown that recent satellite derived total alkalinity in the subtropics have increased as compared with climatological data; this is reflective of large scale changes in the global water cycle. Total alkalinity increases imply increased dissolution of calcareous minerals and difficulty for calcifying organisms to make their shells.

Spatial variability in the response of surface-water extent to climate extremes across the Prairie Pothole Region and adjacent Northern Prairie, United States

NASA Astrophysics Data System (ADS)

Vanderhoof, M.; Lane, C.; McManus, M.; Alexander, L. C.; Christensen, J.

2017-12-01

Surface-water extent, duration and movement will depend not only on climatic inputs but also the relative importance of different hydrologic pathways (e.g., surface storage, infiltration, evapotranspiration, stream outflows). We mapped surface-water extent from historic drought years to historic wet years spanning 1985 - 2015 across eleven Landsat path/rows representing the Prairie Pothole Region (PPR) and adjacent Northern Prairie of the United States. The PPR not only experienced a greater surface water extent under median conditions (2.6 times more) relative to the adjacent Northern Prairie, but showed a greater difference between drought and deluge conditions as well (range averaged 8.5 ha surface water km-2 relative to 2.5 ha surface water km-2 for the PPR and Northern Prairie, respectively). To explain the spatial variability in the amount of surface water expansion and contraction we used a two-stage modeling approach. First, surface-water extent was regressed on accumulated water availability (precipitation minus potential evapotranspiration). The slope of surface-water extent to climate inputs (per watershed) was our dependent variable in the second stage. That slope was regressed against independent variables representing hydrology-related landscape characteristics (e.g., infiltration capacity, surface storage capacity, stream density). Stream-connected surface water can leave via stream flow, influencing the rate at which surface-water may leave a location, therefore stream-connected and disconnected surface water were analyzed separately. Stream-connected surface water responded more strongly to wetter climatic conditions (i.e., accumulated) in landscapes with more lakes and less artificial drainage (e.g., ditching, tile drainage). Disconnected surface water responded more strongly to wetter climatic conditions when landscapes contained greater wetland density, fewer streams and a lower predicted rate of infiltration. From these findings, we can expect that the relationship between upstream and downstream waters will require consideration of hydrology-related landscape characteristics, and that climate-change related shifts in precipitation and evaporative demand will have an uneven effect on surface water expansion and contraction across the landscape.

Integrating satellite remote sensing data and field data to predict rangeland structural indicators at the continental scale

NASA Astrophysics Data System (ADS)

Zhang, J.; Okin, G.

2016-12-01

Rangelands provide a variety of important ecosystem goods and services across drylands globally. They are also the most important emitters of dust across the globe. Field data collection based on points does not represent spatially continuous information about surface variables and, given the vast size of the world's rangelands, cannot cover even a small fraction of their area. Remote sensing is potentially a labor- and time-saving method to observe important rangeland vegetation variables at both temporal and spatial scales. Information on vegetation cover, bare gap size, and plant height provide key rangeland vegetation variables in arid and semiarid rangelands, in part because they strongly impact dust emission and determine wildlife habitat characteristics. This study reports on relationships between remote sensing in the reflected solar spectrum and field measures related to these three variables, and shows how these relationships can be extended to produce spatially and temporally continuous datasets coupled with quantitative estimates of error. Field data for this study included over 3,800 Assessment, Inventory, and Monitoring (AIM) measurements on Bureau of Land Management (BLM) lands throughout the western US. Remote sensing data were derived from MODIS nadir BRDF-adjusted reflectance (NBAR) and Landsat 8 OLI surface reflectance. Normalized bare gap size, total foliar cover, herbaceous cover and herbaceous height exhibit the greatest predictability from remote sensing variables with physically-reasonable relationships between remote sensing variables and field measures. Data fields produced using these relationships across the western US exhibit good agreement with independent high-resolution imagery.

Validation of Satellite Retrieved Land Surface Variables

NASA Technical Reports Server (NTRS)

Lakshmi, Venkataraman; Susskind, Joel

1999-01-01

The effective use of satellite observations of the land surface is limited by the lack of high spatial resolution ground data sets for validation of satellite products. Recent large scale field experiments include FIFE, HAPEX-Sahel and BOREAS which provide us with data sets that have large spatial coverage and long time coverage. It is the objective of this paper to characterize the difference between the satellite estimates and the ground observations. This study and others along similar lines will help us in utilization of satellite retrieved data in large scale modeling studies.

Spatial prediction of near surface soil water retention functions using hydrogeophysics

NASA Astrophysics Data System (ADS)

Gibson, J. P.; Franz, T. E.

2017-12-01

The hydrological community often turns to widely available spatial datasets such as SSURGO to characterize the spatial variability of soil across a landscape of interest. This has served as a reasonable first approximation when lacking localized soil data. However, previous work has shown that information loss within land surface models primarily stems from parameterization. Localized soil sampling is both expensive and time intense, and thus a need exists in connecting spatial datasets with ground observations. Given that hydrogeophysics is data-dense, rapid, and relatively easy to adopt, it is a promising technique to help dovetail localized soil sampling with larger spatial datasets. In this work, we utilize 2 geophysical techniques; cosmic ray neutron probe and electromagnetic induction, to identify temporally stable soil moisture patterns. This is achieved by measuring numerous times over a range of wet to dry field conditions in order to apply an empirical orthogonal function. We then present measured water retention functions of shallow cores extracted within each temporally stable zone. Lastly, we use soil moisture patterns as a covariate to predict soil hydraulic properties in areas without measurement and validate using a leave-one-out cross validation analysis. Using these approaches to better constrain soil hydraulic property variability, we speculate that further research can better estimate hydrologic fluxes in areas of interest.

Wind-driven Ocean Circulation and the Spatial-temporal Variability of Dissolved Inorganic Carbon in the Gulf of Tehuantepec, North Eastern Tropical Pacific

NASA Astrophysics Data System (ADS)

Chapa, C.; Beier, E.; Durazo, R.; Martin Hernandez-Ayon, J. M.; Alin, S. R.; Lopez-Perez, A.

2016-12-01

The relationship between the surface enrichment of dissolved inorganic carbon (DIC) and wind variability and circulation in the Gulf of Tehuantepec (GT) was examined from satellite images and in situ data from three cruises (June 2010; April and November 2013). Monthly mean wind climatologies (and derived variables), sea surface temperature and sea surface height anomaly fields were analyzed in the GT and part of the NETP. Signal decomposition according to circulation scales (seasonal, inter-annual, mesoscale) was performed using harmonic analysis for the seasonal components, and empirical orthogonal functions for the residuals, applied to satellite sea-level anomaly data. The results show that wind is the main driving force of the variability in the GT. Mesoscale is the variable with the highest percent of local variance (25-75%), due mainly to mesoscale eddies, followed by seasonality (20-55%), and finally the inter-annual signal (10-30%), dominated by ENSO. Mesoscale and seasonality prevailed during the samplings. The changes in circulation led to variations in the concentration of surface DIC ranging between 100 and 300 µmol kg-1 (436 µatm) due to Ekman pumping. The largest enrichment occurred in November 2013 after a strong northerly wind event. However, the predominance of mesoscale events suggests that changes in dissolved inorganic carbon resulting from mesoscale- derived Ekman pumping may become important in the long term and with a larger spatial and temporal coverage. The results suggest that the seasonal cycle of dissolved inorganic carbon may be linked to wind seasonality.

Cross-scale modeling of surface temperature and tree seedling establishment inmountain landscapes

USGS Publications Warehouse

Dingman, John; Sweet, Lynn C.; McCullough, Ian M.; Davis, Frank W.; Flint, Alan L.; Franklin, Janet; Flint, Lorraine E.

2013-01-01

Abstract: Introduction: Estimating surface temperature from above-ground field measurements is important for understanding the complex landscape patterns of plant seedling survival and establishment, processes which occur at heights of only several centimeters. Currently, future climate models predict temperature at 2 m above ground, leaving ground-surface microclimate not well characterized. Methods: Using a network of field temperature sensors and climate models, a ground-surface temperature method was used to estimate microclimate variability of minimum and maximum temperature. Temperature lapse rates were derived from field temperature sensors and distributed across the landscape capturing differences in solar radiation and cold air drainages modeled at a 30-m spatial resolution. Results: The surface temperature estimation method used for this analysis successfully estimated minimum surface temperatures on north-facing, south-facing, valley, and ridgeline topographic settings, and when compared to measured temperatures yielded an R2 of 0.88, 0.80, 0.88, and 0.80, respectively. Maximum surface temperatures generally had slightly more spatial variability than minimum surface temperatures, resulting in R2 values of 0.86, 0.77, 0.72, and 0.79 for north-facing, south-facing, valley, and ridgeline topographic settings. Quasi-Poisson regressions predicting recruitment of Quercus kelloggii (black oak) seedlings from temperature variables were significantly improved using these estimates of surface temperature compared to air temperature modeled at 2 m. Conclusion: Predicting minimum and maximum ground-surface temperatures using a downscaled climate model coupled with temperature lapse rates estimated from field measurements provides a method for modeling temperature effects on plant recruitment. Such methods could be applied to improve projections of species’ range shifts under climate change. Areas of complex topography can provide intricate microclimates that may allow species to redistribute locally as climate changes.

In Situ Global Sea Surface Salinity and Variability from the NCEI Global Thermosalinograph Database

NASA Astrophysics Data System (ADS)

Wang, Z.; Boyer, T.; Zhang, H. M.

2017-12-01

Sea surface salinity (SSS) plays an important role in the global ocean circulations. The variations of sea surface salinity are key indicators of changes in air-sea water fluxes. Using nearly 30 years of in situ measurements of sea surface salinity from thermosalinographs, we will evaluate the variations of the sea surface salinity in the global ocean. The sea surface salinity data used are from our newly-developed NCEI Global Thermosalinograph Database - NCEI-TSG. This database provides a comprehensive set of quality-controlled in-situ sea-surface salinity and temperature measurements collected from over 340 vessels during the period 1989 to the present. The NCEI-TSG is the world's most complete TSG dataset, containing all data from the different TSG data assembly centers, e.g. COAPS (SAMOS), IODE (GOSUD) and AOML, with more historical data from NCEI's archive to be added. Using this unique dataset, we will investigate the spatial variations of the global SSS and its variability. Annual and interannual variability will also be studied at selected regions.

EMI-Sensor Data to Identify Areas of Manure Accumulation on a Feedlot Surface

USDA-ARS?s Scientific Manuscript database

A study was initiated to test the validity of using electromagnetic induction (EMI) survey data, a prediction-based sampling strategy and ordinary linear regression modeling to predict spatially variable feedlot surface manure accumulation. A 30 m × 60 m feedlot pen with a central mound was selecte...

The advantages, and challenges, in using multiple techniques in the estimation of surface water-groundwater fluxes.

NASA Astrophysics Data System (ADS)

Shanafield, M.; Cook, P. G.

2014-12-01

When estimating surface water-groundwater fluxes, the use of complimentary techniques helps to fill in uncertainties in any individual method, and to potentially gain a better understanding of spatial and temporal variability in a system. It can also be a way of preventing the loss of data during infrequent and unpredictable flow events. For example, much of arid Australia relies on groundwater, which is recharged by streamflow through ephemeral streams during flood events. Three recent surface water/groundwater investigations from arid Australian systems provide good examples of how using multiple field and analysis techniques can help to more fully characterize surface water-groundwater fluxes, but can also result in conflicting values over varying spatial and temporal scales. In the Pilbara region of Western Australia, combining streambed radon measurements, vertical heat transport modeling, and a tracer test helped constrain very low streambed residence times, which are on the order of minutes. Spatial and temporal variability between the methods yielded hyporheic exchange estimates between 10-4 m2 s-1 and 4.2 x 10-2 m2 s-1. In South Australia, three-dimensional heat transport modeling captured heterogeneity within 20 square meters of streambed, identifying areas of sandy soil (flux rates of up to 3 m d-1) and clay (flux rates too slow to be accurately characterized). Streamflow front modeling showed similar flux rates, but averaged over 100 m long stream segments for a 1.6 km reach. Finally, in central Australia, several methods are used to decipher whether any of the flow down a highly ephemeral river contributes to regional groundwater recharge, showing that evaporation and evapotranspiration likely accounts for all of the infiltration into the perched aquifer. Lessons learned from these examples demonstrate the influences of the spatial and temporal variability between techniques on estimated fluxes.

Spatial regression models of park and land-use impacts on the urban heat island in central Beijing.

PubMed

Dai, Zhaoxin; Guldmann, Jean-Michel; Hu, Yunfeng

2018-06-01

Understanding the relationship between urban land structure and land surface temperatures (LST) is important for mitigating the urban heat island (UHI). This paper explores this relationship within central Beijing, an area located within the 2nd Ring Road. The urban variables include the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Build-up Index (NDBI), the area of building footprints, the area of main roads, the area of water bodies and a gravity index for parks that account for both park size and distance. The data are captured over 8 grids of square cells (30 m, 60 m, 90 m, 120 m, 150 m, 180 m, 210 m, 240 m). The research involves: (1) estimating land surface temperatures using Landsat 8 satellite imagery, (2) building the database of urban variables, and (3) conducting regression analyses. The results show that (1) all the variables impact surface temperatures, (2) spatial regressions are necessary to capture neighboring effects, and (3) higher-order polynomial functions are more suitable for capturing the effects of NDVI and NDBI. Copyright © 2018 Elsevier B.V. All rights reserved.

Land surface dynamics monitoring using microwave passive satellite sensors

NASA Astrophysics Data System (ADS)

Guijarro, Lizbeth Noemi

Soil moisture, surface temperature and vegetation are variables that play an important role in our environment. There is growing demand for accurate estimation of these geophysical parameters for the research of global climate models (GCMs), weather, hydrological and flooding models, and for the application to agricultural assessment, land cover change, and a wide variety of other uses that meet the needs for the study of our environment. The different studies covered in this dissertation evaluate the capabilities and limitations of microwave passive sensors to monitor land surface dynamics. The first study evaluates the 19 GHz channel of the SSM/I instrument with a radiative transfer model and in situ datasets from the Illinois stations and the Oklahoma Mesonet to retrieve land surface temperature and surface soil moisture. The surface temperatures were retrieved with an average error of 5 K and the soil moisture with an average error of 6%. The results show that the 19 GHz channel can be used to qualitatively predict the spatial and temporal variability of surface soil moisture and surface temperature at regional scales. In the second study, in situ observations were compared with sensor observations to evaluate aspects of low and high spatial resolution at multiple frequencies with data collected from the Southern Great Plains Experiment (SGP99). The results showed that the sensitivity to soil moisture at each frequency is a function of wavelength and amount of vegetation. The results confirmed that L-band is more optimal for soil moisture, but each sensor can provide soil moisture information if the vegetation water content is low. The spatial variability of the emissivities reveals that resolution suffers considerably at higher frequencies. The third study evaluates C- and X-bands of the AMSR-E instrument. In situ datasets from the Soil Moisture Experiments (SMEX03) in South Central Georgia were utilized to validate the AMSR-E soil moisture product and to derive surface soil moisture with a radiative transfer model. The soil moisture was retrieved with an average error of 2.7% at X-band and 6.7% at C-band. The AMSR-E demonstrated its ability to successfully infer soil moisture during the SMEX03 experiment.

Sea level: measuring the bounding surfaces of the ocean

PubMed Central

Tamisiea, Mark E.; Hughes, Chris W.; Williams, Simon D. P.; Bingley, Richard M.

2014-01-01

The practical need to understand sea level along the coasts, such as for safe navigation given the spatially variable tides, has resulted in tide gauge observations having the distinction of being some of the longest instrumental ocean records. Archives of these records, along with geological constraints, have allowed us to identify the century-scale rise in global sea level. Additional data sources, particularly satellite altimetry missions, have helped us to better identify the rates and causes of sea-level rise and the mechanisms leading to spatial variability in the observed rates. Analysis of all of the data reveals the need for long-term and stable observation systems to assess accurately the regional changes as well as to improve our ability to estimate future changes in sea level. While information from many scientific disciplines is needed to understand sea-level change, this review focuses on contributions from geodesy and the role of the ocean's bounding surfaces: the sea surface and the Earth's crust. PMID:25157196

Use of Seafloor Electromagnetic and Acoustic Backscatter Data for Seafloor Classification: An Example From Martha's Vineyard, Massachusetts.

NASA Astrophysics Data System (ADS)

Evans, R. L.; Kraft, B.; Mayer, L.

2006-12-01

Near surface offshore geophysical data allow sediment classification in coastal settings at high levels of spatial detail. We present data from offshore Martha's Vineyard, Massachusetts collected as part of the Office of Naval Researchś Mine Burial Prediction program. Seafloor electromagnetic data provide estimates of near surface porosity at approximately 10m intervals along each tow-line. In addition, the area has undergone repeat surveys with high resolution acoustic backscatter and bathymetry. In some locations, the geophysical data has been groundtruthed by grab sampling and coring. We examine the spatial variability in near surface sediment properties on the basis of the geophysical data. The EM data are particularly well suited to constructing semi-variograms to display length scales of variability. Preliminary examination does not show any obvious correlation between the EM data and acoustic backscatter, however, further processing of the backscatter is being carried out and so this result is tentative.

Thaw depth spatial and temporal variability at the Limnopolar Lake CALM-S site, Byers Peninsula, Livingston Island, Antarctica.

PubMed

de Pablo, M A; Ramos, M; Molina, A; Prieto, M

2018-02-15

A new Circumpolar Active Layer Monitoring (CALM) site was established in 2009 at the Limnopolar Lake watershed in Byers Peninsula, Livingston Island, Antarctica, to provide a node in the western Antarctic Peninsula, one of the regions that recorded the highest air temperature increase in the planet during the last decades. The first detailed analysis of the temporal and spatial evolution of the thaw depth at the Limnopolar Lake CALM-S site is presented here, after eight years of monitoring. The average values range between 48 and 29cm, decreasing at a ratio of 16cm/decade. The annual thaw depth observations in the 100×100 m CALM grid are variable (Variability Index of 34 to 51%), although both the Variance Coefficient and the Climate Matrix Analysis Residual point to the internal consistency of the data. Those differences could be explained then by the terrain complexity and node-specific variability due to the ground properties. The interannual variability was about 60% during 2009-2012, increasing to 124% due to the presence of snow in 2013, 2015 and 2016. The snow has been proposed here as one of the most important factors controlling the spatial variability of ground thaw depth, since its values correlate with the snow thickness but also with the ground surface temperature and unconfined compression resistance, as measured in 2010. The topography explains the thaw depth spatial distribution pattern, being related to snowmelt water and its accumulation in low-elevation areas (downslope-flow). Patterned grounds and other surface features correlate well with high thaw depth patterns as well. The edaphic factor (E=0.05842m 2 /°C·day; R 2 =0.63) is in agreement with other permafrost environments, since frozen index (F>0.67) and MAAT (<-2°C) denote a continuous permafrost existence in the area. All these characteristics provided the basis for further comparative analyses between others nearby CALM sites. Copyright © 2017 Elsevier B.V. All rights reserved.

Soil Moisture fusion across scales using a multiscale nonstationary Spatial Hierarchical Model

NASA Astrophysics Data System (ADS)

Kathuria, D.; Mohanty, B.; Katzfuss, M.

2017-12-01

Soil moisture (SM) datasets from remote sensing (RS) platforms (such as SMOS and SMAP) and reanalysis products from land surface models are typically available on a coarse spatial granularity of several square km. Ground based sensors, on the other hand, provide observations on a finer spatial scale (meter scale or less) but are sparsely available. SM is affected by high variability due to complex interactions between geologic, topographic, vegetation and atmospheric variables and these interactions change dynamically with footprint scales. Past literature has largely focused on the scale specific effect of these covariates on soil moisture. The present study proposes a robust Multiscale-Nonstationary Spatial Hierarchical Model (MN-SHM) which can assimilate SM from point to RS footprints. The spatial structure of SM across footprints is modeled by a class of scalable covariance functions whose nonstationary depends on atmospheric forcings (such as precipitation) and surface physical controls (such as topography, soil-texture and vegetation). The proposed model is applied to fuse point and airborne ( 1.5 km) SM data obtained during the SMAPVEX12 campaign in the Red River watershed in Southern Manitoba, Canada with SMOS ( 30km) data. It is observed that precipitation, soil-texture and vegetation are the dominant factors which affect the SM distribution across various footprint scales (750 m, 1.5 km, 3 km, 9 km,15 km and 30 km). We conclude that MN-SHM handles the change of support problems easily while retaining reasonable predictive accuracy across multiple spatial resolutions in the presence of surface heterogeneity. The MN-SHM can be considered as a complex non-stationary extension of traditional geostatistical prediction methods (such as Kriging) for fusing multi-platform multi-scale datasets.

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

Hammond, Glenn Edward; Yang, Xiaofan; Song, Xuehang

The groundwater-surface water interaction zone (GSIZ) plays an important role in riverine and watershed ecosystems as the exchange of waters of variable composition and temperature (hydrologic exchange flows) stimulate microbial activity and associated biogeochemical reactions. Variable temporal and spatial scales of hydrologic exchange flows, heterogeneity of the subsurface environment, and complexity of biogeochemical reaction networks in the GSIZ present challenges to incorporation of fundamental process representations and model parameterization across a range of spatial scales (e.g. from pore-scale to field scale). This paper presents a novel hybrid multiscale simulation approach that couples hydrologic-biogeochemical (HBGC) processes between two distinct length scalesmore » of interest.« less

Partitioning the impacts of spatial and climatological rainfall variability in urban drainage modeling

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

2017-03-01

The performance of urban drainage systems is typically examined using hydrological and hydrodynamic models where rainfall input is uniformly distributed, i.e., derived from a single or very few rain gauges. When models are fed with a single uniformly distributed rainfall realization, the response of the urban drainage system to the rainfall variability remains unexplored. The goal of this study was to understand how climate variability and spatial rainfall variability, jointly or individually considered, affect the response of a calibrated hydrodynamic urban drainage model. A stochastic spatially distributed rainfall generator (STREAP - Space-Time Realizations of Areal Precipitation) was used to simulate many realizations of rainfall for a 30-year period, accounting for both climate variability and spatial rainfall variability. The generated rainfall ensemble was used as input into a calibrated hydrodynamic model (EPA SWMM - the US EPA's Storm Water Management Model) to simulate surface runoff and channel flow in a small urban catchment in the city of Lucerne, Switzerland. The variability of peak flows in response to rainfall of different return periods was evaluated at three different locations in the urban drainage network and partitioned among its sources. The main contribution to the total flow variability was found to originate from the natural climate variability (on average over 74 %). In addition, the relative contribution of the spatial rainfall variability to the total flow variability was found to increase with longer return periods. This suggests that while the use of spatially distributed rainfall data can supply valuable information for sewer network design (typically based on rainfall with return periods from 5 to 15 years), there is a more pronounced relevance when conducting flood risk assessments for larger return periods. The results show the importance of using multiple distributed rainfall realizations in urban hydrology studies to capture the total flow variability in the response of the urban drainage systems to heavy rainfall events.

Linking Surface and Subsurface Processes: Implications for Seismic Hazards in Southern California

NASA Astrophysics Data System (ADS)

Lin, J. C.; Moon, S.; Yong, A.; Meng, L.; Martin, A. J.; Davis, P. M.

2017-12-01

Earth's surface and subsurface processes such as bedrock weathering, soil production, and river incision can influence and be influenced by spatial variations in the mechanical strength of surface material. Mechanically weakened rocks tend to have reduced seismic velocity, which can result in larger ground-motion amplification and greater potential for earthquake-induced damages. However, the influence and extent of surface and subsurface processes on the mechanical strength of surface material and seismic site conditions in southern California remain unclear. In this study, we examine whether physics-based models of surface and subsurface processes can explain the spatial variability and non-linearity of near-surface seismic velocity in southern California. We use geophysical measurements (Yong et al., 2013; Ancheta et al., 2014), consisting of shear-wave velocity (Vs) tomography data, Vs profiles, and the time-averaged Vs in the upper 30 m of the crust (Vs30) to infer lateral and vertical variations of surface material properties. Then, we compare Vs30 values with geologic and topographic attributes such as rock type, slope, elevation, and local relief, as well as metrics for surface processes such as soil production and bedrock weathering from topographic stress, frost cracking, chemical reactions, and vegetation presence. Results from this study will improve our understanding of physical processes that control subsurface material properties and their influences on local variability in seismic site conditions.

Minimizing the Standard Deviation of Spatially Averaged Surface Cross-Sectional Data from the Dual-Frequency Precipitation Radar

NASA Technical Reports Server (NTRS)

Meneghini, Robert; Kim, Hyokyung

2016-01-01

For an airborne or spaceborne radar, the precipitation-induced path attenuation can be estimated from the measurements of the normalized surface cross section, sigma 0, in the presence and absence of precipitation. In one implementation, the mean rain-free estimate and its variability are found from a lookup table (LUT) derived from previously measured data. For the dual-frequency precipitation radar aboard the global precipitation measurement satellite, the nominal table consists of the statistics of the rain-free 0 over a 0.5 deg x 0.5 deg latitude-longitude grid using a three-month set of input data. However, a problem with the LUT is an insufficient number of samples in many cells. An alternative table is constructed by a stepwise procedure that begins with the statistics over a 0.25 deg x 0.25 deg grid. If the number of samples at a cell is too few, the area is expanded, cell by cell, choosing at each step that cell that minimizes the variance of the data. The question arises, however, as to whether the selected region corresponds to the smallest variance. To address this question, a second type of variable-averaging grid is constructed using all possible spatial configurations and computing the variance of the data within each region. Comparisons of the standard deviations for the fixed and variable-averaged grids are given as a function of incidence angle and surface type using a three-month set of data. The advantage of variable spatial averaging is that the average standard deviation can be reduced relative to the fixed grid while satisfying the minimum sample requirement.

Mapping Spatial Variability in Health and Wealth Indicators in Accra, Ghana Using High Spatial Resolution Imagery

NASA Astrophysics Data System (ADS)

Engstrom, R.; Ashcroft, E.

2014-12-01

There has been a tremendous amount of research conducted that examines disparities in health and wealth of persons between urban and rural areas however, relatively little research has been undertaken to examine variations within urban areas. A major limitation to elucidating differences with urban areas is the lack of social and demographic data at a sufficiently high spatial resolution to determine these differences. Generally the only available data that contain this information are census data which are collected at most every ten years and are often difficult to obtain at a high enough spatial resolution to allow for examining in depth variability in health and wealth indicators at high spatial resolutions, especially in developing countries. High spatial resolution satellite imagery may be able to provide timely and synoptic information that is related to health and wealth variability within a city. In this study we use two dates of Quickbird imagery (2003 and 2010) classified into the vegetation-impervious surface-soil (VIS) model introduced by Ridd (1995). For 2003 we only have partial coverage of the city, while for 2010 we have a mosaic, which covers the entire city of Accra, Ghana. Variations in the VIS values represent the physical variations within the city and these are compared to variations in economic, and/or sociodemographic data derived from the 2000 Ghanaian census at two spatial resolutions, the enumeration area (approximately US Census Tract) and the neighborhood for the city. Results indicate a significant correlation between both vegetation and impervious surface to type of cooking fuel used in the household, population density, housing density, availability of sewers, cooking space usage, and other variables. The correlations are generally stronger at the neighborhood level and the relationships are stable through time and space. Overall, the results indicate that information derived from high resolution satellite data is related to indicators of health and wealth within a developing world city and that the even if the imagery is collected 10 years after the census information, the relationships are still significant.

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data. Part II: Using Maximum Covariance Analysis to Effectively Compare Spatiotemporal Variability of Satellite and AERONET Measured Aerosol Optical Depth

NASA Technical Reports Server (NTRS)

Li, Jing; Carlson, Barbara E.; Lacis, Andrew A.

2014-01-01

Moderate Resolution Imaging SpectroRadiometer (MODIS) and Multi-angle Imaging Spectroradiomater (MISR) provide regular aerosol observations with global coverage. It is essential to examine the coherency between space- and ground-measured aerosol parameters in representing aerosol spatial and temporal variability, especially in the climate forcing and model validation context. In this paper, we introduce Maximum Covariance Analysis (MCA), also known as Singular Value Decomposition analysis as an effective way to compare correlated aerosol spatial and temporal patterns between satellite measurements and AERONET data. This technique not only successfully extracts the variability of major aerosol regimes but also allows the simultaneous examination of the aerosol variability both spatially and temporally. More importantly, it well accommodates the sparsely distributed AERONET data, for which other spectral decomposition methods, such as Principal Component Analysis, do not yield satisfactory results. The comparison shows overall good agreement between MODIS/MISR and AERONET AOD variability. The correlations between the first three modes of MCA results for both MODIS/AERONET and MISR/ AERONET are above 0.8 for the full data set and above 0.75 for the AOD anomaly data. The correlations between MODIS and MISR modes are also quite high (greater than 0.9). We also examine the extent of spatial agreement between satellite and AERONET AOD data at the selected stations. Some sites with disagreements in the MCA results, such as Kanpur, also have low spatial coherency. This should be associated partly with high AOD spatial variability and partly with uncertainties in satellite retrievals due to the seasonally varying aerosol types and surface properties.

Characterization of the spatial variability of channel morphology

USGS Publications Warehouse

Moody, J.A.; Troutman, B.M.

2002-01-01

The spatial variability of two fundamental morphological variables is investigated for rivers having a wide range of discharge (five orders of magnitude). The variables, water-surface width and average depth, were measured at 58 to 888 equally spaced cross-sections in channel links (river reaches between major tributaries). These measurements provide data to characterize the two-dimensional structure of a channel link which is the fundamental unit of a channel network. The morphological variables have nearly log-normal probability distributions. A general relation was determined which relates the means of the log-transformed variables to the logarithm of discharge similar to previously published downstream hydraulic geometry relations. The spatial variability of the variables is described by two properties: (1) the coefficient of variation which was nearly constant (0.13-0.42) over a wide range of discharge; and (2) the integral length scale in the downstream direction which was approximately equal to one to two mean channel widths. The joint probability distribution of the morphological variables in the downstream direction was modelled as a first-order, bivariate autoregressive process. This model accounted for up to 76 per cent of the total variance. The two-dimensional morphological variables can be scaled such that the channel width-depth process is independent of discharge. The scaling properties will be valuable to modellers of both basin and channel dynamics. Published in 2002 John Wiley and Sons, Ltd.

Variability of intertidal foraminferal assemblages in a salt marsh, Oregon, USA

USGS Publications Warehouse

Milker, Yvonne; Horton, Benjamin P.; Nelson, Alan R.; Engelhart, Simon E.; Witter, Robert C.

2015-01-01

We studied 18 sampling stations along a transect to investigate the similarity between live (rose Bengal stained) foraminiferal populations and dead assemblages, their small-scale spatial variations and the distribution of infaunal foraminifera in a salt marsh (Toms Creek marsh) at the upper end of the South Slough arm of the Coos Bay estuary, Oregon, USA. We aimed to test to what extent taphonomic processes, small-scale variability and infaunal distribution influence the accuracy of sea-level reconstructions based on intertidal foraminifera. Cluster analyses have shown that dead assemblages occur in distinct zones with respect to elevation, a prerequisite for using foraminifera as sea-level indicators. Our nonparametric multivariate analysis of variance showed that small-scale spatial variability has only a small influence on live (rose Bengal stained) populations and dead assemblages. The dissimilarity was higher, however, between live (rose Bengal stained) populations in the middle marsh. We observed early diagenetic dissolution of calcareous tests in the dead assemblages. If comparable post-depositional processes and similar minor spatial variability also characterize fossil assemblages, then dead assemblage are the best modern analogs for paleoenvironmental reconstructions. The Toms Creek tidal flat and low marsh vascular plant zones are dominated by Miliammina fusca, the middle marsh is dominated by Balticammina pseudomacrescens and Trochammina inflata, and the high marsh and upland–marsh transition zone are dominated by Trochamminita irregularis. Analysis of infaunal foraminifera showed that most living specimens are found in the surface sediments and the majority of live (rose Bengal stained) infaunal specimens are restricted to the upper 10 cm, but living individuals are found to depths of 50 cm. The dominant infaunal specimens are similar to those in the corresponding surface samples and no species have been found living solely infaunally. The total numbers of infaunal foraminifera are small compared to the total numbers of dead specimens in the surface samples. This suggests that surface samples adequately represent the modern intertidal environment in Toms Creek.

Temporal and spatial patterns of wetland extent influence variability of surface water connectivity in the Prairie Pothole Region, United States

USGS Publications Warehouse

Vanderhoof, Melanie; Alexander, Laurie C.; Todd, Jason

2016-01-01

Context. Quantifying variability in landscape-scale surface water connectivity can help improve our understanding of the multiple effects of wetlands on downstream waterways. Objectives. We examined how wetland merging and the coalescence of wetlands with streams varied both spatially (among ecoregions) and interannually (from drought to deluge) across parts of the Prairie Pothole Region. Methods. Wetland extent was derived over a time series (1990-2011) using Landsat imagery. Changes in landscape-scale connectivity, generated by the physical coalescence of wetlands with other surface water features, were quantified by fusing static wetland and stream datasets with Landsat-derived wetland extent maps, and related to multiple wetness indices. The usage of Landsat allows for decadal-scale analysis, but limits the types of surface water connections that can be detected. Results. Wetland extent correlated positively with the merging of wetlands and wetlands with streams. Wetness conditions, as defined by drought indices and runoff, were positively correlated with wetland extent, but less consistently correlated with measures of surface water connectivity. The degree of wetland-wetland merging was found to depend less on total wetland area or density, and more on climate conditions, as well as the threshold for how wetland/upland was defined. In contrast, the merging of wetlands with streams was positively correlated with stream density, and inversely related to wetland density. Conclusions. Characterizing the degree of surface water connectivity within the Prairie Pothole Region in North America requires consideration of 1) climate-driven variation in wetness conditions and 2) within-region variation in wetland and stream spatial arrangements.

Models of the thermal effects of melt migration at continental interiors, with applications to the Colorado Plateau

NASA Astrophysics Data System (ADS)

Roy, M.; Rios, D.; Cosburn, K.

2017-12-01

Shear between the moving lithosphere and the underlying asthenospheric mantle can produce dynamic pressure gradients that control patterns of melt migration by percolative flow. Within continental interiors these pressure gradients may be large enough to focus melt migration into zones of low dynamic pressure and thus influence the surface distribution of magmatism. We build upon previous work to show that for a lithospheric keel that protrudes into the "mantle wind," spatially-variable melt migration can lead to spatially-variable thermal weakening of the lithosphere. Our models treat advective heat transfer in porous flow in the limit that heat transfer between the melt and surrounding matrix dominates over conductive heat transfer within either the melt or the solid alone. The models are parameterized by a heat transfer coefficient that we interpret to be related to the efficiency of heat transfer across the fluid-rock interface, related to the geometry and distribution of porosity. Our models quantitatively assess the viability of spatially variable thermal-weakening caused by melt-migration through continental regions that are characterized by variations in lithospheric thickness. We speculate upon the relevance of this process in producing surface patterns of Cenozoic magmatism and heatflow at the Colorado Plateau in the western US.

Geomorphic control of landscape carbon accumulation

USGS Publications Warehouse

Rosenbloom, N.A.; Harden, J.W.; Neff, J.C.; Schimel, D.S.

2006-01-01

We use the CREEP process-response model to simulate soil organic carbon accumulation in an undisturbed prairie site in Iowa. Our primary objectives are to identify spatial patterns of carbon accumulation, and explore the effect of erosion on basin-scale C accumulation. Our results point to two general findings. First, redistribution of soil carbon by erosion results in a net increase in basin-wide carbon storage relative to a noneroding environment. Landscape-average mean residence times are increased in an eroding landscape owing to the burial/preservation of otherwise labile C. Second, field observations taken along a slope transect may overlook significant intraslope variations in carbon accumulation. Spatial patterns of modeled deep C accumulation are complex. While surface carbon with its relatively short equilibration time is predictable from surface properties, deep carbon is strongly influenced by the landscape's geomorphic and climatic history, resulting in wide spatial variability. Convergence and divergence associated with upland swales and interfluves result in bimodal carbon distributions in upper and mid slopes; variability in carbon storage within modeled mid slopes was as high as simulated differences between erosional shoulders and depositional valley bottoms. The bimodality of mid-slope C variability in the model suggests that a three-dimensional sampling strategy is preferable over the traditional two-dimensional analog or "catena" approach. Copyright 2006 by the American Geophysical Union.

Impacts of Realistic Urban Heating, Part I: Spatial Variability of Mean Flow, Turbulent Exchange and Pollutant Dispersion

NASA Astrophysics Data System (ADS)

Nazarian, Negin; Martilli, Alberto; Kleissl, Jan

2018-03-01

As urbanization progresses, more realistic methods are required to analyze the urban microclimate. However, given the complexity and computational cost of numerical models, the effects of realistic representations should be evaluated to identify the level of detail required for an accurate analysis. We consider the realistic representation of surface heating in an idealized three-dimensional urban configuration, and evaluate the spatial variability of flow statistics (mean flow and turbulent fluxes) in urban streets. Large-eddy simulations coupled with an urban energy balance model are employed, and the heating distribution of urban surfaces is parametrized using sets of horizontal and vertical Richardson numbers, characterizing thermal stratification and heating orientation with respect to the wind direction. For all studied conditions, the thermal field is strongly affected by the orientation of heating with respect to the airflow. The modification of airflow by the horizontal heating is also pronounced for strongly unstable conditions. The formation of the canyon vortices is affected by the three-dimensional heating distribution in both spanwise and streamwise street canyons, such that the secondary vortex is seen adjacent to the windward wall. For the dispersion field, however, the overall heating of urban surfaces, and more importantly, the vertical temperature gradient, dominate the distribution of concentration and the removal of pollutants from the building canyon. Accordingly, the spatial variability of concentration is not significantly affected by the detailed heating distribution. The analysis is extended to assess the effects of three-dimensional surface heating on turbulent transfer. Quadrant analysis reveals that the differential heating also affects the dominance of ejection and sweep events and the efficiency of turbulent transfer (exuberance) within the street canyon and at the roof level, while the vertical variation of these parameters is less dependent on the detailed heating of urban facets.

Apparent Resistivity and Estimated Interaction Potential of Surface Water and Groundwater along Selected Canals and Streams in the Elkhorn-Loup Model Study Area, North-Central Nebraska, 2006-07

USGS Publications Warehouse

Teeple, Andrew; Vrabel, Joseph; Kress, Wade H.; Cannia, James C.

2009-01-01

In 2005, the State of Nebraska adopted new legislation that in part requires local Natural Resources Districts to include the effect of groundwater use on surface-water systems in their groundwater management plan. In response the U.S. Geological Survey, in cooperation with the Upper Elkhorn, Lower Elkhorn, Upper Loup, Lower Loup, Middle Niobrara, Lower Niobrara, Lewis and Clark, and Lower Platte North Natural Resources Districts, did a study during 2006-07 to investigate the surface-water and groundwater interaction within a 79,800-square-kilometer area in north-central Nebraska. To determine how streambed materials affect surface-water and groundwater interaction, surface geophysical and lithologic data were integrated at four sites to characterize the hydrogeologic conditions within the study area. Frequency-domain electromagnetic and waterborne direct- current resistivity profiles were collected to map the near-surface hydrogeologic conditions along sections of Ainsworth Canal near Ainsworth, Nebraska; Mirdan and Geranium Canals near Ord, Nebraska; North Loup River near Ord, Nebraska; and Middle Loup River near Thedford, Nebraska. Lithologic data were collected from test holes at each site to aid interpretation of the geophysical data. Geostatistical analysis incorporating the spatial variability of resistivity was used to account for the effect of lithologic heterogeneity on effective hydraulic permeability. The geostatistical analysis and lithologic data descriptions were used to make an interpretation of the hydrogeologic system and derive estimates of surface-water/groundwater interaction potential within the canals and streambeds. The estimated interaction potential at the Ainsworth Canal site and the Mirdan and Geranium Canal site is generally low to moderately low. The sediment textures at nearby test holes typically were silt and clay and fine-to-medium sand. The apparent resistivity values for these sites ranged from 2 to 120 ohm-meters. The vertical and horizontal variability of the apparent resistivity data were consistently low. Low resistive variability indicates little lithologic heterogeneity for either canal site. The surface-water/groundwater interaction-potential estimates are in agreement with the narrow frequency distribution of resistivity, low apparent resistivities, low spatial heterogeneity, and test-hole grain-size ranges. The estimated surface-water/groundwater interaction potential at the North Loup and Middle Loup River sites is moderate to moderately high. The sediment textures at nearby test holes were predominantly fine, medium, and coarse sand with some silt and silty to sandy clay. The apparent resistivity values for these sites ranged from 34 to 1,338 ohm-meters. The vertical variability of the resistivity data was moderately high. The horizontal variability at these sites is low to moderately low. The higher resistive variability at these sites indicates generally greater lithologic heterogeneity than at either the Ainsworth Canal site or the Mirdan and Geranium Canal site. The surface-water/groundwater interaction-potential estimates are in agreement with the generally moderate to high apparent resistivity, the greater spatial heterogeneity, and the variable lithologic texture. A higher interaction potential as compared to the canal sites is expected because of the higher subsurface resistivity and greater lithologic heterogeneity.

The annual and interannual variabilities of precipitable water, surface wind speed, and sea surface temperature over the tropical Pacific

NASA Technical Reports Server (NTRS)

Liu, W. Timothy

1989-01-01

The Nimbus-7 Scanning Multichannel Microwave Radiometer (SSMR) provided simultaneous measurements of three geophysical parameters, each of which describing a certain aspect of the evolution of the 1982-1983 ENSO: the sea-surface temperature (T), precipitable water (W), and surface-wind speed (U). In this paper, values derived from the SSMR were compared with in situ measurements from ships, research buoys, and operational island stations in the tropical Pacific between January 1980 and October 1983, demonstrating the temporal and spatial coherence of the SSMR measurements. The results show that the variabilities of the surface convergence, sea surface temperature, and precipitable water are related. It was found that W anomalies were not always colocated with T anomalies, and that W anomalies were often associated with negative U anomalies, interpreted as surface convergence.

An Evaluation of Antarctica as a Calibration Target for Passive Microwave Satellite Missions with Climate Data Record Applications

NASA Technical Reports Server (NTRS)

Kim, Edward

2011-01-01

Passive microwave remote sensing at L-band (1.4 GHz) is sensitive to soil moisture and sea surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 201 I. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record-provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica-parameters such as surface temperature.

An Evaluation of Antarctica as a Calibration Target for Passive Microwave Satellite Missions

NASA Technical Reports Server (NTRS)

Kim, Edward

2012-01-01

Passive microwave remote sensing at L-band (1.4 GHz) is sensitive to soil moisture and sea surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 201l. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record -- provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica--parameters such as surface temperature.

Analysis of variability of tropical Pacific sea surface temperatures

NASA Astrophysics Data System (ADS)

Davies, Georgina; Cressie, Noel

2016-11-01

Sea surface temperature (SST) in the Pacific Ocean is a key component of many global climate models and the El Niño-Southern Oscillation (ENSO) phenomenon. We shall analyse SST for the period November 1981-December 2014. To study the temporal variability of the ENSO phenomenon, we have selected a subregion of the tropical Pacific Ocean, namely the Niño 3.4 region, as it is thought to be the area where SST anomalies indicate most clearly ENSO's influence on the global atmosphere. SST anomalies, obtained by subtracting the appropriate monthly averages from the data, are the focus of the majority of previous analyses of the Pacific and other oceans' SSTs. Preliminary data analysis showed that not only Niño 3.4 spatial means but also Niño 3.4 spatial variances varied with month of the year. In this article, we conduct an analysis of the raw SST data and introduce diagnostic plots (here, plots of variability vs. central tendency). These plots show strong negative dependence between the spatial standard deviation and the spatial mean. Outliers are present, so we consider robust regression to obtain intercept and slope estimates for the 12 individual months and for all-months-combined. Based on this mean-standard deviation relationship, we define a variance-stabilizing transformation. On the transformed scale, we describe the Niño 3.4 SST time series with a statistical model that is linear, heteroskedastic, and dynamical.

Spatial characteristics of net methylmercury production hot spots in peatlands

Treesearch

Carl P.J. Mitchell; Brian A. Branfireun; Randall K. Kolka

2008-01-01

Many wetlands are sources of methylmercury (MeHg) to surface waters, yet little information exists about the distribution of MeHg within wetlands. Total mercury (THg) and MeHg in peat pore waters were studied in four peatlands in spring, summer, and fall 2005. Marked spatial variability in the distribution of MeHg, and %MeHg as a proxy for net MeHg production, was...

High Frequency Radar Observations of Tidal Current Variability in the Lower Chesapeake Bay

NASA Astrophysics Data System (ADS)

Updyke, T. G.; Dusek, G.; Atkinson, L. P.

2016-02-01

Analysis of eight years of high frequency radar surface current observations in the lower Chesapeake Bay is presented with a focus on the variability of the tidal component of the surface circulation which accounts for a majority of the variance of the surface flow (typically 70-80% for the middle of the radar footprint). Variations in amplitude and phase of the major tidal constituents are examined in the context of water level, wind and river discharge data. Comparisons are made with harmonic analysis results from long-term records of current data measured by three current profilers operated by NOAA as part of the Chesapeake Bay Physical Oceanographic Real-Time System (PORTS). Preliminary results indicate that there is significant spatial variability in the M2 amplitude over the HF radar grid as well as temporal variability when harmonic analysis is performed using bi-monthly time segments over the course of the record.

The spatial variable glacier mass loss over the southeast Tibet Plateau and the climate cause analyses

NASA Astrophysics Data System (ADS)

Ke, L.; Ding, X.; Song, C.; Sheng, Y.

2016-12-01

Temperate glaciers can be highly sensitive to global climate change due to relatively humid and warm local climate. Numerous temperate glaciers are distributed in the southeastern Tibet Plateau (SETP) and their changes are still poorly represented. Based on a latest glacier inventory and ICESat altimetry measurements, we examine the spatial heterogeneity of glacier change in the SETP (including the central and eastern Nyainqêntanglha ranges) and further analyze its relation with climate change by using station-based and gridded meteorological data. Our results show that SETP glaciers experienced drastic surface lowering at about -0.84±0.26 m a-1 on average over 2003-2008. Debris-covered ice thinned at an average rate of -1.13±0.32 m a-1, in comparison with -0.92±0.17 m a-1 over the debris-free ice areas. The thinning rate is the strongest in the southeastern sub-region (up to -1.24 m a-1 ) and moderate ( -0.45 m a-1 ) in the central and northwestern parts, which is in general agreement with the pattern of surface mass changes based on the GRACE gravimetry observation. Long-term climate data at weather stations show that, in comparison with the period of 1992-2002, mean temperature increased by 0.46 °C - 0.59 °C in the recent decade (2003-2013); while the change of summer precipitation exhibited remarkably spatial variability, following a southeast-northwest contrasting pattern (decreasing by over 10% in the southeast, to stable level in the central region, and increment up to 10% in the northwest). This spatially variable precipitation change is consistent with results from CN05 grid data and ERA re-analysis data, and agrees well with the spatial pattern of glacier surface elevation changes. The results suggest that overall negative glacier mass balances in SETP are governed by temperature rising, while the different precipitation change could contribute to inconsistent glacier thinning rates. The spatial pattern of precipitation decrease and mass loss might be tele-connected with the dynamics of the Indian summer monsoon.

On the relationship between thermal emissivity and the Normalized Difference Vegetation Index for natural surfaces

NASA Technical Reports Server (NTRS)

Van De Griend, A. A.; Owe, M.

1993-01-01

The spatial variation of both the thermal emissivity (8-14 microns) and Normalized Difference Vegetation Index (NDVI) was measured for a series of natural surfaces within a savanna environment in Botswana. The measurements were performed with an emissivity-box and with a combined red and near-IR radiometer, with spectral bands corresponding to NOAA/AVHRR. It was found that thermal emissivity was highly correlated with NDVI after logarithmic transformation, with a correlation coefficient of R = 0.94. This empirical relationship is of potential use for energy balance studies using thermal IR remote sensing. The relationship was used in combination with AVHRR (GAC), AVHRR (LAC), and Landsat (TM) data to demonstrate and compare the spatial variability of various spatial scales.

Impacts of Spatial Fidelity Violations in the Forward Signal Model on DOAS-based Greenhouse Gas Retrievals: a Preliminary Analysis for OCO-2 (and Other Missions)

NASA Technical Reports Server (NTRS)

Davis, Anthony B.; Frakenbert, Christian

2012-01-01

Success in three aspects of OCO-2 mission is threatened by unaccounted spa,al variability effects, all involving atmospheric scattering: 1. Low/moderately opaque clouds can escape the prescreening by mimicking a brighter surface. 2. Prescreening does not account for long-range radia,ve impact (adjacency effect) of nearby clouds. Need for extended cloud masking? 3. Oblique looks in target mode are highly exposed to surface adjacency and aerosol variability effects.We'll be covering all three bases!

Calibration of a distributed hydrologic model for six European catchments using remote sensing data

NASA Astrophysics Data System (ADS)

Stisen, S.; Demirel, M. C.; Mendiguren González, G.; Kumar, R.; Rakovec, O.; Samaniego, L. E.

2017-12-01

While observed streamflow has been the single reference for most conventional hydrologic model calibration exercises, the availability of spatially distributed remote sensing observations provide new possibilities for multi-variable calibration assessing both spatial and temporal variability of different hydrologic processes. In this study, we first identify the key transfer parameters of the mesoscale Hydrologic Model (mHM) controlling both the discharge and the spatial distribution of actual evapotranspiration (AET) across six central European catchments (Elbe, Main, Meuse, Moselle, Neckar and Vienne). These catchments are selected based on their limited topographical and climatic variability which enables to evaluate the effect of spatial parameterization on the simulated evapotranspiration patterns. We develop a European scale remote sensing based actual evapotranspiration dataset at a 1 km grid scale driven primarily by land surface temperature observations from MODIS using the TSEB approach. Using the observed AET maps we analyze the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mHM model. This model allows calibrating one-basin-at-a-time or all-basins-together using its unique structure and multi-parameter regionalization approach. Results will indicate any tradeoffs between spatial pattern and discharge simulation during model calibration and through validation against independent internal discharge locations. Moreover, added value on internal water balances will be analyzed.

Section Height Determination Methods of the Isotopographic Surface in a Complex Terrain Relief

ERIC Educational Resources Information Center

Syzdykova, Guldana D.; Kurmankozhaev, Azimhan K.

2016-01-01

A new method for determining the vertical interval of isotopographic surfaces on rugged terrain was developed. The method is based on the concept of determining the differentiated size of the vertical interval using spatial-statistical properties inherent in the modal characteristic, the degree of variability of apical heights and the chosen map…

Validation of solar radiation surfaces from MODIS and reanalysis data over topographically complex terrain

Treesearch

Todd A. Schroeder; Robbie Hember; Nicholas C. Coops; Shunlin Liang

2009-01-01

The magnitude and distribution of incoming shortwave solar radiation (SW) has significant influence on the productive capacity of forest vegetation. Models that estimate forest productivity require accurate and spatially explicit radiation surfaces that resolve both long- and short-term temporal climatic patterns and that account for topographic variability of the land...

Evaluation of fine soil moisture data from the IFloodS (NASA GPM) Ground Validation campaign using a fully-distributed ecohydrological model

NASA Astrophysics Data System (ADS)

Bastola, S.; Dialynas, Y. G.; Arnone, E.; Bras, R. L.

2014-12-01

The spatial variability of soil, vegetation, topography, and precipitation controls hydrological processes, consequently resulting in high spatio-temporal variability of most of the hydrological variables, such as soil moisture. Limitation in existing measuring system to characterize this spatial variability, and its importance in various application have resulted in a need of reconciling spatially distributed soil moisture evolution model and corresponding measurements. Fully distributed ecohydrological model simulates soil moisture at high resolution soil moisture. This is relevant for range of environmental studies e.g., flood forecasting. They can also be used to evaluate the value of space born soil moisture data, by assimilating them into hydrological models. In this study, fine resolution soil moisture data simulated by a physically-based distributed hydrological model, tRIBS-VEGGIE, is compared with soil moisture data collected during the field campaign in Turkey river basin, Iowa. The soil moisture series at the 2 and 4 inch depth exhibited a more rapid response to rainfall as compared to bottom 8 and 20 inch ones. The spatial variability in two distinct land surfaces of Turkey River, IA, reflects the control of vegetation, topography and soil texture in the characterization of spatial variability. The comparison of observed and simulated soil moisture at various depth showed that model was able to capture the dynamics of soil moisture at a number of gauging stations. Discrepancies are large in some of the gauging stations, which are characterized by rugged terrain and represented, in the model, through large computational units.

Spatially complex distribution of dissolved manganese in a fjord as revealed by high-resolution in situ sensing using the autonomous underwater vehicle Autosub.

PubMed

Statham, P J; Connelly, D P; German, C R; Brand, T; Overnell, J O; Bulukin, E; Millard, N; McPhail, S; Pebody, M; Perrett, J; Squire, M; Stevenson, P; Webb, A

2005-12-15

Loch Etive is a fjordic system on the west coast of Scotland. The deep waters of the upper basin are periodically isolated, and during these periods oxygen is lost through benthic respiration and concentrations of dissolved manganese increase. In April 2000 the autonomous underwater vehicle (AUV) Autosub was fitted with an in situ dissolved manganese analyzer and was used to study the spatial variability of this element together with oxygen, salinity, and temperature throughout the basin. Six along-loch transects were completed at either constant height above the seafloor or at constant depth below the surface. The ca. 4000 in situ 10-s-average dissolved Mn (Mnd) data points obtained provide a new quasi-synoptic and highly detailed view of the distribution of manganese in this fjordic environment not possible using conventional (water bottle) sampling. There is substantial variability in concentrations (<25 to >600 nM) and distributions of Mnd. Surface waters are characteristically low in Mnd reflecting mixing of riverine and marine end-member waters, both of which are low in Mnd. The deeper waters are enriched in Mnd, and as the water column always contains some oxygen, this must reflect primarily benthic inputs of reduced dissolved Mn. However, this enrichment of Mnd is spatially very variable, presumably as a result of variability in release of Mn coupled with mixing of water in the loch and removal processes. This work demonstrates how AUVs coupled with chemical sensors can reveal substantial small-scale variability of distributions of chemical species in coastal environments that would not be resolved by conventional sampling approaches. Such information is essential if we are to improve our understanding of the nature and significance of the underlying processes leading to this variability.

Soil nutrient-landscape relationships in a lowland tropical rainforest in Panama

USGS Publications Warehouse

Barthold, F.K.; Stallard, R.F.; Elsenbeer, H.

2008-01-01

Soils play a crucial role in biogeochemical cycles as spatially distributed sources and sinks of nutrients. Any spatial patterns depend on soil forming processes, our understanding of which is still limited, especially in regards to tropical rainforests. The objective of our study was to investigate the effects of landscape properties, with an emphasis on the geometry of the land surface, on the spatial heterogeneity of soil chemical properties, and to test the suitability of soil-landscape modeling as an appropriate technique to predict the spatial variability of exchangeable K and Mg in a humid tropical forest in Panama. We used a design-based, stratified sampling scheme to collect soil samples at 108 sites on Barro Colorado Island, Panama. Stratifying variables are lithology, vegetation and topography. Topographic variables were generated from high-resolution digital elevation models with a grid size of 5 m. We took samples from five depths down to 1 m, and analyzed for total and exchangeable K and Mg. We used simple explorative data analysis techniques to elucidate the importance of lithology for soil total and exchangeable K and Mg. Classification and Regression Trees (CART) were adopted to investigate importance of topography, lithology and vegetation for the spatial distribution of exchangeable K and Mg and with the intention to develop models that regionalize the point observations using digital terrain data as explanatory variables. Our results suggest that topography and vegetation do not control the spatial distribution of the selected soil chemical properties at a landscape scale and lithology is important to some degree. Exchangeable K is distributed equally across the study area indicating that other than landscape processes, e.g. biogeochemical processes, are responsible for its spatial distribution. Lithology contributes to the spatial variation of exchangeable Mg but controlling variables could not be detected. The spatial variation of soil total K and Mg is mainly influenced by lithology. ?? 2007 Elsevier B.V. All rights reserved.

Spatially variable stage-driven groundwater-surface water interaction inferred from time-frequency analysis of distributed temperature sensing data

USGS Publications Warehouse

Mwakanyamale, Kisa; Slater, Lee; Day-Lewis, Frederick D.; Elwaseif, Mehrez; Johnson, Carole D.

2012-01-01

Characterization of groundwater-surface water exchange is essential for improving understanding of contaminant transport between aquifers and rivers. Fiber-optic distributed temperature sensing (FODTS) provides rich spatiotemporal datasets for quantitative and qualitative analysis of groundwater-surface water exchange. We demonstrate how time-frequency analysis of FODTS and synchronous river stage time series from the Columbia River adjacent to the Hanford 300-Area, Richland, Washington, provides spatial information on the strength of stage-driven exchange of uranium contaminated groundwater in response to subsurface heterogeneity. Although used in previous studies, the stage-temperature correlation coefficient proved an unreliable indicator of the stage-driven forcing on groundwater discharge in the presence of other factors influencing river water temperature. In contrast, S-transform analysis of the stage and FODTS data definitively identifies the spatial distribution of discharge zones and provided information on the dominant forcing periods (≥2 d) of the complex dam operations driving stage fluctuations and hence groundwater-surface water exchange at the 300-Area.

Assessment of spatial variability of major-ion concentrations and del oxygen-18 values in surface snow, Upper Fremont Glacier, Wyoming, USA

USGS Publications Warehouse

Naftz, D.L.; Schuster, P.F.; Reddy, M.M.

1994-01-01

One hundred samples were collected from the surface of the Upper Fremont Glacier at equally spaced intervals defined by an 8100m2 snow grid to asesss the significance of lateral variability in major-ion concentrations and del oxygen-18 values. Comparison of the observed variability of each chemical constituent to the variability expected by measurement error indicated substantial lateral variability with the surface-snow layer. Results of the nested ANOVA indicate most of the variance for every constituent is in the values grouped at the two smaller geographic scales (between 506m2 and within 506m2 sections). The variance data from the snow grid were used to develop equations to evaluate the significance of both positive and negative concentration/value peaks of nitrate and del oxygen-18 with depth, in a 160m ice core. Values of del oxygen-18 in the section from 110-150m below the surface consistently vary outside the expected limits and possibly represents cooler temperatures during the Little Ice Age from about 1810 to 1725 A.D. -from Authors

Assimilating a decade of hydrometeorological ship measurements across the North American Great Lakes

NASA Astrophysics Data System (ADS)

Fries, K. J.; Kerkez, B.

2015-12-01

We use a decade of measurements made by the Volunteer Observing Ships (VOS) program on the North American Great Lakes to derive spatial estimates of over-lake air temperature, sea surface temperature, dewpoint, and wind speed. This Lagrangian data set, which annually comprises over 200,000 point observations from over 80,000 ship reports across a 244,000 square kilometer study area, is assimilated using a Gaussian Process machine learning algorithm. This algorithm classifies a model for each hydrometeorological variable using a combination of latitudes, longitudes, seasons of the year, as well as predictions made by the National Digital Forecast Database (NDFD) and Great Lakes Coastal Forecasting System (GLCFS) operational models. We show that our data-driven method significantly improves the spatial and temporal estimation of overlake hydrometeorological variables, while simultaneously providing uncertainty estimates that can be used to improve historical and future predictions on dense spatial and temporal scales. This method stands to improve the prediction of water levels on the Great Lakes, which comprise over 90% of America's surface fresh water, and impact the lives of millions of people living in the basin.

Plot-scale field experiment of surface hydrologic processes with EOS implications

NASA Technical Reports Server (NTRS)

Laymon, Charles A.; Macari, Emir J.; Costes, Nicholas C.

1992-01-01

Plot-scale hydrologic field studies were initiated at NASA Marshall Space Flight Center to a) investigate the spatial and temporal variability of surface and subsurface hydrologic processes, particularly as affected by vegetation, and b) develop experimental techniques and associated instrumentation methodology to study hydrologic processes at increasingly large spatial scales. About 150 instruments, most of which are remotely operated, have been installed at the field site to monitor ground atmospheric conditions, precipitation, interception, soil-water status, and energy flux. This paper describes the nature of the field experiment, instrumentation and sampling rationale, and presents preliminary findings.

Understanding land surface evapotranspiration with satellite multispectral measurements

NASA Technical Reports Server (NTRS)

Menenti, M.

1993-01-01

Quantitative use of remote multispectral measurements to study and map land surface evapotranspiration has been a challenging issue for the past 20 years. Past work is reviewed against process physics. A simple two-layer combination-type model is used which is applicable to both vegetation and bare soil. The theoretic analysis is done to show which land surface properties are implicitly defined by such evaporation models and to assess whether they are measurable as a matter of principle. Conceptual implications of the spatial correlation of land surface properties, as observed by means of remote multispectral measurements, are illustrated with results of work done in arid zones. A normalization of spatial variability of land surface evaporation is proposed by defining a location-dependent potential evaporation and surface temperature range. Examples of the application of remote based estimates of evaporation to hydrological modeling studies in Egypt and Argentina are presented.

Highly variable aerodynamic roughness length (z0) for a hummocky debris-covered glacier

NASA Astrophysics Data System (ADS)

Miles, Evan S.; Steiner, Jakob F.; Brun, Fanny

2017-08-01

The aerodynamic roughness length (z0) is an essential parameter in surface energy balance studies, but few literature values exist for debris-covered glaciers. We use microtopographic and aerodynamic methods to assess the spatial variability of z0 for Lirung Glacier, Nepal. We apply structure from motion to produce digital elevation models for three nested domains: five 1 m2 plots, a 21,300 m2 surface depression, and the lower 550,000 m2 of the debris-mantled tongue. Wind and temperature sensor towers were installed in the vicinity of the plots within the surface depression in October 2014. We calculate z0 according to a variety of transect-based microtopographic parameterizations for each plot, then develop a grid version of the algorithms by aggregating data from all transects. This grid approach is applied to the surface depression digital elevation model to characterize z0 spatial variability. The algorithms reproduce the same variability among transects and plots, but z0 estimates vary by an order of magnitude between algorithms. Across the study depression, results from different algorithms are strongly correlated. Using Monin-Obukov similarity theory, we derive z0 values from the meteorological data. Using different stability criteria, we derive median values of z0 between 0.03 m and 0.05 m, but with considerable uncertainty due to the glacier's complex topography. Considering estimates from these algorithms, results suggest that z0 varies across Lirung Glacier between ˜0.005 m (gravels) to ˜0.5 m (boulders). Future efforts should assess the importance of such variable z0 values in a distributed energy balance model.

Spatial and Temporal Variability of Carbon Dioxide Using Structure Functions in Urban Areas: Insights for Future Active Remote CO2 Sensors

NASA Technical Reports Server (NTRS)

Choi, Yonghoon; Yang, Melissa; Kooi, Susan A.; Browell, Edward V.; DiGangi, Joshua P.

2015-01-01

High resolution in-situ CO2 measurements were recorded onboard the NASA P-3B during the DISCOVER-AQ (Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality) Field Campaigns during July 2011 over Washington DC/Baltimore, MD; January-February 2013 over the San Joaquin Valley, CA; September 2013 over Houston, TX; and July-August 2014 over Denver, CO. Each of these campaigns have approximately two hundred vertical soundings of CO2 within the lower troposphere (surface to about 5 kilometers) at 6-8 different sites in each of the urban areas. In this study, we used structure function analysis, which is a useful way to quantify spatial and temporal variability, by displaying differences with average observations, to evaluate the variability of CO2 in the 0-2 kilometers range (representative of the planetary boundary layer). These results can then be used to provide guidance in the development of science requirements for the future ASCENDS (Active Sensing of CO2 Emissions over Nights, Days, and Seasons) mission to measure near-surface CO2 variability in different urban areas. We also compare the observed in-situ CO2 variability with the variability of the CO2 column-averaged optical depths in the 0-1 kilometer and 0-3.5 kilometers altitude ranges in the four geographically different urban areas, using vertical weighting functions for potential future ASCENDS lidar CO2 sensors operating in the 1.57 and 2.05 millimeter measurement regions. In addition to determining the natural variability of CO2 near the surface and in the column, radiocarbon method using continuous CO2 and CO measurements are used to examine the variation of emission quantification between anthropogenic and biogenic sources in the DC/Maryland urban site.

Neural dynamics of object-based multifocal visual spatial attention and priming: Object cueing, useful-field-of-view, and crowding

PubMed Central

Foley, Nicholas C.; Grossberg, Stephen; Mingolla, Ennio

2015-01-01

How are spatial and object attention coordinated to achieve rapid object learning and recognition during eye movement search? How do prefrontal priming and parietal spatial mechanisms interact to determine the reaction time costs of intra-object attention shifts, inter-object attention shifts, and shifts between visible objects and covertly cued locations? What factors underlie individual differences in the timing and frequency of such attentional shifts? How do transient and sustained spatial attentional mechanisms work and interact? How can volition, mediated via the basal ganglia, influence the span of spatial attention? A neural model is developed of how spatial attention in the where cortical stream coordinates view-invariant object category learning in the what cortical stream under free viewing conditions. The model simulates psychological data about the dynamics of covert attention priming and switching requiring multifocal attention without eye movements. The model predicts how “attentional shrouds” are formed when surface representations in cortical area V4 resonate with spatial attention in posterior parietal cortex (PPC) and prefrontal cortex (PFC), while shrouds compete among themselves for dominance. Winning shrouds support invariant object category learning, and active surface-shroud resonances support conscious surface perception and recognition. Attentive competition between multiple objects and cues simulates reaction-time data from the two-object cueing paradigm. The relative strength of sustained surface-driven and fast-transient motion-driven spatial attention controls individual differences in reaction time for invalid cues. Competition between surface-driven attentional shrouds controls individual differences in detection rate of peripheral targets in useful-field-of-view tasks. The model proposes how the strength of competition can be mediated, though learning or momentary changes in volition, by the basal ganglia. A new explanation of crowding shows how the cortical magnification factor, among other variables, can cause multiple object surfaces to share a single surface-shroud resonance, thereby preventing recognition of the individual objects. PMID:22425615

Neural dynamics of object-based multifocal visual spatial attention and priming: object cueing, useful-field-of-view, and crowding.

PubMed

Foley, Nicholas C; Grossberg, Stephen; Mingolla, Ennio

2012-08-01

How are spatial and object attention coordinated to achieve rapid object learning and recognition during eye movement search? How do prefrontal priming and parietal spatial mechanisms interact to determine the reaction time costs of intra-object attention shifts, inter-object attention shifts, and shifts between visible objects and covertly cued locations? What factors underlie individual differences in the timing and frequency of such attentional shifts? How do transient and sustained spatial attentional mechanisms work and interact? How can volition, mediated via the basal ganglia, influence the span of spatial attention? A neural model is developed of how spatial attention in the where cortical stream coordinates view-invariant object category learning in the what cortical stream under free viewing conditions. The model simulates psychological data about the dynamics of covert attention priming and switching requiring multifocal attention without eye movements. The model predicts how "attentional shrouds" are formed when surface representations in cortical area V4 resonate with spatial attention in posterior parietal cortex (PPC) and prefrontal cortex (PFC), while shrouds compete among themselves for dominance. Winning shrouds support invariant object category learning, and active surface-shroud resonances support conscious surface perception and recognition. Attentive competition between multiple objects and cues simulates reaction-time data from the two-object cueing paradigm. The relative strength of sustained surface-driven and fast-transient motion-driven spatial attention controls individual differences in reaction time for invalid cues. Competition between surface-driven attentional shrouds controls individual differences in detection rate of peripheral targets in useful-field-of-view tasks. The model proposes how the strength of competition can be mediated, though learning or momentary changes in volition, by the basal ganglia. A new explanation of crowding shows how the cortical magnification factor, among other variables, can cause multiple object surfaces to share a single surface-shroud resonance, thereby preventing recognition of the individual objects. Copyright © 2012 Elsevier Inc. All rights reserved.

Quantifying the Uncertainty in High Spatial and Temporal Resolution Synthetic Land Surface Reflectance at Pixel Level Using Ground-Based Measurements

NASA Astrophysics Data System (ADS)

Kong, J.; Ryu, Y.

2017-12-01

Algorithms for fusing high temporal frequency and high spatial resolution satellite images are widely used to develop dense time-series land surface observations. While many studies have revealed that the synthesized frequent high spatial resolution images could be successfully applied in vegetation mapping and monitoring, validation and correction of fused images have not been focused than its importance. To evaluate the precision of fused image in pixel level, in-situ reflectance measurements which could account for the pixel-level heterogeneity are necessary. In this study, the synthetic images of land surface reflectance were predicted by the coarse high-frequency images acquired from MODIS and high spatial resolution images from Landsat-8 OLI using the Flexible Spatiotemporal Data Fusion (FSDAF). Ground-based reflectance was measured by JAZ Spectrometer (Ocean Optics, Dunedin, FL, USA) on rice paddy during five main growth stages in Cheorwon-gun, Republic of Korea, where the landscape heterogeneity changes through the growing season. After analyzing the spatial heterogeneity and seasonal variation of land surface reflectance based on the ground measurements, the uncertainties of the fused images were quantified at pixel level. Finally, this relationship was applied to correct the fused reflectance images and build the seasonal time series of rice paddy surface reflectance. This dataset could be significant for rice planting area extraction, phenological stages detection, and variables estimation.

A rapid and repeatable method to deposit bioaerosols on material surfaces.

PubMed

Calfee, M Worth; Lee, Sang Don; Ryan, Shawn P

2013-03-01

A simple method for repeatably inoculating surfaces with a precise quantity of aerosolized spores was developed. Laboratory studies were conducted to evaluate the variability of the method within and between experiments, the spatial distribution of spore deposition, the applicability of the method to complex surface types, and the relationship between material surface roughness and spore recoveries. Surface concentrations, as estimated by recoveries from wetted-wipe sampling, were between 5×10(3) and 1.5×10(4)CFUcm(-2) across the entire area (930cm(2)) inoculated. Between-test variability (Cv) in spore recoveries was 40%, 81%, 66%, and 20% for stainless steel, concrete, wood, and drywall, respectively. Within-test variability was lower, and did not exceed 33%, 47%, 52%, and 20% for these materials. The data demonstrate that this method is repeatable, is effective at depositing spores across a target surface area, and can be used to dose complex materials such as concrete, wood, and drywall. In addition, the data demonstrate that surface sampling recoveries vary by material type, and this variability can partially be explained by the material surface roughness index. This deposition method was developed for use in biological agent detection, sampling, and decontamination studies, however, is potentially beneficial to any scientific discipline that investigates surfaces containing aerosol-borne particles. Published by Elsevier B.V.

Estimation of Monthly Near Surface Air Temperature Using Geographically Weighted Regression in China

NASA Astrophysics Data System (ADS)

Wang, M. M.; He, G. J.; Zhang, Z. M.; Zhang, Z. J.; Liu, X. G.

2018-04-01

Near surface air temperature (NSAT) is a primary descriptor of terrestrial environment conditions. The availability of NSAT with high spatial resolution is deemed necessary for several applications such as hydrology, meteorology and ecology. In this study, a regression-based NSAT mapping method is proposed. This method is combined remote sensing variables with geographical variables, and uses geographically weighted regression to estimate NSAT. The altitude was selected as geographical variable; and the remote sensing variables include land surface temperature (LST) and Normalized Difference vegetation index (NDVI). The performance of the proposed method was assessed by predict monthly minimum, mean, and maximum NSAT from point station measurements in China, a domain with a large area, complex topography, and highly variable station density, and the NSAT maps were validated against the meteorology observations. Validation results with meteorological data show the proposed method achieved an accuracy of 1.58 °C. It is concluded that the proposed method for mapping NSAT is very operational and has good precision.

Prediction of Ba, Mn and Zn for tropical soils using iron oxides and magnetic susceptibility

NASA Astrophysics Data System (ADS)

Marques Júnior, José; Arantes Camargo, Livia; Reynaldo Ferracciú Alleoni, Luís; Tadeu Pereira, Gener; De Bortoli Teixeira, Daniel; Santos Rabelo de Souza Bahia, Angelica

2017-04-01

Agricultural activity is an important source of potentially toxic elements (PTEs) in soil worldwide but particularly in heavily farmed areas. Spatial distribution characterization of PTE contents in farming areas is crucial to assess further environmental impacts caused by soil contamination. Designing prediction models become quite useful to characterize the spatial variability of continuous variables, as it allows prediction of soil attributes that might be difficult to attain in a large number of samples through conventional methods. This study aimed to evaluate, in three geomorphic surfaces of Oxisols, the capacity for predicting PTEs (Ba, Mn, Zn) and their spatial variability using iron oxides and magnetic susceptibility (MS). Soil samples were collected from three geomorphic surfaces and analyzed for chemical, physical, mineralogical properties, as well as magnetic susceptibility (MS). PTE prediction models were calibrated by multiple linear regression (MLR). MLR calibration accuracy was evaluated using the coefficient of determination (R2). PTE spatial distribution maps were built using the values calculated by the calibrated models that reached the best accuracy by means of geostatistics. The high correlations between the attributes clay, MS, hematite (Hm), iron oxides extracted by sodium dithionite-citrate-bicarbonate (Fed), and iron oxides extracted using acid ammonium oxalate (Feo) with the elements Ba, Mn, and Zn enabled them to be selected as predictors for PTEs. Stepwise multiple linear regression showed that MS and Fed were the best PTE predictors individually, as they promoted no significant increase in R2 when two or more attributes were considered together. The MS-calibrated models for Ba, Mn, and Zn prediction exhibited R2 values of 0.88, 0.66, and 0.55, respectively. These are promising results since MS is a fast, cheap, and non-destructive tool, allowing the prediction of a large number of samples, which in turn enables detailed mapping of large areas. MS predicted values enabled the characterization and the understanding of spatial variability of the studied PTEs.

A connectionist-geostatistical approach for classification of deformation types in ice surfaces

NASA Astrophysics Data System (ADS)

Goetz-Weiss, L. R.; Herzfeld, U. C.; Hale, R. G.; Hunke, E. C.; Bobeck, J.

2014-12-01

Deformation is a class of highly non-linear geophysical processes from which one can infer other geophysical variables in a dynamical system. For example, in an ice-dynamic model, deformation is related to velocity, basal sliding, surface elevation changes, and the stress field at the surface as well as internal to a glacier. While many of these variables cannot be observed, deformation state can be an observable variable, because deformation in glaciers (once a viscosity threshold is exceeded) manifests itself in crevasses.Given the amount of information that can be inferred from observing surface deformation, an automated method for classifying surface imagery becomes increasingly desirable. In this paper a Neural Network is used to recognize classes of crevasse types over the Bering Bagley Glacier System (BBGS) during a surge (2011-2013-?). A surge is a spatially and temporally highly variable and rapid acceleration of the glacier. Therefore, many different crevasse types occur in a short time frame and in close proximity, and these crevasse fields hold information on the geophysical processes of the surge.The connectionist-geostatistical approach uses directional experimental (discrete) variograms to parameterize images into a form that the Neural Network can recognize. Recognizing that each surge wave results in different crevasse types and that environmental conditions affect the appearance in imagery, we have developed a semi-automated pre-training software to adapt the Neural Net to chaining conditions.The method is applied to airborne and satellite imagery to classify surge crevasses from the BBGS surge. This method works well for classifying spatially repetitive images such as the crevasses over Bering Glacier. We expand the network for less repetitive images in order to analyze imagery collected over the Arctic sea ice, to assess the percentage of deformed ice for model calibration.

Local Climate Changes Forced by Changes in Land Use and topography in the Aburrá Valley, Colombia.

NASA Astrophysics Data System (ADS)

Zapata Henao, M. Z.; Hoyos Ortiz, C. D.

2017-12-01

One of the challenges in the numerical weather models is the adequate representation of soil-vegetation-atmosphere interaction at different spatial scales, including scenarios with heterogeneous land cover and complex mountainous terrain. The interaction determines the energy, mass and momentum exchange at the surface and could affect different variables including precipitation, temperature and wind. In order to quantify the long-term climate impact of changes in local land use and to assess the role of topography, two numerical experiments were examined. The first experiment allows assessing the continuous growth of urban areas within the Aburrá Valley, a complex terrain region located in Colombian Andes. The Weather Research Forecast model (WRF) is used as the basis of the experiment. The basic setup involves two nested domains, one representing the continental scale (18 km) and the other the regional scale (2 km). The second experiment allows drastic topography modification, including changing the valley configuration to a plateau. The control run for both experiments corresponds to a climatological scenario. In both experiments the boundary conditions correspond to the climatological continental domain output. Surface temperature, surface winds and precipitation are used as the main variables to compare both experiments relative to the control run. The results of the first experiment show a strong relationship between land cover and the variables, specially for surface temperature and wind speed, due to the strong forcing land cover imposes on the albedo, heat capacity and surface roughness, changing temperature and wind speed magnitudes. The second experiment removes the winds spatial variability related with hill slopes, the direction and magnitude are modulated only by the trade winds and roughness of land cover.

Measuring floodplain spatial patterns using continuous surface metrics at multiple scales

USGS Publications Warehouse

Scown, Murray W.; Thoms, Martin C.; DeJager, Nathan R.

2015-01-01

Interactions between fluvial processes and floodplain ecosystems occur upon a floodplain surface that is often physically complex. Spatial patterns in floodplain topography have only recently been quantified over multiple scales, and discrepancies exist in how floodplain surfaces are perceived to be spatially organised. We measured spatial patterns in floodplain topography for pool 9 of the Upper Mississippi River, USA, using moving window analyses of eight surface metrics applied to a 1 × 1 m2 DEM over multiple scales. The metrics used were Range, SD, Skewness, Kurtosis, CV, SDCURV,Rugosity, and Vol:Area, and window sizes ranged from 10 to 1000 m in radius. Surface metric values were highly variable across the floodplain and revealed a high degree of spatial organisation in floodplain topography. Moran's I correlograms fit to the landscape of each metric at each window size revealed that patchiness existed at nearly all window sizes, but the strength and scale of patchiness changed within window size, suggesting that multiple scales of patchiness and patch structure exist in the topography of this floodplain. Scale thresholds in the spatial patterns were observed, particularly between the 50 and 100 m window sizes for all surface metrics and between the 500 and 750 m window sizes for most metrics. These threshold scales are ~ 15–20% and 150% of the main channel width (1–2% and 10–15% of the floodplain width), respectively. These thresholds may be related to structuring processes operating across distinct scale ranges. By coupling surface metrics, multi-scale analyses, and correlograms, quantifying floodplain topographic complexity is possible in ways that should assist in clarifying how floodplain ecosystems are structured.

Characterization of Turbulent Latent and Sensible Heat Flux Exchange Between the Atmosphere and Ocean in MERRA

NASA Technical Reports Server (NTRS)

Robert, J. Brent; Robertson, Franklin R.; Clayson, Carol Anne; Bosilovich, Michael G.

2012-01-01

Turbulent fluxes of heat and moisture across the atmosphere-ocean interface are fundamental components of the Earth's energy and water balance. Characterizing both the spatiotemporal variability and the fidelity of these exchanges of heat and moisture is critical to understanding the global water and energy cycle variations, quantifying atmosphere-ocean feedbacks, and improving model predictability. This study examines the veracity of the recently completed NASA Modern-Era Retrospective analysis for Research and Applications (MERRA) product with respect to its representation of the surface turbulent heat fluxes. A validation of MERRA turbulent heat fluxes and near-surface bulk variables at local, high-resolution space and time scales is achieved by making comparisons to a large suite of direct observations. Both in situ and satellite-observed gridded surface heat flux estimates are employed to investigate the spatial and temporal variability of the surface fluxes with respect to their annual mean climatologies, their seasonal covariability of near-surface bulk parameters, and their representation of extremes. The impact of data assimilation on the near-surface parameters is assessed through evaluation of incremental analysis update tendencies produced by the assimilation procedure. It is found that MERRA turbulent surface heat fluxes are relatively accurate for typical conditions but have systematically weak vertical gradients in moisture and temperature and have a weaker covariability between the near-surface gradients and wind speed than found in observations. This results in an underestimate of the surface latent and sensible heat fluxes over the western boundary current and storm track regions. The assimilation of observations mostly acts to bring MERRA closer to observational products by increasing moisture and temperature near the surface and decreasing the near-surface wind speeds. The major patterns of spatial and temporal variability of the turbulent heat fluxes produced by MERRA compare favorably to observationally based estimates. However, MERRA is distinct in terms of amplitude. These results suggest that MERRA is likely to be a valuable resource for a number of research applications though, as with all turbulent flux estimates, systematic issues should be taken into account

Characterization of Turbulent Latent and Sensible Heat Flux Exchange Between the Atmosphere and Ocean in MERRA

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Robertson, Franklin R.; Clayson, Carol Anne; Bosilovich, Michael G.

2012-01-01

Turbulent fluxes of heat and moisture across the atmosphere-ocean interface are fundamental components of the Earth s energy and water balance. Characterizing both the spatiotemporal variability and the fidelity of these exchanges of heat and moisture is critical to understanding the global water and energy cycle variations, quantifying atmosphere-ocean feedbacks, and improving model predictability. This study examines the veracity of the recently completed NASA Modern-Era Retrospective analysis for Research and Applications (MERRA) product with respect to its representation of the surface turbulent heat fluxes. A validation of MERRA turbulent heat fluxes and near-surface bulk variables at local, high-resolution space and time scales is achieved by making comparisons to a large suite of direct observations. Both in situ and satellite-observed gridded surface heat flux estimates are employed to investigate the spatial and temporal variability of the surface fluxes with respect to their annual mean climatologies, their seasonal covariability of near-surface bulk parameters, and their representation of extremes. The impact of data assimilation on the near-surface parameters is assessed through evaluation of incremental analysis update tendencies produced by the assimilation procedure. It is found that MERRA turbulent surface heat fluxes are relatively accurate for typical conditions but have systematically weak vertical gradients in moisture and temperature and have a weaker covariability between the near-surface gradients and wind speed than found in observations. This results in an underestimate of the surface latent and sensible heat fluxes over the western boundary current and storm track regions. The assimilation of observations mostly acts to bring MERRA closer to observational products by increasing moisture and temperature near the surface and decreasing the near-surface wind speeds. The major patterns of spatial and temporal variability of the turbulent heat fluxes produced by MERRA compare favorably to observationally based estimates. However, MERRA is distinct in terms of amplitude. These results suggest that MERRA is likely to be a valuable resource for a number of research applications though, as with all turbulent flux estimates, systematic issues should be taken into account.

Spatio-temporal analysis of annual rainfall in Crete, Greece

NASA Astrophysics Data System (ADS)

Varouchakis, Emmanouil A.; Corzo, Gerald A.; Karatzas, George P.; Kotsopoulou, Anastasia

2018-03-01

Analysis of rainfall data from the island of Crete, Greece was performed to identify key hydrological years and return periods as well as to analyze the inter-annual behavior of the rainfall variability during the period 1981-2014. The rainfall spatial distribution was also examined in detail to identify vulnerable areas of the island. Data analysis using statistical tools and spectral analysis were applied to investigate and interpret the temporal course of the available rainfall data set. In addition, spatial analysis techniques were applied and compared to determine the rainfall spatial distribution on the island of Crete. The analysis presented that in contrast to Regional Climate Model estimations, rainfall rates have not decreased, while return periods vary depending on seasonality and geographic location. A small but statistical significant increasing trend was detected in the inter-annual rainfall variations as well as a significant rainfall cycle almost every 8 years. In addition, statistically significant correlation of the island's rainfall variability with the North Atlantic Oscillation is identified for the examined period. On the other hand, regression kriging method combining surface elevation as secondary information improved the estimation of the annual rainfall spatial variability on the island of Crete by 70% compared to ordinary kriging. The rainfall spatial and temporal trends on the island of Crete have variable characteristics that depend on the geographical area and on the hydrological period.

Using a spatially-distributed hydrologic biogeochemistry model with nitrogen transport to study the spatial variation of carbon stocks and fluxes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; He, Y.; Davis, K. J.

2017-12-01

Most current biogeochemical models are 1-D and represent one point in space. Therefore, they cannot resolve topographically driven land surface heterogeneity (e.g., lateral water flow, soil moisture, soil temperature, solar radiation) or the spatial pattern of nutrient availability. A spatially distributed forest biogeochemical model with nitrogen transport, Flux-PIHM-BGC, has been developed by coupling a 1-D mechanistic biogeochemical model Biome-BGC (BBGC) with a spatially distributed land surface hydrologic model, Flux-PIHM, and adding an advection dominated nitrogen transport module. Flux-PIHM is a coupled physically based model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model, and is augmented by adding a topographic solar radiation module. Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as land surface heterogeneities caused by topography. In the coupled Flux-PIHM-BGC model, each Flux-PIHM model grid couples a 1-D BBGC model, while nitrogen is transported among model grids via surface and subsurface water flow. In each grid, Flux-PIHM provides BBGC with soil moisture, soil temperature, and solar radiation, while BBGC provides Flux-PIHM with spatially-distributed leaf area index. The coupled Flux-PIHM-BGC model has been implemented at the Susquehanna/Shale Hills Critical Zone Observatory. The model-predicted aboveground vegetation carbon and soil carbon distributions generally agree with the macro patterns observed within the watershed. The importance of abiotic variables (including soil moisture, soil temperature, solar radiation, and soil mineral nitrogen) in predicting aboveground carbon distribution is calculated using a random forest. The result suggests that the spatial pattern of aboveground carbon is controlled by the distribution of soil mineral nitrogen. A Flux-PIHM-BGC simulation without the nitrogen transport module is also executed. The model without nitrogen transport fails in predicting the spatial patterns of vegetation carbon, which indicates the importance of having a nitrogen transport module in spatially distributed ecohydrologic modeling.

Climatological Downscaling and Evaluation of AGRMET Precipitation Analyses Over the Continental U.S.

NASA Astrophysics Data System (ADS)

Garcia, M.; Peters-Lidard, C. D.; Eylander, J. B.; Daly, C.; Tian, Y.; Zeng, J.

2007-05-01

The spatially distributed application of a land surface model (LSM) over a region of interest requires the application of similarly distributed precipitation fields that can be derived from various sources, including surface gauge networks, surface-based radar, and orbital platforms. The spatial variability of precipitation influences the spatial organization of soil temperature and moisture states and, consequently, the spatial variability of land- atmosphere fluxes. The accuracy of spatially-distributed precipitation fields can contribute significantly to the uncertainty of model-based hydrological states and fluxes at the land surface. Collaborations between the Air Force Weather Agency (AFWA), NASA, and Oregon State University have led to improvements in the processing of meteorological forcing inputs for the NASA-GSFC Land Information System (LIS; Kumar et al. 2006), a sophisticated framework for LSM operation and model coupling experiments. Efforts at AFWA toward the production of surface hydrometeorological products are currently in transition from the legacy Agricultural Meteorology modeling system (AGRMET) to use of the LIS framework and procedures. Recent enhancements to meteorological input processing for application to land surface models in LIS include the assimilation of climate-based information for the spatial interpolation and downscaling of precipitation fields. Climatological information included in the LIS-based downscaling procedure for North America is provided by a monthly high-resolution PRISM (Daly et al. 1994, 2002; Daly 2006) dataset based on a 30-year analysis period. The combination of these sources and methods attempts to address the strengths and weaknesses of available legacy products, objective interpolation methods, and the PRISM knowledge-based methodology. All of these efforts are oriented on an operational need for timely estimation of spatial precipitation fields at adequate spatial resolution for customer dissemination and near-real-time simulations in regions of interest. This work focuses on value added to the AGRMET precipitation product by the inclusion of high-quality climatological information on a monthly time scale. The AGRMET method uses microwave-based satellite precipitation estimates from various polar-orbiting platforms (NOAA POES and DMSP), infrared-based estimates from geostationary platforms (GOES, METEOSAT, etc.), related cloud analysis products, and surface gauge observations in a complex and hierarchical blending process. Results from processing of the legacy AGRMET precipitation products over the U.S. using LIS-based methods for downscaling, both with and without climatological factors, are evaluated against high-resolution monthly analyses using the PRISM knowledge- based method (Daly et al. 2002). It is demonstrated that the incorporation of climatological information in a downscaling procedure can significantly enhance the accuracy, and potential utility, of AFWA precipitation products for military and civilian customer applications.

High spatial variability of carbon dioxide and methane emission in three tropical reservoirs

NASA Astrophysics Data System (ADS)

Reinaldo Paranaiba, José; Barros, Nathan O.; Mendonça, Raquel F.; Linkhorst, Annika; Isidorova, Anastasija; Roland, Fabio; Sobek, Sebastian

2017-04-01

In the tropics, many new large hydropower dams are being built, in order to produce renewable energy for economic growth. Most inland waters, such as rivers, lakes and reservoirs, emit greenhouse gases to the atmosphere, and especially tropical reservoirs have been pointed out as strong sources of methane. However, present estimates of greenhouse gas emission from reservoirs are limited by the amount of available data. In particular, the spatial variability of greenhouse gas emission from reservoirs is insufficiently understood. In order to test the hypothesis that the diffusive emission of carbon dioxide (CO2) and methane (CH4) from tropical reservoirs is characterized by strong spatial variability and incorrectly represented by measurements at one site only, we studied three reservoirs situated in different tropical climates, during the dry period. We conducted spatially resolved measurements of surface water concentrations of dissolved carbon dioxide and methane using an on-line equilibration system, as well as of the gas exchange velocity using floating chambers. We found pronounced spatial variability of diffusive CO2 and CH4 emission in all three reservoirs. River inflow areas were more likely to have high concentrations of particularly CH4, but also CO2, than other areas in the reservoirs. Close to the dam, CH4 concentrations were comparatively low in each reservoir. The variability of CH4 concentration was linked to geographical position, which we ascribe to hot spots of methanogenesis at sites of high sediment deposition, such as river inflow areas. The variability of CO2 concentration seemed instead rather to be linked to in-situ metabolism. Also the gas exchange velocity varied pronouncedly in each reservoir, but without any detectable systematic patterns, calling for further studies. We conclude that accurate upscaling of reservoir greenhouse gas emissions requires accounting for within-reservoir spatial variability, and that the anthropogenic increase of sediment flux from catchments to downstream reservoirs may be linked to increased reservoir CH4 emission.

Modeling spatial and temporal dynamics of wind flow and potential fire behavior following a mountain pine beetle outbreak in a lodgepole pine forest

Treesearch

Chad M. Hoffman; Rodman Linn; Russell Parsons; Carolyn Sieg; Judith Winterkamp

2015-01-01

Patches of live, dead, and dying trees resulting from bark beetle-caused mortality alter spatial and temporal variability in the canopy and surface fuel complex through changes in the foliar moisture content of attacked trees and through the redistribution of canopy fuels. The resulting heterogeneous fuels complexes alter within-canopy wind flow, wind fluctuations, and...

An analysis of spatial representativeness of air temperature monitoring stations

NASA Astrophysics Data System (ADS)

Liu, Suhua; Su, Hongbo; Tian, Jing; Wang, Weizhen

2018-05-01

Surface air temperature is an essential variable for monitoring the atmosphere, and it is generally acquired at meteorological stations that can provide information about only a small area within an r m radius ( r-neighborhood) of the station, which is called the representable radius. In studies on a local scale, ground-based observations of surface air temperatures obtained from scattered stations are usually interpolated using a variety of methods without ascertaining their effectiveness. Thus, it is necessary to evaluate the spatial representativeness of ground-based observations of surface air temperature before conducting studies on a local scale. The present study used remote sensing data to estimate the spatial distribution of surface air temperature using the advection-energy balance for air temperature (ADEBAT) model. Two target stations in the study area were selected to conduct an analysis of spatial representativeness. The results showed that one station (AWS 7) had a representable radius of about 400 m with a possible error of less than 1 K, while the other station (AWS 16) had the radius of about 250 m. The representable radius was large when the heterogeneity of land cover around the station was small.

Spatial Variability of Soil Water and Soil Organic Carbon Contents Under Different Degradation Degrees of Alpine Meadow Soil over the Qinghai-Tibetan Plateau

NASA Astrophysics Data System (ADS)

Zeng, C.; Zhang, F.

2014-12-01

Alpine meadow is one of widespread vegetation types of the Qinghai-Tibetan Plateau. However, alpine meadow ecosystem is undergoing degradation in recent years. The degradation of alpine meadow can changes soil physical and chemical properties as well as it's spatial variability. However, little research has been done that address the spatial patterns of soil properties under different degradation degrees of alpine meadow of the Qinghai-Tibetan Plateau although these changes were important to water and heat study and modelling of land surface. 296 soil surface (0-10 cm) samples were collected using grid sampling design from three different degraded alpine meadow regions (1 km2). Then soil water content (SWC) and organic carbon content (OCC) were measured. Classical statistical and geostatistical methods were employed to study the spatial heterogeneities of SWC and OCC under different degradation degrees (Non-degraded ND, moderately degraded MD, extremely degraded ED) of alpine meadow. Results show that both SWC and OCC of alpine meadow were normally distributed with the exception of SWC under ED. On average, both SWC and OCC of alpine meadow decreased in the order that ND > MD > ED. For nugget ratios, SWC and OCC of alpine meadow showed increasing spatial dependence tendency from ND to ED. For the range of spatial variation, both SWC and OCC of alpine meadow showed increasing tendency in distance with the increasing degree of degradation. In all, the degradation of alpine meadow has significant impact on spatial heterogeneities of SWC and OCC of alpine meadow. With increasing of alpine meadow degradation, soil water condition and nutrient condition become worse, and their distributions in spatial become unevenly.

Temporal and spatial variabilities in the surface moisture content of a fine-grained beach

NASA Astrophysics Data System (ADS)

Namikas, S. L.; Edwards, B. L.; Bitton, M. C. A.; Booth, J. L.; Zhu, Y.

2010-01-01

This study examined spatial and temporal variations in the surface moisture content of a fine-grained beach at Padre Island, Texas, USA. Surface moisture measurements were collected on a 27 × 24 m grid that extended from the dune toe to the upper foreshore. The grid was surveyed at 2 to 4 h intervals for two tidal cycles, generating 17 maps of the spatial distribution of surface moisture. Simultaneous measurements of air temperature and humidity, wind speed and direction, tidal elevation, and water table elevation were used to interpret observed changes in surface moisture. It was found that the spatial distribution of surface moisture was broadly characterized by a cross-shore gradient of high to low content moving landward from the swash zone. The distribution of surface moisture was conceptualized in terms of three zones: saturated (> 25%), intermediate or transitional (5-25%), and dry (< 5%). The position of the saturated zone corresponded to the uppermost swash zone and therefore shifted in accordance with tidal elevation. Moisture contents in the intermediate and dry zones were primarily related to variation in water table depth (which was in turn controlled by tidal elevation) and to a lesser extent by evaporation. Signals associated with atmospheric processes such as evaporation were muted by the minimal degree of variation in atmospheric parameters experienced during most of the study period, but were apparent for the last few hours. The observed spatial and temporal variations in moisture content correspond reasonably well with observations of key controlling processes, but more work is needed to fully characterize this process suite.

Modeling pCO2 variability in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Xue, Z.; He, R.; Fennel, K.; Cai, W.-J.; Lohrenz, S.; Huang, W.-J.; Tian, H.

2014-08-01

A three-dimensional coupled physical-biogeochemical model was used to simulate and examine temporal and spatial variability of surface pCO2 in the Gulf of Mexico (GoM). The model is driven by realistic atmospheric forcing, open boundary conditions from a data-assimilative global ocean circulation model, and observed freshwater and terrestrial nutrient and carbon input from major rivers. A seven-year model hindcast (2004-2010) was performed and was validated against in situ measurements. The model revealed clear seasonality in surface pCO2. Based on the multi-year mean of the model results, the GoM is an overall CO2 sink with a flux of 1.34 × 1012 mol C yr-1, which, together with the enormous fluvial carbon input, is balanced by the carbon export through the Loop Current. A sensitivity experiment was performed where all biological sources and sinks of carbon were disabled. In this simulation surface pCO2 was elevated by ~ 70 ppm, providing the evidence that biological uptake is a primary driver for the observed CO2 sink. The model also provided insights about factors influencing the spatial distribution of surface pCO2 and sources of uncertainty in the carbon budget.

Modeling pCO2 Variability in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Xue, Z. G.; He, R.; Fennel, K.; Cai, W. J.; Lohrenz, S. E.; Huang, W. J.; Tian, H.

2014-12-01

A three-dimensional coupled physical-biogeochemical model was used to simulate and examine temporal and spatial variability of surface pCO2 in the Gulf of Mexico (GoM). The model is driven by realistic atmospheric forcing, open boundary conditions from a data-assimilative global ocean circulation model, and observed freshwater and terrestrial nutrient and carbon input from major rivers. A seven-year model hindcast (2004-2010) was performed and was validated against in situ measurements. The model revealed clear seasonality in surface pCO2. Based on the multi-year mean of the model results, the GoM is an overall CO2 sink with a flux of 1.34 × 1012 mol C yr-1, which, together with the enormous fluvial carbon input, is balanced by the carbon export through the Loop Current. A sensitivity experiment was performed where all biological sources and sinks of carbon were disabled. In this simulation surface pCO2 was elevated by ~70 ppm, providing the evidence that biological uptake is a primary driver for the observed CO2 sink. The model also provided insights about factors influencing the spatial distribution of surface pCO2 and sources of uncertainty in the carbon budget.

[Detecting the moisture content of forest surface soil based on the microwave remote sensing technology.

PubMed

Li, Ming Ze; Gao, Yuan Ke; Di, Xue Ying; Fan, Wen Yi

2016-03-01

The moisture content of forest surface soil is an important parameter in forest ecosystems. It is practically significant for forest ecosystem related research to use microwave remote sensing technology for rapid and accurate estimation of the moisture content of forest surface soil. With the aid of TDR-300 soil moisture content measuring instrument, the moisture contents of forest surface soils of 120 sample plots at Tahe Forestry Bureau of Daxing'anling region in Heilongjiang Province were measured. Taking the moisture content of forest surface soil as the dependent variable and the polarization decomposition parameters of C band Quad-pol SAR data as independent variables, two types of quantitative estimation models (multilinear regression model and BP-neural network model) for predicting moisture content of forest surface soils were developed. The spatial distribution of moisture content of forest surface soil on the regional scale was then derived with model inversion. Results showed that the model precision was 86.0% and 89.4% with RMSE of 3.0% and 2.7% for the multilinear regression model and the BP-neural network model, respectively. It indicated that the BP-neural network model had a better performance than the multilinear regression model in quantitative estimation of the moisture content of forest surface soil. The spatial distribution of forest surface soil moisture content in the study area was then obtained by using the BP neural network model simulation with the Quad-pol SAR data.

Comparative Analysis of the Surface Ozone Regime Over Russia and Europe

NASA Astrophysics Data System (ADS)

Kuznetsov, G. I.; Tarasova, O. A.; Elansky, N. F.; Beloglazov, M. I.

2004-05-01

The data of the measurements of the surface ozone concentration (SOC) at several Russian cites, in TROICA expeditions, data of EMEP network as well as the results of LOTOS model application were used to compare the main characteristics of ozone spatial and temporal variability over Russia and Europe. To carry out this investigation the number of new methods of data analysis were developed and applied. Their complex application gave us possibility to separate clearly the contribution of photochemical processes having mainly periodical component (daily and seasonal). Hence more attention could be paid to the dynamical mechanism impacting SOC regime, their spatial and temporal variability including trends estimation. Spectral windowing application to the filtered database of EMEP network showed that among the different processes providing annual and shorter variability the main part (about 40% of dispersion) is governed by local and synoptical scale processes in the range of 2-7 days. At the same time the spatial distribution of these percentage contribution is non-uniform over Europe. One of the important mechanisms providing this type of variability as well as the longer ones is air transport. To study the impact of air transport the correlation fields were calculated for the transport indices using 2D NILU trajectories and SOC at EMEP network. They showed that at the Eastern border of Europe the growth of the westerlies provides not the decrease but the growth of observed SOC. This approach was use to study the features of the zonal and meridianal transport, its seasonal characteristics and annual variability. Moreover at Kislovodsk High Mountain Station the changes of the transport patters can partly explain even observed trend of SOC. Comparison of the regime at the different locations using TROICA data shows that in the most of Russian cities ozone destruction is observed. The generation of the surface ozone is only possible in the cases of combination of natural and anthropogenic emissions (like forest fires episodes in Moscow region in summer 2002). The spatial structure of the surface ozone over the European Russia was obtained with the application of LOTOS model (TNO) evaluated for 1997. It showed much more uniformity of the SOC fields over Russia with the high concentrations in rural regions in comparison with industrial ones. This conclusion is in a good agreement with the measurements of TROICA expedition. The work is carried out under the support of INTAS grant 01-0016 and RFBR 03-05-64712.

Geostatistical approach for management of soil nutrients with special emphasis on different forms of potassium considering their spatial variation in intensive cropping system of West Bengal, India.

PubMed

Chatterjee, Sourov; Santra, Priyabrata; Majumdar, Kaushik; Ghosh, Debjani; Das, Indranil; Sanyal, S K

2015-04-01

A large part of precision agriculture research in the developing countries is devoted towards precision nutrient management aspects. This has led to better economics and efficiency of nutrient use with off-farm advantages of environmental security. The keystone of precision nutrient management is analysis and interpretation of spatial variability of soils by establishing management zones. In this study, spatial variability of major soil nutrient contents was evaluated in the Ghoragacha village of North 24 Parganas district of West Bengal, India. Surface soil samples from 100 locations, covering different cropping systems of the village, was collected from 0 to 15 cm depth using 100×100 m grid system and analyzed in the laboratory to determine organic carbon (OC), available nitrogen (N), phosphorus (P), and potassium (K) contents of the soil as well as its water-soluble K (KWS), exchangeable K (KEX), and non-exchangeable forms of K (KNEX). Geostatistical analyses were performed to determine the spatial variation structure of each nutrient content within the village, followed by the generation of surface maps through kriging. Four commonly used semivariogram models, i.e., spherical, exponential, Gaussian, and linear models were fitted to each soil property, and the best one was used to prepare surface maps through krigging. Spherical model was found the best for available N and P contents, while linear and exponential model was the best for OC and available K, and for KWS and KNEK, Gausian model was the best. Surface maps of nutrient contents showed that N content (129-195 kg ha(-1)) was the most limiting factor throughout the village, while P status was generally very high ( 10-678 kg ha(-1)) in the soils of the present village. Among the different soil K fractions, KWS registered the maximum variability (CV 75%), while the remaining soil K fractions showed moderate to high variation. Interestingly, KNEX content also showed high variability, which essentially indicates reserve native K exploitation under intensive cultivation. These maps highlight the necessity of estimating the other soil K fractions as well for better understanding of soil K supplying capacity and K fertilization strategy rather than the current recommendations, based on the plant-available K alone. In conclusion, the present study revealed that the variability of nutrient distribution was a consequence of complex interactions between the cropping system, nutrient application rates, and the native soil characteristics, and such interactions could be utilized to develop the nutrient management strategies for intensive small-holder system.

Coronal energy distribution and X-ray activity in the small scale magnetic field of the quiet sun

NASA Technical Reports Server (NTRS)

Habbal, S. R.

1992-01-01

The energy distribution in the small-scale magnetic field that pervades the solar surface, and its relationship to X-ray/coronal activity are discussed. The observed emission from the small scale structures, at temperatures characteristic of the chromosphere, transition region and corona, emanates from the boundaries of supergranular cells, within coronal bright points. This emission is characterized by a strong temporal and spatial variability with no definite pattern. The analysis of simultaneous, multiwavelength EUV observations shows that the spatial density of the enhanced as well as variable emission from the small scale structures exhibits a pronounced temperature dependence with significant maxima at 100,000 and 1,000,000 K. Within the limits of the spatial (1-5 arcsec) and temporal (1-5 min) resolution of data available at present, the observed variability in the small scale structure cannot account for the coroal heating of the quiet sun. The characteristics of their emission are more likely to be an indicator of the coronal heating mechanisms.

The calculation of weakly non-spherical cavitation bubble impact on a solid

NASA Astrophysics Data System (ADS)

Aganin, A. A.; Guseva, T. S.; Kosolapova, L. A.; Khismatullina, N. A.

2016-11-01

The effect of small spheroidal non-sphericity of a cavitation bubble touching a solid at the beginning of its collapse on its impact on the solid of a copper-nickel alloy is investigated. The impact on the solid is realized by means of a high-speed liquid jet arising at collapse on the bubble surface. The shape of the jet, its velocity and pressure are calculated by the boundary element method. The spatial and temporal characteristics of the pressure pulses on the solid surface are determined by the CIP-CUP method on dynamically adaptive grids without explicitly separating the gas-liquid interface. The solid surface layer dynamics is evaluated by the Godunov method. The results are analyzed in dimensionless variables obtained with using the water hammer pressure, the time moment and the jet-solid contact area radius at which the jet begins to spread on the solid surface. It is shown that in those dimensionless variables, the dependence of the spatial and temporal characteristics of the solid surface pressure pulses on the initial bubble shape non-sphericity is relatively small. The nonsphericity also slightly influences the main qualitative features of the dynamic processes inside the solid, whereas its effect on their quantitative characteristics can be significant.

Short-term response of the solid Earth to cryosphere fluctuations and the earthquake cycle in south-central Alaska

NASA Astrophysics Data System (ADS)

Sauber, J. M.; Freymueller, J. T.; Han, S. C.; Davis, J. L.; Ruppert, N. A.

2016-12-01

In southern Alaska surface deformation and gravimetric change are associated with the seismic cycle as well as a strong seasonal cycle of snow accumulation and melt and a variable rate of glacier mass wastage. Numerical modeling of the solid Earth response to cryosphere change on a variety of temporal and spatial scales plays a critical role in supporting the interpretation of time-variable gravity and other geodetic data. In this study we calculate the surface displacements and stresses associated with variable spatial and temporal cryospheric loading and unloading in south-central coastal Alaska. A challenging aspect of estimating the response of the solid Earth to short-term (months to 102 years) regional cryospheric fluctuations is choosing the rock mechanics constitutive laws appropriate to this region. Here we report calculated differences in the predicted surface displacements and stresses during the GRACE time period (2002 to present). Broad-scale, GRACE-derived estimates of cryospheric mass change, along with independent snow melt onset/refreeze timing, snow depth and annual glacier wastage estimates from a variety of methods, were used to approximate the magnitude and timing of cryospheric load changes. We used the CIG finite element code PyLith to enable input of spatially complex surface loads. An as example of our evaluation of the influence of variable short-term surface loads, we calculated and contrasted the predicted surface displacements and stresses for a cooler than average and higher precipitation water year (WY12) versus a warmer than average year (WY05). Our calculation of these comparative stresses is motivated by our earlier empirical evaluation of the influence of short-term cryospheric fluctuations on the background seismic rate between 1988-2006 (Sauber and Ruppert, 2008). During the warmer than average years between 2002-2006 we found a stronger seasonal dependency in the frequency of small tectonic events in the Icy Bay region relative to cooler years. To date, we have focused our 3-D modeling on changes in the thickness of the primarily elastic layer and we also varied the Maxwell viscoelastic relaxation times for the lower crust and upper mantle. We anticipate exploring the influence of transient rheologies and testing alternate 3-D rheological structures.

Spatial variability of soil moisture retrieved by SMOS satellite

NASA Astrophysics Data System (ADS)

Lukowski, Mateusz; Marczewski, Wojciech; Usowicz, Boguslaw; Rojek, Edyta; Slominski, Jan; Lipiec, Jerzy

2015-04-01

Standard statistical methods assume that the analysed variables are independent. Since the majority of the processes observed in the nature are continuous in space and time, this assumption introduces a significant limitation for understanding the examined phenomena. In classical approach, valuable information about the locations of examined observations is completely lost. However, there is a branch of statistics, called geostatistics, which is the study of random variables, but taking into account the space where they occur. A common example of so-called "regionalized variable" is soil moisture. Using in situ methods it is difficult to estimate soil moisture distribution because it is often significantly diversified. Thanks to the geostatistical methods, by employing semivariance analysis, it is possible to get the information about the nature of spatial dependences and their lengths. Since the Soil Moisture and Ocean Salinity mission launch in 2009, the estimation of soil moisture spatial distribution for regional up to continental scale started to be much easier. In this study, the SMOS L2 data for Central and Eastern Europe were examined. The statistical and geostatistical features of moisture distributions of this area were studied for selected natural soil phenomena for 2010-2014 including: freezing, thawing, rainfalls (wetting), drying and drought. Those soil water "states" were recognized employing ground data from the agro-meteorological network of ground-based stations SWEX and SMUDP2 data from SMOS. After pixel regularization, without any upscaling, the geostatistical methods were applied directly on Discrete Global Grid (15-km resolution) in ISEA 4H9 projection, on which SMOS observations are reported. Analysis of spatial distribution of SMOS soil moisture, carried out for each data set, in most cases did not show significant trends. It was therefore assumed that each of the examined distributions of soil moisture in the adopted scale satisfies ergodicity and quasi-stationarity assumptions, required for geostatistical analysis. The semivariograms examinations revealed that spatial dependences occurring in the surface soil moisture distributions for the selected area were more or less 200 km. The exception was the driest of the studied days, when the spatial correlations of soil moisture were not disturbed for a long time by any rainfall. Spatial correlation length on that day was about 400 km. Because of zonal character of frost, the spatial dependences in the examined surface soil moisture distributions during freezing/thawing found to be disturbed. Probably, the amount of water remains the same, but it is not detected by SMOS, hence analysing dielectric constant instead of soil moisture would be more appropriate. Some spatial relations of soil moisture and freezing distribution with existing maps of soil granulometric fractions and soil specific surface area for Poland have also been found. The work was partially funded under the ELBARA_PD (Penetration Depth) project No. 4000107897/13/NL/KML. ELBARA_PD project is funded by the Government of Poland through an ESA (European Space Agency) Contract under the PECS (Plan for European Cooperating States).

Sea level: measuring the bounding surfaces of the ocean.

PubMed

Tamisiea, Mark E; Hughes, Chris W; Williams, Simon D P; Bingley, Richard M

2014-09-28

The practical need to understand sea level along the coasts, such as for safe navigation given the spatially variable tides, has resulted in tide gauge observations having the distinction of being some of the longest instrumental ocean records. Archives of these records, along with geological constraints, have allowed us to identify the century-scale rise in global sea level. Additional data sources, particularly satellite altimetry missions, have helped us to better identify the rates and causes of sea-level rise and the mechanisms leading to spatial variability in the observed rates. Analysis of all of the data reveals the need for long-term and stable observation systems to assess accurately the regional changes as well as to improve our ability to estimate future changes in sea level. While information from many scientific disciplines is needed to understand sea-level change, this review focuses on contributions from geodesy and the role of the ocean's bounding surfaces: the sea surface and the Earth's crust. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

GEWEX SRB Shortwave Release 4

NASA Astrophysics Data System (ADS)

Cox, S. J.; Stackhouse, P. W., Jr.; Mikovitz, J. C.; Zhang, T.

2017-12-01

The NASA/GEWEX Surface Radiation Budget (SRB) project produces shortwave and longwave surface and top of atmosphere radiative fluxes for the 1983-near present time period. Spatial resolution is 1 degree. The new Release 4 uses the newly processed ISCCP HXS product as its primary input for cloud and radiance data. The ninefold increase in pixel number compared to the previous ISCCP DX allows finer gradations in cloud fraction in each grid box. It will also allow higher spatial resolutions (0.5 degree) in future releases. In addition to the input data improvements, several important algorithm improvements have been made since Release 3. These include recalculated atmospheric transmissivities and reflectivities yielding a less transmissive atmosphere. The calculations also include variable aerosol composition, allowing for the use of a detailed aerosol history from the Max Planck Institut Aerosol Climatology (MAC). Ocean albedo and snow/ice albedo are also improved from Release 3. Total solar irradiance is now variable, averaging 1361 Wm-2. Water vapor is taken from ISCCP's nnHIRS product. Results from GSW Release 4 are presented and analyzed. Early comparison to surface measurements show improved agreement.

Aspect-related Vegetation Differences Amplify Soil Moisture Variability in Semiarid Landscapes

NASA Astrophysics Data System (ADS)

Yetemen, O.; Srivastava, A.; Kumari, N.; Saco, P. M.

2017-12-01

Soil moisture variability (SMV) in semiarid landscapes is affected by vegetation, soil texture, climate, aspect, and topography. The heterogeneity in vegetation cover that results from the effects of microclimate, terrain attributes (slope gradient, aspect, drainage area etc.), soil properties, and spatial variability in precipitation have been reported to act as the dominant factors modulating SMV in semiarid ecosystems. However, the role of hillslope aspect in SMV, though reported in many field studies, has not received the same degree of attention probably due to the lack of extensive large datasets. Numerical simulations can then be used to elucidate the contribution of aspect-driven vegetation patterns to this variability. In this work, we perform a sensitivity analysis to study on variables driving SMV using the CHILD landscape evolution model equipped with a spatially-distributed solar-radiation component that couples vegetation dynamics and surface hydrology. To explore how aspect-driven vegetation heterogeneity contributes to the SMV, CHILD was run using a range of parameters selected to reflect different scenarios (from uniform to heterogeneous vegetation cover). Throughout the simulations, the spatial distribution of soil moisture and vegetation cover are computed to estimate the corresponding coefficients of variation. Under the uniform spatial precipitation forcing and uniform soil properties, the factors affecting the spatial distribution of solar insolation are found to play a key role in the SMV through the emergence of aspect-driven vegetation patterns. Hence, factors such as catchment gradient, aspect, and latitude, define water stress and vegetation growth, and in turn affect the available soil moisture content. Interestingly, changes in soil properties (porosity, root depth, and pore-size distribution) over the domain are not as effective as the other factors. These findings show that the factors associated to aspect-related vegetation differences amplify the soil moisture variability of semi-arid landscapes.

Wind effect on salt transport variability in the Bay of Bengal

NASA Astrophysics Data System (ADS)

Sandeep, K. K.; Pant, V.

2017-12-01

The Bay of Bengal (BoB) exhibits large spatial variability in sea surface salinity (SSS) pattern caused by its unique hydrological, meteorological and oceanographical characteristics. This SSS variability is largely controlled by the seasonally reversing monsoon winds and the associated currents. Further, the BoB receives substantial freshwater inputs through excess precipitation over evaporation and river discharge. Rivers like Ganges, Brahmaputra, Mahanadi, Krishna, Godavari, and Irawwady discharge annually a freshwater volume in range between 1.5 x 1012 and 1.83 x 1013 m3 into the bay. A major volume of this freshwater input to the bay occurs during the southwest monsoon (June-September) period. In the present study, a relative role of winds in the SSS variability in the bay is investigated by using an eddy-resolving three dimensional Regional Ocean Modeling System (ROMS) numerical model. The model is configured with realistic bathymetry, coastline of study region and forced with daily climatology of atmospheric variables. River discharges from the major rivers are distributed in the model grid points representing their respective geographic locations. Salt transport estimate from the model simulation for realistic case are compared with the standard reference datasets. Further, different experiments were carried out with idealized surface wind forcing representing the normal, low, high, and very high wind speed conditions in the bay while retaining the realistic daily varying directions for all the cases. The experimental simulations exhibit distinct dispersal patterns of the freshwater plume and SSS in different experiments in response to the idealized winds. Comparison of the meridional and zonal surface salt transport estimated for each experiment showed strong seasonality with varying magnitude in the bay with a maximum spatial and temporal variability in the western and northern parts of the BoB.

Global Distribution and Variability of Surface Skin and Surface Air Temperatures as Depicted in the AIRS Version-6 Data Set

NASA Technical Reports Server (NTRS)

Susskind, Joel; Lee, Jae N.; Iredell, Lena

2014-01-01

In this presentation, we will briefly describe the significant improvements made in the AIRS Version-6 retrieval algorithm, especially as to how they affect retrieved surface skin and surface air temperatures. The global distribution of seasonal 1:30 AM and 1:30 PM local time 12 year climatologies of Ts,a will be presented for the first time. We will also present the spatial distribution of short term 12 year anomaly trends of Ts,a at 1:30 AM and 1:30 PM, as well as the spatial distribution of temporal correlations of Ts,a with the El Nino Index. It will be shown that there are significant differences between the behavior of 1:30 AM and 1:30 PM Ts,a anomalies in some arid land areas.

A Stabilizing Feedback Between Cloud Radiative Effects and Greenland Surface Melt: Verification From Multi-year Automatic Weather Station Measurements

NASA Astrophysics Data System (ADS)

Zender, C. S.; Wang, W.; van As, D.

2017-12-01

Clouds have strong impacts on Greenland's surface melt through the interaction with the dry atmosphere and reflective surfaces. However, their effects are uncertain due to the lack of in situ observations. To better quantify cloud radiative effects (CRE) in Greenland, we analyze and interpret multi-year radiation measurements from 30 automatic weather stations encompassing a broad range of climatological and topographical conditions. During melt season, clouds warm surface over most of Greenland, meaning the longwave greenhouse effect outweighs the shortwave shading effect; on the other hand, the spatial variability of net (longwave and shortwave) CRE is dominated by shortwave CRE and in turn by surface albedo, which controls the potential absorption of solar radiation when clouds are absent. The net warming effect decreases with shortwave CRE from high to low altitudes and from north to south (Fig. 1). The spatial correlation between albedo and net CRE is strong (r=0.93, p<<0.01). In the accumulation zone, the net CRE seasonal trend is controlled by longwave CRE associated with cloud fraction and liquid water content. It becomes stronger from May to July and stays constant in August. In the ablation zone, albedo determines the net CRE seasonal trend, which decreases from May to July and increases afterwards. On an hourly timescale, we find two distinct radiative states in Greenland (Fig. 2). The clear state is characterized by clear-sky conditions or thin clouds, when albedo and solar zenith angle (SZA) weakly correlates with CRE. The cloudy state is characterized by opaque clouds, when the combination of albedo and SZA strongly correlates with CRE (r=0.85, p<0.01). Although cloud properties intrinsically affect CRE, the large melt-season variability of these two non-cloud factors, albedo and solar zenith angle, explains the majority of the CRE variation in spatial distribution, seasonal trend in the ablation zone, and in hourly variability in the cloudy radiative state. Clouds warm the brighter and colder surfaces of Greenland, enhance snow melt, and tend to lower the albedo. Clouds cool the darker and warmer surfaces, inhibiting snow melt, which increases albedo, and thus stabilizes surface melt. This stabilizing mechanism may also occur over sea ice, helping to forestall surface melt as the Arctic becomes dimmer.

Estimating under-five mortality in space and time in a developing world context.

PubMed

Wakefield, Jon; Fuglstad, Geir-Arne; Riebler, Andrea; Godwin, Jessica; Wilson, Katie; Clark, Samuel J

2018-01-01

Accurate estimates of the under-five mortality rate in a developing world context are a key barometer of the health of a nation. This paper describes a new model to analyze survey data on mortality in this context. We are interested in both spatial and temporal description, that is wishing to estimate under-five mortality rate across regions and years and to investigate the association between the under-five mortality rate and spatially varying covariate surfaces. We illustrate the methodology by producing yearly estimates for subnational areas in Kenya over the period 1980-2014 using data from the Demographic and Health Surveys, which use stratified cluster sampling. We use a binomial likelihood with fixed effects for the urban/rural strata and random effects for the clustering to account for the complex survey design. Smoothing is carried out using Bayesian hierarchical models with continuous spatial and temporally discrete components. A key component of the model is an offset to adjust for bias due to the effects of HIV epidemics. Substantively, there has been a sharp decline in Kenya in the under-five mortality rate in the period 1980-2014, but large variability in estimated subnational rates remains. A priority for future research is understanding this variability. In exploratory work, we examine whether a variety of spatial covariate surfaces can explain the variability in under-five mortality rate. Temperature, precipitation, a measure of malaria infection prevalence, and a measure of nearness to cities were candidates for inclusion in the covariate model, but the interplay between space, time, and covariates is complex.

Variability in Soil Properties at Different Spatial Scales (1 m to 1 km) in a Deciduous Forest Ecosystem

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

Garten Jr, Charles T; Kang, S.; Brice, Deanne Jane

2007-01-01

The purpose of this research was to test the hypothesis that variability in 11 soil properties, related to soil texture and soil C and N, would increase from small (1 m) to large (1 km) spatial scales in a temperate, mixed-hardwood forest ecosystem in east Tennessee, USA. The results were somewhat surprising and indicated that a fundamental assumption in geospatial analysis, namely that variability increases with increasing spatial scale, did not apply for at least five of the 11 soil properties measured over a 0.5-km2 area. Composite mineral soil samples (15 cm deep) were collected at 1, 5, 10, 50,more » 250, and 500 m distances from a center point along transects in a north, south, east, and westerly direction. A null hypothesis of equal variance at different spatial scales was rejected (P{le}0.05) for mineral soil C concentration, silt content, and the C-to-N ratios in particulate organic matter (POM), mineral-associated organic matter (MOM), and whole surface soil. Results from different tests of spatial variation, based on coefficients of variation or a Mantel test, led to similar conclusions about measurement variability and geographic distance for eight of the 11 variables examined. Measurements of mineral soil C and N concentrations, C concentrations in MOM, extractable soil NH{sub 4}-N, and clay contents were just as variable at smaller scales (1-10 m) as they were at larger scales (50-500 m). On the other hand, measurement variation in mineral soil C-to-N ratios, MOM C-to-N ratios, and the fraction of soil C in POM clearly increased from smaller to larger spatial scales. With the exception of extractable soil NH4-N, measured soil properties in the forest ecosystem could be estimated (with 95% confidence) to within 15% of their true mean with a relatively modest number of sampling points (n{le}25). For some variables, scaling up variation from smaller to larger spatial domains within the ecosystem could be relatively easy because small-scale variation may be indicative of variation at larger scales.« less

Integrating time-series and spatial surveys to assess annual, lake-wide emissions of carbon dioxide and methane from a eutrophic lake

NASA Astrophysics Data System (ADS)

Loken, L. C.; Crawford, J.; Schramm, P.; Stadler, P.; Stanley, E. H.

2017-12-01

Lakes are important regulators of global carbon cycling and conduits of greenhouse gases to the atmosphere; however, most efflux estimates for individual lakes are based on extrapolations from a limited number of locations. Within-lake variability in carbon dioxide (CO2) and methane (CH4) arises from differences in water sources, physical mixing, and biogeochemical transformations; all of which can vary at multiple temporal and spatial scales. We mapped surface water concentrations of CO2 and CH4 weekly across Lake Mendota (a 39.9 km2 eutrophic lake in Wisconsin, USA) spanning the majority of the 2016 ice-free season (249 days). Combining these maps with a spatially explicit gas transfer velocity (k) model, we estimated the diffusive exchange of both gases with the atmosphere taking into account both spatial and temporal heterogeneity. The cumulative efflux of CO2 (85.3 Mmol) and CH4 (9.47 Mmol) was positive, indicating that on the annual scale Lake Mendota was a net-source of both gases to the atmosphere. Although our model included variability in k, flux patterns reflected the patterns in gas concentrations. During the stratified period, CO2 was generally undersaturated throughout the pelagic zone due to high primary production and differed near river inlets and shorelines. The lake was routinely extremely supersaturated with CH4 with elevated concentrations in expansive littoral areas. During fall mixis, concentrations of both gases increased and became more variable across the lake surface, and their spatial arrangement changed reflecting hypolimentic mixing. In this system, samples collected from the lake center reasonably well-represented the lake-wide mean CO2 concentration, but they poorly represented CH4. While metabolic processes driving CO2 varied across the lake surface, pelagic phytoplankton contributed extensively to overall primary production, which acted at the lake-wide scale. Additionally Lake Mendota's high alkalinity may have masked the metabolic imprint on CO2 patterns. In contrast, heterogeneous CH4 transformations and transport lead to remarkable variation in CH4 across the lake surface that was dynamic through time. Thus, extrapolations from a limited number of locations or timepoints may not adequately describe lake-wide CH4 dynamics.

Surface Modification and Surface - Subsurface Exchange Processes on Europa

NASA Astrophysics Data System (ADS)

Phillips, Cynthia B.; Molaro, Jamie; Hand, Kevin P.

2017-10-01

The surface of Jupiter’s moon Europa is modified by exogenic processes such as sputtering, gardening, radiolysis, sulfur ion implantation, and thermal processing, as well as endogenic processes including tidal shaking, mass wasting, and the effects of subsurface tectonic and perhaps cryovolcanic activity. New materials are created or deposited on the surface (radiolysis, micrometeorite impacts, sulfur ion implantation, cryovolcanic plume deposits), modified in place (thermal segregation, sintering), transported either vertically or horizontally (sputtering, gardening, mass wasting, tectonic and cryovolcanic activity), or lost from Europa completely (sputtering, plumes, larger impacts). Some of these processes vary spatially, as visible in Europa’s leading-trailing hemisphere brightness asymmetry.Endogenic geologic processes also vary spatially, depending on terrain type. The surface can be classified into general landform categories that include tectonic features (ridges, bands, cracks); disrupted “chaos-type” terrain (chaos blocks, matrix, domes, pits, spots); and impact craters (simple, complex, multi-ring). The spatial distribution of these terrain types is relatively random, with some differences in apex-antiapex cratering rates and latitudinal variation in chaos vs. tectonic features.In this work, we extrapolate surface processes and rates from the top meter of the surface in conjunction with global estimates of transport and resurfacing rates. We combine near-surface modification with an estimate of surface-subsurface (and vice versa) transport rates for various geologic terrains based on an average of proposed formation mechanisms, and a spatial distribution of each landform type over Europa’s surface area.Understanding the rates and mass balance for each of these processes, as well as their spatial and temporal variability, allows us to estimate surface - subsurface exchange rates over the average surface age (~50myr) of Europa. Quantifying the timescale and volume of transported material will yield insight on whether such a process may provide fuel to sustain a biosphere in Europa’s subsurface ocean, which is relevant to searches for life by a future mission such as a potential Europa Lander.

Surface Modification and Surface - Subsurface Exchange Processes on Europa

NASA Astrophysics Data System (ADS)

Phillips, C. B.; Molaro, J.; Hand, K. P.

2017-12-01

The surface of Jupiter's moon Europa is modified by exogenic processes such as sputtering, gardening, radiolysis, sulfur ion implantation, and thermal processing, as well as endogenic processes including tidal shaking, mass wasting, and the effects of subsurface tectonic and perhaps cryovolcanic activity. New materials are created or deposited on the surface (radiolysis, micrometeorite impacts, sulfur ion implantation, cryovolcanic plume deposits), modified in place (thermal segregation, sintering), transported either vertically or horizontally (sputtering, gardening, mass wasting, tectonic and cryovolcanic activity), or lost from Europa completely (sputtering, plumes, larger impacts). Some of these processes vary spatially, as visible in Europa's leading-trailing hemisphere brightness asymmetry. Endogenic geologic processes also vary spatially, depending on terrain type. The surface can be classified into general landform categories that include tectonic features (ridges, bands, cracks); disrupted "chaos-type" terrain (chaos blocks, matrix, domes, pits, spots); and impact craters (simple, complex, multi-ring). The spatial distribution of these terrain types is relatively random, with some differences in apex-antiapex cratering rates and latitudinal variation in chaos vs. tectonic features. In this work, we extrapolate surface processes and rates from the top meter of the surface in conjunction with global estimates of transport and resurfacing rates. We combine near-surface modification with an estimate of surface-subsurface (and vice versa) transport rates for various geologic terrains based on an average of proposed formation mechanisms, and a spatial distribution of each landform type over Europa's surface area. Understanding the rates and mass balance for each of these processes, as well as their spatial and temporal variability, allows us to estimate surface - subsurface exchange rates over the average surface age ( 50myr) of Europa. Quantifying the timescale and volume of transported material will yield insight on whether such a process may provide fuel to sustain a biosphere in Europa's subsurface ocean, which is relevant to searches for life by a future mission such as a potential Europa Lander.

Comparing maps of mean monthly surface temperature and precipitation for Alaska and adjacent areas of Canada produced by two different methods

USGS Publications Warehouse

Simpson, James J.; Hufford, Gary L.; Daly, Christopher; Berg, Jared S.; Fleming, Michael D.

2005-01-01

Maps of mean monthly surface temperature and precipitation for Alaska and adjacent areas of Canada, produced by Oregon State University's Spatial Climate Analysis Service (SCAS) and the Alaska Geospatial Data Clearinghouse (AGDC), were analyzed. Because both sets of maps are generally available and in use by the community, there is a need to document differences between the processes and input data sets used by the two groups to produce their respective set of maps and to identify similarities and differences between the two sets of maps and possible reasons for the differences. These differences do not affect the observed large-scale patterns of seasonal and annual variability. Alaska is divided into interior and coastal zones, with consistent but different variability, separated by a transition region. The transition region has high interannual variability but low long-term mean variability. Both data sets support the four major ecosystems and ecosystem transition zone identified in our earlier work. Differences between the two sets of maps do occur, however, on the regional scale; they reflect differences in physiographic domains and in the treatment of these domains by the two groups (AGDC, SCAS). These differences also provide guidance for an improved observational network for Alaska. On the basis of validation with independent in situ data, we conclude that the data set produced by SCAS provides the best spatial coverage of Alaskan long-term mean monthly surface temperature and precipitation currently available. ?? The Arctic Institute of North America.

Snowpack spatial and temporal variability assessment using SMP high-resolution penetrometer

NASA Astrophysics Data System (ADS)

Komarov, Anton; Seliverstov, Yuriy; Sokratov, Sergey; Grebennikov, Pavel

2017-04-01

This research is focused on study of spatial and temporal variability of structure and characteristics of snowpack, quick identification of layers based on hardness and dispersion values received from snow micro penetrometer (SMP). We also discuss the detection of weak layers and definition of their parameters in non-alpine terrain. As long as it is the first SMP tool available in Russia, our intent is to test it in different climate and weather conditions. During two separate snowpack studies in plain and mountain landscapes, we derived density and grain size profiles by comparing snow density and grain size from snowpits and SMP measurements. The first case study was MSU meteorological observatory test site in Moscow. SMP data was obtained by 6 consecutive measurements along 10 m transects with a horizontal resolution of approximately 50 cm. The detailed description of snowpack structure, density, grain size, air and snow temperature was also performed. By comparing this information, the detailed scheme of snowpack evolution was created. The second case study was in Khibiny mountains. One 10-meter-long transect was made. SMP, density, grain size and snow temperature data was obtained with horizontal resolution of approximately 50 cm. The high-definition profile of snowpack density variation was acquired using received data. The analysis of data reveals high spatial and temporal variability in snow density and layer structure in both horizontal and vertical dimensions. It indicates that the spatial variability is exhibiting similar spatial patterns as surface topology. This suggests a strong influence from such factors as wind and liquid water pressure on the temporal and spatial evolution of snow structure. It was also defined, that spatial variation of snowpack characteristics is substantial even within homogeneous plain landscape, while in high-latitude mountain regions it grows significantly.

Spatial statistics of hydrography and water chemistry in a eutrophic boreal lake based on sounding and water samples.

PubMed

Leppäranta, Matti; Lewis, John E; Heini, Anniina; Arvola, Lauri

2018-06-04

Spatial variability, an essential characteristic of lake ecosystems, has often been neglected in field research and monitoring. In this study, we apply spatial statistical methods for the key physics and chemistry variables and chlorophyll a over eight sampling dates in two consecutive years in a large (area 103 km 2 ) eutrophic boreal lake in southern Finland. In the four summer sampling dates, the water body was vertically and horizontally heterogenic except with color and DOC, in the two winter ice-covered dates DO was vertically stratified, while in the two autumn dates, no significant spatial differences in any of the measured variables were found. Chlorophyll a concentration was one order of magnitude lower under the ice cover than in open water. The Moran statistic for spatial correlation was significant for chlorophyll a and NO 2 +NO 3 -N in all summer situations and for dissolved oxygen and pH in three cases. In summer, the mass centers of the chemicals were within 1.5 km from the geometric center of the lake, and the 2nd moment radius ranged in 3.7-4.1 km respective to 3.9 km for the homogeneous situation. The lateral length scales of the studied variables were 1.5-2.5 km, about 1 km longer in the surface layer. The detected spatial "noise" strongly suggests that besides vertical variation also the horizontal variation in eutrophic lakes, in particular, should be considered when the ecosystems are monitored.

Spatial distributions ofC3 and C4 grass functional types in the U.S. great plains and their despendency on inter-annual climate variability

USDA-ARS?s Scientific Manuscript database

Grassland ecosystems in North America are primarily composed of C3 and C4 plant functional types (PFTs) with their relative cover varying spatially and temporally. This study used 500-m MODIS surface reflectance products (MOD09A1) from 2000 to 2009 to extract an NDVI time series of C3 and C4 PFTs in...

An investigation of the observability of ocean-surface parameters using GEOS-3 backscatter data

NASA Technical Reports Server (NTRS)

Miller, L. S.; Priester, R. W.

1978-01-01

The degree to which ocean surface roughness can be synoptically observed through use of the information extracted from the GEOS-3 backscattered waveform data was evaluated. Algorithms are given for use in estimating the radar sensed waveheight distribution or ocean-surface impulse response. Other factors discussed include comparisons between theoretical and experimental radar cross section values, sea state bias effects, spatial variability of significant waveheight data, and sensor-related considerations.

Analysis of satellite precipitation over East Africa during last decades

NASA Astrophysics Data System (ADS)

Cattani, Elsa; Wenhaji Ndomeni, Claudine; Merino, Andrés; Levizzani, Vincenzo

2016-04-01

Daily accumulated precipitation time series from satellite retrieval algorithms (e.g., ARC2 and TAMSAT) are exploited to extract the spatial and temporal variability of East Africa (EA - 5°S-20°N, 28°E-52°E) precipitation during last decades (1983-2013). The Empirical Orthogonal Function (EOF) analysis is applied to precipitation time series to investigate the spatial and temporal variability in particular for October-November-December referred to as the short rain season. Moreover, the connection among EA's precipitation, sea surface temperature, and soil moisture is analyzed through the correlation with the dominant EOF modes of variability. Preliminary results concern the first two EOF's modes for the ARC2 data set. EOF1 is characterized by an inter-annual variability and a positive correlation between precipitation and El Niño, positive Indian Ocean Dipole mode, and soil moisture, while EOF2 shows a dipole structure of spatial variability associated with a longer scale temporal variability. This second dominant mode is mostly linked to sea surface temperature variations in the North Atlantic Ocean. Further analyses are carried out by computing the time series of the joint CCI/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI, http://etccdi.pacificclimate.org/index.shtml), i.e. RX1day, RX5day, CDD, CDD, CWD, SDII, PRCPTOT, R10, R20. The purpose is to identify the occurrenes of extreme events (droughts and floods) and extract precipitation temporal variation by trend analysis (Mann-Kendall technique). Results for the ARC2 data set demonstrate the existence of a dipole spatial pattern in the linear trend of the time series of PRCPTOT (annual precipitation considering days with a rain rate > 1 mm) and SDII (average precipitation on wet days over a year). A negative trend is mainly present over West Ethiopia and Sudan, whereas a positive trend is exhibited over East Ethiopia and Somalia. CDD (maximum number of consecutive dry days) and CWD (maximum number of consecutive wet days) time series do not exhibit a similar behavior and trends are generally weaker with a lower significance level with respect to PRCPTOT and SDII.

Landsat classification of surface-water presence during multiple years to assess response of playa wetlands to climatic variability across the Great Plains Landscape Conservation Cooperative region

USGS Publications Warehouse

Manier, Daniel J.; Rover, Jennifer R.

2018-02-15

To improve understanding of the distribution of ecologically important, ephemeral wetland habitats across the Great Plains, the occurrence and distribution of surface water in playa wetland complexes were documented for four different years across the Great Plains Landscape Conservation Cooperative (GPLCC) region. This information is important because it informs land and wildlife managers about the timing and location of habitat availability. Data with an accurate timestamp that indicate the presence of water, the percent of the area inundated with water, and the spatial distribution of playa wetlands with water are needed for a host of resource inventory, monitoring, and research applications. For example, the distribution of inundated wetlands forms the spatial pattern of available habitat for resident shorebirds and water birds, stop-over habitats for migratory birds, connectivity and clustering of wetland habitats, and surface waters that recharge the Ogallala aquifer; there is considerable variability in the distribution of playa wetlands holding water through time. Documentation of these spatially and temporally intricate processes, here, provides data required to assess connections between inundation and multiple environmental drivers, such as climate, land use, soil, and topography. Climate drivers are understood to interact with land cover, land use and soil attributes in determining the amount of water that flows overland into playa wetlands. Results indicated significant spatial variability represented by differences in the percent of playas inundated among States within the GPLCC. Further, analysis-of-variance comparison of differences in inundation between years showed significant differences in all cases. Although some connections with seasonal moisture patterns may be observed, the complex spatial-temporal gradients of precipitation, temperature, soils, and land use need to be combined as covariates in multivariate models to effectively account for these patterns. We demonstrate the feasibility of using classification of Landsat satellite imagery to describe playa-wetland inundation across years and seasons. Evaluating classifications representing only 4 years of imagery, we found significant year-to-year and state-to-state differences in inundation rates.

Groundwater impacts on surface water quality and nutrient loads in lowland polder catchments: monitoring the greater Amsterdam area

NASA Astrophysics Data System (ADS)

Yu, Liang; Rozemeijer, Joachim; van Breukelen, Boris M.; Ouboter, Maarten; van der Vlugt, Corné; Broers, Hans Peter

2018-01-01

The Amsterdam area, a highly manipulated delta area formed by polders and reclaimed lakes, struggles with high nutrient levels in its surface water system. The polders receive spatially and temporally variable amounts of water and nutrients via surface runoff, groundwater seepage, sewer leakage, and via water inlets from upstream polders. Diffuse anthropogenic sources, such as manure and fertiliser use and atmospheric deposition, add to the water quality problems in the polders. The major nutrient sources and pathways have not yet been clarified due to the complex hydrological system in lowland catchments with both urban and agricultural areas. In this study, the spatial variability of the groundwater seepage impact was identified by exploiting the dense groundwater and surface water monitoring networks in Amsterdam and its surrounding polders. A total of 25 variables (concentrations of total nitrogen (TN), total phosphorus (TP), NH4, NO3, HCO3, SO4, Ca, and Cl in surface water and groundwater, N and P agricultural inputs, seepage rate, elevation, land-use, and soil type) for 144 polders were analysed statistically and interpreted in relation to sources, transport mechanisms, and pathways. The results imply that groundwater is a large source of nutrients in the greater Amsterdam mixed urban-agricultural catchments. The groundwater nutrient concentrations exceeded the surface water environmental quality standards (EQSs) in 93 % of the polders for TP and in 91 % for TN. Groundwater outflow into the polders thus adds to nutrient levels in the surface water. High correlations (R2 up to 0.88) between solutes in groundwater and surface water, together with the close similarities in their spatial patterns, confirmed the large impact of groundwater on surface water chemistry, especially in the polders that have high seepage rates. Our analysis indicates that the elevated nutrient and bicarbonate concentrations in the groundwater seepage originate from the decomposition of organic matter in subsurface sediments coupled to sulfate reduction and possibly methanogenesis. The large loads of nutrient-rich groundwater seepage into the deepest polders indirectly affect surface water quality in the surrounding area, because excess water from the deep polders is pumped out and used to supply water to the surrounding infiltrating polders in dry periods. The study shows the importance of the connection between groundwater and surface water nutrient chemistry in the greater Amsterdam area. We expect that taking account of groundwater-surface water interaction is also important in other subsiding and urbanising deltas around the world, where water is managed intensively in order to enable agricultural productivity and achieve water-sustainable cities.

Improved MODIS aerosol retrieval in urban areas using a land classification approach and empirical orthogonal functions

NASA Astrophysics Data System (ADS)

Levitan, Nathaniel; Gross, Barry

2016-10-01

New, high-resolution aerosol products are required in urban areas to improve the spatial coverage of the products, in terms of both resolution and retrieval frequency. These new products will improve our understanding of the spatial variability of aerosols in urban areas and will be useful in the detection of localized aerosol emissions. Urban aerosol retrieval is challenging for existing algorithms because of the high spatial variability of the surface reflectance, indicating the need for improved urban surface reflectance models. This problem can be stated in the language of novelty detection as the problem of selecting aerosol parameters whose effective surface reflectance spectrum is not an outlier in some space. In this paper, empirical orthogonal functions, a reconstruction-based novelty detection technique, is used to perform single-pixel aerosol retrieval using the single angular and temporal sample provided by the MODIS sensor. The empirical orthogonal basis functions are trained for different land classes using the MODIS BRDF MCD43 product. Existing land classification products are used in training and aerosol retrieval. The retrieval is compared against the existing operational MODIS 3 KM Dark Target (DT) aerosol product and co-located AERONET data. Based on the comparison, our method allows for a significant increase in retrieval frequency and a moderate decrease in the known biases of MODIS urban aerosol retrievals.

A soil-landscape framework for understanding spatial and temporal variability in biogeochemical processes in catchments

NASA Astrophysics Data System (ADS)

McGuire, K. J.; Bailey, S. W.; Ross, D. S.

2017-12-01

Heterogeneity in biophysical properties within catchments challenges how we quantify and characterize biogeochemical processes and interpret catchment outputs. Interactions between the spatiotemporal variability of hydrological states and fluxes and soil development can spatially structure catchments, leading to a framework for understanding patterns in biogeochemical processes. In an upland, glaciated landscape at the Hubbard Brook Experimental Forest (HBEF) in New Hampshire, USA, we are embracing the structure and organization of soils to understand the spatial relations between runoff production zones, distinct soil-biogeochemical environments, and solute retention and release. This presentation will use observations from the HBEF to demonstrate that a soil-landscape framework is essential in understanding the spatial and temporal variability of biogeochemical processes in this catchment. Specific examples will include how laterally developed soils reveal the location of active runoff production zones and lead to gradients in primary mineral dissolution and the distribution of weathering products along hillslopes. Soil development patterns also highlight potential carbon and nitrogen cycling hotspots, differentiate acidic conditions, and affect the regulation of surface water quality. Overall, this work demonstrates the importance of understanding the landscape-level structural organization of soils in characterizing the variation and extent of biogeochemical processes that occur in catchments.

Radiation Products based on a constellation of Geostationary Satellites

NASA Astrophysics Data System (ADS)

Trigo, I. F.; Freitas, S. C.; Barroso, C.; Macedo, J.; Perdigão, R.; Silva, R.; Viterbo, P.

2012-04-01

The various components of the surface radiation budget present high variability in time and space, particularly over land surfaces where spatial heterogeneity of the upward fluxes is high. Geostationary satellites are well-suited to describe the daily cycle of downward and upward radiation fluxes and present spatial resolutions of the order of 3-to-5 km at sub-satellite point, acceptable for many applications. The work presented here is being carried out within the framework of Geoland-2 project, and aims the use of data from geostationary platforms to generate, archive and distribute in near real time four component of the surface radiation budget: land surface albedo, land surface temperature (LST) and downward short- and long-wave fluxes at the surface. All four components are retrieved from the following satellites - GOES-W covering North and South America, Meteosat Second Generation (MSG) covering essentially Europe and Africa, and MTSAT covering part of Asia and Australia. The variables are retrieved independently from each satellite and then merged into a single field, with a 5 km spatial resolution. Data are generated hourly in the case of the downward fluxes and LST, and 10-daily in the case of albedo. In regions covered by both GOES and MSG disks, the interpolated field makes use of both retrievals, giving more weight to those with lower uncertainty. The four components of the surface radiation budget described above are assessed through comparisons with similar parameters retrieved from other sensors (e.g., MODIS, CERES) or from models (e.g., ECMWF forecasts), as well as with in situ observations when available. The presentation will be focused on a brief description of algorithms and auxiliary data used in product estimation. The results of inter-comparisons with other data sources, along with the identification of the retrieval conditions that allow optimal / sub-optimal estimation of these surface radiation parameters will also be analysed. The radiation products generated within the Geoland-2 project are freely available to the user community.

Atmospheric Parameter Climatologies from AIRS: Monitoring Short-, and Longer-Term Climate Variabilities and 'Trends'

NASA Technical Reports Server (NTRS)

Molnar, Gyula; Susskind, Joel

2008-01-01

The AIRS instrument is currently the best space-based tool to simultaneously monitor the vertical distribution of key climatically important atmospheric parameters as well as surface properties, and has provided high quality data for more than 5 years. AIRS analysis results produced at the GODDARD/DAAC, based on Versions 4 & 5 of the AIRS retrieval algorithm, are currently available for public use. Here, first we present an assessment of interrelationships of anomalies (proxies of climate variability based on 5 full years, since Sept. 2002) of various climate parameters at different spatial scales. We also present AIRS-retrievals-based global, regional and 1x1 degree grid-scale "trend"-analyses of important atmospheric parameters for this 5-year period. Note that here "trend" simply means the linear fit to the anomaly (relative the mean seasonal cycle) time series of various parameters at the above-mentioned spatial scales, and we present these to illustrate the usefulness of continuing AIRS-based climate observations. Preliminary validation efforts, in terms of intercomparisons of interannual variabilities with other available satellite data analysis results, will also be addressed. For example, we show that the outgoing longwave radiation (OLR) interannual spatial variabilities from the available state-of-the-art CERES measurements and from the AIRS computations are in remarkably good agreement. Version 6 of the AIRS retrieval scheme (currently under development) promises to further improve bias agreements for the absolute values by implementing a more accurate radiative transfer model for the OLR computations and by improving surface emissivity retrievals.

Spatially telescoping measurements for improved characterization of groundwater-surface water interactions

USGS Publications Warehouse

Kikuchi, Colin; Ferre, Ty P.A.; Welker, Jeffery M.

2012-01-01

The suite of measurement methods available to characterize fluxes between groundwater and surface water is rapidly growing. However, there are few studies that examine approaches to design of field investigations that include multiple methods. We propose that performing field measurements in a spatially telescoping sequence improves measurement flexibility and accounts for nested heterogeneities while still allowing for parsimonious experimental design. We applied this spatially telescoping approach in a study of ground water-surface water (GW-SW) interaction during baseflow conditions along Lucile Creek, located near Wasilla, Alaska. Catchment-scale data, including channel geomorphic indices and hydrogeologic transects, were used to screen areas of potentially significant GW-SW exchange. Specifically, these data indicated increasing groundwater contribution from a deeper regional aquifer along the middle to lower reaches of the stream. This initial assessment was tested using reach-scale estimates of groundwater contribution during baseflow conditions, including differential discharge measurements and the use of chemical tracers analyzed in a three-component mixing model. The reach-scale measurements indicated a large increase in discharge along the middle reaches of the stream accompanied by a shift in chemical composition towards a regional groundwater end member. Finally, point measurements of vertical water fluxes -- obtained using seepage meters as well as temperature-based methods -- were used to evaluate spatial and temporal variability of GW-SW exchange within representative reaches. The spatial variability of upward fluxes, estimated using streambed temperature mapping at the sub-reach scale, was observed to vary in relation to both streambed composition and the magnitude of groundwater contribution from differential discharge measurements. The spatially telescoping approach improved the efficiency of this field investigation. Beginning our assessment with catchment-scale data allowed us to identify locations of GW-SW exchange, plan measurements at representative field sites and improve our interpretation of reach-scale and point-scale measurements.

Forward-Looking Infrared Cameras for Micrometeorological Applications within Vineyards

PubMed Central

Katurji, Marwan; Zawar-Reza, Peyman

2016-01-01

We apply the principles of atmospheric surface layer dynamics within a vineyard canopy to demonstrate the use of forward-looking infrared cameras measuring surface brightness temperature (spectrum bandwidth of 7.5 to 14 μm) at a relatively high temporal rate of 10 s. The temporal surface brightness signal over a few hours of the stable nighttime boundary layer, intermittently interrupted by periods of turbulent heat flux surges, was shown to be related to the observed meteorological measurements by an in situ eddy-covariance system, and reflected the above-canopy wind variability. The infrared raster images were collected and the resultant self-organized spatial cluster provided the meteorological context when compared to in situ data. The spatial brightness temperature pattern was explained in terms of the presence or absence of nighttime cloud cover and down-welling of long-wave radiation and the canopy turbulent heat flux. Time sequential thermography as demonstrated in this research provides positive evidence behind the application of thermal infrared cameras in the domain of micrometeorology, and to enhance our spatial understanding of turbulent eddy interactions with the surface. PMID:27649208

Influence of snow cover changes on surface radiation and heat balance based on the WRF model

NASA Astrophysics Data System (ADS)

Yu, Lingxue; Liu, Tingxiang; Bu, Kun; Yang, Jiuchun; Chang, Liping; Zhang, Shuwen

2017-10-01

The snow cover extent in mid-high latitude areas of the Northern Hemisphere has significantly declined corresponding to the global warming, especially since the 1970s. Snow-climate feedbacks play a critical role in regulating the global radiation balance and influencing surface heat flux exchange. However, the degree to which snow cover changes affect the radiation budget and energy balance on a regional scale and the difference between snow-climate and land use/cover change (LUCC)-climate feedbacks have been rarely studied. In this paper, we selected Heilongjiang Basin, where the snow cover has changed obviously, as our study area and used the WRF model to simulate the influences of snow cover changes on the surface radiation budget and heat balance. In the scenario simulation, the localized surface parameter data improved the accuracy by 10 % compared with the control group. The spatial and temporal analysis of the surface variables showed that the net surface radiation, sensible heat flux, Bowen ratio, temperature and percentage of snow cover were negatively correlated and that the ground heat flux and latent heat flux were positively correlated with the percentage of snow cover. The spatial analysis also showed that a significant relationship existed between the surface variables and land cover types, which was not obviously as that for snow cover changes. Finally, six typical study areas were selected to quantitatively analyse the influence of land cover types beneath the snow cover on heat absorption and transfer, which showed that when the land was snow covered, the conversion of forest to farmland can dramatically influence the net radiation and other surface variables, whereas the snow-free land showed significantly reduced influence. Furthermore, compared with typical land cover changes, e.g., the conversion of forest into farmland, the influence of snow cover changes on net radiation and sensible heat flux were 60 % higher than that of land cover changes, indicating the importance of snow cover changes in the surface-atmospheric feedback system.

Mapping and spatiotemporal analysis tool for hydrological data: Spellmap

USDA-ARS?s Scientific Manuscript database

Lack of data management and analyses tools is one of the major limitations to effectively evaluate and use large datasets of high-resolution atmospheric, surface, and subsurface observations. High spatial and temporal resolution datasets better represent the spatiotemporal variability of hydrologica...

Simple Approaches for Measuring Dry Atmospheric Nitrogen Deposition to Watersheds

EPA Science Inventory

Assessing the effects of atmospheric nitrogen (N) deposition on surface water quality requires accurate accounts of total N deposition (wet, dry, and cloud vapor); however, dry deposition is difficult to measure and is often spatially variable. Affordable passive sampling methods...

Development of Spatiotemporal Bias-Correction Techniques for Downscaling GCM Predictions

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

An approach for mapping large-area impervious surfaces: Synergistic use of Landsat-7 ETM+ and high spatial resolution imagery

USGS Publications Warehouse

Yang, Limin; Huang, Chengquan; Homer, Collin G.; Wylie, Bruce K.; Coan, Michael

2003-01-01

A wide range of urban ecosystem studies, including urban hydrology, urban climate, land use planning, and resource management, require current and accurate geospatial data of urban impervious surfaces. We developed an approach to quantify urban impervious surfaces as a continuous variable by using multisensor and multisource datasets. Subpixel percent impervious surfaces at 30-m resolution were mapped using a regression tree model. The utility, practicality, and affordability of the proposed method for large-area imperviousness mapping were tested over three spatial scales (Sioux Falls, South Dakota, Richmond, Virginia, and the Chesapeake Bay areas of the United States). Average error of predicted versus actual percent impervious surface ranged from 8.8 to 11.4%, with correlation coefficients from 0.82 to 0.91. The approach is being implemented to map impervious surfaces for the entire United States as one of the major components of the circa 2000 national land cover database.

Evaluation of a 12-km Satellite-Era Reanalysis of Surface Mass Balance for the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Cullather, R. I.; Nowicki, S.; Zhao, B.; Max, S.

2016-12-01

The recent contribution to sea level change from the Greenland Ice Sheet is thought to be strongly driven by surface processes including melt and runoff. Global reanalyses are potential means of reconstructing the historical time series of ice sheet surface mass balance (SMB), but lack spatial resolution needed to resolve ablation areas along the periphery of the ice sheet. In this work, the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) is used to examine the spatial and temporal variability of surface melt over the Greenland Ice Sheet. MERRA-2 is produced for the period 1980 to the present at a grid spacing of ½° latitude by ⅝° longitude, and includes snow hydrology processes including compaction, meltwater percolation and refreezing, runoff, and a prognostic surface albedo. The configuration of the MERRA-2 system allows for the background model - the Goddard Earth Observing System model, version 5 (GEOS-5) - to be carried in phase space through analyzed states via the computation of analysis increments, a capability referred to as "replay". Here, a MERRA-2 replay integration is conducted in which atmospheric forcing fields are interpolated and adjusted to sub- atmospheric grid-scale resolution. These adjustments include lapse-rate effects on temperature, humidity, precipitation, and other atmospheric variables that are known to have a strong elevation dependency over ice sheets. The surface coupling is performed such that mass and energy are conserved. The atmospheric forcing influences the surface representation, which operates on land surface tiles with an approximate 12-km spacing. This produces a high-resolution, downscaled SMB which is interactively coupled to the reanalysis model. We compare the downscaled SMB product with other reanalyses, regional climate model values, and a second MERRA-2 replay in which the background model has been replaced with a 12-km, non-hydrostatic version of GEOS-5. The assessment focuses on regional changes in SMB and SMB components, the identification of changes and temporal variability in the SMB equilibrium line, and the relation between SMB and other climate variables related to general circulation.

Spatial and Temporal Variability of Surface Energy Fluxes During Autumn Ice Advance: Observations and Model Validation

NASA Astrophysics Data System (ADS)

Persson, O. P. G.; Blomquist, B.; Grachev, A. A.; Guest, P. S.; Stammerjohn, S. E.; Solomon, A.; Cox, C. J.; Capotondi, A.; Fairall, C. W.; Intrieri, J. M.

2016-12-01

From Oct 4 to Nov 5, 2015, the Office of Naval Research - sponsored Sea State cruise in the Beaufort Sea with the new National Science Foundation R/V Sikuliaq obtained extensive in-situ and remote sensing observations of the lower troposphere, the advancing sea ice, wave state, and upper ocean conditions. In addition, a coupled atmosphere, sea ice, upper-ocean model, based on the RASM model, was run at NOAA/PSD in a hindcast mode for this same time period, providing a 10-day simulation of the atmosphere/ice/ocean evolution. Surface energy fluxes quantitatively represent the air-ice, air-ocean, and ice-ocean interaction processes, determining the cooling (warming) rate of the upper ocean and the growth (melting) rate of sea ice. These fluxes also impact the stratification of the lower troposphere and the upper ocean. In this presentation, both direct and indirect measurements of the energy fluxes during Sea State will be used to explore the spatial and temporal variability of these fluxes and the impacts of this variability on the upper ocean, ice, and lower atmosphere during the autumn ice advance. Analyses have suggested that these fluxes are impacted by atmospheric synoptic evolution, proximity to existing ice, ice-relative wind direction, ice thickness and snow depth. In turn, these fluxes impact upper-ocean heat loss and timing of ice formation, as well as stability in the lower troposphere and upper ocean, and hence heat transport to the free troposphere and ocean mixed-layer. Therefore, the atmospheric structure over the advancing first-year ice differs from that over the nearby open water. Finally, these observational analyses will be used to provide a preliminary validation of the spatial and temporal variability of the surface energy fluxes and the associated lower-tropospheric and upper-ocean structures in the simulations.

Decadal variability of the Tropical Atlantic Ocean Surface Temperature in shipboard measurements and in a Global Ocean-Atmosphere model

NASA Technical Reports Server (NTRS)

Mehta, Vikram M.; Delworth, Thomas

1995-01-01

Sea surface temperature (SST) variability was investigated in a 200-yr integration of a global model of the coupled oceanic and atmospheric general circulations developed at the Geophysical Fluid Dynamics Laboratory (GFDL). The second 100 yr of SST in the coupled model's tropical Atlantic region were analyzed with a variety of techniques. Analyses of SST time series, averaged over approximately the same subregions as the Global Ocean Surface Temperature Atlas (GOSTA) time series, showed that the GFDL SST anomalies also undergo pronounced quasi-oscillatory decadal and multidecadal variability but at somewhat shorter timescales than the GOSTA SST anomalies. Further analyses of the horizontal structures of the decadal timescale variability in the GFDL coupled model showed the existence of two types of variability in general agreement with results of the GOSTA SST time series analyses. One type, characterized by timescales between 8 and 11 yr, has high spatial coherence within each hemisphere but not between the two hemispheres of the tropical Atlantic. A second type, characterized by timescales between 12 and 20 yr, has high spatial coherence between the two hemispheres. The second type of variability is considerably weaker than the first. As in the GOSTA time series, the multidecadal variability in the GFDL SST time series has approximately opposite phases between the tropical North and South Atlantic Oceans. Empirical orthogonal function analyses of the tropical Atlantic SST anomalies revealed a north-south bipolar pattern as the dominant pattern of decadal variability. It is suggested that the bipolar pattern can be interpreted as decadal variability of the interhemispheric gradient of SST anomalies. The decadal and multidecadal timescale variability of the tropical Atlantic SST, both in the actual and in the GFDL model, stands out significantly above the background 'red noise' and is coherent within each of the time series, suggesting that specific sets of processes may be responsible for the choice of the decadal and multidecadal timescales. Finally, it must be emphasized that the GFDL coupled ocean-atmosphere model generates the decadal and multidecadal timescale variability without any externally applied force, solar or lunar, at those timescales.

Downscaling of Remotely Sensed Land Surface Temperature with multi-sensor based products

NASA Astrophysics Data System (ADS)

Jeong, J.; Baik, J.; Choi, M.

2016-12-01

Remotely sensed satellite data provides a bird's eye view, which allows us to understand spatiotemporal behavior of hydrologic variables at global scale. Especially, geostationary satellite continuously observing specific regions is useful to monitor the fluctuations of hydrologic variables as well as meteorological factors. However, there are still problems regarding spatial resolution whether the fine scale land cover can be represented with the spatial resolution of the satellite sensor, especially in the area of complex topography. To solve these problems, many researchers have been trying to establish the relationship among various hydrological factors and combine images from multi-sensor to downscale land surface products. One of geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS), has Meteorological Imager (MI) and Geostationary Ocean Color Imager (GOCI). MI performing the meteorological mission produce Rainfall Intensity (RI), Land Surface Temperature (LST), and many others every 15 minutes. Even though it has high temporal resolution, low spatial resolution of MI data is treated as major research problem in many studies. This study suggests a methodology to downscale 4 km LST datasets derived from MI in finer resolution (500m) by using GOCI datasets in Northeast Asia. Normalized Difference Vegetation Index (NDVI) recognized as variable which has significant relationship with LST are chosen to estimate LST in finer resolution. Each pixels of NDVI and LST are separated according to land cover provided from MODerate resolution Imaging Spectroradiometer (MODIS) to achieve more accurate relationship. Downscaled LST are compared with LST observed from Automated Synoptic Observing System (ASOS) for assessing its accuracy. The downscaled LST results of this study, coupled with advantage of geostationary satellite, can be applied to observe hydrologic process efficiently.

Temporal and spatial patterns in vegetation and atmospheric properties from AVIRIS

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

Roberts, D.A.; Green, R.O.; Adams, J.B.

1997-12-01

Little research has focused on the use of imaging spectrometry for change detection. In this paper, the authors apply Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data to the monitoring of seasonal changes in atmospheric water vapor, liquid water, and surface cover in the vicinity of the Jasper Ridge, CA, for three dates in 1992. Apparent surface reflectance was retrieved and water vapor and liquid water mapped by using a radiative-transfer-based inversion that accounts for spatially variable atmospheres. Spectral mixture analysis (SMA) was used to model reflectance data as mixtures of green vegetation (GV), nonphotosynthetic vegetation (NPV), soil, and shade. Temporal andmore » spatial patterns in endmember fractions and liquid water were compared to the normalized difference vegetation index (NDVI). The reflectance retrieval algorithm was tested by using a temporally invariant target.« less

Study of Spatial Variability of Air Temperature by Means of Remote Sensing Data and Weather Stations in Urban Areas: A Case Study for Campinas - São Paulo, Brazil.

NASA Astrophysics Data System (ADS)

Bezerra, L. M.; Avila, A. M. H. D.; Pereira, V. R.; Gonçalves, R. R. D. V.; Coltri, P. P.

2016-12-01

The surface meteorological and satellite Landsat8 data time series the city of Campinas, southeastern Brazil, has shown the rising temperatures in recent decades. According to scientific studies, part of this increase may be related to the urban sprawl of the city that currently has degree urbanization 98.28% and 1,164,098 inhabitants. Thus, the thermal images can represent reliable information of the surface temperature and this varies according to the land use and land cover. Therefore, were used 17 images of TIRS sensor (Thermal Infrared Sensor), band 10 and spatial resolution of 100 meters aboard satellite Landsat8 between 2013 and 2015 and temperature data from three meteorological stations of the city in different locations. After, was used the Pearson correlation between the measured weather data under 1.5 meters above ground level and surface temperature data estimated by satellite with a real difference 1 hour to less between stations and the satellite. The results indicated the 49% correlation in University of Campinas / Cepagri station, 86% in the Agronomic Institute of Campinas station and 90% in the Viracopos International Airport. This fact can be explained by the different degrees of urbanization where the weather stations are located and the heterogeneous characteristics of the local surface, as its roughness, impermeability, vegetation cover and concentration of buildings. Although these factors contribute to that there is a distortion of the surface temperature values detected by the satellite, the satellite was Landsat8 efficient to represent the spatial variability of temperature. In future studies, new techniques to obtain more accurate data through remote sensing will be studied.

Patterns and drivers for wetland connections in the Prairie Pothole Region, United States

USGS Publications Warehouse

Vanderhoof, Melanie; Christensen, Jay R.; Alexander, Laurie C.

2017-01-01

Ecosystem function in rivers, lakes and coastal waters depends on the functioning of upstream aquatic ecosystems, necessitating an improved understanding of watershed-scale interactions including variable surface-water flows between wetlands and streams. As surface water in the Prairie Pothole Region expands in wet years, surface-water connections occur between many depressional wetlands and streams. Minimal research has explored the spatial patterns and drivers for the abundance of these connections, despite their potential to inform resource management and regulatory programs including the U.S. Clean Water Act. In this study, wetlands were identified that did not intersect the stream network, but were shown with Landsat images (1990–2011) to become merged with the stream network as surface water expanded. Wetlands were found to spill into or consolidate with other wetlands within both small (2–10 wetlands) and large (>100 wetlands) wetland clusters, eventually intersecting a stream channel, most often via a riparian wetland. These surface-water connections occurred over a wide range of wetland distances from streams (averaging 90–1400 m in different ecoregions). Differences in the spatial abundance of wetlands that show a variable surface-water connection to a stream were best explained by smaller wetland-to-wetland distances, greater wetland abundance, and maximum surface-water extent. This analysis demonstrated that wetland arrangement and surface water expansion are important mechanisms for depressional wetlands to connect to streams and provides a first step to understanding the frequency and abundance of these surface-water connections across the Prairie Pothole Region.

Closing the Seasonal Ocean Surface Temperature Balance in the Eastern Tropical Oceans from Remote Sensing and Model Reanalyses

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Clayson, Carol A.

2012-01-01

The Eastern tropical ocean basins are regions of significant atmosphere-ocean interaction and are important to variability across subseasonal to decadal time scales. The numerous physical processes at play in these areas strain the abilities of coupled general circulation models to accurately reproduce observed upper ocean variability. Furthermore, limitations in the observing system of important terms in the surface temperature balance (e.g., turbulent and radiative heat fluxes, advection) introduce uncertainty into the analyses of processes controlling sea surface temperature variability. This study presents recent efforts to close the surface temperature balance through estimation of the terms in the mixed layer temperature budget using state-of-the-art remotely sensed and model-reanalysis derived products. A set of twelve net heat flux estimates constructed using combinations of radiative and turbulent heat flux products - including GEWEX-SRB, ISCCP-SRF, OAFlux, SeaFlux, among several others - are used with estimates of oceanic advection, entrainment, and mixed layer depth variability to investigate the seasonal variability of ocean surface temperatures. Particular emphasis is placed on how well the upper ocean temperature balance is, or is not, closed on these scales using the current generation of observational and model reanalysis products. That is, the magnitudes and spatial variability of residual imbalances are addressed. These residuals are placed into context within the current uncertainties of the surface net heat fluxes and the role of the mixed layer depth variability in scaling the impact of those uncertainties, particularly in the shallow mixed layers of the Eastern tropical ocean basins.

Estimating Small-area Populations by Age and Sex Using Spatial Interpolation and Statistical Inference Methods

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

Qai, Qiang; Rushton, Gerald; Bhaduri, Budhendra L

The objective of this research is to compute population estimates by age and sex for small areas whose boundaries are different from those for which the population counts were made. In our approach, population surfaces and age-sex proportion surfaces are separately estimated. Age-sex population estimates for small areas and their confidence intervals are then computed using a binomial model with the two surfaces as inputs. The approach was implemented for Iowa using a 90 m resolution population grid (LandScan USA) and U.S. Census 2000 population. Three spatial interpolation methods, the areal weighting (AW) method, the ordinary kriging (OK) method, andmore » a modification of the pycnophylactic method, were used on Census Tract populations to estimate the age-sex proportion surfaces. To verify the model, age-sex population estimates were computed for paired Block Groups that straddled Census Tracts and therefore were spatially misaligned with them. The pycnophylactic method and the OK method were more accurate than the AW method. The approach is general and can be used to estimate subgroup-count types of variables from information in existing administrative areas for custom-defined areas used as the spatial basis of support in other applications.« less

Systematic spatial bias in DNA microarray hybridization is caused by probe spot position-dependent variability in lateral diffusion.

PubMed

Steger, Doris; Berry, David; Haider, Susanne; Horn, Matthias; Wagner, Michael; Stocker, Roman; Loy, Alexander

2011-01-01

The hybridization of nucleic acid targets with surface-immobilized probes is a widely used assay for the parallel detection of multiple targets in medical and biological research. Despite its widespread application, DNA microarray technology still suffers from several biases and lack of reproducibility, stemming in part from an incomplete understanding of the processes governing surface hybridization. In particular, non-random spatial variations within individual microarray hybridizations are often observed, but the mechanisms underpinning this positional bias remain incompletely explained. This study identifies and rationalizes a systematic spatial bias in the intensity of surface hybridization, characterized by markedly increased signal intensity of spots located at the boundaries of the spotted areas of the microarray slide. Combining observations from a simplified single-probe block array format with predictions from a mathematical model, the mechanism responsible for this bias is found to be a position-dependent variation in lateral diffusion of target molecules. Numerical simulations reveal a strong influence of microarray well geometry on the spatial bias. Reciprocal adjustment of the size of the microarray hybridization chamber to the area of surface-bound probes is a simple and effective measure to minimize or eliminate the diffusion-based bias, resulting in increased uniformity and accuracy of quantitative DNA microarray hybridization.

Systematic Spatial Bias in DNA Microarray Hybridization Is Caused by Probe Spot Position-Dependent Variability in Lateral Diffusion

PubMed Central

Haider, Susanne; Horn, Matthias; Wagner, Michael; Stocker, Roman; Loy, Alexander

2011-01-01

Background The hybridization of nucleic acid targets with surface-immobilized probes is a widely used assay for the parallel detection of multiple targets in medical and biological research. Despite its widespread application, DNA microarray technology still suffers from several biases and lack of reproducibility, stemming in part from an incomplete understanding of the processes governing surface hybridization. In particular, non-random spatial variations within individual microarray hybridizations are often observed, but the mechanisms underpinning this positional bias remain incompletely explained. Methodology/Principal Findings This study identifies and rationalizes a systematic spatial bias in the intensity of surface hybridization, characterized by markedly increased signal intensity of spots located at the boundaries of the spotted areas of the microarray slide. Combining observations from a simplified single-probe block array format with predictions from a mathematical model, the mechanism responsible for this bias is found to be a position-dependent variation in lateral diffusion of target molecules. Numerical simulations reveal a strong influence of microarray well geometry on the spatial bias. Conclusions Reciprocal adjustment of the size of the microarray hybridization chamber to the area of surface-bound probes is a simple and effective measure to minimize or eliminate the diffusion-based bias, resulting in increased uniformity and accuracy of quantitative DNA microarray hybridization. PMID:21858215

High Resolution Insights into Snow Distribution Provided by Drone Photogrammetry

NASA Astrophysics Data System (ADS)

Redpath, T.; Sirguey, P. J.; Cullen, N. J.; Fitzsimons, S.

2017-12-01

Dynamic in time and space, New Zealand's seasonal snow is largely confined to remote alpine areas, complicating ongoing in situ measurement and characterisation. Improved understanding and modeling of the seasonal snowpack requires fine scale resolution of snow distribution and spatial variability. The potential of remotely piloted aircraft system (RPAS) photogrammetry to resolve spatial and temporal variability of snow depth and water equivalent in a New Zealand alpine catchment is assessed in the Pisa Range, Central Otago. This approach yielded orthophotomosaics and digital surface models (DSM) at 0.05 and 0.15 m spatial resolution, respectively. An autumn reference DSM allowed mapping of winter (02/08/2016) and spring (10/09/2016) snow depth at 0.15 m spatial resolution, via DSM differencing. The consistency and accuracy of the RPAS-derived surface was assessed by comparison of snow-free regions of the spring and autumn DSMs, while accuracy of RPAS retrieved snow depth was assessed with 86 in situ snow probe measurements. Results show a mean vertical residual of 0.024 m between DSMs acquired in autumn and spring. This residual approximated a Laplace distribution, reflecting the influence of large outliers on the small overall bias. Propagation of errors associated with successive DSMs saw snow depth mapped with an accuracy of ± 0.09 m (95% c.l.). Comparing RPAS and in situ snow depth measurements revealed the influence of geo-location uncertainty and interactions between vegetation and the snowpack on snow depth uncertainty and bias. Semi-variogram analysis revealed that the RPAS outperformed systematic in situ measurements in resolving fine scale spatial variability. Despite limitations accompanying RPAS photogrammetry, this study demonstrates a repeatable means of accurately mapping snow depth for an entire, yet relatively small, hydrological basin ( 0.5 km2), at high resolution. Resolving snowpack features associated with re-distribution and preferential accumulation and ablation, snow depth maps provide geostatistically robust insights into seasonal snow processes, with unprecedented detail. Such data may enhance understanding of physical processes controlling spatial and temporal distribution of seasonal snow, and their relative importance at varying spatial and temporal scales.

Soil moisture observations using L-, C-, and X-band microwave radiometers

NASA Astrophysics Data System (ADS)

Bolten, John Dennis

The purpose of this thesis is to further the current understanding of soil moisture remote sensing under varying conditions using L-, C-, and X-band. Aircraft and satellite instruments are used to investigate the effects of frequency and spatial resolution on soil moisture sensitivity. The specific objectives of the research are to examine multi-scale observed and modeled microwave radiobrightness, evaluate new EOS Aqua Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperature and soil moisture retrievals, and examine future satellite-based technologies for soil moisture sensing. The cycling of Earth's water, energy and carbon is vital to understanding global climate. Over land, these processes are largely dependent on the amount of moisture within the top few centimeters of the soil. However, there are currently no methods available that can accurately characterize Earth's soil moisture layer at the spatial scales or temporal resolutions appropriate for climate modeling. The current work uses ground truth, satellite and aircraft remote sensing data from three large-scale field experiments having different land surface, topographic and climate conditions. A physically-based radiative transfer model is used to simulate the observed aircraft and satellite measurements using spatially and temporally co-located surface parameters. A robust analysis of surface heterogeneity and scaling is possible due to the combination of multiple datasets from a range of microwave frequencies and field conditions. Accurate characterization of spatial and temporal variability of soil moisture during the three field experiments is achieved through sensor calibration and algorithm validation. Comparisons of satellite observations and resampled aircraft observations are made using soil moisture from a Numerical Weather Prediction (NWP) model in order to further demonstrate a soil moisture correlation where point data was unavailable. The influence of vegetation, spatial scaling, and surface heterogeneity on multi-scale soil moisture prediction is presented. This work demonstrates that derived soil moisture using remote sensing provides a better coverage of soil moisture spatial variability than traditional in-situ sensors. Effects of spatial scale were shown to be less significant than frequency on soil moisture sensitivity. Retrievals of soil moisture using the current methods proved inadequate under some conditions; however, this study demonstrates the need for concurrent spaceborne frequencies including L-, C, and X-band.

Variability of AVHRR-Derived Clear-Sky Surface Temperature over the Greenland Ice Sheet.

NASA Astrophysics Data System (ADS)

Stroeve, Julienne; Steffen, Konrad

1998-01-01

The Advanced Very High Resolution Radiometer is used to derive surface temperatures for one satellite pass under clear skies over the Greenland ice sheet from 1989 through 1993. The results of these temperatures are presented as monthly means, and their spatial and temporal variability are discussed. Accuracy of the dry snow surface temperatures is estimated to be better than 1 K during summer. This error is expected to increase during polar night due to problems in cloud identification. Results indicate the surface temperature of the Greenland ice sheet is strongly dominated by topography, with minimum surface temperatures associated with the high elevation regions. In the summer, maximum surface temperatures occur during July along the western coast and southern tip of the ice sheet. Minimum temperatures are found at the summit during summer and move farther north during polar night. Large interannual variability in surface temperatures occurs during winter associated with katabatic storm events. Summer temperatures show little variation, although 1992 stands out as being colder than the other years. The reason for the lower temperatures during 1992 is believed to be a result of the 1991 eruption of Mount Pinatubo.

A next generation altimeter for mapping the sea surface height variability: opportunities and challenges

NASA Astrophysics Data System (ADS)

Fu, Lee-Lueng; Morrow, Rosemary

2016-07-01

The global observations of the sea surface height (SSH) have revolutionized oceanography since the beginning of precision radar altimetry in the early 1990s. For the first time we have continuous records of SSH with spatial and temporal sampling for detecting the global mean sea level rise, the waxing and waning of El Niño, and the ocean circulation from gyres to ocean eddies. The limit of spatial resolution of the present constellation of radar altimeters in mapping SSH variability is approaching 100 km (in wavelength) with 3 or more simultaneous altimetric satellites in orbit. At scales shorter than 100 km, the circulation contains substantial amount of kinetic energy in currents, eddies and fronts that are responsible for the stirring and mixing of the ocean, especially from the vertical exchange of the upper ocean with the deep. A mission currently in development will use the technique of radar interferometry for making high-resolution measurement of the height of water over the ocean as well as on land. It is called Surface Water and Ocean Topography (SWOT), which is a joint mission of US NASA and French CNES, with contributions from Canada and UK. SWOT promises the detection of SSH at scales approaching 15 km, depending on the sea state. SWOT will make SSH measurement over a swath of 120 km with a nadir gap of 20 km in a 21-day repeat orbit. A conventional radar altimeter will provide measurement along the nadir. This is an exploratory mission with applications in oceanography and hydrology. The increased spatial resolution offers an opportunity to study ocean surface processes to address important questions about the ocean circulation. However, the limited temporal sampling poses challenges to map the evolution of the ocean variability that changes rapidly at the small scales. The measurement technique and the development of the mission will be presented with emphasis on its science program with outlook on the opportunities and challenges.

Spatiotemporal variability in surface energy balance across tundra, snow and ice in Greenland.

PubMed

Lund, Magnus; Stiegler, Christian; Abermann, Jakob; Citterio, Michele; Hansen, Birger U; van As, Dirk

2017-02-01

The surface energy balance (SEB) is essential for understanding the coupled cryosphere-atmosphere system in the Arctic. In this study, we investigate the spatiotemporal variability in SEB across tundra, snow and ice. During the snow-free period, the main energy sink for ice sites is surface melt. For tundra, energy is used for sensible and latent heat flux and soil heat flux leading to permafrost thaw. Longer snow-free period increases melting of the Greenland Ice Sheet and glaciers and may promote tundra permafrost thaw. During winter, clouds have a warming effect across surface types whereas during summer clouds have a cooling effect over tundra and a warming effect over ice, reflecting the spatial variation in albedo. The complex interactions between factors affecting SEB across surface types remain a challenge for understanding current and future conditions. Extended monitoring activities coupled with modelling efforts are essential for assessing the impact of warming in the Arctic.

Dynamic Bubble Surface Tension Measurements in Northwest Atlantic Seawater

NASA Astrophysics Data System (ADS)

Kieber, D. J.; Long, M. S.; Keene, W. C.; Kinsey, J. D.; Frossard, A. A.; Beaupre, S. R.; Duplessis, P.; Maben, J. R.; Lu, X.; Chang, R.; Zhu, Y.; Bisgrove, J.

2017-12-01

Numerous reports suggest that most organic matter (OM) associated with newly formed primary marine aerosol (PMA) originates from the sea-surface microlayer. However, surface-active OM rapidly adsorbs onto bubble surfaces in the water column and is ejected into the atmosphere when bubbles burst at the air-water interface. Here we present dynamic surface tension measurements of bubbles produced in near surface seawater from biologically productive and oligotrophic sites and in deep seawater collected from 2500 m in the northwest Atlantic. In all cases, the surface tension of bubble surfaces decreased within seconds after the bubbles were exposed to seawater. These observations demonstrate that bubble surfaces are rapidly saturated by surfactant material scavenged from seawater. Spatial and diel variability in bubble surface evolution indicate corresponding variability in surfactant concentrations and/or composition. Our results reveal that surface-active OM is found throughout the water column, and that at least some surfactants are not of recent biological origin. Our results also support the hypothesis that the surface microlayer is a minor to negligible source of OM associated with freshly produced PMA.

Cloudy Windows: What GCM Ensembles, Reanalyses and Observations Tell Us About Uncertainty in Greenland's Future Climate and Surface Melting

NASA Astrophysics Data System (ADS)

Reusch, D. B.

2016-12-01

Any analysis that wants to use a GCM-based scenario of future climate benefits from knowing how much uncertainty the GCM's inherent variability adds to the development of climate change predictions. This is extra relevant in the polar regions due to the potential of global impacts (e.g., sea level rise) from local (ice sheet) climate changes such as more frequent/intense surface melting. High-resolution, regional-scale models using GCMs for boundary/initial conditions in future scenarios inherit a measure of GCM-derived externally-driven uncertainty. We investigate these uncertainties for the Greenland ice sheet using the 30-member CESM1.0-CAM5-BGC Large Ensemble (CESMLE) for recent (1981-2000) and future (2081-2100, RCP 8.5) decades. Recent simulations are skill-tested against the ERA-Interim reanalysis and AWS observations with results informing future scenarios. We focus on key variables influencing surface melting through decadal climatologies, nonlinear analysis of variability with self-organizing maps (SOMs), regional-scale modeling (Polar WRF), and simple melt models. Relative to the ensemble average, spatially averaged climatological July temperature anomalies over a Greenland ice-sheet/ocean domain are mostly between +/- 0.2 °C. The spatial average hides larger local anomalies of up to +/- 2 °C. The ensemble average itself is 2 °C cooler than ERA-Interim. SOMs extend our diagnostics by providing a concise, objective summary of model variability as a set of generalized patterns. For CESMLE, the SOM patterns summarize the variability of multiple realizations of climate. Changes in pattern frequency by ensemble member show the influence of initial conditions. For example, basic statistical analysis of pattern frequency yields interquartile ranges of 2-4% for individual patterns across the ensemble. In climate terms, this tells us about climate state variability through the range of the ensemble, a potentially significant source of melt-prediction uncertainty. SOMs can also capture the different trajectories of climate due to intramodel variability over time. Polar WRF provides higher resolution regional modeling with improved, polar-centric model physics. Simple melt models allow us to characterize impacts of the upstream uncertainties on estimates of surface melting.

Validating modelled variable surface saturation in the riparian zone with thermal infrared images

NASA Astrophysics Data System (ADS)

Glaser, Barbara; Klaus, Julian; Frei, Sven; Frentress, Jay; Pfister, Laurent; Hopp, Luisa

2015-04-01

Variable contributing areas and hydrological connectivity have become prominent new concepts for hydrologic process understanding in recent years. The dynamic connectivity within the hillslope-riparian-stream (HRS) system is known to have a first order control on discharge generation and especially the riparian zone functions as runoff buffering or producing zone. However, despite their importance, the highly dynamic processes of contraction and extension of saturation within the riparian zone and its impact on runoff generation still remain not fully understood. In this study, we analysed the potential of a distributed, fully coupled and physically based model (HydroGeoSphere) to represent the spatial and temporal water flux dynamics of a forested headwater HRS system (6 ha) in western Luxembourg. The model was set up and parameterised under consideration of experimentally-derived knowledge of catchment structure and was run for a period of four years (October 2010 to August 2014). For model evaluation, we especially focused on the temporally varying spatial patterns of surface saturation. We used ground-based thermal infrared (TIR) imagery to map surface saturation with a high spatial and temporal resolution and collected 20 panoramic snapshots of the riparian zone (ca. 10 by 20 m) under different hydrologic conditions. These TIR panoramas were used in addition to several classical discharge and soil moisture time series for a spatially-distributed model validation. In a manual calibration process we optimised model parameters (e.g. porosity, saturated hydraulic conductivity, evaporation depth) to achieve a better agreement between observed and modelled discharges and soil moistures. The subsequent validation of surface saturation patterns by a visual comparison of processed TIR panoramas and corresponding model output panoramas revealed an overall good accordance for all but one region that was always too dry in the model. However, quantitative comparisons of modelled and observed saturated pixel percentages and of their modelled and measured relationships to concurrent discharges revealed remarkable similarities. During the calibration process we observed that surface saturation patterns were mostly affected by changing the soil properties of the topsoil in the riparian zone, but that the discharge behaviour did not change substantially at the same time. This effect of various spatial patterns occurring concomitant to a nearly unchanged integrated response demonstrates the importance of spatially distributed validation data. Our study clearly benefited from using different kinds of data - spatially integrated and distributed, temporally continuous and discrete - for the model evaluation procedure.

A half-decade of field research on the Greenland firn aquifers - major advances and looming questions.

NASA Astrophysics Data System (ADS)

Koenig, L.; Forster, R. R.; Miller, O. L.; Solomon, D. K.; Miège, C.; Schmerr, N. C.; Montgomery, L. N.; Legchenko, A.

2017-12-01

In 2011, researchers first drilled into an unknown firn aquifer in Southeast, Greenland. Over the past half-decade our team has conducted field work instrumenting, modeling and remote sensing the aquifer and surrounding snow/firn/ice to get a more complete picture of the system including formation conditions, controlling mechanisms, spatial and temporal change, and connections with the larger ice sheet system. This work summarizes recently published work on the firn aquifer providing our best estimates on the spatial extents, depths and water volumes for the purpose of estimating available water that could reach the en- or subglacial hydrologic network. To do this we reconcile and explain the differences in water volume estimates from three methods, ice core measurements, magnetic resonance and dilution tests. We present measurements of the hydrologic conductivities within a Greenland firn aquifer from two methods, at multiple locations showing that water can flow more freely in ice sheet aquifers than mountain glaciers and attribute this difference to the longer duration of water retained in ice sheet aquifers. While connections of the aquifer water to the glacier bed have been hypothesized and are supported by surface velocity measurements, we still lack direct observations. We show the surface velocity for most aquifer regions ranges from a few meters to 300 m a year with substantial spatial and temporal variability. Given possible aquifer water input scenarios, derived from our field measurements, to the glacier bed, we compare and contrast the seasonal surface velocities and variability of surface velocity for different outlet glaciers that are both connected and not connected to firn aquifers.

West-WRF Sensitivity to Sea Surface Temperature Boundary Condition in California Precipitation Forecasts of AR Related Events

NASA Astrophysics Data System (ADS)

Zhang, X.; Cornuelle, B. D.; Martin, A.; Weihs, R. R.; Ralph, M.

2017-12-01

We evaluated the merit in coastal precipitation forecasts by inclusion of high resolution sea surface temperature (SST) from blended satellite and in situ observations as a boundary condition (BC) to the Weather Research and Forecast (WRF) mesoscale model through simple perturbation tests. Our sensitivity analyses shows that the limited improvement of watershed scale precipitation forecast is credible. When only SST BC is changed, there is an uncertainty introduced because of artificial model state equilibrium and the nonlinear nature of the WRF model system. With the change of SST on the order of a fraction of a degree centigrade, we found that the part of random perturbation forecast response is saturated after 48 hours when it reaches to the order magnitude of the linear response. It is important to update the SST at a shorter time period, so that the independent excited nonlinear modes can cancel each other. The uncertainty in our SST configuration is quantitatively equivalent to adding to a spatially uncorrelated Guasian noise of zero mean and 0.05 degree of standard deviation to the SST. At this random noise perturbation magnitude, the ensemble average behaves well within a convergent range. It is also found that the sensitivity of forecast changes in response to SST changes. This is measured by the ratio of the spatial variability of mean of the ensemble perturbations over the spatial variability of the corresponding forecast. The ratio is about 10% for surface latent heat flux, 5 % for IWV, and less than 1% for surface pressure.

Modes of hurricane activity variability in the eastern Pacific: Implications for the 2016 season

NASA Astrophysics Data System (ADS)

Boucharel, Julien; Jin, Fei-Fei; England, Matthew H.; Lin, I. I.

2016-11-01

A gridded product of accumulated cyclone energy (ACE) in the eastern Pacific is constructed to assess the dominant mode of tropical cyclone (TC) activity variability. Results of an empirical orthogonal function decomposition and regression analysis of environmental variables indicate that the two dominant modes of ACE variability (40% of the total variance) are related to different flavors of the El Niño-Southern Oscillation (ENSO). The first mode, more active during the later part of the hurricane season (September-November), is linked to the eastern Pacific El Niño through the delayed oceanic control associated with the recharge-discharge mechanism. The second mode, dominant in the early months of the hurricane season, is related to the central Pacific El Niño mode and the associated changes in atmospheric variability. A multilinear regression forecast model of the dominant principal components of ACE variability is then constructed. The wintertime subsurface state of the eastern equatorial Pacific (characterizing ENSO heat discharge), the east-west tilt of the thermocline (describing ENSO phase transition), the anomalous ocean surface conditions in the TC region in spring (portraying atmospheric changes induced by persistence of local surface anomalies), and the intraseasonal atmospheric variability in the western Pacific are found to be good predictors of TC activity. Results complement NOAA's official forecast by providing additional spatial and temporal information. They indicate a more active 2016 season ( 2 times the ACE mean) with a spatial expansion into the central Pacific associated with the heat discharge from the 2015/2016 El Niño.

Modelisation numerique de l'hydrologie pour l'aide a la gestion des bassins versants, par l'utilisation conjointe des systemes d'information geographique et de la methode des elements finis un nouvel outil pour le developpement durable SAGESS

NASA Astrophysics Data System (ADS)

Bel Hadj Kacem, Mohamed Salah

All hydrological processes are affected by the spatial variability of the physical parameters of the watershed, and also by human intervention on the landscape. The water outflow from a watershed strictly depends on the spatial and temporal variabilities of the physical parameters of the watershed. It is now apparent that the integration of mathematical models into GIS's can benefit both GIS and three-dimension environmental models: a true modeling capability can help the modeling community bridge the gap between planners, scientists, decision-makers and end-users. The main goal of this research is to design a practical tool to simulate run-off water surface using Geographic design a practical tool to simulate run-off water surface using Geographic Information Systems and the simulation of the hydrological behavior by the Finite Element Method.

Improving spatial prediction of Schistosoma haematobium prevalence in southern Ghana through new remote sensors and local water access profiles.

PubMed

Kulinkina, Alexandra V; Walz, Yvonne; Koch, Magaly; Biritwum, Nana-Kwadwo; Utzinger, Jürg; Naumova, Elena N

2018-06-04

Schistosomiasis is a water-related neglected tropical disease. In many endemic low- and middle-income countries, insufficient surveillance and reporting lead to poor characterization of the demographic and geographic distribution of schistosomiasis cases. Hence, modeling is relied upon to predict areas of high transmission and to inform control strategies. We hypothesized that utilizing remotely sensed (RS) environmental data in combination with water, sanitation, and hygiene (WASH) variables could improve on the current predictive modeling approaches. Schistosoma haematobium prevalence data, collected from 73 rural Ghanaian schools, were used in a random forest model to investigate the predictive capacity of 15 environmental variables derived from RS data (Landsat 8, Sentinel-2, and Global Digital Elevation Model) with fine spatial resolution (10-30 m). Five methods of variable extraction were tested to determine the spatial linkage between school-based prevalence and the environmental conditions of potential transmission sites, including applying the models to known human water contact locations. Lastly, measures of local water access and groundwater quality were incorporated into RS-based models to assess the relative importance of environmental and WASH variables. Predictive models based on environmental characterization of specific locations where people contact surface water bodies offered some improvement as compared to the traditional approach based on environmental characterization of locations where prevalence is measured. A water index (MNDWI) and topographic variables (elevation and slope) were important environmental risk factors, while overall, groundwater iron concentration predominated in the combined model that included WASH variables. The study helps to understand localized drivers of schistosomiasis transmission. Specifically, unsatisfactory water quality in boreholes perpetuates reliance of surface water bodies, indirectly increasing schistosomiasis risk and resulting in rapid reinfection (up to 40% prevalence six months following preventive chemotherapy). Considering WASH-related risk factors in schistosomiasis prediction can help shift the focus of control strategies from treating symptoms to reducing exposure.

Atmospheric circulation patterns and spatial climatic variations in Beringia

NASA Astrophysics Data System (ADS)

Mock, Cary J.; Bartlein, Patrick J.; Anderson, Patricia M.

1998-08-01

Analyses of more than 40 years of climatic data reveal intriguing spatial variations in climatic patterns for Beringia (North-eastern Siberia and Alaska), aiding the understanding of the hierarchy of climatic controls that operate at different spatial scales within the Arctic. A synoptic climatology, using a subjective classification methodology on January and July sea level pressure, and July 500 hPa height anomaly patterns, identified 13 major atmospheric circulation patterns (26 pairs consisting of 13 synoptic/temperature and 13 synoptic/precipitation comparisons) that occur over Beringia. Composite anomaly maps of circulation, temperature, and precipitation described the spatial variability of surface climatic responses to circulation. Results indicate that nine synoptic pairs yield homogeneous surface climatic anomaly patterns throughout most of Beringia. However, many of the surface climatic responses illustrate heterogeneous anomaly patterns as a result of variations in circulation controls, such as troughing over East Asia and the Pacific subtropical high superimposed over topography, with small shifts in atmospheric circulation dramatically altering spatial variations of anomaly patterns. Distinctive contrasts in climatic responses, as suggested from ten synoptic pairs, are clearly evident for Western Beringia versus Eastern Beringia. These results offer important implications for scholars interested in assessing late Quaternary climatic change in the region from interannual to millennial timescales.

Disentangling Global Warming, Multidecadal Variability, and El Niño in Pacific Temperatures

NASA Astrophysics Data System (ADS)

Wills, Robert C.; Schneider, Tapio; Wallace, John M.; Battisti, David S.; Hartmann, Dennis L.

2018-03-01

A key challenge in climate science is to separate observed temperature changes into components due to internal variability and responses to external forcing. Extended integrations of forced and unforced climate models are often used for this purpose. Here we demonstrate a novel method to separate modes of internal variability from global warming based on differences in time scale and spatial pattern, without relying on climate models. We identify uncorrelated components of Pacific sea surface temperature variability due to global warming, the Pacific Decadal Oscillation (PDO), and the El Niño-Southern Oscillation (ENSO). Our results give statistical representations of PDO and ENSO that are consistent with their being separate processes, operating on different time scales, but are otherwise consistent with canonical definitions. We isolate the multidecadal variability of the PDO and find that it is confined to midlatitudes; tropical sea surface temperatures and their teleconnections mix in higher-frequency variability. This implies that midlatitude PDO anomalies are more persistent than previously thought.

Interannual Variability in Global Dust Storm Initiation on Mars from a GCM with Orbit-Spin Coupling and Active Dust Lifting

NASA Astrophysics Data System (ADS)

Mischna, M.; Shirley, J. H.; Newman, C. E.

2016-12-01

To first order, the occurrence and interannual variability of global dust storms (GDS) on Mars is attributable to two factors: the annual cycle of solar insolation (which delineates a specific `dust storm season'), and the changing spatial distribution and availability of dust at the surface. Recent work has now found a remarkable correspondence between the occurrence of GDS on Mars and years in which the orbital angular momentum of Mars is increasing during the dust storm season. A previously undefined acceleration term `couples' this orbital motion to the rotational motion of the planet and atmosphere, and small but persistent atmospheric accelerations (so-called `coupling term accelerations,' or CTA) change the atmospheric circulation in such a way as to seemingly be favorable to storm development. This becomes a third factor, then, that may regulate the occurrence and variability of GDS. Our prior work with the MarsWRF general circulation model (GCM) was performed either with no atmospheric dust, or with simplified, prescribed dust distributions, and illustrated the dual roles of both insolation and CTA on GDS variability. Recent advances in the MarsWRF GCM dust prescription can now tackle the remaining unaddressed factor: the role of dust availability in controlling the initiation of GDS. Simulations with both infinite and finite global sources of dust have been performed. For a prescribed dust lifting threshold, surface dust is removed from the surface, preferentially from locations with larger surface stress values, transported in the atmosphere and deposited at a later time. Compared to simulations without CTA, those with CTA show more realism in the variability of timing and magnitude of atmospheric dustiness during the dust storm season. For infinite surface dust, the primary dust lifting (peak wind stress) regions are spatially restricted, and year-to-year changes are largely due to variations in the CTA at these few locations. By contrast, in simulations with finite surface dust, the peak stress regions are rapidly exhausted, leading to a far greater distribution of primary dust lifting regions; hence, variations in the CTA over a wider area contribute to the interannual variability of GDS. Results from our suite of simulations will be shown, vis-à-vis the historical record of GDS on Mars.

Spatial variability of surface-sediment porewater pH and related water-column characteristics in deep waters of the northern South China Sea

NASA Astrophysics Data System (ADS)

Shao, Changgao; Sui, Yi; Tang, Danling; Legendre, Louis

2016-12-01

This study analyzes the pH of surface-sediment porewater (i.e. 2-3 cm below the water-sediment interface), and concentrations of CaCO3 and organic carbon (OC) in 1192 sediment cores from the northern South China Sea, in water depths ranging from 137 to 3702 m. This is the first study in the literature to analyze the large-scale spatial variability of deep-water surface-sediment pH over a large ocean basin. The data showed strong spatial variations in pH. The lowest pH values (<7.3) were observed south of Hainan Island, an area that is affected by summer upwelling and freshwater runoff from the Pearl and Red Rivers. Moderately low pH values (generally 7.3-7.5) occurred in two other areas: a submarine canyon, where sediments originated partly from the Pearl River and correspond to a paleo-delta front during the last glacial period; and southwest of Taiwan Island, where waters are affected by the northern branch of the Kuroshio intrusion current (KIC) and runoff from Taiwan rivers. The surface sediments with the highest pH (⩾7.5, and up to 8.3) were located in a fourth area, which corresponded to the western branch of the KIC where sediments have been intensively eroded by bottom currents. The pH of surface-sediment porewater was significantly linearly related to water depth, bottom-water temperature, and CaCO3 concentration (p < 0.05 for the whole sampling area). This study shows that the pH of surface-sediment porewater can be sensitive to characteristics of the overlying water column, and suggests that it will respond to global warming as changes in surface-ocean temperature and pH progressively reach deeper waters.

An application of remotely derived climatological fields for risk assessment of vector-borne diseases : a spatial study of filariasis prevalence in the Nile Delta, Egypt.

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

Crombie, M. K.; Gillies, R. R.; Arvidson, R. E.

1999-12-01

This paper applies a relatively straightforward remote sensing method that is commonly used to derive climatological variables. Measurements of surface reflectance and surface radiant temperature derived from Landsat Thematic Mapper data were used to create maps of fractional vegetation and surface soil moisture availability for the southern Nile delta in Egypt. These climatological variables were subsequently used to investigate the spatial distribution of the vector borne disease Bancroftian filariasis in the Nile delta where it is focally endemic and a growing problem. Averaged surface soil moisture values, computed for a 5-km border area around affected villages, were compared to filariasismore » prevalence rates. Prevalence rates were found to be negligible below a critical soil moisture value of 0.2, presumably because of a lack of appropriate breeding sites for the Culex Pipiens mosquito species. With appropriate modifications to account for local conditions and vector species, this approach should be useful as a means to map, predict, and control insect vector-borne diseases that critically depend on wet areas for propagation. This type of analysis may help governments and health agencies that are involved in filariasis control to better focus limited resources to identifiable high-risk areas.« less

The relationship between Arabian Sea upwelling and Indian Monsoon revisited in a high resolution ocean simulation

NASA Astrophysics Data System (ADS)

Yi, Xing; Hünicke, Birgit; Tim, Nele; Zorita, Eduardo

2018-01-01

Studies based on sediment records, sea-surface temperature and wind suggest that upwelling along the western coast of Arabian Sea is strongly affected by the Indian summer Monsoon. We examine this relationship directly in an eddy-resolving global ocean simulation STORM driven by atmospheric reanalysis over the last 61 years. With its very high spatial resolution (10 km), STORM allows us to identify characteristics of the upwelling system. We analyse the co-variability between upwelling and meteorological and oceanic variables from 1950 to 2010. The analysis reveals high interannual correlations between coastal upwelling and along-shore wind-stress (r = 0.73) as well as with sea-surface temperature (r = -0.83). However, the correlation between the upwelling and the Monsoon is small. We find an atmospheric circulation pattern different from the one that drives the Monsoon as the main modulator of the upwelling variability. In spite of this, the patterns of temperature anomalies that are either linked to Arabian Sea upwelling or to the Monsoon are spatially quite similar, although the physical mechanisms of these links are different. In addition, no long-term trend is detected in our modelled upwelling in the Arabian Sea.

Reconstruction from EOF analysis of SMOS salinity data in Mediterranean Sea

NASA Astrophysics Data System (ADS)

Parard, Gaelle; Alvera-Azcárate, Aida; Barth, Alexander; Olmedo, Estrella; Turiel, Antonio; Becker, Jean-Marie

2017-04-01

Sea Surface Salinity (SSS) data from the Soil Moisture and Ocean Salinity (SMOS) mission is reconstructed in the North Atlantic and the Mediterranean Sea using DINEOF (Data Interpolating Empirical Orthogonal Functions). We used the satellite data Level 2 from SMOS Barcelona Expert Centre between 2011 and 2015. DINEOF is a technique that reconstructs missing data and removes noise by retaining only an optimal set of EOFs. DINEOF analysis is used to detect and remove outliers from the SMOS SSS daily field. The gain obtained with DINEOF method and L2 SMOS data give a higher spatial and temporal resolution between 2011 and 2015, allow to study the SSS variability from daily to seasonal resolution. In order to improve the SMOS salinity data reconstruction we combine with other parameters measured from satellite such chlorophyll, sea surface temperature, precipitation and CDOM variability. After a validation of the SMOS satellite data reconstruction with in situ data (CTD, Argo float salinity measurement) in the North Atlantic and Mediterranean Sea, the main SSS processes and their variability are studied. The gain obtained with the higher spatial and temporal resolution with SMOS salinity data give assess to study the characteristics of oceanic structures in North Atlantic and Mediterranean Sea.

Design and development of a community carbon cycle benchmarking system for CMIP5 models

NASA Astrophysics Data System (ADS)

Mu, M.; Hoffman, F. M.; Lawrence, D. M.; Riley, W. J.; Keppel-Aleks, G.; Randerson, J. T.

2013-12-01

Benchmarking has been widely used to assess the ability of atmosphere, ocean, sea ice, and land surface models to capture the spatial and temporal variability of observations during the historical period. For the carbon cycle and terrestrial ecosystems, the design and development of an open-source community platform has been an important goal as part of the International Land Model Benchmarking (ILAMB) project. Here we designed and developed a software system that enables the user to specify the models, benchmarks, and scoring systems so that results can be tailored to specific model intercomparison projects. We used this system to evaluate the performance of CMIP5 Earth system models (ESMs). Our scoring system used information from four different aspects of climate, including the climatological mean spatial pattern of gridded surface variables, seasonal cycle dynamics, the amplitude of interannual variability, and long-term decadal trends. We used this system to evaluate burned area, global biomass stocks, net ecosystem exchange, gross primary production, and ecosystem respiration from CMIP5 historical simulations. Initial results indicated that the multi-model mean often performed better than many of the individual models for most of the observational constraints.

Growth studies of Mytilus californianus using satellite surface temperatures and chlorophyll data for coastal Oregon

NASA Astrophysics Data System (ADS)

Price, J.; Lakshmi, V.

2013-12-01

The advancement of remote sensing technology has led to better understanding of the spatial and temporal variation in many physical and biological parameters, such as, temperature, salinity, soil moisture, vegetation cover, and community composition. This research takes a novel approach in understanding the temporal and spatial variability of mussel body growth using remotely sensed surface temperatures and chlorophyll-a concentration. Within marine rocky intertidal ecosystems, temperature and food availability influence species abundance, physiological performance, and distribution of mussel species. Current methods to determine the temperature mussel species experience range from in-situ field observations, temperature loggers, temperature models, and using other temperature variables. However, since the temperature that mussel species experience is different from the air temperature due to physical and biological characteristics (size, color, gaping, etc.), it is difficult to accurately predict the thermal stresses they experience. Methods to determine food availability (chlorophyll-a concentration used as a proxy) for mussel species are mostly done at specific study sites using water sampling. This implies that analysis of temperature and food availability across large spatial scales and long temporal scales is not a trivial task given spatial heterogeneity. However, this is an essential step in determination of the impact of changing climate on vulnerable ecosystems such as the marine rocky intertidal system. The purpose of this study was to investigate the potential of using remotely sensed surface temperatures and chlorophyll-a concentration to better understand the temporal and spatial variability of the body growth of the ecologically and economically important rocky intertidal mussel species, Mytilus californianus. Remotely sensed sea surface temperature (SST), land surface temperature (LST), intertidal surface temperature (IST), chlorophyll-a concentration, and mussel body growth were collected for eight study sites along the coast of Oregon, USA for a 12 year period from 2000 through 2011. Differences in surface temperatures, chlorophyll-a concentration, and mussel body growth were seen across study sites. The northernmost study site, Cape Meares, had the highest average SST and the lowest average chlorophyll-a concentration. Interestingly, it also had high average mussel growth. Whereas, Cape Arago and Cape Blanco, the two southernmost study sites, had the lowest average SST and lowest average mussel growth, but had higher average chlorophyll-a concentrations. Furthermore, some study sites showed that mussel growth was related to temperature and at other study sites chlorophyll-a concentration was related to mussel growth. The strongest relationship between either temperature or chlorophyll-a concentration, was found at Boiler Bay, Oregon. Approximately 81% of the variations in mean size-specific mussel growth was explained by mean annual LST anomalies. This means that at Boiler Bay, cooler LST years resulted in less mussel growth and warmer years resulted in higher mussel growth. Results suggest that SST may influence mussel body growth more than chlorophyll-a concentration.

The influence of lithology on surface water sources | Science ...

EPA Pesticide Factsheets

Understanding the temporal and spatial variability of surface water sources within a basin is vital to our ability to manage the impacts of climate variability and land cover change. Water stable isotopes can be used as a tool to determine geographic and seasonal sources of water at the basin scale. Previous studies in the Coastal Range of Oregon reported that the variation in the isotopic signatures of surface water does not conform to the commonly observed “rainout effect”, which exhibits a trend of increasing isotopic depletion with rising elevation. The primary purpose of this research is to investigate the mechanisms governing seasonal and spatial variations in the isotopic signature of surface waters within the Marys River Basin, located in the leeward side of the Oregon Coastal Range. Surface water and precipitation samples were collected every 2-3 weeks for isotopic analysis of δ18O and δ2H for one year. Results indicate a significant difference in isotopic signature between watersheds underlain by basalt and sandstone. The degree of separation was the most distinct during the summer when low flows reflect deeper groundwater sources, whereas isotopic signatures during the rainy season (fall and winter) showed a greater degree of similarity between the two lithologies. This indicates that baseflow within streams drained by sandstone versus basalt is being supplied from two distinctly separate water sources. In addition, Marys River flow at the outle

VEMAP Phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA

USGS Publications Warehouse

Kittel, T.G.F.; Rosenbloom, N.A.; Royle, J. Andrew; Daly, Christopher; Gibson, W.P.; Fisher, H.H.; Thornton, P.; Yates, D.N.; Aulenbach, S.; Kaufman, C.; McKeown, R.; Bachelet, D.; Schimel, D.S.; Neilson, R.; Lenihan, J.; Drapek, R.; Ojima, D.S.; Parton, W.J.; Melillo, J.M.; Kicklighter, D.W.; Tian, H.; McGuire, A.D.; Sykes, M.T.; Smith, B.; Cowling, S.; Hickler, T.; Prentice, I.C.; Running, S.; Hibbard, K.A.; Post, W.M.; King, A.W.; Smith, T.; Rizzo, B.; Woodward, F.I.

2004-01-01

Analysis and simulation of biospheric responses to historical forcing require surface climate data that capture those aspects of climate that control ecological processes, including key spatial gradients and modes of temporal variability. We developed a multivariate, gridded historical climate dataset for the conterminous USA as a common input database for the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP), a biogeochemical and dynamic vegetation model intercomparison. The dataset covers the period 1895-1993 on a 0.5?? latitude/longitude grid. Climate is represented at both monthly and daily timesteps. Variables are: precipitation, mininimum and maximum temperature, total incident solar radiation, daylight-period irradiance, vapor pressure, and daylight-period relative humidity. The dataset was derived from US Historical Climate Network (HCN), cooperative network, and snowpack telemetry (SNOTEL) monthly precipitation and mean minimum and maximum temperature station data. We employed techniques that rely on geostatistical and physical relationships to create the temporally and spatially complete dataset. We developed a local kriging prediction model to infill discontinuous and limited-length station records based on spatial autocorrelation structure of climate anomalies. A spatial interpolation model (PRISM) that accounts for physiographic controls was used to grid the infilled monthly station data. We implemented a stochastic weather generator (modified WGEN) to disaggregate the gridded monthly series to dailies. Radiation and humidity variables were estimated from the dailies using a physically-based empirical surface climate model (MTCLIM3). Derived datasets include a 100 yr model spin-up climate and a historical Palmer Drought Severity Index (PDSI) dataset. The VEMAP dataset exhibits statistically significant trends in temperature, precipitation, solar radiation, vapor pressure, and PDSI for US National Assessment regions. The historical climate and companion datasets are available online at data archive centers. ?? Inter-Research 2004.

Using generalized additive mixed models to assess spatial, temporal, and hydrologic controls on bacteria and nitrate in a vulnerable agricultural aquifer.

PubMed

Mellor, Andrea F P; Cey, Edwin E

2015-11-01

The Abbotsford-Sumas aquifer (ASA) has a history of nitrate contamination from agricultural land use and manure application to soils, yet little is known about its microbial groundwater quality. The goal of this study was to investigate the spatiotemporal distribution of pathogen indicators (Escherichia coli [E. coli] and total coliform [TC]) and nitrate in groundwater, and their potential relation to hydrologic drivers. Sampling of 46 wells over an 11-month period confirmed elevated nitrate concentrations, with more than 50% of samples exceeding 10 mg-N/L. E. coli detections in groundwater were infrequent (4 of 385 total samples) and attributed mainly to surface water-groundwater connections along Fishtrap Creek, which tested positive for E. coli in every sampling event. TC was detected frequently in groundwater (70% of samples) across the ASA. Generalized additive mixed models (GAMMs) yielded valuable insights into relationships between TC or nitrate and a range of spatial, temporal, and hydrologic explanatory variables. Increased TC values over the wetter fall and winter period were most strongly related to groundwater temperatures and levels, while precipitation and well location were weaker (but still significant) predictors. In contrast, the moderate temporal variability in nitrate concentrations was not significantly related to hydrologic forcings. TC was relatively widespread across the ASA and spatial patterns could not be attributed solely to surface water connectivity. Varying nitrate concentrations across the ASA were significantly related to both well location and depth, likely due to spatially variable nitrogen loading and localized geochemical attenuation (i.e., denitrification). Vulnerability of the ASA to bacteria was clearly linked to hydrologic conditions, and was distinct from nitrate, such that a groundwater management strategy specifically for bacterial contaminants is warranted. Copyright © 2015 Elsevier B.V. All rights reserved.

Characterizing Mediterranean Land Surfaces as Component of the Regional Climate System by Remote Sensing

NASA Technical Reports Server (NTRS)

Bolle, H.-J.; Koslowsky, D.; Menenti, M.; Nerry, F.; Otterman, Joseph; Starr, D.

1998-01-01

Extensive areas in the Mediterranean region are subject to land degradation and desertification. The high variability of the coupling between the surface and the atmosphere affects the regional climate. Relevant surface characteristics, such as spectral reflectance, surface emissivity in the thermal-infrared region, and vegetation indices, serve as "primary" level indicators for the state of the surface. Their spatial, seasonal and interannual variability can be monitored from satellites. Using relationships between these primary data and combining them with prior information about the land surfaces (such as topography, dominant soil type, land use, collateral ground measurements and models), a second layer of information is built up which specifies the land surfaces as a component of the regional climate system. To this category of parameters which are directly involved in the exchange of energy, momentum and mass between the surface and the atmosphere, belong broadband albedo, thermodynamic surface temperature, vegetation types, vegetation cover density, soil top moisture, and soil heat flux. Information about these parameters finally leads to the computation of sensible and latent heat fluxes. The methodology was tested with pilot data sets. Full resolution, properly calibrated and normalized NOAA-AVHRR multi-annual primary data sets are presently compiled for the whole Mediterranean area, to study interannual variability and longer term trends.

3-D Acoustic Scattering from 2-D Rough Surfaces Using A Parabolic Equation Model

DTIC Science & Technology

2013-12-01

Frequency Acoustic Propagation in Shallow Water.” Journal of Oceanic Engineering, September 2011: 1–10. Liu, Jin Yuan, Chen Fen Huang, and Ping Chang...loss values at a constant depth. .............................52  xi LIST OF ACRONYMS AND ABBREVIATIONS FD Finite Difference MMPE Monterey...2013). First, at each range step ( xi ), the 3-D field is transformed from cross-range spatial variable (y) to cross-range wavenumber variable (ky

Spatial analysis of factors influencing long-term stress in the grizzly bear (Ursus arctos) population of Alberta, Canada.

PubMed

Bourbonnais, Mathieu L; Nelson, Trisalyn A; Cattet, Marc R L; Darimont, Chris T; Stenhouse, Gordon B

2013-01-01

Non-invasive measures for assessing long-term stress in free ranging mammals are an increasingly important approach for understanding physiological responses to landscape conditions. Using a spatially and temporally expansive dataset of hair cortisol concentrations (HCC) generated from a threatened grizzly bear (Ursus arctos) population in Alberta, Canada, we quantified how variables representing habitat conditions and anthropogenic disturbance impact long-term stress in grizzly bears. We characterized spatial variability in male and female HCC point data using kernel density estimation and quantified variable influence on spatial patterns of male and female HCC stress surfaces using random forests. Separate models were developed for regions inside and outside of parks and protected areas to account for substantial differences in anthropogenic activity and disturbance within the study area. Variance explained in the random forest models ranged from 55.34% to 74.96% for males and 58.15% to 68.46% for females. Predicted HCC levels were higher for females compared to males. Generally, high spatially continuous female HCC levels were associated with parks and protected areas while low-to-moderate levels were associated with increased anthropogenic disturbance. In contrast, male HCC levels were low in parks and protected areas and low-to-moderate in areas with increased anthropogenic disturbance. Spatial variability in gender-specific HCC levels reveal that the type and intensity of external stressors are not uniform across the landscape and that male and female grizzly bears may be exposed to, or perceive, potential stressors differently. We suggest observed spatial patterns of long-term stress may be the result of the availability and distribution of foods related to disturbance features, potential sexual segregation in available habitat selection, and may not be influenced by sources of mortality which represent acute traumas. In this wildlife system and others, conservation and management efforts can benefit by understanding spatial- and gender-based stress responses to landscape conditions.

Spatial Analysis of Factors Influencing Long-Term Stress in the Grizzly Bear (Ursus arctos) Population of Alberta, Canada

PubMed Central

Bourbonnais, Mathieu L.; Nelson, Trisalyn A.; Cattet, Marc R. L.; Darimont, Chris T.; Stenhouse, Gordon B.

2013-01-01

Non-invasive measures for assessing long-term stress in free ranging mammals are an increasingly important approach for understanding physiological responses to landscape conditions. Using a spatially and temporally expansive dataset of hair cortisol concentrations (HCC) generated from a threatened grizzly bear (Ursus arctos) population in Alberta, Canada, we quantified how variables representing habitat conditions and anthropogenic disturbance impact long-term stress in grizzly bears. We characterized spatial variability in male and female HCC point data using kernel density estimation and quantified variable influence on spatial patterns of male and female HCC stress surfaces using random forests. Separate models were developed for regions inside and outside of parks and protected areas to account for substantial differences in anthropogenic activity and disturbance within the study area. Variance explained in the random forest models ranged from 55.34% to 74.96% for males and 58.15% to 68.46% for females. Predicted HCC levels were higher for females compared to males. Generally, high spatially continuous female HCC levels were associated with parks and protected areas while low-to-moderate levels were associated with increased anthropogenic disturbance. In contrast, male HCC levels were low in parks and protected areas and low-to-moderate in areas with increased anthropogenic disturbance. Spatial variability in gender-specific HCC levels reveal that the type and intensity of external stressors are not uniform across the landscape and that male and female grizzly bears may be exposed to, or perceive, potential stressors differently. We suggest observed spatial patterns of long-term stress may be the result of the availability and distribution of foods related to disturbance features, potential sexual segregation in available habitat selection, and may not be influenced by sources of mortality which represent acute traumas. In this wildlife system and others, conservation and management efforts can benefit by understanding spatial- and gender-based stress responses to landscape conditions. PMID:24386273

Exploring new topography-based subgrid spatial structures for improving land surface modeling

DOE PAGES

Tesfa, Teklu K.; Leung, Lai-Yung Ruby

2017-02-22

Topography plays an important role in land surface processes through its influence on atmospheric forcing, soil and vegetation properties, and river network topology and drainage area. Land surface models with a spatial structure that captures spatial heterogeneity, which is directly affected by topography, may improve the representation of land surface processes. Previous studies found that land surface modeling, using subbasins instead of structured grids as computational units, improves the scalability of simulated runoff and streamflow processes. In this study, new land surface spatial structures are explored by further dividing subbasins into subgrid structures based on topographic properties, including surface elevation,more » slope and aspect. Two methods (local and global) of watershed discretization are applied to derive two types of subgrid structures (geo-located and non-geo-located) over the topographically diverse Columbia River basin in the northwestern United States. In the global method, a fixed elevation classification scheme is used to discretize subbasins. The local method utilizes concepts of hypsometric analysis to discretize each subbasin, using different elevation ranges that also naturally account for slope variations. The relative merits of the two methods and subgrid structures are investigated for their ability to capture topographic heterogeneity and the implications of this on representations of atmospheric forcing and land cover spatial patterns. Results showed that the local method reduces the standard deviation (SD) of subgrid surface elevation in the study domain by 17 to 19 % compared to the global method, highlighting the relative advantages of the local method for capturing subgrid topographic variations. The comparison between the two types of subgrid structures showed that the non-geo-located subgrid structures are more consistent across different area threshold values than the geo-located subgrid structures. Altogether the local method and non-geo-located subgrid structures effectively and robustly capture topographic, climatic and vegetation variability, which is important for land surface modeling.« less

Exploring new topography-based subgrid spatial structures for improving land surface modeling

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

Tesfa, Teklu K.; Leung, Lai-Yung Ruby

Topography plays an important role in land surface processes through its influence on atmospheric forcing, soil and vegetation properties, and river network topology and drainage area. Land surface models with a spatial structure that captures spatial heterogeneity, which is directly affected by topography, may improve the representation of land surface processes. Previous studies found that land surface modeling, using subbasins instead of structured grids as computational units, improves the scalability of simulated runoff and streamflow processes. In this study, new land surface spatial structures are explored by further dividing subbasins into subgrid structures based on topographic properties, including surface elevation,more » slope and aspect. Two methods (local and global) of watershed discretization are applied to derive two types of subgrid structures (geo-located and non-geo-located) over the topographically diverse Columbia River basin in the northwestern United States. In the global method, a fixed elevation classification scheme is used to discretize subbasins. The local method utilizes concepts of hypsometric analysis to discretize each subbasin, using different elevation ranges that also naturally account for slope variations. The relative merits of the two methods and subgrid structures are investigated for their ability to capture topographic heterogeneity and the implications of this on representations of atmospheric forcing and land cover spatial patterns. Results showed that the local method reduces the standard deviation (SD) of subgrid surface elevation in the study domain by 17 to 19 % compared to the global method, highlighting the relative advantages of the local method for capturing subgrid topographic variations. The comparison between the two types of subgrid structures showed that the non-geo-located subgrid structures are more consistent across different area threshold values than the geo-located subgrid structures. Altogether the local method and non-geo-located subgrid structures effectively and robustly capture topographic, climatic and vegetation variability, which is important for land surface modeling.« less

Spatiotemporal correlation structure of the Earth's surface temperature

NASA Astrophysics Data System (ADS)

Fredriksen, Hege-Beate; Rypdal, Kristoffer; Rypdal, Martin

2015-04-01

We investigate the spatiotemporal temperature variability for several gridded instrumental and climate model data sets. The temporal variability is analysed by estimating the power spectral density and studying the differences between local and global temperatures, land and sea, and among local temperature records at different locations. The spatiotemporal correlation structure is analysed through cross-spectra that allow us to compute frequency-dependent spatial autocorrelation functions (ACFs). Our results are then compared to theoretical spectra and frequency-dependent spatial ACFs derived from a fractional stochastic-diffusive energy balance model (FEBM). From the FEBM we expect both local and global temperatures to have a long-range persistent temporal behaviour, and the spectral exponent (β) is expected to increase by a factor of two when going from local to global scales. Our comparison of the average local spectrum and the global spectrum shows good agreement with this model, although the FEBM has so far only been studied for a pure land planet and a pure ocean planet, respectively, with no seasonal forcing. Hence it cannot capture the substantial variability among the local spectra, in particular between the spectra for land and sea, and for equatorial and non-equatorial temperatures. Both models and observation data show that land temperatures in general have a low persistence, while sea surface temperatures show a higher, and also more variable degree of persistence. Near the equator the spectra deviate from the power-law shape expected from the FEBM. Instead we observe large variability at time scales of a few years due to ENSO, and a flat spectrum at longer time scales, making the spectrum more reminiscent of that of a red noise process. From the frequency-dependent spatial ACFs we observe that the spatial correlation length increases with increasing time scale, which is also consistent with the FEBM. One consequence of this is that longer-lasting structures must also be wider in space. The spatial correlation length is also observed to be longer for land than for sea. The climate model simulations studied are mainly CMIP5 control runs of length 500-1000 yr. On time scales up to several centuries we do not observe that the difference between the local and global spectral exponents vanish. This also follows from the FEBM and shows that the dynamics is spatiotemporal (not just temporal) even on these time scales.

Distribution of Reynolds stress carried by mesoscale variability in the Antarctic Circumpolar Current

NASA Technical Reports Server (NTRS)

Johnson, Thomas J.; Stewart, Robert H.; Shum, C. K.; Tapley, Byron D.

1992-01-01

Satellite altimeter data collected by the Geosat Exact Repeat Mission were used to investigate turbulent stress resulting from the variability of surface geostrophic currents in the Antarctic Circumpolar Current. The altimeter measured sea level along the subsatellite track. The variability of the along-track slope of sea level is directly proportional to the variability of surface geostrophic currents in the cross-track direction. Because the grid of crossover points is dense at high latitudes, the satellite data could be used for mapping the temporal and spatial variability of the current. Two and a half years of data were used to compute the statistical structure of the variability. The statistics included the probability distribution functions for each component of the current, the time-lagged autocorrelation functions of the variability, and the Reynolds stress produced by the variability. The results demonstrate that stress is correlated with bathymetry. In some areas the distribution of negative stress indicate that eddies contribute to an acceleration of the mean flow, strengthening the hypothesis that baroclinic instability makes important contributions to strong oceanic currents.

Sensitivity of Land Surface Parameters on Thunderstorm Simulation through HRLDAS-WRF Coupling Mode

NASA Astrophysics Data System (ADS)

Kumar, Dinesh; Kumar, Krishan; Mohanty, U. C.; Kisore Osuri, Krishna

2016-07-01

Land surface characteristics play an important role in large scale, regional and mesoscale atmospheric process. Representation of land surface characteristics can be improved through coupling of mesoscale atmospheric models with land surface models. Mesoscale atmospheric models depend on Land Surface Models (LSM) to provide land surface variables such as fluxes of heat, moisture, and momentum for lower boundary layer evolution. Studies have shown that land surface properties such as soil moisture, soil temperature, soil roughness, vegetation cover, have considerable effect on lower boundary layer. Although, the necessity to initialize soil moisture accurately in NWP models is widely acknowledged, monitoring soil moisture at regional and global scale is a very tough task due to high spatial and temporal variability. As a result, the available observation network is unable to provide the required spatial and temporal data for the most part of the globe. Therefore, model for land surface initializations rely on updated land surface properties from LSM. The solution for NWP land-state initialization can be found by combining data assimilation techniques, satellite-derived soil data, and land surface models. Further, it requires an intermediate step to use observed rainfall, satellite derived surface insolation, and meteorological analyses to run an uncoupled (offline) integration of LSM, so that the evolution of modeled soil moisture can be forced by observed forcing conditions. Therefore, for accurate land-state initialization, high resolution land data assimilation system (HRLDAS) is used to provide the essential land surface parameters. Offline-coupling of HRLDAS-WRF has shown much improved results over Delhi, India for four thunder storm events. The evolution of land surface variables particularly soil moisture, soil temperature and surface fluxes have provided more realistic condition. Results have shown that most of domain part became wetter and warmer after assimilation of soil moisture and soil temperature at the initial condition which helped to improve the exchange fluxes at lower atmospheric level. Mixing ratio were increased along with elevated theta-e at lower level giving a signature of improvement in LDAS experiment leading to a suitable condition for convection. In the analysis, moisture convergence, mixing ratio and vertical velocities have improved significantly in terms of intensity and time lag. Surface variables like soil moisture, soil temperature, sensible heat flux and latent heat flux have progressed in a possible realistic pattern. Above discussion suggests that assimilation of soil moisture and soil temperature improves the overall simulations significantly.

Nitrous Oxide Emissions From Northern Forested and Harvested Ecosystems

NASA Astrophysics Data System (ADS)

Kavanaugh, K. M.; Kellman, L. M.

2005-12-01

Very little is known about how deforestation alters the soil subsurface production and surface emissions of N2O from northern forest soils. Soil N2O surface fluxes and subsurface concentrations from two 3 year old harvested and intact forest pairs of contrasting soil texture were monitored during the 2004 and 2005 growing seasons in the Acadian forest of Atlantic Canada in order to: 1) quantify N2O emissions associated with each land-use type, 2) examine spatial and temporal variations in subsurface concentrations and surface fluxes at each site, and 3) determine the suitability of a photoacoustic gas monitor (PGM) for in- situ field measurements vs. field sample collection and laboratory analysis on a gas chromatograph. Each site was instrumented with 11 permanent collars for surface flux measurements designed to capture the microsite variability at the sites. Subsurface soil gas samplers, designed to identify the important zones of N2O production in the vertical profile were installed at depths of 0, 10, 20 and 35 cm below the organic-mineral soil interface. Surface fluxes were measured with non-steady-state vented surface flux chambers with measurements of all surface flux and subsurface data made on a bi-weekly basis. Results suggest that spatial and temporal variability in surface emissions are very high and routinely close to zero. Subsurface profile concentration data shows vertical concentration profiles at intact forest sites with concentrations close to atmospheric, while harvested sites show a pattern of increasing N2O concentration with depth, reaching a maximum of approximately 27000ppb at 35cm.

Local Adaptive Calibration of the GLASS Surface Incident Shortwave Radiation Product Using Smoothing Spline

NASA Astrophysics Data System (ADS)

Zhang, X.; Liang, S.; Wang, G.

2015-12-01

Incident solar radiation (ISR) over the Earth's surface plays an important role in determining the Earth's climate and environment. Generally, can be obtained from direct measurements, remotely sensed data, or reanalysis and general circulation models (GCMs) data. Each type of product has advantages and limitations: the surface direct measurements provide accurate but sparse spatial coverage, whereas other global products may have large uncertainties. Ground measurements have been normally used for validation and occasionally calibration, but transforming their "true values" spatially to improve the satellite products is still a new and challenging topic. In this study, an improved thin-plate smoothing spline approach is presented to locally "calibrate" the Global LAnd Surface Satellite (GLASS) ISR product using the reconstructed ISR data from surface meteorological measurements. The influences of surface elevation on ISR estimation was also considered in the proposed method. The point-based surface reconstructed ISR was used as the response variable, and the GLASS ISR product and the surface elevation data at the corresponding locations as explanatory variables to train the thin plate spline model. We evaluated the performance of the approach using the cross-validation method at both daily and monthly time scales over China. We also evaluated estimated ISR based on the thin-plate spline method using independent ground measurements at 10 sites from the Coordinated Enhanced Observation Network (CEON). These validation results indicated that the thin plate smoothing spline method can be effectively used for calibrating satellite derived ISR products using ground measurements to achieve better accuracy.

Multi-scale landslide hazard assessment: Advances in global and regional methodologies

NASA Astrophysics Data System (ADS)

Kirschbaum, Dalia; Peters-Lidard, Christa; Adler, Robert; Hong, Yang

2010-05-01

The increasing availability of remotely sensed surface data and precipitation provides a unique opportunity to explore how smaller-scale landslide susceptibility and hazard assessment methodologies may be applicable at larger spatial scales. This research first considers an emerging satellite-based global algorithm framework, which evaluates how the landslide susceptibility and satellite derived rainfall estimates can forecast potential landslide conditions. An analysis of this algorithm using a newly developed global landslide inventory catalog suggests that forecasting errors are geographically variable due to improper weighting of surface observables, resolution of the current susceptibility map, and limitations in the availability of landslide inventory data. These methodological and data limitation issues can be more thoroughly assessed at the regional level, where available higher resolution landslide inventories can be applied to empirically derive relationships between surface variables and landslide occurrence. The regional empirical model shows improvement over the global framework in advancing near real-time landslide forecasting efforts; however, there are many uncertainties and assumptions surrounding such a methodology that decreases the functionality and utility of this system. This research seeks to improve upon this initial concept by exploring the potential opportunities and methodological structure needed to advance larger-scale landslide hazard forecasting and make it more of an operational reality. Sensitivity analysis of the surface and rainfall parameters in the preliminary algorithm indicates that surface data resolution and the interdependency of variables must be more appropriately quantified at local and regional scales. Additionally, integrating available surface parameters must be approached in a more theoretical, physically-based manner to better represent the physical processes underlying slope instability and landslide initiation. Several rainfall infiltration and hydrological flow models have been developed to model slope instability at small spatial scales. This research investigates the potential of applying a more quantitative hydrological model to larger spatial scales, utilizing satellite and surface data inputs that are obtainable over different geographic regions. Due to the significant role that data and methodological uncertainties play in the effectiveness of landslide hazard assessment outputs, the methodology and data inputs are considered within an ensemble uncertainty framework in order to better resolve the contribution and limitations of model inputs and to more effectively communicate the model skill for improved landslide hazard assessment.

Estimates of diffuse phosphorus sources in surface waters of the United States using a spatially referenced watershed model

USGS Publications Warehouse

Alexander, R.B.; Smith, R.A.; Schwarz, G.E.

2004-01-01

The statistical watershed model SPARROW (SPAtially Referenced Regression On Watershed attributes) was used to estimate the sources and transport of total phosphorus (TP) in surface waters of the United States. We calibrated the model using stream measurements of TP from 336 watersheds of mixed land use and spatial data on topography, soils, stream hydrography, and land use (agriculture, forest, shrub/grass, urban). The model explained 87% of the spatial variability in log transformed stream TP flux (kg yr-1). Predictions of stream yield (kg ha-1 yr-1) were typically within 45% of the observed values at the monitoring sites. The model identified appreciable effects of soils, streams, and reservoirs on TP transport, The estimated aquatic rates of phosphorus removal declined with increasing stream size and rates of water flushing in reservoirs (i.e. areal hydraulic loads). A phosphorus budget for the 2.9 million km2 Mississippi River Basin provides a detailed accounting of TP delivery to streams, the removal of TP in surface waters, and the stream export of TP from major interior watersheds for sources associated with each land-use type. ?? US Government 2004.

An Investigation on the Spatial Variability of Manning Roughness Coefficients in Continental-scale River Routing Simulations

NASA Astrophysics Data System (ADS)

Luo, X.; Hong, Y.; Lei, X.; Leung, L. R.; Li, H. Y.; Getirana, A.

2017-12-01

As one essential component of the Earth system modeling, the continental-scale river routing computation plays an important role in applications of Earth system models, such as evaluating the impacts of the global change on water resources and flood hazards. The streamflow timing, which depends on the modeled flow velocities, can be an important aspect of the model results. River flow velocities have been estimated by using the Manning's equation where the Manning roughness coefficient is a key and sensitive parameter. In some early continental-scale studies, the Manning coefficient was determined with simplified methods, such as using a constant value for the entire basin. However, large spatial variability is expected in the Manning coefficients for the numerous channels composing the river network in distributed continental-scale hydrologic modeling. In the application of a continental-scale river routing model in the Amazon Basin, we use spatially varying Manning coefficients dependent on channel sizes and attempt to represent the dominant spatial variability of Manning coefficients. Based on the comparisons of simulation results with in situ streamflow records and remotely sensed river stages, we investigate the comparatively optimal Manning coefficients and explicitly demonstrate the advantages of using spatially varying Manning coefficients. The understanding obtained in this study could be helpful in the modeling of surface hydrology at regional to continental scales.

The Canadian Hydrological Model (CHM): A multi-scale, variable-complexity hydrological model for cold regions

NASA Astrophysics Data System (ADS)

Marsh, C.; Pomeroy, J. W.; Wheater, H. S.

2016-12-01

There is a need for hydrological land surface schemes that can link to atmospheric models, provide hydrological prediction at multiple scales and guide the development of multiple objective water predictive systems. Distributed raster-based models suffer from an overrepresentation of topography, leading to wasted computational effort that increases uncertainty due to greater numbers of parameters and initial conditions. The Canadian Hydrological Model (CHM) is a modular, multiphysics, spatially distributed modelling framework designed for representing hydrological processes, including those that operate in cold-regions. Unstructured meshes permit variable spatial resolution, allowing coarse resolutions at low spatial variability and fine resolutions as required. Model uncertainty is reduced by lessening the necessary computational elements relative to high-resolution rasters. CHM uses a novel multi-objective approach for unstructured triangular mesh generation that fulfills hydrologically important constraints (e.g., basin boundaries, water bodies, soil classification, land cover, elevation, and slope/aspect). This provides an efficient spatial representation of parameters and initial conditions, as well as well-formed and well-graded triangles that are suitable for numerical discretization. CHM uses high-quality open source libraries and high performance computing paradigms to provide a framework that allows for integrating current state-of-the-art process algorithms. The impact of changes to model structure, including individual algorithms, parameters, initial conditions, driving meteorology, and spatial/temporal discretization can be easily tested. Initial testing of CHM compared spatial scales and model complexity for a spring melt period at a sub-arctic mountain basin. The meshing algorithm reduced the total number of computational elements and preserved the spatial heterogeneity of predictions.

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.

Improved quantification of mountain snowpack properties using observations from Unmanned Air Vehicles (UAVs)

NASA Astrophysics Data System (ADS)

Shea, J. M.; Harder, P.; Pomeroy, J. W.; Kraaijenbrink, P. D. A.

2017-12-01

Mountain snowpacks represent a critical seasonal reservoir of water for downstream needs, and snowmelt is a significant component of mountain hydrological budgets. Ground-based point measurements are unable to describe the full spatial variability of snow accumulation and melt rates, and repeat Unmanned Air Vehicle (UAV) surveys provide an unparalleled opportunity to measure snow accumulation, redistribution and melt in alpine environments. This study presents results from a UAV-based observation campaign conducted at the Fortress Mountain Snow Laboratory in the Canadian Rockies in 2017. Seven survey flights were conducted between April (maximum snow accumulation) and mid-July (bare ground) to collect imagery with both an RGB camera and thermal infrared imager with the sensefly eBee RTK platform. UAV imagery are processed with structure from motion techniques, and orthoimages, digital elevation models, and surface temperature maps are validated against concurrent ground observations of snow depth, snow water equivalent, and snow surface temperature. We examine the seasonal evolution of snow depth and snow surface temperature, and explore the spatial covariances of these variables with respect to topographic factors and snow ablation rates. Our results have direct implications for scaling snow ablation calculations and model resolution and discretization.

Algal bloom-associated disease outbreaks among users of freshwater lakes-United States, 2009 - 2010

EPA Science Inventory

‘Algal blooms’ are local abundances of phytoplankton – microscopic photosynthesizing aquatic organisms found in surface waters worldwide; blooms are variable temporally and spatially and frequently produce a visible algal scum on the water. Harmful algal blooms (HABs) are abundan...

On the Interaction between Marine Boundary Layer Cellular Cloudiness and Surface Heat Fluxes

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

Kazil, J.; Feingold, G.; Wang, Hailong

2014-01-02

The interaction between marine boundary layer cellular cloudiness and surface uxes of sensible and latent heat is investigated. The investigation focuses on the non-precipitating closed-cell state and the precipitating open-cell state at low geostrophic wind speed. The Advanced Research WRF model is used to conduct cloud-system-resolving simulations with interactive surface fluxes of sensible heat, latent heat, and of sea salt aerosol, and with a detailed representation of the interaction between aerosol particles and clouds. The mechanisms responsible for the temporal evolution and spatial distribution of the surface heat fluxes in the closed- and open-cell state are investigated and explained. Itmore » is found that the horizontal spatial structure of the closed-cell state determines, by entrainment of dry free tropospheric air, the spatial distribution of surface air temperature and water vapor, and, to a lesser degree, of the surface sensible and latent heat flux. The synchronized dynamics of the the open-cell state drives oscillations in surface air temperature, water vapor, and in the surface fluxes of sensible and latent heat, and of sea salt aerosol. Open-cell cloud formation, cloud optical depth and liquid water path, and cloud and rain water path are identified as good predictors of the spatial distribution of surface air temperature and sensible heat flux, but not of surface water vapor and latent heat flux. It is shown that by enhancing the surface sensible heat flux, the open-cell state creates conditions by which it is maintained. While the open-cell state under consideration is not depleted in aerosol, and is insensitive to variations in sea-salt fluxes, it also enhances the sea-salt flux relative to the closed-cell state. In aerosol-depleted conditions, this enhancement may replenish the aerosol needed for cloud formation, and hence contribute to the perpetuation of the open-cell state as well. Spatial homogenization of the surface fluxes is found to have only a small effect on cloud properties in the investigated cases. This indicates that sub-grid scale spatial variability in the surface flux of sensible and latent heat and of sea salt aerosol may not be required in large scale and global models to describe marine boundary layer cellular cloudiness.« less

Middle Pliocene sea surface temperature variability

USGS Publications Warehouse

Dowsett, H.J.; Chandler, M.A.; Cronin, T. M.; Dwyer, Gary S.

2005-01-01

Estimates of sea surface temperature (SST) based upon foraminifer, diatom, and ostracod assemblages from ocean cores reveal a warm phase of the Pliocene between about 3.3 and 3.0 Ma. Pollen records and plant megafossils, although not as well dated, show evidence for a warmer climate at about the same time. Increased greenhouse forcing and altered ocean heat transport are the leading candidates for the underlying cause of Pliocene global warmth. Despite being a period of global warmth, this interval encompasses considerable variability. Two new SST reconstructions are presented that are designed to provide a climatological error bar for warm peak phases of the Pliocene and to document the spatial distribution and magnitude of SST variability within the mid-Pliocene warm period. These data suggest long-term stability of low-latitude SST and document greater variability in regions of maximum warming. Copyright 2005 by the American Geophysical Union.

Multiscale responses of soil stability and invasive plants to removal of non-native grazers from an arid conservation reserve

USGS Publications Warehouse

Beever, E.A.; Huso, M.; Pyke, D.A.

2006-01-01

Disturbances and ecosystem recovery from disturbance both involve numerous processes that operate on multiple spatial and temporal scales. Few studies have investigated how gradients of disturbance intensity and ecosystem responses are distributed across multiple spatial resolutions and also how this relationship changes through time during recovery. We investigated how cover of non-native species and soil-aggregate stability (a measure of vulnerability to erosion by water) in surface and subsurface soils varied spatially during grazing by burros and cattle and whether patterns in these variables changed after grazer removal from Mojave National Preserve, California, USA. We compared distance from water and number of ungulate defecations - metrics of longer-term and recent grazing intensity, respectively, - as predictors of our response variables. We used information-theoretic analyses to compare hierarchical linear models that accounted for important covariates and allowed for interannual variation in the disturbance-response relationship at local and landscape scales. Soil stability was greater under perennial vegetation than in bare interspaces, and surface soil stability decreased with increasing numbers of ungulate defecations. Stability of surface samples was more affected by time since removal of grazers than was stability of subsurface samples, and subsurface soil stability in bare spaces was not related to grazing intensity, time since removal, or any of our other predictors. In the high rainfall year (2003) after cattle had been removed for 1-2 years, cover of all non-native plants averaged nine times higher than in the low-rainfall year (2002). Given the heterogeneity in distribution of large-herbivore impacts that we observed at several resolutions, hierarchical analyses provided a more complete understanding of the spatial and temporal complexities of disturbance and recovery processes in arid ecosystems. ?? 2006 Blackwell Publishing Ltd.

Multi-scale responses of soil stability and invasive plants to removal of non-native grazers from an arid conservation reserve

USGS Publications Warehouse

Beever, Erik A.; Huso, Manuela M. P.; Pyke, David A.

2006-01-01

Disturbances and ecosystem recovery from disturbance both involve numerous processes that operate on multiple spatial and temporal scales. Few studies have investigated how gradients of disturbance intensity and ecosystem responses are distributed across multiple spatial resolutions and also how this relationship changes through time during recovery. We investigated how cover of non-native species and soil-aggregate stability (a measure of vulnerability to erosion by water) in surface and subsurface soils varied spatially during grazing by burros and cattle and whether patterns in these variables changed after grazer removal from Mojave National Preserve, California, USA. We compared distance from water and number of ungulate defecations — metrics of longer-term and recent grazing intensity, respectively, — as predictors of our response variables. We used information-theoretic analyses to compare hierarchical linear models that accounted for important covariates and allowed for interannual variation in the disturbance–response relationship at local and landscape scales. Soil stability was greater under perennial vegetation than in bare interspaces, and surface soil stability decreased with increasing numbers of ungulate defecations. Stability of surface samples was more affected by time since removal of grazers than was stability of subsurface samples, and subsurface soil stability in bare spaces was not related to grazing intensity, time since removal, or any of our other predictors. In the high rainfall year (2003) after cattle had been removed for 1–2 years, cover of all non-native plants averaged nine times higher than in the low-rainfall year (2002). Given the heterogeneity in distribution of large-herbivore impacts that we observed at several resolutions, hierarchical analyses provided a more complete understanding of the spatial and temporal complexities of disturbance and recovery processes in arid ecosystems.

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

NASA Astrophysics Data System (ADS)

Lange, Stefan

2018-05-01

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

Methylmercury bioaccumulation in an urban estuary: Delaware River USA.

PubMed

Buckman, Kate; Taylor, Vivien; Broadley, Hannah; Hocking, Daniel; Balcom, Prentiss; Mason, Rob; Nislow, Keith; Chen, Celia

2017-09-01

Spatial variation in mercury (Hg) and methylmercury (MeHg) bioaccumulation in urban coastal watersheds reflects complex interactions between Hg sources, land use, and environmental gradients. We examined MeHg concentrations in fauna from the Delaware River estuary, and related these measurements to environmental parameters and human impacts on the waterway. The sampling sites followed a north to south gradient of increasing salinity, decreasing urban influence, and increasing marsh cover. Although mean total Hg in surface sediments (top 4cm) peaked in the urban estuarine turbidity maximum and generally decreased downstream, surface sediment MeHg concentrations showed no spatial patterns consistent with the examined environmental gradients, indicating urban influence on Hg loading to the sediment but not subsequent methylation. Surface water particulate MeHg concentration showed a positive correlation with marsh cover whereas dissolved MeHg concentrations were slightly elevated in the estuarine turbidity maximum region. Spatial patterns of MeHg bioaccumulation in resident fauna varied across taxa. Small fish showed increased MeHg concentrations in the more urban/industrial sites upstream, with concentrations generally decreasing farther downstream. Invertebrates either showed no clear spatial patterns in MeHg concentrations (blue crabs, fiddler crabs) or increasing concentrations further downstream (grass shrimp). Best-supported linear mixed models relating tissue concentration to environmental variables reflected these complex patterns, with species specific model results dominated by random site effects with a combination of particulate MeHg and landscape variables influencing bioaccumulation in some species. The data strengthen accumulating evidence that bioaccumulation in estuaries can be decoupled from sediment MeHg concentration, and that drivers of MeHg production and fate may vary within a small region.

Disentangling how landscape spatial and temporal heterogeneity affects Savanna birds.

PubMed

Price, Bronwyn; McAlpine, Clive A; Kutt, Alex S; Ward, Doug; Phinn, Stuart R; Ludwig, John A

2013-01-01

In highly seasonal tropical environments, temporal changes in habitat and resources are a significant determinant of the spatial distribution of species. This study disentangles the effects of spatial and mid to long-term temporal heterogeneity in habitat on the diversity and abundance of savanna birds by testing four competing conceptual models of varying complexity. Focussing on sites in northeast Australia over a 20 year time period, we used ground cover and foliage projected cover surfaces derived from a time series of Landsat Thematic Mapper imagery, rainfall data and site-level vegetation surveys to derive measures of habitat structure at local (1-100 ha) and landscape (100-1000s ha) scales. We used generalised linear models and an information theoretic approach to test the independent effects of spatial and temporal influences on savanna bird diversity and the abundance of eight species with different life-history behaviours. Of four competing models defining influences on assemblages of savanna birds, the most parsimonious included temporal and spatial variability in vegetation cover and site-scale vegetation structure, suggesting savanna bird species respond to spatial and temporal habitat heterogeneity at both the broader landscape scale and at the fine-scale. The relative weight, strength and direction of the explanatory variables changed with each of the eight species, reflecting their different ecology and behavioural traits. This study demonstrates that variations in the spatial pattern of savanna vegetation over periods of 10 to 20 years at the local and landscape scale strongly affect bird diversity and abundance. Thus, it is essential to monitor and manage both spatial and temporal variability in avian habitat to achieve long-term biodiversity outcomes.

Disentangling How Landscape Spatial and Temporal Heterogeneity Affects Savanna Birds

PubMed Central

Price, Bronwyn; McAlpine, Clive A.; Kutt, Alex S.; Ward, Doug; Phinn, Stuart R.; Ludwig, John A.

2013-01-01

In highly seasonal tropical environments, temporal changes in habitat and resources are a significant determinant of the spatial distribution of species. This study disentangles the effects of spatial and mid to long-term temporal heterogeneity in habitat on the diversity and abundance of savanna birds by testing four competing conceptual models of varying complexity. Focussing on sites in northeast Australia over a 20 year time period, we used ground cover and foliage projected cover surfaces derived from a time series of Landsat Thematic Mapper imagery, rainfall data and site-level vegetation surveys to derive measures of habitat structure at local (1–100 ha) and landscape (100–1000s ha) scales. We used generalised linear models and an information theoretic approach to test the independent effects of spatial and temporal influences on savanna bird diversity and the abundance of eight species with different life-history behaviours. Of four competing models defining influences on assemblages of savanna birds, the most parsimonious included temporal and spatial variability in vegetation cover and site-scale vegetation structure, suggesting savanna bird species respond to spatial and temporal habitat heterogeneity at both the broader landscape scale and at the fine-scale. The relative weight, strength and direction of the explanatory variables changed with each of the eight species, reflecting their different ecology and behavioural traits. This study demonstrates that variations in the spatial pattern of savanna vegetation over periods of 10 to 20 years at the local and landscape scale strongly affect bird diversity and abundance. Thus, it is essential to monitor and manage both spatial and temporal variability in avian habitat to achieve long-term biodiversity outcomes. PMID:24066138

Variability of pesticide exposure in a stream mesocosm system: macrophyte-dominated vs. non-vegetated sections.

PubMed

Beketov, Mikhail A; Liess, Matthias

2008-12-01

For flowing water bodies no information is available about patterns of contaminant distribution in flowing water compared to macrophyte-dominated structures. The aim of the study was to examine temporal dynamic and spatial cross-channel variability of pulse exposure of the insecticide thiacloprid in outdoor stream mesocosms. Two distinct cross-channel sections have been considered: macrophyte-dominated littoral and non-vegetated midstream. Median disappearance time ranged from 17 to 43 h (water phase, midstream). We showed that during the exposure pulse (10h) thiacloprid concentrations in the macrophyte-dominated section were 20-60% lower than those in the non-vegetated section. This suggests that spatial variability in contaminant concentrations, particularly in streams containing macrophytes, should be taken into account to enable a more realistic assessment of (i) exposure and associated effects and (ii) mass transport of pesticides and other chemicals into river systems (e.g. losses with surface runoff).

Constraints on Vesta's elemental composition: Fast neutron measurements by Dawn's gamma ray and neutron detector

PubMed Central

Lawrence, David J; Peplowski, Patrick N; Prettyman, Thomas H; Feldman, William C; Bazell, David; Mittlefehldt, David W; Reedy, Robert C; Yamashita, Naoyuki

2013-01-01

Surface composition information from Vesta is reported using fast neutron data collected by the gamma ray and neutron detector on the Dawn spacecraft. After correcting for variations due to hydrogen, fast neutrons show a compositional dynamic range and spatial variability that is consistent with variations in average atomic mass from howardite, eucrite, and diogenite (HED) meteorites. These data provide additional compositional evidence that Vesta is the parent body to HED meteorites. A subset of fast neutron data having lower statistical precision show spatial variations that are consistent with a 400 ppm variability in hydrogen concentrations across Vesta and supports the idea that Vesta's hydrogen is due to long-term delivery of carbonaceous chondrite material. PMID:26074718

New Mexico Tech landmine, UXO, IED detection sensor test facility: measurements in real field soils

NASA Astrophysics Data System (ADS)

Hendrickx, Jan M. H.; Alkov, Nicole; Hong, Sung-ho; Van Dam, Remke L.; Kleissl, Jan; Shannon, Heather; Meason, John; Borchers, Brian; Harmon, Russell S.

2006-05-01

Modeling studies and experimental work have demonstrated that the dynamic behavior of soil physical properties has a significant effect on most sensors for the detection of buried land mines. An outdoor test site has been constructed allowing full control over soil water content and continuous monitoring of important soil properties and environmental conditions. Time domain reflectometry sensors and thermistors measure soil water1 content and temperature, respectively, at different depths above and below the land mines as well as in homogeneous soil away from the land mines. During the two-year operation of the test-site, the soils have evolved to reflect real field soil conditions. This paper compares visual observations as well as ground-penetrating radar and thermal infrared measurements at this site taken immediately after construction in early 2004 with measurements from early 2006. The visual observations reveal that the 2006 soil surfaces exhibit a much higher spatial variability due to the development of mini-reliefs, "loose" and "connected" soil crusts, cracks in clay soils, and vegetation. Evidence is presented that the increased variability of soil surface characteristics leads to a higher natural spatial variability of soil surface temperatures and, thus, to a lower probability to detect landmines using thermal imagery. No evidence was found that the soil surface changes affect the GPR signatures of landmines under the soil conditions encountered in this study. The New Mexico Tech outdoor Landmine Detection Sensor Test Facility is easily accessible and anyone interested is welcome to use it for sensor testing.

Evaluating the impact of sea surface temperature (SST) on spatial distribution of chlorophyll-a concentration in the East China Sea

NASA Astrophysics Data System (ADS)

Ji, Chenxu; Zhang, Yuanzhi; Cheng, Qiuming; Tsou, JinYeu; Jiang, Tingchen; Liang, X. San

2018-06-01

In this study, we analyze spatial and temporal sea surface temperature (SST) and chlorophylla (Chl-a) concentration in the East China Sea (ECS) during the period 2003-2016. Level 3 (4 km) monthly SST and Chl-a data from the Moderate Resolution Imaging Spectroradiometer Satellite (MODIS-Aqua) were reconstructed using the data interpolation empirical orthogonal function (DINEOF) method and used to evaluated the relationship between the two variables. The approaches employed included correlation analysis, regression analysis, and so forth. Our results show that certain strong oceanic SSTs affect Chl-a concentration, with particularly high correlation seen in the coastal area of Jiangsu and Zhejiang provinces. The mean temperature of the high correlated region was 18.67 °C. This finding may suggest that the SST has an important impact on the spatial distribution of Chl-a concentration in the ECS.

Soil variability in engineering applications

NASA Astrophysics Data System (ADS)

Vessia, Giovanna

2014-05-01

Natural geomaterials, as soils and rocks, show spatial variability and heterogeneity of physical and mechanical properties. They can be measured by in field and laboratory testing. The heterogeneity concerns different values of litho-technical parameters pertaining similar lithological units placed close to each other. On the contrary, the variability is inherent to the formation and evolution processes experienced by each geological units (homogeneous geomaterials on average) and captured as a spatial structure of fluctuation of physical property values about their mean trend, e.g. the unit weight, the hydraulic permeability, the friction angle, the cohesion, among others. The preceding spatial variations shall be managed by engineering models to accomplish reliable designing of structures and infrastructures. Materon (1962) introduced the Geostatistics as the most comprehensive tool to manage spatial correlation of parameter measures used in a wide range of earth science applications. In the field of the engineering geology, Vanmarcke (1977) developed the first pioneering attempts to describe and manage the inherent variability in geomaterials although Terzaghi (1943) already highlighted that spatial fluctuations of physical and mechanical parameters used in geotechnical designing cannot be neglected. A few years later, Mandelbrot (1983) and Turcotte (1986) interpreted the internal arrangement of geomaterial according to Fractal Theory. In the same years, Vanmarcke (1983) proposed the Random Field Theory providing mathematical tools to deal with inherent variability of each geological units or stratigraphic succession that can be resembled as one material. In this approach, measurement fluctuations of physical parameters are interpreted through the spatial variability structure consisting in the correlation function and the scale of fluctuation. Fenton and Griffiths (1992) combined random field simulation with the finite element method to produce the Random Finite Element Method (RFEM). This method has been used to investigate the random behavior of soils in the context of a variety of classical geotechnical problems. Afterward, some following studies collected the worldwide variability values of many technical parameters of soils (Phoon and Kulhawy 1999a) and their spatial correlation functions (Phoon and Kulhawy 1999b). In Italy, Cherubini et al. (2007) calculated the spatial variability structure of sandy and clayey soils from the standard cone penetration test readings. The large extent of the worldwide measured spatial variability of soils and rocks heavily affects the reliability of geotechnical designing as well as other uncertainties introduced by testing devices and engineering models. So far, several methods have been provided to deal with the preceding sources of uncertainties in engineering designing models (e.g. First Order Reliability Method, Second Order Reliability Method, Response Surface Method, High Dimensional Model Representation, etc.). Nowadays, the efforts in this field have been focusing on (1) measuring spatial variability of different rocks and soils and (2) developing numerical models that take into account the spatial variability as additional physical variable. References Cherubini C., Vessia G. and Pula W. 2007. Statistical soil characterization of Italian sites for reliability analyses. Proc. 2nd Int. Workshop. on Characterization and Engineering Properties of Natural Soils, 3-4: 2681-2706. Griffiths D.V. and Fenton G.A. 1993. Seepage beneath water retaining structures founded on spatially random soil, Géotechnique, 43(6): 577-587. Mandelbrot B.B. 1983. The Fractal Geometry of Nature. San Francisco: W H Freeman. Matheron G. 1962. Traité de Géostatistique appliquée. Tome 1, Editions Technip, Paris, 334 p. Phoon K.K. and Kulhawy F.H. 1999a. Characterization of geotechnical variability. Can Geotech J, 36(4): 612-624. Phoon K.K. and Kulhawy F.H. 1999b. Evaluation of geotechnical property variability. Can Geotech J, 36(4): 625-639. Terzaghi K. 1943. Theoretical Soil Mechanics. New York: John Wiley and Sons. Turcotte D.L. 1986. Fractals and fragmentation. J Geophys Res, 91: 1921-1926. Vanmarcke E.H. 1977. Probabilistic modeling of soil profiles. J Geotech Eng Div, ASCE, 103: 1227-1246. Vanmarcke E.H. 1983. Random fields: analysis and synthesis. MIT Press, Cambridge.

Monitoring surface urban heat island formation in a tropical mountain city using Landsat data (1987-2015)

NASA Astrophysics Data System (ADS)

Estoque, Ronald C.; Murayama, Yuji

2017-11-01

Since it was first described about two centuries ago and due to its adverse impacts on urban ecological environment and the overall livability of cities, the urban heat island (UHI) phenomenon has been, and still is, an important research topic across various fields of study. However, UHI studies on cities in mountain regions are still lacking. This study aims to contribute to this endeavor by monitoring and examining the formation of surface UHI (SUHI) in a tropical mountain city of Southeast Asia -Baguio City, the summer capital of the Philippines- using Landsat data (1987-2015). Based on mean surface temperature difference between impervious surface (IS) and green space (GS1), SUHI intensity (SUHII) in the study area increased from 2.7 °C in 1987 to 3.4 °C in 2015. Between an urban zone (>86% impervious) and a rural zone (<10% impervious) along the urban-rural gradient, it increased from 4.0 °C in 1987 to 8.2 °C in 2015. These results are consistent with the rapid urbanization of the area over the same period, which resulted in a rapid expansion of impervious surfaces and substantial loss of green spaces. Together with landscape composition variables (e.g. fraction of IS), topographic variables (e.g. hillshade) can help explain a significant amount of spatial variations in surface temperature in the area (R2 = 0.56-0.85) (p < 0.001). The relative importance of the 'fraction of IS' variable also increased, indicating that its unique explanatory and predictive power concerning the spatial variations of surface temperature increases as the city size becomes bigger and SUHI gets more intense. Overall, these results indicate that the cool temperature of the study area being situated in a mountain region did not hinder the formation of SUHI. Thus, the formation and effects of UHIs, including possible mitigation and adaptation measures, should be considered in landscape planning for the sustainable urban development of the area.

Retinotopic Maps, Spatial Tuning, and Locations of Human Visual Areas in Surface Coordinates Characterized with Multifocal and Blocked fMRI Designs

PubMed Central

Henriksson, Linda; Karvonen, Juha; Salminen-Vaparanta, Niina; Railo, Henry; Vanni, Simo

2012-01-01

The localization of visual areas in the human cortex is typically based on mapping the retinotopic organization with functional magnetic resonance imaging (fMRI). The most common approach is to encode the response phase for a slowly moving visual stimulus and to present the result on an individual's reconstructed cortical surface. The main aims of this study were to develop complementary general linear model (GLM)-based retinotopic mapping methods and to characterize the inter-individual variability of the visual area positions on the cortical surface. We studied 15 subjects with two methods: a 24-region multifocal checkerboard stimulus and a blocked presentation of object stimuli at different visual field locations. The retinotopic maps were based on weighted averaging of the GLM parameter estimates for the stimulus regions. In addition to localizing visual areas, both methods could be used to localize multiple retinotopic regions-of-interest. The two methods yielded consistent retinotopic maps in the visual areas V1, V2, V3, hV4, and V3AB. In the higher-level areas IPS0, VO1, LO1, LO2, TO1, and TO2, retinotopy could only be mapped with the blocked stimulus presentation. The gradual widening of spatial tuning and an increase in the responses to stimuli in the ipsilateral visual field along the hierarchy of visual areas likely reflected the increase in the average receptive field size. Finally, after registration to Freesurfer's surface-based atlas of the human cerebral cortex, we calculated the mean and variability of the visual area positions in the spherical surface-based coordinate system and generated probability maps of the visual areas on the average cortical surface. The inter-individual variability in the area locations decreased when the midpoints were calculated along the spherical cortical surface compared with volumetric coordinates. These results can facilitate both analysis of individual functional anatomy and comparisons of visual cortex topology across studies. PMID:22590626

Recent recovery of surface wind speed after decadal decrease: a focus on South Korea

NASA Astrophysics Data System (ADS)

Kim, JongChun; Paik, Kyungrock

2015-09-01

We investigate the multi-decadal variability of observed surface wind speed around South Korea. It is found that surface wind speed exhibits decreasing trend from mid-1950s until 2003, which is similar with the trends reported for other parts of the world. However, the decreasing trend ceases and becomes unclear since then. It is revealed that decreasing wind speed until 2003 is strongly associated with the decreasing trend of the spatial variance in both atmospheric pressure and air temperature across the East Asia for the same period. On the contrary, break of decreasing trend in surface wind speed since 2003 is associated with increasing spatial variance in surface temperature over the East Asia. Ground observation shows that surface wind speed and air temperature exhibit highly negative correlations for both summer and winter prior to 2003. However, since 2003, the correlations differ between seasons. We suggest that mechanisms behind the recent wind speed trend are different between summer and winter. This is on the basis of an interesting finding that air temperature has decreased while surface temperature has increased during winter months since 2003. We hypothesize that such contrasting temperature trends indicate more frequent movement of external cold air mass into the region since 2003. We also hypothesize that increasing summer wind speed is driven by intrusion of warm air mass into the region which is witnessed via increasing spatial variance in surface temperature across East Asia and the fact that both air and surface temperature rise together.

CentNet—A deployable 100-station network for surface exchange research

NASA Astrophysics Data System (ADS)

Oncley, S.; Horst, T. W.; Semmer, S.; Militzer, J.; Maclean, G.; Knudson, K.

2014-12-01

Climate, air quality, atmospheric composition, surface hydrology, and ecological processes are directly affected by the Earth's surface. Complexity of this surface exists at multiple spatial scales, which complicates the understanding of these processes. NCAR/EOL currently provides a facility to the research community to make direct eddy-covariance flux observations to quantify surface-atmosphere interactions. However, just as model resolution has continued to increase, there is a need to increase the spatial density of flux measurements to capture the wide variety of scales that contribute to exchange processes close to the surface. NCAR/EOL now has developed the CentNet facility, that is envisioned to have on the order of 100 surface flux stations deployable for periods of months to years. Each station would measure standard meteorological variables, all components of the surface energy balance (including turbulence fluxes and radiation), atmospheric composition, and other quantities to characterize the surface. Thus, CentNet can support observational research in the biogeosciences, hydrology, urban meteorology, basic meteorology, and turbulence. CentNet has been designed to be adaptable to a wide variety of research problems while keeping operations manageable. Tower infrastructure has been designed to be lightweight, easily deployed, and with a minimal set-up footprint. CentNet uses sensor networks to increase spatial sampling at each station. The data system saves every sample on site to retain flexibility in data analysis. We welcome guidance on development and funding priorities as we build CentNet.

Modeling and analysis of LWIR signature variability associated with 3D and BRDF effects

NASA Astrophysics Data System (ADS)

Adler-Golden, Steven; Less, David; Jin, Xuemin; Rynes, Peter

2016-05-01

Algorithms for retrieval of surface reflectance, emissivity or temperature from a spectral image almost always assume uniform illumination across the scene and horizontal surfaces with Lambertian reflectance. When these algorithms are used to process real 3-D scenes, the retrieved "apparent" values contain the strong, spatially dependent variations in illumination as well as surface bidirectional reflectance distribution function (BRDF) effects. This is especially problematic with horizontal or near-horizontal viewing, where many observed surfaces are vertical, and where horizontal surfaces can show strong specularity. The goals of this study are to characterize long-wavelength infrared (LWIR) signature variability in a HSI 3-D scene and develop practical methods for estimating the true surface values. We take advantage of synthetic near-horizontal imagery generated with the high-fidelity MultiService Electro-optic Signature (MuSES) model, and compare retrievals of temperature and directional-hemispherical reflectance using standard sky downwelling illumination and MuSES-based non-uniform environmental illumination.

Estimation and correction of different flavors of surface observation biases in ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Lorente-Plazas, Raquel; Hacker, Josua P.; Collins, Nancy; Lee, Jared A.

2017-04-01

The impact of assimilating surface observations has been shown in several publications, for improving weather prediction inside of the boundary layer as well as the flow aloft. However, the assimilation of surface observations is often far from optimal due to the presence of both model and observation biases. The sources of these biases can be diverse: an instrumental offset, errors associated to the comparison of point-based observations and grid-cell average, etc. To overcome this challenge, a method was developed using the ensemble Kalman filter. The approach consists on representing each observation bias as a parameter. These bias parameters are added to the forward operator and they extend the state vector. As opposed to the observation bias estimation approaches most common in operational systems (e.g. for satellite radiances), the state vector and parameters are simultaneously updated by applying the Kalman filter equations to the augmented state. The method to estimate and correct the observation bias is evaluated using observing system simulation experiments (OSSEs) with the Weather Research and Forecasting (WRF) model. OSSEs are constructed for the conventional observation network including radiosondes, aircraft observations, atmospheric motion vectors, and surface observations. Three different kinds of biases are added to 2-meter temperature for synthetic METARs. From the simplest to more sophisticated, imposed biases are: (1) a spatially invariant bias, (2) a spatially varying bias proportional to topographic height differences between the model and the observations, and (3) bias that is proportional to the temperature. The target region characterized by complex terrain is the western U.S. on a domain with 30-km grid spacing. Observations are assimilated every 3 hours using an 80-member ensemble during September 2012. Results demonstrate that the approach is able to estimate and correct the bias when it is spatially invariant (experiment 1). More complex bias structure in experiments (2) and (3) are more difficult to estimate, but still possible. Estimated the parameter in experiments with unbiased observations results in spatial and temporal parameter variability about zero, and establishes a threshold on the accuracy of the parameter in further experiments. When the observations are biased, the mean parameter value is close to the true bias, but temporal and spatial variability in the parameter estimates is similar to the parameters used when estimating a zero bias in the observations. The distributions are related to other errors in the forecasts, indicating that the parameters are absorbing some of the forecast error from other sources. In this presentation we elucidate the reasons for the resulting parameter estimates, and their variability.

Estimating the relationship between urban 3D morphology and land surface temperature using airborne LiDAR and Landsat-8 Thermal Infrared Sensor data

NASA Astrophysics Data System (ADS)

Lee, J. H.

2015-12-01

Urban forests are known for mitigating the urban heat island effect and heat-related health issues by reducing air and surface temperature. Beyond the amount of the canopy area, however, little is known what kind of spatial patterns and structures of urban forests best contributes to reducing temperatures and mitigating the urban heat effects. Previous studies attempted to find the relationship between the land surface temperature and various indicators of vegetation abundance using remote sensed data but the majority of those studies relied on two dimensional area based metrics, such as tree canopy cover, impervious surface area, and Normalized Differential Vegetation Index, etc. This study investigates the relationship between the three-dimensional spatial structure of urban forests and urban surface temperature focusing on vertical variance. We use a Landsat-8 Thermal Infrared Sensor image (acquired on July 24, 2014) to estimate the land surface temperature of the City of Sacramento, CA. We extract the height and volume of urban features (both vegetation and non-vegetation) using airborne LiDAR (Light Detection and Ranging) and high spatial resolution aerial imagery. Using regression analysis, we apply empirical approach to find the relationship between the land surface temperature and different sets of variables, which describe spatial patterns and structures of various urban features including trees. Our analysis demonstrates that incorporating vertical variance parameters improve the accuracy of the model. The results of the study suggest urban tree planting is an effective and viable solution to mitigate urban heat by increasing the variance of urban surface as well as evaporative cooling effect.

Multi-scale approach to the environmental factors effects on spatio-temporal variability of Chironomus salinarius (Diptera: Chironomidae) in a French coastal lagoon

NASA Astrophysics Data System (ADS)

Cartier, V.; Claret, C.; Garnier, R.; Fayolle, S.; Franquet, E.

2010-03-01

The complexity of the relationships between environmental factors and organisms can be revealed by sampling designs which consider the contribution to variability of different temporal and spatial scales, compared to total variability. From a management perspective, a multi-scale approach can lead to time-saving. Identifying environmental patterns that help maintain patchy distribution is fundamental in studying coastal lagoons, transition zones between continental and marine waters characterised by great environmental variability on spatial and temporal scales. They often present organic enrichment inducing decreased species richness and increased densities of opportunist species like C hironomus salinarius, a common species that tends to swarm and thus constitutes a nuisance for human populations. This species is dominant in the Bolmon lagoon, a French Mediterranean coastal lagoon under eutrophication. Our objective was to quantify variability due to both spatial and temporal scales and identify the contribution of different environmental factors to this variability. The population of C. salinarius was sampled from June 2007 to June 2008 every two months at 12 sites located in two areas of the Bolmon lagoon, at two different depths, with three sites per area-depth combination. Environmental factors (temperature, dissolved oxygen both in sediment and under water surface, sediment organic matter content and grain size) and microbial activities (i.e. hydrolase activities) were also considered as explanatory factors of chironomid densities and distribution. ANOVA analysis reveals significant spatial differences regarding the distribution of chironomid larvae for the area and the depth scales and their interaction. The spatial effect is also revealed for dissolved oxygen (water), salinity and fine particles (area scale), and for water column depth. All factors but water column depth show a temporal effect. Spearman's correlations highlight the seasonal effect (temperature, dissolved oxygen in sediment and water) as well as the effect of microbial activities on chironomid larvae. Our results show that a multi-scale approach identifies patchy distribution, even when there is relative environmental homogeneity.

Assessing and correcting spatial representativeness of tower eddy-covariance flux measurements

NASA Astrophysics Data System (ADS)

Metzger, S.; Xu, K.; Desai, A. R.; Taylor, J. R.; Kljun, N.; Blanken, P.; Burns, S. P.; Scott, R. L.

2014-12-01

Estimating the landscape-scale exchange of ecologically relevant trace gas and energy fluxes from tower eddy-covariance (EC) measurements is often complicated by surface heterogeneity. For example, a tower EC measurement may represent less than 1% of a grid cell resolved by mechanistic models (order 100-1000 km2). In particular for data assimilation or comparison with large-scale observations, it is hence critical to assess and correct the spatial representativeness of tower EC measurements. We present a procedure that determines from a single EC tower the spatio-temporally explicit flux field of its surrounding. The underlying principle is to extract the relationship between biophysical drivers and ecological responses from measurements under varying environmental conditions. For this purpose, high-frequency EC flux processing and source area calculations (≈60 h-1) are combined with remote sensing retrievals of land surface properties and subsequent machine learning. Methodological details are provided in our companion presentation "Towards the spatial rectification of tower-based eddy-covariance flux observations". We apply the procedure to one year of data from each of four AmeriFlux sites under different climate and ecological environments: Lost Creek shrub fen wetland, Niwot Ridge subalpine conifer, Park Falls mixed forest, and Santa Rita mesquite savanna. We find that heat fluxes from the Park Falls 122-m-high EC measurement and from a surrounding 100 km2 target area differ up to 100 W m-2, or 65%. Moreover, 85% and 24% of the EC flux observations are adequate surrogates of the mean surface-atmosphere exchange and its spatial variability across a 900 km2 target area, respectively, at 5% significance and 80% representativeness levels. Alternatively, the resulting flux grids can be summarized as probability density functions, and used to inform mechanistic models directly with the mean flux value and its spatial variability across a model grid cell. Lastly, for each site we evaluate the applicability of the procedure based on a full bottom-up uncertainty budget.

TES ammonia retrieval strategy and global observations of the spatial and seasonal variability of ammonia (journal)

EPA Science Inventory

Presently only limited sets of tropospheric ammonia (NH3) measurements in the Earth's atmosphere have been reported from satellite and surface station measurements, despite the well-documented negative impact of NH3 on the environment and human health. Presented here is a detaile...

Spatial variability in nitrous oxide and methane emissions from beef cattle feedyard pen surfaces

USDA-ARS?s Scientific Manuscript database

Greenhouse gas emissions from beef cattle feedlots include enteric carbon dioxide and methane, and manure-derived methane, nitrous oxide and carbon dioxide. Enteric methane comprises the largest portion of the greenhouse gas footprint of beef cattle feedyards. For the manure component, methane is th...

Small-scale and mesoscale lake surface water temperature structure: Thermography and in situ measurements from Lake Geneva, Switzerland

NASA Astrophysics Data System (ADS)

Irani Rahaghi, Abolfazl; Lemmin, Ulrich; Bouffard, Damien; Riffler, Michael; Wunderle, Stefan; Barry, Andrew

2017-04-01

Lake surface water temperature (LSWT), which varies spatially and temporarily, reflects meteorological and climatological forcing more than any other physical lake parameter. There are different data sources for LSWT mapping, including remote sensing and in situ measurements. Depending on cloud cover, satellite data can depict large-scale thermal patterns, but not the meso- or small-scale processes. Meso-scale thermography allows complementing (and hence ground-truth) satellite imagery at the sub-pixel scale. A Balloon Launched Imaging and Monitoring Platform (BLIMP) was used to measure the LSWT at the meso-scale. The BLIMP consists of a small balloon tethered to a boat and is equipped with thermal and RGB cameras, as well as other instrumentation for geo-location and communication. A feature matching-based algorithm was implemented to create composite thermal images. Simultaneous ground-truthing of the BLIMP data were achieved using an autonomous craft measuring among other in situ surface/near surface temperatures, radiation and meteorological data. Latent and sensible surface heat fluxes were calculated using the bulk parameterization algorithm based on similarity theory. Results are presented for the day-time stratified low wind speed (up to 3 ms-1) conditions over Lake Geneva for two field campaigns, each of 6 h on 18 March and 19 July 2016. The meso-scale temperature field ( 1-m pixel resolution) had a range and standard deviation of 2.4°C and 0.3°C, respectively, over a 1-km2 area (typical satellite pixel size). Interestingly, at the sub-pixel scale, various temporal and spatial thermal structures are evident - an obvious example being streaks in the along-wind direction during March, which we hypothesize are caused by the steady 3 h wind condition. The results also show that the spatial variability of the estimated total heat flux is due to the corresponding variability of the longwave cooling from the water surface and the latent heat flux.

Land surface phenology of Northeast China during 2000-2015: temporal changes and relationships with climate changes.

PubMed

Zhang, Yue; Li, Lin; Wang, Hongbin; Zhang, Yao; Wang, Naijia; Chen, Junpeng

2017-10-01

As an important crop growing area, Northeast China (NEC) plays a vital role in China's food security, which has been severely affected by climate change in recent years. Vegetation phenology in this region is sensitive to climate change, and currently, the relationship between the phenology of NEC and climate change remains unclear. In this study, we used a satellite-derived normalized difference vegetation index (NDVI) to obtain the temporal patterns of the land surface phenology in NEC from 2000 to 2015 and validated the results using ground phenology observations. We then explored the relationships among land surface phenology, temperature, precipitation, and sunshine hours for relevant periods. Our results showed that the NEC experienced great phenological changes in terms of spatial heterogeneity during 2000-2015. The spatial patterns of land surface phenology mainly changed with altitude and land cover type. In most regions of NEC, the start date of land surface phenology had advanced by approximately 1.0 days year -1 , and the length of land surface phenology had been prolonged by approximately 1.0 days year -1 except for the needle-leaf and cropland areas, due to the warm conditions. We found that a distinct inter-annual variation in land surface phenology related to climate variables, even if some areas presented non-significant trends. Land surface phenology was coupled with climate variables and distinct responses at different combinations of temperature, precipitation, sunshine hours, altitude, and anthropogenic influence. These findings suggest that remote sensing and our phenology extracting methods hold great potential for helping to understand how land surface phenology is sensitive to global climate change.

Nitrate variability in groundwater of North Carolina using monitoring and private well data models.

PubMed

Messier, Kyle P; Kane, Evan; Bolich, Rick; Serre, Marc L

2014-09-16

Nitrate (NO3-) is a widespread contaminant of groundwater and surface water across the United States that has deleterious effects to human and ecological health. This study develops a model for predicting point-level groundwater NO3- at a state scale for monitoring wells and private wells of North Carolina. A land use regression (LUR) model selection procedure is developed for determining nonlinear model explanatory variables when they are known to be correlated. Bayesian Maximum Entropy (BME) is used to integrate the LUR model to create a LUR-BME model of spatial/temporal varying groundwater NO3- concentrations. LUR-BME results in a leave-one-out cross-validation r2 of 0.74 and 0.33 for monitoring and private wells, effectively predicting within spatial covariance ranges. Results show significant differences in the spatial distribution of groundwater NO3- contamination in monitoring versus private wells; high NO3- concentrations in the southeastern plains of North Carolina; and wastewater treatment residuals and swine confined animal feeding operations as local sources of NO3- in monitoring wells. Results are of interest to agencies that regulate drinking water sources or monitor health outcomes from ingestion of drinking water. Lastly, LUR-BME model estimates can be integrated into surface water models for more accurate management of nonpoint sources of nitrogen.

Variability of the gaseous elemental mercury sea-air flux of the Baltic Sea.

PubMed

Kuss, Joachim; Schneider, Bernd

2007-12-01

The importance of the sea as a sink for atmospheric mercury has been established quantitatively through models based on wet and dry deposition data, but little is known about the release of mercury from sea areas. The concentration of elemental mercury (Hg0) in sea surface water and in the marine atmosphere of the Baltic Sea was measured at high spatial resolution in February, April, July, and November 2006. Wind-speed records and the gas-exchange transfer velocity were then used to calculate Hg0 sea-air fluxes on the basis of Hg0 sea-air concentration differences. Our results show that the spatial resolution of the surface water Hg0 data can be significantly improved by continuous measurements of Hg0 in air equilibrated with water instead of quantitative extraction of Hg0 from seawater samples. A spatial and highly seasonal variability of the Hg0 sea-air flux was thus determined. In winter, the flux was low and changed in direction. In summer, a strong emission flux of up to 150 ng m(-2) day(-1) in the central Baltic Sea was recorded. The total emission of Hg0 from the studied area (235000 km2) was 4300 +/- 1600 kg in 2006 and exceeded deposition estimates.

Greenland ice sheet albedo variability and feedback: 2000-2015

NASA Astrophysics Data System (ADS)

Box, J. E.; van As, D.; Fausto, R. S.; Mottram, R.; Langen, P. P.; Steffen, K.

2015-12-01

Absorbed solar irradiance represents the dominant source of surface melt energy for Greenland ice. Surface melting has increased as part of a positive feedback amplifier due to surface darkening. The 16 most recent summers of observations from the NASA MODIS sensor indicate a darkening exceeding 6% in July when most melting occurs. Without the darkening, the increase in surface melting would be roughly half as large. A minority of the albedo decline signal may be from sensor degradation. So, in this study, MOD10A1 and MCD43 albedo products from MODIS are evaluated for sensor degradation and anisotropic reflectance errors. Errors are minimized through calibration to GC-Net and PROMICE Greenland snow and ice ground control data. The seasonal and spatial variability in Greenland snow and ice albedo over a 16 year period is presented, including quantifying changing absorbed solar irradiance and melt enhancement due to albedo feedback using the DMI HIRHAM5 5 km model.

Health risks from large-scale water pollution: trends in Central Asia.

PubMed

Törnqvist, Rebecka; Jarsjö, Jerker; Karimov, Bakhtiyor

2011-02-01

Limited data on the pollution status of spatially extensive water systems constrain health-risk assessments at basin-scales. Using a recipient measurement approach in a terminal water body, we show that agricultural and industrial pollutants in groundwater-surface water systems of the Aral Sea Drainage Basin (covering the main part of Central Asia) yield cumulative health hazards above guideline values in downstream surface waters, due to high concentrations of copper, arsenic, nitrite, and to certain extent dichlorodiphenyltrichloroethane (DDT). Considering these high-impact contaminants, we furthermore perform trend analyses of their upstream spatial-temporal distribution, investigating dominant large-scale spreading mechanisms. The ratio between parent DDT and its degradation products showed that discharges into or depositions onto surface waters are likely to be recent or ongoing. In river water, copper concentrations peak during the spring season, after thawing and snow melt. High spatial variability of arsenic concentrations in river water could reflect its local presence in the top soil of nearby agricultural fields. Overall, groundwaters were associated with much higher health risks than surface waters. Health risks can therefore increase considerably, if the downstream population must switch to groundwater-based drinking water supplies during surface water shortage. Arid regions are generally vulnerable to this problem due to ongoing irrigation expansion and climate changes. Copyright © 2010 Elsevier Ltd. All rights reserved.

A spatially resolved retarding field energy analyzer design suitable for uniformity analysis across the surface of a semiconductor wafer

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

Sharma, S., E-mail: shailesh.sharma6@mail.dcu.ie; National Centre for Plasma Science and Technology, Dublin City University, Glasnevin, Dublin 9; Gahan, D., E-mail: david.gahan@impedans.com

2014-04-15

A novel retarding field energy analyzer design capable of measuring the spatial uniformity of the ion energy and ion flux across the surface of a semiconductor wafer is presented. The design consists of 13 individual, compact-sized, analyzers, all of which are multiplexed and controlled by a single acquisition unit. The analyzers were tested to have less than 2% variability from unit to unit due to tight manufacturing tolerances. The main sensor assembly consists of a 300 mm disk to mimic a semiconductor wafer and the plasma sampling orifices of each sensor are flush with disk surface. This device is placedmore » directly on top of the rf biased electrode, at the wafer location, in an industrial capacitively coupled plasma reactor without the need for any modification to the electrode structure. The ion energy distribution, average ion energy, and average ion flux were measured at the 13 locations over the surface of the powered electrode to determine the degree of spatial nonuniformity. The ion energy and ion flux are shown to vary by approximately 20% and 5%, respectively, across the surface of the electrode for the range of conditions investigated in this study.« less

Urban Heat Island in the city of Bari (Italy) ant its relationship with morphological features

NASA Astrophysics Data System (ADS)

Ceppi, C.; Balena, P.; Loconte, P.; Mancini, F.

2012-04-01

The investigation of an Urban Heat Island (UHI) and its relationship with the wide range of factors able to explain its behavior is a very difficult task: the main trouble is represented by the spatial variability of the urban temperature due to the extreme heterogeneousness of the urban coverage and morphological features. In literature it is known that the local surface temperatures are influenced by the changing characteristics in urban surface and modification of land surface processes affecting the surface energy balance and the shape of boundary layer. The whole processes could lead to distinct urban climates. This work is mainly focused on the mechanisms which are actually connecting the urban morphology with the surface temperature as derived by satellite data provided from the ASTER sensor. Urban morphology could be described by several factors depending on the selected scale of analysis. At the macroscale the UHI is more related to the land-use, environmental context and boundary conditions. At the microscale the surface characteristics, urban density, ratio between green and built areas and, construction and built typology are more involved in addition to the composite indicators such as the Sky View factor and the elevation of the built texture. The case study of the city of Bari is faced. It is a medium sized city in the southern Italy, characterized by the presence of a pervasive waterfront and presence of "lame", a natural erosive furrows shallow that are typical of the Apulia country side. Such ephemeral streams convey the stormwater from the plateau of the hilly Murgia areas to the sea. Moreover, the urban complexity of the city exacerbates the spatial variability of the phenomenon. The first step aim at the investigating of the relationship between the thermal behavior and the above mentioned factors by the construction of a set of homogeneous morphological units. The classification is built both in the urban and rural zone. The second step focuses on the development of a spatial statistical analysis based on qualitative and quantitative indicators able to link the classes of urban morphology with the satellite-based surface temperature. The relationships highlighted by such a spatial analysis can be used to model the urban climate and, consequently, develop a new kind of planning more addressed towards the mitigation of the UHI phenomenon.

Remotely sensed sea surface temperature variability off California during a 'Santa Ana' clearing

NASA Technical Reports Server (NTRS)

Lynn, R. J.; Svejkovsky, J.

1984-01-01

Multichannel atmospheric correction equations for the NOAA 6 proposed by Bernstein (1982) and by McClain (1981) are evaluated by using satellite and in situ data collected over and in the Southern California Bight. The temporal and spatial variation of sea surface temperature over small scales is estimated from the data, and the effect of this variation in matching satellite and in situ data sets is discussed. Changes in the temperature fields between images are examined for diurnal variation and for surface advection of horizontal temperature gradients.

Integration of GIS, Geostatistics, and 3-D Technology to Assess the Spatial Distribution of Soil Moisture

NASA Technical Reports Server (NTRS)

Betts, M.; Tsegaye, T.; Tadesse, W.; Coleman, T. L.; Fahsi, A.

1998-01-01

The spatial and temporal distribution of near surface soil moisture is of fundamental importance to many physical, biological, biogeochemical, and hydrological processes. However, knowledge of these space-time dynamics and the processes which control them remains unclear. The integration of geographic information systems (GIS) and geostatistics together promise a simple mechanism to evaluate and display the spatial and temporal distribution of this vital hydrologic and physical variable. Therefore, this research demonstrates the use of geostatistics and GIS to predict and display soil moisture distribution under vegetated and non-vegetated plots. The research was conducted at the Winfred Thomas Agricultural Experiment Station (WTAES), Hazel Green, Alabama. Soil moisture measurement were done on a 10 by 10 m grid from tall fescue grass (GR), alfalfa (AA), bare rough (BR), and bare smooth (BS) plots. Results indicated that variance associated with soil moisture was higher for vegetated plots than non-vegetated plots. The presence of vegetation in general contributed to the spatial variability of soil moisture. Integration of geostatistics and GIS can improve the productivity of farm lands and the precision of farming.

Spatial prediction of wheat Septoria leaf blotch (Septoria tritici) disease severity in central Ethiopia

USGS Publications Warehouse

Wakie, Tewodros; Kumar, Sunil; Senay, Gabriel; Takele, Abera; Lencho, Alemu

2016-01-01

A number of studies have reported the presence of wheat septoria leaf blotch (Septoria tritici; SLB) disease in Ethiopia. However, the environmental factors associated with SLB disease, and areas under risk of SLB disease, have not been studied. Here, we tested the hypothesis that environmental variables can adequately explain observed SLB disease severity levels in West Shewa, Central Ethiopia. Specifically, we identified 50 environmental variables and assessed their relationships with SLB disease severity. Geographically referenced disease severity data were obtained from the field, and linear regression and Boosted Regression Trees (BRT) modeling approaches were used for developing spatial models. Moderate-resolution imaging spectroradiometer (MODIS) derived vegetation indices and land surface temperature (LST) variables highly influenced SLB model predictions. Soil and topographic variables did not sufficiently explain observed SLB disease severity variation in this study. Our results show that wheat growing areas in Central Ethiopia, including highly productive districts, are at risk of SLB disease. The study demonstrates the integration of field data with modeling approaches such as BRT for predicting the spatial patterns of severity of a pathogenic wheat disease in Central Ethiopia. Our results can aid Ethiopia's wheat disease monitoring efforts, while our methods can be replicated for testing related hypotheses elsewhere.

Variability of streambed hydraulic conductivity in an intermittent stream reach regulated by Vented Dams: A case study

NASA Astrophysics Data System (ADS)

Naganna, Sujay Raghavendra; Deka, Paresh Chandra

2018-07-01

The hydro-geological properties of streambed together with the hydraulic gradients determine the fluxes of water, energy and solutes between the stream and underlying aquifer system. Dam induced sedimentation affects hyporheic processes and alters substrate pore space geometries in the course of progressive stabilization of the sediment layers. Uncertainty in stream-aquifer interactions arises from the inherent complex-nested flow paths and spatio-temporal variability of streambed hydraulic properties. A detailed field investigation of streambed hydraulic conductivity (Ks) using Guelph Permeameter was carried out in an intermittent stream reach of the Pavanje river basin located in the mountainous, forested tract of western ghats of India. The present study reports the spatial and temporal variability of streambed hydraulic conductivity along the stream reach obstructed by two Vented Dams in sequence. Statistical tests such as Levene's and Welch's t-tests were employed to check for various variability measures. The strength of spatial dependence and the presence of spatial autocorrelation among the streambed Ks samples were tested by using Moran's I statistic. The measures of central tendency and dispersion pointed out reasonable spatial variability in Ks distribution throughout the study reach during two consecutive years 2016 and 2017. The streambed was heterogeneous with regard to hydraulic conductivity distribution with high-Ks zones near the backwater areas of the vented dam and low-Ks zones particularly at the tail water section of vented dams. Dam operational strategies were responsible for seasonal fluctuations in sedimentation and modifications to streambed substrate characteristics (such as porosity, grain size, packing etc.), resulting in heterogeneous streambed Ks profiles. The channel downstream of vented dams contained significantly more cohesive deposits of fine sediment due to the overflow of surplus suspended sediment-laden water at low velocity and pressure head. The statistical test results accept the hypothesis of significant spatial variability of streambed Ks but refuse to accept the temporal variations. The deterministic and geo-statistical approaches of spatial interpolation provided virtuous surface maps of streambed Ks distribution.

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

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

Prediction of Ba, Co and Ni for tropical soils using diffuse reflectance spectroscopy and X-ray fluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Arantes Camargo, Livia; Marques Júnior, José; Reynaldo Ferracciú Alleoni, Luís; Tadeu Pereira, Gener; De Bortoli Teixeira, Daniel; Santos Rabelo de Souza Bahia, Angélica

2017-04-01

Environmental impact assessments may be assisted by spatial characterization of potentially toxic elements (PTEs). Diffuse reflectance spectroscopy (DRS) and X-ray fluorescence spectroscopy (XRF) are rapid, non-destructive, low-cost, prediction tools for a simultaneous characterization of different soil attributes. Although low concentrations of PTEs might preclude the observation of spectral features, their contents can be predicted using spectroscopy by exploring the existing relationship between the PTEs and soil attributes with spectral features. This study aimed to evaluate, in three geomorphic surfaces of Oxisols, the capacity for predicting PTEs (Ba, Co, and Ni) and their spatial variability by means of diffuse reflectance spectroscopy (DRS) and X-ray fluorescence spectroscopy (XRF). For that, soil samples were collected from three geomorphic surfaces and analyzed for chemical, physical, and mineralogical properties, and then analyzed in DRS (visible + near infrared - VIS+NIR and medium infrared - MIR) and XRF equipment. PTE prediction models were calibrated using partial least squares regression (PLSR). PTE spatial distribution maps were built using the values calculated by the calibrated models that reached the best accuracy using geostatistics. PTE prediction models were satisfactorily calibrated using MIR DRS for Ba, and Co (residual prediction deviation - RPD > 3.0), Vis DRS for Ni (RPD > 2.0) and FRX for all the studied PTEs (RPD > 1.8). DRS- and XRF-predicted values allowed the characterization and the understanding of spatial variability of the studied PTEs.

SPECIAL - The Savanna Patterns of Energy and Carbon Integrated Across the Landscape campaign

NASA Astrophysics Data System (ADS)

Beringer, J.; Hacker, J.; Hutley, L. B.; Leuning, R.; Arndt, S. K.; Amiri, R.; Bannehr, L.; Cernusak, L. A.; Grover, S.; Hensley, C.; Hocking, D. J.; Isaac, P. R.; Jamali, H.; Kanniah, K.; Livesley, S.; Neininger, B.; Paw U, K.; Sea, W. B.; Straten, D.; Tapper, N. J.; Weinmann, R. A.; Wood, S.; Zegelin, S. J.

2010-12-01

We undertook a significant field campaign (SPECIAL) to examine spatial patterns and processes of land surface-atmosphere exchanges (radiation, heat, moisture, CO2 and other trace gasses) across scales from leaf to landscape scales within Australian savannas. Such savanna ecosystems occur in over 20 countries and cover approximately 15% of the world’s land surface. They consist of a mix of trees and grasses that coexist, but are spatially highly varied in their physical structure, species composition and physiological function. This spatial variation is driven by climate factors (rainfall gradients and seasonality) and disturbances (fire, grazing, herbivory, cyclones). Variations in savanna structure, composition and function (i.e. leaf area and function, stem density, albedo, roughness) interact with the overlying atmosphere directly through exchanges of heat and moisture, which alter the overlying boundary layer. Variability in ecosystem types across the landscape can alter regional to global circulation patterns. Equally, savannas are an important part of the global carbon cycle and can influence the climate through net uptake or release of CO2. We utilized a combination of multiscale measurements including fixed flux towers, aircraft-based flux and regional budget measurements, and satellite remotely sensed quantities to quantify the spatial variability utilizing a continental scale rainfall gradient that resulted in a variety of savanna types. The ultimate goal of our research is to be able to produce robust estimates of regional carbon and water cycles to inform land management policy about how they may respond to future environmental changes.

Characterizing riverbed sediment using high-frequency acoustics 2: scattering signatures of Colorado River bed sediment in Marble and Grand Canyons

USGS Publications Warehouse

Buscombe, Daniel D.; Grams, Paul E.; Kaplinski, Matt A.

2014-01-01

In this, the second of a pair of papers on the statistical signatures of riverbed sediment in high-frequency acoustic backscatter, spatially explicit maps of the stochastic geometries (length- and amplitude-scales) of backscatter are related to patches of riverbed surfaces composed of known sediment types, as determined by geo-referenced underwater video observations. Statistics of backscatter magnitudes alone are found to be poor discriminators between sediment types. However, the variance of the power spectrum, and the intercept and slope from a power-law spectral form (termed the spectral strength and exponent, respectively) successfully discriminate between sediment types. A decision-tree approach was able to classify spatially heterogeneous patches of homogeneous sands, gravels (and sand-gravel mixtures), and cobbles/boulders with 95, 88, and 91% accuracy, respectively. Application to sites outside the calibration, and surveys made at calibration sites at different times, were plausible based on observations from underwater video. Analysis of decision trees built with different training data sets suggested that the spectral exponent was consistently the most important variable in the classification. In the absence of theory concerning how spatially variable sediment surfaces scatter high-frequency sound, the primary advantage of this data-driven approach to classify bed sediment over alternatives is that spectral methods have well understood properties and make no assumptions about the distributional form of the fluctuating component of backscatter over small spatial scales.

Instrumenting an upland research catchment in Canterbury, New Zealand to study controls on variability of soil moisture, shallow groundwater and streamflow

NASA Astrophysics Data System (ADS)

McMillan, Hilary; Srinivasan, Ms

2015-04-01

Hydrologists recognise the importance of vertical drainage and deep flow paths in runoff generation, even in headwater catchments. Both soil and groundwater stores are highly variable over multiple scales, and the distribution of water has a strong control on flow rates and timing. In this study, we instrumented an upland headwater catchment in New Zealand to measure the temporal and spatial variation in unsaturated and saturated-zone responses. In NZ, upland catchments are the source of much of the water used in lowland agriculture, but the hydrology of such catchments and their role in water partitioning, storage and transport is poorly understood. The study area is the Langs Gully catchment in the North Branch of the Waipara River, Canterbury: this catchment was chosen to be representative of the foothills environment, with lightly managed dryland pasture and native Matagouri shrub vegetation cover. Over a period of 16 months we measured continuous soil moisture at 32 locations and near-surface water table (< 2 m) at 14 locations, as well as measuring flow at 3 stream gauges. The distributed measurement sites were located to allow comparisons between North and South facing locations, near-stream versus hillslope locations, and convergent versus divergent hillslopes. We found that temporal variability is strongly controlled by the climatic seasonal cycle, for both soil moisture and water table, and for both the mean and extremes of their distributions. Groundwater is a larger water storage component than soil moisture, and the difference increases with catchment wetness. The spatial standard deviation of both soil moisture and groundwater is larger in winter than in summer. It peaks during rainfall events due to partial saturation of the catchment, and also rises in spring as different locations dry out at different rates. The most important controls on spatial variability are aspect and distance from stream. South-facing and near-stream locations have higher water tables and more, larger soil moisture wetting events. Typical hydrological models do not explicitly account for aspect, but our results suggest that it is an important factor in hillslope runoff generation. Co-measurement of soil moisture and water table level allowed us to identify interrelationships between the two. Locations where water tables peaked closest to the surface had consistently wetter soils and higher water tables. These wetter sites were the same across seasons. However, temporary patterns of strong soil moisture response to summer storms did not correspond to the wetter sites. Total catchment spatial variability is composed of multiple variability sources, and the dominant type is sensitive to those stores that are close to a threshold such as field capacity or saturation. Therefore, we classified spatial variability as 'summer mode' or 'winter mode'. In summer mode, variability is controlled by shallow processes e.g. interactions of water with soils and vegetation. In winter mode, variability is controlled by deeper processes e.g. groundwater movement and bypass flow. Double flow peaks observed during some events show the direct impact of groundwater variability on runoff generation. Our results suggest that emergent catchment behaviour depends on the combination of these multiple, time varying components of variability.

Aquifer configuration and geostructural links control the groundwater quality in thin-bedded carbonate-siliciclastic alternations of the Hainich CZE, central Germany

NASA Astrophysics Data System (ADS)

Kohlhepp, Bernd; Lehmann, Robert; Seeber, Paul; Küsel, Kirsten; Trumbore, Susan E.; Totsche, Kai U.

2017-12-01

The quality of near-surface groundwater reservoirs is controlled, but also threatened, by manifold surface-subsurface interactions. Vulnerability studies typically evaluate the variable interplay of surface factors (land management, infiltration patterns) and subsurface factors (hydrostratigraphy, flow properties) in a thorough way, but disregard the resulting groundwater quality. Conversely, hydrogeochemical case studies that address the chemical evolution of groundwater often lack a comprehensive analysis of the structural buildup. In this study, we aim to reconstruct the actual spatial groundwater quality pattern from a synoptic analysis of the hydrostratigraphy, lithostratigraphy, pedology and land use in the Hainich Critical Zone Exploratory (Hainich CZE). This CZE represents a widely distributed yet scarcely described setting of thin-bedded mixed carbonate-siliciclastic strata in hillslope terrains. At the eastern Hainich low-mountain hillslope, bedrock is mainly formed by alternated marine sedimentary rocks of the Upper Muschelkalk (Middle Triassic) that partly host productive groundwater resources. Spatial patterns of the groundwater quality of a 5.4 km long well transect are derived by principal component analysis and hierarchical cluster analysis. Aquifer stratigraphy and geostructural links were deduced from lithological drill core analysis, mineralogical analysis, geophysical borehole logs and mapping data. Maps of preferential recharge zones and recharge potential were deduced from digital (soil) mapping, soil survey data and field measurements of soil hydraulic conductivities (Ks). By attributing spatially variable surface and subsurface conditions, we were able to reconstruct groundwater quality clusters that reflect the type of land management in their preferential recharge areas, aquifer hydraulic conditions and cross-formational exchange via caprock sinkholes or ascending flow. Generally, the aquifer configuration (spatial arrangement of strata, valley incision/outcrops) and related geostructural links (enhanced recharge areas, karst phenomena) control the role of surface factors (input quality and locations) vs. subsurface factors (water-rock interaction, cross-formational flow) for groundwater quality in the multi-layered aquifer system. Our investigation reveals general properties of alternating sequences in hillslope terrains that are prone to forming multi-layered aquifer systems. This synoptic analysis is fundamental and indispensable for a mechanistic understanding of ecological functioning, sustainable resource management and protection.

The Impact of Meteoroid Streams on the Lunar Atmosphere and Dust Environment During the LADEE Mission

NASA Technical Reports Server (NTRS)

Stubbs, T. J.; Glenar, D. A.; Wang, Y.; Hermalyn, B.; Sarantos, M.; Colaprete, A.; Elphic, R. C.

2015-01-01

The scientific objectives of the Lunar Atmosphere and Dust Environment Explorer (LADEE) mission are: (1) determine the composition of the lunar atmosphere, investigate processes controlling distribution and variability - sources, sinks, and surface interactions; and (2) characterize the lunar exospheric dust environment, measure spatial and temporal variability, and influences on the lunar atmosphere. Impacts on the lunar surface from meteoroid streams encountered by the Earth-Moon system are anticipated to result in enhancements in the both the lunar atmosphere and dust environment. Here we describe the annual meteoroid streams expected to be incident at the Moon during the LADEE mission, and their anticipated effects on the lunar environment.

Albedo Spatial Variability and Causes on the Western Greenland Ice Sheet Percolation Zone

NASA Astrophysics Data System (ADS)

Lewis, G.; Osterberg, E. C.; Hawley, R. L.; Koffman, B. G.; Marshall, H. P.; Birkel, S. D.; Dibb, J. E.

2016-12-01

Many recent studies have concluded that Greenland Ice Sheet (GIS) mass loss has been accelerating over recent decades, but spatial and temporal variations in GIS mass balance remain poorly understood due to a complex relationship among precipitation and temperature changes, increasing melt and runoff, ice discharge, and surface albedo. Satellite measurements from MODerate resolution Imaging Spectroradiometer (MODIS) indicate that albedo has been declining over the past decade, but the cause and extent of GIS albedo change remains poorly constrained by field data. As fresh snow (albedo > 0.85) warms and melts, its albedo decreases due to snow grain growth, promoting solar absorption, higher snowpack temperatures and further melt. However, dark impurities like soot and dust can also significantly reduce snow albedo, even in the dry snow zone. While many regional climate models (e.g. the Regional Atmospheric Climate MOdel - RACMO2) calculate albedo spatial resolutions on the order of 10-30 km, and MODIS averages albedo over 500 m, surface features like sastrugi can affect albedo on much smaller scales. Here we assess the relative importance of grain size and shape vs. impurity concentrations on albedo in the western GIS percolation zone. We collected broadband albedo measurements (300-2500 nm at 3-8 nm resolution) at 35 locations using an ASD FieldSpec4 spectroradiometer to simultaneously quantify radiative fluxes and spectral reflectance. Measurements were collected on 10 x 10 m, 1 x 1 km, 5 x 5 km, and 10 x 10 km grids to determine the spatial variability of albedo as part of the 850-km Greenland Traverse for Accumulation and Climate Studies (GreenTrACS) traverse from Raven/Dye 2 to Summit. Additionally, we collected shallow (0-50 cm) snow pit samples every 5 cm at ASD measurement sites to quantify black carbon and mineral dust concentrations and size distributions using a Single Particle Soot Photometer and Coulter Counter, respectively. Preliminary results indicate larger albedo variability in the infrared than visible and near infrared. We compare our in situ field measurements with co-located albedo data from airplanes, satellites, and climate models, and discuss implications for GIS surface mass balance.

Improving Evapotranspiration Estimates Using Multi-Platform Remote Sensing

NASA Astrophysics Data System (ADS)

Knipper, Kyle; Hogue, Terri; Franz, Kristie; Scott, Russell

2016-04-01

Understanding the linkages between energy and water cycles through evapotranspiration (ET) is uniquely challenging given its dependence on a range of climatological parameters and surface/atmospheric heterogeneity. A number of methods have been developed to estimate ET either from primarily remote-sensing observations, in-situ measurements, or a combination of the two. However, the scale of many of these methods may be too large to provide needed information about the spatial and temporal variability of ET that can occur over regions with acute or chronic land cover change and precipitation driven fluxes. The current study aims to improve the spatial and temporal variability of ET utilizing only satellite-based observations by incorporating a potential evapotranspiration (PET) methodology with satellite-based down-scaled soil moisture estimates in southern Arizona, USA. Initially, soil moisture estimates from AMSR2 and SMOS are downscaled to 1km through a triangular relationship between MODIS land surface temperature (MYD11A1), vegetation indices (MOD13Q1/MYD13Q1), and brightness temperature. Downscaled soil moisture values are then used to scale PET to actual ET (AET) at a daily, 1km resolution. Derived AET estimates are compared to observed flux tower estimates, the North American Land Data Assimilation System (NLDAS) model output (i.e. Variable Infiltration Capacity (VIC) Macroscale Hydrologic Model, Mosiac Model, and Noah Model simulations), the Operational Simplified Surface Energy Balance Model (SSEBop), and a calibrated empirical ET model created specifically for the region. Preliminary results indicate a strong increase in correlation when incorporating the downscaling technique to original AMSR2 and SMOS soil moisture values, with the added benefit of being able to decipher small scale heterogeneity in soil moisture (riparian versus desert grassland). AET results show strong correlations with relatively low error and bias when compared to flux tower estimates. In addition, AET results show improved bias to those reported by SSEBop, with similar correlations and errors when compared to the empirical ET model. Spatial patterns of estimated AET display patterns representative of the basin's elevation and vegetation characteristics, with improved spatial resolution and temporal heterogeneity when compared to previous models.

Photometric variability in earthshine observations.

PubMed

Langford, Sally V; Wyithe, J Stuart B; Turner, Edwin L

2009-04-01

The identification of an extrasolar planet as Earth-like will depend on the detection of atmospheric signatures or surface non-uniformities. In this paper we present spatially unresolved flux light curves of Earth for the purpose of studying a prototype extrasolar terrestrial planet. Our monitoring of the photometric variability of earthshine revealed changes of up to 23% per hour in the brightness of Earth's scattered light at around 600 nm, due to the removal of specular reflection from the view of the Moon. This variability is accompanied by reddening of the spectrum and results from a change in surface properties across the continental boundary between the Indian Ocean and Africa's east coast. Our results based on earthshine monitoring indicate that specular reflection should provide a useful tool in determining the presence of liquid water on extrasolar planets via photometric observations.

The NASA Marshall Space Flight Center Earth Global Reference Atmospheric Model-2010 Version

NASA Technical Reports Server (NTRS)

Leslie, F. W.; Justus, C. G.

2011-01-01

Reference or standard atmospheric models have long been used for design and mission planning of various aerospace systems. The NASA Marshall Space Flight Center Global Reference Atmospheric Model was developed in response to the need for a design reference atmosphere that provides complete global geographical variability and complete altitude coverage (surface to orbital altitudes), as well as complete seasonal and monthly variability of the thermodynamic variables and wind components. In addition to providing the geographical, height, and monthly variation of the mean atmospheric state, it includes the ability to simulate spatial and temporal perturbations.

Review of literature on the finite-element solution of the equations of two-dimensional surface-water flow in the horizontal plane

USGS Publications Warehouse

Lee, Jonathan K.; Froehlich, David C.

1987-01-01

Published literature on the application of the finite-element method to solving the equations of two-dimensional surface-water flow in the horizontal plane is reviewed in this report. The finite-element method is ideally suited to modeling two-dimensional flow over complex topography with spatially variable resistance. A two-dimensional finite-element surface-water flow model with depth and vertically averaged velocity components as dependent variables allows the user great flexibility in defining geometric features such as the boundaries of a water body, channels, islands, dikes, and embankments. The following topics are reviewed in this report: alternative formulations of the equations of two-dimensional surface-water flow in the horizontal plane; basic concepts of the finite-element method; discretization of the flow domain and representation of the dependent flow variables; treatment of boundary conditions; discretization of the time domain; methods for modeling bottom, surface, and lateral stresses; approaches to solving systems of nonlinear equations; techniques for solving systems of linear equations; finite-element alternatives to Galerkin's method of weighted residuals; techniques of model validation; and preparation of model input data. References are listed in the final chapter.

Monitoring global snow cover

NASA Technical Reports Server (NTRS)

Armstrong, Richard; Hardman, Molly

1991-01-01

A snow model that supports the daily, operational analysis of global snow depth and age has been developed. It provides improved spatial interpolation of surface reports by incorporating digital elevation data, and by the application of regionalized variables (kriging) through the use of a global snow depth climatology. Where surface observations are inadequate, the model applies satellite remote sensing. Techniques for extrapolation into data-void mountain areas and a procedure to compute snow melt are also contained in the model.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Mishra, U.; Riley, W. J.

2015-01-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ~ 0.55-0.63). Current ESMs operate at coarse spatial scales (50-100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Mishra, U.; Riley, W. J.

2015-07-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data set with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ∼ 0.55-0.63). Current ESMs operate at coarse spatial scales (50-100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

DOE PAGES

Mishra, U.; Riley, W. J.

2015-07-02

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data setmore » with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

DOE PAGES

Mishra, U.; Riley, W. J.

2015-01-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonablemore » fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ~ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

The Influence of Midlatitude Ocean-Atmosphere Coupling on the Low-Frequency Variability of a GCM. Part I: No Tropical SST Forcing*.

NASA Astrophysics Data System (ADS)

Bladé, Ileana

1997-08-01

This study examines the extent to which the thermodynamic interactions between the midlatitude atmosphere and the underlying oceanic mixed layer contribute to the low-frequency atmospheric variability. A general circulation model, run under perpetual northern winter conditions, is coupled to a motionless constant-depth mixed layer in midlatitudes, while elsewhere the sea surface temperature (SST) is kept fixed; interannual tropical SST forcing is not included. It is found that coupling does not modify the spatial organization of the variability. The influence of coupling is manifested as a slight reddening of the spectrum of 500-mb geopotential height and a significant enhancement of the lower-tropospheric thermal variance over the oceans at very low frequencies by virtue of the mixed-layer adjustment to surface air temperature variations that occurs on those timescales. This adjustment effectively reduces the thermal damping of the atmosphere associated with surface heat fluxes (or negative oceanic feedback), thus increasing the thermal variance and the persistence of circulation anomalies.In studying the covariability between ocean and atmosphere it is found that the dominant mode of natural atmospheric variability is coupled to the leading mode of SST in each ocean, with the atmosphere leading the ocean by about one month. The cross-correlation function between oceanic and atmospheric anomalies is strongly asymmetric about zero lag. The SST structures are consistent with direct forcing by the anomalous heat fluxes implied by the concurrent surface air temperature and wind fluctuations. Additionally, composites based on large amplitude SST anomaly events contain no evidence of direct driving of atmospheric perturbations by these SST anomalies. Thus, in terms of the spatial organization of the covariability and the evolution of the coupled system from one regime to another, large-scale air-sea interaction in the model is characterized by one-way atmospheric forcing of the mixed layer.These results are qualitatively consistent with those from an earlier idealized study. They imply a subtle but fundamental role for the midlatitude oceans as stabilizing rather than directly generating atmospheric anomalies. It is argued that this scenario is relevant to the dynamics of extratropical atmosphere-ocean coupling on intraseasonal timescales at least: the model is able to qualitatively reproduce the temporal and spatial characteristics of the observed dominant patterns of interaction on these timescales, particularly over the Atlantic.

Interannual variability of ammonia concentrations over the United States: sources and implications

NASA Astrophysics Data System (ADS)

Schiferl, Luke D.; Heald, Colette L.; Van Damme, Martin; Clarisse, Lieven; Clerbaux, Cathy; Coheur, Pierre-François; Nowak, John B.; Neuman, J. Andrew; Herndon, Scott C.; Roscioli, Joseph R.; Eilerman, Scott J.

2016-09-01

The variability of atmospheric ammonia (NH3), emitted largely from agricultural sources, is an important factor when considering how inorganic fine particulate matter (PM2.5) concentrations and nitrogen cycling are changing over the United States. This study combines new observations of ammonia concentration from the surface, aboard aircraft, and retrieved by satellite to both evaluate the simulation of ammonia in a chemical transport model (GEOS-Chem) and identify which processes control the variability of these concentrations over a 5-year period (2008-2012). We find that the model generally underrepresents the ammonia concentration near large source regions (by 26 % at surface sites) and fails to reproduce the extent of interannual variability observed at the surface during the summer (JJA). Variability in the base simulation surface ammonia concentration is dominated by meteorology (64 %) as compared to reductions in SO2 and NOx emissions imposed by regulation (32 %) over this period. Introduction of year-to-year varying ammonia emissions based on animal population, fertilizer application, and meteorologically driven volatilization does not substantially improve the model comparison with observed ammonia concentrations, and these ammonia emissions changes have little effect on the simulated ammonia concentration variability compared to those caused by the variability of meteorology and acid-precursor emissions. There is also little effect on the PM2.5 concentration due to ammonia emissions variability in the summer when gas-phase changes are favored, but variability in wintertime emissions, as well as in early spring and late fall, will have a larger impact on PM2.5 formation. This work highlights the need for continued improvement in both satellite-based and in situ ammonia measurements to better constrain the magnitude and impacts of spatial and temporal variability in ammonia concentrations.

Multiscale analysis of surface soil moisture dynamics in a mesoscale catchment utilizing an integrated ecohydrological model

NASA Astrophysics Data System (ADS)

Korres, W.; Reichenau, T. G.; Schneider, K.

2012-12-01

Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture, influencing the partitioning of solar energy into latent and sensible heat flux as well as the partitioning of precipitation into runoff and percolation. Numerous studies have shown that in addition to natural factors (rainfall, soil, topography etc.) agricultural management is one of the key drivers for spatio-temporal patterns of soil moisture in agricultural landscapes. Interactions between plant growth, soil hydrology and soil nitrogen transformation processes are modeled by using a dynamically coupled modeling approach. The process-based ecohydrological model components of the integrated decision support system DANUBIA are used to identify the important processes and feedbacks determining soil moisture patterns in agroecosystems. Integrative validation of plant growth and surface soil moisture dynamics serves as a basis for a spatially distributed modeling analysis of surface soil moisture patterns in the northern part of the Rur catchment (1100 sq km), Western Germany. An extensive three year dataset (2007-2009) of surface soil moisture-, plant- (LAI, organ specific biomass and N) and soil- (texture, N, C) measurements was collected. Plant measurements were carried out biweekly for winter wheat, maize, and sugar beet during the growing season. Soil moisture was measured with three FDR soil moisture stations. Meteorological data was measured with an eddy flux station. The results of the model validation showed a very good agreement between the modeled plant parameters (biomass, green LAI) and the measured parameters with values between 0.84 and 0.98 (Willmotts index of agreement). The modeled surface soil moisture (0 - 20 cm) showed also a very favorable agreement with the measurements for winter wheat and sugar beet with an RMSE between 1.68 and 3.45 Vol.-%. For maize, the RMSE was less favorable particularly in the 1.5 months prior to harvest. The modeled soil moisture remained in contrast to the measurements very responsive to precipitation with high soil moisture after precipitation events. This behavior indicates that the soil properties might have changed due to the formation of a surface crust or seal towards the end of the growing season. Spatial soil moisture patterns were investigated using a grid resolution of 150 meter. Spatial autocorrelation was computed on a daily basis using patterns of soil texture as well as transpiration and precipitation indices as co-variables. Spatial patterns of surface soil moisture are mostly determined by the structure of the soil properties (soil type) during winter, early growing season and after harvest of all crops. Later in the growing season, after establishment of a closed canopy the dependence of the soil moisture patterns on soil texture patterns becomes smaller and diminishes quickly after precipitation events, due to differences of the transpiration rate of the different crops. When changing the spatial scale of the analysis, the highest autocorrelation values can be found on a grid cell size between 450 and 1200 meters. Thus, small scale variability of transpiration induced by the land use pattern almost averages out, leaving the larger scale structure of soil properties to explain the soil moisture patterns.

Monitoring the dynamics of surface water fraction from MODIS time series in a Mediterranean environment

NASA Astrophysics Data System (ADS)

Li, Linlin; Vrieling, Anton; Skidmore, Andrew; Wang, Tiejun; Turak, Eren

2018-04-01

Detailed spatial information of changes in surface water extent is needed for water management and biodiversity conservation, particularly in drier parts of the globe where small, temporally-variant wetlands prevail. Although global surface water histories are now generated from 30 m Landsat data, for many locations they contain large temporal gaps particularly for longer periods (>10 years) due to revisit intervals and cloud cover. Daily Moderate Resolution Imaging Spectrometer (MODIS) imagery has potential to fill such gaps, but its relatively coarse spatial resolution may not detect small water bodies, which can be of great ecological importance. To address this problem, this study proposes and tests options for estimating the surface water fraction from MODIS 16-day 500 m Bidirectional Reflectance Distribution Function (BRDF) corrected surface reflectance image composites. The spatial extent of two Landsat tiles over Spain were selected as test areas. We obtained a 500 m reference dataset on surface water fraction by spatially aggregating 30 m binary water masks obtained from the Landsat-derived C-version of Function of Mask (CFmask), which themselves were evaluated against high-resolution Google Earth imagery. Twelve regression tree models were developed with two approaches, Random Forest and Cubist, using spectral metrics derived from MODIS data and topographic parameters generated from a 30 m spatial resolution digital elevation model. Results showed that accuracies were higher when we included annual summary statistics of the spectral metrics as predictor variables. Models trained on a single Landsat tile were ineffective in mapping surface water in the other tile, but global models trained with environmental conditions from both tiles can provide accurate results for both study areas. We achieved the highest accuracy with Cubist global model (R2 = 0.91, RMSE = 11.05%, MAE = 7.67%). Our method was not only effective for mapping permanent water fraction, but also in accurately capturing temporal fluctuations of surface water. Based on this good performance, we produced surface water fraction maps at 16-day interval for the 2000-2015 MODIS archive. Our approach is promising for monitoring surface water fraction at high frequency time intervals over much larger regions provided that training data are collected across the spatial domain for which the model will be applied.

Seasonal and nonseasonal variability of satellite-derived chlorophyll and colored dissolved organic matter concentration in the California Current

NASA Astrophysics Data System (ADS)

Kahru, Mati; Mitchell, B. Greg

2001-02-01

Time series of surface chlorophyll a concentration (Chl) and colored dissolved organic matter (CDOM) derived from the Ocean Color and Temperature Sensor and Sea-Viewing Wide Field-of-View Sensor were evaluated for the California Current area using regional algorithms. Satellite data composited for 8-day periods provide the ability to describe large-scale changes in surface parameters. These changes are difficult to detect based on in situ observations alone that suffer from undersampling the large temporal and spatial variability, especially in Chl. We detected no significant bias in satellite Chl estimates compared with ship-based measurements. The variability in CDOM concentration was significantly smaller than that in Chl, both spatially and temporally. While being subject to large interannual and short-term variations, offshore waters (100-1000 km from the shore) have an annual cycle of Chl and CDOM with a maximum in winter-spring (December-March) and a minimum in late summer. For inshore waters the maximum is more likely in spring (April-May). We detect significant increase in both Chl and CDOM off central and southern California during the La Niña year of 1999. The trend of increasing Chl and CDOM from October 1996 to June 2000 is statistically significant in many areas.

Alternating activation is related to fatigue in lumbar muscles during sustained sitting.

PubMed

Ringheim, Inge; Indahl, Aage; Roeleveld, Karin

2014-06-01

The aim of this study was to investigate the relation between variability in muscle activity and fatigue during a sustained low level contraction in the lumbar muscles. Twenty-five healthy participants (13 men 12 women) performed a 30min sitting task with 5 degrees inclination of the trunk. Surface electromyographic (EMG) signals were recorded bilaterally from the lumbar muscles with 2 high density surface EMG grids of 9×14 electrodes. Median frequency (MDF) decrease, amplitude (RMS) increase and the rating of perceived exertion (RPE) were used as fatigue indices. Alternating activation and spatial and temporal variability were computed and relations with the fatigue indices were explored. During sitting, the mono- and bipolar RMS slightly increased while the MDF remained unchanged indicating no systematic muscle fatigue, although the average RPE increased from 6 to 13 on a scale ranging between 6 and 20. Higher frequency of alternating activation between the left and right side was associated with increased RPE (p=0.03) and decreased MDF (p=0.05). A tendency in the same direction was seen between increased spatial and temporal variation within the grids and increased RPE and decreased MDF. Present findings provide evidence for a relationship between variability in muscle activity and fatigue. Copyright © 2014 Elsevier Ltd. All rights reserved.

An Extended Kriging Method to Interpolate Near-Surface Soil Moisture Data Measured by Wireless Sensor Networks

PubMed Central

Zhang, Jialin; Li, Xiuhong; Yang, Rongjin; Liu, Qiang; Zhao, Long; Dou, Baocheng

2017-01-01

In the practice of interpolating near-surface soil moisture measured by a wireless sensor network (WSN) grid, traditional Kriging methods with auxiliary variables, such as Co-kriging and Kriging with external drift (KED), cannot achieve satisfactory results because of the heterogeneity of soil moisture and its low correlation with the auxiliary variables. This study developed an Extended Kriging method to interpolate with the aid of remote sensing images. The underlying idea is to extend the traditional Kriging by introducing spectral variables, and operating on spatial and spectral combined space. The algorithm has been applied to WSN-measured soil moisture data in HiWATER campaign to generate daily maps from 10 June to 15 July 2012. For comparison, three traditional Kriging methods are applied: Ordinary Kriging (OK), which used WSN data only, Co-kriging and KED, both of which integrated remote sensing data as covariate. Visual inspections indicate that the result from Extended Kriging shows more spatial details than that of OK, Co-kriging, and KED. The Root Mean Square Error (RMSE) of Extended Kriging was found to be the smallest among the four interpolation results. This indicates that the proposed method has advantages in combining remote sensing information and ground measurements in soil moisture interpolation. PMID:28617351

An eleven-year record of mass balance of Brewster Glacier, New Zealand, determined using a geostatistical approach

NASA Astrophysics Data System (ADS)

Cullen, N. J.; Anderson, B.; Sirguey, P. J.; Stumm, D.; Mackintosh, A.; Conway, J. P.; Horgan, H. J.; Dadic, R.; Fitzsimons, S.; Lorrey, A.

2016-12-01

Recognizing the scarcity of glacier mass balance data in the Southern Hemisphere, a mass balance measurement program was started at Brewster Glacier in 2004. Evolution of the measurement regime over the 11 years of data recorded means there are differences in the spatial density of data obtained. To ensure the temporal integrity of the dataset a new, geostatistical approach has been developed to calculate mass balance. Spatial co-variance between elevation and snow depth has enabled a digital elevation model to be used in a co-kriging approach to develop a snow depth index (SDI). By capturing the observed spatial variability in snow depth, the SDI is a more reliable predictor than elevation and is used to adjust each year of measurements consistently despite variability in sampling spatial density. The SDI also resolves the spatial structure of summer balance better than elevation. Co-kriging is used again to spatially interpolate a derived mean summer balance index using SDI as a co-variate, which yields a spatial predictor for summer balance. A similar approach is also used to create a predictor for annual balance, which allows us to revisit years where summer balance was not obtained. The average glacier-wide surface winter, summer and annual mass balances over the period 2005-2015 are 2484, -2586, and -102 mm w.e., respectively, with changes in summer balance explaining most of the variability in annual balance. On the whole, there is good agreement between our ELA and AAR values and those derived from the end-of-summer snowline (EOSS) program, though discrepancies in some years cannot be fully accounted for. A mass balance map of Brewster Glacier in an equilibrium state, which by definition has a glacier-wide mass balance equal to zero (a balanced-budget), is used to calculate values of ELA (1923 ±25 m) and AAR (0.40) representative of the observational period. The relationships between mass balance and ELA/AAR are explored, demonstrating they are mostly linear. On average, the mass balance gradients are found to be equal to 14.5 and 7.4 mm we m-1 in the ablation and accumulation zones, respectively. However, there is considerable variability in the gradients from year to year, as well as variability between different elevation bands. The largest variability in the mass balance gradient is observed in the ablation zone.

Evidence for self-organization in determining spatial patterns of stream nutrients, despite primacy of the geomorphic template

PubMed Central

Dong, Xiaoli; Grimm, Nancy B.

2017-01-01

Nutrients in freshwater ecosystems are highly variable in space and time. Nevertheless, the variety of processes contributing to nutrient patchiness, and the wide range of spatial and temporal scales at which these processes operate, obfuscate how this spatial heterogeneity is generated. Here, we describe the spatial structure of stream nutrient concentration, quantify the relative importance of the physical template and biological processes, and detect and evaluate the role of self-organization in driving such patterns. We examined nutrient spatial patterns in Sycamore Creek, an intermittent desert stream in Arizona that experienced an ecosystem regime shift [from a gravel/algae-dominated to a vascular plant-dominated (hereafter, “wetland”) system] in 2000 when cattle grazing ceased. We conducted high-resolution nutrient surveys in surface water along a 10-km stream reach over four visits spanning 18 y (1995–2013) that represent different successional stages and prewetland stage vs. postwetland state. As expected, groundwater upwelling had a major influence on nutrient spatial patterns. However, self-organization realized by the mechanism of spatial feedbacks also was significant and intensified over ecosystem succession, as a resource (nitrogen) became increasingly limiting. By late succession, the effects of internal spatial feedbacks and groundwater upwelling were approximately equal in magnitude. Wetland establishment influenced nutrient spatial patterns only indirectly, by modifying the extent of surface water/groundwater exchange. This study illustrates that multiple mechanisms interact in a dynamic way to create spatial heterogeneity in riverine ecosystems, and provides a means to detect spatial self-organization against physical template heterogeneity as a dominant driver of spatial patterns. PMID:28559326

Evidence for self-organization in determining spatial patterns of stream nutrients, despite primacy of the geomorphic template.

PubMed

Dong, Xiaoli; Ruhí, Albert; Grimm, Nancy B

2017-06-13

Nutrients in freshwater ecosystems are highly variable in space and time. Nevertheless, the variety of processes contributing to nutrient patchiness, and the wide range of spatial and temporal scales at which these processes operate, obfuscate how this spatial heterogeneity is generated. Here, we describe the spatial structure of stream nutrient concentration, quantify the relative importance of the physical template and biological processes, and detect and evaluate the role of self-organization in driving such patterns. We examined nutrient spatial patterns in Sycamore Creek, an intermittent desert stream in Arizona that experienced an ecosystem regime shift [from a gravel/algae-dominated to a vascular plant-dominated (hereafter, "wetland") system] in 2000 when cattle grazing ceased. We conducted high-resolution nutrient surveys in surface water along a 10-km stream reach over four visits spanning 18 y (1995-2013) that represent different successional stages and prewetland stage vs. postwetland state. As expected, groundwater upwelling had a major influence on nutrient spatial patterns. However, self-organization realized by the mechanism of spatial feedbacks also was significant and intensified over ecosystem succession, as a resource (nitrogen) became increasingly limiting. By late succession, the effects of internal spatial feedbacks and groundwater upwelling were approximately equal in magnitude. Wetland establishment influenced nutrient spatial patterns only indirectly, by modifying the extent of surface water/groundwater exchange. This study illustrates that multiple mechanisms interact in a dynamic way to create spatial heterogeneity in riverine ecosystems, and provides a means to detect spatial self-organization against physical template heterogeneity as a dominant driver of spatial patterns.

The land-use legacy effect: Towards a mechanistic understanding of time-lagged water quality responses to land use/cover.

PubMed

Martin, Sherry L; Hayes, Daniel B; Kendall, Anthony D; Hyndman, David W

2017-02-01

Numerous studies have linked land use/land cover (LULC) to aquatic ecosystem responses, however only a few have included the dynamics of changing LULC in their analysis. In this study, we explicitly recognize changing LULC by linking mechanistic groundwater flow and travel time models to a historical time series of LULC, creating a land-use legacy map. We then illustrate the utility of legacy maps to explore relationships between dynamic LULC and lake water chemistry. We tested two main concepts about mechanisms linking LULC and lake water chemistry: groundwater pathways are an important mechanism driving legacy effects; and, LULC over multiple spatial scales is more closely related to lake chemistry than LULC over a single spatial scale. We applied statistical models to twelve water chemistry variables, ranging from nutrients to relatively conservative ions, to better understand the roles of biogeochemical reactivity and solubility on connections between LULC and aquatic ecosystem response. Our study illustrates how different areas can have long groundwater pathways that represent different LULC than what can be seen on the landscape today. These groundwater pathways delay the arrival of nutrients and other water quality constituents, thus creating a legacy of historic land uses that eventually reaches surface water. We find that: 1) several water chemistry variables are best fit by legacy LULC while others have a stronger link to current LULC, and 2) single spatial scales of LULC analysis performed worse for most variables. Our novel combination of temporal and spatial scales was the best overall model fit for most variables, including SRP where this model explained 54% of the variation. We show that it is important to explicitly account for temporal and spatial context when linking LULC to ecosystem response. Copyright © 2016. Published by Elsevier B.V.

What spatial scales are believable for climate model projections of sea surface temperature?

NASA Astrophysics Data System (ADS)

Kwiatkowski, Lester; Halloran, Paul R.; Mumby, Peter J.; Stephenson, David B.

2014-09-01

Earth system models (ESMs) provide high resolution simulations of variables such as sea surface temperature (SST) that are often used in off-line biological impact models. Coral reef modellers have used such model outputs extensively to project both regional and global changes to coral growth and bleaching frequency. We assess model skill at capturing sub-regional climatologies and patterns of historical warming. This study uses an established wavelet-based spatial comparison technique to assess the skill of the coupled model intercomparison project phase 5 models to capture spatial SST patterns in coral regions. We show that models typically have medium to high skill at capturing climatological spatial patterns of SSTs within key coral regions, with model skill typically improving at larger spatial scales (≥4°). However models have much lower skill at modelling historical warming patters and are shown to often perform no better than chance at regional scales (e.g. Southeast Asian) and worse than chance at finer scales (<8°). Our findings suggest that output from current generation ESMs is not yet suitable for making sub-regional projections of change in coral bleaching frequency and other marine processes linked to SST warming.

Risk assessment of groundwater level variability using variable Kriging methods

NASA Astrophysics Data System (ADS)

Spanoudaki, Katerina; Kampanis, Nikolaos A.

2015-04-01

Assessment of the water table level spatial variability in aquifers provides useful information regarding optimal groundwater management. This information becomes more important in basins where the water table level has fallen significantly. The spatial variability of the water table level in this work is estimated based on hydraulic head measured during the wet period of the hydrological year 2007-2008, in a sparsely monitored basin in Crete, Greece, which is of high socioeconomic and agricultural interest. Three Kriging-based methodologies are elaborated in Matlab environment to estimate the spatial variability of the water table level in the basin. The first methodology is based on the Ordinary Kriging approach, the second involves auxiliary information from a Digital Elevation Model in terms of Residual Kriging and the third methodology calculates the probability of the groundwater level to fall below a predefined minimum value that could cause significant problems in groundwater resources availability, by means of Indicator Kriging. The Box-Cox methodology is applied to normalize both the data and the residuals for improved prediction results. In addition, various classical variogram models are applied to determine the spatial dependence of the measurements. The Matérn model proves to be the optimal, which in combination with Kriging methodologies provides the most accurate cross validation estimations. Groundwater level and probability maps are constructed to examine the spatial variability of the groundwater level in the basin and the associated risk that certain locations exhibit regarding a predefined minimum value that has been set for the sustainability of the basin's groundwater resources. Acknowledgement The work presented in this paper has been funded by the Greek State Scholarships Foundation (IKY), Fellowships of Excellence for Postdoctoral Studies (Siemens Program), 'A simulation-optimization model for assessing the best practices for the protection of surface water and groundwater in the coastal zone', (2013 - 2015). Varouchakis, E. A. and D. T. Hristopulos (2013). "Improvement of groundwater level prediction in sparsely gauged basins using physical laws and local geographic features as auxiliary variables." Advances in Water Resources 52: 34-49. Kitanidis, P. K. (1997). Introduction to geostatistics, Cambridge: University Press.

Characterization of the spatial distribution of porosity in the eogenetic karst Miami Limestone using ground penetrating radar

NASA Astrophysics Data System (ADS)

Mount, G. J.; Comas, X.; Wright, W. J.; McClellan, M. D.

2014-12-01

Hydrogeologic characterization of karst limestone aquifers is difficult due to the variability in the spatial distribution of porosity and dissolution features. Typical methods for aquifer investigation, such as drilling and pump testing, are limited by the scale or spatial extent of the measurement. Hydrogeophysical techniques such as ground penetrating radar (GPR) can provide indirect measurements of aquifer properties and be expanded spatially beyond typical point measures. This investigation used a multiscale approach to identify and quantify porosity distribution in the Miami Limestone, the lithostratigraphic unit that composes the uppermost portions of the Biscayne Aquifer in Miami Dade County, Florida. At the meter scale, laboratory measures of porosity and dielectric permittivity were made on blocks of Miami Limestone using zero offset GPR, laboratory and digital image techniques. Results show good correspondence between GPR and analytical porosity estimates and show variability between 22 and 66 %. GPR measurements at the field scale 10-1000 m investigated the bulk porosity of the limestone based on the assumption that a directly measured water table would remain at a consistent depth in the GPR reflection record. Porosity variability determined from the changes in the depth to water table resulted in porosity values that ranged from 33 to 61 %, with the greatest porosity variability being attributed to the presence of dissolution features. At the larger field scales, 100 - 1000 m, fitting of hyperbolic diffractions in GPR common offsets determined the vertical and horizontal variability of porosity in the saturated subsurface. Results indicate that porosity can vary between 23 and 41 %, and delineate potential areas of enhanced recharge or groundwater / surface water interactions. This study shows porosity variability in the Miami Limestone can range from 22 to 66 % within 1.5 m distances, with areas of high macroporosity or karst dissolution features occupying the higher end of the range. Spatial variability in porosity distribution may affect ground water recharge, allowing zones of high porosity and thus enhanced infiltration to concentrate contaminants into the aquifer and may play a role in small and regional scale aquifer models.

Spatial Variability of Factors Influencing the Distribution of Triclosan in Sediments and Water of an Urbanized Estuarine Embayment

EPA Science Inventory

Triclosan (TCS) is a broad spectrum anti-microbial compound added to many consumer and personal care products. TCS enters water bodies primarily through wastewater treatment plant (WWTP) effluent and may be introduced by combined sewer overflows or surface water runoff. In estu...

Variability of furrow infiltration and irrigation performance in a macroporous soil

USDA-ARS?s Scientific Manuscript database

The study of spatial and temporal variations of infiltration in furrows is essential for the design and management of surface irrigation. A key difficulty in quantifying the process is that infiltration is dependent on the depth of flow, which varies along a furrow and with time. An additional diffi...

Spatial and Temporal Variability of Cross-Basin Acoustic Ray Paths

DTIC Science & Technology

1990-12-01

have greatly benefited from his guidance and the numerous discussions we have had. VI I. INTRODUCTION A. THE GREENHOUSE EFFECT Investigation of potential...from the earth’s surface. Increased levels of these gases in the atmosphere will thus raise the earth’s temperature, i.e., the " greenhouse effect ". Almost

Response surface models of subsoil K concentration for loess over till soils in Missouri

USDA-ARS?s Scientific Manuscript database

Crop uptake of potassium (K) has demonstrated sensitivity to subsoil variation in K content. This fact has not been sufficiently considered in K management strategies in part due to logistical difficulties in sampling spatially variable subsoil K. We propose a simplified soil factorial model, a resp...

A neutral model of low-severity fire regimes

Treesearch

Don McKenzie; Amy E. Hessl

2008-01-01

Climate, topography, fuel loadings, and human activities all affect spatial and temporal patterns of fire occurrence. Because fire occurrence is a stochastic process, an understanding of baseline variability is necessary in order to identify constraints on surface fire regimes. With a suitable null, or neutral, model, characteristics of natural fire regimes estimated...

Spatial and temporal variations of particulate organic carbon in the Yellow-Bohai Sea over 2002-2016.

PubMed

Fan, Hang; Wang, Xiujun; Zhang, Haibo; Yu, Zhitong

2018-05-22

The Yellow-Bohai Sea (YBS) is a typical marginal sea in the Northwest Pacific Ocean; however, little is known about the dynamics of particulate organic carbon (POC) and underlying mechanisms. Here, we analyze the spatial and temporal variations of surface POC derived from MODIS-Aqua during 2002-2016. Overall, POC is higher in the Bohai Sea (315-588 mg m -3 ) than in the Yellow Sea (181-492 mg m -3 ), and higher in the nearshore than in the offshore. Surface POC is highest in spring in the YBS, and lowest in winter (summer) in the Bohai Sea (the Yellow Sea). The spatial and seasonal patterns of POC are due to combined influences of primary productivity, water exchange, sediment resuspension and terrestrial inputs. Surface POC shows an overall decreasing trend prior to 2012 followed by an upward trend until 2015 in the YBS, which is almost opposite to chlorophyll; the decrease (increase) may result from strengthened (weakened) water exchange with the East China Sea through the Yellow Sea Warm Current. Declined terrestrial runoff is also partly responsible for the decrease prior to 2012. Our study suggests that water exchange and sediment resuspension are dominant factors regulating the spatial and temporal variability of POC in the YBS.

Modeling Coupled Movement of Water, Vapor, and Energy in Soils and at the Soil-Atmosphere Interface Using HYDRUS

NASA Astrophysics Data System (ADS)

Simunek, Jiri; Brunetti, Giuseppe; Saito, Hirotaka; Bristow, Keith

2017-04-01

Mass and energy fluxes in the subsurface are closely coupled and cannot be evaluated without considering their mutual interactions. However, only a few numerical models consider coupled water, vapor and energy transport in both the subsurface and at the soil-atmosphere interface. While hydrological and thermal processes in the subsurface are commonly implemented in existing models, which often consider both isothermally and thermally induced water and vapor flow, the interactions at the soil-atmosphere interface are often simplified, and the effects of slope inclination, slope azimuth, variable surface albedo and plant shading on incoming radiation and spatially variable surface mass and energy balance, and consequently on soil moisture and temperature distributions, are rarely considered. In this presentation we discuss these missing elements and our attempts to implement them into the HYDRUS model. We demonstrate implications of some of these interactions and their impact on the spatial distributions of soil temperature and water content, and their effect on soil evaporation. Additionally, we will demonstrate the use of the HYDRUS model to simulate processes relevant to the ground source heat pump systems.

The methods of geomorphometry and digital soil mapping for assessing spatial variability in the properties of agrogray soils on a slope

NASA Astrophysics Data System (ADS)

Gopp, N. V.; Nechaeva, T. V.; Savenkov, O. A.; Smirnova, N. V.; Smirnov, V. V.

2017-01-01

The relationships between the morphometric parameters (MPs) of topography calculated on the basis of digital elevation model (ASTER GDEM, 30 m) and the properties of the plow layer of agrogray soils on a slope were analyzed. The contribution of MPs to the spatial variability of the soil moisture reached 42%; to the content of physical clay (<0.01 mm particles), 59%; to the humus content, 46%; to the total nitrogen content, 31%; to the content of nitrate nitrogen, 28%; to the content of mobile phosphorus, 40%; to the content of exchangeable potassium, 45%; to the content of exchangeable calcium, 67%; to the content of exchangeable magnesium, 40%; and to the soil pH, 42%. A comparative analysis of the plow layer within the eluvial and transitional parts of the slope was performed with the use of geomorphometric methods and digital soil mapping. The regression analysis showed statistically significant correlations between the properties of the plow layer and the MPs describing surface runoff, geometric forms of surface, and the soil temperature regime.

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

Mishra, U.; Riley, W. J.

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data setmore » with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Baseline element concentrations in soils and plants, Wattenmeer National Park, North and East Frisian Islands, Federal Republic of Germany

USGS Publications Warehouse

Severson, R.C.; Gough, L.P.; van den Boom, G.

1992-01-01

Baseline element concentrations are given for dune grass (Ammophilia arenaria), willow (Salix repens), moss (Hylocomium splendens) and associated surface soils. Baseline and variability data for pH, ash, Al, As, Ba, C, Ca, Cd, Ce, Co, Cr, Cu, Fe, Hg, K, La, Li, Mg, Mn, Na, Nb, Nd, Ni, P, Pb, S, Sc, Se, Sr, Th, Ti, V, Y, Yb, and Zn are reported; however, not all variables are reported for all media because, in some media, certain elements were below the analytical detection limit. Spatial variation in element concentration between five Frisian Islands are given for each of the sample media. In general, only a few elements in each media showed statistically significant differences between the islands sampled. The measured concentrations in all sample media exhibited ranges that cannot be attributed to anthropogenic additions of trace elements, with the possible exception of Hg and Pb in surface soils.Baseline element concentrations are given for dune grass (Ammophilia arenaria), willow (Salix repens), moss (Hylocomium splendens) and associated surface soils. Baseline and variability data for pH, ash, Al, As, Ba, C, Ca, Cd, Ce, Co, Cr, Cu, Fe, Hg, K, La, Li, Mg, Mn, Na, Nb, Nd, Ni, P, Pb, S, Sc, Se, Sr, Th, Ti, V, Y, Yb, and Zn are reported; however, not all variables are reported for all media because, in some media, certain elements were below the analytical detection limit. Spatial variation in element concentration between five Frisian Islands are given for each of the sample media. In general, only a few elements in each media showed statistically significant differences between the islands sampled. The measured concentrations in all sample media exhibited ranges that cannot be attributed to anthropogenic additions of trace elements, with the possible exception of Hg and Pb in surface soils.

Tropical Warm Pool Surface Heat Budgets and Temperature: Contrasts Between 1997-98 El Nino and 1998-99 La Nina

NASA Technical Reports Server (NTRS)

Chou, Shu-Hsien; Chou, Ming-Dah; Chan, Pui-King; Lin, Po-Hsiung; Wang, Kung-Hwa

2003-01-01

Seasonal and interannual variations of the net surface heating F(sub NET) and sea surface temperature tendency (T(sub s)/dt) in the tropical eastern Indian and western Pacific Oceans are studied. The surface heat fluxes are derived from the Special Sensor Microwave/Imager and Japanese Geostationary Meteorological Satellite radiance measurements for the period October 1997-September 2000. It is found that the magnitude of solar heating is lager than that of evaporative cooling, but the spatial variation of the latter is significantly large than the former. As a result, the spatial variations of seasonal and interannual variability of F(sub NET), follow closely that of evaporative cooling. Seasonal variations of F(sub NET) and T(sub s)/dt are significantly correlated, except for the equatorial western Pacific. The high correlation is primarily attributable to high correlation between seasonal cycles of solar heating and T(sub s)/dt. The change of F(sub NET) between 1997-98 El Nino and 1998-99 La Nina is significantly larger in the tropical eastern Indian Ocean than tropical western Pacific. For the former region, the reduced evaporative cooling arising from weakened winds during the El Nino is generally associated with enhanced solar heating due to decreased cloudiness, and thus increases the interannual variability of F(sub NET). For the latter region, the reduced evaporative cooling due to weakened winds is generally associated with but exceeds the reduced solar heating arising from increased cloudiness, and vise versa. Thus the interannual variability of F(sub NET) is reduced due to this offsetting effect. Interannual variations of F(sub NET) and T(sub s)/dt have very low correlation. This is most likely related to interannual variability of ocean dynamics, which includes the variations of solar radiation penetrating through oceanic mixed layer, upwelling of cold thermocline water, Indonesian throughflow for transporting heat from the Pacific to Indian Ocean, and interhemispheric transport in the Indian Ocean.

Different combination of MODIS land surface temperature data for daily air surface temperature estimation in North West Vietnam

NASA Astrophysics Data System (ADS)

Noi Phan, Thanh; Kappas, Martin; Degener, Jan

2017-04-01

Land air temperature (Ta) with high spatial and temporal resolution plays an important role in various applications, such as: crop growth monitoring and simulations, environmental risk models, weather forecasting, land use cover change, urban heat islands, etc. Daily Ta (including Ta-max, Ta-min, and Ta-mean) is usually measured by weather stations (often at 2 m above the ground); thus, Ta is limited in spatial coverage. Satellite data, especially MODIS land surface temperature (LST) data at 1 kilometre and high temporal resolution (4 times per day, combining TERRA and AQUA) are free available and easily to access. However, there is a difference between Ta and LST because of the complex surface energy budget and multiple related variables between them. Several researches states that the Ta could be estimated using MODIS LST data with accurate of 2-4oC. However, there are only a handful of studies using dynamically combining of four MODIS LST data for Ta estimation. In this study, we evaluated all 15 - possible - combinations of four MODIS LST using support vector machine (SVM) and random forests (RFs) models. MODIS LST and Ta data was extracted from 4 weather stations in rural area in North West Vietnam from 2010 to 2012 (three years). Our results indicated that the accuracy of Ta estimation was affected by the different combination and the combined data (multiple variables) gave better results than those of single LST (solely variable), the best result was achieved (coefficient of determination (R2) = 0.95, 0.97, 0.97; root mean square error (RMSE) =1.7, 1.4, 1.2 oC for Ta-min, Ta-max, Ta-mean respectively) when all four LSTs were combined and RFs performed better than SVM.

An Assessment of Southern Ocean Water Masses and Sea Ice During 1988-2007 in a Suite of Interannual CORE-II Simulations

NASA Technical Reports Server (NTRS)

Downes, Stephanie M.; Farneti, Riccardo; Uotila, Petteri; Griffies, Stephen M.; Marsland, Simon J.; Bailey, David; Behrens, Erik; Bentsen, Mats; Bi, Daohua; Biastoch, Arne;

Contribution of rivers and floodplains to the global terrestrial water storage variability

NASA Astrophysics Data System (ADS)

Getirana, A.; Kumar, S.; Girotto, M.; Rodell, M.

2017-12-01

Since the launch of the GRACE mission in 2002, the scientific community has gained significant insight into terrestrial water storage (TWS) variations around the world. Still, understanding of the relationship between TWS variations and changes in its individual components (groundwater, soil moisture, surface waters, snow, and vegetation water storage) has not advanced beyond small-scale studies based on in situ data. Although a few studies have demonstrated the impact that surface water storage (SWS) has on TWS in tropical basins, the vast majority of investigations on TWS decomposition systematically neglect SWS by assuming that its contribution to TWS is trivial. Even though that assumption might be a close representation of the truth in specific locations, the actual impact of SWS on the global TWS change and its spatial variability is unknown. This study aims to quantify the contribution of rivers and floodplains on the global terrestrial water storage (TWS) variability. We use state-of-the-art models to simulate land surface processes and river dynamics in order to separate TWS into its main components. Based on a proposed impact index, we show that surface water storage (SWS) contributes to 7% of TWS globally, but that contribution highly varies spatially. The primary contribution of SWS to TWS is in the tropics, and in major rivers flowing over arid regions or at high latitudes. About 20-23% of both Amazon and Nile basins' TWS changes are due to SWS. SWS has low impact in Western U.S., Northern Africa, Middle-East and central Asia. Based on comparisons against GRACE-based estimates, we conclude that using SWS significantly improves TWS simulations in most South America, Africa and Northern India, confirming the need for SWS as a key component of TWS change.

Quantifying the processes controlling intraseasonal mixed-layer temperature variability in the tropical Indian Ocean

NASA Astrophysics Data System (ADS)

Halkides, D. J.; Waliser, Duane E.; Lee, Tong; Menemenlis, Dimitris; Guan, Bin

2015-02-01

Spatial and temporal variation of processes that determine ocean mixed-layer (ML) temperature (MLT) variability on the timescale of the Madden-Julian Oscillation (MJO) in the Tropical Indian Ocean (TIO) are examined in a heat-conserving ocean state estimate for years 1993-2011. We introduce a new metric for representing spatial variability of the relative importance of processes. In general, horizontal advection is most important at the Equator. Subsurface processes and surface heat flux are more important away from the Equator, with surface heat flux being the more dominant factor. Analyses at key sites are discussed in the context of local dynamics and literature. At 0°, 80.5°E, for MLT events > 2 standard deviations, ocean dynamics account for more than two thirds of the net tendency during cooling and warming phases. Zonal advection alone accounts for ˜40% of the net tendency. Moderate events (1-2 standard deviations) show more differences between events, and some are dominated by surface heat flux. At 8°S, 67°E in the Seychelles-Chagos Thermocline Ridge (SCTR) area, surface heat flux accounts for ˜70% of the tendency during strong cooling and warming phases; subsurface processes linked to ML depth (MLD) deepening (shoaling) during cooling (warming) account for ˜30%. MLT is more sensitive to subsurface processes in the SCTR, due to the thin MLD, thin barrier layer and raised thermocline. Results for 8°S, 67°E support assertions by Vialard et al. (2008) not previously confirmed due to measurement error that prevented budget closure and the small number of events studied. The roles of MLD, barrier layer thickness, and thermocline depth on different timescales are examined.

Subtropical Gyre Variability Observed by Ocean Color Satellites

NASA Technical Reports Server (NTRS)

McClain, Charles R.; Signorini, Sergio R.; Christian, James R.

2002-01-01

The subtropical gyres of the world are extensive, coherent regions that occupy about 40% of the surface of the earth. Once thought to be homogeneous and static habitats, there is increasing evidence that mid-latitude gyres exhibit substantial physical and biological variability on a variety of time scales. While biological productivity within these oligotrophic regions may be relatively small, their immense size makes their total contribution significant. Global distributions of dynamic height derived from satellite altimeter data, and chlorophyll concentration derived from satellite ocean color data, show that the dynamic center of the gyres, the region of maximum dynamic height where the thermocline is deepest, does not coincide with the region of minimum chlorophyll concentration. The physical and biological processes by which this distribution of ocean properties is maintained, and the spatial and temporal scales of variability associated with these processes, are analyzed using global surface chlorophyll-a concentrations, sea surface height, sea surface temperature and surface winds from operational satellite and meteorological sources, and hydrographic data from climatologies and individual surveys. Seasonal and interannual variability in the areal extent of the subtropical gyres are examined using 8 months (November 1996 - June 1997) of OCTS and nearly 5 years (September 1997 - June 02) of SeaWiFS ocean color data and are interpreted in the context of climate variability and measured changes in other ocean properties (i.e., wind forcing, surface currents, Ekman pumping, and vertical mixing). The North Pacific and North Atlantic gyres are observed to be shrinking over this period, while the South Pacific, South Atlantic, and South Indian Ocean gyres appear to be expanding.

Qualitatively Assessing Randomness in SVD Results

NASA Astrophysics Data System (ADS)

Lamb, K. W.; Miller, W. P.; Kalra, A.; Anderson, S.; Rodriguez, A.

2012-12-01

Singular Value Decomposition (SVD) is a powerful tool for identifying regions of significant co-variability between two spatially distributed datasets. SVD has been widely used in atmospheric research to define relationships between sea surface temperatures, geopotential height, wind, precipitation and streamflow data for myriad regions across the globe. A typical application for SVD is to identify leading climate drivers (as observed in the wind or pressure data) for a particular hydrologic response variable such as precipitation, streamflow, or soil moisture. One can also investigate the lagged relationship between a climate variable and the hydrologic response variable using SVD. When performing these studies it is important to limit the spatial bounds of the climate variable to reduce the chance of random co-variance relationships being identified. On the other hand, a climate region that is too small may ignore climate signals which have more than a statistical relationship to a hydrologic response variable. The proposed research seeks to identify a qualitative method of identifying random co-variability relationships between two data sets. The research identifies the heterogeneous correlation maps from several past results and compares these results with correlation maps produced using purely random and quasi-random climate data. The comparison identifies a methodology to determine if a particular region on a correlation map may be explained by a physical mechanism or is simply statistical chance.

Influence of the Surface and Cloud Nonuniformities in the Solar Energy Fluxes in the Arctic

NASA Technical Reports Server (NTRS)

Rozwadowska, A.; Cahalan, R. F.; Einaudi, Franco (Technical Monitor)

2000-01-01

Solar energy fluxes reaching the surface and absorbed by it are basic components of the energy balance of the Arctic. They depend mainly on the solar zenith angle, a state of the atmosphere, especially the cloudiness, and the surface albedo. However, they can also be modified by variabilities in the surface albedo and cloud optical thickness. The surface of the Arctic can be highly nonuniform. The surface of the Arctic Ocean, which covers the huge part of the Arctic can be view as a mosaic of sea water, sea ice, snow and, in the melting period, melting ponds. In our paper, results are presented of Monte Carlo simulations of the expected influence of nonuniform cloud structure and nonuniform surface albedo on radiative fluxes at the Arctic surface. In particular, the plane parallel biases in the surface absorptance and atmospheric transmittance are studied. The bias is defined as the difference between the real absorptance or transmittance (i.e. nonuniform conditions) averaged over a given area, and the uniform or plane parallel case with the same mean cloud optical thickness and the same mean surface albedo. The dependence of the biases is analysed with respect to the following: domain averaged values of the cloud optical thickness and surface albedo, scales of their spatial variabilities, correlation between cloud optical thickness and cloud albedo variabilities, cloud height, and the solar zenith angle. Ranges of means and standard deviations of the input parameters typical of Arctic conditions are obtained from the SHEBA experiment.

Spatial variability of the Black Sea surface temperature from high resolution modeling and satellite measurements

NASA Astrophysics Data System (ADS)

Mizyuk, Artem; Senderov, Maxim; Korotaev, Gennady

2016-04-01

Large number of numerical ocean models were implemented for the Black Sea basin during last two decades. They reproduce rather similar structure of synoptical variability of the circulation. Since 00-s numerical studies of the mesoscale structure are carried out using high performance computing (HPC). With the growing capacity of computing resources it is now possible to reconstruct the Black Sea currents with spatial resolution of several hundreds meters. However, how realistic these results can be? In the proposed study an attempt is made to understand which spatial scales are reproduced by ocean model in the Black Sea. Simulations are made using parallel version of NEMO (Nucleus for European Modelling of the Ocean). A two regional configurations with spatial resolutions 5 km and 2.5 km are described. Comparison of the SST from simulations with two spatial resolutions shows rather qualitative difference of the spatial structures. Results of high resolution simulation are compared also with satellite observations and observation-based products from Copernicus using spatial correlation and spectral analysis. Spatial scales of correlations functions for simulated and observed SST are rather close and differs much from satellite SST reanalysis. Evolution of spectral density for modelled SST and reanalysis showed agreed time periods of small scales intensification. Using of the spectral analysis for satellite measurements is complicated due to gaps. The research leading to this results has received funding from Russian Science Foundation (project № 15-17-20020)

Exploring the Linkage between Urban Flood Risk and Spatial Patterns in Small Urbanized Catchments of Beijing, China

PubMed Central

Yao, Lei; Chen, Liding; Wei, Wei

2017-01-01

In the context of global urbanization, urban flood risk in many cities has become a serious environmental issue, threatening the health of residents and the environment. A number of hydrological studies have linked urban flooding issues closely to the spectrum of spatial patterns of urbanization, but relatively little attention has been given to small-scale catchments within the realm of urban systems. This study aims to explore the hydrological effects of small-scaled urbanized catchments assigned with various landscape patterns. Twelve typical residential catchments in Beijing were selected as the study areas. Total Impervious Area (TIA), Directly Connected Impervious Area (DCIA), and a drainage index were used as the catchment spatial metrics. Three scenarios were designed as different spatial arrangement of catchment imperviousness. Runoff variables including total and peak runoff depth (Qt and Qp) were simulated by using Strom Water Management Model (SWMM). The relationship between catchment spatial patterns and runoff variables were determined, and the results demonstrated that, spatial patterns have inherent influences on flood risks in small urbanized catchments. Specifically: (1) imperviousness acts as an effective indicator in affecting both Qt and Qp; (2) reducing the number of rainwater inlets appropriately will benefit the catchment peak flow mitigation; (3) different spatial concentrations of impervious surfaces have inherent influences on Qp. These findings provide insights into the role of urban spatial patterns in driving rainfall-runoff processes in small urbanized catchments, which is essential for urban planning and flood management. PMID:28264521

Exploring the Linkage between Urban Flood Risk and Spatial Patterns in Small Urbanized Catchments of Beijing, China.

PubMed

Yao, Lei; Chen, Liding; Wei, Wei

2017-02-28

In the context of global urbanization, urban flood risk in many cities has become a serious environmental issue, threatening the health of residents and the environment. A number of hydrological studies have linked urban flooding issues closely to the spectrum of spatial patterns of urbanization, but relatively little attention has been given to small-scale catchments within the realm of urban systems. This study aims to explore the hydrological effects of small-scaled urbanized catchments assigned with various landscape patterns. Twelve typical residential catchments in Beijing were selected as the study areas. Total Impervious Area ( TIA ), Directly Connected Impervious Area ( DCIA ), and a drainage index were used as the catchment spatial metrics. Three scenarios were designed as different spatial arrangement of catchment imperviousness. Runoff variables including total and peak runoff depth ( Q t and Q p ) were simulated by using Strom Water Management Model (SWMM). The relationship between catchment spatial patterns and runoff variables were determined, and the results demonstrated that, spatial patterns have inherent influences on flood risks in small urbanized catchments. Specifically: (1) imperviousness acts as an effective indicator in affecting both Q t and Q p ; (2) reducing the number of rainwater inlets appropriately will benefit the catchment peak flow mitigation; (3) different spatial concentrations of impervious surfaces have inherent influences on Q p . These findings provide insights into the role of urban spatial patterns in driving rainfall-runoff processes in small urbanized catchments, which is essential for urban planning and flood management.

The Dynamics of Laurentian Great Lakes Surface Energy Budgets

NASA Astrophysics Data System (ADS)

Spence, C.; Blanken, P.; Lenters, J. D.; Gronewold, A.; Kerkez, B.; Xue, P.; Froelich, N.

2015-12-01

The Laurentian Great Lakes constitute the largest freshwater surface in the world and are a valuable North American natural and socio-economic resource. In response to calls for improved monitoring and research on the energy and water budgets of the lakes, there has been a growing ensemble of in situ measurements - including offshore eddy flux towers, buoy-based sensors, and vessel-based platforms -deployed through an ongoing, bi-national collaboration known as the Great Lakes Evaporation Network (GLEN). The objective of GLEN is to reduce uncertainty in Great Lakes seasonal and 6-month water level forecasts, as well as climate change projections of the surface energy balance and water level fluctuations. Although It remains challenging to quantify and scale energy budgets and fluxes over such large water bodies, this presentation will report on recent successes in three areas: First, in estimating evaporation rates over each of the Great Lakes; Second, defining evaporation variability among the lakes, especially in winter and; Third, explaining the interaction between ice cover, water temperature, and evaporation across a variety of temporal and spatial scales. Research gaps remain, particularly those related to spatial variability and scaling of turbulent fluxes, so the presentation will also describe how this will be addressed with enhanced instrument and platform arrays.

Dynamics of the Antarctic Circumpolar Current. Evidence for Topographic Effects from Altimeter Data and Numerical Model Output

NASA Technical Reports Server (NTRS)

Gille, Sarah T.

1995-01-01

Geosat altimeter data and numerical model output are used to examine the circulation and dynamics of the Antarctic Circumpolar Current (ACC). The mean sea surface height across the ACC has been reconstructed from height variability measured by the altimeter, without assuming prior knowledge of the geoid. The results indicate locations for the Subantarctic and Polar Fronts which are consistent with in situ observations and indicate that the fronts are substantially steered by bathymetry. Detailed examination of spatial and temporal variability indicates a spatial decorrelation scale of 85 km and a temporal e-folding scale of 34 days. Empirical Orthogonal Function analysis suggests that the scales of motion are relatively short, occuring on 1000 km length-scales rather than basin or global scales. The momentum balance of the ACC has been investigated using output from the high resolution primitive equation model in combination with altimeter data. In the Semtner-Chervin quarter-degree general circulation model topographic form stress is the dominant process balancing the surface wind forcing. In stream coordinates, the dominant effect transporting momentum across the ACC is bibarmonic friction. Potential vorticity is considered on Montgomery streamlines in the model output and along surface streamlines in model and altimeter data. (AN)

Antarctic Surface Temperatures Using Satellite Infrared Data from 1979 Through 1995

NASA Technical Reports Server (NTRS)

Comiso, Josefino C.; Stock, Larry

1997-01-01

The large scale spatial and temporal variations of surface ice temperature over the Antarctic region are studied using infrared data derived from the Nimbus-7 Temperature Humidity Infrared Radiometer (THIR) from 1979 through 1985 and from the NOAA Advanced Very High Resolution Radiometer (AVHRR) from 1984 through 1995. Enhanced techniques suitable for the polar regions for cloud masking and atmospheric correction were used before converting radiances to surface temperatures. The observed spatial distribution of surface temperature is highly correlated with surface ice sheet topography and agrees well with ice station temperatures with 2K to 4K standard deviations. The average surface ice temperature over the entire continent fluctuates by about 30K from summer to winter while that over the Antarctic Plateau varies by about 45K. Interannual fluctuations of the coldest interannual variations in surface temperature are highest at the Antarctic Plateau and the ice shelves (e.g., Ross and Ronne) with a periodic cycle of about 5 years and standard deviations of about 11K and 9K, respectively. Despite large temporal variability, however, especially in some regions, a regression analysis that includes removal of the seasonal cycle shows no apparent trend in temperature during the period 1979 through 1995.

Spatial variability analysis of combining the water quality and groundwater flow model to plan groundwater and surface water management in the Pingtung plain

NASA Astrophysics Data System (ADS)

Chen, Ching-Fang; Chen, Jui-Sheng; Jang, Cheng-Shin

2014-05-01

As a result of rapid economic growth in the Pingtung Plain, the use of groundwater resources has changed dramatically. The groundwater is quite rich in the Pingtung plain and the most important water sources. During the several decades, a substantial amount of groundwater has been pumped for the drinking, irrigation and aquaculture water supplies. However, because the sustainable use concept of groundwater resources is lack, excessive pumping of groundwater causes the occurrence of serious land subsidence and sea water intrusion. Thus, the management and conservation of groundwater resources in the Pingtung plain are considerably critical. This study aims to assess the conjunct use effect of groundwater and surface water in the Pingtung plain on recharge by reducing the amount of groundwater extraction. The groundwater quality variability and groundwater flow models are combined to spatially analyze potential zones of groundwater used for multi-purpose in the Pingtung Plain. First, multivariate indicator kriging (MVIK) is used to analyze spatial variability of groundwater quality based on drinking, aquaculture and irrigation water quality standards, and probabilistically delineate suitable zones in the study area. Then, the groundwater flow model, Processing MODFLOW (PMWIN), is adopted to simulate groundwater flow. The groundwater flow model must be conducted by the calibration and verification processes, and the regional groundwater recovery is discussed when specified water rights are replaced by surface water in the Pingtung plain. Finally, the most suitable zones of reducing groundwater use are determined for multi-purpose according to combining groundwater quality and quantity. The study results can establish a sound and low-impact management plan of groundwater resources utilization for the multi-purpose groundwater use, and prevent decreasing ground water tables, and the occurrence of land subsidence and sea water intrusion in the Pingtung plain.

In the hot seat : Insolation and ENSO controls on vegetation productivity in tropical Africa inferred from NDVI

NASA Astrophysics Data System (ADS)

Ivory, S.; Russell, J. L.; Cohen, A. S.

2010-12-01

Threats to tropical biodiversity with serious and costly implications for both ecosystems and human well-being in Africa have led the IPCC to classify this region as vulnerable to negative impacts from climate change. Yet little is known about how vegetation communities respond to altered patterns of rainfall and evaporation. Paleoclimate records within the tropics can help answer questions about how vegetation response to climate forcing changes over time. However, sparse spatial extent of records and uncertainty surrounding the climate-vegetation relationship complicate these insights. Understanding the climatic mechanisms involved in landscape change at all temporal scales creates the need for quantitative constraints of the modern relationship between climatic controls, hydrology, and vegetation. Though modern observational data can help elucidate this relationship, low resolution and complicated rainfall/vegetation associations make them less than ideal. Satellite data of vegetation productivity (NDVI) with continuous high-resolution spatial coverage provides a robust and elegant tool for identifying the link between global and regional controls and vegetation. We use regression analyses of variables either previously proposed or potentially important in regulating Afro-tropical vegetation (insolation, out-going long-wave radiation, geopotential height, Southern Oscillation Index, Indian Ocean Dipole, Indian Monsoon precipitation, sea-level pressure, surface wind, sea-surface temperature) on continuous, time-varying spatial fields of 8km NDVI for sub-Saharan Africa. These analyses show the importance of global atmospheric controls in producing regional intra-annual and inter-annual vegetation variability. Dipole patterns emerge primarily correlated with both the seasonal and inter-annual extent of the Intertropical Convergence Zone (ITCZ). Inter-annual ITCZ variability drives patterns in African vegetation resulting from the effect of insolation anomalies and ENSO events on atmospheric circulation rather than sea surface temperatures or teleconnections to mid/high latitudes. Global controls on tropical atmospheric circulation regulate vegetation throughout sub-Saharan Africa on many time scales through alteration of dry season length and moisture convergence, rather than precipitation amount.

From BASE-ASIA Toward 7-SEAS: A Satellite-Surface Perspective of Boreal Spring Biomass-Burning Aerosols and Clouds in Southeast Asia

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee; Hsu, N. Christina; Lau, William K.-M.; Li, Can; Gabriel, Philip M.; Ji, Qiang; Holben, Brent N.; Welton, E. Judd; Nguyen, Anh X.; Janjai, Serm;

Shift in the microbial community composition of surface water and sediment along an urban river.

PubMed

Wang, Lan; Zhang, Jing; Li, Huilin; Yang, Hong; Peng, Chao; Peng, Zhengsong; Lu, Lu

2018-06-15

Urban rivers represent a unique ecosystem in which pollution occurs regularly, leading to significantly altered of chemical and biological characteristics of the surface water and sediments. However, the impact of urbanization on the diversity and structure of the river microbial community has not been well documented. As a major tributary of the Yangtze River, the Jialing River flows through many cities. Here, a comprehensive analysis of the spatial microbial distribution in the surface water and sediments in the Nanchong section of Jialing River and its two urban branches was conducted using 16S rRNA gene-based Illumina MiSeq sequencing. The results revealed distinct differences in surface water bacterial composition along the river with a differential distribution of Proteobacteria, Cyanobacteria, Actinobacteria, Bacteroidetes and Acidobacteria (P < 0.05). The bacterial diversity in sediments was significantly higher than their corresponding water samples. Additionally, archaeal communities showed obvious spatial variability in the surface water. The construction of the hydropower station resulted in increased Cyanobacteria abundance in the upstream (32.2%) compared to its downstream (10.3%). Several taxonomic groups of potential fecal indicator bacteria, like Flavobacteria and Bacteroidia, showed an increasing trend in the urban water. PICRUSt metabolic inference analysis revealed a growing number of genes associated with xenobiotic metabolism and nitrogen metabolism in the urban water, indicating that urban discharges might act as the dominant selective force to alter the microbial communities. Redundancy analysis suggested that the microbial community structure was influenced by several environmental factors. TP (P < 0.01) and NO 3 - (P < 0.05), and metals (Zn, Fe) (P < 0.05) were the most significant drivers determining the microbial community composition in the urban river. These results highlight that river microbial communities exhibit spatial variation in urban areas due to the joint influence of chemical variables associated with sewage discharging and construction of hydropower stations. Copyright © 2018 Elsevier B.V. All rights reserved.

Investigating carbon flux variability in subtropical peat soils of the Everglades using hydrogeophysical methods

NASA Astrophysics Data System (ADS)

Comas, Xavier; Wright, William

2014-08-01

The spatial and temporal variability in accumulation and release of greenhouse gases (mainly methane and carbon dioxide) to the atmosphere from peat soils remains very uncertain. The use of near-surface geophysical methods such as ground penetrating radar (GPR) has proven useful during the last decade to expand scales of measurement as related to in situ gas distribution and dynamics beyond traditional methods (i.e., gas chambers). However, this approach has focused exclusively on boreal peatlands, while no studies in subtropical systems like the Everglades using these techniques exist. In this paper GPR is combined with gas traps, time-lapse cameras, gas chromatography, and surface deformation measurements to explore biogenic gas dynamics (mainly gas buildup and release) in two locations in the Everglades. Similar to previous studies in northern peatlands, our data in the Everglades show a statistically significant correlation between the following: (1) GPR-estimated gas content and gas fluxes, (2) GPR-estimated gas content and surface deformation, and (3) atmospheric pressure and both GPR-estimated gas content and gas flux. From these results several gas-releasing events ranging between 33.8 and 718.8 mg CH4 m-2 d-1 were detected as identified by the following: (1) decreases in GPR-estimated gas content within the peat matrix, (2) increases in gas fluxes captured by gas traps and time-lapse cameras, and (3) decreases in surface deformation. Furthermore, gas-releasing events corresponded to periods of high atmospheric pressure. Changes in gas accumulation and release were attributed to differences in seasonality and peat soil type between sites. These results suggest that biogenic gas releases in the Everglades are spatially and temporarily variable. For example, flux events measured at hourly scales were up to threefold larger when compared to daily fluxes, therefore suggesting that flux measurements decline when averaged over longer time spans. This research therefore questions what the appropriate spatial and temporal scale of measurement is necessary to properly capture the dynamics of biogenic gas release in subtropical peat soils.

On the soil moisture estimate at basin scale in Mediterranean basins with the ASAR sensor: the Mulargia basin case study

NASA Astrophysics Data System (ADS)

Fois, Laura; Montaldo, Nicola

2017-04-01

Soil moisture plays a key role in water and energy exchanges between soil, vegetation and atmosphere. For water resources planning and managementthesoil moistureneeds to be accurately and spatially monitored, specially where the risk of desertification is high, such as Mediterranean basins. In this sense active remote sensors are very attractive for soil moisture monitoring. But Mediterranean basinsaretypicallycharacterized by strong topography and high spatial variability of physiographic properties, and only high spatial resolution sensorsare potentially able to monitor the strong soil moisture spatial variability.In this regard the Envisat ASAR (Advanced Synthetic Aperture Radar) sensor offers the attractive opportunity ofsoil moisture mapping at fine spatial and temporal resolutions(up to 30 m, every 30 days). We test the ASAR sensor for soil moisture estimate in an interesting Sardinian case study, the Mulargia basin withan area of about 70 sq.km. The position of the Sardinia island in the center of the western Mediterranean Sea basin, its low urbanization and human activity make Sardinia a perfect reference laboratory for Mediterranean hydrologic studies. The Mulargia basin is a typical Mediterranean basinin water-limited conditions, and is an experimental basin from 2003. For soil moisture mapping23 satellite ASAR imagery at single and dual polarization were acquired for the 2003-2004period.Satellite observationsmay bevalidated through spatially distributed soil moisture ground-truth data, collected over the whole basin using the TDR technique and the gravimetric method, in days with available radar images. The results show that ASAR sensor observations can be successfully used for soil moisture mapping at different seasons, both wet and dry, but an accurate calibration with field data is necessary. We detect a strong relationship between the soil moisture spatial variability and the physiographic properties of the basin, such as soil water storage capacity, deep and texture of soils, type and density of vegetation, and topographic parameters. Finally we demonstrate that the high resolution ASAR imagery are an attractive tool for estimating surface soil moisture at basin scale, offering a unique opportunity for monitoring the soil moisture spatial variability in typical Mediterranean basins.

Spatial Variability and Stocks of Soil Organic Carbon in the Gobi Desert of Northwestern China

PubMed Central

Zhang, Pingping; Shao, Ming'an

2014-01-01

Soil organic carbon (SOC) plays an important role in improving soil properties and the C global cycle. Limited attention, though, has been given to assessing the spatial patterns and stocks of SOC in desert ecosystems. In this study, we quantitatively evaluated the spatial variability of SOC and its influencing factors and estimated SOC storage in a region (40 km2) of the Gobi desert. SOC exhibited a log-normal depth distribution with means of 1.6, 1.5, 1.4, and 1.4 g kg−1 for the 0–10, 10–20, 20–30, and 30–40 cm layers, respectively, and was moderately variable according to the coefficients of variation (37–42%). Variability of SOC increased as the sampling area expanded and could be well parameterized as a power function of the sampling area. Significant correlations were detected between SOC and soil physical properties, i.e. stone, sand, silt, and clay contents and soil bulk density. The relatively coarse fractions, i.e. sand, silt, and stone contents, had the largest effects on SOC variability. Experimental semivariograms of SOC were best fitted by exponential models. Nugget-to-sill ratios indicated a strong spatial dependence for SOC concentrations at all depths in the study area. The surface layer (0–10 cm) had the largest spatial dependency compared with the other layers. The mapping revealed a decreasing trend of SOC concentrations from south to north across this region of the Gobi desert, with higher levels close to an oasis and lower levels surrounded by mountains and near the desert. SOC density to depths of 20 and 40 cm for this 40 km2 area was estimated at 0.42 and 0.68 kg C m−2, respectively. This study provides an important contribution to understanding the role of the Gobi desert in the global carbon cycle. PMID:24733073

Effects Of Spatial Variability In Marshes On Coastal Erosion Under Storm Conditions

NASA Astrophysics Data System (ADS)

Lunghino, B.; Suckale, J.; Fringer, O. B.; Maldonado, S.; Ferreira, C.; Marras, S.; Mandel, T.

2016-12-01

To quantify the contribution of marshes in protecting coastlines, engineers and planners need to evaluate how variability in marsh characteristics and storm conditions affect erosion in the inundation zone. Previous studies show that spatial patterns in marshes significantly affect flow and sediment transport under normal tidal conditions [1, 2]. This study investigates the effect of spatial variability on floodplain sediment transport under a range of extreme hydrodynamic conditions that occur during storm events. We model the hydrodynamics of storm surge conditions on an idealized coastal floodplain by solving the 2D shallow water equations. We approximate the effect of vegetation on hydrodynamics as a constant drag coefficient. The model calculates suspended sediment transport with the advection-diffusion equation and updates morphology with erosional and depositional fluxes. We conduct numerical experiments in which we vary both the scale of the storm event and the spatial patterns of vegetation and evaluate the impact on erosion and deposition on the floodplain. We find that the alongshore extent of the vegetation is the primary control on the net volume of sediment eroded. Scour occurs in narrow channels between vegetated areas, but this does not significantly alter the net volume of sediment transported. Deposition occurs in vegetated areas under the full range of flow velocities we test. These results suggest that resolving all variability in vegetation is not necessary to quantify net sediment transport volumes at the floodplain scale. Increasing the scale of the storm event does not alter the role of spatial variability. References [1] Meire, D. W., Kondziolka, J. M., and Nepf, H. M. Interaction between neighboring vegetation patches: Impact on flow and deposition. Water Resources Research 50, 5 (2014), 3809-3825. [2] Temmerman, S., Bouma, T., Govers, G., Wang, Z., De Vries, M., and Her- man, P. Impact of vegetation on flow routing and sedimentation patterns: Three-dimensional modeling for a tidal marsh. Journal of Geophysical Research: Earth Surface 110, F4 (2005).

Low damage electrical modification of 4H-SiC via ultrafast laser irradiation

NASA Astrophysics Data System (ADS)

Ahn, Minhyung; Cahyadi, Rico; Wendorf, Joseph; Bowen, Willie; Torralva, Ben; Yalisove, Steven; Phillips, Jamie

2018-04-01

The electrical properties of 4H-SiC under ultrafast laser irradiation in the low fluence regime (<0.50 J/cm2) are presented. The appearance of high spatial frequency laser induced periodic surface structures is observed at a fluence near 0.25 J/cm2 and above, with variability in environments like in air, nitrogen, and a vacuum. In addition to the formation of periodic surface structures, ultrafast laser irradiation results in possible surface oxidation and amorphization of the material. Lateral conductance exhibits orders of magnitude increase, which is attributed to either surface conduction or modification of electrical contact properties, depending on the initial material conductivity. Schottky barrier formation on ultrafast laser irradiated 4H-SiC shows an increase in the barrier height, an increase in the ideality factor, and sub-bandgap photovoltaic responses, suggesting the formation of photo-active point defects. The results suggest that the ultrafast laser irradiation technique provides a means of engineering spatially localized structural and electronic modification of wide bandgap materials such as 4H-SiC with relatively low surface damage via low temperature processing.

Methods for Combination of GRACE Gravimetry and ICESat Altimetry over Antarctica on Monthly Timescales

NASA Astrophysics Data System (ADS)

Hardy, R. A.; Nerem, R. S.; Wiese, D. N.

2017-12-01

Gravity and surface elevation change data altimetry provide different perspectives on mass variability in Antarctica. In anticipation of the concurrent operation of the successors of GRACE and ICESat, GRACE Follow-On and ICESat-2, we approach the problem of combining these data for enhanced spatial resolution and disaggregation of Antarctica's major mass transport processes. Using elevation changes gathered from over 500 million overlapping ICESat laser shot pairs between 2003 and 2009, we construct gridded models of Antarctic elevation change for each ICESat operational period. Comparing these elevation grids with temporally registered JPL RL05M mascon solutions, we exploit the relationship between surface mass flux and elevation change to inform estimates of effective surface density. These density estimates enable solutions for glacial isostatic adjustment and monthly estimates of surface mass change. These are used alongside spatial statistics from both the data and models of surface mass balance to produce enhanced estimates of Antarctic mass balance. We validate our solutions by modeling the effects of elastic loading and GIA from these solutions on the vertical motion of Antarctica's GNSS sites.

Sub-nA spatially resolved conductivity profiling of surface and interface defects in ceria films

DOE PAGES

Farrow, Tim; Yang, Nan; Doria, Sandra; ...

2015-03-17

Spatial variability of conductivity in ceria is explored using scanning probe microscopy with galvanostatic control. Ionically blocking electrodes are used to probe the conductivity under opposite polarities to reveal possible differences in the defect structure across a thin film of CeO2. Data suggest the existence of a large spatial inhomogeneity that could give rise to constant phase elements during standard electrochemical characterization, potentially affecting the overall conductivity of films on the macroscale. The approach discussed here can also be utilized for other mixed ionic electronic conductor systems including memristors and electroresistors, as well as physical systems such as ferroelectric tunnelingmore » barriers« less

A Survey of Spatial and Seasonal Water Isotope Variability on the Juneau Icefield, Alaksa

NASA Astrophysics Data System (ADS)

Dennis, D.; Carter, A.; Clinger, A. E.; Eads, O. L.; Gotwals, S.; Gunderson, J.; Hollyday, A. E.; Klein, E. S.; Markle, B. R.; Timms, J. R.

2015-12-01

The depletion of stable oxygen-hydrogen isotopes (δ18O and δH) is well correlated with temperature change, which is driven by variation in topography, climate, and atmospheric circulation. This study presents a survey of the spatial and seasonal variability of isotopic signatures on the Juneau Icefield (JI), Alaska, USA which spans over 3,000 square-kilometers. To examine small scale variability in the previous year's accumulation, samples were taken at regular intervals from snow pits and a one square-kilometer surficial grid. Surface snow samples were collected across the icefield to evaluate large scale variability, ranging approximately 1,000 meters in elevation and 100 kilometers in distance. Individual precipitation events were also sampled to track percolation throughout the snowpack and temperature correlations. A survey of this extent has never been undertaken on the JI. Samples were analyzed in the field using a Los Gatos laser isotope analyzer. This survey helps us better understand isotope fractionation on temperate glaciers in coastal environments and provides preliminary information on the suitability of the JI for a future ice core drilling project.

Relating Solar Resource Variability to Cloud Type

NASA Astrophysics Data System (ADS)

Hinkelman, L. M.; Sengupta, M.

2012-12-01

Power production from renewable energy (RE) resources is rapidly increasing. Generation of renewable energy is quite variable since the solar and wind resources that form the inputs are, themselves, inherently variable. There is thus a need to understand the impact of renewable generation on the transmission grid. Such studies require estimates of high temporal and spatial resolution power output under various scenarios, which can be created from corresponding solar resource data. Satellite-based solar resource estimates are the best source of long-term solar irradiance data for the typically large areas covered by transmission studies. As satellite-based resource datasets are generally available at lower temporal and spatial resolution than required, there is, in turn, a need to downscale these resource data. Downscaling in both space and time requires information about solar irradiance variability, which is primarily a function of cloud types and properties. In this study, we analyze the relationship between solar resource variability and satellite-based cloud properties. One-minute resolution surface irradiance data were obtained from a number of stations operated by the National Oceanic and Atmospheric Administration (NOAA) under the Surface Radiation (SURFRAD) and Integrated Surface Irradiance Study (ISIS) networks as well as from NREL's Solar Radiation Research Laboratory (SRRL) in Golden, Colorado. Individual sites were selected so that a range of meteorological conditions would be represented. Cloud information at a nominal 4 km resolution and half hour intervals was derived from NOAA's Geostationary Operation Environmental Satellite (GOES) series of satellites. Cloud class information from the GOES data set was then used to select and composite irradiance data from the measurement sites. The irradiance variability for each cloud classification was characterized using general statistics of the fluxes themselves and their variability in time, as represented by ramps computed for time scales from 10 s to 0.5 hr. The statistical relationships derived using this method will be presented, comparing and contrasting the statistics computed for the different cloud types. The implications for downscaling irradiances from satellites or forecast models will also be discussed.

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.

Relationship between Surface Urban Heat Island intensity and sensible heat flux retrieved from meteorological parameters observed by road weather stations in urban area

NASA Astrophysics Data System (ADS)

Gawuć, Lech

2017-04-01

Urban Heat Island (UHI) is a direct consequence of altered energy balance in urban areas (Oke 1982). There has been a significant effort put into an understanding of air temperature variability in urban areas and underlying mechanisms (Arnfield 2003, Grimmond 2006, Stewart 2011, Barlow 2014). However, studies that are concerned on surface temperature are less frequent. Therefore, Voogt & Oke (2003) proposed term "Surface Urban Heat Island (SUHI)", which is analogical to UHI and it is defined as a difference in land surface temperature (LST) between urban and rural areas. SUHI is a phenomenon that is not only concerned with high spatial variability, but also with high temporal variability (Weng and Fu 2014). In spite of the fact that satellite remote sensing techniques give a full spatial pattern over a vast area, such measurements are strictly limited to cloudless conditions during a satellite overpass (Sobrino et al., 2012). This significantly reduces the availability and applicability of satellite LST observations, especially over areas and seasons with high cloudiness occurrence. Also, the surface temperature is influenced by synoptic conditions (e.g., wind and humidity) (Gawuc & Struzewska 2016). Hence, utilising single observations is not sufficient to obtain a full image of spatiotemporal variability of urban LST and SUHI intensity (Gawuc & Struzewska 2016). One of the possible solutions would be a utilisation of time-series of LST data, which could be useful to monitor the UHI growth of individual cities and thus, to reveal the impact of urbanisation on local climate (Tran et al., 2006). The relationship between UHI and synoptic conditions have been summarised by Arnfield (2003). However, similar analyses conducted for urban LST and SUHI are lacking. We will present analyses of the relationship between time series of remotely-sensed LST and SUHI intensity and in-situ meteorological observations collected by road weather stations network, namely: road surface kinetic temperature, wind speed, air temperature, soil temperature at a depth of 30 cm, road surface condition, relative humidity. Also, as there are wind speed and temperature observations at different heights available, we will calculate sensible heat flux in order to relate it to the intensity of SUHI.

Correlations between soil respiration and soil properties in sugarcane areas under green and slash-and-burn management systems

NASA Astrophysics Data System (ADS)

Rodrigo Panosso, Alan; Milori, Débora M. B. P.; Marques Júnior, José; Martin-Neto, Ladislau; La Scala, Newton, Jr.

2010-05-01

Soil management causes changes in soil physical, chemical, and biological properties that consequently affect its CO2 emission. In this work we studied soil respiration (FCO2) in areas with sugarcane production in southern Brazil under two different sugarcane management systems: green (G), consisting of mechanized harvesting that produces a large amount of crop residues left on the soil surface, and slash-and-burn (SB), in which the residues are burned before manual harvest, leaving no residues on the soil surface. The study was conducted after the harvest period in two side-by-side grids installed in adjacent areas, having 20 measurement points each. The objective of this work was to determinate whether soil physical and chemical properties within each plot were useful in order to explain the spatial variability of FCO2, supposedly influence by each management system. Most of the soil physical properties studied showed no significant differences between management systems, but on the other hand most of the chemical properties differed significantly when SB and G areas were compared. Total FCO2 was 31% higher in the SB plot (729 g CO2 m-2) when compared to the G plot (557 g CO2 m-2) throughout the 70-day period after harvest studied. This seems to be related to the sensitivity of FCO2 to precipitation events, as respiration in this plot increased significantly with increases in soil moisture. Despite temporal variability showed to be positively related to soil moisture, inside each management system there was a negative correlation (p<0.01) between the spatial changes of FCO2 and soil moisture (MS), R= -0.56 and -0.59 for G and SB respectively. There was no spatial correlation between FCO2 and soil organic matter in each management system, however, the humification index (Hum) of organic matter was negatively linear correlated with FCO2 in SB (R= -0.53, p<0.05) while positively linear correlated in G area (R=0.42, p<0.10). The multiple regression model analysis applied in each management system indicates that 63% of the FCO2 spatial variability in G managed could be explained by the model: FCO2(G)= 4.11978 -0.07672MS + 0.0045Hum +1.5352K -0.04474FWP, where K and FWP are potassium content and free water porosity in G area, respectively. On the other hand, 75% of FCO2 spatial variability in SB managed plot was accounted by the model: FCO2(SB) = 10.66774 -0.08624MS -0.02904Hum -2.42548K. Therefore, soil moisture, humification index of organic matter and potassium level were the main properties able to explain the spatial variability of FCO2 in both sugarcane management systems. This result indicates that changes in sugarcane management systems could result in changes on the soil chemical properties, mostly, especially humification index of organic matter. It seems that in conversion from slash-and-burn to green harvest system, free water porosity turns to be an important aspect in order to explain part of FCO2 spatial variability in green managed system.

[Spatial heterogeneity of soil salinization and its influencing factors in the typical region of the Mu Us Desert-Loess Plateau transitional zone, Northwest China].

PubMed

Zhao, Xuan; Hao, Qi Li; Sun, Ying Ying

2017-06-18

Studies on the spatial heterogeneity of saline soil in the Mu Us Desert-Loess Plateau transition zone are meaningful for understanding the mechanisms of land desertification. Taking the Mu Us Desert-Loess Plateau transition zone as the study subject, its spatial heterogeneity of pH, electrical conductivity (EC) and total salt content were analyzed by using on-site sampling followed with indoor analysis, classical statistical and geostatistical analysis. The results indicated that: 1) The average values of pH, EC and total salt content were 8.44, 5.13 mS·cm -1 and 21.66 g·kg -1 , respectively, and the coefficient of variation ranged from 6.9% to 73.3%. The pH was weakly variable, while EC and total salt content were moderately variable. 2) Results of semivariogram analysis showed that the most fitting model for spatial variability of all three indexes was spherical model. The C 0 /(C 0 +C) ratios of three indexes ranged from 8.6% to 14.3%, which suggested the spatial variability of all indexes had a strong spatial autocorrelation, and the structural factors played a more important role. The variation range decreased in order of pH

How important are coastal fronts to albacore tuna (Thunnus alalunga) habitat in the Northeast Pacific Ocean?

NASA Astrophysics Data System (ADS)

Nieto, Karen; Xu, Yi; Teo, Steven L. H.; McClatchie, Sam; Holmes, John

2017-01-01

We used satellite sea surface temperature (SST) data to characterize coastal fronts and then tested the effects of the fronts and other environmental variables on the distribution of the albacore tuna (Thunnus alalunga) catches in the coastal areas (from the coast to 200 nm offshore) of the Northeast Pacific Ocean. A boosted regression tree (BRT) model was used to explain the spatial and temporal patterns in albacore tuna catch per unit effort (CPUE) (1988-2011), using frontal features (distance to the front and temperature gradient), and other environmental variables like SST, surface chlorophyll concentration (chlorophyll), and geostrophic currents as explanatory variables. Based on over two decades of high-resolution data, the modeled results confirmed previous findings that albacore CPUE distribution is strongly influenced by SST and chlorophyll at fishing locations, and the distance of fronts from the coast (DFRONT-COAST), albeit with substantial seasonal and interannual variation. Albacore CPUEs were higher near warm, low chlorophyll oceanic waters, and near SST fronts. We performed sequential leave-one-year-out cross-validations for all years and found that the relationships in the BRT models were robust for the entire study period. Spatial distributions of model-predicted albacore CPUE were similar to observations, but the model was unable to predict very high CPUEs in some areas. These results help to explain previously observed variability in albacore CPUE and will likely help improve international fisheries management in the face of environmental changes.

Dynamical Mapping of Anopheles darlingi Densities in a Residual Malaria Transmission Area of French Guiana by Using Remote Sensing and Meteorological Data.

PubMed

Adde, Antoine; Roux, Emmanuel; Mangeas, Morgan; Dessay, Nadine; Nacher, Mathieu; Dusfour, Isabelle; Girod, Romain; Briolant, Sébastien

2016-01-01

Local variation in the density of Anopheles mosquitoes and the risk of exposure to bites are essential to explain the spatial and temporal heterogeneities in the transmission of malaria. Vector distribution is driven by environmental factors. Based on variables derived from satellite imagery and meteorological observations, this study aimed to dynamically model and map the densities of Anopheles darlingi in the municipality of Saint-Georges de l'Oyapock (French Guiana). Longitudinal sampling sessions of An. darlingi densities were conducted between September 2012 and October 2014. Landscape and meteorological data were collected and processed to extract a panel of variables that were potentially related to An. darlingi ecology. Based on these data, a robust methodology was formed to estimate a statistical predictive model of the spatial-temporal variations in the densities of An. darlingi in Saint-Georges de l'Oyapock. The final cross-validated model integrated two landscape variables-dense forest surface and built surface-together with four meteorological variables related to rainfall, evapotranspiration, and the minimal and maximal temperatures. Extrapolation of the model allowed the generation of predictive weekly maps of An. darlingi densities at a resolution of 10-m. Our results supported the use of satellite imagery and meteorological data to predict malaria vector densities. Such fine-scale modeling approach might be a useful tool for health authorities to plan control strategies and social communication in a cost-effective, targeted, and timely manner.

Spatial variability of soil salinity in coastal saline soil at different scales in the Yellow River Delta, China.

PubMed

Wang, Zhuoran; Zhao, Gengxing; Gao, Mingxiu; Chang, Chunyan

2017-02-01

The objectives of this study were to explore the spatial variability of soil salinity in coastal saline soil at macro, meso and micro scales in the Yellow River delta, China. Soil electrical conductivities (ECs) were measured at 0-15, 15-30, 30-45 and 45-60 cm soil depths at 49 sampling sites during November 9 to 11, 2013. Soil salinity was converted from soil ECs based on laboratory analyses. Our results indicated that at the macro scale, soil salinity was high with strong variability in each soil layer, and the content increased and the variability weakened with increasing soil depth. From east to west in the region, the farther away from the sea, the lower the soil salinity was. The degrees of soil salinization in three deeper soil layers are 1.14, 1.24 and 1.40 times higher than that in the surface soil. At the meso scale, the sequence of soil salinity in different topographies, soil texture and vegetation decreased, respectively, as follows: depression >flatland >hillock >batture; sandy loam >light loam >medium loam >heavy loam >clay; bare land >suaeda salsa >reed >cogongrass >cotton >paddy >winter wheat. At the micro scale, soil salinity changed with elevation in natural micro-topography and with anthropogenic activities in cultivated land. As the study area narrowed down to different scales, the spatial variability of soil salinity weakened gradually in cultivated land and salt wasteland except the bare land.

The correspondence of surface climate parameters with satellite and terrain data

NASA Technical Reports Server (NTRS)

Dozier, Jeff; Davis, Frank

1987-01-01

One of the goals of the research was to develop a ground sampling stragegy for calibrating remotely sensed measurements of surface climate parameters. The initial sampling strategy involved the stratification of the terrain based on important ancillary surface variables such as slope, exposure, insolation, geology, drainage, fire history, etc. For a spatially heterogeneous population, sampling error is reduced and efficiency increased by stratification of the landscape into more homogeneous sub-areas and by employing periodic random spacing of samples. These concepts were applied in the initial stratification of the study site for the purpose of locating and allocating instrumentation.

Accuracy and Spatial Variability in GPS Surveying for Landslide Mapping on Road Inventories at a Semi-Detailed Scale: the Case in Colombia

NASA Astrophysics Data System (ADS)

Murillo Feo, C. A.; Martnez Martinez, L. J.; Correa Muñoz, N. A.

2016-06-01

The accuracy of locating attributes on topographic surfaces when, using GPS in mountainous areas, is affected by obstacles to wave propagation. As part of this research on the semi-automatic detection of landslides, we evaluate the accuracy and spatial distribution of the horizontal error in GPS positioning in the tertiary road network of six municipalities located in mountainous areas in the department of Cauca, Colombia, using geo-referencing with GPS mapping equipment and static-fast and pseudo-kinematic methods. We obtained quality parameters for the GPS surveys with differential correction, using a post-processing method. The consolidated database underwent exploratory analyses to determine the statistical distribution, a multivariate analysis to establish relationships and partnerships between the variables, and an analysis of the spatial variability and calculus of accuracy, considering the effect of non-Gaussian distribution errors. The evaluation of the internal validity of the data provide metrics with a confidence level of 95% between 1.24 and 2.45 m in the static-fast mode and between 0.86 and 4.2 m in the pseudo-kinematic mode. The external validity had an absolute error of 4.69 m, indicating that this descriptor is more critical than precision. Based on the ASPRS standard, the scale obtained with the evaluated equipment was in the order of 1:20000, a level of detail expected in the landslide-mapping project. Modelling the spatial variability of the horizontal errors from the empirical semi-variogram analysis showed predictions errors close to the external validity of the devices.

Intercomparison Between in situ and AVHRR Polar Pathfinder-Derived Surface Albedo over Greenland

NASA Technical Reports Server (NTRS)

Stroeve, Julienne C.; Box, Jason E.; Fowler, Charles; Haran, Terence; Key, Jeffery

2001-01-01

The Advanced Very High Resolution (AVHRR) Polar Pathfinder Data (APP) provides the first long time series of consistent, calibrated surface albedo and surface temperature data for the polar regions. Validations of these products have consisted of individual studies that analyzed algorithm performance for limited regions and or time periods. This paper reports on comparisons made between the APP-derived surface albedo and that measured at fourteen automatic weather stations (AWS) around the Greenland ice sheet from January 1997 to August 1998. Results show that satellite-derived surface albedo values are on average 10% less than those measured by the AWS stations. However, the station measurements tend to be biased high by about 4% and thus the differences in absolute albedo may be less (e.g. 6%). In regions of the ice sheet where the albedo variability is small, such as the dry snow facies, the APP albedo uncertainty exceeds the natural variability. Further work is needed to improve the absolute accuracy of the APP-derived surface albedo. Even so, the data provide temporally and spatially consistent estimates of the Greenland ice sheet albedo.

Observed seasonal and interannual variability of the near-surface thermal structure of the Arabian Sea Warm Pool

NASA Astrophysics Data System (ADS)

Rao, R. R.; Ramakrishna, S. S. V. S.

2017-06-01

The observed seasonal and interannual variability of near-surface thermal structure of the Arabian Sea Warm Pool (ASWP) is examined utilizing a reanalysis data set for the period 1990-2008. During a year, the ASWP progressively builds from February, reaches its peak by May only in the topmost 60 m water column. The ASWP Index showed a strong seasonal cycle with distinct interannual signatures. The years with higher (lower) sea surface temperature (SST) and larger (smaller) spatial extent are termed as strong (weak) ASWP years. The differences in the magnitude and spatial extent of thermal structure between the strong and weak ASWP regimes are seen more prominently in the topmost 40 m water column. The heat content values with respect to 28 °C isotherm (HC28) are relatively higher (lower) during strong (weak) ASWP years. Even the secondary peak in HC28 seen during the preceding November-December showed higher (lower) magnitude during the strong ASWP (weak) years. The influence of the observed variability in the surface wind field, surface net air-sea heat flux, near-surface mixed layer thickness, sea surface height (SSH) anomaly, depth of 20 °C isotherm and barrier layer thickness is examined to explain the observed differences in the near-surface thermal structure of the ASWP between strong and weak regimes. The surface wind speed is much weaker in particular during the preceding October and February-March corresponding to the strong ASWP years when compared to those of the weak ASWP years implying its important role. Both stronger winter cooling during weak ASWP years and stronger pre-monsoon heating during strong ASWP years through the surface air-sea heat fluxes contribute to the observed sharp contrast in the magnitudes of both the regimes of the ASWP. The upwelling Rossby wave during the preceding summer monsoon, post-monsoon and winter seasons is stronger corresponding to the weak ASWP regime when compared to the strong ASWP regime resulting in greater cooling of the near-surface layers during the summer monsoon season of the preceding year. On the other hand, the downwelling Rossby wave is stronger during pre-monsoon months during the strong ASWP regime when compared to weak ASWP regime leading to lesser cooling during strong ASWP regime.

Estimation of the temperature spatial variability in confined spaces based on thermal imaging

NASA Astrophysics Data System (ADS)

Augustyn, Grzegorz; Jurasz, Jakub; Jurczyk, Krzysztof; Korbiel, Tomasz; Mikulik, Jerzy; Pawlik, Marcin; Rumin, Rafał

2017-11-01

In developed countries the salaries of office workers are several times higher than the total cost of maintaining and operating the building. Therefore even a small improvement in human work productivity and performance as a result of enhancing the quality of their work environment may lead to a meaningful economic benefits. The air temperature is the most commonly used indicator in assessing the indoor environment quality. What is more, it is well known that thermal comfort has the biggest impact on employees performance and their ability to work efficiently. In majority of office buildings, indoor temperature is managed by heating, ventilation and air conditioning (HVAC) appliances. However the way how they are currently managed and controlled leads to the nonhomogeneous distribution of temperature in certain space. An approach to determining the spatial variability of temperature in confined spaces was introduced based on thermal imaging temperature measurements. The conducted research and obtained results enabled positive verification of the method and creation of surface plot illustrating the temperature variability.

Trans-Pacific transport and evolution of aerosols: evaluation of quasi-global WRF-Chem simulation with multiple observations

NASA Astrophysics Data System (ADS)

Hu, Zhiyuan; Zhao, Chun; Huang, Jianping; Leung, L. Ruby; Qian, Yun; Yu, Hongbin; Huang, Lei; Kalashnikova, Olga V.

2016-05-01

A fully coupled meteorology-chemistry model (WRF-Chem, the Weather Research and Forecasting model coupled with chemistry) has been configured to conduct quasi-global simulation for 5 years (2010-2014) and evaluated with multiple observation data sets for the first time. The evaluation focuses on the simulation over the trans-Pacific transport region using various reanalysis and observational data sets for meteorological fields and aerosol properties. The simulation generally captures the overall spatial and seasonal variability of satellite retrieved aerosol optical depth (AOD) and absorbing AOD (AAOD) over the Pacific that is determined by the outflow of pollutants and dust and the emissions of marine aerosols. The assessment of simulated extinction Ångström exponent (EAE) indicates that the model generally reproduces the variability of aerosol size distributions as seen by satellites. In addition, the vertical profile of aerosol extinction and its seasonality over the Pacific are also well simulated. The difference between the simulation and satellite retrievals can be mainly attributed to model biases in estimating marine aerosol emissions as well as the satellite sampling and retrieval uncertainties. Compared with the surface measurements over the western USA, the model reasonably simulates the observed magnitude and seasonality of dust, sulfate, and nitrate surface concentrations, but significantly underestimates the peak surface concentrations of carbonaceous aerosol likely due to model biases in the spatial and temporal variability of biomass burning emissions and secondary organic aerosol (SOA) production. A sensitivity simulation shows that the trans-Pacific transported dust, sulfate, and nitrate can make significant contribution to surface concentrations over the rural areas of the western USA, while the peaks of carbonaceous aerosol surface concentrations are dominated by the North American emissions. Both the retrievals and simulation show small interannual variability of aerosol characteristics for 2010-2014 averaged over three Pacific sub-regions. The evaluation in this study demonstrates that the WRF-Chem quasi-global simulation can be used for investigating trans-Pacific transport of aerosols and providing reasonable inflow chemical boundaries for the western USA, allowing one to further understand the impact of transported pollutants on the regional air quality and climate with high-resolution nested regional modeling.

Eigenvector Spatial Filtering Regression Modeling of Ground PM2.5 Concentrations Using Remotely Sensed Data.

PubMed

Zhang, Jingyi; Li, Bin; Chen, Yumin; Chen, Meijie; Fang, Tao; Liu, Yongfeng

2018-06-11

This paper proposes a regression model using the Eigenvector Spatial Filtering (ESF) method to estimate ground PM 2.5 concentrations. Covariates are derived from remotely sensed data including aerosol optical depth, normal differential vegetation index, surface temperature, air pressure, relative humidity, height of planetary boundary layer and digital elevation model. In addition, cultural variables such as factory densities and road densities are also used in the model. With the Yangtze River Delta region as the study area, we constructed ESF-based Regression (ESFR) models at different time scales, using data for the period between December 2015 and November 2016. We found that the ESFR models effectively filtered spatial autocorrelation in the OLS residuals and resulted in increases in the goodness-of-fit metrics as well as reductions in residual standard errors and cross-validation errors, compared to the classic OLS models. The annual ESFR model explained 70% of the variability in PM 2.5 concentrations, 16.7% more than the non-spatial OLS model. With the ESFR models, we performed detail analyses on the spatial and temporal distributions of PM 2.5 concentrations in the study area. The model predictions are lower than ground observations but match the general trend. The experiment shows that ESFR provides a promising approach to PM 2.5 analysis and prediction.

Diurnal Cycles of High Resolution Land Surface Temperatures (LSTs) Determined from UAV Platforms Across a Range of Surface Types

NASA Astrophysics Data System (ADS)

McCabe, M.; Rosas Aguilar, J.; Parkes, S. D.; Aragon, B.

2017-12-01

Observation of land surface temperature (LST) has many practical uses, from studying boundary layer dynamics and land-atmosphere coupling, to investigating surface properties such as soil moisture status, heat stress and surface heat fluxes. Typically, LST is observed via satellite based sensors such as LandSat or via point measurements using IR radiometers. These measurements provide either good spatial coverage and resolution or good temporal coverage. However, neither are able to provide the needed spatial and temporal resolution for many of the research applications described above. Technological developments in the use of Unmanned Aerial Vehicles (UAVs), together with small thermal frame cameras, has enabled a capacity to overcome this spatiotemporal constraint. Utilising UAV platforms to collect LST measurements across diurnal cycles provides an opportunity to study how meteorological and surface properties vary in both space and time. Here we describe the collection of LST data from a multi-rotor UAV across a study domain that is observed multiple times throughout the day. Flights over crops of Rhodes grass and alfalfa, along with a bare desert surface, were repeated with between 8 and 11 surveys covering the period from early morning to sunset. Analysis of the collected thermal imagery shows that the constructed LST maps illustrate a strong diurnal cycle consistent with expected trends, but with considerable spatial and temporal variability observed within and between the different domains. These results offer new insights into the dynamics of land surface behavior in both dry and wet soil conditions and at spatiotemporal scales that are unable to be replicated using traditional satellite platforms.

Integrating Map Algebra and Statistical Modeling for Spatio- Temporal Analysis of Monthly Mean Daily Incident Photosynthetically Active Radiation (PAR) over a Complex Terrain.

PubMed

Evrendilek, Fatih

2007-12-12

This study aims at quantifying spatio-temporal dynamics of monthly mean dailyincident photosynthetically active radiation (PAR) over a vast and complex terrain such asTurkey. The spatial interpolation method of universal kriging, and the combination ofmultiple linear regression (MLR) models and map algebra techniques were implemented togenerate surface maps of PAR with a grid resolution of 500 x 500 m as a function of fivegeographical and 14 climatic variables. Performance of the geostatistical and MLR modelswas compared using mean prediction error (MPE), root-mean-square prediction error(RMSPE), average standard prediction error (ASE), mean standardized prediction error(MSPE), root-mean-square standardized prediction error (RMSSPE), and adjustedcoefficient of determination (R² adj. ). The best-fit MLR- and universal kriging-generatedmodels of monthly mean daily PAR were validated against an independent 37-year observeddataset of 35 climate stations derived from 160 stations across Turkey by the Jackknifingmethod. The spatial variability patterns of monthly mean daily incident PAR were moreaccurately reflected in the surface maps created by the MLR-based models than in thosecreated by the universal kriging method, in particular, for spring (May) and autumn(November). The MLR-based spatial interpolation algorithms of PAR described in thisstudy indicated the significance of the multifactor approach to understanding and mappingspatio-temporal dynamics of PAR for a complex terrain over meso-scales.

SST Variation Due to Interactive Convective-Radiative Processes

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Shie, C.-L.; Johnson, D.; Simpson, J.; Li, X.; Sui, C.-H.

2000-01-01

The recent linking of Cloud-Resolving Models (CRMs) to Ocean-Mixed Layer (OML) models has provided a powerful new means of quantifying the role of cloud systems in ocean-atmosphere coupling. This is due to the fact that the CRM can better resolve clouds and cloud systems and allow for explicit cloud-radiation interaction. For example, Anderson (1997) applied an atmospheric forcing associated with a CRM simulated squall line to a 3-D OML model (one way or passive interaction). His results suggested that the spatial variability resulting from the squall forcing can last at least 24 hours when forced with otherwise spatially uniform fluxes. In addition, the sea surface salinity (SSS) variability continuously decreased following the forcing, while some of the SST variability remained when a diurnal mixed layer capped off the surface structure. The forcing used in the OML model, however, focused on shorter time (8 h) and smaller spatial scales (100-120 km). In this study, the 3-D Goddard Cumulus Ensemble Model (GCE; 512 x 512 x 23 cu km, 2-km horizontal resolution) is used to simulate convective active episodes occurring in the Western Pacific warm pool and Eastern Atlantic regions. The model is integrated for seven days, and the simulated results are coupled to an OML model to better understand the impact of precipitation and changes in the planetary boundary layer upon SST variation. We will specifically examine and compare the results of linking the OML model with various spatially-averaged outputs from GCE simulations (i.e., 2 km vs. 10-50 km horizontal resolutions), in order to help understand the SST sensitivity to multi-scale influences. This will allow us to assess the importance of explicitly simulated deep and shallow clouds, as well as the subgrid-scale effects (in coarse-model runs) upon SST variation. Results using both 1-D and 2-D OML models will be evaluated to assess the effects of horizontal advection.

An Improved GRACE Terrestrial Water Storage Assimilation System For Estimating Large-Scale Soil Moisture and Shallow Groundwater

NASA Astrophysics Data System (ADS)

Girotto, M.; De Lannoy, G. J. M.; Reichle, R. H.; Rodell, M.

2015-12-01

The Gravity Recovery And Climate Experiment (GRACE) mission is unique because it provides highly accurate column integrated estimates of terrestrial water storage (TWS) variations. Major limitations of GRACE-based TWS observations are related to their monthly temporal and coarse spatial resolution (around 330 km at the equator), and to the vertical integration of the water storage components. These challenges can be addressed through data assimilation. To date, it is still not obvious how best to assimilate GRACE-TWS observations into a land surface model, in order to improve hydrological variables, and many details have yet to be worked out. This presentation discusses specific recent features of the assimilation of gridded GRACE-TWS data into the NASA Goddard Earth Observing System (GEOS-5) Catchment land surface model to improve soil moisture and shallow groundwater estimates at the continental scale. The major recent advancements introduced by the presented work with respect to earlier systems include: 1) the assimilation of gridded GRACE-TWS data product with scaling factors that are specifically derived for data assimilation purposes only; 2) the assimilation is performed through a 3D assimilation scheme, in which reasonable spatial and temporal error standard deviations and correlations are exploited; 3) the analysis step uses an optimized calculation and application of the analysis increments; 4) a poor-man's adaptive estimation of a spatially variable measurement error. This work shows that even if they are characterized by a coarse spatial and temporal resolution, the observed column integrated GRACE-TWS data have potential for improving our understanding of soil moisture and shallow groundwater variations.

The tropical Pacific as a key pacemaker of the variable rates of global warming

NASA Astrophysics Data System (ADS)

Kosaka, Yu; Xie, Shang-Ping

2016-09-01

Global mean surface temperature change over the past 120 years resembles a rising staircase: the overall warming trend was interrupted by the mid-twentieth-century big hiatus and the warming slowdown since about 1998. The Interdecadal Pacific Oscillation has been implicated in modulations of global mean surface temperatures, but which part of the mode drives the variability in warming rates is unclear. Here we present a successful simulation of the global warming staircase since 1900 with a global ocean-atmosphere coupled model where tropical Pacific sea surface temperatures are forced to follow the observed evolution. Without prescribed tropical Pacific variability, the same model, on average, produces a continual warming trend that accelerates after the 1960s. We identify four events where the tropical Pacific decadal cooling markedly slowed down the warming trend. Matching the observed spatial and seasonal fingerprints we identify the tropical Pacific as a key pacemaker of the warming staircase, with radiative forcing driving the overall warming trend. Specifically, tropical Pacific variability amplifies the first warming epoch of the 1910s-1940s and determines the timing when the big hiatus starts and ends. Our method of removing internal variability from the observed record can be used for real-time monitoring of anthropogenic warming.

Fine Particulate Matter Predictions Using High Resolution Aerosol Optical Depth (AOD) Retrievals

NASA Technical Reports Server (NTRS)

Chudnovsky, Alexandra A.; Koutrakis, Petros; Kloog, Itai; Melly, Steven; Nordio, Francesco; Lyapustin, Alexei; Wang, Jujie; Schwartz, Joel

2014-01-01

To date, spatial-temporal patterns of particulate matter (PM) within urban areas have primarily been examined using models. On the other hand, satellites extend spatial coverage but their spatial resolution is too coarse. In order to address this issue, here we report on spatial variability in PM levels derived from high 1 km resolution AOD product of Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm developed for MODIS satellite. We apply day-specific calibrations of AOD data to predict PM(sub 2.5) concentrations within the New England area of the United States. To improve the accuracy of our model, land use and meteorological variables were incorporated. We used inverse probability weighting (IPW) to account for nonrandom missingness of AOD and nested regions within days to capture spatial variation. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance among others. Out-of-sample "ten-fold" cross-validation was used to quantify the accuracy of model predictions. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations, with out-of- sample R(sub 2) of 0.89. Furthermore, our study shows that the model captures the pollution levels along highways and many urban locations thereby extending our ability to investigate the spatial patterns of urban air quality, such as examining exposures in areas with high traffic. Our results also show high accuracy within the cities of Boston and New Haven thereby indicating that MAIAC data can be used to examine intra-urban exposure contrasts in PM(sub 2.5) levels.

Effective soil hydraulic properties in space and time: some field data analysis and modeling concepts

USDA-ARS?s Scientific Manuscript database

Soil hydraulic properties, which control surface fluxes and storage of water and chemicals in the soil profile, vary in space and time. Spatial variability above the measurement scale (e.g., soil area of 0.07 m2 or support volume of 14 L) must be upscaled appropriately to determine “effective” hydr...

Remote sensing-based predictors improve distribution models of rare, early successional and boradleaf tree species in Utah

Treesearch

N. E. Zimmermann; T. C. Edwards; G. G. Moisen; T. S. Frescino; J. A. Blackard

2007-01-01

Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species...

NASA Cold Land Processes Experiment (CLPX 2002/03): Atmospheric analyses datasets

Treesearch

Glen E. Liston; Daniel L. Birkenheuer; Christopher A. Hiemstra; Donald W. Cline; Kelly Elder

2008-01-01

This paper describes the Local Analysis and Prediction System (LAPS) and the 20-km horizontal grid version of the Rapid Update Cycle (RUC20) atmospheric analyses datasets, which are available as part of the Cold Land Processes Field Experiment (CLPX) data archive. The LAPS dataset contains spatially and temporally continuous atmospheric and surface variables over...

Utility of an image-based canopy reflectance modeling tool for remote estimation and LAI and leaf chlorophyll content at regional scales

USDA-ARS?s Scientific Manuscript database

Radiance data recorded by remote sensors function as a unique source for monitoring the terrestrial biosphere and vegetation dynamics at a range of spatial and temporal scales. A key challenge is to relate the remote sensing signal to critical variables describing land surface vegetation canopies su...

Temporal and Spatial Variability of the Ras Al-Hadd Jet/Front in the Northwest Arabian Sea

NASA Astrophysics Data System (ADS)

Al Shaqsi, Hilal Mohamed Said

Thirteen years of 1.1 km resolution daily satellites remote sensing sea surface temperature datasets (2002-2014), sea surface winds, sea surface height, Argo floats, daily three-hour interval wind datasets, and hourly records of oceanography physical parameters from mooring current meters were processed and analyzed to investigate the dynamics, temporal and spatial variability of the Ras Al-Hadd Jet off the northwest Arabian Sea. Cayula and Cornillon single image edge detection algorithm was used to detect these thermal fronts. The Ras Al-Hadd thermal front was found to have two seasonal peaks. The first peak occurred during the intensified southwest monsoon period (July/August), while the second peak was clearly observed during the transitional period or the Post-Southwest monsoon (September-October). Interannual and intraseasonal variability showed the occurrence of the Ras Al-Hadd thermal fronts in the northwest Arabian Sea. The southwest monsoon winds, the Somalia Current, the East Arabian Current, and the warmer high salinity waters from the Sea of Oman are the main factors influencing the creation of the Ras Al-Hadd Jet. Based on direct observations, current velocity in the Cape Ras Al-Hadd Jet exceeded 120 cms-1, and the wind speed was over 12 ms-1 during the southwest monsoon seasons. The mean width and the mean length of the Jet were approximately 40 km and 260 km, respectively. Neither the winter monsoon, nor the Pre-Southwest monsoon seasons showed signs of the Ras Al-Hadd Jet or fronts in the northwest Arabian Sea.

Spatial variability of turbulent fluxes in the roughness sublayer of an even-aged pine forest

USGS Publications Warehouse

Katul, G.; Hsieh, C.-I.; Bowling, D.; Clark, K.; Shurpali, N.; Turnipseed, A.; Albertson, J.; Tu, K.; Hollinger, D.; Evans, B. M.; Offerle, B.; Anderson, D.; Ellsworth, D.; Vogel, C.; Oren, R.

1999-01-01

The spatial variability of turbulent flow statistics in the roughness sublayer (RSL) of a uniform even-aged 14 m (= h) tall loblolly pine forest was investigated experimentally. Using seven existing walkup towers at this stand, high frequency velocity, temperature, water vapour and carbon dioxide concentrations were measured at 15.5 m above the ground surface from October 6 to 10 in 1997. These seven towers were separated by at least 100 m from each other. The objective of this study was to examine whether single tower turbulence statistics measurements represent the flow properties of RSL turbulence above a uniform even-aged managed loblolly pine forest as a best-case scenario for natural forested ecosystems. From the intensive space-time series measurements, it was demonstrated that standard deviations of longitudinal and vertical velocities (??(u), ??(w)) and temperature (??(T)) are more planar homogeneous than their vertical flux of momentum (u(*)2) and sensible heat (H) counterparts. Also, the measured H is more horizontally homogeneous when compared to fluxes of other scalar entities such as CO2 and water vapour. While the spatial variability in fluxes was significant (> 15%), this unique data set confirmed that single tower measurements represent the 'canonical' structure of single-point RSL turbulence statistics, especially flux-variance relationships. Implications to extending the 'moving-equilibrium' hypothesis for RSL flows are discussed. The spatial variability in all RSL flow variables was not constant in time and varied strongly with spatially averaged friction velocity u(*), especially when u(*) was small. It is shown that flow properties derived from two-point temporal statistics such as correlation functions are more sensitive to local variability in leaf area density when compared to single point flow statistics. Specifically, that the local relationship between the reciprocal of the vertical velocity integral time scale (I(w)) and the arrival frequency of organized structures (u??/h) predicted from a mixing-layer theory exhibited dependence on the local leaf area index. The broader implications of these findings to the measurement and modelling of RSL flows are also discussed.

Modeling post-wildfire hydrological processes with ParFlow

NASA Astrophysics Data System (ADS)

Escobar, I. S.; Lopez, S. R.; Kinoshita, A. M.

2017-12-01

Wildfires alter the natural processes within a watershed, such as surface runoff, evapotranspiration rates, and subsurface water storage. Post-fire hydrologic models are typically one-dimensional, empirically-based models or two-dimensional, conceptually-based models with lumped parameter distributions. These models are useful for modeling and predictions at the watershed outlet; however, do not provide detailed, distributed hydrologic processes at the point scale within the watershed. This research uses ParFlow, a three-dimensional, distributed hydrologic model to simulate post-fire hydrologic processes by representing the spatial and temporal variability of soil burn severity (via hydrophobicity) and vegetation recovery. Using this approach, we are able to evaluate the change in post-fire water components (surface flow, lateral flow, baseflow, and evapotranspiration). This work builds upon previous field and remote sensing analysis conducted for the 2003 Old Fire Burn in Devil Canyon, located in southern California (USA). This model is initially developed for a hillslope defined by a 500 m by 1000 m lateral extent. The subsurface reaches 12.4 m and is assigned a variable cell thickness to explicitly consider soil burn severity throughout the stages of recovery and vegetation regrowth. We consider four slope and eight hydrophobic layer configurations. Evapotranspiration is used as a proxy for vegetation regrowth and is represented by the satellite-based Simplified Surface Energy Balance (SSEBOP) product. The pre- and post-fire surface runoff, subsurface storage, and surface storage interactions are evaluated at the point scale. Results will be used as a basis for developing and fine-tuning a watershed-scale model. Long-term simulations will advance our understanding of post-fire hydrological partitioning between water balance components and the spatial variability of watershed processes, providing improved guidance for post-fire watershed management. In reference to the presenter, Isabel Escobar: Research is funded by the NASA-DIRECT STEM Program. Travel expenses for this presentation is funded by CSU-LSAMP. CSU-LSAMP is supported by the National Science Foundation under Grant # HRD-1302873 and the CSU Office of Chancellor.

Estimating Long Term Surface Soil Moisture in the GCIP Area From Satellite Microwave Observations

NASA Technical Reports Server (NTRS)

Owe, Manfred; deJeu, Vrije; VandeGriend, Adriaan A.

2000-01-01

Soil moisture is an important component of the water and energy balances of the Earth's surface. Furthermore, it has been identified as a parameter of significant potential for improving the accuracy of large-scale land surface-atmosphere interaction models. However, accurate estimates of surface soil moisture are often difficult to make, especially at large spatial scales. Soil moisture is a highly variable land surface parameter, and while point measurements are usually accurate, they are representative only of the immediate site which was sampled. Simple averaging of point values to obtain spatial means often leads to substantial errors. Since remotely sensed observations are already a spatially averaged or areally integrated value, they are ideally suited for measuring land surface parameters, and as such, are a logical input to regional or larger scale land process models. A nine-year database of surface soil moisture is being developed for the Central United States from satellite microwave observations. This region forms much of the GCIP study area, and contains most of the Mississippi, Rio Grande, and Red River drainages. Daytime and nighttime microwave brightness temperatures were observed at a frequency of 6.6 GHz, by the Scanning Multichannel Microwave Radiometer (SMMR), onboard the Nimbus 7 satellite. The life of the SMMR instrument spanned from Nov. 1978 to Aug. 1987. At 6.6 GHz, the instrument provided a spatial resolution of approximately 150 km, and an orbital frequency over any pixel-sized area of about 2 daytime and 2 nighttime passes per week. Ground measurements of surface soil moisture from various locations throughout the study area are used to calibrate the microwave observations. Because ground measurements are usually only single point values, and since the time of satellite coverage does not always coincide with the ground measurements, the soil moisture data were used to calibrate a regional water balance for the top 1, 5, and 10 cm surface layers in order to interpolate daily surface moisture values. Such a climate-based approach is often more appropriate for estimating large-area spatially averaged soil moisture because meteorological data are generally more spatially representative than isolated point measurements of soil moisture. Vegetation radiative transfer characteristics, such as the canopy transmissivity, were estimated from vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and the 37 GHz Microwave Polarization Difference Index (MPDI). Passive microwave remote sensing presents the greatest potential for providing regular spatially representative estimates of surface soil moisture at global scales. Real time estimates should improve weather and climate modelling efforts, while the development of historical data sets will provide necessary information for simulation and validation of long-term climate and global change studies.

The effect of surface electrical stimulation on swallowing in dysphagic Parkinson patients.

PubMed

Baijens, Laura W J; Speyer, Renée; Passos, Valeria Lima; Pilz, Walmari; Roodenburg, Nel; Clavé, Père

2012-12-01

Surface electrical stimulation has been applied on a large scale to treat oropharyngeal dysphagia. Patients suffering from oropharyngeal dysphagia in the presence of Parkinson's disease have been treated with surface electrical stimulation. Because of controversial reports on this treatment, a pilot study was set up. This study describes the effects of a single session of surface electrical stimulation using different electrode positions in ten patients with idiopathic Parkinson's disease (median Hoehn and Yahr score: II) and oropharyngeal dysphagia compared to ten age- and gender-matched healthy control subjects during videofluoroscopy of swallowing. Three different electrode positions were applied in random order per subject. For each electrode position, the electrical current was respectively turned "on" and "off" in random order. Temporal, spatial, and visuoperceptual variables were scored by experienced raters who were blinded to the group, electrode position, and status (on/off) of the electrical current. Interrater and interrater reliabilities were calculated. Only a few significant effects of a single session of surface electrical stimulation using different electrode positions in dysphagic Parkinson patients could be observed in this study. Furthermore, significant results for temporal and spatial variables were found regardless of the status of the electrical current in both groups suggesting placebo effects. Following adjustment for electrical current status as well as electrode positions (both not significant, P > 0.05) in the statistical model, significant group differences between Parkinson patients and healthy control subjects emerged. Further studies are necessary to evaluate the potential therapeutic effect and mechanism of electrical stimulation in dysphagic patients with Parkinson's disease.

spads 1.0: a toolbox to perform spatial analyses on DNA sequence data sets.

PubMed

Dellicour, Simon; Mardulyn, Patrick

2014-05-01

SPADS 1.0 (for 'Spatial and Population Analysis of DNA Sequences') is a population genetic toolbox for characterizing genetic variability within and among populations from DNA sequences. In view of the drastic increase in genetic information available through sequencing methods, spads was specifically designed to deal with multilocus data sets of DNA sequences. It computes several summary statistics from populations or groups of populations, performs input file conversions for other population genetic programs and implements locus-by-locus and multilocus versions of two clustering algorithms to study the genetic structure of populations. The toolbox also includes two MATLAB and r functions, GDISPAL and GDIVPAL, to display differentiation and diversity patterns across landscapes. These functions aim to generate interpolating surfaces based on multilocus distance and diversity indices. In the case of multiple loci, such surfaces can represent a useful alternative to multiple pie charts maps traditionally used in phylogeography to represent the spatial distribution of genetic diversity. These coloured surfaces can also be used to compare different data sets or different diversity and/or distance measures estimated on the same data set. © 2013 John Wiley & Sons Ltd.

The Effect of Topographic Shadowing by Ice on Irradiance in the Greenland Ice Sheet Ablation Zone

NASA Astrophysics Data System (ADS)

Leidman, S. Z.; Rennermalm, A. K.; Ryan, J.; Cooper, M. G.; Smith, L. C.

2017-12-01

Accurately predicting runoff contributions to global sea level rise requires more refined surface mass balance (SMB) models of the Greenland Ice Sheet (GrIS). Topographic shadowing has shown to be important in the SMB of snow-covered regions, yet SMB models for the GrIS generally ignore how surface topography affects spatial variability of incoming solar radiation on a surface. In the ablation zone of Southwest Greenland, deeply incised supraglacial drainage features, fracturing, and large-scale bed deformation result in extensive areas of rough surface topography. This topography blocks direct radiation such that shadowed areas receive less energy for melting while other topographic features such as peaks recieve more energy. In this study, we quantify how shadowing from local topography features changes incoming solar radiation. We apply the ArcGIS Pro Solar Radiation Toolset to calculate the direct and diffuse irradiance in sunlit and shadowed areas by determining the sun's movement for every half hour increment of 2016. Multiple digital elevation models (DEMs) with spatial resolutions ranging from 0.06 to 5m were derived from fixed wing and quadcopter UAV imagery collected in summer 2016 and the ArcticDEM dataset. Our findings show that shadowing significantly decreases irradiance compared to smoothed surfaces where local topography is removed. This decrease is exponentially proportional to the DEM pixel sized with 5m DEMs only able to capture a small percentage of the effect. Applying these calculations to the ArcticDEM to cover a larger study area indicates that decreases in irradiance are nonlinearly proportional to elevation with highly crevassed areas showing a larger effect from shadowing. Even so, shading at higher elevations reduces irradiance enough to result in several centimeters snow water equivalence (SWE) per year of over-prediction of runoff in SMB models. Furthermore, analysis of solar radiation products shows that shadowing predicts albedo variability far better than a range of variables derived from UAV imagery mosaics including slope, aspect, elevation, or the distance to dark surface features. In summary, implementation of the effect of shadowing on irradiance should therefore be considered for accurate surface mass balance calculations for the Greenland ice sheet.

The tropopause cold trap in the Australian Monsoon during STEP/AMEX 1987

NASA Technical Reports Server (NTRS)

Selkirk, Henry B.

1993-01-01

The relationship between deep convection and tropopause cold trap conditions is examined for the tropical northern Australia region during the 1986-87 summer monsoon season, emphasizing the Australia Monsoon Experiment (AMEX) period when the NASA Stratosphere-Troposphere Exchange Project (STEP) was being conducted. The factors related to the spatial and temporal variability of the cold point potential temperature (CPPT) are investigated. A framework is developed for describing the relationships among surface average equivalent potential temperature in the surface layer (AEPTSL) the height of deep convection, and stratosphere-troposphere exchange. The time-mean pattern of convection, large-scale circulation, and surface AEPTSL in the Australian monsoon and the evolution of the convective environment during the monsoon period and the extended transition season which preceded it are described. The time-mean fields of cold point level variables are examined and the statistical relationships between mean CPPT, surface AEPTSL, and deep convection are described. Day-to-day variations of CPPT are examined in terms of these time mean relationships.

Measuring the spatial variation in surface moisture on a coastal beach with an infra-red terrestrial laser scanner

NASA Astrophysics Data System (ADS)

Smit, Yvonne; Donker, Jasper; Ruessink, Gerben

2016-04-01

Coastal sand dunes provide essential protection against marine flooding. Consequently, dune erosion during severe storms has been studied intensively, resulting in well-developed erosion models for use in scientific and applied projects. Nowadays there is growing awareness that similarly advanced knowledge on dune recovery and growth is needed to predict future dune development. For this reason, aeolian sand transport from the beach into the dunes has to be investigated thoroughly. Surface moisture is a major factor limiting aeolian transport on sandy beaches. By increasing the velocity threshold for sediment entrainment, pick-up rates reduce and the fetch length increases. Conventional measurement techniques cannot adequately characterize the spatial and temporal distribution of surface moisture content required to study the effects on aeolian transport. Here we present a new method for detecting surface moisture at high temporal and spatial resolution using the RIEGL VZ-400 terrestrial laser scanner (TLS). Because this TLS operates at a wavelength near a water absorption band (1550 nm), TLS reflectance is an accurate parameter to measure surface soil moisture over its full range. Three days of intensive laser scanning were performed on a Dutch beach to illustrate the applicability of the TLS. Gravimetric soil moisture samples were used to calibrate the relation between reflectance and surface moisture. Results reveal a robust negative relation for the full range of possible surface moisture contents (0% - 25%). This relation holds to about 80 m from the TLS. Within this distance the TLS typically produces O(106-107) data points, which we averaged into soil moisture maps with a 0.25x0.25 m resolution. This grid size largely removes small moisture disturbances induced by, for example, footprints or tire tracks, while retaining larger scale trends. As the next step in our research, we will analyze the obtained maps to determine which processes affect the spatial and temporal surface-moisture variability.

Sources of Uncertainty in Predicting Land Surface Fluxes Using Diverse Data and Models

NASA Technical Reports Server (NTRS)

Dungan, Jennifer L.; Wang, Weile; Michaelis, Andrew; Votava, Petr; Nemani, Ramakrishma

2010-01-01

In the domain of predicting land surface fluxes, models are used to bring data from large observation networks and satellite remote sensing together to make predictions about present and future states of the Earth. Characterizing the uncertainty about such predictions is a complex process and one that is not yet fully understood. Uncertainty exists about initialization, measurement and interpolation of input variables; model parameters; model structure; and mixed spatial and temporal supports. Multiple models or structures often exist to describe the same processes. Uncertainty about structure is currently addressed by running an ensemble of different models and examining the distribution of model outputs. To illustrate structural uncertainty, a multi-model ensemble experiment we have been conducting using the Terrestrial Observation and Prediction System (TOPS) will be discussed. TOPS uses public versions of process-based ecosystem models that use satellite-derived inputs along with surface climate data and land surface characterization to produce predictions of ecosystem fluxes including gross and net primary production and net ecosystem exchange. Using the TOPS framework, we have explored the uncertainty arising from the application of models with different assumptions, structures, parameters, and variable definitions. With a small number of models, this only begins to capture the range of possible spatial fields of ecosystem fluxes. Few attempts have been made to systematically address the components of uncertainty in such a framework. We discuss the characterization of uncertainty for this approach including both quantifiable and poorly known aspects.

Surface Water and Energy Budgets for Sub-Saharan Africa in GFDL Coupled Climate Model

NASA Astrophysics Data System (ADS)

Tian, D.; Wood, E. F.; Vecchi, G. A.; Jia, L.; Pan, M.

2015-12-01

This study compare surface water and energy budget variables from the Geophysical Fluid Dynamics Laboratory (GFDL) FLOR models with the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), Princeton University Global Meteorological Forcing Dataset (PGF), and PGF-driven Variable Infiltration Capacity (VIC) model outputs, as well as available observations over the sub-Saharan Africa. The comparison was made for four configurations of the FLOR models that included FLOR phase 1 (FLOR-p1) and phase 2 (FLOR-p2) and two phases of flux adjusted versions (FLOR-FA-p1 and FLOR-FA-p2). Compared to p1, simulated atmospheric states in p2 were nudged to the Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. The seasonal cycle and annual mean of major surface water (precipitation, evapotranspiration, runoff, and change of storage) and energy variables (sensible heat, ground heat, latent heat, net solar radiation, net longwave radiation, and skin temperature) over a 34-yr period during 1981-2014 were compared in different regions in sub-Saharan Africa (West Africa, East Africa, and Southern Africa). In addition to evaluating the means in three sub-regions, empirical orthogonal functions (EOFs) analyses were conducted to compare both spatial and temporal characteristics of water and energy budget variables from four versions of GFDL FLOR, NCEP CFSR, PGF, and VIC outputs. This presentation will show how well each coupled climate model represented land surface physics and reproduced spatiotemporal characteristics of surface water and energy budget variables. We discuss what caused differences in surface water and energy budgets in land surface components of coupled climate model, climate reanalysis, and reanalysis driven land surface model. The comparisons will reveal whether flux adjustment and nudging would improve depiction of the surface water and energy budgets in coupled climate models.

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

Kumar, R.; Barth, M. C.; Nair, V. S.

This study examines differences in the surface black carbon (BC) aerosol loading between the Bay of Bengal (BoB) and the Arabian Sea (AS) and identifies dominant sources of BC in South Asia and surrounding regions during March-May 2006 (Integrated Campaign for Aerosols, Gases and Radiation Budget, ICARB) period. A total of 13 BC tracers are introduced in the Weather Research and Forecasting Model coupled with Chemistry to address these objectives. The model reproduced the temporal and spatial variability of BC distribution observed over the AS and the BoB during the ICARB ship cruise and captured spatial variability at the inlandmore » sites. In general, the model underestimates the observed BC mass concentrations. However, the model-observation discrepancy in this study is smaller compared to previous studies. Model results show that ICARB measurements were fairly well representative of the AS and the BoB during the pre-monsoon season. Elevated BC mass concentrations in the BoB are due to 5 times stronger influence of anthropogenic emissions on the BoB compared to the AS. Biomass burning in Burma also affects the BoB much more strongly than the AS. Results show that anthropogenic and biomass burning emissions, respectively, accounted for 60 and 37% of the average +/- standard deviation (representing spatial and temporal variability) BC mass concentration (1341 +/- 2353 ng m(-3)) in South Asia. BC emissions from residential (61 %) and industrial (23 %) sectors are the major anthropogenic sources, except in the Himalayas where vehicular emissions dominate. We find that regional-scale transport of anthropogenic emissions contributes up to 25% of BC mass concentrations in western and eastern India, suggesting that surface BC mass concentrations cannot be linked directly to the local emissions in different regions of South Asia.« less

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

Kumar, R.; Barth, M. C.; Nair, V. S.

This study examines differences in the surface black carbon (BC) aerosol loading between the Bay of Bengal (BoB) and the Arabian Sea (AS) and identifies dominant sources of BC in South Asia and surrounding regions during March–May 2006 (Integrated Campaign for Aerosols, Gases and Radiation Budget, ICARB) period. A total of 13 BC tracers are introduced in the Weather Research and Forecasting Model coupled with Chemistry to address these objectives. The model reproduced the temporal and spatial variability of BC distribution observed over the AS and the BoB during the ICARB ship cruise and captured spatial variability at the inlandmore » sites. In general, the model underestimates the observed BC mass concentrations. However, the model–observation discrepancy in this study is smaller compared to previous studies. Model results show that ICARB measurements were fairly well representative of the AS and the BoB during the pre-monsoon season. Elevated BC mass concentrations in the BoB are due to 5 times stronger influence of anthropogenic emissions on the BoB compared to the AS. Biomass burning in Burma also affects the BoB much more strongly than the AS. Results show that anthropogenic and biomass burning emissions, respectively, accounted for 60 and 37% of the average ± standard deviation (representing spatial and temporal variability) BC mass concentration (1341 ± 2353 ng m -3) in South Asia. BC emissions from residential (61%) and industrial (23%) sectors are the major anthropogenic sources, except in the Himalayas where vehicular emissions dominate. We find that regional-scale transport of anthropogenic emissions contributes up to 25% of BC mass concentrations in western and eastern India, suggesting that surface BC mass concentrations cannot be linked directly to the local emissions in different regions of South Asia.« less

MALIBU: A High Spatial Resolution Multi-Angle Imaging Unmanned Airborne System to Validate Satellite-derived BRDF/Albedo Products

NASA Astrophysics Data System (ADS)

Wang, Z.; Roman, M. O.; Pahlevan, N.; Stachura, M.; McCorkel, J.; Bland, G.; Schaaf, C.

2016-12-01

Albedo is a key climate forcing variable that governs the absorption of incoming solar radiation and its ultimate transfer to the atmosphere. Albedo contributes significant uncertainties in the simulation of climate changes; and as such, it is defined by the Global Climate Observing System (GCOS) as a terrestrial essential climate variable (ECV) required by global and regional climate and biogeochemical models. NASA's Goddard Space Flight Center's Multi AngLe Imaging Bidirectional Reflectance Distribution Function small-UAS (MALIBU) is part of a series of pathfinder missions to develop enhanced multi-angular remote sensing techniques using small Unmanned Aircraft Systems (sUAS). The MALIBU instrument package includes two multispectral imagers oriented at two different viewing geometries (i.e., port and starboard sides) capture vegetation optical properties and structural characteristics. This is achieved by analyzing the surface reflectance anisotropy signal (i.e., BRDF shape) obtained from the combination of surface reflectance from different view-illumination angles and spectral channels. Satellite measures of surface albedo from MODIS, VIIRS, and Landsat have been evaluated by comparison with spatially representative albedometer data from sparsely distributed flux towers at fixed heights. However, the mismatch between the footprint of ground measurements and the satellite footprint challenges efforts at validation, especially for heterogeneous landscapes. The BRDF (Bidirectional Reflectance Distribution Function) models of surface anisotropy have only been evaluated with airborne BRDF data over a very few locations. The MALIBU platform that acquires extremely high resolution sub-meter measures of surface anisotropy and surface albedo, can thus serve as an important source of reference data to enable global land product validation efforts, and resolve the errors and uncertainties in the various existing products generated by NASA and its national and international partners.

Spatial characterization of long-term hydrological change in the Arkavathy watershed adjacent to Bangalore, India

NASA Astrophysics Data System (ADS)

Penny, Gopal; Srinivasan, Veena; Dronova, Iryna; Lele, Sharachchandra; Thompson, Sally

2018-01-01

The complexity and heterogeneity of human water use over large spatial areas and decadal timescales can impede the understanding of hydrological change, particularly in regions with sparse monitoring of the water cycle. In the Arkavathy watershed in southern India, surface water inflows to major reservoirs decreased over a 40-year period during which urbanization, groundwater depletion, modification of the river network, and changes in agricultural practices also occurred. These multiple, interacting drivers combined with limited hydrological monitoring make attribution of the causes of diminishing water resources in the watershed challenging and impede effective policy responses. To mitigate these challenges, we developed a novel, spatially distributed dataset to understand hydrological change by characterizing the residual trends in surface water extent that remain after controlling for precipitation variations and comparing the trends with historical land use maps to assess human drivers of change. Using an automated classification approach with subpixel unmixing, we classified water extent in nearly 1700 man-made lakes, or tanks, in Landsat images from 1973 to 2010. The classification results compared well with a reference dataset of water extent of tanks (R2 = 0.95). We modeled the water extent of 42 clusters of tanks in a multiple regression on simple hydrological covariates (including precipitation) and time. Inter-annual variability in precipitation accounted for 63 % of the predicted variability in water extent. However, precipitation did not exhibit statistically significant trends in any part of the watershed. After controlling for precipitation variability, we found statistically significant temporal trends in water extent, both positive and negative, in 13 of the clusters. Based on a water balance argument, we inferred that these trends likely reflect a non-stationary relationship between precipitation and watershed runoff. Independently of precipitation, water extent increased in a region downstream of Bangalore, likely due to increased urban effluents, and declined in the northern portion of the Arkavathy. Comparison of the drying trends with land use indicated that they were most strongly associated with irrigated agriculture, sourced almost exclusively by groundwater. This suggests that groundwater abstraction was a major driver of hydrological change in this watershed. Disaggregating the watershed-scale hydrological response via remote sensing of surface water bodies over multiple decades yielded a spatially resolved characterization of hydrological change in an otherwise poorly monitored watershed. This approach presents an opportunity to understand hydrological change in heavily managed watersheds where surface water bodies integrate upstream runoff and can be delineated using satellite imagery.

Impacts of Climate Change on Surface Ozone and Intercontinental Ozone Pollution: A Multi-Model Study

NASA Technical Reports Server (NTRS)

Doherty, R. M.; Wild, O.; Shindell, D. T.; Zeng, G.; MacKenzie, I. A.; Collins, W. J.; Fiore, A. M.; Stevenson, D. S.; Dentener, F. J.; Schultz, M. G.;

Reconstructing satellite images to quantify spatially explicit land surface change caused by fires and succession: A demonstration in the Yukon River Basin of interior Alaska

USGS Publications Warehouse

Huang, Shengli; Jin, Suming; Dahal, Devendra; Chen, Xuexia; Young, Claudia; Liu, Heping; Liu, Shuguang

2013-01-01

Land surface change caused by fires and succession is confounded by many site-specific factors and requires further study. The objective of this study was to reveal the spatially explicit land surface change by minimizing the confounding factors of weather variability, seasonal offset, topography, land cover, and drainage. In a pilot study of the Yukon River Basin of interior Alaska, we retrieved Normalized Difference Vegetation Index (NDVI), albedo, and land surface temperature (LST) from a postfire Landsat image acquired on August 5th, 2004. With a Landsat reference image acquired on June 26th, 1986, we reconstructed NDVI, albedo, and LST of 1987–2004 fire scars for August 5th, 2004, assuming that these fires had not occurred. The difference between actual postfire and assuming-no-fire scenarios depicted the fires and succession impact. Our results demonstrated the following: (1) NDVI showed an immediate decrease after burning but gradually recovered to prefire levels in the following years, in which burn severity might play an important role during this process; (2) Albedo showed an immediate decrease after burning but then recovered and became higher than prefire levels; and (3) Most fires caused surface warming, but cooler surfaces did exist; time-since-fire affected the prefire and postfire LST difference but no absolute trend could be found. Our approach provided spatially explicit land surface change rather than average condition, enabling a better understanding of fires and succession impact on ecological consequences at the pixel level.

Factors Driving Potential Ammonia Oxidation in Canadian Arctic Ecosystems: Does Spatial Scale Matter?

PubMed Central

Banerjee, Samiran

2012-01-01

Ammonia oxidation is a major process in nitrogen cycling, and it plays a key role in nitrogen limited soil ecosystems such as those in the arctic. Although mm-scale spatial dependency of ammonia oxidizers has been investigated, little is known about the field-scale spatial dependency of aerobic ammonia oxidation processes and ammonia-oxidizing archaeal and bacterial communities, particularly in arctic soils. The purpose of this study was to explore the drivers of ammonia oxidation at the field scale in cryosols (soils with permafrost within 1 m of the surface). We measured aerobic ammonia oxidation potential (both autotrophic and heterotrophic) and functional gene abundance (bacterial amoA and archaeal amoA) in 279 soil samples collected from three arctic ecosystems. The variability associated with quantifying genes was substantially less than the spatial variability observed in these soils, suggesting that molecular methods can be used reliably evaluate spatial dependency in arctic ecosystems. Ammonia-oxidizing archaeal and bacterial communities and aerobic ammonia oxidation were spatially autocorrelated. Gene abundances were spatially structured within 4 m, whereas biochemical processes were structured within 40 m. Ammonia oxidation was driven at small scales (<1m) by moisture and total organic carbon, whereas gene abundance and other edaphic factors drove ammonia oxidation at medium (1 to 10 m) and large (10 to 100 m) scales. In these arctic soils heterotrophs contributed between 29 and 47% of total ammonia oxidation potential. The spatial scale for aerobic ammonia oxidation genes differed from potential ammonia oxidation, suggesting that in arctic ecosystems edaphic, rather than genetic, factors are an important control on ammonia oxidation. PMID:22081570

Correlation of gravestone decay and air quality 1960-2010

NASA Astrophysics Data System (ADS)

Mooers, H. D.; Carlson, M. J.; Harrison, R. M.; Inkpen, R. J.; Loeffler, S.

2017-03-01

Evaluation of spatial and temporal variability in surface recession of lead-lettered Carrara marble gravestones provides a quantitative measure of acid flux to the stone surfaces and is closely related to local land use and air quality. Correlation of stone decay, land use, and air quality for the period after 1960 when reliable estimates of atmospheric pollution are available is evaluated. Gravestone decay and SO2 measurements are interpolated spatially using deterministic and geostatistical techniques. A general lack of spatial correlation was identified and therefore a land-use-based technique for correlation of stone decay and air quality is employed. Decadally averaged stone decay is highly correlated with land use averaged spatially over an optimum radius of ≈7 km even though air quality, determined by records from the UK monitoring network, is not highly correlated with gravestone decay. The relationships among stone decay, air-quality, and land use is complicated by the relatively low spatial density of both gravestone decay and air quality data and the fact that air quality data is available only as annual averages and therefore seasonal dependence cannot be evaluated. However, acid deposition calculated from gravestone decay suggests that the deposition efficiency of SO2 has increased appreciably since 1980 indicating an increase in the SO2 oxidation process possibly related to reactions with ammonia.

The contrasting response of Hadley circulation to different meridional structure of sea surface temperature in CMIP5

NASA Astrophysics Data System (ADS)

Feng, Juan; Li, Jianping; Zhu, Jianlei; Li, Yang; Li, Fei

2018-02-01

The response of the Hadley circulation (HC) to the sea surface temperature (SST) is determined by the meridional structure of SST and varies according to the changing nature of this meridional structure. The capability of the models from the phase 5 of the Coupled Model Intercomparison Project (CMIP5) is utilized to represent the contrast response of the HC to different meridional SST structures. To evaluate the responses, the variations of HC and SST were linearly decomposed into two components: the equatorially asymmetric (HEA for HC, and SEA for SST) and equatorially symmetric (HES for HC, and SES for SST) components. The result shows that the climatological features of HC and tropical SST (including the spatial structures and amplitude) are reasonably simulated in all the models. However, the response contrast of HC to different SST meridional structures shows uncertainties among models. This may be due to the fact that the long-term temporal variabilities of HEA, HES, and SEA are limited reproduced in the models, although the spatial structures of their long-term variabilities are relatively reasonably simulated. These results indicate that the performance of the CMIP5 models to simulate long-term temporal variability of different meridional SST structures and related HC variations plays a fundamental role in the successful reproduction of the response of HC to different meridional SST structures.

Long-Term Trends, Variability and Extremes of In Situ Sea Surface Temperature Measured Along the Eastern Adriatic Coast and its Relationship to Hemispheric Processes

NASA Astrophysics Data System (ADS)

Grbec, Branka; Matić, Frano; Beg Paklar, Gordana; Morović, Mira; Popović, Ružica; Vilibić, Ivica

2018-02-01

This paper examines long-term series of in situ sea surface temperature (SST) data measured at nine coastal and one open sea stations along the eastern Adriatic Sea for the period 1959-2015. Monthly and yearly averages were used to document SST trends and variability, while clustering and connections to hemispheric indices were achieved by applying the Principal Component Analysis (PCA) and Self-Organizing Maps (SOM) method. Both PCA and SOM revealed the dominance of temporal changes with respect to the effects of spatial differences in SST anomalies, indicating the prevalence of hemispheric processes over local dynamics, such as bora wind spatial inhomogeneity. SST extremes were connected with blocking atmospheric patterns. A substantial warming between 1979 and 2015, in total exceeding 1 °C, was preceded by a period with a negative SST trend, implying strong multidecadal variability in the Adriatic. The strongest connection was found between yearly SST and the East Atlantic (EA) pattern, while North Atlantic Oscillation (NAO) and East Atlantic/West Russia (EAWR) patterns were found to also affect February SST values. Quantification of the Adriatic SST and their connection to hemispheric indices allow for more precise projections of future SST, considered to be rather important for Adriatic thermohaline circulation, biogeochemistry and fisheries, and sensitive to ongoing climate change.

Space and time variability of the surface color field in the northern Adriatic Sea

NASA Technical Reports Server (NTRS)

Barale, Vittorio; Mcclain, Charles R.; Malanotte-Rizzoli, Paola

1986-01-01

A time series of coastal zone color scanner images for the years 1979 and 1980 was used to observe the spatial and temporal variability of bio-optical processes and circulation patterns of the northern Adriatic Sea on monthly, seasonal, and interannual scales. The chlorophyll-like pigment concentrations derived from satellite data exhibited a high correlation with sea truth measurements performed during seven surveys in the summer of both years. Comparison of the mean pigment fields indicates a general increase in concentration values and larger scales of coastal features from 1979 to 1980. This variability may be linked to the different patterns of nutrient influx due to coastal runoff in the 2 years. The distribution of surface features is consistent with the general cyclonic circulation pattern. The pigment heterogeneity appears to be governed by fluctuations of freshwater discharge, while the dominant wind fields do not appear to have important direct effects. The Po River presents a plume spreading predominantly in a southeastern direction, with scales positively correlated with its outflow. The spatial scales of the western coastal layer, in contrast, are negatively correlated with this outflow and the plume scales. Both results are consistent with, and may be rationalized by, recent theoretical and experimental results involving a dynamical balance between nonlinear advection and bottom friction, with alternate predominance of one of the two effects.

Experimental Investigation of 2D thermal signature and 3D X-Ray Computed Tomography in contrasting Wettable and Water-Repellent Beads

NASA Astrophysics Data System (ADS)

Alsih, Abdulkareem; Flavel, Richard; McGrath, Gavan

2017-04-01

This study presents experimental results investigating spatial patterns of infiltration and evaporation in heterogeneous water repellent media. Infrared camera measurements and 3D X-ray computed tomography imaging was performed across wet-dry cycles on glass beads with engineered patches of water repellence. The imaging revealed spatial variability in infiltration and the redistribution of water in the media resulting in differences in relative evaporation rates during drying. It appears that the spatial organization of the heterogeneity play a role in the breakdown of water repellence at the interface of the two media. This suggests a potential mechanism for self-organization of repellency spatial patterns in field soils. At the interface between wettable and water repellent beads a lateral drying front propagates towards the wettable beads from the repellent beads. During this drying the relative surface temperatures change from a relatively cooler repellent media surface to a relatively cooler wettable media surface indicating the changes in evaporative water loss between the beads of varying water repellence. The lateral drying front was confirmed using thermography in a small-scale model of glass beads with chemically induced repellence and then subjected to 3D X-ray imaging. Pore-scale imaging identified the hydrology at the interface of the two media and at the drying front giving insights into the physics of water flow in water repellent soil.

Spatial Homogeneity of Bacterial Communities Associated with the Surface Mucus Layer of the Reef-Building Coral Acropora palmata.

PubMed

Kemp, Dustin W; Rivers, Adam R; Kemp, Keri M; Lipp, Erin K; Porter, James W; Wares, John P

2015-01-01

Coral surface mucus layer (SML) microbiota are critical components of the coral holobiont and play important roles in nutrient cycling and defense against pathogens. We sequenced 16S rRNA amplicons to examine the structure of the SML microbiome within and between colonies of the threatened Caribbean reef-building coral Acropora palmata in the Florida Keys. Samples were taken from three spatially distinct colony regions--uppermost (high irradiance), underside (low irradiance), and the colony base--representing microhabitats that vary in irradiance and water flow. Phylogenetic diversity (PD) values of coral SML bacteria communities were greater than surrounding seawater and lower than adjacent sediment. Bacterial diversity and community composition was consistent among the three microhabitats. Cyanobacteria, Bacteroidetes, Alphaproteobacteria, and Proteobacteria, respectively were the most abundant phyla represented in the samples. This is the first time spatial variability of the surface mucus layer of A. palmata has been studied. Homogeneity in the microbiome of A. palmata contrasts with SML heterogeneity found in other Caribbean corals. These findings suggest that, during non-stressful conditions, host regulation of SML microbiota may override diverse physiochemical influences induced by the topographical complexity of A. palmata. Documenting the spatial distribution of SML microbes is essential to understanding the functional roles these microorganisms play in coral health and adaptability to environmental perturbations.

External forcing as a metronome for Atlantic multidecadal variability

NASA Astrophysics Data System (ADS)

Otterå, Odd Helge; Bentsen, Mats; Drange, Helge; Suo, Lingling

2010-10-01

Instrumental records, proxy data and climate modelling show that multidecadal variability is a dominant feature of North Atlantic sea-surface temperature variations, with potential impacts on regional climate. To understand the observed variability and to gauge any potential for climate predictions it is essential to identify the physical mechanisms that lead to this variability, and to explore the spatial and temporal characteristics of multidecadal variability modes. Here we use a coupled ocean-atmosphere general circulation model to show that the phasing of the multidecadal fluctuations in the North Atlantic during the past 600 years is, to a large degree, governed by changes in the external solar and volcanic forcings. We find that volcanoes play a particularly important part in the phasing of the multidecadal variability through their direct influence on tropical sea-surface temperatures, on the leading mode of northern-hemisphere atmosphere circulation and on the Atlantic thermohaline circulation. We suggest that the implications of our findings for decadal climate prediction are twofold: because volcanic eruptions cannot be predicted a decade in advance, longer-term climate predictability may prove challenging, whereas the systematic post-eruption changes in ocean and atmosphere may hold promise for shorter-term climate prediction.

Radon emanation from the moon - Spatial and temporal variability.

NASA Technical Reports Server (NTRS)

Gorenstein, P.; Golub, L.; Bjorkholm, P.

1973-01-01

Observations of Rn-222 and Po-210 on the lunar surface with the orbiting Apollo alpha particle spectrometer reveal a number of features in their spatial distribution and indicate the existence of time variations in lunar radon emission. Localized Rn-222 or Po-210 around the craters Aristarchus and Grimaldi and the edges of virtually all maria indicates time varying radon emission and suggests a correlation between alpha 'hot spots' and sites of transient optical events observed from the earth. In a gross sense, the slower variations of Rn-222 seem to correlate with the distribution of gamma activity.

Determination of the spatial variability of temperature and moisture near a tropical Pacific island with MTI satellite images

NASA Astrophysics Data System (ADS)

Kurzeja, Robert J.; O'Steen, Byron L.; Pendergast, Malcolm M.

2002-01-01

The Tropical Pacific Island of Nauru is a US DOE ARM observation site that monitors tropical climate and atmospheric radiation. This observation site is ideal for validating MTI images because of the extensive deployment of continuously operating instruments. MTI images are also useful in assessing the effect of the island on the ocean climate and on the ARM data. An MTI image has been used to determine the spatial distribution of water vapor and sea-surface temperature near the island. The results are compared with a three-dimensional numerical model simulation.

A multi-model ensemble view of winter heat flux dynamics and the dipole mode in the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Liguori, Giovanni; Di Lorenzo, Emanuele; Cabos, William

2017-02-01

Changes in surface heat fluxes affect several climate processes controlling the Mediterranean climate. These include the winter formation of deep waters, which is the primary driver of the Mediterranean Sea overturning circulation. Previous studies that characterize the spatial and temporal variability of surface heat flux anomalies over the basin reveal the existence of two statistically dominant patterns of variability: a monopole of uniform sign and an east-west dipole of opposite signs. In this work, we use the 12 regional climate model ensemble from the EU-FP6 ENSEMBLES project to diagnose the large-scale atmospheric processes that control the variability of heat fluxes over the Mediterranean Sea from interannual to decadal timescales (here defined as timescales > 6 year). Our findings suggest that while the monopole structure captures variability in the winter-to-winter domain-average net heat flux, the dipole pattern tracks changes in the Mediterranean climate that are connected to the East Atlantic/Western Russia (EA/WR) atmospheric teleconnection pattern. Furthermore, while the monopole exhibits significant differences in the spatial structure across the multi-model ensemble, the dipole pattern is very robust and more clearly identifiable in the anomaly maps of individual years. A heat budget analysis of the dipole pattern reveals that changes in winds associated with the EA/WR pattern exert dominant control through both a direct effect on the latent heat flux (i.e., wind speed) and an indirect effect through specific humidity (e.g., wind advection). A simple reconstruction of the heat flux variability over the deep-water formation regions of the Gulf of Lion and the Aegean Sea reveals that the combination of the monopole and dipole time series explains over 90 % of the heat flux variance in these regions. Given the important role that surface heat flux anomalies play in deep-water formation and the regional climate, improving our knowledge on the dynamics controlling the leading modes of heat flux variability may enhance our predictability of the climate of the Mediterranean area.

Surface nanobubble nucleation dynamics during water-ethanol exchange

NASA Astrophysics Data System (ADS)

Chan, Chon U.; Ohl, Claus-Dieter

2015-11-01

Water-ethanol exchange has been a promising nucleation method for surface attached nanobubbles since their discovery. In this process, water and ethanol displace each other sequentially on a substrate. As the gas solubility is 36 times higher in ethanol than water, it was suggested that the exchange process leads to transient supersaturation and is responsible for the nanobubble nucleation. In this work, we visualize the nucleation dynamics by controllably mixing water and ethanol. It depicts the temporal evolution of the conventional exchange in a single field of view, detailing the conditions for surface nanobubble nucleation and the flow field that influences their spatial organization. This technique can also pattern surface nanobubbles with variable size distribution.

An integrated approach for estimation of methane emissions from wetlands and lakes in high latitude regions

NASA Astrophysics Data System (ADS)

Chiu, C.; Bowling, L. C.; Podest, E.; Bohn, T. J.; Lettenmaier, D. P.; Schroeder, R.; McDonald, K. C.

2009-04-01

In recent years, there has been increasing evidence of significant alteration in the extent of lakes and wetlands in high latitude regions due in part to thawing permafrost, as well as other changes governing surface and subsurface hydrology. Methane is a 23 times more efficient greenhouse gas than carbon dioxide; changes in surface water extent, and the associated subsurface anaerobic conditions, are important controls on methane emissions in high latitude regions. Methane emissions from wetlands vary substantially in both time and space, and are influenced by plant growth, soil organic matter decomposition, methanogenesis, and methane oxidation controlled by soil temperature, water table level and net primary productivity (NPP). The understanding of spatial and temporal heterogeneity of surface saturation, thermal regime and carbon substrate in northern Eurasian wetlands from point measurements are limited. In order to better estimate the magnitude and variability of methane emissions from northern lakes and wetlands, we present an integrated assessment approach based on remote sensing image classification, land surface modeling and process-based ecosystem modeling. Wetlands classifications based on L-band JERS-1 SAR (100m) and ALOS PALSAR (~30m) are used together with topographic information to parameterize a lake and wetland algorithm in the Variable Infiltration Capacity (VIC) land surface model at 25 km resolution. The enhanced VIC algorithm allows subsurface moisture exchange between surface water and wetlands and includes a sub-grid parameterization of water table position within the wetland area using a generalized topographic index. Average methane emissions are simulated by using the Walter and Heimann methane emission model based on temporally and spatially varying soil temperature, net primary productivity and water table generated from the modified VIC model. Our five preliminary study areas include the Z. Dvina, Upper Volga, Yeloguy, Syum, and Chaya river basins. The temporally-variable inundation extent simulated by the VIC model is compared to 25 km resolution inundation products developed from combined QuikSCAT, AMSR-E and MODIS data sets covering the time period from 2002 onward. The seasonal variation in methane emissions associated with sub-grid variability in water table extent is explored between 1948 and 2006. This work was carried out at Purdue University, at the University of Washington, and at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the NASA.

Mapping Surface Temperatures on a Debris-Covered Glacier with an Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Kraaijenbrink, Philip D. A.; Shea, Joseph M.; Litt, Maxime; Steiner, Jakob F.; Treichler, Désirée; Koch, Inka; Immerzeel, Walter W.

2018-05-01

A mantel of debris cover often accumulates across the surface of glaciers in active mountain ranges with exceptionally steep terrain, such as the Andes, Himalaya and New Zealand Alps. Such a supraglacial debris layer has a major influence on a glacier's surface energy budget, enhancing radiation absorption and melt when the layer is thin, but insulating the ice when thicker than a few cm. Information on spatially distributed debris surface temperature has the potential to provide insight into the properties of the debris, its effects on the ice below and its influence on the near-surface boundary layer. Here, we deploy an unmanned aerial vehicle (UAV) equipped with a thermal infrared sensor on three separate missions over one day to map changing surface temperatures across the debris-covered Lirung Glacier in the Central Himalaya. We present a methodology to georeference and process the acquired thermal imagery, and correct for emissivity and sensor bias. Derived UAV surface temperatures are compared with distributed simultaneous in situ temperature measurements as well as with Landsat 8 thermal satellite imagery. Results show that the UAV-derived surface temperatures vary greatly both spatially and temporally, with -1.4±1.8, 11.0 ±5.2 and 15.3±4.7 °C for the three flights (mean±sd), respectively. The range in surface temperatures over the glacier during the morning is very large with almost 50 °C. Ground-based measurements are generally in agreement with the UAV imagery, but considerable deviations are present that are likely due to differences in measurement technique and approach, and validation is difficult as a result. The difference in spatial and temporal variability captured by the UAV as compared with much coarser satellite imagery is striking and it shows that satellite derived temperature maps should be interpreted with care. We conclude that UAVs provide a suitable means to acquire surface temperature maps of debris-covered glacier surfaces at high spatial and temporal resolution, but that there are caveats with regard to absolute temperature measurement.

Quantifying Diurnal and Spatial Variations in CO2 Concentrations and Partial Columns using High-Resolution Global Model Simulations

NASA Astrophysics Data System (ADS)

Pawson, S.; Nielsen, J.; Ott, L. E.; Darmenov, A.; Putman, W.

2015-12-01

Model-data fusion approaches, such as global inverse modeling for surface flux estimation, have traditionally been performed at spatial resolutions of several tens to a few hundreds of kilometers. Use of such coarse scales presents a fundamental limitation in reconciling the modeled field with both the atmospheric observations and the distribution of surface emissions and uptake. Emissions typically occur on small scales, including point sources (e.g. power plants, forest fires) or with inhomegeneous structure. Biological uptake can have spatial variations related to complex, diverse vegetation, etc. Atmospheric observations of CO2 are either surface based, providing information at a single point, or space based with a finite-sized footprint. For instance, GOSAT and OCO-2 have footprint sizes of around 10km and proposed active sensors (such as ASCENDS) will likely have even finer footprints. One important aspect of reconciling models to measurements is the representativeness of the observation for the model field, and this depends on the generally unknown spatio-temporal variations of the CO2 field around the measurement location and time. This work presents an assessment of the global spatio-temporal variations of the CO2 field using the "7km GEOS-5 Nature Run" (7km-G5NR), which includes CO2 emissions and uptake mapped to the finest possible resolution. Results are shown for surface CO2 concentrations, total-column CO2, and separate upper and lower tropospheric columns. Spatial variability is shown to be largest in regions with strong point sources and at night in regions with complex terrain, especially where biological processes dominate the local CO2 fluxes, where the day-night differences are also most marked. The spatio-temporal variations are strongest for surface concentrations and for lower tropospheric CO2. While these results are largely anticipated, these high resolution simulations provide quantitative estimates of the global nature of spatio-temporal CO2 variability. Implications for characterizing representativeness of passive CO2 observations will be discussed. Differences between daytime and nighttime structures will be considered in light of active CO2 sensors. Finally, some possible limitations of the model will be highlighted, using some global 3-km simulations.

The Effects Of Urban Landscape Patterns On Rainfall-Runoff Processes At Small Scale

NASA Astrophysics Data System (ADS)

Chen, L.

2016-12-01

Many studies have indicated that urban landscape change may alter rainfall-runoff processes. However, how urban landscape pattern affect this process is little addressed. In this study, the hydrological effects of landscape pattern on rainfall-runoff processes at small-scale was explored. Twelve residential blocks with independent drainage systems in Beijing were selected as case study areas. Impervious metrics of these blocks, i.e., total impervious area (TIA) and directly connected impervious area (DCIA), were identified. A drainage index describing catchment general drainage load and the overland flow distance, Ad, was estimated and used as one of the landscape spatial metrics. Three scenarios were designed to test the potential influence of impervious surface pattern on runoff processes. Runoff variables including total and peak runoff depth (Qt and Qp) were simulated under different rainfall conditions by Storm Water Management Model (SWMM). The relationship between landscape patterns and runoff variables were analyzed, and further among the three scenarios. The results demonstrated that, in small urban blocks, spatial patterns have inherent influences on rainfall-runoff processes. Specifically, (1) Imperviousness acts as effective indicators in predicting both Qt and Qp. As rainfall intensity increases, the major affecting factor changes from DCIA to TIA for both Qt and Qp; (2) Increasing the size of drainage area dominated by each drainage inlet will benefit the block peak flow mitigation; (3) Different spatial concentrations of impervious surfaces have inherent influences on Qp, when impervious surfaces located away from the outlet can reduce the peak flow discharge. These findings may provide insights into the role of urban landscape patterns in driving rainfall-runoff responses in urbanization, which is essential for urban planning and stormwater management.

Distribution of ancient carbon in buried soils in an eroding loess landscape

NASA Astrophysics Data System (ADS)

Szymanski, L. M.; Mason, J. A.; De Graaff, M. A.; Berhe, A. A.; Marin-Spiotta, E.

2017-12-01

Understanding the processes that contribute to the accumulation and loss of carbon in soils and the implications for land management is vital for mitigating climate change. Buried soils or paleosols that represent former surface horizons can store more organic carbon than mineral horizons at equivalent depths due to burial restricting microbial decomposition. The presence of buried soils defies modeled expectations of exponential declines in carbon concentrations with depth, especially in locations where successive depositional events lead to multiple buried soil layers. Buried soils are found in a diversity of depositional environments across latitudes and without accounting for their presence can lead to underestimates of regional carbon reservoirs. Here we present data on the spatial distribution of carbon in a paleosol loess sequence in Nebraska, focusing on one prominent paleosol, the Brady soil. The Brady soil has been identified throughout the Central Great Plains and began developing at the end of the Pleistocene and was subsequently buried by loess in the early Holocene (Mason et al. 2003). Preliminary analyses of the Brady soil at its deepest, 6-m below the surface, reveal large differences in the composition and degree of decomposition of organic matter from the modern soil. We sampled along burial and erosional transects to characterize spatial variability in the depth of Brady soil from the modern landscape surface and to determine how these differences may alter the amount and composition of organic carbon. A more accurate determination of the spatial extent and heterogeneity of buried soil carbon will improve regional estimates of carbon reservoirs. This assessment of its variability across the landscape will inform future planned work on the vulnerability of ancient carbon to disturbance.

Seasonal and spatial variabilities in northern Gulf of Alaska surface water iron concentrations driven by shelf sediment resuspension, glacial meltwater, a Yakutat eddy, and dust

NASA Astrophysics Data System (ADS)

Crusius, John; Schroth, Andrew W.; Resing, Joseph A.; Cullen, Jay; Campbell, Robert W.

2017-06-01

Phytoplankton growth in the Gulf of Alaska (GoA) is limited by iron (Fe), yet Fe sources are poorly constrained. We examine the temporal and spatial distributions of Fe, and its sources in the GoA, based on data from three cruises carried out in 2010 from the Copper River (AK) mouth to beyond the shelf break. April data are the first to describe late winter Fe behavior before surface water nitrate depletion began. Sediment resuspension during winter and spring storms generated high "total dissolvable Fe" (TDFe) concentrations of 1000 nmol kg-1 along the entire continental shelf, which decreased beyond the shelf break. In July, high TDFe concentrations were similar on the shelf, but more spatially variable, and driven by low-salinity glacial meltwater. Conversely, dissolved Fe (DFe) concentrations in surface waters were far lower and more seasonally consistent, ranging from 4 nmol kg-1 in nearshore waters to 0.6-1.5 nmol kg-1 seaward of the shelf break during April and July, despite dramatic depletion of nitrate over that period. The reasonably constant DFe concentrations are likely maintained during the year across the shelf by complexation by strong organic ligands, coupled with ample supply of labile particulate Fe. The April DFe data can be simulated using a simple numerical model that assumes a DFe flux from shelf sediments, horizontal transport by eddy diffusion, and removal by scavenging. Given how global change is altering many processes impacting the Fe cycle, additional studies are needed to examine controls on DFe in the Gulf of Alaska.

Assessing the spatial variability of mountain precipitation in California's Sierra Nevada using the Airborne Snow Observatory

NASA Astrophysics Data System (ADS)

Brandt, T.; Deems, J. S.; Painter, T. H.; Dozier, J.

2016-12-01

In California's Sierra Nevada, 10 or fewer winter storms are responsible for most of the annual precipitation, which falls mostly as snow. Presently, surface stations are used to measure the dynamics of mountain precipitation. However, even in places like the Sierra Nevada—one of the most gauged regions in the world—the paucity of surface stations can lead to large errors in precipitation thereby biasing both total water year and short-term streamflow forecasts. Remotely sensed snow depth and water equivalent, at a time scale that resolves storms, might provide a novel solution to the problems of: (1) quantifying the spatial variability of mountain precipitation; and (2) assessing gridded precipitation products that are mostly based on surface station interpolation. NASA's Airborne Snow Observatory (ASO), an imaging spectrometer and LiDAR system, has measured snow in the Tuolumne River Basin in California's Sierra Nevada for the past four years, 2013-2016; and, measurements will continue. Principally, ASO monitors the progression of melt for water supply forecasting, nonetheless, a number of flights bracketed storms allowing for estimates of snow accumulation. In this study we examine a few of the ASO recorded storms to determine both the basin and subbasin orographic effect as well as the spatial patterns in total precipitation. We then compare these results to a number of gridded climate products and weather models including: Daymet, the Parameter-elevation Regressions on Independent Slopes Model (PRISM), the North American Land Data Assimilation System (NLDAS-2), and the Weather Research and Forecasting (WRF) model. Finally, to put each ASO recorded storm into context, we use a climatology produced from snow pillows and the North American Regional Reanalysis (NARR) for 2014-2016 to examine key accumulation events, and classify storms based on their integrated water vapor flux.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Mapping surface temperature variability on a debris-covered glacier with an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Kraaijenbrink, P. D. A.; Litt, M.; Shea, J. M.; Treichler, D.; Koch, I.; Immerzeel, W.

2016-12-01

Debris-covered glacier tongues cover about 12% of the glacier surface in high mountain Asia and much of the melt water is generated from those glaciers. A thin layer of supraglacial debris enhances ice melt by lowering the albedo, while thicker debris insulates the ice and reduces melt. Data on debris thickness is therefore an important input for energy balance modelling of these glaciers. Thermal infrared remote sensing can be used to estimate the debris thickness by using an inverse relation between debris surface temperature and thickness. To date this has only been performed using coarse spaceborne thermal imagery, which cannot reveal small scale variation in debris thickness and its influence on the heterogeneous melt patterns on debris-covered glaciers. We deployed an unmanned aerial vehicle mounted with a thermal infrared sensor over the debris-covered Lirung Glacier in Nepal three times in May 2016 to reveal the spatial and temporal variability of surface temperature in high detail. The UAV survey matched a Landsat 8 overpass to be able to make a comparison with spaceborne thermal imagery. The UAV-acquired data is processed using Structure from Motion photogrammetry and georeferenced using DGPS-measured ground control points. Different surface types were distinguished by using data acquired by an additional optical UAV survey in order to correct for differences in surface emissivity. In situ temperature measurements and incoming solar radiation data are used to calibrate the temperature calculations. Debris thicknesses derived are validated by thickness measurements of a ground penetrating radar. Preliminary analysis reveals a spatially highly heterogeneous pattern of surface temperature over Lirung Glacier with a range in temperature of over 40 K. At dawn the debris is relatively cold and its temperature is influenced strongly by the ice underneath. Exposed to the high solar radiation at the high altitude the debris layer heats up very rapidly as sunrise progresses, and the influence of ice on debris surface temperature reduces considerably. Many patterns are revealed that cannot be detected from the Landsat data, both on small spatial and temporal scales. The high detail the UAV-borne thermal imagery provides in time and space has great potential in the research of debris cover and its characteristics.

Multisource Imaging of Seasonal Dynamics in Land Surface Phenology Using Harmonized Landsat and Sentinel-2 Data

NASA Astrophysics Data System (ADS)

Melaas, E. K.; Graesser, J.; Friedl, M. A.

2017-12-01

Land surface phenology, including the timing of phenophase transitions and the entire seasonal cycle of surface reflectance and vegetation indices, is important for a myriad of applications including monitoring the response of terrestrial ecosystems to climate variability and extreme events, and land cover mapping. While methods to monitor and map phenology from coarse spatial resolution instruments such as MODIS are now relatively mature, the spatial resolution of these instruments is inadequate where vegetation properties, land use, and land cover vary at spatial scales of tens of meters. To address this need, algorithms to map phenology at moderate spatial resolution (30 m) using data from Landsat have recently been developed. However, the 16-day repeat cycle of Landsat presents significant challenges in regions where changes are rapid or where cloud cover reduces the frequency of clear-sky views. The European Space Agency's Sentinel-2 satellites, which are designed to provide moderate spatial resolution data at 5-day revisit frequency near the equator and 3 day revisit frequency in the mid-latitudes, will alleviate this constraint in many parts of the world. Here, we use harmonized time series of data from Sentinel-2A and Landsat OLI (HLS) to quantify the timing of land surface phenology metrics across a sample of deciduous forest and grassland-dominated sites, and then compare these estimates with co-located in situ observations. The resulting phenology maps demonstrate the improved information related to landscape-scale features that can be estimated from HLS data relative to comparable metrics from coarse spatial resolution instruments. For example, our results based on HLS data reveal spatial patterns in phenological metrics related to topographic and land cover controls that are not resolved in MODIS data, and show good agreement with transition dates observed from in situ measurements. Our results also show systematic bias toward earlier timing of spring, which is caused by inadequate density of observations that will be mitigated once data from Sentinel-2B are available. Overall, our results highlight the potential for using moderate spatial resolution data from Landsat and Sentinel-2 for developing operational phenology algorithms and products in support of the science community.

Impact of Spatial Sampling on Continuity of MODIS-VIIRS Land Surface Reflectance Products: A Simulation Approach

NASA Technical Reports Server (NTRS)

Pahlevan, Nima; Sarkar, Sudipta; Devadiga, Sadashiva; Wolfe, Robert E.; Roman, Miguel; Vermote, Eric; Lin, Guoqing; Xiong, Xiaoxiong

2016-01-01

With the increasing need to construct long-term climate-quality data records to understand, monitor, and predict climate variability and change, it is vital to continue systematic satellite measurements along with the development of new technology for more quantitative and accurate observations. The Suomi National Polar-orbiting Partnership mission provides continuity in monitoring the Earths surface and its atmosphere in a similar fashion as the heritage MODIS instruments onboard the National Aeronautics and Space Administrations Terra and Aqua satellites. In this paper, we aim at quantifying the consistency of Aqua MODIS and Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Reflectance (LSR) and NDVI products as related to their inherent spatial sampling characteristics. To avoid interferences from sources of measurement and/or processing errors other than spatial sampling, including calibration, atmospheric correction, and the effects of the bidirectional reflectance distribution function, the MODIS and VIIRSLSR products were simulated using the Landsat-8s Operational Land Imager (OLI) LSR products. The simulations were performed using the instruments point spread functions on a daily basis for various OLI scenes over a 16-day orbit cycle. It was found that the daily mean differences due to discrepancies in spatial sampling remain below 0.0015 (1) in absolute surface reflectance at subgranule scale (i.e., OLI scene size).We also found that the MODISVIIRS product intercomparisons appear to be minimally impacted when differences in the corresponding view zenith angles (VZAs) are within the range of -15deg to -35deg (VZA(sub v) - VZA(sub m)), where VIIRS and MODIS footprints resemble in size. In general, depending on the spatial heterogeneity of the OLI scene contents, per-grid-cell differences can reach up to 20.Further spatial analysis of the simulated NDVI and LSR products revealed that, depending on the user accuracy requirements for product intercomparisons, spatial aggregations may be used. It was found that if per-grid-cell differences on the order of 10(in LSR or NDVI) are tolerated, the product intercomparisons are expected to be immune from differences in spatial sampling.

Reconstructing spatial-temporal continuous MODIS land surface temperature using the DINEOF method

NASA Astrophysics Data System (ADS)

Zhou, Wang; Peng, Bin; Shi, Jiancheng

2017-10-01

Land surface temperature (LST) is one of the key states of the Earth surface system. Remote sensing has the capability to obtain high-frequency LST observations with global coverage. However, mainly due to cloud cover, there are always gaps in the remotely sensed LST product, which hampers the application of satellite-based LST in data-driven modeling of surface energy and water exchange processes. We explored the suitability of the data interpolating empirical orthogonal functions (DINEOF) method in moderate resolution imaging spectroradiometer LST reconstruction around Ali on the Tibetan Plateau. To validate the reconstruction accuracy, synthetic clouds during both daytime and nighttime are created. With DINEOF reconstruction, the root mean square error and bias under synthetic clouds in daytime are 4.57 and -0.0472 K, respectively, and during the nighttime are 2.30 and 0.0045 K, respectively. The DINEOF method can well recover the spatial pattern of LST. Time-series analysis of LST before and after DINEOF reconstruction from 2002 to 2016 shows that the annual and interannual variabilities of LST can be well reconstructed by the DINEOF method.

Using Remotely Sensed Information for Near Real-Time Landslide Hazard Assessment

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia; Adler, Robert; Peters-Lidard, Christa

2013-01-01

The increasing availability of remotely sensed precipitation and surface products provides a unique opportunity to explore how landslide susceptibility and hazard assessment may be approached at larger spatial scales with higher resolution remote sensing products. A prototype global landslide hazard assessment framework has been developed to evaluate how landslide susceptibility and satellite-derived precipitation estimates can be used to identify potential landslide conditions in near-real time. Preliminary analysis of this algorithm suggests that forecasting errors are geographically variable due to the resolution and accuracy of the current susceptibility map and the application of satellite-based rainfall estimates. This research is currently working to improve the algorithm through considering higher spatial and temporal resolution landslide susceptibility information and testing different rainfall triggering thresholds, antecedent rainfall scenarios, and various surface products at regional and global scales.

Scaling water and energy fluxes in climate systems - Three land-atmospheric modeling experiments

NASA Technical Reports Server (NTRS)

Wood, Eric F.; Lakshmi, Venkataraman

1993-01-01

Three numerical experiments that investigate the scaling of land-surface processes - either of the inputs or parameters - are reported, and the aggregated processes are compared to the spatially variable case. The first is the aggregation of the hydrologic response in a catchment due to rainfall during a storm event and due to evaporative demands during interstorm periods. The second is the spatial and temporal aggregation of latent heat fluxes, as calculated from SiB. The third is the aggregation of remotely sensed land vegetation and latent and sensible heat fluxes using TM data from the FIFE experiment of 1987 in Kansas. In all three experiments it was found that the surface fluxes and land characteristics can be scaled, and that macroscale models based on effective parameters are sufficient to account for the small-scale heterogeneities investigated.

Spatial Variability of Snowpack Properties On Small Slopes

NASA Astrophysics Data System (ADS)

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

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

Variability in Surface BRDF at Different Spatial Scales (30m-500m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

NASA Technical Reports Server (NTRS)

Roman, Miguel O.; Gatebe, Charles K.; Schaaf, Crystal B.; Poudyal, Rajesh; Wang, Zhuosen; King, Michael D.

2012-01-01

Over the past decade, the role of multiangle 1 remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75deg off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular 18 characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertainties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Variability in Surface BRDF at Different Spatial Scales (30 m-500 m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

NASA Technical Reports Server (NTRS)

Roman, Miguel O.; Gatebe, Charles K.; Schaaf, Crystal B.; Poudyal, Rajesh; Wang, Zhousen; King, Michael D.

2011-01-01

Over the past decade, the role of multiangle remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75 off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertain ties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Spatial Patterns of Variability in Antarctic Surface Temperature: Connections to the Southern Hemisphere Annular Mode and the Southern Oscillation

NASA Technical Reports Server (NTRS)

Kwok, Ron; Comiso, Josefino C.; Koblinsky, Chester J. (Technical Monitor)

2002-01-01

The 17-year (1982-1998) trend in surface temperature shows a general cooling over the Antarctic continent, warming of the sea ice zone, with moderate changes over the oceans. Warming of the peripheral seas is associated with negative trends in the regional sea ice extent. Effects of the Southern Hemisphere Annular Mode (SAM) and the extrapolar Southern Oscillation (SO) on surface temperature are quantified through regression analysis. Positive polarities of the SAM are associated with cold anomalies over most of Antarctica, with the most notable exception of the Antarctic Peninsula. Positive temperature anomalies and ice edge retreat in the Pacific sector are associated with El Nino episodes. Over the past two decades, the drift towards high polarity in the SAM and negative polarity in the SO indices couple to produce a spatial pattern with warmer temperatures in the Antarctic Peninsula and peripheral seas, and cooler temperatures over much of East Antarctica.

Delineating recurrent fish spawning habitats in the North Sea

NASA Astrophysics Data System (ADS)

Lelièvre, S.; Vaz, S.; Martin, C. S.; Loots, C.

2014-08-01

The functional value of spawning habitats makes them critically important for the completion of fish life cycles and spawning grounds are now considered to be “essential habitats”. Inter-annual fluctuations in spawning ground distributions of dab (Limanda Limanda), plaice (Pleuronectes platessa), cod (Gadus morhua) and whiting (Merlangius merlangus) were investigated in the southern North Sea and eastern English Channel, from 2006 to 2009. The preferential spawning habitats of these species were modelled using generalised linear models, with egg distribution being used as proxy of spawners' location. Egg spatial and temporal distributions were explored based on six environmental variables: sea surface temperature and salinity, chlorophyll a concentration, depth, bedstress and seabed sediment types. In most cases, egg density was found to be strongly related to these environmental variables. Egg densities were positively correlated with shallow to intermediate depths having low temperature and relatively high salinity. Habitat models were used to map annual, i.e. 2006 to 2009, winter spatial distributions of eggs, for each species separately. Then, annual maps were combined to explore the spatial variability of each species' spawning grounds, and define recurrent, occasional, rare and unfavourable spawning areas. The recurrent spawning grounds of all four species were located in the south-eastern part of the study area, mainly along the Dutch and German coasts. This study contributes knowledge necessary to the spatial management of fishery resources in the area, and may also be used to identify marine areas with particular habitat features that need to be preserved.

Physically-based parameterization of spatially variable soil and vegetation using satellite multispectral data

NASA Technical Reports Server (NTRS)

Jasinski, Michael F.; Eagleson, Peter S.

1989-01-01

A stochastic-geometric landsurface reflectance model is formulated and tested for the parameterization of spatially variable vegetation and soil at subpixel scales using satellite multispectral images without ground truth. Landscapes are conceptualized as 3-D Lambertian reflecting surfaces consisting of plant canopies, represented by solid geometric figures, superposed on a flat soil background. A computer simulation program is developed to investigate image characteristics at various spatial aggregations representative of satellite observational scales, or pixels. The evolution of the shape and structure of the red-infrared space, or scattergram, of typical semivegetated scenes is investigated by sequentially introducing model variables into the simulation. The analytical moments of the total pixel reflectance, including the mean, variance, spatial covariance, and cross-spectral covariance, are derived in terms of the moments of the individual fractional cover and reflectance components. The moments are applied to the solution of the inverse problem: The estimation of subpixel landscape properties on a pixel-by-pixel basis, given only one multispectral image and limited assumptions on the structure of the landscape. The landsurface reflectance model and inversion technique are tested using actual aerial radiometric data collected over regularly spaced pecan trees, and using both aerial and LANDSAT Thematic Mapper data obtained over discontinuous, randomly spaced conifer canopies in a natural forested watershed. Different amounts of solar backscattered diffuse radiation are assumed and the sensitivity of the estimated landsurface parameters to those amounts is examined.

VEMAP phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA

Treesearch

Timothy G.F. Kittel; Nan. A. Rosenbloom; J.A. Royle; C. Daly; W.P. Gibson; H.H. Fisher; P. Thornton; D.N. Yates; S. Aulenbach; C. Kaufman; R. McKeown; Dominque Bachelet; David S. Schimel

2004-01-01

Analysis and simulation of biospheric responses to historical forcing require surface climate data that capture those aspects of climate that control ecological processes, including key spatial gradients and modes of temporal variability. We developed a multivariate, gridded historical climate dataset for the conterminous USA as a common input database for the...

Flood hazards analysis based on changes of hydrodynamic processes in fluvial systems of Sao Paulo, Brazil.

NASA Astrophysics Data System (ADS)

Simas, Iury; Rodrigues, Cleide

2016-04-01

The metropolis of Sao Paulo, with its 7940 Km² and over 20 million inhabitants, is increasingly being consolidated with disregard for the dynamics of its fluvial systems and natural limitations imposed by fluvial terraces, floodplains and slopes. Events such as floods and flash floods became particularly persistent mainly in socially and environmentally vulnerable areas. The Aricanduva River basin was selected as the ideal area for the development of the flood hazard analysis since it presents the main geological and geomorphological features found in the urban site. According to studies carried out by Anthropic Geomorphology approach in São Paulo, to study this phenomenon is necessary to take into account the original hydromorphological systems and its functional conditions, as well as in which dimensions the Anthropic factor changes the balance between the main variables of surface processes. Considering those principles, an alternative model of geographical data was proposed and enabled to identify the role of different driving forces in terms of spatial conditioning of certain flood events. Spatial relationships between different variables, such as anthropogenic and original morphology, were analyzed for that purpose in addition to climate data. The surface hydrodynamic tendency spatial model conceived for this study takes as key variables: 1- The land use present at the observed date combined with the predominant lithological group, represented by a value ranging 0-100, based on indexes of the National Soil Conservation Service (NSCS-USA) and the Hydraulic Technology Center Foundation (FCTH-Brazil) to determine the resulting balance of runoff/infiltration. 2- The original slope, applying thresholds from which it's possible to determine greater tendency for runoff (in percents). 3- The minimal features of relief, combining the curvature of surface in plant and profile. Those three key variables were combined in a Geographic Information System in a series of tests to get weighted values, defining fuzzy limits in the resulting matrix. For comparison purposes, with this method it was possible to create surface hydrodynamic tendency charts of different periods of urban consolidation. Considerable changes of superficial hydrodynamic tendencies in our universe of study were identified, specially pointing to the expected positive tendency change for runoff, due to the current predominant urban land uses. Furthermore, the model enabled an associated analysis with interpolated pluvial values, pointing and quantifying, in terms of runoff volume increase, the influence of occupied areas to the occurrences of floods in areas previously not-known to be affected.

Clouds and the Earth's Radiant Energy System (CERES) Data Products for Climate Research

NASA Technical Reports Server (NTRS)

Kato, Seiji; Loeb, Norman G.; Rutan, David A.; Rose, Fred G.

2015-01-01

NASA's Clouds and the Earth's Radiant Energy System (CERES) project integrates CERES, Moderate Resolution Imaging Spectroradiometer (MODIS), and geostationary satellite observations to provide top-of-atmosphere (TOA) irradiances derived from broadband radiance observations by CERES instruments. It also uses snow cover and sea ice extent retrieved from microwave instruments as well as thermodynamic variables from reanalysis. In addition, these variables are used for surface and atmospheric irradiance computations. The CERES project provides TOA, surface, and atmospheric irradiances in various spatial and temporal resolutions. These data sets are for climate research and evaluation of climate models. Long-term observations are required to understand how the Earth system responds to radiative forcing. A simple model is used to estimate the time to detect trends in TOA reflected shortwave and emitted longwave irradiances.

Spherical-earth Gravity and Magnetic Anomaly Modeling by Gauss-legendre Quadrature Integration

NASA Technical Reports Server (NTRS)

Vonfrese, R. R. B.; Hinze, W. J.; Braile, L. W.; Luca, A. J. (Principal Investigator)

1981-01-01

The anomalous potential of gravity and magnetic fields and their spatial derivatives on a spherical Earth for an arbitrary body represented by an equivalent point source distribution of gravity poles or magnetic dipoles were calculated. The distribution of equivalent point sources was determined directly from the coordinate limits of the source volume. Variable integration limits for an arbitrarily shaped body are derived from interpolation of points which approximate the body's surface envelope. The versatility of the method is enhanced by the ability to treat physical property variations within the source volume and to consider variable magnetic fields over the source and observation surface. A number of examples verify and illustrate the capabilities of the technique, including preliminary modeling of potential field signatures for Mississippi embayment crustal structure at satellite elevations.

Improved Satellite Retrievals of NO2 and SO2 over the Canadian Oil Sands and Comparisons with Surface Measurements

NASA Technical Reports Server (NTRS)

McLinden, C. A.; Fioletov, V.; Boersma, K. F.; Kharol, S. K.; Krotkov, N.; Lamsal, L.; Makar, P. A.; Martin, R. V.; Veefkind, J. P.; Yang, K.

2014-01-01

Satellite remote sensing is increasingly being used to monitor air quality over localized sources such as the Canadian oil sands. Following an initial study, significantly low biases have been identified in current NO2 and SO2 retrieval products from the Ozone Monitoring Instrument (OMI) satellite sensor over this location resulting from a combination of its rapid development and small spatial scale. Air mass factors (AMFs) used to convert line-of-sight "slant" columns to vertical columns were re-calculated for this region based on updated and higher resolution input information including absorber profiles from a regional-scale (15 km × 15 km resolution) air quality model, higher spatial and temporal resolution surface reflectivity, and an improved treatment of snow. The overall impact of these new Environment Canada (EC) AMFs led to substantial increases in the peak NO2 and SO2 average vertical column density (VCD), occurring over an area of intensive surface mining, by factors of 2 and 1.4, respectively, relative to estimates made with previous AMFs. Comparisons are made with long-term averages of NO2 and SO2 (2005-2011) from in situ surface monitors by using the air quality model to map the OMI VCDs to surface concentrations. This new OMI-EC product is able to capture the spatial distribution of the in situ instruments (slopes of 0.65 to 1.0, correlation coefficients of greater than 0.9). The concentration absolute values from surface network observations were in reasonable agreement, with OMI-EC NO2 and SO2 biased low by roughly 30%. Several complications were addressed including correction for the interference effect in the surface NO2 instruments and smoothing and clear-sky biases in the OMI measurements. Overall these results highlight the importance of using input information that accounts for the spatial and temporal variability of the location of interest when performing retrievals.

Tidal and atmospheric forcing of the upper ocean in the Gulf of California. I - Sea surface temperature variability

NASA Technical Reports Server (NTRS)

Paden, Cynthia A.; Winant, Clinton D.; Abbott, Mark R.

1991-01-01

SST variability in the northern Gulf of California is examined on the basis of findings of two years of satellite infrared imagery (1984-1986). Empirical orthogonal functions of the temporal and spatial SST variance for 20 monthly mean images show that the dominant SST patterns are generated by spatially varying tidal mixing in the presence of seasonal heating and cooling. Atmospheric forcing of the northern gulf appears to occur over large spatial scales. Area-averaged SSTs for the Guaymas Basin, island region, and northern basin exhibit significant fluctuations which are highly correlated. These fluctuations in SST correspond to similar fluctuations in the air temperature which are related to synoptic weather events over the gulf. A regression analysis of the SST relative to the fortnightly tidal range shows that tidal mixing occurs over the sills in the island region as well as on the shallow northern shelf. Mixing over the sills occurs as a result of large breaking internal waves of internal hydraulic jumps which mix over water in the upper 300-500 m.

Spatial and temporal variability in the R-5 infiltration data set: Déjà vu and rainfall-runoff simulations

NASA Astrophysics Data System (ADS)

Loague, Keith; Kyriakidis, Phaedon C.

1997-12-01

This paper is a continuation of the event-based rainfall-runoff model evaluation study reported by Loague and Freeze [1985[. Here we reevaluate the performance of a quasi-physically based rainfall-runoff model for three large events from the well-known R-5 catchment. Five different statistical criteria are used to quantitatively judge model performance. Temporal variability in the large R-5 infiltration data set [Loague and Gander, 1990] is filtered by working in terms of permeability. The transformed data set is reanalyzed via geostatistical methods to model the spatial distribution of permeability across the R-5 catchment. We present new estimates of the spatial distribution of infiltration that are in turn used in our rainfall-runoff simulations with the Horton rainfall-runoff model. The new rainfall-runoff simulations, complicated by reinfiltration impacts at the smaller scales of characterization, indicate that the near-surface hydrologic response of the R-5 catchment is most probably dominated by a combination of the Horton and Dunne overland flow mechanisms.

Estimating ocean production from satellite-derived chlorophyll - Insights from the EASTROPAC data set

NASA Technical Reports Server (NTRS)

Eppley, R. W.; Stewart, E.; Abbott, M. R.; Owen, R. W.

1985-01-01

The EASTROPAC expedition took place in 1967-68 in the eastern tropical Pacific Ocean. Primary production was related to near-surface chlorophyll in these data. Much of the variability in the relation was due to the light-history of the phytoplankton and its photoadaptive state. This was due to changes in the depth of mixing of the surface waters more than changes in insolation. Accurate estimates of production from satellite chlorophyll measurements may require knowledge of the temporal and spatial variation in mixing of this region.

Direct mapping of ion diffusion times on LiCoO2 surfaces with nanometer resolution

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

Guo, Senli; Jesse, Stephen; Kalnaus, Sergiy

2011-01-01

The strong coupling between the molar volume and mobile ion concentration in ionically-conductive solids is used for spatially-resolved studies of ionic transport on the polycrystalline LiCoO2 surface by time-resolved spectroscopy. Strong variability between ionic transport at the grain boundaries and within the grains is observed, and the relationship between relaxation and hysteresis loop formation is established. The use of the strain measurements allows ionic transport be probed on the nanoscale, and suggests enormous potential for probing ionic materials and devices.

Wind Characteristics of Coastal and Inland Surface Flows

NASA Astrophysics Data System (ADS)

Subramanian, Chelakara; Lazarus, Steven; Jin, Tetsuya

2015-11-01

Lidar measurements of the winds in the surface layer (up to 80 m) inland and near the beach are studied to better characterize the velocity profile and the effect of roughness. Mean and root-mean-squared profiles of horizontal and vertical wind components are analyzed. The effects of variable time (18, 60 and 600 seconds) averaging on the above profiles are discussed. The validity of common surface layer wind profile models to estimate skin friction drag is assessed in light of these measurements. Other turbulence statistics such as auto- and cross- correlations in spatial and temporal domains are also presented. The help of FIT DMES field measurement crew is acknowledged.

Assessment of the Suitability of High Resolution Numerical Weather Model Outputs for Hydrological Modelling in Mountainous Cold Regions

NASA Astrophysics Data System (ADS)

Rasouli, K.; Pomeroy, J. W.; Hayashi, M.; Fang, X.; Gutmann, E. D.; Li, Y.

2017-12-01

The hydrology of mountainous cold regions has a large spatial variability that is driven both by climate variability and near-surface process variability associated with complex terrain and patterns of vegetation, soils, and hydrogeology. There is a need to downscale large-scale atmospheric circulations towards the fine scales that cold regions hydrological processes operate at to assess their spatial variability in complex terrain and quantify uncertainties by comparison to field observations. In this research, three high resolution numerical weather prediction models, namely, the Intermediate Complexity Atmosphere Research (ICAR), Weather Research and Forecasting (WRF), and Global Environmental Multiscale (GEM) models are used to represent spatial and temporal patterns of atmospheric conditions appropriate for hydrological modelling. An area covering high mountains and foothills of the Canadian Rockies was selected to assess and compare high resolution ICAR (1 km × 1 km), WRF (4 km × 4 km), and GEM (2.5 km × 2.5 km) model outputs with station-based meteorological measurements. ICAR with very low computational cost was run with different initial and boundary conditions and with finer spatial resolution, which allowed an assessment of modelling uncertainty and scaling that was difficult with WRF. Results show that ICAR, when compared with WRF and GEM, performs very well in precipitation and air temperature modelling in the Canadian Rockies, while all three models show a fair performance in simulating wind and humidity fields. Representation of local-scale atmospheric dynamics leading to realistic fields of temperature and precipitation by ICAR, WRF, and GEM makes these models suitable for high resolution cold regions hydrological predictions in complex terrain, which is a key factor in estimating water security in western Canada.

Regional co-variability of spatial and temporal soil moisture-precipitation coupling in North Africa: an observational perspective

NASA Astrophysics Data System (ADS)

Petrova, Irina Y.; van Heerwaarden, Chiel C.; Hohenegger, Cathy; Guichard, Françoise

2018-06-01

The magnitude and sign of soil moisture-precipitation coupling (SMPC) is investigated using a probability-based approach and 10 years of daily microwave satellite data across North Africa at a 1° horizontal scale. Specifically, the co-existence and co-variability of spatial (i.e. using soil moisture gradients) and temporal (i.e. using soil moisture anomaly) soil moisture effects on afternoon rainfall is explored. The analysis shows that in the semi-arid environment of the Sahel, the negative spatial and the negative temporal coupling relationships do not only co-exist, but are also dependent on one another. Hence, if afternoon rain falls over temporally drier soils, it is likely to be surrounded by a wetter environment. Two regions are identified as SMPC hot spots. These are the south-western part of the domain (7-15° N, 10° W-7° E), with the most robust negative SMPC signal, and the South Sudanese region (5-13° N, 24-34° E). The sign and significance of the coupling in the latter region is found to be largely modulated by the presence of wetlands and is susceptible to the number of long-lived propagating convective systems. The presence of wetlands and an irrigated land area is found to account for about 30 % of strong and significant spatial SMPC in the North African domain. This study provides the first insight into regional variability of SMPC in North Africa, and supports the potential relevance of mechanisms associated with enhanced sensible heat flux and mesoscale variability in surface soil moisture for deep convection development.

Applying Geospatial Techniques to Investigate Boundary Layer Land-Atmosphere Interactions Involved in Tornadogensis

NASA Astrophysics Data System (ADS)

Weigel, A. M.; Griffin, R.; Knupp, K. R.; Molthan, A.; Coleman, T.

2017-12-01

Northern Alabama is among the most tornado-prone regions in the United States. This region has a higher degree of spatial variability in both terrain and land cover than the more frequently studied North American Great Plains region due to its proximity to the southern Appalachian Mountains and Cumberland Plateau. More research is needed to understand North Alabama's high tornado frequency and how land surface heterogeneity influences tornadogenesis in the boundary layer. Several modeling and simulation studies stretching back to the 1970's have found that variations in the land surface induce tornadic-like flow near the surface, illustrating a need for further investigation. This presentation introduces research investigating the hypothesis that horizontal gradients in land surface roughness, normal to the direction of flow in the boundary layer, induce vertically oriented vorticity at the surface that can potentially aid in tornadogenesis. A novel approach was implemented to test this hypothesis using a GIS-based quadrant pattern analysis method. This method was developed to quantify spatial relationships and patterns between horizontal variations in land surface roughness and locations of tornadogenesis. Land surface roughness was modeled using the Noah land surface model parameterization scheme which, was applied to MODIS 500 m and Landsat 30 m data in order to compare the relationship between tornadogenesis locations and roughness gradients at different spatial scales. This analysis found a statistical relationship between areas of higher roughness located normal to flow surrounding tornadogenesis locations that supports the tested hypothesis. In this presentation, the innovative use of satellite remote sensing data and GIS technologies to address interactions between the land and atmosphere will be highlighted.

A step towards considering the spatial heterogeneity of urban key features in urban hydrology flood modelling

NASA Astrophysics Data System (ADS)

Leandro, J.; Schumann, A.; Pfister, A.

2016-04-01

Some of the major challenges in modelling rainfall-runoff in urbanised areas are the complex interaction between the sewer system and the overland surface, and the spatial heterogeneity of the urban key features. The former requires the sewer network and the system of surface flow paths to be solved simultaneously. The latter is still an unresolved issue because the heterogeneity of runoff formation requires high detailed information and includes a large variety of feature specific rainfall-runoff dynamics. This paper discloses a methodology for considering the variability of building types and the spatial heterogeneity of land surfaces. The former is achieved by developing a specific conceptual rainfall-runoff model and the latter by defining a fully distributed approach for infiltration processes in urban areas with limited storage capacity dependent on OpenStreetMaps (OSM). The model complexity is increased stepwise by adding components to an existing 2D overland flow model. The different steps are defined as modelling levels. The methodology is applied in a German case study. Results highlight that: (a) spatial heterogeneity of urban features has a medium to high impact on the estimated overland flood-depths, (b) the addition of multiple urban features have a higher cumulative effect due to the dynamic effects simulated by the model, (c) connecting the runoff from buildings to the sewer contributes to the non-linear effects observed on the overland flood-depths, and (d) OSM data is useful in identifying pounding areas (for which infiltration plays a decisive role) and permeable natural surface flow paths (which delay the flood propagation).

Albedo climatology for European land surfaces retrieved from AVHRR data (1990-2014) and its spatial and temporal analysis from green-up to vegetation senescence

NASA Astrophysics Data System (ADS)

Sütterlin, M.; Stöckli, R.; Schaaf, C. B.; Wunderle, S.

2016-07-01

Satellite-based, long-term records of surface albedo characterization that accurately capture spatial and temporal patterns are essential to develop climate models and to monitor the impact of land use changes on the terrestrial energy and water balance. This study presents the first Bidirectional Reflectance Distribution Function (BRDF) and albedo data set derived from the Advanced Very High Resolution Radiometer (AVHRR) Local Area Coverage reflectance data acquired on board National Oceanic and Atmospheric Administration and Meteorological Operational platforms from 1990 to 2014 over Europe. The objectives of this paper are to describe the data set's surface albedo climatology and anomalies in the visible, near-infrared, and shortwave broadbands for the growing season months of May to September in order to facilitate utilization of the data by the climate modeling communities. The results demonstrate that the AVHRR BRDF and albedo data have temporal and spatial patterns that are appropriate for the underlying predominant land cover type and accurately reflect the associated climate variation. Visible and near-infrared broadband albedo anomalies are found to be contrasting in most years, and their spatial distributions depict responses of vegetation to climate events (e.g., heat waves). Visible albedo of crops and near-infrared albedo of pastures show a higher interannual variation than respective albedos of other snow-free land covers, while the interannual standard deviations are found to be lower than 0.015. Our findings indicate the importance of taking into account the spectrally distinct variability of surface albedo when analyzing its complex spatiotemporal dynamics in climate-related research.

Development of a New Methodology for Computing Surface Sensible Heat Fluxes using Thermal Imagery

NASA Astrophysics Data System (ADS)

Morrison, T. J.; Calaf, M.; Fernando, H. J.; Price, T. A.; Pardyjak, E.

2017-12-01

Current numerical weather predication models utilize similarity to characterize momentum, moisture, and heat fluxes. Such formulations are only valid under the ideal assumptions of spatial homogeneity, statistical stationary, and zero subsidence. However, recent surface temperature measurements from the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) Program on the Salt Flats of Utah's West desert, show that even under the most a priori ideal conditions, heterogeneity of the aforementioned variables exists. We present a new method to extract spatially-distributed measurements of surface sensible heat flux from thermal imagery. The approach consists of using a surface energy budget, where the ground heat flux is easily computed from limited measurements using a force-restore-type methodology, the latent heat fluxes are neglected, and the energy storage is computed using a lumped capacitance model. Preliminary validation of the method is presented using experimental data acquired from a nearby sonic anemometer during the MATERHORN campaign. Additional evaluation is required to confirm the method's validity. Further decomposition analysis of on-site instrumentation (thermal camera, cold-hotwire probes, and sonic anemometers) using Proper Orthogonal Decomposition (POD), and wavelet analysis, reveals time scale similarity between the flow and surface fluctuations.

Field-calibrated model of melt, refreezing, and runoff for polar ice caps: Application to Devon Ice Cap

NASA Astrophysics Data System (ADS)

Morris, Richard M.; Mair, Douglas W. F.; Nienow, Peter W.; Bell, Christina; Burgess, David O.; Wright, Andrew P.

2014-09-01

Understanding the controls on the amount of surface meltwater that refreezes, rather than becoming runoff, over polar ice masses is necessary for modeling their surface mass balance and ultimately for predicting their future contributions to global sea level change. We present a modified version of a physically based model that includes an energy balance routine and explicit calculation of near-surface meltwater refreezing capacity, to simulate the evolution of near-surface density and temperature profiles across Devon Ice Cap in Arctic Canada. Uniquely, our model is initiated and calibrated using high spatial resolution measurements of snow and firn densities across almost the entire elevation range of the ice cap for the summer of 2004 and subsequently validated with the same type of measurements obtained during the very different meteorological conditions of summer 2006. The model captures the spatial variability across the transect in bulk snowpack properties although it slightly underestimates the flow of meltwater into the firn of previous years. The percentage of meltwater that becomes runoff is similar in both years; however, the spatial pattern of this melt-runoff relationship is different in the 2 years. The model is found to be insensitive to variation in the depth of impermeable layers within the firn but is very sensitive to variation in air temperature, since the refreezing capacity of firn decreases with increasing temperature. We highlight that the sensitivity of the ice cap's surface mass balance to air temperature is itself dependent on air temperature.