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At least 955 records · Page 53

How Universal is the Relationship Between Remotely Sensed Vegetation Indices and Crop Leaf Area Index? A Global Assessment

Leaf Area Index (LAI) is a key variable that bridges remote sensing observations to the quantification of agroecosystem processes. In this study, we assessed the universality of the relationships between crop LAI and remotely sensed Vegetation Indices (VIs). We first compiled a global dataset of 1459 in situ quality-controlled crop LAI measurements and collected Landsat satellite images to derive five different VIs including Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), two versions of the Enhanced Vegetation Index (EVI and EVI2), and Green Chlorophyll Index (CI(sub Green)). Based on this dataset, we developed global LAI-VI relationships for each crop type and VI using symbolic regression and Theil-Sen (TS) robust estimator. Results suggest that the global LAI-VI relationships are statistically significant, crop-specific, and mostly non-linear. These relationships explain more than half of the total variance in ground LAI observations (R2 greater than 0.5), and provide LAI estimates with RMSE below 1.2 m2/m2. Among the five VIs, EVI/EVI2 are the most effective, and the crop-specific LAI-EVI and LAI-EVI2 relationships constructed by TS, are robust when tested by three independent validation datasets of varied spatial scales. While the heterogeneity of agricultural landscapes leads to a diverse set of local LAI-VI relationships, the relationships provided here represent global universality on an average basis, allowing the generation of large-scale spatial-explicit LAI maps. This study contributes to the operationalization of large-area crop modeling and, by extension, has relevance to both fundamental and applied agroecosystem research.

Vegetation Index↗

Approaches of comparison for clear-sky radiative fluxes from general circulation models with Earth Radiation Budget Experiment data

In order to compare the clear-sky greenhouse effect and cloud-radiative forcing from general circulation models with Earth Radiation Budget Experiments (ERBE) data, it is necessary to calculate the general circulation model (GCM) clear-sky radiative fluxes in a way consistent with ERBE. This study discusses problems associated with the available methods for clear-sky radiative flux computations in GCMs and proposes a new approach, which uses a statistical relationship between the grid cloud cover and the availability of ERBE clear-sky measurement, established from ERBE pixel data, to sample the model radiative fluxes. Calculations with version 2 of the National Center for Atmospheric Research (NCAR) Community Climate Model using observed sea surface temperature (SST) show good agreement of clear-sky sampling from the proposed method with ERBE sampling. It is also shown that large improvements are achieved in the spatial variability of the model clear-sky radiative fluxes over ocean, with reference to ERBE, by using the new clear-sky sampling method.

Zhang, M. H.↗

Fluid Physics Under a Stochastic Acceleration Field

The research summarized in this report has involved a combined theoretical and computational study of fluid flow that results from the random acceleration environment present onboard space orbiters, also known as g-jitter. We have focused on a statistical description of the observed g-jitter, on the flows that such an acceleration field can induce in a number of experimental configurations of interest, and on extending previously developed methodology to boundary layer flows. Narrow band noise has been shown to describe many of the features of acceleration data collected during space missions. The scale of baroclinically induced flows when the driving acceleration is random is not given by the Rayleigh number. Spatially uniform g-jitter induces additional hydrodynamic forces among suspended particles in incompressible fluids. Stochastic modulation of the control parameter shifts the location of the onset of an oscillatory instability. Random vibration of solid boundaries leads to separation of boundary layers. Steady streaming ahead of a modulated solid-melt interface enhances solute transport, and modifies the stability boundaries of a planar front.

Vinals, Jorge↗

The MJO-ENSO Relationship: A Re-assessment

Noting the similarities among the spatial patterns of outgoing longwave radiation among MJO and ENSO, Lau and Chan speculated a possible relationship between the two phenomena. This speculation received a substantial boost in credibility after the 1997-98 El Nino, when MJO activities were found to be substantially enhanced prior to the onset of the warm phase, and clear signals of oceanic Kelvin waves forced by MJO induced anomalous surface wind were detected as possible triggers of ENSO. Yet statistical and modeling studies have so far yielded either nil or at best, very weak relationship between MJO activities and SST. Recently Kessler suggested using an MJO index which includes convective variability in the equatorial central Pacific lead to a more robust MJO-ENSO relationship. Clearly, while MJO might have been instrumental in triggering some El Nino, there are other events that can occur without any MJO trigger.

Lau, William K. M.↗

Exploring Carbon Mineral Systems: Recent Advances in C Mineral Evolution, Mineral Ecology, and Network Analysis

Large and growing data resources on the spatial and temporal diversity and distribution of the more than 400 carbon-bearing mineral species reveal patterns of mineral evolution and ecology. Recent advances in analytical and visualization techniques leverage these data and are propelling mineralogy from a largely descriptive field into one of prediction within complex, integrated, multidimensional systems. These discoveries include: (1) systematic changes in the character of carbon minerals and their networks of coexisting species through deep time; (2) improved statistical predictions of the number and types of carbon minerals that occur on Earth but are yet to be discovered and described; and (3) a range of proposed and ongoing studies related to the quantification of network structures and trends, relation of mineral “natural kinds” to their genetic environments, prediction of the location of mineral species across the globe, examination of the tectonic drivers of mineralization through deep time, quantification of preservational and sampling bias in the mineralogical record, and characterization of feedback relationships between minerals and geochemical environments with microbial populations. These aspects of Earth’s carbon mineralogy underscore the complex coevolution of the geosphere and biosphere and highlight the possibility for scientific discovery in Earth and planetary systems.

Carbon↗

Wichita Climate II: Quantifying and Mapping Urban Heat to Inform Equitable and Sustainable Urban Planning Initiatives in Wichita, Kansas

Wichita, Kansas is experiencing a host of climate threats, particularly extreme heat manifested through Urban Heat Islands (UHI). Heat is unevenly distributed within cities due to factors such as income inequality, historical discriminatory practices like redlining, and divestment in neighborhoods of color. This leads to less vegetation and more heat-absorbing infrastructure in specific communities. Moreover, adverse effects of heat, including heat-related morbidity and mortality, disproportionately impact populations that experience vulnerability through social inequities and structural discrimination. Heat vulnerability is a combination of the factors of heat exposure, sensitivity, and adaptive capacity, and can be harnessed to guide urban heat interventions. This DEVELOP project partnered with the City of Wichita to understand the spatial distribution and drivers of UHIs and heat vulnerability indicators. The team modeled outcomes of tree cover interventions using Landsat 8’s Thermal Infrared Sensor (TIRS) and Operational Land Imager (OLI), Landsat 9 TIRS-2 and OLI-2, and the International Space Station’s Ecosystem Spaceborne Thermal Radiometer Experiment on the International Space Station (ECOSTRESS) sensor, along with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Cooling model. The team also leveraged statistical analysis by implementing principal component analysis to develop a heat vulnerability index (HVI) specific to Wichita. Ultimately, the project’s outputs will inform the City of Wichita’s Climate Adaptation and Mitigation Plan, identify priority areas for heat mitigation initiatives, and be used in public-facing communications to educate communities on the impacts of urban heat.

Environmental Justice↗

Convective Weather Forecast Quality Metrics for Air Traffic Management Decision-Making

Since numerical weather prediction models are unable to accurately forecast the severity and the location of the storm cells several hours into the future when compared with observation data, there has been a growing interest in probabilistic description of convective weather. The classical approach for generating uncertainty bounds consists of integrating the state equations and covariance propagation equations forward in time. This step is readily recognized as the process update step of the Kalman Filter algorithm. The second well known method, known as the Monte Carlo method, consists of generating output samples by driving the forecast algorithm with input samples selected from distributions. The statistical properties of the distributions of the output samples are then used for defining the uncertainty bounds of the output variables. This method is computationally expensive for a complex model compared to the covariance propagation method. The main advantage of the Monte Carlo method is that a complex non-linear model can be easily handled. Recently, a few different methods for probabilistic forecasting have appeared in the literature. A method for computing probability of convection in a region using forecast data is described in Ref. 5. Probability at a grid location is computed as the fraction of grid points, within a box of specified dimensions around the grid location, with forecast convection precipitation exceeding a specified threshold. The main limitation of this method is that the results are dependent on the chosen dimensions of the box. The examples presented Ref. 5 show that this process is equivalent to low-pass filtering of the forecast data with a finite support spatial filter. References 6 and 7 describe the technique for computing percentage coverage within a 92 x 92 square-kilometer box and assigning the value to the center 4 x 4 square-kilometer box. This technique is same as that described in Ref. 5. Characterizing the forecast, following the process described in Refs. 5 through 7, in terms of percentage coverage or confidence level is notionally sound compared to characterizing in terms of probabilities because the probability of the forecast being correct can only be determined using actual observations. References 5 through 7 only use the forecast data and not the observations. The method for computing the probability of detection, false alarm ratio and several forecast quality metrics (Skill Scores) using both the forecast and observation data are given in Ref. 2. This paper extends the statistical verification method in Ref. 2 to determine co-occurrence probabilities. The method consists of computing the probability that a severe weather cell (grid location) is detected in the observation data in the neighborhood of the severe weather cell in the forecast data. Probabilities of occurrence at the grid location and in its neighborhood with higher severity, and with lower severity in the observation data compared to that in the forecast data are examined. The method proposed in Refs. 5 through 7 is used for computing the probability that a certain number of cells in the neighborhood of severe weather cells in the forecast data are seen as severe weather cells in the observation data. Finally, the probability of existence of gaps in the observation data in the neighborhood of severe weather cells in forecast data is computed. Gaps are defined as openings between severe weather cells through which an aircraft can safely fly to its intended destination. The rest of the paper is organized as follows. Section II summarizes the statistical verification method described in Ref. 2. The extension of this method for computing the co-occurrence probabilities in discussed in Section HI. Numerical examples using NCWF forecast data and NCWD observation data are presented in Section III to elucidate the characteristics of the co-occurrence probabilities. This section also discusses the procedure for computing throbabilities that the severity of convection in the observation data will be higher or lower in the neighborhood of grid locations compared to that indicated at the grid locations in the forecast data. The probability of coverage of neighborhood grid cells is also described via examples in this section. Section IV discusses the gap detection algorithm and presents a numerical example to illustrate the method. The locations of the detected gaps in the observation data are used along with the locations of convective weather cells in the forecast data to determine the probability of existence of gaps in the neighborhood of these cells. Finally, the paper is concluded in Section V.

Chatterji, Gano B.↗

Efficient Implementation of an Optimal Interpolator for Large Spatial Data Sets

Interpolating scattered data points is a problem of wide ranging interest. A number of approaches for interpolation have been proposed both from theoretical domains such as computational geometry and in applications' fields such as geostatistics. Our motivation arises from geological and mining applications. In many instances data can be costly to compute and are available only at nonuniformly scattered positions. Because of the high cost of collecting measurements, high accuracy is required in the interpolants. One of the most popular interpolation methods in this field is called ordinary kriging. It is popular because it is a best linear unbiased estimator. The price for its statistical optimality is that the estimator is computationally very expensive. This is because the value of each interpolant is given by the solution of a large dense linear system. In practice, kriging problems have been solved approximately by restricting the domain to a small local neighborhood of points that lie near the query point. Determining the proper size for this neighborhood is a solved by ad hoc methods, and it has been shown that this approach leads to undesirable discontinuities in the interpolant. Recently a more principled approach to approximating kriging has been proposed based on a technique called covariance tapering. This process achieves its efficiency by replacing the large dense kriging system with a much sparser linear system. This technique has been applied to a restriction of our problem, called simple kriging, which is not unbiased for general data sets. In this paper we generalize these results by showing how to apply covariance tapering to the more general problem of ordinary kriging. Through experimentation we demonstrate the space and time efficiency and accuracy of approximating ordinary kriging through the use of covariance tapering combined with iterative methods for solving large sparse systems. We demonstrate our approach on large data sizes arising both from synthetic sources and from real applications.

Memarsadeghi, Nargess↗

Techniques for generation of control and guidance signals derived from optical fields, part 2

The development is reported of a high resolution technique for the detection and identification of landmarks from spacecraft optical fields. By making use of nonlinear regression analysis, a method is presented whereby a sequence of synthetic images produced by a digital computer can be automatically adjusted to provide a least squares approximation to a real image. The convergence of the method is demonstrated by means of a computer simulation for both elliptical and rectangular patterns. Statistical simulation studies with elliptical and rectangular patterns show that the computational techniques developed are able to at least match human pattern recognition capabilities, even in the presence of large amounts of noise. Unlike most pattern recognition techniques, this ability is unaffected by arbitrary pattern rotation, translation, and scale change. Further development of the basic approach may eventually allow a spacecraft or robot vehicle to be provided with an ability to very accurately determine its spatial relationship to arbitrary known objects within its optical field of view.

Hemami, H.↗

Sea ice ridging in the eastern Weddell Sea

Measurements of sea ice ridge heights and spatial frequency in the eastern Weddell Sea using a shift-based acoustical sounder are reported. A total of 933 ridges were measured along a track length of 415 km using a minimum ridge sail height of 0.75 m. The ridge frequency varied from 0.4 to 10.5 ridges per km. The mean height of the ridges was found to be about 1.1 m regardless of the ridge frequency. These results are compared to other ridging statistics from the Ross Sea and found to be similar. Comparison with Arctic data indicates that the height and frequency of the ridges are considerably less in the Weddell Sea than in the Arctic. Whereas in the Arctic, the mean ridge height tends to increase with the ridge frequency, this was not found to be the case in the Weddell Sea, where the mean ridge height remained constant irrespective of the ridge frequency. Estimates of the contribution of deformed ice to the total ice thickness are generally low except for a single 53-km section where the ridge frequency increased by an order of magnitude.

Lytle, V. I.↗

Climatological Features of the Upper Troposphere and Stratosphere in the GEOS-5 "MERRA" Analyses (1979-2008)

The realism of various aspects of the upper troposphere and stratosphere in the "Modern Era Retrospective-analysis for Research and Applications" (MERRA) dataset will be examined. The MERRA reanalysis extends from 1979 until the present, using the Goddard Earth Observing System, Version 5 (GEOS-5) data assimilation system. The model and analysis have a half-degree spatial resolution with 72 layers that are constrained by observations between the Earth's surface and the stratopause. A comprehensive, time-evolving suite of meteorological observations (e.g., in-situ temperature, moisture, wind and pressure measurements and space-based infrared and microwave radiances) is assimilated. Results show realistic depiction of dominant features, such as the quasi-biennial oscillation, jet structures (including interannual variaficns) and tropopause characteristics, as validated using independent observations and system statistics. Challenges for such reanalyses include the stability to transitions in the observing system, such as the replacement of MSU/SSU by the AMSU-A data in the middle atmosphere. The paper will discuss the use of satellite radiances and examine impacts of satellite drifts and instrument changes on the analyses.

Pawson, S.↗

Improved Hierarchical Optimization-Based Classification of Hyperspectral Images Using Shape Analysis

A new spectral-spatial method for classification of hyperspectral images is proposed. The HSegClas method is based on the integration of probabilistic classification and shape analysis within the hierarchical step-wise optimization algorithm. First, probabilistic support vector machines classification is applied. Then, at each iteration two neighboring regions with the smallest Dissimilarity Criterion (DC) are merged, and classification probabilities are recomputed. The important contribution of this work consists in estimating a DC between regions as a function of statistical, classification and geometrical (area and rectangularity) features. Experimental results are presented on a 102-band ROSIS image of the Center of Pavia, Italy. The developed approach yields more accurate classification results when compared to previously proposed methods.

Classification↗

New capabilities for the Wallops Island SPANDAR

Systems incorporated into the SPANDAR to increase spatial resolution and data processing capabilities are described. They include a minicomputer that performs real-time formatting of video data, rapid antenna scan control, and control of a digital integrator; a frequency diversity technique for faster accumulation of independent video samples; the on-line calibration system for insertion of high and low calibration signals during every PRF interval; and utilization of a large capacity, high speed computer. The resultant data will be used to create statistical thunderstorm models for designing microwave communications systems.

Kropfli, R. A.↗

The role of drop velocity in statistical spray description

The justification for describing a spray by treating drop velocity as a random variable on an equal statistical basis with drop size was studied experimentally. A double exposure technique using fluorescent drop photography was used to make size and velocity measurements at selected locations in a steady ethanol spray formed by a swirl atomizer. The size velocity data were categorized to construct bivariate spray density functions to describe the spray immediately after formation and during downstream propagation. Bimodal density functions were formed by environmental interaction during downstream propagation. Large differences were also found between spatial mass density and mass flux size distribution at the same location.

Groeneweg, J. F.↗

Direct simulation of isothermal-wall supersonic channel flow

The motivation for this work is the fact that in turbulent flows where compressibility effects are important, they are often poorly understood. A few examples of such flows are those associated with astrophysical phenomena and those found in combustion chambers, supersonic diffusers and nozzles, and over high-speed airfoils. For this project, we are primarily interested in compressibility effects near solid surfaces. Our main objective is an improved understanding of the fundamentals of compressible wall-bounded turbulence, which can in turn be used to cast light upon modeling concepts such as the Morkovin hypothesis and the Van Driest transformation. To this end, we have performed a direct numerical simulation (DNS) study of supersonic turbulent flow in a plane channel with constant-temperature walls. All of the relevant spatial and temporal scales are resolved so that no sub grid scale or turbulence model is necessary. The channel geometry was chosen so that finite Mach number effects can be isolated by comparing the present results to well established incompressible channel data. Here the fluid is assumed to be an ideal gas with constant specific heats, constant Prandtl number, and power-law temperature-dependent viscosity. Isothermal-wall boundary conditions are imposed so that a statistically stationary state may be obtained. The flow is driven by a uniform (in space) body force (rather than a mean pressure gradient) to preserve stream wise homogeneity, with the body force defined so that the total mass flux is constant.

Coleman, Gary N.↗

Radio-Optical Alignments in a Low Radio Luminosity Sample

We present an optically-based study of the alignment between the radio axes and the optical major axes of eight z approximately 0.7 radio galaxies in a 7C sample. The radio galaxies in this sample are approximately 20-times less radio luminous than 3C galaxies at the same redshift, and are significantly less radio-luminous than any other well-defined samples studied to date. Using Nordic Optical Telescope images taken in good seeing conditions at rest-frame wavelengths just longward of the 4000A break, we find a statistically significant alignment effect in the 7C sample. Furthermore, in two cases where the aligned components are well separated from the host we have been able to confirm spectroscopically that they are indeed at the same redshift as the radio galaxy. However, a quantitative analysis of the alignment in this sample and in a corresponding 3C sample from HST (Hubble Space Telescope) archival data indicates that the percentage of aligned flux may be lower and of smaller spatial scale in the 7C sample. Our study suggests that alignments on the 50-kpc scale are probably closely related to the radio luminosity, whereas those on the 15 kpc scale are not. We discuss these results in the context of popular models for the alignment effect.

Lacy, Mark↗

Direct Numerical Simulation of Supersonic Turbulent Boundary Layers

The talk will present some initial results from the direct numerical simulation (DNS) of compressible turbulent boundary layers. We solve numerically the compressible Navier-Stokes equations using a method based on Spalart's transformation for the incompressible turbulent boundary layer. This allows the spatially developing boundary layer to be transformed to a calculation with periodic boundary conditions in the streamwise and spanwise directions. The equations are solved using Fourier expansions in the horizontal directions and B-splines in the wall-normal direction. The first simulation is at Mach 2.5 with a momentum thickness Reynolds number based on wall viscosity of R(sub theta(sup 1)) = 825. We are examining the physics of the compressible boundary layer using turbulence statistics and budget equations. The turbulence statistics include: rms (root mean square) and mean profiles, energy spectra, and two-point correlations. It is found that there are large density gradients which require significantly more resolution than the incompressible case.

Guarini, Stephen↗

Forecasting Lightning Threat using Cloud-resolving Model Simulations

As numerical forecasts capable of resolving individual convective clouds become more common, it is of interest to see if quantitative forecasts of lightning flash rate density are possible, based on fields computed by the numerical model. Previous observational research has shown robust relationships between observed lightning flash rates and inferred updraft and large precipitation ice fields in the mixed phase regions of storms, and that these relationships might allow simulated fields to serve as proxies for lightning flash rate density. It is shown in this paper that two simple proxy fields do indeed provide reasonable and cost-effective bases for creating time-evolving maps of predicted lightning flash rate density, judging from a series of diverse simulation case study events in North Alabama for which Lightning Mapping Array data provide ground truth. One method is based on the product of upward velocity and the mixing ratio of precipitating ice hydrometeors, modeled as graupel only, in the mixed phase region of storms at the -15\dgc\ level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domainwide statistics of the peak values of simulated flash rate proxy fields against domainwide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. A blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Weather Research and Forecast Model simulations of selected North Alabama cases show that this model can distinguish the general character and intensity of most convective events, and that the proposed methods show promise as a means of generating quantitatively realistic fields of lightning threat. However, because models tend to have more difficulty in correctly predicting the instantaneous placement of storms, forecasts of the detailed location of the lightning threat based on single simulations can be in error. Although these model shortcomings presently limit the precision of lightning threat forecasts from individual runs of current generation models, the techniques proposed herein should continue to be applicable as newer and more accurate physically-based model versions, physical parameterizations, initialization techniques and ensembles of cloud-allowing forecasts become available.

McCaul, E. W., Jr.↗