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At least 37 records · Page 2

Assessment of landscape-scale fluxes of carbon dioxide and methane in subtropical coastal wetlands of South Florida

Coastal wetlands play a significant role in the storage of “blue carbon,” indicating their importance in the carbon biogeochemistry in the coastal zone and in global climate change mitigation strategies. We present airborne eddy covariance observations of CO 2 and CH 2 fluxes collected in southern Florida as part of the NASA BlueFlux mission during April 2022, October 2022, February 2023, and April 2023. The flux data generated from this mission consists of over 100 flight hours and more than 6,000 km of horizontal distance over coastal saline and freshwater wetlands. We find that the spatial and temporal heterogeneity in CO 2 and CH 2 exchange is primarily influenced by season, vegetation type, ecosystem productivity, and soil inundation. The largest CO 2 uptake fluxes of more than 20 μmol m -2 s -1 were observed over mangroves during all deployments and over swamp forests during flights in April. The greatest CH 4 effluxes of more than 250 nmol m -2 s -1 were measured at the end of the wet season in October 2022 over freshwater marshes and swamp shrublands. Although the combined Everglades National Park and Big Cypress National Preserve region was a net sink for carbon, CH 4 emissions reduced the ecosystem carbon uptake capacity (net CO 2 exchange rates) by 11%–91%. Average total net carbon exchange rates during the flight periods were −4 to −0.2 g CO 2 -eq m -2 d -1 . Our results highlight the importance of preserving mangrove forests and point to potential avenues of further research for greenhouse gas mitigation strategies.

atmosphere

Radiative Flux Measurements from ARISE: A Comparison with CERES Top-of-Atmosphere Radiative Fluxes

Uncertainty in top-of-atmosphere (TOA) radiation fluxes observations are larger in the Arctic than in other regions. These uncertainties are due to the low sun angles and the highly reflective, anisotropic, and heterogeneous surface conditions. Quantifying, attributing, and reducing Arctic TOA radiative flux uncertainty enables a better understanding of the rapidly changing Arctic. To advance this goal, we compare the Cloud and Earth’s Radiant Energy System (CERES) TOA radiative fluxes with Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) campaign measurements collected in September 2014. We compare CERES TOA and aircraft radiative flux measurements using two complementary approaches: grid box average fluxes and instantaneously matched footprints. The grid box mean flux comparison indicates an agreement between CERES and aircraft measurements within 2 uncertainty (calibration and inversion) in the longwave for all five grid boxes and for four-of-five grid boxes in the shortwave; shortwave and longwave mean differences are -7.9 and +2.3 Wm‑2, respectively. The comparison of 36 instantaneously matched footprints with aircraft measurements reveals mean differences of -10.5 and 0.4 Wm‑2 in the shortwave and longwave, respectively. To further explore the persistent negative difference in the shortwave, we further quantify the effects of temporal and spatial sampling differences, angular distribution models, and scene identification to CERES-aircraft differences. Our analysis indicates that sampling differences (including scene evolution) account for an additional 1.8 and 1.7% uncertainty in the shortwave and longwave, respectively and indicates no bias. After accounting for this sampling uncertainty, all CERES-aircraft grid box mean fluxes agree within 2 uncertainty. Scene identification errors due to sea ice concentration data set differences exhibit no bias in the shortwave flux difference and indicate the possibility of substantial differences in the CERES fluxes in specific cases with large spatial heterogeneity. Considering the instantaneously matched footprints, we find that the angular distribution models account may account for up to ‑7.3 Wm-2 of the persistent CERES-aircraft shortwave flux difference due to systematic differences in the anisotropy for sea ice partly cloudy scenes. Additional analysis using a special scan model with the CERES FM2 instrument suggests a significant view zenith angle dependence of the CERES fluxes for sea ice partly cloudy scenes where shortwave fluxes systematically decrease with increasing view zenith angle; no dependence is found for other scene types. We conclude that (1) spatial heterogeneity and scene temporal evolution substantially limit our ability to use aircraft measurements to place strong constraints on CERES TOA fluxes and (2) that the representation of anisotropy in sea ice partly cloudy scenes is a significant factor contributing to the persistent negative CERES-aircraft shortwave flux difference in this comparison and require additional data to analysis fully quantify the potential bias.

Patrick C Taylor

A comparison between CERES TOA Radiative Fluxes and Airborne Radiative Flux Measurements from ARISE

Uncertainty in top-of-atmosphere (TOA) radiation fluxes observations are larger in the Arctic than in other regions. These uncertainties are due to the low sun angles and the highly reflective, anisotropic, and heterogeneous surface conditions. Quantifying, attributing, and reducing Arctic TOA radiative flux uncertainty enables a better understanding of the rapidly changing Arctic. To advance this goal, we compare the Cloud and Earth’s Radiant Energy System (CERES) TOA radiative fluxes with Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) campaign measurements collected in September 2014. We compare CERES TOA and aircraft radiative flux measurements using two complementary approaches: grid box average fluxes and instantaneously matched footprints. The grid box mean flux comparison indicates an agreement between CERES and aircraft measurements within 2σ uncertainty (calibration and inversion) in the longwave for all five grid boxes and for four-of-five grid boxes in the shortwave; shortwave and longwave mean differences are -7.9 and +2.3 Wm 2, respectively. The comparison of 36 40 instantaneously matched footprints with aircraft measurements reveals mean differences of -120.25 and -1.00.4 Wm 2 in the shortwave and longwave, respectively. To further explore the persistent negative difference in the shortwave, Wwe further quantify the effects of temporal and spatial sampling differences, angular distribution models, and scene identification to CERES-aircraft differences. Our analysis indicates that sampling differences (including scene evolution) account for an additional 1.8 and 1.7% uncertainty in the shortwave and longwave, respectively and , but indicates no bias. After accounting for this sampling uncertainty, all CERES-aircraft grid box mean fluxes agree within 2σ uncertainty. Scene identification errors due to sea ice concentration data set differences exhibit no bias in the shortwave flux difference and indicate the possibility of substantial differences in the CERES fluxes in specific cases with large spatial heterogeneity. Considering the instantaneously matched footprints, we find that the angular distribution models account may account for up to 7.3 Wm-2 of the persistent CERES-aircraft shortwave flux difference due to systematic differences in the anisotropy for sea ice partly cloudy scenes. Additional analysis using a special programmable scan model with the CERES FM2 instrument suggests a significant view zenith angle dependence of the CERES fluxes for sea ice partly cloudy scenes where shortwave fluxes systematically decrease with increasing view zenith angle; no dependence is found for other scene types. We conclude that (1) spatial heterogeneity and scene temporal evolution substantially limit our ability to use aircraft measurements to place strong constraints on CERES TOA fluxes and (2) that the representation of anisotropy in sea ice partly cloudy scenes is likely a significant factor contributing to the persistent negative CERES-aircraft shortwave flux difference in this comparison and require additional data to analysis fully quantify the potential bias.

Patrick C. Taylor

Monitoring Land Surface Albedo and Vegetation Dynamics Using High Spatial and Temporal Resolution Synthetic Time Series from Landsat and the MODIS BRDF/NBAR/Albedo Product

Seasonal vegetation phenology can significantly alter surface albedo which in turn affects the global energy balance and the albedo warmingcooling feedbacks that impact climate change. To monitor and quantify the surface dynamics of heterogeneous landscapes, high temporal and spatial resolution synthetic time series of albedo and the enhanced vegetation index (EVI) were generated from the 500-meter Moderate Resolution Imaging Spectroradiometer (MODIS) operational Collection V006 daily BRDF (Bidirectional Reflectance Distribution Function) / NBAR (Nadir BRDF-Adjusted Reflectance) / albedo products and 30-meter Landsat 5 albedo and near-nadir reflectance data through the use of the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The traditional Landsat Albedo (Shuai et al., 2011) makes use of the MODIS BRDFAlbedo products (MCD43) by assigning appropriate BRDFs from coincident MODIS products to each Landsat image to generate a 30-meter Landsat albedo product for that acquisition date. The available cloud free Landsat 5 albedos (due to clouds, generated every 16 days at best) were used in conjunction with the daily MODIS albedos to determine the appropriate 30-meter albedos for the intervening daily time steps in this study. These enhanced daily 30-meter spatial resolution synthetic time series were then used to track albedo and vegetation phenology dynamics over three Ameriflux tower sites (Harvard Forest in 2007, Santa Rita in 2011 and Walker Branch in 2005). These Ameriflux sites were chosen as they are all quite nearby new towers coming on line for the National Ecological Observatory Network (NEON), and thus represent locations which will be served by spatially paired albedo measures in the near future. The availability of data from the NEON towers will greatly expand the sources of tower albedometer data available for evaluation of satellite products. At these three Ameriflux tower sites the synthetic time series of broadband shortwave albedos were evaluated using the tower albedo measurements with a Root Mean Square Error (RMSE) less than 0.013 and a bias within the range of 0.006. These synthetic time series provide much greater spatial detail than the 500 meter gridded MODIS data, especially over more heterogeneous surfaces, which improves the efforts to characterize and monitor the spatial variation across species and communities. The mean of the difference between maximum and minimum synthetic time series of albedo within the MODIS pixels over a subset of satellite data of Harvard Forest (16 kilometers by 14 kilometers) was as high as 0.2 during the snow-covered period and reduced to around 0.1 during the snow-free period. Similarly, we have used STARFM to also couple MODIS Nadir BRDF-Adjusted Reflectances (NBAR) values with Landsat 5 reflectances to generate daily synthetic times series of NBAR and thus Enhanced Vegetation Index (NBAR-EVI) at a 30-meter resolution. While normally STARFM is used with directional reflectances, the use of the view angle corrected daily MODIS NBAR values will provide more consistent time series. These synthetic times series of EVI are shown to capture seasonal vegetation dynamics with finer spatial and temporal details, especially over heterogeneous land surfaces.

Vegetation Index

Stress and Strain Heterogeneity and Persistence in Uniaxially‐ and Triaxially‐Loaded Sandstone

Two critical questions in brittle rock mechanics are how rocks developed localized strains and to what extent internal stress heterogeneity controls this localization and subsequent macroscopic failure. Definitive answers have not yet been found, but would provide insight into rock fracture mechanics as relevant to hydrocarbon extraction and sequestration. Here, we use synchrotron X‐ray tomography (XRT) and 3D X‐ray diffraction (3DXRD) during uniaxial and triaxial tests on Nugget and Bentheimer sandstones to examine strain and stress localization prior to mechanical failure. 3DXRD was used to measure intra‐granular lattice strains which were used to compute elastic stress tensors of each grain. Digital volume correlation (DVC) was applied to XRT images to determine the strain field in the sample. Both samples featured marked spatial heterogeneity, localization, and temporal persistence of elevated stresses and strains during their mechanical deformation toward failure. Both samples featured a majority of grains with at least one principal stress component that was tensile, a signature of the influence of heterogeneity on stress transmission. Measurements further revealed that compressive stress orientations and statistics evolved in a similar manner to those of inter‐particle forces in loose granular materials, with triaxially‐compressed rock exhibiting enhanced grain stress heterogeneity compared to uniaxially‐compressed rock. Our results complement recent work by others who employed XRT and scanning 3DXRD to study triaxially‐compressed sandstone, but extend those results to uniaxial compression, sandstones of varied porosity, and grain stress measurements throughout the 3D full extent of the samples rather than in a single layer examined with scanning 3DXRD.

58 GEOSCIENCES

Strike-slip faulting, wrinkle ridges, and time variable stress states in the Coprates Region of Mars

The existence of strike-slip faults was recently documented in two locations on Mars. Two clear examples are reviewed located southeast of Valles Marineris and preliminary evidence is presented for more widespread strike-slip deformation elsewhere in Coprates. The first two examples show that strike-slip faulting occurred in a broad zone east of the Coprates Rise spanning approximately 400 km east-west by perhaps 1000 km north-south. The last example suggests that the growth of major wrinkle ridges throughout Coprates may have been influenced by horizontally directed shear stresses and that more than one generation of ridges was produced. Thus, 'compressional' deformation of ridged plains south of Valles Marineris was spatially heterogeneous and a temporal change in stress may have been involved.

Schultz, Richard A.

Two dimensional, transient catalytic combustion of CO-air on platinum

The light off transient of catalytic combustion of lean CO-air mixtures in a platinum coated channel of a honeycomb monolith is studied with a model that resolves transient radial and axial gradients in both the gas and the solid. For the conditions studied it is concluded that: the initial heat release occurs near the entrance at the gas-solid interface and is controlled by heterogeneous reactions; large spatial and temporal temperature gradients occur in the solid near the entrance controlled mostly by the availability of fuel; the temperature of the solid near the entrance achieves almost its steady state value before significant heating of the back; heterogeneous reactions and the gas heated up front and flowing downstream heat the back of the solid; the overall transient time is controlled by the thermal inertia of the solid and by forced convection; radiation significantly influences both transient and steady state particularly near the entrance; the oxidation of CO occurs mostly on the catalyst and becomes diffusion controlled soon into the transient.

Sinha, N.

Controlled electrochemical nutrient delivery to enhance marine primary productivity

Oceanic photosynthesis contributes to approximately half of the Earth’s net annual primary productivity. Marine photosynthetic productivity has a high degree of heterogeneity due to spatial and temporal co-limitations of light, temperature, and/or nutrients. Across coastal, near-shore, and open ocean regions, insufficient concentrations of key nutrients (e.g., N, P, Fe) can limit primary productivity. Although studies have shown a significant increase in primary productivity with the addition of low doses of trace nutrients, a sustainable approach to reliably deliver and maintain low doses of nutrients and ensure their bioavailability, remains a challenge. Chemical nutrient addition has relied on the use of chelating agents to ensure nutrient bioavailability, but synthetic chelators are persistent environmental pollutants. In this study, we demonstrate for the first time the use of a controlled electrochemical nutrient delivery (CEND) approach to accelerate the growth of phytoplankton without the need for such chelators. Our study uses commercial stainless-steel electrodes to deliver low concentrations of iron to enhance growth rates in the microalga Picochlorum celeri TG2. To demonstrate the process control offered by the CEND method, we evaluate iron delivery as a function of pulse time, pulse frequency, and rest time between pulses. Our data show that at the same total Fe dose of 163 ppb, electrochemical iron delivery can achieve 9.54 ± 0.58 mg biomass/µg Fe, which is comparable to 9.14 ± 0.17 mg biomass/µg Fe achieved with chemical iron additions that include the synthetic chelating agent ethylenediaminetetraacetic acid (EDTA). Further, when different total iron doses (163 ppb, 325 ppb, and 650 ppb) were delivered over 72 h using CEND, biomass yield per iron dose was higher at lower doses: 9.54 ± 0.58 mg biomass/µg Fe at 163 ppb vs. 4.32 ± 0.32 mg biomass/µg Fe at 650 ppb. This highlights the benefits of CEND in delivering frequent and low doses of nutrients for improved process efficiency. Preliminary assessments show both lower cost and reduced greenhouse gas emissions from electrochemical over chemical iron additions with EDTA. The CEND approach opens new pathways to enhance marine primary productivity, without the unintended environmental impacts of synthetic chelators.

analytical chemistry

Real Time Land-Surface Hydrologic Modeling Over Continental US

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.

Houser, Paul R.

Modeling and Prediction of Wildfire Hazard in Southern California, Integration of Models with Imaging Spectrometry

Large urban wildfires throughout southern California have caused billions of dollars of damage and significant loss of life over the last few decades. Rapid urban growth along the wildland interface, high fuel loads and a potential increase in the frequency of large fires due to climatic change suggest that the problem will worsen in the future. Improved fire spread prediction and reduced uncertainty in assessing fire hazard would be significant, both economically and socially. Current problems in the modeling of fire spread include the role of plant community differences, spatial heterogeneity in fuels and spatio-temporal changes in fuels. In this research, we evaluated the potential of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR) data for providing improved maps of wildfire fuel properties. Analysis concentrated in two areas of Southern California, the Santa Monica Mountains and Santa Barbara Front Range. Wildfire fuel information can be divided into four basic categories: fuel type, fuel load (live green and woody biomass), fuel moisture and fuel condition (live vs senesced fuels). To map fuel type, AVIRIS data were used to map vegetation species using Multiple Endmember Spectral Mixture Analysis (MESMA) and Binary Decision Trees. Green live biomass and canopy moisture were mapped using AVIRIS through analysis of the 980 nm liquid water absorption feature and compared to alternate measures of moisture and field measurements. Woody biomass was mapped using L and P band cross polarimetric data acquired in 1998 and 1999. Fuel condition was mapped using spectral mixture analysis to map green vegetation (green leaves), nonphotosynthetic vegetation (NPV; stems, wood and litter), shade and soil. Summaries describing the potential of hyperspectral and SAR data for fuel mapping are provided by Roberts et al. and Dennison et al. To utilize remotely sensed data to assess fire hazard, fuel-type maps were translated into standard fuel models accessible to the FARSITE fire spread simulator. The FARSITE model and BEHAVE are considered industry standards for fire behavior analysis. Anderson level fuels map, generated using a binary decision tree classifier are available for multiple dates in the Santa Monica Mountains and at least one date for Santa Barbara. Fuel maps that will fill in the areas between Santa Barbara and the Santa Monica Mountains study sites are in progress, as part of a NASA Regional Earth Science Application Center, the Southern California Wildfire Hazard Center. Species-level maps, were supplied to fire managing agencies (Los Angeles County Fire, California Department of Forestry). Research results were published extensively in the refereed and non-refereed literature. Educational outreach included funding of several graduate students, undergraduate intern training and an article featured in the California Alliance for Minorities Program (CAMP) Quarterly Journal.

Roberts, Dar A.

On the Feasibility of Studying Shortwave Aerosol Radiative Forcing of Climate Using Dual-Wavelength Aerosol Backscatter Lidar

The current low confidence in the estimates of aerosol-induced perturbations of Earth's radiation balance is caused by the highly non-uniform compositional, spatial and temporal distributions of tropospheric aerosols on a global scale owing to their heterogeneous sources and short lifetimes. Nevertheless, recent studies have shown that the inclusion of aerosol effects in climate model calculations can improve agreement with observed spatial and temporal temperature distributions. In light of the short lifetimes of aerosols, determination of their global distribution with space-borne sensors seems to be a necessary approach. Until recently, satellite measurements of tropospheric aerosols have been approximate and did not provide the full set of information required to determine their radiative effects. With the advent of active aerosol remote sensing from space (e.g., PICASSO-CENA), the applicability fo lidar-derived aerosol 180 deg -backscatter data to radiative flux calculations and hence studies of aerosol effects on climate needs to be investigated.

Redemann, Jens

Modeling of Sub-Grid Heterogeneity and its Impact on GCM Global Radiation Balance

The spatial and temporal variability of high, low, and mid-level clouds is obtained from ISCCP D1 data. Monthly mean global maps of the observed cloud variability are used to re-scale GCM prognostic cloud optical depths and radiative parameters via the Monte Carlo cloud heterogeneity parameterization that utilizes the existing plane-parallel GCM radiative transfer model to compute radiative fluxes for inhomogeneous cloud distributions. The GCM radiative fluxes at TOA and the ground surface are then compared to ERBE and GEBA results. These comparisons show that including sub-grid cloud variability in the GCM radiative model improves agreement between the GCM radiative energy budget components and observations,

Lacis, Andrew

Deconvolution of dynamic heterogeneity in protein structure

Heterogeneity is intrinsic to the dynamic process of a chemical reaction. As reactants are converted to products via intermediates, the nature and extent of heterogeneity vary temporally throughout the duration of the reaction and spatially across the molecular ensemble. The goal of many biophysical techniques, including crystallography and spectroscopy, is to establish a reaction trajectory that follows an experimentally provoked dynamic process. It is essential to properly analyze and resolve heterogeneity inevitably embedded in experimental datasets. We have developed a deconvolution technique based on singular value decomposition (SVD), which we have rigorously practiced in diverse research projects. In this review, we recapitulate the motivation and challenges in addressing the heterogeneity problem and lay out the mathematical foundation of our methodology that enables isolation of chemically sensible structural signals. We also present a few case studies to demonstrate the concept and outcome of the SVD-based deconvolution. Finally, we highlight a few recent studies with mechanistic insights made possible by heterogeneity deconvolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review

In this paper we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort.

Earth observations

Laser-Induced Incandescence in Microgravity

Knowledge of soot concentration is important due to its presence and impact upon a wide range of combustion processes ranging from diffusion to premixed flames, laminar to turbulent processes and homogeneous to heterogeneous combustion. Measurement of soot volume fraction (f(sub v)) is essential to discerning its formation and growth. The presence of soot also affects other physical and chemical properties of combustion thereby affecting studies not directly concerned with either its formation or growth, such as radiative heat transfer, CO oxidation and fuel vaporization or pyrolysis rates. Microgravity offers unique opportunities for studying both soot growth and the effect of soot radiation upon flame structure and spread. Spatial scales and residence time scales are greatly extended in 0-g facilitating soot growth studies. With the varied geometries, short duration microgravity test times and time-varying processes there is a demand for measurement of f(sub v) with high spatial and temporal resolution. Laser-induced incandescence (LII) has advanced f(sub v) measurements in many 1-g combustion processes. To create laser-induced incandescence, a pulsed high intensity laser heats soot to incandescence temperatures. Using appropriate spectral and temporal detection conditions, the resulting incandescence can be selectively detected apart from the non-laser-heated soot and flame gases. Theoretical modelling and experiments have shown that the resulting incandescence is representative of f(sub v). Using an intensified array camera and a laser sheet for excitation, one- and two-dimensionally resolved LII images of f(sub v) have been obtained in 1-g. LII has been characterized and developed at NASA-Lewis for soot volume fraction determination in a wide range of 1-g combustion applications. Broadly grouped, the characterization work has included studies of excitation intensity, excitation wavelength and the optimum temporal and spectral detection conditions to enable an accurate representation of soot volume fraction by LII. Tests for special requirements imposed by different combustion processes have been performed in laminar and turbulent diffusion flames, rich sooting premixed flames, single droplet combustion, and other heterogeneous combustion. These studies demonstrated LII's high sensitivity, temporal and spatial capabilities and its geometric versatility. In contrast to the advantages offered to combustion studies by a microgravity environment, advanced diagnostics, specifically those requiring pulsed laser diagnostics have been limited due to the size, weight and power limitations in a low-gravity environment. Reported here are the first demonstrations of LII performed in a microgravity environment. Examples are shown for laminar and turbulent gas-jet diffusion flames in 0-g.

VanderWal, Randy L.

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

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.

Justice, C. O.