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Data Fusion and Mining Techniques to Map Water Use and Drought across Spatial and Temporal Scales

As the world’s water resources come under increasing tension due to dual stressors of climate change and population growth, accurate knowledge of water consumption through evapotranspiration (ET) over a range in spatial scales will be critical in developing adaptation strategies. Remote sensing methods for monitoring consumptive water use (e.g, ET) are becoming increasingly important, especially in areas of significant water and food insecurity. One method to estimate ET from satellite-based methods, the Atmosphere Land Exchange Inverse (ALEXI) model uses the change in mid-morning land surface temperature to estimate the partitioning of sensible and latent heat fluxes which are then used to estimate daily ET. This presentation will outline several recent enhancements to the ALEXI modeling system, with a focus on global ET and drought monitoring. Until recently, ALEXI has been limited to areas with high resolution temporal sampling of geostationary sensors. The use of geostationary sensors makes global mapping a complicated process, especially for real-time applications, as data from as many as five different sensors are required to be ingested and harmonized to create a global mosaic. However, our research team has developed a new and novel method of using twice-daily observations from polar-orbiting sensors such as MODIS and VIIRS to estimate the mid-morning rise in LST that is used to drive the energy balance estimations within ALEXI. This allows the method to be applied globally using a single sensor (in this case, initially MODIS with a planned transition to VIIRS) rather than a global compositing of all available geostationary data. Other advantages of this new method include the higher spatial resolution provided by MODIS and VIIRS and the increased sampling at high latitudes where oblique view angles limit the utility of geostationary sensors. This presentation will focus on global applications for mapping water use and drought using data mining and data fusion across spatial scales extending from 5-km to 30-m “field-scale” estimates.

Christopher Hain↗
DOE OSTI2022

The parameter-level performance of covariance matrix conditioning in cosmic microwave background data analyses

Empirical estimates of the band power covariance matrix are commonly used in cosmic microwave background (CMB) power spectrum analyses. While this approach easily captures correlations in the data, noise in the resulting covariance estimate can systematically bias the parameter fitting. Conditioning the estimated covariance matrix, by applying prior information on the shape of the eigenvectors, can reduce these biases and ensure the recovery of robust parameter constraints. In this work, we use simulations to benchmark the performance of four different conditioning schemes, motivated by contemporary CMB analyses. The simulated surveys measure the TT, TE, and EE power spectra over the angular multipole range 300 ≤ ℓ ≤ 3500 in Δℓ = 50 wide bins, for temperature map-noise levels of 10, 6.4, and $2\, \mu$K arcmin. We divide the survey data into N real = 30, 50, or 100 uniform subsets. We show the results of different conditioning schemes on the errors in the covariance estimate, and how these uncertainties on the covariance matrix propagate to the best-fitting parameters and parameter uncertainties. The most significant effect we find is an additional scatter in the best-fitting point, beyond what is expected from the data likelihood. For a minimal conditioning strategy, N real = 30, and a temperature map-noise level of 10$\, \mu$K arcmin, we find the uncertainty on the recovered best-fitting parameter to be ×1.3 larger than the apparent posterior width from the likelihood (×1.2 larger than the uncertainty when the true covariance is used). Stronger priors on the covariance matrix reduce the misestimation of parameter uncertainties to $\lt 1{{\ \rm per\ cent}}$. As expected, empirical estimates perform better with higher N real , ameliorating the adverse effects on parameter constraints.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Crystal c-axis mapping of hcp metals by conventional reflected polarized light microscopy: Application to untextured and textured cp-Titanium

Highlights: • A computer-aided methodology based on reflected PLM was developed for c-axis orientation mapping of hcp structures. • The methodology was applied to two alpha cp-Ti bulk samples with different texture characteristics. • Calibration and validation of the methodology were performed by using EBSD. - Abstract: Nowadays the crystallographic characterization of polycrystalline metals and metallic alloys is usually performed by means of the electron backscatter diffraction (EBSD) technique. However, when dealing with coarse structures presenting intrinsic optical anisotropy, polarized light microscopy (PLM) imaging might be an alternative or a complementary time-efficient technique. Accordingly, a new computer-aided methodology has been developed in the present study and successfully applied on the crystal c-axis characterization of a hexagonal close-packed (hcp) structure, alpha commercial pure-Titanium (cp-Ti). In this sense, the correlation between EBSD-based crystallographic parameters and PLM-based parameters under certain light microscope settings has been first established by direct comparison using a representative amount of random orientations. Finally, PLM-based c-axis mapping and subsequent c-axis texture plotting have been performed and validated with EBSD for untextured and textured cp-Ti.

36 MATERIALS SCIENCE↗
DOE OSTI2021

High-Resolution Spatio-Temporal Estimation of Net Ecosystem Exchange in Ice-Wedge Polygon Tundra Using In Situ Sensors and Remote Sensing Data

Land-atmosphere carbon exchange is known to be extremely heterogeneous in arctic ice-wedge polygonal tundra regions. In this study, a Kalman filter-based method was developed to estimate the spatio-temporal dynamics of daytime average net ecosystem exchange (NEEday) at 0.5-m resolution over a 550 m by 700 m study site. We integrated multi-scale, multi-type datasets, including normalized difference vegetation indices (NDVIs) obtained from a novel automated mobile sensor system (or tram system) and a greenness index map obtained from airborne imagery. We took advantage of the significant correlations between NDVI and NEEday identified based on flux chamber measurements. The weighted average of the estimated NEEday within the flux-tower footprint agreed with the flux tower data in term of its seasonal dynamics. We then evaluated the spatial variability of the growing season average NEEday, as a function of polygon geomorphic classes; i.e., the combination of polygon types—which are known to present different degradation stages associated with permafrost thaw—and microtopographic features (i.e., troughs, centers and rims). Our study suggests the importance of considering microtopographic features and their spatial coverage in computing spatially aggregated carbon exchange.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1982

Investigation of Antarctic crust and upper mantle using MAGSAT and other geophysical data

Antarctica is the perfect proving ground for testing data reduction procedures which are alternatives to the standard procedure employing polynomial fitting. Unreduced data (observed values minus corefield model theo each pass) were averaged in 3 degree bins. The resulting map was then high pass filtered using a finite Fourier transform filter so that spectral peaks between 4200 km and 5280 km were diminished by 1/3, peaks corresponding to wavelengths greater than or equal to 5280 km were diminished by 1/2, and the d.c. component was set equal to zero. The surface subtracted in this way differs from the polynomials used in the standard method in that it is static over the 5 north data window. The map produced is presented and the effects of the static model are compared to those of the dynamic mode.

Bentley, C. R.↗
DOE OSTI2015

Structural comparison of four different antibodies interacting with human papillomavirus 16 and mechanisms of neutralization

Cryo-electron microscopy (cryo-EM) was used to solve the structures of human papillomavirus type 16 (HPV16) complexed with fragments of antibody (Fab) from three different neutralizing monoclonals (mAbs): H16.1A, H16.14J, and H263.A2. The structure-function analysis revealed predominantly monovalent binding of each Fab with capsid interactions that involved multiple loops from symmetry related copies of the major capsid protein. The residues identified in each Fab-virus interface map to a conformational groove on the surface of the capsomer. In addition to the known involvement of the FG and HI loops, the DE loop was also found to constitute the core of each epitope. Surprisingly, the epitope mapping also identified minor contributions by EF and BC loops. Complementary immunological assays included mAb and Fab neutralization. The specific binding characteristics of mAbs correlated with different neutralizing behaviors in pre- and post-attachment neutralization assays. - Highlights: • We present HPV16-Fab complexes from neutralizing mAbs: H16.1A, H16.14J, and H263.A2. • The structure-function analysis revealed predominantly monovalent binding of each mAb. • Capsid–Fab interactions involved multiple loops from symmetry related L1 proteins. • Besides the known FG and HI loops, epitope mapping also identified DE, EF, and BC loops. • Neutralizing assays complement the structures to show multiple neutralization mechanisms.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Machine-Learning-Based Mapping and Modeling of Solar Energy with Ultra-High Spatiotemporal Granularity

Despite the rapid growth of solar energy, we still lack a dynamic, high-fidelity database that tracks the spatiotemporal variations of solar PVs and their associated infrastructures across different places at a spatially resolved scale. The absence of such data presents a barrier to various applications such as solar PV growth projection, solar energy integration, solar incentive design, and climate risk assessment. In this project, we aim to bridge this gap by developing AI-based algorithms to extract granular information about solar PV installations and their associated infrastructures (i.e., distribution grids) from widely available unstructured data like remote sensing images and street views. As a result, we have built the Solar Energy Atlas, a fine-grained, large-scale geospatial overlay of distributed solar PVs and distribution grids. On top of it, we have advanced the understanding of solar adoption and distribution grid vulnerability to climate-induced extremes. Our major contributions can be summarized as follow: (1) By developing new AI algorithms, we have built the most comprehensive solar PV spatiotemporal database covering the entire US. This is the first time we obtained the exact GPS locations, size, subtype, and installation year information for rooftop solar PVs across the US. This database can be used for solar PV growth projection, solar energy integration, solar energy policy analysis and design, and spatially-resolved climate risk assessment. (2) Leveraging this database, we have uncovered the socioeconomic driving factors that are correlated with earlier onset of solar adoption and higher saturated adoption levels. We have identified the heterogeneity in the effects of different types of financial incentives on solar adoption and provided implications for tailoring incentive design based on local income levels to promote equitable solar adoption. (3) We have developed a distribution grid GIS mapping algorithm which can obtain granular geospatial and topology information about distribution grids using multi-modal open data, reducing the dependency on hard-to-obtain smart meter data of conventional approaches. It shows effectiveness in both the U.S. and Sub-Saharan Africa. Using this algorithm, we have uncovered the non-uniform vulnerability of distribution grids to wildfires in California in the aspects of undergrounding protection and Distributed Energy Resources (DER) preparedness. This has provided important implications for improving the affordability and equity of grid adaptation approaches. (3) We have made our produced database publicly available and provided user-friendly interface to enable various stakeholders and the general public to interact with the data. We have also integrated the produced data into the Data Commons platform to enable the public to access the data and correlate it with other location-specific characteristics simply using natural language as queries. The impact of our project is three-fold: (1) New algorithms for mapping solar PVs and distribution grids across space and time, which are open source to facilitate researchers and industry; (2) New databases of solar PVs and distribution grids that have been made publicly available for engineering, social, and policy applications; (3) New understandings and actionable insights on the potential approaches to promoting solar adoption and reducing energy infrastructure vulnerabilities. In this report, we start by discussing the project background and motivation (section 5), followed by the overview of project objectives (section 6). Results and discussion for each task are presented in section 7. Significant accomplishments are summarized in section 8. This report will be concluded by discussing the paths forwards (section 9), products (section 10), and team roles (section 11).

14 SOLAR ENERGY↗
DOE OSTI2017

Structure-toxicity relationship of cefoperazone and its impurities to developing zebrafish by transcriptome and Raman analysis

Cefoperazone (CFP) is a potent antibacterial agent that is widely used for the treatment of bacterial infections. Previously, we found that both the C-7 and C-3 substituents of CFP are toxic functional groups, and two groups could affect gene expression in zebrafish embryos, thereby resulting in variable abnormal phenotypes. (6R, 7S)-cefoperazone (7S-CFP) is the 7-epimer of CFP and 1-methyl-1H-tetrazole-5-thiol (MTT) is the C-3 substituent of CFP. Both molecules are impurities isolated from CFP that can induce adverse effects. Transcriptome analysis was performed in the present study to identify differentially expressed genes (DEGs), coupled with Raman mapping of individual organ regions to detect changes in the biochemical composition of zebrafish embryos, which reflect the differences in distribution of the compounds. CFP, 7S–CFP, and MTT exposure altered the expression of 254, 368, and 1153 genes, respectively. Gene ontology analysis revealed that various processes related to development, growth, and morphology of tissues were significantly enriched with DEGs. We integrated seven co-DEGs with protein-protein interaction networks and identified various developmental processes that were regulated by the three compounds, including vasodilation, eye, brain, melanogenesis, and heart looping. Our findings suggested that Calca and Ptger4a may be potentially utilized as novel biomarkers for CFP, which causes bleeding. Raman analysis indicated that CFP, 7S-CFP, and MTT exhibited abnormal maps in tissues, which coincided with changes in their expression and morphological features. This study may provide bioinformatics and spectral information that may be used in further investigations on the relationship between structure and toxicity of drugs and impurities. - Highlights: • We studied the relationship between the structure and toxicity of cefoperazone. • Transcriptome strategy was performed to identify differentially expressed genes. • We integrated seven co-DEGs with protein-protein interaction networks. • Our results founded the novel biomarkers for cefoperazone, which causes bleeding. • Raman analysis indicated that three compounds exhibited abnormal maps in tissues.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2021

An Investigation on Seasonal and Diurnal Cycles of TOA Shortwave Radiations from DSCOVR/EPIC, CERES, MERRA-2, and ERA5

Reflected shortwave (SW) solar radiations at the top of atmosphere from Clouds and the Earth’s Radiant Energy System (CERES), Modern Era-Retrospective analysis for Research and Applications version 2 (MERRA-2), and ECMWF Reanalysis 5th Generation (ERA5) are examined to better under-stand their differences in spatial and temporal variations (seasonal and diurnal cycle time-scale) with respect to the observations from the Earth Polychromatic Imaging Camera (EPIC) on Deep Space Climate Observatory (DSCOVR) satellite. Comparisons between two reanalyses (MERRA-2 and ERA5) and EPIC reveal that MERRA-2 has a generally larger deviation from EPIC than ERA5, in terms of the SW radiance and diurnal variability in all seasons, which can be attributed to larger cloud biases in MERRA-2. MERRA-2 produces more ice/liquid water content than ERA5 over the tropical warm pool, leading to positive SW biases in cloud and radiance, while both reanalyses underestimate the observed SW radiance from EPIC in the stratus-topped region off the western coast of US/Mexico in the boreal summer. Himalaya/Tibet region in the boreal spring/summer and the midlatitude Southern Hemisphere in the boreal winter are the regions where MERRA-2 and ERA5 deviate largely from EPIC but their deviations have the opposite sign. Vertical structures of cloud ice/liquid water content explain reasonably well these contrasting differences between the two reanalyses. As two independent observa-ions, CERES and EPIC agree well with each other in terms of the SW radiance maps, showing 2-3% mean absolute errors over the tropical-midlatitudes. The CERES-EPIC consistency further confirms that the reanalyses still have challenges in representing the SW flux and its global distribution. In the CERES-EPIC observation differences, CERES slightly overestimates the diurnal cycle (as a function of local solar time) of the observed EPIC irradiance in the morning and underestimates in the after-noon, while the opposite is the case in the reanalyses.

Reflected shortwave radiance↗
NASA NTRS1979

A summary of research on the NASA-Global Atmospheric Sampling Program performed by the Atmospheric Sciences Research Center

The annual variations of ozone near the tropopause are derived from aircraft exhibit year-to-year differences which are not explicitly accounted for by the simple, classical ozone transport theory. Phenomena such as tropopause lifting, interannual variations in the rates of stratospheric-tropospheric exchange and meridional mixing, contribute differently to the distribution of ozone in this altitude region. Ozone encounter climatologies have been represented by global maps which show the probabilities of exceeding ambient ozone levels of 200, 300, and 400 ppbV along flight routes during the year. Continuous ozone records obtained from the GASP system revealed the presence of gravity waves whose wavelength is of the order 20 km. The GASP data cannot, however, be utilized for the evaluation of horizontal fluxes of such quantities as ozone, sensible heat, and zonal momentum; the data are too sparsely and irregularly distributed for the computation of stable correlations. Multiple species data from the unique circumglobal flight of a Pan American airliner on 28-30 October 1977 are discussed with particular regard to the apparent interhemispheric differences in tropospheric species concentrations, variation between the Arctic and Antarctic stratospheres, to possible covariations between species, and to potential source regions for various constituents.

Falconer, P. D.↗
NASA NTRS1993

Mapping the distribution of vesicular textures on silicic lavas using the Thermal Infrared Multispectral Scanner

To investigate the effect of vesicularity on TIMS (Thermal Infrared Multispectral Scanner) imagery independent of chemical variations, we studied a large rhyolitic flow of uniform composition but textural heterogeneity. The imagery was recalibrated so that the digital number values for a lake in the scene matched a calculated ideal spectrum for water. TIMS spectra for the lava show useful differences in coarsely and finely vesicular pumice data, particularly in TIMS bands 3 and 4. Images generated by ratioing these bands accurately map out those areas known from field studies to be coarsely vesicular pumice. These texture-related emissivity variations are probably due to the larger vesicles being relatively deeper and separated by smaller septa leaving less smooth glass available to give the characteristic emission of the lava. In studies of inaccessible lava flows (as on Mars) areas of coarsely vesicular pumice must be identified and avoided before chemical variations can be interpreted. Remotely determined distributions of vesicular and glassy textures can also be related to the volatile contents and potential hazards associated with the emplacement of silicic lava flows on Earth.

Ondrusek, Jaime↗
DOE OSTI2017

Internal delensing of Planck CMB temperature and polarization

We present a first internal delensing of CMB maps, both in temperature and polarization, using the public foreground-cleaned (SMICA) Planck 2015 maps. After forming quadratic estimates of the lensing potential, we use the corresponding displacement field to undo the lensing on the same data. We build differences of the delensed spectra to the original data spectra specifically to look for delensing signatures. After taking into account reconstruction noise biases in the delensed spectra, we find an expected sharpening of the power spectrum acoustic peaks with a delensing efficiency of 29 % (TT) 25 % (TE) and 22 % (EE). The detection significance of the delensing effects is very high in all spectra: 12 σ in EE polarization; 18 σ in TE; and 20 σ in TT. The null hypothesis of no lensing in the maps is rejected at 26 σ. While direct detection of the power in lensing B-modes themselves is not possible at high significance at Planck noise levels, we do detect (at 4.5 σ {under the null hypothesis}) delensing effects in the B-mode map, with 7 % reduction in lensing power. Our results provide a first demonstration of polarization delensing, and generally of internal CMB delensing, and stand in agreement with the baseline ΛCDM Planck 2015 cosmology expectations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Mixed-state entanglement and information recovery in thermalized states and evaporating black holes

We study the universal behavior of quantum information-theoretic quantities in thermalized isolated quantum many-body systems and evaporating black holes. In particular, we study a genuine mixed-state entanglement measure called the logarithmic negativity, other correlation measures including the Renyi negativities and the mutual information, and a signature of multipartite entanglement called the reflected entropy. We also probe the feasibility of recovering quantum information from subsystems of a thermalized quantum many-body system or from the radiation of an evaporating black hole, using quantities such as relative entropy and Petz map fidelity. A recently developed technique called the equilibrium approximation allows us to probe these quantities at finite temperature. We find striking qualitative differences from the infinite temperature case, which has been the topic of previous studies using Haar-random states. In particular, we find regimes where the logarithmic negativity is extensive but the mutual information is sub-extensive, indicating a large amount of undistillable, bound entanglement in thermalized states. For evaporating black holes at finite temperature, both the logarithmic negativity and the Petz map fidelity reveal an important new time scale t b , which is earlier than the Page time t p by a finite fraction of the total evaporation time. We find that t b , as opposed to t p , is the time scale at which quantum entanglement between different parts of the radiation becomes extensive, and the fidelity of information recovery for a large diary thrown into the black hole starts to grow.

2D Gravity↗
NASA NTRS2008

Finland Validation of the New Blended Snow Product

As part of an ongoing effort to validate satellite remote sensing snow products for the recentlydeveloped U.S. Air Force Weather Agency (AFWA) - NASA blended snow product, Satellite and in-situ data for snow extent and snow water equivalent (SWE) are evaluated in Finland for the 2006-2007 snow season Finnish Meteorological Institute (FMI) daily weather station data and Finnish Environment Institute (SYKE) bi-monthly snow course data are used as ground truth. Initial comparison results display positive agreement between the AFWA NASA Snow Algorithm (ANSA) snow extent and SWE maps and in situ data, with discrepancies in accordance with known AMSR-E and MODIS snow mapping limitations. Future ANSA product improvement plans include additional validation and inclusion of fractional snow cover in the ANSA data product. Furthermore, the AMSR-E 19 GHz (horizontal channel) with the difference between ascending and descending satellite passes (Diurnal Amplitude Variations, DAV) will be used to detect the onset of melt, and QuikSCAT scatterometer data (14 GHz) will be used to map areas of actively melting snow.

Kim, E. J.↗
NASA NTRS2011

Informing Aerosol Transport Models With Satellite Multi-Angle Aerosol Measurements

As the aerosol products from the NASA Earth Observing System's Multi-angle Imaging SpectroRadiometer (MISR) mature, we are placing greater focus on ways of using the aerosol amount and type data products, and aerosol plume heights, to constrain aerosol transport models. We have demonstrated the ability to map aerosol air-mass-types regionally, and have identified product upgrades required to apply them globally, including the need for a quality flag indicating the aerosol type information content, that varies depending upon retrieval conditions. We have shown that MISR aerosol type can distinguish smoke from dust, volcanic ash from sulfate and water particles, and can identify qualitative differences in mixtures of smoke, dust, and pollution aerosol components in urban settings. We demonstrated the use of stereo imaging to map smoke, dust, and volcanic effluent plume injection height, and the combination of MISR and MODIS aerosol optical depth maps to constrain wildfire smoke source strength. This talk will briefly highlight where we stand on these application, with emphasis on the steps we are taking toward applying the capabilities toward constraining aerosol transport models, planet-wide.

Limbacher, J.↗
NASA NTRS2014

The Miniature Radio Frequency Instruments (Mini-RF) Global Observations of Earth's Moon

Radar provides a unique means to analyze the surface and subsurface physical properties of geologic deposits, including their wavelength-scale roughness, the relative depth of the deposits, and some limited compositional information. The NASA Lunar Reconnaissance Orbiter's (LRO) Miniature Radio Frequency (Mini-RF) instrument has enabled these analyses on the Moon at a global scale. Mini-RF has accumulated 67% coverage of the lunar surface in S-band (12.6 cm) radar with a resolution of 30 m/pixel. Here we present new Mini-RF global orthorectified uncontrolled S-band maps of the Moon and use them for analysis of lunar surface physical properties. Reported here are readily apparent global- and regional-scale differences in lunar surface physical properties that suggest three distinct terranes, namely: a (1) Nearside Radar Dark Region; (2) Orientale basin and continuous ejecta; and the (3) Highlands Radar Bright Region. Integrating these observations with new data from LRO's Diviner Radiometer rock abundance maps, as well Clementine and Lunar Prospector derived compositional values show multiple distinct lunar surface terranes and sub-terranes based upon both physical and compositional surface properties. Previous geochemical investigations of the Moon suggested its crust is best divided into three to four basic crustal provinces or terranes (Feldspathic Highlands Terrane (-An and -Outer), Procellarum KREEP Terrane, and South Pole Aitken Terrane) that are distinct from one another. However, integration of these geochemical data sets with new geophysical data sets allows us to refine these terranes. The result shows a more complex view of these same crustal provinces and provides valuable scientific and hazard perspectives for future targeted human and robotic exploration.

Radar observations↗
DOE OSTI2025

Mapping heat vulnerability in cities: A tale of two california cities

Extreme heat is a major cause of weather-related deaths in the United States. To address this, a heat vulnerability index (HVI) is crucial for assessing heat risk and identifying vulnerable urban areas and populations, supporting city planning and emergency response. Current HVI studies often use Principal Component Analysis (PCA) on environmental, socioeconomic, and medical data to aggregate vulnerability indicators into a single index. However, these fixed aggregation weights struggle to adapt to different use cases, which may require varying focuses. Moreover, existing tools primarily consider outdoor heat exposure, providing an incomplete picture of actual exposure, as people spend most of their time indoors. Our research introduces an HVI web mapping tool that addresses these gaps in the literature by: (1) allowing flexible weights to adapt to different use cases, and (2) uniquely integrating both outdoor and indoor heat exposure by considering building characteristics for a more comprehensive risk assessment. We demonstrated this tool in two California cities with contrasting climates: Fresno (inland, arid, hot summers) and Oakland (temperate coastal). This HVI mapping tool provides essential decision support for policymakers and stakeholders in both short-term heat mitigation and long-term urban planning for building interventions and infrastructure development.

BES↗
NASA NTRS1990

Radiometric calibration and monitoring of NOAA AVHRR visible data

Results and corrections to calibration for the NOAA-7, -8, -9, -10, and -11 AVHRR Channel 1 data, covering the period from July 1983 through December 1989, are presented. Results from the NOAA-7 and NOAA-9 analysis are used as examples to illustrate key points and present detailed results. In the AVHRR monitor procedure, the spatial variability index is calculated first to classify the data as CLEAR or CLOUD. This classification is then used to sort the data to produce three 1D radiance histograms for different surface types. The surface reflectances are retrieved from the radiances, and a set of reflectance filters are applied to sort the data into global surface reflectance maps. An examination of the NOAA-7 results shows that the NOAA-7 radiometer sensitivity actually decreased at a rate of about 0.5-1.0 percent per year. Trends inferred from the point measurements representing independent calibrations at different times, using models, known sites, and coincident aircraft measurements, agree well with the satellite methods.

Brest, Christopher L.↗