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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Application of AVHRR vegetation index to study atmosphere-biosphere exchange of CO2: Results from a 3-D tracer transport model

The 'normalized difference vegetation indices' (NVI) derived from AVHRR radiances are combined with field data of soil respiration and a global map of net primary productivity to prescribe, for the globe, the seasonal exchange of CO2 between the atmosphere and the terrestrial biosphere. The monthly fluxes of CO2 thus obtained are used as inputs to a 3-D tracer transport model which uses winds generated by a 3-D atmospheric general circulation model to advect CO2 as an inert constituent. Analysis of the 3-D model results shows reasonable agreement between the simulated and observed annual cycles of atmospheric CO2 at the locations of the remote monitoring stations. The application is shown of atmospheric CO2 distributions to calibrate the NVI in terms of carbon fluxes. The approach suggests that the NVI may be used to provide quantitative information about long term and global scale variations of photosynthetic activity and of atmospheric CO2 concentrations provided that variations in the atmospheric circulation and in atmospheric composition are known.

Fung, Inez Y.↗
NASA NTRS1993

Cloud properties from the analysis of AVHRR observations for FIRE 2

Preliminary results are presented for cloud properties from the analysis of AVHRR observations for FIRE 2. The properties were obtained from a combination of the spatial coherence method and a multispectral retrieval scheme. Geographically gritted fields for the number of cloud layers were produced. For single layered cloud systems, fractional cloud cover, cloud emission temperature, cloud emissivity, and particle size were retrieved. Statistics on the properties of upper-level clouds and the Coffeeville cloud conditions are presented.

Lin, Xijian↗
NASA NTRS1994

Some practical aspects of lossless and nearly-lossless compression of AVHRR imagery

Compression of Advanced Very high Resolution Radiometers (AVHRR) imagery operating in a lossless or nearly-lossless mode is evaluated. Several practical issues are analyzed including: variability of compression over time and among channels, rate-smoothing buffer size, multi-spectral preprocessing of data, day/night handling, and impact on key operational data applications. This analysis is based on a DPCM algorithm employing the Universal Noiseless Coder, which is a candidate for inclusion in many future remote sensing systems. It is shown that compression rates of about 2:1 (daytime) can be achieved with modest buffer sizes (less than or equal to 2.5 Mbytes) and a relatively simple multi-spectral preprocessing step.

Hogan, David B.↗
NASA NTRS1994

Lossless compression of NOAA-AVHRR satellite data

A high-performance lossless compression system for satellite NOAA data is developed. The data is called 'high resolution picture transmission' (HRPT) data, and consists of around 93 percent advanced very high resolution radiometer (AVHRR) multi-channel image data and 7 percent of miscellaneous data. In compressing the image portion, we classify each pixel into 10 different groups and apply a multi-channel prediction and a non-linear error conversion. The entropy coder is an arithmetic coder which is adaptive and regenerates the approximation of the statistical properties of the source as an initial probability table. To compress the non-image part, we used the general compressor (gzip). From experimental results, the original information is compressed down to 25 percent to approx. 40 percent.

Takamura, Seishi↗
NASA NTRS1994

Computation and use of the reflectivity at 3.75 micrometers from AVHRR thermal channels

Global study of land surface properties uses AVHRR channels 1 and 2, but channel 3 may be of interest, although its use requires preprocessing. It consists of both a reflective part and an emissive part, the former can be derived from T3, T4 and T5. Since the water vapor affects channel 3, its content is retrieved from the channel 4 and 5 using the split window technique. A formula of reflective part retrieval at 3.75 micrometers is tested in the case of sunglint observations where the emissivities of channels 4 and 5 can be set to the unity. The formula is adapted and validated to land surface using the FIFE-87 data set. Preliminary applications of the reflectance at 3.75 micrometers to the studies of surface properties retrieval, aerosol retrieval over land, and desertic aerosol retrieval, are addressed.

Roger, J. C.↗
NASA NTRS1995

The correlated k-distribution technique as applied to the AVHRR channels

Correlated k-distributions have been created to account for the molecular absorption found in the spectral ranges of the five Advanced Very High Resolution Radiometer (AVHRR) satellite channels. The production of the k-distributions was based upon an exponential-sum fitting of transmissions (ESFT) technique which was applied to reference line-by-line absorptance calculations. To account for the overlap of spectral features from different molecular species, the present routines made use of the multiplication transmissivity property which allows for considerable flexibility, especially when altering relative mixing ratios of the various molecular species. To determine the accuracy of the correlated k-distribution technique as compared to the line-by-line procedure, atmospheric flux and heating rate calculations were run for a wide variety of atmospheric conditions. For the atmospheric conditions taken into consideration, the correlated k-distribution technique has yielded results within about 0.5% for both the cases where the satellite spectral response functions were applied and where they were not. The correlated k-distribution's principal advantages is that it can be incorporated directly into multiple scattering routines that consider scattering as well as absorption by clouds and aerosol particles.

Kratz, David P.↗
NASA NTRS1997

Iterative edge- and wavelet-based image registration of AVHRR and GOES satellite imagery

Most automatic registration methods are either correlation-based, feature-based, or a combination of both. Examples of features which can be utilized for automatic image registration are edges, regions, corners, or wavelet-extracted features. In this paper, we describe two proposed approaches, based on edge or edge-like features, which are very appropriate to highlight regions of interest such as coastlines. The two iterative methods utilize the Normalized Cross-Correlation of edge and wavelet features and are applied to such problems as image-to-map registration, landmarking, and channel-to-channel co-registration, utilizing test data, AVHRR data, as well as GOES image data.

LeMoigne, Jacqueline↗
NASA NTRS1999

Aerosol Retrievals Using Channel 1 and 2 AVHRR Data

The effect of tropospheric aerosols on global climate via the direct and indirect radiative forcings is one of the largest remaining uncertainties in climate change studies. Current assessments of the direct aerosol radiative effect mainly focus on sulfate aerosols. It has become clear, however, that other aerosol types like soil dust and smoke from biomass burning are also likely to be important climate forcing factors. The magnitude and even the sign of the climate forcing caused by these aerosol types is still unknown. General circulation models (GCMs) can be used to estimate the climatic effect of the direct radiative forcing by tropospheric and stratospheric aerosols. Aerosol optical properties are already parameterized in the Goddard Institute for Space Studies GCM. Once the global distribution of aerosol properties (optical thickness, size distribution, and chemical composition) is available, the calculation of the direct aerosol forcing is rather straighfforward. However, estimates of the indirect aerosol effect require additional knowledge of the physics and chemistry of aerosol-cloud interactions which are still poorly understood. One of the main objectives of the Global Aerosol Climatology Project, established in 1998 as a joint initiative of NASA's Radiation Science Program and GEWEX, is to infer the global distribution of aerosols, their properties, and their seasonal and interannual variations for the full period of available satellite data. This will be accomplished primarily through a systematic application of multichannel aerosol retrieval algorithms to existing satellite data and advanced 3-dimensional aerosol chemistry/transport models. In this paper we outline the methodology of analyzing channel 1 and 2 AVHRR radiance data over the oceans and describe preliminary retrieval results.

Mishchenko, Michael I.↗
NASA NTRS1999

Polar-Wide Geophysical Products Derived from AVHRR

This is the final report for the AVHRR Polar Pathfinder (APP) project activities at Boston University (BU). The grant to J. Key is part of a group proposal with the University of Colorado (CU) as the lead institution (J. Masianik, PI). The report is a summary of accomplishments over the three-year BU project, although the NASA grant to BU was only for the third year. For the first two years funding at BU was obtained via a subcontract from CU. The overall project report will be provided by the investigators at the University of Colorado this fall, when their no-cost extension period is completed. That report will also contain the information given here. As per NASA guidelines, this report is limited to three pages.

Key, Jeffrey R.↗
NASA NTRS2000

BOREAS Level 3-b AVHRR-LAC Imagery: Scaled At-sensor Radiance in LGSOWG Format

The BOREAS Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. Data acquired from the AVHRR instrument on the NOAA-9, -11, -12, and -14 satellites were processed and archived for the BOREAS region by the MRSC and BORIS. The data were acquired by CCRS and were provided for use by BOREAS researchers. A few winter acquisitions are available, but the archive contains primarily growing season imagery. These gridded, at-sensor radiance image data cover the period of 30-Jan-1994 to 18-Sep-1996. Geographically, the data cover the entire 1,000-km x 1,000-km BOREAS region. The data are stored in binary image format files.

Hall, Forrest G.↗
NASA NTRS2000

BOREAS RSS-7 Regional LAI and FPAR Images From 10-Day AVHRR-LAC Composites

The BOReal Ecosystem-Atmosphere Study Remote Sensing Science (BOREAS RSS-7) team collected various data sets to develop and validate an algorithm to allow the retrieval of the spatial distribution of Leaf Area Index (LAI) from remotely sensed images. Advanced Very High Resolution Radiometer (AVHRR) level-4c 10-day composite Normalized Difference Vegetation Index (NDVI) images produced at CCRS were used to produce images of LAI and the Fraction of Photosynthetically Active Radiation (FPAR) absorbed by plant canopies for the three summer IFCs in 1994 across the BOREAS region. The algorithms were developed based on ground measurements and Landsat Thematic Mapper (TM) images. The data are stored in binary image format files.

Hall, Forrest G.↗
NASA NTRS2001

Intercomparison Between in situ and AVHRR Polar Pathfinder-Derived Surface Albedo over Greenland

The Advanced Very High Resolution (AVHRR) Polar Pathfinder Data (APP) provides the first long time series of consistent, calibrated surface albedo and surface temperature data for the polar regions. Validations of these products have consisted of individual studies that analyzed algorithm performance for limited regions and or time periods. This paper reports on comparisons made between the APP-derived surface albedo and that measured at fourteen automatic weather stations (AWS) around the Greenland ice sheet from January 1997 to August 1998. Results show that satellite-derived surface albedo values are on average 10% less than those measured by the AWS stations. However, the station measurements tend to be biased high by about 4% and thus the differences in absolute albedo may be less (e.g. 6%). In regions of the ice sheet where the albedo variability is small, such as the dry snow facies, the APP albedo uncertainty exceeds the natural variability. Further work is needed to improve the absolute accuracy of the APP-derived surface albedo. Even so, the data provide temporally and spatially consistent estimates of the Greenland ice sheet albedo.

Stroeve, Julienne C.↗
NASA NTRS1997

Global Transport of Aerosol and CO: Initial 3-D Simulations of MAPS, TOMS, and AVHRR

Carbon monoxide concentrations and aerosol properties provide the tracers of global tropospheric perturbation by humankind that are most easily observed from satellite platforms. Aircraft field observations are additionally needed for us to simulate and understand the patterns observed. We report on our accumulating experience in making detailed, situation-specific, 3-D simulations of these tropospheric constituents as observed from the MAPS CO sensor, the Advanced Very High Resolution Radiometer (AVHRR) aerosol scattering data, and the Total Ozone Mapping Spectrometer (TOMS) absorbing-aerosol information. We have found a strong complimentarity of satellite and aircraft data in this effort, and recommend modelers use: (1) satellite data to pose initial questions; (2) aircraft data for modelers' first detailed simulations; and (3) a return to satellite data for global generalization. This work provides one example. Our main tools are the MM5 numerical model for meteorological assimilation and GRACES, our NASA Ames tracer-chemistry model, which incorporates emissions estimates. We report on several six-week simulations of global biomass burning effects as observed in the MAPS October 1994 dataset, and show the usefulness of two aircraft datasets, the TRACE-A (1992) and PEM-Tropics missions of NASA's Global Tropospheric Experiment. Additional information is contained in the original extended abstract.

Chatfield, Robert B.↗
NASA NTRS1995

Cloud Masking and Surface Temperature Distribution in the Polar Regions Using AVHRR and other Satellite Data

Surface temperature is one of the key variables associated with weather and climate. Accurate measurements of surface air temperatures are routinely made in meteorological stations around the world. Also, satellite data have been used to produce synoptic global temperature distributions. However, not much attention has been paid on temperature distributions in the polar regions. In the polar regions, the number of stations is very sparse. Because of adverse weather conditions and general inaccessibility, surface field measurements are also limited. Furthermore, accurate retrievals from satellite data in the region have been difficult to make because of persistent cloudiness and ambiguities in the discrimination of clouds from snow or ice. Surface temperature observations are required in the polar regions for air-sea-ice interaction studies, especially in the calculation of heat, salinity, and humidity fluxes. They are also useful in identifying areas of melt or meltponding within the sea ice pack and the ice sheets and in the calculation of emissivities of these surfaces. Moreover, the polar regions are unique in that they are the sites of temperature extremes, the location of which is difficult to identify without a global monitoring system. Furthermore, the regions may provide an early signal to a potential climate change because such signal is expected to be amplified in the region due to feedback effects. In cloud free areas, the thermal channels from infrared systems provide surface temperatures at relatively good accuracies. Previous capabilities include the use of the Temperature Humidity Infrared Radiometer (THIR) onboard the Nimbus-7 satellite which was launched in 1978. Current capabilities include the use of the Advance Very High Resolution Radiometer (AVHRR) aboard NOAA satellites. Together, these two systems cover a span of 16 years of thermal infrared data. Techniques for retrieving surface temperatures with these sensors in the polar regions have been developed. Errors have been estimated to range from 1K to 5K mainly due to cloud masking problems. With many additional channels available, it is expected that the EOS-Moderate Resolution Imaging Spectroradiometer (MODIS) will provide an improved characterization of clouds and a good discrimination of clouds from snow or ice surfaces.

Comiso, Joey C.↗
NASA NTRS2004

Recent History of Large-Scale Ecosystem Disturbances in North America Derived from the AVHRR Satellite Record

Ecosystem structure and function are strongly impacted by disturbance events, many of which in North America are associated with seasonal temperature extremes, wildfires, and tropical storms. This study was conducted to evaluate patterns in a 19-year record of global satellite observations of vegetation phenology from the Advanced Very High Resolution Radiometer (AVHRR) as a means to characterize major ecosystem disturbance events and regimes. The fraction absorbed of photosynthetically active radiation (FPAR) by vegetation canopies worldwide has been computed at a monthly time interval from 1982 to 2000 and gridded at a spatial resolution of 8-km globally. Potential disturbance events were identified in the FPAR time series by locating anomalously low values (FPAR-LO) that lasted longer than 12 consecutive months at any 8-km pixel. We can find verifiable evidence of numerous disturbance types across North America, including major regional patterns of cold and heat waves, forest fires, tropical storms, and large-scale forest logging. Summed over 19 years, areas potentially influenced by major ecosystem disturbances (one FPAR-LO event over the period 1982-2000) total to more than 766,000 km2. The periods of highest detection frequency were 1987-1989, 1995-1997, and 1999. Sub- continental regions of Alaska and Central Canada had the highest proportion (greater than 90%) of FPAR-LO pixels detected in forests, tundra shrublands, and wetland areas. The Great Lakes region showed the highest proportion (39%) of FPAR-LO pixels detected in cropland areas, whereas the western United States showed the highest proportion (16%) of FPAR-LO pixels detected in grassland areas. Based on this analysis, an historical picture is emerging of periodic droughts and heat waves, possibly coupled with herbivorous insect outbreaks, as among the most important causes of ecosystem disturbance in North America.

Potter, Christopher↗
NASA NTRS2005

Comparison of Monthly Mean Cloud Fraction and Cloud Optical depth Determined from Surface Cloud Radar, TOVS, AVHRR, and MODIS over Barrow, Alaska

A one year comparison is made of mean monthly values of cloud fraction and cloud optical depth over Barrow, Alaska (71 deg 19.378 min North, 156 deg 36.934 min West) between 35 GHz radar-based retrievals, the TOVS Pathfinder Path-P product, the AVHRR APP-X product, and a MODIS based cloud retrieval product from the CERES-Team. The data sets represent largely disparate spatial and temporal scales, however, in this paper, the focus is to provide a preliminary analysis of how the mean monthly values derived from these different data sets compare, and determine how they can best be used separately, and in combination to provide reliable estimates of long-term trends of changing cloud properties. The radar and satellite data sets described here incorporate Arctic specific modifications that account for cloud detection challenges specific to the Arctic environment. The year 2000 was chosen for this initial comparison because the cloud radar data was particularly continuous and reliable that year, and all of the satellite retrievals of interest were also available for the year 2000. Cloud fraction was chosen as a comparison variable as accurate detection of cloud is the primary product that is necessary for any other cloud property retrievals. Cloud optical depth was additionally selected as it is likely the single cloud property that is most closely correlated to cloud influences on surface radiation budgets.

Uttal, Taneil↗
NASA NTRS2016

Validation of Cloud Parameters Derived from Geostationary Satellites, AVHRR, MODIS, and VIIRS Using SatCORPS Algorithms

Validation is a key component of remote sensing that can take many different forms. The NASA LaRC Satellite ClOud and Radiative Property retrieval System (SatCORPS) is applied to many different imager datasets including those from the geostationary satellites, Meteosat, Himiwari-8, INSAT-3D, GOES, and MTSAT, as well as from the low-Earth orbiting satellite imagers, MODIS, AVHRR, and VIIRS. While each of these imagers have similar sets of channels with wavelengths near 0.65, 3.7, 11, and 12 micrometers, many differences among them can lead to discrepancies in the retrievals. These differences include spatial resolution, spectral response functions, viewing conditions, and calibrations, among others. Even when analyzed with nearly identical algorithms, it is necessary, because of those discrepancies, to validate the results from each imager separately in order to assess the uncertainties in the individual parameters. This paper presents comparisons of various SatCORPS-retrieved cloud parameters with independent measurements and retrievals from a variety of instruments. These include surface and space-based lidar and radar data from CALIPSO and CloudSat, respectively, to assess the cloud fraction, height, base, optical depth, and ice water path; satellite and surface microwave radiometers to evaluate cloud liquid water path; surface-based radiometers to evaluate optical depth and effective particle size; and airborne in-situ data to evaluate ice water content, effective particle size, and other parameters. The results of comparisons are compared and contrasted and the factors influencing the differences are discussed.

Minnis, P.↗