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NASA NTRSDate not supplied

Toward Consistent Long-term Records of Cloud Fraction from MODIS and VIIRS for CERES

In order to produce a long-term and stable climate record of Earth’s energy budget for NASA’s Clouds and Earth’s Radiant Energy System (CERES) project, a consistent cloud fraction record across different measurement platforms­­ is a crucial first step. As Aqua satellite is approaching the end of its operational lifetime, NOAA-20 VIIRS observations on the JPSS-2 spacecraft will be used for cloud detection to continue the long-term Earth energy budget record. Two steps are designed to achieve this goal. The first step is a quick approach that revises the CERES NOAA-20 VIIRS Edition 1 A (CV Ed1A) cloud mask to incorporate Cross-track Infrared Sounder (CrIS) water vapor and CO_2 channels into the VIIRS cloud mask (CV Ed1B) to produce a consistent cloud fraction with CERES MODIS Edition 4 (CM Ed4) to avoid potential discontinuity when Aqua orbit drifts beyond tolerance before the next Edition is completed. The second step is to develop, as part of CERES next edition (Ed5), a unified MODIS and VIIRS cloud mask using common channels to produce consistent cloud products with improved radiative transfer models, refined clear sky predictions, new GMAO reanalysis products, and the latest radiance collections of MODIS and VIIRS data. This poster will present cloud fraction comparison between CV Ed1B and CM Ed4, as well as the preliminary results of ongoing Ed5 including pixel level cloud mask results, monthly global cloud fraction differences between MODIS and VIIRS (consistency), and initial validation using CALIPSO data (accuracy).

CERES↗
NASA NTRS1992

Overview for the reanalysis of Mariner 9 UV spectrometer data for ozone, cloud, and dust abundances, and their interaction over climate timescales

Mariner 9 UV spectrometer data were reinverted for the ozone abundance, cloud abundance, dust abundance, and polar-cap albedo. The original reduction of the spectra ignored the presence of atmospheric dust and clouds, even though their abundance is substantial and can mask appreciable amounts of ozone if not accounted for (Lindner, 1988). The Mariner 9 ozone data has been used as a benchmark in all theoretical models of atmospheric composition, escape, and photochemistry. A second objective is to examine the data for the interrelationship of the ozone cycle, dust cycle, and cloud cycle, on an annual, inter-annual, and climatic basis, testing predictions by Lindner (1988). This also has implications for many terrestrial ozone studies, such as the ozone hole, acid rain, and ozone-smog. A third objective is to evaluate the efficacy of the reflectance spectroscopy technique at retrieving the ozone abundance on Mars. This would be useful for planning ozone observations on future Mars missions or the terrestrial troposphere.

Lindner, Bernhard Lee↗
NASA NTRS2023

Passive Microwave Arctic Sea Ice Melt Onset Dates From the Advanced Horizontal Range Algorithm 1979 - 2022

The onset of the summer melt season is a key stage of the Arctic sea ice seasonal cycle and is an indicator of climate change. Surface melting of the bare or snow-covered sea ice is detected using passive microwave satellite observations. The data set presented here is a 44 year record of Arctic sea ice annual melt onset (MO) dates for 1979–2022 produced using an updated version of the Advanced Horizontal Range Algorithm (AHRA). This data product contains annual maps of the sea ice MO date and a set of descriptive statistics summarizing the data. This paper describes a new update of the AHRA methodology, now AHRA V5, including key changes to the algorithm starting date and sea ice mask methodology to improve estimates of early-season MO dates especially near the sea ice periphery. AHRA V5 data are suitable for monitoring trends in Arctic and regional sea ice MO dates and for process studies of atmosphere-sea ice interactions during the early spring and summer months.

Angela C. Bliss↗
NASA NTRS2015

Land Boundary Conditions for the Goddard Earth Observing System Model Version 5 (GEOS-5) Climate Modeling System: Recent Updates and Data File Descriptions

The Earths land surface boundary conditions in the Goddard Earth Observing System version 5 (GEOS-5) modeling system were updated using recent high spatial and temporal resolution global data products. The updates include: (i) construction of a global 10-arcsec land-ocean lakes-ice mask; (ii) incorporation of a 10-arcsec Globcover 2009 land cover dataset; (iii) implementation of Level 12 Pfafstetter hydrologic catchments; (iv) use of hybridized SRTM global topography data; (v) construction of the HWSDv1.21-STATSGO2 merged global 30 arc second soil mineral and carbon data in conjunction with a highly-refined soil classification system; (vi) production of diffuse visible and near-infrared 8-day MODIS albedo climatologies at 30-arcsec from the period 2001-2011; and (vii) production of the GEOLAND2 and MODIS merged 8-day LAI climatology at 30-arcsec for GEOS-5. The global data sets were preprocessed and used to construct global raster data files for the software (mkCatchParam) that computes parameters on catchment-tiles for various atmospheric grids. The updates also include a few bug fixes in mkCatchParam, as well as changes (improvements in algorithms, etc.) to mkCatchParam that allow it to produce tile-space parameters efficiently for high resolution AGCM grids. The update process also includes the construction of data files describing the vegetation type fractions, soil background albedo, nitrogen deposition and mean annual 2m air temperature to be used with the future Catchment CN model and the global stream channel network to be used with the future global runoff routing model. This report provides detailed descriptions of the data production process and data file format of each updated data set.

GEOS-5↗
NASA NTRS1994

A GPS coverage model

The results of several case studies using the Global Positioning System coverage model developed at Ohio University are summarized. Presented are results pertaining to outage area, outage dynamics, and availability. Input parameters to the model include the satellite orbit data, service area of interest, geometry requirements, and horizon and antenna mask angles. It is shown for precision-landing Category 1 requirements that the planned GPS 21 Primary Satellite Constellation produces significant outage area and unavailability. It is also shown that a decrease in the user equivalent range error dramatically decreases outage area and improves the service availability.

Skidmore, Trent A.↗
NASA NTRS2002

Exploring Heart and Lung Function in Space: ARMS Experiments

The Advanced Respiratory Monitoring System (ARMS) is a suite of monitoring instruments and supplies used to study the heart, lungs, and metabolism. Many experiments sponsored by the European Space Agency (ESA) will be conducted using ARMS during STS-107. The near-weightless environment of space causes the body to undergo many physiological adaptations, and the regulation of blood pressure is no exception. Astronauts also experience a decrease in blood volume as an adaptation to microgravity. Reduced blood volume may not provide enough blood pressure to the head during entry or landing. As a result, astronauts often experience light-headedness, and sometimes even fainting, when they stand shortly after returning to Earth. To help regulate blood pressure and heart rate, baroreceptors, sensors located in artery walls in the neck and near the heart, control blood pressure by sending information to the brain and ensuring blood flow to organs. These mechanisms work properly in Earth's gravity but must adapt in the microgravity environment of space. However, upon return to Earth during entry and landing, the cardiovascular system must readjust itself to gravity, which can cause fluctuation in the control of blood pressure and heart rate. Although the system recovers in hours or days, these occurrences are not easily predicted or understood - a puzzle investigators will study with the ARMS equipment. In space, researchers can focus on aspects of the cardiovascular system normally masked by gravity. The STS-107 experiments using ARMS will provide data on how the heart and lungs function in space, as well as how the nervous system controls them. Exercise will also be combined with breath holding and straining (the Valsalva maneuver) to test how heart rate and blood pressure react to different stresses. This understanding will improve astronauts' cardiopulmonary function after return to Earth, and may well help Earthbound patients who experience similar effects after long-term bed rest.

Andre Kuipers↗
NASA NTRS2018

Snow Observations from Space: an Approach to Map Snow Cover from Three Decades of Landsat Imagery Across Switzerland

Snow accumulation is one of the most important forms of water storage. The natural cycle of water is being increasingly influenced by climate change and will continue to change in the future. To understand the evolution of snow cover and to perfect its accurate detection UN Environment/GRID-Geneva and the University of Geneva have developed a Snow Detection tool called “Snow Observations from Space” for the Swiss Data Cube. The Snow Detection tool uses the C Function of Mask to identify snow pixels and then subsequently produces a normalized detection raster. Through further development, this tool will reach its full potential as an accurate method of detecting snow cover change for Switzerland.

Frau, Lorenzo↗
NASA NTRS2006

Spatial and Temporal Distribution of Clouds as Observed by MODIS Onboard the Terra and Aqua Satellites

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24,2000 for Terra and June 24,2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, and fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. Over the last year, extensive improvements and enhancements in the global cloud products have been implemented, and reprocessing of all MODIS data on Terra has commenced since first light in February 2000. In the cloud mask algorithm, the most extensive improvements were in distinguishing clouds at nighttime, including the challenging polar darkness regions of the world. Additional improvements have been made to properly distinguish sunglint from clouds in the tropical ocean regions, and to improve the identification of clouds from snow during daytime in Polar Regions. We will show global monthly mean cloud fraction for both Terra and Aqua, and show how similar the global daytime cloud fraction is from these morning and afternoon orbits, respectively. We will also show the zonal distribution of cloud fraction over land and ocean regions for both Terra and Aqua, and show the time series of global cloud fraction from July 2002 through June 2006.

King, Michael D.↗
NASA NTRS1981

The reduction, verification and interpretation of Magsat magnetic data over Canada

Magnetic anomalies of lithospheric origin are weak at Magsat altitudes (20 to 30 nT at most), and are easily masked by much larger effects caused by field-aligned and other currents at high latitudes. Most of Canada lies under the influence of ionospheric currents in the auroral zone and polar cap. A more refined selection of quiet Magsat data allowed a revised scalar magnetic anomaly map of the whole region north of about 40 deg N latitude. Very preliminary vector anomaly maps and absolute vector component maps were derived. The scalar magnitudes show great promise for mapping the total force and anomaly fields. The Z vector data also appear to be good. The horizontal X and Y vector data are seriously contaminated with external fields and maybe other effects.

Coles, R. L.↗
NASA NTRS2004

NASA Tech Briefs, December 2004

opics include: High-Rate Digital Receiver Board; Signal Design for Improved Ranging Among Multiple Transceivers; Automated Analysis, Classification, and Display of Waveforms; Fast-Acquisition/Weak-Signal-Tracking GPS Receiver for HEO; Format for Interchange and Display of 3D Terrain Data; Program Analyzes Radar Altimeter Data; Indoor Navigation using Direction Sensor and Beacons; Software Assists in Responding to Anomalous Conditions; Software for Autonomous Spacecraft Maneuvers; WinPlot; Software for Automated Testing of Mission-Control Displays; Nanocarpets for Trapping Microscopic Particles; Precious-Metal Salt Coatings for Detecting Hydrazines; Amplifying Electrochemical Indicators; Better End-Cap Processing for Oxidation-Resistant Polyimides; Carbon-Fiber Brush Heat Exchangers; Solar-Powered Airplane with Cameras and WLAN; A Resonator for Low-Threshold Frequency Conversion; Masked Proportional Routing; Algorithm Determines Wind Speed and Direction from Venturi-Sensor Data; Feature-Identification and Data-Compression Software; Alternative Attitude Commanding and Control for Precise Spacecraft Landing; Inspecting Friction Stir Welding using Electromagnetic Probes; and Helicity in Supercritical O2/H2 and C7H16/N2 Mixing Layers.

Source record↗
NASA NTRS1984

A preliminary study of the feasibility of detecting the floating macrophytes by means of digital processing of MSS/LANDSAT data

The feasibility of mapping the floating macrophytes (mostly water hyacinth: (Eichornia crassipes) in the Salto Grande reservoir in Americana, SP, by means of digital processing of MSS/LANDSAT data is described. The area occupied by the macrophytes was extracted by exclusion after the merging of two thematic masks representing the area of vegetation free water surface. One of the masks was obtained from a date when the vegetal cover is insignificant, while the other represents a large infestation episode. The utilization of digital processing of MSS/LANDSAT data techniques for the documentation of macrophytes infestation is feasible only when the phenomenon occurs in large areas.

Valeriano, D. D.↗
NASA NTRS1983

Monitoring the defoliation of hardwood forests in Pennsylvania using LANDSAT

An automated system for conducting annual gypsy moth defoliation surveys using LANDSAT MSS data and digital processing techniques is described. A two-step preprocessing procedure was developed that uses multitemporal data sets representing forest canopy conditions before and after defoliation to create a digital image in which all nonforest cover types are eliminated or masked out of a LANDSAT image that exhibits insect defoliation. A temporal window for defoliation assessment was identified and a statewide data base was established. A data management system to interface image analysis software with the statewide data base was developed and a cost benefit analysis of this operational system was conducted.

Dottavio, C. L.↗
NASA NTRS2007

Remote Sensing of the Radiative and Microphysical Properties of Clouds during TC4: Results from MAS, MASTER, MODIS, and MISR

The MODIS Airborne Simulator (MAS) and MODIS/ASTER Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional reflectance and brightness temperature of clouds at 50 discrete wavelengths between 0.47 and 14.3 (12.9 m for MASTER). These observations were obtained from the NASA ER-2 aircraft as part of the Tropical Composition, Clouds and Climate Coupling Experiment (TC4) conducted over Central America and surrounding Pacific and Atlantic Oceans between July 17 and August 8, 2007. Multispectral images in eight distinct bands were used to derive a confidence in clear sky (or alternatively the probability of cloud) over land and ocean ecosystems. Based on the results of individual tests run as part of this cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). Finally, the cloud optical thickness and effective radius were derived for both liquid water and ice clouds that were detected during each flight, using a nearly identical algorithm as that implemented operationally to process MODIS cloud data from the Aqua and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS and MASTER date in TC4, is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals used three distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of MODIS on the Terra spacecraft. Finally, this MODIS-based algorithm was adapted to MISR data to infer the cloud optical thickness of liquid water clouds from MISR. Results of this analysis will be presented and discussed.

King, Michael D.↗
NASA NTRS2021

Maya Forest Water Resources I: Using NASA Earth Observations to Map Forested Inundation in the Maya Forest

As climate change increases the severity and frequency of extreme weather events in the tropics, it is vital for the safety of local communities and the health of ecosystems to monitor seasonal inundation. Forested inundation affects the ability of forested wetlands to provide ecosystem services, such as flood mitigation, water filtration, carbon storage, and erosion mitigation. While ground-based monitoring has traditionally been used to map inundation extent, those methods are costly and time-intensive. The NASA DEVELOP team focused on seasonal inundation throughout 2008 in the Maya Forest, when changes in inundation were drastic. To monitor seasonal inundation, our team used in situ field data and Earth observations from Landsat 7 Enhanced Thematic Mapper (ETM+), Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) 1, Shuttle Radar Topography Mission (SRTM), and products from the Ice, Cloud, and Land Elevation Satellite (ICESat). The team applied a Random Forest algorithm to Landsat 7 imagery, generating an object-level land cover classification with an overall accuracy of 72.1% and forest class with 100% recall and 78% precision. The team applied L-band backscatter thresholds from existing literature to forest-masked ALOS imagery and refined the thresholds in an iterative process using field data and hydrology models to delineate seasonal inundation extent. These publicly available data products help end users from Belize’s Land Information Center (LIC) and Forest Department, Guatemala’s Center for Monitoring and Evaluation (CEMEC), and Mexico’s El Colegio de la Frontera Sur (ECOSUR) to inform land management and protect community infrastructure.

Madelyn Savan↗
NASA NTRS1981

Anthropometric data error detecting and correction with a computer

Data obtained with automated anthropometric data aquisition equipment was examined for short term errors. The least squares curve fitting technique was used to ascertain which data values were erroneous and to replace them, if possible, with corrected values. Errors were due to random reflections of light, masking of the light rays, and other types of optical and electrical interference. It was found that the signals were impossible to eliminate from the initial data produced by the television cameras, and that this was primarily a software problem requiring a digital computer to refine the data off line. The specific data of interest was related to the arm reach envelope of a human being.

Chesak, D. D.↗
NASA NTRS1981

The evaluation of alternate methodologies for land cover classification in an urbanizing area

The usefulness of LANDSAT in classifying land cover and in identifying and classifying land use change was investigated using an urbanizing area as the study area. The question of what was the best technique for classification was the primary focus of the study. The many computer-assisted techniques available to analyze LANDSAT data were evaluated. Techniques of statistical training (polygons from CRT, unsupervised clustering, polygons from digitizer and binary masks) were tested with minimum distance to the mean, maximum likelihood and canonical analysis with minimum distance to the mean classifiers. The twelve output images were compared to photointerpreted samples, ground verified samples and a current land use data base. Results indicate that for a reconnaissance inventory, the unsupervised training with canonical analysis-minimum distance classifier is the most efficient. If more detailed ground truth and ground verification is available, the polygons from the digitizer training with the canonical analysis minimum distance is more accurate.

Smekofski, R. M.↗
NASA NTRS2016

Implementing Connected Component Labeling as a User Defined Operator for SciDB

We have implemented a flexible User Defined Operator (UDO) for labeling connected components of a binary mask expressed as an array in SciDB, a parallel distributed database management system based on the array data model. This UDO is able to process very large multidimensional arrays by exploiting SciDB's memory management mechanism that efficiently manipulates arrays whose memory requirements far exceed available physical memory. The UDO takes as primary inputs a binary mask array and a binary stencil array that specifies the connectivity of a given cell to its neighbors. The UDO returns an array of the same shape as the input mask array with each foreground cell containing the label of the component it belongs to. By default, dimensions are treated as non-periodic, but the UDO also accepts optional input parameters to specify periodicity in any of the array dimensions. The UDO requires four stages to completely label connected components. In the first stage, labels are computed for each subarray or chunk of the mask array in parallel across SciDB instances using the weighted quick union (WQU) with half-path compression algorithm. In the second stage, labels around chunk boundaries from the first stage are stored in a temporary SciDB array that is then replicated across all SciDB instances. Equivalences are resolved by again applying the WQU algorithm to these boundary labels. In the third stage, relabeling is done for each chunk using the resolved equivalences. In the fourth stage, the resolved labels, which so far are "flattened" coordinates of the original binary mask array, are renamed with sequential integers for legibility. The UDO is demonstrated on a 3-D mask of O(1011) elements, with O(108) foreground cells and O(106) connected components. The operator completes in 19 minutes using 84 SciDB instances.

UDO↗
NASA NTRS2017

Generating Land Surface Reflectance for the New Generation of Geostationary Satellite Sensors with the MAIAC Algorithm

The latest generation of geostationary satellite sensors, including the GOES-16/ABI and the Himawari 8/AHI, provide exciting capability to monitor land surface at very high temporal resolutions (5-15 minute intervals) and with spatial and spectral characteristics that mimic the Earth Observing System flagship MODIS. However, geostationary data feature changing sun angles at constant view geometry, which is almost reciprocal to sun-synchronous observations. Such a challenge needs to be carefully addressed before one can exploit the full potential of the new sources of data. Here we take on this challenge with Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, recently developed for accurate and globally robust applications like the MODIS Collection 6 re-processing. MAIAC first grids the top-of- atmosphere measurements to a fixed grid so that the spectral and physical signatures of each grid cell are stacked (“remembered”) over time and used to dramatically improve cloud/shadow/snow detection, which is by far the dominant error source in the remote sensing. It also exploits the changing sun-view geometry of the geostationary sensor to characterize surface BRDF with augmented angular resolution for accurate aerosol retrievals and atmospheric correction. The high temporal resolutions of the geostationary data indeed make the BRDF retrieval much simpler and more robust as compared with sun-synchronous sensors such as MODIS. As a prototype test for the geostationary-data processing pipeline on NASA Earth Exchange (GEONEX), we apply MAIAC to process 18 months of data from Himawari 8/AHI over Australia. We generate a suite of test results, including the input TOA reflectance and the output cloud mask, aerosol optical depth (AOD), and the atmospherically-corrected surface reflectance for a variety of geographic locations, terrain, and land cover types. Comparison with MODIS data indicates a general agreement between the retrieved surface reflectance products. Furthermore, the geostationary results satisfactorily capture the movement of clouds and variations in atmospheric dust/aerosol concentrations, suggesting that high quality land surface and vegetation datasets from the advanced geostationary sensors can help complement and improve the corresponding EOS products.

geostationary satellite sensors↗