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At least 145 records · Page 8

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NASA NTRSDate not supplied

CERES Clouds and Radiative Swath (CRS) data in HDF. (CER_CRS_Terra-FM2-MODIS_Edition2A

The Clouds and Radiative Swath (CRS) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The CRS contains all of the CERES SSF product data. For each CERES footprint on the SSF the CRS also contains vertical flux profiles evaluated at four levels in the atmosphere: the surface, 500-, 70-, and 1-hPa. The CRS fluxes and cloud parameters are adjusted for consistency with a radiative transfer model and adjusted fluxes are evaluated at the four atmospheric levels for both clear-sky and total-sky. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2001-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CLOUD LAYER AREA↗

NASA NTRSDate not supplied

CERES Clouds and Radiative Swath (CRS) data in HDF. (CER_CRS_Terra-FM1-MODIS_Edition2B)

The Clouds and Radiative Swath (CRS) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The CRS contains all of the CERES SSF product data. For each CERES footprint on the SSF the CRS also contains vertical flux profiles evaluated at four levels in the atmosphere: the surface, 500-, 70-, and 1-hPa. The CRS fluxes and cloud parameters are adjusted for consistency with a radiative transfer model and adjusted fluxes are evaluated at the four atmospheric levels for both clear-sky and total-sky. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

SHORTWAVE FLUX↗

NASA NTRSDate not supplied

CERES Clouds and Radiative Swath (CRS) data in HDF. (CER_CRS_Terra-FM2-MODIS_Edition2B)

SHORTWAVE UNFILTERED RADIANCE↗

DOE OSTI2024

A global gridded dataset for cloud vertical structure from combined CloudSat and CALIPSO observations

Abstract. The vertical structure of clouds has a profound effect on the global energy budget, the global circulation, and the atmospheric hydrological cycle. The CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) missions have taken complementary, colocated observations of cloud vertical structure for over a decade. However, no globally gridded dataset is available to the public for the full length of this unique combined data record. Here we present the 3S-GEOPROF-COMB product (Bertrand et al. 2023, https://doi.org/10.5281/zenodo.8057791), a globally gridded (level 3S) community data product summarizing geometrical profiles (GEOPROF) of hydrometeor occurrence from combined (COMB) CloudSat and CALIPSO data. Our product is calculated from the latest release (R05) of per-orbit (level-2) combined cloud mask profiles. We process a set of cloud cover, vertical cloud fraction, and sampling variables at 2.5, 5, and 10° spatial resolutions and monthly and seasonal temporal resolutions. We address the 2011 reduction in CloudSat data collection with Daylight-Only Operations (DO-Op) mode by subsampling pre-2011 data to mimic DO-Op collection patterns, thereby allowing users to evaluate the impact of the reduced sampling on their analyses. We evaluate our data product against CloudSat-only and CALIPSO-only global-gridded data products as well as four comparable surface-based sites, underscoring the added value of the combined product. Interest in the product is anticipated for the study of cloud processes, cloud–climate interactions, and as a candidate baseline climate data record for comparison to follow-up satellite missions, among other uses.

Bertrand, Leah (ORCID:0009000001607558)↗

DOE OSTI2023

GeoDAWN West Central Nevada EarthMRI Data

This submission includes both the original product resolution (OPR) and LiDAR point cloud (LPC) LiDAR data collected as part of GeoDAWN: Geoscience Data Acquisition for Western Nevada. The USGS Earth Mapping Resources Initiative (EarthMRI) and USGS 3D Elevation Program (3DEP), Department of Energy Geothermal Technologies Office, Natural Resources Conservation Services, and Bureau of Land Management have partnered to conduct airborne geophysical and 3DEP lidar surveys over parts of Nevada and California to collect information on undiscovered geothermal, critical mineral, and groundwater resources in the western Great Basin and the Walker Lane region.

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

GeoDAWN Northwestern Elko County Nevada EarthMRI Data

This submission includes both the original product resolution (OPR) and LiDAR point cloud (LPC) LiDAR data collected as part of GeoDAWN: Geoscience Data Acquisition for Northwestern Elko County, Nevada. The USGS Earth Mapping Resources Initiative (EarthMRI) and USGS 3D Elevation Program (3DEP), Department of Energy Geothermal Technologies Office, Natural Resources Conservation Services, and Bureau of Land Management have partnered to conduct airborne geophysical and 3DEP lidar surveys over parts of Nevada and California to collect information on undiscovered geothermal, critical mineral, and groundwater resources in the western Great Basin and the Walker Lane region.

15 GEOTHERMAL ENERGY↗

NASA NTRS2008

Near-Real Time Cloud Retrievals from Operational and Research Meteorological Satellites

A set of cloud retrieval algorithms developed for CERES and applied to MODIS data have been adapted to analyze other satellite imager data in near-real time. The cloud products, including single-layer cloud amount, top and base height, optical depth, phase, effective particle size, and liquid and ice water paths, are being retrieved from GOES- 10/11/12, MTSAT-1R, FY-2C, and Meteosat imager data as well as from MODIS. A comprehensive system to normalize the calibrations to MODIS has been implemented to maximize consistency in the products across platforms. Estimates of surface and top-of-atmosphere broadband radiative fluxes are also provided. Multilayered cloud properties are retrieved from GOES-12, Meteosat, and MODIS data. Native pixel resolution analyses are performed over selected domains, while reduced sampling is used for full-disk retrievals. Tools have been developed for matching the pixel-level results with instrumented surface sites and active sensor satellites. The calibrations, methods, examples of the products, and comparisons with the ICESat GLAS lidar are discussed. These products are currently being used for aircraft icing diagnoses, numerical weather modeling assimilation, and atmospheric radiation research and have potential for use in many other applications.

Minnis, Patrick↗

NASA NTRS2002

MODIS Data from the GES DISC DAAC: Moderate-Resolution Imaging Spectroradiometer (MODIS)

The Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC) is responsible for the distribution of the Level 1 data, and the higher levels of all Ocean and Atmosphere products (Land products are distributed through the Land Processes (LP) DAAC DAAC, and the Snow and Ice products are distributed though the National Snow and Ice Data Center (NSIDC) DAAC). Ocean products include sea surface temperature (SST), concentrations of chlorophyll, pigment and coccolithophores, fluorescence, absorptions, and primary productivity. Atmosphere products include aerosols, atmospheric water vapor, clouds and cloud masks, and atmospheric profiles from 20 layers. While most MODIS data products are archived in the Hierarchical Data Format-Earth Observing System (HDF-EOS 2.7) format, the ocean binned products and primary productivity products (Level 4) are in the native HDF4 format. MODIS Level 1 and 2 data are of the Swath type and are packaged in files representing five minutes of Files for Level 3 and 4 are global products at daily, weekly, monthly or yearly resolutions. Apart from the ocean binned and Level 4 products, these are in Grid type, and the maps are in the Cylindrical Equidistant projection with rectangular grid. Terra viewing (scenes of approximately 2000 by 2330 km). MODIS data have several levels of maturity. Most products are released with a provisional level of maturity and only announced as validated after rigorous testing by the MODIS Science Teams. MODIS/Terra Level 1, and all MODIS/Terra 11 micron SST products are announced as validated. At the time of this publication, the MODIS Data Support Team (MDST) is working with the Ocean Science Team toward announcing the validated status of the remainder of MODIS/Terra Ocean products. MODIS/Aqua Level 1 and cloud mask products are released with provisional maturity.

Source record↗

NASA NTRSDate not supplied

Novel Hourly-Resolved Global Cloud Property Composite from Operational Satellites Imagers

Numerous applications in satellite remote sensing of surface properties, atmospheric state, composition, and radiation require accurate knowledge of the location and characteristics of clouds. Operational satellite imager radiances are valuable for cloud detection and for deriving many different physical parameters that can be used for a variety of weather, aviation, and energy applications. The NASA Satellite ClOud and Radiation Property retrieval System (SatCORPS) applies a suite of algorithms to meteorological satellite data to provide cloud properties, radiative fluxes and other parameters on a global scale. This paper describes a new global high-resolution dataset of cloud properties made available for community use that is constructed from analyses of a constellation of meteorological satellite imagers. Data taken from Meteosat-8/9 and -11, Himawari-8/9, GOES-16, and -17/-18, Aqua, Terra, Suomi-NPP and NOAA-20 are processed and composited on a 3-km grid to provide hourly global coverage. A historical multi-year dataset is available to serve various needs including modeling challenges related to cloud evaluations and parameterizations. Near real-time data products are also currently available between 60N and 60S. Efforts are underway to operationalize polar orbiting satellite cloud detection methods for low-latency applications over polar regions. The cloud detection and retrieval algorithms have been developed over many years to support NASA weather and climate programs such as the Clouds and Earth’s Radiant Energy System (CERES). To improve the utility of the data products, machine learning and other innovative methods are applied in various ways to help minimize data product uncertainties under the most challenging conditions and to improve their consistency at all times of day. A brief description of the methods highlighting the unique aspects of the SatCORPS data products will be presented along with information on their status and availability.

SatCORPS↗

NASA NTRS2001

Global Lidar Measurements of Clouds and Aerosols from Space Using the Geoscience Laser Altimeter System (GLAS)

The Geoscience Laser Altimeter System (GLAS) is scheduled for launch on the ICESat satellite as part of the NASA EOS mission in 2002. GLAS will be used to perform high resolution surface altimetry and will also provide a continuously operating atmospheric lidar to profile clouds, aerosols, and the planetary boundary layer with horizontal and vertical resolution of 175 and 76.8 m, respectively. GLAS is the first active satellite atmospheric profiler to provide global coverage. Data products include direct measurements of the heights of aerosol and cloud layers, and the optical depth of transmissive layers. In this poster we provide an overview of the GLAS atmospheric data products, present a simulated GLAS data set, and show results from the simulated data set using the GLAS data processing algorithm. Optical results from the ER-2 Cloud Physics Lidar (CPL), which uses many of the same processing algorithms as GLAS, show algorithm performance with real atmospheric conditions during the Southern African Regional Science Initiative (SAFARI 2000).

Hlavka, Dennis L.↗

NASA NTRS2012

Applications for Near-Real Time Satellite Cloud and Radiation Products

At NASA Langley Research Center, a variety of cloud, clear-sky, and radiation products are being derived at different scales from regional to global using geostationary satellite (GEOSat) and lower Earth-orbiting (LEOSat) imager data. With growing availability, these products are becoming increasingly valuable for weather forecasting and nowcasting. These products include, but are not limited to, cloud-top and base heights, cloud water path and particle size, cloud temperature and phase, surface skin temperature and albedo, and top-of-atmosphere radiation budget. Some of these data products are currently assimilated operationally in a numerical weather prediction model. Others are used unofficially for nowcasting, while testing is underway for other applications. These applications include the use of cloud water path in an NWP model, cloud optical depth for detecting convective initiation in cirrus-filled skies, and aircraft icing condition diagnoses among others. This paper briefly describes a currently operating system that analyzes data from GEOSats around the globe (GOES, Meteosat, MTSAT, FY-2) and LEOSats (AVHRR and MODIS) and makes the products available in near-real time through a variety of media. Current potential future use of these products is discussed.

Minnis, Patrick↗

NASA NTRSDate not supplied

Hydrological Data at the NASA GES DISC: Current Capabilities and New Opportunities

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of twelve NASA Earth science data centers that document, process, archive and distribute data from Earth observation missions and projects. GES DISC maintains an archive of several hydrology datasets, including the Land Data Assimilation Systems (LDAS) and the Gravity Recovery and Climate Experiment (GRACE) Data Assimilation for Drought Monitoring (GRACE-DA-DM) data products. These datasets include model output of heat fluxes, rain, snow, soil temperature, soil moisture, and runoff; and observational forcing data, including surface pressure, temperature, precipitation, downward shortwave and longwave radiation, humidity, and wind. The temporal resolution of the hydrology data at GES DISC ranges from hourly to monthly, and spatial resolutions range from 0.1° to 1.0°. The GES DISC provides services which enable users to aggregate, temporally and spatially subset, regrid, and visualize archived data including the GES DISC Subsetter, Hydrology Data Rods, and the Geospatial Interactive Online Visualization and Analysis Infrastructure (GIOVANNI). The Hydrology Data Rods service optimally reorganizes large hydrological data sets as extended time series, providing more efficient access for the hydrological community. The time series data (aka “data rods”) were integrated into hydrology community tools, such as the Data Rods Explorer on HydroShare. Furthermore, the GES DISC is in the process of migrating its data and services to the cloud. Hydrological data available at the GES DISC are now available in the Amazon Web Services (AWS) cloud (us-west-2 region) providing users Direct S3 data access and the capability for cloud computing operations. In this presentation, the hydrology data products and services currently available at the GES DISC will be summarized. Also discussed are the migration to the cloud, user support through this transition, and the status of migrating the data rods service to the cloud.

Ashley Heath↗

NASA NTRSDate not supplied

TPSAS-NF1676L-31179-DND

This presentation will brief the GEWEX Radiation Panel on the progress and results of the GEWEX SRB project during the last year toward production and assessment of the Release 4.0 data set. First, an update is presented regarding SRB Release 4.0 "Integrated Product" that produces consistent with GEWEX projects estimating land and ocean latent and sensible heat fluxes. Changes from the Release 3/3.1 data products to Release 4 are reviewed both for key inputs (such as the ISCCP HXS, the nn-HIRS, Land and Sea surface temperatures) and key algorithm changes. Differences between the old and new input properties are assessed and flux sensitivities to those inputs are summarized. Sample radiative flux data products are presented and compared against the previous version for span of the production run, currently from 1998 through 2012. These fluxes are also compared to surface measurements (i.e., BSRN) and CERES (Clouds and Earth's Radiant Energy System) data products both in terms of bulk statistics and also time series variability. Lastly, the plans for continued processing, archival, assessment and research and will be presented to the panel for discussion and feedback.

Paul W Stackhouse, Jr↗

NASA NTRS1991

The Earth Observing System Data and Information System

The system is described in terms of the broad context of scientific cooperation and research which are facilitated by the architecture designed and the nature of the generated data. The Earth Observing System Data and Information System (EOSDIS) is composed of earth-science and applications data systems which archive global-change data and distribute the information to system users. Several archive centers catalogue selected Pathfinder data sets and generate new data products (such as maps of sea ice, cloud studies, etc.) with consistent calibration of all data. The schedule of three versions of EOSDIS is discussed with reference to the system architecture, programmatic plans, and data policy. The critical issue for EOSDIS is international cooperation to sponsor an infrastructure of global change data of this magnitude for public benefit and scientific research.

Maiden, Martha E.↗

NASA NTRS2004

Atmospheric and Surface Reflectance Measurements by the Geoscience Laser Altimeter System

The Geoscience Laser Altimeter System launched in early 2003 is the first satellite instrument IC space to globally observe the distribution of clouds and aerosol through laser remote sensing. The instrument is a basic backscatter lidar that operates at two wavelengths, 532 and 1064 nm. The mission data products for atmospheric observations include the calibrated, observed, attenuated backscatter cross section for cloud and aerosol; height detection for multiple cloud layers; planetary boundary layer height; cirrus and aerosol optical depth and the height distribution of aerosol and cloud scattering cross section profiles. The data will enhance knowledge in several areas of atmospheric science: the distribution, transport and influence of atmospheric aerosol, significantly more accurate measurements of the coverage and height of cirrus and other clouds, polar cloud climatology and radiation influence, the dynamics planetary boundary layer and others. An overview and summary of initial results are presented. Initial results from the first months of operation show the detailed height structure of clouds and aerosol on a global basis as expected. The 532 nm channel was expected to be the more sensitive and primary channel for aerosol measurements, but extensive aerosol loading in many regions are observed by the 1064 nm channel. Sensitivities are down to a few times l0(exp 6) l/(m-sr), much better than originally expected. The 532 channel adds an order of magnitude addition sensitivity. Initial comparisons to aerosol models have been done. Similarly for global cloud cover, good results are obtained just from the 1064 nm channel and from both channels, a measurement of multiple layers and cloud overlap has been made. Antarctica observations show high levels of total cloud cover including unique low-level cirrus and blowing snow. Data products have been generated for cloud, aerosol and PBL presence and heights in addition to the basic scattering cross section profiles.

Spinhirne, James D.↗

NASA NTRS2021

On-Orbit Calibration and Performance Assessments of Terra and Aqua Modis Thermal Emissive Bands

Terra and Aqua MODIS have successfully operated for more than 20 and 18 years, respectively, and far exceeded their designed lifetimes of 6 years. MODIS has 36 spectral bands, among which 16 are the thermal emissive bands (TEB) covering a wavelength range from 3.75 to 14.24 μm. Observations from the MODIS TEB have been used to generate a number of data products, such as surface/cloud/atmospheric temperatures, cloud top altitude, and water vapor properties. To a large extent, the quality of the MODIS L1B radiance product has been maintained through the entirety of each mission via extensive on-orbit calibration and validation efforts. MODIS TEB calibration uses a quadratic algorithm and is referenced to an on-board blackbody with its temperature measurements traceable to the NIST standard. We provide an overview of the MODIS instrument operations, key TEB calibration activities, and algorithms used in the latest L1B data Collection 6.1 (C6.1) and describe the TEB on-orbit performance for both Terra and Aqua MODIS. The TEB gain trends have been stable to within 5% over the Terra mission after 2003 under the same electronic configuration, except for bands 27 to 30, and within 3% over the Aqua mission. The Terra MODIS optical crosstalk correction implemented right after launch has been very effective in removing the ghost images in its photoconductive detector bands 32 to 36. Starting from C6.1, an electronic crosstalk correction algorithm has also been applied to the Terra MODIS photovoltaic detector long-wave infrared bands 27 to 30. The noise characterization performance remains stable with most TEB detectors continuously meeting their design requirements. A gradual loss of the Aqua MODIS radiative cooler margin reached its maximum in 2013 and has been slowly recovering since then. On-orbit changes in TEB response versus scan angle are extremely small based on pitch maneuver observations and assessments using vicarious approaches. The remaining challenges in TEB calibration and proposed improvements for the upcoming data collection with L1B data production and reprocessing are discussed.

Terra↗

DOE OSTI2023

System and method to fuse multiple sources of optical data to generate a high-resolution, frequent and cloud-/gap-free surface reflectance product

Aspects of the subject disclosure may include, for example, performing, by a processing system, image fusion using two or more groups of images to generate predicted images, wherein each group of the two or more groups has one of a different resolution, a different frequency temporal pattern or a combination thereof than another of the two or more groups. Gap filling can be performed by the processing system to correct images of the two or more groups. Additional embodiments are disclosed.

Guan, Kaiyu↗

NASA NTRSDate not supplied

Machine Learning Algorithms for Aerosol and Cloud Detection Using CATS on the ISS

Clouds and aerosols are one of the largest uncertainties in understanding and forecasting the Earth’s changing climate system. The type and height of aerosols are important factors in determining the top-of-atmosphere (TOA) radiation budget, either direct reflection of solar radiation back to space and/or absorption of solar radiation. In addition to their impact on the Earth’s climate system, aerosols near the surface from wildfires, man-made pollution events, and dust storms are hazardous to human health. The phase and height of clouds also play a critical role in determining the role of clouds in the Earth’s climate system. Cirrus clouds in the upper troposphere can induce a significant daytime TOA warming effect, while liquid water clouds near the surface cause a large corresponding cooling effect. Lidar measurements provide accurate vertically resolved information about clouds and aerosols, including complex multi-layer scenes where passive sensors are challenged and at night, when passive sensors are unable to measure cloud and aerosol properties. The Cloud-Aerosol Transport System (CATS) is a lidar instrument that operated for 33 months on the International Space Station (ISS) at the 1064 nm wavelength to measure attenuated total backscatter and depolarization ratio. These fundamental measurements are used to derive “vertical feature mask” cloud and aerosol products, including layer top/base heights, layer geometrical thickness, aerosol type, and cloud phase. While space-based lidar systems like CATS provide cloud and aerosol vertical distributions that improve our understanding of the climate system, averaging of the daytime data from these sensors is required, at the expense of spatial resolution, to improve the daytime signal-to noise (SNR) and thus atmospheric layer detection. This presentation shows results from machine learning (ML) techniques that, when applied to CATS data: 1. improve the 1064 nm SNR 2. enable detection of atmospheric features during daytime with a horizontal resolution of 350 m or 5 km (compared to the 60 km required for standard CATS data products) 3. increase the number of atmospheric layers detected in the CATS data. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination, cloud phase, and aerosol typing compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime. The ML tools described in this paper can facilitate the development of smaller, low-cost lidar systems in the future and enable real-time accessibility of lidar data products from future lidar systems for monitoring and forecasting of hazardous events.

John Yorks↗