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Using the NASA EOSDIS Common Metadata Repository

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  • A-Train Integrated CALIPSO, CloudSat, CERES, and MODIS Merged Product Release B1

    https://cmr.earthdata.nasa.gov/search/concepts/C5769450-LARC_ASDC.xml
    Description:

    The CER-NEWS_CCCM_Aqua-FM3-MODIS-CAL-CS_RelB1 contains the current CERES CCCM data. The CALIPSO-CloudSat-CERES-MODIS (CCCM) data set integrates measurements from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), CloudSat Cloud Profiling Radar (CPR), Clouds and the Earth's Radiant Energy System (CERES), and the Moderate Resolution Imaging Spectroradiometer (MODIS) data. The cloud and aerosol properties from CALIOP and cloud properties from the CPR are matched to a MODIS pixel and then an Aqua CERES footprint. The product contains only the CERES footprint in each scan that has the highest CALIPSO and CloudSat ground track coverage. The product consists of all cloud and aerosol properties derived from MODIS radiances included in the Single Scanner Footprint (SSF) product and computed irradiances included in the Cloud Radiative Swath (CRS) product. Two sets of SSF variables are including the CCCM data. One set covers the entire CERES footprint and the other set is only over CALIOP and CPR ground track. CERES derived top-of-atmosphere (TOA) shortwave, longwave and window irradiances by angular distribution models are also included. In addition, irradiance profiles computed by a radiative transfer model using MODIS, CALIOP, and CPR derived aerosol, clouds, and surface properties are included in the product. Furthermore, MODIS-derived cloud properties from the algorithm that incorporates CALIOP and CPR cloud information are also included. MODIS-derived cloud properties and TOA irradiances derived from CERES radiances are produced by the same algorithm that produces CERES SSF and CRS products. However, the CCCM product should not be considered as a climate data record since various input data product versions and algorithm modifications will occur along the course of the measurement period. The scan and packet numbers unique to the CERES footprint provide the means to match the data to other CERES products, although the CCCM product contains more near nadir CERES footprints compared with SSF and CRS products. The resulting HDF granule contains 24 hours of data.CERES is a key component of the Earth Observing System (EOS) program. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions are a follow-on to the successful Earth Radiation Budget Experiment (ERBE) mission. The first CERES instrument (PFM) was launched on November 27, 1997 as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit on board the EOS flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched on board EOS Aqua on May 4, 2002. The newest CERES instrument (FM5) was launched on board the Suomi National Polar-orbiting Partnership (NPP) satellite on October 28, 2011.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -90 -180 90 180

    LARC_ASDC Short Name: CER-NEWS_CCCM_Aqua-FM3-MODIS-CAL-CS Version ID: RelB1 Unique ID: C5769450-LARC_ASDC

  • ABoVE: Burn Severity, Fire Progression, and Field Data, NWT, Canada, 2015-2016

    https://cmr.earthdata.nasa.gov/search/concepts/C1422976988-ORNL_DAAC.xml
    Description:

    This data set provides a fire progression map for year 2015 and measures of burn severity and vegetation community biophysical data collected from areas that were burned by wildfires in 2014 and 2015 in the Northwest Territories, Canada. Field data collected in 2016 include an estimate of burn severity, woody seedling/sprouting data, soil moisture, peat depth, thaw depth, and vegetation cover for selected sites.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 59.93 -135.54 68.33 -106.76

    ORNL_DAAC Short Name: Wildfires_NWT_Canada_1548 Version ID: 1 Unique ID: C1422976988-ORNL_DAAC

  • ABoVE: Burn Severity, Fire Progression, Landcover and Field Data, NWT, Canada, 2014

    https://cmr.earthdata.nasa.gov/search/concepts/C1248454748-ORNL_DAAC.xml
    Description:

    This data set provides peatland landcover classification maps, fire progression maps, and vegetation community biophysical data collected from areas that were burned by wildfire in 2014 in the Northwest Territories, Canada. The peatland maps include peatland type (bog, fen, marsh, swamp) and level of biomass (open, forested). The fire progression maps enabled an assessment of wildfire progression rates at a daily time scale. Field data, collected in 2015, include an estimate of burn severity, woody seedling/sprouting data, soil moisture, and tree diameter and height of burned sites and similar vegetation characterization at landcover validation sites.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 60.33 -121.6 64.25 -110.68

    ORNL_DAAC Short Name: Wildfires_2014_NWT_Canada_1307 Version ID: 1 Unique ID: C1248454748-ORNL_DAAC

  • ABoVE: Corrected MODIS MAIAC Reflectance at Tower Sites, Alaska and Canada, 2000-2016

    https://cmr.earthdata.nasa.gov/search/concepts/C1627102549-ORNL_DAAC.xml
    Description:

    This dataset provides angular corrections of MODIS Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC) surface reflectances by two methods at each of 62 flux tower sites (1 km x 1 km area) across the ABoVE domain in Alaska and western Canada from 2000 to 2015/2016. The original MAIAC reflectance data were corrected to consistent view and illumination angles (0 degree view zenith angle and 45 degree of sun zenith angle) using two independent algorithms: the first based on the original BRDF (Bidirectional Reflectance Distribution Function) parameters provided by the MAIAC team, and the second based on a machine learning approach (random forests). The corrected data preserve the original MAIAC data's sub-daily temporal resolution and 1 km spatial resolution with seven land bands (bands 1-7) and five ocean bands (bands 8-12). The resulting tower site sub-daily timeseries of angular corrected surface reflectances are suitable for long-term studies on patterns, processes, and dynamics of surface phenomena.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 42.64 -157.41 71.32 -74.04

    ORNL_DAAC Short Name: MODIS_MAIAC_Reflectance_1700 Version ID: 1 Unique ID: C1627102549-ORNL_DAAC

  • ABoVE: Fractional Open Water Cover for Pan-Arctic and ABoVE-Domain Regions, 2002-2015

    https://cmr.earthdata.nasa.gov/search/concepts/C1358859924-ORNL_DAAC.xml
    Description:

    This data set provides land surface fractional open water cover maps for two overlapping regions: the entire pan-Arctic region (latitude > 45 degrees) and the Arctic-Boreal Vulnerability Experiment (ABoVE) domain across Alaska and Canada. The data are a 10-day averaged time step at 5-km spatial resolution for the period 2002-2015. Data represent the aerial portion of a grid cell covered by open water. The data were produced using high frequency (89 GHz) brightness temperatures from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and the Advanced Microwave Scanning Radiometer 2 (AMSR2), with other ancillary inputs from AMSR-E/AMSR2 25-km products and the Moderate Resolution Imaging Spectroradiometer (MODIS). The resulting data record for fractional water is suitable for documenting open water patterns and inundation dynamics in boreal-Arctic ecosystems experiencing rapid climate change.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 39.38 -180 90 180

    ORNL_DAAC Short Name: ABoVE_Frac_Open_Water_1362 Version ID: 1 Unique ID: C1358859924-ORNL_DAAC

  • ABoVE: Ignitions, burned area and emissions of fires in AK, YT, and NWT, 2001-2015

    https://cmr.earthdata.nasa.gov/search/concepts/C1400101586-ORNL_DAAC.xml
    Description:

    This data set provides estimates of daily burned area, carbon emissions and uncertainty, and daily fire ignition locations for boreal fires in Alaska, USA, and the Yukon and Northwest Territories, Canada. The data are at 500-m resolution for the period 2001 to 2015.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 59.99 -176.93 75.75 -100

    ORNL_DAAC Short Name: Alaskan_Wildfire_C_Emissions_1341 Version ID: 1 Unique ID: C1400101586-ORNL_DAAC

  • ABoVE: MODIS-derived Maximum NDVI, Northern Alaska and Yukon Territory for 2002-2017

    https://cmr.earthdata.nasa.gov/search/concepts/C1566856315-ORNL_DAAC.xml
    Description:

    This dataset provides the maximum Normalized Difference Vegetation Index (NDVI) at 1-km resolution over northern Alaska, USA and the Yukon Territory, Canada for each year from 2002-2017, as well as a 16 year maximum NDVI product. MODIS products MOD13Q1 and MYD13Q1 from Collection 6 were acquired at 250-m pixel size from June 1-August 30 of each year. Within each growing season from 2002-2017, the maximum NDVI was determined for each pixel. These maximum NDVI values were then aggregated to 1-km by selecting the maximum NDVI from the sixteen 250-m pixels values nested within each 1-km pixel. A long-term 16-year maximum NDVI was then derived from the time series of annual maximum NDVI values.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 52.17 -175.76 68.97 -97.93

    ORNL_DAAC Short Name: Alaska_Yukon_NDVI_1614 Version ID: 1 Unique ID: C1566856315-ORNL_DAAC

  • ABoVE: Rain-on-Snow Frequency and Distribution during Cold Seasons, Alaska, 2003-2016

    https://cmr.earthdata.nasa.gov/search/concepts/C1579375356-ORNL_DAAC.xml
    Description:

    This dataset provides maps of rain-on-snow (ROS) events across Alaska for the individual months of November to March 2002-2011 and November to March 2012-2016, and annual water year summary maps for 2003-2011 and 2013-2016. ROS events were defined as changes in passive microwave (PM) detection in surface snow wetness and isothermal states induced by atmospheric processes often associated with winter rainfall. The data are summations of the number of days with ROS events per pixel at 6-km spatial resolution per month or per 5-month water year. The daily ROS record encompassed the months when snowmelt from solar irradiance is minimal and snow cover is widespread and relatively consistent throughout the region. Daily ROS geospatial classification across Alaska was derived by combining snow cover and daily microwave brightness temperature retrievals sensitive to landscape freeze-thaw dynamics from overlapping (1) Moderate Resolution Imaging Spectroradiometer (MODIS) MOD10A2 eight-day maximum snow cover extent (SCE) product and (2) Advanced Microwave Scanning Radiometer for EOS (AMSR-E) (2002-2011) and the Advanced Microwave Scanning Radiometer 2 (AMSR2) (2012-to present) Microwave Radiation Imager (MWRI) observations at 19 GHz and 37 GHz.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 48.62 -175.4 73.85 -111.54

    ORNL_DAAC Short Name: Rain-on-Snow_Data_1611 Version ID: 1 Unique ID: C1579375356-ORNL_DAAC

  • AIRS-AMSU variables-CloudSat cloud mask, radar reflectivities, and cloud classification matchups V3.2 (AIRSM_CPR_MAT) at GES DISC

    https://cmr.earthdata.nasa.gov/search/concepts/C1236224182-GES_DISC.xml
    Description:

    This is AIRS-CloudSat collocated subset, in NetCDF 4 format. These data contain collocated: AIRS/AMSU retrievals at AMSU footprints, CloudSat radar reflectivities, and MODIS cloud mask. These data are created within the frames of the MEaSUREs project. The basic task is to bring together retrievals of water vapor and cloud properties from multiple "A-train" instruments (AIRS, AMSR-E, MODIS, AMSU, MLS, CloudSat), classify each "scene" (instrument look) using the cloud information, and develop a merged, multi-sensor climatology of atmospheric water vapor as a function of altitude, stratified by the cloud classes. This is a large science analysis project that will require the use of SciFlo technologies to discover and organize all of the datasets, move and cache datasets as required, find space/time "matchups" between pairs of instruments, and process years of satellite data to produce the climate data records. The short name for this collection is AIRSM_CPR_MAT Parameters contained in the data files include the following: Variable Name|Description|Units CH4_total_column|Retrieved total column CH4| (molecules/cm2) CloudFraction|CloudSat/CALIPSO Cloud Fraction| (None) CloudLayers| Number of hydrometeor layers| (count) clrolr|Clear-sky Outgoing Longwave Radiation|(Watts/m**2) CO_total_column|Retrieved total column CO| (molecules/cm2) CPR_Cloud_mask| CPR Cloud Mask |(None) Data_quality| Data Quality |(None) H2OMMRSat|Water vapor saturation mass mixing ratio|(gm/kg) H2OMMRStd|Water Vapor Mass Mixing Ratio |(gm/kg dry air) MODIS_Cloud_Fraction| MODIS 250m Cloud Fraction| (None) MODIS_scene_var |MODIS scene variability| (None) nSurfStd|1-based index of the first valid level|(None) O3VMRStd|Ozone Volume Mixing Ratio|(vmr) olr|All-sky Outgoing Longwave Radiation|(Watts/m**2) Radar_Reflectivity| Radar Reflectivity Factor| (dBZe) Sigma-Zero| Sigma-Zero| (dB*100) TAirMWOnlyStd|Atmospheric Temperature retrieved using only MW|(K) TCldTopStd|Cloud top temperature|(K) totH2OStd|Total precipitable water vapor| (kg/m**2) totO3Std|Total ozone burden| (Dobson) TSurfAir|Atmospheric Temperature at Surface|(K) TSurfStd|Surface skin temperature|(K) End of parameter information

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -90 -180 90 180

    GES_DISC Short Name: AIRSM_CPR_MAT Version ID: 3.2 Unique ID: C1236224182-GES_DISC

  • AIRS-CloudSat cloud mask and radar reflectivities collocation indexes V4.0 (AIRS_CPR_IND) at GES_DISC

    https://cmr.earthdata.nasa.gov/search/concepts/C1236224151-GES_DISC.xml
    Description:

    Version 4.1 is the current version of the data set. Previous versions are no longer available and have been superseded by Version 4.1. This is AIRS-AMSU-CloudSat collocation indexes, in netCDF-4 format. These data map CloudSat profile indexes to the collocated AMSU field of views, and AIRS IR footprints, per AIRS 6-min granule time. Hence it can be considered as Level 1. These data are created within the frames of the MEaSUREs project. The basic task is to bring together retrievals of water vapor and cloud properties from multiple "A-train" instruments (AIRS, AMSR-E, MODIS, AMSU, MLS, & CloudSat), classify each "scene" (instrument look) using the cloud information, and develop a merged, multi-sensor climatology of atmospheric water vapor as a function of altitude, stratified by the cloud classes. This is a large science analysis project that will require the use of SciFlo technologies to discover and organize all of the datasets, move and cache datasets as required, find space/time "matchups" between pairs of instruments, and process years of satellite data to produce the climate data records. The short name for this collection is AIRS_CPR_IND

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -90 -180 90 180

    GES_DISC Short Name: AIRS_CPR_IND Version ID: 4.0 Unique ID: C1236224151-GES_DISC