{"id":302371,"date":"2023-05-05T13:43:04","date_gmt":"2023-05-05T17:43:04","guid":{"rendered":"https:\/\/www.nasa.gov\/?post_type=topic&p=302371"},"modified":"2023-07-03T14:17:21","modified_gmt":"2023-07-03T18:17:21","slug":"data-products","status":"publish","type":"topic","link":"https:\/\/www.nasa.gov\/nasa-earth-exchange-nex\/earth-observations-geonex\/data-products\/","title":{"rendered":"Data Products"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">Data Products<\/h2>\n\n\n\n<div style=\"height:35px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th>Products<\/th><th><strong>Data Frequency<\/strong><\/th><th><strong>Algorithm<\/strong><\/th><\/tr><\/thead><tbody><tr><td>Top-of-Atmosphere Reflectance Brightness Temperature<br>Solar Zenith\/Azimuth Angles<br>Satellite View Zenith\/Azimuth Angles<\/td><td>10-minute<br>10-minute<br>Fixed<\/td><td>Wang et al. (2020)<br>Yamamoto et al. (2020)<\/td><\/tr><tr><td>Cloud Mask<br>Aerosol Optical Depth<br>Surface Reflectance<br>Surface BRDF<\/td><td>10-minute<br>10-minute<br>10-minute<br>Daily<\/td><td>Lyapustin et al. (2018)<br>Wang et al. (2022)<\/td><\/tr><tr><td>Land Surface Temperature <br><br><br>Surface Solar Radiation<\/td><td>10-minute\/Hourly<br><br><br>10-minute\/Hourly<\/td><td>Yu et al. (2010)<br>Duffy et al. (2021)<br><br>Liang et al. (2006)<br>Li et al. (2023)<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<div style=\"height:52px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Level 1G Products: <\/strong>Top-of-Atmosphere (TOA) Reflectance and Brightness Temperature <\/h3>\n\n\n<div id=\"\" class=\"hds-media hds-module wp-block-image\"><div class=\"margin-left-auto margin-right-auto nasa-block-align-inline\"><div class=\"hds-media-wrapper margin-left-auto margin-right-auto\"><figure class=\"hds-media-inner hds-cover-wrapper hds-media-ratio-fit \"><a href=\"https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/toa.png\"><img fetchpriority=\"high\" decoding=\"async\" width=\"936\" height=\"364\" src=\"https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/toa.png?w=936\" class=\"attachment-2048x2048 size-2048x2048\" alt=\"NEX TOA map of globe\" style=\"transform: scale(1); transform-origin: 50% 50%; object-position: 50% 50%; object-fit: cover;\" block_context=\"nasa-block\" srcset=\"https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/toa.png 936w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/toa.png?resize=300,117 300w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/toa.png?resize=768,299 768w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/toa.png?resize=400,156 400w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/toa.png?resize=600,233 600w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/toa.png?resize=900,350 900w\" sizes=\"(max-width: 936px) 100vw, 936px\" loading=\"eager\" \/><\/a><\/figure><\/div><\/div><\/div>\n\n\n<div style=\"height:14px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>The GeoNEX TOA products provided radiometrically calibrated BRFs (reflective bands), brightness temperatures (emissive bands), and pixelwise Sun angles at every time step, all of which were correctly registered to the common tiled grid in the geographic projection. The true-color image shown above is created based on TOA BRFs from Himawari 8 AHI, GOES 17 ABI, and GOES 16 ABI. The pseudo \u201cgreen band\u201d of the ABI instrument is generated from the red, the blue, and the near-infrared bands with linear weights of 0.483, 0.457, and 0.060, respectively. The thin gray lines indicate coastlines and the boundaries of the GeoNEX tiles. We expect to derive similar MTG\/FCI L1G products to fill up the missing coverage over Europe and Africa in late 2023 or early 2024.<\/p>\n\n\n\n<div style=\"height:38px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Level 2 Products: Surface BRDF and Reflectance<\/strong><\/h3>\n\n\n<div id=\"\" class=\"hds-media hds-module wp-block-image\"><div class=\"margin-left-auto margin-right-auto nasa-block-align-inline\"><div class=\"hds-media-wrapper margin-left-auto margin-right-auto\"><figure class=\"hds-media-inner hds-cover-wrapper hds-media-ratio-fit \"><a href=\"https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/surface-brdf.png\"><img loading=\"lazy\" decoding=\"async\" width=\"936\" height=\"360\" src=\"https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/surface-brdf.png?w=936\" class=\"attachment-2048x2048 size-2048x2048\" alt=\"\" style=\"transform: scale(1); transform-origin: 50% 50%; object-position: 50% 50%; object-fit: cover;\" block_context=\"nasa-block\" srcset=\"https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/surface-brdf.png 936w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/surface-brdf.png?resize=300,115 300w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/surface-brdf.png?resize=768,295 768w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/surface-brdf.png?resize=400,154 400w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/surface-brdf.png?resize=600,231 600w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/surface-brdf.png?resize=900,346 900w\" sizes=\"(max-width: 936px) 100vw, 936px\" \/><\/a><\/figure><\/div><\/div><\/div>\n\n\n<p>We adopt the Multi-Angle Implementation of Atmospheric Correction (<a href=\"https:\/\/modis-land.gsfc.nasa.gov\/MAIAC.html\" data-type=\"URL\" data-id=\"https:\/\/modis-land.gsfc.nasa.gov\/MAIAC.html\" rel=\"noopener\">MAIAC<\/a>) algorithm to exploit the high temporal resolutions of the latest geostationary satellite sensors (e.g., GOES-16\/17 ABI, Himawari 8\/9 AHI, and Geo-KOMPSAT 2A\/AMI) in deriving surface reflectance (SR), atmospheric aerosol optical depth (AOD), and the corresponding BRDF model parameters. The algorithm is developed based on Green\u2019s functions and BRDF-specific radiative transfer model as well as its framework for time-series processing. It dynamically maintains a set of variables that \u201cmemorize\u201d the surface properties at each grid cell from the preceding time steps and use them for the up-coming processing. Therefore, we can even combine the prior knowledge of surface BRDF with cloudy-sky observations to predict the most likely \u201cclear-sky\u201d surface reflectance at given illumination-view geometries. <\/p>\n\n\n\n<p><\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong><strong>Level 3 Products: Surface Downward Solar Radiation<\/strong><\/strong><\/h3>\n\n\n<div id=\"\" class=\"hds-media hds-module wp-block-image\"><div class=\"margin-left-auto margin-right-auto nasa-block-align-inline\"><div class=\"hds-media-wrapper margin-left-auto margin-right-auto\"><figure class=\"hds-media-inner hds-cover-wrapper hds-media-ratio-fit \"><a href=\"https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/surface-downward-solar-radiation.png\"><img loading=\"lazy\" decoding=\"async\" width=\"936\" height=\"366\" src=\"https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/surface-downward-solar-radiation.png?w=936\" class=\"attachment-2048x2048 size-2048x2048\" alt=\"surface-downward-solar-radiation graphic\" style=\"transform: scale(1); transform-origin: 50% 50%; object-position: 50% 50%; object-fit: cover;\" block_context=\"nasa-block\" srcset=\"https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/surface-downward-solar-radiation.png 936w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/surface-downward-solar-radiation.png?resize=300,117 300w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/surface-downward-solar-radiation.png?resize=768,300 768w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/surface-downward-solar-radiation.png?resize=400,156 400w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/surface-downward-solar-radiation.png?resize=600,235 600w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/surface-downward-solar-radiation.png?resize=900,352 900w\" sizes=\"(max-width: 936px) 100vw, 936px\" \/><\/a><\/figure><\/div><\/div><\/div>\n\n\n<p>We employ a well-established physical-based lookup table (LUT) approach to create a data product of Downward Shortwave Radiation (DSR) and Photosynthetic Active Radiation (PAR) over both AHI and ABI coverage at an hourly temporal step with a 1 km spatial resolution. The DSR and PAR data are validated over in-situ measurement stations. The validation showed that the new GeoNEX DSR and PAR products have accuracy higher than other existing products, with root mean square error (RMSE) of hourly DSR achieving 74.3Wm\u22122 (18.0%), daily DSR estimation achieving 18.0 W m\u22122 (9.2 %), hourly PAR achieving 34.9 W m\u22122 (19.6 %), and daily PAR achieving 9.5 W m\u22122 (10.5 %). <\/p>\n\n\n\n<div style=\"height:52px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Data Access<\/h2>\n\n\n\n<p>Level 1 data and gridded data products are available at the <em><strong><a href=\"https:\/\/data.nas.nasa.gov\/geonex\/data.php\" target=\"_blank\" rel=\"noreferrer noopener\">NASA Earth Exchange data portal<\/a><\/strong><\/em>, hosted by NASA\u2019s Advanced Supercomputing. NASA-supported investigations under the ROSES 2019 <a href=\"https:\/\/nspires.nasaprs.com\/external\/solicitations\/summary!init.do?solId=%7BA786F499-3D4A-1B30-2620-945ACCF3360C%7D&path=open\" target=\"_blank\" rel=\"noreferrer noopener\">“Earth Science Research from Operational Geostationary Satellite Systems\u201d<\/a> program element will, in addition, have access to tools, additional data, computing and support. For questions and\/or issues with the data products, email <a href=\"mailto:support@nas.nasa.gov\">support@nas.nasa.gov<\/a> and include “GeoNEX” in the subject line. \u200b<\/p>\n\n\n\n<p>GeoNEX users with <a href=\"https:\/\/www.nas.nasa.gov\/hecc\/accounts\/getaccounts.html\" target=\"_blank\" rel=\"noreferrer noopener\">NAS accounts<\/a> can find the all data products on the Lustre file systems here \/nex\/datapool\/geonex\/.<\/p>\n\n\n\n<p>Supporting datasets for any research and development of data products, such as MODIS products, Landsat, VIIRS, or any other relevant datasets, can also be found on the NAS file systems at \/nex\/datapool\/<\/p>\n\n\n\n<div style=\"height:49px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Global Grid System<\/h2>\n\n\n\n<p>All GeoNEX products are in a geographic coordinate system (i.e., latitude\/longitude grid) with a spatial resolution of 0.01 x 0.01 degrees (visible\/near infrared bands) or 0.02 x 0.02 degrees (shortwave\/thermal Infrared bands).<\/p>\n\n\n\n<p>The geospatial domain of the GOES ABI is the region from 60\u00b0N, 138\u00b0W to 60\u00b0S, 18\u00b0W. The domain of the Himawari AHI is the region from 60\u00b0N, 78\u00b0E to 60\u00b0S, 198\u00b0E. The regions are divided into 20×20 rectangular tiles, numbered from 0 to 19 in the vertical dimension. Each tile contains 600×600 (visible\/near infrared bands) or 300×300 (shortwave\/thermal infrared bands) pixels, representing 6\u00b0 by 6\u00b0.<\/p>\n\n\n<div id=\"\" class=\"hds-media hds-module wp-block-image\"><div class=\"margin-left-auto margin-right-auto nasa-block-align-inline\"><div class=\"hds-media-wrapper margin-left-auto margin-right-auto\"><figure class=\"hds-media-inner hds-cover-wrapper hds-media-ratio-fit \"><a href=\"https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/globalgrid-v3.png\"><img loading=\"lazy\" decoding=\"async\" width=\"985\" height=\"487\" src=\"https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/globalgrid-v3.png?w=985\" class=\"attachment-2048x2048 size-2048x2048\" alt=\"NEX global grid of GOES and Himawari satellites.\" style=\"transform: scale(1); transform-origin: 50% 50%; object-position: 50% 50%; object-fit: cover;\" block_context=\"nasa-block\" srcset=\"https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/globalgrid-v3.png 985w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/globalgrid-v3.png?resize=300,148 300w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/globalgrid-v3.png?resize=768,380 768w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/globalgrid-v3.png?resize=400,198 400w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/globalgrid-v3.png?resize=600,297 600w, https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/05\/globalgrid-v3.png?resize=900,445 900w\" sizes=\"(max-width: 985px) 100vw, 985px\" \/><\/a><\/figure><figcaption class=\"hds-caption padding-y-2\"><div class=\"hds-caption-text p-sm margin-0\">Coverage and spatial resolution (km) of the GOES and Himawari satellites.<\/div><\/figcaption><\/div><\/div><\/div>\n\n\n<p>The temporal resolution of the products is every 15 minutes (for the full domain) or every 5 minutes (for the conterminous U.S.)<\/p>\n\n\n\n<p>Example for 0.01×0.01 (1km) grid:<\/p>\n\n\n\n<p># Basic parameters<\/p>\n\n\n\n<p>lat_0 = 60<\/p>\n\n\n\n<p>lon_0 = -180<\/p>\n\n\n\n<p>res_x = 0.01                # 0.02 for the 2km grid<\/p>\n\n\n\n<p>res_y = 0.01                # 0.02 for the 2km grid<\/p>\n\n\n\n<p>tile_xdim = 600            # 300 for the 2km grid<\/p>\n\n\n\n<p>tile_ydim = 600            # 300 for the 2km grid<\/p>\n\n\n\n<p># Input information<\/p>\n\n\n\n<p>hid = 14                       # 0 – 59<\/p>\n\n\n\n<p>vid =  5                        # 0 – 19<\/p>\n\n\n\n<p>x = 0                            # column\/sample, 0-(tile_xdim-1) <\/p>\n\n\n\n<p>y = 0                            # row\/line, 0-(tile_ydim-1) <\/p>\n\n\n\n<p># Output formula <\/p>\n\n\n\n<p>lat_ulcnr = lat_0 – (vid*tile_ydim + y)*res_y        # upper-left corner latitude<\/p>\n\n\n\n<p>lon_ulcnr = lon_0 + (hid*tile_xdim + x)*res_y     # upper-left corner longitude<\/p>\n\n\n\n<p>lat_cntr = lat_ulcnr – 0.5*res_y                            # center latitude<\/p>\n\n\n\n<p>lon_cntr = lon_ulcnr + 0.5*res_x                        # center longitude<\/p>\n\n\n\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">File Format<\/h3>\n\n\n\n<p>The data are organized by tile and date. The naming convention of the files is:<\/p>\n\n\n\n<p><Satellite\/Sensor Code><ProductID>_<YYYYMMDD>_<HHMM>_GLBG_h<hid>v<vid>_<version>.hdf<\/p>\n\n\n\n<p><Satellite\/Sensor Code>: HM08_AHI for Himawari 8 AHI, and GO16_ABI or GO17_ABI for GOES<\/p>\n\n\n\n<p><Product ID>: A two-digit number assigned to each GeoNEX product. Currently, only the Product ID of \u201c05\u201d is available, indicating \u201cTop-of-Atmosphere Reflectance\u201d<\/p>\n\n\n\n<p><YYYYMMDD>: Year-Month-Day, e.g., 20180501<\/p>\n\n\n\n<p><HHMM>: Hour-Minute (UTC time), e.g., 2030<\/p>\n\n\n\n<p><hid>, <vid>: Horizontal or Vertical Tile ID (0-19)<\/p>\n\n\n\n<p><version>: Product version code. It is currently \u201c02\u201d<\/p>\n\n\n\n<div style=\"height:59px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Disclaimer<\/h3>\n\n\n\n<p><em>The data are considered provisional and subject to change. The data are provided as is without any warranty of any kind, either express or implied, arising by law or otherwise, including but not limited to warranties of completeness, non-infringement, accuracy, merchantability, or fitness for a particular purpose. The user assumes all risk associated with the use of, or inability to use, the data.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Data Products Products Data Frequency Algorithm Top-of-Atmosphere Reflectance Brightness TemperatureSolar Zenith\/Azimuth AnglesSatellite View Zenith\/Azimuth Angles 10-minute10-minuteFixed Wang et al. (2020)Yamamoto et al. (2020) Cloud MaskAerosol Optical DepthSurface ReflectanceSurface BRDF 10-minute10-minute10-minuteDaily Lyapustin et al. (2018)Wang et al. (2022) Land Surface Temperature  Surface Solar Radiation 10-minute\/Hourly 10-minute\/Hourly Yu et al. (2010)Duffy et al. (2021) Liang et al. [...]<\/p>\n","protected":false},"author":136,"featured_media":251050,"parent":302332,"menu_order":0,"template":"","meta":{"nasa_hds_core_meta_l10n":"en-US","nasa_hds_core_meta_article_editor":"","nasa_hds_core_meta_article_contacts":[],"nasa_hds_core_meta_article_topic":"","nasa_hds_core_meta_linked_locations":[],"nasa_hds_core_meta_article_related_articles":[],"hds_migrate_meta_pr_release_id":"","hds_migrate_meta_pr_release_type":"","nasa_hds_core_meta_location_x":"","nasa_hds_core_meta_location_y":"","nasa_hds_core_meta_gallery_images":[]},"categories":[2834],"news-tags":[],"internal-terms":[],"coauthors":[10409],"parsely":{"version":"1.1.0","meta":{"@context":"https:\/\/schema.org","@type":"WebPage","headline":"Data Products","url":"https:\/\/www.nasa.gov\/nasa-earth-exchange-nex\/earth-observations-geonex\/data-products\/","mainEntityOfPage":{"@type":"WebPage","@id":"https:\/\/www.nasa.gov\/nasa-earth-exchange-nex\/earth-observations-geonex\/data-products\/"},"thumbnailUrl":"https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/03\/our-organization.jpeg?w=150&h=150&crop=1","image":{"@type":"ImageObject","url":"https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/03\/our-organization.jpeg"},"articleSection":"Science & Research","author":[{"@type":"Person","name":"Wen F. Yip"}],"creator":["Wen F. Yip"],"publisher":{"@type":"Organization","name":"NASA","logo":"https:\/\/www.nasa.gov\/wp-content\/themes\/nasa\/assets\/images\/nasa-logo.svg"},"keywords":["Science & Research","Earth Science"],"dateCreated":"2023-05-05T17:43:04Z","datePublished":"2023-05-05T17:43:04Z","dateModified":"2023-07-03T18:17:21Z"},"rendered":"<meta name=\"parsely-title\" content=\"Data Products\" \/>\n<meta name=\"parsely-link\" content=\"https:\/\/www.nasa.gov\/nasa-earth-exchange-nex\/earth-observations-geonex\/data-products\/\" \/>\n<meta name=\"parsely-type\" content=\"index\" \/>\n<meta name=\"parsely-image-url\" content=\"https:\/\/www.nasa.gov\/wp-content\/uploads\/2023\/03\/our-organization.jpeg?w=150&h=150&crop=1\" \/>\n<meta name=\"parsely-pub-date\" content=\"2023-05-05T17:43:04Z\" \/>\n<meta name=\"parsely-section\" content=\"Science & Research\" \/>\n<meta name=\"parsely-tags\" content=\"Science & Research,Earth Science\" \/>\n<meta name=\"parsely-author\" content=\"Wen F. 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