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41 results for “Himawari”
Himawari-8/AHI hourly clear-sky land surface temperature and emissivity dataset (2021.9-2021.12)
<p>This is the clear-sky LST and LSE dataset (0.02°, hourly) derived by the iTES algorithm (Zhou and Cheng, 2020) from the Himawari-8 AHI thermal infrared data. A broadband emissivity (BBE, 8-13.5μm) dataset was also produced using the derived AHI narrowband LSEs (Cheng et al. 2013). The in-situ validation results show that the bias and RMSE of the retrieved AHI LST are 0.19 and 2.93 K in the daytime, and −0.43 and 1.95 K in the nighttime, respectively. The bias and RMSE of the retrieved LSE are less than 0.005 and 0.014, respectively, compared with the latest MYD21 LSE. The time period of this dataset is 2016-2021, covering the AHI 0.02° nominal fixed grid (60°N∼60°S, 80°E∼160°W).</p> <p>This is the LST&E dataset in 2021.09-2021.12</p> <p><strong>Dataset Characteristics:</strong></p> <ul> <li>Spatial Coverage: East Asia and Western Pacific regions (60°N∼60°S, 80°E-140°E)</li> <li>Temporal Coverage: 2021.09-2021.12</li> <li>Spatial Resolution: 0.02 °</li> <li>Temporal Resolution: one hour</li> <li>Projection: GCS_WGS_1984</li> <li>Data Format: NetCDF</li> </ul> <p><strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong></p> <ol> <li> <p>Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. <em>IEEE Transactions on Geoscience and Remote Sensing, 58</em>, 7105-7124</p> </li> <li> <p>Cheng, J., et al. (2013). Estimating the Optimal Broadband Emissivity Spectral Range for Calculating Surface Longwave Net Radiation. <em>IEEE Geoscience and Remote Sensing Letters, 10</em>, 401-40</p> </li> </ol> <p>If you have any questions, please contact Prof. Jie Cheng (Jie_Cheng@bnu.edu.cn).</p>
ELITE emissivity: Himawari-8/AHI daily 0.02° BBE (2020)
<p>The <strong>E</strong>ssential therma<strong>L</strong> <strong>I</strong>nfrared remo<strong>T</strong>e s<strong>E</strong>nsing (<strong>ELITE</strong>) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (<a href="https://elite.bnu.edu.cn">https://elite.bnu.edu.cn</a>).</p> <p>This dataset is the Himawari-8/AHI daily 0.02° BBE produced from the hourly clear-sky narrowband emissivities (NBEs) derived by the iTES algorithm (Zhou and Cheng, 2020). The bias and RMSE of the retrieved hourly NBEs are less than 0.005 and 0.014, respectively, compared with the latest MYD21 LSEs. The temporal resolution and spatial resolution of this dataset are daily and 0.02°, respectively.</p> <p>This is the ELITE Himawari-8/AHI BBE product in 2020. Please <a href="https://www.zenodo.org/record/7636009"><strong><em>click here</em></strong></a> to download the ELITE NBE product in 2019 and <a href="https://www.zenodo.org/record/7663349"><strong><em>click here</em></strong></a> to download the ELITE BBE product in 2021.</p> <p><strong>Dataset Characteristics:</strong></p> <ul> <li>Spatial Coverage: AHI 0.02° nominal fixed grid (60°N∼60°S, 80°E∼160°W)</li> <li>Temporal Coverage: 2020</li> <li>Spatial Resolution: 0.02°</li> <li>Temporal Resolution: daily</li> <li>Data Format: HDF</li> <li>Scale: 0.001</li> </ul> <p><strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong></p> <ol> <li>Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. IEEE Transactions on Geoscience and Remote Sensing, 58(10), 7105-7124.</li> </ol> <p>If you have any questions, please contact Prof. Jie Cheng (eliteqrs@126.com).</p>
SatCORPS CERES GEO Edition 4 Himawari-9 Northern Hemisphere Version 1.2
CER_GEO_Ed4_HIM09_NH_V01.2 is the Satellite Cloud and Radiation Property retrieval System (SatCORPS) Clouds and the Earth's Radiant Energy System (CERES) Geostationary Satellite (GEO) Edition 4 Himawari-9 over the Northern Hemisphere (NH) Version 1.2 data product. Data was collected using the Advanced Himawari Imager (AHI) Instrument on the Himawari-9 platform.Note: Version 1.2 is identical to version 1.0. No changes have been made to the retrieval algorithm.This data set comprises cloud micro-physical and radiation properties derived hourly from Himawari-9 geostationary satellite imager data using the Langley Research Center (LaRC) SATCORPS algorithms supporting the CERES project. The data set is arranged as files for each hour in netCDF-4 format. The observations are at 2 km resolution (at nadir) and are sub-sampled to 6 km (taking every third line and pixel).
SatCORPS CERES GEO Edition 4 Himawari-8 Northern Hemisphere Version 1.2
CER_GEO_Ed4_HIM08_NH_V01.2 is the Satellite Cloud and Radiation Property retrieval System (SatCORPS) Clouds and the Earth's Radiant Energy System (CERES) Geostationary Satellite (GEO) Edition 4 Himawari-8 over the Northern Hemisphere (NH) Version 1.2 data product. Data was collected using the Advanced Himawari Imager (AHI) Instrument on the Himawari-8 platform.Note: Version 1.2 is identical to version 1.0. No changes have been made to the retrieval algorithm.This data set comprises cloud micro-physical and radiation properties derived hourly from Himawari-8 geostationary satellite imager data using the Langley Research Center (LaRC) SATCORPS algorithms supporting the CERES project. The data set is arranged as files for each hour in netCDF-4 format. The observations are at 2 km resolution (at nadir) and are sub-sampled to 6 km (taking every third line and pixel).
SatCORPS CERES GEO Edition 4 Himawari-8 Southern Hemisphere Version 1.2
CER_GEO_Ed4_HIM08_SH_V01.2 is the Satellite Cloud and Radiation Property retrieval System (SatCORPS) Clouds and the Earth's Radiant Energy System (CERES) Geostationary Satellite (GEO) Edition 4 Himawari-8 over the Southern Hemisphere (SH) Version 1.2 data product. Data was collected using the Advanced Himawari Imager (AHI) Instrument on the Himawari-8 platform.Note: Version 1.2 is identical to version 1.0. No changes have been made to the retrieval algorithm.This data set comprises cloud micro-physical and radiation properties derived hourly from Himawari-8 geostationary satellite imager data using the Langley Research Center (LaRC) SATCORPS algorithms supporting the CERES project. The data set is arranged as files for each hour in netCDF-4 format. The observations are at 2 km resolution (at nadir) and are sub-sampled to 6 km (taking every third line and pixel).
SatCORPS CERES GEO Edition 4 Himawari-9 Southern Hemisphere Version 1.2
CER_GEO_Ed4_HIM09_SH_V01.2 is the Satellite Cloud and Radiation Property retrieval System (SatCORPS) Clouds and the Earth's Radiant Energy System (CERES) Geostationary Satellite (GEO) Edition 4 Himawari-9 over the Southern Hemisphere (SH) Version 1.2 data product. Data was collected using the Advanced Himawari Imager (AHI) Instrument on the Himawari-9 platform.Note: Version 1.2 is identical to version 1.0. No changes have been made to the retrieval algorithm.This data set comprises cloud micro-physical and radiation properties derived hourly from Himawari-9 geostationary satellite imager data using the Langley Research Center (LaRC) SATCORPS algorithms supporting the CERES project. The data set is arranged as files for each hour in netCDF-4 format. The observations are at 2 km resolution (at nadir) and are sub-sampled to 6 km (taking every third line and pixel).
GHRSST NOAA/STAR Himawari-08 AHI L3C Pacific Ocean Region SST v2.70 dataset in GDS2
The ACSPO H08/AHI L3C (Level 3 Collated) product is a gridded version of the ACSPO H08/AHI L2P product available at https://podaac.jpl.nasa.gov/dataset/AHI_H08-STAR-L2P-v2.70. The L3C output files are 1hr granules in NetCDF4 format, compliant with the GHRSST Data Specification version 2 (GDS2). There are 24 granules available per 24hr interval, with a total data volume of 0.2GB/day. Valid SSTs are found over clear-sky oceans, sea, lakes or rivers, with fill values reported elsewhere. The following layers are reported: SST, ACSPO clear-sky mask (ACSM; provided in each grid as part of l2p_flags, which also includes day/night, land, ice, twilight, and glint flags), NCEP wind speed and ACSPO SST minus reference (Canadian Met Centre 0.1deg L4 SST; available at https://podaac.jpl.nasa.gov/dataset/CMC0.1deg-CMC-L4-GLOB-v3.0 ). All valid SSTs in L3C are recommended for users, although data over internal waters may not have enough in situ data to be adequately validated. Per GDS2 specifications, two additional Sensor-Specific Error Statistics layers (bias and standard deviation) are reported in each pixel with valid SST (Petrenko et al., 2016). The ACSPO VIIRS L3U product is monitored and validated against iQuam in situ data (Xu and Ignatov, 2014) in SQUAM (Dash et al, 2010).
GHRSST L2P NOAA/ACSPO Himawari-09 AHI Pacific Ocean Region Sea Surface Temperature v2.90 dataset
The H09-AHI-L2P-ACSPO-v2.90 dataset contains the Subskin Sea Surface Temperature (SST) produced by the NOAA ACSPO system from the Advanced Himawari Imager (AHI; largely identical to GOES-R/ABI) onboard the Himawari-9 (H09) satellite. The H09 is a Japanese weather satellite, the 9th of the Himawari geostationary weather satellite operated by the Japan Meteorological Agency. It was launched on November 2, 2016 into its nominal position at 140.7-deg E, and declared operational on December 13, 2022, replacing the Himawari-8. The AHI is the primary instrument on the Himawari Series for imaging Earth’s weather, oceans, and environment with high temporal and spatial resolutions. <br><br>The H08/AHI maps SST in a Full Disk (FD) area from 80E-160W and 60S-60N, with spatial resolution 2km at nadir to 15km/VZA (view zenith angle) 67-deg, and 10-min temporal sampling. The 10-min FD data are subsequently collated in time, to produce the 1-hr product, with improved coverage and reduced cloud leakages and image noise. The L2P data is produced in GHRSST compliant netCDF4 GDS2 format, with 24 granules per day, and a total data volume 1.2 GB/day. The near-real time (NRT) data are updated hourly, with several hours latency. The NRT files are replaced with Delayed Mode (DM) files, with a latency of approximately 2-months. File names remain unchanged, and DM vs NRT can be identified by different time stamps and global attributes inside the files (MERRA instead of GFS for atmospheric profiles, and same day CMC L4 analyses in DM instead of one-day delayed in NRT processing). <br><br>Pixel earth locations are not reported in the granules, as they remain unchanged from granule to granule. Pixel locations can be obtained using a flat lat/lon file or a Python script available via Documents tab from the dataset landing page. Climate and Forecast (CF) metadata aware software (e.g., Panoply, xarray) can detect and map the data as is via the granule CF projection attributes and variables. The ACSPO H09 HAI SSTs are validated against quality controlled in situ data from the NOAA iQuam system (Xu and Ignatov, 2014) and continuously monitored in the NOAA SQUAM system (Dash et al, 2010). A 0.02-deg equal-angle gridded L3C product 0.7GB/day) is available at https://podaac.jpl.nasa.gov/dataset/H09-AHI-L3C-ACSPO-v2.90
GHRSST NOAA/STAR Himawari-08 AHI L2P Pacific Ocean Region SST v2.70 dataset in GDS2
Himawari-8 (H08) was launched on 7 October 2014 into its nominal position at 140.7-deg E, and declared operational on 7 July 2015. The Advanced Himawari Imager (AHI; largely identical to GOES-R/ABI) is a 16 channel sensor, of which five (3.9, 8.4, 10.3, 11.2, and 12.3 um) are suitable for SST. Accurate sensor calibration, image navigation and (co)registration, high spectral fidelity, and sophisticated pre-processing (geo-rectification, radiance equalization, and mapping) offer vastly enhanced capabilities for SST retrievals, over the heritage GOES-I/P and MTSAT-2 Imagers. From altitude 35,800km, H08/AHI maps SST in a Full Disk (FD) area from 80E-160W and 60S-60N, with spatial resolution 2km at nadir to 15km at view zenith angle 67-deg, with a 10-min temporal sampling. The AHI L2P (swath) SST product is derived at the native sensor resolution using NOAA's Advanced Clear-Sky Processor for Ocean (ACSPO) system. ACSPO processes every 10-min FD data, identifies good quality ocean pixels (Petrenko et al., 2010) and derives SST using the four-band (8.4, 10.3, 11.2 and 12.3um) Non-Linear SST (NLSST) regression algorithm (Petrenko et al., 2014), trained against in situ SSTs from drifting and tropical mooring buoys in the NOAA iQuam system (Xu and Ignatov, 2014). The 10-min data are subsequently collated in time, to produce 1-hr L2P product, with improved coverage, and reduced cloud leakages and image noise. The collated L2P reports SSTs and brightness temperatures (BTs) in clear-sky water pixels (defined as ocean, sea, lake or river), and fill values elsewhere. All pixels with valid SSTs are recommended for use. ACSPO files also include sun-sensor geometry, l2p_flags (day/night, land, ice, twilight, and glint flags), and NCEP wind speed. The L2P is reported in NetCDF4 GHRSST Data Specification version 2 (GDS2) format, 24 granules per day, with a total data volume 0.6GB/day. Pixel earth locations are not reported in the granules, as they remain unchanged from granule to granule. Those can be obtained using a flat lat/lon file or a Python script (see Documentation page). Per GDS2 specifications, two additional Sensor-Specific Error Statistics layers (SSES bias and standard deviation) are reported in each pixel (Petrenko et al., 2016). The H08 AHI SSTs and BTs are continuously validated against in situ data in SQUAM (Dash et al, 2010), and RTM simulation in MICROS (Liang and Ignatov, 2011). A reduced size (0.2GB/day), 0.02-deg equal-angle gridded ACSPO L3C product is available at https://podaac.jpl.nasa.gov/dataset/AHI_H08-STAR-L3C-v2.70.
Himawari-8/AHI hourly clear-sky land surface temperature and emissivity dataset (2017.5-2017.8)
<p>This is the clear-sky LST and LSE dataset (0.02°, hourly) derived by the iTES algorithm (Zhou and Cheng, 2020) from the Himawari-8 AHI thermal infrared data. A broadband emissivity (BBE, 8-13.5μm) dataset was also produced using the derived AHI narrowband LSEs (Cheng et al. 2013). The in-situ validation results show that the bias and RMSE of the retrieved AHI LST are 0.19 and 2.93 K in the daytime, and −0.43 and 1.95 K in the nighttime, respectively. The bias and RMSE of the retrieved LSE are less than 0.005 and 0.014, respectively, compared with the latest MYD21 LSE. The time period of this dataset is 2016-2021, covering the AHI 0.02° nominal fixed grid (60°N∼60°S, 80°E∼160°W).</p> <p>This is the LST&E dataset in 2017.05-2017.08</p> <p><strong>Dataset Characteristics:</strong></p> <ul> <li>Spatial Coverage: East Asia and Western Pacific regions (60°N∼60°S, 80°E-140°E)</li> <li>Temporal Coverage: 2017.05-2017.08</li> <li>Spatial Resolution: 0.02 °</li> <li>Temporal Resolution: one hour</li> <li>Projection: GCS_WGS_1984</li> <li>Data Format: NetCDF</li> </ul> <p><strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong></p> <ol> <li> <p>Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. <em>IEEE Transactions on Geoscience and Remote Sensing, 58</em>, 7105-7124</p> </li> <li> <p>Cheng, J., et al. (2013). Estimating the Optimal Broadband Emissivity Spectral Range for Calculating Surface Longwave Net Radiation. <em>IEEE Geoscience and Remote Sensing Letters, 10</em>, 401-40</p> </li> </ol> <p>If you have any questions, please contact Prof. Jie Cheng (Jie_Cheng@bnu.edu.cn).</p>
Himawari-8/AHI hourly clear-sky land surface temperature and emissivity dataset (2020.9-2020.12)
<p>This is the clear-sky LST and LSE dataset (0.02°, hourly) derived by the iTES algorithm (Zhou and Cheng, 2020) from the Himawari-8 AHI thermal infrared data. A broadband emissivity (BBE, 8-13.5μm) dataset was also produced using the derived AHI narrowband LSEs (Cheng et al. 2013). The in-situ validation results show that the bias and RMSE of the retrieved AHI LST are 0.19 and 2.93 K in the daytime, and −0.43 and 1.95 K in the nighttime, respectively. The bias and RMSE of the retrieved LSE are less than 0.005 and 0.014, respectively, compared with the latest MYD21 LSE. The time period of this dataset is 2016-2021, covering the AHI 0.02° nominal fixed grid (60°N∼60°S, 80°E∼160°W).</p> <p>This is the LST&E dataset in 2020.09-2020.12</p> <p><strong>Dataset Characteristics:</strong></p> <ul> <li>Spatial Coverage: East Asia and Western Pacific regions (60°N∼60°S, 80°E-140°E)</li> <li>Temporal Coverage: 2020.09-2020.12</li> <li>Spatial Resolution: 0.02 °</li> <li>Temporal Resolution: one hour</li> <li>Projection: GCS_WGS_1984</li> <li>Data Format: NetCDF</li> </ul> <p><strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong></p> <ol> <li> <p>Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. <em>IEEE Transactions on Geoscience and Remote Sensing, 58</em>, 7105-7124</p> </li> <li> <p>Cheng, J., et al. (2013). Estimating the Optimal Broadband Emissivity Spectral Range for Calculating Surface Longwave Net Radiation. <em>IEEE Geoscience and Remote Sensing Letters, 10</em>, 401-40</p> </li> </ol> <p>If you have any questions, please contact Prof. Jie Cheng (Jie_Cheng@bnu.edu.cn).</p>
AHI/Himawari-09 Dark Target Aerosol 10-Min L2 Full Disk 10 km
The AHI/Himawari-09 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_AHI_H09 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 142 granules over the daylit hours of a 24-hour period (there are no images produced at 02:20 or 14:20 UTC for navigation purposes). The Himawari-9 platform currently serves in the operational Himawari position (near 140.7°E) since it was launched November 2, 2016, and replaces Himawari-8. The Himawari-9/AHI collection record spans from 13th December 2022 through 31st December 2022.The XAERDT_L2_AHI_H09 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites.The XAERDT_L2_AHI_H09 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs.For more information consult LAADS product description page at:https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_AHI_H09Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/
SatCORPS CERES GEO Edition 4 Himawari-9 Southern Hemisphere Version 1.4
CER_GEO_Ed4_HIM09_SH_V01.4 is the Satellite Cloud and Radiation Property Retrieval System (SatCORPS) Clouds and the Earth's Radiant Energy System (CERES) Geostationary Satellite (GEO) Edition 4 Himawari-9 over the Southern Hemisphere (SH) Version 1.4 data product. Data was collected using the Advanced Himawari Imager (AHI) Instrument on the Himawari-9 platform. Note: Version 1.4 uses the Global Modeling and Assimilation Office (GMAO) Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis for atmospheric input; Version 1.2 used GMAO's GEOS-5.4.1. No changes have been made to the cloud retrieval algorithm.This data set comprises cloud micro-physical and radiation properties derived hourly from Himawari-9 geostationary satellite imager data using the Langley Research Center (LARC) SATCORPS algorithms supporting the CERES project. The data set is arranged as files for each hour and in netCDF-4 format. The observations are at 2 km resolution (at nadir) and are sub-sampled to 6 km (taking every third line and pixel).
GHRSST L3C NOAA/ACSPO Himawari-09 AHI Pacific Ocean Region Sea Surface Temperature v2.90 dataset
The H09-AHI-L3C-ACSPO-v2.90 dataset contains the Subskin Sea Surface Temperature (SST) produced by the NOAA ACSPO system from the Advanced Himawari Imager (AHI; largely identical to GOES-R/ABI) onboard the Himawari-9 (H09) satellite. The H09 is a Japanese weather satellite, the 9th of the Himawari geostationary weather satellite operated by the Japan Meteorological Agency. It was launched on November 2, 2016 into its nominal position at 140.7-deg E, and declared operational on December 13, 2022, replacing the Himawari-8. The AHI is the primary instrument on the Himawari Series for imaging Earth’s weather, oceans, and environment with high temporal and spatial resolutions. <br><br>The H09-AHI-L3C-ACSPO-v2.90 dataset is a gridded version of the ACSPO H09-AHI-L2P-ACSPO-v2.90 dataset (https://podaac.jpl.nasa.gov/dataset/AHI_H09-STAR-L2P-v2.90). The L3C (Level 3 Collated) data is mapped on 0.02-deg lat-lon grid and outputs 24 hourly granules per day, with a daily volume of 0.7 GB/day. Valid SSTs are found over oceans, sea, lakes or rivers, with fill values reported elsewhere. All valid SSTs in L3C are recommended for users, although data over internal waters may not have enough in situ data to be adequately validated. Per GDS2 specifications, two additional Sensor-Specific Error Statistics layers (bias and standard deviation) are reported in each pixel with valid SST. <br><br>The ACSPO H09/AHI L3C product is validated against iQuam in situ data (Xu and Ignatov, 2014) and continuously monitored in the NOAA SQUAM system (Dash et al, 2010). The NRT files are replaced with Delayed Mode (DM) files, with a latency of approximately 2-months. File names remain unchanged, and DM vs NRT can be identified by different time stamps and global attributes inside the files (MERRA for DM instead of GFS for atmospheric profiles, and same day CMC L4 analyses in DM instead of one-day delayed in NRT processing).
SatCORPS CERES GEO Edition 4 Himawari-8 Northern Hemisphere Version 1.4
CER_GEO_Ed4_HIM08_NH_V01.4 is the Satellite Cloud and Radiation Property retrieval System (SatCORPS) Clouds and the Earth's Radiant Energy System (CERES) Geostationary Satellite (GEO) Edition 4 Himawari-8 over the Northern Hemisphere (NH) Version 1.4 data product. Data was collected using the Advanced Himawari Imager (AHI) Instrument on the Himawari-8 platform.Note: Version 1.4 uses the Global Modeling and Assimilation Office (GMAO) Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis for atmospheric input; Version 1.2 used GMAO's GEOS-5.4.1. No changes have been made to the cloud retrieval algorithm.This data set comprises cloud micro-physical and radiation properties derived hourly from Himawari-8 geostationary satellite imager data using the Langley Research Center (LaRC) SATCORPS algorithms supporting the CERES project. The data set is arranged as files for each hour in netCDF-4 format. The observations are at 2 km resolution (at nadir) and are sub-sampled to 6 km (taking every third line and pixel).
SatCORPS CERES GEO Edition 4 Himawari-9 Northern Hemisphere Version 1.4
CER_GEO_Ed4_HIM09_NH_V01.4 is the Satellite Cloud and Radiation Property retrieval System (SatCORPS) Clouds and the Earth's Radiant Energy System (CERES) Geostationary Satellite (GEO) Edition 4 Himawari-9 over the Northern Hemisphere (NH) Version 1.4 data product. Data was collected using the Advanced Himawari Imager (AHI) Instrument on the Himawari-9 platform.Note: Version 1.4 uses the Global Modeling and Assimilation Office (GMAO) Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis for atmospheric input; Version 1.2 used GMAO's GEOS-5.4.1. No changes have been made to the cloud retrieval algorithm.This data set comprises cloud micro-physical and radiation properties derived hourly from Himawari-9 geostationary satellite imager data using the Langley Research Center (LaRC) SATCORPS algorithms supporting the CERES project. The data set is arranged as files for each hour in netCDF-4 format. The observations are at 2 km resolution (at nadir) and are sub-sampled to 6 km (taking every third line and pixel).
AHI/Himawari-08 Dark Target Aerosol 10-Min L2 Full Disk 10 km
The AHI/Himawari-08 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_AHI_H08 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 142 granules over the daylit hours of a 24-hour period (there are no images produced at 02:20 or 14:20 UTC for navigation purposes). The Himawari-8 platform served in the operational Himawari position (near 140.7°E) between October 2014 and 13 December 2022. Himawari-9 replaced Himawari-8 and is currently operational. The Himawari-8/AHI collection record spans from January 2019 through 12th December 2022. The final 19 days of 2022 (December 13 through 31) are served by L2 products derived from the Himawari-9/AHI instrument.The XAERDT_L2_AHI_H08 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites.The XAERDT_L2_AHI_H08 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs.For more information consult LAADS product description page at:https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_AHI_H08Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/
Himawari-08 AHI Deep Blue Aerosol L2
The Himawari-08 AHI Deep Blue Aerosol L2 Full Disk product, short-name AERDB_L2_AHI_H08 is produced every 30 minutes and contains full-disk observation data. The L2 data products comprise 10 x 10 native GEO pixels. Each spectral band with 0.5 km or 2 km resolution is downscaled or upscaled to a nominal ~1 km horizontal pixel size in the production process. To distinguish them from native instrument pixels, these 10 x 10 aggregated pixels are also called retrieval pixels. Therefore, the L2 products’ image dimensions are roughly 10 km x 10 km at the sub-satellite point and are larger away from that point because of the combined effects of the sensor’s scanning geometry and Earth’s curvature. This first release of these products spans from May 2019 through April 2020 with a potential to generate additional temporal coverage in the future. The Level-2 (L2) Advanced Himawari Imager (AHI) Himawari-8 Deep Blue Aerosol Full-Disk dataset is part of a 12-product suite produced by an Earth Science Research from Operational Geostationary Satellite Systems (ESROGSS)-funded project. The 12 products in this project include nine derived from three Geostationary Earth Observation (GEO) instruments and three from merged data from GEO and Low-Earth Orbit (LEO) instruments.The AERDB_L2_AHI_H08 product, in netCDF4 format, contains 51 Science Data Set (SDS) layers. For more information consult LAADS product description page at:https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/AERDB_L2_AHI_H08Or, Deep Blue aerosol project webpage at: https://earth.gsfc.nasa.gov/climate/data/deep-blue
SatCORPS CERES GEO Edition 4 Himawari-8 Southern Hemisphere Version 1.4
CER_GEO_Ed4_HIM08_SH_V01.4 is the Satellite Cloud and Radiation Property retrieval System (SatCORPS) Clouds and the Earth's Radiant Energy System (CERES) Geostationary Satellite (GEO) Edition 4 Himawari-8 over the Southern Hemisphere (SH) Version 1.4 data product. Data was collected using the Advanced Himawari Imager (AHI) Instrument on the Himawari-8 platform.Note: Version 1.4 uses the Global Modeling and Assimilation Office (GMAO) Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis for atmospheric input; Version 1.2 used GMAO's GEOS-5.4.1. No changes have been made to the cloud retrieval algorithm.This data set comprises cloud micro-physical and radiation properties derived hourly from Himawari-8 geostationary satellite imager data using the Langley Research Center (LARC) SATCORPS algorithms supporting the CERES project. The data set is arranged as files for each hour in netCDF-4 format. The observations are at 2 km resolution (at nadir) and are sub-sampled to 6 km (taking every third line and pixel).
Hourly aerosol assimilation of Himawari-8 AOT using the four-dimensional local ensemble transform Kalman filter
<p>These data are simulated results used in the manuscript titled "Hourly aerosol assimilation of Himawari-8 AOT using the four-dimensional local ensemble transform Kalman filter" to Journal of Advances in Modeling Earth Systems. </p>
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