Dataset

Himawari-8 - GeoCat 1.0.3 Australian Domain Level 1 v1.0

Also known as: Himawari8-AusGeo1.0.3_L1
CLEX
Dr Claire Louise Vincent (Principal investigator) ARC Centre of Excellence for Climate Extremes Data Manager (Managed by)
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25914/60096221a8f7a&rft.title=Himawari-8 - GeoCat 1.0.3 Australian Domain Level 1 v1.0&rft.identifier=10.25914/60096221a8f7a&rft.publisher=CLEX&rft.description=This dataset contains derived satellite observations of cloud properties over the Australian region at hourly temporal resolution and 2 km spatial resolution. The Himawari-8 CSPPGeo Geocat collection Level-1 (L1) grid is on 2 km of horizontal resolution that includes Australia and the Maritime Continent. The L1 product include full output variables from CSPP-Geo Geocat and Advance Himawari Imagery on Himawari-8, 25, and 41 variables, respectively, with hourly temporal resolution for Austral summer months (Nov-March) from 01 November 2015 to 31 March 2020. This dataset is produced using the Geostationary Cloud Algorithm Testbed (Geocat) together with pre-processed ancillary data. The tool used to apply Geocat is described here: http://cimss.ssec.wisc.edu/csppgeo/geocat.htmlhttp://cimss.ssec.wisc.edu/csppgeo/geocat.html . The input data are Himawari-8 AHI retrievals v1.3, freely available from the Japanese Meteorological Agency. Meteorological Satellite Centre of JMA:  https://www.data.jma.go.jp/mscweb/en/himawari89/space_segment/sample_hisd.html Ancillary data come from OISST Huang, B., C. Liu, V. Banzon, E. Freeman, G. Graham, W. Hankins, T. Smith, and H.-M. Zhang, 2020: Improvements of the Daily Optimum Sea Surface Temperature (DOISST) - Version 2.1, doi:10.1175/JTECH-D-19-0177.1 GFS Global Forecast System (GFS) [0.5 Deg.] Landing Page  NOAA daily 4km snow and Ice Cover  HDF file containing merged NISE and IMS files on a daily gridded product. NISE - Brodzik, M. J. and J. S. Stewart. 2016. Near-Real-Time SSM/I-SSMIS EASE-Grid Daily Global Ice Concentration and Snow Extent, Version 5. [Indicate subset used]. Boulder, Colorado, USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/3KB2JPLFPK3R. [2020-10-01]. IMS - U.S. National Ice Center. 2008, updated daily. IMS Daily Northern Hemisphere Snow and Ice Analysis at 1 km, 4 km, and 24 km Resolutions, Version 1. [Indicate subset used]. Boulder, Colorado, USA. NSIDC: National Snow and Ice Data Center. doi: https://doi.org/10.7265/N52R3PMC. [2020-10-01]. L1 product includes the following variables: brightness temperature for channels from 7 to 16 reflectance for channels from 1 to 7 emissivity for channel 7 This dataset is a product of the Centre of Excellence for Climate Extremes (CLEX) Extreme Rainfall research project NB Some images were not available for processing at the time of the dataset release, we listed all the missing timesteps in the file L1_file_gaps_20210225.txt More images might become available and then new lists will be created accordingly with the timestamp indicating when the files where added. We ask users to specify the date they access the datasets when they cite them as indicated in the citation field.&rft.creator=Dr Claire Louise Vincent&rft.date=2020&rft.coverage=70.16,-51.42 188.80,-51.42 188.80,23.09 70.16, 23.09 70.16,-51.42&rft_rights=Users are free to share, copy and redistribute the material in any medium or format; adapt, remix, transform, and build upon the material for any purpose, even commercially. Users must give appropriate credit, provide a link to the license, and indicate if changes were made. They may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use. They may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.&rft_rights=Creative Commons - Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/legalcode&rft_subject=Cloud Physics&rft_subject=EARTH SCIENCES&rft_subject=ATMOSPHERIC SCIENCES&rft_subject=Meteorology&rft_subject=Atmospheric Dynamics&rft.type=dataset&rft.language=English Access the data
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Licence & Rights:

Open Licence view details
CC-BY

Creative Commons - Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/legalcode

Users are free to share, copy and redistribute the material in any medium or format; adapt, remix, transform, and build upon the material for any purpose, even commercially. Users must give appropriate credit, provide a link to the license, and indicate if changes were made. They may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use. They may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Access:

Open view details

Data is freely available on the NCI thredds server

Full description

This dataset contains derived satellite observations of cloud properties over the Australian region at hourly temporal resolution and 2 km spatial resolution. The Himawari-8 CSPPGeo Geocat collection Level-1 (L1) grid is on 2 km of horizontal resolution that includes Australia and the Maritime Continent. The L1 product include full output variables from CSPP-Geo Geocat and Advance Himawari Imagery on Himawari-8, 25, and 41 variables, respectively, with hourly temporal resolution for Austral summer months (Nov-March) from 01 November 2015 to 31 March 2020. This dataset is produced using the Geostationary Cloud Algorithm Testbed (Geocat) together with pre-processed ancillary data. The tool used to apply Geocat is described here: http://cimss.ssec.wisc.edu/csppgeo/geocat.htmlhttp://cimss.ssec.wisc.edu/csppgeo/geocat.html .
The input data are Himawari-8 AHI retrievals v1.3, freely available from the Japanese Meteorological Agency. Meteorological Satellite Centre of JMA:  https://www.data.jma.go.jp/mscweb/en/himawari89/space_segment/sample_hisd.html

Ancillary data come from

  • OISST Huang, B., C. Liu, V. Banzon, E. Freeman, G. Graham, W. Hankins, T. Smith, and H.-M. Zhang, 2020: Improvements of the Daily Optimum Sea Surface Temperature (DOISST) - Version 2.1, doi:10.1175/JTECH-D-19-0177.1
  • GFS Global Forecast System (GFS) [0.5 Deg.] Landing Page 
  • NOAA daily 4km snow and Ice Cover 

    HDF file containing merged NISE and IMS files on a daily gridded product.

    NISE - Brodzik, M. J. and J. S. Stewart. 2016. Near-Real-Time SSM/I-SSMIS EASE-Grid Daily Global Ice Concentration and Snow Extent, Version 5. [Indicate subset used]. Boulder, Colorado, USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/3KB2JPLFPK3R. [2020-10-01].

    IMS - U.S. National Ice Center. 2008, updated daily. IMS Daily Northern Hemisphere Snow and Ice Analysis at 1 km, 4 km, and 24 km Resolutions, Version 1. [Indicate subset used]. Boulder, Colorado, USA. NSIDC: National Snow and Ice Data Center. doi: https://doi.org/10.7265/N52R3PMC. [2020-10-01].

L1 product includes the following variables:

  • brightness temperature for channels from 7 to 16
  • reflectance for channels from 1 to 7
  • emissivity for channel 7

This dataset is a product of the Centre of Excellence for Climate Extremes (CLEX) Extreme Rainfall research project

NB Some images were not available for processing at the time of the dataset release, we listed all the missing timesteps in the file L1_file_gaps_20210225.txt

More images might become available and then new lists will be created accordingly with the timestamp indicating when the files where added.

We ask users to specify the date they access the datasets when they cite them as indicated in the citation field.

Created: 2020-12-01

Data time period: 2015-11-01 to 2020-03-31

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Spatial Coverage And Location

kmlPolyCoords: 70.16,-51.42 188.80,-51.42 188.80,23.09 70.16, 23.09 70.16,-51.42

Subjects
Atmospheric Sciences | Atmospheric Dynamics | Cloud Physics | Earth Sciences | Meteorology |

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