Oct. 31, 2018 Updated
JAXA Himawari Monitor
Sep. 2015 JAXA/EORC

Starting to provide the Himawari L1 Gridded Data and change the provision period of Himawari Standard Data.

On August 31, 2016, we will start distribution of the "Himawari L1 Gridded data (NetCDF4 format)" as well as the "Himawari Standard Data (HSD format)" provided by the Japan Meteorological Agency (JMA). Himawari L1 Gridded data is generated by JAXA/EORC from the Himawari Standard Data with re-sampling to equal latitude-longitude grids. Please note that we will keep the Himawari Standard Data of the latest 30 days on the JAXA P-Tree system from October 2016, but you can download the Himawari L1 Gridded data of whole period.

1. Description of himawari data

JAXA's P-Tree system, that provides multi-satellite products, releases the geostationary satellite Himawari Standard Data provided by the Japan Meteorological Agency (JMA) as well as the geophysical parameter data produced by JAXA using the Himawari Standard Data.

Available Himawari Standard Data (HSD)

Full-disk

Observation areaFull-disk
Temporal resolution10-minute
Spatial resolution0.5km (band 3), 1km (band 1,2,4), 2km (band 5-16)

Japan Area

Observation areaJapan area (Region 1 & 2)
Temporal resolution2.5-minute
Spatial resolution0.5km (band 3), 1km (band 1,2,4), 2km (band 5-16)

Target Area

Observation areaTarget Area (Region 3)
Temporal resolution2.5-minute
Spatial resolution0.5km (band 3), 1km (band 1,2,4), 2km (band 5-16)

Color Image Data

Note png images of Full-disk, Japan area and Target area, compositing three visible bands (blue: 0.47 micron; green: 0.51 micron; red: 0.64 micron).
Color Image Data


Available Himawari L1 Data (Himawari L1 Gridded data)

Full-disk

File typeNetCDF
ProjectionEQR
Observation area60S-60N, 80E-160W
Temporal resolution10-minute
Spatial resolution 5km (Pixel number: 2401, Line number: 2401) 2km (Pixel number: 6001, Line number: 6001)
Data albedo(reflectance*cos(SOZ) of band01~band06)
Brightness temperature of band07~band16
satellite zenith angle, satellite azimuth angle,
solar zenith angle, solar azimuth angle, observation hours (UT)

Japan Area

File typeNetCDF
ProjectionEQR
Observation area24N-50N, 123E-150E
Temporal resolution10-minute
Spatial resolution 1km (Pixel number: 2701, Line number: 2601)
Data albedo(reflectance*cos(SOZ) of band01~band06)
Brightness temperature of band07, 14, 15
satellite zenith angle, satellite azimuth angle,
solar zenith angle, solar azimuth angle, observation hours (UT)


Available Geophysical Parameters

README

Aerosol Property (day-time only)

File typeNetCDF
Aerosol Optical Thickness
Latest version2.1 (Level 2), 3.0 (Level 3)
Observation areaFull-disk
Temporal resolution10-minute (Level 2), 1-hour (Level 3),
1-day (Level 3), 1-month (Level 3)
Spatial resolution 5km (Pixel number: 2401, Line number: 2401)
Data Angstrom exponent, Aerosol optical thickness at 500nm, Uncertainty of aerosol optical thickness, QA flag
Notice Ångström exponent included in this product is under validation. Users should keep in mind that the data is NOT quality assured.
JAXA Himawari Monitor aerosol products reference

Cloud Property (day-time only)

File typeNetCDF
Cloud Optical Thickness
Latest version1.0
Observation areaFull-disk
Temporal resolution10-minute (Level 2)
Spatial resolution 5km (Pixel number: 2401, Line number: 2401)
Data Cloud optical thickness, Cloud effective radius, Cloud top temperature,
Cloud top height, Cloud types (ISCCP Definition)

Sea Surface Temperature

File typeNetCDF(GDS2.0
Sea Surface Temperature
Latest version1.2
Observation areaFull-disk
Temporal resolution10-minute (Level 2), 1-hour (Level 3), 1-day(Level 3), 1-month (Level 3)
Spatial resolution 2km (Pixel number: 6001, Line number: 6001)
Data Sea Surface Temperature
(Please refer to the GDS2.0 format for other data included in 10-min, hourly and daily products.)
Notice JAXA has released Himawari SST standard product (version 1.2) since August 31, 2016. After uploading the standard product, the near-realtime (NRT) product will be removed from the server 72 hours after observation.
Note File version index (fv)
Himawari SST product file has a file version index (fvXX) in the filename to describe the number of processing times. File version index will be updated for example when the L3 product file will be re-generated due to L1 missing or delay. The P-tree system distributes the newest product file regarding the file version index.

Sea Surface Temperature(Night Mode)

File typeNetCDF(GDS2.0
Sea Surface Temperature(Night Mode)
Latest version1.2
Observation areaFull-disk
Temporal resolution1-hour (Level 3)
Spatial resolution 2km (Pixel number: 6001, Line number: 6001)
Data Please refer to the GDS2.0 format
Notice JAXA has released Himawari SST standard product (version 1.2) since August 31, 2016. After uploading the standard product, the near-realtime (NRT) product will be removed from the server 72 hours after observation.
Note File version index (fv)
Himawari SST product file has a file version index (fvXX) in the filename to describe the number of processing times. File version index will be updated for example when the L3 product file will be re-generated due to L1 missing or delay. The P-tree system distributes the newest product file regarding the file version index.

Short Wave Radiation / Photosynthetically Available Radiation

File typeNetCDF
Short Wave Radiation
Latest version1.0
Observation areaFull-disk
Temporal resolution10-minute (Level 2), 1-hour (Level 3), 1-day (Level 3), 1-month (Level 3)
Spatial resolution 5km (Pixel number: 2401, Line number: 2401)
1km Japan* (Pixel number: 2701, Line number: 2601)
*Rectangular area: 24N-50N, 123E-150E
Data Total atmosphere optical thickness of band 2, Total atmosphere angstrom exponent, Photosynthetically active radiation, Shortwave radiation, UltraViolet-A radiation, UltraViolet-B radiation

Chlorophyll-a

File typeNetCDF
Chlorophyll-a
Latest version1.0
Observation areaFull-disk
Temporal resolution1-hour (Level 3), 1-day (Level 3), 1-month (Level 3)
Spatial resolution 5km (Pixel number: 2401, Line number: 2401)
1km Japan* (Pixel number: 2701, Line number: 2601)
*Rectangular area: 24N-50N, 123E-150E
Data Water-leaving reflectance of band 01~03, chlorophyll-a concentration, absorption coefficient of phytoplankton+cdom+detritus, absorption coefficient of particles, Aerosol optical thickness of band 2, Aerosol angstrom exponent

Wild Fire

File typecsv (format: Level 2 | Level 3)
Wild Fire
Latest versionVersion Beta
Observation areaFull-disk
Temporal resolution10-minute (Level 2), 1-hour (Level 3), 1-day (Level 3), 1-month (Level 3)
Spatial resolution 2km
Notice This product is a beta version and is intended to show the preliminary result from Himawari-8. Users should keep in mind that the data is NOT quality assured.

Model Products

README

Aerosol Property by MRI/JMA

File typeNetCDF
Aerosol Optical Thickness
Latest versionVersion Beta
AreaGlobal
Temporal resolution1-hour (Level 4)
Spatial resolution Longitude 0.375 deg., Latitude 0.37147 to 0.37461 deg. (Gaussian)
(Pixel number: 960, Line number: 480)
Data Aerosol optical thickness at 550 nm (Sulfate, BC, Organic Aerosol, Sea Salt, Dust), PM2.5 surface conc., PM10 surface conc.
Notice This product is a beta version and is intended to show the preliminary result from Himawari-8. Users should keep in mind that the data is NOT quality assured.
Note This product is the forecast (every one hour) of aerosol properties by the MRI/JMA global aerosol model called Model of Aerosol Species IN the Global AtmospheRe (MASINGAR). This product is assimilated by Himawari L3 aerosol optical depth at 00, 03, 06, and 09UTC. The opposite side of the Himawari observation area is assimilated at 12 and 18UTC using MODIS/Terra+Aqua L3 Value-added Aerosol Optical Depth - NRT dataset due to lack of aerosol retrievals by Himawari. (As for the image on the top page, there are cases where preliminary forecast is displayed that was derived by assimilating observation data before the previous day.) Please refer to the reference below for the assimilation method etc. The aerosol data assimilation system based on MASINGER was developed by Meteorological Research Institute and Kyushu University. The products are produced at Meteorological Research Institute, and provided by JAXA P-Tree System, Japan Aerospace Exploration Agency (JAXA).
Acknowledgements MODIS/Terra+Aqua L3 Value-added Aerosol Optical Depth - NRT datasets were acquired from the Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC), located in the Goddard Space Flight Center in Greenbelt, Maryland (https://ladsweb.nascom.nasa.gov/).


Sea Surface Temperature (JAXA,JAMSTEC)

File typeNetCDF
Sea Surface Temperature
(Left: Observation by Himawari, Right: Model assimilation)

There is no missing area in the simulated ocean and we are able to forecast a state of ocean.
Latest versionv20180705
AreaAround Japan
(117E-150E, 17N-50N)
Temporal resolution1-hour (Level 4)
Spatial resolution About 3km (1/36 deg.)
(Pixel number: 1190, Line number: 1190)
Data Sea Surface Temperature
Note This product is constructed by data assimilation using high resolution regional ocean model "JCOPE-T" developed by JAMSTEC and observation data including the 4 types satellite SST data provided by JAXA. When we do the data assimilation, we do the bias correction of satellite SST data using GCOM-W/AMSR2 SST data as refer to reference value, because the bias in observation data is undesirable for data assimilation. Near Real-Time data (analysis and forecast) and Best Estimate data are included in this product. Update frequency and period are follow.
Near Real-Time data: Every day except Saturdays.
- Analysis (ANAL): 5-days (replaced every update)
- Forecast (FCST): 16-days (replaced every update)
Best Estimate data: Every week
 (update in the beginning of the week; Sunday or Monday)
- This is delay mode data which is provided about two weeks late.
- 7-days data are added every update.

This research is JAXA-JAMSTEC joint research and a part of the Japan Coastal Ocean Predictability Experiment (JCOPE).

2. Links

3. Reporting requirement

Please specify the following sentence when you publish a thesis, a report, and so on by using the research products and images supplied by the Service.

"'Research product of XXX (produced from Himawari-8) that was used in this paper' was supplied by the P-Tree System, Japan Aerospace Exploration Agency (JAXA)."

Please specify the following sentence when you publish a thesis, a report, and so on by using model product supplied by the Service.

For Aerosol model:
"Aerosol model product that was used in this paper was developed by Meteorological Research Institute and Kyushu University, and supplied by the P-Tree System, Japan Aerospace Exploration Agency (JAXA)."

For Sea Surface Temperature model:
"Sea Surface Temperature model product that was used in this paper was developed by Japan Agency for Marine-earth Science and Technology (JAMSTEC), and supplied by the P-Tree System, Japan Aerospace Exploration Agency (JAXA)."

If you are writing a document (including papers and thesis), please refer to the algorithm papers of the product you are using, which is listed in the following section "6. References".

4. FAQ

For frequently asked questions, please refer FAQ page.

5. Contact Information

If there are any concerns or questions about the Service, please contact us at the following:

following: JAXA/EORC P-Tree secretariat
Location: Japan Aerospace Exploration Agency (JAXA)
Space Technology Directorate I, Earth Observation Research Center (EORC)
2-1-1 Sengen, Tsukuba, Ibaraki, 305-8505
E-mail:

6. Documents

7. References

  • About Himawari-8 satellite and instrument:

    K. Bessho et al., 2016: An introduction to Himawari-8/9 - Japan's new-generation geostationary meteorological satellites, J. Meteorol. Soc. Japan, 94, doi:10.2151/jmsj.2016-009.
    https://www.jstage.jst.go.jp/article/jmsj/94/2/94_2016-009/_article

  • About Sea Surface Temperature algorithm:

    Y. Kurihara, H. Murakami, and M. Kachi, 2016: Sea surface temperature from the new Japanese geostationary meteorological Himawari-8 satellite. Geophys. Res. Letters. DOI: 10.1002/2015GL067159.
    http://onlinelibrary.wiley.com/doi/10.1002/2015GL067159/full

  • About Sea Surface Temperature model:

    (Ocean model)
    Varlamov, S. M., X. Guo, T. Miyama, K. Ichikawa, T. Waseda, and Y. Miyazawa, 2015: M2 baroclinic tide variability modulated by the ocean circulation south of Japan, J. Geophys. Res. Oceans, 120, 3681-3710. DOI:10.1002/2015JC010739.
    https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2015JC010739.

    (Data assimilation method)
    Miyazawa, Y., S. M. Varlamov, T. Miyama, X. Guo, T. Hihara, K. Kiyomatsu, M. Kachi, Y. Kurihara, H. Murakami, Assimilation of high-resolution sea surface temperature data into an operational nowcast/forecast system around Japan using a multi-scale three-dimensional variational scheme, Ocean Dyn., 67, 713-728. DOI: 10.1007/s10236-017-1056-1.
    https://link.springer.com/article/10.1007/s10236-017-1056-1.

  • About Aerosol algorithm:

    (L2 Aerosol Algorithm)
    Yoshida, M, M. Kikuchi, T. M. Nagao, H. Murakami, T. Nomaki, and A. Higurashi, 2018: Common retrieval of aerosol properties for imaging satellite sensors, J. Meteor. Soc. Japan, doi:10.2151/jmsj.2018-039.
    https://www.jstage.jst.go.jp/article/jmsj/advpub/0/advpub_2018-039/_article/-char/en.

    (L3 Hourly Aerosol Algorithm)
    Kikuchi, M., H. Murakami, K. Suzuki, T. M. Nagao, and A. Higurashi, Improved Hourly Estimates of Aerosol Optical Thickness using Spatiotemporal Variability Derived from Himawari-8 Geostationary Satellite, IEEE Transactions on Geoscience and Remote Sensing, accepted.
    https://ieeexplore.ieee.org/document/8334203/.

  • About Aerosol model:

    (assimilation method)
    Yumimoto, K., Tanaka, T. Y., Oshima, N., and Maki, T, 2017: JRAero: the Japanese Reanalysis for Aerosol v1.0, Geosci. Model Dev., 10, 3225-3253
    https://doi.org/10.5194/gmd-10-3225-2017.

    (assimilation with Himawari-8 Aerosol optical properties)
    Yumimoto, K., T. Y. Tanaka, M. Yoshida, M. Kikuchi, T. M. Nagao, H. Murakami, and T. Maki, 2018: Assimilation and forecasting experiment for heavy Siberian wildfire smoke in May 2016 with Himawari-8 aerosol optical thickness. J. Meteor. Soc. Japan, 96B
    http://jmsj.metsoc.jp/GA/JMSJ2018-035.html.

    (quotation for MODIS assimilation)
    MODIS/Terra+Aqua Near Real Time value-added Aerosol Optical Depth Product, 6.1NRT, L2 Swath 1 km and 5 km, C6, NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC), Goddard Space Flight Center, Greenbelt, MD.
    http://dx.doi.org/10.5067/MODIS/MCDAODHD.NRT.061.

  • About Short Wave Radiation / Photosynthetically Available Radiation algorithm:

    R. Frouin and H. Murakami, 2007: Estimating photosynthetically available radiation at the ocean surface from ADEOS-II global imager data. J. Oceanography, 63, 493-503.

  • About Chlorophyll-a algorithm:

    Murakami, H. (2016): Ocean color estimation by Himawari-8/AHI, Proc. SPIE 9878, Remote Sensing of the Oceans and Inland Waters: Techniques, Applications, and Challenges, 987810 (May 7, 2016); doi:10.1117/12.2225422;
    http://dx.doi.org/10.1117/12.2225422.

  • About Cloud Retrieval Algorithm
    (Cloud Flag Algorithm)

    Ishida, H., and T. Y. Nakajima, 2009: Development of an unbiased cloud detection algorithm for a spaceborne multispectral imager, J. Geophys. Res., 114, D07206, doi:10.1029/2008JD010710.

    Ishida, H., T. Y. Nakajima, T. Yokota, N. Kikuchi, and H. Watanabe, 2011: Investigation of GOSAT TANSO-CAI cloud screening ability through an inter-satellite comparison, J. Appl. Meteor. Climatol., 50, 1571?1586. doi: http://dx.doi.org/10.1175/2011JAMC2672.1.

    Letu, H., T. M. Nagao, T. Y. Nakajima, and Y. Matsumae, 2014: Method for validating cloud mask obtained from satellite measurements using ground-based sky camera. Applied optics, 53(31), 7523-7533.

    Nakajima, T. Y., T. Tsuchiya, H. Ishida, and H. Shimoda, 2011: Cloud detection performance of spaceborne visible-to-infrared multispectral imagers. Applied Optics, 50, 2601-2616.

    (Cloud Retrieval Algorithm)

    Kawamoto, K., T. Nakajima, and T. Y. Nakajima, 2001: A Global Determination of Cloud Microphysics with AVHRR Remote Sensing, J. Clim., 14(9), 2054?2068, doi:10.1175/1520-0442(2001)014<2054:AGDOCM>2.0.CO;2.

    Nakajima, T. Y., and T. Nakajima, 1995: Wide-Area Determination of Cloud Microphysical Properties from NOAA AVHRR Measurements for FIRE and ASTEX Regions, J. Atmos. Sci., 52(23), 4043?4059, doi:10.1175/1520-0469(1995)052<4043:WADOCM>2.0.CO;2.

    (Scattering property database for nonspherical ice particles)

    Ishimoto, H., K. Masuda., Y. Mano, N. Orikasa, and A. Uchiyama, 2012a, Optical modeling of irregularly shaped ice particles in convective cirrus. In radiation processed in the atmosphere and ocean (IRS2012): Proceedings of the International Radiation Symposium (IRC/IAMAS) 1531, 184-187.

    Ishimoto, H., K. Masuda, Y. Mano, N. Orikasa, and A. Uchiyama, 2012b: Irregularly shaped ice aggregates in optical modeling of convectively generated ice clouds, J. Quant. Spectrosc. Radiat. Transfer, 113, 632?643.

    Masuda, K., H. Ishimoto, and Y. Mano, 2012: Efficient method of computing a geometric optics integral for light scattering, Meteorology and Geophysics ., 63, 15?19.

    Letu, H., T. Y. Nakajima, and T. N. Matsui, 2012: Development of an ice crystal scattering database for the global change observation mission/second generation global imager satellite mission: Investigating the refractive index grid system and potential retrieval error. Appl. Opt., 51, 6172-6178.

    Letu, H. H. Ishimoto, J. Riedi, T. Y. Nakajima, L. C.-Labonnote, A. J. Baran, T. M. Nagao, and M. Sekiguchi, 2016: Investigation of ice particle habits to be used for ice cloud remote sensing for the GCOM-C satellite mission. Atmos. Chem. Phys, 16(18), 12287-12303.

    Letu, H., T. M. Nagao, T. Y. Nakajima J. Riedi, H. Ishimoto, A. J. Baran, H. Shang, M. Sekiguchi, and M. Kikuchi: Ice cloud properties from Himawari-8/AHI next-generation geostationary satellite: Capability of the AHI to monitor the DC cloud generation process. IEEE Transactions on Geoscience and Remote Sensing, in revision.

  • Radiative Transfer Code

    Nakajima, T., and M. Tanaka (1986), Matrix formulation for the transfer of solar radiation in a plane-parallel scattering atmosphere, J. Quant. Spectrosc. Radiat. Transfer, 35, 13?21, doi:10.1016/0022-4073(86)90088-9.

    Nakajima, T., and M. Tanaka (1988), Algorithms for radiative intensity calculations in moderately thick atmospheres using a truncation approximation, J. Quant. Spectrosc. Radiat. Transfer, 40, 51?69, doi:10.1016/0022-4073(88)90031-3.

    Ota, Y., A. Higurashi, T. Nakajima, and T. Yokota (2009), Matrix formulations of radiative transfer including the polarization effect in a coupled atmosphere-ocean system, J. Quant. Spectrosc. Radiat. Transfer, 111, 878?894, doi:10.1016/j.jqsrt.2009.11.021.

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