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GK-2A Visible Calibration

The meteorological instrument MI(Meteorological Imager) of GK-2A has one visible channel of the center wavelength at 0.675㎛ with 1km spatial resolution.

GK-2A visible calibratio
Channels Wavelength Spatial
Visible 0.67 1Km Weekly cloud images, Asian dust, forest fires, fog observation, atmospheric motion vector

※ The GK-2A MI channel characteristic

No on-board calibration

There is no on-board calibration target for GK-2A MI visible channel such as solar diffuser. Thus, ground calibration is needed for calibration and monitoring of visible channel degradation with time. However, in infrared channels, the on-board calibration is conducted from blackbody.

Ground calibration

NMSC has vicarious calibration system for visible channel. Vicarious calibration is the method using the corresponded theoretical reflectances with the observation point and time. In the calibration system, the theoretical reflectances for four targets: ocean, desert, water cloud(WC) and deep convective cloud(DCC) are simulated and utilized as reference values.


NMSC performs the vicarious calibration by using ocean, desert, WC and DCC. These algorithms are based on the development of meteorological data processing system for communication, ocean and meteorological satellite ATBD.

NMSC choose the four targets, whose properties are well-known for calculating TOA(Top-Of-Atmosphere) reflectance, for having uniformly distributed reflectances between 0 and 1. And NMSC selected the suitable models for each target to improve calibration accuracy.

The thresholds of each target and the models are followings :

The thresholds of each target and the models are followings
Targets Applications
Ocean Thresholds of Target
  • ㆍNo Cloud
  • ㆍNo sun-glint
  • ㆍAerosol Optical Thickness < 0.1
  • ㆍWind speed < 7m/s
Model 6S
Desert Thresholds of Target
  • ㆍ11 fixed targets of Simpson desert in Australia
Model 6S
Water Cloud Thresholds of Target
  • ㆍCloud Optical Thickness ≥ 5
  • ㆍCloud Top Temperature ≥ 273K or ≤ 227 K
DCC Thresholds of Target
  • ㆍTB10.8≤ 190K
    • where TB10.8: Brightness Temp. at 10.8㎛ band
  • ㆍHomogeneity checks
    • - STD(TB10.8) ≤ 1K
    • - STD(R0.6)/Mean(R0.6) ≤ 0.03
    • where R0.6: Visible reflectance

※ 6S : Second Simulation of the Satellite Signal in the Solar Spectrum
   SBDART : Santa Barbara DISORT Atmospheric Radiative Transfer

The characteristics of each target are followings:


The ocean targets are usually homogeneous and dark but should be considered only a clear pixel without a cloud for sensor calibration. The reflectance of ocean is affected by aerosol, because the surface reflectance is so small. Therefore, AOT(Aerosol Optical Thickness) has to be considered as an ancillary data in radiative transfer modeling. In addition, it has the advantage that radiance can be calculated without BRDF (bidirectional reflectance distribution function) because the surface reflectance of the ocean is nearly homogeneous.


KMA conducted desert calibration for 11 fixed desert targets among Simpson Desert in Australia. There is no need to use AOT as ancillary data from other satellites, because of the low effect of aerosol by high surface reflectivity of desert. However, accurate surface BRDF needs to be used for model input, since the variation of surface BRDF is low with time. The surface BRDF can be updated with longer period than other targets.

Water Cloud

The atmosphere and surface effects can be minimized in the simulation of TOA radiance over the WC targets due to strong reflection of cloud layer. According to the actual test for WC reflectances sensitivity, TOA reflectance is more dependent on cloud optical properties than surface and atmospheric effects. In addition, the reflectance is more sensitive with cloud optical thickness(COT) than particle sizes of cloud since the absorption rate of visible rays into cloud particle is low. Thus, the cloud optical properties are necessary as the model input for more accurate result.


DCC target has the largest reflectance among the targets: ocean, desert, WC and DCC. The vertical distribution of DCCs is assumed from 1km to 15km. COT and particle size of the DCC are assumed to be 200 and 20µm, respectively. The pixel of which the brightness temperature (TB) of IR1(10.8µm) is less than 190K are selected as DCCs for calibration.


NMSC provides the three types of outcomes in this web page. There are the two time series of regression coefficients and ratios for each target, and the one scatter plot.

Regression coefficients between the observed and simulated reflectances

The time series of regression slopes(C1) and intercepts(C0) are computed between the observed and simulated reflectances. The C1 and C0 in the web page represent the 30days moving averaged values.

Reflectance(Observed)= C1 * Reflectance(Simulated) + C0

Ratios of the observed reflectance to simulated reflectance for each target

The time series of ratios of the observed reflectance to simulated reflectance represents the 30days moving averaged value.


Scatter plot between observed and simulated reflectance

The comparison of reflectance between observation and simulation is provided in the scatter plot with the regression line.


KMA, 2009: Development of Meteorological Data Processing System for Communication, Ocean and Meteorological Satellite(ATBD).

Chun, H. W., & Sohn, B. J., 2006: Calibration for the solar channel using MODIS-derived BRDF parameters over Australian desert targets. Target, 4(6), 8.

Ham S. H. 2006: Improvement of cloud's spectral reflection simulation using MODIS cloud products. 12th Conference on Atmospheric Radiation.

Sohn, B-J., Seung-Hee Ham, Ping Yang, 2009: Possibility of the Visible-Channel Calibration Using Deep Convective Clouds Overshooting the TTL. J. Appl. Meteor. Climatol., 48, 2271-2283.