Arata Okuyama

Intercalibration of Advanced Microwave Scanning Radiometer-2 (AMSR2) Brightness Temperature

Here, we describe the characteristics of brightness temperature (Tb) measured by the Advanced Microwave Scanning Radiometer-2 (AMSR2) onboard the Global Change Observation Mission 1st-Water (GCOM-W1). This mission aims to achieve long-term global monitoring of Earth using two polar-orbiting satellite observation systems with three consecutive generations. GCOM-W1, the first satellite of the GCOM-W (Water) series, was launched successfully on May 18, 2012. AMSR2 is a single-mission instrument onboard the GCOM-W1 satellite. The basic characteristics of AMSR2 are similar to those of its predecessor, AMSR-E; this allows the continuation of AMSR-E observations but with several improvements, including a larger main reflector (2.0-m diameter), additional channels at C-band frequency, an improved calibration system, and increased reliability imparted by the addition of a redundant momentum wheel. Since July 3, 2012, the instrument has functioned properly and has accumulated a data set of Tb measurements. During the initial calibration and validation period, Tb values are being evaluated and characterized according to various methodologies, including intercalibration between similar microwave radiometers [e.g., the Tropical Rainfall Measuring Mission Microwave Imager (TMI)] based on radiative transfer computations. The intercalibration results for the ocean area as the cold end and the rainforest area the as warm end demonstrate that Tb measured by AMSR2 exhibits no apparent seasonal variation, with a maximum calibration difference of approximately 5 K compared to TMI and AMSR-E. This calibration difference appears to depend on the Tb of the observed object.

Preliminary validation of Himawari-8/AHI navigation and calibration

The next-generation geostationary meteorological satellite of the Japan Meteorological Agency (JMA), Himawari-8, entered operation on 7 July 2015. Himawari-8 features the new 16-band Advanced Himawari Imager (AHI), whose spatial resolution and observation frequency are improved over those of its predecessor MTSAT-series satellites. These improvements will bring unprecedented levels of performance in nowcasting services and short-range weather forecasting systems. In view of the essential nature of navigation and radiometric calibration in fully leveraging the imager’s potential, this study reports on the current status of navigation and calibration for the AHI. Image navigation is accurate to within 1 km, and band-to-band co-registration has also been validated. Infrared-band calibration is accurate to within 0.2 K with no significant diurnal variation, and is being validated using an approach developed under the GSICS project. Validation approaches are currently being tested for the visible and near-infrared bands. In this study, two of such approaches were compared and found to produce largely consistent results.

MTSAT-1R Visible Imager Point Spread Correction Function, Part I: The Need for, Validation of, and Calibration With

The multifunctional transport satellite (MTSAT)-1R imager was launched in 2005 and is operated by the Japan Meteorological Agency (JMA). A nonlinear behavior in the MTSAT-1R visible sensor response is observed when the instrument is intercalibrated with coincident moderate resolution imaging spectroradiometer (MODIS) ray-matched radiances. Analysis reveals that the nonlinear behavior is not a result of imager navigation, sensor spectral response difference, nor scan pattern. Examination of coincident MTSAT-1R and MTSAT-2 images reveals that MTSAT-1R dark ocean radiances are affected by neighboring bright clouds, whereas large regions of dark ocean radiances are not impacted. Although the IR and visible optical paths are shared, the MTSAT-1R brightness temperatures are not affected. A dust contaminant coating the mirror, which only affects certain wavelengths, may be one explanation. To address the nonlinearity, a pixel point spread function (PSF) correction algorithm is implemented, wherein most of the radiance contribution is from the pixel field of view itself, as well as including a small contribution from all pixels within a radii of several hundred kilometers. The application of the PSF-corrected ~80% of the affected pixel radiances. After application, a near linear response is observed between the coincident MTSAT-1R and Aqua-MODIS ray-matched radiances, and the intercept is now near the predicted space count of zero. The monthly calibration gain noise is reduced by one-third when compared with the non-PSF-corrected gains. The monthly gains are the most erratic during the first two years of operation, and the MTSAT-1R visible sensor is degrading at ~1.9 % decade.

MTSAT-1R Visible Imager Point Spread Function Correction, Part II: Theory

An image processing methodology is presented to recover the quality of the Multifunctional Transport Satellite (MTSAT)-1R visible channel data affected by spatial crosstalk. The slight blurring of the visible optical path is attributed to an imperfection in the mirror surface caused either by flawed polishing or a dust contaminant. The methodology assumes that the dispersed portion of the signal is small and distributed randomly around the optical axis, which allows the image to be deconvolved using an inverted point spread function (PSF). The PSF is described by four parameters, which are solved using a maximum-likelihood estimator using coincident collocated MTSAT-2 images as truth. A subpixel image matching technique is used to align the MTSAT-2 pixels into the MTSAT-1R projection and to correct for navigation errors and cloud displacement due to the time and viewing geometry differences between the two satellite observations. An optimal set of the PSF parameters is derived by an iterative routine based on the 4-D Powells conjugate direction method that minimizes the difference between the PSF-corrected MTSAT-1R and the collocated MTSAT-2 images. The PSF parameters were found to be consistent over the 5 days of available daytime coincident and MTSAT-1R and MTSAT-2 images. After applying the PSF parameters, the visible sensor response is nearly linear, and the space count is close to zero. The overall linear regression standard error was reduced by 52%. Users can easily apply the PSF parameter coefficients to the MTSAT-1R imager pixel level counts to restore the original quality of the entire MTSAT-1R record.

Himawari-8/AHI latest performance of navigation and calibration

The new-generation Himawari-8 geostationary meteorological satellite of the Japan Meteorological Agency (JMA) started operation in July 2015 after the completion of in-orbit testing and checking of the overall system. Himawari-8 features the new Advanced Himawari Imager (AHI), which has 16 bands and double the spatial resolution of its MTSAT-series predecessor satellites [1]. Full-disk imagery is obtained every 10 minutes, and regional observation at 2.5-minute intervals is also conducted. These significant improvements are expected to bring unprecedented levels of performance in nowcasting services and short-range weather forecasting systems. To leverage the full potential of the advanced imager, high precision in navigation and radiometric calibration is essential. This is estimated in off-line processes such as pattern matching for navigation and the Global Space-based Inter-Calibration System (GSICS) for radiometric calibration. On 9 March 2016, JMA updated its ground processing system, including the image navigation and registration (INR) module, for further quality improvement. This update covered improvement of the band-to-band co-registration process for infrared bands, improvement of the resampling process, and implementation of a coherent noise reduction process. Results from the off-line processes showed that the update had improved Himawari Standard Data (HSD), which is Himawari-8/AHI L1B-equivalent data.

Development of 2D deconvolution method to repair blurred MTSAT-1R visible imagery

Spatial cross-talk has been discovered in the visible channel data of the Multi-functional Transport Satellite (MTSAT)-1R. The slight image blurring is attributed to an imperfection in the mirror surface caused either by flawed polishing or a dust contaminant. An image processing methodology is described that employs a two-dimensional deconvolution routine to recover the original undistorted MTSAT-1R data counts. The methodology assumes that the dispersed portion of the signal is small and distributed randomly around the optical axis, which allows the image blurring to be described by a point spread function (PSF) based on the Gaussian profile. The PSF is described by 4 parameters, which are solved using a maximum likelihood estimator using coincident collocated MTSAT-2 images as truth. A subpixel image matching technique is used to align the MTSAT-2 pixels into the MTSAT-1R projection and to correct for navigation errors and cloud displacement due to the time and viewing geometry differences between the two satellite observations. An optimal set of the PSF parameters is derived by an iterative routine based on the 4-dimensional Powell’s conjugate direction method that minimizes the difference between PSF-corrected MTSAT-1R and collocated MTSAT-2 images. This iterative approach is computationally intensive and was optimized analytically as well as by coding in assembly language incorporating parallel processing. The PSF parameters were found to be consistent over the 5-days of available daytime coincident MTSAT-1R and MTSAT-2 images, and can easily be applied to the MTSAT-1R imager pixel level counts to restore the original quality of the entire MTSAT-1R record.