The intercomparison of the reflective solar bands (RSB) between the instruments onboard a geostationary orbit satellite and a low Earth orbit satellite is very helpful in assessing their calibration consistency. Himawari-8 was launched on October 7, 2014, and Geostationary Operational Environmental Satellite (GOES)-R was launched on November 19, 2016. Unlike previous GOES instruments, the Advanced Himawari Imager (AHI) on Himawari-8 and the Advanced Baseline Imager (ABI) on GOES-R have onboard calibrators for the RSB. Independent assessment of calibration is nonetheless important to enhance their product quality. MODIS and visible infrared imager radiometer suite (VIIRS) can provide good references for sensor calibration. The intercomparison between AHI and VIIRS is performed over a pseudoinvariant target. The use of stable and uniform calibration sites provides comparison with accurate adjustment for band spectral difference, reduction of impact from pixel mismatching, and consistency of BRDF and atmospheric correction. The site used is the Strzelecki Desert in Australia. Due to the difference in solar and view angles, two corrections must be applied to compare the measurements. The first is the atmospheric scattering correction applied to the top of atmosphere reflectance measurements. The second correction is applied to correct the BRDF effect. The atmospheric correction is performed using a vector version of the Second Simulation of a Satellite Signal in the Solar Spectrum (6SV) model and the BRDF correction is performed using a semiempirical model. Our results show that AHI band 1 (0.47 μm) has a good agreement with VIIRS band M3 within 0.15%. AHI band 5 (1.61 μm) shows the largest difference (5.09%) with VIIRS band M10, whereas AHI band 5 shows the least difference (1.87%) in comparison with VIIRS band I3. The methods developed in this work can also be directly applied to assess GOES-16/ABI calibration consistency, a topic we will address in the future.
Signatures of electronic crosstalk contamination are clearly seen in Aqua MODIS Moon images from bands 20 to 30 (1.375 and 3.75 - 9.73 μm). Electronic crosstalk can potentially impact L1B products, causing image artifacts such as striping and radiometric bias, the severity of which will depend on the amount of signal leaked, how it compares to the flux levels in the receiving image, and on the ability of the calibration in absorbing the contamination. In this paper, we address two distinct manifestations of electronic crosstalk contamination seen in Aqua MODIS lunar images that we call the simple and complex ghosts. The simple ghosts appear in lunar images from bands 20 to 30, affect detector 1 only, and each ghost is caused by signal leak from one sending detector only. The complex ghosts form negative regions in Aqua MODIS lunar images from bands 27 to 30 and are caused by multiple sending detectors and bands. We map the crosstalk signatures back to their respective sending bands/detectors, by determining the displacement between the main lunar image and the crosstalk ghosts. We assume the contaminating signal is proportional to the signal of the sending band/detector and derive linear crosstalk coefficients for the simple ghosts in bands 20 to 26 and 28 to 30 and for the complex ghosts in band 29 for the entire mission. The linear crosstalk coefficients can then be applied in the correction of L1A Earth and calibration data that will generate corrected L1B images from which we can assess the impact the contamination has on the L1B product.
The modulation transfer function, or MTF, is a common measure of image fidelity, which has been historically characterized on-orbit using high contrast images of the lunar limb obtained by remote sensing instruments onboard both low-orbit and geostationary satellites. Himawari-8, launched in 2014, is a Japanese geostationary satellite that carries the Advanced Himawari Imager (AHI), a near-identical copy of the Advanced Baseline Imager (ABI) instrument onboard the GOES-16 satellite. In this paper, we apply a variation of the slantededge method for deriving the MTF from lunar images, first verified by us on simulated test images, to the Himawari-8/AHI L1A and L1B data. The MTF is derived along the North/South and East/West directions separately. The AHI L1A images used in the characterization of the MTF are obtained from lunar observations routinely acquired for validating the radiometric calibration. The L1B data, which is spatially re-sampled, come from serendipitous lunar observations where the Moon appears close to the Earth’s disk. We developed and implemented an algorithm to identify such occurrences using the SPICE/Icy package to predict the times where the Moon is visible in the L1B imagery and demonstrate their use for MTF derivation.
MODIS onboard the Terra and Aqua satellites have operated since 1999 and 2002, respectively. The inter-comparison between their thermal emissive bands is a useful tool in assessing their calibration consistency and enhancing their product quality. Terra and Aqua MODIS has the same spectral bands and calibration algorithm. The comparison between them will be beneficial for instrument calibration. However, the comparison is hindered by the time difference of their measurements, since Terra is in the morning orbit and Aqua is in the afternoon orbit. GOES-16 was launched on November 19, 2016 and Himawari-8 was launched on October 7, 2014. The Advanced Baseline Imager (ABI) onboard GOES-16 and the Advanced Himawari Imager (AHI) onboard Himawari-8 are in the same class and have almost identical thermal spectral bands. Their comparison will be very useful for sensor calibration assessment. However, the comparison is challenged by the fact that they image different regions of the Earth. The sensors on GEO satellite and the sensors on LEO satellite may have matching bands with close spectral coverage. This work focuses on bridging the thermal band comparison between LEO-LEO sensors and between GEO-GEO sensors. The double difference method is applied to assess the BT measurements between the two MODIS instruments using the GOES imager as a bridge. The comparison between ABI and AHI can also be performed with bridging by either MODIS or VIIRS measurements. GOES-16 and Himawari-8 are both positioned over tropical ocean regions. Thus, the comparison with simultaneous nadir overpass can provide assessments for brightness temperature (BT) measurements over the ocean surface type. The comparison can also be extended to simultaneous off-nadir measurement over other types of targets that cover different BT range.
The inter-comparison of the reflective solar bands between the instruments onboard a geostationary orbit satellite and onboard a low Earth orbit satellite is very helpful to assess their calibration consistency. GOES-R was launched on November 19, 2016 and Himawari 8 was launched October 7, 2014. Unlike the previous GOES instruments, the Advanced Baseline Imager on GOES-16 (GOES-R became GOES-16 after November 29 when it reached orbit) and the Advanced Himawari Imager (AHI) on Himawari 8 have onboard calibrators for the reflective solar bands. The assessment of calibration is important for their product quality enhancement. MODIS and VIIRS, with their stringent calibration requirements and excellent on-orbit calibration performance, provide good references. The simultaneous nadir overpass (SNO) and ray-matching are widely used inter-comparison methods for reflective solar bands. In this work, the inter-comparisons are performed over a pseudo-invariant target. The use of stable and uniform calibration sites provides comparison with appropriate reflectance level, accurate adjustment for band spectral coverage difference, reduction of impact from pixel mismatching, and consistency of BRDF and atmospheric correction. The site in this work is a desert site in Australia (latitude -29.0 South; longitude 139.8 East). Due to the difference in solar and view angles, two corrections are applied to have comparable measurements. The first is the atmospheric scattering correction. The satellite sensor measurements are top of atmosphere reflectance. The scattering, especially Rayleigh scattering, should be removed allowing the ground reflectance to be derived. Secondly, the angle differences magnify the BRDF effect. The ground reflectance should be corrected to have comparable measurements. The atmospheric correction is performed using a vector version of the Second Simulation of a Satellite Signal in the Solar Spectrum modeling and BRDF correction is performed using a semi-empirical model. AHI band 1 (0.47μm) shows good matching with VIIRS band M3 with difference of 0.15%. AHI band 5 (1.69μm) shows largest difference in comparison with VIIRS M10.
MODerate-resolution Imaging Spectroradiometer (MODIS) has 36 bands. Among them, 16 thermal emissive bands covering a wavelength range from 3.8 to 14.4 μm. After 16 years on-orbit operation, the electronic crosstalk of a few Terra MODIS thermal emissive bands develop substantial issues which cause biases in the EV brightness temperature measurements and surface feature contamination. The crosstalk effects on band 27 with center wavelength at 6.7 μm and band 29 at 8.5 μm increased significantly in recent years, affecting downstream products such as water vapor and cloud mask. The crosstalk issue can be observed from nearly monthly scheduled lunar measurements, from which the crosstalk coefficients can be derived. Most of MODIS thermal bands are saturated at moon surface temperatures and the development of an alternative approach is very helpful for verification. In this work, a physical model was developed to assess the crosstalk impact on calibration as well as in Earth view brightness temperature retrieval. This model was applied to Terra MODIS band 29 empirically for correction of Earth brightness temperature measurements. In the model development, the detector nonlinear response is considered. The impacts of the electronic crosstalk are assessed in two steps. The first step consists of determining the impact on calibration using the on-board blackbody (BB). Due to the detector nonlinear response and large background signal, both linear and nonlinear coefficients are affected by the crosstalk from sending bands. The crosstalk impact on calibration coefficients was calculated. The second step is to calculate the effects on the Earth view brightness temperature retrieval. The effects include those from affected calibration coefficients and the contamination of Earth view measurements. This model links the measurement bias with crosstalk coefficients, detector nonlinearity, and the ratio of Earth measurements between the sending and receiving bands. The correction of the electronic crosstalk can be implemented empirically from the processed bias at different brightness temperature. The implementation can be done through two approaches. As routine calibration assessment for thermal infrared bands, the trending over select Earth scenes is processed for all the detectors in a band and the band averaged bias is derived for certain time. In this case, the correction of an affected band can be made using the regression of the model with band averaged bias and then corrections of detector differences are applied. The second approach requires the trending for individual detectors and the bias for each detector is used for regression with the model. A test using the first approach was made for Terra MODIS band 29 with the biases derived from long-term trending of sea surface temperature and Dome-C surface temperature.
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