**1. Introduction**

Earth science and climate studies have made significant progress in the recent decades along with continual advances in remote sensing technologies. Progressing along improving imaging capability is the intersensor comparison methodology, a method of evaluating the performance of sensor data or associated retrievals by comparing against a reference sensor, which is also certain to be utilized in greater capacity in the coming era. For multispectral sensors, it can be argued that the two units of the MODerate-resolution Imaging Spectradiometer (MODIS) [1,2], in the Terra and Aqua satellites launched on 18 December 1999 and 4 May 2002, respectively, are the forerunners leading the era of the high-performance instruments and big data. The twin MODIS, with 36 bands covering the spectral range of 0.45 to 12.4 μm are now closing in on two prolific decades of data acquisition. However, it is not until the launch of the next major multispectral sensor—the Visible Imaging Infrared Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (SNPP) satellite on 28 October 2011 [3,4]—that the twin MODIS finally has a comparable counterpart to generate high precision intersensor comparison result. Numerous radiometric intercomparisons of the reflective solar bands (RSBs) of Aqua MODIS and SNPP VIIRS ensued [5–7] utilizing the simultaneous nadir overpasses (SNOs) approach [8–11]. These studies demonstrated the capability of the radiometric intercomparison at the 1-km spatial resolution regime to be typically few percent. A main goal of this paper is to show that the capability, under an improved analysis procedure, is at the level of 1% precision or better.

The coming era is certain to make intersensor comparison a tool of increasing importance as more high-performance multispectral sensors are continually being launched into operation. For example, the Ocean and Land Colour (OLCI) Instrument and its companion Sea and Land Surface Temperature Radiometer (SLSTR) housed in the Sentinel-3A satellite [12] are the recently launched polar-orbiting multispectral sensors, with approximately 300-m spatial resolution. The first follow-on of VIIRS built is one on the Joint Polar Satellite System-1 (JPSS-1) satellite [13], or J1 satellite (officially designated as NOAA-20 post launch), was launched on 18 November 2017. A total of four follow-on VIIRS—J1 to J4 VIIRS—for which the SNPP VIIRS serves as the precursor, are scheduled to span the next 20 years of operation. The technological advancement also extends to geostationary sensors, with Himawari-8 Advanced Himawari Imager (AHI) [14,15], GOES-R Advanced Baseline Imager (ABI) [16–18], and GOES-S ABI [18], all with 1-km spatial resolution, recently launched. More follow-on geostationary sensors are also in the plan of succession. The demand for assessing sensor data quality and to monitor radiometric performance will certainly increase.

The overall accuracy of radiometric data depends on many inputs, but the regularly carried out on-orbit radiometric calibration operation to characterize the changing performance of detectors is one of central importance. One main commonality among the four instruments considered here—Terra and Aqua MODIS, SNPP VIIRS, and Sentinel-3A OLCI—is a fully equipped onboard calibration suite for carrying out the regularly scheduled on-orbit calibration. They following a similar strategy, including using a specially made solar diffuser (SD) panel for RSB performance characterization. This built-in calibration capability is a mark of the new generation high-performance multispectral sensors and makes them valuable radiometric references for other sensors or any climate studies to inter- or cross-calibrate. Thus establishing radiometric consistency between any pair of such independently calibrated sensor will be beneficial, and intersensor comparison is a most proper tool for this purpose. In addition, intercalibration using any of these sensors as a radiometric reference requires also a reliable intersensor comparison methodology. While there are numerous approaches for post-launch radiometric evaluation, the current knowledge points to intersensor comparison as potentially the most precise approach.

However, there are many other factors impacting the overall accuracy of the sensor data and also intersensor comparison result beyond just band or detector performance. One of such, outside the capability of the standard on-orbit calibration, is the response-versus-scan angle (RVS) effect of the scan mirror that can add in a systematic angle-dependent bias along-scan. For example, in the MODIS Collection 6 release [19,20], the addition of the time-dependent RVS characterization is a key upgrade to the RSB calibration methodology to mitigate the RVS effect that is beyond the capability of the on-orbit calibration methodology. For SNPP VIIRS, the time-dependent RVS effect is not yet an issue, but its potential emergence remains a possibility. Various common issues also create challenges for intersensor comparison analysis. Angle- or scene-dependent effects associated with the scenes, including the biredirectional reflectance distribution factor (BRDF) of the SNO scenes, also introduce additional complications into intersensor comparison result. For removing various confounding effects associated with larger angles or viewing areas, Chu et al. [7] utilized a "nadir-only" framework of SNO analysis in an Aqua MODIS versus SNPP VIIRS study, that limits the viewing angle to the Earth scenes to near 0◦ degree by using a small-sized comparison area. This study adopts the same "nadir-only" approach specifically in the context of examining the capability of intercomparison in evaluating on-orbit RSB calibration performance, and furthermore uses multiyear comparison time series that incorporate all high-quality SNO events as a tool of evaluation.

This study further distinguishes between statistical and physical constraints. For example, statistical analyses subject all physical conditions such as cloudy scenes or those of various geolocational conditions under the same criteria. This analysis carefully avoids any premature applications of physical constraints, such as the removal of cloudy scenes that can unnecessarily remove legitimate and usable data. Because statistical and physical attributes do not necessarily correlate, physical constraints should be applied only for targeted purposes. Also, for keeping data and results clean for achieving unambiguous and precise analysis, this work does not adjust or correct of data. It is often customary to adjust result such as using the spectral band adjustment factors (SBAFs) to account for spectral differences, but this study does not presume these practices to be reliable at the 1% precision level—the aim here is to first establish a clean groundwork before these other issues can be further examined.

In summary, this work examines the capability of intercomparison in a "nadir-only" refinement of SNO analysis that isolates the on-orbit RSB calibration from other large area-associated issues for a multiyear evaluation using comparison time series. In particular, Aqua MODIS versus SNPP VIIRS is used as the main case study because of their longer history with many studies already established numerous important findings. One more relevant point is that an intercomparison is a relative evaluation that is conclusive only when the reference sensor has already been established as reliable. Additional information, such using product retrievals derived from sensor data or another sensor for cross-examination, is often required to draw stronger conclusions. In other words, a stable radiometric comparison result can be deceptive due to both sensors containing coincidentally similar error in calibration. Nevertheless, intercomparison is most valuable when result shows deviating features that signals problems such as incorrect implementation, inadequate calibration or instrument anomalies. The current high-performance multispectral sensors with good imaging capability already has the 1% interscomparison capability that can ascertain various radiometric deviations of few percent; however, other types of sensors such as hyperspectral or microwave are either with insufficient spatial resolution or have not been shown with applicable precise intercomparison.

The organization of this paper is as follows. Section 2 briefly describes the four instruments and some general issues of radiometric intercomparison. Section 3 shows the results of the examination of the intercomparison methodology, emphasizing SNPP VIIRS versus Aqua MODIS in the 1-km regime. Section 4 shows the result of the examination for four different regimes of intercomparison, from 375 m to 1 km. Section 5 demonstrates cross-comparisons using Aqua MODIS, Sentinel-3A OLCI, and SNPP VIIRS. Section 6 provides a general discussion of relevant issues. Section 7 provides a summary and conclusion.
