LAUSR

Abstract. A technique that utilizes quasi-deep convective clouds (qDCC) for the calibration assessment of the thermal emissive bands (TEB) on remote sensing instruments has been proven viable. The Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Suomi-National Polar-orbiting Partnership (S-NPP) and NOAA-20 (N20) Visible Infrared Imaging Radiometer Suite (VIIRS) TEB calibration uses a nonlinear algorithm with nonlinear coefficients that rely on on-orbit blackbody (BB) warm-up and cool-down operations for updates. However, a limited BB temperature range affects the calibration’s accuracy, particularly for cold scenes. The deep convective clouds (DCC) core, one of the coldest Earth scenes, is suitable for MODIS calibration assessments, more specifically, for the evaluation of the offset term’s effect in its TEB quadratic calibration function. Moreover, nighttime qDCC measurements provide the advantage of removing solar reflectance effects during daytime, thus enhancing the assessment’s accuracy for the mid-wave infrared TEB. This qDCC method is applied to the Terra MODIS and VIIRS TEB, and their stabilities are assessed using long-term qDCC trending measurements over the instruments’ missions. The measurements from bands with an 11-μm wavelength are used to identify the DCC pixels. The 11-μm bands, MODIS band 31, and VIIRS bands M15 and I5 are stable throughout the MODIS and VIIRS missions and have shown excellent calibration accuracy and noise performance. Hence, using these bands as references, a normalization method is employed to enhance the accuracy of the stability and consistency assessments. The S-NPP VIIRS TEB show stable trends over the instrument’s mission. The S-NPP-to-N20 VIIRS comparison shows that their TEB measurements are consistent over qDCC. The Terra MODIS TEB also shows stable performance—except for bands 27, 29, and 30. Terra MODIS band 30 shows a large downward trend throughout the mission, whereas bands 27 and 29 show slight, upward drifts. Finally, a calibration correction using qDCC assessments is discussed and intended to be used in a future calibration algorithm collection.