Optimization of a Deep Convective Cloud Technique in Evaluating the Long-Term Radiometric Stability of MODIS Reflective Solar Bands

Abstract

MODIS reflective solar bands are calibrated on-orbit using a solar diffuser and near-monthly lunar observations. To monitor the performance and effectiveness of the on-orbit calibrations, pseudo-invariant targets such as deep convective clouds (DCCs), Libya-4, and Dome-C are used to track the long-term stability of MODIS Level 1B product. However, the current MODIS operational DCC technique (DCCT) simply uses the criteria set for the 0.65-µm band. We optimize several critical DCCT parameters including the 11-µm IR-band Brightness Temperature (BT11) threshold for DCC identification, DCC core size and uniformity to help locate DCCs at convection centers, data collection time interval, and probability distribution function (PDF) bin increment for each channel. The mode reflectances corresponding to the PDF peaks are utilized as the DCC reflectances. Results show that the BT11 threshold and time interval are most critical for the Short Wave Infrared (SWIR) bands. The Bidirectional Reflectance Distribution Function model is most effective in reducing the DCC anisotropy for the visible channels. The uniformity filters and PDF bin size have minimal impacts on the visible channels and a larger impact on the SWIR bands. The newly optimized DCCT will be used for future evaluation of MODIS on-orbit calibration by MODIS Characterization Support Team.

Comparing airborne and satellite retrievals of cloud optical thickness and particle effective radius using a spectral radiance ratio technique: two case studies for cirrus and deep convective clouds

“…It is essential to address all components of the measurement system, i.e., sensors and algorithms, along with the originally measured radiances and derived data products, and continue validation activities throughout the satellite lifetime (Larar et al, 2010). Radiance measurements above highly reflecting surfaces such as salt lake, desert, snow/ice (Wan, 2014), and clouds (Mu et al, 2017) are usually evaluated in order to monitor the long-term stability of the satellite sensors. An estimated uncertainty of about 1-5 % in the case of MODIS reflective solar bands (RSBs) was reported by Xiong et al (2003).…”

Geostationary Visible Imager Calibration for the CERES SYN1deg Edition 4 Product

“…The Met-10 DERM uncertainty combines of the Met-9 ATO-RM uncertainty of 0.68% (Figure 10a), the daily Met-9 DERM of 0.81% (Table 1) with Met-9-to-Met-10 desert SBAF of 0.1%, and Met-10 DERM trend SE of 0.56% (Figure 10b), respectively, for a total uncertainty of 1.2%. The DCC-mode uncertainty includes the Aqua-MODIS 5-year DCC-mode standard deviation, the MODIS to GEO DCC SBAF, a possible 1-K mismatch between the GEO and MODIS 205K BT, which translates to a reflectivity difference of 0.15% [56], and the DCC-mode monthly gain trend SE. The Met-10 DCC-mode uncertainty combines the Aqua-MODIS DCC-mode standard deviation for the GEO 0 • E position of 0.65% (Figure 7), the MODIS-to-Met-9 DCC SBAF of 0.1%, the 1-K BT mismatch uncertainty of 0.15%, and the Met-10 trend SE of 0.77% (Figure 10b), for a total uncertainty of 1.0%.…”

Methods of Earth-view-based calibration of the response versus scan angle of the MODIS reflective solar bands

“…Deep convective clouds (DCC) have proven to be a reliable target for monitoring sensor performance and may also be used to derive the on-orbit RVS. [13][14][15] In this paper, we review the history of RVS algorithms for Aqua and Terra MODIS instruments. We discuss the relative advantages of different methods of EV-based RVS calibration in an effort to develop an optimal strategy as MODIS calibration is forced to increasingly rely on Earth view targets.…”