Methodology development for calibration assessment using quasi-deep convective clouds with application to Aqua MODIS...

Area of Science:

• Satellite remote sensing
• Atmospheric science
• Instrument calibration

Background:

• Deep convective clouds (DCC) are crucial for calibrating satellite sensors, particularly thermal emissive bands (TEB).
• Daytime DCC measurements are affected by solar radiance, limiting their use for midwave infrared (MWIR) band calibration.
• Existing DCC calibration methods require refinement to address measurement fluctuations and asymmetrical distributions.

Purpose of the Study:

• To develop and validate a new calibration assessment technique for MWIR bands using quasi-DCC (qDCC).
• To improve the accuracy of DCC-based calibration by implementing a normalization method for TEB.
• To evaluate the calibration performance of Aqua MODIS instruments using the refined DCC techniques.

Main Methods:

• Utilizing brightness temperature (BT) and visible reflectance thresholds to identify DCC.
• Developing a qDCC technique for MWIR band calibration assessment.
• Implementing a DCC normalization method using an empirical model to address BT fluctuations and asymmetrical distributions.

Main Results:

• The qDCC technique demonstrates feasibility for MWIR band calibration assessment.
• DCC normalization results in symmetrical and Gaussian-like BT distributions for TEB.
• Calibration stability, noise performance, and consistency of Aqua MODIS TEB are evaluated.
• The formatter reset effect on Aqua MODIS calibration offset bias is analyzed.

Conclusions:

• The qDCC technique provides a viable method for MWIR band calibration assessment.
• DCC normalization significantly improves the accuracy and reliability of TEB calibration assessments.
• The study provides insights into Aqua MODIS calibration performance and proposes corrections for future improvements.