239 Evaluation of Inter-Sensor Biases between SNPP/ATMS and POES/AMSU-A

Monday, 8 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
Cheng-Zhi Zou, NESDIS, College Park, MD

The Advanced Technology Microwave Sounder (ATMS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite mission is a new generation of microwave sounder designed to measure the atmospheric temperature and moisture profiles for numerical weather prediction. The ATMS will also be equipped on the NOAA next generation of operational weather satellite series—the Joint Polar Satellite System (JPSS), potentially providing atmospheric temperature and moisture observations for the next two decades. The potentially long-time observations from the SNPP and JPSS ATMS have important climate implication-- it can be merged with its predecessor, the Advanced Microwave Sounding Unit (AMSU-A), to form a long-term climate data record for climate change monitoring and investigation.

Before the merging, it is critically important to understand the inter-sensor biases between the two different instruments. The SNPP was launched on October 2011, having nearly 6 years of overlaps at 2017 with the current operational POES satellites. This overlap provides an opportunity to evaluate the inter-sensor biases between ATMS and AMSU-A for future climate applications. We use the recalibrated/inter-calibrated AMSU-A observations for this evaluation. The recalibrated AMSU-A data was based on an Integrated Microwave Inter-calibration Approach (IMICA), which removed or minimized time-varying inter-satellites biases, resulting in inter-satellite biases to be on the order of 0.1K. As a result, the recalibrated AMSU-A data can serve as a reference. The ATMS data may be compared with AMSU-A on any satellites within the recalibrated satellite constellation and the comparison results will be basically same. By comparing ATMS with AMSU-A data on multiple POES satellites, potential issues in the ATMS, if ever exiting, may be revealed.

In this study, we present and analyze the ATMS-AMSU-A comparison results. We will mainly analyze the oxygen channels from ATMS channels 5 to 15. Difference time series in global means as well as in simultaneous nadir overpasses (SNOs) are both analyzed to achieve the best judgment on the bias nature between the two instruments. Global inter-sensor bias patterns will also be analyzed to understand the diurnal influence on the biases. We found that ATMS performs very well in terms of stability. But calibration change was identified and confirmed which caused large bias jumps starting from March 2017. Conclusion and recommendation for future directions will be made based on the results.

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