Extending the Air-Sea Essential Climate Variables CDR with AMSR3 and MWI Microwave Radiances

Remote Sensing Systems (RSS) provides a global community of researchers and decision makers with inter-calibrated microwave radiances and Air-Sea Essential Climate Variable (AS-ECV) geophysical retrievals originating from passive spaceborne sensors. The geophysical retrievals include: sea-surface temperature, near-surface ocean wind speed and direction, columnar atmospheric water vapor, columnar cloud liquid water, and sea-surface rain rate. In total, RSS generates microwave radiance and AS-ECV data from 14 microwave radiometers that span a time period of 35+ years. Consistent calibration procedures and retrieval methods have been applied during the data processing to ensure these datasets are suitable for climate research. Geophysical retrievals from two new sensors will be added to the RSS data repository in the 2023 to 2024 timeframe: GOSAT-GW AMSR3 and WSF-M MWI. The addition of these two microwave sensors, with their excellent spatial and temporal coverage, will extend the microwave AS-ECV climate data record (CDR) by up to ten years. In this presentation, we will present the intercalibration framework for integrating AS-ECVs from AMSR3 and MWI into the current CDR.

Historically, the RSS Radiative Transfer Model (RTM) developed for the SSMI sensor was the primary standard for inter-calibrating passive microwave radiances ranging from 6 to 89 GHz. Now, the calibration is tied to GMI onboard GPM. GMI’s unique design enabled absolute calibration of its antenna temperatures and brightness temperatures using various known calibration parameters, including hot load and cold sky antenna temperature tie points, coefficients that describe the non-linearity between sensor counts and antenna temperatures, and cold space spillover. In this presentation, we will describe how the GMI radiances will be used to calibrate AMSR3 and MWI. GMI’s 65-degree inclined orbit is not sun-synchronous, and it allows tight collocation windows with other satellite sensors. This is particularly useful for calibrating AMSR3 and MWI day and night observations. For a set of collocations, a double difference method will be used to find the AMSR3 and MWI calibration parameters that best match the GMI absolutely-calibrated radiances. We will present the inter-calibration process in detail, including the optimization of calibration parameters, the AS-ECVs used in the RTM in order to correct for small differences between sensors, and cases where the sensor radiance channel is not present in GMI.