Special Sensor Microwave Imager/Sounder Updates for the Global Precipitation Measurement V07 Data Suite

Observations from the Special Sensor Microwave Imager/Sounder (SSMIS) onboard the Defense Meteorological Satellite Program F16, F17, F18, and F19 spacecrafts provide a significant portion of the microwave radiometer data within the Global Precipitation Measurement (GPM) mission constellation. In preparation for the GPM Version 7 (V07) data release, SSMIS corrections developed over a decade ago and incorporated in GPM Version 5 (V05) are reexamined and updated. The calibration updates presented here include pointing parameters affecting geolocation and viewing geometry, along-scan bias adjustments to account for scan edge falloffs and sun angle corrections to account for heating anomalies including an emissive reflector. To address errors in the V05 geolocation, the sensor roll, pitch, yaw, half cone angle, and timing offsets are reanalyzed and updated. The along-scan bias adjustment is updated in a manner consistent with recent Special Sensor Microwave Imager updates to account for variations in scene temperature. Finally, significant improvements to the SSMIS sun angle correction are made by using data from the entire mission, extending the corrections to include the higher frequency channels, and deriving a more consistent channel-to-channel correction. From V05 to V07, the geolocation adjustment is approximately 5-10 km, the earth incidence angle difference is 0-0.4 degrees, and the average brightness temperature change is 0-2 K, but individual pixels may be up to several kelvin difference depending on sensor and channel. The result of these updates is a significant improvement in the quality and long-term consistency of the SSMIS data that are included in the GPM V07 dataset.

Automated summary

This article presents the reexamination and update of SSMIS data from the Defense Meteorological Satellite Program. The updates include calibration parameters, along-scan bias adjustments, and sun angle corrections, resulting in improved quality and consistency of the SSMIS data.