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Developing Algorithms to Merge SSU and AMSU Observations for Generation of Stratospheric Temperature Climate Data Record From 1979 to Present

Principal Investigator: Cheng-Zhi Zou

Global mean anomaly time series for the three SSU channels and their AMSU-A equivalents after applying the merging algorithms

Click to enlarge - Global mean anomaly time series for the three SSU channels and their AMSU-A equivalents after applying the merging algorithms. The blue lines in the inserted boxes are the difference time series between SSU channels and their AMSU-A equivalents derived from the merging algorithms during their overlapping observations.

The stratospheric temperature trends are one of the central indicators for anthropogenic global warming. Observations from the Stratospheric Sounding Unit (SSU) onboard NOAA historical polar orbiting satellites have been playing a vital role in detecting the long-term trends and variability in the middle and upper stratospheric temperatures during 1979-2006. The SSU successor is the Advanced Microwave Sounding Unit-A (AMSU-A) starting from 1998 until present. It is desirable to merge the two observations together to extend the SSU data record to provide continued monitoring of changes in the stratospheric temperatures from 1979 to present. Unfortunately, the two observations came from different atmospheric layers with the SSU weighting functions covering atmospheric layers much thicker than those of the AMSU-A channels. In addition, the SSU weighting function varies with time and locations, posing a challenge to merge with AMSU-A with accuracy high enough for development of climate-quality data record.

In FY2015, STAR scientists developed a novel variational approach for the SSU and AMSU-A merging, accounting for matching in both of their temperatures and weighting functions. The approach solves for time- and latitudinal-dependent merging coefficients from a variational equation specifically designed for this problem, and it yielded zero mean inter- satellite biases with small standard deviation and negligible bias drift over time between SSU and its derived AMSU-A equivalent during their overlapping period (see Figure below). The solution satisfies the necessary condition for the merged time series to reliably detect long- term climate trend. Meanwhile, their weighting functions were matched with reasonably good accuracy, ensuring the merging is physically sound.

The global mean temperature trends during 1979-2015 derived from the merged time series were -0.64, -0.69, -0.77 K/Dec, respectively, for the three extended SSU channels, representing layer mean temperatures of the mid-stratosphere, upper-stratosphere, and top-stratosphere. This cooling effect is consistent with predictions from the anthropogenic global warming theories that both increases of carbon dioxide (and other greenhouse gases) and ozone depletion will cause a cooling response in the stratospheric temperatures. The merged observations were also compared with climate model simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP-5). Excellent agreement was found for global as well as latitudinal mean trends.

In conclusion, the extended SSU time series was demonstrated to be a credible dataset in monitoring changes in the stratospheric temperatures and verifying climate model simulations of the anthropogenic global warming effect.

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