6. Conclusions

In this study, we summarized research studies for quantifying global water vapor variation estimated using measurements from active GPS RO sensors and passive infrared and microwave sounders. A new inversion algorithm by inverting the GPS RO observations collocated with the NASA Aqua AIRS measurements to retrieve enhanced temperature and water vapor profiles is introduced. This effort is meant to generate improved temperature and moisture profiles, which are not possible by each individual sensors at the locations and times for the RO-AIRS collocated pairs. In addition, we also introduce a new approach for retrieving RO data with collocated MW measurements. By including the RO refractivity forward operator into the currently available MiRS package, we are able to provide the improved temperature and moisture profile in the troposphere.

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In the combined RO and AIRS retrieval (for simulation experiments), the high vertical resolution RO retrieved temperature profiles are able to help to resolve the sharp temperature inversion layer in the UT/LS (i.e., the tropopause) and constrain AIRS water vapor retrieval in the same altitude. Because RO data are also very sensitive to water vapor variation in the moisture rich troposphere, the RO data shall also help to provide extra water vapor information for the combined AIRS and RO retrievals in the lower troposphere. It is demonstrated that the combined AIRS and RO observations act to constrain the individual solutions, the significantly improved water vapor RMSE is found in both the middle and lower troposphere. The RMSEs of water vapor mixing ratio for AIRS and GPS RO improved from 1.5 and 1.0 g/kg at surface, respectively, to 0.5 g/kg for the GPS RO combined AIRS retrievals. Since GPS refractivity is less sensitive to temperature in the troposphere, only small temperature RMSE improvements are found. Similar results are found in the COSMIC, ATMS, and ATMS+COSMIC retrieval results.

In future, we will apply AIRS and COSMIC data from 2006 to 2016 to the derived physical inversion algorithm and validate the retrieval results against in situ data. COSMIC's success has also prompted U.S. agencies to move forward with a follow-on FORMOSAT-7/COSMIC-2 (hereafter COSMIC-2) RO mission with Taiwan. The mission will launch six satellites into low-inclination orbits in early 2018 which is expected to yield up to 6000 uniformly distributed RO profiles per day. This would allow numerous RO and AMSU/ATMS coincident pairs after 2018, which would provide unprecedented atmospheric thermal and hydrometer information below clouds under various atmospheric conditions, which was not possible before.
