Student Seminar: Jing Feng
Cloud-assisted retrieval of stratospheric water vapor from nadir view satellite measurements
Water vapor in dry atmospheric environments is of great importance for weather and climate. For example, despite of its scarcity, stratospheric water vapor is an important atmospheric component that can greatly influence climate change, due to its radiative and chemical impacts. Recent studies suggest that stratospheric water vapor may have strong relations to surface climate change and stratospheric ozone loss, highlighting the need of improved monitoring of stratospheric water vapor. However, the retrieval of stratospheric water vapor is known to be challenging. Satellite nadir view radiance measurements usually do not have sufficient sensitivity to the low concentration of stratospheric water vapor while limb view measurements have large sampling footprints, making small scale water vapor hard to be detected.
This study tests the feasibility of retrieving the stratospheric water vapor in the presence of dense upper tropospheric clouds, which block the radiance emission and obscuration of the lower atmosphere for stratospheric retrieval. This investigation uses synthetic satellite radiance simulated from atmospheric profiles using a radiative transfer model, MODTRAN, and adopts a widely-used optimal estimation method [Rodgers 2000] that iteratively retrieve the stratospheric temperature and humidity.
We find the quality of retrieval results depends on several factors. High spectral resolution and low level of measurement noise are especially beneficial to the retrieval accuracy, while the coverage of far infrared band is also critical. An ideal case is able to effectively reduce 44% uncertainty for specific humidity, and improve 55% of accuracy for column integrated water vapor in the lower stratosphere.聽