The Tibetan Plateau – known as the ‘Asian water tower’ because of its huge water storage capacity in glaciers – has a profound impact on local and downstream ecosystems. However, it is a challenge to establish and maintain in situ observations there due to the complex terrain. Thanks to satellite technology, scientists may have found a substitute.
In sharp contrast with the importance of the ‘Asian water tower’, sufficient in situ observations in the Tibetan Plateau have been lacking due to the complex terrain. Satellite and reanalysis datasets may offer an alternative, as outlined in new research from the Chinese Academy of Sciences.
“Both satellite and reanalysis datasets are substitutes to reproduce the water vapor features over the Tibetan Plateau, but the time scale should be considered,” explains Yin Zhao, a doctoral student from the Institute of Atmospheric Physics, Chinese Academy of Sciences. Zhao is the lead author of a recently published study on this topic in the journal Climate Dynamics, along with her mentor Professor Tianjun Zhou.
“In recent years, new versions of satellite data have been released and more reanalysis datasets have been updated. However, their quality needs to be evaluated – in particular, the reliability of existing satellite and reanalysis data products in capturing features of water vapor over the Tibetan Plateau,” says Zhao.
After evaluating two NASA satellite datasets and seven widely used reanalysis datasets, the researchers found both satellite datasets to be a reliable way of reproducing the total column water vapor characteristics over the Tibetan Plateau, and that the difference between them was negligible. However, the quality of reanalysis datasets varied with time scales considered.
“There is larger uncertainty among reanalysis datasets than in satellite datasets because of the climate models, observations assimilated, and the assimilation process. So the quality of reanalysis data varies with the time scale considered and there is no perfect reanalysis dataset,” says Zhou, who suggests using reanalysis data with caution.
The researchers therefore constructed a skill-weighted ensemble mean of reanalysis datasets. Using the spatially gridded data AIRS-only as a reference, greater weights were given to the higher quality reanalysis dataset. This quality-weighted ensemble data performed better than unweighted ensemble data and most of the single reanalysis data.
“Our analysis provides essential information about both the strengths and weakness of the current existing substitutes for the observational data, including satellite products and reanalysis data. We recommend the application of the skill-weighted ensemble mean of reanalysis data in future studies of the water cycle over the Tibetan Plateau, as it takes different time scales into account,” concludes Zhao.
This press release was first published on the Chinese Academy of Sciences website.
Read more: Zhao, Y. and Zhou, T. ‘Asian water tower evinced in total column water vapor: a comparison among multiple satellite and reanalysis datasets.’ Climate Dynamics (2019): https://doi.org/10.1007/s00382-019-04999-4