Contribution of Recycled Moisture to Precipitation in Northeastern Tibetan Plateau: A Case Study Based on Bayesian Estimation
| Autor: | Xiuxiu Yu, Mingjun Zhang, Xue Qiu, Cunwei Che, Shengjie Wang, Zhiwen Dong, Hongfei Meng |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Atmospheric Science
010504 meteorology & atmospheric sciences 0208 environmental biotechnology Growing season 02 engineering and technology Bayesian mixing model Environmental Science (miscellaneous) Atmospheric sciences 01 natural sciences Degree (temperature) Meteorology. Climatology Precipitation MixSIAR Water cycle 0105 earth and related environmental sciences Bayes estimator geography Plateau geography.geographical_feature_category Moisture growing season Advection 020801 environmental engineering Qilian Mountains recycled moisture Environmental science QC851-999 |
| Zdroj: | Atmosphere, Vol 12, Iss 731, p 731 (2021) Atmosphere Volume 12 Issue 6 |
| ISSN: | 2073-4433 |
| Popis: | (1) Background: The degree to which local precipitation is supplied by recycled moisture is a reflection of land surface–atmosphere interactions and a potentially significant climate feedback mechanism. This study tries to figure out the water cycle and precipitation mechanism at a mountainous region and then provides a reference for similar mountainous regions outside China. (2) Methods: The dual-isotopes and Bayes-based program MixSIAR is used to assess contributions of advected, transpirated and evaporated vapor to local precipitation. (3) Results: The average percent contribution of recycled moisture (i.e., the sum of surface evaporated vapor and transpirated vapor) to local precipitation at the Qilian Mountains during 2017 plant growing season is about 37% (the upper quartile and the lower quartile was 30% and 43%, respectively). (4) Conclusions: Although the contribution of advection vapor dominated during the plant growing season, the contribution of recycled moisture is also important in such an alpine region. Furthermore, the commonly used simple linear mixing models often yield contributions greater than 100% or less than 0% and are likely to underestimate the contribution of recycled moisture to local precipitation. Although the alternative Bayesian model is not perfect, either, it is still a big improvement. |
| Databáze: | OpenAIRE |
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