Planetary Boundary Layer Height Variations Over the Tibetan Plateau in Relation to Local Climate Variables and Large-Scale Circulation
The lowest layer of the Earth's atmosphere, the planetary boundary layer (PBL), may reach extremely high above the Tibetan Plateau (TP). Moreover, the TP is a hotspot region for climate interactions, exerting far-reaching in uences on atmospheric conditions. However, very little is known about the temporal and spatial variations in planetary boundary layer height (PBLH) across the vast plateau and how the PBLH may be related to other climate variables. Therefore, this study utilises the recently available reanalysis dataset ERA5 to investigate rstly how the PBLH has varied during the last four decades to establish a PBLH climatology for the TP, and secondly how it may be related to local climate variables and large-scale circulation. It is shown that the variations in TP PBLH are large. Over the interior of the plateau the PBLH sometimes exceeds 6000 m in the afternoon, while it only grows to about half of this height in the southeastern TP. PBLH trends range from -65 m per decade in the monsoon season in central TP to +70 m per decade in southeastern TP in the dry season, resulting in a very weak overall trend. The spatial patterns in the PBLH trends are strikingly similar to the trends of surface sensible heat ux, which is strongly correlated with PBLH over most of the plateau in both the dry season and the monsoon season, suggesting that surface sensible heat ux is the dominating factor behind the PBLH trends. In addition, it is found that even in the absence of a stratospheric intrusion the low extra-tropical tropopause may reach very close to the high PBL tops which could potentially lead to enhanced stratosphere-troposphere exchanges. Further, PBLH is analysed in relation to large-scale climate indices such as the El Ni~no Southern Oscillation (ENSO) index and the Indian Summer Monsoon (ISM) index. Although the relations are generally weak, some associations can be discerned, such as statistically signi cant anticorrelation between PBLH and ENSO for the dry season as well as detrended PBLH and detrended ISM for the summer mean.