Comment on tc-2022-117

Abstract

Glacier evolution across Tien Shan and Pamir is heterogeneous in space and time. This heterogeneity is believed to be mainly driven by contrasting climatic settings and changing atmospheric conditions. However, a systematic and consistent region-wide analysis of the climatic and static morphological drivers remains limited to date. Meteorological reanalysis and remote sensing products, and novel approaches to derive region-wide annual mass balance time series, all provide the basis to investigate the drivers behind the observed heterogeneous glacier response. Here, we investigate the consistency of interpretations derived from available datasets through correlation analyses between climatic and static drivers with mass balance estimates in Tien Shan and Pamir. Our results show that even supposedly similar datasets lead to different and partly contradicting assumptions on dominant drivers of mass balance variability. Only when considering all glaciers in the Pamir and Tien Shan together, we find a similar picture of dominant meteorological drivers over space. Using either existing mountain subdivisions or glacier subdivisions based on mass balance variability, no consistencies can be found. Within different mass balance and meteorological datasets the results suggest very different drivers. This conclusion is even more prominent in the temporal correlation analysis where contradicting patterns of dominant drivers result from presumably similar meteorological datasets. Clear non-climatic drivers could not be identified. Even with newly available mass balance and meteorological data, a knowledge gap about the main mechanisms behind the heterogeneous glacier response in Central Asia remains. The results highlight that apparent but false consistencies across studies using a single dataset might largely relate to the chosen dataset rather than to the processes or involved environmental variables. As long as no glaciological, meteorological, or hydrological in situ observation network provides data for direct calibration and validation of extensive datasets, we cannot predict a realistic improvement in our understanding of the changing cryosphere at regional scale for Tien Shan and Pamir.