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Temporal variability in air temperature lapse rates across the glacierised terrain of the Chandra basin, western Himalaya
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Abstract
The air temperature lapse rate (TLR) is one of the essential parameters for glacio-hydrological studies. However, TLR estimations are limited in the glacierised regions of Himalaya due to a scarcity of long-term observations. Therefore, a dense in-situ monitoring network over a high Himalayan region is needed to estimate the TLR accurately. Here, in-situ air temperature data is obtained from Automatic Weather Stations (AWS) installed over the Chandra basin, western Himalaya, from October 2020 to September 2022. This data is used to estimate the TLR by regressing the air temperature with the corresponding elevations. We estimated the mean annual TLR of 3.8 ± 0.3°C km− 1 for the entire Chandra basin, significantly less than the standard environmental lapse rate (6.5°C km− 1). We found substantial seasonal variability in each TLR time series. The maximum TLR is 5.8 ± 0.2°C km− 1 during the summer, and the minimum is -1.6 ± 0.1°C km− 1 during winter, comparing all the meteorological stations. Further, we observe strong diurnal fluctuations of TLR, which has maximum and minimum values during 10:00 to 18:00 hrs and 20:00 to 09:00 hrs, respectively. The study highlights that the temporal variability of TLR is site-specific and strongly correlated with wind speed, relative humidity, and radiation fluxes. Furthermore, a temperature-index model is used to assess the implications of TLR by estimating glacier mass balance. This study highlights the importance of considering observed TLR to accurately model surface mass balance over the glacierised Himalayan region.
Research Square Platform LLC
Title: Temporal variability in air temperature lapse rates across the glacierised terrain of the Chandra basin, western Himalaya
Description:
Abstract
The air temperature lapse rate (TLR) is one of the essential parameters for glacio-hydrological studies.
However, TLR estimations are limited in the glacierised regions of Himalaya due to a scarcity of long-term observations.
Therefore, a dense in-situ monitoring network over a high Himalayan region is needed to estimate the TLR accurately.
Here, in-situ air temperature data is obtained from Automatic Weather Stations (AWS) installed over the Chandra basin, western Himalaya, from October 2020 to September 2022.
This data is used to estimate the TLR by regressing the air temperature with the corresponding elevations.
We estimated the mean annual TLR of 3.
8 ± 0.
3°C km− 1 for the entire Chandra basin, significantly less than the standard environmental lapse rate (6.
5°C km− 1).
We found substantial seasonal variability in each TLR time series.
The maximum TLR is 5.
8 ± 0.
2°C km− 1 during the summer, and the minimum is -1.
6 ± 0.
1°C km− 1 during winter, comparing all the meteorological stations.
Further, we observe strong diurnal fluctuations of TLR, which has maximum and minimum values during 10:00 to 18:00 hrs and 20:00 to 09:00 hrs, respectively.
The study highlights that the temporal variability of TLR is site-specific and strongly correlated with wind speed, relative humidity, and radiation fluxes.
Furthermore, a temperature-index model is used to assess the implications of TLR by estimating glacier mass balance.
This study highlights the importance of considering observed TLR to accurately model surface mass balance over the glacierised Himalayan region.
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