Predictability of summertime diurnal winds over ungauged mountain glaciers

Abstract. Glacier and valley winds are characteristic features of the microclimate of glacierised valleys. The speed of such winds influences the turbulent heat flux, which contributes to ice melt significantly. Sparse in-situ meteorological measurements and the inability of large-scale climate data products to capture such local winds introduce uncertainty into glacier- to global-scale mass-balance calculations. Here, we propose an empirical model having three parameters, namely, the mean wind speed, the sensitivity of the diurnal winds to temperature, and a time-scale parameter, to predict the mean summertime diurnal wind speed on valley glaciers, based only on reanalysis temperature. Utilising data from 28 weather stations on 18 valley glaciers across the globe, we show that the model, driven solely by reanalysis temperature, reproduces the observed mean summertime diurnal wind speed with a mean RMSE of 0.24 m s−1 across stations, which is 8.8 % of the mean observed wind speed. Interestingly, the three model parameters can be estimated even on an ungauged glacier based on the mean temperature and regional slope. A leave-one-out analysis of the stations suggests a root-mean-squared error of 0.85 m s−1 on average, which is a ∼200 % improvement over a standard reanalysis product. The performance of the model is largely independent of the number of stations available for calibration, as long as it is 21 or more. The presented empirical parametrisation can improve wind speed estimates on ungauged glaciers, leading to better glacier mass-balance calculations.

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Publication Details

Journal
˜The œcryosphere
Published
2026-09-01
DOI
https://doi.org/10.5194/tc-20-4911-2026
Primary Topic
Cryospheric studies and observations
Type
article
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article

Predictability of summertime diurnal winds over ungauged mountain glaciers

Himanshu Kaushik, Chandan Sarangi, Argha Banerjee, Ramachandran Shankar et al.
˜The œcryosphere
Cryospheric studies and observations
article

Predictability of summertime diurnal winds over ungauged mountain glaciers

Himanshu Kaushik, Chandan Sarangi, Argha Banerjee, Ramachandran Shankar, Mohd. Farooq Azam, Jayan Krishnanand
article en

Abstract

Abstract. Glacier and valley winds are characteristic features of the microclimate of glacierised valleys. The speed of such winds influences the turbulent heat flux, which contributes to ice melt significantly. Sparse in-situ meteorological measurements and the inability of large-scale climate data products to capture such local winds introduce uncertainty into glacier- to global-scale mass-balance calculations. Here, we propose an empirical model having three parameters, namely, the mean wind speed, the sensitivity of the diurnal winds to temperature, and a time-scale parameter, to predict the mean summertime diurnal wind speed on valley glaciers, based only on reanalysis temperature. Utilising data from 28 weather stations on 18 valley glaciers across the globe, we show that the model, driven solely by reanalysis temperature, reproduces the observed mean summertime diurnal wind speed with a mean RMSE of 0.24 m s−1 across stations, which is 8.8 % of the mean observed wind speed. Interestingly, the three model parameters can be estimated even on an ungauged glacier based on the mean temperature and regional slope. A leave-one-out analysis of the stations suggests a root-mean-squared error of 0.85 m s−1 on average, which is a ∼200 % improvement over a standard reanalysis product. The performance of the model is largely independent of the number of stations available for calibration, as long as it is 21 or more. The presented empirical parametrisation can improve wind speed estimates on ungauged glaciers, leading to better glacier mass-balance calculations.

˜The œcryosphereVol. 20(9)
Indian Institute of Science Education and Research Pune (IN), Indian Institute of Technology Madras (IN), Institute of Mathematical Sciences (IN), Indian Institute of Technology Indore (IN)
Climate action
Openalex Percentile: Top 14%
Cryospheric studies and observations
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