Blackening Cryosphere: Revealing Hotspot Shifts and HGB-Based Forecasting of Absorbing Aerosol Threats over the Himalayan Frozen Frontiers

TL;DR

This study analyzes the transport and seasonal variability of black carbon and mineral dust aerosols over Pakistan and the Himalayas, developing a machine learning forecast model to predict high aerosol events and assess cryospheric melting risks.

Contribution

It introduces a novel histogram-based gradient boosting classifier for predicting aerosol exceedance events over the Himalayas using satellite data and seasonal indicators.

Findings

High predictive accuracy with ROC-AUC of 0.791

Forecasts identify Himalayan regions at elevated aerosol risk

Model demonstrates good probability calibration

Abstract

Black carbon and mineral dust are key absorbing aerosols that influence atmospheric radiation and increasingly threaten global cryospheric stability. This study examines the long-range transport and seasonal variability of these aerosols over Pakistan and their movement toward the western Himalayas. Using satellite-derived Absorption Aerosol Optical Depth (AAOD) data from 2019 to mid-2025, we analyse their spatiotemporal behaviour across Pakistan's urban lowlands and high-altitude regions. Fifteen-day aggregated AAOD fields are used to track seasonal transport into glaciated terrain, where deposited aerosols can darken snow and ice and accelerate melt. For high-AAOD events, a probabilistic forecasting approach based on machine learning (ML) was developed. Using geographical, seasonal, and lagged indicators, a histogram-based gradient boosting classifier was trained to predict AAOD exceedance one step in advance. ROC-AUC, PR-AUC, and the Brier score were used to assess the model's performance. The results show high predictive capacity and good probability calibration, with values of 0.791, 0.269, and 0.028, respectively. Forecasts indicate that areas adjacent to Himalayan glaciers consistently exhibit the highest probability of increasing AAOD, signalling an elevated risk of aerosol-induced snowmelt.