Avzalshoev (2026) Rumi27/TajGEM: v1.0.0 — Zenodo Archive Release

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Open MIND
• Year: 2026
• Date: 2026-04-20
• Authors: Zafar Avzalshoev
• DOI: 10.5281/zenodo.19657577

Research Groups

Not specified in the provided text.

Short Summary

TajGEM is a regional modeling framework developed to simulate glacier mass balance and retreat dynamics in Central Asia by integrating climate reanalysis and glacier inventories via ensemble machine learning.

Objective

• To simulate and analyze the evolution, mass balance, and retreat dynamics of glaciers within the Tajikistan and broader Central Asian region.

Study Configuration

• Spatial Scale: Regional (Tajikistan / Central Asia).
• Temporal Scale: Not explicitly specified (utilizes ERA5 reanalysis and RGI inventories).

Methodology and Data

• Models used: Ensemble machine learning models.
• Data sources: ERA5 climate reanalysis and RGI (Randolph Glacier Inventory) glacier inventories.

Main Results

• Development of the TajGEM v1.0.0 framework, providing a computational tool for the simulation of glacier mass balance and retreat in the target region.

Contributions

• Provides a specialized regional framework for Central Asia that combines high-resolution climate reanalysis (ERA5) and glacier inventories (RGI) with an ensemble machine learning approach to improve the simulation of glacier dynamics.

Funding

Not specified in the provided text.

Citation

@article{Avzalshoev2026Rumi27TajGEM,
  author = {Avzalshoev, Zafar},
  title = {Rumi27/TajGEM: v1.0.0 — Zenodo Archive Release},
  journal = {Open MIND},
  year = {2026},
  doi = {10.5281/zenodo.19657577},
  url = {https://doi.org/10.5281/zenodo.19657577}
}