Future global annual frozen ground distribution datasets based on Frost Number Model with Kappa coefficient

Read full text
Authors: Xiaoduo Pan, Hu Li, Xiaowei Nie
Cited by: 1
References: 69

Abstract

Abstract Permafrost, which underlies roughly one-fifth of global land area, is highly vulnerable to ongoing climate warming and its degradation has important implications for hydrological processes, carbon cycling, ecosystems, and infrastructure stability. It remains challenging to accurately project its future distribution due to various factors. The Surface Frost Index (SFI) threshold is a critical parameter that captures first-order thermal forcing for projecting future permafrost distribution. Here, the future global annual frozen ground distribution datasets are produced using an optimized frost number threshold ( F at ) calibrated via kappa coefficient-based accuracy assessment. By comparing simulated outputs with benchmark maps, we identify the optimal F at . Applying this threshold to downscaled CMIP6 data (0.25° resolution), we generate annual frozen ground distributions (2020–2099) under four SSP scenarios (SSP126, SSP245, SSP370, SSP585). The datasets reveal accelerated permafrost degradation, with mid-century (2040–2060) losses of 19 ± 3% to 28 ± 3% and late-century (2080–2099) losses escalating to 21 ± 3% to 61 ± 5%, peaking under SSP585. These high-resolution projections provide critical insights for assessing climate impacts and guiding cryospheric adaptation strategies.

Fields of Study & Subjects

Climate change and permafrost Urban Heat Island Mitigation Cryospheric studies and observations

Publication details

Journal / source
Scientific Data
Publisher
Springer Science and Business Media LLC
Volume
13
Issue
1
Publication date
28 February 2026
Language
EN