Twenty years of Kilimanjaro observations across 5000 m reveal tropical elevation-dependent warming under clear-sky conditions

Abstract Mountain regions are experiencing rapid climate change. However, temperature trends along elevation gradients remain poorly understood in the tropics, where long-term high-elevation air temperature ( T air ) observations are sparse. Here, we examine elevation-dependent warming (EDW) on Mount Kilimanjaro by combining a unique long-term in situ T air transect with Moderate Resolution Imaging Spectroradiometer (MODIS) land-surface temperature (LST), surface and topographic datasets. Using machine learning, we map clear-sky T air at four MODIS overpasses at 1 km resolution for 2004–2024. The models showed strong predictive performance, with RMSE values of 1.76 °C and 1.36 °C, and R 2 values of 0.94 and 0.95 for daytime and nighttime models, respectively. Modelled T air reveals strong diurnal contrasts: daytime T air shows strong spatial variability affected by radiation and surface properties, while nighttime T air varies more gradually with elevation. Trend analysis (2004–2019) identifies EDW under clear-sky conditions. Daytime trends become positive near the summit (+0.05 to +0.10 °C/decade), while strongest cooling occurs at 3000–3500 m (−0.13 to −0.14 °C/decade), coinciding with vegetation and land-cover change. Nighttime weak warming dominates most elevations (+0.04 to +0.15 °C/decade), while the summit remains near-neutral. These contrasts indicate that EDW on Kilimanjaro is shaped not only by elevation-dependent climate responses, but also by vegetation and land-cover changes that modify local surface-atmosphere coupling.

Authors

Institutions

Publication Details

Journal
npj Climate and Atmospheric Science
Published
2026-10-05
DOI
https://doi.org/10.1038/s41612-026-01560-z
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Twenty years of Kilimanjaro observations across 5000 m reveal tropical elevation-dependent warming under clear-sky conditions

Yaping Mo, Yongming Xu, Harold Lovell, Pepin Nick
npj Climate and Atmospheric Science
Climate variability and models
article

Twenty years of Kilimanjaro observations across 5000 m reveal tropical elevation-dependent warming under clear-sky conditions

Yaping Mo, Yongming Xu, Harold Lovell, Pepin Nick
article en

Abstract

Abstract Mountain regions are experiencing rapid climate change. However, temperature trends along elevation gradients remain poorly understood in the tropics, where long-term high-elevation air temperature ( T air ) observations are sparse. Here, we examine elevation-dependent warming (EDW) on Mount Kilimanjaro by combining a unique long-term in situ T air transect with Moderate Resolution Imaging Spectroradiometer (MODIS) land-surface temperature (LST), surface and topographic datasets. Using machine learning, we map clear-sky T air at four MODIS overpasses at 1 km resolution for 2004–2024. The models showed strong predictive performance, with RMSE values of 1.76 °C and 1.36 °C, and R 2 values of 0.94 and 0.95 for daytime and nighttime models, respectively. Modelled T air reveals strong diurnal contrasts: daytime T air shows strong spatial variability affected by radiation and surface properties, while nighttime T air varies more gradually with elevation. Trend analysis (2004–2019) identifies EDW under clear-sky conditions. Daytime trends become positive near the summit (+0.05 to +0.10 °C/decade), while strongest cooling occurs at 3000–3500 m (−0.13 to −0.14 °C/decade), coinciding with vegetation and land-cover change. Nighttime weak warming dominates most elevations (+0.04 to +0.15 °C/decade), while the summit remains near-neutral. These contrasts indicate that EDW on Kilimanjaro is shaped not only by elevation-dependent climate responses, but also by vegetation and land-cover changes that modify local surface-atmosphere coupling.

npj Climate and Atmospheric Science
Nanjing University of Information Science and Technology (CN), University of Portsmouth (GB)
Openalex Percentile: Top 14%
Climate variability and models
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Twenty years of Kilimanjaro observations across 5000 m reveal tropical elevation-dependent warming under clear-sky conditions — Yaping Mo, Yongming Xu, et al. · npj Climate and Atmospheric Science (2026) | TGRS Research Map | TGRS