Station‐Based Assessment of Sub‐Seasonal Climate Trends in the Tyrolean Alps (Austria)

ABSTRACT The assessment and understanding of climatic changes in mountain regions with complex topography, and their impact on snowmelt and river runoff, are of great importance for the water supply worldwide. Analyses based on observations from high alpine monitoring networks are crucial in this regard. This study quantifies the magnitude and significance of climate trends on the sub‐seasonal scale across elevations by compiling and processing measurements from multiple meteorological station networks in the Tyrolean Alps (Austria). We processed time series from more than 300 locations, of which 86 had records long enough to be included in the trend analysis. Our analysis indicates a warming rate of 0.43°C/dec over 1964–2023 (mean across 27 homogenised time series), with stronger warming in recent decades and greater sub‐seasonal trend variability when shortening the analysis window from 60 to 30 years. Similar sub‐seasonal trend patterns also appear in snow and discharge data sets. Between 1994 and 2023, elevation‐dependent differences in temperature trends emerge in January, with warming at low elevations and slight cooling at high elevations. Analyses of hourly precipitation indicate a tendency towards more hours of heavy rainfall in summer. Our study provides a systematic comparison of multi‐variate observations from multiple data providers in complex mountain terrain, offering new insights into sub‐seasonal and elevation‐dependent characteristics of climate change.

Authors

Institutions

Publication Details

Journal
International Journal of Climatology
Published
2026-07-30
DOI
https://doi.org/10.1002/joc.70527
Primary Topic
Cryospheric studies and observations
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Station‐Based Assessment of Sub‐Seasonal Climate Trends in the Tyrolean Alps (Austria)

Ulrich Strasser, Gertraud Meißl, Johannes Schöber, Elena Bertazza et al.
International Journal of Climatology
Cryospheric studies and observations
article

Station‐Based Assessment of Sub‐Seasonal Climate Trends in the Tyrolean Alps (Austria)

Ulrich Strasser, Gertraud Meißl, Johannes Schöber, Elena Bertazza, Theresa Schellander‐Gorgas, Erwin Rottler, Franz Wagner
article en

Abstract

ABSTRACT The assessment and understanding of climatic changes in mountain regions with complex topography, and their impact on snowmelt and river runoff, are of great importance for the water supply worldwide. Analyses based on observations from high alpine monitoring networks are crucial in this regard. This study quantifies the magnitude and significance of climate trends on the sub‐seasonal scale across elevations by compiling and processing measurements from multiple meteorological station networks in the Tyrolean Alps (Austria). We processed time series from more than 300 locations, of which 86 had records long enough to be included in the trend analysis. Our analysis indicates a warming rate of 0.43°C/dec over 1964–2023 (mean across 27 homogenised time series), with stronger warming in recent decades and greater sub‐seasonal trend variability when shortening the analysis window from 60 to 30 years. Similar sub‐seasonal trend patterns also appear in snow and discharge data sets. Between 1994 and 2023, elevation‐dependent differences in temperature trends emerge in January, with warming at low elevations and slight cooling at high elevations. Analyses of hourly precipitation indicate a tendency towards more hours of heavy rainfall in summer. Our study provides a systematic comparison of multi‐variate observations from multiple data providers in complex mountain terrain, offering new insights into sub‐seasonal and elevation‐dependent characteristics of climate change.

International Journal of Climatology
Universität Innsbruck (AT), General Electric (Austria) (AT), Tirol Kliniken (AT)
Airport Cooperative Research Program
Climate action
Openalex Percentile: Top 13%
Cryospheric studies and observations
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.