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Research article - Peer-reviewed, 2021

High-resolution analysis of observed thermal growing season variability over northern Europe

Aalto, Juha; Pirinen, Pentti; Kauppi, Pekka E.; Rantanen, Mika; Lussana, Cristian; Lyytikainen-Saarenmaa, Paivi; Gregow, Hilppa

Abstract

Strong historical and predicted future warming over high-latitudes prompt significant effects on agricultural and forest ecosystems. Thus, there is an urgent need for spatially-detailed information of current thermal growing season (GS) conditions and their past changes. Here, we deployed a large network of weather stations, high-resolution geospatial environmental data and semi-parametric regression to model the spatial variation in multiple GS variables (i.e. beginning, end, length, degree day sum [GDDS, base temperature + 5 degrees C]) and their intra-annual variability and temporal trends in respect to geographical location, topography, water and forest cover, and urban land use variables over northern Europe. Our analyses revealed substantial spatial variability in average GS conditions (1990-2019) and consistent temporal trends (1950-2019). We showed that there have been significant changes in thermal GS towards earlier beginnings (on average 15 days over the study period), increased length (23 days) and GDDS (287 degrees C days). By using a spatial interpolation of weather station data to a regular grid we predicted current GS conditions at high resolution (100 m x 100 m) and with high accuracy (correlation >= 0.92 between observed and predicted mean GS values), whereas spatial variation in temporal trends and interannual variability were more demanding to predict. The spatial variation in GS variables was mostly driven by latitudinal and elevational gradients, albeit they were constrained by local scale variables. The proximity of sea and lakes, and high forest cover suppressed temporal trends and inter-annual variability potentially indicating local climate buffering. The produced high-resolution datasets showcased the diversity in thermal GS conditions and impacts of climate change over northern Europe. They are valuable in various forest management and ecosystem applications, and in adaptation to climate change.

Keywords

Thermal growing season; Statistical modeling; Climate change; Generalized additive model; Local climate; GIS

Published in

Climate Dynamics
2021,
Publisher: SPRINGER

    Associated SLU-program

    SLU Forest Damage Center

    Sustainable Development Goals

    SDG15 Life on land
    SDG13 Climate action

    UKÄ Subject classification

    Climate Research

    Publication identifier

    DOI: https://doi.org/10.1007/s00382-021-05970-y

    Permanent link to this page (URI)

    https://res.slu.se/id/publ/113958