Biogeophysical Effects of Land-Use and Land-Cover Change Not Detectable in Warmest Month


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Date

2023-03-15

Publication Type

Journal Article

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Abstract

Land-use and land-cover changes (hereafter simply "land use") alter climates biogeophysically by affecting surface fluxes of energy and water. Yet, near-surface temperature responses to land use across observational versus model -based studies and spatial-temporal scales can be inconsistent. Here we assess the prevalence of the historical land use signal of daily maximum temperatures averaged over the warmest month of the year (tLU) using regularized optimal fingerprint-ing for detection and attribution. We use observations from the Climatic Research Unit and Berkeley Earth alongside his-torical simulations with and without land use from phase 6 of the Coupled Model Intercomparison Project to reconstruct an experiment representing the effects of land use on climate. To assess the signal of land use at spatially resolved conti-nental and global scales, we aggregate all input data across reference regions and continents, respectively. At both scales, land use does not comprise a significantly detectable set of forcings for two of four Earth system models and their multimo-del mean. Furthermore, using a principal component analysis, we find that tLU is mostly composed of the nonlocal effects of land use rather than its local effects. These findings show that, at scales relevant for climate attribution, uncertainties in Earth system model representations of land use are too high relative to the effects of internal variability to confidently assess land use.

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Publication status

published

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Book title

Volume

36 (6)

Pages / Article No.

1845 - 1861

Publisher

American Meteorological Society

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Edition / version

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Subject

Principal components analysis; Regression analysis; General circulation models; Land surface model; Climate variability; Trends

Organisational unit

03778 - Seneviratne, Sonia / Seneviratne, Sonia check_circle

Notes

Funding

101003536 - Earth system models for the future (EC)

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