Detection of non‐climatic biases in land surface temperature records by comparing climatic data and their model simulations

AbstractThe 0.6 °C warming observed in global temperature datasets from 1940 to 1960 to 2000–2020 can be partially due to urban heat island (UHI) and other non-climatic biases in the underlying data, although several previous studies have argued to the contrary. Here we identify land regions where s...

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Published in:Climate Dynamics
Main Author: Nicola Scafetta
Format: Article in Journal/Newspaper
Language:English
Published: 2021
Subjects:
Online Access:https://www.openaccessrepository.it/record/79863
https://doi.org/10.1007/s00382-021-05626-x
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spelling ftopenaccessrep:oai:zenodo.org:79863 2023-10-25T01:39:13+02:00 Detection of non‐climatic biases in land surface temperature records by comparing climatic data and their model simulations Nicola Scafetta 2021-01-17 https://www.openaccessrepository.it/record/79863 https://doi.org/10.1007/s00382-021-05626-x eng eng url:https://www.openaccessrepository.it/communities/itmirror https://www.openaccessrepository.it/record/79863 doi:10.1007/s00382-021-05626-x info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ Aurora Universities Network Atmospheric Science info:eu-repo/semantics/article publication-article 2021 ftopenaccessrep https://doi.org/10.1007/s00382-021-05626-x 2023-09-26T22:20:03Z AbstractThe 0.6 °C warming observed in global temperature datasets from 1940 to 1960 to 2000–2020 can be partially due to urban heat island (UHI) and other non-climatic biases in the underlying data, although several previous studies have argued to the contrary. Here we identify land regions where such biases could be present by locally evaluating their diurnal temperature range (DTR = TMax − TMin trends between the decades 1945–1954 and 2005–2014 and between the decades 1951–1960 and 1991–2000 versus their synthetic hindcasts produced by the CMIP5 models. Vast regions of Asia (in particular Russia and China) and North America, a significant part of Europe, part of Oceania, and relatively small parts of South America (in particular Colombia and Venezuela) and Africa show DTR reductions up to 0.5–1.5 °C larger than the hindcasted ones, mostly where fast urbanization has occurred, such as in central-east China. Besides, it is found: (1) from May to October, TMax globally warmed 40% less than the hindcast; (2) in Greenland, which appears nearly free of any non-climatic contamination, TMean warmed about 50% less than the hindcast; (3) the world macro-regions with, on average, the lowest DTR reductions and with low urbanization (60S-30N:120 W–90 E and 60 S–10 N:90 E–180 E: Central and South America, Africa, and Oceania) warmed about 20–30% less than the models' hindcast. Yet, the world macro-region with, on average, the largest DTR reductions and with high urbanization (30 N–80 N:180 W–180 E: most of North America, Europe, and Central Asia) warmed just a little bit more (5%) than the hindcast, which indicates that the models well agree only with potentially problematic temperature records. Indeed, also tree-based proxy temperature reconstructions covering the 30°N–70°N land area produce significantly less warming than the correspondent instrumentally-based temperature record since 1980. Finally, we compare land and sea surface temperature data versus their CMIP5 simulations and find that 25–45% of the 1 °C land ... Article in Journal/Newspaper Greenland Istituto Nazionale di Fisica Nucleare (INFN): Open Access Repository Greenland Climate Dynamics 56 9-10 2959 2982
institution Open Polar
collection Istituto Nazionale di Fisica Nucleare (INFN): Open Access Repository
op_collection_id ftopenaccessrep
language English
topic Aurora Universities Network
Atmospheric Science
spellingShingle Aurora Universities Network
Atmospheric Science
Nicola Scafetta
Detection of non‐climatic biases in land surface temperature records by comparing climatic data and their model simulations
topic_facet Aurora Universities Network
Atmospheric Science
description AbstractThe 0.6 °C warming observed in global temperature datasets from 1940 to 1960 to 2000–2020 can be partially due to urban heat island (UHI) and other non-climatic biases in the underlying data, although several previous studies have argued to the contrary. Here we identify land regions where such biases could be present by locally evaluating their diurnal temperature range (DTR = TMax − TMin trends between the decades 1945–1954 and 2005–2014 and between the decades 1951–1960 and 1991–2000 versus their synthetic hindcasts produced by the CMIP5 models. Vast regions of Asia (in particular Russia and China) and North America, a significant part of Europe, part of Oceania, and relatively small parts of South America (in particular Colombia and Venezuela) and Africa show DTR reductions up to 0.5–1.5 °C larger than the hindcasted ones, mostly where fast urbanization has occurred, such as in central-east China. Besides, it is found: (1) from May to October, TMax globally warmed 40% less than the hindcast; (2) in Greenland, which appears nearly free of any non-climatic contamination, TMean warmed about 50% less than the hindcast; (3) the world macro-regions with, on average, the lowest DTR reductions and with low urbanization (60S-30N:120 W–90 E and 60 S–10 N:90 E–180 E: Central and South America, Africa, and Oceania) warmed about 20–30% less than the models' hindcast. Yet, the world macro-region with, on average, the largest DTR reductions and with high urbanization (30 N–80 N:180 W–180 E: most of North America, Europe, and Central Asia) warmed just a little bit more (5%) than the hindcast, which indicates that the models well agree only with potentially problematic temperature records. Indeed, also tree-based proxy temperature reconstructions covering the 30°N–70°N land area produce significantly less warming than the correspondent instrumentally-based temperature record since 1980. Finally, we compare land and sea surface temperature data versus their CMIP5 simulations and find that 25–45% of the 1 °C land ...
format Article in Journal/Newspaper
author Nicola Scafetta
author_facet Nicola Scafetta
author_sort Nicola Scafetta
title Detection of non‐climatic biases in land surface temperature records by comparing climatic data and their model simulations
title_short Detection of non‐climatic biases in land surface temperature records by comparing climatic data and their model simulations
title_full Detection of non‐climatic biases in land surface temperature records by comparing climatic data and their model simulations
title_fullStr Detection of non‐climatic biases in land surface temperature records by comparing climatic data and their model simulations
title_full_unstemmed Detection of non‐climatic biases in land surface temperature records by comparing climatic data and their model simulations
title_sort detection of non‐climatic biases in land surface temperature records by comparing climatic data and their model simulations
publishDate 2021
url https://www.openaccessrepository.it/record/79863
https://doi.org/10.1007/s00382-021-05626-x
geographic Greenland
geographic_facet Greenland
genre Greenland
genre_facet Greenland
op_relation url:https://www.openaccessrepository.it/communities/itmirror
https://www.openaccessrepository.it/record/79863
doi:10.1007/s00382-021-05626-x
op_rights info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.1007/s00382-021-05626-x
container_title Climate Dynamics
container_volume 56
container_issue 9-10
container_start_page 2959
op_container_end_page 2982
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