Forest loss in Brazil increases maximum temperatures within 50 km

Forest cover loss in the tropics is well known to cause warming at deforested sites, with maximum temperatures being particularly sensitive. Forest loss causes warming by altering local energy balance and surface roughness, local changes that can propagate across a wide range of spatial scales. Cons...

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Main Authors: Avery S Cohn, Nishan Bhattarai, Jake Campolo, Octavia Crompton, David Dralle, John Duncan, Sally Thompson
Format: Article
Language:English
Published: IOP Publishing 2019-01-01
Series:Environmental Research Letters
Subjects:
Online Access:https://doi.org/10.1088/1748-9326/ab31fb
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author Avery S Cohn
Nishan Bhattarai
Jake Campolo
Octavia Crompton
David Dralle
John Duncan
Sally Thompson
author_facet Avery S Cohn
Nishan Bhattarai
Jake Campolo
Octavia Crompton
David Dralle
John Duncan
Sally Thompson
author_sort Avery S Cohn
collection DOAJ
description Forest cover loss in the tropics is well known to cause warming at deforested sites, with maximum temperatures being particularly sensitive. Forest loss causes warming by altering local energy balance and surface roughness, local changes that can propagate across a wide range of spatial scales. Consequently, temperature increases result from not only changes in forest cover at a site, but also by the aggregate effects of non-local forest loss. We explored such non-local warming within Brazil’s Amazon and Cerrado biomes, the region with the world’s single largest amount of forest loss since 2000. Two datasets, one consisting of in-situ air temperature observations and a second, larger dataset consisting of ATs derived from remotely-sensed observations of land surface temperature, were used to quantify changes in maximum temperature due to forest cover loss at varying length-scales. We considered undisturbed forest locations (1 km ^2 in extent), and forest loss trends in annuli (‘halos’), located 1–2 km, 2–4 km, 4–10 km and 10–50 km from these undisturbed sites. Our research finds significant and substantial non-local warming, suggesting that historical estimates of warming due to forest cover loss under-estimate warming or mis-attribute warming to local change, where non-local changes also influence the pattern of temperature warming.
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spelling doaj.art-cdcb5cc422fa4712b1b6b0e31d117d0a2023-08-09T14:44:58ZengIOP PublishingEnvironmental Research Letters1748-93262019-01-0114808404710.1088/1748-9326/ab31fbForest loss in Brazil increases maximum temperatures within 50 kmAvery S Cohn0https://orcid.org/0000-0002-6906-0488Nishan Bhattarai1https://orcid.org/0000-0003-2749-3549Jake Campolo2Octavia Crompton3David Dralle4https://orcid.org/0000-0002-1944-2103John Duncan5Sally Thompson6Friedman School of Nutrition Science and Policy, Tufts University , 150 Harrison Avenue, Boston, MA, 02155, United States of AmericaSchool of Environment and Sustainability, University of Michigan , 440 Church St, Ann Arbor, MI, 48109, United States of AmericaDepartment of Earth System Science, Stanford University , 473 Via Ortega, Stanford, CA 94305, United States of AmericaDepartment of Civil and Environmental Engineering, Davis Hall, UC Berkeley, Berkeley, CA, 94720, United States of AmericaDepartment of Geology, California State University , Sacramento, 6000 J Street, Sacramento, CA 95819, United States of AmericaSchool of Environment and Agriculture, University of Western Australia , 35 Stirling Hwy, Crawley, WA, 6009, AustraliaDepartment of Civil and Environmental Engineering, Davis Hall, UC Berkeley, Berkeley, CA, 94720, United States of America; Department of Civil, Environmental and Mining Engineering, University of Western Australia , 35 Stirling Hwy, Crawley, WA, 6009, AustraliaForest cover loss in the tropics is well known to cause warming at deforested sites, with maximum temperatures being particularly sensitive. Forest loss causes warming by altering local energy balance and surface roughness, local changes that can propagate across a wide range of spatial scales. Consequently, temperature increases result from not only changes in forest cover at a site, but also by the aggregate effects of non-local forest loss. We explored such non-local warming within Brazil’s Amazon and Cerrado biomes, the region with the world’s single largest amount of forest loss since 2000. Two datasets, one consisting of in-situ air temperature observations and a second, larger dataset consisting of ATs derived from remotely-sensed observations of land surface temperature, were used to quantify changes in maximum temperature due to forest cover loss at varying length-scales. We considered undisturbed forest locations (1 km ^2 in extent), and forest loss trends in annuli (‘halos’), located 1–2 km, 2–4 km, 4–10 km and 10–50 km from these undisturbed sites. Our research finds significant and substantial non-local warming, suggesting that historical estimates of warming due to forest cover loss under-estimate warming or mis-attribute warming to local change, where non-local changes also influence the pattern of temperature warming.https://doi.org/10.1088/1748-9326/ab31fbforestsclimate changeextreme heatbiogeophysical climate changeland use and land cover changeremote sensing
spellingShingle Avery S Cohn
Nishan Bhattarai
Jake Campolo
Octavia Crompton
David Dralle
John Duncan
Sally Thompson
Forest loss in Brazil increases maximum temperatures within 50 km
Environmental Research Letters
forests
climate change
extreme heat
biogeophysical climate change
land use and land cover change
remote sensing
title Forest loss in Brazil increases maximum temperatures within 50 km
title_full Forest loss in Brazil increases maximum temperatures within 50 km
title_fullStr Forest loss in Brazil increases maximum temperatures within 50 km
title_full_unstemmed Forest loss in Brazil increases maximum temperatures within 50 km
title_short Forest loss in Brazil increases maximum temperatures within 50 km
title_sort forest loss in brazil increases maximum temperatures within 50 km
topic forests
climate change
extreme heat
biogeophysical climate change
land use and land cover change
remote sensing
url https://doi.org/10.1088/1748-9326/ab31fb
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