Optimizing the isoprene emission model MEGAN with satellite and ground-based observational constraints

Simple item page
dc.contributor.authorDiMaria, Christian A.
dc.contributor.authorJones, Dylan B. A.
dc.contributor.authorWorden, Helen
dc.contributor.authorBloom, A. Anthony
dc.contributor.authorBowman, Kevin
dc.contributor.authorStavrakou, Trissevgeni
dc.contributor.authorMiyazaki, Kazuyuki
dc.contributor.authorWorden, John
dc.contributor.authorGuenther, Alex
dc.contributor.authorSarkar, Chinmoy
dc.contributor.authorSeco, Roger
dc.contributor.authorPark, Jeong-Hoo
dc.contributor.authorTota, Julio
dc.contributor.authorGomes Alves, Eliane
dc.contributor.authorFerracci, Valerio
dc.date.accessioned2023-02-15T11:54:41Z
dc.date.available2023-02-15T11:54:41Z
dc.date.issued2023-02-02
dc.description.abstractIsoprene is a hydrocarbon emitted in large quantities by terrestrial vegetation. It is a precursor to several air quality and climate pollutants including ozone. Emission rates vary with plant species and environmental conditions. This variability can be modeled using the Model of Emissions of Gases and Aerosols from Nature (MEGAN). MEGAN parameterizes isoprene emission rates as a vegetation-specific standard rate which is modulated by scaling factors that depend on meteorological and environmental driving variables. Recent experiments have identified large uncertainties in the MEGAN temperature response parameterization, while the emission rates under standard conditions are poorly constrained in some regions due to a lack of representative measurements and uncertainties in landcover. In this study, we use Bayesian model-data fusion to optimize the MEGAN temperature response and standard emission rates using satellite- and ground-based observational constraints. Optimization of the standard emission rate with satellite constraints reduced model biases but was highly sensitive to model input errors and drought stress and was found to be inconsistent with ground-based constraints at an Amazonian field site, reflecting large uncertainties in the satellite-based emissions. Optimization of the temperature response with ground-based constraints increased the temperature sensitivity of the model by a factor of five at an Amazonian field site but had no impact at a UK field site, demonstrating significant ecosystem-dependent variability of the isoprene emission temperature sensitivity. Ground-based measurements of isoprene across a wide range of ecosystems will be key for obtaining an accurate representation of isoprene emission temperature sensitivity in global biogeochemical models.en_UK
dc.identifier.citationDiMaria CA, Jones DB, Worden H, et al., (2023) Optimizing the isoprene emission model MEGAN with satellite and ground-based observational constraints. Journal of Geophysical Research: Atmospheres, Volume 128, Issue 4, February 2023, Article number e2022JD037822en_UK
dc.identifier.issn2169-897X
dc.identifier.urihttps://doi.org/10.1029/2022JD037822
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/19197
dc.language.isoenen_UK
dc.publisherAmerican Geophysical Union (AGU) - Wileyen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectisoprene emissionsen_UK
dc.subjectmodel-data fusionen_UK
dc.subjectmodel optimizationen_UK
dc.subjectremote sensingen_UK
dc.subjecteddy covarianceen_UK
dc.subjectMonte Carlo algorithmen_UK
dc.titleOptimizing the isoprene emission model MEGAN with satellite and ground-based observational constraintsen_UK
dc.typeArticleen_UK
dc.typeThesisen_UK

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Optimizing_the_isoprene_emission_model_MEGAN-2023.pdf
Size:
2.34 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.63 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Staff publications (SWEE)