Modeling Profiles of Micrometeorological Variables in a Tropical Premontane Rainforest Using Multi‐Layered CLM (CLM‐ML)

Abstract This study updates the multi‐layered Community Land Model (CLM‐ml) for hillslopes and compares predictions from against observations collected in tropical montane rainforest, Costa Rica. Modifications are made in order to capture a wider array of vertical leaf area distributions, predict CO...

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Autores principales:	Jaeyoung Song, Gretchen R. Miller, Anthony T. Cahill, Luiza Maria T. Aparecido, Georgianne W. Moore
Formato:	article
Lenguaje:	EN
Publicado:	American Geophysical Union (AGU) 2021
Materias:	hillslope land surface model leaf area density multi‐layer model tropical rainforest turbulence model Physical geography GB3-5030 Oceanography GC1-1581
Acceso en línea:	https://doaj.org/article/7f56570389a546d8bfe157d962511b65
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spelling	oai:doaj.org-article:7f56570389a546d8bfe157d962511b652021-11-24T08:11:41ZModeling Profiles of Micrometeorological Variables in a Tropical Premontane Rainforest Using Multi‐Layered CLM (CLM‐ML)1942-246610.1029/2020MS002259https://doaj.org/article/7f56570389a546d8bfe157d962511b652021-05-01T00:00:00Zhttps://doi.org/10.1029/2020MS002259https://doaj.org/toc/1942-2466Abstract This study updates the multi‐layered Community Land Model (CLM‐ml) for hillslopes and compares predictions from against observations collected in tropical montane rainforest, Costa Rica. Modifications are made in order to capture a wider array of vertical leaf area distributions, predict CO2 profiles, account for soil respiration, and adjust wind forcings for difficult topographic settings. Test results indicate that the modified multi‐layer CLM model can successfully replicate the shape of various micrometeorological profiles (humidity, CO2, temperature, and wind speed) under the canopy. In the single‐layer models (CLM4.5 and CLM5), excessive day‐to‐night differences in leaf temperature and leaf wetness were originally noted, but CLM‐ml significantly improved these issues, decreasing the amplitudes of diurnal cycles by 67% and 47%. Sub‐canopy considerations, such as canopy shapes and turbulent transfer parameters, also played a significant role in model performance. More importantly, unlike single layer models, the results that CLM‐ml produces can be compared to variables measured within the canopy to provide far more detailed diagnostic information. Further observations and model developments, aimed at reflecting surface heterogeneity, will be necessary to adequately capture the complexity and the features of the tropical montane rainforest.Jaeyoung SongGretchen R. MillerAnthony T. CahillLuiza Maria T. AparecidoGeorgianne W. MooreAmerican Geophysical Union (AGU)articlehillslopeland surface modelleaf area densitymulti‐layer modeltropical rainforestturbulence modelPhysical geographyGB3-5030OceanographyGC1-1581ENJournal of Advances in Modeling Earth Systems, Vol 13, Iss 5, Pp n/a-n/a (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	hillslope land surface model leaf area density multi‐layer model tropical rainforest turbulence model Physical geography GB3-5030 Oceanography GC1-1581
spellingShingle	hillslope land surface model leaf area density multi‐layer model tropical rainforest turbulence model Physical geography GB3-5030 Oceanography GC1-1581 Jaeyoung Song Gretchen R. Miller Anthony T. Cahill Luiza Maria T. Aparecido Georgianne W. Moore Modeling Profiles of Micrometeorological Variables in a Tropical Premontane Rainforest Using Multi‐Layered CLM (CLM‐ML)
description	Abstract This study updates the multi‐layered Community Land Model (CLM‐ml) for hillslopes and compares predictions from against observations collected in tropical montane rainforest, Costa Rica. Modifications are made in order to capture a wider array of vertical leaf area distributions, predict CO2 profiles, account for soil respiration, and adjust wind forcings for difficult topographic settings. Test results indicate that the modified multi‐layer CLM model can successfully replicate the shape of various micrometeorological profiles (humidity, CO2, temperature, and wind speed) under the canopy. In the single‐layer models (CLM4.5 and CLM5), excessive day‐to‐night differences in leaf temperature and leaf wetness were originally noted, but CLM‐ml significantly improved these issues, decreasing the amplitudes of diurnal cycles by 67% and 47%. Sub‐canopy considerations, such as canopy shapes and turbulent transfer parameters, also played a significant role in model performance. More importantly, unlike single layer models, the results that CLM‐ml produces can be compared to variables measured within the canopy to provide far more detailed diagnostic information. Further observations and model developments, aimed at reflecting surface heterogeneity, will be necessary to adequately capture the complexity and the features of the tropical montane rainforest.
format	article
author	Jaeyoung Song Gretchen R. Miller Anthony T. Cahill Luiza Maria T. Aparecido Georgianne W. Moore
author_facet	Jaeyoung Song Gretchen R. Miller Anthony T. Cahill Luiza Maria T. Aparecido Georgianne W. Moore
author_sort	Jaeyoung Song
title	Modeling Profiles of Micrometeorological Variables in a Tropical Premontane Rainforest Using Multi‐Layered CLM (CLM‐ML)
title_short	Modeling Profiles of Micrometeorological Variables in a Tropical Premontane Rainforest Using Multi‐Layered CLM (CLM‐ML)
title_full	Modeling Profiles of Micrometeorological Variables in a Tropical Premontane Rainforest Using Multi‐Layered CLM (CLM‐ML)
title_fullStr	Modeling Profiles of Micrometeorological Variables in a Tropical Premontane Rainforest Using Multi‐Layered CLM (CLM‐ML)
title_full_unstemmed	Modeling Profiles of Micrometeorological Variables in a Tropical Premontane Rainforest Using Multi‐Layered CLM (CLM‐ML)
title_sort	modeling profiles of micrometeorological variables in a tropical premontane rainforest using multi‐layered clm (clm‐ml)
publisher	American Geophysical Union (AGU)
publishDate	2021
url	https://doaj.org/article/7f56570389a546d8bfe157d962511b65
work_keys_str_mv	AT jaeyoungsong modelingprofilesofmicrometeorologicalvariablesinatropicalpremontanerainforestusingmultilayeredclmclmml AT gretchenrmiller modelingprofilesofmicrometeorologicalvariablesinatropicalpremontanerainforestusingmultilayeredclmclmml AT anthonytcahill modelingprofilesofmicrometeorologicalvariablesinatropicalpremontanerainforestusingmultilayeredclmclmml AT luizamariataparecido modelingprofilesofmicrometeorologicalvariablesinatropicalpremontanerainforestusingmultilayeredclmclmml AT georgiannewmoore modelingprofilesofmicrometeorologicalvariablesinatropicalpremontanerainforestusingmultilayeredclmclmml
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Modeling Profiles of Micrometeorological Variables in a Tropical Premontane Rainforest Using Multi‐Layered CLM (CLM‐ML)

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