Latent heat exchange in the boreal and arctic biomes

V. Kasurinen, K. Alfredsen, P. Kolari, I. Mammarella, P. Alekseychik, J. Rinne, T. Vesala, P. Bernier, J. Boike, M. Langer, L.B. Marchesini, J. van Huissteden, A.J. Dolman, T. Sachs, T. Ohta, A. Varlagin, A. Rocha, A. Arain, W. Oechel, M. Lund & 7 others A. Grelle, A. Lindroth, A. Black, M. Aurela, T. Laurila, A. Lohila, F. Berninger

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

In this study latent heat flux (λE) measurements made at 65 boreal and arctic eddy-covariance (EC) sites were analyses by using the Penman-Monteith equation. Sites were stratified into nine different ecosystem types: harvested and burnt forest areas, pine forests, spruce or fir forests, Douglas-fir forests, broadleaf deciduous forests, larch forests, wetlands, tundra and natural grasslands. The Penman-Monteith equation was calibrated with variable surface resistances against half-hourly eddy-covariance data and clear differences between ecosystem types were observed. Based on the modeled behavior of surface and aerodynamic resistances, surface resistance tightly control λE in most mature forests, while it had less importance in ecosystems having shorter vegetation like young or recently harvested forests, grasslands, wetlands and tundra. The parameters of the Penman-Monteith equation were clearly different for winter and summer conditions, indicating that phenological effects on surface resistance are important. We also compared the simulated λE of different ecosystem types under meteorological conditions at one site. Values of λE varied between 15% and 38% of the net radiation in the simulations with mean ecosystem parameters. In general, the simulations suggest that λE is higher from forested ecosystems than from grasslands, wetlands or tundra-type ecosystems. Forests showed usually a tighter stomatal control of λE as indicated by a pronounced sensitivity of surface resistance to atmospheric vapor pressure deficit. Nevertheless, the surface resistance of forests was lower than for open vegetation types including wetlands. Tundra and wetlands had higher surface resistances, which were less sensitive to vapor pressure deficits. The results indicate that the variation in surface resistance within and between different vegetation types might play a significant role in energy exchange between terrestrial ecosystems and atmosphere. These results suggest the need to take into account vegetation type and phenology in energy exchange modeling.
Original languageEnglish
Article number11
Pages (from-to)3439-3456
JournalGlobal Change Biology
Issue number20
DOIs
Publication statusPublished - 2014

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Latent heat
Surface resistance
biome
Ecosystems
Wetlands
tundra
Penman-Monteith equation
wetland
vegetation type
grassland
Vapor pressure
eddy covariance
vapor pressure
ecosystem
net radiation
latent heat flux
Atmospheric pressure
deciduous forest
terrestrial ecosystem
Heat flux

Cite this

Kasurinen, V., Alfredsen, K., Kolari, P., Mammarella, I., Alekseychik, P., Rinne, J., ... Berninger, F. (2014). Latent heat exchange in the boreal and arctic biomes. Global Change Biology, (20), 3439-3456. [11]. https://doi.org/10.1111/gcb.12640
Kasurinen, V. ; Alfredsen, K. ; Kolari, P. ; Mammarella, I. ; Alekseychik, P. ; Rinne, J. ; Vesala, T. ; Bernier, P. ; Boike, J. ; Langer, M. ; Marchesini, L.B. ; van Huissteden, J. ; Dolman, A.J. ; Sachs, T. ; Ohta, T. ; Varlagin, A. ; Rocha, A. ; Arain, A. ; Oechel, W. ; Lund, M. ; Grelle, A. ; Lindroth, A. ; Black, A. ; Aurela, M. ; Laurila, T. ; Lohila, A. ; Berninger, F. / Latent heat exchange in the boreal and arctic biomes. In: Global Change Biology. 2014 ; No. 20. pp. 3439-3456.
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abstract = "In this study latent heat flux (λE) measurements made at 65 boreal and arctic eddy-covariance (EC) sites were analyses by using the Penman-Monteith equation. Sites were stratified into nine different ecosystem types: harvested and burnt forest areas, pine forests, spruce or fir forests, Douglas-fir forests, broadleaf deciduous forests, larch forests, wetlands, tundra and natural grasslands. The Penman-Monteith equation was calibrated with variable surface resistances against half-hourly eddy-covariance data and clear differences between ecosystem types were observed. Based on the modeled behavior of surface and aerodynamic resistances, surface resistance tightly control λE in most mature forests, while it had less importance in ecosystems having shorter vegetation like young or recently harvested forests, grasslands, wetlands and tundra. The parameters of the Penman-Monteith equation were clearly different for winter and summer conditions, indicating that phenological effects on surface resistance are important. We also compared the simulated λE of different ecosystem types under meteorological conditions at one site. Values of λE varied between 15{\%} and 38{\%} of the net radiation in the simulations with mean ecosystem parameters. In general, the simulations suggest that λE is higher from forested ecosystems than from grasslands, wetlands or tundra-type ecosystems. Forests showed usually a tighter stomatal control of λE as indicated by a pronounced sensitivity of surface resistance to atmospheric vapor pressure deficit. Nevertheless, the surface resistance of forests was lower than for open vegetation types including wetlands. Tundra and wetlands had higher surface resistances, which were less sensitive to vapor pressure deficits. The results indicate that the variation in surface resistance within and between different vegetation types might play a significant role in energy exchange between terrestrial ecosystems and atmosphere. These results suggest the need to take into account vegetation type and phenology in energy exchange modeling.",
author = "V. Kasurinen and K. Alfredsen and P. Kolari and I. Mammarella and P. Alekseychik and J. Rinne and T. Vesala and P. Bernier and J. Boike and M. Langer and L.B. Marchesini and {van Huissteden}, J. and A.J. Dolman and T. Sachs and T. Ohta and A. Varlagin and A. Rocha and A. Arain and W. Oechel and M. Lund and A. Grelle and A. Lindroth and A. Black and M. Aurela and T. Laurila and A. Lohila and F. Berninger",
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Kasurinen, V, Alfredsen, K, Kolari, P, Mammarella, I, Alekseychik, P, Rinne, J, Vesala, T, Bernier, P, Boike, J, Langer, M, Marchesini, LB, van Huissteden, J, Dolman, AJ, Sachs, T, Ohta, T, Varlagin, A, Rocha, A, Arain, A, Oechel, W, Lund, M, Grelle, A, Lindroth, A, Black, A, Aurela, M, Laurila, T, Lohila, A & Berninger, F 2014, 'Latent heat exchange in the boreal and arctic biomes' Global Change Biology, no. 20, 11, pp. 3439-3456. https://doi.org/10.1111/gcb.12640

Latent heat exchange in the boreal and arctic biomes. / Kasurinen, V.; Alfredsen, K.; Kolari, P.; Mammarella, I.; Alekseychik, P.; Rinne, J.; Vesala, T.; Bernier, P.; Boike, J.; Langer, M.; Marchesini, L.B.; van Huissteden, J.; Dolman, A.J.; Sachs, T.; Ohta, T.; Varlagin, A.; Rocha, A.; Arain, A.; Oechel, W.; Lund, M.; Grelle, A.; Lindroth, A.; Black, A.; Aurela, M.; Laurila, T.; Lohila, A.; Berninger, F.

In: Global Change Biology, No. 20, 11, 2014, p. 3439-3456.

Research output: Contribution to JournalArticleAcademicpeer-review

TY - JOUR

T1 - Latent heat exchange in the boreal and arctic biomes

AU - Kasurinen, V.

AU - Alfredsen, K.

AU - Kolari, P.

AU - Mammarella, I.

AU - Alekseychik, P.

AU - Rinne, J.

AU - Vesala, T.

AU - Bernier, P.

AU - Boike, J.

AU - Langer, M.

AU - Marchesini, L.B.

AU - van Huissteden, J.

AU - Dolman, A.J.

AU - Sachs, T.

AU - Ohta, T.

AU - Varlagin, A.

AU - Rocha, A.

AU - Arain, A.

AU - Oechel, W.

AU - Lund, M.

AU - Grelle, A.

AU - Lindroth, A.

AU - Black, A.

AU - Aurela, M.

AU - Laurila, T.

AU - Lohila, A.

AU - Berninger, F.

PY - 2014

Y1 - 2014

N2 - In this study latent heat flux (λE) measurements made at 65 boreal and arctic eddy-covariance (EC) sites were analyses by using the Penman-Monteith equation. Sites were stratified into nine different ecosystem types: harvested and burnt forest areas, pine forests, spruce or fir forests, Douglas-fir forests, broadleaf deciduous forests, larch forests, wetlands, tundra and natural grasslands. The Penman-Monteith equation was calibrated with variable surface resistances against half-hourly eddy-covariance data and clear differences between ecosystem types were observed. Based on the modeled behavior of surface and aerodynamic resistances, surface resistance tightly control λE in most mature forests, while it had less importance in ecosystems having shorter vegetation like young or recently harvested forests, grasslands, wetlands and tundra. The parameters of the Penman-Monteith equation were clearly different for winter and summer conditions, indicating that phenological effects on surface resistance are important. We also compared the simulated λE of different ecosystem types under meteorological conditions at one site. Values of λE varied between 15% and 38% of the net radiation in the simulations with mean ecosystem parameters. In general, the simulations suggest that λE is higher from forested ecosystems than from grasslands, wetlands or tundra-type ecosystems. Forests showed usually a tighter stomatal control of λE as indicated by a pronounced sensitivity of surface resistance to atmospheric vapor pressure deficit. Nevertheless, the surface resistance of forests was lower than for open vegetation types including wetlands. Tundra and wetlands had higher surface resistances, which were less sensitive to vapor pressure deficits. The results indicate that the variation in surface resistance within and between different vegetation types might play a significant role in energy exchange between terrestrial ecosystems and atmosphere. These results suggest the need to take into account vegetation type and phenology in energy exchange modeling.

AB - In this study latent heat flux (λE) measurements made at 65 boreal and arctic eddy-covariance (EC) sites were analyses by using the Penman-Monteith equation. Sites were stratified into nine different ecosystem types: harvested and burnt forest areas, pine forests, spruce or fir forests, Douglas-fir forests, broadleaf deciduous forests, larch forests, wetlands, tundra and natural grasslands. The Penman-Monteith equation was calibrated with variable surface resistances against half-hourly eddy-covariance data and clear differences between ecosystem types were observed. Based on the modeled behavior of surface and aerodynamic resistances, surface resistance tightly control λE in most mature forests, while it had less importance in ecosystems having shorter vegetation like young or recently harvested forests, grasslands, wetlands and tundra. The parameters of the Penman-Monteith equation were clearly different for winter and summer conditions, indicating that phenological effects on surface resistance are important. We also compared the simulated λE of different ecosystem types under meteorological conditions at one site. Values of λE varied between 15% and 38% of the net radiation in the simulations with mean ecosystem parameters. In general, the simulations suggest that λE is higher from forested ecosystems than from grasslands, wetlands or tundra-type ecosystems. Forests showed usually a tighter stomatal control of λE as indicated by a pronounced sensitivity of surface resistance to atmospheric vapor pressure deficit. Nevertheless, the surface resistance of forests was lower than for open vegetation types including wetlands. Tundra and wetlands had higher surface resistances, which were less sensitive to vapor pressure deficits. The results indicate that the variation in surface resistance within and between different vegetation types might play a significant role in energy exchange between terrestrial ecosystems and atmosphere. These results suggest the need to take into account vegetation type and phenology in energy exchange modeling.

U2 - 10.1111/gcb.12640

DO - 10.1111/gcb.12640

M3 - Article

SP - 3439

EP - 3456

JO - Global Change Biology

JF - Global Change Biology

SN - 1354-1013

IS - 20

M1 - 11

ER -

Kasurinen V, Alfredsen K, Kolari P, Mammarella I, Alekseychik P, Rinne J et al. Latent heat exchange in the boreal and arctic biomes. Global Change Biology. 2014;(20):3439-3456. 11. https://doi.org/10.1111/gcb.12640