Understanding water and energy fluxes in the Amazonia: Lessons from an observation‐model intercomparison

Journal Article · Wed Mar 03 00:00:00 EST 2021 · Global Change Biology

DOI:https://doi.org/10.1111/gcb.15555· OSTI ID:1783366

Restrepo‐Coupe, Natalia  ^[1]; Albert, Loren P.  ^[2]; Longo, Marcos  ^[3]; Baker, Ian  ^[4]; Levine, Naomi M.  ^[5]; Mercado, Lina M. ^[6]; da Araujo, Alessandro C. ^[7]; Christoffersen, Bradley O'Donnell ^[8]; Costa, Marcos H. ^[9]; Fitzjarrald, David R. ^[10]; Galbraith, David  ^[11]; Imbuzeiro, Hewlley ^[9]; Malhi, Yadvinder ^[12]; von Randow, Celso ^[13]; Zeng, Xubin ^[14]; Moorcroft, Paul  ^[15]; Saleska, Scott R.  ^[16]

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1. Department of Ecology and Evolutionary Biology University of Arizona Tucson AZ USA, School of Life Sciences University of Technology Sydney Ultimo NSW Australia
2. Department of Ecology and Evolutionary Biology University of Arizona Tucson AZ USA, Biology Department West Virginia University Morgantown WV USA
3. Department of Organismic and Evolutionary Biology Harvard University Cambridge MA USA, Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA
4. Colorado State University Atmospheric Science Fort Collins CO USA
5. Department of Organismic and Evolutionary Biology Harvard University Cambridge MA USA, College of Letters, Arts, and Science University of Southern California Los Angeles CA USA
6. University of Exeter College of Life and Environmental Sciences Exeter Devon UK, Centre for Ecology and Hydrology Wallingford Oxfordshire UK
7. Embrapa Amazônia Oriental Belém, Pará Brazil, Programa LBA Instituto Nacional de Pesquisas da Amazônia (INPA) Manaus Amazonas Brazil
8. Department of Biology University of Texas Rio Grande Valley Edinburg TX USA, Earth and Environmental Sciences Division Los Alamos National Laboratory Los Alamos NM USA
9. Department of Agricultural Engineering Federal University of Vicosa Vicosa Mato Grosso Brazil
10. University at Albany SUNY Albany NY USA
11. School of Geography University of Leeds Leeds UK
12. Environmental Change Institute School of Geography and the Environment University of Oxford Oxford UK
13. National Institute for Space Research (INPE) Center for Earth Systems Science São José dos Campos São Pablo Brazil
14. Department of Hydrology and Atmospheric Sciences University of Arizona Tucson AZ USA
15. Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA
16. Department of Ecology and Evolutionary Biology University of Arizona Tucson AZ USA

Abstract Tropical forests are an important part of global water and energy cycles, but the mechanisms that drive seasonality of their land‐atmosphere exchanges have proven challenging to capture in models. Here, we (1) report the seasonality of fluxes of latent heat (LE), sensible heat ( H ), and outgoing short and longwave radiation at four diverse tropical forest sites across Amazonia—along the equator from the Caxiuanã and Tapajós National Forests in the eastern Amazon to a forest near Manaus, and from the equatorial zone to the southern forest in Reserva Jaru; (2) investigate how vegetation and climate influence these fluxes; and (3) evaluate land surface model performance by comparing simulations to observations. We found that previously identified failure of models to capture observed dry‐season increases in evapotranspiration (ET) was associated with model overestimations of (1) magnitude and seasonality of Bowen ratios (relative to aseasonal observations in which sensible was only 20%–30% of the latent heat flux) indicating model exaggerated water limitation, (2) canopy emissivity and reflectance (albedo was only 10%–15% of incoming solar radiation, compared to 0.15%–0.22% simulated), and (3) vegetation temperatures (due to underestimation of dry‐season ET and associated cooling). These partially compensating model‐observation discrepancies (e.g., higher temperatures expected from excess Bowen ratios were partially ameliorated by brighter leaves and more interception/evaporation) significantly biased seasonal model estimates of net radiation ( R _n ), the key driver of water and energy fluxes (LE ~ 0.6 R _n and H  ~ 0.15 R _n ), though these biases varied among sites and models. A better representation of energy‐related parameters associated with dynamic phenology (e.g., leaf optical properties, canopy interception, and skin temperature) could improve simulations and benchmarking of current vegetation–atmosphere exchange and reduce uncertainty of regional and global biogeochemical models.

• Sponsoring Organization: USDOE
• OSTI ID: 1783366
• Journal Information: Global Change Biology, Journal Name: Global Change Biology Vol. 27 Journal Issue: 9; ISSN 1354-1013
• Publisher: Wiley-Blackwell
• Country of Publication: United Kingdom
• Language: English