TY - JOUR
T1 - Verification of land-atmosphere coupling in forecast models, reanalyses, and land surface models using flux site observations
AU - Dirmeyer, Paul A.
AU - Chen, Liang
AU - Wu, Jiexia
AU - Shin, Chul Su
AU - Huang, Bohua
AU - Cash, Benjamin A.
AU - Bosilovich, Michael G.
AU - Mahanama, Sarith
AU - Koster, Randal D.
AU - Santanello, Joseph A.
AU - Ek, Michael B.
AU - Balsamo, Gianpaolo
AU - Dutra, Emanuel
AU - Lawrence, David M.
N1 - Funding Information:
Acknowledgments. This work has been primarily supported by National Aeronautics and Space Administration Grant NNX13AQ21G. NCAR model simulations were conducted with support from the National Science Foundation Grant AGS-1419445. The ERA-Interim reanalysis data are provided by ECMWF and processed by LSCE. This work uses eddy covariance data acquired and shared by the FLUXNET community (listed in Table S1), including these networks: Ameri-Flux, AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada, GreenGrass, ICOS, KoFlux, LBA, NECC, OzFlux-TERN, TCOS-Siberia, and USCCC. The FLUXNET eddy covariance data processing and harmonization was carried out by the European Fluxes Database Cluster, AmeriFlux Management Project, and Fluxdata project of FLUXNET, with the support of CDIAC and ICOS Ecosystem Thematic Center, and the OzFlux, China-Flux and AsiaFlux offices. Taylor diagrams were produced using a modified version of the GrADS script developed by Bin Guan. We thank Cristina Benzo for her contributions to produce Table S1 and Eleanor Blyth and two anonymous reviewers for their helpful review comments.
Funding Information:
This work has been primarily supported by National Aeronautics and Space Administration Grant NNX13AQ21G. NCAR model simulations were conducted with support from the National Science Foundation Grant AGS-1419445. The ERAInterim reanalysis data are provided by ECMWF and processed by LSCE. This work uses eddy covariance data acquired and shared by the FLUXNET community (listed in Table S1), including these networks: Ameri-Flux, AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada, GreenGrass, ICOS, KoFlux, LBA, NECC, OzFlux- TERN, TCOS-Siberia, and USCCC. The FLUXNET eddy covariance data processing and harmonization was carried out by the European Fluxes Database Cluster, AmeriFlux Management Project, and Fluxdata project of FLUXNET, with the support of CDIAC and ICOS Ecosystem Thematic Center, and the OzFlux, China-Flux and AsiaFlux offices. Taylor diagrams were produced using a modified version of the GrADS script developed by Bin Guan. We thank Cristina Benzo for her contributions to produce Table S1 and Eleanor Blyth and two anonymous reviewers for their helpful review comments.
Publisher Copyright:
© 2018 American Meteorological Society.
PY - 2018/2/1
Y1 - 2018/2/1
N2 - This study compares four model systems in three configurations (LSM, LSM 1 GCM, and reanalysis) with global flux tower observations to validate states, surface fluxes, and coupling indices between land and atmosphere. Models clearly underrepresent the feedback of surface fluxes on boundary layer properties (the atmospheric leg of land-atmosphere coupling) and may overrepresent the connection between soil moisture and surface fluxes (the terrestrial leg). Models generally underrepresent spatial and temporal variability relative to observations, which is at least partially an artifact of the differences in spatial scale between model grid boxes and flux tower footprints. All models bias high in near-surface humidity and downward shortwave radiation, struggle to represent precipitation accurately, and show serious problems in reproducing surface albedos. These errors create challenges for models to partition surface energy properly, and errors are traceable through the surface energy and water cycles. The spatial distribution of the amplitude and phase of annual cycles (first harmonic) are generally well reproduced, but the biases in means tend to reflect in these amplitudes. Interannual variability is also a challenge for models to reproduce. Although the models validate better against Bowen-ratio-corrected surface flux observations, which allow for closure of surface energy balances at flux tower sites, it is not clear whether the corrected fluxes are more representative of actual fluxes. The analysis illuminates targets for coupled land-atmosphere model development, as well as the value of long-term globally distributed observational monitoring.
AB - This study compares four model systems in three configurations (LSM, LSM 1 GCM, and reanalysis) with global flux tower observations to validate states, surface fluxes, and coupling indices between land and atmosphere. Models clearly underrepresent the feedback of surface fluxes on boundary layer properties (the atmospheric leg of land-atmosphere coupling) and may overrepresent the connection between soil moisture and surface fluxes (the terrestrial leg). Models generally underrepresent spatial and temporal variability relative to observations, which is at least partially an artifact of the differences in spatial scale between model grid boxes and flux tower footprints. All models bias high in near-surface humidity and downward shortwave radiation, struggle to represent precipitation accurately, and show serious problems in reproducing surface albedos. These errors create challenges for models to partition surface energy properly, and errors are traceable through the surface energy and water cycles. The spatial distribution of the amplitude and phase of annual cycles (first harmonic) are generally well reproduced, but the biases in means tend to reflect in these amplitudes. Interannual variability is also a challenge for models to reproduce. Although the models validate better against Bowen-ratio-corrected surface flux observations, which allow for closure of surface energy balances at flux tower sites, it is not clear whether the corrected fluxes are more representative of actual fluxes. The analysis illuminates targets for coupled land-atmosphere model development, as well as the value of long-term globally distributed observational monitoring.
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U2 - 10.1175/JHM-D-17-0152.1
DO - 10.1175/JHM-D-17-0152.1
M3 - Article
AN - SCOPUS:85042657580
SN - 1525-755X
VL - 19
SP - 375
EP - 392
JO - Journal of Hydrometeorology
JF - Journal of Hydrometeorology
IS - 2
ER -