Estimates of Global Surface Hydrology and Heat Fluxes from the Community Land Model (CLM4.5) with Four Atmospheric Forcing Datasets
AffiliationUniv Arizona, Dept Atmospher Sci
MetadataShow full item record
PublisherAMER METEOROLOGICAL SOC
CitationEstimates of Global Surface Hydrology and Heat Fluxes from the Community Land Model (CLM4.5) with Four Atmospheric Forcing Datasets 2016, 17 (9):2493 Journal of Hydrometeorology
JournalJournal of Hydrometeorology
Rights2016 American Meteorological Society
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at email@example.com.
AbstractGlobal land surface hydrology and heat fluxes can be estimated by running a land surface model (LSM) driven by the atmospheric forcing dataset. Previous multimodel studies focused on the impact of different LSMs on model results. Here the sensitivity of the Community Land Model, version 4.5 (CLM4.5), results to the atmospheric forcing dataset is documented. Together with the model default global forcing dataset (CRU-NCEP, hereafter CRUNCEP), three newly developed, reanalysis-based, near-surface meteorological datasets (i.e., MERRA, CFSR, and ERA-Interim) with the precipitation adjusted by the Global Precipitation Climatology Project monthly product were used to drive CLM4.5. All four simulations were run at 0.5 degrees x0.5 degrees grids from 1979 to 2009 with the identical initialization. The simulated monthly surface hydrology variables, fluxes, and the forcing datasets were then evaluated against various observation-based datasets (soil moisture, runoff, snow depth and water equivalent, and flux tower measurements). To partially avoid the mismatch between model gridbox values and point measurements, three approaches were taken. The model simulations based on three newly constructed forcing datasets are overall better than the simulation from CRUNCEP, in particular for soil moisture and snow quantities. The ensemble mean from the CLM4.5 simulations using the four forcing datasets is generally superior to individual simulations, and the ensemble mean latent and sensible heat fluxes over global land (60 degrees S-90 degrees N) are 42.8 and 40.3 W m(-2), respectively. The differences in both precipitation and other atmospheric forcing variables (e.g., air temperature and downward solar radiation) contribute to the differences in simulated results. The datasets are available from the authors for further evaluation and for various applications.
NotePublished Online: 13 September 2016; 6 Month Embargo.
VersionFinal published version
SponsorsNational Science Foundation of China (NSFC) ; NSF [AGS-0944101]; NSFC