Simulating surface energy fluxes using the variable-resolution Community Earth System Model (VR-CESM)

Elizabeth A. Burakowski, Ahmed Tawfik, Andrew Ouimette, Lucie Lepine, Colin Zarzycki, Kimberly Novick, Scott Ollinger, Gordon Bonan

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Recent advances in variable-resolution (VR) global models provide the tools necessary to investigate local and global impacts of land cover by embedding a high-resolution grid over areas of interest in a seamless and computationally efficient manner. We used two eddy covariance tower clusters in the Eastern USA to evaluate surface energy fluxes (latent heat, λE; sensible heat, H; net radiation, Rn; and ground heat, G) and surface properties (aerodynamic resistance to heat transfer, raero; Bowen ratio, β; and albedo, α) by uncoupled point simulations of the land-only Community Land Model (PTCLM4.5) and two coupled land–atmosphere Community Earth System Model (CESM1.3) simulations. The CESM simulations included a 1° uniform grid global simulation and global 1° simulation with a 0.25° refined VR grid over the Eastern USA. Tower clusters included the following plant functional types—broadleaf deciduous temperate (hardwood) forest, C3 non-Arctic grass (grass), a cropland, and needleleaf evergreen temperate (pine) forest. During the growing season, diurnal cycles of λE and H for grass and the cropland were simulated well by PTCLM4.5 and VR-CESM1.3; however, λE (H) was biased low (high) at the hardwood and pine forested sites, contributing to biases in β. Growing season Rn was generally well simulated by CLM4.5 and VR-CESM1.3; however, modeled elevated albedo (indicative of snow cover) persisted longer in winter and spring leading to large biases in Rn and α. The introduction of a VR grid does not adversely impact surface energy fluxes compared to 1° uniform grids and highlights the usefulness of this approach for future efforts to predict land–atmosphere fluxes across heterogeneous landscapes.

Original languageEnglish (US)
Pages (from-to)115-133
Number of pages19
JournalTheoretical and Applied Climatology
Volume138
Issue number1-2
DOIs
StatePublished - Oct 1 2019

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

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