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Add a new E-epsilon PBL scheme: (#1303)
TYPE: new feature KEYWORDS: E-epsilon, EEPS, TKE, PBL SOURCE: Chunxi Zhang: 1: (past) International Pacific Research Center, University of Hawai‘i at Mānoa 2: (past) Center for Analysis and Prediction of Storms, University of Oklahoma 3: (current) I. M. System Group, Inc. (IMSG); NOAA/EMC Yuqing Wang International Pacific Research Center, and Department of Atmospheric Sciences, University of Hawai‘i at Mānoa DESCRIPTION OF CHANGES: A turbulence kinetic energy (TKE) and TKE dissipation rate (ε) based 1.5-order closure PBL parameterization is added: 1) the file module_bl_eepsilon.F includes the module for this scheme 2) standard procedures for a new scheme in WRF: changed init, addtendc and driver 3) three more variables are declared in registry.EM_COMMON. e.g., pep_pbl (TKE dissipation rate, state) pek_adv (TKE advection, scalar) pep_adv (PEP advection, scalar) the files module_first_rd_step_part1.F and start_em.F are revised accordingly this scheme is denfied as eepsscheme bl_pbl_physics == 16 4) add module_bl_eepsilon in Makefile LIST OF MODIFIED FILES: phys/module_bl_eepsilon.F phys/module_pbl_driver.F phys/module_physics_init.F phys/module_physics_addtendc.F phys/Makefile Registry/Registry.EM_COMM dyn_em/module_first_rk_step_part1.F dyn_em/start_em.F run/README.namelist TESTS CONDUCTED: 1. Automated jenkins testing is all PASS. 2. The performances of the newly implemented EEPS scheme and the existing Yonsei University (YSU) scheme, the University of Washington (UW) scheme, and Mellor–Yamada–Nakanishi–Niino (MYNN) scheme are evaluated over the stratocumulus dominated southeast Pacific (SEP) and over the Southern Great Plains (SGP) where strong PBL diurnal variation is common. The simulations by these PBL parameterizations are compared with various observations from two field campaigns: the Variability of American Monsoon Systems Project (VAMOS) Ocean–Cloud–Atmosphere–Land Study (VOCALS) in 2008 over the SEP and the Land–Atmosphere Feedback Experiment (LAFE) in 2017 over the SGP. Results show that the EEPS and YSU schemes perform comparably over both regions, while the MYNN scheme performs differently in many aspects, especially over the SEP. The EEPS (MYNN) scheme slightly (significantly) underestimates liquid water path over the SEP. Compared with observations, the UW scheme produces the best PBL height over the SEP. The MYNN produces too high PBL height over the western part of the SEP while both the YSU and EEPS schemes produce too low PBL and cloud-top heights. The differences among the PBL schemes in simulating the PBL features over the SGP are relatively small. 3. See published paper: Zhang, C., Y. Wang, and M. Xue, 2020: Evaluation of an E–ε and Three Other Boundary Layer Parameterization Schemes in the WRF Model over the Southeast Pacific and the Southern Great Plains. Mon. Wea. Rev., 148, 1121–1145, https://doi.org/10.1175/MWR-D-19-0084.1. RELEASE NOTE: A turbulence kinetic energy (TKE) and TKE dissipation rate (ε) based 1.5-order closure PBL parameterization (E–ε, EEPS) is added (Zhang et al. 2020, MWR). Works with surface layer options, 1, 91, 2 and 5. (Thanks to Chunxi Zhang and Yuqing Wang of University of Hawaii.)
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