Evaluating the performance of two surface layer schemes for the momentum and heat exchange processes during severe haze pollution in Jing-Jin-Ji in eastern China

Abstract. The turbulent flux parameterization schemes in the surface layer are crucial for air pollution modeling. There have been some deficiencies in the prediction of air pollutants by atmosphere chemical models, which is closely related to the uncertainties of the momentum and sensible heat fluxes calculated in the surface layer. The differences between two surface layer schemes (Li and MM5 schemes) were discussed, and the performances of two schemes were mainly evaluated based on the observed momentum and sensible heat fluxes during a heavy haze episode in Jing-Jin-Ji in eastern China. The results showed that the aerodynamic roughness length z0m and the thermal roughness length z0h played major roles in the flux calculation. Compared with the Li scheme, ignoring the difference between z0m and z0h in the MM5 scheme induced a great error in the calculation of the sensible heat flux (e.g., the error was 54 % at Gucheng station). Besides the roughness length, the algorithm for the surface turbulent flux as well as the roughness sublayer also resulted in certain errors in the MM5 scheme. In addition, magnitudes of z0m and z0h have significant influence on the two schemes. The large z0m and z0m∕z0h in megacities with a rough surface (e.g., Beijing) resulted in much larger differences of momentum and sensible heat fluxes between Li and MM5, compared with the small z0m and z0m∕z0h in suburban areas with a smooth surface (e.g., Gucheng). The Li scheme could better characterize the evolution of atmospheric stratification than the MM5 scheme in general, especially for the transition stage from unstable to stable atmospheric stratification, corresponding to the PM2.5 accumulation. The biases of momentum and sensible heat fluxes from Li were lower, about 38 % and 43 %, respectively, than those from MM5 during this stage. This study indicates the superiority of the Li scheme in describing regional atmospheric stratification and an improved possibility of severe haze prediction in Jing-Jin-Ji in eastern China by coupling it into atmosphere chemical models.

[1]  J. Lelieveld,et al.  Intercomparison of boundary layer parameterizations for summer conditions in the eastern Mediterranean island of Cyprus using the WRF - ARW model , 2017, Atmospheric Research.

[2]  Zhanqing Li,et al.  Aerosol and boundary-layer interactions and impact on air quality , 2017 .

[3]  Cheng Liu,et al.  Feedback effects of boundary-layer meteorological factors on cumulative explosive growth of PM 2.5 during winter heavy pollution episodes in Beijing from 2013 to 2016 , 2017 .

[4]  Jianjun He,et al.  Attributions of meteorological and emission factors to the 2015 winter severe haze pollution episodes in China's Jing-Jin-Ji area , 2017 .

[5]  T. Zhao,et al.  The Impacts of Different PBL Schemes on the Simulation of PM2.5 during Severe Haze Episodes in the Jing-Jin-Ji Region and Its Surroundings in China , 2016 .

[6]  Fei Chen,et al.  Erratum to: An Update of Non-iterative Solutions for Surface Fluxes Under Unstable Conditions , 2016, Boundary-Layer Meteorology.

[7]  Fei Chen,et al.  An Update of Non-iterative Solutions for Surface Fluxes Under Unstable Conditions , 2015, Boundary-Layer Meteorology.

[8]  Yu Qu,et al.  Formation mechanism of continuous extreme haze episodes in the megacity Beijing, China, in January 2013 , 2015 .

[9]  Tim Li,et al.  Mesoscale modeling study of the interactions between aerosols and PBL meteorology during a haze episode in Jing–Jin–Ji (China) and its nearby surrounding region – Part 1: Aerosol distributions and meteorological features , 2014 .

[10]  Tim Li,et al.  Mesoscale modelling study of the interactions between aerosols and PBL meteorology during a haze episode in China Jing–Jin–Ji and its near surrounding region – Part 2: Aerosols' radiative feedback effects , 2014 .

[11]  Yuxuan Wang,et al.  Simulating aerosol–radiation–cloud feedbacks on meteorology and air quality over eastern China under severe haze conditionsin winter , 2014 .

[12]  Hong Wang,et al.  A multisource observation study of the severe prolonged regional haze episode over eastern China in January 2013 , 2014 .

[13]  W. Helgason,et al.  A study of the atmospheric surface layer and roughness lengths on the high‐altitude tropical Zongo glacier, Bolivia , 2014 .

[14]  Hong Wang,et al.  An improved non-iterative surface layer flux scheme for atmospheric stable stratification conditions , 2013 .

[15]  Defining the roughness sublayer and its turbulence statistics , 2013 .

[16]  D. B. Subrahamanyam,et al.  Improvements in Sensible Heat-Flux Parametrization in the High-Resolution Regional Model (HRM) Through the Modified Treatment of the Roughness Length for Heat , 2013, Boundary-Layer Meteorology.

[17]  Qiang Li,et al.  Meteorological conditions for the persistent severe fog and haze event over eastern China in January 2013 , 2013, Science China Earth Sciences.

[18]  F. Cheng,et al.  The role of boundary layer schemes in meteorological and air quality simulations of the Taiwan area , 2012 .

[19]  H. Wouters,et al.  Comprehensive Parametrization of Surface-Layer Transfer Coefficients for Use in Atmospheric Numerical Models , 2012, Boundary-Layer Meteorology.

[20]  Alexis K.H. Lau,et al.  Evaluation of nonlocal and local planetary boundary layer schemes in the WRF model , 2012 .

[21]  Michael D. Moran,et al.  Evaluation of the meteorological forcing used for the Air Quality Model Evaluation International Initiative (AQMEII) air quality simulations , 2012 .

[22]  J. Dudhia,et al.  A Revised Scheme for the WRF Surface Layer Formulation , 2012 .

[23]  Jie He,et al.  Improving land surface temperature modeling for dry land of China , 2011 .

[24]  Fuqing Zhang,et al.  Evaluation of Three Planetary Boundary Layer Schemes in the WRF Model , 2010 .

[25]  K. Ridder.  Bulk Transfer Relations for the Roughness Sublayer , 2010 .

[26]  D. Lenschow,et al.  Climate simulations with a new air‐sea turbulent flux parameterization in the National Center for Atmospheric Research Community Atmosphere Model (CAM3) , 2010 .

[27]  Ying Zhang,et al.  On the coupling strength between the land surface and the atmosphere: From viewpoint of surface exchange coefficients , 2009 .

[28]  Ken-ichi Narita,et al.  Roughness length for heat over an urban canopy , 2009 .

[29]  A. Monin,et al.  Basic laws of turbulent mixing in the surface layer of the atmosphere , 2009 .

[30]  Toshio Koike,et al.  Turbulent flux transfer over bare-soil surfaces: Characteristics and parameterization , 2008 .

[31]  W. Brutsaert,et al.  Flux-profile Relationships for Wind Speed and Temperature in the Stable Atmospheric Boundary Layer , 2005 .

[32]  Toshio Koike,et al.  Surface Flux Parameterization in the Tibetan Plateau , 2003 .

[33]  Toshio Koike,et al.  Analytical Solution of Surface Layer Similarity Equations , 2001 .

[34]  Jielun Sun,et al.  Diurnal Variations of Thermal Roughness Height over a Grassland , 1999 .

[35]  Yuheng Song.  An Improvement of the Louis Scheme for the Surface Layer in an Atmospheric Modelling System , 1998 .

[36]  G. W. Thurtell,et al.  The Validity of Similarity Theory in the Roughness Sublayer Above Forests , 1998 .

[37]  Anne Verhoef,et al.  Some Practical Notes on the Parameter kB−1 for Sparse Vegetation , 1997 .

[38]  U. Högström.  Review of some basic characteristics of the atmospheric surface layer , 1996 .

[39]  J. Launiainen.  Derivation of the relationship between the Obukhov stability parameter and the bulk Richardson number for flux-profile studies , 1995 .

[40]  M. S. Moran,et al.  Sensible heat flux - Radiometric surface temperature relationship for eight semiarid areas , 1994 .

[41]  Albert A. M. Holtslag,et al.  Flux Parameterization over Land Surfaces for Atmospheric Models , 1991 .

[42]  R. Stull.  An Introduction to Boundary Layer Meteorology , 1988 .

[43]  A. Holtslag,et al.  Applied Modeling of the Nighttime Surface Energy Balance over Land , 1988 .

[44]  Da‐Lin Zhang,et al.  A High-Resolution Model of the Planetary Boundary Layer—Sensitivity Tests and Comparisons with SESAME-79 Data , 1982 .

[45]  E. K. Webb,et al.  Correction of flux measurements for density effects due to heat and water vapour transfer , 1980 .

[46]  J. Louis.  A parametric model of vertical eddy fluxes in the atmosphere , 1979 .

[47]  R. Francey,et al.  Bulk characteristics of heat transfer in the unstable, baroclinic atmospheric boundary layer , 1978 .

[48]  J. R. Garratt,et al.  Transfer characteristics for a heterogeneous surface of large aerodynamic roughness , 1978 .

[49]  A. Dyer.  A review of flux-profile relationships , 1974 .

[50]  B. Hicks,et al.  Momentum, heat and water vapour transfer to and from natural and artificial surfaces , 1973 .

[51]  E. F. Bradley,et al.  Flux-Profile Relationships in the Atmospheric Surface Layer , 1971 .

[52]  C. Paulson.  The Mathematical Representation of Wind Speed and Temperature Profiles in the Unstable Atmospheric Surface Layer , 1970 .

[53]  E. K. Webb.  Profile relationships: The log‐linear range, and extension to strong stability , 1970 .

[54]  A. Dyer.  The turbulent transport of heat and water vapour in an unstable atmosphere , 1967 .