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

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.

Characteristics of Land–Air Exchange Parameters over Grassland in Southeast Tibet

Accurate parameters that describe land–air exchange processes are essential for studying and predicting atmospheric processes over the Tibetan Plateau. Radiation, atmospheric thermal and moisture conditions, and turbulent heat and momentum fluxes were measured in the Yarlung Zangbo River, southeast Tibet, in May–July 2013. Based on the data, land–air exchange parameters were derived over the grassland surface, including the aerodynamic roughness length z0m, thermal roughness length z0h, the excess resistance to heat transfer kB−1 (where k represents the von Kármán constant and B−1 represents the Stanton number), and momentum and heat transfer coefficients (CD and CH, respectively). The average z0m was 7.0 cm, with a standard deviation of 1.4 cm; these values are higher than those observed in the central and western plateau regions and may have been affected by the tall grass and bush surface covers that surrounded the observation site. The average kB−1 was 5.7 ± 1.8, which is higher than that in other plateau regions in the same season. The average CD during the observation period, (11.9 ± 1.6) × 10−3, is also higher than that of other plateau regions. The commonly used iterative scheme and three noniterative turbulent flux parameterization schemes were evaluated over southeast Tibet using the above observational data. Parameter CD was underestimated by most schemes, whereas CH was overestimated by all schemes. Additional studies suggested that the iterative scheme performed best in retrieving the land–air exchange parameters and can be applied over southeast Tibet.

Evaluation of Noah Frozen Soil Parameterization for Application to a Tibetan Meadow Ecosystem

This study evaluates the Noah land surface model (LSM) in its ability to simulate water and heat exchanges over frozen ground in a Tibetan meadow ecosystem. A comprehensive dataset including in situ micrometeorological and soil moisture–temperature profile measurements collected between November and March is utilized, and analyses of the measurements reveal that the measured soil freezing characteristics are better captured by 1) modifying the parameter bl implemented in the current Noah LSM that constrains the shape parameter of soil water retention curve utilized by the water potential freezing point depression equation to produce appropriate liquid water content θliq under subzero temperature conditions and 2) neglecting the ice effect on soil-specific surface and thus matric potential via setting the empirical parameter that accounts for the effect of increase in specific surface of soil particles and ice–liquid water ck to zero. The numerical experiments performed with the Noah model run show that in comparison to the default Noah LSM, adoption of ck = 0 and site-specific bl values reduces the overestimation of θliq across the soil profile. Implementation of augmentations such as the parameterization of diurnally varying thermal roughness length resolves the overestimation of daytime turbulent heat fluxes and underestimation of surface temperature. Further adoption of a new heat conductivity parameterization reduces the overestimation of nighttime surface temperature. An appropriate treatment of phase change efficiency that accounts for changing freezing rate with varying liquid water contents is also needed to reduce the temperature underestimation across soil profiles.

Evaluation of Turbulent Surface Flux Parameterizations over Tall Grass in a Beijing Suburb

Numerical weather and climate prediction systems necessitate accurate land surface–atmosphere fluxes, whose determination typically replies on a suite of parameterization schemes. The authors present a field investigation over tall grass in a Beijing suburb, where the aerodynamic roughness length (z0) and zero-plane displacement height (d) are found to be 0.02 and 0.44 m, respectively (the value of d is close to two-thirds the average grass height during this field experiment). Both z0 and d values are then used as input parameters of an analytic model of flux footprint; the footprint model reveals that eddy-covariance flux measurements are mainly representative of the tall grass surface concerned herein, potential influences from anthropogenic sources in this suburban area notwithstanding. Based on the “fair weather” data (with an energy balance ratio of 0.89), the authors evaluate four parameterizations of turbulent surface fluxes, namely, a total of three traditional “iterative” schemes and one “noniterative” scheme developed recently to reduce computational time. Their performances are intercompared in terms of the estimations of the sensible heat flux and two turbulence components (the friction velocity and temperature scale). In weakly stable to unstable conditions, two schemes are recommended here for their good performance overall; the first scheme stems jointly from the work of Högström and Beljaars and Holtslag, and the second stems from that of Li et al.. For this tall grass surface, the choice of z0/z0h = 100 (z0h is the thermal roughness length) is more appropriate than another choice of 10, because the former produces comparatively accurate sensible heat flux estimations.

Significant Decrease of Uncertainties in Sensible Heat Flux Simulation Using Temporally Variable Aerodynamic Roughness in Two Typical Forest Ecosystems of China

Aerodynamic roughness length zom is an important parameter for reliably simulating surface fluxes. It varies with wind speed, atmospheric stratification, terrain, and other factors. However, it is usually considered a constant. It is known that uncertainties in zom result in latent heat flux (LE) simulation errors, since zom links LE with aerodynamic resistance. The effects of zom on sensible heat flux (SH) simulation are usually neglected because there is no direct link between the two. By comparing SH simulations with three types of zom inputs, it is found that allowing zom temporal variation in an SH simulation model significantly improves agreement between simulated and measured SH and also decreases the sensitivity of the SH model to the heat transfer coefficient Ct, which in turn determines the linkage between zom and thermal roughness length zoh.

Improving the Noah Land Surface Model in Arid Regions with an Appropriate Parameterization of the Thermal Roughness Length

Daytime land surface temperatures in arid and semiarid regions are typically not well simulated in current land surface models (LSMs). This study first evaluates the importance of parameterizing the thermal roughness length (z0h) to model the surface temperature (Tsfc) and turbulent sensible heat flux (H) in arid regions. Six schemes for z0h are implemented into the Noah LSM, revealing the high sensitivity of the simulations to its parameterization. Comparisons are then performed between the original Noah LSM and a revised version with a novel z0h scheme against observations at four arid or semiarid sites, including one in Arizona and three in western China. The land they cover is sparse grass or bare soil. The results indicate that the original Noah LSM significantly underestimates Tsfc and overestimates H in the daytime, whereas the revised model can simulate well both Tsfc and H simultaneously. The improved version benefits from the successful modeling of the diurnal variation of z0h, which the original model cannot produce.