Switching between First-Order Closure Schemes in a Numerical Mesoscale Model

Abstract. The planetary boundary layer (PBL) height (PBLH) is an important parameter for weather, climate, and air quality models. Radiosonde is one of the most commonly used instruments for PBLH determination and is generally accepted as a standard for other methods. However, mainstream approaches for the estimation of PBLH from radiosonde present some uncertainties and even show disadvantages under some circumstances, and the results need to be visually verified, especially during the transition period of different PBL regimes. To avoid the limitations of individual methods and provide a benchmark estimation of PBLH, we propose an ensemble method based on high-resolution radiosonde data collected in Beijing in 2017. Seven existing methods including four gradient-based methods are combined along with statistical modification. The ensemble method is verified at 08:00, 14:00, and 20:00 Beijing time (BJT = UTC+8), respectively. The overestimation of PBLH can be effectively eliminated by setting thresholds for gradient-based methods, and the inconsistency between individual methods can be reduced by clustering. Based on the statistics of a 1-year observational analysis, the effectiveness (E) of the ensemble method reaches up to 62.6 %, an increase of 6.5 %–53.0 % compared to the existing methods. Nevertheless, the ensemble method suffers to some extent from uncertainties caused by the consistent overestimation of PBLH, the profiles with a multi-layer structure, and the intermittent turbulence in the stable boundary layer (SBL). Finally, this method has been applied to characterize the diurnal and seasonal variations of different PBL regimes. Particularly, the average convective boundary layer (CBL) height is found to be the highest in summer, and the SBL is lowest in summer with about 200 m. The average PBLH at the transition stage lies around 1100 m except in winter. These findings imply that the ensemble method is reliable and effective.

The boundary layer characteristics at Central Amazonia were studied using the WRF model, with a domain of 3 one-way interacting nested grids. The results from the inner domain (1 km) for different PBL schemes (nonlocal (ACM2, MRF, SH, YSU, QNSE-EDMF) and local (BouLac, GBM, MYNN2.5, MYNN3, MYJ, UW)) were analyzed against in situ observations. This validation dataset was made during the GoAmazon 2014/5 experiment. The PBL heights (PBLH) were compared with ceilometer (Vaisala Oy, Finland) measurements installed during the field work. Short-term forecasts (72-h) were conducted (with a 12 h spin-up) for 4 different and typical cases: rainy and dry seasons for a typical (2014) and an ENSO-influenced (2015) years. The statistical analysis was performed separately for daytime and nighttime due to the pronounced diurnal variation, which revealed that the PBLH is better predicted during daytime. The local schemes (MYNN2.5, MYNN3, MYJ) give reasonable estimates for the convective boundary layer and non-local scheme (SH) for stable conditions. The diagnosed PBLH spatial fields for nighttime (02 Local Time – UTC-4 h) and daytime (14 LT) were investigated. The PBLH spatial fields revealed that nonlocal PBL schemes are influenced by the hydrography, while local PBL schemes were not. In general, the local MYNN2.5 and MYNN3 and the nonlocal QNSE-EDMF schemes predicted a deeper PBLH. Nonlocal schemes (ACM2 and MRF) depict the hydrography in their PBLH distribution with higher PBLH over the land (> 1500 m) and lower over the water bodies (< 800 m) during the daytime. The same typical values for nighttime are 100-200 m over the continent and 50-100 m over the water. The values during ENSO (2015) were higher than for the typical year (2014).

Regionalization of the summertime planetary boundary layer height in comparison with various reanalysis datasets over China

Abstract. Radiosonde (RS) is widely used to detect the vertical structures of the planetary boundary layer (PBL), and numerous methods have been proposed for retrieving PBL height (PBLH) from RS data. However, an algorithm that is suitable under all atmospheric conditions does not exist. This study evaluates the performance of four common PBLH algorithms under different thermodynamic stability conditions based on RS data collected from nine sites in January–December 2019. The four RS algorithms are the potential temperature gradient method (GMθ), relative humidity (RH) gradient method (GMRH), parcel method (PM) and Richardson number method (RM). Atmospheric conditions are divided into convective boundary layer (CBL), neutral boundary layer (NBL) and stable boundary layer (SBL) on the basis of the potential temperature profile. Results indicate that SBL is dominant at nighttime, whilst CBL dominates at daytime. Under all and SBL classifications, PBLH retrieved by RM is typically higher than those retrieved using the other methods. On the contrary, the PBLH result retrieved by PM is the lowest. Under CBL and NBL classifications, PBLH retrieved by PM is the highest. PBLH retrieved by GMθ and GMRH is relatively low under all classifications. Moreover, the uncertainty analysis shows that the consistency of PBLH retrieved by different algorithms is more than 80 % under CBL and NBL classifications. By contrast, the consistency of PBLH is less than 60 % under SBL classification. The average profiles and standard deviations of wind speed and potential temperature under consistent and inconsistent conditions are also investigated. The results indicate that consistent cases are typically accompanied by evident atmospheric stratification, such as a large gradient in the potential temperature profile or a low-level jet in the wind speed profile. These results indicate that the reliability of the PBLH results retrieved from RS data is affected by the structure of the boundary layer. Overall, GMθ and RM are appropriate for CBL condition. GMθ and PM are recommended for NBL condition. GMθ and GMRH are robust for SBL condition. This comprehensive comparison provides a reference for selecting the appropriate algorithm when retrieving PBLH from RS data.

Comparisons of PBL heights derived from CALIPSO and ECMWF reanalysis data over China

Long-term measurements of planetary boundary layer height and interactions with PM2.5 in Shanghai, China

A portable Scheimpflug lidar system has been employed for atmospheric boundary layer studies. Atmospheric backscattering signals were continuously recorded from 21 August to 28 August 2018. The covariance wavelet transform (CWT) method was utilized to identify the maximum gradient of recorded lidar curves as the planetary boundary layer (PBL) height. As the directly retrieved PBL height could be underestimated or overestimated due to the presence of residual layers and thin clouds, localized atmospheric turbulence, aerosol stratification, etc., a CWT-based quality-control algorithm has also been developed to improve the reliability of the PBL height retrieval. The temporal distribution of the final PBL height has shown a clear diurnal variation as the ambient temperature changed due to the increasing and decreasing of surface heating during a one-week continuous measurement campaign. The promising results have shown great potential in employing the Scheimpflug lidar technique and the CWT-based method in the determination of the PBL height.

This thesis tackles the problem of the automated detection of the atmospheric boundary layer (BL) height, h, from aerosol lidar/ceilometer observations. A new method, the Bayesian Selective Method (BSM), is presented. It implements a Bayesian statistical inference procedure which combines in an statistically optimal way different sources of information. Firstly atmospheric stratification boundaries are located from discontinuities in the ceilometer back-scattered signal. The BSM then identifies the discontinuity edge that has the highest probability to effectively mark the BL height. Information from the contemporaneus physical boundary layer model simulations and a climatological dataset of BL height evolution are combined in the assimilation framework to assist this choice. The BSM algorithm has been tested for four months of continuous ceilometer measurements collected during the BASE:ALFA project and is shown to realistically diagnose the BL depth evolution in many different weather conditions. Then the BASE:ALFA dataset is used to investigate the boundary layer structure in stable conditions. Functions from the Obukhov similarity theory are used as regression curves to fit observed velocity and temperature profiles in the lower half of the stable boundary layer. Surface fluxes of heat and momentum are best-fitting parameters in this exercise and are compared with what measured by a sonic anemometer. The comparison shows remarkable discrepancies, more evident in cases for which the bulk Richardson number turns out to be quite large. This analysis supports earlier results, that surface turbulent fluxes are not the appropriate scaling parameters for profiles of mean quantities in very stable conditions. One of the practical consequences is that boundary layer height diagnostic formulations which mainly rely on surface fluxes are in disagreement to what obtained by inspecting co-located radiosounding profiles.

There is a deep atmospheric boundary layer on the Tibetan Plateau (TP) that has always been of interest to researchers. The variation in the atmospheric boundary layer under the influence of the southern branch of the westerly wind and that of the Asian monsoon was analyzed using sounding data collected in 2014 and 2019. Then, the hourly high-resolution comprehensive observation data for the land-atmosphere interaction on the TP and the ERA5 reanalysis data were used to study the influence of the atmospheric boundary layer’s structure in Mount Everest, Nyingchi, Nam Co, Nagqu, and Shiquan River regions. The results show that the height of the convective boundary layer observed at the Mount Everest, Nyingchi, Nam Co, Nagqu, and Shiquan River stations on the TP under the influence of the southern branch of the westerly wind was higher than that during the Asian monsoon season. The height of the convective boundary layer in the Shiquan River area was often highest at 20:00. The structure of the boundary layer in the Mount Everest area was often affected by the westerly jets and glacial winds. The inversion layer developed earlier in the Nyingchi area than at the other stations. The height of the boundary layer was positively correlated with the sensible heat flux and negatively correlated with the latent heat flux. The vertical velocity in the atmospheric boundary layer in the Nyingchi area decreased, which may be one of the reasons why the height of the convective boundary layer was lower in this area than at the other stations and humidity inversion often occurred in this area.

Abstract. We investigate the boundary-layer (BL) height at Hyytiälä in southern Finland diagnosed from radiosonde observations, a microwave radiometer (MWR) and ERA5 reanalysis. Four different, pre-existing algorithms are used to diagnose the BL height from the radiosondes. The diagnosed BL height is sensitive to the method used. The level of agreement, and the sign of systematic bias between the four different methods, depends on the surface-layer stability. For very unstable situations, the median BL height diagnosed from the radiosondes varies from 600 to 1500 m depending on which method is applied. Good agreement between the BL height in ERA5 and diagnosed from the radiosondes using Richardson-number-based methods is found for almost all stability classes, suggesting that ERA5 has adequate vertical resolution near the surface to resolve the BL structure. However, ERA5 overestimates the BL height in very stable conditions, highlighting the ongoing challenge for numerical models to correctly resolve the stable BL. Furthermore, ERA5 BL height differs most from the radiosondes at 18:00 UTC, suggesting ERA5 does not resolve the evening transition correctly. BL height estimates from the MWR are also found to be reliable in unstable situations but often are inaccurate under stable conditions when, in comparison to ERA5 BL heights, they are much deeper. The errors in the MWR BL height estimates originate from the limitations of the manufacturer's algorithm for stable conditions and also the misidentification of the type of BL. A climatology of the annual and diurnal cycle of BL height, based on ERA5 data, and surface-layer stability, based on eddy covariance observations, was created. The shallowest (353 m) monthly median BL height occurs in February and the deepest (576 m) in June. In winter there is no diurnal cycle in BL height; unstable BLs are rare, yet so are very stable BLs. The shallowest BLs occur at night in spring and summer, and very stable conditions are most common at night in the warm season. Finally, using ERA5 gridded data, we determined that the BL height observed at Hyytiälä is representative of most land areas in southern and central Finland. However, the spatial variability of the BL height is largest during daytime in summer, reducing the area over which BL height observations from Hyytiälä would be representative.

Weather Forecasting-Chemistry (WRF-Chem) is an air pollution model that combines meteorological factors and atmospheric chemistry simultaneously (online coupled). Many schemes selected on WRF-Chem according to boundary layer conditions of the study area. The objectives of this study were to evaluate WRF-Chem model and analyze the sensitivity of Yonsei University (YSU) scheme and Mellor Yamada Janjic (MYJ) scheme as physical boundary layer parameters, especially for Jakarta region. Particulate matter 10 micrometers or less in diameter (PM10) selected as the air pollutant parameter. The model outputs compared to observational data in five locations in Jakarta. The regression analysis between air temperature data shows that the values of R2 are 0.5 - 0.6 in February and 0.5 - 0.9 in August. Another result, the wind velocity from WRF-Chem overestimates but the hourly averages have a similar diurnal pattern with the observation. The PM10 concentration model output is underestimated which is caused by local emissions that are not accommodated in the model. The sensitivity analysis shows a higher sensitivity index for MYJ than YSU scheme, especially in August, so the model outcome of the MYJ scheme has a good response to the observations in Jakarta. It is seen that the extreme concentration of PM10 produced through the WRF-Chem with both schemes in February and August have the same time in morning. The model output of WRF-Chem through both schemes also demonstrate the minimum concentration of PM10 that follows during afternoon. The Planetary Boundary Layer (PBL) height analysis shows that in morning until noon, the PBL height with MYJ scheme is lower than YSU. It is different for other hours, that from the afternoon through the night until next morning, the height of PBL with MYJ scheme is thicker than YSU. At the point when the PBL is high, the pollutants assorted in a more volume so the estimation of the pollutant concentration estimated on the surface will be reduced.

The Atmospheric Boundary Layer (ABL) height is a key parameter in air quality research as well as for numerical simulations and forecasts. The identification of thermally stable layers, often with radiosondes, has been a common approach for estimating ABL height, though with limited temporal coverage. Remote sensing techniques offer essentially continuous measurements. Nevertheless, ABL height retrievals from different methods can vary greatly when compared, which is particularly notable for topographically complex terrains, such as that surrounding Mexico City. This study, employing one year of data in Mexico City, reveals that the daytime convective boundary layer height (retrieved from Doppler lidar data) is typically lower than the aerosol layer height (retrieved from ceilometer data). Although both estimated heights evolved diurnally, the more elevated aerosol layer decays more slowly, suggesting that the mechanisms that elevate aerosols are not limited to convective motions. Additionally, both diurnal and seasonal variability are investigated, comparing remotely sensed-retrieved heights with thermally stable layers estimated from radiosonde data. Multiple stable layers often develop, those at higher levels have similar values to the ceilometer-retrieved heights, while stable layers at lower heights are similar to Doppler lidar height retrievals. The present research constitutes the first detailed analysis of ceilometer backscatter and Doppler lidar thresholding methods for estimating ABL height over Mexico City, and our results illustrate the complexity of mixing mechanisms on the ABL in this region of complex orography.

Abstract. Accurate boundary layer structure and height are critical in the analysis of the features of air pollutants and local circulation. Although surface-based remote sensing instruments provide a high temporal resolution of the boundary layer structure, there are numerous uncertainties in terms of the accurate determination of the atmospheric boundary layer heights (ABLHs). In this study, an algorithm for an integrated system for ABLH estimation (ISABLE) was developed and applied to the vertical profile data obtained using a ceilometer and a microwave radiometer in Seoul city, Korea. A maximum of 19 ABLHs were estimated via the conventional time-variance, gradient, wavelet, and clustering methods using the backscatter coefficient from the ceilometer. Meanwhile, several stable boundary layer heights were extracted through near-surface inversion and environmental lapse rate methods using the potential temperature from the microwave radiometer. The ISABLE algorithm can find an optimal ABLH from post-processing, such as k-means clustering and density-based spatial clustering of applications with noise (DBSCAN) techniques. It was found that the ABLH determined using ISABLE exhibited more significant correlation coefficients and smaller mean bias and root mean square error between the radiosonde-derived ABLHs than those obtained using the most conventional methods. Clear skies exhibited higher daytime ABLH than cloudy skies, and the daily maximum ABLH was recorded in summer because of the more intense radiation. The ABLHs estimated by ISABLE are expected to contribute to the parameterization of vertical diffusion in the atmospheric boundary layer.

The planetary boundary layer height (PBLH) regulates air pollutant dispersion, yet the combined effects of aerosols and meteorology remain insufficiently quantified. Here, an interpretable XGBoost SHAP framework is applied to daytime (08:00–20:00 BJT) PBLH across the Beijing–Tianjin–Hebei (BTH) and Yangtze River Delta (YRD) regions using ERA5 and MERRA‐2 reanalysis data for 2013–2023. The mean PBLH in BTH (812 m) is about 125 m higher than in YRD (687 m), largely due to contrasting humidity conditions (46.3% vs. 68.6%). Meteorology dominates PBLH variability, with surface net solar radiation (SSR) and near‐surface wind speed correlating positively, whereas relative humidity (RH) is the opposite. Among aerosol factors, single‐scattering albedo (SSA) exerts the strongest influence (10.9% in BTH; 10.8% in YRD). In BTH, absorbing aerosols are associated with lower PBL more strongly than scattering aerosols, whereas in YRD neither type exerts dominant control. High RH enhances the hygroscopic growth of scattering aerosols, increasing the extinction efficiency and SSA and weakening the positive SSA–PBLH relationship, especially in YRD. Component‐specific analysis shows that hygroscopic components are identified as the major contributors to scattering extinction, with the sulfate effect markedly amplified under humid conditions. Seasonal analysis shows that thermal variables (SSR, RH) dominate the model in summer, while dynamic factors are more influential in winter, especially over BTH. These findings provide quantitative evidence for the coupled impacts of aerosols and meteorology, especially hygroscopic growth, on boundary layer dynamics, offering a scientific basis for region‐specific air quality management in eastern China.

The planetary boundary layer height (PBLH) is a fundamental variable of the planetary boundary layer (PBL). The effect of surface heterogeneity is challenging in the PBL parameterization for numerical weather and climate models. Here we use large eddy simulation data to investigate the impact of surface heating heterogeneity on the PBLH spatial variations and mean values over a domain of typical mesoscale model grid size. It is found that this impact depends on background wind condition. Variance decomposition and Fourier spectra both reveal that for the fully developed sheared convective PBL, surface heterogeneity contributes little to the spatial variation of PBLH, except for the case with heterogeneity scale of 14.4 km. This suggests that surface heterogeneity with length scales less than ∼10 km, which is typical for mesoscale modeling, does not induce significant subgrid spatial variation of PBLH. The domain‐averaged PBLH is found to generally increase as surface heterogeneity scale decreases, until reaching the scale on the order of PBLH. The findings can be used to inform the parameterization development of PBL processes over heterogeneous surface.