Previous studies have reported air pollution‐radiation interactions in the urban boundary layer (UBL), but vertical gradient variations in the radiation budget and heat flux under air pollution conditions are relatively sparse. In this study, based on gradient observations from the Beijing 325 m meteorological tower in December 2015, the characteristics of near‐surface radiation balance and energy budget at three levels under different pollution conditions were comparatively investigated. Relative to clean days, both downward and upward shortwave radiation (DSR and USR) dropped during daytime, while downward and upward longwave radiation (DLR and ULR) enhanced during nighttime on heavily polluted days, showing that with evaluated height, the drop magnitudes of DSR and USR decreased, while the enhancement magnitude of DLR (ULR) decreased (increased). The combined effects of four radiation components significantly induced the reduction in net radiation (R_n) on polluted days, leading to the near‐surface energy budget change. In addition, the monthly averaged anthropogenic heat flux (Q_f) was estimated to quantitatively calculate the heat storage (G) term in the surface energy budget. During daytime, compared to the clean episodes, the sensible heat flux (H) was reduced more than R_n in the whole near‐surface UBL during heavy polluted episodes, resulting in smaller H/(R_n + Q_f) and larger G/(R_n + Q_f). Finally, we revealed that weak thermal forcing effects caused by insufficient availability of net radiation energy at the surface and weak dynamic motion associated with weak winds were both responsible for the larger reduction (increase) in H (G) during pollution episodes in the whole near‐surface UBL.

The important roles that the atmospheric boundary layer (ABL) plays in the central Arctic climate system have been recognized, but the atmospheric boundary layer height (ABLH), defined as the layer of continuous turbulence adjacent to the surface, has rarely been investigated. Using a year-round radiosonde dataset during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, we improve a Richardson-number-based algorithm that takes cloud effects into consideration and subsequently analyze the characteristics and variability of the ABLH over the Arctic Ocean. The results reveal that the annual cycle is clearly characterized by a distinct peak in May and two respective minima in January and July. This annual variation in the ABLH is primarily controlled by the evolution of the ABL thermal structure. Temperature inversions in the winter and summer are intensified by seasonal radiative cooling and warm-air advection with the surface temperature constrained by melting, respectively, leading to the low ABLH at these times. Meteorological and turbulence variables also play a significant role in ABLH variation, including the near-surface potential temperature gradient, friction velocity, and turbulent kinetic energy (TKE) dissipation rate. In addition, the MOSAiC ABLH is more suppressed than the ABLH during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment in the summer, which indicates that there is large variability in the Arctic ABL structure during the summer melting season.

The planetary boundary layer height (PBLH) is a crucial indicator reflecting the region of the atmosphere characterized by continuous turbulence. Here, we use radiosonde and surface meteorological observations (4–7 times per day, year‐round measurements) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition to derive the PBLH (PBLH_MOSAiC), and further evaluate the PBLH from the ERA5 reanalysis (PBLH_ERA5). Comparisons between PBLH_MOSAiC and PBLH_ERA5 from different perspectives reveal that: (a) The overestimation of PBLH_ERA5 when the sea ice concentration is >90% is significant with the centered root mean squared error reaching up to 201 m; (b) The difference between the two products is notably pronounced in cold seasons, while it is comparatively diminished in warm seasons; (c) In neutral boundary layers, differences in PBLH_ERA5 are larger compared with stable and convective boundary layers. In addition, the analysis of error sources indicates that the bias of PBLH_ERA5 is sensitive to the bias of vertical thermal structure and wind speed profiles in ERA5 data sets in all conditions. Finally, we find a Random Forest model effectively reduces the bias of PBLH_ERA5 with the index of agreement reaching up to 0.71 in the test data set, while a multiple linear regression demonstrates comparable performance to the Random Forest model.

The effects of atmospheric thermal structure on the surface energy flux are poorly understood over the Arctic sea‐ice surface. Here, we explore the mechanism of sensible heat exchange under different types of thermal structures over the Arctic sea‐ice surface by using data collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition. The quadrant analysis indicates that strong surface temperature inversions below 100 m enhance non‐local effects on the positive (upward) sensible heat flux () through entrainment of large eddies from the convective boundary layer aloft. However, strong surface inversions restrict the contributions of large eddies to the negative (downward) due to intensified surface stability. By inspecting the existing parameterization schemes, we found that the European Center for Medium‐Range Weather Forecasts Integrated Forecasting System scheme fails to predict the impacts of non‐local processes on the positive , and an adjustment term to correct the bias of parameterized is proposed.

By analyzing the data collected over a rice paddy field in China, the occurrence of large drag coefficient in light winds (U ≤ 1ms⁻¹) under near‐neutral conditions (−0.1 ≤ z/L ≤ 0.1) is analyzed in this study. It is found that, with the use of either vector‐ or scalar‐averaged wind speed, the drag coefficient under near‐neutral conditions (C_DN) always increases with the decrease of wind speed. Such behavior of C_DN cannot be interpreted by the change of aerodynamic roughness length z₀ because it would need to be enlarged by an order of magnitude. While in light winds, the nonlocal transport, which is caused by large‐scale eddies and overlooked by traditional Monin‐Obukhov Similarity theory, is found to be the main cause of increased C_DN. At last, a fixing term related to nonlocal effects is proposed based on our observation, and its applicability is verified with two AmeriFlux observation sites with a landscape of forest and savanna, respectively.

Freezing temperature parameterization significantly impacts the heat balance at sea‐ice bottom and, consequently, the simulated sea‐ice thickness. Here, the single‐column model ICEPACK was used to investigate the impact of the freezing temperature parameterization on the simulated sea‐ice thermodynamic growth during the MOSAiC expedition from October 2019 to September 2020. It is shown that large model errors exist with the standard parameterization and that different formulations for calculating the freezing temperature impact the simulated sea‐ice thickness significantly. Considering the winter mixed layer temperature, a modified parameterization of the freezing point temperature based on Mushy scheme was developed. The mean absolute error (ratio) of simulating sea‐ice thickness for all buoys reduces from 7.4 cm (4.9%) with the “Millero” scheme, which performs the best among the existing schemes in the ICEPACK model, to 4.2 cm (2.9%) with the new developed scheme.