Vertical wind shear (VWS) is one of the key meteorological factors in modulating ground-level particulate matter with an aerodynamic diameter of 2.5 µm or less (PM_2.5). Due to the lack of high-resolution vertical wind measurements, how the VWS affects ground-level PM_2.5 remains highly debated. Here we employed the wind profiling observations from the fine-time-resolution radar wind profiler (RWP), together with hourly ground-level PM_2.5 measurements, to explore the wind features in the planetary boundary layer (PBL) and their association with aerosols in Beijing for the period from December 1, 2018, to February 28, 2019. Overall, southerly wind anomalies almost dominated throughout the whole PBL or even beyond the PBL under polluted conditions during the course of a day, as totally opposed to the northerly wind anomalies in the PBL under clean conditions. Besides, the ground-level PM_2.5 pollution exhibited a strong dependence on the VWS. A much weaker VWS was observed in the lower part of the PBL under polluted conditions, compared with that under clean conditions, which could be due to the strong ground-level PM_2.5 accumulation induced by weak vertical mixing in the PBL. Notably, weak northbound transboundary PM_2.5 pollution mainly appeared within the PBL, where relatively small VWS dominated. Above the PBL, strong northerlies winds also favored the long-range transport of aerosols, which in turn deteriorated the air quality in Beijing as well. This was well corroborated by the synoptic-scale circulation and backward trajectory analysis. Therefore, we argued here that not only the wind speed in the vertical but the VWS were important for the investigation of aerosol pollution formation mechanism in Beijing. Also, our findings offer wider insights into the role of VWS from RWP in modulating the variation of PM_2.5, which deserves explicit consideration in the forecast of air quality in the future.

This study first quantifies the virga precipitation occurrence percentage using three spaceborne radar observations, including Tropical Rainfall Measuring Mission Precipitation Radar (PR), Global Precipitation Measurement dual‐frequency PR (Ku‐band PR/Ka‐band PR [KuPR/KaPR]), and CloudSat Cloud Profiling Radar (CPR). PR and KuPR/KaPR show that virga occurrence percentage is over 30% in arid regions (e.g., Sahara desert and deserts of Australia). CPR reveals similar virga geospatial distribution. However, the virga percentage based on CPR is about twice as large as that based on PR and KuPR/KaPR due to better detection sensitivity. Results also show that the majority of the virga clouds are altostratus and cirrus. Second, we investigate the virga precipitation contribution to the passive microwave radiometer false precipitation detection. Virga precipitation accounts for as much as 50% (30%) of Tropical Rainfall Measuring Mission Microwave Imager (Global Precipitation Measurement Microwave Imager) false detection results in arid regions. The underlying reason is because precipitation detection over land primarily relies on the ice scattering signature, while virga and light precipitation (e.g., 1 mm/hr) have similar amounts of ice water path in arid regions.

The non-hydrostatic atmospheric Model for Prediction Across Scales (MPAS-A), a global variable-resolution modeling framework, is applied at a range of resolutions from hydrostatic (60, 30, 16 km) to non-hydrostatic (4 km) scales using regional refinement over East Asia to simulate an extreme precipitation event. The event is triggered by a typical wind shear in the lower layer of the Meiyu front in East China on 25–27 June 2012 during the East Asian summer monsoon season. The simulations are evaluated using ground observations and reanalysis data. The simulated distribution and intensity of precipitation are analyzed to investigate the sensitivity to model configuration, resolution, and physics parameterizations. In general, simulations using global uniform-resolution and variable-resolution meshes share similar characteristics of precipitation and wind in the refined region with comparable horizontal resolution. Further experiments at multiple resolutions reveal the significant impacts of horizontal resolution on simulating the distribution and intensity of precipitation and updrafts. More specifically, simulations at coarser resolutions shift the zonal distribution of the rain belt and produce weaker heavy precipitation centers that are misplaced relative to the observed locations. In comparison, simulations employing 4 km cell spacing produce more realistic features of precipitation and wind. The difference among experiments in modeling rain belt features is mainly due to the difference in simulated wind shear formation and evolution during this event. Sensitivity experiments show that cloud microphysics have significant effects on modeling precipitation at non-hydrostatic scales, but their impacts are relatively small compared to that of convective parameterizations for simulations at hydrostatic scales. This study provides the first evidence supporting the use of convection-permitting global variable-resolution simulations for studying and improving forecasting of extreme precipitation over East China and motivates the need for a more systematic study of heavy precipitation events and the impacts of physics parameterizations and topography in the future. The key points are as follows. Model for Prediction Across Scales (MPAS) simulations at global uniform and variable resolutions share similar characteristics of precipitation and wind in the refined region. Numerical experiments reveal significant impacts of resolution on simulating the distribution and intensity of precipitation and updrafts. This study provides evidence supporting the use of convection-permitting global variable-resolution simulation to study extreme precipitation.

Mineral dust is the most important natural source of atmospheric ice nuclei (IN) which may significantly mediate the properties of ice cloud through heterogeneous nucleation and lead to crucial impacts on hydrological and energy cycle. The potential dust IN effect on cloud top temperature (CTT) in a well-developed mesoscale convective system (MCS) was studied using both satellite observations and cloud resolving model (CRM) simulations. We combined satellite observations from passive spectrometer, active cloud radar, lidar, and wind field simulations from CRM to identify the place where ice cloud mixed with dust particles. For given ice water path, the CTT of dust-mixed cloud is warmer than that in relatively pristine cloud. The probability distribution function (PDF) of CTT for dust-mixed clouds shifted to the warmer end and showed two peaks at about −45 °C and −25 °C. The PDF for relatively pristine cloud only show one peak at −55 °C. Cloud simulations with different microphysical schemes agreed well with each other and showed better agreement with satellite observations in pristine clouds, but they showed large discrepancies in dust-mixed clouds. Some microphysical schemes failed to predict the warm peak of CTT related to heterogeneous ice formation.

The current study investigates the potential impacts of Sahara dust on rainfall vertical structure over the Atlantic Ocean by employing multisensor satellite observations. The variabilities in rainfall vertical structure are decomposed by empirical orthogonal function (EOF) analysis. For a given near surface rain rate, the mean storm height of stratiform rain under dust‐laden condition is significantly higher than that under the dust‐free condition. The stratiform rain rate at the layers well above the freezing level is substantially enhanced under dust‐laden condition. Those changes may result from dynamic and thermodynamic effect of Sahara Air Layer effect and/or the effect that dust aerosol acting as additional ice nuclei. For convective rain, there is no significant difference in the leading three normalized EOF modes between the dust‐laden and dust‐free sectors, implying that dust effect, if exists, is not strong enough to cause evident changes in convective rainfall profiles. For stratiform rain, the EOF1 shows no signals of dust effect either. However, significant difference is found in the EOF2 and EOF3 modes between dust‐laden and dust‐free conditions. The normalized EOF2 and EOF3 under dust‐laden condition both represent enhanced rain rate at the upper layer well above the freezing level, where heterogeneous ice nucleation prevails. The statistical study shows consistent results with the case study, except that the aerosol‐related changes in stratiform rainfall vertical structure is isolated in the EOF3 only. This study suggests that EOF analysis is a promising way for isolating the potential and relatively weak aerosol effects on precipitation from the strong dynamic effects.

In this study, a simplified semiphysical retrieval algorithm for latent heat (LH) released from precipitation over the Tibetan Plateau is derived and analyzed. The physical basis of this algorithm is that the vertical gradient of rain rate (−dR/dZ or Γ) represents the temporal rate of rain formation based on the steady state assumption, and the precipitation formation rate is closely related to the cloud formation rate, which is directly proportional to the latent heating rate. In this algorithm, the LH rate is represented as a linear function of Γ with fixed slope and intercept term determined by 3‐month Weather Research and Forecasting Model simulations over the Tibetan Plateau. Comparison to model results shows that the retrieval scheme can correctly capture the main features of LH horizontally and vertically. Comparison with results from other two widely accepted LH algorithms using Global Precipitation Measurement Dual Precipitation Radar real observations shows that this retrieval scheme generally agrees with them over low‐altitude areas but yields more convective‐type LH over the highlands with a relatively low heating center. This algorithm is specially designed for application to high altitudes. With this algorithm and the associated coefficients provided, researchers can readily do LH retrieval in their cases of interest by themselves. The only required input is the vertical profile of rain rate, which is available from current satellite precipitation radar observations.