Description: The Rossby radius of deformation is a parameter that describes the relative role of buoyant and inertial forces for atmospheric phenomena in a flow regime. It will be demonstrated that it can also be used to determine whether or not forcing for vertical motions in the region between upper level tropospheric jet streaks overlaps or interacts. Using predefined points in the entrance and exit regions of neighboring upper level jet streaks, the distance between them is calculated for each event. If they are closer than twice the Rossby radius of deformation, the resulting region affected by both streaks is termed the Rossby Radius of Deformation Overlap Zone (RRDOZ). Plan-view and cross-sectional analysis shows that ageostrophic transverse circulations within the RRDOZ led to enhanced upward vertical velocities as predicted in prior research. Lastly, a short-term climatology for overlap events in North America is derived, and these are classified according to three proposed archetypes.

Description: Though land use regression (LUR) models have been widely utilized to simulate air pollution distribution, unclear spatial scale effects of contributing characteristic variables usually make results study-specific. In this study, LUR models for PM2.5 in Houston Metropolitan Area, US were developed under scales of 100 m, 300 m, 500 m, 800 m, and 1000–5000 m with intervals of 500 m by employing the idea of statistically optimized analysis. Results show that the annual average PM2.5 concentration in Houston was significantly influenced by area ratios of open space urban and medium intensity urban at a 100 m scale, as well as of high intensity urban at a 500 m scale, whose correlation coefficients valued −0.64, 0.72, and 0.56, respectively. The fitting degree of LUR model at the optimized spatial scale (adj. R2 = 0.78) is obviously better than those at any other unified spatial scales (adj. R2 ranging from 0.19 to 0.65). Differences of PM2.5 concentrations produced by LUR models with best-, moderate-, weakest fitting degree, as well as ordinary kriging were evident, while the LUR model achieved the best cross-validation accuracy at the optimized spatial scale. Results suggested that statistical based optimized spatial scales of characteristic variables might possibly ensure the performance of LUR models in mapping PM2.5 distribution.

Description: A cell-ratio constant false-alarm rate (CR-CFAR) method for detecting the Doppler frequency shift is proposed to improve the accuracy of velocity measured by coherent Doppler wind lidar (CWL) in low signal-to-noise ratio (SNR) environments. The method analyzes the spectrum to solve issues of weak signal submergence in noise encountered in the widely used periodogram method. This characteristic is that the signal region slope is larger than the noise region slope in the frequency spectrum. We combined the ratio and CFAR to propose the CR-CFAR method. The peak area is discriminated from the spectrum using this method. By removing background noise, the peak signal is obtained along with the Doppler shift. To verify the CR-CFAR method, a campaign experiment using both CWL and a commercial Doppler lidar was performed in Hami, China (42°32′ N, 94°03′ E) during 1–7 June 2016. The results showed that the proposed method significantly improved the reliability of CWL data under low SNR conditions. The height—at which both horizontal wind speed correlativity and horizontal wind direction correlativity exceeded 0.99—increased by 65 m. The relative deviation of the horizontal wind speed at 120 m decreased from 40.37% to 11.04%. We used the CR-CFAR method to analyze continuous data. A greater number of wind field characteristics were obtained during observation compared to those obtained using the common wind field inversion method.

Description: In order to improve the performance of X-band dual-polarization radars, it is necessary to conduct attenuation correction before using the X-band radar data. This study analyzes a variety of attenuation correction methods for the X-band radar reflectivity, and proposes a high-resolution slide self-consistency correction (SSCC) method, which is an improvement of Kim et al.’s method based on Bringi et al.’s original method. The new method is comprehensively evaluated with the observational data of convective cloud, stratiform cloud, and the stratiform cloud with embedded convection. Comparing with the intrinsic reflectivity at X-band calculated from the reflectivity at S-band, it is found that the new method can effectively reduce the correction errors when calculating differential propagation shift increments using the conventional self-consistency attenuation correction method. This method can efficiently correct the X-band dual-polarization radar reflectivity, in particular, for the echoes with reflectivity greater than 35 dBZ.

Description: Here, we report the chemical characterization and identification of the possible sources of particulate matter (fraction PM10) at two different sites in Naples. PM10 concentration and its chemical composition were studied using the crustal enrichment factor (EF) and principal component analysis (PCA). In all of the seasons, the PM10 levels, were significantly higher (p 〈 0.01) in the urban-traffic site (denominated NA02) than in the urban-background site (denominated NA01). In order to reconstruct the particle mass, the components were classified into seven classes as follows: mineral dust (MD), trace elements (TE), organic matter (OM), elemental carbon (EC), sea salt (SS), secondary inorganic aerosol (SIA) and undetermined parts (unknown (UNK)). According to the chemical mass closure obtained, the major contribution was OM, which was higher (p 〈 0.01) during summer than in other seasons. In both sites, a good correlation (R2 > 0.8) was obtained between reconstructed mass and gravimetric mass. PCA analysis explained 76% and 79% of the variance in NA01 and NA02, respectively. The emission sources were the same for both sites; but, the location of the site, the different distances from the sources and the presence and absence of vegetation proved the different concentrations and compositions of PM10.

Description: In this study, we investigate the sources of moisture (and moisture for precipitation) over the Danube River Basin (DRB) by means of a Lagrangian approach using the FLEXPART V9.0 particle dispersion model together with ERA-Interim reanalysis data to track changes in atmospheric moisture over 10-day trajectories. This approach computes the budget of evaporation-minus-precipitation by calculating changes in specific humidity along forward and backward trajectories. We considered a time period of 34 years, from 1980 to 2014, which allowed for the identification of climatological sources and moisture transport towards the basin. Results show that the DRB mainly receives moisture from seven different oceanic, maritime, and terrestrial moisture source regions: North Atlantic Ocean, North Africa, the Mediterranean Sea, Black Sea, Caspian Sea, the Danube River Basin, and Central and Eastern Europe. The contribution of these sources varies by season. During winter (October–March) the main moisture source for the DRB is the Mediterranean Sea, while during summer (April–September) the dominant source of moisture is the DRB itself. Moisture from each source has a different contribution to precipitation in the DRB. Among the sources studied, results show that the moisture from the Mediterranean Sea provides the greatest contribution to precipitation in the basin in both seasons, extending to the whole basin for the winter, but being more confined to the western side during the summer. Moisture from the Caspian and Black Seas contributes to precipitation rather less.

Description: Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) is an important satellite precipitation product of Global Precipitation Measurement (GPM) mission. Quantitative information about the errors of IMERG has great significance for the data developers and end users. In order to investigate the characteristics and the source of the errors contained in IMERG, a bias-decomposition scheme was employed to evaluate the hourly IMERG over the eastern part of Mainland China during the warm season. First, the total bias of IMERG before and after calibration (termed as precipitationUncal and precipitationCal) was calculated using rain gauge measurements as reference. Then the bias was decomposed into three independent components including false bias, missed bias, and hit bias. Finally, the hit bias was further decomposed according to the rainfall intensity measured by rain gauges. The results indicate that (1) the bias of precipitationUncal over the north part is dominated by hit bias and false bias, leading to the serious overestimation for the precipitation over this area, but it underestimates the precipitation over the south part with the false bias and missed bias acting as major contributors; (2) the precipitationCal overestimates the precipitation over more than 80% of the study areas mainly as a result of a large amplitude of false bias; (3) the calibration algorithm used by IMERG could not reduce the missed bias and enlarges the false bias over some regions, revealing a shortcoming of this algorithm in that it could not effectively alleviate the bias resulting from the rain areas delineation; (4) the hit bias of IMERG is strongly related with the rainfall intensity of rain gauge measurements, which should be beneficial for reducing the errors of IMERG. This study provides a deep insight into the characteristics and sources of the biases inherent in IMERG, which is significant for its utilization and possible correction in future.

Description: Ground-based monitoring networks for evaluating atmospheric composition relevant to impacts on human health and the environment now exist worldwide (according to the United Nations Environment Programme, 48% of countries have an air quality monitoring system). Of course, this has not always been the case. Here, we analyse for the first time the key developments in network coordination and standardisation over the last 150 years that underpin the current implementations of city-scale to global monitoring networks for atmospheric composition. Examples include improvements in respect of site type and site representativeness, measurement methods, quality assurance, and data archiving. From the 1950s, these developments have progressed through two distinct types of network: those designed for the protection of human health, and those designed to increase scientific understanding of atmospheric composition and its interaction with the terrestrial environment. The step changes in network coordination and standardisation have increased confidence in the comparability of measurements made at different sites. Acknowledged limitations in the current state of monitoring networks include a sole focus on compliance monitoring. In the context of the unprecedented volumes of atmospheric composition data now being collected, we suggest the next developments in network standardisation should include more integrated analyses of monitor and other relevant data within “chemical climatology” frameworks that seek to more directly link the impacts, state and drivers of atmospheric composition. These approaches would also enhance the role of monitoring networks in the development and evaluation of air pollution mitigation strategies.

Description: In this work, the feasibility of estimating rain rate based on polarimetric Global Navigation Satellite Systems (GNSS) signals is explored in theory. After analyzing the cause of polarimetric signals, three physical-mathematical relation models between co-polar phase shift (KHH, KVV), specific differential phase shift (KDP), and rain rate (R) are respectively investigated. These relation models are simulated based on four different empirical equations of nonspherical raindrops and simulated Gamma raindrop size distribution. They are also respectively analyzed based on realistic Gamma raindrop size distribution and maximum diameter of raindrops under three different rain types: stratiform rain, cumuliform rain, and mixed clouds rain. The sensitivity of phase shift with respect to some main influencing factors, such as shape of raindrops, frequency, as well as elevation angle, is also discussed, respectively. The numerical results in this study show that the results by scattering algorithms T-matrix are consistent with those from Rayleigh Scattering Approximation. It reveals that they all have the possibility to estimate rain rate using the KHH-R, KVV-R or KDP-R relation. It can also be found that the three models are all affected by shape of raindrops and frequency, while the elevation angle has no effect on KHH-R. Finally, higher frequency L1 or B1 and lower elevation angle are recommended and microscopic characteristics of raindrops, such as shape and size distribution, are deemed to be important and required for further consideration in future experiments. Since phase shift is not affected by attenuation and not biased by ground clutter cancellers, this method has considerable potential in precipitation monitoring, which provides new opportunities for atmospheric research.

Description: Dust storms and sandy dust events originating in arid and semi-arid areas can transport particulate material, pollutants, and potential transport long distances from their sources. Exposure to desert dust particles is generally acknowledged to endanger human health. However, most studies have examined anthropogenic particulate sources, with few studies considering contributions from natural desert dust. A systematic literature review was undertaken using the ISI Web of Knowledge and PubMed databases with the objective of identifying all studies presenting results on the potential health impact from desert dust particles across the world. This review reveals an imbalance between the areas most exposed to dust and the areas most studied in terms of health effects. Among the human health effects of dust storms are mortality and morbidity, arising from respiratory system, circulatory system, and other diseases. We summarize the quantitative results of current scientific health research and possible pathological mechanisms, and describe some of the many challenges related to understanding health effects from exposures to desert dust particles. Overall, for respiratory and circulatory mortality, both positive and negative associations have been reported for PM10 of desert dust, but only a positive relationship was reported between PM2.5–10 and mortality, and a positive relationship was also reported between PM2.5 and human mortality. Future pathological studies should continue to focus on those mechanisms causing the most harmful effect of desert dust on respiratory and cardiovascular diseases. More attention should also be paid to the association between desert dust and the morbidity of other diseases, such as those affecting the reproductive system and nervous system.