Open AccessArticle
Evaluating the Relationship between Field Aerodynamic Roughness and the MODIS BRDF, NDVI, and Wind Speed over Grassland
Atmosphere 2017, 8(1), 16; doi:10.3390/atmos8010016 (registering DOI) -
Abstract
Aerodynamic roughness (AR) is an important parameter that influences the momentum and energy exchange between the earth’s surface and the atmosphere. In this study, profile wind data observed during the vegetation growing period (April–September) in 2013 and 2014 at the A’rou grassland station,
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Aerodynamic roughness (AR) is an important parameter that influences the momentum and energy exchange between the earth’s surface and the atmosphere. In this study, profile wind data observed during the vegetation growing period (April–September) in 2013 and 2014 at the A’rou grassland station, which is in the upstream of the Heihe River Basin (HRB), were used to determine the relationship between the field AR and the Moderate-resolution Imaging Spectroradiometer (MODIS) near-infrared (NIR) bi-directional reflectance distribution function (BRDF) R index, the normalized difference vegetation index (NDVI), and a combination of these indices. In addition, the relationship between the average wind speed at a height of 1 m and the field AR is also presented. The results indicate that the MODIS NIR BRDF_R index and the NDVI are both sensitive indicators of the AR over grassland (R2: 0.5228 for NIR BRDF_R; R2: 0.579 for NDVI). Moreover, the combined index shows a significantly increased R2 value of 0.721, which is close to the result inferred from the wind speed (R2: 0.7411). The proposed remote sensing-based combination index (CI) has the potential for use in evaluations of the AR over grasslands during growing season and its sensitivity can reach levels that are comparable to considering the effects of wind speed, which usually requires ground-based observations. Full article
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Open AccessArticle
Lidar and Ceilometer Observations and Comparisons of Atmospheric Cloud Structure at Nagqu of Tibetan Plateau in 2014 Summer
Atmosphere 2017, 8(1), 9; doi:10.3390/atmos8010009 (registering DOI) -
Abstract
In the project of the Third Tibetan Plateau Experiment of Atmospheric Science (TIPEX III), the intensive observation of cloud and precipitation in Nagqu was conducted from 1 July to 31 August 2014. The CL31 ceilometer and a WAter vapor, Cloud and Aerosol Lidar
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In the project of the Third Tibetan Plateau Experiment of Atmospheric Science (TIPEX III), the intensive observation of cloud and precipitation in Nagqu was conducted from 1 July to 31 August 2014. The CL31 ceilometer and a WAter vapor, Cloud and Aerosol Lidar (WACAL) were deployed and focused on studying the cloud macroscopic characteristics and vertical distribution. The statistical result of CL31 ceilometer in continuous operation mode shows that the cloud occurrence is about 81% with a majority of simple one-layer cloud. The cloud base and top height are retrieved by improved differential zero-crossing method using lidar data. The results of cloud base height (CBH) are compared with CL31 ceilometer, showing a good consistency with each other, however, in some cases, the CL31 ceilometer overestimates the CBH and is also validated by synchronous radiosonde data. The time snippet comparisons of cloud property between CL31 ceilometer and lidar imply that the cloud properties have obvious diurnal variations with “U” shape distribution. The cloud development including the time-spatial distribution features also has distinct diurnal variations based on the lidar measurement. The detection range of lidar goes beyond the maximum height of CL31 ceilometer, offering substantial observations to the analysis of cirrus cloud radiation characteristics and formation mechanism. Full article
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Open AccessArticle
Evaluation of Surface Clutter for Future Geostationary Spaceborne Weather Radar
Atmosphere 2017, 8(1), 14; doi:10.3390/atmos8010014 (registering DOI) -
Abstract
Surface clutter interference will be one of the important problems for the future of geostationary spaceborne weather radar (GSWR). The aim of this work is to provide some numerical analyses on surface clutter interference and part of the performance evaluation for the future
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Surface clutter interference will be one of the important problems for the future of geostationary spaceborne weather radar (GSWR). The aim of this work is to provide some numerical analyses on surface clutter interference and part of the performance evaluation for the future implementation of GSWR. The received powers of rain echoes, land and sea surfaces from a radar scattering volume are calculated numerically based on the derived radar equations, assuming a uniform rain layer and appropriate land and sea surface scattering models. An antenna pattern function based on a Bessel curve and Taylor weighting is considered to approximate the realistic spherical antenna of a GSWR. The power ratio of the rain echo signal to clutter (SCR) is then used to evaluate the extension of surface clutter interference. The study demonstrates that the entire region of surface clutter interference in GSWR will be wider than those in tropical rainfall measuring mission precipitation radar (TRMM PR). Most strong surface clutter comes from the antenna mainlobe, and the decrease of clutter contamination through reducing the level of the antenna sidelobe and range sidelobe are not obvious. In addition, the clutter interference is easily affected by rain attenuation in the Ka-band. When rain intensity is greater than 10 mm/h, most of rain echoes at off-nadir scanning angles will not be interfered by surface clutter. Full article
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Open AccessArticle
Projected Changes in Temperature Extremes in China Using PRECIS
Atmosphere 2017, 8(1), 15; doi:10.3390/atmos8010015 (registering DOI) -
Abstract
Temperature extremes can cause disastrous impacts on ecological and social economic systems. China is very sensitive to climate change, as its warming rate exceeds that of the global mean level. This paper focused on the spatial and temporal changes of the temperature extremes
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Temperature extremes can cause disastrous impacts on ecological and social economic systems. China is very sensitive to climate change, as its warming rate exceeds that of the global mean level. This paper focused on the spatial and temporal changes of the temperature extremes characterized by the 95th percentile of maximum temperature (TX95), the 5th percentile of the minimum temperature (TN5), high-temperature days (HTD) and low-temperature days (LTD). The daily maximum and minimum temperatures generated by PRECIS under different Representative Concentration Pathways (RCPs) are used in the research. The results show that: (1) Model simulation data can reproduce the spatial distribution features of the maximum temperature (Tmax) and minimum temperature (Tmin) as well as that of the extreme temperature indices; (2) By the end of the 21st century (2070–2099), both the Tmax and Tmin are warmer than the baseline level (1961–1990) in China and the eight sub-regions. However, there are regional differences in the asymmetrical warming features, as the Tmin warms more than the Tmax in the northern part of China and the Tibetan Plateau, while the Tmax warms more than the Tmin in the southern part of China; (3) The frequency of the warm extremes would become more usual, as the HTD characterized by the present-day threshold would increase by 106%, 196% and 346%, under RCP2.6, RCP4.5 and RCP8.5, respectively, while the cold extremes characterized by the LTD would become less frequent by the end of the 21st century, decreasing by 75%, 90% and 98% under RCP2.6, RCP4.5 and RCP8.5, respectively. The southern and eastern parts of the Tibetan Plateau respond sensitively to changes in both the hot and cold extremes, suggesting its higher likelihood to suffer from climate warming; (4) The intensity of the warm (cold) extremes would increase (decrease) significantly, characterized by the changes in the TX95 (TN5) by the end of the 21st century, and the magnitude of the increase in the TN5 is larger than that of the TX95 in the national mean value. The changes in both the TX95 and TN5 are larger under the higher versus weaker emission scenario, indicating that it is essential to reduce the GHG emissions and take adaptation measures in the future. Full article
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Open AccessArticle
Ensemble Classification for Anomalous Propagation Echo Detection with Clustering-Based Subset-Selection Method
Atmosphere 2017, 8(1), 11; doi:10.3390/atmos8010011 -
Abstract
Several types of non-precipitation echoes appear in radar images and disrupt the weather forecasting process. An anomalous propagation echo is an unwanted observation result similar to a precipitation echo. It occurs through radar-beam ducting because of the temperature, humidity distribution, and other complicated
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Several types of non-precipitation echoes appear in radar images and disrupt the weather forecasting process. An anomalous propagation echo is an unwanted observation result similar to a precipitation echo. It occurs through radar-beam ducting because of the temperature, humidity distribution, and other complicated atmospheric conditions. Anomalous propagation echoes should be removed because they make weather forecasting difficult. In this paper, we suggest an ensemble classification method based on an artificial neural network and a clustering-based subset-selection method. This method allows us to implement an efficient classification method when a feature space has complicated distributions. By separating the input data into atomic and non-atomic clusters, each derived cluster will receive its own base classifier. In the experiments, we compared our method with a standalone artificial neural network classifier. The suggested ensemble classifier showed 84.14% performance, which was about 2% higher than that of the k-means clustering-based ensemble classifier and about 4% higher than the standalone artificial neural network classifier. Full article
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Open AccessArticle
Contemporary Temperature Fluctuation in Urban Areas of Pakistan
Atmosphere 2017, 8(1), 12; doi:10.3390/atmos8010012 -
Abstract
Annual temperature data from thirty meteorological stations in Pakistan’s major urban areas were selected to investigate trends in annual average and maximum temperature during 1970–2009. A combination of parametric and non-parametric tests including linear regression, the Mann-Kendall trend test and Sen’s slope estimator
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Annual temperature data from thirty meteorological stations in Pakistan’s major urban areas were selected to investigate trends in annual average and maximum temperature during 1970–2009. A combination of parametric and non-parametric tests including linear regression, the Mann-Kendall trend test and Sen’s slope estimator was used for the analysis. Annual average and maximum temperature series showed an overall increasing trend for 90% of the stations and a decreasing trend for 10% of the stations in the study area. The highest significant increment of annual average temperature was observed at Gilgit, Hyderabad, Quetta and Lasbela stations at the rate of 0.49 °C per decade. The highest increment of annual maximum temperature was obtained at Chitral, Gilgit, Nawabshah and Quetta at the rate of 0.31 °C per decade. According to simple linear regression and the Mann-Kendall test, the annual average temperature showed a significant increasing trend for 43% of the stations (at a 0.001 level of significance) and 23% of the stations (at the 0.05 level). Annual maximum temperature showed a significant increasing trend for 26% of the stations (at the 0.001 level of significance) and 23% of the stations (at the 0.05 level). In general, the results showed increasing trends for the considered parameters, although annual average temperature showed a higher increasing rate than annual maximum temperature during the study period. Full article
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Open AccessArticle
Water Tank Experiments on Stratified Flow over Double Mountain-Shaped Obstacles at High-Reynolds Number
Atmosphere 2017, 8(1), 13; doi:10.3390/atmos8010013 -
Abstract
In this article, we present an overview of the HyIV-CNRS-SecORo (Hydralab IV-CNRS-Secondary Orography and Rotors Experiments) laboratory experiments carried out in the CNRM (Centre National de Recherches Météorologiques) large stratified water flume. The experiments were designed to systematically study the influence of double
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In this article, we present an overview of the HyIV-CNRS-SecORo (Hydralab IV-CNRS-Secondary Orography and Rotors Experiments) laboratory experiments carried out in the CNRM (Centre National de Recherches Météorologiques) large stratified water flume. The experiments were designed to systematically study the influence of double obstacles on stably stratified flow. The experimental set-up consists of a two-layer flow in the water tank, with a lower neutral and an upper stable layer separated by a sharp density discontinuity. This type of layering over terrain is known to be conducive to a variety of possible responses in the atmosphere, from hydraulic jumps to lee waves and highly turbulent rotors. In each experiment, obstacles were towed through the tank at a constant speed. The towing speed and the size of the tank allowed high Reynolds-number flow similar to the atmosphere. Here, we present the experimental design, together with an overview of laboratory experiments conducted and their results. We develop a regime diagram for flow over single and double obstacles and examine the parameter space where the secondary obstacle has the largest influence on the flow. Trapped lee waves, rotors, hydraulic jumps, lee-wave interference and flushing of the valley atmosphere are successfully reproduced in the stratified water tank. Obstacle height and ridge separation distance are shown to control lee-wave interference. Results, however, differ partially from previous findings on the flow over double ridges reported in the literature due to the presence of nonlinearities and possible differences in the boundary layer structure. The secondary obstacle also influences the transition between different flow regimes and makes trapped lee waves possible for higher Froude numbers than expected for an isolated obstacle. Full article
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Open AccessArticle
Predicting PM2.5 Concentrations at a Regional Background Station Using Second Order Self-Organizing Fuzzy Neural Network
Atmosphere 2017, 8(1), 10; doi:10.3390/atmos8010010 -
Abstract
This study aims to develop a second order self-organizing fuzzy neural network (SOFNN) to predict the hourly concentrations of fine particulate matter (PM2.5) for the next 24 h at a regional background station called Shangdianzi (SDZ) in China from 14 to
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This study aims to develop a second order self-organizing fuzzy neural network (SOFNN) to predict the hourly concentrations of fine particulate matter (PM2.5) for the next 24 h at a regional background station called Shangdianzi (SDZ) in China from 14 to 23 January 2010. The structure of the SOFNN was automatically adjusted according to the sensitivity analysis (SA) of model output and the parameter-learning phase was performed applying a second order gradient (SOG) algorithm. Principal component analysis (PCA) was employed to select the dominating factors for PM2.5 concentrations as the input variables for the SOFNN. It was found that the dominating variables (relative humidity (RH), pressure (Pre), aerosol optical depth (AOD), wind speed (WS) and wind direction (WD)) extracted by PCA agreed well with the characteristics of PM2.5 at SDZ where the PM2.5 concentrations were heavily affected by meteorological parameters and were closely related to AOD. The forecasting results showed that the proposed SOG-SASOFNN performed better than other models with higher coefficient of determination (R2) during both training phase and test phase (0.89 and 0.84, respectively) in predicting PM2.5 concentrations at SDZ. In conclusion, the developed SOG-SASOFNN provided satisfying results for modeling the hourly distribution of PM2.5 at SDZ during the studied period. Full article
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Open AccessArticle
Properties of the Long-Term Oscillations in the Middle Atmosphere Based on Observations from TIMED/SABER Instrument and FPI over Kelan
Atmosphere 2017, 8(1), 7; doi:10.3390/atmos8010007 -
Abstract
The properties of the long-term oscillations in the middle atmosphere have been investigated using the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) temperature data and Fabry–Perot interferometer (FPI) data. Results for SABER temperature show that the semiannual oscillation (SAO) has three
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The properties of the long-term oscillations in the middle atmosphere have been investigated using the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) temperature data and Fabry–Perot interferometer (FPI) data. Results for SABER temperature show that the semiannual oscillation (SAO) has three amplitude maxima at altitudes of 45, 75, and 85 km, respectively, and shows prominent seasonal asymmetries there. The SAOs in the upper mesosphere (75 km) are out of phase with those in the mesopause (85 km) in the tropical regions, which can generate an enhancement of 11 K on average at each equinox, contributing to the lower mesospheric inversion layer (MIL). It is shown that stronger enhancement can be found at the spring equinox than at the autumn equinox. The triennial oscillation (TO) is significant in the tropical region. The spectral peak of the TO is probably a sub-peak of the quasi-biennial oscillation (QBO) and is due to modulation of QBO. In addition, there may be potential interaction of the TO with SAO at 85 km at the equator. The relation between ENSO and TO has also been discussed. The ENSO signal may modulate the amplitude of the TO, mainly in the lower stratosphere. The annual oscillation (AO) and SAO are analyzed over Kelan by FPI data. Generally, the amplitudes of FPI wind are smaller than those of the Horizontal Wind Model (HWM07). The comparison between FPI and TIMED Doppler Interferometer (TIDI) winds shows relatively large discrepancy. This may be due to the tidal aliasing in the nighttime results derived from the FPI data. Results also show that the algorithm to derive FPI temperature needs improvements. Full article
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Open AccessEditorial
Acknowledgement to Reviewers of Atmosphere in 2016
Atmosphere 2017, 8(1), 8; doi:10.3390/atmos8010008 -
Abstract The editors of Atmosphere would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2016.[...] Full article
Open AccessArticle
A Geostatistics-Based Method to Determine the Pixel Distance in a Structure Function Model for Aerosol Optical Depth Inversion
Atmosphere 2017, 8(1), 6; doi:10.3390/atmos8010006 -
Abstract
Inversion of aerosol optical depth (AOD) over bright land surface by optical remote sensing is particularly challenging because surface reflectance dominates the satellite signal. A structure function method is suitable and can effectively solve aerosol optical depth inversion in high reflectance areas. How
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Inversion of aerosol optical depth (AOD) over bright land surface by optical remote sensing is particularly challenging because surface reflectance dominates the satellite signal. A structure function method is suitable and can effectively solve aerosol optical depth inversion in high reflectance areas. How to select d (the pixel distance between two pixels) value is one of the key problems with the structure function method. We present a method based on geostatistics, where variogram theory is referenced, to determine the pixel distance in structure function model for aerosol optical depth inversion. This method was validated by the Moderate Resolution Imaging Spectroradiometer (MODIS) 1 km resolution level 1B data from Beijing, China. The results indicate that the relationship between variogram and d in four different directions can be fitted by exponential function, of which correlation coefficients are all above 0.9. Compared with the MODIS aerosol product (MOD 04 product), the inversion AOD has higher accuracy, with an absolute error of −0.00187 instead of −0.00854 and a relative error of 0.99% instead of 4.35%, based on AERosol RObotic NETwork (AERONET) observations. For validation, we applied this new method separately to both Beijing–Tianjin–Hebei region and MODIS 500 m resolution images for region and resolution validation. The results show that inversion AOD has higher accuracy and more efficient pixels. Full article
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Open AccessArticle
Diagnosing Lee Wave Rotor Onset Using a Linear Model Including a Boundary Layer
Atmosphere 2017, 8(1), 5; doi:10.3390/atmos8010005 -
Abstract
A linear model is used to diagnose the onset of rotors in flow over 2D hills, for atmospheres that are neutrally stratified near the surface and stably stratified aloft, with a sharp temperature inversion in between, where trapped lee waves may propagate. This
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A linear model is used to diagnose the onset of rotors in flow over 2D hills, for atmospheres that are neutrally stratified near the surface and stably stratified aloft, with a sharp temperature inversion in between, where trapped lee waves may propagate. This is achieved by coupling an inviscid two-layer mountain-wave model and a bulk boundary-layer model. The full model shows some ability to diagnose flow stagnation associated with rotors as a function of key input parameters, such as the Froude number and the height of the inversion, in numerical simulations and laboratory experiments carried out by previous authors. While calculations including only the effects of mean flow attenuation and velocity perturbation amplification within the surface layer represent flow stagnation fairly well in the more non-hydrostatic cases, only the full model, taking into account the feedback of the surface layer on the inviscid flow, satisfactorily predicts flow stagnation in the most hydrostatic case, although the corresponding condition is unable to discriminate between rotors and hydraulic jumps. Versions of the model not including this feedback severely underestimate the amplitude of trapped lee waves in that case, where the Fourier transform of the hill has zeros, showing that those waves are not forced directly by the orography. Full article
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Open AccessArticle
Deposition of PM2.5 Sulfate in the Spring on Urban Forests in Beijing, China
Atmosphere 2017, 8(1), 3; doi:10.3390/atmos8010003 -
Abstract
Water-soluble ions such as sulfate may have great impacts on atmospheric pollution. To determine the deposition effect of PM2.5 sulfates, the major PM2.5 constituents, in the forest canopy in Beijing, China, an investigation was carried out in an urban forest, Olympic
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Water-soluble ions such as sulfate may have great impacts on atmospheric pollution. To determine the deposition effect of PM2.5 sulfates, the major PM2.5 constituents, in the forest canopy in Beijing, China, an investigation was carried out in an urban forest, Olympic Forest Park, and a suburban forest, Jiufeng National Forest Park. We measured the vertical distributions of sulfate by using monitoring towers in the two forests at the same times in March and May 2013. Sulfate (SO42−) was predominant in all PM2.5 water-soluble inorganic ions, with a proportion >40%. The vertical concentration of SO42− increased with height, and the average sulfate concentration in Olympic Forest Park was higher than that in Jiufeng National Forest Park. Results also revealed that meteorological conditions had significant impacts on both the sulfate concentration and the deposition velocity. In winter, the deposition of SO42− through the canopy was not obvious in the two forest parks, which was quite the opposite in spring. The deposition velocity in the daytime was higher than that in the nighttime in both Olympic Forest Park (0.9 ± 1.0 cm/s vs. 0.4 ± 0.3 cm/s) and Jiufeng National Forest Park (1.3 ± 1.2 cm/s vs. 0.8 ± 0.8 cm/s). While Jiufeng National Forest Park turned out to have a higher average sulfate deposition velocity than Olympic Forest Park. Full article
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Open AccessArticle
Characterization of Positive Cloud to Ground Flashes Observed in Indonesia
Atmosphere 2017, 8(1), 4; doi:10.3390/atmos8010004 -
Abstract
The characteristics of 77 electric field changes of positive cloud to ground (CG) flashes in the tropics of Indonesia were investigated. It was found that the arithmetic mean (AM) and geometric mean (GM) values for 0%–100% and 10%–90% rise time were 12.7 μs,
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The characteristics of 77 electric field changes of positive cloud to ground (CG) flashes in the tropics of Indonesia were investigated. It was found that the arithmetic mean (AM) and geometric mean (GM) values for 0%–100% and 10%–90% rise time were 12.7 μs, 11.9 μs and 6.1 μs, 5.8 μs, respectively. The percentages of single, double, and triple strokes of lightning flashes were 83% (64 cases), 16% (12 cases), and 1% (1 case), respectively. The AM and GM of the interstroke intervals and the return stroke (RS) amplitude ratios were 163.9 ms, 0.29, and 13.3 ms, 0.26, respectively. Furthermore, it was also found that 7 (9%) of 77 positive CG flashes had double peak return stroke waveforms with AM and GM values for 0%–100% and 10%–90% rise time of subsequent return strokes that were 6.7 μs, 6.4 μs and 4.1 μs, 4 μs, respectively. We inferred that these double peaks are produced by two ground terminations with a time interval varying from 7 to 560 μs. Full article
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Open AccessArticle
Assessing Upper Tropospheric Jet Streak Proximity Using the Rossby Radius of Deformation
Atmosphere 2017, 8(1), 2; doi:10.3390/atmos8010002 -
Abstract
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
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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. Full article
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Open AccessArticle
Land Use Regression Modeling of PM2.5 Concentrations at Optimized Spatial Scales
Atmosphere 2017, 8(1), 1; doi:10.3390/atmos8010001 -
Abstract
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
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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. Full article
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Open AccessArticle
Rain Attenuation Correction of Reflectivity for X-Band Dual-Polarization Radar
Atmosphere 2016, 7(12), 164; doi:10.3390/atmos7120164 -
Abstract
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
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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. Full article
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Open AccessArticle
Applications of Cell-Ratio Constant False-Alarm Rate Method in Coherent Doppler Wind Lidar
Atmosphere 2016, 7(12), 165; doi:10.3390/atmos7120165 -
Abstract
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
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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. Full article
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Open AccessArticle
Chemical Composition of PM10 at Urban Sites in Naples (Italy)
Atmosphere 2016, 7(12), 163; doi:10.3390/atmos7120163 -
Abstract
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
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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. Full article
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Open AccessArticle
Tracking the Origin of Moisture over the Danube River Basin Using a Lagrangian Approach
Atmosphere 2016, 7(12), 162; doi:10.3390/atmos7120162 -
Abstract
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
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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. Full article
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