Due to the complex sources of aerosols in coastal regions in China. The Optical Properties of Aerosols and Clouds(OPAC) isn’t been able to cover the microphysical and optical properties of coastal mixed aerosols. This research employs an external mixing method to mix the maritime clean aerosols with other aerosol types in different proportions by volume. Four mixed aerosol environments were defined, which are clean marine-average continent environment (SS-CV), clean marine-polluted continent environment (SS-CP), clean marine-urban environment (SS-UR), and clean marine-desert environment (SS-DESERT). Simulation experiments were conducted on the aerosol optical parameters(including extinction coefficient (EXT) and LiDAR ratio (SA)) of these four environments at 550 nm and 1000nmwavelengths, in order to analyze the variation of aerosol optical parameters with relative humidity (RH) and component number density in different mixed environments. The results indicate that EXT of aerosols in the four mixed environments increased with RH in both wavelengths, and EXT of aerosols increased linearly with the number density of components. The variation of SA is influenced by multiple factors such as wavelengths, relative humidity, and Multi factor effects of relative humidity and component number density. For the SS-CV, SS-CP, and SS-UR mixtures, water soluble and accumulation mode sea salts have a greater influence on SA and EXT, while for the SS-DESERT mixture, accumulation mode mineral and mode sea salts particles have a more substantial effect. This study enhances the understanding and prediction of optical property changes in complex aerosol environments near marine regions.
We verify a simple alternative method to estimate the Fried parameter over a horizontal propagation path using the refractive index measured by a pair of micro-thermometers. The results show a relatively reliable estimate, especially when the optical turbulence in the path is relatively strong. Moreover, we also discuss the relationship between the Fried parameter value with the overall intensity of optical turbulence and the length of the propagation path theoretically. The influence of these two factors shows a prominent exponential characteristic, which also can be speculated from the formula.
In order to study the optical properties of aerosols in Qingdao, the temperature, humidity, wind speed and direction, and visibility were measured in Shinan District of Qingdao from 2019 to August 2020, and the seasonal variation characteristics of the optical thickness as well as Angstrom exponent in the area were analyzed using MODIS data. The analysis results found that particulate matter (PM) and relative humidity were the main factors affecting visibility. particulate matter concentration and visibility showed a negative exponential relationship. In the initial stage of PM governance, the improvement in visibility is not significant despite the reduction of particulate matter. However, once the PM concentration reaches a certain level, the improvement in visibility becomes remarkably evident. Analyzing the optical characteristics of Qingdao provides valuable insights into the local pollution control.
MODIS data and SEBS model were used to estimate the surface energy flux in Hefei City from March to December 2021. Verified by comparison with the EC measured values, and the sensitivity analysis of each parameter in the model was carried out. The results show that the net radiation flux(Rn) is the highest in September and the lowest in December. The Rn of water body is the highest, and urban area is the lowest. There was little correlation between soil heat flux(G) and seasonal variation. The main urban area and water body were higher, while the G was lower in the area with high vegetation coverage. The sensible heat flux(H) is obviously affected by the seasons, and the average H in December is the lowest, and even negative. Compared with the measured value, the average absolute error is 9W/m2, and the average relative error is 7%. The latent heat flux(LE) average absolute error between the inversion value and the measured value is 97W/m2, and the average relative error is 25.9%. The LE is relatively small in the main urban area, and relatively large in the area with high vegetation coverage. Sensitivity analysis of the model parameters was shows that the Rn is negatively correlated with the surface reflectance and surface temperature, and the expansion and contraction of air pressure, NDVI and wind speed have no effect on the Rn, G was negatively correlated with NDVI. Surface temperature and air temperature have the greatest influence on H and LE.
The atmospheric boundary layer is the layer most closely associated with human life, and the occurrence and development of atmospheric optical turbulence in the atmospheric boundary layer are of great significance for atmospheric optical transport, etc. Meanwhile, the study of optical turbulence in the whole ocean environment is also of vital importance, and it is important to statistically analyze the variations of the atmospheric optical turbulence parameters by using the existing optical turbulence models due to the lack of ocean data. In this paper, the atmospheric turbulence parameters are estimated by different external scale models (HMNSP99, Dewan, HV and WSTG models), and the atmospheric refractive index structure constant(C2n) computed by different models are compared by using the coastal sounding measured data, through error analysis and correlation studies, it has been found that the HV model changes with height in the atmospheric boundary layer, but cannot reflect the characteristics of the change of C2n well. The HMNSP99 model is about one order of magnitude smaller than the measured data, while the WSTG model is about one order of magnitude larger than the measured data. However, the trends of the two models are in good agreement. In contrast, the Dewan model and the HMNSP99 model show good consistency with the measured data, and the correlation is above 0.6. The Dewan and HMNSP99 model are closer in magnitude to the measured data, therefore, when studying optical turbulence parameters in the atmospheric boundary layer, the Dewan and HMNSP99 models are more reliable. They can also provide key indicators for optical turbulence prediction and astronomical site selection.
Aerosol scattering and absorption coefficients are important parameters that characterize the optical properties of aerosols, which have significant impacts on the radiation balance, air quality, and climate change of the Earth. In order to further improve the understanding of the relationship between aerosol optical properties and meteorological parameters in the offshore areas of Guangdong Maoming, the scattering and absorption coefficients of aerosols as well as meteorological parameters such as temperature, humidity, pressure, wind speed, wind direction, and visibility were measured. In this study, a prediction model of aerosol scattering and absorption coefficients based on the CatBoost algorithm was proposed using the measured data. Firstly, the measured data was preprocessed, and then a CatBoost algorithm model based on ensemble learning was constructed and trained. The Optuna framework was used to optimize the hyperparameters of the model to obtain the final aerosol scattering and absorption coefficient prediction model. Finally, the machine learning model was used to predict the scattering and absorption coefficients of aerosols in the offshore areas of Maoming. The model was compared with XGBoost and LightGBM algorithm models, and the mean squared error (MSE) and mean absolute error (MAE) were used as evaluation metrics to assess the accuracy of the model predictions. Based on the evaluation metrics, the CatBoost algorithm model based on Optuna automatic hyperparameter optimization performed the best among several models. The experimental results showed that when the training and testing data came from the same region, the MAE of the CatBoost algorithm model based on Optuna hyperparameter optimization was about 5.33, and the MSE was about 48.764, achieving a prediction accuracy of 90.88% for aerosol scattering and absorption coefficients.
KEYWORDS: Visibility, Machine learning, Education and training, Atmospheric modeling, Performance modeling, Meteorology, Data modeling, Solids, Random forests, Linear regression
Since there are many possible influencing factors of visibility, lightweight data requirements in practical applications of machine learning in visibility prediction can reduce the corresponding data observation cost and collection difficulty. By using the long-term measured data in Qingdao, this research comprehensively compares the performance of five common machine learning methods under different training parameter schemes, including XGBoost, LightGBM, Random Forest (RF), Support Vector Machine (SVM) and Multiple Linear Regression (MLR). The lightweight visibility prediction schemes based on pollutant parameter optimization are established. The seasonal training data of five machine learning models is preprocessed, and then performance evaluations of predictions are carried out. The analysis results show that in terms of models, ensemble learning models, including XGBoost, LightGBM, and RF, have significantly better seasonal visibility prediction effects than SVM and MLR models; XGBoost and LightGBM also have slightly better prediction effects than RF models. In terms of pollutant parameters, solid pollutants have a greater impact on visibility prediction than gaseous pollutants; PM2.5 is more influential than PM10 in visibility prediction. The visibility prediction scheme with six parameters using meteorological parameters and PM2.5 based on XGBoost or LightGBM model is preferably established in this research. This scheme can achieve the same prediction performance as the 11 parameter prediction scheme. The Correlation Coefficient (CC) of the results is around 0.85. The results of this study can not only be used to provide a machine learning scheme reference for practical visibility prediction applications, but also help to deepen the understanding of the factors affecting visibility.
As one of the current scientific research hotspots, atmospheric aerosol not only affects human health and environmental quality, but also has an important impact on atmospheric radiation transmission, laser engineering and other fields. In this paper, we used multi-rotors UAV as a platform, equipped with Portable Optical Particle Profiler (POPS) and meteorological parameter instrument to measure near-surface aerosol properties in Hefei, China, and analyzed the characteristics of aerosol particle number concentration, effective radius and vertical spectrum distribution. The results show that in Hefei, the concentration of aerosol particles in the near-surface layer varies significantly from day to day. The size distribution of aerosol particle shows "double peaks", which can be described by the superposition of two modes. The peak centers are at 0.18 μm and about 0.5 μm. In this study, the physical parameters of aerosols obtained by UAVs can be used to calculate the optical properties of aerosols. It also provides technical support for the subsequent research of aerosols in the modeling of atmospheric aerosols in the region.
As the "roof of the world", the Tibetan Plateau (TP, in short) exhibits the distinctive "heat island" characteristics compared to the same latitude region, and plays a decisive role in the atmospheric thermal structure of the TP and surroundings. ERA5 reanalysis data from January 2017 to December 2020 are used to analyze the meridional distribution characteristics of the average skin temperature and the potential temperature lapse rate at coldest point tropopause (CPT) in the highaltitude areas of the TP in summer. The Pearson correlation coefficient between the measured data and the reanalyzed data in the Da Qaidam area (95°21’E, 37° 51’N, 3180m above sea level (ASL)) in August 2020 is 0.88, indicating good usability of the reanalyzed data. The average skin temperature of TP in summer shows a feature of "high in the south and low in the north", which is ~20° higher than the atmospheric temperature of surrounding low-altitude area at the same altitude. The distribution of heat sources on the TP not only affects the location and intensity of the South Asian High, but also aggravates the thermal difference between land and sea, which promotes the formation of the Asian summer monsoon. The strong heat source in the southern TP, on the one hand, directly affects the atmospheric thermal structure over the southern TP through enhancing upward transportation; on the other hand, indirectly affects the high-altitude atmospheric thermal structure of the region north to TP through the background transportation of westerly and summer monsoons. The potential temperature lapse rate at CPT over the high-altitude area of TP also has significant characteristics of north-south differences, indicating that the "heat source effect" can regulate the intensity of atmospheric turbulence.
Mie-scattering lidar is an active remote sensing tool for inverting atmospheric properties by detecting the interaction between lasers and various molecules and aerosol particles in the atmosphere. It has become a powerful detection tool for atmospheric aerosols. However, whether it is a coaxial or parallel-axis laser radar, the accuracy of measurement and inversion in the blind zone and transition zone needs to be improved. This paper studies and establishes a new method of the Mie scattering lidar extinction profile correction based on the UAV-borne aerosol radiosonde. In this method, the UAV (unmanned aerial vehicle) is equipped with an optical aerosol radiosonde (Portable Optical Particle Profiler, POPS), and measures particle spectrum information and related meteorological parameters in the same detection path as lidar. Therefore, by using the Mie scattering theory simulation, the aerosol extinction profile in the lidar short-range blind zone and transition zone can be derived from the UAV-borne aerosol radiosonde data. The horizontal measurement verification test shows that the near-ground extinction coefficient by the new UAV method is in good agreement with that obtained by the lidar Collis slope method.
The complex refractive index of aerosol particles has a vital influence on the radiation effect of aerosols. From July to October 2020, a long-term observation of marine aerosols in the Pacific Ocean was carried out by a surveying vessel.Based on the number concentration of marine aerosol particles measured by optical particle counter (OPC), the extinction coefficient and scattering coefficient of marine aerosol measured by single scattering albedo monitor (CAPS), combined with meteorological data, and through Mie scattering theory, the influence of the change of real and imaginary parts of marine aerosol particle refractive index on particle single scattering albedo is studied. The measurement results show that the range of single scattering albedo of marine aerosol is about 0.7-0.9. The inversion results show that the real part of aerosol refractive index varies from 1.335 to 1.45 and the imaginary part varies from 0.011 to 0.018.
Knowledge of the atmospheric optical turbulence profile (AOTP) is critical for atmospheric optics studies. Meteorological sounding of long-term AOTP observations at seas often comes at an outrageous cost. It is necessary to establish a mathematical model driven by conventional meteorological parameters to predicate the AOTPs at high altitudes. Conventional meteorological parameters TUH (i.e., temperature, wind speed and relative humidity), have an important impact on the sea surface turbulence. AOTPs together with TUHs in Maoming were obtained. Based on the artificial neural network (NN) algorithm, an NN model is established according to the data to predict the upper atmospheric turbulence profile. The AOTPs measurements were used to validate the model predictions with the existing estimation theory. Cross-validation between these methods are performed and evaluated with mean absolute error (MAE), mean variance (MSE) and root mean square variance (RMSE). The results show that the predicted values simulated by the NN algorithm agree well with the real values, which proves that it is feasible and reliable to use the NN to simulate the atmospheric turbulence profile.
Atmospheric stability characterizes the intensity of vertical movement near the ground. Monin- Obukhov length is the most commonly used also most important stability parameter in boundary layer theory, which can be calculated by the dimensional analysis method on the basis of the similarity theory of the near-surface layer. The M-O parameter ζ is often used to characterize the stability (the ratio of height to M-O length). When the atmospheric stratification is neutral, ζ=0; when the atmospheric stratification is stable, ζ>0, and the larger the value, the more stable the atmosphere; When the atmosphere stratification is unstable, ζ<0, and the smaller the value, the more unstable the atmosphere. Using the three-dimensional wind speed data of the ship-borne three-dimensional ultrasonic anemometer and the meteorological data observed by the automatic weather station, combined with similar theory, to analyze the atmospheric stability parameter ζ above the sea surface. The results show that the atmospheric stability has an obvious diurnal variation trend, the night atmosphere is mostly stable, and the atmospheric turbulence is vigorous at noon. Besides, using three-dimensional ultrasonic wind speed data combined with virtual temperature correction, the atmospheric refractive index structure constant is calculated and compared with the measured value of the micro-thermal meter. This paper also analyzes the values of friction velocity 𝒖𝒖∗, characteristic temperature 𝑻𝑻∗ , characteristic humidity 𝑸𝑸∗ and atmospheric refractive index structure constant Cn2 under different stability conditions to understand the changing characteristics of optical turbulence on the underlying surface of the ocean.
The refractive index structure parameter C2n is a physical quantity used to characterize atmospheric optical turbulence, which is of great significance to the study of light wave transmission in turbulent atmosphere. In this paper, the C2n of coastal area from November 2019 to early January 2020 were measured by shipborne ultrasonic anemometers and microthermometer. Turbulence characteristics are statistically analyzed and the differences between results derived from the two measurement methods are discussed. The results show that the C2n measured by two instruments is generally consistent but have deviation. It is preliminarily inferred that the ultrasonic anemometer will oscillate due to the influence of the experimental environment on the wind field and the land-sea breeze, resulting high frequency noise that leads to higher measurement results than the micro-thermometer.
As an important part of the atmospheric environment, aerosols play a critical role in the study of the relationship between light and radiation. However, due to the complex spatiotemporal distribution of aerosols, it is much difficult to measure their microphysical properties and to determine their optical properties in coastal areas. In this paper, basic meteorological elements (e.g., wind speed, temperature, humidity) are simulated with the numerical weather forecasting (WRF) model. Then, the coastal aerosol model (CAM) together with the observation data is used to simulate the aerosol particle size distribution (APSD) and extinction coefficient for the coastal environment of Qingdao. Finally, data measured by the automatic weather station and particle counter in the coastal area are compared to their corresponding simulations. According to the comparisons results, temperature simulations were higher from an overall perspective (<2°C) with the correlation coefficient larger than 0.96; humidity simulations were comparatively lower on the 11th and 12th day (<10%) than those onthe 13th day (<20%), but the correlation coefficient was still larger than 0.8. With the meterological parameters simulations, the CAM model was used to predict the APSDs. It is founded that simulations for large particles are generally larger, while those for giant particles are generally smaller, but the simulated temperature, humidity, APSD and extinction coefficient are very consistent with their corresponding measurements. The method established in this paper is promising for the simulation and forecast of both the meteorological elements and aerosol microphysical properties.
Tibetan Plateau, known as the third pole of the Earth, has an important impact on the atmospheric circulation and weather in East Asia. The detection of meteorological elements in the near-surface layer of the area is of great significance for the in-depth study of the meteorological mechanism of the boundary layer. In this paper, we used multi-rotor UAV (Unmanned Aerial Vehicle) combined with conventional observations to independently design a measurement platform with various sensors, data storage and transmission components, measuring conventional meteorological parameters, and temperature structure constants (Ct2 ). The suitability analysis of the platform was carried out through drone sonde and kite-balloon sonde experiments in Lhasa area (91°08′07′′E, 29°39′36′′N). Comparative analysis of two kinds of data shows that 403MHz wireless transmission adopted by the two methods is stable, and two sounding results of temperature, air pressure and Ct2 have good consistency between each other, with acceptable normal ranges of error. This work provides a new boundary layer detection method, and also has positive significance for scientific research work in meteorology and environmental monitoring.
Lidar has been widely used in remote sensing of atmospheric environment because of its high spatial-temporal resolution and detection sensitivity. As the main noise source in lidar detection, solar background radiation is an important factor to determine target from background. The background noise, which is estimated by taking the average value of the lidar echo signal at a certain height, is usually removed directly. However, the background noise also contains some useful information on the whole layer of the atmosphere. In this paper, atmospheric radiation transmission model software MODTRAN 5.0 was used to simulate the lidar background noise under clear sky condition, combined with micro-pulse lidar (MPL) and meteorological element sounding data. The daytime background noise received by lidar were simulated by standard model method and user-defined model method. The standard model method uses standard atmospheric and aerosol model, which is the common way in traditional background radiation simulation. The user-defined model method uses aerosol and meteorological data measured in Maoming, Guangdong Province in October 2018 to build a user-defined atmospheric model. Results shows that the overall trends of the simulated background radiation from two methods are quite similar to the MPL observation. The user-defined model method can produce more consistent results with the observation than the standard model method, mainly due to that standard model cannot be completely consistent with the real experimental environment. The simulation results in this paper can be used to improve the daytime MPL retrieval, and can also be applied to the retrieving of aerosol particle size information and optical characteristics of cloud in further study.
Above-low-cloud aerosol (ACA) has important impacts on low clouds bellow. Based on the satellite data from 2007 to 2010, this study analyzed the relationship between ACA optical depth (OD), ACA occurrences and low cloud integrated color ratio (CR) over tropic Atlantic region where ACA frequently occurs. The results show that, the integrated attenuated CR (IACR) of low cloud is about 30%-50% larger over smoke region in smoke outbreak seasons than other regions or seasons. However, the IACR of low cloud over dust region shows small difference between dust outbreak seasons and other seasons. It indicates that above-low-cloud smoke aerosol can introduce stronger color effect than dust. The integrated corrected CR (ICCR) of low cloud tends to decrease with increasing above-cloud dust OD, while the low cloud ICCR shows weak relationship with above-low-cloud smoke OD. And, the above-low-cloud dust aerosol could introduce strong microphysics effect, that is, the low cloud droplet size may decrease with increasing burden of dust aerosol above.
This paper studied the marine-type aerosol distribution characteristics with the Wide-range Particle Spectrometer (WPS) obsevations boared on ”Shen Kuo” ship, over the South China Sea from June 21 to July 2, 2019. Particle spectral distributions at different time, fitted by the log-normal distribution method, and compared with the fine particle measurements in Hefei. Results show that the particle distributions over the South China Sea mainly show peaks around 95nm and 480nm respectively, while peaks around 26nm and 100nm in Hefei. The maximum concentration of fine particles in Hefei can reach 13×103 /cm3 , which is much higher than that over the South China Sea with a peak concentration of 6×103 /cm3 .
Because of the special topography surrounded by sea on three sides, the coastal area of Qingdao is greatly affected by the aerosol of sea salt sources, and has a significant maritime climate. Based on the meteorological observation data measured by the Qingdao seaside from September to October 2019, the correlations between the atmospheric conventional meteorological parameters of the typical sea area and the influence of meteorological parameters on the atmospheric aerosol optical parameters were analyzed. The results indicate that,(1) the relative humidity has opposite daily variation to temperature, and the change of atmospheric pressure slightly lags behind the relative humidity;(2) there is a relationship between the change of weather and meteorological parameters, that is, the parameters such as temperature and relative humidity, visibility and particle number density distribution on sunny days are significantly different from those in rainy days;(3) visibility is positively correlated with the daily variation of wind speed and temperature, and is negatively correlated with the daily variation of relative humidity. It shows that conventional meteorological parameters such as relative humidity, temperature, and atmospheric pressure are closely related to optical parameters such as particle size distribution and visibility. The above statistical analysis results have reference value for the establishment of the regional aerosol model in the coastal area of Qingdao.
The altitude of atmospheric medium involved in atmospheric optics has a height range of 100km, and the most complicated variation of atmospheric properties is mainly in the atmospheric boundary layer (ABL). The variety of ABL height is of considerable significance to the distribution of aerosol, cloud, and other processes. Since the research of Chinese marine ABL analysis is limited, in this study, we improved the algorithm by using 532nm total attenuated backscattering (TAB) for retrieving atmospheric boundary layer height (ABLH) from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and verified the results gained from micro-pulse lidar (MPL) and radiosonde over the South China Sea. Finally, we used the validated ABLH algorithm model to retrieve the ABLH against CALIPSO data from Mar. 2018 to Feb.2019 over the South China Sea.
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