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High temporal-spatial resolution measurement of the air temperature is important for human health and research on the urban heat island. Since conventional methods can hardly meet the demands, a novel measurement of the air temperature has been proposed by using the battery temperature sensor of the smartphone, which can provide a refined data in a crowdsourcing way. Firstly, a heat transfer retrieval model among the air temperature, battery temperature, and the pocket of the clothing or the desk is established. Then coefficients of the retrieval model are obtained by the dataset measured through the smartphone and the thermometer in the linear fitting method. Finally, we retrieve the air temperature in a specific site with time resolution of one minute based on the retrieval model by three independent smartphones. Retrieval air temperature of four models strongly correlates to the true value, indicating that the retrieval model can sense the variation of the air temperature. Meanwhile, root mean square errors of the 1st and 4th model are 0.35 and 0.45∘, implying the high retrieval accuracy. The results suggest that the retrieval model can provide a short timescale (minute) and robust estimation of the air temperature by smartphone temperature sensors.

Based on the power-law relation between rain intensity and corresponding specific attenuation, precipitation inversion by oblique earth–space link (OEL) has become a supplement to conventional method. However, the attenuation caused by melting layer has a significant effect on its performance. According to the microphysics, thermodynamics, and scattering properties of melting hydrometeors, a melting layer model is introduced to improve OEL inversion approach. Meanwhile, the observations by a microrain radar (MRR) located at Nanjing Reference Climatological Station (NRCS) are used and plenty of numerical simulations are also performed, which aim to validate the melting layer model. The choice of raindrop size distribution (DSD) determines the simulated values of radar reflectivity factor (RRF) and path-integrated attenuation (PIA). The gamma distribution gives the results of simulated RRF that are consistent with MRR observations. Considering the nonspherical shape of melting hydrometeors, its effects on attenuation calculation are discussed based on $T$ -matrix, which indicates the error due to hydrometeor shape is negligible below Ka-band. The values of PIA derived from our melting layer model show good agreements with MRR observations. In the simulation experiment, we found the average multiplier of melting layer attenuation is a function of rain intensity and frequency. The relation is established by using the nonlinear least-squares method. According to the multiplier, a novel model is proposed to estimate the melting layer attenuation. Compared with other existing attenuation models, it shows a similar performance in different frequency bands. Moreover, we introduce an equivalent multiplier into OEL rainfall inversion model, which demonstrates the obvious enhancement of effectiveness and robustness of improved model in the validation experiment.

In this article, a water vapor density inversion model based on the long short-term memory network is proposed for E-band commercial microwave links (CMLs). A full-duplex E-band microwave link located in Prague (two sublinks with frequencies of 73.5 and 83.5 GHz, both vertically polarized) was used to verify the performance of the model. The results show that the model inversion results are in good agreement with the water vapor density calculated by temperature and humidity sensors. Compared with previous water vapor inversion methods based on CMLs, this model has a higher temporal resolution and can realize real-time monitoring.

This article proposes a new rainfall-type classification method using the differential attenuation rates (DARs) calculated from microwave links with multiple frequencies and dual polarization. Several machine-learning algorithms were employed for classification [decision tree (DT), probabilistic neural network (PNN), Gaussian discriminant analysis (GDA), and logistic regression (LR)]. This method was simulated by two or three frequencies (combination of frequencies of 15, 25, 38, 60, and 80 GHz). The results showed that DT, PNN, GDA, and LR achieved maximum accuracies of 88.9%, 84.6%, 66.8%, and 67.6% for the dual-frequency model, respectively, and 89.6%, 85.8%, 67.6%, and 68.7% for the tri-frequency model, respectively, which is obviously better than the classification method based on the sequence of rain rates from the ITU-R model. The model accuracies based on GDA and LR algorithms are obviously lower than those based on DT and PNN due to the defects of the algorithms. In addition, the effects of different noise levels on classification performance are also discussed.

Microwave links (MLs), ranging from 10 to 30 GHz, have been widely applied for estimating rainfall; however, links below 10 GHz have rarely been applied, although they are more widespread via applications such as cellphone signals. This letter analyzes the feasibility of using cellular device like transmission signal to detect rain by establishing a 2-GHz ML and presents a detection method to classify dry/rainy periods by using statistical parameters from attenuation measurements. The detection model is trained using the C4.5 algorithm based on the combination of the average, standard deviation, minimum, and maximum of the attenuation measurements over the course of 1 min. The method is then applied for seven rain events, using a disdrometer to validate the results. The true positive rates of dry periods are all greater than 70%, and those of rainy periods are greater than 60%, indicating that the method performs well and could detect most of dry and rainy periods correctly. The results indicate the preliminary feasibility of using cellphone signals to detect rain.

Recently, the oblique earth-space links (OELs) between satellite and earth station have been used for rainfall monitoring as a supplement to existing observation methods. Most recent studies achieved the rainfall measurement by OELs based on the empirical method such as power-law (PL) model. In practice, two crucial issues need to be addressed: 1) identification of rain and no-rain periods; and 2) determination of attenuation baseline. To solve these problems, this article adopts several machine learning algorithms based on the analysis of earth-space link signal characteristics. For the first issue, we choose the support vector machine as a classifier and the adaptive synthetic sampling algorithm is deployed to eliminate the effects caused by the data imbalance. For the second issue, the long short-term neural network is selected for the determination of attenuation baseline since it has a good ability to solve time-series problem. In terms of the rainfall inversion, we establish a new model by combining the back-propagation (BP) network and genetic algorithm (GA). The PL model is also used as a comparison. To validate the proposed method, we set up an earth-space link that receives the signal from AsiaSat5 in 12.32 GHz. The results demonstrate that the two issues are successfully addressed and the inversion of precipitation is also carried out. Compared to disdrometer, the correlation and mean absolute error of GA-BP model are 0.83 and 1.30 mm/h, respectively, indicating a great potential to use densely OELs for global precipitation monitoring.

Since the founding of the People’s Republic of China 70 years ago, the subject of atmospheric physics and atmospheric environment has developed rapidly in China, providing important support for the development of atmospheric science and guarantee for the development of national economy. In this paper, the general advancement of atmospheric physics and atmospheric environment in last 70 years was described. The main research progress of atmospheric physics and atmospheric environment in the past 40 years of reform and opening-up was reviewed, the outstanding research achievements since the 21st century were summarized, the major problems and challenges are pointed out, and the key directions and suggestions for future development are put forward.

Raindrop size distribution (RSD) characteristics over the South China Sea (SCS) are examined with onboard Parsivel disdrometer measurements collected during marine surveys from 2012 to 2016. The observed rainfall is divided into pre-monsoon, monsoon, and post-monsoon periods based on the different large-scale circumstances. In addition to disdrometer data, sounding observation, FY-2E satellite, SPRINTARS (Spectral Radiation-Transport Model for Aerosol Species), and NCEP reanalysis datasets are used to illustrate the dynamical and microphysical characteristics associated with the rainfall in different periods. Significant variations have been observed in respect of raindrops among the three periods. Intercomparison reveals that small drops (D < 1 mm) are prevalent during pre-monsoon precipitation, whereas medium drops (1–3 mm) are predominant in monsoon precipitation. Overall, the post-monsoon precipitation is characterized by the least concentration of raindrops among the three periods. But, several large raindrops could also occur due to severe convective precipitation events in this period. Classification of the precipitation into stratiform and convective regimes shows that the lg(Nw) value of convective rainfall is the largest (smallest) in the pre-monsoon (post-monsoon) period, whereas the Dm value is the smallest (largest) in the pre-monsoon (post-monsoon) period. An inversion relationship between the coefficient A and the exponential b of the Z—R relationships for precipitation during the three periods is found. Empirical relations between Dm and the radar reflectivity factors at Ku and Ka bands are also derived to improve the rainfall retrieval algorithms over the SCS. Furthermore, the possible causative mechanisms for the significant RSD variability in different periods are also discussed with respect to warm and cold rain processes, raindrop evaporation, convective activities, and other meteorological factors.

Theoretical analyses show that both the rain-induced attenuation of electromagnetic signals and rainfall intensity are relative to the raindrop size distribution (DSD). In this paper, an im...

High-precision rainfall field reconstruction and nowcasting play an important role in many aspects of social life. In recent years, the rain-induced signal attenuation of oblique earth-space links (OELs) has been presented to monitor regional rainfall. In this paper, we set up the first OEL in Nanjing, China, for the estimation of rain intensity. A year of observations from this link are also compared with the measurements from laser disdrometer OTT-Parsivel (OTT), between which the correlation is 0.86 and the determination coefficient is 0.73. Then, the simulation experiment is carried out: an OELs network is built, and the Kriging interpolation algorithm is employed to perform rainfall field reconstruction. The rainfall fields of plum rain season from 2016 to 2019 have been reconstructed by this network, which shows a good agreement with satellite remote sensing data. The resulting root-mean-square errors are lower than 3.46 mm/h and spatial correlations are higher than 0.80. Finally, we have achieved the nowcasting of rainfall field based on a machine-learning approach, especially deep learning. It can be seen from experiment results that the motion of rain cell and the position of peak rain intensity are predicted successfully, which is of great significant for taking concerted actions in case of emergency. Our experiment demonstrates that the densely distributed OELs are expected to become a futuristic rainfall monitoring system complementing existing weather radar and rain gauge observation networks.

The influence to filamentation of femtosecond by atmospheric turbulence at wavelength of 400 nm has been studied numerically. Simulations show that the distance of filamentation at 400 nm is advanced, the number of filaments increases, and the energy of filaments decreases with the addition of turbulent screen. Compared with the filaments formed by the 800 nm femtosecond laser, the nonlinear propagation of 400 nm laser has a longer filamentation distance in the turbulent atmosphere, and the clamping light intensity of the filaments is higher, but the number of filaments has reduced. With the increase of propagation distance, the multifilament structure disappears and the beam gradually converges into a stable monofilament structure. The position of the monofilament structure at 400 nm is closer than the 800 nm. Therefore, stable filament structure can be obtained more easily with a femtosecond laser at 400 nm.

PSTD (Pseudo Spectral Time Domain) is an excellent model for the light scattering simulation of nonspherical aerosol particles. However, due to the particularity of its discretization form of the Maxwell's equations, the traditional Total Field/Scattering Field (TF/SF) technique for FDTD (Finite Differential Time Domain) is not applicable to PSTD, and the time-consuming pure scattering field technique is mainly applied to introduce the incident wave. To this end, the weighted TF/SF technique proposed by X. Gao is generalized and applied to the 3D-PSTD scattering model. Using this technique, the incident light can be effectively introduced by modifying the electromagnetic components in an inserted connecting region between the total field and the scattering field region with incident terms, where the incident terms are obtained by weighting the incident field by a window function. To optimally determine the thickness of connection region and the window function type for PSTD calculations, their influence on the modeling accuracy is firstly analyzed. To further verify the effectiveness and advantages of the weighted TF/SF technique, the improved PSTD model is validated against the PSTD model equipped with pure scattering field technique in both calculation accuracy and efficiency. The results show that, the performance of PSTD seems to be not sensitive to variation of window functions. The number of the connection layer required decreases with the increasing of spatial resolution, where for spatial resolution of 24 grids per wavelength, a 6-layer region is thick enough. The scattering phase matrices and integral scattering parameters obtained by the improved PSTD show an excellent consistency with those well-tested models for spherical and nonspherical particles, illustrating that the weighted TF/SF technique can introduce the incident precisely. The weighted TF/SF technique shows higher computational efficiency than pure scattering technique.

The performance of absorbing boundary condition (ABC) is an important factor influencing the simulation accuracy of MRTD (Multi-Resolution Time-Domain) scattering model for non-spherical aerosol particles. To this end, the Convolution Perfectly Matched Layer (CPML), an excellent ABC in FDTD scheme, is generalized and applied to the MRTD scattering model developed by our team. In this model, the time domain is discretized by exponential differential scheme, and the discretization of space domain is implemented by Galerkin principle. To evaluate the performance of CPML, its simulation results are compared with those of BPML (Berenger's Perfectly Matched Layer) and ADE-PML (Perfectly Matched Layer with Auxiliary Differential Equation) for spherical and non-spherical particles, and their simulation errors are analyzed as well. The simulation results show that, for scattering phase matrices, the performance of CPML is better than that of BPML; the computational accuracy of CPML is comparable to that of ADE-PML on the whole, but at scattering angles where phase matrix elements fluctuate sharply, the performance of CPML is slightly better than that of ADE-PML. After orientation averaging process, the differences among the results of different ABCs are reduced to some extent. It also can be found that ABCs have a much weaker influence on integral scattering parameters (such as extinction and absorption efficiencies) than scattering phase matrices, this phenomenon can be explained by the error averaging process in the numerical volume integration.

Gaussian distribution is used to describe the power law along the propagation path and phase screen of the non-Kolmogorov turbulence is proposed based on the equivalent refractive-index structure constants. Various simulations of Gaussian beam propagation in Kolmogorov and non-Kolmogorov turbulence are used for telling the difference between isotropic and anisotropic turbulence. The results imply that the non-Kolmogorov turbulence makes a great influence on the simulations via power law in spectrum and the number of phase screens. Furthermore, the influence is mainly reflected in light intensity and beam drift. Statistics suggest that when Gaussian beam propagate through single phase screen of non-Kolmogorov, maximum and uniformity of light intensity increase first and then decrease with power law, and beam drift firstly increases and then to stabilize. When Gaussian beam propagate through multiple phase screens, relative errors of beam drift decrease with the number of phase screens. And scintillation indices in non-Kolmogorov turbulence is larger than that in Kolmogorov turbulence when the number is small. When the number is big, the scintillation indices in non-Kolmogorov turbulence is smaller than that in Kolmogorov turbulence. The results shown in this paper demonstrate the effect of the non-Kolmogorov turbulence on laser atmospheric transmissions. Thus, this paper suggests a possible direction of the improvement of the laser transmission accuracy over a long distance through the atmosphere.

The effects of water vapor ionization on the nonlinear propagation of femtosecond laser pulses with a 248 nm wavelength are numerically investigated in this paper. It is found that ionization of H2O molecules plays a significant role in air ionization, which seriously affects the dynamic and energy deposition of filamentation. The propagation of femtosecond pulses in air with different humidity levels are compared. The total number of electrons and total deposited pulse energy increase with the humidity increases. However, they tend to be saturated in high humidity conditions. Results presented here are conducive to characterizing the long-range propagation of filaments under atmospheric conditions.

Retrieval of ice cloud properties using passive terahertz wave radiometer from space has gained increasing attention currently. A multi-channel regression inversion method for passive remote sensing of ice water path (IWP) in the terahertz band is presented. The characteristics of the upward terahertz radiation in the clear-sky and cloudy-sky are first analyzed using the Atmospheric Radiative Transfer Simulator (ARTS). Nine representative center frequencies with different offsets are selected to study the changes of terahertz radiation caused by microphysical parameters of ice clouds. Then, multiple linear regression method is applied to the inversion of IWP. Combinations of different channels are selected for regression to eliminate the influence of other factors (i.e., particle size and cloud height). The optimal fitting equation are obtained by the stepwise regression method using two oxygen absorption channels (118.75 ± 1.1 GHz, 118.75 ± 3.0 GHz), two water vapor absorption channels (183.31 ± 1.0 GHz, 183.31 ± 7.0 GHz), and two window channels (243.20 ± 2.5 GHz, 874.4 ± 6.0 GHz). Finally, the errors of the proposed inversion method are evaluated. The simulation results show that the absolute errors of this method for the low IWP cases are below 7 g/m2, and the relative errors for the high IWP cases are generally ranging from 10 to 30%, indicating that the multi-channel regression inversion method can achieve satisfactory accuracy.

As a method that does not require additional cost, precipitation measurement by microwave links (MLs) has quickly attracted the attention of experts in meteorological, hydrological, and other related fields, of which wet-dry classification by MLs is one of the most important methods. Considering that existing commercial MLs are usually single-path, single-polarization, or low-frequency MLs, this paper uses the C-band ML and analyzes the variation in the receive signal level (RSL) of the C-band ML under the conditions of no rain, drizzle, light rain, and moderate rain. The RSL data are analyzed at different time scales by using long short-term memory (LSTM) network techniques, and then the method for distinguishing parts of the precipitation period by using the RSL from low-frequency MLs is proposed and validated. The results show that wet-dry classification is ideal. The accuracy on each day was higher than 60%, and some days had accuracies that were even higher than 98%. MLs below 10 GHz also had the potential to monitor ground rainfall. This study will broaden the range of available equipment for MLs for precipitation measurement.

Estimation of raindrop size distribution (DSD) is essential in many meteorological and hydrologic fields. This paper proposes a method for retrieving path-averaged DSD parameters using joint dual-frequency and dual-polarization microwave links of the telecommunication system. Detailed analyses of the rain-induced attenuation calculation are performed based on the T-matrix method. A forward model is established for describing the relation between the DSD and the rain-induced attenuation. Then, the method is proposed to retrieve propagation path DSD parameters based on Levenberg–Marquardt optimization algorithm. The numerical simulation for path-averaged DSD retrieval shows that the RMSEs of three gamma DSD parameters are 0.34 mm−1, 0.81, and 3.21×103 m−3·mm−1, respectively, in rainfall intensity above 30 mm/h. Meanwhile, the method can retrieve the rainfall intensity without the influence of variational DSD. Theoretical analyses and numerical simulations confirm that the method for retrieving path-averaged DSD parameters is promising. The method can complement existing DSD monitoring systems such as the disdrometer and provide high-resolution rainfall measurements with widely distributed microwave links without additional cost.

Water vapor is a key element in both the greenhouse effect and the water cycle. However, water vapor has not been well studied due to the limitations of conventional monitoring instruments. Recently, estimating rain rate by the rain-induced attenuation of commercial microwave links (MLs) has been proven to be a feasible method. Similar to rainfall, water vapor also attenuates the energy of MLs. Thus, MLs also have the potential of estimating water vapor. This study proposes a method to estimate water vapor density by using the received signal level (RSL) of MLs at 15, 18, and 23 GHz, which is the first attempt to estimate water vapor by MLs below 20 GHz. This method trains a sensing model with prior RSL data and water vapor density by the support vector machine, and the model can directly estimate the water vapor density from the RSLs without preprocessing. The results show that the measurement resolution of the proposed method is less than 1 g/m3. The correlation coefficients between automatic weather stations and MLs range from 0.72 to 0.81, and the root mean square errors range from 1.57 to 2.31 g/m3. With the large availability of signal measurements from communications operators, this method has the potential of providing refined data on water vapor density, which can contribute to research on the atmospheric boundary layer and numerical weather forecasting.

Accurate and real-time rainfall estimation is a pressing need for forecasting the flood disaster and reducing the loss. In this study, we exploit the potential of estimating the rainfall by microwave links in East China. Eight microwave links at 15 GHz and 23 GHz, operated by China Mobile, are used for estimating the rain rate in real-time in Jiangyin, China from June to July 2020. First, we analyze the correlation between the rain-induced attenuation of microwave links and the rain rate measured by rain gauges. The correlation coefficient values are higher than 0.77 with the highest one over 0.9, showing a strong positive correlation. The real-time results indicate that microwave links estimate the rainfall with a higher temporal resolution than the rain gauges. Meanwhile, the rain rate that was estimated by microwave links also correlates well with the actual rain rate, and most of the values of the mean absolute error are less than 1.50 mm/h. Besides, the total rainfall’s relative deviation values are less than 5% with the smallest one reaching 1%. The quantitative results also indicate that microwave links could lead to better forecasting of water levels and, hence, better warnings for flood disasters.

The Invariant Imbedding (IIM) T-matrix method is recognized as one of the most promising scattering models since it can perform the scattering simulation of the nonspherical particles in a semi-analytical way. However, because the T-matrix should be updated in each iterative process, its computational efficiency is an important issue in the actual scattering simulation. To alleviate this problem, the symmetrical properties for the nonspherical particles with symmetrical geometries are systematically investigated in this paper. Firstly, the symmetry of the U-matrix (an important matrix in the IIM T-matrix model) is derived for the particles with mirror symmetry with respect to the coordinate planes. In this case, the U-matrix is firstly decomposed into the sine and cosine components, and then its symmetrical properties are obtained by combining the spatial symmetry of the permittivity and the symmetry of the angular functions. In the second part, the symmetry of the U-matrix is derived for the particles with N-folds symmetrical geometry, and based on the symmetrical properties, the method to simplify the T-matrix iteration is further proposed. In this case, it can be found that by using the symmetry of the U-matrix, both the U-matrix and T-matrix can be rearranged into the block diagonal ones, and the calculation of the T-matrix can be decomposed into the iteration of several block sub-matrices, which can cut down the computational amount and memory consumption notably. Also, it can be seen that the derivation process also provides another point of view to understand the symmetry of T-matrix for the particles with N-folds symmetrical geometry.

Refraction is an important factor influencing radiative transfer since it can modify the propagation trajectory and polarization states of lights; therefore, it is necessary to quantitively evaluate the effect of atmospheric refraction on radiative transfer process. To this end, a new atmospheric radiative transfer model including refraction process is proposed. The model accuracy is validated against benchmark results, literature results, and well-tested radiative transfer models such as discrete coordinate method and RT3/PolRadtran. The impact of atmospheric refraction on both polarized radiance and fluxes is discussed for pure Rayleigh scattering atmosphere, atmosphere with aerosol, and cloud. The results show that atmospheric refraction has a significant influence on both the radiance and polarization states of diffuse light, where the relative change of the radiance of reflected light and transmitted light due to refraction can achieve 6.3% and 7.4% for Rayleigh scattering atmosphere, 7.2% and 7.8% for atmosphere with aerosol, and 6.2% and 6.8% for cloudy atmosphere, respectively. The relative change of the degree of polarization ranges from near zero in the horizon to 9.5% near neutral points. The angular distribution pattern of the relative change of the radiance for atmosphere with aerosol and cloud is very similar to that for pure Rayleigh scattering case, where its magnitude decreases gradually with the increasing of zenith angle for reflected light; but for transmitted light, the variation characteristics is opposite. The impact of refraction is gradually enhanced with the increasing of solar zenith angles and the optical depth of aerosol and cloud. As the wavelength of incident light increases, the impact declines rapidly for Rayleigh scattering medium. The relative change of the fluxes due to refraction is most notable for Middle Latitude Winter profile (about 8.2043% and 7.3225% for the transmitted and reflected light, respectively, at 0.35 µm). With increasing the optical depth of aerosol, the influence of refraction on the fluxes is gradually enhanced. For cloudy atmosphere, the relative changes of the fluxes due to refraction are not very sensitive to the variation of cloud optical depth and effective radius of cloud drops.

The Invariant Imbedding (IIM) T-matrix method has been recognized as one of the most promising method to derive exact solution of the light scattering properties of the nonspherical atmospheric particles after the significant improvement by Bi L. and Yang P. Compared with DDA (Discrete Dipole Approximation) and the time domain methods, it can calculate the scattering properties of the random-oriented particles analytically once the T-matrix of the particle is obtained. In order to better understand the modeling capability of this model and optimize the parameter settings for the particles with different geometrical and optical properties, the factors influencing the modeling accuracy are systematically analyzed, which includes the discretization schemes of the radial integral, the discrete point numbers of the radial, zenith and azimuthal integrals. The results show that, the calculation accuracy of Gaussian quadrature technique is higher than that of the trapezoidal rule in the radial discretization. For particles with large size parameter or refractive index, the density of the discrete points (both for the radial discretization and the mesh generation of the zenith and azimuth angles) should be increased correspondingly to ensure the calculation accuracy. Finer discrete grids are also required for particles with extreme shapes (e.g., particles with large aspect ratios). Based on the analysis above, the method to determine the parameters of scattering simulation is further proposed for particles with different geometrical and optical properties, by which the discretization of the computational domain can be optimized once the refractive index and geometry of the particle are known. The method is also validated for cylinders and hexagonal prisms, the results shows that the optimization scheme can be applicable to particles with different shapes.

To study difference at the urban scale (a few tens of kilometers), the raindrop size distribution (DSD) characteristics at five sites (Luhe (LH), Pukou (PK), Jingning (JN), Lishui (LS) and Gaochun (GC)) within five districts of Nanjing are compared using five years of PARticle SIze VELocity (PARSIVEL) disdrometer data during the East Asian rainy season. The percentage of class C5 (extreme rainfall) to rain amount at LH (industrial zone) is significantly higher than that at the other sites (up to 38%). In addition, LH has the largest log10Nw value, while JN (closest to the city center) has the largest Dm value for all rain rate classes and rainfall types. Compared with those of stratiform rainfall, the A and b values of convective rainfall from the Z-R relationship are remarkably more dispersed among the different sites. Moreover, the X-band is more robust to site differences than the S-band and C-band, and thus may be more suitable for rainfall monitoring at the urban scale.

The invariant imbedding T-matrix method has been recognized as one of the rigorous computational tools to simulate the light scattering by atmospheric nonspherical particles after the efficient implementation by L. Bi and P. Yang. Compared with the T-matrix model based on the Extended Boundary Condition Method (“EBCM”), it is suitable for the light scattering simulation of particles with any shapes. However, since the T-matrix must be updated in each iterative process, its computational efficiency is relatively lower than EBCM, especially for the particles with large sizes and large aspect ratios. To this end, an efficient realization scheme of the IIM T-matrix method is proposed in this paper. The principle and the structure of our IIM T-matrix code is firstly introduced, and then the symmetric properties of the U-matrix (an important matrix in the IIM T-matrix method) is derived; to simplify the iteration of T-matrix calculation, the implicit matrix inversion scheme is also proposed. To validate the effectiveness of these improvements, the computational efficiency and accuracy is systematically investigated for the particles with different shapes and sizes. The simulation results indicate that the computational time is reduced notably after the model is improved by the symmetry of U-matrix and the implicit matrix inversion scheme, where for the spheroid with (a, b) = (2.5 µm, 3.0 µm) at λ=0.5 µm (the particle is treated as complex geometries without any symmetry), the computational efficiency is improved by nearly 40%. Excellent agreement is also achieved between the scattering parameters obtained by the IIM T-matrix method and the well-test scattering models (such as BECM, DDASCAT, MRTD and IGOA, etc.), indicating that the IIM T-matrix method can simulate the light scattering by nonspherical particles effectively.

In atmospheric radiative transfer models, the light scattering properties of the nonspherical particles are needed to be averaged over specific orientation and size distributions to obtain the representative values. However, since the light scattering simulation processes of the typical models (such as DDA, FDTD, etc.) are closely dependent on particle's orientation, their computations should be repeated for many times to realize the orientation averaging process, which is a very time-consuming task. To solve this problem, the analytical algorithm to calculate the scattering parameters of the random-oriented particles based the Invariant Imbedding T-matrix method (IIM T-matrix method) is developed by Bi L., by which the scattering parameters of the randomly oriented particles can be calculated analytically. To give a more full description of this algorithm, the derivation process of this model is deduced following Mishchenko's idea in this paper. To facilitate the realization of this algorithm, an efficient implementation of the computational scheme is also introduced in detail. To validate the modeling accuracy of this algorithm, the results of the IIM T-matrix method are compared with those of the EBCM T-matrix method and DDASCAT for particles with different sizes and shapes. The results show that good agreement is achieved between the scattering parameters calculated by different models, where, the relative differences between the phase functions calculated by IIM and EBCM method are generally smaller than 5%, and the relative deviations of the extinction, scattering cross sections are all less than 0.5%, which indicates that the analytical algorithm can simulate the scattering parameters of the random-oriented particles with high accuracy. Compared to the traditional T-matrix method, the advantage of this algorithm is that it can be applicable to arbitrarily shaped particles.

Ceilometers are originally designed for cloud base height monitoring. Since a few years, the number of ceilometers available worldwide is rapidly increasing, and these simple backscatter lidars are investigated to be used for aerosol research. This study presents an assessment of the potential of CYY-2B ceilometer for the quantitative retrieval of aerosol properties. The signal-to-noise ratio of the ceilometer is calculated, and the effective height of inversion is determined. It is shown that the effective height of the ceilometer for backscatter coefficient profile inversion is 3-4 km at night and about 1.5–2 km during the day, which is lower than that of the micropulse lidar (MPL) system. The accuracy of the backscatter coefficient profiles derived from the CYY-2B ceilometer is analyzed by using the Vaisala CL51 ceilometer, MPL, forward scatter visibility instrument, and aerosol optical depth (AOD) dataset from aerosol robotic network (AERONET). Spectral conversions of the ceilometer’s and lidar’s data are performed using the Ångström exponent estimated by AERONET measurements. A good agreement is found between two ceilometers and the MPL lidar in backscatter coefficient profiles inversion. The AODs agree well with the AERONET AODs during the observation period of small AODs. However, for the period of large AODs, the results are approximately 50%–60% of AERONET AODs. The limited range of extinction integration is the main cause of this problem.

In order to improve the computational efficiency of multi-resolution time domain (MRTD) scattering model, a multi-size synchronous-computational scheme (MSCS) is proposed. By using MSCS, the scattering properties of the particles with different sizes can be simultaneously calculated by MRTD model in one wave-particle interaction simulation. In this model, the pulse plane wave with a wide spectrum is taken as the incident light, and the light scattering simulation for particles with different sizes is transformed into the scattering calculation for a size-fixed particle at different wavelengths. To guarantee the stability and precision of the improved MRTD (IMRTD) model, the method to design model’s input parameters, such as the spatial resolution, discrete time interval and pulse width, is proposed. To validate the accuracy of IMRTD model, its results are compared with those of Mie and T-Matrix theory, and the influence of spatial resolution on the precision of IMRTD is analyzed as well. At last, model’s computational efficiency is also discussed. The simulation results show that, IMRTD method can calculate the scattering parameters of particles with different sizes simultaneously and accurately, where, in case that the pulse width is 5.56 × 10−8ns, and the radius of the size-fixed particle is 0.5μm (its size parameter is 6.28), light scattering process by particles with size parameters up to 12.56 can be successfully simulated. With the increasing of spatial resolution, the simulation accuracy is improved for all particles, and the improvement for large particles is more notable than that for small ones. It can also be found that the computational efficiency of IMRTD is much higher than that of traditional version.

Aiming at the simultaneous measurement of the size, shape, fall velocity of precipitation particles, a ground-based optical instrument, the precipitation micro-physical characteristics sensor (PMCS) was developed, it can record the double-exposure image of each particle in a single frame, by which the size, equivalent diameter, axis ratio of raindrops can be calculated, its fall velocity can be calculated according to its displacement and time interval. The PMCS is calibrated by some glass balls with certain diameters in sunny, cloudy, and night conditions, based on which a fitted relationship between the threshold and image area is obtained and used to ensure the measurement accuracy of raindrop sizes. The field measurement of PMCS has obtained plenty of raindrops images, based on which the shape, axis ratio, and fall velocity of raindrops were calculated and discussed. The typical shape of large raindrop takes on an oblate ellipsoid with a flatter base and a more raised top, the axis ratio of raindrops decrease linearly with the increasing of diameter, the fall velocity of raindrops increases exponentially with the increasing of the diameter, and above observed data are in good agreement with the empirical model. These results validate the performance of PMCS, which can be widely applied for interpreting weather radar data, investigating regional precipitation features, and studying the physical process of precipitation.