i. This PDF file contains the front matter associated with SPIE Proceedings Volume 10786, including the Title Page, Copyright information, Table of Contents, Author and Conference Committee lists.

The EPS-SG Visible/Infrared Imaging mission is dedicated to supporting the optical imagery user needs for Numerical Weather Prediction (NWP), Nowcasting (NWC) and climate in the 2020 onwards timeframe. The VII mission is fulfilled by the METimage instrument, to be embarked on the Metop-SG-A satellites. METimage will fly in the mid-morning orbit of the Joint Polar System, whilst the early-afternoon orbits are served by the JPSS (U.S. Joint Polar Satellite System) Visible Infrared Imager Radiometer Suite (VIIRS). METimage is a cross-purpose medium resolution, multispectral optical imager, measuring radiation emitted and reflected by the Earth from a low-altitude sun synchronous orbit with a minimum swath width of 2700 km. The top of the atmosphere outgoing radiance will be sampled every 500 m (at nadir) with measurements made in 20 spectral channels ranging from 443 nm in the visible up to 13.345 μm in the thermal infrared.

The following METimage geophysical products will be generated and validated by EUMETSAT:

Cloud mask

Atmospheric motion vectors.

Cloud top height, microphysics and volcanic ash

Cloud top pressure using the oxygen-A band

Total precipitable water vapour from METimage visible/near-infrared bands.

Total precipitable water vapour from METimage thermal infra-red bands

This paper focuses on the validation activities planned for the METimage geophysical products to ensure they meet user requirements for the lifetime of the mission. The validation of level 2 variables relies on the availability of simultaneous and independent data providing the same information on the same horizontal scale. Validation methods include intercomparisons with other validated missions through simultaneous nadir overpasses (both low Earth orbit and geostationary), comparisons with ground based observations, and short term weather forecasts. The level 2 product performance will be validated with respect to user requirements for all geographic regions and seasonal variation.

The main focus of this paper is a comparison of unfiltered radiances measured by CERES instruments operating on three different platforms, namely the JPSS1 or N20, Terra and Aqua satellites. Data for the comparison have been continuously collected since Flight Model 6 or FM6 aboard the JPSS1 started its science mission in January of 2018. Three different strategies have been devised for the purpose of comparing CERES scanners. Using a special scanning mode, viewing geometries of instruments (FM6 and FM3, and also FM6 and FM1) can be matched to enable comparison at the unfiltered radiance level, and to provide a large data set for comparing the shotwave channel. In addition, using a special elevation scan profile on FM6 and FM3, an unprecedented high precision dataset can be collected for a more stringent test of the consistency between the two instruments for selected scene types. Statistics are computed for different scene types, and a confidence test is applied to gridded averages to show the existing consistency between measurements taken from the two different platforms. Preliminary results of the unfiltered radiance comparison are based on ES8s or ERBE-like data products; an Edition1-CV for FM6, and Edition4 for FM1 and FM3.

Natural and anthropogenic aerosol emissions play a fundamental role both in directly modulating the incoming solar radiation and affecting air quality in the planetary boundary layer. Likewise, their indirect effects impact cloud lifetime, atmospheric column thermodynamics and precipitation patterns. For this reason, it is of crucial importance to assess aerosol spatial and temporal variability to reduce the uncertainty in forecasting future scenarios by the climatological models. In this study we developed an image based robust methodology that permits to retrieve the atmospheric path radiance and then the Aerosol Optical Depth (AOD) using satellite high-resolution spatial images paired with the Fu-Liou-Gu radiative transfer model. We applied our methodology to study aerosol variability in the PO valley (Northern Italy), one of the most polluted region in Europe.

In this study, an experiment aimed to integrate Global Navigation Satellite System (GNSS) atmospheric data with meteorological data into a neural network system is performed. Precipitable Water Vapor (PWV) estimates derived from GNSS are combined with surface pressure, surface temperature and relative humidity obtained continuously from ground-based meteorological stations. The work aims to develop a methodology to forecast short-term intense rainfall. Hence, all the data is sampled at one hour interval. A continuous time series of 3 years of GNSS data from one station in Lisbon, Portugal, is processed. Meteorological data from a nearby meteorological station are collected. Remote sensing data of cloud top from SEVIRI is used, providing collocated data also on an hourly basis. A 3 year time series of hourly accumulated precipitation data are also available for evaluation of the neural network results. In previous studies, it was found that time varying PWV is correlated with rainfall, with a strong increase of PWV peaking just before intense rainfall, and with a strong decrease afterwards. However, a significant amount of false positives was found, meaning that the evolution of PWV does not contain enough information to infer future rain. In this work a multilayer fitting network is used to process the GNSS and meteorological data inputs in order to estimate the target outputs, given by the hourly precipitation. It is found that the combination of GNSS data and meteorological variables processed by neural network improves the detection of heavy rainfall events and reduces the number of false positives.

In context of numerical weather prediction (NWP), increased usage of satellites radiance observations from passive microwave sensors have brought significant improvements in the forecast skills. In the infrared spectral region, hyperspectral sounder instruments such as IASI have already benefitted the NWP assimilation systems, but they are useful only under clear sky conditions. Currently, microwave instruments are providing wealth of information on clouds, precipitation and surface etc., but only with limited number of channels. Furthermore, due to limited number of channels and with poor signal-to-noise ratio, existing passive microwave sensors have very poor resolution and accuracy.

We are currently developing a new microwave instrument concept, based on superconducting filterbank spectrometers, which will enable high spectral resolution observations of atmospheric temperature and humidity profiles across the microwave/sub-millimeter wavelength region with photon-noise-limited sensitivity. This study aims at investigating the information content on temperature and water-vapour that could be provided by such a hyperspectral microwave instrument under clear sky-conditions. Here, we present a new concept of Transition Edge Sensors (TESs)-based hyperspectral microwave instrument for atmospheric sounding applications. In this study, for assessing the impact of hyperspectral sampling in microwave spectral region in clear sky-conditions, we have estimated the information content as standard figure of merit called as degrees of freedom for signal (DFS). The DFS for a set of temperature and humidity sounding channels (50-60 GHz, 118GHz and 183 GHz) have been analyzed under the linear optimal estimation theory framework.

Atmospheric correction is a necessary step in image processing data and spectra recorded by spaceborne sensors for pure cloudless atmosphere, primarily in the visible and near-IR spectral range. We have present a fast and sufficiently accurate method of atmospheric correction based on the proposed analytical solutions describing with high accuracy the spectrum of outgoing radiation at the top boundary of the cloudless atmosphere. This technique includes the model of the atmosphere and its optical parameters that are important in terms of radiation transfer. The solution of the inverse problem for finding unknown parameters of the model is carried out by the method of non-linear least squares (Levenberg-Marquardt algorithm) for an individual selected pixel of the image (its spectrum), taking into account the adjacency effects. Using the found parameters of the atmosphere and the average surface reflectance, assuming homogeneity of the atmosphere within a certain area of the hyperspectral image (around dark pixel), the spectral reflectance at the Earth's surface is calculated for all other pixels. It is essential that the procedure of the numerical simulation with non-linear least squares of the direct transfer problem is based on using analytical solutions, which provides a very short calculation time of the atmospheric parameters (seconds or less) and the ability to perform atmospheric correction "on- y." The developed technique SHARC (Sattelite Hypercube Atmosheric Rapid Correction) was performed using the synthetic outgoing radiation spectra at the top of atmosphere (TOA), obtained by exact radiative transfer calculations (COART and LibRadTran codes), as well as the spectra of real space images Hyperion hyper- spectrometer.

Global Navigation Satellite System radio occultation (GNSS-RO) is an important technique used to sound the Earth's atmosphere and provide data products to numerical weather prediction (NWP) systems as well as to climate research. It provides a high vertical resolution and SI-traceability that are both valuable complements to other Earth observation systems. In addition to direct components refracted in the atmosphere, many received RO signals contain reflected components thanks to the specular and relatively smooth characteristics of the ocean. These reflected components can interfere the retrieval of the direct part of the signal, and can also contain meteorological information of their own, e.g., information about the refractivity at the Earth's surface. While the conventional method to detect such reflections is by using radio-holographic methods, it has been shown that it is possible to see reflections using wave optics inversion, specifically while inspecting the amplitude of the output of phase matching (PM). The primary objective of this paper is to analyze the appearance of these reflections in the amplitude output from another wave optics algorithm, namely the much faster full spectrum inversion (FSI). PM and FSI are closely related algorithms - they both use the method of stationary phase to derive the bending angle from a measured signal. We apply our own implementation of FSI to the same GNSS-RO measurements that PM was previously applied to and show that the amplitudes of the outputs again indicate reflection in the surface of the ocean. Our results show that the amplitudes output from the FSI and PM algorithms are practically identical and that the reflection signatures thus appear equally well.

A pragmatic, data driven approach, which for the first time combines existing in situ and remote sensing data sets with a networked mobile air pollutant measurement strategy in the urban space is an objective of the Smart Air Quality Network (SmartAQnet) project. It aims to implement an intelligent, reproducible, finely-tuned (spatial, temporal), yet cost-effective air quality measuring network, initially in the model region of Augsburg, Germany. Central to this is the development and utilization of partial, already existing (but not yet combined) data on the one hand and the collection and integration of relevant missing data on the other hand. Unmanned aerial vehicles (UAV) with low-weight meteorological sensors and particle counter are used to monitor the three-dimensional dynamics of the lower atmosphere. Ground-based remote sensing by ceilometer for mixing layer height detection as well as a Radio-Acoustic Sounding System (RASS) for temperature and wind profile measurements at the University campus complete the new network architecture and UAV height profiling of atmospheric parameters.

The SmartAQnet research initiative focuses on the subject of data access and data-based applications. Such complex monitoring provides the basis of deeper process understanding of air pollution exposure. The network architecture is shown and first results about spatial variation of meteorological influences upon air pollution exposure is presented using ceilometer, UAV and the existing monitoring network data.

A.M. Obukhov Institute of Atmospheric Physics (OIAP) of Russian Academy of Sciences (RAS) performs regular measurements of the integral tropospheric content of such reactive gases as nitrogen dioxide (NO₂) and formaldehyde (HCHO) by the MAX-DOAS method at the Zvenigorod Scientific Station (ZSS) since 2009. For each average hourly gas contents in the troposphere at ZSS in 2009-2017 the backward trajectories of the air particles were calculated using the trajectory model NOAA HYSPLIT_4 and the grid meteorological data NOAA NCEP GDAS0p5. Using the backward trajectories, the PSCF (potential source contribution function) method was used to calculate detailed (resolution 0.1°×0.1°) fields of probability of the transport to ZSS of air masses which are extremely polluted with formaldehyde and nitrogen dioxide from a potential source. Similarly, using the CWT (concentration weighted trajectory) method, detailed fields of the average contribution of the potential source to the tropospheric NO₂ and HCHO contents at ZSS were reconstructed. The relative influence of the Moscow megacity and the industrialized region in the east of the Moscow Oblast on the contamination of the lower troposphere of the Western Moscow Oblast with nitrogen dioxide and formaldehyde is specified.

The mechanisms of dangerous effects of lightning discharges are investigated in the paper. Analysis of electrical parameters of thunderstorm discharges in the atmosphere using the data of geophysical monitoring center of the High- Mountain Geophysical Institute (Nalchik, Russia), which includes a network of automatic lightning sensors LS8000 were fulfilled. The results of the ground discharges registration and the time of their increase received during its operation are analyzed. The authors determined the statistical distribution of the amplitude of the lightning current. It is found that the parameters of the discharges in different areas are varies in a great range and can change over time. The effective operation of lightning protection systems and the implementation of life safety measures in case of thunderstorms requires monitoring of the lightning discharge situation in each region.

IASI (Infrared Atmospheric Sounder Interferometer) soundings for the years 2014 to 2017 over sea surface for the Hawaii region have been used to retrieve column amount of CO₂, CH₄, N₂O. The analysis allowed us to derive CO₂, CH₄ and N₂O growth rates, trend and seasonality, which have been compared to in situ observations from the Mauna Loa validation station. Day and night soundings have been used. During the day, for CO₂ and N₂O we make specifically use of the IASI short wave band (2000 to 2250 cm^-1), which is sensitive to sun radiation. Our forward/inverse module deals with sun radiation using a Cox-Munck model for the bidirectional reflectance distribution function. This makes it possible to exploit IASI soundings in sun-glint or close to sun-glint mode, which improves sensitivity of retrievals close to the surface. The analysis has been performed with our total IASI level 2 processor or τ²IP, which uses the whole IASI spectral coverage, therefore making it possible to exploit the whole information content of data. The code τ²IP also uses a random projection approach to reduce the dimensionality of the data space. Our analysis show that growth rate, trend and seasonality are extracted with high accuracy (we observe correlation with in situ data close or higher than 0.90). After validation, we have applied τ²IP to seven years of data over the Arctic sea basin and computed summer maps (July to September) of CO₂ and sea skin temperature. The results show that the increase of skin temperature parallels the increase of CO² column amount over the Arctic basin.

The total aerosol burden in the atmosphere is typically represented by aerosol optical depth (AOD). To capture important and climate-relevant signatures of the aerosol burden, such as year-to-year and seasonal variability, continuous multi-year AOD observations are required. For more than two decades, these observations have been performed at the mid-continental Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility (CF) using ground-based passive remote sensing. The partially overlapping and fragmentary AOD records at the ARM SGP CF have been provided by four individual instruments, namely two co-located (C1 and E13) Multifilter Rotating Shadowband Radiometers (MFRSRs), a Normal Incidence Multifilter Radiometer (NIMFR), and a Cimel Sunphotometer (CSPHOT). Since these individual records are sporadic with instrument- and time-dependent data quality, development of a continuous multi-year high-quality AOD dataset is a challenging task. In this work, an initial development of a continuous 20-year (1997-2017) high-quality AOD product is introduced. The development involves (1) incorporation of the available data quality information and delivery of the historical time series of AOD with high quality from four individual instruments, (2) comparison of multiple AOD retrievals to identify potential instrument-related issues and/or retrieval problems, and (3) merging these individual time series, generation of a two-decade continuous climatology of high-quality AOD and reporting of the uncertainty estimations of the merged product.

The monitoring of the impact of aerosols in Latin America on a local scale is usually limited due to the infrastructure and instrumentation available. In Colombia, there are two international ground surface monitoring networks, the AErosol RObotic NETwork (AERONET) and the Latin American LIDAR NETwork (LALINET). However, the AERONET performance relies on only one sun photometer which makes measurements distributed among five ground-based stations in different cities such as Bogotá and Medellín. On the other hand, LALINET has only one ground-based station formed by an elastic LiDAR system located at Medellín. Although Cali is the largest city of Colombian southwestern, with an accelerated grown rate of both urban and vehicular fleet, and counts with the third largest population of this country, is not reached by these networks. Here, we report on the implementation of a monostatic-coaxial multispectral LiDAR system using a pulsed Nd:YAG laser with 450 mJ of average energy at 1064 nm. To perform the atmospheric measurements, this system is capable of spatially resolving elastic backscatter down to 3.75 m with a Pulse Repetition Frequency (PRF) of 10 Hz. We have developed a hybrid algorithm for data analysis by combining the Fitting and Gradient method and the Klett-Fernald algorithm to estimate the Planetary Boundary Layer (PBL) Top and the optical properties of aerosols. This work constitutes the first quantitative atmospheric exploration to study the aerosols dynamics and the PBL in the northwest of South America.

The IPCC has identified the indirect aerosol effect as the biggest uncertainty in the Earth's climate system. For this reason, efforts are being made to measure aerosols and the associated effect on the climate. Antarctica is often used to reveal changes in the global background. One of the characteristics enabling to separate aerosol of the local origin from the background level is the aerosol vertical profile. A MAX-DOAS technique is among the approaches that can give information on the aerosol vertical distribution.
The paper presents instrumentation and preliminary results of aerosol measurements which were conducted in eastern Antarctica, near the Russian station "Progress" (69°22S 76°23E, Larsemann Hills). The aerosol measurements were performed using a MAX-DOAS instrument called MARS-B originally designed by NOMREC of BSU. The MARS-B instrument records spectra of the scattered sunlight in a range of the elevation angles of 0°–90° in the UV and visible range of 341-426 and 416-500 nm with FWHM=0.32 nm.
To retrieve aerosol extinction, we used its influence on the optical depth of the collision complex O₂-O₂ (or O₄) of the molecular oxygen O₂. Aerosol extinction was obtained for the wavelengths of 370 and 458 nm. The MAX-DOAS aerosol measurements were performed in January and February, 2014, and were further compared with Cimel-CE318 solar photometer data for clear days. Features of two data series are discussed in brief.

Substantial difference between cloud amounts obtained from active and passive remote sensing has been documented by previous studies. The difference is typically attributed to two main factors: the different field-of-view (FOV) (first factor) and different sensitivity to cloud properties (second factor) of the active and passive ground-based instruments. The relative impact of these two main factors on shallow cumuli cloud amount is demonstrated in this study. The demonstration involves a new multi-year (2000-2017) product, which integrates both the active and passive remote sensing data collected at the mid-continental Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility. Cloud fraction (CF) obtained from the narrow-FOV lidar-radar observations and wide-FOV fractional sky cover (FSC) acquired from sky images are key components of the integrated product. Results of this study indicate that (1) CF tends to overestimate FSC and this overestimation can be large (~40% on average) even at extended temporal scales (several years) and (2) the observed overestimate is primarily due to different sensitivity of the active and passive remote sensing instruments to shallow cumuli, while the limited FOV of active remote sensing instruments plays a minor role in such overestimation.

Cloud coverage is an important issue for Earth observation satellite programs as remote sensing images are useless if their cloud fraction is too high or if specific targets are not visible. These flawed acquisitions must be reintroduced in the waiting list, leading to significant delays. Agile satellites are able to choose between several targets according to various priority parameters, including cloud coverage forecasting. This paper assesses a short-term cloud forecasting method which uses time series acquired by a geosynchronous satellite and a cloud motion vector processing technique to predict the evolution of the cloud coverage up to six hours in the future. Using several SPOT/Pléiades acquisition dates from 2015 to 2017, and the corresponding Meteosat-8 datasets, cloud fraction forecasts have been produced for time horizons ranging from fifteen minutes to six hours, and compared to other forecast results obtained using two classical numerical weather prediction (NWP) models: GFS and ICON. Satellite-based forecast showed several advantages compared to these methods. First, the algorithm is much faster – a few minutes, whereas NWP models need several hours to build a forecast – allowing to get a result quickly from fresh dataset. Moreover, forecasts obtained with satellite images have a better time resolution – 15 minutes instead of one hour – and outperform GFS and ICON results in terms of prediction accuracy for horizons less than 3.5 hours.

Microphysical properties of the cirrus cloud ice crystals with the horizontal orientation are required for numerical models of radiation balance. Retrieving the orientation distributions function of the crystals from a vertically pointing lidar is a very complicated problem because of lake of the information. The paper shows that the lidars with zenith scanning can be effectively used to retrieve the degree of the horizontally oriented particles (flutter). It is also shown that all the elements of the Mueller matrix give no extra information as far as the depolarization ratio compare to the lidar ratio. Optical properties of the hexagonal ice plates with the size of 10, 30, 100 and 300 μm for the wavelengths of 0.355, 0.532 and 1.064 μm were obtained within the physical optics approximation.

After the launch of the first indigenous navigation satellite, IRNSS, by India, the precipitation water (PW) has caught the attention of researchers as it poses limitations to the position estimates provided by the navigation satellites, by incorporating delay to the satellite signal. Moreover, knowledge of the upper air meteorological element, like the precipitation water (PW) is essential in understanding cloud microphysics and rainfall dynamics. In this paper the authors have made an attempt to study the PW, along with the cloud liquid water (CLW), and the latent heat (LH) over Salem, a southern suburb in India. The aim of this paper is to estimate precipitation water (PW) from the knowledge of rainfall. Correlations of surface rainfall with these elements have been established. The correlations of the CLW/PW/LH have also been investigated under convective rainfall. The CLW, PW and LH values at 14 levels of the atmosphere, from the Earth’s surface up to a height of 18 km above; and the rainfall values have been obtained from the data product 2A12 of the microwave imager (TMI) onboard the Tropical Rainfall Measuring Mission satellite (TRMM). The surface rainfall and the convective rainfall are found to bear significant correlations with these elements. Thus, it appears that it is possible to estimate these elements from the knowledge of surface rainfall. The findings of this paper will be helpful in validating the IRNSS-retrieved precipitation water. The paper also investigates the influence of sunspot number (SSN) and Total Solar Irradiance (TSI) on rainfall over Salem. The SSN/ TSI data have been obtained from the Solar Influences Data Analysis Centre (SIDC), Royal Observatory of Belgium, and the rainfall data have been obtained from the India Meteorological Department (IMD).

Rapid increase of population and urban sprawl have an immense impact on local climatic conditions. Urban heat island, increased surface roughness and enhanced aerosol are some of the prominent factors affecting precipitation in such highly populated urban areas. Among these, the complex interaction of aerosol particles with solar radiation have acknowledged their importance in radiation budget and hence climate dynamics. Being cloud condensation nuclei they also influence cloud lifetime and microphysics in turn influencing precipitation. Present investigation emphases on understanding rainfall and aerosol trends and its spatial occurrence pattern with respect to urbanization. An approach where population as an indicator for urbanization is used in this study rather than a profound investigation on the individual factors of urban induced precipitation anomalies. Mann Kendall trend test is carried out at grid level on a 0.25 degree gridded rainfall data and the trends are then related with the distribution of population in the study area. Areas of significant rainfall trends are identified and are analyzed for spatial patterns around urban areas. These identified urban zones are then further analyzed for aerosol variability. Being a monsoon region, a seasonal variation of aerosols are performed. The results shows that during the monsoon season there is a significant increase in rainfall along the Western Ghats, whereas certain grids along the western coast located at the downwind of populated areas such a Mangalore shows a significant decreasing trend. The overall spatial pattern of rainfall trend during pre-monsoon season is indicative of the influence of urban areas on rainfall. This observation during the pre-monsoon season is quantified which shows that 61% of the trends are included within urban influence zones which are only 36% of the size of Karnataka. Further various cloud characteristics and its association with aerosol loading in these urban areas were investigated. The results are indicative of higher aerosol events suppressing rainfall in these urban areas.

Observed since 1998 recovery of the ozone layer likely caused by prohibiting some ozone-depleting substances under the Montreal Protocol may be unstable. Therefore the homogeneity of the ozone observations in comparison with data of previous decades continues to be important. The network of fully automated Brewer spectrophotometers operated since the earlier 1980s is one of the oldest global systems providing data for the ozone assessments. The existing software for control Brewer spectrophotometers was created more than 35 years ago and is in need of redeveloping to continue the long-term observations in the face of changing computer platforms. New cross-platform operating software for the Brewer is under development by a group of researchers from OIAP of RAS. The software is capable of running on computers with modern multitasking operating systems (Windows, Linux, macOS), and at the same time it has one codebase. In the new Brewer operating software, the Model/View architecture is implemented to separate the code of measurement data (models) from the code of rendering this data to the user or spectrophotometer (views). The model is responsible for data management and provides an interface for reading and writing this data, and the view retrieves the necessary data from the model, reacting to its changes, and sends the data to the user (or spectrophotometer), placing them properly in the GUI of application or into the serial port interface to which a spectrophotometer is connected. Models are developed in the C++ programming language using the cross-platform Qt framework, while the relational database SQLite is used as a persistent storage. The developed database of the new software for storing measurement data and instrumental constants consists of more than 30 tables and stores about 800 pieces of information. This software allows keeping the quality and uniformity of ozone and UV-radiation measurements on the Brewer spectrophotometers of the global ozone network.

Passive Fourier Transform Infrared (FTIR) and Differential Optical Absorption Spectroscopy (DOAS) techniques, i.e. those making use of natural radiation sources are used since the 1970s for the remote sensing of trace gases in the atmosphere. Characteristic for these methods is that they can be put to stationary or mobile use (e.g. cars, multicopters, balloons, aircraft, satellites), are capable of very quickly generating indicative data over a large measurement range and permit quantitative determinations of defined substances. A number of distinct method variations has been developed for specific purposes that cover a broad range of applications in emission and ambient air measurements.

These reasons prompted the Commission on Air Pollution Prevention of VDI and DIN (a standards committee of the German Standards Institute) to establish the German Standards VDI 4211 and 4212 on these techniques. Both Standards are also intended to support and encourage manufacturers and start-ups to develop and produce marketable instruments in consideration of future air monitoring concepts (small, mobile, versatile, multi-component analysers). In order to pave the way for these methods to be recognized by the authorities as equivalent methods to established air quality monitoring methods experience-based minimum requirements for selected performance characteristics are recommended which may be the basis for a future type testing procedure.

Several types of optical imaging methods in scattering media are described in this paper. For each method, the relevant studies and typical systems are listed, and their parameter characteristics and applicable scenarios are analyzed. Prospects for the development of optical imaging technology in scattering media are discussed.

Thin semitransparent cloud removal is not an easy task, because the data optical remote sensing satellite acquired contains not only the information from the terrain object but also the information from the thin semitransparent cloud. For this reason, an atmospheric correction method was used in this study to remove the effect of cloud. A case study is carried out in the world famous cloudy area in the coastal area of the South China Sea. The qualitative and quantitative results show this method works well in the coastal area of cloudy South China Sea. It will make full use of the potential of GF-1 and Landsat data in this area by using this method.

The results of the investigation of radiation characteristics of cirrus consisting of crystalline ice particles with a preferred orientation are discussed. The orientation degree of particles is estimated from the backscattering phase matrices, which are determined with the high-altitude polarization lidar developed at National Research Tomsk State University. It is shown that the orientation of ice crystals in clouds with anomalously high backscattering affects significantly the transmission of solar radiation.

Aerosols can affect climate in multiple and complex ways through their interactions with radiation and clouds. They scatter and absorb sunlight, which modifies the Earth’s radiative balance. Aerosol scattering generally tends to cool the climate, but aerosol absorption has the opposite effect, tending to warm the climate system. Aerosols also serve as condensation and ice nucleation sites, on which cloud droplets and ice particles can form. When influenced by a higher amount of aerosol particles, clouds of liquid water droplets tend to consist of more, but smaller, droplets, which causes these clouds to reflect more solar radiation. To investigate aerosol-cloud-radiation effects, an earth system model called “MIROC-ESM” was used. Long-term simulations using this earth system model were performed for the period 1850 to 2005, using a set of external forces. One simulation used all external forcing, and the other used all external forcing except for anthropogenic aerosols. The comparison between the two simulations showed that anthropogenic aerosol increase leads to cooling of the climate. Additionally, an energy budget analysis indicated that climatic changes to clearsky radiative cooling are primarily determined by changes in column water vapor and aerosol optical thickness. The cloud radiative effect can be related to temperature change.

A doppler wind lidar was employed to investigate the features of the Low-Level Jet (LLJ) at Ipero, Sao Paulo State, Brazil. The Ipero Municipality already host a nuclear facility for uranium enrichment and a new plant, a nuclear reactor, is planned to be built there. The nuclear activities require a good understanding of atmospheric dispersion, as for normal operation conditions as for accidental emissions. The LLJ is a natural phenomenon that may occur within the Planetary Boundary Layer and plays an important role for the atmospheric dispersion. Knowing the LLJ characteristics is essential to evaluate the performances of the weather forecast models that are used as input for the atmospheric dispersion models. The field campaign results showed that the LLJs occur with high frequency at Ipero and that the Stable Boundary Layer (SBL) is shallow, which in turn is unfavored for pollutant dilution because all surface emissions remain confined within the SBL. The 2 weather forecast models evaluated didn´t reproduce the LLJ, despite their high horizontal resolution. The numerical models also underestimated the wind speed. Both the LLJ and the wind speed are key parameters for dispersion simulations. As the weather forecast models diverge of the observational data, they must be better parameterized for provide reliable simulations before being adopted as input for any atmospheric dispersion models. The field campaign (planned to extend for 1 year) data are essential for the parameterization of the numerical models.

The damage caused by thunderstorms increases year by year - this is due to an increase in thunderstorm activity, as well as urbanization, the development of new territories and the expansion of the use of microelectronics and microprocessor technology. The increase in thunderstorm activity is also associated with climate change and solar activity growth, and predicts further growth. This means that comprehensive research and long-term monitoring of thunderstorms are needed, and the importance of systematic analysis of lightning activity data, search for protection measures and warnings about the development of hazardous thunderstorms is increasing. In this article the authors presents the report about on the analysis of the data of remote observations of the network of sensors of auto - radar-rangefinder LS 8000 on the territory of the North Caucasus for the period from 2009 to 2016.