This PDF file contains the front matter associated with SPIE Proceedings Volume 10001 including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

To investigate the methane distributions and transports, the role of related atmospheric processes by determination of vertical profiles of wind, turbulence, temperature and humidity as well as nocturnal boundary layer (NBL) height and the quantification of methane emissions at local and plot scale the so-called ScaleX-campaign was performed in a pre-alpine observatory in Southern Germany from 01 June until 31 July 2015. The following measurements from the ground up to the free troposphere were performed: layering of the atmosphere by a ceilometer (Vaisala CL51); temperature, wind, turbulence profiles from 50 m up to 500 m by a Radio-Acoustic Sounding System (RASS, Metek GmbH); temperature, humidity profiles in situ by a hexacopter; methane farm emissions by two open-path laser spectrometers (Boreal GasFinder2); methane concentrations in situ (Los Gatos DLT-100) with tubes in 0.3 m agl and 5 sampling heads; and methane soil emissions by a big chamber (10 m length, 2.60 m width, up to 0.61 m height) with a plastic cover. The methane concentrations near the surface show a daily variation with a maximum and a frequent double-peak structure during night-time. Analysis of the variation of the nocturnal methane concentration together with the hexacopter and RASS data indicates that the first peak in the nocturnal methane concentration is probably due to local cooling and stabilization which keeps the methane emissions from the soil near the ground. The second peak seems to be due to advection of methane-enriched air which had formed in the environment of the nearby farm yards. These dairy farm emissions were determined by up-wind and down-wind open-path concentration measurements, turbulence data from an EC station nearby and Backward Lagrangian Simulation (WindTrax software). The methane fluxes at plot scale (big chamber) are characterized by emissions at water saturated grassland patches, by an exponential decrease of these emissions during grassland drying, and by an uptake of methane at dry grassland. Highest methane concentrations are found with lowest NBL heights which were determined from the ceilometer monitoring (correlation coefficient 0.56).

Detailed studies and researches about clouds and precipitations characterization are considered to play a key role in weather and strong events prediction. Most monitoring instruments perform indirect monitoring operation, sensing the parameters from a remote position and not being directly inside the phenomenon. A feasibility analysis of a set of disposable sensors is presented. The very light sensors are planned to be dropped by a plane or a UAV (Unmanned Aerial Vehicle) in the atmosphere and are designed to dynamically behave as very light particles similar to raindrops in their fluctuations and falling through the atmosphere. In order to realize sensing probes with a similar fluid-dynamic behavior of drops, the weight, the size and the surface properties of the probes should be carefully designed. An estimated size of the order of many centimeters and a total weight of less than 15 g is needed. Consequently particular attention has to be paid in designing electronic boards and in the choice of integrated measurement sensors as well as the transmitter. Minimum power consumption should be also guaranteed, in order to assure the proper working during the fluctuating and falling time. Sensors installed on the sensing probe will measure different atmospheric parameters (e.g. humidity, temperature, pressure, acceleration) with a sampling interval of the order of some milliseconds. All data are then sent to a receiver located on the ground and can then be stored and post processed for further analysis.

This paper describes one of the issues that are facing the remote sensing community in the not so far future; scientists ask for certain requirement that cannot be fulfilled either due to cost issues or technological issues. The paper starts with giving a short and quick historical overview of the development of spectrometer based remote sensing systems. Next, the likely end of the spectrometers will be explained, followed by a possible alternative.

MACCS is a Multi-Mission Atmospheric Correction and Cloud Screening software. This tool has been developed by CNES. It is based on a multi-temporal algorithm that makes an optimized use of image time series to characterize the atmosphere and detect clouds. We have generated level-2 Sentinel-2 products on various targets over Europe but also over deserts or urban areas with high aerosol optical thickness (AOT). The results are validated by comparison to in-situ measurements from AERONET for AOT and water vapor. We also directly validate ground reflectance using CNES Lacrau photometer. Then, the joint effort of CNES and DLR to merge their algorithms MACCS and ATCOR into a so-called MAJA processing chain will be detailed, together with the future development and validation plan. Finally, the sentinel-2 level-2 production plan will be presented in the context of THEIA land data center.

Comparisons of unfiltered radiances measured by CERES instruments aboard three different satellites, Terra, Aqua, and NPP-Suomi are presented. To enable a comparison at the unfiltered radiance level, viewing geometries of the instruments are matched in the minor plane about 68°N around the summer solstice time for the smallest solar zenith angles of measurements for these high latitudes. Data set for comparison for CERES on Terra and Aqua has been collected since 2002, and for Terra and NPP-S since 2012 in annual field campaigns. For the former, data are collected in June, and for the latter from May to July of each year. Results of comparison are reported for all-sky condition and

PICASSO - A PICo-satellite for Atmospheric and Space Science Observations is an ESA project led by the Belgian Institute for Space Aeronomy, in collaboration with VTT Technical Research Centre of Finland Ltd, Clyde Space Ltd. (UK) and Centre Spatial de Liège (BE). The test campaign for the engineering model of the PICASSO VISION instrument, a miniaturized nanosatellite spectral imager, has been successfully completed. The test results look very promising. The proto-flight model of VISION has also been successfully integrated and it is waiting for the final integration to the satellite platform.

Preliminary measurements of profiles of aerosol/cloud in the lower atmosphere using a homemade stationary groundbased lidar system will be presented. In addition, information on basic characteristics and performance of the lidar system will be provided. Aerosol/Cloud lidar system in monostatic coaxial configuration uses the fundamental (1064 nm) and the second harmonic (532 nm) of a pulsed solid state Nd:YAG laser to provide information on the relative concentration and spatial distribution of aerosol particles and cloud water droplets. Beam expander is used to reduce the laser beam divergence before to be transmitted into the atmosphere. In this study, high-resolution vertical profiles from the near ground up to 15 km altitude are obtained. A Newtonian telescope of diameter 400 mm with an adjustable field of view (FOV) is used to collect the elastic backscattered signal. A photomultiplier tube (PMT) is used for the 532 nm wavelength detection channel, while an avalanche photodiode (APD) is used for the 1064 nm wavelength detection channel. The optoelectronic detection channels use two similar very high frequency preamplification circuit. Data are acquired with a nominal spatial resolution of 7.5 m using a 12-bit 20 MHz analog-to-digital converter (ADC) for each channel. Many functions, such as, range determination, background subtraction, digitization, and averaging are performed by the receiver subsystem. In addition, spatial resolution and linear dynamic range were optimized during signal processing.

We discuss accuracy of our recently developed RT code SORD using 2 benchmark scenarios published by the IPRT group in 2015. These scenarios define atmospheres with a complicate dependence of scattering and absorption properties over height (profile). Equal step, dh=1km, is assumed in the profiles. We developed subroutines that split such atmospheres into layers of the same optical thickness, dτ. We provide full text of the subroutines with comments in Appendix. The dτ is a step for vertical integration in the method of successive orders. Modification of the input profiles from “equal step over h” to “equal step over τ” changes input for RT simulations. This may cause errors at or above the acceptable level of the measurement uncertainty. We show errors of the RT code SORD for both intensity and polarization. In addition to that, using our discrete ordinates RT code IPOL, we discuss one more IPRT scenario, in which changes in height profile indeed cause unacceptable errors. Clear understanding of source and magnitude of these errors is important, e.g. for the AERONET retrieval algorithm.

Aerosol optical depth (AOD) derived from hyperspectral measurements can serve as an invaluable input for simultaneous retrievals of particle size distributions and major trace gases. The required hyperspectral measurements are provided by a new ground-based radiometer, the so-called Shortwave Array Spectroradiometer-Hemispheric (SAS-He), recently developed with support from the Department of Energy (DOE) Office Atmospheric Radiation Measurement (ARM) Program. The SAS-He has wide spectral coverage (350-1700nm) and high spectral resolution: about 2.4 nm and 6 nm within 350-1000 nm and 970-1700 nm spectral ranges, respectively. To illustrate an initial performance of the SAS-He, we take advantage of integrated dataset collected during the ARM-supported Two-Column Aerosol Project (TCAP) over the US coastal region (Cape Cod, Massachusetts). This dataset includes AODs derived using data from Aerosol Robotic Network (AERONET) sunphotometer and Multi-Filter Rotating Shadowband Radiometer (MFRSR). We demonstrate that, on average, the SAS-He AODs closely match the MFRSR and AERONET AODs in the ultraviolet and visible spectral ranges for this area with highly variable AOD. Also, we discuss corrections of SAS-He total optical depth for gas absorption in the near-infrared spectral range and their operational implementation

The NOAA Microwave Integrated Retrieval System (MiRS) retrieves the atmospheric profiles of state variables (temperature, moisture, liquid cloud, hydrometeors, surface emissivity spectrum and skin temperature) simultaneously and coherently with one-dimension Variational (1DVar) method based on passive microwave radiance observation from multiple polar-orbiting operational satellites, including NOAA18, NOAA19, MetOp (A and B), DMSP (F16 and F18) and SNPP. In MiRS, the geophysical consistency between the retrieved state variables is obtained through the constraint from the state variable background covariance matrices, which define the variability of each state variable and the relationship between them. The current atmospheric covariance matrices were mainly built based on the ECMWF 60 layer sample data set (EC60). Because no rain data available in EC60, the MM5 model output rain was used as a substitute. Although MiRS performs well based on current matrices, obviously, there is room for improvement if the matrices could be rebuilt based more representative, higher resolution dataset, and most importantly, all variables are from one datasets, so the cross relationship between parameters could be properly represented. The ECMWF IFS-137 dataset (EC137) is the most recent ECMWF sample data set. Besides several major modifications and improvements in ECMWF forecasting system, comparing with EC60, the profiles in EC137 have more than doubled vertical resolution. The hydrometeor variables are included in EC137, rather than in EC60. With upgraded sampling method, the profiles in EC137 are more evenly distributed in both temporal and spatial domains. And the profile population in EC137 shows significant different statistic characters than its precedents. To generate the new matrices, EC137 data is interpolated from 137 layers to 100 layers. The variable units are transferred to be used for radiation transfer calculation and match with those used in MiRS. For example, the unit of rain and snow is transferred from mass flux (Kg/(m2*s)) to water content (Kg/m2) with the assumption of rain (snow) drop speed as 4.0 (1.0) m/s. Comparing the matrix based on EC137 and that of current MiRS, except the variation in details, there are two significant distinct features are noticeable. First, the snow variable becomes effective in EC137 matrix because the snow variable is provided in EC137 rather than in EC60 and MM5. Second, the covariance between rain and other variables becomes meaningful in EC137 matrix. In the old matrix, rain is not well correlated with other variables, as rain data is from MM5, but other parameters are from EC60, two unrelated datasets. All these differences imply different, most likely better performance of MiRS system if employing the background covariance matrices based on EC137. Tuning is conducted after implementation of the new EC137 matrices. And the impact of the new matrices is assessed by comparing the retrieval products based on the new and old matrices, and with colloated dropsonde, radiosonde and ECMWF analysis profiles.

The state of the art of atmospheric correction for moderate resolution and high resolution sensors is based on assuming that the surface reflectance at the bottom of the atmosphere is uniform. This assumption accounts for multiple scattering but ignores the contribution of neighboring pixels, that is it ignores adjacency effects. Its great advantage however is to substantially reduce the computational cost of performing atmospheric correction and make the problem computationally tractable. In a recent paper, (Sei, 2015) a computationally efficient method was introduced for the correction of adjacency effects through the use of fast FFT-based evaluations of singular integrals and the use of analytic continuation. It was shown that divergent Neumann series can be avoided and accurate results be obtained for clear and turbid atmospheres. We analyze in this paper the error of the standard state of the art Lambertian atmospheric correction method on Landsat imagery and compare it to our newly introduced method. We show that for high contrast scenes the state of the art atmospheric correction yields much larger errors than our method.

A new method for atmospheric correction of high resolution patches over heterogeneous terrain is presented. This efficient method performs atmospheric correction of high resolution surface pressure variations over a patch where gaseous and aerosol constituents can be assumed constant. This is of interest for the validation of surface reflectance for pixels surrounding Aeronet sites in heterogeneous terrain. The method efficiency stems from the smooth variations with surface pressure of the functions used in the atmospheric correction which is exploited to decouple the high resolution variation of elevation/pressure in the atmospheric correction process. This results in very few radiative transfer code evaluations independent of the number of high resolution pixels in the patch. The method allows pressure correction at every point of a high resolution scene decreasing the errors in heterogeneous terrains of current methods by up to two orders of magnitude. The technique can be applied for calibration and validation of surface reflectance to provide a much greater volume of data for performance evaluation.

For the satellite remote sensing data, it is necessary to evaluate the adjacency effect due to atmospheric scattering. Accurate modeling of the adjacency effect requires capabilities dealing with rugged areas and multiple scattering. In this paper, estimation of the adjacency effect is done by calculating the contribution of photons after the multiple scattering process through a many layered atmosphere. For the requirement of fast calculation in remote sensing simulation system, we adopt the approximate ISAACS 2-stream and flux adding method to model the adjacency effect. We evaluate the multiple scattering model by simulating the at-sensor radiance observed over synthetic rugged scenes under varying atmospheric conditions. Radiance comparisons with a single scattering model show good agreement in the clear atmosphere. Relative radiance differences are found to be about 11% in the dust atmosphere, increasing to 15% in the steep areas. Being coupled with the simulation model for remote sensing, it can be used in generation of simulated datasets and validation of the data processing algorithms.

This work focuses on the statistical analysis of day and night hourly pattern of columnar aerosol properties. To that end, we use the large database of star-photometry measurements at the University of Granada station (37.16°N, 3.60°W, 680 m a.s.l; South-East of Spain) for nighttime characterization, and co-located AERONET measurements for the daytime. The aerosol properties studied are the aerosol optical depth (AOD), Angstrom parameter (α(440-870)), aerosol optical depths of fine (AOD_fine) and coarse mode (AOD_coarse) through the Spectral Deconvolution Algorithm (SDA). Microphysical properties are calculated by inverting AOD spectra and include the effective radius (r_eff) and volume concentration (V) of the total size distribution, and also the effective radius of the fine mode (r_fine). The initial analysis for the different air masses that reach the study area reveals that generally day and night values of AOD and α(440-870) are not different statistically. Nighttime values of AOD_fine, r_eff and r_fine do however, present larger values. The influence of North African air masses is remarkable both during the day and night, with high particle loads and low values of the Angstrom parameters and also with large contribution of coarse particles as AOD_coarse and r_eff values are almost the double than for other air masses. The analyses of day-to-night hourly values reveal an increase in AOD, AOD_fine and AOD_coarse during the day and a decrease during the night. Such a pattern could be explained by the different emission rates, accumulation, aging and deposition of particles. Changes in particle radius are also observed as part of the day-tonight particle evolution process, being r_fine variations important mainly at daytime while for r_eff variations are more important at nighttime. Results of day-to-night evolution were found to be independent of air mass origin, and seem to be mainly associated with local processes.

Hourly measurements of pollen near-surface concentration and lidar-derived profiles of volume and particle depolarization ratios during a 5-day pollination event observed in Barcelona, Spain, between 27 – 31 March, 2015, are presented. Maximum hourly pollen concentrations of 4700 and 1200 m^-3 h^-1 were found for Platanus and Pinus, respectively, which represented together more than 80 % of the total pollen. . The pollen concentration was found positively correlated with temperature (correlation coefficient, r, of 0.95) and wind speed (r = 0.82) and negatively correlated with relative humidity (r = -0.18). The ground concentration shows a clear diurnal cycle although pollen activity is also detected during nighttime in three occasions and is clearly associated with periods of strong wind speeds. Everyday a clear diurnal cycle caused by the vertical transport of the airborne pollen was visible on the lidar-derived profiles of the volume depolarization ratio with maxima usually reached between 12 and 15 UT. On average the volume depolarization ratios in the pollen plume ranged between 0.08 and 0.22. Except in the cases of nocturnal pollen activity, the correlation coefficients between volume depolarization ratio and near-surface concentration are high (>0.68). The dispersion of the Platanus and Pinus in the atmosphere was simulated with the Nonhydrostatic Multiscale Meteorological Model on the B grid at the Barcelona Supercomputing Center with a newly developed Chemical Transport Model (NMMB/BSC-CTM). Model near-surface daily pollen concentrations were compared to our observations at two sites: in Barcelona and Bellaterra (12 km NE of Barcelona). Model hourly pollen concentrations were compared to our observations in Barcelona. Better results are obtained for Pinus than for Platanus. Guidelines are proposed to improve the dispersion of airborne pollen by atmospheric models.

In this research, satellite observation data were assimilated into Weather Research and Forecasting Model (WRF) by using Three-dimensional Variational Data Assimilation System (3DVAR) to analyze its impacts on heavy rainfall forecasts. The weather case for this research was during 13-18 September 2015. Tropical cyclone VAMCO, forming in South China Sea near with Vietnam, moved on west direction to the Northeast of Thailand. After passed through Vietnam, the tropical cyclone was become to depression and there was heavy rainfall throughout the area of Thailand. Observation data, used in this research, included microwave radiance observations from the Advanced Microwave Sounding Unit-A (AMSU-A), infrared radiance observations from Infrared Atmospheric Sounding Interferometer (IASI), and GPS radio occultation (RO) from the COSMIC and CHAMP missions. The experiments were designed in five cases, namely, 1) without data assimilation (CTRL); 2) with only RO data (RO); 3) with only AMSU-A data (AMSUA); 4) with only IASI data (IASI); and 5) with all of RO, AMSU-A and IASI data assimilation (ALL). Then all experiment results would be compared with both NCEP FNL (Final) Operational Global Analysis and the observation data from Thai Meteorological Department weather stations. The experiments result demonstrated that with microwave (AMSU-A), infrared (IASI) and GPS radio occultation (RO) data assimilation can produce the positive impact on analyses and forecast. All of satellite data assimilations have corresponding positive effects in term of temperature and humidity forecasting, and the GPS-RO assimilation produces the best of temperature and humidity forecast biases. The satellite data assimilation has a good impact on temperature and humidity in lower troposphere and vertical distribution that very helpful for heavy rainfall forecast improvement.

Remote sensing using THz wave has irreplaceable advantage comparing to the microwave and the infrared waves, and study on the THz remote sensing become more and more popular in recent years. The major applications of the remote sensing in THz wavelengths are the retrieval of the atmospheric parameters and the microphysical information of the ice cloud. The remote sensing of the atmosphere is based on the radiation of THz wave along the earth-space path of which the most significant part is the upward radiation of the atmosphere. The upward radiation of the atmosphere in sunny day in the low latitude area is computed and analyzed in this paper. The absorption of THz wave by the atmosphere is calculated using the formulations illustrated in the Recommendation ITU-R P.676 to save machine hour, the frequency range is then restricted below 1THz. The frequencies used for the retrieval of atmospheric parameters such as temperature and water content are usually a few hundred GHz, at the lower end of THz wavelengths, so this frequency range is sufficient. The radiation contribution of every atmospheric layer for typical frequencies such as absorption window frequencies and peak frequencies are analyzed. Results show that at frequencies which absorption is severe, information about lower atmosphere cannot reach the receiver onboard a satellite or other high platforms due to the strong absorption along the path.

The National Institute of Meteorological Sciences has operated a ground-based Fourier Transform Spectrometer (FTS) at Anmyeondo, Korea since December 2012. Anmyeondo FTS site is a designated operational station of Total Carbon Column Observing Network (TCCON) and belongs to regional Global Atmosphere Watch observatory. A Bruker IFS-125HR model, which has a significantly high spectral resolution by 0.02 cm-1, is employed and instrument specification is almost same as the TCCON configuration. such as a spectrum range of 3,800~16,000 cm-1, a resolution of 1 cm-1, InGaAs and Si-Diode detectors and CaF2 beam splitter. It is found that measured spectra have a good agreement with simulated spectra. In order to improve the spectral accuracy and stability, The Operational Automatic System for Intensity of Sunray (OASIS) has been developed. The OASIS can provide consistent photon energy optimized to detector range by controlling the diameter of solar beam reflected from the mirror of suntracker. As a result, monthly modulation efficiency (ME), which indicates the spectral accuracy of FTS measurement, has been recorded the vicinity of 99.9% since Feb 2015. The ME of 98% is regarded as the error of 0.1% in the ground-based in-situ CO2 measurement. Total column abundances of CO2 and CH4 during 2015 are estimated by using GGG v14 and compared with ground-based in-situ CO2 and CH4 measurements at the height of 86 m above sea level. The seasonality of CO2 is well captured by both FTS and in-situ measurements while there is considerable difference on the amplitude of CO2 seasonal variation due to the insensitivity of column CO2 to the surface carbon cycle dynamics in nature as well as anthropogenic sources. Total column CO2 and CH4 approximately vary from 395 ppm to 405 ppm and from 1.82 ppm to 1.88 ppm, respectively. It should be noted that few measurements obtained in July to August because of a lot of cloud and fog. It is found that enhancement of CH4 from the FTS at Anmyeondo during summer and autumn well corresponds to that from ground-based in-situ CH4 observation. The increase of methane in this period is likely due to CH4 emission from rice paddies and desalinated sea water trapped by seawall around the site.

Clouds cover approximately 70% of the Earth's surface and therefore play a crucial rule in governing both the climate system and the hydrological cycle. The microphysical properties of clouds such as the cloud particle size distribution, shape distribution and spatial homogeneity contribute significantly to the net radiative effect of clouds and these properties must therefore be measured and understood to determine the exact contribution of clouds to the climate system. Significant discrepancies are observed between meteorological models and observations, particularly in polar regions that are most sensitive to changes in climate, suggesting a lack of understanding of these complex microphysical processes. Remote sensing techniques such as polarimetric LIDAR and radar allow microphysical cloud measurements with high temporal and spatial resolution however these instruments must be calibrated and validated by direct in situ measurements. To this end a low cost, light weight holographic imaging device has been developed and experimentally tested that is suitable for deployment on a weather balloon or tower structure to significantly increase the availability of in situ microphysics retrievals.

Cloud detection of satellite imagery is very important for quantitative remote sensing research and remote sensing applications. However, many satellite sensors don’t have enough bands for a quick, accurate, and simple detection of clouds. Particularly, the newly launched moderate to high spatial resolution satellite sensors of China, such as the charge-coupled device on-board the Chinese Huan Jing 1 (HJ-1/CCD) and the wide field of view (WFV) sensor on-board the Gao Fen 1 (GF-1), only have four available bands including blue, green, red, and near infrared bands, which are far from the requirements of most could detection methods. In order to solve this problem, an improved and automated cloud detection method for Chinese satellite sensors called OCM (Object oriented Cloud and cloud-shadow Matching method) is presented in this paper. It firstly modified the Automatic Cloud Cover Assessment (ACCA) method, which was developed for Landsat-7 data, to get an initial cloud map. The modified ACCA method is mainly based on threshold and different threshold setting produces different cloud map. Subsequently, a strict threshold is used to produce a cloud map with high confidence and large amount of cloud omission and a loose threshold is used to produce a cloud map with low confidence and large amount of commission. Secondly, a corresponding cloud-shadow map is also produced using the threshold of near-infrared band. Thirdly, the cloud maps and cloud-shadow map are transferred to cloud objects and cloud-shadow objects. Cloud and cloud-shadow are usually in pairs; consequently, the final cloud and cloud-shadow maps are made based on the relationship between cloud and cloud-shadow objects. OCM method was tested using almost 200 HJ-1/CCD images across China and the overall accuracy of cloud detection is close to 90%.

Although the fact that lidars are used more than half a century, so many of the technical and methodological problem of the laser sensing has not been resolved. Laser sensing of optically dense aerosol formations (such as clouds or fog) belongs to the need of careful study. This is because the lidar signal from such formations is due not only single, but also multiple scattering, which significantly affects both the intensity value and the state of polarization of the received radiation. We have obtained an analytical expression for the time delay of the lidar return from the cloud layer due to multiple scattering. It is shown that the value of this lidar return is determined by the lower boundary, the microstructure and the thickness of the cloud layer, and a field-of-view of lidar receiving system.

A new method for atmospheric correction of high resolution patches over heterogeneous terrain is presented. This efficient method performs atmospheric correction of high resolution surface pressure variations over a patch where gaseous and aerosol constituents can be assumed constant. This is of interest for the validation of surface reflectance for pixels surrounding Aeronet sites in heterogeneous terrain. The method efficiency stems from the smooth variations with surface pressure of the functions used in the atmospheric correction which is exploited to decouple the high resolution variation of elevation/pressure in the atmospheric correction process. This results in very few radiative transfer code evaluations independent of the number of high resolution pixels in the patch. The method allows pressure correction at every point of a high resolution scene decreasing the errors in heterogeneous terrains of current methods by up to two orders of magnitude. The technique can be applied for calibration and validation of surface reflectance to provide a much greater volume of data for performance evaluation.

A Lufft’s CHM 15k “Nimbus” ceilometer and a collocated Cimel Sunphotometer were used to observe planetary boundary layer (PBL) evolution and free tropospheric aerosol layers during a heat-wave that occurred over Central Europe in August 2015. Both instruments were operated in Racibórz, Poland by the Institute of Geophysics PAS since May 2015. The analysis of the data suggests that the PBL top has been elevated to approximately 3000m, a height rarely observed over Poland. Moreover, in the period between 4th and 16th August an unusually high number of aerosol layers were visible in the signals. An analysis based on a backward air mass trajectory (HySplit) and thermal hot-spot (MODVOLC) models combined with a specialized “MISR INteractive eXplorer” (MINX) software provide evidence that at least some of the aerosol was of biomass burning type originating from a strong episode of wildfires in Ukraine.

In this paper the results of the study of the polarization characteristics of double scattering lidar return from drip clouds presents. We calculated the distribution of the intensity of the radiation scattered by cloud and detected by CCDcamera at sensing circularly and linearly polarized radiation. CCD-camera setting in the receiving system lidar.

There are many different statistical and empirical methods of forest fire danger use at present time. All systems have not physical basis. Last decade deterministic-probabilistic method is rapidly developed in Tomsk Polytechnic University. Forest sites classification is one way to estimate forest fire danger. We used this method in present work. Forest fire danger estimation depends on forest vegetation condition, forest fire retrospective, precipitation and air temperature. In fact, we use modified Nesterov Criterion. Lightning activity is under consideration as a high temperature source in present work. We use Web-GIS platform for program realization of this method. The program realization of the fire danger assessment system is the Web-oriented geoinformation system developed by the Django platform in the programming language Python. The GeoDjango framework was used for realization of cartographic functions. We suggest using of Terra/Aqua MODIS products for hot spot monitoring. Typical territory for forest fire danger estimation is Proletarskoe forestry of Kherson region (Ukraine).

Optical properties of the cirrus cloud ice crystals with preferred azimuthal orientation are required for current numerical models of the Earth's radiation balance. Retrieving the orientation distributions function of the crystals from a vertically pointing polarization lidar measuring the full Mueller matrix is a very complicated problem because of lake of information. Lidars with zenith scanning can be used only to retrieve the properties of horizontally oriented particles. The paper shows that if the particles have preferred azimuthal orientation, the polarization lidars with azimuthal scanning should be used. It is also shown that all the elements of the Mueller matrix give no extra information compare to the depolarization ratio. Optical properties of preferred azimuthal oriented hexagonal ice columns with size from 10 to 1000 μm for wavelengths of 0.355, 0.532 and 1.064 μm were collected as a data bank.

Many countries try to launch satellite to observe the Earth surface. As important of surface remote sensing is increased, the reflectance of surface is a core parameter of the ground climate. But observing the reflectance of surface by satellite have weakness such as temporal resolution and being affected by view or solar angles. The bidirectional effects of the surface reflectance may make many noises to the time series. These noises can lead to make errors when determining surface reflectance. To correct bidirectional error of surface reflectance, using correction model for normalized the sensor data is necessary. A Bidirectional Reflectance Distribution Function (BRDF) is making accuracy higher method to correct scattering (Isotropic scattering, Geometric scattering, Volumetric scattering). To correct bidirectional error of surface reflectance, BRDF was used in this study. To correct bidirectional error of surface reflectance, we apply Bidirectional Reflectance Distribution Function (BRDF) to retrieve surface reflectance. And we apply 2 steps for retrieving Background Surface Reflectance (BSR). The first step is retrieving Bidirectional Reflectance Distribution (BRD) coefficients. Before retrieving BSR, we did pre-running BRDF to retrieve BRD coefficients to correct scatterings (Isotropic scattering, Geometric scattering, Volumetric scattering). In pre-running BRDF, we apply BRDF with observed surface reflectance of SPOT/VEGETATION (VGT-S1) and angular data to get BRD coefficients for calculating scattering. After that, we apply BRDF again in the opposite direction with BRD coefficients and angular data to retrieve BSR as a second step. As a result, BSR has very similar reflectance to one of VGT-S1. And reflectance in BSR is shown adequate. The highest reflectance of BSR is not over 0.4μm in blue channel, 0.45μm in red channel, 0.55μm in NIR channel. And for validation we compare reflectance of clear sky pixel from SPOT/VGT status map data. As a result of comparing BSR with VGT-S1, bias is from 0.0116 to 0.0158 and RMSE is from 0.0459 to 0.0545. They are very reasonable results, so we confirm that BSR is similar to VGT-S1. And weakness of this study is missing pixel in BSR which are observed less time to retrieve BRD components. If missing pixels are filled, BSR is better to retrieve surface products with more accuracy. And we think that after filling the missing pixel and being more accurate, it can be useful data to retrieve surface product which made by surface reflectance like cloud masking and retrieving aerosol.

Water vapor is main absorption factor of outgoing longwave radiation. Because increase of water vapor accelerate to become high land surface temperature, it is essential to monitoring the changes in the amount of water vapor and to investigating the causes of such changes. This paper, we monitor variability pattern of Total Precipitable Water (TPW) which observed by satellite. But long-term investigation of climate over Korea peninsula is very difficult due to climatic characteristic in middle latitude of instable atmospheric. El Nino that is one of climate variables appears regularly when compared to the others. Also, precipitation of all climate variables play an important part to analyze variability pattern of water vapor because it is produced by water vapor. Therefore, if we know climatic variability by them, correlation analysis between TPW and climate variables can be improved. In this study, we analyze long-term change of TPW from Moderate-Resolution Imaging Spectroadiometer (MODIS) and precipitation change in middle area of Korea peninsula quantitatively and El Nino was compared to relation of TPW and precipitation. The aim of study is to investigate precipitation and El Nino has an impact on variability pattern of TPW. First, time series analysis is used to calculate TPW and precipitation quantitatively, and anomaly analysis is performed to analyze their correlation. From the results obtained, TPW and precipitation has correlation mostly but the part had inverse correlation was found. We compare it with El Nino of anomaly results. As a result, after El Nino occurred, TPW and precipitation had inverse correlation.

Major anthropogenic sources of sulphur dioxide in the troposphere include point sources such as power plants and combustion-derived industrial sources. Spatially resolved remote sensing of atmospheric trace gases is desirable for better estimation and validation of emission from those sources. It has been reported that Imaging Differential Optical Absorption Spectroscopy (I-DOAS) technique can provide the spatially resolved two-dimensional distribution measurement of atmospheric trace gases. This study presents the results of I-DOAS observations of SO₂ from a large power plant. The stack plume from the Taean coal-fired power plant was remotely sensed with an I-DOAS instrument. The slant column density (SCD) of SO₂ was derived by data analysis of the absorption spectra of the scattered sunlight measured by an I-DOAS over the power plant stacks. Two-dimensional distribution of SO₂ SCD was obtained over the viewing window of the I-DOAS instrument. The measured SCDs were converted to mixing ratios in order to estimate the rate of SO₂ emission from each stack. The maximum mixing ratio of SO₂ was measured to be 28.1 ppm with a SCD value of 4.15×1017 molecules/cm². Based on the exit velocity of the plume from the stack, the emission rate of SO₂ was estimated to be 22.54 g/s. Remote sensing of SO₂ with an I-DOAS instrument can be very useful for independent estimation and validation of the emission rates from major point sources as well as area sources.

The present article describes a new concept of lightning-caused forest fire danger using a probabilistic criterion. The assessment of forest fire danger is made on the basis of the algorithm that classifies the forest territory by vegetation conditions. Lightning activity is processed by the MODIS spectroradiometer according to the World Wide Lightning Location Network data and remote sensing data for the Timiryazevskiy forestry in the Tomsk Region. The cluster analysis of the WWLLN and MOD06_L2 product data are used in the present paper.