This PDF file contains the front matter associated with SPIE Proceedings Volume 9242, including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

Surface solar radiation forecasting permits to predict photovoltaic plant production for a massive and safe integration of solar energy into the electric network. For short-term forecasts (intra-day), methods using images from meteorological geostationary satellites are more suitable than numerical weather prediction models. Forecast schemes consist in assessing cloud motion vectors and in extrapolating cloud patterns from a given satellite image in order to predict cloud cover state above a PV plant. Atmospheric motion vectors retrieval techniques have been studied for several decades in order to improve weather forecasts. However, solar energy forecasting requires the extraction of cloud motion vectors on a finer spatial- and time-resolution than those provided for weather forecast applications. Even if motion vector retrieval is a wide research field in image processing related topics, only block-matching techniques are operationally used for solar energy forecasts via satellite images. In this paper, we propose two motion vectors extraction methods originating from video compression techniques (correlation phase and optical flow methods). We implemented them on a 6-day dataset of Meteosat-10 satellite diurnal images. We proceeded to cloud pattern extrapolation and compared predicted cloud maps against actual ones at different time horizons from 15 minutes to 4 hours ahead. Forecast scores were compared to the state-of-the-art (block matching) method. Correlation phase methods do not outperform block-matching but their computation time is about 25 times shorter. Optical flow based method outperforms all the methods with a satisfactory time computing.

Cirrus clouds are product of weather processes, and hence their occurrence and macrophysical/optical properties can vary significantly over different regions of the world, deriving in different implications in climate-related issues. In this sense, a few case studies of cirrus clouds observed at both subtropical and polar latitudes are examined. Observations are carried out in three stations: Sao Paulo (Brazil, 23.6°S/46.8°W) and Sta. Cruz de Tenerife (Spain, 28.5°N/16.3°W), being both subtropical sites, and the Belgrano II base (Argentina, 78ºS/35ºW) in the Antarctic continent. Active remote sensing (LIDAR) is used for profiling measurements, and cirrus clouds features are retrieved by using a recently proposed methodology. Local radiosounding profiles are also used for cirrus-temperature correlation analysis. Optical and macrophysical properties (COD-cloud optical depth, top/base heights and Lidar Ratio, mainly) of both the subtropical and polar cirrus clouds are reported. This study is focused on the classification of the daily cloud features into three Cirrus COD-related categories: svCi-subvisual (COD < 0.06), stCi-semitransparent (0.06 < COD < 0.3), and opCiopaque (COD < 0.3) clouds. In general, subtropical Cirrus clouds present lower LR values and are found at higher altitudes than those detected at polar latitudes. In addition, a higher svCi presence is observed over the polar station along the day, since svCi clouds are formed at lower temperatures. However, results are specific for those particular cases analyzed in this preliminary work. Similarities and differences can be plausibly provided, as long as a larger dataset can be available to be analyzed in each station.

The availability of very high spatial resolution sensors has for the past few years allowed a precise description of atmospheric scenes for remote sensing and surveillance applications. Clouds presence in the field of view is one of the key factors limiting the performances of these sensors for target detections. However, in order to develop such detection algorithms for images with a fine spatial resolution, a fast 3D radiative transfer tool dedicated to scene generation is necessary to obtain large number of realistic cloud scenes. Three-dimensional effects become more important when going to higher model resolution. For that purpose, fast solutions are needed since three-dimensional radiative transfer solvers are computationally far too expensive. Two different strategies are presented in this paper. On the one hand, an optimization of the explicit method Spherical Harmonic Discrete Ordinate Method (SHDOM) developed by Evans, K. F. (1998), associated with a fast image rendering solution. On the other hand, a fast approximation of 3D radiative transfer.

We introduce and evaluate a simple retrieval of areal-averaged surface albedo using ground-based measurements of atmospheric transmission alone at five wavelengths (415, 500, 615, 673 and 870nm), under fully overcast conditions. Our retrieval is based on a one-line semi-analytical equation and widely accepted assumptions regarding the weak spectral dependence of cloud optical properties, such as cloud optical depth and asymmetry parameter, in the visible and near-infrared spectral range. To illustrate the performance of our retrieval, we use as input measurements of spectral atmospheric transmission from the Multi-Filter Rotating Shadowband Radiometer (MFRSR). These MFRSR data are collected at two well-established continental sites in the United States supported by the U.S. Department of Energy’s (DOE’s) Atmospheric Radiation Measurement (ARM) Program and National Oceanic and Atmospheric Administration (NOAA). The areal-averaged albedos obtained from the MFRSR are compared with collocated and coincident Moderate Resolution Imaging Spectroradiometer (MODIS) white-sky albedo. In particular, these comparisons are made at four MFRSR wavelengths (500, 615, 673 and 870nm) and for four seasons (winter, spring, summer and fall) at the ARM site using multi-year (2008-2013) MFRSR and MODIS data. Good agreement, on average, for these wavelengths results in small values (≤0.015) of the corresponding root mean square errors (RMSEs) for these two sites. The obtained RMSEs are comparable with those obtained previously for the shortwave albedos (MODIS-derived versus tower-measured) for these sites during growing seasons. We also demonstrate good agreement between tower-based daily-averaged surface albedos measured for “nearby” overcast and non-overcast days. Thus, our retrieval originally developed for overcast conditions likely can be extended for non-overcast days by interpolating between overcast retrievals.

Human activities put an increasing stress on the Earth’ environment and push the safe and sustainable boundaries of the vulnerable eco-system. It is of utmost importance to gauge with a comprehensive research program the current status of the environment, particularly in the most vulnerable locations. The Pan-Eurasian Experiment (PEEX) is a new multidisciplinary research program aiming at resolving the major uncertainties in the Earth system science and global sustainability questions in the Arctic and boreal Pan-Eurasian regions. The PEEX program aims to (i) understand the Earth system and the influence of environmental and societal changes in both pristine and industrialized Pan-Eurasian environments, (ii) establish and sustain long-term, continuous and comprehensive ground-based airborne and seaborne research infrastructures, and utilize satellite data and multi-scale model frameworks filling the gaps of the insitu observational network, (iii) contribute to regional climate scenarios in the northern Pan-Eurasia and determine the relevant factors and interactions influencing human and societal wellbeing (iv) promote the dissemination of PEEX scientific results and strategies in scientific and stake-holder communities and policy making, (v) educate the next generation of multidisciplinary global change experts and scientists, and (vi) increase the public awareness of climate change impacts in the Pan- Eurasian region. In this contribution, we underline general features of the satellite observations relevant to the PEEX research program and how satellite observations connect to the ground-based observations.

Surface solar radiation forecasting permits to predict photovoltaic plant production for a massive and safe integration of solar energy into the electric network. For short-term forecasts (intra-day), methods using images from meteorological geostationary satellites are more suitable than numerical weather prediction models. Forecast schemes consist in assessing cloud motion vectors and in extrapolating cloud patterns from a given satellite image in order to predict cloud cover state above a PV plant. Atmospheric motion vectors retrieval techniques have been studied for several decades in order to improve weather forecasts. However, solar energy forecasting requires the extraction of cloud motion vectors on a finer spatial- and time-resolution than those provided for weather forecast applications. Even if motion vector retrieval is a wide research field in image processing related topics, only block-matching techniques are operationally used for solar energy forecasts via satellite images. In this paper, we propose two motion vectors extraction methods originating from video compression techniques (correlation phase and optical flow methods). We implemented them on a 6-day dataset of Meteosat-10 satellite diurnal images. We proceeded to cloud pattern extrapolation and compared predicted cloud maps against actual ones at different time horizons from 15 minutes to 4 hours ahead. Forecast scores were compared to the state-of-the-art (block matching) method. Correlation phase methods do not outperform block-matching but their computation time is about 25 times shorter. Optical flow based method outperforms all the methods with a satisfactory time computing.

In the framework of AMISOC (Atmospheric Minor Species relevant to the Ozone Chemistry) project, a multiinstrumented campaign was performed in the Canary Islands area in summer-time from 01 July to 11 August 2013. Both ground-based remote-sensing and airborne in-situ measurements were performed under dust loading conditions. Saharan dusty (DD) conditions were reported during 57% of the overall campaign period. Particular DD cases corresponded to a 2-day period with a progressively arriving Saharan dust intrusion over Tenerife on 31 July (weak incidence) and 01 August (strong incidence). As reference, the non-dusty (ND) situation on 30 July was also examined. Vertical size distributions (SD) for particles within an extended fine-to-coarse (0.16-2.8 μm) mode were provided by using aircraft aerosol PCASP sonde measurements. Extinction profiles and Lidar ratio (LR) values were derived from Micro Pulse Lidar measurements. Despite no MAXDOAS aerosol profiling retrievals were available, the potential of this technique has also been introduced. A good agreement is found between the optical and microphysical properties, showing dust particles confined in a wide layer of around 4.5 km thickness from 1.5 to 6 km height. Dust incidence mostly affected the Free Troposphere (FT). LR ranged between 50 and 55 sr, showing typical values for Saharan dust particles. In general, the dust impact on mass concentration was enhanced due to the increase of larger particles, affecting both the Boundary layer (BL) and FT, but showing differences depending on the dusty case. MAXDOAS profiles are expected to be included in an extended version of this work.

When monitoring target areas covered with vegetation from a satellite, it is very useful to estimate the vegetation index using the surface anisotropic reflectance, which is dependent on both solar and viewing geometries, from satellite data. In this study, the algorithm for estimating optical properties of atmospheric aerosols such as the optical thickness (τ), the refractive index (Nr), the mixing ratio of small particles in the bimodal log-normal distribution function (C) and the bidirectional reflectance (R) from only the radiance and polarization at the 865nm channel received by the PARASOL/POLDER is described. Parameters of the bimodal log-normal distribution function: mean radius, r1, standard deviation, σ1, of fine aerosols, and r2, σ2 of coarse aerosols were fixed, and these values were estimated from monthly averaged size distribution at AERONET sites managed by NASA near the target area. Moreover, it is assumed that the contribution of the surface reflectance with directional anisotropy to the polarized radiance received by the satellite is small because it is shown from our ground-based polarization measurements of light ray reflected by the grassland that degrees of polarization of the reflected light by the grassland are very low values at the 865nm channel. First aerosol properties were estimated from only the polarized radiance and then the bidirectional reflectance given by the Ross-Li BRDF model was estimated from only the total radiance at target areas in PARASOL/POLDER data over the Japanese islands taken on April 28, 2012 and April 25, 2010. The estimated optical thickness of aerosols was checked with those given in AERONET sites and the estimated parameters of BRDF were compared with those of vegetation measured from the radio-controlled helicopter. Consequently, it is shown that the algorithm described in the present study provides reasonable values for aerosol properties and surface bidirectional reflectance.

Within the European Metrology Research Programme (EMRP)¹ the EUMETRISPEC joint research project was focused on metrological aspects of spectral reference line data² as presented earlier³. We review EUMETRISPEC’s first funding through the EMRP and the outcome of this metrology effort to support the line data and the atmospheric remote sensing community. We describe current examples from the EMRP project to address present deficiencies of available line data. Key points of this project were the development of an open European hardware infrastructure for traceable spectral reference data and the development of standardized procedures to measure traceable molecular spectral line data. The paper describes the development of a spectroscopy infrastructure based on a Bruker IFS 125 HR high-resolution Fourier- Transform Infrared (FTIR) spectrometer, discusses the achieved results on molecular line parameters (e.g. line strengths and pressure broadening coefficients) of the greenhouse gas species CO₂ and CO. Here, metrology aims to provide its additional input in terms of improved quality management, detailed uncertainty assessments and ultimately traceable spectral data linked to the SI units wherever tightened data quality objectives and improved data quality are required for certain remote sensing applications. In this paper we show how metrology efforts support this goal by means of spectroscopy infrastructure. An outline of future activities is given promoting the discussion with the remote sensing community and fostering improved links to the metrology community.

In the framework of the project ChArMEx (the Chemistry-Aerosol Mediterranean Experiment, http://charmex.lsce.ipsl.fr/), the variability of aerosol optical, microphysical and radiative properties is examined in three regional background sites on a southwest – northeast (SW–NE) straight line in the middle of the western Mediterranean Basin (WMB). The three sites are on the northward transport pathway of African dust:  Ersa, Corsica Island, France (43.00ºN, 9.36ºW, 80 m a.s.l),  Palma de Mallorca, Mallorca Island, Spain (39.55ºN, 2.62ºE, 10 m a.s.l) and  Alborán, Alboran Island, Spain (35.94ºN, 3.04ºW, 15 m a.s.l). AERONET (AErosol RObotic NETwork) sun-photometer products are mainly used. A preliminary analysis shows that at Ersa and Palma sites the annual aerosol optical depth (AOD) has a similar trend with a peak around 0.2 in July. The winter/spring AOD is lower in Palma than in Ersa, while it is reverse in summer/autumn. The aerosol particle size distribution (and the coarse mode fraction) shows clearly the SW–NE gradient with a decreasing coarse mode peak (and a decreasing coarse mode fraction from 0.5 - 0.35 - 0.2 in July) along the axis Alborán - Palma de Mallorca - Ersa. In addition to the seasonal and annual variability analysis, the analysis of AERONET products is completed with a large variety of ground-based and sounding balloons remote sensing and in situ instruments during the Special Observation Period (SOP) of the ADRIMED campaign in June 2013. The second part of the presentation will focus on the comparison of the observations at Palma de Mallorca and Ersa of the same long-range transported airmasses. The observations include lidar vertical profiles, balloon borne OPC (Optical Particle Counter) and MSG/SEVIRI AOD, among others.

This contribution evaluates an approach using an extended Kalman filter (EKF) to estimate the planetary boundary layer height (PBLH) from lidar measurements obtained in the framework of the European Aerosol Research LIdar NETwork (EARLINET) at 12 UTC ± 30-min. for a 7-year period (2007-2013) under different synoptic flows over the complex geographical area of Barcelona, Spain. PBLH diagnosed with the EKF technique are compared with classic lidar methods and radiosounding estimates. Seven unique synoptic flows are identified using cluster analysis of 5756 HYSPLIT (HYbrid Single Particle Lagrangian Integrated Trajectory) three-day backtrajectories for a 16-year period (1998-2013) arriving at 0.5 km, 1.5 km, and 3 km, to represent the lower PBL, upper PBL, and low free troposphere, respectively. Regional recirculations are dominant with 54% of the annual total at 0.5 km and 57% of the total lidar days at 1.5 km, with a clear preference for summertime (0.5 km: 36% and 1.5 km: 29%). PBLH retrievals using the EKF method range from 0.79 - 1.6 km asl. Highest PBLH are observed in southwest flows (15.2% of total) and regional recirculations from the east (34.8% of total), mainly caused by the stagnant synoptic pattern in summertime over the Iberian Peninsula. Lowest PBLH are associated with north (19.6% of total) and northeast (4.3% of total) synoptic flows, when fresh air masses tend to lower PBLH. The adaptive nature of the EKF technique allows retrieval of reliable PBLH without the need for long time averaging or range smoothing, as typical with classic methods.

The paper focuses on retrieving the microphysical characteristics of cirrus clouds from lidar data. The beam-splitting algorithm developed by the authors within framework of physical optics approximation has been used to solve the problem of light scattering by the hexagonal ice crystals. The paper presents the color ratio, depolarization ratio, and lidar ratio that have been calculated for the first time for quasi-horizontally and randomly oriented hexagonal ice particles. The lidar experimental data measuring simultaneously the depolarization ratio and color ratio in cirrus clouds are also presented.

Monitoring particulate matter less than 10 μm (PM10) near the ground routinely is critical for Malaysia for emergency management because Malaysia receives considerable amount of pollutants from both local and trans-boundary sources. Nevertheless, aerosol data covering major cities over a large spatial extent and on a continuous manner are limited. Thus, in the present study we aimed to estimate PM10 at 5 km spatial scale using AOD derived from MERIS sensor at 3 metropolitan cities in Malaysia. MERIS level 2 AOD data covering 5 years (2007-2011) were used to develop an empirical model to estimate PM10 at 11 locations covering Klang valley, Penang and Johor Bahru metropolitan cities. This study is different from previous studies conducted in Malaysia because in the current study we estimated PM10 by considering meteorological parameters that affect aerosol properties, including atmospheric stability, surface temperature and relative humidity derived from MODIS data and our product will be at ~5 km spatial scale. Results of this study show that the direct correlation between monthly averaged AOD and PM10 yielded a low and insignificant relationship (R²= 0.04 and RMSE = 7.06μg m^-3). However, when AOD, relative humidity, land surface temperature and k index (atmospheric stability) were combined in a multiple linear regression analysis the correlation coefficient increased to 0.34 and the RMSE decreased to 8.91μg m^-3. Among the variables k- index showed highest correlation with PM 10 (R²=0.35) compared to other variables. We further improved the relationship among PM10 and the independent variables using Artificial Neural Network. Results show that the correlation coefficient of the calibration dataset increased to 0.65 with low RMSE of 6.72μg m^-3. The results may change when we consider more data points covering 10 years (2002- 2011) and enable the construction of a local model to estimate PM10 in urban areas in Malaysia.

The OMPS Limb Profiler (LP) was launched on board the NASA Suomi National Polar-orbiting Partnership (SNPP) satellite in October 2011. OMPS-LP is a limb-scattering hyperspectral sensor that provides ozone profiling capability at 1.8 km vertical resolution from cloud top to 60 km altitude. The use of three parallel slits allows global coverage in approximately four days. We have recently completed a full reprocessing of all LP data products, designated as Release 2, that improves the accuracy and quality of these products. Level 1 gridded radiance (L1G) changes include intra-orbit and seasonal correction of variations in wavelength registration, revised static and intra-orbit tangent height adjustments, and simplified pixel selection from multiple images. Ozone profile retrieval changes include removal of the explicit aerosol correction, exclusion of channels contaminated by stratospheric OH emission, a revised instrument noise characterization, improved synthetic solar spectrum, improved pressure and temperature ancillary data, and a revised ozone climatology. Release 2 data products also include aerosol extinction coefficient profiles derived with the prelaunch retrieval algorithm. Our evaluation of OMPS LP Release 2 data quality is good. Zonal average ozone profile comparisons with Aura MLS data typically show good agreement, within 5-10% over the altitude range 20-50 km between 60°S and 60°N. The aerosol profiles agree well with concurrent satellite measurements such as CALIPSO and OSIRIS, and clearly detect exceptional events such as volcanic eruptions and the Chelyabinsk bolide in February 2013.

This paper focuses on stratospheric temperature observations by the Atmospheric InfraRed Sounder (AIRS) aboard NASA’s Aqua satellite. We validate a nine-year record (2003 – 2011) of data retrieved with a scientific retrieval processor independent from the operational processor operated by NASA. The retrieval discussed here provides stratospheric temperature profiles for each individual AIRS footprint and has nine times better horizontal sampling than the operational data provided by NASA. The high-resolution temperature data are considered optimal for for gravity wave studies. For validation the high-resolution retrieval data are compared with results from the AIRS operational Level-2 data and the ERA-Interim meteorological reanalysis. Due to the large amount of data we performed statistical comparisons of monthly zonal mean cross-sections and time series. The comparisons show that the high-resolution temperature data are in good agreement with the validation data sets. The bias in the zonal averages is mostly within ±2K. The bias reaches a maximum of 7K to ERA-Interim and 4K to the AIRS operational data at the stratopause, it is related to the different resolutions of the data sets. Variability is nearly the same in all three data sets, having maximum standard deviations around the polar vortex in the mid and upper stratosphere. The validation presented here indicates that the high-resolution temperature retrievals are well-suited for scientific studies. In particular, we expect that they will become a valuable asset for future studies of stratospheric gravity waves.

Time distributions of ground-based LIDAR echo-signals reflected by the bottom of a liquid droplets cloud were calculated with the help of local estimates of Monte Carlo methods for wavelengths from visible to submillimeter range. The calculations are performed for three models of clouds. In the first model the cloud layer consists only of small droplets of radius from 1 to 20 microns, in the second one there are small and large droplets of radius from 1 to 85 microns and in the third one we take into account small, large and supersize droplets. A density of a particle size distribution is generalized on results of cloud microstructure observations in temperate latitudes. Wavelength range for which one should take into account large and supersize droplets in cloud models is found.

Characterization of gas clouds are challenging situations to address due to the large and uneven distribution of these fast moving entities. Whether gas characterization is carried out for gas leaks surveys or environmental monitoring purposes, explosives and/or toxic chemicals are often involved. In such situations, airborne measurements present distinct advantages over ground based-techniques since large areas can be covered efficiently from a safe distance. In order to illustrate the potential of airborne thermal infrared hyperspectral imaging for gas cloud characterization, measurements were carried out above smokestacks and a ground-based gas release experiment. Quantitative airborne chemical images of carbon monoxide (CO) and ethylene (C2H4) were obtained from measurements carried out using a midwave (MWIR, 3-5 m) and a longwave (LWIR, 8-12 m) airborne infrared hyperspectral sensor respectively. Scattering effects were observed in the MWIR experiments on smokestacks as a result of water condensation upon rapid cool down of the hot emission gases. Airborne measurements were carried out using both mapping and targeting acquisition modes. The later provides unique time-dependent information such as the gas cloud direction and velocity.

The tropospheric distribution of greenhouse gases (GHGs) depends on surface flux variations, atmospheric chemistry and transport processes over a range of spatial and temporal scales. Accurate and precise atmospheric concentration observations of GHGs can be used to infer surface flux estimates, though their interpretation relies on unbiased atmospheric transport models. GHOST is a novel, compact shortwave infrared spectrometer which will observe tropospheric columns of CO₂, CO, CH₄ and H₂O (along with the HDO/H₂O ratio) during deployment on board the NASA Global Hawk unmanned aerial vehicle. The primary science objectives of GHOST are to: 1) test atmospheric transport models; 2) evaluate satellite observations of GHG column observations over oceans; and 3) complement in-situ tropopause transition layer observations from other Global Hawk instruments. GHOST comprises a target acquisition module (TAM), a fibre slicer and feed system, and a multiple order spectrograph. The TAM is programmed to direct solar radiation reflected by the ocean surface into a fibre optic bundle. Incoming light is then split into four spectral bands, selected to optimise remote observations of GHGs. The design uses a single grating and detector for all four spectral bands. We summarise the GHOST concept and its objectives, and describe the instrument design and proposed deployment aboard the Global Hawk platform.

This paper presents a method for tomographically reconstructing atmospheric temperature profiles and wind velocity fields based on acoustic travel time measurements between two or more Unmanned Aerial Vehicles (UAVs). The technique offers mobility and the capacity to monitor hazardous atmospheric environments, otherwise not justifiable on the basis of cost or risk. Simulations, in which the parametric fields of the atmosphere are modelled as a weighted sum of Radial Basis Functions, demonstrate the technique’s potential performance envelope. The approach also allows local meteorological measurements made at the UAVs to supplement any time delay observations. This increases the accuracy of the technique, which has potential for practical applications in boundary layer meteorology, the theory of atmospheric turbulence, and wave propagation through a turbulent atmosphere.

This paper presents a method for tomographically reconstructing spatially varying 3D atmospheric temperature profiles and wind velocity fields based. Measurements of the acoustic signature measured onboard a small Unmanned Aerial Vehicle (UAV) are compared to ground-based observations of the same signals. The frequency-shifted signal variations are then used to estimate the acoustic propagation delay between the UAV and the ground microphones, which are also affected by atmospheric temperature and wind speed vectors along each sound ray path. The wind and temperature profiles are modelled as the weighted sum of Radial Basis Functions (RBFs), which also allow local meteorological measurements made at the UAV and ground receivers to supplement any acoustic observations. Tomography is used to provide a full 3D reconstruction/visualisation of the observed atmosphere. The technique offers observational mobility under direct user control and the capacity to monitor hazardous atmospheric environments, otherwise not justifiable on the basis of cost or risk. This paper summarises the tomographic technique and reports on the results of simulations and initial field trials. The technique has practical applications for atmospheric research, sound propagation studies, boundary layer meteorology, air pollution measurements, analysis of wind shear, and wind farm surveys.

Emission sources as well as wind speed and direction and MLH are important factors which influence high air pollutant concentrations. This is generally known (Schäfer et al., 2006) but the detailed understanding of processes directing certain air pollutant concentrations like HCHO is not complete. To study these processes a long-term campaign in Augsburg, Germany, was performed since March 2012. The concentrations of NO, NO₂, O₃ and HCHO, which were measured with a DOAS from OPSIS across a main traffic road and a nearby park area, are analysed. A ceilometer CL31 from Vaisala which is an eye-safe commercial mini-lidar system is applied to detect layering of the lower atmosphere continuously. Special software for this ceilometer with MATLAB provides routine retrievals of lower atmosphere layering from vertical profiles of laser backscatter data. Meteorological data were measured by a ground-based weather station at the measurement site as well as taken from monitoring data archives of the German National Meteorological Service (DWD), which are measured by radiosondes (Oberschleißheim). Correlation analyses are applied to show the coupling of temporal variations of NO, NO2, O3 and HCHO concentrations with temperature, mixing layer height and wind speed. HCHO which is emitted from both anthropogenic and biogenic sources is studied especially.

Measurements of the formaldehyde (HCHO) atmospheric column are performed at Zvenigorod Scientific Station, Moscow Region, Russia since 2008 by the MAX-DOAS instrument. A previously developed algorithm for the formaldehyde retrieval was updated by adding an availability to use information on the surface albedo and the height of the atmospheric boundary layer provided by other measurements and/or modeling. We present preliminary results of the analysis of observations performed in 2010-2012. The obtained data allow quantifying the Moscow megapolis influence on air quality at Zvenigorod. The average HCHO vertical column density observed at the east winds is larger than one at the west winds. The Moscow influence causes the difference of about 0.85×1016 mol cm-2 between these values. This difference slightly depends on the air temperature and the season. A temperature effect is noticeable in the formaldehyde atmospheric column. Our data show statistically significant positive temperature effect in formaldehyde for the background and polluted conditions for temperatures from –5°C to +35°C. The temperature trend in formaldehyde data at Zvenigorod varies between 7.5×10¹⁴ and 9.3×10¹⁴ mol cm^-2 °C^-1 for all wind directions. The increase of the formaldehyde atmospheric column with the increase of the air temperature can be caused by the HCHO formation from non-methane biogenic volatile organic compounds (mainly - isoprene) for which more emission is expected at higher temperatures, and by growth of areas of forest and turf fires.

A set of three dimensionless parameters is proposed to characterize lidar systems. Two of them are based on an asymptotic approximation of the output signal-to-noise ratio as a function of the input optical power reaching the photoreceiver when there is no background radiation. Of these, one is defined as the ratio between the input signal power level coming from a reference range in a reference atmosphere (reference power level) and the input power level that would produce a reference output signal-to-noise ratio if the photoreceiver operated always in signal-shot noise limited regime. The other is defined as the ratio between the reference power level and the input power level for which the signal-induced shot noise power equals the receiver noise power. A third parameter, defined as the ratio between the background optical power at the photoreceiver input and the reference power level, quantifies the effect of background radiation. With these three parameters a good approximation to the output signal-to-noise ratio of the lidar can be calculated as a function of the power reduction with respect to the power reaching the photodetector in the reference situation. These parameters can also be used to compare and rank the performance of different systems.

In this work we propose a technique for 15-minutes cumulative rainfall mapping, applied over Tuscany, using Italian weather radar networks together with the regional rain gauge network. In order to assess the accuracy of the radar-based rainfall estimates, we have compared them with spatial coincident rain gauge measurements. Precipitation at ground is our target observable: rain gauge measurements of such parameter have a so small error that we consider it negligible (especially if compared from what retrievable from radars). In order to make comparable the observations given from these two types of sensors, we have collected cumulative rainfall over areas a few tens of kilometres wide. The method used to spatialise rain gauges data has been the Ordinary Block Kriging. In this case the comparison results have shown a good correlation between the cumulative rainfall obtained from the rain gauges and those obtained by the radar measurements. Such results are encouraging in the perspective of using the radar observations for near real time cumulative rainfall nowcasting purposes. In addition the joint use of satellite instruments as SEVIRI sensors on board of MSG-3 satellite can add relevant information on the nature, spatial distribution and temporal evolution of cloudiness over the area under study. For this issue we will analyse several MSG-3 channel images, which are related to cloud physical characteristics or ground features in case of clear sky.

Atmospheric correction of satellite images is necessary for many applications of remote sensing, i.e. computation of vegetation indices and biomass estimation. The largest uncertainty in atmospheric correction arises out of spatial and temporal variation of aerosol amount and type. Therefore validation of aerosol estimation is one important step in validation of atmospheric correction algorithms. Our ground-based measurements of aerosol-optical thickness spectra (AOT) were performed synchronously to overpasses of satellites Rapid-Eye and Landsat. Validation of aerosol retrieval by the widely used atmospheric correction tool ATCOR^1,2 was then realized by comparison of AOT derived from satellite data with the ground-truths. Mean uncertainty is ΔAOT550 ≈ 0.04, corresponding approximately to uncertainty in surface albedo of Δρ ≈ 0.004. Generally, ATCOR-derived AOT values are mostly overestimated when compared to the ground-truth measurements. Very little differences are found between Rapid-Eye and Landsat sensors. Differences between using rural and maritime aerosols are negligible within the visible spectral range.

Validation of in-orbit instrument performance is a function of stability in both instrument and calibration source. This paper describes a method using lunar observations scanning near full moon by the Clouds and Earth Radiant Energy System (CERES) instruments. The Moon offers an external source whose signal variance is predictable and non-degrading. From 2006 to present, these in-orbit observations have become standardized and compiled for the Flight Models -1 and -2 aboard the Terra satellite, for Flight Models-3 and -4 aboard the Aqua satellite, and beginning 2012, for Flight Model-5 aboard Suomi-NPP. Instrument performance measurements studied are detector sensitivity stability, pointing accuracy and static detector point response function. This validation method also shows trends per CERES data channel of 0.8% per decade or less for Flight Models 1-4. Using instrument gimbal data and computed lunar position, the pointing error of each detector telescope, the accuracy and consistency of the alignment between the detectors can be determined. The maximum pointing error was 0.2o in azimuth and 0.17o in elevation which corresponds to an error in geolocation near nadir of 2.09 km. With the exception of one detector, all instruments were found to have consistent detector alignment from 2006 to present. All alignment error was within 0.1o with most detector telescopes showing a consistent alignment offset of less than 0.02o.

The main focus of this paper is a comparison of unfiltered radiances measured by CERES instruments operating on three different platforms, namely the Suomi-NPP, Terra and Aqua satellites. Data for the comparison have been continuously collected since FM5 aboard the S-NPP started its science mission in February of 2012. Three difference strategies have been devised for the purpose of comparing CERES scanners, and two of them utilize a special scanning mode. Since in all three strategies viewing geometries of instruments (FM5 and FM3, and also FM5 and FM1) are matched, comparison at the unfiltered radiance level is enabled. This approach provides a data set with reduced uncertainties for comparing shortwave channels, and also outgoing daytime longwave radiation. Gridded averages are mainly processed to determine differences in scanner’s measurements, and statistics are computed primarily for “all-sky” conditions. However, in one of the strategies, comparison is done at a footprint level for a more stringent test of the consistency between the two instruments (FM5 and FM3) for specific scene types. Results of the unfiltered radiance comparison are based on ES8 or ERBE-like data product using Edition-1 for FM5, and Edition-3 for FM1 and FM3.

Downward longwave radiation (DLR) at the earth’s surface is a major component of surface radiation budget and thus the climate, and remote sensing provides the most effective method to get surface DLR on a large scale. This paper presents a comparison of several DLR algorithms for both clear-sky and cloudy-sky conditions. These algorithms were applied to MODIS Terra data and extensively validated using one year's ground data at 13 stations around globe. For clear sky conditions, two algorithms using atmospheric parameters, two algorithms using satellite thermal radiances, and an algorithm that combined using satellite thermal data and atmospheric parameters were compared. The validation result indicated that the first type of algorithms often underestimated DLRs over high altitude regions, while the second type of algorithms performed well over these regions but had significant positive errors over arid regions. The third type of algorithm had acceptable results over all types of regions. Furthermore, the study found that using NCEP derived atmospheric parameters could effectively improve the performance of the first algorithms over high altitude regions, compared with MODIS atmospheric product. For cloudy conditions, three parametric algorithms that determined cloud radiative effect by cloud base temperature, and an empirical algorithm that employed cloud water path and cloud ice path were compared. The validation results indicated that the empirical algorithm had best results in most of the sites, while the three parametric algorithms were greatly influenced by the uncertainties of cloud parameters.

Downward shortwave radiation (DSR) receipt at the Earth’s surface is an important parameter in models of ecosystem dynamics and climate change. This paper presents a methodology to estimate DSR using hourly geostationary satellite (MTSAT-1R) and MODIS BRDF albedo parameter product (MCD43C1). The proposed algorithm retrieves atmospheric parameters directly from MTSAT-1R images by searching and interpolating look-up tables (LUT), which are created by the SBDART. The derived cloud optical thickness together with surface albedo and DEM are used to calculate the instantaneous downward shortwave radiation under cloudy sky. Hourly and daily DSR is calculated by the diurnal cycle integration of hourly instantaneous downward flux. The retrieved daily DSR is compared with ground-based measurements at 96 stations from China Meteorological Administration (CMA). The results show that the estimated DSR is in good agreement with ground measurements over China with a correlation coefficient of 0.93 and a mean bias of 5.8%. Root-mean square differences in the daily DSR are 20.7% for all sky conditions. The daily DSR is also compared with observations on Tibetan Plateau and the results shows a correlation coefficient of 0.91 and a mean bias of 1.53%. Root-mean square differences are 17.5%. The differences between the satellite derived estimates and ground observations may be attributed to calibration uncertainty of the satellite sensor and the ground instruments, undetected cloud shadows, steps of the LUT parameters, uncertainty in determining surface reflectance, and errors in ground observations.

Both natural and anthropogenic aerosols are emitted to the atmosphere. The increase in anthropogenic aerosol emissions in East Asia associated with rapid economic growth combined with the complex behavior of natural dusts makes predicting aerosol distribution in this region extremely difficult. Therefore, detailed investigation of atmospheric particles is important. In this study, the characteristics of aerosols over East Asia were investigated using a combination of ground measurements and model simulations. Ground measurement data was collected using a sunphotometer supported by NASA/AERONET (aerosol robotics network) and a suspended particulate matter (SPM) sampler. In addition to altering the radiation budget, aerosols may also affect cloud cover and precipitation, which, in turn, influence the emission of natural aerosols. Thus, model simulations were utilized to investigate the influence of these changes on natural dust loading.

In this study two neural networks were implemented in order to emulate a retrieval model and to estimate the sulphur dioxide (SO₂) columnar content and cloud height from volcanic eruption. ANNs were trained using all Infrared Atmospheric Sounding Interferometer (IASI) channels in Thermal Infrared (TIR) as inputs, and the corresponding values of SO₂ content and height of volcanic cloud obtained using the Oxford SO₂ retrievals as target outputs. The retrieval is demonstrated for the eruption of the Eyjafjallajökull volcano (Iceland) occurred in 2010 and to three IASI images of the Grímsvötn volcanic eruption that occurred in May 2011, in order to evaluate the networks for an unknown eruption. The results of validation, both for Eyjafjallajökull independent data-sets, provided root mean square error (RMSE) values between neural network outputs and targets lower than 20 DU for SO₂ total column and 200 mb for cloud height, therefore demonstrating the feasibility to estimate SO₂ values using a neural network approach, and its importance in near real time monitoring activities, owing to its fast application. Concerning the validation carried out with neural networks on images from the Grímsvötn eruption, the RMSE of the outputs remained lower than the Standard Deviation (STD) of targets, and the neural network underestimated retrieval only where target outputs showed different statistics than those used during the training phase.

Monitoring volcanic emissions is important for many reasons, most notably for impacts on climate and possible hazards for human health or aviation safety. Satellite instruments allow for long-term monitoring of volcanic emissions on a global scale. In this paper we introduce new detection indices for volcanic ash and sulfur dioxide (SO₂) that are optimized for radiance measurements of the Atmospheric InfraRed Sounder (AIRS). Radiative transfer calculations are used to determine the sensitivity of the ash index (AI) on the aerosol optical depth and the SO₂ index (SI) on the SO₂ column density. A case study on AIRS observations after the eruption of the Puyehue Cordon-Caulle, Chile, in June 2011 demonstrates that the new indices work in practice. A statistical analysis of a ten-year record (2002 to 2013) of AIRS data provides AI thresholds that help to better discriminate volcanic emissions from regular events such as dust storms. We compared our new SI with the AIRS operational product and found that it is more sensitive and better suppresses interfering background signals. Our new volcanic emission data products have been successfully applied in other scientific studies.

Spectral unmixing technique is used in remote sensed data analysis for the determination of certain basis spectra called 'endmembers'. Once those spectra are found, the image cube can be 'unmixed' into fractional abundance of each material in each pixel. In the present work infrared spectra recorded by Infrared Atmospheric Sounding Interferometer (IASI) were used to characterize the emission from Grimsvotn volcanic eruption on 2011. In particular, a methodology based on spectral unmixing theory was used in order to extract the spectral signature of volcanic cloud constituents, such as ash and sulphur dioxide (SO2) and maps of their abundances in a IASI image were obtained. Taking the advantage of IASI broad spectral coverage the broadband signature in the Thermal Infrared (TIR) radiance spectra in the 1000-1410 cm^-1 range associated with the presence of aerosols was obtained. Volcanic ash and SO₂ spectral signatures were extracted, as well as those related to the simultaneous presence of ash, SO₂ and cloud. The study proved that spectral unmixing, applied to Hyperspectral images, is able to identify volcanic aerosols and other species like SO₂ despite a strong presence of meteorological clouds. Moreover, the analysis of hyperspectral datasets permitted to generate abundance maps for each endmember extracted. In particular, maps obtained for the test case of 2011 May, 23th put in evidence the separation between clouds of ejected SO₂ and volcanic ash. The former dispersed at Northern latitudes, whilst the latter was situated at southern latitudes, South of Iceland.

This work intends to develop an efficient algorithm for aerosol retrieval in haze episodes. The increasing emissions of anthropogenic particles provide the serious air pollutants. Although extreme concentrations of aerosols in the atmosphere can prevent aerosol monitoring with surface-level sun/sky photometers, satellites can still be used in such conditions to observe the Earth’s atmosphere from space. It is known that the precise simulation of multiple light-scattering processes within the atmosphere is necessary for aerosol remote sensing and needs a long computational time especially in such an optically thick atmosphere as aerosol episode. Accordingly efficient and practical algorithms for radiation simulations are indispensable to retrieve particle characteristics in a case of serious air pollution.

The microphysical processes in fog are examined based on an analysis of four fog events captured by the in-situ and remote sensing synergy at the Cabauw Experimental Site for Atmospheric Research (CESAR) in the western part of the Netherlands. A 35 GHz cloud radar at CESAR has been used in “fog mode” for the first time in the campaign. In this paper, the microphysical parameterization of fog is first introduced as the basis for analyzing the microphysical processes in the lifecycle of fog. The general microphysical characteristics of the four fog events are studied and key microphysical parameters (droplet number concentration, liquid water content, mean radius, and spectral standard deviation) related to fog are found lower than those in other sites due to the low aerosol concentration at Cabauw. The dominant processes in fog are investigated from the relationships among the key microphysical parameters. The positive correlations of each two parameters in lifecycle stages of a stratus-fog case suggest the dominant scheme in fog is droplet activation with subsequent hygroscopic growth and/or droplet evaporation, which is also supported by the combined observations of visibility and radar reflectivity. The shape of fog drop size distribution regularly broadens and then narrows in the whole lifecycle. However, other mechanisms could exist, although not dominating. Collision-coalescence is a significant factor for the continued growth of big fog droplets when they have reached certain sizes in the mature stage. In the datasets, the collision-coalescence process could be distinguished from the unusual negative correlations among the key microphysical parameters in the lifecycle of another stratus-fog case, and the temporal evolutions of droplet number concentration, mean radius, spectra width, visibility and radar reflectivity show the evidence of it.

Retrieval errors of the atmospheric composition using optical methods (DOAS et al.) are under the determining influence of the cloudiness during the measurements. If there is information about the clouds, the optical model of the atmosphere used to interpret the measurements can be adjusted, and the retrieval errors are reduced. For the reconstruction of the parameters of clouds a method was developed based on taking pictures of the sky by a pair of cameras and subsequent processing of the obtained sequence of stereo of frames by a method of morphological analysis of images. Since the directions of the optical axes of the cameras are not exactly known, the graduation of the direction of sight of the cameras was conducted at the first stage using the photographs of the stars in the night sky. As a result, the coefficients of the affine transformation relating own coordinate systems of the cameras were determined. The authors have confined themselves to affine transformations, as the angle between the optical axes was small enough, and the corresponding points on the stereo pair were chosen near the optical axis. At the second stage, the relative shift of the image of the cloud fragment on the second frame of the pair was calculated. Stereo pairs obtained by simultaneous photography, allowed us to estimate the height of cloud. The paper poses and solves the problem of graduation of direction of sight of the cameras, shortly describes the main features of other steps of the method of estimating the height of cloud base. The examples of first evaluations in a real photo are analyzed.

The precipitation radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) satellite has high vertical resolution, and ground radar (GR) has relatively good capability to detect weak precipitation and relatively good horizontal resolution. The joint utilization of PR and GR will be an important factor in maximizing the benefit to be reaped from both instruments. In this paper, we will blend the PR data and GR reflectivity in Nanjing, China based on image fusion algorithm. Integrating PR and GR mainly includes following steps: spatial-temporal matchup of PR and GR data, image fusion algorithms selection and quality evaluation of the fused image.

For users of Electro-Optical (EO) sensors at sea, knowledge on their resolution is of key operational importance for the prediction of the obtainable classification ranges. Small targets may be located at ranges of 20 km and more and the present day sensor pixel size may be as small as 10 μrad. In this type of scenarios, sensor resolution will be limited by blur, generated by atmospheric turbulence, easily being greater than 30 μrad (at 20 km range). Predictions of the blur size are generally based upon the theory, developed by Fried [1]. In this theory, the turbulence strength is characterized by the structure parameter for the refractive index C_n ², of which data are assumed to be available from secondary instruments. The theory predicts the atmospheric Modulation Transfer Function (MTF), which can be incorporated into the total system MTF, used in range performance predictions, as described by Holst [2]. Validation of blur predictions by measurements is a complex effort due to the rapid variations of the blur with time and the problems associated with the simultaneous acquisition of proper C_n ² data. During the FATMOSE trial, carried out over a range of 15.7 km in the False Bay near Simon’s Town (South Africa) from November 2009 to October 2010, these data were collected in a large variety of atmospheric conditions [3]. In stead of the atmospheric MTF, the horizontal and vertical line spread function (LSF) was measured with a camera with 5 μrad resolution. Various methods for the determination of the LSF and the associated problems are discussed in the paper. The width of the LSF is via its Fourier transform directly related to the MTF. C_n ² data were collected with a standard BLS scintillometer over a nearby range. Additional C_n ² data were obtained via conversion of the scintillation data from the same camera and from a high speed transmissometer, collecting data over the same range. Comparisons between blur and Beam Wander predictions and measurements from the FATMOSE campaign are discussed in the paper as well as their impact on the range performance of present day sensors at sea.

Optical turbulence represented by the structure function parameter of the refractive index C_n ² is a relevant parameter for the performance of electro-optical systems and characterization of the atmospheric influence on imaging. It was investigated during a field trial above an Highveld grassland in the atmospheric surface layer at the Rietvlei Nature Reserve close to Pretoria in South Africa from 18th June to 30th June 2013. This campaign was performed to compare different measurement techniques analyzing the diurnal formation of the vertical distribution of optical turbulence up to a height of 16 m above ground. The chosen time period was characterized by a pronounced diurnal cycle of the meteorological conditions, i.e. low variations from day to day. Ultra sonic anemometers were used to measure high frequency time series (50 Hz) of temperature at single points. From the statistical analysis of these time series C_n ² was derived. Three instruments were mounted at a portable mast in the center of slant path measurements over a horizontal distance of 1000 m using large aperture scintillometers (Boundary layer scintillometer BLS 900). Averaging over a time period of 5 minutes, the results of both methods are compared. The agreement in the results of optical turbulence is quite good. Discrepancies and agreement are analyzed with respect to the atmospheric stability and other meteorological parameters. Lowest values of C_n ² at 4.6 m above ground amount to about 8*10^-17 m^-2/3, daily maxima to 6*10^-13 m^-2/3. Additional to the nearly constant meteorological conditions in the diurnal cycle, the uniformity of the terrain let the results of this measurement campaign an ideal data set for investigating methodological questions regarding a comparison of single point measurements with integrated measurements over a horizontal distance. Four stability regimes were identified in the diurnal cycle and investigated. These are convective conditions during the day, neutral conditions about sunrise and sunset, and two different stable regimes at night.

The quality, availability and diversity of satellite-derived earth observation data products are continuously improving. Such satellite products can provide an extensive and complementary view on many matters with respect to intensive but localised in-situ or ground measurements. A search has been undertaken on the available types and sources of satellite data products that could be applicable in the study of the spatio-temporal distribution of aero-optical turbulence in the atmospheric boundary layer. This has included all satellite data products that are relevant to the surface energy balance such as surface reflectance, temperature and emissivity. It was also important to identify active archive data services that can provide preprocessed and quality-filtered time-series products. Products derived from the Moderate Resolution Imaging Spectrometer (MODIS) and other sensors on the NASA Terra and Aqua platforms were of special interest. The use of climatological shortwave and longwave radiative transfer models, combined with satellite-derived data was explored as a method of elucidating the surface heat balance. An in-situ dataset from the Rietvlei vertical turbulence profiling campaign of 2013 was used to validate a number of aspects of the satellite-derived heat balance approach.

A series of experiments have been conducted to evaluate the accuracy of single station, optical systems for measurement of average crosswind velocity. By analyzing the spatial-temporal cross-correlation function of signals caused by turbulence-induced refractive index irregularities, the wind velocity perpendicular to the line of sight is determined. This method allows also for direct measurement of the turbulence structure parameter C_n ² by the angle-of arrival technique. These real-time turbulence values are incorporated into the wind vector estimation to achieve higher accuracy. The evaluated systems include an active technique which measures the backscatter of the transmitted laser pulses and a passive technique where the naturally illuminated scene serves as the light source. Both active and passive systems have been compared to a series of ultrasonic anemometers located along the measurement path. The experiments were performed along a uniform path in various locations. Very good fits (about 0.5 m/sec) have been obtained at all turbulence conditions along a 1000m path.

It is well known that a laser beam propagating through optical atmosphere is affected by atmospheric turbulence. In this paper, we describe an experimental double-passage system for laser beam propagation along a horizontal urban path that can be useful for applications such as free-space laser communications. The setup includes a telescope to focus a laser beam on a retro-reflector, which is located 410 meters away, and the optical-test bench with which we measure intensity and phase fluctuations of the reflected beam. In our measurements scintillation is decreasing with distance from the center of the pupil. This shows the need for further theoretical modelling of double-passage systems.

We study the influence of each Zernike mode on the propagation of a laser beam through the atmosphere by two different numerical methods. In the first method, an idealized adaptive optics system is modeled to subtract a certain number of Zernike modes from the beam. The effect of each aberration is quantified using the Strehl ratio of the longterm exposure in target/receiver plane. In the second method, the strength of each Zernike mode is varied using a numerical space-filling design during the generation of the phase screens. The resulting central intensity for each point of the design is then studied by a linear discriminant analysis, which yields to the importance of each Zernike mode. The results of the two methods are consistent. They indicate that, for a focused Gaussian beam and for certain geometries and turbulence strengths, the hypothesis of diminishing gains with correction of each new mode is not true. For such cases, we observe jumps in the calculated criteria, which indicate an increased importance of some particular modes, especially coma. The implications of these results for the design of adaptive optics systems are discussed.

Our approach for modeling laser beam propagation through turbulence involves parabolic equation method and results of experimental investigation in laboratory. The analytic solution to the problem of the Gaussian beam propagation through non-uniform gas has been derived. The solution depends on the refracted index, i.e. on the gas density. The density distribution can be found from the Navier-Stokes system. The appropriate solution may be constructed by two ways : (i) as a series in powers of vorticity which is supposed to be small; (ii) with the aid of the parametrix method which includes an iterative procedure. It follows from the solution that acoustic radiation of vortex rings arises. Statistical properties of the propagating beam were found from the solution to the parabolic equation as average over time. In experiments the propagation path was equal to 7 m. The laser beam propagation was accompanied by convection and lateral wind. The frequency of turbulent fluctuations was equal to 2-10 Hz. Phase trajectories were found as well as statistical properties of the beam intensity in turbulent gas flow. The conclusion is as follows. Statistical characteristics traditionally used for the estimation of the laser beam special distortions in the open space transmission channels are to be complemented by the dynamic parameters such as the space of embeddings dimension, characteristic frequencies for the phase trajectories and so on.

The use of remote sensing techniques such as adaptive optics and image restoration post processing to correct for aberrations in a wavefront of light propagating through turbulent environment has become customary for many areas including astronomy, medical imaging, and industrial applications. EO imaging underwater has been mainly concentrated on overcoming scattering effects rather than dealing with underwater turbulence. However, the effects of turbulence have crucial impact over long image-transmission ranges and under extreme turbulence conditions become important over path length of a few feet. Our group has developed a program that attempts to define under which circumstances application of atmospheric remote sensing techniques could be envisioned. In our experiments we employ the NRL Rayleigh–Bénard convection tank for simulated turbulence environment at Stennis Space Center, MS. A 5m long water tank is equipped with heating and cooling plates that generate a well measured thermal gradient that in turn produces various degrees of turbulence. The image or laser beam spot can be propagated along the tank’s length where it is distorted by induced turbulence. In this work we report on the experimental and theoretical findings of the ongoing program. The paper will introduce the experimental setup, the techniques used, and the measurements made as well as describe novel methods for postprocessing and correction of images degraded by underwater turbulence.

Fluctuations in the images of scenes viewed over large distances are the most obvious manifestation of the turbulence effects on the imaging of the incoherent objects. While the average or long-exposure imaging is arguably the most well studied topic of the optical propagation in turbulence, and substantial progress was also made in understanding the average short-exposure imaging, the image scintillations for complex extended scenes are not well understood. We discuss some available results of the image scintillation theory and report on some recent progress. We introduce the concept of the scintillation imaging, when unlike the conventional turbulence imaging techniques the variance of the series of images of the scene is calculated and used to gain information either about the object or about the turbulence on the propagation path. The third constraint in the turbulent PSF [1] plays a critical role in the scintillation imaging making scintillation images insensitive to the constant background and emphasizing the areas with higher local contrast. The bilinear structure of the Object-to-Variance (O2V) maps makes it impossible to use the analogues of the PSF or MTF for scintillation images and precludes development of the general theory of scintillation imaging. We discuss the fundamental properties of the O2V kernel and discuss four examples of scintillation images of simple objects. We present the measurement data where colored scintillation images of the edge were obtained. The variance distributions are normalized using the traditional long-exposure images to remove dependence on the object brightness. In this case scintillations are concentrated near the edge and carry information about the turbulence on the imaging path. The amplitude and width of these variance distributions are sensitive to the turbulence level and can be used as passive scintillometer without the need to deploy the laser source and receiver at both ends of the propagation path. Variance images of the object with sinusoidal brightness distribution consists of the uniform background and doublefrequency sinusoidal oscillations. It has the features consistent with turbulent super-resolution originally described in [2]. Namely, for unresolved object oscillating components disappears while the background persevere.

IMOTEP is a GPU-based (Graphical Processing Units) software relying on a fast parallel implementation of Fresnel diffraction through successive phase screens. Its applications include active imaging, laser telemetry and passive imaging through turbulence with anisoplanatic spatial and temporal fluctuations. Thanks to parallel implementation on GPU, speedups ranging from 40X to 70X are achieved. The present paper gives a brief overview of IMOTEP models, algorithms, implementation and user interface. It then focuses on major improvements recently brought to the anisoplanatic imaging simulation method. Previously, we took advantage of the computational power offered by the GPU to develop a simulation method based on large series of deterministic realisations of the PSF distorted by turbulence. The phase screen propagation algorithm, by reproducing higher moments of the incident wavefront distortion, provides realistic PSFs. However, we first used a coarse gaussian model to fit the numerical PSFs and characterise there spatial statistics through only 3 parameters (two-dimensional displacements of centroid and width). Meanwhile, this approach was unable to reproduce the effects related to the details of the PSF structure, especially the “speckles” leading to prominent high-frequency content in short-exposure images. To overcome this limitation, we recently implemented a new empirical model of the PSF, based on Principal Components Analysis (PCA), ought to catch most of the PSF complexity. The GPU implementation allows estimating and handling efficiently the numerous (up to several hundreds) principal components typically required under the strong turbulence regime. A first demanding computational step involves PCA, phase screen propagation and covariance estimates. In a second step, realistic instantaneous images, fully accounting for anisoplanatic effects, are quickly generated. Preliminary results are presented.

The EOSTAR model aims at assessing the performance of electro-optical (EO) sensors deployed in a maritime surface scenario, by providing operational performance measures (such as detection ranges) and synthetic images. The target library of EOSTAR includes larger surface vessels, for which the exhaust plume may constitute a significant signature element in the thermal wavelength bands. The main steps of the methodology to include thermal signatures of exhaust plumes in EOSTAR are discussed, and illustrative examples demonstrate the impact of the ship’s superstructure, the plume exit conditions, and the environment on the plume behavior and signature.

Correction of atmospheric effects on the propagation of laser light can be achieved with adaptive optics (AO) by relying on adequate wavefront sensors. For free-space laser communications and for tracking of high-speed airborne objects, conventional wavefront sensing methods e.g. those based on the Shack-Hartmann sensor (SHS), are not always effective. Partial obscuration and saturation of the detector due to strong turbulence lead to errors in wavefront reconstruction. Another drawback of Shack-Hartmann wavefront-sensing is the timeconsuming readout of the whole detector and subsequent matrix-vector multiplication necessary to reconstruct the wavefront. We characterize a promising modal alternative: digital holographic wavefront sensor (DHWS).We examine the performance of the sensor for single-, and multimode operation and its dependence on the detector size, scintillation, residual tip/tilt and misalignments.

Based on a proposed electrically tunable liquid crystal (LC) micro-lens array (MLA) instead of a commonly used microlens array with fixed focal length in a conventional type, a new prototyped Shack-Hartmann sensor is reported. The LCMLA with 128 × 128 elements is fabricated by the methods of photolithography and hydrochloric acid etching. Composed of the proposed LC-MLA and a CCD, a new type Shack-Hartmann wavefront sensor is got. This kind sensor can solve problems of the tradition wavefront sensor that the larger measurement range and high measurement accurate can't be realized by the same device. Except for adaptive switching the two working modes, this wavefront sensor also has a dual-mode imaging feature with obtaining wavefront information of the target and it's two-dimensional optical intensity image at the same time. In order to verify it's characteristics, an extreme experiment is designed, which introduces a distortion wavefront. At this circumstanc, the traditional wavefront sensor can't get anything. However, with proposed wavefront sensor, this situation can be solved by adjusting the applied voltage of LC-MLA to change it's focal length. With a reconstruction method, the three-dimensional information of the wavefront can be got. At the same time, the two-dimensional optical intensity image is also got. From the experiments, we can prove that it can effectively improve detection sensitivity and dynamic measurement range of wavefront. Results of the prototype demonstrated qualitatively verify this feasibility. This kind new type wavefront sensor will have a wide variety of applications in adaptive optics.

Adaptive optics (AO) system can be used to detect and compensate the aberrational wavefront of beam in real time. The compensative ability will be affected by the detecting precision of wavefront. Noise is one of the most important factors that affect the detecting precision of Hartmann-Shack (HS) sensor. Noise can induce the errors of centroid detected by HS sensor, consequently influences the wavefront reconstruction. Based on the characteristic of Charge Coupled Devices (CCD), the model that simulates the detecting precision of wavefront affected by noise is built. Based on the factual application scene of artificial beacon, for typical HS sensor, the effects of noise on the detecting precision of wavefront are simulated, and the relations of wavefront beam spot in CCD, and the number of pixel used to calculate spot centroid are analyzed. Several results that can be used in engineering application are obtained.

Liquid crystal based phase only spatial light modulator has attracted many research interests since last decades because of its superior advantage. Until now the liquid crystal spatial light modulator has been applied in many fields, but the response speed of nematic LC limited its further application. In this paper, an optically addressed phase only LC spatial light modulator was proposed based on polymer network liquid crystal. Morphology effect on the light scattering of PNLC was studied, which was mainly consisted of fiber and fiber bundles. The morphology nearly determined the light scattering and electro-optical property. Due to the high threshold voltage, to address the PNLC phase modulator was also concerned. Optical addressing method was proposed, in which BSO crystal was selected to replace one of the glass substrate. The response speed of PNLC was so fast that the reorientation of liquid crystal director will follow the change of effective voltage applied on LC layer, which was related with the voltage signal and especially with electron transport of photo-induced carriers due to diffusion and drift. The on state dynamic response of phase change was investigated. Based on this device, beam steering was also achieved by loading 488nm laser strip on the optical addressed phase only spatial light modulator.

Efficiency of the adaptive focusing of coherent laser beam of radiation in a turbulent atmosphere is examined. The calculation of distributing of averaged intensity of the field of coherent laser beam, focused in a turbulent media at the use of adaptive phase correction with the use of image of non-coherent source as a guide source is executed. We will mark that for effective work of wave-front cross-correlation sensor at track it is necessary to use maximally small in size, but contrasting display element. From the analysis of the theoretical expression easily to conclude that for vertical atmospheric paths, taking as a size of effective object of track the minimum settled object at a short exposure, such object can be counted practically by a point object. And he can be effectively used for the correction of phase. In an atmosphere on extensive paths strong aerosol scattering of image of guide source is possible and only extensive enough object, i.e., an object, having low spatial frequencies (LSF), will be visible contrastingly on a background other objects. It is related to that frequency-contrast characteristic of aerosol atmosphere has maximum in the area LSF and falls on spatial high-frequencies.