The study of interactions between aerosol particles, atmospheric dynamics and clouds and their resulting corresponding indirect effects on precipitation and radiative transfer demand new measurement strategies combining the strength of lidar, radar, and in-situ instrumentation. To match this challenge the Leipzig Aerosol and Cloud Remote Observations System (LACROS) has been set up at TROPOS, combining the strengths of a unique set of active and passive remote sensing and in-situ measurement systems.

The exploitation of multifrequency differential attenuation measurements at microwaves made between two LEO satellites in limb mode is the ground of the NDSA (Normalized Differential Spectral Attenuation) approach for estimating integrated tropospheric water vapor profiles through multifrequency measurements at 17, 19, 21, 179 and 182 GHz, plus 32 GHz for liquid water detection and correction (whenever possible). Such measurements are affected by two kinds of impairments, the first generated by thermal noise at the receiver, the second generated by the signals’ fluctuations due to the variations of the tropospheric refraction index and referred to as scintillation disturbance. Characterizing scintillation for simulating its effects to evaluate NDSA performance is not easy in general: in particular, it is quite hard (and also rather questionable so some extent) to relate the scintillation parameters to a given simulated atmospheric situation. For this reason, in the past years we limited ourselves to evaluate the NDSA performance by accounting for scintillation in a parametric way, independently of the atmospheric context in which simulations were carried out. In this paper, instead, we show the first results of the NDSA performance analysis based on a completely different approach, where the scintillation profiles and parameters are directly derived from the simulated atmospheric context, based on a procedure that starts from high resolution radiosonde data. A brief critical analysis of such an approach is proposed, evidencing some aspects related to the current knowledge of the scintillation spectra and parameters. The NDSA performance analysis based on certain hypotheses for the scintillation characteristics is then shown for some selected simulated atmospheric conditions.

Monitoring of atmospheric compounds at high latitudes is a key factor for a better understanding of the processes driving the chemical cycles of ozone and related chemical species. In this frame, the GASCOD (Gas Analizer Spectrometer Correlating Optical Differences) equipment is installed at the Mario Zucchelli Station (MZS - 74.69S, 164.12E) since December 1995, carrying out observations of nitrogen dioxide (NO₂) and ozone (O₃). The recent advances in sensor technologies and processor capabilities, suggested the setup of a new equipment, based on the same optical layout of the 'old' GASCOD , with enhanced performances and improved capabilities for the measurements of solar radiation in the UV-visible spectral range (300-700nm). The efforts accomplished, allowed for the increase of the investigated tracers. Actually, mainly due to the enlargement of the covered spectral range and to the adoption of a CCD sensor, in addition to the NO₂ and O₃ compounds, others species can be monitored with the new instrumental setup such as bromine, chlorine and iodine oxides (BrO, OClO and IO). The innovative equipment called GASCODNG (GASCOD New Generation) was installed at MZS during the 2012/2013 Italian Antarctic expedition, in the framework of the research projects SAMOA (Automatic Station Monitoring Antarctic Ozonosphere) and MATAGRO (Monitoring Atmospheric Tracers in Antarctica with Ground Based Observations) funded by the Italian and Portuguese Antarctic programs respectively. In this paper a brief description of the new equipment is provided, highlighting the main improvements with regard to the 'old' one. Furthermore the full dataset (1996 - 2012) of NO₂ total columns, obtained with the GASCOD installed at MZS, is compared with the data obtained with satellite borne equipments (GOME, SCIAMACHY, OMI and GOME2) and the main statistical parameters are analyzed and discussed in detail.

The use of CFCs, which are the main responsible for the ozone depletion in the upper atmosphere and the formation of the so-called “ozone hole” over Antarctic Region, was phase out by Montreal Protocol (1989). CFCs' concentration is recently reported to decrease in the free atmosphere, but severe episodes of ozone depletion in both Arctic and Antarctic regions are still occurring. Nevertheless the complete recovery of the Ozone layer is expected by about 2050. Recent simulation of perturbations in stratospheric chemistry highlight that circulation, temperature and composition are strictly correlated and they influence the global climate changes. Chemical composition plays an important role in the thermodynamic of the atmosphere, as every gaseous species can absorb and emit in different wavelengths, so their different concentration is responsible for the heating or cooling of the atmosphere. Therefore long-term observations are required to monitor the evolution of the stratospheric ozone layer. Measurements from satellite remote sensing instruments, which provide wide coverage, are supplementary to selective ground-based observations which are usually better calibrated, more stable in time and cover a wider time span. The combination of the data derived from different space-borne instruments calibrated with ground-based sensors is needed to produce homogeneous and consistent long-term data records. These last are required for robust investigations and especially for trend analysis. Here, we perform a review of the major remote-sensing techniques and of the principal datasets available to study the evolution of ozone layer in the past decades and predict future behavio

European metrology research has seen a tremendous change of focus concerning research impacting specific fields of applications. The European Metrology Research Programme (EMRP)¹ in its different calls on environmental and energy subjects has revealed many new metrology projects devoted to problems, applications, and stakeholder needs in atmospheric sensing, pollution management, air quality assessments, and new energy technologies. We present the current status of development of a European infrastructure for traceable spectral reference data to be used, e.g., in remote sensing or for new developments of field-employable spectrometric transfer standards. This is demonstrated by means of standardized measurement approaches we are developing and by new measurement results regarding H₂O, CO₂, and N₂O molecular line parameters, in this paper pressure broadening coefficients. Molecular line data are required to process raw spectra in order to extract column concentrations or local emission rates of specific analytes. Without molecular line data, all instruments were to be calibrated frequently by means of certified reference gas mixtures which were to keep available onboard throughout the instrument’s life time. At present, many instruments use line data from managed line collections like HITRAN and GEISA. These comprise paramount information on many thousands of lines for many different molecular species, but, modern remote sensing applications, like CO₂ emission monitoring by satellites, tend to significantly tighten data quality objectives and thus require improved data quality that go quite frequently beyond that of the present database entries. In this presentation, we will show how metrology attempts to benefit this aim.

We present satellite-based data of the column-averaged dry air mole fraction of atmospheric carbon dioxide (XCO₂) and methane (XCH₄), which were derived from the radiance spectra measured by Greenhouse gases Observing SATellite (GOSAT). We have applied new version of the Photon path-length Probability Density Function (PPDF)-based algorithm to estimate XCO₂ and PPDF parameters. These parameters serve to allow for optical path modification due to atmospheric light scattering and they are retrieved simultaneously with CO2 concentration using radiance spectra from all available GOSAT short wave infrared (SWIR) bands (oxygen A-band, 1.6-μm, and 2.0-μm CO₂ absorption bands). For the methane abundance, retrieved from 1.67-μm absorption band, we applied optical path correction based on PPDF parameters from 1.6-μm CO₂ absorption band. Similarly to widely used CO₂-proxy technique, this correction assumes identical light path modifications in 1.67-μm and 1.6-μm bands. This approach is believed to offer some advantages over the proxy technique since it does not use any prior assumptions on carbon dioxide concentrations. Both carbon dioxide and methane GOSAT retrievals were validated using ground-based Fourier Transform Spectrometer (FTS) measurements provided by the Total Carbon Column Observing Network (TCCON). For XCO₂ retrievals we found subppm station-to-station bias (GOSAT versus TCCON); single-scan precision of mostly below 2 ppm (0.5%); and correlation coefficient for the Northern Hemisphere TCCON stations above 0.8. For XCH4 retrievals over TCCON sites we found single-scan precision below 1 % and correlation coefficient above 0.8.

Air pollution episodes in urban areas often occur during low wind speeds and low mixing layer height (MLH) and can not only be ascribed to increased local anthropogenic emissions. The continuous knowledge of MLH is supporting the understanding of processes directing air quality. If the MLH is located near to the ground, which occurs mainly during winter and night-time, air pollution can be high due to a strongly limited air mass dilution. The Vaisala ceilometer CL31, which is an eye-safe commercial mini-lidar system, is used for long-term continuous remote sensing of MLH. The ceilometer measurements provide information about the range-dependent aerosol concentration; gradient minima within this profile mark the borders of mixed layers. Special software for this ceilometer developed with MATLAB provides routine retrievals of lower atmosphere layering from vertical profiles of laser backscatter data. To study the gaseous pollutants and those compounds important for secondary aerosol formation like NO and NO₂ as well as O₃ The data retrieval software is extended to improve remote sensing of MLH. The original 10-minute-interval values are used to calculate continuous 1-hour-mean values. Gaps and strong variations of the original data are considered. The results of investigations of the meteorological influences and the role of emissions within the context of the air quality in Augsburg are discussed. a DOAS is operated since March 2012 in Augsburg. Information about different road traffic emissions is provided by this one instrument i.e. by path-integrated air pollution information in different directions. The DOAS contains an analyser and an emitter/receiver unit pointing to three retroreflectors. The retroreflectors were installed at lamp masts so that the paths were about 10 m above street level and perpendicular across the streets. The emitter/receiver unit was in a distance of about 20 m to an in situ air pollution measurement station at the ground. Ground-based (weather station) and radiosonde (German National Meteorological Service (DWD), Oberschleißheim) measured meteorological data are used.

The main purpose of eye-safe laser ceilometers is regular reporting of cloud base height, vertical visibility, and cloud cover. These instruments operate unattended in harsh weather conditions. The application of state-of-the-art electronics increases the quality of backscatter profiles and thus qualifies modern ceilometers for applications beyond cloud base detection. The single lens optics of the ceilometers introduced in this paper results in a compact and robust design and enables their application in campaigns monitoring climate change effects. That is why three of the German Terrestrial Environmental Observatories (TERENO) run by the Karlsruhe Institute of Technology are equipped with a ceilometer. The Technical University of Denmark (DTU) utilizes such an instrument to study arctic cloud formation at Station Nord, Greenland. Recent applications include site assessment for solar energy applications in the Arabic Peninsula and monitoring of Sahara dust cloud and biomass burning plume events over Germany. Backward trajectory calculations with the HYSPLIT trajectory model provided by the NOAA Air Resources Laboratory have been carried out to investigate possible sources, including wood fires in southern France and eruptions of the Eyjafjallajökull and Puyehue- Cordón Caulle volcanoes.

An instrument concept called the Birefringent Imaging Doppler Wind Interferometer (BIDWIN) is being validated in the Atmospheric and Space Physics Lab at the University of New Brunswick in collaboration with COM DEV Ltd (Ottawa, Canada) to determine its capabilities for measuring Doppler wind fields in the Earth’s nightglow. The instrument is adapted from a similar approach used to obtain two dimensional images of high speed (~1000 m/s) flow fields in plasmas at the Australian National University. For that application the precision of the wind measurements was not explored in detail. With BIDWIN, the intent is to obtain ~ 5 m/s precision on each bin of a CCD image of the wind field. An examination of the instrument concept and sensitivity of the wind measurements made using this approach is undertaken to determine the feasibility of this criterion. The BIDWIN has the advantage over other instruments that can be used for a similar purpose (such as the field widened Michelson interferometer and Fabry-Perot interferometer) in that it has no moving parts, has a large throughput, is light weight and is relatively cheap to construct. In this paper, the instrument concept is presented and the ideal and non-ideal instrument effects are explored. Calibration measurements conducted using a proto-type of the instrument are used to verify the instrument concept and confirm the feasibility of the approach for making atmospheric wind measurements.

A new algorithm to determine the nitrogen dioxide column density in the atmosphere using the MKIV Brewer spectrophotometers is proposed. The updated technique minimizes the measurement noise and the contribution of several natural and instrumental factors that could interfere with the measurement. For that, recent spectroscopic data are employed in the retrieval and a new set of weighting factors was recalculated taking into account the instrumental characteristics of a real MKIV Brewer. The algorithm was successfully tested on a set of synthetic spectra simulated with a radiative transfer code.

The Advanced Baseline Imager (ABI) is the primary instrument onboard GOES-R for imaging Earth’s weather, climate, and environment and will be used for a wide range of applications related to weather, oceans, land, climate, and hazards (fires, volcanoes, hurricanes, and storms that spawn tornados). It will provide over 65% of all the mission data products currently defined. ABI views the Earth with 16 different spectral bands, including two visible channels, four nearinfrared channels and ten infrared channels at 0.5, 1, and 2 km spatial resolutions respectively. For most of the operational ABI retrieval algorithms, the collocated/co-registered radiance dataset are at 2 km resolution for all of the bands required. This requires down-scaling of the radiance data from 0.5 or 1 km to 2 km for ABI visible and near-IR bands (2 or 1, 3 & 5 respectively), the reference of 2 km is the nominal resolution at the satellite sub-point. In this paper, the spatial resolution characteristic of the ABI fixed grid level1b radiance data is discussed. An optimum interpolation algorithm which has been developed for the ABI multiple channel radiance down-scaling processing is present.

Global Ozone Monitoring by Occultation of Stars (GOMOS) is a satellite instrument onboard the ENVISAT platform that was in operation during 2002{2012. During these years, GOMOS observed about 880 000 vertical profiles of ozone, NO₂, NO₃ and aerosols. The GOMOS measurement principle is relatively simple based on the stellar-occultation technique. In this paper, we present an alternative retrieval algorithm for processing the GOMOS measurements. The presented algorithm is based on the so-called one-step approach, where both the spectral and the vertical inversions are executed simultaneously. This approach has several attractive features. In particular, the one-step approach allows a better use of the smoothness prior information and, unlike in the operative algorithm, the prior given to one specie affects the other species too. This feature is critical when going near the detection limit, especially in the upper troposphere lower stratosphere (UTLS) region. The main challenge in the GOMOS one-step algorithm is to find the correct smoothness priors for the different species at different altitudes. In this paper, we give a technical description of the one-step retrieval algorithm and discuss the differences between this and the operative algorithm. In the case study part of this paper, we compare the one-step and the operative ozone retrievals in Arctic region during the exceptional ozone-depletion conditions in spring 2011. We show that the quality of the ozone profiles can be improved by introducing the one-step algorithm. The improvement is drastic in the lower stratosphere at 15{20km altitude.

Mineral dust has a significant impact on air quality by reducing visibility and causing adverse health effects on humans such as increased respiratory symptoms and decreased lung function. Ground-based monitoring of PM₁₀ and PM_2.5 is the common metric used for assessing air quality degradation. Because of vast dust sources in Northern China and Mongolia, a limited number of existing ground-based sites across this region renders air quality monitoring difficult. Information about air quality within these regions can only be gained by the use of models or satellite data. The goal of this study is to determine satellite value-added information from three passive and one active satellite sensors for the assessment and improvement of local air quality modeling.

A new analytical technique, named fragmentary spectrum registration (FSR), with use of acousto-optical spectrometers (AOS’s) is proposed and studied. It is based on the method of differential optical absorption spectroscopy (DOAS) and the unique AOS feature of fast (10 μs) random spectral access (RSA). The technique is the most efficient for objects exhibiting sparse optical spectra. The technique permits a substantial (up to 100 times) reduction of detection time in comparison with the record time of total spectrum and provides the decrease of inaccuracy of quantitative analysis of multicomponent mixtures containing substances with similar spectral features. The results of numerical simulation with use of real spectra detected by the trace gas monitoring system GAOS based on AOS are presented and discussed. The experimental results demonstrate the capabilities of the FSR-technique for the huge reduction of the measurement time or for the decrease of measurement error (up to 2.5 times) when the total measurement time is fixed while concentrations being varied from the environment background up to industrial emissions level.

ACE is a proposed Tier 2 NASA Decadal Survey mission that will focus on clouds, aerosols, and precipitation as well as ocean ecosystems. The primary objective of the clouds component of this mission is to advance our ability to predict changes to the Earth’s hydrological cycle and energy balance in response to climate forcings by generating observational constraints on future science questions, especially those associated with the effects of aerosol on clouds and precipitation. ACE will continue and extend the measurement heritage that began with the A-Train and that will continue through Earthcare. ACE planning efforts have identified several data streams that can contribute significantly to characterizing the properties of clouds and precipitation and the physical processes that force these properties. These include dual frequency Doppler radar, high spectral resolution lidar, polarimetric visible imagers, passive microwave and submillimeter wave radiometry. While all these data streams are technologically feasible, their total cost is substantial and likely prohibitive. It is, therefore, necessary to critically evaluate their contributions to the ACE science goals. We have begun developing algorithms to explore this trade space. Specifically, we will describe our early exploratory algorithms that take as input the set of potential ACE-like data streams and evaluate critically to what extent each data stream influences the error in a specific cloud quantity retrieval.

Clouds play an important role in influencing the dynamics of local and global weather and climate conditions. Continuous monitoring of clouds is vital for weather forecasting and for air-traffic control. Convective clouds such as Towering Cumulus (TCU) and Cumulonimbus clouds (CB) are associated with thunderstorms, turbulence and atmospheric instability. Human observers periodically report the presence of CB and TCU clouds during operational hours at airports and observatories; however such observations are expensive and time limited. Robust, automatic classification of cloud type using infrared ground-based instrumentation offers the advantage of continuous, real-time (24/7) data capture and the representation of cloud structure in the form of a thermal map, which can greatly help to characterise certain cloud formations. The work presented here utilised a ground based infrared (8-14 μm) imaging device mounted on a pan/tilt unit for capturing high spatial resolution sky images. These images were processed to extract 45 separate textural features using statistical and spatial frequency based analytical techniques. These features were used to train a weighted k-nearest neighbour (KNN) classifier in order to determine cloud type. Ground truth data were obtained by inspection of images captured simultaneously from a visible wavelength colour camera at the same installation, with approximately the same field of view as the infrared device. These images were classified by a trained cloud observer. Results from the KNN classifier gave an encouraging success rate. A Probability of Detection (POD) of up to 90% with a Probability of False Alarm (POFA) as low as 16% was achieved.

The Extreme Universe Space Observatory (EUSO) is an astronomical telescope that will be hosted by the Japan Experiment Module (JEM) on the International Space Station (ISS). The telescope will determine Ultra High Energy Cosmic Rays properties by measuring the UV fluorescence light emitted by the particles generated in the interaction between the cosmic rays and the atmosphere. Therefore, cloud information is crucial for a proper interpretation of the data. To obtain the cloud top height an IR camera is being designed. The design is constrained by JEM-EUSO requirements which are mainly the instrument weight, power and data rate. These requirements have led to a bi-spectral camera option with 1 μm-wide bands centered at 10.8 and 12 μm. The bi-spectral design has allowed us to develop a Split Window Algorithm to correct the atmospheric effects and retrieve the cloud temperature from the brightness temperatures in the bands aforementioned. The algorithm has been checked in synthetic scenarios at pixel level. The simulations consider clouds at different levels with diverse atmospheric conditions. The results show that the algorithm is able to retrieve the temperature with accuracy much better than the required one by the JEM-EUSO mission of 3K. It has also been tested in 2D real scenarios (MODIS images). The algorithm has been applied to MODIS brightness temperatures in bands 31 and 32 which are similar to those of the IR camera. The temperatures retrieved by the algorithm are in a very good agreement with the cloud top temperatures given by MODIS.

The aerosol radiative effect in the longwave spectral range is often neglected in atmospheric aerosol forcing studies, hence very few researches are conducted in this field at local scale, and even less at regional scale. However, strong absorbing aerosols, like mineral dust, can have a small, but non-negligible heating effect in the longwave spectral range which can slightly counteract the aerosol cooling effect in the shortwave. The objective of this research is to perform a sensitivity study of an aerosol radiative transfer model as a function of dust particle properties. GAME model¹, which can compute vertically resolved shortwave and longwave values of aerosol radiative forcing, is used. Before developing the sensitivity analysis, the aerosol radiative transfer model is validated by comparing its outputs with results published previously. Radiative forcing simulations in the longwave have shown an important sensitivity to the following parameters: aerosol size and refractive index, aerosol vertical distribution, humidity, surface temperature and albedo. A couple of strong mineral dust intrusion observed by means of lidar and sun-photometer are also presented in terms of shortwave and longwave radiative forcing.

Ground-based remote sensing and in situ observations of aerosol microphysical and optical properties have been collected during summertime (June-August, 2012) as part of the Two-Column Aerosol Project (TCAP; http://campaign.arm.gov/tcap/), which was supported by the U.S. Department of Energy’s (DOE’s) Atmospheric Radiation Measurement (ARM) Program (http://www.arm.gov/). The overall goal of the TCAP field campaign is to study the evolution of optical and microphysical properties of atmospheric aerosol transported from North America to the Atlantic and their impact on the radiation energy budget. During TCAP, the ground-based ARM Mobile Facility (AMF) was deployed on Cape Cod, an arm-shaped peninsula situated on the easternmost portion of Massachusetts (along the east coast of the United States) and that is generally downwind of large metropolitan areas. The AMF site was equipped with numerous instruments for sampling aerosol, cloud and radiative properties, including a Multi-Filter Rotating Shadowband Radiometer (MFRSR), a Scanning Mobility Particle Sizer (SMPS), an Aerodynamic Particle Sizer (APS), and a three-wavelength nephelometer. In this study we present an analysis of diurnal and day-to-day variability of the column and near-surface aerosol properties obtained from remote sensing (MFRSR data) and ground-based in situ measurements (SMPS, APS, and nephelometer data). In particular, we show that the observed diurnal variability of the MFRSR aerosol optical depth is strong and comparable with that obtained previously from the AERONET climatology in Mexico City, which has a larger aerosol loading. Moreover, we illustrate how the variability of aerosol properties impacts the direct aerosol radiative forcing at different time scales.

The Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) data retrieved at 0:55 μm with spatial resolutions of 10 km and 1 km AOD have been considered in this work. The 10 km resolution of MODIS AOD product is from the MODIS Collection 5:1 dark target retrieval and the 1 km resolution retrieval is from the new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. We evaluate ability of these two products to characterize the spatial distribution of aerosols in urban areas through comparison with surface PM₁₀ measurements. The Po Valley area (northern Italy) is considered in this study since urban air pollution is an important concern. Population and industrial activities are located in a large number of urban areas distributed within the valley. The 10 km spatial resolution of MODIS AOD product is considered too large for air quality studies at the urban scale. Using MAIAC data at 1 km, we examine the relationship between PM₁₀ concentrations, AOD, and AOD normalized by Planetary Boundary Layer (PBL) depths obtained from NCEP global analysis, for year 2012 over the Po Valley. Results show that the MAIAC retrieval provides a high resolution depiction of the AOD within the Po Valley and performs nearly as well in a statistical sense as the standard MODIS retrieval during the time period considered. Results also show that normalization by the analyzed PBL depth to obtain an estimate of the mean boundary layer extinction is needed to capture the seasonal cycle of the observed PM₁₀ over the Po Valley.

The B3M-FTS instrument, inherited from ACE-FTS and PARIS, is built by Canadian ABB and Beijing Vision Sky Aerospace Co., Ltd. The B3M is a complete stand-alone spectrometer designed to operate from the ground in moderate environment. It can acquire atmospheric spectra with the Sun as back illumination. This instrument is an adapted version of the classical Michelson interferometer using an optimized optical layout, and it is a high-resolution infrared Fourier transform spectrometer operating in the 750 to 4100cm^-1 spectral range. In this paper, the instrument concept of a compact, portable, high-resolution Fourier transform spectrometer is introduced. Some test results of the instrument such as ILS and SNR are presented, and the spectral resolution of 0.028cm^-1 @ 750cm^-1 and SNR over 100:1 are achieved. Sample atmospheric absorption spectra and corresponding retrieval results measured by the FTS are given. The B3M-FTS, with its high performance, provides the capability to monitor the atmospheric composition changes by measuring the atmospheric absorption spectra of solar radiance. Lots of measurements have been acquired at the Olympics atmospheric observation super-station. Up to now, the VMRs of near 10 trace gases have been retrieved. The success of atmospheric composition profile retrieval using the FTS measurements makes the further application of FTS type payload possible in China.

It is of great interest to investigate the optical, microphysical, and geometrical properties of clouds that play crucial role in the earth climate system. Water clouds are generally optically thick and consequently have a great cooling effect on earth-atmosphere radiation budget. The water clouds usually exist in a lower troposphere where aerosol-cloud interaction occurs frequently, and then cloud droplet size variation in uences re ection of solar radiation as well. Further, a cloud layer height is one of the key properties that determine downward longwave radiation and then surface radiation budget. In this study, top height, geometrical thickness and bottom height of a water cloud layer are investigated as cloud geometrical properties in particular. Several studies show that observation data of some spectral regions including oxygen A-band, enables us to retrieve the cloud geometrical properties as well as the optical thickness and the effective particle radius. In this study, an algorithm was developed to retrieve simultaneously the cloud optical thickness, effective particle radius, top height, geometrical thickness and then bottom height of a cloud layer with the spectral observation of visible, near infrared, thermal infrared, and oxygen A-band channels. This algorithm was applied to Advanced Earth Observing Satellite － II / Global Imager (ADEOS-II / GLI) dataset so as to retrieve global distribution of cloud geometrical properties. The retrieved results around Japan were compared with other observation such as ground-based active sensors, which suggest this algorithm works for cloud system over ocean at least although the cloud bottom height was underestimated. The underestimation is attributed to cloud inhomogeneity at this stage and should be investigated in detail.

Sensitivity to mechanical vibrations of Fourier Transform Spectrometers (FTS) is a well-known phenomenon. It is especially critical for FTS devoted to atmospheric studies (like the Planetary Fourier Spectrometer (PFS) onboard Mars Express 2003), as absorption bands for the gases of low concentration are comparable with the generated instrument spectral noise. The adopted techniques for the vibration sensitivity reduction suffer of limitations in practical implementation, leaving residual modulations of the interferogram and the so-called ghosts in the spectra. Moreover as it is often impossible to measure the vibrations during the FTS measurement, the position and magnitude of these ghosts cannot be evaluated. Up to now the adopted ghost reduction techniques are mostly based on the averaging of spectra, because the disturbance phase is randomly distributed. This paper presents an innovative data treatment technique which allows single spectrum correction from distortions of unknown nature. Such a technique would increase the spatial resolution of the mapping process and becomes crucial when the desired information is linked to a particular mapping area associated to an individual spectrum. The full study consists in the explicit analysis of the ghost formation and the post-processing algorithm based on the semiblind deconvolution method – an iterative numerical algorithm of the series of consecutive deconvolutions. The technique was tested on the data from the PFS and the algorithm proved to be consistent according to the selected efficiency criteria (coming from the available general information about the signal spectral shape).

This paper is devoted to the miniaturized Fourier Transform Spectrometer “MicroMIMA” (Micro Mars Infrared MApper) design. The instrument has been designed for the spectral characterization and monitoring of the Martian atmosphere, bound to investigate its composition, minor species abundances and evolution during time. The spectral resolution of MicroMIMA is of 2 cm^-1 (with the option to be extended up to 1 cm^-1) that allows to recognize the spectral features of the main elements of interest in the atmosphere and in particular to assess methane abundance with ppb resolution. The instrument configuration has been optimized in order to achieve the highest sensitivity in the 2 to 5 μm spectral range, along with the reduction of noise, i.e. the Signal-to-Noise Ratio (SNR) has been used as figure of merit. The optimization has been carried-out under the constraints of instrument mass, volume, power consumption and spectral resolution. For the proposed optical layout evaluation of the theoretical SNR for different measurements was performed accounting both for laboratory observations on Earth and acquisition of Martian atmosphere spectrum during the mission. Moreover, the instrument trace gas detection capability was evaluated.

In this work, we focus on estimations of fine particulate matter using MODIS AOD as part of a neural network scheme and compare this to both simple linear regressions and GEOS-CHEM products. In making this comparison, it is well known the seasonal and geographical dependences observed in the PM2.5-AOD relationship; thus, to enhance our predictions, we apply WRF PBL information to our neural network method and assess its performance. As part of our analysis, we first explore the baseline effectiveness of AOD and PBL as strong factors in estimating PM2.5 in a local experiment using data collected at one site in New York City. Then, we expand our analysis to a regional domain where daily estimations are obtained based on site location and season. In our local test, we find the high efficiency of the neural network estimations when AOD, PBL and seasonality are primarily assessed (R~0.94 in summer). Later, we test our regional network and compare it with the GEOS-CHEM PM2.5 product. From this, we see better estimations from our experiment using urban/non-urban stations and applying different spatial schemes for training the neural network (R_NN~0.80, R_GEOS-CHEM~0.57 in an urban station with a distance radius of 0.1 degree; R_NN~0.74, R_GEOSCHEM~0.69 in a non-urban station with a distance radius of 0.3 degree). Finally, we create regional daily PM2.5 maps and compare them to GEOS-CHEM outputs, evaluating the corresponding estimations using ground readings.

The space borne measurements provide global view of atmospheric aerosol distribution. The Ozone Monitoring Instrument (OMI) on board NASAs Earth Observing System (EOS) Aura satellite is a Dutch-Finnish nadir-viewing solar backscatter spectrometer measuring in the ultraviolet and visible wavelengths. OMI measures several trace gases and aerosols that are important in many air quality and climate studies. The OMI aerosol measurements are used, for example, for detecting volcanic ash plumes, wild fires and transportation of desert dust. We present a methodology for improving the uncertainty quantification in the aerosols retrieval algorithm. We have used the OMI measurements in this feasibility study. Our focus is on the uncertainties originating from the pre-calculated aerosol models. These models are never complete descriptions of the reality. This aerosol model uncertainty is estimated using Gaussian processes with computational tools from spatial statistics. Our approach is based on smooth systematic differences between the observed and modelled reflectances. When acknowledging this model inadequacy in the estimation of aerosol optical thickness (AOT), the uncertainty estimates are more realistic. We present here a real world example of applying the methodology.

Air pollution in megacities has become a serious problem. Fine particles called PM_2.5, with a diameter of 2.5 micrometres or less, are particularly problematic. Our observation site, located in eastern Osaka, is home to many smalland medium-scale manufacturing enterprises. A clear atmosphere is rare in this area, and the air is usually polluted with suspended particles emitted from diesel vehicles and industries. Furthermore, pollutants carried by winds from China add to the levels of pollution in the atmosphere. In this work, we investigate the size and composition of particulate matter with a scanning electron microscope (SEM) coupled with an energy-dispersive X-ray analyser (EDX). We use sampling data from an PM sampler mounted on the roof of a building at Kinki University at a height of about 50 m above sea level. It is evident that aerosol properties such as the amount, size, shape, and composition, change when anthropogenic or dust aerosol is transported. The level of sulphate and the percentage of fine particle increase in severe air pollution. In contrast, it is clear that silicon, which is possibly derived from soil particles, becomes dominant and that the number of large particles increase during the dust event.

The electromagnetic signal transmitted by the global navigation and positioning systems (GNSS) suffers a delay which is mainly caused by the water vapor in the atmosphere. Estimating the delay affecting the signal propagation, it is possible to estimate the water vapor column on the troposphere above each station. The aim of this study is to characterize the water vapor field on the troposphere over time by GNSS techniques. It is expected that can also come to assist in the Nowcasting particularly in the prediction of severe meteorological phenomena. Several events of strong, intense and short precipitation, observed in the Lisbon region throughout 2012 were analyzed. The choice of these events was based on the analysis of hourly precipitation given by a meteorological station located on Lisbon center. This region is monitored by a network of 15 GNSS stations covering about 100 square kilometers. The relationship between the GPS precipitable water vapor (PWV) and the hourly accumulated precipitation was evaluated over time (1D closest GPSmeteorological station plots) and spatially (2D maps) interpolated over the GNSS and meteorological stations. It was verified that there were a high and sudden increment of the GPS PWV prior to severe precipitation events. The PWV increment starts 6 to 10 hours before the rain and the value has increased between 57% and 75% relatively to the PWV value observed previously. In this study is shown that GPS data has good potential for forecasting severe rain events and high moisture flux situations.

Estimation of forest fire danger has traditionally been based on historical fire weather climatology. This presentation describes a new concept for an improved estimation of forest fire danger, which takes into account the possibility of forest fuel ignition as a result of focused sun’s light. For example, glass containers, their splinters and large drops of coniferous trees pitch can be a fire hazard due to their potential for focusing the sun’s rays (under favorable conditions) and, consequently for setting forest fuel ablaze. Our analysis of numerous observational reports suggests that the forest fuel ignition process can be described by system of the non-stationary nonlinear equations of heat conductivity and diffusion with corresponding initial and boundary conditions. To solve these equations, we apply well-established numerical methods. This presentation includes model results and their comparison with available observational constrains together with suggestions for using remote sensing data.

Optical remote sensing observations often are the primary data source for many studies and applications in large scale, even in tropical regions. Frequent clouds over moist tropical regions often cause difficulty in obtaining good-quality high-resolution images. Different cloud styles and shadows make it hard to be masked on the images. The ZY-1 02C satellite, where multi-spectral and panchromatic imagers were on-boarded, was launched on 22 Nov. 2011. The objective of this satellite is to acquire data contributing for earth resources and environmental monitoring, as well as for other applications such as land use and disaster reduction. The multi-spectral imager has three wavebands, centered at 0.55 micrometer (green), 0.66 micrometer (red) and 0.83 micrometer (near infrared), at a spatial resolution of 10 meters. Panchromatic band, centered at 0.68 micrometer, has a spatial resolution of 5 m and is not used in this study. A twostage algorithm is presented to detect cloud and cloud shadow for ZY-1 02C multi-spectral measurements in this study. First, maximum and minimum filters with a moving window size of 5 by 5 pixels are operated on ZY-1 02C multispectral measurements. Optimal thresholds are selected by spatial statistics and visual examination. Pixels in maximumfiltered images with a grey level higher than the given thresholds (Tc) are labeled as potential cloud. In contrast, pixels in minimum-filtered images with a grey value lower than the given thresholds (Ts) are considered as potential shadow. Second, the contextual are used to mask out errors with potential cloud and shadow (e.g. vegetation canopy-cast shadow, road and bare soil) in previous stage. A window size of 9 by 9 centered at each potential cloud position is searched. If no potential shadow is found the potential cloud is rejected. Meanwhile, each potential shadow also is tested to get the final cloud and cloud shadow mask. Two ZY-1 02C multi-spectral images acquired over Pearl River Delta, a subtropical region in South China, are used to validate the two-stage algorithm. The research result indicates that, two-stage algorithm developed in this study has successfully detected the cloud and shadow on ZY-1 02C multi-spectral images.

We have performed a series of experiments aiming at understanding the statistics of deep turbulence over cities. The experimental setup consisted of a Shack-Hartmann wavefront sensor and an imaging camera that simultaneously recorded wavefront-, and focal-plane data, respectively. At the same time, measurements of deep optical turbulence were performed at the urban area of interest using two large-aperture scintillometer systems to get an impression of the strength of C_n² above the rooftops of Ettlingen. Our focus is “urban” turbulence because we are interested in the usefulness of adaptive optics for free-space optical communications over urban areas. We discuss methods of determining departure from Kolmogorov turbulence. Our “last mile problem” is that urban turbulence can be significantly stronger, in the sense of flatter power spectrum, compared to the classic Kolmogorov turbulence. This could pose a significant challenge for adaptive optics systems.

The optical effect of atmospheric turbulence greatly inhibits the achievable range of Detection, Recognition and Identification (DRI) of targets when using imaging sensors within the surface layer. Since turbulence tends to be worst near the ground and decays with height, the question often arises as to how much DRI range could be gained by elevating the sensor. Because this potential DRI gain depends on the rate of decay of turbulence strength with height in any particular environment, there is a need to measure the strength profile of turbulence with respect to height in various environments under different atmospheric and meteorological conditions. Various techniques exist to measure turbulence strength, including scintillometry, sonic anemometry, Sound Detection and Ranging (SODAR) and the analysis of point source imagery. These techniques vary in absolute sensitivity, sensitivity to range profile, temporal and spatial response, making comparison and interpretation challenging. We describe a field experiment using multiple scintillometers, sonic anemometers and point source videography to collect statistics on atmospheric turbulence strength at different heights above ground. The environment is a relatively flat, temperate to sub-tropical grassland area on the interior plateau of Southern Africa near Pretoria. The site in question, Rietvlei Nature Reserve, offers good spatial homogeneity over a substantial area and low average wind speed. Rietvlei was therefore chosen to simplify comparison of techniques as well as to obtain representative turbulence profile data for temperate grassland. A key element of the experimental layout is to place a sonic anemometer 15 m above ground at the centre of a 1 km slant-path extending from ground level to a height of 30 m. An optical scintillometer is operated along the slant-path. The experiment layout and practical implementation are described in detail and initial results are presented.

Optical turbulence represented by the structure function parameter of the refractive index C_n² is regarded as one of the chief causes of image degradation of ground-based astronomical telescopes operating in visible or infrared wavebands. Especially, it affects the attainable spatial resolution. Therefore since the middle of September 2012 the optical turbulence has been monitored between two German solar telescopes at the Observatory in Tenerife /Canary Islands /Spain. It comprises the solar telescope GREGOR and the vacuum tower telescope VTT mounted on two 30 m high towers. Between the two towers at the level of the telescopes, C_n² was measured using a Laser-Scintillometer SLS40 (Scintec, Rottenburg, Germany). The horizontal distance of the measurement path was 75 m. The first results of the measurements starting from the 15th September 2012 up to the end of December 2012 are presented and analyzed using simultaneous measured meteorological data of wind, temperature and humidity. Daily and seasonal variations are shown and discussed.

Atmospheric turbulence is usually simulated at the laboratory by generating convective free flows with hot surfaces, or heaters. It is tacitly assumed that propagation experiments in this environment are comparable to those usually found outdoors. Nevertheless, it is unclear under which conditions the analogy between convective and isotropic turbulence is valid; that is, obeying Kolmogorov isotropic models. For instance, near-ground-level turbulence often is driven by shear ratchets deviating from established inertial models. In this case, a value for the structure constant can be obtained but it would be unable to distinguish between both classes of turbulence. We have performed a conceptually simple experiment of laser beam propagation through two types of artificial turbulence: isotropic turbulence generated by a turbulator [Proc. SPIE 8535, 853508 (2012)], and convective turbulence by controlling the temperature of electric heaters. In both cases, a thin laser beam propagates across the turbulent path, and its wandering is registered by a position sensor detector. The strength of the optical turbulence, in terms of the structure constant, is obtained from the wandering variance. It is expressed as a function of the temperature difference between cold and hot sources in each setup. We compare the time series behaviour for each turbulence with increasing turbulence strength by estimating the Hurst exponent, H, through detrended fluctuation analysis (DFA). Refractive index fluctuations are inherently fractal; this characteristic is reflected in their spectra power-law dependence—in the inertial range. This fractal behaviour is inherited by time series of optical quantities, such as the wandering, by the occurrence of long-range correlations. By analyzing the wandering time series with this technique, we are able to correlate the turbulence strength to the value of the Hurt exponent. Ultimately, we characterize both types of turbulence.

In this paper, we present the process of validating the atmospheric modelling software MATISSE (Advanced Modelling of the Earth for the Imaging and the Simulation of the Scenes and their Environment, developed by ONERA) by comparing simulation results of terrestrial and atmospheric background to MODIS satellite images. Analyses have been carried out for wavebands in the visible (VIS) as well as the longwave infrared (LWIR) spectrum.

Density oscillations in the vicinity of vortex rings in air have been investigated. The calculations were fulfilled on the basis of the Navier-Stokes equations. We used series expansions of unknown functions in powers of a parameter which characterizes vorticity. As a result, we got a non-uniform system of parabolic differential equations with constant coefficients. The frequency of oscillations depends only on the dimensions and the shape of the ring in the case of small vorticity (weak turbulence). We analyzed oscillations generated by rings with circular cross-section. The size of the rings varied in a wide range. It includes inertial range and dissipation range. It is interesting to note that first of all the amplitude of oscillations increases, reaches its maximum and then decreases up to zero. These data can be used for modeling the propagation of a Gaussian beam through the turbulent atmosphere. We analyzed intensity fluctuations (scintillations) of the beam after the passage through the non-uniform region which contains vortex rings. We considered an ill-posed problem (that of super-resolution) connected with image restoration. In such cases if the input data are slightly changed, the solution may vary considerably. The proposed procedure is as follows. We change the instrument function in such a manner that it will be reversible one within the limits of accuracy. The procedure enables to solve some problems referring to the turbulent atmosphere. Ke

High Energy Laser weapons (HEL) have unique attributes which distinguish them from limitations of kinetic energy weapons. HEL weapons engagement process typical starts with identifying the target and selecting the aim point on the target through a high magnification telescope. One scenario for such a HEL system is the countermeasure against rockets, artillery or mortar (RAM) objects to protect ships, camps or other infrastructure from terrorist attacks. For target identification and especially to resolve the aim point it is significant to ensure high resolution imaging of RAM objects. During the whole ballistic flight phase the knowledge about the expectable imaging quality is important to estimate and evaluate the countermeasure system performance. Hereby image quality is mainly influenced by unavoidable atmospheric turbulence. Analytical calculations have been taken to analyze and evaluate image quality parameters during an approaching RAM object. In general, Kolmogorov turbulence theory was implemented to determine atmospheric coherence length and isoplanatic angle. The image acquisition is distinguishing between long and short exposure times to characterize tip/tilt image shift and the impact of high order turbulence fluctuations. Two different observer positions are considered to show the influence of the selected sensor site. Furthermore two different turbulence strengths are investigated to point out the effect of climate or weather condition. It is well known that atmospheric turbulence degenerates image sharpness and creates blurred images. Investigations are done to estimate the effectiveness of simple tip/tilt systems or low order adaptive optics for laser based C-RAM systems.

We propose the use of an aperture diverse imaging system for high-resolution imaging through strong atmospheric turbulence. The system has two channels. One channel partitions the aperture into a set of annular apertures that provide a set of images of the target at different spatial resolutions. The other channel feeds an imaging Shack-Hartmann wavefront sensor with a small number of sub-apertures. The combined imagery from this setup is processed using a blind restoration algorithm that captures the inherent temporal correlations in the observed atmospheric wave fronts. This approach shows significant promise for providing high-fidelity imagery for observations acquired through strong atmospheric turbulence. The approach also allows for the separation of the phase perturbations from different layers of the atmosphere. This characteristic offers potential for the accurate restoration of images with fields of view substantially larger than the isoplanatic angle.

Observing the Sun with high angular resolution is difficult because the turbulence in the atmosphere is strongest during day time. In this paper we describe the principles of solar adaptive optics exemplified by the two German solar telescopes VTT and GREGOR at the Observatorio del Teide. With theses systems we obtain near diffraction limited images of the Sun. Ways to overcome the limits of conventional AO by applying multiconjugate adaptive optics (MCAO) are shown.

We are studying the effectiveness of HWFS for measuring the first few low-order aberrations. In literature a value of 10%Strehl ratio has been assumed as a threshold of usefulness of adaptive-optics correction for laser communications. We want to check whether such a value can be achieved through the use of HWFS for compensation of laser beams over long horizontal paths. We realized HWFS by recording an analog multiplex hologram. We analyzed the sensor’s response to incoming laser beams with defined wavefront aberrations. The test wavefronts were aberrated with the deformable mirror DM-52-15 by ALPAO. We studied the influence of tip/tilt on the senor’s accuracy. The effect of a tilted laser beam on HWFS is an unsymmetrical misalignment of the reconstructed spots. In this case the use of small photodiodes for intensity measurement- a configuration recommended for tip/tilt-free beam – can lead to error-prone measurements.