This PDF file contains the front matter associated with SPIE Proceedings Volume 8177, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.

A method to estimate wind velocity using the backscatter lidar signals of transported aerosol particles is presented. The lidar signal is correlated along range and time dimensions for each line of sight in which the lidar is pointing. The method is based on the analysis of contours of these range-time auto-correlation functions. This analysis obtains ellipse curve parameters which are related to the radial velocity and to the square wind speed, locally retrieved for a given line of sight. The combination of data from several angular positions enables the wind direction retrieval. Two possible implementations of the method are considered and tested with an actual measurement with the lidar of the Universitat Politècnica de Catalunya (UPC).

The bidimensional auto-correlation for the lidar signal measured along a single line of sight (LOS) is spectrally analyzed to estimate the wind turbulence variance, while a correlation contour analysis retrieves the mean wind speed. A combined model of a turbulent wind field plus an isotropic gaussian aerosol concentration field is used to 1) estimate the wind field variance causing diffusion on the aerosol structures and 2) to extend the contour autocorrelation analysis to include the turbulence effect and correct the mean wind estimation. The present analysis is intended to be used on a single LOS sensing, that can provide an estimation of the relative turbulence.

Clouds and the Earth's Radiant Energy System (CERES) instruments are scanning radiometers on board the Terra and Aqua satellites since March of 2000 and June of 2002, respectively; hence, their continuous Earth's radiation budget dataset is more than a decade long. Since there are four CERES scanners in operation, it is important that their measurements are consistent. A focus of this paper is on placing two Aqua CERES sensors on the same radiometric scale as FM1 on Terra. The paper contains a description of radiation budget experiments that are used in this task, and a complete set of results. It is shown that one-time adjustments to gains and spectral response functions are sufficient in putting FM3 and FM4 on the same radiometric scale as FM1 at the beginning of their mission. The Edition 3 of ERBE-like data products use derived corrections for Aqua CERES sensors.

An impact of intensive background clutter on lidar photodetectors leads to changes of their sensitivity and can even overload them. As a result, information on atmospheric optical parameters is distorted and sometimes can be completely lost. Since a problem of lidar system structure and parameters adaptation to background radiation remains actual one, some advanced methods and means to improve atmospheric lidar stability against sky background clutter are discussed.

Integrated approach has been adopted at the ADvanced Environmental Research Center (ADEMRC), Gwangju Institute of Science and Technology (GIST), Korea for effective monitoring of atmospheric aerosol. Various active and passive optical remote sensing techniques such as multi-wavelength (3β+2α+1δ) Raman LIDAR, sun-photometry, MAX-DOAS, and satellite retrieval have been utilized. This integrated monitoring system approach combined with in-situ surface measurement is to allow better characterization of physical and optical properties of atmospheric aerosol. Information on the vertical distribution and microphysical properties of atmospheric aerosol is important for understanding its transport characteristics as well as radiative effect. The GIST multi-wavelength (3β + 2α+1δ) Raman lidar system can measure vertical profiles of optical properties of atmospheric aerosols such as extinction coefficients at 355 and 532nm, particle backscatter coefficients at 355, 532 and 1064 nm, and depolarization ratio at 532nm. The incomplete overlap between the telescope field-of-view and beam divergence of the transmitting laser significantly affects lidar measurement, resulting in higher uncertainty near the surface where atmospheric aerosols of interest are concentrated. Differential Optical Absorption Spectroscopy (DOAS) technique is applied as a complementary tool for the detection of atmospheric aerosols near the surface. The passive Multi-Axis DOAS (MAX-DOAS) technique uses scattered sunlight as a light source from several viewing directions. Recently developed aerosol retrieval algorithm based on O4 slant column densities (SCDs) measured at UV and visible wavelengths has been utilized to derive aerosol information (e.g., aerosol optical depth (AOD) and aerosol extinction coefficients (AECs)) in the lower troposphere. The aerosol extinction coefficient at 356 nm was retrieved for the 0-1 and 1-2 km layers based on the MAX-DOAS measurements using the retrieval algorithm. Ground-based measurements of tropospheric aerosol using multi-wavelength Raman lidar system and a mobile MAX-DOAS system had been carried out at the Gwangju Institute of Science and Technology (GIST). To evaluate the performance of the integrated measurement system (Lidar + MAX-DOAS), an aerosol retrieval method called STAR (satellite aerosol retrieval) has been applied to compare the satellite AOD products with those based on the Raman lidar and MAX-DOAS measurements. It allows complete monitoring of atmospheric aerosols' vertical profiles for better estimation of their radiative effects on atmospheric environment and climate change.

The mixing layer height (MLH) is an important factor which influences exchange processes of ground level 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. Ceilometers CL31 (backscatter profiles at 910 nm) were applied to detect the MLH in Augsburg since 2006. Radiosonde data cannot be used alternatively because they do not provide sufficient information. The Vaisala ceilometers LD40 and CL31 are operated which are eye-safe commercial lidar systems. Special software for these ceilometers provides routine retrievals of lower atmosphere layering from vertical profiles (vertical gradient) of laser backscatter density data. The performance of the ceilometers is sufficient to detect convective layer depths exceeding 2000 m and nocturnal stable layers down to 50 m. The radiosonde data from the station Oberschleissheim near Munich (about 50 km away from Augsburg city) are also used for MLH determination. A summer and a winter episode of MLH measurement results are investigated. The profile behaviour of relative humidity (strong decrease) and virtual potential temperature (inversion) of the radiosonde agree mostly well with the MLH indication from ceilometer laser backscatter density gradients. The remote sensing by ceilometers can fill the temporal gap of information between the two radiosonde profiles per day so that the daily course of the MLH is available.

Eye-safe lidar ceilometers are reliable tools for unattended boundary layer structure monitoring around the clock. A single lens optical design enables precise assessment of inversion layers and nocturnal stable layers below 200 m. This design has been chosen for the Vaisala Ceilometers CL31 and CL51. Based on the gradient method, an automatic algorithm for online retrieval of boundary layer depth and additional residual structures has been developed. This robust all weather algorithm is part of the Vaisala boundary layer reporting and analysis tool BL-VIEW. The data averaging intervals used depend on range and signal noise; detection thresholds vary with signal amplitude. All layer heights reported are accomponied by a quality index. In most cases the lowest of these layers is a good measure for the mixing layer height. The continuous knowledge of this atmospheric parameter is supporting the understanding of processes directing air quality. The utility of mixing layer height values for air quality forecast can be further increased by additionally utilizing unaveraged profiles for gradient minima detection. Based on their variation from the result of the BL-VIEW algorithm, confidence levels and error bars can be calculated. Results are presented from campaigns at three different sites. Validation with mixing layer height values derived from co-located radiosoundings confirm the applicability of this novel method.

The performance of the OMPS/LP retrieval algorithm is assessed by conducting a series of numerical experiments and evaluating the quality of the primary (ozone profile) and secondary products (aerosol profiles, NO2, cloud height, surface reflectance) as well as height registration under a set of realistic atmospheric conditions selected randomly. The study considers a number of orbits corresponding to Winter/Summer solstice and Spring/Autumn Equinox. It is shown that the quality of the OMPS/LP retrieval products (accuracy, precision, vertical resolution, height registration) varies along the orbit, as the single scattering angle transitions from backscatter to forward scatter and zenith angles vary from sunrise to sunset. Instrument effects (straylight, gain consolidation, instrument noise) are also investigated. It is shown that ozone profiles can be retrieved with an accuracy of 5% or better from the tropopause up to 50 km, a precision of about 3-5% from 18 to 50 km, and a vertical resolution of 1.5-2 km. Stratospheric aerosol extinction profile can be retrieved with an accuracy/precision of about 30%. The scene-based tangent height registration algorithm is shown to yield height information with an RMS error of 250-300m.

Scheduled for launch in October 2011, the NPOESS Preparatory Project (NPP) mission includes the Ozone Mapping and Profiler Suite (OMPS) which is composed of two Nadir looking sensors and an Earth-limb viewing sensor. This paper is concerned with the OMPS limb sensor, the primary product of which is an ozone vertical profile with a 1.5 km vertical resolution, a vertical range of cloud top to 60 km and an along-track spacing of 125 km. Secondary products include stratospheric aerosol vertical distribution, cloud top height and NO₂ vertical profiles. The paper describes the OMPS mission (sensor specifications, orbital characteristics, timeline), reviews the heritage in space-based ozone measurements, illustrates the limb sensor expected performance (accuracy and precision), describes the planned product validation effort (comparison with ground and space instruments) and defines the data release procedure (content, format and release schedule).

Darkest pixel atmospheric correction is the simplest and fully image-based correction method. This paper presents an overview of a proposed 'fast atmospheric correction algorithm' developed at MATLAB based on the RT equation basics and the darkest pixel approach. The task is to retrieve the aerosol optical thickness (AOT) from the application of this atmospheric correction. The effectiveness of this algorithm is performed by comparing the AOT values from the algorithm with those measured in-situ both from MICROTOPS II hand-held sunphotometer and the CIMEL sunphotometer (AERONET).

The ultraspectral infrared radiances obtained from satellite observations provide atmospheric, surface, and/or cloud information. The intent of the measurement of the thermodynamic state is the initialization of weather and climate models. Great effort has been given to retrieving and validating these atmospheric, surface, and/or cloud properties. Error Consistency Analysis Scheme (ECAS), through fast radiative transfer model (RTM) forward and inverse calculations, has been developed to estimate the error budget in terms of absolute and standard deviation of differences in both spectral radiance and retrieved geophysical parameter domains. The retrieval error is assessed through ECAS without assistance of other independent measurements such as radiosonde data. ECAS re-evaluates instrument random noise, and establishes the link between radiometric accuracy and retrieved geophysical parameter accuracy. ECAS can be applied to measurements of any ultraspectral instrument and any retrieval scheme with associated RTM. In this paper, ECAS is described and demonstration is made with the measurements of the METOP-A satellite Infrared Atmospheric Sounding Interferometer (IASI).

This work intends to develop an algorithm for aerosol retrieval based on the combined use of CAI (Cloud aerosol imager) on the satellite GOSAT and POLDER (Polarization and directionality of Earth's reflectances) on PARASOL. The CAI measures the total intensity at 0.380, 0.674 and 0.870 μm. The measurements at 0.380 μm have an advantage for detecting the absorbing aerosols, such as carbonaceous as well as dust aerosols. On the contrary, POLDER provides the multi directional polarization information at 0.670 and 0.865 μm. The polarization information is useful to retrieve aerosol characteristics over land because the polarization by the land surface is much smaller than the total one. Our algorithm is mainly based on the radiative transfer calculations in the Earth atmosphere model involving various kinds of atmospheric particles. This algorithm is applied for the Russian forest fire events happened in summer of 2010. As results, aerosol optical thickness (AOT), Angstrom exponent and single scattering albedo (SSA) are retrieved. The retrieved results are partially validated with ground based measurements of AERONET. It is found that AOT takes the values of ~2 all over the event region and larger than ~5 over the plume core. The particle size information retrieved as Angstrom exponent indicates the existence of small aerosols in the plume. The SSA takes the lower value of ~0.85, especially lower in the edge of plume than at the plume core. This fact might suggest the changing of particle property by water vapor uptake during transport.

Mueller matrices for ice crystals horizontally and preferably oriented in horizontal plane are calculated with a code ("facet-tracing") based on the geometric optics. For the case of preferably oriented ice crystals particles uniform and normal distributions of flutter with maximum dimension of 5° are analyzed. The main physical regularities inherent to the scattering matrices are discussed. Degree of polarization of the scattered light is shown to be a qualitative criterion of number of photon trajectories that contribute effectively to the scattered light. The inverse scattering problem of retrieving aspect ratios of the horizontally/preferably oriented hexagonal ice plates from polarization of the scattered light in the bistatic sounding scheme has been proposed and discussed.

Retrieval of atmospheric aerosol characteristics from satellite data, i.e. aerosol remote sensing, is based on the light scattering theory. The aerosol properties are estimated by comparing satellite measurements with the numerical values of radiation simulations in the Earth atmosphere model. This study was designed to develop an efficient algorithm to retrieve aerosol characteristics in aerosol events, which are associated with extreme concentrations of aerosols in the atmosphere such as a yellow-sand storm. It is known that the large increase in the optical thickness of the atmosphere during aerosol events prevents the use of sun/sky photometry from the surface level. However, space-based observations are possible for monitoring the atmospheric aerosols during such events. This study focuses on new algorithms being used to detect the event core with a high optical thickness and a simulation scheme for radiative transfer in the dense radiation field being employed. Finally, the practical application of our algorithms was tested using Aqua/MODIS data for a yellow-sand storm.

Ceilometers are applied to detect layering of the lower atmosphere continuously. This is necessary because not only wind speeds and directions but also atmospheric layering and especially the mixing layer height (MLH) influence exchange processes of ground level emissions. It will be discussed how the ceilometer monitoring information can be used to determine the MLH influence upon the particle size distribution (PSD) which is detected near the ground. The information about atmospheric layering is continuously monitored by uninterrupted remote sensing measurements with the Vaisala ceilometers LD40 and CL31 which are eye-safe commercial lidar systems. Special software for these ceilometers provides routine retrievals of lower atmosphere layering from vertical profiles of laser backscatter data. The meteorological data are collected by the air pollution monitoring station of the Bavarian State Agency of Environment (LfU) at the southern edge of Augsburg and at the airport at the northern edge of Augsburg by the German National Meteorological Service (DWD). PSD are measured at the aerosol measurement station in the centre of Augsburg by the Cooperative Health Research in the Region of Augsburg (KORA). The two intensive measurement periods during the winter 2006/2007 and 2007/2008 are studied. The weather situations are characterized, the meteorological influences upon air pollutant concentrations like wind speed and wind direction are studied and the correlations of ceilometer backscatter densities and MLH with PSD are determined.

Available CL31 ceilometer measurements (backscatter profiles at 910 nm) have been applied to detect the Eyjafjallajökull volcanic plume after the eruption on April 14^th, 2011. Ceilometer backscatter intensities in Augsburg showed a layer of strongly enhanced backscatter above the planetary boundary layer (PBL) only on April 17^th until 13:00. From 02:00 until 13:00, the volcanic plume subsided and was finally mixed into the PBL where its clear signature finally disappeared. From 17:00 until mid-night, a structured layer in the upper part of the PBL became visible and is interpreted as a remnant of the formerly confined plume layer above a stable lower atmosphere. The ceilometer observations further indicate that there was a defined upper boundary of the PBL and the lower atmosphere was well mixed on April 17^th from 13:00 until 17:00 up to about 1500 m a.g.l., i.e. the vertical extension of the PBL was relatively large. Entrainment of volcanic material into the PBL must be assumed in this phase, but a corresponding signal on the near-surface air composition at Augsburg was not detectable due to strong dilution and high background concentrations. On April 19^th, the situation became different: Due to convection, the distinct separation of the PBL and the free troposphere above disappeared. During the following night, a stable near-surface layer and a residual second layer were formed. Such meteorological conditions favoured the enrichment of air pollutants near surface level, as seen during the night from April 19^th to April 20^th.

One month of MFRSR data collected at two sites in the central California (USA) region during the CARES campaign are processed and the MFRSR-derived AODs at 500 nm wavelength are compared with available AODs provided by AERONET measurements. We find that the MFRSR and AERONET AODs are small (~0.05) and comparable. A reasonable quantitative agreement between column aerosol size distributions (up to 2 μm) from the MFRSR and AERONET retrievals is illustrated as well. Analysis of the retrieved (MFRSR and AERONET) and in situ measured aerosol size distributions suggests that the contribution of the coarse mode to aerosol optical properties is substantial for several days. The results of a radiative closure experiment performed for the two sites and one-month period show a favorable agreement between the calculated and measured broadband downwelling irradiances (bias does not exceed about 3 Wm^-2), and thus imply that the MFRSR-derived aerosol optical properties are reasonable.

We apply recent (2009-2010) level 2.0 MAN-based AODs for assessing those from two MODIS sensors aboard Terra and Aqua satellites with morning and afternoon equatorial crossing times, respectively. To compare correctly the MAN- and MODIS-based AODs (550 nm), considerable attention is given to match ship tracks and satellite overpasses both temporally (within ±1.5h) and spatially (within 10 km). Overall, analysis of collocated and coincident satellite and shipboard data reveals capabilities of two MODIS sensors to capture the strong spatial and temporal variations of AOD quite well, although a better agreement between the MAN- and MODIS-based AODs is observed for Aqua instrument. Our results further highlight the importance of unique MAN AODs for assessment of over-ocean satellite retrievals.

Long range transport leads mineral dusts to internally/externally mix with the ambient aerosols, such as soot particles, naturally. The physicochemical characteristics of dust particles thus are dramatically altered after mixing with soot aggregates. Therefore, the investigation on the optical properties of mineral dust along with their pathway causes a significant topic for understanding the impacts of Asian dust storm on regional air quality, environment and climate. Unfortunately, the previous researches regarding to the optical properties of dust/soot mixture for satellite remote sensing are scarce. Consequently, the objective of this study is to simulate the effects of mixing with soot aggregates on the optical properties of dust particles for satellite observations based on the well developed models. A tri-axial ellipsoidal model for dust particles by introducing the third morphological freedom to improve the symmetry of spheroids has been developed and showed in good agreement for the retrievals of dust optical properties from remote sensing measurements and ground based observations. For the model of soot aggregation, the scattering properties of fractal aggregates can be obtained with the Rayleigh-Debye-Gans (RDG), superposition T-matrix and Generalized Multiple Mie (GMM) methods. The results show that the AOD (aerosol optical depth) retrievals of dust particle will be underestimated while the SSA (single scattering albedo) will be overestimated when neglecting the combination of soot aggregates. The simulations also suggest that simultaneously retrieve AOD and SSA based on the apparent reflectance may induce large uncertainty for the dust/soot mixtures.

The aerosol-cloud interaction is a complex and critical process in assessing the climate radiative effects of aerosol and cloud. Lidar can simultaneously measure the range-resolved distribution of aerosol-cloud with the high spatial-temporal resolution, and hence provides the opportunity to explore the cloud-aerosol optical properties and their interaction. Their interactions have been indicated by the significant variation of optical properties and droplet size of aerosol and cloud at the cloud vicinity or edges. But due to dramatic non-linear or irregular variation of lidar returns by the cloud, the evaluation of lidar algorithm deriving cloud extinction coefficient becomes quite important especially at the edges because the common algorithms may result in the artificial influence on the retrievals of cloud extinction and extinctionto- backscatter ratio (e.g. lidar ratio or S-ratio). In particular, the relationships of water cloud optical properties with the droplet size are simulated which include lidar ratio, color ratio and extinction ratio are used and general trends with measurements are demonstrated. To obtain color ratios (355/1064), a good calibration procedure for the 1064nm channel is required and we show that calibration errors using low water drop clouds allow absolute calibration < 10%. Preliminary results seem to indicate that small pre-nucleated droplets form at the aerosol - cloud boundary which is consistent with aerosol uptake into clouds. In addition, we also explore the increase in aerosol lidar-ratio below cloud indicative of hygroscopic growth.

The quantification of the first direct aerosol cloud interaction mechanism requires simultaneous observations of cloud water drop properties as well as aerosol properties below the cloud. The simultaneous measurement of both these properties is very difficult from space borne systems and efforts to develop ground remote sensing measurements are critical. To measure the cloud properties, we make use of an approach which combines a Microwave radiometer and a MFRSR radiometer for simultaneous Cloud Optical Depth (COD) and Liquid Water Path (LWP). From these measurements, effective droplet diameter can be estimated assuming the homogeneity of the cloud. In using the diffuse flux, we confirm that for COD > 2 and solar zenith angles < 60, the standard MFRSR correction can be applied with errors < 1%. In addition, we develop a method whereby regional retrieval of Microphysical properties from multispectral extinction measurements can be made based on NN based methods trained on full sky scans. Also, we discuss the uncertainty in the inferred COD due to various input parameters in the formation of Look-Up-Tables and present preliminary data sets for evaluation. Finally, we discuss methods to extract useful aerosol information during partly cloudy conditions that can be used to better define the state of the aerosol prior to cloud interaction.

Atmospheric mineral dust particles have significant effects on climate and the environment, and despite notable advances in modeling and satellite and ground-based measurements, remain one of the major factors contributing to large uncertainty in aerosol radiative forcing. We examine the Multi-angle Imaging SpectroRadiometer (MISR) 11+ year aerosol data record to demonstrate MISR's unique strengths and assess potential biases of MISR products for dust study applications. In particular, we examine MISR's unique capabilities to 1) distinguish dust aerosol from spherical aerosol types, 2) provide aerosol optical depths over bright desert source regions, and 3) provide high-resolution retrievals of dust plume heights and associated winds. We show examples of regional and global MISR data products in dusty regions together with quantitative evaluations of product accuracies through comparisons with independent data sources, and demonstrate applications of MISR data to dust regional and climatological studies, such as dust property evolution during transport, dust source climatology in relation to climatic factors, and dust source dynamics. The potential use of MISR radiance data to study dust properties is also discussed.

Recent studies have shown that polarimetric radars are capable of providing distributions of rain intensity with high accuracy. Variables obtained by the polarimetric radars include radar reflectivity factor (Zhh), differential propagation phase (Φdp) and differential reflectivity (Zdr). A number of methods to estimate rain intensity from these variables have been proposed. In this study, the rain intensity estimated from the differential reflectivity and radar reflectivity factor measured with a C-band polarimetric radar is used to analyze a local heavy rainfall event as a case study because the differential reflectivity measured with C-band radar is more sensitive to large raindrops associated with heavy rainfalls than is radars operating at other frequencies. Results show that the estimated rainfall intensity agrees well with surface observations made during the event. Moreover, the so-called high Zdr column, a large differential reflectivity region was clearly analyzed aloft about 10 minutes prior to the local heavy rainfall on the ground, suggesting that the differential reflectivity observed with C-band polarimetric radar can be a good index to detect heavy precipitation events in advance.

Information extraction from remotely sensed images acquired in the visible and near-infrared (VNIR) frequency range strongly depends on an accurate cloud pixel screening. Indeed, many remote sensing applications require a preliminary cloud detection phase to obtain profitable results. In this paper we propose to integrate the potential of the MAP-MRF methodology with the multispectral approach for augmenting the capability of the algorithm to detect cloudy pixels. In particular the proposed technique combines information from some SEVIRI sensor channels (in particular the channels 0.64ìm, 1.6ìm, 3.9ìm, 7.3ìm and 10.8ìm) with the classification obtained by the MAP-MRF method in the 0.8ìm channel in order to discriminate between snowy and cloudy pixels. The validation is performed on challenging images of Alps mountains acquired by the SEVIRI sensor during winter months. Results show significant improvements with respect to existing methods. In particular we highlight a more precise classification at the cloud borders and a considerable reduction of unsolicited holes inside the cloud masses.u

Formosat-2 satellite equips with the high-spatial-resolution (2m ground sampling distance) remote sensing instrument. It has been being operated on the daily-revisiting mission orbit by National Space organization (NSPO) of Taiwan since May 21 2004. NSPO has also serving as one of the ground receiving stations for daily processing the received Formosat- 2 images. The current cloud coverage assessment of Formosat-2 image for NSPO Image Processing System generally consists of two major steps. Firstly, an un-supervised K-means method is used for automatically estimating the cloud statistic of Formosat-2 image. Secondly, manual estimation of cloud coverage from Formosat-2 image is processed by manual examination. Apparently, a more accurate Automatic Cloud Coverage Assessment (ACCA) method certainly increases the efficiency of processing step 2 with a good prediction of cloud statistic. In this paper, mainly based on the research results from Chang et al, Irish, and Gotoh, we propose a modified Formosat-2 ACCA method which considered pre-processing and post-processing analysis. For pre-processing analysis, cloud statistic is determined by using un-supervised K-means classification, Sobel's method, Otsu's method, non-cloudy pixels reexamination, and cross-band filter method. Box-Counting fractal method is considered as a post-processing tool to double check the results of pre-processing analysis for increasing the efficiency of manual examination.

We perform a case study for estimating the impact of the vertical distribution of cloud fraction on the normalized cloud radiative forcing (CRF) using a decade-long (2000-2009) high resolution dataset of cloud macrophysical and radiative properties. This dataset is developed for fair-weather cumuli (FWC) observed at the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. The design of the case study reduces effects associated with non-cloud factors, such as the diurnal changes of aerosol loading and solar zenith angle. The results of the case study suggest that the impact of the vertical cloud structure can be substantial. Therefore, taking into account the vertical distribution of clouds would be beneficial for more comprehensive parameterizations aimed to portray the complex interactions between clouds and radiation more accurately.

We processed a eight-year time series (2001-2008) of zenith wet delay and associated precipitable water (PW) contents from the permanent GPS station THTI (OGT) and a corresponding precipitation time series from the pluviometer of the Matatia valley (7 km South East from the GPS receiver). Daily GPS data were obtained (including zenith total delay and North and East gradients) by applying the PPP strategy of the GIPSY-OASIS II package w.r.t. IGS final products. We used the Saastamoinen model to extract the hydrostatic part of the delay. Taking into account surface meteorological measurements, we transformed the resulting wet delay into an estimate of PW above the receiver. The precipitation dataset consisted of rainfall gauge measurements spanning the same period provided by the "Direction de l'Equipement" (GEGDP). This work poses a preliminary diagnostic on the evolution of PW and precipitations over French Polynesia with emphasis on a broad range of timescales, from seasonal to diurnal components. Before this study, no monitoring system had provided accurate and quasi continuous measures of PW in French Polynesia.

The dust storm happens in the Middle East with very high frequency. According to the dust storm effects, it is vital to study on the dust storms in the Middle East. The first step toward the study on dust storm is the enhancement of dust storms and determination of the point sources. In this paper, a new false color composite (FCC) map for the dust storm enhancement and point sources determination in the Middle East has been developed. The 28 Terra-MODIS images in 2008 and 2009 were utilized in this study. We tried to replace the Red, Green and Blue bands in RGB maps with the bands or maps that enhance the dust storms. Hence, famous indices for dust storm detection (NDDI, D and BTD) were generated using the different bands of MODIS images. These indices with some bands of MODIS were utilized for FCC map generation with different combinations. Among the different combinations, four better FCC maps were selected and these four FCC are compared using visual interpretation. The results of visual interpretations showed that the best FCC map for enhancement of dust storm in the middle east is an especial combination of the three indices (Red: D, Green: BTD and Blue: NDDI). Therefore, we utilized of this new FCC method for the enhancement of dust storms and determination of point sources in Middle East.

Knowledge of tropical cyclone intensity is good for pre-analysis on its development and its possible damage. It is the lack of observations in situ and the drawback of numerical model that make the remotely sensing from space be a useful method for tropical cyclone study. In this paper, a preliminary study on estimating tropical cyclone intensity by using MODIS (Moderate Resolution Imaging Spectroradiometer) data is present. The typhoon 0922 Nida is as a case for this study and the maximum wind speed in the cyclone is used to an index of cyclone intensity. By detecting the typhoon body from MODIS observation, the eyewall and edge of Nida is identified. The cloud-top height and cloud-top temperature in tropical cyclone region, which are two key parameters for estimating tropical cyclone intensity, is also obtained from MODIS observations. The retrieved cloud-top height is compared and validated with the CloudSat radar observations, which just cross the neighborhood of the 0922 storm center. According to a physically based framework, the maximum wind speed is estimated approximately from the background sea surface temperature, cloud-top temperature and cloud-top height. A simple result indicates that the technique for estimating cyclone intensity from MODIS observation is feasible. On the other hand, the future applications and some potential uncertainties on means are needed to be on second thoughts and discussed.

A radar is a powerful tool for measurement of the 3-D structure of precipitation. Recently, polarimetric radar is widely used because it can measure the size of raindrops to some degree and therefore can measures more accurate rainfall rate than the conventional weather radar. A space-borne radar is also widely used in precipitation studies. The Tropical Rainfall Measuring Mission (TRMM) satellite has been continuously monitoring precipitation on a global scale since the launch in November, 1977. Following the TRMM, the Global Precipitation Mission (GPM) is scheduled to launch in 2013. The polarimetric parameters observed with the polarimetric radar depend on various precipitation properties in a complex way. Multiple scattering contributions cannot be neglected for a radar operated at higher frequency of 35 GHz higher onboard the GPM. To develop a robust algorithm for more accurate measurements of precipitation from those radars, we should evaluate how micro-physical properties of precipitation link to the received signals. We have developed a generalized radar simulator for polarimetric and space-borne radar (GPASS). This is a physically-based simulator in which the scattering properties of cloud and raindrops are calculated by using radio wave scattering theory. Thus we can make detailed study how the radar signals vary with micro-physical properties of precipitation by using the simulator. We will present the simulator in detail and the limit of the Rayleigh approximation for polarimetric radar.

Bayesian algorithms are a common method of retrieving cloud properties from a set of observed passive microwave brightness temperature (TB) measurements. In practice, such methods often use predefined databases from cloud resolving models to perform the retrieval. Successful performance in these types of Bayesian retrievals is greatly affected by the similarity of TBs between observed and predefined databases. Here Empirical Orthogonal Function (EOF) analysis methods were used to illustrate the importance of predefined simulation databases on the ability to retrieve known regional variability in cloud structures across different parts of the tropical oceans and to provide insight on the relative impact of environmental conditions to limitations in cloud model microphysical parameterizations in retrieving different types of cloud structures. The spatial distributions of EOF coefficients in EOF space showed that there were both underrepresentation and overrepresentation between manifolds of the predefined and observed databases.

The particulate matter is a typical indicator of small particles in the atmosphere. In addition to providing impacts on climate and environment, these small particles can bring adverse effects on human health. Then an accurate estimation of particulate matter is an urgent subject. We set up SPM sampler attached to our AERONET (Aerosol Robotics Network) station in urban city of Higashi-Osaka in Japan. The SPM sampler provides particle information about the concentrations of various SPMs (e.g., PM10 and PM2.5) separately. The AEROENT program is world wide ground based sunphotometric observation networks by NASA and provides the spectral information about aerosol optical thickness (AOT) and Angstrom exponent (α). Simultaneous measurements show that a linear correlation definitely exists between AOT and PM2.5. These results indicate that particulate matter can be estimated from AOT. However AOT represents integrated values of column aerosol amount retrieved from optical property, while particulate matter concentration presents in-situ aerosol loading on the surface. Then simple way using linear correlation brings the discrepancy between observed and estimated particulate matter. In this work, we use cluster information about aerosol type to reduce the discrepancy. Our improved method will be useful for retrieving particulate matter from satellite measurements.

Asian dust storms, which often occur on spring, can long range transport and pass through the China Seas. During this process, it makes some impact on marine ecology and region climate. In this paper, the optical and thermal properties of Asian dust aerosols are firstly presented from the satellite MODIS observations. By comparing strong dust, weak dust, clear water and clouds, the reflectances of dust aerosols over ocean at the visible 0.47μm 0.86μm, and the near-infrared 1.64μm have some significant features, it satisfies R0.47<R1.64<R0.86 for strong dust aerosol over ocean, the weak dust aerosol meets R1.64<R0.47<R0.86, even R1.64<R0.86<R0.47, and the dust reflectance may be from 0.1 to 0.3. At the thermal atmospheric windows bands 8.5, 11 and 12μm, for cloud and clear water region, the brightness temperature at 12μm is highest and the temperature at 11μm is close to 12μm. However, for dust aerosols, the brightness temperature at 12μm is much greater than those at 8.5μm and 11μm. The brightness temperature difference between 8.5μm and 11μm is small and the lower is the difference, the stronger is the dust aerosol. Based on those visible and thermal characteristics, a detection algorithm for dust aerosols over ocean is designed and is conducted for some cases. It can identify the strong and the weak dust regions well and it is nice to study the dust properties deeply.

Aiming the remote sensing low cost, up-gradable and modular tools development for monitoring relevant atmospheric parameters and processes in the whole troposphere (from 250 m to 12-15 Km altitude), a new configuration LIDAR system, i.e. ^ESYROLIDAR, dedicated for tropospheric aerosols and clouds high temporal (minutes) and spatial resolutions (meters) monitoring have been developed and tested. This extremely up-gradable configuration of ^ESYROLIDAR is based on: a multi -wavelengths (1064, 532 and 355 nm) powerful (200, 100 and 45 mJ/pulse) and relatively high variable repetition rate (up to 30 Hz) Nd:YAG pulsed laser, a large Newtonian telescope (40 cm diameter of collector mirror) and a new opto-mechanics detection module built in an original "eye geometry" consideration. The firsts tests and measurements were performed at the site of Science and Technology Park TehnopolIS (Iasi city located on the northeastern region of Romania), using a basic configuration with a 532 nm elastic detection with depolarization study module. Different types of clouds up to 12 km in daylight are highlighted from this first measurement. Measurements and tests made in other recent campaigns for 355 nm elastic channel are also presented. The ability of the new LIDAR system to determine the height of planetary boundary layer (PBL) determined from the LIDAR signals, as well as the aerosols load and optical parameters (extinction and backscatter) and the evaluation of atmospheric dynamics at high spatial-temporal resolutions are clearly confirmed. This paper presents the ^ESYROLIDAR basic configuration with its two VIS elastic channels (532 nm, parallel and cross). The first measurements made with the UV (355 nm - interchangeable channel) and VIS (532 nm) elastic channels are illustrated by typical examples. The quality of ^ESYROLIDAR atmospheric profiles is based on advantages of low divergence (0.15 mrad), relatively high repetition rate (30 Hz) and the coaxial UV-VIS-NIR .The present challenges are first a new robust more automatized alignment system and second the integration of more Raman detection channels i.e. Raman H₂O water vapor at 407 nm. This system is the base of the ROmanian LIdar NETwork (ROLINET).