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An accurate model and parameterization of fog is needed to increase the reliability and usefulness of electro-optical systems in all relevant environments. Current models vary widely in their ability to accurately predict the size distribution and subsequent optical properties of fog. The Advanced Navy Aerosol Model (ANAM), developed to model the distribution of aerosols in the maritime environment, does not currently include a model for fog. One of the more prevalent methods for modeling particle size spectra consists of fitting a modified gamma function to fog measurement data. This limits the fog distribution to a single mode. Here we establish an empirical model for predicting complicated multimodal fog droplet size spectra using machine learning techniques. This is accomplished through careful measurements of fog in a controlled laboratory environment and measuring fog particle size distributions during outdoor fog events.

Space Situational Awareness (SSA) is of utmost importance in today's congested and contested space environment. Satellites must perform orbital corrections for station keeping, devices like high efficiency electric propulsion systems such as a Hall effect thrusters (HETs) to accomplish this are on the rise. The health of this system is extremely important to ensure the satellite can maintain proper position and perform its intended mission. Electron temperature is a commonly used diagnostic to determine the efficiency of a hall thruster. Recent papers have coordinated near infrared (NIR) spectral measurements of emission lines in xenon and krypton to electron temperature measurements. Ground based observations of these spectral lines could allow the health of the thruster to be determined while the satellite is in operation. Another issue worth considering is the availability of SSA assets for ground-based observations. The current SSA architecture is limited and task saturated. If smaller telescopes, like those at universities, could successfully detect these signatures they could augment data collection for the SSA network. To facilitate this, precise atmospheric modeling must be used to pull out the signature. Within the atmosphere, the NIR has a higher transmission ratio and typical HET propellants are approximately 3x the intensity in the NIR versus the visible spectrum making it ideal for ground based observations. The proposed research will focus on developing a model to determine xenon and krypton signatures through the atmosphere and estimate the efficacy through ground-based observations. The model will take power modes, orbit geometries, and satellite altitudes into consideration and be correlated with lab and field observations.

The daytime sky has been recently demonstrated as a useful calibration tool for deriving polarization cross-talk properties of large astronomical telescopes. The Daniel K Inouye Solar Telescope (DKIST) and other large telescopes under construction can benefit from precise polarimetric calibration of large mirrors. Several atmospheric phenomena and instrumental errors potentially limit the techniques accuracy. At the 3.67m AEOS telescope on Haleakala, we have performed a large observing campaign with the HiVIS spectropolarimeter to identify limitations and develop algorithms for extracting consistent calibrations. Effective sampling of the telescope optical configurations and filtering of data for several derived parameters provide robustness to the derived Mueller matrix calibrations. Second-order scattering models of the sky show that this method is relatively insensitive to multiple-scattering in the sky provided calibration observations are done in regions of high polarization degree. The technique is also insensitive to assumptions about telescope induced polarization provided the mirror coatings are highly reflective. Zemax-derived polarization models show agreement between the functional dependence of polarization predictions and the corresponding on-sky calibrations., Comment: Accepted for publication in SPIE JATIS

Short wave radiation (SWR) and its attenuation with depth have a major impact on the vertical distribution of the oceanic water temperature, dynamical processes, and ocean-atmosphere interactions. In numerical modeling of oceanic processes, the SWR usually comes from the atmospheric model predictions, while the short wave attenuation schemes are internally prescribed (estimated) inside the oceanic dynamical model. It has been reported that atmospheric models show a tendency to overestimate the shortwave radiation due to underestimation of predicted low-level clouds. Most existing schemes to specify the attenuation of SWR with depth in numerical models are based on: the Jerlov (1976) water-types classification; climatological estimates of attenuation coefficients or from the biological model predictions of light-absorbing and scattering water constituents. All of the above attenuation schemes are prone to introducing errors in the attenuation of short wave radiation with depth. As a result, we have to deal with two types of errors in the oceanic modeling: those due to the incorrect specification of the magnitude of SWR at the surface (from the atmospheric model), and those due to inaccurate vertical attenuation of SWR (prescribed in the oceanic model). We have developed an approach for estimating errors in the oceanic model heat budget due to errors in surface values of SWR and in its attenuation with depth. Based on this approach, we present examples illustrating sensitivities of the heat budget of the water column to the changes in specification of surface SWR and its attenuation.

Water level was estimated, using AltiKa radar altimeter onboard the SARAL satellite, over the Ukai reservoir using modified algorithms specifically for inland water bodies. The methodology was based on waveform classification, waveform retracking, and dedicated inland range corrections algorithms. The 40-Hz waveforms were classified based on linear discriminant analysis and Bayesian classifier. Waveforms were retracked using Brown, Ice-2, threshold, and offset center of gravity methods. Retracking algorithms were implemented on full waveform and subwaveforms (only one leading edge) for estimating the improvement in the retrieved range. European Centre for Medium-Range Weather Forecasts (ECMWF) operational, ECMWF re-analysis pressure fields, and global ionosphere maps were used to exactly estimate the range corrections. The microwave and optical images were used for estimating the extent of the water body and altimeter track location. Four global positioning system (GPS) field trips were conducted on same day as the SARAL pass using two dual frequency GPS. One GPS was mounted close to the dam in static mode and the other was used on a moving vehicle within the reservoir in Kinematic mode. In situ gauge dataset was provided by the Ukai dam authority for the time period January 1972 to March 2015. The altimeter retrieved water level results were then validated with the GPS survey and in situ gauge dataset. With good selection of virtual station (waveform classification, back scattering coefficient), Ice-2 retracker and subwaveform retracker both work better with an overall root-mean-square error

In this paper, we draw attention to the requirements for obtaining measurement data essential to accurate modeling and prediction of atmospheric laser beam propagation at heights 10 meters or less above the ocean surface. This is an atmospheric zone we call the marine boundary layer . There are numerous models and applications for optical beam propagation in the upper atmosphere that based on the Kolmogorov Theory of Turbulence. However, close to the ocean surface standard procedures for measuring and modeling the effects of boundary layer turbulence may no longer apply. In addition to classical measurement procedures, we suggest a new methodology and measurement procedures for exploration of beam propagation and the ensuing dynamics within the marine boundary layer. [1,2]

In this study we investigated the impact of land surface surface process & land-atmospheric interaction on weather and surface hydrology. The ultimate goal is to integrate remote sense data into numerical mesoscale weather prediction and regional climate model in order to improve prediction of the impacts of land-atmosphere interactions and land-surface processes on regional weather, and hydrology. We have used climatology based green vegetation fraction and 8-day Moderate Resolution Imaging Spectroradiometer (MODIS) based green vegetation fraction and integrated in the Land Information System to conduct uncoupled simulation to understand the impact on surface and hydrological parameters in the summer season. The vegetation response is also realized through coupled regional climate simulation in which climatological based greenness and 8-days varying vegetation is investigated and quantify the impact of vegetation on summertime precipitation process. This study has bought following findings (a) Satellite based vegetation indices captures vegetation temporal patterns more realistic than climatological vegetation data and detects early/late spring signature through vegetation indices, (b) Integrated satellite vegetation greenness input data in regional weather model resolved much better soil moisture and soil temperature including the diurnal cycle of surface heat fluxes and surface temperature in the simulation. Secondly, integration of the TRMM based satellite rainfall product into coupled hydrological and Atmospheric model and results shows better resolved soil moisture patterns in the remote regions of the Asia Mountain regions.

Oil spills are one of the major environmental concerns, especially in the coastal zones of the ocean. Satellite remote sensing imagery has proved to be a useful tool for monitoring oil spills in the marine environment. With its two daily acquisitions and the possibility to obtain near-real-time data free of charge, the Moderate Resolution Imaging Spectroradiometer (MODIS) shows interesting potential as such a cost-effective supplementary tool. Several researches on oil spill detection in MODIS imagery has been carried out for the past few years. Basically, oil spills were manually detected from MODIS imagery [1,2]. The disadvantage of the manual detection method is inefficient and subjective. Shi et al. proposed an oil spill detection method from MODIS imagery by using fuzzy cluster and texture feature extraction [3]. It works in an automatic manner and does not require any priori knowledge of occurrence or the spectral attributes of spills. But its efficiency in very near shore regions is limited. Chen and Zhao detected oil spills from the oil-water contrast ratio image by using a thresholding method [4].They found that the oil-water contrast ratio can be enhanced by replacing the original image with the ratio image of two different band ones in 400-800 nm. To obtain the oil-water contrast ratio image from the MODIS imagery, they selected the oil spill area and the background sea area and then calculated the mean radiance or emissivity value in those areas. By doing so, the automation and the accuracy of the method were reduced. Adamo et al. [5] and Kudryavtsev et al. [6] proposed physical methods for oil spill detection from MODIS imagery acquired in sunglint conditions. These two methods take imaging geometry into consideration and have the aid of other models or functions such as the Cox and Munk (1954) model [7],the CMOD4 model [8,9], the ECMWF (European Centre for Medium-Range Weather Forecasts) atmospheric model, and the transfer function, which increase the algorithm complexity and rely on some assumptions.

In the fields of early warning, one is depending on reliable image exploitation: Only if the applied detection and tracking algorithms work efficiently, the threat approach alert can be given fast enough to ensure an automatic initiation of the countermeasure. In order to evaluate the performance of those algorithms for a certain electro-optical (EO) sensor system, test sequences need to be created as realistic and comprehensive as possible. Since both, background and target signature, depend on the environmental conditions, a detailed knowledge of the meteorology and climatology is necessary. Trials for measuring these environmental characteristics serve as a solid basis, but might only constitute the conditions during a rather short period of time. To represent the entire variation of meteorology and climatology that the future system will be exposed to, the application of comprehensive atmospheric modelling tools is essential. This paper gives an introduction of the atmospheric modelling tools that are currently used at Fraunhofer IOSB to simulate spectral background signatures in the infrared (IR) range. It is also demonstrated, how those signatures are affected by changing atmospheric and climatic conditions. In conclusion – and with a special focus on the modelling of different cloud types - sources of error and limits are discussed.

Some X-ray instruments require the utilization of large-area windows to provide vacuum barriers. The necessary attributes of the window material include transparency to X-rays, low scattering, and possession of suitable mechanical properties for reliable long-term performance. Kapton is one such material except that it is a polymer and a large window made from Kapton with a pressure differential of one atmosphere across it can undergo substantial deformation at room temperature. In this paper, we report on the mechanical testing of Kapton samples including creep measurements, and comparison with published data. We use of these data together with analytical / numerical models to predict the changes in the profile of Kapton vacuum windows over time, and show good agreement with experimental measurements.

This study investigates laser beam propagation through an atmospheric boundary layer near the ocean surface. Objectives of this research are to ascertain feasibility limits for achieving maximum energy efficiency at extended ranges in the face of atmospheric and other distortions as the laser beam penetrates through transitional (anisotropic) and turbulent (isotropic) boundary layer regimes. Various aspects of turbulence modeling of laser beam propagation near the ocean surface are discussed including: Kolmogorov's model of atmospheric turbulence, parameterized structure functions (e.g., velocity and temperature gradients, gradients in refractive index) and other important factors affecting near surface propagation such as humidity, aerosols, and wave slap . Various preliminary modeled propagation results are shown, and a new methodology is proposed for improving existing model estimates with new time domain measurement procedures.

This study investigates laser beam propagation through an atmospheric boundary layer near the ocean surface. Objectives of this research are to ascertain feasibility limits for achieving maximum energy efficiency at extended ranges in the face of atmospheric and other distortions as the laser beam penetrates through transitional (anisotropic) and turbulent (isotropic) boundary layer regimes. Various aspects of turbulence modeling of laser beam propagation near the ocean surface are discussed including: Kolmogorov’s model of atmospheric turbulence, parameterized structure functions (e.g., velocity and temperature gradients, gradients in refractive index) and other important factors affecting near surface propagation such as humidity, aerosols, and wave slap. Various preliminary modeled propagation results are shown, and a new methodology is proposed for improving existing model estimates with new time domain measurement procedures.

The infrared (IR) energy radiated from any source passes through the atmosphere before reaching the sensor. As a result, the total signature captured by the IR sensor is significantly modified by the atmospheric effects. The dominant physical quantities that constitute the mentioned atmospheric effects are the atmospheric transmittance and the atmospheric path radiance. The incoming IR radiation is attenuated by the transmittance and path radiance is added on top of the attenuated radiation. In IR scene simulations OpenGL is widely used for rendering purposes. In the literature there are studies, which model the atmospheric effects in an IR band using OpenGLs exponential fog model as suggested by Beers law. In the standard pipeline of OpenGL, the related fog model needs single equivalent OpenGL variables for the transmittance and path radiance, which actually depend on both the distance between the source and the sensor and also on the wavelength of interest. However, in the conditions where the range dependency cannot be modeled as an exponential function, it is not accurate to replace the atmospheric quantities with a single parameter. The introduction of OpenGL Shading Language (GLSL) has enabled the developers to use the GPU more flexible. In this paper, a novel method is proposed for the atmospheric effects modeling using the least squares estimation with polynomial fitting by programmable OpenGL shader programs built with GLSL. In this context, a radiative transfer model code is used to obtain the transmittance and path radiance data. Then, polynomial fits are computed for the range dependency of these variables. Hence, the atmospheric effects model data that will be uploaded in the GPU memory is significantly reduced. Moreover, the error because of fitting is negligible as long as narrow IR bands are used.

Fast and accurate computation of light path deviation due to atmospheric refraction is an important requirement for real-time simulation of optical imaging sensor systems. A large body of existing literature covers various methods for application of Snell’s Law to the light path ray tracing problem. This paper provides a discussion of the adaptation to real time simulation of atmospheric refraction ray tracing techniques used in mid-1980's LOWTRAN releases. The refraction ray trace algorithm published in a LOWTRAN-6 technical report by Kneizys (et. al.) has been coded in MATLAB for development, and in C-language for simulation use. To this published algorithm we have added tuning parameters for variable path segment lengths, and extensions for Earth grazing and exoatmospheric "near Earth" ray paths. Model atmosphere properties used to exercise the refraction algorithm were obtained from tables published in another LOWTRAN-6 related report. The LOWTRAN-6 based refraction model is applicable to atmospheric propagation at wavelengths in the IR and visible bands of the electromagnetic spectrum. It has been used during the past two years by engineers at the U.S. Army Aviation and Missile Research, Development and Engineering Center (AMRDEC) in support of several advanced imaging sensor simulations. Recently, a faster (but sufficiently accurate) method using Gauss-Chebyshev Quadrature integration for evaluating the refraction integral was adopted.

The Optical Payload for Lasercomm Science (OPALS) Flight System on-board the International Space Station uses a charge coupled device (CCD) camera to detect a beacon laser from Earth. Relative measurements of the background contributed by upwelling radiance under diverse illumination conditions and varying surface terrain is presented. In some cases clouds in the field-of-view allowed a comparison of terrestrial and cloud-top upwelling radiance. In this paper we will report these measurements and examine the extent of agreement with atmospheric model predictions.

The efficient particle measurement methods are very important for the assessment of ambient air quality. Compared with other methods, the light scattering method has the advantages of non-destructive and real time detection, and has been used in the detection and analysis of particle composition and concentration. Different from non-polarized light scattering detection, polarized light scattering is suitable for the measurement of fine particles, such as PM 1 and PM 2.5 . In this paper, we establish a three-component model to describe three typical particle elements in atmospheric suspended matters, and also set several pollution state changes according to some reported real measured data. By our primary polarization simulation under weak scattering approximation, we analyze Mueller matrix elements fluctuation with the different changes of particle concentration and distribution, and then extract two characteristic elements to follow the status particle composition. The results imply the potential of the backscattered polarization characterization to distinguish and evaluate the parameter variation in an atmospheric particulate model, and also show the possible sensitivity higher than the non-polarization characteristic.

This paper will focus on the effect of atmospheric conditions on EO sensor performance using computer models. We have shown the importance of accurately modeling atmospheric effects for predicting the performance of an EO sensor. A simple example will demonstrated how real conditions for several sites in China will significantly impact on image correction, hyperspectral imaging, and remote sensing. The current state-of-the-art model for computing atmospheric transmission and radiance is, MODTRAN® 5, developed by the US Air Force Research Laboratory and Spectral Science, Inc. Research by the US Air Force, Navy and Army resulted in the public release of LOWTRAN 2 in the early 1970’s. Subsequent releases of LOWTRAN and MODTRAN® have continued until the present. Please verify that (1) all pages are present, (2) all figures are correct, (3) all fonts and special characters are correct, and (4) all text and figures fit within the red margin lines shown on this review document. Complete formatting information is available at http://SPIE.org/manuscripts Return to the Manage Active Submissions page at http://spie.org/submissions/tasks.aspx and approve or disapprove this submission. Your manuscript will not be published without this approval. Please contact author_help@spie.org with any questions or concerns. The paper will demonstrate the importance of using validated models and local measured meteorological, atmospheric and aerosol conditions to accurately simulate the atmospheric transmission and radiance. Frequently default conditions are used which can produce errors of as much as 75% in these values. This can have significant impact on remote sensing applications.

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

The alternative Bendersky, Kopeika, and Blaunstein (BKB) model of measuring the refractive structure index parameter, Cn² has proven to be a reliable, well-used means of quantifying and characterizing the atmospheric turbulence in a given environment. This model relies on various meteorological parameters such as temperature, wind speed, relative humidity, and time of day in order to procure the resulting Cn² quantity. Using experimentally confirmed results from a desert environment, the utility of this model may be extended to other climates by adapting temporal hour weights used within the model. The adaptation of these weighted parameters are shown to have a relationship with the unique weather conditions of a given region which are demonstrated by data points collected from two testing ranges located in Florida in addition to archived weather data. The resulting extended model is then compared to commercial scintillometer data for validation. Keywords: BKB Model, Scintillation, Scintillometer, Atmospheric Turbulence, Refractive Index Structure Parameter

The advent of expensive, large-aperture telescopes and complex adaptive optics (AO) systems has strengthened the need for detailed simulation of such systems from the top of the atmosphere to control algorithms. The credibility of any simulation is underpinned by the quality of the atmosphere model used for introducing phase variations into the incident photons. Hitherto, simulations which incorporate wind layers have relied upon phase screen generation methods that tax the computation and memory capacities of the platforms on which they run. This places limits on parameters of a simulation, such as exposure time or resolution, thus compromising its utility. As aperture sizes and fields of view increase the problem will only get worse. We present an autoregressive method for evolving atmospheric phase that is efficient in its use of computation resources and allows for variability in the power contained in frozen flow or stochastic components of the atmosphere. Users have the flexibility of generating atmosphere datacubes in advance of runs where memory constraints allow to save on computation time or of computing the phase at each time step for long exposure times. Preliminary tests of model atmospheres generated using this method show power spectral density and rms phase in accordance with established metrics for Kolmogorov models.

Long range imaging systems have applications in vessel traffic monitoring, border and coastal observation, and generic surveillance. Often, sign reading and identification capabilities are required, and medium or long-wave infrared systems are simply not the best solution for these tasks, because of the low scene contrast. Among reflected light imagers, the short-wave infrared has a competitive advantage over the visible and near-infrared spectrum, being less affected by path attenuation, scattering and turbulence. However, predicting a SWIR system long range performance still represents a challenge because of the need of an accurate atmospheric modelling. In this paper, we present the key limiting performance factors for long range applications, and how we used popular atmospheric models to extract the synthetic simulation parameters needed for range performance prediction. We then present a case study for a long range application, where the main requirement is to read a vessel name at distances greater than 10km. The results show a significant advantage of SWIR over visible and near-infrared solutions for long range identification tasks.

An Atmospheric radiative transfer model calculates radiative transfer of electromagnetic radiation through a planetary atmosphere. Both shortwave radiance and longwave radiance parameterizations in an atmospheric model calculate radiation fluxes and heating rates in the earth-atmospheric system. One radiative transfer model is the rapid radiative transfer model (RRTM), which calculates of longwave and shortwave atmospheric radiative fluxes and heating rates. Longwave broadband radiative transfer code for general circulation model (GCM) applications, RRTMG, is based on the single-column reference code, RRTM. The RRTMG is a validated, correlated k-distribution band model for the calculation of longwave and shortwave atmospheric radiative fluxes and heating rates. The focus of this paper is on the RRTMG long wave (RRTMG_LW) model. In order to improve computational efficiency, RRTMG_LW incorporates several modifications compared to RRTM. In RRTM_LW there are 16 g points in each of the spectral bands for a total of 256 g points. In RRTMG_LW, the number of g points in each spectral band varies from 2 to 16 depending on the absorption in each band. RRTMG_LW employs a computationally efficient correlated-k method for radiative transfer calculations. It contains 16 spectral bands with various number of quadrature points (g points) in each of the bands. In total, there are 140 g points. The radiative effects of all significant atmospheric gases are included in RRTMG_LW. Active gas absorbers include H 2 O, O 3 , CO 2 , CH 4 , N 2 O, O 2 and four types of halocarbons: CFC-11, CFC-12, CFC-22, and CCL4. RRTMG_LW also treats the absorption and scattering from liquid and ice clouds and aerosols. For cloudysky radiative transfer, a maximum-random cloud overlapping scheme is used. Small scale cloud variability, such as cloud fraction and the vertical overlap of clouds can be represented using a statistical technique in RRTMG_LW. Due to its accuracy, RRTMG_LW has been implemented operationally in many weather forecast and climate models. RRTMG_LW is in operational use in ECMWF weather forecast system, the NCEP global forecast system, the ECHAM5 climate model, Community Earth System Model (CESM) and the weather and forecasting (WRF) model. RRTMG_LW has also been evaluated for use in GFDL climate model. In this paper, we examine the feasibility of using graphics processing units (GPUs) to accelerate the RRTMG_LW as used by the WRF. GPUs can provide a substantial improvement in RRTMG speed by supporting the parallel computation of large numbers of independent radiative calculations. Furthermore, using commodity GPUs for accelerating RRTMG_LW allows getting a much higher computational performance at lower price point than traditional CPUs. Furthermore, power and cooling costs are significantly reduced by using GPUs. A GPU-compatible version of RRTMG was implemented and thorough testing was performed to ensure that the original level of accuracy is retained. Our results show that GPUs can provide significant speedup over conventional CPUs. In particular, Nvidia’s GTX 680 GPU card can provide a speedup of 69x for the compared to its single-threaded Fortran counterpart running on Intel Xeon E5-2603 CPU.

A dual wavelength micro pulse polarization lidar system is designed, in which Nd:YAG laser at 1064nm and 532nm is employed as the exciting source, to research the depolarization ratio, the lidar ratio and the angstrom coefficient of aerosols. Numerical simulations are performed with the standard atmospheric model to verify the detection ability of the system. The simulation results show that the lidar system is capable of detecting the depolarization ratio of aerosols up to a height larger than 6 km at night and 2 km in the daytime with a sigal to noise ratio of 10. In the meantime, the lidar system can also be used to detect the angstrom coefficient, and can provide important scientific data for studies of the relastionship among these parameters.

Signal-to-noise ratio (SNR) is an important parameter of infrared detection system. SNR of infrared detection system is determined by the target infrared radiation, atmospheric transmittance, background infrared radiation and the detector noise. The infrared radiation flux in the atmosphere is determined by the selective absorption of the gas molecules, the atmospheric environment, and the transmission distance of the radiation, etc, so the atmospheric transmittance and infrared radiance flux are intricate parameters. A radiometric model for the calculation of SNR of infrared detection system is developed and used to evaluate the effects of various parameters on signal-to-noise ratio (SNR). An atmospheric modeling tool, MODTRAN, is used to model wavelength-dependent atmospheric transmission and sky background radiance. Then a new expression of SNR is deduced. Instead of using constants such as average atmospheric transmission and average wavelength in traditional method, it uses discrete values for atmospheric transmission and sky background radiance. The integrals in general expression of SNR are converted to summations. The accuracy of SNR obtained from the new method can be improved. By adopting atmospheric condition of the 1976 US standard, no clouds urban aerosols, fall-winter aerosol profiles, the typical spectrum characters of sky background radiance and transmittance are computed by MODTRON. Then the operating ranges corresponding to the threshold quantity of SNR are calculated with the new method. The calculated operating ranges are more close to the measured operating range than those calculated with the traditional method.

The rapid development of the communication technology and sensing applications calls for broader bandwidth and faster speed. The influence of atmosphere on the propagation character of THz wave can mainly fall into two categories: the scattering of the particles in the atmosphere and the absorption of atmosphere molecules which can be divided into two aspects: line-by-line and continuum absorption. The most controversial point is the calculation of continuum absorption. The specific attenuation of different humidity are calculated by AM model and the modified VVW line shape method and compared with that of ITU-R P.676-9. The continuum absorption of the AM model is calculated using the MT-CKD method, another method to calculate the continuum absorption is to introduce continuum-like terms of water vapor and dry air which is used in the modified VVW line shape method. The result shows a better agreement of the modified VVW line shape method than that of the AM model because the coefficient can be modified to fit the ITU-R P.676-9, and the difference between the AM model and the ITU-R P.676-9 is small, too. The best fit coefficients of modified VVW line shape method for different humidity are obtained. And the relation of the coefficients and the humidity can be expressed by two regressed equations, and the humidity modification is included in the new correction terms.

Currently there are extensive modeling and measurement capabilities for the region extending from 100 ft above sea surface to space, but few such capabilities exist for the region ex tending up to 10 ft above the sea surface. By measuring and characterizing conditions in the mari ne boundary layer existing be low 30 ft above the sea surface such as turbulence and extinction, the optical communication capabilities of maritime vessels when op erating at or near the surface may be extended and enhanced. Key physical parameters such as absorption, scattering, and turbulence strength ( C n2 ) along the propagation path have a degree of variability on meteorological conditions as well optical wavelength. Modeling of the atmospheric environment is thus critical in order to generate a good understanding of optical propagation through the atmosphere. NUWC is utilizing software provided by MZA to model C n2 and resultant beam propagation characteristics through the near-marine boundary layer. We are developi ng the capability of near-marine boundary layer atmospheric and turbulence measurements and modeling as well as optical la ser link testing at outdoor test sites. Measurements are performed with optical laser links (e.g., bit rate error), scintillometer, and particle image velocimetry (PIV) cameras, while turbulence and propagation modeling is achieved using MODTRAN5, ATMTools, NSLOT, LEEDR, and WaveTrain modeling and simulation code. By better understanding the effects of turbulence on optical transmission in the near-marine boundary layer through modeling and experimental measurements, measures can be implemented to reduce the bit error rate and increase data throughput, enabling more efficient and accurate communication link capabilities. Keywords: Free-space optics, marine boundary layer, communication networks, turbulence, MODTRAN

Wind profile is fundamental in many atmospheric phenomena. Radiosonde, windprofiler, and Doppler lidar, have been developed for the wind measurement. Radiosonde and windprofiler are used to obtain wind profiles. About 1,300 weather stations launch radiosondes to obtain profiles of pressure, wind, temperature, and humidity. Most of the weather stations are on land, while the stations on the sea are very sparse. Spaceborne visible and infrared imagers and microwave scatterometers can obtain wind data only at a specific altitude. Current wind observations are not enough and their reliability in the global climate model and weather prediction must be improved. Many scientific groups anticipate the realization of a global observation system for three-dimensional wind measurements. The spaceborne Doppler lidar is regarded as one of the candidate sensors for the global wind measurements. The working group on Japanese spaceborne Doppler Lidar has been established to realize for wind measurements from space. In this paper, we describe the activities and goals of this working group.

In this presentation we will discuss the performance of classification and retrieval algorithms for spaceborne cloud and precipitation radars such as the Global Precipitation Measurement mission [1] Dual-frequency Precipitation Radar (GPM/DPR) [2], and notional radar for the Aerosol/Clouds/Ecosystem (ACE) [1] mission and related concepts. Spaceborne radar measurements are simulated either from Airborne Precipitation Radar 2 nd Generation (APR-2, [3]) observations, or from atmospheric model outputs via instrument simulators contained in the NASA Earth Observing Systems Simulators Suite (NEOS 3 ). Both methods account for the three dimensional nature of the scattering field at resolutions smaller than that of the spaceborne radar under consideration. We will focus on the impact of nonhomogeneities of the field of hydrometeors within the beam. We will discuss also the performance of methods to identify and mitigate such conditions, and the resulting improvements in retrieval accuracy. The classification and retrieval algorithms analyzed in this study are those derived from APR-2’s Suite of Processing and Retrieval Algorithms (ASPRA); here generalized to operate on an arbitrary set of radar configuration parameters to study the expected performance of spaceborne cloud and precipitation radars. The presentation will highlight which findings extend to other algorithm families and which ones do not.

We studied the semi-diurnal variation of surface rainfall over southern Africa and the Amazon simulated by a global cloud system resolving model (Nonhydrostatic ICosahedral Atmospheric Model; NICAM) under realistic conditions with land-sea contrast. This semi-diurnal variation was found to be consistent with the Tropical rainfall Measuring Mission (TRMM) and Meteosat-8 observations. The timing of the primary afternoon rainfall peak by the NICAM coincides with TRMM/PR primary afternoon peak, and the secondary early morning peak by the NICAM simulation agree with the TRMM/PR observations within two hours. Mean size of deep convection (DC), defined by 213K of the Meteosat-8 infrared data shows semi-diurnal variation, although the number of DC show diurnal variation with coincident peak with TRMM/PR primary peak. The semi-diurnal variation of the mean size of DC and number of DC is simulated with small secondary peak over southern Africa by NICAM, whose DC is defined by OLR smaller than 112 W m-2 (corresponding to 213 K in cumulative frequency).

The emergence of high-resolution satellites with new spectral channels and the ability to change its viewing angle has highlighted the importance of modeling the atmospheric effects. So, atmospheric correction serves a critical role in the processing of remotely sensed image data, particularly with respect to identification of pixel content. Efficient and accurate realization of images in units of reflectance, rather than radiance, has proven to be a crucial point in the pre-processing of images in remote sensing applications, acquired under a variety of measurement conditions. However, reflectance of the objects recorded by satellite sensors is generally affected by atmospheric absorption and scattering, sensor-targetillumination geometry, and sensor calibration. These normally result in distortion of the actual reflectance of the objects that subsequently affects the extraction of information from images. The use of atmospheric models has significantly improved the results of the corrections. In this study we have proceeded to make the atmospheric correction of the eight multispectral bands of high resolution WorldView-2 satellite by three different atmospherics models (COST, DOS, 6S) defining the geometry of the satellite observation, viewing angle and setting the weather conditions more suited for the acquired images of the study area (Granadilla, Canary Islands). For this purpose, the reflectance obtained by COST, DOS and 6S atmospheric correction techniques are compared with the Top of Atmosphere (TOA) reflectance. Specifically, the 6S atmospheric correction model, based on radiative transfer theory, provides patterns which describe properly atmospheric conditions in this specific study area for monitoring turbid coastal environments. To check the proper functioning of the atmospheric correction comparison was performed between ground-based measurements and corresponding obtained by the eight multispectral satellite channels through the 6S atmospheric model, with similar date, weather and lighting conditions.

Aerosol retrieval work from satellite data, i.e. aerosol remote sensing, is divided into three parts as: satellite data analysis, aerosol modeling and multiple light scattering calculation in the atmosphere model which is called radiative transfer simulation. The aerosol model is compiled from the accumulated measurements during more than ten years provided with the world wide aerosol monitoring network (AERONET). The radiative transfer simulations take Rayleigh scattering by molecules and Mie scattering by aerosols in the atmosphere, and reflection by the Earth surface into account. Thus the aerosol properties are estimated by comparing satellite measurements with the numerical values of radiation simulations in the Earth-atmosphere-surface model. It is reasonable to consider that the precise simulation of multiple light-scattering processes is necessary, and needs a long computational time especially in an optically thick atmosphere model. Therefore efficient algorithms for radiative transfer problems are indispensable to retrieve aerosols from space.

The NDSA (Normalized Differential Spectral Attenuation) approach is based on the conversion of a spectral parameter (the spectral sensitivity S) derived from power measurements, into the total content of water vapor (IWV, Integrated Water Vapor) along the propagation path between the two LEO satellites, through pre-determined IWV-S relations. This paper shows how some problems concerning the relationships between IWV (Integrated Water Vapor) and S could be overcome. In fact, two basic problems affected the reliability of such empirical IWV-S relations found so far: the first was the fact that the accuracy of the radiosonde data used to derive them was not uniformly distributed in the northern and southern hemisphere; the second was the limited amount of radiosonde data available at the highest altitudes (above 10 km), and their scarce reliability. Furthermore, the problem of correcting for the presence of liquid water needed to be considered. Here we present the results of a global scale analysis of the IWV-S relations made utilizing the ECMWF global atmospheric model. S and IWV were simulated and computed at all altitudes from 0 to 20 km, obtaining IWV-S relations for 17, 19, 21, 179 and 182 GHz. Also, the correction of IWV estimates by the presence of liquid water is shown to be effective by using an additional frequency around 30 GHz.

The studies on planetary radiative transfer computation have become important elements to disk-averaged spectral characterization of potential exoplanets. In this paper, we report an improved ray-tracing based atmospheric simulation model as a part of 3-D earth-like planet model with 3 principle sub-components i.e. land, sea and atmosphere. Any changes in ray paths and their characteristics such as radiative power and direction are computed as they experience reflection, refraction, transmission, absorption and scattering. Improved atmospheric BSDF algorithms uses Q.Liu's combined Rayleigh and aerosol Henrey-Greenstein scattering phase function. The input cloud-free atmosphere model consists of 48 layers with vertical absorption profiles and a scattering layer with their input characteristics using the GIOVANNI database. Total Solar Irradiance data are obtained from Solar Radiation and Climate Experiment (SORCE) mission. Using aerosol scattering computation, we first tested the atmospheric scattering effects with imaging simulation with HRIV, EPOXI. Then we examined the computational validity of atmospheric model with the measurements of global, direct and diffuse radiation taken from NREL(National Renewable Energy Laboratory)s pyranometers and pyrheliometers on a ground station for cases of single incident angle and for simultaneous multiple incident angles of the solar beam.

Traditional color and airmass corrections can typically achieve ~0.02 mag precision in photometric observing conditions. A major limiting factor is the variability in atmospheric throughput, which changes on timescales of less than a night. We present preliminary results for a system to monitor the throughput of the atmosphere, which should enable photometric precision when coupled to more traditional techniques of less than 1% in photometric conditions. The system, aTmCam, consists of a set of imagers each with a narrow-band filter that monitors the brightness of suitable standard stars. Each narrowband filter is selected to monitor a different wavelength region of the atmospheric transmission, including regions dominated by the precipitable water absorption and aerosol scattering. We have built a prototype system to test the notion that an atmospheric model derived from a few color indices measurements can be an accurate representation of the true atmospheric transmission. We have measured the atmospheric transmission with both narrowband photometric measurements and spec- troscopic measurements; we show that the narrowband imaging approach can predict the changes in the throughput of the atmosphere to better than ~10% across a broad wavelength range, so as to achieve photometric precision less than 0.01 mag., Comment: 11 pages, 8 figures. To appear in conference proceeding: "Calibration and Standardization of Large Surveys and Missions in Astronomy and Astrophysics" (Fermilab, April 16-18, 2012)

On the basis of 95500 MASS/DIMM measurements of optical turbulence pro le obtained on Mt. Shatdzhatmazin 2009-2011 we have constructed 2 atmosphere models for this summit: one consisting of 9 typical turbulencepro les, and other of 300 randomly selected pro les. Pro les represent Cn2 and wind speed values estimated at13 standard MASS altitudes. We discuss advantages and disadvantages of these models from the point of view ofAO simulation. We used these models as input parameters in analytical simulation (PAOLA tool) of AO systemof future 2.5-m telescope of SAI. This simulation was used to estimate optimal parameters of this system andperformance characteristics corresponding to these parameters. Second 300-pro les atmosphere model allowedto evaluate the performance in terms of statistical distributions of metrics. E.g. for subaperture size 0.35 m andoptimizable exposure (lower limit 2 ms), the NGS AO system will deliver Strehl ratio more than 0.46 in R-bandusing R=13 guide star for 10% of time.Keywords: Adaptive optics simulation, atmospheric optical turbulence, site testing

Modeling and simulating the atmosphere in a controlled environment has been a study of interest to scientists for decades. The development of new technologies allows scientists to perform this task in a more realistic and controlled environment and provides a powerful tool for the study and better understanding of the propagation of light through the atmosphere. Technologies like Free-space laser communications (FSLC) and/or studies on light propagation through the atmosphere are areas which constantly benefit from breakthroughs in the development of atmospheric turbulence simulators. In this paper we present the results of the implementation of a phase only spatial light modulator (SLM) as an atmospheric turbulence simulator at the Short-Wave Infra-Red (SWIR) regime and its use with a FSLC system.

A new method of infrared image generation for typical aircraft that based on GPU is proposed. Complete procedure of infrared simulation including temperature model, radiation model, atmosphere model and image-forming system model is built in this paper. All of these models are solved and rendered with GPU which has powerful calculating ability. The result shows that dynamic infrared image of aircraft which varies with the status of aircraft could be generated efficiently with this method. Considering that temperature field could not be calculated real-timely and the unsatisfied simulation details in former infrared simulation methods, a new implementation method of calculating the temperature field with vertex texture of GPU is proposed.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

A lidar-based method was used to separate profiles of optical parameters due to different aerosol types over different European Aerosol Research LIdar NETwork (EARLINET) stations. The method makes uses of particle backscatter profiles at 532 nm and vertically resolved linear particle depolarization ratio measurements at the same wavelength. Values of particle depolarization ratio of 'pure' aerosol types (Saharan dust, biomass burning aerosols, anthropogenic aerosols, Volcanic ash aerosols) were taken from literature. Cases of CALIPSO space-borne lidar system were selected on the basis of different mixing state of the atmosphere over EARLINET stations. To identify the origin of air-masses four-day air mass back trajectories were computed using HYbrid Single-Particle Langrangian Integrated Trajectory (HYSPLIT) model, for different arrival heights, for the location and time under study was used. Also, the Dust REgional Atmospheric Modeling (DREAM) model was used to identify cases where dust from Saharan region was affecting the place under study. For our analysis we have used Atmospheric Volume Description (AVD), Cloud-Aerosol Discrimination (CAD) and extinction Quality Control (QC) flags to screen out CALIOP data. The method was applied for different horizontal resolution of 5, 25, 45 and 105 km. The height-resolved lidar results were finally compared with column-integrated products obtained with Aerosol Robotic Network Sun photometer (AERONET) in order to see to what extent Sun photometer columnar data are representative when different aerosol layers are present in the atmosphere.

Using an 850-nanometer-wavelength free-space optical (FSO)communications system of our own design, we acquired field data for the transmitted and received signals in fog at Point Loma, CA for a range of optical depths within the multiple-scattering regime. Statistical estimators for the atmospheric channel transfer function and the related coherency function were computed directly from the experimental data. We interpret the resulting channel transfer function estimates in terms of the physics of the atmospheric propagation channel and fog aerosol particle distributions. We investigate the behavior of the estimators using both real field-test data and simulated propagation data. We compare the field-data channel transfer function estimates against the outputs from a computationally-intensive radiative-transfer theory model-based approach, which we also developed previously for the FSO multiple-scattering atmospheric channel. Our results show that the data-driven channel transfer function estimates are in close agreement with the radiative transfer modeling, and provide comparable receiver signal detection performance improvements while being significantly less time and computationally-intensive.

This is a study on seasonal climate forecasts for the Asian Monsoon region. The unique aspect of this study is that it became possible to use the forecast results from as many as 16 state of the art coupled atmosphere-ocean models. A downscaling component, with respect to observed rainfall estimates uses data sets from TRMM and a dense rain gauge distriburion; this enables the forecasts of each model to be bias corrected to a common 25 km resolution. The downscaling statistics for each model, at each grid location is developed during a training phase of the model forecasts; the forecasts from all of the member models use the downscaling coefficients of the training phase. These forecasts are next used for the construction of a multimodel superensemble. A major result of this paper is on the climatology of the model rainfall. From the downscaled multimodel superensemble which shows a correlation of nearly 1.0 with respect to the observed climatology. This high skill is important for addressing the rainfall anomaly forecasts, which are defined in terms of departures from the observed (rather than a model based) climatology. The second part of this study addresses seasonal climate forecasts of Asian monsoon precipitation anomalies. Seasonal climate forecasts over the larger monsoon Asia domain and over the regional belts are evaluated. The superensemble forecasts invariably carry the highest skill compared to the member models globally and regionally. This relates largely to the presence of large systematic errors in models that carry low seasonal prediction skills. Such models carry persistent signatures of systematic errors, and their errors are recognized by the multimodel superensemble. One of the conclusions of this study is that given the uncertainties in current modeling for seasonal rainfall forecasts, post processing of multimodel forecasts, using the superensemble methodology, seems to provide the most promising results for the rainfall anomaly forecasts.

Understanding the Earth spectral bio-signatures provides an important reference datum for accurate de-convolution of collapsed spectral signals from potential earth-like planets of other star systems. This study presents a new ray tracing computation method including an improved 3D optical earth model constructed with the coastal line and vegetation distribution data from the Global Ecological Zone (GEZ) map. Using non-Lambertian bidirectional scattering distribution function (BSDF) models, the input earth surface model is characterized with three different scattering properties and their annual variations depending on monthly changes in vegetation distribution, sea ice coverage and illumination angle. The input atmosphere model consists of one layer with Rayleigh scattering model from the sea level to 100 km in altitude and its radiative transfer characteristics is computed for four seasons using the SMART codes. The ocean scattering model is a combination of sun-glint scattering and Lambertian scattering models. The land surface scattering is defined with the semi empirical parametric kernel method used for MODIS and POLDER missions. These three component models were integrated into the final Earth model that was then incorporated into the in-house built integrated ray tracing (IRT) model capable of computing both spectral imaging and radiative transfer performance of a hypothetical space instrument as it observes the Earth from its designated orbit. The IRT model simulation inputs include variation in earth orientation, illuminated phases, and seasonal sea ice and vegetation distribution. The trial simulation runs result in the annual variations in phase dependent disk averaged spectra (DAS) and its associated bio-signatures such as NDVI. The full computational details are presented together with the resulting annual variation in DAS and its associated bio-signatures.

In a companion paper presented at this conference we described how The Aerospace Corporation's Parameterized Image Chain Analysis & Simulation SOftware (PICASSO) may be used in conjunction with a limited number of runs of AFRL's MODTRAN4 radiative transfer code, to quickly predict the top-of-atmosphere (TOA) radiance received in the visible through midwave IR (MWIR) by an earth viewing sensor, for any arbitrary combination of solar and sensor elevation angles. The method is particularly useful for large-scale scene simulations where each pixel could have a unique value of reflectance/emissivity and temperature, making the run-time required for direct prediction via MODTRAN4 prohibitive. In order to be self-consistent, the method described requires an atmospheric model (defined, at a minimum, as a set of vertical temperature, pressure and water vapor profiles) that is consistent with the average scene temperature. MODTRAN4 provides only six model atmospheres, ranging from sub-arctic winter to tropical conditions - too few to cover with sufficient temperature resolution the full range of average scene temperatures that might be of interest. Model atmospheres consistent with intermediate temperature values can be difficult to come by, and in any event, their use would be too cumbersome for use in trade studies involving a large number of average scene temperatures. In this paper we describe and assess a method for predicting TOA radiance for any arbitrary average scene temperature, starting from only a limited number of model atmospheres.

The VST telescope is equipped with an Atmospheric Dispersion Corrector to counterbalance the spectral dispersion introduced by the atmosphere. The well known effect of atmospheric refraction is the bending of incoming light due to variable atmospheric density along the light path. This effect depends on the tangent of the zenith angle and also varies with altitude, humidity and wavelength. Since the magnitude of refraction depends on the wavelength, the resulting effect is not only a deviation of the light beam from its original direction but also a spectral dispersion of the beam. This effect can be corrected by introducing a dispersing element in the instrument. In the VST case the device that compensates for this effect is based on a set of four prisms in two cemented doublet pairs. The system provides an adjustable counter dispersion by counter-rotating the two pairs of prisms. The counter-rotating angle depends on the atmospheric dispersion, which is computed with an atmospheric model using both environmental data (temperature, pressure, humidity) and the telescope position. Two different approaches have been compared for the computations to cross-check the results. The electromechanical system has been assembled, tested and debugged prior to the shipping to Chile. This paper describes the atmospheric models used in the VST case and the most recent phases of work.

We will discuss the implementation and calibration of a new GPS based water vapor monitor installed at Cerro Pachon for the Gemini Observatory in Chile. The primary goal of this system is the use of GPS signals to monitor the Precipitable Water Vapor (PWV) in the atmosphere in near-realtime. This is vital in maximizing the efficiency of queue observations in the thermal infrared in which atmospheric transmission and sensitivity is highly dependent on PWV. The GPS WV system was calibrated using near-IR spectroscopy of known water lines based on atmosphere models and imaging the thermal mid-IR background. Observations were conducted using the near-IR imager/spectrometer Phoenix for K, L, and M-band spectroscopy (2.2μm, 3.5μm, 4.5μm) and the mid-infrared imager/spectrometer T-ReCS imaging between 8-20 μm.

Models for material reflectance properties, atmospheric effects and hyperspectral sensor properties in the VNIR/SWIR spectral region can be used to predict the detailed spectral structure of spectra to be measured in future field data collections. It is useful to have databases of predicted spectra that span a wide range of possible atmospheric conditions, given that the ambient environmental conditions for a measurement are rarely known in advance. A radiative transfer (RT) code such as MODTRAN® can be used to model the effects of atmospheric propagation in the predicted spectra as measured by a remotely deployed sensor. We are generating a database of optimized atmospheres that considers variations in solar angle, vertical-path-integrated water vapor density, and aerosol and cloud scatterer types and densities. This database provides a large set of discrete atmospheres. To improve the accuracy of the atmospheric spectral functions for a given hyperspectral image, we have developed an atmospheric perturbation model that is based on a rigorous physics-based approach to the variation of the spectral functions that are contained in the database. We will demonstrate how this new approach to atmospheric modeling improves the accuracy of models for VNIR/SWIR spectra collected with a space-based hyperspectral sensor.

In order to study the effects of atmospheric transmission on remote sensing images, a simulated system on effects of atmospheric absorption and scattering on remote sensing images is proposed in space field. The atmosphere model is build based on MODTRAN. Due to the large effects from neighbor pixels in high resolution images, atmospheric cross radiation is considered in the mode, and a FFT-based computation method for the adjacent effect is proposed, which is practical in digital image process. The simulation experiment results show that the quantization measurement is made for atmospheric influence, and images from the ground to the entrance pupil of satellite camera are rebuilt effectively.

Meso-scale atmospheric models outputs are valuable data for cloud and aerosols retrievals. In view of the launch the Global Change Observation Mission-Climate/Second generation Global Imager (GCOM-C/SGLI) satellite, atmospheric models products are tested against satellite observations data in order to evaluate the degree of reliability and the sensitivity of these models outputs to variations of atmospheric conditions. The analyses presented in this study are based on two models outputs: the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) and the National Center for Environmental Protection/Department Of Energy (NCEP/DOE) re-analysis-2 data. Terra/Moderate Resolution Imaging Spectrometer (Terra/MODIS) satellite sensor observations of water vapor radiances are used as the verification data set for the tests conducted. These tests are based on the comparison between upper tropospheric water vapor properties (clear sky and above-low clouds) observed by satellite and radiative transfer forward calculations (using models' predicted atmospheric profiles, the satellite sensor spectral response and geometrical characteristics) derived from NICAM and NCEP/DOE. The parameters measured are the upper tropospheric brightness temperature (UTBT) and relative humidity (UTRH). Discrepancies between simulated data and observations are analyzed in terms of atmospheric instability, cloud convection movements and, effective emissivity. The results obtained show that both NICAM and NCEP/DOE simulated UTBT and UTRH outputs have a relatively comparable distribution pattern. However, simulations performed with the NCEP/DOE outputs present generally fewer discrepancies with satellite observations. For the interpretation of these results, the stability index study shows that differences between models and observation data tend to be high in unstable atmospheres. This atmospheric instability can be attributed to cloud convection processes affecting areas adjacent to convective clouds. As the amount of convective clouds increases, the errors in the water vapour depiction by the models increase also. Analyses of heat movements studied through the variation of the cloud effective emissivity suggest that the discrepancies between the observations and the models increase with the decrease of the clouds' effective emissivity. Adjustments of some of the models parameters, notably the microphysical parameterization of the clouds resolving scheme, are suggested in order to improve the accuracy of the models' results.

This paper presents the results obtained by collecting systematically the following: - spectro-radiometric measurements of dark and white targets that can be served pseudo-invariant targets using the GER 1500 and SVC HR-1024 field spectroradiometers; sun-photometer measurements using MICROTOPS II sun-photometer for measuring the AOT and water vapour. These field data assists the assessment of the effectiveness of the existing atmospheric correction algorithms either simple or sophisticated such as atmospheric modeling. The in-situ measurements have been already collected on June-August 2008 and from March to July 2009. Six targets are selected to be served as calibration targets in order to assess the effectiveness of the existing atmospheric corrections. For this paper only the following atmospheric correction methods have been tested: darkest pixel atmospheric correction, covariance matrix method, multi-temporal normalization method, 6S model, 'new method using pseudo-invariant targets and empirical line empirical line regression method'. The accuracy assessment has been done based on the reflectance and aerosol optical thickness. Results of the accuracy assessment based on the reflectance retrieval values are presented. The duration of the project is three years started from 2008 up to 2011 and further measurements are still undertaken. The most effective atmospheric correction applied for the three ASTER bands was the 'New method using pseudo-invariant targets and empirical line' (Hadjimitsis et al., 2009) and then the Darkest Pixel correction method (which has been provided a reasonable correction only for bands 1, 2 bands). The future task consists of creating 'a complete database of the spectral signatures of several target's that can be served non-variant and calibration targets.

At present, system design usually assumes the Kolmogorov model of refractive index fluctuation spectra in the atmosphere. However, experimental data indicates that in the atmospheric boundary layer and at higher altitudes the turbulence can be different from Kolmogorov's type. In optical communications, analytical models of mean irradiance and scintillation index have been developed for a traditional Kolmogorov spectrum and must be revised for non-Kolmogorov turbulence. The image quality (resolution, MTF, etc.) is essentially dependent on the properties of turbulent media. Turbulence MTF must be generalized to include non-Kolmogorov statistics. The change in fluctuation correlations of the refractive index can lead to a considerable change in both the MTF form and the resolution value. In this work, on the basis of measurements and model calculations, the influence of non-Kolmogorov turbulence on imaging and communications through the atmosphere is estimated for different scenarios of vertical and slant-path propagation. The atmospheric model of an arbitrary (non-Kolmogorov) spectrum is applied to estimate the statistical quantities associated with optical communication links (e.g., scintillation and fading statistics) and imaging system. Implications can be significant for optical communication, imaging through the atmosphere, and remote sensing.

A Mie-Rayleigh-Raman lidar contains a 200mJ-532nm laser, a 400mm telescope and three detection channels was constructed in this paper. The three detection channels are Mie channel, Rayleigh channel and Raman channel respectively. For the intensity of the aer osol backscattering in boundary layers, analog PMT is used in the Mie channel, from the signal of the analog PMT aerosol extinction can be obtained. The Rayleigh channel detects the Rayleigh backscattering of the atmospheric molecular, while the Raman channel detects the vibrational Raman signal of N 2 , which is 607nm in the system. From the Rayleigh and Raman channels above, air density profile and then the temperature profile from 5Km to 55Km can be inverted. Primary measurement results were also presented in this paper, to verify the accuracy of the temperature, comparison was conducted betw een the lidar measurement and the atmospheric model. The result showed good agreements. Backscattering coefficient of aerosol in the range of 10Km was also presented in the end, which indicated the ability of aerosol monitoring. Keywords: lidar; Mie; Rayleigh; Raman; temperature profile; extinction