WorldWideScience

Sample records for satellite retrieval algorithms

  1. Ozone Profile Retrieval Algorithm (OPERA) for nadir-looking satellite instruments in the UV-VIS

    NARCIS (Netherlands)

    Van Peet, J.C.A.; Van der A, R.J.; Tuinder, O.N.E.; Wolfram, E.; Salvador, J.; Levelt, P.F.; Kelder, H.M.

    2014-01-01

    For the retrieval of the vertical distribution of ozone in the atmosphere the Ozone ProfilE Retrieval Algorithm (OPERA) has been further developed. The new version (1.26) of OPERA is capable of retrieving ozone profiles from UV–VIS observations of most nadir-looking satellite instruments like GOME,

  2. Advances in Satellite Microwave Precipitation Retrieval Algorithms Over Land

    Science.gov (United States)

    Wang, N. Y.; You, Y.; Ferraro, R. R.

    2015-12-01

    Precipitation plays a key role in the earth's climate system, particularly in the aspect of its water and energy balance. Satellite microwave (MW) observations of precipitation provide a viable mean to achieve global measurement of precipitation with sufficient sampling density and accuracy. However, accurate precipitation information over land from satellite MW is a challenging problem. The Goddard Profiling Algorithm (GPROF) algorithm for the Global Precipitation Measurement (GPM) is built around the Bayesian formulation (Evans et al., 1995; Kummerow et al., 1996). GPROF uses the likelihood function and the prior probability distribution function to calculate the expected value of precipitation rate, given the observed brightness temperatures. It is particularly convenient to draw samples from a prior PDF from a predefined database of observations or models. GPROF algorithm does not search all database entries but only the subset thought to correspond to the actual observation. The GPM GPROF V1 database focuses on stratification by surface emissivity class, land surface temperature and total precipitable water. However, there is much uncertainty as to what is the optimal information needed to subset the database for different conditions. To this end, we conduct a database stratification study of using National Mosaic and Multi-Sensor Quantitative Precipitation Estimation, Special Sensor Microwave Imager/Sounder (SSMIS) and Advanced Technology Microwave Sounder (ATMS) and reanalysis data from Modern-Era Retrospective Analysis for Research and Applications (MERRA). Our database study (You et al., 2015) shows that environmental factors such as surface elevation, relative humidity, and storm vertical structure and height, and ice thickness can help in stratifying a single large database to smaller and more homogeneous subsets, in which the surface condition and precipitation vertical profiles are similar. It is found that the probability of detection (POD) increases

  3. Impact of Missing Passive Microwave Sensors on Multi-Satellite Precipitation Retrieval Algorithm

    Directory of Open Access Journals (Sweden)

    Bin Yong

    2015-01-01

    Full Text Available The impact of one or two missing passive microwave (PMW input sensors on the end product of multi-satellite precipitation products is an interesting but obscure issue for both algorithm developers and data users. On 28 January 2013, the Version-7 TRMM Multi-satellite Precipitation Analysis (TMPA products were reproduced and re-released by National Aeronautics and Space Administration (NASA Goddard Space Flight Center because the Advanced Microwave Sounding Unit-B (AMSU-B and the Special Sensor Microwave Imager-Sounder-F16 (SSMIS-F16 input data were unintentionally disregarded in the prior retrieval. Thus, this study investigates the sensitivity of TMPA algorithm results to missing PMW sensors by intercomparing the “early” and “late” Version-7 TMPA real-time (TMPA-RT precipitation estimates (i.e., without and with AMSU-B, SSMIS-F16 sensors with an independent high-density gauge network of 200 tipping-bucket rain gauges over the Chinese Jinghe river basin (45,421 km2. The retrieval counts and retrieval frequency of various PMW and Infrared (IR sensors incorporated into the TMPA system were also analyzed to identify and diagnose the impacts of sensor availability on the TMPA-RT retrieval accuracy. Results show that the incorporation of AMSU-B and SSMIS-F16 has substantially reduced systematic errors. The improvement exhibits rather strong seasonal and topographic dependencies. Our analyses suggest that one or two single PMW sensors might play a key role in affecting the end product of current combined microwave-infrared precipitation estimates. This finding supports algorithm developers’ current endeavor in spatiotemporally incorporating as many PMW sensors as possible in the multi-satellite precipitation retrieval system called Integrated Multi-satellitE Retrievals for Global Precipitation Measurement mission (IMERG. This study also recommends users of satellite precipitation products to switch to the newest Version-7 TMPA datasets and

  4. Fuzzy Classification of Ocean Color Satellite Data for Bio-optical Algorithm Constituent Retrievals

    Science.gov (United States)

    Campbell, Janet W.

    1998-01-01

    The ocean has been traditionally viewed as a 2 class system. Morel and Prieur (1977) classified ocean water according to the dominant absorbent particle suspended in the water column. Case 1 is described as having a high concentration of phytoplankton (and detritus) relative to other particles. Conversely, case 2 is described as having inorganic particles such as suspended sediments in high concentrations. Little work has gone into the problem of mixing bio-optical models for these different water types. An approach is put forth here to blend bio-optical algorithms based on a fuzzy classification scheme. This scheme involves two procedures. First, a clustering procedure identifies classes and builds class statistics from in-situ optical measurements. Next, a classification procedure assigns satellite pixels partial memberships to these classes based on their ocean color reflectance signature. These membership assignments can be used as the basis for a weighting retrievals from class-specific bio-optical algorithms. This technique is demonstrated with in-situ optical measurements and an image from the SeaWiFS ocean color satellite.

  5. Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations

    Science.gov (United States)

    Dubovik, O.; Herman, M.; Holdak, A.; Lapyonok, T.; Tanré, D.; Deuzé, J. L.; Ducos, F.; Sinyuk, A.; Lopatin, A.

    2011-05-01

    The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL micro-satellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation. The algorithm is designed to retrieve complete aerosol properties globally. Over land, the algorithm retrieves the parameters of underlying surface simultaneously with aerosol. In all situations, the approach is anticipated to achieve a robust retrieval of complete aerosol properties including information about aerosol particle sizes, shape, absorption and composition (refractive index). In order to achieve reliable retrieval from PARASOL observations even over very reflective

  6. Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations

    Directory of Open Access Journals (Sweden)

    O. Dubovik

    2011-05-01

    Full Text Available The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns that is not common in satellite observations. The POLDER imager on board the PARASOL micro-satellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation.

    The algorithm is designed to retrieve complete aerosol properties globally. Over land, the algorithm retrieves the parameters of underlying surface simultaneously with aerosol. In all situations, the approach is anticipated to achieve a robust retrieval of complete aerosol properties including information about aerosol particle sizes, shape, absorption and composition (refractive index. In order to achieve reliable retrieval from PARASOL observations

  7. Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations

    Directory of Open Access Journals (Sweden)

    O. Dubovik

    2010-11-01

    Full Text Available The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns that is not common in satellite observations. The POLDER imager on board of the PARASOL micro-satellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of the all available angular observations of total and polarized radiances obtained by POLDER sensor in the window spectral channels where absorption by gaseous is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed on retrieval of extended set of parameters affecting measured radiation.

    The algorithm is designed to retrieve complete aerosol properties globally. Over land, the algorithm retrieves the parameters of underlying surface simultaneously with aerosol. In all situations, the approach is anticipated to achieve a robust retrieval of complete aerosol properties including information about aerosol particle sizes, shape, absorption and composition (refractive index. In order to achieve

  8. Low-cost Citizen Science Balloon Platform for Measuring Air Pollutants to Improve Satellite Retrieval Algorithms

    Science.gov (United States)

    Potosnak, M. J.; Beck-Winchatz, B.; Ritter, P.

    2016-12-01

    High-altitude balloons (HABs) are an engaging platform for citizen science and formal and informal STEM education. However, the logistics of launching, chasing and recovering a payload on a 1200 g or 1500 g balloon can be daunting for many novice school groups and citizen scientists, and the cost can be prohibitive. In addition, there are many interesting scientific applications that do not require reaching the stratosphere, including measuring atmospheric pollutants in the planetary boundary layer. With a large number of citizen scientist flights, these data can be used to constrain satellite retrieval algorithms. In this poster presentation, we discuss a novel approach based on small (30 g) balloons that are cheap and easy to handle, and low-cost tracking devices (SPOT trackers for hikers) that do not require a radio license. Our scientific goal is to measure air quality in the lower troposphere. For example, particulate matter (PM) is an air pollutant that varies on small spatial scales and has sources in rural areas like biomass burning and farming practices such as tilling. Our HAB platform test flight incorporates an optical PM sensor, an integrated single board computer that records the PM sensor signal in addition to flight parameters (pressure, location and altitude), and a low-cost tracking system. Our goal is for the entire platform to cost less than $500. While the datasets generated by these flights are typically small, integrating a network of flight data from citizen scientists into a form usable for comparison to satellite data will require big data techniques.

  9. A New Algorithm for the Satellite-Based Retrieval of Solar Surface Irradiance in Spectral Bands

    Directory of Open Access Journals (Sweden)

    Annette Hammer

    2012-03-01

    Full Text Available Accurate solar surface irradiance data is a prerequisite for an efficient planning and operation of solar energy systems. Further, it is essential for climate monitoring and analysis. Recently, the demand on information about spectrally resolved solar surface irradiance has grown. As surface measurements are rare, satellite derived information with high accuracy might fill this gap. This paper describes a new approach for the retrieval of spectrally resolved solar surface irradiance from satellite data. The method combines a eigenvector-hybrid look-up table approach for the clear sky case with satellite derived cloud transmission (Heliosat method. The eigenvector LUT approach is already used to retrieve the broadband solar surface irradiance of data sets provided by the Climate Monitoring Satellite Application Facility (CM-SAF. This paper describes the extension of this approach to wavelength bands and the combination with spectrally resolved cloud transmission values derived with radiative transfer corrections of the broadband cloud transmission. Thus, the new approach is based on radiative transfer modeling and enables the use of extended information about the atmospheric state, among others, to resolve the effect of water vapor and ozone absorption bands. The method is validated with spectrally resolved measurements from two sites in Europe and by comparison with radiative transfer calculations. The validation results demonstrate the ability of the method to retrieve accurate spectrally resolved irradiance from satellites. The accuracy is in the range of the uncertainty of surface measurements, with exception of the UV and NIR ( ≥ 1200 nm part of the spectrum, where higher deviations occur.

  10. Ozone ProfilE Retrieval Algorithm for nadir-looking satellite instruments in the UV-VIS

    Directory of Open Access Journals (Sweden)

    J. C. A. van Peet

    2013-10-01

    Full Text Available For the retrieval of the vertical distribution of ozone in the atmosphere the Ozone ProfilE Retrieval Algorithm (OPERA has been further developed. The new version (1.26 of OPERA is capable of retrieving ozone profiles from UV-VIS observations of most nadir looking satellite instruments like GOME, SCIAMACHY, OMI and GOME-2. The set-up of OPERA is described and results are presented for GOME and GOME-2 observations. The retrieved ozone profiles are globally compared to ozone sondes for the year 1997 and 2008. Relative differences between GOME/GOME-2 and ozone sondes are within the limits as specified by the user requirements from the Climate Change Initiative (CCI program of ESA. To demonstrate the performance of the algorithm under extreme circumstances the 2009 Antarctic ozone hole season was investigated in more detail using GOME-2 ozone profiles and lidar data, which showed an unusual persistence of the vortex over the Río Gallegos observing station (51° S, 69.3° W. By applying OPERA to multiple instruments a timeseries of ozone profiles from 1996 to 2013 from a single robust algorithm can be created.

  11. Novel Algorithms for Retrieval of Hydrology and Ice Regimes of Middle-sized Inland Water Bodies from Satellite Altimetry

    Science.gov (United States)

    Troitskaya, Y. I.; Rybushkina, G. V.; Kuznetsova, A. M.; Baidakov, G. A.; Soustova, I.

    2014-12-01

    A novel method of regional adaptive re-tracking based on constructing a theoretical model describing the formation of telemetric waveforms by reflection from the piecewise constant model surface corresponding to the geography of the region is considered. The algorithm includes four consecutive steps: a) constructing a local piecewise model of a reflecting surface in the neighbourhood of the reservoir; b) solving a direct problem by calculating the reflected waveforms within the framework of the model; c) imposing restrictions and validity criteria for the algorithm based on waveform modelling; d) solving the inverse problem by retrieving a tracking point by the improved threshold algorithm. The results obtained on the basis of standard algorithm and method for adaptive re-tracking at Rybinsk , Gorky, Kuibyshev, Saratov and Volgograd reservoirs and middle-sized lakes of Russia: Chany, Segozero, Hanko, Onego, Beloye are compared to each other and to the field data of hydrological stations in reservoirs and lakes. The possibility of determination of significant wave height (SWH) in the lakes through a two-step adaptive retracking is investigated. Comparing results of retracting of SGDR data and ground measurements shows, that retrieving wave parameters in medium sized water bodies still meets difficulties. The direction of improvement of the existing algorithm is associated with comprehensive use of altimetry data, field studies and numerical modeling of high resolution. A simple method for timing of water freezing and ice break-up in lakes based on analysis of along-track dependencies of brightness temperatures at 18.7 and 34 GHz registered by microwave radiometer of altimetry satellite Jason-2. Comparison with in situ data of Russian Register of hydraulic structures on the example of reservoirs of the Volga River and the Don River confirms ability of the proposed method to determine quantitatively the freezing and break-up times for middle-sized inland water bodies.

  12. The GRAPE aerosol retrieval algorithm

    Directory of Open Access Journals (Sweden)

    G. E. Thomas

    2009-11-01

    Full Text Available The aerosol component of the Oxford-Rutherford Aerosol and Cloud (ORAC combined cloud and aerosol retrieval scheme is described and the theoretical performance of the algorithm is analysed. ORAC is an optimal estimation retrieval scheme for deriving cloud and aerosol properties from measurements made by imaging satellite radiometers and, when applied to cloud free radiances, provides estimates of aerosol optical depth at a wavelength of 550 nm, aerosol effective radius and surface reflectance at 550 nm. The aerosol retrieval component of ORAC has several incarnations – this paper addresses the version which operates in conjunction with the cloud retrieval component of ORAC (described by Watts et al., 1998, as applied in producing the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE data-set.

    The algorithm is described in detail and its performance examined. This includes a discussion of errors resulting from the formulation of the forward model, sensitivity of the retrieval to the measurements and a priori constraints, and errors resulting from assumptions made about the atmospheric/surface state.

  13. Retrieval algorithm for densities of mesospheric and lower thermospheric metal and ion species from satellite borne limb emission signals

    Science.gov (United States)

    Langowski, M.; Sinnhuber, M.; Aikin, A. C.; von Savigny, C.; Burrows, J. P.

    2013-05-01

    Meteoroids bombard the earth's atmosphere during its orbit around the sun, depositing a highly varying and significant amount of matter into the thermosphere and mesosphere. The strength of the material source needs to be characterized and its impact on atmospheric chemistry assessed. In this study an algorithm for the retrieval of metal and metal ion number densities for a two-dimensional (latitude, altitude) grid is described and explained. Dayglow emission spectra of the mesosphere and lower thermosphere are used, which are obtained by passive satellite remote sensing with the SCIAMACHY instrument on Envisat. The limb scans cover the tangent altitude range from 50 to 150 km. Metals and metal ions are strong emitters in this region and form sharply peaked layers with a FWHM of several 10 km in the mesosphere and lower thermosphere with peak altitudes between 90 to 110 km. The emission signal is first separated from the background signal, arising from Rayleigh and Raman scattering of solar radiation by air molecules. A forward radiative transfer model calculating the slant column density (SCD) from a given vertical distribution was developed. This non-linear model is inverted in an iterative procedure to yield the vertical profiles for the emitting species. Several constraints are applied to the solution, for numerical stability reasons and to get physically reasonable solutions. The algorithm is applied to SCIAMACHY limb-emission observations for the retrieval of Mg and Mg+ using emission signatures at 285.2 and 279.6/280.4 nm, respectively. Results are presented for these three lines as well as error estimations and sensitivity tests on different constraint strength and different separation approaches for the background signal.

  14. Retrieval algorithm for CO2 and CH4 column abundances from short-wavelength infrared spectral observations by the Greenhouse Gases Observing Satellite

    Directory of Open Access Journals (Sweden)

    I. Morino

    2010-11-01

    Full Text Available The Greenhouse gases Observing SATellite (GOSAT was launched on 23 January 2009 to monitor the global distributions of carbon dioxide and methane from space. It has operated continuously since then. Here we describe a retrieval algorithm for column abundances of these gases from the short-wavelength infrared spectra obtained by the Thermal And Near infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS. The algorithm consists of three steps. First, cloud-free observational scenes are selected by several cloud-detection methods. Then, column abundances of carbon dioxide and methane are retrieved based on the optimal estimation method. Finally, the retrieval quality is examined to exclude low-quality and/or aerosol-contaminated results. Most of the retrieval random errors come from the instrumental noise. The interferences by auxiliary parameters retrieved simultaneously with gas abundances are small. The evaluated precisions of the retrieved column abundances for single observations are less than 1% in most cases. The interhemispherical differences and the temporal variation patterns of the retrieved column abundances agree well with the current state of knowledge.

  15. Retrieval algorithm for CO2 and CH4 column abundances from short-wavelength infrared spectral observations by the Greenhouse gases observing satellite

    Directory of Open Access Journals (Sweden)

    I. Morino

    2011-04-01

    Full Text Available The Greenhouse gases Observing SATellite (GOSAT was launched on 23 January 2009 to monitor the global distributions of carbon dioxide and methane from space. It has operated continuously since then. Here, we describe a retrieval algorithm for column abundances of these gases from the short-wavelength infrared spectra obtained by the Thermal And Near infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS. The algorithm consists of three steps. First, cloud-free observational scenes are selected by several cloud-detection methods. Then, column abundances of carbon dioxide and methane are retrieved based on the optimal estimation method. Finally, the retrieval quality is examined to exclude low-quality and/or aerosol-contaminated results. Most of the retrieval random errors come from instrumental noise. The interferences due to auxiliary parameters retrieved simultaneously with gas abundances are small. The evaluated precisions of the retrieved column abundances for single observations are less than 1% in most cases. The interhemispherical differences and temporal variation patterns of the retrieved column abundances show features similar to those of an atmospheric transport model.

  16. Long-term analysis of aerosol optical depth over Northeast Asia using a satellite-based measurement: MI Yonsei Aerosol Retrieval Algorithm (YAER)

    Science.gov (United States)

    Kim, Mijin; Kim, Jhoon; Yoon, Jongmin; Chung, Chu-Yong; Chung, Sung-Rae

    2017-04-01

    In 2010, the Korean geostationary earth orbit (GEO) satellite, the Communication, Ocean, and Meteorological Satellite (COMS), was launched including the Meteorological Imager (MI). The MI measures atmospheric condition over Northeast Asia (NEA) using a single visible channel centered at 0.675 μm and four IR channels at 3.75, 6.75, 10.8, 12.0 μm. The visible measurement can also be utilized for the retrieval of aerosol optical properties (AOPs). Since the GEO satellite measurement has an advantage for continuous monitoring of AOPs, we can analyze the spatiotemporal variation of the aerosol using the MI observations over NEA. Therefore, we developed an algorithm to retrieve aerosol optical depth (AOD) using the visible observation of MI, and named as MI Yonsei Aerosol Retrieval Algorithm (YAER). In this study, we investigated the accuracy of MI YAER AOD by comparing the values with the long-term products of AERONET sun-photometer. The result showed that the MI AODs were significantly overestimated than the AERONET values over bright surface in low AOD case. Because the MI visible channel centered at red color range, contribution of aerosol signal to the measured reflectance is relatively lower than the surface contribution. Therefore, the AOD error in low AOD case over bright surface can be a fundamental limitation of the algorithm. Meanwhile, an assumption of background aerosol optical depth (BAOD) could result in the retrieval uncertainty, also. To estimate the surface reflectance by considering polluted air condition over the NEA, we estimated the BAOD from the MODIS dark target (DT) aerosol products by pixel. The satellite-based AOD retrieval, however, largely depends on the accuracy of the surface reflectance estimation especially in low AOD case, and thus, the BAOD could include the uncertainty in surface reflectance estimation of the satellite-based retrieval. Therefore, we re-estimated the BAOD using the ground-based sun-photometer measurement, and

  17. The inter-comparison of major satellite aerosol retrieval algorithms using simulated intensity and polarization characteristics of reflected light

    Directory of Open Access Journals (Sweden)

    A. A. Kokhanovsky

    2010-07-01

    Full Text Available Remote sensing of aerosol from space is a challenging and typically underdetermined retrieval task, requiring many assumptions to be made with respect to the aerosol and surface models. Therefore, the quality of a priori information plays a central role in any retrieval process (apart from the cloud screening procedure and the forward radiative transfer model, which to be most accurate should include the treatment of light polarization and molecular-aerosol coupling. In this paper the performance of various algorithms with respect to the of spectral aerosol optical thickness determination from optical spaceborne measurements is studied. The algorithms are based on various types of measurements (spectral, angular, polarization, or some combination of these. It is confirmed that multiangular spectropolarimetric measurements provide more powerful constraints compared to spectral intensity measurements alone, particularly those acquired at a single view angle and which rely on a priori assumptions regarding the particle phase function in the retrieval process.

  18. Sensitivity of Satellite-Based Skin Temperature to Different Surface Emissivity and NWP Reanalysis Sources Demonstrated Using a Single-Channel, Viewing-Angle-Corrected Retrieval Algorithm

    Science.gov (United States)

    Scarino, B. R.; Minnis, P.; Yost, C. R.; Chee, T.; Palikonda, R.

    2015-12-01

    Single-channel algorithms for satellite thermal-infrared- (TIR-) derived land and sea surface skin temperature (LST and SST) are advantageous in that they can be easily applied to a variety of satellite sensors. They can also accommodate decade-spanning instrument series, particularly for periods when split-window capabilities are not available. However, the benefit of one unified retrieval methodology for all sensors comes at the cost of critical sensitivity to surface emissivity (ɛs) and atmospheric transmittance estimation. It has been demonstrated that as little as 0.01 variance in ɛs can amount to more than a 0.5-K adjustment in retrieved LST values. Atmospheric transmittance requires calculations that employ vertical profiles of temperature and humidity from numerical weather prediction (NWP) models. Selection of a given NWP model can significantly affect LST and SST agreement relative to their respective validation sources. Thus, it is necessary to understand the accuracies of the retrievals for various NWP models to ensure the best LST/SST retrievals. The sensitivities of the single-channel retrievals to surface emittance and NWP profiles are investigated using NASA Langley historic land and ocean clear-sky skin temperature (Ts) values derived from high-resolution 11-μm TIR brightness temperature measured from geostationary satellites (GEOSat) and Advanced Very High Resolution Radiometers (AVHRR). It is shown that mean GEOSat-derived, anisotropy-corrected LST can vary by up to ±0.8 K depending on whether CERES or MODIS ɛs sources are used. Furthermore, the use of either NOAA Global Forecast System (GFS) or NASA Goddard Modern-Era Retrospective Analysis for Research and Applications (MERRA) for the radiative transfer model initial atmospheric state can account for more than 0.5-K variation in mean Ts. The results are compared to measurements from the Surface Radiation Budget Network (SURFRAD), an Atmospheric Radiation Measurement (ARM) Program ground

  19. Adaptive re-tracking algorithm for retrieval of water level variations and wave heights from satellite altimetry data for middle-sized inland water bodies

    Science.gov (United States)

    Troitskaya, Yuliya; Lebedev, Sergey; Soustova, Irina; Rybushkina, Galina; Papko, Vladislav; Baidakov, Georgy; Panyutin, Andrey

    One of the recent applications of satellite altimetry originally designed for measurements of the sea level [1] is associated with remote investigation of the water level of inland waters: lakes, rivers, reservoirs [2-7]. The altimetry data re-tracking algorithms developed for open ocean conditions (e.g. Ocean-1,2) [1] often cannot be used in these cases, since the radar return is significantly contaminated by reflection from the land. The problem of minimization of errors in the water level retrieval for inland waters from altimetry measurements can be resolved by re-tracking satellite altimetry data. Recently, special re-tracking algorithms have been actively developed for re-processing altimetry data in the coastal zone when reflection from land strongly affects echo shapes: threshold re-tracking, The other methods of re-tracking (threshold re-tracking, beta-re-tracking, improved threshold re-tracking) were developed in [9-11]. The latest development in this field is PISTACH product [12], in which retracking bases on the classification of typical forms of telemetric waveforms in the coastal zones and inland water bodies. In this paper a novel method of regional adaptive re-tracking based on constructing a theoretical model describing the formation of telemetric waveforms by reflection from the piecewise constant model surface corresponding to the geography of the region is considered. It was proposed in [13, 14], where the algorithm for assessing water level in inland water bodies and in the coastal zone of the ocean with an error of about 10-15 cm was constructed. The algorithm includes four consecutive steps: - constructing a local piecewise model of a reflecting surface in the neighbourhood of the reservoir; - solving a direct problem by calculating the reflected waveforms within the framework of the model; - imposing restrictions and validity criteria for the algorithm based on waveform modelling; - solving the inverse problem by retrieving a tracking point

  20. Retrieval algorithm for densities of mesospheric and lower thermospheric metal atom and ion species from satellite-borne limb emission signals

    Science.gov (United States)

    Langowski, M.; Sinnhuber, M.; Aikin, A. C.; von Savigny, C.; Burrows, J. P.

    2014-01-01

    Meteoroids bombard Earth's atmosphere during its orbit around the Sun, depositing a highly varying and significant amount of matter into the thermosphere and mesosphere. The strength of the material source needs to be characterized and its impact on atmospheric chemistry assessed. In this study an algorithm for the retrieval of metal atom and ion number densities for a two-dimensional (latitude, altitude) grid is described and explained. Dayglow emission spectra of the mesosphere and lower thermosphere are used, which are obtained by passive satellite remote sensing with the SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) instrument on board Envisat. The limb scans cover the tangent altitude range from 50 to 150 km. Metal atoms and ions are strong emitters in this region and form sharply peaked layers with a FWHM (full width at half maximum) of several 10 km in the mesosphere and lower thermosphere measuring peak altitudes between 90 to 110 km. The emission signal is first separated from the background signal, arising from Rayleigh and Raman scattering of solar radiation by air molecules. A forward radiative transfer model calculating the slant column density (SCD) from a given vertical distribution was developed. This nonlinear model is inverted in an iterative procedure to yield the vertical profiles for the emitting species. Several constraints are applied to the solution for numerical stability reasons and to get physically reasonable solutions. The algorithm is applied to SCIAMACHY limb-emission observations for the retrieval of Mg and Mg+ using emission signatures at 285.2 and 279.6/280.4 nm, respectively. Results are presented for these three lines as well as error estimations and sensitivity tests on different constraint strength and different separation approaches for the background signal.

  1. A Fast and Sensitive New Satellite SO2 Retrieval Algorithm based on Principal Component Analysis: Application to the Ozone Monitoring Instrument

    Science.gov (United States)

    Li, Can; Joiner, Joanna; Krotkov, A.; Bhartia, Pawan K.

    2013-01-01

    We describe a new algorithm to retrieve SO2 from satellite-measured hyperspectral radiances. We employ the principal component analysis technique in regions with no significant SO2 to capture radiance variability caused by both physical processes (e.g., Rayleigh and Raman scattering and ozone absorption) and measurement artifacts. We use the resulting principal components and SO2 Jacobians calculated with a radiative transfer model to directly estimate SO2 vertical column density in one step. Application to the Ozone Monitoring Instrument (OMI) radiance spectra in 310.5-340 nm demonstrates that this approach can greatly reduce biases in the operational OMI product and decrease the noise by a factor of 2, providing greater sensitivity to anthropogenic emissions. The new algorithm is fast, eliminates the need for instrument-specific radiance correction schemes, and can be easily adapted to other sensors. These attributes make it a promising technique for producing longterm, consistent SO2 records for air quality and climate research.

  2. Two-Channel Satellite Retrievals of Aerosol Properties: An Overview

    Science.gov (United States)

    Mishchenko, Michael I.

    1999-01-01

    In order to reduce current uncertainties in the evaluation of the direct and indirect effects of tropospheric aerosols on climate on the global scale, it has been suggested to apply multi-channel retrieval algorithms to the full period of existing satellite data. This talk will outline the methodology of interpreting two-channel satellite radiance data over the ocean and describe a detailed analysis of the sensitivity of retrieved aerosol parameters to the assumptions made in different retrieval algorithms. We will specifically address the calibration and cloud screening issues, consider the suitability of existing satellite data sets to detecting short- and long-term regional and global changes, compare preliminary results obtained by several research groups, and discuss the prospects of creating an advanced retroactive climatology of aerosol optical thickness and size over the oceans.

  3. The Aquarius Salinity Retrieval Algorithm

    Science.gov (United States)

    Meissner, Thomas; Wentz, Frank; Hilburn, Kyle; Lagerloef, Gary; Le Vine, David

    2012-01-01

    The first part of this presentation gives an overview over the Aquarius salinity retrieval algorithm. The instrument calibration [2] converts Aquarius radiometer counts into antenna temperatures (TA). The salinity retrieval algorithm converts those TA into brightness temperatures (TB) at a flat ocean surface. As a first step, contributions arising from the intrusion of solar, lunar and galactic radiation are subtracted. The antenna pattern correction (APC) removes the effects of cross-polarization contamination and spillover. The Aquarius radiometer measures the 3rd Stokes parameter in addition to vertical (v) and horizontal (h) polarizations, which allows for an easy removal of ionospheric Faraday rotation. The atmospheric absorption at L-band is almost entirely due to molecular oxygen, which can be calculated based on auxiliary input fields from numerical weather prediction models and then successively removed from the TB. The final step in the TA to TB conversion is the correction for the roughness of the sea surface due to wind, which is addressed in more detail in section 3. The TB of the flat ocean surface can now be matched to a salinity value using a surface emission model that is based on a model for the dielectric constant of sea water [3], [4] and an auxiliary field for the sea surface temperature. In the current processing only v-pol TB are used for this last step.

  4. A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery

    Directory of Open Access Journals (Sweden)

    Byongjun Hwang

    2017-07-01

    Full Text Available In this study, we present an algorithm for summer sea ice conditions that semi-automatically produces the floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar data. Currently, floe size distribution data from satellite images are very rare in the literature, mainly due to the lack of a reliable algorithm to produce such data. Here, we developed the algorithm by combining various image analysis methods, including Kernel Graph Cuts, distance transformation and watershed transformation, and a rule-based boundary revalidation. The developed algorithm has been validated against the ground truth that was extracted manually with the aid of 1-m resolution visible satellite data. Comprehensive validation analysis has shown both perspectives and limitations. The algorithm tends to fail to detect small floes (mostly less than 100 m in mean caliper diameter compared to ground truth, which is mainly due to limitations in water-ice segmentation. Some variability in the power law exponent of floe size distribution is observed due to the effects of control parameters in the process of de-noising, Kernel Graph Cuts segmentation, thresholds for boundary revalidation and image resolution. Nonetheless, the algorithm, for floes larger than 100 m, has shown a reasonable agreement with ground truth under various selections of these control parameters. Considering that the coverage and spatial resolution of satellite Synthetic Aperture Radar data have increased significantly in recent years, the developed algorithm opens a new possibility to produce large volumes of floe size distribution data, which is essential for improving our understanding and prediction of the Arctic sea ice cover

  5. The potential of clear-sky carbon dioxide satellite retrievals

    Directory of Open Access Journals (Sweden)

    R. R. Nelson

    2015-12-01

    Full Text Available Since the launch of the Greenhouse Gases Observing Satellite (GOSAT in 2009, retrieval algorithms designed to infer the column-averaged dry-air mole fraction of carbon dioxide (XCO2 from hyperspectral near-infrared observations of reflected sunlight have been greatly improved. They now generally include the scattering effects of clouds and aerosols, as early work found that absorption-only retrievals, which neglected these effects, often incurred unacceptably large errors, even for scenes with optically thin cloud or aerosol layers. However, these "full-physics" retrievals tend to be computationally expensive and may incur biases from trying to deduce the properties of clouds and aerosols when there are none present. Additionally, algorithms are now available that can quickly and effectively identify and remove most scenes in which cloud or aerosol scattering plays a significant role. In this work, we test the hypothesis that non-scattering, or "clear-sky", retrievals may perform as well as full-physics retrievals for sufficiently clear scenes. Clear-sky retrievals could potentially avoid errors and biases brought about by trying to infer properties of clouds and aerosols when none are present. Clear-sky retrievals are also desirable because they are orders of magnitude faster than full-physics retrievals. Here we use a simplified version of the Atmospheric Carbon Observations from Space (ACOS XCO2 retrieval algorithm that does not include the scattering and absorption effects of clouds or aerosols. It was found that for simulated Orbiting Carbon Observatory-2 (OCO-2 measurements, the clear-sky retrieval had errors comparable to those of the full-physics retrieval. For real GOSAT data, the clear-sky retrieval had nearly indistinguishable error characteristics over land, but roughly 30–60 % larger errors over ocean, depending on filtration level, compared to the full-physics retrieval. In general, the clear-sky retrieval had XCO2 root

  6. Retrieval of Aerosol Properties from Satellite Data

    NARCIS (Netherlands)

    Kusmierczyk-Michulec, J.; Roblez Gonzalez, C.; Decae, R.; Leeuw, G. de

    2003-01-01

    Algorithms for the retrieval of aerosol properties over land and over sea have been developed by the TNO Physics and Electronics Laboratory (TNO-FEL) for several instruments, such as AVHRR (Veefkind et al., 1998a), GOME, ATSR-2 (Veelkind et al. 1998a, b; 1999) and OMI (Torres et al. 2002). OMI will

  7. The Aquarius Salinity Retrieval Algorithm: Early Results

    Science.gov (United States)

    Meissner, Thomas; Wentz, Frank J.; Lagerloef, Gary; LeVine, David

    2012-01-01

    (cal/val) activity needs to be completed. This is necessary in order to tune the inputs to the algorithm and remove biases that arise due to the instrument calibration, foremost the values of the noise diode injection temperatures and the losses that occur in the feedhorns. This is the subject of the second part of our presentation. The basic tool is to analyze the observed difference between the Aquarius measured TA and an expected TA that is computed from a reference salinity field. It is also necessary to derive a relation between the scatterometer backscatter measurements and the radiometer emissivity that is induced by surface winds. In order to do this we collocate Aquarius radiometer and scatterometer measurements with wind speed retrievals from the WindSat and SSMIS F17 microwave radiometers. Both of these satellites fly in orbits that have the same equatorial ascending crossing time (6 pm) as the Aquarius/SAC-D observatory. Rain retrievals from WindSat and SSMIS F 17 can be used to remove Aquarius observations that are rain contaminated. A byproduct of this analysis is a prediction for the wind-induced sea surface emissivity at L-band.

  8. Retrieval of aerosol optical depth for Chongqing using the HJ-1 satellite data

    Science.gov (United States)

    Wang, Zengwu; Yang, Shiqi; Zeng, Qiaolin; Wang, Yongqian

    2017-06-01

    Aerosol optical depth (AOD) is a common indicator applied in monitoring aerosols in the atmosphere. The hilly landscape and rapid economic growth of the megacity Chongqing have facilitated increased aerosol concentration, and it is meaningful to accurately retrieve AOD over Chongqing. The HJ-1A/B satellite of China carries a sensor/camera called the Charge Coupled Device (CCD), the spatial resolution of which meets the requirement for retrieving high resolution AOD. In this paper, analysis of the AOD retrievals from different methods using the HJ-1 satellite data revealed the most suitable algorithm. Through comparison with the AOD product of Moderate Resolution Imaging Spectroradiometer (MODIS), the AOD retrieval results using enhanced vegetation index (EVI) to estimate dark pixels showed the highest correlation. The continental aerosol model was used to build a lookup table that was able to facilitate a good AOD retrieval for both city and rural areas. Finally, the algorithm that combined dark pixels, buffer areas, and the deep blue algorithm was found to be most suitable for AOD retrieval. The AOD retrieval results based on the HJ-1 data were consistent with MODIS products, and our algorithm yields reasonable results in most cases. The results were also compared with ground-based PM10 measurements synchronized with the overpass time of the HJ-1 satellite, and high correlation was found. The findings are relevant to other Chinese satellite data used for retrieving AOD on the same channels.

  9. Information content of ozone retrieval algorithms

    Science.gov (United States)

    Rodgers, C.; Bhartia, P. K.; Chu, W. P.; Curran, R.; Deluisi, J.; Gille, J. C.; Hudson, R.; Mateer, C.; Rusch, D.; Thomas, R. J.

    1989-01-01

    The algorithms are characterized that were used for production processing by the major suppliers of ozone data to show quantitatively: how the retrieved profile is related to the actual profile (This characterizes the altitude range and vertical resolution of the data); the nature of systematic errors in the retrieved profiles, including their vertical structure and relation to uncertain instrumental parameters; how trends in the real ozone are reflected in trends in the retrieved ozone profile; and how trends in other quantities (both instrumental and atmospheric) might appear as trends in the ozone profile. No serious deficiencies were found in the algorithms used in generating the major available ozone data sets. As the measurements are all indirect in someway, and the retrieved profiles have different characteristics, data from different instruments are not directly comparable.

  10. Developing the Integrated Multi-Satellite Retrievals for GPM (IMERG)

    Science.gov (United States)

    Huffman, G. J.; Bolvin, D. T.; Braithwaite, D.; Hsu, K.; Joyce, R.; Kidd, C.; Sorooshian, S.; Xie, P.; Yoo, S.-H.

    2012-04-01

    The Integrated Multi-satellitE Retrievals for GPM (IMERG) will provide the Day-1 algorithm for computing combined precipitation estimates as part of GPM. The focus is assembling the best time series of (nearly) global precipitation from the international constellation of precipitation-relevant satellites and global surface precipitation gauge analyses. It is planned that the time series will encompass both the TRMM and GPM eras, and that the coverage will be extended to fully global as algorithms are developed that provide skill in the difficult high-latitude environment. IMERG is being developed as a unified U.S. algorithm that takes advantage of strengths in the three groups that are contributing expertise: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA), which addresses inter-satellite calibration of precipitation estimates and monthly scale combination of satellite and gauge analyses; 2) the CPC Morphing algorithm with Kalman Filtering (K-CMORPH), which provides quality-weighted time interpolation of precipitation patterns following storm motion; and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS), which provides a neural-network-based scheme for generating microwave-calibrated precipitation estimates from geosynchronous infrared brightness temperatures. In this talk we summarize the code-level integration on which IMERG is based, including the important issues that drive the design and implementation, plans for testing and starting to run the system, and current status. One concept being pioneered by the IMERG team is that combination datasets should be computed multiple times at different latencies to serve the needs of different groups of users. Although reprocessing all of the latency "runs" complicates the reprocessing scenario, experience demonstrates that it is essential for the users. Fortunately, the IMERG team has worked with the

  11. Accounting for the effects of surface BRDF on satellite cloud and trace-gas retrievals: a new approach based on geometry-dependent Lambertian equivalent reflectivity applied to OMI algorithms

    Science.gov (United States)

    Vasilkov, Alexander; Qin, Wenhan; Krotkov, Nickolay; Lamsal, Lok; Spurr, Robert; Haffner, David; Joiner, Joanna; Yang, Eun-Su; Marchenko, Sergey

    2017-01-01

    Most satellite nadir ultraviolet and visible cloud, aerosol, and trace-gas algorithms make use of climatological surface reflectivity databases. For example, cloud and NO2 retrievals for the Ozone Monitoring Instrument (OMI) use monthly gridded surface reflectivity climatologies that do not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun-sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (LER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. The geometry-dependent LER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from the Moderate Resolution Imaging Spectroradiometer (MODIS) over land and the Cox-Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare the geometry-dependent and climatological LERs for two wavelengths, 354 and 466 nm, that are used in OMI cloud algorithms to derive cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and geometry-dependent LERs is carried out. Geometry-dependent LER and corresponding retrieved cloud products are then used as inputs to our OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with geometry-dependent LERs can increase NO2 vertical columns by up to 50 % in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.

  12. Accounting for the Effects of Surface BRDF on Satellite Cloud and Trace-Gas Retrievals: A New Approach Based on Geometry-Dependent Lambertian-Equivalent Reflectivity Applied to OMI Algorithms

    Science.gov (United States)

    Vasilkov, Alexander; Qin, Wenhan; Krotkov, Nickolay; Lamsal, Lok; Spurr, Robert; Haffner, David; Joiner, Joanna; Yang, Eun-Su; Marchenko, Sergey

    2017-01-01

    Most satellite nadir ultraviolet and visible cloud, aerosol, and trace-gas algorithms make use of climatological surface reflectivity databases. For example, cloud and NO2 retrievals for the Ozone Monitoring Instrument (OMI) use monthly gridded surface reflectivity climatologies that do not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun-sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (LER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. The geometry-dependent LER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from the Moderate Resolution Imaging Spectroradiometer (MODIS) over land and the Cox-Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare the geometry-dependent and climatological LERs for two wavelengths, 354 and 466 nm, that are used in OMI cloud algorithms to derive cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and geometry-dependent LERs is carried out. Geometry-dependent LER and corresponding retrieved cloud products are then used as inputs to our OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with geometry-dependent LERs can increase NO2 vertical columns by up to 50% in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.

  13. Accounting for the Effects of Surface BRDF on Satellite Cloud and Trace-Gas Retrievals: A New Approach Based on Geometry-Dependent Lambertian-Equivalent Reflectivity Applied to OMI Algorithms

    Science.gov (United States)

    Vasilkov, Alexander; Qin, Wenhan; Krotkov, Nickolay; Lamsal, Lok; Spurr, Robert; Haffner, David; Joiner, Joanna; Yang, Eun-Su; Marchenko, Sergey

    2017-01-01

    Most satellite nadir ultraviolet and visible cloud, aerosol, and trace-gas algorithms make use of climatological surface reflectivity databases. For example, cloud and NO2 retrievals for the Ozone Monitoring Instrument (OMI) use monthly gridded surface reflectivity climatologies that do not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun-sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (LER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. The geometry-dependent LER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from the Moderate Resolution Imaging Spectroradiometer (MODIS) over land and the Cox-Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare the geometry-dependent and climatological LERs for two wavelengths, 354 and 466 nm, that are used in OMI cloud algorithms to derive cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and geometry-dependent LERs is carried out. Geometry-dependent LER and corresponding retrieved cloud products are then used as inputs to our OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with geometry-dependent LERs can increase NO2 vertical columns by up to 50% in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.

  14. Using ARM Data to Evaluate Satellite Surface Solar Flux Retrievals

    Energy Technology Data Exchange (ETDEWEB)

    Hinkelman, L.M.; Stackhouse, P.W.; Young, D.F.; Long, C.N.; Rutan, D.

    2005-03-18

    The accurate, long-term radiometric data collected by Atmospheric Radiation Measurement (ARM) has become essential to the evaluation of surface radiation budget data from satellites. Since the spatial and temporal characteristics of data from these two sources are very different, the comparisons are typically made for long-term average values. While such studies provide a general indication of the quality of satellite flux products, more detailed analysis is required to understand specific retrieval algorithm weaknesses. Here we show how data from the ARM shortwave flux analysis (SFA) value added product (VAP) are being used to assess solar fluxes in the Global Energy and Water Cycle Experiment (GEWEX) Surface Radiation Budget (SRB), release 2.5.

  15. Aerosol optical properties derived from the DRAGON-NE Asia campaign, and implications for a single-channel algorithm to retrieve aerosol optical depth in spring from Meteorological Imager (MI) on-board the Communication, Ocean, and Meteorological Satellite (COMS)

    Science.gov (United States)

    Kim, M.; Kim, J.; Jeong, U.; Kim, W.; Hong, H.; Holben, B.; Eck, T. F.; Lim, J. H.; Song, C. K.; Lee, S.; Chung, C.-Y.

    2016-02-01

    An aerosol model optimized for northeast Asia is updated with the inversion data from the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-northeast (NE) Asia campaign which was conducted during spring from March to May 2012. This updated aerosol model was then applied to a single visible channel algorithm to retrieve aerosol optical depth (AOD) from a Meteorological Imager (MI) on-board the geostationary meteorological satellite, Communication, Ocean, and Meteorological Satellite (COMS). This model plays an important role in retrieving accurate AOD from a single visible channel measurement. For the single-channel retrieval, sensitivity tests showed that perturbations by 4 % (0.926 ± 0.04) in the assumed single scattering albedo (SSA) can result in the retrieval error in AOD by over 20 %. Since the measured reflectance at the top of the atmosphere depends on both AOD and SSA, the overestimation of assumed SSA in the aerosol model leads to an underestimation of AOD. Based on the AErosol RObotic NETwork (AERONET) inversion data sets obtained over East Asia before 2011, seasonally analyzed aerosol optical properties (AOPs) were categorized by SSAs at 675 nm of 0.92 ± 0.035 for spring (March, April, and May). After the DRAGON-NE Asia campaign in 2012, the SSA during spring showed a slight increase to 0.93 ± 0.035. In terms of the volume size distribution, the mode radius of coarse particles was increased from 2.08 ± 0.40 to 2.14 ± 0.40. While the original aerosol model consists of volume size distribution and refractive indices obtained before 2011, the new model is constructed by using a total data set after the DRAGON-NE Asia campaign. The large volume of data in high spatial resolution from this intensive campaign can be used to improve the representative aerosol model for East Asia. Accordingly, the new AOD data sets retrieved from a single-channel algorithm, which uses a precalculated look-up table (LUT) with the new aerosol model, show an

  16. System refinement for content based satellite image retrieval

    Directory of Open Access Journals (Sweden)

    NourElDin Laban

    2012-06-01

    Full Text Available We are witnessing a large increase in satellite generated data especially in the form of images. Hence intelligent processing of the huge amount of data received by dozens of earth observing satellites, with specific satellite image oriented approaches, presents itself as a pressing need. Content based satellite image retrieval (CBSIR approaches have mainly been driven so far by approaches dealing with traditional images. In this paper we introduce a novel approach that refines image retrieval process using the unique properties to satellite images. Our approach uses a Query by polygon (QBP paradigm for the content of interest instead of using the more conventional rectangular query by image approach. First, we extract features from the satellite images using multiple tiling sizes. Accordingly the system uses these multilevel features within a multilevel retrieval system that refines the retrieval process. Our multilevel refinement approach has been experimentally validated against the conventional one yielding enhanced precision and recall rates.

  17. Snowline retrievals using operational satellite data

    Science.gov (United States)

    Becker, R.

    2010-09-01

    Making use of atmosphere and surface parameters derived from satellite remote sensing is of increasing importance to describe appropriately status and changes of weather and climate. Even in regions with poor coverage concerning ground based measurements and/or heterogenous terrain satellite products contribute to fill temporal and spatial gaps. Imaging radiometers provide information on surface snow and ice based on multispectral algorithms with a spatial resolution from 250 m to about 3000 m. Observations by passive imaging spectro-/radiometers like SEVIRI onboard Meteosat second generation, Noaa/MetOp AVHRR and Terra/Aqua MODIS have the potential to provide snow products on a daily basis with spatial resolution comparable or better than grid increment of the hydrological models. For the evaluation of MODIS imagery a dedicated algorithm was set up utilising multispectral thresholding of calibrated radiances to separate clear land and sea from cloudy and snow-covered scenes. The scheme works independently of a-priori atmospheric data like numerical model forecasts. It outputs a combined snow/cloudmask that is finally convoluted with background topography information (GIS), allowing for the calculation of snowlines. The core snow and ice detection is based on a NDSI module (normalised difference snow index, Hall et.al. 2001). A well established algorithm developed within the framework of the Satellite Application Facility for Nowcasting (NWCSAF, Dybbroe et.al. 2005), is used to detect snowy pixels in the AVHRR imagery. MODIS and AVHRR results were compared to each other. It shows a good agreement by means of correlation (.94) but systematic deviations are considered. A verification study was carried out by taking into account all European synoptical and climatological snow measurements with snow depths of at least 1 cm. The scores show a clear seasonal cycle with PODs of .2 in summer (both) and .86 (AVHRR) and .82 (MODIS) in winter months. The evaluation data

  18. EVOLVING RETRIEVAL ALGORITHMS WITH A GENETIC PROGRAMMING SCHEME

    Energy Technology Data Exchange (ETDEWEB)

    J. THEILER; ET AL

    1999-06-01

    The retrieval of scene properties (surface temperature, material type, vegetation health, etc.) from remotely sensed data is the ultimate goal of many earth observing satellites. The algorithms that have been developed for these retrievals are informed by physical models of how the raw data were generated. This includes models of radiation as emitted and/or rejected by the scene, propagated through the atmosphere, collected by the optics, detected by the sensor, and digitized by the electronics. To some extent, the retrieval is the inverse of this ''forward'' modeling problem. But in contrast to this forward modeling, the practical task of making inferences about the original scene usually requires some ad hoc assumptions, good physical intuition, and a healthy dose of trial and error. The standard MTI data processing pipeline will employ algorithms developed with this traditional approach. But we will discuss some preliminary research on the use of a genetic programming scheme to ''evolve'' retrieval algorithms. Such a scheme cannot compete with the physical intuition of a remote sensing scientist, but it may be able to automate some of the trial and error. In this scenario, a training set is used, which consists of multispectral image data and the associated ''ground truth;'' that is, a registered map of the desired retrieval quantity. The genetic programming scheme attempts to combine a core set of image processing primitives to produce an IDL (Interactive Data Language) program which estimates this retrieval quantity from the raw data.

  19. Fast Simulators for Satellite Cloud Optical Centroid Pressure Retrievals, 1. Evaluation of OMI Cloud Retrievals

    Science.gov (United States)

    Joiner, J.; Vasilkov, A.; Gupta, P.; Bhartia, P. K.; Veefkind, P.; Sneep, M.; de Haan, J.; Polonsky, I.; Spurr, R.

    2012-01-01

    The cloud Optical Centroid Pressure (OCP), also known as the effective cloud pressure, is a satellite-derived parameter that is commonly used in trace-gas retrievals to account for the effects of clouds on near-infrared through ultraviolet radiance measurements. Fast simulators are desirable to further expand the use of cloud OCP retrievals into the operational and climate communities for applications such as data assimilation and evaluation of cloud vertical structure in general circulation models. In this paper, we develop and validate fast simulators that provide estimates of the cloud OCP given a vertical profile of optical extinction. We use a pressure-weighting scheme where the weights depend upon optical parameters of clouds and/or aerosol. A cloud weighting function is easily extracted using this formulation. We then use fast simulators to compare two different satellite cloud OCP retrievals from the Ozone Monitoring Instrument (OMI) with estimates based on collocated cloud extinction profiles from a combination of CloudS at radar and MODIS visible radiance data. These comparisons are made over a wide range of conditions to provide a comprehensive validation of the OMI cloud OCP retrievals. We find generally good agreement between OMI cloud OCPs and those predicted by CloudSat. However, the OMI cloud OCPs from the two independent algorithms agree better with each other than either does with the estimates from CloudSat/MODIS. Differences between OMI cloud OCPs and those based on CloudSat/MODIS may result from undetected snow/ice at the surface, cloud 3-D effects, low altitude clouds missed by CloudSat, and the fact that CloudSat only observes a relatively small fraction of an OMI field-of-view.

  20. Fast simulators for satellite cloud optical centroid pressure retrievals; evaluation of OMI cloud retrievals

    Directory of Open Access Journals (Sweden)

    J. Joiner

    2012-03-01

    Full Text Available The cloud Optical Centroid Pressure (OCP is a satellite-derived parameter that is commonly used in trace-gas retrievals to account for the effects of clouds on near-infrared through ultraviolet radiance measurements. Fast simulators are desirable to further expand the use of cloud OCP retrievals into the operational and climate communities for applications such as data assimilation and evaluation of cloud vertical structure in general circulation models. In this paper, we develop and validate fast simulators that provide estimates of the cloud OCP given a vertical profile of optical extinction. We use a pressure-weighting scheme where the weights depend upon optical parameters of clouds and/or aerosols. A cloud weighting function is easily extracted using this formulation. We then use fast simulators to compare two different satellite cloud OCP retrievals, from the Ozone Monitoring Instrument (OMI, with estimates based on collocated cloud extinction profiles from a combination of CloudSat radar and MODIS visible radiance data. These comparisons are made over a wide range of conditions to provide a comprehensive validation of the OMI cloud OCP retrievals. We find generally good agreement between OMI cloud OCPs and those predicted by CloudSat. However, the OMI cloud OCPs from the two independent algorithms agree better with each other than either does with the estimates from CloudSat/MODIS. Differences between OMI cloud OCPs and those based on CloudSat/MODIS may result from undetected snow/ice at the surface, cloud 3-D effects, cases of low clouds obscurred by ground-clutter in CloudSat observations and by opaque high clouds in CALIPSO lidar observations, and the fact that CloudSat/CALIPSO only observes a relatively small fraction of an OMI field-of-view.

  1. Efficient Methods to Assimilate Satellite Retrievals Based on Information Content. Part 2; Suboptimal Retrieval Assimilation

    Science.gov (United States)

    Joiner, J.; Dee, D. P.

    1998-01-01

    One of the outstanding problems in data assimilation has been and continues to be how best to utilize satellite data while balancing the tradeoff between accuracy and computational cost. A number of weather prediction centers have recently achieved remarkable success in improving their forecast skill by changing the method by which satellite data are assimilated into the forecast model from the traditional approach of assimilating retrievals to the direct assimilation of radiances in a variational framework. The operational implementation of such a substantial change in methodology involves a great number of technical details, e.g., pertaining to quality control procedures, systematic error correction techniques, and tuning of the statistical parameters in the analysis algorithm. Although there are clear theoretical advantages to the direct radiance assimilation approach, it is not obvious at all to what extent the improvements that have been obtained so far can be attributed to the change in methodology, or to various technical aspects of the implementation. The issue is of interest because retrieval assimilation retains many practical and logistical advantages which may become even more significant in the near future when increasingly high-volume data sources become available. The central question we address here is: how much improvement can we expect from assimilating radiances rather than retrievals, all other things being equal? We compare the two approaches in a simplified one-dimensional theoretical framework, in which problems related to quality control and systematic error correction are conveniently absent. By assuming a perfect radiative transfer model and perfect knowledge of radiance and background error covariances, we are able to formulate a nonlinear local error analysis for each assimilation method. Direct radiance assimilation is optimal in this idealized context, while the traditional method of assimilating retrievals is suboptimal because it

  2. a Distributed Polygon Retrieval Algorithm Using Mapreduce

    Science.gov (United States)

    Guo, Q.; Palanisamy, B.; Karimi, H. A.

    2015-07-01

    The burst of large-scale spatial terrain data due to the proliferation of data acquisition devices like 3D laser scanners poses challenges to spatial data analysis and computation. Among many spatial analyses and computations, polygon retrieval is a fundamental operation which is often performed under real-time constraints. However, existing sequential algorithms fail to meet this demand for larger sizes of terrain data. Motivated by the MapReduce programming model, a well-adopted large-scale parallel data processing technique, we present a MapReduce-based polygon retrieval algorithm designed with the objective of reducing the IO and CPU loads of spatial data processing. By indexing the data based on a quad-tree approach, a significant amount of unneeded data is filtered in the filtering stage and it reduces the IO overhead. The indexed data also facilitates querying the relationship between the terrain data and query area in shorter time. The results of the experiments performed in our Hadoop cluster demonstrate that our algorithm performs significantly better than the existing distributed algorithms.

  3. A DISTRIBUTED POLYGON RETRIEVAL ALGORITHM USING MAPREDUCE

    Directory of Open Access Journals (Sweden)

    Q. Guo

    2015-07-01

    Full Text Available The burst of large-scale spatial terrain data due to the proliferation of data acquisition devices like 3D laser scanners poses challenges to spatial data analysis and computation. Among many spatial analyses and computations, polygon retrieval is a fundamental operation which is often performed under real-time constraints. However, existing sequential algorithms fail to meet this demand for larger sizes of terrain data. Motivated by the MapReduce programming model, a well-adopted large-scale parallel data processing technique, we present a MapReduce-based polygon retrieval algorithm designed with the objective of reducing the IO and CPU loads of spatial data processing. By indexing the data based on a quad-tree approach, a significant amount of unneeded data is filtered in the filtering stage and it reduces the IO overhead. The indexed data also facilitates querying the relationship between the terrain data and query area in shorter time. The results of the experiments performed in our Hadoop cluster demonstrate that our algorithm performs significantly better than the existing distributed algorithms.

  4. CHINA RETRIEVES 19th RECOVERABLE SATELLITE

    Institute of Scientific and Technical Information of China (English)

    2004-01-01

    China on Sept.25 recovered its 19th recoverable sci-tech experimental satellite 27 days after the satellite orbited in space. The satellite, which was launched on Aug.29 from the Jiuquan Satellite Launch Center in Gansu Province, northwest China, touched the ground at 7:55 a.m.on Sept.25. The satellite, atop a Long March 2C carrier rocket, is mainly for

  5. Transfer and distortion of atmospheric information in the satellite temperature retrieval problem

    Science.gov (United States)

    Thompson, O. E.

    1981-01-01

    A systematic approach to investigating the transfer of basic ambient temperature information and its distortion by satellite systems and subsequent analysis algorithms is discussed. The retrieval analysis cycle is derived, the variance spectrum of information is examined as it takes different forms in that process, and the quality and quantity of information existing at each stop is compared with the initial ambient temperature information. Temperature retrieval algorithms can smooth, add, or further distort information, depending on how stable the algorithm is, and how heavily influenced by a priori data.

  6. Heavy precipitation retrieval from combined satellite observations and ground-based lightning measurements

    Science.gov (United States)

    Mugnai, A.; Dietrich, S.; Casella, D.; di Paola, F.; Formenton, M.; Sanò, P.

    2010-09-01

    We have developed a series of algorithms for the retrieval of precipitation (especially, heavy precipitation) over the Mediterranean area using satellite observations from the available microwave (MW) radiometers onboard low Earth orbit (LEO) satellites and from the visible-infrared (VIS-IR) SEVIRI radiometer onboard the European geosynchronous (GEO) satellite Meteosat Second Generation (MSG), in conjunction with lightning data from ground-based networks - such as ZEUS and LINET. These are: • A new approach for precipitation retrieval from space (which we call the Cloud Dynamics and Radiation Database approach, CDRD) that incorporates lightning and environmental/dynamical information in addition to the upwelling microwave brightness temperatures (TB’s) so as to reduce the retrieval uncertainty and improve the retrieval performance; • A new combined MW-IR technique for producing frequent precipitation retrievals from space (which we call PM-GCD technique), that uses passive-microwave (PM) retrievals in conjunction with lightning information and the Global Convection Detection (GCD) technique to discriminate deep convective clouds within the GEO observations; • A new morphing approach (which we call the Lightning-based Precipitation Evolving Technique, L-PET) that uses the available lightning measurements for propagating the rainfall estimates from satellite-borne MW radiometers to a much higher time resolution than the MW observations. We will present and discuss our combined MW/IR/lightning precipitation algorithms and analyses with special reference to some case studies over the western Mediterranean.

  7. Precipitation retrieval from satellite within EUMETSAT's H-SAF

    Science.gov (United States)

    Mugnai, A.; Dietrich, S.; Levizzani, V.; Casella, D.; Cattani, E.; di Paola, F.; Formenton, M.; Laviola, S.; Sanò, P.

    2010-09-01

    currently limited to Institutions that participate in product development and/or validation activities. The emphasis of precipitation product generation in H-SAF is on near-real-time applications, as requested by the European hydrological community and, specifically in Italy, by the Civil Protection Department (DPC) - i.e., the Italian Agency which is responsible for disaster management. DPC is a major sponsor of the Italian participation to H-SAF, with increasing involvement in product validation and impact assessment activities. We will present and discuss the basic algorithms for precipitation retrieval from satellite, that have been developed by CNR-ISAC. We will also discuss the activities that will be performed during CDOP in order to enhance and improve algorithms and processing schemes and extend them to satellites that will be operational in the 2010-2017 timeframe - with special emphasis on the GEO Meteosat Third Generation (MTG) satellite which is scheduled to be launched by EUMETSAT in 2017, and on the LEO Core Observatory of the Global Precipitation Measurement (GPM) mission which will launched by NASA and JAXA in 2013.

  8. Spatial Cloud Detection and Retrieval System for Satellite Images

    Directory of Open Access Journals (Sweden)

    Ayman Nasr

    2013-01-01

    Full Text Available In last the decade we witnessed a large increase in data generated by earth observing satellites. Hence, intelligent processing of the huge amount of data received by hundreds of earth receiving stations, with specific satellite image oriented approaches, presents itself as a pressing need. One of the most important steps in earlier stages of satellite image processing is cloud detection. Satellite images having a large percentage of cloud cannot be used in further analysis. While there are many approaches that deal with different semantic meaning, there are rarely approaches that deal specifically with cloud detection and retrieval. In this paper we introduce a novel approach that spatially detect and retrieve clouds in satellite images using their unique properties .Our approach is developed as spatial cloud detection and retrieval system (SCDRS that introduce a complete framework for specific semantic retrieval system. It uses a Query by polygon (QBP paradigm for the content of interest instead of using the more conventional rectangular query by image approach. First, we extract features from the satellite images using multiple tile sizes using spatial and textural properties of cloud regions. Second, we retrieve our tiles using a parametric statistical approach within a multilevel refinement process. Our approach has been experimentally validated against the conventional ones yielding enhanced precision and recall rates in the same time it gives more precise detection of cloud coverage regions.

  9. A sustainable genetic algorithm for satellite resource allocation

    Science.gov (United States)

    Abbott, R. J.; Campbell, M. L.; Krenz, W. C.

    1995-01-01

    A hybrid genetic algorithm is used to schedule tasks for 8 satellites, which can be modelled as a robot whose task is to retrieve objects from a two dimensional field. The objective is to find a schedule that maximizes the value of objects retrieved. Typical of the real-world tasks to which this corresponds is the scheduling of ground contacts for a communications satellite. An important feature of our application is that the amount of time available for running the scheduler is not necessarily known in advance. This requires that the scheduler produce reasonably good results after a short period but that it also continue to improve its results if allowed to run for a longer period. We satisfy this requirement by developing what we call a sustainable genetic algorithm.

  10. Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations: 2. Retrieval evaluation

    Science.gov (United States)

    Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Wind, Gala; Yang, Ping

    2016-05-01

    An infrared-based optimal estimation (OE-IR) algorithm for retrieving ice cloud properties is evaluated. Specifically, the implementation of the algorithm with MODerate resolution Imaging Spectroradiometer (MODIS) observations is assessed in comparison with the operational retrieval products from MODIS on the Aqua satellite (MYD06), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and the Imaging Infrared Radiometer (IIR); the latter two instruments fly on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite in the Afternoon Constellation (A-Train) with Aqua. The results show that OE-IR cloud optical thickness (τ) and effective radius (reff) retrievals perform best for ice clouds having 0.5 1 km) occurs for τ < 0.5. Analysis of 1 month of the OE-IR retrievals shows large τ and reff uncertainties in storm track regions and the southern oceans where convective clouds are frequently observed, as well as in high-latitude regions where temperature differences between the surface and cloud top are more ambiguous. Generally, comparisons between the OE-IR and the operational products show consistent τ and h retrievals. However, obvious differences between the OE-IR and the MODIS Collection 6 reff are found.

  11. Evaluation of Land Surface Temperature Operationally Retrieved from Korean Geostationary Satellite (COMS Data

    Directory of Open Access Journals (Sweden)

    A-Ra Cho

    2013-08-01

    Full Text Available We evaluated the precision of land surface temperature (LST operationally retrieved from the Korean multipurpose geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS. The split-window (SW-type retrieval algorithm was developed through radiative transfer model simulations under various atmospheric profiles, satellite zenith angles, surface emissivity values and surface lapse rate conditions using Moderate Resolution Atmospheric Transmission version 4 (MODTRAN4. The estimation capabilities of the COMS SW (CSW LST algorithm were evaluated for various impacting factors, and the retrieval accuracy of COMS LST data was evaluated with collocated Moderate Resolution Imaging Spectroradiometer (MODIS LST data. The surface emissivity values for two SW channels were generated using a vegetation cover method. The CSW algorithm estimated the LST distribution reasonably well (averaged bias = 0.00 K, Root Mean Square Error (RMSE = 1.41 K, correlation coefficient = 0.99; however, the estimation capabilities of the CSW algorithm were significantly impacted by large brightness temperature differences and surface lapse rates. The CSW algorithm reproduced spatiotemporal variations of LST comparing well to MODIS LST data, irrespective of what month or time of day the data were collected from. The one-year evaluation results with MODIS LST data showed that the annual mean bias, RMSE and correlation coefficient for the CSW algorithm were −1.009 K, 2.613 K and 0.988, respectively.

  12. Improvement of retrieval algorithms for severe air pollution

    Science.gov (United States)

    Mukai, Sonoyo; Sano, Itaru; Nakata, Makiko

    2016-10-01

    Increased emissions of anthropogenic aerosols associated with economic growth can lead to increased concentrations of hazardous air pollutants. Furthermore, dust storms or biomass burning plumes can cause serious environmental hazards, yet their aerosol properties are poorly understood. Our research group has worked on the development of an efficient algorithm for aerosol retrieval during hazy episodes (dense concentrations of atmospheric aerosols). It is noted that near UV measurements are available for detection of carbonaceous aerosols. The biomass burning aerosols (BBA) due to large-scale forest fires and/or burn agriculture exacerbated the severe air pollution. It is known that global warming and climate change have caused increasing instances of forest fires, which have in turn accelerated climate change. It is well known that this negative cycle decreases the quality of the global environment and human health. The Japan Aerospace Exploration Agency (JAXA) has been developing a new Earth observing system, the GCOM (Global Change Observation Mission) project, which consists of two satellite series: GCOM-W1 and GCOM-C1. The first GCOM-C satellite will board the SGLI (second generation GLI [global imager]) to be launched in early 2017. The SGLI is capable of multi-channel (19) observation, including a near UV channel (0.380 μm) and two polarization channels at red and near-infrared wavelengths of 0.67 and 0.87 μm. Thus, global aerosol retrieval will be achieved with simultaneous polarization and total radiance. In this study, algorithm improvement for aerosol remote sensing, especially of BBA episodes, is examined using Terra/MODIS measurements from 2003, when the GLI and POLDER-2 sensors were working onboard the Japanese satellite ADEOS-2.

  13. Cloud retrievals from satellite data using optimal estimation: evaluation and application to ATSR

    Directory of Open Access Journals (Sweden)

    C. A. Poulsen

    2012-08-01

    Full Text Available Clouds play an important role in balancing the Earth's radiation budget. Hence, it is vital that cloud climatologies are produced that quantify cloud macro and micro physical parameters and the associated uncertainty. In this paper, we present an algorithm ORAC (Oxford-RAL retrieval of Aerosol and Cloud which is based on fitting a physically consistent cloud model to satellite observations simultaneously from the visible to the mid-infrared, thereby ensuring that the resulting cloud properties provide both a good representation of the short-wave and long-wave radiative effects of the observed cloud. The advantages of the optimal estimation method are that it enables rigorous error propagation and the inclusion of all measurements and any a priori information and associated errors in a rigorous mathematical framework. The algorithm provides a measure of the consistency between retrieval representation of cloud and satellite radiances. The cloud parameters retrieved are the cloud top pressure, cloud optical depth, cloud effective radius, cloud fraction and cloud phase.

    The algorithm can be applied to most visible/infrared satellite instruments. In this paper, we demonstrate the applicability to the Along-Track Scanning Radiometers ATSR-2 and AATSR. Examples of applying the algorithm to ATSR-2 flight data are presented and the sensitivity of the retrievals assessed, in particular the algorithm is evaluated for a number of simulated single-layer and multi-layer conditions. The algorithm was found to perform well for single-layer cloud except when the cloud was very thin; i.e., less than 1 optical depths. For the multi-layer cloud, the algorithm was robust except when the upper ice cloud layer is less than five optical depths. In these cases the retrieved cloud top pressure and cloud effective radius become a weighted average of the 2 layers. The sum of optical depth of multi-layer cloud is retrieved well until the cloud becomes thick

  14. A fast SEVIRI simulator for quantifying retrieval uncertainties in the CM SAF cloud physical property algorithm

    Directory of Open Access Journals (Sweden)

    B. J. Jonkheid

    2012-11-01

    Full Text Available The uncertainties in the cloud physical properties derived from satellite observations make it difficult to interpret model evaluation studies. In this paper, the uncertainties in the cloud water path (CWP retrievals derived with the cloud physical properties retrieval algorithm (CPP of the climate monitoring satellite application facility (CM SAF are investigated. To this end, a numerical simulator of MSG-SEVIRI observations has been developed that calculates the reflectances at 0.64 and 1.63 μm for a wide range of cloud parameter values, satellite viewing geometries and surface albedos using a plane-parallel radiative transfer model. The reflectances thus obtained are used as input to CPP, and the retrieved values of CWP are compared to the original input of the simulator. Cloud parameters considered in this paper refer to e.g. sub-pixel broken clouds and the simultaneous occurrence of ice and liquid water clouds within one pixel. These configurations are not represented in the CPP algorithm and as such the associated retrieval uncertainties are potentially substantial.

    It is shown that the CWP retrievals are very sensitive to the assumptions made in the CPP code. The CWP retrieval errors are generally small for unbroken single-layer clouds with COT > 10, with retrieval errors of ~3% for liquid water clouds to ~10% for ice clouds. In a multi-layer cloud, when both liquid water and ice clouds are present in a pixel, the CWP retrieval errors increase dramatically; depending on the cloud, this can lead to uncertainties of 40–80%. CWP retrievals also become more uncertain when the cloud does not cover the entire pixel, leading to errors of ~50% for cloud fractions of 0.75 and even larger errors for smaller cloud fractions. Thus, the satellite retrieval of cloud physical properties of broken clouds as well as multi-layer clouds is complicated by inherent difficulties, and the proper interpretation of such retrievals requires extra care.

  15. Relevance Feedback Algorithm Based on Collaborative Filtering in Image Retrieval

    Directory of Open Access Journals (Sweden)

    Yan Sun

    2010-12-01

    Full Text Available Content-based image retrieval is a very dynamic study field, and in this field, how to improve retrieval speed and retrieval accuracy is a hot issue. The retrieval performance can be improved when applying relevance feedback to image retrieval and introducing the participation of people to the retrieval process. However, as for many existing image retrieval methods, there are disadvantages of relevance feedback with information not being fully saved and used, and their accuracy and flexibility are relatively poor. Based on this, the collaborative filtering technology was combined with relevance feedback in this study, and an improved relevance feedback algorithm based on collaborative filtering was proposed. In the method, the collaborative filtering technology was used not only to predict the semantic relevance between images in database and the retrieval samples, but to analyze feedback log files in image retrieval, which can make the historical data of relevance feedback be fully used by image retrieval system, and further to improve the efficiency of feedback. The improved algorithm presented has been tested on the content-based image retrieval database, and the performance of the algorithm has been analyzed and compared with the existing algorithms. The experimental results showed that, compared with the traditional feedback algorithms, this method can obviously improve the efficiency of relevance feedback, and effectively promote the recall and precision of image retrieval.

  16. Cloud and Thermodynamic Parameters Retrieved from Satellite Ultraspectral Infrared Measurements

    Science.gov (United States)

    Zhou, Daniel K.; Smith, William L.; Larar, Allen M.; Liu, Xu; Taylor, Jonathan P.; Schluessel, Peter; Strow, L. Larrabee; Mango, Stephen A.

    2008-01-01

    Atmospheric-thermodynamic parameters and surface properties are basic meteorological parameters for weather forecasting. A physical geophysical parameter retrieval scheme dealing with cloudy and cloud-free radiance observed with satellite ultraspectral infrared sounders has been developed and applied to the Infrared Atmospheric Sounding Interferometer (IASI) and the Atmospheric InfraRed Sounder (AIRS). The retrieved parameters presented herein are from radiance data gathered during the Joint Airborne IASI Validation Experiment (JAIVEx). JAIVEx provided intensive aircraft observations obtained from airborne Fourier Transform Spectrometer (FTS) systems, in-situ measurements, and dedicated dropsonde and radiosonde measurements for the validation of the IASI products. Here, IASI atmospheric profile retrievals are compared with those obtained from dedicated dropsondes, radiosondes, and the airborne FTS system. The IASI examples presented here demonstrate the ability to retrieve fine-scale horizontal features with high vertical resolution from satellite ultraspectral sounder radiance spectra.

  17. Atmospheric correction for sea surface temperature retrieval from single thermal channel radiometer data onboard Kalpana satellite

    Science.gov (United States)

    Shahi, Naveen R.; Agarwal, Neeraj; Mathur, Aloke K.; Sarkar, Abhijit

    2011-06-01

    An atmospheric correction method has been applied on sea surface temperature (SST) retrieval algorithm using Very High Resolution Radiometer (VHRR) single window channel radiance data onboard Kalpana satellite (K-SAT). The technique makes use of concurrent water vapour fields available from Microwave Imager onboard Tropical Rainfall Measuring Mission (TRMM/TMI) satellite. Total water vapour content and satellite zenith angle dependent SST retrieval algorithm has been developed using Radiative Transfer Model [MODTRAN ver3.0] simulations for Kalpana 10.5-12.5 μm thermal window channel. Retrieval of Kalpana SST (K-SST) has been carried out for every half-hourly acquisition of Kalpana data for the year 2008 to cover whole annual cycle of SST over Indian Ocean (IO). Validation of the retrieved corrected SST has been carried out using near-simultaneous observations of ship and buoys datasets covering Arabian Sea, Bay of Bengal and IO regions. A significant improvement in Root Mean Square Deviation (RMSD) of K-SST with respect to buoy (1.50-1.02 K) and to ship datasets (1.41-1.19 K) is seen with the use of near real-time water vapour fields of TMI. Furthermore, comparison of the retrieved SST has also been carried out using near simultaneous observations of TRMM/TMI SST over IO regions. The analysis shows that K-SST has overall cold bias of 1.17 K and an RMSD of 1.09 K after bias correction.

  18. Applying Genetic Algorithms To Query Optimization in Document Retrieval.

    Science.gov (United States)

    Horng, Jorng-Tzong; Yeh, Ching-Chang

    2000-01-01

    Proposes a novel approach to automatically retrieve keywords and then uses genetic algorithms to adapt the keyword weights. Discusses Chinese text retrieval, term frequency rating formulas, vector space models, bigrams, the PAT-tree structure for information retrieval, query vectors, and relevance feedback. (Author/LRW)

  19. Applying Genetic Algorithms To Query Optimization in Document Retrieval.

    Science.gov (United States)

    Horng, Jorng-Tzong; Yeh, Ching-Chang

    2000-01-01

    Proposes a novel approach to automatically retrieve keywords and then uses genetic algorithms to adapt the keyword weights. Discusses Chinese text retrieval, term frequency rating formulas, vector space models, bigrams, the PAT-tree structure for information retrieval, query vectors, and relevance feedback. (Author/LRW)

  20. An Improved Wind Speed Retrieval Algorithm For The CYGNSS Mission

    Science.gov (United States)

    Ruf, C. S.; Clarizia, M. P.

    2015-12-01

    The NASA spaceborne Cyclone Global Navigation Satellite System (CYGNSS) mission is a constellation of 8 microsatellites focused on tropical cyclone (TC) inner core process studies. CYGNSS will be launched in October 2016, and will use GPS-Reflectometry (GPS-R) to measure ocean surface wind speed in all precipitating conditions, and with sufficient frequency to resolve genesis and rapid intensification. Here we present a modified and improved version of the current baseline Level 2 (L2) wind speed retrieval algorithm designed for CYGNSS. An overview of the current approach is first presented, which makes use of two different observables computed from 1-second Level 1b (L1b) delay-Doppler Maps (DDMs) of radar cross section. The first observable, the Delay-Doppler Map Average (DDMA), is the averaged radar cross section over a delay-Doppler window around the DDM peak (i.e. the specular reflection point coordinate in delay and Doppler). The second, the Leading Edge Slope (LES), is the leading edge of the Integrated Delay Waveform (IDW), obtained by integrating the DDM along the Doppler dimension. The observables are calculated over a limited range of time delays and Doppler frequencies to comply with baseline spatial resolution requirements for the retrieved winds, which in the case of CYGNSS is 25 km. In the current approach, the relationship between the observable value and the surface winds is described by an empirical Geophysical Model Function (GMF) that is characterized by a very high slope in the high wind regime, for both DDMA and LES observables, causing large errors in the retrieval at high winds. A simple mathematical modification of these observables is proposed, which linearizes the relationship between ocean surface roughness and the observables. This significantly reduces the non-linearity present in the GMF that relate the observables to the wind speed, and reduces the root-mean square error between true and retrieved winds, particularly in the high wind

  1. NASA Team 2 Sea Ice Concentration Algorithm Retrieval Uncertainty

    Science.gov (United States)

    Brucker, Ludovic; Cavalieri, Donald J.; Markus, Thorsten; Ivanoff, Alvaro

    2014-01-01

    Satellite microwave radiometers are widely used to estimate sea ice cover properties (concentration, extent, and area) through the use of sea ice concentration (IC) algorithms. Rare are the algorithms providing associated IC uncertainty estimates. Algorithm uncertainty estimates are needed to assess accurately global and regional trends in IC (and thus extent and area), and to improve sea ice predictions on seasonal to interannual timescales using data assimilation approaches. This paper presents a method to provide relative IC uncertainty estimates using the enhanced NASA Team (NT2) IC algorithm. The proposed approach takes advantage of the NT2 calculations and solely relies on the brightness temperatures (TBs) used as input. NT2 IC and its associated relative uncertainty are obtained for both the Northern and Southern Hemispheres using the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) TB. NT2 IC relative uncertainties estimated on a footprint-by-footprint swath-by-swath basis were averaged daily over each 12.5-km grid cell of the polar stereographic grid. For both hemispheres and throughout the year, the NT2 relative uncertainty is less than 5%. In the Southern Hemisphere, it is low in the interior ice pack, and it increases in the marginal ice zone up to 5%. In the Northern Hemisphere, areas with high uncertainties are also found in the high IC area of the Central Arctic. Retrieval uncertainties are greater in areas corresponding to NT2 ice types associated with deep snow and new ice. Seasonal variations in uncertainty show larger values in summer as a result of melt conditions and greater atmospheric contributions. Our analysis also includes an evaluation of the NT2 algorithm sensitivity to AMSR-E sensor noise. There is a 60% probability that the IC does not change (to within the computed retrieval precision of 1%) due to sensor noise, and the cumulated probability shows that there is a 90% chance that the IC varies by less than

  2. Retrieval of vegetation hydrodynamic parameters from satellite multispectral data

    Science.gov (United States)

    Forzieri, Giovanni; Degetto, Massimo; Righetti, Maurizio; Castelli, Fabio; Preti, Federico

    2013-04-01

    Riparian vegetation plays a crucial role on affecting the floodplain hydraulic roughness, which in turn significantly influences the dynamics of flood waves. This work explores the potential accuracies of retrieving vegetation hydrodynamic parameters through satellite multispectral data. The method is focused on estimation of vegetation height and flexural rigidity for herbaceous patterns and of plant density, tree height, stem diameter, crown base height and crown diameter of high-forest and coppice consociations for arboreal and shrub patterns. The retrieval algorithm performs: (1) classification procedure of riparian corridor; (2) land cover-based Principal Component Analysis of spectral channels; (3) explorative analysis of correlation structure between principal components and biomechanical properties and (4) model identification/estimation/validation for floodplain roughness parameterization. To capture the impacts of stiff/flexible vegetation, a GIS hydrodynamic model has been coupled with a flow resistance external routine that estimates the hydraulic roughness by using simulated water stages and the remote sensing-derived vegetation parameters. The procedure is tested along a 3-km reach of the Avisio river (Trentino Alto Adige, Italy) by comparing extended field surveys and a synchronous SPOT-5 multispectral image acquired on 28/08/2004. Results showed significant correlation values between spectral-derived information and hydrodynamic parameters. Predictive models provided high coefficients of determination, especially for mixed arboreal and shrub land covers. The generated structural parameter maps represent spatially explicit data layers that can be used as inputs to hydrodynamic models to analyze flow resistance effects in different submergence conditions of vegetation. The hydraulic modelling results showed that the new method is able to provide accurate hydraulic output data and to enhance the roughness estimation up to 73% with respect to a

  3. Neural network algorithms for retrieval of harmful algal blooms in the west Florida shelf from VIIRS satellite observations and comparisons with other techniques, without the need for a fluorescence channel

    Science.gov (United States)

    El-habashi, A.; Ahmed, S.

    2015-10-01

    New approaches are described that use of the Ocean Color Remote Sensing Reflectance readings (OC Rrs) available from the existing Visible Infrared Imaging Radiometer Suite (VIIRS) bands to detect and retrieve Karenia brevis (KB) Harmful Algal Blooms (HABs) that frequently plague the coasts of the West Florida Shelf (WFS). Unfortunately, VIIRS, unlike MODIS, does not have a 678 nm channel to detect Chlorophyll fluorescence, which is used with MODIS in the normalized fluorescence height (nFLH) algorithm which has been shown to help in effectively detecting and tracking KB HABs. We present here the use of neural network (NN) algorithms for KB HABS retrievals in the WFS. These NNs, previously reported by us, were trained, using a wide range of suitably parametrized synthetic data typical of coastal waters, to form a multiband inversion algorithm which models the relationship between Rrs values at the 486, 551 and 671nm VIIRS bands against the values of phytoplankton absorption (aph), CDOM absorption (ag), non-algal particles (NAP) absorption (aNAP) and the particulate backscattering bbp coefficients, all at 443nm, and permits retrievals of these parameters. We use the NN to retrieve aph443 in the WFS. The retrieved aph443 values are then filtered by applying known limiting conditions on minimum Chlorophyll concentration [Chla] and low backscatter properties associated with KB HABS in the WFS, thereby identifying, delineating and quantifying the aph443 values, and hence [Chl] concentrations representing KB HABS. Comparisons with in-situ measurements and other techniques including MODIS nFLH confirm the viability of both the NN retrievals and the filtering approaches devised.

  4. Software for validating parameters retrieved from satellite

    Digital Repository Service at National Institute of Oceanography (India)

    Muraleedharan, P.M.; Sathe, P.V.; Pankajakshan, T.

    surface layer (skin temperature) whereas the conventional sea truth platforms (MB) measure temperature represented by the upper 2-3 m layer (Wick et al., 1992). During the day, the air temperature instantly modifies the skin temperature of the sea... between satellite measured skin and multi-channel SST. J. Geophys. Res., 97: 5569-5595. Now the weighted average of SST is obtained from the following relation ...

  5. Sensitivity, uncertainty analyses and algorithm selection for Sea Ice Thickness retrieval from Radar Altimeter

    CERN Document Server

    Djepa, Vera

    2013-01-01

    For accurate forecast of climate change, sea ice mass balance, ocean circulation and sea- atmosphere interactions is required to have long term records of Sea Ice Thickness (SIT). Different approaches have been applied to retrieve SIT and only satellite altimetry, radar or laser, have been proven to provide hemispheric estimates of SIT distribution over a sufficient thickness range. To simplify the algorithm for SIT retrieval from RA, constant ice density has been applied until now, which lead to different results for derived SIT and SID, in dependence on input information for sea ice density and snow depth. The purpose of this paper is to select algorithm for SID and SIT retrieval from RA, using statistical, sensitivity analyses and independent observations of SID from moored ULS, or on Submarine. The impact of ice density and snow depth on accuracy of the retrieved SIT has been examined, applying sensitivity analyses, and the propagated uncertainties have been summarised. Accuracy of algorithms for snow dep...

  6. Satellite rainfall retrieval by logistic regression

    Science.gov (United States)

    Chiu, Long S.

    1986-01-01

    The potential use of logistic regression in rainfall estimation from satellite measurements is investigated. Satellite measurements provide covariate information in terms of radiances from different remote sensors.The logistic regression technique can effectively accommodate many covariates and test their significance in the estimation. The outcome from the logistical model is the probability that the rainrate of a satellite pixel is above a certain threshold. By varying the thresholds, a rainrate histogram can be obtained, from which the mean and the variant can be estimated. A logistical model is developed and applied to rainfall data collected during GATE, using as covariates the fractional rain area and a radiance measurement which is deduced from a microwave temperature-rainrate relation. It is demonstrated that the fractional rain area is an important covariate in the model, consistent with the use of the so-called Area Time Integral in estimating total rain volume in other studies. To calibrate the logistical model, simulated rain fields generated by rainfield models with prescribed parameters are needed. A stringent test of the logistical model is its ability to recover the prescribed parameters of simulated rain fields. A rain field simulation model which preserves the fractional rain area and lognormality of rainrates as found in GATE is developed. A stochastic regression model of branching and immigration whose solutions are lognormally distributed in some asymptotic limits has also been developed.

  7. Spatial Distribution of Accuracy of Aerosol Retrievals from Multiple Satellite Sensors

    Science.gov (United States)

    Petrenko, Maksym; Ichoku, Charles

    2012-01-01

    Remote sensing of aerosols from space has been a subject of extensive research, with multiple sensors retrieving aerosol properties globally on a daily or weekly basis. The diverse algorithms used for these retrievals operate on different types of reflected signals based on different assumptions about the underlying physical phenomena. Depending on the actual retrieval conditions and especially on the geographical location of the sensed aerosol parcels, the combination of these factors might be advantageous for one or more of the sensors and unfavorable for others, resulting in disagreements between similar aerosol parameters retrieved from different sensors. In this presentation, we will demonstrate the use of the Multi-sensor Aerosol Products Sampling System (MAPSS) to analyze and intercompare aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS. Based on this intercomparison, we are determining geographical locations where these products provide the greatest accuracy of the retrievals and identifying the products that are the most suitable for retrieval at these locations. The analyses are performed by comparing quality-screened satellite aerosol products to available collocated ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations, during the period of 2006-2010 when all the satellite sensors were operating concurrently. Furthermore, we will discuss results of a statistical approach that is applied to the collocated data to detect and remove potential data outliers that can bias the results of the analysis.

  8. Global Precipitation Measurement (GPM) Microwave Imager Falling Snow Retrieval Algorithm Performance

    Science.gov (United States)

    Skofronick Jackson, Gail; Munchak, Stephen J.; Johnson, Benjamin T.

    2015-04-01

    Retrievals of falling snow from space represent an important data set for understanding the Earth's atmospheric, hydrological, and energy cycles. While satellite-based remote sensing provides global coverage of falling snow events, the science is relatively new and retrievals are still undergoing development with challenges and uncertainties remaining. This work reports on the development and post-launch testing of retrieval algorithms for the NASA Global Precipitation Measurement (GPM) mission Core Observatory satellite launched in February 2014. In particular, we will report on GPM Microwave Imager (GMI) radiometer instrument algorithm performance with respect to falling snow detection and estimation. Since GPM's launch, the at-launch GMI precipitation algorithms, based on a Bayesian framework, have been used with the new GPM data. The at-launch database is generated using proxy satellite data merged with surface measurements (instead of models). One year after launch, the Bayesian database will begin to be replaced with the more realistic observational data from the GPM spacecraft radar retrievals and GMI data. It is expected that the observational database will be much more accurate for falling snow retrievals because that database will take full advantage of the 166 and 183 GHz snow-sensitive channels. Furthermore, much retrieval algorithm work has been done to improve GPM retrievals over land. The Bayesian framework for GMI retrievals is dependent on the a priori database used in the algorithm and how profiles are selected from that database. Thus, a land classification sorts land surfaces into ~15 different categories for surface-specific databases (radiometer brightness temperatures are quite dependent on surface characteristics). In addition, our work has shown that knowing if the land surface is snow-covered, or not, can improve the performance of the algorithm. Improvements were made to the algorithm that allow for daily inputs of ancillary snow cover

  9. Classification of Aerosol Retrievals from Spaceborne Polarimetry Using a Multiparameter Algorithm

    Science.gov (United States)

    Russell, Philip B.; Kacenelenbogen, Meloe; Livingston, John M.; Hasekamp, Otto P.; Burton, Sharon P.; Schuster, Gregory L.; Johnson, Matthew S.; Knobelspiesse, Kirk D.; Redemann, Jens; Ramachandran, S.; hide

    2013-01-01

    In this presentation, we demonstrate application of a new aerosol classification algorithm to retrievals from the POLDER-3 polarimter on the PARASOL spacecraft. Motivation and method: Since the development of global aerosol measurements by satellites and AERONET, classification of observed aerosols into several types (e.g., urban-industrial, biomass burning, mineral dust, maritime, and various subtypes or mixtures of these) has proven useful to: understanding aerosol sources, transformations, effects, and feedback mechanisms; improving accuracy of satellite retrievals and quantifying assessments of aerosol radiative impacts on climate.

  10. A novel algorithm for satellite data transmission

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    For remote sensing satellite data transmission,a novel algorithm is proposed in this paper.It integrates different type feature descriptors into multistage recognizers.In the first level,the dynamic clustering algorithm is used.In the second level,the improved support vector machines algorithm demonstrates its validity.In the third level,the shape matrices similarity comparison algorithm shows its excellent performance.The single child recognizers are connected in series,but they are independent of each other.Objects which are not recognized correctly by the lower level recognizers are then put into the higher level recognizers.Experimental results show that the multistage recognition algorithm improves the accuracy greatly with higher level feature descriptors and higher level recognizers.The algorithm may offer a new methodology for high speed satellite data transmission.

  11. Wind vector retrieval algorithm from spaceborne lidar data

    Institute of Scientific and Technical Information of China (English)

    WANG Tianyu; PAN Delu; HE Xianqiang; WANG Difeng

    2014-01-01

    The principal purpose of this paper is to extract entire sea surface wind’s information from spaceborne lidar, and particularly to utilize a appropriate algorithm for removing the interference information due to white-caps and subsurface water. Wind speeds are obtained through empirical relationship with sea surface mean square slopes. Wind directions are derived from relationship between wind speeds and wind directions im-plied in CMOD5n geophysical models function (GMF). Whitecaps backscattering signals were distinguished with the help of lidar depolarization ratio measurements and rectified by whitecaps coverage equation. Subsurface water backscattering signals were corrected by means of inverse distance weighted (IDW ) from neighborhood non-singular data with optimal subsurface water backscattering calibration parameters. To verify the algorithm reliably, it selected NDBC’s TAO buoy-laying area as survey region in camparison with buoys’ wind field data and METOP satellite ASCAT of 25 km single orbit wind field data after temporal-spa-tial matching. Validation results showed that the retrieval algorithm works well in terms of root mean square error (RMSE) less than 2m/s and wind direction’s RMSE less than 21 degree.

  12. Comparison of satellite reflectance algorithms for estimating ...

    Science.gov (United States)

    We analyzed 10 established and 4 new satellite reflectance algorithms for estimating chlorophyll-a (Chl-a) in a temperate reservoir in southwest Ohio using coincident hyperspectral aircraft imagery and dense water truth collected within one hour of image acquisition to develop simple proxies for algal blooms and to facilitate portability between multispectral satellite imagers for regional algal bloom monitoring. Narrow band hyperspectral aircraft images were upscaled spectrally and spatially to simulate 5 current and near future satellite imaging systems. Established and new Chl-a algorithms were then applied to the synthetic satellite images and then compared to calibrated Chl-a water truth measurements collected from 44 sites within one hour of aircraft acquisition of the imagery. Masks based on the spatial resolution of the synthetic satellite imagery were then applied to eliminate mixed pixels including vegetated shorelines. Medium-resolution Landsat and finer resolution data were evaluated against 29 coincident water truth sites. Coarse-resolution MODIS and MERIS-like data were evaluated against 9 coincident water truth sites. Each synthetic satellite data set was then evaluated for the performance of a variety of spectrally appropriate algorithms with regard to the estimation of Chl-a concentrations against the water truth data set. The goal is to inform water resource decisions on the appropriate satellite data acquisition and processing for the es

  13. Quantifying retrieval uncertainties in the CM-SAF cloud physical property algorithm with simulated SEVIRI observations

    Directory of Open Access Journals (Sweden)

    B. J. Jonkheid

    2012-02-01

    Full Text Available The uncertainties in the cloud physical properties derived from satellite observations make it difficult to interpret model evaluation studies. In this paper, the uncertainties in the cloud water path (CWP retrievals derived with the cloud physical properties retrieval algorithm (CPP of the climate monitoring satellite application facility (CM-SAF are investigated. To this end, a numerical simulator of MSG-SEVIRI observations was developed that calculates the reflectances at 0.64 and 1.63 μm for a wide range of cloud parameters, satellite viewing geometries and surface albedos. These reflectances are used as input to CPP, and the retrieved values of CWP are compared to the original input of the simulator.

    It is shown that the CWP retrievals are very sensitive to the assumptions made in the CPP code. The CWP retrieval errors are generally small for unbroken single-phase clouds with COT >10, with retrieval errors of ~3% for liquid water clouds to ~10% for ice clouds. When both liquid water and ice clouds are present in a pixel, the CWP retrieval errors increase dramatically; depending on the cloud, this can lead to uncertainties of 40–80%. CWP retrievals also become more uncertain when the cloud does not cover the entire pixel, leading to errors of ~50% for cloud fractions of 0.75 and even larger errors for smaller cloud fractions. Thus, the satellite retrieval of cloud physical properties of broken clouds and multi-phase clouds is complicated by inherent difficulties, and the proper interpretation of such retrievals requires extra care.

  14. Cloud retrievals from satellite data using optimal estimation: evaluation and application to ATSR

    Directory of Open Access Journals (Sweden)

    C. A. Poulsen

    2011-04-01

    Full Text Available Clouds play an important role in balancing the Earth's radiation budget. Clouds reflect sunlight which cools the Earth, and also trap infrared radiation in the same manner as greenhouse gases. Changes in cloud cover and cloud properties over time can have important consequences for climate. The Intergovernmental Panel for Climate Change (IPCC has identified current gaps in the understanding of clouds and related climate feedback processes as a leading cause of uncertainty in forecasting climate change. In this paper we present an algorithm that uses optimal estimation to retrieve cloud parameters from satellite multi-spectral imager data, in particular the Along-Track Scanning Radiometers ATSR-2 and AATSR. The cloud parameters retrieved are the cloud top pressure, cloud optical depth, cloud effective radius, cloud fraction and cloud phase. Importantly, the technique also provides estimated errors along with the retrieved values and quantifies the consistency between retrieval representation of cloud and satellite radiances. This should enable the effective use of the products for comparison with climate models or for exploitation via data assimilation. The technique is evaluated by performing retrieval simulations for a variety of simulated single layer and multi-layer conditions. Examples of applying the algorithm to ATSR-2 flight data are presented and the sensitivity of the retrievals assessed. This algorithm has been applied to both ATSR-2 and AATSR visible and infrared measurements in the context of the GRAPE (Global Retrieval and cloud Product Evaluation project to produce a 14 year consistent record for climate research (Sayer et al., 2010.

  15. Estimating the Retrievability of Temperature Profiles from Satellite Infrared Measurements

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A method is developed to assess retrievability, namely the retrieval potential for atmospheric temperature profiles, from satellite infrared measurements in clear-sky conditions. This technique is based upon generalized linear inverse theory and empirical orthogonal function analysis. Utilizing the NCEP global temperature reanalysis data in January and July from 1999 to 2003, the retrievabilities obtained with the Atmospheric Infrared Sounder (AIRS) and the High Resolution Infrared Radiation Sounder/3 (HIRS/3)sounding channel data are derived respectively for each standard pressure level on a global scale. As an incidental result of this study, the optimum truncation number in the method of generalized linear inverse is deduced too. The results show that the retrievabilities of temperature obtained with the two datasets are similar in spatial distribution and seasonal change characteristics. As for the vertical distribution, the retrievabilities are low in the upper and lower atmosphere, and high between 400 hPa and 850 hPa. For the geographical distribution, the retrievabilities are low in the low-latitude oceanic regions and in some regions in Antarctica, and relatively high in mid-high latitudes and continental regions. Compared with the HIRS/3 data, the retrievability obtained with the AIRS data can be improved by an amount between 0.15 and 0.40.

  16. A Non-MLE Approach for Satellite Scatterometer Wind Vector Retrievals in Tropical Cyclones

    Directory of Open Access Journals (Sweden)

    Suleiman Alsweiss

    2014-05-01

    Full Text Available Satellite microwave scatterometers are the principal source of global synoptic-scale ocean vector wind (OVW measurements for a number of scientific and operational oceanic wind applications. However, for extreme wind events such as tropical cyclones, their performance is significantly degraded. This paper presents a novel OVW retrieval algorithm for tropical cyclones which improves the accuracy of scatterometer based ocean surface winds when compared to low-flying aircraft with in-situ and remotely sensed observations. Unlike the traditional maximum likelihood estimation (MLE wind vector retrieval technique, this new approach sequentially estimates scalar wind directions and wind speeds. A detailed description of the algorithm is provided along with results for ten QuikSCAT hurricane overpasses (from 2003–2008 to evaluate the performance of the new algorithm. Results are compared with independent surface wind analyses from the National Oceanic and Atmospheric Administration (NOAA Hurricane Research Division’s H*Wind surface analyses and with the corresponding SeaWinds Project’s L2B-12.5 km OVW products. They demonstrate that the proposed algorithm extends the SeaWinds capability to retrieve wind speeds beyond the current range of approximately 35 m/s (minimal hurricane category-1 with improved wind direction accuracy, making this new approach a potential candidate for current and future conically scanning scatterometer wind retrieval algorithms.

  17. The validation of the Yonsei CArbon Retrieval algorithm with improved aerosol information using GOSAT measurements

    Science.gov (United States)

    Jung, Yeonjin; Kim, Jhoon; Kim, Woogyung; Boesch, Hartmut; Goo, Tae-Young; Cho, Chunho

    2017-04-01

    Although several CO2 retrieval algorithms have been developed to improve our understanding about carbon cycle, limitations in spatial coverage and uncertainties due to aerosols and thin cirrus clouds are still remained as a problem for monitoring CO2 concentration globally. Based on an optimal estimation method, the Yonsei CArbon Retrieval (YCAR) algorithm was developed to retrieve the column-averaged dry-air mole fraction of carbon dioxide (XCO2) using the Greenhouse Gases Observing SATellite (GOSAT) measurements with optimized a priori CO2 profiles and aerosol models over East Asia. In previous studies, the aerosol optical properties (AOP) are the most important factors in CO2 retrievals since AOPs are assumed as fixed parameters during retrieval process, resulting in significant XCO2 retrieval error up to 2.5 ppm. In this study, to reduce these errors caused by inaccurate aerosol optical information, the YCAR algorithm improved with taking into account aerosol optical properties as well as aerosol vertical distribution simultaneously. The CO2 retrievals with two difference aerosol approaches have been analyzed using the GOSAT spectra and have been evaluated throughout the comparison with collocated ground-based observations at several Total Carbon Column Observing Network (TCCON) sites. The improved YCAR algorithm has biases of 0.59±0.48 ppm and 2.16±0.87 ppm at Saga and Tsukuba sites, respectively, with smaller biases and higher correlation coefficients compared to the GOSAT operational algorithm. In addition, the XCO2 retrievals will be validated at other TCCON sites and error analysis will be evaluated. These results reveal that considering better aerosol information can improve the accuracy of CO2 retrieval algorithm and provide more useful XCO2 information with reduced uncertainties. This study would be expected to provide useful information in estimating carbon sources and sinks.

  18. Evaluation of Retrieval Algorithms for Ice Microphysics Using CALIPSO/CloudSat and Earthcare

    Science.gov (United States)

    Okamoto, Hajime; Sato, Kaori; Hagihara, Yuichiro; Ishimoto, Hiroshi; Borovoi, Anatoli; Konoshonkin, Alexander; Kustova, Natalia

    2016-06-01

    We developed lidar-radar algorithms that can be applied to Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar and CloudSat data to retrieve ice microphysics. The algorithms were the extended version of previously reported algorithm [1] and can treat both of nadir pointing of CALIPSO lidar period and 3°-off-nadir pointing one. We used the scattering data bank produced by the physical optics methods [2] and created lidar look-up tables of quasi-horizontally oriented ice plates (Q2D-plate) for nadir- and off-nadir lidar pointing periods. Then LUTs were implemented in the ice retrieval algorithms. We performed several sensitivity studies to evaluate uncertainties in the retrieved ice microphysics due to ice particle orientation and shape. It was found that the implementation of orientation of horizontally oriented ice plate model in the algorithm drastically improved the retrieval results in both for nadir- and off-nadir lidar pointing periods. Differences in the retrieved microphysics between only randomly oriented ice model (3D-ice) and mixture of 3D-ice and Q2Dplate model were large especially in off-nadir period, e.g., 100% in effective radius and one order in ice water content, respectively. And differences in the retrieved ice microphysics among different mixture models were smaller than about 50% for effective radius in nadir period.

  19. A radiative transfer algorithm for identification and retrieval of rain from Megha-Tropiques MADRAS

    Science.gov (United States)

    Varma, Atul K.; Piyush, D. N.; Gohil, B. S.; Basu, Sujit; Pal, P. K.

    2015-03-01

    The present study explains a radiative transfer based method for rain retrieval over the global land and oceans. The study explores the possibility of applying an existing algorithm for SSM/I to Megha-Tropiques (MT) MADRAS radiometer which is carried out by developing a radiative transfer based transfer function between scattering index (SI) from SSM/I and MADRAS measurements. Prior to quantitative estimation of rain from MADRAS, rain affected observations are identified. The scheme for rain identification over oceans presented herein from MADRAS, is used for rain flagging in the operational algorithms for the retrieval of other geophysical parameters, like cloud liquid water, total precipitable water and wind speed. SSM/I equivalent SI from MADRAS measurements is used for rain rate retrieval and testing is done with the actual measurements of brightness temperatures from SSM/I. The rain rates retrieved from MADRAS are compared with the other complimentary satellites. A comparison of daily average rain from MADRAS with that from the TRMM 3B42 is found to have a correlation of 0.67 and rms difference of 0.40 mm h-1 and nearly 0 mm h-1 bias. Similar monthly scale comparisons over the oceans provide correlation of 0.83 and 0.79 with bias of -0.03 and 0 mm h-1 with respect to TRMM-3B42 and SSM/I, respectively. Usability of the rain retrieval algorithm for intense rain associated with a deep depression is also demonstrated by comparing the spatial distribution of intense rain with other satellite measurements. Finally, the probability distribution of daily rain from MADRAS with TRMM-3B42 is presented. The approach presented herein can be generalized over other rain retrieval schemes and to any other pair of satellite missions even when they were operational during different periods of time. The study is particularly useful for Global Precipitation Mission (GPM) constellations for using a common precipitation retrieval algorithm.

  20. Intercomparison of retrieval algorithms for the specific surface area of snow from near-infrared satellite data in mountainous terrain, and comparison with the output of a semi-distributed snowpack model

    Directory of Open Access Journals (Sweden)

    A. Mary

    2013-04-01

    Full Text Available This study compares different methods to retrieve the specific surface area (SSA of snow from satellite radiance measurements in mountainous terrain. It aims at addressing the effect on the retrieval of topographic corrections of reflectance, namely slope and aspect of terrain, multiple reflections on neighbouring slopes and accounting (or not for the anisotropy of snow reflectance. Using MODerate resolution Imaging Spectrometer (MODIS data for six different clear sky scenes spanning a wide range of snow conditions during the winter season 2008–2009 over a domain of 46 × 50 km in the French Alps, we compared SSA retrievals with and without topographic correction, with a spherical or non-spherical snow reflectance model and, in spherical case, with or without anisotropy corrections. The retrieved SSA values were compared to field measurements and to the results of the detailed snowpack model Crocus, fed by driving data from the SAFRAN meteorological analysis. It was found that the difference in terms of surface SSA between retrieved values and SAFRAN-Crocus output was minimal when the topographic correction was taken into account, when using a retrieval method assuming disconnected spherical snow grains. In this case, the root mean square deviation was 9.4 m2 kg−1 and the mean difference was 0.1 m2 kg−1, based on 3170 pairs of observation and simulated values. The added-value of the anisotropy correction was not significant in our case, which may be explained by the presence of mixed pixels and surface roughness. MODIS retrieved data show SSA variations with elevation and aspect which are physically consistent and in good agreement with SAFRAN-Crocus outputs. The variability of the MODIS retrieved SSA within the topographic classes of the model was found to be relatively small (3.9 m2 kg−1. This indicates that semi-distributed snowpack simulations in mountainous terrain with a sufficiently large number of classes provides a

  1. Monitoring Snow Using Geostationary Satellite Retrievals During the SAAWSO Project

    Science.gov (United States)

    Rabin, Robert M.; Gultepe, Ismail; Kuligowski, Robert J.; Heidinger, Andrew K.

    2016-09-01

    The SAAWSO (Satellite Applications for Arctic Weather and SAR (Search And Rescue) Operations) field programs were conducted by Environment Canada near St. Johns, NL and Goose Bay, NL in the winters of 2012-13 and 2013-14, respectively. The goals of these programs were to validate satellite-based nowcasting products, including snow amount, wind intensity, and cloud physical parameters (e.g., cloud cover), over northern latitudes with potential applications to Search And Rescue (SAR) operations. Ground-based in situ sensors and remote sensing platforms were used to measure microphysical properties of precipitation, clouds and fog, radiation, temperature, moisture and wind profiles. Multi-spectral infrared observations obtained from Geostationary Operational Environmental Satellite (GOES)-13 provided estimates of cloud top temperature and height, phase (water, ice), hydrometer size, extinction, optical depth, and horizontal wind patterns at 15 min intervals. In this work, a technique developed for identifying clouds capable of producing high snowfall rates and incorporating wind information from the satellite observations is described. The cloud top physical properties retrieved from operational satellite observations are validated using measurements obtained from the ground-based in situ and remote sensing platforms collected during two precipitation events: a blizzard heavy snow storm case and a moderate snow event. The retrieved snow precipitation rates are found to be comparable to those of ground-based platform measurements in the heavy snow event.

  2. Satellite cloud and precipitation property retrievals for climate monitoring and hydrological applications

    Science.gov (United States)

    Wolters, E. L. A.

    2012-03-01

    This thesis presents the retrieval, evaluation, and application of cloud physical property datasets (cloud phase, cloud particle effective radius, and precipitation occurrence and intensity) obtained from Spinning Enhanced Visible and Infrared Imager (SEVIRI) reflectance measurements using the Cloud Physical Properties (CPP) retrieval algorithm. In Chapter 3 it is shown that the CPP cloud-phase retrieval algorithm has sufficient accuracy (West Africa. During the afternoon, precipitation occurrence frequency over dry soils becomes significantly higher than over wet soils, whereas for precipitation intensity no significant difference is discerned. The study demonstrates that the combination of satellite-based soil moisture and precipitation observations can be helpful in improving the understanding of the land surface-precipitation interaction over tropical areas. The thesis concludes with a number of recommendations on future algorithm improvements and potential research applications. For both cloud phase and precipitation properties, extension of the algorithm to include nighttime observations would be desirable to enable detailed studies on the full diurnal cycle. Further, the SEVIRI High-Resolution Visible (HRV) channel could be incorporated to correct retrieved cloud physical properties for broken and inhomogeneous cloud cases. Finally, the accurate cloud phase and precipitation datasets combined with the high SEVIRI spatial and temporal sampling resolution enables possibilities for detailed research on climate monitoring, nowcasting applications, evaluation of cloud schemes in climate models, studies on land surface-precipitation interactions (with a special focus on the diurnal cycle), and assimilation of the datasets in weather and climate models

  3. Retrieval of fire radiative power and biomass combustion using the Korean geostationary meteorological satellite

    Science.gov (United States)

    Kim, D. S.; Lee, Y. W.

    2013-10-01

    Global warming induced by greenhouse gases is increasing wildfire frequencies and scale. Since wildfire again releases greenhouse gases(GHGs) into the air, the vicious cycle is repeated. Satellite remote sensing is a useful tool for detecting wildfire. However, estimating the GHGs emission from wildfire has not been challenged yet. Wildfires are estimated to be responsible for, on average, around 30% of global total CO emissions, 10% of methane emissions, 38% of tropospheric ozone, and over 86% of black carbon. So we need to quantify the emitted gases by biomass combustions, which can be measured by the FRP (fire radiative power) derived from the spectral characteristics of satellite sensors. This paper described the algorithm for retrieval of FRP using COMS(Communication, Ocean and Meteorological Satellite), the Korean geostationary meteorological satellite. The FRP of wildfire is retrieved by single waveband methods suitable to COMS channels. The retrieval of FRP is dependent on the emissivity of each bandwidth. So, we used MODIS NDVI through a spatio-temporal calibration for the emissivity calculations. We made sure that the FRP in wildfire pixel is much higher than its spatially and temporally neighboring pixels. For future work, we should quantify the relationships between FRP and the biomass combustion according to fuel types.

  4. Diagnosing Aircraft Icing Potential from Satellite Cloud Retrievals

    Science.gov (United States)

    Smith, William L., Jr.; Minnis, Patrick; Fleeger, Cecilia; Spangenberg, Douglas

    2013-01-01

    The threat for aircraft icing in clouds is a significant hazard that routinely impacts aviation operations. Accurate diagnoses and forecasts of aircraft icing conditions requires identifying the location and vertical distribution of clouds with super-cooled liquid water (SLW) droplets, as well as the characteristics of the droplet size distribution. Traditional forecasting methods rely on guidance from numerical models and conventional observations, neither of which currently resolve cloud properties adequately on the optimal scales needed for aviation. Satellite imagers provide measurements over large areas with high spatial resolution that can be interpreted to identify the locations and characteristics of clouds, including features associated with adverse weather and storms. This paper describes new techniques for interpreting cloud products derived from satellite data to infer the flight icing threat to aircraft. For unobscured low clouds, the icing threat is determined using empirical relationships developed from correlations between satellite imager retrievals of liquid water path and droplet size with icing conditions reported by pilots (PIREPS). For deep ice over water cloud systems, ice and liquid water content (IWC and LWC) profiles are derived by using the imager cloud properties to constrain climatological information on cloud vertical structure and water phase obtained apriori from radar and lidar observations, and from cloud model analyses. Retrievals of the SLW content embedded within overlapping clouds are mapped to the icing threat using guidance from an airfoil modeling study. Compared to PIREPS and ground-based icing remote sensing datasets, the satellite icing detection and intensity accuracies are approximately 90% and 70%, respectively, and found to be similar for both low level and deep ice over water cloud systems. The satellite-derived icing boundaries capture the reported altitudes over 90% of the time. Satellite analyses corresponding to

  5. EOF-based regression algorithm for the fast retrieval of atmospheric CO2 total column amount from the GOSAT observations

    Science.gov (United States)

    Bril, Andrey; Maksyutov, Shamil; Belikov, Dmitry; Oshchepkov, Sergey; Yoshida, Yukio; Deutscher, Nicholas M.; Griffith, David; Hase, Frank; Kivi, Rigel; Morino, Isamu; Notholt, Justus; Pollard, David F.; Sussmann, Ralf; Velazco, Voltaire A.; Warneke, Thorsten

    2017-03-01

    This paper presents a novel retrieval algorithm for the rapid retrieval of the carbon dioxide total column amounts from high resolution spectra in the short wave infrared (SWIR) range observations by the Greenhouse gases Observing Satellite (GOSAT). The algorithm performs EOF (Empirical Orthogonal Function)-based decomposition of the measured spectral radiance and derives the relationship of limited number of the decomposition coefficients in terms of the principal components with target gas amount and a priori data such as airmass, surface pressure, etc. The regression formulae for retrieving target gas amounts are derived using training sets of collocated GOSAT and ground-based observations. The precision/accuracy characteristics of the algorithm are analyzed by the comparison of the retrievals with those from the Total Carbon Column Observing Network (TCCON) measurements and with the modeled data, and appear similar to those achieved by full-physics retrieval algorithms.

  6. The semianalytical cloud retrieval algorithm for SCIAMACHY I. The validation

    Directory of Open Access Journals (Sweden)

    A. A. Kokhanovsky

    2006-01-01

    Full Text Available A recently developed cloud retrieval algorithm for the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY is briefly presented and validated using independent and well tested cloud retrieval techniques based on the look-up-table approach for MODeration resolutIon Spectrometer (MODIS data. The results of the cloud top height retrievals using measurements in the oxygen A-band by an airborne crossed Czerny-Turner spectrograph and the Global Ozone Monitoring Experiment (GOME instrument are compared with those obtained from airborne dual photography and retrievals using data from Along Track Scanning Radiometer (ATSR-2, respectively.

  7. Global Land Surface Emissivity Retrieved From Satellite Ultraspectral IR Measurements

    Science.gov (United States)

    Zhou, D. K.; Larar, A. M.; Liu, Xu; Smith, W. L.; Strow, L. L.; Yang, Ping; Schlussel, P.; Calbet, X.

    2011-01-01

    Ultraspectral resolution infrared (IR) radiances obtained from nadir observations provide information about the atmosphere, surface, aerosols, and clouds. Surface spectral emissivity (SSE) and surface skin temperature from current and future operational satellites can and will reveal critical information about the Earth s ecosystem and land-surface-type properties, which might be utilized as a means of long-term monitoring of the Earth s environment and global climate change. In this study, fast radiative transfer models applied to the atmosphere under all weather conditions are used for atmospheric profile and surface or cloud parameter retrieval from ultraspectral and/or hyperspectral spaceborne IR soundings. An inversion scheme, dealing with cloudy as well as cloud-free radiances observed with ultraspectral IR sounders, has been developed to simultaneously retrieve atmospheric thermodynamic and surface or cloud microphysical parameters. This inversion scheme has been applied to the Infrared Atmospheric Sounding Interferometer (IASI). Rapidly produced SSE is initially evaluated through quality control checks on the retrievals of other impacted surface and atmospheric parameters. Initial validation of retrieved emissivity spectra is conducted with Namib and Kalahari desert laboratory measurements. Seasonal products of global land SSE and surface skin temperature retrieved with IASI are presented to demonstrate seasonal variation of SSE.

  8. Atmospheric correction for sea surface temperature retrieval from single thermal channel radiometer data onboard Kalpana satellite

    Indian Academy of Sciences (India)

    Naveen R Shahi; Neeraj Agarwal; Aloke K Mathur; Abhijit Sarkar

    2011-06-01

    An atmospheric correction method has been applied on sea surface temperature (SST) retrieval algorithm using Very High Resolution Radiometer (VHRR) single window channel radiance data onboard Kalpana satellite (K-SAT). The technique makes use of concurrent water vapour fields available from Microwave Imager onboard Tropical Rainfall Measuring Mission (TRMM/TMI) satellite. Total water vapour content and satellite zenith angle dependent SST retrieval algorithm has been developed using Radiative Transfer Model [MODTRAN ver3.0] simulations for Kalpana 10.5–12.5 m thermal window channel. Retrieval of Kalpana SST (K-SST) has been carried out for every half-hourly acquisition of Kalpana data for the year 2008 to cover whole annual cycle of SST over Indian Ocean (IO). Validation of the retrieved corrected SST has been carried out using near-simultaneous observations of ship and buoys datasets covering Arabian Sea, Bay of Bengal and IO regions. A significant improvement in Root Mean Square Deviation (RMSD) of K-SST with respect to buoy (1.50–1.02 K) and to ship datasets (1.41–1.19 K) is seen with the use of near real-time water vapour fields of TMI. Furthermore, comparison of the retrieved SST has also been carried out using near simultaneous observations of TRMM/TMI SST over IO regions. The analysis shows that K-SST has overall cold bias of 1.17 K and an RMSD of 1.09 K after bias correction.

  9. A novel mathematical formula for retrieval algorithm

    OpenAIRE

    2014-01-01

    A method is proposed to retrieve mathematical formula in LaTeX documents. Firstly, we represent the retrieved mathematical formula by binary tree according to its LaTeX description, normalize the structure of the binary tree, and obtain the structure code and then search the mathematical formula table that is named by the structure code and the formula elements of the first two levels of the binary tree in the mathematical formula database. If the table exists, then we search the normalizing ...

  10. Performance of the Falling Snow Retrieval Algorithms for the Global Precipitation Measurement (GPM) Mission

    Science.gov (United States)

    Skofronick-Jackson, Gail; Munchak, Stephen J.; Ringerud, Sarah

    2016-01-01

    Retrievals of falling snow from space represent an important data set for understanding the Earth's atmospheric, hydrological, and energy cycles, especially during climate change. Estimates of falling snow must be captured to obtain the true global precipitation water cycle, snowfall accumulations are required for hydrological studies, and without knowledge of the frozen particles in clouds one cannot adequately understand the energy and radiation budgets. While satellite-based remote sensing provides global coverage of falling snow events, the science is relatively new and retrievals are still undergoing development with challenges remaining). This work reports on the development and testing of retrieval algorithms for the Global Precipitation Measurement (GPM) mission Core Satellite, launched February 2014.

  11. Iterative Algorithms for Ptychographic Phase Retrieval

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Chao; Qian, Jianliang; Schirotzek, Andre; Maia, Filipe; Marchesini, Stefano

    2011-05-03

    Ptychography promises diffraction limited resolution without the need for high resolution lenses. To achieve high resolution one has to solve the phase problem for many partially overlapping frames. Here we review some of the existing methods for solving ptychographic phase retrieval problem from a numerical analysis point of view, and propose alternative methods based on numerical optimization.

  12. Total ozone retrieval from satellite multichannel filter radiometer measurements

    Energy Technology Data Exchange (ETDEWEB)

    Lovill, J.E.; Sullivan, T.J.; Weichel, R.L.; Ellis, J.S.; Huebel, J.G.; Korver, J.; Weidhaas, P.P.; Phelps, F.A.

    1978-05-25

    A total ozone retrieval model has been developed to process radiance data gathered by a satellite-mounted multichannel filter radiometer (MFR). Extensive effort went into theoretical radiative transfer modeling, a retrieval scheme was developed, and the technique was applied to the MFR radiance measurements. The high quality of the total ozone retrieval results was determined through comparisons with Dobson measurements. Included in the report are global total ozone maps for 20 days between May 12 and July 5, 1977. A comparison of MFR results for 13 days in June 1977 with Dobson spectrophotometer measurements of ozone for the same period showed good agreement: there was a root-mean-square difference of 6.2% (equivalent to 20.2 m.atm.cm). The estimated global total ozone value for June 1977 (296 m.atm.cm) was in good agreement with satellite backscatter ultraviolet data for June 1970 (304 m.atm.cm) and June 1971 (preliminary data--299 m.atm.cm).

  13. A surface reflectance scheme for retrieving aerosol optical depth over urban surfaces in MODIS Dark Target retrieval algorithm

    Science.gov (United States)

    Gupta, Pawan; Levy, Robert C.; Mattoo, Shana; Remer, Lorraine A.; Munchak, Leigh A.

    2016-07-01

    The MODerate resolution Imaging Spectroradiometer (MODIS) instruments, aboard the two Earth Observing System (EOS) satellites Terra and Aqua, provide aerosol information with nearly daily global coverage at moderate spatial resolution (10 and 3 km). Almost 15 years of aerosol data records are now available from MODIS that can be used for various climate and air-quality applications. However, the application of MODIS aerosol products for air-quality concerns is limited by a reduction in retrieval accuracy over urban surfaces. This is largely because the urban surface reflectance behaves differently than that assumed for natural surfaces. In this study, we address the inaccuracies produced by the MODIS Dark Target (MDT) algorithm aerosol optical depth (AOD) retrievals over urban areas and suggest improvements by modifying the surface reflectance scheme in the algorithm. By integrating MODIS Land Surface Reflectance and Land Cover Type information into the aerosol surface parameterization scheme for urban areas, much of the issues associated with the standard algorithm have been mitigated for our test region, the continental United States (CONUS). The new surface scheme takes into account the change in underlying surface type and is only applied for MODIS pixels with urban percentage (UP) larger than 20 %. Over the urban areas where the new scheme has been applied (UP > 20 %), the number of AOD retrievals falling within expected error (EE %) has increased by 20 %, and the strong positive bias against ground-based sun photometry has been eliminated. However, we note that the new retrieval introduces a small negative bias for AOD values less than 0.1 due to the ultra-sensitivity of the AOD retrieval to the surface parameterization under low atmospheric aerosol loadings. Global application of the new urban surface parameterization appears promising, but further research and analysis are required before global implementation.

  14. An operational retrieval algorithm for determining aerosol optical properties in the ultraviolet

    Science.gov (United States)

    Taylor, Thomas E.; L'Ecuyer, Tristan S.; Slusser, James R.; Stephens, Graeme L.; Goering, Christian D.

    2008-02-01

    This paper describes a number of practical considerations concerning the optimization and operational implementation of an algorithm used to characterize the optical properties of aerosols across part of the ultraviolet (UV) spectrum. The algorithm estimates values of aerosol optical depth (AOD) and aerosol single scattering albedo (SSA) at seven wavelengths in the UV, as well as total column ozone (TOC) and wavelength-independent asymmetry factor (g) using direct and diffuse irradiances measured with a UV multifilter rotating shadowband radiometer (UV-MFRSR). A novel method for cloud screening the irradiance data set is introduced, as well as several improvements and optimizations to the retrieval scheme which yield a more realistic physical model for the inversion and increase the efficiency of the algorithm. Introduction of a wavelength-dependent retrieval error budget generated from rigorous forward model analysis as well as broadened covariances on the a priori values of AOD, SSA and g and tightened covariances of TOC allows sufficient retrieval sensitivity and resolution to obtain unique solutions of aerosol optical properties as demonstrated by synthetic retrievals. Analysis of a cloud screened data set (May 2003) from Panther Junction, Texas, demonstrates that the algorithm produces realistic values of the optical properties that compare favorably with pseudo-independent methods for AOD, TOC and calculated Ångstrom exponents. Retrieval errors of all parameters (except TOC) are shown to be negatively correlated to AOD, while the Shannon information content is positively correlated, indicating that retrieval skill improves with increasing atmospheric turbidity. When implemented operationally on more than thirty instruments in the Ultraviolet Monitoring and Research Program's (UVMRP) network, this retrieval algorithm will provide a comprehensive and internally consistent climatology of ground-based aerosol properties in the UV spectral range that can be used

  15. Evaluating cloud precipitation efficiency with satellite retrievals of water isotopologues

    Science.gov (United States)

    Bailey, A.; Noone, D. C.; Wood, R.

    2015-12-01

    The efficiency with which clouds precipitate is believed to influence climate by modifying cloud lifetime and, ultimately, cloud amount. Aerosols can influence this linkage by reducing the effective radii of cloud droplets and suppressing precipitation. This relationship, however, is not unidirectional. Cloud precipitation efficiency can also regulate particle concentrations, since precipitation effectively scavenges aerosols from the atmosphere. One challenge in studying how aerosols, clouds, and precipitation processes interrelate is that observational constraints are difficult to attain. This work evaluates the ability of isotope ratios in water vapor to quantify cloud precipitation efficiency across the tropical and subtropical oceans. Theory suggests isotope ratios will record the precipitation efficiency of a convective plume, since heavier isotopologues precipitate preferentially; and a recent analysis of in situ measurements from the Mauna Loa Observatory (MLO, Hawaii, USA) verifies this to be the case. The challenge now lies in understanding whether satellite retrievals of isotope ratios in water vapor are sensitive enough to track precipitation efficiency globally. To answer this question, vertical profiles of the D/H ratio derived from NASA's Tropospheric Emission Spectrometer (TES) are first compared with the MLO in situ measurements. A qualitative match indicates the satellite retrievals can distinguish high from low precipitation efficiency convection. To expand the analysis geographically, TES profiles between 40°S and 40°N are compared with estimates of precipitation efficiency derived from the Tropical Rainfall Measuring Mission (TRMM) and ECMWF's ERA-Interim. Retrievals are binned by lower-tropospheric humidity and by vertical velocity in order to minimize large-scale thermodynamical influences. Co-located cloud retrievals provide the context necessary to evaluate the utility of these new estimates in elucidating cloud feedbacks on climate.

  16. Structural uncertainty in air mass factor calculation for NO2 and HCHO satellite retrievals

    Science.gov (United States)

    Lorente, Alba; Folkert Boersma, K.; Yu, Huan; Dörner, Steffen; Hilboll, Andreas; Richter, Andreas; Liu, Mengyao; Lamsal, Lok N.; Barkley, Michael; De Smedt, Isabelle; Van Roozendael, Michel; Wang, Yang; Wagner, Thomas; Beirle, Steffen; Lin, Jin-Tai; Krotkov, Nickolay; Stammes, Piet; Wang, Ping; Eskes, Henk J.; Krol, Maarten

    2017-03-01

    Air mass factor (AMF) calculation is the largest source of uncertainty in NO2 and HCHO satellite retrievals in situations with enhanced trace gas concentrations in the lower troposphere. Structural uncertainty arises when different retrieval methodologies are applied within the scientific community to the same satellite observations. Here, we address the issue of AMF structural uncertainty via a detailed comparison of AMF calculation methods that are structurally different between seven retrieval groups for measurements from the Ozone Monitoring Instrument (OMI). We estimate the escalation of structural uncertainty in every sub-step of the AMF calculation process. This goes beyond the algorithm uncertainty estimates provided in state-of-the-art retrievals, which address the theoretical propagation of uncertainties for one particular retrieval algorithm only. We find that top-of-atmosphere reflectances simulated by four radiative transfer models (RTMs) (DAK, McArtim, SCIATRAN and VLIDORT) agree within 1.5 %. We find that different retrieval groups agree well in the calculations of altitude resolved AMFs from different RTMs (to within 3 %), and in the tropospheric AMFs (to within 6 %) as long as identical ancillary data (surface albedo, terrain height, cloud parameters and trace gas profile) and cloud and aerosol correction procedures are being used. Structural uncertainty increases sharply when retrieval groups use their preference for ancillary data, cloud and aerosol correction. On average, we estimate the AMF structural uncertainty to be 42 % over polluted regions and 31 % over unpolluted regions, mostly driven by substantial differences in the a priori trace gas profiles, surface albedo and cloud parameters. Sensitivity studies for one particular algorithm indicate that different cloud correction approaches result in substantial AMF differences in polluted conditions (5 to 40 % depending on cloud fraction and cloud pressure, and 11 % on average) even for low

  17. Uncertainty characterization of AOD for the AATSR dual and single view retrieval algorithms

    Directory of Open Access Journals (Sweden)

    P. Kolmonen

    2013-04-01

    Full Text Available The uncertainty associated with satellite-retrieved aerosol properties is needed when these data are used to constrain chemical transport or climate models by using data assimilation. Global uncertainty as provided by comparison with independent ground-based observations is usually not adequate for that purpose. Rather the per-pixel uncertainty is needed. In this work we describe how these are determined in the AATSR dual and single view aerosol retrieval algorithms (ADV and ASV which are used to retrieve aerosol optical properties from reflectance measured at the top of the atmosphere. AATSR is the Aerosol Along-Track Scanning Radiometer which flies on the European Space Agency Environmental Satellite ENVISAT. In addition, issues related to multi-year retrievals are described and discussed. The aerosol optical depth (AOD retrieved for the year 2008 is validated versus ground-based AERONET sun photometer measurements with good agreement (r = 0.85. The comparison of the AOD uncertainties with those provided by AERONET shows that they behave well in a statistical sense. Other considerations regarding global multi-year aerosol retrievals are presented and discussed.

  18. An enhanced single-channel algorithm for retrieving land surface temperature from Landsat series data

    Science.gov (United States)

    Wang, Mengmeng; Zhang, Zhaoming; He, Guojin; Wang, Guizhou; Long, Tengfei; Peng, Yan

    2016-10-01

    Land surface temperature (LST) is a critical parameter in the physics of Earth surface processes and is required for many applications related to ecology and environment. Landsat series satellites have provided more than 30 years of thermal information at medium spatial resolution. This paper proposes an enhanced single-channel algorithm (SCen) for retrieving LST from Landsat series data (Landsat 4 to Landsat 8). The SCen algorithm includes three atmospheric functions (AFs), and the latitude and acquisition month of Landsat image were added to the AF models to improve LST retrieval. Performance of the SCen algorithm was assessed with both simulated and in situ data, and accuracy of three single-channel algorithms (including the monowindow algorithm developed by Qin et al., SCQin, and the generalized single-channel algorithm developed by Jiménez-Muñoz and Sobrino, SCJ&S) were compared. The accuracy assessments with simulated data had root-mean-square deviations (RMSDs) for the SCen, SCJ&S, and SCQin algorithms of 1.363 K, 1.858 K, and 2.509 K, respectively. Validation with in situ data showed RMSDs for the SCen and SCJ&S algorithms of 1.04 K and 1.49 K, respectively. It was concluded that the SCen algorithm is very operational, has good precision, and can be used to develop an LST product for Landsat series data.

  19. FRESCO+: an improved O2 A-band cloud retrieval algorithm for tropospheric trace gas retrievals

    Directory of Open Access Journals (Sweden)

    M. van Roozendael

    2008-11-01

    Full Text Available The FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A-band algorithm has been used to retrieve cloud information from measurements of the O2 A-band around 760 nm by GOME, SCIAMACHY and GOME-2. The cloud parameters retrieved by FRESCO are the effective cloud fraction and cloud pressure, which are used for cloud correction in the retrieval of trace gases like O3 and NO2. To improve the cloud pressure retrieval for partly cloudy scenes, single Rayleigh scattering has been included in an improved version of the algorithm, called FRESCO+. We compared FRESCO+ and FRESCO effective cloud fractions and cloud pressures using simulated spectra and one month of GOME measured spectra. As expected, FRESCO+ gives more reliable cloud pressures over partly cloudy pixels. Simulations and comparisons with ground-based radar/lidar measurements of clouds show that the FRESCO+ cloud pressure is about the optical midlevel of the cloud. Globally averaged, the FRESCO+ cloud pressure is about 50 hPa higher than the FRESCO cloud pressure, while the FRESCO+ effective cloud fraction is about 0.01 larger. The effect of FRESCO+ cloud parameters on O3 and NO2 vertical column density (VCD retrievals is studied using SCIAMACHY data and ground-based DOAS measurements. We find that the FRESCO+ algorithm has a significant effect on tropospheric NO2 retrievals but a minor effect on total O3 retrievals. The retrieved SCIAMACHY tropospheric NO2 VCDs using FRESCO+ cloud parameters (v1.1 are lower than the tropospheric NO2VCDs which used FRESCO cloud parameters (v1.04, in particular over heavily polluted areas with low clouds. The difference between SCIAMACHY tropospheric NO2 VCDs v1.1 and ground-based MAXDOAS measurements performed in Cabauw, The Netherlands, during the DANDELIONS campaign is about −2.12×1014molec cm−2.

  20. The SMOS ocean salinity retrieval algorithm

    Science.gov (United States)

    Font, J.

    2009-04-01

    SMOS (Soil Moisture and Ocean Salinity) will be, from spring 2009, the first space mission attempting the determination of sea surface salinity using microwave L-band radiometry. The SMOS aperture synthesis technique poses strict requirements to instrument calibration and stability for a successful brightness temperature image reconstruction. Besides this, the low sensitivity of Tb to salinity, even at L-band, and the still not fully developed/validated emissivity models at this frequency taking into account all the physical processes that impact on it, mainly the effects of surface roughness, plus the need of removing from the recorded signal the contributions of scattered radiation from external sources (sun, galaxy) result in a really challenging salinity determination by SMOS. In this presentation we review the approach implemented in SMOS for salinity retrieval from the calibrated brightness temperature maps. The different processing steps are summarily described, as well as their implementation status and validation in the SMOS level 2 salinity processor.

  1. Web Structure Mining: Exploring Hyperlinks and Algorithms for Information Retrieval

    Directory of Open Access Journals (Sweden)

    P. R. Kumar

    2010-01-01

    Full Text Available Problem statement: A study on hyperlink analysis and the algorithms used for link analysis in the Web Information retrieval was done. Approach: This research was initiated because of the dependability of search engines for information retrieval in the web. Understand the web structure mining and determine the importance of hyperlink in web information retrieval particularly using the Google Search engine. Hyperlink analysis was important methodology used by famous search engine Google to rank the pages. Results: The different algorithms used for link analysis like PageRank (PR, Weighted PageRank (WPR and Hyperlink-Induced Topic Search (HITS algorithms are discussed and compared. PageRank algorithm was implemented using a Java program and the convergence of the PageRank values are shown in a chart form. Conclusion: This study was done basically to explore the link structure algorithms for ranking and compare those algorithms. The further research on this area will be problems facing PageRank algorithm and how to handle those problems.

  2. Retrieving the Height of Smoke and Dust Aerosols by Synergistic Use of Multiple Satellite Sensors

    Science.gov (United States)

    Lee, Jaehwa; Hsu, N. Christina; Bettenhausen, Corey; Sayer, Andrew M.; Seftor, Colin J.; Jeong, Myeong-Jae

    2016-01-01

    The Aerosol Single scattering albedo and Height Estimation (ASHE) algorithm was first introduced in Jeong and Hsu (2008) to provide aerosol layer height and single scattering albedo (SSA) for biomass burning smoke aerosols. By using multiple satellite sensors synergistically, ASHE can provide the height information over much broader areas than lidar observations alone. The complete ASHE algorithm uses aerosol data from MODIS or VIIRS, OMI or OMPS, and CALIOP. A simplified algorithm also exists that does not require CALIOP data as long as the SSA of the aerosol layer is provided by another source. Several updates have recently been made: inclusion of dust layers in the retrieval process, better determination of the input aerosol layer height from CALIOP, improvement in aerosol optical depth (AOD) for nonspherical dust, development of quality assurance (QA) procedure, etc.

  3. Using radiance of cloud shadow for retrieve Investigation of AOD retrieval with Himawari-8 satellite data

    Science.gov (United States)

    Sun, Ta-Min; Chang, Yuan-Hsiang; Chang, Kuo-En; Lin, Tang-Huang

    2016-04-01

    As we know, the emission of pollutants, such as dust storm, biomass burning and anthropogenic pollution are serious issues related to the environmental change and human health topics in Asia. With the high temporal observation over a broad area, the new generated geostationary satellite, Himawari-8 (H-8) seems to be a good choice for atmospheric pollution monitor. It can provide the observation over Asia with 16 bands in visible and thermal infrared spectral every 10 minutes. For the atmospheric pollutant monitor by means of remote sensing, the retrieval of aerosol optical depth (AOD) is the most important index. In this study, the long method is employed for AOD retrieval which depends on the path radiance significantly. Apparent radiance of the suitable cloud shadow is selected as the path radiance. In order to let the atmospheric pollution monitor is used efficiently, so the distribution of the path radiance is using the objective analysis to expand it. The results of AOD retrieval from H-8 visible data are well consistent with MODIS (Moderate Resolution Imaging Spectroradiometer) AOD products and ground measurements AERONET (Aerosol Robotic Networks), indicating the practical of proposed approach for the AOD retrieval with H-8 data.

  4. Spatio-temporal multi-modality ontology for indexing and retrieving satellite images

    OpenAIRE

    MESSOUDI, Wassim; FARAH, Imed Riadh; SAHEB ETTABAA, Karim; Ben Ghezala, Henda; SOLAIMAN, Basel

    2009-01-01

    International audience; This paper presents spatio-temporal multi-modality ontology for indexing and retrieving satellite images in the high level to improve the quality of the system retrieval and to perform semantic in the retrieval process.Our approach is based on three modules: (1) regions and features extraction, (2) ontological indexing and (3) semantic image retrieval. The first module allows extracting regions from the satellite image using the fuzzy c-means FCM) segmentation algorith...

  5. Using Satellite Aerosol Retrievals to Monitor Surface Particulate Air Quality

    Science.gov (United States)

    Levy, Robert C.; Remer, Lorraine A.; Kahn, Ralph A.; Chu, D. Allen; Mattoo, Shana; Holben, Brent N.; Schafer, Joel S.

    2011-01-01

    The MODIS and MISR aerosol products were designed nearly two decades ago for the purpose of climate applications. Since launch of Terra in 1999, these two sensors have provided global, quantitative information about column-integrated aerosol properties, including aerosol optical depth (AOD) and relative aerosol type parameters (such as Angstrom exponent). Although primarily designed for climate, the air quality (AQ) community quickly recognized that passive satellite products could be used for particulate air quality monitoring and forecasting. However, AOD and particulate matter (PM) concentrations have different units, and represent aerosol conditions in different layers of the atmosphere. Also, due to low visible contrast over brighter surface conditions, satellite-derived aerosol retrievals tend to have larger uncertainty in urban or populated regions. Nonetheless, the AQ community has made significant progress in relating column-integrated AOD at ambient relative humidity (RH) to surface PM concentrations at dried RH. Knowledge of aerosol optical and microphysical properties, ambient meteorological conditions, and especially vertical profile, are critical for physically relating AOD and PM. To make urban-scale maps of PM, we also must account for spatial variability. Since surface PM may vary on a finer spatial scale than the resolution of standard MODIS (10 km) and MISR (17km) products, we test higher-resolution versions of MODIS (3km) and MISR (1km research mode) retrievals. The recent (July 2011) DISCOVER-AQ campaign in the mid-Atlantic offers a comprehensive network of sun photometers (DRAGON) and other data that we use for validating the higher resolution satellite data. In the future, we expect that the wealth of aircraft and ground-based measurements, collected during DISCOVER-AQ, will help us quantitatively link remote sensed and ground-based measurements in the urban region.

  6. A unified evaluation of iterative projection algorithms for phase retrieval

    Energy Technology Data Exchange (ETDEWEB)

    Marchesini, S

    2006-03-08

    Iterative projection algorithms are successfully being used as a substitute of lenses to recombine, numerically rather than optically, light scattered by illuminated objects. Images obtained computationally allow aberration-free diffraction-limited imaging and allow new types of imaging using radiation for which no lenses exist. The challenge of this imaging technique is transferred from the lenses to the algorithms. We evaluate these new computational ''instruments'' developed for the phase retrieval problem, and discuss acceleration strategies.

  7. Feature Selection for Image Retrieval based on Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Preeti Kushwaha

    2016-12-01

    Full Text Available This paper describes the development and implementation of feature selection for content based image retrieval. We are working on CBIR system with new efficient technique. In this system, we use multi feature extraction such as colour, texture and shape. The three techniques are used for feature extraction such as colour moment, gray level co- occurrence matrix and edge histogram descriptor. To reduce curse of dimensionality and find best optimal features from feature set using feature selection based on genetic algorithm. These features are divided into similar image classes using clustering for fast retrieval and improve the execution time. Clustering technique is done by k-means algorithm. The experimental result shows feature selection using GA reduces the time for retrieval and also increases the retrieval precision, thus it gives better and faster results as compared to normal image retrieval system. The result also shows precision and recall of proposed approach compared to previous approach for each image class. The CBIR system is more efficient and better performs using feature selection based on Genetic Algorithm.

  8. Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters.

    Science.gov (United States)

    Wang, Jiao; Deng, Zhiqiang

    2017-06-01

    A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82-90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.

  9. Earth Observation Satellites Scheduling Based on Decomposition Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Feng Yao

    2010-11-01

    Full Text Available A decomposition-based optimization algorithm was proposed for solving Earth Observation Satellites scheduling problem. The problem was decomposed into task assignment main problem and single satellite scheduling sub-problem. In task assignment phase, the tasks were allocated to the satellites, and each satellite would schedule the task respectively in single satellite scheduling phase. We adopted an adaptive ant colony optimization algorithm to search the optimal task assignment scheme. Adaptive parameter adjusting strategy and pheromone trail smoothing strategy were introduced to balance the exploration and the exploitation of search process. A heuristic algorithm and a very fast simulated annealing algorithm were proposed to solve the single satellite scheduling problem. The task assignment scheme was valued by integrating the observation scheduling result of multiple satellites. The result was responded to the ant colony optimization algorithm, which can guide the search process of ant colony optimization. Computation results showed that the approach was effective to the satellites observation scheduling problem.

  10. Text Classification Retrieval Based on Complex Network and ICA Algorithm

    Directory of Open Access Journals (Sweden)

    Hongxia Li

    2013-08-01

    Full Text Available With the development of computer science and information technology, the library is developing toward information and network. The library digital process converts the book into digital information. The high-quality preservation and management are achieved by computer technology as well as text classification techniques. It realizes knowledge appreciation. This paper introduces complex network theory in the text classification process and put forwards the ICA semantic clustering algorithm. It realizes the independent component analysis of complex network text classification. Through the ICA clustering algorithm of independent component, it realizes character words clustering extraction of text classification. The visualization of text retrieval is improved. Finally, we make a comparative analysis of collocation algorithm and ICA clustering algorithm through text classification and keyword search experiment. The paper gives the clustering degree of algorithm and accuracy figure. Through simulation analysis, we find that ICA clustering algorithm increases by 1.2% comparing with text classification clustering degree. Accuracy can be improved by 11.1% at most. It improves the efficiency and accuracy of text classification retrieval. It also provides a theoretical reference for text retrieval classification of eBook

  11. Study of phase retrieval algorithm from partially coherent light

    Science.gov (United States)

    Yan, Liu; Hong, Cheng; Wei, Sui; Wei, Zhang

    2014-11-01

    The goal of phase retrieval is to recover the phase information from intensity distribution which is an important topic in optics and image processing. The algorithm based on the transport of intensity equation only need to measure the spatial intensity of the center plane and adjacent light field plane, and reconstruct the phase object by solving second order differential equations. The algorithm is derived in the coherent light field. And the partially coherent light field is described more complex. The field at any point in the space experiences statistical fluctuations over time. Therefore, traditional TIE algorithms cannot be applied in calculating the phase of partially coherent light field. In this thesis, the phase retrieval algorithm is proposed for partially coherent light field. First, the description and propagation equation of partially coherent light field is established. Then, the phase is retrieved by TIE Fourier transform. Experimental results with simulated uniform and non-uniform illumination demonstrate the effectiveness of the proposed method in phase retrieval for partially coherent light field.

  12. Retrieval of macrophysical cloud parameters from MIPAS: algorithm description

    Directory of Open Access Journals (Sweden)

    J. Hurley

    2011-04-01

    Full Text Available The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS onboard ENVISAT has the potential to be particularly useful for studying high, thin clouds, which have been difficult to observe in the past. This paper details the development, implementation and testing of an optimal-estimation-type retrieval for three macrophysical cloud parameters (cloud top height, cloud top temperature and cloud extinction coefficient from infrared spectra measured by MIPAS. A preliminary estimation of a parameterisation of the optical and geometrical filling of the measurement field-of-view by cloud is employed as the first step of the retrieval process to improve the choice of a priori for the macrophysical parameters themselves.

    Preliminary application to single-scattering simulations indicates that the retrieval error stemming from uncertainties introduced by noise and by a priori variances in the retrieval process itself is small – although it should be noted that these retrieval errors do not include the significant errors stemming from the assumption of homogeneity and the non-scattering nature of the forward model. Such errors are preliminarily and qualitatively assessed here, and are likely to be the dominant error sources. The retrieval converges for 99% of input cases, although sometimes fails to converge for vetically-thin (<1 km clouds. The retrieval algorithm is applied to MIPAS data; the results of which are qualitatively compared with CALIPSO cloud top heights and PARASOL cloud opacities. From comparison with CALIPSO cloud products, it must be noted that the cloud detection method used in this algorithm appears to potentially misdetect stratospheric aerosol layers as cloud.

    This algorithm has been adopted by the European Space Agency's "MIPclouds" project.

  13. Retrievals of Falling Snow from Satellite-borne Active and Passive Sensors

    Science.gov (United States)

    Jackson, Gail; Munchak, S. Joseph; Johnson, Benjamin

    2014-05-01

    Precipitation, including rain and snow, is a critical part of the Earth's energy and hydrology cycles. Precipitation impacts latent heating profiles locally while global circulation patterns distribute precipitation and energy from the equator to the poles. For the hydrological cycle, falling snow is a primary contributor in northern latitudes during the winter seasons. Falling snow is the source of snow pack accumulations that provide fresh water resources for many communities in the world. Furthermore, falling snow impacts society by causing transportation disruptions during severe snow events. In order to collect information on the complete global precipitation cycle, both liquid and frozen precipitation must be collected. The Global Precipitation Measurement (GPM) mission's Core satellite, scheduled for launch in February 2014, is well designed to detect and estimate falling snow. The GPM core carries a passive radiometer with frequencies (10-183 GHz) and an active radar with Ku- and Ka-band frequencies. Combined with the 65o inclination of the GPM Core satellite, these instruments allow for the GPM Core to sense and retrieve information about falling snow and light rain in regions of the earth where snow is common. The GPM Core's comprehensive active and passive channel set will also allow it to serve as a unifying reference for GPM constellation radiometer satellites. Since falling snow from space is the next precipitation measurement challenge from space, information is needed to guide retrieval algorithm development for these current and future missions. This information includes thresholds of detection for various sensor channel configurations, sensitivity to macroscale snow event system characteristics, and sensitivity to microscale snowflake particle characteristics. While the work in this area will continue for many years to come, our group has made substantial progress in this area by identifying minimum detectable melted rates of ~0.5 mm hr-1. Results

  14. Day 1 and Beyond for Multi-satellite Retrievals in GPM (Invited)

    Science.gov (United States)

    Huffman, G. J.; Bolvin, D.; Braithwaite, D.; Hsu, K.; Joyce, R.; Kidd, C.; Sorooshian, S.; Xie, P.

    2013-12-01

    Merged multi-satellite estimates of precipitation constitute one of the key goals of the Global Precipitation Measurement (GPM) mission. These allow users access to quasi-global precipitation estimates at relatively fine time/space scales without detailed knowledge of satellites, sensors, or algorithms. The Integrated Multi-satellitE Retrievals for GPM (IMERG) algorithm will provide the at-launch combined-satellite precipitation dataset being produced by the U.S. GPM Science Team. This talk will review IMERG's development as a unified U.S. algorithm that takes advantage of strengths in three current U.S. algorithms, namely the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), CPC Morphing algorithm with Kalman Filtering (KF-CMORPH), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS). The goal is to provide a long-term, fine-scale record of global precipitation from the entire constellation of precipitation-relevant satellite sensors, with input from surface precipitation gauges as feasible. The record will begin January 1998 corresponding with the start of the TRMM and extend as GPM records additional data. Although homogeneity is considered desirable, the use of diverse and evolving data sources works against the strict long-term homogeneity that characterizes a Climate Data Record (CDR). We plan to compute multiple runs at different latencies (most likely around 4 hours, 12 hours, and 2 months after observation time) to address the needs of different groups of users. We will describe the current focus of bringing up the Day-1 IMERG in the Precipitation Processing System using TRMM-based calibration until the GPM sensor algorithms finish check-out in 2014, and then transition to GPM-based calibration after that. However, at the same time we are looking ahead to the next challenges for Day 2 and beyond. This talk will briefly

  15. An algorithm for retrieving fine and coarse aerosol microphysical properties from AERONET-type photopolarimetric measurements

    Science.gov (United States)

    Xu, X.; Wang, J.; Zeng, J.; Spurr, R. J. D.; Liu, X.; Dubovik, O.; Li, Z.; Li, L.; Holben, B. N.; Mishchenko, M. I.

    2014-12-01

    A new retrieval algorithm has been developed to retrieve both fine and coarse modal aerosol properties from multi-spectral and multi-angular solar polarimetric radiation fields such as those measured by the AErosol RObotic NETwork (AERONET) but with additional channels of polarization observations (hereafter AEROENT-type measurements). Most AERONET sites lack the capability to measure light polarization, though a few measure polarization only at 870 nm. From both theory and real cases, we show that adding multi-spectral polarization data can allow a mode-resolved inversion of aerosol microphysical parameters. In brief, the retrieval algorithm incorporates AERONET-type measurements in conjunction with advanced vector radiative transfer model specifically designed for studying the inversion problems in aerosol remote sensing. It retrieves aerosol parameters associated to a bi-lognormal particle size distribution (PSD) including aerosol volume concentrations, effective radius and variance, and complex indices of aerosol refraction. Our algorithm differs from the current AERONET inversion algorithm in two major aspects. First, it retrieves effective radius and variance and total volume by assuming a bi-modal lognormal PSD, while AERONET one retrieves aerosol volumes of 22 size bins. Second, our algorithm retrieves spectral refractive indices for both fine and coarse modes. Mode-resolved refractive indices can improve the estimate of single scattering albedo (SSA) for each mode, which also benefits the evaluation for satellite products and chemistry transport models. While bi-lognormal PSD can well represent aerosol size spectrum in most cases, future research efforts will include implementation for tri-modal aerosol mixtures in situations of cloud-formation or volcanic aerosols. Applying the algorithm to a suite of real cases over Beijing_RADI site, we found that our retrievals are overall consistent with AERONET inversion products, but can offer mode

  16. Early Examples from the Integrated Multi-Satellite Retrievals for GPM (IMERG)

    Science.gov (United States)

    Huffman, George; Bolvin, David; Braithwaite, Daniel; Hsu, Kuolin; Joyce, Robert; Kidd, Christopher; Sorooshian, Soroosh; Xie, Pingping

    2014-05-01

    The U.S. GPM Science Team's Day-1 algorithm for computing combined precipitation estimates as part of GPM is the Integrated Multi-satellitE Retrievals for GPM (IMERG). The goal is to compute the best time series of (nearly) global precipitation from "all" precipitation-relevant satellites and global surface precipitation gauge analyses. IMERG is being developed as a unified U.S. algorithm drawing on strengths in the three contributing groups, whose previous work includes: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA); 2) the CPC Morphing algorithm with Kalman Filtering (K-CMORPH); and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS). We review the IMERG design and development, plans for testing, and current status. Some of the lessons learned in running and reprocessing the previous data sets include the importance of quality-controlling input data sets, strategies for coping with transitions in the various input data sets, and practical approaches to retrospective analysis of multiple output products (namely the real- and post-real-time data streams). IMERG output will be illustrated using early test data, including the variety of supporting fields, such as the merged-microwave and infrared estimates, and the precipitation type. We end by considering recent changes in input data specifications, the transition from TRMM-based calibration to GPM-based, and further "Day 2" development.

  17. PM-GCD - a combined IR-MW satellite technique for frequent retrieval of heavy precipitation

    Science.gov (United States)

    Casella, D.; Dietrich, S.; di Paola, F.; Formenton, M.; Mugnai, A.; Porcù, F.; Sanò, P.

    2012-01-01

    Precipitation retrievals based on measurements from microwave (MW) radiometers onboard low-Earth-orbit (LEO) satellites can reach high level of accuracy - especially regarding convective precipitation. At the present stage though, these observations cannot provide satisfactory coverage of the evolution of intense and rapid precipitating systems. As a result, the obtained precipitation retrievals are often of limited use for many important applications - especially in supporting authorities for flood alerts and weather warnings. To tackle this problem, over the past two decades several techniques have been developed combining accurate MW estimates with frequent infrared (IR) observations from geosynchronous (GEO) satellites, such as the European Meteosat Second Generation (MSG). In this framework, we have developed a new fast and simple precipitation retrieval technique which we call Passive Microwave - Global Convective Diagnostic, (PM-GCD). This method uses MW retrievals in conjunction with the Global Convective Diagnostic (GCD) technique which discriminates deep convective clouds based on the difference between the MSG water vapor (6.2 μm) and thermal-IR (10.8 μm) channels. Specifically, MSG observations and the GCD technique are used to identify deep convective areas. These areas are then calibrated using MW precipitation estimates based on observations from the Advanced Microwave Sounding Unit (AMSU) radiometers onboard operational NOAA and Eumetsat satellites, and then finally propagated in time with a simple tracking algorithm. In this paper, we describe the PM-GCD technique, analyzing its results for a case study that refers to a flood event that struck the island of Sicily in southern Italy on 1-2 October 2009.

  18. An improved NO2 retrieval for the GOME-2 satellite instrument

    Directory of Open Access Journals (Sweden)

    J. P. Burrows

    2011-01-01

    Full Text Available Satellite observations of nitrogen dioxide (NO2 provide valuable information on both stratospheric and tropospheric composition. Nadir measurements from GOME, SCIAMACHY, OMI, and GOME-2 have been used in many studies on tropospheric NO2 burdens, the importance of different NOx emissions sources and their change over time. The observations made by the three GOME-2 instruments will extend the existing data set by more than a decade, and a high quality of the data as well as their good consistency with existing time series is of high importance. In this paper, an improved GOME-2 NO2 retrieval is described which reduces the scatter of the individual NO2 columns globally but in particular in the region of the Southern Atlantic Anomaly. This is achieved by using a larger fitting window including more spectral points, and by applying a two step spike removal algorithm in the fit. The new GOME-2 data set is shown to have good consistency with SCIAMACHY NO2 columns. Remaining small differences are shown to be linked to changes in the daily solar irradiance measurements used in both GOME-2 and SCIAMACHY retrievals. In the large retrieval window, a not previously identified spectral signature was found which is linked to deserts and other regions with bare soil. Inclusion of this empirically derived pseudo cross-section significantly improves the retrievals and potentially provides information on surface properties and desert aerosols. Using the new GOME-2 NO2 data set, a long-term average of tropospheric columns was computed and high-pass filtered. The resulting map shows evidence for pollution from several additional shipping lanes, not previously identified in satellite observations. This illustrates the excellent signal to noise ratio achievable with the improved GOME-2 retrievals.

  19. Aquarius Salinity Retrieval Algorithm: Final Pre-Launch Version

    Science.gov (United States)

    Wentz, Frank J.; Le Vine, David M.

    2011-01-01

    This document provides the theoretical basis for the Aquarius salinity retrieval algorithm. The inputs to the algorithm are the Aquarius antenna temperature (T(sub A)) measurements along with a number of NCEP operational products and pre-computed tables of space radiation coming from the galaxy and sun. The output is sea-surface salinity and many intermediate variables required for the salinity calculation. This revision of the Algorithm Theoretical Basis Document (ATBD) is intended to be the final pre-launch version.

  20. Exploiting the sensitivity of two satellite cloud height retrievals to cloud vertical distribution

    Directory of Open Access Journals (Sweden)

    C. K. Carbajal Henken

    2015-03-01

    Full Text Available This work presents a study on the sensitivity of two satellite cloud height retrievals to cloud vertical distribution. The difference in sensitivity is exploited by relating the difference in the retrieved cloud heights to cloud vertical extent. The two cloud height retrievals, performed within the Freie Universität Berlin AATSR MERIS Cloud (FAME-C algorithm, are based on independent measurements and different retrieval techniques. First, cloud top temperature (CTT is retrieved from Advanced Along Track Scanning Radiometer (AATSR measurements in the thermal infrared. Second, cloud top pressure (CTP is retrieved from Medium Resolution Imaging Spectrometer (MERIS measurements in the oxygen-A absorption band. Both CTT and CTP are converted to cloud top height (CTH using atmospheric profiles from a numerical weather prediction model. A sensitivity study using radiative transfer simulations in the near-infrared and thermal infrared were performed to demonstrate the larger impact of the assumed cloud vertical extinction profile on MERIS than on AATSR top-of-atmosphere measurements. The difference in retrieved CTH (ΔCTH from AATSR and MERIS are related to cloud vertical extent (CVE as observed by ground-based lidar and radar at three ARM sites. To increase the impact of the cloud vertical extinction profile on the MERIS-CTP retrievals, single-layer and geometrically thin clouds are assumed in the forward model. The results of the comparison to the ground-based observations were separated into single-layer and multi-layer cloud cases. Analogous to previous findings, the MERIS-CTP retrievals appear to be close to pressure levels in the middle of the cloud. Assuming a linear relationship, the ΔCTH multiplied by 2.5 gives an estimate on the CVE for single-layer clouds. The relationship is weaker for multi-layer clouds. Due to large variations of cloud vertical extinction profiles occurring in nature, a quantitative estimate of the cloud vertical extent

  1. Genetic Algorithms for Satellite Scheduling Problems

    Directory of Open Access Journals (Sweden)

    Fatos Xhafa

    2012-01-01

    Full Text Available Recently there has been a growing interest in mission operations scheduling problem. The problem, in a variety of formulations, arises in management of satellite/space missions requiring efficient allocation of user requests to make possible the communication between operations teams and spacecraft systems. Not only large space agencies, such as ESA (European Space Agency and NASA, but also smaller research institutions and universities can establish nowadays their satellite mission, and thus need intelligent systems to automate the allocation of ground station services to space missions. In this paper, we present some relevant formulations of the satellite scheduling viewed as a family of problems and identify various forms of optimization objectives. The main complexities, due highly constrained nature, windows accessibility and visibility, multi-objectives and conflicting objectives are examined. Then, we discuss the resolution of the problem through different heuristic methods. In particular, we focus on the version of ground station scheduling, for which we present computational results obtained with Genetic Algorithms using the STK simulation toolkit.

  2. An improved Glyoxal retrieval from OMI satellite data

    Science.gov (United States)

    Alvarado, Leonardo; Richter, Andreas; Vrekoussis, Mihalis; Wittrock, Folkard; Burrows, John

    2013-04-01

    Glyoxal (CHOCHO) originates from natural and anthropogenic activities similar to formaldehyde (HCHO). It is the smallest of the alpha-dicarbonyls and the most predominant in the atmosphere. It is an intermediate product in the oxidation of most VOCs and an indicator of secondary aerosol formation in the atmosphere. Among others, CHOCHO is a product of the oxidation of isoprene, alkyne, and aromatic hydrocarbons. CHOCHO is not influenced directly by vehicle emissions, because direct CHOCHO emissions are believed to be small. CHOCHO has a short lifetime (few hours) in the presence of sunlight, because it is removed from the atmosphere by photolysis and reaction with OH. Also, CHOCHO is removed by dry and wet deposition. For atmospheric observations, CHOCHO is of interest as it has slightly different sources than HCHO, and can be used as indicator of the rate of photochemical VOCs processing, because in contrast to HCHO it is not produced in the oxidation of methane. Atmospheric CHOCHO columns can be determined by remote sensing using the Differential Optical Absorption Spectroscopy (DOAS) method. This sensitive technique has been used both from the ground applying active and passive DOAS and from satellite. Global fields of HCHO and CHOCHO have been retrieved from GOME, SCIAMACHY, GOME-2 and OMI measurements. Some aspects of CHOCHO retrievals still have to be improved, including possible spectral interferences over water and better correction of cloud and aerosol effects, in particular in cases of biomass burning when atmospheric aerosol levels are high. This study is focused on a new CHOCHO OMI product, including preliminary test of spectral interference with liquid water over ocean regions and comparison with CHOCHO retrievals using GOME-2 measurements over oceans and continental regions.

  3. Satellite observation of atmospheric methane: intercomparison between AIRS and GOSAT TANSO-FTS retrievals

    Science.gov (United States)

    Zou, Mingmin; Xiong, Xiaozhen; Saitoh, Naoko; Warner, Juying; Zhang, Ying; Chen, Liangfu; Weng, Fuzhong; Fan, Meng

    2016-08-01

    Space-borne observations of atmospheric methane (CH4) have been made using the Atmospheric Infrared Sounder (AIRS) on the EOS/Aqua satellite since August 2002 and the Thermal and Near-infrared Sensor for Carbon Observation Fourier Transform Spectrometer (TANSO-FTS) on the Greenhouse Gases Observing Satellite (GOSAT) since April 2009. This study compared the GOSAT TANSO-FTS thermal infrared (TIR) version 1.0 CH4 product with the collocated AIRS version 6 CH4 product using data from 1 August 2010 to 30 June 2012, including the CH4 mixing ratios and the total column amounts. The results show that at 300-600 hPa, where both AIRS and GOSAT-TIR CH4 have peak sensitivities, they agree very well, but GOSAT-TIR retrievals tend to be higher than AIRS in layer 200-300 hPa. At 300 hPa the CH4 mixing ratio from GOSAT-TIR is, on average, 10.3 ± 31.8 ppbv higher than that from AIRS, and at 600 hPa GOSAT-TIR retrieved CH4 is -16.2 ± 25.7 ppbv lower than AIRS CH4. Comparison of the total column amount of CH4 shows that GOSAT-TIR agrees with AIRS to within 1 % in the mid-latitude regions of the Southern Hemisphere and in the tropics. In the mid to high latitudes in the Northern Hemisphere, comparison shows that GOSAT-TIR is ˜ 1-2 % lower than AIRS, and in the high-latitude regions of the Southern Hemisphere the difference of GOSAT from AIRS varies from -3 % in October to +2 % in July. The difference between AIRS and GOSAT TANSO-FTS retrievals is mainly due to the difference in retrieval algorithms and instruments themselves, and the larger difference in the high-latitude regions is associated with the low information content and small degrees of freedom of the retrieval. The degrees of freedom of GOSAT-TIR retrievals are lower than that of AIRS, which also indicates that the constraint in GOSAT-TIR retrievals may be too strong. From the good correlation between AIRS and GOSAT-TIR retrievals and the seasonal variation they observed, we are confident that the thermal infrared

  4. Satellite-based retrieval of particulate matter concentrations over the United Arab Emirates (UAE)

    Science.gov (United States)

    Zhao, Jun; Temimi, Marouane; Hareb, Fahad; Eibedingil, Iyasu

    2016-04-01

    In this study, an empirical algorithm was established to retrieve particulate matter (PM) concentrations (PM2.5 and PM10) using satellite-derived aerosol optical depth (AOD) over the United Arab Emirates (UAE). Validation of the proposed algorithm using ground truth data demonstrates its good accuracy. Time series of in situ measured PM concentrations between 2014 and 2015 showed high values in summer and low values in winter. Estimated and in situ measured PM concentrations were higher in 2015 than 2014. Remote sensing is an essential tool to reveal and back track the seasonality and inter-annual variations of PM concentrations and provide valuable information on the protection of human health and the response of air quality to anthropogenic activities and climate change.

  5. The influence of aerosols and land-use type on NO2 satellite retrieval over China

    Science.gov (United States)

    Liu, Mengyao; Lin, Jintai; Boersma, Folkert; Eskes, Henk; Chimot, Julien

    2017-04-01

    Both aerosols and surface reflectance have a strong influence on the retrieval of NO2 tropospheric vertical column densities (VCDs), especially over China with its heavy aerosol loading and rapid changes in land-use type. However, satellite retrievals of NO2 VCDs usually do not explicitly account for aerosol optical effects and surface reflectance anisotropy (BRDF) that varies in space and time. We develop an improved algorithm to derive tropospheric AMFs and VCDs over China from the OMI instrument - POMINO and DOMINO. This method can also be applied to TropOMI NO2 retrievals in the future. With small pixels of TropOMI and higher probability of encountering clear-sky scenes, the influence of BRDF and aerosol interference becomes more important than for OMI. Daily aerosol information is taken from the GEOS-Chem chemistry transport model and the aerosol optical depth (AOD) is adjusted via MODIS AOD climatology. We take the MODIS MCD43C2 C5 product to account for BRDF effects. The relative altitude of NO2 and aerosols is critical factor influencing the NO2 retrieval. In order to evaluate the aerosol extinction profiles (AEP) of GEOS-Chem improve our algorithm, we compare the GEOS-Chem simulation with CALIOP and develop a CALIOP AEP climatology to regulate the model's AEP. This provides a new way to include aerosol information into the tracer gas retrieval for OMI and TropOMI. Preliminary results indicate that the model performs reasonably well in reproducing the AEP shape. However, it seems to overestimate aerosols under 2km and underestimate above. We find that relative humidity (RH) is an important factor influencing the AEP shape when comparing the model with observations. If we adjust the GEOS-Chem RH to CALIOP's RH, the correlations of their AEPs also improve. Besides, take advantage of our retrieval method, we executed sensitivity tests to analyze their influences on NO2 trend and spatiotemporal variations in retrieval. It' the first time to investigate

  6. Tropospheric ozone column retrieval from the Ozone Monitoring Instrument by means of a neural network algorithm

    Directory of Open Access Journals (Sweden)

    P. Sellitto

    2011-05-01

    Full Text Available Monitoring tropospheric ozone from space is of critical importance in order to gain more thorough knowledge on phenomena affecting air quality and the greenhouse effect. Deriving information on tropospheric ozone from UV/VIS nadir satellite spectrometers is difficult owing to the weak sensitivity of the measured radiance spectra to variations of ozone in the troposphere. Here we propose an alternative method of analysis to retrieve tropospheric ozone columns from Ozone Monitoring Instrument radiances by means of a Neural Network algorithms. An extended set of ozone sonde measurements at northern mid-latitudes has been considered as the training and test data set. The design of the algorithm is extensively discussed. Our retrievals are compared to both tropospheric ozone residuals and optimal estimation retrievals over a similar independent test data set. Results show that our algorithm has comparable accuracy with respect to both correlative methods and its performance is slightly better over a subset containing only European ozone sonde stations. Possible sources of errors are analyzed. Finally, the capabilities of our algorithm to derive information on boundary layer ozone are studied and the results critically discussed.

  7. New algorithm for MODIS chlorophyll fluorescence height retrieval: performance and comparison with the current product

    Science.gov (United States)

    Ioannou, I.; Zhou, J.; Gilerson, A.; Gross, B.; Moshary, F.; Ahmed, S.

    2009-09-01

    Our previous studies showed that the Fluorescence Line Height (FLH) product, which uses 3 NIR bands at 667, 678, and 746 nm on the MODerate-resolution Imaging Spectroradiometer (MODIS) sensor, and similar bands on MERIS sensor, is not reliable in coastal waters because of a peak in the elastic reflectance spectra which occurs due to the confluence of chlorophyll and water absorption spectra and which overlaps spectrally the chlorophyll fluorescence. This combination of two overlapping peaks makes fluorescence signal retrieval inaccurate. As a consequence, the present FLH algorithm significantly underestimates fluorescence magnitudes in coastal waters. To overcome this problem, we introduce a new and more accurate approach for the retrieval of FLH in turbid waters by the MODIS sensor, which exploits the correlation between the blue-green and red bands reflectance ratios. We show that by making use of the combined remote sensing reflectance's (Rrs) at 488nm, 547nm, 667nm and 678nm we can retrieve fluorescence accurately in case 2 waters even for low fluorescence quantum yield when fluorescence magnitudes are low. The derivation and validation of our algorithm was performed using extensive synthetic datasets which cover a large variability of parameters typical of coastal waters: with CDOM absorption at 400nm 0-2 m-1, mineral concentration 0-5g/m3 and chlorophyll concentration of 0.5-100 mg/m3. In addition, we applied this proposed algorithm to MODIS satellite data and compared it with the traditional FLH algorithm.

  8. Evaluating cloud retrieval algorithms with the ARM BBHRP framework

    Energy Technology Data Exchange (ETDEWEB)

    Mlawer,E.; Dunn,M.; Mlawer, E.; Shippert, T.; Troyan, D.; Johnson, K. L.; Miller, M. A.; Delamere, J.; Turner, D. D.; Jensen, M. P.; Flynn, C.; Shupe, M.; Comstock, J.; Long, C. N.; Clough, S. T.; Sivaraman, C.; Khaiyer, M.; Xie, S.; Rutan, D.; Minnis, P.

    2008-03-10

    Climate and weather prediction models require accurate calculations of vertical profiles of radiative heating. Although heating rate calculations cannot be directly validated due to the lack of corresponding observations, surface and top-of-atmosphere measurements can indirectly establish the quality of computed heating rates through validation of the calculated irradiances at the atmospheric boundaries. The ARM Broadband Heating Rate Profile (BBHRP) project, a collaboration of all the working groups in the program, was designed with these heating rate validations as a key objective. Given the large dependence of radiative heating rates on cloud properties, a critical component of BBHRP radiative closure analyses has been the evaluation of cloud microphysical retrieval algorithms. This evaluation is an important step in establishing the necessary confidence in the continuous profiles of computed radiative heating rates produced by BBHRP at the ARM Climate Research Facility (ACRF) sites that are needed for modeling studies. This poster details the continued effort to evaluate cloud property retrieval algorithms within the BBHRP framework, a key focus of the project this year. A requirement for the computation of accurate heating rate profiles is a robust cloud microphysical product that captures the occurrence, height, and phase of clouds above each ACRF site. Various approaches to retrieve the microphysical properties of liquid, ice, and mixed-phase clouds have been processed in BBHRP for the ACRF Southern Great Plains (SGP) and the North Slope of Alaska (NSA) sites. These retrieval methods span a range of assumptions concerning the parameterization of cloud location, particle density, size, shape, and involve different measurement sources. We will present the radiative closure results from several different retrieval approaches for the SGP site, including those from Microbase, the current 'reference' retrieval approach in BBHRP. At the NSA, mixed

  9. Tropospheric BrO column densities in the Arctic derived from satellite: retrieval and comparison to ground-based measurements

    OpenAIRE

    H Sihler; Platt, U.; Beirle, S.; Marbach, T.; S. Kühl; S. Dörner; Verschaeve, J.; Frieß, U.; Pöhler, D.; Vogel, L.; Sander, R.; T. Wagner

    2012-01-01

    During polar spring, halogen radicals like bromine monoxide (BrO) play an important role in the chemistry of tropospheric ozone destruction. Satellite measurements of the BrO distribution have become a particularly useful tool to investigate this probably natural phenomenon, but the separation of stratospheric and tropospheric partial columns of BrO is challenging. In this study, an algorithm was developed to retrieve tropospheric vertical...

  10. Direct Radiative Forcing from Saharan Mineral Dust Layers from In-situ Measurements and Satellite Retrievals

    Science.gov (United States)

    Sauer, D. N.; Vázquez-Navarro, M.; Gasteiger, J.; Chouza, F.; Weinzierl, B.

    2016-12-01

    Mineral dust is the major species of airborne particulate matter by mass in the atmosphere. Each year an estimated 200-3000 Tg of dust are emitted from the North African desert and arid regions alone. A large fraction of the dust is lifted into the free troposphere and gets transported in extended dust layers westward over the Atlantic Ocean into the Caribbean Sea. Especially over the dark surface of the ocean, those dust layers exert a significant effect on the atmospheric radiative balance though aerosol-radiation interactions. During the Saharan Aerosol Long-range Transport and Aerosol-Cloud-Interaction Experiment (SALTRACE) in summer 2013 airborne in-situ aerosol measurements on both sides of the Atlantic Ocean, near the African coast and the Caribbean were performed. In this study we use data about aerosol microphysical properties acquired between Cabo Verde and Senegal to derive the aerosol optical properties and the resulting radiative forcing using the radiative transfer package libRadtran. We compare the results to values retrieved from MSG/SEVIRI data using the RRUMS algorithm. The RRUMS algorithm can derive shortwave and longwave top-of-atmosphere outgoing fluxes using only information issued from the narrow-band MSG/SEVIRI channels. A specific calibration based on collocated Terra/CERES measurements ensures a correct retrieval of the upwelling flux from the dust covered pixels. The comparison of radiative forcings based on in-situ data to satellite-retrieved values enables us to extend the radiative forcing estimates from small-scale in-situ measurements to large scale satellite coverage over the Atlantic Ocean.

  11. Heading Toward Launch with the Integrated Multi-Satellite Retrievals for GPM (IMERG)

    Science.gov (United States)

    Huffman, George J.; Bolvin, David T.; Nelkin, Eric J.; Adler, Robert F.

    2012-01-01

    The Day-l algorithm for computing combined precipitation estimates in GPM is the Integrated Multi-satellitE Retrievals for GPM (IMERG). We plan for the period of record to encompass both the TRMM and GPM eras, and the coverage to extend to fully global as experience is gained in the difficult high-latitude environment. IMERG is being developed as a unified U.S. algorithm that takes advantage of strengths in the three groups that are contributing expertise: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA), which addresses inter-satellite calibration of precipitation estimates and monthly scale combination of satellite and gauge analyses; 2) the CPC Morphing algorithm with Kalman Filtering (KF-CMORPH), which provides quality-weighted time interpolation of precipitation patterns following cloud motion; and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS), which provides a neural-network-based scheme for generating microwave-calibrated precipitation estimates from geosynchronous infrared brightness temperatures. In this talk we summarize the major building blocks and important design issues driven by user needs and practical data issues. One concept being pioneered by the IMERG team is that the code system should produce estimates for the same time period but at different latencies to support the requirements of different groups of users. Another user requirement is that all these runs must be reprocessed as new IMERG versions are introduced. IMERG's status at meeting time will be summarized, and the processing scenario in the transition from TRMM to GPM will be laid out. Initially, IMERG will be run with TRMM-based calibration, and then a conversion to a GPM-based calibration will be employed after the GPM sensor products are validated. A complete reprocessing will be computed, which will complete the transition from TMPA.

  12. A Hybrid Algorithm for Satellite Data Transmission Schedule Based on Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    LI Yun-feng; WU Xiao-yue

    2008-01-01

    A hybrid scheduling algorithm based on genetic algorithm is proposed in this paper for reconnaissance satellite data transmission. At first, based on description of satellite data transmission request, satellite data transmission task modal and satellite data transmission scheduling problem model are established. Secondly, the conflicts in scheduling are discussed. According to the meaning of possible conflict, the method to divide possible conflict task set is given. Thirdly, a hybrid algorithm which consists of genetic algorithm and heuristic information is presented. The heuristic information comes from two concepts, conflict degree and conflict number. Finally, an example shows the algorithm's feasibility and performance better than other traditional algorithms.

  13. Retrieval of Aerosol Microphysical Properties from AERONET Photo-Polarimetric Measurements. 2: A New Research Algorithm and Case Demonstration

    Science.gov (United States)

    Xu, Xiaoguang; Wang, Jun; Zeng, Jing; Spurr, Robert; Liu, Xiong; Dubovik, Oleg; Li, Li; Li, Zhengqiang; Mishchenko, Michael I.; Siniuk, Aliaksandr; Holben, Brent N.

    2015-01-01

    A new research algorithm is presented here as the second part of a two-part study to retrieve aerosol microphysical properties from the multispectral and multiangular photopolarimetric measurements taken by Aerosol Robotic Network's (AERONET's) new-generation Sun photometer. The algorithm uses an advanced UNified and Linearized Vector Radiative Transfer Model and incorporates a statistical optimization approach.While the new algorithmhas heritage from AERONET operational inversion algorithm in constraining a priori and retrieval smoothness, it has two new features. First, the new algorithmretrieves the effective radius, effective variance, and total volume of aerosols associated with a continuous bimodal particle size distribution (PSD) function, while the AERONET operational algorithm retrieves aerosol volume over 22 size bins. Second, our algorithm retrieves complex refractive indices for both fine and coarsemodes,while the AERONET operational algorithm assumes a size-independent aerosol refractive index. Mode-resolved refractive indices can improve the estimate of the single-scattering albedo (SSA) for each aerosol mode and thus facilitate the validation of satellite products and chemistry transport models. We applied the algorithm to a suite of real cases over Beijing_RADI site and found that our retrievals are overall consistent with AERONET operational inversions but can offer mode-resolved refractive index and SSA with acceptable accuracy for the aerosol composed by spherical particles. Along with the retrieval using both radiance and polarization, we also performed radiance-only retrieval to demonstrate the improvements by adding polarization in the inversion. Contrast analysis indicates that with polarization, retrieval error can be reduced by over 50% in PSD parameters, 10-30% in the refractive index, and 10-40% in SSA, which is consistent with theoretical analysis presented in the companion paper of this two-part study.

  14. Retrieval of Aerosol Microphysical Properties from AERONET Photo-Polarimetric Measurements. 2: A New Research Algorithm and Case Demonstration

    Science.gov (United States)

    Xu, Xiaoguang; Wang, Jun; Zeng, Jing; Spurr, Robert; Liu, Xiong; Dubovik, Oleg; Li, Li; Li, Zhengqiang; Mishchenko, Michael I.; Siniuk, Aliaksandr; hide

    2015-01-01

    A new research algorithm is presented here as the second part of a two-part study to retrieve aerosol microphysical properties from the multispectral and multiangular photopolarimetric measurements taken by Aerosol Robotic Network's (AERONET's) new-generation Sun photometer. The algorithm uses an advanced UNified and Linearized Vector Radiative Transfer Model and incorporates a statistical optimization approach.While the new algorithmhas heritage from AERONET operational inversion algorithm in constraining a priori and retrieval smoothness, it has two new features. First, the new algorithmretrieves the effective radius, effective variance, and total volume of aerosols associated with a continuous bimodal particle size distribution (PSD) function, while the AERONET operational algorithm retrieves aerosol volume over 22 size bins. Second, our algorithm retrieves complex refractive indices for both fine and coarsemodes,while the AERONET operational algorithm assumes a size-independent aerosol refractive index. Mode-resolved refractive indices can improve the estimate of the single-scattering albedo (SSA) for each aerosol mode and thus facilitate the validation of satellite products and chemistry transport models. We applied the algorithm to a suite of real cases over Beijing_RADI site and found that our retrievals are overall consistent with AERONET operational inversions but can offer mode-resolved refractive index and SSA with acceptable accuracy for the aerosol composed by spherical particles. Along with the retrieval using both radiance and polarization, we also performed radiance-only retrieval to demonstrate the improvements by adding polarization in the inversion. Contrast analysis indicates that with polarization, retrieval error can be reduced by over 50% in PSD parameters, 10-30% in the refractive index, and 10-40% in SSA, which is consistent with theoretical analysis presented in the companion paper of this two-part study.

  15. View of a pallet configured to support 51-A satellite-retrieval mission

    Science.gov (United States)

    1984-01-01

    A high angle view of a Spacelab type pallet configured to support NASA's 51-A satellite-retrieval mission. At left are two capture devices called 'stingers' used to enter the communications satellites at the nozzle of the spent engine. Center are circular areas for clamping down and securing the satellites for the remainder of the trip.

  16. MUTUAL IMAGE TRANSFORMATION ALGORITHMS FOR VISUAL INFORMATION PROCESSING AND RETRIEVAL

    Directory of Open Access Journals (Sweden)

    G. A. Kukharev

    2017-01-01

    Full Text Available Subject of Research. The paper deals with methods and algorithms for mutual transformation of related pairs of images in order to enhance the capabilities of cross-modal multimedia retrieval (CMMR technologies. We have thoroughly studied the problem of mutual transformation of face images of various kinds (e.g. photos and drawn pictures. This problem is widely represented in practice. Research is this area is based on existing datasets. The algorithms we have proposed in this paper can be applied to arbitrary pairs of related images due to the unified mathematical specification. Method. We have presented three image transformation algorithms. The first one is based on principal component analysis and Karhunen-Loève transform (1DPCA/1DKLT. Unlike the existing solution, it does not use the training set during the transformation process. The second algorithm assumes generation of an image population. The third algorithm performs the transformation based on two-dimensional principal component analysis and Karhunen-Loève transform (2DPCA/2DKLT. Main Results. The experiments on image transformation and population generation have revealed the main features of each algorithm. The first algorithm allows construction of an accurate and stable model of transition between two given sets of images. The second algorithm can be used to add new images to existing bases and the third algorithm is capable of performing the transformation outside the training dataset. Practical Relevance. Taking into account the qualities of the proposed algorithms, we have provided recommendations concerning their application. Possible scenarios include construction of a transition model for related pairs of images, mutual transformation of the images inside and outside the dataset as well as population generation in order to increase representativeness of existing datasets. Thus, the proposed algorithms can be used to improve reliability of face recognition performed on images

  17. Evaluation of Aerosol Pollution Determination From MODIS Satellite Retrievals for Semi-Arid Reno, NV, USA with In-Situ Measurements

    Science.gov (United States)

    Loria-Salazar, S. Marcela

    The aim of the present work is to carry out a detailed analysis of ground and columnar aerosol properties obtained by in-situ Photoacoustic and Integrated Nephelometer (PIN), Cimel CE-318 sunphotometer and MODIS instrument onboard Aqua and Terra satellites, for semi-arid Reno, Nevada, USA in the local summer months of 2012. Satellite determination of local aerosol pollution is desirable because of the potential for broad spatial and temporal coverage. However, retrieval of quantitative measures of air pollution such as Aerosol Optical Depth (AOD) from satellite measurements is challenging because of the underlying surface albedo being heterogeneous in space and time. Therefore, comparisons of satellite retrievals with measurements from ground-based sun photometers are crucial for validation, testing, and further development of instruments and retrieval algorithms. Ground-based sunphotometry and in-situ ground observations show that seasonal weather changes and fire plumes have great influence on the atmosphere aerosol optics. The Apparent Optical Height (AOH) follows the shape of the development of the Convective Boundary Layer (CBL) when fire conditions were not present. However, significant fine particle optical depth was inferred beyond the CBL thereby complicating the use of remote sensing measurements for near-ground aerosol pollution measurements. A meteorological analysis was performed to help diagnose the nature of the aerosols above Reno. The calculation of a Zephyr index and back trajectory analysis demonstrated that a local circulation often induces aerosol transport from Northern CA over the Sierra Nevada Mountains that doubles the Aerosol Optical Depth (AOD) at 500 nm. Sunphotometer measurements were used as a `ground truth' for satellite retrievals to evaluate the current state of the science retrievals in this challenging location. Satellite retrieved for AOD showed the presence of wild fires in Northern CA during August. AOD retrieved using the

  18. An overview of neural network applications for soil moisture retrieval from radar satellite sensors

    Science.gov (United States)

    Santi, E.; Paloscia, S.; Pettinato, S.

    2014-10-01

    Frequent and spatially distributed measurements of soil moisture (SMC), at different spatial scales, are advisable for all applications related to the environmental disciplines, such as climatology, meteorology, hydrology and agriculture. Satellite sensors operating in the low part of microwave spectrum are very suitable for this purpose, and their signals can be directly related to the moisture content of the observed surfaces, provided that all the contributions from soil and vegetation to the measured signal are properly accounted for. Among the algorithms used for the retrieval of SMC from both active (i.e. Synthetic Aperture Radar, SAR or real aperture radars) and passive (radiometers) microwave sensors, the artificial neural networks (ANN) represent the best compromise between accuracy and computation speed. ANN based algorithms have been developed at IFAC, and adapted to several radar and radiometric satellite sensors, in order to generate SMC products at different spatial resolutions, varying from hundreds of meters to tens of kilometers. These algorithms, which use the ANN techniques for inverting theoretical and semi-empirical models, such as Advanced Integral Equation (AIEM), Oh models, and Radiative transfer Theory (RTT), have been adapted to the C-band acquisitions from SAR (Envisat/ASAR) and real aperture radar (ASCAT) and to the X-band SAR acquisitions of Cosmo-SkyMed and TerraSAR-X. Moreover, a specific ANN algorithm has also been implemented for the L-band active and passive acquisitions of the incoming SMAP mission. The latter satellite will carry onboard simultaneously one radar and one radiometer operating at the same frequency, but with different spatial resolutions (3 and 40 km, respectively). Large datasets of co-located satellite acquisitions and direct SMC measurements on several test sites located worldwide have been used along with simulations derived from forward electromagnetic models for setting up, training and validating these

  19. An enhanced VIIRS aerosol optical thickness (AOT) retrieval algorithm over land using a global surface reflectance ratio database

    Science.gov (United States)

    Zhang, Hai; Kondragunta, Shobha; Laszlo, Istvan; Liu, Hongqing; Remer, Lorraine A.; Huang, Jingfeng; Superczynski, Stephen; Ciren, Pubu

    2016-09-01

    The Visible/Infrared Imager Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (S-NPP) satellite has been retrieving aerosol optical thickness (AOT), operationally and globally, over ocean and land since shortly after S-NPP launch in 2011. However, the current operational VIIRS AOT retrieval algorithm over land has two limitations in its assumptions for land surfaces: (1) it only retrieves AOT over the dark surfaces and (2) it assumes that the global surface reflectance ratios between VIIRS bands are constants. In this work, we develop a surface reflectance ratio database over land with a spatial resolution 0.1° × 0.1° using 2 years of VIIRS top of atmosphere reflectances. We enhance the current operational VIIRS AOT retrieval algorithm by applying the surface reflectance ratio database in the algorithm. The enhanced algorithm is able to retrieve AOT over both dark and bright surfaces. Over bright surfaces, the VIIRS AOT retrievals from the enhanced algorithm have a correlation of 0.79, mean bias of -0.008, and standard deviation (STD) of error of 0.139 when compared against the ground-based observations at the global AERONET (Aerosol Robotic Network) sites. Over dark surfaces, the VIIRS AOT retrievals using the surface reflectance ratio database improve the root-mean-square error from 0.150 to 0.123. The use of the surface reflectance ratio database also increases the data coverage of more than 20% over dark surfaces. The AOT retrievals over bright surfaces are comparable to MODIS Deep Blue AOT retrievals.

  20. Remote sensing of cloud top pressure/height from SEVIRI: analysis of ten current retrieval algorithms

    Science.gov (United States)

    Hamann, U.; Walther, A.; Baum, B.; Bennartz, R.; Bugliaro, L.; Derrien, M.; Francis, P. N.; Heidinger, A.; Joro, S.; Kniffka, A.; Le Gléau, H.; Lockhoff, M.; Lutz, H.-J.; Meirink, J. F.; Minnis, P.; Palikonda, R.; Roebeling, R.; Thoss, A.; Platnick, S.; Watts, P.; Wind, G.

    2014-09-01

    The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR) wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH) - a crucial parameter to estimate the thermal cloud radiative forcing - can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). In the first part we compare ten SEVIRI cloud top pressure (CTP) data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 km lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between 0.77 and 0.90. The

  1. Remote sensing of cloud top pressure/height from SEVIRI: analysis of ten current retrieval algorithms

    Directory of Open Access Journals (Sweden)

    U. Hamann

    2014-09-01

    Full Text Available The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH – a crucial parameter to estimate the thermal cloud radiative forcing – can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI onboard Meteosat Second Generation (MSG. In the first part we compare ten SEVIRI cloud top pressure (CTP data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud–Aerosol LIdar with Orthogonal Polarization (CALIOP and Cloud Profiling Radar (CPR instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 km lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between

  2. Remote Sensing of Cloud Top Height from SEVIRI: Analysis of Eleven Current Retrieval Algorithms

    Science.gov (United States)

    Hamann, U.; Walther, A.; Baum, B.; Bennartz, R.; Bugliaro, L.; Derrien, M.; Francis, P. N.; Heidinger, A.; Joro, S.; Kniffka, A.; hide

    2014-01-01

    The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR) wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH) - a crucial parameter to estimate the thermal cloud radiative forcing - can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). In the first part we compare ten SEVIRI cloud top pressure (CTP) data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 kilometers lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between 0.77 and 0

  3. Remote Sensing of Cloud Top Height from SEVIRI: Analysis of Eleven Current Retrieval Algorithms

    Science.gov (United States)

    Hamann, U.; Walther, A.; Baum, B.; Bennartz, R.; Bugliaro, L.; Derrien, M.; Francis, P. N.; Heidinger, A.; Joro, S.; Kniffka, A.; Le Gleau, H.; Lockhoff, M.; Lutz, H.-J.; Meirink, J. F.; Minnis, P.; Palikonda, R.; Roebeling, R.; Thoss, A.; Platnick, S.; Watts, P.; Wind, G.

    2014-01-01

    The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR) wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH) - a crucial parameter to estimate the thermal cloud radiative forcing - can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). In the first part we compare ten SEVIRI cloud top pressure (CTP) data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 kilometers lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between 0.77 and 0

  4. Semi-empirical Algorithm for the Retrieval of Ecology-Relevant Water Constituents in Various Aquatic Environments

    Directory of Open Access Journals (Sweden)

    Robert Shuchman

    2009-03-01

    Full Text Available An advanced operational semi-empirical algorithm for processing satellite remote sensing data in the visible region is described. Based on the Levenberg-Marquardt multivariate optimization procedure, the algorithm is developed for retrieving major water colour producing agents: chlorophyll-a, suspended minerals and dissolved organics. Two assurance units incorporated by the algorithm are intended to flag pixels with inaccurate atmospheric correction and specific hydro-optical properties not covered by the applied hydro-optical model. The hydro-optical model is a set of spectral cross-sections of absorption and backscattering of the colour producing agents. The combination of the optimization procedure and a replaceable hydro-optical model makes the developed algorithm not specific to a particular satellite sensor or a water body. The algorithm performance efficiency is amply illustrated for SeaWiFS, MODIS and MERIS images over a variety of water bodies.

  5. Optimal estimation retrieval of aerosol microphysical properties from SAGE II satellite observations in the volcanically unperturbed lower stratosphere

    Directory of Open Access Journals (Sweden)

    T. Deshler

    2010-05-01

    Full Text Available Stratospheric aerosol particles under non-volcanic conditions are typically smaller than 0.1 μm. Due to fundamental limitations of the scattering theory in the Rayleigh limit, these tiny particles are hard to measure by satellite instruments. As a consequence, current estimates of global aerosol properties retrieved from spectral aerosol extinction measurements tend to be strongly biased. Aerosol surface area densities, for instance, are observed to be about 40% smaller than those derived from correlative in situ measurements (Deshler et al., 2003. An accurate knowledge of the global distribution of aerosol properties is, however, essential to better understand and quantify the role they play in atmospheric chemistry, dynamics, radiation and climate. To address this need a new retrieval algorithm was developed, which employs a nonlinear Optimal Estimation (OE method to iteratively solve for the monomodal size distribution parameters which are statistically most consistent with both the satellite-measured multi-wavelength aerosol extinction data and a priori information. By thus combining spectral extinction measurements (at visible to near infrared wavelengths with prior knowledge of aerosol properties at background level, even the smallest particles are taken into account which are practically invisible to optical remote sensing instruments. The performance of the OE retrieval algorithm was assessed based on synthetic spectral extinction data generated from both monomodal and small-mode-dominant bimodal sulphuric acid aerosol size distributions. For monomodal background aerosol, the new algorithm was shown to fairly accurately retrieve the particle sizes and associated integrated properties (surface area and volume densities, even in the presence of large extinction uncertainty. The associated retrieved uncertainties are a good estimate of the true errors. In the case of bimodal background aerosol, where the retrieved (monomodal size

  6. Tropospheric BrO column densities in the Arctic derived from satellite: retrieval and comparison to ground-based measurements

    Directory of Open Access Journals (Sweden)

    H. Sihler

    2012-11-01

    Full Text Available During polar spring, halogen radicals like bromine monoxide (BrO play an important role in the chemistry of tropospheric ozone destruction. Satellite measurements of the BrO distribution have become a particularly useful tool to investigate this probably natural phenomenon, but the separation of stratospheric and tropospheric partial columns of BrO is challenging. In this study, an algorithm was developed to retrieve tropospheric vertical column densities of BrO from data of high-resolution spectroscopic satellite instruments such as the second Global Ozone Monitoring Experiment (GOME-2. Unlike recently published approaches, the presented algorithm is capable of separating the fraction of BrO in the activated troposphere from the total BrO column solely based on remotely measured properties. The presented algorithm furthermore allows to estimate a realistic measurement error of the tropospheric BrO column. The sensitivity of each satellite pixel to BrO in the boundary layer is quantified using the measured UV radiance and the column density of the oxygen collision complex O4. A comparison of the sensitivities with CALIPSO LIDAR observations demonstrates that clouds shielding near-surface trace-gas columns can be reliably detected even over ice and snow. Retrieved tropospheric BrO columns are then compared to ground-based BrO measurements from two Arctic field campaigns in the Amundsen Gulf and at Barrow in 2008 and 2009, respectively. Our algorithm was found to be capable of retrieving enhanced near-surface BrO during both campaigns in good agreement with ground-based data. Some differences between ground-based and satellite measurements observed at Barrow can be explained by both elevated and shallow surface layers of BrO. The observations strongly suggest that surface release processes are the dominating source of BrO and that boundary layer meteorology influences the vertical distribution.

  7. Satellite radiometric remote sensing of rainfall fields: multi-sensor retrieval techniques at geostationary scale

    Directory of Open Access Journals (Sweden)

    F. S. Marzano

    2005-01-01

    Full Text Available The Microwave Infrared Combined Rainfall Algorithm (MICRA consists in a statistical integration method using the satellite microwave-based rain-rate estimates, assumed to be accurate enough, to calibrate spaceborne infrared measurements on limited sub-regions and time windows. Rainfall retrieval is pursued at the space-time scale of typical geostationary observations, that is at a spatial resolution of few kilometers and a repetition period of few tens of minutes. The actual implementation is explained, although the basic concepts of MICRA are very general and the method is easy to be extended for considering innovative statistical techniques or measurements from additional space-borne platforms. In order to demonstrate the potentiality of MICRA, case studies over central Italy are also discussed. Finally, preliminary results of MICRA validation by ground based remote and in situ measurements are shown and a comparison with a Neural Network (NN based technique is briefly illustrated.

  8. Phase function effects for ocean color retrieval algorithm

    Science.gov (United States)

    Du, KePing; Lee, Zhongping

    2010-10-01

    Inherent optical properties (IOPs), e.g., absorption, back scattering coefficients, and volume scattering function, are important parameters for radiance transfer simulation. Commercially available instruments (e.g., Wetlabs ACS, BB9, etc, and HOBILabs a-sphere, HS6, etc) basically only measure absorption and back scattering coefficients. In this paper, we used the same IOPs of International Ocean-Colour Coordinating Group (IOCCG) report 5 and Hydrolight to simulate the radiance distribution, however, different phase functions, say, a new phase function derived from the measured data by multispectral volume scattering meter (MVSM) in coastal waters, the widely used Petzold average phase function, and the Fournier-Forand (FF) phase function, were employed in the simulations. The simulation results were used to develop the retrieval algorithm with angular effects correction based on the quasi-analytical algorithm(QAA) developed by Lee et al.. Results showed that not only the back scattering probability, but also the angular shape of phase function are important for ocean color retrieval algorithm. Considering the importance of phase function in ocean color remote sensing, methods to validate the phase function data should be developed.

  9. Remote sensing of cloud top pressure/height from SEVIRI: analysis of ten current retrieval algorithms

    Directory of Open Access Journals (Sweden)

    U. Hamann

    2014-01-01

    Full Text Available The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH – a crucial parameter to estimate the thermal cloud radiative forcing – can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI onboard Meteosat Second Generation (MSG. In the first part we compare the ten SEVIRI cloud top pressure (CTP datasets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas good agreement is found for the cores of the deep convective system having a high optical depth. Furthermore, a good agreement between the algorithms is observed for trade wind cumulus and marine stratocumulus clouds. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP and Cloud Profiling Radar (CPR instruments. It is important to note that the different measurement techniques cause differences in the retrieved CHT data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted signal. Therefore some systematic diffrences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 km lower than CALIOP observations, and the correlation coefficients between the

  10. An enhanced algorithm to estimate BDS satellite's differential code biases

    Science.gov (United States)

    Shi, Chuang; Fan, Lei; Li, Min; Liu, Zhizhao; Gu, Shengfeng; Zhong, Shiming; Song, Weiwei

    2016-02-01

    This paper proposes an enhanced algorithm to estimate the differential code biases (DCB) on three frequencies of the BeiDou Navigation Satellite System (BDS) satellites. By forming ionospheric observables derived from uncombined precise point positioning and geometry-free linear combination of phase-smoothed range, satellite DCBs are determined together with ionospheric delay that is modeled at each individual station. Specifically, the DCB and ionospheric delay are estimated in a weighted least-squares estimator by considering the precision of ionospheric observables, and a misclosure constraint for different types of satellite DCBs is introduced. This algorithm was tested by GNSS data collected in November and December 2013 from 29 stations of Multi-GNSS Experiment (MGEX) and BeiDou Experimental Tracking Stations. Results show that the proposed algorithm is able to precisely estimate BDS satellite DCBs, where the mean value of day-to-day scattering is about 0.19 ns and the RMS of the difference with respect to MGEX DCB products is about 0.24 ns. In order to make comparison, an existing algorithm based on IGG: Institute of Geodesy and Geophysics, China (IGGDCB), is also used to process the same dataset. Results show that, the DCB difference between results from the enhanced algorithm and the DCB products from Center for Orbit Determination in Europe (CODE) and MGEX is reduced in average by 46 % for GPS satellites and 14 % for BDS satellites, when compared with DCB difference between the results of IGGDCB algorithm and the DCB products from CODE and MGEX. In addition, we find the day-to-day scattering of BDS IGSO satellites is obviously lower than that of GEO and MEO satellites, and a significant bias exists in daily DCB values of GEO satellites comparing with MGEX DCB product. This proposed algorithm also provides a new approach to estimate the satellite DCBs of multiple GNSS systems.

  11. Retrieval of vertical wind profiles during monsoon from satellite observed winds over the Indian Ocean using complex EOF analysis

    Indian Academy of Sciences (India)

    C M Kishtawal; Sujit Basu; S Karthikeyan

    2001-03-01

    The aim of this paper is to study the feasibility of deriving vertical wind profiles from current satellite observations. With this aim, we carried out complex empirical orthogonal function (CEOF) analysis of a large number of radiosonde observations of wind profiles over the Indian Ocean during the monsoon months. It has been found that the first two CEOFs explain 67% of the total variance in wind fields. While the first principal component is well correlated with the winds at 850 mb ( = 0.80), the second one is highly correlated with winds at 200 mb ( = 0.89). This analysis formed the basis of a retrieval algorithm which ensures the retrieval of vertical profiles of winds using satellite tracked cloud motion vector winds. Under the assumption that accurate measurements of wind are available at the above mentioned levels, the r.m.s. error of retrieval of each component of wind is estimated to range between 2ms-1 and 6ms-1 at different levels, which is much less than the natural variance of winds at these levels. For a better visualization of retrieval, we have provided retrieved and true wind profiles side by side for four typical synoptic conditions during the monsoon season.

  12. Exploiting the sensitivity of two satellite cloud height retrievals to cloud vertical distribution

    Science.gov (United States)

    Carbajal Henken, C. K.; Doppler, L.; Lindstrot, R.; Preusker, R.; Fischer, J.

    2015-08-01

    This work presents a study on the sensitivity of two satellite cloud height retrievals to cloud vertical distribution. The difference in sensitivity is exploited by relating the difference in the retrieved cloud heights to cloud vertical extent. The two cloud height retrievals, performed within the Freie Universität Berlin AATSR MERIS Cloud (FAME-C) algorithm, are based on independent measurements and different retrieval techniques. First, cloud-top temperature (CTT) is retrieved from Advanced Along Track Scanning Radiometer (AATSR) measurements in the thermal infrared. Second, cloud-top pressure (CTP) is retrieved from Medium Resolution Imaging Spectrometer (MERIS) measurements in the oxygen-A absorption band and a nearby window channel. Both CTT and CTP are converted to cloud-top height (CTH) using atmospheric profiles from a numerical weather prediction model. First, a sensitivity study using radiative transfer simulations in the near-infrared and thermal infrared was performed to demonstrate, in a quantitative manner, the larger impact of the assumed cloud vertical extinction profile, described in terms of shape and vertical extent, on MERIS than on AATSR top-of-atmosphere measurements. Consequently, cloud vertical extinction profiles will have a larger influence on the MERIS than on the AATSR cloud height retrievals for most cloud types. Second, the difference in retrieved CTH (ΔCTH) from AATSR and MERIS are related to cloud vertical extent (CVE), as observed by ground-based lidar and radar at three ARM sites. To increase the impact of the cloud vertical extinction profile on the MERIS-CTP retrievals, single-layer and geometrically thin clouds are assumed in the forward model. Similarly to previous findings, the MERIS-CTP retrievals appear to be close to pressure levels in the middle of the cloud. Assuming a linear relationship, the ΔCTH multiplied by 2.5 gives an estimate on the CVE for single-layer clouds. The relationship is stronger for single

  13. Comparison Of Modified Dual Ternary Indexing And Multi-Key Hashing Algorithms For Music Information Retrieval

    OpenAIRE

    2010-01-01

    In this work we have compared two indexing algorithms that have been used to index and retrieve Carnatic music songs. We have compared a modified algorithm of the Dual ternary indexing algorithm for music indexing and retrieval with the multi-key hashing indexing algorithm proposed by us. The modification in the dual ternary algorithm was essential to handle variable length query phrase and to accommodate features specific to Carnatic music. The dual ternary indexing algorithm is ...

  14. Comparative Results of AIRS/AMSU and CrIS/ATMS Retrievals Using a Scientifically Equivalent Retrieval Algorithm

    Science.gov (United States)

    Susskind, Joel; Kouvaris, Louis; Iredell, Lena

    2016-01-01

    The AIRS Science Team Version-6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRS/AMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrIS/ATMS is the only scheduled follow on to AIRS/AMSU. The objective of this research is to prepare for generation of long term CrIS/ATMS CDRs using a retrieval algorithm that is scientifically equivalent to AIRS/AMSU Version-7.

  15. Web multimedia information retrieval using improved Bayesian algorithm

    Institute of Scientific and Technical Information of China (English)

    余铁军; 陈纯; 余铁民; 林怀忠

    2003-01-01

    The main thrust of this paper is application of a novel data mining approach on the log of user' s feedback to improve web multimedia information retrieval performance. A user space model was constructed based on data mining, and then integrated into the original information space model to improve the accuracy of the new information space model. It can remove clutter and irrelevant text information and help to eliminate mismatch between the page author' s expression and the user' s understanding and expectation. User spacemodel was also utilized to discover the relationship between high-level and low-level features for assigning weight. The authors proposed improved Bayesian algorithm for data mining. Experiment proved that the au-thors' proposed algorithm was efficient.

  16. Web multimedia information retrieval using improved Bayesian algorithm

    Institute of Scientific and Technical Information of China (English)

    余轶军; 陈纯; 余轶民; 林怀忠

    2003-01-01

    The main thrust of this paper is application of a novel data mining approach on the log of user's feedback to improve web multimedia information retrieval performance. A user space model was constructed based on data mining, and then integrated into the original information space model to improve the accuracy of the new information space model. It can remove clutter and irrelevant text information and help to eliminate mismatch between the page author's expression and the user's understanding and expectation. User space model was also utilized to discover the relationship between high-level and low-level features for assigning weight. The authors proposed improved Bayesian algorithm for data mining. Experiment proved that the authors' proposed algorithm was efficient.

  17. MISR Research Aerosol Algorithm: refinements for dark water retrievals

    Directory of Open Access Journals (Sweden)

    J. A. Limbacher

    2014-07-01

    Full Text Available We explore systematically the cumulative effect of many assumptions made in the MISR Research Aerosol retrieval algorithm, with the aim of quantifying the main sources of bias and uncertainty over ocean, and correcting them to the extent possible. 1132 coincident, surface-based sun photometer spectral aerosol optical depth (AOD measurements are used for validation. Based on comparisons between these data and our baseline case (similar to the MISR Standard algorithm, but without the "modified linear mixing" approximation, for mid-visible AOD 68% of green, red, and NIR values fall within 0.03 or 10%. For Ångström exponent (ANG: 68% of 1117 validation cases for AOD > 0.01 fall within 0.275 of the sun photometer values, compared to 49% for the SA. ANG RMSE decreases by 16% compared to the SA, and the median absolute error drops by 36%.

  18. Feasibility study for GCOM-C/SGLI: Retrieval algorithms for carbonaceous aerosols

    Science.gov (United States)

    Mukai, Sonoyo; Sano, Itaru; Yasumoto, Masayoshi; Fujito, Toshiyuki; Nakata, Makiko; Kokhanovsky, Alexander

    2016-04-01

    The Japan Aerospace Exploration Agency (JAXA) has been developing the new Earth observing system, GCOM (Global Change Observation Mission) project, which consists of two satellite series of GCOM-W1 and GCOM-C1. The 1st GCOM-C satellite will board the SGLI (second generation global imager) which also includes polarimetric sensor and be planed to launch in early of 2017. The SGLI has multi (19)-channels including near UV channel (380 nm) and two polarization channels at red and near-infrared wavelengths of 670 and 870 nm. EUMETSAT plans to collect polarization measurements with a POLDER follow on 3MI / EPS-SG in 2021. Then the efficient retrieval algorithms for aerosol and/or cloud based on the combination use of radiance and polarization are strongly expected. This work focuses on serious biomass burning episodes in East Asia. It is noted that the near UV measurements are available for detection of the carbonaceous aerosols. The biomass burning aerosols (BBA) generated by forest fire and/or agriculture biomass burning have influenced on the severe air pollutions. It is known that the forest fire increases due to global warming and a climate change, and has influences on them vice versa. It is well known that this negative cycle decreases the quality of global environment and human health. We intend to consider not only retrieval algorithms of remote sensing for severe air pollutions but also detection and/or distinction of aerosols and clouds, because mixture of aerosols and clouds are often occurred in the severe air pollutions. Then precise distinction of aerosols and clouds, namely aerosols in cloudy scenes and/or clouds in heavy aerosol episode, is desired. Aerosol retrieval in the hazy atmosphere has been achieved based on radiation simulation method of successive order of scattering 1,2. In this work, we use both radiance and polarization measurements observed by GLI and POLDER-2 on Japanese ADEOS-2 satellite in 2003 as a simulated data. As a result the

  19. Orbiting Retrievable Far and Extreme Ultraviolet Spectrometer - Shuttle Pallet Satellite (ORFEUS-SPAS)

    Science.gov (United States)

    1993-01-01

    The objective of the ORFEUS mission is to launch a deployable/retrievable astronomical platform and obtain ultraviolet spectra for both astrophysically interesting sources and the intervening interstellar medium. Also, the IMAX cameras will obtain footage of both the Shuttle and the ORFEUS-SPAS satellite during the deployment/retrieval operations phase of the ORFEUS-SPAS mission.

  20. Assessment of two aerosol optical thickness retrieval algorithms applied to MODIS Aqua and Terra measurements in Europe

    Directory of Open Access Journals (Sweden)

    P. Glantz

    2012-07-01

    Full Text Available The aim of the present study is to validate AOT (aerosol optical thickness and Ångström exponent (α, obtained from MODIS (MODerate resolution Imaging Spectroradiometer Aqua and Terra calibrated level 1 data (1 km horizontal resolution at ground with the SAER (Satellite AErosol Retrieval algorithm and with MODIS Collection 5 (c005 standard product retrievals (10 km horizontal resolution, against AERONET (AErosol RObotic NETwork sun photometer observations over land surfaces in Europe. An inter-comparison of AOT at 0.469 nm obtained with the two algorithms has also been performed. The time periods investigated were chosen to enable a validation of the findings of the two algorithms for a maximal possible variation in sun elevation. The satellite retrievals were also performed with a significant variation in the satellite-viewing geometry, since Aqua and Terra passed the investigation area twice a day for several of the cases analyzed. The validation with AERONET shows that the AOT at 0.469 and 0.555 nm obtained with MODIS c005 is within the expected uncertainty of one standard deviation of the MODIS c005 retrievals (ΔAOT = ± 0.05 ± 0.15 · AOT. The AOT at 0.443 nm retrieved with SAER, but with a much finer spatial resolution, also agreed reasonably well with AERONET measurements. The majority of the SAER AOT values are within the MODIS c005 expected uncertainty range, although somewhat larger average absolute deviation occurs compared to the results obtained with the MODIS c005 algorithm. The discrepancy between AOT from SAER and AERONET is, however, substantially larger for the wavelength 488 nm. This means that the values are, to a larger extent, outside of the expected MODIS uncertainty range. In addition, both satellite retrieval algorithms are unable to estimate α accurately, although the MODIS c005 algorithm performs better. Based on the inter-comparison of the SAER and MODIS c005 algorithms, it was found that SAER on the whole is

  1. Tropospheric BrO column densities in the Arctic from satellite: retrieval and comparison to ground-based measurements

    Directory of Open Access Journals (Sweden)

    H. Sihler

    2012-05-01

    Full Text Available During polar spring, halogen radicals like bromine monoxide (BrO play an important role in the chemistry of tropospheric ozone destruction. Satellite measurements of the BrO-distribution have become a particularly useful tool to investigate this probably natural phenomenon, but the separation of stratospheric and tropospheric partial columns of BrO is challenging. In this study, an algorithm was developed to retrieve tropospheric vertical column densities of BrO from data of high-resolution spectroscopic satellite instruments such as the second Global Ozone Monitoring Experiment (GOME-2. Unlike recently published approaches, the presented algorithm is capable of separating the fraction of BrO in the activated troposphere from the total BrO column solely based on remotely measured properties. The sensitivity of each satellite pixel to BrO in the boundary-layer is quantified using the measured UV-radiance and the column density of the oxygen collision complex O4. A comparison of the sensitivities with CALIPSO LIDAR observations demonstrates that clouds shielding near-surface trace-gas columns can be reliably detected even over ice and snow. Retrieved tropospheric BrO columns are then compared to ground-based BrO measurements from two Arctic field campaigns in the Amundsen Gulf and at Barrow in 2008 and 2009, respectively. Our algorithm was found to be capable of retrieving enhanced near-surface BrO during both campaigns in good agreement to ground-based data. Some differences between ground-based and satellite measurements observed at Barrow can be explained by both, elevated and shallow surface layers of BrO. The observations strongly suggest that surface release processes are the dominating source of BrO and that boundary-layer meteorology influences the vertical distribution.

  2. Study on the Algorithm to Retrieve Precipitation with X-Band Synthetic Aperture Radar

    Institute of Scientific and Technical Information of China (English)

    XIE Yanan; HUAN Jianping; TAO Yang

    2010-01-01

    In order to obtain the global precipitation distribution data,this paper investigates the precipitation distribution model,the normalized radar cross-section model,and the retrieval algorithm with X-band synthetic aperture radar(X-SAR).A new retrieval algorithm based on the surface-scattering reference attenuation is developed to retrieve the rain rate above the ground surface.This new algorithm needs no statistical work load and has more extensive applications.Calculations using the new algorithm for three cases verify that the rainfall is retrieved with high precision,which proves the capability of the algorithm.

  3. Improved Algorithms for Accurate Retrieval of UV - Visible Diffuse Attenuation Coefficients in Optically Complex, Inshore Waters

    Science.gov (United States)

    Cao, Fang; Fichot, Cedric G.; Hooker, Stanford B.; Miller, William L.

    2014-01-01

    Photochemical processes driven by high-energy ultraviolet radiation (UVR) in inshore, estuarine, and coastal waters play an important role in global bio geochemical cycles and biological systems. A key to modeling photochemical processes in these optically complex waters is an accurate description of the vertical distribution of UVR in the water column which can be obtained using the diffuse attenuation coefficients of down welling irradiance (Kd()). The Sea UV Sea UVc algorithms (Fichot et al., 2008) can accurately retrieve Kd ( 320, 340, 380,412, 443 and 490 nm) in oceanic and coastal waters using multispectral remote sensing reflectances (Rrs(), Sea WiFS bands). However, SeaUVSeaUVc algorithms are currently not optimized for use in optically complex, inshore waters, where they tend to severely underestimate Kd(). Here, a new training data set of optical properties collected in optically complex, inshore waters was used to re-parameterize the published SeaUVSeaUVc algorithms, resulting in improved Kd() retrievals for turbid, estuarine waters. Although the updated SeaUVSeaUVc algorithms perform best in optically complex waters, the published SeaUVSeaUVc models still perform well in most coastal and oceanic waters. Therefore, we propose a composite set of SeaUVSeaUVc algorithms, optimized for Kd() retrieval in almost all marine systems, ranging from oceanic to inshore waters. The composite algorithm set can retrieve Kd from ocean color with good accuracy across this wide range of water types (e.g., within 13 mean relative error for Kd(340)). A validation step using three independent, in situ data sets indicates that the composite SeaUVSeaUVc can generate accurate Kd values from 320 490 nm using satellite imagery on a global scale. Taking advantage of the inherent benefits of our statistical methods, we pooled the validation data with the training set, obtaining an optimized composite model for estimating Kd() in UV wavelengths for almost all marine waters. This

  4. A Physically Constrained Calibration Database for Land Surface Temperature Using Infrared Retrieval Algorithms

    Directory of Open Access Journals (Sweden)

    João P. A. Martins

    2016-09-01

    Full Text Available Land surface temperature (LST is routinely retrieved from remote sensing instruments using semi-empirical relationships between top of atmosphere (TOA radiances and LST, using ancillary data such as total column water vapor or emissivity. These algorithms are calibrated using a set of forward radiative transfer simulations that return the TOA radiances given the LST and the thermodynamic profiles. The simulations are done in order to cover a wide range of surface and atmospheric conditions and viewing geometries. This study analyzes calibration strategies while considering some of the most critical factors that need to be taken into account when building a calibration dataset, covering the full dynamic range of relevant variables. A sensitivity analysis of split-windows and single channel algorithms revealed that selecting a set of atmospheric profiles that spans the full range of surface temperatures and total column water vapor combinations that are physically possible seems beneficial for the quality of the regression model. However, the calibration is extremely sensitive to the low-level structure of the atmosphere, indicating that the presence of atmospheric boundary layer features such as temperature inversions or strong vertical gradients of thermodynamic properties may affect LST retrievals in a non-trivial way. This article describes the criteria established in the EUMETSAT Land Surface Analysis—Satellite Application Facility to calibrate its LST algorithms, applied both for current and forthcoming sensors.

  5. A Minimum Cost Handover Algorithm for Mobile Satellite Networks

    Institute of Scientific and Technical Information of China (English)

    Zhang Tao; Zhang Jun

    2008-01-01

    For mobile satellite networks,an appropriate handover scheme should be devised to shorten handover delay with optimized application of network resources.By introducing the handover cost model of service,this article proposes a rerouting triggering scheme for path optimization after handover and a new minimum cost handover algorithm for mobile satellite networks.This algorithm ensures the quality of service (QoS) parameters,such as delay,during the handover and minimizes the handover costs.Simulation indicates that this algorithm is superior to other current algorithms in guaranteeing the QoS and decreasing handover costs.

  6. Packet routing algorithm for polar orbit LEO satellite constellation network

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Broadband satellite networks are capable of providing global coverage and support various services. The networks constructed by Low Earth Orbit (LEO) satellite constellations have attracted great interests because of their short round-trip delays and wide bandwidths. A challenging problem is to develop a simple and efficient packet routing algorithm for the LEO satellite constellation network. This paper presents a SpiderWeb Topological Network (SWTN) and a distributed packet routing algorithm for the LEO satellite constellation network based on the SWTN. The algorithm gives the minimum propagation delay paths with low computational complexity and requires no routing tables, which is practical for on-board processing. The performance of the algorithm is demonstrated through simulations.

  7. The satellite-based remote sensing of particulate matter (PM) in support to urban air quality: PM variability and hot spots within the Cordoba city (Argentina) as revealed by the high-resolution MAIAC-algorithm retrievals applied to a ten-years dataset (2

    Science.gov (United States)

    Della Ceca, Lara Sofia; Carreras, Hebe A.; Lyapustin, Alexei I.; Barnaba, Francesca

    2016-04-01

    Particulate matter (PM) is one of the major harmful pollutants to public health and the environment [1]. In developed countries, specific air-quality legislation establishes limit values for PM metrics (e.g., PM10, PM2.5) to protect the citizens health (e.g., European Commission Directive 2008/50, US Clean Air Act). Extensive PM measuring networks therefore exist in these countries to comply with the legislation. In less developed countries air quality monitoring networks are still lacking and satellite-based datasets could represent a valid alternative to fill observational gaps. The main PM (or aerosol) parameter retrieved from satellite is the 'aerosol optical depth' (AOD), an optical parameter quantifying the aerosol load in the whole atmospheric column. Datasets from the MODIS sensors on board of the NASA spacecrafts TERRA and AQUA are among the longest records of AOD from space. However, although extremely useful in regional and global studies, the standard 10 km-resolution MODIS AOD product is not suitable to be employed at the urban scale. Recently, a new algorithm called Multi-Angle Implementation of Atmospheric Correction (MAIAC) was developed for MODIS, providing AOD at 1 km resolution [2]. In this work, the MAIAC AOD retrievals over the decade 2003-2013 were employed to investigate the spatiotemporal variation of atmospheric aerosols over the Argentinean city of Cordoba and its surroundings, an area where a very scarce dataset of in situ PM data is available. The MAIAC retrievals over the city were firstly validated using a 'ground truth' AOD dataset from the Cordoba sunphotometer operating within the global AERONET network [3]. This validation showed the good performances of the MAIAC algorithm in the area. The satellite MAIAC AOD dataset was therefore employed to investigate the 10-years trend as well as seasonal and monthly patterns of particulate matter in the Cordoba city. The first showed a marked increase of AOD over time, particularly evident in

  8. A feasibility study for the retrieval of the total column precipitable water vapor from satellite observations in the blue spectral range

    Directory of Open Access Journals (Sweden)

    T. Wagner

    2013-04-01

    Full Text Available We present a new algorithm for satellite retrievals of the atmospheric water vapor column in the blue spectral range. The water vapor absorption cross section in the blue spectral range is much weaker than in the red spectral range. Thus the detection limit and the uncertainty of individual observations is systematically larger than for retrievals at longer wavelengths. Nevertheless, water vapor retrievals in the blue spectral range have also several advantages: since the surface albedo in the blue spectral range is similar over land and ocean, water vapor retrievals are more consistent than for longer wavelengths. Compared to retrievals at longer wavelengths, over ocean the sensitivity for atmospheric layers close to the surface is higher due to the (typically 2 to 3 times higher ocean albedo in the blue. Water vapor retrievals in the blue spectral range are also possible for satellite sensors, which do not measure at longer wavelengths of the visible spectral range like the Ozone Monitoring instrument (OMI. We investigated details of the water vapor retrieval in the blue spectral range based on radiative transfer simulations and observations from the Global Ozone Monitoring Experiment 2 (GOME-2 and OMI. It is demonstrated that it is possible to retrieve the atmospheric water vapor column density in the blue spectral range over most parts of the globe. The findings of our study are of importance also for future satellite missions like e.g. Sentinel 4 and 5.

  9. A feasibility study for the retrieval of the total column precipitable water vapour from satellite observations in the blue spectral range

    Directory of Open Access Journals (Sweden)

    T. Wagner

    2013-10-01

    Full Text Available We present a new algorithm for satellite retrievals of the atmospheric water vapour column in the blue spectral range. The water vapour absorption cross section in the blue spectral range is much weaker than in the red spectral range. Thus the detection limit and the uncertainty of individual observations are systematically larger than for retrievals at longer wavelengths. Nevertheless, water vapour retrievals in the blue spectral range have also several advantages: since the surface albedo in the blue spectral range is similar over land and ocean, water vapour retrievals are more consistent than for longer wavelengths. Compared to retrievals at longer wavelengths, the sensitivity for atmospheric layers close to the surface is higher due to the (typically 2 to 3 times higher ocean albedo in the blue. Water vapour retrievals in the blue spectral range are also possible for satellite sensors, which do not measure at longer wavelengths of the visible spectral range like the Ozone Monitoring Instrument (OMI. We investigated details of the water vapour retrieval in the blue spectral range based on radiative transfer simulations and observations from the Global Ozone Monitoring Experiment 2 (GOME-2 and OMI. It is demonstrated that it is possible to retrieve the atmospheric water vapour column density in the blue spectral range over most parts of the globe. The findings of our study are of importance also for future satellite missions (e.g. Sentinel 4 and 5.

  10. The performance of Yonsei CArbon Retrieval (YCAR) algorithm with improved aerosol information using GOSAT measurements over East Asia

    Science.gov (United States)

    Jung, Y.; Kim, J.; Kim, W.; Boesch, H.; Yoshida, Y.; Cho, C.; Lee, H.; Goo, T. Y.

    2016-12-01

    The Greenhouse Gases Observing SATellite (GOSAT) is the first satellite dedicated to measure atmospheric CO2 concentrations from space that can able to improve our knowledge about carbon cycle. Several studies have performed to develop the CO2 retrieval algorithms using GOSAT measurements, but limitations in spatial coverage and uncertainties due to aerosols and thin cirrus clouds are still remained as a problem for monitoring CO2 concentration globally. In this study, we develop the Yonsei CArbon Retrieval (YCAR) algorithm based on optimal estimation method to retrieve the column-averaged dry-air mole fraction of carbon dioxide (XCO2) with optimized a priori CO2 profiles and aerosol models over East Asia. In previous studies, the aerosol optical properties (AOP) and the aerosol top height used to cause significant errors in retrieved XCO2 up to 2.5 ppm. Since this bias comes from a rough assumption of aerosol information in the forward model used in CO2 retrieval process, the YCAR algorithm improves the process to take into account AOPs as well as aerosol vertical distribution; total AOD and the fine mode fraction (FMF) are obtained from the ground-based measurements closely located, and other parameters are obtained from a priori information. Comparing to ground-based XCO2 measurements, the YCAR XCO2 product has a bias of 0.59±0.48 ppm and 2.16±0.87 ppm at Saga and Tsukuba sites, respectively, showing lower biases and higher correlations rather than the GOSAT standard products. These results reveal that considering better aerosol information can improve the accuracy of CO2 retrieval algorithm and provide more useful XCO2 information with reduced uncertainties.

  11. An advanced retrieval algorithm for greenhouse gases using polarization information measured by GOSAT TANSO-FTS SWIR I: Simulation study

    Science.gov (United States)

    Kikuchi, N.; Yoshida, Y.; Uchino, O.; Morino, I.; Yokota, T.

    2016-11-01

    We present an algorithm for retrieving column-averaged dry air mole fraction of carbon dioxide (XCO2) and methane (XCH4) from reflected spectra in the shortwave infrared (SWIR) measured by the TANSO-FTS (Thermal And Near infrared Sensor for carbon Observation Fourier Transform Spectrometer) sensor on board the Greenhouse gases Observing SATellite (GOSAT). The algorithm uses the two linear polarizations observed by TANSO-FTS to improve corrections to the interference effects of atmospheric aerosols, which degrade the accuracy in the retrieved greenhouse gas concentrations. To account for polarization by the land surface reflection in the forward model, we introduced a bidirectional reflection matrix model that has two parameters to be retrieved simultaneously with other state parameters. The accuracy in XCO2 and XCH4 values retrieved with the algorithm was evaluated by using simulated retrievals over both land and ocean, focusing on the capability of the algorithm to correct imperfect prior knowledge of aerosols. To do this, we first generated simulated TANSO-FTS spectra using a global distribution of aerosols computed by the aerosol transport model SPRINTARS. Then the simulated spectra were submitted to the algorithms as measurements both with and without polarization information, adopting a priori profiles of aerosols that differ from the true profiles. We found that the accuracy of XCO2 and XCH4, as well as profiles of aerosols, retrieved with polarization information was considerably improved over values retrieved without polarization information, for simulated observations over land with aerosol optical thickness greater than 0.1 at 1.6 μm.

  12. Evaluation of Satellite Retrievals of Ocean Chlorophyll-a in the California Current

    Directory of Open Access Journals (Sweden)

    Mati Kahru

    2014-09-01

    Full Text Available Retrievals of ocean surface chlorophyll-a concentration (Chla by multiple ocean color satellite sensors (SeaWiFS, MODIS-Terra, MODIS-Aqua, MERIS, VIIRS using standard algorithms were evaluated in the California Current using a large archive of in situ measurements. Over the full range of in situ Chla, all sensors produced a coefficient of determination (R2 between 0.79 and 0.88 and a median absolute percent error (MdAPE between 21% and 27%. However, at in situ Chla > 1 mg m−3, only products from MERIS (both the ESA produced algal_1 and NASA produced chlor_a maintained reasonable accuracy (R2 from 0.74 to 0.52 and MdAPE from 23% to 31%, respectively, while the other sensors had R2 below 0.5 and MdAPE higher than 36%. We show that the low accuracy at medium and high Chla is caused by the poor retrieval of remote sensing reflectance.

  13. Monitoring and tracking the trans-Pacific transport of aerosols using multi-satellite aerosol optical depth retrievals

    Directory of Open Access Journals (Sweden)

    A. R. Naeger

    2015-10-01

    Full Text Available The primary goal of this study was to generate a near-real time (NRT aerosol optical depth (AOD product capable of providing a comprehensive understanding of the aerosol spatial distribution over the Pacific Ocean in order to better monitor and track the trans-Pacific transport of aerosols. Therefore, we developed a NRT product that takes advantage of observations from both low-earth orbiting and geostationary satellites. In particular, we utilize AOD products from the Moderate Resolution Imaging Spectroradiometer (MODIS and Suomi National Polar-orbiting Partnership (NPP Visible Infrared Imaging Radiometer Suite (VIIRS satellites. Then, we combine these AOD products with our own retrieval algorithms developed for the NOAA Geostationary Operational Environmental Satellite (GOES-15 and Japan Meteorological Agency (JMA Multi-functional Transport Satellite (MTSAT-2 to generate a NRT daily AOD composite product. We present examples of the daily AOD composite product for a case study of trans-Pacific transport of Asian pollution and dust aerosols in mid-March 2014. Overall, the new product successfully tracks this aerosol plume during its trans-Pacific transport to the west coast of North America. However, we identify several areas across the domain of interest from Asia to North America where the new product can encounter significant uncertainties due to the inclusion of the geostationary AOD retrievals. The uncertainties associated with geostationary AOD retrievals are expected to be minimized after the successful launch of the next-generation advanced NOAA GOES-R and recently launched JMA Himawari satellites. Observations from these advanced satellites will ultimately provide an enhanced understanding of the spatial and temporal distribution of aerosols over the Pacific.

  14. Algorithm of orbit determination using one or two GPS satellites

    Institute of Scientific and Technical Information of China (English)

    刘艳芳; 洪炳荣; 郭建宁; 巨涛

    1999-01-01

    The problem of orbit determination using one or two GPS satellites is discussed. Methods of getting initial values based on linear translation is presented; the Secant method and the descend Newton iterative procedure and the continuation algorithm are used synthetically to solve the nonlinear equations. Computer simulation shows that this algorithm can give preliminary state of satellite orbit with a certain precision in short time.

  15. Algorithm Development for Land Surface Temperature Retrieval: Application to Chinese Gaofen-5 Data

    Directory of Open Access Journals (Sweden)

    Yuanyuan Chen

    2017-02-01

    Full Text Available Land surface temperature (LST is a key variable in the study of the energy exchange between the land surface and the atmosphere. Among the different methods proposed to estimate LST, the quadratic split-window (SW method has achieved considerable popularity. This method works well when the emissivities are high in both channels. Unfortunately, it performs poorly for low land surface emissivities (LSEs. To solve this problem, assuming that the LSE is known, the constant in the quadratic SW method was calculated by maintaining the other coefficients the same as those obtained for the black body condition. This procedure permits transfer of the emissivity effect to the constant. The result demonstrated that the constant was influenced by both atmospheric water vapour content (W and atmospheric temperature (T0 in the bottom layer. To parameterize the constant, an exponential approximation between W and T0 was used. A LST retrieval algorithm was proposed. The error for the proposed algorithm was RMSE = 0.70 K. Sensitivity analysis results showed that under the consideration of NEΔT = 0.2 K, 20% uncertainty in W and 1% uncertainties in the channel mean emissivity and the channel emissivity difference, the RMSE was 1.29 K. Compared with AST 08 product, the proposed algorithm underestimated LST by about 0.8 K for both study areas when ASTER L1B data was used as a proxy of Gaofen-5 (GF-5 satellite data. The GF-5 satellite is scheduled to be launched in 2017.

  16. A COMPARISON BETWEEN TWO ALGORITHMS FOR THE RETRIEVAL OF SOIL MOISTURE USING AMSR-E DATA

    Directory of Open Access Journals (Sweden)

    Simonetta ePaloscia

    2015-04-01

    Full Text Available A comparison between two algorithms for estimating soil moisture with microwave satellite data was carried out by using the datasets collected on the four Agricultural Research Service (ARS watershed sites in the US from 2002 to 2009. These sites collectively represent a wide range of ground conditions and precipitation regimes (from natural to agricultural surfaces and from desert to humid regions and provide long-term in-situ data. One of the algorithms is the artificial neural network-based algorithm developed by the Institute of Applied Physics of the National Research Council (IFAC-CNR (HydroAlgo and the second one is the Single Channel Algorithm (SCA developed by USDA-ARS (US Department of Agriculture-Agricultural Research Service. Both algorithms are based on the same radiative transfer equations but are implemented very differently. Both made use of datasets provided by the Japanese Aerospace Exploration Agency (JAXA, within the framework of Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E and Global Change Observation Mission–Water GCOM/AMSR-2 programs. Results demonstrated that both algorithms perform better than the mission specified accuracy, with Root Mean Square Error (RMSE ≤0.06 m3/m3 and Bias <0.02 m3/m3. These results expand on previous investigations using different algorithms and sites. The novelty of the paper consists of the fact that it is the first intercomparison of the HydroAlgo algorithm with a more traditional retrieval algorithm, which offers an approach to higher spatial resolution products.

  17. A Lightning Channel Retrieval Algorithm for the North Alabama Lightning Mapping Array (LMA)

    Science.gov (United States)

    Koshak, William; Arnold, James E. (Technical Monitor)

    2002-01-01

    A new multi-station VHF time-of-arrival (TOA) antenna network is, at the time of this writing, coming on-line in Northern Alabama. The network, called the Lightning Mapping Array (LMA), employs GPS timing and detects VHF radiation from discrete segments (effectively point emitters) that comprise the channel of lightning strokes within cloud and ground flashes. The network will support on-going ground validation activities of the low Earth orbiting Lightning Imaging Sensor (LIS) satellite developed at NASA Marshall Space Flight Center (MSFC) in Huntsville, Alabama. It will also provide for many interesting and detailed studies of the distribution and evolution of thunderstorms and lightning in the Tennessee Valley, and will offer many interesting comparisons with other meteorological/geophysical wets associated with lightning and thunderstorms. In order to take full advantage of these benefits, it is essential that the LMA channel mapping accuracy (in both space and time) be fully characterized and optimized. In this study, a new revised channel mapping retrieval algorithm is introduced. The algorithm is an extension of earlier work provided in Koshak and Solakiewicz (1996) in the analysis of the NASA Kennedy Space Center (KSC) Lightning Detection and Ranging (LDAR) system. As in the 1996 study, direct algebraic solutions are obtained by inverting a simple linear system of equations, thereby making computer searches through a multi-dimensional parameter domain of a Chi-Squared function unnecessary. However, the new algorithm is developed completely in spherical Earth-centered coordinates (longitude, latitude, altitude), rather than in the (x, y, z) cartesian coordinates employed in the 1996 study. Hence, no mathematical transformations from (x, y, z) into spherical coordinates are required (such transformations involve more numerical error propagation, more computer program coding, and slightly more CPU computing time). The new algorithm also has a more realistic

  18. Developments in the Aerosol Layer Height Retrieval Algorithm for the Copernicus Sentinel-4/UVN Instrument

    Science.gov (United States)

    Nanda, Swadhin; Sanders, Abram; Veefkind, Pepijn

    2016-04-01

    The Sentinel-4 mission is a part of the European Commission's Copernicus programme, the goal of which is to provide geo-information to manage environmental assets, and to observe, understand and mitigate the effects of the changing climate. The Sentinel-4/UVN instrument design is motivated by the need to monitor trace gas concentrations and aerosols in the atmosphere from a geostationary orbit. The on-board instrument is a high resolution UV-VIS-NIR (UVN) spectrometer system that provides hourly radiance measurements over Europe and northern Africa with a spatial sampling of 8 km. The main application area of Sentinel-4/UVN is air quality. One of the data products that is being developed for Sentinel-4/UVN is the Aerosol Layer Height (ALH). The goal is to determine the height of aerosol plumes with a resolution of better than 0.5 - 1 km. The ALH product thus targets aerosol layers in the free troposphere, such as desert dust, volcanic ash and biomass during plumes. KNMI is assigned with the development of the Aerosol Layer Height (ALH) algorithm. Its heritage is the ALH algorithm developed by Sanders and De Haan (ATBD, 2016) for the TROPOMI instrument on board the Sentinel-5 Precursor mission that is to be launched in June or July 2016 (tentative date). The retrieval algorithm designed so far for the aerosol height product is based on the absorption characteristics of the oxygen-A band (759-770 nm). The algorithm has heritage to the ALH algorithm developed for TROPOMI on the Sentinel 5 precursor satellite. New aspects for Sentinel-4/UVN include the higher resolution (0.116 nm compared to 0.4 for TROPOMI) and hourly observation from the geostationary orbit. The algorithm uses optimal estimation to obtain a spectral fit of the reflectance across absorption band, while assuming a single uniform layer with fixed width to represent the aerosol vertical distribution. The state vector includes amongst other elements the height of this layer and its aerosol optical

  19. Early assessment of Integrated Multi-satellite Retrievals for Global Precipitation Measurement over China

    Science.gov (United States)

    Guo, Hao; Chen, Sheng; Bao, Anming; Behrangi, Ali; Hong, Yang; Ndayisaba, Felix; Hu, Junjun; Stepanian, Phillip M.

    2016-07-01

    Two post-real time precipitation products from the Integrated Multi-satellite Retrievals for Global Precipitation Measurement Mission (IMERG) are systematically evaluated over China with China daily Precipitation Analysis Product (CPAP) as reference. The IMERG products include the gauge-corrected IMERG product (IMERG_Cal) and the version of IMERG without direct gauge correction (IMERG_Uncal). The post-research TRMM Multisatellite Precipitation Analysis version 7 (TMPA-3B42V7) is also evaluated concurrently with IMERG for better perspective. In order to be consistent with CPAP, the evaluation and comparison of selected products are performed at 0.25° and daily resolutions from 12 March 2014 through 28 February 2015. The results show that: Both IMERG and 3B42V7 show similar performances. Compared to IMERG_Uncal, IMERG_Cal shows significant improvement in overall and conditional bias and in the correlation coefficient. Both IMERG_Cal and IMERG_Uncal perform relatively poor in winter and over-detect slight precipitation events in northwestern China. As an early validation of the GPM-era IMERG products that inherit the TRMM-era global satellite precipitation products, these findings will provide useful feedbacks and insights for algorithm developers and data users over China and beyond.

  20. Analysis of CrIS ATMS and AIRS AMSU Data Using Scientifically Equivalent Retrieval Algorithms

    Science.gov (United States)

    Susskind, Joel; Kouvaris, Louis; Iredell, Lena; Blaisdell, John

    2016-01-01

    Monthly mean August 2014 Version-6.28 AIRS and CrIS products agree well with OMPS and CERES, and reasonably well with each other. Version-6.28 CrIS total precipitable water is biased dry compared to AIRS. AIRS and CrIS Version-6.36 water vapor products are both improved compared to Version-6.28. Version-6.36 AIRS and CrIS total precipitable water also shows improved agreement with each other. AIRS Version-6.36 total ozone agrees even better with OMPS than does AIRS Version-6.28, and gives reasonable results during polar winter where OMPS does not generate products. CrIS and ATMS are high spectral resolution IR and Microwave atmospheric sounders currently flying on the SNPP satellite, and are also scheduled for flight on future NPOESS satellites. CrIS/ATMS have similar sounding capabilities to those of the AIRS/AMSU sounder suite flying on EOS Aqua. The objective of this research is to develop and implement scientifically equivalent AIRS/AMSU and CrIS/ATMS retrieval algorithms with the goal of generating a continuous data record of AIRS/AMSU and CrIS/ATMS level-3 data products with a seamless transition between them in time. To achieve this, monthly mean AIRS/AMSU and CrIS/ATMS retrieved products, and more importantly their interannual differences, should show excellent agreement with each other. The currently operational AIRS Science Team Version-6 retrieval algorithm has generated 14 years of level-3 data products. A scientifically improved AIRS Version-7 retrieval algorithm is expected to become operational in 2017. We see significant improvements in water vapor and ozone in Version-7 retrieval methodology compared to Version-6.We are working toward finalization and implementation of scientifically equivalent AIRS/AMSU and CrIS/ATMS Version-7 retrieval algorithms to be used for the eventual processing of all AIRS/AMSU and CrIS/ATMS data. The latest version of our retrieval algorithm is Verison-6.36, which includes almost all the improvements we want in Version-7

  1. 大气SO2柱总量遥感反演算法比较分析及验证∗%Comparison and validation of band residual difference algorithm and principal comp onent analysis algorithm for retrievals of atmospheric SO2 columns from satellite observations

    Institute of Scientific and Technical Information of China (English)

    闫欢欢; 李晓静; 张兴赢; 王维和; 陈良富; 张美根; 徐晋

    2016-01-01

    Meter for Atmospheric CHartographY (SCIAMACHY), and Ozone Monitoring Instrument (OMI) have high SO2 monitoring capability. The OMI, which was launched on the EOS/Aura platform in July 2004, has the same hyperspectral measurements as the GOME and SCIAMACHY, but offers the improved spatial resolution at nadir (13 × 24 km2) and daily global coverage for short-lifetime SO2. For OMI operational SO2 planetary boundary layer (PBL) retrieval, the previous band residual difference (BRD) algorithm has been replaced by principal component analysis (PCA) algorithm, which effectively reduces the systematic biases in SO2 column retrievals. However, there are few studies on the evaluations and validations of PCA SO2 retrievals over China, and the long-term comparisons with BRD SO2 retrievals also need to be conducted. In this study, the accuracies of PCA and BRD SO2 retrievals are validated by using ground-based multi axis differential optical absorption spectroscopy (MAX-DOAS) located in Beijing, and regional atmospheric modeling system, community multi-scale air quality (RAMS-CMAQ) modeling system model which can simulate the vertical distribution of atmospheric SO2. Moreover, BRD and PCA SO2 retrievals from oceanic area, eastern China and Reunion volcanic eruption are compared to find the long-term trend and spatiotemporal dif-ferences between SO2 columns. Finally, the uncertainty of SO2 retrieval, caused by measurement errors, band selection and input parameter errors in radiative transfer model, are analysed to understand the limitations of BRD and PCA algorithms. Results show that both PCA and BRD SO2 retrievals over Beijing are lower than ground-based MAX-DOAS mea-surements of SO2. PCA and BRD SO2 retrievals over eastern China are lower than the simulated SO2 columns fromRAMS-CMAQ in winter 2008, but in July and August BRD SO2 columns are higher than RAMS-CMAQ simulations. The values of SO2 columns from BRD over China are more consistent with those from ground-based MAX-DOAS and

  2. Optimal Scheduling for Retrieval Jobs in Double-Deep AS/RS by Evolutionary Algorithms

    Directory of Open Access Journals (Sweden)

    Kuo-Yang Wu

    2013-01-01

    Full Text Available We investigate the optimal scheduling of retrieval jobs for double-deep type Automated Storage and Retrieval Systems (AS/RS in the Flexible Manufacturing System (FMS used in modern industrial production. Three types of evolutionary algorithms, the Genetic Algorithm (GA, the Immune Genetic Algorithm (IGA, and the Particle Swarm Optimization (PSO algorithm, are implemented to obtain the optimal assignments. The objective is to minimize the working distance, that is, the shortest retrieval time travelled by the Storage and Retrieval (S/R machine. Simulation results and comparisons show the advantages and feasibility of the proposed methods.

  3. Classification of Aerosol Retrievals from Spaceborne Polarimetry Using a Multi-Parameter Algorithm

    Science.gov (United States)

    Russell, P. B.; Kacenelenbogen, M. S.; Livingston, J. M.; Hasekamp, O.; Burton, S. P.; Schuster, G. L.; Redemann, J.; Ramachandran, S.; Holben, B. N.

    2013-12-01

    In this presentation we demonstrate application of a new aerosol classification algorithm to retrievals from the POLDER-3 polarimeter on the PARASOL spacecraft. Motivation and method: Since the development of global aerosol measurements by satellites and AERONET, classification of observed aerosols into several types (e,g., urban-industrial, biomass burning, mineral dust, maritime, and various subtypes or mixtures of these) has proven useful to: understanding aerosol sources, transformations, effects, and feedback mechanisms; improving accuracy of satellite retrievals; and quantifying assessments of aerosol radiative impacts on climate. With ongoing improvements in satellite measurement capability, the number of aerosol parameters retrieved from spaceborne sensors has been growing, from the initial aerosol optical depth at one or a few wavelengths to a list that now includes complex refractive index, single scattering albedo (SSA), and depolarization of backscatter, each at several wavelengths; wavelength dependences of extinction, scattering, absorption, SSA, and backscatter; and several particle size and shape parameters. Making optimal use of these varied data products requires objective, multi-dimensional analysis methods. We describe such a method, which uses a modified Mahalanobis distance to quantify how far a data point described by N aerosol parameters is from each of several prespecified classes. The method makes explicit use of uncertainties in input parameters, treating a point and its N-dimensional uncertainty as an extended data point or pseudo-cluster E. It then uses a modified Mahalanobis distance, DEC, to assign that observation to the class (cluster) C that has minimum DEC from the point (equivalently, the class to which the point has maximum probability of belonging). The method also uses Wilks' overall lambda to indicate how well the input data lend themselves to separation into classes and Wilks' partial lambda to indicate the relative

  4. Wave steepness retrieved from scatterometer data in a genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    GUO Jie; HE Yijun

    2012-01-01

    Wave steepness is an important characteristic of a high sea state,and is widely applied on wave propagations at ports,ships,offshore platforms,and CO2 circulation in the ocean.Obtaining wave steepness is a difficult task that depends heavily on theoretical research on wavelength distribution and direct observations.Development of remote-sensing techniques provides new opportunities to study wave steepness.At present,two formulas are proposed to estimate wave steepness from QuikSCAT and ERS-1/2 scatterometer data.We found that wave steepness retrieving is not affected by radar band,and polarization method,and that relationship of wave steepness with radar backscattering cross section is similar to that with wind.Therefore,we adopted and modified a genetic algorithm for relating wave steepness with radar backscattering cross section.Results show that the root-mean-square error of the wave steepness retrieved is 0.005 in two cases from ERS-1/2 scatterometer data and from QuikSCAT scatterometer data.

  5. PACKET ROUTING ALGORITHM FOR LEO SATELLITE CONSTELLATION NETWORK

    Institute of Scientific and Technical Information of China (English)

    Wang Kaidong; Tian Bin; Yi Kechu

    2005-01-01

    A novel distributed packet routing algorithm for Low Earth Orbit (LEO) satellite networks based on spiderweb topology is presented. The algorithm gives the shortest path with very low computational complexity and without on-board routing tables, which is suitable and practical for on-board processing. Simulation results show its practicability and feasibility.

  6. Dynamic Routing Algorithm for Increasing Robustness in Satellite Networks

    Institute of Scientific and Technical Information of China (English)

    LI Dong-ni; ZHANG Da-kun

    2008-01-01

    In low earth orbit(LEO)and medium earth orbit(MEO)satellite networks,the network topology changes rapidly because of the high relative speed movement of satellites.When some inter-satellite links (ISLs)fail,they can not be repaired in a short time.In order to increase the robustness for LEO/MEO satellite networks,an effective dynamic routing algorithm is proposed.All the routes to a certain node are found by constructing a destination oriented acyclic directed graph(DOADG)with the node as the destination.In this algorithm,multiple routes are provided,loop-free is guaranteed,and as long as the DOADG maintains,it is not necessary to reroute even if some ISLs fail.Simulation results show that comparing to the conventional routing algorithms,it is more efficient and reliable,costs less transmission overhead and converges faster.

  7. Improving User Access to the Integrated Multi-Satellite Retrievals for GPM (IMERG) Products

    Science.gov (United States)

    Huffman, George; Bolvin, David; Nelkin, Eric; Kidd, Christopher

    2016-04-01

    The U.S. Global Precipitation Measurement mission (GPM) team has developed the Integrated Multi-satellitE Retrievals for GPM (IMERG) algorithm to take advantage of the international constellation of precipitation-relevant satellites and the Global Precipitation Climatology Centre surface precipitation gauge analysis. The goal is to provide a long record of homogeneous, high-resolution quasi-global estimates of precipitation. While expert scientific researchers are major users of the IMERG products, it is clear that many other user communities and disciplines also desire access to the data for wide-ranging applications. Lessons learned during the Tropical Rainfall Measuring Mission, the predecessor to GPM, led to some basic design choices that provided the framework for supporting multiple user bases. For example, two near-real-time "runs" are computed, the Early and Late (currently 5 and 15 hours after observation time, respectively), then the Final Run about 3 months later. The datasets contain multiple fields that provide insight into the computation of the complete precipitation data field, as well as diagnostic (currently) estimates of the precipitation's phase. In parallel with this, the archive sites are working to provide the IMERG data in a variety of formats, and with subsetting and simple interactive analysis to make the data more easily available to non-expert users. The various options for accessing the data are summarized under the pmm.nasa.gov data access page. The talk will end by considering the feasibility of major user requests, including polar coverage, a simplified Data Quality Index, and reduced data latency for the Early Run. In brief, the first two are challenging, but under the team's control. The last requires significant action by some of the satellite data providers.

  8. Aerosol retrieval algorithm for the characterization of local aerosol using MODIS L1B data

    Science.gov (United States)

    Wahab, A. M.; Sarker, M. L. R.

    2014-02-01

    Atmospheric aerosol plays an important role in radiation budget, climate change, hydrology and visibility. However, it has immense effect on the air quality, especially in densely populated areas where high concentration of aerosol is associated with premature death and the decrease of life expectancy. Therefore, an accurate estimation of aerosol with spatial distribution is essential, and satellite data has increasingly been used to estimate aerosol optical depth (AOD). Aerosol product (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) data is available at global scale but problems arise due to low spatial resolution, time-lag availability of AOD product as well as the use of generalized aerosol models in retrieval algorithm instead of local aerosol models. This study focuses on the aerosol retrieval algorithm for the characterization of local aerosol in Hong Kong for a long period of time (2006-2011) using high spatial resolution MODIS level 1B data (500 m resolution) and taking into account the local aerosol models. Two methods (dark dense vegetation and MODIS land surface reflectance product) were used for the estimation of the surface reflectance over land and Santa Barbara DISORT Radiative Transfer (SBDART) code was used to construct LUTs for calculating the aerosol reflectance as a function of AOD. Results indicate that AOD can be estimated at the local scale from high resolution MODIS data, and the obtained accuracy (ca. 87%) is very much comparable with the accuracy obtained from other studies (80%-95%) for AOD estimation.

  9. A microwave satellite water vapour column retrieval for polar winter conditions

    Science.gov (United States)

    Perro, Christopher; Lesins, Glen; Duck, Thomas J.; Cadeddu, Maria

    2016-05-01

    A new microwave satellite water vapour retrieval for the polar winter atmosphere is presented. The retrieval builds on the work of Miao et al. (2001) and Melsheimer and Heygster (2008), employing auxiliary information for atmospheric conditions and numerical optimization. It was tested using simulated and actual measurements from the Microwave Humidity Sounder (MHS) satellite instruments. Ground truth was provided by the G-band vapour radiometer (GVR) at Barrow, Alaska. For water vapour columns less than 6 kg m-2, comparisons between the retrieval and GVR result in a root mean square (RMS) deviation of 0.39 kg m-2 and a systematic bias of 0.08 kg m-2. These results are compared with RMS deviations and biases at Barrow for the retrieval of Melsheimer and Heygster (2008), the AIRS and MIRS satellite data products, and the ERA-Interim, NCEP, JRA-55, and ASR reanalyses. When applied to MHS measurements, the new retrieval produces a smaller RMS deviation and bias than for the earlier retrieval and satellite data products. The RMS deviations for the new retrieval were comparable to those for the ERA-Interim, JRA-55, and ASR reanalyses; however, the MHS retrievals have much finer horizontal resolution (15 km at nadir) and reveal more structure. The new retrieval can be used to obtain pan-Arctic maps of water vapour columns of unprecedented quality. It may also be applied to measurements from the Special Sensor Microwave/Temperature 2 (SSM/T2), Advanced Microwave Sounding Unit B (AMSU-B), Special Sensor Microwave Imager/Sounder (SSMIS), Advanced Technology Microwave Sounder (ATMS), and Chinese MicroWave Humidity Sounder (MWHS) instruments.

  10. Status of SMILES research products and retrieval algorithm description.

    Science.gov (United States)

    Baron, Philippe; Kasai, Yasuko; Ochiai, Satoshi; Sagawa, Hideo; Mendrok, Jana; Urban, Joachim; Murtagh, Donal P.; Moller, Joakim; Murayama, Yasuhiro

    The super-conducting SubMillimeter wave Limb Emission Sounder (SMILES) is a high sensi-tive radiometer to study atmospheric dynamics and chemistry with a strong emphasis on the stratosphere. It is the result of the collaboration between the Japanese Aerospace Exploration Agency (JAXA) and the National Institute of Information and Communications and Technol-ogy (NICT, Japan). It is operating from the Japanese Experiment Module (JEM) onboard the International Space Station. Observations started on October, 2009. The latitude coverage is typically from -38° to 65° . The main products are the distribution from the upper-troposphere to the mesosphere of O3 and its isotopes, H35 Cl, H37 Cl, ClO, BrO, HO2 , HOCl, H2 O2 , CH3 CN and H2 O. Thanks to its high signal to noise ratio, SMILES is very well suited for observing radicals with very low abundances such as BrO and HO2 . Furthermore due to the ISS orbit precession, it is possible to follow their diurnal variation at given latitudes. The operational processing of the observations is done in JAXA for levels 1b and 2 data, and in NICT for level 3 data. A system for research on retrieval algorithms has been developed by NICT. The results are named research products. In this presentation, we will present the status and the algorithms for the NICT research products as well as the ongoing research including plans for new products.

  11. A Fuzzy Genetic Algorithm Approach to an Adaptive Information Retrieval Agent.

    Science.gov (United States)

    Martin-Bautista, Maria J.; Vila, Maria-Amparo; Larsen, Henrik Legind

    1999-01-01

    Presents an approach to a Genetic Information Retrieval Agent Filter (GIRAF) that filters and ranks documents retrieved from the Internet according to users' preferences by using a Genetic Algorithm and fuzzy set theory to handle the imprecision of users' preferences and users' evaluation of the retrieved documents. (Author/LRW)

  12. Satellite Sampling and Retrieval Errors in Regional Monthly Rain Estimates from TMI AMSR-E, SSM/I, AMSU-B and the TRMM PR

    Science.gov (United States)

    Fisher, Brad; Wolff, David B.

    2010-01-01

    Passive and active microwave rain sensors onboard earth-orbiting satellites estimate monthly rainfall from the instantaneous rain statistics collected during satellite overpasses. It is well known that climate-scale rain estimates from meteorological satellites incur sampling errors resulting from the process of discrete temporal sampling and statistical averaging. Sampling and retrieval errors ultimately become entangled in the estimation of the mean monthly rain rate. The sampling component of the error budget effectively introduces statistical noise into climate-scale rain estimates that obscure the error component associated with the instantaneous rain retrieval. Estimating the accuracy of the retrievals on monthly scales therefore necessitates a decomposition of the total error budget into sampling and retrieval error quantities. This paper presents results from a statistical evaluation of the sampling and retrieval errors for five different space-borne rain sensors on board nine orbiting satellites. Using an error decomposition methodology developed by one of the authors, sampling and retrieval errors were estimated at 0.25 resolution within 150 km of ground-based weather radars located at Kwajalein, Marshall Islands and Melbourne, Florida. Error and bias statistics were calculated according to the land, ocean and coast classifications of the surface terrain mask developed for the Goddard Profiling (GPROF) rain algorithm. Variations in the comparative error statistics are attributed to various factors related to differences in the swath geometry of each rain sensor, the orbital and instrument characteristics of the satellite and the regional climatology. The most significant result from this study found that each of the satellites incurred negative longterm oceanic retrieval biases of 10 to 30%.

  13. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    Science.gov (United States)

    Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2015-08-01

    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide rainfall maps can be derived from the signal attenuations of microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm and provide the corresponding code. Moreover, the code (in the scripting language "R") is made available including a data set of commercial microwave links. The purpose of this paper is to promote rainfall monitoring utilizing microwave links from cellular communication networks as an alternative or complementary means for global, continental-scale rainfall monitoring.

  14. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    Science.gov (United States)

    Overeem, Aart; Uijlenhoet, Remko; Leijnse, Hidde

    2016-04-01

    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide rainfall maps can be derived from the signal attenuations of microwave links in such a network. We present a rainfall retrieval algorithm, which is employed to obtain rainfall maps from microwave links in a cellular communication network. We compare these rainfall maps to gauge-adjusted radar rainfall maps. The microwave link data set, as well as the developed code, a package in the open source scripting language "R", are freely available at GitHub (https://github.com/overeem11/RAINLINK). The purpose of this presentation is to promote rainfall mapping utilizing microwave links from cellular communication networks as an alternative or complementary means for continental-scale rainfall monitoring.

  15. GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign

    Science.gov (United States)

    Choi, Myungje; Kim, Jhoon; Lee, Jaehwa; Kim, Mijin; Park, Young-Je; Jeong, Ukkyo; Kim, Woogyung; Hong, Hyunkee; Holben, Brent; Eck, Thomas F.; Song, Chul H.; Lim, Jae-Hyun; Song, Chang-Keun

    2016-04-01

    The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements made to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm together with validation results during the Distributed Regional Aerosol Gridded Observation Networks - Northeast Asia 2012 campaign (DRAGON-NE Asia 2012 campaign). The evaluation during the spring season over East Asia is important because of high aerosol concentrations and diverse types of Asian dust and haze. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single-scattering albedo (SSA) at 440 nm, Ångström exponent (AE) between 440 and 860 nm, and aerosol type. The aerosol models are created based on a global analysis of the Aerosol Robotic Networks (AERONET) inversion data, and covers a broad range of size distribution and absorptivity, including nonspherical dust properties. The Cox-Munk ocean bidirectional reflectance distribution function (BRDF) model is used over ocean, and an improved minimum reflectance technique is used over land. Because turbid water is persistent over the Yellow Sea, the land algorithm is used for such cases. The aerosol products are evaluated against AERONET observations and MODIS Collection 6 aerosol products retrieved from Dark Target (DT) and Deep Blue (DB) algorithms during the DRAGON-NE Asia 2012 campaign conducted from March to May 2012. Comparison of AOD from GOCI and AERONET resulted in a Pearson correlation coefficient of 0.881 and a linear regression equation with GOCI AOD = 1.083 × AERONET AOD - 0.042. The correlation between GOCI and MODIS AODs is higher over ocean than land. GOCI AOD shows better

  16. GOCI Yonsei Aerosol Retrieval (YAER algorithm and validation during DRAGON-NE Asia 2012 campaign

    Directory of Open Access Journals (Sweden)

    M. Choi

    2015-09-01

    Full Text Available The Geostationary Ocean Color Imager (GOCI onboard the Communication, Ocean, and Meteorology Satellites (COMS is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements to the GOCI Yonsei Aerosol Retrieval (YAER algorithm over ocean and land together with validation results during the DRAGON-NE Asia 2012 campaign. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD at 550 nm, fine-mode fraction (FMF at 550 nm, single scattering albedo (SSA at 440 nm, Angstrom exponent (AE between 440 and 860 nm, and aerosol type from selected aerosol models in calculating AOD. Assumed aerosol models are compiled from global Aerosol Robotic Networks (AERONET inversion data, and categorized according to AOD, FMF, and SSA. Nonsphericity is considered, and unified aerosol models are used over land and ocean. Different assumptions for surface reflectance are applied over ocean and land. Surface reflectance over the ocean varies with geometry and wind speed, while surface reflectance over land is obtained from the 1–3 % darkest pixels in a 6 km × 6 km area during 30 days. In the East China Sea and Yellow Sea, significant area is covered persistently by turbid waters, for which the land algorithm is used for aerosol retrieval. To detect turbid water pixels, TOA reflectance difference at 660 nm is used. GOCI YAER products are validated using other aerosol products from AERONET and the MODIS Collection 6 aerosol data from "Dark Target (DT" and "Deep Blue (DB" algorithms during the DRAGON-NE Asia 2012 campaign from March to May 2012. Comparison of AOD from GOCI and AERONET gives a Pearson correlation coefficient of 0.885 and a linear regression equation with GOCI AOD =1.086 × AERONET AOD – 0.041. GOCI and MODIS AODs are more

  17. GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during DRAGON-NE Asia 2012 campaign

    Science.gov (United States)

    Choi, M.; Kim, J.; Lee, J.; Kim, M.; Park, Y. Je; Jeong, U.; Kim, W.; Holben, B.; Eck, T. F.; Lim, J. H.; Song, C. K.

    2015-09-01

    The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorology Satellites (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm over ocean and land together with validation results during the DRAGON-NE Asia 2012 campaign. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single scattering albedo (SSA) at 440 nm, Angstrom exponent (AE) between 440 and 860 nm, and aerosol type from selected aerosol models in calculating AOD. Assumed aerosol models are compiled from global Aerosol Robotic Networks (AERONET) inversion data, and categorized according to AOD, FMF, and SSA. Nonsphericity is considered, and unified aerosol models are used over land and ocean. Different assumptions for surface reflectance are applied over ocean and land. Surface reflectance over the ocean varies with geometry and wind speed, while surface reflectance over land is obtained from the 1-3 % darkest pixels in a 6 km × 6 km area during 30 days. In the East China Sea and Yellow Sea, significant area is covered persistently by turbid waters, for which the land algorithm is used for aerosol retrieval. To detect turbid water pixels, TOA reflectance difference at 660 nm is used. GOCI YAER products are validated using other aerosol products from AERONET and the MODIS Collection 6 aerosol data from "Dark Target (DT)" and "Deep Blue (DB)" algorithms during the DRAGON-NE Asia 2012 campaign from March to May 2012. Comparison of AOD from GOCI and AERONET gives a Pearson correlation coefficient of 0.885 and a linear regression equation with GOCI AOD =1.086 × AERONET AOD - 0.041. GOCI and MODIS AODs are more highly correlated

  18. Meteorological considerations and satellite retrievals in supporting to the assessment of local hydrologic homogeneity over Italy

    Science.gov (United States)

    Gabriele, Salvatore; Laviola, Sante; Chiaravalloti, Francesco

    2014-05-01

    Regional frequency analysis is a useful tool for estimating precipitation quantiles more accurately than at-site frequency analysis, especially in the case of regions with a brief history of short-time rainfall records. Since the rainfalls with short duration are mainly due to convective phenomena, usually affecting areas of few square kilometers, the description of these events with traditional tools such as in-situ rain gauges is often incomplete and not exhaustive. Thus, the application of these datasets to the regional analysis typically provides unrealistic description of the event and large miscalculations of the return time, usually higher than observation. Therefore, in order to evaluate the possible regional homogeneity and improve the performance of hydrologic models the inference analysis of the regional climatic regimes is revealed a useful tool. Starting from the intense rainfall of 19 November 2013 over Southern Italy, we demonstrate that the synoptic meteorological situation well-matched with results of Gabriele & Chiaravalloti (2013a, 2013b) where the regional homogeneity has been calculated on the basis of different climate indexes such as Convective Available Potential Energy (CAPE) and the Q-vector Divergence (QD). In support to that analysis two different methodologies based on satellite microwave information have been applied: the Water vapor Strong Lines at 183 GHz (183-WSL) (Laviola and Levizzani, 2011) algorithm provides to define the precipitation patterns while the MicroWave Cloud Classification (MWCC) (Miglietta et al., 2013) characterizes the cloud type in terms of stratiform and convective. Although, this study is still in progress the current results clearly demonstrate that the Mediterranean storms move on a sort of 'preferential trajectories' especially during the months September-November where the most intense convections have been found. Laviola, S., and V. Levizzani, 2011: The 183-WSL fast rainrate retrieval algorithm. Part I

  19. A level 2 wind speed retrieval algorithm for the CYGNSS mission

    Science.gov (United States)

    Clarizia, Maria Paola; Ruf, Christopher; O'Brien, Andrew; Gleason, Scott

    2014-05-01

    The NASA EV-2 Cyclone Global Navigation Satellite System (CYGNSS) is a spaceborne mission focused on tropical cyclone (TC) inner core process studies. CYGNSS consists of a constellation of 8 microsatellites, which will measure ocean surface wind speed in all precipitating conditions, including those experienced in the TC eyewall, and with sufficient frequency to resolve genesis and rapid intensification. It does so through the use of an innovative remote sensing technique, known as Global Navigation Satellite System-Reflectometry, or GNSS-R. GNSS-R uses signals of opportunity from navigation constellations (e.g. GPS, GLONASS, Galileo), scattered by the surface of the ocean, to retrieve the surface wind speed. The dense space-time sampling capabilities, the ability of L-band signals to penetrate well through rain, and the possibility of simple, low-cost/low-power GNSS receivers, make GNSS-R ideal for the CYGNSS goals. Here we present an overview of a Level 2 (L2) wind speed retrieval algorithm, which would be particularly suitable for CYGNSS, and could be used to estimate winds from GNSS-R in general. The approach makes use of two different observables computed from 1-second Level 2a (L2a) delay-Doppler Maps (DDMs) of radar cross section. The first observable is called Delay-Doppler Map Average (DDMA), and it's the averaged radar cross section over a delay-Doppler window around the DDM peak (i.e. the specular reflection point coordinate in delay and Doppler). The second is called the Leading Edge Slope (LES), and it's the leading edge of the Integrated Delay Waveform (IDW), obtained by integrating the DDM along the Doppler dimension. The observables are calculated over a limited range of delays and Doppler frequencies, to comply with baseline spatial resolution requirements for the retrieved winds, which in the case of CYGNSS is 25 km x 25 km. If the observable from the 1-second DDM corresponds to a resolution higher than the specified one, time-averaging between

  20. Testing the MODIS Satellite Retrieval of Aerosol Fine-Mode Fraction

    Science.gov (United States)

    Anderson, Theodore L.; Wu, Yonghua; Chu, D. Allen; Schmid, Beat; Redemann, Jens; Dubovik, Oleg

    2005-01-01

    Satellite retrievals of the fine-mode fraction (FMF) of midvisible aerosol optical depth, tau, are potentially valuable for constraining chemical transport models and for assessing the global distribution of anthropogenic aerosols. Here we compare satellite retrievals of FMF from the Moderate Resolution Imaging Spectroradiometer (MODIS) to suborbital data on the submicrometer fraction (SMF) of tau. SMF is a closely related parameter that is directly measurable by in situ techniques. The primary suborbital method uses in situ profiling of SMF combined with airborne Sun photometry both to validate the in situ estimate of ambient extinction and to take into account the aerosol above the highest flight level. This method is independent of the satellite retrieval and has well-known accuracy but entails considerable logistical and technical difficulties. An alternate method uses Sun photometer measurements near the surface and an empirical relation between SMF and the Angstrom exponent, A, a measure of the wavelength dependence of optical depth or extinction. Eleven primary and fifteen alternate comparisons are examined involving varying mixtures of dust, sea salt, and pollution in the vicinity of Korea and Japan. MODIS ocean retrievals of FMF are shown to be systematically higher than suborbital estimates of SMF by about 0.2. The most significant cause of this discrepancy involves the relationship between 5 and fine-mode partitioning; in situ measurements indicate a systematically different relationship from what is assumed in the satellite retrievals. Based on these findings, we recommend: (1) satellite programs should concentrate on retrieving and validating since an excellent validation program is in place for doing this, and (2) suborbital measurements should be used to derive relationships between A and fine-mode partitioning to allow interpretation of the satellite data in terms of fine-mode aerosol optical depth.

  1. Efficient Satellite Scheduling Based on Improved Vector Evaluated Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Tengyue Mao

    2012-03-01

    Full Text Available Satellite scheduling is a typical multi-peak, many-valley, nonlinear multi-objective optimization problem. How to effectively implement the satellite scheduling is a crucial research in space areas.This paper mainly discusses the performance of VEGA (Vector Evaluated Genetic Algorithm based on the study of basic principles of VEGA algorithm, algorithm realization and test function, and then improves VEGA algorithm through introducing vector coding, new crossover and mutation operators, new methods to assign fitness and hold good individuals. As a result, the diversity and convergence of improved VEGA algorithm of improved VEGA algorithm have been significantly enhanced and will be applied to Earth-Mars orbit optimization. At the same time, this paper analyzes the results of the improved VEGA, whose results of performance analysis and evaluation show that although VEGA has a profound impact upon multi-objective evolutionary research,  multi-objective evolutionary algorithm on the basis of Pareto seems to be a more effective method to get the non-dominated solutions from the perspective of diversity and convergence of experimental result. Finally, based on Visual C + + integrated development environment, we have implemented improved vector evaluation algorithm in the satellite scheduling.

  2. Comparison between volcanic ash satellite retrievals and FALL3D transport model

    Science.gov (United States)

    Corradini, Stefano; Merucci, Luca; Folch, Arnau

    2010-05-01

    Volcanic eruptions represent one of the most important sources of natural pollution because of the large emission of gas and solid particles into the atmosphere. Volcanic clouds can contain different gas species (mainly H2O, CO2, SO2 and HCl) and a mix of silicate-bearing ash particles in the size range from 0.1 μm to few mm. Determining the properties, movement and extent of volcanic ash clouds is an important scientific, economic, and public safety issue because of the harmful effects on environment, public health and aviation. In particular, real-time tracking and forecasting of volcanic clouds is key for aviation safety. Several encounters of en-route aircrafts with volcanic ash clouds have demonstrated the harming effects of fine ash particles on modern aircrafts. Alongside these considerations, the economical consequences caused by disruption of airports must be also taken into account. Both security and economical issues require robust and affordable ash cloud detection and trajectory forecasting, ideally combining remote sensing and modeling. We perform a quantitative comparison between Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of volcanic ash cloud mass and Aerosol Optical Depth (AOD) with the FALL3D ash dispersal model. MODIS, aboard the NASA-Terra and NASA-Aqua polar satellites, is a multispectral instrument with 36 spectral bands from Visible (VIS) to Thermal InfraRed (TIR) and spatial resolution varying between 250 and 1000 m at nadir. The MODIS channels centered around 11 and 12 mm have been used for the ash retrievals through the Brightness Temperature Difference algorithm and MODTRAN simulations. FALL3D is a 3-D time-dependent Eulerian model for the transport and deposition of volcanic particles that outputs, among other variables, cloud column mass and AOD. We consider the Mt. Etna volcano 2002 eruptive event as a test case. Results show a good agreement between the mean AOT retrieved and the spatial ash dispersion in the

  3. Mapping cultivable land from satellite imagery with clustering algorithms

    Science.gov (United States)

    Arango, R. B.; Campos, A. M.; Combarro, E. F.; Canas, E. R.; Díaz, I.

    2016-07-01

    Open data satellite imagery provides valuable data for the planning and decision-making processes related with environmental domains. Specifically, agriculture uses remote sensing in a wide range of services, ranging from monitoring the health of the crops to forecasting the spread of crop diseases. In particular, this paper focuses on a methodology for the automatic delimitation of cultivable land by means of machine learning algorithms and satellite data. The method uses a partition clustering algorithm called Partitioning Around Medoids and considers the quality of the clusters obtained for each satellite band in order to evaluate which one better identifies cultivable land. The proposed method was tested with vineyards using as input the spectral and thermal bands of the Landsat 8 satellite. The experimental results show the great potential of this method for cultivable land monitoring from remote-sensed multispectral imagery.

  4. PM-GCD – a combined IR–MW satellite technique for frequent retrieval of heavy precipitation

    Directory of Open Access Journals (Sweden)

    D. Casella

    2012-01-01

    Full Text Available Precipitation retrievals based on measurements from microwave (MW radiometers onboard low-Earth-orbit (LEO satellites can reach high level of accuracy – especially regarding convective precipitation. At the present stage though, these observations cannot provide satisfactory coverage of the evolution of intense and rapid precipitating systems. As a result, the obtained precipitation retrievals are often of limited use for many important applications – especially in supporting authorities for flood alerts and weather warnings. To tackle this problem, over the past two decades several techniques have been developed combining accurate MW estimates with frequent infrared (IR observations from geosynchronous (GEO satellites, such as the European Meteosat Second Generation (MSG. In this framework, we have developed a new fast and simple precipitation retrieval technique which we call Passive Microwave – Global Convective Diagnostic, (PM-GCD. This method uses MW retrievals in conjunction with the Global Convective Diagnostic (GCD technique which discriminates deep convective clouds based on the difference between the MSG water vapor (6.2 μm and thermal-IR (10.8 μm channels. Specifically, MSG observations and the GCD technique are used to identify deep convective areas. These areas are then calibrated using MW precipitation estimates based on observations from the Advanced Microwave Sounding Unit (AMSU radiometers onboard operational NOAA and Eumetsat satellites, and then finally propagated in time with a simple tracking algorithm. In this paper, we describe the PM-GCD technique, analyzing its results for a case study that refers to a flood event that struck the island of Sicily in southern Italy on 1–2 October 2009.

  5. A Fast Prediction Algorithm of Satellite Passes

    OpenAIRE

    Palmer, P. L.; Mai, Yan

    2000-01-01

    Low cost, fast access and multi-functional small satellites are being increasingly used to provide and exchange information for a wide variety of professions. They are particularly useful, for example, as a resource in very remote areas where they can provide useful information such as to rescue teams for changing conditions in a disaster zone and monitoring the sea state to warn approaching shipping. Unlike terrestrial communication systems, the receiver/transmitter in these di_erent applica...

  6. Satellite-retrieval and modeling of glacier mass balance

    NARCIS (Netherlands)

    Ruyter de Wildt, Martijn Sybren de

    2002-01-01

    In this research project we use satellite measurements to infer the mean specific mass balance (Bm) of glaciers. Vatnajökull, the largest ice cap in Europe, is being used as a test-case because this ice cap has often been studied. Only one aspect of Vatnajökull has not been investigated so far, and

  7. Retrieval algorithm of sea surface wind vectors for WindSat based on a simple forward model

    Institute of Scientific and Technical Information of China (English)

    ZHAO Yili

    2013-01-01

    WindSat/Coriolis is the first satellite-borne polarimetric microwave radiometer,which aims to improve the potential of polarimetric microwave radiometry for measuring sea surface wind vectors from space.In this paper,a wind vector retrieval algorithm based on a novel and simple forward model was developed for WindSat.The retrieval algorithm of sea surface wind speed was developed using multiple linear regression based on the simulation dataset of the novel forward model.Sea surface wind directions that minimize the difference between simulated and measured values of the third and fourth Stokes parameters were found using maximum likelihood estimation,by which a group of ambiguous wind directions was obtained.A median filter was then used to remove ambiguity of wind direction.Evaluated with sea surface wind speed and direction data from the U.S.National Data Buoy Center (NDBC),root mean square errors are 1.2 m/s and 30° for retrieved wind speed and wind direction,respectively.The evaluation results suggest that the simple forward model and the retrieval algorithm are practicable for near-real time applications,without reducing accuracy.

  8. Retrieval of Atmospheric Horizontal Visibility by Statistical Regression from NOAA/AVHRR Satellite Data

    Institute of Scientific and Technical Information of China (English)

    HUANG Fei; WANG Hong; QIAN Junping; WANG Guofu

    2006-01-01

    Based on the atmospheric horizontal visibility data from forty-seven observational stations along the eastern coast of China near the Taiwan Strait and simultaneous NOAA/AVHRR multichannel satellite data during January 2001 to December 2002, the spectral characters associated with visibility were investigated.Successful retrieval of visibility from multichannel NOAA/AVHRR data was performed using the principal component regression (PCR) method.A sample of retrieved visibility distribution was discussed with a sea fog process.The correlation coefficient between the observed and retrieved visibility was about 0.82, which is far higher than the 99.9% confidence level by statistical test.The rate of successful retrieval is 94.98% of the 458 cases during 2001- 2002.The error distribution showed that high visibilities were usually under-estimated and low visibilities were over-estimated and the relative error between the observed and retrieved visibilities was about 21.4%.

  9. An Improved Mono-Window Algorithm for Land Surface Temperature Retrieval from Landsat 8 Thermal Infrared Sensor Data

    Directory of Open Access Journals (Sweden)

    Fei Wang

    2015-04-01

    Full Text Available The successful launch of the Landsat 8 satellite with two thermal infrared bands on February 11, 2013, for continuous Earth observation provided another opportunity for remote sensing of land surface temperature (LST. However, calibration notices issued by the United States Geological Survey (USGS indicated that data from the Landsat 8 Thermal Infrared Sensor (TIRS Band 11 have large uncertainty and suggested using TIRS Band 10 data as a single spectral band for LST estimation. In this study, we presented an improved mono-window (IMW algorithm for LST retrieval from the Landsat 8 TIRS Band 10 data. Three essential parameters (ground emissivity, atmospheric transmittance and effective mean atmospheric temperature were required for the IMW algorithm to retrieve LST. A new method was proposed to estimate the parameter of effective mean atmospheric temperature from local meteorological data. The other two essential parameters could be both estimated through the so-called land cover approach. Sensitivity analysis conducted for the IMW algorithm revealed that the possible error in estimating the required atmospheric water vapor content has the most significant impact on the probable LST estimation error. Under moderate errors in both water vapor content and ground emissivity, the algorithm had an accuracy of ~1.4 K for LST retrieval. Validation of the IMW algorithm using the simulated datasets for various situations indicated that the LST difference between the retrieved and the simulated ones was 0.67 K on average, with an RMSE of 0.43 K. Comparison of our IMW algorithm with the single-channel (SC algorithm for three main atmosphere profiles indicated that the average error and RMSE of the IMW algorithm were −0.05 K and 0.84 K, respectively, which were less than the −2.86 K and 1.05 K of the SC algorithm. Application of the IMW algorithm to Nanjing and its vicinity in east China resulted in a reasonable LST estimation for the region. Spatial

  10. CMA: an efficient index algorithm of clustering supporting fast retrieval of large image databases

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    To realize content-based retrieval of large image databases, it is required to develop an efficient index and retrieval scheme. This paper proposes an index algorithm of clustering called CMA, which supports fast retrieval of large image databases. CMA takes advantages of k-means and self-adaptive algorithms. It is simple and works without any user interactions. There are two main stages in this algorithm. In the first stage, it classifies images in a database into several clusters, and automatically gets the necessary parameters for the next stage-k-means iteration. The CMA algorithm is tested on a large database of more than ten thousand images and compare it with k-means algorithm. Experimental results show that this algorithm is effective in both precision and retrieval time.

  11. The 183-WSL Fast Rain Rate Retrieval Algorithm. Part II: Validation Using Ground Radar Measurements

    Science.gov (United States)

    Laviola, Sante; Levizzani, Vincenzo

    2014-01-01

    The Water vapour Strong Lines at 183 GHz (183-WSL) algorithm is a method for the retrieval of rain rates and precipitation type classification (convectivestratiform), that makes use of the water vapor absorption lines centered at 183.31 GHz of the Advanced Microwave Sounding Unit module B (AMSU-B) and of the Microwave Humidity Sounder (MHS) flying on NOAA-15-18 and NOAA-19Metop-A satellite series, respectively. The characteristics of this algorithm were described in Part I of this paper together with comparisons against analogous precipitation products. The focus of Part II is the analysis of the performance of the 183-WSL technique based on surface radar measurements. The ground truth dataset consists of 2.5 years of rainfall intensity fields from the NIMROD European radar network which covers North-Western Europe. The investigation of the 183-WSL retrieval performance is based on a twofold approach: 1) the dichotomous statistic is used to evaluate the capabilities of the method to identify rain and no-rain clouds; 2) the accuracy statistic is applied to quantify the errors in the estimation of rain rates.The results reveal that the 183-WSL technique shows good skills in the detection of rainno-rain areas and in the quantification of rain rate intensities. The categorical analysis shows annual values of the POD, FAR and HK indices varying in the range 0.80-0.82, 0.330.36 and 0.39-0.46, respectively. The RMSE value is 2.8 millimeters per hour for the whole period despite an overestimation in the retrieved rain rates. Of note is the distribution of the 183-WSL monthly mean rain rate with respect to radar: the seasonal fluctuations of the average rainfalls measured by radar are reproduced by the 183-WSL. However, the retrieval method appears to suffer for the winter seasonal conditions especially when the soil is partially frozen and the surface emissivity drastically changes. This fact is verified observing the discrepancy distribution diagrams where2the 183-WSL

  12. Retrieving Marine Inherent Optical Properties from Satellites Using Temperature and Salinity-dependent Backscattering by Seawater

    Science.gov (United States)

    Werdell, Paul J.; Franz, Bryan Alden; Lefler, Jason Travis; Robinson, Wayne D.; Boss, Emmanuel

    2013-01-01

    Time-series of marine inherent optical properties (IOPs) from ocean color satellite instruments provide valuable data records for studying long-term time changes in ocean ecosystems. Semi-analytical algorithms (SAAs) provide a common method for estimating IOPs from radiometric measurements of the marine light field. Most SAAs assign constant spectral values for seawater absorption and backscattering, assume spectral shape functions of the remaining constituent absorption and scattering components (e.g., phytoplankton, non-algal particles, and colored dissolved organic matter), and retrieve the magnitudes of each remaining constituent required to match the spectral distribution of measured radiances. Here, we explore the use of temperature- and salinity-dependent values for seawater backscattering in lieu of the constant spectrum currently employed by most SAAs. Our results suggest that use of temperature- and salinity-dependent seawater spectra elevate the SAA-derived particle backscattering, reduce the non-algal particles plus colored dissolved organic matter absorption, and leave the derived absorption by phytoplankton unchanged.

  13. SOLUTION OF THE SATELLITE TRANSFER PROBLEM WITH HYBRID MEMETIC ALGORITHM

    Directory of Open Access Journals (Sweden)

    A. V. Panteleyev

    2014-01-01

    Full Text Available This paper presents a hybrid memetic algorithm (MA to solve the problem of finding the optimal program control of nonlinear continuous deterministic systems based on the concept of the meme, which is one of the promising solutions obtained in the course of implementing the procedure for searching the extremes. On the basis of the proposed algorithm the software complex is formed in C#. The solution of satellite transfer problem is presented.

  14. Bayesian Estimation of Precipitation from Satellite Passive Microwave Observations Using Combined Radar-Radiometer Retrievals

    Science.gov (United States)

    Grecu, Mircea; Olson, William S.

    2006-01-01

    Precipitation estimation from satellite passive microwave radiometer observations is a problem that does not have a unique solution that is insensitive to errors in the input data. Traditionally, to make this problem well posed, a priori information derived from physical models or independent, high-quality observations is incorporated into the solution. In the present study, a database of precipitation profiles and associated brightness temperatures is constructed to serve as a priori information in a passive microwave radiometer algorithm. The precipitation profiles are derived from a Tropical Rainfall Measuring Mission (TRMM) combined radar radiometer algorithm, and the brightness temperatures are TRMM Microwave Imager (TMI) observed. Because the observed brightness temperatures are consistent with those derived from a radiative transfer model embedded in the combined algorithm, the precipitation brightness temperature database is considered to be physically consistent. The database examined here is derived from the analysis of a month-long record of TRMM data that yields more than a million profiles of precipitation and associated brightness temperatures. These profiles are clustered into a tractable number of classes based on the local sea surface temperature, a radiometer-based estimate of the echo-top height (the height beyond which the reflectivity drops below 17 dBZ), and brightness temperature principal components. For each class, the mean precipitation profile, brightness temperature principal components, and probability of occurrence are determined. The precipitation brightness temperature database supports a radiometer-only algorithm that incorporates a Bayesian estimation methodology. In the Bayesian framework, precipitation estimates are weighted averages of the mean precipitation values corresponding to the classes in the database, with the weights being determined according to the similarity between the observed brightness temperature principal

  15. On the retrieval of significant wave heights from spaceborne Synthetic Aperture Radar using the Max-Planck Institut algorithm.

    Science.gov (United States)

    Violante-Carvalho, Nelson

    2005-12-01

    Synthetic Aperture Radar (SAR) onboard satellites is the only source of directional wave spectra with continuous and global coverage. Millions of SAR Wave Mode (SWM) imagettes have been acquired since the launch in the early 1990's of the first European Remote Sensing Satellite ERS-1 and its successors ERS-2 and ENVISAT, which has opened up many possibilities specially for wave data assimilation purposes. The main aim of data assimilation is to improve the forecasting introducing available observations into the modeling procedures in order to minimize the differences between model estimates and measurements. However there are limitations in the retrieval of the directional spectrum from SAR images due to nonlinearities in the mapping mechanism. The Max-Planck Institut (MPI) scheme, the first proposed and most widely used algorithm to retrieve directional wave spectra from SAR images, is employed to compare significant wave heights retrieved from ERS-1 SAR against buoy measurements and against the WAM wave model. It is shown that for periods shorter than 12 seconds the WAM model performs better than the MPI, despite the fact that the model is used as first guess to the MPI method, that is the retrieval is deteriorating the first guess. For periods longer than 12 seconds, the part of the spectrum that is directly measured by SAR, the performance of the MPI scheme is at least as good as the WAM model.

  16. Simulation of land surface temperatures: comparison of two climate models and satellite retrievals

    Directory of Open Access Journals (Sweden)

    J. M. Edwards

    2009-03-01

    Full Text Available Recently there has been significant progress in the retrieval of land surface temperature from satellite observations. Satellite retrievals of surface temperature offer several advantages, including broad spatial coverage, and such data are potentially of great value in assessing general circulation models of the atmosphere. Here, retrievals of the land surface temperature over the contiguous United States are compared with simulations from two climate models. The models generally simulate the diurnal range realistically, but show significant warm biases during the summer. The models' diurnal cycle of surface temperature is related to their surface flux budgets. Differences in the diurnal cycle of the surface flux budget between the models are found to be more pronounced than those in the diurnal cycle of surface temperature.

  17. Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers

    Science.gov (United States)

    Rosenfeld, Daniel; Zheng, Youtong; Hashimshoni, Eyal; Pöhlker, Mira L.; Jefferson, Anne; Pöhlker, Christopher; Yu, Xing; Zhu, Yannian; Liu, Guihua; Yue, Zhiguo; Fischman, Baruch; Li, Zhanqing; Giguzin, David; Goren, Tom; Artaxo, Paulo; Pöschl, Ulrich

    2016-01-01

    Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. Our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation (S) is determined by Wb and the satellite-retrieved cloud base drop concentrations (Ndb), which is the same as CCN(S). Validation against ground-based CCN instruments at Oklahoma, at Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. The limitation for small solar backscattering angles of <25° restricts the satellite coverage to ∼25% of the world area in a single day. PMID:26944081

  18. The Multi-Sensor Aerosol Products Sampling System (MAPSS) for Integrated Analysis of Satellite Retrieval Uncertainties

    Science.gov (United States)

    Ichoku, Charles; Petrenko, Maksym; Leptoukh, Gregory

    2010-01-01

    Among the known atmospheric constituents, aerosols represent the greatest uncertainty in climate research. Although satellite-based aerosol retrieval has practically become routine, especially during the last decade, there is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. As long as there is no consensus and the inconsistencies are not well characterized and understood ', there will be no way of developing reliable climate data records from satellite aerosol measurements. Fortunately, the most globally representative well-calibrated ground-based aerosol measurements corresponding to the satellite-retrieved products are available from the Aerosol Robotic Network (AERONET). To adequately utilize the advantages offered by this vital resource,., an online Multi-sensor Aerosol Products Sampling System (MAPSS) was recently developed. The aim of MAPSS is to facilitate detailed comparative analysis of satellite aerosol measurements from different sensors (Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and Calipso-CALIOP) based on the collocation of these data products over AERONET stations. In this presentation, we will describe the strategy of the MAPSS system, its potential advantages for the aerosol community, and the preliminary results of an integrated comparative uncertainty analysis of aerosol products from multiple satellite sensors.

  19. An Introduction to Genetic Algorithms and to Their Use in Information Retrieval.

    Science.gov (United States)

    Jones, Gareth; And Others

    1994-01-01

    Genetic algorithms, a class of nondeterministic algorithms in which the role of chance makes the precise nature of a solution impossible to guarantee, seem to be well suited to combinatorial-optimization problems in information retrieval. Provides an introduction to techniques and characteristics of genetic algorithms and illustrates their…

  20. Heuristic Scheduling Algorithm Oriented Dynamic Tasks for Imaging Satellites

    Directory of Open Access Journals (Sweden)

    Maocai Wang

    2014-01-01

    Full Text Available Imaging satellite scheduling is an NP-hard problem with many complex constraints. This paper researches the scheduling problem for dynamic tasks oriented to some emergency cases. After the dynamic properties of satellite scheduling were analyzed, the optimization model is proposed in this paper. Based on the model, two heuristic algorithms are proposed to solve the problem. The first heuristic algorithm arranges new tasks by inserting or deleting them, then inserting them repeatedly according to the priority from low to high, which is named IDI algorithm. The second one called ISDR adopts four steps: insert directly, insert by shifting, insert by deleting, and reinsert the tasks deleted. Moreover, two heuristic factors, congestion degree of a time window and the overlapping degree of a task, are employed to improve the algorithm’s performance. Finally, a case is given to test the algorithms. The results show that the IDI algorithm is better than ISDR from the running time point of view while ISDR algorithm with heuristic factors is more effective with regard to algorithm performance. Moreover, the results also show that our method has good performance for the larger size of the dynamic tasks in comparison with the other two methods.

  1. A Survey of Stemming Algorithms in Information Retrieval

    Science.gov (United States)

    Moral, Cristian; de Antonio, Angélica; Imbert, Ricardo; Ramírez, Jaime

    2014-01-01

    Background: During the last fifty years, improved information retrieval techniques have become necessary because of the huge amount of information people have available, which continues to increase rapidly due to the use of new technologies and the Internet. Stemming is one of the processes that can improve information retrieval in terms of…

  2. Influence of 3D Radiative Effects on Satellite Retrievals of Cloud Properties

    Science.gov (United States)

    Varnai, Tamas; Marshak, Alexander; Einaudi, Franco (Technical Monitor)

    2001-01-01

    When cloud properties are retrieved from satellite observations, the calculations apply 1D theory to the 3D world: they only consider vertical structures and ignore horizontal cloud variability. This presentation discusses how big the resulting errors can be in the operational retrievals of cloud optical thickness. A new technique was developed to estimate the magnitude of potential errors by analyzing the spatial patterns of visible and infrared images. The proposed technique was used to set error bars for optical depths retrieved from new MODIS measurements. Initial results indicate that the 1 km resolution retrievals are subject to abundant uncertainties. Averaging over 50 by 50 km areas reduces the errors, but does not remove them completely; even in the relatively simple case of high sun (30 degree zenith angle), about a fifth of the examined areas had biases larger than ten percent. As expected, errors increase substantially for more oblique illumination.

  3. Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals

    Directory of Open Access Journals (Sweden)

    Y. Y. Liu

    2010-09-01

    Full Text Available Combining information derived from satellite-based passive and active microwave sensors has the potential to offer improved retrievals of surface soil moisture variations at global scales. Here we propose a technique to take advantage of retrieval characteristics of passive (AMSR-E and active (ASCAT microwave satellite estimates over sparse-to-moderately vegetated areas to obtain an improved soil moisture product. To do this, absolute soil moisture values from AMSR-E and relative soil moisture derived from ASCAT are rescaled against a reference land surface model date set using a cumulative distribution function (CDF matching approach. While this technique imposes the bias of the reference to the rescaled satellite products, it adjusts both satellite products to the same range and almost preserves the correlation between satellite products and in situ measurements. Comparisons with in situ data demonstrated that over the regions where the correlation coefficient between rescaled AMSR-E and ASCAT is above 0.65 (hereafter referred to as transitional regions, merging the different satellite products together increases the number of observations while minimally changing the accuracy of soil moisture retrievals. These transitional regions also delineate the boundary between sparsely and moderately vegetated regions where rescaled AMSR-E and ASCAT are respectively used in the merged product. Thus the merged product carries the advantages of better spatial coverage overall and increased number of observations particularly for the transitional regions. The combination approach developed in this study has the potential to be applied to existing microwave satellites as well as to new microwave missions. Accordingly, a long-term global soil moisture dataset can be developed and extended, enhancing basic understanding of the role of soil moisture in the water, energy and carbon cycles.

  4. Towards a surface radiation climatology: Retrieval of downward irradiances from satellites

    Science.gov (United States)

    Schmetz, Johannes

    Methods are reviewed for retrieving the downward shortwave (0.3-4 μm) and longwave (4-100 μm) irradiances at the earth's surface from satellites. Emphasis is placed on elucidating the physical aspects relevant to the satellite retrieval. For the shortwave irradiance an example of a retrieval is presented. The shortwave retrieval is facilitated by a close linear coupling between the reflected radiance field at the top of the atmosphere and the surface irradiance. A linear relationship between planetary albedo and surface irradiance does also account properly for cloud absorption, since cloud absorption and albedo are linearly related. In the longwave the retrieval is more difficult since only atmospheric window radiances at the top of the atmosphere can bear information on the near-surface radiation field. For the remainder of the longwave spectrum the radiation regimes at the top of the atmosphere and at the surface are decoupled. More than 80% of the clear-sky longwave flux reaching the surface is emitted within the lowest 500 m of the atmosphere. In cloudy conditions the radiation fields at the surface and at the top of the atmosphere are entirely decoupled. Cloud contributions to the surface irradiance are important within the atmospheric window (8-13 μm) and the relative contribution increases in drier climates. Summaries are presented of various techniques devised for both the solar and longwave surface irradiances. A compilation of reported standard errors of shortwave techniques in comparison with ground measurements yields median values of about 5% and 10% for monthly and daily mean values, respectively. Standard errors for the longwave are of the order of 10-25 W m -2. Reported biases are typically of the order of 5 W m -2. For the shortwave retrieval there are fairly good prospects to obtain monthly mean estimates with the requested accuracy of about 10 W m -2 over regional scale areas. The inherent problems of the longwave still entails improvements

  5. Bridging Ground Validation and Algorithms: Using Scattering and Integral Tables to Incorporate Observed DSD Correlations into Satellite Algorithms

    Science.gov (United States)

    Williams, C. R.

    2012-12-01

    The NASA Global Precipitation Mission (GPM) raindrop size distribution (DSD) Working Group is composed of NASA PMM Science Team Members and is charged to "investigate the correlations between DSD parameters using Ground Validation (GV) data sets that support, or guide, the assumptions used in satellite retrieval algorithms." Correlations between DSD parameters can be used to constrain the unknowns and reduce the degrees-of-freedom in under-constrained satellite algorithms. Over the past two years, the GPM DSD Working Group has analyzed GV data and has found correlations between the mass-weighted mean raindrop diameter (Dm) and the mass distribution standard deviation (Sm) that follows a power-law relationship. This Dm-Sm power-law relationship appears to be robust and has been observed in surface disdrometer and vertically pointing radar observations. One benefit of a Dm-Sm power-law relationship is that a three parameter DSD can be modeled with just two parameters: Dm and Nw that determines the DSD amplitude. In order to incorporate observed DSD correlations into satellite algorithms, the GPM DSD Working Group is developing scattering and integral tables that can be used by satellite algorithms. Scattering tables describe the interaction of electromagnetic waves on individual particles to generate cross sections of backscattering, extinction, and scattering. Scattering tables are independent of the distribution of particles. Integral tables combine scattering table outputs with DSD parameters and DSD correlations to generate integrated normalized reflectivity, attenuation, scattering, emission, and asymmetry coefficients. Integral tables contain both frequency dependent scattering properties and cloud microphysics. The GPM DSD Working Group has developed scattering tables for raindrops at both Dual Precipitation Radar (DPR) frequencies and at all GMI radiometer frequencies less than 100 GHz. Scattering tables include Mie and T-matrix scattering with H- and V

  6. Optimal reconfiguration of satellite constellations with the auction algorithm

    Science.gov (United States)

    de Weck, Olivier L.; Scialom, Uriel; Siddiqi, Afreen

    2008-01-01

    Traditionally, satellite constellation design has focused on optimizing global, zonal or regional coverage with a minimum number of satellites. In some instances, however, it is desirable to deploy a constellation in stages to gradually expand capacity. This requires launching additional satellites and reconfiguring the existing on-orbit satellites. Also, a constellation might be retasked and reconfigured after it is initially fielded for operational reasons. This paper presents a methodology for optimizing orbital reconfigurations of satellite constellations. The work focuses on technical aspects for transforming an initial constellation A into a new constellation, B, typically with a larger number of satellites. A general framework was developed to study the orbital reconfiguration problem. The framework was applied to low Earth orbit constellations of communication satellites. This paper specifically addresses the problem of determining the optimal assignment for transferring on-orbit satellites in constellation A to constellation B such that the total ΔV for the reconfiguration is minimized. It is shown that the auction algorithm, used for solving general network flow problems, can efficiently and reliably determine the optimum assignment of satellites of A to slots of B. Based on this methodology, reconfiguration maps can be created, which show the energy required for transforming one constellation into another as a function of type (Street-of-Coverage, Walker, Draim), altitude, ground elevation angle and fold of coverage. Suggested extensions of this work include quantification of the tradeoff between reconfiguration time and ΔV, multiple successive reconfigurations, balancing propellant consumption within the constellation during reconfiguration as well as using reconfigurability as an objective during initial constellation design.

  7. Retrieving leaf area index from SPOT4 satellite data

    Directory of Open Access Journals (Sweden)

    M. Aboelghar

    2010-12-01

    Full Text Available A research project was conducted as collaboration between the National Authority for Remote Sensing and Space Sciences (NARSS in Egypt and the Institute of Remote Sensing Applications (IRSA, Chinese Academy of Sciences. The objective of this study is to generate normalized difference vegetation index (NDVI–leaf area index (LAI statistical inversion models for three rice varieties planted in Egypt (Giza-178, Sakha-102, and Sakha-104 using the data of two rice growing seasons. Field observations were carried out to collect LAI field measurements during 2008 and 2009 rice seasons. The SPOT4 satellite data acquired in rice season of 2008 and 2009 conjunction with field observations dates were used to calculate the vegetation indices values. Statistical analyses were performed to confirm the assumptions of inversion modeling for plant variables and to get reliable models that fit the inversion relationship between LAI and NDVI. The inversion process resulted in three NDVI–LAI models adequate to predict LAI with 95% confidence for the three different rice varieties. The accuracy of the generated models ranged between 50% in the case of Sakha-104 and 82% in the case of Giza-178. LAI maps were produced from NDVI imageries based on the generated models.

  8. Retrieval of frontal cloudiness microstructure characteristics from satellite radiometeric data

    Science.gov (United States)

    Bakhanov, V.; Dorman, B.; Kryvobok, A.

    This paper presents results of consecutive numerical simulation of the NOAA satellite signal reflectance of frontal mixed stratiform clouds for channels of AVHRR in visible and near infrared regions of spectrum The simulation is based on the next models a The time-dependent numerical microphysical model of stratiform frontal clouds with 3 forms of ice crystals needles plates columnes b Models of computations of scattering characteristics of drop and crystal systems Simulations of scattering characteristics of liquid drops are based on the Mie theory Simulations of scattering properties of randomly oriented ice crystals are based on the geometric optics and far-field diffraction approximation Computations were realized in visible and near-infrared part of spectrum lambda 1 0 55 mu m lambda 2 1 6 mu m lambda quad 3 quad quad 3 6 quad mu m c The Discrete Ordinate Method DOM for simulation of solar radiation transfer in not uniform clouds Simulations of CR cloud reflrctance show that CR lambda 1 and CR lambda 2 change synchronously with the cloud intrgral optical thickness IOT which is detrmined basically with liquid water content LWC The channel lambda quad 3 3 6 mu m is less sensible to the optical thickness CR lambda 2 and CR lambda 3 are very different in a great LWC region but become close in a region of significant crystallization and precipitation The comparison CR lambda 1 CR lambda quad 2 CR lambda 3 gives

  9. Experiments in Discourse Analysis Impact on Information Classification and Retrieval Algorithms.

    Science.gov (United States)

    Morato, Jorge; Llorens, J.; Genova, G.; Moreiro, J. A.

    2003-01-01

    Discusses the inclusion of contextual information in indexing and retrieval systems to improve results and the ability to carry out text analysis by means of linguistic knowledge. Presents research that investigated whether discourse variables have an impact on information and retrieval and classification algorithms. (Author/LRW)

  10. Surface Emissivity Retrieved with Satellite Ultraspectral IR Measurements for Monitoring Global Change

    Science.gov (United States)

    Zhou, Daniel K.; Larar, Allen M.; Liu, Xu; Smith, William L.; Schluessel, Peter

    2009-01-01

    Surface and atmospheric thermodynamic parameters retrieved with advanced ultraspectral remote sensors aboard Earth observing satellites are critical to general atmospheric and Earth science research, climate monitoring, and weather prediction. Ultraspectral resolution infrared radiance obtained from nadir observations provide atmospheric, surface, and cloud information. Presented here is the global surface IR emissivity retrieved from Infrared Atmospheric Sounding Interferometer (IASI) measurements under "clear-sky" conditions. Fast radiative transfer models, applied to the cloud-free (or clouded) atmosphere, are used for atmospheric profile and surface parameter (or cloud parameter) retrieval. The inversion scheme, dealing with cloudy as well as cloud-free radiances observed with ultraspectral infrared sounders, has been developed to simultaneously retrieve atmospheric thermodynamic and surface (or cloud microphysical) parameters. Rapidly produced surface emissivity is initially evaluated through quality control checks on the retrievals of other impacted atmospheric and surface parameters. Surface emissivity and surface skin temperature from the current and future operational satellites can and will reveal critical information on the Earth s ecosystem and land surface type properties, which can be utilized as part of long-term monitoring for the Earth s environment and global climate change.

  11. Improvements and Extensions for Joint Polar Satellite System Algorithms

    Science.gov (United States)

    Grant, K. D.

    2016-12-01

    The National Oceanic and Atmospheric Administration (NOAA) and National Aeronautics and Space Administration (NASA) are jointly acquiring the next-generation civilian weather satellite system: the Joint Polar Satellite System (JPSS). JPSS replaced the afternoon orbit component and ground processing of the old POES system managed by NOAA. JPSS satellites carry sensors designed to collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The ground processing system for JPSS is the Common Ground System (CGS), and provides command, control, and communications (C3), data processing and product delivery. CGS's data processing capability provides environmental data products (Sensor Data Records (SDRs) and Environmental Data Records (EDRs)) to the NOAA Satellite Operations Facility. The first satellite in the JPSS constellation, S-NPP, was launched in October 2011. The second satellite, JPSS-1, is scheduled for launch in January 2017. During a satellite's calibration and validation (Cal/Val) campaign, numerous algorithm updates occur. Changes identified during Cal/Val become available for implementation into the operational system for both S-NPP and JPSS-1. In addition, new capabilities, such as higher spectral and spatial resolution, will be exercised on JPSS-1. This paper will describe changes to current algorithms and products as a result of S-NPP Cal/Val and related initiatives for improved capabilities. Improvements include Cross Track Infrared Sounder high spectral processing, extended spectral and spatial ranges for Ozone Mapping and Profiler Suite ozone Total Column and Nadir Profiles, and updates to Vegetation Index, Snow Cover, Active Fires, Suspended Matter, and Ocean Color. Updates will include Sea Surface Temperature, Cloud Mask, Cloud Properties, and other improvements.

  12. Satellite Retrieval of Precipitation: An Overview%卫星遥感反演降水研究综述

    Institute of Scientific and Technical Information of China (English)

    刘元波; 傅巧妮; 宋平; 赵晓松; 豆翠翠

    2011-01-01

    Precipitation is a fundamental component of the global water cycle. It is a key hydrologic variable of the water cycle in meteorology, climatology and hydrology. Accurate observation of precipitation and its regional, global distributions has long been a challenging scientific goal. With five-decade development of space-borne sen- sors, the approaches to retrieving precipitation appear mature. This paper briefly describes the principles and the main types of retrieval algorithms of precipitation using visible/infrared (VIS/IR), passive-microwave (PMW), precipitation radar (PR) data, or their combinations. The VIS/IR algorithms generally had relatively low retrieval accuracy, but it could provide better long-term retrieval due to better temporal sampling of geostationary data. The PMW algorithms were more accurate but more complicated than the VIS/IR algorithms in retrieval of instantaneous precipitation, and the PMW data had low spatial and temporal resolution. Among all the PMW algorithms, the God- dard Profiling Algorithm (GPROF) is the most widely applied one. The PR algorithm enabled capture of three-di- mensional precipitation structure over the ocean and land. While the PR retrievals had accuracy on the order of ground-radar data, it had limited coverage of the Earth' s surface. The deficiencies of a single sensor algorithm were alleviated with the combination use of multi-sensors. A number of algorithms have been proposed with a parti- cular combination of VIS/IR, PMW, and/or PR data. The commonly used algorithms include the Climate Predic- tion Center Morphing (CMORPH) algorithm, the Tropical Rainfall Measuring Mission (TRMM) Muhisatellite Pre- cipitation Analysis (TMPA) algorithm and the Global Satellite Mapping of Precipitation (GSMaP) algorithm. Cur- rently, scientific efforts have been made to compare and evaluate the existing algorithms, for example, the Programto Evaluate High-Resolution Precipitation Products

  13. Accurate Image Retrieval Algorithm Based on Color and Texture Feature

    Directory of Open Access Journals (Sweden)

    Chunlai Yan

    2013-06-01

    Full Text Available Content-Based Image Retrieval (CBIR is one of the most active hot spots in the current research field of multimedia retrieval. According to the description and extraction of visual content (feature of the image, CBIR aims to find images that contain specified content (feature in the image database. In this paper, several key technologies of CBIR, e. g. the extraction of the color and texture features of the image, as well as the similarity measures are investigated. On the basis of the theoretical research, an image retrieval system based on color and texture features is designed. In this system, the Weighted Color Feature based on HSV space is adopted as a color feature vector, four features of the Co-occurrence Matrix, saying Energy, Entropy, Inertia Quadrature and Correlation, are used to construct texture vectors, and the Euclidean distance for similarity measure is employed as well. Experimental results show that this CBIR system is efficient in image retrieval.

  14. Phase-retrieval algorithms applied in a 4-f system for optical image encryption: a comparison

    Science.gov (United States)

    Situ, Guohai; Zhang, Jingjuan

    2005-01-01

    Phase retrieval algorithms based on 4-f system for optical image encryption are compared in respect of the image retrieval quality and the convergence. Simulation results show that enlarging the searching space can decrypt the image with extremely high quality, while employing the searching strategy of modifying both the phase-distributions in the input and the frequency planes can result in much faster convergence for the algorithm.

  15. Deriving atmospheric visibility from satellite retrieved aerosol optical depth

    Science.gov (United States)

    Riffler, M.; Schneider, Ch.; Popp, Ch.; Wunderle, S.

    2009-04-01

    Atmospheric visibility is a measure that reflects different physical and chemical properties of the atmosphere. In general, poor visibility conditions come along with risks for transportation (e.g. road traffic, aviation) and can negatively impact human health since visibility impairment often implies the presence of atmospheric pollution. Ambient pollutants, particulate matter, and few gaseous species decrease the perceptibility of distant objects. Common estimations of this parameter are usually based on human observations or devices that measure the transmittance of light from an artificial light source over a short distance. Such measurements are mainly performed at airports and some meteorological stations. A major disadvantage of these observations is the gap between the measurements, leaving large areas without any information. As aerosols are one of the most important factors influencing atmospheric visibility in the visible range, the knowledge of their spatial distribution can be used to infer visibility with the so called Koschmieder equation, which relates visibility and atmospheric extinction. In this study, we evaluate the applicability of satellite aerosol optical depth (AOD) products from the Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) to infer atmospheric visibility on large spatial scale. First results applying AOD values scaled with the planetary boundary layer height are promising. For the comparison we use a full automated and objective procedure for the estimation of atmospheric visibility with the help of a digital panorama camera serving as ground truth. To further investigate the relation between the vertical measure of AOD and the horizontal visibility data from the Aerosol Robotic Network (AERONET) site Laegeren (Switzerland), where the digital camera is mounted, are included as well. Finally, the derived visibility maps are compared with synoptical observations in central

  16. Utilizing the MODIS 1.38 micrometer Channel for Cirrus Cloud Optical Thickness Retrievals: Algorithm and Retrieval Uncertainties

    Science.gov (United States)

    Meyer, Kerry; Platnick, Steven

    2010-01-01

    The cloud products from the Moderate Resolution Imaging Spectroradiometers (MODIS) on Terra and Aqua have been widely used within the atmospheric research community. The retrieval algorithms, however, oftentimes have difficulty detecting and retrieving thin cirrus, due to sensitivities to surface reflectance. Conversely, the 1.38 micron channel, located within a strong water vapor absorption band, is quite useful for detecting thin cirrus clouds since the signal from the surface can be blocked or substantially attenuated by the absorption of atmospheric water vapor below cirrus. This channel, however, suffers from nonnegligible attenuation due to the water vapor located above and within the cloud layer. Here we provide details of a new technique pairing the 1.38 micron and 1.24 micron channels to estimate the above/in-cloud water vapor attenuation and to subsequently retrieve thin cirrus optical thickness (tau) from attenuation-corrected 1.38 p.m reflectance measurements. In selected oceanic cases, this approach is found to increase cirrus retrievals by up to 38% over MOD06. For these cases, baseline 1.38 micron retrieval uncertainties are estimated to be between 15 and 20% for moderately thick cirrus (tau > 1), with the largest error source being the unknown cloud effective particle radius, which is not retrieved with the described technique. Uncertainties increase to around 90% for the thinnest clouds (tau < 0.5) where instrument and surface uncertainties dominate.

  17. Melt ponds and marginal ice zone from new algorithm of sea ice concentration retrieval

    Science.gov (United States)

    Repina, Irina; Tikhonov, Vasiliy; Komarova, Nataliia; Raev, Mikhail; Sharkov, Evgeniy

    2016-04-01

    Studies of spatial and temporal properties of sea ice distribution in polar regions help to monitor global environmental changes and reveal their natural and anthropogenic factors, as well as make forecasts of weather, marine transportation and fishing conditions, assess perspectives of mineral mining on the continental shelf, etc. Contact methods of observation are often insufficient to meet the goals, very complicated technically and organizationally and not always safe for people involved. Remote sensing techniques are believed to be the best alternative. Its include monitoring of polar regions by means of passive microwave sensing with the aim to determine spatial distribution, types, thickness and snow cover of ice. However, the algorithms employed today to retrieve sea ice characteristics from passive microwave sensing data for different reasons give significant errors, especially in summer period and also near ice edges and in cases of open ice. A new algorithm of sea ice concentration retrieval in polar regions from satellite microwave radiometry data is discussed. Beside estimating sea ice concentration, the algorithm makes it possible to indicate ice areas with melting snow and melt ponds. Melt ponds are an important element of the Arctic climate system. Covering up to 50% of the surface of drifting ice in summer, they are characterized by low albedo values and absorb several times more incident shortwave radiation than the rest of the snow and ice cover. The change of melt ponds area in summer period 1987-2015 is investigated. The marginal ice zone (MIZ) is defined as the area where open ocean processes, including specifically ocean waves, alter significantly the dynamical properties of the sea ice cover. Ocean wave fields comprise short waves generated locally and swell propagating from the large ocean basins. Depending on factors like wind direction and ocean currents, it may consist of anything from isolated, small and large ice floes drifting over a

  18. A new algorithm for agile satellite-based acquisition operations

    Science.gov (United States)

    Bunkheila, Federico; Ortore, Emiliano; Circi, Christian

    2016-06-01

    Taking advantage of the high manoeuvrability and the accurate pointing of the so-called agile satellites, an algorithm which allows efficient management of the operations concerning optical acquisitions is described. Fundamentally, this algorithm can be subdivided into two parts: in the first one the algorithm operates a geometric classification of the areas of interest and a partitioning of these areas into stripes which develop along the optimal scan directions; in the second one it computes the succession of the time windows in which the acquisition operations of the areas of interest are feasible, taking into consideration the potential restrictions associated with these operations and with the geometric and stereoscopic constraints. The results and the performances of the proposed algorithm have been determined and discussed considering the case of the Periodic Sun-Synchronous Orbits.

  19. New Methods for Retrieval of Chlorophyll Red Fluorescence from Hyperspectral Satellite Instruments: Simulations and Application to GOME-2 and SCIAMACHY

    Science.gov (United States)

    Joiner, Joanna; Yoshida, Yasuko; Guanter, Luis; Middleton, Elizabeth M.

    2016-01-01

    to estimate red SIF emission. Our approach is then an extension of previous approaches applied to satellite data that utilized only the filling-in of SFLs by red SIF. We conducted retrievals of red SIF using an extensive database of simulated radiances covering a wide range of conditions. Our new algorithm produces good agreement between the simulated truth and retrievals and shows the potential of the O2 bands for noise reduction in red SIF retrievals as compared with approaches that rely solely on SFL filling. Biases seen with existing satellite data, most likely due to instrumental artifacts that vary in time, space, and with instrument, must be addressed in order to obtain reasonable results. Our 8-year record of red SIF observations over land with the GOME-2 allows for the first time reliable global mapping of monthly anomalies. These anomalies are shown to have similar spatiotemporal structure as those in the far red, particularly for drought-prone regions. There is a somewhat larger percentage response in the red as compared with the far red for these areas that are drought sensitive. We also demonstrate that good-quality ocean fluorescence line height retrievals can be achieved with GOME-2, SCIAMACHY, and similar instruments by utilizing the full complement of radiance measurements that span the red SIF emission feature.

  20. Handoff algorithm for mobile satellite systems with ancillary terrestrial component

    KAUST Repository

    Sadek, Mirette

    2012-06-01

    This paper presents a locally optimal handoff algorithm for integrated satellite/ground communication systems. We derive the handoff decision function and present the results in the form of tradeoff curves between the number of handoffs and the number of link degradation events in a given distance covered by the mobile user. This is a practical receiver-controlled handoff algorithm that optimizes the handoff process from a user perspective based on the received signal strength rather than from a network perspective. © 2012 IEEE.

  1. Satellite Constellation Design with Adaptively Continuous Ant System Algorithm

    Institute of Scientific and Technical Information of China (English)

    He Quan; Han Chao

    2007-01-01

    The ant system algorithm (ASA) has proved to be a novel meta-heuristic algorithm to solve many multivariable problems. In this paper, the earth coverage of satellite constellation is analyzed and a (n + 1)-fold coverage rate is put forward to evaluate the coverage performance of a satellite constellation. An optimization model of constellation parameters is established on the basis of the coverage performance. As a newly developed method, ASA can be applied to optimize the constellation parameters. In order to improve the ASA,a rule for adaptive number of ants is proposed, by which the search range is obviously enlarged and the convergence speed increased.Simulation results have shown that the ASA is more quick and efficient than other methods.

  2. Ozone Profile Retrieval from Satellite Observation Using High Spectral Resolution Infrared Sounding Instrument

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper presents a preliminary result on the retrieval of atmospheric ozone profiles using an im proved regression technique and utilizing the data from the Atmospheric InfraRed Sounder (AIRS), a hyper-spectral instrument expected to be flown on the EOS-AQUA platform in 2002. Simulated AIRS spectra were used to study the sensitivity of AIRS radiance on the tropospheric and stratospheric ozone changes, and to study the impact of various channel combinations on the ozone profile retrieval. Sensitivity study results indicate that the AIRS high resolution spectral channels between the wavenumber 650- 800 cm-1 provide very useful information to accurately retrieve tropospheric and stratospheric ozone pro files. Eigenvector decomposition of AIRS spectra indicate that no more than 100 eigenvectors are needed to retrieve very accurate ozone profiles. The accuracy of the retrieved atmospheric ozone profile from the pres ent technique and utilizing the AIRS data was compared with the accuracy obtained from current Advanced TIROS Operational Vertical Sounder (ATOVS) data aboard National Oceanic and Atmospheric Admini stration (NOAA) satellites. As expected, a comparison of retrieval results confirms that the ozone profile re trieved with the AIRS data is superior to that of ATOVS.

  3. Comparison Of Modified Dual Ternary Indexing And Multi-Key Hashing Algorithms For Music Information Retrieval

    Directory of Open Access Journals (Sweden)

    Rajeswari Sridhar

    2010-07-01

    Full Text Available In this work we have compared two indexing algorithms that have been used to index and retrieve Carnatic music songs. We have compared a modified algorithm of the Dual ternary indexing algorithm for music indexing and retrieval with the multi-key hashing indexing algorithm proposed by us. The modification in the dual ternary algorithm was essential to handle variable length query phrase and to accommodate features specific to Carnatic music. The dual ternary indexing algorithm is adapted for Carnatic music by segmenting using the segmentation technique for Carnatic music. The dual ternary algorithm is compared with the multi-key hashing algorithm designed by us for indexing and retrieval in which features like MFCC, spectral flux, melody string and spectral centroid are used as features for indexing data into a hash table. The way in which collision resolution was handled by this hash table is different than the normal hash table approaches. It was observed that multi-key hashing based retrieval had a lesser time complexity than dual-ternary based indexing The algorithms were also compared for their precision and recall in which multi-key hashing had a better recall than modified dual ternary indexing for the sample data considered.

  4. An extended validation test for data input into parameterized retrieval algorithms

    Science.gov (United States)

    Schaale, Michael; Schroeder, Thomas

    2013-05-01

    The retrieval of environmental data from multi-spectral remotely sensed data is very often based on the (partial) inversion of extensive radiative transfer simulations (RTS). The inversion can be utilized in different ways, e.g. through the usage of polynomials or artificial neural networks. The inversion algorithms (IA) usually contain numerous parameters, which have to be adapted by regression schemes in a training phase with the help of the RTS data. The subsequent processing of real remotely sensed data by an adapted IA requires a validity test (VT) of the input data (usually a vector consisting of TOA radiances, environmental and geometric data) before inputting them into the IA. This test ensures that these or similar data were included in the training phase of the IA and thus helps to avoid unpredictable extrapolation effects. In standard procedures these "out-of-scope" data are identified by a simple convexity test (CT). CT means that each element of the input vector is tested to lie between the minimum and maximum values of the corresponding element used in the training data set. This assumption is rather crude as it assumes a homogeneously filled data space. But in general the data are not distributed homogeneously and thus a CT is an incomplete and unsatisfactory check. This paper proposes a solution to the problem sketched above by the development and implementation of an enhanced VT (eVT), which is based on a density map of the data space. The density map itself is approximated by an extended neuronal vector quantization method. The newly developed eVT algorithm is tested with known distributions of artificial data. Although the eVT is not limited to a specific retrieval/inversion scheme it is finally applied to an existing retrieval scheme for coastal water constituents from satellite data (MERIS) acquired over coastal regions in Europe (here: FUB/WeW water processor for VISAT-BEAM). A comparison against the data filtered by a simple CT further

  5. Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers

    OpenAIRE

    2016-01-01

    Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting wea...

  6. Assessing the Relative Performance of Microwave-Based Satellite Rain Rate Retrievals Using TRMM Ground Validation Data

    Science.gov (United States)

    Wolff, David B.; Fisher, Brad L.

    2011-01-01

    Space-borne microwave sensors provide critical rain information used in several global multi-satellite rain products, which in turn are used for a variety of important studies, including landslide forecasting, flash flood warning, data assimilation, climate studies, and validation of model forecasts of precipitation. This study employs four years (2003-2006) of satellite data to assess the relative performance and skill of SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), AMSR-E (Aqua) and the TRMM Microwave Imager (TMI) in estimating surface rainfall based on direct instantaneous comparisons with ground-based rain estimates from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The relative performance of each of these satellite estimates is examined via comparisons with space- and time-coincident GV radar-based rain rate estimates. Because underlying surface terrain is known to affect the relative performance of the satellite algorithms, the data for MELB was further stratified into ocean, land and coast categories using a 0.25deg terrain mask. Of all the satellite estimates compared in this study, TMI and AMSR-E exhibited considerably higher correlations and skills in estimating/observing surface precipitation. While SSM/I and AMSU-B exhibited lower correlations and skills for each of the different terrain categories, the SSM/I absolute biases trended slightly lower than AMSR-E over ocean, where the observations from both emission and scattering channels were used in the retrievals. AMSU-B exhibited the least skill relative to GV in all of the relevant statistical categories, and an anomalous spike was observed in the probability distribution functions near 1.0 mm/hr. This statistical artifact appears to be related to attempts by algorithm developers to include some lighter rain rates, not easily detectable by its scatter-only frequencies. AMSU

  7. On the Simulation of Sea States with High Significant Wave Height for the Validation of Parameter Retrieval Algorithms for Future Altimetry Missions

    Science.gov (United States)

    Kuschenerus, Mieke; Cullen, Robert

    2016-08-01

    To ensure reliability and precision of wave height estimates for future satellite altimetry missions such as Sentinel 6, reliable parameter retrieval algorithms that can extract significant wave heights up to 20 m have to be established. The retrieved parameters, i.e. the retrieval methods need to be validated extensively on a wide range of possible significant wave heights. Although current missions require wave height retrievals up to 20 m, there is little evidence of systematic validation of parameter retrieval methods for sea states with wave heights above 10 m. This paper provides a definition of a set of simulated sea states with significant wave height up to 20 m, that allow simulation of radar altimeter response echoes for extreme sea states in SAR and low resolution mode. The simulated radar responses are used to derive significant wave height estimates, which can be compared with the initial models, allowing precision estimations of the applied parameter retrieval methods. Thus we establish a validation method for significant wave height retrieval for sea states causing high significant wave heights, to allow improved understanding and planning of future satellite altimetry mission validation.

  8. Applying satellite retrievals to identify urban emissions of GHG's over East Asia

    Science.gov (United States)

    Shim, C.; Henze, D. K.

    2016-12-01

    Here we have used satellite retrievals to identify GHG's emissions over East Asia. With multi-year GOSAT CO2/CH4 products (2009 - 2014) and recent OCO-2 retrievals (2014 - 2015), better availability of the data enabled to show the regional/local scale (less than 1° x 1° spatial resolution) urban GHG's emissions. We identified the urban emissions from the enhanced values of xCO2/xCH4 and estimated the correlation of those signals with available GHG's emissions inventory over East Asia. Also, some of those retrievals were compared with ground/aircraft measurements to verify those remotely sensed data. Those efforts are useful to identify regional/local anthropogenic GHG's emissions over East Asia where the GHG's emissions inventories are still uncertain, which can support government policy to mitigate air pollution. In addition, we introduce our efforts to constrain the emissions of CO2 from GOSAT/OCO-2 data using 4-Dvar inverse modeling framework and we show some preliminary results. This study represents the current progress to understand sub-continental scale atmospheric CO2 variabilities and its emissions with recent satellite retrievals and advanced modeling.

  9. Optical identity authentication scheme based on elliptic curve digital signature algorithm and phase retrieval algorithm.

    Science.gov (United States)

    Fan, Desheng; Meng, Xiangfeng; Wang, Yurong; Yang, Xiulun; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

    2013-08-10

    An optical identity authentication scheme based on the elliptic curve digital signature algorithm (ECDSA) and phase retrieval algorithm (PRA) is proposed. In this scheme, a user's certification image and the quick response code of the user identity's keyed-hash message authentication code (HMAC) with added noise, serving as the amplitude and phase restriction, respectively, are digitally encoded into two phase keys using a PRA in the Fresnel domain. During the authentication process, when the two phase keys are presented to the system and illuminated by a plane wave of correct wavelength, an output image is generated in the output plane. By identifying whether there is a match between the amplitude of the output image and all the certification images pre-stored in the database, the system can thus accomplish a first-level verification. After the confirmation of first-level verification, the ECDSA signature is decoded from the phase part of the output image and verified to allege whether the user's identity is legal or not. Moreover, the introduction of HMAC makes it almost impossible to forge the signature and hence the phase keys thanks to the HMAC's irreversible property. Theoretical analysis and numerical simulations both validate the feasibility of our proposed scheme.

  10. Comparison Of Modified Dual Ternary Indexing And Multi-Key Hashing Algorithms For Music Information Retrieval

    CERN Document Server

    Sridhar, Rajeswari; Karthiga, S; T, Geetha; 10.5121/ijaia.2010.1305

    2010-01-01

    In this work we have compared two indexing algorithms that have been used to index and retrieve Carnatic music songs. We have compared a modified algorithm of the Dual ternary indexing algorithm for music indexing and retrieval with the multi-key hashing indexing algorithm proposed by us. The modification in the dual ternary algorithm was essential to handle variable length query phrase and to accommodate features specific to Carnatic music. The dual ternary indexing algorithm is adapted for Carnatic music by segmenting using the segmentation technique for Carnatic music. The dual ternary algorithm is compared with the multi-key hashing algorithm designed by us for indexing and retrieval in which features like MFCC, spectral flux, melody string and spectral centroid are used as features for indexing data into a hash table. The way in which collision resolution was handled by this hash table is different than the normal hash table approaches. It was observed that multi-key hashing based retrieval had a lesser ...

  11. Retrieval of aerosol optical properties from OMI radiances using a multiwavelength algorithm : Application to Western Europe

    NARCIS (Netherlands)

    Curier, R.L.; Veefkind, J.P.; Braak, R.; Veihelmann, B.; Torres, O.; Leeuw, G. de

    2008-01-01

    The Ozone Monitoring Instrument (OMI) multiwavelength algorithm has been developed to retrieve aerosol optical depth using OMI-measured reflectance at the top of the atmosphere. This algorithm was further developed by using surface reflectance data from a field campaign in Cabauw (The Netherlands),

  12. Greenhouse gas profiling by infrared-laser and microwave occultation: retrieval algorithm and demonstration results from end-to-end simulations

    Directory of Open Access Journals (Sweden)

    V. Proschek

    2011-04-01

    Full Text Available Measuring greenhouse gas (GHG profiles with global coverage and high accuracy and vertical resolution in the upper troposphere and lower stratosphere (UTLS is key for improved monitoring of GHG concentrations in the free atmosphere. In this respect a new satellite mission concept adding an infrared-laser part to the already well studied microwave occultation technique exploits the joint propagation of infrared-laser and microwave signals between Low Earth Orbit (LEO satellites. This synergetic combination, referred to as LEO-LEO microwave and infrared-laser occultation (LMIO method, enables to retrieve thermodynamic profiles (pressure, temperature, humidity and accurate altitude levels from the microwave signals and GHG profiles from the simultaneously measured infrared-laser signals. However, due to the novelty of the LMIO method, a retrieval algorithm for GHG profiling did not yet exist. Here we introduce such an algorithm for retrieving GHGs from LEO-LEO infrared-laser occultation (LIO data, applied as a second step after retrieving thermodynamic profiles from LEO-LEO microwave occultation (LMO data as recently introduced in detail by Schweitzer et al. (2011b. We thoroughly describe the LIO retrieval algorithm and unveil the synergy with the LMO-retrieved pressure, temperature, and altitude information. We furthermore demonstrate the effective independence of the GHG retrieval results from background (a priori information in discussing demonstration results from LMIO end-to-end simulations for a representative set of GHG profiles, including carbon dioxide (CO2, water vapor (H2O, methane (CH4, and ozone (O3. The GHGs except for ozone are well retrieved throughout the UTLS, while ozone is well retrieved from 10 km to 15 km upwards, since the ozone layer resides in the lower stratosphere. The GHG retrieval errors are generally smaller than 1% to 3% r.m.s., at a vertical resolution of about 1 km. The

  13. Greenhouse gas profiling by infrared-laser and microwave occultation: retrieval algorithm and demonstration results from end-to-end simulations

    Directory of Open Access Journals (Sweden)

    V. Proschek

    2011-10-01

    Full Text Available Measuring greenhouse gas (GHG profiles with global coverage and high accuracy and vertical resolution in the upper troposphere and lower stratosphere (UTLS is key for improved monitoring of GHG concentrations in the free atmosphere. In this respect a new satellite mission concept adding an infrared-laser part to the already well studied microwave occultation technique exploits the joint propagation of infrared-laser and microwave signals between Low Earth Orbit (LEO satellites. This synergetic combination, referred to as LEO-LEO microwave and infrared-laser occultation (LMIO method, enables to retrieve thermodynamic profiles (pressure, temperature, humidity and accurate altitude levels from the microwave signals and GHG profiles from the simultaneously measured infrared-laser signals. However, due to the novelty of the LMIO method, a retrieval algorithm for GHG profiling is not yet available. Here we introduce such an algorithm for retrieving GHGs from LEO-LEO infrared-laser occultation (LIO data, applied as a second step after retrieving thermodynamic profiles from LEO-LEO microwave occultation (LMO data. We thoroughly describe the LIO retrieval algorithm and unveil the synergy with the LMO-retrieved pressure, temperature, and altitude information. We furthermore demonstrate the effective independence of the GHG retrieval results from background (a priori information in discussing demonstration results from LMIO end-to-end simulations for a representative set of GHG profiles, including carbon dioxide (CO2, water vapor (H2O, methane (CH4, and ozone (O3. The GHGs except for ozone are well retrieved throughout the UTLS, while ozone is well retrieved from about 10 km to 15 km upwards, since the ozone layer resides in the lower stratosphere. The GHG retrieval errors are generally smaller than 1% to 3% r.m.s., at a vertical resolution of about 1 km. The retrieved profiles also appear unbiased, which points

  14. TCP-ATCA: Improved Transmission Control Algorithm in Satellite Network

    Institute of Scientific and Technical Information of China (English)

    Liu Feng; Liu Hengna; Zhao Han

    2008-01-01

    An adaptive transmission control algorithm based on TCP (TCP-ATCA) is proposed to reduce the effects of long propagation de- lay and high link error rate of the satellite network on the performances. The flow control and the error recovery are differentiated by combined dynamic random early detection-explicit congestion notification (DRED-ECN) algorithm, and, moreover, the pertaining con- gestion control methods are used in TCP-ATCA to improve the throughput. By introducing the entire recovery algorithm, the unneces- sary congestion window decrease is reduced, and the throughput and fairness are improved. Simulation results show that, compared with TCP-Reno, TCP-ATCA provides a better throughput performance when the link capacity is higher (≥ 600 packet/s), and roughly the same when it is lower. At the same time, TCP-ATCA also increases fairness and reduces transmission delay.

  15. Algorithm for image retrieval based on edge gradient orientation statistical code.

    Science.gov (United States)

    Zeng, Jiexian; Zhao, Yonggang; Li, Weiye; Fu, Xiang

    2014-01-01

    Image edge gradient direction not only contains important information of the shape, but also has a simple, lower complexity characteristic. Considering that the edge gradient direction histograms and edge direction autocorrelogram do not have the rotation invariance, we put forward the image retrieval algorithm which is based on edge gradient orientation statistical code (hereinafter referred to as EGOSC) by sharing the application of the statistics method in the edge direction of the chain code in eight neighborhoods to the statistics of the edge gradient direction. Firstly, we construct the n-direction vector and make maximal summation restriction on EGOSC to make sure this algorithm is invariable for rotation effectively. Then, we use Euclidean distance of edge gradient direction entropy to measure shape similarity, so that this method is not sensitive to scaling, color, and illumination change. The experimental results and the algorithm analysis demonstrate that the algorithm can be used for content-based image retrieval and has good retrieval results.

  16. Horizontal wind velocity retrieval using a Levenberg-Marquardt algorithm for an airborne wind lidar

    Science.gov (United States)

    Zhu, Jinshan; Li, Zhigang; Liu, Zhishen

    2016-04-01

    We established a model for an airborne wind lidar. Numerical optimization algorithms should be used to solve this nonlinear model. We designed a Levenberg-Marquardt (L-M) algorithm and tested it with the modeled data. The retrieved velocity and the true velocity agree very well, and the adjusted R2 is 0.99947. We have carried out an airborne coherent wind lidar experiment in January 2015, and we used the model and the L-M algorithm to process the wind lidar experiment data, and compared the retrieved results with the radiosonde wind profile. The consistency is very good, especially at an altitude above 1.8 km. We may speculate that when the atmosphere flows are not so dramatic, the lidar and the radiosonde measurements are strictly synchronous, it is possible to retrieve horizontal wind speeds and directions consistently with the radiosonde using our wind lidar model and the L-M algorithm.

  17. Microwave retrievals of terrestrial precipitation over snow-covered surfaces: A lesson from the GPM satellite

    Science.gov (United States)

    Ebtehaj, A. M.; Kummerow, C. D.

    2017-06-01

    Satellites are playing an ever-increasing role in estimating precipitation over remote areas. Improving satellite retrievals of precipitation requires increased understanding of its passive microwave signatures over different land surfaces. Snow-covered surfaces are notoriously difficult to interpret because they exhibit both emission from the land below and scattering from the ice crystals. Using data from the Global Precipitation Measurement (GPM) satellite, we demonstrate that microwave brightness temperatures of rain and snowfall transition from a scattering to an emission regime from summer to winter, due to expansion of less emissive snow cover. Evidence suggests that the combination of low- (10-19 GHz) and high-frequency (89-166 GHz) channels provides the maximum amount of information for snowfall detection. The results demonstrate that, using a multifrequency matching method, the probability of snowfall detection can even be higher than rainfall—chiefly because of the information content of the low-frequency channels that respond to the (near) surface temperature.

  18. Soil Moisture Retrieval Using Reflected Signals of BeiDou GEO Satellites

    Directory of Open Access Journals (Sweden)

    ZOU Wenbo

    2016-02-01

    Full Text Available This paper proposes a method of continuous long-term soil moisture measurement using signals from BeiDou GEO satellites. It also presents the soil moisture inversion model as well as the relevant signal processing steps. Moreover, a land-based experiment is carried out to verify its validity. This method adopts the dual-antenna Global Navigation Satellite System Reflection (GNSS-R mode to receive and process direct signal from BeiDou GEO satellites and reflected signal from soil. Based on signal synchronization, the reflectivity of soil can be calculated according to the extracted signal power values. And then, the soil moisture can be obtained in light of the inversion model. By taking singals from BeiDou GEO satellites, not only the positioning calculation step of general GNSS-R data processing can be ignored, but also a continuous long-term observation of soil moisture for fixed area can be realized. Experiment results based on the method above show a good continuity in both time and magnitude. They are also highly consistent with reference values and the root mean square error equals to 0.049. Compared with BeiDou IGSO and GPS MEO satellites, BeiDou GEO satellites can present a better performance in soil moisture retrieval.

  19. Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS

    Directory of Open Access Journals (Sweden)

    Tara Blakey

    2016-10-01

    Full Text Available This study evaluated the ability to improve Sea-Viewing Wide Field-of-View Sensor (SeaWiFS chl-a retrieval from optically shallow coastal waters by applying algorithms specific to the pixels’ benthic class. The form of the Ocean Color (OC algorithm was assumed for this study. The operational atmospheric correction producing Level 2 SeaWiFS data was retained since the focus of this study was on establishing the benefit from the alternative specification of the bio-optical algorithm. Benthic class was determined through satellite image-based classification methods. Accuracy of the chl-a algorithms evaluated was determined through comparison with coincident in situ measurements of chl-a. The regionally-tuned models that were allowed to vary by benthic class produced more accurate estimates of chl-a than the single, unified regionally-tuned model. Mean absolute percent difference was approximately 70% for the regionally-tuned, benthic class-specific algorithms. Evaluation of the residuals indicated the potential for further improvement to chl-a estimation through finer characterization of benthic environments. Atmospheric correction procedures specialized to coastal environments were recognized as areas for future improvement as these procedures would improve both classification and algorithm tuning.

  20. The STRatospheric Estimation Algorithm from Mainz (STREAM): estimating stratospheric NO2 from nadir-viewing satellites by weighted convolution

    Science.gov (United States)

    Beirle, Steffen; Hörmann, Christoph; Jöckel, Patrick; Liu, Song; Penning de Vries, Marloes; Pozzer, Andrea; Sihler, Holger; Valks, Pieter; Wagner, Thomas

    2016-07-01

    The STRatospheric Estimation Algorithm from Mainz (STREAM) determines stratospheric columns of NO2 which are needed for the retrieval of tropospheric columns from satellite observations. It is based on the total column measurements over clean, remote regions as well as over clouded scenes where the tropospheric column is effectively shielded. The contribution of individual satellite measurements to the stratospheric estimate is controlled by various weighting factors. STREAM is a flexible and robust algorithm and does not require input from chemical transport models. It was developed as a verification algorithm for the upcoming satellite instrument TROPOMI, as a complement to the operational stratospheric correction based on data assimilation. STREAM was successfully applied to the UV/vis satellite instruments GOME 1/2, SCIAMACHY, and OMI. It overcomes some of the artifacts of previous algorithms, as it is capable of reproducing gradients of stratospheric NO2, e.g., related to the polar vortex, and reduces interpolation errors over continents. Based on synthetic input data, the uncertainty of STREAM was quantified as about 0.1-0.2 × 1015 molecules cm-2, in accordance with the typical deviations between stratospheric estimates from different algorithms compared in this study.

  1. Observations of Three-Dimensional Radiative Effects that Influence Satellite Retrievals of Cloud Properties

    Science.gov (United States)

    Varnai, Tamas; Marshak, Alexander; Lau, William K. M. (Technical Monitor)

    2001-01-01

    This paper examines three-dimensional (3D) radiative effects, which arise from horizontal radiative interactions between areas that have different cloud properties. Earlier studies have argued that these effects can cause significant uncertainties in current satellite retrievals of cloud properties, because the retrievals rely on one-dimensional (1D) theory and do not consider the effects of horizontal changes in cloud properties. This study addresses two questions: which retrieved cloud properties are influenced by 3D radiative effects, and where 3D effects tend to occur? The influence of 3D effects is detected from the wayside illumination and shadowing make clouds appear asymmetric: Areas appear brighter if the cloud top surface is tilted toward, rather than away from, the Sun. The analysis of 30 images by the Moderate Resolution Imaging Spectroradiometer (MODIS) reveals that retrievals of cloud optical thickness and cloud water content are most influenced by 3D effects, whereas retrievals of cloud particle size are much less affected. The results also indicate that while 3D effects are strongest at cloud edges, cloud top variability in cloud interiors, even in overcast regions, also produces considerable 3D effects. Finally, significant 3D effects are found in a wide variety of situations, ranging from thin clouds to thick ones and from low clouds to high ones.

  2. A method for retrieving clouds with satellite infrared radiances using the particle filter

    Science.gov (United States)

    Xu, Dongmei; Auligné, Thomas; Descombes, Gaël; Snyder, Chris

    2016-11-01

    Ensemble-based techniques have been widely utilized in estimating uncertainties in various problems of interest in geophysical applications. A new cloud retrieval method is proposed based on the particle filter (PF) by using ensembles of cloud information in the framework of Gridpoint Statistical Interpolation (GSI) system. The PF cloud retrieval method is compared with the Multivariate Minimum Residual (MMR) method that was previously established and verified. Cloud retrieval experiments involving a variety of cloudy types are conducted with the PF and MMR methods with measurements of infrared radiances on multi-sensors onboard both geostationary and polar satellites, respectively. It is found that the retrieved cloud masks with both methods are consistent with other independent cloud products. MMR is prone to producing ambiguous small-fraction clouds, while PF detects clearer cloud signals, yielding closer heights of cloud top and cloud base to other references. More collections of small-fraction particles are able to effectively estimate the semi-transparent high clouds. It is found that radiances with high spectral resolutions contribute to quantitative cloud top and cloud base retrievals. In addition, a different way of resolving the filtering problem over each model grid is tested to better aggregate the weights with all available sensors considered, which is proven to be less constrained by the ordering of sensors. Compared to the MMR method, the PF method is overall more computationally efficient, and the cost of the model grid-based PF method scales more directly with the number of computing nodes.

  3. Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals

    Directory of Open Access Journals (Sweden)

    Y. Y. Liu

    2011-02-01

    Full Text Available Combining information derived from satellite-based passive and active microwave sensors has the potential to offer improved estimates of surface soil moisture at global scale. We develop and evaluate a methodology that takes advantage of the retrieval characteristics of passive (AMSR-E and active (ASCAT microwave satellite estimates to produce an improved soil moisture product. First, volumetric soil water content (m3 m−3 from AMSR-E and degree of saturation (% from ASCAT are rescaled against a reference land surface model data set using a cumulative distribution function matching approach. While this imposes any bias of the reference on the rescaled satellite products, it adjusts them to the same range and preserves the dynamics of original satellite-based products. Comparison with in situ measurements demonstrates that where the correlation coefficient between rescaled AMSR-E and ASCAT is greater than 0.65 ("transitional regions", merging the different satellite products increases the number of observations while minimally changing the accuracy of soil moisture retrievals. These transitional regions also delineate the boundary between sparsely and moderately vegetated regions where rescaled AMSR-E and ASCAT, respectively, are used for the merged product. Therefore the merged product carries the advantages of better spatial coverage overall and increased number of observations, particularly for the transitional regions. The combination method developed has the potential to be applied to existing microwave satellites as well as to new missions. Accordingly, a long-term global soil moisture dataset can be developed and extended, enhancing basic understanding of the role of soil moisture in the water, energy and carbon cycles.

  4. Impact of sea surface temperature on satellite retrieval of sea surface salinity

    Science.gov (United States)

    Jin, Xuchen; Zhu, Qiankun; He, Xianqiang; Chen, Peng; Wang, Difeng; Hao, Zengzhou; Huang, Haiqing

    2016-10-01

    Currently, global sea surface salinity (SSS) can be retrieved by the satellite microwave radiometer onboard the satellite, such as the Soil Moisture and Ocean Salinity(SMOS) and the Aqurius. SMOS is an Earth Explorer Opportunity Mission from the European Space Agency(ESA). It was launched at a sun-synchronous orbit in 2009 and one of the payloads is called MIRAS(Microwave Imaging Radiometer using Aperture Synthesis), which is the first interferometric microwave radiometer designed for observing SSS at L-band(1.41 GHz).The foundation of the salinity retrieval by microwave radiometer is that the sea surface radiance at L-band has the most suitable sensitivity with the variation of the salinity. It is well known that the sensitivity of brightness temperatures(TB) to SSS depends on the sea surface temperature (SST), but the quantitative impact of the SST on the satellite retrieval of the SSS is still poorly known. In this study, we investigate the impact of the SST on the accuracy of salinity retrieval from the SMOS. First of all, The dielectric constant model proposed by Klein and Swift has been used to estimate the vertically and horizontally polarized brightness temperatures(TV and TH) of a smooth sea water surface at L-band and derive the derivatives of TV and TH as a function of SSS to show the relative sensitivity at 45° incident angle. Then, we use the GAM(generalized additive model) method to evaluate the association between the satellite-measured brightness temperature and in-situ SSS at different SST. Moreover, the satellite-derived SSS from the SMOS is validated using the ARGO data to assess the RMSE(root mean squared error). We compare the SMOS SSS and ARGO SSS over two regions of Pacific ocean far from land and ice under different SST. The RMSE of retrieved SSS at different SST have been estimated. Our results showed that SST is one of the most significant factors affecting the accuracy of SSS retrieval. The satellite-measured brightness temperature has a

  5. Alternative phase-diverse phase retrieval algorithm based on Levenberg-Marquardt nonlinear optimization.

    Science.gov (United States)

    Mao, Heng; Zhao, Dazun

    2009-03-16

    A modified Levenberg-Marquardt (MLM) algorithm is proposed to substitute for modified G-S (MGS) algorithm in some situations of phase-diverse phase retrieval wavefront sensing (WFS), such as the obstructed pupil, in which the second derivative information is specifically employed to eliminate the local minimum stagnation. Experiments have been performed to validate MLM algorithm in WFS accuracy (less than lambda/30 RMS) referring to ZYGO interferometer results and in WFS repeatability (less than lambda/200 RMS), even the dynamic range is more than 7 lambda PV. Moreover, experiments have shown the MLM algorithm is superior to the MGS algorithm both in WFS accuracy and repeatability.

  6. A Three-Dimensional Satellite Retrieval Method for Atmospheric Temperature and Moisture Profiles

    Institute of Scientific and Technical Information of China (English)

    ZHANG Lei; QIU Chongjian; HUANG Jianping

    2008-01-01

    A three-dimensional variational method iS proposed to simultaneously retrieve the 3-D atmospheric temperature and moisture profiles from satellite radiance measurements.To include both vertical structure and the horizontal patterns of the atmospheric temperature and moisture.an EOF technique iS used to decompose the temperature and moisture field in a 3-D space.A number of numerical simulations are conducted and they demonstrate that the 3-D method iS less sensitive to the observation errors compared to the 1-D method.When the observation error iS more than 2.0 K.to get the best results.the truncation number for the EOF'S expansion have to be restricted to 2 in the 1-D method.while it can be set as large as 40 in a 3-D method.This results in the truncation error being reduced and the retrieval accuracy being improved in the 3-D method.Compared to the 1-D method.the rlTLS errors of the 3-D method are reduced by 48%and 36%for the temperature and moisture retrievals,respectively.Using the real satellite measured brightness temperatures at 0557 UTC 31 July 2002,the temperature and moisture profiles are retrieved over a region(20°-45°N,100°-125°E)and compared with 37 collocated radiosonde observations.The results show that the retrieval accuracy with a 3-D method iS significantly higher than those with the 1-D method.

  7. A study of multiyear ice concentration retrieval algorithms using AMSR-E data

    Institute of Scientific and Technical Information of China (English)

    HAO Guanghua; SU Jie

    2015-01-01

    In recent years, the rapid decline of Arctic sea ice area (SIA) and sea ice extent (SIE), especially for the multiyear (MY) ice, has led to significant effect on climate change. The accurate retrieval of MY ice concentration retrieval is very important and challenging to understand the ongoing changes. Three MY ice concentration retrieval algorithms were systematically evaluated. A similar total ice concentration was yielded by these algorithms, while the retrieved MY sea ice concentrations differs from each other. The MY SIA derived from NASA TEAM algorithm is relatively stable. Other two algorithms created seasonal fluctuations of MY SIA, particularly in autumn and winter. In this paper, we proposed an ice concentration retrieval algorithm, which developed the NASA TEAM algorithm by adding to use AMSR-E 6.9 GHz brightness temperature data and sea ice concentration using 89.0 GHz data. Comparison with the reference MY SIA from reference MY ice, indicates that the mean difference and root mean square (rms) difference of MY SIA derived from the algorithm of this study are 0.65×106 km2 and 0.69×106 km2 during January to March, –0.06×106 km2 and 0.14×106 km2 during September to December respectively. Comparison with MY SIE obtained from weekly ice age data provided by University of Colorado show that, the mean difference and rms difference are 0.69×106 km2 and 0.84×106 km2, respectively. The developed algorithm proposed in this study has smaller difference compared with the reference MY ice and MY SIE from ice age data than the Wang’s, Lomax’ and NASA TEAM algorithms.

  8. Training for Retrieval of Knowledge under Stress through Algorithmic Decomposition

    Science.gov (United States)

    1986-10-01

    explained the base- rate problem and the way of solution. This natural language mediation is a verbal strategy for learning process. Imagery can be used...Light Bulb and Dyslexia problems used by Lichtenstein & MacGregor (1985). The problems are presented in Appendix D. All aspects of the problems were...algorithm was composed for the Dyslexia version. The algorithm and the tutorial are presented in Appendix E. Problems’ type. As in the original study

  9. The Ground Flash Fraction Retrieval Algorithm Employing Differential Evolution: Simulations and Applications

    Science.gov (United States)

    Koshak, William; Solakiewicz, Richard

    2012-01-01

    The ability to estimate the fraction of ground flashes in a set of flashes observed by a satellite lightning imager, such as the future GOES-R Geostationary Lightning Mapper (GLM), would likely improve operational and scientific applications (e.g., severe weather warnings, lightning nitrogen oxides studies, and global electric circuit analyses). A Bayesian inversion method, called the Ground Flash Fraction Retrieval Algorithm (GoFFRA), was recently developed for estimating the ground flash fraction. The method uses a constrained mixed exponential distribution model to describe a particular lightning optical measurement called the Maximum Group Area (MGA). To obtain the optimum model parameters (one of which is the desired ground flash fraction), a scalar function must be minimized. This minimization is difficult because of two problems: (1) Label Switching (LS), and (2) Parameter Identity Theft (PIT). The LS problem is well known in the literature on mixed exponential distributions, and the PIT problem was discovered in this study. Each problem occurs when one allows the numerical minimizer to freely roam through the parameter search space; this allows certain solution parameters to interchange roles which leads to fundamental ambiguities, and solution error. A major accomplishment of this study is that we have employed a state-of-the-art genetic-based global optimization algorithm called Differential Evolution (DE) that constrains the parameter search in such a way as to remove both the LS and PIT problems. To test the performance of the GoFFRA when DE is employed, we applied it to analyze simulated MGA datasets that we generated from known mixed exponential distributions. Moreover, we evaluated the GoFFRA/DE method by applying it to analyze actual MGAs derived from low-Earth orbiting lightning imaging sensor data; the actual MGA data were classified as either ground or cloud flash MGAs using National Lightning Detection Network[TM] (NLDN) data. Solution error

  10. Estimating cloud optical thickness and associated surface UV irradiance from SEVIRI by implementing a semi-analytical cloud retrieval algorithm

    Directory of Open Access Journals (Sweden)

    P. Pandey

    2012-01-01

    Full Text Available In this paper, we describe the implementation of the Semi-Analytical Cloud Retrieval Algorithm (SACURA, to obtain scaled cloud optical thickness (SCOT from satellite imagery acquired with the SEVIRI instrument and surface UV irradiance levels. In estimation of SCOT particular care is given to the proper specification of the background (i.e., cloud-free spectral albedo and the retrieval of the cloud water phase from reflectance ratios in SEVIRI's 0.6 μm and 1.6 μm spectral bands. The SACURA scheme is then applied to daytime SEVIRI imagery over Europe, for the month of June 2006, at 15-min time increments. The resulting SCOT fields are compared with values obtained by the CloudSat experimental satellite mission, yielding a negligible bias, correlation coefficients ranging from 0.51 to 0.78, and a root mean square difference of 1 to 2 SCOT increments. These findings compare favourably to results from similar intercomparison exercises reported in the literature. Based on the retrieved SCOT from SEVIRI and radiative transfer modelling approach, simple parameterisations are proposed to estimate the surface UV-A and UV-B irradiance. The validation of the modelled UV-A and UV-B irradiance against the measurements over two Belgian stations, Redu and Ostend, indicate good agreement with the high correlation, index of agreement and low bias. The SCOT fields estimated by implementing SACURA on imagery from geostationary satellite are reliable and its impact on surface UV irradiance levels is well produced.

  11. Influence of low spatial resolution a priori data on tropospheric NO2 satellite retrievals

    Directory of Open Access Journals (Sweden)

    J. P. Burrows

    2011-09-01

    Full Text Available The retrieval of tropospheric columns of NO2 and other trace gases from satellite observations of backscattered solar radiation relies on the use of accurate a priori information. The spatial resolution of current space sensors is often significantly higher than that of the a priori datasets used, introducing uncertainties from spatial misrepresentation. In this study, the effect of spatial under-sampling of a priori data on the retrieval of NO2 columns was studied for a typical coastal area (around San Francisco. High-resolution (15 × 15 km2 NO2 a priori data from the WRF-Chem model in combination with high-resolution MODIS surface reflectance and aerosol data were used to investigate the uncertainty introduced by applying a priori data at typical global chemical transport model resolution. The results show that the relative uncertainties can be large (more than a factor of 2 if all a priori data used is at the coarsest resolution for individual measurements, mainly due to spatial variations in NO2 profile and surface albedo, with smaller contributions from aerosols and surface height changes. Similar sensitivities are expected for other coastal regions and localised sources such as power plants, highlighting the need for high-resolution a priori data in quantitative analysis of the spatial patterns retrieved from satellite observations of tropospheric pollution.

  12. Influence of under-sampled a priori data on tropospheric NO2 satellite retrievals

    Directory of Open Access Journals (Sweden)

    M. Trainer

    2011-03-01

    Full Text Available The retrieval of tropospheric columns of NO2 and other trace gases from satellite observations of backscattered solar radiation relies on the use of accurate a priori information. The spatial resolution of current space sensors is often significantly higher than that of the a priori datasets used, introducing uncertainties from spatial misrepresentation. In this study, the effect of spatial under-sampling of a priori data on the retrieval of NO2 columns was studied for a typical coastal area (around San Francisco. High-resolution (15 × 15 km2 NO2 a priori data from the WRF-Chem model in combination with high-resolution MODIS surface reflectance and aerosol data were used to investigate the uncertainty introduced by applying a priori data at typical global chemical transport model resolution. The results show that the relative uncertainties can be large (more than a factor of 2 for individual measurements, mainly due to spatial variations in NO2 profile and surface albedo, with smaller contributions from aerosols and surface height changes. Similar sensitivities are expected for other coastal regions and localised sources such as power plants, highlighting the need for high-resolution a priori data in quantitative analysis of the spatial patterns retrieved from satellite observations of tropospheric pollution.

  13. COMPARING THE PERFORMANCE OF SEMANTIC IMAGE RETRIEVAL USING SPARQL QUERY, DECISION TREE ALGORITHM AND LIRE

    Directory of Open Access Journals (Sweden)

    Magesh

    2013-01-01

    Full Text Available The ontology based framework is developed for representing image domain. The textual features of images are extracted and annotated as the part of the ontology. The ontology is represented in Web Ontology Language (OWL format which is based on Resource Description Framework (RDF and Resource Description Framework Schema (RDFS. Internally, the RDF statements represent an RDF graph which provides the way to represent the image data in a semantic manner. Various tools and languages are used to retrieve the semantically relevant textual data from ontology model. The SPARQL query language is more popular methods to retrieve the textual data stored in the ontology. The text or keyword based search is not adequate for retrieving images. The end users are not able to convey the visual features of an image in SPARQL query form. Moreover, the SPARQL query provides more accurate results by traversing through RDF graph. The relevant images cannot be retrieved by one to one mapping. So the relevancy can be provided by some kind of onto mapping. The relevancy is achieved by applying a decision tree algorithm. This study proposes methods to retrieve the images from ontology and compare the image retrieval performance by using SPARQL query language, decision tree algorithm and Lire which is an open source image search engine. The SPARQL query language is used to retrieving the semantically relevant images using keyword based annotation and the decision tree algorithms are used in retrieving the relevant images using visual features of an image. Lastly, the image retrieval efficiency is compared and graph is plotted to indicate the efficiency of the system.

  14. Identification and recovery of discontinuous synoptic features in satellite-retrieved brightness temperatures using a radiative transfer model

    Science.gov (United States)

    White, G. A., III; Mcguirk, J. P.; Thompson, A. H.

    1988-01-01

    An attempt is made to recover and identify discontinuous synoptic features from satellite-retrieved brightness temperatures, with attention to near-discontinuities in temperature and moisture that are typically found in fronts and inversions. Efforts are made to ascertain whether the vectors of satellite channel brightness temperatures can be classified according to synoptic source, and whether those sources are amenable to quantification.

  15. An algorithm for retrieving surface downwelling longwave radiation: A study of interactive physical mechanisms

    Science.gov (United States)

    Zhou, Yaping

    1999-12-01

    In this thesis, a new algorithm for retrieving the surface downwelling longwave flux is developed based on a detailed study of radiation models and observational data. The radiation models used in this study, the Column Radiation Models (CRM) from the National Center for Atmospheric Research (NCAR) community climate model (CCM) version2 and version3 and the Moderate Resolution Transmittance (MODTRAN3) Code, are validated with the CAGEX (CERES/ARM/GEWEX) project version 1.1.2 data taken at the Atmospheric Radiation Measurement (ARM) Program Oklahoma Central Facility. Results show that the accuracy of the radiation model is quite consistent with the models' level of complexity for clear skies. For cloudy skies, the cloud input parameters from various instruments need careful examination and preprocessing. The discrepancy between model calculations and observations can be significantly reduced by choice of input parameters and by tuning the optical properties within the models. Detailed sensitivity tests are conducted on the CCM3CRM to study the effect of atmospheric temperature and water vapor profiles upon the clear sky surface and top of atmosphere outgoing longwave fluxes. The study shows that the surface downwelling longwave flux can be largely determined from only two parameters: the surface upwelling longwave flux and the total precipitable water vapor. Cloudy sky sensitivities are conducted with both CCM3CRM and Modtran3. Both models find the cloud base height to be the most important factor determining the surface downwelling longwave, especially for low clouds. However, when considering partial cloud cases in the real world, column cloud liquid water seems to be a better parameter for the cloudy sky algorithm. The ARM observations at the Oklahoma Central Facility and the Tropical Western Pacific (TWP) Manus Island are used in deriving and validating the algorithm. The observations show similar relations found in the sensitivity tests for both clear skies and

  16. GMTR: two-dimensional geo-fit multitarget retrieval model for michelson interferometer for passive atmospheric sounding/environmental satellite observations.

    Science.gov (United States)

    Carlotti, Massimo; Brizzi, Gabriele; Papandrea, Enzo; Prevedelli, Marco; Ridolfi, Marco; Dinelli, Bianca Maria; Magnani, Luca

    2006-02-01

    We present a new retrieval model designed to analyze the observations of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), which is on board the ENVironmental SATellite (ENVISAT). The new geo-fit multitarget retrieval model (GMTR) implements the geo-fit two-dimensional inversion for the simultaneous retrieval of several targets including a set of atmospheric constituents that are not considered by the ground processor of the MIPAS experiment. We describe the innovative solutions adopted in the inversion algorithm and the main functionalities of the corresponding computer code. The performance of GMTR is compared with that of the MIPAS ground processor in terms of accuracy of the retrieval products. Furthermore, we show the capability of GMTR to resolve the horizontal structures of the atmosphere. The new retrieval model is implemented in an optimized computer code that is distributed by the European Space Agency as "open source" in a package that includes a full set of auxiliary data for the retrieval of 28 atmospheric targets.

  17. ALGORITHM OF SAR SATELLITE ATTITUDE MEASUREMENT USING GPS AIDED BY KINEMATIC VECTOR

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    In this paper, in order to improve the accuracy of the Synthetic Aperture Radar (SAR)satellite attitude using Global Positioning System (GPS) wide-band carrier phase, the SAR satellite attitude kinematic vector and Kalman filter are introduced. Introducing the state variable function of GPS attitude determination algorithm in SAR satellite by means of kinematic vector and describing the observation function by the GPS wide-band carrier phase, the paper uses the Kalman filter algorithm to obtian the attitude variables of SAR satellite. Compared the simulation results of Kalman filter algorithm with the least square algorithm and explicit solution, it is indicated that the Kalman filter algorithm is the best.

  18. Evaluating the Impact of Smoke Particle Absorption on Passive Satellite Cloud Optical Depth Retrievals

    Science.gov (United States)

    Alfaro-Contreras, R.; Zhang, J.; Reid, J. S.; Campbell, J. R.

    2013-12-01

    Absorbing aerosol particles, when lifted above clouds, can perturb top-of-atmosphere radiation radiances measured by passive satellite sensors through the absorption of reflected solar energy. This scenario, if not properly screened, impacts cloud physical retrievals, like cloud optical depth (COD), conducted using radiances/channels in the visible spectrum. We describe observations of smoke particle presence above cloud off the southwest coast of Africa, using spatially and temporally collocated Aqua Moderate Resolution Imaging Spectroradiometer (AQUA MODIS), Ozone Monitoring Instrument (OMI) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements. Results from this study indicate that above cloud aerosol episodes happen rather frequent in the smoke outflow region during the Northern Hemisphere summer where above cloud aerosol plumes introduce a significant bias to MODIS COD retrievals in the visible spectrum. This suggests that individual COD retrievals as well as COD climatology from MODIS can be affected over the smoke outflow region by above cloud aerosol contamination and thus showing the need to account for the presence of above cloud absorbing aerosols in the MODIS visible COD retrievals.

  19. NDACC UV-visible total ozone measurements: improved retrieval and comparison with correlative satellite and ground-based observations

    Directory of Open Access Journals (Sweden)

    F. Hendrick

    2010-08-01

    Full Text Available Accurate long-term monitoring of total ozone is one of the most important requirements for identifying possible natural or anthropogenic changes in the composition of the stratosphere. For this purpose, the NDACC (Network for the Detection of Atmospheric Composition Change UV-visible Working Group has made recommendations for improving and homogenizing the retrieval of total ozone columns from twilight zenith-sky visible spectrometers. These instruments, deployed all over the world in about 35 stations, allow measurements of total ozone twice daily with little sensitivity to stratospheric temperature and cloud cover. The NDACC recommendations address both the DOAS retrieval parameters and the calculation of air mass factors (AMF needed for the conversion of O3 slant column densities into vertical column amounts. The most important improvement is the use of O3 AMF look-up tables calculated using the TOMS V8 O3 profile climatology, that allows accounting for the dependence of the O3 AMF on the seasonal and latitudinal variations of the O3 vertical distribution. To investigate their impact on the retrieved ozone columns, the recommendations have been applied to measurements from the NDACC/SAOZ (Système d'Analyse par Observation Zénithale network. The revised SAOZ ozone data from eight stations covering all latitude regions have been compared to TOMS, GOME-GDP4, SCIAMACHY-TOSOMI, OMI-TOMS, and OMI-DOAS satellite overpass observations, as well as to those of collocated Dobson and Brewer instruments. A significant improvement is obtained after applying the new O3 AMFs, although systematic seasonal differences between SAOZ and all other instruments remain. These are shown to mainly originate from i the temperature dependence of the ozone absorption cross sections in the UV being not or improperly corrected by some retrieval algorithms, and ii the longitudinal differences in

  20. Development and Comparison of Ground and Satellite-based Retrievals of Cirrus Cloud Physical Properties

    Energy Technology Data Exchange (ETDEWEB)

    Mitchell, David L

    2009-10-14

    This report is the final update on ARM research conducted at DRI through May of 2006. A relatively minor amount of work was done after May, and last month (November), two journal papers partially funded by this project were published. The other investigator on this project, Dr. Bob d'Entremont, will be submitting his report in February 2007 when his no-cost extension expires. The main developments for this period, which concludes most of the DRI research on this project, are as follows: (1) Further development of a retrieval method for cirrus cloud ice particle effective diameter (De) and ice water path (IWP) using terrestrial radiances measured from satellites; (2) Revision and publication of the journal article 'Testing and Comparing the Modified Anomalous Diffraction Approximation'; and (3) Revision and publication of our radar retrieval method for IWC and snowfall rate.

  1. Daytime Ionosphere Retrieval Algorithm for the Ionospheric Connection Explorer (ICON)

    Science.gov (United States)

    Stephan, Andrew W.; Korpela, Eric J.; Sirk, Martin M.; England, Scott L.; Immel, Thomas J.

    2017-07-01

    The NASA Ionospheric Connection Explorer Extreme Ultraviolet spectrograph, ICON EUV, will measure altitude profiles of the daytime extreme-ultraviolet (EUV) OII emission near 83.4 and 61.7 nm that are used to determine density profiles and state parameters of the ionosphere. This paper describes the algorithm concept and approach to inverting these measured OII emission profiles to derive the associated O+ density profile from 150-450 km as a proxy for the electron content in the F-region of the ionosphere. The algorithm incorporates a bias evaluation and feedback step, developed at the U.S. Naval Research Laboratory using data from the Special Sensor Ultraviolet Limb Imager (SSULI) and the Remote Atmospheric and Ionospheric Detection System (RAIDS) missions, that is able to effectively mitigate the effects of systematic instrument calibration errors and inaccuracies in the original photon source within the forward model. Results are presented from end-to-end simulations that convolved simulated airglow profiles with the expected instrument measurement response to produce profiles that were inverted with the algorithm to return data products for comparison to truth. Simulations of measurements over a representative ICON orbit show the algorithm is able to reproduce hmF2 values to better than 5 km accuracy, and NmF2 to better than 12% accuracy over a 12-second integration, and demonstrate that the ICON EUV instrument and daytime ionosphere algorithm can meet the ICON science objectives which require 20 km vertical resolution in hmF2 and 18% precision in NmF2.

  2. TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms

    Directory of Open Access Journals (Sweden)

    Patrick Marina

    2017-01-01

    Full Text Available On-site measurements from rain gauge provide important information for the design, construction, and operation of water resources engineering projects, groundwater potentials, and the water supply and irrigation systems. A dense gauging network is needed to accurately characterize the variation of rainfall over a region, unfitting for conditions with limited networks, such as in Sarawak, Malaysia. Hence, satellite-based algorithm estimates are introduced as an innovative solution to these challenges. With accessibility to dataset retrievals from public domain websites, it has become a useful source to measure rainfall for a wider coverage area at finer temporal resolution. This paper aims to investigate the rainfall estimates prepared by Tropical Rainfall Measuring Mission (TRMM to explain whether it is suitable to represent the distribution of extreme rainfall in Sungai Sarawak Basin. Based on the findings, more uniform correlations for the investigated storms can be observed for low to medium altitude (>40 MASL. It is found for the investigated events of Jan 05-11, 2009: the normalized root mean square error (NRMSE = 36.7 %; and good correlation (CC = 0.9. These findings suggest that satellite algorithm estimations from TRMM are suitable to represent the spatial distribution of extreme rainfall.

  3. Comparison Of Modified Dual Ternary Indexing And Multi-Key Hashing Algorithms For Music Information Retrieval

    Directory of Open Access Journals (Sweden)

    Rajeswari Sridhar

    2010-07-01

    Full Text Available In this work we have compared two indexing algorithms that have been used to index and retrieveCarnatic music songs. We have compared a modified algorithm of the Dual ternary indexing algorithmfor music indexing and retrieval with the multi-key hashing indexing algorithm proposed by us. Themodification in the dual ternary algorithm was essential to handle variable length query phrase and toaccommodate features specific to Carnatic music. The dual ternary indexing algorithm is adapted forCarnatic music by segmenting using the segmentation technique for Carnatic music. The dual ternaryalgorithm is compared with the multi-key hashing algorithm designed by us for indexing and retrieval inwhich features like MFCC, spectral flux, melody string and spectral centroid are used as features forindexing data into a hash table. The way in which collision resolution was handled by this hash table isdifferent than the normal hash table approaches. It was observed that multi-key hashing based retrievalhad a lesser time complexity than dual-ternary based indexing The algorithms were also compared fortheir precision and recall in which multi-key hashing had a better recall than modified dual ternaryindexing for the sample data considered.

  4. Improvement of Aerosol Optical Depth Retrieval over Hong Kong from a Geostationary Meteorological Satellite Using Critical Reflectance with Background Optical Depth Correction

    Science.gov (United States)

    Kim, Mijin; Kim, Jhoon; Wong, Man Sing; Yoon, Jongmin; Lee, Jaehwa; Wu, Dong L.; Chan, P.W.; Nichol, Janet E.; Chung, Chu-Yong; Ou, Mi-Lim

    2014-01-01

    Despite continuous efforts to retrieve aerosol optical depth (AOD) using a conventional 5-channelmeteorological imager in geostationary orbit, the accuracy in urban areas has been poorer than other areas primarily due to complex urban surface properties and mixed aerosol types from different emission sources. The two largest error sources in aerosol retrieval have been aerosol type selection and surface reflectance. In selecting the aerosol type from a single visible channel, the season-dependent aerosol optical properties were adopted from longterm measurements of Aerosol Robotic Network (AERONET) sun-photometers. With the aerosol optical properties obtained fromthe AERONET inversion data, look-up tableswere calculated by using a radiative transfer code: the Second Simulation of the Satellite Signal in the Solar Spectrum (6S). Surface reflectance was estimated using the clear sky composite method, awidely used technique for geostationary retrievals. Over East Asia, the AOD retrieved from the Meteorological Imager showed good agreement, although the values were affected by cloud contamination errors. However, the conventional retrieval of the AOD over Hong Kong was largely underestimated due to the lack of information on the aerosol type and surface properties. To detect spatial and temporal variation of aerosol type over the area, the critical reflectance method, a technique to retrieve single scattering albedo (SSA), was applied. Additionally, the background aerosol effect was corrected to improve the accuracy of the surface reflectance over Hong Kong. The AOD retrieved froma modified algorithmwas compared to the collocated data measured by AERONET in Hong Kong. The comparison showed that the new aerosol type selection using the critical reflectance and the corrected surface reflectance significantly improved the accuracy of AODs in Hong Kong areas,with a correlation coefficient increase from0.65 to 0.76 and a regression line change from tMI [basic algorithm] = 0

  5. A satellite schedulability prediction algorithm for EO SPS

    Institute of Scientific and Technical Information of China (English)

    Li Jun; Li Jun; Jing Ning; Hu Weidong; Chen Hao

    2013-01-01

    With notably few exceptions,the existing satellite mission operations cannot provide the ability of schedulability prediction,including the latest satellite planning service (SPS) standard-Sensor Planning Service Interface Standard 2.0 Earth Observation Satellite Tasking Extension (EO SPS) approved by Open Geospatial Consortium (OGC).The requestor can do nothing but waiting for the results of time consuming batch scheduling.It is often too late to adjust the request when receiving scheduling failures.A supervised learning algorithm based on robust decision tree and bagging support vector machine (Bagging SVM) is proposed to solve the problem above.The Bagging SVM is applied to improve the accuracy of classification and robust decision tree is utilized to reduce the error mean and error variation.The simulations and analysis show that a prediction action can be accomplished in near real-time with high accuracy.This means the decision makers can maximize the probability of successful scheduling through changing request parameters or take action to accommodate the scheduling failures in time.

  6. Image Dodging Algorithm for GF-1 Satellite WFV Imagery

    Directory of Open Access Journals (Sweden)

    HAN Jie

    2016-12-01

    Full Text Available Image dodging method is one of the important processes that determines whether the mosaicking image can be used for remote sensing quantitative application. GF-1 satellite is the first satellite in CHEOS (Chinese high-resolution earth observation system. WFV multispectral sensor is one of the instruments onboard GF-1 satellite which consist of four cameras to mosaic imaging. According to the characteristics of WFV sensor, this paper proposes an image dodging algorithm based on cross/inter-radiometric calibration method. First, the traditional cross calibration method is applied to obtain the calibration coefficients of one WFV camera. Then statistical analysis and simulation methods are adopted to build the correlation models of DN and TOA (top of atmosphere radiances between adjacent cameras. The proposed method can not only accomplish the radiation performance transfer, but also can fulfill the image dodging. The experimental results show the cross/inter-radiometric calibration coefficients in this paper can effectively eliminate the radiation inconsistency problem of the adjacent camera image which realizes the image dodging. So our proposed dodging method can provide an important reference for other similar sensor in future.

  7. Phase Retrieval Algorithm for Form Testing Metrology in Production Environment

    Directory of Open Access Journals (Sweden)

    Stephan Stuerwald

    2010-08-01

    Full Text Available Form testing interferometry permits a fast, non-tactile and full- field quantitative phase imaging of components in ultra precise manufacturing. To reduce the influence of vibrations under manufacturing conditions, it is most common to use the FT- based spatial carrier phase measurement technique (SCPM which requires only a single interferogram recording. The utilization of a generalized, relatively new spatial phase-shifting method operating in the position space opens up prospects for reduced phase noise and less reconstruction errors of the calculated phase-map under production conditions. Therefore this phase-shifting technique is investigated for applicability in machine integrated interferometric form testing of optical lenses. A characterization of the algorithm and a comparison with the commonly used FT-based algorithm is performed. As a reference, measurements are carried out with a coordinate measuring machine with nanometre accuracy.

  8. Characterization and assessment of different algorithms for retrieval of mean square slopes from GNSS-R measurements

    Science.gov (United States)

    Clarizia, Maria Paola; Ruf, Christopher; Gommenginger, Christine

    2013-04-01

    Global Navigation Satellite System-Reflectometry (GNSS-R) exploits signals of opportunity from navigation constellations (e.g. GPS, GLONASS, Galileo), scattered by the surface of the ocean, to retrieve the surface wind and wave fields. GNSS-R represents a true innovation in remote sensing, and it is receiving a growing interest from the scientific community. Its main advantages lie in the dense space-time sampling capabilities, the ability of L-band signals to penetrate well through rain, and the possibility of simple, low-cost/low-power GNSS receivers. These recognized strengths of GNSS-R recently led to the approval of the NASA EV-2 Cyclone Global Navigation Satellite System (CYGNSS), a spaceborne mission focused on tropical cyclone (TC) inner core process studies. CYGNSS attempts to resolve the problem of inadequate observations and modeling of the inner core, which represents the principal deficiency with current TC intensity forecasts, and which can be overcome with GNSS-R. The present study focuses on the information content about the sea surface roughness and wind speed, that is contained in spaceborne GNSS-R Delay-Doppler Maps (DDMs). A number of algorithms for the retrieval of Mean Square Slopes (MSS) - representative of the surface roughness - are analyzed. These include existing algorithms based on least-square fitting procedures (e.g. 2D least-square fitting of DDMs, using the Zavorotny-Voronovich DDM theoretical model), or based on direct observables (e.g. DDM volume), as well as "new" algorithms, which make use of waveforms derived from the DDM, which have thusfar been unexploited (e.g. integrated delay and Doppler waveforms). The analysis is carried out using simulated DDMs generated by the mature forward model end-to-end simulator developed for CYGNSS. A comparison of the results obtained for different retrieval algorithms will be presented. In particular, the performance of the algorithms considered is investigated and characterized for the case of

  9. A fast video clip retrieval algorithm based on VA-file

    Science.gov (United States)

    Liu, Fangjie; Dong, DaoGuo; Miao, Xiaoping; Xue, XiangYang

    2003-12-01

    Video clip retrieval is a significant research topic of content-base multimedia retrieval. Generally, video clip retrieval process is carried out as following: (1) segment a video clip into shots; (2) extract a key frame from each shot as its representative; (3) denote every key frame as a feature vector, and thus a video clip can be denoted as a sequence of feature vectors; (4) retrieve match clip by computing the similarity between the feature vector sequence of a query clip and the feature vector sequence of any clip in database. To carry out fast video clip retrieval the index structure is indispensable. According to our literature survey, S2-tree [17] is the one and only index structure having been applied to support video clip retrieval, which combines the characteristics of both X-tree and Suffix-tree and converts the series vectors retrieval to string matching. But S2-tree structure will not be applicable if the feature vector's dimension is beyond 20, because the X-tree itself cannot be used to sustain similarity query effectively when dimensions of vectors are beyond 20. Furthermore, it cannot support flexible similarity definitions between two vector sequences. VA-file represents the vector approximately by compressing the original data and it maintains the original order when representing vectors in a sequence, which is a very valuable merit for vector sequences matching. In this paper, a new video clip similarity model as well as video clip retrieval algorithm based on VA-File are proposed. The experiments show that our algorithm incredibly shortened the retrieval time compared to sequential scanning without index structure.

  10. Satellite Retrievals of Karenia brevis Harmful Algal Blooms in the West Florida Shelf Using Neural Networks and Comparisons with Other Techniques

    Directory of Open Access Journals (Sweden)

    Ahmed El-habashi

    2016-05-01

    Full Text Available We describe the application of a Neural Network (NN previously developed by us, to the detection and tracking, of Karenia brevis Harmful Algal Blooms (KB HABs that plague the coasts of the West Florida Shelf (WFS using Visible Infrared Imaging Radiometer Suite (VIIRS satellite observations. Previous approaches for the detection of KB HABs in the WFS primarily used observations from the Moderate Resolution Imaging Spectroradiometer Aqua (MODIS-A satellite. They depended on the remote sensing reflectance signal at the 678 nm chlorophyll fluorescence band (Rrs678 needed for both the normalized fluorescence height (nFLH and Red Band Difference algorithms (RBD currently used. VIIRS which has replaced MODIS-A, unfortunately does not have a 678 nm fluorescence channel so we customized the NN approach to retrieve phytoplankton absorption at 443 nm (aph443 using only Rrs measurements from existing VIIRS channels at 486, 551 and 671 nm. The aph443 values in these retrieved VIIRS images, can in turn be correlated to chlorophyll-a concentrations [Chla] and KB cell counts. To retrieve KB values, the VIIRS NN retrieved aph443 images are filtered by applying limiting constraints, defined by (i low backscatter at Rrs 551 nm and (ii a minimum aph443 value known to be associated with KB HABs in the WFS. The resulting filtered residual images, are then used to delineate and quantify the existing KB HABs. Comparisons with KB HABs satellite retrievals obtained using other techniques, including nFLH, as well as with in situ measurements reported over a four year period, confirm the viability of the NN technique, when combined with the filtering constraints devised, for effective detection of KB HABs.

  11. Improved Ozone and Carbon Monoxide Profile Retrievals Using Multispectral Measurements from NASA "A Train", NPP, and TROPOMI Satellites

    Science.gov (United States)

    Fu, D.; Bowman, K. W.; Kulawik, S. S.; Miyazaki, K.; Worden, J. R.; Worden, H. M.; Livesey, N. J.; Payne, V.; Luo, M.; Natraj, V.; Veefkind, P.; Aben, I.; Landgraf, J.; Flynn, L. E.; Han, Y.; Liu, X.; Strow, L. L.; Kuai, L.

    2015-12-01

    Tropospheric ozone is at the juncture of air quality and climate. Ozone directly impacts human and plant health, and directly forces the climate system through absorption of thermal radiation. Carbon monoxide is a chemical precursor of greenhouse gases CO2 and tropospheric O3, and is also an ideal tracer of transport processes due to its medium life time (weeks to months). The Aqua-AIRS and Aura-OMI instruments in the NASA "A-Train", CrIS and OMPS instruments on the NOAA Suomi-NPP, IASI and GOME-2 on METOP and TROPOMI aboard the Sentinel 5 precursor (S5p) have the potential to provide the synoptic chemical and dynamical context for ozone necessary to quantify long-range transport at global scales and to provide an anchor to the near-term constellation of geostationary sounders: NASA TEMPO, ESA Sentinel 4, and the Korean GEMS. We introduce the JPL MUlti-SpEctral, MUlti-SpEcies, MUlti-SatEllite (MUSES) retrieval algorithm, which ingests panspectral observations across multiple platforms in a non-linear optimal estimation framework. MUSES incorporates advances in remote sensing science developed during the EOS-Aura era including rigorous error analysis diagnostics and observation operators needed for trend analysis, climate model evaluation, and data assimilation. Its performance has been demonstrated through prototype studies for multi-satellite missions (AIRS, CrIS, TROPOMI, TES, OMI, and OMPS). We present joint tropospheric ozone retrievals from AIRS/OMI and CrIS/OMPS over global scales, and demonstrate the potential of joint carbon monoxide profiles from TROPOMI/CrIS. These results indicate that ozone can be retrieved with ~2 degrees of freedom for signal (dofs) in the troposphere, which is similar to TES. Joint CO profiles have dofs similar to the MOPITT multispectral retrieval but with higher spatial resolution and coverage. Consequently, multispectral retrievals show promise in providing continuity with NASA EOS observations and pave the way towards a new

  12. The Time Series Technique for Aerosol Retrievals over Land from MODIS: Algorithm MAIAC

    Science.gov (United States)

    Lyapustin, Alexei; Wang, Yujie

    2008-01-01

    Atmospheric aerosols interact with sun light by scattering and absorbing radiation. By changing irradiance of the Earth surface, modifying cloud fractional cover and microphysical properties and a number of other mechanisms, they affect the energy balance, hydrological cycle, and planetary climate [IPCC, 2007]. In many world regions there is a growing impact of aerosols on air quality and human health. The Earth Observing System [NASA, 1999] initiated high quality global Earth observations and operational aerosol retrievals over land. With the wide swath (2300 km) of MODIS instrument, the MODIS Dark Target algorithm [Kaufman et al., 1997; Remer et al., 2005; Levy et al., 2007] currently complemented with the Deep Blue method [Hsu et al., 2004] provides daily global view of planetary atmospheric aerosol. The MISR algorithm [Martonchik et al., 1998; Diner et al., 2005] makes high quality aerosol retrievals in 300 km swaths covering the globe in 8 days. With MODIS aerosol program being very successful, there are still several unresolved issues in the retrieval algorithms. The current processing is pixel-based and relies on a single-orbit data. Such an approach produces a single measurement for every pixel characterized by two main unknowns, aerosol optical thickness (AOT) and surface reflectance (SR). This lack of information constitutes a fundamental problem of the remote sensing which cannot be resolved without a priori information. For example, MODIS Dark Target algorithm makes spectral assumptions about surface reflectance, whereas the Deep Blue method uses ancillary global database of surface reflectance composed from minimal monthly measurements with Rayleigh correction. Both algorithms use Lambertian surface model. The surface-related assumptions in the aerosol retrievals may affect subsequent atmospheric correction in unintended way. For example, the Dark Target algorithm uses an empirical relationship to predict SR in the Blue (B3) and Red (B1) bands from the

  13. Visibility conflict resolution for multiple antennae and multi-satellites via genetic algorithm

    Science.gov (United States)

    Lee, Junghyun; Hyun, Chung; Ahn, Hyosung; Wang, Semyung; Choi, Sujin; Jung, Okchul; Chung, Daewon; Ko, Kwanghee

    Satellite mission control systems typically are operated by scheduling missions to the visibility between ground stations and satellites. The communication for the mission is achieved by interacting with satellite visibility and ground station support. Specifically, the satellite forms a cone-type visibility passing over a ground station, and the antennas of ground stations support the satellite. When two or more satellites pass by at the same time or consecutively, the satellites may generate a visibility conflict. As the number of satellites increases, solving visibility conflict becomes important issue. In this study, we propose a visibility conflict resolution algorithm of multi-satellites by using a genetic algorithm (GA). The problem is converted to scheduling optimization modeling. The visibility of satellites and the supports of antennas are considered as tasks and resources individually. The visibility of satellites is allocated to the total support time of antennas as much as possible for users to obtain the maximum benefit. We focus on a genetic algorithm approach because the problem is complex and not defined explicitly. The genetic algorithm can be applied to such a complex model since it only needs an objective function and can approach a global optimum. However, the mathematical proof of global optimality for the genetic algorithm is very challenging. Therefore, we apply a greedy algorithm and show that our genetic approach is reasonable by comparing with the performance of greedy algorithm application.

  14. A Retrieval Algorithm of Sheet Metal Parts Based on Relationships of Features

    Institute of Scientific and Technical Information of China (English)

    WANG Dawei; YAN Guangrong; LEI Yi; ZHANG Jiaying

    2012-01-01

    With the rapid increase in the number of three-dimensional (3D) models each year,to quickly and easily find the part desired has become a big challenge of enterprises.Meanwhile,many methods and algorithms have been proposed for part retrieval.However,most of the existing methods are designed for mechanical parts,and can not be well worked for sheet metal part retrieval.An approach to feature-based retrieval of sheet metal parts is presented.Firstly,the features frequently used in sheet metal part design are chosen as the "key words" in retrieval.Based on those features,a relative position model is built to express the different relationships of the features in 3D space.Secondly,a description method of the model is studied.With the description method the relative position of features in sheet metal parts can be expressed by four location description matrices.Thirdly,based on the relative position model and location description matrices,the equivalent definition of relationships of two feature groups is given which is the basis to calculate the similarity of two sheet metal parts.Next,the formula of retrieval algorithm for sheet metal parts is given.Finally,a prototype system is developed to test and verify the effectiveness of the retrieval method suggested.Experiments verify that the new method is able to meet the requirements of searching sheet metal parts and possesses potentials in practical application.

  15. Phase-Retrieval Uncertainty Estimation and Algorithm Comparison for the JWST-ISIM Test Campaign

    Science.gov (United States)

    Aronstein, David L.; Smith, J. Scott

    2016-01-01

    Phase retrieval, the process of determining the exitpupil wavefront of an optical instrument from image-plane intensity measurements, is the baseline methodology for characterizing the wavefront for the suite of science instruments (SIs) in the Integrated Science Instrument Module (ISIM) for the James Webb Space Telescope (JWST). JWST is a large, infrared space telescope with a 6.5-meter diameter primary mirror. JWST is currently NASA's flagship mission and will be the premier space observatory of the next decade. ISIM contains four optical benches with nine unique instruments, including redundancies. ISIM was characterized at the Goddard Space Flight Center (GSFC) in Greenbelt, MD in a series of cryogenic vacuum tests using a telescope simulator. During these tests, phase-retrieval algorithms were used to characterize the instruments. The objective of this paper is to describe the Monte-Carlo simulations that were used to establish uncertainties (i.e., error bars) for the wavefronts of the various instruments in ISIM. Multiple retrieval algorithms were used in the analysis of ISIM phase-retrieval focus-sweep data, including an iterativetransform algorithm and a nonlinear optimization algorithm. These algorithms emphasize the recovery of numerous optical parameters, including low-order wavefront composition described by Zernike polynomial terms and high-order wavefront described by a point-by-point map, location of instrument best focus, focal ratio, exit-pupil amplitude, the morphology of any extended object, and optical jitter. The secondary objective of this paper is to report on the relative accuracies of these algorithms for the ISIM instrument tests, and a comparison of their computational complexity and their performance on central and graphical processing unit clusters. From a phase-retrieval perspective, the ISIM test campaign includes a variety of source illumination bandwidths, various image-plane sampling criteria above and below the Nyquist- Shannon

  16. The pre-launch status of TanSat Mission: Instrument, Retrieval algorithm, Flux inversion and Validation

    Science.gov (United States)

    Liu, Yi; Yin, Zengshan; Yang, Zhongdong; Zheng, Yuquan; Yan, Changxiang; Tian, Xiangjun; Yang, Dongxu

    2016-04-01

    After 5 years development, The Chinese carbon dioxide observation satellite (TanSat), the first scientific experimental CO2 satellite of China, step into the pre-launch phase. The characters of pre-launch carbon dioxide spectrometer have been optimized during the laboratory test and calibration. Radiometric calibration shows a SNR of 440 (O2A 0.76um band), 300 (CO2 1.61um band) and 180 (CO2 2.06um band) on average in the typical radiance condition. Instrument line shape was calibrated automatically in using a well design testing system with laser control and record. After a series of test and calibration in laboratory, the instrumental performances meet the design requirements. TanSat will be launched on August 2016. The optimal estimation theory was involved in TanSat XCO2 retrieval algorithm in a full physics way with simulation of the radiance transfer in atmosphere. Gas absorption, aerosol and cirrus scattering and surface reflectance associate with wavelength dispersion have been considered in inversion for better correction the interference errors to XCO2. In order to simulate the radiance transfer precisely and efficiently, we develop a fast vector radiative transfer simulation method. Application of TanSat algorithm on GOSAT observation (ATANGO) is appropriate to evaluate the performance of algorithm. Validated with TCCON measurements, the ATANGO product achieves a 1.5 ppm precision. A Chinese carbon cycle data- assimilation system Tan-Tracker is developed based on the atmospheric chemical transport model GEOS-Chem. Tan-Tracker is a dual-pass data-assimilation system in which both CO2 concentrations and CO2 fluxes are simultaneously assimilated from atmospheric observations. A validation network has been established around China to support a series of CO2 satellite of China, which include 3 IFS-125HR and 4 Optical Spectrum Analyzer etc.

  17. Improved Water Level Retrieval from Epoch-by-Epoch Single and Double Difference GNSS-R Algorithms

    Directory of Open Access Journals (Sweden)

    WANG Nazi

    2016-07-01

    Full Text Available GNSS-R is a new technology for monitoring the water level with high efficiency. Compared with conventional water level measurement technique, such as satellite altimetry and tide gauges, GNSS-R can observe more reflected points with high temporal and spatial resolution and unaffected by the influence of the plate vertical motion. This paper presented an improved cGNSS-R altimetry algorithm based on single difference to derive the reflector heights epoch-by-epoch, which can enhance the temporal and spatial resolution of surface height measurements, furthermore, the other algorithm based on the double differenced carrier phase measurements was also presented in this paper. By using the observed data of cGNSS-R altimetry experiment conducted on Qinghe bridge of East Lake, Wuhan, the reflector heights between the reflected antenna and the lake surface were given to prove the above mentioned algorithms, and the precision were ±2~±4 cm. The results show that the proposed algorithms based on single and double difference which are used for water level retrieval can sufficiently decrease the influences due to clock error, ionospheric and tropospheric error.

  18. Object-based Evaluation of Satellite Precipitation Retrievals: A Case Study of the Summer Season over CONUS

    Science.gov (United States)

    Li, J.; Xu, P.

    2015-12-01

    Satellite precipitation retrievals that have high spatial and temporal resolutions are suitable for various applications, such as hydrologic modeling and watershed management. Many validation studies have been established to understand the strengths and limitations of these satellite precipitation retrievals. In this study, an object-based validation approach is adopted to evaluate several satellite precipitation retrievals focusing on the spatial and geometric patterns of precipitation. This object-based validation approach identifies precipitation objects using an image processing technique referred to as watershed transform. Several object attributes are diagnosed and analyzed based on the distance measurement. Three object-based verification scores are summarized to determine the overall performances of satellite precipitation retrievals. The Integrated Multi-satellitE Retrievals for GPM (IMERG) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) were evaluated using the object-based approach. The NOAA stage IV MPE multi-sensor composite rain analysis was utilized as the ground observations. The comparative assessments were conducted at 0.25° by 0.25° on a daily scale in the summer season of 2014 over the continental United States (CONUS). The results suggest that IMERG possesses the similar spatial pattern of local-scale precipitation areas against stage IV observations. In addition, IMERG depicts the sizes and locations of precipitation areas more accurately against stage IV.

  19. Investigating CloudSat Retrievals Sensitivity to Forward Iterative Algorithm Parameters in the Mixed Cloud Layers

    Science.gov (United States)

    Qiu, Yujun; Lu, Chunsong

    2016-09-01

    When millimeter-wave cloud radar data are used for the forward iterative retrieval of the liquid water content (LWC) and effective radius of cloud droplets ( R e) in a cloud layer, the prior values and tolerance ranges of the cloud droplet number density ( N t), scale parameter ( R g) and spectral width parameter ( W g) in the iterative algorithm are the main factors that affect the retrieval accuracy. In this study, we used data from stratus and convective clouds that were simultaneously observed by CloudSat and aircraft to conduct a sensitivity analysis of N t, R g, and W g for the retrieval accuracies of LWC and R e in both stratus and convective clouds. N t is the least sensitive parameter for accurately retrieving stratus LWC and R e in both stratus and convective clouds, except for retrieving the convective cloud LWC. Opposite to N t, R g is the most sensitive parameter for both LWC and R e retrievals. As to the effects of parameter tolerance ranges on the retrievals of LWC and R e, the least important parameter is the N t tolerance range; the most important one is the W g tolerance range for retrieving convective cloud LWC and R e, the R g is the important parameter for retrieving stratus LWC and R e. To obtain accurate retrieved values for clouds in a specific region, it is important to use typical values of the sensitive parameters, which could be calculated from in situ observations of cloud droplet size distributions. In addition, the sensitivities of the LWC and R e to the three parameters are stronger in convective clouds than in stratus clouds. This may be related to the melting and merging of solid cloud droplets during the convective mixing process in the convective clouds.

  20. Experimental robustness of Fourier Ptychography phase retrieval algorithms

    CERN Document Server

    Yeh, Li-Hao; Zhong, Jingshan; Tian, Lei; Chen, Michael; Tang, Gongguo; Soltanolkotabi, Mahdi; Waller, Laura

    2015-01-01

    Fourier ptychography is a new computational microscopy technique that provides gigapixel-scale intensity and phase images with both wide field-of-view and high resolution. By capturing a stack of low-resolution images under different illumination angles, a nonlinear inverse algorithm can be used to computationally reconstruct the high-resolution complex field. Here, we compare and classify multiple proposed inverse algorithms in terms of experimental robustness. We find that the main sources of error are noise, aberrations and mis-calibration (i.e. model mis-match). Using simulations and experiments, we demonstrate that the choice of cost function plays a critical role, with amplitude-based cost functions performing better than intensity-based ones. The reason for this is that Fourier ptychography datasets consist of images from both brightfield and darkfield illumination, representing a large range of measured intensities. Both noise (e.g. Poisson noise) and model mis-match errors are shown to scale with int...

  1. Effects of Slope and Aspect Variations on Satellite Surface Temperature Retrievals and Mesoscale Analysis in Mountainous Terrain.

    Science.gov (United States)

    Lipton, Alan E.

    1992-03-01

    Surface temperature retrieval in mountainous areas is complicated by the high variability of temperatures that can occur within a single satellite field of view. Temperatures depend in part on slope orientation relative to the sun, which can vary radically over very short distances. The surface temperature detected by a satellite is biased toward the temperatures of the sub-field-of-view terrain elements that most directly face the satellite. Numerical simulations were conducted to estimate the effects of satellite viewing geometry on surface temperature retrievals for a section of central Colorado. Surface temperatures were computed using a mesoscale model with a parameterization of subgrid variations in slope and aspect angles.The simulations indicate that the slope-aspect effect can lead to local surface temperature variations up to 30°C for autumn conditions in the Colorado mountains. For realistic satellite viewing conditions, these variations can give rise to biases in retrieved surface temperatures of about 3°C. Relative biases between retrievals from two satellites with different viewing angles can be over 6°C, which could lead to confusion when merging datasets. The bias computations were limited by the resolution of the available terrain height data (90 m). The results suggest that the biases would be significantly larger if the data resolution was fine enough to represent every detail of the real Colorado terrain or if retrievals were made in mountain areas that have a larger proportion of steep slopes than the Colorado Rockies. The computed bias gradients across the Colorado domain were not large enough to significantly alter the forcing of the diurnal upslope-downslope circulations, according to simulations in which surface temperature retrievals with view-dependent biases were assimilated into time-continuous analyses. View-dependent retrieval biases may be relevant to climatological analysts that rely on remotely sensed data, given that bias

  2. Development of a prototype algorithm for the operational retrieval of height-resolved products from GOME

    Science.gov (United States)

    Spurr, Robert J. D.

    1997-01-01

    Global ozone monitoring experiment (GOME) level 2 products of total ozone column amounts have been generated on a routine operational basis since July 1996. These products and the level 1 radiance products are the major outputs from the ERS-2 ground segment GOME data processor (GDP) at DLR in Germany. Off-line scientific work has already shown the feasibility of ozone profile retrieval from GOME. It is demonstrated how the retrievals can be performed in an operational context. Height-resolved retrieval is based on the optimal estimation technique, #and cloud-contaminated scenes are treated in an equivalent reflecting surface approximation. The prototype must be able to handle GOME measurements routinely on a global basis. Requirements for the major components of the algorithm are described: this incorporates an overall strategy for operational height-resolved retrieval from GOME.

  3. Evaluation of Retrieval Algorithms for Ice Microphysics Using CALIPSO/CloudSat and Earthcare

    Directory of Open Access Journals (Sweden)

    Okamoto Hajime

    2016-01-01

    We performed several sensitivity studies to evaluate uncertainties in the retrieved ice microphysics due to ice particle orientation and shape. It was found that the implementation of orientation of horizontally oriented ice plate model in the algorithm drastically improved the retrieval results in both for nadir- and off-nadir lidar pointing periods. Differences in the retrieved microphysics between only randomly oriented ice model (3D-ice and mixture of 3D-ice and Q2Dplate model were large especially in off-nadir period, e.g., 100% in effective radius and one order in ice water content, respectively. And differences in the retrieved ice microphysics among different mixture models were smaller than about 50% for effective radius in nadir period.

  4. Genetic Algorithm-Based Relevance Feedback for Image Retrieval Using Local Similarity Patterns.

    Science.gov (United States)

    Stejic, Zoran; Takama, Yasufumi; Hirota, Kaoru

    2003-01-01

    Proposes local similarity pattern (LSP) as a new method for computing digital image similarity. Topics include optimizing similarity computation based on genetic algorithm; relevance feedback; and an evaluation of LSP on five databases that showed an increase in retrieval precision over other methods for computing image similarity. (Author/LRW)

  5. Comparison of SAR Wind Speed Retrieval Algorithms for Evaluating Offshore Wind Energy Resources

    DEFF Research Database (Denmark)

    Kozai, K.; Ohsawa, T.; Takeyama, Y.

    2010-01-01

    Envisat/ASAR-derived offshore wind speeds and energy densities based on 4 different SAR wind speed retrieval algorithms (CMOD4, CMOD-IFR2, CMOD5, CMOD5.N) are compared with observed wind speeds and energy densities for evaluating offshore wind energy resources. CMOD4 ignores effects of atmospheric...

  6. The SUMO Ship Detector Algorithm for Satellite Radar Images

    Directory of Open Access Journals (Sweden)

    Harm Greidanus

    2017-03-01

    Full Text Available Search for Unidentified Maritime Objects (SUMO is an algorithm for ship detection in satellite Synthetic Aperture Radar (SAR images. It has been developed over the course of more than 15 years, using a large amount of SAR images from almost all available SAR satellites operating in L-, C- and X-band. As validated by benchmark tests, it performs very well on a wide range of SAR image modes (from Spotlight to ScanSAR and resolutions (from 1–100 m and for all types and sizes of ships, within the physical limits imposed by the radar imaging. This paper describes, in detail, the algorithmic approach in all of the steps of the ship detection: land masking, clutter estimation, detection thresholding, target clustering, ship attribute estimation and false alarm suppression. SUMO is a pixel-based CFAR (Constant False Alarm Rate detector for multi-look radar images. It assumes a K distribution for the sea clutter, corrected however for deviations of the actual sea clutter from this distribution, implementing a fast and robust method for the clutter background estimation. The clustering of detected pixels into targets (ships uses several thresholds to deal with the typically irregular distribution of the radar backscatter over a ship. In a multi-polarization image, the different channels are fused. Azimuth ambiguities, a common source of false alarms in ship detection, are removed. A reliability indicator is computed for each target. In post-processing, using the results of a series of images, additional false alarms from recurrent (fixed targets including range ambiguities are also removed. SUMO can run in semi-automatic mode, where an operator can verify each detected target. It can also run in fully automatic mode, where batches of over 10,000 images have successfully been processed in less than two hours. The number of satellite SAR systems keeps increasing, as does their application to maritime surveillance. The open data policy of the EU

  7. Validation of Two MODIS Aerosols Algorithms with SKYNET and Prospects for Future Climate Satellites Such as the GCOM-C/SGLI

    Directory of Open Access Journals (Sweden)

    Jules R. Dim

    2013-01-01

    Full Text Available Potential improvements of aerosols algorithms for future climate-oriented satellites such as the coming Global Change Observation Mission Climate/Second generation Global Imager (GCOM-C/SGLI are discussed based on a validation study of three years’ (2008–2010 daily aerosols properties, that is, the aerosol optical thickness (AOT and the Ångström exponent (AE retrieved from two MODIS algorithms. The ground-truth data used for this validation study are aerosols measurements from 3 SKYNET ground sites. The results obtained show a good agreement between the ground-truth data AOT and that of one of the satellites’ algorithms, then a systematic overestimation (around 0.2 by the other satellites’ algorithm. The examination of the AE shows a clear underestimation (by around 0.2–0.3 by both satellites’ algorithms. The uncertainties explaining these ground-satellites’ algorithms discrepancies are examined: the cloud contamination affects differently the aerosols properties (AOT and AE of both satellites’ algorithms due to the retrieval scale differences between these algorithms. The deviation of the real part of the refractive index values assumed by the satellites’ algorithms from that of the ground tends to decrease the accuracy of the AOT of both satellites’ algorithms. The asymmetry factor (AF of the ground tends to increase the AE ground-satellites discrepancies as well.

  8. Sensitivity of Marine Warm Cloud Retrieval Statistics to Algorithm Choices: Examples from MODIS Collection 6

    Science.gov (United States)

    Platnick, S.; Wind, G.; Zhang, Z.; Ackerman, S. A.; Maddux, B. C.

    2012-12-01

    The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate effective radii results using the 1.6, 2.1, and 3.7 μm spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "not-clear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 MODIS retrieval algorithm removed pixels associated with cloud edges (defined by immediate adjacency to "clear" MOD/MYD35 pixels) as well as ocean pixels with partly cloudy elements in the 250m MODIS cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the 1D cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.

  9. Sensitivity of Marine Warm Cloud Retrieval Statistics to Algorithm Choices: Examples from MODIS Collection 6

    Science.gov (United States)

    Platnick, Steven; Wind, Galina; Zhang, Zhibo; Ackerman, Steven A.; Maddux, Brent

    2012-01-01

    The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate effective radii results using the l.6, 2.1, and 3.7 m spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "notclear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 MODIS retrieval algorithm removed pixels associated with cloud'edges as well as ocean pixels with partly cloudy elements in the 250m MODIS cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the ID cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.

  10. Limiting Factors for Satellite-Based Retrievals of Surface-Level Carbon Monoxide

    Science.gov (United States)

    Martinez-Alonso, S.; Deeter, M. N.; Worden, H. M.; Barré, J.

    2015-12-01

    CO is mostly produced in the lower troposphere by incomplete combustion of biomass and fuels. CO oxidation consumes ~75% of the tropospheric OH, which then is not available to remove CH4 and other greenhouse gases. CO oxidation also leads to the production of tropospheric O3. These critical impacts of CO on air quality and climate require accurate determination of the abundance and evolution of CO near the surface.Satellite retrievals would be well-suited to monitor surface CO globally. However, how do they compare to actual surface abundances? Some aspects to be considered include: the vertical sensitivity of retrievals (given by the averaging kernels), or how thick are the atmospheric layers that can be resolved; the vertical correlation length of CO with respect to the thickness of those layers; and the horizontal variability of CO with respect to the instrument's footprint.To investigate these questions we analyze MOPITT retrievals, DISCOVER-AQ and NOAA profiles, as well as WDCGG surface measurements. MOPITT, on board NASA's Terra satellite, has been measuring tropospheric CO since 2000, providing the longest global CO record to date. Its unique multispectral CO product offers enhanced sensitivity to CO near the surface. Vertical profiles of the lower troposphere were acquired during the DISCOVER-AQ airborne campaigns over selected regions of the USA. NOAA's airborne flask sampling program results in a multi-year, multi-seasonal record of vertical profiles from near the surface up to the mid troposphere, acquired over a number of stations, mostly in North America. Long-term, cross-calibrated surface CO data from ground stations worldwide are available through the WDCGG.Statistical analyses of the DISCOVER-AQ and NOAA profiles indicate that surface vertical correlation length varies greatly depending on geographic location. This may explain contrasting results obtained for different ground stations when comparing MOPITT and WDCGG co-located data and timeseries.

  11. Algorithm for Automated Mapping of Land Surface Temperature Using LANDSAT 8 Satellite Data

    Directory of Open Access Journals (Sweden)

    Ugur Avdan

    2016-01-01

    Full Text Available Land surface temperature is an important factor in many areas, such as global climate change, hydrological, geo-/biophysical, and urban land use/land cover. As the latest launched satellite from the LANDSAT family, LANDSAT 8 has opened new possibilities for understanding the events on the Earth with remote sensing. This study presents an algorithm for the automatic mapping of land surface temperature from LANDSAT 8 data. The tool was developed using the LANDSAT 8 thermal infrared sensor Band 10 data. Different methods and formulas were used in the algorithm that successfully retrieves the land surface temperature to help us study the thermal environment of the ground surface. To verify the algorithm, the land surface temperature and the near-air temperature were compared. The results showed that, for the first case, the standard deviation was 2.4°C, and for the second case, it was 2.7°C. For future studies, the tool should be refined with in situ measurements of land surface temperature.

  12. Monitoring carbon dioxide from space: Retrieval algorithm and flux inversion based on GOSAT data and using CarbonTracker-China

    Science.gov (United States)

    Yang, Dongxu; Zhang, Huifang; Liu, Yi; Chen, Baozhang; Cai, Zhaonan; Lü, Daren

    2017-08-01

    Monitoring atmospheric carbon dioxide (CO2) from space-borne state-of-the-art hyperspectral instruments can provide a high precision global dataset to improve carbon flux estimation and reduce the uncertainty of climate projection. Here, we introduce a carbon flux inversion system for estimating carbon flux with satellite measurements under the support of "The Strategic Priority Research Program of the Chinese Academy of Sciences—Climate Change: Carbon Budget and Relevant Issues". The carbon flux inversion system is composed of two separate parts: the Institute of Atmospheric Physics Carbon Dioxide Retrieval Algorithm for Satellite Remote Sensing (IAPCAS), and CarbonTracker-China (CT-China), developed at the Chinese Academy of Sciences. The Greenhouse gases Observing SATellite (GOSAT) measurements are used in the carbon flux inversion experiment. To improve the quality of the IAPCAS-GOSAT retrieval, we have developed a post-screening and bias correction method, resulting in 25%-30% of the data remaining after quality control. Based on these data, the seasonal variation of XCO2 (column-averaged CO2 dry-air mole fraction) is studied, and a strong relation with vegetation cover and population is identified. Then, the IAPCAS-GOSAT XCO2 product is used in carbon flux estimation by CT-China. The net ecosystem CO2 exchange is -0.34 Pg C yr-1 (±0.08 Pg C yr-1), with a large error reduction of 84%, which is a significant improvement on the error reduction when compared with in situ-only inversion.

  13. An Evaluation of Satellite Retrievals of Snowfall in Regions of Complex Terrain

    Science.gov (United States)

    Reed, K. A.; Nesbitt, S. W.; Kulie, M.; L'Ecuyer, T. S.; Wood, N.

    2013-12-01

    Snowfall in regions of complex terrain plays an important role in the global hydrologic cycle, and can have major physical and social implications ranging from water resource management, to flash flooding, to climate change impacts. Due to the diversity of impacts that can result from snowfall, the ability to directly observe and measure snowfall in real-time is of great importance. However, the physical limitations of ground-based radars particularly in complex terrain and the lack of spatially complete measurement networks in mountainous regions make high-resolution ground-based snowfall observations a challenging task. Spaceborne satellite retrievals of snowfall such as those that will be made possible by the Global Precipitation Measurement (GPM) mission offer the ability to make high spatial and temporal resolution measurements that are otherwise not possible using traditional ground-based methods. This study seeks to investigate the skill level of current spaceborne snowfall products over the complex terrain of the Rocky Mountains in the western United States. Satellite derived snowfall products from measurements obtained via instruments including the CloudSat Cloud Profiling Radar (CPR), EOS Aqua Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and GCOM-W1 Advanced Microwave Scanning Radiometer 2 (AMSR2) are evaluated using ground-based observations such as the Natural Resources Conservation Service Snow Telemetry (SNOTEL) data and the NCEP Stage IV data. Satellite derived snowfall variables including snowfall rate and snow water equivalent are compared to ground-based observations to determine the overall accuracy and skill level of current satellite derived snowfall products in the region of interest. An analysis is also done to determine how the accuracy and skill level change based on varying snowfall regimes such as light, moderate, and heavy snowfall events. The knowledge gained will be used to determine how satellite derived snowfall

  14. Influence of aerosols and surface reflectance on satellite NO2 retrieval: seasonal and spatial characteristics and implications for NOx emission constraints

    Science.gov (United States)

    Lin, J.-T.; Liu, M.-Y.; Xin, J.-Y.; Boersma, K. F.; Spurr, R.; Martin, R.; Zhang, Q.

    2015-10-01

    Satellite retrievals of vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) normally do not explicitly account for aerosol optical effects and surface reflectance anisotropy that vary with space and time. Here, we conduct an improved retrieval of NO2 VCDs over China, called the POMINO algorithm, based on measurements from the Ozone Monitoring Instrument (OMI), and we test the importance of a number of aerosol and surface reflectance treatments in this algorithm. POMINO uses a parallelized LIDORT-driven AMFv6 package to derive tropospheric air mass factors via pixel-specific radiative transfer calculations with no look-up tables, taking slant column densities from DOMINO v2. Prerequisite cloud optical properties are derived from a dedicated cloud retrieval process that is fully consistent with the main NO2 retrieval. Aerosol optical properties are taken from GEOS-Chem simulations constrained by MODIS aerosol optical depth (AOD) data. MODIS bi-directional reflectance distribution function (BRDF) data are used for surface reflectance over land. For the present analysis, POMINO level-2 data for 2012 are aggregated into monthly means on a 0.25° long. × 0.25° lat. grid. POMINO-retrieved annual mean NO2 VCDs vary from 15-25 × 1015 cm-2 over the polluted North China Plain (NCP) to below 1015 cm-2 over much of western China. Using POMINO to infer Chinese emissions of nitrogen oxides leads to annual anthropogenic emissions of 9.05 TgN yr-1, an increase from 2006 (Lin, 2012) by about 19 %. Replacing the MODIS BRDF data with the OMLER v1 monthly climatological albedo data affects NO2 VCDs by up to 40 % for certain locations and seasons. The effect on constrained NOx emissions is small. Excluding aerosol information from the retrieval process (this is the traditional "implicit" treatment) enhances annual mean NO2 VCDs by 15-40 % over much of eastern China. Seasonally, NO2 VCDs are reduced by 10-20 % over parts of the NCP in spring and over northern China

  15. Developing a compositing algorithm for retrieval of green vegetation fraction

    Science.gov (United States)

    Jiang, Z.; Ju, J.; vargas, M.; Csiszar, I. A.

    2012-12-01

    Real-time weekly global green vegetation fraction (GVF) is needed in the numeric weather, climate and hydrological models. The current NOAA operational GVF product is derived from weekly AVHRR NDVI data, which are composited using the maximum-value compositing (MVC) method. MVC is a widely used technique to remove cloud and atmospheric contamination over land surface by selecting the observation of the maximum NDVI in a compositing period. However, it is well documented that the maximum NDVI is often selected from high sensor zenith angles (SZA), which may introduce error in GVF retrieval. To reduce the composite sensor zenith angles, a view angle adjusted soil-adjusted vegetation index (VA-SAVI), instead of NDVI, is proposed as the criterion of compositing in this study (VA-SAVI=SAVI-C×SZA2, where C is a coefficient). The observation with the maximum VA-SAVI (MVA-SAVI) is selected to represent a compositing period. To evaluate the MVA-SAVI compositing method, global Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua daily surface reflectance data (MYD09GA) in different seasons were composited using the MVA-SAVI method. Composite data were then compared with the 16-day MVC composite data, the MODIS standard 16-day vegetation index (MYD13A1) and 8-day surface reflectance data (MYD09A1). It was found that the mean 16-day composite sensor zenith angle by MVA-SAVI was 13.5°, whereas the mean sensor zenith angles composited by MVC was 39.3°, demonstrated that MVA-SAVI compositing tends to select observations close to the nadir view. MVA-SAVI compositing produced the mean sensor zenith angle 10° and 6° smaller than the MYD13A1 and MYD09A1 data and the mean NDVI (EVI) values 1.4% and 3.2% (4.0% and 3.3%) higher than those the MYD13A1 and MYD09A1 data, respectively. The smaller composited sensor zenith angles and higher vegetation index values suggest that MVA-SAVI compositing is a better compositing method than the MODIS compositing methods and the

  16. Validation of Cloud Parameters Derived from Geostationary Satellites, AVHRR, MODIS, and VIIRS Using SatCORPS Algorithms

    Science.gov (United States)

    Minnis, P.; Sun-Mack, S.; Bedka, K. M.; Yost, C. R.; Trepte, Q. Z.; Smith, W. L., Jr.; Painemal, D.; Chen, Y.; Palikonda, R.; Dong, X.; Xi, B.

    2016-01-01

    Validation is a key component of remote sensing that can take many different forms. The NASA LaRC Satellite ClOud and Radiative Property retrieval System (SatCORPS) is applied to many different imager datasets including those from the geostationary satellites, Meteosat, Himiwari-8, INSAT-3D, GOES, and MTSAT, as well as from the low-Earth orbiting satellite imagers, MODIS, AVHRR, and VIIRS. While each of these imagers have similar sets of channels with wavelengths near 0.65, 3.7, 11, and 12 micrometers, many differences among them can lead to discrepancies in the retrievals. These differences include spatial resolution, spectral response functions, viewing conditions, and calibrations, among others. Even when analyzed with nearly identical algorithms, it is necessary, because of those discrepancies, to validate the results from each imager separately in order to assess the uncertainties in the individual parameters. This paper presents comparisons of various SatCORPS-retrieved cloud parameters with independent measurements and retrievals from a variety of instruments. These include surface and space-based lidar and radar data from CALIPSO and CloudSat, respectively, to assess the cloud fraction, height, base, optical depth, and ice water path; satellite and surface microwave radiometers to evaluate cloud liquid water path; surface-based radiometers to evaluate optical depth and effective particle size; and airborne in-situ data to evaluate ice water content, effective particle size, and other parameters. The results of comparisons are compared and contrasted and the factors influencing the differences are discussed.

  17. Application of phase retrieval algorithm in reflective tomography laser radar imaging

    Institute of Scientific and Technical Information of China (English)

    Xiaofeng Jin; Jianfeng Sun; Yi Yan; Yu Zhou; Liren Liu

    2011-01-01

    @@ We apply phase retrieval method to align projection data for tomographic reconstruction in reflective tomography laser radar imaging. In our experiment, the target is placed on a spin table with an unknown,but fixed, axis. The oscillatory motion of the target in the incident direction of the laser pulse is added at each view to simulate the real satellites random motion. The experimental simulation results demonstrate the effectiveness of this method to improve image reconstruction quality. Future research also includes the development of projection registration based on phase retrieval for targets with more complicated structure.%We apply phase retrieval method to align projection data for tomographic reconstruction in reflective tomography laser radar imaging. In our experiment, the target is placed on a spin table with an unknown,but fixed, axis. The oscillatory motion of the target in the incident direction of the laser pulse is added at each view to simulate the real satellites random motion. The experimental simulation results demonstrate the effectiveness of this method to improve image reconstruction quality. Future research also includes the development of projection registration based on phase retrieval for targets with more complicated structure.

  18. Efficient Algorithm for Railway Tracks Detection Using Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Ali Javed

    2012-10-01

    Full Text Available Satellite imagery can produce maps including roads, railway tracks, buildings, bridges, oceans, lakes, rivers, etc. In developed countries like USA, Canada, Australia, Europe, images produced by Google map are of high resolution and good quality. On the other hand, mostly images of the third world countries like Pakistan, Asian and African countries are of poor quality and not clearly visible. Similarly railway tracks of these countries are hardly visible in Google map. We have developed an efficient algorithm for railway track detection from a low quality image of Google map. This would lead to detect damaged railway track, railway crossings and help to schedule/divert locomotive movements in order to avoid catastrophe.

  19. Stochastic optimal phase retrieval algorithm for high-contrast imaging

    Science.gov (United States)

    Give'on, Amir; Kasdin, N. Jeremy; Vanderbei, Robert J.; Spergel, David N.; Littman, Michael G.; Gurfil, Pini

    2003-12-01

    The Princeton University Terrestrial Planet Finder (TPF) has been working on a novel method for direct imaging of extra solar planets using a shaped-pupil coronagraph. The entrance pupil of the coronagraph is optimized to have a point spread function (PSF) that provides the suppression level needed at the angular separation required for detection of extra solar planets. When integration time is to be minimized, the photon count at the planet location in the image plane is a Poisson distributed random process. The ultimate limitation of these high-dynamic-range imaging systems comes from scattering due to imperfections in the optical surfaces of the collecting system. The first step in correcting the wavefront errors is the estimation of the phase aberrations. The phase aberration caused by these imperfections is assumed to be a sum of two-dimensional sinusoidal functions. Its parameters are estimated using a global search with a genetic algorithm and a local optimization with the BFGS quasi-Newton method with a mixed quadratic and cubic line search procedure.

  20. Retrieval of Dry Snow Parameters from Radiometric Data Using a Dense Medium Model and Genetic Algorithms

    Science.gov (United States)

    Tedesco, Marco; Kim, Edward J.

    2005-01-01

    In this paper, GA-based techniques are used to invert the equations of an electromagnetic model based on Dense Medium Radiative Transfer Theory (DMRT) under the Quasi Crystalline Approximation with Coherent Potential to retrieve snow depth, mean grain size and fractional volume from microwave brightness temperatures. The technique is initially tested on both noisy and not-noisy simulated data. During this phase, different configurations of genetic algorithm parameters are considered to quantify how their change can affect the algorithm performance. A configuration of GA parameters is then selected and the algorithm is applied to experimental data acquired during the NASA Cold Land Process Experiment. Snow parameters retrieved with the GA-DMRT technique are then compared with snow parameters measured on field.

  1. Improved interpretation of satellite altimeter data using genetic algorithms

    Science.gov (United States)

    Messa, Kenneth; Lybanon, Matthew

    1992-01-01

    Genetic algorithms (GA) are optimization techniques that are based on the mechanics of evolution and natural selection. They take advantage of the power of cumulative selection, in which successive incremental improvements in a solution structure become the basis for continued development. A GA is an iterative procedure that maintains a 'population' of 'organisms' (candidate solutions). Through successive 'generations' (iterations) the population as a whole improves in simulation of Darwin's 'survival of the fittest'. GA's have been shown to be successful where noise significantly reduces the ability of other search techniques to work effectively. Satellite altimetry provides useful information about oceanographic phenomena. It provides rapid global coverage of the oceans and is not as severely hampered by cloud cover as infrared imagery. Despite these and other benefits, several factors lead to significant difficulty in interpretation. The GA approach to the improved interpretation of satellite data involves the representation of the ocean surface model as a string of parameters or coefficients from the model. The GA searches in parallel, a population of such representations (organisms) to obtain the individual that is best suited to 'survive', that is, the fittest as measured with respect to some 'fitness' function. The fittest organism is the one that best represents the ocean surface model with respect to the altimeter data.

  2. Retrieving Clear-Sky Surface Skin Temperature for Numerical Weather Prediction Applications from Geostationary Satellite Data

    Directory of Open Access Journals (Sweden)

    Baojuan Shan

    2013-01-01

    Full Text Available Atmospheric models rely on high-accuracy, high-resolution initial radiometric and surface conditions for better short-term meteorological forecasts, as well as improved evaluation of global climate models. Remote sensing of the Earth’s energy budget, particularly with instruments flown on geostationary satellites, allows for near-real-time evaluation of cloud and surface radiation properties. The persistence and coverage of geostationary remote sensing instruments grant the frequent retrieval of near-instantaneous quasi-global skin temperature. Among other cloud and clear-sky retrieval parameters, NASA Langley provides a non-polar, high-resolution land and ocean skin temperature dataset for atmospheric modelers by applying an inverted correlated k-distribution method to clear-pixel values of top-of-atmosphere infrared temperature. The present paper shows that this method yields clear-sky skin temperature values that are, for the most part, within 2 K of measurements from ground-site instruments, like the Southern Great Plains Atmospheric Radiation Measurement (ARM Infrared Thermometer and the National Climatic Data Center Apogee Precision Infrared Thermocouple Sensor. The level of accuracy relative to the ARM site is comparable to that of the Moderate-resolution Imaging Spectroradiometer (MODIS with the benefit of an increased number of daily measurements without added bias or increased error. Additionally, matched comparisons of the high-resolution skin temperature product with MODIS land surface temperature reveal a level of accuracy well within 1 K for both day and night. This confidence will help in characterizing the diurnal and seasonal biases and root-mean-square differences between the retrievals and modeled values from the NASA Goddard Earth Observing System Version 5 (GEOS-5 in preparation for assimilation of the retrievals into GEOS-5. Modelers should find the immediate availability and broad coverage of these skin temperature

  3. Snow thickness retrieval over thick Arctic sea ice using SMOS satellite data

    Directory of Open Access Journals (Sweden)

    N. Maaß

    2013-12-01

    Full Text Available The microwave interferometric radiometer of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS mission measures at a frequency of 1.4 GHz in the L-band. In contrast to other microwave satellites, low frequency measurements in L-band have a large penetration depth in sea ice and thus contain information on the ice thickness. Previous ice thickness retrievals have neglected a snow layer on top of the ice. Here, we implement a snow layer in our emission model and investigate how snow influences L-band brightness temperatures and whether it is possible to retrieve snow thickness over thick Arctic sea ice from SMOS data. We find that the brightness temperatures above snow-covered sea ice are higher than above bare sea ice and that horizontal polarisation is more affected by the snow layer than vertical polarisation. In accordance with our theoretical investigations, the root mean square deviation between simulated and observed horizontally polarised brightness temperatures decreases from 20.9 K to 4.7 K, when we include the snow layer in the simulations. Although dry snow is almost transparent in L-band, we find brightness temperatures to increase with increasing snow thickness under cold Arctic conditions. The brightness temperatures' dependence on snow thickness can be explained by the thermal insulation of snow and its dependence on the snow layer thickness. This temperature effect allows us to retrieve snow thickness over thick sea ice. For the best simulation scenario and snow thicknesses up to 35 cm, the average snow thickness retrieved from horizontally polarised SMOS brightness temperatures agrees within 0.1 cm with the average snow thickness measured during the IceBridge flight campaign in the Arctic in spring 2012. The corresponding root mean square deviation is 5.5 cm, and the coefficient of determination is r2 = 0.58.

  4. Snow thickness retrieval over thick Arctic sea ice using SMOS satellite data

    Directory of Open Access Journals (Sweden)

    N. Maaß

    2013-07-01

    Full Text Available The microwave interferometric radiometer of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS mission measures at a frequency of 1.4 GHz in the L-band. In contrast to other microwave satellites, low frequency measurements in L-band have a large penetration depth in sea ice and thus contain information on the ice thickness. Previous ice thickness retrievals have neglected a snow layer on top of the ice. Here, we implement a snow layer in our emission model and investigate how snow influences L-band brightness temperatures and whether it is possible to retrieve snow thickness over thick Arctic sea ice from SMOS data. We find that the brightness temperatures above snow-covered sea ice are higher than above bare sea ice and that horizontal polarisation is more affected by the snow layer than vertical polarisation. In accordance with our theoretical investigations, the root mean square deviation between simulated and observed horizontally polarised brightness temperatures decreases from 20.0 K to 4.4 K, when we include the snow layer in the simulations. Under cold Arctic conditions we find brightness temperatures to increase with increasing snow thickness. Because dry snow is almost transparent in L-band, this brightness temperature's dependence on snow thickness origins from the thermal insulation of snow and its dependence on the snow layer thickness. This temperature effect allows us to retrieve snow thickness over thick sea ice. For the best simulation scenario and snow thicknesses up to 35 cm, the average snow thickness retrieved from horizontally polarised SMOS brightness temperatures agrees within 0.7 cm with the average snow thickness measured during the IceBridge flight campaign in the Arctic in spring 2012. The corresponding root mean square deviation is 6.3 cm, and the correlation coefficient is r2 = 0.55.

  5. Retrieval Using Texture Features in High Resolution Multi-spectral Satellite Imagery

    Energy Technology Data Exchange (ETDEWEB)

    Newsam, S D; Kamath, C

    2004-01-22

    Texture features have long been used in remote sensing applications to represent and retrieve image regions similar to a query region. Various representations of texture have been proposed based on the Fourier power spectrum, spatial co-occurrence, wavelets, Gabor filters, etc. These representations vary in their computational complexity and their suitability for representing different region types. Much of the work done thus far has focused on panchromatic imagery at low to moderate spatial resolutions, such as images from Landsat 1-7 which have a resolution of 15-30 m/pixel, and from SPOT 1-5 which have a resolution of 2.5-20 m/pixel. However, it is not clear which texture representation works best for the new classes of high resolution panchromatic (60-100 cm/pixel) and multi-spectral (4 bands for red, green, blue, and near infra-red at 2.4-4 m/pixel) imagery. It is also not clear how the different spectral bands should be combined. In this paper, we investigate the retrieval performance of several different texture representations using multi-spectral satellite images from IKONOS. A query-by-example framework, along with a manually chosen ground truth dataset, allows different combinations of texture representations and spectral bands to be compared. We focus on the specific problem of retrieving inhabited regions from images of urban and rural scenes. Preliminary results show that (1) the use of all spectral bands improves the retrieval performance, and (2) co-occurrence, wavelet and Gabor texture features perform comparably.

  6. Improvements of a COMS Land Surface Temperature Retrieval Algorithm Based on the Temperature Lapse Rate and Water Vapor/Aerosol Effect

    Directory of Open Access Journals (Sweden)

    A-Ra Cho

    2015-02-01

    Full Text Available The National Meteorological Satellite Center in Korea retrieves land surface temperature (LST by applying the split-window LST algorithm (CSW_v1.0 to Communication, Ocean, and Meteorological Satellite (COMS data. Considerable errors were detected under conditions of high water vapor content or temperature lapse rates during validation with Moderate Resolution Imaging Spectroradiometer (MODIS LST because of the too simplified LST algorithm. In this study, six types of LST retrieval equations (CSW_v2.0 were developed to upgrade the CSW_v1.0. These methods were developed by classifying “dry,” “normal,” and “wet” cases for day and night and considering the relative sizes of brightness temperature difference (BTD values. Similar to CSW_v1.0, the LST retrieved by CSW_v2.0 had a correlation coefficient of 0.99 with the prescribed LST and a slightly larger bias of −0.03 K from 0.00K; the root mean square error (RMSE improved from 1.41 K to 1.39 K. In general, CSW_v2.0 improved the retrieval accuracy compared to CSW_v1.0, especially when the lapse rate was high (mid-day and dawn and the water vapor content was high. The spatial distributions of LST retrieved by CSW_v2.0 were found to be similar to the MODIS LST independently of the season, day/night, and geographic locations. The validation using one year’s MODIS LST data showed that CSW_v2.0 improved the retrieval accuracy of LST in terms of correlations (from 0.988 to 0.989, bias (from −1.009 K to 0.292 K, and RMSEs (from 2.613 K to 2.237 K.

  7. Snow thickness retrieval using SMOS satellite data: Comparison with airborne IceBridge and buoy measurements

    Science.gov (United States)

    Maaß, N.; Kaleschke, L.; Tian-Kunze, X.

    2015-12-01

    The passive microwave mission SMOS (Soil Moisture and Ocean Salinity) provides daily coverage of the polar regions and its data have been used to retrieve thin sea ice thickness up to about one meter. In addition, there has been an attempt to retrieve snow thickness over thick Arctic multi-year ice, which is a crucial parameter for the freeboard-based estimation of (thick) sea ice thickness from lidar and radar altimetry. SMOS provides measurements at a frequency of 1.4 GHz (L-band) at horizontal and vertical polarization for a range of incidence angles (0 to 60°). The retrieval of ice or snow parameters from SMOS measurements is based on an emission model that describes the 1.4 GHz brightness temperature of (snow-covered) sea ice as a function of the ice and snow thicknesses and the permittivities of these media, which are mainly determined by ice temperature and salinity and snow density, respectively. In the first attempts to retrieve snow thickness from SMOS data, these parameters were assumed to be constant in the emission model, and the resulting maps were compared with airborne ice and snow thickness measurements taken during NASA's Operation IceBridge mission in spring 2012. The present approach to produce SMOS snow thickness maps is more elaborate. For example, available information on the ice surface temperature from MODIS (MODerate resolution Imaging Spectroradiometer) satellite images or from the IceBridge campaign itself are used, and the ice in the retrieval model is described by temperature and salinity profiles instead of using bulk values. As a first step we have produced (winter/spring) snow thickness maps of the Arctic, from 3-day-averages up to monthly means, using the available SMOS data from 2010 on. Here, we show how our spatial snow thickness distributions compare with IceBridge campaign data in the western Arctic from spring 2011 to 2015. In addition, we show how the temporal evolution of SMOS-retrieved snow thickness compares with snow

  8. Accounting for surface reflectance anisotropy in satellite retrievals of tropospheric NO2

    Directory of Open Access Journals (Sweden)

    B. Buchmann

    2010-05-01

    Full Text Available Surface reflectance is a key parameter in satellite trace gas retrievals in the UV/visible range and in particular for the retrieval of nitrogen dioxide (NO2 vertical tropospheric columns (VTCs. Current operational retrievals rely on coarse-resolution reflectance data and do not account for the generally anisotropic properties of surface reflectance. Here we present a NO2 VTC retrieval that uses MODIS bi-directional reflectance distribution function (BRDF data at high temporal (8 days and spatial (1 km×1 km resolution in combination with the LIDORT radiative transfer model to account for the dependence of surface reflectance on viewing and illumination geometry. The method was applied to two years of NO2 observations from the Ozone Monitoring Instrument (OMI over Europe. Due to its wide swath, OMI is particularly sensitive to BRDF effects. Using representative BRDF parameters for various land surfaces, we found that in July (low solar zenith angles and November (high solar zenith angles and for typical viewing geometries of OMI, differences between MODIS black-sky albedos and surface bi-directional reflectances are of the order of 0–10% and 0–40%, respectively, depending on the position of the OMI pixel within the swath. In the retrieval, black-sky albedo was treated as a Lambertian (isotropic reflectance, while for BRDF effects we used the kernel-based approach in the MODIS BRDF product. Air Mass Factors were computed using the LIDORT radiative transfer model based on these surface reflectance conditions. Differences in NO2 VTCs based on the Lambertian and BRDF approaches were found to be of the order of 0–3% in July and 0–20% in November with the extreme values found at large viewing angles. The much larger differences in November are partly due to higher solar zenith angles and partly to the choice of a priori NO2 profiles – the latter typically have more pronounced maxima in the boundary layer during the cold season. However, BRDF

  9. Validation of SMOS L1C and L2 Products and Important Parameters of the Retrieval Algorithm in the Skjern River Catchment, Western Denmark

    DEFF Research Database (Denmark)

    Bircher, Simone; Skou, Niels; Kerr, Yann H.

    2013-01-01

    The Soil Moisture and Ocean Salinity (SMOS) satellite with a passive L-band radiometer monitors surface soil moisture. In addition to soil moisture, vegetation optical thickness tau(NAD) is retrieved (L2 product) from brightness temperatures (T-B, L1C product) using an algorithm based on the L...... and the most sensitive algorithm parameters were analyzed by network and airborne campaign data collected within one SMOS pixel (44 km diameter). The SMOS retrieval is based on the prevailing low vegetation class. For the L1C comparison, T-B's were calculated from in situ soil moisture using L-MEB. Consistent......-band Microwave Emission of the Biosphere (L-MEB) model with initial guesses on the two parameters (derived from ECMWF products and ECOCLIMAP Leaf Area Index, respectively) and other auxiliary input. This paper presents the validation work carried out in the Skjern River Catchment, Denmark. L1C/L2 data...

  10. Hierarchical Supervisor and Agent Routing Algorithm in LEO/MEO Double-layered Optical Satellite Network

    Science.gov (United States)

    Li, Yongjun; Zhao, Shanghong

    2016-09-01

    A novel routing algorithm (Hierarchical Supervisor and Agent Routing Algorithm, HSARA) for LEO/MEO (low earth orbit/medium earth orbit) double-layered optical satellite network is brought forward. The so-called supervisor (MEO satellite) is designed for failure recovery and network management. LEO satellites are grouped according to the virtual managed field of MEO which is different from coverage area of MEO satellite in RF satellite network. In each LEO group, one LEO satellite which has maximal persistent link with its supervisor is called the agent. A LEO group is updated when this optical inter-orbit links between agent LEO satellite and the corresponding MEO satellite supervisor cuts off. In this way, computations of topology changes and LEO group updating can be decreased. Expense of routing is integration of delay and wavelength utilization. HSARA algorithm simulations are implemented and the results are as follows: average network delay of HSARA can reduce 21 ms and 31.2 ms compared with traditional multilayered satellite routing and single-layer LEO satellite respectively; LEO/MEO double-layered optical satellite network can cover polar region which cannot be covered by single-layered LEO satellite and throughput is 1% more than that of single-layered LEO satellite averagely. Therefore, exact global coverage can be achieved with this double-layered optical satellite network.

  11. Interference of Heavy Aerosol Loading on the VIIRS Aerosol Optical Depth (AOD Retrieval Algorithm

    Directory of Open Access Journals (Sweden)

    Yang Wang

    2017-04-01

    Full Text Available Aerosol optical depth (AOD has been widely used in climate research, atmospheric environmental observations, and other applications. However, high AOD retrieval remains challenging over heavily polluted regions, such as the North China Plain (NCP. The Visible Infrared Imaging Radiometer Suite (VIIRS, which was designed as a successor to the Moderate Resolution Imaging Spectroradiometer (MODIS, will undertake the aerosol observations mission in the coming years. Using the VIIRS AOD retrieval algorithm as an example, we analyzed the influence of heavy aerosol loading through the 6SV radiative transfer model (RTM with a focus on three aspects: cloud masking, ephemeral water body tests, and data quality estimation. First, certain pixels were mistakenly screened out as clouds and ephemeral water bodies because of heavy aerosols, resulting in the loss of AOD retrievals. Second, the greenness of the surface could not be accurately identified by the top of atmosphere (TOA index, and the quality of the aggregation data may be artificially high. Thus, the AOD retrieval algorithm did not perform satisfactorily, indicated by the low availability of data coverage (at least 37.97% of all data records were missing according to ground-based observations and overestimation of the data quality (high-quality data increased from 63.42% to 80.97% according to radiative simulations. To resolve these problems, the implementation of a spatial variability cloud mask method and surficial index are suggested in order to improve the algorithm.

  12. AERONET-based models of smoke-dominated aerosol near source regions and transported over oceans, and implications for satellite retrievals of aerosol optical depth

    Science.gov (United States)

    Sayer, A. M.; Hsu, N. C.; Eck, T. F.; Smirnov, A.; Holben, B. N.

    2014-10-01

    Smoke aerosols from biomass burning are an important component of the global aerosol system. Analysis of Aerosol Robotic Network (AERONET) retrievals of aerosol microphysical/optical parameters at 10 sites reveals variety between biomass burning aerosols in different global source regions, in terms of aerosol particle size and single scatter albedo (SSA). Case studies of smoke observed at coastal/island AERONET sites also mostly lie within the range of variability at the near-source sites. Differences between sites tend to be larger than variability at an individual site, although optical properties for some sites in different regions can be quite similar. Across the sites, typical midvisible SSA ranges from ~ 0.95-0.97 (sites dominated by boreal forest or peat burning, typically with larger fine-mode particle radius and spread) to ~ 0.88-0.9 (sites most influenced by grass, shrub, or crop burning, typically smaller fine-mode particle radius and spread). The tropical forest site Alta Floresta (Brazil) is closer to this second category, although with intermediate SSA ~ 0.92. The strongest absorption is seen in southern African savannah at Mongu (Zambia), with average midvisible SSA ~ 0.85. Sites with stronger absorption also tend to have stronger spectral gradients in SSA, becoming more absorbing at longer wavelengths. Microphysical/optical models are presented in detail so as to facilitate their use in radiative transfer calculations, including extension to UV (ultraviolet) wavelengths, and lidar ratios. One intended application is to serve as candidate optical models for use in satellite aerosol optical depth (AOD) retrieval algorithms. The models presently adopted by these algorithms over ocean often have insufficient absorption (i.e. too high SSA) to represent these biomass burning aerosols. The underestimates in satellite-retrieved AOD in smoke outflow regions, which have important consequences for applications of these satellite data sets, are consistent with

  13. Employing satellite retrieved soil moisture for parameter estimation of the hydrologic model mHM

    Science.gov (United States)

    Zink, Matthias; Mai, Juliane; Rakovec, Oldrich; Schrön, Martin; Kumar, Rohini; Schäfer, David; Samaniego, Luis

    2016-04-01

    Hydrological models are usually calibrated against observed streamflow at the catchment outlet and thus they are conditioned by an integral catchment signal. Rakovec et al. 2016 (JHM) recently demonstrated that constraining model parameters against river discharge is a necessary, but not a sufficient condition. Such a procedure ensures the fulfillment of the catchment's water balance but can lead to high predictive uncertainties of model internal states, like soil moisture, or a lack in spatial representativeness of the model. However, some hydrologic applications, as e.g. soil drought monitoring and prediction, rely on this information. Within this study we propose a framework in which the mesoscale Hydrologic Model (mHM) is calibrated with soil moisture retrievals from various sources. The aim is to condition the model on soil moisture (SM), while preserving good performance in streamflow estimation. We identify the most appropriate objective functions by conducting synthetic experiments. The best objective function is determined based on: 1) deviation between synthetic and simulated soil moisture, 2) nonparametric comparison of SM fields (e.g. copulas), and 3) by euclidian distance of model parameters, which is zero if the parameters of the synthetic data are recovered. Those objective functions performing best are used to calibrate mHM against different satellite soil moisture products, e.g. ESA-CCI, H-SAF, and in situ observations. This procedure is tested in three distinct European basins (upper Sava, Neckar, and upper Guadalquivir basin) ranging from snow domination to semi arid climatic conditions. Results obtained with the synthetic experiment indicate that objective functions focusing on the temporal dynamics of SM are preferable to objective functions aiming at spatial patterns or catchment averages. Since the deviation of soil moisture fields (1) and their copulas (2) don't lead to conclusive results, the decision of the best performing objective

  14. A Numerical Testbed for Remote Sensing of Aerosols, and its Demonstration for Evaluating Retrieval Synergy from a Geostationary Satellite Constellation of GEO-CAPE and GOES-R

    Science.gov (United States)

    Wang, Jun; Xu, Xiaoguang; Ding, Shouguo; Zeng, Jing; Spurr, Robert; Liu, Xiong; Chance, Kelly; Mishchenko, Michael I.

    2014-01-01

    We present a numerical testbed for remote sensing of aerosols, together with a demonstration for evaluating retrieval synergy from a geostationary satellite constellation. The testbed combines inverse (optimal-estimation) software with a forward model containing linearized code for computing particle scattering (for both spherical and non-spherical particles), a kernel-based (land and ocean) surface bi-directional reflectance facility, and a linearized radiative transfer model for polarized radiance. Calculation of gas absorption spectra uses the HITRAN (HIgh-resolution TRANsmission molecular absorption) database of spectroscopic line parameters and other trace species cross-sections. The outputs of the testbed include not only the Stokes 4-vector elements and their sensitivities (Jacobians) with respect to the aerosol single scattering and physical parameters (such as size and shape parameters, refractive index, and plume height), but also DFS (Degree of Freedom for Signal) values for retrieval of these parameters. This testbed can be used as a tool to provide an objective assessment of aerosol information content that can be retrieved for any constellation of (planned or real) satellite sensors and for any combination of algorithm design factors (in terms of wavelengths, viewing angles, radiance and/or polarization to be measured or used). We summarize the components of the testbed, including the derivation and validation of analytical formulae for Jacobian calculations. Benchmark calculations from the forward model are documented. In the context of NASA's Decadal Survey Mission GEOCAPE (GEOstationary Coastal and Air Pollution Events), we demonstrate the use of the testbed to conduct a feasibility study of using polarization measurements in and around the O2 A band for the retrieval of aerosol height information from space, as well as an to assess potential improvement in the retrieval of aerosol fine and coarse mode aerosol optical depth (AOD) through the

  15. SBUV version 8.6 Retrieval Algorithm: Error Analysis and Validation Technique

    Science.gov (United States)

    Kramarova, N. A.; Bhartia, P. K.; Frith, P. K.; McPeters, S. M.; Labow, R. D.; Taylor, G.; Fisher, S.; DeLand, M.

    2012-01-01

    SBUV version 8.6 algorithm was used to reprocess data from the Back Scattered Ultra Violet (BUV), the Solar Back Scattered Ultra Violet (SBUV) and a number of SBUV/2 instruments, which 'span a 41-year period from 1970 to 2011 (except a 5-year gap in the 1970s)[see Bhartia et al, 2012]. In the new version Daumont et al. [1992] ozone cross section were used, and new ozone [McPeters et ai, 2007] and cloud climatologies Doiner and Bhartia, 1995] were implemented. The algorithm uses the Optimum Estimation technique [Rodgers, 2000] to retrieve ozone profiles as ozone layer (partial column, DU) on 21 pressure layers. The corresponding total ozone values are calculated by summing ozone columns at individual layers. The algorithm is optimized to accurately retrieve monthly zonal mean (mzm) profiles rather than an individual profile, since it uses monthly zonal mean ozone climatology as the A Priori. Thus, the SBUV version 8.6 ozone dataset is better suited for long-term trend analysis and monitoring ozone changes rather than for studying short-term ozone variability. Here we discuss some characteristics of the SBUV algorithm and sources of error in the SBUV profile and total ozone retrievals. For the first time the Averaging Kernels, smoothing errors and weighting functions (or Jacobians) are included in the SBUV metadata. The Averaging Kernels (AK) represent the sensitivity of the retrieved profile to the true state and contain valuable information about the retrieval algorithm, such as Vertical Resolution, Degrees of Freedom for Signals (DFS) and Retrieval Efficiency [Rodgers, 2000]. Analysis of AK for mzm ozone profiles shows that the total number of DFS for ozone profiles varies from 4.4 to 5.5 out of 6-9 wavelengths used for retrieval. The number of wavelengths in turn depends on solar zenith angles. Between 25 and 0.5 hPa, where SBUV vertical resolution is the highest, DFS for individual layers are about 0.5.

  16. A comparison of iterative algorithms and a mixed approach for in-line x-ray phase retrieval.

    Science.gov (United States)

    Meng, Fanbo; Zhang, Da; Wu, Xizeng; Liu, Hong

    2009-08-15

    Previous studies have shown that iterative in-line x-ray phase retrieval algorithms may have higher precision than direct retrieval algorithms. This communication compares three iterative phase retrieval algorithms in terms of accuracy and efficiency using computer simulations. We found the Fourier transformation based algorithm (FT) is of the fastest convergence, while the Poisson-solver based algorithm (PS) has higher precision. The traditional Gerchberg-Saxton algorithm (GS) is very slow and sometimes does not converge in our tests. Then a mixed FT-PS algorithm is presented to achieve both high efficiency and high accuracy. The mixed algorithm is tested using simulated images with different noise level and experimentally obtained images of a piece of chicken breast muscle.

  17. Informing radar retrieval algorithm development using an alternative soil moisture validation technique

    Science.gov (United States)

    Crow, W. T.; Wagner, W.

    2009-12-01

    Applying basic data assimilation techniques to the evaluation of remote-sensing products can clarify the impact of sensor design issues on the value of retrievals for hydrologic applications. For instance, the impact of incidence angle on the accuracy of radar surface soil moisture retrievals is largely unknown due to discrepancies in theoretical backscatter models as well as limitations in the availability of sufficiently-extensive ground-based soil moisture observations for validation purposes. In this presentation we will describe and apply a data assimilation evaluation technique for scatterometer-based surface soil moisture retrievals that does not require ground-based soil moisture observations to examine the sensitivity of retrieval skill to variations in incidence angle. Past results with the approach have shown that it is capable of detecting relative variations in the correlation between anomalies in remotely-sensed surface soil moisture retrievals and ground-truth soil moisture measurements. Application of the evaluation approach to the TU-Wien WARP5.0 European Space Radar (ERS) soil moisture data set over two regional-scale (~1000 km) domains in the Southern United States indicates a relative reduction in anomaly correlation-based skill of between 20% and 30% when moving between the lowest ( 50 degrees) incidence angle ranges. These changes in anomaly-based correlation provide a useful proxy for relative variations in the value of estimates for data assimilation applications and can therefore be used to inform the design of appropriate retrieval algorithms. For example, the observed sensitivity of correlation-based skill with incidence angle is in approximate agreement with soil moisture retrieval uncertainty predictions made using the WARP5.0 backscatter model. However, the coupling of a bare soil backscatter model with the so-called "vegetation water cloud" model is shown to generally over-estimate the impact of incidence angle on retrieval skill

  18. New dynamic routing algorithm based on MANET in LEO/MEO satellite network

    Institute of Scientific and Technical Information of China (English)

    LI Zhe; LI Dong-ni; WANG Guang-xing

    2006-01-01

    The features of low earth orbit/medium earth orbit (LEO/MEO) satellite networks routing algorithm based on inter-satellite link are analyzed and the similarities between satellite networks and mobile Ad Hoc network (MANET) are pointed out.The similar parts in MANET routing protocol are used in the satellite network for reference.A new dynamic routing algorithm based on MANET in LEO/MEO satellite networks,which fits for the LEO/MEO satellite communication system,is proposed.At the same time,the model of the algorithm is simulated and features are analyzed.It is shown that the algorithm has strong adaptability.It can give the network high autonomy,perfect function,low system overhead and great compatibility.

  19. A comparison between two algorithms for the retrieval of soil moisture using AMSR-E data

    Science.gov (United States)

    A comparison between two algorithms for estimating soil moisture with microwave satellite data was carried out by using the datasets collected on the four Agricultural Research Service (ARS) watershed sites in the US from 2002 to 2009. These sites collectively represent a wide range of ground condit...

  20. A Multicast Routing Algorithm for Datagram Service in Delta LEO Satellite Constellation Networks

    Directory of Open Access Journals (Sweden)

    Yanpeng Ma

    2014-04-01

    Full Text Available Satellites can broadcast datagram over wide areas, therefore, the satellite network has congenital advantages to implement multicast service. LEO satellite has the property of efficient bandwidth usage, lower propagation delay and lower power consumption in the user terminals and satellites. Therefore, the constellation network composed by LEO satellites is an essential part of future satellite communication networks. In this paper, we propose a virtual center based multicast (VCMulticast routing algorithm for LEO satellite constellation network. The algorithm uses the geographic center information of group users to route multicast datagrams, with less memory, computer power and signaling overhead. We evaluate the delay and performance of our algorithm by means of simulations in the OPENET simulator. The results indicate that the delay of the proposed multicast method exceeds the minimum propagation by at most 29.1% on the average, which is a quite acceptable achievement, considering the resource overhead reduction that can be introduced by our proposal

  1. PM-GCD - A combined IR-MW satellite technique for frequent retrieval of heavy precipitation: Application to the EU FLASH project

    Science.gov (United States)

    Casella, Daniele; Dietrich, Stefano; di Paola, Francesco; Formenton, Marco; Mugnai, Alberto; Sanò, Paolo

    2010-05-01

    Precipitation retrievals based on measurements from microwave (MW) radiometers onboard low-Earth-orbit (LEO) satellites can reach a high level of accuracy - and especially so, for deep convective precipitating systems. However, these observations do not provide a satisfactorily coverage of the rapid evolution of intense precipitating systems. As a result, the obtained precipitation retrievals are often of limited use for many important applications -- including support to authorities in activating flood alarms. To avoid this problem, several techniques have been developed that combine accurate MW estimates with frequent infrared (IR) observations from geosynchronous (GEO) satellites, such as the European Meteosat Second Generation (MSG). Within the European Union FP6 FLASH project, we have developed a new combined MW-IR technique for producing frequent precipitation retrievals from space (which we call PM-GCD technique). This technique uses passive-microwave (PM) retrievals in conjunction with the Global Convection Detection (GCD) technique that discriminates deep convective clouds within the GEO observations, based on the difference between the water vapor (6.2 μm ) and thermal-IR (10.8 μm ) channels. In essence, within the PM-GCD technique, deep convective areas are defined from MSG observations, then calibrated using MW-AMSU precipitation retrievals and finally propagated over time with a simple tracking algorithm. In this paper, we describe the PM-GCD technique and discuss the results of its application to a flood event that occurred on September 12-15, 2006 over the north-western Mediterranean coastal areas, and that has been selected for joint research by the EU FLASH and HYDRATE projects.

  2. Algorithm for Image Retrieval Based on Edge Gradient Orientation Statistical Code

    Directory of Open Access Journals (Sweden)

    Jiexian Zeng

    2014-01-01

    Full Text Available Image edge gradient direction not only contains important information of the shape, but also has a simple, lower complexity characteristic. Considering that the edge gradient direction histograms and edge direction autocorrelogram do not have the rotation invariance, we put forward the image retrieval algorithm which is based on edge gradient orientation statistical code (hereinafter referred to as EGOSC by sharing the application of the statistics method in the edge direction of the chain code in eight neighborhoods to the statistics of the edge gradient direction. Firstly, we construct the n-direction vector and make maximal summation restriction on EGOSC to make sure this algorithm is invariable for rotation effectively. Then, we use Euclidean distance of edge gradient direction entropy to measure shape similarity, so that this method is not sensitive to scaling, color, and illumination change. The experimental results and the algorithm analysis demonstrate that the algorithm can be used for content-based image retrieval and has good retrieval results.

  3. Improving volcanic ash predictions with the HYSPLIT dispersion model by assimilating MODIS satellite retrievals

    Science.gov (United States)

    Chai, Tianfeng; Crawford, Alice; Stunder, Barbara; Pavolonis, Michael J.; Draxler, Roland; Stein, Ariel

    2017-02-01

    Currently, the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) runs the HYSPLIT dispersion model with a unit mass release rate to predict the transport and dispersion of volcanic ash. The model predictions provide information for the Volcanic Ash Advisory Centers (VAAC) to issue advisories to meteorological watch offices, area control centers, flight information centers, and others. This research aims to provide quantitative forecasts of ash distributions generated by objectively and optimally estimating the volcanic ash source strengths, vertical distribution, and temporal variations using an observation-modeling inversion technique. In this top-down approach, a cost functional is defined to quantify the differences between the model predictions and the satellite measurements of column-integrated ash concentrations weighted by the model and observation uncertainties. Minimizing this cost functional by adjusting the sources provides the volcanic ash emission estimates. As an example, MODIS (Moderate Resolution Imaging Spectroradiometer) satellite retrievals of the 2008 Kasatochi volcanic ash clouds are used to test the HYSPLIT volcanic ash inverse system. Because the satellite retrievals include the ash cloud top height but not the bottom height, there are different model diagnostic choices for comparing the model results with the observed mass loadings. Three options are presented and tested. Although the emission estimates vary significantly with different options, the subsequent model predictions with the different release estimates all show decent skill when evaluated against the unassimilated satellite observations at later times. Among the three options, integrating over three model layers yields slightly better results than integrating from the surface up to the observed volcanic ash cloud top or using a single model layer. Inverse tests also show that including the ash-free region to constrain the model is not

  4. A New Inversion-Based Algorithm for Retrieval of Over-Water Rain Rate from SSM/I Multichannel Imagery

    Science.gov (United States)

    Petty, Grant W.; Stettner, David R.

    1994-01-01

    This paper discusses certain aspects of a new inversion based algorithm for the retrieval of rain rate over the open ocean from the special sensor microwave/imager (SSM/I) multichannel imagery. This algorithm takes a more detailed physical approach to the retrieval problem than previously discussed algorithms that perform explicit forward radiative transfer calculations based on detailed model hydrometer profiles and attempt to match the observations to the predicted brightness temperature.

  5. Optical and Microphysical Retrievals of Marine Stratocumulus Clouds off the Coast of Namibia from Satellite and Aircraft

    Science.gov (United States)

    Platnick, Steven E.

    2010-01-01

    these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, and fundamental atmospheric research. The archived MODIS Collection 5 cloud products processing stream will be used to analyze low water cloud scenes off the Namibian and Angolan coasts during SAFARI 2000 time period, as well as other years. Pixel-level Terra and Aqua MODIS retrievals (l. km spatial resolution at nadir) and gridded (1' uniform grid) statistics of cloud optical thickness and effective particle radius will be presented, including joint probability distributions between the two quantities. In addition, perspectives from the MODIS Airborne Simulator, which flew on the ER-2 during SAFARI 2000 providing high spatial resolution retrievals (50 m at nadir), will be presented as appropriate. The H-SAF Program requires an experimental operational European-centric Satellite Precipitation Algorithm System (E-SPAS) that produces medium spatial resolution and high temporal resolution surface rainfall and snowfall estimates over the Greater European Region including the Greater Mediterranean Basin. Currently, there are various types of experimental operational algorithm methods of differing spatiotemporal resolutions that generate global precipitation estimates. This address will first assess the current status of these methods and then recommend a methodology for the H-SAF Program that deviates somewhat from the current approach under development but one that takes advantage of existing techniques and existing software developed for the TRMM Project and available through the public domain.

  6. Impact of rain-induced sea surface roughness variations on salinity retrieval from the Aquarius/SAC-D satellite

    Institute of Scientific and Technical Information of China (English)

    MA Wentao; YANG Xiaofeng; YU Yang; LIU Guihong; LI Ziwei; JING Cheng

    2015-01-01

    Rainfall has two significant effects on the sea surface, including salinity decreasing and surface becoming rougher, which have further influence on L-band sea surface emissivity. Investigations using the Aquarius and TRMM 3B42 matchup dataset indicate that the retrieved sea surface salinity (SSS) is underestimated by the present Aquarius algorithm compared to numerical model outputs, especially in cases of a high rain rate. For example, the bias between satellite-observed SSS and numerical model SSS is approximately 2 when the rain rate is 25 mm/h. The bias can be eliminated by accounting for rain-induced roughness, which is usually modeled by rain-generated ring-wave spectrum. The rain spectrum will be input into the Small Slope Approximation (SSA) model for the simulation of sea surface emissivity influenced by rain. The comparison with theoretical model indicated that the empirical model of rain spectrumis more suitable to be used in the simulation. Further, the coefficients of the rain spectrum are modified by fitting the simulations with the observations of the 2–year Aquarius and TRMM matchup dataset. The calculations confirm that the sea surface emissivity increases with the wind speed and rain rate. The increase induced by the rain rate is rapid in the case of low rain rate and low wind speed. Finally, a modified model of sea surface emissivity including the rain spectrum is proposed and validated by using the matchup dataset in May 2014. Compared with observations, the bias of the rain-induced sea surface emissivity simulated by the modified modelis approximately 1e–4, and the RMSE is slightly larger than 1e–3. With using more matchup data, thebias between model retrieved sea surface salinities and observationsmay be further corrected, and the RMSE may be reduced to less than 1 in the cases of low rain rate and low wind speed.

  7. Tropospheric ozone column retrieval at northern mid-latitudes from the Ozone Monitoring Instrument by means of a neural network algorithm

    Directory of Open Access Journals (Sweden)

    P. Sellitto

    2011-11-01

    Full Text Available Monitoring tropospheric ozone from space is of critical importance in order to gain more thorough knowledge on phenomena affecting air quality and the greenhouse effect. Deriving information on tropospheric ozone from UV/VIS nadir satellite spectrometers is difficult owing to the weak sensitivity of the measured radiance spectra to variations of ozone in the troposphere. Here we propose an alternative method of analysis to retrieve tropospheric ozone columns from Ozone Monitoring Instrument radiances by means of a neural network algorithm. An extended set of ozone sonde measurements at northern mid-latitudes for the years 2004–2008 has been considered as the training and test data set. The design of the algorithm is extensively discussed. Our retrievals are compared to both tropospheric ozone residuals and optimal estimation retrievals over a similar independent test data set. Results show that our algorithm has comparable accuracy with respect to both correlative methods and its performance is slightly better over a subset containing only European ozone sonde stations. Possible sources of errors are analyzed. Finally, the capabilities of our algorithm to derive information on boundary layer ozone are studied and the results critically discussed.

  8. AERONET-based microphysical and optical properties of smoke-dominated aerosol near source regions and transported over oceans, and implications for satellite retrievals of aerosol optical depth

    Science.gov (United States)

    Sayer, A. M.; Hsu, N. C.; Eck, T. F.; Smirnov, A.; Holben, B. N.

    2013-09-01

    Smoke aerosols from biomass burning are an important component of the global aerosol cycle. Analysis of Aerosol Robotic Network (AERONET) retrievals of size distribution and refractive index reveals variety between biomass burning aerosols in different global source regions, in terms of aerosol particle size and single scatter albedo (SSA). Case studies of smoke transported to coastal/island AERONET sites also mostly lie within the range of variability at near-source sites. Two broad ''families'' of aerosol properties are found, corresponding to sites dominated by boreal forest burning (larger, broader fine mode, with midvisible SSA ∼0.95), and those influenced by grass, shrub, or crop burning with additional forest contributions (smaller, narrower particles with SSA ∼0.88-0.9 in the midvisible). The strongest absorption is seen in southern African savannah at Mongu (Zambia), with average SSA ∼0.85 in the midvisible. These can serve as candidate sets of aerosol microphysical/optical properties for use in satellite aerosol optical depth (AOD) retrieval algorithms. The models presently adopted by these algorithms over ocean are often insufficiently absorbing to represent these biomass burning aerosols. A corollary of this is an underestimate of AOD in smoke outflow regions, which has important consequences for applications of these satellite datasets.

  9. Genetic Algorithm Phase Retrieval for the Systematic Image-Based Optical Alignment Testbed

    Science.gov (United States)

    Taylor, Jaime; Rakoczy, John; Steincamp, James

    2003-01-01

    Phase retrieval requires calculation of the real-valued phase of the pupil fimction from the image intensity distribution and characteristics of an optical system. Genetic 'algorithms were used to solve two one-dimensional phase retrieval problem. A GA successfully estimated the coefficients of a polynomial expansion of the phase when the number of coefficients was correctly specified. A GA also successfully estimated the multiple p h e s of a segmented optical system analogous to the seven-mirror Systematic Image-Based Optical Alignment (SIBOA) testbed located at NASA s Marshall Space Flight Center. The SIBOA testbed was developed to investigate phase retrieval techniques. Tiphilt and piston motions of the mirrors accomplish phase corrections. A constant phase over each mirror can be achieved by an independent tip/tilt correction: the phase Conection term can then be factored out of the Discrete Fourier Tranform (DFT), greatly reducing computations.

  10. A physics-based statistical algorithm for retrieving land surface temperature from AMSR-E passive microwave data

    Institute of Scientific and Technical Information of China (English)

    MAO KeBiao; SHI JianCheng; LI ZhaoLiang; QIN ZhiHao; LI ManChun; XU Bin

    2007-01-01

    AMSR-E and MODIS are two EOS (Earth Observing System) instruments on board the Aqua satellite. A regression analysis between the brightness of all AMSR-E bands and the MODIS land surface temperature product indicated that the 89 GHz vertical polarization is the best single band to retrieve land surface temperature. According to simulation analysis with AIEM, the difference of different frequencies can eliminate the influence of water in soil and atmosphere, and also the surface roughness partly. The analysis results indicate that the radiation mechanism of surface covered snow is different from others. In order to retrieve land surface temperature more accurately, the land surface should be at least classified into three types: water covered surface, snow covered surface, and non-water and non-snow covered land surface. In order to improve the practicality and accuracy of the algorithm, we built different equations for different ranges of temperature. The average land surface temperature error is about 2-3℃ relative to the MODIS LST product.

  11. A physics-based statistical algorithm for retrieving land surface temperature from AMSR-E passive microwave data

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    AMSR-E and MODIS are two EOS (Earth Observing System) instruments on board the Aqua satellite. A regression analysis between the brightness of all AMSR-E bands and the MODIS land surface tem-perature product indicated that the 89 GHz vertical polarization is the best single band to retrieve land surface temperature. According to simulation analysis with AIEM,the difference of different frequen-cies can eliminate the influence of water in soil and atmosphere,and also the surface roughness partly. The analysis results indicate that the radiation mechanism of surface covered snow is different from others. In order to retrieve land surface temperature more accurately,the land surface should be at least classified into three types:water covered surface,snow covered surface,and non-water and non-snow covered land surface. In order to improve the practicality and accuracy of the algorithm,we built different equations for different ranges of temperature. The average land surface temperature er-ror is about 2―3℃ relative to the MODIS LST product.

  12. A new method to retrieve salinity profiles from sea surface salinity observed by SMOS satellite

    Institute of Scientific and Technical Information of China (English)

    YANG Tingting; CHEN Zhongbiao; HE Yijun

    2015-01-01

    This paper proposes a new method to retrieve salinity profiles from the sea surface salinity (SSS) observed by the Soil Moisture and Ocean Salinity (SMOS) satellite. The main vertical patterns of the salinity profiles are firstly extracted from the salinity profiles measured by Argo using the empirical orthogonal function. To determine the time coefficients for each vertical pattern, two statistical models are developed. In the linear model, a transfer function is proposed to relate the SSS observed by SMOS (SMOS_SSS) with that measured by Argo, and then a linear relationship between the SMOS_SSS and the time coefficient is established. In the nonlinear model, the neural network is utilized to estimate the time coefficients from SMOS_SSS, months and positions of the salinity profiles. The two models are validated by comparing the salinity profiles retrieved from SMOS with those measured by Argo and the climatological salinities. The root-mean-square error (RMSE) of the linear and nonlinear model are 0.08–0.16 and 0.08–0.14 for the upper 400 m, which are 0.01–0.07 and 0.01–0.09 smaller than the RMSE of climatology. The error sources of the method are also discussed.

  13. On the retrieval of significant wave heights from spaceborne Synthetic Aperture Radar (ERS-SAR using the Max-Planck Institut (MPI algorithm

    Directory of Open Access Journals (Sweden)

    Violante-Carvalho Nelson

    2005-01-01

    Full Text Available Synthetic Aperture Radar (SAR onboard satellites is the only source of directional wave spectra with continuous and global coverage. Millions of SAR Wave Mode (SWM imagettes have been acquired since the launch in the early 1990's of the first European Remote Sensing Satellite ERS-1 and its successors ERS-2 and ENVISAT, which has opened up many possibilities specially for wave data assimilation purposes. The main aim of data assimilation is to improve the forecasting introducing available observations into the modeling procedures in order to minimize the differences between model estimates and measurements. However there are limitations in the retrieval of the directional spectrum from SAR images due to nonlinearities in the mapping mechanism. The Max-Planck Institut (MPI scheme, the first proposed and most widely used algorithm to retrieve directional wave spectra from SAR images, is employed to compare significant wave heights retrieved from ERS-1 SAR against buoy measurements and against the WAM wave model. It is shown that for periods shorter than 12 seconds the WAM model performs better than the MPI, despite the fact that the model is used as first guess to the MPI method, that is the retrieval is deteriorating the first guess. For periods longer than 12 seconds, the part of the spectrum that is directly measured by SAR, the performance of the MPI scheme is at least as good as the WAM model.

  14. New temperature and pressure retrieval algorithm for high-resolution infrared solar occultation spectroscopy: analysis and validation against ACE-FTS and COSMIC

    Directory of Open Access Journals (Sweden)

    K. S. Olsen

    2015-10-01

    Full Text Available Motivated by the initial selection of a high-resolution solar occultation Fourier transform spectrometer (FTS to fly to Mars on the ExoMars Trace Gas Orbiter, we have been developing algorithms for retrieving volume mixing ratio vertical profiles of trace gases, the primary component of which is a new algorithm and software for retrieving vertical profiles of temperature and pressure from the spectra. In contrast to Earth-observing instruments, which can rely on accurate meteorological models, a priori information, and spacecraft position, Mars retrievals require a method with minimal reliance on such data. The temperature and pressure retrieval algorithms developed for this work were evaluated using Earth-observing spectra from the Atmospheric Chemistry Experiment (ACE FTS, a solar occultation instrument in orbit since 2003, and the basis for the instrument selected for a Mars mission. ACE-FTS makes multiple measurements during an occultation, separated in altitude by 1.5–5 km, and we analyze 10 CO2 vibration-rotation bands at each altitude, each with a different usable altitude range. We describe the algorithms and present results of their application and their comparison to the ACE-FTS data products. The Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC provides vertical profiles of temperature up to 40 km with high vertical resolution. Using six satellites and GPS radio occultation, COSMIC's data product has excellent temporal and spatial coverage, allowing us to find coincident measurements with ACE with very tight criteria: less than 1.5 h and 150 km. We present an inter-comparison of temperature profiles retrieved from ACE-FTS using our algorithm, that of the ACE Science Team (v3.5, and from COSMIC. When our retrievals are compared to ACE-FTS v3.5, we find mean differences between −5 and +2 K, and that our retrieved profiles have no seasonal or zonal biases, but do have a warm bias in the stratosphere and

  15. Position error in profiles retrieved from MIPAS observations with a 1-D algorithm

    Directory of Open Access Journals (Sweden)

    M. Carlotti

    2012-09-01

    Full Text Available The information load (IL analysis, first introduced for the two-dimensional approach (Carlotti and Magnani, 2009, is applied to the inversion of MIPAS observations operated with a 1-dimensional (1-D retrieval algorithm. The IL distribution of MIPAS spectra is shown to be often asymmetrical with respect to the tangent points of the observations and permits to identify the preferential latitude where the profiles retrieved with a 1-D algorithm should be geo-located. Therefore a position error is made when the tangent points of the observations are used to assign the geo-location of the retrieved profile. We assess the amplitude of the position error for some of the MIPAS main targets and we show that the IL analysis can also be used as a tool for the selection of observations that, when analyzed, minimize the position error of the retrieved profile. When the temperature (T profiles are used for the retrieval of volume mixing ratio (VMR of atmospheric constituents, the T position error (of the order of 1.5 degrees of latitude induces a VMR error that is directly connected with the horizontal T gradients. Temperature profiles can be externally-provided or determined in a previous step of the retrieval process. In the first case, the IL analysis shows that a meaningful fraction (often exceeding 50% of the VMR error deriving from the 1-D approximation is to be attributed to the mismatch between the position assigned to the external T profile and the positions where T is required by the analyzed observations. In the second case the retrieved T values suffer by an error of 1.5–2 K due to neglecting the horizontal variability of T; however the error induced on VMRs is of minor entity because of the generally small mismatch between the IL distribution of the observations analyzed to retrieve T and those analyzed to retrieve the VMR target. An estimate of the contribution of the

  16. Characterization and error analysis of an operational retrieval algorithm for estimating column ozone and aerosol properties from ground-based ultra-violet irradiance measurements

    Science.gov (United States)

    Taylor, Thomas E.; L'Ecuyer, Tristan; Slusser, James; Stephens, Graeme; Krotkov, Nick; Davis, John; Goering, Christian

    2005-08-01

    Extensive sensitivity and error characteristics of a recently developed optimal estimation retrieval algorithm which simultaneously determines aerosol optical depth (AOD), aerosol single scatter albedo (SSA) and total ozone column (TOC) from ultra-violet irradiances are described. The algorithm inverts measured diffuse and direct irradiances at 7 channels in the UV spectral range obtained from the United States Department of Agriculture's (USDA) UV-B Monitoring and Research Program's (UVMRP) network of 33 ground-based UV-MFRSR instruments to produce aerosol optical properties and TOC at all seven wavelengths. Sensitivity studies of the Tropospheric Ultra-violet/Visible (TUV) radiative transfer model performed for various operating modes (Delta-Eddington versus n-stream Discrete Ordinate) over domains of AOD, SSA, TOC, asymmetry parameter and surface albedo show that the solutions are well constrained. Realistic input error budgets and diagnostic and error outputs from the retrieval are analyzed to demonstrate the atmospheric conditions under which the retrieval provides useful and significant results. After optimizing the algorithm for the USDA site in Panther Junction, Texas the retrieval algorithm was run on a cloud screened set of irradiance measurements for the month of May 2003. Comparisons to independently derived AOD's are favorable with root mean square (RMS) differences of about 3% to 7% at 300nm and less than 1% at 368nm, on May 12 and 22, 2003. This retrieval method will be used to build an aerosol climatology and provide ground-truthing of satellite measurements by running it operationally on the USDA UV network database.

  17. WEB SEARCH ENGINE BASED SEMANTIC SIMILARITY MEASURE BETWEEN WORDS USING PATTERN RETRIEVAL ALGORITHM

    Directory of Open Access Journals (Sweden)

    Pushpa C N

    2013-02-01

    Full Text Available Semantic Similarity measures plays an important role in information retrieval, natural language processing and various tasks on web such as relation extraction, community mining, document clustering, and automatic meta-data extraction. In this paper, we have proposed a Pattern Retrieval Algorithm [PRA] to compute the semantic similarity measure between the words by combining both page count method and web snippets method. Four association measures are used to find semantic similarity between words in page count method using web search engines. We use a Sequential Minimal Optimization (SMO support vector machines (SVM to find the optimal combination of page counts-based similarity scores and top-ranking patterns from the web snippets method. The SVM is trained to classify synonymous word-pairs and nonsynonymous word-pairs. The proposed approach aims to improve the Correlation values, Precision, Recall, and F-measures, compared to the existing methods. The proposed algorithm outperforms by 89.8 % of correlation value.

  18. Fresnel domain nonlinear optical image encryption scheme based on Gerchberg-Saxton phase-retrieval algorithm.

    Science.gov (United States)

    Rajput, Sudheesh K; Nishchal, Naveen K

    2014-01-20

    We propose a novel nonlinear image-encryption scheme based on a Gerchberg-Saxton (G-S) phase-retrieval algorithm in the Fresnel transform domain. The decryption process can be performed using conventional double random phase encoding (DRPE) architecture. The encryption is realized by applying G-S phase-retrieval algorithm twice, which generates two asymmetric keys from intermediate phases. The asymmetric keys are generated in such a way that decryption is possible optically with a conventional DRPE method. Due to the asymmetric nature of the keys, the proposed encryption process is nonlinear and offers enhanced security. The cryptanalysis has been carried out, which proves the robustness of proposed scheme against known-plaintext, chosen-plaintext, and special attacks. A simple optical setup for decryption has also been suggested. Results of computer simulation support the idea of the proposed cryptosystem.

  19. Optical double image security using random phase fractional Fourier domain encoding and phase-retrieval algorithm

    Science.gov (United States)

    Rajput, Sudheesh K.; Nishchal, Naveen K.

    2017-04-01

    We propose a novel security scheme based on the double random phase fractional domain encoding (DRPE) and modified Gerchberg-Saxton (G-S) phase retrieval algorithm for securing two images simultaneously. Any one of the images to be encrypted is converted into a phase-only image using modified G-S algorithm and this function is used as a key for encrypting another image. The original images are retrieved employing the concept of known-plaintext attack and following the DRPE decryption steps with all correct keys. The proposed scheme is also used for encryption of two color images with the help of convolution theorem and phase-truncated fractional Fourier transform. With some modification, the scheme is extended for simultaneous encryption of gray-scale and color images. As a proof-of-concept, simulation results have been presented for securing two gray-scale images, two color images, and simultaneous gray-scale and color images.

  20. Improved modeling of cloudy-sky actinic flux using satellite cloud retrievals

    Science.gov (United States)

    Ryu, Young-Hee; Hodzic, Alma; Descombes, Gael; Hall, Samuel; Minnis, Patrick; Spangenberg, Douglas; Ullmann, Kirk; Madronich, Sasha

    2017-02-01

    Clouds play a critical role in modulating tropospheric radiation and thus photochemistry. We develop a methodology for calculating the vertical distribution of tropospheric ultraviolet (300-420 nm) actinic fluxes using satellite cloud retrievals and a radiative transfer model. We demonstrate that our approach can accurately reproduce airborne-measured actinic fluxes from the 2013 Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign as a case study. The results show that the actinic flux is reduced below moderately thick clouds with increasing cloud optical depth and can be enhanced by a factor of 2 above clouds. Inside clouds, the actinic flux can be enhanced by up to 2.4 times in the upper part of clouds or reduced up to 10 times in the lower parts of clouds. Our study suggests that the use of satellite-derived actinic fluxes as input to chemistry-transport models can improve the accuracy of photochemistry calculations.

  1. A Seasonally Robust Empirical Algorithm to Retrieve Suspended Sediment Concentrations in the Scheldt River

    Directory of Open Access Journals (Sweden)

    Dries Raymaekers

    2010-08-01

    Full Text Available A seasonally robust algorithm for the retrieval of Suspended Particulate Matter (SPM in the Scheldt River from hyperspectral images is presented. This algorithm can be applied without the need to simultaneously acquire samples (from vessels and pontoons. Especially in dynamic environments such as estuaries, this leads to a large reduction of costs, both in equipment and personnel. The algorithm was established empirically using in situ data of the water-leaving reflectance obtained over the tidal cycle during different seasons and different years. Different bands and band combinations were tested. Strong correlations were obtained for exponential relationships between band ratios and SPM concentration. The best performing relationships are validated using airborne hyperspectral data acquired in June 2005 and October 2007 at different moments in the tidal cycle. A band ratio algorithm (710 nm/596 nm was successfully applied to a hyperspectral AHS image of the Scheldt River to obtain an SPM concentration map.

  2. Research and Application on Web Information Retrieval Based on Improved FP-Growth Algorithm

    Institute of Scientific and Technical Information of China (English)

    JIAO Minghai; YAN Ping; JIANG Huiyan

    2006-01-01

    A kind of single linked lists named aggregative chain is introduced to the algorithm, thus improving the architecture of FP tree. The new FP tree is a one-way tree and only the pointers that point its parent at each node are kept. Route information of different nodes in a same item are compressed into aggregative chains so that the frequent patterns will be produced in aggregative chains without generating node links and conditional pattern bases. An example of Web key words retrieval is given to analyze and verify the frequent pattern algorithm in this paper.

  3. Double color image encryption using iterative phase retrieval algorithm in quaternion gyrator domain.

    Science.gov (United States)

    Shao, Zhuhong; Shu, Huazhong; Wu, Jiasong; Dong, Zhifang; Coatrieux, Gouenou; Coatrieux, Jean Louis

    2014-03-10

    This paper describes a novel algorithm to encrypt double color images into a single undistinguishable image in quaternion gyrator domain. By using an iterative phase retrieval algorithm, the phase masks used for encryption are obtained. Subsequently, the encrypted image is generated via cascaded quaternion gyrator transforms with different rotation angles. The parameters in quaternion gyrator transforms and phases serve as encryption keys. By knowing these keys, the original color images can be fully restituted. Numerical simulations have demonstrated the validity of the proposed encryption system as well as its robustness against loss of data and additive Gaussian noise.

  4. Representativeness errors in comparing chemistry transport and chemistry climate models with satellite UV-Vis tropospheric column retrievals

    NARCIS (Netherlands)

    Boersma, K.F.; Vinken, G.C.M.; Eskes, H.J.

    2016-01-01

    Ultraviolet-visible (UV-Vis) satellite retrievals of trace gas columns of nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO) are useful to test and improve models of atmospheric composition, for data assimilation, air quality hindcasting and forecasting, a

  5. On relaxed averaged alternating reflections (RAAR) algorithm for phase retrieval with structured illumination

    Science.gov (United States)

    Li, Ji; Zhou, Tie

    2017-02-01

    In this paper, we consider the phase retrieval problem with structured illumination, which leads to a pixel-dependent deterministic phase shift term in the physical model. The existence of the phase shift term can ease the numerical algorithm for phase retrieval. The relaxed averaged alternating reflections (RAAR) algorithm is modified to adapt to two or more diffraction patterns, and the modified RAAR algorithm operates in the Fourier domain rather than the space domain. The RAAR is motivated by a linear combination of the reflection projection and projection onto the measurement space, with parameter β trading off the two projections. Although the local convergence of the RAAR algorithm with an initialization within the basin of attraction is proved for 0<β ≤slant 1 , the numerical performance with a random initialization varies with different values of β. Numerical simulations are presented to demonstrate the effectiveness and stability of the algorithm with 0.5<β <1 , compared to the ER (β =0.5 ) method and Douglas-Rachford (β =1 ) method. The numerical global convergence of the RAAR with 0.5<β <1 is also illustrated in our tests.

  6. An algorithm for retrieval of precipitation using microwave humidity sounder channels around 183 GHz

    Science.gov (United States)

    Varma, A. K.; Piyush, D. N.

    2016-05-01

    An algorithm is developed to identify precipitation affected pixels and quantitatively measure the precipitation using Megha-Tropiques humidity sounder (SAPHIR) channels around water vapor absorption line at 183 GHz. Based on observed brightness temperatures at all the six channels of the SAPHIR, a probabilistic rain identification algorithm is proposed. The rain thus identified is subjected to intensive testing using SAPHIR and PR collocated dataset, that showed that false alarm and missing rain is below 0.9 mm/h. Further a radiative transfer simulations supported rain retrieval algorithm is developed that explained a correlation of 0.7 and rmse of 0.81 mm/h. When both precipitation detection and retrieval algorithms are applied the correlation marginally deteriorates but rmse reduces to 0.55 mm/h. Further comparisons are made of monthly, daily and instantaneous rain over different geographical regions from SAPHIR with corresponding rain values from GSMap, TRMM-3B42 V7 and TRMM-TMI/PR, etc. The paper provides details of algorithm development and validation results.

  7. Image Retrieval Approach Based on Intuitive Fuzzy Set Combined with Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    WANG Xiao-yin; XU Wei-hua; HU Chang-zhen

    2009-01-01

    Aiming at shortcomings of traditional image retrieval systems,a new image retrieval approach based on color features of image combining intuitive fuzzy theory with genetic algorithm is proposed.Each image is segmented into a constant number of sub-images in vertical direction.Color features are extracted from every sub-image to get chromosome coding.It is considered that fuzzy membership and intuitive fuzzy hesitancy degree of every pixel's color in image are associated to all the color histogram bins.Certain feature,fuzzy feature and intuitive fuzzy feature of colors in an image,are used together to describe the content of image.Efficient combinations of sub-image are selected according to operation of selecting,crossing and variation.Retrieval resuits are obtained from image matching based on these color feature combinations of sub-images.Tests show that this approach can improve the accuracy of image retrieval in the case of not decreasing the speed of image retrieval.Its mean precision is above 80%.

  8. Adaption of the MODIS aerosol retrieval algorithm by airborne spectral surface reflectance measurements over urban areas: a case study

    Directory of Open Access Journals (Sweden)

    E. Jäkel

    2015-07-01

    Full Text Available MODIS retrievals of the aerosol optical depth (AOD are biased over urban areas, where surface reflectance is not well characterized. Since the operational MODIS aerosol retrieval for dark targets assumes fixed spectral slopes to calculate the surface reflectance at 0.47 μm, the algorithm may fail in urban areas with different spectral characteristics of the surface reflectance. To investigate this bias we have implemented variable spectral slopes into the operational MODIS aerosol algorithms of Collection 5 (C5 and C6. The variation of slopes is based on airborne measurements of surface reflectances over the city of Zhongshan, China. AOD retrieval results of the operational and the modified algorithms were compared for a MODIS measurement over Zhongshan. For this case slightly lower AOD values were derived using the modified algorithm. The retrieval methods were additionally applied to MODIS data of the Beijing area for a period between 2010–2014 when also AERONET data were available. A reduction of the differences between the AOD retrieved using the modified C5 algorithm and AERONET was found, whereby the mean difference from 0.31 ± 0.11 for the operational C5 and 0.18 ± 0.12 for the operational C6 where reduced to a mean difference of 0.09 ± 0.18 by using the modified C5 retrieval. Furthermore, the sensitivity of the MODIS AOD retrieval for several surface types was investigated. Radiative transfer simulations were performed to model reflectances at top of atmosphere for predefined aerosol properties. The reflectances were used as input for the retrieval methods. It is shown that the operational MODIS AOD retrieval over land reproduces the AOD reference input of 0.85 for dark surface types [retrieved AOD = 0.87 (C5]. An overestimation of AOD = 0.99 is found for urban surfaces, whereby the modified C5 algorithm shows a good performance with a retrieved value of AOD = 0.86.

  9. A Prototype Algorithm for Land Surface Temperature Retrieval from Sentinel-3 Mission

    Science.gov (United States)

    Sobrino, Jose A.; Jimenez-Munoz, Juan C.; Soria, Guillem; Brockmann, Carsten; Ruescas, Ana; Danne, Olaf; North, Peter; Phillipe, Pierre; Berger, Michel; Merchant, Chris; Ghent, Darren; Remedios, John

    2015-12-01

    In this work we present a prototype algorithm to retrieve Land Surface Temperature (LST) from OLCI and SLSTR instruments on board Sentinel-3 platform, which was developed in the framework of the SEN4LST project. For this purpose, data acquired with the ENVISAT MERIS and AATSR instruments are used as a benchmark. The objective is to improve the LST standard product (level 2) currently derived from the single AATSR instrument taking advantages of the improved characteristics of the future OLCI and SLSTR instruments. Hence, the high spectral resolution of OLCI instrument and the dual-view and thermal bands available in the SLSTR instruments have the potential to improve the characterization of the atmosphere and therefore to improve the atmospheric correction and cloud mask. Bands in the solar domain available in both instruments allow the retrieval of the surface emissivity, being a key input to the LST algorithm. Pairs of MERIS/AATSR are processed over different sites and validated with in situ measurements using the LST processor included in the BEAM software. Results showed that the proposed LST algorithm improves LST retrievals of the standard level-2 product.

  10. Synergetic radar and lidar algorithm for the retrieval of radiative and microphysical properties in ice clouds

    Science.gov (United States)

    Tinel, Claire; Testud, Jacques; Protat, Alain; Pelon, Jacques R.

    2003-04-01

    To appreciate the radiative impact of clouds in the dynamics of the global atmosphere, it is important to deploy from space, from aircraft, or from ground, instruments able to describe the cloud layering and to document the cloud characteristics (namely liquid and/or ice water content, and the effective particle radius). In the framework of EarthCARE (ESA), that plans to associate a cloud radar and a lidar on the same spatial platform, RALI (RAdar-LIdar) airborne system is an interesting demonstrator. RALI combines the 95 GHz radar of the CETP and the 0.5 μm wavelength backscattering lidar of the SA. In order to derive the radiative and microphysical properties of clouds, a synergetic algorithm has been developed. It combines the apparent backscatter coefficient, βa, from the lidar and the apparent reflectivity, Za, from the radar to infer properties of the particle size distribution. The principle of this algorithm is to apply in parallel the Hitschfeld-Bordan algorithm to the radar and the Klett algorithm to the lidar. Taken separately, these two algorithms are unstable, but by considering a mutual constraint, it is shown that a stable solution can be established. This solution formulates the retrieval of the true reflectivity and backscattering coefficient, to access microphysical and radiative parameters of clouds. This algorithm allows also to retrieve the variable N0* parameter, which is a normalization parameter of the particle size distribution. This synergetic algorithm has been tested with simulated cases, and results of the algorithm applied on real data are validated by microphysical in-situ measurements.

  11. Improvement and Simulation of an Autonomous Time Synchronization Algorithm for a Layered Satellite Constellation

    Directory of Open Access Journals (Sweden)

    Feijiang Huang

    2013-01-01

    Full Text Available Autonomous time synchronization for satellite constellations is a key technology to establish a constellation system time without the use of a ground station. The characteristics of satellite visibility time for layered satellite constellations containing geostationary earth orbit (GEO, inclined geosynchronous orbit (IGSO, and medium earth orbit (MEO satellites are simulated by establishing a visible satellite model. Based on the satellite visible simulation results for a layered constellation, this study investigates the autonomous time synchronization algorithm that corresponds to the layered constellation structure, analyzes the main error of the time synchronization algorithm, and proposes methods to improve the characteristics of satellite movement in the constellation. This study uses an improved two-way time synchronization algorithm for autonomous time synchronization in the GEO-MEO satellite layer of a layered satellite constellation. The simulation results show that in a condition with simulation errors, the time synchronization precision of this improved algorithm can be controlled within 5 ns and used in high-precision autonomous time synchronization between layered satellite constellations.

  12. A Synergic Algorithm for Retrieval of Aerosol Optical Depth over Land

    Institute of Scientific and Technical Information of China (English)

    GUO Jianping; XUE Yong; CAO Chunxiang; ZHANG Hao; GUANG Jie; ZHANG Xiaoye; LI Xiaowen

    2009-01-01

    In this paper,a novel algorithm for aerosol optical depth(AOD) retrieval with a 1 km spatial resolution over land is presented using the Advanced Along Track Scanning Radiometer (AATSR) dual-view capability at 0.55,0.66 and 0.87 μm,in combination with the Bi-directional Reflectance Distribution Function (BRDF) model,a product of the Moderate Resolution Imaging Spectroradiometer (MODIS).The BRDF characteristics of the land surface,i.e.prior input parameters for this algorithm,are computed by extracting the geometrical information from AATSR and reducing the kernels from the MODIS BRDF/Albedo Model Parameters Product.Finally,AOD,with a 1 km resolution at 0.55,0.66 and 0.87 μm for the forward and nadir views of AATSR,can be simultaneously obtained.Extensive validations of AOD derived from AATSR during the period from August 2005 to July 2006 in Beijing and its surrounding area,against in-situ AErosol RObotic NETwork (AERONET) measurements,were performed.The AOD difference between the retrievals from the forward and nadir views of AATSR was less than 5.72%,1.9% and 13.7%,respectively.Meanwhile,it was found that the AATSR retrievals using the synergic algorithm developed in this paper are more favorable than those by assuming a Lambert surface,for the coefficient of determination between AATSR derived AOD and AERONET mearured AOD,decreased by 15.5% and 18.5%,compared to those derived by the synergic algorithm.This further suggests that the synergic algorithm can be potentially used in climate change and air quality monitoring.

  13. Operational retrieval of Asian sand and dust storm from FY-2C geostationary meteorological satellite and its application to real time forecast in Asia

    Directory of Open Access Journals (Sweden)

    T. Niu

    2008-03-01

    Full Text Available This paper describes an operational retrieval algorithm for the sand/dust storm (SDS from FY-2C/S-VISSR (Stretched-Visible and Infrared Spin-Scan Radiometer developed at the National Satellite Meteorological Center (NSMC of China. This algorithm, called Dust Retrieval Algorithm based on Geostationary Imager (DRAGI, is based on the optical and radiative physical properties of SDS in mid-infrared and thermal infrared spectral regions as well as the observation of all bands in the geostationary imager, which include the Brightness Temperature Difference (BTD in split window channels, Infrared Difference Dust Index (IDDI and the ratio of middle infrared reflectance to visible reflectance. It also combines the visible and water vapor bands observation of the geostationary imager to identify the dust clouds from the surface targets and meteorological clouds. The output product is validated by and related to other dust aerosol observations such as the synoptic weather reports, surface visibility, aerosol optical depth (AOD and ground-based PM10 observations. Using the SDS-IDD product and a data assimilation scheme, the dust forecast model CUACE/Dust achieved a substantial improvement to the SDS predictions in spring 2006.

  14. Source mass eruption rate retrieved from satellite-based data using statistical modelling

    Science.gov (United States)

    Gouhier, Mathieu; Guillin, Arnaud; Azzaoui, Nourddine; Eychenne, Julia; Valade, Sébastien

    2015-04-01

    Ash clouds emitted during volcanic eruptions have long been recognized as a major hazard likely to have dramatic consequences on aircrafts, environment and people. Thus, the International Civil Aviation Organization (ICAO) established nine Volcanic Ash Advisory Centers (VAACs) around the world, whose mission is to forecast the location and concentration of ash clouds over hours to days, using volcanic ash transport and dispersion models (VATDs). Those models use input parameters such as plume height (PH), particle size distribution (PSD), and mass eruption rate (MER), the latter being a key parameter as it directly controls the amount of ash injected into the atmosphere. The MER can be obtained rather accurately from detailed ground deposit studies, but this method does not match the operational requirements in case of a volcanic crisis. Thus, VAACs use empirical laws to determine the MER from the estimation of the plume height. In some cases, this method can be difficult to apply, either because plume height data are not available or because uncertainties related to this method are too large. We propose here an alternative method based on the utilization of satellite data to assess the MER at the source, during explosive eruptions. Satellite-based techniques allow fine ash cloud loading to be quantitatively retrieved far from the source vent. Those measurements can be carried out in a systematic and real-time fashion using geostationary satellite, in particular. We tested here the relationship likely to exist between the amount of fine ash dispersed in the atmosphere and of coarser tephra deposited on the ground. The sum of both contributions yielding an estimate of the MER. For this purpose we examined 19 eruptions (of known duration) in detail for which both (i) the amount of fine ash dispersed in the atmosphere, and (ii) the mass of tephra deposited on the ground have been estimated and published. We combined these data with contextual information that may

  15. Microphysical properties and distribution retrieval with a variable base point algorithm

    Science.gov (United States)

    Osterloh, Lukas; Böckmann, Christine

    2009-09-01

    We present a new algorithm for the retrieval of the volume distribution - and thus, other relevant microphysical properties such as the effective radius - of stratospheric and tropospheric aerosols from multiwavelength lidar data. We consider the basic equation as a linear ill-posed problem and solve the linear system derived from spline collocation. Starting from here, algorithmical improvements for the inversion process are proposed. While a standard approach consisting of spline collocation and a regularization method such as truncated singular value decomposition or Tikhonov-Philips regularization proves sufficient in some cases, that kind of algorithm is not suitable for a more general case; the base points of the spline collocation take a key role here. Indeed, there is a direct connection between the number and position of the base points on the solution, as the problem of the correct regularization parameter - which is represented here by both location and number of base points - and its implications on over- or underregularization of the solution have to be investigated. Here, we present an algorithm that makes use of the fact that smoother areas of the solution require less base points in the vicinity for a proper reconstruction, combined with a Padé-type iterative regularization method. The algorithm starts with equidistant base points, then moves these base points during the calculation away from the smoother areas of the solution. This algorithm proved to work very well in many different simulation cases. Different weight functions for the base point shift are investigated, leading to slightly different results. Also, an improvement on this algoritm is proposed which, in addition to the position of the base points, also actively controls the actual number of base points, as solutions that more smooth in a global sense require less base points. Finally, we also take a look at how this new algorithm can also help us in simultaneously retrieving the

  16. Practical split-window algorithm for retrieving land surface temperature over agricultural areas from ASTER data

    Science.gov (United States)

    Wang, Songhan; He, Longhua

    2014-01-01

    A practical split-window algorithm which involves two parameters (transmittance and emissivity) utilized to retrieve land-surface temperature over agricultural areas from the Advanced Spaceborne Thermal Emission and Reflection Radiometer data is presented. First, by calculating the relationship between thermal radiation intensity and temperature, the Planck function is simplified using exponential function which is applied to deduce the split-window algorithm. Second, how to obtain transmittance from water vapor content and the method for estimating emissivity using normalized difference vegetation index are discussed in detail. Sensitivity analysis demonstrates that the algorithm is not sensitive to these two parameters. Finally, a standard atmospheric simulation method has been used to validate the proposed algorithm, and comparison between the algorithm and the prior study has been carried out. The results indicate that the average accuracy is 0.32 K for the case without error in both transmittance and emissivity, which is better than the prior algorithm. The accuracy is also 0.32 K when the transmittance is computed from the water content by piecewise cubic polynomial fit. The accuracy is about 0.30 K˜0.33 K corresponding to different Pv (Pv is the proportion of vegetation) values, which indicates that this algorithm is suitable for different land surface types over agricultural areas.

  17. An inversion method for retrieving soil moisture information from satellite altimetry observations

    Science.gov (United States)

    Uebbing, Bernd; Forootan, Ehsan; Kusche, Jürgen; Braakmann-Folgmann, Anne

    2016-04-01

    Soil moisture represents an important component of the terrestrial water cycle that controls., evapotranspiration and vegetation growth. Consequently, knowledge on soil moisture variability is essential to understand the interactions between land and atmosphere. Yet, terrestrial measurements are sparse and their information content is limited due to the large spatial variability of soil moisture. Therefore, over the last two decades, several active and passive radar and satellite missions such as ERS/SCAT, AMSR, SMOS or SMAP have been providing backscatter information that can be used to estimate surface conditions including soil moisture which is proportional to the dielectric constant of the upper (few cm) soil layers . Another source of soil moisture information are satellite radar altimeters, originally designed to measure sea surface height over the oceans. Measurements of Jason-1/2 (Ku- and C-Band) or Envisat (Ku- and S-Band) nadir radar backscatter provide high-resolution along-track information (~ 300m along-track resolution) on backscatter every ~10 days (Jason-1/2) or ~35 days (Envisat). Recent studies found good correlation between backscatter and soil moisture in upper layers, especially in arid and semi-arid regions, indicating the potential of satellite altimetry both to reconstruct and to monitor soil moisture variability. However, measuring soil moisture using altimetry has some drawbacks that include: (1) the noisy behavior of the altimetry-derived backscatter (due to e.g., existence of surface water in the radar foot-print), (2) the strong assumptions for converting altimetry backscatters to the soil moisture storage changes, and (3) the need for interpolating between the tracks. In this study, we suggest a new inversion framework that allows to retrieve soil moisture information from along-track Jason-2 and Envisat satellite altimetry data, and we test this scheme over the Australian arid and semi-arid regions. Our method consists of: (i

  18. Next Generation Aura-OMI SO2 Retrieval Algorithm: Introduction and Implementation Status

    Science.gov (United States)

    Li, Can; Joiner, Joanna; Krotkov, Nickolay A.; Bhartia, Pawan K.

    2014-01-01

    We introduce our next generation algorithm to retrieve SO2 using radiance measurements from the Aura Ozone Monitoring Instrument (OMI). We employ a principal component analysis technique to analyze OMI radiance spectral in 310.5-340 nm acquired over regions with no significant SO2. The resulting principal components (PCs) capture radiance variability caused by both physical processes (e.g., Rayleigh and Raman scattering, and ozone absorption) and measurement artifacts, enabling us to account for these various interferences in SO2 retrievals. By fitting these PCs along with SO2 Jacobians calculated with a radiative transfer model to OMI-measured radiance spectra, we directly estimate SO2 vertical column density in one step. As compared with the previous generation operational OMSO2 PBL (Planetary Boundary Layer) SO2 product, our new algorithm greatly reduces unphysical biases and decreases the noise by a factor of two, providing greater sensitivity to anthropogenic emissions. The new algorithm is fast, eliminates the need for instrument-specific radiance correction schemes, and can be easily adapted to other sensors. These attributes make it a promising technique for producing long-term, consistent SO2 records for air quality and climate research. We have operationally implemented this new algorithm on OMI SIPS for producing the new generation standard OMI SO2 products.

  19. A DISTRIBUTED QOS ROUTING BASED ON ANT ALGORITHM FOR LEO SATELLITE NETWORK

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Low Earth Orbit (LEO) satellites provide short round-trip delays and are becoming increasingly important. One of the challenges in LEO satellite networks is the development of specialized and efficient routing algorithms. To satisfy the QoS requirements of multimedia applications, satellite routing protocols should consider handovers and minimize their effect on the active connections. A distributed QoS routing scheme based on heuristic ant algorithm is proposed for satisfying delay bound and avoiding link congestion. Simulation results show that the call blocking probabilities of this algorithm are less than that of Shortest Path First (SPF) with different delay bound.

  20. Advancing of Land Surface Temperature Retrieval Using Extreme Learning Machine and Spatio-Temporal Adaptive Data Fusion Algorithm

    Directory of Open Access Journals (Sweden)

    Yang Bai

    2015-04-01

    Full Text Available As a critical variable to characterize the biophysical processes in ecological environment, and as a key indicator in the surface energy balance, evapotranspiration and urban heat islands, Land Surface Temperature (LST retrieved from Thermal Infra-Red (TIR images at both high temporal and spatial resolution is in urgent need. However, due to the limitations of the existing satellite sensors, there is no earth observation which can obtain TIR at detailed spatial- and temporal-resolution simultaneously. Thus, several attempts of image fusion by blending the TIR data from high temporal resolution sensor with data from high spatial resolution sensor have been studied. This paper presents a novel data fusion method by integrating image fusion and spatio-temporal fusion techniques, for deriving LST datasets at 30 m spatial resolution from daily MODIS image and Landsat ETM+ images. The Landsat ETM+ TIR data were firstly enhanced based on extreme learning machine (ELM algorithm using neural network regression model, from 60 m to 30 m resolution. Then, the MODIS LST and enhanced Landsat ETM+ TIR data were fused by Spatio-temporal Adaptive Data Fusion Algorithm for Temperature mapping (SADFAT in order to derive high resolution synthetic data. The synthetic images were evaluated for both testing and simulated satellite images. The average difference (AD and absolute average difference (AAD are smaller than 1.7 K, where the correlation coefficient (CC and root-mean-square error (RMSE are 0.755 and 1.824, respectively, showing that the proposed method enhances the spatial resolution of the predicted LST images and preserves the spectral information at the same time.

  1. On the suitability of global algorithms for the retrieval of SST from the north Indian Ocean using NOAA/AVHRR

    Digital Repository Service at National Institute of Oceanography (India)

    Shenoi, S.S.C.

    The errors associated with the SST retrievals from the north Indian Ocean, using global multichannel sea surface temperature (MCSST), nonlinear sea surface temperature (NLSST), and Pathfinder sea surface temperature (PFSST) algorithms are analysed...

  2. An Empirical Algorithm for Wave Retrieval from Co-Polarization X-Band SAR Imagery

    Directory of Open Access Journals (Sweden)

    Weizeng Shao

    2017-07-01

    Full Text Available In this study, we proposed an empirical algorithm for significant wave height (SWH retrieval from TerraSAR-X/TanDEM (TS-X/TD-X X-band synthetic aperture radar (SAR co-polarization (vertical-vertical (VV and horizontal-horizontal (HH images. As the existing empirical algorithm at X-band, i.e., XWAVE, is applied for wave retrieval from HH-polarization TS-X/TD-X image, polarization ratio (PR has to be used for inverting wind speed, which is treated as an input in XWAVE. Wind speed encounters saturation in tropical cyclone. In our work, wind speed is replaced by normalized radar cross section (NRCS to avoiding using SAR-derived wind speed, which does not work in high winds, and the empirical algorithm can be conveniently implemented without converting NRCS in HH-polarization to NRCS in VV-polarization by using X-band PR. A total of 120 TS-X/TD-X images, 60 in VV-polarization and 60 in HH-polarization, with homogenous wave patterns, and the coincide significant wave height data from European Centre for Medium-Range Weather Forecasts (ECMWF reanalysis field at a 0.125° grid were collected as a dataset for tuning the algorithm. The range of SWH is from 0 to 7 m. We then applied the algorithm to 24 VV and 21 HH additional SAR images to extract SWH at locations of 30 National Oceanic and Atmospheric Administration (NOAA National Data Buoy Center (NDBC buoys. It is found that the algorithm performs well with a SWH stander deviation (STD of about 0.5 m for both VV and HH polarization TS-X/TD-X images. For large wave validation (SWH 6–7 m, we applied the empirical algorithm to a tropical cyclone Sandy TD-X image acquired in 2012, and obtained good result with a SWH STD of 0.3 m. We concluded that the proposed empirical algorithm works for wave retrieval from TS-X/TD-X image in co-polarization without external sea surface wind information.

  3. MISR Dark Water aerosol retrievals: operational algorithm sensitivity to particle non-sphericity

    Directory of Open Access Journals (Sweden)

    O. V. Kalashnikova

    2013-08-01

    Full Text Available The aim of this study is to theoretically investigate the sensitivity of the Multi-angle Imaging SpectroRadiometer (MISR operational (version 22 Dark Water retrieval algorithm to aerosol non-sphericity over the global oceans under actual observing conditions, accounting for current algorithm assumptions. Non-spherical (dust aerosol models, which were introduced in version 16 of the MISR aerosol product, improved the quality and coverage of retrievals in dusty regions. Due to the sensitivity of the retrieval to the presence of non-spherical aerosols, the MISR aerosol product has been successfully used to track the location and evolution of mineral dust plumes from the Sahara across the Atlantic, for example. However, the MISR global non-spherical aerosol optical depth (AOD fraction product has been found to have several climatological artifacts superimposed on valid detections of mineral dust, including high non-spherical fraction in the Southern Ocean and seasonally variable bands of high non-sphericity. In this paper we introduce a formal approach to examine the ability of the operational MISR Dark Water algorithm to distinguish among various spherical and non-spherical particles as a function of the variable MISR viewing geometry. We demonstrate the following under the criteria currently implemented: (1 Dark Water retrieval sensitivity to particle non-sphericity decreases for AOD below about 0.1 primarily due to an unnecessarily large lower bound imposed on the uncertainty in MISR observations at low light levels, and improves when this lower bound is removed; (2 Dark Water retrievals are able to distinguish between the spherical and non-spherical particles currently used for all MISR viewing geometries when the AOD exceeds 0.1; (3 the sensitivity of the MISR retrievals to aerosol non-sphericity varies in a complex way that depends on the sampling of the scattering phase function and the contribution from multiple scattering; and (4 non

  4. MISR Dark Water aerosol retrievals: operational algorithm sensitivity to particle non-sphericity

    Directory of Open Access Journals (Sweden)

    O. V. Kalashnikova

    2013-02-01

    Full Text Available The aim of this study is to theoretically investigate the sensitivity of the Multi-angle Imaging SpectroRadiometer (MISR operational (Version 22 Dark Water retrieval algorithm to aerosol non-sphericity over the global oceans under actual observing conditions, accounting for current algorithm assumptions. Non-spherical (dust aerosol models, which were introduced in Version 16 of the MISR aerosol product, improved the quality and coverage of retrievals in dusty regions. Due to the sensitivity of the retrieval to the presence of non-spherical aerosols, the MISR aerosol product has been successfully used to track the location and evolution of mineral dust plumes from the Sahara across the Atlantic, for example. However, the MISR global non-spherical aerosol optical depth (AOD fraction product has been found to have several climatological artifacts superimposed on valid detections of mineral dust, including high non-spherical fraction in the Southern Ocean and seasonally variable bands of high non-sphericity. In this paper we introduce a formal approach to examine the ability of the operational MISR Dark Water algorithm to distinguish among various spherical and non-spherical particles as a function of the variable MISR viewing geometry. We demonstrate that under the criteria currently implemented: (1 Dark Water retrieval sensitivity to particle non-sphericity decreases for AOD below about 0.1 primarily due to an unnecessarily large lower bound imposed on the uncertainty in MISR observations at low light levels, and improves when this lower bound is removed; (2 Dark Water retrievals are able to distinguish between the spherical and non-spherical particles currently used for all MISR viewing geometries when the AOD exceeds 0.1; (3 the sensitivity of the MISR retrievals to aerosol non-sphericity varies in a complex way that depends on the sampling of the scattering phase function and the contribution from multiple scattering; and (4 non

  5. Simulation of the satellite radar altimeter sea ice thickness retrieval uncertainty

    Directory of Open Access Journals (Sweden)

    R. T. Tonboe

    2009-07-01

    Full Text Available Although it is well known that radar waves penetrate into snow and sea ice, the exact mechanisms for radar-altimeter scattering and its link to the depth of the effective scattering surface from sea ice are still unknown. Previously proposed mechanisms linked the snow ice interface, i.e. the dominating scattering horizon, directly with the depth of the effective scattering surface. However, simulations using a multilayer radar scattering model show that the effective scattering surface is affected by snow-cover and ice properties. With the coming Cryosat-2 (planned launch 2009 satellite radar altimeter it is proposed that sea ice thickness can be derived by measuring its freeboard. In this study we evaluate the radar altimeter sea ice thickness retrieval uncertainty in terms of floe buoyancy, radar penetration and ice type distribution using both a scattering model and ''Archimedes' principle''. The effect of the snow cover on the floe buoyancy and the radar penetration and on the ice cover spatial and temporal variability is assessed from field campaign measurements in the Arctic and Antarctic. In addition to these well known uncertainties we use high resolution RADARSAT SAR data to simulate errors due to the variability of the effective scattering surface as a result of the sub-footprint spatial backscatter and elevation distribution sometimes called preferential sampling. In particular in areas where ridges represent a significant part of the ice volume (e.g. the Lincoln Sea the simulated altimeter thickness estimate is lower than the real average footprint thickness. This means that the errors are large, yet manageable if the relevant quantities are known a priori. A discussion of the radar altimeter ice thickness retrieval uncertainties concludes the paper.

  6. Simulation of the satellite radar altimeter sea ice thickness retrieval uncertainty

    Science.gov (United States)

    Tonboe, R. T.; Pedersen, L. T.; Haas, C.

    2009-07-01

    Although it is well known that radar waves penetrate into snow and sea ice, the exact mechanisms for radar-altimeter scattering and its link to the depth of the effective scattering surface from sea ice are still unknown. Previously proposed mechanisms linked the snow ice interface, i.e. the dominating scattering horizon, directly with the depth of the effective scattering surface. However, simulations using a multilayer radar scattering model show that the effective scattering surface is affected by snow-cover and ice properties. With the coming Cryosat-2 (planned launch 2009) satellite radar altimeter it is proposed that sea ice thickness can be derived by measuring its freeboard. In this study we evaluate the radar altimeter sea ice thickness retrieval uncertainty in terms of floe buoyancy, radar penetration and ice type distribution using both a scattering model and ''Archimedes' principle''. The effect of the snow cover on the floe buoyancy and the radar penetration and on the ice cover spatial and temporal variability is assessed from field campaign measurements in the Arctic and Antarctic. In addition to these well known uncertainties we use high resolution RADARSAT SAR data to simulate errors due to the variability of the effective scattering surface as a result of the sub-footprint spatial backscatter and elevation distribution sometimes called preferential sampling. In particular in areas where ridges represent a significant part of the ice volume (e.g. the Lincoln Sea) the simulated altimeter thickness estimate is lower than the real average footprint thickness. This means that the errors are large, yet manageable if the relevant quantities are known a priori. A discussion of the radar altimeter ice thickness retrieval uncertainties concludes the paper.

  7. Three years of greenhouse gas column-averaged dry air mole fractions retrieved from satellite – Part 1: Carbon dioxide

    Directory of Open Access Journals (Sweden)

    O. Schneising

    2008-07-01

    Full Text Available Carbon dioxide (CO2 and methane (CH4 are the two most important anthropogenic greenhouse gases. SCIAMACHY on ENVISAT is the first satellite instrument whose measurements are sensitive to concentration changes of the two gases at all altitude levels down to the Earth's surface where the source/sink signals are largest. We have processed three years (2003–2005 of SCIAMACHY near-infrared nadir measurements to simultaneously retrieve vertical columns of CO2 (from the 1.58 μm absorption band, CH4 (1.66 μm and oxygen (O2 A-band at 0.76 μm using the scientific retrieval algorithm WFM-DOAS. We show that the latest version of WFM-DOAS, version 1.0, which is used for this study, has been significantly improved with respect to its accuracy compared to the previous versions while essentially maintaining its high processing speed (~1 min per orbit, corresponding to ~6000 single measurements, and per gas on a standard PC. The greenhouse gas columns are converted to dry air column-averaged mole fractions, denoted XCO2 (in ppm and XCH4 (in ppb, by dividing the greenhouse gas columns by simultaneously retrieved dry air columns. For XCO2 dry air columns are obtained from the retrieved O2 columns. For XCH4 dry air columns are obtained from the retrieved CO2 columns because of better cancellation of light path related errors compared to using O2 columns retrieved from the spectrally distant O2 A-band. Here we focus on a discussion of the XCO2 data set. The XCH4 data set is discussed in a separate paper (Part 2. In order to assess the quality of the retrieved XCO2 we present comparisons with Fourier Transform Spectroscopy (FTS XCO2 measurements at two northern hemispheric mid-latitude ground stations. To assess the quality globally, we present detailed comparisons with

  8. Near-Real Time Satellite-Retrieved Cloud and Surface Properties for Weather and Aviation Safety Applications

    Science.gov (United States)

    Minnis, Patrick; Smith, William L., Jr.; Bedka, Kristopher M.; Nguyen, Louis; Palikonda, Rabindra; Hong, Gang; Trepte, Qing Z.; Chee, Thad; Scarino, Benjamin; Spangenberg, Douglas A.; Sun-Mack, Szedung; Fleeger, Cecilia; Ayers, J. Kirk; Chang, Fu-Lung; Heck, Patrick M.

    2014-01-01

    Cloud properties determined from satellite imager radiances provide a valuable source of information for nowcasting and weather forecasting. In recent years, it has been shown that assimilation of cloud top temperature, optical depth, and total water path can increase the accuracies of weather analyses and forecasts. Aircraft icing conditions can be accurately diagnosed in near-­-real time (NRT) retrievals of cloud effective particle size, phase, and water path, providing valuable data for pilots. NRT retrievals of surface skin temperature can also be assimilated in numerical weather prediction models to provide more accurate representations of solar heating and longwave cooling at the surface, where convective initiation. These and other applications are being exploited more frequently as the value of NRT cloud data become recognized. At NASA Langley, cloud properties and surface skin temperature are being retrieved in near-­-real time globally from both geostationary (GEO) and low-­-earth orbiting (LEO) satellite imagers for weather model assimilation and nowcasting for hazards such as aircraft icing. Cloud data from GEO satellites over North America are disseminated through NCEP, while those data and global LEO and GEO retrievals are disseminated from a Langley website. This paper presents an overview of the various available datasets, provides examples of their application, and discusses the use of the various datasets downstream. Future challenges and areas of improvement are also presented.

  9. Single-intensity-recording optical encryption technique based on phase retrieval algorithm and QR code

    Science.gov (United States)

    Wang, Zhi-peng; Zhang, Shuai; Liu, Hong-zhao; Qin, Yi

    2014-12-01

    Based on phase retrieval algorithm and QR code, a new optical encryption technology that only needs to record one intensity distribution is proposed. In this encryption process, firstly, the QR code is generated from the information to be encrypted; and then the generated QR code is placed in the input plane of 4-f system to have a double random phase encryption. For only one intensity distribution in the output plane is recorded as the ciphertext, the encryption process is greatly simplified. In the decryption process, the corresponding QR code is retrieved using phase retrieval algorithm. A priori information about QR code is used as support constraint in the input plane, which helps solve the stagnation problem. The original information can be recovered without distortion by scanning the QR code. The encryption process can be implemented either optically or digitally, and the decryption process uses digital method. In addition, the security of the proposed optical encryption technology is analyzed. Theoretical analysis and computer simulations show that this optical encryption system is invulnerable to various attacks, and suitable for harsh transmission conditions.

  10. Efficient Retrieval of Text for Biomedical Domain using Expectation Maximization Algorithm

    Directory of Open Access Journals (Sweden)

    Sumit Vashishtha

    2011-11-01

    Full Text Available Data mining, a branch of computer science [1], is the process of extracting patterns from large data sets by combining methods from statistics and artificial intelligence with database management. Data mining is seen as an increasingly important tool by modern business to transform data into business intelligence giving an informational advantage. Biomedical text retrieval refers to text retrieval techniques applied to biomedical resources and literature available of the biomedical and molecular biology domain. The volume of published biomedical research, and therefore the underlying biomedical knowledge base, is expanding at an increasing rate. Biomedical text retrieval is a way to aid researchers in coping with information overload. By discovering predictive relationships between different pieces of extracted data, data-mining algorithms can be used to improve the accuracy of information extraction. However, textual variation due to typos, abbreviations, and other sources can prevent the productive discovery and utilization of hard-matching rules. Recent methods of soft clustering can exploit predictive relationships in textual data. This paper presents a technique for using soft clustering data mining algorithm to increase the accuracy of biomedical text extraction. Experimental results demonstrate that this approach improves text extraction more effectively that hard keyword matching rules.

  11. Influence of aerosols and surface reflectance on satellite NO2 retrieval: seasonal and spatial characteristics and implications for NOx emission constraints

    Science.gov (United States)

    Lin, J.-T.; Liu, M.-Y.; Xin, J.-Y.; Boersma, K. F.; Spurr, R.; Martin, R.; Zhang, Q.

    2015-04-01

    Satellite retrievals of vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) normally do not explicitly account for aerosol optical effects and surface reflectance anisotropy that vary with space and time. Here, we conduct an improved retrieval of NO2 VCDs over China, called the POMINO algorithm, based on measurements from the Ozone Monitoring Instrument (OMI), and we test the importance of a number of aerosol and surface reflectance treatments in this algorithm. POMINO uses a parallelized LIDORT-driven AMFv6 package to derive tropospheric air mass factors via pixel-specific radiative transfer calculations with no look-up tables, taking slant column densities from DOMINO v2. Prerequisite cloud optical properties are derived from a dedicated cloud retrieval process that is fully consistent with the main NO2 retrieval. Aerosol optical properties are taken from GEOS-Chem simulations constrained by MODIS AOD values. MODIS bi-directional reflectance distribution function (BRDF) data are used for surface reflectance over land. For the present analysis, POMINO level-2 data for 2012 are aggregated into monthly means on a 0.25° long. × 0.25° lat. grid. POMINO-retrieved annual mean NO2 VCDs vary from 15-25 × 1015 cm-2 over the polluted North China Plain (NCP) to below 1015 cm-2 over much of west China. The subsequently-constrained Chinese annual anthropogenic emissions are 9.05 TgN yr-1, an increase from 2006 (Lin, 2012) by about 19%. Replacing the MODIS BRDF data with the OMLER v1 monthly climatological albedo data affects NO2 VCDs by up to 40% for certain locations and seasons. The effect on constrained NOx emissions is small. Excluding aerosol information from the retrieval process (this is the traditional "implicit" treatment) enhances annual mean NO2 VCDs by 15-40% over much of east China. Seasonally, NO2 VCDs are reduced by 10-20% over parts of the NCP in spring and over north China in winter, despite the general enhancements in summer and fall

  12. Performance of TCP Vegas, Bic and Reno Congestion Control Algorithms on Iridium Satellite Constellations

    Directory of Open Access Journals (Sweden)

    M.Nirmala

    2012-11-01

    Full Text Available Satellite networking is different from wired or wireless networks. The behavior and the performance of TCP/IP in normal wireless network as well as in wired network are different from one another. The TCP/IP protocol was not designed to perform well over high-latency or noisy channels so its performance over satellite networks are totally different. Each satellite networks/constellations have different properties. The deployment height, motion, direction, link capacity – all differ from one satellite constellations to another. So, certainly the behavior of TCP/IP will considerably differ from one satellite constellations than another.The Performance of three different TCP Congestion algorithms, Vegas, Reno and Bic are taken for evaluation on the simulated satellite network Iridium and the performance of the three algorithms under the satellites constellation is measured using suitable metrics. It is observed that, irrespective of the high end to end delay, the behavior of TCP/IP under Satellite network is somewhat resembling a high latency wired network. TCP under satellite network is not like that of a mobile ADHOC network. The observation resulted that the overall performance of Vegas was good in Iridium constellations. These reasons should be explored for designing a better congestion control algorithm exclusively for Satellite Networks.

  13. Validating Microwave-Based Satellite Rain Rate Retrievals Over TRMM Ground Validation Sites

    Science.gov (United States)

    Fisher, B. L.; Wolff, D. B.

    2008-12-01

    Multi-channel, passive microwave instruments are commonly used today to probe the structure of rain systems and to estimate surface rainfall from space. Until the advent of meteorological satellites and the development of remote sensing techniques for measuring precipitation from space, there was no observational system capable of providing accurate estimates of surface precipitation on global scales. Since the early 1970s, microwave measurements from satellites have provided quantitative estimates of surface rainfall by observing the emission and scattering processes due to the existence of clouds and precipitation in the atmosphere. This study assesses the relative performance of microwave precipitation estimates from seven polar-orbiting satellites and the TRMM TMI using four years (2003-2006) of instantaneous radar rain estimates obtained from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The seven polar orbiters include three different sensor types: SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), and AMSR-E. The TMI aboard the TRMM satellite flies in a sun asynchronous orbit between 35 S and 35 N latitudes. The rain information from these satellites are combined and used to generate several multi-satellite rain products, namely the Goddard TRMM Multi-satellite Precipitation Analysis (TMPA), NOAA's CPC Morphing Technique (CMORPH) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). Instantaneous rain rates derived from each sensor were matched to the GV estimates in time and space at a resolution of 0.25 degrees. The study evaluates the measurement and error characteristics of the various satellite estimates through inter-comparisons with GV radar estimates. The GV rain observations provided an empirical ground-based reference for assessing the relative performance of each sensor and sensor

  14. High resolution modeling of CO2 over Europe: implications for representation errors of satellite retrievals

    Directory of Open Access Journals (Sweden)

    T. Koch

    2010-01-01

    Full Text Available Satellite retrievals for column CO2 with better spatial and temporal sampling are expected to improve the current surface flux estimates of CO2 via inverse techniques. However, the spatial scale mismatch between remotely sensed CO2 and current generation inverse models can induce representation errors, which can cause systematic biases in flux estimates. This study is focused on estimating these representation errors associated with utilization of satellite measurements in global models with a horizontal resolution of about 1 degree or less. For this we used simulated CO2 from the high resolution modeling framework WRF-VPRM, which links CO2 fluxes from a diagnostic biosphere model to a weather forecasting model at 10×10 km2 horizontal resolution. Sub-grid variability of column averaged CO2, i.e. the variability not resolved by global models, reached up to 1.2 ppm with a median value of 0.4 ppm. Statistical analysis of the simulation results indicate that orography plays an important role. Using sub-grid variability of orography and CO2 fluxes as well as resolved mixing ratio of CO2, a linear model can be formulated that could explain about 50% of the spatial patterns in the systematic (bias or correlated error component of representation error in column and near-surface CO2 during day- and night-times. These findings give hints for a parameterization of representation error which would allow for the representation error to taken into account in inverse models or data assimilation systems.

  15. Arrange and Average Algorithm for Microphysical Retrievals with A "3β+3α" Lidar Configuration

    Science.gov (United States)

    Chemyakin, Eduard; Müller, Detlef; Burton, Sharon; Hostetler, Chris; Ferrare, Richard

    2016-06-01

    We present the results of a comparison study in which a simple, automated, and unsupervised algorithm, which we call the arrange and average algorithm, was used to infer microphysical parameters (complex refractive index (CRI), effective radius, total number, surface area, and volume concentrations) of atmospheric aerosol particles. The algorithm normally uses backscatter coefficients (β) at 355, 532, and 1064 nm and extinction coefficients (α) at 355 and 532 nm as input information. We compared the performance of the algorithm for the existing "3β+α" and potential "3β+3α" configurations of a multiwavelength aerosol Raman lidar or highspectral-resolution lidar (HSRL). The "3β+3α" configuration uses an extra extinction coefficient at 1064 nm. Testing of the algorithm is based on synthetic optical data that are computed from prescribed CRIs and monomodal logarithmically normal particle size distributions that represent spherical, primarily fine mode aerosols. We investigated the degree to which the microphysical results retrieved by this algorithm benefits from the increased number of input extinction coefficients.

  16. Contextual Information Retrieval based on Algorithmic Information Theory and Statistical Outlier Detection

    CERN Document Server

    Martinez, Rafael; Rodriguez, Francisco de Borja; Camacho, David

    2007-01-01

    The main contribution of this paper is to design an Information Retrieval (IR) technique based on Algorithmic Information Theory (using the Normalized Compression Distance- NCD), statistical techniques (outliers), and novel organization of data base structure. The paper shows how they can be integrated to retrieve information from generic databases using long (text-based) queries. Two important problems are analyzed in the paper. On the one hand, how to detect "false positives" when the distance among the documents is very low and there is actual similarity. On the other hand, we propose a way to structure a document database which similarities distance estimation depends on the length of the selected text. Finally, the experimental evaluations that have been carried out to study previous problems are shown.

  17. A Fast Image Retrieval Algorithm with Multi-Channel Textural Features in PACS

    Institute of Scientific and Technical Information of China (English)

    ZHANG Dong; YANG Yan; QIN Qian-qing

    2005-01-01

    The paper presents a fast algorithm for image retrieval using multi-channel textural features in medical picture archiving and communication system (PACS). By choosing different linear or nonlinear operators in prediction and update lifting step, the linear or nonlinear M-band wavelet decomposition can be achieved in Mband lifting. It provides the advantages such as fast transform, in-place calculation and integer-integer transform. The set of wavelet moment forms multi-channel textural feature vector related to the texture distribution of each wavelet images. The experimental results of CT image database show that the retrieval approach of multi-channel textural features is effective for image indexing and has lower computational complexity and less memory. It is much easier to implement in hardware and suitable for the applications of real time medical processing system.

  18. Multi-Algorithm Indices and Look-Up Table for Chlorophyll-a Retrieval in Highly Turbid Water Bodies Using Multispectral Data

    Directory of Open Access Journals (Sweden)

    Salem Ibrahim Salem

    2017-06-01

    Full Text Available Many approaches have been proposed for monitoring the eutrophication of Case 2 waters using remote sensing data. Semi-analytical algorithms and spectrum matching are two major approaches for chlorophyll-a (Chla retrieval. Semi-analytical algorithms provide indices correlated with phytoplankton characteristics, (e.g., maximum and minimum absorption peaks. Algorithms’ indices are correlated with measured Chla through the regression process. The main drawback of the semi-analytical algorithms is that the derived relation is location and data limited. Spectrum matching and the look-up table approach rely on matching the measured reflectance with a large library of simulated references corresponding to wide ranges of water properties. The spectral matching approach taking hyperspectral measured reflectance as an input, leading to difficulties in incorporating data from multispectral satellites. Consequently, multi-algorithm indices and the look-up table (MAIN-LUT technique is proposed to combine the merits of semi-analytical algorithms and look-up table, which can be applied to multispectral data. Eight combinations of four algorithms (i.e., 2-band, 3-band, maximum chlorophyll index, and normalized difference chlorophyll index are investigated for the MAIN-LUT technique. In situ measurements and Medium Resolution Imaging Spectrometer (MERIS sensor data are used to validate MAIN-LUT. In general, the MAIN-LUT provide a comparable retrieval accuracy with locally tuned algorithms. The most accurate of the locally tuned algorithms varied among datasets, revealing the limitation of these algorithms to be applied universally. In contrast, the MAIN-LUT provided relatively high retrieval accuracy for Tokyo Bay (R2 = 0.692, root mean square error (RMSE = 21.4 mg m−3, Lake Kasumigaura (R2 = 0.866, RMSE = 11.3 mg m−3, and MERIS data over Lake Kasumigaura (R2 = 0.57, RMSE = 36.5 mg m−3. The simulated reflectance library of MAIN-LUT was generated based on

  19. Satellite retrievals of leaf chlorophyll and photosynthetic capacity for improved modeling of GPP

    KAUST Repository

    Houborg, Rasmus

    2013-08-01

    This study investigates the utility of in situ and satellite-based leaf chlorophyll (Chl) estimates for quantifying leaf photosynthetic capacity and for constraining model simulations of Gross Primary Productivity (GPP) over a corn field in Maryland, U.S.A. The maximum rate of carboxylation (V-max) represents a key control on leaf photosynthesis within the widely employed C-3 and C-4 photosynthesis models proposed by Farquhar et al. (1980) and Collatz et al. (1992), respectively. A semi-mechanistic relationship between V-max(5) (V-max normalized to 25 degrees C) and Chl is derived based on interlinkages between V-max(25), Rubisco enzyme kinetics, leaf nitrogen, and Chl reported in the experimental literature. The resulting linear V-max(25) - Chl relationship is embedded within the photosynthesis scheme of the Community Land Model (CLM), thereby bypassing the use of fixed plant functional type (PFT) specific V-max(25) values. The effect of the updated parameterization on simulated carbon fluxes is tested over a corn field growing season using: (1) a detailed Chl time-series established on the basis of intensive field measurements and (2) Chl estimates derived from Landsat imagery using the REGularized canopy reFLECtance (REGFLEC) tool. Validations against flux tower observations demonstrate benefit of using Chl to parameterize V-max(25) to account for variations in nitrogen availability imposed by severe environmental conditions. The use of V-max(25) that varied seasonally as a function of satellite-based Chl, rather than a fixed PFT-specific value, significantly improved the agreement with observed tower fluxes with Pearson\\'s correlation coefficient (r) increasing from 0.88 to 0.93 and the root-mean-square-deviation decreasing from 4.77 to 3.48 mu mol m(-2) s(-1). The results support the use of Chl as a proxy for photosynthetic capacity using generalized relationships between V-max(25) and Chl, and advocate the potential of satellite retrieved Chl for

  20. Pi-MAX: a new parametrized algorithm to retrieve vertical profiles of trace gases and aerosols from MAX-DOAS measurements

    Science.gov (United States)

    Remmers, Julia; Beirle, Steffen; Doerner, Steffen; Wagner, Thomas

    2013-04-01

    Multi-Axis (MAX-) DOAS instruments observe scattered sunlight under various mostly slant elevation angles. From such observations information on tropospheric profiles of trace gases and aerosols can be retrieved. MAX-DOAS observations can be used to quantify emissions and to study chemical processes in the atmosphere. Measuring (horizontally and vertically) averaged concentrations the technique can be used as a link between in-situ and satellite measurements. Thus satellite observations of tropospheric trace gases can be validated. IMAX (Parametrized Inversion for MAX-DOAS measurements) is a parametrized method to retrieve vertical profiles of trace gases (such as H2O, NO2, HCHO, CHOCHO) and aerosols. No online calculations are necessary, since look-up tables (LUT) calculated with a Monte Carlo based radiative Transport Model are used. In this manner it is user-friendly, easy to distribute and applicable to every measurement location. The here shown measurements took place in the Maldives in March, 2012, during the CARDEX campaign. Simultaneous sun photometry-, Lidar- and UAV-measurements provide the possibility to validate the new algorithm. We present time series of profiles of trace gas concentrations and aerosol extinction We discuss the effects of clouds on the retrieved results.

  1. Retrieval of humidity and temperature profiles over the oceans from INSAT 3D satellite radiances

    Indian Academy of Sciences (India)

    C Krishnamoorthy; Deo Kumar; C Balaji

    2016-03-01

    In this study, retrieval of temperature and humidity profiles of atmosphere from INSAT 3D-observed radiances has been accomplished. As the first step, a fast forward radiative transfer model using an Artificial neural network has been developed and it was proven to be highly effective, giving a correlationcoefficient of 0.97. In order to develop this, a diverse set of physics-based clear sky profiles of pressure (P), temperature (T) and specific humidity (q) has been developed. The developed database was further used for geophysical retrieval experiments in two different frameworks, namely, an ANN and Bayesianestimation. The neural network retrievals were performed for three different cases, viz., temperature only retrieval, humidity only retrieval and combined retrieval. The temperature/humidity only ANN retrievals were found superior to combined retrieval using an ANN. Furthermore, Bayesian estimation showed superior results when compared with the combined ANN retrievals.

  2. Evaluating the Height of Biomass Burning Smoke Aerosols Retrieved from Synergistic Use of Multiple Satellite Sensors Over Southeast Asia

    Science.gov (United States)

    Lee, Jaehwa; Hsu, N. Christina; Bettenhausen, Corey; Sayer, Andrew M.; Seftor, Colin J.; Jeong, Myeong-Jae; Tsay, Si-Chee; Welton, Ellsworth J.; Wang, Sheng-Hsiang; Chen, Wei-Nai

    2016-01-01

    This study evaluates the height of biomass burning smoke aerosols retrieved from a combined use of Visible Infrared Imaging Radiometer Suite (VIIRS), Ozone Mapping and Profiler Suite (OMPS), and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations. The retrieved heights are compared against space borne and ground-based lidar measurements during the peak biomass burning season (March and April) over Southeast Asia from 2013 to 2015. Based on the comparison against CALIOP, a quality assurance (QA) procedure is developed. It is found that 74 (8184) of the retrieved heights fall within 1 km of CALIOP observations for unfiltered (QA-filtered) data, with root-mean-square error (RMSE) of 1.1 km (0.81.0 km). Eliminating the requirement of CALIOP observations from the retrieval process significantly increases the temporal coverage with only a slight decrease in the retrieval accuracy; for best QA data, 64 of data fall within 1 km of CALIOP observations with RMSE of 1.1 km. When compared with Micro-Pulse Lidar Network (MPLNET) measurements deployed at Doi Ang Khang, Thailand, the retrieved heights show RMSE of 1.7 km (1.1 km) for unfiltered (QA-filtered) data for the complete algorithm, and 0.9 km (0.8 km) for the simplified algorithm.

  3. Design of Content Based Image Retrieval Scheme for Diabetic Retinopathy Images using Harmony Search Algorithm.

    Science.gov (United States)

    Sivakamasundari, J; Natarajan, V

    2015-01-01

    Diabetic Retinopathy (DR) is a disorder that affects the structure of retinal blood vessels due to long-standing diabetes mellitus. Automated segmentation of blood vessel is vital for periodic screening and timely diagnosis. An attempt has been made to generate continuous retinal vasculature for the design of Content Based Image Retrieval (CBIR) application. The typical normal and abnormal retinal images are preprocessed to improve the vessel contrast. The blood vessels are segmented using evolutionary based Harmony Search Algorithm (HSA) combined with Otsu Multilevel Thresholding (MLT) method by best objective functions. The segmentation results are validated with corresponding ground truth images using binary similarity measures. The statistical, textural and structural features are obtained from the segmented images of normal and DR affected retina and are analyzed. CBIR in medical image retrieval applications are used to assist physicians in clinical decision-support techniques and research fields. A CBIR system is developed using HSA based Otsu MLT segmentation technique and the features obtained from the segmented images. Similarity matching is carried out between the features of query and database images using Euclidean Distance measure. Similar images are ranked and retrieved. The retrieval performance of CBIR system is evaluated in terms of precision and recall. The CBIR systems developed using HSA based Otsu MLT and conventional Otsu MLT methods are compared. The retrieval performance such as precision and recall are found to be 96% and 58% for CBIR system using HSA based Otsu MLT segmentation. This automated CBIR system could be recommended for use in computer assisted diagnosis for diabetic retinopathy screening.

  4. Multi-Grid-Cell Validation of Satellite Aerosol Property Retrievals in INTEX/ITCT/ICARTT 2004

    Science.gov (United States)

    Russell, P. B.; Livingston, J. M.; Redemann, J.; Schmid, B.; Ramirez, S. A.; Eilers, J.; Kahn, R.; Chu, D. A.; Remer, L.; Quinn, P. K.; Rood, M. J.; Wang, W.

    2007-01-01

    Aerosol transport off the US Northeast coast during the Summer 2004 International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) Intercontinental Chemical Transport Experiment (INTEX) and Intercontinental Transport and Chemical Transformation (ITCT) experiments produced a wide range of aerosol types and aerosol optical depth (AOD) values, often with strong horizontal AOD gradients. In these conditions we flew the 14-channel NASA Ames Airborne Tracking Sun photometer (AATS) on a Jetstream 31 (J31) aircraft. Legs flown at low altitude (usually less than 100 m ASL) provided comparisons of AATS AOD spectra to retrievals for 90 grid cells of the satellite radiometers MODIS-Terra, MODIS-Aqua, and MISR, all over the ocean. Characterization of the retrieval environment was aided by using vertical profiles by the J31 (showing aerosol vertical structure) and, on occasion, shipboard measurements of light scattering and absorption. AATS provides AOD at 13 wavelengths lambda from 354 to 2138 nm, spanning the range of aerosol retrieval wavelengths for MODIS over ocean (466-2119 nm) and MISR (446-866 nm). Midvisible AOD on low-altitude J31 legs in satellite grid cells ranged from 0.05 to 0.9, with horizontal gradients often in the range 0.05 to 0.13 per 10 km. When possible, we used ship measurements of humidified aerosol scattering and absorption to estimate AOD below the J31. In these cases, which had J31 altitudes 60-110 m ASL (typical of J31 low-altitude transects), estimated midvisible AOD below the J31 ranged from 0.003 to 0.013, with mean 0.009 and standard deviation 0.003. These values averaged 6 percent of AOD above the 53 1. MISR-AATS comparisons on 29 July 2004 in 8 grid cells (each -17.6 km x 17.6 km) show that MISR versions 15 and 16 captured the AATS-measured AOD gradient (correlation coefficient R2 = 0.87 to 0.92), but the MISR gradient was somewhat weaker than the AATS gradient. The large AOD (midvisible values up to -0.9) and

  5. Integrating satellite retrieved leaf chlorophyll into land surface models for constraining simulations of water and carbon fluxes

    KAUST Repository

    Houborg, Rasmus

    2013-07-01

    In terrestrial biosphere models, key biochemical controls on carbon uptake by vegetation canopies are typically assigned fixed literature-based values for broad categories of vegetation types although in reality significant spatial and temporal variability exists. Satellite remote sensing can support modeling efforts by offering distributed information on important land surface characteristics, which would be very difficult to obtain otherwise. This study investigates the utility of satellite based retrievals of leaf chlorophyll for estimating leaf photosynthetic capacity and for constraining model simulations of water and carbon fluxes. © 2013 IEEE.

  6. A rapid place name locating algorithm based on ontology qualitative retrieval, ranking and recommendation

    Science.gov (United States)

    Fan, Hong; Zhu, Anfeng; Zhang, Weixia

    2015-12-01

    In order to meet the rapid positioning of 12315 complaints, aiming at the natural language expression of telephone complaints, a semantic retrieval framework is proposed which is based on natural language parsing and geographical names ontology reasoning. Among them, a search result ranking and recommended algorithms is proposed which is regarding both geo-name conceptual similarity and spatial geometry relation similarity. The experiments show that this method can assist the operator to quickly find location of 12,315 complaints, increased industry and commerce customer satisfaction.

  7. Linear algorithms for phase retrieval in the Fresnel region: validity conditions

    CERN Document Server

    Gureyev, T E

    2015-01-01

    We describe the relationship between different forms of linearized expressions for the spatial distribution of intensity of X-ray projection images obtained in the Fresnel region. We prove that under the natural validity conditions some of the previously published expressions can be simplified without a loss of accuracy. We also introduce modified validity conditions which are likely to be fulfilled in many relevant practical cases, and which lead to a further significant simplification of the expression for the image-plane intensity, permitting simple non-iterative linear algorithms for the phase retrieval.

  8. Intercomparison of daytime stratospheric NO2 satellite retrievals and model simulations

    Science.gov (United States)

    Belmonte Rivas, M.; Veefkind, P.; Boersma, F.; Levelt, P.; Eskes, H.; Gille, J.

    2014-07-01

    This paper evaluates the agreement between stratospheric NO2 retrievals from infrared limb sounders (Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and High Resolution Dynamics Limb Sounder (HIRDLS)) and solar UV/VIS backscatter sensors (Ozone Monitoring Instrument (OMI), Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) limb and nadir) over the 2005-2007 period and across the seasons. The observational agreement is contrasted with the representation of NO2 profiles in 3-D chemical transport models such as the Whole Atmosphere Community Climate Model (WACCM) and TM4. A conclusion central to this work is that the definition of a reference for stratospheric NO2 columns formed by consistent agreement among SCIAMACHY, MIPAS and HIRDLS limb records (all of which agree to within 0.25 × 1015 molecules cm-2 or better than 10%) allows us to draw attention to relative errors in other data sets, e.g., (1) WACCM overestimates NO2 densities in the extratropical lower stratosphere, particularly in the springtime and over northern latitudes by up to 35% relative to limb observations, and (2) there are remarkable discrepancies between stratospheric NO2 column estimates from limb and nadir techniques, with a characteristic seasonally and latitudinally dependent pattern. We find that SCIAMACHY nadir and OMI stratospheric columns show overall biases of -0.5 × 1015 molecules cm-2 (-20%) and +0.6 × 1015 molecules cm-2 (+20%) relative to limb observations, respectively. It is argued that additive biases in nadir stratospheric columns are not expected to affect tropospheric retrievals significantly, and that they can be attributed to errors in the total slant column density, related either to algorithmic or instrumental effects. In order to obtain accurate and long-term time series of stratospheric NO2, an effort towards the harmonization of currently used differential optical absorption spectroscopy (DOAS) approaches to nadir

  9. Dust aerosol impact on the retrieval of cloud top height from satellite observations of CALIPSO, CloudSat and MODIS

    Science.gov (United States)

    Wang, Wencai; Sheng, Lifang; Dong, Xu; Qu, Wenjun; Sun, Jilin; Jin, Hongchun; Logan, Timothy

    2017-02-01

    Dust aerosol effect on the retrievals of dusty cloud top height (DCTH) are analyzed over Northwest China using cloud products from MODerate Resolution Imaging Spectroradiometer (MODIS) on Aqua, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat for the Spring season of March-May over the years 2007-2011. An excellent agreement is found between CloudSat and CALIPSO derived DCTHs for all cloud types, suggesting that the effect of dust aerosols plays a small role in DCTHs determination for lidar and radar measurements. However, the presence of dust aerosols greatly affects the retrievals of DCTHs for MODIS compared with pure clouds and the active sensors derived results. The differences of DCTHs retrieving from CloudSat and MODIS range from -2.30 to 6.8 km. Likewise, the differences of DCTHs retrieving from CALIPSO and MODIS range from -2.66 to 6.78 km. In addition, the results show that the differences in DCTHs for active and passive sensors are dependent on cloud type. On the whole, dust aerosols have the largest effect on cloud top heights (CTH) retrieved of nimbostratus (Ns), followed by altocumulus (Ac) and altostratus (As), the last is cirrus (Ci) over Northwest China. Our results also indicate that the accuracy of MODIS-derived retrievals reduces accompanied with a decrease of height.

  10. An Algorithm for Soil Moisture Retrieval using Multi-frequency Observations for Future the Water Cycle Observation Mission (WCOM)

    Science.gov (United States)

    Chen, Liang; Zhao, Tianjie; Wang, Cheng; Wan, Xiaoyun

    2017-04-01

    Soil moisture is one of the important parts in the global land surface ecosystem, water cycle and energy cycle, which control the water and heat energy exchange between land and atmosphere. Earth observation satellites play a critical role in providing information for understanding the global water cycle, which dominates the Earth-climate system. A new satellite concept of global Water Cycle Observation Mission (WCOM) is proposed in China, aiming to provide higher accuracy and consistent measurements of key elements of water cycle from space, including soil moisture, ocean salinity, freeze-thaw, snow water equivalent and etc. The expected more consistent and accurate datasets would be used to refine existing long-time series of satellite measurements, to constrain hydrological model projections and to detect the trends necessary for global change studies. The WCOM mission concept is a combination of active and passive microwave instruments. There will be three payloads: 1) an L-S-C tri-frequency Full-Polarized Interferometric synthetic aperture microwave Radiometer (FPIR); 2) a Polarized Microwave radiometric Imager (PMI) covering 6.8 GHz to 150 GHz bands; 3) an X-Ku Dual-Frequency Polarized SCATterometer (DFPSCAT). A soil moisture retrieval algorithm using the multi-frequency radiometer measurements is developed in this study. Through analyzing the simulated database of the Advanced Integral Equation Model (AIEM) under WCOM (Water Cycle Observation Mission) sensor configurations, a parameterized surface reflectivity model for multi-frequency Full-Polarized Interferometric synthetic aperture microwave Radiometer (FPIR) and Polarized Microwave radiometric Imager (PMI) are developed. In this model, influences of surface roughness parameters (e.g. RMS height, correlation length and type of autocorrelation function) on surface reflectivity are considered. It is found that the surface roughness and temperature can be cancelled out using the relationship of the multi

  11. Adaption of the MODIS aerosol retrieval algorithm using airborne spectral surface reflectance measurements over urban areas: a case study

    Science.gov (United States)

    Jäkel, E.; Mey, B.; Levy, R.; Gu, X.; Yu, T.; Li, Z.; Althausen, D.; Heese, B.; Wendisch, M.

    2015-12-01

    MODIS (MOderate-resolution Imaging Spectroradiometer) retrievals of aerosol optical depth (AOD) are biased over urban areas, primarily because the reflectance characteristics of urban surfaces are different than that assumed by the retrieval algorithm. Specifically, the operational "dark-target" retrieval is tuned towards vegetated (dark) surfaces and assumes a spectral relationship to estimate the surface reflectance in blue and red wavelengths. From airborne measurements of surface reflectance over the city of Zhongshan, China, were collected that could replace the assumptions within the MODIS retrieval algorithm. The subsequent impact was tested upon two versions of the operational algorithm, Collections 5 and 6 (C5 and C6). AOD retrieval results of the operational and modified algorithms were compared for a specific case study over Zhongshan to show minor differences between them all. However, the Zhongshan-based spectral surface relationship was applied to a much larger urban sample, specifically to the MODIS data taken over Beijing between 2010 and 2014. These results were compared directly to ground-based AERONET (AErosol RObotic NETwork) measurements of AOD. A significant reduction of the differences between the AOD retrieved by the modified algorithms and AERONET was found, whereby the mean difference decreased from 0.27±0.14 for the operational C5 and 0.19±0.12 for the operational C6 to 0.10±0.15 and -0.02±0.17 by using the modified C5 and C6 retrievals. Since the modified algorithms assume a higher contribution by the surface to the total measured reflectance from MODIS, consequently the overestimation of AOD by the operational methods is reduced. Furthermore, the sensitivity of the MODIS AOD retrieval with respect to different surface types was investigated. Radiative transfer simulations were performed to model reflectances at top of atmosphere for predefined aerosol properties. The reflectance data were used as input for the retrieval methods. It

  12. Optimization of the GSFC TROPOZ DIAL retrieval using synthetic lidar returns and ozonesondes - Part 1: Algorithm validation

    Science.gov (United States)

    Sullivan, J. T.; McGee, T. J.; Leblanc, T.; Sumnicht, G. K.; Twigg, L. W.

    2015-10-01

    The main purpose of the NASA Goddard Space Flight Center TROPospheric OZone DIfferential Absorption Lidar (GSFC TROPOZ DIAL) is to measure the vertical distribution of tropospheric ozone for science investigations. Because of the important health and climate impacts of tropospheric ozone, it is imperative to quantify background photochemical ozone concentrations and ozone layers aloft, especially during air quality episodes. For these reasons, this paper addresses the necessary procedures to validate the TROPOZ retrieval algorithm and confirm that it is properly representing ozone concentrations. This paper is focused on ensuring the TROPOZ algorithm is properly quantifying ozone concentrations, and a following paper will focus on a systematic uncertainty analysis. This methodology begins by simulating synthetic lidar returns from actual TROPOZ lidar return signals in combination with a known ozone profile. From these synthetic signals, it is possible to explicitly determine retrieval algorithm biases from the known profile. This was then systematically performed to identify any areas that need refinement for a new operational version of the TROPOZ retrieval algorithm. One immediate outcome of this exercise was that a bin registration error in the correction for detector saturation within the original retrieval was discovered and was subsequently corrected for. Another noticeable outcome was that the vertical smoothing in the retrieval algorithm was upgraded from a constant vertical resolution to a variable vertical resolution to yield a statistical uncertainty of <10 %. This new and optimized vertical-resolution scheme retains the ability to resolve fluctuations in the known ozone profile, but it now allows near-field signals to be more appropriately smoothed. With these revisions to the previous TROPOZ retrieval, the optimized TROPOZ retrieval algorithm (TROPOZopt) has been effective in retrieving nearly 200 m lower to the surface. Also, as compared to the

  13. Time variable gravity retrieval and treatment of temporal aliasing using optical two-way links between GALILEO and LEO satellites

    Science.gov (United States)

    Hauk, Markus; Pail, Roland; Murböck, Michael; Schlicht, Anja

    2016-04-01

    For the determination of temporal gravity fields satellite missions such as GRACE (Gravity Recovery and Climate Experiment) or CHAMP (Challenging Minisatellite Payload) were used in the last decade. These missions improved the knowledge of atmospheric, oceanic and tidal mass variations. The most limiting factor of temporal gravity retrieval quality is temporal aliasing due to the undersampling of high frequency signals, especially in the atmosphere and oceans. This kind of error causes the typical stripes in spatial representations of global gravity fields such as from GRACE. As part of the GETRIS (Geodesy and Time Reference in Space) mission, that aims to establish a geodetic reference station and precise time- and frequency reference in space by using optical two-way communication links between geostationary (GEO) and low Earth orbiting (LEO) satellites, a possible future gravity field mission can be set up. By expanding the GETRIS space segment to the global satellite navigation systems (GNSS) the optical two-way links also connect the GALILEO satellites among themselves and to LEO satellites. From these links between GALILEO and LEO satellites gravitational information can be extracted. In our simulations inter-satellite links between GALILEO and LEO satellites are used to determine temporal changes in the Earth's gravitational field. One of the main goals of this work is to find a suitable constellation together with the best analysis method to reduce temporal aliasing errors. Concerning non-tidal aliasing, it could be shown that the co-estimation of short-period long-wavelength gravity field signals, the so-called Wiese approach, is a powerful method for aliasing reduction (Wiese et al. 2013). By means of a closed loop mission simulator using inter-satellite observations as acceleration differences along the line-of-sight, different mission scenarios for GALILEO-LEO inter-satellite links and different functional models like the Wiese approach are analysed.

  14. Satellite Retrieval of Soil Moisture:An Overview%卫星遥感反演土壤水分研究综述

    Institute of Scientific and Technical Information of China (English)

    陈书林; 刘元波; 温作民

    2012-01-01

    Soil moisture is a key variable influencing a variety of land surface processes.Accurate estimation of spatio-temporally distributed soil moisture is one of the challenging issues in quantitative remote sensing.This paper briefly describes the major algorithms for retrieving soil moisture using optical,passive-microwave and active-microwave remote sensing,or their combinations.The optical algorithms have relatively low accuracy of retrieval,but good spatial and temporal resolutions.The typical algorithms include the Index-based approach and the soil thermal inertia-based approach.The passive-microwave algorithms have relative high accuracy but low spatial resolutions.It can be grouped into the retrieval approaches for soil moisture only and the approaches for relevant parameters in addition to soil moisture.The active-microwave algorithms have generally high accuracy with a high spatial resolution.The algorithms can be divided into three classes: empirical,physical and semi-empirical approaches.In addition,a number of algorithms have been proposed,which combines in particular optical,passive-microwave,or active-microwave data.Because the algorithms often combine the advantages of the multi-sensors,they can achieve a high accuracy with a good spatial resolution.With the achievement of retrieval techniques,several global soil moisture data sets have been generated.The widely used data sets include the European Remote Sensing satellites/ Meteorological Operational satellite programme(ERS/MetOp) data sets,the Advanced Microwave Scanning Radiometer for EOS(AMSR-E) data sets,and the Soil Moisture and Ocean Salinity(SMOS) data sets.The ERS/MetOp data sets provides global soil moisture data with a spatial resolution of 25-km so far since July,1991,retrieved from the TU-Wien approach using C-band microwave data.The AMSR-E data sets provides global soil moisture data with a spatial resolution of 25-km for the period from June,2002 to September,2011,retrieved from the Land

  15. Aerosol height retrieval from satellite visible measurements: application to OMI 477 nm O2-O2 spectral band, based on Neural Networks

    Science.gov (United States)

    Chimot, Julien; Veefkind, Pepijn; Vlemmix, Tim; Levelt, Pieternel

    2017-04-01

    The ability to monitor air quality and climate from UltraViolet-Visible (UV-Vis) satellite spectral measurements relies on accurate trace gas (e.g. NO2, SO2, HCHO, O3) columns combined with aerosol properties and vertical distribution. In the absence of clouds, the most important error source on the observations of trace gases in the troposphere are aerosols, since their scattering and absorbing properties modify the average light path followed by the detected photons. Large impacts due to their vertical distribution uncertainties remain when retrieving vertical column densities of trace gases from UV-Vis air quality space-borne sensors [Krotkov et al., 2008; Boersma et al., 2011; Barkley et al., 2012; Hewson et al., 2015; Castellanos et al., 2015; Chimot et al., 2016a]. Aerosols and trace gases share, over urban and industrialized areas, similar anthropogenic sources, and their concentrations, as shown by the satellite observations, often present significant correlations [Veefkind et al., 2011]. We have recently developed a Multilayer Perceptron Neural Network (NN) algorithm to retrieve Aerosol Layer Height (ALH) from the OMI 477 nm O2-O2 absorption band [Chimot et al., 2016b]. This algorithm represents aerosols in the troposphere as a single scattering layer defined by its mean altitude and homogeneous optical properties. This algorithm enables the link between the OMI O2-O2 slant column density derived from the 477 nm spectral measurements and the aerosol layer altitude. A prior information about the Aerosol Optical Thickness (AOT) is needed to distinguish the effects due to the amount of fine particles and their altitude. Therefore, the ALH retrieval strongly benefits from a synergy between OMI 477 nm O2-O2 spectral measurements and MODIS AOT product. Aerosol layer heights are currently retrieved with an uncertainty in the range of 260-800 m for scenes with AOT larger than 1. Improvement of these retrievals can be expected by improving assumptions on the

  16. Improved retrieval of complex supercontinuum pulses from XFROG traces using a ptychographic algorithm.

    Science.gov (United States)

    Heidt, Alexander M; Spangenberg, Dirk-Mathys; Brügmann, Michael; Rohwer, Erich G; Feurer, Thomas

    2016-11-01

    We demonstrate that time-domain ptychography, a recently introduced iterative ultrafast pulse retrieval algorithm, has properties well suited for the reconstruction of complex light pulses with large time-bandwidth products from a cross-correlation frequency-resolved optical gating (XFROG) measurement. It achieves temporal resolution on the scale of a single optical cycle using long probe pulses and low sampling rates. In comparison to existing algorithms, ptychography minimizes the data to be recorded and processed, and significantly reduces the computational time of the reconstruction. Experimentally, we measure the temporal waveform of an octave-spanning, 3.5 ps long, supercontinuum pulse generated in photonic crystal fiber, resolving features as short as 5.7 fs with sub-fs resolution and 30 dB dynamic range using 100 fs probe pulses and similarly large delay steps.

  17. Oversampling smoothness (OSS): an effective algorithm for phase retrieval of noisy diffraction intensities

    CERN Document Server

    Rodriguez, Jose A; Chen, Chien-Chun; Zou, Yunfei; Miao, Jianwei

    2012-01-01

    Coherent diffraction imaging (CDI) is high-resolution lensless microscopy that has been applied to image a wide range of specimens using synchrotron radiation, X-ray free electron lasers, high harmonic generation, soft X-ray laser and electrons. Despite these rapid advances, it remains a challenge to reconstruct fine features in weakly scattering objects such as biological specimens from noisy data. Here we present an effective iterative algorithm, termed oversampling smoothness (OSS), for phase retrieval of noisy diffraction intensities. OSS exploits the correlation information among the pixels or voxels in the region outside of a support in real space. By properly applying spatial frequency filters to the pixels or voxels outside the support at different stage of the iterative process (i.e. a smoothness constraint), OSS finds a balance between the hybrid input-output (HIO) and error reduction (ER) algorithms to search for a global minimum in solution space, while reducing the oscillations in the reconstruct...

  18. Effects of Per-Pixel Variability on Uncertainties in Bathymetric Retrievals from High-Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Elizabeth J. Botha

    2016-05-01

    Full Text Available Increased sophistication of high spatial resolution multispectral satellite sensors provides enhanced bathymetric mapping capability. However, the enhancements are counter-acted by per-pixel variability in sunglint, atmospheric path length and directional effects. This case-study highlights retrieval errors from images acquired at non-optimal geometrical combinations. The effects of variations in the environmental noise on water surface reflectance and the accuracy of environmental variable retrievals were quantified. Two WorldView-2 satellite images were acquired, within one minute of each other, with Image 1 placed in a near-optimal sun-sensor geometric configuration and Image 2 placed close to the specular point of the Bidirectional Reflectance Distribution Function (BRDF. Image 2 had higher total environmental noise due to increased surface glint and higher atmospheric path-scattering. Generally, depths were under-estimated from Image 2, compared to Image 1. A partial improvement in retrieval error after glint correction of Image 2 resulted in an increase of the maximum depth to which accurate depth estimations were returned. This case-study indicates that critical analysis of individual images, accounting for the entire sun elevation and azimuth and satellite sensor pointing and geometry as well as anticipated wave height and direction, is required to ensure an image is fit for purpose for aquatic data analysis.

  19. Arctic clouds and surface radiation – a critical comparison of satellite retrievals and the ERA-interim reanalysis

    Directory of Open Access Journals (Sweden)

    M. Zygmuntowska

    2011-12-01

    Full Text Available Clouds regulate Earth's radiation budget, both by reflecting part of the incoming sunlight leading to cooling and by absorbing and emitting infrared radiation which tends to have a warming effect. Globally averaged, at the top of the atmosphere the cloud radiative effect is to cool the climate, while at the Arctic surface, clouds are thought to be warming. Ground-based observations of central Arctic Ocean cloudiness are limited to sporadic field campaigns. Therefore many studies rely on satellite- or reanalysis data. Here we compare a passive instrument, the AVHRR-based retrieval from CM-SAF, with recently launched active instruments onboard CloudSat and CALIPSO and the widely used ERA-Interim reanalysis. We find that the three data sets differ significantly. In summer, the two satellite products agree having monthly means of 70–80 percent, but the reanalysis are approximately ten percent higher. In winter passive satellite instruments have serious difficulties, detecting only half the cloudiness of the reanalysis, active instruments being in between. The monthly mean long- and shortwave components of the surface cloud radiative effect obtained from the ERA-Interim reanalysis are about twice that calculated on the basis of CloudSat retrievals. We discuss these discrepancies in terms of instrument-, retrieval- and reanalysis characteristics.

  20. Satellite retrieval of the liquid water fraction in tropical clouds between −20 and −38 °C

    Directory of Open Access Journals (Sweden)

    D. L. Mitchell

    2012-07-01

    Full Text Available This study describes a satellite remote sensing method for directly retrieving the liquid water fraction in mixed phase clouds, and appears unique in this respect. The method uses MODIS split-window channels for retrieving the liquid fraction from cold clouds where the liquid water fraction is less than 50% of the total condensate. This makes use of the observation that clouds only containing ice exhibit effective 12-to-11 μm absorption optical thickness ratios (βeff that are quasi-constant with retrieved cloud temperature T. This observation was made possible by using two CO2 channels to retrieve T and then using the 12 and 11 μm channels to retrieve emissivities and βeff. Thus for T < −40 °C, βeff is constant, but for T > −40 °C, βeff slowly increases due to the presence of liquid water, revealing mean liquid fractions of ~ 10% around −22 °C from tropical clouds identified as cirrus by the cloud mask. However, the uncertainties for these retrievals are large, and extensive in situ measurements are needed to refine and validate these retrievals. Such liquid levels are shown to reduce the cloud effective diameter De such that cloud optical thickness will increase by more than 50% for a given water path, relative to De corresponding to pure ice clouds. Such retrieval information is needed for validation of the cloud microphysics in climate models. Since low levels of liquid water can dominate cloud optical properties, tropical clouds between −25 and −20 °C may be susceptible to the first aerosol indirect effect.

  1. Oversampling smoothness: an effective algorithm for phase retrieval of noisy diffraction intensities.

    Science.gov (United States)

    Rodriguez, Jose A; Xu, Rui; Chen, Chien-Chun; Zou, Yunfei; Miao, Jianwei

    2013-04-01

    Coherent diffraction imaging (CDI) is high-resolution lensless microscopy that has been applied to image a wide range of specimens using synchrotron radiation, X-ray free-electron lasers, high harmonic generation, soft X-ray lasers and electrons. Despite recent rapid advances, it remains a challenge to reconstruct fine features in weakly scattering objects such as biological specimens from noisy data. Here an effective iterative algorithm, termed oversampling smoothness (OSS), for phase retrieval of noisy diffraction intensities is presented. OSS exploits the correlation information among the pixels or voxels in the region outside of a support in real space. By properly applying spatial frequency filters to the pixels or voxels outside the support at different stages of the iterative process (i.e. a smoothness constraint), OSS finds a balance between the hybrid input-output (HIO) and error reduction (ER) algorithms to search for a global minimum in solution space, while reducing the oscillations in the reconstruction. Both numerical simulations with Poisson noise and experimental data from a biological cell indicate that OSS consistently outperforms the HIO, ER-HIO and noise robust (NR)-HIO algorithms at all noise levels in terms of accuracy and consistency of the reconstructions. It is expected that OSS will find application in the rapidly growing CDI field, as well as other disciplines where phase retrieval from noisy Fourier magnitudes is needed. The MATLAB (The MathWorks Inc., Natick, MA, USA) source code of the OSS algorithm is freely available from http://www.physics.ucla.edu/research/imaging.

  2. A New Optical Surface Measurement Method with Iterative Sparsity-Constrained Threshold Phase Retrieval Algorithm

    Directory of Open Access Journals (Sweden)

    Yi Niu

    2014-01-01

    Full Text Available Due to its low complexity and acceptable accuracy, phase retrieval technique has been proposed as an alternative to solve the classic optical surface measurement task. However, to capture the overall wave field, phase retrieval based optical surface measurement (PROSM system has to moderate the CCD position during the multiple-sampling procedure. The mechanical modules of CCD movement may bring about unexpectable deviation to the final results. To overcome this drawback, we propose a new PROSM method based on spatial light modulator (SLM. The mechanical CCD movement can be replaced by an electrical moderation of SLM patterns; thus the deviation can be significantly suppressed in the new PROSM method. In addition, to further improve the performance, we propose a new iterative threshold phase retrieval algorithm with sparsity-constraint to effectively reconstruct the phase of wave field. Experimental results show that the new method provides a more simple and robust solution for the optical surface measurement than the traditional techniques and achieves higher accuracy.

  3. Intercomparison of Satellite Dust Retrieval Products over the West African Sahara During the Fennec Campaign in June 2011

    Science.gov (United States)

    Banks, J.R.; Brindley, H. E.; Flamant, C.; Garay, M. J.; Hsu, N. C.; Kalashnikova, O. V.; Klueser, L.; Sayer, A. M.

    2013-01-01

    Dust retrievals over the Sahara Desert during June 2011 from the IASI, MISR, MODIS, and SEVIRI satellite instruments are compared against each other in order to understand the strengths and weaknesses of each retrieval approach. Particular attention is paid to the effects of meteorological conditions, land surface properties, and the magnitude of the dust loading. The period of study corresponds to the time of the first Fennec intensive measurement campaign, which provides new ground-based and aircraft measurements of the dust characteristics and loading. Validation using ground-based AERONET sunphotometer data indicate that of the satellite instruments, SEVIRI is most able to retrieve dust during optically thick dust events, whereas IASI and MODIS perform better at low dust loadings. This may significantly affect observations of dust emission and the mean dust climatology. MISR and MODIS are least sensitive to variations in meteorological conditions, while SEVIRI tends to overestimate the aerosol optical depth (AOD) under moist conditions (with a bias against AERONET of 0.31), especially at low dust loadings where the AOD<1. Further comparisons are made with airborne LIDAR measurements taken during the Fennec campaign, which provide further evidence for the inferences made from the AERONET comparisons. The effect of surface properties on the retrievals is also investigated. Over elevated surfaces IASI retrieves AODs which are most consistent with AERONET observations, while the AODs retrieved by MODIS tend to be biased low. In contrast, over the least emissive surfaces IASI significantly underestimates the AOD (with a bias of -0.41), while MISR and SEVIRI show closest agreement.

  4. Understanding the aerosol information content in multi-spectral reflectance measurements using a synergetic retrieval algorithm

    Directory of Open Access Journals (Sweden)

    D. Martynenko

    2010-11-01

    Full Text Available An information content analysis for multi-wavelength SYNergetic AErosol Retrieval algorithm SYNAER was performed to quantify the number of independent pieces of information that can be retrieved. In particular, the capability of SYNAER to discern various aerosol types is assessed. This information content depends on the aerosol optical depth, the surface albedo spectrum and the observation geometry. The theoretical analysis is performed for a large number of scenarios with various geometries and surface albedo spectra for ocean, soil and vegetation. When the surface albedo spectrum and its accuracy is known under cloud-free conditions, reflectance measurements used in SYNAER is able to provide for 2–4° of freedom that can be attributed to retrieval parameters: aerosol optical depth, aerosol type and surface albedo.

    The focus of this work is placed on an information content analysis with emphasis to the aerosol type classification. This analysis is applied to synthetic reflectance measurements for 40 predefined aerosol mixtures of different basic components, given by sea salt, mineral dust, biomass burning and diesel aerosols, water soluble and water insoluble aerosols. The range of aerosol parameters considered through the 40 mixtures covers the natural variability of tropospheric aerosols. After the information content analysis performed in Holzer-Popp et al. (2008 there was a necessity to compare derived degrees of freedom with retrieved aerosol optical depth for different aerosol types, which is the main focus of this paper.

    The principle component analysis was used to determine the correspondence between degrees of freedom for signal in the retrieval and derived aerosol types. The main results of the analysis indicate correspondence between the major groups of the aerosol types, which are: water soluble aerosol, soot, mineral dust and sea salt and degrees of freedom in the algorithm and show the ability of the SYNAER to

  5. A Novel Method for Optimum Global Positioning System Satellite Selection Based on a Modified Genetic Algorithm.

    Science.gov (United States)

    Song, Jiancai; Xue, Guixiang; Kang, Yanan

    2016-01-01

    In this paper, a novel method for selecting a navigation satellite subset for a global positioning system (GPS) based on a genetic algorithm is presented. This approach is based on minimizing the factors in the geometric dilution of precision (GDOP) using a modified genetic algorithm (MGA) with an elite conservation strategy, adaptive selection, adaptive mutation, and a hybrid genetic algorithm that can select a subset of the satellites represented by specific numbers in the interval (4 ∼ n) while maintaining position accuracy. A comprehensive simulation demonstrates that the MGA-based satellite selection method effectively selects the correct number of optimal satellite subsets using receiver autonomous integrity monitoring (RAIM) or fault detection and exclusion (FDE). This method is more adaptable and flexible for GPS receivers, particularly for those used in handset equipment and mobile phones.

  6. New methods for the retrieval of chlorophyll red fluorescence from hyperspectral satellite instruments: simulations and application to GOME-2 and SCIAMACHY

    Science.gov (United States)

    Joiner, Joanna; Yoshida, Yasuko; Guanter, Luis; Middleton, Elizabeth M.

    2016-08-01

    Global satellite measurements of solar-induced fluorescence (SIF) from chlorophyll over land and ocean have proven useful for a number of different applications related to physiology, phenology, and productivity of plants and phytoplankton. Terrestrial chlorophyll fluorescence is emitted throughout the red and far-red spectrum, producing two broad peaks near 683 and 736 nm. From ocean surfaces, phytoplankton fluorescence emissions are entirely from the red region (683 nm peak). Studies using satellite-derived SIF over land have focused almost exclusively on measurements in the far red (wavelengths > 712 nm), since those are the most easily obtained with existing instrumentation. Here, we examine new ways to use existing hyperspectral satellite data sets to retrieve red SIF (wavelengths unique opportunity to compare red and far-red terrestrial SIF at regional spatial scales. Terrestrial SIF has been estimated with ground-, aircraft-, or satellite-based instruments by measuring the filling-in of atmospheric and/or solar absorption spectral features by SIF. Our approach makes use of the oxygen (O2) γ band that is not affected by SIF. The SIF-free O2 γ band helps to estimate absorption within the spectrally variable O2 B band, which is filled in by red SIF. SIF also fills in the spectrally stable solar Fraunhofer lines (SFLs) at wavelengths both inside and just outside the O2 B band, which further helps to estimate red SIF emission. Our approach is then an extension of previous approaches applied to satellite data that utilized only the filling-in of SFLs by red SIF. We conducted retrievals of red SIF using an extensive database of simulated radiances covering a wide range of conditions. Our new algorithm produces good agreement between the simulated truth and retrievals and shows the potential of the O2 bands for noise reduction in red SIF retrievals as compared with approaches that rely solely on SFL filling. Biases seen with existing satellite data, most likely

  7. CBMIR: SHAPE-BASED IMAGE RETRIEVAL USING CANNY EDGE DETECTION AND K-MEANS CLUSTERING ALGORITHMS FOR MEDICAL IMAGES

    Directory of Open Access Journals (Sweden)

    B.Ramamurthy,

    2011-03-01

    Full Text Available The accumulation of large collections of digital images has created the need for efficient and intelligent schemes for classifying and retrieval of images. In this work, “CBMIR: Shape-Based Image Retrieval Using Canny Edge Detection and K-Means Clustering Algorithms for Medical Images”, has been developed to retrieve the medical images from huge volume of medical databases. This requires the preprocessing, feature extraction, classification, retrieval and indexing steps in order to develop an efficient medical image retrieval system. In this work, for preprocessing step, the image segmentation method has been carried out, for feature extraction, basic shape feature has been extracted using canny edge detection algorithm, and for classification, K-means classification algorithm has been used. For retrieval of images, Euclidian distance method values are calculated between query image and database images. The goal of this work is to provide a medical image retrieval system for further use of medical diagnosis purpose in the field of medical domain.

  8. Optimization of Determinant Factors of Satellite Electrical Power System with Particle Swarm Optimization (PSO Algorithm

    Directory of Open Access Journals (Sweden)

    Mojtaba Biglarahmadi

    2014-03-01

    Full Text Available Weight and dimension, cost, and performance are determinant factors for design, fabrication, and launch the satellites which are related to the mission type of the satellites. Each satellite includes several subsystems such as Electrical Power Subsystem (EPS, Navigation Subsystem, Thermal Subsystem, etc. The purpose of this paper is to optimize these determinant factors by Particle Swarm Optimization (PSO algorithm, for Electrical Power Subsystem. This paper considers the effects of selecting various types of Photovoltaic (PV cells and batteries on weight and dimension, cost, and performance of the satellite. We have used two various types of PVs and two various type of batteries in optimization of the Electrical Power Subsystem (EPS

  9. Fully phase color image encryption based on joint fractional Fourier transform correlator and phase retrieval algorithm

    Institute of Scientific and Technical Information of China (English)

    Ding Lu; Weimin Jin

    2011-01-01

    A novel fully phase color image encryption/decryption scheme based on joint fractional Fourier transform correlator (JFRTC) and phase retrieval algorithm (PRA) is proposed. The security of the system is enhanced by the fractional order as a new added key. This method takes full advantage of the parallel processing features of the optical system and could optically realize single-channel color image encryption.The system and operation procedures are simplified. The simulation results of a color image indicate that the new method provides efficient solutions with a strong sense of security.%@@ A novel fully phase color image encryption/decryption scheme based on joint fractional Fourier transform correlator (JFRTC) and phase retrieval algorithm (PRA) is proposed. The security of the system is enhanced by the fractional order as a new added key. This method takes full advantage of the parallel processing features of the optical system and could optically realize single-channel color image encryption. The system and operation procedures are simplified. The simulation results of a color image indicate that the new method provides efficient solutions with a strong sense of security.

  10. Application of iterative phase-retrieval algorithms to ARPES orbital tomography

    Science.gov (United States)

    Kliuiev, P.; Latychevskaia, T.; Osterwalder, J.; Hengsberger, M.; Castiglioni, L.

    2016-09-01

    Electronic wave functions of planar molecules can be reconstructed via inverse Fourier transform of angle-resolved photoelectron spectroscopy (ARPES) data, provided the phase of the electron wave in the detector plane is known. Since the recorded intensity is proportional to the absolute square of the Fourier transform of the initial state wave function, information about the phase distribution is lost in the measurement. It was shown that the phase can be retrieved in some cases by iterative algorithms using a priori information about the object such as its size and symmetry. We suggest a more generalized and robust approach for the reconstruction of molecular orbitals based on state-of-the-art phase-retrieval algorithms currently used in coherent diffraction imaging (CDI). We draw an analogy between the phase problem in molecular orbital imaging by ARPES and of that in optical CDI by performing an optical analogue experiment on micrometer-sized structures. We successfully reconstruct amplitude and phase of both the micrometer-sized objects and a molecular orbital from the optical and photoelectron far-field intensity distributions, respectively, without any prior information about the shape of the objects.

  11. [Retrieval of Copper Pollution Information from Hyperspectral Satellite Data in a Vegetation Cover Mining Area].

    Science.gov (United States)

    Qu, Yong-hua; Jiao, Si-hong; Liu, Su-hong; Zhu, Ye-qing

    2015-11-01

    Heavy metal mining activities have caused the complex influence on the ecological environment of the mining regions. For example, a larg