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Sample records for algorithm retrieves cloud

  1. Evaluation of multi-layer cloud property retrievals from optimal estimation and Bayesian retrieval algorithms

    NASA Astrophysics Data System (ADS)

    Ding, Y.; Yang, P.

    2015-12-01

    Three physical and radiative cloud properties, namely, optical thickness (tau), effective diameter (De), and cloud top height(h) can be simultaneously inferred from IR radiances for multi-layer cloud cases. The retrieval algorithm implementation is based on a computationally efficient radiative transfer model and spaceborne measurements of narrowband infrared (IR) radiances at the top of the atmosphere. This study focuses on the evaluation of the retrieval results derived from two different algorithms, optimal estimation (OE) algorithm and Bayesian retrieval algorithm. Both of the two methods are able to offer comprehensive error analysis and quality flags. The evaluation results can potentially useful for retrieving the multi-layer clouds properties, a research subject that receives little attention. This presentation will discuss the pros and cons of retrieving cloud properties from the aforesaid retrieval algorithms.

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

    NASA Astrophysics Data System (ADS)

    Wang, P.; Stammes, P.; van der A, R.; Pinardi, G.; van Roozendael, M.

    2008-11-01

    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.

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

    NASA Astrophysics Data System (ADS)

    Wang, P.; Stammes, P.; van der A, R.; Pinardi, G.; van Roozendael, M.

    2008-05-01

    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 shows 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 densities (VCD) 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 NO2 VCDs 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 -2.12×1014 molec cm-2.

  4. Evaluating cloud retrieval algorithms with the ARM BBHRP framework

    SciTech Connect

    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-phase clouds and

  5. Cloud effects on chlorophyll retrieval algorithm of MODIS

    NASA Astrophysics Data System (ADS)

    Du, KePing; Gao, Yonggang; Lee, ZhongPing; Xi, Ying; Wang, Jindi

    2006-12-01

    Ocean environment attracts more and more attention, whereas monitoring ocean environment using ocean color imagery (e.g., MODIS) has become one of the important fields in modern oceanography. After analyzing a few individual modules of the radiative transfer process, an end-to-end numerical model for ocean remote sensing is developed. This model combines MODTRAN and HYDROLIGHT, both are state-of-the-art radiative transfer models for atmosphere and water, respectively. Also, a simple but realistic cloud model is added to it. This combined model calculates the downward radiance on water surface using MODTRAN and the independent cloud model, which replaces the empirical and semi-empirical models used in RADTRAN (Gregg and Carder 1991). Especially, with information of cloud's location and brightness from by the cloud model, the combined model provides more accurate radiance on water surface. Further, the effects of cloud position (from 30 degree to 180 degree for the cloud central azimuth angle) and coverage (from about 10% to 80%) on retrieved chlorophyll concentration by standard MODIS algorithm is analyzed. It is found that the nearer the cloud to the Sun the smaller the effect on the derived chlorophyll.

  6. Sensitivity of cloud retrieval statistics to algorithm choices: Lessons learned from MODIS product development

    NASA Astrophysics Data System (ADS)

    Platnick, Steven; Ackerman, Steven; King, Michael; Zhang, Zhibo; Wind, Galina

    2013-04-01

    Cloud detection algorithms search for measurement signatures that differentiate a cloud-contaminated or "not-clear" pixel from the clear-sky background. These signatures can be spectral, textural or temporal in nature. The magnitude of the difference between the cloud and the background must exceed a threshold value for the pixel to be classified having a not-clear FOV. All detection algorithms employ multiple tests ranging across some portion of the solar reflectance and/or infrared spectrum. However, a cloud is not a single, uniform object, but rather has a distribution of optical thickness and morphology. As a result, problems can arise when the distributions of cloud and clear-sky background characteristics overlap, making some test results indeterminate and/or leading to some amount of detection misclassification. Further, imager cloud retrieval statistics are highly sensitive to how a pixel identified as not-clear by a cloud mask is determined to be useful for cloud-top and optical retrievals based on 1-D radiative models. This presentation provides an overview of the different 'choices' algorithm developers make in cloud detection algorithms and the impact on regional and global cloud amounts and fractional coverage, cloud type and property distributions. Lessons learned over the course of the MODIS cloud product development history are discussed. As an example, we will focus on the 1km MODIS Collection 5 cloud optical retrieval algorithm (product MOD06/MYD06 for Terra and Aqua, respectively) which removed pixels associated with cloud edges as defined by immediate adjacency to clear FOV MODIS cloud mask (MOD35/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 algorithm. The Collection 6 algorithm attempts retrievals for these two types of partly cloudy pixel populations, but allows a user to isolate or filter out the populations. Retrieval sensitivities for these

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

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Technical Reports Server (NTRS)

    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.

  9. An Intercomparison of Microphysical Retrieval Algorithms for Upper-Tropospheric Ice Clouds

    SciTech Connect

    Comstock, Jennifer M.; d'Entremont, Robert; DeSlover, Daniel; Mace, Gerald G.; Matrosov, S. Y.; McFarlane, Sally A.; Minnis, Patrick; Mitchell, David; Sassen, Kenneth; Shupe, Matthew D.; Turner, David D.; Wang, Zhien

    2007-02-01

    The large horizontal extent, location in the cold upper troposphere, and ice composition make cirrus clouds important modulators of the earth’s radiation budget and climate. Cirrus cloud microphysical properties are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. Accurate retrievals of cloud properties are crucial for improving the representation of cloud scale processes in large-scale models and for accurately predicting the earth’s future climate. A number of passive and active remote sensing retrievals exist for estimating the microphysical properties of upper tropospheric clouds. We believe significant progress has been made in the evolution of these retrieval algorithms in the last decade; however, there is room for improvement. Members of the Atmospheric Radiation Measurement program (ARM) Cloud Properties Working Group are involved in an intercomparison of optical depth (tau), ice water path, and characteristic particle size in ice clouds retrieved using ground-based instruments. The goals of this intercomparison are to evaluate the accuracy of state-of-the-art algorithms, quantify the uncertainties, and make recommendations for improvement. Currently, there is significant scatter in the algorithms for difficult clouds with very small optical depths (tau<0.3) and thick ice clouds (tau>1). The good news is that for thin cirrus (0.3algorithms tend to converge. In this first stage of the intercomparison, we present results from a representative case study, compare the retrieved cloud properties with aircraft and satellite measurements, and perform a radiative closure experiment to begin gauging the accuracy of these retrieval algorithms.

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

    NASA Astrophysics Data System (ADS)

    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 < τ < 7 and reff < 50 µm. For global ice clouds, the averaged retrieval uncertainties of τ and reff are 19% and 33%, respectively. For optically thick ice clouds with τ larger than 10, however, the τ and reff retrieval uncertainties can exceed 30% and 50%, respectively. For ice cloud top height (h), the averaged global uncertainty is 0.48 km. Relatively large h uncertainty (e.g., > 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. Aerosol and cloud properties using (A)ATSR: retrieval algorithm and application for aerosol-cloud interaction

    NASA Astrophysics Data System (ADS)

    Sogacheva, Larisa; De Leeuw, Gerrit; Kolmonen, Pekka; Virtanen, Timo H.; Saponaro, Giulia; Kokhanovsky, Alexander

    Aerosols and clouds play an important role in radiative transfer and are key elements of the water and energy cycles. The interactions between aerosol particles and cloud drops are critical to identifying the earth radiation budget. Accurate evaluation of the effects of aerosols and clouds on climate requires global information on aerosol properties which can only be provided using satellite remote sensing. Among the satellite instruments used for aerosol and cloud retrieval is the (Advanced) Along-Track Scanning Radiometer ((A)ATSR) on board the European Space Agency (ESA) satellite ENVISAT (1997-2012). (A)ATSR measures top-of-the-atmosphere (TOA) radiances at 7 wavelengths in the spectral range from the visible to the thermal infrared. It has two views, one at nadir and the other one at 55o forward view; conical scan covers a swath of 512 km. The (A)ATSR resolution is 1 km at nadir. The aerosol retrieval algorithm (dual-view over land and single-view over ocean) was constructed for ATSR-2 data (e.g. Veefkind et al. 1998). The most recent version of ADV (AATSR Dual View) is described in Kolmonen et al. (2013). The (A)ATSR dual-view allows retrieval without prior information about land surface reflectance. A semi-analytical cloud retrieval algorithm using backscattered radiation in 0.4-2.4 μm spectral region has been implemented to ADV for the determination of the optical thickness, the liquid water path, and the effective size of droplets from spectral measurements of the intensity of light reflected from water clouds with large optical thickness. In AacDV ((A)ATSR aerosol and cloud Dual View) aerosol and cloud retrievals are combined. Cloud retrieval starts when cloud tests for aerosol retrieval show the presence of clouds. The algorithm was early introduced in Kokhanovsky et al. (2003). It works well for thick clouds. In addition to cloud properties, cloud top height is estimated using information from both nadir and forward views. AacDV has been successfully

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

    NASA Technical Reports Server (NTRS)

    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.

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

    NASA Technical Reports Server (NTRS)

    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

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

    NASA Astrophysics Data System (ADS)

    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

  15. An Intercomparison of Microphysical Retrieval Algorithms for Upper Tropospheric Ice Clouds

    NASA Technical Reports Server (NTRS)

    Comstock, Jennifer M.; d'Entremont, Robert; DeSlover, Daniel; Mace, Gerald G.; Matrosov, Sergey Y.; McFarlane, Sally A.; Minnis, Patrick; Mitchell, David; Sassen, Kenneth; Shupe, Matthew D.; Turner, David D.; Wang, Zhien

    2006-01-01

    The large horizontal extent, location in the cold upper troposphere, and ice composition make cirrus clouds important modulators of the earth's radiation budget and climate. Cirrus cloud microphysical properties are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. Accurate retrievals of cloud properties are crucial for improving the representation of cloud scale processes in large-scale models and for accurately predicting the earth's future climate. A number of passive and active remote sensing retrieval algorithms exist for estimating the microphysical properties of upper tropospheric clouds. We believe significant progress has been made in the evolution of these retrieval algorithms in the last decade, however, there is room for improvement. Members of the Atmospheric Radiation measurement program (ARM) Cloud properties Working Group are involved in an intercomparison of optical depth(tau), ice water path, and characteristic particle size in clouds retrieved using ground-based instruments. The goals of this intercomparison are to evaluate the accuracy of state-of-the-art algorithms, quantify the uncertainties, and make recommendations for improvement.

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

    NASA Astrophysics Data System (ADS)

    Hamann, U.; Walther, A.; Baum, B.; Bennartz, R.; Bugliaro, L.; Derrien, M.; Francis, P.; 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.

    2014-01-01

    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 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 SEVIRI and the

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

    NASA Astrophysics Data System (ADS)

    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.

  18. Impact of Non-Uniform Beam Filling on Spaceborne Cloud and Precipitation Radar Retrieval Algorithms

    NASA Technical Reports Server (NTRS)

    Tanelli, Simone; Sacco, Gian Franco; Durden, Stephen L.; Haddad, Ziad S.

    2012-01-01

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

  19. Estimation of cloud optical thickness by processing SEVIRI images and implementing a semi analytical cloud property retrieval algorithm

    NASA Astrophysics Data System (ADS)

    Pandey, P.; De Ridder, K.; van Lipzig, N.

    2009-04-01

    Clouds play a very important role in the Earth's climate system, as they form an intermediate layer between Sun and the Earth. Satellite remote sensing systems are the only means to provide information about clouds on large scales. The geostationary satellite, Meteosat Second Generation (MSG) has onboard an imaging radiometer, the Spinning Enhanced Visible and Infrared Imager (SEVIRI). SEVIRI is a 12 channel imager, with 11 channels observing the earth's full disk with a temporal resolution of 15 min and spatial resolution of 3 km at nadir, and a high resolution visible (HRV) channel. The visible channels (0.6 µm and 0.81 µm) and near infrared channel (1.6µm) of SEVIRI are being used to retrieve the cloud optical thickness (COT). The study domain is over Europe covering the region between 35°N - 70°N and 10°W - 30°E. SEVIRI level 1.5 images over this domain are being acquired from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) archive. The processing of this imagery, involves a number of steps before estimating the COT. The steps involved in pre-processing are as follows. First, the digital count number is acquired from the imagery. Image geo-coding is performed in order to relate the pixel positions to the corresponding longitude and latitude. Solar zenith angle is determined as a function of latitude and time. The radiometric conversion is done using the values of offsets and slopes of each band. The values of radiance obtained are then used to calculate the reflectance for channels in the visible spectrum using the information of solar zenith angle. An attempt is made to estimate the COT from the observed radiances. A semi analytical algorithm [Kokhanovsky et al., 2003] is implemented for the estimation of cloud optical thickness from the visible spectrum of light intensity reflected from clouds. The asymptotical solution of the radiative transfer equation, for clouds with large optical thickness, is the basis of

  20. ARM Cloud Retrieval Ensemble Data Set (ACRED)

    SciTech Connect

    Zhao, C; Xie, S; Klein, SA; McCoy, R; Comstock, JM; Delanoë, J; Deng, M; Dunn, M; Hogan, RJ; Jensen, MP; Mace, GG; McFarlane, SA; O’Connor, EJ; Protat, A; Shupe, MD; Turner, D; Wang, Z

    2011-09-12

    This document describes a new Atmospheric Radiation Measurement (ARM) data set, the ARM Cloud Retrieval Ensemble Data Set (ACRED), which is created by assembling nine existing ground-based cloud retrievals of ARM measurements from different cloud retrieval algorithms. The current version of ACRED includes an hourly average of nine ground-based retrievals with vertical resolution of 45 m for 512 layers. The techniques used for the nine cloud retrievals are briefly described in this document. This document also outlines the ACRED data availability, variables, and the nine retrieval products. Technical details about the generation of ACRED, such as the methods used for time average and vertical re-grid, are also provided.

  1. Assessment of Uncertainty in Cloud Radiative Effects and Heating Rates through Retrieval Algorithm Differences: Analysis using 3-years of ARM data at Darwin, Australia

    SciTech Connect

    Comstock, Jennifer M.; Protat, Alain; McFarlane, Sally A.; Delanoe, Julien; Deng, Min

    2013-05-22

    Ground-based radar and lidar observations obtained at the Department of Energy’s Atmospheric Radiation Measurement Program’s Tropical Western Pacific site located in Darwin, Australia are used to retrieve ice cloud properties in anvil and cirrus clouds. Cloud microphysical properties derived from four different retrieval algorithms (two radar-lidar and two radar only algorithms) are compared by examining mean profiles and probability density functions of effective radius (Re), ice water content (IWC), extinction, ice number concentration, ice crystal fall speed, and vertical air velocity. Retrieval algorithm uncertainty is quantified using radiative flux closure exercises. The effect of uncertainty in retrieved quantities on the cloud radiative effect and radiative heating rates are presented. Our analysis shows that IWC compares well among algorithms, but Re shows significant discrepancies, which is attributed primarily to assumptions of particle shape. Uncertainty in Re and IWC translates into sometimes-large differences in cloud radiative effect (CRE) though the majority of cases have a CRE difference of roughly 10 W m-2 on average. These differences, which we believe are primarily driven by the uncertainty in Re, can cause up to 2 K/day difference in the radiative heating rates between algorithms.

  2. Aerosol and cloud retrieval using AATSR

    NASA Astrophysics Data System (ADS)

    Sogacheva, Larisa; Kolmonen, Pekka; Virtanen, Timo; Saponaro, Giulia; Kokhanovsky, Alexander; de Leeuw, Gerrit

    2013-04-01

    Aerosols and clouds play an important role in terrestrial atmospheric dynamics, thermodynamics, chemistry, and radiative transfer and are key elements of the water and energy cycles. Accurate evaluation of the effects of aerosols and clouds on climate requires global information on aerosol properties. Such global information can only be provided using satellite remote sensing. Among the satellite instruments used for aerosol and cloud retrieval is the Advanced Along-Track Scanning Radiometer (AATSR) on board the European Space Agency (ESA) satellite ENVISAT. Many instruments and retrieval techniques have been developed and applied to satellite data to derive cloud data products (Kokhanonsky et al., 2009). However, many problems still remain to be solved. They are mostly related to the usage of homogeneous, single-layered cloud model. Further issues exist for studies of thin clouds, where both cloud inhomogeniety, cloud fraction and the underlying surface bi-directional reflectance must be accounted for in the retrieval process. The aerosol retrieval algorithm (dual-view over land and single-view over ocean) was constructed for ATSR-2 data (e.g. Veefkind et al. 1998). The most recent version of ADV (AATSR Dual View) is described in Kolmenen et al. (2012). The ATSR dual-view allows retrieval without prior information about land surface reflectance. A semi-analytical cloud retrieval algorithm using backscattered radiation in 0.4-2.4 μm spectral region has recently been implemented to ADV for the determination of the optical thickness, the liquid water path, and the effective size of droplets from spectral measurements of the intensity of light reflected from water clouds with large optical thickness. In AacDV (AATSR aerosol and cloud Dual View) aerosol and cloud retrievals are combined. Cloud retrieval starts when cloud tests for aerosol retrieval show the presence of clouds. The algorithm was early introduced in Kokhanovsky et al. (2003). It works well for thick

  3. Retrieving Atmospheric Profiles Data in the Presence of Clouds from Hyperspectral Remote Sensing Data

    NASA Technical Reports Server (NTRS)

    Liu, Xu; Larar, Allen M.; Zhou, Daniel K.; Kizer, Susan H.; Wu, Wan; Barnet, Christopher; Divakarla, Murty; Guo, Guang; Blackwell, Bill; Smith, William L.; Yang, Ping; Gu, Degui

    2011-01-01

    Different methods for retrieving atmospheric profiles in the presence of clouds from hyperspectral satellite remote sensing data will be described. We will present results from the JPSS cloud-clearing algorithm and NASA Langley cloud retrieval algorithm.

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

    NASA Technical Reports Server (NTRS)

    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.

  5. Thermodynamic and cloud parameter retrieval using infrared spectral data

    NASA Technical Reports Server (NTRS)

    Zhou, Daniel K.; Smith, William L., Sr.; Liu, Xu; Larar, Allen M.; Huang, Hung-Lung A.; Li, Jun; McGill, Matthew J.; Mango, Stephen A.

    2005-01-01

    High-resolution infrared radiance spectra obtained from near nadir observations provide atmospheric, surface, and cloud property information. A fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. The retrieval algorithm is presented along with its application to recent field experiment data from the NPOESS Airborne Sounding Testbed - Interferometer (NAST-I). The retrieval accuracy dependence on cloud properties is discussed. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with an accuracy of approximately 1.0 km. Preliminary NAST-I retrieval results from the recent Atlantic-THORPEX Regional Campaign (ATReC) are presented and compared with coincident observations obtained from dropsondes and the nadir-pointing Cloud Physics Lidar (CPL).

  6. Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations: 1. Forward model, error analysis, and information content

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

    An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (τ), effective radius (reff), and cloud top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary data sets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

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

    NASA Technical Reports Server (NTRS)

    Joiner, J.; Vasilkov, A. P.; Gupta, Pawan; Bhartia, P. K.; Veefkind, Pepijn; Sneep, Maarten; deHaan, Johan; Polonsky, Igor; Spurr, Robert

    2011-01-01

    We have developed a relatively simple scheme for simulating retrieved cloud optical centroid pressures (OCP) from satellite solar backscatter observations. We have compared simulator results with those from more detailed retrieval simulators that more fully account for the complex radiative transfer in a cloudy atmosphere. We used this fast simulator to conduct a comprehensive evaluation of cloud OCPs from the two OMI algorithms using collocated data from CloudSat and Aqua MODIS, a unique situation afforded by the A-train formation of satellites. We find that both OMI algorithms perform reasonably well and that the two algorithms agree better with each other than either does with the collocated CloudSat data. This indicates that patchy snow/ice, cloud 3D, and aerosol effects not simulated with the CloudSat data are affecting both algorithms similarly. We note that the collocation with CloudSat occurs mainly on the East side of OMI's swath. Therefore, we are not able to address cross-track biases in OMI cloud OCP retrievals. Our fast simulator may also be used to simulate cloud OCP from output generated by general circulation models (GCM) with appropriate account of cloud overlap. We have implemented such a scheme and plan to compare OMI data with GCM output in the near future.

  8. Global Multispectral Cloud Retrievals from MODIS

    NASA Technical Reports Server (NTRS)

    King, Michael D.

    2003-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4,2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua, and will show characteristics of cloud optical and microphysical properties as a function of latitude for land and ocean separately, and contrast the statistical properties of similar cloud types in various parts of the world.

  9. Thin and thick cloud top height retrieval algorithm with the Infrared Camera and LIDAR of the JEM-EUSO Space Mission

    NASA Astrophysics Data System (ADS)

    Sáez-Cano, G.; Morales de los Ríos, J. A.; del Peral, L.; Neronov, A.; Wada, S.; Rodríguez Frías, M. D.

    2015-03-01

    The origin of cosmic rays have remained a mistery for more than a century. JEM-EUSO is a pioneer space-based telescope that will be located at the International Space Station (ISS) and its aim is to detect Ultra High Energy Cosmic Rays (UHECR) and Extremely High Energy Cosmic Rays (EHECR) by observing the atmosphere. Unlike ground-based telescopes, JEM-EUSO will observe from upwards, and therefore, for a properly UHECR reconstruction under cloudy conditions, a key element of JEM-EUSO is an Atmospheric Monitoring System (AMS). This AMS consists of a space qualified bi-spectral Infrared Camera, that will provide the cloud coverage and cloud top height in the JEM-EUSO Field of View (FoV) and a LIDAR, that will measure the atmospheric optical depth in the direction it has been shot. In this paper we will explain the effects of clouds for the determination of the UHECR arrival direction. Moreover, since the cloud top height retrieval is crucial to analyze the UHECR and EHECR events under cloudy conditions, the retrieval algorithm that fulfills the technical requierements of the Infrared Camera of JEM-EUSO to reconstruct the cloud top height is presently reported.

  10. Ten Years of Cloud Optical and Microphysical Retrievals from MODIS

    NASA Astrophysics Data System (ADS)

    Platnick, S. E.; King, M. D.; Wind, G.; Hubanks, P.; Arnold, G. T.; Amarasinghe, N.

    2009-12-01

    The MODIS cloud optical properties algorithm (MOD06/MYD06 for Terra and Aqua MODIS, respectively) has undergone extensive improvements and enhancements since the launch of Terra. These changes have included: improvements in the cloud thermodynamic phase algorithm; substantial changes in the ice cloud light scattering look up tables (LUTs); a clear-sky restoral algorithm for flagging heavy aerosol and sunglint; greatly improved spectral surface albedo maps, including the spectral albedo of snow by ecosystem; inclusion of pixel-level uncertainty estimates for cloud optical thickness, effective radius, and water path derived for three error sources that includes the sensitivity of the retrievals to solar and viewing geometries. To improve overall retrieval quality, we have also implemented cloud edge removal and partly cloudy detection (using MOD35 cloud mask 250m tests), added a supplementary cloud optical thickness and effective radius algorithm over snow and sea ice surfaces and over the ocean, which enables comparison with the “standard” 2.1 µm effective radius retrieval, and added a multi-layer cloud detection algorithm. We will discuss the status of the MOD06 algorithm and show examples of pixel-level (Level-2) cloud retrievals for selected data granules, as well as gridded (Level-3) statistics, notably monthly means and histograms (1D and 2D, with the latter giving correlations between cloud optical thickness and effective radius, and other cloud product pairs).

  11. Ten Years of Cloud Optical and Microphysical Retrievals from MODIS

    NASA Technical Reports Server (NTRS)

    Platnick, Steven; King, Michael D.; Wind, Galina; Hubanks, Paul; Arnold, G. Thomas; Amarasinghe, Nandana

    2010-01-01

    The MODIS cloud optical properties algorithm (MOD06/MYD06 for Terra and Aqua MODIS, respectively) has undergone extensive improvements and enhancements since the launch of Terra. These changes have included: improvements in the cloud thermodynamic phase algorithm; substantial changes in the ice cloud light scattering look up tables (LUTs); a clear-sky restoral algorithm for flagging heavy aerosol and sunglint; greatly improved spectral surface albedo maps, including the spectral albedo of snow by ecosystem; inclusion of pixel-level uncertainty estimates for cloud optical thickness, effective radius, and water path derived for three error sources that includes the sensitivity of the retrievals to solar and viewing geometries. To improve overall retrieval quality, we have also implemented cloud edge removal and partly cloudy detection (using MOD35 cloud mask 250m tests), added a supplementary cloud optical thickness and effective radius algorithm over snow and sea ice surfaces and over the ocean, which enables comparison with the "standard" 2.1 11m effective radius retrieval, and added a multi-layer cloud detection algorithm. We will discuss the status of the MOD06 algorithm and show examples of pixellevel (Level-2) cloud retrievals for selected data granules, as well as gridded (Level-3) statistics, notably monthly means and histograms (lD and 2D, with the latter giving correlations between cloud optical thickness and effective radius, and other cloud product pairs).

  12. Cloud model bat algorithm.

    PubMed

    Zhou, Yongquan; Xie, Jian; Li, Liangliang; Ma, Mingzhi

    2014-01-01

    Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA) is proposed. This paper focuses on remodeling echolocation model based on living and preying characteristics of bats, utilizing the transformation theory of cloud model to depict the qualitative concept: "bats approach their prey." Furthermore, Lévy flight mode and population information communication mechanism of bats are introduced to balance the advantage between exploration and exploitation. The simulation results show that the cloud model bat algorithm has good performance on functions optimization. PMID:24967425

  13. Physical Validation of GPM Retrieval Algorithms Over Land: An Overview of the Mid-Latitude Continental Convective Clouds Experiment (MC3E)

    NASA Technical Reports Server (NTRS)

    Petersen, Walter A.; Jensen, Michael P.

    2011-01-01

    The joint NASA Global Precipitation Measurement (GPM) -- DOE Atmospheric Radiation Measurement (ARM) Midlatitude Continental Convective Clouds Experiment (MC3E) was conducted from April 22-June 6, 2011, centered on the DOE-ARM Southern Great Plains Central Facility site in northern Oklahoma. GPM field campaign objectives focused on the collection of airborne and ground-based measurements of warm-season continental precipitation processes to support refinement of GPM retrieval algorithm physics over land, and to improve the fidelity of coupled cloud resolving and land-surface satellite simulator models. DOE ARM objectives were synergistically focused on relating observations of cloud microphysics and the surrounding environment to feedbacks on convective system dynamics, an effort driven by the need to better represent those interactions in numerical modeling frameworks. More specific topics addressed by MC3E include ice processes and ice characteristics as coupled to precipitation at the surface and radiometer signals measured in space, the correlation properties of rainfall and drop size distributions and impacts on dual-frequency radar retrieval algorithms, the transition of cloud water to rain water (e.g., autoconversion processes) and the vertical distribution of cloud water in precipitating clouds, and vertical draft structure statistics in cumulus convection. The MC3E observational strategy relied on NASA ER-2 high-altitude airborne multi-frequency radar (HIWRAP Ka-Ku band) and radiometer (AMPR, CoSMIR; 10-183 GHz) sampling (a GPM "proxy") over an atmospheric column being simultaneously profiled in situ by the University of North Dakota Citation microphysics aircraft, an array of ground-based multi-frequency scanning polarimetric radars (DOE Ka-W, X and C-band; NASA D3R Ka-Ku and NPOL S-bands) and wind-profilers (S/UHF bands), supported by a dense network of over 20 disdrometers and rain gauges, all nested in the coverage of a six-station mesoscale rawinsonde

  14. Correction of Rayleigh Scattering Effects in Cloud Optical Thickness Retrievals

    NASA Technical Reports Server (NTRS)

    Wang, Meng-Hua; King, Michael D.

    1997-01-01

    We present results that demonstrate the effects of Rayleigh scattering on the 9 retrieval of cloud optical thickness at a visible wavelength (0.66 Am). The sensor-measured radiance at a visible wavelength (0.66 Am) is usually used to infer remotely the cloud optical thickness from aircraft or satellite instruments. For example, we find that without removing Rayleigh scattering effects, errors in the retrieved cloud optical thickness for a thin water cloud layer (T = 2.0) range from 15 to 60%, depending on solar zenith angle and viewing geometry. For an optically thick cloud (T = 10), on the other hand, errors can range from 10 to 60% for large solar zenith angles (0-60 deg) because of enhanced Rayleigh scattering. It is therefore particularly important to correct for Rayleigh scattering contributions to the reflected signal from a cloud layer both (1) for the case of thin clouds and (2) for large solar zenith angles and all clouds. On the basis of the single scattering approximation, we propose an iterative method for effectively removing Rayleigh scattering contributions from the measured radiance signal in cloud optical thickness retrievals. The proposed correction algorithm works very well and can easily be incorporated into any cloud retrieval algorithm. The Rayleigh correction method is applicable to cloud at any pressure, providing that the cloud top pressure is known to within +/- 100 bPa. With the Rayleigh correction the errors in retrieved cloud optical thickness are usually reduced to within 3%. In cases of both thin cloud layers and thick ,clouds with large solar zenith angles, the errors are usually reduced by a factor of about 2 to over 10. The Rayleigh correction algorithm has been tested with simulations for realistic cloud optical and microphysical properties with different solar and viewing geometries. We apply the Rayleigh correction algorithm to the cloud optical thickness retrievals from experimental data obtained during the Atlantic

  15. Polarimetric Retrievals of Cloud Droplet Number Concentrations

    NASA Astrophysics Data System (ADS)

    Sinclair, K.; Cairns, B.; Hair, J. W.; Hu, Y.; Hostetler, C. A.

    2014-12-01

    Cloud droplet number concentration (CDNC) is one of the most significant microphysical properties of liquid clouds and is essential for the understanding of aerosol-cloud interaction. It impacts radiative forcing, cloud evolution, precipitation, global climate and, through observation, can be used to monitor the cloud albedo effect, or the first indirect effect. The IPCC's Fifth Assessment Report continues to consider aerosol-cloud interactions as one of the largest uncertainties in radiative forcing of climate. The SABOR experiment, which was a NASA-led ship and air campaign off the east coast of the United States during July and August of 2014, provided an opportunity for the Research Scanning Polarimeter (RSP) to develop and cross-validate a new approach of sensing CDNC with the High Spectral Resolution Lidar (HSRL). The RSP is an airborne prototype of the Aerosol Polarimetry Sensor (APS) that was on-board the Glory satellite. It is a scanning sensor that provides high-precision measurements of polarized and full-intensity radiances at multiple angles over a wide spectral range. The distinctive feature of the polarimetric technique is that it does not make any assumption of the liquid water profile within the cloud. The approach involves (1) estimating the droplet size distribution from polarized reflectance observations in the rainbow, (2) using polarized reflectance to estimate above cloud water vapor and total reflectance to find how much near infra-red light is being absorbed in clouds, (3) finding cloud physical thickness from the absorption and cloud top pressure retrievals assuming a saturated mixing ratio for water vapor and (4) determining the cloud droplet number concentration from the physical thickness and droplet size distribution retrievals. An overview of the polarimetric technique will be presented along with the results of applying the new approach to SABOR campaign data. An analysis of the algorithm's performance when compared with the HSRL

  16. Quantifying the Climate-Scale Accuracy of Satellite Cloud Retrievals

    NASA Astrophysics Data System (ADS)

    Roberts, Y.; Wielicki, B. A.; Sun-Mack, S.; Minnis, P.; Liang, L.; Di Girolamo, L.

    2014-12-01

    Instrument calibration and cloud retrieval algorithms have been developed to minimize retrieval errors on small scales. However, measurement uncertainties and assumptions within retrieval algorithms at the pixel level may alias into decadal-scale trends of cloud properties. We first, therefore, quantify how instrument calibration changes could alias into cloud property trends. For a perfect observing system the climate trend accuracy is limited only by the natural variability of the climate variable. Alternatively, for an actual observing system, the climate trend accuracy is additionally limited by the measurement uncertainty. Drifts in calibration over time may therefore be disguised as a true climate trend. We impose absolute calibration changes to MODIS spectral reflectance used as input to the CERES Cloud Property Retrieval System (CPRS) and run the modified MODIS reflectance through the CPRS to determine the sensitivity of cloud properties to calibration changes. We then use these changes to determine the impact of instrument calibration changes on trend uncertainty in reflected solar cloud properties. Secondly, we quantify how much cloud retrieval algorithm assumptions alias into cloud optical retrieval trends by starting with the largest of these biases: the plane-parallel assumption in cloud optical thickness (τC) retrievals. First, we collect liquid water cloud fields obtained from Multi-angle Imaging Spectroradiometer (MISR) measurements to construct realistic probability distribution functions (PDFs) of 3D cloud anisotropy (a measure of the degree to which clouds depart from plane-parallel) for different ISCCP cloud types. Next, we will conduct a theoretical study with dynamically simulated cloud fields and a 3D radiative transfer model to determine the relationship between 3D cloud anisotropy and 3D τC bias for each cloud type. Combining these results provides distributions of 3D τC bias by cloud type. Finally, we will estimate the change in

  17. FAME-C: Retrieval of cloud top pressure with vertically inhomogeneous cloud profiles

    NASA Astrophysics Data System (ADS)

    Henken, Cintia Carbajal; Lindstrot, Rasmus; Filipitsch, Florian; Walther, Andi; Preusker, Rene; Fischer, Jürgen

    2013-05-01

    A synergistic FAME-C (Freie Universität Berlin AATSR-MERIS Cloud Retrieval) algorithm is developed within the frame of the ESA CCI Cloud project. Within FAME-C the ratio of two MERIS measurements (the Oxygen-A absorption channel and a window channel) is used to retrieve cloud top pressure. In case of high, extended clouds the retrieved cloud top pressure is generally too high. This can be understood as an overestimation of extinction in upper cloud layers due to the assumption of vertical homogeneous clouds in the radiative transfer simulations. To include more realistic cloud vertical profiles, one year of data from the Cloud Profiling Radar (CPR) onboard CloudSat has been used to determine average normalized cloud vertical extinction profiles with a fixed pressure thickness for nine cloud types. The nine cloud types are based on the ISCCP COT-CTP classification table. The retrieved cloud top pressure, now using CloudSat cloud profiles in the forward model, is compared to CPR reflectivities as well as the retrieved cloud top pressure using vertically homogeneous cloud profiles. In the first number of cases under examination the overestimation of cloud top pressure, and therefore the bias, is reduced by a large amount when using CloudSat vertical cloud profiles. Another advantage is that no assumption about the cloud geometrical thickness has to be made in the new retrieval. It should be noted that comparisons between FAME-C products and A-train products can only be made at high latitudes where A-train and ENVISAT have overlapping overflights.

  18. View angle dependence of cloud optical thicknesses retrieved by MODIS

    NASA Technical Reports Server (NTRS)

    Marshak, Alexander; Varnai, Tamas

    2005-01-01

    This study examines whether cloud inhomogeneity influences the view angle dependence of MODIS cloud optical thickness (tau) retrieval results. The degree of cloud inhomogeneity is characterized through the local gradient in 11 microns brightness temperature. The analysis of liquid phase clouds in a one year long global dataset of Collection 4 MODIS data reveals that while optical thickness retrievals give remarkably consistent results for all view directions if clouds are homogeneous, they give much higher tau-values for oblique views than for overhead views if clouds are inhomogeneous and the sun is fairly oblique. For solar zenith angles larger than 55deg, the mean optical thickness retrieved for the most inhomogeneous third of cloudy pixels is more than 30% higher for oblique views than for overhead views. After considering a variety of possible scenarios, the paper concludes that the most likely reason for the increase lies in three-dimensional radiative interactions that are not considered in current, one-dimensional retrieval algorithms. Namely, the radiative effect of cloud sides viewed at oblique angles seems to contribute most to the enhanced tau-values. The results presented here will help understand cloud retrieval uncertainties related to cloud inhomogeneity. They complement the uncertainty estimates that will start accompanying MODIS cloud products in Collection 5 and may eventually help correct for the observed view angle dependent biases.

  19. Multilayer cloud detection and retrieval of cloud physical and optical properties from thermal infrared measurements

    NASA Astrophysics Data System (ADS)

    Iwabuchi, H.; Tokoro, Y.; Saito, M.; Putri, N. S.; Katagiri, S.; Sekiguchi, M.

    2015-12-01

    Recent studies using active remote sensing have revealed significant occurrence of multi-layer cloud. Detection of multi-layer cloud is important in passive remote sensing for quality assessment of cloud property retrieval and identification of uncertain retrievals. An algorithm using several thermal infrared (TIR) bands at 6-13.5 micron wavelengths to detect multilayer cloud and retrieve cloud physical and optical properties including cloud thermodynamic phase is developed. This significantly extends applicability of passive remote sensing and improves accuracy of cloud property retrieval. The method uses the split window bands as well as the carbon dioxide and water vapor absorption bands. The forward model uses the two-stream approximation to solve radiative transfer with gaseous absorption treated by the correlated-k distribution method. Brightness temperature errors are evaluated by model-to-model and model-to-measurement comparisons. Top pressure of lower cloud in multi-layer cloud column can be retrieved if the upper cloud optical thickness is less than 6. The optimal estimation method is used to simultaneously infer several cloud properties including water path, effective particle radius and cloud-top pressure. The method is applied to the Moderate Resolution Imaging Spectroradiometer (MODIS) using 10 TIR bands and compared to MODIS operational product and active remote sensing measurements, showing promising results. The TIR method well detects optically thin clouds and retrieve their properties with relatively high accuracy. Particularly, cloud-top of optically thin cloud is estimated well. Multi-layer cloud detection works usually, while the TIR measurements miss very thin cloud that appears near the tropopause. The algorithm will be applied to frequent observation data from a new Japanese geostationary satellite, Himawari-8.

  20. Toward Understanding of Differences in Current Cloud Retrievals of ARM Ground-based Measurements

    SciTech Connect

    Zhao, Chuanfeng; Xie, Shaocheng; Klein, Stephen A.; Protat, Alain; Shupe, Matthew D.; McFarlane, Sally A.; Comstock, Jennifer M.; Delanoe, Julien; Deng, Min; Dunn, Maureen; Hogan, Robin; Huang, Dong; Jensen, Michael; Mace, Gerald G.; McCoy, Renata; O'Conner, Ewan J.; Turner, Dave; Wang, Zhien

    2012-05-30

    Accurate observations of cloud microphysical properties are needed for evaluating and improving the representation of cloud processes in climate models. However, large differences are found in current cloud products retrieved from ground-based remote sensing measurements using various retrieval algorithms. Understanding the differences is an important step to address uncertainties in the cloud retrievals. In this study, an in-depth analysis of nine existing ground-based cloud retrievals using ARM remote sensing measurements is carried out. We place emphasize on boundary layer overcast clouds and high level ice clouds, which are the focus of many current retrieval development efforts due to their radiative importance and relatively simple structure. Large systematic discrepancies in cloud microphysical properties are found in these two types of clouds among the nine cloud retrieval products, particularly for the cloud liquid and ice effective radius. It is shown that most of these large differences have their roots in the retrieval algorithms used by these cloud products, including the retrieval theoretical bases, assumptions, as well as input and constraint parameters. This study suggests the need to further validate current retrieval theories and assumptions and even the development of new retrieval algorithms with more observations under different cloud regimes.

  1. Outcome of the fourth Cloud Retrieval Evaluation Workshop

    NASA Astrophysics Data System (ADS)

    Roebeling, Rob; Baum, Bryan; Bennartz, Ralf; Hamann, Ulrich; Heidinger, Andrew; Fokke Meirink, Jan; Stengel, Martin; Thoss, Anke; Walther, Andi; Watts, Phil

    2014-05-01

    Accurate measurements of global distributions of cloud parameters and their diurnal, seasonal, and inter-annual variations are needed to improve the understanding of the role of clouds in the weather and climate system, and to monitor their time-space variations. Cloud parameters retrieved from satellite observations, such as cloud vertical placement, cloud water path and cloud particle size, play an important role. In order to give weather and climate researchers more confidence in the quality of these retrievals their validity needs to be determined and their error characteristics need to be quantified. The purpose of the 4th Cloud Retrieval Evaluation Workshop (CREW-4), which was held from 3-7 March 2014 in Grainau, Germany, is to enhance our knowledge on state-of-art cloud properties retrievals from passive imaging satellites, and pave the path towards optimising these retrievals for weather and climate applications, such as data assimilation, model analysis, or climate monitoring. An important objective of CREW is to identify and address research questions on level-2 cloud parameter retrievals from operational algorithms and level-3 aggregation methods. To facilitate the above, the workshop participants presented and discussed inter-comparison and validation results of cloud parameter products from different passive sensors (e.g. SEVIRI, MODIS, AVHRR) and/or different operational algorithms (e.g. MODIS, CM-SAF, CIMSS). In addition, recommendations were made to foster commonality for the operational algorithms and their cloud parameter products among the participating operational and research groups, and to develop international partnerships within the Global Energy and Water Cycle Experiment (GEWEX) and the Coordination Group for Meteorological Satellites (CGMS). In parallel breakout sessions in depth discussions were held on: i) cloud parameter retrieval methods, ii) cloud parameter retrieval evaluations, iii) cloud parameter utilization for severe weather

  2. Study of cloud effect on the tropospheric temperature retrievals

    NASA Astrophysics Data System (ADS)

    Navas-Guzmán, F.; Stähli, O.; Kämpfer, N.

    2014-02-01

    In this paper, we address the characterization of clouds and its inclusion in microwave retrievals in order to study its effect on tropospheric temperature profiles measured by TEMPERA radiometer. TEMPERA is the first ground-based microwave radiometer that allows to obtain temperature profiles in the troposphere and stratosphere at the same time. In order to characterize the clouds a multi-instrumental approach has been performed. Cloud base altitudes were detected using ceilometer measurements while the integrated liquid water was measured by TROWARA radiometer. Both instruments are co-located with TEMPERA in Bern (Switzerland). Using this information and a constant Liquid Water Content value inside the cloud a liquid profile is provided to characterize the clouds in the inversion algorithm. Microwave temperature profiles have been obtained incorporating this water liquid profile in the inversion algorithm and also without considering the clouds, in order to asses its effect on the retrievals. The results have been compared with the temperature profiles from radiosondes which are launched twice a day at the aerological station of MeteoSwiss in Payerne (40 km W of Bern). Almost one year of data has been analyzed and 60 non-precipitating cloud cases were studied. The statistical analysis carried out over all the cases evidenced that temperature retrievals improved in most of the cases when clouds were incorporated in the inversion algorithm.

  3. Solar Occultation Retrieval Algorithm Development

    NASA Technical Reports Server (NTRS)

    Lumpe, Jerry D.

    2004-01-01

    This effort addresses the comparison and validation of currently operational solar occultation retrieval algorithms, and the development of generalized algorithms for future application to multiple platforms. initial development of generalized forward model algorithms capable of simulating transmission data from of the POAM II/III and SAGE II/III instruments. Work in the 2" quarter will focus on: completion of forward model algorithms, including accurate spectral characteristics for all instruments, and comparison of simulated transmission data with actual level 1 instrument data for specific occultation events.

  4. MODIS Retrievals of Cloud Optical Thickness and Particle Radius

    NASA Technical Reports Server (NTRS)

    Platnick, S.; King, M. D.; Ackerman, S. A.; Gray, M.; Moody, E.; Arnold, G. T.; Einaudi, Franco (Technical Monitor)

    2000-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) provides an unprecedented opportunity for global cloud studies with 36 spectral bands from the visible through the infrared, and spatial resolution from 250 m to 1 km at nadir. In particular, all solar window bands useful for simultaneous retrievals of cloud optical thickness and particle size (0.67, 0.86, 1.2, 1.6, 2.1, and 3.7 micron bands) are now available on a single satellite instrument/platform for the first time. An operational algorithm for the retrieval of these optical and cloud physical properties (including water path) have been developed for both liquid and ice phase clouds. The product is archived into two categories: pixel-level retrievals at 1 km spatial resolution (referred to as a Level-2 product) and global gridded statistics (Level-3 product). An overview of the MODIS cloud retrieval algorithm and early level-2 and -3 results will be presented. A number of MODIS cloud validation activities are being planned, including the recent Southern Africa Regional Science Initiative 2000 (SAFARI-2000) dry season campaign conducted in August/September 2000. The later part of the experiment concentrated on MODIS validation in the Namibian stratocumulus regime off the southwest coast of Africa. Early retrieval results from this regime will be discussed.

  5. ATOMIC AND MOLECULAR PHYSICS: Retrieval algorithm of quantitative analysis of passive Fourier transform infrared (FTRD) remote sensing measurements of chemical gas cloud from measuring the transmissivity by passive remote Fourier transform infrared

    NASA Astrophysics Data System (ADS)

    Liu, Zhi-Ming; Liu, Wen-Qing; Gao, Ming-Guang; Tong, Jing-Jing; Zhang, Tian-Shu; Xu, Liang; Wei, Xiu-Li

    2008-11-01

    Passive Fourier transform infrared (FTIR) remote sensing measurement of chemical gas cloud is a vital technology. It takes an important part in many fields for the detection of released gases. The principle of concentration measurement is based on the Beer-Lambert law. Unlike the active measurement, for the passive remote sensing, in most cases, the difference between the temperature of the gas cloud and the brightness temperature of the background is usually a few kelvins. The gas cloud emission is almost equal to the background emission, thereby the emission of the gas cloud cannot be ignored. The concentration retrieval algorithm is quite different from the active measurement. In this paper, the concentration retrieval algorithm for the passive FTIR remote measurement of gas cloud is presented in detail, which involves radiative transfer model, radiometric calibration, absorption coefficient calculation, et al. The background spectrum has a broad feature, which is a slowly varying function of frequency. In this paper, the background spectrum is fitted with a polynomial by using the Levenberg-Marquardt method which is a kind of nonlinear least squares fitting algorithm. No background spectra are required. Thus, this method allows mobile, real-time and fast measurements of gas clouds.

  6. Retrievals of cloud optical depth and effective radius from Thin-Cloud Rotating Shadowband Radiometer measurements

    SciTech Connect

    Yin B.; Vogelmann A.; Min Q.; Duan M.; Bartholomew M. J.; Turner D. D.

    2011-12-13

    A Thin-Cloud Rotating Shadowband Radiometer (TCRSR) was developed and deployed in a field test at the Atmospheric Radiation Measurement Climate Research Facility's Southern Great Plains site. The TCRSR measures the forward-scattering lobe of the direct solar beam (i.e., the solar aureole) through an optically thin cloud (optical depth < 8). We applied the retrieval algorithm of Min and Duan (2005) to the TCRSR measurements of the solar aureole to derive simultaneously the cloud optical depth (COD) and cloud drop effective radius (DER), subsequently inferring the cloud liquid-water path (LWP). After careful calibration and preprocessing, our results indicate that the TCRSR is able to retrieve simultaneously these three properties for optically thin water clouds. Colocated instruments, such as the MultiFilter Rotating Shadowband Radiometer (MFRSR), atmospheric emitted radiance interferometer (AERI), and Microwave Radiometer (MWR), are used to evaluate our retrieval results. The relative difference between retrieved CODs from the TCRSR and those from the MFRSR is less than 5%. The distribution of retrieved LWPs from the TCRSR is similar to those from the MWR and AERI. The differences between the TCRSR-based retrieved DERs and those from the AERI are apparent in some time periods, and the uncertainties of the DER retrievals are discussed in detail in this article.

  7. Improving Total Column Ozone Retrievals by Using Cloud Pressures Derived from Raman Scattering in the UV

    NASA Technical Reports Server (NTRS)

    Vasilkov, A.; Joiner, J.; Yang, K.; Bhartia, P. K.

    2004-01-01

    The higher spectral resolution, coverage, and sampling of the Aura satellite ozone monitoring instrument (OMI), as compared with the total ozone mapping spectrometer (TOMS) should allow for improved ozone retrievals, including estimates of tropospheric ozone. By default, the TOMS-like OMI total column ozone algorithm uses climatological cloud-top pressures based on infrared (IR) measurements to estimate the column ozone below the clouds. Alternatively, cloud pressure can be retrieved using atmospheric rotational Raman scattering with OMI. The retrieved cloud pressures should be more consistent with assumptions made in the total ozone algorithm. Here, we use data from the global ozone monitoring experiment (GOME) to estimate total ozone using both the IR-climatological and retrieved cloud pressures. The exceed approximately 15 DU. Use of the UV cloud pressure retrievals leads to a smoother distribution of ozone along a satellite track by reducing small spatial irregularities presumably caused by errors in the climatological cloud pressures.

  8. Interpretation of FRESCO cloud retrievals in case of absorbing aerosol events

    NASA Astrophysics Data System (ADS)

    Wang, P.; Tuinder, O. N. E.; Tilstra, L. G.; de Graaf, M.; Stammes, P.

    2012-10-01

    Cloud and aerosol information is needed in trace gas retrievals from satellite measurements. The Fast REtrieval Scheme for Clouds from the Oxygen A band (FRESCO) cloud algorithm employs reflectance spectra of the O2 A band around 760 nm to derive cloud pressure and effective cloud fraction. In general, clouds contribute more to the O2 A band reflectance than aerosols. Therefore, the FRESCO algorithm does not correct for aerosol effects in the retrievals and attributes the retrieved cloud information entirely to the presence of clouds, and not to aerosols. For events with high aerosol loading, aerosols may have a dominant effect, especially for almost cloud free scenes. We have analysed FRESCO cloud data and Absorbing Aerosol Index (AAI) data from the Global Ozone Monitoring Experiment (GOME-2) instrument on the Metop-A satellite for events with typical absorbing aerosol types, such as volcanic ash, desert dust and smoke. We find that the FRESCO effective cloud fractions are correlated with the AAI data for these absorbing aerosol events and that the FRESCO cloud pressure contains information on aerosol layer pressure. For cloud free scenes, the derived FRESCO cloud pressure is close to the aerosol layer pressure, especially for optically thick aerosol layers. For cloudy scenes, if the strongly absorbing aerosols are located above the clouds, then the retrieved FRESCO cloud pressure may represent the height of the aerosol layer rather than the height of the clouds. Combining FRESCO and AAI data, an estimate for the aerosol layer pressure can be given.

  9. Retrieval of cloud height from SCIAMACHY using oxygen absorption around 630nm

    NASA Astrophysics Data System (ADS)

    Grzegorski, Michael; Deutschmann, Tim; Platt, Ulrich; Wang, Ping; Wagner, Thomas

    2010-05-01

    The SCanning Imaging Absorption spectrometer for Atmospheric ChartographY (SCIAMACHY) on ENVISAT allows measurements of different atmospheric trace gases (e.g. O3, NO2, SO2, CH4, HCHO, CO, BrO, H2O, O2, O4) using the DOAS technique. The HICRU algorithm retrieves cloud height using the spectral analysis of the oxygen absorption around 630nm combined with results of the Monte-Carlo model TRACY-II and a new SCIAMACHY surface albedo database. The results are compared to: 1.) cloud height retrievals of other satellite instruments (MERIS, MODIS) 2.) ISCCP climatology 3.) SCIAMACHY cloud algorithms (SACURA, FRESCO+) 4.) LIDAR/RADAR measurements. For low clouds, the HICRU algorithm retrieves cloud heights more close to the the top, because of the assumption of an appropriate cloud model with a realistic estimation of the scattering inside the cloud. It is also demonstrated, that none the three SCIAMACHY cloud algorithms HICRU, SACURA and FRESCO+ is able to retrieve the top of high clouds because of principal characteristics of the retrieval methods based on oxygen absorption. But oxygen absorptions can provide important additional information on the vertical cloud structure and multiple cloud layers if the method is combined with cloud-top-retrieval using windows in the thermal infrared. An application of these concepts to the GOSAT instrument will be discussed.

  10. Sensitivity of PARASOL multi-angle photopolarimetric aerosol retrievals to cloud contamination

    NASA Astrophysics Data System (ADS)

    Stap, F. A.; Hasekamp, O. P.; Röckmann, T.

    2015-03-01

    An important problem in satellite remote sensing of aerosols is related to the need to perform an adequate cloud screening. If a cloud screening is applied that is not strict enough, the ground scene has the probability of residual cloud cover which causes large errors on the retrieved aerosol parameters. On the other hand, if the cloud-screening procedure is too strict, too many clear sky cases, especially near-cloud scenes, will falsely be flagged cloudy. The detrimental effects of cloud contamination as well as the importance of aerosol cloud interactions that can be studied in these near-cloud scenes call for new approaches to cloud screening. Multi-angle multi-wavelength photopolarimetric measurements have a unique capability to distinguish between scattering by (liquid) cloud droplets and aerosol particles. In this paper the sensitivity of aerosol retrievals from multi-angle photopolarimetric measurements to cloud contamination is investigated and the ability to intrinsically filter the cloud-contaminated scenes based on a goodness-of-fit criteria is evaluated. Hereto, an aerosol retrieval algorithm is applied to a partially clouded over-ocean synthetic data set as well as non-cloud-screened over-ocean POLDER-3/PARASOL observations. It is found that a goodness-of-fit filter, together with a filter on the coarse mode refractive index (mrcoarse > 1.335) and a cirrus screening, adequately rejects the cloud-contaminated scenes. No bias or larger SD are found in the retrieved parameters for this intrinsic cloud filter compared to the parameters retrieved in a priori cloud-screened data set (using MODIS/AQUA cloud masks) of PARASOL observations. Moreover, less high-aerosol load scenes are misinterpreted as cloud contaminated. The retrieved aerosol optical thickness, single scattering albedo and Ångström exponent show good agreement with AERONET observations. Furthermore, the synthetic retrievals give confidence in the ability of the algorithm to correctly

  11. New Multispectral Cloud Retrievals from MODIS

    NASA Technical Reports Server (NTRS)

    King, Michael D.; Platnick, Steven; Tsay, Si-Chee; Ackerman, Steven A.; Menzel, W. Paul; Gray, Mark A.; Moody, Eric G.; Li, Jason Y.; Arnold, G. Thomas

    2001-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun- synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (two bands), 500 m (five bands) and 1000 m (29 bands). In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

  12. MODIS Cloud Optical Property Retrieval Uncertainties Derived from Pixel-Level VNIR/SWIR Radiometric Uncertainties

    NASA Technical Reports Server (NTRS)

    Platnick, S.; Wind, G.; Xiong, X.

    2011-01-01

    Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of optical thickness and effective particle radius for liquid water and ice phase clouds employ a well-known VNIR/ SWIR solar reflectance technique. For this type of algorithm, we evaluate the quantitative uncertainty in simultaneous retrievals of these two cloud parameters to pixel-level radiometric calibration estimates and other fundamental (and tractable) error sources.

  13. New Multispectral Cloud Retrievals from MODIS

    NASA Technical Reports Server (NTRS)

    Platnick, Steven; Tsay, Si-Chee; Ackerman, Steven A.; Gray, Mark A.; Moody, Eric G.; Li, Jason Y.; Arnold, G. T.; King, Michael D. (Technical Monitor)

    2000-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this paper I will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of cloud drops and ice crystals. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

  14. The Aquarius Salinity Retrieval Algorithm

    NASA Technical Reports Server (NTRS)

    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.

  15. A General Uncertainty Quantification Methodology for Cloud Microphysical Property Retrievals

    NASA Astrophysics Data System (ADS)

    Tang, Q.; Xie, S.; Chen, X.; Zhao, C.

    2014-12-01

    The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program provides long-term (~20 years) ground-based cloud remote sensing observations. However, there are large uncertainties in the retrieval products of cloud microphysical properties based on the active and/or passive remote-sensing measurements. To address this uncertainty issue, a DOE Atmospheric System Research scientific focus study, Quantification of Uncertainties in Cloud Retrievals (QUICR), has been formed. In addition to an overview of recent progress of QUICR, we will demonstrate the capacity of an observation-based general uncertainty quantification (UQ) methodology via the ARM Climate Research Facility baseline cloud microphysical properties (MICROBASE) product. This UQ method utilizes the Karhunen-Loéve expansion (KLE) and Central Limit Theorems (CLT) to quantify the retrieval uncertainties from observations and algorithm parameters. The input perturbations are imposed on major modes to take into account the cross correlations between input data, which greatly reduces the dimension of random variables (up to a factor of 50) and quantifies vertically resolved full probability distribution functions of retrieved quantities. Moreover, this KLE/CLT approach has the capability of attributing the uncertainties in the retrieval output to individual uncertainty source and thus sheds light on improving the retrieval algorithm and observations. We will present the results of a case study for the ice water content at the Southern Great Plains during an intensive observing period on March 9, 2000. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  16. FAME-C: cloud property retrieval using synergistic AATSR and MERIS observations

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    A newly developed daytime cloud property retrieval algorithm FAME-C (Freie Universität Berlin AATSR MERIS Cloud) is presented. Synergistic observations from AATSR and MERIS, both mounted on the polar orbiting satellite ENVISAT, are used for cloud screening. For cloudy pixels two main steps are carried out in a sequential form. First, a micro-physical cloud property retrieval is performed using an AATSR near-infrared and visible channel. Cloud phase, cloud optical thickness, and effective radius are retrieved, and subsequently cloud water path is computed. Second, two independent cloud top height products are retrieved. For cloud top temperature AATSR brightness temperatures are used, while for cloud top pressure the MERIS oxygen-A absorption channel is used. Results from the micro-physical retrieval serve as input for the two cloud top height retrievals. Introduced are the AATSR and MERIS forward models and auxiliary data needed in FAME-C. Also, the optimal estimation method with uncertainty estimates, which also provides for uncertainty estimated of the retrieved property on a pixel-basis, is presented. Within the frame of the ESA Climate Change Initiative project first global cloud property retrievals have been conducted for the years 2007-2009. For this time period verification efforts are presented comparing FAME-C cloud micro-physical properties to MODIS-TERRA derived cloud micro-physical properties for four selected regions on the globe. The results show reasonable accuracies between the cloud micro-physical retrievals. Biases are generally smallest for marine stratocumulus clouds; -0.28, 0.41μm and -0.18 g m-2 for cloud optical thickness, effective radius and cloud water path, respectively. This is also true for the root mean square error. Also, both cloud top height products are compared to cloud top heights derived from ground-based cloud radars located at several ARM sites. FAME-C mostly shows an underestimation of cloud top heights when compared to

  17. Cloud Property Retrieval and 3D Radiative Transfer

    NASA Technical Reports Server (NTRS)

    Cahalan, Robert F.

    2003-01-01

    Cloud thickness and photon mean-free-path together determine the scale of "radiative smoothing" of cloud fluxes and radiances. This scale is observed as a change in the spatial spectrum of cloud radiances, and also as the "halo size" seen by off beam lidar such as THOR and WAIL. Such of beam lidar returns are now being used to retrieve cloud layer thickness and vertical scattering extinction profile. We illustrate with recent measurements taken at the Oklahoma ARM site, comparing these to the-dependent 3D simulations. These and other measurements sensitive to 3D transfer in clouds, coupled with Monte Carlo and other 3D transfer methods, are providing a better understanding of the dependence of radiation on cloud inhomogeneity, and to suggest new retrieval algorithms appropriate for inhomogeneous clouds. The international "Intercomparison of 3D Radiation Codes" or I3RC, program is coordinating and evaluating the variety of 3D radiative transfer methods now available, and to make them more widely available. Information is on the Web at: http://i3rc.gsfc.nasa.gov/. Input consists of selected cloud fields derived from data sources such as radar, microwave and satellite, and from models involved in the GEWEX Cloud Systems Studies. Output is selected radiative quantities that characterize the large-scale properties of the fields of radiative fluxes and heating. Several example cloud fields will be used to illustrate. I3RC is currently implementing an "open source" 3d code capable of solving the baseline cases. Maintenance of this effort is one of the goals of a new 3DRT Working Group under the International Radiation Commission. It is hoped that the 3DRT WG will include active participation by land and ocean modelers as well, such as 3D vegetation modelers participating in RAMI.

  18. High Vertically Resolved Atmospheric and Surface/Cloud Parameters Retrieved with Infrared Atmospheric Sounding Interferometer (IASI)

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

    The Joint Airborne IASI Validation Experiment (JAIVEx) was conducted during April 2007 mainly for validation of the IASI on the MetOp satellite. IASI possesses an ultra-spectral resolution of 0.25/cm and a spectral coverage from 645 to 2760/cm. Ultra-spectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. An advanced retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. This physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the cloud-free and/or clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals are achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error < 1 km). Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI observations are obtained and presented. These retrievals will be further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed - Interferometer (NAST-I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The

  19. Satellite retrieval of cloud properties from the O2 A-band for air quality and climate applications

    NASA Astrophysics Data System (ADS)

    Wang, P.; Stammes, P.; van der A, R.

    2009-04-01

    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+. FRESCO+ gives more reliable cloud pressures over partly cloudy pixels. Simulations and comparisons with ground-based radar measurements of clouds shows 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. From ground-based validation (P. Wang et al., Atmos. Chem. Phys., 8, 6565-6576, 2008) it appears that the FRESCO+ cloud retrievals improve the retrieval of tropospheric NO2 as compared to FRESCO. So FRESCO+ contributes to better monitoring of air quality from space. The FRESCO+ cloud algorithm has been applied to GOME and SCIAMACHY measurements since the beginning of the missions. Monthly averaged SCIAMACHY FRESCO+ effective cloud fraction and cloud pressure maps show similar patterns as the ISCCP cloud maps, although there are some differences, due to the different meaning of the cloud products and due to the fact that photons in the O2 A-band penetrate into clouds. The 6-year averaged seasonal cloud maps from SCIAMACHY data have good agreement with the global circulation patterns. Therefore, the FRESCO+ products are not only efficient for cloud correction of trace gas retrievals but also contribute additional information for climate research.

  20. Retrieving optical properties of dusty clouds from MFRSR and Lidar measurements

    NASA Astrophysics Data System (ADS)

    Wang, T.; Huang, J.

    2009-12-01

    Based on the scattering properties of nonspherical dust aerosol, a new method is developed for retrieving dust aerosol optical depths of dusty clouds. The dusty clouds are defined as the hybrid system of dust plume and cloud. The new method is based on transmittance measurements from surface-based instruments Multi-filter Rotating Shadowband Radiometer (MFRSR) and cloud parameters from Lidar measurements. It uses the difference of absorption between dust aerosols and water droplets for distinguishing and estimating the optical properties of dusts and clouds, respectively. This new retrieval method is not sensitive to the retrieval error of cloud properties and the maximum absolute deviations of dust aerosol and total optical depths for thin dusty cloud retrieval algorithm are only 0.056 and 0.1, respectively, for given possible uncertainties. The retrieval error for thick dusty cloud mainly depends on Lidar-based total dusty cloud properties. This algorithm was applied to retrieve the dusty cloud properties by using MFRSR and Lidar Measurements, during 2008 China-US joined dust field campaign (March-June 2008). This presentation will provide the preliminary results.

  1. Interpretation of FRESCO cloud retrievals in case of absorbing aerosol events

    NASA Astrophysics Data System (ADS)

    Wang, P.; Tuinder, O. N. E.; Tilstra, L. G.; Stammes, P.

    2011-12-01

    Cloud and aerosol information is needed in trace gas retrievals from satellite measurements. The Fast REtrieval Scheme for Clouds from the Oxygen A band (FRESCO) cloud algorithm employs reflectance spectra of the O2 A band around 760 nm to derive cloud pressure and effective cloud fraction. In general, clouds contribute more to the O2 A band reflectance than aerosols. Therefore, the FRESCO algorithm does not correct for aerosol effects in the retrievals and attributes the retrieved cloud information entirely to the presence of clouds, and not to aerosols. For events with high aerosol loading, aerosols may have a dominant effect, especially for almost cloud-free scenes. We have analysed FRESCO cloud data and Absorbing Aerosol Index (AAI) data from the Global Ozone Monitoring Experiment (GOME-2) instrument on the Metop-A satellite for events with typical absorbing aerosol types, such as volcanic ash, desert dust and smoke. We find that the FRESCO effective cloud fractions are correlated with the AAI data for these absorbing aerosol events and that the FRESCO cloud pressures contain information on aerosol layer pressure. For cloud-free scenes, the derived FRESCO cloud pressures are close to those of the aerosol layer for optically thick aerosols. For cloudy scenes, if the strongly absorbing aerosols are located above the clouds, then the retrieved FRESCO cloud pressures may represent the height of the aerosol layer rather than the height of the clouds. Combining FRESCO cloud data and AAI, an estimate for the aerosol layer pressure can be given, which can be beneficial for aviation safety and operations in case of e.g. volcanic ash plumes.

  2. Cloud Retrieval Intercomparisons Between SEVIRI, MODIS and VIIRS with CHIMAERA PGE06 Data Collection 6 Products

    NASA Technical Reports Server (NTRS)

    Wind, Galina; Riedi, Jerome; Platnick, Steven; Heidinger, Andrew

    2014-01-01

    The Cross-platform HIgh resolution Multi-instrument AtmosphEric Retrieval Algorithms (CHIMAERA) system allows us to perform MODIS-like cloud top, optical and microphysical properties retrievals on any sensor that possesses a minimum set of common spectral channels. The CHIMAERA system uses a shared-core architecture that takes retrieval method out of the equation when intercomparisons are made. Here we show an example of such retrieval and a comparison of simultaneous retrievals done using SEVIRI, MODIS and VIIRS sensors. All sensor retrievals are performed using CLAVR-x (or CLAVR-x based) cloud top properties algorithm. SEVIRI uses the SAF_NWC cloud mask. MODIS and VIIRS use the IFF-based cloud mask that is a shared algorithm between MODIS and VIIRS. The MODIS and VIIRS retrievals are performed using a VIIRS branch of CHIMAERA that limits available MODIS channel set. Even though in that mode certain MODIS products such as multilayer cloud map are not available, the cloud retrieval remains fully equivalent to operational Data Collection 6.

  3. CloudSat-Constrained Cloud Ice Water Path and Cloud Top Height Retrievals from MHS 157 and 183.3 GHz Radiances

    NASA Technical Reports Server (NTRS)

    Gong, J.; Wu, D. L.

    2014-01-01

    Ice water path (IWP) and cloud top height (ht) are two of the key variables in determining cloud radiative and thermodynamical properties in climate models. Large uncertainty remains among IWP measurements from satellite sensors, in large part due to the assumptions made for cloud microphysics in these retrievals. In this study, we develop a fast algorithm to retrieve IWP from the 157, 183.3+/-3 and 190.3 GHz radiances of the Microwave Humidity Sounder (MHS) such that the MHS cloud ice retrieval is consistent with CloudSat IWP measurements. This retrieval is obtained by constraining the empirical forward models between collocated and coincident measurements of CloudSat IWP and MHS cloud-induced radiance depression (Tcir) at these channels. The empirical forward model is represented by a lookup table (LUT) of Tcir-IWP relationships as a function of ht and the frequency channel.With ht simultaneously retrieved, the IWP is found to be more accurate. The useful range of the MHS IWP retrieval is between 0.5 and 10 kg/sq m, and agrees well with CloudSat in terms of the normalized probability density function (PDF). Compared to the empirical model, current operational radiative transfer models (RTMs) still have significant uncertainties in characterizing the observed Tcir-IWP relationships. Therefore, the empirical LUT method developed here remains an effective approach to retrieving ice cloud properties from the MHS-like microwave channels.

  4. MODIS Cloud Optical Property Retrieval Uncertainties Derived from Pixel-Level Radiometric Error Estimates

    NASA Technical Reports Server (NTRS)

    Platnick, Steven; Wind, Galina; Xiong, Xiaoxiong

    2011-01-01

    MODIS retrievals of cloud optical thickness and effective particle radius employ a well-known VNIR/SWIR solar reflectance technique. For this type of algorithm, we evaluate the uncertainty in simultaneous retrievals of these two parameters to pixel-level (scene-dependent) radiometric error estimates as well as other tractable error sources.

  5. Development, Comparisons and Evaluation of Aerosol Retrieval Algorithms

    NASA Astrophysics Data System (ADS)

    de Leeuw, G.; Holzer-Popp, T.; Aerosol-cci Team

    2011-12-01

    The Climate Change Initiative (cci) of the European Space Agency (ESA) has brought together a team of European Aerosol retrieval groups working on the development and improvement of aerosol retrieval algorithms. The goal of this cooperation is the development of methods to provide the best possible information on climate and climate change based on satellite observations. To achieve this, algorithms are characterized in detail as regards the retrieval approaches, the aerosol models used in each algorithm, cloud detection and surface treatment. A round-robin intercomparison of results from the various participating algorithms serves to identify the best modules or combinations of modules for each sensor. Annual global datasets including their uncertainties will then be produced and validated. The project builds on 9 existing algorithms to produce spectral aerosol optical depth (AOD and Ångström exponent) as well as other aerosol information; two instruments are included to provide the absorbing aerosol index (AAI) and stratospheric aerosol information. The algorithms included are: - 3 for ATSR (ORAC developed by RAL / Oxford university, ADV developed by FMI and the SU algorithm developed by Swansea University ) - 2 for MERIS (BAER by Bremen university and the ESA standard handled by HYGEOS) - 1 for POLDER over ocean (LOA) - 1 for synergetic retrieval (SYNAER by DLR ) - 1 for OMI retreival of the absorbing aerosol index with averaging kernel information (KNMI) - 1 for GOMOS stratospheric extinction profile retrieval (BIRA) The first seven algorithms aim at the retrieval of the AOD. However, each of the algorithms used differ in their approach, even for algorithms working with the same instrument such as ATSR or MERIS. To analyse the strengths and weaknesses of each algorithm several tests are made. The starting point for comparison and measurement of improvements is a retrieval run for 1 month, September 2008. The data from the same month are subsequently used for

  6. Using Cloud Top Pressures Derived from Raman Scattering in the UV for the OMI Total Column Ozone Retrievals

    NASA Technical Reports Server (NTRS)

    Joiner, J.; Vasilkov, A. P.; Bhartia, P. K.; Yang, K.

    2003-01-01

    The OMI cloud pressure product is necessary for accounting for cloud effects on the mission- critical total ozone product. One of the OM1 cloud pressure algorithms uses UV measurements to derive cloud pressures from the high frequency structure of top- of-atmosphere reflectance caused by rotational Raman scattering (RRS) in the atmosphere. RRS results in filling-in of Fraunhofer lines in the backscatter UV spectra (also known as the Ring effect). The magnitude of filling-in of the Fraunhofer lines is roughly proportional to the average number of solar photon scatterings in the atmosphere above the clouds. This property of RRS is used to deduce an effective cloud pressure. The cloud pressure algorithm retrieves the cloud pressure and cloud fraction using a concept of the Mixed Lambert Equivalent Reflectivity (MLER) also used for the TOMS-V8 OM1 total column ozone algorithm. Currently, this OMI total column ozone algorithm utilizes information about cloud top pressures from a climatology based on IR measurements. The IR-derived cloud top pressure is known to be lower than UV-derived cloud top pressure because UV radiation penetrates clouds deeper than IR radiation. That is why the UV-derived cloud pressure may be more consistent withthe total ozone algorithm. We estimate total column ozone differences caused by replacing the cloud pressure climatology with cloud pressures retrieved from GOME data same as used for retrieval of ozone.

  7. System engineering approach to GPM retrieval algorithms

    SciTech Connect

    Rose, C. R.; Chandrasekar, V.

    2004-01-01

    System engineering principles and methods are very useful in large-scale complex systems for developing the engineering requirements from end-user needs. Integrating research into system engineering is a challenging task. The proposed Global Precipitation Mission (GPM) satellite will use a dual-wavelength precipitation radar to measure and map global precipitation with unprecedented accuracy, resolution and areal coverage. The satellite vehicle, precipitation radars, retrieval algorithms, and ground validation (GV) functions are all critical subsystems of the overall GPM system and each contributes to the success of the mission. Errors in the radar measurements and models can adversely affect the retrieved output values. Ground validation (GV) systems are intended to provide timely feedback to the satellite and retrieval algorithms based on measured data. These GV sites will consist of radars and DSD measurement systems and also have intrinsic constraints. One of the retrieval algorithms being studied for use with GPM is the dual-wavelength DSD algorithm that does not use the surface reference technique (SRT). The underlying microphysics of precipitation structures and drop-size distributions (DSDs) dictate the types of models and retrieval algorithms that can be used to estimate precipitation. Many types of dual-wavelength algorithms have been studied. Meneghini (2002) analyzed the performance of single-pass dual-wavelength surface-reference-technique (SRT) based algorithms. Mardiana (2003) demonstrated that a dual-wavelength retrieval algorithm could be successfully used without the use of the SRT. It uses an iterative approach based on measured reflectivities at both wavelengths and complex microphysical models to estimate both No and Do at each range bin. More recently, Liao (2004) proposed a solution to the Do ambiguity problem in rain within the dual-wavelength algorithm and showed a possible melting layer model based on stratified spheres. With the No and Do

  8. Evaluation of Ice cloud retrievals using CloudSat/CALIPSO/MODIS/AIRS and EarthCARE

    NASA Astrophysics Data System (ADS)

    Okamoto, H.; Sato, K.; Hagihara, Y.; Tanaka, K.; Ishimoto, H.; Makino, T.; Nishizawa, T.; Sugimoto, N.

    2014-12-01

    We analyzed characterization of ice water content and ice water path and discussed the uncertainties of these quantities. We developed the retrieval algorithms that use CloudSat and CALIOP on CALIPSO and also the one for CloudSat, CALIOP and MODIS on Aqua. There are several possible sources of uncertainties in the retrieved values. The backscattering properties of ice particles have not been yet fully understood in lidar wavelengths. There are also uncertainties in the retrieval results in radar- or lidar-only detected cloud regions where only one of the two sensors detected clouds. Multiple scattering contribution in space-borne lidar observations has not been fully evaluated too. In order to assess and reduce these uncertainties, we introduced two approaches. Analyses of independent physical quantities based on the same physical ice particle models used in the retrievals of microphysics might be useful in order to test consistency in the ice particle model and its scattering properties. Second approach is to develop a new type of ground-based active sensor system. Concerning the first approach, backscattering color ratio of ice particles was derived from the backscattering coefficient at 532nm and 1064nm for periods before and after the change of the laser tilt angle from 0.3 degrees off nadir to 3 degrees off nadir. Then we examined relationships between the retrieved color ratio and the retrieved microphysics and found the relations agreed with the theoretically estimated ones.For the second approach, Multi-Field of view Multiple Scattering Polarization Lidar has been developed to resolve the angular dependence of backscattering and depolarization ratio and has been employed to evaluate the uncertainties in the retrievals. We performed global evaluation of ice microphysical properties and examined relationships between ice microphysics and ice super saturation information from AIRS on Aqua. Finally we introduced the JAXA-ESA satellite mission EarthCARE that

  9. Cloud Property Retrieval Products for Graciosa Island, Azores

    SciTech Connect

    Dong, Xiquan

    2014-05-05

    The motivation for developing this product was to use the Dong et al. 1998 method to retrieve cloud microphysical properties, such as cloud droplet effective radius, cloud droplets number concentration, and optical thickness. These retrieved properties have been used to validate the satellite retrieval, and evaluate the climate simulations and reanalyses. We had been using this method to retrieve cloud microphysical properties over ARM SGP and NSA sites. We also modified the method for the AMF at Shouxian, China and some IOPs, e.g. ARM IOP at SGP in March, 2000. The ARSCL data from ARM data archive over the SGP and NSA have been used to determine the cloud boundary and cloud phase. For these ARM permanent sites, the ARSCL data was developed based on MMCR measurements, however, there were no data available at the Azores field campaign. We followed the steps to generate this derived product and also include the MPLCMASK cloud retrievals to determine the most accurate cloud boundaries, including the thin cirrus clouds that WACR may under-detect. We use these as input to retrieve the cloud microphysical properties. Due to the different temporal resolutions of the derived cloud boundary heights product and the cloud properties product, we submit them as two separate netcdf files.

  10. Final Report: Operational Retrieval of Cloud Microphysical Properties Using Combined Measurements by Diverse Instruments

    SciTech Connect

    Richard T. Austin

    2008-06-30

    The report on the final phase of the project describes improvements in the ice and liquid cloud retrieval algorithms due to the use of three-parameter particle size distributions in which all three parameters may vary with height, testing of the improved retrievals by comparisons of measured and calculated fluxes, and further improvement in liquid retrievals obtained by adding liquid water path information from the microwave radiometer to radar and visible optical depth information.

  11. Lidar cirrus cloud retrieval - methodology and applications

    NASA Astrophysics Data System (ADS)

    Larroza, Eliane; Keckhut, Philippe; Nakaema, Walter; Brogniez, Gérard; Dubuisson, Philippe; Pelon, Jacques; Duflot, Valentin; Marquestaut, Nicolas; Payen, Guillaume

    2016-04-01

    In the last decades numerical modeling has experimented sensitive improvements on accuracy and capability for climate predictions. In the same time it has demanded the reduction of uncertainties related with the respective input parameters. In this context, high altitude clouds (cirrus) have attracted special attention for their role as radiative forcing. Also such clouds are associated with the vertical transport of water vapor from the surface to upper troposphere/lower stratosphere (URLS) in form of ice crystals with variability of concentration and morphology. Still cirrus formation can occur spatially and temporally in great part of the globe due to horizontal motion of air masses and circulations. Determining accurately the physical properties of cirrus clouds still represents a challenge. Especially the so-called subvisible cirrus clouds (optical depth inferior to 0.03) are invisible for space-based passive observations. On the other hand, ground based active remote sensing as lidar can be used to suppress such deficiency. Lidar signal can provide spatial and temporal high resolution to characterize physically (height, geometric thickness, mean temperature) and optically (optical depth, extinction-to-scattering ratio or lidar ratio, depolarization ratio) the cirrus clouds. This report describes the evolution of the methodology initially adopted to retrieval systematically the lidar ratio and the subsequent application on case studies and climatology on the tropical sites of the globe - São Paulo, Brazil (23.33 S, 46.44 W) and OPAR observatory at Ille de La Réunion (21.07 S, 55.38 W). Also is attempting a synergy between different instrumentations and lidar measurements: a infrared radiometer to estimate the kind of ice crystals compounding the clouds; CALIPSO satellite observations and trajectory model (HYSPLIT) for tracking air masses potentially responsible for the horizontal displacement of cirrus. This last approach is particularly interesting to

  12. Synergy of stereo cloud top height and ORAC optimal estimation cloud retrieval: evaluation and application to AATSR

    NASA Astrophysics Data System (ADS)

    Fisher, Daniel; Poulsen, Caroline A.; Thomas, Gareth E.; Muller, Jan-Peter

    2016-03-01

    In this paper we evaluate the impact on the cloud parameter retrievals of the ORAC (Optimal Retrieval of Aerosol and Cloud) algorithm following the inclusion of stereo-derived cloud top heights as a priori information. This is performed in a mathematically rigorous way using the ORAC optimal estimation retrieval framework, which includes the facility to use such independent a priori information. Key to the use of a priori information is a characterisation of their associated uncertainty. This paper demonstrates the improvements that are possible using this approach and also considers their impact on the microphysical cloud parameters retrieved. The Along-Track Scanning Radiometer (AATSR) instrument has two views and three thermal channels, so it is well placed to demonstrate the synergy of the two techniques. The stereo retrieval is able to improve the accuracy of the retrieved cloud top height when compared to collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), particularly in the presence of boundary layer inversions and high clouds. The impact of the stereo a priori information on the microphysical cloud properties of cloud optical thickness (COT) and effective radius (RE) was evaluated and generally found to be very small for single-layer clouds conditions over open water (mean RE differences of 2.2 (±5.9) microns and mean COD differences of 0.5 (±1.8) for single-layer ice clouds over open water at elevations of above 9 km, which are most strongly affected by the inclusion of the a priori).

  13. Iterative phase retrieval algorithms. I: optimization.

    PubMed

    Guo, Changliang; Liu, Shi; Sheridan, John T

    2015-05-20

    Two modified Gerchberg-Saxton (GS) iterative phase retrieval algorithms are proposed. The first we refer to as the spatial phase perturbation GS algorithm (SPP GSA). The second is a combined GS hybrid input-output algorithm (GS/HIOA). In this paper (Part I), it is demonstrated that the SPP GS and GS/HIO algorithms are both much better at avoiding stagnation during phase retrieval, allowing them to successfully locate superior solutions compared with either the GS or the HIO algorithms. The performances of the SPP GS and GS/HIO algorithms are also compared. Then, the error reduction (ER) algorithm is combined with the HIO algorithm (ER/HIOA) to retrieve the input object image and the phase, given only some knowledge of its extent and the amplitude in the Fourier domain. In Part II, the algorithms developed here are applied to carry out known plaintext and ciphertext attacks on amplitude encoding and phase encoding double random phase encryption systems. Significantly, ER/HIOA is then used to carry out a ciphertext-only attack on AE DRPE systems. PMID:26192504

  14. Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC)

    NASA Astrophysics Data System (ADS)

    Meyer, Kerry; Yang, Yuekui; Platnick, Steven

    2016-04-01

    This paper presents an investigation of the expected uncertainties of a single-channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud-temperature-threshold-based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC Sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single-channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single-channel COT retrieval is feasible for EPIC. For ice clouds, single-channel retrieval errors are minimal (< 2 %) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10 %, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

  15. Impact of spatial resolution on cirrus infrared satellite retrievals in the presence of cloud heterogeneity

    NASA Astrophysics Data System (ADS)

    Fauchez, T.; Platnick, S. E.; Meyer, K.; Zhang, Z.; Cornet, C.; Szczap, F.; Dubuisson, P.

    2015-12-01

    Cirrus clouds are an important part of the Earth radiation budget but an accurate assessment of their role remains highly uncertain. Cirrus optical properties such as Cloud Optical Thickness (COT) and ice crystal effective particle size are often retrieved with a combination of Visible/Near InfraRed (VNIR) and ShortWave-InfraRed (SWIR) reflectance channels. Alternatively, Thermal InfraRed (TIR) techniques, such as the Split Window Technique (SWT), have demonstrated better accuracy for thin cirrus effective radius retrievals with small effective radii. However, current global operational algorithms for both retrieval methods assume that cloudy pixels are horizontally homogeneous (Plane Parallel Approximation (PPA)) and independent (Independent Pixel Approximation (IPA)). The impact of these approximations on ice cloud retrievals needs to be understood and, as far as possible, corrected. Horizontal heterogeneity effects in the TIR spectrum are mainly dominated by the PPA bias that primarily depends on the COT subpixel heterogeneity; for solar reflectance channels, in addition to the PPA bias, the IPA can lead to significant retrieval errors due to a significant photon horizontal transport between cloudy columns, as well as brightening and shadowing effects that are more difficult to quantify. Furthermore TIR retrievals techniques have demonstrated better retrieval accuracy for thin cirrus having small effective radii over solar reflectance techniques. The TIR range is thus particularly relevant in order to characterize, as accurately as possible, thin cirrus clouds. Heterogeneity effects in the TIR are evaluated as a function of spatial resolution in order to estimate the optimal spatial resolution for TIR retrieval applications. These investigations are performed using a cirrus 3D cloud generator (3DCloud), a 3D radiative transfer code (3DMCPOL), and two retrieval algorithms, namely the operational MODIS retrieval algorithm (MOD06) and a research-level SWT algorithm.

  16. Information content of ozone retrieval algorithms

    NASA Technical Reports Server (NTRS)

    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.

  17. Cloud, Aerosol, and Volcanic Ash Retrievals Using ASTR and SLSTR with ORAC

    NASA Astrophysics Data System (ADS)

    McGarragh, Gregory; Poulsen, Caroline; Povey, Adam; Thomas, Gareth; Christensen, Matt; Sus, Oliver; Schlundt, Cornelia; Stapelberg, Stefan; Stengel, Martin; Grainger, Don

    2015-12-01

    The Optimal Retrieval of Aerosol and Cloud (ORAC) is a generalized optimal estimation system that retrieves cloud, aerosol and volcanic ash parameters using satellite imager measurements in the visible to infrared. Use of the same algorithm for different sensors and parameters leads to consistency that facilitates inter-comparison and interaction studies. ORAC currently supports ATSR, AVHRR, MODIS and SEVIRI. In this proceeding we discuss the ORAC retrieval algorithm applied to ATSR data including the retrieval methodology, the forward model, uncertainty characterization and discrimination/classification techniques. Application of ORAC to SLSTR data is discussed including the additional features that SLSTR provides relative to the ATSR heritage. The ORAC level 2 and level 3 results are discussed and an application of level 3 results to the study of cloud/aerosol interactions is presented.

  18. FAME-C: cloud property retrieval using synergistic AATSR and MERIS observations

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

    A newly developed daytime cloud property retrieval algorithm, FAME-C (Freie Universität Berlin AATSR MERIS Cloud), is presented. Synergistic observations from the Advanced Along-Track Scanning Radiometer (AATSR) and the Medium Resolution Imaging Spectrometer (MERIS), both mounted on the polar-orbiting Environmental Satellite (Envisat), are used for cloud screening. For cloudy pixels two main steps are carried out in a sequential form. First, a cloud optical and microphysical property retrieval is performed using an AATSR near-infrared and visible channel. Cloud phase, cloud optical thickness, and effective radius are retrieved, and subsequently cloud water path is computed. Second, two cloud top height products are retrieved based on independent techniques. For cloud top temperature, measurements in the AATSR infrared channels are used, while for cloud top pressure, measurements in the MERIS oxygen-A absorption channel are used. Results from the cloud optical and microphysical property retrieval serve as input for the two cloud top height retrievals. Introduced here are the AATSR and MERIS forward models and auxiliary data needed in FAME-C. Also, the optimal estimation method, which provides uncertainty estimates of the retrieved property on a pixel basis, is presented. Within the frame of the European Space Agency (ESA) Climate Change Initiative (CCI) project, the first global cloud property retrievals have been conducted for the years 2007-2009. For this time period, verification efforts are presented, comparing, for four selected regions around the globe, FAME-C cloud optical and microphysical properties to cloud optical and microphysical properties derived from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra satellite. The results show a reasonable agreement between the cloud optical and microphysical property retrievals. Biases are generally smallest for marine stratocumulus clouds: -0.28, 0.41 μm and -0.18 g m-2 for

  19. Influence of 3D Effects on 1D Aerosol Retrievals in Synthetic, Partially Clouded Scenes

    NASA Astrophysics Data System (ADS)

    Stap, F. A.; Hasekamp, O. P.; Emde, C.

    2014-12-01

    Most satellite measurements of the microphysical and radiative properties of aerosol near clouds are either strictly screened for, or hindered by sub-pixel cloud contamination. This may change with the advent of a new generation of aerosol retrieval algorithms,intended for multi-angle, multi-wavelength photo-polarimetric instruments such as POLDER3on board PARASOL, which show ability to separate between aerosol and cloud particles.In order to obtain the required computational efficiency these algorithms typically make use of 1D radiative transfer models and are thus unable to account for the 3D effects that occur in actual, partially clouded scenes.Here, we apply an aerosol retrieval algorithm, which employs a 1D radiative transfer code and the independent pixel approximation, on synthetic, 3D, partially cloudedscenes calculated with the Monte Carlo radiative transfer code MYSTIC.The influence of the 3D effects due to clouds on the retrieved microphysical and optical aerosol properties is presented and the ability of the algorithm to retrieve these properties in partially clouded scenes will be discussed.

  20. Retrieve Optically Thick Ice Cloud Microphysical Properties by Using Airborne Dual-Wavelength Radar Measurements

    NASA Technical Reports Server (NTRS)

    Wang, Zhien; Heymsfield, Gerald M.; Li, Lihua; Heymsfield, Andrew J.

    2005-01-01

    An algorithm to retrieve optically thick ice cloud microphysical property profiles is developed by using the GSFC 9.6 GHz ER-2 Doppler Radar (EDOP) and the 94 GHz Cloud Radar System (CRS) measurements aboard the high-altitude ER-2 aircraft. In situ size distribution and total water content data from the CRYSTAL-FACE field campaign are used for the algorithm development. To reduce uncertainty in calculated radar reflectivity factors (Ze) at these wavelengths, coincident radar measurements and size distribution data are used to guide the selection of mass-length relationships and to deal with the density and non-spherical effects of ice crystals on the Ze calculations. The algorithm is able to retrieve microphysical property profiles of optically thick ice clouds, such as, deep convective and anvil clouds, which are very challenging for single frequency radar and lidar. Examples of retrieved microphysical properties for a deep convective clouds are presented, which show that EDOP and CRS measurements provide rich information to study cloud structure and evolution. Good agreement between IWPs derived from an independent submillimeter-wave radiometer, CoSSIR, and dual-wavelength radar measurements indicates accuracy of the IWC retrieved from the two-frequency radar algorithm.

  1. A Comparison of Cirrus Clouds Retrieved From POLDER-3/PARASOL and MODIS/Aqua

    NASA Astrophysics Data System (ADS)

    Zhang, Z.; Yang, P.; Riedi, J.; Kattawar, G.

    2007-12-01

    MODIS on board Aqua and POLDER-3 on board PARASOL are two key instruments in the A-Train constellation of satellites. MODIS has 36 spectral bands with wavelength ranging from 0.41 to 14.5 μm, but makes measurement at only one direction without information about polarization. POLDER performs multidirectional measurements, of both reflectance and polarization, at nine spectral channels (from 443 to 1020 nm). The two instruments offer different, and somehow complementary, advantages for the remote sensing of microphysical and optical properties of cirrus clouds. In this study, a comparison of cirrus clouds retrieved from the two instruments is made to obtain understanding of the possibility, advantages and limitations of synergetic retrieval. First, the comparison is made between the single scattering properties of "Inhomogeneous Hexagonal Monocrystals" (IHM) used in POLDER retrieval algorithm and the ice-crystal ensemble model used for MODIS. Substantial differences are found in the scattering phase matrix. Co-located cloud mask and cloud top height retrievals are compared, with the emphasis on high and thin cirrus clouds. The optical thicknesses of cirrus clouds retrieved by POLDER are compared with those by MODIS, with and without the constraint that the cloud effective particle size retrieved by MODIS must be similar to that of IHM.

  2. Progress in Understanding the Impacts of 3-D Cloud Structure on MODIS Cloud Property Retrievals for Marine Boundary Layer Clouds

    NASA Technical Reports Server (NTRS)

    Zhang, Zhibo; Werner, Frank; Miller, Daniel; Platnick, Steven; Ackerman, Andrew; DiGirolamo, Larry; Meyer, Kerry; Marshak, Alexander; Wind, Galina; Zhao, Guangyu

    2016-01-01

    Theory: A novel framework based on 2-D Tayler expansion for quantifying the uncertainty in MODIS retrievals caused by sub-pixel reflectance inhomogeneity. (Zhang et al. 2016). How cloud vertical structure influences MODIS LWP retrievals. (Miller et al. 2016). Observation: Analysis of failed MODIS cloud property retrievals. (Cho et al. 2015). Cloud property retrievals from 15m resolution ASTER observations. (Werner et al. 2016). Modeling: LES-Satellite observation simulator (Zhang et al. 2012, Miller et al. 2016).

  3. Dual-field-of-view Raman lidar measurements for the retrieval of cloud microphysical properties.

    PubMed

    Schmidt, Jörg; Wandinger, Ulla; Malinka, Aleksey

    2013-04-10

    Dual-field-of-view Raman lidar measurements, detecting Raman-scattered light with two fields of view simultaneously, are used for the first time to retrieve cloud microphysical properties. The measurements are performed with the Multiwavelength Atmospheric Raman Lidar for Temperature, Humidity, and Aerosol Profiling (MARTHA) at the Leibniz Institute for Tropospheric Research in Leipzig, Germany. Light that is scattered in forward direction by cloud droplets and inelastically backscattered by N2 molecules is detected. A forward iterative algorithm uses the measured signals to derive profiles of the effective cloud droplet radius, extinction coefficient, and liquid-water content of the investigated clouds. The setup, algorithm, error analysis, and a measurement example are presented. The obtained liquid-water path is validated by observations with a microwave radiometer. With the capability to retrieve aerosol properties as well as cloud microphysical properties, the Raman lidar MARTHA is an ideal tool for studies of the aerosol indirect effect. PMID:23670751

  4. An integrated approach toward the incorporation of clouds in the temperature retrievals from microwave measurements

    NASA Astrophysics Data System (ADS)

    Navas-Guzmán, F.; Stähli, O.; Kämpfer, N.

    2014-06-01

    In this paper, we address the characterization of clouds and its inclusion in microwave retrievals in order to study its effect on tropospheric temperature profiles measured by TEMPERA radiometer. TEMPERA is the first ground-based microwave radiometer that makes it possible to obtain temperature profiles in the troposphere and stratosphere at the same time. In order to characterize the clouds a multi-instrumental approach has been adopted. Cloud base altitudes were detected using ceilometer measurements while the integrated liquid water was measured by TROWARA radiometer. Both instruments are co-located with TEMPERA in Bern (Switzerland). Using this information and a constant Liquid Water Content value inside the cloud a liquid profile is provided to characterize the clouds in the inversion algorithm. Microwave temperature profiles have been obtained incorporating this water liquid profile in the inversion algorithm and also without considering the clouds, in order to assess its effect on the retrievals. The results have been compared with the temperature profiles from radiosondes which are launched twice a day at the aerological station of MeteoSwiss in Payerne (40 km W of Bern). Almost 1 year of data have been analysed and 60 non-precipitating cloud cases were studied. The statistical analysis carried out over all the cases evidenced that temperature retrievals improved in most of the cases when clouds were incorporated in the inversion algorithm.

  5. Above-Cloud Precipitable Water Retrievals using the MODIS 0.94 micron Band with Applications for Multi-Layer Cloud Detection

    NASA Technical Reports Server (NTRS)

    Platnick, S.; Wind, G.

    2004-01-01

    In order to perform satellite retrievals of cloud properties, it is important to account for the effect of the above-cloud atmosphere on the observations. The solar bands used in the operational MODIS Terra and Aqua cloud optical and microphysical algorithms (visible, NIR, and SWIR spectral windows) are primarily affected by water vapor, and to a lesser extent by well-mixed gases. For water vapor, the above-cloud column amount, or precipitable water, provides adequate information for an atmospheric correction; details of the vertical vapor distribution are not typically necessary for the level of correction required. Cloud-top pressure has a secondary effect due to pressure broadening influences. For well- mixed gases, cloud-top pressure is also required for estimates of above-cloud abundances. We present a method for obtaining above-cloud precipitable water over dark Ocean surfaces using the MODIS 0.94 pm vapor absorption band. The retrieval includes an iterative procedure for establishing cloud-top temperature and pressure, and is useful for both single layer water and ice clouds. Knowledge of cloud thermodynamic phase is fundamental in retrieving cloud optical and microphysical properties. However, in cases of optically thin cirrus overlapping lower water clouds, the concept of a single unique phase is ill- defined and depends, at least, on the spectral region of interest. We will present a method for multi-layer and multi-phase cloud detection which uses above-cloud precipitable water retrievals along with several existing MODIS operational cloud products (cloud-top pressure derived from a C02 slicing algorithm, IR and SWIR phase retrievals). Results are catagorized by whether the radiative signature in the MODIS solar bands is primarily that of a water cloud with ice cloud contamination, or visa-versa. Examples in polar and mid-latitude regions will be shown.

  6. Towards a true aerosol-and-cloud retrieval scheme

    NASA Astrophysics Data System (ADS)

    Thomas, Gareth; Poulsen, Caroline; Povey, Adam; McGarragh, Greg; Jerg, Matthias; Siddans, Richard; Grainger, Don

    2014-05-01

    The Optimal Retrieval of Aerosol and Cloud (ORAC) - formally the Oxford-RAL Aerosol and Cloud retrieval - offers a framework that can provide consistent and well characterised properties of both aerosols and clouds from a range of imaging satellite instruments. Several practical issues stand in the way of achieving the potential of this combined scheme however; in particular the sometimes conflicting priorities and requirements of aerosol and cloud retrieval problems, and the question of the unambiguous identification of aerosol and cloud pixels. This presentation will present recent developments made to the ORAC scheme for both aerosol and cloud, and detail how these are being integrated into a single retrieval framework. The implementation of a probabilistic method for pixel identification will also be presented, for both cloud detection and aerosol/cloud type selection. The method is based on Bayesian methods applied the optimal estimation retrieval output of ORAC and is particularly aimed at providing additional information in the so-called "twilight zone", where pixels can't be unambiguously identified as either aerosol or cloud and traditional cloud or aerosol products do not provide results.

  7. Retrieval Of Cloud Pressure And Chlorophyll Content Using Raman Scattering In GOME Ultraviolet Spectra

    NASA Technical Reports Server (NTRS)

    Atlas, Robert (Technical Monitor); Joiner, Joanna; Vasikov, Alexander; Flittner, David; Gleason, James; Bhartia, P. K.

    2002-01-01

    Reliable cloud pressure estimates are needed for accurate retrieval of ozone and other trace gases using satellite-borne backscatter ultraviolet (buv) instruments such as the global ozone monitoring experiment (GOME). Cloud pressure can be derived from buv instruments by utilizing the properties of rotational-Raman scattering (RRS) and absorption by O2-O2. In this paper we estimate cloud pressure from GOME observations in the 355-400 nm spectral range using the concept of a Lambertian-equivalent reflectivity (LER) surface. GOME has full spectral coverage in this range at relatively high spectral resolution with a very high signal-to-noise ratio. This allows for much more accurate estimates of cloud pressure than were possible with its predecessors SBUV and TOMS. We also demonstrate the potential capability to retrieve chlorophyll content with full-spectral buv instruments. We compare our retrieved LER cloud pressure with cloud top pressures derived from the infrared ATSR instrument on the same satellite. The findings confirm results from previous studies that showed retrieved LER cloud pressures from buv observations are systematically higher than IR-derived cloud-top pressure. Simulations using Mie-scattering radiative transfer algorithms that include O2-O2 absorption and RRS show that these differences can be explained by increased photon path length within and below cloud.

  8. Integrating retrieved cloud information with model simulation to extend usability of tracer gas retrievals.

    NASA Astrophysics Data System (ADS)

    Tan, Q.; Prinn, R.

    2007-12-01

    We have explored the possibility of using retrieved cloud information to extend the usability of trace gas concentration retrievals from satellites, since choosing only cloud-free retrievals might lead to a bias in their source-sink estimates using inverse modeling, i.e. the geographic locations of cloud-free or cloudy regions and trace gas source or sink regions might be correlated. We used methane retrievals (IMAP) and cloud retrievals (FRESCO) from SCIAMACHY as an example for this study, and assumed agreement between 3D model simulations (MATCH) and cloud-free satellite retrievals as a proxy for defining usability of satellite data. We found that when the pixel is very cloudy (f>0.7), the model simulation, which is integrated with retrieved cloud top height and cloud fraction data, yields similar agreement with observations as obtained with cloud-free pixels (f=0). The addition of cloudy pixel data significantly extends the spatial and temporal coverage of methane retrievals that can be used in source and sink studies. We also tried to overlay the MODIS aerosol retrievals with SCIAMACHY methane data to test the impact of aerosols on trace gas retrievals. Since these two retrievals are somewhat orthogonal, i.e. stronger MODIS aerosol signals over the ocean, and stronger SCIAMACHY methane signals over the land, we have not found a significant correlation between these two retrievals. Other possible reasons for this result could be the different passing times of the two satellites and the wave length differences of the two retrievals.

  9. MODIS Collection 6 Shortwave-Derived Cloud Phase Discrimination Algorithm and comparisons with CALIOP and POLDER

    NASA Astrophysics Data System (ADS)

    Marchant, B.; Platnick, S. E.; Arnold, T.; Meyer, K.; Riedi, J.

    2014-12-01

    Cloud thermodynamic phase (ice or liquid) discrimination is an important first step for cloud retrievals from passive sensors such as MODIS (Moderate-Resolution Imaging Spectroradiometer). Because ice and liquid phase clouds have very different scattering and absorbing properties, an incorrect cloud phase decision can lead to substantial uncertainties in the cloud optical and microphysical property products such as cloud optical thickness or effective particle radius. Furthermore, it is well-established that ice and liquid clouds have different impacts on the Earth's energy budget and hydrological cycle, thus accurately monitoring the spatial and temporal distribution of these clouds is of continued importance. For MODIS Collection 6 (C6), the shortwave-derived cloud thermodynamic phase algorithm used by the optical and microphysical property retrievals has been completely rewritten to improve the phase discrimination skill for a variety of cloudy scenes (e.g., thin/thick clouds, over ocean/land/desert/snow/ice surface, etc). To evaluate the performance of the C6 cloud phase algorithm, extensive granule-level and global comparisons have been conducted against the heritage C5 algorithm, CALIOP, and POLDER. A wholesale improvement is seen for C6 compared to C5. We will present an overview of the MODIS C6 cloud phase algorithm updates and their impacts on cloud retrieval statistics, as well as ongoing efforts to continue algorithm improvement.

  10. Validation of AIRS/AMSU Cloud Retrievals Using MODIS Cloud Analyses

    NASA Technical Reports Server (NTRS)

    Molnar, Gyula I.; Susskind, Joel

    2005-01-01

    The AIRS/AMSU (flying on the EOS-AQUA satellite) sounding retrieval methodology allows for the retrieval of key atmospheric/surface parameters under partially cloudy conditions (Susskind et al.). In addition, cloud parameters are also derived from the AIRS/AMSU observations. Within each AIRS footprint, cloud parameters at up to 2 cloud layers are determined with differing cloud top pressures and effective (product of infrared emissivity at 11 microns and physical cloud fraction) cloud fractions. However, so far the AIRS cloud product has not been rigorously evaluated/validated. Fortunately, collocated/coincident radiances measured by MODIS/AQUA (at a much lower spectral resolution but roughly an order of-magnitude higher spatial resolution than that of AIRS) are used to determine analogous cloud products from MODIS. This allows us for a rather rare and interesting possibility: the intercomparisons and mutual validation of imager vs. sounder-based cloud products obtained from the same satellite positions. First, we present results of small-scale (granules) instantaneous intercomparisons. Next, we will evaluate differences of temporally averaged (monthly) means as well as the representation of inter-annual variability of cloud parameters as presented by the two cloud data sets. In particular, we present statistical differences in the retrieved parameters of cloud fraction and cloud top pressure. We will investigate what type of cloud systems are retrieved most consistently (if any) with both retrieval schemes, and attempt to assess reasons behind statistically significant differences.

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

    NASA Astrophysics Data System (ADS)

    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 (< 5%) and precision (< 10%) for climate monitoring purposes through comparisons with ground-based radar and lidar cloud-phase observations. In addition, the increase in ice cloud occurrence frequency throughout the day resulting from convection can be followed well. In Chapter 4, the effect of different horizontal sampling resolutions on the cloud particle effective radius (re) and cloud-phase retrievals in case of broken and inhomogeneous overcast clouds is quantified using both simulations and retrievals. At low cloud fractions, the retrieved low-resolution re is overestimated by up to 5 μm compared to at high resolution, due to the contribution of the underlying surface to the observed reflectances. In about 4% of the cases this overestimation leads to cloud-phase misclassifications, which is reduced to 2% when applying an additional cloud-top temperature check in the cloud-phase retrieval algorithm. The accuracy of CPP precipitation retrievals is evaluated with TRMM-PR and CMORPH observations in Chapter 5. Rain occurrence frequency from CPP-PP agrees well with TRMM-PR-observed values (corr=0.86), while rain rates agree to a lesser extent (corr=0.50). Investigation of the precipitation intensity frequency distributions from CPP reveal good agreement with TRMM-PR and rain gauge observations, although at moderate rain rates CPP overestimates relative to the rain gauges. Further, it is demonstrated that CPP is suitable to monitor both the seasonal and diurnal cycle of rainfall during daytime. CPP detects a larger dynamical range

  12. Infrared Retrievals of Ice Cloud Properties and Uncertainties with an Optimal Estimation Retrieval Method

    NASA Astrophysics Data System (ADS)

    Wang, C.; Platnick, S. E.; Meyer, K.; Zhang, Z.

    2014-12-01

    We developed an optimal estimation (OE)-based method using infrared (IR) observations to retrieve ice cloud optical thickness (COT), cloud effective radius (CER), and cloud top height (CTH) simultaneously. The OE-based retrieval is coupled with a fast IR radiative transfer model (RTM) that simulates observations of different sensors, and corresponding Jacobians in cloudy atmospheres. Ice cloud optical properties are calculated using the MODIS Collection 6 (C6) ice crystal habit (severely roughened hexagonal column aggregates). The OE-based method can be applied to various IR space-borne and airborne sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the enhanced MODIS Airborne Simulator (eMAS), by optimally selecting IR bands with high information content. Four major error sources (i.e., the measurement error, fast RTM error, model input error, and pre-assumed ice crystal habit error) are taken into account in our OE retrieval method. We show that measurement error and fast RTM error have little impact on cloud retrievals, whereas errors from the model input and pre-assumed ice crystal habit significantly increase retrieval uncertainties when the cloud is optically thin. Comparisons between the OE-retrieved ice cloud properties and other operational cloud products (e.g., the MODIS C6 and CALIOP cloud products) are shown.

  13. Cloud-Scale Vertical Velocity and Turbulent Dissipation Rate Retrievals

    DOE Data Explorer

    Shupe, Matthew

    2013-05-22

    Time-height fields of retrieved in-cloud vertical wind velocity and turbulent dissipation rate, both retrieved primarily from vertically-pointing, Ka-band cloud radar measurements. Files are available for manually-selected, stratiform, mixed-phase cloud cases observed at the North Slope of Alaska (NSA) site during periods covering the Mixed-Phase Arctic Cloud Experiment (MPACE, late September through early November 2004) and the Indirect and Semi-Direct Aerosol Campaign (ISDAC, April-early May 2008). These time periods will be expanded in a future submission.

  14. Towards vertical cloud profile retrieval from satellite observations.

    NASA Astrophysics Data System (ADS)

    van Zadelhoff, G.-J.; Donovan, D. P.; Schutgens, N. A. J.

    2003-04-01

    In 2004 the satellites CloudSat and CALIPSO will be launched giving a first opportunity to retrieve vertical profiles of cloud macro- and micro-physical properties (LWC, IWC and Reff) on a global base using the combination of a lidar and radar. The two satellites will fly in tight formation (460 km after each other) resulting in co-located observations with a delay of ~1 minute, with a vertical resolution of 60 to 180 m for the Lidar and 500 m for the radar. In this poster we present the current status of the KNMI lidar-radar algorithm and the ongoing work to implement this procedure for use in the CALIPSO-CloudSat combination. Discussed are the impact of the time lag between the lidar and radar observations and how to deal with this. Secondly the transfering of the radar and lidar data to a common spatial and temporal grid. Finally the need for multiple scattering calculations for the lidar due to the large footprint of the beam is discussed. The work described is also part of the preparation for a future ESA/NASDA candidate satellite mission EarthCARE.

  15. Multilayered Clouds Identification and Retrieval for CERES Using MODIS

    NASA Technical Reports Server (NTRS)

    Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Yi, Yuhong; Huang, Jainping; Lin, Bin; Fan, Alice; Gibson, Sharon; Chang, Fu-Lung

    2006-01-01

    Traditionally, analyses of satellite data have been limited to interpreting the radiances in terms of single layer clouds. Generally, this results in significant errors in the retrieved properties for multilayered cloud systems. Two techniques for detecting overlapped clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. The first technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other method uses microwave (MWR) data. The use of BTD, the 11-12 micrometer brightness temperature difference, in conjunction with tau, the retrieved visible optical depth, was suggested by Kawamoto et al. (2001) and used by Pavlonis et al. (2004) as a means to detect multilayered clouds. Combining visible (VIS; 0.65 micrometer) and infrared (IR) retrievals of cloud properties with microwave (MW) retrievals of cloud water temperature Tw and liquid water path LWP retrieved from satellite microwave imagers appears to be a fruitful approach for detecting and retrieving overlapped clouds (Lin et al., 1998, Ho et al., 2003, Huang et al., 2005). The BTD method is limited to optically thin cirrus over low clouds, while the MWR method is limited to ocean areas only. With the availability of VIS and IR data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and MW data from the Advanced Microwave Scanning Radiometer EOS (AMSR-E), both on Aqua, it is now possible to examine both approaches simultaneously. This paper explores the use of the BTD method as applied to MODIS and AMSR-E data taken from the Aqua satellite over non-polar ocean surfaces.

  16. European ISCCP sector surface and satellite retrieved cloud comparison

    NASA Astrophysics Data System (ADS)

    Drake, F.; Sèze, G.; Desbois, M.; Henderson-Sellers, A.

    A comparison between surface-observed total, low and high cloud amount and retrievals from METEOSAT radiance data made using the cluster technique of Desbois et al. has been undertaken. Observations for 12.00 GMT for the 20 day period 22nd July to 10th August 1983 were compared with retrievals made from METEOSAT radiances measured at 11.30 GMT. The comparisons for total and low cloud amount were made for 204 stations covering France, southern Britain and West Germany although high cloud amount comparisons were not possible for France, so only 114 stations were used. The location and time period were selected to coincide with one of the regions designated for the validation phase of the International Satellite Cloud Climatology Project, ISCCP. The results are generally good: for total cloud amount 30% of retrievals were fully in agreement and 64% of the differences were within +/-1 okta. As anticipated, the surface observations offered additional information oin low cloud cover in multi-layer situations. Surface observers were also found to identify thin cirrus which was not detected by the satellite retrieval and to detect small gaps in cloud decks and small clouds missed by the satellite retrieval.

  17. Frequency and causes of failed MODIS cloud property retrievals for liquid phase clouds over global oceans

    NASA Astrophysics Data System (ADS)

    Cho, Hyoun-Myoung; Zhang, Zhibo; Meyer, Kerry; Lebsock, Matthew; Platnick, Steven; Ackerman, Andrew S.; Di Girolamo, Larry; -Labonnote, Laurent C.; Cornet, Céline; Riedi, Jerome; Holz, Robert E.

    2015-05-01

    Moderate Resolution Imaging Spectroradiometer (MODIS) retrieves cloud droplet effective radius (r_e) and optical thickness (τ) by projecting observed cloud reflectances onto a precomputed look-up table (LUT). When observations fall outside of the LUT, the retrieval is considered "failed" because no combination of τ and r_e within the LUT can explain the observed cloud reflectances. In this study, the frequency and potential causes of failed MODIS retrievals for marine liquid phase (MLP) clouds are analyzed based on 1 year of Aqua MODIS Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86 μm and 2.1 μm MODIS channel combination has an overall failure rate of about 16% (10% for the 0.86 μm and 3.7 μm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade wind cumulus regimes. The leading type of failure is the "r_e too large" failure accounting for 60%-85% of all failed retrievals. The rest is mostly due to the "r_e too small" or τ retrieval failures. Enhanced retrieval failure rates are found when MLP cloud pixels are partially cloudy or have high subpixel inhomogeneity, are located at special Sun-satellite viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to cloud masking, cloud overlapping, and/or cloud phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated CloudSat radar reflectivity observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r_e values observed in these clouds are the consequence of true cloud microphysics or still due to artifacts not included in this study.

  18. Cloud retrieval using infrared sounder data - Error analysis

    NASA Technical Reports Server (NTRS)

    Wielicki, B. A.; Coakley, J. A., Jr.

    1981-01-01

    An error analysis is presented for cloud-top pressure and cloud-amount retrieval using infrared sounder data. Rms and bias errors are determined for instrument noise (typical of the HIRS-2 instrument on Tiros-N) and for uncertainties in the temperature profiles and water vapor profiles used to estimate clear-sky radiances. Errors are determined for a range of test cloud amounts (0.1-1.0) and cloud-top pressures (920-100 mb). Rms errors vary by an order of magnitude depending on the cloud height and cloud amount within the satellite's field of view. Large bias errors are found for low-altitude clouds. These bias errors are shown to result from physical constraints placed on retrieved cloud properties, i.e., cloud amounts between 0.0 and 1.0 and cloud-top pressures between the ground and tropopause levels. Middle-level and high-level clouds (above 3-4 km) are retrieved with low bias and rms errors.

  19. Optical Thickness and Effective Radius Retrievals of Liquid Water Clouds over Ice and Snow Surface

    NASA Technical Reports Server (NTRS)

    Platnick, S.; King, M. D.; Tsay, S.-C.; Arnold, G. T.; Gerber, H.; Hobbs, P. V.; Rangno, A.

    1999-01-01

    Cloud optical thickness and effective radius retrievals from solar reflectance measurements traditionally depend on a combination of spectral channels that are absorbing and non-absorbing for liquid water droplets. Reflectances in non-absorbing channels (e.g., 0.67, 0.86 micrometer bands) are largely dependent on cloud optical thickness, while longer wavelength absorbing channels (1.6, 2.1, and 3.7 micrometer window bands) provide cloud particle size information. Retrievals are complicated by the presence of an underlying ice/snow surface. At the shorter wavelengths, sea ice is both bright and highly variable, significantly increasing cloud retrieval uncertainty. However, reflectances at the longer wavelengths are relatively small and may be comparable to that of dark open water. Sea ice spectral albedos derived from Cloud Absorption Radiometer (CAR) measurements during April 1992 and June 1995 Arctic field deployments are used to illustrate these statements. A modification to the traditional retrieval technique is devised. The new algorithm uses a combination of absorbing spectral channels for which the snow/ice albedo is relatively small. Using this approach, preliminary retrievals have been made with the MODIS Airborne Simulator (MAS) imager flown aboard the NASA ER-2 during FIRE-ACE. Data from coordinated ER-2 and University of Washington CV-580 aircraft observations of liquid water stratus clouds on June 3 and June 6, 1998 have been examined. Size retrievals are compared with in situ cloud profile measurements of effective radius made with the CV-580 PMS FSSP probe, and optical thickness retrievals are compared with extinction profiles derived from the Gerber Scientific "g-meter" probe. MAS retrievals are shown to be in good agreement with the in situ measurements.

  20. Ground-based assessment of retrieved aerosol properties from GOSAT observations in multiple carbon dioxide retrieval algorithms

    NASA Astrophysics Data System (ADS)

    Nelson, R.; O'Dell, C. W.; Frankenberg, C.; Oshchepkov, S.; Bril, A.; Yokota, T.; Yoshida, Y.; Butz, A.; Guerlet, S.; Boesch, H.; Parker, R.

    2012-12-01

    Spaced-based near-infrared measurements of greenhouse gases such as carbon dioxide and methane are now routinely made from the Greenhouse Gases Observing Satellite (GOSAT) via an assortment of retrieval algorithms. The measurements are based on assumed knowledge of the light paths followed by the measured solar photons, paths which can be altered in the presence of clouds and aerosols. Most algorithms therefore attempt to simultaneously retrieval aerosol information alongside the desired gas concentrations, in an attempt to mitigate errors caused by atmospheric scattering. However, recent studies have hinted that most algorithms tend to retrieve biased aerosol information over certain surface types (such as bright surfaces), leading in particular to biased estimates of the column-averaged dry air mole fraction of carbon dioxide (XCO2). In this work, we compare GOSAT-retrieved AEROSOL properties from multiple XCO2 retrieval algorithms with those of the well-validated AERONET sun photometer network. We present a correlation analysis of retrieved aerosol errors and their effect on retrieved XCO2, as a function of multiple variables such as surface type and viewing geometry, with the goal of providing critical information on how best to deal with aerosols in the context of these challenging greenhouse gas retrievals.

  1. Effect of Thin Cirrus Clouds on Dust Optical Depth Retrievals From MODIS Observations

    NASA Technical Reports Server (NTRS)

    Feng, Qian; Hsu, N. Christina; Yang, Ping; Tsay, Si-Chee

    2011-01-01

    The effect of thin cirrus clouds in retrieving the dust optical depth from MODIS observations is investigated by using a simplified aerosol retrieval algorithm based on the principles of the Deep Blue aerosol property retrieval method. Specifically, the errors of the retrieved dust optical depth due to thin cirrus contamination are quantified through the comparison of two retrievals by assuming dust-only atmospheres and the counterparts with overlapping mineral dust and thin cirrus clouds. To account for the effect of the polarization state of radiation field on radiance simulation, a vector radiative transfer model is used to generate the lookup tables. In the forward radiative transfer simulations involved in generating the lookup tables, the Rayleigh scattering by atmospheric gaseous molecules and the reflection of the surface assumed to be Lambertian are fully taken into account. Additionally, the spheroid model is utilized to account for the nonsphericity of dust particles In computing their optical properties. For simplicity, the single-scattering albedo, scattering phase matrix, and optical depth are specified a priori for thin cirrus clouds assumed to consist of droxtal ice crystals. The present results indicate that the errors in the retrieved dust optical depths due to the contamination of thin cirrus clouds depend on the scattering angle, underlying surface reflectance, and dust optical depth. Under heavy dusty conditions, the absolute errors are comparable to the predescribed optical depths of thin cirrus clouds.

  2. Cloudy Sounding and Cloud-Top Height Retrieval From AIRS Alone Single Field-of-View Radiance Measurements

    NASA Technical Reports Server (NTRS)

    Weisz, Elisabeth; Li, Jun; Li, Jinlong; Zhou, Daniel K.; Huang, Hung-Lung; Goldberg, Mitchell D.; Yang, Ping

    2007-01-01

    High-spectral resolution measurements from the Atmospheric Infrared Sounder (AIRS) onboard the EOS (Earth Observing System) Aqua satellite provide unique information about atmospheric state, surface and cloud properties. This paper presents an AIRS alone single field-of-view (SFOV) retrieval algorithm to simultaneously retrieve temperature, humidity and ozone profiles under all weather conditions, as well as cloud top pressure (CTP) and cloud optical thickness (COT) under cloudy skies. For optically thick cloud conditions the above-cloud soundings are derived, whereas for clear skies and optically thin cloud conditions the profiles are retrieved from 0.005 hPa down to the earth's surface. Initial validation has been conducted by using the operational MODIS (Moderate Resolution Imaging Spectroradiometer) product, ECMWF (European Center of Medium range Weather Forecasts) analysis fields and radiosonde observations (RAOBs). These inter-comparisons clearly demonstrate the potential of this algorithm to process data from 38 high-spectral infrared (IR) sounder instruments.

  3. Cloud effective particle size and water content profile retrievals using combined lidar and radar observations, 2, Comparison with IR radiometer and in situ measurements of ice clouds

    NASA Astrophysics Data System (ADS)

    Donovan, D. P.; van Lammeren, A. C. A. P.; Hogan, R. J.; Russchenberg, H. W. J.; Apituley, A.; Francis, P.; Testud, J.; Pelon, J.; Quante, M.; Goddard, J.

    2001-11-01

    A new combined iidar/radar inversion procedure has been developed for cloud effective radius and water content retrievals. The algorithm treats the lidar extinction, derived effective particle size, and multiple-scattering effects together in a consistent fashion. This procedure has been applied to data taken during the Netherlands Cloud and Radiation (CLARA) campaign and the Cloud Lidar and Radar Experiment (CLARE'98) multisensor cloud measurement campaign. The results of the algorithm compare well with simultaneous IR radiometer cloud measurements as well as with measurements made by using aircraft-mounted two-dimensional probe particle-sizing instruments.

  4. The Radiative Consistency of Atmospheric Infrared Sounder and Moderate Resolution Imaging Spectroradiometer Cloud Retrievals

    NASA Technical Reports Server (NTRS)

    Kahn, Brian H.; Fishbein, Evan; Nasiri, Shaima L.; Eldering, Annmarie; Fetzer, Eric J.; Garay, Michael J.; Lee, Sung-Yung

    2007-01-01

    The consistency of cloud top temperature (Tc) and effective cloud fraction (f) retrieved by the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU) observation suite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on the EOS-Aqua platform are investigated. Collocated AIRS and MODIS TC and f are compared via an 'effective scene brightness temperature' (Tb,e). Tb,e is calculated with partial field of view (FOV) contributions from TC and surface temperature (TS), weighted by f and 1-f, respectively. AIRS reports up to two cloud layers while MODIS reports up to one. However, MODIS reports TC, TS, and f at a higher spatial resolution than AIRS. As a result, pixel-scale comparisons of TC and f are difficult to interpret, demonstrating the need for alternatives such as Tb,e. AIRS-MODIS Tb,e differences ((Delta)Tb,e) for identical observing scenes are useful as a diagnostic for cloud quantity comparisons. The smallest values of DTb,e are for high and opaque clouds, with increasing scatter in (Delta)Tb,e for clouds of smaller opacity and lower altitude. A persistent positive bias in DTb,e is observed in warmer and low-latitude scenes, characterized by a mixture of MODIS CO2 slicing and 11-mm window retrievals. These scenes contain heterogeneous cloud cover, including mixtures of multilayered cloudiness and misplaced MODIS cloud top pressure. The spatial patterns of (Delta)Tb,e are systematic and do not correlate well with collocated AIRS-MODIS radiance differences, which are more random in nature and smaller in magnitude than (Delta)Tb,e. This suggests that the observed inconsistencies in AIRS and MODIS cloud fields are dominated by retrieval algorithm differences, instead of differences in the observed radiances. The results presented here have implications for the validation of cloudy satellite retrieval algorithms, and use of cloud products in quantitative analyses.

  5. Global cloud top height retrieval using SCIAMACHY limb spectra: model studies and first results

    NASA Astrophysics Data System (ADS)

    Eichmann, Kai-Uwe; Lelli, Luca; von Savigny, Christian; Sembhi, Harjinder; Burrows, John P.

    2016-03-01

    Cloud top heights (CTHs) are retrieved for the period 1 January 2003 to 7 April 2012 using height-resolved limb spectra measured with the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) on board ENVISAT (ENVIronmental SATellite). In this study, we present the retrieval code SCODA (SCIAMACHY cloud detection algorithm) based on a colour index method and test the accuracy of the retrieved CTHs in comparison to other methods. Sensitivity studies using the radiative transfer model SCIATRAN show that the method is capable of detecting cloud tops down to about 5 km and very thin cirrus clouds up to the tropopause. Volcanic particles can be detected that occasionally reach the lower stratosphere. Upper tropospheric ice clouds are observable for a nadir cloud optical thickness (COT) ≥ 0.01, which is in the subvisual range. This detection sensitivity decreases towards the lowermost troposphere. The COT detection limit for a water cloud top height of 5 km is roughly 0.1. This value is much lower than thresholds reported for passive cloud detection methods in nadir-viewing direction. Low clouds at 2 to 3 km can only be retrieved under very clean atmospheric conditions, as light scattering of aerosol particles interferes with the cloud particle scattering. We compare co-located SCIAMACHY limb and nadir cloud parameters that are retrieved with the Semi-Analytical CloUd Retrieval Algorithm (SACURA). Only opaque clouds (τN,c > 5) are detected with the nadir passive retrieval technique in the UV-visible and infrared wavelength ranges. Thus, due to the frequent occurrence of thin clouds and subvisual cirrus clouds in the tropics, larger CTH deviations are detected between both viewing geometries. Zonal mean CTH differences can be as high as 4 km in the tropics. The agreement in global cloud fields is sufficiently good. However, the land-sea contrast, as seen in nadir cloud occurrence frequency distributions, is not

  6. Inter-comparison of CALIPSO and CloudSat retrieved profiles of aerosol and cloud microphysical parameters with aircraft profiles over a tropical region

    NASA Astrophysics Data System (ADS)

    Padmakumari, B.; Harikishan, G.; Maheskumar, R. S.

    2016-05-01

    Satellites play a major role in understanding the spatial and vertical distribution of aerosols and cloud microphysical parameters over a large area. However, the inherent limitations in satellite retrievals can be improved through inter-comparisons with airborne platforms. Over the Indian sub-continent, the vertical profiles retrieved from space-borne lidar such as CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization) on board the satellite CALIPSO and Cloud Profiling Radar (CPR) on board the satellite CloudSat were inter- compared with the aircraft observations conducted during Cloud Aerosol Interactions and Precipitation Enhancement Experiment (CAIPEEX). In the absence of high clouds, both aircraft and CALIOP showed similar features of aerosol layering and water-ice cloud signatures. As CALIOP could not penetrate the thick clouds, the aerosol information below the cloud is missed. While the aircraft could measure high concentrations below the cloud base and above the low clouds in the presence of high clouds. The aircraft derived liquid water content (LWC) and droplet effective radii (Re) showed steady increase from cloud base to cloud top with a variable cloud droplet number concentration (CDNC). While the CloudSat derived LWC, CDNC and Re showed increase from the cloud top to cloud base in contradiction to the aircraft measurements. The CloudSat profiles are underestimated as compared to the corresponding aircraft profiles. Validation of satellite retrieved vertical profiles with aircraft measurements is very much essential over the tropics to improve the retrieval algorithms and to constrain the uncertainties in the regional cloud parameterization schemes.

  7. Global cloud top height retrieval using SCIAMACHY limb spectra: model studies and first results

    NASA Astrophysics Data System (ADS)

    Eichmann, K.-U.; Lelli, L.; von Savigny, C.; Sembhi, H.; Burrows, J. P.

    2015-08-01

    Cloud top heights (CTH) were retrieved for the period 1 January 2003 to 7 April 2012 using height-resolved limb spectra measured with the Scanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board ENVISAT (ENVIronmental SATellite). In this study, we tested the sensitivity of the colour index method used in the retrieval code SCODA (SCIAMACHY Cloud Detection Algorithm) and the accuracy of the retrieved CTHs in comparison to other methods. Sensitivity studies using the radiative transfer model SCIATRAN showed that the method is capable of generally detecting cloud tops down to about 5 km and very thin cirrus clouds even up to the tropopause. Volcanic particles can also be detected that occasionally reach the lower stratosphere. Low clouds at 2-3 km can only be retrieved under very clean atmospheric conditions, as light scattering of aerosols interferes with the cloud retrieval. Upper tropospheric ice clouds are detectable for cloud optical depths down to about τN = 0.005, which is in the subvisual range. The detection sensitivity decreases towards the surface. An optical thickness of roughly 0.1 was the lower detection limit for water cloud top heights at 5 km. This value is much lower than thresholds reported for the passive cloud detection in nadir viewing direction. Comparisons with SCIAMACHY nadir cloud top heights, calculated with the Semi-Analytical CloUd Retrieval Algorithm (SACURA), showed a good agreement in the global cloud field distribution. But only opaque clouds (τN > 5) are detectable with the nadir passive retrieval technique in the UV-visible and infrared wavelength range. So due to the frequent occurrence of thin and sub-visual cirrus clouds in the tropics, large cloud top height deviations were detected between both viewing geometries. Also the land/sea contrast seen in nadir retrievals was not detected in limb mode. Co-located cloud top height measurements of the limb viewing Michelson Interferometer for Passive

  8. a Distributed Polygon Retrieval Algorithm Using Mapreduce

    NASA Astrophysics Data System (ADS)

    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.

  9. The US-DOE ARM/ASR Effort in Quantifying Uncertainty in Ground-Based Cloud Property Retrievals (Invited)

    NASA Astrophysics Data System (ADS)

    Xie, S.; Protat, A.; Zhao, C.

    2013-12-01

    One primary goal of the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program is to obtain and retrieve cloud microphysical properties from detailed cloud observations using ground-based active and passive remote sensors. However, there is large uncertainty in the retrieved cloud property products. Studies have shown that the uncertainty could arise from instrument limitations, measurement errors, sampling errors, retrieval algorithm deficiencies in assumptions, as well as inconsistent input data and constraints used by different algorithms. To quantify the uncertainty in cloud retrievals, a scientific focus group, Quantification of Uncertainties In Cloud Retrievals (QUICR), was recently created by the DOE Atmospheric System Research (ASR) program. This talk will provide an overview of the recent research activities conducted within QUICR and discuss its current collaborations with the European cloud retrieval community and future plans. The goal of QUICR is to develop a methodology for characterizing and quantifying uncertainties in current and future ARM cloud retrievals. The Work at LLNL was performed under the auspices of the U. S. Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research by Lawrence Livermore National Laboratory under contract No. DE-AC52-07NA27344. LLNL-ABS-641258.

  10. Evaluation of Operational Rainfall Retrieval Algorithms over Brazil

    NASA Astrophysics Data System (ADS)

    Morales, C.; Machado, L. A. T.; Angelis, C. F.

    2009-04-01

    Over the past 2 years, two rainfall estimation algorithms (Hydroestimator and USProb) have been operational at the Satellite Division of the Brazilian Space Research Institute (INPE). Hydroestimator is an IR technique that was based on the NESDIS Autoestimator algorithm, while USProb is a continental microwave retrieval that was developed for the Amazon Region. Besides these two schemes, another algorithm that makes use of IR and VIS channels and a cloud tracking technique (Fortracc) have been developed. During the conference, two years of rainfall estimation over Brazil will be used to diagnose the performance of such algorithms. These analysis will be concentrated on instantaneous, hourly, daily and monthly statistics in addition to the diurnal cycle representation. As the ground thruth, quality control rain guages and weather radar rain maps are employed over most part of Brazil. Moreover, regional statistics will be employed due to different precipitating systems acting in Brazil, i.e., the nothern part hold most of tropical convection, while northeast show warm cloud systems and the south, southeast and center Brazil have a combination of tropical convection, cold fronts, mesoscale convective systems and localized convection. Finally at the end of the presention, few annoucements will be made on behalf of GPM-Brazil. In that opportunity it will be shown the 2010 calendar activity for the Brazilian Field Campaigns as part of the Precipitation Measuring Mission (PMM) validation program.

  11. An evaluation of a semi-analytical cloud property retrieval using Meteosat Second Generation, MODIS and CloudSat

    NASA Astrophysics Data System (ADS)

    Kühnlein, M.; Nauss, T.; Appelhans, T.; Kokhanovsky, A. A.; Thies, B.

    2012-04-01

    Knowledge of cloud properties such as cloud effective radius and optical thickness is essential to understand their role in the dynamic radiation budget and climate change. The Spinning Enhanced Visible and Infrared Instrument (SEVIRI) on board Meteosat Second Generation (MSG) with its high temporal resolution (15 minutes) permits a non-continuous monitoring of the evolution of cloud properties what has motivated the adaptation of the SLALOM algorithm developed by Nauss and Kokhanovsky (2011) to MSG SEVIRI. The optical properties of SLALOM are compared against the LUT-based approach by Platnick et al. (2003) using data from the MODIS sensor on-board of the NASA EOS Aqua and Terra satellites (King and Greenstone, 1999) as well as the cloud optical depth product (2B-TAU) of CloudSat (Polonsky et al., 2008) and results are shown over ocean and land. Over water the retrievals show very close results where differences increase over land.

  12. Comparing different methods to retrieve cloud top height from Meteosat satellite data

    NASA Astrophysics Data System (ADS)

    Tabone, I.; Briz, S.; Anzalone, A.; De Castro, A. J.; Lopez, F.; Ferrarese, S.; Isgrò, F.; Cassardo, C.; Cremonini, R.; Bertaina, M.

    2015-10-01

    Cloud parameters such as the Cloud Top Height (CTH), Cloud Top Temperature (CTT), emissivity, particle size and optical depth have always been matter of interest for the atmospheric community. Particularly the CTH provides information leading to better understand the cloud radiative effects. Although there are many meteorological satellites providing the CTH, there are other sensors, not devoted to this purpose, that give some information from which this crucial parameter can be estimated. In this contribution we will describe three different methodologies to retrieve the CTH. The first technique is based on stereo-vision algorithms and requires two different views of the same scene and does not need of extra atmospheric information. In the second one, brightness temperatures in two IR spectral bands are converted to real cloud temperature by means of the proposed algorithms. From the CTT, the CTH is estimated using temperature vertical profiles (measured or modeled). The third technique retrieves the CTH from the output parameters of post event simulations performed by a Numerical Weather Prediction (NWP) model that in this work will be the mesoscale model WRF (Weather Research Forecast). This article presents a preliminary work, in which the heights retrieved by the three methodologies applied to the geostationary satellite Meteosat 10 are compared with the heights given by MODIS sensor installed on the polar satellite AQUA. This promising results show that valuable information about CTH can be retrieved from Meteosat which provide high frequency and large scale data useful for weather and climate research.

  13. Global Weather States and Their Properties from Passive and Active Satellite Cloud Retrievals

    NASA Technical Reports Server (NTRS)

    Tselioudis, George; Rossow, William; Zhang, Yuanchong; Konsta, Dimitra

    2013-01-01

    In this study, the authors apply a clustering algorithm to International Satellite Cloud Climatology Project (ISCCP) cloud optical thickness-cloud top pressure histograms in order to derive weather states (WSs) for the global domain. The cloud property distribution within each WS is examined and the geographical variability of each WS is mapped. Once the global WSs are derived, a combination of CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical cloud structure retrievals is used to derive the vertical distribution of the cloud field within each WS. Finally, the dynamic environment and the radiative signature of the WSs are derived and their variability is examined. The cluster analysis produces a comprehensive description of global atmospheric conditions through the derivation of 11 WSs, each representing a distinct cloud structure characterized by the horizontal distribution of cloud optical depth and cloud top pressure. Matching those distinct WSs with cloud vertical profiles derived from CloudSat and CALIPSO retrievals shows that the ISCCP WSs exhibit unique distributions of vertical layering that correspond well to the horizontal structure of cloud properties. Matching the derived WSs with vertical velocity measurements shows a normal progression in dynamic regime when moving from the most convective to the least convective WS. Time trend analysis of the WSs shows a sharp increase of the fair-weather WS in the 1990s and a flattening of that increase in the 2000s. The fact that the fair-weather WS is the one with the lowest cloud radiative cooling capability implies that this behavior has contributed excess radiative warming to the global radiative budget during the 1990s.

  14. Enhanced Deep Blue aerosol retrieval algorithm: The second generation

    NASA Astrophysics Data System (ADS)

    Hsu, N. C.; Jeong, M.-J.; Bettenhausen, C.; Sayer, A. M.; Hansell, R.; Seftor, C. S.; Huang, J.; Tsay, S.-C.

    2013-08-01

    The aerosol products retrieved using the Moderate Resolution Imaging Spectroradiometer (MODIS) collection 5.1 Deep Blue algorithm have provided useful information about aerosol properties over bright-reflecting land surfaces, such as desert, semiarid, and urban regions. However, many components of the C5.1 retrieval algorithm needed to be improved; for example, the use of a static surface database to estimate surface reflectances. This is particularly important over regions of mixed vegetated and nonvegetated surfaces, which may undergo strong seasonal changes in land cover. In order to address this issue, we develop a hybrid approach, which takes advantage of the combination of precalculated surface reflectance database and normalized difference vegetation index in determining the surface reflectance for aerosol retrievals. As a result, the spatial coverage of aerosol data generated by the enhanced Deep Blue algorithm has been extended from the arid and semiarid regions to the entire land areas. In this paper, the changes made in the enhanced Deep Blue algorithm regarding the surface reflectance estimation, aerosol model selection, and cloud screening schemes for producing the MODIS collection 6 aerosol products are discussed. A similar approach has also been applied to the algorithm that generates the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Deep Blue products. Based upon our preliminary results of comparing the enhanced Deep Blue aerosol products with the Aerosol Robotic Network (AERONET) measurements, the expected error of the Deep Blue aerosol optical thickness (AOT) is estimated to be better than 0.05 + 20%. Using 10 AERONET sites with long-term time series, 79% of the best quality Deep Blue AOT values are found to fall within this expected error.

  15. First Results from the OMI Rotational Raman Scattering Cloud Pressure Algorithm

    NASA Technical Reports Server (NTRS)

    Joiner, Joanna; Vasilkov, Alexander P.

    2006-01-01

    We have developed an algorithm to retrieve scattering cloud pressures and other cloud properties with the Aura Ozone Monitoring Instrument (OMI). The scattering cloud pressure is retrieved using the effects of rotational Raman scattering (RRS). It is defined as the pressure of a Lambertian surface that would produce the observed amount of RRS consistent with the derived reflectivity of that surface. The independent pixel approximation is used in conjunction with the Lambertian-equivalent reflectivity model to provide an effective radiative cloud fraction and scattering pressure in the presence of broken or thin cloud. The derived cloud pressures will enable accurate retrievals of trace gas mixing ratios, including ozone, in the troposphere within and above clouds. We describe details of the algorithm that will be used for the first release of these products. We compare our scattering cloud pressures with cloud-top pressures and other cloud properties from the Aqua Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument. OMI and MODIS are part of the so-called A-train satellites flying in formation within 30 min of each other. Differences between OMI and MODIS are expected because the MODIS observations in the thermal infrared are more sensitive to the cloud top whereas the backscattered photons in the ultraviolet can penetrate deeper into clouds. Radiative transfer calculations are consistent with the observed differences. The OMI cloud pressures are shown to be correlated with the cirrus reflectance. This relationship indicates that OMI can probe through thin or moderately thick cirrus to lower lying water clouds.

  16. The 183-WSL fast rain rate retrieval algorithm: Part I: Retrieval design

    NASA Astrophysics Data System (ADS)

    Laviola, Sante; Levizzani, Vincenzo

    2011-03-01

    The Water vapour Strong Lines at 183 GHz (183-WSL) fast retrieval method retrieves rain rates and classifies precipitation types for applications in nowcasting and weather monitoring. The retrieval scheme consists of two fast algorithms, over land and over ocean, that use the water vapour absorption lines at 183.31 GHz corresponding to the channels 3 (183.31 ± 1 GHz), 4 (183.31 ± 3 GHz) and 5 (183.31 ± 7 GHz) of the Advanced Microwave Sounding Unit module B (AMSU-B) and of the Microwave Humidity Sounder (MHS) flying on NOAA-15-18 and Metop-A satellite series, respectively. The method retrieves rain rates by exploiting the extinction of radiation due to rain drops following four subsequent steps. After ingesting the satellite data stream, the window channels at 89 and 150 GHz are used to compute scattering-based thresholds and the 183-WSLW module for rainfall area discrimination and precipitation type classification as stratiform or convective on the basis of the thresholds calculated for land/mixed and sea surfaces. The thresholds are based on the brightness temperature difference Δwin = TB89 - TB150 and are different over land (L) and over sea (S): cloud droplets and water vapour (Δwin < 3 K L; Δwin < 0 K S), stratiform rain (3 K < Δwin < 10 K L; 0 K < Δwin < 10 K S), and convective rain (Δwin > 10 K L and S). The thresholds, initially empirically derived from observations, are corroborated by the simulations of the RTTOV radiative transfer model applied to 20000 ECMWF atmospheric profiles at midlatitudes and the use of data from the Nimrod radar network. A snow cover mask and a digital elevation model are used to eliminate false rain area attribution, especially over elevated terrain. A probability of detection logistic function is also applied in the transition region from no-rain to rain adjacent to the clouds to ensure continuity of the rainfall field. Finally, the last step is dedicated to the rain rate retrieval with the modules 183-WSLS (stratiform

  17. Haze and clouds properties of Saturn's 2011 giant vortex retrieved from Cassini VIMS-V data.

    NASA Astrophysics Data System (ADS)

    Oliva, F.; Adriani, A.; Moriconi, M. L.; Liberti, G. L.; d'Aversa, E.

    2014-04-01

    This work is focused on the retrieval of the microphysical and geometrical properties of the clouds and hazes overlying the giant vortex observed in 2011 at Saturn, by the Visual and Infrared Mapping Spectrometer (VIMS) on board of Cassini. The retrieval algorithm is based on the optimal estimation technique [15] and takes advantage of a forward radiative transfer model developed by adapting the LibRadtran code [13] to the atmosphere of Saturn. For each of the retrieved parameters - that are effective radii, top pressures and total number densities for each considered deck - a 2D spatial map has been produced.

  18. Evaluation of quantitative satellite-based retrievals of volcanic ash clouds

    NASA Astrophysics Data System (ADS)

    Schneider, D. J.; Pavolonis, M. J.; Bojinski, S.; Siddans, R.; Thomas, G.

    2015-12-01

    Volcanic ash clouds are a serious hazard to aviation, and mitigation requires a robust system of volcano monitoring, eruption detection, characterization of cloud properties, forecast of cloud movement, and communication of warnings. Several research groups have developed quantitative satellite-based volcanic ash products and some of these are in operational use by Volcanic Ash Advisory Centers around the world to aid in characterizing cloud properties and forecasting regions of ash hazard. The algorithms applied to the satellite data utilize a variety of techniques, and thus produce results that differ. The World Meteorological Organization has recently sponsored an intercomparison study of satellite-based retrievals with four goals: 1) to establish a validation protocol for satellite-based volcanic ash products, 2) to quantify and understand differences in products, 3) to develop best practices, and 4) to standardize volcanic cloud geophysical parameters. Six volcanic eruption cases were considered in the intercomparison: Eyjafallajökull, Grimsvötn, Kelut, Kirishimayama, Puyehue-Cordón Caulle, and Sarychev Peak. Twenty-four algorithms were utilized, which retrieved parameters including: ash cloud top height, ash column mass loading, ash effective radius, and ash optical depth at visible and thermal-infrared wavelengths. Results were compared to space-based, airborne, and ground-based lidars; complementary satellite retrievals; and manual "expert evaluation" of ash extent. The intercomparison results will feed into the International Civil Aviation Organization "Roadmap for International Airways Volcano Watch", which integrates volcanic meteorological information into decision support systems for aircraft operations.

  19. Analysis of cloud optical thickness retrieved from CIMEL measurements

    NASA Astrophysics Data System (ADS)

    Marshak, A.; Barker, H.; Evans, K.; Pavloski, C.; Knyazikhin, Y.; Holben, B.; Wiscombe, W.

    2002-05-01

    When conditions are inappropriate to make AERONET measurements that are suitable for aerosol studies, new measurements related to cloud physics can be made instead. As such, several AERONET CIMEL sunphotometers have been equipped with a new "cloud mode." This mode allows the CIMELs to make measurements of zenith radiance when the Sun in blocked by clouds. When in cloud mode, a CIMEL points straight up every 10-15 minutes and takes 10 measurements over a 9 second time interval at four wavelengths: 440, 670, 870, and 1020 nm. For cloudy conditions above green vegetation, the spectral contrast in surface albedo dominates over Rayleigh and aerosol effects; this makes normalized zenith radiances almost indistinguishable at 440 and 670 as well as at 870 and 1020 nm. We have developed a new method for retrieving cloud optical thickness, even for broken clouds, that uses data from the 670 and 870 nm channels to build a Normalized Difference Cloud Index (NDCI). The retrieval can be improved if, in addition to CIMEL zenith radiances, surface downward flux measurements at both wavelengths are also available. Based on theoretical calculations and preliminary analysis of CIMEL measurements at the ARM Central Facility in Oklahoma, there is good correlation between NDCI and cloud liquid water path retrieved from microwave radiometer for cloudy sky above green vegetation.

  20. An Improved Algorithm for Retrieving Surface Downwelling Longwave Radiation from Satellite Measurements

    NASA Technical Reports Server (NTRS)

    Zhou, Yaping; Kratz, David P.; Wilber, Anne C.; Gupta, Shashi K.; Cess, Robert D.

    2006-01-01

    Retrieving surface longwave radiation from space has been a difficult task since the surface downwelling longwave radiation (SDLW) are integrations from radiation emitted by the entire atmosphere, while those emitted from the upper atmosphere are absorbed before reaching the surface. It is particularly problematic when thick clouds are present since thick clouds will virtually block all the longwave radiation from above, while satellites observe atmosphere emissions mostly from above the clouds. Zhou and Cess developed an algorithm for retrieving SDLW based upon detailed studies using radiative transfer model calculations and surface radiometric measurements. Their algorithm linked clear sky SDLW with surface upwelling longwave flux and column precipitable water vapor. For cloudy sky cases, they used cloud liquid water path as an additional parameter to account for the effects of clouds. Despite the simplicity of their algorithm, it performed very well for most geographical regions except for those regions where the atmospheric conditions near the surface tend to be extremely cold and dry. Systematic errors were also found for areas that were covered with ice clouds. An improved version of the algorithm was developed that prevents the large errors in the SDLW at low water vapor amounts. The new algorithm also utilizes cloud fraction and cloud liquid and ice water paths measured from the Cloud and the Earth's Radiant Energy System (CERES) satellites to separately compute the clear and cloudy portions of the fluxes. The new algorithm has been validated against surface measurements at 29 stations around the globe for the Terra and Aqua satellites. The results show significant improvement over the original version. The revised Zhou-Cess algorithm is also slightly better or comparable to more sophisticated algorithms currently implemented in the CERES processing. It will be incorporated in the CERES project as one of the empirical surface radiation algorithms.

  1. Retrieval Algorithms for the Halogen Occultation Experiment

    NASA Technical Reports Server (NTRS)

    Thompson, Robert E.; Gordley, Larry L.

    2009-01-01

    The Halogen Occultation Experiment (HALOE) on the Upper Atmosphere Research Satellite (UARS) provided high quality measurements of key middle atmosphere constituents, aerosol characteristics, and temperature for 14 years (1991-2005). This report is an outline of the Level 2 retrieval algorithms, and it also describes the great care that was taken in characterizing the instrument prior to launch and throughout its mission life. It represents an historical record of the techniques used to analyze the data and of the steps that must be considered for the development of a similar experiment for future satellite missions.

  2. Multi-sensor approach to retrieving water cloud physical properties and drizzle fraction

    NASA Astrophysics Data System (ADS)

    Prianto Rusli, Stephanie; Donovan, David; Russchenberg, Herman

    2015-04-01

    Accurately representing clouds and their interaction with the surrounding matter and radiation are one of the most important factors in climate modeling. In particular, feedback processes involving low level water clouds play a significant role in determining the net effect of cloud climate forcing. An accurate description of cloud physical properties is therefore necessary to quantify these processes and their implications. To this end, measurements combined from a variety of remote sensing instruments at different wavelengths provide crucial information about the clouds. To exploit this, building upon previous work in this field, we have developed a ground-based multi-sensor retrieval algorithm within an optimal estimation framework. The inverse problem of 'translating' the radar, lidar, and microwave radiometer measurements into retrieval products is formulated in a physically consistent manner, without relying on approximate empirical proxies (such as explicit liquid water content vs radar reflectivity factor relationships). We apply the algorithm to synthetic signals based on the output of large eddy simulation model runs and present here the preliminary results. Given temperature, humidity profiles, information from the measurements, and apriori contraints, we derive the liquid water content profile. Assuming a monomodal gamma droplet size distribution, the number concentration, effective size of the cloud droplets and the extinction coefficient are computed. The retrieved profiles provide a good fit to the true ones. The algorithm is being improved to take into account the presence of drizzle, an important aspect that affects cloud lifetime. Quantifying the amount of drizzle would enable the proper use of the radar reflectivity. Further development to allow retrieval of temperature and humidity profiles as well is anticipated.

  3. Arctic Mixed-Phase Cloud Properties from AERI Lidar Observations: Algorithm and Results from SHEBA

    SciTech Connect

    Turner, David D.

    2005-04-01

    A new approach to retrieve microphysical properties from mixed-phase Arctic clouds is presented. This mixed-phase cloud property retrieval algorithm (MIXCRA) retrieves cloud optical depth, ice fraction, and the effective radius of the water and ice particles from ground-based, high-resolution infrared radiance and lidar cloud boundary observations. The theoretical basis for this technique is that the absorption coefficient of ice is greater than that of liquid water from 10 to 13 μm, whereas liquid water is more absorbing than ice from 16 to 25 μm. MIXCRA retrievals are only valid for optically thin (τvisible < 6) single-layer clouds when the precipitable water vapor is less than 1 cm. MIXCRA was applied to the Atmospheric Emitted Radiance Interferometer (AERI) data that were collected during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment from November 1997 to May 1998, where 63% of all of the cloudy scenes above the SHEBA site met this specification. The retrieval determined that approximately 48% of these clouds were mixed phase and that a significant number of clouds (during all 7 months) contained liquid water, even for cloud temperatures as low as 240 K. The retrieved distributions of effective radii for water and ice particles in single-phase clouds are shown to be different than the effective radii in mixed-phase clouds.

  4. New Cirrus Retrieval Algorithms and Results from eMAS during SEAC4RS

    NASA Astrophysics Data System (ADS)

    Holz, R.; Platnick, S. E.; Meyer, K.; Wang, C.; Wind, G.; Arnold, T.; King, M. D.; Yorks, J. E.; McGill, M. J.

    2014-12-01

    The enhanced MODIS Airborne Simulator (eMAS) scanning imager was flown on the ER-2 during the SEAC4RS field campaign. The imager provides measurements in 38 spectral channels from the visible into the 13μm CO2 absorption bands at approximately 25 m nadir spatial resolution at cirrus altitudes, and with a swath width of about 18 km, provided substantial context and synergy for other ER-2 cirrus observations. The eMAS is an update to the original MAS scanner, having new midwave and IR spectrometers coupled with the previous VNIR/SWIR spectrometers. In addition to the standard MODIS-like cloud retrieval algorithm (MOD06/MYD06 for MODIS Terra/Aqua, respectively) that provides cirrus optical thickness (COT) and effective particle radius (CER) from several channel combinations, three new algorithms were developed to take advantage of unique aspects of eMAS and/or other ER-2 observations. The first uses a combination of two solar reflectance channels within the 1.88 μm water vapor absorption band, each with significantly different single scattering albedo, allowing for simultaneous COT and CER retrievals. The advantage of this algorithm is that the strong water vapor absorption can significantly reduce the sensitivity to lower level clouds and ocean/land surface properties thus better isolating cirrus properties. A second algorithm uses a suite of infrared channels in an optimal estimation algorithm to simultaneously retrieve COT, CER, and cloud-top pressure/temperature. Finally, a window IR algorithm is used to retrieve COT in synergy with the ER-2 Cloud Physics Lidar (CPL) cloud top/base boundary measurements. Using a variety of quantifiable error sources, uncertainties for all eMAS retrievals will be shown along with comparisons with CPL COT retrievals.

  5. Cloud Retrieval Information Content Studies with the Pre-Aerosol, Cloud and ocean Ecosystem (PACE) Ocean Color Imager (OCI)

    NASA Astrophysics Data System (ADS)

    Coddington, Odele; Platnick, Steven; Pilewskie, Peter; Schmidt, Sebastian

    2016-04-01

    The NASA Pre-Aerosol, Cloud and ocean Ecosystem (PACE) Science Definition Team (SDT) report released in 2012 defined imager stability requirements for the Ocean Color Instrument (OCI) at the sub-percent level. While the instrument suite and measurement requirements are currently being determined, the PACE SDT report provided details on imager options and spectral specifications. The options for a threshold instrument included a hyperspectral imager from 350-800 nm, two near-infrared (NIR) channels, and three short wave infrared (SWIR) channels at 1240, 1640, and 2130 nm. Other instrument options include a variation of the threshold instrument with 3 additional spectral channels at 940, 1378, and 2250 nm and the inclusion of a spectral polarimeter. In this work, we present cloud retrieval information content studies of optical thickness, droplet effective radius, and thermodynamic phase to quantify the potential for continuing the low cloud climate data record established by the MOderate Resolution and Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) missions with the PACE OCI instrument (i.e., non-polarized cloud reflectances and in the absence of midwave and longwave infrared channels). The information content analysis is performed using the GEneralized Nonlinear Retrieval Analysis (GENRA) methodology and the Collection 6 simulated cloud reflectance data for the common MODIS/VIIRS algorithm (MODAWG) for Cloud Mask, Cloud-Top, and Optical Properties. We show that using both channels near 2 microns improves the probability of cloud phase discrimination with shortwave-only cloud reflectance retrievals. Ongoing work will extend the information content analysis, currently performed for dark ocean surfaces, to different land surface types.

  6. A new algorithm for detecting cloud height using OMPS/LP measurements

    NASA Astrophysics Data System (ADS)

    Chen, Zhong; DeLand, Matthew; Bhartia, Pawan K.

    2016-03-01

    The Ozone Mapping and Profiler Suite Limb Profiler (OMPS/LP) ozone product requires the determination of cloud height for each event to establish the lower boundary of the profile for the retrieval algorithm. We have created a revised cloud detection algorithm for LP measurements that uses the spectral dependence of the vertical gradient in radiance between two wavelengths in the visible and near-IR spectral regions. This approach provides better discrimination between clouds and aerosols than results obtained using a single wavelength. Observed LP cloud height values show good agreement with coincident Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements.

  7. Multispectral Cloud Retrievals from MODIS on Terra and Aqua

    NASA Technical Reports Server (NTRS)

    King, Michael D.; Platnick, Steven; Ackerman, Steven A.; Menzel, W. Paul; Gray, Mark A.; Moody, Eric G.

    2002-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and the Aqua spacecraft on April 26, 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from each polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

  8. An Improved Algorithm for Retrieving Surface Downwelling Longwave Radiation from Satellite Measurements

    NASA Technical Reports Server (NTRS)

    Zhou, Yaping; Kratz, David P.; Wilber, Anne C.; Gupta, Shashi K.; Cess, Robert D.

    2007-01-01

    Zhou and Cess [2001] developed an algorithm for retrieving surface downwelling longwave radiation (SDLW) based upon detailed studies using radiative transfer model calculations and surface radiometric measurements. Their algorithm linked clear sky SDLW with surface upwelling longwave flux and column precipitable water vapor. For cloudy sky cases, they used cloud liquid water path as an additional parameter to account for the effects of clouds. Despite the simplicity of their algorithm, it performed very well for most geographical regions except for those regions where the atmospheric conditions near the surface tend to be extremely cold and dry. Systematic errors were also found for scenes that were covered with ice clouds. An improved version of the algorithm prevents the large errors in the SDLW at low water vapor amounts by taking into account that under such conditions the SDLW and water vapor amount are nearly linear in their relationship. The new algorithm also utilizes cloud fraction and cloud liquid and ice water paths available from the Cloud and the Earth's Radiant Energy System (CERES) single scanner footprint (SSF) product to separately compute the clear and cloudy portions of the fluxes. The new algorithm has been validated against surface measurements at 29 stations around the globe for Terra and Aqua satellites. The results show significant improvement over the original version. The revised Zhou-Cess algorithm is also slightly better or comparable to more sophisticated algorithms currently implemented in the CERES processing and will be incorporated as one of the CERES empirical surface radiation algorithms.

  9. The Microbase Value-Added Product: A Baseline Retrieval of Cloud Microphysical Properties

    SciTech Connect

    Dunn, M; Johnson, K; Jensen, M

    2011-05-31

    This report describes the Atmospheric Radiation Measurement (ARM) Climate Research Facility baseline cloud microphysical properties (MICROBASE) value-added product (VAP). MICROBASE uses a combination of millimeter-wavelength cloud radar, microwave radiometer, and radiosonde observations to estimate the vertical profiles of the primary microphysical parameters of clouds including the liquid/ice water content and liquid/ice cloud particle effective radius. MICROBASE is a baseline algorithm designed to apply to most conditions and locations using a single set of parameterizations and a simple determination of water phase based on temperature. This document provides the user of this product with guidelines to assist in determining the accuracy of the product under certain conditions. Quality control flags are designed to identify outliers and indicate instances where the retrieval assumptions may not be met. The overall methodology is described in this report through a detailed description of the input variables, algorithms, and output products.

  10. Sensitivity of Satellite-Retrieved Cloud Properties to the Effective Variance of Cloud Droplet Size Distribution

    SciTech Connect

    Arduini, R.F.; Minnis, P.; Smith, W.L.Jr.; Ayers, J.K.; Khaiyer, M.M.; Heck, P.

    2005-03-18

    Cloud reflectance models currently used in cloud property retrievals from satellites have been developed using size distributions defined by a set of fixed effective radii with a fixed effective variance. The satellite retrievals used for the Atmospheric Radiation Measurement (ARM) program assume droplet size distributions with an effective variance value of 0.10 (Minnis et al. 1998); the International Satellite Cloud Climatology Project uses 0.15 (Rossow and Schiffer 1999); and the Moderate Resolution Imaging Spectroradiometer (MODIS) team uses 0.13 (Nakajima and King 1990). These distributions are not necessarily representative of the actual sizes present in the clouds being observed. Because the assumed distributions can affect the reflectance patterns and near-infrared absorption, even for the same droplet effective radius reff, it is desirable to use the optimal size distributions in satellite retrievals of cloud properties. Collocated observations of the same clouds from different geostationary satellites, at different viewing angles, indicate that the current models may not be optimal (Ayers et al. 2005). Similarly, hour-to-hour variations in effective radius and optical depth reveal an unexplained dependence on scattering angle. To explore this issue, this paper examines the sensitivity of the cloud reflectance at 0.65 and 3.90-{micro}m to changes in the effective variance, or the spectral dispersion, of the modeled size distributions. The effects on the scattering phase functions and on the cloud reflectances are presented, as well as some resultant effects on the retrieved cloud properties.

  11. Retrieval of water cloud properties from carbon dioxide lidar soundings.

    PubMed

    Piatt, C M; Takashima, T

    1987-04-01

    Lidar backscatter signatures from model water clouds are calculated for CO(2) lidar wavelengths (9.2-10.8 microm) using Mie theory. The lidar isotropic mass backscatter coefficient is found to be quite variable both with cloud model and with wavelength, with values ranging from ~90 to 15 g(-1) cm(2) at 9.2-microm wavelength and from 25 to 5 g(-1) cm(2) at 11 microm, there being a general decrease in values with increasing wavelength. The cloud isotropic backscatter-to-extinction ratio similarly varies with both wavelength and cloud model between extreme values of 0.14 and 0.008. It is found that the cloud mass extinction coefficient has a value at any wavelength which is independent of cloud model droplet size distribution to within ~10% accuracy, in agreement with other studies. The value of this quantity varies from 1929 g(-1) cm(2) at 9.2 microm to 1258 g(-1) cm(2) at 11.0 microm. If the isotropic volume backscatter coefficient and the isotropic backscatter-to-extinction ratio are measured by lidar, then using the above characteristics of mass extinction coefficient the cloud liquid water content can be measured at any wavelength to an accuracy of ~20% when the cloud optical depth is between 0 and 0.5, with an increasing error with increasing cloud optical depth. Using the relationship between cloud droplet mode radius and backscatter-to-extinction ratio, the mode radius can be determined to ~10% accuracy. Multiple scattering in the backscattered beam for the case of absorbing water clouds at CO(2) wavelengths is also considered. The cloud depth to which accurate information can be retrieved in typical water clouds varies from ~80 to 250 m depending on the wavelength and the cloud model, although some information is available to depths of 500 m in some clouds. PMID:20454313

  12. Fast cloud parameter retrievals of MIPAS/Envisat

    NASA Astrophysics Data System (ADS)

    Spang, R.; Arndt, K.; Dudhia, A.; Höpfner, M.; Hoffmann, L.; Hurley, J.; Grainger, R. G.; Griessbach, S.; Poulsen, C.; Remedios, J. J.; Riese, M.; Sembhi, H.; Siddans, R.; Waterfall, A.; Zehner, C.

    2012-08-01

    The infrared limb spectra of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on board the Envisat satellite include detailed information on tropospheric clouds and polar stratospheric clouds (PSC). However, no consolidated cloud product is available for the scientific community. Here we describe a fast prototype processor for cloud parameter retrieval from MIPAS (MIPclouds). Retrieval of parameters such as cloud top height, temperature, and extinction are implemented, as well as retrieval of microphysical parameters, e.g. effective radius and the integrated quantities over the limb path (surface area density and volume density). MIPclouds classifies clouds as either liquid or ice cloud in the upper troposphere and polar stratospheric clouds types in the stratosphere based on statistical combinations of colour ratios and brightness temperature differences. Comparison of limb measurements of clouds with model results or cloud parameters from nadir looking instruments is often difficult due to different observation geometries. We therefore introduce a new concept, the limb-integrated surface area density path (ADP). By means of validation and radiative transfer calculations of realistic 2-D cloud fields as input for a blind test retrieval (BTR), we demonstrate that ADP is an extremely valuable parameter for future comparison with model data of ice water content, when applying limb integration (ray tracing) through the model fields. In addition, ADP is used for a more objective definition of detection thresholds of the applied detection methods. Based on BTR, a detection threshold of ADP = 107 μm2 cm-2 and an ice water content of 10-5 g m-3 is estimated, depending on the horizontal and vertical extent of the cloud. Intensive validation of the cloud detection methods shows that the limb-sounding MIPAS instrument has a sensitivity in detecting stratospheric and tropospheric clouds similar to that of space- and ground-based lidars, with a tendency

  13. Resolving ice cloud optical thickness biases between CALIOP and MODIS using infrared retrievals

    NASA Astrophysics Data System (ADS)

    Holz, Robert E.; Platnick, Steven; Meyer, Kerry; Vaughan, Mark; Heidinger, Andrew; Yang, Ping; Wind, Gala; Dutcher, Steven; Ackerman, Steven; Amarasinghe, Nandana; Nagle, Fredrick; Wang, Chenxi

    2016-04-01

    Despite its importance as one of the key radiative properties that determines the impact of upper tropospheric clouds on the radiation balance, ice cloud optical thickness (IOT) has proven to be one of the more challenging properties to retrieve from space-based remote sensing measurements. In particular, optically thin upper tropospheric ice clouds (cirrus) have been especially challenging due to their tenuous nature, extensive spatial scales, and complex particle shapes and light-scattering characteristics. The lack of independent validation motivates the investigation presented in this paper, wherein systematic biases between MODIS Collection 5 (C5) and CALIOP Version 3 (V3) unconstrained retrievals of tenuous IOT (< 3) are examined using a month of collocated A-Train observations. An initial comparison revealed a factor of 2 bias between the MODIS and CALIOP IOT retrievals. This bias is investigated using an infrared (IR) radiative closure approach that compares both products with MODIS IR cirrus retrievals developed for this assessment. The analysis finds that both the MODIS C5 and the unconstrained CALIOP V3 retrievals are biased (high and low, respectively) relative to the IR IOT retrievals. Based on this finding, the MODIS and CALIOP algorithms are investigated with the goal of explaining and minimizing the biases relative to the IR. For MODIS we find that the assumed ice single-scattering properties used for the C5 retrievals are not consistent with the mean IR COT distribution. The C5 ice scattering database results in the asymmetry parameter (g) varying as a function of effective radius with mean values that are too large. The MODIS retrievals have been brought into agreement with the IR by adopting a new ice scattering model for Collection 6 (C6) consisting of a modified gamma distribution comprised of a single habit (severely roughened aggregated columns); the C6 ice cloud optical property models have a constant g ≈ 0.75 in the mid-visible spectrum

  14. Resolving ice cloud optical thickness biases between CALIOP and MODIS using infrared retrievals

    NASA Astrophysics Data System (ADS)

    Holz, R. E.; Platnick, S.; Meyer, K.; Vaughan, M.; Heidinger, A.; Yang, P.; Wind, G.; Dutcher, S.; Ackerman, S.; Amarasinghe, N.; Nagle, F.; Wang, C.

    2015-10-01

    Despite its importance as one of the key radiative properties that determines the impact of upper tropospheric clouds on the radiation balance, ice cloud optical thickness (IOT) has proven to be one of the more challenging properties to retrieve from space-based remote sensing measurements. In particular, optically thin upper tropospheric ice clouds (cirrus) have been especially challenging due to their tenuous nature, extensive spatial scales, and complex particle shapes and light scattering characteristics. The lack of independent validation motivates the investigation presented in this paper, wherein systematic biases between MODIS Collection 5 (C5) and CALIOP Version 3 (V3) unconstrained retrievals of tenuous IOT (< 3) are examined using a month of collocated A-Train observations. An initial comparison revealed a factor of two bias between the MODIS and CALIOP IOT retrievals. This bias is investigated using an infrared (IR) radiative closure approach that compares both products with MODIS IR cirrus retrievals developed for this assessment. The analysis finds that both the MODIS C5 and the unconstrained CALIOP V3 retrievals are biased (high and low, respectively) relative to the IR IOT retrievals. Based on this finding, the MODIS and CALIOP algorithms are investigated with the goal of explaining and minimizing the biases relative to the IR. For MODIS we find that the assumed ice single scattering properties used for the C5 retrievals are not consistent with the mean IR COT distribution. The C5 ice scattering database results in the asymmetry parameter (g) varying as a function of effective radius with mean values that are too large. The MODIS retrievals have been brought into agreement with the IR by adopting a new ice scattering model for Collection 6 (C6) consisting of a modified gamma distribution comprised of a single habit (severely roughened aggregated columns); the C6 ice cloud optical property models have a constant g ~ 0.75 in the mid-visible spectrum

  15. Development of an Algorithm for MODIS and VIIRS Cloud Optical Property Data Record Continuity

    NASA Astrophysics Data System (ADS)

    Meyer, K.; Platnick, S. E.; Ackerman, S. A.; Heidinger, A. K.; Holz, R.; Wind, G.; Amarasinghe, N.; Marchant, B.

    2015-12-01

    The launch of Suomi NPP in the fall of 2011 began the next generation of U.S. operational polar orbiting environmental observations. Similar to MODIS, the VIIRS imager provides visible through IR observations at moderate spatial resolution with a 1330 LT equatorial crossing consistent with MODIS on the Aqua platform. However, unlike MODIS, VIIRS lacks key water vapor and CO2 absorbing channels used by the MODIS cloud algorithms for high cloud detection and cloud-top property retrievals. In addition, there is a significant change in the spectral location of the 2.1μm shortwave-infrared channel used by MODIS for cloud optical/microphysical retrievals. Given the instrument differences between MODIS EOS and VIIRS S-NPP/JPSS, we discuss our adopted method for merging the 15+ year MODIS observational record with VIIRS in order to generate cloud optical property data record continuity across the observing systems. The optical property retrieval code uses heritage algorithms that produce the existing MODIS cloud optical and microphysical properties product (MOD06). As explained in other presentations submitted to this session, the NOAA AWG/CLAVR-x cloud-top property algorithm and a common MODIS-VIIRS cloud mask feed into the optical property algorithm to account for the different channel sets of the two imagers. Data granule and aggregated examples for the current version of the algorithm will be shown.

  16. Students as Ground Observers for Satellite Cloud Retrieval Validation

    NASA Technical Reports Server (NTRS)

    Chambers, Lin H.; Costulis, P. Kay; Young, David F.; Rogerson, Tina M.

    2004-01-01

    The Students' Cloud Observations On-Line (S'COOL) Project was initiated in 1997 to obtain student observations of clouds coinciding with the overpass of the Clouds and the Earth's Radiant Energy System (CERES) instruments on NASA's Earth Observing System satellites. Over the past seven years we have accumulated more than 9,000 cases worldwide where student observations are available within 15 minutes of a CERES observation. This paper reports on comparisons between the student and satellite data as one facet of the validation of the CERES cloud retrievals. Available comparisons include cloud cover, cloud height, cloud layering, and cloud visual opacity. The large volume of comparisons allows some assessment of the impact of surface cover, such as snow and ice, reported by the students. The S'COOL observation database, accessible via the Internet at http://scool.larc.nasa.gov, contains over 32,000 student observations and is growing by over 700 observations each month. Some of these observations may be useful for assessment of other satellite cloud products. In particular, some observing sites have been making hourly observations of clouds during the school day to learn about the diurnal cycle of cloudiness.

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

    NASA Astrophysics Data System (ADS)

    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; Barbosa, Henrique M. J.; Pöschl, Ulrich; Andreae, Meinrat O.

    2016-05-01

    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.

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

    PubMed

    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; Barbosa, Henrique M J; Pöschl, Ulrich; Andreae, Meinrat O

    2016-05-24

    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

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

    PubMed Central

    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

  20. Fast cloud parameter retrievals of MIPAS/Envisat

    NASA Astrophysics Data System (ADS)

    Spang, R.; Arndt, K.; Dudhia, A.; Höpfner, M.; Hoffmann, L.; Hurley, J.; Grainger, R. G.; Griessbach, S.; Poulsen, C.; Remedios, J. J.; Riese, M.; Sembhi, H.; Siddans, R.; Waterfall, A.; Zehner, C.

    2011-12-01

    The infrared limb spectra of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on board the Envisat satellite include detailed information on tropospheric clouds and polar stratospheric clouds (PSC). However, no consolidated cloud product is available for the scientific community. Here we describe a fast prototype processor for cloud parameter retrieval from MIPAS (MIPclouds). Retrieval of parameters such as cloud top height, temperature, and extinction are implemented, as well as of microphysical parameters, e.g. effective radius and the integrated quantities over the limb path (surface area density and volume density). MIPclouds classifies clouds as either liquid or ice cloud in the upper troposphere and polar stratospheric clouds types in the stratosphere based on statistical combinations of colour ratios and brightness temperature differences. Comparison of limb measurements of clouds with model results or cloud parameters from nadir looking instruments is often difficult due to different observation geometries. We therefore introduce a new concept, the limb-integrated surface area density path (ADP). By means of validation and radiative transfer calculations of realistic 2-D cloud fields as input for a blind test retrieval (BTR), we demonstrate that ADP is an extremely valuable parameter for future comparison with 3-D model data of ice water content, when applying limb integration (ray tracing) through the model fields. In addition, ADP is used for a more objective definition of a cloud detection threshold. Based on BTR, a detection threshold for ADP of 107 μm2 cm-2 and an ice water content of 10-5 g m-3 is estimated, depending on the horizontal and vertical extent of the cloud. Intensive validation of the cloud detection methods shows that the limb-sounding MIPAS instrument has a sensitivity in detecting stratospheric and tropospheric clouds similar to that of space- and ground-based lidars, with a tendency for higher cloud top heights

  1. The Aquarius Salinity Retrieval Algorithm: Early Results

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

    The Aquarius L-band radiometer/scatterometer system is designed to provide monthly salinity maps at 150 km spatial scale to a 0.2 psu accuracy. The sensor was launched on June 10, 2011, aboard the Argentine CONAE SAC-D spacecraft. The L-band radiometers and the scatterometer have been taking science data observations since August 25, 2011. The first part of this presentation gives an overview over the Aquarius salinity retrieval algorithm. The instrument calibration 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 O2, 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. This is based on the radar backscatter measurements by the scatterometer. 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 and an auxiliary field for the sea surface temperature. In the current processing (as of writing this abstract) only v-pol TB are used for this last process and NCEP winds are used for the roughness correction. Before the salinity algorithm can be operationally implemented and its accuracy assessed by comparing versus in situ measurements, an extensive calibration and validation

  2. Accuracy Assessments of Cloud Droplet Size Retrievals from Polarized Reflectance Measurements by the Research Scanning Polarimeter

    NASA Technical Reports Server (NTRS)

    Alexandrov, Mikhail Dmitrievic; Cairns, Brian; Emde, Claudia; Ackerman, Andrew S.; vanDiedenhove, Bastiaan

    2012-01-01

    We present an algorithm for the retrieval of cloud droplet size distribution parameters (effective radius and variance) from the Research Scanning Polarimeter (RSP) measurements. The RSP is an airborne prototype for the Aerosol Polarimetery Sensor (APS), which was on-board of the NASA Glory satellite. This instrument measures both polarized and total reflectance in 9 spectral channels with central wavelengths ranging from 410 to 2260 nm. The cloud droplet size retrievals use the polarized reflectance in the scattering angle range between 135deg and 165deg, where they exhibit the sharply defined structure known as the rain- or cloud-bow. The shape of the rainbow is determined mainly by the single scattering properties of cloud particles. This significantly simplifies both forward modeling and inversions, while also substantially reducing uncertainties caused by the aerosol loading and possible presence of undetected clouds nearby. In this study we present the accuracy evaluation of our algorithm based on the results of sensitivity tests performed using realistic simulated cloud radiation fields.

  3. Cloud Optical Depth Retrievals from Solar Background "signal" of Micropulse Lidars

    NASA Technical Reports Server (NTRS)

    Chiu, J. Christine; Marshak, A.; Wiscombe, W.; Valencia, S.; Welton, E. J.

    2007-01-01

    Pulsed lidars are commonly used to retrieve vertical distributions of cloud and aerosol layers. It is widely believed that lidar cloud retrievals (other than cloud base altitude) are limited to optically thin clouds. Here we demonstrate that lidars can retrieve optical depths of thick clouds using solar background light as a signal, rather than (as now) merely a noise to be subtracted. Validations against other instruments show that retrieved cloud optical depths agree within 10-15% for overcast stratus and broken clouds. In fact, for broken cloud situations one can retrieve not only the aerosol properties in clear-sky periods using lidar signals, but also the optical depth of thick clouds in cloudy periods using solar background signals. This indicates that, in general, it may be possible to retrieve both aerosol and cloud properties using a single lidar. Thus, lidar observations have great untapped potential to study interactions between clouds and aerosols.

  4. Cloud retrieval using ship-based spectral transmissivity measurements

    NASA Astrophysics Data System (ADS)

    Brueckner, M.; Macke, A.; Wendisch, M.; Kanitz, T.; Pospichal, B.

    2013-05-01

    Within the scope of the OCEANET-Project (autonomous measurement platforms for energy and material exchange between ocean and atmosphere) on board of the research vessel Polarstern clouds have been investigated over the Atlantic Ocean under different atmospheric conditions and climate zones by active and passive remote sensing. An existing measurement platform, including lidar, microwave radiometer, all sky camera and broadband radiation sensors, has been extended by spectral radiation measurements with the COmpact RAdiation measurements System (CORAS). CORAS measures spectral downward radiances and irradiances in the visible to near-infrared wavelength region. The data were corrected to consider the movements of the ship and with it the misalignment of the sensor plane from earth's horizon. Using observed and modeled spectral transmitted radiances cloud properties such as cloud optical thickness (τ) and effective radius (reff) were retrieved. The vertical cloud structure with limitations for thick clouds is obtained from lidar and microwave radiometer measurements. The all sky camera provides information on the horizontal cloud variability. Cloud optical thickness and effective radius, will be retrieved by using a plane parallel radiative transfer model.

  5. MERIS albedo climatology for FRESCO+ O2 A-band cloud retrieval

    NASA Astrophysics Data System (ADS)

    Popp, C.; Wang, P.; Brunner, D.; Stammes, P.; Zhou, Y.; Grzegorski, M.

    2011-03-01

    A new global albedo climatology for Oxygen A-band cloud retrievals is presented. The climatology is based on MEdium Resolution Imaging Spectrometer (MERIS) Albedomap data and its favourable impact on the derivation of cloud fraction is demonstrated for the FRESCO+ (Fast Retrieval Scheme for Clouds from the Oxygen A-band) algorithm. To date, a relatively coarse resolution (1° × 1°) surface reflectance dataset from GOME (Global Ozone Monitoring Experiment) Lambert-equivalent reflectivity (LER) is used in FRESCO+. The GOME LER climatology does not account for the usually higher spatial resolution of UV/VIS instruments designed for trace gas remote sensing which introduces several artefacts, e.g. in regions with sharp spectral contrasts like coastlines or over bright surface targets. Therefore, MERIS black-sky albedo (BSA) data from the period October 2002 to October 2006 were aggregated to a grid of 0.25° × 0.25° for each month of the year and for different spectral channels. In contrary to other available surface reflectivity datasets, MERIS includes channels at 754 nm and 775 nm which are located close to the spectral windows required for O2 A-band cloud retrievals. The MERIS BSA in the near-infrared compares well to Moderate Resolution Imaging Spectroradiometer (MODIS) derived BSA with an average difference lower than 1% and a correlation coefficient of 0.98. However, when relating MERIS BSA to GOME LER a distinctly lower correlation (0.80) and enhanced scatter is found. Effective cloud fractions from two exemplary months (January and July 2006) of Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) data were subsequently derived with FRESCO+ and compared to those from the Heidelberg Iterative Cloud Retrieval Utilities (HICRU) algorithm. The MERIS climatology generally improves FRESCO+ effective cloud fractions. In particular small cloud fractions are in better agreement with HICRU. This is of importance for atmospheric trace gas

  6. Diagnosing Aircraft Icing Potential from Satellite Cloud Retrievals

    NASA Technical Reports Server (NTRS)

    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

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

    ERIC Educational Resources Information Center

    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)

  8. A new approach to retrieving cirrus cloud height with a combination of MODIS 1.24- and 1.38-μm channels

    NASA Astrophysics Data System (ADS)

    Wang, Chenxi; Ding, Shouguo; Yang, Ping; Baum, Bryan; Dessler, Andrew E.

    2012-12-01

    An approach is developed for inferring cloud top height (CTH) by using two shortwave infrared (SWIR) channels (i.e., 1.24- and 1.38-μm) with similar cloud scattering and absorption properties but very different water vapor absorption properties. This channel combination is used to accurately infer the column water vapor amount above the clouds, from which the CTH can be retrieved. The approach performs best for ice clouds located in the upper troposphere. For those clouds, our approach performs as well or better than the current operational cloud height retrieval algorithm adopted by the MODIS science team.

  9. Cloud masking and surface classi[|#12#|]cation algorithm for GCOM-C1/SGLI purpose

    NASA Astrophysics Data System (ADS)

    Chen, N.; Tanikawa, T.; Li, W.; Stamnes, K. H.; Hori, M.; Aoki, T.

    2011-12-01

    We have developed new algorithms for cloud masking and surface classification of The Global Change Observation Mission-Climate/Second-generation Global Imager (GCOM-C1/SGLI). Our goal is to identify clear-sky pixels of snow-covered surfaces for our snow parameter retrieval algorithms. The cloud masking algorithm includes multiple indices including the Normalized Difference Snow Index (NDSI), the Normalized Difference Vegetation Index (NDVI), a Brightness Temperature test and the R1.38 test over land and ocean to provide a collective index of cloud screening of the scene. The Normalized Difference Ice Index (NDII) test along with a R0.67/R0.86 test provide discrimination of snow and sea ice over the ocean. Our algorithm is further validated against the MODIS MOD35 cloud product and the CLoud and Aerosol Unbiased Decision Intellectual Algorithm (CLAUDIA) results.

  10. Near-Real Time Cloud Retrievals from Operational and Research Meteorological Satellites

    NASA Technical Reports Server (NTRS)

    Minnis, Patrick; Nguyen, Louis; Palilonda, Rabindra; Heck, Patrick W.; Spangenberg, Douglas A.; Doelling, David R.; Ayers, J. Kirk; Smith, William L., Jr.; Khaiyer, Mandana M.; Trepte, Qing Z.; Avey, Lance A.; Chang, Fu-Lung; Yost, Chris R.; Chee, Thad L.; Sun-Mack, Szedung

    2008-01-01

    A set of cloud retrieval algorithms developed for CERES and applied to MODIS data have been adapted to analyze other satellite imager data in near-real time. The cloud products, including single-layer cloud amount, top and base height, optical depth, phase, effective particle size, and liquid and ice water paths, are being retrieved from GOES- 10/11/12, MTSAT-1R, FY-2C, and Meteosat imager data as well as from MODIS. A comprehensive system to normalize the calibrations to MODIS has been implemented to maximize consistency in the products across platforms. Estimates of surface and top-of-atmosphere broadband radiative fluxes are also provided. Multilayered cloud properties are retrieved from GOES-12, Meteosat, and MODIS data. Native pixel resolution analyses are performed over selected domains, while reduced sampling is used for full-disk retrievals. Tools have been developed for matching the pixel-level results with instrumented surface sites and active sensor satellites. The calibrations, methods, examples of the products, and comparisons with the ICESat GLAS lidar are discussed. These products are currently being used for aircraft icing diagnoses, numerical weather modeling assimilation, and atmospheric radiation research and have potential for use in many other applications.

  11. Retrievals of cloud microphysical properties from the Research Scanning Polarimeter measurements made during PODEX field campaign

    NASA Astrophysics Data System (ADS)

    Alexandrov, M. D.; Cairns, B.; Sinclair, K.

    2013-12-01

    We present the retrievals of cloud droplet size distribution parameters (effective radius and variance) from the Research Scanning Polarimeter (RSP) measurements made during NASA's POlarimeter Definition EXperiment (PODEX), which was based in Palmdale, California in January - February 2013. The RSP is an airborne prototype for the Aerosol Polarimetery Sensor (APS), which was built for the NASA Glory Mission project. This instrument measures both polarized and total reflectances in 9 spectral channels with center wavelengths of 410, 470, 555, 670, 865, 960, 1590, 1880 and 2250 nm. The RSP is a push broom scanner making samples at 0.8 degree intervals within 60 degrees from nadir in both forward and backward directions. The data from actual RSP scans is aggregated into "virtual" scans, each consisting of all reflectances (at a variety of scattering angles) from a single point on the ground or at the cloud top. In the case of water clouds the rainbow is observed in the polarized reflectances in the scattering angle range between 135 and 170 degrees. It has a unique signature that is being used to accurately determine the droplet size and is not affected by cloud morphology. Simple parametric fitting algorithm applied to these polarized reflectances provides retrievals of the droplet effective radius and variance assuming a prescribed size distribution shape (gamma distribution). In addition to this, we use a non-parametric method, Rainbow Fourier Transform (RFT), which allows to retrieve the droplet size distribution a parametric model. Of particular interest is the information contained in droplet size distribution width, which is indicative of cloud life cycle. The absorbing band method is also applied to RSP total reflectance observations. The difference in the retrieved droplet size between polarized and absorbing band techniques is expected to reflect the strength of the vertical gradient in cloud liquid water content. In addition to established retrieval

  12. Cloud Coverage and Height Distribution from the GLAS Polar Orbiting Lidar: Comparison to Passive Cloud Retrievals

    NASA Technical Reports Server (NTRS)

    Spinhime, J. D.; Palm, S. P.; Hlavka, D. L.; Hart, W. D.; Mahesh, A.

    2004-01-01

    The Geoscience Laser Altimeter System (GLAS) began full on orbit operations in September 2003. A main application of the two-wavelength GLAS lidar is highly accurate detection and profiling of global cloud cover. Initial analysis indicates that cloud and aerosol layers are consistently detected on a global basis to cross-sections down to 10(exp -6) per meter. Images of the lidar data dramatically and accurately show the vertical structure of cloud and aerosol to the limit of signal attenuation. The GLAS lidar has made the most accurate measurement of global cloud coverage and height to date. In addition to the calibrated lidar signal, GLAS data products include multi level boundaries and optical depth of all transmissive layers. Processing includes a multi-variable separation of cloud and aerosol layers. An initial application of the data results is to compare monthly cloud means from several months of GLAS observations in 2003 to existing cloud climatologies from other satellite measurement. In some cases direct comparison to passive cloud retrievals is possible. A limitation of the lidar measurements is nadir only sampling. However monthly means exhibit reasonably good global statistics and coverage results, at other than polar regions, compare well with other measurements but show significant differences in height distribution. For polar regions where passive cloud retrievals are problematic and where orbit track density is greatest, the GLAS results are particularly an advance in cloud cover information. Direct comparison to MODIS retrievals show a better than 90% agreement in cloud detection for daytime, but less than 60% at night. Height retrievals are in much less agreement. GLAS is a part of the NASA EOS project and data products are thus openly available to the science community (see http://glo.gsfc.nasa.gov).

  13. Clouds and Shortwave Fluxes at Nauru. Part I: Retrieved Cloud Properties

    SciTech Connect

    McFarlane, Sally A.; Evans, K. F.

    2004-03-01

    The datasets currently being collected at the Atmospheric Radiation Measurement (ARM)Program's sites on the islands of Nauru and Manus represent the longest time series of ground based cloud measurements available in the tropical western Pacific region. This paper presents statistics of retrieved microphysical properties of non-precipitating liquid and ice clouds and estimates of the shortwave cloud radiative effect from 12 months of data collected at the Nauru site between June 1999 and May 2000. Non-precipitating liquid clouds observed at Nauru were primarily shallow cumulus with bases less than 1 km. Of the retrieved liquid clouds, 90% had liquid water path less than 100 grams per square meter. The average retrieved effective radius was 9.9 microns, however limitations in the sensitivity of the two-channel microwave radiometer led to large uncertainties in retrieved effective radius and liquid water content for the shallow clouds typically seen at Nauru. The frequency of liquid c loud detection, height of liquid cloud base, and magnitude of the shortwave cloud radiative effect showed a clear diurnal cycle, which is most likely related to the island effect and the existence of the Nauru cloud plume. An average shortwave radiative cloud effect of -55.4 watts per square meter was estimated over the study period, which is significantly lower than studies during the Tropical Ocean Global Atmosphere Coupled Ocean Atmosphere Response Experiment (TOGA-COARE). Differences in clear sky modeling do not seem large enough to account for this difference, indicating that there was probably less cloud over Nauru during the current study period than during TOGA-COARE, which is consistent with the phase of the El-Nino Southern Oscillation (ENSO) during the two periods.

  14. MERIS albedo climatology for FRESCO+ O2 A-band cloud retrieval

    NASA Astrophysics Data System (ADS)

    Popp, C.; Wang, P.; Brunner, D.; Stammes, P.; Zhou, Y.; Grzegorski, M.

    2010-10-01

    A new global albedo climatology for Oxygen A-band cloud retrievals is presented. The climatology is based on MEdium Resolution Imaging Spectrometer (MERIS) Albedomap data and its favourable impact on the derivation of cloud fraction is demonstrated for the FRESCO+ (Fast Retrieval Scheme for Clouds from the Oxygen A-band) algorithm. To date, a relatively coarse resolution (1° × 1°) surface reflectance dataset from GOME (Global Ozone Monitoring Experiment) Lambert-equivalent reflectivity (LER) is used in FRESCO+. The GOME LER climatology does not account for the usually higher spatial resolution of UV/VIS instruments designed for trace gas remote sensing which introduces several artefacts, e.g. in regions with sharp spectral contrasts like coastlines or over bright surface targets. Therefore, MERIS black-sky albedo (BSA) data from the period October 2002 to October 2006 were aggregated to a grid of 0.25° × 0.25° for each month of the year and for different spectral channels. In contrary to other available surface reflectivity datasets, MERIS includes channels at 754 nm and 775 nm which are located close to the spectral windows required for O2 A-band cloud retrievals. The MERIS BSA in the near infrared compares well to Moderate Resolution Imaging Spectroradiometer (MODIS) derived BSA with an average difference lower than 1% and a correlation coefficient of 0.98. However, when relating MERIS BSA to GOME LER a distinctly lower correlation (0.80) and enhanced scatter is found. Effective cloud fractions from two exemplary months (January and July 2006) of Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) data were subsequently derived with FRESCO+ and compared to those from the Heidelberg Iterative Cloud Retrieval Utilities (HICRU) algorithm. The MERIS climatology generally improves FRESCO+ effective cloud fractions. In particular small cloud fractions are in better agreement with HICRU. This is of importance for atmospheric trace gas

  15. MODIS Collection 6 shortwave-derived cloud phase classification algorithm and comparisons with CALIOP

    NASA Astrophysics Data System (ADS)

    Marchant, B.; Platnick, S.; Meyer, K.; Arnold, G. T.; Riedi, J.

    2015-11-01

    Cloud thermodynamic phase (ice, liquid, undetermined) classification is an important first step for cloud retrievals from passive sensors such as MODIS (Moderate-Resolution Imaging Spectroradiometer). Because ice and liquid phase clouds have very different scattering and absorbing properties, an incorrect cloud phase decision can lead to substantial errors in the cloud optical and microphysical property products such as cloud optical thickness or effective particle radius. Furthermore, it is well established that ice and liquid clouds have different impacts on the Earth's energy budget and hydrological cycle, thus accurately monitoring the spatial and temporal distribution of these clouds is of continued importance. For MODIS Collection 6 (C6), the shortwave-derived cloud thermodynamic phase algorithm used by the optical and microphysical property retrievals has been completely rewritten to improve the phase discrimination skill for a variety of cloudy scenes (e.g., thin/thick clouds, over ocean/land/desert/snow/ice surface, etc). To evaluate the performance of the C6 cloud phase algorithm, extensive granule-level and global comparisons have been conducted against the heritage C5 algorithm and CALIOP. A wholesale improvement is seen for C6 compared to C5.

  16. MODIS Collection 6 shortwave-derived cloud phase classification algorithm and comparisons with CALIOP

    NASA Astrophysics Data System (ADS)

    Marchant, Benjamin; Platnick, Steven; Meyer, Kerry; Arnold, G. Thomas; Riedi, Jérôme

    2016-04-01

    Cloud thermodynamic phase (ice, liquid, undetermined) classification is an important first step for cloud retrievals from passive sensors such as MODIS (Moderate Resolution Imaging Spectroradiometer). Because ice and liquid phase clouds have very different scattering and absorbing properties, an incorrect cloud phase decision can lead to substantial errors in the cloud optical and microphysical property products such as cloud optical thickness or effective particle radius. Furthermore, it is well established that ice and liquid clouds have different impacts on the Earth's energy budget and hydrological cycle, thus accurately monitoring the spatial and temporal distribution of these clouds is of continued importance. For MODIS Collection 6 (C6), the shortwave-derived cloud thermodynamic phase algorithm used by the optical and microphysical property retrievals has been completely rewritten to improve the phase discrimination skill for a variety of cloudy scenes (e.g., thin/thick clouds, over ocean/land/desert/snow/ice surface, etc). To evaluate the performance of the C6 cloud phase algorithm, extensive granule-level and global comparisons have been conducted against the heritage C5 algorithm and CALIOP. A wholesale improvement is seen for C6 compared to C5.

  17. Cloud and Cloud Shadow Masking Using Multi-Temporal Cloud Masking Algorithm in Tropical Environmental

    NASA Astrophysics Data System (ADS)

    Candra, D. S.; Phinn, S.; Scarth, P.

    2016-06-01

    A cloud masking approach based on multi-temporal satellite images is proposed. The basic idea of this approach is to detect cloud and cloud shadow by using the difference reflectance values between clear pixels and cloud and cloud shadow contaminated pixels. Several bands of satellite image which have big difference values are selected for developing Multi-temporal Cloud Masking (MCM) algorithm. Some experimental analyses are conducted by using Landsat-8 images. Band 3 and band 4 are selected because they can distinguish between cloud and non cloud. Afterwards, band 5 and band 6 are used to distinguish between cloud shadow and clear. The results show that the MCM algorithm can detect cloud and cloud shadow appropriately. Moreover, qualitative and quantitative assessments are conducted using visual inspections and confusion matrix, respectively, to evaluate the reliability of this algorithm. Comparison between this algorithm and QA band are conducted to prove the reliability of the approach. The results show that MCM better than QA band and the accuracy of the results are very high.

  18. Toward autonomous surface-based infrared remote sensing of polar clouds: cloud-height retrievals

    NASA Astrophysics Data System (ADS)

    Rowe, Penny M.; Cox, Christopher J.; Walden, Von P.

    2016-08-01

    Polar regions are characterized by their remoteness, making measurements challenging, but an improved knowledge of clouds and radiation is necessary to understand polar climate change. Infrared radiance spectrometers can operate continuously from the surface and have low power requirements relative to active sensors. Here we explore the feasibility of retrieving cloud height with an infrared spectrometer that would be designed for use in remote polar locations. Using a wide variety of simulated spectra of mixed-phase polar clouds at varying instrument resolutions, retrieval accuracy is explored using the CO2 slicing/sorting and the minimum local emissivity variance (MLEV) methods. In the absence of imposed errors and for clouds with optical depths greater than ˜ 0.3, cloud-height retrievals from simulated spectra using CO2 slicing/sorting and MLEV are found to have roughly equivalent high accuracies: at an instrument resolution of 0.5 cm-1, mean biases are found to be ˜ 0.2 km for clouds with bases below 2 and -0.2 km for higher clouds. Accuracy is found to decrease with coarsening resolution and become worse overall for MLEV than for CO2 slicing/sorting; however, the two methods have differing sensitivity to different sources of error, suggesting an approach that combines them. For expected errors in the atmospheric state as well as both instrument noise and bias of 0.2 mW/(m2 sr cm-1), at a resolution of 4 cm-1, average retrieval errors are found to be less than ˜ 0.5 km for cloud bases within 1 km of the surface, increasing to ˜ 1.5 km at 4 km. This sensitivity indicates that a portable, surface-based infrared radiance spectrometer could provide an important complement in remote locations to satellite-based measurements, for which retrievals of low-level cloud are challenging.

  19. Retrievals of Cloud Fraction and Cloud Albedo from Surface-based Shortwave Radiation Measurements: A Comparison of 16 Year Measurements

    SciTech Connect

    Xie, Yu; Liu, Yangang; Long, Charles N.; Min, Qilong

    2014-07-27

    Ground-based radiation measurements have been widely conducted to gain information on clouds and the surface radiation budget; here several different techniques for retrieving cloud fraction (Long2006, Min2008 and XL2013) and cloud albedo (Min2008, Liu2011 and XL2013) from ground-based shortwave broadband and spectral radiation measurements are examined, and sixteen years of retrievals collected at the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site are compared. The comparison shows overall good agreement between the retrievals of both cloud fraction and cloud albedo, with noted differences however. The Long2006 and Min2008 cloud fractions are greater on average than the XL2013 values. Compared to Min2008 and Liu2011, the XL2013 retrieval of cloud albedo tends to be greater for thin clouds but smaller for thick clouds, with the differences decreasing with increasing cloud fraction. Further analysis reveals that the approaches that retrieve cloud fraction and cloud albedo separately may suffer from mutual contamination of errors in retrieved cloud fraction and cloud albedo. Potential influences of cloud absorption, land-surface albedo, cloud structure, and measurement instruments are explored.

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

    NASA Technical Reports Server (NTRS)

    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.

  1. A Solar Reflectance Method for Retrieving Cloud Optical Thickness and Droplet Size Over Snow and Ice Surfaces

    NASA Technical Reports Server (NTRS)

    Platnick, S.; Li, J. Y.; King, M. D.; Gerber, H.; Hobbs, P. V.

    1999-01-01

    Cloud optical thickness and effective radius retrievals from solar reflectance measurements are traditionally implemented using a combination of spectral channels that are absorbing and non-absorbing for water particles. Reflectances in non-absorbing channels (e.g., 0.67, 0.86, 1.2 micron spectral window bands) are largely dependent on cloud optical thickness, while longer wavelength absorbing channels (1.6, 2. 1, and 3.7 micron window bands) provide cloud particle size information. Cloud retrievals over ice and snow surfaces present serious difficulties. At the shorter wavelengths, ice is bright and highly variable, both characteristics acting to significantly increase cloud retrieval uncertainty. In contrast, reflectances at the longer wavelengths are relatively small and may be comparable to that of dark open water. A modification to the traditional cloud retrieval technique is devised. The new algorithm uses only a combination of absorbing spectral channels for which the snow/ice albedo is relatively small. Using this approach, retrievals have been made with the MODIS Airborne Simulator (MAS) imager flown aboard the NASA ER-2 from May - June 1998 during the Arctic FIRE-ACE field deployment. Data from several coordinated ER-2 and University of Washington CV-580 in situ aircraft observations of liquid water stratus clouds are examined. MAS retrievals of optical thickness, droplet effective radius, and liquid water path are shown to be in good agreement with the in situ measurements. The initial success of the technique has implications for future operational satellite cloud retrieval algorithms in polar and wintertime regions.

  2. Discrimination of Biomass Burning Smoke and Clouds in MAIAC Algorithm

    NASA Technical Reports Server (NTRS)

    Lyapustin, A.; Korkin, S.; Wang, Y.; Quayle, B.; Laszlo, I.

    2012-01-01

    The multi-angle implementation of atmospheric correction (MAIAC) algorithm makes aerosol retrievals from MODIS data at 1 km resolution providing information about the fine scale aerosol variability. This information is required in different applications such as urban air quality analysis, aerosol source identification etc. The quality of high resolution aerosol data is directly linked to the quality of cloud mask, in particular detection of small (sub-pixel) and low clouds. This work continues research in this direction, describing a technique to detect small clouds and introducing the smoke test to discriminate the biomass burning smoke from the clouds. The smoke test relies on a relative increase of aerosol absorption at MODIS wavelength 0.412 micrometers as compared to 0.47-0.67 micrometers due to multiple scattering and enhanced absorption by organic carbon released during combustion. This general principle has been successfully used in the OMI detection of absorbing aerosols based on UV measurements. This paper provides the algorithm detail and illustrates its performance on two examples of wildfires in US Pacific North-West and in Georgia/Florida of 2007.

  3. Developments of global greenhouse gas retrieval algorithm using Aerosol information from GOSAT-CAI

    NASA Astrophysics Data System (ADS)

    Kim, Woogyung; kim, Jhoon; Jung, Yeonjin; lee, Hanlim; Boesch, Hartmut

    2014-05-01

    Human activities have resulted in increasing atmospheric CO2 concentration since the beginning of Industrial Revolution to reaching CO2 concentration over 400 ppm at Mauna Loa observatory for the first time. (IPCC, 2007). However, our current knowledge of carbon cycle is still insufficient due to lack of observations. Satellite measurement is one of the most effective approaches to improve the accuracy of carbon source and sink estimates by monitoring the global CO2 distributions with high spatio-temporal resolutions (Rayner and O'Brien, 2001; Houweling et al., 2004). Currently, GOSAT has provided valuable information to observe global CO2 trend, enables our extended understanding of CO2 and preparation for future satellite plan. However, due to its physical limitation, GOSAT CO2 retrieval results have low spatial resolution and cannot cover wide area. Another obstruction of GOSAT CO2 retrieval is low data availability mainly due to contamination by clouds and aerosols. Especially, in East Asia, one of the most important aerosol source areas, it is hard to have successful retrieval result due to high aerosol concentration. The main purpose of this study is to improve data availability of GOSAT CO2 retrieval. In this study, current state of CO2 retrieval algorithm development is introduced and preliminary results are shown. This algorithm is based on optimal estimation method and utilized VLIDORT the vector discrete ordinate radiative transfer model. This proto type algorithm, developed from various combinations of state vectors to find accurate CO2 concentration, shows reasonable result. Especially the aerosol retrieval algorithm using GOSAT-CAI measurements, which provide aerosol information for the same area with GOSAT-FTS measurements, are utilized as input data of CO2 retrieval. Other CO2 retrieval algorithms use chemical transport model result or climatologically expected values as aerosol information which is the main reason of low data availability. With

  4. Atmospheric parameterization schemes for satellite cloud property retrieval during FIRE IFO 2

    NASA Technical Reports Server (NTRS)

    Titlow, James; Baum, Bryan A.

    1993-01-01

    Satellite cloud retrieval algorithms generally require atmospheric temperature and humidity profiles to determine such cloud properties as pressure and height. For instance, the CO2 slicing technique called the ratio method requires the calculation of theoretical upwelling radiances both at the surface and a prescribed number (40) of atmospheric levels. This technique has been applied to data from, for example, the High Resolution Infrared Radiometer Sounder (HIRS/2, henceforth HIRS) flown aboard the NOAA series of polar orbiting satellites and the High Resolution Interferometer Sounder (HIS). In this particular study, four NOAA-11 HIRS channels in the 15-micron region are used. The ratio method may be applied to various channel combinations to estimate cloud top heights using channels in the 15-mu m region. Presently, the multispectral, multiresolution (MSMR) scheme uses 4 HIRS channel combination estimates for mid- to high-level cloud pressure retrieval and Advanced Very High Resolution Radiometer (AVHRR) data for low-level (is greater than 700 mb) cloud level retrieval. In order to determine theoretical upwelling radiances, atmospheric temperature and water vapor profiles must be provided as well as profiles of other radiatively important gas absorber constituents such as CO2, O3, and CH4. The assumed temperature and humidity profiles have a large effect on transmittance and radiance profiles, which in turn are used with HIRS data to calculate cloud pressure, and thus cloud height and temperature. For large spatial scale satellite data analysis, atmospheric parameterization schemes for cloud retrieval algorithms are usually based on a gridded product such as that provided by the European Center for Medium Range Weather Forecasting (ECMWF) or the National Meteorological Center (NMC). These global, gridded products prescribe temperature and humidity profiles for a limited number of pressure levels (up to 14) in a vertical atmospheric column. The FIRE IFO 2

  5. An algorithm to retrieve precipitation with synthetic aperture radar

    NASA Astrophysics Data System (ADS)

    Xie, Ya'nan; Liu, Zhikun; An, Dawei

    2016-06-01

    This paper presents a new type of rainfall retrieval algorithm, called the model-oriented statistical and Volterra integration. It is a combination of the model-oriented statistical (MOS) and Volterra integral equation (VIE) approaches. The steps involved in this new algorithm can be briefly illustrated as follows. Firstly, information such as the start point and width of the rain is obtained through pre-analysis of the data received by synthetic aperture radar (SAR). Secondly, the VIE retrieval algorithm is employed over a short distance to obtain information on the shape of the rain. Finally, the rain rate can be calculated by using the MOS retrieval algorithm. Simulation results show that the proposed algorithm is effective and simple, and can lead to time savings of nearly 50% compared with MOS. An example of application of SAR data is also discussed, involving the retrieval of precipitation information over the South China Sea.

  6. A Comparison of Aerosol Parameterizations in the ACOS XCO2 Retrieval Algorithm

    NASA Astrophysics Data System (ADS)

    Nelson, R. R.; O'Dell, C.; Crisp, D.; Eldering, A.; Frankenberg, C.; Gunson, M. R.; Natraj, V.; Fu, D.

    2014-12-01

    An effective parameterization of clouds and aerosols in retrieval algorithms is essential for reducing measurement errors and biases in estimates of the column-averaged dry-air mole fraction of carbon dioxide (XCO2) from space-based measurements of near-infrared reflected sunlight. The NASA Atmospheric CO2 Observations from Space (ACOS) XCO2 retrieval algorithm has evolved significantly over the past several years in an effort to more accurately represent the impact of clouds and aerosols on XCO2. Recent ACOS algorithm versions up to build 3.4 used a water cloud type, ice cloud type, and two generic aerosol types for each sounding. ACOS build 3.5 uses the same cloud parameterization, but was modified to replace the "one-size-fits-all" aerosol scheme. Build 3.5 uses a monthly aerosol climatology based on the Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis to choose the two most likely aerosol types for a given measurement location, along with typical optical depths. The five MERRA types available for selection are sulfate, dust, sea salt, organic carbon, and black carbon. The algorithm then uses a pre-assigned Gaussian width and height and fits for the aerosol amount and peak height based on information from the 760 nm O2 A-band and the CO2 bands centered near 1610 and 2060 nm. Here we compare ACOS builds 3.4 and build 3.5 to quantify the impact of the aerosol scheme update. Two types of tests were performed. Simulated Orbiting Carbon Observatory 2 (OCO-2) retrievals and their associated aerosol and cloud profiles were compared to the "true" aerosol and cloud profiles used to create the simulated environment for a given measurement. The retrieval algorithms were also run on Greenhouse gases Observing SATellite (GOSAT) observations and compared to AErosol RObotic NETwork (AERONET) aerosol optical depth measurements in order to quantify the ability of the algorithms to retrieve information about aerosol optical depths. XCO2 errors

  7. Improved Cloud and Snow Screening in MAIAC Aerosol Retrievals Using Spectral and Spatial Analysis

    NASA Technical Reports Server (NTRS)

    Lyapustin, A.; Wang, Y.; Laszlo, I.; Kokrkin, S.

    2012-01-01

    An improved cloud/snow screening technique in the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is described. It is implemented as part of MAIAC aerosol retrievals based on analysis of spectral residuals and spatial variability. Comparisons with AERONET aerosol observations and a large-scale MODIS data analysis show strong suppression of aerosol optical thickness outliers due to unresolved clouds and snow. At the same time, the developed filter does not reduce the aerosol retrieval capability at high 1 km resolution in strongly inhomogeneous environments, such as near centers of the active fires. Despite significant improvement, the optical depth outliers in high spatial resolution data are and will remain the problem to be addressed by the application-dependent specialized filtering techniques.

  8. Extending MODIS Deep Blue Aerosol Retrieval Coverage to Cases of Absorbing Aerosols Above Clouds: First Results

    NASA Technical Reports Server (NTRS)

    Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Shinozuka, Y.; Schmid, B.

    2015-01-01

    Absorbing smoke or mineral dust aerosols above clouds (AAC) are a frequent occurrence in certain regions and seasons. Operational aerosol retrievals from sensors like MODIS omit AAC because they are designed to work only over cloud-free scenes. However, AAC can in principle be quantified by these sensors in some situations (e.g. Jethva et al., 2013; Meyer et al., 2013). We present a summary of some analyses of the potential of MODIS-like instruments for this purpose, along with two case studies using airborne observations from the Ames Airborne Tracking Sunphotometer (AATS; http://geo.arc.nasa.gov/sgg/AATS-website/) as a validation data source for a preliminary AAC algorithm applied to MODIS measurements. AAC retrievals will eventually be added to the MODIS Deep Blue (Hsu et al., 2013) processing chain.

  9. Cloud cover retrieved from skyviewer: A validation with human observations

    NASA Astrophysics Data System (ADS)

    Kim, Bu-Yo; Jee, Joon-Bum; Zo, Il-Sung; Lee, Kyu-Tae

    2016-02-01

    Cloud cover information is used alongside weather forecasts in various fields of research; however, ground observation of cloud cover is conducted by human observers, a method that is subjective and has low temporal and spatial resolutions. To address these problems, we have developed an improved algorithm to calculate cloud cover using sky image data obtained with Skyviewer equipment. The algorithm uses a variable threshold for the Red Blue Ratio (RBR), determined from the frequency distribution of the Green Blue Ratio (GBR), to calculate cloud cover more accurately than existing algorithms. To verify the accuracy of the algorithm, we conducted daily, monthly, seasonal, and yearly statistical analyses of human observations of cloud cover, obtained every hour from 0800 to 1700 Local Standard Time (LST) for the entirety of 2012 at the Gangwon Regional Meteorological Administration (GRMA), Korea. A case study compared daily images taken at 1200 LST in each season with pixel images of cloud cover calculated by our improved algorithm. The selected cases yielded a high correlation coefficient of 0.93 with the GRMA data. A monthly case study showed low root mean square errors (RMSEs) and high correlation coefficients (Rs) for December (RMSE = 1.64 tenths and R = 0.92) and August (RMSE = 1.43 tenths and R = 0.91). In addition, seasonal cases yielded a high correlation of 0.9 and 87% consistency within ± 2 tenths for winter and a correlation of 0.83 and 82% consistency for summer, when cases of cloud-free or overcast conditions are frequent. Annual analyses showed that the bias of GRMA and Skyviewer cloud cover data for 2012 was -0.36 tenth, and the RMSE was 2.12 tenths, with the GRMA data showing more cloud cover. Considering that the GRMA and Skyviewer data were gathered at different spatial locations, GRMA and Skyviewer data were well correlated (R = 0.87) and showed a consistency of 80% in their cloud cover data (consistent within ± 2 tenths).

  10. Retrieval of Aerosol Within Cloud Fields Using the MODIS Airborne Simulator (MAS)

    NASA Astrophysics Data System (ADS)

    Munchak, L. A.; Levy, R. C.; Mattoo, S.; Patadia, F.; Wilcox, E. M.; Marshak, A.

    2015-12-01

    Passive satellite remote sensing has become essential for obtaining global information about aerosol properties, including aerosol optical depth (AOD) and aerosol fine mode fraction (FMF). However, due to the spatial resolution of satellite aerosol products (typically 3 km and larger), observing aerosol within dense partly cloudy fields is difficult from space. Here, we apply an adapted version of the MODIS Collection 6 dark target algorithm to the 50-meter MODIS airborne simulator retrieved reflectances measured during the SEAC4RS campaign during 2013 to robustly retrieve aerosol with a 500 m resolution. We show good agreement with AERONET and MODIS away from cloud, suggesting that the algorithm is working as expected. However, closer to cloud, significant AOD increases are observed. We investigate the cause of these AOD increases, including examining the potential for undetected cloud contamination, reflectance increases due to unconsidered 3D radiative effects, and the impact of humidification on aerosol properties. In combination with other sensors that flew in SEAC4RS, these high-resolution observations of aerosol in partly cloudy fields can be used to characterize the radiative impact of the "twilight zone" between cloud and aerosol which is typically not considered in current estimates of direct aerosol radiative forcing.

  11. Development of an Algorithm Suite for MODIS and VIIRS Cloud Data Record Continuity

    NASA Astrophysics Data System (ADS)

    Platnick, S. E.; Holz, R.; Heidinger, A. K.; Ackerman, S. A.; Meyer, K.; Frey, R.; Wind, G.; Amarasinghe, N.

    2014-12-01

    The launch of Suomi NPP in the fall of 2011 began the next generation of the U.S. operational polar orbiting environmental observations. Similar to MODIS, the VIIRS imager provides visible through IR observations at moderate spatial resolution with a 1330 LT equatorial crossing consistent with MODIS on the Aqua platform. However, unlike MODIS, VIIRS lacks key water vapor and CO2 absorbing channels used by the MODIS cloud algorithms for high cloud detection and cloud-top property retrievals (including emissivity), as well as multilayer cloud detection. In addition, there is a significant change in the spectral location of the 2.1 μm shortwave-infrared channel used by MODIS for cloud microphysical retrievals. The climate science community will face an interruption in the continuity of key global cloud data sets once the NASA EOS Terra and Aqua sensors cease operation. Given the instrument differences between MODIS EOS and VIIRS S-NPP/JPSS, we discuss methods for merging the 14+ year MODIS observational record with VIIRS/CrIS observations in order to generate cloud climate data record continuity across the observing systems. The main approach used by our team was to develop a cloud retrieval algorithm suite that is applied only to the common MODIS and VIIRS spectral channels. The suite uses heritage algorithms that produce the existing MODIS cloud mask (MOD35), MODIS cloud optical and microphysical properties (MOD06), and NOAA AWG/CLAVR-x cloud-top property products. Global monthly results from this hybrid algorithm suite (referred to as MODAWG) will be shown. Collocated CALIPSO comparisons will be shown that can independently evaluate inter-instrument product consistency for a subset of the MODAWG datasets.

  12. The resolution-dependence of satellite-based cloud retrievals: First results from ASTER and MODIS observations

    NASA Astrophysics Data System (ADS)

    Werner, F.; Wind, G.; Zhang, Z.; Platnick, S. E.; Di Girolamo, L.

    2015-12-01

    The spatial resolution dependence of retrieved optical and microphysical cloud properties of marine shallow convective water clouds is presented using data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), as well as the Moderate-resolution Imaging Spectroradiometer (MODIS) onboard the scientific research satellite Terra. Both instruments are characterized by vastly different spatial resolutions of 15m (ASTER) and 1000m (MODIS), respectively. Cloud optical thickness (τ) and effective droplet radius (reff) are derived by means of the Cross-platform HIgh resolution Multi-instrument AtmosphEric Retrieval Algorithms (CHIMAERA) system which yields MODIS-like cloud property retrievals via a shared-core architecture. The retrieval algorithm employs a standard bi-spectral retrieval scheme with two reflectances (ρ) in the visible to near-infrared spectral wavelength range (VNIR, 0.86μm) and shortwave infrared spectral wavelength range (SWIR, 2.1μm), respectively. For an exemplary granule the high-resolution ρ sampled by the ASTER instrument are aggregated from 15m to an increasingly coarse spatial resolution between (30-1000m). Subsequently, retrieved τ and reff from aggregated ρ are compared to the mean of the high-resolution cloud properties within the aggregated pixels. The differences in retrieved τ and reff are related to the sub-pixel covariance of ρ in the VNIR and SWIR band, as well as the inhomogeneity index (i.e., the ratio of standard deviation to mean value of ρ in the VNIR). This analysis highlights the impact of sub-pixel inhomogeneity and plane-parallel assumptions in the cloud property retrieval. CHIMAERA also allows for a comparison of ASTER and MODIS retrievals without introducing biases due to individual instrument algorithms. Retrieved τ and reff from the 1000m aggregated ρ sampled by ASTER are compared to the retrieved cloud properties provided by MODIS. The presented results highlight the different

  13. Global Comparison of Microwave and Optical Cloud Liquid Water Path Retrievals

    NASA Astrophysics Data System (ADS)

    Chellappan, S.; Horváth, Á.

    2009-04-01

    In this study, we analyzed one year of spatially and temporally matched microwave and optical cloud liquid water path (CLWP) estimates from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. Specifically, microwave CLWPs were produced by the Wentz algorithm, while optical CLWPs were parameterized from MODIS cloud optical thickness and droplet effective radius. We considered both the operational MODIS estimates assuming vertically homogeneous clouds and an adiabatic cloud model, which reduces operational values by approximately 17%. We then systematically investigated differences between AMSR-E and MODIS CLWP retrievals in warm oceanic clouds as a function of a variety of factors such as cloud fraction, geographic location, effective radius profile, cloud temperature, and rain rate. When all cloud fractions were considered, AMSR-E CLWPs tended to overestimate operational MODIS CLWPs with corresponding global annual means of 58 g/m2 and 40 g/m2, respectively, the rms difference was 42 g/m2, and the datasets were only moderately correlated with a coefficient of 0.71. Global monthly means showed similar AMSR-E overestimations of 15-25 g/m2. These results were due to a high bias in microwave retrievals, which rapidly increased with decreasing cloud fraction. This AMSR-E overestimation in broken cloud fields is not yet fully understood; however, we found a positive microwave bias in cloud-free scenes too, which was a strong function of surface wind speed and column water vapor amount, indicating possible shortcomings in the surface emission parameterization and gaseous absorption models of the Wentz algorithm. In strictly overcast cases, the datasets were significantly better correlated with a coefficient of 0.83, but now operational MODIS retrievals were on average 16% larger than AMSR-E values. The global annual means were 91 g/m2 and 108 g/m2 for AMSR-E and MODIS

  14. [Retrieval of the Optical Thickness and Cloud Top Height of Cirrus Clouds Based on AIRS IR High Spectral Resolution Data].

    PubMed

    Cao, Ya-nan; Wei, He-li; Dai, Cong-ming; Zhang, Xue-hai

    2015-05-01

    A study was carried out to retrieve optical thickness and cloud top height of cirrus clouds from the Atmospheric Infrared Sounder (AIRS) high spectral resolution data in 1070~1135 cm-1 IR band using a Combined Atmospheric Radiative Transfer model (CART) by brightness temperature difference between model simulation and AIRS observation. The research is based on AIRS LIB high spectral infrared observation data combined with Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product data. Brightness temperature spectra based, on the retrieved cirrus optical thickness and cloud top height were simulated and compared with brightness temperature spectra of AIRS observation in the 650~1150 cm-1 band. The cirrus optical thickness and cloud top height retrieved were compared with brightness temperature of AIRS for channel 760 (900.56 cm-1, 11. 1 µm) and cirrus reflectance of MODIS cloud product. And cloud top height retrieved was compared with cloud top height from MODIS. Results show that the brightness temperature spectra simulated were basically consistent with AIRS observation under the condition of retrieval in the 650~1150 cm-1 band. It means that CART can be used to simulate AIRS brightness temperature spectra. The retrieved cirrus parameters are consistent with brightness temperature of AIRS for channel 11. 1 µm with low brightness temperature corresponding to large cirrus optical thickness and high cloud top height. And the retrieved cirrus parameters are consistent with cirrus reflectance of MODIS cloud product with high cirrus reflectance corresponding to large cirrus optical thickness and high cloud top height. Correlation coefficient of brightness temperature between retrieved cloud top height and MODIS cloud top height was relatively high. They are mostly located in the range of 8. 5~11.5 km, and their probability distribution trend is approximately identical. CART model is feasible to retrieve cirrus properties, and the retrieval is reliable. PMID

  15. Fuzzy Information Retrieval Using Genetic Algorithms and Relevance Feedback.

    ERIC Educational Resources Information Center

    Petry, Frederick E.; And Others

    1993-01-01

    Describes an approach that combines concepts from information retrieval, fuzzy set theory, and genetic programing to improve weighted Boolean query formulation via relevance feedback. Highlights include background on information retrieval systems; genetic algorithms; subproblem formulation; and preliminary results based on a testbed. (Contains 12…

  16. MISR research-aerosol-algorithm refinements for dark water retrievals

    NASA Astrophysics Data System (ADS)

    Limbacher, J. A.; Kahn, R. A.

    2014-11-01

    We explore systematically the cumulative effect of many assumptions made in the Multi-angle Imaging SpectroRadiometer (MISR) research aerosol retrieval algorithm with the aim of quantifying the main sources of uncertainty over ocean, and correcting them to the extent possible. A total of 1129 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 558 nm AOD < 0.10, a high bias of 0.024 is reduced by about one-third when (1) ocean surface under-light is included and the assumed whitecap reflectance at 672 nm is increased, (2) physically based adjustments in particle microphysical properties and mixtures are made, (3) an adaptive pixel selection method is used, (4) spectral reflectance uncertainty is estimated from vicarious calibration, and (5) minor radiometric calibration changes are made for the 672 and 866 nm channels. Applying (6) more stringent cloud screening (setting the maximum fraction not-clear to 0.50) brings all median spectral biases to about 0.01. When all adjustments except more stringent cloud screening are applied, and a modified acceptance criterion is used, the Root-Mean-Square-Error (RMSE) decreases for all wavelengths by 8-27% for the research algorithm relative to the baseline, and is 12-36% lower than the RMSE for the Version 22 MISR standard algorithm (SA, with no adjustments applied). At 558 nm, 87% of AOD data falls within the greater of 0.05 or 20% of validation values; 62% of the 446 nm AOD data, and > 68% of 558, 672, and 866 nm AOD values fall within the greater of 0.03 or 10%. For the Ångström exponent (ANG), 67% of 1119 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 17% compared to the SA, and the median absolute error drops by

  17. Visualizing and improving the robustness of phase retrieval algorithms

    SciTech Connect

    Tripathi, Ashish; Leyffer, Sven; Munson, Todd; Wild, Stefan M.

    2015-06-01

    Coherent x-ray diffractive imaging is a novel imaging technique that utilizes phase retrieval and nonlinear optimization methods to image matter at nanometer scales. We explore how the convergence properties of a popular phase retrieval algorithm, Fienup's HIO, behave by introducing a reduced dimensionality problem allowing us to visualize and quantify convergence to local minima and the globally optimal solution. We then introduce generalizations of HIO that improve upon the original algorithm's ability to converge to the globally optimal solution.

  18. Comparison of cloud properties between cloudsat retrievals and airplane measurements in mixed-phase cloud layers of weak convective and stratus clouds

    NASA Astrophysics Data System (ADS)

    Qiu, Yujun; Choularton, Thomas; Crosier, Jonathan; Liu, Zixia

    2015-12-01

    Cloud microphysical properties including liquid and ice particle number concentration (NC), liquid water content (LWC), ice water content (IWC) and effective radius (RE) were retrieved from CloudSat data for a weakly convective and a widespread stratus cloud. Within the mixed-phase cloud layers, liquid-phase fractions needed to be assumed in the data retrieval process, and one existing linear ( p 1) and two exponential ( p 2 and p 3) functions, which estimate the liquid-phase fraction as a function of subfreezing temperature (from -20°C to 0°C), were tested. The retrieved NC, LWC, IWC and RE using p 1 were on average larger than airplane measurements in the same cloud layer. Function p 2 performed better than p 1 or p 3 in retrieving the NCs of cloud droplets in the convective cloud, while function p 1 performed better in the stratus cloud. Function p 3 performed better in LWC estimation in both convective and stratus clouds. The REs of cloud droplets calculated using the retrieved cloud droplet NC and LWC were closer to the values of in situ observations than those retrieved directly using the p 1 function. The retrieved NCs of ice particles in both convective and stratus clouds, on the assumption of liquid-phase fraction during the retrieval of liquid droplet NCs, were closer to those of airplane observations than on the assumption of function p 1.

  19. Cloud and Aerosol Retrieval for the 2001 GLAS Satellite Lidar Mission

    NASA Technical Reports Server (NTRS)

    Hart, William D.; Palm, Stephen P.; Spinhirne, James D.

    2000-01-01

    The Geoscience Laser Altimeter System (GLAS) is scheduled for launch in July of 2001 aboard the Ice, Cloud and Land Elevation Satellite (ICESAT). In addition to being a precision altimeter for mapping the height of the Earth's icesheets, GLAS will be an atmospheric lidar, sensitive enough to detect gaseous, aerosol, and cloud backscatter signals, at horizontal and vertical resolutions of 175 and 75m, respectively. GLAS will be the first lidar to produce temporally continuous atmospheric backscatter profiles with nearly global coverage (94-degree orbital inclination). With a projected operational lifetime of five years, GLAS will collect approximately six billion lidar return profiles. The large volume of data dictates that operational analysis algorithms, which need to keep pace with the data yield of the instrument, must be efficient. So, we need to evaluate the ability of operational algorithms to detect atmospheric constituents that affect global climate. We have to quantify, in a statistical manner, the accuracy and precision of GLAS cloud and aerosol observations. Our poster presentation will show the results of modeling studies that are designed to reveal the effectiveness and sensitivity of GLAS in detecting various atmospheric cloud and aerosol features. The studies consist of analyzing simulated lidar returns. Simulation cases are constructed either from idealized renditions of atmospheric cloud and aerosol layers or from data obtained by the NASA ER-2 Cloud Lidar System (CLS). The fabricated renditions permit quantitative evaluations of operational algorithms to retrieve cloud and aerosol parameters. The use of observational data permits the evaluations of performance for actual atmospheric conditions. The intended outcome of the presentation is that climatology community will be able to use the results of these studies to evaluate and quantify the impact of GLAS data upon atmospheric modeling efforts.

  20. Automated retrieval of cloud and aerosol properties from the ARM Raman lidar, part 1: feature detection

    SciTech Connect

    Thorsen, Tyler J.; Fu, Qiang; Newsom, Rob K.; Turner, David D.; Comstock, Jennifer M.

    2015-11-01

    A Feature detection and EXtinction retrieval (FEX) algorithm for the Atmospheric Radiation Measurement (ARM) program’s Raman lidar (RL) has been developed. Presented here is part 1 of the FEX algorithm: the detection of features including both clouds and aerosols. The approach of FEX is to use multiple quantities— scattering ratios derived using elastic and nitro-gen channel signals from two fields of view, the scattering ratio derived using only the elastic channel, and the total volume depolarization ratio— to identify features using range-dependent detection thresholds. FEX is designed to be context-sensitive with thresholds determined for each profile by calculating the expected clear-sky signal and noise. The use of multiple quantities pro-vides complementary depictions of cloud and aerosol locations and allows for consistency checks to improve the accuracy of the feature mask. The depolarization ratio is shown to be particularly effective at detecting optically-thin features containing non-spherical particles such as cirrus clouds. Improve-ments over the existing ARM RL cloud mask are shown. The performance of FEX is validated against a collocated micropulse lidar and observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite over the ARM Darwin, Australia site. While we focus on a specific lidar system, the FEX framework presented here is suitable for other Raman or high spectral resolution lidars.

  1. Comparison of four machine learning algorithms for their applicability in satellite-based optical rainfall retrievals

    NASA Astrophysics Data System (ADS)

    Meyer, Hanna; Kühnlein, Meike; Appelhans, Tim; Nauss, Thomas

    2016-03-01

    Machine learning (ML) algorithms have successfully been demonstrated to be valuable tools in satellite-based rainfall retrievals which show the practicability of using ML algorithms when faced with high dimensional and complex data. Moreover, recent developments in parallel computing with ML present new possibilities for training and prediction speed and therefore make their usage in real-time systems feasible. This study compares four ML algorithms - random forests (RF), neural networks (NNET), averaged neural networks (AVNNET) and support vector machines (SVM) - for rainfall area detection and rainfall rate assignment using MSG SEVIRI data over Germany. Satellite-based proxies for cloud top height, cloud top temperature, cloud phase and cloud water path serve as predictor variables. The results indicate an overestimation of rainfall area delineation regardless of the ML algorithm (averaged bias = 1.8) but a high probability of detection ranging from 81% (SVM) to 85% (NNET). On a 24-hour basis, the performance of the rainfall rate assignment yielded R2 values between 0.39 (SVM) and 0.44 (AVNNET). Though the differences in the algorithms' performance were rather small, NNET and AVNNET were identified as the most suitable algorithms. On average, they demonstrated the best performance in rainfall area delineation as well as in rainfall rate assignment. NNET's computational speed is an additional advantage in work with large datasets such as in remote sensing based rainfall retrievals. However, since no single algorithm performed considerably better than the others we conclude that further research in providing suitable predictors for rainfall is of greater necessity than an optimization through the choice of the ML algorithm.

  2. Comparison of machine learning algorithms for their applicability in satellite-based optical rainfall retrievals

    NASA Astrophysics Data System (ADS)

    Meyer, Hanna; Kühnlein, Meike; Appelhans, Tim; Nauss, Thomas

    2015-04-01

    Machine learning (ML) algorithms have been successfully evaluated as valuable tools in satellite-based rainfall retrievals which shows the high potential of ML algorithms when faced with high dimensional and complex data. Moreover, the recent developments in parallel computing with ML offer new possibilities in terms of training and predicting speed and therefore makes their usage in real time systems feasible. The present study compares four ML algorithms for rainfall area detection and rainfall rate assignment during daytime, night-time and twilight using MSG SEVIRI data over Germany. Satellite-based proxies for cloud top height, cloud top temperature, cloud phase and cloud water path are applied as predictor variables. As machine learning algorithms, random forests (RF), neural networks (NNET), averaged neural networks (AVNNET) and support vector machines (SVM) are chosen. The comparison is realised in three steps. First, an extensive tuning study is carried out to customise each of the models. Secondly, the models are trained using the optimum values of model parameters found in the tuning study. Finally, the trained models are used to detect rainfall areas and to assign rainfall rates using an independent validation datasets which is compared against ground-based radar data. To train and validate the models, the radar-based RADOLAN RW product from the German Weather Service (DWD) is used which provides area-wide gauge-adjusted hourly precipitation information. Though the differences in the performance of the algorithms were rather small, NNET and AVNNET have been identified as the most suitable algorithms. On average, they showed the best performance in rainfall area delineation as well as in rainfall rate assignment. The fast computation time of NNET allows to work with large datasets as it is required in remote sensing based rainfall retrievals. However, since none of the algorithms performed considerably better that the others we conclude that research

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

    NASA Technical Reports Server (NTRS)

    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.

  4. An Automated Cloud-edge Detection Algorithm Using Cloud Physics and Radar Data

    NASA Technical Reports Server (NTRS)

    Ward, Jennifer G.; Merceret, Francis J.; Grainger, Cedric A.

    2003-01-01

    An automated cloud edge detection algorithm was developed and extensively tested. The algorithm uses in-situ cloud physics data measured by a research aircraft coupled with ground-based weather radar measurements to determine whether the aircraft is in or out of cloud. Cloud edges are determined when the in/out state changes, subject to a hysteresis constraint. The hysteresis constraint prevents isolated transient cloud puffs or data dropouts from being identified as cloud boundaries. The algorithm was verified by detailed manual examination of the data set in comparison to the results from application of the automated algorithm.

  5. Active and Passive Microwave Retrieval Algorithm for Hydrometeor Concentration Profiles: Application to the HAMP Instrument

    NASA Astrophysics Data System (ADS)

    Orlandi, E.; Mech, M.; Crewell, S.; Lammert, A.

    2012-12-01

    Clouds and precipitation play an important role in the atmospheric water cycle and radiation budget. Unfortunately, the understanding of the processes involved in cloud and precipitation formation and their description in global and regional models are still poor. To improve our understanding of these processes and to reduce model uncertainties, new observation and retrieval techniques are needed. The upcoming Global Precipitation Mission (GPM) provides a combination of a 36 GHz cloud radar and a suite of passive microwave instruments. In the retrieval development process for this and other upcoming missions, airborne platforms are a useful tool to test the algorithms exploiting the synergy of active and passive microwave instruments, and to validate satellite retrievals. In this respect HAMP (Microwave Package for HALO, the High Altitude Long Range aircraft), consisting of a 36 GHz Doppler cloud radar and a 26-channel radiometer, is an ideal test-bed. HAMP radiometers have frequencies along absorption lines (22, 60, 118 and 183 GHz) and in window regions, overlapping with those of AMSU A and B. HAMP will participate in early 2013 in the dedicated remote sensing HALO mission NARVAL (Next-generation Aircraft Remote-sensing for VALidation studies). During NARVAL, the HALO payload will include a water vapor lidar and drop sondes in addition to HAMP. The NARVAL campaign will thus be a excellent opportunity to test a newly developed retrieval algorithm, which exploits the synergy between passive and active microwave observations. In this work we present a Bayesian algorithm to retrieve precipitation rate, liquid and frozen hydrometeor concentration, as well as temperature and humidity profiles from the synergetic use of active and passive microwave nadir observations. Temperature and humidity are derived solely from passive radiometer measurements while the combined cloud radar and radiometer observations are used to retrieve hydrometeor concentration profiles. Lidar

  6. Improving warm rain estimation in the PERSIANN-CCS satellite-based retrieval algorithm

    NASA Astrophysics Data System (ADS)

    Karbalaee, N.; Hsu, K. L.; Sorooshian, S.

    2015-12-01

    The Precipitation Estimation from remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) is one of the algorithms being integrated in the IMERG (Integrated Multi-Satellite Retrievals for the Global Precipitation Mission GPM) to estimate precipitation at 0.04 lat-long scale every 30-minute. PERSIANN-CCS extracts features from infrared cloud image segmentation from three brightness temperature thresholds (220K, 235K, and 253K). Warm raining clouds with brightness temperature higher than 253K are not covered from the current algorithm. To improve rain detection from warm rain, in this study, the cloud image segmentation threshold to cover warmer clouds is extended from 253K to 300K. Several other temperature thresholds between 253K and 300K were also examined. K-means cluster algorithm was used to classify extracted image features to 400 groups. Rainfall rates from each cluster were retrained using radar rainfall measurements. Case studies were carried out over CONUS to investigate the ability to improve detection of warm rainfall from segmentation and image classification using warmer temperature thresholds. Satellite image and radar rainfall data in both summer and winter seasons were used in the experiments in year 2012 as a training data. Overall results show that rain detection from warm clouds is significantly improved. However, it also shows that the false rain detection is also relatively increased when the segmentation temperature is increased.

  7. Iterative Algorithms for Ptychographic Phase Retrieval

    SciTech Connect

    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.

  8. Why different passive microwave algorithms give different soil moisture retrievals

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Several algorithms have been used to retrieve surface soil moisture from brightness temperature observations provided by low frequency microwave satellite sensors such as the Advanced Microwave Scanning Radiometer on NASA EOS satellite Aqua (AMSR-E). Most of these algorithms have originated from the...

  9. Daytime Cloud Property Retrievals Over the Arctic from Multispectral MODIS Data

    NASA Technical Reports Server (NTRS)

    Spangenberg, Douglas A.; Trepte, Qing; Minnis, Patrick; Uttal, Taneil

    2004-01-01

    Improving climate model predictions over Earth's polar regions requires a complete understanding of polar clouds properties. Passive satellite remote sensing techniques can be used to retrieve macro and microphysical properties of polar cloud systems. However, over the Arctic, there is minimal contrast between clouds and the background snow surface observed in satellite data, especially for visible wavelengths. This makes it difficult to identify clouds and retrieve their properties from space. Variable snow and ice cover, temperature inversions, and the predominance of mixed-phase clouds further complicate cloud property identification. For this study, the operational Clouds and the Earth s Radiant Energy System (CERES) cloud mask is first used to discriminate clouds from the background surface in Terra Moderate Resolution Imaging Spectroradiometer (MODIS) data. A solar-infrared infrared nearinfrared technique (SINT) first used by Platnick et al. (2001) is used here to retrieve cloud properties over snow and ice covered regions.

  10. Implementation of Cloud Retrievals for Tropospheric Emission Spectrometer (TES) Atmospheric Retrievals: Part 1. Description and Characterization of Errors on Trace Gas Retrievals

    NASA Technical Reports Server (NTRS)

    Kulawik, Susan S.; Worden, John; Eldering, Annmarie; Bowman, Kevin; Gunson, Michael; Osterman, Gregory B.; Zhang, Lin; Clough, Shepard A.; Shephard, Mark W.; Beer, Reinhard

    2006-01-01

    We develop an approach to estimate and characterize trace gas retrievals in the presence of clouds in high spectral measurements of upwelling radiance in the infrared spectral region (650-2260/cm). The radiance contribution of clouds is parameterized in terms of a set of frequency-dependent nonscattering optical depths and a cloud height. These cloud parameters are retrieved jointly with surface temperature, emissivity, atmospheric temperature, and trace gases such as ozone from spectral data. We demonstrate the application of this approach using data from the Tropospheric Emission Spectrometer (TES) and test data simulated with a scattering radiative transfer model. We show the value of this approach in that it results in accurate estimates of errors for trace gas retrievals, and the retrieved values improve over the initial guess for a wide range of cloud conditions. Comparisons are made between TES retrievals of ozone, temperature, and water to model fields from the Global Modeling and Assimilation Office (GMAO), temperature retrievals from the Atmospheric Infrared Sounder (AIRS), tropospheric ozone columns from the Goddard Earth Observing System (GEOS) GEOS-Chem, and ozone retrievals from the Total Ozone Mapping Spectrometer (TOMS). In each of these cases, this cloud retrieval approach does not introduce observable biases into TES retrievals.

  11. Ice hydrometeor profile retrieval algorithm for high frequency microwave radiometers: application to the CoSSIR instrument during TC4

    NASA Astrophysics Data System (ADS)

    Evans, K. F.; Wang, J. R.; O'C Starr, D.; Heymsfield, G.; Li, L.; Tian, L.; Lawson, R. P.; Heymsfield, A. J.; Bansemer, A.

    2012-04-01

    A Bayesian algorithm to retrieve profiles of cloud ice water content (IWC), ice particle size (Dme), and relative humidity from millimeter-wave/submillimeter-wave radiometers is presented. The first part of the algorithm prepares an a priori file with cumulative distribution functions (CDFs) and empirical orthogonal functions (EOFs) of profiles of temperature, relative humidity, three ice particle parameters (IWC, Dme, distribution width), and two liquid cloud parameters. The a priori CDFs and EOFs are derived from CloudSat radar reflectivity profiles and associated ECMWF temperature and relative humidity profiles combined with three cloud microphysical probability distributions obtained from in situ cloud probes. The second part of the algorithm uses the CDF/EOF file to perform a Bayesian retrieval with a hybrid technique that uses Monte Carlo integration (MCI) or, when too few MCI cases match the observations, uses optimization to maximize the posterior probability function. The very computationally intensive Markov chain Monte Carlo (MCMC) method also may be chosen as a solution method. The radiative transfer model assumes mixtures of several shapes of randomly oriented ice particles, and here random aggregates of hexagonal plates, spheres, and dendrites are used for tropical convection. A new physical model of stochastic dendritic snowflake aggregation is developed. The retrieval algorithm is applied to data from the Compact Scanning Submillimeter-wave Imaging Radiometer (CoSSIR) flown on the ER-2 aircraft during the Tropical Composition, Cloud and Climate Coupling (TC4) experiment in 2007. Example retrievals with error bars are shown for nadir profiles of IWC, Dme, and relative humidity, and nadir and conical scan swath retrievals of ice water path and average Dme. The ice cloud retrievals are evaluated by retrieving integrated 94 GHz backscattering from CoSSIR for comparison with the Cloud Radar System (CRS) flown on the same aircraft. The rms difference in

  12. The Earth Clouds and Radiation Explorer (EarthCARE) Mission: Cloud and Aerosol Lidar and Imager algorithms.

    NASA Astrophysics Data System (ADS)

    Donovan, David; van Zadelhoff, Gerd-Jan; Wandinger, Ulla; Hünerbein, Anjah; Fischer, Jurgen; von Bismarck, Jonas; Eisinger, Michael; Lajas, Dulce; Wehr, Tobias

    2015-04-01

    The value of multi-sensor remote sensing applied to clouds and aerosol has become clear in recent years. For example, combinations of instruments including passive radiometers, lidars and cloud radars have proved invaluable for their ability to retrieve profiles of cloud macrophysical and microphysical properties. This is amply illustrated by various results from the US-DoE ARM (and similar) surface sites as well as results from data collected by sensors aboard the A-train satellites CloudSat, CALIPSO, and Terra. The Earth Clouds Aerosol and Radiation Explorer (EarthCARE) mission is a combined ESA/JAXA mission to be launched in 2018 which has been designed with sensor-synergy playing a key role. The mission consists of a cloud-profiling radar (CPR), a high-spectral resolution cloud/aerosol lidar (ATLID), a cloud/aerosol multi-spectral imager (MSI), and a three-view broad-band radiometer (BBR). The mission will deliver cloud, aerosol and radiation products focusing on horizontal scales ranging from 1 km to 10 km. EarthCARE data will be used in multiple ways ranging from model evaluation studies, to GCM-orientated cloud microphysical property parameterization development, to data assimilation activities. Recently a number of activities, funded by ESA, have kicked-off which will ultimately deliver operational algorithms for EarthCARE. One of these activities is the "Atmospheric Products from Imager and Lidar" (APRIL) project which focuses on the development of lidar, imager and combined lidar-imager cloud and aerosol algorithms. In this presentation an overview of the APRIL algorithms within the wider context of the planned EarthCARE processing chain will be given.

  13. The Retrieval of Ice-Cloud Properties from Cloud Radar and Lidar Synergy.

    NASA Astrophysics Data System (ADS)

    Tinel, Claire; Testud, Jacques; Pelon, Jacques; Hogan, Robin J.; Protat, Alain; Delanoë, Julien; Bouniol, Dominique

    2005-06-01

    Clouds are an important component of the earth's climate system. A better description of their microphysical properties is needed to improve radiative transfer calculations. In the framework of the Earth, Clouds, Aerosols, and Radiation Explorer (EarthCARE) mission preparation, the radar-lidar (RALI) airborne system, developed at L'Institut Pierre Simon Laplace (France), can be used as an airborne demonstrator. This paper presents an original method that combines cloud radar (94-95 GHz) and lidar data to derive the radiative and microphysical properties of clouds. It combines the apparent backscatter reflectivity from the radar and the apparent backscatter coefficient from the lidar. The principle of this algorithm relies on the use of a relationship between the extinction coefficient and the radar specific attenuation, derived from airborne microphysical data and Mie scattering calculations. To solve radar and lidar equations in the cloud region where signals can be obtained from both instruments, the extinction coefficients at some reference range z0 must be known. Because the algorithms are stable for inversion performed from range z0 toward the emitter, z0 is chosen at the farther cloud boundary as observed by the lidar. Then, making an assumption of a relationship between extinction coefficient and backscattering coefficient, the whole extinction coefficient, the apparent reflectivity, cloud physical parameters, the effective radius, and ice water content profiles are derived. This algorithm is applied to a blind test for downward-looking instruments where the original profiles are derived from in situ measurements. It is also applied to real lidar and radar data, obtained during the 1998 Cloud Lidar and Radar Experiment (CLARE'98) field project when a prototype airborne RALI system was flown pointing at nadir. The results from the synergetic algorithm agree reasonably well with the in situ measurements.

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

    NASA Technical Reports Server (NTRS)

    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.

  15. Genetic refinement of cloud-masking algorithms for the multi-spectral thermal imager (MTI)

    SciTech Connect

    Hirsch, K. L.; Davis, A. B.; Harvey, N. R.; Rohde, C. A.; Brumby, Steven P.

    2001-01-01

    The Multi-spectral Thermal Imager (MTI) is a high-performance remote-sensing satellite designed, owned and operated by the U.S. Department of Energy, with a dual mission in environmental studies and in nonproliferation. It has enhanced spatial and radiometric resolutions and state-of-the-art calibration capabilities. This instrumental development puts a new burden on retrieval algorithm developers to pass this accuracy on to the inferred geophysical parameters. In particular, the atmospheric correction scheme assumes the intervening atmosphere will be modeled as a plane-parallel horizontally-homogeneous medium. A single dense-enough cloud in view of the ground target can easily offset reality from the calculations, hence the need for a reliable cloud-masking algorithm. Pixel-scale cloud detection relies on the simple facts that clouds are generally whiter, brighter, and colder than the ground below; spatially, dense clouds are generally large on some scale. This is a good basis for searching multispectral datacubes for cloud signatures. However, the resulting cloud mask can be very sensitive to the choice of thresholds in whiteness, brightness, temperature, and connectivity. We have used a genetic algorithm trained on (MODIS Airborne Simulator-based) simulated MTI data to design a cloud-mask. Its performance is compared quantitatively to hand-drawn training data and to the EOS/Terra MODIS cloud mask.

  16. Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms: validation against collocated MODIS and CALIOP data

    NASA Astrophysics Data System (ADS)

    Taylor, Thomas E.; O'Dell, Christopher W.; Frankenberg, Christian; Partain, Philip T.; Cronk, Heather Q.; Savtchenko, Andrey; Nelson, Robert R.; Rosenthal, Emily J.; Chang, Albert Y.; Fisher, Brenden; Osterman, Gregory B.; Pollock, Randy H.; Crisp, David; Eldering, Annmarie; Gunson, Michael R.

    2016-03-01

    The objective of the National Aeronautics and Space Administration's (NASA) Orbiting Carbon Observatory-2 (OCO-2) mission is to retrieve the column-averaged carbon dioxide (CO2) dry air mole fraction (XCO2) from satellite measurements of reflected sunlight in the near-infrared. These estimates can be biased by clouds and aerosols, i.e., contamination, within the instrument's field of view. Screening of the most contaminated soundings minimizes unnecessary calls to the computationally expensive Level 2 (L2) XCO2 retrieval algorithm. Hence, robust cloud screening methods have been an important focus of the OCO-2 algorithm development team. Two distinct, computationally inexpensive cloud screening algorithms have been developed for this application. The A-Band Preprocessor (ABP) retrieves the surface pressure using measurements in the 0.76 µm O2 A band, neglecting scattering by clouds and aerosols, which introduce photon path-length differences that can cause large deviations between the expected and retrieved surface pressure. The Iterative Maximum A Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) retrieves independent estimates of the CO2 and H2O column abundances using observations taken at 1.61 µm (weak CO2 band) and 2.06 µm (strong CO2 band), while neglecting atmospheric scattering. The CO2 and H2O column abundances retrieved in these two spectral regions differ significantly in the presence of cloud and scattering aerosols. The combination of these two algorithms, which are sensitive to different features in the spectra, provides the basis for cloud screening of the OCO-2 data set.To validate the OCO-2 cloud screening approach, collocated measurements from NASA's Moderate Resolution Imaging Spectrometer (MODIS), aboard the Aqua platform, were compared to results from the two OCO-2 cloud screening algorithms. With tuning of algorithmic threshold parameters that allows for processing of ≃ 20-25 % of all OCO-2 soundings

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

    NASA Astrophysics Data System (ADS)

    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.

  18. Development and application of a probability distribution retrieval scheme to the remote sensing of clouds and precipitation

    NASA Astrophysics Data System (ADS)

    McKague, Darren Shawn

    2001-12-01

    The statistical properties of clouds and precipitation on a global scale are important to our understanding of climate. Inversion methods exist to retrieve the needed cloud and precipitation properties from satellite data pixel-by-pixel that can then be summarized over large data sets to obtain the desired statistics. These methods can be quite computationally expensive, and typically don't provide errors on the statistics. A new method is developed to directly retrieve probability distributions of parameters from the distribution of measured radiances. The method also provides estimates of the errors on the retrieved distributions. The method can retrieve joint distributions of parameters that allows for the study of the connection between parameters. A forward radiative transfer model creates a mapping from retrieval parameter space to radiance space. A Monte Carlo procedure uses the mapping to transform probability density from the observed radiance histogram to a two- dimensional retrieval property probability distribution function (PDF). An estimate of the uncertainty in the retrieved PDF is calculated from random realizations of the radiance to retrieval parameter PDF transformation given the uncertainty of the observed radiances, the radiance PDF, the forward radiative transfer, the finite number of prior state vectors, and the non-unique mapping to retrieval parameter space. The retrieval method is also applied to the remote sensing of precipitation from SSM/I microwave data. A method of stochastically generating hydrometeor fields based on the fields from a numerical cloud model is used to create the precipitation parameter radiance space transformation. The impact of vertical and horizontal variability within the hydrometeor fields has a significant impact on algorithm performance. Beamfilling factors are computed from the simulated hydrometeor fields. The beamfilling factors vary quite a bit depending upon the horizontal structure of the rain. The

  19. Enhanced Deep Blue Aerosol Retrieval Algorithm: The Second Generation

    NASA Technical Reports Server (NTRS)

    Hsu, N. C.; Jeong, M.-J.; Bettenhausen, C.; Sayer, A. M.; Hansell, R.; Seftor, C. S.; Huang, J.; Tsay, S.-C.

    2013-01-01

    The aerosol products retrieved using the MODIS collection 5.1 Deep Blue algorithm have provided useful information about aerosol properties over bright-reflecting land surfaces, such as desert, semi-arid, and urban regions. However, many components of the C5.1 retrieval algorithm needed to be improved; for example, the use of a static surface database to estimate surface reflectances. This is particularly important over regions of mixed vegetated and non- vegetated surfaces, which may undergo strong seasonal changes in land cover. In order to address this issue, we develop a hybrid approach, which takes advantage of the combination of pre-calculated surface reflectance database and normalized difference vegetation index in determining the surface reflectance for aerosol retrievals. As a result, the spatial coverage of aerosol data generated by the enhanced Deep Blue algorithm has been extended from the arid and semi-arid regions to the entire land areas.

  20. Iterative phase retrieval algorithms. Part II: Attacking optical encryption systems.

    PubMed

    Guo, Changliang; Liu, Shi; Sheridan, John T

    2015-05-20

    The modified iterative phase retrieval algorithms developed in Part I [Guo et al., Appl. Opt.54, 4698 (2015)] are applied to perform known plaintext and ciphertext attacks on amplitude encoding and phase encoding Fourier-transform-based double random phase encryption (DRPE) systems. It is shown that the new algorithms can retrieve the two random phase keys (RPKs) perfectly. The performances of the algorithms are tested by using the retrieved RPKs to decrypt a set of different ciphertexts encrypted using the same RPKs. Significantly, it is also shown that the DRPE system is, under certain conditions, vulnerable to ciphertext-only attack, i.e., in some cases an attacker can decrypt DRPE data successfully when only the ciphertext is intercepted. PMID:26192505

  1. EVOLVING RETRIEVAL ALGORITHMS WITH A GENETIC PROGRAMMING SCHEME

    SciTech Connect

    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.

  2. Evolving retrieval algorithms with a genetic programming scheme

    NASA Astrophysics Data System (ADS)

    Theiler, James P.; Harvey, Neal R.; Brumby, Steven P.; Szymanski, John J.; Alferink, Steve; Perkins, Simon J.; Porter, Reid B.; Bloch, Jeffrey J.

    1999-10-01

    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 reflected 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.

  3. Algorithm for Automated Detection of Edges of Clouds

    NASA Technical Reports Server (NTRS)

    Ward, Jennifer G.; Merceret, Francis J.

    2006-01-01

    An algorithm processes cloud-physics data gathered in situ by an aircraft, along with reflectivity data gathered by ground-based radar, to determine whether the aircraft is inside or outside a cloud at a given time. A cloud edge is deemed to be detected when the in/out state changes, subject to a hysteresis constraint. Such determinations are important in continuing research on relationships among lightning, electric charges in clouds, and decay of electric fields with distance from cloud edges.

  4. A new high spectral resolution lidar technique for direct retrievals of cloud and aerosol extinction

    NASA Astrophysics Data System (ADS)

    Yorks, J. E.; McGill, M. J.; Hlavka, D. L.

    2014-12-01

    The Airborne Cloud-Aerosol Transport System (ACATS) is a Doppler lidar system and high spectral resolution lidar (HSRL) recently developed at NASA Goddard Space Flight Center (GSFC). ACATS passes the returned atmospheric backscatter through a single etalon and divides the transmitted signal into several channels (wavelength intervals), which are measured simultaneously and independently (Figure 1). Both the particulate and molecular scattered signal can be directly and unambiguously measured, allowing for direct retrievals of particle extinction. The broad Rayleigh-scattered spectrum is imaged as a nearly flat background, illustrated in Figure 1c. The integral of the particulate backscattered spectrum is analogous to the aerosol measurement from the typical absorption filter HSRL technique in that the molecular and particulate backscatter components can be separated (Figure 1c and 1d). The main difference between HSRL systems that use the iodine filter technique and the multichannel etalon technique used in the ACATS instrument is that the latter directly measures the spectral broadening of the particulate backscatter using the etalon to filter out all backscattered light with the exception of a narrow wavelength interval (1.5 picometers for ACATS) that contains the particulate spectrum (grey, Figure 1a). This study outlines the method and retrieval algorithms for ACATS data products, focusing on the HSRL derived cloud and aerosol properties. While previous ground-based multi-channel etalon systems have been built and operated for wind retrievals, there has been no airborne demonstration of the technique and the method has not been used to derive HSRL cloud and aerosol properties. ACATS has flown on the NASA ER-2 during flights over Alaska in July 2014 and as part of the Wallops Airborne Vegetation Experiment (WAVE) in September 2012. This study will focus on the HSRL aspect of the ACATS instrument, since the method and retrieval algorithms have direct application

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

    NASA Astrophysics Data System (ADS)

    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.

  6. Long-term tropical tropospheric ozone column retrievals using the Convective Clouds Differential (CCD) technique

    NASA Astrophysics Data System (ADS)

    Leventidou, Elpida; Ebojie, Felix; Eichmann, Kai-Uwe; Weber, Mark; Burrows, John P.

    2015-04-01

    Ozone influences most of the chemical reactions in the troposphere.Its tropospheric abundance can be retrieved using space-borne observations of vertically integrated ozone and cloud heights. The Convective Clouds Differential (CCD) technique (Ziemke et al., 1998 and Valks et al., 2014) takes advantage of the frequent occurrence of convective clouds in the western Pacific region by subtracting above-cloud ozone of this region from clear-sky ozone elsewhere to derive global monthly mean tropospheric amount. An important assumption is that the above-cloud ozone in the western Pacific simulates the stratospheric ozone and that the stratospheric ozone field is invariant with longitude; which is approximately true in the tropics. A CCD algorithm has been developed and is applied to optical remote sensing observations from three satellite instruments, so that a unique long-term record of monthly averaged tropical (20∘S, 20∘N) tropospheric vertically integrated ozone (1995-2012) is created. The validation of the CCD results with tropospheric ozone data from ozonesondes (Tompson et al., 2003) and Limb-Nadir matching observations (Ebojie et al. 2014) will be presented.

  7. Tomographic retrieval of cloud liquid water fields from a single scanning microwave radiometer aboard a moving platform – Part 1: Field trial results from the Wakasa Bay experiment

    SciTech Connect

    Huang, D.; Gasiewski, A.; Wiscombe, W.

    2010-07-22

    Tomographic methods offer great potential for retrieving three-dimensional spatial distributions of cloud liquid water from radiometric observations by passive microwave sensors. Fixed tomographic systems require multiple radiometers, while mobile systems can use just a single radiometer. Part 1 (this paper) examines the results from a limited cloud tomography trial with a single-radiometer airborne system carried out as part of the 2003 AMSR-E validation campaign over Wakasa Bay of the Sea of Japan. During this trial, the Polarimetric Scanning Radiometer (PSR) and Microwave Imaging Radiometer (MIR) aboard the NASA P-3 research aircraft provided a useful dataset for testing the cloud tomography method over a system of low-level clouds. We do tomographic retrievals with a constrained inversion algorithm using three configurations: PSR, MIR, and combined PSR and MIR data. The liquid water paths from the PSR retrieval are consistent with those from the MIR retrieval. The retrieved cloud field based on the combined data appears to be physically plausible and consistent with the cloud image obtained by a cloud radar. We find that some vertically-uniform clouds appear at high altitudes in the retrieved field where the radar shows clear sky. This is likely due to the sub-optimal data collection strategy. This sets the stage for Part 2 of this study that aims to define optimal data collection strategies using observation system simulation experiments.

  8. The Retrieval of Stratocumulus Cloud Properties by Ground-Based Cloud Radar.

    NASA Astrophysics Data System (ADS)

    Fox, Neil I.; Illingworth, Anthony J.

    1997-05-01

    The radiative characteristics of stratocumulus clouds are dependent upon their microphysical properties, primarily the liquid water content and effective radius of the drop population. Aircraft observations of droplet spectra in warm stratocumulus over the North Atlantic and around the British Isles by the Hercules C-130 aircraft of the U.K. Meteorological Office Meteorological Research Flight have been used to calculate the radar reflectivity, liquid water content, and effective radius. Empirically derived relationships, found from more than 4000 km of flight data on 11 separate days, that link reflectivity with either liquid water content or effective radius have been derived. These empirical relationships are significantly different from those predicted if the cloud droplet spectrum is modeled as a gamma function. Occasional drizzle-sized drops are frequently present within the cloud, and even though their concentration is very low, they dominate the reflectivity and these empirical relationships fail. However, although the drizzle drops increase the reflectivity, they have a negligible effect on the liquid water content and effective radius of the cloud. As these drops have a significant fall velocity in comparison to the cloud droplets, it is suggested that a ground-based Doppler radar could separate the components of the reflectivity due to bimodal drop spectra and the vertical structure of the cloud properties that determine radiative transfer could be retrieved.

  9. Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms; validation against collocated MODIS and CALIOP data

    NASA Astrophysics Data System (ADS)

    Taylor, T. E.; O'Dell, C. W.; Frankenberg, C.; Partain, P.; Cronk, H. Q.; Savtchenko, A.; Nelson, R. R.; Rosenthal, E. J.; Chang, A. Y.; Fisher, B.; Osterman, G.; Pollock, R. H.; Crisp, D.; Eldering, A.; Gunson, M. R.

    2015-12-01

    The objective of the National Aeronautics and Space Administration's (NASA) Orbiting Carbon Observatory-2 (OCO-2) mission is to retrieve the column-averaged carbon dioxide (CO2) dry air mole fraction (XCO2) from satellite measurements of reflected sunlight in the near-infrared. These estimates can be biased by clouds and aerosols within the instrument's field of view (FOV). Screening of the most contaminated soundings minimizes unnecessary calls to the computationally expensive Level 2 (L2) XCO2 retrieval algorithm. Hence, robust cloud screening methods have been an important focus of the OCO-2 algorithm development team. Two distinct, computationally inexpensive cloud screening algorithms have been developed for this application. The A-Band Preprocessor (ABP) retrieves the surface pressure using measurements in the 0.76 μm O2 A-band, neglecting scattering by clouds and aerosols, which introduce photon path-length (PPL) differences that can cause large deviations between the expected and retrieved surface pressure. The Iterative Maximum A-Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) retrieves independent estimates of the CO2 and H2O column abundances using observations taken at 1.61 μm (weak CO2 band) and 2.06 μm (strong CO2 band), while neglecting atmospheric scattering. The CO2 and H2O column abundances retrieved in these two spectral regions differ significantly in the presence of cloud and scattering aerosols. The combination of these two algorithms, which key off of different features in the spectra, provides the basis for cloud screening of the OCO-2 data set. To validate the OCO-2 cloud screening approach, collocated measurements from NASA's Moderate Resolution Imaging Spectrometer (MODIS), aboard the Aqua platform, were compared to results from the two OCO-2 cloud screening algorithms. With tuning to allow throughputs of ≃ 30 %, agreement between the OCO-2 and MODIS cloud screening methods is found to be

  10. Implementation of Future Climate Satellite Cloud Algorithms: Case of the GCOM-C/SGLI

    NASA Astrophysics Data System (ADS)

    Dim, J. R.; Murakami, H.; Nakajima, T. Y.; Takamura, T.

    2012-12-01

    The Global Change Observation Mission-Climate/Second Generation GLobal Imager (GCOM-C/SGLI) is a future Earth observation satellite to be launched in 2015. Its major objective is the monitoring of long-term climate changes. A major factor of these changes is the cloud impact. A new cloud algorithm adapted to the spectral characteristics of the GCOM-C/SGLI and the products derived are currently tested. The tests consist of evaluating the performance of the cloud optical thickness (COT) and the cloud particle effective radius (CLER) against simulation data, and equivalent products derived from a compatible satellite, the Terra/MODerate resolution Image Spectrometer (Terra/MODIS). In addition to these tests, the sensitivity of the products derived from this algorithm, to external and internal cloud related parameters, is analyzed. The base-map of the initial data input for this algorithm is made of geometrically corrected radiances of the Advanced Earth Observation Satellite II/GLobal Imager (ADEOS-II/GLI) and the GCOM-C/SGLI simulated radiances. The results of these performance tests, based on timely matching products, show that the GCOM-C/SGLI algorithm performs relatively well for averagely overcast scenes, with an agreement rate of ±20% with the satellite simulation products and the Terra/MODIS COT and CLER. A negative bias is however frequently observed, with the GCOM-C/SGLI retrieved parameters showing higher values at high COT levels. The algorithm also seems less reactive to thin and small particles' clouds mainly in land areas, compared to Terra/MODIS data and the satellite simulation products. Sensitivity to varying ground albedo, cloud phase, cloud structure and cloud location are analyzed to understand the influence of these parameters on the results obtained. Possible consequences of these influences on long-term climate variations and the bases for the improvement of the present algorithm in various cloud types' conditions are discussed.

  11. Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

    DOE PAGESBeta

    Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; Feingold, G.; Eloranta, E.; O'Connor, E. J.; Cadeddu, M. P.

    2015-02-16

    Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer cloud using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from large-eddy simulation snapshots of cumulusmore » under stratocumulus, where cloud water path is retrieved with an error of 31 g m−2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the northeast Pacific. Here, retrieved cloud water path agrees well with independent 3-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m−2.« less

  12. Nighttime cloud properties retrieval using MODIS and artificial neural networks

    NASA Astrophysics Data System (ADS)

    Pérez, J. C.; Cerdeña, A.; González, A.

    The aim of this work is to develop a methodology for inferring water cloud macro and microphysical properties from nighttime MODIS imagery This method is based on the inversion of a theoretical radiative transfer model that simulates the radiances detected in each of the sensor infrared bands In this case LibRadtran package Mayer and Kylling 2005 was used which allows us the calculation of the radiation field in the Earth s atmosphere given a specified set of atmospheric and cloud parameters However due to the complexity of this forward model its inversion cannot be performed in an analytical way To accomplish this task we propose an operational technique based on artificial neural networks ANNs whose main characteristic is the ability to retrieve cloud properties much faster than conventional methods Platnick et al 2003 Gonzalez et al 2002 Thus the procedure is as follows Using the theoretical radiative model a Look Up Table LUT is generated for a great variety of surface cloud and atmospheric conditions This dataset is divided randomly into a training set two-thirds of the items and a test set one third of the items which are used to train the neural network in order to fit the inversion problem In this study multilayer perceptrons MLPs with two hidden layers are used and the backpropagation with momentum method is used in the training process Furthermore to accelerate the convergence of ANN s evolutionary techniques are used to search the ANN configuration that provides the best fit Furthermore in order to check the

  13. A Study of Uncertainties for MODIS Cloud Retrievals of Optical Thickness and Effective Radius

    NASA Technical Reports Server (NTRS)

    Platnick, Steven; Pincus, Robert

    2002-01-01

    The investigation spanned four linked components as summarized in section III, each relating to some aspect of uncertainty assessment in the retrieval of cloud optical and microphysical properties using solar reflectance algorithms such as the MODIS operational cloud product (product IDS MOD06, MDY06 for Terra and Aqua, respectively). As discussed, three of these components have been fully completed (items (l), (2), and (3) while item (4) has been partially completed. These efforts have resulted in peer-reviewed publications and/or information delivered to the MODIS P.I. (M. D. King) for inclusion in the cloud product Quality Assessment (QA) output, a portion of the product output used, in part, for retrieval error assignments. This final report begins with a synopsis of the proposed investigation (section III) followed by a summary of work performed up through the last report including updates (section IV). Section V describes new activities. Publications from the efforts are listed in section VI. Figures (available in powerpoint format) are found in section VII.

  14. Application of active spaceborne remote sensing for understanding biases between passive cloud water path retrievals

    NASA Astrophysics Data System (ADS)

    Lebsock, Matthew; Su, Hui

    2014-07-01

    Bias between the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) version 2 and the Moderate Resolution Imaging Spectroradiometer (MODIS) collection 5.1 cloud liquid water path (Wc) products are explored with the aid of coincident active observations from the CloudSat radar and the CALIPSO lidar. In terms of detection, the active observations provide precise separation of cloudy from clear sky and precipitating from nonprecipitating clouds. In addition, they offer a unique quantification of precipitation water path (Wp) in warm clouds. They also provide an independent quantification of Wc that is based on an accurate surface reference technique, which is an independent arbiter between the two passive approaches. The results herein establish the potential for CloudSat and CALIPSO to provide an independent assessment of bias between the conventional passive remote sensing methods from reflected solar and emitted microwave radiation. After applying a common data filter to the observations to account for sampling biases, AMSR-E is biased high relative to MODIS in the global mean by 26.4 gm-2. The RMS difference in the regional patterns is 32.4 gm-2, which highlights a large geographical dependence in the bias which is related to the tropical transitions from stratocumulus to cumulus cloud regimes. The contributions of four potential sources for this bias are investigated by exploiting the active observations: (1) bias in MODIS related to solar zenith angle dependence accounts for -2.3 gm-2, (2) bias in MODIS due to undersampling of cloud edges accounts for 4.2 gm-2, (3) a wind speed and water vapor-dependent "clear-sky biase" in the AMSR-E retrieval accounts for 6.3 gm-2, and (4) evidence suggests that much of the remaining 18 gm-2 bias is related to the assumed partitioning of the observed emission signal between cloud and precipitation water in the AMSR-E retrieval. This is most evident through the correlations between the regional mean patterns of Wp and the Wc

  15. Towards a Multisensor Approach to Improve on Current TRMM Retrievals of Clouds and Precipitation

    NASA Technical Reports Server (NTRS)

    Stephens, Graeme L.; LEcuyer, Tristan S.; Austin, Richard T.

    2002-01-01

    The Tropical Rainfall Measuring Mission (TRMM) was designed to measure tropical rainfall and its variation from a low inclination orbiting satellite. The TRMM payload was carefully chosen to overcome a number of limitations of past satellite observing systems. This payload is predicated on the combination of active and passive observations from the TRMM Precipitation Radar (PR) and TRMM Microwave Imager (TMI) and Visible and Infrared Scanner (VIRS). Our research over the past three years has been devoted to the challenge of developing the most effective way of combining complementary information from these sensors to provide the most consistent estimate of precipitation. We have approached this problem from three directions. The first was to carry out preliminary analysis of passive microwave and infrared data from the TMI and VIRS instruments to understand the character of clear and cloudy skies in the basis defined by polarization and brightness temperature differences. Using this information as a foundation, the properties of two retrieval algorithms were analyzed, one for retrieving ice clouds from VIRS that was developed in parallel with this project and the other for rainfall from the TMI. Finally, the knowledge gleaned from each of these studies, coupled with ancillary data from NWP models and a broadband radiative transfer model, was used to create and algorithm for synthesizing the principal components of the Earth's energy budget from the basic building blocks of the atmosphere, gases, clouds, and precipitation. Principal results from each of these areas of research and their role in the TRMM and climate communities are summarized.

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

    NASA Technical Reports Server (NTRS)

    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.

  17. Statistical Retrieval of Thin Liquid Cloud Microphysical Properties Using Ground-Based Infrared and Microwave Observations

    NASA Astrophysics Data System (ADS)

    Marke, Tobias; Löhnert, Ulrich; Ebell, Kerstin; Turner, David D.

    2016-04-01

    In this study, liquid water cloud microphysical properties are retrieved by exploiting passive remote sensing techniques in the microwave and infrared spectral regime. Liquid water clouds are highly frequent in various climate regimes and play a significant role in terms of interaction with radiation. Small perturbations in the amount of liquid water contained in the cloud can cause large variations in the radiative fluxes. This effect enhances for thin clouds with a low liquid water path (LWP), which requires accurate retrieval information on the cloud properties. Retrieving low LWP values using the microwave spectral regime reveals large relative errors, whereas the potential for infrared methods is high. Therefore robust and computationally low demanding synergistic retrievals based on a multivariate regression and a neural network are derived to estimate LWP and cloud effective radius. While the regression-type synergy retrievals are strongly influenced by the nonlinearities of saturating signals in the infrared regime for higher LWP, the neural network retrieval is able to retrieve LWP and cloud effective radius with a higher accuracy than the single instrument retrievals. This is achieved by examining synthetic observations in the low LWP range. Furthermore, the performance of the retrievals is assessed in a radiative closure study for the downwelling shortwave flux, using measurements of a microwave radiometer, a broadband infrared radiometer and a spectrally highly resolved Atmospheric Emitted Radiance Interferometer (AERI).

  18. A TRMM-GPM cloud radiation database for satellite microwave precipitation retrieval

    NASA Astrophysics Data System (ADS)

    Tripoli, G. J.; Dietrich, S.; Kuo, K.-S.; Mugnai, A.; Panegrossi, G.; Smith, E. A.

    2003-04-01

    A Cloud Radiation Database (CRDB) is being developed to improve satellite microwave rain retrieval algorithms being with TRMM measurements and intended for future GPM applications. The CRDB consists of simulation results from a detailed cloud resolving model (CRM) combined with results from a detailed passive microwave radiative transfer model (PMRM) generated by using CRM model output as input to the PMRM. The simulations consist of a variety of precipitating weather system structures that space-borne microwave sensors encounter over the globe. These include both convective and stratiform systems, deep and shallow clouds, and warm and cold rain processes. The CRM used to create entries into the CRDB is tested for its ability to simulate microphysical processes as validated by in situ measurements available from special field programs and through comparison of simulated brightness temperatures to direct brightness temperature observations from space. This 3-way intercomparison procedure performed in cloud-radiation model verification studies is leading to the improvement of prognostic-based microphysical parameterization schemes that are used in all weather models featuring explicitly predicted microphysics. Plane-parallel, 3-dimensional reverse Monte Carlo, and 3-dimensional analytic RTE schemes are being used in the PMRM calculation of brightness temperatures. Development is also underway to test a new fully 3-dimensional analytic radiative transfer model vis-à-vis its capability in improving simulations of space-based brightness measurements. Techniques to retrieve optimal data base entries for particular observations are being explored. Possible metrics needed to make these choices include geographic location, cloud top height, stratiform or convective phase, season, and other possible stratifications. Another possible methodology under study is using global or large basin-scale or even global scale CRM simulations of a typical mix of seasonal weather systems

  19. A new multispectral cloud retrieval method for ship-based solar transmissivity measurements

    NASA Astrophysics Data System (ADS)

    Brückner, M.; Pospichal, B.; Macke, A.; Wendisch, M.

    2014-10-01

    Within the German Leibniz-network OCEANET project, ship-based lidar and microwave remote sensing as well as spectral zenith radiance observations with the COmpact RAdiation measurements System (CORAS) were performed. During three cruises latitudes between 50°N and 50°S were covered. A new spectral retrieval method to derive the cloud optical thickness τ and the droplet effective radius reff using CORAS measurements is developed. The method matches CORAS measurements of ratios of spectral transmissivity at six wavelengths with modeled transmissivities. This retrieval is fast and accurate and thus suitable for operational purposes. The new approach circumvents ambiguities of existing cloud retrievals and reduces the influence of measurement uncertainties. It is applied to homogenous and heterogeneous liquid water and cirrus clouds. In boundary layer liquid water clouds, the retrieved effective radius was more variable, whereas in the cirrus it was rather constant. Furthermore, the liquid water path LWP was derived and compared to data from a microwave radiometer. The new retrieval tends to overestimate LWP for thick liquid water clouds but slightly underestimate LWP for thin clouds. The presented method cannot be applied to mixed-phase clouds. The maximum retrieval of τ and reff for liquid water clouds is 80 in τ and 30 μm in reff, respectively; for cirrus clouds the limitations of the retrieval are 10 in τ and 60 μm in reff.

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

    SciTech Connect

    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.

  1. Estimate of the Impact of Absorbing Aerosol Over Cloud on the MODIS Retrievals of Cloud Optical Thickness and Effective Radius Using Two Independent Retrievals of Liquid Water Path

    NASA Technical Reports Server (NTRS)

    Wilcox, Eric M.; Harshvardhan; Platnick, Steven

    2009-01-01

    Two independent satellite retrievals of cloud liquid water path (LWP) from the NASA Aqua satellite are used to diagnose the impact of absorbing biomass burning aerosol overlaying boundary-layer marine water clouds on the Moderate Resolution Imaging Spectrometer (MODIS) retrievals of cloud optical thickness (tau) and cloud droplet effective radius (r(sub e)). In the MODIS retrieval over oceans, cloud reflectance in the 0.86-micrometer and 2.13-micrometer bands is used to simultaneously retrieve tau and r(sub e). A low bias in the MODIS tau retrieval may result from reductions in the 0.86-micrometer reflectance, which is only very weakly absorbed by clouds, owing to absorption by aerosols in cases where biomass burning aerosols occur above water clouds. MODIS LWP, derived from the product of the retrieved tau and r(sub e), is compared with LWP ocean retrievals from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E), determined from cloud microwave emission that is transparent to aerosols. For the coastal Atlantic southern African region investigated in this study, a systematic difference between AMSR-E and MODIS LWP retrievals is found for stratocumulus clouds over three biomass burning months in 2005 and 2006 that is consistent with above-cloud absorbing aerosols. Biomass burning aerosol is detected using the ultraviolet aerosol index from the Ozone Monitoring Instrument (OMI) on the Aura satellite. The LWP difference (AMSR-E minus MODIS) increases both with increasing tau and increasing OMI aerosol index. During the biomass burning season the mean LWP difference is 14 g per square meters, which is within the 15-20 g per square meter range of estimated uncertainties in instantaneous LWP retrievals. For samples with only low amounts of overlaying smoke (OMI AI less than or equal to 1) the difference is 9.4, suggesting that the impact of smoke aerosols on the mean MODIS LWP is 5.6 g per square meter. Only for scenes with OMI aerosol index greater than 2 does the

  2. Retrieval of Aerosol Optical Depth Under Thin Cirrus from MODIS: Application to an Ocean Algorithm

    NASA Technical Reports Server (NTRS)

    Lee, Jaehwa; Hsu, Nai-Yung Christina; Sayer, Andrew Mark; Bettenhausen, Corey

    2013-01-01

    A strategy for retrieving aerosol optical depth (AOD) under conditions of thin cirrus coverage from the Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. We adopt an empirical method that derives the cirrus contribution to measured reflectance in seven bands from the visible to shortwave infrared (0.47, 0.55, 0.65, 0.86, 1.24, 1.63, and 2.12 µm, commonly used for AOD retrievals) by using the correlations between the top-of-atmosphere (TOA) reflectance at 1.38 micron and these bands. The 1.38 micron band is used due to its strong absorption by water vapor and allows us to extract the contribution of cirrus clouds to TOA reflectance and create cirrus-corrected TOA reflectances in the seven bands of interest. These cirrus-corrected TOA reflectances are then used in the aerosol retrieval algorithm to determine cirrus-corrected AOD. The cirrus correction algorithm reduces the cirrus contamination in the AOD data as shown by a decrease in both magnitude and spatial variability of AOD over areas contaminated by thin cirrus. Comparisons of retrieved AOD against Aerosol Robotic Network observations at Nauru in the equatorial Pacific reveal that the cirrus correction procedure improves the data quality: the percentage of data within the expected error +/-(0.03 + 0.05 ×AOD) increases from 40% to 80% for cirrus-corrected points only and from 80% to 86% for all points (i.e., both corrected and uncorrected retrievals). Statistical comparisons with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) retrievals are also carried out. A high correlation (R = 0.89) between the CALIOP cirrus optical depth and AOD correction magnitude suggests potential applicability of the cirrus correction procedure to other MODIS-like sensors.

  3. Improving aerosol distributions below clouds by assimilating satellite-retrieved cloud droplet number

    PubMed Central

    Saide, Pablo E.; Carmichael, Gregory R.; Spak, Scott N.; Minnis, Patrick; Ayers, J. Kirk

    2012-01-01

    Limitations in current capabilities to constrain aerosols adversely impact atmospheric simulations. Typically, aerosol burdens within models are constrained employing satellite aerosol optical properties, which are not available under cloudy conditions. Here we set the first steps to overcome the long-standing limitation that aerosols cannot be constrained using satellite remote sensing under cloudy conditions. We introduce a unique data assimilation method that uses cloud droplet number (Nd) retrievals to improve predicted below-cloud aerosol mass and number concentrations. The assimilation, which uses an adjoint aerosol activation parameterization, improves agreement with independent Nd observations and with in situ aerosol measurements below shallow cumulus clouds. The impacts of a single assimilation on aerosol and cloud forecasts extend beyond 24 h. Unlike previous methods, this technique can directly improve predictions of near-surface fine mode aerosols responsible for human health impacts and low-cloud radiative forcing. Better constrained aerosol distributions will help improve health effects studies, atmospheric emissions estimates, and air-quality, weather, and climate predictions. PMID:22778436

  4. Crossover Improvement for the Genetic Algorithm in Information Retrieval.

    ERIC Educational Resources Information Center

    Vrajitoru, Dana

    1998-01-01

    In information retrieval (IR), the aim of genetic algorithms (GA) is to help a system to find, in a huge documents collection, a good reply to a query expressed by the user. Analysis of phenomena seen during the implementation of a GA for IR has led to a new crossover operation, which is introduced and compared to other learning methods.…

  5. Retrieval algorithms for special sensor microwave/imager (SSM/I)

    NASA Astrophysics Data System (ADS)

    Liu, Quanhua; Simmer, Clemens

    1998-08-01

    Regression method, look-up table technique, neural network, and physical inversion method are discussed in this study. Results from model calculations and measurements show that all retrieval algorithms achieve the similar accuracy for total precipitable water and sea surface wind. However, in contrast to the regression method physical inversion method, look-up table technique, and neural network yield a better accuracy for the cloud liquid water path. Instantaneous comparisons between ship-based radiosonding and the estimate from Special Sensor Microwave/Imager give rms errors of 2.9 Wm-2 and 2.7 ms-1 for the total column water vapor and sea surface wind, respectively. Due to the limit of data source comparison for cloud liquid water path is only performed for different data sets. Comparison for precipitation is only carried out with different algorithms.

  6. A variational approach for retrieving ice cloud properties from infrared measurements: application in the context of two IIR validation campaigns

    NASA Astrophysics Data System (ADS)

    Sourdeval, O.; C.-Labonnote, L.; Brogniez, G.; Jourdan, O.; Pelon, J.; Garnier, A.

    2013-02-01

    Cirrus are cloud types that are recognized to have a strong impact on the Earth-atmosphere radiation balance. This impact is however still poorly understood, due to the difficulties in describing the large variability of their properties in global climate models. Consequently, numerous airborne and space borne missions have been dedicated to their study in the last decades. The satellite constellation A-Train has proven to be particularly helpful to study cirrus on global scale due to such instruments as the Infrared Imaging Radiometer (IIR), which shows great sensitivity to the radiative and microphysical properties of these clouds. This study presents an algorithm that uses thermal infrared measurements to retrieve the optical thickness of cirrus and the effective size of their ice crystals. This algorithm is based on an optimal estimation scheme, which possesses the advantage of attributing precise uncertainties to the retrieved parameters. Two IIR airborne validation campaigns have been chosen as case studies. It is observed that optical thicknesses could be accurately retrieved but that large uncertainties may occur on the effective diameters. Strong agreements have been found between the products of our algorithm when separately applied to the measurements of IIR and of the airborne radiometer CLIMAT-AV, which comforts the results of previous validations of IIR level-1 measurements. Comparisons with in situ observations and with operational products of IIR also show confidence in our results. However, we have found that the quality of our retrievals can be strongly impacted by uncertainties related to the choice of a pristine crystal model and by poor constraints on the properties of possible liquid cloud layers underneath cirrus. Simultaneous retrievals of liquid clouds radiative and microphysical properties or the use of different ice crystal models should therefore be considered to improve the quality of the results.

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

    NASA Technical Reports Server (NTRS)

    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

  8. Combined Radar and Radiometer Analysis of Precipitation Profiles for a Parametric Retrieval Algorithm

    NASA Technical Reports Server (NTRS)

    Masunaga, Hirohiko; Kummerow, Christian D.

    2005-01-01

    A methodology to analyze precipitation profiles using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and precipitation radar (PR) is proposed. Rainfall profiles are retrieved from PR measurements, defined as the best-fit solution selected from precalculated profiles by cloud-resolving models (CRMs), under explicitly defined assumptions of drop size distribution (DSD) and ice hydrometeor models. The PR path-integrated attenuation (PIA), where available, is further used to adjust DSD in a manner that is similar to the PR operational algorithm. Combined with the TMI-retrieved nonraining geophysical parameters, the three-dimensional structure of the geophysical parameters is obtained across the satellite-observed domains. Microwave brightness temperatures are then computed for a comparison with TMI observations to examine if the radar-retrieved rainfall is consistent in the radiometric measurement space. The inconsistency in microwave brightness temperatures is reduced by iterating the retrieval procedure with updated assumptions of the DSD and ice-density models. The proposed methodology is expected to refine the a priori rain profile database and error models for use by parametric passive microwave algorithms, aimed at the Global Precipitation Measurement (GPM) mission, as well as a future TRMM algorithms.

  9. A synergisitic Neural Network Soil Moisture Retrieval Algorithm for SMAP

    NASA Astrophysics Data System (ADS)

    Kolassa, J.; Reichle, R. H.; Gentine, P.; Prigent, C.; Aires, F.; Fang, B.

    2015-12-01

    A Neural Network (NN)-based algorithm is developed to retrieve surface soil moisture from Soil Moisture Active/Passive (SMAP) microwave observations. This statistical approach serves as an alternative to the official Radiative Transfer (RT) based SMAP retrieval algorithm, since it avoids an explicit formulation of the RT processes as well as the use of often uncertain or unavailable a priori knowledge for additional surface parameters. The NN algorithm is calibrated on observations from the SMAP radiometer and radar as well as surface soil moisture fields from the MERRA-2 reanalysis. To highlight different physical aspects of the satellite signals and to maximize the soil moisture information, different preprocessing techniques of the SMAP data are investigated. These include an analysis of radiometer polarization and diurnal indices to isolate the surface temperature contribution, as well as the radar co- and cross-polarized channels to account for vegetation effects. A major difference with respect to the official retrieval is the increased importance given to the information provided by the SMAP radar or other active sensors, utilizing not only the relative spatial structures, but also the absolute soil moisture information provided. The NN methodology combines multiple sensor observations in a data fusion approach and is thus able to fully exploit the complementarity of the information provided by the different instruments. The algorithm is used to compute global estimates of surface soil moisture and evaluated against retrieved soil moisture from SMOS as well as in situ observations from the International Soil Moisture Network (ISMN). The calibration on MERRA-2 data means that the NN retrieval algorithm functions as the model operator in a data assimilation framework yielding soil moisture estimates that are very compatible with the model. This could facilitate the assimilation of SMAP observations into land surface and numerical weather prediction models.

  10. Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

    DOE PAGESBeta

    Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; Feingold, G.; Eloranta, E.; O'Connor, E. J.; Cadeddu, M. P.

    2015-07-02

    Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer clouds using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances under conditions when precipitation does not reach the surface. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievalsmore » using synthetic measurements from large-eddy simulation snapshots of cumulus under stratocumulus, where cloud water path is retrieved with an error of 31 g m-2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the Northeast Pacific. Here, retrieved cloud water path agrees well with independent three-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m-2.« less

  11. Development and Evaluation of a Simple Algorithm to Find Cloud Optical Depth with Emphasis on Thin Ice Clouds

    SciTech Connect

    Barnard, James C.; Long, Charles N.; Kassianov, Evgueni I.; McFarlane, Sally A.; Comstock, Jennifer M.; Freer, Matthew; McFarquhar, Greg

    2008-04-14

    We present here an algorithm for determining cloud optical depth, τ, using data from shortwave broadband irradiances, focusing on the case of optically thin clouds. This method is empirical and consists of applying a one-line equation to the shortwave flux analysis described by Long and Ackerman (2000). We apply this method to cirrus clouds observed at the Atmospheric Radiation Measurement Program’s (ARM) Darwin, Australia site during the Tropical Warm Pool International Cloud Experiment (TWP-ICE) campaign and cirrus clouds observed at ARM’s Southern Great Plains (SGP) site. These cases were chosen because independent verification of cloud optical depth retrievals is possible. For the TWP-ICE case, the calculated optical depths compare favorably (to within about 1 unit) with a “first principles” τ calculated from a vertical profile of ice particle size distributions obtained from an aircraft sounding. For the SGP case, the results from the algorithm correspond reasonably well with τ values obtained from an average over other methods; some of which have been subject to independent verification. The medians of the two time series are 0.79 and 0.81, for the empirical and averaged values, respectively (although such close agreement is likely to be fortuitous). This tool may be applied wherever measurements of the three components of the shortwave broadband flux are available at 1- to 5-minute resolution. Because these measurements are made across the world, it then becomes possible to estimate optical depth at many locations.

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

    NASA Technical Reports Server (NTRS)

    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.

  13. A better understanding of POLDER's cloud droplet size retrieval: impact of cloud horizontal inhomogeneity and directional sampling

    NASA Astrophysics Data System (ADS)

    Shang, H.; Chen, L.; Bréon, F.-M.; Letu, H.; Li, S.; Wang, Z.; Su, L.

    2015-07-01

    The principles of the Polarization and Directionality of the Earth's Reflectance (POLDER) cloud droplet size retrieval requires that clouds are horizontally homogeneous. Nevertheless, the retrieval is applied by combining all measurements from an area of 150 km × 150 km to compensate for POLDER's insufficient directional sampling. Using the POLDER-like data simulated with the RT3 model, we investigate the impact of cloud horizontal inhomogeneity and directional sampling on the retrieval, and then analyze which spatial resolution is potentially accessible from the measurements. Case studies show that the sub-scale variability in droplet effective radius (CDR) can mislead both the CDR and effective variance (EV) retrievals. Nevertheless, the sub-scale variations in EV and cloud optical thickness (COT) only influence the EV retrievals and not the CDR estimate. In the directional sampling cases studied, the retrieval is accurate using limited observations and is largely independent of random noise. Several improvements have been made to the original POLDER droplet size retrieval. For example, the measurements in the primary rainbow region (137-145°) are used to ensure accurate large droplet (> 15 μm) retrievals and reduce the uncertainties caused by cloud heterogeneity. We apply the improved method using the POLDER global L1B data for June 2008, the new CDR results are compared with the operational CDRs. The comparison show that the operational CDRs tend to be underestimated for large droplets. The reason is that the cloudbow oscillations in the scattering angle region of 145-165° are weak for cloud fields with CDR > 15 μm. Lastly, a sub-scale retrieval case is analyzed, illustrating that a higher resolution, e.g., 42 km × 42 km, can be used when inverting cloud droplet size parameters from POLDER measurements.

  14. Impact of cloud horizontal inhomogeneity and directional sampling on the retrieval of cloud droplet size by the POLDER instrument

    NASA Astrophysics Data System (ADS)

    Shang, H.; Chen, L.; Bréon, F. M.; Letu, H.; Li, S.; Wang, Z.; Su, L.

    2015-11-01

    The principles of cloud droplet size retrieval via Polarization and Directionality of the Earth's Reflectance (POLDER) requires that clouds be horizontally homogeneous. The retrieval is performed by combining all measurements from an area of 150 km × 150 km to compensate for POLDER's insufficient directional sampling. Using POLDER-like data simulated with the RT3 model, we investigate the impact of cloud horizontal inhomogeneity and directional sampling on the retrieval and analyze which spatial resolution is potentially accessible from the measurements. Case studies show that the sub-grid-scale variability in droplet effective radius (CDR) can significantly reduce valid retrievals and introduce small biases to the CDR (~ 1.5 μm) and effective variance (EV) estimates. Nevertheless, the sub-grid-scale variations in EV and cloud optical thickness (COT) only influence the EV retrievals and not the CDR estimate. In the directional sampling cases studied, the retrieval using limited observations is accurate and is largely free of random noise. Several improvements have been made to the original POLDER droplet size retrieval. For example, measurements in the primary rainbow region (137-145°) are used to ensure retrievals of large droplet (> 15 μm) and to reduce the uncertainties caused by cloud heterogeneity. We apply the improved method using the POLDER global L1B data from June 2008, and the new CDR results are compared with the operational CDRs. The comparison shows that the operational CDRs tend to be underestimated for large droplets because the cloudbow oscillations in the scattering angle region of 145-165° are weak for cloud fields with CDR > 15 μm. Finally, a sub-grid-scale retrieval case demonstrates that a higher resolution, e.g., 42 km × 42 km, can be used when inverting cloud droplet size distribution parameters from POLDER measurements.

  15. Synergetic use of microwave radiometer and multifilter rotating shadowband radiometer observations for the validation of satellite cloud retrievals

    NASA Astrophysics Data System (ADS)

    Deneke, H. M.; Meirink, J. M.; Greuell, W.; Wolters, E.; Roebeling, R.; Simmer, C.

    2009-12-01

    Bi-spectral algorithms to estimate cloud properties from reflected solar radiation at an absorbing and a non-absorbing wavelength are routinely applied to observations of meteorological satellite imagers. The underlying inversion process is highly underconstrained, and is based on the simplified view of 1D radiative transfer theory. It is therefore difficult to quantify the overall accuracy of these retrievals, and validation with independent datasets is crucial. The combination of measurements from a multifilter rotating shadowband radiometer and a passive microwave radiometer allows us to obtain a simultaneous and independent estimate of cloud optical thickness, liquid water path and effective droplet size from surface observations. In this study, a comparison of the surface-derived time series of these cloud properties for two European sites is carried out with collocated and synchronised retrievals from the geostationary METEOSAT SEVIRI satellite imager. This is done in order to test the suitability of this approach for routine quality monitoring of the cloud property products generated by the Satellite Application Facility on Climate Monitoring (CM-SAF). A discussion of the uncertainties affecting the surface and satellite algorithm is given. Particular attention is paid to the spatial and temporal matching of measurements. Also, the effects of cloud variability and the different resolution scales of the instruments are studied. This allows us to assess the level of agreement of the individual time series under specific conditions. It is shown that validation statistics are highly sensitive to quality screening and case selection, as well as the spatial and temporal averaging scales used for the comparison. This finding highlights the necessity to quantify the effects of sensor resolution and variability on cloud datasets, and to develop standard procedures to be able to compare validation results for different retrieval algorithms and satellite platforms.

  16. Examination of phase retrieval algorithms for patterned EUV mask metrology

    NASA Astrophysics Data System (ADS)

    Claus, Rene A.; Wang, Yow-Gwo; Wojdyla, Antoine; Benk, Markus P.; Goldberg, Kenneth A.; Neureuther, Andrew R.; Naulleau, Patrick P.

    2015-10-01

    We evaluate the performance of several phase retrieval algorithms using through-focus aerial image measurements of patterned EUV photomasks. Patterns present a challenge for phase retrieval algorithms due to the high- contrast and strong diffraction they produce. For this study, we look at the ability to correctly recover phase for line-space patterns on an EUV mask with a TaN absorber and for an etched EUV multilayer phase shift mask. The recovered phase and amplitude extracted from measurements taken using the SHARP EUV microscope at Lawrence Berkeley National Laboratory is compared to rigorous, 3D electromagnetic simulations. The impact of uncertainty in background intensity, coherence, and focus on the recovered field is evaluated to see if the algorithms respond differently.

  17. Total ozone column derived from GOME and SCIAMACHY using KNMI retrieval algorithms: Validation against Brewer measurements at the Iberian Peninsula

    NASA Astrophysics Data System (ADS)

    Antón, M.; Kroon, M.; López, M.; Vilaplana, J. M.; Bañón, M.; van der A, R.; Veefkind, J. P.; Stammes, P.; Alados-Arboledas, L.

    2011-11-01

    This article focuses on the validation of the total ozone column (TOC) data set acquired by the Global Ozone Monitoring Experiment (GOME) and the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) satellite remote sensing instruments using the Total Ozone Retrieval Scheme for the GOME Instrument Based on the Ozone Monitoring Instrument (TOGOMI) and Total Ozone Retrieval Scheme for the SCIAMACHY Instrument Based on the Ozone Monitoring Instrument (TOSOMI) retrieval algorithms developed by the Royal Netherlands Meteorological Institute. In this analysis, spatially colocated, daily averaged ground-based observations performed by five well-calibrated Brewer spectrophotometers at the Iberian Peninsula are used. The period of study runs from January 2004 to December 2009. The agreement between satellite and ground-based TOC data is excellent (R2 higher than 0.94). Nevertheless, the TOC data derived from both satellite instruments underestimate the ground-based data. On average, this underestimation is 1.1% for GOME and 1.3% for SCIAMACHY. The SCIAMACHY-Brewer TOC differences show a significant solar zenith angle (SZA) dependence which causes a systematic seasonal dependence. By contrast, GOME-Brewer TOC differences show no significant SZA dependence and hence no seasonality although processed with exactly the same algorithm. The satellite-Brewer TOC differences for the two satellite instruments show a clear and similar dependence on the viewing zenith angle under cloudy conditions. In addition, both the GOME-Brewer and SCIAMACHY-Brewer TOC differences reveal a very similar behavior with respect to the satellite cloud properties, being cloud fraction and cloud top pressure, which originate from the same cloud algorithm (Fast Retrieval Scheme for Clouds from the Oxygen A-Band (FRESCO+)) in both the TOSOMI and TOGOMI retrieval algorithms.

  18. A 1DVAR retrieval applied to GMI: Algorithm description, validation, and sensitivities

    NASA Astrophysics Data System (ADS)

    Duncan, David I.; Kummerow, Christian D.

    2016-06-01

    A fully physical, 1-D variational inversion algorithm (1DVAR) has been developed to simultaneously retrieve total precipitable water (TPW), 10 m wind speed, and cloud liquid water path (CLWP) over ocean. Results presented are for the Global Precipitation Measurement Microwave Imager (GMI), but the algorithm is adaptable to any microwave imager. The Colorado State University 1DVAR is novel in that the observation error covariances are not assumed to be zero and empirical orthogonal functions are utilized to retrieve the structure of the water vapor profile, aided by GMI's high-frequency channels. Validation against radiosonde and ocean buoy observations demonstrates a near zero bias for wind speed and a small positive bias for water vapor, respectively, with RMS errors that rival those of benchmark products. RMS errors against validation are 2.6 mm and 1.2 m/s for TPW and wind speed. No calibration adjustments were made to achieve these results, and no "truth" data were used to train the algorithm. The advantages of this fully physical inversion are its adaptability, transparency, and full description of retrieval errors. Sensitivities of the algorithm are explored in detail.

  19. Retrieval of Polar Stratospheric Cloud Microphysical Properties from Lidar Measurements: Dependence on Particle Shape Assumptions

    NASA Technical Reports Server (NTRS)

    Reichardt, J.; Reichardt, S.; Yang, P.; McGee, T. J.; Bhartia, P. K. (Technical Monitor)

    2001-01-01

    A retrieval algorithm has been developed for the microphysical analysis of polar stratospheric cloud (PSC) optical data obtained using lidar instrumentation. The parameterization scheme of the PSC microphysical properties allows for coexistence of up to three different particle types with size-dependent shapes. The finite difference time domain (FDTD) method has been used to calculate optical properties of particles with maximum dimensions equal to or less than 2 mu m and with shapes that can be considered more representative of PSCs on the scale of individual crystals than the commonly assumed spheroids. Specifically. these are irregular and hexagonal crystals. Selection of the optical parameters that are input to the inversion algorithm is based on a potential data set such as that gathered by two of the lidars on board the NASA DC-8 during the Stratospheric Aerosol and Gas Experiment 0 p (SAGE) Ozone Loss Validation experiment (SOLVE) campaign in winter 1999/2000: the Airborne Raman Ozone and Temperature Lidar (AROTEL) and the NASA Langley Differential Absorption Lidar (DIAL). The 0 microphysical retrieval algorithm has been applied to study how particle shape assumptions affect the inversion of lidar data measured in leewave PSCs. The model simulations show that under the assumption of spheroidal particle shapes, PSC surface and volume density are systematically smaller than the FDTD-based values by, respectively, approximately 10-30% and approximately 5-23%.

  20. Retrieval of Cloud Phase Using the Moderate Resolution Imaging Spectroradiometer Data during the Mixed-Phase Arctic Cloud Experiment

    SciTech Connect

    Spangenberg, D.; Minnis, P.; Shupe, M.; Uttal, T.; Poellot, M.

    2005-03-18

    Improving climate model predictions over Earth's polar regions requires a comprehensive knowledge of polar cloud microphysics. Over the Arctic, there is minimal contrast between the clouds and background snow surface, making it difficult to detect clouds and retrieve their phase from space. Snow and ice cover, temperature inversions, and the predominance of mixed-phase clouds make it even more difficult to determine cloud phase. Also, since determining cloud phase is the first step toward analyzing cloud optical depth, particle size, and water content, it is vital that the phase be correct in order to obtain accurate microphysical and bulk properties. Changes in these cloud properties will, in turn, affect the Arctic climate since clouds are expected to play a critical role in the sea ice albedo feedback. In this paper, the IR trispectral technique (IRTST) is used as a starting point for a WV and 11-{micro}m brightness temperature (T11) parameterization (WVT11P) of cloud phase using MODIS data. In addition to its ability to detect mixed-phase clouds, the WVT11P also has the capability to identify thin cirrus clouds overlying mixed or liquid phase clouds (multiphase ice). Results from the Atmospheric Radiation Measurement (ARM) MODIS phase model (AMPHM) are compared to the surface-based cloud phase retrievals over the ARM North Slope of Alaska (NSA) Barrow site and to in-situ data taken from University of North Dakota Citation (CIT) aircraft which flew during the Mixed-Phase Arctic Cloud Experiment (MPACE). It will be shown that the IRTST and WVT11P combined to form the AMPHM can achieve a relative high accuracy of phase discrimination compared to the surface-based retrievals. Since it only uses MODIS WV and IR channels, the AMPHM is robust in the sense that it can be applied to daytime, twilight, and nighttime scenes with no discontinuities in the output phase.

  1. CAD Model Retrieval Based on Graduated Assignment Algorithm

    NASA Astrophysics Data System (ADS)

    Tao, Songqiao

    2015-06-01

    A retrieval approach for CAD models based on graduated assignment algorithm is proposed in this paper. First, CAD models are transformed into face adjacency graphs (FAGs). Second, the vertex compatibility matrix and edge compatibility matrix between the FAGs of the query and data models are calculated, and the similarity metric for the two comparison models is established from their compatibility matrices, which serves as the optimization objective function for selecting vertex mapping matrix M between the two comparison models. Finally, Sinkhorn's alternative normalization approach for M's rows and columns is adopted to find the optimal vertex mapping matrix M. Experimental results have shown that the proposed approach supports CAD model retrieval.

  2. Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application

    NASA Technical Reports Server (NTRS)

    Key, Jeff; Maslanik, James; Steffen, Konrad

    1994-01-01

    One essential parameter used in the estimation of radiative and turbulent heat fluxes from satellite data is surface temperature. Sea and land surface temperature (SST and LST) retrieval algorithms that utilize the thermal infrared portion of the spectrum have been developed, with the degree of success dependent primarily upon the variability of the surface and atmospheric characteristics. However, little effort has been directed to the retrieval of the sea ice surface temperature (IST) in the Arctic and Antarctic pack ice or the ice sheet surface temperature over Antarctica and Greenland. The reason is not one of methodology, but rather our limited knowledge of atmospheric temperature, humidity, and aerosol vertical, spatial and temporal distributions, the microphysical properties of polar clouds, and the spectral characteristics of snow, ice, and water surfaces. Over the open ocean the surface is warm, dark, and relatively homogeneous. This makes SST retrieval, including cloud clearing, a fairly straightforward task. Over the ice, however, the surface within a single satellite pixel is likely to be highly heterogeneous, a mixture of ice of various thicknesses, open water, and snow cover in the case of sea ice. Additionally, the Arctic is cloudy - very cloudy - with typical cloud cover amounts ranging from 60-90 percent. There are few observations of cloud cover amounts over Antarctica. The goal of this research is to increase our knowledge of surface temperature patterns and magnitudes in both polar regions, by examining existing data and improving our ability to use satellite data as a monitoring tool. Four instruments are of interest in this study: the AVHRR, ATSR, SMMR, and SSM/I. Our objectives are as follows. Refine the existing AVHRR retrieval algorithm defined in Key and Haefliger (1992; hereafter KH92) and applied elsewhere. Develop a method for IST retrieval from ATSR data similar to the one used for SST. Further investigate the possibility of estimating

  3. The Operational MODIS Cloud Optical and Microphysical Property Product: Overview of the Collection 6 Algorithm and Preliminary Results

    NASA Technical Reports Server (NTRS)

    Platnick, Steven; King, Michael D.; Wind, Galina; Amarasinghe, Nandana; Marchant, Benjamin; Arnold, G. Thomas

    2012-01-01

    Operational Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of cloud optical and microphysical properties (part of the archived products MOD06 and MYD06, for MODIS Terra and Aqua, respectively) are currently being reprocessed along with other MODIS Atmosphere Team products. The latest "Collection 6" processing stream, which is expected to begin production by summer 2012, includes updates to the previous cloud retrieval algorithm along with new capabilities. The 1 km retrievals, based on well-known solar reflectance techniques, include cloud optical thickness, effective particle radius, and water path, as well as thermodynamic phase derived from a combination of solar and infrared tests. Being both global and of high spatial resolution requires an algorithm that is computationally efficient and can perform over all surface types. Collection 6 additions and enhancements include: (i) absolute effective particle radius retrievals derived separately from the 1.6 and 3.7 !-lm bands (instead of differences relative to the standard 2.1 !-lm retrieval), (ii) comprehensive look-up tables for cloud reflectance and emissivity (no asymptotic theory) with a wind-speed interpolated Cox-Munk BRDF for ocean surfaces, (iii) retrievals for both liquid water and ice phases for each pixel, and a subsequent determination of the phase based, in part, on effective radius retrieval outcomes for the two phases, (iv) new ice cloud radiative models using roughened particles with a specified habit, (v) updated spatially-complete global spectral surface albedo maps derived from MODIS Collection 5, (vi) enhanced pixel-level uncertainty calculations incorporating additional radiative error sources including the MODIS L1 B uncertainty index for assessing band and scene-dependent radiometric uncertainties, (v) and use of a new 1 km cloud top pressure/temperature algorithm (also part of MOD06) for atmospheric corrections and low cloud non-unity emissivity temperature adjustments.

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

    NASA Astrophysics Data System (ADS)

    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

  5. Improved retrievals of the optical properties of cirrus clouds by a combination of lidar methods.

    PubMed

    Cadet, Bertrand; Giraud, Vincent; Haeffelin, Martial; Keckhut, Philippe; Rechou, Anne; Baldy, Serge

    2005-03-20

    We focus on improvement of the retrieval of optical properties of cirrus clouds by combining two lidar methods. We retrieve the cloud's optical depth by using independently the molecular backscattering profile below and above the cloud [molecular integration (MI) method] and the backscattering profile inside the cloud with an a priori effective lidar ratio [particle integration (PI) method]. When the MI method is reliable, the combined MI-PI method allows us to retrieve the optimal effective lidar ratio. We compare these results with Raman lidar retrievals. We then use the derived optimal effective lidar ratio for retrieval with the PI method for situations in which the MI method cannot be applied. PMID:15818860

  6. Retrieval of subvisual cirrus cloud optical thickness from limb-scatter measurements

    NASA Astrophysics Data System (ADS)

    Wiensz, J. T.; Degenstein, D. A.; Lloyd, N. D.; Bourassa, A. E.

    2013-01-01

    We present a technique for estimating the optical thickness of subvisual cirrus clouds detected by OSIRIS (Optical Spectrograph and Infrared Imaging System), a limb-viewing satellite instrument that measures scattered radiances from the UV to the near-IR. The measurement set is composed of a ratio of limb radiance profiles at two wavelengths that indicates the presence of cloud-scattering regions. Cross-sections and phase functions from an in situ database are used to simulate scattering by cloud-particles. With appropriate configurations discussed in this paper, the SASKTRAN successive-orders of scatter radiative transfer model is able to simulate accurately the in-cloud radiances from OSIRIS. Configured in this way, the model is used with a multiplicative algebraic reconstruction technique (MART) to retrieve the cloud extinction profile for an assumed effective cloud particle size. The sensitivity of these retrievals to key auxiliary model parameters is shown, and it is shown that the retrieved extinction profile, for an assumed effective cloud particle size, models well the measured in-cloud radiances from OSIRIS. The greatest sensitivity of the retrieved optical thickness is to the effective cloud particle size. Since OSIRIS has an 11-yr record of subvisual cirrus cloud detections, the work described in this manuscript provides a very useful method for providing a long-term global record of the properties of these clouds.

  7. Physically-Retrieving Cloud and Thermodynamic Parameters from Ultraspectral IR Measurements

    NASA Technical Reports Server (NTRS)

    Zhou, Daniel K.; Smith, William L., Sr.; Liu, Xu; Larar, Allen M.; Mango, Stephen A.; Huang, Hung-Lung

    2007-01-01

    A physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error < 1 km). NPOESS Airborne Sounder Testbed Interferometer (NAST-I) retrievals from the Atlantic-THORPEX Regional Campaign are compared with coincident observations obtained from dropsondes and the nadir-pointing Cloud Physics Lidar (CPL). This work was motivated by the need to obtain solutions for atmospheric soundings from infrared radiances observed for every individual field of view, regardless of cloud cover, from future ultraspectral geostationary satellite sounding instruments, such as the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and the Hyperspectral Environmental Suite (HES). However, this retrieval approach can also be applied to the ultraspectral sounding instruments to fly on Polar satellites, such as the Infrared Atmospheric Sounding Interferometer (IASI) on the European MetOp satellite, the Cross-track Infrared Sounder (CrIS) on the NPOESS Preparatory Project and the following NPOESS series of satellites.

  8. Retrieving co-occurring cloud and precipitation properties of warm marine boundary layer clouds with A-Train data

    NASA Astrophysics Data System (ADS)

    Mace, Gerald G.; Avey, Stephanie; Cooper, Steven; Lebsock, Matthew; Tanelli, Simone; Dobrowalski, Greg

    2016-04-01

    In marine boundary layer (MBL) clouds the formation of precipitation from the cloud droplet distribution in the presence of variable aerosol plays a fundamental role in determining the coupling of these clouds to their environment and ultimately to the climate system. Here the degree to which A-Train satellite measurements can diagnose simultaneously occurring cloud and precipitation properties in MBL clouds is examined. Beginning with the measurements provided by CloudSat and Moderate Resolution Imaging Spectroradiometer (including a newly available microwave brightness temperature from CloudSat), and a climatology of MBL cloud properties from past field campaigns, an assumption is made that any hydrometeor volume could contain both cloud droplet and precipitation droplet modes. Bayesian optimal estimation is then used to derive atmospheric states by inverting a measurement vector carefully accounting for uncertainties due to instrument noise, forward model error, and assumptions. It is found that in many cases where significant precipitation coexists with cloud, due to forward model error driven by uncertainties in assumptions, the uncertainty in retrieved cloud properties is greater than the variance in the prior climatology. It is often necessary to average several thousand (hundred) precipitating (weakly precipitating) profiles to obtain meaningful information regarding the properties important to microphysical processes. Regardless, if such process level information is deemed necessary for better constraining predictive models of the climate system, measurement systems specifically designed to accomplish such retrievals must be considered for the future.

  9. Synergistic multi-sensor and multi-frequency retrieval of cloud ice water path constrained by CloudSat collocations

    NASA Astrophysics Data System (ADS)

    Islam, Tanvir; Srivastava, Prashant K.

    2015-08-01

    The cloud ice water path (IWP) is one of the major parameters that have a strong influence on earth's radiation budget. Onboard satellite sensors are recognized as valuable tools to measure the IWP in a global scale. Albeit, active sensors such as the Cloud Profiling Radar (CPR) onboard the CloudSat satellite has better capability to measure the ice water content profile, thus, its vertical integral, IWP, than any passive microwave (MW) or infrared (IR) sensors. In this study, we investigate the retrieval of IWP from MW and IR sensors, including AMSU-A, MHS, and HIRS instruments on-board the N19 satellite, such that the retrieval is consistent with the CloudSat IWP estimates. This is achieved through the collocations between the passive satellite measurements and CloudSat scenes. Potential benefit of synergistic multi-sensor multi-frequency retrieval is investigated. Two modeling approaches are explored for the IWP retrieval - generalized linear model (GLM) and neural network (NN). The investigation has been carried out over both ocean and land surface types. The MW/IR synergy is found to be retrieved more accurate IWP than the individual AMSU-A, MHS, or HIRS measurements. Both GLM and NN approaches have been able to exploit the synergistic retrievals.

  10. The OMPS Limb Profiler Instrument: Two-Dimensional Retrieval Algorithm

    NASA Technical Reports Server (NTRS)

    Rault, Didier F.

    2010-01-01

    The upcoming Ozone Mapper and Profiler Suite (OMPS), which will be launched on the NPOESS Preparatory Project (NPP) platform in early 2011, will continue monitoring the global distribution of the Earth's middle atmosphere ozone and aerosol. OMPS is composed of three instruments, namely the Total Column Mapper (heritage: TOMS, OMI), the Nadir Profiler (heritage: SBUV) and the Limb Profiler (heritage: SOLSE/LORE, OSIRIS, SCIAMACHY, SAGE III). The ultimate goal of the mission is to better understand and quantify the rate of stratospheric ozone recovery. The focus of the paper will be on the Limb Profiler (LP) instrument. The LP instrument will measure the Earth's limb radiance (which is due to the scattering of solar photons by air molecules, aerosol and Earth surface) in the ultra-violet (UV), visible and near infrared, from 285 to 1000 nm. The LP simultaneously images the whole vertical extent of the Earth's limb through three vertical slits, each covering a vertical tangent height range of 100 km and each horizontally spaced by 250 km in the cross-track direction. Measurements are made every 19 seconds along the orbit track, which corresponds to a distance of about 150km. Several data analysis tools are presently being constructed and tested to retrieve ozone and aerosol vertical distribution from limb radiance measurements. The primary NASA algorithm is based on earlier algorithms developed for the SOLSE/LORE and SAGE III limb scatter missions. All the existing retrieval algorithms rely on a spherical symmetry assumption for the atmosphere structure. While this assumption is reasonable in most of the stratosphere, it is no longer valid in regions of prime scientific interest, such as polar vortex and UTLS regions. The paper will describe a two-dimensional retrieval algorithm whereby the ozone distribution is simultaneously retrieved vertically and horizontally for a whole orbit. The retrieval code relies on (1) a forward 2D Radiative Transfer code (to model limb

  11. Development of microwave rainfall retrieval algorithm for climate applications

    NASA Astrophysics Data System (ADS)

    KIM, J. H.; Shin, D. B.

    2014-12-01

    With the accumulated satellite datasets for decades, it is possible that satellite-based data could contribute to sustained climate applications. Level-3 products from microwave sensors for climate applications can be obtained from several algorithms. For examples, the Microwave Emission brightness Temperature Histogram (METH) algorithm produces level-3 rainfalls directly, whereas the Goddard profiling (GPROF) algorithm first generates instantaneous rainfalls and then temporal and spatial averaging process leads to level-3 products. The rainfall algorithm developed in this study follows a similar approach to averaging instantaneous rainfalls. However, the algorithm is designed to produce instantaneous rainfalls at an optimal resolution showing reduced non-linearity in brightness temperature (TB)-rain rate(R) relations. It is found that the resolution tends to effectively utilize emission channels whose footprints are relatively larger than those of scattering channels. This algorithm is mainly composed of a-priori databases (DBs) and a Bayesian inversion module. The DB contains massive pairs of simulated microwave TBs and rain rates, obtained by WRF (version 3.4) and RTTOV (version 11.1) simulations. To improve the accuracy and efficiency of retrieval process, data mining technique is additionally considered. The entire DB is classified into eight types based on Köppen climate classification criteria using reanalysis data. Among these sub-DBs, only one sub-DB which presents the most similar physical characteristics is selected by considering the thermodynamics of input data. When the Bayesian inversion is applied to the selected DB, instantaneous rain rate with 6 hours interval is retrieved. The retrieved monthly mean rainfalls are statistically compared with CMAP and GPCP, respectively.

  12. Cloud Height Retrieval with Oxygen A and B Bands for the Deep Space Climate Observatory (DSCOVR) Mission

    NASA Technical Reports Server (NTRS)

    Yang, Yuekui; Marshak, Alexander; Mao, Jianping; Lyapustin, Alexei; Herman, Jay

    2012-01-01

    Planned to fly in 2014, the Deep Space Climate Observatory (DSCOVR) would see the whole sunlit half of the Earth from the L 1 Lagrangian point and would provide simultaneous data on cloud and aerosol properties with its Earth Polychromatic Imaging Camera (EPIC). EPIC images the Earth on a 2Kx2K CCD array, which gives a horizontal resolution of about 10 km at nadir. A filter-wheel provides consecutive images in 10 spectral channels ranging from the UV to the near-IR, including the oxygen A and B bands. This paper presents a study of retrieving cloud height with EPIC's oxygen A and B bands. As the first step, we analyzed the effect of cloud optical and geometrical properties, sun-view geometry, and surface type on the cloud height determination. Second, we developed two cloud height retrieval algorithms that are based on the Mixed Lambertian-Equivalent Reflectivity (MLER) concept: one utilizes the absolute radiances at the Oxygen A and B bands and the other uses the radiance ratios between the absorption and reference channels of the two bands. Third, we applied the algorithms to the simulated EPIC data and to the data from SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY (SCIAMACHY) observations. Results show that oxygen A and B bands complement each other: A band is better suited for retrievals over ocean, while B band is better over vegetated land due to a much darker surface. Improvements to the MLER model, including corrections to surface contribution and photon path inside clouds, will also be discussed.

  13. An automatic cloud mask algorithm based on time series of MODIS measurements

    NASA Astrophysics Data System (ADS)

    Lyapustin, A.; Wang, Y.; Frey, R.

    2008-08-01

    Quality of aerosol retrievals and atmospheric correction over land depends strongly on accuracy of the cloud mask (CM) algorithm. The heritage CM algorithms developed for AVHRR and MODIS use the latest sensor measurements of spectral reflectance and brightness temperature and perform processing at the pixel level. The algorithms are threshold-based and empirically tuned. They do not explicitly address the classical problem of cloud search, wherein the baseline clear-skies scene is defined for comparison. Here we report on a new land CM algorithm, which explicitly builds and maintains a reference clear-skies image of the surface (refcm) using a time series of MODIS measurements. The new algorithm, developed as part of the multiangle implementation of atmospheric correction (MAIAC) algorithm for MODIS, relies on the fact that clear-skies images of the same surface area have a common textural pattern, defined by the surface topography, boundaries of rivers and lakes, distribution of soils and vegetation, etc. This pattern changes slowly given the daily rate of global Earth observations, whereas clouds introduce high-frequency random disturbances. Under clear skies, consecutive gridded images of the same surface area have a high covariance, whereas in presence of clouds covariance is usually low. This idea is central to initialization of refcm, which is used to derive cloud mask in combination with spectral and brightness temperature tests. The refcm is continuously updated with the latest clear-skies MODIS measurements, thus adapting to seasonal and rapid surface changes. The algorithm is enhanced by an internal dynamic land-water-snow classification coupled with a surface change mask. An initial comparison shows that the new algorithm offers the potential to perform better than the MODIS MOD35 cloud mask in situations where the land surface is changing rapidly and over Earth regions covered by snow and ice.

  14. Validation of OMI Total Ozone Retrievals from the SAO Ozone Profile Algorithm and Three Operational Algorithms 3 with Brewer Measurements

    NASA Astrophysics Data System (ADS)

    Bak, Juseon; Kim, Jae H.; Liu, Xiong; Chance, Kelly

    2015-04-01

    The optimal estimation (OE) based ozone profile algorithm developed at Smithsonian 3 Astrophysical Observatory (SAO) is assessed as to its accuracy to extract total ozone amount from 4 Ozone Monitoring Instrument (OMI) measurements through the validation using Brewer ground 5 based measurements between January 2005 and December 2008. We compare it against the quality of 6 three OMI operational ozone products, derived from NASA TOMS, KNMI DOAS, and KNMI OE 7 algorithms, respectively. The validation demonstrates that the SAO ozone profile algorithm generally 8 has the best total ozone retrieval performance compared to the three OMI operational ozone products. 9 The individual station comparisons show an agreement between SAO and Brewer within ± 1% except 10 at polar stations (~ -2 %), with a high correlation coefficient of ~ 0.99 at most stations. The KNMI OE 11 algorithm systematically overestimates the true total ozone value at all stations with a bias from 2 % 12 at low/mid latitude stations to 5 % at high latitude stations. On the other hand, TOMS/DOAS 13 algorithm underestimates total ozone by ~ -1.7 % on average. The standard deviations of differences 14 are ~ 1.8 % for SAO and TOMS while DOAS and KNMI show the standard deviation values of 2.2 15 and 2.5 %, respectively. The remarkable stability of SAO OE algorithm is found with no significant 16 dependency on algorithmic variables such as viewing geometries, cloud parameters, and time. In 17 comparison, the severe dependency on both solar and viewing zenith angles is found in KNMI OE 18 algorithm, which is characterized with a negative (positive) correlation with smaller (larger) solar 19 zenith angles and the strong cross-track dependent biases ranging from 4% at nadir and 1% at off-20 nadir positions. The dependence of DOAS and TOMS algorithms on the algorithmic variables is 21 marginal compared to KNMI OE algorithm, but distinct compared to SAO OE algorithm. Relative 22 differences between SAO/DOAS and

  15. Retrieval of Aerosol Optical Depth in Vicinity of Broken Clouds from Reflectance Ratios: Case Study

    SciTech Connect

    Kassianov, Evgueni I.; Ovchinnikov, Mikhail; Berg, Larry K.; McFarlane, Sally A.; Flynn, Connor J.; Ferrare, Richard; Hostetler, Chris A.; Alexandrov, Mikhail

    2010-10-06

    A recently developed reflectance ratio (RR) method for the retrieval of aerosol optical depth (AOD) is evaluated using extensive airborne and ground-based data sets collected during the Cloud and Land Surface Interaction Campaign (CLASIC) and the Cumulus Humilis Aerosol Processing Study (CHAPS), which took place in June 2007 over the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains site. A detailed case study is performed for a field of single-layer shallow cumuli observed on June 12, 2007. The RR method is applied to retrieve the spectral values of AOD from the reflectance ratios measured by the MODIS Airborne Simulator (MAS) for two pairs of wavelengths (660 and 470 nm and 870 and 470 nm) collected at a spatial resolution of 0.05 km. The retrieval is compared with an independent AOD estimate from three ground-based Multi-filter Rotating Shadowband Radiometers (MFRSRs). The interpolation algorithm that is used to project MFRSR point measurements onto the aircraft flight tracks is tested using AOD derived from NASA Langley High Spectral Resolution Lidar (HSRL). The RR AOD estimates are in a good agreement (within 5%) with the MFRSR-derived AOD values for the 660-nm wavelength. The AODs obtained from MAS reflectance ratios overestimate those derived from MFRSR measurements by 15-30% for the 470-nm wavelength and underestimate the 870-nm AOD by the same amount.

  16. Retrieval, Inter-Comparison, and Validation of Above-Cloud Aerosol Optical Depth from A-train Sensors

    NASA Technical Reports Server (NTRS)

    Jethva, Hiren; Torres, Omar; Bhartia, Pawan K.; Remer, Lorraine; Redemann, Jens; Dunagan, Stephen E.; Livingston, John; Shinozuka, Yohei; Kacenelenbogen, Meloe; Segal-Rosenbeimer, Michal; Spurr, Rob

    2014-01-01

    Absorbing aerosols produced from biomass burning and dust outbreaks are often found to overlay lower level cloud decks and pose greater potentials of exerting positive radiative effects (warming) whose magnitude directly depends on the aerosol loading above cloud, optical properties of clouds and aerosols, and cloud fraction. Recent development of a 'color ratio' (CR) algorithm applied to observations made by the Aura/OMI and Aqua/MODIS constitutes a major breakthrough and has provided unprecedented maps of above-cloud aerosol optical depth (ACAOD). The CR technique employs reflectance measurements at TOA in two channels (354 and 388 nm for OMI; 470 and 860 nm for MODIS) to retrieve ACAOD in near-UV and visible regions and aerosol-corrected cloud optical depth, simultaneously. An inter-satellite comparison of ACAOD retrieved from NASA's A-train sensors reveals a good level of agreement between the passive sensors over the homogeneous cloud fields. Direct measurements of ACA such as carried out by the NASA Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) can be of immense help in validating ACA retrievals. We validate the ACA optical depth retrieved using the CR method applied to the MODIS cloudy-sky reflectance against the airborne AATS and 4STAR measurements. A thorough search of the historic AATS-4STAR database collected during different field campaigns revealed five events where biomass burning, dust, and wildfire-emitted aerosols were found to overlay lower level cloud decks observed during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS- 2013, respectively. The co-located satellite-airborne measurements revealed a good agreement (RMSE less than 0.1 for AOD at 500 nm) with most matchups falling within the estimated uncertainties in the MODIS retrievals. An extensive validation of satellite-based ACA retrievals requires equivalent field measurements particularly over the regions where ACA are often

  17. Phase-retrieval algorithms for a complicated optical system

    NASA Technical Reports Server (NTRS)

    Fienup, J. R.

    1993-01-01

    Phase-retrieval algorithms have been developed that handle a complicated optical system that requires multiple Fresnellike transforms to propagate from one end of the system to the other including the absorption by apertures in more than one plane and allowance for bad detector pixels. Gradient-search algorithms and generalizations of the iterative-transform phase-retrieval algorithms are derived. Analytic expressions for the gradient of an error metric, with respect to polynomial coefficients and with respect to point-by-point phase descriptions, are given. The entire gradient can be computed with the number of transforms required to propagate a wave front from one end of the optical system to the other and back again, independent of the number of coefficients or phase points. This greatly speeds the computation. The reconstruction of pupil amplitude is also given. A convergence proof of the generalized iterative transform algorithm is given. These improved algorithms permit a more accurate characterization of complicated optical systems from their point spread functions.

  18. A Prototype Algorithm for Land Surface Temperature Retrieval from Sentinel-3 Mission

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Technical Reports Server (NTRS)

    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.

  20. Statistical characteristics of cloud variability. Part 1: Retrieved cloud liquid water path at three ARM sites

    NASA Astrophysics Data System (ADS)

    Huang, Dong; Campos, Edwin; Liu, Yangang

    2014-09-01

    Statistical characteristics of cloud variability are examined for their dependence on averaging scales and best representation of probability density function with the decade-long retrieval products of cloud liquid water path (LWP) from the tropical western Pacific (TWP), Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites of the Department of Energy's Atmospheric Radiation Measurement Program. The statistical moments of LWP show some seasonal variation at the SGP and NSA sites but not much at the TWP site. It is found that the standard deviation, relative dispersion (the ratio of the standard deviation to the mean), and skewness all quickly increase with the averaging window size when the window size is small and become more or less flat when the window size exceeds 12 h. On average, the cloud LWP at the TWP site has the largest values of standard deviation, relative dispersion, and skewness, whereas the NSA site exhibits the least. Correlation analysis shows that there is a positive correlation between the mean LWP and the standard deviation. The skewness is found to be closely related to the relative dispersion with a correlation coefficient of 0.6. The comparison further shows that the lognormal, Weibull, and gamma distributions reasonably explain the observed relationship between skewness and relative dispersion over a wide range of scales.

  1. 3D Monte Carlo simulation of solar radiance in the clear-sky and low-cloud atmosphere for retrieval of aerosol and cloud characteristics

    NASA Astrophysics Data System (ADS)

    Zhuravleva, Tatiana; Bedareva, Tatiana; Nasrtdinov, Ilmir

    As is well known, the spectral measurements of direct and diffuse solar radiation can be used to retrieve the optical and microphysical characteristics of atmospheric aerosol and clouds. Most methods of radiation calculations, which are used to solve the inverse problems, are implemented under the assumption of horizontal homogeneity of the atmosphere (clear-sky and overcast conditions). However, it is recognized that the 3D effects of clouds have a significant impact on the transfer of solar radiation in the atmosphere which can be the cause of errors in retrieval of aerosol and cloud properties. In this work, we present the algorithms of the Monte Carlo method for calculating the angular structure of diffuse radiation in the molecular-aerosol atmosphere and the appearance of isolated cloud. The simulation of radiative characteristics with specified spectral resolution is performed in spherical model of the atmosphere for the conditions of observations at the Earth’s surface and at the top of the atmosphere. Cloud is approximated by inverted paraboloid. The molecular absorption is accounted for on the basis of approximation of transmission function by short exponential series (k-distribution method). The specific features of the radiative transfer, caused by the 3D effects of clouds, are considered depending on cloud location in space and its sizes, sensing scheme, and illumination conditions. The simulation results of the brightness fields in the clear sky and in the appearance of isolated cloud are compared. This work was supported in part by the Russian Fund for Basic Research (through the grant no. 12-05-00169).

  2. Optical property retrievals of subvisual cirrus clouds from OSIRIS limb-scatter measurements

    NASA Astrophysics Data System (ADS)

    Wiensz, J. T.; Degenstein, D. A.; Lloyd, N. D.; Bourassa, A. E.

    2012-08-01

    We present a technique for retrieving the optical properties of subvisual cirrus clouds detected by OSIRIS, a limb-viewing satellite instrument that measures scattered radiances from the UV to the near-IR. The measurement set is composed of a ratio of limb radiance profiles at two wavelengths that indicates the presence of cloud-scattering regions. Optical properties from an in-situ database are used to simulate scattering by cloud-particles. With appropriate configurations discussed in this paper, the SASKTRAN successive-orders of scatter radiative transfer model is able to simulate accurately the in-cloud radiances from OSIRIS. Configured in this way, the model is used with a multiplicative algebraic reconstruction technique (MART) to retrieve the cloud extinction profile for an assumed effective cloud particle size. The sensitivity of these retrievals to key auxiliary model parameters is shown, and it is demonstrated that the retrieved extinction profile models accurately the measured in-cloud radiances from OSIRIS. Since OSIRIS has an 11-yr record of subvisual cirrus cloud detections, the work described in this manuscript provides a very useful method for providing a long-term global record of the properties of these clouds.

  3. Developments of global greenhouse gas retrieval algorithm based on Optimal Estimation Method

    NASA Astrophysics Data System (ADS)

    Kim, W. V.; Kim, J.; Lee, H.; Jung, Y.; Boesch, H.

    2013-12-01

    After the industrial revolution, atmospheric carbon dioxide concentration increased drastically over the last 250 years. It is still increasing and over than 400ppm of carbon dioxide was measured at Mauna Loa observatory for the first time which value was considered as important milestone. Therefore, understanding the source, emission, transport and sink of global carbon dioxide is unprecedentedly important. Currently, Total Carbon Column Observing Network (TCCON) is operated to observe CO2 concentration by ground base instruments. However, the number of site is very few and concentrated to Europe and North America. Remote sensing of CO2 could supplement those limitations. Greenhouse Gases Observing SATellite (GOSAT) which was launched 2009 is measuring column density of CO2 and other satellites are planned to launch in a few years. GOSAT provide valuable measurement data but its low spatial resolution and poor success rate of retrieval due to aerosol and cloud, forced the results to cover less than half of the whole globe. To improve data availability, accurate aerosol information is necessary, especially for East Asia region where the aerosol concentration is higher than other region. For the first step, we are developing CO2 retrieval algorithm based on optimal estimation method with VLIDORT the vector discrete ordinate radiative transfer model. Proto type algorithm, developed from various combinations of state vectors to find best combination of state vectors, shows appropriate result and good agreement with TCCON measurements. To reduce calculation cost low-stream interpolation is applied for model simulation and the simulation time is drastically reduced. For the further study, GOSAT CO2 retrieval algorithm will be combined with accurate GOSAT-CAI aerosol retrieval algorithm to obtain more accurate result especially for East Asia.

  4. Aerosol Retrieval and Atmospheric Correction Algorithms for EPIC

    NASA Astrophysics Data System (ADS)

    Wang, Y.; Lyapustin, A.; Marshak, A.; Korkin, S.; Herman, J. R.

    2011-12-01

    EPIC is a multi-spectral imager onboard planned Deep Space Climate ObserVatoRy (DSCOVR) designed for observations of the full illuminated disk of the Earth with high temporal and coarse spatial resolution (10 km) from Lagrangian L1 point. During the course of the day, EPIC will view the same Earth surface area in the full range of solar and view zenith angles at equator with fixed scattering angle near the backscattering direction. This talk will describe a new aerosol retrieval/atmospheric correction algorithm developed for EPIC and tested with EPIC Simulator data. This algorithm uses the time series approach and consists of two stages: the first stage is designed to periodically re-initialize the surface spectral bidirectional reflectance (BRF) on stable low AOD days. Such days can be selected based on the same measured reflectance between the morning and afternoon reciprocal view geometries of EPIC. On the second stage, the algorithm will monitor the diurnal cycle of aerosol optical depth and fine mode fraction based on the known spectral surface BRF. Testing of the developed algorithm with simulated EPIC data over continental USA showed a good accuracy of AOD retrievals (10-20%) except over very bright surfaces.

  5. Aerosol Retrieval and Atmospheric Correction Algorithms for EPIC

    NASA Technical Reports Server (NTRS)

    Wang, Yujie; Lyapustin, Alexei; Marshak, Alexander; Korkin, Sergey; Herman, Jay

    2011-01-01

    EPIC is a multi-spectral imager onboard planned Deep Space Climate ObserVatoRy (DSCOVR) designed for observations of the full illuminated disk of the Earth with high temporal and coarse spatial resolution (10 km) from Lagrangian L1 point. During the course of the day, EPIC will view the same Earth surface area in the full range of solar and view zenith angles at equator with fixed scattering angle near the backscattering direction. This talk will describe a new aerosol retrieval/atmospheric correction algorithm developed for EPIC and tested with EPIC Simulator data. This algorithm uses the time series approach and consists of two stages: the first stage is designed to periodically re-initialize the surface spectral bidirectional reflectance (BRF) on stable low AOD days. Such days can be selected based on the same measured reflectance between the morning and afternoon reciprocal view geometries of EPIC. On the second stage, the algorithm will monitor the diurnal cycle of aerosol optical depth and fine mode fraction based on the known spectral surface BRF. Testing of the developed algorithm with simulated EPIC data over continental USA showed a good accuracy of AOD retrievals (10-20%) except over very bright surfaces.

  6. Extending "Deep Blue" Aerosol Retrieval Coverage to Cases of Absorbing Aerosols Above Clouds: Sensitivity Analysis and First Case Studies

    NASA Technical Reports Server (NTRS)

    Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Schmid, B.; Shinozuka, Y.

    2016-01-01

    Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty approximately 25-50 percent (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty approximately10-20 percent, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

  7. Extending "Deep Blue" aerosol retrieval coverage to cases of absorbing aerosols above clouds: Sensitivity analysis and first case studies

    NASA Astrophysics Data System (ADS)

    Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Schmid, B.; Shinozuka, Y.

    2016-05-01

    Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty ˜25-50% (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty ˜10-20%, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

  8. Empirical analysis of aerosol and thin cloud optical depth effects on CO2 retrievals from GOSAT

    NASA Astrophysics Data System (ADS)

    Saha, A.; O'Neill, N. T.; Strong, K.; Nakajima, T.; Uchino, O.; Shiobara, M.

    2014-12-01

    Ground-based sunphotometer observations of aerosol and cloud optical properties at AEROCAN / AERONET sites co-located with TCCON (Total Carbon Column Observing Network) high resolution Fourier Transform Spectrometers (FTS) were used to investigate the aerosol and cloud influence on column-averaged dry-air mole fraction of carbon dioxide (XCO2) retrieved from the TANSO-FTS (Thermal And Near-infrared Sensor for carbon Observation - FTS) of GOSAT (Greenhouse gases Observing SATellite). This instrument employs high resolution spectra measured in the Short-Wavelength InfraRed (SWIR) band to retrieve XCO2estimates. GOSAT XCO2 retrievals are nominally corrected for the contaminating backscatter influence of aerosols and thin clouds. However if the satellite-retrieved aerosol and thin cloud optical depths applied to the CO2 correction is biased then the correction and the retrieved CO2 values will be biased. We employed independent ground based estimates of both cloud screened and non cloud screened AOD (aerosol optical depth) in the CO2 SWIR channel and compared this with the GOSAT SWIR-channel OD retrievals to see if that bias was related to variations in the (generally negative) CO2 bias (ΔXCO2= XCO2(GOSAT) - XCO2(TCCON)). Results are presented for a number of TCCON validation sites.

  9. Evaluating MODIS cloud retrievals with in situ observations from VOCALS-REx

    NASA Astrophysics Data System (ADS)

    King, N. J.; Bower, K. N.; Crosier, J.; Crawford, I.

    2013-01-01

    Microphysical measurements collected during eleven profiles, by the UK BAe-146 aircraft, through marine stratocumulus as part of the Variability of the American Monsoon Systems (VAMOS) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) are compared to collocated overpasses of the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua and Terra satellite platforms. The full depth of the cloud is sampled in each case using a Cloud Droplet Probe (CDP) and a Two-Dimensional Stereo Probe (2DS) together sizing cloud and precipitation droplets in the diameter range 2-1260 μm. This allows the total optical depth (τc) of the cloud and effective radius (re) of the droplet size distribution to be compared to MODIS cloud retrievals of the same quantities along with the secondarily derived total liquid water path. When compared to the effective radius at cloud top, the MODIS retrieved re using the 2.1 μm wavelength channel overestimates the in situ measurements on average by 13% with the largest overestimations coinciding with the detection by the 2DS of drizzle sized droplets. We show through consideration of the full vertical profile and penetration depths of the wavelengths used in the retrieval that the expected retrieved values are less than those at cloud top thus increasing the apparent bias in re retrievals particularly when using the 1.6 and 2.1 μm channels, with the 3.7 μm channel retrievals displaying the best agreement with in situ values. Retrievals of τc also tend to overestimate in situ values which, coupled with a high bias in re retrievals, lead to an overestimation of liquid water path. There is little apparent correlation between the variation of the three near-infrared re retrievals and the vertical structure of the cloud observed in situ. Retrievals are performed using measured profiles of water vapour and temperature along with an accurate knowledge of the width of the droplet size distribution which improve agreement

  10. Evaluating MODIS cloud retrievals with in situ observations from VOCALS-REx

    NASA Astrophysics Data System (ADS)

    King, N. J.; Bower, K. N.; Crosier, J.; Crawford, I.

    2012-09-01

    Microphysical measurements collected during eleven profiles through marine stratocumulus as part of the Variability of the American Monsoon Systems (VAMOS) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) are compared to collocated overpasses of the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua and Terra satellite platforms. The full depth of the cloud is sampled in each case using a Cloud Droplet Probe (CDP) and a Two-Dimensional Stereo Probe (2DS) together sizing cloud and precipitation droplets in the diameter range 2-1260 μm. This allows the total optical depth (τc) of the cloud and effective radius (re) of the droplet size distribution to be compared to MODIS cloud retrievals of the same quantities along with the secondarily derived total liquid water path. When compared to the effective radius at cloud top, the MODIS retrieved re using the 2.1 μm wavelength channel overestimates the in situ measurements on average by 13% with the largest overestimations coinciding with the detection by the 2DS of drizzle sized droplets. We show through consideration of the full vertical profile and penetration depths of the wavelengths used in the retrieval that the expected retrieved values are less than those at cloud top thus increasing the apparent bias in re retrievals particularly when using the 1.6 and 2.1 μm channels, with the 3.7 μm channel retrievals displaying the best agreement with in situ values. Retrievals of τc also tend to overestimate in situ values which, coupled with a high bias in re retrievals, lead to an overestimation of liquid water path. There is little apparent correlation between the variation of the three near-infrared re retrievals and the vertical structure of the cloud observed in situ. Retrievals are performed using measured profiles of water vapour and temperature along with an accurate knowledge of the width of the droplet size distribution which improve agreement between in situ and retrieved

  11. SSM/I Rain Retrievals Within a Unified All-Weather Ocean Algorithm

    NASA Technical Reports Server (NTRS)

    Wentz, Frank J.; Spencer, Roy W.

    1996-01-01

    A new method for the physical retrieval of rain rates from satellite microwave radiometers is presented and compared to two other rainfall climatologies derived from satellites. The method is part of a unified ocean parameter retrieval algorithm that is based on the fundamental principles of radiative transfer. The algorithm simultaneously finds near-surface wind speed W, columnar water vapor V, columnar cloud liquid water L, rain rate R, and effective radiating temperature T(sub U) for the upwelling radiation. The performance of the algorithm in the absence of rain is discussed in Wentz, and this paper focuses on the rain component of the algorithm. A particular strength of the unified algorithm is its ability to 'orthogonalize' the retrievals so that there is minimum cross-talk between the retrieved parameters. For example, comparisons of the retrieved water vapor with radiosonde observations show that there is very little correlation between the water vapor retrieval error and rain rate. For rain rates from 1 to 15 mm/h, the rms difference between the retrieved water vapor and the radiosonde value is 5 mm. A novel feature of the rain retrieval method is a beamfilling correction that is based upon the ratio of the retrieved liquid water absorption coefficients at 37 GHz and 19.35 GHz. This ratio decreases by about 40% when heavy and light rain co-exist within the SSM/I footprint as compared to the case of uniform rain. This correction has the effect of increasing the rain rate when the spectral ratio of the absorption coefficients is small. Even with this beamfilling correction, tropical rainfall is still unrealistically low when the freezing level in the tropics (approx. 5 km) is used to specify the rain layer thickness. We restore realism by reducing the assumed averaged tropical rain layer thickness to 3 km, thereby accounting for the existence of warm rain processes in which the rain layer does not extend to the freezing level. Global rain rates are produced

  12. Statistics Analysis of the Uncertainties in Cloud Optical Depth Retrievals Caused by Three-Dimensional Radiative Effects

    NASA Technical Reports Server (NTRS)

    Varnai, Tamas; Marshak, Alexander

    2000-01-01

    This paper presents a simple approach to estimate the uncertainties that arise in satellite retrievals of cloud optical depth when the retrievals use one-dimensional radiative transfer theory for heterogeneous clouds that have variations in all three dimensions. For the first time, preliminary error bounds are set to estimate the uncertainty of cloud optical depth retrievals. These estimates can help us better understand the nature of uncertainties that three-dimensional effects can introduce into retrievals of this important product of the MODIS instrument. The probability distribution of resulting retrieval errors is examined through theoretical simulations of shortwave cloud reflection for a wide variety of cloud fields. The results are used to illustrate how retrieval uncertainties change with observable and known parameters, such as solar elevation or cloud brightness. Furthermore, the results indicate that a tendency observed in an earlier study, clouds appearing thicker for oblique sun, is indeed caused by three-dimensional radiative effects.

  13. Improved Surface and Tropospheric Temperatures Determined Using Only Shortwave Channels: The AIRS Science Team Version-6 Retrieval Algorithm

    NASA Technical Reports Server (NTRS)

    Susskind, Joel; Blaisdell, John; Iredell, Lena

    2011-01-01

    The Goddard DISC has generated products derived from AIRS/AMSU-A observations, starting from September 2002 when the AIRS instrument became stable, using the AIRS Science Team Version-5 retrieval algorithm. The AIRS Science Team Version-6 retrieval algorithm will be finalized in September 2011. This paper describes some of the significant improvements contained in the Version-6 retrieval algorithm, compared to that used in Version-5, with an emphasis on the improvement of atmospheric temperature profiles, ocean and land surface skin temperatures, and ocean and land surface spectral emissivities. AIRS contains 2378 spectral channels covering portions of the spectral region 650 cm(sup -1) (15.38 micrometers) - 2665 cm(sup -1) (3.752 micrometers). These spectral regions contain significant absorption features from two CO2 absorption bands, the 15 micrometers (longwave) CO2 band, and the 4.3 micrometers (shortwave) CO2 absorption band. There are also two atmospheric window regions, the 12 micrometer - 8 micrometer (longwave) window, and the 4.17 micrometer - 3.75 micrometer (shortwave) window. Historically, determination of surface and atmospheric temperatures from satellite observations was performed using primarily observations in the longwave window and CO2 absorption regions. According to cloud clearing theory, more accurate soundings of both surface skin and atmospheric temperatures can be obtained under partial cloud cover conditions if one uses observations in longwave channels to determine coefficients which generate cloud cleared radiances R(sup ^)(sub i) for all channels, and uses R(sup ^)(sub i) only from shortwave channels in the determination of surface and atmospheric temperatures. This procedure is now being used in the AIRS Version-6 Retrieval Algorithm. Results are presented for both daytime and nighttime conditions showing improved Version-6 surface and atmospheric soundings under partial cloud cover.

  14. The Invigoration of Deep Convective Clouds Over the Atlantic: Aerosol Effect, Meteorology or Retrieval Artifact?

    NASA Technical Reports Server (NTRS)

    Koren, Ilan; Feingold, Graham; Remer, Lorraine A.

    2010-01-01

    Associations between cloud properties and aerosol loading are frequently observed in products derived from satellite measurements. These observed trends between clouds and aerosol optical depth suggest aerosol modification of cloud dynamics, yet there are uncertainties involved in satellite retrievals that have the potential to lead to incorrect conclusions. Two of the most challenging problems are addressed here: the potential for retrieved aerosol optical depth to be cloud-contaminated, and as a result, artificially correlated with cloud parameters; and the potential for correlations between aerosol and cloud parameters to be erroneously considered to be causal. Here these issues are tackled directly by studying the effects of the aerosol on convective clouds in the tropical Atlantic Ocean using satellite remote sensing, a chemical transport model, and a reanalysis of meteorological fields. Results show that there is a robust positive correlation between cloud fraction or cloud top height and the aerosol optical depth, regardless of whether a stringent filtering of aerosol measurements in the vicinity of clouds is applied, or not. These same positive correlations emerge when replacing the observed aerosol field with that derived from a chemical transport model. Model-reanalysis data is used to address the causality question by providing meteorological context for the satellite observations. A correlation exercise between the full suite of meteorological fields derived from model reanalysis and satellite-derived cloud fields shows that observed cloud top height and cloud fraction correlate best with model pressure updraft velocity and relative humidity. Observed aerosol optical depth does correlate with meteorological parameters but usually different parameters from those that correlate with observed cloud fields. The result is a near-orthogonal influence of aerosol and meteorological fields on cloud top height and cloud fraction. The results strengthen the case

  15. An Assessment of Differences Between Cloud Effective Particle Radius Retrievals for Marine Water Clouds from Three MODIS Spectral Bands

    NASA Technical Reports Server (NTRS)

    Platnick, Steven; Zhang, Zhibo

    2011-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product provides three separate 1 km resolution retrievals of cloud particle effective radii (r (sub e)), derived from 1.6, 2.1 and 3.7 micron band observations. In this study, differences among the three size retrievals for maritime water clouds (designated as r (sub e), 1.6 r (sub e), 2.1 and r (sub e),3.7) were systematically investigated through a series of case studies and global analyses. Substantial differences are found between r (sub e),3.7 and r (sub e),2.1 retrievals (delta r (sub e),3.7-2.l), with a strong dependence on cloud regime. The differences are typically small, within +/- 2 micron, over relatively spatially homogeneous coastal stratocumulus cloud regions. However, for trade wind cumulus regimes, r (sub e),3.7 was found to be substantially smaller than r (sub e),2.1, sometimes by more than 10 micron. The correlation of delta r(sub e),3.7-2.1 with key cloud parameters, including the cloud optical thickness (tau), r (sub e) and a cloud horizontal heterogeneity index (H-sigma) derived from 250 m resolution MODIS 0.86 micron band observations, were investigated using one month of MODIS Terra data. It was found that differences among the three r (sub e) retrievals for optically thin clouds (tau <5) are highly variable, ranging from - 15 micron to 10 micron, likely due to the large MODIS retrieval uncertainties when the cloud is thin. The delta r (sub e),3.7-2.1 exhibited a threshold-like dependence on both r (sub e),2.l and H-sigma. The re,3.7 is found to agree reasonably well with re,2.! when re,2.l is smaller than about 15J-Lm, but becomes increasingly smaller than re,2.1 once re,2.! exceeds this size. All three re retrievals showed little dependence when H-sigma < 0.3 (defined as standard deviation divided by the mean for the 250 m pixels within a 1 km pixel retrieval). However, for H-=sigma >0.3, both r (sub e),1.6 and r (sub e),2.1 were seen to increase quickly with H-sigma. On the

  16. Evaluation of Satellite-Based Upper Troposphere Cloud Top Height Retrievals in Multilayer Cloud Conditions During TC4

    NASA Technical Reports Server (NTRS)

    Chang, Fu-Lung; Minnis, Patrick; Ayers, J. Kirk; McGill, Matthew J.; Palikonda, Rabindra; Spangenberg, Douglas A.; Smith, William L., Jr.; Yost, Christopher R.

    2010-01-01

    Upper troposphere cloud top heights (CTHs), restricted to cloud top pressures (CTPs) less than 500 hPa, inferred using four satellite retrieval methods applied to Twelfth Geostationary Operational Environmental Satellite (GOES-12) data are evaluated using measurements during the July August 2007 Tropical Composition, Cloud and Climate Coupling Experiment (TC4). The four methods are the single-layer CO2-absorption technique (SCO2AT), a modified CO2-absorption technique (MCO2AT) developed for improving both single-layered and multilayered cloud retrievals, a standard version of the Visible Infrared Solar-infrared Split-window Technique (old VISST), and a new version of VISST (new VISST) recently developed to improve cloud property retrievals. They are evaluated by comparing with ER-2 aircraft-based Cloud Physics Lidar (CPL) data taken during 9 days having extensive upper troposphere cirrus, anvil, and convective clouds. Compared to the 89% coverage by upper tropospheric clouds detected by the CPL, the SCO2AT, MCO2AT, old VISST, and new VISST retrieved CTPs less than 500 hPa in 76, 76, 69, and 74% of the matched pixels, respectively. Most of the differences are due to subvisible and optically thin cirrus clouds occurring near the tropopause that were detected only by the CPL. The mean upper tropospheric CTHs for the 9 days are 14.2 (+/- 2.1) km from the CPL and 10.7 (+/- 2.1), 12.1 (+/- 1.6), 9.7 (+/- 2.9), and 11.4 (+/- 2.8) km from the SCO2AT, MCO2AT, old VISST, and new VISST, respectively. Compared to the CPL, the MCO2AT CTHs had the smallest mean biases for semitransparent high clouds in both single-layered and multilayered situations whereas the new VISST CTHs had the smallest mean biases when upper clouds were opaque and optically thick. The biases for all techniques increased with increasing numbers of cloud layers. The transparency of the upper layer clouds tends to increase with the numbers of cloud layers.

  17. Multi-sensor cloud and aerosol retrieval simulator and remote sensing from model parameters - Part 2: Aerosols

    NASA Astrophysics Data System (ADS)

    Wind, Galina; da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

    2016-07-01

    The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a "simulated radiance" product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land-ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers.This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled.In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model subgrid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to

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

    NASA Astrophysics Data System (ADS)

    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

  19. NASA Team 2 Sea Ice Concentration Algorithm Retrieval Uncertainty

    NASA Technical Reports Server (NTRS)

    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

  20. Cloud-Aerosol Interactions: Retrieving Aerosol Ångström Exponents from Calipso Measurements of Opaque Water Clouds

    NASA Astrophysics Data System (ADS)

    Vaughan, Mark; Liu, Zhaoyan; Hu, Yong-Xiang; Powell, Kathleen; Omar, Ali; Rodier, Sharon; Hunt, William; Kar, Jayanta; Tackett, Jason; Getzewich, Brian; Lee, Kam-Pui

    2016-06-01

    Backscatter and extinction from water clouds are well-understood, both theoretically and experimentally, and thus changes to the expected measurement of layer-integrated attenuated backscatter can be used to infer the optical properties of overlying layers. In this paper we offer a first look at a new retrieval technique that uses CALIPSO measurements of opaque water clouds to derive optical depths and Ångström exponents for overlying aerosol layers.

  1. View angle dependence of MODIS liquid water path retrievals in warm oceanic clouds

    PubMed Central

    Horváth, Ákos; Seethala, Chellappan; Deneke, Hartwig

    2014-01-01

    We investigated the view angle dependence of domain mean Moderate Resolution Imaging Spectroradiometer (MODIS) liquid water path (LWP) and that of corresponding cloud optical thickness, effective radius, and liquid cloud fraction as proxy for plane-parallel retrieval biases. Independent Advanced Microwave Scanning Radiometer–EOS LWP was used to corroborate that the observed variations with sun-view geometry were not severely affected by seasonal/latitudinal changes in cloud properties. Microwave retrievals showed generally small (<10%) cross-swath variations. The view angle (cross-swath) dependence of MODIS optical thickness was weaker in backscatter than forward scatter directions and transitioned from mild ∩ shape to stronger ∪ shape as heterogeneity, sun angle, or latitude increased. The 2.2 µm effective radius variations always had a ∪ shape, which became pronounced and asymmetric toward forward scatter in the most heterogeneous clouds and/or at the lowest sun. Cloud fraction had the strongest and always ∪-shaped view angle dependence. As a result, in-cloud MODIS cloud liquid water path (CLWP) showed surprisingly good view angle (cross-swath) consistency, usually comparable to that of microwave retrievals, due to cancelation between optical thickness and effective radius biases. Larger (20–40%) nadir-relative increases were observed in the most extreme heterogeneity and sun angle bins, that is, typically in the polar regions, which, however, constituted only 3–8% of retrievals. The good consistency of MODIS in-cloud CLWP was lost for gridbox mean LWP, which was dominated by the strong cloud fraction increase with view angle. More worryingly, MODIS LWP exhibited significant and systematic absolute increases with heterogeneity and sun angle that is not present in microwave LWP. Key Points Microwave LWP shows small overall and cross-swath variations MODIS in-cloud LWP also shows good view angle consistency in most cases MODIS retrievals show strong

  2. Intercomparison of MAX-DOAS NO2 retrieval algorithms

    NASA Astrophysics Data System (ADS)

    Peters, Enno; Pinardi, Gaia; Bösch, Tim; Wittrock, Folkard; Richter, Andreas; Burrows, John P.; Van Roozendael, Michel; Piters, Ankie; Wagner, Thomas; Drosoglou, Theano; Bais, Alkis; Wang, Shanshan; Saiz-Lopez, Alfonso

    2016-04-01

    maturity and comparability of the retrieval algorithms but also point at areas where further homogenization or at least better documentation of retrieval procedures would be beneficial.

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

    NASA Technical Reports Server (NTRS)

    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.

  4. How Do A-train Sensors Intercompare in the Retrieval of Above-cloud Aerosol Optical Depth? A Case Study-based Assessment

    NASA Technical Reports Server (NTRS)

    Jethva, Hiren; Torres, Omar; Waquet, Fabien; Chand, Duli; Hu, Yongxiang

    2014-01-01

    We intercompare the above-cloud aerosol optical depth (ACAOD) of biomass burning plumes retrieved from A-train sensors, i.e., Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Polarization and Directionality of Earth Reflectances (POLDER), and Ozone Monitoring Instrument (OMI). These sensors have shown independent capabilities to retrieve aerosol loading above marine boundary layer clouds-a kind of situation often found over the southeast Atlantic Ocean during dry burning season. A systematic comparison reveals that all passive sensors and CALIOP-based research methods derive comparable ACAOD with differences mostly within 0.2 over homogeneous cloud fields. The 532 nm ACAOD retrieved by CALIOP operational algorithm is underestimated. The retrieved 1064 nm AOD however shows closer agreement with passive sensors. Given the different types of measurements processed with different algorithms, the reported close agreement between them is encouraging. Due to unavailability of direct measurements above cloud, the validation of satellite-based ACAOD remains an open challenge. The intersatellite comparison however can be useful for the relative evaluation and consistency check

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

    NASA Technical Reports Server (NTRS)

    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 AIRSAMSU 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. CrISATMS is the only scheduled follow on to AIRSAMSU. The objective of this research is to prepare for generation of a long term CrISATMS level-3 data using a finalized retrieval algorithm that is scientifically equivalent to AIRSAMSU Version-7.

  6. Evaluation of Multilayer Cloud Detection Using a MODIS CO2-Slicing Algorithm With CALIPSO-CloudSat Measurements

    NASA Technical Reports Server (NTRS)

    Viudez-Mora, Antonio; Kato, Seiji

    2015-01-01

    This work evaluates the multilayer cloud (MCF) algorithm based on CO2-slicing techniques against CALISPO-CloudSat (CLCS) measurement. This evaluation showed that the MCF underestimates the presence of multilayered clouds compared with CLCS and are retrained to cloud emissivities below 0.8 and cloud optical septs no larger than 0.3.

  7. The progress of Chinese Carbon Dioxide Satellite (TanSat): observation design, Retrieval algorithm and validation network

    NASA Astrophysics Data System (ADS)

    Liu, Y.

    2014-12-01

    The Chinese carbon dioxide observation satellite (TanSat) project is the national high technology research and development program. It is funded by the ministry of science and technology of the people's republic of China and the Chinese Academy of Sciences. TanSat will monitor carbon dioxide in Sun-Synchronous orbit by a hyper resolution grating spectrometer - Carbon Dioxide Sensor. A wide field of view moderate resolution imaging spectrometer - Cloud and Aerosol Polarization Imager (CAPI) will measure the aerosol and cloud properties synchronously. TanSat project turned to Critical Design Phase after Preliminary Design Review on June 2013, and it plan to finish Critical Design Review on December 2014 and launch on July 2016. A multi-bands retrieval algorithm has been developed to approach XCO2 with applying O2A band observation to reduce aerosol and cirrus cloud influence. The state vector list has been modified from previous two-bands algorithm by adding aerosol model parameters, cirrus cloud model parameters and linear correction on O2A bands. Application of TanSat XCO2 retrieval Algorithm on GOSAT Observation (ATANGO) has been developed from multi-bands TanSat algorithm. GOSAT observation has been used in retrieval experiment of ATANGO. A preliminary inter comparison test has been carried out with the XCO2 product of University of Leicester (UoL) full physics algorithm. The bias of 1.2 hPa (~0.1%) and 2.4ppm (~0.6%) of surface pressure and XCO2 between ATANGO and UoL were indicated, and the standard deviation of 2.8hPa (~0.28%) and 1.23ppm (~0.3%) of surface pressure and XCO2 between ATANGO and UoL were found. The Ground-based observation network of XCO2 in China was developed, which include three Fourier transform infrared spectroscopy (IFS-125) over Xinglong, Beijing, Shenzhen, and three Optical Spectrum Analyzers (OSA) over Shangdong, Hainan Island, and Dunhuang, with different latitude and background. The measurement spectrum has been investigated with a

  8. Ice hydrometeor profile retrieval algorithm for high-frequency microwave radiometers: application to the CoSSIR instrument during TC4

    NASA Astrophysics Data System (ADS)

    Evans, K. F.; Wang, J. R.; O'C Starr, D.; Heymsfield, G.; Li, L.; Tian, L.; Lawson, R. P.; Heymsfield, A. J.; Bansemer, A.

    2012-09-01

    A Bayesian algorithm to retrieve profiles of cloud ice water content (IWC), ice particle size (Dme), and relative humidity from millimeter-wave/submillimeter-wave radiometers is presented. The first part of the algorithm prepares an a priori file with cumulative distribution functions (CDFs) and empirical orthogonal functions (EOFs) of profiles of temperature, relative humidity, three ice particle parameters (IWC, Dme, distribution width), and two liquid cloud parameters. The a priori CDFs and EOFs are derived from CloudSat radar reflectivity profiles and associated ECMWF temperature and relative humidity profiles combined with three cloud microphysical probability distributions obtained from in situ cloud probes. The second part of the algorithm uses the CDF/EOF file to perform a Bayesian retrieval with a hybrid technique that uses Monte Carlo integration (MCI) or, when too few MCI cases match the observations, uses optimization to maximize the posterior probability function. The very computationally intensive Markov chain Monte Carlo (MCMC) method also may be chosen as a solution method. The radiative transfer model assumes mixtures of several shapes of randomly oriented ice particles, and here random aggregates of spheres, dendrites, and hexagonal plates are used for tropical convection. A new physical model of stochastic dendritic snowflake aggregation is developed. The retrieval algorithm is applied to data from the Compact Scanning Submillimeter-wave Imaging Radiometer (CoSSIR) flown on the ER-2 aircraft during the Tropical Composition, Cloud and Climate Coupling (TC4) experiment in 2007. Example retrievals with error bars are shown for nadir profiles of IWC, Dme, and relative humidity, and nadir and conical scan swath retrievals of ice water path and average Dme. The ice cloud retrievals are evaluated by retrieving integrated 94 GHz backscattering from CoSSIR for comparison with the Cloud Radar System (CRS) flown on the same aircraft. The rms difference in

  9. Retrieval of Atmospheric CO2 Concentration above Clouds and Cloud Top Pressure from Airborne Lidar Measurements during ASCENDS Science Campaigns

    NASA Astrophysics Data System (ADS)

    Mao, J.; Ramanathan, A. K.; Rodriguez, M.; Allan, G. R.; Hasselbrack, W. E.; Abshire, J. B.; Riris, H.; Kawa, S. R.

    2014-12-01

    NASA Goddard is developing an integrated-path, differential absorption (IPDA) lidar approach to measure atmospheric CO2 concentrations from space as a candidate for NASA's ASCENDS (Active Sensing of CO2 Emissions over Nights, Days, and Seasons) mission. The approach uses pulsed lasers to measure both CO2 and O2 absorption simultaneously in the vertical path to the surface at a number of wavelengths across a CO2 line at 1572.335 nm and an O2 line doublet near 764.7 nm. Measurements of time-resolved laser backscatter profiles from the atmosphere allow the technique to estimate column CO2 and O2 number density and range to cloud tops in addition to those to the ground. This allows retrievals of CO2 column above clouds and cloud top pressure, and all-sky measurement capability from space. This additional information can be used to evaluate atmospheric transport processes and other remote sensing carbon data in the free atmosphere, improve carbon data assimilation in models and help global and regional carbon flux estimates. We show some preliminary results of this capability using airborne lidar measurements from the summers of 2011 and 2014 ASCENDS science campaigns. These show simultaneous retrievals of CO2 and O2 column densities for laser returns from low-level marine stratus clouds in the west coast of California. This demonstrates the supplemental capability of the future space carbon mission to measure CO2 above clouds, which is valuable particularly for the areas with persistent cloud covers, e.g, tropical ITCZ, west coasts of continents with marine layered clouds and southern ocean with highest occurrence of low-level clouds, where underneath carbon cycles are active but passive remote sensing techniques using the reflected short wave sunlight are unable to measure accurately due to cloud scattering effect. We exercise cloud top pressure retrieval from O2 absorption measurements during the flights over the low-level marine stratus cloud decks, which is one of

  10. Retrieval algorithm development and product validation for TERRA/MOPITT

    NASA Astrophysics Data System (ADS)

    Deeter, M. N.; Martínez-Alonso, S.; Worden, H. M.; Emmons, L. K.; Dean, V.; Mao, D.; Edwards, D. P.; Gille, J. C.

    2014-10-01

    Satellite observations of tropospheric carbon monoxide (CO) are employed in diverse applications including air quality studies, chemical weather forecasting and the characterization of CO emissions through inverse modeling. The TERRA / MOPITT ('Measurements of Pollution in the Troposphere') instrument incorporates a set of gas correlation radiometers to observe CO simultaneously in both a thermal-infrared (TIR) band near 4.7 µm and a near-infrared (NIR) band near 2.3 μm. This multispectral capability is unique to MOPITT. The MOPITT retrieval algorithm for vertical profiles of CO has been refined almost continuously since TERRA was launched at the end of 1999. Retrieval algorithm enhancements are the result of ongoing analyses of instrument performance, improved radiative transfer modeling, and systematic comparisons with correlative data, including in-situ profiles measured from aircraft and products from other satellite instruments. In the following, we describe the methods used to routinely evaluate MOPITT CO profiles. As the satellite instrument with the longest record for CO, methods for assessing the long-term stability are becoming increasingly important.

  11. Hyperspectral remote sensing algorithms for retrieving forest chlorophyll content

    NASA Astrophysics Data System (ADS)

    Zhang, Yongqin

    Quantitative estimates of forest chlorophyll content from hyperspectral remote sensing are of great use for terrestrial carbon cycle modeling and sustainable forest management. Open forest canopies present a big challenge for the separation of the effects from canopy structure and leaf optical properties, and thus the retrieval of biochemical parameters. Process-based algorithms were developed to estimate the chlorophyll content of broadleaves and needleleaves from hyperspectral measurements. Field experiments were conducted from 2003 to 2004 near Sudbury and Haliburton, Ontario, to collect canopy structural, leaf biophysical and biochemical data. Experiments show that optical properties and biochemical contents of broadleaves change with the growing season and canopy height. Needleleaves from different sites, age classes, and branch orientations demonstrate different visible optical properties in relation to their chlorophyll contents. A process-based radiative transfer model PROSPECT was modified to retrieve leaf chlorophyll content from measured leaf spectra. For broadleaves, leaf thickness was introduced to consider the seasonal and canopy-gradient variation in light absorption. The accuracy of chlorophyll retrieval is increased from 67% to 91%. For needleleaves, the effects of needleleaf width and thickness, and geometrical effects of leaf-holding devices on spectra measurements were taken into account. These modifications improve the accuracy of chlorophyll retrieval from 31% to 59%. Correct exposure for digital hemispherical photographs is crucial for estimating canopy structural parameters. A photographic exposure theory was tested for different forest types with various canopy closures and under different sky conditions. The exposure method improves the estimates of leaf area index by 40% in comparison with commonly used automatic exposure. The effects of canopy structure on optical remote sensing signals were investigated using the geometrical

  12. Registration algorithm of point clouds based on multiscale normal features

    NASA Astrophysics Data System (ADS)

    Lu, Jun; Peng, Zhongtao; Su, Hang; Xia, GuiHua

    2015-01-01

    The point cloud registration technology for obtaining a three-dimensional digital model is widely applied in many areas. To improve the accuracy and speed of point cloud registration, a registration method based on multiscale normal vectors is proposed. The proposed registration method mainly includes three parts: the selection of key points, the calculation of feature descriptors, and the determining and optimization of correspondences. First, key points are selected from the point cloud based on the changes of magnitude of multiscale curvatures obtained by using principal components analysis. Then the feature descriptor of each key point is proposed, which consists of 21 elements based on multiscale normal vectors and curvatures. The correspondences in a pair of two point clouds are determined according to the descriptor's similarity of key points in the source point cloud and target point cloud. Correspondences are optimized by using a random sampling consistency algorithm and clustering technology. Finally, singular value decomposition is applied to optimized correspondences so that the rigid transformation matrix between two point clouds is obtained. Experimental results show that the proposed point cloud registration algorithm has a faster calculation speed, higher registration accuracy, and better antinoise performance.

  13. Understanding Differences Between Co-Incident CloudSat, Aqua/MODIS and NOAA18 MHS Ice water Path Retrievals Over the Tropical Oceans

    NASA Technical Reports Server (NTRS)

    Pittman, Jasna; Robertson, Franklin; Blankenship, Clay

    2008-01-01

    Accurate measurement of the physical and radiative properties of clouds and their representation in climate models continues to be a challe nge. Model parameterizations are still subject to a large number of t unable parameters; furthermore, accurate and representative in situ o bservations are very sparse, and satellite observations historically have significant quantitative uncertainties, particularly with respect to particle size distribution (PSD) and cloud phase. Ice Water Path (IWP), or amount of ice present in a cloud column, is an important cl oud property to accurately quantify, because it is an integral measur e of the microphysical properties of clouds and the cloud feedback pr ocesses in the climate system. This paper investigates near co-incident retrievals of IWP over tropical oceans using three diverse measurem ent systems: radar from CloudSat, Vis/IR from Aqua/MODIS, and microwa ve from NOAA-18IMHS. CloudSat 94 GHz radar measurements provide high resolution vertical and along-orbit structure of cloud reflectivity a nd enable IWP (and IWC) retrievals. Overlapping MODIS measurements of cloud optical thickness and phase allow estimates of IWP when cloud tops are identified as being ice. Periodically, NOAA18 becomes co-inci dent in space I time to enable comparison of A-Train measurements to IWP inferred from the 157 and 89 GHz channel radiances. This latter m easurement is effective only for thick convective anvil systems. We s tratify these co-incident data (less than 4 minutes separation) into cirrus only, cirrus overlying liquid water clouds, and precipitating d eep convective clouds. Substantial biases in IWP and ice effective ra dius are found. Systematic differences in these retrievals are consid ered in light of the uncertainties in a priori assumptions ofPSDs, sp ectral sensitivity and algorithm strategies, which have a direct impact on the IWP product.

  14. Retrieval of atmospheric methane from high spectral resolution satellite measurements: a correction for cirrus cloud effects.

    PubMed

    Bril, Andrey; Oshchepkov, Sergey; Yokota, Tatsuya

    2009-04-10

    We assessed the accuracy of methane (CH(4)) retrievals from synthetic radiance spectra particular to Greenhouse Gases Observing Satellite observations. We focused on estimating the CH(4) vertical column amount from an atmosphere that includes thin cirrus clouds, taking into account uncertain meteorological conditions. A photon path-length probability density function (PPDF)-based method was adapted to correct for atmospheric scattering effects in CH(4) retrievals. This method was shown to provide similar retrieval accuracy as compared to a carbon dioxide (CO(2))-proxy-based correction approach. It infers some advantages of PPDF-based method for methane retrievals under high variability of CO(2) abundance. PMID:19363553

  15. CALIOP/CALIPSO: Improvement in the retrieval algorithm and a few applications

    NASA Astrophysics Data System (ADS)

    Kacenelenbogen, M. S.; Vaughan, M.; Redemann, J.; Hoff, R. M.; Rogers, R.; Ferrare, R. A.; Russell, P. B.; Hostetler, C. A.; Hair, J. W.; Holben, B.

    2010-12-01

    The Cloud Aerosol LIdar with Orthogonal Polarization (CALIOP), on board the CALIPSO platform, has measured profiles of total attenuated backscatter coefficient (level 1 products) since June 2006. CALIOP’s level 2 products, such as the aerosol backscatter and extinction coefficient profiles, are retrieved using a complex succession of automated algorithms. One of our goals was to help identify potential shortcomings in the CALIOP version 2 level 2 aerosol extinction product and to illustrate some of the motivation for the changes that were introduced in the next version of CALIOP data (version 3, currently being processed). As a first step, we compared CALIOP version 2-derived AOD with collocated MODerate-resolution Imaging Spectroradiometer (MODIS) AOD retrievals over the Continental United States. The best statistical agreement between those two quantities was found over the Eastern part of the United States with, nonetheless, a weak correlation (R~0.4) and an apparent CALIOP version 2 underestimation (by ~66 %) of MODIS AOD. To help quantify the potential factors contributing to the uncertainty of the CALIOP aerosol extinction retrieval, we then focused on a one-day, multi-instrument, multiplatform comparison study during the CALIPSO and Twilight Zone (CATZ) validation campaign on August 04, 2007. This case study illustrates the following potential reasons for a bias in the version 2 CALIOP AOD: (i) CALIOP’s low signal-to-noise ratio (SNR) leading to the misclassification and/or lack of aerosol layer identification, especially close to the Earth’s surface; (ii) the cloud contamination of CALIOP version 2 aerosol backscatter and extinction profiles; (iii) potentially erroneous assumptions of the backscatter-to-extinction ratio (Sa) used in CALIOP’s extinction retrievals; and (iv) calibration coefficient biases in the CALIOP daytime attenuated backscatter coefficient profiles. We then show the use of the CALIPSO aerosol vertical distribution information in

  16. Development of a regional rain retrieval algorithm for exclusive mesoscale convective systems over peninsular India

    NASA Astrophysics Data System (ADS)

    Dutta, Devajyoti; Sharma, Sanjay; Das, Jyotirmay; Gairola, R. M.

    2012-06-01

    The present study emphasize the development of a region specific rain retrieval algorithm by taking into accounts the cloud features. Brightness temperatures (Tbs) from various TRMM Microwave Imager (TMI) channels are calibrated with near surface rain intensity as observed from the TRMM - Precipitation Radar. It shows that Tb-R relations during exclusive-Mesoscale Convective System (MCS) events have greater dynamical range compared to combined events of non-MCS and MCS. Increased dynamical range of Tb-R relations for exclusive-MCS events have led to the development of an Artificial Neural Network (ANN) based regional algorithm for rain intensity estimation. By using the exclusive MCSs algorithm, reasonably good improvement in the accuracy of rain intensity estimation is observed. A case study of a comparison of rain intensity estimation by the exclusive-MCS regional algorithm and the global TRMM 2A12 rain product with a Doppler Weather Radar shows significant improvement in rain intensity estimation by the developed regional algorithm.

  17. The effects of cloud inhomogeneities upon radiative fluxes, and the supply of a cloud truth validation dataset

    NASA Technical Reports Server (NTRS)

    Welch, Ronald M.

    1993-01-01

    A series of cloud and sea ice retrieval algorithms are being developed in support of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Science Team objectives. These retrievals include the following: cloud fractional area, cloud optical thickness, cloud phase (water or ice), cloud particle effective radius, cloud top heights, cloud base height, cloud top temperature, cloud emissivity, cloud 3-D structure, cloud field scales of organization, sea ice fractional area, sea ice temperature, sea ice albedo, and sea surface temperature. Due to the problems of accurately retrieving cloud properties over bright surfaces, an advanced cloud classification method was developed which is based upon spectral and textural features and artificial intelligence classifiers.

  18. Validation of Retrieved Aerosol Optical Properties over Northeast Asia for Five Years from GOSAT TANSO-Cloud and Aerosol Imager

    NASA Astrophysics Data System (ADS)

    Kim, J.; Lee, S.; KIM, M.; Choi, M.; Go, S.; Lim, H.; Goo, T. Y.; Nakajima, T.; Kuze, A.; Shiomi, K.; Yokota, T.

    2015-12-01

    An aerosol retrieval algorithm was developed from Thermal And Near infrared Sensor for carbon Observation-Cloud and Aerosol Imager (TANSO-CAI) onboard the Greenhouse Gases Observing Satellite (GOSAT). The algorithm retrieves aerosol optical depth (AOD), size distribution of aerosol, and aerosol type in 0.1 degree grid resolution by look-up tables, which is used in retrieving optical properties of aerosol using inversion products from Aerosol Robotic NETwork (AERONET) sun-photometer observation. To improve the accuracy of aerosol algorithm, first, this algorithm considered the annually estimated radiometric degradation factor of TANSO-CAI suggested by Kuze et al. (2014). Second, surface reflectance was determined by two methods: one using the clear sky composite method from CAI measurements and the other the database from MODerate resolution Imaging Sensor (MODIS) surface reflectance data. At a given pixel, the surface reflectance is selected by using normalized difference vegetation index (NDVI) depending on season (Hsu et al., 2013). In this study, the retrieved AODs were compared with those of AERONET and MODIS dataset for different season over five years. Comparisons of AODs between AERONET and CAI show reasonable agreement with correlation coefficients of 0.65 ~ 0.97 and regression slopes between 0.7 and 1.2 for the whole period, depending on season and sites. Moreover, those between MODIS and CAI for the same period show agreements with correlation coefficients of 0.7 ~ 0.9 and regression slopes between 0.7 and 1.0, depending on season and regions. The results show reasonably good correlation, however, the largest error source in aerosol retrieval has been surface reflectance of TANSO-CAI due to its 3-days revisit orbit characteristics.

  19. Retrieval and Validation of Aerosol Optical Properties over East Asia from TANSO-Cloud and Aerosol Imager

    NASA Astrophysics Data System (ADS)

    Lee, Sanghee; Kim, Jhoon; Kim, Mijin; Choi, Myungje; Go, Sujung; Lim, HyunKwang; Ou, Mi-Lim; Goo, Tae-Young; Yokota, Tatsuya

    2015-04-01

    Aerosol is a significant component on air quality and climate change. In particular, spatial and temporal distribution of aerosol shows large variability over East Asia, thus has large effect in retrieving carbon dioxide from Greenhouse Gases Observing Satellite (GOSAT) Thermal And Near infrared Sensor for carbon Observation Fourier Transform Spectrometer (TANSO-FTS). An aerosol retrieval algorithm was developed from TANSO- Cloud and Aerosol Imager (CAI) onboard the GOSAT. The algorithm retrieves aerosol optical depth (AOD), size distribution of aerosol, and aerosol type in 0.1 degree grid resolution and surface reflectance was estimated using the clear sky composite method. To test aerosol absorptivity, the reflectance difference method was considered using channels of TANSO-CAI. In this study, the retrieved aerosol optical depth (AOD) was compared with those of Aerosol Robotic NETwork (AERONET) and MODerate resolution Imaging Sensor (MODIS) dataset from September 2011 and August 2014. Comparisons of AODs between AERONET and CAI show the reasonably good correlation with correlation coefficient of 0.77 and regression slope of 0.87 for the whole period. Moreover, those between MODIS and CAI for the same period show correlations with correlation coefficient of 0.7 ~ 0.9 and regression slope of 0.7 ~ 1.2, depending on season and comparison regions however, the largest error source in aerosol retrieval has been surface reflectance. Over ocean and some Land, surface reflectance tends to be overestimated, and thereby CAI-AOD tends to be underestimated. Based on the results with CAI algorithm developed, the algorithm is continuously improved for better performance.

  20. Cloud Power Spectra-Dependence on Solar Zenith Angle and Wavelength, Implications for Cloud Optical Property Retrievals

    NASA Technical Reports Server (NTRS)

    Oreopoulos, Lazaros; Marshak, A.; Cahalan, R. F.; Wen, G.

    1999-01-01

    Scale breaks (spatial scales at which power-law exponent changes occur) observed in Landsat radiances have proven to be useful indicators of radiative interactions, and have aided the development of improved techniques in the remote sensing of clouds. This work extends previous theoretical studies to absorbing wavelengths by using both Landsat Thematic Mapper (TM) observations and Monte Carlo (MC) simulations to infer the systematic dependencies of power spectral shape on cloud characteristics, illumination conditions, and wavelength. We show that MC simulations operating on a simple fractal model of horizontally inhomogeneous clouds produce power spectra that qualitatively resemble observed spectra. We also show that the decrease in the spectra power-law exponent seen at intermediate scales (referred to as "roughening") as the Sun becomes more oblique is more pronounced at absorbing wavelengths. An automated procedure designed to detect the small scale break location is unable to find systematic differences between TM Band 4 and Band 7, despite the fact that MC simulations point to systematic differences in horizontal fluxes. The effect of these qualitative characteristics of the spatial spectra on the retrieval of cloud optical properties is examined by comparing power spectra of nadir radiances with power spectra of optical properties retrieved using either traditional Independent Pixel Approximation approaches or modifications based on normalized radiance indices and the inverse Non-local Independent Pixel Approximation. Assuming that the actual cloud properties follow perfect scaling behavior at all scales, we show the improvement of the proposed retrieval modifications.

  1. Integrated framework for retrievals in a networked radar environment: Application to the Mid-latitude Continental Convective Clouds Experiment

    NASA Astrophysics Data System (ADS)

    Hardin, J. C.; Chandrasekar, C. V.; Yoshikawa, E.; Ushio, T.

    2012-12-01

    The Mid-Latitude Continental Convective Clouds Experiment (MC3E), was a joint DOE Atmospheric Radiation Measurement (ARM) and NASA Global Precipitation Measurements (GPM) field campaign that took place from April - June 2011 in Central Oklahoma centered at the ARM Southern Great Plains site. The experiment was a collaborative effort between the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility and the National Aeronautics and Space Administration (NASA) Global Precipitation Measurement (GPM) mission Ground Validation (GV) program. The field campaign involved a large suite of observing infrastructure currently available in the central United States, combined with an extensive sounding array, remote sensing and in situ aircraft observations, NASA GPM ground validation remote sensors, and new ARM instrumentation. The overarching goal was to provide the most complete characterization of convective cloud systems, precipitation, and the environment that has ever been obtained, providing constraints for model cumulus parameterizations and space-based rainfall retrieval algorithms over land that had never before been available. The experiment consisted of a large number of ground radars, including NASA scanning dual-polarization radar systems (NPOL) at S-band, wind profilers, and a dense network of surface disdrometers. In addition to these special MC3E instruments, there were three networked scanning X-band radar systems, four wind profilers, a C-band scanning radar, a dual-wavelength (Ka/W) scanning cloud radar. There is extensive literature on the retrieval algorithms for precipitation and cloud parameters from single frequency, dual-polarization radar systems. With the cost of instruments such as radars becoming more affordable, multiple radar deployments are becoming more common in special programs, and the MC3E is a text book example of such a deployment. Networked deployments are becoming more common popularized by the

  2. On the rainfall retrieval with the 183-WSL algorithm over Northern Europe

    NASA Astrophysics Data System (ADS)

    Laviola, S.; Cattani, E.; Marra, F.; Levizzani, V.; Kidd, C.

    2009-04-01

    The algorithm 183-WSL (Laviola and Levizzani 2008) exploits variations in emitted radiation within the water vapor absorption band at 183.31 GHz due to the extinction by rain drops for the estimation of rainfall rates over ocean and land surfaces. The 183-WSL retrieval scheme infers rain types on the basis of signal extinction associated to the presence of different hydrometeor states. Icy hydrometeors, which generally scatter more at high frequencies, are linked to higher rain rates. At the same time the signal depression due to absorption by liquid rain drops, which is typically lower than the scattering signal by ice crystals, is suitable to derive the lighter rain rates. Previous comparisons with other techniques have demonstrated the robustness of the 183-WSL results with respect to different precipitating events mainly at mid-latitudes. The present challenge of our research is to validate the 183-WSL algorithm results at higher latitudes. Some case studies are proposed located over Northern Europe covering different seasonal rain events. Precipitation formed at latitudes higher than 50 degrees is layered within the first kilometers of the atmosphere and generally structured as large stratified clouds with icy particles aloft. Rain rates associated with these stratiform systems are normally light and persistent and the formation of snowflake aggregates is quite common. On the other hand, during the summer season large scale systems and long time precipitation can generate floods and intense run-off. The goal of this work is to emphasize the capability of the 183-WSL algorithm to discern multi-seasonal different rain types when compared with rain rates derived from radar networks considered as ground truth. Moreover, a suite of microphysical parameters will be retrieved from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and InfraRed Imager (SEVIRI) and employed to characterize the observed precipitation and better understand the retrieval

  3. Long Term Cloud Property Datasets From MODIS and AVHRR Using the CERES Cloud Algorithm

    NASA Technical Reports Server (NTRS)

    Minnis, Patrick; Bedka, Kristopher M.; Doelling, David R.; Sun-Mack, Sunny; Yost, Christopher R.; Trepte, Qing Z.; Bedka, Sarah T.; Palikonda, Rabindra; Scarino, Benjamin R.; Chen, Yan; Hong, Gang; Bhatt, Rajendra

    2015-01-01

    Cloud properties play a critical role in climate change. Monitoring cloud properties over long time periods is needed to detect changes and to validate and constrain models. The Clouds and the Earth's Radiant Energy System (CERES) project has developed several cloud datasets from Aqua and Terra MODIS data to better interpret broadband radiation measurements and improve understanding of the role of clouds in the radiation budget. The algorithms applied to MODIS data have been adapted to utilize various combinations of channels on the Advanced Very High Resolution Radiometer (AVHRR) on the long-term time series of NOAA and MetOp satellites to provide a new cloud climate data record. These datasets can be useful for a variety of studies. This paper presents results of the MODIS and AVHRR analyses covering the period from 1980-2014. Validation and comparisons with other datasets are also given.

  4. A Physically Based Algorithm for Non-Blackbody Correction of Cloud-Top Temperature and Application to Convection Study

    NASA Technical Reports Server (NTRS)

    Wang, Chunpeng; Lou, Zhengzhao Johnny; Chen, Xiuhong; Zeng, Xiping; Tao, Wei-Kuo; Huang, Xianglei

    2014-01-01

    Cloud-top temperature (CTT) is an important parameter for convective clouds and is usually different from the 11-micrometers brightness temperature due to non-blackbody effects. This paper presents an algorithm for estimating convective CTT by using simultaneous passive [Moderate Resolution Imaging Spectroradiometer (MODIS)] and active [CloudSat 1 Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)] measurements of clouds to correct for the non-blackbody effect. To do this, a weighting function of the MODIS 11-micrometers band is explicitly calculated by feeding cloud hydrometer profiles from CloudSat and CALIPSO retrievals and temperature and humidity profiles based on ECMWF analyses into a radiation transfer model.Among 16 837 tropical deep convective clouds observed by CloudSat in 2008, the averaged effective emission level (EEL) of the 11-mm channel is located at optical depth; approximately 0.72, with a standard deviation of 0.3. The distance between the EEL and cloud-top height determined by CloudSat is shown to be related to a parameter called cloud-top fuzziness (CTF), defined as the vertical separation between 230 and 10 dBZ of CloudSat radar reflectivity. On the basis of these findings a relationship is then developed between the CTF and the difference between MODIS 11-micrometers brightness temperature and physical CTT, the latter being the non-blackbody correction of CTT. Correction of the non-blackbody effect of CTT is applied to analyze convective cloud-top buoyancy. With this correction, about 70% of the convective cores observed by CloudSat in the height range of 6-10 km have positive buoyancy near cloud top, meaning clouds are still growing vertically, although their final fate cannot be determined by snapshot observations.

  5. Multipath Routing Algorithm Applied to Cloud Data Center Services

    NASA Astrophysics Data System (ADS)

    Matsuura, Hiroshi

    Cloud data center services, such as video on demand (VoD) and sensor data monitoring, have become popular. The quality of service (QoS) between a client and a cloud data center should be assured by satisfying each service's required bandwidth and delay. Multipath traffic engineering is effective for dispersing traffic flows on a network; therefore, an improved k-shortest paths first (k-SPF) algorithm is applied to these cloud data center services to satisfy their required QoS. k-SPF can create a set of multipaths between a cloud data center and all edge routers, to which client nodes are connected, within one algorithm process. Thus, k-SPF can produce k shortest simple paths between a cloud data center and every access router faster than with conventional Yen's algorithm. By using a parameter in the algorithm, k-SPF can also impartially use links on a network and shorten the average hop-count and number of necessary MPLS labels for multiple paths that comprise a multipath.

  6. Optical Characteristics of Aerosols and Clouds Retrieved from Sky Radiometer Data of SKYNET

    NASA Astrophysics Data System (ADS)

    Khatri, P.; Irie, H.; Takamura, T.

    2015-12-01

    SKYNET is an observation network to collect data related to aerosols, clouds, and radiation using a variety of ground-based instruments. The sky radiometer, manufactured by PREDE Co. Ltd., Japan, is one of the SKYNET instruments. Present research activities have made it possible to retrieve not only optical characteristics of aerosols and clouds, but also columnar water vapor and ozone concentrations using data of this instrument. This study analyzes sky radiometer data of various sites to understand optical characteristics of aerosols of different backgrounds. Several interesting results were obtained. For example, the light-absorption capacity of dust aerosols was observed to depend on not only mixed pollutants but also on aerosol size. We further studied the effects of aerosols on atmospheric heat budget using such observation data and a radiative transfer model. The results showed clear spatial and temporal variations of aerosol radiative forcing at the surface as well as top of atmosphere (TOA). Sky radiometer data of selected super sites of SKYNET were also analyzed to understand the optical characteristics of clouds. Such retrieved cloud parameters were validated using irradiances measured at the surface as well as MODIS cloud parameters. Though differences exist with respect to MODIS cloud parameters, irradiances calculated using sky radiometer retrieved cloud parameters agree fairly well with observed values.

  7. How do A-train Sensors Intercompare in the Retrieval of Above-Cloud Aerosol Optical Depth? A Case Study-based Assessment

    SciTech Connect

    Jethva, Hiren T.; Torres, Omar; Waquet, Fabien; Chand, Duli; Hu, Yong X.

    2014-01-15

    We inter-compare the above-cloud aerosol optical depth (ACAOD) of biomass burning plumes retrieved from different A-train sensors, i.e., MODIS, CALIOP, POLDER, and OMI. These sensors have shown independent capabilities to detect and retrieve aerosol loading above marine boundary layer clouds--a kind of situation often found over the Southeast Atlantic Ocean during dry burning season. A systematic one-to-one comparison reveals that, in general, all passive sensors and CALIOP-based research methods derive comparable ACAOD with differences mostly within 0.2 over homogeneous cloud fields. The 532-nm ACAOD retrieved by CALIOP operational algorithm is largely underestimated; however, it’s 1064-nm AOD when converted to 500 nm shows closer agreement to the passive sensors. Given the different types of sensor measurements processed with different algorithms, the close agreement between them is encouraging. Due to lack of adequate direct measurements above cloud, the validation of satellite-based ACAOD retrievals remains an open challenge. The inter-satellite comparison, however, can be useful for the relative evaluation and consistency check.

  8. Examining the Impact of Overlying Aerosols on the Retrieval of Cloud Optical Properties from Passive Remote Sensing

    NASA Technical Reports Server (NTRS)

    Coddington, O. M.; Pilewskie, P.; Redemann, J.; Platnick, S.; Russell, P. B.; Schmidt, K. S.; Gore, W. J.; Livingston, J.; Wind, G.; Vukicevic, T.

    2010-01-01

    Haywood et al. (2004) show that an aerosol layer above a cloud can cause a bias in the retrieved cloud optical thickness and effective radius. Monitoring for this potential bias is difficult because space ]based passive remote sensing cannot unambiguously detect or characterize aerosol above cloud. We show that cloud retrievals from aircraft measurements above cloud and below an overlying aerosol layer are a means to test this bias. The data were collected during the Intercontinental Chemical Transport Experiment (INTEX-A) study based out of Portsmouth, New Hampshire, United States, above extensive, marine stratus cloud banks affected by industrial outflow. Solar Spectral Flux Radiometer (SSFR) irradiance measurements taken along a lower level flight leg above cloud and below aerosol were unaffected by the overlying aerosol. Along upper level flight legs, the irradiance reflected from cloud top was transmitted through an aerosol layer. We compare SSFR cloud retrievals from below ]aerosol legs to satellite retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) in order to detect an aerosol ]induced bias. In regions of small variation in cloud properties, we find that SSFR and MODIS-retrieved cloud optical thickness compares within the uncertainty range for each instrument while SSFR effective radius tend to be smaller than MODIS values (by 1-2 microns) and at the low end of MODIS uncertainty estimates. In regions of large variation in cloud properties, differences in SSFR and MODIS ]retrieved cloud optical thickness and effective radius can reach values of 10 and 10 microns, respectively. We include aerosols in forward modeling to test the sensitivity of SSFR cloud retrievals to overlying aerosol layers. We find an overlying absorbing aerosol layer biases SSFR cloud retrievals to smaller effective radii and optical thickness while nonabsorbing aerosols had no impact.

  9. Final report (Grant No. DOE DE-FG02-97ER62366) [Retrieval of cloud fraction and type using broadband diffuse and total shortwave irradiance measurements

    SciTech Connect

    Clothiaux, Eugene

    2001-05-17

    The primary research effort supported by Grant No. DOE DEFG02-97ER62366 titled ''Retrieval of Cloud Fraction and Type Using Broadband Diffuse and Total Shortwave Irradiance Measurements'' was application of clear-sky identification and cloud fraction estimation algorithms developed by Charles N. Long and Thomas P. Ackerman to the downwelling total, direct and diffuse shortwave irradiance measurements made at all of the central, boundary, and extended facilities of the DOE Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SOP) site. Goals of the research were finalization and publication of the two algorithms in the peer-reviewed literature and operational application of them to all of aforementioned data streams from the ARM SGP site. The clear-sky identification algorithm was published as Long and Ackerman (2000) in the Journal of Geophysical Research, while a description of the cloud fraction estimation algorithm made it to the scientific literature as Long et al. (1999) in the Proceedings of the 10th American Meteorological Association Conference on Atmospheric Radiation held in Madison, Wisconsin. The cloud fraction estimation algorithm relies on empirical relationships between the outputs of the clear-sky identification algorithm and cloud fraction; as such, the cloud fraction estimation algorithm requires significant amounts of data both to properly develop the empirical relationships and to thoroughly test them. With this perspective in mind the major focus of our research efforts in the later half of the project became the operational implementation of the clear-sky identification algorithm on DOE ARM SGP data so that we could develop the data set necessary for final tuning of the cloud fraction estimation algorithm in research extending beyond the lifetime of the project.

  10. The Airborne Cloud-Aerosol Transport System. Part I; Overview and Description of the Instrument and Retrival Algorithms

    NASA Technical Reports Server (NTRS)

    Yorks, John E.; Mcgill, Matthew J.; Scott, V. Stanley; Kupchock, Andrew; Wake, Shane; Hlavka, Dennis; Hart, William; Selmer, Patrick

    2014-01-01

    The Airborne Cloud-Aerosol Transport System (ACATS) is a multi-channel Doppler lidar system recently developed at NASA Goddard Space Flight Center (GSFC). A unique aspect of the multi-channel Doppler lidar concept such as ACATS is that it is also, by its very nature, a high spectral resolution lidar (HSRL). Both the particulate and molecular scattered signal can be directly and unambiguously measured, allowing for direct retrievals of particulate extinction. ACATS is therefore capable of simultaneously resolving the backscatterextinction properties and motion of a particle from a high altitude aircraft. ACATS has flown on the NASA ER-2 during test flights over California in June 2012 and science flights during the Wallops Airborne Vegetation Experiment (WAVE) in September 2012. This paper provides an overview of the ACATS method and instrument design, describes the ACATS retrieval algorithms for cloud and aerosol properties, and demonstrates the data products that will be derived from the ACATS data using initial results from the WAVE project. The HSRL retrieval algorithms developed for ACATS have direct application to future spaceborne missions such as the Cloud-Aerosol Transport System (CATS) to be installed on the International Space Station (ISS). Furthermore, the direct extinction and particle wind velocity retrieved from the ACATS data can be used for science applications such 27 as dust or smoke transport and convective outflow in anvil cirrus clouds.

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

    NASA Technical Reports Server (NTRS)

    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.

  12. Influence of inhomogeneous cloud fields on optical properties retrieved from satellite observations

    NASA Astrophysics Data System (ADS)

    Dim, Jules R.; Takamura, Tamio; Okada, Itaru; Nakajima, Takashi Y.; Takenaka, Hideaki

    2007-07-01

    Analyses of solar radiation exchanges between the atmosphere and clouds are vital for the understanding of climate processes and cycles. Comparisons of satellite-to-satellite or satellite-to-ground-truth observations aiming at, elucidating the radiative behavior of atmospheric components (clouds, aerosols, gas, etc.), or validating data of a particular satellite are a common practice in global radiation investigations. In order to assess the quality of cloud optical properties derived from Geostationary Meteorological Satellite-5/Stretched Visible Infrared Spin Scan Radiometer (GMS-5/SVISSR), the former procedure (satellite-to-satellite comparison) was used. Data derived from GMS-5/SVISSR satellite were compared with those from the polar-orbiting Terra-Moderate Resolution Imaging Spectroradiometer (Terra-MODIS) satellite. This comparison showed serious discrepancies between cloud optical depth (COD) data retrieved from the two satellites' observations. GMS-5/SVISSR-retrieved COD appeared mostly lower than that of Terra-MODIS. To understand the origin of such differences, an identification procedure of the major factors likely to affect these data is conducted. Some of these factors were the satellite viewing and solar conditions, the cloud thermodynamic phase differentiation and particle effective radius, and the cloud inhomogeneity. Then emphasis was put on the examination of the latter effect (i.e., the cloud inhomogeneity). The analysis procedure was as follows: First, data having close-viewing geometries between both satellites were selected and used to understand the effects of the remaining factors. Among these, the cloud thermodynamic phase appeared to play the major role as analyses showed that most of the COD differences between both satellites were confined within ice clouds while warm clouds had the least discrepancies. This would suggest that the choice of a water cloud particle radiative transfer model to analyze a 2-phase cloud radiation data, as used

  13. Retrieval of cloud microphysical parameters from INSAT-3D: a feasibility study using radiative transfer simulations

    NASA Astrophysics Data System (ADS)

    Jinya, John; Bipasha, Paul S.

    2016-05-01

    Clouds strongly modulate the Earths energy balance and its atmosphere through their interaction with the solar and terrestrial radiation. They interact with radiation in various ways like scattering, emission and absorption. By observing these changes in radiation at different wavelength, cloud properties can be estimated. Cloud properties are of utmost importance in studying different weather and climate phenomena. At present, no satellite provides cloud microphysical parameters over the Indian region with high temporal resolution. INSAT-3D imager observations in 6 spectral channels from geostationary platform offer opportunity to study continuous cloud properties over Indian region. Visible (0.65 μm) and shortwave-infrared (1.67 μm) channel radiances can be used to retrieve cloud microphysical parameters such as cloud optical thickness (COT) and cloud effective radius (CER). In this paper, we have carried out a feasibility study with the objective of cloud microphysics retrieval. For this, an inter-comparison of 15 globally available radiative transfer models (RTM) were carried out with the aim of generating a Look-up- Table (LUT). SBDART model was chosen for the simulations. The sensitivity of each spectral channel to different cloud properties was investigated. The inputs to the RT model were configured over our study region (50°S - 50°N and 20°E - 130°E) and a large number of simulations were carried out using random input vectors to generate the LUT. The determination of cloud optical thickness and cloud effective radius from spectral reflectance measurements constitutes the inverse problem and is typically solved by comparing the measured reflectances with entries in LUT and searching for the combination of COT and CER that gives the best fit. The products are available on the website www.mosdac.gov.in

  14. How Often and Why MODIS Cloud Property Retrievals Fail for Liquid-Phase Clouds over Ocean? a Comprehensive Analysis Based on a-Train Observations

    NASA Astrophysics Data System (ADS)

    Zhang, Z.; Cho, H. M.; Platnick, S. E.; Meyer, K.; Lebsock, M. D.

    2014-12-01

    The cloud optical thickness (τ) and droplet effective radius (re) are two key cloud parameters retrieved by MODIS (Moderate Resolution Imaging Spectroradiometer). These MODIS cloud products are widely used in a broad range of earth system science applications. In this paper, we present a comprehensive analysis of the failed cloud τ and/or re retrievals for liquid-phase clouds over ocean in the Collection 6 MODIS cloud product. The main findings from this study are summarized as follows: MODIS retrieval failure rates for marine boundary layer (MBL) clouds have a strong dependence on the spectral combination used for retrieval (e.g., 0.86 + 2.1 µm vs. 0.8 + 3.7 µm) and the cloud morphology (i.e., "good" pixels vs. partly cloudy (PCL) pixels). Combining all clear-sky-restoral (CSR) categories (CSR=0,1 and 3), the 0.86 + 2.1 µm and 0.86 + 3.7 µm spectral combinations have an overall failure rate of about 20% and 12%, respectively (See figure below). The PCL pixels (CSR=1 & 3) have significantly higher failure rates and contribute more to the total failure population than the "good" (CSR=0) pixels. The majority of the failed retrievals are caused by the re too large failure, which explains about 85% and 70% of the failed 0.86 + 2.1 µm and 0.86 + 3.7 µm retrievals, respectively. The remaining failures are either due to the re too small failure or τ retrieval failure. The geographical distribution of failure rates has a significant dependence on cloud regime, lower over the coastal stratocumulus cloud regime and higher over the broken trade-wind cumulus cloud regime over open oceans. Enhanced retrieval failure rates are found when MBL clouds have high sub-pixel inhomogeneity , or are located at special Sun-satellite viewing geometries, such as sunglint, large viewing or solar zenith angle, or cloudbow and glory angles, or subject to cloud masking, cloud overlapping and/or cloud phase retrieval issues. About 80% of the failure retrievals can be attributed to at

  15. Improvements in dark water, low light-level AOD retrievals in MISR operational algorithm

    NASA Astrophysics Data System (ADS)

    Witek, M. L.; Diner, D. J.; Garay, M. J.; Xu, F.

    2015-12-01

    Satellite remote sensing of aerosols is taking bold steps towards higher spatial resolutions, as evidenced by the newly released MODIS 3 km product and the soon to be released MISR 4.4 km product. Finer horizontal resolution allows for a better aerosol characterization in proximity to clouds—which is important for studying indirect aerosol effects—but also poses additional challenges due to various cloud artifact effects. It is therefore imperative to refine satellite algorithms to correctly interpret aerosol behavior in the proximity of clouds. For instance, MISR aerosol optical depth (AOD) retrievals frequently overestimate AODs in pristine oceanic areas, in particular close to Antarctica, as evidenced by comparison with Maritime Aerosol Network (MAN) observations. We trace the origin of this overestimation to stray light, or veiling light, being scattered more or less uniformly over the camera's field of view and reducing the contrast of the primary image. We found that the MISR-MODIS radiance difference in dark areas correlates with average scene brightness within the whole MISR camera field of view. A simple, single parameter model is proposed to effect the corrections. Collocated MISR/MODIS pixels are used to fit the parameter in the MISR nadir camera. For the off-nadir cameras two alternative approaches are employed that are based on MISR radiances and radiative transfer model calculations. These two methods are prone to higher uncertainties, but suggest somewhat increasing correction values for the longer focal length cameras. Finally, the empirical corrections applied in the operational MISR retrieval algorithm substantially decrease AODs in analyzed cases, and lead to closer agreement with MAN and MODIS, proving the efficacy of the developed procedure.

  16. Variability in AIRS-retrieved cloud amount and thermodynamic phase over west versus east Antarctica influenced by the SAM

    NASA Astrophysics Data System (ADS)

    Lubin, Dan; Kahn, Brian H.; Lazzara, Matthew A.; Rowe, Penny; Walden, Von P.

    2015-02-01

    In a sample of summertime cloud retrievals from the NASA Atmospheric Infrared Sounder (AIRS), a positive Southern Annular Mode (SAM) index polarity is associated with greater cloud frequency and larger effective cloud fraction over West Antarctica compared with a negative SAM index polarity. The opposite result appears over the high East Antarctic Plateau. Comparing AIRS-retrieved cloud fraction with Antarctic Automatic Weather Station 2 m air temperature data, a positive and significant correlation is found over most of West Antarctica, signifying a longwave heating effect of clouds. Over East Antarctica correlations between Sun elevation and 2 m air temperature are strongest, consistent with lower cloud amount.

  17. Characterization of errors in cirrus simulations from a cloud resolving model for application in ice water content retrievals

    NASA Astrophysics Data System (ADS)

    Benedetti, A.; Stephens, G. L.

    Data available from the Atmospheric Radiation Measurement-Unmanned Aerospace Vehicle (ARM-UAV) Spring 1999 experiment are used in this study to estimate errors in cirrus simulations from a 3D Cloud Resolving Model (CRM). The performance of the model, heritage of the CSU Regional Atmospheric Modeling System (RAMS) is assessed by direct comparison of modeled and observed fields. Results show that the CRM succeeds in placing the cloud at approximately the correct altitude, but consistently overestimates the Ice Water Content (IWC). A statistical approach is introduced and applied to quantify average model bias under the assumption of bias-free observations. An error covariance matrix associated with simulated fields is also computed, and used to identify model strengths and deficiencies. Model fields are then used in the context of an optimum estimation retrieval of IWC from a combination of radar and radiometric observations. The retrieval is based on the knowledge of an a priori profile and relative error covariance to ensure algorithm convergence and stability. RAMS average Ice Water Content, corrected for the bias, and the related error covariance matrix derived in this study are used to provide this a priori information to the retrieval.

  18. Retrieval of cloud optical properties using airborne hyperspectral cameras during the VOCALS campaign.

    NASA Astrophysics Data System (ADS)

    Labrador, L.; Vaughan, G.

    2009-09-01

    A set of two hyperspectral imaging sensors have been used to analyze the optical properties of stratocumulus cloud off the coast of Northern Chile within the framework of the VAMOS Ocean Clouds Atmosphere Land Study (VOCALS) during September-October 2008. The SPECIM Aisa Eagle & Hawk are tandem pushbroom-type hyperspectral imagers scanning in the 400-970 and 970-2500 nm range, respectively. The instruments were mounted onboard the National Environmental Research Council's (NERC) Dornier DO-228 aircraft, based in Arica, northern Chile during the campaign. An area approximately 600 x 200 km was surveyed off the northern coast of Chile and a total of 14 science flights were carried out where hyperspectral data were successfully collected over the stratocumulus deck at altitudes varying between 10000 and 15000 ft. Cloud optical properties, such as cloud optical thickness, cloud effective radius and liquid water path can be retrieved which can then be compared with space-borne hyperspectral imagers' retrievals. Atmospheric corrections have been applied to enable the comparison between the different type of sensors and the analysis requires, amongst other, solving the back-scattering problems associated with off-nadir views. The high resolution, both spatial and temporal, of these airborne sensors makes them ideal to validate satellite retrievals of cloud optical properties.

  19. Absorbing Aerosols Above Cloud: Detection, Quantitative Retrieval, and Radiative Forcing from Satellite-based Passive Sensors

    NASA Astrophysics Data System (ADS)

    Jethva, H.; Torres, O.; Remer, L. A.; Bhartia, P. K.

    2012-12-01

    Light absorbing particles such as carbonaceous aerosols generated from biomass burning activities and windblown dust particles can exert a net warming effect on climate; the strength of which depends on the absorption capacity of the particles and brightness of the underlying reflecting background. When advected over low-level bright clouds, these aerosols absorb the cloud reflected radiation from ultra-violet (UV) to shortwave-IR (SWIR) and makes cloud scene darker-a phenomenon commonly known as "cloud darkening". The apparent "darkening" effect can be seen by eyes in satellite images as well as quantitatively in the spectral reflectance measurements made by space borne sensors over regions where light absorbing carbonaceous and dust aerosols overlay low-level cloud decks. Theoretical radiative transfer simulations support the observational evidence, and further reveal that the strength of the cloud darkening and its spectral signature (or color ratio) between measurements at two wavelengths are a bi-function of aerosol and cloud optical thickness (AOT and COT); both are measures of the total amount of light extinction caused by aerosols and cloud, respectively. Here, we developed a retrieval technique, named as the "color ratio method" that uses the satellite measurements at two channels, one at shorter wavelength in the visible and one at longer wavelength in the shortwave-IR for the simultaneous retrieval of AOT and COT. The present technique requires assumptions on the aerosol single-scattering albedo and aerosol-cloud separation which are supplemented by the Aerosol Robotic Network (AERONET) and space borne CALIOP lidar measurements. The retrieval technique has been tested making use of the near-UV and visible reflectance observations made by the Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) for distinct above-cloud smoke and dust aerosol events observed seasonally over the southeast and tropical Atlantic Ocean

  20. Improvement of Passive Microwave Rainfall Retrieval Algorithm over Mountainous Terrain

    NASA Astrophysics Data System (ADS)

    Shige, S.; Yamamoto, M.

    2015-12-01

    The microwave radiometer (MWR) algorithms underestimate heavy rainfall associated with shallow orographic rainfall systems owing to weak ice scattering signatures. Underestimation of the Global Satellite Mapping of Precipitation (GSMaP) MWR has been mitigated by an orographic/nonorographic rainfall classification scheme (Shige et al. 2013, 2015; Taniguchi et al. 2013; Yamamoto and Shige 2015). The orographic/nonorographic rainfall classification scheme is developed on the basis of orographically forced upward vertical motion and the convergence of surface moisture flux estimated from ancillary data. Lookup tables derived from orographic precipitation profiles are used to estimate rainfall for an orographic rainfall pixel, whereas those derived from original precipitation profiles are used to estimate rainfall for a nonorographic rainfall pixel. The orographic/nonorographic rainfall classification scheme has been used by the version of GSMaP products, which are available in near real time (about 4 h after observation) via the Internet (http://sharaku.eorc.jaxa.jp/GSMaP/index.htm). The current version of GSMaP MWR algorithm with the orographic/nonorographic rainfall classification scheme improves rainfall estimation over the entire tropical region, but there is still room for improvement. In this talk, further improvement of orographic rainfall retrievals will be shown.

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

    NASA Astrophysics Data System (ADS)

    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.

  2. Satellite Inference of Thermals and Cloud Base Updraft Speeds Based on Retrieved Surface and Cloud Base Temperatures

    NASA Astrophysics Data System (ADS)

    Zheng, Y.; Rosenfeld, D.; Li, Z.

    2014-12-01

    Updraft speeds of thermals have always been difficult to measure, despite the significant role they play in transporting pollutants and in cloud formation and precipitation. In this study, updraft speeds measured by Doppler lidar are found to be correlated with the observed planetary boundary layer (PBL) and surface properties in the buoyancy-driven PBL over the Southern Great Plains (SGP) site operated by the U.S. Department of Energy's Atmospheric Radiation Program (ARM). Based on the found relationships, two approaches are proposed to estimate both maximum (Wmax ) and cloud base (Wb ) updraft speeds. The required input data are PBL height, 10-m horizontal wind speed, wind shear, surface skin temperature and 2-m air temperature. The application for remote sensing of updraft speeds in cloud-topped PBL from space was tested by using satellite-retrieved surface and cloud base temperature in combination with European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis data. Validation against lidar-measured updraft speeds indicates the feasibility of retrieving Wmax (root-mean-square error, RMSE, is 0.32 m/s) and Wb (RMSE is 0.42 m/s) for global coverage. This information is essential to advance the understanding of aerosol-cloud interactions. This method does not work for stable or mechanically-driven PBL.

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

    ERIC Educational Resources Information Center

    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)

  4. Simultaneous Retrieval of Aerosol and Cloud Properties During the MILAGRO Field Campaign

    NASA Technical Reports Server (NTRS)

    Knobelspiesse, K.; Cairns, B.; Redemann, J.; Bergstrom, R. W.; Stohl, A.

    2011-01-01

    Estimation of Direct Climate Forcing (DCF) due to aerosols in cloudy areas has historically been a difficult task, mainly because of a lack of appropriate measurements. Recently, passive remote sensing instruments have been developed that have the potential to retrieve both cloud and aerosol properties using polarimetric, multiple view angle, and multi spectral observations, and therefore determine DCF from aerosols above clouds. One such instrument is the Research Scanning Polarimeter (RSP), an airborne prototype of a sensor on the NASA Glory satellite, which unfortunately failed to reach orbit during its launch in March of 2011. In the spring of 2006, the RSP was deployed on an aircraft based in Veracruz, Mexico, as part of the Megacity Initiative: Local and Global Research Observations (MILAGRO) field campaign. On 13 March, the RSP over flew an aerosol layer lofted above a low altitude marine stratocumulus cloud close to shore in the Gulf of Mexico. We investigate the feasibility of retrieving aerosol properties over clouds using these data. Our approach is to first determine cloud droplet size distribution using the angular location of the cloud bow and other features in the polarized reflectance. The selected cloud was then used in a multiple scattering radiative transfer model optimization to determine the aerosol optical properties and fine tune the cloud size distribution. In this scene, we were able to retrieve aerosol optical depth, the fine mode aerosol size distribution parameters and the cloud droplet size distribution parameters to a degree of accuracy required for climate modeling. This required assumptions about the aerosol vertical distribution and the optical properties of the coarse aerosol size mode. A sensitivity study was also performed to place this study in the context of future systematic scanning polarimeter observations, which found that the aerosol complex refractive index can also be observed accurately if the aerosol optical depth is

  5. Image-Based Airborne LiDAR Point Cloud Encoding for 3d Building Model Retrieval

    NASA Astrophysics Data System (ADS)

    Chen, Yi-Chen; Lin, Chao-Hung

    2016-06-01

    With the development of Web 2.0 and cyber city modeling, an increasing number of 3D models have been available on web-based model-sharing platforms with many applications such as navigation, urban planning, and virtual reality. Based on the concept of data reuse, a 3D model retrieval system is proposed to retrieve building models similar to a user-specified query. The basic idea behind this system is to reuse these existing 3D building models instead of reconstruction from point clouds. To efficiently retrieve models, the models in databases are compactly encoded by using a shape descriptor generally. However, most of the geometric descriptors in related works are applied to polygonal models. In this study, the input query of the model retrieval system is a point cloud acquired by Light Detection and Ranging (LiDAR) systems because of the efficient scene scanning and spatial information collection. Using Point clouds with sparse, noisy, and incomplete sampling as input queries is more difficult than that by using 3D models. Because that the building roof is more informative than other parts in the airborne LiDAR point cloud, an image-based approach is proposed to encode both point clouds from input queries and 3D models in databases. The main goal of data encoding is that the models in the database and input point clouds can be consistently encoded. Firstly, top-view depth images of buildings are generated to represent the geometry surface of a building roof. Secondly, geometric features are extracted from depth images based on height, edge and plane of building. Finally, descriptors can be extracted by spatial histograms and used in 3D model retrieval system. For data retrieval, the models are retrieved by matching the encoding coefficients of point clouds and building models. In experiments, a database including about 900,000 3D models collected from the Internet is used for evaluation of data retrieval. The results of the proposed method show a clear superiority

  6. A physically based algorithm for non-blackbody correction of the cloud top temperature for the convective clouds

    NASA Astrophysics Data System (ADS)

    Wang, C.; Luo, Z. J.; Chen, X.; Zeng, X.; Tao, W.; Huang, X.

    2012-12-01

    Cloud top temperature is a key parameter to retrieval in the remote sensing of convective clouds. Passive remote sensing cannot directly measure the temperature at the cloud tops. Here we explore a synergistic way of estimating cloud top temperature by making use of the simultaneous passive and active remote sensing of clouds (in this case, CloudSat and MODIS). Weighting function of the MODIS 11μm band is explicitly calculated by feeding cloud hydrometer profiles from CloudSat retrievals and temperature and humidity profiles based on ECMWF ERA-interim reanalysis into a radiation transfer model. Among 19,699 tropical deep convective clouds observed by the CloudSat in 2008, the averaged effective emission level (EEL, where the weighting function attains its maximum) is at optical depth 0.91 with a standard deviation of 0.33. Furthermore, the vertical gradient of CloudSat radar reflectivity, an indicator of the fuzziness of convective cloud top, is linearly proportional to, d_{CTH-EEL}, the distance between the EEL of 11μm channel and cloud top height (CTH) determined by the CloudSat when d_{CTH-EEL}<0.6km. Beyond 0.6km, the distance has little sensitivity to the vertical gradient of CloudSat radar reflectivity. Based on these findings, we derive a formula between the fuzziness in the cloud top region, which is measurable by CloudSat, and the MODIS 11μm brightness temperature assuming that the difference between effective emission temperature and the 11μm brightness temperature is proportional to the cloud top fuzziness. This formula is verified using the simulated deep convective cloud profiles by the Goddard Cumulus Ensemble model. We further discuss the application of this formula in estimating cloud top buoyancy as well as the error characteristics of the radiative calculation within such deep-convective clouds.

  7. A 3D Cloud-Construction Algorithm for the EarthCARE Satellite Mission

    NASA Technical Reports Server (NTRS)

    Barker, H. W.; Jerg, M. P.; Wehr, T.; Kato, S.; Donovan, D. P.; Hogan, R. J.

    2011-01-01

    This article presents and assesses an algorithm that constructs 3D distributions of cloud from passive satellite imagery and collocated 2D nadir profiles of cloud properties inferred synergistically from lidar, cloud radar and imager data.

  8. A single field of view method for retrieving tropospheric temperature profiles from cloud-contaminated radiance data

    NASA Technical Reports Server (NTRS)

    Hodges, D. B.; Scoggins, J. R.

    1977-01-01

    The paper presents a method for retrieving single field of view tropospheric temperature profiles directly from cloud-contaminated radiance data through the use of auxiliary data such as observed shelter temperatures and estimated cloud-top height. A model was formulated to calculate cloud parameters for use with the radiative transport equation at an estimated cloud-top level. The cloud and temperature data are used in conjunction with real and simulated radiance data from NOAA satellites.

  9. Evaluation of long-term surface-retrieved cloud droplet number concentration with in situ aircraft observations

    NASA Astrophysics Data System (ADS)

    Lim, Kyo-Sun Sunny; Riihimaki, Laura; Comstock, Jennifer M.; Schmid, Beat; Sivaraman, Chitra; Shi, Yan; McFarquhar, Greg M.

    2016-03-01

    A new operational retrieval of cloud droplet number concentration (ND) at cloud base has been produced from surface remote sensors at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site for 13 years from January 1998 to January 2011. The retrieval is based on surface radiometer measurements of cloud optical depth from the multifilter rotating shadow band radiometer and liquid water path from the microwave radiometer (MWR). It is only applicable for single-layered overcast warm (stratus or stratocumulus) clouds. Evaluation with in situ aircraft measurements during the extended-term aircraft field campaign, Routine ARM Aerial Facility (AAF) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO), shows that the retrieved ND robustly reproduces the primary mode of the in situ measured probability density function (PDF) but produces too wide a distribution, primarily caused by frequent high cloud droplet number concentration. Our analysis shows that the error in the MWR retrievals at low liquid water paths is one possible reason for this deficiency. Modification through the diagnosed liquid water path from the coordinate solution improves not only the PDF of the retrieved ND but also the relationship between the cloud droplet number concentration and cloud droplet effective radius. Consideration of entrainment effects rather than assuming an adiabatic cloud improves the values of the ND retrieval by reducing the magnitude of cloud droplet number concentration. Aircraft measurements and retrieval comparisons suggest that retrieving the vertical distribution of cloud droplet number concentration and effective radius is feasible with an improvement of the parameter representing the mixing effects between environment and clouds and with a better understanding of the effect of mixing degree on cloud properties.

  10. Multi-sensor Cloud Retrieval Simulator and Remote Sensing from Model Parameters . Pt. 1; Synthetic Sensor Radiance Formulation; [Synthetic Sensor Radiance Formulation

    NASA Technical Reports Server (NTRS)

    Wind, G.; DaSilva, A. M.; Norris, P. M.; Platnick, S.

    2013-01-01

    In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.

  11. Aerosols correction of the OMI tropospheric NO2 retrievals over cloud-free scenes: Different methodologies based on the O2-O2 477 nm band

    NASA Astrophysics Data System (ADS)

    Chimot, Julien; Vlemmix, Tim; Veefkind, Pepijn; Levelt, Pieternel

    2016-04-01

    Numerous studies have drawn attention to the complexities related to the retrievals of tropospheric NO2 columns derived from satellite UltraViolet-Visible (UV-Vis) measurements in the presence of aerosols. Correction for aerosol effects will remain a challenge for the next generation of air quality satellite instruments such as TROPOMI on Sentinel-5 Precursor, Sentinel-4 and Sentinel-5. The Ozone Monitoring Instrument (OMI) instrument has provided daily global measurements of tropospheric NO2 for more than a decade. However, aerosols are not explicitly taken into account in the current operational OMI tropospheric NO2 retrieval chain (DOMINO v2 [Boersma et al., 2011]). Our study analyses 2 approaches for an operational aerosol correction, based on the use of the O2-O2 477 nm band. The 1st approach is the cloud-model based aerosol correction, also named "implicit aerosol correction", and already used in the operational chain. The OMI O2-O2 cloud retrieval algorithm, based on the Differential Optical Absorption Spectroscopy (DOAS) approach, is applied both to cloudy and to cloud-free scenes with aerosols present. Perturbation of the OMI cloud retrievals over scenes dominated by aerosols has been observed in recent studies led by [Castellanos et al., 2015; Lin et al., 2015; Lin et al., 2014]. We investigated the causes of these perturbations by: (1) confronting the OMI tropospheric NO2, clouds and MODIS AQUA aerosol products; (2) characterizing the key drivers of the aerosol net effects, compared to a signal from clouds, in the UV-Vis spectra. This study has focused on large industrialised areas like East-China, over cloud-free scenes. One of the key findings is the limitation due to the coarse sampling of the employed cloud Look-Up Table (LUT) to convert the results of the applied DOAS fit into effective cloud fraction and pressure. This leads to an underestimation of tropospheric NO2 amount in cases of particles located at elevated altitude. A higher sampling of the

  12. Impact of aerosols on the OMI tropospheric NO2 retrievals over industrialized regions: how accurate is the aerosol correction of cloud-free scenes via a simple cloud model?

    NASA Astrophysics Data System (ADS)

    Chimot, J.; Vlemmix, T.; Veefkind, J. P.; de Haan, J. F.; Levelt, P. F.

    2015-08-01

    The Ozone Monitoring Instrument (OMI) instrument has provided daily global measurements of tropospheric NO2 for more than a decade. Numerous studies have drawn attention to the complexities related to measurements of tropospheric NO2 in the presence of aerosols. Fine particles affect the OMI spectral measurements and the length of the average light path followed by the photons. However, they are not explicitly taken into account in the current OMI tropospheric NO2 retrieval chain. Instead, the operational OMI O2-O2 cloud retrieval algorithm is applied both to cloudy scenes and to cloud free scenes with aerosols present. This paper describes in detail the complex interplay between the spectral effects of aerosols, the OMI O2-O2 cloud retrieval algorithm and the impact on the accuracy of the tropospheric NO2 retrievals through the computed Air Mass Factor (AMF) over cloud-free scenes. Collocated OMI NO2 and MODIS Aqua aerosol products are analysed over East China, in industrialized area. In addition, aerosol effects on the tropospheric NO2 AMF and the retrieval of OMI cloud parameters are simulated. Both the observation-based and the simulation-based approach demonstrate that the retrieved cloud fraction linearly increases with increasing Aerosol Optical Thickness (AOT), but the magnitude of this increase depends on the aerosol properties and surface albedo. This increase is induced by the additional scattering effects of aerosols which enhance the scene brightness. The decreasing effective cloud pressure with increasing AOT represents primarily the absorbing effects of aerosols. The study cases show that the actual aerosol correction based on the implemented OMI cloud model results in biases between -20 and -40 % for the DOMINO tropospheric NO2 product in cases of high aerosol pollution (AOT ≥ 0.6) and elevated particles. On the contrary, when aerosols are relatively close to the surface or mixed with NO2, aerosol correction based on the cloud model results in

  13. Water droplets and ice retrievals in volcanic clouds using multispectral TIR satellite data. Correction procedure for SO2 estimation

    NASA Astrophysics Data System (ADS)

    Corradini, Stefano; Guerrieri, Lorenzo; Merucci, Luca; Pugnaghi, Sergio; Salerno, Giuseppe

    2015-04-01

    Among ash and gases, the volcanic clouds generated from several 2011-2014 Etna (Italy) lava fountains, were characterized by the huge presence of water droplets (wd) and/or ice. In some cases the wd/ice presence totally masked the ash signal and always significantly influenced the SO2 retrievals. Here the MODIS multispectral measurements are used to retrieve the volcanic wd and ice particles by means of two different techniques based on BTD (Brightness Temperature Difference) algorithm and VPR (Volcanic Plume Removal) approach. As test case the MODIS-Aqua images collected on Etna volcano the 10 April 2011 at 12:30 UTC and the 12 August 2011 at 11:15 UTC have been considered. Similarly to volcanic ashes, the wd/ice particles reduce the top of atmosphere radiance in the entire TIR spectral range, including the channels used for the SO2 retrieval. The net effect is a significant SO2 overestimation. Here two procedures for the correction of the wd/ice influence on SO2 retrieval are proposed. The results obtained from the MODIS 10 April 2011 MODIS image have been compared with the measurements collected by the FLAME ground-based network of DOAS instruments deployed on Mt. Etna.

  14. Spectral Dependence of MODIS Cloud Droplet Effective Radius Retrievals for Marine Boundary Layer Clouds

    NASA Technical Reports Server (NTRS)

    Zhang, Zhibo; Platnick, Steven E.; Ackerman, Andrew S.; Cho, Hyoun-Myoung

    2014-01-01

    Low-level warm marine boundary layer (MBL) clouds cover large regions of Earth's surface. They have a significant role in Earth's radiative energy balance and hydrological cycle. Despite the fundamental role of low-level warm water clouds in climate, our understanding of these clouds is still limited. In particular, connections between their properties (e.g. cloud fraction, cloud water path, and cloud droplet size) and environmental factors such as aerosol loading and meteorological conditions continue to be uncertain or unknown. Modeling these clouds in climate models remains a challenging problem. As a result, the influence of aerosols on these clouds in the past and future, and the potential impacts of these clouds on global warming remain open questions leading to substantial uncertainty in climate projections. To improve our understanding of these clouds, we need continuous observations of cloud properties on both a global scale and over a long enough timescale for climate studies. At present, satellite-based remote sensing is the only means of providing such observations.

  15. Retrieval of Aerosol Optical Depth Above Clouds from OMI Observations: Sensitivity Analysis, Case Studies

    NASA Technical Reports Server (NTRS)

    Torres, O.; Jethva, H.; Bhartia, P. K.

    2012-01-01

    A large fraction of the atmospheric aerosol load reaching the free troposphere is frequently located above low clouds. Most commonly observed aerosols above clouds are carbonaceous particles generally associated with biomass burning and boreal forest fires, and mineral aerosols originated in arid and semi-arid regions and transported across large distances, often above clouds. Because these aerosols absorb solar radiation, their role in the radiative transfer balance of the earth atmosphere system is especially important. The generally negative (cooling) top of the atmosphere direct effect of absorbing aerosols, may turn into warming when the light-absorbing particles are located above clouds. The actual effect depends on the aerosol load and the single scattering albedo, and on the geometric cloud fraction. In spite of its potential significance, the role of aerosols above clouds is not adequately accounted for in the assessment of aerosol radiative forcing effects due to the lack of measurements. In this paper we discuss the basis of a simple technique that uses near-UV observations to simultaneously derive the optical depth of both the aerosol layer and the underlying cloud for overcast conditions. The two-parameter retrieval method described here makes use of the UV aerosol index and reflectance measurements at 388 nm. A detailed sensitivity analysis indicates that the measured radiances depend mainly on the aerosol absorption exponent and aerosol-cloud separation. The technique was applied to above-cloud aerosol events over the Southern Atlantic Ocean yielding realistic results as indicated by indirect evaluation methods. An error analysis indicates that for typical overcast cloudy conditions and aerosol loads, the aerosol optical depth can be retrieved with an accuracy of approximately 54% whereas the cloud optical depth can be derived within 17% of the true value.

  16. Detection and Retrieval of Multi-Layered Cloud Properties Using Satellite Data

    NASA Technical Reports Server (NTRS)

    Minnis, Patrick; Sun-Mack, Sunny; Chen, Yan; Yi, Helen; Huang, Jian-Ping; Nguyen, Louis; Khaiyer, Mandana M.

    2005-01-01

    Four techniques for detecting multilayered clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. A new technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other methods examined here use atmospheric sounding data (CO2-slicing, CO2), BTD, or microwave data. The CO2 and BTD methods are limited to optically thin cirrus over low clouds, while the MWR methods are limited to ocean areas only. This paper explores the use of the BTD and CO2 methods as applied to Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer EOS (AMSR-E) data taken from the Aqua satellite over ocean surfaces. Cloud properties derived from MODIS data for the Clouds and the Earth's Radiant Energy System (CERES) Project are used to classify cloud phase and optical properties. The preliminary results focus on a MODIS image taken off the Uruguayan coast. The combined MW visible infrared (MVI) method is assumed to be the reference for detecting multilayered ice-over-water clouds. The BTD and CO2 techniques accurately match the MVI classifications in only 51 and 41% of the cases, respectively. Much additional study is need to determine the uncertainties in the MVI method and to analyze many more overlapped cloud scenes.

  17. Computation of the Effects of Inhomogeneous Clouds on Retrieval of Remotely Sensed Properties

    NASA Technical Reports Server (NTRS)

    Chambers, Lin H.

    1998-01-01

    Current and future earth observation programs depend on satellite measurements of radiance to retrieve the properties of clouds on a global basis. At present, this retrieval is made assuming that the clouds in the instrument field of view are plane parallel and independent of adjacent pixels. While this assumption is known to be false except in very limited cases, its impact can be evaluated, and if possible corrected, based on emerging theoretical techniques. In this study, the Spherical Harmonic Discrete Ordinate Method (SHDOM, Evans, 1996) has been used to assess the sensitivity of the retrieval to a variety of cloud parameters. SHDOM allows the plane parallel assumption to be relaxed and makes 2D and even 3D radiative solutions practical. A previous study (Chambers et al., 1996) assessed the effect of horizontal inhomogeneity in 45 LANDSAT scenes of boundary layer clouds over ocean. The four scenes studied here represent overcast, broken, scattered and strongly thermally forced cloud fields and are used to perform sensitivity studies to a wider variety of parameters. Comparisons are made at three solar zenith angles (theta (sub 0) = 0, 49, and 63 degrees) to avoid ambiguity in the results due to solar zenith angle.

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

    NASA Technical Reports Server (NTRS)

    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

  19. The GOME-2 total column ozone product: Retrieval algorithm and ground-based validation

    NASA Astrophysics Data System (ADS)

    Loyola, D. G.; Koukouli, M. E.; Valks, P.; Balis, D. S.; Hao, N.; van Roozendael, M.; Spurr, R. J. D.; Zimmer, W.; Kiemle, S.; Lerot, C.; Lambert, J.-C.

    2011-04-01

    The Global Ozone Monitoring Instrument (GOME-2) was launched on EUMESAT's MetOp-A satellite in October 2006. This paper is concerned with the retrieval algorithm GOME Data Processor (GDP) version 4.4 used by the EUMETSAT Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M-SAF) for the operational generation of GOME-2 total ozone products. GDP 4.4 is the latest version of the GDP 4.0 algorithm, which is employed for the generation of official Level 2 total ozone and other trace gas products from GOME and SCIAMACHY. Here we focus on enhancements introduced in GDP 4.4: improved cloud retrieval algorithms including detection of Sun glint effects, a correction for intracloud ozone, better treatment of snow and ice conditions, accurate radiative transfer modeling for large viewing angles, and elimination of scan angle dependencies inherited from Level 1 radiances. Furthermore, the first global validation results for 3 years (2007-2009) of GOME-2/MetOp-A total ozone measurements using Brewer and Dobson measurements as references are presented. The GOME-2/MetOp-A total ozone data obtained with GDP 4.4 slightly underestimates ground-based ozone by about 0.5% to 1% over the middle latitudes of the Northern Hemisphere and slightly overestimates by around 0.5% over the middle latitudes in the Southern Hemisphere. Over high latitudes in the Northern Hemisphere, GOME-2 total ozone has almost no offset relative to Dobson readings, while over high latitudes in the Southern Hemisphere GOME-2 exhibits a small negative bias below 1%. For tropical latitudes, GOME-2 measures on average lower ozone by 0% to 2% compared to Dobson measurements.

  20. A New Normalized Difference Cloud Retrieval Technique Applied to Landsat Radiances Over the Oklahoma ARM Site

    NASA Technical Reports Server (NTRS)

    Orepoulos, Lazaros; Cahalan, Robert; Marshak, Alexander; Wen, Guoyong

    1999-01-01

    We suggest a new approach to cloud retrieval, using a normalized difference of nadir reflectivities (NDNR) constructed from a non-absorbing and absorbing (with respect to liquid water) wavelength. Using Monte Carlo simulations we show that this quantity has the potential of removing first order scattering effects caused by cloud side illumination and shadowing at oblique Sun angles. Application of the technique to TM (Thematic Mapper) radiance observations from Landsat-5 over the Southern Great Plains site of the ARM (Atmospheric Radiation Measurement) program gives very similar regional statistics and histograms, but significant differences at the pixel level. NDNR can be also combined with the inverse NIPA (Nonlocal Independent Pixel Approximation) of Marshak (1998) which is applied for the first time on overcast Landsat scene subscenes. We demonstrate the sensitivity of the NIPA-retrieved cloud fields on the parameters of the method and discuss practical issues related to the optimal choice of these parameters.

  1. Towards More Consistent Retrievals of Ice Cloud Optical and Microphysical Properties from Polar Orbiting Sensors

    NASA Astrophysics Data System (ADS)

    Baum, B. A.; Heymsfield, A.; Yang, P.

    2011-12-01

    Differences exist in the ice cloud optical thickness and effective particle size products provided by teams working with data from AVHRR (Advanced Very High Resolution Radiometer), MODIS (MODerate resolution Imaging Spectroradiometer), POLDER (Polarization and Directionality of the Earth Reflectance), Imaging Infrared Radiometer (IIR), and CALIOP (Cloud Aerosol LIdar with Orthogonal Polarization). The issue is in large part due to the assumed ice cloud single-scattering properties that each team uses in their retrievals. To gain insight into this problem, we are developing ice cloud single-scattering properties consistently from solar through far-infrared wavelengths by merging ice cloud microphysical data from in situ measurements with the very latest light scattering calculations for ice habits that include droxtals, solid/hollow columns, plates, solid/hollow bullet rosettes, aggregates of columns, and small/large aggregates of plates. The in-situ measurements are from a variety of field campaigns, including ARM-IOP, CRYSTAL-FACE, ACTIVE, SCOUT, MidCiX, pre-AVE, TC-4, and MACPEX. Among other advances, the light scattering calculations include the full phase matrix (i.e., polarization), incorporate a new treatment of forward scattering, and three levels of surface roughness from smooth to severely roughened. This talk will focus on improvements to our methodology for building both spectral and narrowband bulk scattering optical models appropriate for satellite imagers and hyperspectral infrared sensors. The new models provide a basis for investigating retrieval differences in the products from the sensor teams. We will discuss recent work towards improving the consistency of ice cloud microphysical/optical property retrievals between solar, polarimetric, and infrared retrieval approaches. It will be demonstrated that severely roughened ice particles correspond best in comparisons to polarization measurements. Further discussion will provide insight as to the

  2. Cloud cover retrieved from ground-base observation using Skyviewer : A validation with human observations

    NASA Astrophysics Data System (ADS)

    Kim, Bu-Yo; Jee, Joon-Bum; Zo, Il-Sung; Lee, Kyu-Tae

    2016-04-01

    Cloud cover is used in various fields of research in addition to weather forecasts; however, the ground observation of cloud cover is conducted by human observers, a method with low objectivity, temporal and spatial resolutions. Therefore, to address these problems, we have developed an improved algorithm to calculate cloud cover using sky image data obtained with Skyviewer equipment. The algorithm uses a variable threshold of the Red Blue Ratio (RBR) determined from the frequency distributions of the Green Blue Ratio (GBR) to calculate cloud cover more accurately than existing algorithms. To verify the accuracy of the algorithm, we conducted daily, monthly, seasonal and yearly statistical analysis on human observations of cloud cover obtained every hour from 0800 to 1700 LST for the entire year of 2012 at Gangwon Regional Meteorological Administration (GRMA), Korea. A daily case study compared the images of 1200 LST cases by season and pixel images of cloud cover calculated by the algorithm. The selected weekly cases yielded a high correlation of 0.93 with GRMA data. A monthly case study showed low RMSEs and high correlations for December (RMSE=1.64 tenths and r=0.92) and August (RMSE=1.43 tenths and r=0.91). In addition, seasonal cases yielded a high correlation of 0.9 and 87% consistency within ±2 tenths for winter and a correlation of 0.83 and 82% consistency for summer, when cases of cloud-free or overcast conditions are frequent. Annual analysis showed that the bias of GRMA and Skyviewer for the year of 2012 was -0.36 tenth, with cloud cover of the GRMA data being greater, whilst RMSE was 2.12 tenths. Considering the spatial inconsistency of the data used in the analysis, GRMA and Skyviewer showed a high correlation (0.87) and 80% consistency for cases with a difference in cloud cover of within ±2 tenths.

  3. Improved Temperature Sounding and Quality Control Methodology Using AIRS/AMSU Data: The AIRS Science Team Version 5 Retrieval Algorithm

    NASA Technical Reports Server (NTRS)

    Susskind, Joel; Blaisdell, John M.; Iredell, Lena; Keita, Fricky

    2009-01-01

    This paper describes the AIRS Science Team Version 5 retrieval algorithm in terms of its three most significant improvements over the methodology used in the AIRS Science Team Version 4 retrieval algorithm. Improved physics in Version 5 allows for use of AIRS clear column radiances in the entire 4.3 micron CO2 absorption band in the retrieval of temperature profiles T(p) during both day and night. Tropospheric sounding 15 micron CO2 observations are now used primarily in the generation of clear column radiances .R(sub i) for all channels. This new approach allows for the generation of more accurate values of .R(sub i) and T(p) under most cloud conditions. Secondly, Version 5 contains a new methodology to provide accurate case-by-case error estimates for retrieved geophysical parameters and for channel-by-channel clear column radiances. Thresholds of these error estimates are used in a new approach for Quality Control. Finally, Version 5 also contains for the first time an approach to provide AIRS soundings in partially cloudy conditions that does not require use of any microwave data. This new AIRS Only sounding methodology, referred to as AIRS Version 5 AO, was developed as a backup to AIRS Version 5 should the AMSU-A instrument fail. Results are shown comparing the relative performance of the AIRS Version 4, Version 5, and Version 5 AO for the single day, January 25, 2003. The Goddard DISC is now generating and distributing products derived using the AIRS Science Team Version 5 retrieval algorithm. This paper also described the Quality Control flags contained in the DISC AIRS/AMSU retrieval products and their intended use for scientific research purposes.

  4. GCM estimate of the indirect aerosol forcing using satellite-retrieved cloud droplet effective radii

    SciTech Connect

    Boucher, O.

    1995-05-01

    In a recent paper, satellite data radiances were analyzed to retrieve cloud droplet effective radii and significant interhemispheric differences for both maritime and continental clouds were reported. The mean cloud droplet radius in the Northern Hemisphere is smaller than in the Southern Hemisphere by about 0.7 {mu}m. This hemispheric contrast suggests the presence of an aerosol effect on cloud droplet size and is consistent with higher cloud condensation nuclei number concentration in the Northern Hemisphere due to anthropogenic production of aerosol precursors. In the present study, we constrain a climate model with the satellite retrievals and discuss the climate forcing that can be inferred from the observed distribution of cloud droplet radius. Based on two sets of experiments, this sensitivity study suggests that the indirect radiative forcing by anthropogenic aerosols could be about -0.6 or -1 W m{sup -2} averaged in the 0{degrees}-50{degrees}N latitude band. The uncertainty of these estimates is difficult to assess but is at least 50%. 30 refs., 3 figs., 1 tab.

  5. Retrievals of Thick Cloud Optical Depth from the Geoscience Laser Altimeter System (GLAS) by Calibration of Solar Background Signal

    NASA Technical Reports Server (NTRS)

    Yang, Yuekui; Marshak, Alexander; Chiu, J. Christine; Wiscombe, Warren J.; Palm, Stephen P.; Davis, Anthony B.; Spangenberg, Douglas A.; Nguyen, Louis; Spinhirne, James D.; Minnis, Patrick

    2008-01-01

    Laser beams emitted from the Geoscience Laser Altimeter System (GLAS), as well as other space-borne laser instruments, can only penetrate clouds to a limit of a few optical depths. As a result, only optical depths of thinner clouds (< about 3 for GLAS) are retrieved from the reflected lidar signal. This paper presents a comprehensive study of possible retrievals of optical depth of thick clouds using solar background light and treating GLAS as a solar radiometer. To do so we first calibrate the reflected solar radiation received by the photon-counting detectors of GLAS' 532 nm channel, which is the primary channel for atmospheric products. The solar background radiation is regarded as a noise to be subtracted in the retrieval process of the lidar products. However, once calibrated, it becomes a signal that can be used in studying the properties of optically thick clouds. In this paper, three calibration methods are presented: (I) calibration with coincident airborne and GLAS observations; (2) calibration with coincident Geostationary Operational Environmental Satellite (GOES) and GLAS observations of deep convective clouds; (3) calibration from the first principles using optical depth of thin water clouds over ocean retrieved by GLAS active remote sensing. Results from the three methods agree well with each other. Cloud optical depth (COD) is retrieved from the calibrated solar background signal using a one-channel retrieval. Comparison with COD retrieved from GOES during GLAS overpasses shows that the average difference between the two retrievals is 24%. As an example, the COD values retrieved from GLAS solar background are illustrated for a marine stratocumulus cloud field that is too thick to be penetrated by the GLAS laser. Based on this study, optical depths for thick clouds will be provided as a supplementary product to the existing operational GLAS cloud products in future GLAS data releases.

  6. Linear Contrail Coverage and Cloud Property Retrievals from 2012 MODIS Imagery over the Northern Hemisphere

    NASA Astrophysics Data System (ADS)

    Duda, D. P.; Minnis, P.; Chee, T.; Khlopenkov, K. V.; Bedka, S. T.

    2015-12-01

    Observation of linear contrail cirrus coverage and retrieval of their optical properties are valuable data for validating atmospheric climate models that represent contrail formation explicitly. These data can reduce our uncertainty of the regional effects of contrail-generated cirrus on global radiative forcing, and thus improve our estimation of the impact of aviation on climate change. We continue our work to create a multi-year climatology of the physical properties of linear contrails from multi-spectral satellite observations. We use an automated contrail detection algorithm (CDA) to determine the coverage of linear persistent contrails over the Northern Hemisphere during 2012. The contrail detection algorithm is a modified form of the Mannstein et al. (1999) method, and uses several channels from thermal infrared MODIS data to reduce the occurrence of false positive detections. Global aircraft emissions waypoint data provided by FAA allow comparison of detected contrails with commercial aircraft flight tracks. A pixel-level product based on the advected flight tracks defined by the waypoint data and U-V wind component profiles from the NASA GMAO MERRA reanalyses has been developed to assign a confidence of contrail detection for the contrail mask. To account for possible contrail cirrus missed by the CDA, a post-processing method based on the assumption that pixels adjacent to detected linear contrails will have radiative signatures similar to those of the detected contrails is applied to the Northern Hemisphere data. Results from MODIS measurements during 2012 will be presented, representing a near-global climatology of contrail coverage. Linear contrail coverage will be compared with coverage estimates determined previously from 2006 MODIS data and with maps of potential persistent contrail formation derived from MERRA reanalysis data for both 2006 and 2012. In addition, contrail physical properties such as optical depth and particle size derived from the

  7. Polarization Lidar Liquid Cloud Detection Algorithm for Winter Mountain Storms

    NASA Technical Reports Server (NTRS)

    Sassen, Kenneth; Zhao, Hongjie

    1992-01-01

    We have collected an extensive polarization lidar dataset from elevated sites in the Tushar Mountains of Utah in support of winter storm cloud seeding research and experiments. Our truck-mounted ruby lidar collected zenith, dual-polarization lidar data through a roof window equipped with a wiper system to prevent snowfall accumulation. Lidar returns were collected at a rate of one shot every 1 to 5 min during declared storm periods over the 1985 and 1987 mid-Jan. to mid-Mar. Field seasons. The mid-barrier remote sensor field site was located at 2.57 km MSL. Of chief interest to weather modification efforts are the heights of supercooled liquid water (SLW) clouds, which must be known to assess their 'seedability' (i.e., temperature and height suitability for artificially increasing snowfall). We are currently re-examining out entire dataset to determine the climatological properties of SLW clouds in winter storms using an autonomous computer algorithm.

  8. Forest Height Retrieval Algorithm Using a Complex Visibility Function Approach

    NASA Astrophysics Data System (ADS)

    Chu, T.; Zebker, H. A.

    2011-12-01

    Vegetation structure and biomass on earth's terrestrial surface are critical parameters that influences global carbon cycle, habitat, climate, and resources of economic value. Space-borne and air-borne remote sensing instruments are the most practical means of obtaining information such as tree height and biomass on a large scale. SAR (Synthetic aperture radars) especially InSAR (Interferometric SAR) has been utilized in the recent years to quantify vegetation parameters such as height and biomass. However methods used to quantify global vegetation has yet to produce accurate results. It is the goal of this study to develop a signal-processing algorithm through simulation to determine vegetation heights that would lead to accurate height and biomass retrievals. A standard SAR image represents a projection of the 3D distributed backscatter onto a 2D plane. InSAR is capable of determining topography or the height of vegetation. Vegetation height is determined from the mean scattering phase center of all scatterers within a resolution cell. InSAR is capable of generating a 3D height surface, but the distribution of scatters in height is under-determined and cannot be resolved by a single-baseline measurement. One interferogram therefore is insufficient to uniquely determine vertical characteristics of even a simple 3D forest. An aperture synthesis technique in the height or vertical dimension would enable improved resolution capability to distinguish scatterers of different location in the vertical dimension. Repeat pass observations allow us differential interferometry to populate the frequency domain from which we can use the Fourier transform relation to get to the brightness or backscatter domain. Ryle and Hewish first introduced this technique of aperture synthesis in the 1960's for large radio telescope arrays. This technique would allow us to focus the antenna beam pattern in the vertical direction and increase vertical resolving power. It enable us to

  9. Properties of marine stratocumulus obtained with partly cloudy pixel retrievals and found in the MODIS MOD06 cloud product

    NASA Astrophysics Data System (ADS)

    Boeke, Robyn C.; Allan, Andrea M.; Coakley, James A.

    2016-06-01

    Partly cloudy pixel retrievals (PCPRs) of cloud properties for marine stratocumulus were compared with those of the 1 km Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product (MOD06). In addition, the fractional cloud cover obtained from the PCPRs applied to 1 km MODIS radiances was compared with that derived from the 250 m cloud mask (MOD35). The comparisons were made for pixels that were overcast and pixels that were only partially covered by clouds. Accounting for failed retrievals in both the MOD06 cloud properties and those obtained with the PCPRs leads to the suggestion that regional cloud cover be estimated in terms of lower and upper limits. The average could serve as the best estimate of the cloud cover, and the difference between the average and an extreme could serve as the uncertainty. The comparisons reveal that the overcast assumption used in the MODIS cloud property retrievals leads to cloud cover, droplet effective radii, and cloud top temperatures that are overestimated and, shortwave optical depths, liquid water paths that are underestimated. These biases persist when the properties are averaged to form spatial and temporal means. Owing to significant horizontal variations of cloud liquid water within the 1 km MODIS pixels, visible optical depths, droplet effective radii, and liquid water paths derived from the PCPRs show similar biases. The trends of the biases with pixel-scale and regional-scale cloud cover suggest that estimates of the aerosol indirect radiative forcing derived from satellites have been overestimated.

  10. Retrieval of Aerosol Optical Depth in Vicinity of Broken Clouds from Reflectance Ratios: A Novel Approach

    SciTech Connect

    Kassianov, Evgueni I.; Ovtchinnikov, Mikhail; Berg, Larry K.; McFarlane, Sally A.; Flynn, Connor J.

    2008-10-13

    A novel method for the retrieval of aerosol optical depth (AOD) under partly cloudy conditions has been suggested. The method exploits reflectance ratios, which are not sensitive to the three-dimensional (3D) effects of clouds. As a result, the new method provides an effective way to avoid the 3D cloud effects, which otherwise would have a large (up to 140%) contaminating impact on the aerosol retrievals. The 1D version of the radiative transfer model has been used to develop look-up tables (LUTs) of reflectance ratios as functions of two parameters describing the spectral dependence of AOD (a power law). The new method implements an innovative 2D inversion for simultaneous retrieval of these two parameters and, thus, the spectral behavior of AOD. The performance of the new method has been illustrated with a model-output inverse problem. We demonstrated that a new retrieval has the potential for (i) detection of clear pixels outside of cloud shadows and (ii) accurate (~15%) estimation of AOD for the majority of them.

  11. Retrieving the Convective Thermals and Updraft Speeds at Cloud Base from VIIRS

    NASA Astrophysics Data System (ADS)

    Zheng, Y.; Rosenfeld, D.; Li, Z.

    2015-12-01

    Updraft speeds of thermals have always been difficult to measure, despite significant roles they play in transporting pollutants and in cloud formation and precipitation. To our knowledge, no attempt to date has been made to estimate updraft speed from satellite information in the boundary layer and at the cloud base. In this study, we introduce two methods of retrieving the maximum updraft (Wmax) and updraft at cloud base (Wb) in the planetary boundary layer topped by convective clouds. The first method uses ground-air temperature difference to characterize the surface sensible heat flux, which is found to be correlated with updraft speeds measured by the Doppler lidar over the Southern Great Plains (SGP). Based on the relationship, we use the satellite-retrieved surface skin temperature and reanalysis surface air temperature to estimate the updrafts. The second method is based on a good linear correlation between cloud base height and updrafts, which was found over the SGP, the central Amazon, and on board a ship sailing between Honolulu and Los Angeles. We found a universal relationship for both land and ocean. The performance of these two methods of retrieving updrafts was tested against the lidar and Radar measurements with good agreements found for both methods. Compared with the first method that only works over land, the second method expands its applicability to ocean and is more accurate in retrieving Wmax the with RMSE (root-mean-square error) = 0.38 m/s and MAPE (mean-absolute-percentage-error) = 19%, and Wb with RMSE = 0.34 m/s and MAPE = 21%.

  12. Retrieval of cloud fraction and height anomalies and their trend from temporally and spatially averaged infrared spectra observed from space

    NASA Astrophysics Data System (ADS)

    Kato, S.; Rose, F. G.; Liu, X.; Wielicki, B. A.; Mlynczak, M. G.

    2013-12-01

    Understanding how clouds and atmospheric properties change with time under radiative forcing is necessary to understand feedback. Generally, global clouds and atmospheric Understanding how clouds and atmospheric properties change with time under radiative forcing is necessary to understand feedback. Generally, global clouds and atmospheric properties are retrieved from satellite-based instruments. Subsequently, retrieved values from an instrument's field-of-view are averaged and the time rate of change of cloud or atmospheric properties can be inferred from averaged properties. This is simple in concept but identifying artifacts of the retrieval is difficult in practice. An alternative way to derive a trend of cloud and atmospheric properties is tying their property change directly to the observed radiance change. This average-then-retrieve approach directly utilizes instrument stability but requires separating cloud and atmospheric property changes contributing to the highly spatially and temporally averaged observed radiance change. In this presentation, we demonstrate the average-then-retrieve approach by simulating the retrieval of cloud fraction and height anomalies from highly averaged longwave spectra. We use 28 years of reanalysis (Modern Era Retrospective-Analysis for Research MERRA) for the simulation and retrieve annual 10° zonal cloud fraction and height anomalies, as well as temperature and water vapor amount anomalies. The error in retrieved anomalies is estimated based on the method discussed in Kato et al. (2011). The uncertainty in the trend estimated from retrieved anomalies is also discussed. Reference Kato, S., B. A. Wielicki, F. G. Rose, X. Liu, P. C. Taylor, D. P. Kratz, M. G. Mlynczak, D. F. Young, N. Phojanamongkolkij, S. Sun-Mack, W. F. Miller, Y. Chen, 2011b, Detection of atmospheric changes in spatially and temporally averaged infrared spectra observed from space, J Climate, 24, 6392-6407, Doi: 10.1175/JCLI-D-10-05005.1.

  13. Are remote-sensing retrieved aerosol radiative properties a suitable proxy for cloud condensation nuclei?

    NASA Astrophysics Data System (ADS)

    Stier, Philip

    2014-05-01

    Aerosol-cloud interactions arguably remain the single greatest uncertainty among anthropogenic perturbations of the climate system. The large uncertainties associated with their representation in global aerosol climate models have emphasised the need for observational studies. In-situ measurements provide a detailed description of aerosol and cloud microphysical properties, providing strong observational constraints on aerosol cloud interactions. However, their spatio-temporal sampling is sparse so that "observational" estimates of global aerosol cloud interactions generally rely on co-located satellite retrievals of aerosol radiative properties and cloud properties. In this study I will critically evaluate the suitability of remote-sensing retrieved aerosol radiative properties, such as aerosol optical depth (AOD), aerosol index (AI) and aerosol fine mode optical depth, as proxy for cloud condensation nuclei (CCN). This analysis based on the fully self-consistent calculation of aerosol radiative properties and CCN in the aerosol climate model ECHAM-HAM. Correlating simulated aerosol radiative properties with CCN at a range of supersaturations (sampling different sizes/composition of the aerosol spectrum) highlights limitations in the suitability of AOD and AI as proxy for CCN. These discrepancies arise from a range of factors, including the limited representativeness of column-integrated aerosol radiative properties for surface or cloud-base CCN as well as the effects of humidity growth of aerosols, affecting AOD/AI but not CCN. Simulated correlations show a strong regional variability, with significant implications for "observational" estimates of aerosol cloud interactions from remote-sensing as well as in-situ data.

  14. Simultaneous Retrievals of Polar Mesospheric Clouds (PMCs) with Ozone from OMI UV measurements

    NASA Astrophysics Data System (ADS)

    Bak, J.; Liu, X.; Kim, J. H.; Deland, M. T.; Chance, K.

    2015-09-01

    The presence of polar mesospheric clouds (PMCs) at high latitudes could affect the retrieval of ozone profiles using backscattered ultraviolet (BUV) measurements. PMC-induced errors in ozone profile retrievals from Ozone Monitoring Instrument (OMI) BUV measurements are investigated through comparisons with Microwave Limb Sounder (MLS) ozone measurements. This comparison demonstrates that the presence of PMCs leads to systematic biases at altitudes above 6 hPa in summer high latitudes; the biases increase from ~ -2 % at 2 hPa to ~ -20 % at 0.5 hPa on average, and are significantly correlated with brightness of PMCs. Sensitivity studies show that the radiance sensitivity to PMCs strongly depends on wavelengths, increasing by a factor of ~ 4 from 300 to 265 nm. It also strongly depends on the PMC scattering, thus depending on viewing geometry. The optimal estimation-based retrieval sensitivity analysis shows that PMCs located at 80-85 km have the greatest effect on ozone retrievals at ~ 0.2 hPa (~ 60 km), where the retrieval errors range from -2.5 % with PMC optical depth (POD) of 10-4 to -20 % with 10-3 at back scattering angles, and the impacts increase by a factor of ~ 5 at forward scattering angles due to stronger PMC sensitivities. To reduce the interference of PMCs on ozone retrievals, we perform simultaneous retrievals of POD and ozone with a loose constraint of 10-3 for POD, which results in retrieval errors of 1-4 × 10-4. It is demonstrated that the negative bias of OMI ozone retrievals relative to MLS could be improved by including the PMC in the forward model calculation and retrieval.

  15. Retrieval of atmospheric properties from hyper and multispectral imagery with the FLAASH atmospheric correction algorithm

    NASA Astrophysics Data System (ADS)

    Perkins, Timothy; Adler-Golden, Steven; Matthew, Michael; Berk, Alexander; Anderson, Gail; Gardner, James; Felde, Gerald

    2005-10-01

    Atmospheric Correction Algorithms (ACAs) are used in applications of remotely sensed Hyperspectral and Multispectral Imagery (HSI/MSI) to correct for atmospheric effects on measurements acquired by air and space-borne systems. The Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) algorithm is a forward-model based ACA created for HSI and MSI instruments which operate in the visible through shortwave infrared (Vis-SWIR) spectral regime. Designed as a general-purpose, physics-based code for inverting at-sensor radiance measurements into surface reflectance, FLAASH provides a collection of spectral analysis and atmospheric retrieval methods including: a per-pixel vertical water vapor column estimate, determination of aerosol optical depth, estimation of scattering for compensation of adjacency effects, detection/characterization of clouds, and smoothing of spectral structure resulting from an imperfect atmospheric correction. To further improve the accuracy of the atmospheric correction process, FLAASH will also detect and compensate for sensor-introduced artifacts such as optical smile and wavelength mis-calibration. FLAASH relies on the MODTRANTM radiative transfer (RT) code as the physical basis behind its mathematical formulation, and has been developed in parallel with upgrades to MODTRAN in order to take advantage of the latest improvements in speed and accuracy. For example, the rapid, high fidelity multiple scattering (MS) option available in MODTRAN4 can greatly improve the accuracy of atmospheric retrievals over the 2-stream approximation. In this paper, advanced features available in FLAASH are described, including the principles and methods used to derive atmospheric parameters from HSI and MSI data. Results are presented from processing of Hyperion, AVIRIS, and LANDSAT data.

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

    NASA Astrophysics Data System (ADS)

    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

  17. Simulations of Infrared Radiances Over a Deep Convective Cloud System Observed During TC4- Potential for Enhancing Nocturnal Ice Cloud Retrievals

    NASA Technical Reports Server (NTRS)

    Minnis, Patrick; Hong, Gang; Ayers, Jeffrey Kirk; Smith, William L.; Yost, Christopher R.; Heymsfield, Andrew J.; Heymsfield, Gerald M.; Hlavka, Dennis L.; King, Michael D.; Korn, Errol M.; Mcgill, Matthew J.; Selkirk, Henry B.; Thompson, Anne M.; Tian, Lin; Yang, Ping

    2012-01-01

    Retrievals of ice cloud properties using infrared measurements at 3.7, 6.7, 7.3, 8.5, 10.8, and 12.0 microns can provide consistent results regardless of solar illumination, but are limited to cloud optical thicknesses tau < approx.6. This paper investigates the variations in radiances at these wavelengths over a deep convective cloud system for their potential to extend retrievals of tau and ice particle size D(sub e) to optically thick clouds. Measurements from the Moderate Resolution Imaging Spectroradiometer Airborne Simulator--ASTER, the Scanning High-resolution Interferometer Sounder, the Cloud Physics Lidar (CPL), and the Cloud Radar System (CRS) aboard the NASA ER-2 aircraft during the NASA TC4 (Tropical Composition, Cloud and Climate Coupling) experiment flight during 5 August 2007, are used to examine the retrieval capabilities of infrared radiances over optically thick ice clouds. Simulations based on coincident in-situ measurements and combined cloud tau from CRS and CPL measurements are comparable to the observations. They reveal that brightness temperatures at these bands and their differences (BTD) are sensitive to tau up to approx.20 and that for ice clouds having tau > 20, the 3.7 - 10.8 microns and 3.7 - 6.7 microns BTDs are the most sensitive to D(sub e). Satellite imagery appears consistent with these results. Keywords: clouds; optical depth; particle size; satellite; TC4; multispectral thermal infrared

  18. Simulations of Infrared Radiances Over a Deep Convective Cloud System Observed During TC4: Potential for Enhancing Nocturnal Ice Cloud Retrievals

    NASA Technical Reports Server (NTRS)

    Minnis, Patrick; Hong, Gang; Ayers, Kirk; Smith, William L., Jr.; Yost, Christopher R.; Heymsfield, Andrew J.; Heymsfield, Gerald M.; Hlavka, Dennis L.; King, Michael D.; Korn, Errol; McGill, Matthew; Selkirk, Henry B.; Thompson, Anne M.; Tian, Lin; Yang, Ping

    2012-01-01

    Retrievals of ice cloud properties using infrared measurements at 3.7, 6.7, 7.3, 8.5, 10.8, and 12.0 microns can provide consistent results regardless of solar illumination, but are limited to cloud optical thicknesses tau < approx.6. This paper investigates the variations in radiances at these wavelengths over a deep convective cloud system for their potential to extend retrievals of tau and ice particle size D(sub e) to optically thick clouds. Measurements from the Moderate Resolution Imaging Spectroradiometer Airborne Simulator--ASTER, the Scanning High-resolution Interferometer Sounder, the Cloud Physics Lidar (CPL), and the Cloud Radar System (CRS) aboard the NASA ER-2 aircraft during the NASA TC4 (Tropical Composition, Cloud and Climate Coupling) experiment flight during 5 August 2007, are used to examine the retrieval capabilities of infrared radiances over optically thick ice clouds. Simulations based on coincident in-situ measurements and combined cloud tau from CRS and CPL measurements are comparable to the observations. They reveal that brightness temperatures at these bands and their differences (BTD) are sensitive to tau up to approx.20 and that for ice clouds having tau > 20, the 3.7 - 10.8 microns and 3.7 - 6.7 microns BTDs are the most sensitive to D(sub e). Satellite imagery appears consistent with these results. Keywords: clouds; optical depth; particle size; satellite; TC4; multispectral thermal infrared

  19. Comparison of CALIPSO-Like, LaRC, and MODIS Retrievals of Ice Cloud Properties over SIRTA in France and Florida during CRYSTAL-FACE

    NASA Technical Reports Server (NTRS)

    Chiriaco, M.; Chepfer, H.; Haeffelin, M.; Minnis, P.; Noel, V.; Platnick, S.; McGill, M.; Baumgardner, D.; Dubuisson, P.; Pelon, J.; Spangenberg, D.; Sun-Mack, S.; Wind, G.

    2007-01-01

    This study compares cirrus particle effective radius retrieved by a CALIPSO-like method with two similar methods using MODIS, MODI Airborne Simulator (MAS), and GOES imagery. The CALIPSO-like method uses lidar measurements coupled with the split-window technique that uses the infrared spectral information contained at the 8.65-micrometer, 11.15-micrometer and 12.05-micrometer bands to infer the microphysical properties of cirrus clouds. The two other methods, sing passive remote sensing at visible and infrared wavelengths, are the operational MODIS cloud products (referred to by its archival product identifier MOD06 for MODIS Terra) and MODIS retrievals performed by the CERES team at LaRC (Langley Research Center) in support of CERES algorithms; the two algorithms will be referred to as MOD06- and LaRC-method, respectively. The three techniques are compared at two different latitudes: (i) the mid-latitude ice clouds study uses 18 days of observations at the Palaiseau ground-based site in France (SIRTA: Site Instrumental de Recherche par Teledetection Atmospherique) including a ground-based 532 nm lidar and the Moderate Resolution Imaging Spectrometer (MODIS) overpasses on the Terra Platform, (ii) the tropical ice clouds study uses 14 different flight legs of observations collected in Florida, during the intensive field experiment CRYSTAL-FACE (Cirrus Regional Study of Tropical Anvils and cirrus Layers-Florida Area Cirrus Experiment), including the airborne Cloud Physics Lidar (CPL) and the MAS. The comparison of the three methods gives consistent results for the particle effective radius and the optical thickness, but discrepancies in cloud detection and altitudes. The study confirms the value of an active remote-sensing method (CALIPSO-like) for the study of sub-visible ice clouds, in both mid-latitudes and tropics. Nevertheless, this method is not reliable in optically very thick tropical ice clouds.

  20. The OMPS Limb Profiler Instrument: An Alternative Data Analysis and Retrieval Algorithm

    NASA Technical Reports Server (NTRS)

    Rault, Didier F.; Lumpe, Jerry; Eden, Thomas

    2009-01-01

    The upcoming Ozone Mapper and Profiler Suite (OMPS), which will be launched on the NPOESS Preparatory Project (NPP) platform in early 2011, will continue monitoring the global distribution of the Earth's middle atmosphere ozone and aerosol. OMPS is composed of three instruments, namely the Total Column Mapper (heritage: TOMS, OMI), the Nadir Profiler (heritage: SBUV) and the Limb Profiler (heritage: SOLSE/LORE, OSIRIS, SCIAMACHY, SAGE III). The ultimate goal of the mission is to better understand and quantify the rate of stratospheric ozone recovery. The focus of the paper will be on the Limb Profiler (LP) instrument. The LP instrument will measure the Earth fs limb radiance (which is due to the scattering of solar photons by air molecules, aerosol and Earth surface) in the ultra-violet (UV), visible and near infrared, from 285 to 1000 nm. The LP simultaneously images the whole vertical extent of the Earth's limb through three vertical slits, each covering a vertical tangent height range of 100 km and each horizontally spaced by 250 km in the cross-track direction. The focal plane of the LP spectrometer is a two ]dimensional CCD array comprised of 340 x 740 pixels. Several data analysis tools are presently being constructed and tested to retrieve ozone and aerosol vertical distribution from limb radiance measurements. The primary NASA algorithm is based on earlier algorithms developed for the SOLSE/LORE and SAGE III limb scatter missions. The paper will describe an alternative algorithm which will retrieve ozone density and aerosol extinction directly from radiance data collected on individual CCD pixels. This alternative method uses an optimal estimation approach to retrieve ozone and aerosol in the 10-60 km range from the information contained within an ensemble of about 50000 down-linked pixels. Tangent height registration is performed using the Rayleigh Scattering Attitude Sensor (RSAS) technique applied to columns of pixels in the 340-360 nm range. Cloud

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

    ERIC Educational Resources Information Center

    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…

  2. A Survey of Stemming Algorithms in Information Retrieval

    ERIC Educational Resources Information Center

    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…

  3. Multilevel cloud retrieval using multispectral HIRS and AVHRR data: Nighttime oceanic analysis

    NASA Technical Reports Server (NTRS)

    Baum, Bryan A.; Arduini, Robert F.; Wielicki, Bruce A.; Minnis, Patrick; Tsay, Si-Chee

    1994-01-01

    A multispectral, multiresolution (MSMR) method is developed for analyzing scenes of overlapping cloud layers. The MSMR method is applied to data from the NOAA 11 advanced very high resolution radiometer (AVHRR) and the high-resolution infrared radiometer sounder (HIRS-2). The data are from a nighttime oceanic scene in which a semitransparent cirrus veil overlays a large-scale stratus cloud. Low-cloud and clear-sky radiances are determined using a spatial coherence technique. Middle to upper level cloud pressures and radiances are estimated from HIRS-2 15 micrometer CO2 band radiometric data. The MSMR method improves the interpretation of a nighttime, oceanic scene containing thin cirrus over a large-scale stratiform cloud. If, for example, the same scene is analyzed using only the AVHRR 10.8 micrometer channel, the accompanying retrieved cloud heights are found to be between the cirrus and stratus cloud heights and are incorrectly identified as midlevel altostratus clouds. Theoretical radiative transfer model results for both water droplet spheres and randomly oriented hexagonal ice crystals are compared to observed AVHRR brightness temperature differences (BTD) between the 3.7- and 10.8 micrometer channels (BTD(sup 34)) and between the 10.8- and 12- micrometer channels (BTD(sup 45)) to distinguish among the effects of cloud optical depth, particle size, and phase for both single-layer clouds and overlapping two-layer clouds. Theoretical BTD calculations are used to estimate the range of effective particle sizes for eac h cloud layer. The data for the cirrus in the case study region near Bermuda are consistent with theoretical results for relatively small randomly oriented hexagonal ice crystals. The observed BTD(sup 34) and BTD(sup 45) values are lower for the cirrus above a lower-level cloud than for single-level cirrus with no underlying cloud. In certain cases the BTD analysis provides a way to distinguish between clouds composed of supercooled water droplets

  4. Evaluation of gridded Scanning ARM Cloud Radar reflectivity observations and vertical Doppler velocity retrievals

    NASA Astrophysics Data System (ADS)

    Lamer, K.; Tatarevic, A.; Jo, I.; Kollias, P.

    2013-11-01

    The Scanning ARM Cloud Radars (SACR's) provide continuous atmospheric observations aspiring to capture the 3-D cloud-scale structure. Sampling clouds in 3-D is challenging due to their temporal-spatial scales, the need to sample the sky at high elevations and cloud radar limitations. Thus, a common scan strategy is to repetitively slice the atmosphere from horizon to horizon as clouds advect over the radar (Cross-Wind Range Height Indicator - CWRHI). Here, the processing and gridding of the SACR CW-RHI scans are presented. First, the SACR sample observations from the ARM Oklahoma (SGP) and Cape-Cod (PVC) sites are post-processed (detection mask, velocity de-aliasing and gaseous attenuation correction). The resulting radial Doppler moment fields are then mapped to Cartesian coordinates with time as one of the dimension. The Cartesian-gridded Doppler velocity fields are next decomposed into the horizontal wind velocity contribution and the vertical Doppler velocity component. For validation purposes, all gridded and retrieved fields are compared to collocated zenith pointing ARM cloud radar measurements. We consider that the SACR sensitivity loss with range, the cloud type observed and the research purpose should be considered in determining the gridded domain size. Our results also demonstrate that the gridded SACR observations resolve the main features of low and high stratiform clouds. It is established that the CW-RHI observations complemented with processing techniques could lead to robust 3-D clouds dynamical representations up to 25-30° off zenith. The proposed gridded products are expected to advance our understanding of 3-D cloud morphology, dynamics, anisotropy and lead to more realistic 3-D radiative transfer calculations.

  5. Evaluation of gridded scanning ARM cloud radar reflectivity observations and vertical doppler velocity retrievals

    NASA Astrophysics Data System (ADS)

    Lamer, K.; Tatarevic, A.; Jo, I.; Kollias, P.

    2014-04-01

    The scanning Atmospheric Radiation Measurement (ARM) cloud radars (SACRs) provide continuous atmospheric observations aspiring to capture the 3-D cloud-scale structure. Sampling clouds in 3-D is challenging due to their temporal-spatial scales, the need to sample the sky at high elevations and cloud radar limitations. Thus, a suggested scan strategy is to repetitively slice the atmosphere from horizon to horizon as clouds advect over the radar (Cross-Wind Range-Height Indicator - CW-RHI). Here, the processing and gridding of the SACR CW-RHI scans are presented. First, the SACR sample observations from the ARM Southern Great Plains and Cape Cod sites are post-processed (detection mask, gaseous attenuation correction, insect filtering and velocity de-aliasing). The resulting radial Doppler moment fields are then mapped to Cartesian coordinates with time as one of the dimensions. Next the Cartesian-gridded Doppler velocity fields are decomposed into the horizontal wind velocity contribution and the vertical Doppler velocity component. For validation purposes, all gridded and retrieved fields are compared to collocated zenith-pointing ARM cloud radar measurements. We consider that the SACR sensitivity loss with range, the cloud type observed and the research purpose should be considered in determining the gridded domain size. Our results also demonstrate that the gridded SACR observations resolve the main features of low and high stratiform clouds. It is established that the CW-RHI observations complemented with processing techniques could lead to robust 3-D cloud dynamical representations up to 25-30 degrees off zenith. The proposed gridded products are expected to advance our understanding of 3-D cloud morphology, dynamics and anisotropy and lead to more realistic 3-D radiative transfer calculations.

  6. The role of cloud contamination, aerosol layer height and aerosol model in the assessment of the OMI near-UV retrievals over the ocean

    NASA Astrophysics Data System (ADS)

    Gassó, Santiago; Torres, Omar

    2016-07-01

    Retrievals of aerosol optical depth (AOD) at 388 nm over the ocean from the Ozone Monitoring Instrument (OMI) two-channel near-UV algorithm (OMAERUV) have been compared with independent AOD measurements. The analysis was carried out over the open ocean (OMI and MODerate-resolution Imaging Spectrometer (MODIS) AOD comparisons) and over coastal and island sites (OMI and AERONET, the AErosol RObotic NETwork). Additionally, a research version of the retrieval algorithm (using MODIS and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) information as constraints) was utilized to evaluate the sensitivity of the retrieval to different assumed aerosol properties. Overall, the comparison resulted in differences (OMI minus independent measurements) within the expected levels of uncertainty for the OMI AOD retrievals (0.1 for AOD < 0.3, 30 % for AOD > 0.3). Using examples from case studies with outliers, the reasons that led to the observed differences were examined with specific purpose to determine whether they are related to instrument limitations (i.e., pixel size, calibration) or algorithm assumptions (such as aerosol shape, aerosol height). The analysis confirms that OMAERUV does an adequate job at rejecting cloudy scenes within the instrument's capabilities. There is a residual cloud contamination in OMI pixels with quality flag 0 (the best conditions for aerosol retrieval according to the algorithm), resulting in a bias towards high AODs in OMAERUV. This bias is more pronounced at low concentrations of absorbing aerosols (AOD 388 nm ˜ < 0.5). For higher aerosol loadings, the bias remains within OMI's AOD uncertainties. In pixels where OMAERUV assigned a dust aerosol model, a fraction of them (< 20 %) had retrieved AODs significantly lower than AERONET and MODIS AODs. In a case study, a detailed examination of the aerosol height from CALIOP and the AODs from MODIS, along with sensitivity tests, was carried out by varying the different assumed parameters in the

  7. Cloud Screening and Quality Control Algorithm for Star Photometer Data: Assessment with Lidar Measurements and with All-sky Images

    NASA Technical Reports Server (NTRS)

    Ramirez, Daniel Perez; Lyamani, H.; Olmo, F. J.; Whiteman, D. N.; Navas-Guzman, F.; Alados-Arboledas, L.

    2012-01-01

    This paper presents the development and set up of a cloud screening and data quality control algorithm for a star photometer based on CCD camera as detector. These algorithms are necessary for passive remote sensing techniques to retrieve the columnar aerosol optical depth, delta Ae(lambda), and precipitable water vapor content, W, at nighttime. This cloud screening procedure consists of calculating moving averages of delta Ae() and W under different time-windows combined with a procedure for detecting outliers. Additionally, to avoid undesirable Ae(lambda) and W fluctuations caused by the atmospheric turbulence, the data are averaged on 30 min. The algorithm is applied to the star photometer deployed in the city of Granada (37.16 N, 3.60 W, 680 ma.s.l.; South-East of Spain) for the measurements acquired between March 2007 and September 2009. The algorithm is evaluated with correlative measurements registered by a lidar system and also with all-sky images obtained at the sunset and sunrise of the previous and following days. Promising results are obtained detecting cloud-affected data. Additionally, the cloud screening algorithm has been evaluated under different aerosol conditions including Saharan dust intrusion, biomass burning and pollution events.

  8. Towards a new aerosol climatology to improve the SPECMAGIC algorithm to retrieve surface solar irradiation from MVIRI and SEVIRI

    NASA Astrophysics Data System (ADS)

    Träger-Chatterjee, Christine; Müller, Richard W.; Trentmann, Jörg

    2015-04-01

    The Satellite Application Facility on Climate Monitoring (CM SAF) provides long-term climate datasets of surface solar radiation for more than 30 years retrieved from MVIRI and SEVIRI instruments on board the METEOSAT first and second generation satellites, respectively. The surface solar radiation is retrieved using the SPECMAGIC algorithm. The SPECMAGIC method is composed of the Heliosat approach to calculate the cloud transmission and a clear sky model. The Heliosat approach as well as the SPECMAGIC method will be described in the presentation "The SPECMAGIC algorithm for the retrieval of spectrally resolved surface radiation, overview and applications" by R. Müller in this session. The clear sky model SPECMAGIC consists of look-up tables calculated with the radiative transfer model libradtran for the consideration of aerosol as well as water vapour and ozone. The effect of four different state of the art aerosol data sources on the accuracy of surface solar radiation derived with SPECMAGIC is evaluated. The respective results are compared with calculations assuming constant aerosol (0.15) and zero optical depth. The SPECMAGIC calculations using the different aerosol information are compared to measurements of stations of the Baseline Surface Radiation Network (BSRN). The results indicate that in regions with a low frequency of clouds and enhanced variability of aerosol optical depth the climatologies investigated lead to large underestimations of the surface solar radiation, indicating that high aerosol optical depth provided by these climatologies are overestimated. As a consequence the best performing aerosol climatology investigated is modified in such a way very high AODs are cut down, which leads to promising results in the surface solar radiation retrieval.

  9. The Effects of an Absorbing Smoke Layer on MODIS Marine Boundary Layer Cloud Optical Property Retrievals and Radiative Forcing

    NASA Technical Reports Server (NTRS)

    Meyer, Kerry; Platnick, Steven

    2012-01-01

    Clouds, aerosols, and their interactions are widely considered to be key uncertainty components in our current understanding of the Earth's atmosphere and radiation budget. The work presented here is focused on the quasi-permanent marine boundary layer . (MBL) clouds off the southern Atlantic coast of Africa and the effects on MODIS cloud optical property retrievals (MOD06) of an overlying absorbing smoke layer. During much of August and September, a persistent smoke layer resides over this region, produced from extensive biomass burning throughout the southern African savanna. The resulting absorption, which increases with decreasing wavelength, potentially introduces biases into the MODIS cloud optical property retrievals of the underlying MBL clouds. This effect is more pronounced in the cloud optical thickness retrievals, which over ocean are derived from the wavelength channel centered near 0.86 micron (effective particle size retrievals are derived from the longer-wavelength near-IR channels at 1.6, 2.1, and 3.7 microns). Here, the spatial distributions of the scalar statistics of both the cloud and aerosol layers are first determined from the CALIOP 5 km layer products. Next, the MOD06 look-up tables (LUTs) are adjusted by inserting an absorbing smoke layer of varying optical thickness over the cloud. Retrievals are subsequently performed for a subset of MODIS pixels collocated with the CALIOP ground track, using smoke optical thickness from the CALIOP 5km aerosol layer product to select the appropriate LUT. The resulting differences in cloud optical property retrievals due to the inclusion of the smoke layer in the LUTs will be examined. In addition, the direct radiative forcing of this smoke layer will be investigated from the perspective of the cloud optical property retrieval differences.

  10. Validating Above-cloud Aerosol Optical Depth Retrieved from MODIS using NASA Ames Airborne Sun-Tracking Photometric and Spectrometric (AATS and 4STAR) Measurements

    NASA Astrophysics Data System (ADS)

    Jethva, H. T.; Torres, O.; Remer, L. A.; Redemann, J.; Dunagan, S. E.; Livingston, J. M.; Shinozuka, Y.; Kacenelenbogen, M. S.; Segal-Rosenhaimer, M.

    2014-12-01

    Absorbing aerosols produced from biomass burning and dust outbreaks are often found to overlay the lower level cloud decks as evident in the satellite images. In contrast to the cloud-free atmosphere, in which aerosols generally tend to cool the atmosphere, the presence of absorbing aerosols above cloud poses greater potential of exerting positive radiative effects (warming) whose magnitude directly depends on the aerosol loading above cloud, optical properties of clouds and aerosols, and cloud fraction. In recent years, development of algorithms that exploit satellite-based passive measurements of ultraviolet (UV), visible, and polarized light as well as lidar-based active measurements constitute a major breakthrough in the field of remote sensing of aerosols. While the unprecedented quantitative information on aerosol loading above cloud is now available from NASA's A-train sensors, a greater question remains ahead: How to validate the satellite retrievals of above-cloud aerosols (ACA)? Direct measurements of ACA such as carried out by the NASA Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) can be of immense help in validating ACA retrievals. In this study, we validate the ACA optical depth retrieved using the 'color ratio' (CR) method applied to the MODIS cloudy-sky reflectance by using the airborne AATS and 4STAR measurements. A thorough search of the historic AATS-4STAR database collected during different field campaigns revealed five events where biomass burning, dust, and wildfire-emitted aerosols were found to overlay lower level cloud decks observed during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS-2013, respectively. The co-located satellite-airborne measurements revealed a good agreement (root-mean-square-error<0.1 for Aerosol Optical Depth (AOD) at 500 nm) with most matchups falling within the estimated uncertainties in the MODIS retrievals (-10% to +50%). An extensive validation of

  11. CDRD and PNPR satellite passive microwave precipitation retrieval algorithms: EuroTRMM/EURAINSAT origins and H-SAF operations

    NASA Astrophysics Data System (ADS)

    Mugnai, A.; Smith, E. A.; Tripoli, G. J.; Bizzarri, B.; Casella, D.; Dietrich, S.; Di Paola, F.; Panegrossi, G.; Sanò, P.

    2013-04-01

    Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) is a EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) program, designed to deliver satellite products of hydrological interest (precipitation, soil moisture and snow parameters) over the European and Mediterranean region to research and operations users worldwide. Six satellite precipitation algorithms and concomitant precipitation products are the responsibility of various agencies in Italy. Two of these algorithms have been designed for maximum accuracy by restricting their inputs to measurements from conical and cross-track scanning passive microwave (PMW) radiometers mounted on various low Earth orbiting satellites. They have been developed at the Italian National Research Council/Institute of Atmospheric Sciences and Climate in Rome (CNR/ISAC-Rome), and are providing operational retrievals of surface rain rate and its phase properties. Each of these algorithms is physically based, however, the first of these, referred to as the Cloud Dynamics and Radiation Database (CDRD) algorithm, uses a Bayesian-based solution solver, while the second, referred to as the PMW Neural-net Precipitation Retrieval (PNPR) algorithm, uses a neural network-based solution solver. Herein we first provide an overview of the two initial EU research and applications programs that motivated their initial development, EuroTRMM and EURAINSAT (European Satellite Rainfall Analysis and Monitoring at the Geostationary Scale), and the current H-SAF program that provides the framework for their operational use and continued development. We stress the relevance of the CDRD and PNPR algorithms and their precipitation products in helping secure the goals of H-SAF's scientific and operations agenda, the former helpful as a secondary calibration reference to other algorithms in H-SAF's complete mix of algorithms. Descriptions of the algorithms' designs are provided

  12. Retrieving Cloud Fraction in the Field-of-View of a High-Spectral Resolution Infrared Radiometer

    SciTech Connect

    Turner, David D.; Holz, R. E.

    2005-07-01

    The combination of radiance from both clear and cloudy regions of sky adds significant uncertainty to retrievals of atmospheric state profiles and cloud microphysical properties from infrared radiometers. In this article, we use observations of radiance from both the 8-13 μm and 3-5 μm bands to retrieve estimates of the cloud fraction in the field-of-view, as well as microphysical cloud The combination of radiance from both clear and cloudy regions of sky adds significant uncertainty to retrievals of atmospheric state profiles and cloud microphysical properties from infrared radiometers. In this article, we use observations of radiance from both the 8-13 μm and 3-5 μm bands to retrieve estimates of the cloud fraction in the field-of-view, as well as microphysical cloud properties, from high-spectral-resolution infrared radiometers. Cloud fraction derived from imagers as well as high-time-resolution observations show good agreement and high correlation with our derived cloud fraction values. This is shown for both ground-based and aircraft based observations. We also demonstrate that the use of the addition information in the 3-5 μm band extends the dynamic range and accuracy of microphysical properties that can be retrieved from infrared radiance data.

  13. How do A-train Sensors Inter-Compare in the Retrieval of Above-Cloud Aerosol Optical Depth? A Case Study based Assessment

    NASA Astrophysics Data System (ADS)

    Jethva, H. T.; Torres, O.; Waquet, F.; Chand, D.

    2013-12-01

    Atmospheric aerosols are known to produce a net cooling effect in the cloud-free conditions. However, when present over the reflective cloud decks, absorbing aerosols such as biomass burning generated smoke and wind-blown dust can potentially exert a large positive forcing through enhanced atmospheric heating resulting from cloud-aerosol radiative interactions. The interest on this aspect of aerosol science has grown significantly in the recent years. Particularly, development of the satellite-based retrieval techniques and unprecedented knowledge on the above-cloud aerosol optical depth (ACAOD) is of great relevance. A direct validation of satellite ACAOD is a difficult task primarily due to lack of ample in situ and/or remote sensing measurements of aerosols above cloud. In these circumstances, a comparative analysis on the inter-satellite ACAOD retrievals can be performed for the sack of consistency check. Here, we inter-compare the ACAOD of biomass burning plumes observed from different A-train sensors, i.e., MODIS [Jethva et al., 2013], CALIOP [Chand et al., 2008], POLDER [Waquet et al., 2009], and OMI [Torres et al., 2012]. These sensors have been shown to acquire sensitivity and independent capabilities to detect and retrieve aerosol loading above marine stratocumulus clouds--a kind of situation often found over the southeastern Atlantic Ocean during dry burning season. A systematic one-to-one comparison reveals that, in general, all passive sensors and CALIOP-based research methods retrieve comparable ACAOD over homogeneous cloud fields. The high-resolution sensors (MODIS and CALIOP) are able to retrieve aerosols over thin clouds but with larger discrepancies. Given the different types of sensor measurements processed with different algorithms, a reasonable agreement between them is encouraging. A direct validation of satellite-based ACAOD remains an open challenge for which dedicated field measurements over the region of frequent aerosol/cloud overlap are

  14. Cloud Liquid Water Path Comparisons from Passive Microwave and Solar Reflectance Satellite Measurements: Assessment of Sub-Field-of-View Cloud Effects in Microwave Retrievals

    NASA Technical Reports Server (NTRS)

    Greenwald, Thomas J.; Christopher, Sundar A.; Chou, Joyce

    1997-01-01

    Satellite observations of the cloud liquid water path (LWP) are compared from special sensor microwave imager (SSM/I) measurements and GOES 8 imager solar reflectance (SR) measurements to ascertain the impact of sub-field-of-view (FOV) cloud effects on SSM/I 37 GHz retrievals. The SR retrievals also incorporate estimates of the cloud droplet effective radius derived from the GOES 8 3.9-micron channel. The comparisons consist of simultaneous collocated and full-resolution measurements and are limited to nonprecipitating marine stratocumulus in the eastern Pacific for two days in October 1995. The retrievals from these independent methods are consistent for overcast SSM/I FOVS, with RMS differences as low as 0.030 kg/sq m, although biases exist for clouds with more open spatial structure, where the RMS differences increase to 0.039 kg/sq m. For broken cloudiness within the SSM/I FOV the average beam-filling error (BFE) in the microwave retrievals is found to be about 22% (average cloud amount of 73%). This systematic error is comparable with the average random errors in the microwave retrievals. However, even larger BFEs can be expected for individual FOVs and for regions with less cloudiness. By scaling the microwave retrievals by the cloud amount within the FOV, the systematic BFE can be significantly reduced but with increased RMS differences of O.046-0.058 kg/sq m when compared to the SR retrievals. The beam-filling effects reported here are significant and are expected to impact directly upon studies that use instantaneous SSM/I measurements of cloud LWP, such as cloud classification studies and validation studies involving surface-based or in situ data.

  15. An Integrated Approach toward Retrieving Physically Consistent Profiles of Temperature, Humidity, and Cloud Liquid Water.

    NASA Astrophysics Data System (ADS)

    Löhnert, Ulrich; Crewell, Susanne; Simmer, Clemens

    2004-09-01

    A method is presented for deriving physically consistent profiles of temperature, humidity, and cloud liquid water content. This approach combines a ground-based multichannel microwave radiometer, a cloud radar, a lidar-ceilometer, the nearest operational radiosonde measurement, and ground-level measurements of standard meteorological properties with statistics derived from results of a microphysical cloud model. All measurements are integrated within the framework of optimal estimation to guarantee a retrieved profile with maximum information content. The developed integrated profiling technique (IPT) is applied to synthetic cloud model output as a test of accuracy. It is shown that the liquid water content profiles obtained with the IPT are significantly more accurate than common methods that use the microwave-derived liquid water path to scale the radar reflectivity profile. The IPT is also applied to 2 months of the European Cloud Liquid Water Network (CLIWA-NET) Baltic Sea Experiment (BALTEX) BRIDGE main experiment (BBC) campaign data, considering liquid-phase, nonprecipitating clouds only. Error analysis indicates root-mean-square uncertainties of less than 1 K in temperature and less than 1 g m-3 in humidity, where the relative error in liquid water content ranges from 15% to 25%. A comparison of the vertically integrated humidity profile from the IPT with the nearest operational radiosonde shows an acceptable bias error of 0.13 kg m-2 when the Rosenkranz gas absorption model is used. However, if the Liebe gas absorption model is used, this systematic error increases to -1.24 kg m-2, showing that the IPT humidity retrieval is significantly dependent on the chosen gas absorption model.


  16. Temporal Variability of Surface Solar Irradiance as a Function of Satellite-retrieved Cloud

    NASA Astrophysics Data System (ADS)

    Hinkelman, L. M.; Sengupta, M.; Habte, A.

    2014-12-01

    Studies of the impact of renewables on the electrical transmission grid are needed as power production from renewable energy resources increases. These studies require estimates of high temporal and spatial resolution power output under various scenarios. Satellite-based solar resource estimates are the best source of long-term irradiance data but are generally of lower temporal and spatial resolution than needed and thus require downscaling. Likewise, weather forecast models cannot provide high spatial or temporal irradiance predictions. Downscaling requires information about solar irradiance variability in both space and time, which is primarily a function of cloud properties. In this study, we analyze the relationships between the temporal variability of surface solar irradiance and satellite-based cloud properties. One-minute resolution surface solar irradiance data were obtained from the National Oceanic and Atmospheric Administration's Surface Radiation (SURFRAD) network. These sites are distributed across the United States to cover a range of meteorological conditions. Cloud information at a nominal 4 km resolution and half hour intervals was retrieved from NOAA's Geostationary Operation Environmental Satellites (GOES). The retrieved cloud properties were then used to select and composite irradiance data from the measurement sites in order to identify the cloud properties that exert the strongest control over short-term irradiance variability. The irradiance variability was characterized using statistics of both the irradiances themselves and of irradiance differences computed for short time scales (minutes). The relationships derived using this method will be presented, comparing and contrasting the statistics computed for the different cloud properties. The implications for downscaling irradiance from satellites or forecast models will also be discussed.

  17. From Point Clouds to Architectural Models: Algorithms for Shape Reconstruction

    NASA Astrophysics Data System (ADS)

    Canciani, M.; Falcolini, C.; Saccone, M.; Spadafora, G.

    2013-02-01

    The use of terrestrial laser scanners in architectural survey applications has become more and more common. Row data complexity, as given by scanner restitution, leads to several problems about design and 3D-modelling starting from Point Clouds. In this context we present a study on architectural sections and mathematical algorithms for their shape reconstruction, according to known or definite geometrical rules, focusing on shapes of different complexity. Each step of the semi-automatic algorithm has been developed using Mathematica software and CAD, integrating both programs in order to reconstruct a geometrical CAD model of the object. Our study is motivated by the fact that, for architectural survey, most of three dimensional modelling procedures concerning point clouds produce superabundant, but often unnecessary, information and are also very expensive in terms of cpu time using more and more sophisticated hardware and software. On the contrary, it's important to simplify/decimate the point cloud in order to recognize a particular form out of some definite geometric/architectonic shapes. Such a process consists of several steps: first the definition of plane sections and characterization of their architecture; secondly the construction of a continuous plane curve depending on some parameters. In the third step we allow the selection on the curve of some nodal points with given specific characteristics (symmetry, tangency conditions, shadowing exclusion, corners, … ). The fourth and last step is the construction of a best shape defined by the comparison with an abacus of known geometrical elements, such as moulding profiles, leading to a precise architectonical section. The algorithms have been developed and tested in very different situations and are presented in a case study of complex geometries such as some mouldings profiles in the Church of San Carlo alle Quattro Fontane.

  18. Performance of the Lidar Design and Data Algorithms for the GLAS Global Cloud and Aerosol Measurements

    NASA Technical Reports Server (NTRS)

    Spinhirne, James D.; Palm, Stephen P.; Hlavka, Dennis L.; Hart, William D.

    2007-01-01

    The Geoscience Laser Altimeter System (GLAS) launched in early 2003 is the first polar orbiting satellite lidar. The instrument design includes high performance observations of the distribution and optical scattering cross sections of atmospheric clouds and aerosol. The backscatter lidar operates at two wavelengths, 532 and 1064 nm. For the atmospheric cloud and aerosol measurements, the 532 nm channel was designed for ultra high efficiency with solid state photon counting detectors and etalon filtering. Data processing algorithms were developed to calibrate and normalize the signals and produce global scale data products of the height distribution of cloud and aerosol layers and their optical depths and particulate scattering cross sections up to the limit of optical attenuation. The paper will concentrate on the effectiveness and limitations of the lidar channel design and data product algorithms. Both atmospheric receiver channels meet and exceed their design goals. Geiger Mode Avalanche Photodiode modules are used for the 532 nm signal. The operational experience is that some signal artifacts and non-linearity require correction in data processing. As with all photon counting detectors, a pulse-pile-up calibration is an important aspect of the measurement. Additional signal corrections were found to be necessary relating to correction of a saturation signal-run-on effect and also for daytime data, a small range dependent variation in the responsivity. It was possible to correct for these signal errors in data processing and achieve the requirement to accurately profile aerosol and cloud cross section down to 10-7 llm-sr. The analysis procedure employs a precise calibration against molecular scattering in the mid-stratosphere. The 1064 nm channel detection employs a high-speed analog APD for surface and atmospheric measurements where the detection sensitivity is limited by detector noise and is over an order of magnitude less than at 532 nm. A unique feature of

  19. Impact of Cumulus Cloud Spacing on Landsat Atmospheric Correction and Aerosol Retrieval

    NASA Technical Reports Server (NTRS)

    Wen, Guoyong; Cahalan, Robert F.; Tsay, Si-Chee; Oreopoulos, Lazaros

    2001-01-01

    A Landsat-7 ETM+ image acquired over the Southern Great Plains DoE/ARM site during the ARESE II experiment is used to study the effect of clouds on reflected radiation in clear patches of a cumulus cloud field. The result shows that the apparent path radiance in the clear patches is enhanced by nearby clouds in both band 1 (blue) and band 3 (red) of ETM+. More importantly, the magnitude of the enhancement depends on the mean cloud-free distance in the clear patches. For cloud-free distance less than 0.5 km, the enhancement of apparent path radiance is more than 0.025 and 0.015 (reflectance units) in band 1 and band 3 respectively, which corresponds to an enhancement of apparent aerosol optical thickness of approximately 0.25 and approximately 0.15. Neglecting of the 3-D cloud effect would lead to underestimates of surface reflectance of approximately 0.025 and approximately 0.015 in the blue and red band respectively, if the true aerosol optical thickness is 0.2 and the surface reflectance is 0.05. The enhancement decreases exponentially with mean cloud-free distance, reaching asymptotic values of 0.09 for band 1 and 0.027 for band 3 at a mean cloud-free distance about 2 km. The asymptotic values are slightly larger than the mean path radiances retrieved from a completely clear region -- 0.086 and 0.024 for the blue and red band respectively.

  20. Validation of satellite retrievals of cloud microsphysics and liquid water path using observations from FIRE

    NASA Technical Reports Server (NTRS)

    Rossow, W.; White, A.; Han, Q.; Welch, R.; Chou, J.

    1995-01-01

    Cloud effective radii (r(sub e)) and cloud liquid water path (LWP) are derived from ISCCP spatially sampled satellite data and validated with ground-based pyranometer and microwave radiometer measurements taken on San Nicolas Island during the 1987 FIRE IFO. Values of r(sub e) derived from the ISCCP data are also compared to values retrieved by a hybrid method that uses the combination of LWP derived from microwave measurement and optical thickness derived from GOES data. The results show that there is significant variability in cloud properties over a 100 km x 80 km area and that the values at San Nicolas Island are not necessarily representative of the surrounding cloud field. On the other hand, even though there were large spatial variations in optical depth, the r(sub e) values remained relatively constant (with sigma less than or equal to 2-3 microns in most cases) in the marine stratocumulus. Furthermore, values of r(sub e) derived from the upper portion of the cloud generally are representative of the entire stratiform cloud. When LWP values are less than 100 g m(exp -2), then LWP values derived from ISCCP data agree well with those values estimated from ground-based microwave measurements. In most cases LWP differences were less than 20 g m(exp -2). However, when LWP values become large (e.g., greater than or equal to 200 g m(exp -2)), then relative differences may be as large as 50%- 100%. There are two reasons for this discrepancy in the large LWP clouds: (1) larger vertical inhomogeneities in precipitating clouds and (2) sampling errors on days of high spatial variability of cloud optical thicknesses. Variations of r(sub e) in stratiform clouds may indicate drizzle: clouds with droplet sizes larger than 15 microns appear to be associated with drizzling, while those less than 10 microns are indicative of nonprecipitating clouds. Differences in r(sub e) values between the GOES and ISCCP datasets are found to be 0.16 +/- 0.98 micron.

  1. Deriving Arctic Cloud Microphysics at Barrow, Alaska. Algorithms, Results, and Radiative Closure

    SciTech Connect

    Shupe, Matthew D.; Turner, David D.; Zwink, Alexander; Thieman, Mandana M.; Mlawer, Eli J.; Shippert, Timothy

    2015-07-01

    Cloud phase and microphysical properties control the radiative effects of clouds in the climate system and are therefore crucial to characterize in a variety of conditions and locations. An Arctic-specific, ground-based, multi-sensor cloud retrieval system is described here and applied to two years of observations from Barrow, Alaska. Over these two years, clouds occurred 75% of the time, with cloud ice and liquid each occurring nearly 60% of the time. Liquid water occurred at least 25% of the time even in the winter, and existed up to heights of 8 km. The vertically integrated mass of liquid was typically larger than that of ice. While it is generally difficult to evaluate the overall uncertainty of a comprehensive cloud retrieval system of this type, radiative flux closure analyses were performed where flux calculations using the derived microphysical properties were compared to measurements at the surface and top-of-atmosphere. Radiative closure biases were generally smaller for cloudy scenes relative to clear skies, while the variability of flux closure results was only moderately larger than under clear skies. The best closure at the surface was obtained for liquid-containing clouds. Radiative closure results were compared to those based on a similar, yet simpler, cloud retrieval system. These comparisons demonstrated the importance of accurate cloud phase classification, and specifically the identification of liquid water, for determining radiative fluxes. Enhanced retrievals of liquid water path for thin clouds were also shown to improve radiative flux calculations.

  2. A single field of view method for retrieving tropospheric temperature profiles from cloud-contaminated radiance data

    NASA Technical Reports Server (NTRS)

    Hodges, D. B.

    1976-01-01

    An iterative method is presented to retrieve single field of view (FOV) tropospheric temperature profiles directly from cloud-contaminated radiance data. A well-defined temperature profile may be calculated from the radiative transfer equation (RTE) for a partly cloudy atmosphere when the average fractional cloud amount and cloud-top height for the FOV are known. A cloud model is formulated to calculate the fractional cloud amount from an estimated cloud-top height. The method is then examined through use of simulated radiance data calculated through vertical integration of the RTE for a partly cloudy atmosphere using known values of cloud-top height(s) and fractional cloud amount(s). Temperature profiles are retrieved from the simulated data assuming various errors in the cloud parameters. Temperature profiles are retrieved from NOAA-4 satellite-measured radiance data obtained over an area dominated by an active cold front and with considerable cloud cover and compared with radiosonde data. The effects of using various guessed profiles and the number of iterations are considered.

  3. Turkish Cloud-Radiation Database (CRD) and Its Application with CDR Bayesian Probability Algorithm

    NASA Astrophysics Data System (ADS)

    Oztopal, A.; Mugnai, A.; Casella, D.; Formenton, M.; Sano, P.; Sonmez, I.; Sen, Z.; Hsaf Team

    2010-12-01

    ABSTRACT It is rather a very difficult task to determine ground rainfall amounts from few Special Sensor Microwave Imager/Sounder (SSMI/S) channels. Although ground rainfall cannot be observed from the space directly, but knowledge about the cloud physics helps to estimate the amound of ground rainfall. SSMI/S includes so much information about the atmospheric structure, however it cannot provide cloud micro-physical structural information. In such a situation, in the rainfall algorithm, besides the SSMI/S data, it is necessary to incorporate cloud micro-physical properties from an external data source. These properties can be obtained quite simply by the help of Cloud Resolving Model (CRM). Later, in addition to all available data, also micro-physical properties obtained from Radiative Transfer Model (RTM) help to determine the SSMI/S brightness temperatures (Brightness temperatures - TBs), which can then be correlated with Cloud-Radiation Database (CRD) data generation. SSMI/S satellite data and CDR provide a common basis for rainfall prediction procedure through CDR Bayesian probability algorithm, which combines the two sets of data in a scientific manner. The first applications of this algorithm, which is being used up today, is due to various researchers. In this work, in order to establish a reflection of available data processing CDR CRM University of Wisconsin - Non-hydrostatic Modeling System (UW-NMS) model is employed, which is first developed by Prof. Gregory J. Tripoli. It is also used by Turkish Meteorological Service by benefiting from radar network data, and finally 14 simulations are realized in this study. Moreover, one case study is fulfilled by using a 3X3 spatial filtering, and then radar data and result of CDR Bayesian probability algorithm are compared with each other. On 9 September 2009 at 03:40 GMT rainfall event on comparatively flat area matches far better with the retrieval values and hence the spatial rainfall occurrence extent and

  4. Cirrus Clouds Optical, Microphysical and Radiative Properties Observed During Crystal-Face Experiment: I. A Radar-Lidar Retrieval System

    NASA Technical Reports Server (NTRS)

    Mitrescu, C.; Haynes, J. M.; Stephens, G. L.; Heymsfield, G. M.; McGill, M. J.

    2004-01-01

    A method of retrieving cloud microphysical properties using combined observations from both cloud radar and lidar is introduced. This retrieval makes use of an improvement to the traditional optimal estimation retrieval method, whereby a series of corrections are applied to the state vector during the search for an iterative solution. This allows faster convergence to a solution and is less processor intensive. The method is first applied to a synthetic cloud t o demonstrate its validity, and it is shown that the retrieval reliably reproduces vertical profiles of ice water content. The retrieval method is then applied to radar and lidar observations from the CRYSTAL-FACE experiment, and vertical profiles of ice crystal diameter, number concentration, and ice water content are retrieved for a cirrus cloud layers observed one day of that experiment. The validity of the relationship between visible extinction coefficient and radar reflectivity was examined. While synthetic tests showed such a functional relationship, the measured data only partially supported such a conclusion. This is due to errors in the forward model (as explained above) as well as errors in the data sets, including possible mismatch between lidar and radar profiles or errors in the optical depth. Empirical relationships between number concentrations and mean particle diameter were also examined. The results indicate that a distinct and robust relationship exists between these retrieved quantities and it is argued that such a relationship is more than an artifact of the retrieval process offering insight into the nature of the microphysical processes taking place in cirrus.

  5. PROGRESS REPORT OF FY 2004 ACTIVITIES: IMPROVED WATER VAPOR AND CLOUD RETRIEVALS AT THE NSA/AAO

    SciTech Connect

    E. R. Westwater; V. V. Leuskiy; M. Klein; A. J. Gasiewski; and J. A. Shaw

    2004-11-01

    The basic goals of the research are to develop and test algorithms and deploy instruments that improve measurements of water vapor, cloud liquid, and cloud coverage, with a focus on the Arctic conditions of cold temperatures and low concentrations of water vapor. The importance of accurate measurements of column amounts of water vapor and cloud liquid has been well documented by scientists within the Atmospheric Radiation Measurement Program. Although several technologies have been investigated to measure these column amounts, microwave radiometers (MWR) have been used operationally by the ARM program for passive retrievals of these quantities: precipitable water vapor (PWV) and integrated water liquid (IWL). The technology of PWV and IWL retrievals has advanced steadily since the basic 2-channel MWR was first deployed at ARM CART sites Important advances are the development and refinement of the tipcal calibration method [1,2], and improvement of forward model radiative transfer algorithms [3,4]. However, the concern still remains that current instruments deployed by ARM may be inadequate to measure low amounts of PWV and IWL. In the case of water vapor, this is especially important because of the possibility of scaling and/or quality control of radiosondes by the water amount. Extremely dry conditions, with PWV less than 3 mm, commonly occur in Polar Regions during the winter months. Accurate measurements of the PWV during such dry conditions are needed to improve our understanding of the regional radiation energy budgets. The results of a 1999 experiment conducted at the ARM North Slope of Alaska/Adjacent Arctic Ocean (NSA/AAO) site during March of 1999 [5] have shown that the strength associated with the 183 GHz water vapor absorption line makes radiometry in this frequency regime suitable for measuring low amounts of PWV. As a portion of our research, we conducted another millimeter wave radiometric experiment at the NSA/AAO in March-April 2004. This

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

    NASA Technical Reports Server (NTRS)

    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.

  7. Bulk Hydrometeor Types of Mid-Latitude Convective Systems from Bin-Resolving Cloud Simulations and Dual-Polarimetric Scanning Radar Retrieval

    NASA Astrophysics Data System (ADS)

    Matsui, T.; Iguchi, T.; Tao, W. K.; Dolan, B.; Rutledge, S. A.

    2014-12-01

    Robust hydrometeor identification (HID) algorithm has emerged through the use of multi-wavelength polarimetric weather radars [Dolan et al. 2013]. This presentation provides a simple yet useful method to evaluate simulated hydrometeor profiles against the polarimetric radar-retrieved HID data in the specific case study of the Mid-latitude Continental Convective Cloud Experiment (MC3E). The MC3E is the joint NASA-DOE-funded field campaign over the DOE Southern Great Plains (SGP) site, Oklahoma, USA in Spring 2011. We focus on the April 25 case, which observed a strong deep convective system propagating over the SGP site. Colorado State University (CSU) multi-wavelength HID algorithm revealed instantaneous HID profiles and also time-integrated HID diagram separately for shallow, deep stratiform, and deep convective columns. These retrievals are used to evaluate the Weather Research Forecasting model with Spectra-Bin Microphysics (WRF-SBM) [Iguchi et al. 2013]. For this, we have developed a simple emulator of the CSU HID algorithm to consider similar hydrometeor assumptions between the WRF-SBM and CSU HID algorithm. Initial evaluation appears to be reasonable in profiles of shallow and deep stratiform columns between WRF-SBM and CSU HID retrievals, while there is apparent discrepancy in deep convective columns, which is further related to an intuitive assumption in the CSU HID algorithm. Finally feasibility and uncertainties of this approach are discussed.

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

    NASA Astrophysics Data System (ADS)

    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.

  9. Use of In Situ Cloud Condensation Nuclei, Extinction, and Aerosol Size Distribution Measurements to Test a Method for Retrieving Cloud Condensation Nuclei Profiles From Surface Measurements

    NASA Technical Reports Server (NTRS)

    Ghan, Stephen J.; Rissman, Tracey A.; Ellman, Robert; Ferrare, Richard A.; Turner, David; Flynn, Connor; Wang, Jian; Ogren, John; Hudson, James; Jonsson, Haflidi H.; VanReken, Timothy; Flagan, Richard C.; Seinfeld, John H.

    2006-01-01

    If the aerosol composition and size distribution below cloud are uniform, the vertical profile of cloud condensation nuclei (CCN) concentration can be retrieved entirely from surface measurements of CCN concentration and particle humidification function and surface-based retrievals of relative humidity and aerosol extinction or backscatter. This provides the potential for long-term measurements of CCN concentrations near cloud base. We have used a combination of aircraft, surface in situ, and surface remote sensing measurements to test various aspects of the retrieval scheme. Our analysis leads us to the following conclusions. The retrieval works better for supersaturations of 0.1% than for 1% because CCN concentrations at 0.1% are controlled by the same particles that control extinction and backscatter. If in situ measurements of extinction are used, the retrieval explains a majority of the CCN variance at high supersaturation for at least two and perhaps five of the eight flights examined. The retrieval of the vertical profile of the humidification factor is not the major limitation of the CCN retrieval scheme. Vertical structure in the aerosol size distribution and composition is the dominant source of error in the CCN retrieval, but this vertical structure is difficult to measure from remote sensing at visible wavelengths.

  10. Improved methodology for surface and atmospheric soundings, error estimates, and quality control procedures: the atmospheric infrared sounder science team version-6 retrieval algorithm

    NASA Astrophysics Data System (ADS)

    Susskind, Joel; Blaisdell, John M.; Iredell, Lena

    2014-01-01

    The atmospheric infrared sounder (AIRS) science team version-6 AIRS/advanced microwave sounding unit (AMSU) retrieval algorithm is now operational at the Goddard Data and Information Services Center (DISC). AIRS version-6 level-2 products are generated near real time at the Goddard DISC and all level-2 and level-3 products are available starting from September 2002. Some of the significant improvements in retrieval methodology contained in the version-6 retrieval algorithm compared to that previously used in version-5 are described. In particular, the AIRS science team made major improvements with regard to the algorithms used to (1) derive surface skin temperature and surface spectral emissivity; (2) generate the initial state used to start the cloud clearing and retrieval procedures; and (3) derive error estimates and use them for quality control. Significant improvements have also been made in the generation of cloud parameters. In addition to the basic AIRS/AMSU mode, version-6 also operates in an AIRS only (AO) mode, which produces results almost as good as those of the full AIRS/AMSU mode. The improvements of some AIRS version-6 and version-6 AO products compared to those obtained using version-5 are also demonstrated.

  11. Improved Methodology for Surface and Atmospheric Soundings, Error Estimates, and Quality Control Procedures: the AIRS Science Team Version-6 Retrieval Algorithm

    NASA Technical Reports Server (NTRS)

    Susskind, Joel; Blaisdell, John; Iredell, Lena

    2014-01-01

    The AIRS Science Team Version-6 AIRS/AMSU retrieval algorithm is now operational at the Goddard DISC. AIRS Version-6 level-2 products are generated near real-time at the Goddard DISC and all level-2 and level-3 products are available starting from September 2002. This paper describes some of the significant improvements in retrieval methodology contained in the Version-6 retrieval algorithm compared to that previously used in Version-5. In particular, the AIRS Science Team made major improvements with regard to the algorithms used to 1) derive surface skin temperature and surface spectral emissivity; 2) generate the initial state used to start the cloud clearing and retrieval procedures; and 3) derive error estimates and use them for Quality Control. Significant improvements have also been made in the generation of cloud parameters. In addition to the basic AIRS/AMSU mode, Version-6 also operates in an AIRS Only (AO) mode which produces results almost as good as those of the full AIRS/AMSU mode. This paper also demonstrates the improvements of some AIRS Version-6 and Version-6 AO products compared to those obtained using Version-5.

  12. Diagnostic study on retrieving bulk microphysical properties of low-level stratiform clouds and its implication on climate research

    SciTech Connect

    Chin, H.-N.S.; Rodriguez, D.J.; Cederwall, R.T.; Chuang, C.C.; Grossman, A.S.; Yio, J.J.; Fu, Q.; Miller, M.A.

    1998-03-01

    The importance of low-level stratiform clouds to the planetary radiation balance is due to their persistence and coverage, and their effect on the planetary albedo. The vertical distribution of liquid water in these clouds is pertinent to many applications in atmospheric research. As a result, some cloud retrieval techniques have been developed with the assumptions, such as an adiabatic condition, no loss of liquid water via drizzle and/or a large liquid water path.

  13. Assessment of the Performance of the Chilbolton 3-GHz Advanced Meteorological Radar for Cloud-Top-Height Retrieval.

    NASA Astrophysics Data System (ADS)

    Naud, C. M.; Muller, J.-P.; Slack, E. C.; Wrench, C. L.; Clothiaux, E. E.

    2005-06-01

    The Chilbolton 3-GHz Advanced Meteorological Radar (CAMRa), which is mounted on a fully steerable 25-m dish, can provide three-dimensional information on the presence of hydrometeors. The potential for this radar to make useful measurements of low-altitude liquid water cloud structure is investigated. To assess the cloud-height assignment capabilities of the 3-GHz radar, low-level cloud-top heights were retrieved from CAMRa measurements made between May and July 2003 and were compared with cloud-top heights retrieved from a vertically pointing 94-GHz radar that operates alongside CAMRa. The average difference between the 94- and 3-GHz radar-derived cloud-top heights is shown to be -0.1 ± 0.4 km. To assess the capability of 3-GHz radar scans to be used for satellite-derived cloud-top-height validation, multiangle imaging spectroradiometer (MISR) cloud-top heights were compared with both 94- and 3-GHz radar retrievals. The average difference between 94-GHz radar and MISR cloud-top heights is shown to be 0.1 ± 0.3 km, while the 3-GHz radar and MISR average cloud-top-height difference is shown to be -0.2 ± 0.6 km. In assessing the value of the CAMRa measurements, the problems associated with low-reflectivity values from stratiform liquid water clouds, ground clutter, and Bragg scattering resulting from turbulent mixing are all addressed. It is shown that, despite the difficulties, the potential exists for CAMRa measurements to contribute significantly to liquid water cloud-top-height retrievals, leading to the production of two-dimensional transects (i.e., maps) of cloud-top height.

  14. Ensembles of satellite aerosol retrievals based on three AATSR algorithms within aerosol_cci

    NASA Astrophysics Data System (ADS)

    Kosmale, Miriam; Popp, Thomas

    2016-04-01

    Ensemble techniques are widely used in the modelling community, combining different modelling results in order to reduce uncertainties. This approach could be also adapted to satellite measurements. Aerosol_cci is an ESA funded project, where most of the European aerosol retrieval groups work together. The different algorithms are homogenized as far as it makes sense, but remain essentially different. Datasets are compared with ground based measurements and between each other. Three AATSR algorithms (Swansea university aerosol retrieval, ADV aerosol retrieval by FMI and Oxford aerosol retrieval ORAC) provide within this project 17 year global aerosol records. Each of these algorithms provides also uncertainty information on pixel level. Within the presented work, an ensembles of the three AATSR algorithms is performed. The advantage over each single algorithm is the higher spatial coverage due to more measurement pixels per gridbox. A validation to ground based AERONET measurements shows still a good correlation of the ensemble, compared to the single algorithms. Annual mean maps show the global aerosol distribution, based on a combination of the three aerosol algorithms. In addition, pixel level uncertainties of each algorithm are used for weighting the contributions, in order to reduce the uncertainty of the ensemble. Results of different versions of the ensembles for aerosol optical depth will be presented and discussed. The results are validated against ground based AERONET measurements. A higher spatial coverage on daily basis allows better results in annual mean maps. The benefit of using pixel level uncertainties is analysed.

  15. Two algorithms to fill cloud gaps in LST time series

    NASA Astrophysics Data System (ADS)

    Frey, Corinne; Kuenzer, Claudia

    2013-04-01

    Cloud contamination is a challenge for optical remote sensing. This is especially true for the recording of a fast changing radiative quantity like land surface temperature (LST). The substitution of cloud contaminated pixels with estimated values - gap filling - is not straightforward but possible to a certain extent, as this research shows for medium-resolution time series of MODIS data. Area of interest is the Upper Mekong Delta (UMD). The background for this work is an analysis of the temporal development of 1-km LST in the context of the WISDOM project. The climate of the UMD is characterized by peak rainfalls in the summer months, which is also the time where cloud contamination is highest in the area. Average number of available daytime observations per pixel can go down to less than five for example in the month of June. In winter the average number may reach 25 observations a month. This situation is not appropriate to the calculation of longterm statistics; an adequate gap filling method should be used beforehand. In this research, two different algorithms were tested on an 11 year time series: 1) a gradient based algorithm and 2) a method based on ECMWF era interim re-analysis data. The first algorithm searches for stable inter-image gradients from a given environment and for a certain period of time. These gradients are then used to estimate LST for cloud contaminated pixels in each acquisition. The estimated LSTs are clear-sky LSTs and solely based on the MODIS LST time series. The second method estimates LST on the base of adapted ECMWF era interim skin temperatures and creates a set of expected LSTs. The estimated values were used to fill the gaps in the original dataset, creating two new daily, 1 km datasets. The maps filled with the gradient based method had more than the double amount of valid pixels than the original dataset. The second method (ECMWF era interim based) was able to fill all data gaps. From the gap filled data sets then monthly

  16. Cloud identification using genetic algorithms and massively parallel computation

    NASA Technical Reports Server (NTRS)

    Buckles, Bill P.; Petry, Frederick E.

    1996-01-01

    As a Guest Computational Investigator under the NASA administered component of the High Performance Computing and Communication Program, we implemented a massively parallel genetic algorithm on the MasPar SIMD computer. Experiments were conducted using Earth Science data in the domains of meteorology and oceanography. Results obtained in these domains are competitive with, and in most cases better than, similar problems solved using other methods. In the meteorological domain, we chose to identify clouds using AVHRR spectral data. Four cloud speciations were used although most researchers settle for three. Results were remarkedly consistent across all tests (91% accuracy). Refinements of this method may lead to more timely and complete information for Global Circulation Models (GCMS) that are prevalent in weather forecasting and global environment studies. In the oceanographic domain, we chose to identify ocean currents from a spectrometer having similar characteristics to AVHRR. Here the results were mixed (60% to 80% accuracy). Given that one is willing to run the experiment several times (say 10), then it is acceptable to claim the higher accuracy rating. This problem has never been successfully automated. Therefore, these results are encouraging even though less impressive than the cloud experiment. Successful conclusion of an automated ocean current detection system would impact coastal fishing, naval tactics, and the study of micro-climates. Finally we contributed to the basic knowledge of GA (genetic algorithm) behavior in parallel environments. We developed better knowledge of the use of subpopulations in the context of shared breeding pools and the migration of individuals. Rigorous experiments were conducted based on quantifiable performance criteria. While much of the work confirmed current wisdom, for the first time we were able to submit conclusive evidence. The software developed under this grant was placed in the public domain. An extensive user

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

    NASA Technical Reports Server (NTRS)

    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

  18. GFIT2: an experimental algorithm for vertical profile retrieval from near IR spectra

    NASA Astrophysics Data System (ADS)

    Connor, B. J.; Sherlock, V.; Toon, G.; Wunch, D.; Wennberg, P.

    2015-11-01

    An algorithm for retrieval of vertical profiles from ground-based spectra in the near IR is described and tested. Known as GFIT2, the algorithm is primarily intended for CO2, and is used exclusively for CO2 in this paper. Retrieval of CO2 vertical profiles from ground-based spectra is theoretically possible, would be very beneficial for carbon cycle studies and the validation of satellite measurements, and has been the focus of much research in recent years. GFIT2 is tested by application both to synthetic spectra, and to measurements at two TCCON sites. We demonstrate that there are approximately 3° of freedom for the CO2 profile, and the algorithm performs as expected on synthetic spectra. We show that the accuracy of retrievals of CO2 from measurements in the 1.6 μ spectral band is limited by small uncertainties in calculation of the atmospheric spectrum. We investigate several techniques to minimize the effect of these uncertainties in calculation of the spectrum. These techniques are somewhat effective, but to date have not been demonstrated to produce CO2 profile retrievals superior to existing techniques for retrieval of column abundance. We finish by discussing on-going research which may allow CO2 profile retrievals with sufficient accuracy to significantly improve on the results of column retrievals, both in total column abundance and in profile shape.

  19. How Various Sources of Uncertainty Affect Retrieval Uncertainty in the Optimal Estimation Framework Using a Non-precipitating Liquid Clouds Example

    NASA Astrophysics Data System (ADS)

    Xu, Z.; Mace, G. G.; Turner, D. D.; Posselt, D. J.

    2014-12-01

    Optimal estimation (OE) is a commonly used inverse method in the geosciences. In a Bayesian context, a set of measurements (y) is related to the state vector to be retrieved (x) by the forward model F(x). Assuming Gaussian statistics, OE returns an optimal solution and its associated uncertainty by minimizing the cost function that consists of the state vector-a priori state difference weighted by the a priori uncertainty and the measurement-forward model difference weighted by the uncertainties of observation and forward model. OE algorithms are easy to implement and are finding increasing use within communities attempting to derive, for instance, cloud and precipitation microphysical properties from remote sensing data. However, even though OE algorithms are simple to implement, obtaining rigorous uncertainty estimates from them is a significant challenge. Our objective with this work is to illustrate the growth of retrieval uncertainty within the OE framework due to various sources using simple real world examples of non-precipitating liquid clouds. Within the OE retrieval, several sources of uncertainties contribute to the overall retrieval uncertainty (Sx), including the measurement uncertainty (Sy), the uncertainties in a priori information (Sa) and uncertainties in the forward model due to imperfectly known parameters (Sb). In this study, two examples are given to demonstrate how uncertainties in Sy, Sa and Sb affect the ultimate retrieval uncertainty Sx. We apply OE technique to retrieve cloud liquid water content (LWC) and total number from measurements of radar reflectivity and extinction obtained in 2005 Marine Stratus/Stratocumulus Experiment (MASE). In the first example, the forward model is assumed perfect, which means all parameters are certain and Sb is zero. Then we perturb Sy and Sa separately and observe the response of Sx. We find the observation error Sy contributes significantly to the retrieval uncertainty under the assumption of "perfect

  20. The "RED Versa NIR" Plane to Retrieve Broken-Cloud Optical Depth from Ground-Based Measurements"

    NASA Technical Reports Server (NTRS)

    Marshak, A.; Knyazikhin, Y.; Evans, K.; Wiscombe, W.

    2003-01-01

    A new method for retrieving cloud optical depth from ground-based measurements of zenith radiance in the RED and near infrared (MR) spectral regions is introduced. Because zenith radiance does not have a one-to-one relationship with optical depth, it is absolutely impossible to use a monochromatic retrieval. On the other side, algebraic combinations of spectral radiances such as NDCI while largely removing nouniquiness and the radiative effects of cloud inhomogeneity, can result in poor retrievals due to its insensitivity to cloud fraction. Instead, both RED and NIR radiances as points on the 'RED vs. NIR' plane are proposed to be used for retrieval. The proposed retrieval method is applied to Cimel measurements at the Atmospheric Radiation Measurements (ARM) site in Oklahoma. Cimel, a multi-channel sunphotometer, is a part of AERONET - a ground-based network for monitoring aerosol optical properties. The results of retrieval are compared with the ones from Microwave Radiometer (MWR) and Multi-Filter Rotating Shadowband Radiometers (MFRSR) located next to Cimel at the ARM site. In addition, the performance of the retrieval method is assessed using a fractal model of cloud inhomogeneity and broken cloudiness. The preliminary results look very promising both theoretically and from measurements.

  1. Polarimetric Retrievals of Surface and Cirrus Clouds Properties in the Region Affected by the Deepwater Horizon Oil Spill

    NASA Technical Reports Server (NTRS)

    Ottaviani, Matteo; Cairns, Brian; Chowdhary, Jacek; Van Diedenhoven, Bastiaan; Knobelspiesse, Kirk; Hostetler, Chris; Ferrare, Rich; Burton, Sharon; Hair, John; Obland, Michael D.; Rogers, Raymond

    2012-01-01

    prohibitive variability in atmospheric conditions (very inhomogeneous aerosol distribution and cloud cover). Although the results presented for the surface are essentially unaffected, we discuss the results obtained by typing algorithms in sorting the complex mix of aerosol types, and show evidence of oriented ice in cirrus clouds present in the area. In this context, polarization measurements at 1880 nm were used to infer ice habit and cirrus optical depth, which was found in the subvisual/threshold-visible regime, confirming the utility of the aforementioned RSP channel for the remote sensing of even thin cold clouds.

  2. Millimeter-Wave Imaging Radiometer (MIR) Data Processing and Development of Water Vapor Retrieval Algorithms

    NASA Technical Reports Server (NTRS)

    Chang, L. Aron

    1998-01-01

    This document describes the final report of the Millimeter-wave Imaging Radiometer (MIR) Data Processing and Development of Water Vapor Retrieval