Science.gov

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

    NASA Astrophysics Data System (ADS)

    Qiu, Yujun; Lu, Chunsong

    2016-09-01

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

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. Cloud retrieval algorithm for the imaging spectro-polarimeter on board EUMETSAT Polar System - Second Generation (EPS-SG)

    NASA Astrophysics Data System (ADS)

    Kokhanovsky, Alexander; Munro, Rose

    2015-04-01

    The atmospheric remote sensing benefits a lot from the use of spectro - polarimetric imagers on board satellite platforms. Due to the movement of the spacecraft, any given scene can be observed from many directions by an imaging polarimeter. This concept has been proven with the measurements of POLDER - 1, 2, and 3 on board ADEOS and PARASOL platforms. POLDER has performed measurements of the Stokes vector (first three components) of reflected light in 16 directions at several wavelengths in the visible and near - infrared. The 3MI (Multi-viewing, Multi-channel, Multi-polarization Imaging) on board of a future (2021) EPS-SG mission is very similar to POLDER. However, the measurements are performed at more spectral channels as compared to POLDER and also at a better spatial resolution (4*4km). In particular, the measurements of the Stokes vector components (I, Q, U) of the reflected solar light are performed at the wavelengths 410, 443, 490, 555, 670, 865, 1650, and 2130nm. In addition, the intensity of reflected light is measured at 763, 765, 910, and 1370nm. The FWHM of the channel at 763nm is 10nm and it is 20 nm at other channels (except at 765nm, 865nm, 1650nm, and 2130nm, where FWHM is equal to 40nm). The imaging spectro-polarimeter enables enhanced retrievals of aerosol and cloud properties using spaceborne observations. In particular, the following parameters of clouds can be retrieved: cloud top altitude, liquid water path, the average size of particles in the clouds, and the cloud thermodynamic state. The cloud albedo, cloud optical thickness, single scattering albedo and other optical parameters of clouds can be derived as well. In this presentation we describe the cloud retrieval algorithm CROP developed at EUMETSAT for the retrievals of cloud microphysical, geometrical, and optical characteristics using 3MI observations. The retrievals are performed only for completely cloudy pixels. The measurements at channels 763 and 765nm are used to get cloud top

  13. Development of Cloud and Precipitation Property Retrieval Algorithms and Measurement Simulators from ASR Data

    SciTech Connect

    Mace, Gerald G.

    2016-02-10

    What has made the ASR program unique is the amount of information that is available. The suite of recently deployed instruments significantly expands the scope of the program (Mather and Voyles, 2013). The breadth of this information allows us to pose sophisticated process-level questions. Our ASR project, now entering its third year, has been about developing algorithms that use this information in ways that fully exploit the new capacity of the ARM data streams. Using optimal estimation (OE) and Markov Chain Monte Carlo (MCMC) inversion techniques, we have developed methodologies that allow us to use multiple radar frequency Doppler spectra along with lidar and passive constraints where data streams can be added or subtracted efficiently and algorithms can be reformulated for various combinations of hydrometeors by exchanging sets of empirical coefficients. These methodologies have been applied to boundary layer clouds, mixed phase snow cloud systems, and cirrus.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. Improvement of MODIS aerosol retrievals near clouds

    NASA Astrophysics Data System (ADS)

    Wen, Guoyong; Marshak, Alexander; Levy, Robert C.; Remer, Lorraine A.; Loeb, Norman G.; Várnai, Tamás.; Cahalan, Robert F.

    2013-08-01

    retrieval of aerosol properties near clouds from reflected sunlight is challenging. Sunlight reflected from clouds can effectively enhance the reflectance in nearby clear regions. Ignoring cloud 3-D radiative effects can lead to large biases in aerosol retrievals, risking an incorrect interpretation of satellite observations on aerosol-cloud interaction. Earlier, we developed a simple model to compute the cloud-induced clear-sky radiance enhancement that is due to radiative interaction between boundary layer clouds and the molecular layer above. This paper focuses on the application and implementation of the correction algorithm. This is the first time that this method is being applied to a full Moderate Resolution Imaging Spectroradiometer (MODIS) granule. The process of the correction includes converting Clouds and the Earth's Radiant Energy System broadband flux to visible narrowband flux, computing the clear-sky radiance enhancement, and retrieving aerosol properties. We find that the correction leads to smaller values in aerosol optical depth (AOD), Ångström exponent, and the small mode aerosol fraction of the total AOD. It also makes the average aerosol particle size larger near clouds than far away from clouds, which is more realistic than the opposite behavior observed in operational retrievals. We discuss issues in the current correction method as well as our plans to validate the algorithm.

  19. 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.

  20. 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).

  1. 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.

  2. Global Multispectral Cloud Retrievals from MODIS

    NASA Technical Reports Server (NTRS)

    King, Michael D.; Platnick, Steven; Ackerman, Steven A.; Menzel, W. Paul; Riedi, Jerome C.; Baum, Bryan A.

    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.

  3. 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).

  4. Volumetric Geophysical Retrievals in Precipitating Cloud Systems

    NASA Astrophysics Data System (ADS)

    Collis, S. M.; North, K. W.; Jensen, M. P.; Kollias, P.; Williams, C. R.; Bharadwaj, N.; Fridlind, A. M.; Widener, K.; Giangrande, S.

    2011-12-01

    Cloud and climate modeling efforts focused around the Mid-Latitude Continental Convective Clouds Experiment (MC3E) require the retrieval of high quality geophysical parameters pertinent to storm microphysical and dynamical properties. The installation of high resolution polarimetric X- and C-Band scanning radars have greatly enhanced measurements at the Atmospheric Radiation Measurement Southern Great Plain site, however, the volumetric data collected by these sensors is only indirectly related to storm properties. This presentation will outline efforts towards creating a suite of model-like Value Added Products (VAPs) for MC3E derived using existing and new retrieval techniques. Particular focus will be on retrieval of storm dynamics, precipitation microphysics and rainfall accumulations from the scanning radar measurements. Algorithm details and verification efforts will be showcased as well as a timetable for data availability.

  5. 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

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

    NASA Astrophysics Data System (ADS)

    Petersen, W. A.; Jensen, M. P.

    2011-12-01

    The joint NASA GPM - DOE 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 network. As an exploratory effort to examine land-surface emissivity

  7. 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

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. Outcome of the third cloud retrieval evaluation workshop

    NASA Astrophysics Data System (ADS)

    Roebeling, Rob; Baum, Bryan; Bennartz, Ralf; Hamann, Ulrich; Heidinger, Andy; Thoss, Anke; Walther, Andi

    2013-05-01

    Accurate measurements of global distributions of cloud parameters and their diurnal, seasonal, and interannual variations are needed to improve understanding of the role of clouds in the weather and climate system, and to monitor their time-space variations. Cloud properties retrieved from satellite observations, such as cloud vertical placement, cloud water path and cloud particle size, play an important role for such studies. In order to give climate and weather researchers more confidence in the quality of these retrievals their validity needs to be determined and their error characteristics must be quantified. The purpose of the Cloud Retrieval Evaluation Workshop (CREW), held from 15-18 Nov. 2011 in Madison, Wisconsin, USA, is to enhance knowledge on state-of-art cloud properties retrievals from passive imaging satellites, and pave the path towards optimizing these retrievals for climate monitoring as well as for the analysis of cloud parameterizations in climate and weather models. CREW also seeks to observe and understand methods used to prepare daily and monthly cloud parameter climatologies. An important workshop component is discussion on results of the algorithm and sensor comparisons and validation studies. Hereto a common database with about 12 different cloud properties retrievals from passive imagers (MSG, MODIS, AVHRR, POLDER and/or AIRS), complemented with cloud measurements that serve as a reference (CLOUDSAT, CALIPSO, AMSU, MISR), was prepared for a number of "golden days". The passive imager cloud property retrievals were inter-compared and validated against Cloudsat, Calipso and AMSU observations. In our presentation we summarize the outcome of the inter-comparison and validation work done in the framework of CREW, and elaborate on reasons for observed differences. More in depth discussions were held on retrieval principles and validation, and utilization of cloud parameters for climate research. This was done in parallel breakout sessions on

  14. Toward understanding of differences in current cloud retrievals of ARM ground-based measurements

    SciTech Connect

    Zhao C.; Dunn M.; Xie, S.; Klein, S. A.; Protat, A.; Shupe, M. D.; McFarlane, S. A.; Comstock, J. M.; Delanoë, J.; Deng, M.; Hogan, R. J.; Huang, D.; Jensen, M. P.; Mace, G. G.; McCoy, R.; O’Connor, E. J.; Turner, D. D.; Wang, Z.

    2012-05-30

    Accurate observations of cloud microphysical properties are needed for evaluating and improving the representation of cloud processes in climate models and better estimate of the Earth radiative budget. 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 emphasis 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 particle effective radius. Note that the differences among some retrieval products are even larger than the prescribed uncertainties reported by the retrieval algorithm developers. It is shown that most of these large differences have their roots in 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.

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  17. On the Retrieval and Analysis of Multilevel Clouds

    NASA Technical Reports Server (NTRS)

    Baum, Bryan A.; Wielicki, Bruce A.

    1992-01-01

    , but are generally applied operationally to any given cloud occurrence. The CO2 slicing algorithms are most accurate for clouds than occur in a single, well-defined layer, or for multi-layered cloud cases in which the uppermost cloud layer is nearly black. Significant cloud height retrieval errors may ensue if the HIRS Field-Of-View (FOV) is cotaminated with low cloud. McCleese and Wilson (1976) have shown that the retrieved cloud height for the case of multiple cloud layers is a weighted average of the cloud heights actually present. The weight is approximately proportional to the product of the cloud heigt and the effective cloud amount. The effect of their result is that the uppermost cloud layer dominates the cloud pressure retrieval. Beyond stating that the higher cloud dominates the cloud pressure retrieval, there is no quantitative information to provide a way of estimating the errors in cloud pressure retrieval one should expect for certain common multilevel cloud situations or any suggestions on how to reduce the errors. In this paper we estimate the magnitude of the errors and use a simple algorithm to reduce the errors in optically thin cloud height retrival.

  18. 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.

  19. Multi-Spectral Cloud Property Retrieval

    NASA Technical Reports Server (NTRS)

    Carlson, Barbara E.; Lynch, R

    1999-01-01

    Despite numerous studies to retrieve cloud properties using infrared measurements the information content of the data has not yet been fully exploited. In an effort to more fully utilize the information content of infrared measurements, we have developed a multi-spectral technique for retrieving effective cloud particle size, optical depth and effective cloud temperature. While applicable to all cloud types, we begin by validating our retrieval technique through analysis of MS spectral radiances obtained during the SUCCESS field campaign over the ARM SGP CART facility, and compare our retrieval product with lidar and MODIS Airborne Simulator (MAS) measurement results. The technique is then applied to the Nimbus-4 MS infrared spectral measurements to obtain global cloud information.

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

    NASA Astrophysics Data System (ADS)

    Poulsen, C. A.; Watts, P. D.; Thomas, G. E.; Sayer, A. M.; Siddans, R.; Grainger, R. G.; Lawrence, B. N.; Campmany, E.; Dean, S. M.; Arnold, C.

    2011-04-01

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

  1. Validating MODIS above-cloud aerosol optical depth retrieved from "color ratio" algorithm using direct measurements made by NASA's airborne AATS and 4STAR sensors

    NASA Astrophysics Data System (ADS)

    Jethva, Hiren; Torres, Omar; Remer, Lorraine; Redemann, Jens; Livingston, John; Dunagan, Stephen; Shinozuka, Yohei; Kacenelenbogen, Meloe; Segal Rosenheimer, Michal; Spurr, Rob

    2016-10-01

    We present the validation analysis of above-cloud aerosol optical depth (ACAOD) retrieved from the "color ratio" method applied to MODIS cloudy-sky reflectance measurements using the limited direct measurements made by NASA's airborne Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) sensors. A thorough search of the airborne database collection revealed a total of five significant events in which an airborne sun photometer, coincident with the MODIS overpass, observed partially absorbing aerosols emitted from agricultural biomass burning, dust, and wildfires over a low-level cloud deck during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS 2013 campaigns, respectively. The co-located satellite-airborne matchups revealed a good agreement (root-mean-square difference < 0.1), with most matchups falling within the estimated uncertainties associated the MODIS retrievals (about -10 to +50 %). The co-retrieved cloud optical depth was comparable to that of the MODIS operational cloud product for ACE-ASIA and SEAC4RS, however, higher by 30-50 % for the SAFARI-2000 case study. The reason for this discrepancy could be attributed to the distinct aerosol optical properties encountered during respective campaigns. A brief discussion on the sources of uncertainty in the satellite-based ACAOD retrieval and co-location procedure is presented. Field experiments dedicated to making direct measurements of aerosols above cloud are needed for the extensive validation of satellite-based retrievals.

  2. A stochastic cloud model for cloud and ozone retrievals from UV measurements

    NASA Astrophysics Data System (ADS)

    Efremenko, Dmitry S.; Schüssler, Olena; Doicu, Adrian; Loyola, Diego

    2016-11-01

    The new generation of satellite instruments provides measurements in and around the Oxygen A-band on a global basis and with a relatively high spatial resolution. These data are commonly used for the determination of cloud properties. A stochastic model and radiative transfer model, previously developed by the authors, is used as the forward model component in retrievals of cloud parameters and ozone total and partial columns. The cloud retrieval algorithm combines local and global optimization routines, and yields a retrieval accuracy of about 1% and a fast computational time. Retrieved parameters are the cloud optical thickness and the cloud-top height. It was found that the use of the independent pixel approximation instead of the stochastic cloud model leads to large errors in the retrieved cloud parameters, as well as, in the retrieved ozone height resolved partial columns. The latter can be reduced by using the stochastic cloud model to compute the optimal value of the regularization parameter in the framework of Tikhonov regularization.

  3. Retrieval of ice cloud microphysical parameters using the CloudSat millimeter-wave radar and temperature

    NASA Astrophysics Data System (ADS)

    Austin, Richard T.; Heymsfield, Andrew J.; Stephens, Graeme L.

    2009-04-01

    A new remote sensing retrieval of ice cloud microphysics has been developed for use with millimeter-wave radar from ground-, air-, or space-based sensors. Developed from an earlier retrieval that used measurements of radar reflectivity factor together with a priori information about the likely cloud targets, the new retrieval includes temperature information as well to assist in determining the correct region of state space, particularly for those size distribution parameters that are less constrained by the radar measurements. These algorithms have served as the ice cloud retrieval algorithms in Releases 3 and 4 of the CloudSat 2B-CWC-RO Standard Data Product. Several comparison studies have been performed on the previous and current retrieval algorithms: some involving tests of the algorithms on simulated radar data (based on actual cloud probe data or cloud resolving models) and others featuring statistical comparisons of the R04 2B-CWC-RO product (current algorithm) to ice cloud mass retrievals by other spaceborne, airborne, and ground-based instruments or alternative algorithms using the same CloudSat radar data. Comparisons involving simulated radar data based on a database of cloud probe data showed generally good performance, with ice water content (IWC) bias errors estimated to be less than 40%. Comparisons to ice water content and ice water path estimates by other instruments are mixed. When the comparison is restricted to different retrieval approaches using the same CloudSat radar measurements, CloudSat R04 results generally agree with alternative IWC retrievals for IWC < 1000 mg m-3 at altitudes below 12 km but differ at higher ice contents and altitudes, either exceeding other retrievals or falling within a spread of retrieval values. Validation and reconciliation of all these approaches will continue to be a topic for further research.

  4. 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.

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

    NASA Astrophysics Data System (ADS)

    Poulsen, C. A.; Siddans, R.; Thomas, G. E.; Sayer, A. M.; Grainger, R. G.; Campmany, E.; Dean, S. M.; Arnold, C.; Watts, P. D.

    2012-08-01

    Clouds play an important role in balancing the Earth's radiation budget. Hence, it is vital that cloud climatologies are produced that quantify cloud macro and micro physical parameters and the associated uncertainty. In this paper, we present an algorithm ORAC (Oxford-RAL retrieval of Aerosol and Cloud) which is based on fitting a physically consistent cloud model to satellite observations simultaneously from the visible to the mid-infrared, thereby ensuring that the resulting cloud properties provide both a good representation of the short-wave and long-wave radiative effects of the observed cloud. The advantages of the optimal estimation method are that it enables rigorous error propagation and the inclusion of all measurements and any a priori information and associated errors in a rigorous mathematical framework. The algorithm provides a measure of the consistency between retrieval representation of cloud and satellite radiances. The cloud parameters retrieved are the cloud top pressure, cloud optical depth, cloud effective radius, cloud fraction and cloud phase. The algorithm can be applied to most visible/infrared satellite instruments. In this paper, we demonstrate the applicability to the Along-Track Scanning Radiometers ATSR-2 and AATSR. Examples of applying the algorithm to ATSR-2 flight data are presented and the sensitivity of the retrievals assessed, in particular the algorithm is evaluated for a number of simulated single-layer and multi-layer conditions. The algorithm was found to perform well for single-layer cloud except when the cloud was very thin; i.e., less than 1 optical depths. For the multi-layer cloud, the algorithm was robust except when the upper ice cloud layer is less than five optical depths. In these cases the retrieved cloud top pressure and cloud effective radius become a weighted average of the 2 layers. The sum of optical depth of multi-layer cloud is retrieved well until the cloud becomes thick, greater than 50 optical depths

  6. Retrievals of ice cloud microphysical properties of deep convective systems using radar measurements: Convective Cloud Microphysical Retrieval

    SciTech Connect

    Tian, Jingjing; Dong, Xiquan; Xi, Baike; Wang, Jingyu; Homeyer, Cameron R.; McFarquhar, Greg M.; Fan, Jiwen

    2016-09-23

    This study presents new algorithms for retrieving ice cloud microphysical properties (ice water content (IWC) and median mass diameter (Dm)) for the stratiform and thick anvil regions of Deep Convective Systems (DCSs) using Next-Generation Radar (NEXRAD) reflectivity and recently developed empirical relationships from aircraft in situ measurements during the Midlatitude Continental Convective Clouds Experiment (MC3E). A classic DCS case on 20 May 2011 is used to compare the retrieved IWC profiles with other retrieval and cloud-resolving model simulations. The mean values of each retrieved and simulated IWC fall within one standard derivation of the other two. The statistical results from six selected cases during MC3E show that the aircraft in situ derived IWC and Dm are 0.47 ± 0.29 g m-3 and 2.02 ± 1.3 mm, while the mean values of retrievals have a positive bias of 0.16 g m-3 (34%) and a negative bias of 0.39 mm (19%). To validate the newly developed retrieval algorithms from this study, IWC and Dm are performed with other DCS cases during Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX) field campaign using composite gridded NEXRAD reflectivity and compared with in situ IWC and Dm from aircraft. A total of 64 1-min collocated aircraft and radar samples are available for comparisons, and the averages of radar retrieved and aircraft in situ measured IWCs are 1.22 g m-3 and 1.26 g m-3 with a correlation of 0.5, and their averaged Dm values are 2.15 and 1.80 mm. These comparisons have shown that the retrieval algorithms 45 developed during MC3E can retrieve similar ice cloud microphysical properties of DCS to aircraft in situ measurements during BAMEX with median errors of ~40% and ~25% for IWC and Dm retrievals, respectively. This is indicating our retrieval algorithms are suitable for other midlatitude continental DCS ice clouds, especially at stratiform rain and thick anvil regions. In addition, based on the averaged IWC and Dm values during MC3E and

  7. 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.

  8. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2017-01-01

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

  11. Sensitivity of PARASOL multi-angle photo-polarimetric aerosol retrievals to cloud contamination

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

    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 photo-polarimetric 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, photo-polarimetric 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, synthetic data-set including partial cloud cover as well as non-cloud screened 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 reject the cloud contaminated scenes. No bias nor 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

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

  13. The operational methane retrieval algorithm for TROPOMI

    NASA Astrophysics Data System (ADS)

    Hu, Haili; Hasekamp, Otto; Butz, André; Galli, André; Landgraf, Jochen; Aan de Brugh, Joost; Borsdorff, Tobias; Scheepmaker, Remco; Aben, Ilse

    2016-11-01

    This work presents the operational methane retrieval algorithm for the Sentinel 5 Precursor (S5P) satellite and its performance tested on realistic ensembles of simulated measurements. The target product is the column-averaged dry air volume mixing ratio of methane (XCH4), which will be retrieved simultaneously with scattering properties of the atmosphere. The algorithm attempts to fit spectra observed by the shortwave and near-infrared channels of the TROPOspheric Monitoring Instrument (TROPOMI) spectrometer aboard S5P.The sensitivity of the retrieval performance to atmospheric scattering properties, atmospheric input data and instrument calibration errors is evaluated. In addition, we investigate the effect of inhomogeneous slit illumination on the instrument spectral response function. Finally, we discuss the cloud filters to be used operationally and as backup.We show that the required accuracy and precision of < 1 % for the XCH4 product are met for clear-sky measurements over land surfaces and after appropriate filtering of difficult scenes. The algorithm is very stable, having a convergence rate of 99 %. The forward model error is less than 1 % for about 95 % of the valid retrievals. Model errors in the input profile of water do not influence the retrieval outcome noticeably. The methane product is expected to meet the requirements if errors in input profiles of pressure and temperature remain below 0.3 % and 2 K, respectively. We further find that, of all instrument calibration errors investigated here, our retrievals are the most sensitive to an error in the instrument spectral response function of the shortwave infrared channel.

  14. 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

  15. MODIS cloud and aerosol retrieval simulator and its applications

    NASA Astrophysics Data System (ADS)

    Wind, Galina

    Executing a cloud or aerosol physical properties retrieval algorithm from controlled synthetic data is an important step in retrieval algorithm development. Synthetic data can help answer questions about the sensitivity and performance of the algorithm or aid in determining how an existing retrieval algorithm may perform with a planned sensor. Synthetic data can also help in solving issues that may have surfaced in the retrieval results. Synthetic data become very important when other validation methods, such as field campaigns,are of limited scope. These tend to be of relatively short duration and often are costly. Ground stations have limited spatial coverage whilesynthetic data can cover large spatial and temporal scales and a wide variety of conditions at a low cost. In this work I develop an advanced cloud and aerosol retrieval simulator for the MODIS instrument, also known as Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS). In a close collaboration with the modeling community I have seamlessly combined the GEOS-5 global climate model with the DISORT radiative transfer code, widely used by the remote sensing community, with the observations from the MODIS instrument to create the simulator. With the MCARS simulator it was then possible to solve the long standing issue with the MODIS aerosol optical depth retrievals that had a low bias for smoke aerosols. MODIS aerosol retrieval did not account for effects of humidity on smoke aerosols. The MCARS simulator also revealed an issue that has not been recognized previously, namely,the value of fine mode fraction could create a linear dependence between retrieved aerosol optical depth and land surface reflectance. MCARS provided the ability to examine aerosol retrievals against "ground truth" for hundreds of thousands of simultaneous samples for an area covered by only three AERONET ground stations. Findings from MCARS are already being used to improve the performance of operational MODIS aerosol

  16. 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.

  17. 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.

  18. 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.

  19. The OMI Cloud Pressure Algorithm Based on UV Measurements

    NASA Astrophysics Data System (ADS)

    Vasilkov, A. P.; Joiner, J.; Flittner, D. E.; Gleason, J. F.; Bhartia, P. K.

    2003-12-01

    The OMI cloud pressure product is deemed "mission-essential" for OMI because the product is necessary for correction of the mission-critical total ozone product. Cloud pressure can be derived from the high frequency structure of top-of-atmosphere reflectance in the UV 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 effective cloud pressure and cloud fraction using a concept of the Modified Lambert Equivalent Reflectivity (MLER). The MLER concept is used for several of the OMI algorithms including the retrieval of ozone and other trace gases. Therefore, the cloud pressure algorithm is consistent with other OMI algorithms. Details of the cloud pressure algorithm are discussed including the correction for vibrational Raman scattering in the ocean that also significantly contributes to filling-in of Fraunhofer lines in the backscatter UV spectra over pixels with thin or broken clouds. Examples of retrieving cloud pressure from GOME data are presented.

  20. 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

  1. 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.

  2. Cloud and moisture fields derived from the GLA retrievals of HIRS2/MSU data

    NASA Technical Reports Server (NTRS)

    Reuter, D.; Susskind, J.

    1986-01-01

    The GLA retrieval scheme for the analysis of HIRS and MSU radiances is applied to derive cloud and humidity fields from the HIRS2/MSU data for June 1979. For the retrieval of cloud fraction and cloud top pressure, the original algorithm of Susskind et al. (1983) and Susskind et al. (1984) was improved. The derived profiles of the monthly mean fields of cloud fraction and cloud top pressure clearly show the intertropical convergence zone, with the most intense convection in the monsoonal region of the southern Asia and over Central America, which show up as containing the highest cloud top levels and largest cloud amount. For the retrieval of humidity profiles, which are not one of the products of the original processing system, a new algorithm was derived.

  3. 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

  4. 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.

  5. 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.

  6. Retrieval of radiative and microphysical properties of clouds from multispectral infrared measurements

    NASA Astrophysics Data System (ADS)

    Iwabuchi, Hironobu; Saito, Masanori; Tokoro, Yuka; Putri, Nurfiena Sagita; Sekiguchi, Miho

    2016-12-01

    Satellite remote sensing of the macroscopic, microphysical, and optical properties of clouds are useful for studying spatial and temporal variations of clouds at various scales and constraining cloud physical processes in climate and weather prediction models. Instead of using separate independent algorithms for different cloud properties, a unified, optimal estimation-based cloud retrieval algorithm is developed and applied to moderate resolution imaging spectroradiometer (MODIS) observations using ten thermal infrared bands. The model considers sensor configurations, background surface and atmospheric profile, and microphysical and optical models of ice and liquid cloud particles and radiative transfer in a plane-parallel, multilayered atmosphere. Measurement and model errors are thoroughly quantified from direct comparisons of clear-sky observations over the ocean with model calculations. Performance tests by retrieval simulations show that ice cloud properties are retrieved with high accuracy when cloud optical thickness (COT) is between 0.1 and 10. Cloud-top pressure is inferred with uncertainty lower than 10 % when COT is larger than 0.3. Applying the method to a tropical cloud system and comparing the results with the MODIS Collection 6 cloud product shows good agreement for ice cloud optical thickness when COT is less than about 5. Cloud-top height agrees well with estimates obtained by the CO2 slicing method used in the MODIS product. The present algorithm can detect optically thin parts at the edges of high clouds well in comparison with the MODIS product, in which these parts are recognized as low clouds by the infrared window method. The cloud thermodynamic phase in the present algorithm is constrained by cloud-top temperature, which tends not to produce results with an ice cloud that is too warm and liquid cloud that is too cold.

  7. The retrieval of cloud-top pressure of multilayer clouds using combined measurements of MERIS and AATSR onboard ENVISAT

    NASA Astrophysics Data System (ADS)

    Lindstrot, R.; Preusker, R.; Fischer, J.

    2009-04-01

    Measurements of the Medium Resolution Imaging Spectrometer (MERIS) within the oxygen A band at 762nm are operationally used for the retrieval of cloud-top pressure. A validation with airborne LIDAR measurements revealed a high accuracy (~25hPa) of the cloud-top pressure product in case of low, single-layer clouds. However, problems arise in presence of multilayered clouds, as the single channel within the oxygen A band does not allow the identification of multiple cloud layers. The retrieved cloud height thus represents the effective single layer height, located in-between the true cloud layers. This problem can be resolved by combining MERIS observations with measurements in the thermal infrared spectral range. Since clouds are strongly absorbing at infrared wavelengths, the cloud-top temperature of even optically thin clouds can be determined and related to cloud-top pressure using the respective temperature profile. The Advanced Along Track Scanning Radiometer (AATSR) onboard ENVISAT provides radiance measurements in the thermal infrared region that can easily be combined with MERIS observations, as both are nadir viewing, imaging instruments with a similar spatial resolution of ~1km. The synergetic measurements can be used for the retrieval of the height of two cloud layers in case the upper layer is optically thin (? ? 5). The retrieval algorithm is based on the Optimal Estimation technique using radiative transfer simulations of the Matrix Operator Model (MOMO).

  8. 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.

  9. 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.

  10. Atmospheric, Cloud, and Surface Parameters Retrieved from Satellite Ultra-spectral Infrared Sounder Measurements

    NASA Technical Reports Server (NTRS)

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

    2007-01-01

    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 clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multivariable 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. This retrieval algorithm is applied to the MetOp satellite Infrared Atmospheric Sounding Interferometer (IASI) launched on October 19, 2006. IASI possesses an ultra-spectral resolution of 0.25 cm(exp -1) and a spectral coverage from 645 to 2760 cm(exp -1). Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI measurements are obtained and presented.

  11. 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.

  12. Nimbus-7 global cloud climatology. I - Algorithms and validation

    NASA Technical Reports Server (NTRS)

    Stowe, L. L.; Wellemeyer, C. G.; Yeh, H. Y. M.; Eck, T. F.; Hwang, P. H.; Kyle, H. L.

    1988-01-01

    An improved version of the Nimbus-7 cloud retrieval algorithm was validated using data from Nimbus-7 Temperature Humidity Infrared Radiometer and Total Ozone Mapping Spectrometer to determine cloudiness parameters for the globe. Quantitative validation of total cloud amount was performed by comparing the algorithm results with estimates derived from GOES images and auxiliary meteorological data. The systematic errors of the Nimbus-7 total cloud-amount algorithm, relative to the GOES-derived estimates, were found to be less than 10 percent. The random errors of daily estimates ranged between 7 and 16 percent, day or night.

  13. Comparisons of cloud cover and cloud fractions using remote-sensing retrievals

    SciTech Connect

    Krueger, S K; Rodriguez, D

    1999-05-18

    The DOE's Atmospheric Radiation Measurement (ARM) Program employs both upward- and downward-looking remote-sensing instruments to measure the horizontal and vertical distributions of clouds across its Southern Great Plains (SGP) site. No single instrument is capable of completely determining these distributions over the scales of interest to ARM's Single Column Modeling (SCM) and Instantaneous Radiative Flux (IRF) groups; these groups embody the primary strategies through which ARM expects to achieve its objectives of developing and testing cloud formation (USDOE, 1996). Collectively, however, the data from ARM's cloud-detecting instruments offer the potential for such a three-dimensional characterization. Data intercomparisons, like the ones illustrated here, are steps in this direction. Specifically, they are valuable because they help: provide a measure of uncertainty in ARM's measurement capabilities, calibrate retrieval methods and refine algorithms and concepts. In the process, we are forced to think of meaningful ways in which measurements from different instruments can be compared and, perhaps, combined. While the ultimate goal of this particular effort is to develop the ability to accurately characterize cloud fields in three dimensions over time at the SGP site, along the way we will address such questions as ''which source, or combination of cloud data sources, offers a best estimate product?'' and ''how can cloud observations be used to evaluate the representation of clouds in numerical models?''. Examples of some initial comparisons, involving satellite, millimeter cloud radar, whole sky imager and ceilometer data, are provided herein.

  14. Cloud Property Retrieval Products for Graciosa Island, Azores

    DOE Data Explorer

    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.

  15. 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.

  16. CalNex cloud properties retrieved from a ship-based spectrometer and comparisons with satellite and aircraft retrieved cloud properties

    NASA Astrophysics Data System (ADS)

    McBride, P. J.; Schmidt, K. S.; Pilewskie, P.; Walther, A.; Heidinger, A. K.; Wolfe, D. E.; Fairall, C. W.; Lance, S.

    2012-10-01

    An algorithm to retrieve cloud optical thickness and effective radius (reff) from spectral transmittance was applied to radiance and irradiance observations of the Solar Spectral Flux Radiometer (SSFR) during the Research at the Nexus of Air Quality and Climate Change Campaign (CalNex). Data from an overcast day, 16 May 2010, was used to validate the algorithm. Retrievals from the SSFR, deployed on the Woods Hole Oceanic Institute R/V Atlantis, were compared to retrievals made from an airborne SSFR, the Geostationary Operations Environmental Satellite (GOES), an Atlantis-based microwave radiometer, and the Moderate Resolution Imaging Spectroradiometer. In situ observations of reff during a flight over the Atlantis were compared to the Atlantis SSFR and GOES retrievals. The cloud statistics for the CalNex campaign were compared to previous studies. The agreement between the different retrievals, quantified by determining the number of coincident observations when retrieval uncertainty overlapped, improved as the difference between the field-of-views (FOV) of the instruments decreased. It is shown that averaging the 1 Hz SSFR observations to the 15 minute GOES interval cannot fully account for the impact of the different FOVs. The average in situ reff (7.7 μm) fell between the average reff retrieved using the Atlantis-based SSFR radiance (5.7 μm) and irradiance (9.5 μm). The CalNex clouds showed a diurnal pattern observed in previous studies of marine boundary layer clouds in the region. The distribution of cloud optical thickness and liquid water path during CalNex was shown to be a gamma distribution, consistent with previous studies of high cloud fraction marine boundary layer clouds.

  17. 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

  18. 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

  19. 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

  20. 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.

  1. CalNex cloud properties retrieved from a ship-based spectrometer and comparisons with satellite and aircraft retrieved cloud properties

    NASA Astrophysics Data System (ADS)

    McBride, P. J.; Schmidt, K. S.; Pilewskie, P.; Walther, A.; Heidinger, A. K.; Wolfe, D. E.; Fairall, C. W.; Lance, S.

    2011-11-01

    An algorithm to retrieve cloud optical thickness and effective radius (reff) from spectral transmittance was applied to radiance and irradiance observations of the Solar Spectral Flux Radiometer (SSFR) during the Research at the Nexus of Air Quality and Climate Change Campaign (CalNex). Data from an overcast day, 16 May 2010, was used to validate the algorithm. Retrievals from the SSFR, deployed on the Woods Hole Oceanic Institute R/V Atlantis, were compared to retrievals made from an airborne SSFR, the Geostationary Operations Environmental Satellite (GOES), an Atlantis-based microwave radiometer, and the Moderate Resolution Imaging Spectroradiometer. In situ observations of reffduring a flight over the Atlantis were compared to the Atlantis SSFR and GOES retrievals. The cloud statistics for the CalNex campaign were compared to previous studies. The agreement between the different retrievals, quantified by determining the number of coincident observations when retrieval uncertainty overlapped, improved as the difference between the field-of-views (FOV) of the instruments decreased. It is shown that averaging the 1 Hz SSFR observations to the 15 minute GOES interval cannot fully account for the impact of the different FOVs. The average in situ reff (7.7 μm) fell between the average reffretrieved using the Atlantis-based SSFR radiance (5.7μm) and irradiance (9.5 μm). The CalNex clouds showed a diurnal pattern observed in previous studies of marine boundary layer clouds in the region. The distribution of cloud optical thickness and liquid water path during CalNex was shown to be a gamma distribution, consistent with previous studies of high cloud fraction marine boundary layer clouds.

  2. 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.

  3. Comparison of retrieved noctilucent cloud particle properties from Odin tomography scans and model simulations

    NASA Astrophysics Data System (ADS)

    Megner, Linda; Christensen, Ole M.; Karlsson, Bodil; Benze, Susanne; Fomichev, Victor I.

    2016-12-01

    Mesospheric ice particles, known as noctilucent clouds or polar mesospheric clouds, have long been observed by rocket instruments, satellites and ground-based remote sensing, while models have been used to simulate ice particle growth and cloud properties. However, the fact that different measurement techniques are sensitive to different parts of the ice particle distribution makes it difficult to compare retrieved parameters such as ice particle radius or ice concentration from different experiments. In this work we investigate the accuracy of satellite retrieval based on scattered light and how this affects derived cloud properties. We apply the retrieval algorithm on spectral signals calculated from modelled cloud distributions and compare the results to the properties of the original distributions. We find that ice mass density is accurately retrieved whereas mean radius is often overestimated and high ice concentrations are generally underestimated. The reason is partly that measurements based on scattered light are insensitive to the smaller particles and partly that the retrieval algorithm assumes a Gaussian size distribution. Once we know the limits of the satellite retrieval we proceed to compare the properties retrieved from the modelled cloud distributions to those observed by the Optical, Spectroscopic, and Infrared Remote Imaging System (OSIRIS) instrument on the Odin satellite. We find that a model with a stationary atmosphere, as given by average atmospheric conditions, does not yield cloud properties that are in agreement with the observations, whereas a model with realistic temperature and vertical wind variations does. This indicates that average atmospheric conditions are insufficient to understand the process of noctilucent cloud growth and that a realistic atmospheric variability is crucial for cloud formation and growth. Further, the agreement between results from the model, when set up with a realistically variable atmosphere, and the

  4. 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).

  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. 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.

  7. 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.

  8. Exploring the Effects of Cloud Vertical Structure on Cloud Microphysical Retrievals based on Polarized Reflectances

    NASA Astrophysics Data System (ADS)

    Miller, D. J.; Zhang, Z.; Platnick, S. E.; Ackerman, A. S.; Cornet, C.; Baum, B. A.

    2013-12-01

    A polarized cloud reflectance simulator was developed by coupling an LES cloud model with a polarized radiative transfer model to assess the capabilities of polarimetric cloud retrievals. With future remote sensing campaigns like NASA's Aerosols/Clouds/Ecosystems (ACE) planning to feature advanced polarimetric instruments it is important for the cloud remote sensing community to understand the retrievable information available and the related systematic/methodical limitations. The cloud retrieval simulator we have developed allows us to probe these important questions in a realistically relevant test bed. Our simulator utilizes a polarized adding-doubling radiative transfer model and an LES cloud field from a DHARMA simulation (Ackerman et al. 2004) with cloud properties based on the stratocumulus clouds observed during the DYCOMS-II field campaign. In this study we will focus on how the vertical structure of cloud microphysics can influence polarized cloud effective radius retrievals. Numerous previous studies have explored how retrievals based on total reflectance are affected by cloud vertical structure (Platnick 2000, Chang and Li 2002) but no such studies about the effects of vertical structure on polarized retrievals exist. Unlike the total cloud reflectance, which is predominantly multiply scattered light, the polarized reflectance is primarily the result of singly scattered photons. Thus the polarized reflectance is sensitive to only the uppermost region of the cloud (tau~<1) where photons can scatter once and still escape before being scattered again. This means that retrievals based on polarized reflectance have the potential to reveal behaviors specific to the cloud top. For example cloud top entrainment of dry air, a major influencer on the microphysical development of cloud droplets, can be potentially studied with polarimetric retrievals.

  9. 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.

  10. Global retrieval of ATSR cloud parameters and evaluation (GRAPE): dataset assessment

    NASA Astrophysics Data System (ADS)

    Sayer, A. M.; Poulsen, C. A.; Arnold, C.; Campmany, E.; Dean, S.; Ewen, G. B. L.; Grainger, R. G.; Lawrence, B. N.; Siddans, R.; Thomas, G. E.; Watts, P. D.

    2011-04-01

    GRAPE and the two MODIS products considered is generally high (greater than 0.7 for most cloud properties), except for liquid and ice cloud effective radius, which also show biases between the datasets. For liquid clouds, part of the difference is linked to choice of wavelengths used in the retrieval. Total cloud cover is slightly lower in GRAPE (0.64) than the CALIOP dataset (0.66). GRAPE underestimates liquid cloud water path relative to microwave radiometers by up to 100 g m-2 near the Equator and overestimates by around 50 g m-2 in the storm tracks. Finally, potential future improvements to the algorithm are outlined.

  11. Global retrieval of ATSR cloud parameters and evaluation (GRAPE): dataset assessment

    NASA Astrophysics Data System (ADS)

    Sayer, A. M.; Poulsen, C. A.; Arnold, C.; Campmany, E.; Dean, S.; Ewen, G. B. L.; Grainger, R. G.; Lawrence, B. N.; Siddans, R.; Thomas, G. E.; Watts, P. D.

    2010-11-01

    GRAPE and the two MODIS products considered is generally high (greater than 0.7 for most cloud properties), except for liquid and ice cloud effective radius, which also show biases between the datasets. For liquid clouds, part of the difference is linked to choice of wavelengths used in the retrieval. Total cloud cover is slightly lower in GRAPE (0.64) than the CALIOP dataset (0.66). GRAPE underestimates liquid cloud water path relative to microwave radiometers by up to 100 g m-2 near the Equator and overestimates by around 50 g m-2 in the storm tracks. Finally, potential future improvements to the algorithm are outlined.

  12. 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.

  13. Joint AOT-Single Scattering Albedo Retrieval in Algorithm MAIAC

    NASA Astrophysics Data System (ADS)

    Lyapustin, A.

    2015-12-01

    Multi-Angle Implementation of Atmospheric Correction (MAIAC) is a new algorithm which uses time series analysis and processing of groups of pixels for advanced cloud detection and retrieval of aerosol and surface bidirectional reflectance properties. MAIAC C6+ re-processing of MODIS data record, scheduled to begin in November 2015, will create a suite of products MCD19. Due to high 1km resolution, MAIAC provides information about fine scale aerosol variability required in different applications such as urban air quality analysis. During the past year, we developed a new MAIAC capability to retrieve Single Scattering Albedo (SSA) from MODIS by adapting OMI heritage approach of O. Torres. We will describe MAIAC retrieval approach, AERONET AOT and SSA validation for different world biomass burning regions, and will compare MAIAC results with other sensors.

  14. 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.

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

    PubMed

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

    2015-05-16

    Moderate Resolution Imaging Spectroradiometer (MODIS) retrieves cloud droplet effective radius (re ) 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 re 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 "re too large" failure accounting for 60%-85% of all failed retrievals. The rest is mostly due to the "re 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 re values observed in these clouds are the consequence of true cloud microphysics or still due to artifacts not included in this study.

  17. 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.

  18. Development of a Global Multilayered Cloud Retrieval System

    NASA Technical Reports Server (NTRS)

    Huang, J.; Minnis, P.; Lin, B.; Yi, Y.; Ayers, J. K.; Khaiyer, M. M.; Arduini, R.; Fan, T.-F

    2004-01-01

    A more rigorous multilayered cloud retrieval system has been developed to improve the determination of high cloud properties in multilayered clouds. The MCRS attempts a more realistic interpretation of the radiance field than earlier methods because it explicitly resolves the radiative transfer that would produce the observed radiances. A two-layer cloud model was used to simulate multilayered cloud radiative characteristics. Despite the use of a simplified two-layer cloud reflectance parameterization, the MCRS clearly produced a more accurate retrieval of ice water path than simple differencing techniques used in the past. More satellite data and ground observation have to be used to test the MCRS. The MCRS methods are quite appropriate for interpreting the radiances when the high cloud has a relatively large optical depth (tau(sub I) greater than 2). For thinner ice clouds, a more accurate retrieval might be possible using infrared methods. Selection of an ice cloud retrieval and a variety of other issues must be explored before a complete global application of this technique can be implemented. Nevertheless, the initial results look promising.

  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. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. Ozone retrieval errors associated with clouds in total ozone mapping spectrometer (TOMS) data

    NASA Astrophysics Data System (ADS)

    Liu, Xiong

    This study characterizes TOMS Ozone Retrieval Errors (ORES) associated with incorrect Cloud-Top Pressures (CTPs) and with assuming opaque Lambertian clouds, investigates these errors' effects on tropospheric ozone derivation, and analyzes ozone anomalies over TOMS data. Large errors occurring in TOMS assumed CTPs and inaccurate CTP-caused ORES are most significantly from inappropriately added ozone below clouds. Because OREs are usually within the TOMS retrieval precision when Cloud Optical Depth (COD) ≥ 20, assuming angular-independent cloud reflection is good. Because of In-Cloud Ozone Absorption ENhancement (ICOAEN), assuming opaque clouds can introduce large positive OREs even for optically thick clouds. For a 2--12 km water cloud of COD 40 with 20.8 DU ozone homogeneously distributed inside the cloud, the ORE is 17.8 DU at nadir view. The ICOAEN effect depends strongly on viewing geometry and inter-cloud ozone amount and distribution; it is typically 5--13 DU over the tropical Atlantic and Africa and 1--7 DU over the tropical Pacific for deep convective clouds. The TOMS Partial Cloud Model (PCM) is good because negative PCM effect partly cancels other positive errors. At COD ≤ 5, the TOMS algorithm retrieves approximately the correct total ozone because of compensating errors. With increasing COD up to 20--40, negative PCM effect decreases more dramatically than positive effects, so overall positive ORE increases and is dominated by the ICOAEN effect. The ICOAEN effect can largely underestimate tropospheric ozone derived from cloudy/clear difference techniques. The convective cloud differential and cloud-clear pair methods use minimum ozone above clouds to cancel positive errors. A Positive or Negative Ozone Anomaly (POA/NOA) is defined to occur if the ozone/reflectivity correlation coefficient in a region is ≥0.5 or ≤-0.5. Average fractions of OA occurrence are 31.8% and 35.8% in Nimbus-7 and Earth-Probe TOMS data, respectively. Most tropical NOAs

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Using SEVIRI radiances to retrieve cloud optical properties of convective cloud systems

    NASA Astrophysics Data System (ADS)

    Müller, Jennifer; Fischer, Jürgen; Hünerbein, Anja; Deneke, Hartwig; Macke, Andreas

    2013-05-01

    In this case study the development of cloud properties (cloud optical depth, effective radius and cloud top height) during the life-cycle of a convective cloud system over Europe was analyzed. To retrieve the properties we developed a retrieval scheme based on the radiative transfer code MOMO and an optimal estimation procedure. Input data are the visible to short-wavelength infrared channels from SEVIRI. In contrast to many other retrieval schemes we used 4 channels simultaneously. Especially the 3,9μm channel provides additional information due to the fact that it measures solar reflectance and thermal emission and allows the inclusion of cloud top height into the retrieval. By using a time series of SEVIRI measurements we want to provide and examine the microphysical development of the cloud over life-time. We monitored the growth of the system and found the most active parts of the convection with the highest water content and optical depth in those regions where the cloud top height is largest, too. The effective radius of the cloud particles is largest in older regions of the cloud system, where the cloud is already decaying.

  13. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  15. 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.

  16. 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.

  17. 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.

  18. Extending 'Deep Blue' aerosol retrieval coverage to cases of absorbing aerosols above clouds: sensitivity analysis and first case studies

    SciTech Connect

    Sayer, Andrew M.; Hsu, C.; Bettenhausen, Corey; Lee, Jae N.; Redemann, Jens; Schmid, Beat; Shinozuka, Yohei

    2016-05-07

    Cases of absorbing aerosols above clouds (AAC), 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

  19. 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

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

    PubMed Central

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

    2015-01-01

    Abstract 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. PMID:27656330

  1. A New Algorithm for Detecting Cloud Height using OMPS/LP Measurements

    NASA Technical Reports Server (NTRS)

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

    2016-01-01

    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.

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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.

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

    SciTech Connect

    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.

    2016-03-04

    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. In this paper, 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. Finally, the limitation for small solar backscattering angles of <25° restricts the satellite coverage to ~25% of the world area in a single day.

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

    DOE PAGES

    Rosenfeld, Daniel; Zheng, Youtong; Hashimshoni, Eyal; ...

    2016-03-04

    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. In this paper, 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 concentrationsmore » (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. Finally, the limitation for small solar backscattering angles of <25° restricts the satellite coverage to ~25% of the world area in a single day.« less

  9. 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

  10. 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.

  11. Multiangle photopolarimetric aerosol retrievals in the vicinity of clouds: Synthetic study based on a large eddy simulation

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

    We investigate the effect of cloud contamination and 3-D radiative transfer effects on aerosol retrievals from multiangle photopolarimetric measurements in the vicinity of clouds. To this end multiangle, multiwavelength photopolarimetric observations are simulated using a 3-D radiative transfer model for scenes with realistic cloud properties, based on a large eddy simulation. Spatial resolutions of 2 × 2, 4 × 4, and 6 × 6 km2 have been considered. It is found that a goodness-of-fit criterion efficiently filters out cloud contamination. However, it does not filter out all scenes that are affected by 3-D radiative effects, resulting in small biases in the retrieved aerosol optical thickness (AOT) and single-scattering albedo (SSA). We also found that measurements at higher spatial resolution (2 × 2 km2) do not result in retrievals closer to clouds compared to measurements at coarser spatial resolutions (4 × 4 and 6 × 6 km2). If cloud parameters are fitted simultaneously with aerosol parameters using a 1-D radiative transfer model and the Independent Pixel Approximation, more successful retrievals are obtained in partially cloudy scenes and in the vicinity of clouds. This effect is most apparent at 6 × 6 km2 and only marginal at 2 × 2 km2 resolution. The retrieved aerosol AOT and SSA from the simultaneous aerosol and cloud retrievals still have a small bias, like the aerosol-only retrievals. We conclude that in order to substantially improve aerosol retrievals in the vicinity of clouds, a retrieval algorithm is needed that takes into account 3-D radiative transfer effects.

  12. 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.

  13. 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.

  14. A snow wetness retrieval algorithm for SAR

    NASA Technical Reports Server (NTRS)

    Shi, Jian-Cheng; Dozier, Jeff

    1992-01-01

    The objectives of this study are: (1) to evaluate the backscattering signals response to snow wetness; and (2) to develop an algorithm for snow wetness measurement using C-band polarimetric synthetic aperture radar (SAR). In hydrological investigations, modeling and forecasting of snowmelt runoff requires information about snowpack properties and their spatial variability. In particular, timely measurement of snow parameters is needed for operational hydrology. The liquid water content of snowpack is one of the important parameters. Active microwave sensors are highly sensitive to liquid water in the snowpack because of the large dielectric contrast between ice and water in the microwave spectrum. They are not affected by weather and have a spatial resolution compatible with the topographic variation in alpine regions. However, a quantitative algorithm for retrieval snow wetness has not yet been developed.

  15. 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.

  16. 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

  17. Retrievals of Cloud Droplet Size from the RSP Data: Validation Using in Situ Measurements

    NASA Technical Reports Server (NTRS)

    Alexandrov, Mikhail D.; Cairns, Brian; Sinclair, Kenneth; Wasilewski, Andrzej P.; Ziemba, Luke; Crosbie, Ewan; Hair, John; Hu, Yongxiang; Hostetler, Chris; Stamnes, Snorre

    2016-01-01

    We present comparisons of cloud droplet size distributions retrieved from the Research Scanning Polarimeter (RSP) data with correlative in situ measurements made during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). This field experiment was based at St. Johns airport, Newfoundland, Canada with the latest deployment in May - June 2016. RSP was onboard the NASA C-130 aircraft together with an array of in situ and other remote sensing instrumentation. The RSP is an along-track scanner measuring polarized and total reflectances in9 spectral channels. Its unique high angular resolution allows for characterization of liquid water droplet size using the rainbow structure observed in the polarized reflectances in the scattering angle range between 135 and 165 degrees. A parametric fitting algorithm applied to the 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 us to retrieve the droplet size distribution (DSD) itself. The latter is important in the case of clouds with complex structure, which results in multi-modal DSDs. During NAAMES the aircraft performed a number of flight patterns specifically designed for comparison of remote sensing retrievals and in situ measurements. These patterns consisted of two flight segments above the same straight ground track. One of these segments was flown above clouds allowing for remote sensing measurements, while the other was at the cloud top where cloud droplets were sampled. We compare the DSDs retrieved from the RSP data with in situ measurements made by the Cloud Droplet Probe (CDP). The comparisons show generally good agreement with deviations explainable by the position of the aircraft within cloud and by presence of additional cloud layers in RSP view that do not contribute to the in situ DSDs. In the

  18. 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

  19. Marine boundary layer cloud property retrievals from high-resolution ASTER observations: case studies and comparison with Terra MODIS

    NASA Astrophysics Data System (ADS)

    Werner, Frank; Wind, Galina; Zhang, Zhibo; Platnick, Steven; Di Girolamo, Larry; Zhao, Guangyu; Amarasinghe, Nandana; Meyer, Kerry

    2016-12-01

    A research-level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. It is based on the operational MODIS algorithm. This paper documents the technical details of this algorithm and evaluates the retrievals for selected marine boundary layer cloud scenes through comparisons with the operational MODIS Data Collection 6 (C6) cloud product. The newly developed, ASTER-specific cloud masking algorithm is evaluated through comparison with an independent algorithm reported in [Zhao and Di Girolamo(2006)]. To validate and evaluate the cloud optical thickness (τ) and cloud effective radius (reff) from ASTER, the high-spatial-resolution ASTER observations are first aggregated to the same 1000 m resolution as MODIS. Subsequently, τaA and reff, aA retrieved from the aggregated ASTER radiances are compared with the collocated MODIS retrievals. For overcast pixels, the two data sets agree very well with Pearson's product-moment correlation coefficients of R > 0.970. However, for partially cloudy pixels there are significant differences between reff, aA and the MODIS results which can exceed 10 µm. Moreover, it is shown that the numerous delicate cloud structures in the example marine boundary layer scenes, resolved by the high-resolution ASTER retrievals, are smoothed by the MODIS observations. The overall good agreement between the research-level ASTER results and the operational MODIS C6 products proves the feasibility of MODIS-like retrievals from ASTER reflectance measurements and provides the basis for future studies concerning the scale dependency of satellite observations and three-dimensional radiative effects.

  20. 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.

  1. 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

  2. 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).

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. Retrievals of Ice Cloud Microphysical Properties of Deep Convective Systems using Radar Measurements

    NASA Astrophysics Data System (ADS)

    Tian, J.; Dong, X.; Xi, B.; Wang, J.; Homeyer, C. R.

    2015-12-01

    This study presents innovative algorithms for retrieving ice cloud microphysical properties of Deep Convective Systems (DCSs) using Next-Generation Radar (NEXRAD) reflectivity and newly derived empirical relationships from aircraft in situ measurements in Wang et al. (2015) during the Midlatitude Continental Convective Clouds Experiment (MC3E). With composite gridded NEXRAD radar reflectivity, four-dimensional (space-time) ice cloud microphysical properties of DCSs are retrieved, which is not possible from either in situ sampling at a single altitude or from vertical pointing radar measurements. For this study, aircraft in situ measurements provide the best-estimated ice cloud microphysical properties for validating the radar retrievals. Two statistical comparisons between retrieved and aircraft in situ measured ice microphysical properties are conducted from six selected cases during MC3E. For the temporal-averaged method, the averaged ice water content (IWC) and median mass diameter (Dm) from aircraft in situ measurements are 0.50 g m-3 and 1.51 mm, while the retrievals from radar reflectivity have negative biases of 0.12 g m-3 (24%) and 0.02 mm (1.3%) with correlations of 0.71 and 0.48, respectively. For the spatial-averaged method, the IWC retrievals are closer to the aircraft results (0.51 vs. 0.47 g m-3) with a positive bias of 8.5%, whereas the Dm retrievals are larger than the aircraft results (1.65 mm vs. 1.51 mm) with a positive bias of 9.3%. The retrieved IWCs decrease from ~0.6 g m-3 at 5 km to ~0.15 g m-3 at 13 km, and Dm values decrease from ~2 mm to ~0.7 mm at the same levels. In general, the aircraft in situ measured IWC and Dm values at each level are within one standard derivation of retrieved properties. Good agreements between microphysical properties measured from aircraft and retrieved from radar reflectivity measurements indicate the reasonable accuracy of our retrievals.

  11. 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.

  12. 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.

  13. 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)

  14. 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

  15. Ground Based Retrievals of Cloud Properties for Liquid, Glaciated and Mixed Phase Conditions

    NASA Astrophysics Data System (ADS)

    Mishra, S.; Mitchell, D. L.; Deslover, D.

    2008-12-01

    Cirrus cloud microphysical data from recent field programs using new instruments tend to minimize or remove the problem of ice particle shattering. These measurements suggest that in most instances, the anomalously high concentrations of small ice crystals reported in earlier in situ measurements are absent. These earlier measurements of small crystals indicated an abrupt increase in concentration for ice particle lengths around 60 μm and smaller, resulting in a "small particle mode." In addition, a new methodology we developed for satellite and ground-based remote sensing indicates that this small mode is either absent or lower in amplitude than earlier aircraft measurements have indicated. Remote sensing results presented on our website (http://www.dri.edu/Projects/Mitchell/) address both anvil and in situ synoptic cirrus in tropical and mid-latitude regions. This leads us to hypothesize that, in general, ice particle size distributions (PSD) are monomodal. This study applies this hypothesis to mixed phase clouds to estimate the ice water path (IWP) and liquid water path (LWP). When our remote sensing method indicates the cloud PSD as bimodal, the small mode is attributed to liquid water while the large mode is attributed to ice particles. Data from Mixed-Phase Arctic Cloud Experiment (M-PACE), conducted at the north slope of Alaska (winter 2004), have been used to test this new method for retrieving the LWP and IWP. The framework of the retrieval algorithm consists of the modified anomalous diffraction approximation (MADA) for mixed phase cloud optical properties, a radar reflectivity-ice microphysics relationship and a temperature-dependent ice PSD scheme. Cloud thermal emission measurements made by the ground-based Atmospheric Emitted Radiance Interferometer (AERI) yield information on the total water path (TWP) while reflectivity measurements from the Millimeter Cloud Radar (MMCR) in combination with the ice PSD slope are used to derive the IWP. This

  16. 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.

  17. 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.

  18. 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).

  19. Global Retrieval of Cloud Particle Size and Optical Thickness Using ISCCP Data

    NASA Technical Reports Server (NTRS)

    Welch, Ronald M.; Han, Qingyuan

    1998-01-01

    The primary thrust of this investigation is to develop an algorithm to retrieve cloud particle sizes using ISCCP data. The research under this grant has been successful in obtaining initial results of global distribution of ice-particle sizes. Further research about possible problems caused by nonsphericity of ice particle sizes is currently underway. An algorithm of retrieving ice-cloud particle sizes using ISCCP CX data has been developed. The first survey of ice-particle size in a near-global scale has been completed. Comparison with in situ measurements of ice crystal sizes during FIRE I shows good agreement. The initial results show that the global mean size of ice crystals (De) is about 60 micron. This result is consistent with the range of in situ measurements all over the world if definitions of effective particle size are unified (see next section). The survey also shows that there is no distinct difference of ice-particle sizes between continental and maritime ice-clouds. There are many different definitions of effective particle size used in ice-cloud research. Simple comparisons between values of in situ measurement and satellite remote sensing are misleading and may lead to incorrect conclusions. We reviewed different definitions of effective particle sizes used in the literature and compared their relative magnitudes.

  20. Retrieval of Cirrus Cloud Radiative and Backscattering Properties Using Combined Lidar and Infrared Radiometer (LIRAD) Measurements

    SciTech Connect

    Comstock, Jennifer M.; Sassen, Kenneth

    2001-10-01

    A method for retrieval of cirrus macrophysical and radiative properties using combined ruby lidar and infrared radiometer measurements is explained in detail. The retrieval algorithm includes estimation of a variable backscatter-to-extinction ratio for each lidar profile, which accounts for changes in cloud microphysical properties with time. The technique also utilizes a correlated K distribution radiative transfer model,where absorption coefficients K have been tabulated specifically for the bandwidth and filter function of the infrared radiometer. The radiative transfer model allows for estimation of infrared emission due to atmospheric water vapor,ozone,and carbon dioxide, which is essential for deriving cirrus radiative properties. Also described is an improved technique for estimation of upwelling IR radiation that is emitted by the surface of the earth and reflected by the cloud into the radiometer field-of-view. Derived cirrus cloud properties include base and top height and temperature, visible optical depth, emittance, backscatter-to-extinction ratio, and extinction-to-absorption ratio. The purpose of this algorithm is to facilitate the analysis of the extensive high-cloud dataset obtained at the University of Utah, Facility for Atmospheric Remote Sensing in Salt Lake City, UT. To illustrate the method, a cirrus case study is presented.

  1. 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.

  2. [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.

  3. 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.

  4. 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.

  5. Testing remote sensing on artificial observations: impact of drizzle and 3-D cloud structure on effective radius retrievals

    NASA Astrophysics Data System (ADS)

    Zinner, T.; Wind, G.; Platnick, S.; Ackerman, A. S.

    2010-10-01

    Remote sensing of cloud effective particle size with passive sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS) is an important tool for cloud microphysical studies. As a measure of the radiatively relevant droplet size, effective radius can be retrieved with different combinations of visible through shortwave and midwave infrared channels. In practice, retrieved effective radii from these combinations can be quite different. This difference is perhaps indicative of different penetration depths and path lengths for the spectral reflectances used. In addition, operational liquid water cloud retrievals are based on the assumption of a relatively narrow distribution of droplet sizes; the role of larger precipitation particles in these distributions is neglected. Therefore, possible explanations for the discrepancy in some MODIS spectral size retrievals could include 3-D radiative transport effects, including sub-pixel cloud inhomogeneity, and/or the impact of drizzle formation. For three cloud cases the possible factors of influence are isolated and investigated in detail by the use of simulated cloud scenes and synthetic satellite data: marine boundary layer cloud scenes from large eddy simulations (LES) with detailed microphysics are combined with Monte Carlo radiative transfer calculations that explicitly account for the detailed droplet size distributions as well as 3-D radiative transfer to simulate MODIS observations. The operational MODIS optical thickness and effective radius retrieval algorithm is applied to these and the results are compared to the given LES microphysics. We investigate two types of marine cloud situations each with and without drizzle from LES simulations: (1) a typical daytime stratocumulus deck at two times in the diurnal cycle and (2) one scene with scattered cumulus. Only small impact of drizzle formation on the retrieved domain average and on the differences between the three effective radius retrievals is noticed

  6. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2008-02-01

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

  8. 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.

  9. 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.

  10. Statistical retrieval of thin liquid cloud microphysical properties using ground-based infrared and microwave observations

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

    In this article, liquid water cloud microphysical properties are retrieved by a combination of microwave and infrared ground-based observations. Clouds containing liquid water are frequently occurring in most 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 is enhanced for thin clouds (liquid water path, LWP <100 g/m2), which makes accurate retrieval information of the cloud properties crucial. Due to large relative errors in retrieving low LWP values from observations in the microwave domain and a high sensitivity for infrared methods when the LWP is low, a synergistic retrieval based on a neural network approach is built to estimate both LWP and cloud effective radius (reff). These statistical retrievals can be applied without high computational demand but imply constraints like prior information on cloud phase and cloud layering. The neural network retrievals are able to retrieve LWP and reff for thin clouds with a mean relative error of 9% and 17%, respectively. This is demonstrated using synthetic observations of a microwave radiometer (MWR) and a spectrally highly resolved infrared interferometer. The accuracy and robustness of the synergistic retrievals is confirmed by a low bias in a radiative closure study for the downwelling shortwave flux, even for marginally invalid scenes. Also, broadband infrared radiance observations, in combination with the MWR, have the potential to retrieve LWP with a higher accuracy than a MWR-only retrieval.

  11. 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

    1995-01-01

    During the second phase project year we have made progress in the development and refinement of surface temperature retrieval algorithms and in product generation. More specifically, we have accomplished the following: (1) acquired a new advanced very high resolution radiometer (AVHRR) data set for the Beaufort Sea area spanning an entire year; (2) acquired additional along-track scanning radiometer(ATSR) data for the Arctic and Antarctic now totalling over eight months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) developed cloud masking procedures for both AVHRR and ATSR; (6) generated a two-week bi-polar global area coverage (GAC) set of composite images from which IST is being estimated; (7) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; and (8) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and special sensor microwave imager (SSM/I).

  12. Dust aerosol impact on the retrieval of cloud top height from satellite observations of CALIPSO, CloudSat and MODIS

    NASA Astrophysics Data System (ADS)

    Wang, Wencai; Sheng, Lifang; Dong, Xu; Qu, Wenjun; Sun, Jilin; Jin, Hongchun; Logan, Timothy

    2017-02-01

    Dust aerosol effect on the retrievals of dusty cloud top height (DCTH) are analyzed over Northwest China using cloud products from MODerate Resolution Imaging Spectroradiometer (MODIS) on Aqua, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat for the Spring season of March-May over the years 2007-2011. An excellent agreement is found between CloudSat and CALIPSO derived DCTHs for all cloud types, suggesting that the effect of dust aerosols plays a small role in DCTHs determination for lidar and radar measurements. However, the presence of dust aerosols greatly affects the retrievals of DCTHs for MODIS compared with pure clouds and the active sensors derived results. The differences of DCTHs retrieving from CloudSat and MODIS range from -2.30 to 6.8 km. Likewise, the differences of DCTHs retrieving from CALIPSO and MODIS range from -2.66 to 6.78 km. In addition, the results show that the differences in DCTHs for active and passive sensors are dependent on cloud type. On the whole, dust aerosols have the largest effect on cloud top heights (CTH) retrieved of nimbostratus (Ns), followed by altocumulus (Ac) and altostratus (As), the last is cirrus (Ci) over Northwest China. Our results also indicate that the accuracy of MODIS-derived retrievals reduces accompanied with a decrease of height.

  13. 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.

  14. 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.

  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. A Slow Retrieval Algorithm for Satellite and Surface Based Instruments

    NASA Technical Reports Server (NTRS)

    Weaver, C.; Flittner, D.

    2007-01-01

    We present results of a retrieval algorithm for satellite and ground based instruments using the Arizona radiative transfer code. A state vector describing the atmospheric and surface condition is iteratively modified until the calculated radiances match the observed values. Elements of the state vector include: aerosol concentrations, radius, optical properties, mass-weighted altitudes, chlorophyll concentration and wind speed. While computationally expensive, many assumptions used in other retrieval algorithms are not invoked. We present co-located retrievals for MODIS, SEAWIFS and nearby AERONET sites. MODIS AQUA and SEA WIFS: Ten MODIS (.412 - 2.110 microns) and eight SEA WIFS (.412-.865 microns) radiances (.412-.865 microns) include channels where aerosols absorb and reflect radiation. We focus on retrieving bio-mass burning aerosols that are advected over open ocean. Since chlorophyll absorbs at frequencies where black carbon absorbs, our retrieval algorithm accounts for chlorophyll absorption by simultaneously retrieving both aerosol and chlorophyll amount. Our retrieved chlorophyll concentrations are similar to those from the Ocean Color Group. AERONET: Both Almucantar and Principle plane radiances are used to retrieve the state of the atmosphere and ocean conditions. Our retrieved aerosol size distributions and optical properties are consistent with the aerosol inversions from the AERONET group.

  17. Visualizing and improving the robustness of phase retrieval algorithms

    DOE PAGES

    Tripathi, Ashish; Leyffer, Sven; Munson, Todd; ...

    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. 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.

  19. 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.

  20. 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

  1. 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.

  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

    During the first half of our second project year we have accomplished the following: (1) acquired a new AVHRR data set for the Beaufort Sea area spanning an entire year; (2) acquired additional ATSR data for the Arctic and Antarctic now totaling over seven months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; (6) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and SSM/I; and (7) continued work on compositing GAC data for coverage of the entire Arctic and Antarctic. During the second half of the year we will continue along these same lines, and will undertake a detailed validation study of the AVHRR and ATSR retrievals using LEADEX and the Beaufort Sea year-long data. Cloud masking methods used for the AVHRR will be modified for use with the ATSR. Methods of blending in situ and satellite-derived surface temperature data sets will be investigated.

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

  5. 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

  6. 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.

  7. 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.

  8. 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

  9. 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

  10. A comparison of cloud albedo and cloud fraction retrievals from long-term surface based shortwave radiation measurements

    NASA Astrophysics Data System (ADS)

    Xie, Y.; Liu, Y.

    2013-12-01

    Cloud albedo and cloud fraction are intimately related, and separate retrievals often suffer from mutual contamination of errors. Here a new analytical approach is first presented to simultaneously retrieve cloud albedo and cloud fraction from the total and direct SW radiative fluxes measured at the surface and thus eliminate the potential mutual error contamination. The approach is then validated by comparing to the solutions calculated by applying the Rapid Radiative Transfer Model (RRTM) to a variety of combinations of given values of cloud albedo and cloud fraction. We finally apply the approach to obtain cloud albedo and cloud fraction from the long-term surface radiation measurements at the ARM SGP site, and evaluated the newly derived data against the existing ARM products. The potential of using the same framework for evaluating SCMs are also explored.

  11. Impact of Three-Dimensional Radiative Effects on Satellite Retrievals of Cloud Droplet Sizes

    NASA Technical Reports Server (NTRS)

    Marshak, Alexander; Platnick, Steven; Varnai, Tamas; Wen, Guoyong; Cahalan, Robert F.

    2006-01-01

    There are several dozen papers that study the effects of cloud horizontal inhomogeneity on the retrievals of cloud optical thickness, but only a few of them deal with cloud droplet sizes. This paper is one of the first comprehensive attempts to fill this gap: It takes a close theoretical look at the radiative effects of cloud 3-D structure in retrievals of droplet effective radii. Under some general assumptions, it was found that ignoring subpixel (unresolved) variability produces a negative bias in the retrieved effective radius, while ignoring cloud inhomogeneity at scales larger than a pixel scale (resolved variability), on the contrary, leads to overestimation of the domain average droplet size. The theoretical results are illustrated with examples from Large Eddy Simulations (LES) of cumulus (Cu) and stratocumulus (Sc) cloud fields. The analysis of cloud drop size distributions retrieved from both LES fields confirms that ignoring shadowing in 1-D retrievals results in substantial overestimation of effective radii which is more pronounced for broken Cu than for Sc clouds. Collocated measurements of broken Cu clouds by Moderate Resolution Imaging Spectrometer (MODIS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) are used to check simulations and theory with observations. The analysis of ASTER and MODIS data and associated derived products recommends against blindly using retrieved effective radii for broken cloud fields, especially if one wants to relate aerosol amounts to cloud droplet sizes.

  12. 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...

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

    DOE PAGES

    Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; ...

    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

  14. 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.

  15. Retrieval of cloud ice water path using SAPHIR on board Megha-Tropiques over the tropical ocean

    NASA Astrophysics Data System (ADS)

    Piyush, Durgesh Nandan; Goyal, Jayesh; Srinivasan, J.

    2017-04-01

    The SAPHIR sensor onboard Megha-Tropiques (MT) measures the earth emitted radiation at frequencies near the water vapor absorption band. SAPHIR operates in six frequencies ranging from 183 ± 0.1 to 183 ± 11 GHz. These frequencies have been used to retrieve cloud ice water path (IWP) at a very high resolution. A method to retrieve IWP over the Indian ocean region is attempted in this study. The study is in two parts, in first part a radiative transfer based simulation is carried out to give an insight of using SAPHIR frequency channels for IWP retrieval, in the next part the real observations of SAPHIR and TRMM-TMI was used for IWP retrieval. The concurrent observations of SAPHIR brightness temperatures (Tbs) and TRMM TMI IWP were used in the development of the retrieval algorithm. An Eigen Vector analysis was done to identify weight of each channel in retrieving IWP; following this a two channel regression based algorithm was developed. The SAPHIR channels which are away from the water vapor absorption band were used to avoid possible water vapor contamination. When the retrieval is compared with independent test dataset, it gives a correlation of 0.80 and RMSE of 3.5%. SAPHIR derived IWP has been compared with other available global IWP products such as TMI, MSPPS, CloudSat and GPM-GMI qualitatively as well as quantitatively. PDF comparison of SAPHIR derived IWP found to have good agreement with CloudSat. Zonal mean comparison with recently launched GMI shows the strength of this algorithm.

  16. Distributed data organization and parallel data retrieval methods for huge laser scanner point clouds

    NASA Astrophysics Data System (ADS)

    Hongchao, Ma; Wang, Zongyue

    2011-02-01

    This paper proposes a novel method for distributed data organization and parallel data retrieval from huge volume point clouds generated by airborne Light Detection and Ranging (LiDAR) technology under a cluster computing environment, in order to allow fast analysis, processing, and visualization of the point clouds within a given area. The proposed method is suitable for both grid and quadtree data structures. As for distribution strategy, cross distribution of the dataset would be more efficient than serial distribution in terms of non-redundant datasets, since a dataset is more uniformly distributed in the former arrangement. However, redundant datasets are necessary in order to meet the frequent need of input and output operations in multi-client scenarios: the first copy would be distributed by a cross distribution strategy while the second (and later) would be distributed by an iterated exchanging distribution strategy. Such a distribution strategy would distribute datasets more uniformly to each data server. In data retrieval, a greedy algorithm is used to allocate the query task to a data server, where the computing load is lightest if the data block needing to be retrieved is stored among multiple data servers. Experiments show that the method proposed in this paper can satisfy the demands of frequent and fast data query.

  17. 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.

  18. Aerosol direct effect retrieval over clouds from space-borne passive hyperspectral measurements (Invited)

    NASA Astrophysics Data System (ADS)

    de Graaf, M.; Tilstra, L.; Stammes, P.

    2013-12-01

    A novel approach for the retrieval of the aerosol direct radiative effect (DRE) over clouds will be presented, which is independent of aerosol parameters estimates. The direct effect at the top of the atmosphere (TOA) of aerosols over clouds can be estimated using hyperspectral reflectance measurements from space-borne spectrometers, when the equivalent aerosol-unpolluted cloud scene reflectance spectrum is known. For smoke over clouds the cloud parameters can be estimated from the shortwave infrared (SWIR), where the absorption of the small smoke particles becomes sufficiently small. Using precomputed tables of cloud reflectance spectra, the unpolluted cloud scene spectrum can then be simulated and compared to the real measured polluted cloud scene reflectance spectrum. The UV-radiation absorption by the smoke will lead to a difference between the measured and simulated spectra, which is proportional to the aerosol DRE at TOA. Aerosol microphysical assumptions and retrievals are avoided by modeling only the aerosol-free scene spectra, all the aerosol effects are in the reflectance measurements. The method works especially well for cloud scenes, which can be simulated relatively accurately. An algorithm was developed to derive the aerosol DRE over marine clouds, using the space-borne spectrometer SCIAMACHY, which produced shortwave reflectance spectra (from 240 to 1700 nm contiguously) from 2002 till 2012. These are ideally suited to study the effect of aerosols on the shortwave spectrum. However, since aerosols in general do not have high resolution spectral features, the algorithm can be adapted to suit data from any combination of instruments that measures UV, visible and SWIR reflectances simultaneously. Examples include OMI and MODIS, flying in the A-Train constellation, and TROPOMI, on the future Sentinel 5 precursor mission, combined with NOAA's NPP VIIRS. This would produce aerosol DRE estimates with unprecedented accuracy and spatial resolution. The

  19. 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.

  20. 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

  1. Retrievals and Comparisons of Various MODIS-Spectrum Inferred Water Cloud Droplet Effective Radii

    NASA Technical Reports Server (NTRS)

    Fu-Lung, Chang; Minnis, Patrick; Lin, Bin; Sunny, Sun-Mack; Khaiyer, Mandana M.

    2007-01-01

    Cloud droplet effective radius retrievals from different Aqua MODIS nearinfrared channels (2.1- micrometer, 3.7- micrometer, and 1.6- micrometer) show considerable differences even among most confident QC pixels. Both Collection 004 and Collection 005 MOD06 show smaller mean effective radii at 3.7- micrometer wavelength than at 2.1- micrometer and 1.6- micrometer wavelengths. Differences in effective radius retrievals between Collection 004 and Collection 005 may be affected by cloud top height/temperature differences, which mainly occur for optically thin clouds. Changes in cloud top height and temperature for thin clouds have different impacts on the effective radius retrievals from 2.1- micrometer, 3.7- micrometer, and 1.6- micrometer channels. Independent retrievals (this study) show, on average, more consistency in the three effective radius retrievals. This study is for Aqua MODIS only.

  2. 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

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

    PubMed

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

    2012-07-24

    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 (N(d)) retrievals to improve predicted below-cloud aerosol mass and number concentrations. The assimilation, which uses an adjoint aerosol activation parameterization, improves agreement with independent N(d) 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.

  5. 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.

  6. Ground return signal simulation and retrieval algorithm of spaceborne integrated path DIAL for CO2 measurements

    NASA Astrophysics Data System (ADS)

    Liu, Bing-Yi; Wang, Jun-Yang; Liu, Zhi-Shen

    2014-11-01

    Spaceborne integrated path differential absorption (IPDA) lidar is an active-detection system which is able to perform global CO2 measurement with high accuracy of 1ppmv at day and night over ground and clouds. To evaluate the detection performance of the system, simulation of the ground return signal and retrieval algorithm for CO2 concentration are presented in this paper. Ground return signals of spaceborne IPDA lidar under various ground surface reflectivity and atmospheric aerosol optical depths are simulated using given system parameters, standard atmosphere profiles and HITRAN database, which can be used as reference for determining system parameters. The simulated signals are further applied to the research on retrieval algorithm for CO2 concentration. The column-weighted dry air mixing ratio of CO2 denoted by XCO2 is obtained. As the deviations of XCO2 between the initial values for simulation and the results from retrieval algorithm are within the expected error ranges, it is proved that the simulation and retrieval algorithm are reliable.

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

    DOE PAGES

    Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; ...

    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

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. Impact of Cloud Model Microphysics on Passive Microwave Retrievals of Cloud Properties. Part II: Uncertainty in Rain, Hydrometeor Structure, and Latent Heating Retrievals

    NASA Astrophysics Data System (ADS)

    Seo, Eun-Kyoung; Biggerstaff, Michael I.

    2006-07-01

    The impact of model microphysics on the retrieval of cloud properties based on passive microwave observations was examined using a three-dimensional, nonhydrostatic, adaptive-grid cloud model to simulate a mesoscale convective system over ocean. Two microphysical schemes, based on similar bulk two-class liquid and three-class ice parameterizations, were used to simulate storms with differing amounts of supercooled cloud water typical of both the tropical oceanic environment, in which there is little supercooled cloud water, and midlatitude continental environments in which supercooled cloud water is more plentiful. For convective surface-level rain rates, the uncertainty varied between 20% and 60% depending on which combination of passive and active microwave observations was used in the retrieval. The uncertainty in surface rain rate did not depend on the microphysical scheme or the parameter settings except for retrievals over stratiform regions based on 85-GHz brightness temperatures TB alone or 85-GHz TB and radar reflectivity combined. In contrast, systematic differences in the treatment of the production of cloud water, cloud ice, and snow between the parameterization schemes coupled with the low correlation between those properties and the passive microwave TB examined here led to significant differences in the uncertainty in retrievals of those cloud properties and latent heating. The variability in uncertainty of hydrometeor structure and latent heating associated with the different microphysical parameterizations exceeded the inherent variability in TB cloud property relations. This was true at the finescales of the cloud model as well as at scales consistent with satellite footprints in which the inherent variability in TB cloud property relations are reduced by area averaging.

  13. 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.

  14. 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.

  15. 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%.

  16. 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.

  17. The effect of spatial resolution upon cloud optical property retrievals. I - Optical thickness

    NASA Technical Reports Server (NTRS)

    Feind, Rand E.; Christopher, Sundar A.; Welch, Ronald M.

    1992-01-01

    High spectral and spatial resolution Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery is used to study the effects of spatial resolution upon fair weather cumulus cloud optical thickness retrievals. As a preprocessing step, a variation of the Gao and Goetz three-band ratio technique is used to discriminate clouds from the background. The combination of the elimination of cloud shadow pixels and using the first derivative of the histogram allows for accurate cloud edge discrimination. The data are progressively degraded from 20 m to 960 m spatial resolution. The results show that retrieved cloud area increases with decreasing spatial resolution. The results also show that there is a monotonic decrease in retrieved cloud optical thickness with decreasing spatial resolution. It is also demonstrated that the use of a single, monospectral reflectance threshold is inadequate for identifying cloud pixels in fair weather cumulus scenes and presumably in any inhomogeneous cloud field. Cloud edges have a distribution of reflectance thresholds. The incorrect identification of cloud edges significantly impacts the accurate retrieval of cloud optical thickness values.

  18. Improved OSIRIS NO2 retrieval algorithm: description and validation

    NASA Astrophysics Data System (ADS)

    Sioris, Christopher E.; Rieger, Landon A.; Lloyd, Nicholas D.; Bourassa, Adam E.; Roth, Chris Z.; Degenstein, Douglas A.; Camy-Peyret, Claude; Pfeilsticker, Klaus; Berthet, Gwenaël; Catoire, Valéry; Goutail, Florence; Pommereau, Jean-Pierre; McLinden, Chris A.

    2017-03-01

    A new retrieval algorithm for OSIRIS (Optical Spectrograph and Infrared Imager System) nitrogen dioxide (NO2) profiles is described and validated. The algorithm relies on spectral fitting to obtain slant column densities of NO2, followed by inversion using an algebraic reconstruction technique and the SaskTran spherical radiative transfer model (RTM) to obtain vertical profiles of local number density. The validation covers different latitudes (tropical to polar), years (2002-2012), all seasons (winter, spring, summer, and autumn), different concentrations of nitrogen dioxide (from denoxified polar vortex to polar summer), a range of solar zenith angles (68.6-90.5°), and altitudes between 10.5 and 39 km, thereby covering the full retrieval range of a typical OSIRIS NO2 profile. The use of a larger spectral fitting window than used in previous retrievals reduces retrieval uncertainties and the scatter in the retrieved profiles due to noisy radiances. Improvements are also demonstrated through the validation in terms of bias reduction at 15-17 km relative to the OSIRIS operational v3.0 algorithm. The diurnal variation of NO2 along the line of sight is included in a fully spherical multiple scattering RTM for the first time. Using this forward model with built-in photochemistry, the scatter of the differences relative to the correlative balloon NO2 profile data is reduced.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  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. Implementing Agglomerative Hierarchic Clustering Algorithms for Use in Document Retrieval.

    ERIC Educational Resources Information Center

    Voorhees, Ellen M.

    1986-01-01

    Describes a computerized information retrieval system that uses three agglomerative hierarchic clustering algorithms--single link, complete link, and group average link--and explains their implementations. It is noted that these implementations have been used to cluster a collection of 12,000 documents. (LRW)

  6. Study of phase retrieval algorithm from partially coherent light

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  7. 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.

  8. 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.

  9. Developments of aerosol retrieval algorithm for Geostationary Environmental Monitoring Spectrometer (GEMS) and the retrieval accuracy test

    NASA Astrophysics Data System (ADS)

    KIM, M.; Kim, J.; Jeong, U.; Ahn, C.; Bhartia, P. K.; Torres, O.

    2013-12-01

    A scanning UV-Visible spectrometer, the GEMS (Geostationary Environment Monitoring Spectrometer) onboard the GEO-KOMPSAT2B (Geostationary Korea Multi-Purpose Satellite) is planned to be launched in geostationary orbit in 2018. The GEMS employs hyper-spectral imaging with 0.6 nm resolution to observe solar backscatter radiation in the UV and Visible range. In the UV range, the low surface contribution to the backscattered radiation and strong interaction between aerosol absorption and molecular scattering can be advantageous in retrieving aerosol optical properties such as aerosol optical depth (AOD) and single scattering albedo (SSA). By taking the advantage, the OMI UV aerosol algorithm has provided information on the absorbing aerosol (Torres et al., 2007; Ahn et al., 2008). This study presents a UV-VIS algorithm to retrieve AOD and SSA from GEMS. The algorithm is based on the general inversion method, which uses pre-calculated look-up table with assumed aerosol properties and measurement condition. To obtain the retrieval accuracy, the error of the look-up table method occurred by the interpolation of pre-calculated radiances is estimated by using the reference dataset, and the uncertainties about aerosol type and height are evaluated. Also, the GEMS aerosol algorithm is tested with measured normalized radiance from OMI, a provisional data set for GEMS measurement, and the results are compared with the values from AERONET measurements over Asia. Additionally, the method for simultaneous retrieve of the AOD and aerosol height is discussed.

  10. 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

  11. Ice Cloud Optical Depth Retrievals from CRISM Multispectral Images

    NASA Astrophysics Data System (ADS)

    Klassen, David R.

    2014-11-01

    One set of data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) on the Mars Reconnaissance Orbiter (MRO) is the multispectral survey that measured the visible-through-near-infrared reflectance of the entire planet of Mars at specific wavelengths. The spectral data from several sols were be combined to create multi-spectral maps of Mars. In addition, these maps can be zonally averaged to create a latitude vs season image cube of Mars. All of these image cubes can be fit using a full radiative transfer modeling in order to retrieve ice cloud optical depth—as a map for one of the particular dates, or as a latitude vs season record.To compare the data radiative transfer models, a measure of the actual surface reflectance is needed. There are several possible ways to model this, such as using a nearby region that is "close enough" or by looking at the same region at different times and assuming one of those is the actual surface reflectance. Neither of these is ideal for trying to process an entire map of data because aerosol clouds can be fairly extensive both spatially and temporally.Another technique is to assume that the surface can be modeled as a linear combination of a limited set of intrinsic spectral endmembers. A combination of Principal Component Analysis (PCA) and Target Transformation (TT) has been used to recover just such a set of spectral endmember shapes. The coefficients in the linear combination then become additional fitting parameters in the radiative transfer modeling of each map point—all parameters are adjusted until the RMS error between the model and the data is minimized. Based on previous work, the PCA of martian spectral image cubes is relatively consistent regardless of season, implying the underlying, large-scale, intrinsic traits that dominate the data variance are relatively constant. These overall PCA results can then be used to create a single set of spectral endmembers that can be used for any of the data

  12. Optically-Thin Cirrus Cloud Radiance Bias in Satellite Radiometric Sea Surface Temperature Retrieval

    NASA Astrophysics Data System (ADS)

    Marquis, J. W.; Bogdanoff, A.; Campbell, J. R.; Cummings, J. A.; Westphal, D. L.; Smith, N. J.; Zhang, J.

    2015-12-01

    Satellite-based retrievals of sea surface temperature (SST) are highly sensitive to the optical properties of the atmosphere, including clouds. Cloudy pixels, in particular, are screened in order to avoid potential retrieval contamination in their presence. Due to the lack of continuous in-situ observations across the global oceans, though, SSTs calculated from satellite radiances are often the most practical way to obtain a sufficient global estimate. Cloud clearing techniques struggle to flag cloudy retrievals from passive radiometers with cloud optical depths less than 0.3. These optically-thin clouds are almost exclusively cirrus. Corresponding radiance biases associated with unscreened cirrus can be significant due to their inherently cold cloud top temperatures. To investigate frequency of such cloud contamination, 1-km SST observations over tropical oceans (±30° latitude) from the Moderate Resolution Imaging Spectroradiometer aboard NASA's Aqua satellite (AQUA-MODIS) are collocated with cloud profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument aboard NASA's CALIPSO satellite. Potential SST biases based on radiance retrievals for MODIS, AVHRR and VIIRS are solved using a radiative transfer model (RTM) with integrated cirrus cloud properties of varying cloud top height and optical depth. Frequencies of occurrence for each cloud top height and optical depth from the collocated CALIOP/AQUA-MODIS data are superimposed upon the conceptual cloud SST radiance bias models to estimate potential net bias. Using the CALIPSO-MODIS collocations, clouds of all types are found to be present in the best quality AQUA-MODIS Level-2 data at a frequency of 25%, with over 90% of those clouds being cirrus. The RTM simulations suggest that when cirrus are present, the mean SST bias due only to cloud is over 0.6°C over the tropical oceans.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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

  18. Tomographic retrieval of cloud liquid water fields from a single scanning microwave radiometer aboard a moving platform – Part 2: Observation system simulation experiments

    SciTech Connect

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

    2010-07-01

    Part 1 of this research concluded that many conditions of the 2003 Wakasa Bay experiment were not optimal for the purpose of tomographic retrieval. Part 2 (this paper) then aims to find possible improvements to the mobile cloud tomography method using observation system simulation experiments. We demonstrate that the incorporation of the L{sub 1} norm total variation regularization in the tomographic retrieval algorithm better reproduces discontinuous structures than the widely used L{sub 2} norm Tikhonov regularization. The simulation experiments reveal that a typical ground-based mobile setup substantially outperforms an airborne one because the ground-based setup usually moves slower and has greater contrast in microwave brightness between clouds and the background. It is shown that, as expected, the error in the cloud tomography retrievals increases monotonically with both the radiometer noise level and the uncertainty in the estimate of background brightness temperature. It is also revealed that a lower speed of platform motion or a faster scanning radiometer results in more scan cycles and more overlap between the swaths of successive scan cycles, both of which help to improve the retrieval accuracy. The last factor examined is aircraft height. It is found that the optimal aircraft height is 0.5 to 1.0 km above the cloud top. To summarize, this research demonstrates the feasibility of tomographically retrieving the spatial structure of cloud liquid water using current microwave radiometric technology and provides several general guidelines to improve future field-based studies of cloud tomography.

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. Hubble Space Telescope characterized by using phase-retrieval algorithms.

    PubMed

    Fienup, J R; Marron, J C; Schulz, T J; Seldin, J H

    1993-04-01

    We describe several results characterizing the Hubble Space Telescope from measured point spread functions by using phase-retrieval algorithms. The Cramer-Rao lower bounds show that point spread functions taken well out of focus result in smaller errors when aberrations are estimated and that, for those images, photon noise is not a limiting factor. Reconstruction experiments with both simulated and real data show that the calculation of wave-front propagation by the retrieval algorithms must be performed with a multiple-plane propagation rather than a simple fast Fourier transform to ensure the high accuracy required. Pupil reconstruction was performed and indicates a misalignment of the optical axis of a camera relay telescope relative to the main telescope. After we accounted for measured spherical aberration in the relay telescope, our estimate of the conic constant of the primary mirror of the HST was - 1.0144.

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. Obtaining the Grobner Initialization for the Ground Flash Fraction Retrieval Algorithm

    NASA Technical Reports Server (NTRS)

    Solakiewicz, R.; Attele, R.; Koshak, W.

    2011-01-01

    At optical wavelengths and from the vantage point of space, the multiple scattering cloud medium obscures one's view and prevents one from easily determining what flashes strike the ground. However, recent investigations have made some progress examining the (easier, but still difficult) problem of estimating the ground flash fraction in a set of N flashes observed from space In the study by Koshak, a Bayesian inversion method was introduced for retrieving the fraction of ground flashes in a set of flashes observed from a (low earth orbiting or geostationary) satellite lightning imager. The method employed a constrained mixed exponential distribution model to describe the lightning optical measurements. To obtain the optimum model parameters, a scalar function of three variables (one of which is the ground flash fraction) was minimized by a numerical method. This method has formed the basis of a Ground Flash Fraction Retrieval Algorithm (GoFFRA) that is being tested as part of GOES-R GLM risk reduction.

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

    NASA Astrophysics Data System (ADS)

    Crow, W. T.; Wagner, W.

    2009-12-01

    Applying basic data assimilation techniques to the evaluation of remote-sensing products can clarify the impact of sensor design issues on the value of retrievals for hydrologic applications. For instance, the impact of incidence angle on the accuracy of radar surface soil moisture retrievals is largely unknown due to discrepancies in theoretical backscatter models as well as limitations in the availability of sufficiently-extensive ground-based soil moisture observations for validation purposes. In this presentation we will describe and apply a data assimilation evaluation technique for scatterometer-based surface soil moisture retrievals that does not require ground-based soil moisture observations to examine the sensitivity of retrieval skill to variations in incidence angle. Past results with the approach have shown that it is capable of detecting relative variations in the correlation between anomalies in remotely-sensed surface soil moisture retrievals and ground-truth soil moisture measurements. Application of the evaluation approach to the TU-Wien WARP5.0 European Space Radar (ERS) soil moisture data set over two regional-scale (~1000 km) domains in the Southern United States indicates a relative reduction in anomaly correlation-based skill of between 20% and 30% when moving between the lowest (< 26 degrees) and highest ERS (> 50 degrees) incidence angle ranges. These changes in anomaly-based correlation provide a useful proxy for relative variations in the value of estimates for data assimilation applications and can therefore be used to inform the design of appropriate retrieval algorithms. For example, the observed sensitivity of correlation-based skill with incidence angle is in approximate agreement with soil moisture retrieval uncertainty predictions made using the WARP5.0 backscatter model. However, the coupling of a bare soil backscatter model with the so-called "vegetation water cloud" model is shown to generally over-estimate the impact of

  11. 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

  12. A cloud masking algorithm for EARLINET lidar systems

    NASA Astrophysics Data System (ADS)

    Binietoglou, Ioannis; Baars, Holger; D'Amico, Giuseppe; Nicolae, Doina

    2015-04-01

    Cloud masking is an important first step in any aerosol lidar processing chain as most data processing algorithms can only be applied on cloud free observations. Up to now, the selection of a cloud-free time interval for data processing is typically performed manually, and this is one of the outstanding problems for automatic processing of lidar data in networks such as EARLINET. In this contribution we present initial developments of a cloud masking algorithm that permits the selection of the appropriate time intervals for lidar data processing based on uncalibrated lidar signals. The algorithm is based on a signal normalization procedure using the range of observed values of lidar returns, designed to work with different lidar systems with minimal user input. This normalization procedure can be applied to measurement periods of only few hours, even if no suitable cloud-free interval exists, and thus can be used even when only a short period of lidar measurements is available. Clouds are detected based on a combination of criteria including the magnitude of the normalized lidar signal and time-space edge detection performed using the Sobel operator. In this way the algorithm avoids misclassification of strong aerosol layers as clouds. Cloud detection is performed using the highest available time and vertical resolution of the lidar signals, allowing the effective detection of low-level clouds (e.g. cumulus humilis). Special attention is given to suppress false cloud detection due to signal noise that can affect the algorithm's performance, especially during day-time. In this contribution we present the details of algorithm, the effect of lidar characteristics (space-time resolution, available wavelengths, signal-to-noise ratio) to detection performance, and highlight the current strengths and limitations of the algorithm using lidar scenes from different lidar systems in different locations across Europe.

  13. 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

  14. Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters . Part 2; Aerosols

    NASA Technical Reports Server (NTRS)

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

    2016-01-01

    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 sub grid 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

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. Improving Satellite Quantitative Precipitation Estimation Using GOES-Retrieved Cloud Optical Depth

    SciTech Connect

    Stenz, Ronald; Dong, Xiquan; Xi, Baike; Feng, Zhe; Kuligowski, Robert J.

    2016-02-01

    To address significant gaps in ground-based radar coverage and rain gauge networks in the U.S., geostationary satellite quantitative precipitation estimates (QPEs) such as the Self-Calibrating Multivariate Precipitation Retrievals (SCaMPR) can be used to fill in both the spatial and temporal gaps of ground-based measurements. Additionally, with the launch of GOES-R, the temporal resolution of satellite QPEs may be comparable to that of Weather Service Radar-1988 Doppler (WSR-88D) volume scans as GOES images will be available every five minutes. However, while satellite QPEs have strengths in spatial coverage and temporal resolution, they face limitations particularly during convective events. Deep Convective Systems (DCSs) have large cloud shields with similar brightness temperatures (BTs) over nearly the entire system, but widely varying precipitation rates beneath these clouds. Geostationary satellite QPEs relying on the indirect relationship between BTs and precipitation rates often suffer from large errors because anvil regions (little/no precipitation) cannot be distinguished from rain-cores (heavy precipitation) using only BTs. However, a combination of BTs and optical depth (τ) has been found to reduce overestimates of precipitation in anvil regions (Stenz et al. 2014). A new rain mask algorithm incorporating both τ and BTs has been developed, and its application to the existing SCaMPR algorithm was evaluated. The performance of the modified SCaMPR was evaluated using traditional skill scores and a more detailed analysis of performance in individual DCS components by utilizing the Feng et al. (2012) classification algorithm. SCaMPR estimates with the new rain mask applied benefited from significantly reduced overestimates of precipitation in anvil regions and overall improvements in skill scores.

  1. 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.

  2. 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

  3. 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.

  4. Retrieval of volcanic ash and ice cloud physical properties together with gas concentration from IASI measurements using the AVL model

    NASA Astrophysics Data System (ADS)

    Kochenova, S.; De Mazière, M.; Kumps, N.; Vandenbussche, S.; Kerzenmacher, T.

    2013-05-01

    Observation and tracking of volcanic aerosols are important for preventing possible aviation hazards and determining the influence of aerosols on climate. The useful information primary includes the concentration, particle size and altitude of aerosol load. Moreover, volcanic eruptions are usually accompanied by strong emissions of SO2 and enhanced concentrations of H2O in the atmosphere. Volcanic ash particles can also catalyze the formation of ice clouds by serving as cloud nuclei. Hyperspectral infrared sounders, such as IASI (Infrared Atmospheric Sounding Interferometer), have proven to be powerful tools for capturing volcanic aerosol and ice cloud signatures and enhanced volcanic gas concentrations. Information on atmospheric constituents is extracted from such hyperspectral measurements with the help of radiative transfer (RT) codes capable of solving both direct and inverse RT problems. We will demonstrate the retrieval of aerosol and ice cloud physical properties together with gas concentration from IASI measurements with the help of the AVL RT model. AVL is one of the 'code combination packages' which are becoming more and more popular in the scientific domain. It consists of several codes, each of which handles a specific set of physics-related tasks. The codes function smoothly as a whole due to the use of a special interface. AVL is perfectly suitable (i) to model the propagation of UV-visible-IR radiation through a coupled atmosphere-surface system for a wide range of atmospheric, spectral and geometrical conditions; and (ii) to retrieve vertical gas profiles and aerosol concentration through the use of its embedded retrieval algorithm on the basis of an optimal estimation method (OEM). The retrievals are performed for IASI measurements (radiance, Level 1C product) carried out over Eyjafjallajökull volcano, Iceland, in April 2010.

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. Post-processing to remove residual clouds from aerosol optical depth retrieved using the Advanced Along Track Scanning Radiometer

    NASA Astrophysics Data System (ADS)

    Sogacheva, Larisa; Kolmonen, Pekka; Virtanen, Timo H.; Rodriguez, Edith; Saponaro, Giulia; de Leeuw, Gerrit

    2017-02-01

    Cloud misclassification is a serious problem in the retrieval of aerosol optical depth (AOD), which might considerably bias the AOD results. On the one hand, residual cloud contamination leads to AOD overestimation, whereas the removal of high-AOD pixels (due to their misclassification as clouds) leads to underestimation. To remove cloud-contaminated areas in AOD retrieved from reflectances measured with the (Advanced) Along Track Scanning Radiometers (ATSR-2 and AATSR), using the ATSR dual-view algorithm (ADV) over land or the ATSR single-view algorithm (ASV) over ocean, a cloud post-processing (CPP) scheme has been developed at the Finnish Meteorological Institute (FMI) as described in Kolmonen et al. (2016). The application of this scheme results in the removal of cloud-contaminated areas, providing spatially smoother AOD maps and favourable comparison with AOD obtained from the ground-based reference measurements from the AERONET sun photometer network. However, closer inspection shows that the CPP also removes areas with elevated AOD not due to cloud contamination, as shown in this paper. We present an improved CPP scheme which better discriminates between cloud-free and cloud-contaminated areas. The CPP thresholds have been further evaluated and adjusted according to the findings. The thresholds for the detection of high-AOD regions (> 60 % of the retrieved pixels should be high-AOD (> 0.6) pixels), and cloud contamination criteria for low-AOD regions have been accepted as the default for AOD global post-processing in the improved CPP. Retaining elevated AOD while effectively removing cloud-contaminated pixels affects the resulting global and regional mean AOD values as well as coverage. Effects of the CPP scheme on both spatial and temporal variation for the period 2002-2012 are discussed. With the improved CPP, the AOD coverage increases by 10-15 % with respect to the existing scheme. The validation versus AERONET shows an improvement of the correlation

  10. Cloud cover estimation optical package: New facility, algorithms and techniques

    NASA Astrophysics Data System (ADS)

    Krinitskiy, Mikhail

    2017-02-01

    Short- and long-wave radiation is an important component of surface heat budget over sea and land. For estimating them accurate observations of the cloud cover are needed. While massively observed visually, for building accurate parameterizations cloud cover needs also to be quantified using precise instrumental measurements. Major disadvantages of the most of existing cloud-cameras are associated with their complicated design and inaccuracy of post-processing algorithms which typically result in the uncertainties of 20% to 30% in the camera-based estimates of cloud cover. The accuracy of these types of algorithm in terms of true scoring compared to human-observed values is typically less than 10%. We developed new generation package for cloud cover estimating, which provides much more accurate results and also allows for measuring additional characteristics. New algorithm, namely SAIL GrIx, based on routine approach, also developed for this package. It uses the synthetic controlling index ("grayness rate index") which allows to suppress the background sunburn effect. This makes it possible to increase the reliability of the detection of the optically thin clouds. The accuracy of this algorithm in terms of true scoring became 30%. One more approach, namely SAIL GrIx ML, we have used to increase the cloud cover estimating accuracy is the algorithm that uses machine learning technique along with some other signal processing techniques. Sun disk condition appears to be a strong feature in this kind of models. Artificial Neural Networks type of model demonstrates the best quality. This model accuracy in terms of true scoring increases up to 95,5%. Application of a new algorithm lets us to modify the design of the optical sensing package and to avoid the use of the solar trackers. This made the design of the cloud camera much more compact. New cloud-camera has already been tested in several missions across Atlantic and Indian oceans on board of IORAS research vessels.

  11. CDRD and PNPR passive microwave precipitation retrieval algorithms: verification study over Africa and Southern Atlantic

    NASA Astrophysics Data System (ADS)

    Panegrossi, Giulia; Casella, Daniele; Cinzia Marra, Anna; Petracca, Marco; Sanò, Paolo; Dietrich, Stefano

    2015-04-01

    The ongoing NASA/JAXA Global Precipitation Measurement mission (GPM) requires the full exploitation of the complete constellation of passive microwave (PMW) radiometers orbiting around the globe for global precipitation monitoring. In this context the coherence of the estimates of precipitation using different passive microwave radiometers is a crucial need. We have developed two different passive microwave precipitation retrieval algorithms: one is the Cloud Dynamics Radiation Database algorithm (CDRD), a physically ¬based Bayesian algorithm for conically scanning radiometers (i.e., DMSP SSMIS); the other one is the Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for cross¬-track scanning radiometers (i.e., NOAA and MetOp¬A/B AMSU-¬A/MHS, and NPP Suomi ATMS). The algorithms, originally created for application over Europe and the Mediterranean basin, and used operationally within the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF, http://hsaf.meteoam.it), have been recently modified and extended to Africa and Southern Atlantic for application to the MSG full disk area. The two algorithms are based on the same physical foundation, i.e., the same cloud-radiation model simulations as a priori information in the Bayesian solver and as training dataset in the neural network approach, and they also use similar procedures for identification of frozen background surface, detection of snowfall, and determination of a pixel based quality index of the surface precipitation retrievals. In addition, similar procedures for the screening of not ¬precipitating pixels are used. A novel algorithm for the detection of precipitation in tropical/sub-tropical areas has been developed. The precipitation detection algorithm shows a small rate of false alarms (also over arid/desert regions), a superior detection capability in comparison with other widely used screening algorithms, and it is applicable

  12. 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.

  13. 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

  14. Optical Algorithm for Cloud Shadow Detection Over Water

    DTIC Science & Technology

    2013-02-01

    contextual information to detect cumulus clouds and cloud shadows in Landsat data," Int. J. Remote Sens., vol. 3, no. l.pp. 51-62,1982. [12] T...Betendes, S. K. Sengupta, R. M. Welch, B. A. Wielicki, and M. Navar, " Cumulus cloud base height estimation from high spatial resolution rr-r 740 IEEE...REPORT DATE (DD-MM-YYYY) 05-02-2013 2. REPORT TYPE Journal Article 3. DATES COVERED (From ■ To) 4. TITLE AND SUBTITLE Optical Algorithm for Cloud

  15. Phase function effects for ocean color retrieval algorithm

    NASA Astrophysics Data System (ADS)

    Du, KePing; Lee, Zhongping

    2010-10-01

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

  16. 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.

  17. 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

  18. 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

  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. 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.

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

  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. Movable aperture lensless transmission microscopy: a novel phase retrieval algorithm.

    PubMed

    Faulkner, H M L; Rodenburg, J M

    2004-07-09

    We propose an iterative phase retrieval method that uses a series of diffraction patterns, measured only in intensity, to solve for both amplitude and phase of the image wave function over a wide field of view and at wavelength-limited resolution. The new technique requires an aperture that is scanned to two or more positions over the object wave function. A simple implementation of the method is modeled and demonstrated, showing how the algorithm uses overlapping data in real space to resolve ambiguities in the solution. The technique opens up the possibility of practical transmission lensless microscopy at subatomic resolution using electrons, x rays, or nuclear particles.

  4. Directional, horizontal inhomogeneities of cloud optical thickness fields retrieved from ground-based and airbornespectral imaging

    NASA Astrophysics Data System (ADS)

    Schäfer, Michael; Bierwirth, Eike; Ehrlich, André; Jäkel, Evelyn; Werner, Frank; Wendisch, Manfred

    2017-02-01

    Clouds exhibit distinct horizontal inhomogeneities of their optical and microphysical properties, which complicate their realistic representation in weather and climate models. In order to investigate the horizontal structure of cloud inhomogeneities, 2-D horizontal fields of optical thickness (τ) of subtropical cirrus and Arctic stratus are investigated with a spatial resolution of less than 10 m. The 2-D τ-fields are derived from (a) downward (transmitted) solar spectral radiance measurements from the ground beneath four subtropical cirrus and (b) upward (reflected) radiances measured from aircraft above 10 Arctic stratus. The data were collected during two field campaigns: (a) Clouds, Aerosol, Radiation, and tuRbulence in the trade wind regime over BArbados (CARRIBA) and (b) VERtical Distribution of Ice in Arctic clouds (VERDI). One-dimensional and 2-D autocorrelation functions, as well as power spectral densities, are derived from the retrieved τ-fields. The typical spatial scale of cloud inhomogeneities is quantified for each cloud case. Similarly, the scales at which 3-D radiative effects influence the radiance field are identified. In most of the investigated cloud cases considerable cloud inhomogeneities with a prevailing directional structure are found. In these cases, the cloud inhomogeneities favour a specific horizontal direction, while across this direction the cloud is of homogeneous character. The investigations reveal that it is not sufficient to quantify horizontal cloud inhomogeneities using 1-D inhomogeneity parameters; 2-D parameters are necessary.

  5. Web multimedia information retrieval using improved Bayesian algorithm.

    PubMed

    Yu, Yi-Jun; Chen, Chun; Yu, Yi-Min; Lin, Huai-Zhong

    2003-01-01

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

  6. Improvements to the OMI O2-O2 operational cloud algorithm and comparisons with ground-based radar-lidar observations

    NASA Astrophysics Data System (ADS)

    Pepijn Veefkind, J.; de Haan, Johan F.; Sneep, Maarten; Levelt, Pieternel F.

    2016-12-01

    The OMI (Ozone Monitoring Instrument on board NASA's Earth Observing System (EOS) Aura satellite) OMCLDO2 cloud product supports trace gas retrievals of for example ozone and nitrogen dioxide. The OMCLDO2 algorithm derives the effective cloud fraction and effective cloud pressure using a DOAS (differential optical absorption spectroscopy) fit of the O2-O2 absorption feature around 477 nm. A new version of the OMI OMCLDO2 cloud product is presented that contains several improvements, of which the introduction of a temperature correction on the O2-O2 slant columns and the updated look-up tables have the largest impact. Whereas the differences in the effective cloud fraction are on average limited to 0.01, the differences of the effective cloud pressure can be up to 200 hPa, especially at cloud fractions below 0.3. As expected, the temperature correction depends on latitude and season. The updated look-up tables have a systematic effect on the cloud pressure at low cloud fractions. The improvements at low cloud fractions are very important for the retrieval of trace gases in the lower troposphere, for example for nitrogen dioxide and formaldehyde. The cloud pressure retrievals of the improved algorithm are compared with ground-based radar-lidar observations for three sites at mid-latitudes. For low clouds that have a limited vertical extent the comparison yields good agreement. For higher clouds, which are vertically extensive and often contain several layers, the satellite retrievals give a lower cloud height. For high clouds, mixed results are obtained.

  7. 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

  8. 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.

  9. 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.

  10. Retrieving ice cloud properties by using a fast infrared radiative transfer model

    NASA Astrophysics Data System (ADS)

    Wang, C.; Yang, P.; Heidinger, A. K.; Platnick, S. E.; Baum, B. A.

    2010-12-01

    A new fast infrared radiative transfer (RT) model based on pre-computed look-up tables (LUTs) including the LUTs for emissivity function and cloud effective temperature is proposed. This model can be applied to the simulation of upward radiance (or brightness temperature) at 8.5, 11.0 and 12.0 μm at the top of the atmosphere (TOA) under cloudy-sky conditions. Optical depths of Atmospheric layers resulting from gaseous absorption are derived from the correlated-K distribution (CKD) method. The cloud reflection and transmission functions are computed from the discrete ordinates radiative transfer model (DISORT). In addition to the LUTs of reflection and transmission functions of cloud in traditional RT models, the LUTs of emissivity and effective temperature are also included to improve the accuracy. Generally speaking, for an atmosphere containing a single ice cloud layer with small optical thickness (i.e., less than 5.0), the brightness temperature differences (BTDs) between the fast model and DISORT results are approximately less than 0.1K, whereas the BTDs are less than 0.02K when the ice cloud optical thickness is larger than 5.0. Moreover, with the fast RT model, cloud optical and microphysical properties of ice clouds are retrieved from MODIS and CALIPSO observations and the MERRA reanalysis data. The present retrievals are compared with the MODIS operational cloud products (MYD06).

  11. An evaluation of CALIOP/CALIPSO's aerosol-above-cloud detection and retrieval capability over North America

    NASA Astrophysics Data System (ADS)

    Kacenelenbogen, M.; Redemann, J.; Vaughan, M. A.; Omar, A. H.; Russell, P. B.; Burton, S.; Rogers, R. R.; Ferrare, R. A.; Hostetler, C. A.

    2014-01-01

    Assessing the accuracy of the aerosol-above-cloud (AAC) properties derived by CALIOP (the Cloud-Aerosol Lidar with Orthogonal Polarization) is challenged by the shortage of accurate global validation measurements. We have used measurements of aerosol vertical profiles from the NASA Langley airborne High Spectral Resolution Lidar (HSRL-1) in 86 CALIOP-coincident flights to evaluate CALIOP AAC detection, classification, and retrieval. Our study shows that CALIOP detects ~23% of the HSRL-detected AAC. According to our CALIOP-HSRL data set, the majority of AAC aerosol optical depth (AOD) values are < 0.1 at 532 nm over North America. Our analyses show that the standard CALIOP retrieval algorithm substantially underestimates the occurrence frequency of AAC when optical depths are less than ~0.02. Those aerosols with low AOD values can still have a consequent radiative forcing effect depending on the underlying cloud cover and overlying aerosol absorption properties. We find essentially no correlation between CALIOP and HSRL AAC AOD (R2 = 0.27 and N = 151). We show that the CALIOP underestimation of AAC is mostly due to tenuous aerosol layers with backscatter less than the CALIOP detection threshold. The application of an alternate CALIOP AAC retrieval method (depolarization ratio) to our data set yields very few coincident cases. We stress the need for more extensive suborbital CALIOP validation campaigns to acquire a process-level understanding of AAC implications and further evaluate CALIOP's AAC detection and retrieval capability, especially over the ocean and in different parts of the world where AAC are more frequently observed and show higher values of AOD.

  12. Retrieval of ammonia abundances and cloud opacities on Jupiter from Voyager IRIS spectra

    NASA Technical Reports Server (NTRS)

    Conrath, B. J.; Gierasch, P. J.

    1986-01-01

    Gaseous ammonia abundances and cloud opacities are retrieved from Voyager IRIS 5- and 45-micron data on the basis of a simplified atmospheric model and a two-stream radiative transfer approximation, assuming a single cloud layer with 680-mbar base pressure and 0.14 gas scale height. Brightness temperature measurements obtained as a function of emission angle from selected planetary locations are used to verify the model and constrain a number of its parameters.

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

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

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

  14. Impact of Cloud Model Microphysics on Passive Microwave Retrievals of Cloud Properties. Part I: Model Comparison Using EOF Analyses

    NASA Astrophysics Data System (ADS)

    Biggerstaff, Michael I.; Seo, Eun-Kyoung; Hristova-Veleva, Svetla M.; Kim, Kwang-Yul

    2006-07-01

    The impact of model microphysics on the relationships among hydrometeor profiles, latent heating, and derived satellite microwave brightness temperatures TB have been examined using a nonhydrostatic, adaptive-grid cloud model to simulate a mesoscale convective system over water. Two microphysical schemes (each employing three-ice bulk parameterizations) were tested for two different assumptions in the number of ice crystals assumed to be activated at 0°C to produce simulations with differing amounts of supercooled cloud water. The model output was examined using empirical orthogonal function (EOF) analysis, which provided a quantitative framework in which to compare the simulations. Differences in the structure of the vertical anomaly patterns were related to physical processes and attributed to different approaches in cloud microphysical parameterizations in the two schemes. Correlations between the first EOF coefficients of cloud properties and TB at frequencies associated with the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) showed additional differences between the two parameterization schemes that affected the relationship between hydrometeors and TB. Classified in terms of TB, the microphysical schemes produced significantly different mean vertical profiles of cloud water, cloud ice, snow, vertical velocity, and latent heating. The impact of supercooled cloud water on the 85-GHz TB led to a 15% variation in mean convective rain mass at the surface. The variability in mean profiles produced by the four simulations indicates that the retrievals of cloud properties, especially latent heating, based on TMI frequencies are dependent on the particular microphysical parameterizations used to construct the retrieval database.

  15. 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.

  16. A statistical retrieval algorithm for root zone soil moisture

    NASA Astrophysics Data System (ADS)

    Lindau, Ralf; Simmer, Clemens

    2014-11-01

    An algorithm for the estimation of root zone soil moisture is presented. Global fields of the soil moisture within the uppermost metre of soil are derived with a temporal resolution of 10 days. For calibration, long-term soil moisture observations from the former Soviet Union are used. The variance of the measurements is largely dominated by the spatial variability of the long-term mean soil moisture, while the temporal variability gives comparatively small contribution. Consequently, the algorithm is organised into two steps. The first step concentrates on the retrieval of the spatial variance of the long-term means, which comprises more than 85% of the total soil moisture variability. A major part of the spatial variance can be explained by four easily available fields: the climatological precipitation, land use, soil texture, and terrain slope. The second step of the algorithm is dedicated to the local temporal variability. This part of variability is recovered by using passive microwave data from scanning multichannel microwave radiometre (SMMR) supported by monthly averaged fields of air temperature and precipitation. The 6-GHz channel of SMMR is shown to be severely disturbed by radio frequency interference, so that information from the 10-GHz channel is used instead. The algorithm provides reasonable soil moisture fields which is confirmed by a comparison with independent measurements from Illinois.

  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. 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

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. Retrieving microphysical properties and air motion of cirrus clouds based on the doppler moments method using cloud radar

    NASA Astrophysics Data System (ADS)

    Zhong, Lingzhi; Liu, Liping; Deng, Min; Zhou, Xiuji

    2012-05-01

    Radar parameters including radar reflectivity, Doppler velocity, and Doppler spectrum width were obtained from Doppler spectrum moments. The Doppler spectrum moment is the convolution of both the particle spectrum and the mean air vertical motion. Unlike strong precipitation, the motion of particles in cirrus clouds is quite close to the air motion around them. In this study, a method of Doppler moments was developed and used to retrieve cirrus cloud microphysical properties such as the mean air vertical velocity, mass-weighted diameter, effective particle size, and ice content. Ice content values were retrieved using both the Doppler spectrum method and classic Z-IWC (radar reflectivity-ice water content) relationships; however, the former is a more reasonable method.

  4. The correction for multiple scattering of the lidar retrieving in thin clouds

    NASA Astrophysics Data System (ADS)

    Melnikova, Irina; Vasilyev, Alexander; Samulenkov, Dmitriy; Sapunov, Maxim; Tagaev, Vladislav

    2017-02-01

    The lidar sounding in the cloudy atmosphere needs accounting the multiple scattering. The standard approach for the retrieval of optical parameters and morphology of aerosol particles might be not sufficient. Here the theoretical analyti cal and numerical methods for calculation of multiple scattering contributions in the backscattered lidar signal are used. The optical thickness of clouds that provokes a distinct multiply scattered light is determined. The possible correction as subtraction of the multiple scattered part from registered signal is proposed for clouds optically thicker than 4. The routine processing is possible for corrected the lidar signal if cloud optically thicker than 4 or without correction if cloud is opt ically thinner than 4. Considered observational data obtained in St. Petersburg lidar station appeared thin enough for application the standard procedure without correction. Optical parameters in and out of cloud are obtained.

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. Cloud ice water content retrieved from the CALIOP space-based lidar

    NASA Astrophysics Data System (ADS)

    Avery, Melody; Winker, David; Heymsfield, Andrew; Vaughan, Mark; Young, Stuart; Hu, Yongxiang; Trepte, Charles

    2012-03-01

    Ice water content (IWC) profiles are derived from retrievals of optical extinction from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite lidar, using a parameterization derived from particle probe measurements acquired during several aircraft field campaigns. With more than five years of data now available, CALIOP IWC is well suited for characterization of the climate-sensitive upper troposphere/lower stratosphere where reliable global IWC measurements are needed to reduce climate model uncertainty. We describe CALIOP IWC and compare it with global satellite-based and regional airborne IWC measurements made during August 2007. IWC distributions in a convective cloud sampled during the Tropical Clouds, Chemistry, Composition and Climate experiment show temperature-dependent differences between in situ measured IWC, IWC retrieved from CloudSat and CALIOP, and IWC parameterized from the airborne Cloud Physics Lidar (CPL) 532 nm volume extinction coefficients. At temperatures above -50°C the CALIOP IWC retrieval indicates less cloud ice than the other instruments, due to signal attenuation and screening for horizontally-oriented ice crystals. Above 12 km where temperatures drop below -50°C CALIOP compares well with in situ IWC measurements. In situ measurements are limited above 12 km, and more cold-temperature comparisons are needed. Global zonal in-cloud IWC averages at altitudes above 9 km show that CloudSat IWC is roughly an order of magnitude higher than CALIOP IWC, consistent with a higher detection threshold. When averaged to the vertical resolution characteristic of Microwave Limb Sounder (MLS), global zonal averages of CALIOP and MLS IWC were found to agree to about +/-50%.

  10. 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.

  11. Improved modeling of cloudy-sky actinic flux using satellite cloud retrievals

    NASA Astrophysics Data System (ADS)

    Ryu, Young-Hee; Hodzic, Alma; Descombes, Gael; Hall, Samuel; Minnis, Patrick; Spangenberg, Douglas; Ullmann, Kirk; Madronich, Sasha

    2017-02-01

    Clouds play a critical role in modulating tropospheric radiation and thus photochemistry. We develop a methodology for calculating the vertical distribution of tropospheric ultraviolet (300-420 nm) actinic fluxes using satellite cloud retrievals and a radiative transfer model. We demonstrate that our approach can accurately reproduce airborne-measured actinic fluxes from the 2013 Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign as a case study. The results show that the actinic flux is reduced below moderately thick clouds with increasing cloud optical depth and can be enhanced by a factor of 2 above clouds. Inside clouds, the actinic flux can be enhanced by up to 2.4 times in the upper part of clouds or reduced up to 10 times in the lower parts of clouds. Our study suggests that the use of satellite-derived actinic fluxes as input to chemistry-transport models can improve the accuracy of photochemistry calculations.

  12. 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.

  13. 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.

  14. The 3D Radiative Effects of Clouds in Aerosol Retrieval: Can we Remove Them?

    SciTech Connect

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

    2009-09-30

    We outline a new method, called the ratio method, developed to retrieve aerosol optical depth (AOD) under broken cloud conditions and present validation results from sensitivity and case studies. Results of the sensitivity study demonstrate that the ratio method, which exploits ratios of reflectances in the visible spectral range, has the potential for accurate AOD retrievals under different observational conditions and random errors in input data. Also, we examine the performance of the ratio method using aircraft data collected during the Cloud and Land Surface Interaction Campaign (CLASIC) and the Cumulus Humilis Aerosol Processing Study (CHAPS). Results of the case study suggest that the ratio method has the ability to retrieve AOD from multi-spectral aircraft observations of the reflected solar radiation.

  15. Improvement of retrieval algorithms for severe air pollution

    NASA Astrophysics Data System (ADS)

    Mukai, Sonoyo; Sano, Itaru; Nakata, Makiko

    2016-10-01

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

  16. 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.

  17. 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.

  18. [The comparison of algorithms on the CT image retrieval of Xinjiang local liver hydatid disease].

    PubMed

    Yan, Chuanbo; Hamit, Murat; Li, Li; Chen, Jianjun; Hu, Yahting; Kong, Dewei; Zhou, Jingjing

    2013-10-01

    Xinjiang local liver hydatid disease is an infectious parasitic disease in Xinjiang pastoral areas. Based on the image features, selecting the appropriate distance algorithms to retrieve the image quickly and accurately, different distance algorithms have been induced in this area, which can greatly assist the doctors to early detect, diagnose and cure the liver hydatid disease. This paper compared the performance of different distance algorithms to retrieve the image when using the liver hydatid disease medical image texture features. The results showed that: for the liver hydatid disease medical images retrieval based on gray level cocurrence matrix (GLCM) texture features, the Mahalanobis distance algorithm is superior to other distance algorithms.

  19. 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)

  20. 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.

  1. 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.

  2. 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.

  3. a Review of Point Clouds Segmentation and Classification Algorithms

    NASA Astrophysics Data System (ADS)

    Grilli, E.; Menna, F.; Remondino, F.

    2017-02-01

    Today 3D models and point clouds are very popular being currently used in several fields, shared through the internet and even accessed on mobile phones. Despite their broad availability, there is still a relevant need of methods, preferably automatic, to provide 3D data with meaningful attributes that characterize and provide significance to the objects represented in 3D. Segmentation is the process of grouping point clouds into multiple homogeneous regions with similar properties whereas classification is the step that labels these regions. The main goal of this paper is to analyse the most popular methodologies and algorithms to segment and classify 3D point clouds. Strong and weak points of the different solutions presented in literature or implemented in commercial software will be listed and shortly explained. For some algorithms, the results of the segmentation and classification is shown using real examples at different scale in the Cultural Heritage field. Finally, open issues and research topics will be discussed.

  4. 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

  5. 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.

  6. Comparison of Ice Cloud Particle Sizes Retrieved From Satellite Data Derived From In Situ Measurements

    NASA Technical Reports Server (NTRS)

    Han, Qingyuan; Rossow, William B.; Chou, Joyce; Welch, Ronald M.

    1997-01-01

    Cloud microphysical parameterizations have attracted a great deal of attention in recent years due to their effect on cloud radiative properties and cloud-related hydrological processes in large-scale models. The parameterization of cirrus particle size has been demonstrated as an indispensable component in the climate feedback analysis. Therefore, global-scale, long-term observations of cirrus particle sizes are required both as a basis of and as a validation of parameterizations for climate models. While there is a global scale, long-term survey of water cloud droplet sizes (Han et al. 1994), there is no comparable study for cirrus ice crystals. In this paper a near-global survey of cirrus ice crystal sizes is conducted using ISCCP satellite data analysis. The retrieval scheme uses phase functions based upon hexagonal crystals calculated by a ray tracing technique. The results show that global mean values of D(e) are about 60 micro-m. This study also investigates the possible reasons for the significant difference between satellite retrieved effective radii (approx. 60 micro-m) and aircraft measured particle sizes (approx. 200 micro-m) during the FIRE I IFO experiment. They are (1) vertical inhomogeneity of cirrus particle sizes; (2) lower limit of the instrument used in aircraft measurements; (3) different definitions of effective particle sizes; and (4) possible inappropriate phase functions used in satellite retrieval.

  7. 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

  8. 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

  9. 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

  10. 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.

  11. Improvement of OMI ozone profile retrievals by simultaneously fitting polar mesospheric clouds

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

    The presence of polar mesospheric clouds (PMCs) at summer high latitudes could affect the retrieval of ozone profiles using backscattered ultraviolet (UV) measurements. PMC-induced errors in ozone profile retrievals from Ozone Monitoring Instrument (OMI) backscattered UV measurements are investigated through comparisons with Microwave Limb Sounder (MLS) ozone measurements. This comparison demonstrates that the presence of PMCs leads to systematic biases for pressures smaller than 6 hPa; 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 wavelength, 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 vertical optical depth (POD) of 10-4 to -20 % with 10-3 POD at backscattering angles. 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 can be improved by including the PMC in the forward-model calculation and retrieval.

  12. 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.

  13. 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.

  14. 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.

  15. Observed Precipitation Vertical Structure to Support Assumptions used in Satellite Rainfall Retrieval Algorithms

    NASA Astrophysics Data System (ADS)

    Williams, C. R.

    2015-12-01

    Due to a limited number of measurements made on a single space-craft, satellite rainfall retrieval algorithms are under-constrained and often make assumptions about the vertical structure of precipitation. For example, an algorithm may assume the rain rate is constant with height below the freezing level. In order to help support or validate the assumptions used in NASA Global Precipitation Measurement (GPM) satellite rainfall retrieval algorithms, this study investigates the vertical structure of raindrop size distribution (DSD) parameters derived from vertically pointing ground based Doppler radars during GPM field campaigns MC3E (Mid-latitude Continental Convective Clouds Experiment), IFloodS (Iowa Flood Studies), and IPHEX (Integrated Precipitation and Hydrology EXperiment). The three estimated DSD parameters represent the scale and shape of the raindrop size distribution using the parameters: normalized number concentration Nw, mass spectrum mean diameter Dm, and mass spectrum effective variance νm = σm2 / Dm2(mass spectrum variance / mean diameter squared). A vertical pattern in the DSD parameters was often observed during stratiform rain. While the reflectivity was nearly uniform with height, the normalized number concentration (Nw) and mean diameter (Dm) had opposite vertical structures with Nw decreasing and Dm increasing from the melting layer down to the surface. Interestingly, the mass spectrum effective variance (νm) decreased as the raindrops fall indicating that the DSD was evolving into a narrower effective mass spectrum with a loss of small and/or large raindrops. This vertical structure of DSD parameters suggests breakup, coalescence, and evaporation were occurring in the vertical column. In summary, the analysis of vertically pointing radar data during GPM ground validation field campaigns suggests that the net result of breakup, coalescence, and evaporation during stratiform rain appear in the vertical structure of DSD parameters Nw, Dm, and

  16. A Ground Flash Fraction Retrieval Algorithm for GLM

    NASA Technical Reports Server (NTRS)

    Koshak, William J.

    2010-01-01

    A Bayesian inversion method is introduced for retrieving the fraction of ground flashes in a set of N lightning observed by a satellite lightning imager (such as the Geostationary Lightning Mapper, GLM). An exponential model is applied as a physically reasonable constraint to describe the measured lightning optical parameter distributions. Population statistics (i.e., the mean and variance) are invoked to add additional constraints to the retrieval process. The Maximum A Posteriori (MAP) solution is employed. The approach is tested by performing simulated retrievals, and retrieval error statistics are provided. The approach is feasible for N greater than 2000, and retrieval errors decrease as N is increased.

  17. 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

  18. The Role of Cloud Contamination, Aerosol Layer Height and Aerosol Model in the Assessment of the OMI Near-UV Retrievals Over the Ocean

    NASA Technical Reports Server (NTRS)

    Gasso, Santiago; Torres, Omar

    2016-01-01

    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 less than 0.3, 30% for AOD greater than 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 approximately less than 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 (less than 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

  19. 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.

  20. 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

  1. Retrievals of Vertical Air Motion from the HIAPER Cloud Radar during CSET

    NASA Astrophysics Data System (ADS)

    Schwartz, M. C.; Ghate, V. P.; Vivekanandan, J.; Tsai, P.; Ellis, S. M.

    2015-12-01

    Marine boundary layer cumulus and stratocumulus clouds are significant factors in the Earth's climate system and hence need to be accurately represented in Global Climate Model (GCM) simulations. One feature germane to these clouds, and where GCMs encounter difficulty, is the transition from stratocumulus- to cumulus-capped marine boundary layers (MBLs). This transition is climatologically important due to the large decreases in cloud cover and to the significant changes in boundary layer structure that accompany it. An important component of understanding this transition is the ability to characterize the evolution of the vertical velocity structure of the MBL. During the Cloud System Evolution in the Trades (CSET) field program, held in July and August 2015, the NSF/NCAR Gulfstream-V High-performance Instrumented Airborne Platform for Environmental Research (GV HIAPER) aircraft made several transects from California to Hawaii to characterize the stratocumulus to Cumulus transition. The GV-HIAPER carried several remote sensing and in situ instruments for observing aerosol, cloud, precipitation, radiation and meteorological properties. Within selected air masses, flight legs were conducted above, inside, and below the cloud layers during aircraft transits from California to Hawaii. The same air masses (as determined by parcel trajectory analysis) were resampled on the return flight to California a day later. Of particular importance to studying MBL clouds are the HIAPER Cloud Radar (HCR) and the High Spectral Resolution Lidar (HSRL), which provided mapping of aerosol, cloud, and precipitation structures. From the W-band HCR, full radar Doppler spectra were calculated at 0.5 sec resolution. The 532 nm HSRL was fully calibrated and used to retrieve the aerosol extinction profiles. We have first combined the data collected by the HCR and the HSRL to create a hydrometeor mask, which will be used to characterize changes in the cloud structure. The Doppler spectrum from

  2. 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.

  3. Evaluation of long-term surface-retrieved cloud droplet number concentration with in situ aircraft observations: ARM Cloud Droplet Number Concentration

    SciTech Connect

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

    2016-03-06

    A new cloud-droplet number concentration (NDROP) value added product (VAP) has been produced at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for the 13 years from January 1998 to January 2011. The retrieval is based on surface radiometer measurements of cloud optical depth from the multi-filter rotating shadow-band radiometer (MFRSR) and liquid water path from the microwave radiometer (MWR). It is only applicable for single-layered warm clouds. Validation with in situ aircraft measurements during the extended-term aircraft field campaign, Routine ARM Aerial Facility (AAF) CLOWD Optical Radiative Observations (RACORO), shows that the NDROP VAP robustly reproduces the primary mode of the in situ measured probability density function (PDF), but produces a too wide 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 NDROP VAP 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 NDROP 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.

  4. 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

  5. Low altitude cloud height and methane humidity retrievals on Titan in the near-IR

    NASA Astrophysics Data System (ADS)

    Adamkovics, M.; Hayes, A.; Mitchell, J.; De Pater, I.; Young, E.

    2013-12-01

    The formation of low altitude clouds on Titan, with cloud-top altitudes below ~10km, likely occurs by a fundamentally different mechanism than for the clouds commonly observed to have cloud-tops in the upper troposphere, above ~15km [1]. Near-infrared spectroscopy of clouds has been the method of choice for determining cloud altitudes [2], however, uncertainties in aerosols scattering properties and opacities, together with limitations in laboratory measurements of gas opacities (in particular for methane), lead to uncertainties in how accurately the altitude of low clouds can be retrieved [3]. Here we revisit near-IR spectra obtained with Keck and Cassini using new laboratory methane line data in the HITRAN 2012 database [4] to address the problem of measuring the altitudes of low clouds. We discuss the role of topography in relation to the formation of low clouds and other diagnostics of conditions near the surface, such as the tropospheric methane humidity. We reanalyze measurements the tropospheric humidity variation [5] and describe observational strategies for improved diagnostics of the tropospheric humidity on Titan . Acknowledgements: Funding for this work is provided by the NSF grant AST-1008788 and NASA OPR grant NNX12AM81G. References: [1] Brown, et al. (2009) ApJ, 706, L110-L113. [2] Ádámkovics et al. (2010) Icarus, 208, 868-877. [3] Griffith et al. (2012) Icarus, 218, 975-988. [4] Rothman et al. (2013) AIP Conf. Proc., 1545, 223-231. [5] Penteado & Griffith (2010) Icarus, 206, 345-351.

  6. 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.

  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. Comparison of GLAS retrieved cloud fields with model generated rainfall fields

    NASA Technical Reports Server (NTRS)

    Susskind, J.; Kalnay, E.

    1984-01-01

    Monthly mean fractional cloud cover for January and February 1979, retrieved from SOP 1 of FGGE, are compared with the total precipitation field derived diagonally from the GLAS analysis/forecast system for the same time period. The breakdown of cloudiness into day (3 AM) and night (3 PM) is consistent with maps of outgoing long wave and short wave radiation inferred from AVHRR data. Of the many regions of coincidence, there is a particularly striking phenomenon: west of the coast of Peru, at about 20 deg S, there is a distinct small scale maximum in precipitation which coincides precisely with a maximum in the cloudiness field. This maximum in cloudiness and precipitation does not appear in the NOAA/NESS fields of albedo and outgoing long wave radiation which are normally sensitive to cloud fields. These low level clouds with warm tops are a mainly nocturnal phenomenon.

  9. Martian Surface NIR Spectral Modeling for Ice Cloud Optical Depth Retrievals using CRISM Mapping Data

    NASA Astrophysics Data System (ADS)

    Klassen, D. R.

    2011-10-01

    One goal in the study of Mars is to understand its water cycle and the total water budget. As part of this, I am working on trying to measure water ice content in Martian clouds. The catch is that in order to measure the water abundance in clouds using near-infrared (NIR) spectra, one must know the surface spectrum, since it is an input for radiative transfer modeling—but to get the surface spectrum, one must be able to remove the effects of the atmosphere and aerosols. I will present four primary methods of modeling away the surface in order to retrieve the ice cloud (and dust) optical depth and compare and contrast them for both ease-of-use and apparent accuracy.

  10. 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

  11. ATMS- and AMSU-A-derived hurricane warm core structures using a modified retrieval algorithm

    NASA Astrophysics Data System (ADS)

    Tian, Xiaoxu; Zou, Xiaolei

    2016-11-01

    The Advanced Technology Microwave Sounder (ATMS) is a cross-track microwave radiometer. Its temperature sounding channels 5-15 can provide measurements of thermal radiation emitted from different layers of the atmosphere. In this study, a traditional Advanced Microwave Sounding Unit-A (AMSU-A) temperature retrieval algorithm is modified to remove the scan biases in the temperature retrieval and to include only those ATMS sounding channels that are correlated with the atmospheric temperatures on the pressure level of the retrieval. The warm core structures derived for Hurricane Sandy when it moved from tropics to middle latitudes are examined. It is shown that scan biases that are present in the traditional retrieval are adequately removed using the modified algorithm. In addition, temperature retrievals in the upper troposphere ( 250 hPa) obtained by using the modified algorithm have more homogeneous warm core structures and those from the traditional retrieval are affected by small-scale features from the low troposphere such as precipitation. Based on ATMS observations, Hurricane Sandy's warm core was confined to the upper troposphere during its intensifying stage and when it was located in the tropics but extended to the entire troposphere when it moved into subtropics and middle latitudes and stopped its further intensification. The modified algorithm was also applied to AMSU-A observation data to retrieve the warm core structures of Hurricane Michael. The retrieved warm core features are more realistic when compared with those from the operational Microwave Integrated Retrieval System (MIRS).

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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…

  18. 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.

  19. Optical surface measurement using phase retrieval hybrid algorithm based on diffraction angular spectrum theory

    NASA Astrophysics Data System (ADS)

    Feng, Liang; Zeng, Zhi-ge; Wu, Yong-qian

    2013-08-01

    In order to test the high dynamic range error beyond one wavelength after the rough polish process, we design a phase retrieval hybrid algorithm based on diffraction angular spectrum theory. Phase retrieval is a wave front sensing method that uses the intensity distribution to reconstruct the phase distribution of optical field. Phase retrieval is established on the model of diffractive propagation and approach the real intensity distribution gradually. In this paper, we introduce the basic principle and challenges of optical surface measurement using phase retrieval, then discuss the major parts of phase retrieval: diffractive propagation and hybrid algorithm. The angular spectrum theory describes the diffractive propagation in the frequency domain instead of spatial domain, which simplifies the computation greatly. Through the theoretical analysis, the angular spectrum in discrete form is more effective when the high frequency part values less and the diffractive distance isn't far. The phase retrieval hybrid algorithm derives from modified GS algorithm and conjugate gradient method, aiming to solve the problem of phase wrapping caused by the high dynamic range error. In the algorithm, phase distribution is described by Zernike polynomials and the coefficients of Zernike polynomials are optimized by the hybrid algorithm. Simulation results show that the retrieved phase distribution and real phase distribution are quite contiguous for the high dynamic range error beyond λ.

  20. 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…

  1. 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

  2. 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.

  3. A spectral method for retrieving cloud optical thickness and effective radius from surface-based transmittance measurements

    NASA Astrophysics Data System (ADS)

    McBride, P. J.; Schmidt, K. S.; Pilewskie, P.; Kittelman, A. S.; Wolfe, D. E.

    2011-07-01

    We introduce a new spectral method for the retrieval of optical thickness and effective radius from cloud transmittance that relies on the spectral slope of the normalized transmittance between 1565 nm and 1634 nm, and on cloud transmittance at a visible wavelength. The standard dual-wavelength technique, which is traditionally used in reflectance-based retrievals, is ill-suited for transmittance because it lacks sensitivity to effective radius, especially for optically thin clouds. Using the spectral slope rather than the transmittance itself enhances the sensitivity of transmittance observations with respect to the effective radius. This is demonstrated by applying it to the moderate spectral resolution observations from the Solar Spectral Flux Radiometer (SSFR) and Shortwave Spectroradiometer (SWS), and by examining the retrieval uncertainties of the standard and the spectral method for data from the DOE ARM Southern Great Plains (SGP) site and a NOAA ship cruise (ICEALOT). The liquid water path (LWP) is derived from the retrieved optical thickness and effective radius, based on two different assumptions about the cloud vertical profile, and compared to the simultaneous observations from a microwave radiometer. Optical thickness and effective radius is also compared to MODIS retrievals. In general, the effective radius uncertainties were much larger for the standard retrieval than for the spectral retrieval, particularly for thin clouds. When defining 2 μm as upper limit for the tolerable uncertainty of the effective radius, the standard method returned only very few valid retrievals for clouds with an optical thickness below 25. For the analyzed ICEALOT data (mean optical thickness 23), the spectral method provided valid retrievals for 84 % of the data (24 % for the standard method). For the SGP data (mean optical thickness 44), both methods provided a high return of 90 % for the spectral method and 78 % for the standard method.

  4. 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

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

    ERIC Educational Resources Information Center

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

    2003-01-01

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

  6. Improved Determination of Surface and Atmospheric Temperatures Using Only Shortwave AIRS Channels: The AIRS Version 6 Retrieval Algorithm

    NASA Technical Reports Server (NTRS)

    Susskind, Joel; Blaisdell, John; Iredell, Lena

    2010-01-01

    AIRS was launched on EOS Aqua on May 4, 2002 together with ASMU-A and HSB to form a next generation polar orbiting infrared and microwave atmosphere sounding system (Pagano et al 2003). The theoretical approach used to analyze AIRS/AMSU/HSB data in the presence of clouds in the AIRS Science Team Version 3 at-launch algorithm, and that used in the Version 4 post-launch algorithm, have been published previously. Significant theoretical and practical improvements have been made in the analysis of AIRS/AMSU data since the Version 4 algorithm. Most of these have already been incorporated in the AIRS Science Team Version 5 algorithm (Susskind et al 2010), now being used operationally at the Goddard DISC. The AIRS Version 5 retrieval algorithm contains three significant improvements over Version 4. Improved physics in Version 5 allowed for use of AIRS clear column radiances (R(sub i)) 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 were used primarily in the generation of clear column radiances (R(sub i)) for all channels. This new approach allowed for the generation of accurate Quality Controlled values of R(sub i) and T(p) under more stressing cloud conditions. Secondly, Version 5 contained 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 contained 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 was developed as a backup to AIRS Version 5 should the AMSU-A instrument fail. Susskind et al 2010 shows that Version 5 AIRS Only sounding are only slightly degraded from the AIRS/AMSU soundings, even at large fractional cloud

  7. 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.

  8. Ice Concentration Retrieval in Stratiform Mixed-phase Clouds Using Cloud Radar Reflectivity Measurements and 1D Ice Growth Model Simulations

    SciTech Connect

    Zhang, Damao; Wang, Zhien; Heymsfield, Andrew J.; Fan, Jiwen; Luo, Tao

    2014-10-01

    Measurement of ice number concentration in clouds is important but still challenging. Stratiform mixed-phase clouds (SMCs) provide a simple scenario for retrieving ice number concentration from remote sensing measurements. The simple ice generation and growth pattern in SMCs offers opportunities to use cloud radar reflectivity (Ze) measurements and other cloud properties to infer ice number concentration quantitatively. To understand the strong temperature dependency of ice habit and growth rate quantitatively, we develop a 1-D ice growth model to calculate the ice diffusional growth along its falling trajectory in SMCs. The radar reflectivity and fall velocity profiles of ice crystals calculated from the 1-D ice growth model are evaluated with the Atmospheric Radiation Measurements (ARM) Climate Research Facility (ACRF) ground-based high vertical resolution radar measurements. Combining Ze measurements and 1-D ice growth model simulations, we develop a method to retrieve the ice number concentrations in SMCs at given cloud top temperature (CTT) and liquid water path (LWP). The retrieved ice concentrations in SMCs are evaluated with in situ measurements and with a three-dimensional cloud-resolving model simulation with a bin microphysical scheme. These comparisons show that the retrieved ice number concentrations are within an uncertainty of a factor of 2, statistically.

  9. 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

  10. 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.

    2016-02-01

    The Ozone Monitoring Instrument (OMI) 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 operational OMI tropospheric NO2 retrieval chain (DOMINO - Derivation of OMI tropospheric NO2) product. Instead, the operational OMI O2 - O2 cloud retrieval algorithm is applied both to cloudy and to cloud-free scenes (i.e. clear sky) dominated by the presence of aerosols. This paper describes in detail the complex interplay between the spectral effects of aerosols in the satellite observation and the associated response of the OMI O2 - O2 cloud retrieval algorithm. Then, it evaluates the impact on the accuracy of the tropospheric NO2 retrievals through the computed Air Mass Factor (AMF) with a focus on cloud-free scenes. For that purpose, collocated OMI NO2 and MODIS (Moderate Resolution Imaging Spectroradiometer) Aqua aerosol products are analysed over the strongly industrialized East China 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 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 primarily represents the shielding effects of the O2 - O2 column located below the aerosol layers. The study cases show that the aerosol correction based on the implemented OMI cloud model results in biases

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 3D Cloud Radiative Effects on Aerosol Optical Thickness Retrievals in Cumulus Cloud Fields in the Biomass Burning Region in Brazil

    NASA Technical Reports Server (NTRS)

    Wen, Guo-Yong; Marshak, Alexander; Cahalan, Robert F.

    2004-01-01

    Aerosol amount in clear regions of a cloudy atmosphere is a critical parameter in studying the interaction between aerosols and clouds. Since the global cloud cover is about 50%, cloudy scenes are often encountered in any satellite images. Aerosols are more or less transparent, while clouds are extremely reflective in the visible spectrum of solar radiation. The radiative transfer in clear-cloudy condition is highly three- dimensional (3D). This paper focuses on estimating the 3D effects on aerosol optical thickness retrievals using Monte Carlo simulations. An ASTER image of cumulus cloud fields in the biomass burning region in Brazil is simulated in this study. The MODIS products (i-e., cloud optical thickness, particle effective radius, cloud top pressure, surface reflectance, etc.) are used to construct the cloud property and surface reflectance fields. To estimate the cloud 3-D effects, we assume a plane-parallel stratification of aerosol properties in the 60 km x 60 km ASTER image. The simulated solar radiation at the top of the atmosphere is compared with plane-parallel calculations. Furthermore, the 3D cloud radiative effects on aerosol optical thickness retrieval are estimated.

  16. Retrieval of Venus' clouds parameters with polarization using SPICAV-IR onboard Venus Express

    NASA Astrophysics Data System (ADS)

    Rossi, Loïc; Marcq, Emmanuel; Montmessin, Franck; Fedorova, Anna; Stam, Daphne; Bertaux, Jean-Loup; Korablev, Oleg

    2015-04-01

    Understanding the structure and dynamics of Venus' clouds is essential as they have a strong impact on the radiative balance and atmospheric chemistry of the planet. Polarimetry has greatly contributed to our knwoledge about the properties of the cloud layers located between 48 and ~ 70 km. Hansen and Hovenier (1974), using ground-based observations, found the cloud particles to be ~ 1μm spherical droplets, with a refractive index corresponding to a concentrated sulfuric acid-water solution. Later, Kawabata et al. (1980), using polarimetric data from OCPP onboard Pioneer Venus retrieved the properties of the haze: effective radius of ~ 0.25μm, refractive indices consistent with a sulfuric acid-water solution, variance of the particle size distribution. We introduce here new measurements obtained with the SPICAV-IR spectrometer onboard ESA's Venus Express. Observing Venus in the visible and IR from 650 nm to 1625 nm with a good spatial and temporal converage, SPICAV's sensitivity to the degree of linear polarization gives us an opportunity to put better constraints on haze and cloud particles at Venus cloud top, as well as their spatial and temporal variability. These observations reveal a particular feature called glory, observed by SPICAV-IR and VMC (Markiewicz et al. 2014). Using a radiative transfer code taking into account polarization (de Haan et al. 1987, de Rooij et al. 1984, Stam et al. 1999), we model the cloud layers and the glory allowing us to retrieve the real part of the refractive index, the effective radius and variance of the particle size distribution from the main cloud layer. Our results confirm that the particles are spherical, with a narrow size distribution and with refractive indices that are compatible with H2SO4-H2O solutions (Rossi et al. 2014). Using the large latitudinal coverage of the data, we can also retrieve the variation of the overlying haze layer optical thickness. We find that τh is increasing with increasing latitude, in

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

    SciTech Connect

    Mitchell, David L

    2009-10-14

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

  18. Retrieved Surface Emissivity Impact of New Cloud-Clearing Channel Set

    NASA Technical Reports Server (NTRS)

    Fishbein, Evan F.; Hook, Simon

    2006-01-01

    A viewgraph presentation on a proposed new cloud clearing channel set to improve land products and validate surface emissivity is given. The topics include: 1) Methodology; 2) Channel Selection; 3) Temperature Statistics; 4) 850 hPa Temperature Variability; 5) Status of Surface Retrieval; 6) Emissivity at 9 micrometers; 7) Emissivity Spectra; 8) Ha Megev (Israel); 9) Egypt One; 10) Salonga National Park, Zaire; 11) HaGolan (Israel/Syria); 12) Emissivity at 3.75 micrometers; 13) Improving Surface Retrieval; 14) Work Needed for V5 Delivery; 15) Effects of MODIS Emissivity; 16) Channel Selection; 17) 500 hPa Temperature Variability; 18) 850 hPa Temperature Variability; and 19) 850 hPa Temperature Differences;

  19. 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.

  20. Long-term Validation of Cloud-droplet Number Concentration Value Added Product (NDROP VAP) Retrieved from Surface Measurements

    NASA Astrophysics Data System (ADS)

    Lim, K. S. S.; Riihimaki, L.; Comstock, J. M.; Schmid, B.; Sivaraman, C.; Shi, Y.; McFarquhar, G. M.

    2015-12-01

    A new cloud-droplet number concentration (NDROP) Value Added Product (VAP) has been produced at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for the 13 years from January 1998 to January 2011. The droplet number concentration values are retrieved from surface radiometer measurements of cloud optical depth from the multi-filter rotating shadow-band radiometer (MFRSR) and liquid water path from the microwave radiometer (MWR). We validate the NDROP VAP with in situ aircraft measurements from the Cloud and Aerosol Spectrometer probe during the long-term aircraft field campaign, Routine ARM Aerial Facility (AAF) CLOWD Optical Radiative Observations (RACORO). The NDROP VAP considers entrainment effects rather than assuming an adiabatic cloud, which improves the values of the NDROP VAP by reducing the magnitude of cloud-droplet number concentration. The NDROP VAP captures the primary mode of in situ measured droplet number concentration, but produces too wide a distribution due to too frequent high cloud-droplet number concentrations. The large droplet number concentration error corresponds to errors in the MWR retrievals at low liquid water paths due to the limitations of the instrument. Modification of the NDROP VAP through the diagnosed liquid water path, which is constrained by the coordinated solution using cloud optical depth and cloud-droplet effective radius retrievals, alleviates this problem, leading to better agreement with in situ measurements.

  1. 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.

  2. An Atmospheric Radiation Measurement Value-Added Product to Retrieve Optically Thin Cloud Visible Optical Depth using Micropulse Lidar

    SciTech Connect

    Lo, C; Comstock, JM; Flynn, C

    2006-10-01

    The purpose of the Micropulse Lidar (MPL) Cloud Optical Depth (MPLCOD) Value-Added Product (VAP) is to retrieve the visible (short-wave) cloud optical depth for optically thin clouds using MPL. The advantage of using the MPL to derive optical depth is that lidar is able to detect optically thin cloud layers that may not be detected by millimeter cloud radar or radiometric techniques. The disadvantage of using lidar to derive optical depth is that the lidar signal becomes attenuation limited when τ approaches 3 (this value can vary depending on instrument specifications). As a result, the lidar will not detect optically thin clouds if an optically thick cloud obstructs the lidar beam.

  3. Microphysical properties of the November 26 cirrus cloud retrieved by Doppler radar/IR radiometer technique

    NASA Technical Reports Server (NTRS)

    Matrosov, Sergey Y.; Kropfli, Robert A.; Orr, Brad W.; Snider, Jack B.

    1993-01-01

    Gaining information about cirrus cloud microphysics requires development of remote sensing techniques. In an earlier paper. Matrosov et al. (1992) proposed a method to estimate ice water path (IWP) (i.e., vertically integrated ice mass content IMC) and characteristic particle size averaged through the cloud from combined groundbased measurements of radar reflectivities and IR brightness temperatures of the downwelling thermal radiation in the transparency region of 10-12 mu m. For some applications, the vertically averaged characteristic particle sizes and IWP could be the appropriate information to use. However, vertical profiles of cloud microphysical parameters can provide a better understanding of cloud structure and development. Here we describe a further development of the previous method by Matrosov et al. (1992) for retrieving vertical profiles of cirrus particle sizes and IMC rather than their vertically averaged values. In addition to measurements of radar reflectivities, the measurements of Doppler velocities are used in the new method. This provides us with two vertical profiles of measurements to infer two vertical profiles of unknowns, i.e., particle characteristic sizes and IMC. Simultaneous measurements of the IR brightness temperatures are still needed to resolve an ambiguity in particle size-fall velocity relationships.

  4. Retrieval of cloud optical parameters from space-based backscatter lidar data.

    PubMed

    Balin, Y S; Samoilova, S V; Krekova, M M; Winker, D M

    1999-10-20

    We present an approach to estimating the multiple-scattering (MS) contribution to lidar return signals from clouds recorded from space that enables us to describe in more detail the return formation at the depth where first orders of scattering dominate. Estimates made have enabled us to propose a method for correcting solutions of single-scattering lidar equations for the MS contribution. We also describe an algorithm for reconstructing the profiles of the cloud scattering coefficient and the optical thickness tau under conditions of a priori uncertainties. The approach proposed is illustrated with results for optical parameters of cirrus and stratiform clouds determined from return signals calculated by the Monte Carlo method as well as from return signals acquired with the American spaceborne lidar during the Lidar In-Space Technology Experiment (LITE).

  5. Characterizing a New Surface-Based Shortwave Cloud Retrieval Technique, Based on Transmitted Radiance for Soil and Vegetated Surface Types

    NASA Technical Reports Server (NTRS)

    Coddington, Odele; Pilewskie, Peter; Schmidt, K. Sebastian; McBride, Patrick J.; Vukicevic, Tomislava

    2013-01-01

    This paper presents an approach using the GEneralized Nonlinear Retrieval Analysis (GENRA) tool and general inverse theory diagnostics including the maximum likelihood solution and the Shannon information content to investigate the performance of a new spectral technique for the retrieval of cloud optical properties from surface based transmittance measurements. The cumulative retrieval information over broad ranges in cloud optical thickness (tau), droplet effective radius (r(sub e)), and overhead sun angles is quantified under two conditions known to impact transmitted radiation; the variability in land surface albedo and atmospheric water vapor content. Our conclusions are: (1) the retrieved cloud properties are more sensitive to the natural variability in land surface albedo than to water vapor content; (2) the new spectral technique is more accurate (but still imprecise) than a standard approach, in particular for tau between 5 and 60 and r(sub e) less than approximately 20 nm; and (3) the retrieved cloud properties are dependent on sun angle for clouds of tau from 5 to 10 and r(sub e) less than 10 nm, with maximum sensitivity obtained for an overhead sun.

  6. Lidar multiple scattering factors inferred from CALIPSO lidar and IIR retrievals of semi-transparent cirrus cloud optical depths over oceans

    NASA Astrophysics Data System (ADS)

    Garnier, A.; Pelon, J.; Vaughan, M. A.; Winker, D. M.; Trepte, C. R.; Dubuisson, P.

    2015-07-01

    Cirrus cloud absorption optical depths retrieved at 12.05 μm are compared to extinction optical depths retrieved at 0.532 μm from perfectly co-located observations of single-layered semi-transparent cirrus over ocean made by the Imaging Infrared Radiometer (IIR) and the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP) flying on board the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite. IIR infrared absorption optical depths are compared to CALIOP visible extinction optical depths when the latter can be directly derived from the measured apparent two-way transmittance through the cloud. An evaluation of the CALIOP multiple scattering factor is inferred from these comparisons after assessing and correcting biases in IIR and CALIOP optical depths reported in version 3 data products. In particular, the blackbody radiance taken in the IIR version 3 algorithm is evaluated, and IIR retrievals are corrected accordingly. Numerical simulations and IIR retrievals of ice crystal sizes suggest that the ratios of CALIOP extinction and IIR absorption optical depths should remain roughly constant with respect to temperature. Instead, these ratios are found to increase quasi-linearly by about 40 % as the temperature at the layer centroid altitude decreases from 240 to 200 K. It is discussed that this behavior can be explained by variations of the multiple scattering factor ηT applied to correct the measured apparent two-way transmittance for contribution of forward-scattering. While the CALIOP version 3 retrievals hold ηT fixed at 0.6, this study shows that ηT varies with temperature (and hence cloud particle size) from ηT = 0.8 at 200 K to ηT = 0.5 at 240 K for single-layered semi-transparent cirrus clouds with optical depth larger than 0.3. The revised parameterization of ηT introduces a concomitant temperature dependence in the simultaneously derived CALIOP lidar ratios that is consistent with observed changes in CALIOP

  7. Near-Real Time Satellite-Retrieved Cloud and Surface Properties for Weather and Aviation Safety Applications

    NASA Astrophysics Data System (ADS)

    Minnis, P.; Smith, W., Jr.; Bedka, K. M.; Nguyen, L.; Palikonda, R.; Hong, G.; Trepte, Q.; Chee, T.; Scarino, B. R.; Spangenberg, D.; Sun-Mack, S.; Fleeger, C.; Ayers, J. K.; Chang, F. L.; Heck, P. W.

    2014-12-01

    Cloud properties determined from satellite imager radiances provide a valuable source of information for nowcasting and weather forecasting. In recent years, it has been shown that assimilation of cloud top temperature, optical depth, and total water path can increase the accuracies of weather analyses and forecasts. Aircraft icing conditions can be accurately diagnosed in near-real time (NRT) retrievals of cloud effective particle size, phase, and water path, providing valuable data for pilots. NRT retrievals of surface skin temperature can also be assimilated in numerical weather prediction models to provide more accurate representations of solar heating and longwave cooling at the surface, where convective initiation. These and other applications are being exploited more frequently as the value of NRT cloud data become recognized. At NASA Langley, cloud properties and surface skin temperature are being retrieved in near-real time globally from both geostationary (GEO) and low-earth orbiting (LEO) satellite imagers for weather model assimilation and nowcasting for hazards such as aircraft icing. Cloud data from GEO satellites over North America are disseminated through NCEP, while those data and global LEO and GEO retrievals are disseminated from a Langley website. This paper presents an overview of the various available datasets, provides examples of their application, and discusses the use of the various datasets downstream. Future challenges and areas of improvement are also presented.

  8. Near-Real Time Satellite-Retrieved Cloud and Surface Properties for Weather and Aviation Safety Applications

    NASA Technical Reports Server (NTRS)

    Minnis, Patrick; Smith, William L., Jr.; Bedka, Kristopher M.; Nguyen, Louis; Palikonda, Rabindra; Hong, Gang; Trepte, Qing Z.; Chee, Thad; Scarino, Benjamin; Spangenberg, Douglas A.; Sun-Mack, Szedung; Fleeger, Cecilia; Ayers, J. Kirk; Chang, Fu-Lung; Heck, Patrick M.

    2014-01-01

    Cloud properties determined from satellite imager radiances provide a valuable source of information for nowcasting and weather forecasting. In recent years, it has been shown that assimilation of cloud top temperature, optical depth, and total water path can increase the accuracies of weather analyses and forecasts. Aircraft icing conditions can be accurately diagnosed in near-­-real time (NRT) retrievals of cloud effective particle size, phase, and water path, providing valuable data for pilots. NRT retrievals of surface skin temperature can also be assimilated in numerical weather prediction models to provide more accurate representations of solar heating and longwave cooling at the surface, where convective initiation. These and other applications are being exploited more frequently as the value of NRT cloud data become recognized. At NASA Langley, cloud properties and surface skin temperature are being retrieved in near-­-real time globally from both geostationary (GEO) and low-­-earth orbiting (LEO) satellite imagers for weather model assimilation and nowcasting for hazards such as aircraft icing. Cloud data from GEO satellites over North America are disseminated through NCEP, while those data and global LEO and GEO retrievals are disseminated from a Langley website. This paper presents an overview of the various available datasets, provides examples of their application, and discusses the use of the various datasets downstream. Future challenges and areas of improvement are also presented.

  9. 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.

  10. MERIS albedo climatology and its effect on the FRESCO+ O2 A-band cloud retrieval from SCIAMACHY data

    NASA Astrophysics Data System (ADS)

    Popp, Christoph; Wang, Ping; Brunner, Dominik; Stammes, Piet; Zhou, Yipin

    2010-05-01

    Accurate cloud information is an important prerequisite for the retrieval of atmospheric trace gases from spaceborne UV/VIS sensors. Errors in the estimated cloud fraction and cloud height (pressure) result in an erroneous air mass factor and thus can lead to inaccuracies in the vertical column densities of the retrieved trace gas. In ESA's TEMIS (Tropospheric Emission Monitoring Internet Service) project, the FRESCO+ (Fast Retrieval Scheme for Clouds from the Oxygen A-band) cloud retrieval is applied to, amongst others, SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY) data to determine these quantities. Effective cloud fraction and pressure are inverted by (i) radiative transfer simulations of top-of-atmosphere reflectance based on O2 absorption, single Rayleigh scattering, surface and cloud albedo in three spectral windows covering the O2 A-band and (ii) a subsequent fitting of the simulated to the measured spectrum. However, FRESCO+ relies on a relatively coarse resolution surface albedo climatology (1° x 1°) compiled from GOME (Global Ozone Monitoring Experiment) measurements in the 1990's which introduces several artifacts, e.g. an overestimation of cloud fraction at coastlines or over some mountainous regions. Therefore, we test the substitution of the GOME climatology with a new land surface albedo climatology compiled for every month from MEdium Resolution Imaging Spectrometer (MERIS) Albedomap data (0.05° x 0.05°) covering the period January 2003 to October 2006. The MERIS channels at 754nm and 775nm are located spectrally close to the corresponding GOME channels (758nm and 772nm) on both sides of the O2 A-band. Further, the increased spatial resolution of the MERIS product allows to better account for SCIAMACHY's pixel size of approximately 30x60km. The aim of this study is to describe and assess (i) the compilation and quality of the MERIS climatology (ii) the differences to the GOME climatology, and (iii) possible

  11. Retrieving fall streaks signatures in radar data to study microphysical changes of particle populations within a mixed phase clouds

    NASA Astrophysics Data System (ADS)

    Pfitzenmaier, Lukas; Dufournet, Yann; Unal, Christine; Russchenberg, Herman

    2016-04-01

    Within mixed-phase clouds the interaction of ice crystals with super-cooled liquid water leads to an enhanced growth of the ice particles. The growth of ice particles from mixed-phase interactions is an important process for precipitation formation in the mid-latitudes. However, such a process is still not clearly understood, nowerdays. To understand the ice particle growth within these clouds the microphysical changes of a single particle population falling through the cloud have to be analysed. Using the 3 beam configuration of the Transportable Atmospheric Radar (TARA) we retrieve the full 3-D Doppler velocity vector. This retrieved dynamical information is used to retrieve the path of a single particle population through the measured cloud system - the so called fall streak - so that microphysical changes along those path can be studied. A way to study changes in ice particle microphysics is to analyse radar Doppler spectra. Microphysical changes along the path of a population of ice particles through a mixed-phase cloud can be correlated to changes in the retrieved radar spectrograms. The instrumental synergy setup during the ACCEPT campaign (Analysis of the Composition of Clouds with Extended Polarization Techniques campaign), fall 2014, Cabauw the Netherlands, allows to detect liquid water layers within mixed-phase clouds. Therefore, identified changes within the retrieved spectrograms can be linked to the presence of super-cooled liquid layers. In this work we will explain the backtracking methodology and its use for the interpretation of velocity spectra. The application of this new methodology for ice particle growth process studies within mixed-phase clouds will be discussed.

  12. 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

  13. Phase retrieval algorithm for JWST Flight and Testbed Telescope

    NASA Astrophysics Data System (ADS)

    Dean, Bruce H.; Aronstein, David L.; Smith, J. Scott; Shiri, Ron; Acton, D. Scott

    2006-06-01

    An image-based wavefront sensing and control algorithm for the James Webb Space Telescope (JWST) is presented. The algorithm heritage is discussed in addition to implications for algorithm performance dictated by NASA's Technology Readiness Level (TRL) 6. The algorithm uses feedback through an adaptive diversity function to avoid the need for phase-unwrapping post-processing steps. Algorithm results are demonstrated using JWST Testbed Telescope (TBT) commissioning data and the accuracy is assessed by comparison with interferometer results on a multi-wave phase aberration. Strategies for minimizing aliasing artifacts in the recovered phase are presented and orthogonal basis functions are implemented for representing wavefronts in irregular hexagonal apertures. Algorithm implementation on a parallel cluster of high-speed digital signal processors (DSPs) is also discussed.

  14. A Comparison of High Spectral Resolution Infrared Cloud-Top Pressure Altitude Algorithms Using S-HIS Measurements

    NASA Technical Reports Server (NTRS)

    Holz, Robert E.; Ackerman, Steve; Antonelli, Paolo; Nagle, Fred; McGill, Matthew; Hlavka, Dennis L.; Hart, William D.

    2005-01-01

    This paper presents a comparison of cloud-top altitude retrieval methods applied to S-HIS (Scanning High Resolution Interferometer Sounder) measurements. Included in this comparison is an improvement to the traditional CO2 Slicing method. The new method, CO2 Sorting, determines optimal channel pairs to apply the CO2 Slicing. Measurements from collocated samples of the Cloud Physics Lidar (CPL) and Modis Airborne Simulator (MAS) instruments assist in the comparison. For optically thick clouds good correlation between the S-HIS and lidar cloud-top retrievals are found. For tenuous ice clouds there can be large differences between lidar (CPL) and S-HIS retrieved