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Sample records for algorithm retrieves cloud

  1. 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.

  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.

    2008-05-01

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

  3. Evaluating cloud retrieval algorithms with the ARM BBHRP framework

    SciTech Connect

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

    2008-03-10

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

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

    NASA Astrophysics Data System (ADS)

    Qiu, Yujun; Lu, Chunsong

    2016-08-01

    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.

  5. 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.

  6. Cloud effects on chlorophyll retrieval algorithm of MODIS

    NASA Astrophysics Data System (ADS)

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

    2006-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    Cloud detection algorithms search for measurement signatures that differentiate a cloud-contaminated or "not-clear" pixel from the clear-sky background. These signatures can be spectral, textural or temporal in nature. The magnitude of the difference between the cloud and the background must exceed a threshold value for the pixel to be classified having a not-clear FOV. All detection algorithms employ multiple tests ranging across some portion of the solar reflectance and/or infrared spectrum. However, a cloud is not a single, uniform object, but rather has a distribution of optical thickness and morphology. As a result, problems can arise when the distributions of cloud and clear-sky background characteristics overlap, making some test results indeterminate and/or leading to some amount of detection misclassification. Further, imager cloud retrieval statistics are highly sensitive to how a pixel identified as not-clear by a cloud mask is determined to be useful for cloud-top and optical retrievals based on 1-D radiative models. This presentation provides an overview of the different 'choices' algorithm developers make in cloud detection algorithms and the impact on regional and global cloud amounts and fractional coverage, cloud type and property distributions. Lessons learned over the course of the MODIS cloud product development history are discussed. As an example, we will focus on the 1km MODIS Collection 5 cloud optical retrieval algorithm (product MOD06/MYD06 for Terra and Aqua, respectively) which removed pixels associated with cloud edges as defined by immediate adjacency to clear FOV MODIS cloud mask (MOD35/MYD35) pixels as well as ocean pixels with partly cloudy elements in the 250m MODIS cloud mask - part of the so-called Clear Sky Restoral algorithm. The Collection 6 algorithm attempts retrievals for these two types of partly cloudy pixel populations, but allows a user to isolate or filter out the populations. Retrieval sensitivities for these

  8. Retrieving vertical profiles of water-cloud droplet effective radius: Algorithm modification and preliminary application

    NASA Astrophysics Data System (ADS)

    Chang, Fu-Lung; Li, Zhanqing

    2003-12-01

    [2002] proposed a new cloud microphysics retrieval technique that can estimate the vertical profile of droplet effective radius (DER) for water clouds using multispectral near-infrared (NIR) measurements. The underlying principle of the retrieval technique is that radiance measurements at distinct multi-NIR wavelengths possess different penetration depths inside the cloud and this conveys certain information on the DER vertical profile (DVP). However, this information is insufficient to retrieve any shape of DVP and thus a linear DVP was assumed. In this study, three DVPs are examined: (1) as in [2002], a linear DVP proportional to the in-cloud optical depth, (2) a linear DVP proportional to the height within the cloud, and (3) a DVP where the liquid water content (LWC) within the cloud varies linearly with height. The latter two assumptions are in closer conformity with in-situ observations. Algorithms that can retrieve both the DVP and cloud liquid water path (LWP) are presented. The cloud LWPs derived based on the retrieved DVPs are more sound than those obtained from assuming a vertical-constant DER profile. To enhance the DVP retrievals, a split-window technique is presented to better estimate the amount of above-cloud precipitable water (PW). The retrieval algorithms are applied to the MODIS Level-1B 1-km data and presently tested for two stratiform cloud cases observed over the north-central Oklahoma where independent cloud microphysics data are available from the United States Department of Energy's Atmospheric Radiation Measurement (ARM) Program. Good agreements in the retrieved DER profile, LWP, and above-cloud PW are found in a preliminary demonstration of the new approach. Sensitivity of the retrieved DER profile to uncertainties in the above-cloud PW and surface albedos is also discussed.

  9. Satellite-based retrieval of ice cloud properties using a semianalytical algorithm

    NASA Astrophysics Data System (ADS)

    Kokhanovsky, A. A.; Nauss, T.

    2005-10-01

    A semianalytical algorithm for the retrieval of ice cloud properties from satellite data is presented. The new method is based on the semianalytical cloud retrieval algorithm and uses solutions of the asymptotic radiative transfer theory applicable for optically thick media. Therefore the new method is much less computer time expensive than the commonly used lookup table approaches. Usually, the cloud optical thickness and cloud effective droplet radius are reported for water and ice clouds even though both parameters are dependent on the actual crystal shape assumed in the retrieval procedures. Thus the authors propose to use the reduced optical thickness (ROT) and the particle absorption length (PAL) for the characterization of ice clouds. This implies that no a priori or climatological estimates of the particle shape/size distribution are necessary and increases the comparability of different cloud retrieval algorithms, which are built on many different distribution functions. If still necessary, the retrieved ROT and PAL can easily be transferred to values of the optical thickness and the cloud effective droplet radius by assuming any of those size distribution functions. The developed technique has been applied to data from the NASA EOS Terra Moderate Resolution Imaging Spectroradiometer sensor. The scene shows Hurricane Jeanne just before its landfall near the coast of Florida in September 2004. Both the reduced cloud optical thickness and the particle absorption length have been derived for the eye wall region.

  10. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  12. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

    An infrared-based optimal estimation (OE-IR) algorithm for retrieving ice cloud properties is evaluated. Specifically, the implementation of the algorithm with MODerate resolution Imaging Spectroradiometer (MODIS) observations is assessed in comparison with the operational retrieval products from MODIS on the Aqua satellite (MYD06), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and the Imaging Infrared Radiometer (IIR); the latter two instruments fly on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite in the Afternoon Constellation (A-Train) with Aqua. The results show that OE-IR cloud optical thickness (τ) and effective radius (reff) retrievals perform best for ice clouds having 0.5 < τ < 7 and reff < 50 µm. For global ice clouds, the averaged retrieval uncertainties of τ and reff are 19% and 33%, respectively. For optically thick ice clouds with τ larger than 10, however, the τ and reff retrieval uncertainties can exceed 30% and 50%, respectively. For ice cloud top height (h), the averaged global uncertainty is 0.48 km. Relatively large h uncertainty (e.g., > 1 km) occurs for τ < 0.5. Analysis of 1 month of the OE-IR retrievals shows large τ and reff uncertainties in storm track regions and the southern oceans where convective clouds are frequently observed, as well as in high-latitude regions where temperature differences between the surface and cloud top are more ambiguous. Generally, comparisons between the OE-IR and the operational products show consistent τ and h retrievals. However, obvious differences between the OE-IR and the MODIS Collection 6 reff are found.

  14. The ESA Cloud CCI project: Generation of Multi Sensor consistent Cloud Properties with an Optimal Estimation Based Retrieval Algorithm

    NASA Astrophysics Data System (ADS)

    Jerg, M.; Stengel, M.; Hollmann, R.; Poulsen, C.

    2012-04-01

    The ultimate objective of the ESA Climate Change Initiative (CCI) Cloud project is to provide long-term coherent cloud property data sets exploiting and improving on the synergetic capabilities of past, existing, and upcoming European and American satellite missions. The synergetic approach allows not only for improved accuracy and extended temporal and spatial sampling of retrieved cloud properties better than those provided by single instruments alone but potentially also for improved (inter-)calibration and enhanced homogeneity and stability of the derived time series. Such advances are required by the scientific community to facilitate further progress in satellite-based climate monitoring, which leads to a better understanding of climate. Some of the primary objectives of ESA Cloud CCI Cloud are (1) the development of inter-calibrated radiance data sets, so called Fundamental Climate Data Records - for ESA and non ESA instruments through an international collaboration, (2) the development of an optimal estimation based retrieval framework for cloud related essential climate variables like cloud cover, cloud top height and temperature, liquid and ice water path, and (3) the development of two multi-annual global data sets for the mentioned cloud properties including uncertainty estimates. These two data sets are characterized by different combinations of satellite systems: the AVHRR heritage product comprising (A)ATSR, AVHRR and MODIS and the novel (A)ATSR - MERIS product which is based on a synergetic retrieval using both instruments. Both datasets cover the years 2007-2009 in the first project phase. ESA Cloud CCI will also carry out a comprehensive validation of the cloud property products and provide a common data base as in the framework of the Global Energy and Water Cycle Experiment (GEWEX). The presentation will give an overview of the ESA Cloud CCI project and its goals and approaches and then continue with results from the Round Robin algorithm

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

  17. 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

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

    NASA Technical Reports Server (NTRS)

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

    2006-01-01

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

  19. 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.

  20. 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.

  1. A cloud and radiation model-based algorithm for rainfall retrieval from SSM/I multispectral microwave measurements

    NASA Technical Reports Server (NTRS)

    Xiang, Xuwu; Smith, Eric A.; Tripoli, Gregory J.

    1992-01-01

    A hybrid statistical-physical retrieval scheme is explored which combines a statistical approach with an approach based on the development of cloud-radiation models designed to simulate precipitating atmospheres. The algorithm employs the detailed microphysical information from a cloud model as input to a radiative transfer model which generates a cloud-radiation model database. Statistical procedures are then invoked to objectively generate an initial guess composite profile data set from the database. The retrieval algorithm has been tested for a tropical typhoon case using Special Sensor Microwave/Imager (SSM/I) data and has shown satisfactory results.

  2. Errors in the retrieval of thin-cloud optical parameters obtained with a two-boundary algorithm.

    PubMed

    Del Guasta, M

    1998-08-20

    The effect of various errors on the retrieval of optical depth, integrated backscatter, and extinction-to-backscatter ratio in optically thin clouds by use of a two-boundary algorithm is discussed. Uncertainties regarding aerosol loading at the cloud base and top lead to relevant errors that are often larger than those produced by signal noise. Formulas expressing the errors in the lidar-derived optical quantities dependent on optical depth and aerosol uncertainties at the base and top are derived for different fitting procedures. A method for the reduction of errors in the case of consecutive cloud measurements is explored, consisting of the fitting of the retrieved optical-depth-integrated backscatter data to obtain a correct extinction-to-backscatter ratio.

  3. 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

  4. 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.

  5. 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.

  6. Assessment of uncertainty in cloud radiative effects and heating rates through retrieval algorithm differences: Analysis using 3 years of ARM data at Darwin, Australia

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

    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), visible extinction coefficient, 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 is presented. Our analysis shows that IWC compares well among algorithms, but Re shows significant discrepancies, which are attributed primarily to assumptions of particle shape. Uncertainty in Re and IWC translates into sometimes large differences in cloud shortwave 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/d difference in the radiative heating rates between algorithms.

  7. 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.

  8. 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.

  9. 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).

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  11. 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.

  12. 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).

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  14. Cloud model bat algorithm.

    PubMed

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

    2014-01-01

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

  15. 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

  16. 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

  17. 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

  18. 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

  19. Cirrus cloud retrieval using infrared sounding data: Multilevel cloud errors

    NASA Technical Reports Server (NTRS)

    Baum, Bryan A.; Wielicki, Bruce A.

    1994-01-01

    In this study we perform an error analysis for cloud-top pressure retrieval using the High-Resolution Infrared Radiometric Sounder (HIRS/2) 15-microns CO2 channels for the two-layer case of transmissive cirrus overlying an overcast, opaque stratiform cloud. This analysis includes standard deviation and bias error due to instrument noise and the presence of two cloud layers, the lower of which is opaque. Instantaneous cloud pressure retrieval errors are determined for a range of cloud amounts (0.1-1.0) and cloud-top pressures (850-250 mb). Large cloud-top pressure retrieval errors are found to occur when a lower opaque layer is present underneath an upper transmissive cloud layer in the satellite field of view (FOV). Errors tend to increase with decreasing upper-cloud effective cloud amount and with decreasing cloud height (increasing pressure). Errors in retrieved upper-cloud pressure result in corresponding errors in derived effective cloud amount. For the case in which a HIRS FOV has two distinct cloud layers, the difference between the retrieved and actual cloud-top pressure is positive in all cases, meaning that the retrieved upper-cloud height is lower than the actual upper-cloud height. In addition, errors in retrieved cloud pressure are found to depend upon the lapse rate between the low-level cloud top and the surface. We examined which sounder channel combinations would minimize the total errors in derived cirrus cloud height caused by instrument noise and by the presence of a lower-level cloud. We find that while the sounding channels that peak between 700 and 1000 mb minimize random errors, the sounding channels that peak at 300-500 mb minimize bias errors. For a cloud climatology, the bias errors are most critical.

  20. 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.

  1. 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.

  2. Outcome of the Third Cloud Retrieval Evaluation Workshop

    NASA Astrophysics Data System (ADS)

    Roebeling, R.; Baum, B.; Bennartz, R.; Hamann, U.; Heidinger, A.; Thoss, A.; Walther, A.

    2012-04-01

    Accurate measurements of global distributions of cloud parameters and their diurnal, seasonal, and inter-annual variations are needed to improve the understanding of the role of clouds in the weather and climate system, and to monitor their time-space variations. Cloud properties retrieved from satellite observations, such as cloud vertical placement, cloud water path and cloud particle size, play an important role 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 need to be quantified. The purpose of the Cloud Retrieval Evaluation Workshop (CREW), which was held from 15-18 November 2011 in Madison, Wisconsin, USA, is to enhance our knowledge on state-of-art cloud properties retrievals from passive imaging satellites, and pave the path towards optimising these retrievals for climate monitoring as well as for the analysis of cloud parameterizations in climate and weather models. CREW also seeks to observe and understand methods that are used to prepare daily and monthly cloud parameter climatologies. An important component of the workshop is the discussion on the 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 will summarize the outcome of the inter-comparison and validation work done in the framework of CREW, and elaborate on the reasons for the observed differences. More in depth discussions were held on retrieval principles and validation, and the utilization of cloud parameters for

  3. 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

  4. Outcome of the fourth Cloud Retrieval Evaluation Workshop

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  5. 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.

  6. 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.

  7. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2012-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  10. 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

  11. 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.

  12. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  14. Cloud Property Retrieval and 3D Radiative Transfer

    NASA Technical Reports Server (NTRS)

    Cahalan, Robert F.

    2003-01-01

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

  15. 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.

  16. 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

  17. Precipitating Snow Retrievals from Combined Airborne Cloud Radar and Millimeter-Wave Radiometer Observations

    NASA Technical Reports Server (NTRS)

    Grecu, Mircea; Olson, William S.

    2008-01-01

    An algorithm for retrieving snow over oceans from combined cloud radar and millimeter-wave radiometer observations is developed. The algorithm involves the use of physical models to simulate cloud radar and millimeter-wave radiometer observations from basic atmospheric variables such as hydrometeor content, temperature, and relative humidity profiles and is based on an optimal estimation technique to retrieve these variables from actual observations. A high-resolution simulation of a lake-effect snowstorm by a cloud-resolving model is used to test the algorithm. That is, synthetic observations are generated from the output of the cloud numerical model, and the retrieval algorithm is applied to the synthetic data. The algorithm performance is assessed by comparing the retrievals with the reference variables used in synthesizing the observations. The synthetic observation experiment indicates good performance of the retrieval algorithm. The algorithm is also applied to real observations from the Wakasa Bay field experiment that took place over the Sea of Japan in January and February 2003. The application of the retrieval algorithm to data from the field experiment yields snow estimates that are consistent with both the cloud radar and radiometer observations.

  18. 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.

  19. 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).

  20. 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.

  1. Retrieving Latent Heat Vertical Structure Using Precipitation and Cloud Profiles

    NASA Astrophysics Data System (ADS)

    Li, R.; Min, Q.; Wu, X.

    2011-12-01

    The latent heat (LH) released from tropical precipitation plays a critical role in driving regional and global atmosphere circulation. However, the vertical distribution of LH is one of most difficult parameters to be measured and has a large uncertainty in both residual diagnostic products and satellite retrievals. Most of current satellite LH products use limited observational information of precipitation and cloud profiles and highly depend on cloud resolving model (CRM) simulations. Our novel approach, distinguishing from existing schemes, is directly using observable precipitation and cloud profiles in combination with phase change partition parameterization of various kinds from the CRM simulations to produce the latent heating profiles. This hybrid latent heat algorithm separately deals with the condensation-evaporation heating (LHc_e), the deposition-sublimation heating (LHd_s) and the freezing-melting heating (LHf_m) for convective rain, stratiform rain, and shallow warm rain. Each component is based on physical processes, such as nucleation and auto conversion, by combining observable precipitation and cloud profiles. Although the proposed algorithm utilizes microphysical parameterizations from a specific CRM, the general LH vertical structure is primarily determined by the precipitation and cloud profiles observable from cloud and precipitation radars available at ground sites or from satellite platforms, and less sensitive to the specific CRM. The self consistency tests of this algorithm show good agreements with the CRM simulated LH at different spatial and temporal scales, even at simultaneous and pixel level. The applications of this algorithm are expected to provide new information for understanding the heating budget in the atmosphere and its impacts on the atmosphere circulations at various spatial and temporal scales.

  2. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2003-01-01

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

  4. 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

  5. An intercomparison of radar-based liquid cloud microphysics retrievals and implication for model evaluation studies

    NASA Astrophysics Data System (ADS)

    Huang, D.; Zhao, C.; Dunn, M.; Dong, X.; Mace, G. G.; Jensen, M. P.; Xie, S.; Liu, Y.

    2011-12-01

    To assess if current radar-based liquid cloud microphysical retrievals of the Atmospheric Radiation Measurement (ARM) program can provide useful constraints for modeling studies, this paper presents intercomparison results of three cloud products at the Southern Great Plains (SGP) site: the ARM MICROBASE, University of Utah (UU), and University of North Dakota (UND) products over the nine-year period from 1998 to 2006. The probability density and spatial autocorrelation functions of the three cloud Liquid Water Content (LWC) retrievals appear to be consistent with each other, while large differences are found in the droplet effective radius retrievals. The differences in the vertical distribution of both cloud LWC and droplet effective radius retrievals are found to be alarmingly large, with the relative difference between nine-year mean cloud LWC retrievals ranging from 20% at low altitudes to 100% at high altitudes. Nevertheless, the spread in LWC retrievals is much smaller than that in cloud simulations by climate and cloud resolving models. The MICROBASE effective radius ranges from 2.0 at high altitudes to 6.0 μm at low altitudes and the UU and UND droplet effective radius is 6 μm larger. Further analysis through a suite of retrieval experiments shows that the difference between MICROBASE and UU LWC retrievals stems primarily from the partition total Liquid Water path (LWP) into supercooled and warm liquid, and from the input cloud boundaries and LWP. The large differences between MICROBASE and UU droplet effective radius retrievals are mainly due to rain/drizzle contamination and the assumptions of cloud droplet concentration used in the retrieval algorithms. The large discrepancy between different products suggests caution in model evaluation with these observational products, and calls for improved retrievals in general.

  6. System engineering approach to GPM retrieval algorithms

    SciTech Connect

    Rose, C. R.; Chandrasekar, V.

    2004-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  8. 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.

  9. 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.

  10. An improved cloud retrieval algorithim using HIRS2-MSU radiance measurements

    NASA Technical Reports Server (NTRS)

    Mcmillin, Larry; Zhou, Si-Song; Yang, Shi-Keng

    1994-01-01

    Cloud-top heights and cloud amounts are produced as part of the operational processing of polar-satellite data at the National Environmental Satellite Data and Information Service (NESDIS). These products were compared with similar products from the air force's real-time nephanalysis (RTNEPH), from the International Satellite Cloud Climatology Project, and from NASA Goddard's processing of satellite data. It was found that the amount of high-level cloud was too small in the NESDIS results, while the amount of low-level cloud was too large. An examination of the NESDIS algorithm revealed that the differences in cloud distributions were caused by the selection of channels used for the cloud retrievals. Cloud retrievals are most accurate at the levels at which the channels that are used are most sensitive. In addition, it was found that no one pair of channels was best at all levels. A new procedure was developed that varied the channels as a function of an initial estimate of the cloud height. This procedure produced improved cloud retrievals that were then compared with the RTNEPH results. The comparison showed that the two methods provide similar retrievals of cloud height and amount.

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  12. 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

  13. 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.

  14. 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.

  15. 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).

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

    PubMed

    Schmidt, Jörg; Wandinger, Ulla; Malinka, Aleksey

    2013-04-10

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

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

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

    NASA Astrophysics Data System (ADS)

    Wolters, E. L. A.

    2012-03-01

    This thesis presents the retrieval, evaluation, and application of cloud physical property datasets (cloud phase, cloud particle effective radius, and precipitation occurrence and intensity) obtained from Spinning Enhanced Visible and Infrared Imager (SEVIRI) reflectance measurements using the Cloud Physical Properties (CPP) retrieval algorithm. In Chapter 3 it is shown that the CPP cloud-phase retrieval algorithm has sufficient accuracy (< 5%) and precision (< 10%) for climate monitoring purposes through comparisons with ground-based radar and lidar cloud-phase observations. In addition, the increase in ice cloud occurrence frequency throughout the day resulting from convection can be followed well. In Chapter 4, the effect of different horizontal sampling resolutions on the cloud particle effective radius (re) and cloud-phase retrievals in case of broken and inhomogeneous overcast clouds is quantified using both simulations and retrievals. At low cloud fractions, the retrieved low-resolution re is overestimated by up to 5 μm compared to at high resolution, due to the contribution of the underlying surface to the observed reflectances. In about 4% of the cases this overestimation leads to cloud-phase misclassifications, which is reduced to 2% when applying an additional cloud-top temperature check in the cloud-phase retrieval algorithm. The accuracy of CPP precipitation retrievals is evaluated with TRMM-PR and CMORPH observations in Chapter 5. Rain occurrence frequency from CPP-PP agrees well with TRMM-PR-observed values (corr=0.86), while rain rates agree to a lesser extent (corr=0.50). Investigation of the precipitation intensity frequency distributions from CPP reveal good agreement with TRMM-PR and rain gauge observations, although at moderate rain rates CPP overestimates relative to the rain gauges. Further, it is demonstrated that CPP is suitable to monitor both the seasonal and diurnal cycle of rainfall during daytime. CPP detects a larger dynamical range

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Retrieval of the aerosol direct radiative effect over clouds from spaceborne spectrometry

    NASA Astrophysics Data System (ADS)

    Graaf, M.; Tilstra, L. G.; Wang, P.; Stammes, P.

    2012-04-01

    The solar radiative absorption by an aerosol layer above clouds is quantified using passive satellite spectrometry from the ultraviolet (UV) to the shortwave infrared (SWIR). UV-absorbing aerosols have a strong signature that can be detected using UV reflectance measurements, even when above clouds. Since the aerosol extinction optical thickness decreases rapidly with increasing wavelength for biomass burning aerosols, the properties of the clouds below the aerosol layer can be retrieved in the SWIR, where aerosol extinction optical thickness is sufficiently small. Using radiative transfer computations, the contribution of the clouds to the reflected radiation can be modeled for the entire solar spectrum. In this way, cloud and aerosol effects can be separated for a scene with aerosols above clouds. Aerosol microphysical assumptions and retrievals are avoided by modeling only the pure (aerosol-free) cloud spectra. An algorithm was developed using the spaceborne spectrometer Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY). The aerosol direct radiative effect (DRE) over clouds over the South Atlantic Ocean west of Africa, averaged through August 2006 was found to be 23 ± 8 Wm-2 with a mean variation over the region in this month of 22 Wm-2. The largest aerosol DRE over clouds found in that month was 132 ± 8 Wm-2. The algorithm can be applied to any instrument, or a combination of instruments, that measures UV, visible and SWIR reflectances at the top of the atmosphere (TOA) simultaneously.

  9. The radiative consistency of Atmospheric Infrared Sounder and Moderate Resolution Imaging Spectroradiometer cloud retrievals

    NASA Astrophysics Data System (ADS)

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

    2007-05-01

    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 (ΔTb,e) for identical observing scenes are useful as a diagnostic for cloud quantity comparisons. The smallest values of ΔTb,e are for high and opaque clouds, with increasing scatter in ΔTb,e for clouds of smaller opacity and lower altitude. A persistent positive bias in ΔTb,e is observed in warmer and low-latitude scenes, characterized by a mixture of MODIS CO2 slicing and 11-μm window retrievals. These scenes contain heterogeneous cloud cover, including mixtures of multilayered cloudiness and misplaced MODIS cloud top pressure. The spatial patterns of ΔTb,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 ΔTb,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.

  10. 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.

  11. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  13. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  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. 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.

  17. 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.

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

    NASA Astrophysics Data System (ADS)

    Laviola, Sante; Levizzani, Vincenzo

    2011-03-01

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

  19. Retrieval of cirrus cloud optical thickness and top altitude from geostationary remote sensing

    NASA Astrophysics Data System (ADS)

    Kox, S.; Bugliaro, L.; Ostler, A.

    2014-04-01

    A novel approach for the detection of cirrus clouds and the retrieval of optical thickness and top altitude based on the measurements of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard the geostationary Meteosat Second Generation (MSG) satellite is presented. Trained with 8 000 000 co-incident measurements of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission the new "cirrus optical properties derived from CALIOP and SEVIRI algorithm during day and night" (COCS) algorithm utilizes a backpropagation neural network to provide accurate measurements of cirrus optical depth τ at λ =532 nm and top altitude z every 15 min covering almost one third of Earth's atmosphere. The retrieved values are validated with independent measurements of CALIOP and the optical thickness derived by an airborne high spectral resolution lidar.

  20. Retrieval of cirrus cloud optical thickness and top altitude from geostationary remote sensing

    NASA Astrophysics Data System (ADS)

    Kox, S.; Bugliaro, L.; Ostler, A.

    2014-10-01

    A novel approach for the detection of cirrus clouds and the retrieval of optical thickness and top altitude based on the measurements of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard the geostationary Meteosat Second Generation (MSG) satellite is presented. Trained with 8 000 000 co-incident measurements of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission the new "cirrus optical properties derived from CALIOP and SEVIRI algorithm during day and night" (COCS) algorithm utilizes a backpropagation neural network to provide accurate measurements of cirrus optical depth τ at λ = 532 nm and top altitude z every 15 min covering almost one-third of the Earth's atmosphere. The retrieved values are validated with independent measurements of CALIOP and the optical thickness derived by an airborne high spectral resolution lidar.

  1. Neural Networks algorithm development for polarimetric observations of above cloud aerosols (ACA)

    NASA Astrophysics Data System (ADS)

    Segal-Rosenhaimer, M.; Knobelspiesse, K. D.; Redemann, J.

    2015-12-01

    The direct and indirect radiative effects of above clouds aerosols (ACA) are still highly uncertain in current climate assessments. Much of this uncertainty is observational as most orbital remote sensing algorithms were not designed to simultaneously retrieve aerosol and cloud optical properties. Recently, several algorithms have been developed to infer ACA loading and properties using passive, single view angle instruments (OMI, MODIS). Yet, these are not operational and still require rigorous validation. Multiangle polarimetric instruments like POLDER, and RSP show promise for detection and quantification of ACA. However, the retrieval methods for polarimetric measurements entail some drawbacks such as assuming homogeneity of the underlying cloud field for POLDER and retrieved cloud effective radii as an input into RSP scheme. In addition, these methods require computationally expensive RT calculations, which precludes real-time polarimetric data analysis during field campaigns. Here we describe the development of a new algorithm to retrieve atmospheric aerosol and cloud optical properties from observations by polarimetrically sensitive instruments using Neural Networks (NN), which are computationally efficient and fast enough to produce results in the field. This algorithm is specific for ACA, and developed primarily to support the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign, which will acquire measurements of ACA in the South-East Atlantic Ocean during episodes of absorbing aerosols above Stratocumulus cloud decks in 2016-18. The algorithm will use a trained NN scheme for concurrent cloud and aerosol microphysical property retrievals that will be input to optimal estimation method. We will discuss the overall retrieval scheme, focusing on the input variables. Specifically, we use principle component analysis (PCA) to examine the information content available to describe the simulated cloud scenes (with adequate noise

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

    NASA Technical Reports Server (NTRS)

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

    2006-01-01

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

  3. Optimal Estimation Retrieval of Cloud Ice Particle Size Distributions

    NASA Astrophysics Data System (ADS)

    Griffith, B. D.; Kummerow, C.

    2006-12-01

    An optimal estimation retrieval technique has been applied to a multi-frequency airborne radar and radiometer data set from the Wakasa Bay AMSR-E validation experiment. First, airborne radar observations at 13.4, 35.6 and 94.9 GHz were integrated to retrieve all three parameters of a normalized gamma ice particle size distribution (PSD). The retrieved PSD was validated against near-simultaneous in situ cloud probe observations. The differences between the retrieved and in situ measured PSDs were explored through sensitivity analysis, and the sources of uncertainty were found to be the bulk density of the cloud ice and the aspect ratio of aspherical particles modeled as oblate spheroids. The optimal estimation technique was then applied to select an optimal density and aspect ratio for the cloud under study through integration of the in situ and radar observations. The optimal ice size-density relationship was found to be ρ(D)=0.07×D^{- 1.58} g cm-3 where the diameter, D, is in mm, and the oblate spheroid aspect ratio was found to be 0.53. The use of these optimal values, as improved assumptions in the PSD retrieval, reduced the uncertainty in the optimized forward model from ± 6 dB to ± 2 dB. Next, the retrieval technique was expanded to include passive microwave observations and retrieve a full column vertical hydrometeor profile. Eleven airborne passive microwave frequencies from 10.7 to 340 GHz were integrated with the airborne radar observations to retrieve all three parameters of a normalized gamma PSD at each vertical level in the column. The retrieved vertical profile was validated against a clear sky scene before being applied to the horizontal extent of an ice cloud. The retrieved PSD showed vertical structure consistent with cloud microphysical processes. PSDs were retrieved using both the general and improved assumption case-specific density and shape models. A comparison revealed an order of magnitude difference in ice water path between the two

  4. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  6. A 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.

  7. 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.

  8. 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.

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

    SciTech Connect

    Dunn, M; Johnson, K; Jensen, M

    2011-05-31

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

  10. 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.

  11. Past, present, and future of the MISR height-resolved, cloud-track wind retrieval

    NASA Astrophysics Data System (ADS)

    Mueller, K. J.; Moroney, C. M.; Garay, M. J.; Jovanovic, V. M.

    2009-12-01

    MISR multi-angle measurements offer the unique capability of resolving position, altitude, and motion of clouds over a 7 minute interval, purely by image correspondence and geometric triangulation. Cloud motion is retrieved operationally at 70.4km x 70.4km horizontal resolution and packaged as part of the MISR standard suite of products. A consistent approach, requiring no a priori information and applied globally throughout MISR’s 10-year history, make this product suitable for reanalysis of wind in observation sparse regions such as the Poles or the Southern Ocean. Featuring far superior resolution (17.6km along satellite trajectory, 1.1km across), 2.5 times the coverage, and increased precision and accuracy, the upcoming MISR cloud motion product will extend scientific applicability to the mesoscale: including hurricane modeling, and marine stratocumulus organization. This product release will build upon a steady evolution of algorithm enhancements that have transformed cloud motion retrieval from a measurement first conceived as a means of calculating unbiased cloud height, into a first-class science product. Here we will review previous and upcoming milestones in this evolution. The accuracy, bias, and coverage of past and forthcoming algorithm revisions relative to standard wind validation datasets including rawinsonde retrievals and NCEP reanalysis will be reviewed.

  12. Assessment of the NPOESS/VIIRS Nighttime Infrared Cloud Optical Properties Algorithms

    NASA Astrophysics Data System (ADS)

    Wong, E.; Ou, S. C.

    2008-12-01

    In this paper we will describe two NPOESS VIIRS IR algorithms used to retrieve microphysical properties for water and ice clouds during nighttime conditions. Both algorithms employ four VIIRS IR channels: M12 (3.7 μm), M14 (8.55 μm), M15 (10.7 μm) and M16 (12 μm). The physical basis for the two algorithms is similar in that while the Cloud Top Temperature (CTT) is derived from M14 and M16 for ice clouds the Cloud Optical Thickness (COT) and Cloud Effective Particle Size (CEPS) are derived from M12 and M15. The two algorithms depart in the different radiative transfer parameterization equations used for ice and water clouds. Both the VIIRS nighttime IR algorithms and the CERES split-window method employ the 3.7 μm and 10.7 μm bands for cloud optical properties retrievals, apparently based on similar physical principles but with different implementations. It is reasonable to expect that the VIIRS and CERES IR algorithms produce comparable performance and similar limitations. To demonstrate the VIIRS nighttime IR algorithm performance, we will select a number of test cases using NASA MODIS L1b radiance products as proxy input data for VIIRS. The VIIRS retrieved COT and CEPS will then be compared to cloud products available from the MODIS, NASA CALIPSO, CloudSat and CERES sensors. For the MODIS product, the nighttime cloud emissivity will serve as an indirect comparison to VIIRS COT. For the CALIPSO and CloudSat products, the layered COT will be used for direct comparison. Finally, the CERES products will provide direct comparison with COT as well as CEPS. This study can only provide a qualitative assessment of the VIIRS IR algorithms due to the large uncertainties in these cloud products.

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

    SciTech Connect

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

    2005-03-18

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

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

    PubMed

    Piatt, C M; Takashima, T

    1987-04-01

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

  15. 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

  16. 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

  17. 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.

  18. Validation of MODIS aerosol retrievals and evaluation of potential cloud contamination in East Asia.

    PubMed

    Xia, Xiang-Ao; Chen, Hong-Bin; Wang, Pu-Cai

    2004-01-01

    MODIS aerosol retrievals onboard Terra/Aqua and ground truth data obtained from AERONET (Aerosol Robtic Network) solar direct radiance measurements are collocated to evaluate the quality of the former in East Asia. AERONET stations in East Asia are separated into two groups according to their locations and the preliminary validation results for each station. The validation results showed that the accuracy of MODIS aerosol retrievals in East Asia is a little worse than that obtained in other regions such as Eastern U.S., Western Europe, Brazil and so on. The primary reason is due to the improper aerosol model used in MODIS aerosol retrieval algorithm, so it is of significance to characterize aerosol properties properly according to long-term ground-based remote sensing or other relevant in situ observations in order to improve MODIS retrievals in East Asia. Cloud contamination is proved to be one of large errors, which is demonstrated by the significant relation between MODIS aerosol retrievals versus cloud fraction, as well as notable improvement of linear relation between satellite and ground aerosol data after potential cloud contamination screened. Hence, it is suggested that more stringent clear sky condition be set in use of MODIS aerosol data. It should be pointed out that the improvement might be offset by other error sources in some cases because of complex relation between different errors. Large seasonal variation of surface reflection and uncertainties associated with it result in large intercepts and random error in MODIS aerosol retrievals in northern inland of East Asia. It remains to be a big problem to retrieve aerosols accurately in inland characterized by relatively larger surface reflection than the requirement in MODIS aerosol retrieval algorithm.

  19. 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

  20. 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

  1. 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.

  2. Fast cloud parameter retrievals of MIPAS/Envisat

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  3. 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.

  4. 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

  5. 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.

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

    PubMed

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

    2016-05-24

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

  7. 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.

  8. Evaluating CloudSat Ice Water Retrievals Using a Cloud Resolving Model: Sensitivities to Frozen Particle Properties and Implications for Model-Data Comparisons

    NASA Astrophysics Data System (ADS)

    Woods, C. P.; Waliser, D.; Li, F.; Austin, R.; Stephens, G.; Vane, D.; Tao, W.; Tompkins, A.

    2007-12-01

    The sensitivities of CloudSat ice water content retrievals to frozen particle characteristics are tested by generating CloudSat-like retrievals from profiles of known ice water content. First, `truth' values of total ice water content are generated by a cloud-resolving model (MM5). The MM5 model profiles are generated using the Reisner- Thompson microphysical parameterization scheme, which allows for the existence of multiple types of frozen particles (cloud ice, snow and graupel). Next, a 94-GHz reflectivity simulator, called QuickBeam, is used to generate a CloudSat-like view of the model generated profiles. Since reflectivity is highly dependent on the characteristics of the scattering particles (e.g., density, size distribution), a set of tests are performed to determine the sensitivity of the reflectivity to the assumed properties of cloud ice and snow particles. Finally, the CloudSat ice water content retrieval algorithm is applied to the profiles of 94-GHz reflectivity, producing 'simulated retrieved' values of ice water content, which can be compared to the `truth' values. The comparisons suggest that CloudSat ice water content retrievals are sensitive to the frozen particle properties often parameterized in models (e.g., particle density, particle size distributions). The sensitivity tests provide a better understanding of how the different components of the frozen water mass impact the ice water content retrieved by CloudSat. Such information is important when comparing the measurements to modeled frozen water mass quantities, including those from various levels of sophistication in global climate models. Additionally, we demonstrate how information gained in this study may be used for improving the retrieval system. A simple height-based retrieval correction that effectively corrects for the vertically varying characteristics of frozen particles is examined.

  9. 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.

  10. 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

  11. 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

  12. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  14. Estimation of 3-D Cloud Effects on TOMS Satellite Retrieval of Surface UV Irradiance

    NASA Technical Reports Server (NTRS)

    Krotkov, Nickolay A.; Geogdzhayev, I.; Herman, J. R.

    1998-01-01

    To improve surface UV irradiance retrieval from the Total Ozone Mapping Spectrometer (TOMS) we simulate errors of the TOMS cloud correction algorithm for summertime broken cloud conditions. Cloud scenes (50 km by 50 km) are modeled by a normal random (Gaussian) field with a fixed lower boundary and conservative scattering. The model relates stochastic field characteristics with the cloud amount, mean cloud diameter and aspect ratio. Clouds are embedded into Rayleigh atmosphere with standard ozone profile. Radiative transfer calculations of the radiance at the top of the atmosphere and irradiance at the surface were performed using 3-D Monte Carlo (MC) code. The results are averaged over the satellite field of view on the surface (50 km by 50 km) and compared with TOMS predicted surface irradiance for the same scene reflectance. The TOMS algorithm assumes horizontally homogeneous Cl-type cloud between 3 km and 5.5 km. The effective optical depth is determined by fitting observed (MC) radiance at 380 nm. Having the same radiance at the satellite the homogeneous and broken cloud models predict different average irradiances at the surface. This is due to the differences in Bidirectional Reflection Distribution Function (BRDF) for homogeneous and broken cloud scenes with the same hemispherical albedo. For typical TOMS observational geometry at mid-latitudes the simulated single pixels errors may be as large as +/- 20%. Qualitatively these errors are due to the dominance of the non-horizontal cloud surfaces, which are not accounted for in the homogeneous cloud model. However, due to high variability of the real cloud shapes and types it is unclear how these single pixel errors would affect TOMS time-integrated UV exposure over extended periods (weeks to months) for different regions.

  15. 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.

  16. 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

  17. 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)

  18. 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

  19. 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).

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

    SciTech Connect

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

    2004-03-01

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

  1. Cloud optical thickness retrievals from ground-based pyranometer measurements

    NASA Astrophysics Data System (ADS)

    Qiu, Jinhuan

    2006-11-01

    A method is developed to retrieve total cloud optical thickness (COT) from global solar radiation (GSR) detected by ground-based pyranometer, and approaches to input aerosol/molecular/gas parameters for COT retrievals are presented. On the basis of numerical simulations and comparative tests, main error factors of COT retrievals are analyzed, which include radiation data error, cloud inhomogeneity, uncertainties of aerosol optical parameters, and surface albedo. The retrieved COT error, caused by a -5% or 5% systematic error of the GSR measurement, is within ±0.6 and ±5.0 for COT ranges of 0-5.0 and 5-100, respectively. The AOT, the aerosol single scatter albedo (SSA), and the surface albedo are three significant parameters affecting COT retrieval accuracy. The mean SSA in the pyranometer spectral response range and the broadband surface albedo are suitably used in the retrievals. If uncertainties of AOT, SSA, and surface albedo are within ±0.1, ±0.05, and ±0.05, respectively, the retrieval accuracy is accepted for most applications. Furthermore, COTs (τPyr) from pyranometer data at two meteorological observatories are compared with COTs (τISCCP) from ISCCP and COTs (τMODIS) from MODIS. The relative standard deviations between monthly mean τPyr and τMODIS, or τPyr and τISCCP, are all less than 45.4% for both sites. The agreement among the yearly mean τPyr,τMODIS, and τISCCP is satisfactory. The absolute (relative) deviations between the yearly mean τPyr and τMODIS are within ±1.55 (8%) for both sites, and the deviations between the τPyr and τISCCP are within ±1.94 (25%). The yearly mean τPyr also agrees considerably well with τISCCP in the broken cloud case.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  9. 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.

  10. 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

  11. 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.

  12. Improving Estimates of Cloud Properties Through the Application of an Adiabatic Spectrally Consistent Retrieval to the MODIS Cloud Product

    NASA Astrophysics Data System (ADS)

    Rausch, J.; Bennartz, R.; Puygrenier, V.; Brenguier, J. L.

    2014-12-01

    We attempt to infer cloud vertical structure and improve estimates of cloud microphysical properties through the application of an Adiabatic Spectrally Consistent Retrieval (ASCR) to Moderate Resolution Imaging Spectroradiometer (MODIS) observations. The MODIS Cloud Product provides estimates of cloud optical thickness and droplet effective radius for three near-infrared absorption wavelengths (1.6, 2.1 and 3.7 mm) under the assumption of a plane-parallel, vertically homogeneous (VH) cloud. This is not a physically realistic assumption for boundary layer clouds, where an adiabatically stratified liquid water content profile conforms better. ASCR transforms VH retrievals of optical thickness and droplet effective radii into adiabatically stratified retrievals, exploiting the varying photon penetration depth of each absorption channel. Taking advantage of the data screening and quality controls applied to the MODIS Cloud Product, existing retrievals of optical thickness and droplet effective radii are inverted to obtain equivalent scene reflectances from which two-channel and four-channel adiabatically stratified retrievals of cloud geometrical thickness (H) and cloud droplet number concentration (N) are performed using an optimal estimation framework. Through a comparison of the 2-channel and 4-channel N and H retrievals, we attempt to estimate the degree to which a cloud conforms to an adiabatically stratified model, near cloud-top. Results will be presented, demonstrating ASCR's performance relative to VH retrievals from the cloud product through an analysis of one year's observations of marine stratocumulus from MODIS near the South American and African Continents.

  13. 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.

  14. 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.

  15. Development of aerosol retrieval algorithm for Geostationary Environmental Monitoring Spectrometer (GEMS)

    NASA Astrophysics Data System (ADS)

    Kim, Mijin; Kim, Jhoon; Park, Sang Seo; Jeong, Ukkyo; Ahn, Changwoo; Bhartia, Pawan. K.; Torres, Omar; Song, Chang-Keun; Han, Jin-Seok

    2014-05-01

    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). 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 (LUT) with assumed aerosol properties and measurement condition. To calculate LUT, aerosol optical properties over Asia [70°E-145°E, 0°N-50°N] are obtained from AERONET inversion data (level 2.0) at 46 AERONET sites, and are applied to VLIDORT (spur, 2006). Because the backscattering radiance in UV-Visible range has significant sensitivity to radiance absorptivity and size distribution of loading aerosol, aerosol types are classified from AERONET inversion data by using aerosol classification method suggested in Lee et al. (2010). Then the LUTs are calculated with average optical properties for each aerosol type. The GEMS aerosol algorithm is tested with OMI level-1B dataset, a provisional data for GEMS measurement. The aerosol types for each measured scene are selected by using both of UVAI and VISAI, and AOD and SSA are simultaneously retrieved by comparing simulated radiance with selected aerosol type and the measured value. The AOD and SSA retrieved from GEMS aerosol algorithm are well matched with OMI products, although the retrieved AOD is slightly higher than OMI value. To detect cloud pixel, spatial standard deviation test of radiance is applied in the

  16. 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).

  17. An algorithm to retrieve precipitation with synthetic aperture radar

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  18. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  20. [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.

  1. 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.

  2. A method to retrieve super-thin cloud optical depth over ocean background with polarized sunlight

    NASA Astrophysics Data System (ADS)

    Sun, W.; Baize, R. R.; Videen, G.; Hu, Y.; Fu, Q.

    2015-10-01

    In this work, an algorithm that uses the polarization angle of the backscattered solar radiation to detect clouds with optical depth (OD) < ~ 0.3 is further developed. We find that at viewing angles within ± ∼ 8° around the backscattering direction, the p-polarized intensity that is parallel to the meridian plane of reflected light from the surface is sensitive to, and nearly linearly related to, the optical depth of super-thin clouds. Moreover, our sensitivity study suggests that the p-polarized intensity at these viewing angles is not sensitive to the ocean surface conditions. Using this property of p-polarized intensity, super-thin clouds' optical depth can be retrieved.

  3. 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…

  4. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

    We explore systematically the cumulative effect of many assumptions made in the Multi-angle Imaging SpectroRadiometer (MISR) research aerosol retrieval algorithm with the aim of quantifying the main sources of uncertainty over ocean, and correcting them to the extent possible. A total of 1129 coincident, surface-based sun photometer spectral aerosol optical depth (AOD) measurements are used for validation. Based on comparisons between these data and our baseline case (similar to the MISR standard algorithm, but without the "modified linear mixing" approximation), for 558 nm AOD < 0.10, a high bias of 0.024 is reduced by about one-third when (1) ocean surface under-light is included and the assumed whitecap reflectance at 672 nm is increased, (2) physically based adjustments in particle microphysical properties and mixtures are made, (3) an adaptive pixel selection method is used, (4) spectral reflectance uncertainty is estimated from vicarious calibration, and (5) minor radiometric calibration changes are made for the 672 and 866 nm channels. Applying (6) more stringent cloud screening (setting the maximum fraction not-clear to 0.50) brings all median spectral biases to about 0.01. When all adjustments except more stringent cloud screening are applied, and a modified acceptance criterion is used, the Root-Mean-Square-Error (RMSE) decreases for all wavelengths by 8-27% for the research algorithm relative to the baseline, and is 12-36% lower than the RMSE for the Version 22 MISR standard algorithm (SA, with no adjustments applied). At 558 nm, 87% of AOD data falls within the greater of 0.05 or 20% of validation values; 62% of the 446 nm AOD data, and > 68% of 558, 672, and 866 nm AOD values fall within the greater of 0.03 or 10%. For the Ångström exponent (ANG), 67% of 1119 validation cases for AOD > 0.01 fall within 0.275 of the sun photometer values, compared to 49% for the SA. ANG RMSE decreases by 17% compared to the SA, and the median absolute error drops by

  6. Visualizing and improving the robustness of phase retrieval algorithms

    SciTech Connect

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

    2015-06-01

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

  7. 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.

  8. 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

  9. 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.

  10. Retrieval of cloud top height, effective emissivity, and particle size, from aircraft high-spectral-resolution infrared measurements

    NASA Astrophysics Data System (ADS)

    Antonelli, Paolo B.; Ackerman, Steven A.; Menzel, W. Paul; Huang, Hung-Lung; Baum, Bryan A.; Smith, William L.

    2002-02-01

    In this study we compare different approaches to retrieve Cloud Top Height (CTH), Cloud Effective Emissivity (CEE), and the Cloud Particle Size (CPS) from aircraft high-spectral resolution infrared measurements. Two independent methods are used to infer CTH. One approach is based on a high spectral resolution version of the CO2 Slicing algorithm characterized by a statistically based selection of the optimal channel pairs. Another approach the Minimum Local Emissivity Variance algorithm (MLEV) takes advantage of high-resolution observations in the 8-12 micron region to simultaneously derive CTH and CEE. Once CTH has been retrieved a third method, based on the comparison between simulated and observed radiances, is used to infer CPS and CEE. Simulated radiances are computed for 18 microwindows between 8.5 and 12 microns. The cirrus scattering calculations are based on three-dimensional randomly oriented ice columns assuming six different particle size distributions. Multiple scattering calculations are performed for 26 different cloud optical thicknesses (COT) between 0 and 20. The simulated radiances are then compared to the observed radiances to infer COT and CPS for each spectral measurement. We applied these approaches to High-resolution Interferometer Sounder (HIS), National Polar-Orbiting Operational Environmental Satellite System Airborne Sounder Testbed-Interferometer (NAST-I) and Scanning-HIS (S-HIS) data. The preliminary results, consistent between the different algorithms, suggest that the high spectral resolution measurements improve the accuracy of the cloud property retrievals.

  11. 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.

  12. FPGA implementation of sparse matrix algorithm for information retrieval

    NASA Astrophysics Data System (ADS)

    Bojanic, Slobodan; Jevtic, Ruzica; Nieto-Taladriz, Octavio

    2005-06-01

    Information text data retrieval requires a tremendous amount of processing time because of the size of the data and the complexity of information retrieval algorithms. In this paper the solution to this problem is proposed via hardware supported information retrieval algorithms. Reconfigurable computing may adopt frequent hardware modifications through its tailorable hardware and exploits parallelism for a given application through reconfigurable and flexible hardware units. The degree of the parallelism can be tuned for data. In this work we implemented standard BLAS (basic linear algebra subprogram) sparse matrix algorithm named Compressed Sparse Row (CSR) that is showed to be more efficient in terms of storage space requirement and query-processing timing over the other sparse matrix algorithms for information retrieval application. Although inverted index algorithm is treated as the de facto standard for information retrieval for years, an alternative approach to store the index of text collection in a sparse matrix structure gains more attention. This approach performs query processing using sparse matrix-vector multiplication and due to parallelization achieves a substantial efficiency over the sequential inverted index. The parallel implementations of information retrieval kernel are presented in this work targeting the Virtex II Field Programmable Gate Arrays (FPGAs) board from Xilinx. A recent development in scientific applications is the use of FPGA to achieve high performance results. Computational results are compared to implementations on other platforms. The design achieves a high level of parallelism for the overall function while retaining highly optimised hardware within processing unit.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  14. 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.

  15. 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.

  16. 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.

  17. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  19. 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.

  20. Independent component analysis based two-step phase retrieval algorithm

    NASA Astrophysics Data System (ADS)

    Xu, Xiaofei; Shou, Junwei; Lu, Xiaoxu; Yin, Zhenxing; Tian, Jindong; Li, Dong; Zhong, Liyun

    2016-10-01

    Based on the independent component analysis (ICA), we achieve phase retrieval from two-frame phase-shifting interferograms with unknown phase shifts. First, we remove the background of interferogram with a Gaussian high-pass filter. Second, the background-removed interferograms are decomposed into a group of mutual independent components through performing the pixel position recombination of an interferogram. Third, the phase shifts and the measured phase can be retrieved with high accuracy from the ratio of independent components. Compared with the existing two-step phase retrieval algorithms, both the simulation calculation and experimental result show that the proposed ICA based two-step algorithm reveals the advantage in the accuracy improvement of phase retrieval.

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

    NASA Astrophysics Data System (ADS)

    McKague, Darren Shawn

    2001-12-01

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

  2. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.; Feingold, G.; Eloranta, E.; O'Connor, E. J.; Cadeddu, M. P.

    2015-02-16

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

  11. [Progress in retrieving land surface temperature for the cloud-covered pixels from thermal infrared remote sensing data].

    PubMed

    Zhou, Yi; Qin, Zhi-Hao; Bao, Gang

    2014-02-01

    Land surface temperature (LST), which reflects surface properties, is one of the key parameters in the physics of land surface processes from local through global scales. LST is very required in time and space for a wide variety of scientific studies and thermal infrared (TIR) remote sensing applications. Satellite TIR channels are very available for LST retrieval but only in clear skies. However, when the surface is obscured by clouds, the actual retrieved LST for the corresponding pixel is, or is contaminated by, the cloud top temperature. Lacking understanding of the complex relationships between clouds and LST, the estimation of LST for cloud-covered pixels poses a big problem and challenge for thermal remote sensing scientists. In the present paper, a review of algorithms and approaches related to LST retrieval for cloud-covered pixels from TIR data is presented, and the characteristics of each method are also discussed. Directions for future research to improve the accuracy of satellite-derived LST for cloud-covered pixels are then suggested.

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

    NASA Astrophysics Data System (ADS)

    Lebsock, Matthew; Su, Hui

    2014-07-01

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

  13. 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

  14. 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.

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2003-04-01

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

  17. 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

  18. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  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. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

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

    PubMed

    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.

  4. 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

  5. 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.…

  6. A Fast Retrieving Algorithm of Hierarchical Relationships Using Trie Structures.

    ERIC Educational Resources Information Center

    Koyama, Masafumi; Morita, Kazuhiro; Fuketa, Masao; Aoe, Jun-Ichi

    1998-01-01

    Presents a faster method for determining hierarchical relationships in information retrieval by using trie structures instead of a linear storage of a concept code. Highlights include case structures, a knowledge representation for natural-language understanding with semantic constraints; a compression algorithm of tries; and evaluation.…

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

    NASA Technical Reports Server (NTRS)

    Lyapustin, Alexei; Wang, Yujie

    2008-01-01

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

  8. 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.; Feingold, G.; Eloranta, E.; O'Connor, E. J.; Cadeddu, M. P.

    2015-07-02

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

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

  10. A model sensitivity study of the impact of clouds on satellite detection and retrieval of volcanic ash

    NASA Astrophysics Data System (ADS)

    Kylling, A.; Kristiansen, N.; Stohl, A.; Buras-Schnell, R.; Emde, C.; Gasteiger, J.

    2015-05-01

    Volcanic ash is commonly observed by infrared detectors on board Earth-orbiting satellites. In the presence of ice and/or liquid-water clouds, the detected volcanic ash signature may be altered. In this paper the sensitivity of detection and retrieval of volcanic ash to the presence of ice and liquid-water clouds was quantified by simulating synthetic equivalents to satellite infrared images with a 3-D radiative transfer model. The sensitivity study was made for the two recent eruptions of Eyjafjallajökull (2010) and Grímsvötn (2011) using realistic water and ice clouds and volcanic ash clouds. The water and ice clouds were taken from European Centre for Medium-Range Weather Forecast (ECMWF) analysis data and the volcanic ash cloud fields from simulations by the Lagrangian particle dispersion model FLEXPART. The radiative transfer simulations were made both with and without ice and liquid-water clouds for the geometry and channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI). The synthetic SEVIRI images were used as input to standard reverse absorption ash detection and retrieval methods. Ice and liquid-water clouds were on average found to reduce the number of detected ash-affected pixels by 6-12%. However, the effect was highly variable and for individual scenes up to 40% of pixels with mass loading >0.2 g m-2 could not be detected due to the presence of water and ice clouds. For coincident pixels, i.e. pixels where ash was both present in the FLEXPART (hereafter referred to as "Flexpart") simulation and detected by the algorithm, the presence of clouds overall increased the retrieved mean mass loading for the Eyjafjallajökull (2010) eruption by about 13%, while for the Grímsvötn (2011) eruption ash-mass loadings the effect was a 4% decrease of the retrieved ash-mass loading. However, larger differences were seen between scenes (standard deviations of ±30 and ±20% for Eyjafjallajökull and Grímsvötn, respectively) and even larger ones

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  12. 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.

  13. 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.

  14. 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.

  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. Examination of phase retrieval algorithms for patterned EUV mask metrology

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  17. 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.

  18. 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.

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

    NASA Astrophysics Data System (ADS)

    Duncan, David I.; Kummerow, Christian D.

    2016-06-01

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

  20. 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

  1. 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

  2. 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.

  3. 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.

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

    NASA Astrophysics Data System (ADS)

    Islam, Tanvir; Srivastava, Prashant K.

    2015-08-01

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

  5. 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.

  6. 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

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. Development of microwave rainfall retrieval algorithm for climate applications

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Huang, Dong; Campos, Edwin; Liu, Yangang

    2014-09-01

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

  13. 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.

  14. Development and Validation of a Polar Cloud Algorithm for CERES

    NASA Technical Reports Server (NTRS)

    1999-01-01

    The objectives of this project, as described in the original proposal, were to develop an algorithm for diagnosing cloud properties over snow- and ice-covered surfaces, particularly at night, using satellite radiances from the Advanced Very High Resolution Radiometer (AVHRR) and High-resolution Infrared Radiation Sounder (HIRS) sensors. Products from this algorithm include a cloud mask and additional cloud properties such as cloud phase, amount, and height. The SIVIS software package, developed as a part of the CERES project, was originally the primary tool used to develop the algorithm, but as it is no longer supported we have had to pursue a new tool to enable the combination and analysis of collocated radiances from AVHRR and HIRS. This turned out to be a much larger endeavor than we expected, but we now have the data sets collocated (with many thanks to B. Baum for the fundamental code) and we have developed a nighttime cloud detection algorithm. Using this algorithm we have also computed realistic-looking cloud fractions from AVHRR brightness temperatures. A method to identify cloud phase has also been implemented. Atmospheric information from the TIROS Operational Vertical Sounder (TOVS) Polar Pathfinder Data Set, which includes temperature and moisture profiles as well as surface information, provides information required for determining cloud-top height.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  16. A physically-based retrieval of cloud liquid water from SSM/I measurements

    NASA Technical Reports Server (NTRS)

    Greenwald, Thomas J.; Stephens, Graeme L.; Vonder Haar, Thomas H.

    1992-01-01

    A simple physical scheme is proposed for retrieving cloud liquid water over the ice-free global oceans from Special Sensor Microwave/Imager (SSM/I) observations. Details of the microwave retrieval scheme are discussed, and the microwave-derived liquid water amounts are compared with the ground radiometer and AVHRR-derived liquid water for stratocumulus clouds off the coast of California. Global distributions of the liquid water path derived by the method proposed here are presented.

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  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. 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

  2. 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

  3. An intercomparison of radar-based liquid cloud microphysics retrievals and implications for model evaluation studies

    NASA Astrophysics Data System (ADS)

    Huang, D.; Zhao, C.; Dunn, M.; Dong, X.; Mace, G. G.; Jensen, M. P.; Xie, S.; Liu, Y.

    2012-06-01

    This paper presents a statistical comparison of three cloud retrieval products of the Atmospheric Radiation Measurement (ARM) program at the Southern Great Plains (SGP) site from 1998 to 2006: MICROBASE, University of Utah (UU), and University of North Dakota (UND) products. The probability density functions of the various cloud liquid water content (LWC) retrievals appear to be consistent with each other. While the mean MICROBASE and UU cloud LWC retrievals agree well in the middle of cloud, the discrepancy increases to about 0.03 gm-3 at cloud top and cloud base. Alarmingly large differences are found in the droplet effective radius (re) retrievals. The mean MICROBASE re is more than 6 μm lower than the UU re, whereas the discrepancy is reduced to within 1 μm if columns containing raining and/or mixed-phase layers are excluded from the comparison. A suite of stratified comparisons and retrieval experiments reveal that the LWC difference stems primarily from rain contamination, partitioning of total liquid later path (LWP) into warm and supercooled liquid, and the input cloud mask and LWP. The large discrepancy among the re retrievals is mainly due to rain contamination and the presence of mixed-phase layers. Since rain or ice particles are likely to dominate radar backscattering over cloud droplets, the large discrepancy found in this paper can be thought of as a physical limitation of single-frequency radar approaches. It is therefore suggested that data users should use the retrievals with caution when rain and/or mixed-phase layers are present in the column.

  4. 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

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. The effect of cloud screening on MAX-DOAS aerosol retrievals.

    NASA Astrophysics Data System (ADS)

    Gielen, Clio; Van Roozendael, Michel; Hendrik, Francois; Fayt, Caroline; Hermans, Christian; Pinardi, Gaia; De Backer, Hugo; De Bock, Veerle; Laffineur, Quentin; Vlemmix, Tim

    2014-05-01

    In recent years, ground-based multi-axis differential absorption spectroscopy (MAX-DOAS) has shown to be ideally suited for the retrieval of tropospheric trace gases and deriving information on the aerosol properties. These measurements are invaluable to our understanding of the physics and chemistry of the atmospheric system, and the impact on the Earth's climate. Unfortunately, MAX-DOAS measurements are often performed under strong non-clear-sky conditions, causing strong data quality degradation and uncertainties on the retrievals. Here we present the result of our cloud-screening method, using the colour index (CI), on aerosol retrievals from MAX-DOAS measurements (AOD and vertical profiles). We focus on two large data sets, from the Brussels and Beijing area. Using the CI we define 3 different sky conditions: bad (=full thick cloud cover/extreme aerosols), mediocre (=thin clouds/aerosols) and good (=clear sky). We also flag the presence of broken/scattered clouds. We further compare our cloud-screening method with results from cloud-cover fractions derived from thermic infrared measurements. In general, our method shows good results to qualify the sky and cloud conditions of MAX-DOAS measurements, without the need for other external cloud-detection systems. Removing data under bad-sky and broken-cloud conditions results in a strongly improved agreement, in both correlation and slope, between the MAX-DOAS aerosol retrievals and data from other instruments (e.g. AERONET, Brewer). With the improved AOD retrievals, the seasonal and diurnal variations of the aerosol content and vertical distribution at both sites can be investigated in further detail. By combining with additional information derived by other instruments (Brewer, lidar, ...) operated at the stations, we will further study the observed aerosol characteristics, and their influence on and by meteorological conditions such as clouds and/or the boundary layer height.

  10. 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.

  11. 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

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  1. 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.

  2. Retrieving cloud geometrical extents from MIPAS/ENVISAT measurements with a 2-D tomographic approach.

    PubMed

    Castelli, E; Dinelli, B M; Carlotti, M; Arnone, E; Papandrea, E; Ridolfi, M

    2011-10-10

    Clouds represent a critical factor in regulating the Earth's atmosphere and its energy balance. Satellite instruments can measure the energy balance and global atmospheric properties only through an accurate knowledge of the vertical profile of cloudiness, which is as yet one of the key shortages in atmospheric science. The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on-board the ENVISAT satellite, designed to infer the amount of atmospheric trace-gases, demonstrated also sensitivity to the radiation emitted from clouds. In order to model the effect of the geometrical extent of a cloud on MIPAS measurements, we developed a retrieval model capable to simulate cloud effects on broad spectral intervals accounting for the two-dimensional (2-D) variability of the atmosphere in the satellite orbit plane. The 2-D analysis revealed a sensitivity of MIPAS spectra to both the vertical and horizontal extents and the position of clouds along the instrument line of sight. One-dimensional models were found to underestimate Cloud Top Height (CTH) by approximating clouds as an infinite horizontal layer with a finite vertical extents. With the 2-D approach, we showed it is possible, for optically thin Polar Stratospheric Clouds (PSCs), to retrieve both CTH and horizontal dimension by analyzing simultaneously all the limb observations that come across the cloud with their field of view. For a selected case study we found a very good agreement for both PSC CTH and horizontal extents retrieved from MIPAS measurements and those retrieved from coincident CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarisation) measurements.

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  4. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

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

  6. Retrieval of Cloud Ice Water Content Profiles from Advanced Microwave Sounding Unit-B Brightness Temperatures Near the Atmospheric Radiation Measurement Southern Great Plains Site

    SciTech Connect

    Seo, E-K.; Liu, G.

    2005-03-18

    One of the Atmospheric Radiation Measurement (ARM) Program important goals is to develop and test radiation and cloud parameterizations of climate models using single column modeling (SCMs) (Randall et al. 1996). As forcing terms, SCMs need advection tendency of cloud condensates besides the tendencies of temperature, moisture and momentum. To compute the tendency terms of cloud condensates, 3D distribution of cloud condensates over a scale much larger than the climate model's grid scale is needed. Since they can cover a large area within a short time period, satellite measurements are useful utilities to provide advection tendency of cloud condensates for SCMs. However, so far, most satellite retrieval algorithms only retrieve vertically integrated quantities, for example, in the case of cloud ice, ice water path (IWP). To fulfill the requirement of 3D ice water content field for computing ice water advection, in this study, we develop an ice water content profile retrieval algorithm by combining the vertical distribution characteristics obtained from long-term surface radar observations and satellite high-frequency microwave observations that cover a large area. The algorithm is based on the Bayesian theorem using a priori database derived from analyzing cloud radar observations at the Southern Great Plains (SGP) site. The end product of the algorithm is a 3D ice water content covering 10{sup o} x 10{sup o} surrounding the SGP site during the passage of the satellite. This 3D ice water content, together with wind field analysis, can be used to compute the advection tendency of ice water for SCMs.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    SciTech Connect

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

    2014-01-15

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

  9. 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.

  10. 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.

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

    NASA Technical Reports Server (NTRS)

    Platnick, Steven E.

    2010-01-01

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

  12. 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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  14. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  17. 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

  18. 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

  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. Improvement of Passive Microwave Rainfall Retrieval Algorithm over Mountainous Terrain

    NASA Astrophysics Data System (ADS)

    Shige, S.; Yamamoto, M.

    2015-12-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

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

  2. 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.

  3. 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.

  4. 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.

  5. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  7. Impact of aerosols on the OMI tropospheric NO2 retrievals over industrialized regions: how accurate is the aerosol correction of cloud-free scenes via a simple cloud model?

    NASA Astrophysics Data System (ADS)

    Chimot, J.; Vlemmix, T.; Veefkind, J. P.; de Haan, J. F.; Levelt, P. F.

    2015-08-01

    The Ozone Monitoring Instrument (OMI) instrument has provided daily global measurements of tropospheric NO2 for more than a decade. Numerous studies have drawn attention to the complexities related to measurements of tropospheric NO2 in the presence of aerosols. Fine particles affect the OMI spectral measurements and the length of the average light path followed by the photons. However, they are not explicitly taken into account in the current OMI tropospheric NO2 retrieval chain. Instead, the operational OMI O2-O2 cloud retrieval algorithm is applied both to cloudy scenes and to cloud free scenes with aerosols present. This paper describes in detail the complex interplay between the spectral effects of aerosols, the OMI O2-O2 cloud retrieval algorithm and the impact on the accuracy of the tropospheric NO2 retrievals through the computed Air Mass Factor (AMF) over cloud-free scenes. Collocated OMI NO2 and MODIS Aqua aerosol products are analysed over East China, in industrialized area. In addition, aerosol effects on the tropospheric NO2 AMF and the retrieval of OMI cloud parameters are simulated. Both the observation-based and the simulation-based approach demonstrate that the retrieved cloud fraction linearly increases with increasing Aerosol Optical Thickness (AOT), but the magnitude of this increase depends on the aerosol properties and surface albedo. This increase is induced by the additional scattering effects of aerosols which enhance the scene brightness. The decreasing effective cloud pressure with increasing AOT represents primarily the absorbing effects of aerosols. The study cases show that the actual aerosol correction based on the implemented OMI cloud model results in biases between -20 and -40 % for the DOMINO tropospheric NO2 product in cases of high aerosol pollution (AOT ≥ 0.6) and elevated particles. On the contrary, when aerosols are relatively close to the surface or mixed with NO2, aerosol correction based on the cloud model results in

  8. Water droplets and ice retrievals in volcanic clouds using multispectral TIR satellite data. Correction procedure for SO2 estimation

    NASA Astrophysics Data System (ADS)

    Corradini, Stefano; Guerrieri, Lorenzo; Merucci, Luca; Pugnaghi, Sergio; Salerno, Giuseppe

    2015-04-01

    Among ash and gases, the volcanic clouds generated from several 2011-2014 Etna (Italy) lava fountains, were characterized by the huge presence of water droplets (wd) and/or ice. In some cases the wd/ice presence totally masked the ash signal and always significantly influenced the SO2 retrievals. Here the MODIS multispectral measurements are used to retrieve the volcanic wd and ice particles by means of two different techniques based on BTD (Brightness Temperature Difference) algorithm and VPR (Volcanic Plume Removal) approach. As test case the MODIS-Aqua images collected on Etna volcano the 10 April 2011 at 12:30 UTC and the 12 August 2011 at 11:15 UTC have been considered. Similarly to volcanic ashes, the wd/ice particles reduce the top of atmosphere radiance in the entire TIR spectral range, including the channels used for the SO2 retrieval. The net effect is a significant SO2 overestimation. Here two procedures for the correction of the wd/ice influence on SO2 retrieval are proposed. The results obtained from the MODIS 10 April 2011 MODIS image have been compared with the measurements collected by the FLAME ground-based network of DOAS instruments deployed on Mt. Etna.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Pre-Launch Performance Evaluations of Falling Snow using the Global Precipitation Measurement (GPM) Radiometer Retrieval Algorithm

    NASA Astrophysics Data System (ADS)

    Skofronick Jackson, G.; Munchak, S. J.; Johnson, B. T.

    2013-12-01

    Retrievals of falling snow from space represent an important data set for understanding the Earth's atmospheric, hydrological, and energy cycles. 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. This work reports on the development and pre-launch testing of retrieval algorithms for the Global Precipitation Measurement (GPM) mission Core Observatory satellite, to be launched in early 2014. In particular, we will report on GPM Microwave Imager (GMI) radiometer instrument algorithm performance with respect to falling snow detection and estimation. While satellite-based remote sensing can provide global coverage of falling snow events, the science is relatively new and retrievals are still undergoing development with challenges remaining. Estimates of falling snow from ground and space based sensors have been difficult due to the physical characteristics of snowflakes including their complex shapes, sizes, fall patterns, melting fractions, and densities; and their remotely sensed radiative characteristics. While these challenges remain, knowledge of their impact on expected retrieval results is an important key for understanding falling snow retrieval estimations. Our earlier work in this field has shown, through both theoretical and observational studies, that falling snow rates of approximately 0.5 mm/hr (melted) can be detected from GMI (Skofronick-Jackson, et al., IEEE Trans. Geoscience and Remote Sensing, 2013, Munchak and Skofronick-Jackson, Atmospheric Research, 2013). Throughout 2013, the at-launch GMI precipitation algorithms (called GPROF2014), based on a Bayesian framework, have been revised and delivered to the GPM data processing center with the final algorithm to be delivered in September 2013. The Bayesian framework for GMI

  14. A New Normalized Difference Cloud Retrieval Technique Applied to Landsat Radiances Over the Oklahoma ARM Site

    NASA Technical Reports Server (NTRS)

    Orepoulos, Lazaros; Cahalan, Robert; Marshak, Alexander; Wen, Guoyong

    1999-01-01

    We suggest a new approach to cloud retrieval, using a normalized difference of nadir reflectivities (NDNR) constructed from a non-absorbing and absorbing (with respect to liquid water) wavelength. Using Monte Carlo simulations we show that this quantity has the potential of removing first order scattering effects caused by cloud side illumination and shadowing at oblique Sun angles. Application of the technique to TM (Thematic Mapper) radiance observations from Landsat-5 over the Southern Great Plains site of the ARM (Atmospheric Radiation Measurement) program gives very similar regional statistics and histograms, but significant differences at the pixel level. NDNR can be also combined with the inverse NIPA (Nonlocal Independent Pixel Approximation) of Marshak (1998) which is applied for the first time on overcast Landsat scene subscenes. We demonstrate the sensitivity of the NIPA-retrieved cloud fields on the parameters of the method and discuss practical issues related to the optimal choice of these parameters.

  15. 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

  16. A New Normalized Difference Cloud Retrieval Technique Applied to Landsat Radiances over the Oklahoma ARM Site.

    NASA Astrophysics Data System (ADS)

    Oreopoulos, Lazaros; Cahalan, Robert F.; Marshak, Alexander; Wen, Guoyong

    2000-12-01

    that corrects for radiative smoothing, thus providing a retrieval framework where all 3D cloud effects can potentially be accounted for. The effectiveness of the new technique is demonstrated using Monte Carlo simulations. Real-world application is shown to be feasible using Thematic Mapper (TM) radiance observations from Landsat-5 over the Southern Great Plains (SGP) site of the Atmospheric Radiation Measurement (ARM) Program. For the moderately oblique (45°) solar zenith angle of the available Landsat scene, NDNR gives similar regional statistics and histograms when compared with standard independent pixel approximation (IPA), but significant differences at the pixel level. Inverse NIPA is also applied for the first time on observed high-resolution radiances of overcast Landsat subscenes. The dependence of the NIPA-retrieved cloud fields on the parameters of the method is illustrated and practical issues related to the optimal choice of these parameters are discussed.It is natural to compare novel cloud retrieval techniques with standard IPA retrievals. IPA is useful in revealing the inadequacy of plane parallel theory in certain situations and in demonstrating sensitivities to parameter choices, parameterizations, and assumptions. For example, it is found that IPA has problems in matching modeled and observed band-7 (2.2 m) reflectance values for 6% of the pixels, most of which are at cloud edges. For simultaneous cloud optical depth-droplet effective radius retrievals (where a conservative and an absorptive TM band are needed), it is found that the band-4 (0.83 m)-band-7 pair was the most well behaved, having less saturation, smaller changes in nominal calibration, and better overall consistency with modeled values than other bands. Mean values of optical depth, effective radius, and liquid water path (LWP) for typical IPA retrievals using this pair are = 22, re = 11 m, and LWP = 157 g m2, respectively. Inclusion of aerosol scattering above clouds results

  17. Cloud cover retrieved from ground-base observation using Skyviewer : A validation with human observations

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    Cloud cover is used in various fields of research in addition to weather forecasts; however, the ground observation of cloud cover is conducted by human observers, a method with low objectivity, temporal and spatial resolutions. Therefore, to address these problems, we have developed an improved algorithm to calculate cloud cover using sky image data obtained with Skyviewer equipment. The algorithm uses a variable threshold of the Red Blue Ratio (RBR) determined from the frequency distributions of the Green Blue Ratio (GBR) to calculate cloud cover more accurately than existing algorithms. To verify the accuracy of the algorithm, we conducted daily, monthly, seasonal and yearly statistical analysis on human observations of cloud cover obtained every hour from 0800 to 1700 LST for the entire year of 2012 at Gangwon Regional Meteorological Administration (GRMA), Korea. A daily case study compared the images of 1200 LST cases by season and pixel images of cloud cover calculated by the algorithm. The selected weekly cases yielded a high correlation of 0.93 with GRMA data. A monthly case study showed low RMSEs and high correlations for December (RMSE=1.64 tenths and r=0.92) and August (RMSE=1.43 tenths and r=0.91). In addition, seasonal cases yielded a high correlation of 0.9 and 87% consistency within ±2 tenths for winter and a correlation of 0.83 and 82% consistency for summer, when cases of cloud-free or overcast conditions are frequent. Annual analysis showed that the bias of GRMA and Skyviewer for the year of 2012 was -0.36 tenth, with cloud cover of the GRMA data being greater, whilst RMSE was 2.12 tenths. Considering the spatial inconsistency of the data used in the analysis, GRMA and Skyviewer showed a high correlation (0.87) and 80% consistency for cases with a difference in cloud cover of within ±2 tenths.

  18. Towards More Consistent Retrievals of Ice Cloud Optical and Microphysical Properties from Polar Orbiting Sensors

    NASA Astrophysics Data System (ADS)

    Baum, B. A.; Heymsfield, A.; Yang, P.

    2011-12-01

    Differences exist in the ice cloud optical thickness and effective particle size products provided by teams working with data from AVHRR (Advanced Very High Resolution Radiometer), MODIS (MODerate resolution Imaging Spectroradiometer), POLDER (Polarization and Directionality of the Earth Reflectance), Imaging Infrared Radiometer (IIR), and CALIOP (Cloud Aerosol LIdar with Orthogonal Polarization). The issue is in large part due to the assumed ice cloud single-scattering properties that each team uses in their retrievals. To gain insight into this problem, we are developing ice cloud single-scattering properties consistently from solar through far-infrared wavelengths by merging ice cloud microphysical data from in situ measurements with the very latest light scattering calculations for ice habits that include droxtals, solid/hollow columns, plates, solid/hollow bullet rosettes, aggregates of columns, and small/large aggregates of plates. The in-situ measurements are from a variety of field campaigns, including ARM-IOP, CRYSTAL-FACE, ACTIVE, SCOUT, MidCiX, pre-AVE, TC-4, and MACPEX. Among other advances, the light scattering calculations include the full phase matrix (i.e., polarization), incorporate a new treatment of forward scattering, and three levels of surface roughness from smooth to severely roughened. This talk will focus on improvements to our methodology for building both spectral and narrowband bulk scattering optical models appropriate for satellite imagers and hyperspectral infrared sensors. The new models provide a basis for investigating retrieval differences in the products from the sensor teams. We will discuss recent work towards improving the consistency of ice cloud microphysical/optical property retrievals between solar, polarimetric, and infrared retrieval approaches. It will be demonstrated that severely roughened ice particles correspond best in comparisons to polarization measurements. Further discussion will provide insight as to the

  19. 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.

  20. 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.

  1. 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

  2. Comparison between the first Odin-SMR, Aura MLS and CloudSat retrievals of cloud ice mass in the upper tropical troposphere

    NASA Astrophysics Data System (ADS)

    Eriksson, P.; Ekström, M.; Rydberg, B.; Wu, D. L.; Austin, R. T.; Murtagh, D. P.

    2007-08-01

    Emerging microwave satellite techniques are expected to provide improved global measurements of cloud ice mass. CloudSat, Aura MLS and Odin-SMR fall into this category and first cloud ice retrievals from these instruments are compared. The comparison is made for partial ice water columns above 12 km, following the SMR retrieval product. None of the instruments shows significant false cloud detections and a consistent view of the geographical distribution of cloud ice is obtained, but differences on the absolute levels exist. CloudSat gives the lowest values, with an overall mean of 2.12 g/m2. A comparable mean for MLS is 4.30 g/m2. This relatively high mean can be an indication of overestimation of the vertical altitude of cloud ice by the MLS retrievals. The vertical response of SMR has also some uncertainty, but this does not affect the comparison between MLS and CloudSat. SMR observations are sensitive to cloud inhomogeneities inside the footprint and some compensation is required. Results in good agreement with CloudSat, both in regard of the mean and probability density functions, are obtained for a weak compensation, while a simple characterisation of the effect indicates the need for stronger compensation. The SMR mean was found to be 1.89/2.62/4.10 g/m2 for no/selected/strongest compensation, respectively. Assumptions about the particle size distribution are a consideration for all three instruments, and constitute the dominating retrieval uncertainty for CloudSat. The comparison indicates a retrieval accuracy of about 40% (3.1±1.2 g/m2). This number is already very small compared to uncertainties of cloud ice parametrisation in atmospheric models, but can be decreased further through a better understanding of main retrieval error sources.

  3. 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

  4. Properties of marine stratocumulus obtained with partly cloudy pixel retrievals and found in the MODIS MOD06 cloud product

    NASA Astrophysics Data System (ADS)

    Boeke, Robyn C.; Allan, Andrea M.; Coakley, James A.

    2016-06-01

    Partly cloudy pixel retrievals (PCPRs) of cloud properties for marine stratocumulus were compared with those of the 1 km Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product (MOD06). In addition, the fractional cloud cover obtained from the PCPRs applied to 1 km MODIS radiances was compared with that derived from the 250 m cloud mask (MOD35). The comparisons were made for pixels that were overcast and pixels that were only partially covered by clouds. Accounting for failed retrievals in both the MOD06 cloud properties and those obtained with the PCPRs leads to the suggestion that regional cloud cover be estimated in terms of lower and upper limits. The average could serve as the best estimate of the cloud cover, and the difference between the average and an extreme could serve as the uncertainty. The comparisons reveal that the overcast assumption used in the MODIS cloud property retrievals leads to cloud cover, droplet effective radii, and cloud top temperatures that are overestimated and, shortwave optical depths, liquid water paths that are underestimated. These biases persist when the properties are averaged to form spatial and temporal means. Owing to significant horizontal variations of cloud liquid water within the 1 km MODIS pixels, visible optical depths, droplet effective radii, and liquid water paths derived from the PCPRs show similar biases. The trends of the biases with pixel-scale and regional-scale cloud cover suggest that estimates of the aerosol indirect radiative forcing derived from satellites have been overestimated.

  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. Retrieving the Convective Thermals and Updraft Speeds at Cloud Base from VIIRS

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    Updraft speeds of thermals have always been difficult to measure, despite significant roles they play in transporting pollutants and in cloud formation and precipitation. To our knowledge, no attempt to date has been made to estimate updraft speed from satellite information in the boundary layer and at the cloud base. In this study, we introduce two methods of retrieving the maximum updraft (Wmax) and updraft at cloud base (Wb) in the planetary boundary layer topped by convective clouds. The first method uses ground-air temperature difference to characterize the surface sensible heat flux, which is found to be correlated with updraft speeds measured by the Doppler lidar over the Southern Great Plains (SGP). Based on the relationship, we use the satellite-retrieved surface skin temperature and reanalysis surface air temperature to estimate the updrafts. The second method is based on a good linear correlation between cloud base height and updrafts, which was found over the SGP, the central Amazon, and on board a ship sailing between Honolulu and Los Angeles. We found a universal relationship for both land and ocean. The performance of these two methods of retrieving updrafts was tested against the lidar and Radar measurements with good agreements found for both methods. Compared with the first method that only works over land, the second method expands its applicability to ocean and is more accurate in retrieving Wmax the with RMSE (root-mean-square error) = 0.38 m/s and MAPE (mean-absolute-percentage-error) = 19%, and Wb with RMSE = 0.34 m/s and MAPE = 21%.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. Improved Limb Atmospheric Spectrometer (ILAS) data retrieval algorithm for Version 5.20 gas profile products

    NASA Astrophysics Data System (ADS)

    Yokota, T.; Nakajima, H.; Sugita, T.; Tsubaki, H.; Itou, Y.; Kaji, M.; Suzuki, M.; Kanzawa, H.; Park, J. H.; Sasano, Y.

    2002-12-01

    The Improved Limb Atmospheric Spectrometer (ILAS), a sensor for stratospheric ozone layer observation using a solar occultation technique, was mounted on the Advanced Earth Observing Satellite (ADEOS), which was put into a Sun-synchronous polar orbit in August 1996. Operational measurements were recorded over high-latitude regions from November 1996 to June 1997. This paper describes the data processing algorithm of Version 5.20 used to retrieve vertical profiles of gases such as ozone, nitric acid, nitrogen dioxide, nitrous oxide, methane, and water vapor from the infrared spectral measurements of ILAS. To simultaneously derive mixing ratios of individual gas species as a function of altitude, the nonlinear least squares method was utilized for spectral fitting, and the onion peeling method was applied to perform vertical profiling. This paper also discusses in detail estimation of errors (internal and external errors) associated with the derived gas profiles and compares the errors with repeatability. The internal error estimated from residuals in spectral fitting was generally larger than the repeatability, which suggests either that some unknown factors have not been incorporated into the forward model for simulating observed transmittance data or that some parameters in the model are inaccurate. The external error was almost comparable in magnitude to the repeatability. Numerical simulations were carried out to investigate performance of the nongaseous correction technique. The results showed that the background level of sulfuric acid aerosols has little effect on the retrieved profiles, while polar stratospheric clouds (PSCs) with extinction coefficients of the order of 10-3 km-1 at a wavelength of 780 nm have nonnegligible effects on the profiles of some gas species. Despite the problems that require further investigations, it is shown that the ILAS Version 5.20 algorithm generates scientifically useful products.

  14. Retrieval of atmospheric properties from hyper and multispectral imagery with the FLAASH atmospheric correction algorithm

    NASA Astrophysics Data System (ADS)

    Perkins, Timothy; Adler-Golden, Steven; Matthew, Michael; Berk, Alexander; Anderson, Gail; Gardner, James; Felde, Gerald

    2005-10-01

    Atmospheric Correction Algorithms (ACAs) are used in applications of remotely sensed Hyperspectral and Multispectral Imagery (HSI/MSI) to correct for atmospheric effects on measurements acquired by air and space-borne systems. The Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) algorithm is a forward-model based ACA created for HSI and MSI instruments which operate in the visible through shortwave infrared (Vis-SWIR) spectral regime. Designed as a general-purpose, physics-based code for inverting at-sensor radiance measurements into surface reflectance, FLAASH provides a collection of spectral analysis and atmospheric retrieval methods including: a per-pixel vertical water vapor column estimate, determination of aerosol optical depth, estimation of scattering for compensation of adjacency effects, detection/characterization of clouds, and smoothing of spectral structure resulting from an imperfect atmospheric correction. To further improve the accuracy of the atmospheric correction process, FLAASH will also detect and compensate for sensor-introduced artifacts such as optical smile and wavelength mis-calibration. FLAASH relies on the MODTRANTM radiative transfer (RT) code as the physical basis behind its mathematical formulation, and has been developed in parallel with upgrades to MODTRAN in order to take advantage of the latest improvements in speed and accuracy. For example, the rapid, high fidelity multiple scattering (MS) option available in MODTRAN4 can greatly improve the accuracy of atmospheric retrievals over the 2-stream approximation. In this paper, advanced features available in FLAASH are described, including the principles and methods used to derive atmospheric parameters from HSI and MSI data. Results are presented from processing of Hyperion, AVIRIS, and LANDSAT data.

  15. Airborne retrieval of cirrus cloud optical and microphysical properties using Airborne Remote Earth Sensing System 5.1-5.3 and 3.7-μm channel data

    NASA Astrophysics Data System (ADS)

    Ou, S. C.; Liou, K. N.; Yang, P.; Rolland, P.; Caudill, T. R.; Lisowski, J.; Morrison, B.

    1998-09-01

    We present an airborne retrieval algorithm to infer cirrus cloud temperature, optical depth, and mean effective sizes using the Airborne Remote Earth Sensing System (ARES) hyperspectral spectrometer data for the 5.1-5.3 and 3.7 μm channels. The algorithm, development and the selection of the channels are based on the principle and parameterization of radiative transfer involving cirrus clouds and the associated atmospheric and surface properties. It has been applied to a selected case of the ARES data collected over the western Boston area on September 16, 1995. Validation of the retrieved parameters was carried out using the collocated and coincident ground-based 8.6-mm radar data and ice crystal size distribution measurements obtained from the 2D-P probe on board the high-altitude reconnaissance platform (HARP). We show that the retrieved cirrus cloud temperature, mean effective ice crystal size, and optical depth match closely with those derived from the observations.

  16. 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

  17. Multilevel cloud retrieval using multispectral HIRS and AVHRR data: Nighttime oceanic analysis

    NASA Technical Reports Server (NTRS)

    Baum, Bryan A.; Arduini, Robert F.; Wielicki, Bruce A.; Minnis, Patrick; Tsay, Si-Chee

    1994-01-01

    A multispectral, multiresolution (MSMR) method is developed for analyzing scenes of overlapping cloud layers. The MSMR method is applied to data from the NOAA 11 advanced very high resolution radiometer (AVHRR) and the high-resolution infrared radiometer sounder (HIRS-2). The data are from a nighttime oceanic scene in which a semitransparent cirrus veil overlays a large-scale stratus cloud. Low-cloud and clear-sky radiances are determined using a spatial coherence technique. Middle to upper level cloud pressures and radiances are estimated from HIRS-2 15 micrometer CO2 band radiometric data. The MSMR method improves the interpretation of a nighttime, oceanic scene containing thin cirrus over a large-scale stratiform cloud. If, for example, the same scene is analyzed using only the AVHRR 10.8 micrometer channel, the accompanying retrieved cloud heights are found to be between the cirrus and stratus cloud heights and are incorrectly identified as midlevel altostratus clouds. Theoretical radiative transfer model results for both water droplet spheres and randomly oriented hexagonal ice crystals are compared to observed AVHRR brightness temperature differences (BTD) between the 3.7- and 10.8 micrometer channels (BTD(sup 34)) and between the 10.8- and 12- micrometer channels (BTD(sup 45)) to distinguish among the effects of cloud optical depth, particle size, and phase for both single-layer clouds and overlapping two-layer clouds. Theoretical BTD calculations are used to estimate the range of effective particle sizes for eac h cloud layer. The data for the cirrus in the case study region near Bermuda are consistent with theoretical results for relatively small randomly oriented hexagonal ice crystals. The observed BTD(sup 34) and BTD(sup 45) values are lower for the cirrus above a lower-level cloud than for single-level cirrus with no underlying cloud. In certain cases the BTD analysis provides a way to distinguish between clouds composed of supercooled water droplets

  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 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

  20. 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…

  1. 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…

  2. Retrieval of thermodynamic variables with deep convective clouds Experiments in three dimensions

    NASA Technical Reports Server (NTRS)

    Hane, C. E.; Wilhelmson, R. B.; Gal-Chen, T.

    1981-01-01

    A three-dimensional numerical cloud model has been used to test a method for retrieving temperature and pressure deviation fields from detailed wind and water fields in deep convective clouds. A comparison of the retrieved fields with the output from the numerical model was used to test the validity of the theoretical treatment and accuracy of the programming. The local time derivatives of each of the velocity components are known to be potential problem sources in using Doppler radar data, and a test was done with this derivative estimated over a 4 min time span rather than 30 s, resulting in excellent agreement with the original solution for this data set. When the local derivative was eliminated, the solution was judged useful for general temperature patterns. Errors due to the inability to measure cloudwater mixing ratio and inaccuracies in rainwater mixing ratio were found to be significant, but not so severe as in the turbulence and steady-state sensitivity tests.

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. Improved retrieval algorithm of tree height by POLINSAR

    NASA Astrophysics Data System (ADS)

    Li, Yongsheng; Liu, Xiuguo; Gao, Wei; Song, Yan

    2008-12-01

    Tree height is an important biophysical parameter. It is a need for forest and biomass map for the estimation of carbon budget. Polarimetric SAR interferometry (PolInSAR) has been applied successfully to retrieve biophysical parameters from forest areas. In the real process, the retrieval result is not truthfulness because of non-volumetric scattering decorrelation scatterer. The scatterer is generated by coherence noise. The scatterer will be misjudged and mistook for a tree. Before Retrieving of Tree Height, non-volumetric scattering decorrelation scatterer needed to be removed. This paper will propose to combine the linear and optimization polarization interferometric coherence to remove the nonvolumetric scattering decorrelation scatterer. The retrieval results have been proved reasonable.

  13. Temporal Variability of Surface Solar Irradiance as a Function of Satellite-retrieved Cloud

    NASA Astrophysics Data System (ADS)

    Hinkelman, L. M.; Sengupta, M.; Habte, A.

    2014-12-01

    Studies of the impact of renewables on the electrical transmission grid are needed as power production from renewable energy resources increases. These studies require estimates of high temporal and spatial resolution power output under various scenarios. Satellite-based solar resource estimates are the best source of long-term irradiance data but are generally of lower temporal and spatial resolution than needed and thus require downscaling. Likewise, weather forecast models cannot provide high spatial or temporal irradiance predictions. Downscaling requires information about solar irradiance variability in both space and time, which is primarily a function of cloud properties. In this study, we analyze the relationships between the temporal variability of surface solar irradiance and satellite-based cloud properties. One-minute resolution surface solar irradiance data were obtained from the National Oceanic and Atmospheric Administration's Surface Radiation (SURFRAD) network. These sites are distributed across the United States to cover a range of meteorological conditions. Cloud information at a nominal 4 km resolution and half hour intervals was retrieved from NOAA's Geostationary Operation Environmental Satellites (GOES). The retrieved cloud properties were then used to select and composite irradiance data from the measurement sites in order to identify the cloud properties that exert the strongest control over short-term irradiance variability. The irradiance variability was characterized using statistics of both the irradiances themselves and of irradiance differences computed for short time scales (minutes). The relationships derived using this method will be presented, comparing and contrasting the statistics computed for the different cloud properties. The implications for downscaling irradiance from satellites or forecast models will also be discussed.

  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. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. Deriving Arctic Cloud Microphysics at Barrow, Alaska. Algorithms, Results, and Radiative Closure

    SciTech Connect

    Shupe, Matthew D.; Turner, David D.; Zwink, Alexander; Thieman, Mandana M.; Mlawer, Eli J.; Shippert, Timothy

    2015-07-01

    Cloud phase and microphysical properties control the radiative effects of clouds in the climate system and are therefore crucial to characterize in a variety of conditions and locations. An Arctic-specific, ground-based, multi-sensor cloud retrieval system is described here and applied to two years of observations from Barrow, Alaska. Over these two years, clouds occurred 75% of the time, with cloud ice and liquid each occurring nearly 60% of the time. Liquid water occurred at least 25% of the time even in the winter, and existed up to heights of 8 km. The vertically integrated mass of liquid was typically larger than that of ice. While it is generally difficult to evaluate the overall uncertainty of a comprehensive cloud retrieval system of this type, radiative flux closure analyses were performed where flux calculations using the derived microphysical properties were compared to measurements at the surface and top-of-atmosphere. Radiative closure biases were generally smaller for cloudy scenes relative to clear skies, while the variability of flux closure results was only moderately larger than under clear skies. The best closure at the surface was obtained for liquid-containing clouds. Radiative closure results were compared to those based on a similar, yet simpler, cloud retrieval system. These comparisons demonstrated the importance of accurate cloud phase classification, and specifically the identification of liquid water, for determining radiative fluxes. Enhanced retrievals of liquid water path for thin clouds were also shown to improve radiative flux calculations.

  2. From Point Clouds to Architectural Models: Algorithms for Shape Reconstruction

    NASA Astrophysics Data System (ADS)

    Canciani, M.; Falcolini, C.; Saccone, M.; Spadafora, G.

    2013-02-01

    The use of terrestrial laser scanners in architectural survey applications has become more and more common. Row data complexity, as given by scanner restitution, leads to several problems about design and 3D-modelling starting from Point Clouds. In this context we present a study on architectural sections and mathematical algorithms for their shape reconstruction, according to known or definite geometrical rules, focusing on shapes of different complexity. Each step of the semi-automatic algorithm has been developed using Mathematica software and CAD, integrating both programs in order to reconstruct a geometrical CAD model of the object. Our study is motivated by the fact that, for architectural survey, most of three dimensional modelling procedures concerning point clouds produce superabundant, but often unnecessary, information and are also very expensive in terms of cpu time using more and more sophisticated hardware and software. On the contrary, it's important to simplify/decimate the point cloud in order to recognize a particular form out of some definite geometric/architectonic shapes. Such a process consists of several steps: first the definition of plane sections and characterization of their architecture; secondly the construction of a continuous plane curve depending on some parameters. In the third step we allow the selection on the curve of some nodal points with given specific characteristics (symmetry, tangency conditions, shadowing exclusion, corners, … ). The fourth and last step is the construction of a best shape defined by the comparison with an abacus of known geometrical elements, such as moulding profiles, leading to a precise architectonical section. The algorithms have been developed and tested in very different situations and are presented in a case study of complex geometries such as some mouldings profiles in the Church of San Carlo alle Quattro Fontane.

  3. Turkish Cloud-Radiation Database (CRD) and Its Application with CDR Bayesian Probability Algorithm

    NASA Astrophysics Data System (ADS)

    Oztopal, A.; Mugnai, A.; Casella, D.; Formenton, M.; Sano, P.; Sonmez, I.; Sen, Z.; Hsaf Team

    2010-12-01

    ABSTRACT It is rather a very difficult task to determine ground rainfall amounts from few Special Sensor Microwave Imager/Sounder (SSMI/S) channels. Although ground rainfall cannot be observed from the space directly, but knowledge about the cloud physics helps to estimate the amound of ground rainfall. SSMI/S includes so much information about the atmospheric structure, however it cannot provide cloud micro-physical structural information. In such a situation, in the rainfall algorithm, besides the SSMI/S data, it is necessary to incorporate cloud micro-physical properties from an external data source. These properties can be obtained quite simply by the help of Cloud Resolving Model (CRM). Later, in addition to all available data, also micro-physical properties obtained from Radiative Transfer Model (RTM) help to determine the SSMI/S brightness temperatures (Brightness temperatures - TBs), which can then be correlated with Cloud-Radiation Database (CRD) data generation. SSMI/S satellite data and CDR provide a common basis for rainfall prediction procedure through CDR Bayesian probability algorithm, which combines the two sets of data in a scientific manner. The first applications of this algorithm, which is being used up today, is due to various researchers. In this work, in order to establish a reflection of available data processing CDR CRM University of Wisconsin - Non-hydrostatic Modeling System (UW-NMS) model is employed, which is first developed by Prof. Gregory J. Tripoli. It is also used by Turkish Meteorological Service by benefiting from radar network data, and finally 14 simulations are realized in this study. Moreover, one case study is fulfilled by using a 3X3 spatial filtering, and then radar data and result of CDR Bayesian probability algorithm are compared with each other. On 9 September 2009 at 03:40 GMT rainfall event on comparatively flat area matches far better with the retrieval values and hence the spatial rainfall occurrence extent and

  4. 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.

  5. 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.

  6. Improved methodology for surface and atmospheric soundings, error estimates, and quality control procedures: the atmospheric infrared sounder science team version-6 retrieval algorithm

    NASA Astrophysics Data System (ADS)

    Susskind, Joel; Blaisdell, John M.; Iredell, Lena

    2014-01-01

    The atmospheric infrared sounder (AIRS) science team version-6 AIRS/advanced microwave sounding unit (AMSU) retrieval algorithm is now operational at the Goddard Data and Information Services Center (DISC). AIRS version-6 level-2 products are generated near real time at the Goddard DISC and all level-2 and level-3 products are available starting from September 2002. Some of the significant improvements in retrieval methodology contained in the version-6 retrieval algorithm compared to that previously used in version-5 are described. In particular, the AIRS science team made major improvements with regard to the algorithms used to (1) derive surface skin temperature and surface spectral emissivity; (2) generate the initial state used to start the cloud clearing and retrieval procedures; and (3) derive error estimates and use them for quality control. Significant improvements have also been made in the generation of cloud parameters. In addition to the basic AIRS/AMSU mode, version-6 also operates in an AIRS only (AO) mode, which produces results almost as good as those of the full AIRS/AMSU mode. The improvements of some AIRS version-6 and version-6 AO products compared to those obtained using version-5 are also demonstrated.

  7. 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.

  8. 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.

  9. 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.

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

    PubMed

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

    2014-01-01

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

  11. 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.

  12. Impact of aerosols on the OMI tropospheric NO2 retrievals over industrialized regions: how accurate is the aerosol correction of cloud-free scenes via a simple cloud model?

    NASA Astrophysics Data System (ADS)

    Chimot, J.; Vlemmix, T.; Veefkind, J. P.; de Haan, J. F.; Levelt, P. F.

    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

  13. 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

  14. Millimeter-Wave Imaging Radiometer (MIR) Data Processing and Development of Water Vapor Retrieval Algorithms

    NASA Technical Reports Server (NTRS)

    Chang, L. Aron

    1998-01-01

    This document describes the final report of the Millimeter-wave Imaging Radiometer (MIR) Data Processing and Development of Water Vapor Retrieval Algorithms. Volumes of radiometric data have been collected using airborne MIR measurements during a series of field experiments since May 1992. Calibrated brightness temperature data in MIR channels are now available for studies of various hydrological parameters of the atmosphere and Earth's surface. Water vapor retrieval algorithms using multichannel MIR data input are developed for the profiling of atmospheric humidity. The retrieval algorithms are also extended to do three-dimensional mapping of moisture field using continuous observation provided by airborne sensor MIR or spaceborne sensor SSM/T-2. Validation studies for water vapor retrieval are carried out through the intercomparison of collocated and concurrent measurements using different instruments including lidars and radiosondes. The developed MIR water vapor retrieval algorithm is capable of humidity profiling under meteorological conditions ranging from clear column to moderately cloudy sky. Simulative water vapor retrieval studies using extended microwave channels near 183 and 557 GHz strong absorption lines indicate feasibility of humidity profiling to layers in the upper troposphere and improve the overall vertical resolution through the atmosphere.

  15. Algorithms and sensitivity analyses for stratospheric aerosol and gas experiment II water vapor retrieval

    SciTech Connect

    Chu, W.P.; Thomason, L.W.; Buglia, J.J.; McCormick, M.P.; McMaster, L.M. ); Chiou, E.W.; Larsen, J.C. ); Rind, D. ); Oltmans, S. )

    1993-03-20

    This paper provides a detailed description of the current operational inversion algorithm for the retrieval of water vapor vertical profiles from the Stratospheric Aerosol and Gas Experiment II (SAGE II) occultation data at the 0.94-[mu]m wavelength channel. This algorithm is different from the algorithm used for the retrieval of the other species such as aerosol, ozone, and nitrogen dioxide because of the nonlinear relationship between the concentration versus the broad band absorption characteristics of water vapor. Included in the discussion of the retrieval algorithm are problems related to the accuracy of the computational scheme, accuracy of the removal of other interfering species, and the expected uncertainty of the retrieved profile. A comparative analysis on the computational schemes used for the calculation of the water vapor transmission at the 0.94-[mu]m wavelength region is presented. Analyses are also presented on the sensitivity of the retrievals to interferences from the other species which contribute to the total signature as observed at the 0.94-[mu]m wavelength channel on SAGE II instrument. Error analyses of the SAGE II water vapor retrieval is shown, indicating that good quality water vapor data are being produced by the SAGE II measurements. 27 refs., 10 figs., 1 tab.

  16. Two algorithms to fill cloud gaps in LST time series

    NASA Astrophysics Data System (ADS)

    Frey, Corinne; Kuenzer, Claudia

    2013-04-01

    Cloud contamination is a challenge for optical remote sensing. This is especially true for the recording of a fast changing radiative quantity like land surface temperature (LST). The substitution of cloud contaminated pixels with estimated values - gap filling - is not straightforward but possible to a certain extent, as this research shows for medium-resolution time series of MODIS data. Area of interest is the Upper Mekong Delta (UMD). The background for this work is an analysis of the temporal development of 1-km LST in the context of the WISDOM project. The climate of the UMD is characterized by peak rainfalls in the summer months, which is also the time where cloud contamination is highest in the area. Average number of available daytime observations per pixel can go down to less than five for example in the month of June. In winter the average number may reach 25 observations a month. This situation is not appropriate to the calculation of longterm statistics; an adequate gap filling method should be used beforehand. In this research, two different algorithms were tested on an 11 year time series: 1) a gradient based algorithm and 2) a method based on ECMWF era interim re-analysis data. The first algorithm searches for stable inter-image gradients from a given environment and for a certain period of time. These gradients are then used to estimate LST for cloud contaminated pixels in each acquisition. The estimated LSTs are clear-sky LSTs and solely based on the MODIS LST time series. The second method estimates LST on the base of adapted ECMWF era interim skin temperatures and creates a set of expected LSTs. The estimated values were used to fill the gaps in the original dataset, creating two new daily, 1 km datasets. The maps filled with the gradient based method had more than the double amount of valid pixels than the original dataset. The second method (ECMWF era interim based) was able to fill all data gaps. From the gap filled data sets then monthly

  17. 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

  18. 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.

  19. 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;

  20. 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.

  1. Cloud identification using genetic algorithms and massively parallel computation

    NASA Technical Reports Server (NTRS)

    Buckles, Bill P.; Petry, Frederick E.

    1996-01-01

    As a Guest Computational Investigator under the NASA administered component of the High Performance Computing and Communication Program, we implemented a massively parallel genetic algorithm on the MasPar SIMD computer. Experiments were conducted using Earth Science data in the domains of meteorology and oceanography. Results obtained in these domains are competitive with, and in most cases better than, similar problems solved using other methods. In the meteorological domain, we chose to identify clouds using AVHRR spectral data. Four cloud speciations were used although most researchers settle for three. Results were remarkedly consistent across all tests (91% accuracy). Refinements of this method may lead to more timely and complete information for Global Circulation Models (GCMS) that are prevalent in weather forecasting and global environment studies. In the oceanographic domain, we chose to identify ocean currents from a spectrometer having similar characteristics to AVHRR. Here the results were mixed (60% to 80% accuracy). Given that one is willing to run the experiment several times (say 10), then it is acceptable to claim the higher accuracy rating. This problem has never been successfully automated. Therefore, these results are encouraging even though less impressive than the cloud experiment. Successful conclusion of an automated ocean current detection system would impact coastal fishing, naval tactics, and the study of micro-climates. Finally we contributed to the basic knowledge of GA (genetic algorithm) behavior in parallel environments. We developed better knowledge of the use of subpopulations in the context of shared breeding pools and the migration of individuals. Rigorous experiments were conducted based on quantifiable performance criteria. While much of the work confirmed current wisdom, for the first time we were able to submit conclusive evidence. The software developed under this grant was placed in the public domain. An extensive user

  2. First Look at a Cloud Identification and Tracking Algorithm - Cloud Lifecycle during MC3E. A case study

    NASA Astrophysics Data System (ADS)

    Borque, P.; Kollias, P.; Giangrande, S. E.

    2012-12-01

    Tracking algorithms have been developed for decades, most devoted to following the evolution of severe weather systems and nowcasting storm future position for warning applications. In this work, we center our analysis on observations of non-precipitating clouds. Documenting cloud evolution as they transit through different stages of their lifetime can provide unparalleled potential for meaningful advances in our understanding of cloud dynamics and microphysics. This can result in a unique opportunity for model evaluation and subsequent improvements in model parameterizations. Tracking the evolution of short-lived clouds requires synergistic, complementary, overlapping multi-radar platforms. For this, our study capitalizes on the ARM multi-frequency heterogeneous radar network facility deployed during the Midlatitude Continental Convective Clouds Experiment (MC3E) over central United States. Here, the evolution of cloud proprieties, as well as a detail description and a sensitivity analysis of the tracking algorithm developed, will be presented.

  3. 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.

  4. Atmospheric particles retrieval using satellite remote sensing: Applications for sandstorms and volcanic clouds

    NASA Astrophysics Data System (ADS)

    Gu, Yingxin

    This thesis is concerned with atmospheric particles produced by sandstorms and volcanic eruptions. Three studies were conducted in order to examine particle retrieval methodology, and apply these towards an improved understanding of large-scale sandstorms. A thermal infrared remote sensing retrieval method developed by Wen and Rose [1994], which retrieves particle sizes, optical depth, and total masses of silicate particles in the volcanic cloud, was applied to an April 07, 2001 sandstorm over northern China, using MODIS. Results indicate that the area of the dust cloud observed was 1.34 million km2, the mean particle radius of the dust was 1.44 mum, and the mean optical depth at 11 mum was 0.79. The mean burden of dust was approximately 4.8 tons/km2 and the main portion of the dust storm on April 07, 2001 contained 6.5 million tons of dust. The results are supported by both independent remote sensing data (TOMS) and in-situ data for a similar event in 1998, therefore suggesting that the technique is appropriate for quantitative analysis of silicate dust clouds. This is the first quantitative evaluation of annual and seasonal dust loading in 2003 produced by Saharan dust storms by satellite remote sensing analysis. The retrieved mean particle effective radii of 2003 dust events are between 1.7--2.6 mum which is small enough to be inhaled and is hazardous to human health. The retrieved yearly dust mass load is 658--690 Tg, which is ˜45% of the annual global mineral dust production. Winter is the heaviest dust loading season in the year 2003, which is more than 5 times larger than that in the summer season in 2003.The mean optical depths at 11 mum in the winter season (around 0.7) are higher than those in the summer season (around 0.5). The results could help both meteorologists and environmental scientists to evaluate and predict the hazard degree caused by Saharan dust storms. (Abstract shortened by UMI.)

  5. 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.

  6. 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).

  7. The Effect of Dust Aerosols on Marine Ice Clouds: A Study of MODIS Level-3 Daily Retrieval

    NASA Astrophysics Data System (ADS)

    Wong, S.; Dessler, A. E.

    2004-05-01

    The effect of dust aerosols on marine ice cloud particle size was studied using the Moderate Resolution Imaging Spectroradiometer (MODIS) Level-3 retrieval data. Daily averaged optical thickness of aerosol and daily statistics of ice cloud particles' effective radii were analyzed for May to September 2002 over two regions, a region in the tropical east Atlantic offshore of North Africa, and a region in the northern Indian Ocean in between the Indian continent and the Persian peninsula. It was found that, for clouds that are deep (cloud-top temperature <230K) and optically thick, increasing aerosol optical depth is associated with smaller cloud effective radii. This implies that, through deep convection, dust aerosols blown off the continents during summertime are lofted to the upper troposphere and reduce the effective radii of clouds. The sensitivity of the cloud effective radius to the aerosol loading is quite different between the regions, and reasons for this will be discussed.

  8. 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.

  9. AerGOM, an improved algorithm for stratospheric aerosol extinction retrieval from GOMOS observations - Part 1: Algorithm description

    NASA Astrophysics Data System (ADS)

    Vanhellemont, Filip; Mateshvili, Nina; Blanot, Laurent; Étienne Robert, Charles; Bingen, Christine; Sofieva, Viktoria; Dalaudier, Francis; Tétard, Cédric; Fussen, Didier; Dekemper, Emmanuel; Kyrölä, Erkki; Laine, Marko; Tamminen, Johanna; Zehner, Claus

    2016-09-01

    The GOMOS instrument on Envisat has successfully demonstrated that a UV-Vis-NIR spaceborne stellar occultation instrument is capable of delivering quality data on the gaseous and particulate composition of Earth's atmosphere. Still, some problems related to data inversion remained to be examined. In the past, it was found that the aerosol extinction profile retrievals in the upper troposphere and stratosphere are of good quality at a reference wavelength of 500 nm but suffer from anomalous, retrieval-related perturbations at other wavelengths. Identification of algorithmic problems and subsequent improvement was therefore necessary. This work has been carried out; the resulting AerGOM Level 2 retrieval algorithm together with the first data version AerGOMv1.0 forms the subject of this paper. The AerGOM algorithm differs from the standard GOMOS IPF processor in a number of important ways: more accurate physical laws have been implemented, all retrieval-related covariances are taken into account, and the aerosol extinction spectral model is strongly improved. Retrieval examples demonstrate that the previously observed profile perturbations have disappeared, and the obtained extinction spectra look in general more consistent. We present a detailed validation study in a companion paper; here, to give a first idea of the data quality, a worst-case comparison at 386 nm shows SAGE II-AerGOM correlation coefficients that are up to 1 order of magnitude larger than the ones obtained with the GOMOS IPFv6.01 data set.

  10. Validation of OMI total ozone retrievals from the SAO ozone profile algorithm and three operational algorithms with Brewer measurements

    NASA Astrophysics Data System (ADS)

    Bak, J.; Liu, X.; Kim, J. H.; Chance, K.; Haffner, D. P.

    2015-01-01

    The accuracy of total ozone computed from the Smithsonian Astrophysical Observatory (SAO) optimal estimation (OE) ozone profile algorithm (SOE) applied to the Ozone Monitoring Instrument (OMI) is assessed through comparisons with ground-based Brewer spectrometer measurements from 2005 to 2008. We also compare the three OMI operational ozone products, derived from the NASA Total Ozone Mapping Spectrometer (TOMS) algorithm, the KNMI (Royal Netherlands Meteorological Institute) differential optical absorption spectroscopy (DOAS) algorithm, and KNMI's Optimal Estimation (KOE) algorithm. The best agreement is observed between SAO and Brewer, with a mean difference of within 1% at most individual stations. The KNMI OE algorithm systematically overestimates Brewer total ozone by 2% at low and mid-latitudes and 5% at high latitudes while the TOMS and DOAS algorithms underestimate it by ~1.65% on average. Standard deviations of ~1.8% are calculated for both SOE and TOMS, but DOAS and KOE have higher values of 2.2% and 2.6%, respectively. The stability of the SOE algorithm is found to have insignificant dependence on viewing geometry, cloud parameters, or total ozone column. In comparison, the KOE-Brewer differences are significantly correlated with solar and viewing zenith angles and show significant deviations depending on cloud parameters and total ozone amount. The TOMS algorithm exhibits similar stability to SOE with respect to viewing geometry and total column ozone, but has stronger cloud parameter dependence. The dependence of DOAS on observational geometry and geophysical conditions is marginal compared to KOE, but is distinct compared to the SOE and TOMS algorithms. Comparisons of all four OMI products with Brewer show no apparent long-term drift, but seasonal features are evident, especially for KOE and TOMS. The substantial differences in the KOE vs. SOE algorithm performance cannot be sufficiently explained by the use of soft calibration (in SOE) and the use of

  11. 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 cloud-tops. It is found that CO2 Sorting significantly reduces the cloud height biases for the optically thin cloud (total optical depths less then 1.0). For geometrically thick but optically thin cirrus clouds large differences between the S-HIS infrared cloud top retrievals and the CPL detected cloud top where found. For these cases the cloud height retrieved by the S-HIS cloud retrievals correlated closely with the level the CPL integrated cloud optical depth was approximately 1.0.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  13. 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

  14. 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.

  15. 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.

  16. GFIT2: an experimental algorithm for vertical profile retrieval from near-IR spectra

    NASA Astrophysics Data System (ADS)

    Connor, Brian J.; Sherlock, Vanessa; Toon, Geoff; Wunch, Debra; Wennberg, Paul O.

    2016-08-01

    An algorithm for retrieval of vertical profiles from ground-based spectra in the near IR is described and tested. Known as GFIT2, the algorithm is primarily intended for CO2, and is used exclusively for CO2 in this paper. Retrieval of CO2 vertical profiles from ground-based spectra is theoretically possible, would be very beneficial for carbon cycle studies and the validation of satellite measurements, and has been the focus of much research in recent years. GFIT2 is tested by application both to synthetic spectra and to measurements at two Total Carbon Column Observing Network (TCCON) sites. We demonstrate that there are approximately 3° of freedom for the CO2 profile, and the algorithm performs as expected on synthetic spectra. We show that the accuracy of retrievals of CO2 from measurements in the 1.61μ (6220 cm-1) spectral band is limited by small uncertainties in calculation of the atmospheric spectrum. We investigate several techniques to minimize the effect of these uncertainties in calculation of the spectrum. These techniques are somewhat effective but to date have not been demonstrated to produce CO2 profile retrievals with sufficient precision for applications to carbon dynamics. We finish by discussing ongoing research which may allow CO2 profile retrievals with sufficient accuracy to significantly improve the scientific value of the measurements from that achieved with column retrievals.

  17. 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.

  18. 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

  19. Foundations for statistical-physical precipitation retrieval from passive microwave satellite measurements. II - Emission-source and generalized weighting-function properties of a time-dependent cloud-radiation model

    NASA Technical Reports Server (NTRS)

    Mugnai, Alberto; Smith, Eric A.; Tripoli, Gregory J.

    1993-01-01

    The foremost physical aspects of microphysical-radiative interactions that control the formation and modulation of frequency-dependent passive microwave TB over a continental cold-rain precipitation system are explained within the framework of the essential ingredients of a physically based precipitation-retrieval algorithm. The analysis is based on a modeling study in which a 3D cloud model has provided the objective basis for generating an extensive set of microphysical profiles that describe numerous precipitation features in the course of the evolution of a continental hail storm. A summary of the various components of the algorithm, as well as the surface rain rates, is given. The algorithm employs the cloud model to provide a consistent and objectively generated source of detailed microphysical information as the underpinnings to an inversion-based perturbative retrieval scheme.

  20. Foundations for statistical-physical precipitation retrieval from passive microwave satellite measurements. I - Brightness-temperature properties of a time-dependent cloud-radiation model

    NASA Technical Reports Server (NTRS)

    Smith, Eric A.; Mugnai, Alberto; Cooper, Harry J.; Tripoli, Gregory J.; Xiang, Xuwu

    1992-01-01

    The relationship between emerging microwave brightness temperatures (T(B)s) and vertically distributed mixtures of liquid and frozen hydrometeors was investigated, using a cloud-radiation model, in order to establish the framework for a hybrid statistical-physical rainfall retrieval algorithm. Although strong relationships were found between the T(B) values and various rain parameters, these correlations are misleading in that the T(B)s are largely controlled by fluctuations in the ice-particle mixing ratios, which in turn are highly correlated to fluctuations in liquid-particle mixing ratios. However, the empirically based T(B)-rain-rate (T(B)-RR) algorithms can still be used as tools for estimating precipitation if the hydrometeor profiles used for T(B)-RR algorithms are not specified in an ad hoc fashion.

  1. A cloud detection algorithm using edge detection and information entropy over urban area

    NASA Astrophysics Data System (ADS)

    Zheng, Hong; Wen, Tianxiao; Li, Zhen

    2013-10-01

    Aiming at detecting cloud interference over urban area, an algorithm in this research is proposed to detect urban cloud area combining extracting edge information with information entropy, focusing on distinguishing complex surface features accurately to retain intact surface information. Firstly, image edge sharpening is used. Secondly, Canny edge detector and closing operation are applied to extract and strengthen edge features. Thirdly, information entropy extraction is adopted to ensure cloud positional accuracy. Compared with traditional cloud detection methods, this algorithm protects the integrity of urban surface features efficiently, improving the segmentation accuracy. Test results prove the effectiveness of this algorithm.

  2. High Quality Typhoon Cloud Image Restoration by Combining Genetic Algorithm with Contourlet Transform

    SciTech Connect

    Zhang Changjiang; Wang Xiaodong

    2008-11-06

    An efficient typhoon cloud image restoration algorithm is proposed. Having implemented contourlet transform to a typhoon cloud image, noise is reduced in the high sub-bands. Weight median value filter is used to reduce the noise in the contourlet domain. Inverse contourlet transform is done to obtain the de-noising image. In order to enhance the global contrast of the typhoon cloud image, in-complete Beta transform (IBT) is used to determine non-linear gray transform curve so as to enhance global contrast for the de-noising typhoon cloud image. Genetic algorithm is used to obtain the optimal gray transform curve. Information entropy is used as the fitness function of the genetic algorithm. Experimental results show that the new algorithm is able to well enhance the global for the typhoon cloud image while well reducing the noises in the typhoon cloud image.

  3. Spectrographic phase-retrieval algorithm for femtosecond and attosecond pulses with frequency gaps

    NASA Astrophysics Data System (ADS)

    Seifert, B.; Wallentowitz, S.; Volkmann, U.; Hause, A.; Sperlich, K.; Stolz, H.

    2014-10-01

    We present a phase-reconstruction algorithm for a self-referenced spectrographic pulse characterization technique called “very advanced method for phase and intensity retrieval of e-fields” (VAMPIRE). This technique permits a spectral phase reconstruction of pulses with separated frequency components. The algorithm uses the particular characteristics of VAMPIRE spectrograms. It is a locally structured algorithm which is fast, robust, and it allows us to master stagnation problems. The algorithm is tested by use of both simulated and measured data.

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

    NASA Astrophysics Data System (ADS)

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

    2003-12-01

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

  5. Image encryption using fingerprint as key based on phase retrieval algorithm and public key cryptography

    NASA Astrophysics Data System (ADS)

    Zhao, Tieyu; Ran, Qiwen; Yuan, Lin; Chi, Yingying; Ma, Jing

    2015-09-01

    In this paper, a novel image encryption system with fingerprint used as a secret key is proposed based on the phase retrieval algorithm and RSA public key algorithm. In the system, the encryption keys include the fingerprint and the public key of RSA algorithm, while the decryption keys are the fingerprint and the private key of RSA algorithm. If the users share the fingerprint, then the system will meet the basic agreement of asymmetric cryptography. The system is also applicable for the information authentication. The fingerprint as secret key is used in both the encryption and decryption processes so that the receiver can identify the authenticity of the ciphertext by using the fingerprint in decryption process. Finally, the simulation results show the validity of the encryption scheme and the high robustness against attacks based on the phase retrieval technique.

  6. Cirrus cloud top temperatures retrieved from radiances in the National Polar-Orbiting Operational Environmental Satellite System--Visible Infrared Imager Radiometer Suite 8.55 and 12.0 microm bandpasses.

    PubMed

    Wong, Eric; Hutchison, Keith D; Ou, S C; Liou, K N

    2007-03-10

    We describe what is believed to be a new approach developed for the National Polar-Orbiting Operational Environmental Satellite System (NPOESS) to retrieve pixel-level, cirrus cloud top temperatures (CTTs) from radiances observed in the 8.55 and 12.0 microm bandpasses. The methodology solves numerically a set of nonlinear algebraic equations derived from the theory of radiative transfer based upon the correlation between emissivities in these two bandpasses. This new approach has been demonstrated using NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) as a proxy to Visible Infrared Imager Radiometer Suite (VIIRS) data. Many scenes have been analyzed covering a wide range of geophysical conditions, including single-layered and multilayered cirrus cloud situations along with diverse backgrounds and seasons. For single-layer clouds, the new approach compares very favorably with the MODIS 5 km resolution cloud products; the mean CTT for both methods are very close, while the standard deviation for the new approach is smaller. However, in multilayered cloud situations, the mean CTTs for the new approach appear to be colder than the CTTs from MODIS cloud products, which are acknowledged to be too warm. Finally, partly because the new approach is applied at the pixel level, CTTs do not increase toward cloud edges as is seen in the MODIS products. Based upon these initial results, the new approach to retrieve improved VIIRS cloud top properties has been incorporated into the ground-based data processing segment of the NPOESS system where prelaunch testing of all VIIRS algorithms continues.

  7. Statistical analysis of an LES shallow cumulus cloud ensemble using a cloud tracking algorithm

    NASA Astrophysics Data System (ADS)

    Dawe, J. T.; Austin, P. H.

    2012-01-01

    A technique for the tracking of individual clouds in a Large Eddy Simulation (LES) is presented. We use this technique on an LES of a shallow cumulus cloud field based upon the Barbados Oceanographic and Meteorological Experiment (BOMEX) to calculate statistics of cloud height, lifetime, and other physical properties for individual clouds in the model. We also examine the question of nature versus nurture in shallow cumulus clouds: do properties at cloud base determine the upper-level properties of the clouds (nature), or are cloud properties determined by the environmental conditions they encounter (nurture). We find that clouds which ascend through an environment that has been pre-moistened by previous cloud activity are no more likely to reach the inversion than clouds that ascend through a drier environment. Cloud base thermodynamic properties are uncorrelated with upper-level cloud properties, while mean fractional entrainment and detrainment rates display moderate correlations with cloud properties up to the inversion. Conversely, cloud base area correlates well with upper-level cloud area and maximum cloud height. We conclude that cloud thermodynamic properties are primarily influenced by entrainment and detrainment processes, cloud area and height are primarily influenced by cloud base area, and thus nature and nurture both play roles in the dynamics of BOMEX shallow cumulus clouds.

  8. Statistical analysis of a LES shallow cumulus cloud ensemble using a cloud tracking algorithm

    NASA Astrophysics Data System (ADS)

    Dawe, J. T.; Austin, P. H.

    2011-08-01

    A technique for the tracking of individual clouds in a Large Eddy Simulation (LES) is presented. We use this technique on a LES of a shallow cumulus cloud field based upon the Barbados Oceanographic and Meteorological Experiment (BOMEX) to calculate statistics of cloud height, lifetime, and other physical properties for individual clouds in the model. We also examine the question of nature versus nurture in shallow cumulus clouds: do properties at cloud base determine the upper-level properties of the clouds (nature), or are cloud properties determined by the environmental conditions they encounter (nurture). We find that clouds which ascend through an environment that has been pre-moistened by previous cloud activity are no more likely to reach the inversion than clouds that ascend through a drier environment. Cloud base thermodynamic properties are uncorrelated with upper-level cloud properties, while mean fractional entrainment and detrainment rate displays moderate correlations with cloud properties up to the inversion. Conversely, cloud base area correlates well with upper-level cloud area and maximum cloud height. We conclude that cloud thermodynamic properties are primarily influenced by entrainment and detrainment processes, cloud area and height are primarily influenced by cloud base area, and thus nature and nurture both play roles in the dynamics of BOMEX shallow cumulus clouds.

  9. Millimeter-wave imaging radiometer data processing and development of water vapor retrieval algorithms

    NASA Technical Reports Server (NTRS)

    Chang, L. Aron

    1995-01-01

    This document describes the current status of Millimeter-wave Imaging Radiometer (MIR) data processing and the technical development of the first version of a water vapor retrieval algorithm. The algorithm is being used by NASA/GSFC Microwave Sensors Branch, Laboratory for Hydrospheric Processes. It is capable of a three dimensional mapping of moisture fields using microwave data from airborne sensor of MIR and spaceborne instrument of Special Sensor Microwave/T-2 (SSM/T-2).

  10. North Alabama Lightning Mapping Array (LMA): VHF Source Retrieval Algorithm and Error Analyses

    NASA Technical Reports Server (NTRS)

    Koshak, W. J.; Solakiewicz, R. J.; Blakeslee, R. J.; Goodman, S. J.; Christian, H. J.; Hall, J.; Bailey, J.; Krider, E. P.; Bateman, M. G.; Boccippio, D.

    2003-01-01

    Two approaches are used to characterize how accurately the North Alabama Lightning Mapping Array (LMA) is able to locate lightning VHF sources in space and in time. The first method uses a Monte Carlo computer simulation to estimate source retrieval errors. The simulation applies a VHF source retrieval algorithm that was recently developed at the NASA Marshall Space Flight Center (MSFC) and that is similar, but not identical to, the standard New Mexico Tech retrieval algorithm. The second method uses a purely theoretical technique (i.e., chi-squared Curvature Matrix Theory) to estimate retrieval errors. Both methods assume that the LMA system has an overall rms timing error of 50 ns, but all other possible errors (e.g., multiple sources per retrieval attempt) are neglected. The detailed spatial distributions of retrieval errors are provided. Given that the two methods are completely independent of one another, it is shown that they provide remarkably similar results. However, for many source locations, the Curvature Matrix Theory produces larger altitude error estimates than the (more realistic) Monte Carlo simulation.

  11. A Variational Method to Retrieve the Extinction Profile in Liquid Clouds Using Multiple Field-of-View Lidar

    NASA Technical Reports Server (NTRS)

    Pounder, Nicola L.; Hogan, Robin J.; Varnai, Tamas; Battaglia, Alessandro; Cahalan, Robert F.

    2011-01-01

    While liquid clouds playa very important role in the global radiation budget, it's been very difficult to remotely determine their internal cloud structure. Ordinary lidar instruments (similar to radars but using visible light pulses) receive strong signals from such clouds, but the information is limited to a thin layer near the cloud boundary. Multiple field-of-view (FOV) lidars offer some new hope as they are able to isolate photons that were scattered many times by cloud droplets and penetrated deep into a cloud before returning to the instrument. Their data contains new information on cloud structure, although the lack of fast simulation methods made it challenging to interpret the observations. This paper describes a fast new technique that can simulate multiple-FOV lidar signals and can even estimate the way the signals would change in response to changes in cloud properties-an ability that allows quick refinements in our initial guesses of cloud structure. Results for a hypothetical airborne three-FOV lidar suggest that this approach can help determine cloud structure for a deeper layer in clouds, and can reliably determine the optical thickness of even fairly thick liquid clouds. The algorithm is also applied to stratocumulus observations by the 8-FOV airborne "THOR" lidar. These tests demonstrate that the new method can determine the depth to which a lidar provides useful information on vertical cloud structure. This work opens the way to exploit data from spaceborne lidar and radar more rigorously than has been possible up to now.

  12. Determining Best Estimates and Uncertainties in Cloud Microphysical Parameters from ARM Field Data: Implications for Models, Retrieval Schemes and Aerosol-Cloud-Radiation Interactions

    SciTech Connect

    McFarquhar, Greg

    2015-12-28

    We proposed to analyze in-situ cloud data collected during ARM/ASR field campaigns to create databases of cloud microphysical properties and their uncertainties as needed for the development of improved cloud parameterizations for models and remote sensing retrievals, and for evaluation of model simulations and retrievals. In particular, we proposed to analyze data collected over the Southern Great Plains (SGP) during the Mid-latitude Continental Convective Clouds Experiment (MC3E), the Storm Peak Laboratory Cloud Property Validation Experiment (STORMVEX), the Small Particles in Cirrus (SPARTICUS) Experiment and the Routine AAF Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) field campaign, over the North Slope of Alaska during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) and the Mixed-Phase Arctic Cloud Experiment (M-PACE), and over the Tropical Western Pacific (TWP) during The Tropical Warm Pool International Cloud Experiment (TWP-ICE), to meet the following 3 objectives; derive statistical databases of single ice particle properties (aspect ratio AR, dominant habit, mass, projected area) and distributions of ice crystals (size distributions SDs, mass-dimension m-D, area-dimension A-D relations, mass-weighted fall speeds, single-scattering properties, total concentrations N, ice mass contents IWC), complete with uncertainty estimates; assess processes by which aerosols modulate cloud properties in arctic stratus and mid-latitude cumuli, and quantify aerosol’s influence in context of varying meteorological and surface conditions; and determine how ice cloud microphysical, single-scattering and fall-out properties and contributions of small ice crystals to such properties vary according to location, environment, surface, meteorological and aerosol conditions, and develop parameterizations of such effects.In this report we describe the accomplishments that we made on all 3 research objectives.

  13. The OMPS Limb Profiler instrument: Data analysis and retrieval algorithm

    NASA Astrophysics Data System (ADS)

    Rault, Didier; Loughman, Robert; Bourassa, Adam; Taha, Ghassan; Jaross, Glen; Flittner, Dave

    The Ozone Mapper and Profiler Suite (OMPS) is scheduled to be launched on the NPOESS Preparatory Project (NPP) platform in early 2010. The OMPS will continue monitoring ozone from space, using 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 collection of this ozone data is aimed at fulfilling the U.S. treaty obligation to monitor the ozone depletion for the Montreal Protocol to ensure no gaps on ozone coverage. The paper will describe the data analysis method being presently developed to retrieve ozone vertical distribution from the radiance data measured by the Limb Profiler (LP). The OMPS-LP instrument was designed based upon the SOLSE/LORE heritage and is specially conceived to minimize stray light. The sensor simultaneously images the whole vertical extent of the Earth's limb through three vertical slits, each horizontally spaced at 250 km cross-track interval and covering a vertical tangent height range of 100 km. The calibration stability, which is essential to enable long-term ozone monitoring, is maintained by periodic observations of the sun, using a transmissive diffuser to redirect the solar irradiance into the telescope. To satisfy the anticipated science needs, the accuracy/precision requirements imposed upon the OMPS-LP instrument are tight, ranging from 10

  14. Statistical evaluation of the feasibility of satellite-retrieved cloud parameters as indicators of PM2.5 levels.

    PubMed

    Yu, Chao; Di Girolamo, Larry; Chen, Liangfu; Zhang, Xueying; Liu, Yang

    2015-01-01

    The spatial and temporal characteristics of fine particulate matter (PM2.5, particulate matter <2.5 μm in aerodynamic diameter) are increasingly being studied from satellite aerosol remote sensing data. However, cloud cover severely limits the coverage of satellite-driven PM2.5 models, and little research has been conducted on the association between cloud properties and PM2.5 levels. In this study, we analyzed the relationships between ground PM2.5 concentrations and two satellite-retrieved cloud parameters using data from the Southeastern Aerosol Research and Characterization (SEARCH) Network during 2000-2010. We found that both satellite-retrieved cloud fraction (CF) and cloud optical thickness (COT) are negatively associated with PM2.5 levels. PM2.5 speciation and meteorological analysis suggested that the main reason for these negative relationships might be the decreased secondary particle generation. Stratified analyses by season, land use type, and site location showed that seasonal impacts on this relationship are significant. These associations do not vary substantially between urban and rural sites or inland and coastal sites. The statistically significant negative associations of PM2.5 mass concentrations with CF and COT suggest that satellite-retrieved cloud parameters have the potential to serve as predictors to fill the data gap left by satellite aerosol optical depth in satellite-driven PM2.5 models.

  15. Statistical evaluation of the feasibility of satellite-retrieved cloud parameters as indicators of PM2.5 levels.

    PubMed

    Yu, Chao; Di Girolamo, Larry; Chen, Liangfu; Zhang, Xueying; Liu, Yang

    2015-01-01

    The spatial and temporal characteristics of fine particulate matter (PM2.5, particulate matter <2.5 μm in aerodynamic diameter) are increasingly being studied from satellite aerosol remote sensing data. However, cloud cover severely limits the coverage of satellite-driven PM2.5 models, and little research has been conducted on the association between cloud properties and PM2.5 levels. In this study, we analyzed the relationships between ground PM2.5 concentrations and two satellite-retrieved cloud parameters using data from the Southeastern Aerosol Research and Characterization (SEARCH) Network during 2000-2010. We found that both satellite-retrieved cloud fraction (CF) and cloud optical thickness (COT) are negatively associated with PM2.5 levels. PM2.5 speciation and meteorological analysis suggested that the main reason for these negative relationships might be the decreased secondary particle generation. Stratified analyses by season, land use type, and site location showed that seasonal impacts on this relationship are significant. These associations do not vary substantially between urban and rural sites or inland and coastal sites. The statistically significant negative associations of PM2.5 mass concentrations with CF and COT suggest that satellite-retrieved cloud parameters have the potential to serve as predictors to fill the data gap left by satellite aerosol optical depth in satellite-driven PM2.5 models. PMID:25052693

  16. Verification of new cloud discrimination algorithm using GOSAT TANSO-CAI in the Amazon

    NASA Astrophysics Data System (ADS)

    Oishi, Y.; Ishida, H.; Nakajima, T. Y.

    2015-12-01

    Greenhouse gases Observing SATellite (GOSAT) was launched in 2009 to measure the global atmospheric CO2 and CH4 concentrations. GOSAT is equipped with two sensors: the Thermal And Near-infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS) and the Cloud and Aerosol Imager (TANSO-CAI). The presence of clouds in the instantaneous field-of-view (IFOV) of the FTS leads to incorrect estimates of the concentrations. Thus, the FTS data which are suspected to be cloud-contaminated must be identified using a CAI cloud discrimination algorithm and rejected. Conversely, overestimation of clouds leads to reduce the amount of the FTS data which can be used to estimate the greenhouse gases concentrations. It becomes a serious problem in the region of tropical rainforest such as the Amazon, where there are very few remaining FTS data by cloud cover. The preparation for the launch of the GOSAT-2 in fiscal 2017 has been progressing. To improve the accuracy of estimates of the greenhouse gases concentrations, we need to refine the existing CAI cloud discrimination algorithm. For the reason, a new cloud discrimination algorithm using support vector machines (SVM) was developed. Visual inspections can use the locally optimized thresholds, though the existing CAI cloud discrimination algorithm uses the common thresholds all over the world. Thus, it is certain that the accuracy of visual inspections is better than these algorithms in the limited region without areas such as ice and snow, where it is difficult to discriminate between clouds and ground surfaces. In this study we evaluated the accuracy of the new cloud discrimination algorithm by comparing with the existing CAI cloud discrimination algorithm and visual inspections of the same CAI images in the Amazon. We will present our latest results.

  17. Tomographic retrieval of water vapour and temperature around polar mesospheric clouds using Odin-SMR

    NASA Astrophysics Data System (ADS)

    Christensen, O. M.; Eriksson, P.; Urban, J.; Murtagh, D.; Hultgren, K.; Gumbel, J.

    2014-11-01

    A special observation mode of the Odin satellite provides the first simultaneous measurements of water vapour, temperature and polar mesospheric cloud (PMC) brightness over a large geographical area while still resolving both horizontal and vertical structures in the clouds and background atmosphere. The observation mode has been activated during June, July and August of 2010, 2011 and 2014, and for latitudes between 50 and 82° N. This paper focuses on the water vapour and temperature measurements carried out with Odin's sub-millimetre radiometer (SMR). The tomographic retrieval approach used provides water vapour and temperature between 75-90 km with a vertical resolution of about 2.5 km and a horizontal resolution of about 200 km. The precision of the measurements is estimated to 0.5 ppm for water vapour and 3 K for temperature. Due to limited information about the pressure at the measured altitudes, the results have large uncertainties (> 3 ppm) in the retrieved water vapour. These errors, however, influence mainly the mean atmosphere retrieved for each orbit, and variations around this mean are still reliably captured by the measurements. SMR measurements are performed using two different mixer chains, denoted as frequency mode 19 and 13. Systematic differences between the two frontends have been noted. A first comparison with the Solar Occultation For Ice Experiment instrument (SOFIE) on-board the Aeronomy of Ice in the Mesosphere (AIM) satellite and the Fourier Transform Spectrometer of the Atmospheric Chemistry Experiment (ACE-FTS) on-board SCISAT indicates that the measurements using the frequency mode 19 have a significant low bias in both temperature (> 20 K) and water vapour (> 1 ppm), while the measurements using frequency mode 13 agree with the other instruments considering estimated errors. PMC brightness data are provided by the OSIRIS, Odin's other sensor. Combined SMR and OSIRIS data for some example orbits are considered. For these orbits

  18. Tomographic retrieval of water vapour and temperature around polar mesospheric clouds using Odin-SMR

    NASA Astrophysics Data System (ADS)

    Christensen, O. M.; Eriksson, P.; Urban, J.; Murtagh, D.; Hultgren, K.; Gumbel, J.

    2015-05-01

    A special observation mode of the Odin satellite provides the first simultaneous measurements of water vapour, temperature and polar mesospheric cloud (PMC) brightness over a large geographical area while still resolving both horizontal and vertical structures in the clouds and background atmosphere. The observation mode was activated during June, July and August of 2010 and 2011, and for latitudes between 50 and 82° N. This paper focuses on the water vapour and temperature measurements carried out with Odin's sub-millimetre radiometer (SMR). The tomographic retrieval approach used provides water vapour and temperature between 75 and 90 km with a vertical resolution of about 2.5 km and a horizontal resolution of about 200 km. The precision of the measurements is estimated to 0.2 ppmv for water vapour and 2 K for temperature. Due to limited information about the pressure at the measured altitudes, the results have large uncertainties (> 3 ppmv) in the retrieved water vapour. These errors, however, influence mainly the mean atmosphere retrieved for each orbit, and variations around this mean are still reliably captured by the measurements. SMR measurements are performed using two different mixer chains, denoted as frequency mode 19 and 13. Systematic differences between the two frontends have been noted. A first comparison with the Solar Occultation For Ice Experiment instrument (SOFIE) on-board the Aeronomy of Ice in the Mesosphere (AIM) satellite and the Fourier Transform Spectrometer of the Atmospheric Chemistry Experiment (ACE-FTS) on-board SCISAT indicates that the measurements using the frequency mode 19 have a significant low bias in both temperature (> 15 K) and water vapour (> 0.5 ppmv), while the measurements using frequency mode 13 agree with the other instruments considering estimated errors. PMC brightness data is provided by OSIRIS, Odin's other sensor. Combined SMR and OSIRIS data for some example orbits is considered. For these orbits, effects of

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

    ERIC Educational Resources Information Center

    Stejic, Zoran; Takama, Yasufumi; Hirota, Kaoru

    2003-01-01

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

  20. An optimal-estimation-based aerosol retrieval algorithm using OMI near-UV observations

    NASA Astrophysics Data System (ADS)

    Jeong, U.; Kim, J.; Ahn, C.; Torres, O.; Liu, X.; Bhartia, P. K.; Spurr, R. J. D.; Haffner, D.; Chance, K.; Holben, B. N.

    2016-01-01

    An optimal-estimation(OE)-based aerosol retrieval algorithm using the OMI (Ozone Monitoring Instrument) near-ultraviolet observation was developed in this study. The OE-based algorithm has the merit of providing useful estimates of errors simultaneously with the inversion products. Furthermore, instead of using the traditional look-up tables for inversion, it performs online radiative transfer calculations with the VLIDORT (linearized pseudo-spherical vector discrete ordinate radiative transfer code) to eliminate interpolation errors and improve stability. The measurements and inversion products of the Distributed Regional Aerosol Gridded Observation Network campaign in northeast Asia (DRAGON NE-Asia 2012) were used to validate the retrieved aerosol optical thickness (AOT) and single scattering albedo (SSA). The retrieved AOT and SSA at 388 nm have a correlation with the Aerosol Robotic Network (AERONET) products that is comparable to or better than the correlation with the operational product during the campaign. The OE-based estimated error represented the variance of actual biases of AOT at 388 nm between the retrieval and AERONET measurements better than the operational error estimates. The forward model parameter errors were analyzed separately for both AOT and SSA retrievals. The surface reflectance at 388 nm, the imaginary part of the refractive index at 354 nm, and the number fine-mode fraction (FMF) were found to be the most important parameters affecting the retrieval accuracy of AOT, while FMF was the most important parameter for the SSA retrieval. The additional information provided with the retrievals, including the estimated error and degrees of freedom, is expected to be valuable for relevant studies. Detailed advantages of using the OE method were described and discussed in this paper.

  1. An Optimal-Estimation-Based Aerosol Retrieval Algorithm Using OMI Near-UV Observations

    NASA Technical Reports Server (NTRS)

    Jeong, U; Kim, J.; Ahn, C.; Torres, O.; Liu, X.; Bhartia, P. K.; Spurr, R. J. D.; Haffner, D.; Chance, K.; Holben, B. N.

    2016-01-01

    An optimal-estimation(OE)-based aerosol retrieval algorithm using the OMI (Ozone Monitoring Instrument) near-ultraviolet observation was developed in this study. The OE-based algorithm has the merit of providing useful estimates of errors simultaneously with the inversion products. Furthermore, instead of using the traditional lookup tables for inversion, it performs online radiative transfer calculations with the VLIDORT (linearized pseudo-spherical vector discrete ordinate radiative transfer code) to eliminate interpolation errors and improve stability. The measurements and inversion products of the Distributed Regional Aerosol Gridded Observation Network campaign in northeast Asia (DRAGON NE-Asia 2012) were used to validate the retrieved aerosol optical thickness (AOT) and single scattering albedo (SSA). The retrieved AOT and SSA at 388 nm have a correlation with the Aerosol Robotic Network (AERONET) products that is comparable to or better than the correlation with the operational product during the campaign. The OEbased estimated error represented the variance of actual biases of AOT at 388 nm between the retrieval and AERONET measurements better than the operational error estimates. The forward model parameter errors were analyzed separately for both AOT and SSA retrievals. The surface reflectance at 388 nm, the imaginary part of the refractive index at 354 nm, and the number fine-mode fraction (FMF) were found to be the most important parameters affecting the retrieval accuracy of AOT, while FMF was the most important parameter for the SSA retrieval. The additional information provided with the retrievals, including the estimated error and degrees of freedom, is expected to be valuable for relevant studies. Detailed advantages of using the OE method were described and discussed in this paper.

  2. Advances in Satellite Microwave Precipitation Retrieval Algorithms Over Land

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  3. Adaptive algorithm for cloud cover estimation from all-sky images over the sea

    NASA Astrophysics Data System (ADS)

    Krinitskiy, M. A.; Sinitsyn, A. V.

    2016-05-01

    A new algorithm for cloud cover estimation has been formulated and developed based on the synthetic control index, called the grayness rate index, and an additional algorithm step of adaptive filtering of the Mie scattering contribution. A setup for automated cloud cover estimation has been designed, assembled, and tested under field conditions. The results shows a significant advantage of the new algorithm over currently commonly used procedures.

  4. Comparing Water Vapor Mixing Ratio Profiles and Cloud Vertical Structure from Multiwavelength Raman Lidar Retrievals and Radiosounding Measurements

    NASA Astrophysics Data System (ADS)

    Costa-Surós, Montserrat; Stachlewska, Iwona S.; Markowicz, Krzysztof

    2016-06-01

    A study of comparison of water vapor mixing ratio profiles, relative humidity profiles, and cloud vertical structures using two different instruments, a multiwavelength Aerosol-Depolarization-Raman lidar and radiosoundings, is presented. The observations were taken by the lidar located in Warsaw center and the radiosoundings located about 30km to the North in Legionowo (Poland). We compared the ground-based remote sensing technology with in-situ method in order to improve knowledge about water content thought the atmosphere and cloud formation. The method used for retrieving the cloud vertical structure can be improved comparing the radiosonde results with the lidar observations, which show promising results.

  5. Effective leaf area index retrieving from terrestrial point cloud data: coupling computational geometry application and Gaussian mixture model clustering

    NASA Astrophysics Data System (ADS)

    Jin, S.; Tamura, M.; Susaki, J.

    2014-09-01

    Leaf area index (LAI) is one of the most important structural parameters of forestry studies which manifests the ability of the green vegetation interacted with the solar illumination. Classic understanding about LAI is to consider the green canopy as integration of horizontal leaf layers. Since multi-angle remote sensing technique developed, LAI obliged to be deliberated according to the observation geometry. Effective LAI could formulate the leaf-light interaction virtually and precisely. To retrieve the LAI/effective LAI from remotely sensed data therefore becomes a challenge during the past decades. Laser scanning technique can provide accurate surface echoed coordinates with densely scanned intervals. To utilize the density based statistical algorithm for analyzing the voluminous amount of the 3-D points data is one of the subjects of the laser scanning applications. Computational geometry also provides some mature applications for point cloud data (PCD) processing and analysing. In this paper, authors investigated the feasibility of a new application for retrieving the effective LAI of an isolated broad leaf tree. Simplified curvature was calculated for each point in order to remove those non-photosynthetic tissues. Then PCD were discretized into voxel, and clustered by using Gaussian mixture model. Subsequently the area of each cluster was calculated by employing the computational geometry applications. In order to validate our application, we chose an indoor plant to estimate the leaf area, the correlation coefficient between calculation and measurement was 98.28 %. We finally calculated the effective LAI of the tree with 6 × 6 assumed observation directions.

  6. Implementation on Landsat Data of a Simple Cloud Mask Algorithm Developed for MODIS Land Bands

    NASA Technical Reports Server (NTRS)

    Oreopoulos, Lazaros; Wilson, Michael J.; Varnai, Tamas

    2010-01-01

    This letter assesses the performance on Landsat-7 images of a modified version of a cloud masking algorithm originally developed for clear-sky compositing of Moderate Resolution Imaging Spectroradiometer (MODIS) images at northern mid-latitudes. While data from recent Landsat missions include measurements at thermal wavelengths, and such measurements are also planned for the next mission, thermal tests are not included in the suggested algorithm in its present form to maintain greater versatility and ease of use. To evaluate the masking algorithm we take advantage of the availability of manual (visual) cloud masks developed at USGS for the collection of Landsat scenes used here. As part of our evaluation we also include the Automated Cloud Cover Assesment (ACCA) algorithm that includes thermal tests and is used operationally by the Landsat-7 mission to provide scene cloud fractions, but no cloud masks. We show that the suggested algorithm can perform about as well as ACCA both in terms of scene cloud fraction and pixel-level cloud identification. Specifically, we find that the algorithm gives an error of 1.3% for the scene cloud fraction of 156 scenes, and a root mean square error of 7.2%, while it agrees with the manual mask for 93% of the pixels, figures very similar to those from ACCA (1.2%, 7.1%, 93.7%).

  7. Retrievals of Aerosol and Cloud Particle Microphysics Using Polarization and Depolarization Techniques

    NASA Technical Reports Server (NTRS)

    Mishchenko, Michael; Hansen, James E. (Technical Monitor)

    2001-01-01

    The recent availability of theoretical techniques for computing single and multiple scattering of light by realistic polydispersions of spherical and nonspherical particles and the strong dependence of the Stokes scattering matrix on particle size, shape, and refractive index make polarization and depolarization measurements a powerful particle characterization tool. In this presentation I will describe recent applications of photopolarimetric and lidar depolarization measurements to remote sensing characterization of tropospheric aerosols, polar stratospheric clouds (PSCs), and contrails. The talk will include (1) a short theoretical overview of the effects of particle microphysics on particle single-scattering characteristics; (2) the use of multi-angle multi-spectral photopolarimetry to retrieve the optical thickness, size distribution, refractive index, and number concentration of tropospheric aerosols over the ocean surface; and (3) the application of the T-matrix method to constraining the PSC and contrail particle microphysics using multi-spectral measurements of lidar backscatter and depolarization.

  8. Cloud top height retrieval using the imaging polarimeter (3MI) top-of-atmosphere reflectance measurements in the oxygen absorption band

    NASA Astrophysics Data System (ADS)

    Kokhanovsky, Alexander; Munro, Rose

    2016-04-01

    clouds will screen the oxygen below them and have larger value of ratios x=R(763nm)/r(763nm) as compared to the lower clouds. Here r(763nm) is the value of reflectance at 763nm for the artificial atmosphere free of oxygen. This value can be derived by the linear extrapolation of reflectances at 670 and 865nm as measured by 3MI over ocean. Over land this technique requires a modification.We assume that the top of atmosphere reflectance in the oxygen A-band can be presented in the following way: R(763nm)=r(763nm)T, where the transmittance term can be derived using the radiative transfer theory. The algorithm is validated using synthetic 3MI measurements. It has been found that the retrieval technique can be used for clouds with cloud top heights in the range 0.5-10km and cloud optical thicknesses above 5.0. For lower cloud optical thicknesses, the cloud is inhomogeneous on a scale of the 3MI pixel (4x4km) and the assumption used in the calculation of the transmittance term T (a horizontally homogeneous cloud layer) is no longer valid. The technique can also be applied to heavy aerosol events such as dust outbreaks, smoke, and volcanic eruptions.

  9. Impact of Cloud Vertical and Horizontal Inhomogeneity on Multi-Spectral Retrieval of Liquid Water Cloud Properties: A Study for the GCOM-C/SGLI Cloud Product by Using A-Train and Landsat-8 Measurements